diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000000000000000000000000000000000000..c64e3e5cba3439e5cd0c98fcf7f09dc97a3289a1 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,10 @@ +venv +.conda +.git +examples +clients +.hypothesis +__pycache__ +.vscode +*.egg-info +.pytest_cache diff --git a/.gitattributes b/.gitattributes index a6344aac8c09253b3b630fb776ae94478aa0275b..ff6c194874c26ef207d5c3da6b330694e9eed60d 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,35 +1 @@ -*.7z filter=lfs diff=lfs merge=lfs -text -*.arrow filter=lfs diff=lfs merge=lfs -text -*.bin filter=lfs diff=lfs merge=lfs -text -*.bz2 filter=lfs diff=lfs merge=lfs -text -*.ckpt filter=lfs diff=lfs merge=lfs -text -*.ftz filter=lfs diff=lfs merge=lfs -text -*.gz filter=lfs diff=lfs merge=lfs -text -*.h5 filter=lfs diff=lfs merge=lfs -text -*.joblib filter=lfs diff=lfs merge=lfs -text -*.lfs.* filter=lfs diff=lfs merge=lfs -text -*.mlmodel filter=lfs diff=lfs merge=lfs -text -*.model filter=lfs diff=lfs merge=lfs -text -*.msgpack filter=lfs diff=lfs merge=lfs -text -*.npy filter=lfs diff=lfs merge=lfs -text -*.npz filter=lfs diff=lfs merge=lfs -text -*.onnx filter=lfs diff=lfs merge=lfs -text -*.ot filter=lfs diff=lfs merge=lfs -text -*.parquet filter=lfs diff=lfs merge=lfs -text -*.pb filter=lfs diff=lfs merge=lfs -text -*.pickle filter=lfs diff=lfs merge=lfs -text -*.pkl filter=lfs diff=lfs merge=lfs -text -*.pt filter=lfs diff=lfs merge=lfs -text -*.pth filter=lfs diff=lfs merge=lfs -text -*.rar filter=lfs diff=lfs merge=lfs -text -*.safetensors filter=lfs diff=lfs merge=lfs -text -saved_model/**/* filter=lfs diff=lfs merge=lfs -text -*.tar.* filter=lfs diff=lfs merge=lfs -text -*.tar filter=lfs diff=lfs merge=lfs -text -*.tflite filter=lfs diff=lfs merge=lfs -text -*.tgz filter=lfs diff=lfs merge=lfs -text -*.wasm filter=lfs diff=lfs merge=lfs -text -*.xz filter=lfs diff=lfs merge=lfs -text -*.zip filter=lfs diff=lfs merge=lfs -text -*.zst filter=lfs diff=lfs merge=lfs -text -*tfevents* filter=lfs diff=lfs merge=lfs -text +*_pb2.py* linguist-generated diff --git a/.github/ISSUE_TEMPLATE/bug_report.yaml b/.github/ISSUE_TEMPLATE/bug_report.yaml new file mode 100644 index 0000000000000000000000000000000000000000..fba6c0e7bb8de1307e340fcffd70603c8afc98ff --- /dev/null +++ b/.github/ISSUE_TEMPLATE/bug_report.yaml @@ -0,0 +1,43 @@ +name: 🐛 Bug Report +description: File a bug report to help us improve Chroma +title: "[Bug]: " +labels: ["bug", "triage"] +# assignees: +# - octocat +body: + - type: markdown + attributes: + value: | + Thanks for taking the time to fill out this bug report! + - type: textarea + id: what-happened + attributes: + label: What happened? + description: Also tell us, what did you expect to happen? + placeholder: Tell us what you see! +# value: "A bug happened!" + validations: + required: true + - type: textarea + id: versions + attributes: + label: Versions + description: Your Chroma, Python, and OS versions, as well as whatever else you think relevant. Check that you have [the latest Chroma](https://github.com/chroma-core/chroma/pkgs/container/chroma) as we are a fast moving pre v1.0 project. + placeholder: Chroma v0.3.22, Python 3.9.6, MacOS 12.5 +# value: "A bug happened!" + validations: + required: true + - type: textarea + id: logs + attributes: + label: Relevant log output + description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks. + render: shell +# - type: checkboxes +# id: terms +# attributes: +# label: Code of Conduct +# description: By submitting this issue, you agree to follow our [Code of Conduct](https://example.com) +# options: +# - label: I agree to follow this project's Code of Conduct +# required: true diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml new file mode 100644 index 0000000000000000000000000000000000000000..587ecd17e00fc9f40e1b9d1a9e270e1e46e57db5 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -0,0 +1,5 @@ +blank_issues_enabled: true +contact_links: + - name: 🤷🏻‍♀️ Questions + url: https://discord.com/invite/MMeYNTmh3x + about: Interact with the Chroma community here by asking for help, discussing and more! diff --git a/.github/ISSUE_TEMPLATE/feature_request.yaml b/.github/ISSUE_TEMPLATE/feature_request.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ee8322f79374a93aa7e8f09f7717605f83f082bf --- /dev/null +++ b/.github/ISSUE_TEMPLATE/feature_request.yaml @@ -0,0 +1,46 @@ +name: 🚀 Feature request +description: Suggest an idea for Chroma +title: "[Feature Request]: " +labels: ["enhancement"] +body: + - type: markdown + attributes: + value: | + Thanks for taking the time to request this feature! + - type: textarea + id: problem + attributes: + label: Describe the problem + description: Please provide a clear and concise description the problem this feature would solve. The more information you can provide here, the better. + placeholder: I prefer if... + validations: + required: true + - type: textarea + id: solution + attributes: + label: Describe the proposed solution + description: Please provide a clear and concise description of what you would like to happen. + placeholder: I would like to see... + validations: + required: true + - type: textarea + id: alternatives + attributes: + label: Alternatives considered + description: "Please provide a clear and concise description of any alternative solutions or features you've considered." + - type: dropdown + id: importance + attributes: + label: Importance + description: How important is this feature to you? + options: + - nice to have + - would make my life easier + - i cannot use Chroma without it + validations: + required: true + - type: textarea + id: additional-context + attributes: + label: Additional Information + description: Add any other context or screenshots about the feature request here. diff --git a/.github/ISSUE_TEMPLATE/installation_trouble.yaml b/.github/ISSUE_TEMPLATE/installation_trouble.yaml new file mode 100644 index 0000000000000000000000000000000000000000..df7ae14a78ed8a0a5950ad6e4b4fc847a5bf73aa --- /dev/null +++ b/.github/ISSUE_TEMPLATE/installation_trouble.yaml @@ -0,0 +1,41 @@ +name: Installation Issue +description: Request for install help with Chroma +title: "[Install issue]: " +labels: ["installation trouble"] +body: + - type: markdown + attributes: + value: | + Thanks for taking the time to fill out this issue report! + - type: textarea + id: what-happened + attributes: + label: What happened? + description: Also tell us, what did you expect to happen? + placeholder: Tell us what you see! +# value: "A bug happened!" + validations: + required: true + - type: textarea + id: versions + attributes: + label: Versions + description: We need your Chroma, Python, and OS versions, as well as whatever else you think relevant. + placeholder: Chroma v0.3.14, Python 3.9.6, MacOS 12.5 +# value: "A bug happened!" + validations: + required: true + - type: textarea + id: logs + attributes: + label: Relevant log output + description: Please copy and paste any relevant log output. This will be automatically formatted into code, so no need for backticks. + render: shell +# - type: checkboxes +# id: terms +# attributes: +# label: Code of Conduct +# description: By submitting this issue, you agree to follow our [Code of Conduct](https://example.com) +# options: +# - label: I agree to follow this project's Code of Conduct +# required: true diff --git a/.github/actions/bandit-scan/Dockerfile b/.github/actions/bandit-scan/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..943f04fc8f3703e7f764bb5d0f9a1e9102633e9c --- /dev/null +++ b/.github/actions/bandit-scan/Dockerfile @@ -0,0 +1,7 @@ +FROM python:3.10-alpine AS base-action + +RUN pip3 install -U setuptools pip bandit + +COPY entrypoint.sh /entrypoint.sh +RUN chmod +x /entrypoint.sh +ENTRYPOINT ["sh","/entrypoint.sh"] diff --git a/.github/actions/bandit-scan/action.yaml b/.github/actions/bandit-scan/action.yaml new file mode 100644 index 0000000000000000000000000000000000000000..e0735450f57490395f6d3b9457d7ce68022f4c6d --- /dev/null +++ b/.github/actions/bandit-scan/action.yaml @@ -0,0 +1,26 @@ +name: 'Bandit Scan' +description: 'This action performs a security vulnerability scan of python code using bandit library.' +inputs: + bandit-config: + description: 'Bandit configuration file' + required: false + input-dir: + description: 'Directory to scan' + required: false + default: '.' + format: + description: 'Output format (txt, csv, json, xml, yaml). Default: json' + required: false + default: 'json' + output-file: + description: "The report file to produce. Make sure to align your format with the file extension to avoid confusion." + required: false + default: "bandit-scan.json" +runs: + using: 'docker' + image: 'Dockerfile' + args: + - ${{ inputs.format }} + - ${{ inputs.bandit-config }} + - ${{ inputs.input-dir }} + - ${{ inputs.output-file }} diff --git a/.github/actions/bandit-scan/entrypoint.sh b/.github/actions/bandit-scan/entrypoint.sh new file mode 100755 index 0000000000000000000000000000000000000000..f52daddd781e84e8d96003f095f48a4b684a6f53 --- /dev/null +++ b/.github/actions/bandit-scan/entrypoint.sh @@ -0,0 +1,13 @@ +#!/bin/bash +CFG="-c $2" +if [ -z "$1" ]; then + echo "No path to scan provided" + exit 1 +fi + +if [ -z "$2" ]; then + CFG = "" +fi + +bandit -f "$1" ${CFG} -r "$3" -o "$4" +exit 0 #we want to ignore the exit code of bandit (for now) diff --git a/.github/workflows/chroma-client-integration-test.yml b/.github/workflows/chroma-client-integration-test.yml new file mode 100644 index 0000000000000000000000000000000000000000..5724959c2549a351d1334d9cfc38bea29162ef34 --- /dev/null +++ b/.github/workflows/chroma-client-integration-test.yml @@ -0,0 +1,31 @@ +name: Chroma Client Integration Tests + +on: + push: + branches: + - main + pull_request: + branches: + - main + - '**' + workflow_dispatch: + +jobs: + test: + timeout-minutes: 90 + strategy: + matrix: + python: ['3.8', '3.9', '3.10', '3.11'] + platform: [ubuntu-latest, windows-latest] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python }} + - name: Install test dependencies + run: python -m pip install -r requirements.txt && python -m pip install -r requirements_dev.txt + - name: Test + run: clients/python/integration-test.sh diff --git a/.github/workflows/chroma-cluster-test.yml b/.github/workflows/chroma-cluster-test.yml new file mode 100644 index 0000000000000000000000000000000000000000..e474f43ca7d3bced182bf472f0793d4979935626 --- /dev/null +++ b/.github/workflows/chroma-cluster-test.yml @@ -0,0 +1,42 @@ +name: Chroma Cluster Tests + +on: + push: + branches: + - main + pull_request: + branches: + - main + - '**' + workflow_dispatch: + +jobs: + test: + strategy: + matrix: + python: ['3.8'] + platform: ['16core-64gb-ubuntu-latest'] + testfile: ["chromadb/test/ingest/test_producer_consumer.py", + "chromadb/test/db/test_system.py", + "chromadb/test/segment/distributed/test_memberlist_provider.py",] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python }} + - name: Install test dependencies + run: python -m pip install -r requirements.txt && python -m pip install -r requirements_dev.txt + - name: Start minikube + id: minikube + uses: medyagh/setup-minikube@latest + with: + minikube-version: latest + kubernetes-version: latest + driver: docker + addons: ingress, ingress-dns + start-args: '--profile chroma-test' + - name: Integration Test + run: bin/cluster-test.sh ${{ matrix.testfile }} diff --git a/.github/workflows/chroma-coordinator-test.yaml b/.github/workflows/chroma-coordinator-test.yaml new file mode 100644 index 0000000000000000000000000000000000000000..629a9dfb146656566adeec9d56486b1fb084c382 --- /dev/null +++ b/.github/workflows/chroma-coordinator-test.yaml @@ -0,0 +1,23 @@ +name: Chroma Coordinator Tests + +on: + push: + branches: + - main + pull_request: + branches: + - main + - '**' + workflow_dispatch: + +jobs: + test: + strategy: + matrix: + platform: [ubuntu-latest] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Build and test + run: cd go/coordinator && make test diff --git a/.github/workflows/chroma-integration-test.yml b/.github/workflows/chroma-integration-test.yml new file mode 100644 index 0000000000000000000000000000000000000000..2f731028801ffa825bd65acdca12402b9947d71b --- /dev/null +++ b/.github/workflows/chroma-integration-test.yml @@ -0,0 +1,40 @@ +name: Chroma Integration Tests + +on: + push: + branches: + - main + - team/hypothesis-tests + pull_request: + branches: + - main + - '**' + workflow_dispatch: + +jobs: + test: + strategy: + matrix: + python: ['3.8'] + platform: [ubuntu-latest, windows-latest] + testfile: ["--ignore-glob 'chromadb/test/property/*' --ignore='chromadb/test/test_cli.py' --ignore='chromadb/test/auth/test_simple_rbac_authz.py'", + "chromadb/test/property/test_add.py", + "chromadb/test/test_cli.py", + "chromadb/test/auth/test_simple_rbac_authz.py", + "chromadb/test/property/test_collections.py", + "chromadb/test/property/test_cross_version_persist.py", + "chromadb/test/property/test_embeddings.py", + "chromadb/test/property/test_filtering.py", + "chromadb/test/property/test_persist.py"] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python }} + - name: Install test dependencies + run: python -m pip install -r requirements.txt && python -m pip install -r requirements_dev.txt + - name: Integration Test + run: bin/integration-test ${{ matrix.testfile }} diff --git a/.github/workflows/chroma-js-release.yml b/.github/workflows/chroma-js-release.yml new file mode 100644 index 0000000000000000000000000000000000000000..62af392c29b65ea7c8d763dbd2d2538a9abcd0a7 --- /dev/null +++ b/.github/workflows/chroma-js-release.yml @@ -0,0 +1,42 @@ +name: Chroma Release JS Client + +on: + push: + tags: + - 'js_release_*.*.*' # Match tags in the form js_release_X.Y.Z + - 'js_release_alpha_*.*.*' # Match tags in the form js_release_alpha_X.Y.Z + +jobs: + build-and-release: + runs-on: ubuntu-latest + permissions: write-all + steps: + - name: Check if tag matches the pattern + run: | + if [[ "${{ github.ref }}" =~ ^refs/tags/js_release_alpha_[0-9]+\.[0-9]+\.[0-9]+$ ]]; then + echo "Tag matches the pattern js_release_alpha_X.Y.Z" + echo "NPM_SCRIPT=release_alpha" >> "$GITHUB_ENV" + elif [[ "${{ github.ref }}" =~ ^refs/tags/js_release_[0-9]+\.[0-9]+\.[0-9]+$ ]]; then + echo "Tag matches the pattern js_release_X.Y.Z" + echo "NPM_SCRIPT=release" >> "$GITHUB_ENV" + else + echo "Tag does not match the release tag pattern, exiting workflow" + exit 1 + fi + - name: Checkout + uses: actions/checkout@v3 + with: + fetch-depth: 0 + - name: Set up JS + uses: actions/setup-node@v3 + with: + node-version: '16.x' + registry-url: 'https://registry.npmjs.org' + - name: Install Client Dev Dependencies + run: npm install + working-directory: ./clients/js/ + - name: npm Test & Publish + run: npm run db:run && PORT=8001 npm run $NPM_SCRIPT + working-directory: ./clients/js/ + env: + NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }} diff --git a/.github/workflows/chroma-release-python-client.yml b/.github/workflows/chroma-release-python-client.yml new file mode 100644 index 0000000000000000000000000000000000000000..2abc0d524aba6f15a1f4b63f6e55b4be1a9b6596 --- /dev/null +++ b/.github/workflows/chroma-release-python-client.yml @@ -0,0 +1,58 @@ +name: Chroma Release Python Client + +on: + push: + tags: + - '[0-9]+.[0-9]+.[0-9]+' # Match tags in the form X.Y.Z + branches: + - main + - hammad/thin_client + +jobs: + check_tag: + runs-on: ubuntu-latest + outputs: + tag_matches: ${{ steps.check-tag.outputs.tag_matches }} + steps: + - name: Check Tag + id: check-tag + run: | + if [[ ${{ github.event.ref }} =~ ^refs/tags/[0-9]+\.[0-9]+\.[0-9]+$ ]]; then + echo "tag_matches=true" >> $GITHUB_OUTPUT + fi + build-and-release: + runs-on: ubuntu-latest + needs: check_tag + if: needs.check_tag.outputs.tag_matches == 'true' + permissions: write-all + steps: + - name: Checkout + uses: actions/checkout@v3 + with: + fetch-depth: 0 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + - name: Install Client Dev Dependencies + run: python -m pip install -r ./clients/python/requirements.txt && python -m pip install -r ./clients/python/requirements_dev.txt + - name: Build Client + run: ./clients/python/build_python_thin_client.sh + - name: Install setuptools_scm + run: python -m pip install setuptools_scm + - name: Get Release Version + id: version + run: echo "version=$(python -m setuptools_scm)" >> $GITHUB_OUTPUT + - name: Get current date + id: builddate + run: echo "builddate=$(date +'%Y-%m-%dT%H:%M')" >> $GITHUB_OUTPUT + - name: Publish to Test PyPI + uses: pypa/gh-action-pypi-publish@release/v1 + with: + password: ${{ secrets.TEST_PYPI_PYTHON_CLIENT_PUBLISH_KEY }} + repository-url: https://test.pypi.org/legacy/ + - name: Publish to PyPI + if: startsWith(github.ref, 'refs/tags') + uses: pypa/gh-action-pypi-publish@release/v1 + with: + password: ${{ secrets.PYPI_PYTHON_CLIENT_PUBLISH_KEY }} diff --git a/.github/workflows/chroma-release.yml b/.github/workflows/chroma-release.yml new file mode 100644 index 0000000000000000000000000000000000000000..6c2250a0fb3f32475f002ccc19ac2f395cb5a17f --- /dev/null +++ b/.github/workflows/chroma-release.yml @@ -0,0 +1,179 @@ +name: Chroma Release + +on: + push: + tags: + - "*" + branches: + - main + +env: + GHCR_IMAGE_NAME: "ghcr.io/chroma-core/chroma" + DOCKERHUB_IMAGE_NAME: "chromadb/chroma" + PLATFORMS: linux/amd64,linux/arm64 #linux/riscv64, linux/arm/v7 + +jobs: + check_tag: + runs-on: ubuntu-latest + outputs: + tag_matches: ${{ steps.check-tag.outputs.tag_matches }} + steps: + - name: Check Tag + id: check-tag + run: | + if [[ ${{ github.event.ref }} =~ ^refs/tags/[0-9]+\.[0-9]+\.[0-9]+$ ]]; then + echo "tag_matches=true" >> $GITHUB_OUTPUT + fi + build-and-release: + runs-on: ubuntu-latest + needs: check_tag + permissions: write-all + steps: + - name: Checkout + uses: actions/checkout@v3 + with: + fetch-depth: 0 + # https://github.com/docker/setup-qemu-action - for multiplatform builds + - name: Set up QEMU + uses: docker/setup-qemu-action@v2 + # https://github.com/docker/setup-buildx-action - for multiplatform builds + - name: Set up Docker Buildx + id: buildx + uses: docker/setup-buildx-action@v2 + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: "3.10" + - name: Install Client Dev Dependencies + run: python -m pip install -r requirements_dev.txt + - name: Build Client + run: python -m build + - name: Test Client Package + run: bin/test-package.sh dist/*.tar.gz + - name: Log in to the Github Container registry + uses: docker/login-action@v2.1.0 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + - name: Login to DockerHub + uses: docker/login-action@v2.1.0 + with: + username: ${{ secrets.DOCKERHUB_USERNAME }} + password: ${{ secrets.DOCKERHUB_TOKEN }} + - name: Install setuptools_scm + run: python -m pip install setuptools_scm + - name: Get Release Version + id: version + run: echo "version=$(python -m setuptools_scm)" >> $GITHUB_OUTPUT + - name: Build and push prerelease Docker image + if: "needs.check_tag.outputs.tag_matches != 'true'" + uses: docker/build-push-action@v3.2.0 + with: + context: . + platforms: ${{ env.PLATFORMS }} + push: true + tags: "${{ env.GHCR_IMAGE_NAME }}:${{ steps.version.outputs.version }},${{ env.DOCKERHUB_IMAGE_NAME }}:${{ steps.version.outputs.version }}" + - name: Build and push release Docker image + if: "needs.check_tag.outputs.tag_matches == 'true'" + uses: docker/build-push-action@v3.2.0 + with: + context: . + platforms: ${{ env.PLATFORMS }} + push: true + tags: "${{ env.GHCR_IMAGE_NAME }}:${{ steps.version.outputs.version }},${{ env.DOCKERHUB_IMAGE_NAME }}:${{ steps.version.outputs.version }},${{ env.GHCR_IMAGE_NAME }}:latest,${{ env.DOCKERHUB_IMAGE_NAME }}:latest" + - name: Get current date + id: builddate + run: echo "builddate=$(date +'%Y-%m-%dT%H:%M')" >> $GITHUB_OUTPUT + - name: Publish to Test PyPI + uses: pypa/gh-action-pypi-publish@release/v1 + with: + password: ${{ secrets.TEST_PYPI_API_TOKEN }} + repository_url: https://test.pypi.org/legacy/ + - name: Publish to PyPI + if: "needs.check_tag.outputs.tag_matches == 'true'" + uses: pypa/gh-action-pypi-publish@release/v1 + with: + password: ${{ secrets.PYPI_API_TOKEN }} + - name: Login to AWS + uses: aws-actions/configure-aws-credentials@v1 + with: + role-to-assume: arn:aws:iam::369178033109:role/github-action-generate-cf-template + aws-region: us-east-1 + - name: Generate CloudFormation template + id: generate-cf + if: "needs.check_tag.outputs.tag_matches == 'true'" + run: "pip install boto3 && python bin/generate_cloudformation.py" + - name: Release Tagged Version + uses: ncipollo/release-action@v1.11.1 + if: "needs.check_tag.outputs.tag_matches == 'true'" + with: + body: | + Version: `${{steps.version.outputs.version}}` + Git ref: `${{github.ref}}` + Build Date: `${{steps.builddate.outputs.builddate}}` + PIP Package: `chroma-${{steps.version.outputs.version}}.tar.gz` + Github Container Registry Image: `${{ env.GHCR_IMAGE_NAME }}:${{ steps.version.outputs.version }}` + DockerHub Image: `${{ env.DOCKERHUB_IMAGE_NAME }}:${{ steps.version.outputs.version }}` + artifacts: "dist/chroma-${{steps.version.outputs.version}}.tar.gz" + prerelease: true + generateReleaseNotes: true + - name: Update Tag + uses: richardsimko/update-tag@v1.0.5 + if: "needs.check_tag.outputs.tag_matches != 'true'" + with: + tag_name: latest + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + - name: Release Latest + uses: ncipollo/release-action@v1.11.1 + if: "needs.check_tag.outputs.tag_matches != 'true'" + with: + tag: "latest" + name: "Latest" + body: | + Version: `${{steps.version.outputs.version}}` + Git ref: `${{github.ref}}` + Build Date: `${{steps.builddate.outputs.builddate}}` + PIP Package: `chroma-${{steps.version.outputs.version}}.tar.gz` + Github Container Registry Image: `${{ env.GHCR_IMAGE_NAME }}:${{ steps.version.outputs.version }}` + DockerHub Image: `${{ env.DOCKERHUB_IMAGE_NAME }}:${{ steps.version.outputs.version }}` + artifacts: "dist/chroma-${{steps.version.outputs.version}}.tar.gz" + allowUpdates: true + prerelease: true + - name: Trigger Hosted Chroma FE Release + uses: actions/github-script@v6 + with: + github-token: ${{ secrets.HOSTED_CHROMA_WORKFLOW_DISPATCH_TOKEN }} + script: | + const result = await github.rest.actions.createWorkflowDispatch({ + owner: 'chroma-core', + repo: 'hosted-chroma', + workflow_id: 'build-and-publish-frontend.yaml', + ref: 'main' + }) + console.log(result) + - name: Trigger Hosted Chroma Coordinator Release + uses: actions/github-script@v6 + with: + github-token: ${{ secrets.HOSTED_CHROMA_WORKFLOW_DISPATCH_TOKEN }} + script: | + const result = await github.rest.actions.createWorkflowDispatch({ + owner: 'chroma-core', + repo: 'hosted-chroma', + workflow_id: 'build-and-deploy-coordinator.yaml', + ref: 'main' + }) + console.log(result) + - name: Trigger Hosted Worker Release + uses: actions/github-script@v6 + with: + github-token: ${{ secrets.HOSTED_CHROMA_WORKFLOW_DISPATCH_TOKEN }} + script: | + const result = await github.rest.actions.createWorkflowDispatch({ + owner: 'chroma-core', + repo: 'hosted-chroma', + workflow_id: 'build-and-deploy-worker.yaml', + ref: 'main' + }) + console.log(result) diff --git a/.github/workflows/chroma-test.yml b/.github/workflows/chroma-test.yml new file mode 100644 index 0000000000000000000000000000000000000000..12a5de4b6eda39231c5845a4b8a7081cae7130de --- /dev/null +++ b/.github/workflows/chroma-test.yml @@ -0,0 +1,65 @@ +name: Chroma Tests + +on: + push: + branches: + - main + - team/hypothesis-tests + pull_request: + branches: + - main + - '**' + workflow_dispatch: + +jobs: + test: + timeout-minutes: 90 + strategy: + matrix: + python: ['3.8', '3.9', '3.10', '3.11'] + platform: [ubuntu-latest, windows-latest] + testfile: ["--ignore-glob 'chromadb/test/property/*' --ignore-glob 'chromadb/test/stress/*' --ignore='chromadb/test/auth/test_simple_rbac_authz.py'", + "chromadb/test/auth/test_simple_rbac_authz.py", + "chromadb/test/property/test_add.py", + "chromadb/test/property/test_collections.py", + "chromadb/test/property/test_cross_version_persist.py", + "chromadb/test/property/test_embeddings.py", + "chromadb/test/property/test_filtering.py", + "chromadb/test/property/test_persist.py"] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python }} + - name: Install test dependencies + run: python -m pip install -r requirements.txt && python -m pip install -r requirements_dev.txt + - name: Upgrade SQLite + run: python bin/windows_upgrade_sqlite.py + if: runner.os == 'Windows' + - name: Test + run: python -m pytest ${{ matrix.testfile }} + stress-test: + timeout-minutes: 90 + strategy: + matrix: + python: ['3.8'] + platform: ['16core-64gb-ubuntu-latest', '16core-64gb-windows-latest'] + testfile: ["'chromadb/test/stress/'"] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout + uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python }} + uses: actions/setup-python@v4 + with: + python-version: ${{ matrix.python }} + - name: Install test dependencies + run: python -m pip install -r requirements.txt && python -m pip install -r requirements_dev.txt + - name: Upgrade SQLite + run: python bin/windows_upgrade_sqlite.py + if: runner.os == 'Windows' + - name: Test + run: python -m pytest ${{ matrix.testfile }} diff --git a/.github/workflows/chroma-worker-test.yml b/.github/workflows/chroma-worker-test.yml new file mode 100644 index 0000000000000000000000000000000000000000..33e1012e0c8713f6bb2b16c86dbc9a646707897e --- /dev/null +++ b/.github/workflows/chroma-worker-test.yml @@ -0,0 +1,36 @@ +name: Chroma Worker Tests + +on: + push: + branches: + - main + pull_request: + branches: + - main + - '**' + workflow_dispatch: + +jobs: + test: + strategy: + matrix: + platform: [ubuntu-latest] + runs-on: ${{ matrix.platform }} + steps: + - name: Checkout chroma-hnswlib + uses: actions/checkout@v3 + with: + repository: chroma-core/hnswlib + path: hnswlib + - name: Checkout + uses: actions/checkout@v3 + with: + path: chroma + - name: Install Protoc + uses: arduino/setup-protoc@v2 + - name: Build + run: cargo build --verbose + working-directory: chroma + - name: Test + run: cargo test --verbose + working-directory: chroma diff --git a/.github/workflows/pr-review-checklist.yml b/.github/workflows/pr-review-checklist.yml new file mode 100644 index 0000000000000000000000000000000000000000..fdf9c8576d1cc4e1879ea9b3c8b4e4125b053077 --- /dev/null +++ b/.github/workflows/pr-review-checklist.yml @@ -0,0 +1,37 @@ +name: PR Review Checklist + +on: + pull_request_target: + types: + - opened + +jobs: + PR-Comment: + runs-on: ubuntu-latest + steps: + - name: PR Comment + uses: actions/github-script@v2 + with: + github-token: ${{secrets.GITHUB_TOKEN}} + script: | + github.issues.createComment({ + issue_number: ${{ github.event.number }}, + owner: context.repo.owner, + repo: context.repo.repo, + body: `# Reviewer Checklist + Please leverage this checklist to ensure your code review is thorough before approving + ## Testing, Bugs, Errors, Logs, Documentation + - [ ] Can you think of any use case in which the code does not behave as intended? Have they been tested? + - [ ] Can you think of any inputs or external events that could break the code? Is user input validated and safe? Have they been tested? + - [ ] If appropriate, are there adequate property based tests? + - [ ] If appropriate, are there adequate unit tests? + - [ ] Should any logging, debugging, tracing information be added or removed? + - [ ] Are error messages user-friendly? + - [ ] Have all documentation changes needed been made? + - [ ] Have all non-obvious changes been commented? + ## System Compatibility + - [ ] Are there any potential impacts on other parts of the system or backward compatibility? + - [ ] Does this change intersect with any items on our roadmap, and if so, is there a plan for fitting them together? + ## Quality + - [ ] Is this code of a unexpectedly high quality (Readability, Modularity, Intuitiveness)` + }) diff --git a/.github/workflows/python-vuln.yaml b/.github/workflows/python-vuln.yaml new file mode 100644 index 0000000000000000000000000000000000000000..8e6c33a255c375be95d75bc8d5ee5a9648e51437 --- /dev/null +++ b/.github/workflows/python-vuln.yaml @@ -0,0 +1,28 @@ +name: Python Vulnerability Scan +on: + push: + branches: + - '*' + - '*/**' + paths: + - chromadb/** + - clients/python/** + workflow_dispatch: +jobs: + bandit-scan: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v3 + - uses: ./.github/actions/bandit-scan/ + with: + input-dir: '.' + format: 'json' + bandit-config: 'bandit.yaml' + output-file: 'bandit-report.json' + - name: Upload Bandit Report + uses: actions/upload-artifact@v3 + with: + name: bandit-artifact + path: | + bandit-report.json diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..10e6fd2d7316a59a3ea28b547cf0a2b7e01fe13a --- /dev/null +++ b/.gitignore @@ -0,0 +1,34 @@ +# ignore mac created DS_Store files +**/.DS_Store + +**/__pycache__ + +go/coordinator/bin/ +go/coordinator/**/testdata/ + +*.log + +**/data__nogit + +**/.ipynb_checkpoints + +index_data + +# Default configuration for persist_directory in chromadb/config.py +# Currently it's located in "./chroma/" +chroma/ +chroma_test_data/ +server.htpasswd + +.venv +venv +.env +.chroma +*.egg-info +dist + +.terraform/ +.terraform.lock.hcl +terraform.tfstate +.hypothesis/ +.idea diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..7b1d50ec94058735248fe84a3307957bd3228c34 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,36 @@ +exclude: 'chromadb/proto/(chroma_pb2|coordinator_pb2)\.(py|pyi|py_grpc\.py)' # Generated files +repos: + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.5.0 + hooks: + - id: trailing-whitespace + - id: mixed-line-ending + - id: end-of-file-fixer + - id: requirements-txt-fixer + - id: check-yaml + args: ["--allow-multiple-documents"] + - id: check-xml + - id: check-merge-conflict + - id: check-case-conflict + - id: check-docstring-first + + - repo: https://github.com/psf/black + # https://github.com/psf/black/issues/2493 + rev: 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0000000000000000000000000000000000000000..bc724ce66de218d66bf06b306af52ced91dda685 --- /dev/null +++ b/Cargo.toml @@ -0,0 +1,5 @@ +[workspace] + +members = [ + "rust/worker/" +] diff --git a/DEVELOP.md b/DEVELOP.md new file mode 100644 index 0000000000000000000000000000000000000000..05357f29e60a5a2af7137d13a66d51ae006c1a68 --- /dev/null +++ b/DEVELOP.md @@ -0,0 +1,111 @@ +# Development Instructions + +This project uses the testing, build and release standards specified +by the PyPA organization and documented at +https://packaging.python.org. + +## Setup + +Because of the dependencies it relies on (like `pytorch`), this project does not support Python version >3.10.0. + +Set up a virtual environment and install the project's requirements +and dev requirements: + +``` +python3 -m venv venv # Only need to do this once +source venv/bin/activate # Do this each time you use a new shell for the project +pip install -r requirements.txt +pip install -r requirements_dev.txt +pre-commit install # install the precommit hooks +``` + +You can also install `chromadb` the `pypi` package locally and in editable mode with `pip install -e .`. + +## Running Chroma + +Chroma can be run via 3 modes: +1. Standalone and in-memory: +```python +import chromadb +api = chromadb.Client() +print(api.heartbeat()) +``` + +2. Standalone and in-memory with persistence: + +This by default saves your db and your indexes to a `.chroma` directory and can also load from them. +```python +import chromadb +api = chromadb.PersistentClient(path="/path/to/persist/directory") +print(api.heartbeat()) +``` + + +3. With a persistent backend and a small frontend client + +Run `chroma run --path /chroma_db_path` +```python +import chromadb +api = chromadb.HttpClient(host="localhost", port="8000") + +print(api.heartbeat()) +``` +## Local dev setup for distributed chroma +We use tilt for providing local dev setup. Tilt is an open source project +##### Requirement +- Docker +- Local Kubernetes cluster (Recommended: [OrbStack](https://orbstack.dev/) for mac, [Kind](https://kind.sigs.k8s.io/) for linux) +- [Tilt](https://docs.tilt.dev/) + +For starting the distributed Chroma in the workspace, use `tilt up`. It will create all the required resources and build the necessary Docker image in the current kubectl context. +Once done, it will expose Chroma on port 8000. You can also visit the Tilt dashboard UI at http://localhost:10350/. To clean and remove all the resources created by Tilt, use `tilt down`. + +## Testing + +Unit tests are in the `/chromadb/test` directory. + +To run unit tests using your current environment, run `pytest`. + +## Manual Build + +To manually build a distribution, run `python -m build`. + +The project's source and wheel distributions will be placed in the `dist` directory. + +## Manual Release + +Not yet implemented. + +## Versioning + +This project uses PyPA's `setuptools_scm` module to determine the +version number for build artifacts, meaning the version number is +derived from Git rather than hardcoded in the repository. For full +details, see the +[documentation for setuptools_scm](https://github.com/pypa/setuptools_scm/). + +In brief, version numbers are generated as follows: + +- If the current git head is tagged, the version number is exactly the + tag (e.g, `0.0.1`). +- If the the current git head is a clean checkout, but is not tagged, + the version number is a patch version increment of the most recent + tag, plus `devN` where N is the number of commits since the most + recent tag. For example, if there have been 5 commits since the + `0.0.1` tag, the generated version will be `0.0.2-dev5`. +- If the current head is not a clean checkout, a `+dirty` local + version will be appended to the version number. For example, + `0.0.2-dev5+dirty`. + +At any point, you can manually run `python -m setuptools_scm` to see +what version would be assigned given your current state. + +## Continuous Integration + +This project uses Github Actions to run unit tests automatically upon +every commit to the main branch. See the documentation for Github +Actions and the flow definitions in `.github/workflows` for details. + +## Continuous Delivery + +Not yet implemented. diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..fbba6cb6946978423c0a532c001c65dff9629e72 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,39 @@ +FROM python:3.11-slim-bookworm AS builder +ARG REBUILD_HNSWLIB +RUN apt-get update --fix-missing && apt-get install -y --fix-missing \ + build-essential \ + gcc \ + g++ \ + cmake \ + autoconf && \ + rm -rf /var/lib/apt/lists/* && \ + mkdir /install + +WORKDIR /install + +COPY ./requirements.txt requirements.txt + +RUN pip install --no-cache-dir --upgrade --prefix="/install" -r requirements.txt +RUN if [ "$REBUILD_HNSWLIB" = "true" ]; then pip install --no-binary :all: --force-reinstall --no-cache-dir --prefix="/install" chroma-hnswlib; fi + +FROM python:3.11-slim-bookworm AS final + +RUN mkdir /chroma +WORKDIR /chroma + +COPY --from=builder /install /usr/local +COPY ./bin/docker_entrypoint.sh /docker_entrypoint.sh +COPY ./ /chroma + +RUN chmod +x /docker_entrypoint.sh + +ENV CHROMA_HOST_ADDR "0.0.0.0" +ENV CHROMA_HOST_PORT 7860 +ENV CHROMA_WORKERS 1 +ENV CHROMA_LOG_CONFIG "chromadb/log_config.yml" +ENV CHROMA_TIMEOUT_KEEP_ALIVE 30 + +EXPOSE 7860 + +ENTRYPOINT ["/docker_entrypoint.sh"] +CMD [ "--workers ${CHROMA_WORKERS} --host ${CHROMA_HOST_ADDR} --port ${CHROMA_HOST_PORT} --proxy-headers --log-config ${CHROMA_LOG_CONFIG} --timeout-keep-alive ${CHROMA_TIMEOUT_KEEP_ALIVE}"] \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..261eeb9e9f8b2b4b0d119366dda99c6fd7d35c64 --- /dev/null +++ b/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/README.md b/README.md index 4328857951a1370b57708913f5c9ac0ec53f32b9..139b66583f4ecc04ceb2c534e6aee3be076a9ce5 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,106 @@ ---- -title: Chroma -emoji: 🏢 -colorFrom: indigo -colorTo: indigo -sdk: docker -pinned: false -license: mit ---- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference +

+ Chroma logo +

+ +

+ Chroma - the open-source embedding database.
+ The fastest way to build Python or JavaScript LLM apps with memory! +

+ +

+ + Discord + | + + License + | + + Docs + | + + Homepage + +

+ + +

+ + Integration Tests + | + + Tests + +

+ +```bash +pip install chromadb # python client +# for javascript, npm install chromadb! +# for client-server mode, chroma run --path /chroma_db_path +``` + +The core API is only 4 functions (run our [💡 Google Colab](https://colab.research.google.com/drive/1QEzFyqnoFxq7LUGyP1vzR4iLt9PpCDXv?usp=sharing) or [Replit template](https://replit.com/@swyx/BasicChromaStarter?v=1)): + +```python +import chromadb +# setup Chroma in-memory, for easy prototyping. Can add persistence easily! +client = chromadb.Client() + +# Create collection. get_collection, get_or_create_collection, delete_collection also available! +collection = client.create_collection("all-my-documents") + +# Add docs to the collection. Can also update and delete. Row-based API coming soon! +collection.add( + documents=["This is document1", "This is document2"], # we handle tokenization, embedding, and indexing automatically. You can skip that and add your own embeddings as well + metadatas=[{"source": "notion"}, {"source": "google-docs"}], # filter on these! + ids=["doc1", "doc2"], # unique for each doc +) + +# Query/search 2 most similar results. You can also .get by id +results = collection.query( + query_texts=["This is a query document"], + n_results=2, + # where={"metadata_field": "is_equal_to_this"}, # optional filter + # where_document={"$contains":"search_string"} # optional filter +) +``` + +## Features +- __Simple__: Fully-typed, fully-tested, fully-documented == happiness +- __Integrations__: [`🦜️🔗 LangChain`](https://blog.langchain.dev/langchain-chroma/) (python and js), [`🦙 LlamaIndex`](https://twitter.com/atroyn/status/1628557389762007040) and more soon +- __Dev, Test, Prod__: the same API that runs in your python notebook, scales to your cluster +- __Feature-rich__: Queries, filtering, density estimation and more +- __Free & Open Source__: Apache 2.0 Licensed + +## Use case: ChatGPT for ______ + +For example, the `"Chat your data"` use case: +1. Add documents to your database. You can pass in your own embeddings, embedding function, or let Chroma embed them for you. +2. Query relevant documents with natural language. +3. Compose documents into the context window of an LLM like `GPT3` for additional summarization or analysis. + +## Embeddings? + +What are embeddings? + +- [Read the guide from OpenAI](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings) +- __Literal__: Embedding something turns it from image/text/audio into a list of numbers. 🖼️ or 📄 => `[1.2, 2.1, ....]`. This process makes documents "understandable" to a machine learning model. +- __By analogy__: An embedding represents the essence of a document. This enables documents and queries with the same essence to be "near" each other and therefore easy to find. +- __Technical__: An embedding is the latent-space position of a document at a layer of a deep neural network. For models trained specifically to embed data, this is the last layer. +- __A small example__: If you search your photos for "famous bridge in San Francisco". By embedding this query and comparing it to the embeddings of your photos and their metadata - it should return photos of the Golden Gate Bridge. + +Embeddings databases (also known as **vector databases**) store embeddings and allow you to search by nearest neighbors rather than by substrings like a traditional database. By default, Chroma uses [Sentence Transformers](https://docs.trychroma.com/embeddings#sentence-transformers) to embed for you but you can also use OpenAI embeddings, Cohere (multilingual) embeddings, or your own. + +## Get involved + +Chroma is a rapidly developing project. We welcome PR contributors and ideas for how to improve the project. +- [Join the conversation on Discord](https://discord.gg/MMeYNTmh3x) - `#contributing` channel +- [Review the 🛣️ Roadmap and contribute your ideas](https://docs.trychroma.com/roadmap) +- [Grab an issue and open a PR](https://github.com/chroma-core/chroma/issues) - [`Good first issue tag`](https://github.com/chroma-core/chroma/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) +- [Read our contributing guide](https://docs.trychroma.com/contributing) + +**Release Cadence** +We currently release new tagged versions of the `pypi` and `npm` packages on Mondays. Hotfixes go out at any time during the week. + +## License + +[Apache 2.0](./LICENSE) diff --git a/RELEASE_PROCESS.md b/RELEASE_PROCESS.md new file mode 100644 index 0000000000000000000000000000000000000000..577345c8faedcb02eea9ab8d8010f8a92a806b0c --- /dev/null +++ b/RELEASE_PROCESS.md @@ -0,0 +1,22 @@ +## Release Process + +This guide covers how to release chroma to PyPi + +#### Increase the version number +1. Create a new PR for the release that upgrades the version in code. Name it `release/A.B.C` In [this file](https://github.com/chroma-core/chroma/blob/main/chromadb/__init__.py) update the __ version __. +``` +__version__ = "A.B.C" +``` +2. Add the "release" label to this PR +3. Once the PR is merged, tag your commit SHA with the release version +``` +git tag A.B.C +``` +4. You need to then wait for the github action for main for `chroma release` and `chroma client release` to go green. Not doing this will result in a race condition. + +#### Perform the release +1. Push your tag to origin to create the release +``` +git push origin A.B.C +``` +2. This will trigger a Github action which performs the release diff --git a/Tiltfile b/Tiltfile new file mode 100644 index 0000000000000000000000000000000000000000..7be3d4ca594f36eb5345d98d99c3d0afcc7b4417 --- /dev/null +++ b/Tiltfile @@ -0,0 +1,30 @@ +docker_build('coordinator', + context='.', + dockerfile='./go/coordinator/Dockerfile' +) + +docker_build('server', + context='.', + dockerfile='./Dockerfile', +) + +docker_build('worker', + context='.', + dockerfile='./rust/worker/Dockerfile' +) + + +k8s_yaml(['k8s/dev/setup.yaml']) +k8s_resource( + objects=['chroma:Namespace', 'memberlist-reader:ClusterRole', 'memberlist-reader:ClusterRoleBinding', 'pod-list-role:Role', 'pod-list-role-binding:RoleBinding', 'memberlists.chroma.cluster:CustomResourceDefinition','worker-memberlist:MemberList'], + new_name='k8s_setup', + labels=["infrastructure"] +) +k8s_yaml(['k8s/dev/pulsar.yaml']) +k8s_resource('pulsar', resource_deps=['k8s_setup'], labels=["infrastructure"]) +k8s_yaml(['k8s/dev/server.yaml']) +k8s_resource('server', resource_deps=['k8s_setup'],labels=["chroma"], port_forwards=8000 ) +k8s_yaml(['k8s/dev/coordinator.yaml']) +k8s_resource('coordinator', resource_deps=['pulsar', 'server'], labels=["chroma"]) +k8s_yaml(['k8s/dev/worker.yaml']) +k8s_resource('worker', resource_deps=['coordinator'],labels=["chroma"]) diff --git a/bandit.yaml b/bandit.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9a93633ea12a81e8a03a3f19b4bf38a17a1d3753 --- /dev/null +++ b/bandit.yaml @@ -0,0 +1,4 @@ +# FILE: bandit.yaml +exclude_dirs: [ 'chromadb/test', 'bin', 'build', 'build', '.git', '.venv', 'venv', 'env','.github','examples','clients/js','.vscode' ] +tests: [ ] +skips: [ ] diff --git a/bin/cluster-test.sh b/bin/cluster-test.sh new file mode 100755 index 0000000000000000000000000000000000000000..10c48781c072238d7264fc9d0b56ff605a8ee7f8 --- /dev/null +++ b/bin/cluster-test.sh @@ -0,0 +1,62 @@ +#!/usr/bin/env bash + +set -e + +function cleanup { + # Restore the previous kube context + kubectl config use-context $PREV_CHROMA_KUBE_CONTEXT + # Kill the tunnel process + kill $TUNNEL_PID + minikube delete -p chroma-test +} + +trap cleanup EXIT + +# Save the current kube context into a variable +export PREV_CHROMA_KUBE_CONTEXT=$(kubectl config current-context) + +# Create a new minikube cluster for the test +minikube start -p chroma-test + +# Add the ingress addon to the cluster +minikube addons enable ingress -p chroma-test +minikube addons enable ingress-dns -p chroma-test + +# Setup docker to build inside the minikube cluster and build the image +eval $(minikube -p chroma-test docker-env) +docker build -t server:latest -f Dockerfile . +docker build -t chroma-coordinator:latest -f go/coordinator/Dockerfile . +docker build -t worker -f rust/worker/Dockerfile . --build-arg CHROMA_KUBERNETES_INTEGRATION=1 + +# Apply the kubernetes manifests +kubectl apply -f k8s/deployment +kubectl apply -f k8s/crd +kubectl apply -f k8s/cr +kubectl apply -f k8s/test + +# Wait for the pods in the chroma namespace to be ready +kubectl wait --namespace chroma --for=condition=Ready pods --all --timeout=400s + +# Run mini kube tunnel in the background to expose the service +minikube tunnel -c true -p chroma-test & +TUNNEL_PID=$! + +# Wait for the tunnel to be ready. There isn't an easy way to check if the tunnel is ready. So we just wait for 10 seconds +sleep 10 + +export CHROMA_CLUSTER_TEST_ONLY=1 +export CHROMA_SERVER_HOST=$(kubectl get svc server -n chroma -o=jsonpath='{.status.loadBalancer.ingress[0].ip}') +export PULSAR_BROKER_URL=$(kubectl get svc pulsar-lb -n chroma -o=jsonpath='{.status.loadBalancer.ingress[0].ip}') +export CHROMA_COORDINATOR_HOST=$(kubectl get svc coordinator-lb -n chroma -o=jsonpath='{.status.loadBalancer.ingress[0].ip}') +export CHROMA_SERVER_GRPC_PORT="50051" + +echo "Chroma Server is running at port $CHROMA_SERVER_HOST" +echo "Pulsar Broker is running at port $PULSAR_BROKER_URL" +echo "Chroma Coordinator is running at port $CHROMA_COORDINATOR_HOST" + +echo testing: python -m pytest "$@" +python -m pytest "$@" + +export CHROMA_KUBERNETES_INTEGRATION=1 +cd go/coordinator +go test -timeout 30s -run ^TestNodeWatcher$ github.com/chroma/chroma-coordinator/internal/memberlist_manager diff --git a/bin/docker_entrypoint.sh b/bin/docker_entrypoint.sh new file mode 100755 index 0000000000000000000000000000000000000000..e9498b4fd7ca3c02e43c1c281ca98b2204d89d87 --- /dev/null +++ b/bin/docker_entrypoint.sh @@ -0,0 +1,15 @@ +#!/bin/bash +set -e + +export IS_PERSISTENT=1 +export CHROMA_SERVER_NOFILE=65535 +args="$@" + +if [[ $args =~ ^uvicorn.* ]]; then + echo "Starting server with args: $(eval echo "$args")" + echo -e "\033[31mWARNING: Please remove 'uvicorn chromadb.app:app' from your command line arguments. This is now handled by the entrypoint script." + exec $(eval echo "$args") +else + echo "Starting 'uvicorn chromadb.app:app' with args: $(eval echo "$args")" + exec uvicorn chromadb.app:app $(eval echo "$args") +fi diff --git a/bin/generate_cloudformation.py b/bin/generate_cloudformation.py new file mode 100644 index 0000000000000000000000000000000000000000..4265e0c2a52be8589a8885ef528bb3968788c1c0 --- /dev/null +++ b/bin/generate_cloudformation.py @@ -0,0 +1,198 @@ +import boto3 +import json +import subprocess +import os +import re + + +def b64text(txt): + """Generate Base 64 encoded CF json for a multiline string, subbing in values where appropriate""" + lines = [] + for line in txt.splitlines(True): + if "${" in line: + lines.append({"Fn::Sub": line}) + else: + lines.append(line) + return {"Fn::Base64": {"Fn::Join": ["", lines]}} + + +path = os.path.dirname(os.path.realpath(__file__)) +version = subprocess.check_output(f"{path}/version").decode("ascii").strip() + +with open(f"{path}/templates/docker-compose.yml") as f: + docker_compose_file = str(f.read()) + + +cloud_config_script = """ +#cloud-config +cloud_final_modules: +- [scripts-user, always] +""" + +cloud_init_script = f""" +#!/bin/bash +amazon-linux-extras install docker +usermod -a -G docker ec2-user +curl -L https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m) -o /usr/local/bin/docker-compose +chmod +x /usr/local/bin/docker-compose +ln -s /usr/local/bin/docker-compose /usr/bin/docker-compose +systemctl enable docker +systemctl start docker + +cat << EOF > /home/ec2-user/docker-compose.yml +{docker_compose_file} +EOF + +mkdir /home/ec2-user/config + +docker-compose -f /home/ec2-user/docker-compose.yml up -d +""" + +userdata = f"""Content-Type: multipart/mixed; boundary="//" +MIME-Version: 1.0 + +--// +Content-Type: text/cloud-config; charset="us-ascii" +MIME-Version: 1.0 +Content-Transfer-Encoding: 7bit +Content-Disposition: attachment; filename="cloud-config.txt" + +{cloud_config_script} + +--// +Content-Type: text/x-shellscript; charset="us-ascii" +MIME-Version: 1.0 +Content-Transfer-Encoding: 7bit +Content-Disposition: attachment; filename="userdata.txt" + +{cloud_init_script} +--//-- +""" + +cf = { + "AWSTemplateFormatVersion": "2010-09-09", + "Description": "Create a stack that runs Chroma hosted on a single instance", + "Parameters": { + "KeyName": { + "Description": "Name of an existing EC2 KeyPair to enable SSH access to the instance", + "Type": "String", + "ConstraintDescription": "If present, must be the name of an existing EC2 KeyPair.", + "Default": "", + }, + "InstanceType": { + "Description": "EC2 instance type", + "Type": "String", + "Default": "t3.small", + }, + "ChromaVersion": { + "Description": "Chroma version to install", + "Type": "String", + "Default": version, + }, + }, + "Conditions": { + "HasKeyName": {"Fn::Not": [{"Fn::Equals": [{"Ref": "KeyName"}, ""]}]}, + }, + "Resources": { + "ChromaInstance": { + "Type": "AWS::EC2::Instance", + "Properties": { + "ImageId": { + "Fn::FindInMap": ["Region2AMI", {"Ref": "AWS::Region"}, "AMI"] + }, + "InstanceType": {"Ref": "InstanceType"}, + "UserData": b64text(userdata), + "SecurityGroupIds": [{"Ref": "ChromaInstanceSecurityGroup"}], + "KeyName": { + "Fn::If": [ + "HasKeyName", + {"Ref": "KeyName"}, + {"Ref": "AWS::NoValue"}, + ] + }, + "BlockDeviceMappings": [ + { + "DeviceName": { + "Fn::FindInMap": [ + "Region2AMI", + {"Ref": "AWS::Region"}, + "RootDeviceName", + ] + }, + "Ebs": {"VolumeSize": 24}, + } + ], + }, + }, + "ChromaInstanceSecurityGroup": { + "Type": "AWS::EC2::SecurityGroup", + "Properties": { + "GroupDescription": "Chroma Instance Security Group", + "SecurityGroupIngress": [ + { + "IpProtocol": "tcp", + "FromPort": "22", + "ToPort": "22", + "CidrIp": "0.0.0.0/0", + }, + { + "IpProtocol": "tcp", + "FromPort": "8000", + "ToPort": "8000", + "CidrIp": "0.0.0.0/0", + }, + ], + }, + }, + }, + "Outputs": { + "ServerIp": { + "Description": "IP address of the Chroma server", + "Value": {"Fn::GetAtt": ["ChromaInstance", "PublicIp"]}, + } + }, + "Mappings": {"Region2AMI": {}}, +} + +# Populate the Region2AMI mappings +regions = boto3.client("ec2", region_name="us-east-1").describe_regions()["Regions"] +for region in regions: + region_name = region["RegionName"] + ami_result = boto3.client("ec2", region_name=region_name).describe_images( + Owners=["137112412989"], + Filters=[ + {"Name": "name", "Values": ["amzn2-ami-kernel-5.10-hvm-*-x86_64-gp2"]}, + {"Name": "root-device-type", "Values": ["ebs"]}, + {"Name": "virtualization-type", "Values": ["hvm"]}, + ], + ) + img = ami_result["Images"][0] + ami_id = img["ImageId"] + root_device_name = img["BlockDeviceMappings"][0]["DeviceName"] + cf["Mappings"]["Region2AMI"][region_name] = { + "AMI": ami_id, + "RootDeviceName": root_device_name, + } + + +# Write the CF json to a file +json.dump(cf, open("/tmp/chroma.cf.json", "w"), indent=4) + +# upload to S3 +s3 = boto3.client("s3", region_name="us-east-1") +s3.upload_file( + "/tmp/chroma.cf.json", + "public.trychroma.com", + f"cloudformation/{version}/chroma.cf.json", +) + +# Upload to s3 under /latest version only if this is a release +pattern = re.compile(r"^\d+\.\d+\.\d+$") +if pattern.match(version): + s3.upload_file( + "/tmp/chroma.cf.json", + "public.trychroma.com", + "cloudformation/latest/chroma.cf.json", + ) +else: + print(f"Version {version} is not a 3-part semver, not uploading to /latest") diff --git a/bin/integration-test b/bin/integration-test new file mode 100755 index 0000000000000000000000000000000000000000..3a1b1bb2a079a128f86bae55bf8bc54af30a5048 --- /dev/null +++ b/bin/integration-test @@ -0,0 +1,75 @@ +#!/usr/bin/env bash + +set -e + +export CHROMA_PORT=8000 + +function cleanup { + docker compose -f docker-compose.test.yml down --rmi local --volumes + rm server.htpasswd .chroma_env +} + +function setup_auth { + local auth_type="$1" + case "$auth_type" in + basic) + docker run --rm --entrypoint htpasswd httpd:2 -Bbn admin admin > server.htpasswd + cat < .chroma_env +CHROMA_SERVER_AUTH_CREDENTIALS_FILE="/chroma/server.htpasswd" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.basic.BasicAuthServerProvider" +EOF + ;; + token) + cat < .chroma_env +CHROMA_SERVER_AUTH_CREDENTIALS="test-token" +CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER="AUTHORIZATION" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.token.TokenAuthServerProvider" +EOF + ;; + xtoken) + cat < .chroma_env +CHROMA_SERVER_AUTH_CREDENTIALS="test-token" +CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER="X_CHROMA_TOKEN" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.token.TokenAuthServerProvider" +EOF + ;; + *) + echo "Unknown auth type: $auth_type" + exit 1 + ;; + esac +} + +trap cleanup EXIT + +docker compose -f docker-compose.test.yml up --build -d + +export CHROMA_INTEGRATION_TEST_ONLY=1 +export CHROMA_API_IMPL=chromadb.api.fastapi.FastAPI +export CHROMA_SERVER_HOST=localhost +export CHROMA_SERVER_HTTP_PORT=8000 +export CHROMA_SERVER_NOFILE=65535 + +echo testing: python -m pytest "$@" +python -m pytest "$@" + +cd clients/js + +# moved off of yarn to npm to fix issues with jackspeak/cliui/string-width versions #1314 +npm install +npm run test:run + +docker compose down +cd ../.. +for auth_type in basic token xtoken; do + echo "Testing $auth_type auth" + setup_auth "$auth_type" + cd clients/js + docker compose --env-file ../../.chroma_env -f ../../docker-compose.test-auth.yml up --build -d + yarn test:run-auth-"$auth_type" + cd ../.. + docker compose down +done diff --git a/bin/reset.sh b/bin/reset.sh new file mode 100755 index 0000000000000000000000000000000000000000..92fb04d8224f7a864aea410cc3d2d86aee814971 --- /dev/null +++ b/bin/reset.sh @@ -0,0 +1,13 @@ + #!/usr/bin/env bash + +eval $(minikube -p chroma-test docker-env) + +docker build -t chroma-coordinator:latest -f go/coordinator/Dockerfile . + +kubectl delete deployment coordinator -n chroma + +# Apply the kubernetes manifests +kubectl apply -f k8s/deployment +kubectl apply -f k8s/crd +kubectl apply -f k8s/cr +kubectl apply -f k8s/test diff --git a/bin/templates/docker-compose.yml b/bin/templates/docker-compose.yml new file mode 100644 index 0000000000000000000000000000000000000000..d3199d6150ac24ae55d49cb9c00acf2c4c358f90 --- /dev/null +++ b/bin/templates/docker-compose.yml @@ -0,0 +1,21 @@ +version: '3.9' + +networks: + net: + driver: bridge + +services: + server: + image: ghcr.io/chroma-core/chroma:${ChromaVersion} + volumes: + - index_data:/index_data + ports: + - 8000:8000 + networks: + - net + +volumes: + index_data: + driver: local + backups: + driver: local diff --git a/bin/test-package.sh b/bin/test-package.sh new file mode 100755 index 0000000000000000000000000000000000000000..e1be700b43ae698011e3b20f23ce7795f9ccc76b --- /dev/null +++ b/bin/test-package.sh @@ -0,0 +1,24 @@ +#!/bin/bash + +# Verify PIP tarball +tarball=$(readlink -f $1) +if [ -f "$tarball" ]; then + echo "Testing PIP package from tarball: $tarball" +else + echo "Could not find PIP package: $tarball" +fi + +# Create temporary project dir +dir=$(mktemp -d) + +echo "Building python project dir at $dir ..." + +cd $dir + +python3 -m venv venv + +source venv/bin/activate + +pip install $tarball + +python -c "import chromadb; api = chromadb.Client(); print(api.heartbeat())" diff --git a/bin/test-remote b/bin/test-remote new file mode 100755 index 0000000000000000000000000000000000000000..9997bafdcddbd285f273404a197ec7370b78803e --- /dev/null +++ b/bin/test-remote @@ -0,0 +1,16 @@ +#!/usr/bin/env bash + +set -e + +# Assert first argument is present +if [ -z "$1" ]; then + echo "Usage: bin/test-remote " + exit 1 +fi + +export CHROMA_INTEGRATION_TEST_ONLY=1 +export CHROMA_SERVER_HOST=$1 +export CHROMA_API_IMPL=chromadb.api.fastapi.FastAPI +export CHROMA_SERVER_HTTP_PORT=8000 + +python -m pytest diff --git a/bin/test.py b/bin/test.py new file mode 100644 index 0000000000000000000000000000000000000000..61607b99146f24bd646adec0c6a911cae668034e --- /dev/null +++ b/bin/test.py @@ -0,0 +1,7 @@ +# Sanity check script to ensure that the Chroma client can connect +# and is capable of recieving data. +import chromadb + +# run in in-memory mode +chroma_api = chromadb.Client() +print(chroma_api.heartbeat()) diff --git a/bin/version b/bin/version new file mode 100755 index 0000000000000000000000000000000000000000..41eb44c3d925b92a730bd5f46c09f794124b73b7 --- /dev/null +++ b/bin/version @@ -0,0 +1,8 @@ +#!/usr/bin/env bash +export VERSION=`python -m setuptools_scm` + +if [[ -n `git status --porcelain` ]]; then + VERSION=$VERSION-dirty +fi + +echo $VERSION diff --git a/bin/windows_upgrade_sqlite.py b/bin/windows_upgrade_sqlite.py new file mode 100644 index 0000000000000000000000000000000000000000..1b27011cd128609135f4a0b2fb7b33c5989f569e --- /dev/null +++ b/bin/windows_upgrade_sqlite.py @@ -0,0 +1,20 @@ +import requests +import zipfile +import io +import os +import sys +import shutil + +# Used by Github Action runners to upgrade sqlite version to 3.42.0 +DLL_URL = "https://www.sqlite.org/2023/sqlite-dll-win64-x64-3420000.zip" + +if __name__ == "__main__": + # Download and extract the DLL + r = requests.get(DLL_URL) + z = zipfile.ZipFile(io.BytesIO(r.content)) + z.extractall(".") + # Print current Python path + exec_path = os.path.dirname(sys.executable) + dlls_path = os.path.join(exec_path, "DLLs") + # Copy the DLL to the Python DLLs folder + shutil.copy("sqlite3.dll", dlls_path) diff --git a/chromadb/__init__.py b/chromadb/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..142ab78a05fc713c6b5a634d4808a2c13ac5e711 --- /dev/null +++ b/chromadb/__init__.py @@ -0,0 +1,257 @@ +from typing import Dict, Optional +import logging +from chromadb.api.client import Client as ClientCreator +from chromadb.api.client import AdminClient as AdminClientCreator +from chromadb.auth.token import TokenTransportHeader +import chromadb.config +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Settings +from chromadb.api import AdminAPI, ClientAPI +from chromadb.api.models.Collection import Collection +from chromadb.api.types import ( + CollectionMetadata, + Documents, + EmbeddingFunction, + Embeddings, + IDs, + Include, + Metadata, + Where, + QueryResult, + GetResult, + WhereDocument, + UpdateCollectionMetadata, +) + +# Re-export types from chromadb.types +__all__ = [ + "Collection", + "Metadata", + "Where", + "WhereDocument", + "Documents", + "IDs", + "Embeddings", + "EmbeddingFunction", + "Include", + "CollectionMetadata", + "UpdateCollectionMetadata", + "QueryResult", + "GetResult", +] + +logger = logging.getLogger(__name__) + +__settings = Settings() + +__version__ = "0.4.22" + +# Workaround to deal with Colab's old sqlite3 version +try: + import google.colab # noqa: F401 + + IN_COLAB = True +except ImportError: + IN_COLAB = False + +is_client = False +try: + from chromadb.is_thin_client import is_thin_client + + is_client = is_thin_client +except ImportError: + is_client = False + +if not is_client: + import sqlite3 + + if sqlite3.sqlite_version_info < (3, 35, 0): + if IN_COLAB: + # In Colab, hotswap to pysqlite-binary if it's too old + import subprocess + import sys + + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "pysqlite3-binary"] + ) + __import__("pysqlite3") + sys.modules["sqlite3"] = sys.modules.pop("pysqlite3") + else: + raise RuntimeError( + "\033[91mYour system has an unsupported version of sqlite3. Chroma \ + requires sqlite3 >= 3.35.0.\033[0m\n" + "\033[94mPlease visit \ + https://docs.trychroma.com/troubleshooting#sqlite to learn how \ + to upgrade.\033[0m" + ) + + +def configure(**kwargs) -> None: # type: ignore + """Override Chroma's default settings, environment variables or .env files""" + global __settings + __settings = chromadb.config.Settings(**kwargs) + + +def get_settings() -> Settings: + return __settings + + +def EphemeralClient( + settings: Optional[Settings] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, +) -> ClientAPI: + """ + Creates an in-memory instance of Chroma. This is useful for testing and + development, but not recommended for production use. + + Args: + tenant: The tenant to use for this client. Defaults to the default tenant. + database: The database to use for this client. Defaults to the default database. + """ + if settings is None: + settings = Settings() + settings.is_persistent = False + + return ClientCreator(settings=settings, tenant=tenant, database=database) + + +def PersistentClient( + path: str = "./chroma", + settings: Optional[Settings] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, +) -> ClientAPI: + """ + Creates a persistent instance of Chroma that saves to disk. This is useful for + testing and development, but not recommended for production use. + + Args: + path: The directory to save Chroma's data to. Defaults to "./chroma". + tenant: The tenant to use for this client. Defaults to the default tenant. + database: The database to use for this client. Defaults to the default database. + """ + if settings is None: + settings = Settings() + settings.persist_directory = path + settings.is_persistent = True + + return ClientCreator(tenant=tenant, database=database, settings=settings) + + +def HttpClient( + host: str = "localhost", + port: str = "8000", + ssl: bool = False, + headers: Optional[Dict[str, str]] = None, + settings: Optional[Settings] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, +) -> ClientAPI: + """ + Creates a client that connects to a remote Chroma server. This supports + many clients connecting to the same server, and is the recommended way to + use Chroma in production. + + Args: + host: The hostname of the Chroma server. Defaults to "localhost". + port: The port of the Chroma server. Defaults to "8000". + ssl: Whether to use SSL to connect to the Chroma server. Defaults to False. + headers: A dictionary of headers to send to the Chroma server. Defaults to {}. + settings: A dictionary of settings to communicate with the chroma server. + tenant: The tenant to use for this client. Defaults to the default tenant. + database: The database to use for this client. Defaults to the default database. + """ + + if settings is None: + settings = Settings() + + settings.chroma_api_impl = "chromadb.api.fastapi.FastAPI" + if settings.chroma_server_host and settings.chroma_server_host != host: + raise ValueError( + f"Chroma server host provided in settings[{settings.chroma_server_host}] is different to the one provided in HttpClient: [{host}]" + ) + settings.chroma_server_host = host + if settings.chroma_server_http_port and settings.chroma_server_http_port != port: + raise ValueError( + f"Chroma server http port provided in settings[{settings.chroma_server_http_port}] is different to the one provided in HttpClient: [{port}]" + ) + settings.chroma_server_http_port = port + settings.chroma_server_ssl_enabled = ssl + settings.chroma_server_headers = headers + + return ClientCreator(tenant=tenant, database=database, settings=settings) + + +def CloudClient( + tenant: str, + database: str, + api_key: Optional[str] = None, + settings: Optional[Settings] = None, + *, # Following arguments are keyword-only, intended for testing only. + cloud_host: str = "api.trychroma.com", + cloud_port: str = "8000", + enable_ssl: bool = True, +) -> ClientAPI: + """ + Creates a client to connect to a tennant and database on the Chroma cloud. + + Args: + tenant: The tenant to use for this client. + database: The database to use for this client. + api_key: The api key to use for this client. + """ + + # If no API key is provided, try to load it from the environment variable + if api_key is None: + import os + + api_key = os.environ.get("CHROMA_API_KEY") + + # If the API key is still not provided, prompt the user + if api_key is None: + print( + "\033[93mDon't have an API key?\033[0m Get one at https://app.trychroma.com" + ) + api_key = input("Please enter your Chroma API key: ") + + if settings is None: + settings = Settings() + + settings.chroma_api_impl = "chromadb.api.fastapi.FastAPI" + settings.chroma_server_host = cloud_host + settings.chroma_server_http_port = cloud_port + # Always use SSL for cloud + settings.chroma_server_ssl_enabled = enable_ssl + + settings.chroma_client_auth_provider = "chromadb.auth.token.TokenAuthClientProvider" + settings.chroma_client_auth_credentials = api_key + settings.chroma_client_auth_token_transport_header = ( + TokenTransportHeader.X_CHROMA_TOKEN.name + ) + + return ClientCreator(tenant=tenant, database=database, settings=settings) + + +def Client( + settings: Settings = __settings, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, +) -> ClientAPI: + """ + Return a running chroma.API instance + + tenant: The tenant to use for this client. Defaults to the default tenant. + database: The database to use for this client. Defaults to the default database. + + """ + + return ClientCreator(tenant=tenant, database=database, settings=settings) + + +def AdminClient(settings: Settings = Settings()) -> AdminAPI: + """ + + Creates an admin client that can be used to create tenants and databases. + + """ + return AdminClientCreator(settings=settings) diff --git a/chromadb/api/__init__.py b/chromadb/api/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..b6d5b769afc763ac708073f3355f7e69dfdf2906 --- /dev/null +++ b/chromadb/api/__init__.py @@ -0,0 +1,596 @@ +from abc import ABC, abstractmethod +from typing import Sequence, Optional +from uuid import UUID + +from overrides import override +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT +from chromadb.api.models.Collection import Collection +from chromadb.api.types import ( + CollectionMetadata, + Documents, + Embeddable, + EmbeddingFunction, + DataLoader, + Embeddings, + IDs, + Include, + Loadable, + Metadatas, + URIs, + Where, + QueryResult, + GetResult, + WhereDocument, +) +from chromadb.config import Component, Settings +from chromadb.types import Database, Tenant +import chromadb.utils.embedding_functions as ef + + +class BaseAPI(ABC): + @abstractmethod + def heartbeat(self) -> int: + """Get the current time in nanoseconds since epoch. + Used to check if the server is alive. + + Returns: + int: The current time in nanoseconds since epoch + + """ + pass + + # + # COLLECTION METHODS + # + + @abstractmethod + def list_collections( + self, + limit: Optional[int] = None, + offset: Optional[int] = None, + ) -> Sequence[Collection]: + """List all collections. + Args: + limit: The maximum number of entries to return. Defaults to None. + offset: The number of entries to skip before returning. Defaults to None. + + Returns: + Sequence[Collection]: A list of collections + + Examples: + ```python + client.list_collections() + # [collection(name="my_collection", metadata={})] + ``` + """ + pass + + @abstractmethod + def count_collections(self) -> int: + """Count the number of collections. + + Returns: + int: The number of collections. + + Examples: + ```python + client.count_collections() + # 1 + ``` + """ + pass + + @abstractmethod + def create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + get_or_create: bool = False, + ) -> Collection: + """Create a new collection with the given name and metadata. + Args: + name: The name of the collection to create. + metadata: Optional metadata to associate with the collection. + embedding_function: Optional function to use to embed documents. + Uses the default embedding function if not provided. + get_or_create: If True, return the existing collection if it exists. + data_loader: Optional function to use to load records (documents, images, etc.) + + Returns: + Collection: The newly created collection. + + Raises: + ValueError: If the collection already exists and get_or_create is False. + ValueError: If the collection name is invalid. + + Examples: + ```python + client.create_collection("my_collection") + # collection(name="my_collection", metadata={}) + + client.create_collection("my_collection", metadata={"foo": "bar"}) + # collection(name="my_collection", metadata={"foo": "bar"}) + ``` + """ + pass + + @abstractmethod + def get_collection( + self, + name: str, + id: Optional[UUID] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + ) -> Collection: + """Get a collection with the given name. + Args: + id: The UUID of the collection to get. Id and Name are simultaneously used for lookup if provided. + name: The name of the collection to get + embedding_function: Optional function to use to embed documents. + Uses the default embedding function if not provided. + data_loader: Optional function to use to load records (documents, images, etc.) + + Returns: + Collection: The collection + + Raises: + ValueError: If the collection does not exist + + Examples: + ```python + client.get_collection("my_collection") + # collection(name="my_collection", metadata={}) + ``` + """ + pass + + @abstractmethod + def get_or_create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + ) -> Collection: + """Get or create a collection with the given name and metadata. + Args: + name: The name of the collection to get or create + metadata: Optional metadata to associate with the collection. If + the collection alredy exists, the metadata will be updated if + provided and not None. If the collection does not exist, the + new collection will be created with the provided metadata. + embedding_function: Optional function to use to embed documents + data_loader: Optional function to use to load records (documents, images, etc.) + + Returns: + The collection + + Examples: + ```python + client.get_or_create_collection("my_collection") + # collection(name="my_collection", metadata={}) + ``` + """ + pass + + def _modify( + self, + id: UUID, + new_name: Optional[str] = None, + new_metadata: Optional[CollectionMetadata] = None, + ) -> None: + """[Internal] Modify a collection by UUID. Can update the name and/or metadata. + + Args: + id: The internal UUID of the collection to modify. + new_name: The new name of the collection. + If None, the existing name will remain. Defaults to None. + new_metadata: The new metadata to associate with the collection. + Defaults to None. + """ + pass + + @abstractmethod + def delete_collection( + self, + name: str, + ) -> None: + """Delete a collection with the given name. + Args: + name: The name of the collection to delete. + + Raises: + ValueError: If the collection does not exist. + + Examples: + ```python + client.delete_collection("my_collection") + ``` + """ + pass + + # + # ITEM METHODS + # + + @abstractmethod + def _add( + self, + ids: IDs, + collection_id: UUID, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + """[Internal] Add embeddings to a collection specified by UUID. + If (some) ids already exist, only the new embeddings will be added. + + Args: + ids: The ids to associate with the embeddings. + collection_id: The UUID of the collection to add the embeddings to. + embedding: The sequence of embeddings to add. + metadata: The metadata to associate with the embeddings. Defaults to None. + documents: The documents to associate with the embeddings. Defaults to None. + uris: URIs of data sources for each embedding. Defaults to None. + + Returns: + True if the embeddings were added successfully. + """ + pass + + @abstractmethod + def _update( + self, + collection_id: UUID, + ids: IDs, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + """[Internal] Update entries in a collection specified by UUID. + + Args: + collection_id: The UUID of the collection to update the embeddings in. + ids: The IDs of the entries to update. + embeddings: The sequence of embeddings to update. Defaults to None. + metadatas: The metadata to associate with the embeddings. Defaults to None. + documents: The documents to associate with the embeddings. Defaults to None. + uris: URIs of data sources for each embedding. Defaults to None. + Returns: + True if the embeddings were updated successfully. + """ + pass + + @abstractmethod + def _upsert( + self, + collection_id: UUID, + ids: IDs, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + """[Internal] Add or update entries in the a collection specified by UUID. + If an entry with the same id already exists, it will be updated, + otherwise it will be added. + + Args: + collection_id: The collection to add the embeddings to + ids: The ids to associate with the embeddings. Defaults to None. + embeddings: The sequence of embeddings to add + metadatas: The metadata to associate with the embeddings. Defaults to None. + documents: The documents to associate with the embeddings. Defaults to None. + uris: URIs of data sources for each embedding. Defaults to None. + """ + pass + + @abstractmethod + def _count(self, collection_id: UUID) -> int: + """[Internal] Returns the number of entries in a collection specified by UUID. + + Args: + collection_id: The UUID of the collection to count the embeddings in. + + Returns: + int: The number of embeddings in the collection + + """ + pass + + @abstractmethod + def _peek(self, collection_id: UUID, n: int = 10) -> GetResult: + """[Internal] Returns the first n entries in a collection specified by UUID. + + Args: + collection_id: The UUID of the collection to peek into. + n: The number of entries to peek. Defaults to 10. + + Returns: + GetResult: The first n entries in the collection. + + """ + + pass + + @abstractmethod + def _get( + self, + collection_id: UUID, + ids: Optional[IDs] = None, + where: Optional[Where] = {}, + sort: Optional[str] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + page: Optional[int] = None, + page_size: Optional[int] = None, + where_document: Optional[WhereDocument] = {}, + include: Include = ["embeddings", "metadatas", "documents"], + ) -> GetResult: + """[Internal] Returns entries from a collection specified by UUID. + + Args: + ids: The IDs of the entries to get. Defaults to None. + where: Conditional filtering on metadata. Defaults to {}. + sort: The column to sort the entries by. Defaults to None. + limit: The maximum number of entries to return. Defaults to None. + offset: The number of entries to skip before returning. Defaults to None. + page: The page number to return. Defaults to None. + page_size: The number of entries to return per page. Defaults to None. + where_document: Conditional filtering on documents. Defaults to {}. + include: The fields to include in the response. + Defaults to ["embeddings", "metadatas", "documents"]. + Returns: + GetResult: The entries in the collection that match the query. + + """ + pass + + @abstractmethod + def _delete( + self, + collection_id: UUID, + ids: Optional[IDs], + where: Optional[Where] = {}, + where_document: Optional[WhereDocument] = {}, + ) -> IDs: + """[Internal] Deletes entries from a collection specified by UUID. + + Args: + collection_id: The UUID of the collection to delete the entries from. + ids: The IDs of the entries to delete. Defaults to None. + where: Conditional filtering on metadata. Defaults to {}. + where_document: Conditional filtering on documents. Defaults to {}. + + Returns: + IDs: The list of IDs of the entries that were deleted. + """ + pass + + @abstractmethod + def _query( + self, + collection_id: UUID, + query_embeddings: Embeddings, + n_results: int = 10, + where: Where = {}, + where_document: WhereDocument = {}, + include: Include = ["embeddings", "metadatas", "documents", "distances"], + ) -> QueryResult: + """[Internal] Performs a nearest neighbors query on a collection specified by UUID. + + Args: + collection_id: The UUID of the collection to query. + query_embeddings: The embeddings to use as the query. + n_results: The number of results to return. Defaults to 10. + where: Conditional filtering on metadata. Defaults to {}. + where_document: Conditional filtering on documents. Defaults to {}. + include: The fields to include in the response. + Defaults to ["embeddings", "metadatas", "documents", "distances"]. + + Returns: + QueryResult: The results of the query. + """ + pass + + @abstractmethod + def reset(self) -> bool: + """Resets the database. This will delete all collections and entries. + + Returns: + bool: True if the database was reset successfully. + """ + pass + + @abstractmethod + def get_version(self) -> str: + """Get the version of Chroma. + + Returns: + str: The version of Chroma + + """ + pass + + @abstractmethod + def get_settings(self) -> Settings: + """Get the settings used to initialize. + + Returns: + Settings: The settings used to initialize. + + """ + pass + + @property + @abstractmethod + def max_batch_size(self) -> int: + """Return the maximum number of records that can be submitted in a single call + to submit_embeddings.""" + pass + + +class ClientAPI(BaseAPI, ABC): + tenant: str + database: str + + @abstractmethod + def set_tenant(self, tenant: str, database: str = DEFAULT_DATABASE) -> None: + """Set the tenant and database for the client. Raises an error if the tenant or + database does not exist. + + Args: + tenant: The tenant to set. + database: The database to set. + + """ + pass + + @abstractmethod + def set_database(self, database: str) -> None: + """Set the database for the client. Raises an error if the database does not exist. + + Args: + database: The database to set. + + """ + pass + + @staticmethod + @abstractmethod + def clear_system_cache() -> None: + """Clear the system cache so that new systems can be created for an existing path. + This should only be used for testing purposes.""" + pass + + +class AdminAPI(ABC): + @abstractmethod + def create_database(self, name: str, tenant: str = DEFAULT_TENANT) -> None: + """Create a new database. Raises an error if the database already exists. + + Args: + database: The name of the database to create. + + """ + pass + + @abstractmethod + def get_database(self, name: str, tenant: str = DEFAULT_TENANT) -> Database: + """Get a database. Raises an error if the database does not exist. + + Args: + database: The name of the database to get. + tenant: The tenant of the database to get. + + """ + pass + + @abstractmethod + def create_tenant(self, name: str) -> None: + """Create a new tenant. Raises an error if the tenant already exists. + + Args: + tenant: The name of the tenant to create. + + """ + pass + + @abstractmethod + def get_tenant(self, name: str) -> Tenant: + """Get a tenant. Raises an error if the tenant does not exist. + + Args: + tenant: The name of the tenant to get. + + """ + pass + + +class ServerAPI(BaseAPI, AdminAPI, Component): + """An API instance that extends the relevant Base API methods by passing + in a tenant and database. This is the root component of the Chroma System""" + + @abstractmethod + @override + def list_collections( + self, + limit: Optional[int] = None, + offset: Optional[int] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Sequence[Collection]: + pass + + @abstractmethod + @override + def count_collections( + self, tenant: str = DEFAULT_TENANT, database: str = DEFAULT_DATABASE + ) -> int: + pass + + @abstractmethod + @override + def create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + get_or_create: bool = False, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + pass + + @abstractmethod + @override + def get_collection( + self, + name: str, + id: Optional[UUID] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + pass + + @abstractmethod + @override + def get_or_create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + pass + + @abstractmethod + @override + def delete_collection( + self, + name: str, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> None: + pass diff --git a/chromadb/api/client.py b/chromadb/api/client.py new file mode 100644 index 0000000000000000000000000000000000000000..ba797677e46186d0fd7535f8b01dec8c94d02a8d --- /dev/null +++ b/chromadb/api/client.py @@ -0,0 +1,496 @@ +from typing import ClassVar, Dict, Optional, Sequence +from uuid import UUID +import uuid + +from overrides import override +import requests +from chromadb.api import AdminAPI, ClientAPI, ServerAPI +from chromadb.api.types import ( + CollectionMetadata, + DataLoader, + Documents, + Embeddable, + EmbeddingFunction, + Embeddings, + GetResult, + IDs, + Include, + Loadable, + Metadatas, + QueryResult, + URIs, +) +from chromadb.config import Settings, System +from chromadb.config import DEFAULT_TENANT, DEFAULT_DATABASE +from chromadb.api.models.Collection import Collection +from chromadb.errors import ChromaError +from chromadb.telemetry.product import ProductTelemetryClient +from chromadb.telemetry.product.events import ClientStartEvent +from chromadb.types import Database, Tenant, Where, WhereDocument +import chromadb.utils.embedding_functions as ef + + +class SharedSystemClient: + _identifer_to_system: ClassVar[Dict[str, System]] = {} + _identifier: str + + # region Initialization + def __init__( + self, + settings: Settings = Settings(), + ) -> None: + self._identifier = SharedSystemClient._get_identifier_from_settings(settings) + SharedSystemClient._create_system_if_not_exists(self._identifier, settings) + + @classmethod + def _create_system_if_not_exists( + cls, identifier: str, settings: Settings + ) -> System: + if identifier not in cls._identifer_to_system: + new_system = System(settings) + cls._identifer_to_system[identifier] = new_system + + new_system.instance(ProductTelemetryClient) + new_system.instance(ServerAPI) + + new_system.start() + else: + previous_system = cls._identifer_to_system[identifier] + + # For now, the settings must match + if previous_system.settings != settings: + raise ValueError( + f"An instance of Chroma already exists for {identifier} with different settings" + ) + + return cls._identifer_to_system[identifier] + + @staticmethod + def _get_identifier_from_settings(settings: Settings) -> str: + identifier = "" + api_impl = settings.chroma_api_impl + + if api_impl is None: + raise ValueError("Chroma API implementation must be set in settings") + elif api_impl == "chromadb.api.segment.SegmentAPI": + if settings.is_persistent: + identifier = settings.persist_directory + else: + identifier = ( + "ephemeral" # TODO: support pathing and multiple ephemeral clients + ) + elif api_impl == "chromadb.api.fastapi.FastAPI": + # FastAPI clients can all use unique system identifiers since their configurations can be independent, e.g. different auth tokens + identifier = str(uuid.uuid4()) + else: + raise ValueError(f"Unsupported Chroma API implementation {api_impl}") + + return identifier + + @staticmethod + def _populate_data_from_system(system: System) -> str: + identifier = SharedSystemClient._get_identifier_from_settings(system.settings) + SharedSystemClient._identifer_to_system[identifier] = system + return identifier + + @classmethod + def from_system(cls, system: System) -> "SharedSystemClient": + """Create a client from an existing system. This is useful for testing and debugging.""" + + SharedSystemClient._populate_data_from_system(system) + instance = cls(system.settings) + return instance + + @staticmethod + def clear_system_cache() -> None: + SharedSystemClient._identifer_to_system = {} + + @property + def _system(self) -> System: + return SharedSystemClient._identifer_to_system[self._identifier] + + # endregion + + +class Client(SharedSystemClient, ClientAPI): + """A client for Chroma. This is the main entrypoint for interacting with Chroma. + A client internally stores its tenant and database and proxies calls to a + Server API instance of Chroma. It treats the Server API and corresponding System + as a singleton, so multiple clients connecting to the same resource will share the + same API instance. + + Client implementations should be implement their own API-caching strategies. + """ + + tenant: str = DEFAULT_TENANT + database: str = DEFAULT_DATABASE + + _server: ServerAPI + # An internal admin client for verifying that databases and tenants exist + _admin_client: AdminAPI + + # region Initialization + def __init__( + self, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + settings: Settings = Settings(), + ) -> None: + super().__init__(settings=settings) + self.tenant = tenant + self.database = database + # Create an admin client for verifying that databases and tenants exist + self._admin_client = AdminClient.from_system(self._system) + self._validate_tenant_database(tenant=tenant, database=database) + + # Get the root system component we want to interact with + self._server = self._system.instance(ServerAPI) + + # Submit event for a client start + telemetry_client = self._system.instance(ProductTelemetryClient) + telemetry_client.capture(ClientStartEvent()) + + @classmethod + @override + def from_system( + cls, + system: System, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> "Client": + SharedSystemClient._populate_data_from_system(system) + instance = cls(tenant=tenant, database=database, settings=system.settings) + return instance + + # endregion + + # region BaseAPI Methods + # Note - we could do this in less verbose ways, but they break type checking + @override + def heartbeat(self) -> int: + return self._server.heartbeat() + + @override + def list_collections( + self, limit: Optional[int] = None, offset: Optional[int] = None + ) -> Sequence[Collection]: + return self._server.list_collections( + limit, offset, tenant=self.tenant, database=self.database + ) + + @override + def count_collections(self) -> int: + return self._server.count_collections( + tenant=self.tenant, database=self.database + ) + + @override + def create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + get_or_create: bool = False, + ) -> Collection: + return self._server.create_collection( + name=name, + metadata=metadata, + embedding_function=embedding_function, + data_loader=data_loader, + tenant=self.tenant, + database=self.database, + get_or_create=get_or_create, + ) + + @override + def get_collection( + self, + name: str, + id: Optional[UUID] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + ) -> Collection: + return self._server.get_collection( + id=id, + name=name, + embedding_function=embedding_function, + data_loader=data_loader, + tenant=self.tenant, + database=self.database, + ) + + @override + def get_or_create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + ) -> Collection: + return self._server.get_or_create_collection( + name=name, + metadata=metadata, + embedding_function=embedding_function, + data_loader=data_loader, + tenant=self.tenant, + database=self.database, + ) + + @override + def _modify( + self, + id: UUID, + new_name: Optional[str] = None, + new_metadata: Optional[CollectionMetadata] = None, + ) -> None: + return self._server._modify( + id=id, + new_name=new_name, + new_metadata=new_metadata, + ) + + @override + def delete_collection( + self, + name: str, + ) -> None: + return self._server.delete_collection( + name=name, + tenant=self.tenant, + database=self.database, + ) + + # + # ITEM METHODS + # + + @override + def _add( + self, + ids: IDs, + collection_id: UUID, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + return self._server._add( + ids=ids, + collection_id=collection_id, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ) + + @override + def _update( + self, + collection_id: UUID, + ids: IDs, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + return self._server._update( + collection_id=collection_id, + ids=ids, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ) + + @override + def _upsert( + self, + collection_id: UUID, + ids: IDs, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + return self._server._upsert( + collection_id=collection_id, + ids=ids, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ) + + @override + def _count(self, collection_id: UUID) -> int: + return self._server._count( + collection_id=collection_id, + ) + + @override + def _peek(self, collection_id: UUID, n: int = 10) -> GetResult: + return self._server._peek( + collection_id=collection_id, + n=n, + ) + + @override + def _get( + self, + collection_id: UUID, + ids: Optional[IDs] = None, + where: Optional[Where] = {}, + sort: Optional[str] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + page: Optional[int] = None, + page_size: Optional[int] = None, + where_document: Optional[WhereDocument] = {}, + include: Include = ["embeddings", "metadatas", "documents"], + ) -> GetResult: + return self._server._get( + collection_id=collection_id, + ids=ids, + where=where, + sort=sort, + limit=limit, + offset=offset, + page=page, + page_size=page_size, + where_document=where_document, + include=include, + ) + + def _delete( + self, + collection_id: UUID, + ids: Optional[IDs], + where: Optional[Where] = {}, + where_document: Optional[WhereDocument] = {}, + ) -> IDs: + return self._server._delete( + collection_id=collection_id, + ids=ids, + where=where, + where_document=where_document, + ) + + @override + def _query( + self, + collection_id: UUID, + query_embeddings: Embeddings, + n_results: int = 10, + where: Where = {}, + where_document: WhereDocument = {}, + include: Include = ["embeddings", "metadatas", "documents", "distances"], + ) -> QueryResult: + return self._server._query( + collection_id=collection_id, + query_embeddings=query_embeddings, + n_results=n_results, + where=where, + where_document=where_document, + include=include, + ) + + @override + def reset(self) -> bool: + return self._server.reset() + + @override + def get_version(self) -> str: + return self._server.get_version() + + @override + def get_settings(self) -> Settings: + return self._server.get_settings() + + @property + @override + def max_batch_size(self) -> int: + return self._server.max_batch_size + + # endregion + + # region ClientAPI Methods + + @override + def set_tenant(self, tenant: str, database: str = DEFAULT_DATABASE) -> None: + self._validate_tenant_database(tenant=tenant, database=database) + self.tenant = tenant + self.database = database + + @override + def set_database(self, database: str) -> None: + self._validate_tenant_database(tenant=self.tenant, database=database) + self.database = database + + def _validate_tenant_database(self, tenant: str, database: str) -> None: + try: + self._admin_client.get_tenant(name=tenant) + except requests.exceptions.ConnectionError: + raise ValueError( + "Could not connect to a Chroma server. Are you sure it is running?" + ) + # Propagate ChromaErrors + except ChromaError as e: + raise e + except Exception: + raise ValueError( + f"Could not connect to tenant {tenant}. Are you sure it exists?" + ) + + try: + self._admin_client.get_database(name=database, tenant=tenant) + except requests.exceptions.ConnectionError: + raise ValueError( + "Could not connect to a Chroma server. Are you sure it is running?" + ) + except Exception: + raise ValueError( + f"Could not connect to database {database} for tenant {tenant}. Are you sure it exists?" + ) + + # endregion + + +class AdminClient(SharedSystemClient, AdminAPI): + _server: ServerAPI + + def __init__(self, settings: Settings = Settings()) -> None: + super().__init__(settings) + self._server = self._system.instance(ServerAPI) + + @override + def create_database(self, name: str, tenant: str = DEFAULT_TENANT) -> None: + return self._server.create_database(name=name, tenant=tenant) + + @override + def get_database(self, name: str, tenant: str = DEFAULT_TENANT) -> Database: + return self._server.get_database(name=name, tenant=tenant) + + @override + def create_tenant(self, name: str) -> None: + return self._server.create_tenant(name=name) + + @override + def get_tenant(self, name: str) -> Tenant: + return self._server.get_tenant(name=name) + + @classmethod + @override + def from_system( + cls, + system: System, + ) -> "AdminClient": + SharedSystemClient._populate_data_from_system(system) + instance = cls(settings=system.settings) + return instance diff --git a/chromadb/api/fastapi.py b/chromadb/api/fastapi.py new file mode 100644 index 0000000000000000000000000000000000000000..1ee7a45af54145956b20ad73a2e1a9c0b5b97e5c --- /dev/null +++ b/chromadb/api/fastapi.py @@ -0,0 +1,654 @@ +import json +import logging +from typing import Optional, cast, Tuple +from typing import Sequence +from uuid import UUID + +import requests +from overrides import override + +import chromadb.errors as errors +from chromadb.types import Database, Tenant +import chromadb.utils.embedding_functions as ef +from chromadb.api import ServerAPI +from chromadb.api.models.Collection import Collection +from chromadb.api.types import ( + DataLoader, + Documents, + Embeddable, + Embeddings, + EmbeddingFunction, + IDs, + Include, + Loadable, + Metadatas, + URIs, + Where, + WhereDocument, + GetResult, + QueryResult, + CollectionMetadata, + validate_batch, +) +from chromadb.auth import ( + ClientAuthProvider, +) +from chromadb.auth.providers import RequestsClientAuthProtocolAdapter +from chromadb.auth.registry import resolve_provider +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Settings, System +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.telemetry.product import ProductTelemetryClient +from urllib.parse import urlparse, urlunparse, quote + +logger = logging.getLogger(__name__) + + +class FastAPI(ServerAPI): + _settings: Settings + _max_batch_size: int = -1 + + @staticmethod + def _validate_host(host: str) -> None: + parsed = urlparse(host) + if "/" in host and parsed.scheme not in {"http", "https"}: + raise ValueError( + "Invalid URL. " f"Unrecognized protocol - {parsed.scheme}." + ) + if "/" in host and (not host.startswith("http")): + raise ValueError( + "Invalid URL. " + "Seems that you are trying to pass URL as a host but without \ + specifying the protocol. " + "Please add http:// or https:// to the host." + ) + + @staticmethod + def resolve_url( + chroma_server_host: str, + chroma_server_ssl_enabled: Optional[bool] = False, + default_api_path: Optional[str] = "", + chroma_server_http_port: Optional[int] = 8000, + ) -> str: + _skip_port = False + _chroma_server_host = chroma_server_host + FastAPI._validate_host(_chroma_server_host) + if _chroma_server_host.startswith("http"): + logger.debug("Skipping port as the user is passing a full URL") + _skip_port = True + parsed = urlparse(_chroma_server_host) + + scheme = "https" if chroma_server_ssl_enabled else parsed.scheme or "http" + net_loc = parsed.netloc or parsed.hostname or chroma_server_host + port = ( + ":" + str(parsed.port or chroma_server_http_port) if not _skip_port else "" + ) + path = parsed.path or default_api_path + + if not path or path == net_loc: + path = default_api_path if default_api_path else "" + if not path.endswith(default_api_path or ""): + path = path + default_api_path if default_api_path else "" + full_url = urlunparse( + (scheme, f"{net_loc}{port}", quote(path.replace("//", "/")), "", "", "") + ) + + return full_url + + def __init__(self, system: System): + super().__init__(system) + system.settings.require("chroma_server_host") + system.settings.require("chroma_server_http_port") + + self._opentelemetry_client = self.require(OpenTelemetryClient) + self._product_telemetry_client = self.require(ProductTelemetryClient) + self._settings = system.settings + + self._api_url = FastAPI.resolve_url( + chroma_server_host=str(system.settings.chroma_server_host), + chroma_server_http_port=int(str(system.settings.chroma_server_http_port)), + chroma_server_ssl_enabled=system.settings.chroma_server_ssl_enabled, + default_api_path=system.settings.chroma_server_api_default_path, + ) + + self._header = system.settings.chroma_server_headers + if ( + system.settings.chroma_client_auth_provider + and system.settings.chroma_client_auth_protocol_adapter + ): + self._auth_provider = self.require( + resolve_provider( + system.settings.chroma_client_auth_provider, ClientAuthProvider + ) + ) + self._adapter = cast( + RequestsClientAuthProtocolAdapter, + system.require( + resolve_provider( + system.settings.chroma_client_auth_protocol_adapter, + RequestsClientAuthProtocolAdapter, + ) + ), + ) + self._session = self._adapter.session + else: + self._session = requests.Session() + if self._header is not None: + self._session.headers.update(self._header) + if self._settings.chroma_server_ssl_verify is not None: + self._session.verify = self._settings.chroma_server_ssl_verify + + @trace_method("FastAPI.heartbeat", OpenTelemetryGranularity.OPERATION) + @override + def heartbeat(self) -> int: + """Returns the current server time in nanoseconds to check if the server is alive""" + resp = self._session.get(self._api_url) + raise_chroma_error(resp) + return int(resp.json()["nanosecond heartbeat"]) + + @trace_method("FastAPI.create_database", OpenTelemetryGranularity.OPERATION) + @override + def create_database( + self, + name: str, + tenant: str = DEFAULT_TENANT, + ) -> None: + """Creates a database""" + resp = self._session.post( + self._api_url + "/databases", + data=json.dumps({"name": name}), + params={"tenant": tenant}, + ) + raise_chroma_error(resp) + + @trace_method("FastAPI.get_database", OpenTelemetryGranularity.OPERATION) + @override + def get_database( + self, + name: str, + tenant: str = DEFAULT_TENANT, + ) -> Database: + """Returns a database""" + resp = self._session.get( + self._api_url + "/databases/" + name, + params={"tenant": tenant}, + ) + raise_chroma_error(resp) + resp_json = resp.json() + return Database( + id=resp_json["id"], name=resp_json["name"], tenant=resp_json["tenant"] + ) + + @trace_method("FastAPI.create_tenant", OpenTelemetryGranularity.OPERATION) + @override + def create_tenant(self, name: str) -> None: + resp = self._session.post( + self._api_url + "/tenants", + data=json.dumps({"name": name}), + ) + raise_chroma_error(resp) + + @trace_method("FastAPI.get_tenant", OpenTelemetryGranularity.OPERATION) + @override + def get_tenant(self, name: str) -> Tenant: + resp = self._session.get( + self._api_url + "/tenants/" + name, + ) + raise_chroma_error(resp) + resp_json = resp.json() + return Tenant(name=resp_json["name"]) + + @trace_method("FastAPI.list_collections", OpenTelemetryGranularity.OPERATION) + @override + def list_collections( + self, + limit: Optional[int] = None, + offset: Optional[int] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Sequence[Collection]: + """Returns a list of all collections""" + resp = self._session.get( + self._api_url + "/collections", + params={ + "tenant": tenant, + "database": database, + "limit": limit, + "offset": offset, + }, + ) + raise_chroma_error(resp) + json_collections = resp.json() + collections = [] + for json_collection in json_collections: + collections.append(Collection(self, **json_collection)) + + return collections + + @trace_method("FastAPI.count_collections", OpenTelemetryGranularity.OPERATION) + @override + def count_collections( + self, tenant: str = DEFAULT_TENANT, database: str = DEFAULT_DATABASE + ) -> int: + """Returns a count of collections""" + resp = self._session.get( + self._api_url + "/count_collections", + params={"tenant": tenant, "database": database}, + ) + raise_chroma_error(resp) + return cast(int, resp.json()) + + @trace_method("FastAPI.create_collection", OpenTelemetryGranularity.OPERATION) + @override + def create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + get_or_create: bool = False, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + """Creates a collection""" + resp = self._session.post( + self._api_url + "/collections", + data=json.dumps( + { + "name": name, + "metadata": metadata, + "get_or_create": get_or_create, + } + ), + params={"tenant": tenant, "database": database}, + ) + raise_chroma_error(resp) + resp_json = resp.json() + return Collection( + client=self, + id=resp_json["id"], + name=resp_json["name"], + embedding_function=embedding_function, + data_loader=data_loader, + metadata=resp_json["metadata"], + ) + + @trace_method("FastAPI.get_collection", OpenTelemetryGranularity.OPERATION) + @override + def get_collection( + self, + name: str, + id: Optional[UUID] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + """Returns a collection""" + if (name is None and id is None) or (name is not None and id is not None): + raise ValueError("Name or id must be specified, but not both") + + _params = {"tenant": tenant, "database": database} + if id is not None: + _params["type"] = str(id) + resp = self._session.get( + self._api_url + "/collections/" + name if name else str(id), params=_params + ) + raise_chroma_error(resp) + resp_json = resp.json() + return Collection( + client=self, + name=resp_json["name"], + id=resp_json["id"], + embedding_function=embedding_function, + data_loader=data_loader, + metadata=resp_json["metadata"], + ) + + @trace_method( + "FastAPI.get_or_create_collection", OpenTelemetryGranularity.OPERATION + ) + @override + def get_or_create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + return cast( + Collection, + self.create_collection( + name=name, + metadata=metadata, + embedding_function=embedding_function, + data_loader=data_loader, + get_or_create=True, + tenant=tenant, + database=database, + ), + ) + + @trace_method("FastAPI._modify", OpenTelemetryGranularity.OPERATION) + @override + def _modify( + self, + id: UUID, + new_name: Optional[str] = None, + new_metadata: Optional[CollectionMetadata] = None, + ) -> None: + """Updates a collection""" + resp = self._session.put( + self._api_url + "/collections/" + str(id), + data=json.dumps({"new_metadata": new_metadata, "new_name": new_name}), + ) + raise_chroma_error(resp) + + @trace_method("FastAPI.delete_collection", OpenTelemetryGranularity.OPERATION) + @override + def delete_collection( + self, + name: str, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> None: + """Deletes a collection""" + resp = self._session.delete( + self._api_url + "/collections/" + name, + params={"tenant": tenant, "database": database}, + ) + raise_chroma_error(resp) + + @trace_method("FastAPI._count", OpenTelemetryGranularity.OPERATION) + @override + def _count( + self, + collection_id: UUID, + ) -> int: + """Returns the number of embeddings in the database""" + resp = self._session.get( + self._api_url + "/collections/" + str(collection_id) + "/count" + ) + raise_chroma_error(resp) + return cast(int, resp.json()) + + @trace_method("FastAPI._peek", OpenTelemetryGranularity.OPERATION) + @override + def _peek( + self, + collection_id: UUID, + n: int = 10, + ) -> GetResult: + return cast( + GetResult, + self._get( + collection_id, + limit=n, + include=["embeddings", "documents", "metadatas"], + ), + ) + + @trace_method("FastAPI._get", OpenTelemetryGranularity.OPERATION) + @override + def _get( + self, + collection_id: UUID, + ids: Optional[IDs] = None, + where: Optional[Where] = {}, + sort: Optional[str] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + page: Optional[int] = None, + page_size: Optional[int] = None, + where_document: Optional[WhereDocument] = {}, + include: Include = ["metadatas", "documents"], + ) -> GetResult: + if page and page_size: + offset = (page - 1) * page_size + limit = page_size + + resp = self._session.post( + self._api_url + "/collections/" + str(collection_id) + "/get", + data=json.dumps( + { + "ids": ids, + "where": where, + "sort": sort, + "limit": limit, + "offset": offset, + "where_document": where_document, + "include": include, + } + ), + ) + + raise_chroma_error(resp) + body = resp.json() + return GetResult( + ids=body["ids"], + embeddings=body.get("embeddings", None), + metadatas=body.get("metadatas", None), + documents=body.get("documents", None), + data=None, + uris=body.get("uris", None), + ) + + @trace_method("FastAPI._delete", OpenTelemetryGranularity.OPERATION) + @override + def _delete( + self, + collection_id: UUID, + ids: Optional[IDs] = None, + where: Optional[Where] = {}, + where_document: Optional[WhereDocument] = {}, + ) -> IDs: + """Deletes embeddings from the database""" + resp = self._session.post( + self._api_url + "/collections/" + str(collection_id) + "/delete", + data=json.dumps( + {"where": where, "ids": ids, "where_document": where_document} + ), + ) + + raise_chroma_error(resp) + return cast(IDs, resp.json()) + + @trace_method("FastAPI._submit_batch", OpenTelemetryGranularity.ALL) + def _submit_batch( + self, + batch: Tuple[ + IDs, + Optional[Embeddings], + Optional[Metadatas], + Optional[Documents], + Optional[URIs], + ], + url: str, + ) -> requests.Response: + """ + Submits a batch of embeddings to the database + """ + resp = self._session.post( + self._api_url + url, + data=json.dumps( + { + "ids": batch[0], + "embeddings": batch[1], + "metadatas": batch[2], + "documents": batch[3], + "uris": batch[4], + } + ), + ) + return resp + + @trace_method("FastAPI._add", OpenTelemetryGranularity.ALL) + @override + def _add( + self, + ids: IDs, + collection_id: UUID, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + """ + Adds a batch of embeddings to the database + - pass in column oriented data lists + """ + batch = (ids, embeddings, metadatas, documents, uris) + validate_batch(batch, {"max_batch_size": self.max_batch_size}) + resp = self._submit_batch(batch, "/collections/" + str(collection_id) + "/add") + raise_chroma_error(resp) + return True + + @trace_method("FastAPI._update", OpenTelemetryGranularity.ALL) + @override + def _update( + self, + collection_id: UUID, + ids: IDs, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + """ + Updates a batch of embeddings in the database + - pass in column oriented data lists + """ + batch = (ids, embeddings, metadatas, documents, uris) + validate_batch(batch, {"max_batch_size": self.max_batch_size}) + resp = self._submit_batch( + batch, "/collections/" + str(collection_id) + "/update" + ) + raise_chroma_error(resp) + return True + + @trace_method("FastAPI._upsert", OpenTelemetryGranularity.ALL) + @override + def _upsert( + self, + collection_id: UUID, + ids: IDs, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + """ + Upserts a batch of embeddings in the database + - pass in column oriented data lists + """ + batch = (ids, embeddings, metadatas, documents, uris) + validate_batch(batch, {"max_batch_size": self.max_batch_size}) + resp = self._submit_batch( + batch, "/collections/" + str(collection_id) + "/upsert" + ) + raise_chroma_error(resp) + return True + + @trace_method("FastAPI._query", OpenTelemetryGranularity.ALL) + @override + def _query( + self, + collection_id: UUID, + query_embeddings: Embeddings, + n_results: int = 10, + where: Optional[Where] = {}, + where_document: Optional[WhereDocument] = {}, + include: Include = ["metadatas", "documents", "distances"], + ) -> QueryResult: + """Gets the nearest neighbors of a single embedding""" + resp = self._session.post( + self._api_url + "/collections/" + str(collection_id) + "/query", + data=json.dumps( + { + "query_embeddings": query_embeddings, + "n_results": n_results, + "where": where, + "where_document": where_document, + "include": include, + } + ), + ) + + raise_chroma_error(resp) + body = resp.json() + + return QueryResult( + ids=body["ids"], + distances=body.get("distances", None), + embeddings=body.get("embeddings", None), + metadatas=body.get("metadatas", None), + documents=body.get("documents", None), + uris=body.get("uris", None), + data=None, + ) + + @trace_method("FastAPI.reset", OpenTelemetryGranularity.ALL) + @override + def reset(self) -> bool: + """Resets the database""" + resp = self._session.post(self._api_url + "/reset") + raise_chroma_error(resp) + return cast(bool, resp.json()) + + @trace_method("FastAPI.get_version", OpenTelemetryGranularity.OPERATION) + @override + def get_version(self) -> str: + """Returns the version of the server""" + resp = self._session.get(self._api_url + "/version") + raise_chroma_error(resp) + return cast(str, resp.json()) + + @override + def get_settings(self) -> Settings: + """Returns the settings of the client""" + return self._settings + + @property + @trace_method("FastAPI.max_batch_size", OpenTelemetryGranularity.OPERATION) + @override + def max_batch_size(self) -> int: + if self._max_batch_size == -1: + resp = self._session.get(self._api_url + "/pre-flight-checks") + raise_chroma_error(resp) + self._max_batch_size = cast(int, resp.json()["max_batch_size"]) + return self._max_batch_size + + +def raise_chroma_error(resp: requests.Response) -> None: + """Raises an error if the response is not ok, using a ChromaError if possible""" + if resp.ok: + return + + chroma_error = None + try: + body = resp.json() + if "error" in body: + if body["error"] in errors.error_types: + chroma_error = errors.error_types[body["error"]](body["message"]) + + except BaseException: + pass + + if chroma_error: + raise chroma_error + + try: + resp.raise_for_status() + except requests.HTTPError: + raise (Exception(resp.text)) diff --git a/chromadb/api/models/Collection.py b/chromadb/api/models/Collection.py new file mode 100644 index 0000000000000000000000000000000000000000..6b54c5a7dd50e173fdceb111215ac1abc0551f3f --- /dev/null +++ b/chromadb/api/models/Collection.py @@ -0,0 +1,633 @@ +from typing import TYPE_CHECKING, Optional, Tuple, Any, Union + +import numpy as np +from pydantic import BaseModel, PrivateAttr + +from uuid import UUID +import chromadb.utils.embedding_functions as ef + +from chromadb.api.types import ( + URI, + CollectionMetadata, + DataLoader, + Embedding, + Embeddings, + Embeddable, + Include, + Loadable, + Metadata, + Metadatas, + Document, + Documents, + Image, + Images, + URIs, + Where, + IDs, + EmbeddingFunction, + GetResult, + QueryResult, + ID, + OneOrMany, + WhereDocument, + maybe_cast_one_to_many_ids, + maybe_cast_one_to_many_embedding, + maybe_cast_one_to_many_metadata, + maybe_cast_one_to_many_document, + maybe_cast_one_to_many_image, + maybe_cast_one_to_many_uri, + validate_ids, + validate_include, + validate_metadata, + validate_metadatas, + validate_where, + validate_where_document, + validate_n_results, + validate_embeddings, + validate_embedding_function, +) +import logging + +logger = logging.getLogger(__name__) + +if TYPE_CHECKING: + from chromadb.api import ServerAPI + + +class Collection(BaseModel): + name: str + id: UUID + metadata: Optional[CollectionMetadata] = None + tenant: Optional[str] = None + database: Optional[str] = None + _client: "ServerAPI" = PrivateAttr() + _embedding_function: Optional[EmbeddingFunction[Embeddable]] = PrivateAttr() + _data_loader: Optional[DataLoader[Loadable]] = PrivateAttr() + + def __init__( + self, + client: "ServerAPI", + name: str, + id: UUID, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: Optional[str] = None, + database: Optional[str] = None, + metadata: Optional[CollectionMetadata] = None, + ): + super().__init__( + name=name, metadata=metadata, id=id, tenant=tenant, database=database + ) + self._client = client + + # Check to make sure the embedding function has the right signature, as defined by the EmbeddingFunction protocol + if embedding_function is not None: + validate_embedding_function(embedding_function) + + self._embedding_function = embedding_function + self._data_loader = data_loader + + def __repr__(self) -> str: + return f"Collection(name={self.name})" + + def count(self) -> int: + """The total number of embeddings added to the database + + Returns: + int: The total number of embeddings added to the database + + """ + return self._client._count(collection_id=self.id) + + def add( + self, + ids: OneOrMany[ID], + embeddings: Optional[ + Union[ + OneOrMany[Embedding], + OneOrMany[np.ndarray], + ] + ] = None, + metadatas: Optional[OneOrMany[Metadata]] = None, + documents: Optional[OneOrMany[Document]] = None, + images: Optional[OneOrMany[Image]] = None, + uris: Optional[OneOrMany[URI]] = None, + ) -> None: + """Add embeddings to the data store. + Args: + ids: The ids of the embeddings you wish to add + embeddings: The embeddings to add. If None, embeddings will be computed based on the documents or images using the embedding_function set for the Collection. Optional. + metadatas: The metadata to associate with the embeddings. When querying, you can filter on this metadata. Optional. + documents: The documents to associate with the embeddings. Optional. + images: The images to associate with the embeddings. Optional. + uris: The uris of the images to associate with the embeddings. Optional. + + Returns: + None + + Raises: + ValueError: If you don't provide either embeddings or documents + ValueError: If the length of ids, embeddings, metadatas, or documents don't match + ValueError: If you don't provide an embedding function and don't provide embeddings + ValueError: If you provide both embeddings and documents + ValueError: If you provide an id that already exists + + """ + + ( + ids, + embeddings, + metadatas, + documents, + images, + uris, + ) = self._validate_embedding_set( + ids, embeddings, metadatas, documents, images, uris + ) + + # We need to compute the embeddings if they're not provided + if embeddings is None: + # At this point, we know that one of documents or images are provided from the validation above + if documents is not None: + embeddings = self._embed(input=documents) + elif images is not None: + embeddings = self._embed(input=images) + else: + if uris is None: + raise ValueError( + "You must provide either embeddings, documents, images, or uris." + ) + if self._data_loader is None: + raise ValueError( + "You must set a data loader on the collection if loading from URIs." + ) + embeddings = self._embed(self._data_loader(uris)) + + self._client._add(ids, self.id, embeddings, metadatas, documents, uris) + + def get( + self, + ids: Optional[OneOrMany[ID]] = None, + where: Optional[Where] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + where_document: Optional[WhereDocument] = None, + include: Include = ["metadatas", "documents"], + ) -> GetResult: + """Get embeddings and their associate data from the data store. If no ids or where filter is provided returns + all embeddings up to limit starting at offset. + + Args: + ids: The ids of the embeddings to get. Optional. + where: A Where type dict used to filter results by. E.g. `{"$and": ["color" : "red", "price": {"$gte": 4.20}]}`. Optional. + limit: The number of documents to return. Optional. + offset: The offset to start returning results from. Useful for paging results with limit. Optional. + where_document: A WhereDocument type dict used to filter by the documents. E.g. `{$contains: {"text": "hello"}}`. Optional. + include: A list of what to include in the results. Can contain `"embeddings"`, `"metadatas"`, `"documents"`. Ids are always included. Defaults to `["metadatas", "documents"]`. Optional. + + Returns: + GetResult: A GetResult object containing the results. + + """ + + valid_where = validate_where(where) if where else None + valid_where_document = ( + validate_where_document(where_document) if where_document else None + ) + valid_ids = validate_ids(maybe_cast_one_to_many_ids(ids)) if ids else None + valid_include = validate_include(include, allow_distances=False) + + if "data" in include and self._data_loader is None: + raise ValueError( + "You must set a data loader on the collection if loading from URIs." + ) + + # We need to include uris in the result from the API to load datas + if "data" in include and "uris" not in include: + valid_include.append("uris") + + get_results = self._client._get( + self.id, + valid_ids, + valid_where, + None, + limit, + offset, + where_document=valid_where_document, + include=valid_include, + ) + + if ( + "data" in include + and self._data_loader is not None + and get_results["uris"] is not None + ): + get_results["data"] = self._data_loader(get_results["uris"]) + + # Remove URIs from the result if they weren't requested + if "uris" not in include: + get_results["uris"] = None + + return get_results + + def peek(self, limit: int = 10) -> GetResult: + """Get the first few results in the database up to limit + + Args: + limit: The number of results to return. + + Returns: + GetResult: A GetResult object containing the results. + """ + return self._client._peek(self.id, limit) + + def query( + self, + query_embeddings: Optional[ + Union[ + OneOrMany[Embedding], + OneOrMany[np.ndarray], + ] + ] = None, + query_texts: Optional[OneOrMany[Document]] = None, + query_images: Optional[OneOrMany[Image]] = None, + query_uris: Optional[OneOrMany[URI]] = None, + n_results: int = 10, + where: Optional[Where] = None, + where_document: Optional[WhereDocument] = None, + include: Include = ["metadatas", "documents", "distances"], + ) -> QueryResult: + """Get the n_results nearest neighbor embeddings for provided query_embeddings or query_texts. + + Args: + query_embeddings: The embeddings to get the closes neighbors of. Optional. + query_texts: The document texts to get the closes neighbors of. Optional. + query_images: The images to get the closes neighbors of. Optional. + n_results: The number of neighbors to return for each query_embedding or query_texts. Optional. + where: A Where type dict used to filter results by. E.g. `{"$and": ["color" : "red", "price": {"$gte": 4.20}]}`. Optional. + where_document: A WhereDocument type dict used to filter by the documents. E.g. `{$contains: {"text": "hello"}}`. Optional. + include: A list of what to include in the results. Can contain `"embeddings"`, `"metadatas"`, `"documents"`, `"distances"`. Ids are always included. Defaults to `["metadatas", "documents", "distances"]`. Optional. + + Returns: + QueryResult: A QueryResult object containing the results. + + Raises: + ValueError: If you don't provide either query_embeddings, query_texts, or query_images + ValueError: If you provide both query_embeddings and query_texts + ValueError: If you provide both query_embeddings and query_images + ValueError: If you provide both query_texts and query_images + + """ + + # Users must provide only one of query_embeddings, query_texts, query_images, or query_uris + if not ( + (query_embeddings is not None) + ^ (query_texts is not None) + ^ (query_images is not None) + ^ (query_uris is not None) + ): + raise ValueError( + "You must provide one of query_embeddings, query_texts, query_images, or query_uris." + ) + + valid_where = validate_where(where) if where else {} + valid_where_document = ( + validate_where_document(where_document) if where_document else {} + ) + valid_query_embeddings = ( + validate_embeddings( + self._normalize_embeddings( + maybe_cast_one_to_many_embedding(query_embeddings) + ) + ) + if query_embeddings is not None + else None + ) + valid_query_texts = ( + maybe_cast_one_to_many_document(query_texts) + if query_texts is not None + else None + ) + valid_query_images = ( + maybe_cast_one_to_many_image(query_images) + if query_images is not None + else None + ) + valid_query_uris = ( + maybe_cast_one_to_many_uri(query_uris) if query_uris is not None else None + ) + valid_include = validate_include(include, allow_distances=True) + valid_n_results = validate_n_results(n_results) + + # If query_embeddings are not provided, we need to compute them from the inputs + if valid_query_embeddings is None: + if query_texts is not None: + valid_query_embeddings = self._embed(input=valid_query_texts) + elif query_images is not None: + valid_query_embeddings = self._embed(input=valid_query_images) + else: + if valid_query_uris is None: + raise ValueError( + "You must provide either query_embeddings, query_texts, query_images, or query_uris." + ) + if self._data_loader is None: + raise ValueError( + "You must set a data loader on the collection if loading from URIs." + ) + valid_query_embeddings = self._embed( + self._data_loader(valid_query_uris) + ) + + if "data" in include and "uris" not in include: + valid_include.append("uris") + query_results = self._client._query( + collection_id=self.id, + query_embeddings=valid_query_embeddings, + n_results=valid_n_results, + where=valid_where, + where_document=valid_where_document, + include=include, + ) + + if ( + "data" in include + and self._data_loader is not None + and query_results["uris"] is not None + ): + query_results["data"] = [ + self._data_loader(uris) for uris in query_results["uris"] + ] + + # Remove URIs from the result if they weren't requested + if "uris" not in include: + query_results["uris"] = None + + return query_results + + def modify( + self, name: Optional[str] = None, metadata: Optional[CollectionMetadata] = None + ) -> None: + """Modify the collection name or metadata + + Args: + name: The updated name for the collection. Optional. + metadata: The updated metadata for the collection. Optional. + + Returns: + None + """ + if metadata is not None: + validate_metadata(metadata) + if "hnsw:space" in metadata: + raise ValueError( + "Changing the distance function of a collection once it is created is not supported currently.") + + self._client._modify(id=self.id, new_name=name, new_metadata=metadata) + if name: + self.name = name + if metadata: + self.metadata = metadata + + def update( + self, + ids: OneOrMany[ID], + embeddings: Optional[ + Union[ + OneOrMany[Embedding], + OneOrMany[np.ndarray], + ] + ] = None, + metadatas: Optional[OneOrMany[Metadata]] = None, + documents: Optional[OneOrMany[Document]] = None, + images: Optional[OneOrMany[Image]] = None, + uris: Optional[OneOrMany[URI]] = None, + ) -> None: + """Update the embeddings, metadatas or documents for provided ids. + + Args: + ids: The ids of the embeddings to update + embeddings: The embeddings to update. If None, embeddings will be computed based on the documents or images using the embedding_function set for the Collection. Optional. + metadatas: The metadata to associate with the embeddings. When querying, you can filter on this metadata. Optional. + documents: The documents to associate with the embeddings. Optional. + images: The images to associate with the embeddings. Optional. + Returns: + None + """ + + ( + ids, + embeddings, + metadatas, + documents, + images, + uris, + ) = self._validate_embedding_set( + ids, + embeddings, + metadatas, + documents, + images, + uris, + require_embeddings_or_data=False, + ) + + if embeddings is None: + if documents is not None: + embeddings = self._embed(input=documents) + elif images is not None: + embeddings = self._embed(input=images) + + self._client._update(self.id, ids, embeddings, metadatas, documents, uris) + + def upsert( + self, + ids: OneOrMany[ID], + embeddings: Optional[ + Union[ + OneOrMany[Embedding], + OneOrMany[np.ndarray], + ] + ] = None, + metadatas: Optional[OneOrMany[Metadata]] = None, + documents: Optional[OneOrMany[Document]] = None, + images: Optional[OneOrMany[Image]] = None, + uris: Optional[OneOrMany[URI]] = None, + ) -> None: + """Update the embeddings, metadatas or documents for provided ids, or create them if they don't exist. + + Args: + ids: The ids of the embeddings to update + embeddings: The embeddings to add. If None, embeddings will be computed based on the documents using the embedding_function set for the Collection. Optional. + metadatas: The metadata to associate with the embeddings. When querying, you can filter on this metadata. Optional. + documents: The documents to associate with the embeddings. Optional. + + Returns: + None + """ + + ( + ids, + embeddings, + metadatas, + documents, + images, + uris, + ) = self._validate_embedding_set( + ids, embeddings, metadatas, documents, images, uris + ) + + if embeddings is None: + if documents is not None: + embeddings = self._embed(input=documents) + else: + embeddings = self._embed(input=images) + + self._client._upsert( + collection_id=self.id, + ids=ids, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ) + + def delete( + self, + ids: Optional[IDs] = None, + where: Optional[Where] = None, + where_document: Optional[WhereDocument] = None, + ) -> None: + """Delete the embeddings based on ids and/or a where filter + + Args: + ids: The ids of the embeddings to delete + where: A Where type dict used to filter the delection by. E.g. `{"$and": ["color" : "red", "price": {"$gte": 4.20}]}`. Optional. + where_document: A WhereDocument type dict used to filter the deletion by the document content. E.g. `{$contains: {"text": "hello"}}`. Optional. + + Returns: + None + + Raises: + ValueError: If you don't provide either ids, where, or where_document + """ + ids = validate_ids(maybe_cast_one_to_many_ids(ids)) if ids else None + where = validate_where(where) if where else None + where_document = ( + validate_where_document(where_document) if where_document else None + ) + + self._client._delete(self.id, ids, where, where_document) + + def _validate_embedding_set( + self, + ids: OneOrMany[ID], + embeddings: Optional[ + Union[ + OneOrMany[Embedding], + OneOrMany[np.ndarray], + ] + ], + metadatas: Optional[OneOrMany[Metadata]], + documents: Optional[OneOrMany[Document]], + images: Optional[OneOrMany[Image]] = None, + uris: Optional[OneOrMany[URI]] = None, + require_embeddings_or_data: bool = True, + ) -> Tuple[ + IDs, + Optional[Embeddings], + Optional[Metadatas], + Optional[Documents], + Optional[Images], + Optional[URIs], + ]: + valid_ids = validate_ids(maybe_cast_one_to_many_ids(ids)) + valid_embeddings = ( + validate_embeddings( + self._normalize_embeddings(maybe_cast_one_to_many_embedding(embeddings)) + ) + if embeddings is not None + else None + ) + valid_metadatas = ( + validate_metadatas(maybe_cast_one_to_many_metadata(metadatas)) + if metadatas is not None + else None + ) + valid_documents = ( + maybe_cast_one_to_many_document(documents) + if documents is not None + else None + ) + valid_images = ( + maybe_cast_one_to_many_image(images) if images is not None else None + ) + + valid_uris = maybe_cast_one_to_many_uri(uris) if uris is not None else None + + # Check that one of embeddings or ducuments or images is provided + if require_embeddings_or_data: + if ( + valid_embeddings is None + and valid_documents is None + and valid_images is None + and valid_uris is None + ): + raise ValueError( + "You must provide embeddings, documents, images, or uris." + ) + + # Only one of documents or images can be provided + if valid_documents is not None and valid_images is not None: + raise ValueError("You can only provide documents or images, not both.") + + # Check that, if they're provided, the lengths of the arrays match the length of ids + if valid_embeddings is not None and len(valid_embeddings) != len(valid_ids): + raise ValueError( + f"Number of embeddings {len(valid_embeddings)} must match number of ids {len(valid_ids)}" + ) + if valid_metadatas is not None and len(valid_metadatas) != len(valid_ids): + raise ValueError( + f"Number of metadatas {len(valid_metadatas)} must match number of ids {len(valid_ids)}" + ) + if valid_documents is not None and len(valid_documents) != len(valid_ids): + raise ValueError( + f"Number of documents {len(valid_documents)} must match number of ids {len(valid_ids)}" + ) + if valid_images is not None and len(valid_images) != len(valid_ids): + raise ValueError( + f"Number of images {len(valid_images)} must match number of ids {len(valid_ids)}" + ) + if valid_uris is not None and len(valid_uris) != len(valid_ids): + raise ValueError( + f"Number of uris {len(valid_uris)} must match number of ids {len(valid_ids)}" + ) + + return ( + valid_ids, + valid_embeddings, + valid_metadatas, + valid_documents, + valid_images, + valid_uris, + ) + + @staticmethod + def _normalize_embeddings( + embeddings: Union[ + OneOrMany[Embedding], + OneOrMany[np.ndarray], + ] + ) -> Embeddings: + if isinstance(embeddings, np.ndarray): + return embeddings.tolist() + return embeddings + + def _embed(self, input: Any) -> Embeddings: + if self._embedding_function is None: + raise ValueError( + "You must provide an embedding function to compute embeddings." + "https://docs.trychroma.com/embeddings" + ) + return self._embedding_function(input=input) diff --git a/chromadb/api/segment.py b/chromadb/api/segment.py new file mode 100644 index 0000000000000000000000000000000000000000..72df138d9bece01517a1e0f5b15959b210d03be9 --- /dev/null +++ b/chromadb/api/segment.py @@ -0,0 +1,914 @@ +from chromadb.api import ServerAPI +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Settings, System +from chromadb.db.system import SysDB +from chromadb.segment import SegmentManager, MetadataReader, VectorReader +from chromadb.telemetry.opentelemetry import ( + add_attributes_to_current_span, + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.telemetry.product import ProductTelemetryClient +from chromadb.ingest import Producer +from chromadb.api.models.Collection import Collection +from chromadb import __version__ +from chromadb.errors import InvalidDimensionException, InvalidCollectionException +import chromadb.utils.embedding_functions as ef + +from chromadb.api.types import ( + URI, + CollectionMetadata, + Embeddable, + Document, + EmbeddingFunction, + DataLoader, + IDs, + Embeddings, + Embedding, + Loadable, + Metadatas, + Documents, + URIs, + Where, + WhereDocument, + Include, + GetResult, + QueryResult, + validate_metadata, + validate_update_metadata, + validate_where, + validate_where_document, + validate_batch, +) +from chromadb.telemetry.product.events import ( + CollectionAddEvent, + CollectionDeleteEvent, + CollectionGetEvent, + CollectionUpdateEvent, + CollectionQueryEvent, + ClientCreateCollectionEvent, +) + +import chromadb.types as t + +from typing import Any, Optional, Sequence, Generator, List, cast, Set, Dict +from overrides import override +from uuid import UUID, uuid4 +import time +import logging +import re + + +logger = logging.getLogger(__name__) + + +# mimics s3 bucket requirements for naming +def check_index_name(index_name: str) -> None: + msg = ( + "Expected collection name that " + "(1) contains 3-63 characters, " + "(2) starts and ends with an alphanumeric character, " + "(3) otherwise contains only alphanumeric characters, underscores or hyphens (-), " + "(4) contains no two consecutive periods (..) and " + "(5) is not a valid IPv4 address, " + f"got {index_name}" + ) + if len(index_name) < 3 or len(index_name) > 63: + raise ValueError(msg) + if not re.match("^[a-zA-Z0-9][a-zA-Z0-9._-]*[a-zA-Z0-9]$", index_name): + raise ValueError(msg) + if ".." in index_name: + raise ValueError(msg) + if re.match("^[0-9]{1,3}\\.[0-9]{1,3}\\.[0-9]{1,3}\\.[0-9]{1,3}$", index_name): + raise ValueError(msg) + + +class SegmentAPI(ServerAPI): + """API implementation utilizing the new segment-based internal architecture""" + + _settings: Settings + _sysdb: SysDB + _manager: SegmentManager + _producer: Producer + _product_telemetry_client: ProductTelemetryClient + _opentelemetry_client: OpenTelemetryClient + _tenant_id: str + _topic_ns: str + _collection_cache: Dict[UUID, t.Collection] + + def __init__(self, system: System): + super().__init__(system) + self._settings = system.settings + self._sysdb = self.require(SysDB) + self._manager = self.require(SegmentManager) + self._product_telemetry_client = self.require(ProductTelemetryClient) + self._opentelemetry_client = self.require(OpenTelemetryClient) + self._producer = self.require(Producer) + self._collection_cache = {} + + @override + def heartbeat(self) -> int: + return int(time.time_ns()) + + @override + def create_database(self, name: str, tenant: str = DEFAULT_TENANT) -> None: + if len(name) < 3: + raise ValueError("Database name must be at least 3 characters long") + + self._sysdb.create_database( + id=uuid4(), + name=name, + tenant=tenant, + ) + + @override + def get_database(self, name: str, tenant: str = DEFAULT_TENANT) -> t.Database: + return self._sysdb.get_database(name=name, tenant=tenant) + + @override + def create_tenant(self, name: str) -> None: + if len(name) < 3: + raise ValueError("Tenant name must be at least 3 characters long") + + self._sysdb.create_tenant( + name=name, + ) + + @override + def get_tenant(self, name: str) -> t.Tenant: + return self._sysdb.get_tenant(name=name) + + # TODO: Actually fix CollectionMetadata type to remove type: ignore flags. This is + # necessary because changing the value type from `Any` to`` `Union[str, int, float]` + # causes the system to somehow convert all values to strings. + @trace_method("SegmentAPI.create_collection", OpenTelemetryGranularity.OPERATION) + @override + def create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Any] + ] = ef.DefaultEmbeddingFunction(), + data_loader: Optional[DataLoader[Loadable]] = None, + get_or_create: bool = False, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + if metadata is not None: + validate_metadata(metadata) + + # TODO: remove backwards compatibility in naming requirements + check_index_name(name) + + id = uuid4() + + coll, created = self._sysdb.create_collection( + id=id, + name=name, + metadata=metadata, + dimension=None, + get_or_create=get_or_create, + tenant=tenant, + database=database, + ) + + if created: + segments = self._manager.create_segments(coll) + for segment in segments: + self._sysdb.create_segment(segment) + + # TODO: This event doesn't capture the get_or_create case appropriately + self._product_telemetry_client.capture( + ClientCreateCollectionEvent( + collection_uuid=str(id), + embedding_function=embedding_function.__class__.__name__, + ) + ) + add_attributes_to_current_span({"collection_uuid": str(id)}) + + return Collection( + client=self, + id=coll["id"], + name=name, + metadata=coll["metadata"], # type: ignore + embedding_function=embedding_function, + data_loader=data_loader, + tenant=tenant, + database=database, + ) + + @trace_method( + "SegmentAPI.get_or_create_collection", OpenTelemetryGranularity.OPERATION + ) + @override + def get_or_create_collection( + self, + name: str, + metadata: Optional[CollectionMetadata] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + return self.create_collection( # type: ignore + name=name, + metadata=metadata, + embedding_function=embedding_function, + data_loader=data_loader, + get_or_create=True, + tenant=tenant, + database=database, + ) + + # TODO: Actually fix CollectionMetadata type to remove type: ignore flags. This is + # necessary because changing the value type from `Any` to`` `Union[str, int, float]` + # causes the system to somehow convert all values to strings + @trace_method("SegmentAPI.get_collection", OpenTelemetryGranularity.OPERATION) + @override + def get_collection( + self, + name: Optional[str] = None, + id: Optional[UUID] = None, + embedding_function: Optional[ + EmbeddingFunction[Embeddable] + ] = ef.DefaultEmbeddingFunction(), # type: ignore + data_loader: Optional[DataLoader[Loadable]] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + if id is None and name is None or (id is not None and name is not None): + raise ValueError("Name or id must be specified, but not both") + existing = self._sysdb.get_collections( + id=id, name=name, tenant=tenant, database=database + ) + + if existing: + return Collection( + client=self, + id=existing[0]["id"], + name=existing[0]["name"], + metadata=existing[0]["metadata"], # type: ignore + embedding_function=embedding_function, + data_loader=data_loader, + tenant=existing[0]["tenant"], + database=existing[0]["database"], + ) + else: + raise ValueError(f"Collection {name} does not exist.") + + @trace_method("SegmentAPI.list_collection", OpenTelemetryGranularity.OPERATION) + @override + def list_collections( + self, + limit: Optional[int] = None, + offset: Optional[int] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Sequence[Collection]: + collections = [] + db_collections = self._sysdb.get_collections( + limit=limit, offset=offset, tenant=tenant, database=database + ) + for db_collection in db_collections: + collections.append( + Collection( + client=self, + id=db_collection["id"], + name=db_collection["name"], + metadata=db_collection["metadata"], # type: ignore + tenant=db_collection["tenant"], + database=db_collection["database"], + ) + ) + return collections + + @trace_method("SegmentAPI.count_collections", OpenTelemetryGranularity.OPERATION) + @override + def count_collections( + self, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> int: + collection_count = len( + self._sysdb.get_collections(tenant=tenant, database=database) + ) + + return collection_count + + @trace_method("SegmentAPI._modify", OpenTelemetryGranularity.OPERATION) + @override + def _modify( + self, + id: UUID, + new_name: Optional[str] = None, + new_metadata: Optional[CollectionMetadata] = None, + ) -> None: + if new_name: + # backwards compatibility in naming requirements (for now) + check_index_name(new_name) + + if new_metadata: + validate_update_metadata(new_metadata) + + # TODO eventually we'll want to use OptionalArgument and Unspecified in the + # signature of `_modify` but not changing the API right now. + if new_name and new_metadata: + self._sysdb.update_collection(id, name=new_name, metadata=new_metadata) + elif new_name: + self._sysdb.update_collection(id, name=new_name) + elif new_metadata: + self._sysdb.update_collection(id, metadata=new_metadata) + + @trace_method("SegmentAPI.delete_collection", OpenTelemetryGranularity.OPERATION) + @override + def delete_collection( + self, + name: str, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> None: + existing = self._sysdb.get_collections( + name=name, tenant=tenant, database=database + ) + + if existing: + self._sysdb.delete_collection( + existing[0]["id"], tenant=tenant, database=database + ) + for s in self._manager.delete_segments(existing[0]["id"]): + self._sysdb.delete_segment(s) + if existing and existing[0]["id"] in self._collection_cache: + del self._collection_cache[existing[0]["id"]] + else: + raise ValueError(f"Collection {name} does not exist.") + + @trace_method("SegmentAPI._add", OpenTelemetryGranularity.OPERATION) + @override + def _add( + self, + ids: IDs, + collection_id: UUID, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + coll = self._get_collection(collection_id) + self._manager.hint_use_collection(collection_id, t.Operation.ADD) + validate_batch( + (ids, embeddings, metadatas, documents, uris), + {"max_batch_size": self.max_batch_size}, + ) + records_to_submit = [] + for r in _records( + t.Operation.ADD, + ids=ids, + collection_id=collection_id, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ): + self._validate_embedding_record(coll, r) + records_to_submit.append(r) + self._producer.submit_embeddings(coll["topic"], records_to_submit) + + self._product_telemetry_client.capture( + CollectionAddEvent( + collection_uuid=str(collection_id), + add_amount=len(ids), + with_metadata=len(ids) if metadatas is not None else 0, + with_documents=len(ids) if documents is not None else 0, + with_uris=len(ids) if uris is not None else 0, + ) + ) + return True + + @trace_method("SegmentAPI._update", OpenTelemetryGranularity.OPERATION) + @override + def _update( + self, + collection_id: UUID, + ids: IDs, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + coll = self._get_collection(collection_id) + self._manager.hint_use_collection(collection_id, t.Operation.UPDATE) + validate_batch( + (ids, embeddings, metadatas, documents, uris), + {"max_batch_size": self.max_batch_size}, + ) + records_to_submit = [] + for r in _records( + t.Operation.UPDATE, + ids=ids, + collection_id=collection_id, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ): + self._validate_embedding_record(coll, r) + records_to_submit.append(r) + self._producer.submit_embeddings(coll["topic"], records_to_submit) + + self._product_telemetry_client.capture( + CollectionUpdateEvent( + collection_uuid=str(collection_id), + update_amount=len(ids), + with_embeddings=len(embeddings) if embeddings else 0, + with_metadata=len(metadatas) if metadatas else 0, + with_documents=len(documents) if documents else 0, + with_uris=len(uris) if uris else 0, + ) + ) + + return True + + @trace_method("SegmentAPI._upsert", OpenTelemetryGranularity.OPERATION) + @override + def _upsert( + self, + collection_id: UUID, + ids: IDs, + embeddings: Embeddings, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, + ) -> bool: + coll = self._get_collection(collection_id) + self._manager.hint_use_collection(collection_id, t.Operation.UPSERT) + validate_batch( + (ids, embeddings, metadatas, documents, uris), + {"max_batch_size": self.max_batch_size}, + ) + records_to_submit = [] + for r in _records( + t.Operation.UPSERT, + ids=ids, + collection_id=collection_id, + embeddings=embeddings, + metadatas=metadatas, + documents=documents, + uris=uris, + ): + self._validate_embedding_record(coll, r) + records_to_submit.append(r) + self._producer.submit_embeddings(coll["topic"], records_to_submit) + + return True + + @trace_method("SegmentAPI._get", OpenTelemetryGranularity.OPERATION) + @override + def _get( + self, + collection_id: UUID, + ids: Optional[IDs] = None, + where: Optional[Where] = {}, + sort: Optional[str] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + page: Optional[int] = None, + page_size: Optional[int] = None, + where_document: Optional[WhereDocument] = {}, + include: Include = ["embeddings", "metadatas", "documents"], + ) -> GetResult: + add_attributes_to_current_span( + { + "collection_id": str(collection_id), + "ids_count": len(ids) if ids else 0, + } + ) + + where = validate_where(where) if where is not None and len(where) > 0 else None + where_document = ( + validate_where_document(where_document) + if where_document is not None and len(where_document) > 0 + else None + ) + + metadata_segment = self._manager.get_segment(collection_id, MetadataReader) + + if sort is not None: + raise NotImplementedError("Sorting is not yet supported") + + if page and page_size: + offset = (page - 1) * page_size + limit = page_size + + records = metadata_segment.get_metadata( + where=where, + where_document=where_document, + ids=ids, + limit=limit, + offset=offset, + ) + + if len(records) == 0: + # Nothing to return if there are no records + return GetResult( + ids=[], + embeddings=[] if "embeddings" in include else None, + metadatas=[] if "metadatas" in include else None, + documents=[] if "documents" in include else None, + uris=[] if "uris" in include else None, + data=[] if "data" in include else None, + ) + + vectors: Sequence[t.VectorEmbeddingRecord] = [] + if "embeddings" in include: + vector_ids = [r["id"] for r in records] + vector_segment = self._manager.get_segment(collection_id, VectorReader) + vectors = vector_segment.get_vectors(ids=vector_ids) + + # TODO: Fix type so we don't need to ignore + # It is possible to have a set of records, some with metadata and some without + # Same with documents + + metadatas = [r["metadata"] for r in records] + + if "documents" in include: + documents = [_doc(m) for m in metadatas] + + if "uris" in include: + uris = [_uri(m) for m in metadatas] + + ids_amount = len(ids) if ids else 0 + self._product_telemetry_client.capture( + CollectionGetEvent( + collection_uuid=str(collection_id), + ids_count=ids_amount, + limit=limit if limit else 0, + include_metadata=ids_amount if "metadatas" in include else 0, + include_documents=ids_amount if "documents" in include else 0, + include_uris=ids_amount if "uris" in include else 0, + ) + ) + + return GetResult( + ids=[r["id"] for r in records], + embeddings=[r["embedding"] for r in vectors] + if "embeddings" in include + else None, + metadatas=_clean_metadatas(metadatas) + if "metadatas" in include + else None, # type: ignore + documents=documents if "documents" in include else None, # type: ignore + uris=uris if "uris" in include else None, # type: ignore + data=None, + ) + + @trace_method("SegmentAPI._delete", OpenTelemetryGranularity.OPERATION) + @override + def _delete( + self, + collection_id: UUID, + ids: Optional[IDs] = None, + where: Optional[Where] = None, + where_document: Optional[WhereDocument] = None, + ) -> IDs: + add_attributes_to_current_span( + { + "collection_id": str(collection_id), + "ids_count": len(ids) if ids else 0, + } + ) + + where = validate_where(where) if where is not None and len(where) > 0 else None + where_document = ( + validate_where_document(where_document) + if where_document is not None and len(where_document) > 0 + else None + ) + + # You must have at least one of non-empty ids, where, or where_document. + if ( + (ids is None or (ids is not None and len(ids) == 0)) + and (where is None or (where is not None and len(where) == 0)) + and ( + where_document is None + or (where_document is not None and len(where_document) == 0) + ) + ): + raise ValueError( + """ + You must provide either ids, where, or where_document to delete. If + you want to delete all data in a collection you can delete the + collection itself using the delete_collection method. Or alternatively, + you can get() all the relevant ids and then delete them. + """ + ) + + coll = self._get_collection(collection_id) + self._manager.hint_use_collection(collection_id, t.Operation.DELETE) + + if (where or where_document) or not ids: + metadata_segment = self._manager.get_segment(collection_id, MetadataReader) + records = metadata_segment.get_metadata( + where=where, where_document=where_document, ids=ids + ) + ids_to_delete = [r["id"] for r in records] + else: + ids_to_delete = ids + + if len(ids_to_delete) == 0: + return [] + + records_to_submit = [] + for r in _records( + operation=t.Operation.DELETE, ids=ids_to_delete, collection_id=collection_id + ): + self._validate_embedding_record(coll, r) + records_to_submit.append(r) + self._producer.submit_embeddings(coll["topic"], records_to_submit) + + self._product_telemetry_client.capture( + CollectionDeleteEvent( + collection_uuid=str(collection_id), delete_amount=len(ids_to_delete) + ) + ) + return ids_to_delete + + @trace_method("SegmentAPI._count", OpenTelemetryGranularity.OPERATION) + @override + def _count(self, collection_id: UUID) -> int: + add_attributes_to_current_span({"collection_id": str(collection_id)}) + metadata_segment = self._manager.get_segment(collection_id, MetadataReader) + return metadata_segment.count() + + @trace_method("SegmentAPI._query", OpenTelemetryGranularity.OPERATION) + @override + def _query( + self, + collection_id: UUID, + query_embeddings: Embeddings, + n_results: int = 10, + where: Where = {}, + where_document: WhereDocument = {}, + include: Include = ["documents", "metadatas", "distances"], + ) -> QueryResult: + add_attributes_to_current_span( + { + "collection_id": str(collection_id), + "n_results": n_results, + "where": str(where), + } + ) + where = validate_where(where) if where is not None and len(where) > 0 else where + where_document = ( + validate_where_document(where_document) + if where_document is not None and len(where_document) > 0 + else where_document + ) + + allowed_ids = None + + coll = self._get_collection(collection_id) + for embedding in query_embeddings: + self._validate_dimension(coll, len(embedding), update=False) + + metadata_reader = self._manager.get_segment(collection_id, MetadataReader) + + if where or where_document: + records = metadata_reader.get_metadata( + where=where, where_document=where_document + ) + allowed_ids = [r["id"] for r in records] + + query = t.VectorQuery( + vectors=query_embeddings, + k=n_results, + allowed_ids=allowed_ids, + include_embeddings="embeddings" in include, + options=None, + ) + + vector_reader = self._manager.get_segment(collection_id, VectorReader) + results = vector_reader.query_vectors(query) + + ids: List[List[str]] = [] + distances: List[List[float]] = [] + embeddings: List[List[Embedding]] = [] + documents: List[List[Document]] = [] + uris: List[List[URI]] = [] + metadatas: List[List[t.Metadata]] = [] + + for result in results: + ids.append([r["id"] for r in result]) + if "distances" in include: + distances.append([r["distance"] for r in result]) + if "embeddings" in include: + embeddings.append([cast(Embedding, r["embedding"]) for r in result]) + + if "documents" in include or "metadatas" in include or "uris" in include: + all_ids: Set[str] = set() + for id_list in ids: + all_ids.update(id_list) + records = metadata_reader.get_metadata(ids=list(all_ids)) + metadata_by_id = {r["id"]: r["metadata"] for r in records} + for id_list in ids: + # In the segment based architecture, it is possible for one segment + # to have a record that another segment does not have. This results in + # data inconsistency. For the case of the local segments and the + # local segment manager, there is a case where a thread writes + # a record to the vector segment but not the metadata segment. + # Then a query'ing thread reads from the vector segment and + # queries the metadata segment. The metadata segment does not have + # the record. In this case we choose to return potentially + # incorrect data in the form of None. + metadata_list = [metadata_by_id.get(id, None) for id in id_list] + if "metadatas" in include: + metadatas.append(_clean_metadatas(metadata_list)) # type: ignore + if "documents" in include: + doc_list = [_doc(m) for m in metadata_list] + documents.append(doc_list) # type: ignore + if "uris" in include: + uri_list = [_uri(m) for m in metadata_list] + uris.append(uri_list) # type: ignore + + query_amount = len(query_embeddings) + self._product_telemetry_client.capture( + CollectionQueryEvent( + collection_uuid=str(collection_id), + query_amount=query_amount, + n_results=n_results, + with_metadata_filter=query_amount if where is not None else 0, + with_document_filter=query_amount if where_document is not None else 0, + include_metadatas=query_amount if "metadatas" in include else 0, + include_documents=query_amount if "documents" in include else 0, + include_uris=query_amount if "uris" in include else 0, + include_distances=query_amount if "distances" in include else 0, + ) + ) + + return QueryResult( + ids=ids, + distances=distances if distances else None, + metadatas=metadatas if metadatas else None, + embeddings=embeddings if embeddings else None, + documents=documents if documents else None, + uris=uris if uris else None, + data=None, + ) + + @trace_method("SegmentAPI._peek", OpenTelemetryGranularity.OPERATION) + @override + def _peek(self, collection_id: UUID, n: int = 10) -> GetResult: + add_attributes_to_current_span({"collection_id": str(collection_id)}) + return self._get(collection_id, limit=n) # type: ignore + + @override + def get_version(self) -> str: + return __version__ + + @override + def reset_state(self) -> None: + self._collection_cache = {} + + @override + def reset(self) -> bool: + self._system.reset_state() + return True + + @override + def get_settings(self) -> Settings: + return self._settings + + @property + @override + def max_batch_size(self) -> int: + return self._producer.max_batch_size + + # TODO: This could potentially cause race conditions in a distributed version of the + # system, since the cache is only local. + # TODO: promote collection -> topic to a base class method so that it can be + # used for channel assignment in the distributed version of the system. + @trace_method("SegmentAPI._validate_embedding_record", OpenTelemetryGranularity.ALL) + def _validate_embedding_record( + self, collection: t.Collection, record: t.SubmitEmbeddingRecord + ) -> None: + """Validate the dimension of an embedding record before submitting it to the system.""" + add_attributes_to_current_span({"collection_id": str(collection["id"])}) + if record["embedding"]: + self._validate_dimension(collection, len(record["embedding"]), update=True) + + @trace_method("SegmentAPI._validate_dimension", OpenTelemetryGranularity.ALL) + def _validate_dimension( + self, collection: t.Collection, dim: int, update: bool + ) -> None: + """Validate that a collection supports records of the given dimension. If update + is true, update the collection if the collection doesn't already have a + dimension.""" + if collection["dimension"] is None: + if update: + id = collection["id"] + self._sysdb.update_collection(id=id, dimension=dim) + self._collection_cache[id]["dimension"] = dim + elif collection["dimension"] != dim: + raise InvalidDimensionException( + f"Embedding dimension {dim} does not match collection dimensionality {collection['dimension']}" + ) + else: + return # all is well + + @trace_method("SegmentAPI._get_collection", OpenTelemetryGranularity.ALL) + def _get_collection(self, collection_id: UUID) -> t.Collection: + """Read-through cache for collection data""" + if collection_id not in self._collection_cache: + collections = self._sysdb.get_collections(id=collection_id) + if not collections: + raise InvalidCollectionException( + f"Collection {collection_id} does not exist." + ) + self._collection_cache[collection_id] = collections[0] + return self._collection_cache[collection_id] + + +def _records( + operation: t.Operation, + ids: IDs, + collection_id: UUID, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + uris: Optional[URIs] = None, +) -> Generator[t.SubmitEmbeddingRecord, None, None]: + """Convert parallel lists of embeddings, metadatas and documents to a sequence of + SubmitEmbeddingRecords""" + + # Presumes that callers were invoked via Collection model, which means + # that we know that the embeddings, metadatas and documents have already been + # normalized and are guaranteed to be consistently named lists. + + for i, id in enumerate(ids): + metadata = None + if metadatas: + metadata = metadatas[i] + + if documents: + document = documents[i] + if metadata: + metadata = {**metadata, "chroma:document": document} + else: + metadata = {"chroma:document": document} + + if uris: + uri = uris[i] + if metadata: + metadata = {**metadata, "chroma:uri": uri} + else: + metadata = {"chroma:uri": uri} + + record = t.SubmitEmbeddingRecord( + id=id, + embedding=embeddings[i] if embeddings else None, + encoding=t.ScalarEncoding.FLOAT32, # Hardcode for now + metadata=metadata, + operation=operation, + collection_id=collection_id, + ) + yield record + + +def _doc(metadata: Optional[t.Metadata]) -> Optional[str]: + """Retrieve the document (if any) from a Metadata map""" + + if metadata and "chroma:document" in metadata: + return str(metadata["chroma:document"]) + return None + + +def _uri(metadata: Optional[t.Metadata]) -> Optional[str]: + """Retrieve the uri (if any) from a Metadata map""" + + if metadata and "chroma:uri" in metadata: + return str(metadata["chroma:uri"]) + return None + + +def _clean_metadatas( + metadata: List[Optional[t.Metadata]], +) -> List[Optional[t.Metadata]]: + """Remove any chroma-specific metadata keys that the client shouldn't see from a + list of metadata maps.""" + return [_clean_metadata(m) for m in metadata] + + +def _clean_metadata(metadata: Optional[t.Metadata]) -> Optional[t.Metadata]: + """Remove any chroma-specific metadata keys that the client shouldn't see from a + metadata map.""" + if not metadata: + return None + result = {} + for k, v in metadata.items(): + if not k.startswith("chroma:"): + result[k] = v + if len(result) == 0: + return None + return result diff --git a/chromadb/api/types.py b/chromadb/api/types.py new file mode 100644 index 0000000000000000000000000000000000000000..0054f283e8d05e694da6e74e06de17964441dfbe --- /dev/null +++ b/chromadb/api/types.py @@ -0,0 +1,509 @@ +from typing import Optional, Union, TypeVar, List, Dict, Any, Tuple, cast +from numpy.typing import NDArray +import numpy as np +from typing_extensions import Literal, TypedDict, Protocol +import chromadb.errors as errors +from chromadb.types import ( + Metadata, + UpdateMetadata, + Vector, + LiteralValue, + LogicalOperator, + WhereOperator, + OperatorExpression, + Where, + WhereDocumentOperator, + WhereDocument, +) +from inspect import signature +from tenacity import retry + +# Re-export types from chromadb.types +__all__ = ["Metadata", "Where", "WhereDocument", "UpdateCollectionMetadata"] + +T = TypeVar("T") +OneOrMany = Union[T, List[T]] + +# URIs +URI = str +URIs = List[URI] + + +def maybe_cast_one_to_many_uri(target: OneOrMany[URI]) -> URIs: + if isinstance(target, str): + # One URI + return cast(URIs, [target]) + # Already a sequence + return cast(URIs, target) + + +# IDs +ID = str +IDs = List[ID] + + +def maybe_cast_one_to_many_ids(target: OneOrMany[ID]) -> IDs: + if isinstance(target, str): + # One ID + return cast(IDs, [target]) + # Already a sequence + return cast(IDs, target) + + +# Embeddings +Embedding = Vector +Embeddings = List[Embedding] + + +def maybe_cast_one_to_many_embedding(target: OneOrMany[Embedding]) -> Embeddings: + if isinstance(target, List): + # One Embedding + if isinstance(target[0], (int, float)): + return cast(Embeddings, [target]) + # Already a sequence + return cast(Embeddings, target) + + +# Metadatas +Metadatas = List[Metadata] + + +def maybe_cast_one_to_many_metadata(target: OneOrMany[Metadata]) -> Metadatas: + # One Metadata dict + if isinstance(target, dict): + return cast(Metadatas, [target]) + # Already a sequence + return cast(Metadatas, target) + + +CollectionMetadata = Dict[str, Any] +UpdateCollectionMetadata = UpdateMetadata + +# Documents +Document = str +Documents = List[Document] + + +def is_document(target: Any) -> bool: + if not isinstance(target, str): + return False + return True + + +def maybe_cast_one_to_many_document(target: OneOrMany[Document]) -> Documents: + # One Document + if is_document(target): + return cast(Documents, [target]) + # Already a sequence + return cast(Documents, target) + + +# Images +ImageDType = Union[np.uint, np.int_, np.float_] +Image = NDArray[ImageDType] +Images = List[Image] + + +def is_image(target: Any) -> bool: + if not isinstance(target, np.ndarray): + return False + if len(target.shape) < 2: + return False + return True + + +def maybe_cast_one_to_many_image(target: OneOrMany[Image]) -> Images: + if is_image(target): + return cast(Images, [target]) + # Already a sequence + return cast(Images, target) + + +Parameter = TypeVar("Parameter", Document, Image, Embedding, Metadata, ID) + +# This should ust be List[Literal["documents", "embeddings", "metadatas", "distances"]] +# However, this provokes an incompatibility with the Overrides library and Python 3.7 +Include = List[ + Union[ + Literal["documents"], + Literal["embeddings"], + Literal["metadatas"], + Literal["distances"], + Literal["uris"], + Literal["data"], + ] +] + +# Re-export types from chromadb.types +LiteralValue = LiteralValue +LogicalOperator = LogicalOperator +WhereOperator = WhereOperator +OperatorExpression = OperatorExpression +Where = Where +WhereDocumentOperator = WhereDocumentOperator + +Embeddable = Union[Documents, Images] +D = TypeVar("D", bound=Embeddable, contravariant=True) + + +Loadable = List[Optional[Image]] +L = TypeVar("L", covariant=True, bound=Loadable) + + +class GetResult(TypedDict): + ids: List[ID] + embeddings: Optional[List[Embedding]] + documents: Optional[List[Document]] + uris: Optional[URIs] + data: Optional[Loadable] + metadatas: Optional[List[Metadata]] + + +class QueryResult(TypedDict): + ids: List[IDs] + embeddings: Optional[List[List[Embedding]]] + documents: Optional[List[List[Document]]] + uris: Optional[List[List[URI]]] + data: Optional[List[Loadable]] + metadatas: Optional[List[List[Metadata]]] + distances: Optional[List[List[float]]] + + +class IndexMetadata(TypedDict): + dimensionality: int + # The current number of elements in the index (total = additions - deletes) + curr_elements: int + # The auto-incrementing ID of the last inserted element, never decreases so + # can be used as a count of total historical size. Should increase by 1 every add. + # Assume cannot overflow + total_elements_added: int + time_created: float + + +class EmbeddingFunction(Protocol[D]): + def __call__(self, input: D) -> Embeddings: + ... + + def __init_subclass__(cls) -> None: + super().__init_subclass__() + # Raise an exception if __call__ is not defined since it is expected to be defined + call = getattr(cls, "__call__") + + def __call__(self: EmbeddingFunction[D], input: D) -> Embeddings: + result = call(self, input) + return validate_embeddings(maybe_cast_one_to_many_embedding(result)) + + setattr(cls, "__call__", __call__) + + def embed_with_retries(self, input: D, **retry_kwargs: Dict) -> Embeddings: + return retry(**retry_kwargs)(self.__call__)(input) + + +def validate_embedding_function( + embedding_function: EmbeddingFunction[Embeddable], +) -> None: + function_signature = signature( + embedding_function.__class__.__call__ + ).parameters.keys() + protocol_signature = signature(EmbeddingFunction.__call__).parameters.keys() + + if not function_signature == protocol_signature: + raise ValueError( + f"Expected EmbeddingFunction.__call__ to have the following signature: {protocol_signature}, got {function_signature}\n" + "Please see https://docs.trychroma.com/embeddings for details of the EmbeddingFunction interface.\n" + "Please note the recent change to the EmbeddingFunction interface: https://docs.trychroma.com/migration#migration-to-0416---november-7-2023 \n" + ) + + +class DataLoader(Protocol[L]): + def __call__(self, uris: URIs) -> L: + ... + + +def validate_ids(ids: IDs) -> IDs: + """Validates ids to ensure it is a list of strings""" + if not isinstance(ids, list): + raise ValueError(f"Expected IDs to be a list, got {ids}") + if len(ids) == 0: + raise ValueError(f"Expected IDs to be a non-empty list, got {ids}") + seen = set() + dups = set() + for id_ in ids: + if not isinstance(id_, str): + raise ValueError(f"Expected ID to be a str, got {id_}") + if id_ in seen: + dups.add(id_) + else: + seen.add(id_) + if dups: + n_dups = len(dups) + if n_dups < 10: + example_string = ", ".join(dups) + message = ( + f"Expected IDs to be unique, found duplicates of: {example_string}" + ) + else: + examples = [] + for idx, dup in enumerate(dups): + examples.append(dup) + if idx == 10: + break + example_string = ( + f"{', '.join(examples[:5])}, ..., {', '.join(examples[-5:])}" + ) + message = f"Expected IDs to be unique, found {n_dups} duplicated IDs: {example_string}" + raise errors.DuplicateIDError(message) + return ids + + +def validate_metadata(metadata: Metadata) -> Metadata: + """Validates metadata to ensure it is a dictionary of strings to strings, ints, floats or bools""" + if not isinstance(metadata, dict) and metadata is not None: + raise ValueError(f"Expected metadata to be a dict or None, got {metadata}") + if metadata is None: + return metadata + if len(metadata) == 0: + raise ValueError(f"Expected metadata to be a non-empty dict, got {metadata}") + for key, value in metadata.items(): + if not isinstance(key, str): + raise TypeError( + f"Expected metadata key to be a str, got {key} which is a {type(key)}" + ) + # isinstance(True, int) evaluates to True, so we need to check for bools separately + if not isinstance(value, bool) and not isinstance(value, (str, int, float)): + raise ValueError( + f"Expected metadata value to be a str, int, float or bool, got {value} which is a {type(value)}" + ) + return metadata + + +def validate_update_metadata(metadata: UpdateMetadata) -> UpdateMetadata: + """Validates metadata to ensure it is a dictionary of strings to strings, ints, floats or bools""" + if not isinstance(metadata, dict) and metadata is not None: + raise ValueError(f"Expected metadata to be a dict or None, got {metadata}") + if metadata is None: + return metadata + if len(metadata) == 0: + raise ValueError(f"Expected metadata to be a non-empty dict, got {metadata}") + for key, value in metadata.items(): + if not isinstance(key, str): + raise ValueError(f"Expected metadata key to be a str, got {key}") + # isinstance(True, int) evaluates to True, so we need to check for bools separately + if not isinstance(value, bool) and not isinstance( + value, (str, int, float, type(None)) + ): + raise ValueError( + f"Expected metadata value to be a str, int, or float, got {value}" + ) + return metadata + + +def validate_metadatas(metadatas: Metadatas) -> Metadatas: + """Validates metadatas to ensure it is a list of dictionaries of strings to strings, ints, floats or bools""" + if not isinstance(metadatas, list): + raise ValueError(f"Expected metadatas to be a list, got {metadatas}") + for metadata in metadatas: + validate_metadata(metadata) + return metadatas + + +def validate_where(where: Where) -> Where: + """ + Validates where to ensure it is a dictionary of strings to strings, ints, floats or operator expressions, + or in the case of $and and $or, a list of where expressions + """ + if not isinstance(where, dict): + raise ValueError(f"Expected where to be a dict, got {where}") + if len(where) != 1: + raise ValueError(f"Expected where to have exactly one operator, got {where}") + for key, value in where.items(): + if not isinstance(key, str): + raise ValueError(f"Expected where key to be a str, got {key}") + if ( + key != "$and" + and key != "$or" + and key != "$in" + and key != "$nin" + and not isinstance(value, (str, int, float, dict)) + ): + raise ValueError( + f"Expected where value to be a str, int, float, or operator expression, got {value}" + ) + if key == "$and" or key == "$or": + if not isinstance(value, list): + raise ValueError( + f"Expected where value for $and or $or to be a list of where expressions, got {value}" + ) + if len(value) <= 1: + raise ValueError( + f"Expected where value for $and or $or to be a list with at least two where expressions, got {value}" + ) + for where_expression in value: + validate_where(where_expression) + # Value is a operator expression + if isinstance(value, dict): + # Ensure there is only one operator + if len(value) != 1: + raise ValueError( + f"Expected operator expression to have exactly one operator, got {value}" + ) + + for operator, operand in value.items(): + # Only numbers can be compared with gt, gte, lt, lte + if operator in ["$gt", "$gte", "$lt", "$lte"]: + if not isinstance(operand, (int, float)): + raise ValueError( + f"Expected operand value to be an int or a float for operator {operator}, got {operand}" + ) + if operator in ["$in", "$nin"]: + if not isinstance(operand, list): + raise ValueError( + f"Expected operand value to be an list for operator {operator}, got {operand}" + ) + if operator not in [ + "$gt", + "$gte", + "$lt", + "$lte", + "$ne", + "$eq", + "$in", + "$nin", + ]: + raise ValueError( + f"Expected where operator to be one of $gt, $gte, $lt, $lte, $ne, $eq, $in, $nin, " + f"got {operator}" + ) + + if not isinstance(operand, (str, int, float, list)): + raise ValueError( + f"Expected where operand value to be a str, int, float, or list of those type, got {operand}" + ) + if isinstance(operand, list) and ( + len(operand) == 0 + or not all(isinstance(x, type(operand[0])) for x in operand) + ): + raise ValueError( + f"Expected where operand value to be a non-empty list, and all values to obe of the same type " + f"got {operand}" + ) + return where + + +def validate_where_document(where_document: WhereDocument) -> WhereDocument: + """ + Validates where_document to ensure it is a dictionary of WhereDocumentOperator to strings, or in the case of $and and $or, + a list of where_document expressions + """ + if not isinstance(where_document, dict): + raise ValueError( + f"Expected where document to be a dictionary, got {where_document}" + ) + if len(where_document) != 1: + raise ValueError( + f"Expected where document to have exactly one operator, got {where_document}" + ) + for operator, operand in where_document.items(): + if operator not in ["$contains", "$not_contains", "$and", "$or"]: + raise ValueError( + f"Expected where document operator to be one of $contains, $and, $or, got {operator}" + ) + if operator == "$and" or operator == "$or": + if not isinstance(operand, list): + raise ValueError( + f"Expected document value for $and or $or to be a list of where document expressions, got {operand}" + ) + if len(operand) <= 1: + raise ValueError( + f"Expected document value for $and or $or to be a list with at least two where document expressions, got {operand}" + ) + for where_document_expression in operand: + validate_where_document(where_document_expression) + # Value is a $contains operator + elif not isinstance(operand, str): + raise ValueError( + f"Expected where document operand value for operator $contains to be a str, got {operand}" + ) + elif len(operand) == 0: + raise ValueError( + "Expected where document operand value for operator $contains to be a non-empty str" + ) + return where_document + + +def validate_include(include: Include, allow_distances: bool) -> Include: + """Validates include to ensure it is a list of strings. Since get does not allow distances, allow_distances is used + to control if distances is allowed""" + + if not isinstance(include, list): + raise ValueError(f"Expected include to be a list, got {include}") + for item in include: + if not isinstance(item, str): + raise ValueError(f"Expected include item to be a str, got {item}") + allowed_values = ["embeddings", "documents", "metadatas", "uris", "data"] + if allow_distances: + allowed_values.append("distances") + if item not in allowed_values: + raise ValueError( + f"Expected include item to be one of {', '.join(allowed_values)}, got {item}" + ) + return include + + +def validate_n_results(n_results: int) -> int: + """Validates n_results to ensure it is a positive Integer. Since hnswlib does not allow n_results to be negative.""" + # Check Number of requested results + if not isinstance(n_results, int): + raise ValueError( + f"Expected requested number of results to be a int, got {n_results}" + ) + if n_results <= 0: + raise TypeError( + f"Number of requested results {n_results}, cannot be negative, or zero." + ) + return n_results + + +def validate_embeddings(embeddings: Embeddings) -> Embeddings: + """Validates embeddings to ensure it is a list of list of ints, or floats""" + if not isinstance(embeddings, list): + raise ValueError(f"Expected embeddings to be a list, got {embeddings}") + if len(embeddings) == 0: + raise ValueError( + f"Expected embeddings to be a list with at least one item, got {embeddings}" + ) + if not all([isinstance(e, list) for e in embeddings]): + raise ValueError( + f"Expected each embedding in the embeddings to be a list, got {embeddings}" + ) + for i,embedding in enumerate(embeddings): + if len(embedding) == 0: + raise ValueError( + f"Expected each embedding in the embeddings to be a non-empty list, got empty embedding at pos {i}" + ) + if not all( + [ + isinstance(value, (int, float)) and not isinstance(value, bool) + for value in embedding + ] + ): + raise ValueError( + f"Expected each value in the embedding to be a int or float, got {embeddings}" + ) + return embeddings + + +def validate_batch( + batch: Tuple[ + IDs, + Optional[Embeddings], + Optional[Metadatas], + Optional[Documents], + Optional[URIs], + ], + limits: Dict[str, Any], +) -> None: + if len(batch[0]) > limits["max_batch_size"]: + raise ValueError( + f"Batch size {len(batch[0])} exceeds maximum batch size {limits['max_batch_size']}" + ) diff --git a/chromadb/app.py b/chromadb/app.py new file mode 100644 index 0000000000000000000000000000000000000000..420bc2fce42d770a765f6f1172f8de1e601b87ad --- /dev/null +++ b/chromadb/app.py @@ -0,0 +1,7 @@ +import chromadb +import chromadb.config +from chromadb.server.fastapi import FastAPI + +settings = chromadb.config.Settings() +server = FastAPI(settings) +app = server.app() diff --git a/chromadb/auth/__init__.py b/chromadb/auth/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..b0616fcc103572dab195d74d365a952363c25cb4 --- /dev/null +++ b/chromadb/auth/__init__.py @@ -0,0 +1,449 @@ +""" +Contains only Auth abstractions, no implementations. +""" +import base64 +from functools import partial +import logging +from abc import ABC, abstractmethod +from enum import Enum +from typing import ( + Any, + Callable, + List, + Optional, + Dict, + TypeVar, + Tuple, + Generic, + Union, +) +from dataclasses import dataclass + +from overrides import EnforceOverrides, override +from pydantic import SecretStr + +from chromadb.config import ( + DEFAULT_DATABASE, + DEFAULT_TENANT, + Component, + System, +) +from chromadb.errors import ChromaError + +logger = logging.getLogger(__name__) + +T = TypeVar("T") +S = TypeVar("S") + + +class AuthInfoType(Enum): + COOKIE = "cookie" + HEADER = "header" + URL = "url" + METADATA = "metadata" # gRPC + + +class UserIdentity(EnforceOverrides, ABC): + @abstractmethod + def get_user_id(self) -> str: + ... + + @abstractmethod + def get_user_tenant(self) -> Optional[str]: + ... + + @abstractmethod + def get_user_databases(self) -> Optional[List[str]]: + ... + + @abstractmethod + def get_user_attributes(self) -> Optional[Dict[str, Any]]: + ... + + +class SimpleUserIdentity(UserIdentity): + def __init__( + self, + user_id: str, + tenant: Optional[str] = None, + databases: Optional[List[str]] = None, + attributes: Optional[Dict[str, Any]] = None, + ) -> None: + self._user_id = user_id + self._tenant = tenant + self._attributes = attributes + self._databases = databases + + @override + def get_user_id(self) -> str: + return self._user_id + + @override + def get_user_tenant(self) -> Optional[str]: + return self._tenant if self._tenant else DEFAULT_TENANT + + @override + def get_user_databases(self) -> Optional[List[str]]: + return self._databases + + @override + def get_user_attributes(self) -> Optional[Dict[str, Any]]: + return self._attributes + + +class ClientAuthResponse(EnforceOverrides, ABC): + @abstractmethod + def get_auth_info_type(self) -> AuthInfoType: + ... + + @abstractmethod + def get_auth_info( + self, + ) -> Union[Tuple[str, SecretStr], List[Tuple[str, SecretStr]]]: + ... + + +class ClientAuthProvider(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def authenticate(self) -> ClientAuthResponse: + pass + + +class ClientAuthConfigurationProvider(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def get_configuration(self) -> Optional[T]: + pass + + +class ClientAuthCredentialsProvider(Component, Generic[T]): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def get_credentials(self) -> T: + pass + + +class ClientAuthProtocolAdapter(Component, Generic[T]): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def inject_credentials(self, injection_context: T) -> None: + pass + + +# SERVER-SIDE Abstractions + + +class ServerAuthenticationRequest(EnforceOverrides, ABC, Generic[T]): + @abstractmethod + def get_auth_info(self, auth_info_type: AuthInfoType, auth_info_id: str) -> T: + """ + This method should return the necessary auth info based on the type of + authentication (e.g. header, cookie, url) and a given id for the respective + auth type (e.g. name of the header, cookie, url param). + + :param auth_info_type: The type of auth info to return + :param auth_info_id: The id of the auth info to return + :return: The auth info which can be specific to the implementation + """ + pass + + +class ServerAuthenticationResponse(EnforceOverrides, ABC): + @abstractmethod + def success(self) -> bool: + ... + + @abstractmethod + def get_user_identity(self) -> Optional[UserIdentity]: + ... + + +class SimpleServerAuthenticationResponse(ServerAuthenticationResponse): + """Simple implementation of ServerAuthenticationResponse""" + + _auth_success: bool + _user_identity: Optional[UserIdentity] + + def __init__( + self, auth_success: bool, user_identity: Optional[UserIdentity] + ) -> None: + self._auth_success = auth_success + self._user_identity = user_identity + + @override + def success(self) -> bool: + return self._auth_success + + @override + def get_user_identity(self) -> Optional[UserIdentity]: + return self._user_identity + + +class ServerAuthProvider(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def authenticate( + self, request: ServerAuthenticationRequest[T] + ) -> ServerAuthenticationResponse: + pass + + +class ChromaAuthMiddleware(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def authenticate( + self, request: ServerAuthenticationRequest[T] + ) -> ServerAuthenticationResponse: + ... + + @abstractmethod + def ignore_operation(self, verb: str, path: str) -> bool: + ... + + @abstractmethod + def instrument_server(self, app: T) -> None: + ... + + +class ServerAuthConfigurationProvider(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def get_configuration(self) -> Optional[T]: + pass + + +class AuthenticationError(ChromaError): + @override + def code(self) -> int: + return 401 + + @classmethod + @override + def name(cls) -> str: + return "AuthenticationError" + + +class AbstractCredentials(EnforceOverrides, ABC, Generic[T]): + """ + The class is used by Auth Providers to encapsulate credentials received + from the server and pass them to a ServerAuthCredentialsProvider. + """ + + @abstractmethod + def get_credentials(self) -> Dict[str, T]: + """ + Returns the data encapsulated by the credentials object. + """ + pass + + +class SecretStrAbstractCredentials(AbstractCredentials[SecretStr]): + @abstractmethod + @override + def get_credentials(self) -> Dict[str, SecretStr]: + """ + Returns the data encapsulated by the credentials object. + """ + pass + + +class BasicAuthCredentials(SecretStrAbstractCredentials): + def __init__(self, username: SecretStr, password: SecretStr) -> None: + self.username = username + self.password = password + + @override + def get_credentials(self) -> Dict[str, SecretStr]: + return {"username": self.username, "password": self.password} + + @staticmethod + def from_header(header: str) -> "BasicAuthCredentials": + """ + Parses a basic auth header and returns a BasicAuthCredentials object. + """ + header = header.replace("Basic ", "") + header = header.strip() + base64_decoded = base64.b64decode(header).decode("utf-8") + username, password = base64_decoded.split(":") + return BasicAuthCredentials(SecretStr(username), SecretStr(password)) + + +class ServerAuthCredentialsProvider(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def validate_credentials(self, credentials: AbstractCredentials[T]) -> bool: + ... + + @abstractmethod + def get_user_identity( + self, credentials: AbstractCredentials[T] + ) -> Optional[UserIdentity]: + ... + + +class AuthzResourceTypes(str, Enum): + DB = "db" + COLLECTION = "collection" + TENANT = "tenant" + + +class AuthzResourceActions(str, Enum): + CREATE_DATABASE = "create_database" + GET_DATABASE = "get_database" + CREATE_TENANT = "create_tenant" + GET_TENANT = "get_tenant" + LIST_COLLECTIONS = "list_collections" + COUNT_COLLECTIONS = "count_collections" + GET_COLLECTION = "get_collection" + CREATE_COLLECTION = "create_collection" + GET_OR_CREATE_COLLECTION = "get_or_create_collection" + DELETE_COLLECTION = "delete_collection" + UPDATE_COLLECTION = "update_collection" + ADD = "add" + DELETE = "delete" + GET = "get" + QUERY = "query" + COUNT = "count" + UPDATE = "update" + UPSERT = "upsert" + RESET = "reset" + + +@dataclass +class AuthzUser: + id: Optional[str] + tenant: Optional[str] = DEFAULT_TENANT + attributes: Optional[Dict[str, Any]] = None + claims: Optional[Dict[str, Any]] = None + + +@dataclass +class AuthzResource: + id: Optional[str] + type: Optional[str] + attributes: Optional[Dict[str, Any]] = None + + +class DynamicAuthzResource: + id: Optional[Union[str, Callable[..., str]]] + type: Optional[Union[str, Callable[..., str]]] + attributes: Optional[Union[Dict[str, Any], Callable[..., Dict[str, Any]]]] + + def __init__( + self, + id: Optional[Union[str, Callable[..., str]]] = None, + attributes: Optional[ + Union[Dict[str, Any], Callable[..., Dict[str, Any]]] + ] = lambda **kwargs: {}, + type: Optional[Union[str, Callable[..., str]]] = DEFAULT_DATABASE, + ) -> None: + self.id = id + self.attributes = attributes + self.type = type + + def to_authz_resource(self, **kwargs: Any) -> AuthzResource: + return AuthzResource( + id=self.id(**kwargs) if callable(self.id) else self.id, + type=self.type(**kwargs) if callable(self.type) else self.type, + attributes=self.attributes(**kwargs) + if callable(self.attributes) + else self.attributes, + ) + + +class AuthzDynamicParams: + @staticmethod + def from_function_name(**kwargs: Any) -> Callable[..., str]: + return partial(lambda **kwargs: kwargs["function"].__name__, **kwargs) + + @staticmethod + def from_function_args(**kwargs: Any) -> Callable[..., str]: + return partial( + lambda **kwargs: kwargs["function_args"][kwargs["arg_num"]], **kwargs + ) + + @staticmethod + def from_function_kwargs(**kwargs: Any) -> Callable[..., str]: + return partial( + lambda **kwargs: kwargs["function_kwargs"][kwargs["arg_name"]], **kwargs + ) + + @staticmethod + def dict_from_function_kwargs(**kwargs: Any) -> Callable[..., Dict[str, Any]]: + return partial( + lambda **kwargs: { + k: kwargs["function_kwargs"][k] for k in kwargs["arg_names"] + }, + **kwargs, + ) + + +@dataclass +class AuthzAction: + id: str + attributes: Optional[Dict[str, Any]] = None + + +@dataclass +class AuthorizationContext: + user: AuthzUser + resource: AuthzResource + action: AuthzAction + + +class ServerAuthorizationProvider(Component): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def authorize(self, context: AuthorizationContext) -> bool: + pass + + +class AuthorizationRequestContext(EnforceOverrides, ABC, Generic[T]): + @abstractmethod + def get_request(self) -> T: + ... + + +class ChromaAuthzMiddleware(Component, Generic[T, S]): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def pre_process(self, request: AuthorizationRequestContext[S]) -> None: + ... + + @abstractmethod + def ignore_operation(self, verb: str, path: str) -> bool: + ... + + @abstractmethod + def instrument_server(self, app: T) -> None: + ... + + +class ServerAuthorizationConfigurationProvider(Component, Generic[T]): + def __init__(self, system: System) -> None: + super().__init__(system) + + @abstractmethod + def get_configuration(self) -> T: + pass diff --git a/chromadb/auth/authz/__init__.py b/chromadb/auth/authz/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..0cb350e8ca4904ecc47d33da058ab34e723e99af --- /dev/null +++ b/chromadb/auth/authz/__init__.py @@ -0,0 +1,110 @@ +import logging +from typing import Any, Dict, Set, cast +from overrides import override +import yaml +from chromadb.auth import ( + AuthorizationContext, + ServerAuthorizationConfigurationProvider, + ServerAuthorizationProvider, +) +from chromadb.auth.registry import register_provider, resolve_provider +from chromadb.config import DEFAULT_TENANT, System + +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryGranularity, + trace_method, +) + +logger = logging.getLogger(__name__) + + +@register_provider("local_authz_config") +class LocalUserConfigAuthorizationConfigurationProvider( + ServerAuthorizationConfigurationProvider[Dict[str, Any]] +): + _config_file: str + _config: Dict[str, Any] + + def __init__(self, system: System) -> None: + super().__init__(system) + self._settings = system.settings + if self._settings.chroma_server_authz_config_file: + self._config_file = str(system.settings.chroma_server_authz_config_file) + with open(self._config_file, "r") as f: + self._config = yaml.safe_load(f) + elif self._settings.chroma_server_authz_config: + self._config = self._settings.chroma_server_authz_config + else: + raise ValueError( + "No configuration (CHROMA_SERVER_AUTHZ_CONFIG_FILE) file or " + "configuration (CHROMA_SERVER_AUTHZ_CONFIG) provided for " + "LocalUserConfigAuthorizationConfigurationProvider" + ) + + @override + def get_configuration(self) -> Dict[str, Any]: + return self._config + + +@register_provider("simple_rbac") +class SimpleRBACAuthorizationProvider(ServerAuthorizationProvider): + _authz_config_provider: ServerAuthorizationConfigurationProvider[Dict[str, Any]] + + def __init__(self, system: System) -> None: + super().__init__(system) + self._settings = system.settings + system.settings.require("chroma_server_authz_config_provider") + if self._settings.chroma_server_authz_config_provider: + _cls = resolve_provider( + self._settings.chroma_server_authz_config_provider, + ServerAuthorizationConfigurationProvider, + ) + self._authz_config_provider = cast( + ServerAuthorizationConfigurationProvider[Dict[str, Any]], + self.require(_cls), + ) + _config = self._authz_config_provider.get_configuration() + self._authz_tuples_map: Dict[str, Set[Any]] = {} + for u in _config["users"]: + _actions = _config["roles_mapping"][u["role"]]["actions"] + for a in _actions: + tenant = u["tenant"] if "tenant" in u else DEFAULT_TENANT + if u["id"] not in self._authz_tuples_map.keys(): + self._authz_tuples_map[u["id"]] = set() + self._authz_tuples_map[u["id"]].add( + (u["id"], tenant, *a.split(":")) + ) + logger.debug( + f"Loaded {len(self._authz_tuples_map)} permissions for " + f"({len(_config['users'])}) users" + ) + logger.info( + "Authorization Provider SimpleRBACAuthorizationProvider initialized" + ) + + @trace_method( + "SimpleRBACAuthorizationProvider.authorize", + OpenTelemetryGranularity.ALL, + ) + @override + def authorize(self, context: AuthorizationContext) -> bool: + _authz_tuple = ( + context.user.id, + context.user.tenant, + context.resource.type, + context.action.id, + ) + + policy_decision = False + if ( + context.user.id in self._authz_tuples_map.keys() + and _authz_tuple in self._authz_tuples_map[context.user.id] + ): + policy_decision = True + logger.debug( + f"Authorization decision: Access " + f"{'granted' if policy_decision else 'denied'} for " + f"user [{context.user.id}] attempting to [{context.action.id}]" + f" on [{context.resource}]" + ) + return policy_decision diff --git a/chromadb/auth/basic/__init__.py b/chromadb/auth/basic/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..d561895faf5402f3c112ad581d57184a1244d055 --- /dev/null +++ b/chromadb/auth/basic/__init__.py @@ -0,0 +1,110 @@ +import base64 +import logging +from typing import Tuple, Any, cast + +from overrides import override +from pydantic import SecretStr + +from chromadb.auth import ( + ServerAuthProvider, + ClientAuthProvider, + ServerAuthenticationRequest, + ServerAuthCredentialsProvider, + AuthInfoType, + BasicAuthCredentials, + ClientAuthCredentialsProvider, + ClientAuthResponse, + SimpleServerAuthenticationResponse, +) +from chromadb.auth.registry import register_provider, resolve_provider +from chromadb.config import System +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryGranularity, + trace_method, +) +from chromadb.utils import get_class + +logger = logging.getLogger(__name__) + +__all__ = ["BasicAuthServerProvider", "BasicAuthClientProvider"] + + +class BasicAuthClientAuthResponse(ClientAuthResponse): + def __init__(self, credentials: SecretStr) -> None: + self._credentials = credentials + + @override + def get_auth_info_type(self) -> AuthInfoType: + return AuthInfoType.HEADER + + @override + def get_auth_info(self) -> Tuple[str, SecretStr]: + return "Authorization", SecretStr( + f"Basic {self._credentials.get_secret_value()}" + ) + + +@register_provider("basic") +class BasicAuthClientProvider(ClientAuthProvider): + _credentials_provider: ClientAuthCredentialsProvider[Any] + + def __init__(self, system: System) -> None: + super().__init__(system) + self._settings = system.settings + system.settings.require("chroma_client_auth_credentials_provider") + self._credentials_provider = system.require( + get_class( + str(system.settings.chroma_client_auth_credentials_provider), + ClientAuthCredentialsProvider, + ) + ) + + @override + def authenticate(self) -> ClientAuthResponse: + _creds = self._credentials_provider.get_credentials() + return BasicAuthClientAuthResponse( + SecretStr( + base64.b64encode(f"{_creds.get_secret_value()}".encode("utf-8")).decode( + "utf-8" + ) + ) + ) + + +@register_provider("basic") +class BasicAuthServerProvider(ServerAuthProvider): + _credentials_provider: ServerAuthCredentialsProvider + + def __init__(self, system: System) -> None: + super().__init__(system) + self._settings = system.settings + system.settings.require("chroma_server_auth_credentials_provider") + self._credentials_provider = cast( + ServerAuthCredentialsProvider, + system.require( + resolve_provider( + str(system.settings.chroma_server_auth_credentials_provider), + ServerAuthCredentialsProvider, + ) + ), + ) + + @trace_method("BasicAuthServerProvider.authenticate", OpenTelemetryGranularity.ALL) + @override + def authenticate( + self, request: ServerAuthenticationRequest[Any] + ) -> SimpleServerAuthenticationResponse: + try: + _auth_header = request.get_auth_info(AuthInfoType.HEADER, "Authorization") + _validation = self._credentials_provider.validate_credentials( + BasicAuthCredentials.from_header(_auth_header) + ) + return SimpleServerAuthenticationResponse( + _validation, + self._credentials_provider.get_user_identity( + BasicAuthCredentials.from_header(_auth_header) + ), + ) + except Exception as e: + logger.error(f"BasicAuthServerProvider.authenticate failed: {repr(e)}") + return SimpleServerAuthenticationResponse(False, None) diff --git a/chromadb/auth/fastapi.py b/chromadb/auth/fastapi.py new file mode 100644 index 0000000000000000000000000000000000000000..1f9d3c900c350c15813c1e833c6b8e6069ca62ea --- /dev/null +++ b/chromadb/auth/fastapi.py @@ -0,0 +1,330 @@ +import chromadb +from contextvars import ContextVar +from functools import wraps +import logging +from typing import Callable, Optional, Dict, List, Union, cast, Any +from overrides import override +from starlette.middleware.base import BaseHTTPMiddleware, RequestResponseEndpoint +from starlette.requests import Request +from starlette.responses import Response +from starlette.types import ASGIApp + +from chromadb.config import DEFAULT_TENANT, System +from chromadb.auth import ( + AuthorizationContext, + AuthorizationRequestContext, + AuthzAction, + AuthzResource, + AuthzResourceActions, + AuthzUser, + DynamicAuthzResource, + ServerAuthenticationRequest, + AuthInfoType, + ServerAuthenticationResponse, + ServerAuthProvider, + ChromaAuthMiddleware, + ChromaAuthzMiddleware, + ServerAuthorizationProvider, +) +from chromadb.auth.registry import resolve_provider +from chromadb.errors import AuthorizationError +from chromadb.server.fastapi.utils import fastapi_json_response +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryGranularity, + trace_method, +) + +logger = logging.getLogger(__name__) + + +class FastAPIServerAuthenticationRequest(ServerAuthenticationRequest[Optional[str]]): + def __init__(self, request: Request) -> None: + self._request = request + + @override + def get_auth_info( + self, auth_info_type: AuthInfoType, auth_info_id: str + ) -> Optional[str]: + if auth_info_type == AuthInfoType.HEADER: + return str(self._request.headers[auth_info_id]) + elif auth_info_type == AuthInfoType.COOKIE: + return str(self._request.cookies[auth_info_id]) + elif auth_info_type == AuthInfoType.URL: + return str(self._request.query_params[auth_info_id]) + elif auth_info_type == AuthInfoType.METADATA: + raise ValueError("Metadata not supported for FastAPI") + else: + raise ValueError(f"Unknown auth info type: {auth_info_type}") + + +class FastAPIServerAuthenticationResponse(ServerAuthenticationResponse): + _auth_success: bool + + def __init__(self, auth_success: bool) -> None: + self._auth_success = auth_success + + @override + def success(self) -> bool: + return self._auth_success + + +class FastAPIChromaAuthMiddleware(ChromaAuthMiddleware): + _auth_provider: ServerAuthProvider + + def __init__(self, system: System) -> None: + super().__init__(system) + self._system = system + self._settings = system.settings + self._settings.require("chroma_server_auth_provider") + self._ignore_auth_paths: Dict[ + str, List[str] + ] = self._settings.chroma_server_auth_ignore_paths + if self._settings.chroma_server_auth_provider: + logger.debug( + f"Server Auth Provider: {self._settings.chroma_server_auth_provider}" + ) + _cls = resolve_provider( + self._settings.chroma_server_auth_provider, ServerAuthProvider + ) + self._auth_provider = cast(ServerAuthProvider, self.require(_cls)) + + @trace_method( + "FastAPIChromaAuthMiddleware.authenticate", OpenTelemetryGranularity.ALL + ) + @override + def authenticate( + self, request: ServerAuthenticationRequest[Any] + ) -> ServerAuthenticationResponse: + return self._auth_provider.authenticate(request) + + @trace_method( + "FastAPIChromaAuthMiddleware.ignore_operation", OpenTelemetryGranularity.ALL + ) + @override + def ignore_operation(self, verb: str, path: str) -> bool: + if ( + path in self._ignore_auth_paths.keys() + and verb.upper() in self._ignore_auth_paths[path] + ): + logger.debug(f"Skipping auth for path {path} and method {verb}") + return True + return False + + @override + def instrument_server(self, app: ASGIApp) -> None: + # We can potentially add an `/auth` endpoint to the server to allow for more + # complex auth flows + raise NotImplementedError("Not implemented yet") + + +class FastAPIChromaAuthMiddlewareWrapper(BaseHTTPMiddleware): # type: ignore + def __init__( + self, app: ASGIApp, auth_middleware: FastAPIChromaAuthMiddleware + ) -> None: + super().__init__(app) + self._middleware = auth_middleware + try: + self._middleware.instrument_server(app) + except NotImplementedError: + pass + + @trace_method( + "FastAPIChromaAuthMiddlewareWrapper.dispatch", OpenTelemetryGranularity.ALL + ) + @override + async def dispatch( + self, request: Request, call_next: RequestResponseEndpoint + ) -> Response: + if self._middleware.ignore_operation(request.method, request.url.path): + logger.debug( + f"Skipping auth for path {request.url.path} and method {request.method}" + ) + return await call_next(request) + response = self._middleware.authenticate( + FastAPIServerAuthenticationRequest(request) + ) + if not response or not response.success(): + return fastapi_json_response(AuthorizationError("Unauthorized")) + + request.state.user_identity = response.get_user_identity() + return await call_next(request) + + +request_var: ContextVar[Optional[Request]] = ContextVar("request_var", default=None) +authz_provider: ContextVar[Optional[ServerAuthorizationProvider]] = ContextVar( + "authz_provider", default=None +) + +# This needs to be module-level config, since it's used in authz_context() where we +# don't have a system (so don't have easy access to the settings). +overwrite_singleton_tenant_database_access_from_auth: bool = False + + +def set_overwrite_singleton_tenant_database_access_from_auth( + overwrite: bool = False, +) -> None: + global overwrite_singleton_tenant_database_access_from_auth + overwrite_singleton_tenant_database_access_from_auth = overwrite + + +def authz_context( + action: Union[str, AuthzResourceActions, List[str], List[AuthzResourceActions]], + resource: Union[AuthzResource, DynamicAuthzResource], +) -> Callable[[Callable[..., Any]], Callable[..., Any]]: + def decorator(f: Callable[..., Any]) -> Callable[..., Any]: + @wraps(f) + def wrapped(*args: Any, **kwargs: Dict[Any, Any]) -> Any: + _dynamic_kwargs = { + "api": args[0]._api, + "function": f, + "function_args": args, + "function_kwargs": kwargs, + } + request = request_var.get() + if request: + _provider = authz_provider.get() + a_list: List[Union[str, AuthzAction]] = [] + if not isinstance(action, list): + a_list = [action] + else: + a_list = cast(List[Union[str, AuthzAction]], action) + a_authz_responses = [] + for a in a_list: + _action = a if isinstance(a, AuthzAction) else AuthzAction(id=a) + _resource = ( + resource + if isinstance(resource, AuthzResource) + else resource.to_authz_resource(**_dynamic_kwargs) + ) + _context = AuthorizationContext( + user=AuthzUser( + id=request.state.user_identity.get_user_id() + if hasattr(request.state, "user_identity") + else "Anonymous", + tenant=request.state.user_identity.get_user_tenant() + if hasattr(request.state, "user_identity") + else DEFAULT_TENANT, + attributes=request.state.user_identity.get_user_attributes() + if hasattr(request.state, "user_identity") + else {}, + ), + resource=_resource, + action=_action, + ) + + if _provider: + a_authz_responses.append(_provider.authorize(_context)) + if not any(a_authz_responses): + raise AuthorizationError("Unauthorized") + # In a multi-tenant environment, we may want to allow users to send + # requests without configuring a tenant and DB. If so, they can set + # the request tenant and DB however they like and we simply overwrite it. + if overwrite_singleton_tenant_database_access_from_auth: + desired_tenant = request.state.user_identity.get_user_tenant() + if desired_tenant and "tenant" in kwargs: + if isinstance(kwargs["tenant"], str): + kwargs["tenant"] = desired_tenant + elif isinstance( + kwargs["tenant"], chromadb.server.fastapi.types.CreateTenant + ): + kwargs["tenant"].name = desired_tenant + databases = request.state.user_identity.get_user_databases() + if databases and len(databases) == 1 and "database" in kwargs: + desired_database = databases[0] + if isinstance(kwargs["database"], str): + kwargs["database"] = desired_database + elif isinstance( + kwargs["database"], + chromadb.server.fastapi.types.CreateDatabase, + ): + kwargs["database"].name = desired_database + + return f(*args, **kwargs) + + return wrapped + + return decorator + + +class FastAPIAuthorizationRequestContext(AuthorizationRequestContext[Request]): + _request: Request + + def __init__(self, request: Request) -> None: + self._request = request + pass + + @override + def get_request(self) -> Request: + return self._request + + +class FastAPIChromaAuthzMiddleware(ChromaAuthzMiddleware[ASGIApp, Request]): + _authz_provider: ServerAuthorizationProvider + + def __init__(self, system: System) -> None: + super().__init__(system) + self._system = system + self._settings = system.settings + self._settings.require("chroma_server_authz_provider") + self._ignore_auth_paths: Dict[ + str, List[str] + ] = self._settings.chroma_server_authz_ignore_paths + if self._settings.chroma_server_authz_provider: + logger.debug( + "Server Authorization Provider: " + f"{self._settings.chroma_server_authz_provider}" + ) + _cls = resolve_provider( + self._settings.chroma_server_authz_provider, ServerAuthorizationProvider + ) + self._authz_provider = cast(ServerAuthorizationProvider, self.require(_cls)) + + @override + def pre_process(self, request: AuthorizationRequestContext[Request]) -> None: + rest_request = request.get_request() + request_var.set(rest_request) + authz_provider.set(self._authz_provider) + + @override + def ignore_operation(self, verb: str, path: str) -> bool: + if ( + path in self._ignore_auth_paths.keys() + and verb.upper() in self._ignore_auth_paths[path] + ): + logger.debug(f"Skipping authz for path {path} and method {verb}") + return True + return False + + @override + def instrument_server(self, app: ASGIApp) -> None: + # We can potentially add an `/auth` endpoint to the server to allow + # for more complex auth flows + raise NotImplementedError("Not implemented yet") + + +class FastAPIChromaAuthzMiddlewareWrapper(BaseHTTPMiddleware): # type: ignore + def __init__( + self, app: ASGIApp, authz_middleware: FastAPIChromaAuthzMiddleware + ) -> None: + super().__init__(app) + self._middleware = authz_middleware + try: + self._middleware.instrument_server(app) + except NotImplementedError: + pass + + @trace_method( + "FastAPIChromaAuthzMiddlewareWrapper.dispatch", OpenTelemetryGranularity.ALL + ) + @override + async def dispatch( + self, request: Request, call_next: RequestResponseEndpoint + ) -> Response: + if self._middleware.ignore_operation(request.method, request.url.path): + logger.debug( + f"Skipping authz for path {request.url.path} " + "and method {request.method}" + ) + return await call_next(request) + self._middleware.pre_process(FastAPIAuthorizationRequestContext(request)) + return await call_next(request) diff --git a/chromadb/auth/fastapi_utils.py b/chromadb/auth/fastapi_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..2612bf6716fa9d539ada26464d07d4ec94cba490 --- /dev/null +++ b/chromadb/auth/fastapi_utils.py @@ -0,0 +1,53 @@ +from functools import partial +from typing import Any, Callable, Dict, Optional, Sequence, cast +from chromadb.server.fastapi.utils import string_to_uuid +from chromadb.api import ServerAPI +from chromadb.auth import AuthzResourceTypes + + +def find_key_with_value_of_type( + type: AuthzResourceTypes, **kwargs: Any +) -> Dict[str, Any]: + from chromadb.server.fastapi.types import ( + CreateCollection, + CreateDatabase, + CreateTenant, + ) + + for key, value in kwargs.items(): + if type == AuthzResourceTypes.DB and isinstance(value, CreateDatabase): + return dict(value) + elif type == AuthzResourceTypes.COLLECTION and isinstance( + value, CreateCollection + ): + return dict(value) + elif type == AuthzResourceTypes.TENANT and isinstance(value, CreateTenant): + return dict(value) + return {} + + +def attr_from_resource_object( + type: AuthzResourceTypes, + additional_attrs: Optional[Sequence[str]] = None, + **kwargs: Any, +) -> Callable[..., Dict[str, Any]]: + def _wrap(**wkwargs: Any) -> Dict[str, Any]: + obj = find_key_with_value_of_type(type, **wkwargs) + if additional_attrs: + obj.update({k: wkwargs["function_kwargs"][k] + for k in additional_attrs}) + return obj + + return partial(_wrap, **kwargs) + + +def attr_from_collection_lookup( + collection_id_arg: str, **kwargs: Any +) -> Callable[..., Dict[str, Any]]: + def _wrap(**kwargs: Any) -> Dict[str, Any]: + _api = cast(ServerAPI, kwargs["api"]) + col = _api.get_collection( + id=string_to_uuid(kwargs["function_kwargs"][collection_id_arg])) + return {"tenant": col.tenant, "database": col.database} + + return partial(_wrap, **kwargs) diff --git a/chromadb/auth/providers.py b/chromadb/auth/providers.py new file mode 100644 index 0000000000000000000000000000000000000000..8eb3f4697cbca2e0e71763af13360564ed83025e --- /dev/null +++ b/chromadb/auth/providers.py @@ -0,0 +1,197 @@ +import importlib +import logging +from typing import Optional, cast, Dict, TypeVar, Any + +import requests +from overrides import override +from pydantic import SecretStr +from chromadb.auth import ( + ServerAuthCredentialsProvider, + AbstractCredentials, + ClientAuthCredentialsProvider, + AuthInfoType, + ClientAuthProvider, + ClientAuthProtocolAdapter, + SimpleUserIdentity, +) +from chromadb.auth.registry import register_provider, resolve_provider +from chromadb.config import System +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryGranularity, + trace_method, +) + +T = TypeVar("T") + +logger = logging.getLogger(__name__) + + +class HtpasswdServerAuthCredentialsProvider(ServerAuthCredentialsProvider): + _creds: Dict[str, SecretStr] + + def __init__(self, system: System) -> None: + super().__init__(system) + try: + # Equivalent to import onnxruntime + self.bc = importlib.import_module("bcrypt") + except ImportError: + raise ValueError( + "The bcrypt python package is not installed. " + "Please install it with `pip install bcrypt`" + ) + + @trace_method( + "HtpasswdServerAuthCredentialsProvider.validate_credentials", + OpenTelemetryGranularity.ALL, + ) + @override + def validate_credentials(self, credentials: AbstractCredentials[T]) -> bool: + _creds = cast(Dict[str, SecretStr], credentials.get_credentials()) + if len(_creds) != 2: + logger.error( + "Returned credentials did match expected format: " + "dict[username:SecretStr, password: SecretStr]" + ) + return False + if "username" not in _creds or "password" not in _creds: + logger.error( + "Returned credentials do not contain username or password") + return False + _usr_check = bool( + _creds["username"].get_secret_value() + == self._creds["username"].get_secret_value() + ) + return _usr_check and self.bc.checkpw( + _creds["password"].get_secret_value().encode("utf-8"), + self._creds["password"].get_secret_value().encode("utf-8"), + ) + + @override + def get_user_identity( + self, credentials: AbstractCredentials[T] + ) -> Optional[SimpleUserIdentity]: + _creds = cast(Dict[str, SecretStr], credentials.get_credentials()) + return SimpleUserIdentity(_creds["username"].get_secret_value()) + + +@register_provider("htpasswd_file") +class HtpasswdFileServerAuthCredentialsProvider(HtpasswdServerAuthCredentialsProvider): + def __init__(self, system: System) -> None: + super().__init__(system) + system.settings.require("chroma_server_auth_credentials_file") + _file = str(system.settings.chroma_server_auth_credentials_file) + with open(_file, "r") as f: + _raw_creds = [v for v in f.readline().strip().split(":")] + self._creds = { + "username": SecretStr(_raw_creds[0]), + "password": SecretStr(_raw_creds[1]), + } + if ( + len(self._creds) != 2 + or "username" not in self._creds + or "password" not in self._creds + ): + raise ValueError( + "Invalid Htpasswd credentials found in " + "[chroma_server_auth_credentials]. " + "Must be :." + ) + + +class HtpasswdConfigurationServerAuthCredentialsProvider( + HtpasswdServerAuthCredentialsProvider +): + def __init__(self, system: System) -> None: + super().__init__(system) + system.settings.require("chroma_server_auth_credentials") + _raw_creds = ( + str(system.settings.chroma_server_auth_credentials).strip().split(":") + ) + self._creds = { + "username": SecretStr(_raw_creds[0]), + "password": SecretStr(_raw_creds[1]), + } + if ( + len(self._creds) != 2 + or "username" not in self._creds + or "password" not in self._creds + ): + raise ValueError( + "Invalid Htpasswd credentials found in " + "[chroma_server_auth_credentials]. " + "Must be :." + ) + + +class RequestsClientAuthProtocolAdapter( + ClientAuthProtocolAdapter[requests.PreparedRequest] +): + class _Session(requests.Session): + _protocol_adapter: ClientAuthProtocolAdapter[requests.PreparedRequest] + + def __init__( + self, protocol_adapter: ClientAuthProtocolAdapter[requests.PreparedRequest] + ) -> None: + super().__init__() + self._protocol_adapter = protocol_adapter + + @override + def send( + self, request: requests.PreparedRequest, **kwargs: Any + ) -> requests.Response: + self._protocol_adapter.inject_credentials(request) + return super().send(request, **kwargs) + + _session: _Session + _auth_provider: ClientAuthProvider + + def __init__(self, system: System) -> None: + super().__init__(system) + system.settings.require("chroma_client_auth_provider") + self._auth_provider = cast( + ClientAuthProvider, + system.require( + resolve_provider( + str(system.settings.chroma_client_auth_provider), ClientAuthProvider + ), + ), + ) + self._session = self._Session(self) + self._auth_header = self._auth_provider.authenticate() + + @property + def session(self) -> requests.Session: + return self._session + + @override + def inject_credentials(self, injection_context: requests.PreparedRequest) -> None: + if self._auth_header.get_auth_info_type() == AuthInfoType.HEADER: + _header_info = self._auth_header.get_auth_info() + if isinstance(_header_info, tuple): + injection_context.headers[_header_info[0]] = _header_info[ + 1 + ].get_secret_value() + else: + for header in _header_info: + injection_context.headers[header[0] + ] = header[1].get_secret_value() + else: + raise ValueError( + f"Unsupported auth type: {self._auth_header.get_auth_info_type()}" + ) + + +class ConfigurationClientAuthCredentialsProvider( + ClientAuthCredentialsProvider[SecretStr] +): + _creds: SecretStr + + def __init__(self, system: System) -> None: + super().__init__(system) + system.settings.require("chroma_client_auth_credentials") + self._creds = SecretStr( + str(system.settings.chroma_client_auth_credentials)) + + @override + def get_credentials(self) -> SecretStr: + return self._creds diff --git a/chromadb/auth/registry.py b/chromadb/auth/registry.py new file mode 100644 index 0000000000000000000000000000000000000000..af0f0f903e677eaed32dbba43e1716dd7a147a65 --- /dev/null +++ b/chromadb/auth/registry.py @@ -0,0 +1,123 @@ +import importlib +import logging +import pkgutil +from typing import Union, Dict, Type, Callable # noqa: F401 + +from chromadb.auth import ( + ClientAuthConfigurationProvider, + ClientAuthCredentialsProvider, + ClientAuthProtocolAdapter, + ServerAuthProvider, + ServerAuthConfigurationProvider, + ServerAuthCredentialsProvider, + ClientAuthProvider, + ServerAuthorizationConfigurationProvider, + ServerAuthorizationProvider, +) +from chromadb.utils import get_class + +logger = logging.getLogger(__name__) +ProviderTypes = Union[ + "ClientAuthProvider", + "ClientAuthConfigurationProvider", + "ClientAuthCredentialsProvider", + "ServerAuthProvider", + "ServerAuthConfigurationProvider", + "ServerAuthCredentialsProvider", + "ClientAuthProtocolAdapter", + "ServerAuthorizationProvider", + "ServerAuthorizationConfigurationProvider", +] + +_provider_registry = { + "client_auth_providers": {}, + "client_auth_config_providers": {}, + "client_auth_credentials_providers": {}, + "client_auth_protocol_adapters": {}, + "server_auth_providers": {}, + "server_auth_config_providers": {}, + "server_auth_credentials_providers": {}, + "server_authz_providers": {}, + "server_authz_config_providers": {}, +} # type: Dict[str, Dict[str, Type[ProviderTypes]]] + + +def register_classes_from_package(package_name: str) -> None: + package = importlib.import_module(package_name) + for _, module_name, _ in pkgutil.iter_modules(package.__path__): + full_module_name = f"{package_name}.{module_name}" + _ = importlib.import_module(full_module_name) + + +def register_provider( + short_hand: str, +) -> Callable[[Type[ProviderTypes]], Type[ProviderTypes]]: + def decorator(cls: Type[ProviderTypes]) -> Type[ProviderTypes]: + logger.debug("Registering provider: %s", short_hand) + global _provider_registry + if issubclass(cls, ClientAuthProvider): + _provider_registry["client_auth_providers"][short_hand] = cls + elif issubclass(cls, ClientAuthConfigurationProvider): + _provider_registry["client_auth_config_providers"][short_hand] = cls + elif issubclass(cls, ClientAuthCredentialsProvider): + _provider_registry["client_auth_credentials_providers"][short_hand] = cls + elif issubclass(cls, ClientAuthProtocolAdapter): + _provider_registry["client_auth_protocol_adapters"][short_hand] = cls + elif issubclass(cls, ServerAuthProvider): + _provider_registry["server_auth_providers"][short_hand] = cls + elif issubclass(cls, ServerAuthConfigurationProvider): + _provider_registry["server_auth_config_providers"][short_hand] = cls + elif issubclass(cls, ServerAuthCredentialsProvider): + _provider_registry["server_auth_credentials_providers"][short_hand] = cls + elif issubclass(cls, ServerAuthorizationProvider): + _provider_registry["server_authz_providers"][short_hand] = cls + elif issubclass(cls, ServerAuthorizationConfigurationProvider): + _provider_registry["server_authz_config_providers"][short_hand] = cls + else: + raise ValueError( + "Only ClientAuthProvider, ClientAuthConfigurationProvider, " + "ClientAuthCredentialsProvider, ServerAuthProvider, " + "ServerAuthConfigurationProvider, and ServerAuthCredentialsProvider, " + "ClientAuthProtocolAdapter, ServerAuthorizationProvider, " + "ServerAuthorizationConfigurationProvider can be registered." + ) + return cls + + return decorator + + +def resolve_provider( + class_or_name: str, cls: Type[ProviderTypes] +) -> Type[ProviderTypes]: + register_classes_from_package("chromadb.auth") + global _provider_registry + if issubclass(cls, ClientAuthProvider): + _key = "client_auth_providers" + elif issubclass(cls, ClientAuthConfigurationProvider): + _key = "client_auth_config_providers" + elif issubclass(cls, ClientAuthCredentialsProvider): + _key = "client_auth_credentials_providers" + elif issubclass(cls, ClientAuthProtocolAdapter): + _key = "client_auth_protocol_adapters" + elif issubclass(cls, ServerAuthProvider): + _key = "server_auth_providers" + elif issubclass(cls, ServerAuthConfigurationProvider): + _key = "server_auth_config_providers" + elif issubclass(cls, ServerAuthCredentialsProvider): + _key = "server_auth_credentials_providers" + elif issubclass(cls, ServerAuthorizationProvider): + _key = "server_authz_providers" + elif issubclass(cls, ServerAuthorizationConfigurationProvider): + _key = "server_authz_config_providers" + else: + raise ValueError( + "Only ClientAuthProvider, ClientAuthConfigurationProvider, " + "ClientAuthCredentialsProvider, ServerAuthProvider, " + "ServerAuthConfigurationProvider, and ServerAuthCredentialsProvider, " + "ClientAuthProtocolAdapter, ServerAuthorizationProvider," + "ServerAuthorizationConfigurationProvider, can be registered." + ) + if class_or_name in _provider_registry[_key]: + return _provider_registry[_key][class_or_name] + else: + return get_class(class_or_name, cls) # type: ignore diff --git a/chromadb/auth/token/__init__.py b/chromadb/auth/token/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..4d1998ff5ee49eca5eb3c9abcbf755f2b8673db9 --- /dev/null +++ b/chromadb/auth/token/__init__.py @@ -0,0 +1,291 @@ +import json +import logging +import string +from enum import Enum +from typing import List, Optional, Tuple, Any, TypedDict, cast, Dict, TypeVar + +from overrides import override +from pydantic import SecretStr +import yaml + +from chromadb.auth import ( + ServerAuthProvider, + ClientAuthProvider, + ServerAuthenticationRequest, + ServerAuthCredentialsProvider, + AuthInfoType, + ClientAuthCredentialsProvider, + ClientAuthResponse, + SecretStrAbstractCredentials, + AbstractCredentials, + SimpleServerAuthenticationResponse, + SimpleUserIdentity, +) +from chromadb.auth.registry import register_provider, resolve_provider +from chromadb.config import System +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryGranularity, + trace_method, +) +from chromadb.utils import get_class + +T = TypeVar("T") + +logger = logging.getLogger(__name__) + +__all__ = ["TokenAuthServerProvider", "TokenAuthClientProvider"] + +_token_transport_headers = ["Authorization", "X-Chroma-Token"] + + +class TokenTransportHeader(Enum): + AUTHORIZATION = "Authorization" + X_CHROMA_TOKEN = "X-Chroma-Token" + + +class TokenAuthClientAuthResponse(ClientAuthResponse): + _token_transport_header: TokenTransportHeader + + def __init__( + self, + credentials: SecretStr, + token_transport_header: TokenTransportHeader = TokenTransportHeader.AUTHORIZATION, + ) -> None: + self._credentials = credentials + self._token_transport_header = token_transport_header + + @override + def get_auth_info_type(self) -> AuthInfoType: + return AuthInfoType.HEADER + + @override + def get_auth_info(self) -> Tuple[str, SecretStr]: + if self._token_transport_header == TokenTransportHeader.AUTHORIZATION: + return "Authorization", SecretStr( + f"Bearer {self._credentials.get_secret_value()}" + ) + elif self._token_transport_header == TokenTransportHeader.X_CHROMA_TOKEN: + return "X-Chroma-Token", SecretStr( + f"{self._credentials.get_secret_value()}" + ) + else: + raise ValueError( + f"Invalid token transport header: {self._token_transport_header}" + ) + + +def check_token(token: str) -> None: + token_str = str(token) + if not all( + c in string.digits + string.ascii_letters + string.punctuation + for c in token_str + ): + raise ValueError("Invalid token. Must contain only ASCII letters and digits.") + + +@register_provider("token_config") +class TokenConfigServerAuthCredentialsProvider(ServerAuthCredentialsProvider): + _token: SecretStr + + def __init__(self, system: System) -> None: + super().__init__(system) + system.settings.require("chroma_server_auth_credentials") + token_str = str(system.settings.chroma_server_auth_credentials) + check_token(token_str) + self._token = SecretStr(token_str) + + @trace_method( + "TokenConfigServerAuthCredentialsProvider.validate_credentials", + OpenTelemetryGranularity.ALL, + ) + @override + def validate_credentials(self, credentials: AbstractCredentials[T]) -> bool: + _creds = cast(Dict[str, SecretStr], credentials.get_credentials()) + if "token" not in _creds: + logger.error("Returned credentials do not contain token") + return False + return _creds["token"].get_secret_value() == self._token.get_secret_value() + + @override + def get_user_identity( + self, credentials: AbstractCredentials[T] + ) -> Optional[SimpleUserIdentity]: + return None + + +class Token(TypedDict): + token: str + secret: str + + +class User(TypedDict): + id: str + role: str + tenant: Optional[str] + databases: Optional[List[str]] + tokens: List[Token] + + +@register_provider("user_token_config") +class UserTokenConfigServerAuthCredentialsProvider(ServerAuthCredentialsProvider): + _users: List[User] + _token_user_mapping: Dict[str, str] # reverse mapping of token to user + + def __init__(self, system: System) -> None: + super().__init__(system) + if system.settings.chroma_server_auth_credentials_file: + system.settings.require("chroma_server_auth_credentials_file") + user_file = str(system.settings.chroma_server_auth_credentials_file) + with open(user_file) as f: + self._users = cast(List[User], yaml.safe_load(f)["users"]) + elif system.settings.chroma_server_auth_credentials: + self._users = cast( + List[User], json.loads(system.settings.chroma_server_auth_credentials) + ) + self._token_user_mapping = {} + for user in self._users: + for t in user["tokens"]: + token_str = t["token"] + check_token(token_str) + if token_str in self._token_user_mapping: + raise ValueError("Token already exists for another user") + self._token_user_mapping[token_str] = user["id"] + + def find_user_by_id(self, _user_id: str) -> Optional[User]: + for user in self._users: + if user["id"] == _user_id: + return user + return None + + @override + def validate_credentials(self, credentials: AbstractCredentials[T]) -> bool: + _creds = cast(Dict[str, SecretStr], credentials.get_credentials()) + if "token" not in _creds: + logger.error("Returned credentials do not contain token") + return False + return _creds["token"].get_secret_value() in self._token_user_mapping.keys() + + @override + def get_user_identity( + self, credentials: AbstractCredentials[T] + ) -> Optional[SimpleUserIdentity]: + _creds = cast(Dict[str, SecretStr], credentials.get_credentials()) + if "token" not in _creds: + logger.error("Returned credentials do not contain token") + return None + # below is just simple identity mapping and may need future work for more + # complex use cases + _user_id = self._token_user_mapping[_creds["token"].get_secret_value()] + _user = self.find_user_by_id(_user_id) + return SimpleUserIdentity( + user_id=_user_id, + tenant=_user["tenant"] if _user and "tenant" in _user else "*", + databases=_user["databases"] if _user and "databases" in _user else ["*"], + ) + + +class TokenAuthCredentials(SecretStrAbstractCredentials): + _token: SecretStr + + def __init__(self, token: SecretStr) -> None: + self._token = token + + @override + def get_credentials(self) -> Dict[str, SecretStr]: + return {"token": self._token} + + @staticmethod + def from_header( + header: str, + token_transport_header: TokenTransportHeader = TokenTransportHeader.AUTHORIZATION, + ) -> "TokenAuthCredentials": + """ + Extracts token from header and returns a TokenAuthCredentials object. + """ + if token_transport_header == TokenTransportHeader.AUTHORIZATION: + header = header.replace("Bearer ", "") + header = header.strip() + token = header + elif token_transport_header == TokenTransportHeader.X_CHROMA_TOKEN: + header = header.strip() + token = header + else: + raise ValueError( + f"Invalid token transport header: {token_transport_header}" + ) + return TokenAuthCredentials(SecretStr(token)) + + +@register_provider("token") +class TokenAuthServerProvider(ServerAuthProvider): + _credentials_provider: ServerAuthCredentialsProvider + _token_transport_header: TokenTransportHeader = TokenTransportHeader.AUTHORIZATION + + def __init__(self, system: System) -> None: + super().__init__(system) + self._settings = system.settings + system.settings.require("chroma_server_auth_credentials_provider") + self._credentials_provider = cast( + ServerAuthCredentialsProvider, + system.require( + resolve_provider( + str(system.settings.chroma_server_auth_credentials_provider), + ServerAuthCredentialsProvider, + ) + ), + ) + if system.settings.chroma_server_auth_token_transport_header: + self._token_transport_header = TokenTransportHeader[ + str(system.settings.chroma_server_auth_token_transport_header) + ] + + @trace_method("TokenAuthServerProvider.authenticate", OpenTelemetryGranularity.ALL) + @override + def authenticate( + self, request: ServerAuthenticationRequest[Any] + ) -> SimpleServerAuthenticationResponse: + try: + _auth_header = request.get_auth_info( + AuthInfoType.HEADER, self._token_transport_header.value + ) + _token_creds = TokenAuthCredentials.from_header( + _auth_header, self._token_transport_header + ) + return SimpleServerAuthenticationResponse( + self._credentials_provider.validate_credentials(_token_creds), + self._credentials_provider.get_user_identity(_token_creds), + ) + except Exception as e: + logger.error(f"TokenAuthServerProvider.authenticate failed: {repr(e)}") + return SimpleServerAuthenticationResponse(False, None) + + +@register_provider("token") +class TokenAuthClientProvider(ClientAuthProvider): + _credentials_provider: ClientAuthCredentialsProvider[Any] + _token_transport_header: TokenTransportHeader = TokenTransportHeader.AUTHORIZATION + + def __init__(self, system: System) -> None: + super().__init__(system) + self._settings = system.settings + + system.settings.require("chroma_client_auth_credentials_provider") + self._credentials_provider = system.require( + get_class( + str(system.settings.chroma_client_auth_credentials_provider), + ClientAuthCredentialsProvider, + ) + ) + _token = self._credentials_provider.get_credentials() + check_token(_token.get_secret_value()) + if system.settings.chroma_client_auth_token_transport_header: + self._token_transport_header = TokenTransportHeader[ + str(system.settings.chroma_client_auth_token_transport_header) + ] + + @trace_method("TokenAuthClientProvider.authenticate", OpenTelemetryGranularity.ALL) + @override + def authenticate(self) -> ClientAuthResponse: + _token = self._credentials_provider.get_credentials() + + return TokenAuthClientAuthResponse(_token, self._token_transport_header) diff --git a/chromadb/cli/__init__.py b/chromadb/cli/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/cli/cli.py b/chromadb/cli/cli.py new file mode 100644 index 0000000000000000000000000000000000000000..c009bd5f502a17f0525f10e6583933720819b4b2 --- /dev/null +++ b/chromadb/cli/cli.py @@ -0,0 +1,102 @@ +import logging +from typing import Optional + +import yaml +from typing_extensions import Annotated +import typer +import uvicorn +import os +import webbrowser + +from chromadb.cli.utils import set_log_file_path + +app = typer.Typer() + +_logo = """ + \033[38;5;069m((((((((( \033[38;5;203m(((((\033[38;5;220m#### + \033[38;5;069m(((((((((((((\033[38;5;203m(((((((((\033[38;5;220m######### + \033[38;5;069m(((((((((((((\033[38;5;203m(((((((((((\033[38;5;220m########### + \033[38;5;069m((((((((((((((\033[38;5;203m((((((((((((\033[38;5;220m############ + \033[38;5;069m(((((((((((((\033[38;5;203m((((((((((((((\033[38;5;220m############# + \033[38;5;069m(((((((((((((\033[38;5;203m((((((((((((((\033[38;5;220m############# + \033[38;5;069m((((((((((((\033[38;5;203m(((((((((((((\033[38;5;220m############## + \033[38;5;069m((((((((((((\033[38;5;203m((((((((((((\033[38;5;220m############## + \033[38;5;069m((((((((((\033[38;5;203m(((((((((((\033[38;5;220m############# + \033[38;5;069m((((((((\033[38;5;203m((((((((\033[38;5;220m############## + \033[38;5;069m(((((\033[38;5;203m(((( \033[38;5;220m#########\033[0m + + """ + + +@app.command() # type: ignore +def run( + path: str = typer.Option( + "./chroma_data", help="The path to the file or directory." + ), + host: Annotated[ + Optional[str], typer.Option(help="The host to listen to. Default: localhost") + ] = "localhost", + log_path: Annotated[ + Optional[str], typer.Option(help="The path to the log file.") + ] = "chroma.log", + port: int = typer.Option(8000, help="The port to run the server on."), + test: bool = typer.Option(False, help="Test mode.", show_envvar=False, hidden=True), +) -> None: + """Run a chroma server""" + + print("\033[1m") # Bold logo + print(_logo) + print("\033[1m") # Bold + print("Running Chroma") + print("\033[0m") # Reset + + typer.echo(f"\033[1mSaving data to\033[0m: \033[32m{path}\033[0m") + typer.echo( + f"\033[1mConnect to chroma at\033[0m: \033[32mhttp://{host}:{port}\033[0m" + ) + typer.echo( + "\033[1mGetting started guide\033[0m: https://docs.trychroma.com/getting-started\n\n" + ) + + # set ENV variable for PERSIST_DIRECTORY to path + os.environ["IS_PERSISTENT"] = "True" + os.environ["PERSIST_DIRECTORY"] = path + os.environ["CHROMA_SERVER_NOFILE"] = "65535" + + # get the path where chromadb is installed + chromadb_path = os.path.dirname(os.path.realpath(__file__)) + + # this is the path of the CLI, we want to move up one directory + chromadb_path = os.path.dirname(chromadb_path) + log_config = set_log_file_path(f"{chromadb_path}/log_config.yml", f"{log_path}") + config = { + "app": "chromadb.app:app", + "host": host, + "port": port, + "workers": 1, + "log_config": log_config, # Pass the modified log_config dictionary + "timeout_keep_alive": 30, + } + + if test: + return + + uvicorn.run(**config) + + +@app.command() # type: ignore +def help() -> None: + """Opens help url in your browser""" + + webbrowser.open("https://discord.gg/MMeYNTmh3x") + + +@app.command() # type: ignore +def docs() -> None: + """Opens docs url in your browser""" + + webbrowser.open("https://docs.trychroma.com") + + +if __name__ == "__main__": + app() diff --git a/chromadb/cli/utils.py b/chromadb/cli/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..383715b1b723a63b439caeb66b4d8426b538194b --- /dev/null +++ b/chromadb/cli/utils.py @@ -0,0 +1,17 @@ +from typing import Any, Dict + +import yaml + + +def set_log_file_path( + log_config_path: str, new_filename: str = "chroma.log" +) -> Dict[str, Any]: + """This works with the standard log_config.yml file. + It will not work with custom log configs that may use different handlers""" + with open(f"{log_config_path}", "r") as file: + log_config = yaml.safe_load(file) + for handler in log_config["handlers"].values(): + if handler.get("class") == "logging.handlers.RotatingFileHandler": + handler["filename"] = new_filename + + return log_config diff --git a/chromadb/config.py b/chromadb/config.py new file mode 100644 index 0000000000000000000000000000000000000000..e9ceffc5dd02b075b68fff3a3b52643e4685a928 --- /dev/null +++ b/chromadb/config.py @@ -0,0 +1,432 @@ +import importlib +import inspect +import logging +import os +from abc import ABC +from graphlib import TopologicalSorter +from typing import Optional, List, Any, Dict, Set, Iterable, Union +from typing import Type, TypeVar, cast + +from overrides import EnforceOverrides +from overrides import override +from typing_extensions import Literal +import platform + + +in_pydantic_v2 = False +try: + from pydantic import BaseSettings +except ImportError: + in_pydantic_v2 = True + from pydantic.v1 import BaseSettings + from pydantic.v1 import validator + +if not in_pydantic_v2: + from pydantic import validator # type: ignore # noqa + +# The thin client will have a flag to control which implementations to use +is_thin_client = False +try: + from chromadb.is_thin_client import is_thin_client # type: ignore +except ImportError: + is_thin_client = False + +logger = logging.getLogger(__name__) + +LEGACY_ERROR = """\033[91mYou are using a deprecated configuration of Chroma. + +\033[94mIf you do not have data you wish to migrate, you only need to change how you construct +your Chroma client. Please see the "New Clients" section of https://docs.trychroma.com/migration. +________________________________________________________________________________________________ + +If you do have data you wish to migrate, we have a migration tool you can use in order to +migrate your data to the new Chroma architecture. +Please `pip install chroma-migrate` and run `chroma-migrate` to migrate your data and then +change how you construct your Chroma client. + +See https://docs.trychroma.com/migration for more information or join our discord at https://discord.gg/8g5FESbj for help!\033[0m""" + +_legacy_config_keys = { + "chroma_db_impl", +} + +_legacy_config_values = { + "duckdb", + "duckdb+parquet", + "clickhouse", + "local", + "rest", + "chromadb.db.duckdb.DuckDB", + "chromadb.db.duckdb.PersistentDuckDB", + "chromadb.db.clickhouse.Clickhouse", + "chromadb.api.local.LocalAPI", +} + +# TODO: Don't use concrete types here to avoid circular deps. Strings are fine for right here! +_abstract_type_keys: Dict[str, str] = { + # NOTE: this is to support legacy api construction. Use ServerAPI instead + "chromadb.api.API": "chroma_api_impl", + "chromadb.api.ServerAPI": "chroma_api_impl", + "chromadb.telemetry.product.ProductTelemetryClient": "chroma_product_telemetry_impl", + "chromadb.ingest.Producer": "chroma_producer_impl", + "chromadb.ingest.Consumer": "chroma_consumer_impl", + "chromadb.ingest.CollectionAssignmentPolicy": "chroma_collection_assignment_policy_impl", # noqa + "chromadb.db.system.SysDB": "chroma_sysdb_impl", + "chromadb.segment.SegmentManager": "chroma_segment_manager_impl", + "chromadb.segment.distributed.SegmentDirectory": "chroma_segment_directory_impl", + "chromadb.segment.distributed.MemberlistProvider": "chroma_memberlist_provider_impl", +} + +DEFAULT_TENANT = "default_tenant" +DEFAULT_DATABASE = "default_database" + +class Settings(BaseSettings): # type: ignore + environment: str = "" + + # Legacy config has to be kept around because pydantic will error + # on nonexisting keys + chroma_db_impl: Optional[str] = None + # Can be "chromadb.api.segment.SegmentAPI" or "chromadb.api.fastapi.FastAPI" + chroma_api_impl: str = "chromadb.api.segment.SegmentAPI" + chroma_product_telemetry_impl: str = "chromadb.telemetry.product.posthog.Posthog" + # Required for backwards compatibility + chroma_telemetry_impl: str = chroma_product_telemetry_impl + + # New architecture components + chroma_sysdb_impl: str = "chromadb.db.impl.sqlite.SqliteDB" + chroma_producer_impl: str = "chromadb.db.impl.sqlite.SqliteDB" + chroma_consumer_impl: str = "chromadb.db.impl.sqlite.SqliteDB" + chroma_segment_manager_impl: str = ( + "chromadb.segment.impl.manager.local.LocalSegmentManager" + ) + + # Distributed architecture specific components + chroma_segment_directory_impl: str = "chromadb.segment.impl.distributed.segment_directory.RendezvousHashSegmentDirectory" + chroma_memberlist_provider_impl: str = "chromadb.segment.impl.distributed.segment_directory.CustomResourceMemberlistProvider" + chroma_collection_assignment_policy_impl: str = ( + "chromadb.ingest.impl.simple_policy.SimpleAssignmentPolicy" + ) + worker_memberlist_name: str = "worker-memberlist" + chroma_coordinator_host = "localhost" + + tenant_id: str = "default" + topic_namespace: str = "default" + + is_persistent: bool = False + persist_directory: str = "./chroma" + + chroma_memory_limit_bytes: int = 0 + chroma_segment_cache_policy: Optional[str] = None + + chroma_server_host: Optional[str] = None + chroma_server_headers: Optional[Dict[str, str]] = None + chroma_server_http_port: Optional[str] = None + chroma_server_ssl_enabled: Optional[bool] = False + # the below config value is only applicable to Chroma HTTP clients + chroma_server_ssl_verify: Optional[Union[bool, str]] = None + chroma_server_api_default_path: Optional[str] = "/api/v1" + chroma_server_grpc_port: Optional[str] = None + # eg ["http://localhost:3000"] + chroma_server_cors_allow_origins: List[str] = [] + + @validator("chroma_server_nofile", pre=True, always=True, allow_reuse=True) + def empty_str_to_none(cls, v: str) -> Optional[str]: + if type(v) is str and v.strip() == "": + return None + return v + + chroma_server_nofile: Optional[int] = None + + pulsar_broker_url: Optional[str] = None + pulsar_admin_port: Optional[str] = "8080" + pulsar_broker_port: Optional[str] = "6650" + + chroma_server_auth_provider: Optional[str] = None + + @validator("chroma_server_auth_provider", pre=True, always=True, allow_reuse=True) + def chroma_server_auth_provider_non_empty( + cls: Type["Settings"], v: str + ) -> Optional[str]: + if v and not v.strip(): + raise ValueError( + "chroma_server_auth_provider cannot be empty or just whitespace" + ) + return v + + chroma_server_auth_configuration_provider: Optional[str] = None + chroma_server_auth_configuration_file: Optional[str] = None + chroma_server_auth_credentials_provider: Optional[str] = None + chroma_server_auth_credentials_file: Optional[str] = None + chroma_server_auth_credentials: Optional[str] = None + + @validator( + "chroma_server_auth_credentials_file", pre=True, always=True, allow_reuse=True + ) + def chroma_server_auth_credentials_file_non_empty_file_exists( + cls: Type["Settings"], v: str + ) -> Optional[str]: + if v and not v.strip(): + raise ValueError( + "chroma_server_auth_credentials_file cannot be empty or just whitespace" + ) + if v and not os.path.isfile(os.path.join(v)): + raise ValueError( + f"chroma_server_auth_credentials_file [{v}] does not exist" + ) + return v + + chroma_client_auth_provider: Optional[str] = None + chroma_server_auth_ignore_paths: Dict[str, List[str]] = { + "/api/v1": ["GET"], + "/api/v1/heartbeat": ["GET"], + "/api/v1/version": ["GET"], + } + + chroma_client_auth_credentials_provider: Optional[ + str + ] = "chromadb.auth.providers.ConfigurationClientAuthCredentialsProvider" + chroma_client_auth_protocol_adapter: Optional[ + str + ] = "chromadb.auth.providers.RequestsClientAuthProtocolAdapter" + chroma_client_auth_credentials_file: Optional[str] = None + chroma_client_auth_credentials: Optional[str] = None + chroma_client_auth_token_transport_header: Optional[str] = None + chroma_server_auth_token_transport_header: Optional[str] = None + + chroma_server_authz_provider: Optional[str] = None + + chroma_server_authz_ignore_paths: Dict[str, List[str]] = { + "/api/v1": ["GET"], + "/api/v1/heartbeat": ["GET"], + "/api/v1/version": ["GET"], + } + chroma_server_authz_config_file: Optional[str] = None + + chroma_server_authz_config: Optional[Dict[str, Any]] = None + + @validator( + "chroma_server_authz_config_file", pre=True, always=True, allow_reuse=True + ) + def chroma_server_authz_config_file_non_empty_file_exists( + cls: Type["Settings"], v: str + ) -> Optional[str]: + if v and not v.strip(): + raise ValueError( + "chroma_server_authz_config_file cannot be empty or just whitespace" + ) + if v and not os.path.isfile(os.path.join(v)): + raise ValueError(f"chroma_server_authz_config_file [{v}] does not exist") + return v + + chroma_server_authz_config_provider: Optional[ + str + ] = "chromadb.auth.authz.LocalUserConfigAuthorizationConfigurationProvider" + + # TODO comment + chroma_overwrite_singleton_tenant_database_access_from_auth: bool = False + + anonymized_telemetry: bool = True + + chroma_otel_collection_endpoint: Optional[str] = "" + chroma_otel_service_name: Optional[str] = "chromadb" + chroma_otel_collection_headers: Dict[str, str] = {} + chroma_otel_granularity: Optional[str] = None + + allow_reset: bool = False + + migrations: Literal["none", "validate", "apply"] = "apply" + # you cannot change the hash_algorithm after migrations have already been applied once + # this is intended to be a first-time setup configuration + migrations_hash_algorithm: Literal["md5", "sha256"] = "md5" + + def require(self, key: str) -> Any: + """Return the value of a required config key, or raise an exception if it is not + set""" + val = self[key] + if val is None: + raise ValueError(f"Missing required config value '{key}'") + return val + + def __getitem__(self, key: str) -> Any: + val = getattr(self, key) + # Error on legacy config values + if isinstance(val, str) and val in _legacy_config_values: + raise ValueError(LEGACY_ERROR) + return val + + class Config: + env_file = ".env" + env_file_encoding = "utf-8" + + +T = TypeVar("T", bound="Component") + + +class Component(ABC, EnforceOverrides): + _dependencies: Set["Component"] + _system: "System" + _running: bool + + def __init__(self, system: "System"): + self._dependencies = set() + self._system = system + self._running = False + + def require(self, type: Type[T]) -> T: + """Get a Component instance of the given type, and register as a dependency of + that instance.""" + inst = self._system.instance(type) + self._dependencies.add(inst) + return inst + + def dependencies(self) -> Set["Component"]: + """Return the full set of components this component depends on.""" + return self._dependencies + + def stop(self) -> None: + """Idempotently stop this component's execution and free all associated + resources.""" + logger.debug(f"Stopping component {self.__class__.__name__}") + self._running = False + + def start(self) -> None: + """Idempotently start this component's execution""" + logger.debug(f"Starting component {self.__class__.__name__}") + self._running = True + + def reset_state(self) -> None: + """Reset this component's state to its initial blank state. Only intended to be + called from tests.""" + logger.debug(f"Resetting component {self.__class__.__name__}") + + +class System(Component): + settings: Settings + _instances: Dict[Type[Component], Component] + + def __init__(self, settings: Settings): + if is_thin_client: + # The thin client is a system with only the API component + if settings["chroma_api_impl"] != "chromadb.api.fastapi.FastAPI": + raise RuntimeError( + "Chroma is running in http-only client mode, and can only be run with 'chromadb.api.fastapi.FastAPI' as the chroma_api_impl. \ + see https://docs.trychroma.com/usage-guide?lang=py#using-the-python-http-only-client for more information." + ) + # Validate settings don't contain any legacy config values + for key in _legacy_config_keys: + if settings[key] is not None: + raise ValueError(LEGACY_ERROR) + + if settings["chroma_segment_cache_policy"] is not None and settings["chroma_segment_cache_policy"] != "LRU": + logger.error( + f"Failed to set chroma_segment_cache_policy: Only LRU is available." + ) + if settings["chroma_memory_limit_bytes"] == 0: + logger.error( + f"Failed to set chroma_segment_cache_policy: chroma_memory_limit_bytes is require." + ) + + # Apply the nofile limit if set + if settings["chroma_server_nofile"] is not None: + if platform.system() != "Windows": + import resource + + curr_soft, curr_hard = resource.getrlimit(resource.RLIMIT_NOFILE) + desired_soft = settings["chroma_server_nofile"] + # Validate + if desired_soft > curr_hard: + logging.warning( + f"chroma_server_nofile cannot be set to a value greater than the current hard limit of {curr_hard}. Keeping soft limit at {curr_soft}" + ) + # Apply + elif desired_soft > curr_soft: + try: + resource.setrlimit( + resource.RLIMIT_NOFILE, (desired_soft, curr_hard) + ) + logger.info(f"Set chroma_server_nofile to {desired_soft}") + except Exception as e: + logger.error( + f"Failed to set chroma_server_nofile to {desired_soft}: {e} nofile soft limit will remain at {curr_soft}" + ) + # Don't apply if reducing the limit + elif desired_soft < curr_soft: + logger.warning( + f"chroma_server_nofile is set to {desired_soft}, but this is less than current soft limit of {curr_soft}. chroma_server_nofile will not be set." + ) + else: + logger.warning( + "chroma_server_nofile is not supported on Windows. chroma_server_nofile will not be set." + ) + + self.settings = settings + self._instances = {} + super().__init__(self) + + def instance(self, type: Type[T]) -> T: + """Return an instance of the component type specified. If the system is running, + the component will be started as well.""" + + if inspect.isabstract(type): + type_fqn = get_fqn(type) + if type_fqn not in _abstract_type_keys: + raise ValueError(f"Cannot instantiate abstract type: {type}") + key = _abstract_type_keys[type_fqn] + fqn = self.settings.require(key) + type = get_class(fqn, type) + + if type not in self._instances: + impl = type(self) + self._instances[type] = impl + if self._running: + impl.start() + + inst = self._instances[type] + return cast(T, inst) + + def components(self) -> Iterable[Component]: + """Return the full set of all components and their dependencies in dependency + order.""" + sorter: TopologicalSorter[Component] = TopologicalSorter() + for component in self._instances.values(): + sorter.add(component, *component.dependencies()) + + return sorter.static_order() + + @override + def start(self) -> None: + super().start() + for component in self.components(): + component.start() + + @override + def stop(self) -> None: + super().stop() + for component in reversed(list(self.components())): + component.stop() + + @override + def reset_state(self) -> None: + """Reset the state of this system and all constituents in reverse dependency order""" + if not self.settings.allow_reset: + raise ValueError( + "Resetting is not allowed by this configuration (to enable it, set `allow_reset` to `True` in your Settings() or include `ALLOW_RESET=TRUE` in your environment variables)" + ) + for component in reversed(list(self.components())): + component.reset_state() + + +C = TypeVar("C") + + +def get_class(fqn: str, type: Type[C]) -> Type[C]: + """Given a fully qualifed class name, import the module and return the class""" + module_name, class_name = fqn.rsplit(".", 1) + module = importlib.import_module(module_name) + cls = getattr(module, class_name) + return cast(Type[C], cls) + + +def get_fqn(cls: Type[object]) -> str: + """Given a class, return its fully qualified name""" + return f"{cls.__module__}.{cls.__name__}" diff --git a/chromadb/db/__init__.py b/chromadb/db/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..157277b27498d100b21af0cd3e38175f07090e7e --- /dev/null +++ b/chromadb/db/__init__.py @@ -0,0 +1,123 @@ +from abc import abstractmethod +from typing import List, Sequence, Optional, Tuple +from uuid import UUID +from chromadb.api.types import ( + Embeddings, + Documents, + IDs, + Metadatas, + Metadata, + Where, + WhereDocument, +) +from chromadb.config import Component + + +class DB(Component): + @abstractmethod + def create_collection( + self, + name: str, + metadata: Optional[Metadata] = None, + get_or_create: bool = False, + ) -> Sequence: # type: ignore + pass + + @abstractmethod + def get_collection(self, name: str) -> Sequence: # type: ignore + pass + + @abstractmethod + def list_collections( + self, limit: Optional[int] = None, offset: Optional[int] = None + ) -> Sequence: # type: ignore + pass + + @abstractmethod + def count_collections(self) -> int: + pass + + @abstractmethod + def update_collection( + self, + id: UUID, + new_name: Optional[str] = None, + new_metadata: Optional[Metadata] = None, + ) -> None: + pass + + @abstractmethod + def delete_collection(self, name: str) -> None: + pass + + @abstractmethod + def get_collection_uuid_from_name(self, collection_name: str) -> UUID: + pass + + @abstractmethod + def add( + self, + collection_uuid: UUID, + embeddings: Embeddings, + metadatas: Optional[Metadatas], + documents: Optional[Documents], + ids: List[str], + ) -> List[UUID]: + pass + + @abstractmethod + def get( + self, + where: Where = {}, + collection_name: Optional[str] = None, + collection_uuid: Optional[UUID] = None, + ids: Optional[IDs] = None, + sort: Optional[str] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + where_document: WhereDocument = {}, + columns: Optional[List[str]] = None, + ) -> Sequence: # type: ignore + pass + + @abstractmethod + def update( + self, + collection_uuid: UUID, + ids: IDs, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, + ) -> bool: + pass + + @abstractmethod + def count(self, collection_id: UUID) -> int: + pass + + @abstractmethod + def delete( + self, + where: Where = {}, + collection_uuid: Optional[UUID] = None, + ids: Optional[IDs] = None, + where_document: WhereDocument = {}, + ) -> List[str]: + pass + + @abstractmethod + def get_nearest_neighbors( + self, + collection_uuid: UUID, + where: Where = {}, + embeddings: Optional[Embeddings] = None, + n_results: int = 10, + where_document: WhereDocument = {}, + ) -> Tuple[List[List[UUID]], List[List[float]]]: + pass + + @abstractmethod + def get_by_ids( + self, uuids: List[UUID], columns: Optional[List[str]] = None + ) -> Sequence: # type: ignore + pass diff --git a/chromadb/db/base.py b/chromadb/db/base.py new file mode 100644 index 0000000000000000000000000000000000000000..b7c991b6155072fae9264c31fc2a3f5363741f8e --- /dev/null +++ b/chromadb/db/base.py @@ -0,0 +1,192 @@ +from typing import Any, Optional, Sequence, Tuple, Type +from types import TracebackType +from typing_extensions import Protocol, Self, Literal +from abc import ABC, abstractmethod +from threading import local +from overrides import override, EnforceOverrides +import pypika +import pypika.queries +from chromadb.config import System, Component +from uuid import UUID +from itertools import islice, count + + +class NotFoundError(Exception): + """Raised when a delete or update operation affects no rows""" + + pass + + +class UniqueConstraintError(Exception): + """Raised when an insert operation would violate a unique constraint""" + + pass + + +class Cursor(Protocol): + """Reifies methods we use from a DBAPI2 Cursor since DBAPI2 is not typed.""" + + def execute(self, sql: str, params: Optional[Tuple[Any, ...]] = None) -> Self: + ... + + def executescript(self, script: str) -> Self: + ... + + def executemany( + self, sql: str, params: Optional[Sequence[Tuple[Any, ...]]] = None + ) -> Self: + ... + + def fetchone(self) -> Tuple[Any, ...]: + ... + + def fetchall(self) -> Sequence[Tuple[Any, ...]]: + ... + + +class TxWrapper(ABC, EnforceOverrides): + """Wrapper class for DBAPI 2.0 Connection objects, with which clients can implement transactions. + Makes two guarantees that basic DBAPI 2.0 connections do not: + + - __enter__ returns a Cursor object consistently (instead of a Connection like some do) + - Always re-raises an exception if one was thrown from the body + """ + + @abstractmethod + def __enter__(self) -> Cursor: + pass + + @abstractmethod + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_value: Optional[BaseException], + traceback: Optional[TracebackType], + ) -> Literal[False]: + pass + + +class SqlDB(Component): + """DBAPI 2.0 interface wrapper to ensure consistent behavior between implementations""" + + def __init__(self, system: System): + super().__init__(system) + + @abstractmethod + def tx(self) -> TxWrapper: + """Return a transaction wrapper""" + pass + + @staticmethod + @abstractmethod + def querybuilder() -> Type[pypika.Query]: + """Return a PyPika Query builder of an appropriate subtype for this database + implementation (see + https://pypika.readthedocs.io/en/latest/3_advanced.html#handling-different-database-platforms) + """ + pass + + @staticmethod + @abstractmethod + def parameter_format() -> str: + """Return the appropriate parameter format for this database implementation. + Will be called with str.format(i) where i is the numeric index of the parameter. + """ + pass + + @staticmethod + @abstractmethod + def uuid_to_db(uuid: Optional[UUID]) -> Optional[Any]: + """Convert a UUID to a value that can be passed to the DB driver""" + pass + + @staticmethod + @abstractmethod + def uuid_from_db(value: Optional[Any]) -> Optional[UUID]: + """Convert a value from the DB driver to a UUID""" + pass + + @staticmethod + @abstractmethod + def unique_constraint_error() -> Type[BaseException]: + """Return the exception type that the DB raises when a unique constraint is + violated""" + pass + + def param(self, idx: int) -> pypika.Parameter: + """Return a PyPika Parameter object for the given index""" + return pypika.Parameter(self.parameter_format().format(idx)) + + +_context = local() + + +class ParameterValue(pypika.Parameter): # type: ignore + """ + Wrapper class for PyPika paramters that allows the values for Parameters + to be expressed inline while building a query. See get_sql() for + detailed usage information. + """ + + def __init__(self, value: Any): + self.value = value + + @override + def get_sql(self, **kwargs: Any) -> str: + if isinstance(self.value, (list, tuple)): + _context.values.extend(self.value) + indexes = islice(_context.generator, len(self.value)) + placeholders = ", ".join(_context.formatstr.format(i) for i in indexes) + val = f"({placeholders})" + else: + _context.values.append(self.value) + val = _context.formatstr.format(next(_context.generator)) + + return str(val) + + +def get_sql( + query: pypika.queries.QueryBuilder, formatstr: str = "?" +) -> Tuple[str, Tuple[Any, ...]]: + """ + Wrapper for pypika's get_sql method that allows the values for Parameters + to be expressed inline while building a query, and that returns a tuple of the + SQL string and parameters. This makes it easier to construct complex queries + programmatically and automatically matches up the generated SQL with the required + parameter vector. + + Doing so requires using the ParameterValue class defined in this module instead + of the base pypika.Parameter class. + + Usage Example: + + q = ( + pypika.Query().from_("table") + .select("col1") + .where("col2"==ParameterValue("foo")) + .where("col3"==ParameterValue("bar")) + ) + + sql, params = get_sql(q) + + cursor.execute(sql, params) + + Note how it is not necessary to construct the parameter vector manually... it + will always be generated with the parameter values in the same order as emitted + SQL string. + + The format string should match the parameter format for the database being used. + It will be called with str.format(i) where i is the numeric index of the parameter. + For example, Postgres requires parameters like `:1`, `:2`, etc. so the format string + should be `":{}"`. + + See https://pypika.readthedocs.io/en/latest/2_tutorial.html#parametrized-queries for more + information on parameterized queries in PyPika. + """ + + _context.values = [] + _context.generator = count(1) + _context.formatstr = formatstr + sql = query.get_sql() + params = tuple(_context.values) + return sql, params diff --git a/chromadb/db/impl/__init__.py b/chromadb/db/impl/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/db/impl/grpc/client.py b/chromadb/db/impl/grpc/client.py new file mode 100644 index 0000000000000000000000000000000000000000..32b3b2da164d34439e8f9f492060c6baa42ab7a7 --- /dev/null +++ b/chromadb/db/impl/grpc/client.py @@ -0,0 +1,310 @@ +from typing import List, Optional, Sequence, Tuple, Union, cast +from uuid import UUID +from overrides import overrides +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, System +from chromadb.db.base import NotFoundError, UniqueConstraintError +from chromadb.db.system import SysDB +from chromadb.proto.convert import ( + from_proto_collection, + from_proto_segment, + to_proto_update_metadata, + to_proto_segment, + to_proto_segment_scope, +) +from chromadb.proto.coordinator_pb2 import ( + CreateCollectionRequest, + CreateDatabaseRequest, + CreateSegmentRequest, + CreateTenantRequest, + DeleteCollectionRequest, + DeleteSegmentRequest, + GetCollectionsRequest, + GetCollectionsResponse, + GetDatabaseRequest, + GetSegmentsRequest, + GetTenantRequest, + UpdateCollectionRequest, + UpdateSegmentRequest, +) +from chromadb.proto.coordinator_pb2_grpc import SysDBStub +from chromadb.types import ( + Collection, + Database, + Metadata, + OptionalArgument, + Segment, + SegmentScope, + Tenant, + Unspecified, + UpdateMetadata, +) +from google.protobuf.empty_pb2 import Empty +import grpc + + +class GrpcSysDB(SysDB): + """A gRPC implementation of the SysDB. In the distributed system, the SysDB is also + called the 'Coordinator'. This implementation is used by Chroma frontend servers + to call a remote SysDB (Coordinator) service.""" + + _sys_db_stub: SysDBStub + _channel: grpc.Channel + _coordinator_url: str + _coordinator_port: int + + def __init__(self, system: System): + self._coordinator_url = system.settings.require("chroma_coordinator_host") + # TODO: break out coordinator_port into a separate setting? + self._coordinator_port = system.settings.require("chroma_server_grpc_port") + return super().__init__(system) + + @overrides + def start(self) -> None: + # TODO: add retry policy here + self._channel = grpc.insecure_channel( + f"{self._coordinator_url}:{self._coordinator_port}" + ) + self._sys_db_stub = SysDBStub(self._channel) # type: ignore + return super().start() + + @overrides + def stop(self) -> None: + self._channel.close() + return super().stop() + + @overrides + def reset_state(self) -> None: + self._sys_db_stub.ResetState(Empty()) + return super().reset_state() + + @overrides + def create_database( + self, id: UUID, name: str, tenant: str = DEFAULT_TENANT + ) -> None: + request = CreateDatabaseRequest(id=id.hex, name=name, tenant=tenant) + response = self._sys_db_stub.CreateDatabase(request) + if response.status.code == 409: + raise UniqueConstraintError() + + @overrides + def get_database(self, name: str, tenant: str = DEFAULT_TENANT) -> Database: + request = GetDatabaseRequest(name=name, tenant=tenant) + response = self._sys_db_stub.GetDatabase(request) + if response.status.code == 404: + raise NotFoundError() + return Database( + id=UUID(hex=response.database.id), + name=response.database.name, + tenant=response.database.tenant, + ) + + @overrides + def create_tenant(self, name: str) -> None: + request = CreateTenantRequest(name=name) + response = self._sys_db_stub.CreateTenant(request) + if response.status.code == 409: + raise UniqueConstraintError() + + @overrides + def get_tenant(self, name: str) -> Tenant: + request = GetTenantRequest(name=name) + response = self._sys_db_stub.GetTenant(request) + if response.status.code == 404: + raise NotFoundError() + return Tenant( + name=response.tenant.name, + ) + + @overrides + def create_segment(self, segment: Segment) -> None: + proto_segment = to_proto_segment(segment) + request = CreateSegmentRequest( + segment=proto_segment, + ) + response = self._sys_db_stub.CreateSegment(request) + if response.status.code == 409: + raise UniqueConstraintError() + + @overrides + def delete_segment(self, id: UUID) -> None: + request = DeleteSegmentRequest( + id=id.hex, + ) + response = self._sys_db_stub.DeleteSegment(request) + if response.status.code == 404: + raise NotFoundError() + + @overrides + def get_segments( + self, + id: Optional[UUID] = None, + type: Optional[str] = None, + scope: Optional[SegmentScope] = None, + topic: Optional[str] = None, + collection: Optional[UUID] = None, + ) -> Sequence[Segment]: + request = GetSegmentsRequest( + id=id.hex if id else None, + type=type, + scope=to_proto_segment_scope(scope) if scope else None, + topic=topic, + collection=collection.hex if collection else None, + ) + response = self._sys_db_stub.GetSegments(request) + results: List[Segment] = [] + for proto_segment in response.segments: + segment = from_proto_segment(proto_segment) + results.append(segment) + return results + + @overrides + def update_segment( + self, + id: UUID, + topic: OptionalArgument[Optional[str]] = Unspecified(), + collection: OptionalArgument[Optional[UUID]] = Unspecified(), + metadata: OptionalArgument[Optional[UpdateMetadata]] = Unspecified(), + ) -> None: + write_topic = None + if topic != Unspecified(): + write_topic = cast(Union[str, None], topic) + + write_collection = None + if collection != Unspecified(): + write_collection = cast(Union[UUID, None], collection) + + write_metadata = None + if metadata != Unspecified(): + write_metadata = cast(Union[UpdateMetadata, None], metadata) + + request = UpdateSegmentRequest( + id=id.hex, + topic=write_topic, + collection=write_collection.hex if write_collection else None, + metadata=to_proto_update_metadata(write_metadata) + if write_metadata + else None, + ) + + if topic is None: + request.ClearField("topic") + request.reset_topic = True + + if collection is None: + request.ClearField("collection") + request.reset_collection = True + + if metadata is None: + request.ClearField("metadata") + request.reset_metadata = True + + self._sys_db_stub.UpdateSegment(request) + + @overrides + def create_collection( + self, + id: UUID, + name: str, + metadata: Optional[Metadata] = None, + dimension: Optional[int] = None, + get_or_create: bool = False, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Tuple[Collection, bool]: + request = CreateCollectionRequest( + id=id.hex, + name=name, + metadata=to_proto_update_metadata(metadata) if metadata else None, + dimension=dimension, + get_or_create=get_or_create, + tenant=tenant, + database=database, + ) + response = self._sys_db_stub.CreateCollection(request) + if response.status.code == 409: + raise UniqueConstraintError() + collection = from_proto_collection(response.collection) + return collection, response.created + + @overrides + def delete_collection( + self, id: UUID, tenant: str = DEFAULT_TENANT, database: str = DEFAULT_DATABASE + ) -> None: + request = DeleteCollectionRequest( + id=id.hex, + tenant=tenant, + database=database, + ) + response = self._sys_db_stub.DeleteCollection(request) + if response.status.code == 404: + raise NotFoundError() + + @overrides + def get_collections( + self, + id: Optional[UUID] = None, + topic: Optional[str] = None, + name: Optional[str] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + limit: Optional[int] = None, + offset: Optional[int] = None, + ) -> Sequence[Collection]: + # TODO: implement limit and offset in the gRPC service + request = GetCollectionsRequest( + id=id.hex if id else None, + topic=topic, + name=name, + tenant=tenant, + database=database, + ) + response: GetCollectionsResponse = self._sys_db_stub.GetCollections(request) + results: List[Collection] = [] + for collection in response.collections: + results.append(from_proto_collection(collection)) + return results + + @overrides + def update_collection( + self, + id: UUID, + topic: OptionalArgument[str] = Unspecified(), + name: OptionalArgument[str] = Unspecified(), + dimension: OptionalArgument[Optional[int]] = Unspecified(), + metadata: OptionalArgument[Optional[UpdateMetadata]] = Unspecified(), + ) -> None: + write_topic = None + if topic != Unspecified(): + write_topic = cast(str, topic) + + write_name = None + if name != Unspecified(): + write_name = cast(str, name) + + write_dimension = None + if dimension != Unspecified(): + write_dimension = cast(Union[int, None], dimension) + + write_metadata = None + if metadata != Unspecified(): + write_metadata = cast(Union[UpdateMetadata, None], metadata) + + request = UpdateCollectionRequest( + id=id.hex, + topic=write_topic, + name=write_name, + dimension=write_dimension, + metadata=to_proto_update_metadata(write_metadata) + if write_metadata + else None, + ) + if metadata is None: + request.ClearField("metadata") + request.reset_metadata = True + + response = self._sys_db_stub.UpdateCollection(request) + if response.status.code == 404: + raise NotFoundError() + + def reset_and_wait_for_ready(self) -> None: + self._sys_db_stub.ResetState(Empty(), wait_for_ready=True) diff --git a/chromadb/db/impl/grpc/server.py b/chromadb/db/impl/grpc/server.py new file mode 100644 index 0000000000000000000000000000000000000000..257aa80f0e782c6d19589cce408c0e7a3242aa43 --- /dev/null +++ b/chromadb/db/impl/grpc/server.py @@ -0,0 +1,452 @@ +from concurrent import futures +from typing import Any, Dict, cast +from uuid import UUID +from overrides import overrides +from chromadb.ingest import CollectionAssignmentPolicy +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Component, System +from chromadb.proto.convert import ( + from_proto_metadata, + from_proto_update_metadata, + from_proto_segment, + from_proto_segment_scope, + to_proto_collection, + to_proto_segment, +) +import chromadb.proto.chroma_pb2 as proto +from chromadb.proto.coordinator_pb2 import ( + CreateCollectionRequest, + CreateCollectionResponse, + CreateDatabaseRequest, + CreateSegmentRequest, + DeleteCollectionRequest, + DeleteSegmentRequest, + GetCollectionsRequest, + GetCollectionsResponse, + GetDatabaseRequest, + GetDatabaseResponse, + GetSegmentsRequest, + GetSegmentsResponse, + GetTenantRequest, + GetTenantResponse, + UpdateCollectionRequest, + UpdateSegmentRequest, +) +from chromadb.proto.coordinator_pb2_grpc import ( + SysDBServicer, + add_SysDBServicer_to_server, +) +import grpc +from google.protobuf.empty_pb2 import Empty +from chromadb.types import Collection, Metadata, Segment + + +class GrpcMockSysDB(SysDBServicer, Component): + """A mock sysdb implementation that can be used for testing the grpc client. It stores + state in simple python data structures instead of a database.""" + + _server: grpc.Server + _server_port: int + _assignment_policy: CollectionAssignmentPolicy + _segments: Dict[str, Segment] = {} + _tenants_to_databases_to_collections: Dict[ + str, Dict[str, Dict[str, Collection]] + ] = {} + _tenants_to_database_to_id: Dict[str, Dict[str, UUID]] = {} + + def __init__(self, system: System): + self._server_port = system.settings.require("chroma_server_grpc_port") + self._assignment_policy = system.instance(CollectionAssignmentPolicy) + return super().__init__(system) + + @overrides + def start(self) -> None: + self._server = grpc.server(futures.ThreadPoolExecutor(max_workers=10)) + add_SysDBServicer_to_server(self, self._server) # type: ignore + self._server.add_insecure_port(f"[::]:{self._server_port}") + self._server.start() + return super().start() + + @overrides + def stop(self) -> None: + self._server.stop(0) + return super().stop() + + @overrides + def reset_state(self) -> None: + self._segments = {} + self._tenants_to_databases_to_collections = {} + # Create defaults + self._tenants_to_databases_to_collections[DEFAULT_TENANT] = {} + self._tenants_to_databases_to_collections[DEFAULT_TENANT][DEFAULT_DATABASE] = {} + self._tenants_to_database_to_id[DEFAULT_TENANT] = {} + self._tenants_to_database_to_id[DEFAULT_TENANT][DEFAULT_DATABASE] = UUID(int=0) + return super().reset_state() + + @overrides(check_signature=False) + def CreateDatabase( + self, request: CreateDatabaseRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + tenant = request.tenant + database = request.name + if tenant not in self._tenants_to_databases_to_collections: + return proto.ChromaResponse( + status=proto.Status(code=404, reason=f"Tenant {tenant} not found") + ) + if database in self._tenants_to_databases_to_collections[tenant]: + return proto.ChromaResponse( + status=proto.Status( + code=409, reason=f"Database {database} already exists" + ) + ) + self._tenants_to_databases_to_collections[tenant][database] = {} + self._tenants_to_database_to_id[tenant][database] = UUID(hex=request.id) + return proto.ChromaResponse(status=proto.Status(code=200)) + + @overrides(check_signature=False) + def GetDatabase( + self, request: GetDatabaseRequest, context: grpc.ServicerContext + ) -> GetDatabaseResponse: + tenant = request.tenant + database = request.name + if tenant not in self._tenants_to_databases_to_collections: + return GetDatabaseResponse( + status=proto.Status(code=404, reason=f"Tenant {tenant} not found") + ) + if database not in self._tenants_to_databases_to_collections[tenant]: + return GetDatabaseResponse( + status=proto.Status(code=404, reason=f"Database {database} not found") + ) + id = self._tenants_to_database_to_id[tenant][database] + return GetDatabaseResponse( + status=proto.Status(code=200), + database=proto.Database(id=id.hex, name=database, tenant=tenant), + ) + + @overrides(check_signature=False) + def CreateTenant( + self, request: CreateDatabaseRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + tenant = request.name + if tenant in self._tenants_to_databases_to_collections: + return proto.ChromaResponse( + status=proto.Status(code=409, reason=f"Tenant {tenant} already exists") + ) + self._tenants_to_databases_to_collections[tenant] = {} + self._tenants_to_database_to_id[tenant] = {} + return proto.ChromaResponse(status=proto.Status(code=200)) + + @overrides(check_signature=False) + def GetTenant( + self, request: GetTenantRequest, context: grpc.ServicerContext + ) -> GetTenantResponse: + tenant = request.name + if tenant not in self._tenants_to_databases_to_collections: + return GetTenantResponse( + status=proto.Status(code=404, reason=f"Tenant {tenant} not found") + ) + return GetTenantResponse( + status=proto.Status(code=200), + tenant=proto.Tenant(name=tenant), + ) + + # We are forced to use check_signature=False because the generated proto code + # does not have type annotations for the request and response objects. + # TODO: investigate generating types for the request and response objects + @overrides(check_signature=False) + def CreateSegment( + self, request: CreateSegmentRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + segment = from_proto_segment(request.segment) + if segment["id"].hex in self._segments: + return proto.ChromaResponse( + status=proto.Status( + code=409, reason=f"Segment {segment['id']} already exists" + ) + ) + self._segments[segment["id"].hex] = segment + return proto.ChromaResponse( + status=proto.Status(code=200) + ) # TODO: how are these codes used? Need to determine the standards for the code and reason. + + @overrides(check_signature=False) + def DeleteSegment( + self, request: DeleteSegmentRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + id_to_delete = request.id + if id_to_delete in self._segments: + del self._segments[id_to_delete] + return proto.ChromaResponse(status=proto.Status(code=200)) + else: + return proto.ChromaResponse( + status=proto.Status( + code=404, reason=f"Segment {id_to_delete} not found" + ) + ) + + @overrides(check_signature=False) + def GetSegments( + self, request: GetSegmentsRequest, context: grpc.ServicerContext + ) -> GetSegmentsResponse: + target_id = UUID(hex=request.id) if request.HasField("id") else None + target_type = request.type if request.HasField("type") else None + target_scope = ( + from_proto_segment_scope(request.scope) + if request.HasField("scope") + else None + ) + target_topic = request.topic if request.HasField("topic") else None + target_collection = ( + UUID(hex=request.collection) if request.HasField("collection") else None + ) + + found_segments = [] + for segment in self._segments.values(): + if target_id and segment["id"] != target_id: + continue + if target_type and segment["type"] != target_type: + continue + if target_scope and segment["scope"] != target_scope: + continue + if target_topic and segment["topic"] != target_topic: + continue + if target_collection and segment["collection"] != target_collection: + continue + found_segments.append(segment) + return GetSegmentsResponse( + segments=[to_proto_segment(segment) for segment in found_segments] + ) + + @overrides(check_signature=False) + def UpdateSegment( + self, request: UpdateSegmentRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + id_to_update = UUID(request.id) + if id_to_update.hex not in self._segments: + return proto.ChromaResponse( + status=proto.Status( + code=404, reason=f"Segment {id_to_update} not found" + ) + ) + else: + segment = self._segments[id_to_update.hex] + if request.HasField("topic"): + segment["topic"] = request.topic + if request.HasField("reset_topic") and request.reset_topic: + segment["topic"] = None + if request.HasField("collection"): + segment["collection"] = UUID(hex=request.collection) + if request.HasField("reset_collection") and request.reset_collection: + segment["collection"] = None + if request.HasField("metadata"): + target = cast(Dict[str, Any], segment["metadata"]) + if segment["metadata"] is None: + segment["metadata"] = {} + self._merge_metadata(target, request.metadata) + if request.HasField("reset_metadata") and request.reset_metadata: + segment["metadata"] = {} + return proto.ChromaResponse(status=proto.Status(code=200)) + + @overrides(check_signature=False) + def CreateCollection( + self, request: CreateCollectionRequest, context: grpc.ServicerContext + ) -> CreateCollectionResponse: + collection_name = request.name + tenant = request.tenant + database = request.database + if tenant not in self._tenants_to_databases_to_collections: + return CreateCollectionResponse( + status=proto.Status(code=404, reason=f"Tenant {tenant} not found") + ) + if database not in self._tenants_to_databases_to_collections[tenant]: + return CreateCollectionResponse( + status=proto.Status(code=404, reason=f"Database {database} not found") + ) + + # Check if the collection already exists globally by id + for ( + search_tenant, + databases, + ) in self._tenants_to_databases_to_collections.items(): + for search_database, search_collections in databases.items(): + if request.id in search_collections: + if ( + search_tenant != request.tenant + or search_database != request.database + ): + return CreateCollectionResponse( + status=proto.Status( + code=409, + reason=f"Collection {request.id} already exists in tenant {search_tenant} database {search_database}", + ) + ) + elif not request.get_or_create: + # If the id exists for this tenant and database, and we are not doing a get_or_create, then + # we should return a 409 + return CreateCollectionResponse( + status=proto.Status( + code=409, + reason=f"Collection {request.id} already exists in tenant {search_tenant} database {search_database}", + ) + ) + + # Check if the collection already exists in this database by name + collections = self._tenants_to_databases_to_collections[tenant][database] + matches = [c for c in collections.values() if c["name"] == collection_name] + assert len(matches) <= 1 + if len(matches) > 0: + if request.get_or_create: + existing_collection = matches[0] + if request.HasField("metadata"): + existing_collection["metadata"] = from_proto_metadata( + request.metadata + ) + return CreateCollectionResponse( + status=proto.Status(code=200), + collection=to_proto_collection(existing_collection), + created=False, + ) + return CreateCollectionResponse( + status=proto.Status( + code=409, reason=f"Collection {request.name} already exists" + ) + ) + + id = UUID(hex=request.id) + new_collection = Collection( + id=id, + name=request.name, + metadata=from_proto_metadata(request.metadata), + dimension=request.dimension, + topic=self._assignment_policy.assign_collection(id), + database=database, + tenant=tenant, + ) + collections[request.id] = new_collection + return CreateCollectionResponse( + status=proto.Status(code=200), + collection=to_proto_collection(new_collection), + created=True, + ) + + @overrides(check_signature=False) + def DeleteCollection( + self, request: DeleteCollectionRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + collection_id = request.id + tenant = request.tenant + database = request.database + if tenant not in self._tenants_to_databases_to_collections: + return proto.ChromaResponse( + status=proto.Status(code=404, reason=f"Tenant {tenant} not found") + ) + if database not in self._tenants_to_databases_to_collections[tenant]: + return proto.ChromaResponse( + status=proto.Status(code=404, reason=f"Database {database} not found") + ) + collections = self._tenants_to_databases_to_collections[tenant][database] + if collection_id in collections: + del collections[collection_id] + return proto.ChromaResponse(status=proto.Status(code=200)) + else: + return proto.ChromaResponse( + status=proto.Status( + code=404, reason=f"Collection {collection_id} not found" + ) + ) + + @overrides(check_signature=False) + def GetCollections( + self, request: GetCollectionsRequest, context: grpc.ServicerContext + ) -> GetCollectionsResponse: + target_id = UUID(hex=request.id) if request.HasField("id") else None + target_topic = request.topic if request.HasField("topic") else None + target_name = request.name if request.HasField("name") else None + + tenant = request.tenant + database = request.database + if tenant not in self._tenants_to_databases_to_collections: + return GetCollectionsResponse( + status=proto.Status(code=404, reason=f"Tenant {tenant} not found") + ) + if database not in self._tenants_to_databases_to_collections[tenant]: + return GetCollectionsResponse( + status=proto.Status(code=404, reason=f"Database {database} not found") + ) + collections = self._tenants_to_databases_to_collections[tenant][database] + + found_collections = [] + for collection in collections.values(): + if target_id and collection["id"] != target_id: + continue + if target_topic and collection["topic"] != target_topic: + continue + if target_name and collection["name"] != target_name: + continue + found_collections.append(collection) + return GetCollectionsResponse( + collections=[ + to_proto_collection(collection) for collection in found_collections + ] + ) + + @overrides(check_signature=False) + def UpdateCollection( + self, request: UpdateCollectionRequest, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + id_to_update = UUID(request.id) + # Find the collection with this id + collections = {} + for tenant, databases in self._tenants_to_databases_to_collections.items(): + for database, maybe_collections in databases.items(): + if id_to_update.hex in maybe_collections: + collections = maybe_collections + + if id_to_update.hex not in collections: + return proto.ChromaResponse( + status=proto.Status( + code=404, reason=f"Collection {id_to_update} not found" + ) + ) + else: + collection = collections[id_to_update.hex] + if request.HasField("topic"): + collection["topic"] = request.topic + if request.HasField("name"): + collection["name"] = request.name + if request.HasField("dimension"): + collection["dimension"] = request.dimension + if request.HasField("metadata"): + # TODO: IN SysDB SQlite we have technical debt where we + # replace the entire metadata dict with the new one. We should + # fix that by merging it. For now we just do the same thing here + + update_metadata = from_proto_update_metadata(request.metadata) + cleaned_metadata = None + if update_metadata is not None: + cleaned_metadata = {} + for key, value in update_metadata.items(): + if value is not None: + cleaned_metadata[key] = value + + collection["metadata"] = cleaned_metadata + elif request.HasField("reset_metadata"): + if request.reset_metadata: + collection["metadata"] = {} + + return proto.ChromaResponse(status=proto.Status(code=200)) + + @overrides(check_signature=False) + def ResetState( + self, request: Empty, context: grpc.ServicerContext + ) -> proto.ChromaResponse: + self.reset_state() + return proto.ChromaResponse(status=proto.Status(code=200)) + + def _merge_metadata(self, target: Metadata, source: proto.UpdateMetadata) -> None: + target_metadata = cast(Dict[str, Any], target) + source_metadata = cast(Dict[str, Any], from_proto_update_metadata(source)) + target_metadata.update(source_metadata) + # If a key has a None value, remove it from the metadata + for key, value in source_metadata.items(): + if value is None and key in target: + del target_metadata[key] diff --git a/chromadb/db/impl/sqlite.py b/chromadb/db/impl/sqlite.py new file mode 100644 index 0000000000000000000000000000000000000000..c7cdb30632468a9ea64ba42f29a44d3cdf37b634 --- /dev/null +++ b/chromadb/db/impl/sqlite.py @@ -0,0 +1,248 @@ +from chromadb.db.impl.sqlite_pool import Connection, LockPool, PerThreadPool, Pool +from chromadb.db.migrations import MigratableDB, Migration +from chromadb.config import System, Settings +import chromadb.db.base as base +from chromadb.db.mixins.embeddings_queue import SqlEmbeddingsQueue +from chromadb.db.mixins.sysdb import SqlSysDB +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +import sqlite3 +from overrides import override +import pypika +from typing import Sequence, cast, Optional, Type, Any +from typing_extensions import Literal +from types import TracebackType +import os +from uuid import UUID +from threading import local +from importlib_resources import files +from importlib_resources.abc import Traversable + + +class TxWrapper(base.TxWrapper): + _conn: Connection + _pool: Pool + + def __init__(self, conn_pool: Pool, stack: local): + self._tx_stack = stack + self._conn = conn_pool.connect() + self._pool = conn_pool + + @override + def __enter__(self) -> base.Cursor: + if len(self._tx_stack.stack) == 0: + self._conn.execute("BEGIN;") + self._tx_stack.stack.append(self) + return self._conn.cursor() # type: ignore + + @override + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_value: Optional[BaseException], + traceback: Optional[TracebackType], + ) -> Literal[False]: + self._tx_stack.stack.pop() + if len(self._tx_stack.stack) == 0: + if exc_type is None: + self._conn.commit() + else: + self._conn.rollback() + self._conn.cursor().close() + self._pool.return_to_pool(self._conn) + return False + + +class SqliteDB(MigratableDB, SqlEmbeddingsQueue, SqlSysDB): + _conn_pool: Pool + _settings: Settings + _migration_imports: Sequence[Traversable] + _db_file: str + _tx_stack: local + _is_persistent: bool + + def __init__(self, system: System): + self._settings = system.settings + self._migration_imports = [ + files("chromadb.migrations.embeddings_queue"), + files("chromadb.migrations.sysdb"), + files("chromadb.migrations.metadb"), + ] + self._is_persistent = self._settings.require("is_persistent") + self._opentelemetry_client = system.require(OpenTelemetryClient) + if not self._is_persistent: + # In order to allow sqlite to be shared between multiple threads, we need to use a + # URI connection string with shared cache. + # See https://www.sqlite.org/sharedcache.html + # https://stackoverflow.com/questions/3315046/sharing-a-memory-database-between-different-threads-in-python-using-sqlite3-pa + self._db_file = "file::memory:?cache=shared" + self._conn_pool = LockPool(self._db_file, is_uri=True) + else: + self._db_file = ( + self._settings.require("persist_directory") + "/chroma.sqlite3" + ) + if not os.path.exists(self._db_file): + os.makedirs(os.path.dirname(self._db_file), exist_ok=True) + self._conn_pool = PerThreadPool(self._db_file) + self._tx_stack = local() + super().__init__(system) + + @trace_method("SqliteDB.start", OpenTelemetryGranularity.ALL) + @override + def start(self) -> None: + super().start() + with self.tx() as cur: + cur.execute("PRAGMA foreign_keys = ON") + cur.execute("PRAGMA case_sensitive_like = ON") + self.initialize_migrations() + + @trace_method("SqliteDB.stop", OpenTelemetryGranularity.ALL) + @override + def stop(self) -> None: + super().stop() + self._conn_pool.close() + + @staticmethod + @override + def querybuilder() -> Type[pypika.Query]: + return pypika.Query # type: ignore + + @staticmethod + @override + def parameter_format() -> str: + return "?" + + @staticmethod + @override + def migration_scope() -> str: + return "sqlite" + + @override + def migration_dirs(self) -> Sequence[Traversable]: + return self._migration_imports + + @override + def tx(self) -> TxWrapper: + if not hasattr(self._tx_stack, "stack"): + self._tx_stack.stack = [] + return TxWrapper(self._conn_pool, stack=self._tx_stack) + + @trace_method("SqliteDB.reset_state", OpenTelemetryGranularity.ALL) + @override + def reset_state(self) -> None: + if not self._settings.require("allow_reset"): + raise ValueError( + "Resetting the database is not allowed. Set `allow_reset` to true in the config in tests or other non-production environments where reset should be permitted." + ) + with self.tx() as cur: + # Drop all tables + cur.execute( + """ + SELECT name FROM sqlite_master + WHERE type='table' + """ + ) + for row in cur.fetchall(): + cur.execute(f"DROP TABLE IF EXISTS {row[0]}") + self._conn_pool.close() + self.start() + super().reset_state() + + @trace_method("SqliteDB.setup_migrations", OpenTelemetryGranularity.ALL) + @override + def setup_migrations(self) -> None: + with self.tx() as cur: + cur.execute( + """ + CREATE TABLE IF NOT EXISTS migrations ( + dir TEXT NOT NULL, + version INTEGER NOT NULL, + filename TEXT NOT NULL, + sql TEXT NOT NULL, + hash TEXT NOT NULL, + PRIMARY KEY (dir, version) + ) + """ + ) + + @trace_method("SqliteDB.migrations_initialized", OpenTelemetryGranularity.ALL) + @override + def migrations_initialized(self) -> bool: + with self.tx() as cur: + cur.execute( + """SELECT count(*) FROM sqlite_master + WHERE type='table' AND name='migrations'""" + ) + + if cur.fetchone()[0] == 0: + return False + else: + return True + + @trace_method("SqliteDB.db_migrations", OpenTelemetryGranularity.ALL) + @override + def db_migrations(self, dir: Traversable) -> Sequence[Migration]: + with self.tx() as cur: + cur.execute( + """ + SELECT dir, version, filename, sql, hash + FROM migrations + WHERE dir = ? + ORDER BY version ASC + """, + (dir.name,), + ) + + migrations = [] + for row in cur.fetchall(): + found_dir = cast(str, row[0]) + found_version = cast(int, row[1]) + found_filename = cast(str, row[2]) + found_sql = cast(str, row[3]) + found_hash = cast(str, row[4]) + migrations.append( + Migration( + dir=found_dir, + version=found_version, + filename=found_filename, + sql=found_sql, + hash=found_hash, + scope=self.migration_scope(), + ) + ) + return migrations + + @override + def apply_migration(self, cur: base.Cursor, migration: Migration) -> None: + cur.executescript(migration["sql"]) + cur.execute( + """ + INSERT INTO migrations (dir, version, filename, sql, hash) + VALUES (?, ?, ?, ?, ?) + """, + ( + migration["dir"], + migration["version"], + migration["filename"], + migration["sql"], + migration["hash"], + ), + ) + + @staticmethod + @override + def uuid_from_db(value: Optional[Any]) -> Optional[UUID]: + return UUID(value) if value is not None else None + + @staticmethod + @override + def uuid_to_db(uuid: Optional[UUID]) -> Optional[Any]: + return str(uuid) if uuid is not None else None + + @staticmethod + @override + def unique_constraint_error() -> Type[BaseException]: + return sqlite3.IntegrityError diff --git a/chromadb/db/impl/sqlite_pool.py b/chromadb/db/impl/sqlite_pool.py new file mode 100644 index 0000000000000000000000000000000000000000..83a3edf104bbfcc980ac4ce389bbdce233586f09 --- /dev/null +++ b/chromadb/db/impl/sqlite_pool.py @@ -0,0 +1,159 @@ +import sqlite3 +from abc import ABC, abstractmethod +from typing import Any, Set +import threading +from overrides import override + + +class Connection: + """A threadpool connection that returns itself to the pool on close()""" + + _pool: "Pool" + _db_file: str + _conn: sqlite3.Connection + + def __init__( + self, pool: "Pool", db_file: str, is_uri: bool, *args: Any, **kwargs: Any + ): + self._pool = pool + self._db_file = db_file + self._conn = sqlite3.connect( + db_file, timeout=1000, check_same_thread=False, uri=is_uri, *args, **kwargs + ) # type: ignore + self._conn.isolation_level = None # Handle commits explicitly + + def execute(self, sql: str, parameters=...) -> sqlite3.Cursor: # type: ignore + if parameters is ...: + return self._conn.execute(sql) + return self._conn.execute(sql, parameters) + + def commit(self) -> None: + self._conn.commit() + + def rollback(self) -> None: + self._conn.rollback() + + def cursor(self) -> sqlite3.Cursor: + return self._conn.cursor() + + def close_actual(self) -> None: + """Actually closes the connection to the db""" + self._conn.close() + + +class Pool(ABC): + """Abstract base class for a pool of connections to a sqlite database.""" + + @abstractmethod + def __init__(self, db_file: str, is_uri: bool) -> None: + pass + + @abstractmethod + def connect(self, *args: Any, **kwargs: Any) -> Connection: + """Return a connection from the pool.""" + pass + + @abstractmethod + def close(self) -> None: + """Close all connections in the pool.""" + pass + + @abstractmethod + def return_to_pool(self, conn: Connection) -> None: + """Return a connection to the pool.""" + pass + + +class LockPool(Pool): + """A pool that has a single connection per thread but uses a lock to ensure that only one thread can use it at a time. + This is used because sqlite does not support multithreaded access with connection timeouts when using the + shared cache mode. We use the shared cache mode to allow multiple threads to share a database. + """ + + _connections: Set[Connection] + _lock: threading.RLock + _connection: threading.local + _db_file: str + _is_uri: bool + + def __init__(self, db_file: str, is_uri: bool = False): + self._connections = set() + self._connection = threading.local() + self._lock = threading.RLock() + self._db_file = db_file + self._is_uri = is_uri + + @override + def connect(self, *args: Any, **kwargs: Any) -> Connection: + self._lock.acquire() + if hasattr(self._connection, "conn") and self._connection.conn is not None: + return self._connection.conn # type: ignore # cast doesn't work here for some reason + else: + new_connection = Connection( + self, self._db_file, self._is_uri, *args, **kwargs + ) + self._connection.conn = new_connection + self._connections.add(new_connection) + return new_connection + + @override + def return_to_pool(self, conn: Connection) -> None: + try: + self._lock.release() + except RuntimeError: + pass + + @override + def close(self) -> None: + for conn in self._connections: + conn.close_actual() + self._connections.clear() + self._connection = threading.local() + try: + self._lock.release() + except RuntimeError: + pass + + +class PerThreadPool(Pool): + """Maintains a connection per thread. For now this does not maintain a cap on the number of connections, but it could be + extended to do so and block on connect() if the cap is reached. + """ + + _connections: Set[Connection] + _lock: threading.Lock + _connection: threading.local + _db_file: str + _is_uri_: bool + + def __init__(self, db_file: str, is_uri: bool = False): + self._connections = set() + self._connection = threading.local() + self._lock = threading.Lock() + self._db_file = db_file + self._is_uri = is_uri + + @override + def connect(self, *args: Any, **kwargs: Any) -> Connection: + if hasattr(self._connection, "conn") and self._connection.conn is not None: + return self._connection.conn # type: ignore # cast doesn't work here for some reason + else: + new_connection = Connection( + self, self._db_file, self._is_uri, *args, **kwargs + ) + self._connection.conn = new_connection + with self._lock: + self._connections.add(new_connection) + return new_connection + + @override + def close(self) -> None: + with self._lock: + for conn in self._connections: + conn.close_actual() + self._connections.clear() + self._connection = threading.local() + + @override + def return_to_pool(self, conn: Connection) -> None: + pass # Each thread gets its own connection, so we don't need to return it to the pool diff --git a/chromadb/db/migrations.py b/chromadb/db/migrations.py new file mode 100644 index 0000000000000000000000000000000000000000..97ef029092abae8e347e1e832e0abd1b916486ca --- /dev/null +++ b/chromadb/db/migrations.py @@ -0,0 +1,270 @@ +import sys +from typing import Sequence +from typing_extensions import TypedDict, NotRequired +from importlib_resources.abc import Traversable +import re +import hashlib +from chromadb.db.base import SqlDB, Cursor +from abc import abstractmethod +from chromadb.config import System, Settings +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) + + +class MigrationFile(TypedDict): + path: NotRequired[Traversable] + dir: str + filename: str + version: int + scope: str + + +class Migration(MigrationFile): + hash: str + sql: str + + +class UninitializedMigrationsError(Exception): + def __init__(self) -> None: + super().__init__("Migrations have not been initialized") + + +class UnappliedMigrationsError(Exception): + def __init__(self, dir: str, version: int): + self.dir = dir + self.version = version + super().__init__( + f"Unapplied migrations in {dir}, starting with version {version}" + ) + + +class InconsistentVersionError(Exception): + def __init__(self, dir: str, db_version: int, source_version: int): + super().__init__( + f"Inconsistent migration versions in {dir}:" + + f"db version was {db_version}, source version was {source_version}." + + " Has the migration sequence been modified since being applied to the DB?" + ) + + +class InconsistentHashError(Exception): + def __init__(self, path: str, db_hash: str, source_hash: str): + super().__init__( + f"Inconsistent hashes in {path}:" + + f"db hash was {db_hash}, source has was {source_hash}." + + " Was the migration file modified after being applied to the DB?" + ) + + +class InvalidHashError(Exception): + def __init__(self, alg: str): + super().__init__(f"Invalid hash algorithm specified: {alg}") + + +class InvalidMigrationFilename(Exception): + pass + + +class MigratableDB(SqlDB): + """Simple base class for databases which support basic migrations. + + Migrations are SQL files stored as package resources and accessed via + importlib_resources. + + All migrations in the same directory are assumed to be dependent on previous + migrations in the same directory, where "previous" is defined on lexographical + ordering of filenames. + + Migrations have a ascending numeric version number and a hash of the file contents. + When migrations are applied, the hashes of previous migrations are checked to ensure + that the database is consistent with the source repository. If they are not, an + error is thrown and no migrations will be applied. + + Migration files must follow the naming convention: + ...sql, where is a 5-digit zero-padded + integer, is a short textual description, and is a short string + identifying the database implementation. + """ + + _settings: Settings + + def __init__(self, system: System) -> None: + self._settings = system.settings + self._opentelemetry_client = system.require(OpenTelemetryClient) + super().__init__(system) + + @staticmethod + @abstractmethod + def migration_scope() -> str: + """The database implementation to use for migrations (e.g, sqlite, pgsql)""" + pass + + @abstractmethod + def migration_dirs(self) -> Sequence[Traversable]: + """Directories containing the migration sequences that should be applied to this + DB.""" + pass + + @abstractmethod + def setup_migrations(self) -> None: + """Idempotently creates the migrations table""" + pass + + @abstractmethod + def migrations_initialized(self) -> bool: + """Return true if the migrations table exists""" + pass + + @abstractmethod + def db_migrations(self, dir: Traversable) -> Sequence[Migration]: + """Return a list of all migrations already applied to this database, from the + given source directory, in ascending order.""" + pass + + @abstractmethod + def apply_migration(self, cur: Cursor, migration: Migration) -> None: + """Apply a single migration to the database""" + pass + + def initialize_migrations(self) -> None: + """Initialize migrations for this DB""" + migrate = self._settings.require("migrations") + + if migrate == "validate": + self.validate_migrations() + + if migrate == "apply": + self.apply_migrations() + + @trace_method("MigratableDB.validate_migrations", OpenTelemetryGranularity.ALL) + def validate_migrations(self) -> None: + """Validate all migrations and throw an exception if there are any unapplied + migrations in the source repo.""" + if not self.migrations_initialized(): + raise UninitializedMigrationsError() + for dir in self.migration_dirs(): + db_migrations = self.db_migrations(dir) + source_migrations = find_migrations( + dir, + self.migration_scope(), + self._settings.require("migrations_hash_algorithm"), + ) + unapplied_migrations = verify_migration_sequence( + db_migrations, source_migrations + ) + if len(unapplied_migrations) > 0: + version = unapplied_migrations[0]["version"] + raise UnappliedMigrationsError(dir=dir.name, version=version) + + @trace_method("MigratableDB.apply_migrations", OpenTelemetryGranularity.ALL) + def apply_migrations(self) -> None: + """Validate existing migrations, and apply all new ones.""" + self.setup_migrations() + for dir in self.migration_dirs(): + db_migrations = self.db_migrations(dir) + source_migrations = find_migrations( + dir, + self.migration_scope(), + self._settings.require("migrations_hash_algorithm"), + ) + unapplied_migrations = verify_migration_sequence( + db_migrations, source_migrations + ) + with self.tx() as cur: + for migration in unapplied_migrations: + self.apply_migration(cur, migration) + + +# Format is -..sql +# e.g, 00001-users.sqlite.sql +filename_regex = re.compile(r"(\d+)-(.+)\.(.+)\.sql") + + +def _parse_migration_filename( + dir: str, filename: str, path: Traversable +) -> MigrationFile: + """Parse a migration filename into a MigrationFile object""" + match = filename_regex.match(filename) + if match is None: + raise InvalidMigrationFilename("Invalid migration filename: " + filename) + version, _, scope = match.groups() + return { + "path": path, + "dir": dir, + "filename": filename, + "version": int(version), + "scope": scope, + } + + +def verify_migration_sequence( + db_migrations: Sequence[Migration], + source_migrations: Sequence[Migration], +) -> Sequence[Migration]: + """Given a list of migrations already applied to a database, and a list of + migrations from the source code, validate that the applied migrations are correct + and match the expected migrations. + + Throws an exception if any migrations are missing, out of order, or if the source + hash does not match. + + Returns a list of all unapplied migrations, or an empty list if all migrations are + applied and the database is up to date.""" + + for db_migration, source_migration in zip(db_migrations, source_migrations): + if db_migration["version"] != source_migration["version"]: + raise InconsistentVersionError( + dir=db_migration["dir"], + db_version=db_migration["version"], + source_version=source_migration["version"], + ) + + if db_migration["hash"] != source_migration["hash"]: + raise InconsistentHashError( + path=db_migration["dir"] + "/" + db_migration["filename"], + db_hash=db_migration["hash"], + source_hash=source_migration["hash"], + ) + + return source_migrations[len(db_migrations) :] + + +def find_migrations(dir: Traversable, scope: str, hash_alg: str = "md5") -> Sequence[Migration]: + """Return a list of all migration present in the given directory, in ascending + order. Filter by scope.""" + files = [ + _parse_migration_filename(dir.name, t.name, t) + for t in dir.iterdir() + if t.name.endswith(".sql") + ] + files = list(filter(lambda f: f["scope"] == scope, files)) + files = sorted(files, key=lambda f: f["version"]) + return [_read_migration_file(f, hash_alg) for f in files] + + +def _read_migration_file(file: MigrationFile, hash_alg: str) -> Migration: + """Read a migration file""" + if "path" not in file or not file["path"].is_file(): + raise FileNotFoundError( + f"No migration file found for dir {file['dir']} with filename {file['filename']} and scope {file['scope']} at version {file['version']}" + ) + sql = file["path"].read_text() + + if hash_alg == "md5": + hash = hashlib.md5(sql.encode("utf-8"), usedforsecurity=False).hexdigest() if sys.version_info >= (3, 9) else hashlib.md5(sql.encode("utf-8")).hexdigest() + elif hash_alg == "sha256": + hash = hashlib.sha256(sql.encode("utf-8")).hexdigest() + else: + raise InvalidHashError(alg=hash_alg) + + return { + "hash": hash, + "sql": sql, + "dir": file["dir"], + "filename": file["filename"], + "version": file["version"], + "scope": file["scope"], + } diff --git a/chromadb/db/mixins/embeddings_queue.py b/chromadb/db/mixins/embeddings_queue.py new file mode 100644 index 0000000000000000000000000000000000000000..b5d745b92865a7f71c32484354574a7a163bb1e3 --- /dev/null +++ b/chromadb/db/mixins/embeddings_queue.py @@ -0,0 +1,379 @@ +from chromadb.db.base import SqlDB, ParameterValue, get_sql +from chromadb.ingest import ( + Producer, + Consumer, + encode_vector, + decode_vector, + ConsumerCallbackFn, +) +from chromadb.types import ( + SubmitEmbeddingRecord, + EmbeddingRecord, + SeqId, + ScalarEncoding, + Operation, +) +from chromadb.config import System +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from overrides import override +from collections import defaultdict +from typing import Sequence, Tuple, Optional, Dict, Set, cast +from uuid import UUID +from pypika import Table, functions +import uuid +import json +import logging + +logger = logging.getLogger(__name__) + +_operation_codes = { + Operation.ADD: 0, + Operation.UPDATE: 1, + Operation.UPSERT: 2, + Operation.DELETE: 3, +} +_operation_codes_inv = {v: k for k, v in _operation_codes.items()} + +# Set in conftest.py to rethrow errors in the "async" path during testing +# https://doc.pytest.org/en/latest/example/simple.html#detect-if-running-from-within-a-pytest-run +_called_from_test = False + + +class SqlEmbeddingsQueue(SqlDB, Producer, Consumer): + """A SQL database that stores embeddings, allowing a traditional RDBMS to be used as + the primary ingest queue and satisfying the top level Producer/Consumer interfaces. + + Note that this class is only suitable for use cases where the producer and consumer + are in the same process. + + This is because notifiaction of new embeddings happens solely in-process: this + implementation does not actively listen to the the database for new records added by + other processes. + """ + + class Subscription: + id: UUID + topic_name: str + start: int + end: int + callback: ConsumerCallbackFn + + def __init__( + self, + id: UUID, + topic_name: str, + start: int, + end: int, + callback: ConsumerCallbackFn, + ): + self.id = id + self.topic_name = topic_name + self.start = start + self.end = end + self.callback = callback + + _subscriptions: Dict[str, Set[Subscription]] + _max_batch_size: Optional[int] + # How many variables are in the insert statement for a single record + VARIABLES_PER_RECORD = 6 + + def __init__(self, system: System): + self._subscriptions = defaultdict(set) + self._max_batch_size = None + self._opentelemetry_client = system.require(OpenTelemetryClient) + super().__init__(system) + + @trace_method("SqlEmbeddingsQueue.reset_state", OpenTelemetryGranularity.ALL) + @override + def reset_state(self) -> None: + super().reset_state() + self._subscriptions = defaultdict(set) + + @override + def create_topic(self, topic_name: str) -> None: + # Topic creation is implicit for this impl + pass + + @trace_method("SqlEmbeddingsQueue.delete_topic", OpenTelemetryGranularity.ALL) + @override + def delete_topic(self, topic_name: str) -> None: + t = Table("embeddings_queue") + q = ( + self.querybuilder() + .from_(t) + .where(t.topic == ParameterValue(topic_name)) + .delete() + ) + with self.tx() as cur: + sql, params = get_sql(q, self.parameter_format()) + cur.execute(sql, params) + + @trace_method("SqlEmbeddingsQueue.submit_embedding", OpenTelemetryGranularity.ALL) + @override + def submit_embedding( + self, topic_name: str, embedding: SubmitEmbeddingRecord + ) -> SeqId: + if not self._running: + raise RuntimeError("Component not running") + + return self.submit_embeddings(topic_name, [embedding])[0] + + @trace_method("SqlEmbeddingsQueue.submit_embeddings", OpenTelemetryGranularity.ALL) + @override + def submit_embeddings( + self, topic_name: str, embeddings: Sequence[SubmitEmbeddingRecord] + ) -> Sequence[SeqId]: + if not self._running: + raise RuntimeError("Component not running") + + if len(embeddings) == 0: + return [] + + if len(embeddings) > self.max_batch_size: + raise ValueError( + f""" + Cannot submit more than {self.max_batch_size:,} embeddings at once. + Please submit your embeddings in batches of size + {self.max_batch_size:,} or less. + """ + ) + + t = Table("embeddings_queue") + insert = ( + self.querybuilder() + .into(t) + .columns(t.operation, t.topic, t.id, t.vector, t.encoding, t.metadata) + ) + id_to_idx: Dict[str, int] = {} + for embedding in embeddings: + ( + embedding_bytes, + encoding, + metadata, + ) = self._prepare_vector_encoding_metadata(embedding) + insert = insert.insert( + ParameterValue(_operation_codes[embedding["operation"]]), + ParameterValue(topic_name), + ParameterValue(embedding["id"]), + ParameterValue(embedding_bytes), + ParameterValue(encoding), + ParameterValue(metadata), + ) + id_to_idx[embedding["id"]] = len(id_to_idx) + with self.tx() as cur: + sql, params = get_sql(insert, self.parameter_format()) + # The returning clause does not guarantee order, so we need to do reorder + # the results. https://www.sqlite.org/lang_returning.html + sql = f"{sql} RETURNING seq_id, id" # Pypika doesn't support RETURNING + results = cur.execute(sql, params).fetchall() + # Reorder the results + seq_ids = [cast(SeqId, None)] * len( + results + ) # Lie to mypy: https://stackoverflow.com/questions/76694215/python-type-casting-when-preallocating-list + embedding_records = [] + for seq_id, id in results: + seq_ids[id_to_idx[id]] = seq_id + submit_embedding_record = embeddings[id_to_idx[id]] + # We allow notifying consumers out of order relative to one call to + # submit_embeddings so we do not reorder the records before submitting them + embedding_record = EmbeddingRecord( + id=id, + seq_id=seq_id, + embedding=submit_embedding_record["embedding"], + encoding=submit_embedding_record["encoding"], + metadata=submit_embedding_record["metadata"], + operation=submit_embedding_record["operation"], + ) + embedding_records.append(embedding_record) + self._notify_all(topic_name, embedding_records) + return seq_ids + + @trace_method("SqlEmbeddingsQueue.subscribe", OpenTelemetryGranularity.ALL) + @override + def subscribe( + self, + topic_name: str, + consume_fn: ConsumerCallbackFn, + start: Optional[SeqId] = None, + end: Optional[SeqId] = None, + id: Optional[UUID] = None, + ) -> UUID: + if not self._running: + raise RuntimeError("Component not running") + + subscription_id = id or uuid.uuid4() + start, end = self._validate_range(start, end) + + subscription = self.Subscription( + subscription_id, topic_name, start, end, consume_fn + ) + + # Backfill first, so if it errors we do not add the subscription + self._backfill(subscription) + self._subscriptions[topic_name].add(subscription) + + return subscription_id + + @trace_method("SqlEmbeddingsQueue.unsubscribe", OpenTelemetryGranularity.ALL) + @override + def unsubscribe(self, subscription_id: UUID) -> None: + for topic_name, subscriptions in self._subscriptions.items(): + for subscription in subscriptions: + if subscription.id == subscription_id: + subscriptions.remove(subscription) + if len(subscriptions) == 0: + del self._subscriptions[topic_name] + return + + @override + def min_seqid(self) -> SeqId: + return -1 + + @override + def max_seqid(self) -> SeqId: + return 2**63 - 1 + + @property + @trace_method("SqlEmbeddingsQueue.max_batch_size", OpenTelemetryGranularity.ALL) + @override + def max_batch_size(self) -> int: + if self._max_batch_size is None: + with self.tx() as cur: + cur.execute("PRAGMA compile_options;") + compile_options = cur.fetchall() + + for option in compile_options: + if "MAX_VARIABLE_NUMBER" in option[0]: + # The pragma returns a string like 'MAX_VARIABLE_NUMBER=999' + self._max_batch_size = int(option[0].split("=")[1]) // ( + self.VARIABLES_PER_RECORD + ) + + if self._max_batch_size is None: + # This value is the default for sqlite3 versions < 3.32.0 + # It is the safest value to use if we can't find the pragma for some + # reason + self._max_batch_size = 999 // self.VARIABLES_PER_RECORD + return self._max_batch_size + + @trace_method( + "SqlEmbeddingsQueue._prepare_vector_encoding_metadata", + OpenTelemetryGranularity.ALL, + ) + def _prepare_vector_encoding_metadata( + self, embedding: SubmitEmbeddingRecord + ) -> Tuple[Optional[bytes], Optional[str], Optional[str]]: + if embedding["embedding"]: + encoding_type = cast(ScalarEncoding, embedding["encoding"]) + encoding = encoding_type.value + embedding_bytes = encode_vector(embedding["embedding"], encoding_type) + else: + embedding_bytes = None + encoding = None + metadata = json.dumps(embedding["metadata"]) if embedding["metadata"] else None + return embedding_bytes, encoding, metadata + + @trace_method("SqlEmbeddingsQueue._backfill", OpenTelemetryGranularity.ALL) + def _backfill(self, subscription: Subscription) -> None: + """Backfill the given subscription with any currently matching records in the + DB""" + t = Table("embeddings_queue") + q = ( + self.querybuilder() + .from_(t) + .where(t.topic == ParameterValue(subscription.topic_name)) + .where(t.seq_id > ParameterValue(subscription.start)) + .where(t.seq_id <= ParameterValue(subscription.end)) + .select(t.seq_id, t.operation, t.id, t.vector, t.encoding, t.metadata) + .orderby(t.seq_id) + ) + with self.tx() as cur: + sql, params = get_sql(q, self.parameter_format()) + cur.execute(sql, params) + rows = cur.fetchall() + for row in rows: + if row[3]: + encoding = ScalarEncoding(row[4]) + vector = decode_vector(row[3], encoding) + else: + encoding = None + vector = None + self._notify_one( + subscription, + [ + EmbeddingRecord( + seq_id=row[0], + operation=_operation_codes_inv[row[1]], + id=row[2], + embedding=vector, + encoding=encoding, + metadata=json.loads(row[5]) if row[5] else None, + ) + ], + ) + + @trace_method("SqlEmbeddingsQueue._validate_range", OpenTelemetryGranularity.ALL) + def _validate_range( + self, start: Optional[SeqId], end: Optional[SeqId] + ) -> Tuple[int, int]: + """Validate and normalize the start and end SeqIDs for a subscription using this + impl.""" + start = start or self._next_seq_id() + end = end or self.max_seqid() + if not isinstance(start, int) or not isinstance(end, int): + raise TypeError("SeqIDs must be integers for sql-based EmbeddingsDB") + if start >= end: + raise ValueError(f"Invalid SeqID range: {start} to {end}") + return start, end + + @trace_method("SqlEmbeddingsQueue._next_seq_id", OpenTelemetryGranularity.ALL) + def _next_seq_id(self) -> int: + """Get the next SeqID for this database.""" + t = Table("embeddings_queue") + q = self.querybuilder().from_(t).select(functions.Max(t.seq_id)) + with self.tx() as cur: + cur.execute(q.get_sql()) + return int(cur.fetchone()[0]) + 1 + + @trace_method("SqlEmbeddingsQueue._notify_all", OpenTelemetryGranularity.ALL) + def _notify_all(self, topic: str, embeddings: Sequence[EmbeddingRecord]) -> None: + """Send a notification to each subscriber of the given topic.""" + if self._running: + for sub in self._subscriptions[topic]: + self._notify_one(sub, embeddings) + + @trace_method("SqlEmbeddingsQueue._notify_one", OpenTelemetryGranularity.ALL) + def _notify_one( + self, sub: Subscription, embeddings: Sequence[EmbeddingRecord] + ) -> None: + """Send a notification to a single subscriber.""" + # Filter out any embeddings that are not in the subscription range + should_unsubscribe = False + filtered_embeddings = [] + for embedding in embeddings: + if embedding["seq_id"] <= sub.start: + continue + if embedding["seq_id"] > sub.end: + should_unsubscribe = True + break + filtered_embeddings.append(embedding) + + # Log errors instead of throwing them to preserve async semantics + # for consistency between local and distributed configurations + try: + if len(filtered_embeddings) > 0: + sub.callback(filtered_embeddings) + if should_unsubscribe: + self.unsubscribe(sub.id) + except BaseException as e: + logger.error( + f"Exception occurred invoking consumer for subscription {sub.id.hex}" + + f"to topic {sub.topic_name} %s", + str(e), + ) + if _called_from_test: + raise e diff --git a/chromadb/db/mixins/sysdb.py b/chromadb/db/mixins/sysdb.py new file mode 100644 index 0000000000000000000000000000000000000000..7373aabd0f33e774477a69e47d5a45de43307b5f --- /dev/null +++ b/chromadb/db/mixins/sysdb.py @@ -0,0 +1,747 @@ +from typing import Optional, Sequence, Any, Tuple, cast, Dict, Union, Set +from uuid import UUID +from overrides import override +from pypika import Table, Column +from itertools import groupby + +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, System +from chromadb.db.base import ( + Cursor, + SqlDB, + ParameterValue, + get_sql, + NotFoundError, + UniqueConstraintError, +) +from chromadb.db.system import SysDB +from chromadb.telemetry.opentelemetry import ( + add_attributes_to_current_span, + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.ingest import CollectionAssignmentPolicy, Producer +from chromadb.types import ( + Database, + OptionalArgument, + Segment, + Metadata, + Collection, + SegmentScope, + Tenant, + Unspecified, + UpdateMetadata, +) + + +class SqlSysDB(SqlDB, SysDB): + _assignment_policy: CollectionAssignmentPolicy + # Used only to delete topics on collection deletion. + # TODO: refactor to remove this dependency into a separate interface + _producer: Producer + + def __init__(self, system: System): + self._assignment_policy = system.instance(CollectionAssignmentPolicy) + super().__init__(system) + self._opentelemetry_client = system.require(OpenTelemetryClient) + + @trace_method("SqlSysDB.create_segment", OpenTelemetryGranularity.ALL) + @override + def start(self) -> None: + super().start() + self._producer = self._system.instance(Producer) + + @override + def create_database( + self, id: UUID, name: str, tenant: str = DEFAULT_TENANT + ) -> None: + with self.tx() as cur: + # Get the tenant id for the tenant name and then insert the database with the id, name and tenant id + databases = Table("databases") + tenants = Table("tenants") + insert_database = ( + self.querybuilder() + .into(databases) + .columns(databases.id, databases.name, databases.tenant_id) + .insert( + ParameterValue(self.uuid_to_db(id)), + ParameterValue(name), + self.querybuilder() + .select(tenants.id) + .from_(tenants) + .where(tenants.id == ParameterValue(tenant)), + ) + ) + sql, params = get_sql(insert_database, self.parameter_format()) + try: + cur.execute(sql, params) + except self.unique_constraint_error() as e: + raise UniqueConstraintError( + f"Database {name} already exists for tenant {tenant}" + ) from e + + @override + def get_database(self, name: str, tenant: str = DEFAULT_TENANT) -> Database: + with self.tx() as cur: + databases = Table("databases") + q = ( + self.querybuilder() + .from_(databases) + .select(databases.id, databases.name) + .where(databases.name == ParameterValue(name)) + .where(databases.tenant_id == ParameterValue(tenant)) + ) + sql, params = get_sql(q, self.parameter_format()) + row = cur.execute(sql, params).fetchone() + if not row: + raise NotFoundError(f"Database {name} not found for tenant {tenant}") + if row[0] is None: + raise NotFoundError(f"Database {name} not found for tenant {tenant}") + id: UUID = cast(UUID, self.uuid_from_db(row[0])) + return Database( + id=id, + name=row[1], + tenant=tenant, + ) + + @override + def create_tenant(self, name: str) -> None: + with self.tx() as cur: + tenants = Table("tenants") + insert_tenant = ( + self.querybuilder() + .into(tenants) + .columns(tenants.id) + .insert(ParameterValue(name)) + ) + sql, params = get_sql(insert_tenant, self.parameter_format()) + try: + cur.execute(sql, params) + except self.unique_constraint_error() as e: + raise UniqueConstraintError(f"Tenant {name} already exists") from e + + @override + def get_tenant(self, name: str) -> Tenant: + with self.tx() as cur: + tenants = Table("tenants") + q = ( + self.querybuilder() + .from_(tenants) + .select(tenants.id) + .where(tenants.id == ParameterValue(name)) + ) + sql, params = get_sql(q, self.parameter_format()) + row = cur.execute(sql, params).fetchone() + if not row: + raise NotFoundError(f"Tenant {name} not found") + return Tenant(name=name) + + @override + def create_segment(self, segment: Segment) -> None: + add_attributes_to_current_span( + { + "segment_id": str(segment["id"]), + "segment_type": segment["type"], + "segment_scope": segment["scope"].value, + "segment_topic": str(segment["topic"]), + "collection": str(segment["collection"]), + } + ) + with self.tx() as cur: + segments = Table("segments") + insert_segment = ( + self.querybuilder() + .into(segments) + .columns( + segments.id, + segments.type, + segments.scope, + segments.topic, + segments.collection, + ) + .insert( + ParameterValue(self.uuid_to_db(segment["id"])), + ParameterValue(segment["type"]), + ParameterValue(segment["scope"].value), + ParameterValue(segment["topic"]), + ParameterValue(self.uuid_to_db(segment["collection"])), + ) + ) + sql, params = get_sql(insert_segment, self.parameter_format()) + try: + cur.execute(sql, params) + except self.unique_constraint_error() as e: + raise UniqueConstraintError( + f"Segment {segment['id']} already exists" + ) from e + metadata_t = Table("segment_metadata") + if segment["metadata"]: + self._insert_metadata( + cur, + metadata_t, + metadata_t.segment_id, + segment["id"], + segment["metadata"], + ) + + @trace_method("SqlSysDB.create_collection", OpenTelemetryGranularity.ALL) + @override + def create_collection( + self, + id: UUID, + name: str, + metadata: Optional[Metadata] = None, + dimension: Optional[int] = None, + get_or_create: bool = False, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Tuple[Collection, bool]: + if id is None and not get_or_create: + raise ValueError("id must be specified if get_or_create is False") + + add_attributes_to_current_span( + { + "collection_id": str(id), + "collection_name": name, + } + ) + + existing = self.get_collections(name=name, tenant=tenant, database=database) + if existing: + if get_or_create: + collection = existing[0] + if metadata is not None and collection["metadata"] != metadata: + self.update_collection( + collection["id"], + metadata=metadata, + ) + return ( + self.get_collections( + id=collection["id"], tenant=tenant, database=database + )[0], + False, + ) + else: + raise UniqueConstraintError(f"Collection {name} already exists") + + topic = self._assignment_policy.assign_collection(id) + collection = Collection( + id=id, + topic=topic, + name=name, + metadata=metadata, + dimension=dimension, + tenant=tenant, + database=database, + ) + + with self.tx() as cur: + collections = Table("collections") + databases = Table("databases") + + insert_collection = ( + self.querybuilder() + .into(collections) + .columns( + collections.id, + collections.topic, + collections.name, + collections.dimension, + collections.database_id, + ) + .insert( + ParameterValue(self.uuid_to_db(collection["id"])), + ParameterValue(collection["topic"]), + ParameterValue(collection["name"]), + ParameterValue(collection["dimension"]), + # Get the database id for the database with the given name and tenant + self.querybuilder() + .select(databases.id) + .from_(databases) + .where(databases.name == ParameterValue(database)) + .where(databases.tenant_id == ParameterValue(tenant)), + ) + ) + sql, params = get_sql(insert_collection, self.parameter_format()) + try: + cur.execute(sql, params) + except self.unique_constraint_error() as e: + raise UniqueConstraintError( + f"Collection {collection['id']} already exists" + ) from e + metadata_t = Table("collection_metadata") + if collection["metadata"]: + self._insert_metadata( + cur, + metadata_t, + metadata_t.collection_id, + collection["id"], + collection["metadata"], + ) + return collection, True + + @trace_method("SqlSysDB.get_segments", OpenTelemetryGranularity.ALL) + @override + def get_segments( + self, + id: Optional[UUID] = None, + type: Optional[str] = None, + scope: Optional[SegmentScope] = None, + topic: Optional[str] = None, + collection: Optional[UUID] = None, + ) -> Sequence[Segment]: + add_attributes_to_current_span( + { + "segment_id": str(id), + "segment_type": type if type else "", + "segment_scope": scope.value if scope else "", + "segment_topic": topic if topic else "", + "collection": str(collection), + } + ) + segments_t = Table("segments") + metadata_t = Table("segment_metadata") + q = ( + self.querybuilder() + .from_(segments_t) + .select( + segments_t.id, + segments_t.type, + segments_t.scope, + segments_t.topic, + segments_t.collection, + metadata_t.key, + metadata_t.str_value, + metadata_t.int_value, + metadata_t.float_value, + ) + .left_join(metadata_t) + .on(segments_t.id == metadata_t.segment_id) + .orderby(segments_t.id) + ) + if id: + q = q.where(segments_t.id == ParameterValue(self.uuid_to_db(id))) + if type: + q = q.where(segments_t.type == ParameterValue(type)) + if scope: + q = q.where(segments_t.scope == ParameterValue(scope.value)) + if topic: + q = q.where(segments_t.topic == ParameterValue(topic)) + if collection: + q = q.where( + segments_t.collection == ParameterValue(self.uuid_to_db(collection)) + ) + + with self.tx() as cur: + sql, params = get_sql(q, self.parameter_format()) + rows = cur.execute(sql, params).fetchall() + by_segment = groupby(rows, lambda r: cast(object, r[0])) + segments = [] + for segment_id, segment_rows in by_segment: + id = self.uuid_from_db(str(segment_id)) + rows = list(segment_rows) + type = str(rows[0][1]) + scope = SegmentScope(str(rows[0][2])) + topic = str(rows[0][3]) if rows[0][3] else None + collection = self.uuid_from_db(rows[0][4]) if rows[0][4] else None + metadata = self._metadata_from_rows(rows) + segments.append( + Segment( + id=cast(UUID, id), + type=type, + scope=scope, + topic=topic, + collection=collection, + metadata=metadata, + ) + ) + + return segments + + @trace_method("SqlSysDB.get_collections", OpenTelemetryGranularity.ALL) + @override + def get_collections( + self, + id: Optional[UUID] = None, + topic: Optional[str] = None, + name: Optional[str] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + limit: Optional[int] = None, + offset: Optional[int] = None, + ) -> Sequence[Collection]: + """Get collections by name, embedding function and/or metadata""" + + if name is not None and (tenant is None or database is None): + raise ValueError( + "If name is specified, tenant and database must also be specified in order to uniquely identify the collection" + ) + + add_attributes_to_current_span( + { + "collection_id": str(id), + "collection_topic": topic if topic else "", + "collection_name": name if name else "", + } + ) + + collections_t = Table("collections") + metadata_t = Table("collection_metadata") + databases_t = Table("databases") + q = ( + self.querybuilder() + .from_(collections_t) + .select( + collections_t.id, + collections_t.name, + collections_t.topic, + collections_t.dimension, + databases_t.name, + databases_t.tenant_id, + metadata_t.key, + metadata_t.str_value, + metadata_t.int_value, + metadata_t.float_value, + ) + .left_join(metadata_t) + .on(collections_t.id == metadata_t.collection_id) + .left_join(databases_t) + .on(collections_t.database_id == databases_t.id) + .orderby(collections_t.id) + ) + if id: + q = q.where(collections_t.id == ParameterValue(self.uuid_to_db(id))) + if topic: + q = q.where(collections_t.topic == ParameterValue(topic)) + if name: + q = q.where(collections_t.name == ParameterValue(name)) + + # Only if we have a name, tenant and database do we need to filter databases + # Given an id, we can uniquely identify the collection so we don't need to filter databases + if id is None and tenant and database: + databases_t = Table("databases") + q = q.where( + collections_t.database_id + == self.querybuilder() + .select(databases_t.id) + .from_(databases_t) + .where(databases_t.name == ParameterValue(database)) + .where(databases_t.tenant_id == ParameterValue(tenant)) + ) + # cant set limit and offset here because this is metadata and we havent reduced yet + + with self.tx() as cur: + sql, params = get_sql(q, self.parameter_format()) + rows = cur.execute(sql, params).fetchall() + by_collection = groupby(rows, lambda r: cast(object, r[0])) + collections = [] + for collection_id, collection_rows in by_collection: + id = self.uuid_from_db(str(collection_id)) + rows = list(collection_rows) + name = str(rows[0][1]) + topic = str(rows[0][2]) + dimension = int(rows[0][3]) if rows[0][3] else None + metadata = self._metadata_from_rows(rows) + collections.append( + Collection( + id=cast(UUID, id), + topic=topic, + name=name, + metadata=metadata, + dimension=dimension, + tenant=str(rows[0][5]), + database=str(rows[0][4]), + ) + ) + + # apply limit and offset + if limit is not None: + collections = collections[offset:offset+limit] + else: + collections = collections[offset:] + + return collections + + @trace_method("SqlSysDB.delete_segment", OpenTelemetryGranularity.ALL) + @override + def delete_segment(self, id: UUID) -> None: + """Delete a segment from the SysDB""" + add_attributes_to_current_span( + { + "segment_id": str(id), + } + ) + t = Table("segments") + q = ( + self.querybuilder() + .from_(t) + .where(t.id == ParameterValue(self.uuid_to_db(id))) + .delete() + ) + with self.tx() as cur: + # no need for explicit del from metadata table because of ON DELETE CASCADE + sql, params = get_sql(q, self.parameter_format()) + sql = sql + " RETURNING id" + result = cur.execute(sql, params).fetchone() + if not result: + raise NotFoundError(f"Segment {id} not found") + + @trace_method("SqlSysDB.delete_collection", OpenTelemetryGranularity.ALL) + @override + def delete_collection( + self, + id: UUID, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> None: + """Delete a topic and all associated segments from the SysDB""" + add_attributes_to_current_span( + { + "collection_id": str(id), + } + ) + t = Table("collections") + databases_t = Table("databases") + q = ( + self.querybuilder() + .from_(t) + .where(t.id == ParameterValue(self.uuid_to_db(id))) + .where( + t.database_id + == self.querybuilder() + .select(databases_t.id) + .from_(databases_t) + .where(databases_t.name == ParameterValue(database)) + .where(databases_t.tenant_id == ParameterValue(tenant)) + ) + .delete() + ) + with self.tx() as cur: + # no need for explicit del from metadata table because of ON DELETE CASCADE + sql, params = get_sql(q, self.parameter_format()) + sql = sql + " RETURNING id, topic" + result = cur.execute(sql, params).fetchone() + if not result: + raise NotFoundError(f"Collection {id} not found") + self._producer.delete_topic(result[1]) + + @trace_method("SqlSysDB.update_segment", OpenTelemetryGranularity.ALL) + @override + def update_segment( + self, + id: UUID, + topic: OptionalArgument[Optional[str]] = Unspecified(), + collection: OptionalArgument[Optional[UUID]] = Unspecified(), + metadata: OptionalArgument[Optional[UpdateMetadata]] = Unspecified(), + ) -> None: + add_attributes_to_current_span( + { + "segment_id": str(id), + "collection": str(collection), + } + ) + segments_t = Table("segments") + metadata_t = Table("segment_metadata") + + q = ( + self.querybuilder() + .update(segments_t) + .where(segments_t.id == ParameterValue(self.uuid_to_db(id))) + ) + + if not topic == Unspecified(): + q = q.set(segments_t.topic, ParameterValue(topic)) + + if not collection == Unspecified(): + collection = cast(Optional[UUID], collection) + q = q.set( + segments_t.collection, ParameterValue(self.uuid_to_db(collection)) + ) + + with self.tx() as cur: + sql, params = get_sql(q, self.parameter_format()) + if sql: # pypika emits a blank string if nothing to do + cur.execute(sql, params) + + if metadata is None: + q = ( + self.querybuilder() + .from_(metadata_t) + .where(metadata_t.segment_id == ParameterValue(self.uuid_to_db(id))) + .delete() + ) + sql, params = get_sql(q, self.parameter_format()) + cur.execute(sql, params) + elif metadata != Unspecified(): + metadata = cast(UpdateMetadata, metadata) + metadata = cast(UpdateMetadata, metadata) + self._insert_metadata( + cur, + metadata_t, + metadata_t.segment_id, + id, + metadata, + set(metadata.keys()), + ) + + @trace_method("SqlSysDB.update_collection", OpenTelemetryGranularity.ALL) + @override + def update_collection( + self, + id: UUID, + topic: OptionalArgument[Optional[str]] = Unspecified(), + name: OptionalArgument[str] = Unspecified(), + dimension: OptionalArgument[Optional[int]] = Unspecified(), + metadata: OptionalArgument[Optional[UpdateMetadata]] = Unspecified(), + ) -> None: + add_attributes_to_current_span( + { + "collection_id": str(id), + } + ) + collections_t = Table("collections") + metadata_t = Table("collection_metadata") + + q = ( + self.querybuilder() + .update(collections_t) + .where(collections_t.id == ParameterValue(self.uuid_to_db(id))) + ) + + if not topic == Unspecified(): + q = q.set(collections_t.topic, ParameterValue(topic)) + + if not name == Unspecified(): + q = q.set(collections_t.name, ParameterValue(name)) + + if not dimension == Unspecified(): + q = q.set(collections_t.dimension, ParameterValue(dimension)) + + with self.tx() as cur: + sql, params = get_sql(q, self.parameter_format()) + if sql: # pypika emits a blank string if nothing to do + sql = sql + " RETURNING id" + result = cur.execute(sql, params) + if not result.fetchone(): + raise NotFoundError(f"Collection {id} not found") + + # TODO: Update to use better semantics where it's possible to update + # individual keys without wiping all the existing metadata. + + # For now, follow current legancy semantics where metadata is fully reset + if metadata != Unspecified(): + q = ( + self.querybuilder() + .from_(metadata_t) + .where( + metadata_t.collection_id == ParameterValue(self.uuid_to_db(id)) + ) + .delete() + ) + sql, params = get_sql(q, self.parameter_format()) + cur.execute(sql, params) + if metadata is not None: + metadata = cast(UpdateMetadata, metadata) + self._insert_metadata( + cur, + metadata_t, + metadata_t.collection_id, + id, + metadata, + set(metadata.keys()), + ) + + @trace_method("SqlSysDB._metadata_from_rows", OpenTelemetryGranularity.ALL) + def _metadata_from_rows( + self, rows: Sequence[Tuple[Any, ...]] + ) -> Optional[Metadata]: + """Given SQL rows, return a metadata map (assuming that the last four columns + are the key, str_value, int_value & float_value)""" + add_attributes_to_current_span( + { + "num_rows": len(rows), + } + ) + metadata: Dict[str, Union[str, int, float]] = {} + for row in rows: + key = str(row[-4]) + if row[-3] is not None: + metadata[key] = str(row[-3]) + elif row[-2] is not None: + metadata[key] = int(row[-2]) + elif row[-1] is not None: + metadata[key] = float(row[-1]) + return metadata or None + + @trace_method("SqlSysDB._insert_metadata", OpenTelemetryGranularity.ALL) + def _insert_metadata( + self, + cur: Cursor, + table: Table, + id_col: Column, + id: UUID, + metadata: UpdateMetadata, + clear_keys: Optional[Set[str]] = None, + ) -> None: + # It would be cleaner to use something like ON CONFLICT UPDATE here But that is + # very difficult to do in a portable way (e.g sqlite and postgres have + # completely different sytnax) + add_attributes_to_current_span( + { + "num_keys": len(metadata), + } + ) + if clear_keys: + q = ( + self.querybuilder() + .from_(table) + .where(id_col == ParameterValue(self.uuid_to_db(id))) + .where(table.key.isin([ParameterValue(k) for k in clear_keys])) + .delete() + ) + sql, params = get_sql(q, self.parameter_format()) + cur.execute(sql, params) + + q = ( + self.querybuilder() + .into(table) + .columns( + id_col, + table.key, + table.str_value, + table.int_value, + table.float_value, + ) + ) + sql_id = self.uuid_to_db(id) + for k, v in metadata.items(): + if isinstance(v, str): + q = q.insert( + ParameterValue(sql_id), + ParameterValue(k), + ParameterValue(v), + None, + None, + ) + elif isinstance(v, int): + q = q.insert( + ParameterValue(sql_id), + ParameterValue(k), + None, + ParameterValue(v), + None, + ) + elif isinstance(v, float): + q = q.insert( + ParameterValue(sql_id), + ParameterValue(k), + None, + None, + ParameterValue(v), + ) + elif v is None: + continue + + sql, params = get_sql(q, self.parameter_format()) + if sql: + cur.execute(sql, params) diff --git a/chromadb/db/system.py b/chromadb/db/system.py new file mode 100644 index 0000000000000000000000000000000000000000..15cbf5691c186479af43990acbd6a1b86be6d410 --- /dev/null +++ b/chromadb/db/system.py @@ -0,0 +1,138 @@ +from abc import abstractmethod +from typing import Optional, Sequence, Tuple +from uuid import UUID +from chromadb.types import ( + Collection, + Database, + Tenant, + Metadata, + Segment, + SegmentScope, + OptionalArgument, + Unspecified, + UpdateMetadata, +) +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Component + + +class SysDB(Component): + """Data interface for Chroma's System database""" + + @abstractmethod + def create_database( + self, id: UUID, name: str, tenant: str = DEFAULT_TENANT + ) -> None: + """Create a new database in the System database. Raises an Error if the Database + already exists.""" + pass + + @abstractmethod + def get_database(self, name: str, tenant: str = DEFAULT_TENANT) -> Database: + """Get a database by name and tenant. Raises an Error if the Database does not + exist.""" + pass + + @abstractmethod + def create_tenant(self, name: str) -> None: + """Create a new tenant in the System database. The name must be unique. + Raises an Error if the Tenant already exists.""" + pass + + @abstractmethod + def get_tenant(self, name: str) -> Tenant: + """Get a tenant by name. Raises an Error if the Tenant does not exist.""" + pass + + @abstractmethod + def create_segment(self, segment: Segment) -> None: + """Create a new segment in the System database. Raises an Error if the ID + already exists.""" + pass + + @abstractmethod + def delete_segment(self, id: UUID) -> None: + """Create a new segment in the System database.""" + pass + + @abstractmethod + def get_segments( + self, + id: Optional[UUID] = None, + type: Optional[str] = None, + scope: Optional[SegmentScope] = None, + topic: Optional[str] = None, + collection: Optional[UUID] = None, + ) -> Sequence[Segment]: + """Find segments by id, type, scope, topic or collection.""" + pass + + @abstractmethod + def update_segment( + self, + id: UUID, + topic: OptionalArgument[Optional[str]] = Unspecified(), + collection: OptionalArgument[Optional[UUID]] = Unspecified(), + metadata: OptionalArgument[Optional[UpdateMetadata]] = Unspecified(), + ) -> None: + """Update a segment. Unspecified fields will be left unchanged. For the + metadata, keys with None values will be removed and keys not present in the + UpdateMetadata dict will be left unchanged.""" + pass + + @abstractmethod + def create_collection( + self, + id: UUID, + name: str, + metadata: Optional[Metadata] = None, + dimension: Optional[int] = None, + get_or_create: bool = False, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Tuple[Collection, bool]: + """Create a new collection any associated resources + (Such as the necessary topics) in the SysDB. If get_or_create is True, the + collectionwill be created if one with the same name does not exist. + The metadata will be updated using the same protocol as update_collection. If get_or_create + is False and the collection already exists, a error will be raised. + + Returns a tuple of the created collection and a boolean indicating whether the + collection was created or not. + """ + pass + + @abstractmethod + def delete_collection( + self, id: UUID, tenant: str = DEFAULT_TENANT, database: str = DEFAULT_DATABASE + ) -> None: + """Delete a collection, topic, all associated segments and any associate resources + from the SysDB and the system at large.""" + pass + + @abstractmethod + def get_collections( + self, + id: Optional[UUID] = None, + topic: Optional[str] = None, + name: Optional[str] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + limit: Optional[int] = None, + offset: Optional[int] = None, + ) -> Sequence[Collection]: + """Find collections by id, topic or name. If name is provided, tenant and database must also be provided.""" + pass + + @abstractmethod + def update_collection( + self, + id: UUID, + topic: OptionalArgument[str] = Unspecified(), + name: OptionalArgument[str] = Unspecified(), + dimension: OptionalArgument[Optional[int]] = Unspecified(), + metadata: OptionalArgument[Optional[UpdateMetadata]] = Unspecified(), + ) -> None: + """Update a collection. Unspecified fields will be left unchanged. For metadata, + keys with None values will be removed and keys not present in the UpdateMetadata + dict will be left unchanged.""" + pass diff --git a/chromadb/errors.py b/chromadb/errors.py new file mode 100644 index 0000000000000000000000000000000000000000..f082fc766650ad1efc3547d75500f34cbda2aecc --- /dev/null +++ b/chromadb/errors.py @@ -0,0 +1,86 @@ +from abc import abstractmethod +from typing import Dict, Type +from overrides import overrides, EnforceOverrides + + +class ChromaError(Exception, EnforceOverrides): + def code(self) -> int: + """Return an appropriate HTTP response code for this error""" + return 400 # Bad Request + + def message(self) -> str: + return ", ".join(self.args) + + @classmethod + @abstractmethod + def name(cls) -> str: + """Return the error name""" + pass + + +class InvalidDimensionException(ChromaError): + @classmethod + @overrides + def name(cls) -> str: + return "InvalidDimension" + + +class InvalidCollectionException(ChromaError): + @classmethod + @overrides + def name(cls) -> str: + return "InvalidCollection" + + +class IDAlreadyExistsError(ChromaError): + @overrides + def code(self) -> int: + return 409 # Conflict + + @classmethod + @overrides + def name(cls) -> str: + return "IDAlreadyExists" + + +class DuplicateIDError(ChromaError): + @classmethod + @overrides + def name(cls) -> str: + return "DuplicateID" + + +class InvalidUUIDError(ChromaError): + @classmethod + @overrides + def name(cls) -> str: + return "InvalidUUID" + + +class InvalidHTTPVersion(ChromaError): + @classmethod + @overrides + def name(cls) -> str: + return "InvalidHTTPVersion" + + +class AuthorizationError(ChromaError): + @overrides + def code(self) -> int: + return 401 + + @classmethod + @overrides + def name(cls) -> str: + return "AuthorizationError" + + +error_types: Dict[str, Type[ChromaError]] = { + "InvalidDimension": InvalidDimensionException, + "InvalidCollection": InvalidCollectionException, + "IDAlreadyExists": IDAlreadyExistsError, + "DuplicateID": DuplicateIDError, + "InvalidUUID": InvalidUUIDError, + "InvalidHTTPVersion": InvalidHTTPVersion, + "AuthorizationError": AuthorizationError, +} diff --git a/chromadb/experimental/density_relevance.ipynb b/chromadb/experimental/density_relevance.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..c99ad533e826ef033f61cbc467b290650915675c --- /dev/null +++ b/chromadb/experimental/density_relevance.ipynb @@ -0,0 +1,542 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Density based retrieval relevance\n", + "\n", + "An important aspect of using embeddings-based retreival systems like Chroma is knowing whether there are relevant results to a given query in the existing dataset. As application developers, we would like to know when the system doesn't have enough information to complete a given query or task - we want to know what we don't know. \n", + "\n", + "This is particularly important in the case of retrieval-augmented generation, since it's [often been observed](https://arxiv.org/abs/2302.00093) that supplying irrelevant context serves to confuse the generative model, leading to the degredation of application performance in ways that are difficult to detect. \n", + "\n", + "Unlike a relational database which will not return results if none match the query, a vector search based retrieval system will return the $k$ nearest neighbors to any given query, whether they are relevant or not. \n", + "\n", + "One possible approach one might take is to tune a distance threshold, and reject any results which fall further away from the query. This might be suitable for certain kind of fixed datasets, but in practice such thresholds tend to be very brittle, and often serve to exclude many relevant results while not always excluding irrelevant ones. Additionally, the threshold will need to be continously adapted as the data changes. Additionally, such distance thresholds are not comparable across embedding models for a given dataset, nor across datasets for a given embedding model. \n", + "\n", + "We would prefer to find a data driven approach which can:\n", + "- produce a uniform and comparable measure of relevance for any dataset \n", + "- automatically adapt as the underlying data changes \n", + "- is relatively inexpensive to compute\n", + "\n", + "This notebook demonstrates one possible such approach, which relies on the distribution of distances (pseudo 'density') between points in a given dataset. For a given result, we use compute the percentile the result's distance to the query falls into with respect to the overall distribution of distances in the dataset. This approach produces a uniform measure of relevance for any dataset, and is relatively cheap to compute, and can be computed online as data mutates. \n", + "\n", + "This approach is still very preliminary, and we welcome contributions and alternative approaches - some ideas are listed at the end of this notebook." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Preliminaries" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Install required packages\n", + "\n", + "import sys\n", + "!{sys.executable} -m pip install chromadb numpy umap-learn[plot] matplotlib tqdm datasets" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Dataset\n", + "\n", + "As a demonstration we use the [SciQ dataset](https://arxiv.org/abs/1707.06209), available from [HuggingFace](https://huggingface.co/datasets/sciq). \n", + "\n", + "Dataset description, from HuggingFace:\n", + "\n", + "> The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Found cached dataset sciq (/Users/antontroynikov/.cache/huggingface/datasets/sciq/default/0.1.0/50e5c6e3795b55463819d399ec417bfd4c3c621105e00295ddb5f3633d708493)\n", + "Loading cached processed dataset at /Users/antontroynikov/.cache/huggingface/datasets/sciq/default/0.1.0/50e5c6e3795b55463819d399ec417bfd4c3c621105e00295ddb5f3633d708493/cache-9181e6e3516ba4ed.arrow\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of questions with support: 10481\n" + ] + } + ], + "source": [ + "# Get the SciQ dataset from HuggingFace\n", + "from datasets import load_dataset\n", + "\n", + "dataset = load_dataset(\"sciq\", split=\"train\")\n", + "\n", + "# Filter the dataset to only include questions with a support\n", + "dataset = dataset.filter(lambda x: x['support'] != '')\n", + "\n", + "print(\"Number of questions with support: \", len(dataset))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data loading \n", + "\n", + "We load the dataset into a local persistent instance of Chroma, into a collection called `sciq`. We use Chroma's [default embedding function](https://docs.trychroma.com/embeddings#default-all-minilm-l6-v2), all-MiniLM-L6-v2 from [sentence tranformers](https://www.sbert.net/)." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import chromadb\n", + "from chromadb.config import Settings\n", + "\n", + "chroma_client = chromadb.PersistentClient(path=\"./chroma)\")\n", + "\n", + "collection = chroma_client.get_or_create_collection(name=\"sciq\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Load the data into Chroma and persist, if it hasn't already been loaded and previously. " + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "0df53f502e3a450783f7cbc3b3c658ea", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/11 [00:00" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from umap.umap_ import UMAP\n", + "import umap.plot as umap_plot\n", + "import numpy as np\n", + "\n", + "mapper = UMAP().fit(support_embeddings)\n", + "umap_plot.points(mapper, values=np.array(flat_dists), show_legend=False, theme='inferno')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Computing the density function over distances \n", + "\n", + "Using the returned distances, we compute the density function using `numpy`. " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "# Compute a density function over the distances\n", + "import numpy as np\n", + "hist, bin_edges = np.histogram(flat_dists, bins=100, density=True)\n", + "cumulative_density = np.cumsum(hist) / np.sum(hist)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the density function\n", + "import matplotlib.pyplot as plt\n", + "plt.plot(bin_edges[1:], hist, label=\"Density\")\n", + "plt.plot(bin_edges[1:], cumulative_density, label=\"Cumulative Density\")\n", + "plt.legend(loc=\"upper right\")\n", + "plt.xlabel(\"Distance\")\n", + "plt.show()\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Computing relevance using the density function\n", + "\n", + "We use the percentile a given query falls into with respect to the overall distribution of distances between elements of the dataset, to estimate its relevance. Intuitively, results which are less relevant to the query, should be in higher percentiles than those which are more relevant. \n", + "\n", + "By using the distribution of distances in this way, we eliminate the need to tune an explicit distance threshold, and can instead reason in terms of likelihoods. We could either apply a threshold to the percentile-based relevance directly, or else feed this information into a re-ranking model, or take a sampling approach. " + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [], + "source": [ + "def compute_percentile(dist):\n", + " index = np.searchsorted(bin_edges[1:], dist, side='right')\n", + " return cumulative_density[index - 1]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Evaluation\n", + "\n", + "We evaluate the percentile based relevance score using the SciQ dataset. \n", + "\n", + "1. We query the collection of supporting sentences using the questions from the dataset, returning the 10 nearest results, along with their distances.\n", + "2. We check the results for whether the supporting sentence is present or absent. If it's present in the results, we record the percentile that the support falls into, otherwise we record the percentile of the nearest result. " + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [], + "source": [ + "question_results = collection.query(query_texts=dataset['question'], n_results=10, include=['documents', 'distances'])" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "support_percentiles = []\n", + "missing_support_percentiles = []\n", + "for i, q in enumerate(dataset['question']):\n", + " support = dataset['support'][i]\n", + " if support in question_results['documents'][i]:\n", + " support_index = question_results['documents'][i].index(support)\n", + " percentile = compute_percentile(question_results['distances'][i][support_index])\n", + " support_percentiles.append(percentile)\n", + " else:\n", + " missing_support_percentiles.append(compute_percentile(question_results['distances'][i][0]))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Visualization\n", + "\n", + "We plot histograms of the percentiles for the cases where the support was found, and the case where it wasn't. A lower percentile is more relevant. " + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot normalized histograms of the percentiles\n", + "plt.hist(support_percentiles, bins=20, density=True, alpha=0.5, label='Support')\n", + "plt.hist(missing_support_percentiles, bins=20, density=True, alpha=0.5, label='No support')\n", + "plt.legend(loc='upper right')\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Preliminary results\n", + "\n", + "While we don't observe a clear separation of the two classes, we do note that in general, supports tend to be in lower percentiles, and hence more relevant, than results which aren't the support. \n", + "\n", + "One possible confounding factor is that in some cases, the result does contain the answer to the query question, but is not itself the support for that question. " + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Question: What type of organism is commonly used in preparation of foods such as cheese and yogurt? \n", + "Support: Mesophiles grow best in moderate temperature, typically between 25°C and 40°C (77°F and 104°F). Mesophiles are often found living in or on the bodies of humans or other animals. The optimal growth temperature of many pathogenic mesophiles is 37°C (98°F), the normal human body temperature. Mesophilic organisms have important uses in food preparation, including cheese, yogurt, beer and wine. \n", + "Top result: Bacteria can be used to make cheese from milk. The bacteria turn the milk sugars into lactic acid. The acid is what causes the milk to curdle to form cheese. Bacteria are also involved in producing other foods. Yogurt is made by using bacteria to ferment milk ( Figure below ). Fermenting cabbage with bacteria produces sauerkraut.\n", + "\n", + "Question: Changes from a less-ordered state to a more-ordered state (such as a liquid to a solid) are always what? \n", + "Support: Summary Changes of state are examples of phase changes, or phase transitions. All phase changes are accompanied by changes in the energy of a system. Changes from a more-ordered state to a less-ordered state (such as a liquid to a gas) areendothermic. Changes from a less-ordered state to a more-ordered state (such as a liquid to a solid) are always exothermic. The conversion of a solid to a liquid is called fusion (or melting). The energy required to melt 1 mol of a substance is its enthalpy of fusion (ΔHfus). The energy change required to vaporize 1 mol of a substance is the enthalpy of vaporization (ΔHvap). The direct conversion of a solid to a gas is sublimation. The amount of energy needed to sublime 1 mol of a substance is its enthalpy of sublimation (ΔHsub) and is the sum of the enthalpies of fusion and vaporization. Plots of the temperature of a substance versus heat added or versus heating time at a constant rate of heating are calledheating curves. Heating curves relate temperature changes to phase transitions. A superheated liquid, a liquid at a temperature and pressure at which it should be a gas, is not stable. A cooling curve is not exactly the reverse of the heating curve because many liquids do not freeze at the expected temperature. Instead, they form a supercooled liquid, a metastable liquid phase that exists below the normal melting point. Supercooled liquids usually crystallize on standing, or adding a seed crystal of the same or another substance can induce crystallization. \n", + "Top result: Under the right pressure conditions, lowering the temperature of a substance in the liquid state causes the substance to solidify. The opposite effect occurs if the temperature is increased.\n", + "\n", + "Question: Kilauea in hawaii is the world’s most continuously active volcano. very active volcanoes characteristically eject red-hot rocks and lava rather than this? \n", + "Support: Example 3.5 Calculating Projectile Motion: Hot Rock Projectile Kilauea in Hawaii is the world’s most continuously active volcano. Very active volcanoes characteristically eject red-hot rocks and lava rather than smoke and ash. Suppose a large rock is ejected from the volcano with a speed of 25.0 m/s and at an angle 35.0º above the horizontal, as shown in Figure 3.40. The rock strikes the side of the volcano at an altitude 20.0 m lower than its starting point. (a) Calculate the time it takes the rock to follow this path. (b) What are the magnitude and direction of the rock’s velocity at impact?. \n", + "Top result: Volcanoes can be active, dormant, or extinct.\n", + "\n", + "Question: When a meteoroid reaches earth, what is the remaining object called? \n", + "Support: Meteoroids are smaller than asteroids, ranging from the size of boulders to the size of sand grains. When meteoroids enter Earth’s atmosphere, they vaporize, creating a trail of glowing gas called a meteor. If any of the meteoroid reaches Earth, the remaining object is called a meteorite. \n", + "Top result: A meteoroid is dragged toward Earth by gravity and enters the atmosphere. Friction with the atmosphere heats the object quickly, so it starts to vaporize. As it flies through the atmosphere, it leaves a trail of glowing gases. The object is now a meteor. Most meteors vaporize in the atmosphere. They never reach Earth’s surface. Large meteoroids may not burn up entirely in the atmosphere. A small core may remain and hit Earth’s surface. This is called a meteorite .\n", + "\n", + "Question: What kind of a reaction occurs when a substance reacts quickly with oxygen? \n", + "Support: A combustion reaction occurs when a substance reacts quickly with oxygen (O 2 ). For example, in the Figure below , charcoal is combining with oxygen. Combustion is commonly called burning, and the substance that burns is usually referred to as fuel. The products of a complete combustion reaction include carbon dioxide (CO 2 ) and water vapor (H 2 O). The reaction typically gives off heat and light as well. The general equation for a complete combustion reaction is:. \n", + "Top result: A combustion reaction occurs when a substance reacts quickly with oxygen (O 2 ). You can see an example of a combustion reaction in Figure below . Combustion is commonly called burning. The substance that burns is usually referred to as fuel. The products of a combustion reaction include carbon dioxide (CO 2 ) and water (H 2 O). The reaction typically gives off heat and light as well. The general equation for a combustion reaction can be represented by:.\n", + "\n", + "Question: Organisms categorized by what species descriptor demonstrate a version of allopatric speciation and have limited regions of overlap with one another, but where they overlap they interbreed successfully?. \n", + "Support: Ring species Ring species demonstrate a version of allopatric speciation. Imagine populations of the species A. Over the geographic range of A there exist a number of subpopulations. These subpopulations (A1 to A5) and (Aa to Ae) have limited regions of overlap with one another but where they overlap they interbreed successfully. But populations A5 and Ae no longer interbreed successfully – are these populations separate species?  In this case, there is no clear-cut answer, but it is likely that in the link between the various populations will be broken and one or more species may form in the future. Consider the black bear Ursus americanus. Originally distributed across all of North America, its distribution is now much more fragmented. Isolated populations are free to adapt to their own particular environments and migration between populations is limited. Clearly the environment in Florida is different from that in Mexico, Alaska, or Newfoundland. Different environments will favor different adaptations. If, over time, these populations were to come back into contact with one another, they might or might not be able to interbreed successfully - reproductive isolation may occur and one species may become many. \n", + "Top result: Allopatric speciation occurs when groups from the same species are geographically isolated for long periods. Imagine all the ways that plants or animals could be isolated from each other:.\n", + "\n", + "Question: Zinc is more easily oxidized than iron because zinc has a lower reduction potential. since zinc has a lower reduction potential, it is a more what? \n", + "Support: One way to keep iron from corroding is to keep it painted. The layer of paint prevents the water and oxygen necessary for rust formation from coming into contact with the iron. As long as the paint remains intact, the iron is protected from corrosion. Other strategies include alloying the iron with other metals. For example, stainless steel is mostly iron with a bit of chromium. The chromium tends to collect near the surface, where it forms an oxide layer that protects the iron. Zinc-plated or galvanized iron uses a different strategy. Zinc is more easily oxidized than iron because zinc has a lower reduction potential. Since zinc has a lower reduction potential, it is a more active metal. Thus, even if the zinc coating is scratched, the zinc will still oxidize before the iron. This suggests that this approach should work with other active metals. Another important way to protect metal is to make it the cathode in a galvanic cell. This is cathodic protection and can be used for metals other than just iron. For example, the rusting of underground iron storage tanks and pipes can be prevented or greatly reduced by connecting them to a more active metal such as zinc or magnesium (Figure 17.18). This is also used to protect the metal parts in water heaters. The more active metals (lower reduction potential) are called sacrificial anodes because as they get used up as they corrode (oxidize) at the anode. The metal being protected serves as the cathode, and so does not oxidize (corrode). When the anodes are properly monitored and periodically replaced, the useful lifetime of the iron storage tank can be greatly extended. \n", + "Top result: In the reaction above, the zinc is being oxidized by losing electrons. However, there must be another substance present that gains those electrons and in this case that is the sulfur. In other words, the sulfur is causing the zinc to be oxidized. Sulfur is called the oxidizing agent. The zinc causes the sulfur to gain electrons and become reduced and so the zinc is called the reducing agent. The oxidizing agent is a substance that causes oxidation by accepting electrons. The reducing agent is a substance that causes reduction by losing electrons. The simplest way to think of this is that the oxidizing agent is the substance that is reduced, while the reducing agent is the substance that is oxidized. The sample problem below shows how to analyze a redox reaction.\n", + "\n", + "Question: What are used to write nuclear equations for radioactive decay? \n", + "Support: Nuclear symbols are used to write nuclear equations for radioactive decay. Let’s consider the example of the beta-minus decay of thorium-234 to protactinium-234. This reaction is represented by the equation:. \n", + "Top result: Nuclear symbols are used to write nuclear equations for radioactive decay. Let’s consider an example. Uranium-238 undergoes alpha decay to become thorium-234. (The numbers following the chemical names refer to the number of protons plus neutrons. ) In this reaction, uranium-238 loses two protons and two neutrons to become the element thorium-234. The reaction can be represented by this nuclear equation:.\n", + "\n", + "Question: What is controlled by regulatory proteins that bind to regulatory elements on dna? \n", + "Support: Gene transcription is controlled by regulatory proteins that bind to regulatory elements on DNA. The proteins usually either activate or repress transcription. \n", + "Top result: As shown in Figure below , transcription is controlled by regulatory proteins . The proteins bind to regions of DNA, called regulatory elements , which are located near promoters. After regulatory proteins bind to regulatory elements, they can interact with RNA polymerase, the enzyme that transcribes DNA to mRNA. Regulatory proteins are typically either activators or repressors.\n", + "\n", + "Question: What occurs when the immune system attacks a harmless substance that enters the body from the outside? \n", + "Support: An allergy occurs when the immune system attacks a harmless substance that enters the body from the outside. A substance that causes an allergy is called an allergen. It is the immune system, not the allergen, that causes the symptoms of an allergy. \n", + "Top result: The second line of defense attacks pathogens that manage to enter the body. It includes the inflammatory response and phagocytosis by nonspecific leukocytes.\n", + "\n", + "Question: The plants alternation between haploid and diploud generations allow it to do what? \n", + "Support: All plants have a characteristic life cycle that includes alternation of generations . Plants alternate between haploid and diploid generations. Alternation of generations allows for both asexual and sexual reproduction. Asexual reproduction with spores produces haploid individuals called gametophytes . Sexual reproduction with gametes and fertilization produces diploid individuals called sporophytes . A typical plant’s life cycle is diagrammed in Figure below . \n", + "Top result: Plants alternate between diploid-cell plants and haploid-cell plants. This is called alternation of generations , because the plant type alternates from generation to generation. In alternation of generations, the plant alternates between a sporophyte that has diploid cells and a gametophyte that has haploid cells.\n", + "\n" + ] + } + ], + "source": [ + "for i, q in enumerate(dataset['question'][:20]):\n", + " support = dataset['support'][i]\n", + " top_result = question_results['documents'][i][0]\n", + "\n", + " if support != top_result:\n", + " print(f\"Question: {q} \\nSupport: {support} \\nTop result: {top_result}\\n\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Conclusion\n", + "\n", + "This notebook presents one possible approach to computing a relevance score for embeddings-based retreival, based on the distribution of distances between embeddings in the dataset. We have done some initial evaluation, but there is a lot left to do. \n", + "\n", + "Some things to try include:\n", + "- Construct the distance distribution on the basis of the query-support pairs, rather than between nearest neighbor supports. \n", + "- Additional evaluations comparing different embedding models for the same dataset, as well as datasets with less redundancy. \n", + "- Using the distance distribution to deduplicate data, by finding low-percentile outliers. One idea is to use an LLM in the loop to create summaries of document pairs, creating a single point from several which are near one another. \n", + "- Using relevance as a signal for automatically fine-tuning embedding space. One approach may be to learn an affine transform based on question/answer pairs, to increase the relevance of the correct points relative to others. \n", + "\n", + "We welcome contributions and ideas! " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "chroma", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/chromadb/ingest/__init__.py b/chromadb/ingest/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..73f9cb065f2bd1100d915d378cbe435bb81ce960 --- /dev/null +++ b/chromadb/ingest/__init__.py @@ -0,0 +1,134 @@ +from abc import abstractmethod +from typing import Callable, Optional, Sequence +from chromadb.types import ( + SubmitEmbeddingRecord, + EmbeddingRecord, + SeqId, + Vector, + ScalarEncoding, +) +from chromadb.config import Component +from uuid import UUID +import array + + +def encode_vector(vector: Vector, encoding: ScalarEncoding) -> bytes: + """Encode a vector into a byte array.""" + + if encoding == ScalarEncoding.FLOAT32: + return array.array("f", vector).tobytes() + elif encoding == ScalarEncoding.INT32: + return array.array("i", vector).tobytes() + else: + raise ValueError(f"Unsupported encoding: {encoding.value}") + + +def decode_vector(vector: bytes, encoding: ScalarEncoding) -> Vector: + """Decode a byte array into a vector""" + + if encoding == ScalarEncoding.FLOAT32: + return array.array("f", vector).tolist() + elif encoding == ScalarEncoding.INT32: + return array.array("i", vector).tolist() + else: + raise ValueError(f"Unsupported encoding: {encoding.value}") + + +class Producer(Component): + """Interface for writing embeddings to an ingest stream""" + + @abstractmethod + def create_topic(self, topic_name: str) -> None: + pass + + @abstractmethod + def delete_topic(self, topic_name: str) -> None: + pass + + @abstractmethod + def submit_embedding( + self, topic_name: str, embedding: SubmitEmbeddingRecord + ) -> SeqId: + """Add an embedding record to the given topic. Returns the SeqID of the record.""" + pass + + @abstractmethod + def submit_embeddings( + self, topic_name: str, embeddings: Sequence[SubmitEmbeddingRecord] + ) -> Sequence[SeqId]: + """Add a batch of embedding records to the given topic. Returns the SeqIDs of + the records. The returned SeqIDs will be in the same order as the given + SubmitEmbeddingRecords. However, it is not guaranteed that the SeqIDs will be + processed in the same order as the given SubmitEmbeddingRecords. If the number + of records exceeds the maximum batch size, an exception will be thrown.""" + pass + + @property + @abstractmethod + def max_batch_size(self) -> int: + """Return the maximum number of records that can be submitted in a single call + to submit_embeddings.""" + pass + + +ConsumerCallbackFn = Callable[[Sequence[EmbeddingRecord]], None] + + +class Consumer(Component): + """Interface for reading embeddings off an ingest stream""" + + @abstractmethod + def subscribe( + self, + topic_name: str, + consume_fn: ConsumerCallbackFn, + start: Optional[SeqId] = None, + end: Optional[SeqId] = None, + id: Optional[UUID] = None, + ) -> UUID: + """Register a function that will be called to recieve embeddings for a given + topic. The given function may be called any number of times, with any number of + records, and may be called concurrently. + + Only records between start (exclusive) and end (inclusive) SeqIDs will be + returned. If start is None, the first record returned will be the next record + generated, not including those generated before creating the subscription. If + end is None, the consumer will consume indefinitely, otherwise it will + automatically be unsubscribed when the end SeqID is reached. + + If the function throws an exception, the function may be called again with the + same or different records. + + Takes an optional UUID as a unique subscription ID. If no ID is provided, a new + ID will be generated and returned.""" + pass + + @abstractmethod + def unsubscribe(self, subscription_id: UUID) -> None: + """Unregister a subscription. The consume function will no longer be invoked, + and resources associated with the subscription will be released.""" + pass + + @abstractmethod + def min_seqid(self) -> SeqId: + """Return the minimum possible SeqID in this implementation.""" + pass + + @abstractmethod + def max_seqid(self) -> SeqId: + """Return the maximum possible SeqID in this implementation.""" + pass + + +class CollectionAssignmentPolicy(Component): + """Interface for assigning collections to topics""" + + @abstractmethod + def assign_collection(self, collection_id: UUID) -> str: + """Return the topic that should be used for the given collection""" + pass + + @abstractmethod + def get_topics(self) -> Sequence[str]: + """Return the list of topics that this policy is currently using""" + pass diff --git a/chromadb/ingest/impl/pulsar.py b/chromadb/ingest/impl/pulsar.py new file mode 100644 index 0000000000000000000000000000000000000000..d84cadfa01ea61dab3f8fdab08faf987b0fc7f68 --- /dev/null +++ b/chromadb/ingest/impl/pulsar.py @@ -0,0 +1,317 @@ +from __future__ import annotations +from collections import defaultdict +from typing import Any, Callable, Dict, List, Optional, Sequence, Set, Tuple +import uuid +from chromadb.config import Settings, System +from chromadb.ingest import Consumer, ConsumerCallbackFn, Producer +from overrides import overrides, EnforceOverrides +from uuid import UUID +from chromadb.ingest.impl.pulsar_admin import PulsarAdmin +from chromadb.ingest.impl.utils import create_pulsar_connection_str +from chromadb.proto.convert import from_proto_submit, to_proto_submit +import chromadb.proto.chroma_pb2 as proto +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import SeqId, SubmitEmbeddingRecord +import pulsar +from concurrent.futures import wait, Future + +from chromadb.utils.messageid import int_to_pulsar, pulsar_to_int + + +class PulsarProducer(Producer, EnforceOverrides): + # TODO: ensure trace context propagates + _connection_str: str + _topic_to_producer: Dict[str, pulsar.Producer] + _opentelemetry_client: OpenTelemetryClient + _client: pulsar.Client + _admin: PulsarAdmin + _settings: Settings + + def __init__(self, system: System) -> None: + pulsar_host = system.settings.require("pulsar_broker_url") + pulsar_port = system.settings.require("pulsar_broker_port") + self._connection_str = create_pulsar_connection_str(pulsar_host, pulsar_port) + self._topic_to_producer = {} + self._settings = system.settings + self._admin = PulsarAdmin(system) + self._opentelemetry_client = system.require(OpenTelemetryClient) + super().__init__(system) + + @overrides + def start(self) -> None: + self._client = pulsar.Client(self._connection_str) + super().start() + + @overrides + def stop(self) -> None: + self._client.close() + super().stop() + + @overrides + def create_topic(self, topic_name: str) -> None: + self._admin.create_topic(topic_name) + + @overrides + def delete_topic(self, topic_name: str) -> None: + self._admin.delete_topic(topic_name) + + @trace_method("PulsarProducer.submit_embedding", OpenTelemetryGranularity.ALL) + @overrides + def submit_embedding( + self, topic_name: str, embedding: SubmitEmbeddingRecord + ) -> SeqId: + """Add an embedding record to the given topic. Returns the SeqID of the record.""" + producer = self._get_or_create_producer(topic_name) + proto_submit: proto.SubmitEmbeddingRecord = to_proto_submit(embedding) + # TODO: batch performance / async + msg_id: pulsar.MessageId = producer.send(proto_submit.SerializeToString()) + return pulsar_to_int(msg_id) + + @trace_method("PulsarProducer.submit_embeddings", OpenTelemetryGranularity.ALL) + @overrides + def submit_embeddings( + self, topic_name: str, embeddings: Sequence[SubmitEmbeddingRecord] + ) -> Sequence[SeqId]: + if not self._running: + raise RuntimeError("Component not running") + + if len(embeddings) == 0: + return [] + + if len(embeddings) > self.max_batch_size: + raise ValueError( + f""" + Cannot submit more than {self.max_batch_size:,} embeddings at once. + Please submit your embeddings in batches of size + {self.max_batch_size:,} or less. + """ + ) + + producer = self._get_or_create_producer(topic_name) + protos_to_submit = [to_proto_submit(embedding) for embedding in embeddings] + + def create_producer_callback( + future: Future[int], + ) -> Callable[[Any, pulsar.MessageId], None]: + def producer_callback(res: Any, msg_id: pulsar.MessageId) -> None: + if msg_id: + future.set_result(pulsar_to_int(msg_id)) + else: + future.set_exception( + Exception( + "Unknown error while submitting embedding in producer_callback" + ) + ) + + return producer_callback + + futures = [] + for proto_to_submit in protos_to_submit: + future: Future[int] = Future() + producer.send_async( + proto_to_submit.SerializeToString(), + callback=create_producer_callback(future), + ) + futures.append(future) + + wait(futures) + + results: List[SeqId] = [] + for future in futures: + exception = future.exception() + if exception is not None: + raise exception + results.append(future.result()) + + return results + + @property + @overrides + def max_batch_size(self) -> int: + # For now, we use 1,000 + # TODO: tune this to a reasonable value by default + return 1000 + + def _get_or_create_producer(self, topic_name: str) -> pulsar.Producer: + if topic_name not in self._topic_to_producer: + producer = self._client.create_producer(topic_name) + self._topic_to_producer[topic_name] = producer + return self._topic_to_producer[topic_name] + + @overrides + def reset_state(self) -> None: + if not self._settings.require("allow_reset"): + raise ValueError( + "Resetting the database is not allowed. Set `allow_reset` to true in the config in tests or other non-production environments where reset should be permitted." + ) + for topic_name in self._topic_to_producer: + self._admin.delete_topic(topic_name) + self._topic_to_producer = {} + super().reset_state() + + +class PulsarConsumer(Consumer, EnforceOverrides): + class PulsarSubscription: + id: UUID + topic_name: str + start: int + end: int + callback: ConsumerCallbackFn + consumer: pulsar.Consumer + + def __init__( + self, + id: UUID, + topic_name: str, + start: int, + end: int, + callback: ConsumerCallbackFn, + consumer: pulsar.Consumer, + ): + self.id = id + self.topic_name = topic_name + self.start = start + self.end = end + self.callback = callback + self.consumer = consumer + + _connection_str: str + _client: pulsar.Client + _opentelemetry_client: OpenTelemetryClient + _subscriptions: Dict[str, Set[PulsarSubscription]] + _settings: Settings + + def __init__(self, system: System) -> None: + pulsar_host = system.settings.require("pulsar_broker_url") + pulsar_port = system.settings.require("pulsar_broker_port") + self._connection_str = create_pulsar_connection_str(pulsar_host, pulsar_port) + self._subscriptions = defaultdict(set) + self._settings = system.settings + self._opentelemetry_client = system.require(OpenTelemetryClient) + super().__init__(system) + + @overrides + def start(self) -> None: + self._client = pulsar.Client(self._connection_str) + super().start() + + @overrides + def stop(self) -> None: + self._client.close() + super().stop() + + @trace_method("PulsarConsumer.subscribe", OpenTelemetryGranularity.ALL) + @overrides + def subscribe( + self, + topic_name: str, + consume_fn: ConsumerCallbackFn, + start: Optional[SeqId] = None, + end: Optional[SeqId] = None, + id: Optional[UUID] = None, + ) -> UUID: + """Register a function that will be called to recieve embeddings for a given + topic. The given function may be called any number of times, with any number of + records, and may be called concurrently. + + Only records between start (exclusive) and end (inclusive) SeqIDs will be + returned. If start is None, the first record returned will be the next record + generated, not including those generated before creating the subscription. If + end is None, the consumer will consume indefinitely, otherwise it will + automatically be unsubscribed when the end SeqID is reached. + + If the function throws an exception, the function may be called again with the + same or different records. + + Takes an optional UUID as a unique subscription ID. If no ID is provided, a new + ID will be generated and returned.""" + if not self._running: + raise RuntimeError("Consumer must be started before subscribing") + + subscription_id = ( + id or uuid.uuid4() + ) # TODO: this should really be created by the coordinator and stored in sysdb + + start, end = self._validate_range(start, end) + + def wrap_callback(consumer: pulsar.Consumer, message: pulsar.Message) -> None: + msg_data = message.data() + msg_id = pulsar_to_int(message.message_id()) + submit_embedding_record = proto.SubmitEmbeddingRecord() + proto.SubmitEmbeddingRecord.ParseFromString( + submit_embedding_record, msg_data + ) + embedding_record = from_proto_submit(submit_embedding_record, msg_id) + consume_fn([embedding_record]) + consumer.acknowledge(message) + if msg_id == end: + self.unsubscribe(subscription_id) + + consumer = self._client.subscribe( + topic_name, + subscription_id.hex, + message_listener=wrap_callback, + ) + + subscription = self.PulsarSubscription( + subscription_id, topic_name, start, end, consume_fn, consumer + ) + self._subscriptions[topic_name].add(subscription) + + # NOTE: For some reason the seek() method expects a shadowed MessageId type + # which resides in _msg_id. + consumer.seek(int_to_pulsar(start)._msg_id) + + return subscription_id + + def _validate_range( + self, start: Optional[SeqId], end: Optional[SeqId] + ) -> Tuple[int, int]: + """Validate and normalize the start and end SeqIDs for a subscription using this + impl.""" + start = start or pulsar_to_int(pulsar.MessageId.latest) + end = end or self.max_seqid() + if not isinstance(start, int) or not isinstance(end, int): + raise TypeError("SeqIDs must be integers") + if start >= end: + raise ValueError(f"Invalid SeqID range: {start} to {end}") + return start, end + + @overrides + def unsubscribe(self, subscription_id: UUID) -> None: + """Unregister a subscription. The consume function will no longer be invoked, + and resources associated with the subscription will be released.""" + for topic_name, subscriptions in self._subscriptions.items(): + for subscription in subscriptions: + if subscription.id == subscription_id: + subscription.consumer.close() + subscriptions.remove(subscription) + if len(subscriptions) == 0: + del self._subscriptions[topic_name] + return + + @overrides + def min_seqid(self) -> SeqId: + """Return the minimum possible SeqID in this implementation.""" + return pulsar_to_int(pulsar.MessageId.earliest) + + @overrides + def max_seqid(self) -> SeqId: + """Return the maximum possible SeqID in this implementation.""" + return 2**192 - 1 + + @overrides + def reset_state(self) -> None: + if not self._settings.require("allow_reset"): + raise ValueError( + "Resetting the database is not allowed. Set `allow_reset` to true in the config in tests or other non-production environments where reset should be permitted." + ) + for topic_name, subscriptions in self._subscriptions.items(): + for subscription in subscriptions: + subscription.consumer.close() + self._subscriptions = defaultdict(set) + super().reset_state() diff --git a/chromadb/ingest/impl/pulsar_admin.py b/chromadb/ingest/impl/pulsar_admin.py new file mode 100644 index 0000000000000000000000000000000000000000..e031e4a238bad84a48e8a89a9b9d52c5242cfedf --- /dev/null +++ b/chromadb/ingest/impl/pulsar_admin.py @@ -0,0 +1,81 @@ +# A thin wrapper around the pulsar admin api +import requests +from chromadb.config import System +from chromadb.ingest.impl.utils import parse_topic_name + + +class PulsarAdmin: + """A thin wrapper around the pulsar admin api, only used for interim development towards distributed chroma. + This functionality will be moved to the chroma coordinator.""" + + _connection_str: str + + def __init__(self, system: System): + pulsar_host = system.settings.require("pulsar_broker_url") + pulsar_port = system.settings.require("pulsar_admin_port") + self._connection_str = f"http://{pulsar_host}:{pulsar_port}" + + # Create the default tenant and namespace + # This is a temporary workaround until we have a proper tenant/namespace management system + self.create_tenant("default") + self.create_namespace("default", "default") + + def create_tenant(self, tenant: str) -> None: + """Make a PUT request to the admin api to create the tenant""" + + path = f"/admin/v2/tenants/{tenant}" + url = self._connection_str + path + response = requests.put( + url, json={"allowedClusters": ["standalone"], "adminRoles": []} + ) # TODO: how to manage clusters? + + if response.status_code != 204 and response.status_code != 409: + raise RuntimeError(f"Failed to create tenant {tenant}") + + def create_namespace(self, tenant: str, namespace: str) -> None: + """Make a PUT request to the admin api to create the namespace""" + + path = f"/admin/v2/namespaces/{tenant}/{namespace}" + url = self._connection_str + path + response = requests.put(url) + + if response.status_code != 204 and response.status_code != 409: + raise RuntimeError(f"Failed to create namespace {namespace}") + + def create_topic(self, topic: str) -> None: + # TODO: support non-persistent topics? + tenant, namespace, topic_name = parse_topic_name(topic) + + if tenant != "default": + raise ValueError(f"Only the default tenant is supported, got {tenant}") + if namespace != "default": + raise ValueError( + f"Only the default namespace is supported, got {namespace}" + ) + + # Make a PUT request to the admin api to create the topic + path = f"/admin/v2/persistent/{tenant}/{namespace}/{topic_name}" + url = self._connection_str + path + response = requests.put(url) + + if response.status_code != 204 and response.status_code != 409: + raise RuntimeError(f"Failed to create topic {topic_name}") + + def delete_topic(self, topic: str) -> None: + tenant, namespace, topic_name = parse_topic_name(topic) + + if tenant != "default": + raise ValueError(f"Only the default tenant is supported, got {tenant}") + if namespace != "default": + raise ValueError( + f"Only the default namespace is supported, got {namespace}" + ) + + # Make a PUT request to the admin api to delete the topic + path = f"/admin/v2/persistent/{tenant}/{namespace}/{topic_name}" + # Force delete the topic + path += "?force=true" + url = self._connection_str + path + response = requests.delete(url) + if response.status_code != 204 and response.status_code != 409: + raise RuntimeError(f"Failed to delete topic {topic_name}") diff --git a/chromadb/ingest/impl/simple_policy.py b/chromadb/ingest/impl/simple_policy.py new file mode 100644 index 0000000000000000000000000000000000000000..f8068ee2046d5d83a274322379c888568c3d0fe4 --- /dev/null +++ b/chromadb/ingest/impl/simple_policy.py @@ -0,0 +1,61 @@ +from typing import Sequence +from uuid import UUID +from overrides import overrides +from chromadb.config import System +from chromadb.ingest import CollectionAssignmentPolicy +from chromadb.ingest.impl.utils import create_topic_name + + +class SimpleAssignmentPolicy(CollectionAssignmentPolicy): + """Simple assignment policy that assigns a 1 collection to 1 topic based on the + id of the collection.""" + + _tenant_id: str + _topic_ns: str + + def __init__(self, system: System): + self._tenant_id = system.settings.tenant_id + self._topic_ns = system.settings.topic_namespace + super().__init__(system) + + def _topic(self, collection_id: UUID) -> str: + return create_topic_name(self._tenant_id, self._topic_ns, str(collection_id)) + + @overrides + def assign_collection(self, collection_id: UUID) -> str: + return self._topic(collection_id) + + @overrides + def get_topics(self) -> Sequence[str]: + raise NotImplementedError( + "SimpleAssignmentPolicy does not support get_topics, each collection has its own topic" + ) + + +class RendezvousHashingAssignmentPolicy(CollectionAssignmentPolicy): + """The rendezvous hashing assignment policy assigns a collection to a topic based on the + rendezvous hashing algorithm. This is not actually used in the python sysdb. It is only used in the + go sysdb. However, it is useful here in order to provide a way to get the topic list used for the whole system. + """ + + _tenant_id: str + _topic_ns: str + + def __init__(self, system: System): + self._tenant_id = system.settings.tenant_id + self._topic_ns = system.settings.topic_namespace + super().__init__(system) + + @overrides + def assign_collection(self, collection_id: UUID) -> str: + raise NotImplementedError( + "RendezvousHashingAssignmentPolicy is not implemented" + ) + + @overrides + def get_topics(self) -> Sequence[str]: + # Mirrors go/coordinator/internal/coordinator/assignment_policy.go + return [ + f"persistent://{self._tenant_id}/{self._topic_ns}/chroma_log_{i}" + for i in range(16) + ] diff --git a/chromadb/ingest/impl/utils.py b/chromadb/ingest/impl/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..144384d75db5381d348debcb9d69fe90de61aada --- /dev/null +++ b/chromadb/ingest/impl/utils.py @@ -0,0 +1,20 @@ +import re +from typing import Tuple + +topic_regex = r"persistent:\/\/(?P.+)\/(?P.+)\/(?P.+)" + + +def parse_topic_name(topic_name: str) -> Tuple[str, str, str]: + """Parse the topic name into the tenant, namespace and topic name""" + match = re.match(topic_regex, topic_name) + if not match: + raise ValueError(f"Invalid topic name: {topic_name}") + return match.group("tenant"), match.group("namespace"), match.group("topic") + + +def create_pulsar_connection_str(host: str, port: str) -> str: + return f"pulsar://{host}:{port}" + + +def create_topic_name(tenant: str, namespace: str, topic: str) -> str: + return f"persistent://{tenant}/{namespace}/{topic}" diff --git a/chromadb/log_config.yml b/chromadb/log_config.yml new file mode 100644 index 0000000000000000000000000000000000000000..80e62479917c81b14ba5150d45f7c377bb873692 --- /dev/null +++ b/chromadb/log_config.yml @@ -0,0 +1,37 @@ +version: 1 +disable_existing_loggers: False +formatters: + default: + "()": uvicorn.logging.DefaultFormatter + format: '%(levelprefix)s [%(asctime)s] %(message)s' + use_colors: null + datefmt: '%d-%m-%Y %H:%M:%S' + access: + "()": uvicorn.logging.AccessFormatter + format: '%(levelprefix)s [%(asctime)s] %(client_addr)s - "%(request_line)s" %(status_code)s' + datefmt: '%d-%m-%Y %H:%M:%S' +handlers: + default: + formatter: default + class: logging.StreamHandler + stream: ext://sys.stderr + access: + formatter: access + class: logging.StreamHandler + stream: ext://sys.stdout + console: + class: logging.StreamHandler + stream: ext://sys.stdout + formatter: default + file: + class : logging.handlers.RotatingFileHandler + filename: chroma.log + formatter: default +loggers: + root: + level: WARN + handlers: [console, file] + chromadb: + level: DEBUG + uvicorn: + level: INFO diff --git a/chromadb/migrations/__init__.py b/chromadb/migrations/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/migrations/embeddings_queue/00001-embeddings.sqlite.sql b/chromadb/migrations/embeddings_queue/00001-embeddings.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..078bd897f984fbf892e7041ed530f1cf60062c8e --- /dev/null +++ b/chromadb/migrations/embeddings_queue/00001-embeddings.sqlite.sql @@ -0,0 +1,10 @@ +CREATE TABLE embeddings_queue ( + seq_id INTEGER PRIMARY KEY, + created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, + operation INTEGER NOT NULL, + topic TEXT NOT NULL, + id TEXT NOT NULL, + vector BLOB, + encoding TEXT, + metadata TEXT +); diff --git a/chromadb/migrations/metadb/00001-embedding-metadata.sqlite.sql b/chromadb/migrations/metadb/00001-embedding-metadata.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..cf2e820da64149976bd52a059e1152401266b710 --- /dev/null +++ b/chromadb/migrations/metadb/00001-embedding-metadata.sqlite.sql @@ -0,0 +1,24 @@ +CREATE TABLE embeddings ( + id INTEGER PRIMARY KEY, + segment_id TEXT NOT NULL, + embedding_id TEXT NOT NULL, + seq_id BLOB NOT NULL, + created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP, + UNIQUE (segment_id, embedding_id) +); + +CREATE TABLE embedding_metadata ( + id INTEGER REFERENCES embeddings(id), + key TEXT NOT NULL, + string_value TEXT, + int_value INTEGER, + float_value REAL, + PRIMARY KEY (id, key) +); + +CREATE TABLE max_seq_id ( + segment_id TEXT PRIMARY KEY, + seq_id BLOB NOT NULL +); + +CREATE VIRTUAL TABLE embedding_fulltext USING fts5(id, string_value); diff --git a/chromadb/migrations/metadb/00002-embedding-metadata.sqlite.sql b/chromadb/migrations/metadb/00002-embedding-metadata.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..9684b14ad6d4c5e3455d858d21b2a754434ed16c --- /dev/null +++ b/chromadb/migrations/metadb/00002-embedding-metadata.sqlite.sql @@ -0,0 +1,5 @@ +-- SQLite does not support adding check with alter table, as a result, adding a check +-- involve creating a new table and copying the data over. It is over kill with adding +-- a boolean type column. The application write to the table needs to ensure the data +-- integrity. +ALTER TABLE embedding_metadata ADD COLUMN bool_value INTEGER diff --git a/chromadb/migrations/metadb/00003-full-text-tokenize.sqlite.sql b/chromadb/migrations/metadb/00003-full-text-tokenize.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..2b8aa2111ad37ea6a80bde9b504d8d49d56a8f82 --- /dev/null +++ b/chromadb/migrations/metadb/00003-full-text-tokenize.sqlite.sql @@ -0,0 +1,3 @@ +CREATE VIRTUAL TABLE embedding_fulltext_search USING fts5(string_value, tokenize='trigram'); +INSERT INTO embedding_fulltext_search (rowid, string_value) SELECT rowid, string_value FROM embedding_metadata; +DROP TABLE embedding_fulltext; diff --git a/chromadb/migrations/sysdb/00001-collections.sqlite.sql b/chromadb/migrations/sysdb/00001-collections.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..99abeaab19464ab55493e231edb20c711f9f1184 --- /dev/null +++ b/chromadb/migrations/sysdb/00001-collections.sqlite.sql @@ -0,0 +1,15 @@ +CREATE TABLE collections ( + id TEXT PRIMARY KEY, + name TEXT NOT NULL, + topic TEXT NOT NULL, + UNIQUE (name) +); + +CREATE TABLE collection_metadata ( + collection_id TEXT REFERENCES collections(id) ON DELETE CASCADE, + key TEXT NOT NULL, + str_value TEXT, + int_value INTEGER, + float_value REAL, + PRIMARY KEY (collection_id, key) +); diff --git a/chromadb/migrations/sysdb/00002-segments.sqlite.sql b/chromadb/migrations/sysdb/00002-segments.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..4f4b8c25d0c24f4e5e6f0585e974a8cde3f2b62b --- /dev/null +++ b/chromadb/migrations/sysdb/00002-segments.sqlite.sql @@ -0,0 +1,16 @@ +CREATE TABLE segments ( + id TEXT PRIMARY KEY, + type TEXT NOT NULL, + scope TEXT NOT NULL, + topic TEXT, + collection TEXT REFERENCES collection(id) +); + +CREATE TABLE segment_metadata ( + segment_id TEXT REFERENCES segments(id) ON DELETE CASCADE, + key TEXT NOT NULL, + str_value TEXT, + int_value INTEGER, + float_value REAL, + PRIMARY KEY (segment_id, key) +); diff --git a/chromadb/migrations/sysdb/00003-collection-dimension.sqlite.sql b/chromadb/migrations/sysdb/00003-collection-dimension.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..cb793f49702267faceb208f088059ff01fcb55a4 --- /dev/null +++ b/chromadb/migrations/sysdb/00003-collection-dimension.sqlite.sql @@ -0,0 +1 @@ +ALTER TABLE collections ADD COLUMN dimension INTEGER; diff --git a/chromadb/migrations/sysdb/00004-tenants-databases.sqlite.sql b/chromadb/migrations/sysdb/00004-tenants-databases.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..43372bf97a8f13939189e081a1c851d23fd5c1f1 --- /dev/null +++ b/chromadb/migrations/sysdb/00004-tenants-databases.sqlite.sql @@ -0,0 +1,29 @@ +CREATE TABLE IF NOT EXISTS tenants ( + id TEXT PRIMARY KEY, + UNIQUE (id) +); + +CREATE TABLE IF NOT EXISTS databases ( + id TEXT PRIMARY KEY, -- unique globally + name TEXT NOT NULL, -- unique per tenant + tenant_id TEXT NOT NULL REFERENCES tenants(id) ON DELETE CASCADE, + UNIQUE (tenant_id, name) -- Ensure that a tenant has only one database with a given name +); + +CREATE TABLE IF NOT EXISTS collections_tmp ( + id TEXT PRIMARY KEY, -- unique globally + name TEXT NOT NULL, -- unique per database + topic TEXT NOT NULL, + dimension INTEGER, + database_id TEXT NOT NULL REFERENCES databases(id) ON DELETE CASCADE, + UNIQUE (name, database_id) +); + +-- Create default tenant and database +INSERT OR REPLACE INTO tenants (id) VALUES ('default_tenant'); -- The default tenant id is 'default_tenant' others are UUIDs +INSERT OR REPLACE INTO databases (id, name, tenant_id) VALUES ('00000000-0000-0000-0000-000000000000', 'default_database', 'default_tenant'); + +INSERT OR REPLACE INTO collections_tmp (id, name, topic, dimension, database_id) + SELECT id, name, topic, dimension, '00000000-0000-0000-0000-000000000000' FROM collections; +DROP TABLE collections; +ALTER TABLE collections_tmp RENAME TO collections; diff --git a/chromadb/proto/__init__.py b/chromadb/proto/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/proto/chroma_pb2.py b/chromadb/proto/chroma_pb2.py new file mode 100644 index 0000000000000000000000000000000000000000..84a3ba9b13dd1a6a6164ca539ee4b75bf6f96c69 --- /dev/null +++ b/chromadb/proto/chroma_pb2.py @@ -0,0 +1,74 @@ +# -*- coding: utf-8 -*- +# Generated by the protocol buffer compiler. DO NOT EDIT! +# source: chromadb/proto/chroma.proto +"""Generated protocol buffer code.""" +from google.protobuf import descriptor as _descriptor +from google.protobuf import descriptor_pool as _descriptor_pool +from google.protobuf import symbol_database as _symbol_database +from google.protobuf.internal import builder as _builder +# @@protoc_insertion_point(imports) + +_sym_db = _symbol_database.Default() + + + + +DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1b\x63hromadb/proto/chroma.proto\x12\x06\x63hroma\"&\n\x06Status\x12\x0e\n\x06reason\x18\x01 \x01(\t\x12\x0c\n\x04\x63ode\x18\x02 \x01(\x05\"0\n\x0e\x43hromaResponse\x12\x1e\n\x06status\x18\x01 \x01(\x0b\x32\x0e.chroma.Status\"U\n\x06Vector\x12\x11\n\tdimension\x18\x01 \x01(\x05\x12\x0e\n\x06vector\x18\x02 \x01(\x0c\x12(\n\x08\x65ncoding\x18\x03 \x01(\x0e\x32\x16.chroma.ScalarEncoding\"\xca\x01\n\x07Segment\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0c\n\x04type\x18\x02 \x01(\t\x12#\n\x05scope\x18\x03 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'chromadb.proto.chroma_pb2', _globals) +if _descriptor._USE_C_DESCRIPTORS == False: + DESCRIPTOR._options = None + DESCRIPTOR._serialized_options = b'ZAgithub.com/chroma/chroma-coordinator/internal/proto/coordinatorpb' + _UPDATEMETADATA_METADATAENTRY._options = None + _UPDATEMETADATA_METADATAENTRY._serialized_options = b'8\001' + _globals['_OPERATION']._serialized_start=1785 + _globals['_OPERATION']._serialized_end=1841 + _globals['_SCALARENCODING']._serialized_start=1843 + _globals['_SCALARENCODING']._serialized_end=1883 + _globals['_SEGMENTSCOPE']._serialized_start=1885 + _globals['_SEGMENTSCOPE']._serialized_end=1925 + _globals['_STATUS']._serialized_start=39 + _globals['_STATUS']._serialized_end=77 + _globals['_CHROMARESPONSE']._serialized_start=79 + _globals['_CHROMARESPONSE']._serialized_end=127 + _globals['_VECTOR']._serialized_start=129 + _globals['_VECTOR']._serialized_end=214 + _globals['_SEGMENT']._serialized_start=217 + _globals['_SEGMENT']._serialized_end=419 + _globals['_COLLECTION']._serialized_start=422 + _globals['_COLLECTION']._serialized_end=607 + _globals['_DATABASE']._serialized_start=609 + _globals['_DATABASE']._serialized_end=661 + _globals['_TENANT']._serialized_start=663 + _globals['_TENANT']._serialized_end=685 + _globals['_UPDATEMETADATAVALUE']._serialized_start=687 + _globals['_UPDATEMETADATAVALUE']._serialized_end=785 + _globals['_UPDATEMETADATA']._serialized_start=788 + _globals['_UPDATEMETADATA']._serialized_end=938 + _globals['_UPDATEMETADATA_METADATAENTRY']._serialized_start=862 + _globals['_UPDATEMETADATA_METADATAENTRY']._serialized_end=938 + _globals['_SUBMITEMBEDDINGRECORD']._serialized_start=941 + _globals['_SUBMITEMBEDDINGRECORD']._serialized_end=1145 + _globals['_VECTOREMBEDDINGRECORD']._serialized_start=1147 + _globals['_VECTOREMBEDDINGRECORD']._serialized_end=1230 + _globals['_VECTORQUERYRESULT']._serialized_start=1232 + _globals['_VECTORQUERYRESULT']._serialized_end=1345 + _globals['_VECTORQUERYRESULTS']._serialized_start=1347 + _globals['_VECTORQUERYRESULTS']._serialized_end=1411 + _globals['_SEGMENTSERVERRESPONSE']._serialized_start=1413 + _globals['_SEGMENTSERVERRESPONSE']._serialized_end=1453 + _globals['_GETVECTORSREQUEST']._serialized_start=1455 + _globals['_GETVECTORSREQUEST']._serialized_end=1507 + _globals['_GETVECTORSRESPONSE']._serialized_start=1509 + _globals['_GETVECTORSRESPONSE']._serialized_end=1577 + _globals['_QUERYVECTORSREQUEST']._serialized_start=1580 + _globals['_QUERYVECTORSREQUEST']._serialized_end=1714 + _globals['_QUERYVECTORSRESPONSE']._serialized_start=1716 + _globals['_QUERYVECTORSRESPONSE']._serialized_end=1783 + _globals['_SEGMENTSERVER']._serialized_start=1928 + _globals['_SEGMENTSERVER']._serialized_end=2076 + _globals['_VECTORREADER']._serialized_start=2079 + _globals['_VECTORREADER']._serialized_end=2241 +# @@protoc_insertion_point(module_scope) diff --git a/chromadb/proto/chroma_pb2.pyi b/chromadb/proto/chroma_pb2.pyi new file mode 100644 index 0000000000000000000000000000000000000000..026bfac88211469daaabeda75c327f0616de36f4 --- /dev/null +++ b/chromadb/proto/chroma_pb2.pyi @@ -0,0 +1,205 @@ +from google.protobuf.internal import containers as _containers +from google.protobuf.internal import enum_type_wrapper as _enum_type_wrapper +from google.protobuf import descriptor as _descriptor +from google.protobuf import message as _message +from typing import ClassVar as _ClassVar, Iterable as _Iterable, Mapping as _Mapping, Optional as _Optional, Union as _Union + +DESCRIPTOR: _descriptor.FileDescriptor + +class Operation(int, metaclass=_enum_type_wrapper.EnumTypeWrapper): + __slots__ = [] + ADD: _ClassVar[Operation] + UPDATE: _ClassVar[Operation] + UPSERT: _ClassVar[Operation] + DELETE: _ClassVar[Operation] + +class ScalarEncoding(int, metaclass=_enum_type_wrapper.EnumTypeWrapper): + __slots__ = [] + FLOAT32: _ClassVar[ScalarEncoding] + INT32: _ClassVar[ScalarEncoding] + +class SegmentScope(int, metaclass=_enum_type_wrapper.EnumTypeWrapper): + __slots__ = [] + VECTOR: _ClassVar[SegmentScope] + METADATA: _ClassVar[SegmentScope] +ADD: Operation +UPDATE: Operation +UPSERT: Operation +DELETE: Operation +FLOAT32: ScalarEncoding +INT32: ScalarEncoding +VECTOR: SegmentScope +METADATA: SegmentScope + +class Status(_message.Message): + __slots__ = ["reason", "code"] + REASON_FIELD_NUMBER: _ClassVar[int] + CODE_FIELD_NUMBER: _ClassVar[int] + reason: str + code: int + def __init__(self, reason: _Optional[str] = ..., code: _Optional[int] = ...) -> None: ... + +class ChromaResponse(_message.Message): + __slots__ = ["status"] + STATUS_FIELD_NUMBER: _ClassVar[int] + status: Status + def __init__(self, status: _Optional[_Union[Status, _Mapping]] = ...) -> None: ... + +class Vector(_message.Message): + __slots__ = ["dimension", "vector", "encoding"] + DIMENSION_FIELD_NUMBER: _ClassVar[int] + VECTOR_FIELD_NUMBER: _ClassVar[int] + ENCODING_FIELD_NUMBER: _ClassVar[int] + dimension: int + vector: bytes + encoding: ScalarEncoding + def __init__(self, dimension: _Optional[int] = ..., vector: _Optional[bytes] = ..., encoding: _Optional[_Union[ScalarEncoding, str]] = ...) -> None: ... + +class Segment(_message.Message): + __slots__ = ["id", "type", "scope", "topic", "collection", "metadata"] + ID_FIELD_NUMBER: _ClassVar[int] + TYPE_FIELD_NUMBER: _ClassVar[int] + SCOPE_FIELD_NUMBER: _ClassVar[int] + TOPIC_FIELD_NUMBER: _ClassVar[int] + COLLECTION_FIELD_NUMBER: _ClassVar[int] + METADATA_FIELD_NUMBER: _ClassVar[int] + id: str + type: str + scope: SegmentScope + topic: str + collection: str + metadata: UpdateMetadata + def __init__(self, id: _Optional[str] = ..., type: _Optional[str] = ..., scope: _Optional[_Union[SegmentScope, str]] = ..., topic: _Optional[str] = ..., collection: _Optional[str] = ..., metadata: _Optional[_Union[UpdateMetadata, _Mapping]] = ...) -> None: ... + +class Collection(_message.Message): + __slots__ = ["id", "name", "topic", "metadata", "dimension", "tenant", "database"] + ID_FIELD_NUMBER: _ClassVar[int] + NAME_FIELD_NUMBER: _ClassVar[int] + TOPIC_FIELD_NUMBER: _ClassVar[int] + METADATA_FIELD_NUMBER: _ClassVar[int] + DIMENSION_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + DATABASE_FIELD_NUMBER: _ClassVar[int] + id: str + name: str + topic: str + metadata: UpdateMetadata + dimension: int + tenant: str + database: str + def __init__(self, id: _Optional[str] = ..., name: _Optional[str] = ..., topic: _Optional[str] = ..., metadata: _Optional[_Union[UpdateMetadata, _Mapping]] = ..., dimension: _Optional[int] = ..., tenant: _Optional[str] = ..., database: _Optional[str] = ...) -> None: ... + +class Database(_message.Message): + __slots__ = ["id", "name", "tenant"] + ID_FIELD_NUMBER: _ClassVar[int] + NAME_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + id: str + name: str + tenant: str + def __init__(self, id: _Optional[str] = ..., name: _Optional[str] = ..., tenant: _Optional[str] = ...) -> None: ... + +class Tenant(_message.Message): + __slots__ = ["name"] + NAME_FIELD_NUMBER: _ClassVar[int] + name: str + def __init__(self, name: _Optional[str] = ...) -> None: ... + +class UpdateMetadataValue(_message.Message): + __slots__ = ["string_value", "int_value", "float_value"] + STRING_VALUE_FIELD_NUMBER: _ClassVar[int] + INT_VALUE_FIELD_NUMBER: _ClassVar[int] + FLOAT_VALUE_FIELD_NUMBER: _ClassVar[int] + string_value: str + int_value: int + float_value: float + def __init__(self, string_value: _Optional[str] = ..., int_value: _Optional[int] = ..., float_value: _Optional[float] = ...) -> None: ... + +class UpdateMetadata(_message.Message): + __slots__ = ["metadata"] + class MetadataEntry(_message.Message): + __slots__ = ["key", "value"] + KEY_FIELD_NUMBER: _ClassVar[int] + VALUE_FIELD_NUMBER: _ClassVar[int] + key: str + value: UpdateMetadataValue + def __init__(self, key: _Optional[str] = ..., value: _Optional[_Union[UpdateMetadataValue, _Mapping]] = ...) -> None: ... + METADATA_FIELD_NUMBER: _ClassVar[int] + metadata: _containers.MessageMap[str, UpdateMetadataValue] + def __init__(self, metadata: _Optional[_Mapping[str, UpdateMetadataValue]] = ...) -> None: ... + +class SubmitEmbeddingRecord(_message.Message): + __slots__ = ["id", "vector", "metadata", "operation", "collection_id"] + ID_FIELD_NUMBER: _ClassVar[int] + VECTOR_FIELD_NUMBER: _ClassVar[int] + METADATA_FIELD_NUMBER: _ClassVar[int] + OPERATION_FIELD_NUMBER: _ClassVar[int] + COLLECTION_ID_FIELD_NUMBER: _ClassVar[int] + id: str + vector: Vector + metadata: UpdateMetadata + operation: Operation + collection_id: str + def __init__(self, id: _Optional[str] = ..., vector: _Optional[_Union[Vector, _Mapping]] = ..., metadata: _Optional[_Union[UpdateMetadata, _Mapping]] = ..., operation: _Optional[_Union[Operation, str]] = ..., collection_id: _Optional[str] = ...) -> None: ... + +class VectorEmbeddingRecord(_message.Message): + __slots__ = ["id", "seq_id", "vector"] + ID_FIELD_NUMBER: _ClassVar[int] + SEQ_ID_FIELD_NUMBER: _ClassVar[int] + VECTOR_FIELD_NUMBER: _ClassVar[int] + id: str + seq_id: bytes + vector: Vector + def __init__(self, id: _Optional[str] = ..., seq_id: _Optional[bytes] = ..., vector: _Optional[_Union[Vector, _Mapping]] = ...) -> None: ... + +class VectorQueryResult(_message.Message): + __slots__ = ["id", "seq_id", "distance", "vector"] + ID_FIELD_NUMBER: _ClassVar[int] + SEQ_ID_FIELD_NUMBER: _ClassVar[int] + DISTANCE_FIELD_NUMBER: _ClassVar[int] + VECTOR_FIELD_NUMBER: _ClassVar[int] + id: str + seq_id: bytes + distance: float + vector: Vector + def __init__(self, id: _Optional[str] = ..., seq_id: _Optional[bytes] = ..., distance: _Optional[float] = ..., vector: _Optional[_Union[Vector, _Mapping]] = ...) -> None: ... + +class VectorQueryResults(_message.Message): + __slots__ = ["results"] + RESULTS_FIELD_NUMBER: _ClassVar[int] + results: _containers.RepeatedCompositeFieldContainer[VectorQueryResult] + def __init__(self, results: _Optional[_Iterable[_Union[VectorQueryResult, _Mapping]]] = ...) -> None: ... + +class GetVectorsRequest(_message.Message): + __slots__ = ["ids", "segment_id"] + IDS_FIELD_NUMBER: _ClassVar[int] + SEGMENT_ID_FIELD_NUMBER: _ClassVar[int] + ids: _containers.RepeatedScalarFieldContainer[str] + segment_id: str + def __init__(self, ids: _Optional[_Iterable[str]] = ..., segment_id: _Optional[str] = ...) -> None: ... + +class GetVectorsResponse(_message.Message): + __slots__ = ["records"] + RECORDS_FIELD_NUMBER: _ClassVar[int] + records: _containers.RepeatedCompositeFieldContainer[VectorEmbeddingRecord] + def __init__(self, records: _Optional[_Iterable[_Union[VectorEmbeddingRecord, _Mapping]]] = ...) -> None: ... + +class QueryVectorsRequest(_message.Message): + __slots__ = ["vectors", "k", "allowed_ids", "include_embeddings", "segment_id"] + VECTORS_FIELD_NUMBER: _ClassVar[int] + K_FIELD_NUMBER: _ClassVar[int] + ALLOWED_IDS_FIELD_NUMBER: _ClassVar[int] + INCLUDE_EMBEDDINGS_FIELD_NUMBER: _ClassVar[int] + SEGMENT_ID_FIELD_NUMBER: _ClassVar[int] + vectors: _containers.RepeatedCompositeFieldContainer[Vector] + k: int + allowed_ids: _containers.RepeatedScalarFieldContainer[str] + include_embeddings: bool + segment_id: str + def __init__(self, vectors: _Optional[_Iterable[_Union[Vector, _Mapping]]] = ..., k: _Optional[int] = ..., allowed_ids: _Optional[_Iterable[str]] = ..., include_embeddings: bool = ..., segment_id: _Optional[str] = ...) -> None: ... + +class QueryVectorsResponse(_message.Message): + __slots__ = ["results"] + RESULTS_FIELD_NUMBER: _ClassVar[int] + results: _containers.RepeatedCompositeFieldContainer[VectorQueryResults] + def __init__(self, results: _Optional[_Iterable[_Union[VectorQueryResults, _Mapping]]] = ...) -> None: ... diff --git a/chromadb/proto/chroma_pb2_grpc.py b/chromadb/proto/chroma_pb2_grpc.py new file mode 100644 index 0000000000000000000000000000000000000000..ccd53e449c0d7b52c22e3a0e0ee6927acf45e24e --- /dev/null +++ b/chromadb/proto/chroma_pb2_grpc.py @@ -0,0 +1,124 @@ +# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! +"""Client and server classes corresponding to protobuf-defined services.""" +import grpc + +from chromadb.proto import chroma_pb2 as chromadb_dot_proto_dot_chroma__pb2 + + +class VectorReaderStub(object): + """Vector Reader Interface""" + + def __init__(self, channel): + """Constructor. + + Args: + channel: A grpc.Channel. + """ + self.GetVectors = channel.unary_unary( + "/chroma.VectorReader/GetVectors", + request_serializer=chromadb_dot_proto_dot_chroma__pb2.GetVectorsRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.GetVectorsResponse.FromString, + ) + self.QueryVectors = channel.unary_unary( + "/chroma.VectorReader/QueryVectors", + request_serializer=chromadb_dot_proto_dot_chroma__pb2.QueryVectorsRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.QueryVectorsResponse.FromString, + ) + + +class VectorReaderServicer(object): + """Vector Reader Interface""" + + def GetVectors(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def QueryVectors(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + +def add_VectorReaderServicer_to_server(servicer, server): + rpc_method_handlers = { + "GetVectors": grpc.unary_unary_rpc_method_handler( + servicer.GetVectors, + request_deserializer=chromadb_dot_proto_dot_chroma__pb2.GetVectorsRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.GetVectorsResponse.SerializeToString, + ), + "QueryVectors": grpc.unary_unary_rpc_method_handler( + servicer.QueryVectors, + request_deserializer=chromadb_dot_proto_dot_chroma__pb2.QueryVectorsRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.QueryVectorsResponse.SerializeToString, + ), + } + generic_handler = grpc.method_handlers_generic_handler( + "chroma.VectorReader", rpc_method_handlers + ) + server.add_generic_rpc_handlers((generic_handler,)) + + +# This class is part of an EXPERIMENTAL API. +class VectorReader(object): + """Vector Reader Interface""" + + @staticmethod + def GetVectors( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.VectorReader/GetVectors", + chromadb_dot_proto_dot_chroma__pb2.GetVectorsRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.GetVectorsResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def QueryVectors( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.VectorReader/QueryVectors", + chromadb_dot_proto_dot_chroma__pb2.QueryVectorsRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.QueryVectorsResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) diff --git a/chromadb/proto/convert.py b/chromadb/proto/convert.py new file mode 100644 index 0000000000000000000000000000000000000000..78eaeb89101f24ccef386fb74ec2e84197dceeda --- /dev/null +++ b/chromadb/proto/convert.py @@ -0,0 +1,297 @@ +import array +from uuid import UUID +from typing import Dict, Optional, Tuple, Union, cast +from chromadb.api.types import Embedding +import chromadb.proto.chroma_pb2 as proto +from chromadb.utils.messageid import bytes_to_int, int_to_bytes +from chromadb.types import ( + Collection, + EmbeddingRecord, + Metadata, + Operation, + ScalarEncoding, + Segment, + SegmentScope, + SeqId, + SubmitEmbeddingRecord, + UpdateMetadata, + Vector, + VectorEmbeddingRecord, + VectorQueryResult, +) + + +# TODO: Unit tests for this file, handling optional states etc + + +def to_proto_vector(vector: Vector, encoding: ScalarEncoding) -> proto.Vector: + if encoding == ScalarEncoding.FLOAT32: + as_bytes = array.array("f", vector).tobytes() + proto_encoding = proto.ScalarEncoding.FLOAT32 + elif encoding == ScalarEncoding.INT32: + as_bytes = array.array("i", vector).tobytes() + proto_encoding = proto.ScalarEncoding.INT32 + else: + raise ValueError( + f"Unknown encoding {encoding}, expected one of {ScalarEncoding.FLOAT32} \ + or {ScalarEncoding.INT32}" + ) + + return proto.Vector(dimension=len(vector), vector=as_bytes, encoding=proto_encoding) + + +def from_proto_vector(vector: proto.Vector) -> Tuple[Embedding, ScalarEncoding]: + encoding = vector.encoding + as_array: Union[array.array[float], array.array[int]] + if encoding == proto.ScalarEncoding.FLOAT32: + as_array = array.array("f") + out_encoding = ScalarEncoding.FLOAT32 + elif encoding == proto.ScalarEncoding.INT32: + as_array = array.array("i") + out_encoding = ScalarEncoding.INT32 + else: + raise ValueError( + f"Unknown encoding {encoding}, expected one of \ + {proto.ScalarEncoding.FLOAT32} or {proto.ScalarEncoding.INT32}" + ) + + as_array.frombytes(vector.vector) + return (as_array.tolist(), out_encoding) + + +def from_proto_operation(operation: proto.Operation) -> Operation: + if operation == proto.Operation.ADD: + return Operation.ADD + elif operation == proto.Operation.UPDATE: + return Operation.UPDATE + elif operation == proto.Operation.UPSERT: + return Operation.UPSERT + elif operation == proto.Operation.DELETE: + return Operation.DELETE + else: + # TODO: full error + raise RuntimeError(f"Unknown operation {operation}") + + +def from_proto_metadata(metadata: proto.UpdateMetadata) -> Optional[Metadata]: + return cast(Optional[Metadata], _from_proto_metadata_handle_none(metadata, False)) + + +def from_proto_update_metadata( + metadata: proto.UpdateMetadata, +) -> Optional[UpdateMetadata]: + return cast( + Optional[UpdateMetadata], _from_proto_metadata_handle_none(metadata, True) + ) + + +def _from_proto_metadata_handle_none( + metadata: proto.UpdateMetadata, is_update: bool +) -> Optional[Union[UpdateMetadata, Metadata]]: + if not metadata.metadata: + return None + out_metadata: Dict[str, Union[str, int, float, None]] = {} + for key, value in metadata.metadata.items(): + if value.HasField("string_value"): + out_metadata[key] = value.string_value + elif value.HasField("int_value"): + out_metadata[key] = value.int_value + elif value.HasField("float_value"): + out_metadata[key] = value.float_value + elif is_update: + out_metadata[key] = None + else: + raise ValueError(f"Metadata key {key} value cannot be None") + return out_metadata + + +def to_proto_update_metadata(metadata: UpdateMetadata) -> proto.UpdateMetadata: + return proto.UpdateMetadata( + metadata={k: to_proto_metadata_update_value(v) for k, v in metadata.items()} + ) + + +def from_proto_submit( + submit_embedding_record: proto.SubmitEmbeddingRecord, seq_id: SeqId +) -> EmbeddingRecord: + embedding, encoding = from_proto_vector(submit_embedding_record.vector) + record = EmbeddingRecord( + id=submit_embedding_record.id, + seq_id=seq_id, + embedding=embedding, + encoding=encoding, + metadata=from_proto_update_metadata(submit_embedding_record.metadata), + operation=from_proto_operation(submit_embedding_record.operation), + collection_id=UUID(hex=submit_embedding_record.collection_id), + ) + return record + + +def from_proto_segment(segment: proto.Segment) -> Segment: + return Segment( + id=UUID(hex=segment.id), + type=segment.type, + scope=from_proto_segment_scope(segment.scope), + topic=segment.topic if segment.HasField("topic") else None, + collection=None + if not segment.HasField("collection") + else UUID(hex=segment.collection), + metadata=from_proto_metadata(segment.metadata) + if segment.HasField("metadata") + else None, + ) + + +def to_proto_segment(segment: Segment) -> proto.Segment: + return proto.Segment( + id=segment["id"].hex, + type=segment["type"], + scope=to_proto_segment_scope(segment["scope"]), + topic=segment["topic"], + collection=None if segment["collection"] is None else segment["collection"].hex, + metadata=None + if segment["metadata"] is None + else to_proto_update_metadata(segment["metadata"]), + ) + + +def from_proto_segment_scope(segment_scope: proto.SegmentScope) -> SegmentScope: + if segment_scope == proto.SegmentScope.VECTOR: + return SegmentScope.VECTOR + elif segment_scope == proto.SegmentScope.METADATA: + return SegmentScope.METADATA + else: + raise RuntimeError(f"Unknown segment scope {segment_scope}") + + +def to_proto_segment_scope(segment_scope: SegmentScope) -> proto.SegmentScope: + if segment_scope == SegmentScope.VECTOR: + return proto.SegmentScope.VECTOR + elif segment_scope == SegmentScope.METADATA: + return proto.SegmentScope.METADATA + else: + raise RuntimeError(f"Unknown segment scope {segment_scope}") + + +def to_proto_metadata_update_value( + value: Union[str, int, float, None] +) -> proto.UpdateMetadataValue: + if isinstance(value, str): + return proto.UpdateMetadataValue(string_value=value) + elif isinstance(value, int): + return proto.UpdateMetadataValue(int_value=value) + elif isinstance(value, float): + return proto.UpdateMetadataValue(float_value=value) + elif value is None: + return proto.UpdateMetadataValue() + else: + raise ValueError( + f"Unknown metadata value type {type(value)}, expected one of str, int, \ + float, or None" + ) + + +def from_proto_collection(collection: proto.Collection) -> Collection: + return Collection( + id=UUID(hex=collection.id), + name=collection.name, + topic=collection.topic, + metadata=from_proto_metadata(collection.metadata) + if collection.HasField("metadata") + else None, + dimension=collection.dimension + if collection.HasField("dimension") and collection.dimension + else None, + database=collection.database, + tenant=collection.tenant, + ) + + +def to_proto_collection(collection: Collection) -> proto.Collection: + return proto.Collection( + id=collection["id"].hex, + name=collection["name"], + topic=collection["topic"], + metadata=None + if collection["metadata"] is None + else to_proto_update_metadata(collection["metadata"]), + dimension=collection["dimension"], + tenant=collection["tenant"], + database=collection["database"], + ) + + +def to_proto_operation(operation: Operation) -> proto.Operation: + if operation == Operation.ADD: + return proto.Operation.ADD + elif operation == Operation.UPDATE: + return proto.Operation.UPDATE + elif operation == Operation.UPSERT: + return proto.Operation.UPSERT + elif operation == Operation.DELETE: + return proto.Operation.DELETE + else: + raise ValueError( + f"Unknown operation {operation}, expected one of {Operation.ADD}, \ + {Operation.UPDATE}, {Operation.UPDATE}, or {Operation.DELETE}" + ) + + +def to_proto_submit( + submit_record: SubmitEmbeddingRecord, +) -> proto.SubmitEmbeddingRecord: + vector = None + if submit_record["embedding"] is not None and submit_record["encoding"] is not None: + vector = to_proto_vector(submit_record["embedding"], submit_record["encoding"]) + + metadata = None + if submit_record["metadata"] is not None: + metadata = to_proto_update_metadata(submit_record["metadata"]) + + return proto.SubmitEmbeddingRecord( + id=submit_record["id"], + vector=vector, + metadata=metadata, + operation=to_proto_operation(submit_record["operation"]), + collection_id=submit_record["collection_id"].hex, + ) + + +def from_proto_vector_embedding_record( + embedding_record: proto.VectorEmbeddingRecord, +) -> VectorEmbeddingRecord: + return VectorEmbeddingRecord( + id=embedding_record.id, + seq_id=from_proto_seq_id(embedding_record.seq_id), + embedding=from_proto_vector(embedding_record.vector)[0], + ) + + +def to_proto_vector_embedding_record( + embedding_record: VectorEmbeddingRecord, + encoding: ScalarEncoding, +) -> proto.VectorEmbeddingRecord: + return proto.VectorEmbeddingRecord( + id=embedding_record["id"], + seq_id=to_proto_seq_id(embedding_record["seq_id"]), + vector=to_proto_vector(embedding_record["embedding"], encoding), + ) + + +def from_proto_vector_query_result( + vector_query_result: proto.VectorQueryResult, +) -> VectorQueryResult: + return VectorQueryResult( + id=vector_query_result.id, + seq_id=from_proto_seq_id(vector_query_result.seq_id), + distance=vector_query_result.distance, + embedding=from_proto_vector(vector_query_result.vector)[0], + ) + + +def to_proto_seq_id(seq_id: SeqId) -> bytes: + return int_to_bytes(seq_id) + + +def from_proto_seq_id(seq_id: bytes) -> SeqId: + return bytes_to_int(seq_id) diff --git a/chromadb/proto/coordinator_pb2.py b/chromadb/proto/coordinator_pb2.py new file mode 100644 index 0000000000000000000000000000000000000000..fda6a0998670a6bed4e9eb2d69c4da46b0d6f4f4 --- /dev/null +++ b/chromadb/proto/coordinator_pb2.py @@ -0,0 +1,62 @@ +# -*- coding: utf-8 -*- +# Generated by the protocol buffer compiler. DO NOT EDIT! +# source: chromadb/proto/coordinator.proto +"""Generated protocol buffer code.""" +from google.protobuf import descriptor as _descriptor +from google.protobuf import descriptor_pool as _descriptor_pool +from google.protobuf import symbol_database as _symbol_database +from google.protobuf.internal import builder as _builder +# @@protoc_insertion_point(imports) + +_sym_db = _symbol_database.Default() + + +from chromadb.proto import chroma_pb2 as chromadb_dot_proto_dot_chroma__pb2 +from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2 + + +DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n chromadb/proto/coordinator.proto\x12\x06\x63hroma\x1a\x1b\x63hromadb/proto/chroma.proto\x1a\x1bgoogle/protobuf/empty.proto\"A\n\x15\x43reateDatabaseRequest\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\x0e\n\x06tenant\x18\x03 \x01(\t\"2\n\x12GetDatabaseRequest\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0e\n\x06tenant\x18\x02 \x01(\t\"Y\n\x13GetDatabaseResponse\x12\"\n\x08\x64\x61tabase\x18\x01 \x01(\x0b\x32\x10.chroma.Database\x12\x1e\n\x06status\x18\x02 \x01(\x0b\x32\x0e.chroma.Status\"#\n\x13\x43reateTenantRequest\x12\x0c\n\x04name\x18\x02 \x01(\t\" \n\x10GetTenantRequest\x12\x0c\n\x04name\x18\x01 \x01(\t\"S\n\x11GetTenantResponse\x12\x1e\n\x06tenant\x18\x01 \x01(\x0b\x32\x0e.chroma.Tenant\x12\x1e\n\x06status\x18\x02 \x01(\x0b\x32\x0e.chroma.Status\"8\n\x14\x43reateSegmentRequest\x12 \n\x07segment\x18\x01 \x01(\x0b\x32\x0f.chroma.Segment\"\"\n\x14\x44\x65leteSegmentRequest\x12\n\n\x02id\x18\x01 \x01(\t\"\xc2\x01\n\x12GetSegmentsRequest\x12\x0f\n\x02id\x18\x01 \x01(\tH\x00\x88\x01\x01\x12\x11\n\x04type\x18\x02 \x01(\tH\x01\x88\x01\x01\x12(\n\x05scope\x18\x03 \x01(\x0e\x32\x14.chroma.SegmentScopeH\x02\x88\x01\x01\x12\x12\n\x05topic\x18\x04 \x01(\tH\x03\x88\x01\x01\x12\x17\n\ncollection\x18\x05 \x01(\tH\x04\x88\x01\x01\x42\x05\n\x03_idB\x07\n\x05_typeB\x08\n\x06_scopeB\x08\n\x06_topicB\r\n\x0b_collection\"X\n\x13GetSegmentsResponse\x12!\n\x08segments\x18\x01 \x03(\x0b\x32\x0f.chroma.Segment\x12\x1e\n\x06status\x18\x02 \x01(\x0b\x32\x0e.chroma.Status\"\xfa\x01\n\x14UpdateSegmentRequest\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0f\n\x05topic\x18\x02 \x01(\tH\x00\x12\x15\n\x0breset_topic\x18\x03 \x01(\x08H\x00\x12\x14\n\ncollection\x18\x04 \x01(\tH\x01\x12\x1a\n\x10reset_collection\x18\x05 \x01(\x08H\x01\x12*\n\x08metadata\x18\x06 \x01(\x0b\x32\x16.chroma.UpdateMetadataH\x02\x12\x18\n\x0ereset_metadata\x18\x07 \x01(\x08H\x02\x42\x0e\n\x0ctopic_updateB\x13\n\x11\x63ollection_updateB\x11\n\x0fmetadata_update\"\xe5\x01\n\x17\x43reateCollectionRequest\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0c\n\x04name\x18\x02 \x01(\t\x12-\n\x08metadata\x18\x03 \x01(\x0b\x32\x16.chroma.UpdateMetadataH\x00\x88\x01\x01\x12\x16\n\tdimension\x18\x04 \x01(\x05H\x01\x88\x01\x01\x12\x1a\n\rget_or_create\x18\x05 \x01(\x08H\x02\x88\x01\x01\x12\x0e\n\x06tenant\x18\x06 \x01(\t\x12\x10\n\x08\x64\x61tabase\x18\x07 \x01(\tB\x0b\n\t_metadataB\x0c\n\n_dimensionB\x10\n\x0e_get_or_create\"s\n\x18\x43reateCollectionResponse\x12&\n\ncollection\x18\x01 \x01(\x0b\x32\x12.chroma.Collection\x12\x0f\n\x07\x63reated\x18\x02 \x01(\x08\x12\x1e\n\x06status\x18\x03 \x01(\x0b\x32\x0e.chroma.Status\"G\n\x17\x44\x65leteCollectionRequest\x12\n\n\x02id\x18\x01 \x01(\t\x12\x0e\n\x06tenant\x18\x02 \x01(\t\x12\x10\n\x08\x64\x61tabase\x18\x03 \x01(\t\"\x8b\x01\n\x15GetCollectionsRequest\x12\x0f\n\x02id\x18\x01 \x01(\tH\x00\x88\x01\x01\x12\x11\n\x04name\x18\x02 \x01(\tH\x01\x88\x01\x01\x12\x12\n\x05topic\x18\x03 \x01(\tH\x02\x88\x01\x01\x12\x0e\n\x06tenant\x18\x04 \x01(\t\x12\x10\n\x08\x64\x61tabase\x18\x05 \x01(\tB\x05\n\x03_idB\x07\n\x05_nameB\x08\n\x06_topic\"a\n\x16GetCollectionsResponse\x12\'\n\x0b\x63ollections\x18\x01 \x03(\x0b\x32\x12.chroma.Collection\x12\x1e\n\x06status\x18\x02 \x01(\x0b\x32\x0e.chroma.Status\"\xde\x01\n\x17UpdateCollectionRequest\x12\n\n\x02id\x18\x01 \x01(\t\x12\x12\n\x05topic\x18\x02 \x01(\tH\x01\x88\x01\x01\x12\x11\n\x04name\x18\x03 \x01(\tH\x02\x88\x01\x01\x12\x16\n\tdimension\x18\x04 \x01(\x05H\x03\x88\x01\x01\x12*\n\x08metadata\x18\x05 \x01(\x0b\x32\x16.chroma.UpdateMetadataH\x00\x12\x18\n\x0ereset_metadata\x18\x06 \x01(\x08H\x00\x42\x11\n\x0fmetadata_updateB\x08\n\x06_topicB\x07\n\x05_nameB\x0c\n\n_dimension2\xd6\x07\n\x05SysDB\x12I\n\x0e\x43reateDatabase\x12\x1d.chroma.CreateDatabaseRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12H\n\x0bGetDatabase\x12\x1a.chroma.GetDatabaseRequest\x1a\x1b.chroma.GetDatabaseResponse\"\x00\x12\x45\n\x0c\x43reateTenant\x12\x1b.chroma.CreateTenantRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12\x42\n\tGetTenant\x12\x18.chroma.GetTenantRequest\x1a\x19.chroma.GetTenantResponse\"\x00\x12G\n\rCreateSegment\x12\x1c.chroma.CreateSegmentRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12G\n\rDeleteSegment\x12\x1c.chroma.DeleteSegmentRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12H\n\x0bGetSegments\x12\x1a.chroma.GetSegmentsRequest\x1a\x1b.chroma.GetSegmentsResponse\"\x00\x12G\n\rUpdateSegment\x12\x1c.chroma.UpdateSegmentRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12W\n\x10\x43reateCollection\x12\x1f.chroma.CreateCollectionRequest\x1a .chroma.CreateCollectionResponse\"\x00\x12M\n\x10\x44\x65leteCollection\x12\x1f.chroma.DeleteCollectionRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12Q\n\x0eGetCollections\x12\x1d.chroma.GetCollectionsRequest\x1a\x1e.chroma.GetCollectionsResponse\"\x00\x12M\n\x10UpdateCollection\x12\x1f.chroma.UpdateCollectionRequest\x1a\x16.chroma.ChromaResponse\"\x00\x12>\n\nResetState\x12\x16.google.protobuf.Empty\x1a\x16.chroma.ChromaResponse\"\x00\x42\x43ZAgithub.com/chroma/chroma-coordinator/internal/proto/coordinatorpbb\x06proto3') + +_globals = globals() +_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals) +_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'chromadb.proto.coordinator_pb2', _globals) +if _descriptor._USE_C_DESCRIPTORS == False: + DESCRIPTOR._options = None + DESCRIPTOR._serialized_options = b'ZAgithub.com/chroma/chroma-coordinator/internal/proto/coordinatorpb' + _globals['_CREATEDATABASEREQUEST']._serialized_start=102 + _globals['_CREATEDATABASEREQUEST']._serialized_end=167 + _globals['_GETDATABASEREQUEST']._serialized_start=169 + _globals['_GETDATABASEREQUEST']._serialized_end=219 + _globals['_GETDATABASERESPONSE']._serialized_start=221 + _globals['_GETDATABASERESPONSE']._serialized_end=310 + _globals['_CREATETENANTREQUEST']._serialized_start=312 + _globals['_CREATETENANTREQUEST']._serialized_end=347 + _globals['_GETTENANTREQUEST']._serialized_start=349 + _globals['_GETTENANTREQUEST']._serialized_end=381 + _globals['_GETTENANTRESPONSE']._serialized_start=383 + _globals['_GETTENANTRESPONSE']._serialized_end=466 + _globals['_CREATESEGMENTREQUEST']._serialized_start=468 + _globals['_CREATESEGMENTREQUEST']._serialized_end=524 + _globals['_DELETESEGMENTREQUEST']._serialized_start=526 + _globals['_DELETESEGMENTREQUEST']._serialized_end=560 + _globals['_GETSEGMENTSREQUEST']._serialized_start=563 + _globals['_GETSEGMENTSREQUEST']._serialized_end=757 + _globals['_GETSEGMENTSRESPONSE']._serialized_start=759 + _globals['_GETSEGMENTSRESPONSE']._serialized_end=847 + _globals['_UPDATESEGMENTREQUEST']._serialized_start=850 + _globals['_UPDATESEGMENTREQUEST']._serialized_end=1100 + _globals['_CREATECOLLECTIONREQUEST']._serialized_start=1103 + _globals['_CREATECOLLECTIONREQUEST']._serialized_end=1332 + _globals['_CREATECOLLECTIONRESPONSE']._serialized_start=1334 + _globals['_CREATECOLLECTIONRESPONSE']._serialized_end=1449 + _globals['_DELETECOLLECTIONREQUEST']._serialized_start=1451 + _globals['_DELETECOLLECTIONREQUEST']._serialized_end=1522 + _globals['_GETCOLLECTIONSREQUEST']._serialized_start=1525 + _globals['_GETCOLLECTIONSREQUEST']._serialized_end=1664 + _globals['_GETCOLLECTIONSRESPONSE']._serialized_start=1666 + _globals['_GETCOLLECTIONSRESPONSE']._serialized_end=1763 + _globals['_UPDATECOLLECTIONREQUEST']._serialized_start=1766 + _globals['_UPDATECOLLECTIONREQUEST']._serialized_end=1988 + _globals['_SYSDB']._serialized_start=1991 + _globals['_SYSDB']._serialized_end=2973 +# @@protoc_insertion_point(module_scope) diff --git a/chromadb/proto/coordinator_pb2.pyi b/chromadb/proto/coordinator_pb2.pyi new file mode 100644 index 0000000000000000000000000000000000000000..81545e4e2832775d5aceee1effb63a8bf6502ec8 --- /dev/null +++ b/chromadb/proto/coordinator_pb2.pyi @@ -0,0 +1,182 @@ +from chromadb.proto import chroma_pb2 as _chroma_pb2 +from google.protobuf import empty_pb2 as _empty_pb2 +from google.protobuf.internal import containers as _containers +from google.protobuf import descriptor as _descriptor +from google.protobuf import message as _message +from typing import ClassVar as _ClassVar, Iterable as _Iterable, Mapping as _Mapping, Optional as _Optional, Union as _Union + +DESCRIPTOR: _descriptor.FileDescriptor + +class CreateDatabaseRequest(_message.Message): + __slots__ = ["id", "name", "tenant"] + ID_FIELD_NUMBER: _ClassVar[int] + NAME_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + id: str + name: str + tenant: str + def __init__(self, id: _Optional[str] = ..., name: _Optional[str] = ..., tenant: _Optional[str] = ...) -> None: ... + +class GetDatabaseRequest(_message.Message): + __slots__ = ["name", "tenant"] + NAME_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + name: str + tenant: str + def __init__(self, name: _Optional[str] = ..., tenant: _Optional[str] = ...) -> None: ... + +class GetDatabaseResponse(_message.Message): + __slots__ = ["database", "status"] + DATABASE_FIELD_NUMBER: _ClassVar[int] + STATUS_FIELD_NUMBER: _ClassVar[int] + database: _chroma_pb2.Database + status: _chroma_pb2.Status + def __init__(self, database: _Optional[_Union[_chroma_pb2.Database, _Mapping]] = ..., status: _Optional[_Union[_chroma_pb2.Status, _Mapping]] = ...) -> None: ... + +class CreateTenantRequest(_message.Message): + __slots__ = ["name"] + NAME_FIELD_NUMBER: _ClassVar[int] + name: str + def __init__(self, name: _Optional[str] = ...) -> None: ... + +class GetTenantRequest(_message.Message): + __slots__ = ["name"] + NAME_FIELD_NUMBER: _ClassVar[int] + name: str + def __init__(self, name: _Optional[str] = ...) -> None: ... + +class GetTenantResponse(_message.Message): + __slots__ = ["tenant", "status"] + TENANT_FIELD_NUMBER: _ClassVar[int] + STATUS_FIELD_NUMBER: _ClassVar[int] + tenant: _chroma_pb2.Tenant + status: _chroma_pb2.Status + def __init__(self, tenant: _Optional[_Union[_chroma_pb2.Tenant, _Mapping]] = ..., status: _Optional[_Union[_chroma_pb2.Status, _Mapping]] = ...) -> None: ... + +class CreateSegmentRequest(_message.Message): + __slots__ = ["segment"] + SEGMENT_FIELD_NUMBER: _ClassVar[int] + segment: _chroma_pb2.Segment + def __init__(self, segment: _Optional[_Union[_chroma_pb2.Segment, _Mapping]] = ...) -> None: ... + +class DeleteSegmentRequest(_message.Message): + __slots__ = ["id"] + ID_FIELD_NUMBER: _ClassVar[int] + id: str + def __init__(self, id: _Optional[str] = ...) -> None: ... + +class GetSegmentsRequest(_message.Message): + __slots__ = ["id", "type", "scope", "topic", "collection"] + ID_FIELD_NUMBER: _ClassVar[int] + TYPE_FIELD_NUMBER: _ClassVar[int] + SCOPE_FIELD_NUMBER: _ClassVar[int] + TOPIC_FIELD_NUMBER: _ClassVar[int] + COLLECTION_FIELD_NUMBER: _ClassVar[int] + id: str + type: str + scope: _chroma_pb2.SegmentScope + topic: str + collection: str + def __init__(self, id: _Optional[str] = ..., type: _Optional[str] = ..., scope: _Optional[_Union[_chroma_pb2.SegmentScope, str]] = ..., topic: _Optional[str] = ..., collection: _Optional[str] = ...) -> None: ... + +class GetSegmentsResponse(_message.Message): + __slots__ = ["segments", "status"] + SEGMENTS_FIELD_NUMBER: _ClassVar[int] + STATUS_FIELD_NUMBER: _ClassVar[int] + segments: _containers.RepeatedCompositeFieldContainer[_chroma_pb2.Segment] + status: _chroma_pb2.Status + def __init__(self, segments: _Optional[_Iterable[_Union[_chroma_pb2.Segment, _Mapping]]] = ..., status: _Optional[_Union[_chroma_pb2.Status, _Mapping]] = ...) -> None: ... + +class UpdateSegmentRequest(_message.Message): + __slots__ = ["id", "topic", "reset_topic", "collection", "reset_collection", "metadata", "reset_metadata"] + ID_FIELD_NUMBER: _ClassVar[int] + TOPIC_FIELD_NUMBER: _ClassVar[int] + RESET_TOPIC_FIELD_NUMBER: _ClassVar[int] + COLLECTION_FIELD_NUMBER: _ClassVar[int] + RESET_COLLECTION_FIELD_NUMBER: _ClassVar[int] + METADATA_FIELD_NUMBER: _ClassVar[int] + RESET_METADATA_FIELD_NUMBER: _ClassVar[int] + id: str + topic: str + reset_topic: bool + collection: str + reset_collection: bool + metadata: _chroma_pb2.UpdateMetadata + reset_metadata: bool + def __init__(self, id: _Optional[str] = ..., topic: _Optional[str] = ..., reset_topic: bool = ..., collection: _Optional[str] = ..., reset_collection: bool = ..., metadata: _Optional[_Union[_chroma_pb2.UpdateMetadata, _Mapping]] = ..., reset_metadata: bool = ...) -> None: ... + +class CreateCollectionRequest(_message.Message): + __slots__ = ["id", "name", "metadata", "dimension", "get_or_create", "tenant", "database"] + ID_FIELD_NUMBER: _ClassVar[int] + NAME_FIELD_NUMBER: _ClassVar[int] + METADATA_FIELD_NUMBER: _ClassVar[int] + DIMENSION_FIELD_NUMBER: _ClassVar[int] + GET_OR_CREATE_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + DATABASE_FIELD_NUMBER: _ClassVar[int] + id: str + name: str + metadata: _chroma_pb2.UpdateMetadata + dimension: int + get_or_create: bool + tenant: str + database: str + def __init__(self, id: _Optional[str] = ..., name: _Optional[str] = ..., metadata: _Optional[_Union[_chroma_pb2.UpdateMetadata, _Mapping]] = ..., dimension: _Optional[int] = ..., get_or_create: bool = ..., tenant: _Optional[str] = ..., database: _Optional[str] = ...) -> None: ... + +class CreateCollectionResponse(_message.Message): + __slots__ = ["collection", "created", "status"] + COLLECTION_FIELD_NUMBER: _ClassVar[int] + CREATED_FIELD_NUMBER: _ClassVar[int] + STATUS_FIELD_NUMBER: _ClassVar[int] + collection: _chroma_pb2.Collection + created: bool + status: _chroma_pb2.Status + def __init__(self, collection: _Optional[_Union[_chroma_pb2.Collection, _Mapping]] = ..., created: bool = ..., status: _Optional[_Union[_chroma_pb2.Status, _Mapping]] = ...) -> None: ... + +class DeleteCollectionRequest(_message.Message): + __slots__ = ["id", "tenant", "database"] + ID_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + DATABASE_FIELD_NUMBER: _ClassVar[int] + id: str + tenant: str + database: str + def __init__(self, id: _Optional[str] = ..., tenant: _Optional[str] = ..., database: _Optional[str] = ...) -> None: ... + +class GetCollectionsRequest(_message.Message): + __slots__ = ["id", "name", "topic", "tenant", "database"] + ID_FIELD_NUMBER: _ClassVar[int] + NAME_FIELD_NUMBER: _ClassVar[int] + TOPIC_FIELD_NUMBER: _ClassVar[int] + TENANT_FIELD_NUMBER: _ClassVar[int] + DATABASE_FIELD_NUMBER: _ClassVar[int] + id: str + name: str + topic: str + tenant: str + database: str + def __init__(self, id: _Optional[str] = ..., name: _Optional[str] = ..., topic: _Optional[str] = ..., tenant: _Optional[str] = ..., database: _Optional[str] = ...) -> None: ... + +class GetCollectionsResponse(_message.Message): + __slots__ = ["collections", "status"] + COLLECTIONS_FIELD_NUMBER: _ClassVar[int] + STATUS_FIELD_NUMBER: _ClassVar[int] + collections: _containers.RepeatedCompositeFieldContainer[_chroma_pb2.Collection] + status: _chroma_pb2.Status + def __init__(self, collections: _Optional[_Iterable[_Union[_chroma_pb2.Collection, _Mapping]]] = ..., status: _Optional[_Union[_chroma_pb2.Status, _Mapping]] = ...) -> None: ... + +class UpdateCollectionRequest(_message.Message): + __slots__ = ["id", "topic", "name", "dimension", "metadata", "reset_metadata"] + ID_FIELD_NUMBER: _ClassVar[int] + TOPIC_FIELD_NUMBER: _ClassVar[int] + NAME_FIELD_NUMBER: _ClassVar[int] + DIMENSION_FIELD_NUMBER: _ClassVar[int] + METADATA_FIELD_NUMBER: _ClassVar[int] + RESET_METADATA_FIELD_NUMBER: _ClassVar[int] + id: str + topic: str + name: str + dimension: int + metadata: _chroma_pb2.UpdateMetadata + reset_metadata: bool + def __init__(self, id: _Optional[str] = ..., topic: _Optional[str] = ..., name: _Optional[str] = ..., dimension: _Optional[int] = ..., metadata: _Optional[_Union[_chroma_pb2.UpdateMetadata, _Mapping]] = ..., reset_metadata: bool = ...) -> None: ... diff --git a/chromadb/proto/coordinator_pb2_grpc.py b/chromadb/proto/coordinator_pb2_grpc.py new file mode 100644 index 0000000000000000000000000000000000000000..117c568c71530247f3c07965cd68c72028874ea3 --- /dev/null +++ b/chromadb/proto/coordinator_pb2_grpc.py @@ -0,0 +1,621 @@ +# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! +"""Client and server classes corresponding to protobuf-defined services.""" +import grpc + +from chromadb.proto import chroma_pb2 as chromadb_dot_proto_dot_chroma__pb2 +from chromadb.proto import coordinator_pb2 as chromadb_dot_proto_dot_coordinator__pb2 +from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2 + + +class SysDBStub(object): + """Missing associated documentation comment in .proto file.""" + + def __init__(self, channel): + """Constructor. + + Args: + channel: A grpc.Channel. + """ + self.CreateDatabase = channel.unary_unary( + "/chroma.SysDB/CreateDatabase", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.CreateDatabaseRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.GetDatabase = channel.unary_unary( + "/chroma.SysDB/GetDatabase", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetDatabaseRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetDatabaseResponse.FromString, + ) + self.CreateTenant = channel.unary_unary( + "/chroma.SysDB/CreateTenant", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.CreateTenantRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.GetTenant = channel.unary_unary( + "/chroma.SysDB/GetTenant", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetTenantRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetTenantResponse.FromString, + ) + self.CreateSegment = channel.unary_unary( + "/chroma.SysDB/CreateSegment", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.CreateSegmentRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.DeleteSegment = channel.unary_unary( + "/chroma.SysDB/DeleteSegment", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.DeleteSegmentRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.GetSegments = channel.unary_unary( + "/chroma.SysDB/GetSegments", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetSegmentsRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetSegmentsResponse.FromString, + ) + self.UpdateSegment = channel.unary_unary( + "/chroma.SysDB/UpdateSegment", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.UpdateSegmentRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.CreateCollection = channel.unary_unary( + "/chroma.SysDB/CreateCollection", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.CreateCollectionRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_coordinator__pb2.CreateCollectionResponse.FromString, + ) + self.DeleteCollection = channel.unary_unary( + "/chroma.SysDB/DeleteCollection", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.DeleteCollectionRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.GetCollections = channel.unary_unary( + "/chroma.SysDB/GetCollections", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetCollectionsRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetCollectionsResponse.FromString, + ) + self.UpdateCollection = channel.unary_unary( + "/chroma.SysDB/UpdateCollection", + request_serializer=chromadb_dot_proto_dot_coordinator__pb2.UpdateCollectionRequest.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + self.ResetState = channel.unary_unary( + "/chroma.SysDB/ResetState", + request_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, + response_deserializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + ) + + +class SysDBServicer(object): + """Missing associated documentation comment in .proto file.""" + + def CreateDatabase(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def GetDatabase(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def CreateTenant(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def GetTenant(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def CreateSegment(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def DeleteSegment(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def GetSegments(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def UpdateSegment(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def CreateCollection(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def DeleteCollection(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def GetCollections(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def UpdateCollection(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + def ResetState(self, request, context): + """Missing associated documentation comment in .proto file.""" + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Method not implemented!") + raise NotImplementedError("Method not implemented!") + + +def add_SysDBServicer_to_server(servicer, server): + rpc_method_handlers = { + "CreateDatabase": grpc.unary_unary_rpc_method_handler( + servicer.CreateDatabase, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.CreateDatabaseRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "GetDatabase": grpc.unary_unary_rpc_method_handler( + servicer.GetDatabase, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetDatabaseRequest.FromString, + response_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetDatabaseResponse.SerializeToString, + ), + "CreateTenant": grpc.unary_unary_rpc_method_handler( + servicer.CreateTenant, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.CreateTenantRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "GetTenant": grpc.unary_unary_rpc_method_handler( + servicer.GetTenant, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetTenantRequest.FromString, + response_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetTenantResponse.SerializeToString, + ), + "CreateSegment": grpc.unary_unary_rpc_method_handler( + servicer.CreateSegment, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.CreateSegmentRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "DeleteSegment": grpc.unary_unary_rpc_method_handler( + servicer.DeleteSegment, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.DeleteSegmentRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "GetSegments": grpc.unary_unary_rpc_method_handler( + servicer.GetSegments, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetSegmentsRequest.FromString, + response_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetSegmentsResponse.SerializeToString, + ), + "UpdateSegment": grpc.unary_unary_rpc_method_handler( + servicer.UpdateSegment, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.UpdateSegmentRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "CreateCollection": grpc.unary_unary_rpc_method_handler( + servicer.CreateCollection, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.CreateCollectionRequest.FromString, + response_serializer=chromadb_dot_proto_dot_coordinator__pb2.CreateCollectionResponse.SerializeToString, + ), + "DeleteCollection": grpc.unary_unary_rpc_method_handler( + servicer.DeleteCollection, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.DeleteCollectionRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "GetCollections": grpc.unary_unary_rpc_method_handler( + servicer.GetCollections, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.GetCollectionsRequest.FromString, + response_serializer=chromadb_dot_proto_dot_coordinator__pb2.GetCollectionsResponse.SerializeToString, + ), + "UpdateCollection": grpc.unary_unary_rpc_method_handler( + servicer.UpdateCollection, + request_deserializer=chromadb_dot_proto_dot_coordinator__pb2.UpdateCollectionRequest.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + "ResetState": grpc.unary_unary_rpc_method_handler( + servicer.ResetState, + request_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, + response_serializer=chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.SerializeToString, + ), + } + generic_handler = grpc.method_handlers_generic_handler( + "chroma.SysDB", rpc_method_handlers + ) + server.add_generic_rpc_handlers((generic_handler,)) + + +# This class is part of an EXPERIMENTAL API. +class SysDB(object): + """Missing associated documentation comment in .proto file.""" + + @staticmethod + def CreateDatabase( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/CreateDatabase", + chromadb_dot_proto_dot_coordinator__pb2.CreateDatabaseRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def GetDatabase( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/GetDatabase", + chromadb_dot_proto_dot_coordinator__pb2.GetDatabaseRequest.SerializeToString, + chromadb_dot_proto_dot_coordinator__pb2.GetDatabaseResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def CreateTenant( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/CreateTenant", + chromadb_dot_proto_dot_coordinator__pb2.CreateTenantRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def GetTenant( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/GetTenant", + chromadb_dot_proto_dot_coordinator__pb2.GetTenantRequest.SerializeToString, + chromadb_dot_proto_dot_coordinator__pb2.GetTenantResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def CreateSegment( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/CreateSegment", + chromadb_dot_proto_dot_coordinator__pb2.CreateSegmentRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def DeleteSegment( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/DeleteSegment", + chromadb_dot_proto_dot_coordinator__pb2.DeleteSegmentRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def GetSegments( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/GetSegments", + chromadb_dot_proto_dot_coordinator__pb2.GetSegmentsRequest.SerializeToString, + chromadb_dot_proto_dot_coordinator__pb2.GetSegmentsResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def UpdateSegment( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/UpdateSegment", + chromadb_dot_proto_dot_coordinator__pb2.UpdateSegmentRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def CreateCollection( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/CreateCollection", + chromadb_dot_proto_dot_coordinator__pb2.CreateCollectionRequest.SerializeToString, + chromadb_dot_proto_dot_coordinator__pb2.CreateCollectionResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def DeleteCollection( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/DeleteCollection", + chromadb_dot_proto_dot_coordinator__pb2.DeleteCollectionRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def GetCollections( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/GetCollections", + chromadb_dot_proto_dot_coordinator__pb2.GetCollectionsRequest.SerializeToString, + chromadb_dot_proto_dot_coordinator__pb2.GetCollectionsResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def UpdateCollection( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/UpdateCollection", + chromadb_dot_proto_dot_coordinator__pb2.UpdateCollectionRequest.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) + + @staticmethod + def ResetState( + request, + target, + options=(), + channel_credentials=None, + call_credentials=None, + insecure=False, + compression=None, + wait_for_ready=None, + timeout=None, + metadata=None, + ): + return grpc.experimental.unary_unary( + request, + target, + "/chroma.SysDB/ResetState", + google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, + chromadb_dot_proto_dot_chroma__pb2.ChromaResponse.FromString, + options, + channel_credentials, + insecure, + call_credentials, + compression, + wait_for_ready, + timeout, + metadata, + ) diff --git a/chromadb/py.typed b/chromadb/py.typed new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/segment/__init__.py b/chromadb/segment/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..f9e5afa790344d763932eb3353972df2de6f4ca5 --- /dev/null +++ b/chromadb/segment/__init__.py @@ -0,0 +1,128 @@ +from typing import Optional, Sequence, TypeVar, Type +from abc import abstractmethod +from chromadb.types import ( + Collection, + MetadataEmbeddingRecord, + Operation, + VectorEmbeddingRecord, + Where, + WhereDocument, + VectorQuery, + VectorQueryResult, + Segment, + SeqId, + Metadata, +) +from chromadb.config import Component, System +from uuid import UUID +from enum import Enum + + +class SegmentType(Enum): + SQLITE = "urn:chroma:segment/metadata/sqlite" + HNSW_LOCAL_MEMORY = "urn:chroma:segment/vector/hnsw-local-memory" + HNSW_LOCAL_PERSISTED = "urn:chroma:segment/vector/hnsw-local-persisted" + HNSW_DISTRIBUTED = "urn:chroma:segment/vector/hnsw-distributed" + + +class SegmentImplementation(Component): + @abstractmethod + def __init__(self, sytstem: System, segment: Segment): + pass + + @abstractmethod + def count(self) -> int: + """Get the number of embeddings in this segment""" + pass + + @abstractmethod + def max_seqid(self) -> SeqId: + """Get the maximum SeqID currently indexed by this segment""" + pass + + @staticmethod + def propagate_collection_metadata(metadata: Metadata) -> Optional[Metadata]: + """Given an arbitrary metadata map (e.g, from a collection), validate it and + return metadata (if any) that is applicable and should be applied to the + segment. Validation errors will be reported to the user.""" + return None + + @abstractmethod + def delete(self) -> None: + """Delete the segment and all its data""" + ... + + +S = TypeVar("S", bound=SegmentImplementation) + + +class MetadataReader(SegmentImplementation): + """Embedding Metadata segment interface""" + + @abstractmethod + def get_metadata( + self, + where: Optional[Where] = None, + where_document: Optional[WhereDocument] = None, + ids: Optional[Sequence[str]] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + ) -> Sequence[MetadataEmbeddingRecord]: + """Query for embedding metadata.""" + pass + + +class VectorReader(SegmentImplementation): + """Embedding Vector segment interface""" + + @abstractmethod + def get_vectors( + self, ids: Optional[Sequence[str]] = None + ) -> Sequence[VectorEmbeddingRecord]: + """Get embeddings from the segment. If no IDs are provided, all embeddings are + returned.""" + pass + + @abstractmethod + def query_vectors( + self, query: VectorQuery + ) -> Sequence[Sequence[VectorQueryResult]]: + """Given a vector query, return the top-k nearest neighbors for vector in the + query.""" + pass + + +class SegmentManager(Component): + """Interface for a pluggable strategy for creating, retrieving and instantiating + segments as required""" + + @abstractmethod + def create_segments(self, collection: Collection) -> Sequence[Segment]: + """Return the segments required for a new collection. Returns only segment data, + does not persist to the SysDB""" + pass + + @abstractmethod + def delete_segments(self, collection_id: UUID) -> Sequence[UUID]: + """Delete any local state for all the segments associated with a collection, and + returns a sequence of their IDs. Does not update the SysDB.""" + pass + + # Future Note: To support time travel, add optional parameters to this method to + # retrieve Segment instances that are bounded to events from a specific range of + # time + @abstractmethod + def get_segment(self, collection_id: UUID, type: Type[S]) -> S: + """Return the segment that should be used for servicing queries to a collection. + Implementations should cache appropriately; clients are intended to call this + method repeatedly rather than storing the result (thereby giving this + implementation full control over which segment impls are in or out of memory at + a given time.)""" + pass + + @abstractmethod + def hint_use_collection(self, collection_id: UUID, hint_type: Operation) -> None: + """Signal to the segment manager that a collection is about to be used, so that + it can preload segments as needed. This is only a hint, and implementations are + free to ignore it.""" + pass diff --git a/chromadb/segment/distributed/__init__.py b/chromadb/segment/distributed/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..08efdafd18cfbeebdab0bc0fd0954f2e5c990016 --- /dev/null +++ b/chromadb/segment/distributed/__init__.py @@ -0,0 +1,70 @@ +from abc import abstractmethod +from typing import Any, Callable, List + +from overrides import EnforceOverrides, overrides +from chromadb.config import Component, System +from chromadb.types import Segment + + +class SegmentDirectory(Component): + """A segment directory is a data interface that manages the location of segments. Concretely, this + means that for clustered chroma, it provides the grpc endpoint for a segment.""" + + @abstractmethod + def get_segment_endpoint(self, segment: Segment) -> str: + """Return the segment residence for a given segment ID""" + + @abstractmethod + def register_updated_segment_callback( + self, callback: Callable[[Segment], None] + ) -> None: + """Register a callback that will be called when a segment is updated""" + pass + + +Memberlist = List[str] + + +class MemberlistProvider(Component, EnforceOverrides): + """Returns the latest memberlist and provdes a callback for when it changes. This + callback may be called from a different thread than the one that called. Callers should ensure + that they are thread-safe.""" + + callbacks: List[Callable[[Memberlist], Any]] + + def __init__(self, system: System): + self.callbacks = [] + super().__init__(system) + + @abstractmethod + def get_memberlist(self) -> Memberlist: + """Returns the latest memberlist""" + pass + + @abstractmethod + def set_memberlist_name(self, memberlist: str) -> None: + """Sets the memberlist that this provider will watch""" + pass + + @overrides + def stop(self) -> None: + """Stops watching the memberlist""" + self.callbacks = [] + + def register_updated_memberlist_callback( + self, callback: Callable[[Memberlist], Any] + ) -> None: + """Registers a callback that will be called when the memberlist changes. May be called many times + with the same memberlist, so callers should be idempotent. May be called from a different thread. + """ + self.callbacks.append(callback) + + def unregister_updated_memberlist_callback( + self, callback: Callable[[Memberlist], Any] + ) -> bool: + """Unregisters a callback that was previously registered. Returns True if the callback was + successfully unregistered, False if it was not ever registered.""" + if callback in self.callbacks: + self.callbacks.remove(callback) + return True + return False diff --git a/chromadb/segment/impl/__init__.py b/chromadb/segment/impl/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/segment/impl/distributed/segment_directory.py b/chromadb/segment/impl/distributed/segment_directory.py new file mode 100644 index 0000000000000000000000000000000000000000..70b766de6751b446109000634057f8d4cda1bcb4 --- /dev/null +++ b/chromadb/segment/impl/distributed/segment_directory.py @@ -0,0 +1,231 @@ +from typing import Any, Callable, Dict, Optional, cast +from overrides import EnforceOverrides, override +from chromadb.config import System +from chromadb.segment.distributed import ( + Memberlist, + MemberlistProvider, + SegmentDirectory, +) +from chromadb.types import Segment +from kubernetes import client, config, watch +from kubernetes.client.rest import ApiException +import threading + +from chromadb.utils.rendezvous_hash import assign, murmur3hasher + +# These could go in config but given that they will rarely change, they are here for now to avoid +# polluting the config file further. +WATCH_TIMEOUT_SECONDS = 60 +KUBERNETES_NAMESPACE = "chroma" +KUBERNETES_GROUP = "chroma.cluster" + + +class MockMemberlistProvider(MemberlistProvider, EnforceOverrides): + """A mock memberlist provider for testing""" + + _memberlist: Memberlist + + def __init__(self, system: System): + super().__init__(system) + self._memberlist = ["a", "b", "c"] + + @override + def get_memberlist(self) -> Memberlist: + return self._memberlist + + @override + def set_memberlist_name(self, memberlist: str) -> None: + pass # The mock provider does not need to set the memberlist name + + def update_memberlist(self, memberlist: Memberlist) -> None: + """Updates the memberlist and calls all registered callbacks. This mocks an update from a k8s CR""" + self._memberlist = memberlist + for callback in self.callbacks: + callback(memberlist) + + +class CustomResourceMemberlistProvider(MemberlistProvider, EnforceOverrides): + """A memberlist provider that uses a k8s custom resource to store the memberlist""" + + _kubernetes_api: client.CustomObjectsApi + _memberlist_name: Optional[str] + _curr_memberlist: Optional[Memberlist] + _curr_memberlist_mutex: threading.Lock + _watch_thread: Optional[threading.Thread] + _kill_watch_thread: threading.Event + + def __init__(self, system: System): + super().__init__(system) + config.load_config() + self._kubernetes_api = client.CustomObjectsApi() + self._watch_thread = None + self._memberlist_name = None + self._curr_memberlist = None + self._curr_memberlist_mutex = threading.Lock() + self._kill_watch_thread = threading.Event() + + @override + def start(self) -> None: + if self._memberlist_name is None: + raise ValueError("Memberlist name must be set before starting") + self.get_memberlist() + self._watch_worker_memberlist() + return super().start() + + @override + def stop(self) -> None: + self._curr_memberlist = None + self._memberlist_name = None + + # Stop the watch thread + self._kill_watch_thread.set() + if self._watch_thread is not None: + self._watch_thread.join() + self._watch_thread = None + self._kill_watch_thread.clear() + return super().stop() + + @override + def reset_state(self) -> None: + if not self._system.settings.require("allow_reset"): + raise ValueError( + "Resetting the database is not allowed. Set `allow_reset` to true in the config in tests or other non-production environments where reset should be permitted." + ) + if self._memberlist_name: + self._kubernetes_api.patch_namespaced_custom_object( + group=KUBERNETES_GROUP, + version="v1", + namespace=KUBERNETES_NAMESPACE, + plural="memberlists", + name=self._memberlist_name, + body={ + "kind": "MemberList", + "spec": {"members": []}, + }, + ) + + @override + def get_memberlist(self) -> Memberlist: + if self._curr_memberlist is None: + self._curr_memberlist = self._fetch_memberlist() + return self._curr_memberlist + + @override + def set_memberlist_name(self, memberlist: str) -> None: + self._memberlist_name = memberlist + + def _fetch_memberlist(self) -> Memberlist: + api_response = self._kubernetes_api.get_namespaced_custom_object( + group=KUBERNETES_GROUP, + version="v1", + namespace=KUBERNETES_NAMESPACE, + plural="memberlists", + name=f"{self._memberlist_name}", + ) + api_response = cast(Dict[str, Any], api_response) + if "spec" not in api_response: + return [] + response_spec = cast(Dict[str, Any], api_response["spec"]) + return self._parse_response_memberlist(response_spec) + + def _watch_worker_memberlist(self) -> None: + # TODO: We may want to make this watch function a library function that can be used by other + # components that need to watch k8s custom resources. + def run_watch() -> None: + w = watch.Watch() + + def do_watch() -> None: + for event in w.stream( + self._kubernetes_api.list_namespaced_custom_object, + group=KUBERNETES_GROUP, + version="v1", + namespace=KUBERNETES_NAMESPACE, + plural="memberlists", + field_selector=f"metadata.name={self._memberlist_name}", + timeout_seconds=WATCH_TIMEOUT_SECONDS, + ): + event = cast(Dict[str, Any], event) + response_spec = event["object"]["spec"] + response_spec = cast(Dict[str, Any], response_spec) + with self._curr_memberlist_mutex: + self._curr_memberlist = self._parse_response_memberlist( + response_spec + ) + self._notify(self._curr_memberlist) + + # Watch the custom resource for changes + # Watch with a timeout and retry so we can gracefully stop this if needed + while not self._kill_watch_thread.is_set(): + try: + do_watch() + except ApiException as e: + # If status code is 410, the watch has expired and we need to start a new one. + if e.status == 410: + pass + return + + if self._watch_thread is None: + thread = threading.Thread(target=run_watch, daemon=True) + thread.start() + self._watch_thread = thread + else: + raise Exception("A watch thread is already running.") + + def _parse_response_memberlist( + self, api_response_spec: Dict[str, Any] + ) -> Memberlist: + if "members" not in api_response_spec: + return [] + return [m["url"] for m in api_response_spec["members"]] + + def _notify(self, memberlist: Memberlist) -> None: + for callback in self.callbacks: + callback(memberlist) + + +class RendezvousHashSegmentDirectory(SegmentDirectory, EnforceOverrides): + _memberlist_provider: MemberlistProvider + _curr_memberlist_mutex: threading.Lock + _curr_memberlist: Optional[Memberlist] + + def __init__(self, system: System): + super().__init__(system) + self._memberlist_provider = self.require(MemberlistProvider) + memberlist_name = system.settings.require("worker_memberlist_name") + self._memberlist_provider.set_memberlist_name(memberlist_name) + + self._curr_memberlist = None + self._curr_memberlist_mutex = threading.Lock() + + @override + def start(self) -> None: + self._curr_memberlist = self._memberlist_provider.get_memberlist() + self._memberlist_provider.register_updated_memberlist_callback( + self._update_memberlist + ) + return super().start() + + @override + def stop(self) -> None: + self._memberlist_provider.unregister_updated_memberlist_callback( + self._update_memberlist + ) + return super().stop() + + @override + def get_segment_endpoint(self, segment: Segment) -> str: + if self._curr_memberlist is None or len(self._curr_memberlist) == 0: + raise ValueError("Memberlist is not initialized") + assignment = assign(segment["id"].hex, self._curr_memberlist, murmur3hasher) + assignment = f"{assignment}:50051" # TODO: make port configurable + return assignment + + @override + def register_updated_segment_callback( + self, callback: Callable[[Segment], None] + ) -> None: + raise NotImplementedError() + + def _update_memberlist(self, memberlist: Memberlist) -> None: + with self._curr_memberlist_mutex: + self._curr_memberlist = memberlist diff --git a/chromadb/segment/impl/distributed/server.py b/chromadb/segment/impl/distributed/server.py new file mode 100644 index 0000000000000000000000000000000000000000..d9a6c317f7a5e19adf32bbda2b768eec6e49f2e6 --- /dev/null +++ b/chromadb/segment/impl/distributed/server.py @@ -0,0 +1,187 @@ +from typing import Any, Dict, List, Sequence, Set +from uuid import UUID +from chromadb.config import Settings, System +from chromadb.ingest import CollectionAssignmentPolicy, Consumer +from chromadb.proto.chroma_pb2_grpc import ( + # SegmentServerServicer, + # add_SegmentServerServicer_to_server, + VectorReaderServicer, + add_VectorReaderServicer_to_server, +) +import chromadb.proto.chroma_pb2 as proto +import grpc +from concurrent import futures +from chromadb.proto.convert import ( + to_proto_vector_embedding_record +) +from chromadb.segment import SegmentImplementation, SegmentType +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient +) +from chromadb.types import EmbeddingRecord +from chromadb.segment.distributed import MemberlistProvider, Memberlist +from chromadb.utils.rendezvous_hash import assign, murmur3hasher +from chromadb.ingest.impl.pulsar_admin import PulsarAdmin +import logging +import os + +# This file is a prototype. It will be replaced with a real distributed segment server +# written in a different language. This is just a proof of concept to get the distributed +# segment type working end to end. + +# Run this with python -m chromadb.segment.impl.distributed.server + +SEGMENT_TYPE_IMPLS = { + SegmentType.HNSW_DISTRIBUTED: "chromadb.segment.impl.vector.local_persistent_hnsw.PersistentLocalHnswSegment", +} + + +class SegmentServer(VectorReaderServicer): + _segment_cache: Dict[UUID, SegmentImplementation] = {} + _system: System + _opentelemetry_client: OpenTelemetryClient + _memberlist_provider: MemberlistProvider + _curr_memberlist: Memberlist + _assigned_topics: Set[str] + _topic_to_subscription: Dict[str, UUID] + _consumer: Consumer + + def __init__(self, system: System) -> None: + super().__init__() + self._system = system + + # Init dependency services + self._opentelemetry_client = system.require(OpenTelemetryClient) + # TODO: add term and epoch to segment server + self._memberlist_provider = system.require(MemberlistProvider) + self._memberlist_provider.set_memberlist_name("worker-memberlist") + self._assignment_policy = system.require(CollectionAssignmentPolicy) + self._create_pulsar_topics() + self._consumer = system.require(Consumer) + + # Init data + self._topic_to_subscription = {} + self._assigned_topics = set() + self._curr_memberlist = self._memberlist_provider.get_memberlist() + self._compute_assigned_topics() + + self._memberlist_provider.register_updated_memberlist_callback( + self._on_memberlist_update + ) + + def _compute_assigned_topics(self) -> None: + """Uses rendezvous hashing to compute the topics that this node is responsible for""" + if not self._curr_memberlist: + self._assigned_topics = set() + return + topics = self._assignment_policy.get_topics() + my_ip = os.environ["MY_POD_IP"] + new_assignments: List[str] = [] + for topic in topics: + assigned = assign(topic, self._curr_memberlist, murmur3hasher) + if assigned == my_ip: + new_assignments.append(topic) + new_assignments_set = set(new_assignments) + # TODO: We need to lock around this assignment + net_new_assignments = new_assignments_set - self._assigned_topics + removed_assignments = self._assigned_topics - new_assignments_set + + for topic in removed_assignments: + subscription = self._topic_to_subscription[topic] + self._consumer.unsubscribe(subscription) + del self._topic_to_subscription[topic] + + for topic in net_new_assignments: + subscription = self._consumer.subscribe(topic, self._on_message) + self._topic_to_subscription[topic] = subscription + + self._assigned_topics = new_assignments_set + print( + f"Topic assigment updated and now assigned to {len(self._assigned_topics)} topics" + ) + + def _on_memberlist_update(self, memberlist: Memberlist) -> None: + """Called when the memberlist is updated""" + self._curr_memberlist = memberlist + if len(self._curr_memberlist) > 0: + self._compute_assigned_topics() + else: + # In this case we'd want to warn that there are no members but + # this is not an error, as it could be that the cluster is just starting up + print("Memberlist is empty") + + def _on_message(self, embedding_records: Sequence[EmbeddingRecord]) -> None: + """Called when a message is received from the consumer""" + print(f"Received {len(embedding_records)} records") + print( + f"First record: {embedding_records[0]} is for collection {embedding_records[0]['collection_id']}" + ) + return None + + def _create_pulsar_topics(self) -> None: + """This creates the pulsar topics used by the system. + HACK: THIS IS COMPLETELY A HACK AND WILL BE REPLACED + BY A PROPER TOPIC MANAGEMENT SYSTEM IN THE COORDINATOR""" + topics = self._assignment_policy.get_topics() + admin = PulsarAdmin(self._system) + for topic in topics: + admin.create_topic(topic) + + def QueryVectors( + self, request: proto.QueryVectorsRequest, context: Any + ) -> proto.QueryVectorsResponse: + context.set_code(grpc.StatusCode.UNIMPLEMENTED) + context.set_details("Query segment not implemented yet") + return proto.QueryVectorsResponse() + + # @trace_method( + # "SegmentServer.GetVectors", OpenTelemetryGranularity.OPERATION_AND_SEGMENT + # ) + # def GetVectors( + # self, request: proto.GetVectorsRequest, context: Any + # ) -> proto.GetVectorsResponse: + # segment_id = UUID(hex=request.segment_id) + # if segment_id not in self._segment_cache: + # context.set_code(grpc.StatusCode.NOT_FOUND) + # context.set_details("Segment not found") + # return proto.GetVectorsResponse() + # else: + # segment = self._segment_cache[segment_id] + # segment = cast(VectorReader, segment) + # segment_results = segment.get_vectors(request.ids) + # return_records = [] + # for record in segment_results: + # # TODO: encoding should be based on stored encoding for segment + # # For now we just assume float32 + # return_record = to_proto_vector_embedding_record( + # record, ScalarEncoding.FLOAT32 + # ) + # return_records.append(return_record) + # return proto.GetVectorsResponse(records=return_records) + + # def _cls(self, segment: Segment) -> Type[SegmentImplementation]: + # classname = SEGMENT_TYPE_IMPLS[SegmentType(segment["type"])] + # cls = get_class(classname, SegmentImplementation) + # return cls + + # def _create_instance(self, segment: Segment) -> None: + # if segment["id"] not in self._segment_cache: + # cls = self._cls(segment) + # instance = cls(self._system, segment) + # instance.start() + # self._segment_cache[segment["id"]] = instance + + +if __name__ == "__main__": + logging.basicConfig(level=logging.INFO) + system = System(Settings()) + server = grpc.server(futures.ThreadPoolExecutor(max_workers=10)) + segment_server = SegmentServer(system) + # add_SegmentServerServicer_to_server(segment_server, server) # type: ignore + add_VectorReaderServicer_to_server(segment_server, server) # type: ignore + server.add_insecure_port( + f"[::]:{system.settings.require('chroma_server_grpc_port')}" + ) + system.start() + server.start() + server.wait_for_termination() diff --git a/chromadb/segment/impl/manager/__init__.py b/chromadb/segment/impl/manager/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/segment/impl/manager/cache/__init__.py b/chromadb/segment/impl/manager/cache/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/segment/impl/manager/cache/cache.py b/chromadb/segment/impl/manager/cache/cache.py new file mode 100644 index 0000000000000000000000000000000000000000..80cab0d8e91484fbda5b1e644d2f7ae1a10401a4 --- /dev/null +++ b/chromadb/segment/impl/manager/cache/cache.py @@ -0,0 +1,104 @@ +import uuid +from typing import Any, Callable +from chromadb.types import Segment +from overrides import override +from typing import Dict, Optional +from abc import ABC, abstractmethod + +class SegmentCache(ABC): + @abstractmethod + def get(self, key: uuid.UUID) -> Optional[Segment]: + pass + + @abstractmethod + def pop(self, key: uuid.UUID) -> Optional[Segment]: + pass + + @abstractmethod + def set(self, key: uuid.UUID, value: Segment) -> None: + pass + + @abstractmethod + def reset(self) -> None: + pass + + +class BasicCache(SegmentCache): + def __init__(self): + self.cache:Dict[uuid.UUID, Segment] = {} + + @override + def get(self, key: uuid.UUID) -> Optional[Segment]: + return self.cache.get(key) + + @override + def pop(self, key: uuid.UUID) -> Optional[Segment]: + return self.cache.pop(key, None) + + @override + def set(self, key: uuid.UUID, value: Segment) -> None: + self.cache[key] = value + + @override + def reset(self) -> None: + self.cache = {} + + +class SegmentLRUCache(BasicCache): + """A simple LRU cache implementation that handles objects with dynamic sizes. + The size of each object is determined by a user-provided size function.""" + + def __init__(self, capacity: int, size_func: Callable[[uuid.UUID], int], + callback: Optional[Callable[[uuid.UUID, Segment], Any]] = None): + self.capacity = capacity + self.size_func = size_func + self.cache: Dict[uuid.UUID, Segment] = {} + self.history = [] + self.callback = callback + + def _upsert_key(self, key: uuid.UUID): + if key in self.history: + self.history.remove(key) + self.history.append(key) + else: + self.history.append(key) + + @override + def get(self, key: uuid.UUID) -> Optional[Segment]: + self._upsert_key(key) + if key in self.cache: + return self.cache[key] + else: + return None + + @override + def pop(self, key: uuid.UUID) -> Optional[Segment]: + if key in self.history: + self.history.remove(key) + return self.cache.pop(key, None) + + + @override + def set(self, key: uuid.UUID, value: Segment) -> None: + if key in self.cache: + return + item_size = self.size_func(key) + key_sizes = {key: self.size_func(key) for key in self.cache} + total_size = sum(key_sizes.values()) + index = 0 + # Evict items if capacity is exceeded + while total_size + item_size > self.capacity and len(self.history) > index: + key_delete = self.history[index] + if key_delete in self.cache: + self.callback(key_delete, self.cache[key_delete]) + del self.cache[key_delete] + total_size -= key_sizes[key_delete] + index += 1 + + self.cache[key] = value + self._upsert_key(key) + + @override + def reset(self): + self.cache = {} + self.history = [] diff --git a/chromadb/segment/impl/manager/distributed.py b/chromadb/segment/impl/manager/distributed.py new file mode 100644 index 0000000000000000000000000000000000000000..c114b8a3c967662333fcda13cecd6de59f66d993 --- /dev/null +++ b/chromadb/segment/impl/manager/distributed.py @@ -0,0 +1,178 @@ +from threading import Lock +from chromadb.segment import ( + SegmentImplementation, + SegmentManager, + MetadataReader, + SegmentType, + VectorReader, + S, +) +from chromadb.config import System, get_class +from chromadb.db.system import SysDB +from overrides import override +from chromadb.segment.distributed import SegmentDirectory +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import Collection, Operation, Segment, SegmentScope, Metadata +from typing import Dict, Type, Sequence, Optional, cast +from uuid import UUID, uuid4 +from collections import defaultdict + +# TODO: it is odd that the segment manager is different for distributed vs local +# implementations. This should be refactored to be more consistent and shared. +# needed in this is the ability to specify the desired segment types for a collection +# It is odd that segment manager is coupled to the segment implementation. We need to rethink +# this abstraction. + +SEGMENT_TYPE_IMPLS = { + SegmentType.SQLITE: "chromadb.segment.impl.metadata.sqlite.SqliteMetadataSegment", + SegmentType.HNSW_DISTRIBUTED: "chromadb.segment.impl.vector.grpc_segment.GrpcVectorSegment", +} + + +class DistributedSegmentManager(SegmentManager): + _sysdb: SysDB + _system: System + _opentelemetry_client: OpenTelemetryClient + _instances: Dict[UUID, SegmentImplementation] + _segment_cache: Dict[ + UUID, Dict[SegmentScope, Segment] + ] # collection_id -> scope -> segment + _segment_directory: SegmentDirectory + _lock: Lock + # _segment_server_stubs: Dict[str, SegmentServerStub] # grpc_url -> grpc stub + + def __init__(self, system: System): + super().__init__(system) + self._sysdb = self.require(SysDB) + self._segment_directory = self.require(SegmentDirectory) + self._system = system + self._opentelemetry_client = system.require(OpenTelemetryClient) + self._instances = {} + self._segment_cache = defaultdict(dict) + self._lock = Lock() + + @trace_method( + "DistributedSegmentManager.create_segments", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + @override + def create_segments(self, collection: Collection) -> Sequence[Segment]: + vector_segment = _segment( + SegmentType.HNSW_DISTRIBUTED, SegmentScope.VECTOR, collection + ) + metadata_segment = _segment( + SegmentType.SQLITE, SegmentScope.METADATA, collection + ) + return [vector_segment, metadata_segment] + + @override + def delete_segments(self, collection_id: UUID) -> Sequence[UUID]: + raise NotImplementedError() + + @trace_method( + "DistributedSegmentManager.get_segment", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + @override + def get_segment(self, collection_id: UUID, type: Type[S]) -> S: + if type == MetadataReader: + scope = SegmentScope.METADATA + elif type == VectorReader: + scope = SegmentScope.VECTOR + else: + raise ValueError(f"Invalid segment type: {type}") + + if scope not in self._segment_cache[collection_id]: + segments = self._sysdb.get_segments(collection=collection_id, scope=scope) + known_types = set([k.value for k in SEGMENT_TYPE_IMPLS.keys()]) + # Get the first segment of a known type + segment = next(filter(lambda s: s["type"] in known_types, segments)) + grpc_url = self._segment_directory.get_segment_endpoint(segment) + if segment["metadata"] is not None: + segment["metadata"]["grpc_url"] = grpc_url # type: ignore + else: + segment["metadata"] = {"grpc_url": grpc_url} + # TODO: Register a callback to update the segment when it gets moved + # self._segment_directory.register_updated_segment_callback() + self._segment_cache[collection_id][scope] = segment + + # Instances must be atomically created, so we use a lock to ensure that only one thread + # creates the instance. + with self._lock: + instance = self._instance(self._segment_cache[collection_id][scope]) + return cast(S, instance) + + @trace_method( + "DistributedSegmentManager.hint_use_collection", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + @override + def hint_use_collection(self, collection_id: UUID, hint_type: Operation) -> None: + # TODO: this should call load/release on the target node, node should be stored in metadata + # for now this is fine, but cache invalidation is a problem btwn sysdb and segment manager + types = [MetadataReader, VectorReader] + for type in types: + self.get_segment( + collection_id, type + ) # TODO: this is a hack that mirrors local segment manager to force load the relevant instances + if type == VectorReader: + # Load the remote segment + segments = self._sysdb.get_segments( + collection=collection_id, scope=SegmentScope.VECTOR + ) + known_types = set([k.value for k in SEGMENT_TYPE_IMPLS.keys()]) + segment = next(filter(lambda s: s["type"] in known_types, segments)) + # grpc_url = self._segment_directory.get_segment_endpoint(segment) + + # if grpc_url not in self._segment_server_stubs: + # channel = grpc.insecure_channel(grpc_url) + # self._segment_server_stubs[grpc_url] = SegmentServerStub(channel) # type: ignore + + # TODO: this load is not necessary + # self._segment_server_stubs[grpc_url].LoadSegment( + # to_proto_segment(segment) + # ) + # if grpc_url not in self._segment_server_stubs: + # channel = grpc.insecure_channel(grpc_url) + # self._segment_server_stubs[grpc_url] = SegmentServerStub(channel) + + # self._segment_server_stubs[grpc_url].LoadSegment( + # to_proto_segment(segment) + # ) + + # TODO: rethink duplication from local segment manager + def _cls(self, segment: Segment) -> Type[SegmentImplementation]: + classname = SEGMENT_TYPE_IMPLS[SegmentType(segment["type"])] + cls = get_class(classname, SegmentImplementation) + return cls + + def _instance(self, segment: Segment) -> SegmentImplementation: + if segment["id"] not in self._instances: + cls = self._cls(segment) + instance = cls(self._system, segment) + instance.start() + self._instances[segment["id"]] = instance + return self._instances[segment["id"]] + + +# TODO: rethink duplication from local segment manager +def _segment(type: SegmentType, scope: SegmentScope, collection: Collection) -> Segment: + """Create a metadata dict, propagating metadata correctly for the given segment type.""" + cls = get_class(SEGMENT_TYPE_IMPLS[type], SegmentImplementation) + collection_metadata = collection.get("metadata", None) + metadata: Optional[Metadata] = None + if collection_metadata: + metadata = cls.propagate_collection_metadata(collection_metadata) + + return Segment( + id=uuid4(), + type=type.value, + scope=scope, + topic=collection["topic"], + collection=collection["id"], + metadata=metadata, + ) diff --git a/chromadb/segment/impl/manager/local.py b/chromadb/segment/impl/manager/local.py new file mode 100644 index 0000000000000000000000000000000000000000..c5afef2d01237b0ee678cc107dde033b3edcfd7e --- /dev/null +++ b/chromadb/segment/impl/manager/local.py @@ -0,0 +1,242 @@ +from threading import Lock +from chromadb.segment import ( + SegmentImplementation, + SegmentManager, + MetadataReader, + SegmentType, + VectorReader, + S, +) +import logging +from chromadb.segment.impl.manager.cache.cache import SegmentLRUCache, BasicCache,SegmentCache +import os + +from chromadb.config import System, get_class +from chromadb.db.system import SysDB +from overrides import override +from chromadb.segment.impl.vector.local_persistent_hnsw import ( + PersistentLocalHnswSegment, +) +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import Collection, Operation, Segment, SegmentScope, Metadata +from typing import Dict, Type, Sequence, Optional, cast +from uuid import UUID, uuid4 +import platform + +from chromadb.utils.lru_cache import LRUCache +from chromadb.utils.directory import get_directory_size + + +if platform.system() != "Windows": + import resource +elif platform.system() == "Windows": + import ctypes + +SEGMENT_TYPE_IMPLS = { + SegmentType.SQLITE: "chromadb.segment.impl.metadata.sqlite.SqliteMetadataSegment", + SegmentType.HNSW_LOCAL_MEMORY: "chromadb.segment.impl.vector.local_hnsw.LocalHnswSegment", + SegmentType.HNSW_LOCAL_PERSISTED: "chromadb.segment.impl.vector.local_persistent_hnsw.PersistentLocalHnswSegment", +} + +class LocalSegmentManager(SegmentManager): + _sysdb: SysDB + _system: System + _opentelemetry_client: OpenTelemetryClient + _instances: Dict[UUID, SegmentImplementation] + _vector_instances_file_handle_cache: LRUCache[ + UUID, PersistentLocalHnswSegment + ] # LRU cache to manage file handles across vector segment instances + _vector_segment_type: SegmentType = SegmentType.HNSW_LOCAL_MEMORY + _lock: Lock + _max_file_handles: int + + def __init__(self, system: System): + super().__init__(system) + self._sysdb = self.require(SysDB) + self._system = system + self._opentelemetry_client = system.require(OpenTelemetryClient) + self.logger = logging.getLogger(__name__) + self._instances = {} + self.segment_cache: Dict[SegmentScope, SegmentCache] = {SegmentScope.METADATA: BasicCache()} + if system.settings.chroma_segment_cache_policy == "LRU" and system.settings.chroma_memory_limit_bytes > 0: + self.segment_cache[SegmentScope.VECTOR] = SegmentLRUCache(capacity=system.settings.chroma_memory_limit_bytes,callback=lambda k, v: self.callback_cache_evict(v), size_func=lambda k: self._get_segment_disk_size(k)) + else: + self.segment_cache[SegmentScope.VECTOR] = BasicCache() + + + + + self._lock = Lock() + + # TODO: prototyping with distributed segment for now, but this should be a configurable option + # we need to think about how to handle this configuration + if self._system.settings.require("is_persistent"): + self._vector_segment_type = SegmentType.HNSW_LOCAL_PERSISTED + if platform.system() != "Windows": + self._max_file_handles = resource.getrlimit(resource.RLIMIT_NOFILE)[0] + else: + self._max_file_handles = ctypes.windll.msvcrt._getmaxstdio() # type: ignore + segment_limit = ( + self._max_file_handles + // PersistentLocalHnswSegment.get_file_handle_count() + ) + self._vector_instances_file_handle_cache = LRUCache( + segment_limit, callback=lambda _, v: v.close_persistent_index() + ) + + def callback_cache_evict(self, segment: Segment): + collection_id = segment["collection"] + self.logger.info(f"LRU cache evict collection {collection_id}") + instance = self._instance(segment) + instance.stop() + del self._instances[segment["id"]] + + + @override + def start(self) -> None: + for instance in self._instances.values(): + instance.start() + super().start() + + @override + def stop(self) -> None: + for instance in self._instances.values(): + instance.stop() + super().stop() + + @override + def reset_state(self) -> None: + for instance in self._instances.values(): + instance.stop() + instance.reset_state() + self._instances = {} + self.segment_cache[SegmentScope.VECTOR].reset() + super().reset_state() + + @trace_method( + "LocalSegmentManager.create_segments", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + @override + def create_segments(self, collection: Collection) -> Sequence[Segment]: + vector_segment = _segment( + self._vector_segment_type, SegmentScope.VECTOR, collection + ) + metadata_segment = _segment( + SegmentType.SQLITE, SegmentScope.METADATA, collection + ) + return [vector_segment, metadata_segment] + + @trace_method( + "LocalSegmentManager.delete_segments", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + @override + def delete_segments(self, collection_id: UUID) -> Sequence[UUID]: + segments = self._sysdb.get_segments(collection=collection_id) + for segment in segments: + if segment["id"] in self._instances: + if segment["type"] == SegmentType.HNSW_LOCAL_PERSISTED.value: + instance = self.get_segment(collection_id, VectorReader) + instance.delete() + elif segment["type"] == SegmentType.SQLITE.value: + instance = self.get_segment(collection_id, MetadataReader) + instance.delete() + del self._instances[segment["id"]] + if segment["scope"] is SegmentScope.VECTOR: + self.segment_cache[SegmentScope.VECTOR].pop(collection_id) + if segment["scope"] is SegmentScope.METADATA: + self.segment_cache[SegmentScope.METADATA].pop(collection_id) + return [s["id"] for s in segments] + + @trace_method( + "LocalSegmentManager.get_segment", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + def _get_segment_disk_size(self, collection_id: UUID) -> int: + segments = self._sysdb.get_segments(collection=collection_id, scope=SegmentScope.VECTOR) + if len(segments) == 0: + return 0 + # With local segment manager (single server chroma), a collection always have one segment. + size = get_directory_size( + os.path.join(self._system.settings.require("persist_directory"), str(segments[0]["id"]))) + return size + + def _get_segment_sysdb(self, collection_id:UUID, scope: SegmentScope): + segments = self._sysdb.get_segments(collection=collection_id, scope=scope) + known_types = set([k.value for k in SEGMENT_TYPE_IMPLS.keys()]) + # Get the first segment of a known type + segment = next(filter(lambda s: s["type"] in known_types, segments)) + return segment + @override + def get_segment(self, collection_id: UUID, type: Type[S]) -> S: + if type == MetadataReader: + scope = SegmentScope.METADATA + elif type == VectorReader: + scope = SegmentScope.VECTOR + else: + raise ValueError(f"Invalid segment type: {type}") + + segment = self.segment_cache[scope].get(collection_id) + if segment is None: + segment = self._get_segment_sysdb(collection_id, scope) + self.segment_cache[scope].set(collection_id, segment) + + # Instances must be atomically created, so we use a lock to ensure that only one thread + # creates the instance. + with self._lock: + instance = self._instance(segment) + return cast(S, instance) + + @trace_method( + "LocalSegmentManager.hint_use_collection", + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + ) + @override + def hint_use_collection(self, collection_id: UUID, hint_type: Operation) -> None: + # The local segment manager responds to hints by pre-loading both the metadata and vector + # segments for the given collection. + for type in [MetadataReader, VectorReader]: + # Just use get_segment to load the segment into the cache + instance = self.get_segment(collection_id, type) + # If the segment is a vector segment, we need to keep segments in an LRU cache + # to avoid hitting the OS file handle limit. + if type == VectorReader and self._system.settings.require("is_persistent"): + instance = cast(PersistentLocalHnswSegment, instance) + instance.open_persistent_index() + self._vector_instances_file_handle_cache.set(collection_id, instance) + + def _cls(self, segment: Segment) -> Type[SegmentImplementation]: + classname = SEGMENT_TYPE_IMPLS[SegmentType(segment["type"])] + cls = get_class(classname, SegmentImplementation) + return cls + + def _instance(self, segment: Segment) -> SegmentImplementation: + if segment["id"] not in self._instances: + cls = self._cls(segment) + instance = cls(self._system, segment) + instance.start() + self._instances[segment["id"]] = instance + return self._instances[segment["id"]] + + +def _segment(type: SegmentType, scope: SegmentScope, collection: Collection) -> Segment: + """Create a metadata dict, propagating metadata correctly for the given segment type.""" + cls = get_class(SEGMENT_TYPE_IMPLS[type], SegmentImplementation) + collection_metadata = collection.get("metadata", None) + metadata: Optional[Metadata] = None + if collection_metadata: + metadata = cls.propagate_collection_metadata(collection_metadata) + + return Segment( + id=uuid4(), + type=type.value, + scope=scope, + topic=collection["topic"], + collection=collection["id"], + metadata=metadata + ) diff --git a/chromadb/segment/impl/metadata/sqlite.py b/chromadb/segment/impl/metadata/sqlite.py new file mode 100644 index 0000000000000000000000000000000000000000..2e5af88b0d050868940ffdf117f784c0aa89436a --- /dev/null +++ b/chromadb/segment/impl/metadata/sqlite.py @@ -0,0 +1,739 @@ +from typing import Optional, Sequence, Any, Tuple, cast, Generator, Union, Dict, List +from chromadb.segment import MetadataReader +from chromadb.ingest import Consumer +from chromadb.config import System +from chromadb.types import Segment, InclusionExclusionOperator +from chromadb.db.impl.sqlite import SqliteDB +from overrides import override +from chromadb.db.base import ( + Cursor, + ParameterValue, + get_sql, +) +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import ( + Where, + WhereDocument, + MetadataEmbeddingRecord, + EmbeddingRecord, + SeqId, + Operation, + UpdateMetadata, + LiteralValue, + WhereOperator, +) +from uuid import UUID +from pypika import Table, Tables +from pypika.queries import QueryBuilder +import pypika.functions as fn +from pypika.terms import Criterion +from itertools import groupby +from functools import reduce +import sqlite3 + +import logging + +logger = logging.getLogger(__name__) + + +class SqliteMetadataSegment(MetadataReader): + _consumer: Consumer + _db: SqliteDB + _id: UUID + _opentelemetry_client: OpenTelemetryClient + _topic: Optional[str] + _subscription: Optional[UUID] + + def __init__(self, system: System, segment: Segment): + self._db = system.instance(SqliteDB) + self._consumer = system.instance(Consumer) + self._id = segment["id"] + self._opentelemetry_client = system.require(OpenTelemetryClient) + self._topic = segment["topic"] + + @trace_method("SqliteMetadataSegment.start", OpenTelemetryGranularity.ALL) + @override + def start(self) -> None: + if self._topic: + seq_id = self.max_seqid() + self._subscription = self._consumer.subscribe( + self._topic, self._write_metadata, start=seq_id + ) + + @trace_method("SqliteMetadataSegment.stop", OpenTelemetryGranularity.ALL) + @override + def stop(self) -> None: + if self._subscription: + self._consumer.unsubscribe(self._subscription) + + @trace_method("SqliteMetadataSegment.max_seqid", OpenTelemetryGranularity.ALL) + @override + def max_seqid(self) -> SeqId: + t = Table("max_seq_id") + q = ( + self._db.querybuilder() + .from_(t) + .select(t.seq_id) + .where(t.segment_id == ParameterValue(self._db.uuid_to_db(self._id))) + ) + sql, params = get_sql(q) + with self._db.tx() as cur: + result = cur.execute(sql, params).fetchone() + + if result is None: + return self._consumer.min_seqid() + else: + return _decode_seq_id(result[0]) + + @trace_method("SqliteMetadataSegment.count", OpenTelemetryGranularity.ALL) + @override + def count(self) -> int: + embeddings_t = Table("embeddings") + q = ( + self._db.querybuilder() + .from_(embeddings_t) + .where( + embeddings_t.segment_id == ParameterValue(self._db.uuid_to_db(self._id)) + ) + .select(fn.Count(embeddings_t.id)) + ) + sql, params = get_sql(q) + with self._db.tx() as cur: + result = cur.execute(sql, params).fetchone()[0] + return cast(int, result) + + @trace_method("SqliteMetadataSegment.get_metadata", OpenTelemetryGranularity.ALL) + @override + def get_metadata( + self, + where: Optional[Where] = None, + where_document: Optional[WhereDocument] = None, + ids: Optional[Sequence[str]] = None, + limit: Optional[int] = None, + offset: Optional[int] = None, + ) -> Sequence[MetadataEmbeddingRecord]: + """Query for embedding metadata.""" + embeddings_t, metadata_t, fulltext_t = Tables( + "embeddings", "embedding_metadata", "embedding_fulltext_search" + ) + + limit = limit or 2**63 - 1 + offset = offset or 0 + + if limit < 0: + raise ValueError("Limit cannot be negative") + + q = ( + ( + self._db.querybuilder() + .from_(embeddings_t) + .left_join(metadata_t) + .on(embeddings_t.id == metadata_t.id) + ) + .select( + embeddings_t.id, + embeddings_t.embedding_id, + embeddings_t.seq_id, + metadata_t.key, + metadata_t.string_value, + metadata_t.int_value, + metadata_t.float_value, + metadata_t.bool_value, + ) + .orderby(embeddings_t.embedding_id) + ) + + # If there is a query that touches the metadata table, it uses + # where and where_document filters, we treat this case seperately + if where is not None or where_document is not None: + metadata_q = ( + self._db.querybuilder() + .from_(metadata_t) + .select(metadata_t.id) + .join(embeddings_t) + .on(embeddings_t.id == metadata_t.id) + .orderby(embeddings_t.embedding_id) + .where( + embeddings_t.segment_id + == ParameterValue(self._db.uuid_to_db(self._id)) + ) + .distinct() # These are embedding ids + ) + + if where: + metadata_q = metadata_q.where( + self._where_map_criterion( + metadata_q, where, metadata_t, embeddings_t + ) + ) + if where_document: + metadata_q = metadata_q.where( + self._where_doc_criterion( + metadata_q, where_document, metadata_t, fulltext_t, embeddings_t + ) + ) + if ids is not None: + metadata_q = metadata_q.where( + embeddings_t.embedding_id.isin(ParameterValue(ids)) + ) + + metadata_q = metadata_q.limit(limit) + metadata_q = metadata_q.offset(offset) + + q = q.where(embeddings_t.id.isin(metadata_q)) + else: + # In the case where we don't use the metadata table + # We have to apply limit/offset to embeddings and then join + # with metadata + embeddings_q = ( + self._db.querybuilder() + .from_(embeddings_t) + .select(embeddings_t.id) + .where( + embeddings_t.segment_id + == ParameterValue(self._db.uuid_to_db(self._id)) + ) + .orderby(embeddings_t.embedding_id) + .limit(limit) + .offset(offset) + ) + + if ids is not None: + embeddings_q = embeddings_q.where( + embeddings_t.embedding_id.isin(ParameterValue(ids)) + ) + + q = q.where(embeddings_t.id.isin(embeddings_q)) + + with self._db.tx() as cur: + # Execute the query with the limit and offset already applied + return list(self._records(cur, q)) + + def _records( + self, cur: Cursor, q: QueryBuilder + ) -> Generator[MetadataEmbeddingRecord, None, None]: + """Given a cursor and a QueryBuilder, yield a generator of records. Assumes + cursor returns rows in ID order.""" + + sql, params = get_sql(q) + cur.execute(sql, params) + + cur_iterator = iter(cur.fetchone, None) + group_iterator = groupby(cur_iterator, lambda r: int(r[0])) + + for _, group in group_iterator: + yield self._record(list(group)) + + @trace_method("SqliteMetadataSegment._record", OpenTelemetryGranularity.ALL) + def _record(self, rows: Sequence[Tuple[Any, ...]]) -> MetadataEmbeddingRecord: + """Given a list of DB rows with the same ID, construct a + MetadataEmbeddingRecord""" + _, embedding_id, seq_id = rows[0][:3] + metadata = {} + for row in rows: + key, string_value, int_value, float_value, bool_value = row[3:] + if string_value is not None: + metadata[key] = string_value + elif int_value is not None: + metadata[key] = int_value + elif float_value is not None: + metadata[key] = float_value + elif bool_value is not None: + if bool_value == 1: + metadata[key] = True + else: + metadata[key] = False + + return MetadataEmbeddingRecord( + id=embedding_id, + seq_id=_decode_seq_id(seq_id), + metadata=metadata or None, + ) + + @trace_method("SqliteMetadataSegment._insert_record", OpenTelemetryGranularity.ALL) + def _insert_record( + self, cur: Cursor, record: EmbeddingRecord, upsert: bool + ) -> None: + """Add or update a single EmbeddingRecord into the DB""" + + t = Table("embeddings") + q = ( + self._db.querybuilder() + .into(t) + .columns(t.segment_id, t.embedding_id, t.seq_id) + .where(t.segment_id == ParameterValue(self._db.uuid_to_db(self._id))) + .where(t.embedding_id == ParameterValue(record["id"])) + ).insert( + ParameterValue(self._db.uuid_to_db(self._id)), + ParameterValue(record["id"]), + ParameterValue(_encode_seq_id(record["seq_id"])), + ) + sql, params = get_sql(q) + sql = sql + "RETURNING id" + try: + id = cur.execute(sql, params).fetchone()[0] + except sqlite3.IntegrityError: + # Can't use INSERT OR REPLACE here because it changes the primary key. + if upsert: + return self._update_record(cur, record) + else: + logger.warning(f"Insert of existing embedding ID: {record['id']}") + # We are trying to add for a record that already exists. Fail the call. + # We don't throw an exception since this is in principal an async path + return + + if record["metadata"]: + self._update_metadata(cur, id, record["metadata"]) + + @trace_method( + "SqliteMetadataSegment._update_metadata", OpenTelemetryGranularity.ALL + ) + def _update_metadata(self, cur: Cursor, id: int, metadata: UpdateMetadata) -> None: + """Update the metadata for a single EmbeddingRecord""" + t = Table("embedding_metadata") + to_delete = [k for k, v in metadata.items() if v is None] + if to_delete: + q = ( + self._db.querybuilder() + .from_(t) + .where(t.id == ParameterValue(id)) + .where(t.key.isin(ParameterValue(to_delete))) + .delete() + ) + sql, params = get_sql(q) + cur.execute(sql, params) + + self._insert_metadata(cur, id, metadata) + + @trace_method( + "SqliteMetadataSegment._insert_metadata", OpenTelemetryGranularity.ALL + ) + def _insert_metadata(self, cur: Cursor, id: int, metadata: UpdateMetadata) -> None: + """Insert or update each metadata row for a single embedding record""" + t = Table("embedding_metadata") + q = ( + self._db.querybuilder() + .into(t) + .columns( + t.id, + t.key, + t.string_value, + t.int_value, + t.float_value, + t.bool_value, + ) + ) + for key, value in metadata.items(): + if isinstance(value, str): + q = q.insert( + ParameterValue(id), + ParameterValue(key), + ParameterValue(value), + None, + None, + None, + ) + # isinstance(True, int) evaluates to True, so we need to check for bools separately + elif isinstance(value, bool): + q = q.insert( + ParameterValue(id), + ParameterValue(key), + None, + None, + None, + ParameterValue(value), + ) + elif isinstance(value, int): + q = q.insert( + ParameterValue(id), + ParameterValue(key), + None, + ParameterValue(value), + None, + None, + ) + elif isinstance(value, float): + q = q.insert( + ParameterValue(id), + ParameterValue(key), + None, + None, + ParameterValue(value), + None, + ) + + sql, params = get_sql(q) + sql = sql.replace("INSERT", "INSERT OR REPLACE") + if sql: + cur.execute(sql, params) + + if "chroma:document" in metadata: + t = Table("embedding_fulltext_search") + + def insert_into_fulltext_search() -> None: + q = ( + self._db.querybuilder() + .into(t) + .columns(t.rowid, t.string_value) + .insert( + ParameterValue(id), + ParameterValue(metadata["chroma:document"]), + ) + ) + sql, params = get_sql(q) + cur.execute(sql, params) + + try: + insert_into_fulltext_search() + except sqlite3.IntegrityError: + q = ( + self._db.querybuilder() + .from_(t) + .where(t.rowid == ParameterValue(id)) + .delete() + ) + sql, params = get_sql(q) + cur.execute(sql, params) + insert_into_fulltext_search() + + @trace_method("SqliteMetadataSegment._delete_record", OpenTelemetryGranularity.ALL) + def _delete_record(self, cur: Cursor, record: EmbeddingRecord) -> None: + """Delete a single EmbeddingRecord from the DB""" + t = Table("embeddings") + q = ( + self._db.querybuilder() + .from_(t) + .where(t.segment_id == ParameterValue(self._db.uuid_to_db(self._id))) + .where(t.embedding_id == ParameterValue(record["id"])) + .delete() + ) + sql, params = get_sql(q) + sql = sql + " RETURNING id" + result = cur.execute(sql, params).fetchone() + if result is None: + logger.warning(f"Delete of nonexisting embedding ID: {record['id']}") + else: + id = result[0] + + # Manually delete metadata; cannot use cascade because + # that triggers on replace + metadata_t = Table("embedding_metadata") + q = ( + self._db.querybuilder() + .from_(metadata_t) + .where(metadata_t.id == ParameterValue(id)) + .delete() + ) + sql, params = get_sql(q) + cur.execute(sql, params) + + @trace_method("SqliteMetadataSegment._update_record", OpenTelemetryGranularity.ALL) + def _update_record(self, cur: Cursor, record: EmbeddingRecord) -> None: + """Update a single EmbeddingRecord in the DB""" + t = Table("embeddings") + q = ( + self._db.querybuilder() + .update(t) + .set(t.seq_id, ParameterValue(_encode_seq_id(record["seq_id"]))) + .where(t.segment_id == ParameterValue(self._db.uuid_to_db(self._id))) + .where(t.embedding_id == ParameterValue(record["id"])) + ) + sql, params = get_sql(q) + sql = sql + " RETURNING id" + result = cur.execute(sql, params).fetchone() + if result is None: + logger.warning(f"Update of nonexisting embedding ID: {record['id']}") + else: + id = result[0] + if record["metadata"]: + self._update_metadata(cur, id, record["metadata"]) + + @trace_method("SqliteMetadataSegment._write_metadata", OpenTelemetryGranularity.ALL) + def _write_metadata(self, records: Sequence[EmbeddingRecord]) -> None: + """Write embedding metadata to the database. Care should be taken to ensure + records are append-only (that is, that seq-ids should increase monotonically)""" + with self._db.tx() as cur: + for record in records: + q = ( + self._db.querybuilder() + .into(Table("max_seq_id")) + .columns("segment_id", "seq_id") + .insert( + ParameterValue(self._db.uuid_to_db(self._id)), + ParameterValue(_encode_seq_id(record["seq_id"])), + ) + ) + sql, params = get_sql(q) + sql = sql.replace("INSERT", "INSERT OR REPLACE") + cur.execute(sql, params) + + if record["operation"] == Operation.ADD: + self._insert_record(cur, record, False) + elif record["operation"] == Operation.UPSERT: + self._insert_record(cur, record, True) + elif record["operation"] == Operation.DELETE: + self._delete_record(cur, record) + elif record["operation"] == Operation.UPDATE: + self._update_record(cur, record) + + @trace_method( + "SqliteMetadataSegment._where_map_criterion", OpenTelemetryGranularity.ALL + ) + def _where_map_criterion( + self, q: QueryBuilder, where: Where, metadata_t: Table, embeddings_t: Table + ) -> Criterion: + clause: List[Criterion] = [] + for k, v in where.items(): + if k == "$and": + criteria = [ + self._where_map_criterion(q, w, metadata_t, embeddings_t) + for w in cast(Sequence[Where], v) + ] + clause.append(reduce(lambda x, y: x & y, criteria)) + elif k == "$or": + criteria = [ + self._where_map_criterion(q, w, metadata_t, embeddings_t) + for w in cast(Sequence[Where], v) + ] + clause.append(reduce(lambda x, y: x | y, criteria)) + else: + expr = cast(Union[LiteralValue, Dict[WhereOperator, LiteralValue]], v) + sq = ( + self._db.querybuilder() + .from_(metadata_t) + .select(metadata_t.id) + .where(metadata_t.key == ParameterValue(k)) + .where(_where_clause(expr, metadata_t)) + ) + clause.append(metadata_t.id.isin(sq)) + return reduce(lambda x, y: x & y, clause) + + @trace_method( + "SqliteMetadataSegment._where_doc_criterion", OpenTelemetryGranularity.ALL + ) + def _where_doc_criterion( + self, + q: QueryBuilder, + where: WhereDocument, + metadata_t: Table, + fulltext_t: Table, + embeddings_t: Table, + ) -> Criterion: + for k, v in where.items(): + if k == "$and": + criteria = [ + self._where_doc_criterion( + q, w, metadata_t, fulltext_t, embeddings_t + ) + for w in cast(Sequence[WhereDocument], v) + ] + return reduce(lambda x, y: x & y, criteria) + elif k == "$or": + criteria = [ + self._where_doc_criterion( + q, w, metadata_t, fulltext_t, embeddings_t + ) + for w in cast(Sequence[WhereDocument], v) + ] + return reduce(lambda x, y: x | y, criteria) + elif k == "$contains": + v = cast(str, v) + search_term = f"%{v}%" + + sq = ( + self._db.querybuilder() + .from_(fulltext_t) + .select(fulltext_t.rowid) + .where(fulltext_t.string_value.like(ParameterValue(search_term))) + ) + return metadata_t.id.isin(sq) + elif k == "$not_contains": + v = cast(str, v) + search_term = f"%{v}%" + + sq = ( + self._db.querybuilder() + .from_(fulltext_t) + .select(fulltext_t.rowid) + .where( + fulltext_t.string_value.not_like(ParameterValue(search_term)) + ) + ) + return embeddings_t.id.isin(sq) + else: + raise ValueError(f"Unknown where_doc operator {k}") + raise ValueError("Empty where_doc") + + @trace_method("SqliteMetadataSegment.delete", OpenTelemetryGranularity.ALL) + @override + def delete(self) -> None: + t = Table("embeddings") + t1 = Table("embedding_metadata") + t2 = Table("embedding_fulltext_search") + q0 = ( + self._db.querybuilder() + .from_(t1) + .delete() + .where( + t1.id.isin( + self._db.querybuilder() + .from_(t) + .select(t.id) + .where( + t.segment_id == ParameterValue(self._db.uuid_to_db(self._id)) + ) + ) + ) + ) + q = ( + self._db.querybuilder() + .from_(t) + .delete() + .where( + t.id.isin( + self._db.querybuilder() + .from_(t) + .select(t.id) + .where( + t.segment_id == ParameterValue(self._db.uuid_to_db(self._id)) + ) + ) + ) + ) + q_fts = ( + self._db.querybuilder() + .from_(t2) + .delete() + .where( + t2.rowid.isin( + self._db.querybuilder() + .from_(t) + .select(t.id) + .where( + t.segment_id == ParameterValue(self._db.uuid_to_db(self._id)) + ) + ) + ) + ) + with self._db.tx() as cur: + cur.execute(*get_sql(q_fts)) + cur.execute(*get_sql(q0)) + cur.execute(*get_sql(q)) + + +def _encode_seq_id(seq_id: SeqId) -> bytes: + """Encode a SeqID into a byte array""" + if seq_id.bit_length() <= 64: + return int.to_bytes(seq_id, 8, "big") + elif seq_id.bit_length() <= 192: + return int.to_bytes(seq_id, 24, "big") + else: + raise ValueError(f"Unsupported SeqID: {seq_id}") + + +def _decode_seq_id(seq_id_bytes: bytes) -> SeqId: + """Decode a byte array into a SeqID""" + if len(seq_id_bytes) == 8: + return int.from_bytes(seq_id_bytes, "big") + elif len(seq_id_bytes) == 24: + return int.from_bytes(seq_id_bytes, "big") + else: + raise ValueError(f"Unknown SeqID type with length {len(seq_id_bytes)}") + + +def _where_clause( + expr: Union[ + LiteralValue, + Dict[WhereOperator, LiteralValue], + Dict[InclusionExclusionOperator, List[LiteralValue]], + ], + table: Table, +) -> Criterion: + """Given a field name, an expression, and a table, construct a Pypika Criterion""" + + # Literal value case + if isinstance(expr, (str, int, float, bool)): + return _where_clause({cast(WhereOperator, "$eq"): expr}, table) + + # Operator dict case + operator, value = next(iter(expr.items())) + return _value_criterion(value, operator, table) + + +def _value_criterion( + value: Union[LiteralValue, List[LiteralValue]], + op: Union[WhereOperator, InclusionExclusionOperator], + table: Table, +) -> Criterion: + """Return a criterion to compare a value with the appropriate columns given its type + and the operation type.""" + if isinstance(value, str): + cols = [table.string_value] + # isinstance(True, int) evaluates to True, so we need to check for bools separately + elif isinstance(value, bool) and op in ("$eq", "$ne"): + cols = [table.bool_value] + elif isinstance(value, int) and op in ("$eq", "$ne"): + cols = [table.int_value] + elif isinstance(value, float) and op in ("$eq", "$ne"): + cols = [table.float_value] + elif isinstance(value, list) and op in ("$in", "$nin"): + _v = value + if len(_v) == 0: + raise ValueError(f"Empty list for {op} operator") + if isinstance(value[0], str): + col_exprs = [ + table.string_value.isin(ParameterValue(_v)) + if op == "$in" + else table.string_value.notin(ParameterValue(_v)) + ] + elif isinstance(value[0], bool): + col_exprs = [ + table.bool_value.isin(ParameterValue(_v)) + if op == "$in" + else table.bool_value.notin(ParameterValue(_v)) + ] + elif isinstance(value[0], int): + col_exprs = [ + table.int_value.isin(ParameterValue(_v)) + if op == "$in" + else table.int_value.notin(ParameterValue(_v)) + ] + elif isinstance(value[0], float): + col_exprs = [ + table.float_value.isin(ParameterValue(_v)) + if op == "$in" + else table.float_value.notin(ParameterValue(_v)) + ] + elif isinstance(value, list) and op in ("$in", "$nin"): + col_exprs = [ + table.int_value.isin(ParameterValue(value)) + if op == "$in" + else table.int_value.notin(ParameterValue(value)), + table.float_value.isin(ParameterValue(value)) + if op == "$in" + else table.float_value.notin(ParameterValue(value)), + ] + else: + cols = [table.int_value, table.float_value] + + if op == "$eq": + col_exprs = [col == ParameterValue(value) for col in cols] + elif op == "$ne": + col_exprs = [col != ParameterValue(value) for col in cols] + elif op == "$gt": + col_exprs = [col > ParameterValue(value) for col in cols] + elif op == "$gte": + col_exprs = [col >= ParameterValue(value) for col in cols] + elif op == "$lt": + col_exprs = [col < ParameterValue(value) for col in cols] + elif op == "$lte": + col_exprs = [col <= ParameterValue(value) for col in cols] + + if op == "$ne": + return reduce(lambda x, y: x & y, col_exprs) + else: + return reduce(lambda x, y: x | y, col_exprs) diff --git a/chromadb/segment/impl/vector/batch.py b/chromadb/segment/impl/vector/batch.py new file mode 100644 index 0000000000000000000000000000000000000000..aac533b918fc59c82887816a0171919553f88b96 --- /dev/null +++ b/chromadb/segment/impl/vector/batch.py @@ -0,0 +1,106 @@ +from typing import Dict, List, Set, cast + +from chromadb.types import EmbeddingRecord, Operation, SeqId, Vector + + +class Batch: + """Used to model the set of changes as an atomic operation""" + + _ids_to_records: Dict[str, EmbeddingRecord] + _deleted_ids: Set[str] + _written_ids: Set[str] + _upsert_add_ids: Set[str] # IDs that are being added in an upsert + add_count: int + update_count: int + max_seq_id: SeqId + + def __init__(self) -> None: + self._ids_to_records = {} + self._deleted_ids = set() + self._written_ids = set() + self._upsert_add_ids = set() + self.add_count = 0 + self.update_count = 0 + self.max_seq_id = 0 + + def __len__(self) -> int: + """Get the number of changes in this batch""" + return len(self._written_ids) + len(self._deleted_ids) + + def get_deleted_ids(self) -> List[str]: + """Get the list of deleted embeddings in this batch""" + return list(self._deleted_ids) + + def get_written_ids(self) -> List[str]: + """Get the list of written embeddings in this batch""" + return list(self._written_ids) + + def get_written_vectors(self, ids: List[str]) -> List[Vector]: + """Get the list of vectors to write in this batch""" + return [cast(Vector, self._ids_to_records[id]["embedding"]) for id in ids] + + def get_record(self, id: str) -> EmbeddingRecord: + """Get the record for a given ID""" + return self._ids_to_records[id] + + def is_deleted(self, id: str) -> bool: + """Check if a given ID is deleted""" + return id in self._deleted_ids + + @property + def delete_count(self) -> int: + return len(self._deleted_ids) + + def apply(self, record: EmbeddingRecord, exists_already: bool = False) -> None: + """Apply an embedding record to this batch. Records passed to this method are assumed to be validated for correctness. + For example, a delete or update presumes the ID exists in the index. An add presumes the ID does not exist in the index. + The exists_already flag should be set to True if the ID does exist in the index, and False otherwise. + """ + + id = record["id"] + if record["operation"] == Operation.DELETE: + # If the ID was previously written, remove it from the written set + # And update the add/update/delete counts + if id in self._written_ids: + self._written_ids.remove(id) + if self._ids_to_records[id]["operation"] == Operation.ADD: + self.add_count -= 1 + elif self._ids_to_records[id]["operation"] == Operation.UPDATE: + self.update_count -= 1 + self._deleted_ids.add(id) + elif self._ids_to_records[id]["operation"] == Operation.UPSERT: + if id in self._upsert_add_ids: + self.add_count -= 1 + self._upsert_add_ids.remove(id) + else: + self.update_count -= 1 + self._deleted_ids.add(id) + elif id not in self._deleted_ids: + self._deleted_ids.add(id) + + # Remove the record from the batch + if id in self._ids_to_records: + del self._ids_to_records[id] + + else: + self._ids_to_records[id] = record + self._written_ids.add(id) + + # If the ID was previously deleted, remove it from the deleted set + # And update the delete count + if id in self._deleted_ids: + self._deleted_ids.remove(id) + + # Update the add/update counts + if record["operation"] == Operation.UPSERT: + if not exists_already: + self.add_count += 1 + self._upsert_add_ids.add(id) + else: + self.update_count += 1 + elif record["operation"] == Operation.ADD: + self.add_count += 1 + elif record["operation"] == Operation.UPDATE: + self.update_count += 1 + + self.max_seq_id = max(self.max_seq_id, record["seq_id"]) diff --git a/chromadb/segment/impl/vector/brute_force_index.py b/chromadb/segment/impl/vector/brute_force_index.py new file mode 100644 index 0000000000000000000000000000000000000000..f9466e3f3d4348b18e7475bdb9eb8be8bc9b091b --- /dev/null +++ b/chromadb/segment/impl/vector/brute_force_index.py @@ -0,0 +1,153 @@ +from typing import Any, Callable, Dict, List, Optional, Sequence, Set +import numpy as np +import numpy.typing as npt +from chromadb.types import ( + EmbeddingRecord, + VectorEmbeddingRecord, + VectorQuery, + VectorQueryResult, +) + +from chromadb.utils import distance_functions +import logging + +logger = logging.getLogger(__name__) + + +class BruteForceIndex: + """A lightweight, numpy based brute force index that is used for batches that have not been indexed into hnsw yet. It is not + thread safe and callers should ensure that only one thread is accessing it at a time. + """ + + id_to_index: Dict[str, int] + index_to_id: Dict[int, str] + id_to_seq_id: Dict[str, int] + deleted_ids: Set[str] + free_indices: List[int] + size: int + dimensionality: int + distance_fn: Callable[[npt.NDArray[Any], npt.NDArray[Any]], float] + vectors: npt.NDArray[Any] + + def __init__(self, size: int, dimensionality: int, space: str = "l2"): + if space == "l2": + self.distance_fn = distance_functions.l2 + elif space == "ip": + self.distance_fn = distance_functions.ip + elif space == "cosine": + self.distance_fn = distance_functions.cosine + else: + raise Exception(f"Unknown distance function: {space}") + + self.id_to_index = {} + self.index_to_id = {} + self.id_to_seq_id = {} + self.deleted_ids = set() + self.free_indices = list(range(size)) + self.size = size + self.dimensionality = dimensionality + self.vectors = np.zeros((size, dimensionality)) + + def __len__(self) -> int: + return len(self.id_to_index) + + def clear(self) -> None: + self.id_to_index = {} + self.index_to_id = {} + self.id_to_seq_id = {} + self.deleted_ids.clear() + self.free_indices = list(range(self.size)) + self.vectors.fill(0) + + def upsert(self, records: List[EmbeddingRecord]) -> None: + if len(records) + len(self) > self.size: + raise Exception( + "Index with capacity {} and {} current entries cannot add {} records".format( + self.size, len(self), len(records) + ) + ) + + for i, record in enumerate(records): + id = record["id"] + vector = record["embedding"] + self.id_to_seq_id[id] = record["seq_id"] + if id in self.deleted_ids: + self.deleted_ids.remove(id) + + # TODO: It may be faster to use multi-index selection on the vectors array + if id in self.id_to_index: + # Update + index = self.id_to_index[id] + self.vectors[index] = vector + else: + # Add + next_index = self.free_indices.pop() + self.id_to_index[id] = next_index + self.index_to_id[next_index] = id + self.vectors[next_index] = vector + + def delete(self, records: List[EmbeddingRecord]) -> None: + for record in records: + id = record["id"] + if id in self.id_to_index: + index = self.id_to_index[id] + self.deleted_ids.add(id) + del self.id_to_index[id] + del self.index_to_id[index] + del self.id_to_seq_id[id] + self.vectors[index].fill(np.NaN) + self.free_indices.append(index) + else: + logger.warning(f"Delete of nonexisting embedding ID: {id}") + + def has_id(self, id: str) -> bool: + """Returns whether the index contains the given ID""" + return id in self.id_to_index and id not in self.deleted_ids + + def get_vectors( + self, ids: Optional[Sequence[str]] = None + ) -> Sequence[VectorEmbeddingRecord]: + target_ids = ids or self.id_to_index.keys() + + return [ + VectorEmbeddingRecord( + id=id, + embedding=self.vectors[self.id_to_index[id]].tolist(), + seq_id=self.id_to_seq_id[id], + ) + for id in target_ids + ] + + def query(self, query: VectorQuery) -> Sequence[Sequence[VectorQueryResult]]: + np_query = np.array(query["vectors"]) + allowed_ids = ( + None if query["allowed_ids"] is None else set(query["allowed_ids"]) + ) + distances = np.apply_along_axis( + lambda query: np.apply_along_axis(self.distance_fn, 1, self.vectors, query), + 1, + np_query, + ) + + indices = np.argsort(distances).tolist() + # Filter out deleted labels + filtered_results = [] + for i, index_list in enumerate(indices): + curr_results = [] + for j in index_list: + # If the index is in the index_to_id map, then it has been added + if j in self.index_to_id: + id = self.index_to_id[j] + if id not in self.deleted_ids and ( + allowed_ids is None or id in allowed_ids + ): + curr_results.append( + VectorQueryResult( + id=id, + distance=distances[i][j].item(), + seq_id=self.id_to_seq_id[id], + embedding=self.vectors[j].tolist(), + ) + ) + filtered_results.append(curr_results) + return filtered_results diff --git a/chromadb/segment/impl/vector/grpc_segment.py b/chromadb/segment/impl/vector/grpc_segment.py new file mode 100644 index 0000000000000000000000000000000000000000..7a2062bd239599ffb123a0e66913ca6ed18bc158 --- /dev/null +++ b/chromadb/segment/impl/vector/grpc_segment.py @@ -0,0 +1,104 @@ +from overrides import EnforceOverrides, override +from typing import List, Optional, Sequence +from chromadb.config import System +from chromadb.proto.convert import ( + from_proto_vector_embedding_record, + from_proto_vector_query_result, + to_proto_vector, +) +from chromadb.segment import VectorReader +from chromadb.segment.impl.vector.hnsw_params import PersistentHnswParams +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import ( + Metadata, + ScalarEncoding, + Segment, + VectorEmbeddingRecord, + VectorQuery, + VectorQueryResult, +) +from chromadb.proto.chroma_pb2_grpc import VectorReaderStub +from chromadb.proto.chroma_pb2 import ( + GetVectorsRequest, + GetVectorsResponse, + QueryVectorsRequest, + QueryVectorsResponse, +) +import grpc + + +class GrpcVectorSegment(VectorReader, EnforceOverrides): + _vector_reader_stub: VectorReaderStub + _segment: Segment + _opentelemetry_client: OpenTelemetryClient + + def __init__(self, system: System, segment: Segment): + # TODO: move to start() method + # TODO: close channel in stop() method + if segment["metadata"] is None or segment["metadata"]["grpc_url"] is None: + raise Exception("Missing grpc_url in segment metadata") + + channel = grpc.insecure_channel(segment["metadata"]["grpc_url"]) + self._vector_reader_stub = VectorReaderStub(channel) # type: ignore + self._segment = segment + self._opentelemetry_client = system.require(OpenTelemetryClient) + + @trace_method("GrpcVectorSegment.get_vectors", OpenTelemetryGranularity.ALL) + @override + def get_vectors( + self, ids: Optional[Sequence[str]] = None + ) -> Sequence[VectorEmbeddingRecord]: + request = GetVectorsRequest(ids=ids, segment_id=self._segment["id"].hex) + response: GetVectorsResponse = self._vector_reader_stub.GetVectors(request) + results: List[VectorEmbeddingRecord] = [] + for vector in response.records: + result = from_proto_vector_embedding_record(vector) + results.append(result) + return results + + @trace_method("GrpcVectorSegment.query_vectors", OpenTelemetryGranularity.ALL) + @override + def query_vectors( + self, query: VectorQuery + ) -> Sequence[Sequence[VectorQueryResult]]: + request = QueryVectorsRequest( + vectors=[ + to_proto_vector(vector=v, encoding=ScalarEncoding.FLOAT32) + for v in query["vectors"] + ], + k=query["k"], + allowed_ids=query["allowed_ids"], + include_embeddings=query["include_embeddings"], + segment_id=self._segment["id"].hex, + ) + response: QueryVectorsResponse = self._vector_reader_stub.QueryVectors(request) + results: List[List[VectorQueryResult]] = [] + for result in response.results: + curr_result: List[VectorQueryResult] = [] + for r in result.results: + curr_result.append(from_proto_vector_query_result(r)) + results.append(curr_result) + return results + + @override + def count(self) -> int: + raise NotImplementedError() + + @override + def max_seqid(self) -> int: + return 0 + + @staticmethod + @override + def propagate_collection_metadata(metadata: Metadata) -> Optional[Metadata]: + # Great example of why language sharing is nice. + segment_metadata = PersistentHnswParams.extract(metadata) + return segment_metadata + + @override + def delete(self) -> None: + raise NotImplementedError() diff --git a/chromadb/segment/impl/vector/hnsw_params.py b/chromadb/segment/impl/vector/hnsw_params.py new file mode 100644 index 0000000000000000000000000000000000000000..b12c428150806f9fd47f0322b8a4859084a5954a --- /dev/null +++ b/chromadb/segment/impl/vector/hnsw_params.py @@ -0,0 +1,88 @@ +import multiprocessing +import re +from typing import Any, Callable, Dict, Union + +from chromadb.types import Metadata + + +Validator = Callable[[Union[str, int, float]], bool] + +param_validators: Dict[str, Validator] = { + "hnsw:space": lambda p: bool(re.match(r"^(l2|cosine|ip)$", str(p))), + "hnsw:construction_ef": lambda p: isinstance(p, int), + "hnsw:search_ef": lambda p: isinstance(p, int), + "hnsw:M": lambda p: isinstance(p, int), + "hnsw:num_threads": lambda p: isinstance(p, int), + "hnsw:resize_factor": lambda p: isinstance(p, (int, float)), +} + +# Extra params used for persistent hnsw +persistent_param_validators: Dict[str, Validator] = { + "hnsw:batch_size": lambda p: isinstance(p, int) and p > 2, + "hnsw:sync_threshold": lambda p: isinstance(p, int) and p > 2, +} + + +class Params: + @staticmethod + def _select(metadata: Metadata) -> Dict[str, Any]: + segment_metadata = {} + for param, value in metadata.items(): + if param.startswith("hnsw:"): + segment_metadata[param] = value + return segment_metadata + + @staticmethod + def _validate(metadata: Dict[str, Any], validators: Dict[str, Validator]) -> None: + """Validates the metadata""" + # Validate it + for param, value in metadata.items(): + if param not in validators: + raise ValueError(f"Unknown HNSW parameter: {param}") + if not validators[param](value): + raise ValueError(f"Invalid value for HNSW parameter: {param} = {value}") + + +class HnswParams(Params): + space: str + construction_ef: int + search_ef: int + M: int + num_threads: int + resize_factor: float + + def __init__(self, metadata: Metadata): + metadata = metadata or {} + self.space = str(metadata.get("hnsw:space", "l2")) + self.construction_ef = int(metadata.get("hnsw:construction_ef", 100)) + self.search_ef = int(metadata.get("hnsw:search_ef", 10)) + self.M = int(metadata.get("hnsw:M", 16)) + self.num_threads = int( + metadata.get("hnsw:num_threads", multiprocessing.cpu_count()) + ) + self.resize_factor = float(metadata.get("hnsw:resize_factor", 1.2)) + + @staticmethod + def extract(metadata: Metadata) -> Metadata: + """Validate and return only the relevant hnsw params""" + segment_metadata = HnswParams._select(metadata) + HnswParams._validate(segment_metadata, param_validators) + return segment_metadata + + +class PersistentHnswParams(HnswParams): + batch_size: int + sync_threshold: int + + def __init__(self, metadata: Metadata): + super().__init__(metadata) + self.batch_size = int(metadata.get("hnsw:batch_size", 100)) + self.sync_threshold = int(metadata.get("hnsw:sync_threshold", 1000)) + + @staticmethod + def extract(metadata: Metadata) -> Metadata: + """Returns only the relevant hnsw params""" + all_validators = {**param_validators, **persistent_param_validators} + segment_metadata = PersistentHnswParams._select(metadata) + PersistentHnswParams._validate(segment_metadata, all_validators) + return segment_metadata diff --git a/chromadb/segment/impl/vector/local_hnsw.py b/chromadb/segment/impl/vector/local_hnsw.py new file mode 100644 index 0000000000000000000000000000000000000000..e4437881b2a99370ba19dc7ac5d6c5f14572b980 --- /dev/null +++ b/chromadb/segment/impl/vector/local_hnsw.py @@ -0,0 +1,327 @@ +from overrides import override +from typing import Optional, Sequence, Dict, Set, List, cast +from uuid import UUID +from chromadb.segment import VectorReader +from chromadb.ingest import Consumer +from chromadb.config import System, Settings +from chromadb.segment.impl.vector.batch import Batch +from chromadb.segment.impl.vector.hnsw_params import HnswParams +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import ( + EmbeddingRecord, + VectorEmbeddingRecord, + VectorQuery, + VectorQueryResult, + SeqId, + Segment, + Metadata, + Operation, + Vector, +) +from chromadb.errors import InvalidDimensionException +import hnswlib +from chromadb.utils.read_write_lock import ReadWriteLock, ReadRWLock, WriteRWLock +import logging + +logger = logging.getLogger(__name__) + +DEFAULT_CAPACITY = 1000 + + +class LocalHnswSegment(VectorReader): + _id: UUID + _consumer: Consumer + _topic: Optional[str] + _subscription: UUID + _settings: Settings + _params: HnswParams + + _index: Optional[hnswlib.Index] + _dimensionality: Optional[int] + _total_elements_added: int + _max_seq_id: SeqId + + _lock: ReadWriteLock + + _id_to_label: Dict[str, int] + _label_to_id: Dict[int, str] + _id_to_seq_id: Dict[str, SeqId] + + _opentelemtry_client: OpenTelemetryClient + + def __init__(self, system: System, segment: Segment): + self._consumer = system.instance(Consumer) + self._id = segment["id"] + self._topic = segment["topic"] + self._settings = system.settings + self._params = HnswParams(segment["metadata"] or {}) + + self._index = None + self._dimensionality = None + self._total_elements_added = 0 + self._max_seq_id = self._consumer.min_seqid() + + self._id_to_seq_id = {} + self._id_to_label = {} + self._label_to_id = {} + + self._lock = ReadWriteLock() + self._opentelemtry_client = system.require(OpenTelemetryClient) + super().__init__(system, segment) + + @staticmethod + @override + def propagate_collection_metadata(metadata: Metadata) -> Optional[Metadata]: + # Extract relevant metadata + segment_metadata = HnswParams.extract(metadata) + return segment_metadata + + @trace_method("LocalHnswSegment.start", OpenTelemetryGranularity.ALL) + @override + def start(self) -> None: + super().start() + if self._topic: + seq_id = self.max_seqid() + self._subscription = self._consumer.subscribe( + self._topic, self._write_records, start=seq_id + ) + + @trace_method("LocalHnswSegment.stop", OpenTelemetryGranularity.ALL) + @override + def stop(self) -> None: + super().stop() + if self._subscription: + self._consumer.unsubscribe(self._subscription) + + @trace_method("LocalHnswSegment.get_vectors", OpenTelemetryGranularity.ALL) + @override + def get_vectors( + self, ids: Optional[Sequence[str]] = None + ) -> Sequence[VectorEmbeddingRecord]: + if ids is None: + labels = list(self._label_to_id.keys()) + else: + labels = [] + for id in ids: + if id in self._id_to_label: + labels.append(self._id_to_label[id]) + + results = [] + if self._index is not None: + vectors = cast(Sequence[Vector], self._index.get_items(labels)) + + for label, vector in zip(labels, vectors): + id = self._label_to_id[label] + seq_id = self._id_to_seq_id[id] + results.append( + VectorEmbeddingRecord(id=id, seq_id=seq_id, embedding=vector) + ) + + return results + + @trace_method("LocalHnswSegment.query_vectors", OpenTelemetryGranularity.ALL) + @override + def query_vectors( + self, query: VectorQuery + ) -> Sequence[Sequence[VectorQueryResult]]: + if self._index is None: + return [[] for _ in range(len(query["vectors"]))] + + k = query["k"] + size = len(self._id_to_label) + + if k > size: + logger.warning( + f"Number of requested results {k} is greater than number of elements in index {size}, updating n_results = {size}" + ) + k = size + + labels: Set[int] = set() + ids = query["allowed_ids"] + if ids is not None: + labels = {self._id_to_label[id] for id in ids if id in self._id_to_label} + if len(labels) < k: + k = len(labels) + + def filter_function(label: int) -> bool: + return label in labels + + query_vectors = query["vectors"] + + with ReadRWLock(self._lock): + result_labels, distances = self._index.knn_query( + query_vectors, k=k, filter=filter_function if ids else None + ) + + # TODO: these casts are not correct, hnswlib returns np + # distances = cast(List[List[float]], distances) + # result_labels = cast(List[List[int]], result_labels) + + all_results: List[List[VectorQueryResult]] = [] + for result_i in range(len(result_labels)): + results: List[VectorQueryResult] = [] + for label, distance in zip( + result_labels[result_i], distances[result_i] + ): + id = self._label_to_id[label] + seq_id = self._id_to_seq_id[id] + if query["include_embeddings"]: + embedding = self._index.get_items([label])[0] + else: + embedding = None + results.append( + VectorQueryResult( + id=id, + seq_id=seq_id, + distance=distance.item(), + embedding=embedding, + ) + ) + all_results.append(results) + + return all_results + + @override + def max_seqid(self) -> SeqId: + return self._max_seq_id + + @override + def count(self) -> int: + return len(self._id_to_label) + + @trace_method("LocalHnswSegment._init_index", OpenTelemetryGranularity.ALL) + def _init_index(self, dimensionality: int) -> None: + # more comments available at the source: https://github.com/nmslib/hnswlib + + index = hnswlib.Index( + space=self._params.space, dim=dimensionality + ) # possible options are l2, cosine or ip + index.init_index( + max_elements=DEFAULT_CAPACITY, + ef_construction=self._params.construction_ef, + M=self._params.M, + ) + index.set_ef(self._params.search_ef) + index.set_num_threads(self._params.num_threads) + + self._index = index + self._dimensionality = dimensionality + + @trace_method("LocalHnswSegment._ensure_index", OpenTelemetryGranularity.ALL) + def _ensure_index(self, n: int, dim: int) -> None: + """Create or resize the index as necessary to accomodate N new records""" + if not self._index: + self._dimensionality = dim + self._init_index(dim) + else: + if dim != self._dimensionality: + raise InvalidDimensionException( + f"Dimensionality of ({dim}) does not match index" + + f"dimensionality ({self._dimensionality})" + ) + + index = cast(hnswlib.Index, self._index) + + if (self._total_elements_added + n) > index.get_max_elements(): + new_size = int( + (self._total_elements_added + n) * self._params.resize_factor + ) + index.resize_index(max(new_size, DEFAULT_CAPACITY)) + + @trace_method("LocalHnswSegment._apply_batch", OpenTelemetryGranularity.ALL) + def _apply_batch(self, batch: Batch) -> None: + """Apply a batch of changes, as atomically as possible.""" + deleted_ids = batch.get_deleted_ids() + written_ids = batch.get_written_ids() + vectors_to_write = batch.get_written_vectors(written_ids) + labels_to_write = [0] * len(vectors_to_write) + + if len(deleted_ids) > 0: + index = cast(hnswlib.Index, self._index) + for i in range(len(deleted_ids)): + id = deleted_ids[i] + # Never added this id to hnsw, so we can safely ignore it for deletions + if id not in self._id_to_label: + continue + label = self._id_to_label[id] + + index.mark_deleted(label) + del self._id_to_label[id] + del self._label_to_id[label] + del self._id_to_seq_id[id] + + if len(written_ids) > 0: + self._ensure_index(batch.add_count, len(vectors_to_write[0])) + + next_label = self._total_elements_added + 1 + for i in range(len(written_ids)): + if written_ids[i] not in self._id_to_label: + labels_to_write[i] = next_label + next_label += 1 + else: + labels_to_write[i] = self._id_to_label[written_ids[i]] + + index = cast(hnswlib.Index, self._index) + + # First, update the index + index.add_items(vectors_to_write, labels_to_write) + + # If that succeeds, update the mappings + for i, id in enumerate(written_ids): + self._id_to_seq_id[id] = batch.get_record(id)["seq_id"] + self._id_to_label[id] = labels_to_write[i] + self._label_to_id[labels_to_write[i]] = id + + # If that succeeds, update the total count + self._total_elements_added += batch.add_count + + # If that succeeds, finally the seq ID + self._max_seq_id = batch.max_seq_id + + @trace_method("LocalHnswSegment._write_records", OpenTelemetryGranularity.ALL) + def _write_records(self, records: Sequence[EmbeddingRecord]) -> None: + """Add a batch of embeddings to the index""" + if not self._running: + raise RuntimeError("Cannot add embeddings to stopped component") + + # Avoid all sorts of potential problems by ensuring single-threaded access + with WriteRWLock(self._lock): + batch = Batch() + + for record in records: + self._max_seq_id = max(self._max_seq_id, record["seq_id"]) + id = record["id"] + op = record["operation"] + label = self._id_to_label.get(id, None) + + if op == Operation.DELETE: + if label: + batch.apply(record) + else: + logger.warning(f"Delete of nonexisting embedding ID: {id}") + + elif op == Operation.UPDATE: + if record["embedding"] is not None: + if label is not None: + batch.apply(record) + else: + logger.warning( + f"Update of nonexisting embedding ID: {record['id']}" + ) + elif op == Operation.ADD: + if not label: + batch.apply(record, False) + else: + logger.warning(f"Add of existing embedding ID: {id}") + elif op == Operation.UPSERT: + batch.apply(record, label is not None) + + self._apply_batch(batch) + + @override + def delete(self) -> None: + raise NotImplementedError() diff --git a/chromadb/segment/impl/vector/local_persistent_hnsw.py b/chromadb/segment/impl/vector/local_persistent_hnsw.py new file mode 100644 index 0000000000000000000000000000000000000000..4ab60a1725d44aee320839fe993dd46d3a4ddef9 --- /dev/null +++ b/chromadb/segment/impl/vector/local_persistent_hnsw.py @@ -0,0 +1,458 @@ +import os +import shutil +from overrides import override +import pickle +from typing import Dict, List, Optional, Sequence, Set, cast +from chromadb.config import System +from chromadb.segment.impl.vector.batch import Batch +from chromadb.segment.impl.vector.hnsw_params import PersistentHnswParams +from chromadb.segment.impl.vector.local_hnsw import ( + DEFAULT_CAPACITY, + LocalHnswSegment, +) +from chromadb.segment.impl.vector.brute_force_index import BruteForceIndex +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) +from chromadb.types import ( + EmbeddingRecord, + Metadata, + Operation, + Segment, + SeqId, + Vector, + VectorEmbeddingRecord, + VectorQuery, + VectorQueryResult, +) +import hnswlib +import logging + +from chromadb.utils.read_write_lock import ReadRWLock, WriteRWLock + + +logger = logging.getLogger(__name__) + + +class PersistentData: + """Stores the data and metadata needed for a PersistentLocalHnswSegment""" + + dimensionality: Optional[int] + total_elements_added: int + max_seq_id: SeqId + + id_to_label: Dict[str, int] + label_to_id: Dict[int, str] + id_to_seq_id: Dict[str, SeqId] + + def __init__( + self, + dimensionality: Optional[int], + total_elements_added: int, + max_seq_id: int, + id_to_label: Dict[str, int], + label_to_id: Dict[int, str], + id_to_seq_id: Dict[str, SeqId], + ): + self.dimensionality = dimensionality + self.total_elements_added = total_elements_added + self.max_seq_id = max_seq_id + self.id_to_label = id_to_label + self.label_to_id = label_to_id + self.id_to_seq_id = id_to_seq_id + + @staticmethod + def load_from_file(filename: str) -> "PersistentData": + """Load persistent data from a file""" + with open(filename, "rb") as f: + ret = cast(PersistentData, pickle.load(f)) + return ret + + +class PersistentLocalHnswSegment(LocalHnswSegment): + METADATA_FILE: str = "index_metadata.pickle" + # How many records to add to index at once, we do this because crossing the python/c++ boundary is expensive (for add()) + # When records are not added to the c++ index, they are buffered in memory and served + # via brute force search. + _batch_size: int + _brute_force_index: Optional[BruteForceIndex] + _index_initialized: bool = False + _curr_batch: Batch + # How many records to add to index before syncing to disk + _sync_threshold: int + _persist_data: PersistentData + _persist_directory: str + _allow_reset: bool + + _opentelemtry_client: OpenTelemetryClient + + def __init__(self, system: System, segment: Segment): + super().__init__(system, segment) + + self._opentelemtry_client = system.require(OpenTelemetryClient) + + self._params = PersistentHnswParams(segment["metadata"] or {}) + self._batch_size = self._params.batch_size + self._sync_threshold = self._params.sync_threshold + self._allow_reset = system.settings.allow_reset + self._persist_directory = system.settings.require("persist_directory") + self._curr_batch = Batch() + self._brute_force_index = None + if not os.path.exists(self._get_storage_folder()): + os.makedirs(self._get_storage_folder(), exist_ok=True) + # Load persist data if it exists already, otherwise create it + if self._index_exists(): + self._persist_data = PersistentData.load_from_file( + self._get_metadata_file() + ) + self._dimensionality = self._persist_data.dimensionality + self._total_elements_added = self._persist_data.total_elements_added + self._max_seq_id = self._persist_data.max_seq_id + self._id_to_label = self._persist_data.id_to_label + self._label_to_id = self._persist_data.label_to_id + self._id_to_seq_id = self._persist_data.id_to_seq_id + # If the index was written to, we need to re-initialize it + if len(self._id_to_label) > 0: + self._dimensionality = cast(int, self._dimensionality) + self._init_index(self._dimensionality) + else: + self._persist_data = PersistentData( + self._dimensionality, + self._total_elements_added, + self._max_seq_id, + self._id_to_label, + self._label_to_id, + self._id_to_seq_id, + ) + + @staticmethod + @override + def propagate_collection_metadata(metadata: Metadata) -> Optional[Metadata]: + # Extract relevant metadata + segment_metadata = PersistentHnswParams.extract(metadata) + return segment_metadata + + def _index_exists(self) -> bool: + """Check if the index exists via the metadata file""" + return os.path.exists(self._get_metadata_file()) + + def _get_metadata_file(self) -> str: + """Get the metadata file path""" + return os.path.join(self._get_storage_folder(), self.METADATA_FILE) + + def _get_storage_folder(self) -> str: + """Get the storage folder path""" + folder = os.path.join(self._persist_directory, str(self._id)) + return folder + + @trace_method( + "PersistentLocalHnswSegment._init_index", OpenTelemetryGranularity.ALL + ) + @override + def _init_index(self, dimensionality: int) -> None: + index = hnswlib.Index(space=self._params.space, dim=dimensionality) + self._brute_force_index = BruteForceIndex( + size=self._batch_size, + dimensionality=dimensionality, + space=self._params.space, + ) + + # Check if index exists and load it if it does + if self._index_exists(): + index.load_index( + self._get_storage_folder(), + is_persistent_index=True, + max_elements=int( + max(self.count() * self._params.resize_factor, DEFAULT_CAPACITY) + ), + ) + else: + index.init_index( + max_elements=DEFAULT_CAPACITY, + ef_construction=self._params.construction_ef, + M=self._params.M, + is_persistent_index=True, + persistence_location=self._get_storage_folder(), + ) + + index.set_ef(self._params.search_ef) + index.set_num_threads(self._params.num_threads) + + self._index = index + self._dimensionality = dimensionality + self._index_initialized = True + + @trace_method("PersistentLocalHnswSegment._persist", OpenTelemetryGranularity.ALL) + def _persist(self) -> None: + """Persist the index and data to disk""" + index = cast(hnswlib.Index, self._index) + + # Persist the index + index.persist_dirty() + + # Persist the metadata + self._persist_data.dimensionality = self._dimensionality + self._persist_data.total_elements_added = self._total_elements_added + self._persist_data.max_seq_id = self._max_seq_id + + # TODO: This should really be stored in sqlite, the index itself, or a better + # storage format + self._persist_data.id_to_label = self._id_to_label + self._persist_data.label_to_id = self._label_to_id + self._persist_data.id_to_seq_id = self._id_to_seq_id + + with open(self._get_metadata_file(), "wb") as metadata_file: + pickle.dump(self._persist_data, metadata_file, pickle.HIGHEST_PROTOCOL) + + @trace_method( + "PersistentLocalHnswSegment._apply_batch", OpenTelemetryGranularity.ALL + ) + @override + def _apply_batch(self, batch: Batch) -> None: + super()._apply_batch(batch) + if ( + self._total_elements_added - self._persist_data.total_elements_added + >= self._sync_threshold + ): + self._persist() + + @trace_method( + "PersistentLocalHnswSegment._write_records", OpenTelemetryGranularity.ALL + ) + @override + def _write_records(self, records: Sequence[EmbeddingRecord]) -> None: + """Add a batch of embeddings to the index""" + if not self._running: + raise RuntimeError("Cannot add embeddings to stopped component") + with WriteRWLock(self._lock): + for record in records: + if record["embedding"] is not None: + self._ensure_index(len(records), len(record["embedding"])) + if not self._index_initialized: + # If the index is not initialized here, it means that we have + # not yet added any records to the index. So we can just + # ignore the record since it was a delete. + continue + self._brute_force_index = cast(BruteForceIndex, self._brute_force_index) + + self._max_seq_id = max(self._max_seq_id, record["seq_id"]) + id = record["id"] + op = record["operation"] + exists_in_index = self._id_to_label.get( + id, None + ) is not None or self._brute_force_index.has_id(id) + exists_in_bf_index = self._brute_force_index.has_id(id) + + if op == Operation.DELETE: + if exists_in_index: + self._curr_batch.apply(record) + if exists_in_bf_index: + self._brute_force_index.delete([record]) + else: + logger.warning(f"Delete of nonexisting embedding ID: {id}") + + elif op == Operation.UPDATE: + if record["embedding"] is not None: + if exists_in_index: + self._curr_batch.apply(record) + self._brute_force_index.upsert([record]) + else: + logger.warning( + f"Update of nonexisting embedding ID: {record['id']}" + ) + elif op == Operation.ADD: + if record["embedding"] is not None: + if not exists_in_index: + self._curr_batch.apply(record, not exists_in_index) + self._brute_force_index.upsert([record]) + else: + logger.warning(f"Add of existing embedding ID: {id}") + elif op == Operation.UPSERT: + if record["embedding"] is not None: + self._curr_batch.apply(record, exists_in_index) + self._brute_force_index.upsert([record]) + if len(self._curr_batch) >= self._batch_size: + self._apply_batch(self._curr_batch) + self._curr_batch = Batch() + self._brute_force_index.clear() + + @override + def count(self) -> int: + return ( + len(self._id_to_label) + + self._curr_batch.add_count + - self._curr_batch.delete_count + ) + + @trace_method( + "PersistentLocalHnswSegment.get_vectors", OpenTelemetryGranularity.ALL + ) + @override + def get_vectors( + self, ids: Optional[Sequence[str]] = None + ) -> Sequence[VectorEmbeddingRecord]: + """Get the embeddings from the HNSW index and layered brute force + batch index.""" + + ids_hnsw: Set[str] = set() + ids_bf: Set[str] = set() + + if self._index is not None: + ids_hnsw = set(self._id_to_label.keys()) + if self._brute_force_index is not None: + ids_bf = set(self._curr_batch.get_written_ids()) + + target_ids = ids or list(ids_hnsw.union(ids_bf)) + self._brute_force_index = cast(BruteForceIndex, self._brute_force_index) + hnsw_labels = [] + + results: List[Optional[VectorEmbeddingRecord]] = [] + id_to_index: Dict[str, int] = {} + for i, id in enumerate(target_ids): + if id in ids_bf: + results.append(self._brute_force_index.get_vectors([id])[0]) + elif id in ids_hnsw and id not in self._curr_batch._deleted_ids: + hnsw_labels.append(self._id_to_label[id]) + # Placeholder for hnsw results to be filled in down below so we + # can batch the hnsw get() call + results.append(None) + id_to_index[id] = i + + if len(hnsw_labels) > 0 and self._index is not None: + vectors = cast(Sequence[Vector], self._index.get_items(hnsw_labels)) + + for label, vector in zip(hnsw_labels, vectors): + id = self._label_to_id[label] + seq_id = self._id_to_seq_id[id] + results[id_to_index[id]] = VectorEmbeddingRecord( + id=id, seq_id=seq_id, embedding=vector + ) + + return results # type: ignore ## Python can't cast List with Optional to List with VectorEmbeddingRecord + + @trace_method( + "PersistentLocalHnswSegment.query_vectors", OpenTelemetryGranularity.ALL + ) + @override + def query_vectors( + self, query: VectorQuery + ) -> Sequence[Sequence[VectorQueryResult]]: + if self._index is None and self._brute_force_index is None: + return [[] for _ in range(len(query["vectors"]))] + + k = query["k"] + if k > self.count(): + logger.warning( + f"Number of requested results {k} is greater than number of elements in index {self.count()}, updating n_results = {self.count()}" + ) + k = self.count() + + # Overquery by updated and deleted elements layered on the index because they may + # hide the real nearest neighbors in the hnsw index + hnsw_k = k + self._curr_batch.update_count + self._curr_batch.delete_count + if hnsw_k > len(self._id_to_label): + hnsw_k = len(self._id_to_label) + hnsw_query = VectorQuery( + vectors=query["vectors"], + k=hnsw_k, + allowed_ids=query["allowed_ids"], + include_embeddings=query["include_embeddings"], + options=query["options"], + ) + + # For each query vector, we want to take the top k results from the + # combined results of the brute force and hnsw index + results: List[List[VectorQueryResult]] = [] + self._brute_force_index = cast(BruteForceIndex, self._brute_force_index) + with ReadRWLock(self._lock): + bf_results = self._brute_force_index.query(query) + hnsw_results = super().query_vectors(hnsw_query) + for i in range(len(query["vectors"])): + # Merge results into a single list of size k + bf_pointer: int = 0 + hnsw_pointer: int = 0 + curr_bf_result: Sequence[VectorQueryResult] = bf_results[i] + curr_hnsw_result: Sequence[VectorQueryResult] = hnsw_results[i] + curr_results: List[VectorQueryResult] = [] + # In the case where filters cause the number of results to be less than k, + # we set k to be the number of results + total_results = len(curr_bf_result) + len(curr_hnsw_result) + if total_results == 0: + results.append([]) + else: + while len(curr_results) < min(k, total_results): + if bf_pointer < len(curr_bf_result) and hnsw_pointer < len( + curr_hnsw_result + ): + bf_dist = curr_bf_result[bf_pointer]["distance"] + hnsw_dist = curr_hnsw_result[hnsw_pointer]["distance"] + if bf_dist <= hnsw_dist: + curr_results.append(curr_bf_result[bf_pointer]) + bf_pointer += 1 + else: + id = curr_hnsw_result[hnsw_pointer]["id"] + # Only add the hnsw result if it is not in the brute force index + # as updated or deleted + if not self._brute_force_index.has_id( + id + ) and not self._curr_batch.is_deleted(id): + curr_results.append(curr_hnsw_result[hnsw_pointer]) + hnsw_pointer += 1 + else: + break + remaining = min(k, total_results) - len(curr_results) + if remaining > 0 and hnsw_pointer < len(curr_hnsw_result): + for i in range( + hnsw_pointer, + min(len(curr_hnsw_result), hnsw_pointer + remaining + 1), + ): + id = curr_hnsw_result[i]["id"] + if not self._brute_force_index.has_id( + id + ) and not self._curr_batch.is_deleted(id): + curr_results.append(curr_hnsw_result[i]) + elif remaining > 0 and bf_pointer < len(curr_bf_result): + curr_results.extend( + curr_bf_result[bf_pointer : bf_pointer + remaining] + ) + results.append(curr_results) + return results + + @trace_method( + "PersistentLocalHnswSegment.reset_state", OpenTelemetryGranularity.ALL + ) + @override + def reset_state(self) -> None: + if self._allow_reset: + data_path = self._get_storage_folder() + if os.path.exists(data_path): + self.close_persistent_index() + shutil.rmtree(data_path, ignore_errors=True) + + @trace_method("PersistentLocalHnswSegment.delete", OpenTelemetryGranularity.ALL) + @override + def delete(self) -> None: + data_path = self._get_storage_folder() + if os.path.exists(data_path): + self.close_persistent_index() + shutil.rmtree(data_path, ignore_errors=False) + + @staticmethod + def get_file_handle_count() -> int: + """Return how many file handles are used by the index""" + hnswlib_count = hnswlib.Index.file_handle_count + hnswlib_count = cast(int, hnswlib_count) + # One extra for the metadata file + return hnswlib_count + 1 # type: ignore + + def open_persistent_index(self) -> None: + """Open the persistent index""" + if self._index is not None: + self._index.open_file_handles() + + def close_persistent_index(self) -> None: + """Close the persistent index""" + if self._index is not None: + self._index.close_file_handles() diff --git a/chromadb/server/__init__.py b/chromadb/server/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..eccd02cb0681d6e0031874754a1bbe110b6b12a2 --- /dev/null +++ b/chromadb/server/__init__.py @@ -0,0 +1,9 @@ +from abc import ABC, abstractmethod + +from chromadb.config import Settings + + +class Server(ABC): + @abstractmethod + def __init__(self, settings: Settings): + pass diff --git a/chromadb/server/fastapi/__init__.py b/chromadb/server/fastapi/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..529606a6c368c51216f4ebf67b36a62e75162aeb --- /dev/null +++ b/chromadb/server/fastapi/__init__.py @@ -0,0 +1,622 @@ +from typing import Any, Callable, Dict, List, Sequence, Optional +import fastapi +from fastapi import FastAPI as _FastAPI, Response +from fastapi.responses import JSONResponse + +from fastapi.middleware.cors import CORSMiddleware +from fastapi.routing import APIRoute +from fastapi import HTTPException, status +from uuid import UUID +from chromadb.api.models.Collection import Collection +from chromadb.api.types import GetResult, QueryResult +from chromadb.auth import ( + AuthzDynamicParams, + AuthzResourceActions, + AuthzResourceTypes, + DynamicAuthzResource, +) +from chromadb.auth.fastapi import ( + FastAPIChromaAuthMiddleware, + FastAPIChromaAuthMiddlewareWrapper, + FastAPIChromaAuthzMiddleware, + FastAPIChromaAuthzMiddlewareWrapper, + authz_context, + set_overwrite_singleton_tenant_database_access_from_auth, +) +from chromadb.auth.fastapi_utils import ( + attr_from_collection_lookup, + attr_from_resource_object, +) +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Settings, System +import chromadb.api +from chromadb.api import ServerAPI +from chromadb.errors import ( + ChromaError, + InvalidDimensionException, + InvalidHTTPVersion, +) +from chromadb.server.fastapi.types import ( + AddEmbedding, + CreateDatabase, + CreateTenant, + DeleteEmbedding, + GetEmbedding, + QueryEmbedding, + CreateCollection, + UpdateCollection, + UpdateEmbedding, +) +from starlette.requests import Request + +import logging + +from chromadb.server.fastapi.utils import fastapi_json_response, string_to_uuid as _uuid +from chromadb.telemetry.opentelemetry.fastapi import instrument_fastapi +from chromadb.types import Database, Tenant +from chromadb.telemetry.product import ServerContext, ProductTelemetryClient +from chromadb.telemetry.opentelemetry import ( + OpenTelemetryClient, + OpenTelemetryGranularity, + trace_method, +) + +logger = logging.getLogger(__name__) + + +def use_route_names_as_operation_ids(app: _FastAPI) -> None: + """ + Simplify operation IDs so that generated API clients have simpler function + names. + Should be called only after all routes have been added. + """ + for route in app.routes: + if isinstance(route, APIRoute): + route.operation_id = route.name + + +async def catch_exceptions_middleware( + request: Request, call_next: Callable[[Request], Any] +) -> Response: + try: + return await call_next(request) + except ChromaError as e: + return fastapi_json_response(e) + except Exception as e: + logger.exception(e) + return JSONResponse(content={"error": repr(e)}, status_code=500) + + +async def check_http_version_middleware( + request: Request, call_next: Callable[[Request], Any] +) -> Response: + http_version = request.scope.get("http_version") + if http_version not in ["1.1", "2"]: + raise InvalidHTTPVersion(f"HTTP version {http_version} is not supported") + return await call_next(request) + + +class ChromaAPIRouter(fastapi.APIRouter): # type: ignore + # A simple subclass of fastapi's APIRouter which treats URLs with a trailing "/" the + # same as URLs without. Docs will only contain URLs without trailing "/"s. + def add_api_route(self, path: str, *args: Any, **kwargs: Any) -> None: + # If kwargs["include_in_schema"] isn't passed OR is True, we should only + # include the non-"/" path. If kwargs["include_in_schema"] is False, include + # neither. + exclude_from_schema = ( + "include_in_schema" in kwargs and not kwargs["include_in_schema"] + ) + + def include_in_schema(path: str) -> bool: + nonlocal exclude_from_schema + return not exclude_from_schema and not path.endswith("/") + + kwargs["include_in_schema"] = include_in_schema(path) + super().add_api_route(path, *args, **kwargs) + + if path.endswith("/"): + path = path[:-1] + else: + path = path + "/" + + kwargs["include_in_schema"] = include_in_schema(path) + super().add_api_route(path, *args, **kwargs) + + +class FastAPI(chromadb.server.Server): + def __init__(self, settings: Settings): + super().__init__(settings) + ProductTelemetryClient.SERVER_CONTEXT = ServerContext.FASTAPI + self._app = fastapi.FastAPI(debug=True) + self._system = System(settings) + self._api: ServerAPI = self._system.instance(ServerAPI) + self._opentelemetry_client = self._api.require(OpenTelemetryClient) + self._system.start() + + self._app.middleware("http")(check_http_version_middleware) + self._app.middleware("http")(catch_exceptions_middleware) + self._app.add_middleware( + CORSMiddleware, + allow_headers=["*"], + allow_origins=settings.chroma_server_cors_allow_origins, + allow_methods=["*"], + ) + + self._app.on_event("shutdown")(self.shutdown) + + if settings.chroma_server_authz_provider: + self._app.add_middleware( + FastAPIChromaAuthzMiddlewareWrapper, + authz_middleware=self._api.require(FastAPIChromaAuthzMiddleware), + ) + + if settings.chroma_server_auth_provider: + self._app.add_middleware( + FastAPIChromaAuthMiddlewareWrapper, + auth_middleware=self._api.require(FastAPIChromaAuthMiddleware), + ) + set_overwrite_singleton_tenant_database_access_from_auth( + settings.chroma_overwrite_singleton_tenant_database_access_from_auth + ) + + self.router = ChromaAPIRouter() + + self.router.add_api_route("/api/v1", self.root, methods=["GET"]) + self.router.add_api_route("/api/v1/reset", self.reset, methods=["POST"]) + self.router.add_api_route("/api/v1/version", self.version, methods=["GET"]) + self.router.add_api_route("/api/v1/heartbeat", self.heartbeat, methods=["GET"]) + self.router.add_api_route( + "/api/v1/pre-flight-checks", self.pre_flight_checks, methods=["GET"] + ) + + self.router.add_api_route( + "/api/v1/databases", + self.create_database, + methods=["POST"], + response_model=None, + ) + + self.router.add_api_route( + "/api/v1/databases/{database}", + self.get_database, + methods=["GET"], + response_model=None, + ) + + self.router.add_api_route( + "/api/v1/tenants", + self.create_tenant, + methods=["POST"], + response_model=None, + ) + + self.router.add_api_route( + "/api/v1/tenants/{tenant}", + self.get_tenant, + methods=["GET"], + response_model=None, + ) + + self.router.add_api_route( + "/api/v1/collections", + self.list_collections, + methods=["GET"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/count_collections", + self.count_collections, + methods=["GET"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections", + self.create_collection, + methods=["POST"], + response_model=None, + ) + + self.router.add_api_route( + "/api/v1/collections/{collection_id}/add", + self.add, + methods=["POST"], + status_code=status.HTTP_201_CREATED, + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}/update", + self.update, + methods=["POST"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}/upsert", + self.upsert, + methods=["POST"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}/get", + self.get, + methods=["POST"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}/delete", + self.delete, + methods=["POST"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}/count", + self.count, + methods=["GET"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}/query", + self.get_nearest_neighbors, + methods=["POST"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_name}", + self.get_collection, + methods=["GET"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_id}", + self.update_collection, + methods=["PUT"], + response_model=None, + ) + self.router.add_api_route( + "/api/v1/collections/{collection_name}", + self.delete_collection, + methods=["DELETE"], + response_model=None, + ) + + self._app.include_router(self.router) + + use_route_names_as_operation_ids(self._app) + instrument_fastapi(self._app) + + def shutdown(self) -> None: + self._system.stop() + + def app(self) -> fastapi.FastAPI: + return self._app + + def root(self) -> Dict[str, int]: + return {"nanosecond heartbeat": self._api.heartbeat()} + + def heartbeat(self) -> Dict[str, int]: + return self.root() + + def version(self) -> str: + return self._api.get_version() + + @trace_method("FastAPI.create_database", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.CREATE_DATABASE, + resource=DynamicAuthzResource( + type=AuthzResourceTypes.DB, + attributes=attr_from_resource_object( + type=AuthzResourceTypes.DB, additional_attrs=["tenant"] + ), + ), + ) + def create_database( + self, database: CreateDatabase, tenant: str = DEFAULT_TENANT + ) -> None: + return self._api.create_database(database.name, tenant) + + @trace_method("FastAPI.get_database", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.GET_DATABASE, + resource=DynamicAuthzResource( + id="*", + type=AuthzResourceTypes.DB, + attributes=AuthzDynamicParams.dict_from_function_kwargs( + arg_names=["tenant", "database"] + ), + ), + ) + def get_database(self, database: str, tenant: str = DEFAULT_TENANT) -> Database: + return self._api.get_database(database, tenant) + + @trace_method("FastAPI.create_tenant", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.CREATE_TENANT, + resource=DynamicAuthzResource( + type=AuthzResourceTypes.TENANT, + ), + ) + def create_tenant(self, tenant: CreateTenant) -> None: + return self._api.create_tenant(tenant.name) + + @trace_method("FastAPI.get_tenant", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.GET_TENANT, + resource=DynamicAuthzResource( + id="*", + type=AuthzResourceTypes.TENANT, + ), + ) + def get_tenant(self, tenant: str) -> Tenant: + return self._api.get_tenant(tenant) + + @trace_method("FastAPI.list_collections", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.LIST_COLLECTIONS, + resource=DynamicAuthzResource( + id="*", + type=AuthzResourceTypes.DB, + attributes=AuthzDynamicParams.dict_from_function_kwargs( + arg_names=["tenant", "database"] + ), + ), + ) + def list_collections( + self, + limit: Optional[int] = None, + offset: Optional[int] = None, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Sequence[Collection]: + return self._api.list_collections( + limit=limit, offset=offset, tenant=tenant, database=database + ) + + @trace_method("FastAPI.count_collections", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.COUNT_COLLECTIONS, + resource=DynamicAuthzResource( + id="*", + type=AuthzResourceTypes.DB, + attributes=AuthzDynamicParams.dict_from_function_kwargs( + arg_names=["tenant", "database"] + ), + ), + ) + def count_collections( + self, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> int: + return self._api.count_collections(tenant=tenant, database=database) + + @trace_method("FastAPI.create_collection", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.CREATE_COLLECTION, + resource=DynamicAuthzResource( + id="*", + type=AuthzResourceTypes.DB, + attributes=AuthzDynamicParams.dict_from_function_kwargs( + arg_names=["tenant", "database"] + ), + ), + ) + def create_collection( + self, + collection: CreateCollection, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + return self._api.create_collection( + name=collection.name, + metadata=collection.metadata, + get_or_create=collection.get_or_create, + tenant=tenant, + database=database, + ) + + @trace_method("FastAPI.get_collection", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.GET_COLLECTION, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_name"), + type=AuthzResourceTypes.COLLECTION, + attributes=AuthzDynamicParams.dict_from_function_kwargs( + arg_names=["tenant", "database"] + ), + ), + ) + def get_collection( + self, + collection_name: str, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> Collection: + return self._api.get_collection( + collection_name, tenant=tenant, database=database + ) + + @trace_method("FastAPI.update_collection", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.UPDATE_COLLECTION, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def update_collection( + self, collection_id: str, collection: UpdateCollection + ) -> None: + return self._api._modify( + id=_uuid(collection_id), + new_name=collection.new_name, + new_metadata=collection.new_metadata, + ) + + @trace_method("FastAPI.delete_collection", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.DELETE_COLLECTION, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_name"), + type=AuthzResourceTypes.COLLECTION, + attributes=AuthzDynamicParams.dict_from_function_kwargs( + arg_names=["tenant", "database"] + ), + ), + ) + def delete_collection( + self, + collection_name: str, + tenant: str = DEFAULT_TENANT, + database: str = DEFAULT_DATABASE, + ) -> None: + return self._api.delete_collection( + collection_name, tenant=tenant, database=database + ) + + @trace_method("FastAPI.add", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.ADD, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def add(self, collection_id: str, add: AddEmbedding) -> None: + try: + result = self._api._add( + collection_id=_uuid(collection_id), + embeddings=add.embeddings, # type: ignore + metadatas=add.metadatas, # type: ignore + documents=add.documents, # type: ignore + uris=add.uris, # type: ignore + ids=add.ids, + ) + except InvalidDimensionException as e: + raise HTTPException(status_code=500, detail=str(e)) + return result # type: ignore + + @trace_method("FastAPI.update", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.UPDATE, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def update(self, collection_id: str, add: UpdateEmbedding) -> None: + self._api._update( + ids=add.ids, + collection_id=_uuid(collection_id), + embeddings=add.embeddings, + documents=add.documents, # type: ignore + uris=add.uris, # type: ignore + metadatas=add.metadatas, # type: ignore + ) + + @trace_method("FastAPI.upsert", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.UPSERT, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def upsert(self, collection_id: str, upsert: AddEmbedding) -> None: + self._api._upsert( + collection_id=_uuid(collection_id), + ids=upsert.ids, + embeddings=upsert.embeddings, # type: ignore + documents=upsert.documents, # type: ignore + uris=upsert.uris, # type: ignore + metadatas=upsert.metadatas, # type: ignore + ) + + @trace_method("FastAPI.get", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.GET, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def get(self, collection_id: str, get: GetEmbedding) -> GetResult: + return self._api._get( + collection_id=_uuid(collection_id), + ids=get.ids, + where=get.where, + where_document=get.where_document, + sort=get.sort, + limit=get.limit, + offset=get.offset, + include=get.include, + ) + + @trace_method("FastAPI.delete", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.DELETE, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def delete(self, collection_id: str, delete: DeleteEmbedding) -> List[UUID]: + return self._api._delete( + where=delete.where, # type: ignore + ids=delete.ids, + collection_id=_uuid(collection_id), + where_document=delete.where_document, + ) + + @trace_method("FastAPI.count", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.COUNT, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def count(self, collection_id: str) -> int: + return self._api._count(_uuid(collection_id)) + + @trace_method("FastAPI.reset", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.RESET, + resource=DynamicAuthzResource( + id="*", + type=AuthzResourceTypes.DB, + ), + ) + def reset(self) -> bool: + return self._api.reset() + + @trace_method("FastAPI.get_nearest_neighbors", OpenTelemetryGranularity.OPERATION) + @authz_context( + action=AuthzResourceActions.QUERY, + resource=DynamicAuthzResource( + id=AuthzDynamicParams.from_function_kwargs(arg_name="collection_id"), + type=AuthzResourceTypes.COLLECTION, + attributes=attr_from_collection_lookup(collection_id_arg="collection_id"), + ), + ) + def get_nearest_neighbors( + self, collection_id: str, query: QueryEmbedding + ) -> QueryResult: + nnresult = self._api._query( + collection_id=_uuid(collection_id), + where=query.where, # type: ignore + where_document=query.where_document, # type: ignore + query_embeddings=query.query_embeddings, + n_results=query.n_results, + include=query.include, + ) + return nnresult + + def pre_flight_checks(self) -> Dict[str, Any]: + return { + "max_batch_size": self._api.max_batch_size, + } diff --git a/chromadb/server/fastapi/types.py b/chromadb/server/fastapi/types.py new file mode 100644 index 0000000000000000000000000000000000000000..f8976fca67d39812cbe58334b9919fcb73b4bbe6 --- /dev/null +++ b/chromadb/server/fastapi/types.py @@ -0,0 +1,71 @@ +from pydantic import BaseModel +from typing import Any, Dict, List, Optional +from chromadb.api.types import ( + CollectionMetadata, + Include, +) + + +class AddEmbedding(BaseModel): + # Pydantic doesn't handle Union types cleanly like Embeddings which has + # Union[int, float] so we use Any here to ensure data is parsed + # to its original type. + embeddings: Optional[List[Any]] = None + metadatas: Optional[List[Optional[Dict[Any, Any]]]] = None + documents: Optional[List[Optional[str]]] = None + uris: Optional[List[Optional[str]]] = None + ids: List[str] + + +class UpdateEmbedding(BaseModel): + embeddings: Optional[List[Any]] = None + metadatas: Optional[List[Optional[Dict[Any, Any]]]] = None + documents: Optional[List[Optional[str]]] = None + uris: Optional[List[Optional[str]]] = None + ids: List[str] + + +class QueryEmbedding(BaseModel): + # TODO: Pydantic doesn't bode well with recursive types so we use generic Dicts + # for Where and WhereDocument. This is not ideal, but it works for now since + # there is a lot of downstream validation. + where: Optional[Dict[Any, Any]] = {} + where_document: Optional[Dict[Any, Any]] = {} + query_embeddings: List[Any] + n_results: int = 10 + include: Include = ["metadatas", "documents", "distances"] + + +class GetEmbedding(BaseModel): + ids: Optional[List[str]] = None + where: Optional[Dict[Any, Any]] = None + where_document: Optional[Dict[Any, Any]] = None + sort: Optional[str] = None + limit: Optional[int] = None + offset: Optional[int] = None + include: Include = ["metadatas", "documents"] + + +class DeleteEmbedding(BaseModel): + ids: Optional[List[str]] = None + where: Optional[Dict[Any, Any]] = None + where_document: Optional[Dict[Any, Any]] = None + + +class CreateCollection(BaseModel): + name: str + metadata: Optional[CollectionMetadata] = None + get_or_create: bool = False + + +class UpdateCollection(BaseModel): + new_name: Optional[str] = None + new_metadata: Optional[CollectionMetadata] = None + + +class CreateDatabase(BaseModel): + name: str + + +class CreateTenant(BaseModel): + name: str diff --git a/chromadb/server/fastapi/utils.py b/chromadb/server/fastapi/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..b7e781dae689c7e4b09b08a5bcdeaa3e179278b8 --- /dev/null +++ b/chromadb/server/fastapi/utils.py @@ -0,0 +1,17 @@ +from uuid import UUID +from starlette.responses import JSONResponse + +from chromadb.errors import ChromaError, InvalidUUIDError + + +def fastapi_json_response(error: ChromaError) -> JSONResponse: + return JSONResponse( + content={"error": error.name(), "message": error.message()}, + status_code=error.code(), + ) + +def string_to_uuid(uuid_str: str) -> UUID: + try: + return UUID(uuid_str) + except ValueError: + raise InvalidUUIDError(f"Could not parse {uuid_str} as a UUID") \ No newline at end of file diff --git a/chromadb/telemetry/README.md b/chromadb/telemetry/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4e63b0e29038b6c95db6e0c06c2d7e5bf0edb839 --- /dev/null +++ b/chromadb/telemetry/README.md @@ -0,0 +1,10 @@ +# Telemetry + +This directory holds all the telemetry for Chroma. + +- `product/` contains anonymized product telemetry which we, Chroma, collect so we can + understand usage patterns. For more information, see https://docs.trychroma.com/telemetry. +- `opentelemetry/` contains all of the config for Chroma's [OpenTelemetry](https://opentelemetry.io/docs/instrumentation/python/getting-started/) + setup. These metrics are *not* sent back to Chroma -- anyone operating a Chroma instance + can use the OpenTelemetry metrics and traces to understand how their instance of Chroma + is behaving. diff --git a/chromadb/telemetry/__init__.py b/chromadb/telemetry/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/telemetry/opentelemetry/__init__.py b/chromadb/telemetry/opentelemetry/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..0160c28183d0a3f78fc3bd4f12c72066f7208fcd --- /dev/null +++ b/chromadb/telemetry/opentelemetry/__init__.py @@ -0,0 +1,160 @@ +from functools import wraps +from enum import Enum +from typing import Any, Callable, Dict, Optional, Sequence, Union + +from opentelemetry import trace +from opentelemetry.sdk.resources import SERVICE_NAME, Resource +from opentelemetry.sdk.trace import TracerProvider +from opentelemetry.sdk.trace.export import ( + BatchSpanProcessor, +) +from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter + +from chromadb.config import Component +from chromadb.config import System + + +class OpenTelemetryGranularity(Enum): + """The granularity of the OpenTelemetry spans.""" + + NONE = "none" + """No spans are emitted.""" + + OPERATION = "operation" + """Spans are emitted for each operation.""" + + OPERATION_AND_SEGMENT = "operation_and_segment" + """Spans are emitted for each operation and segment.""" + + ALL = "all" + """Spans are emitted for almost every method call.""" + + # Greater is more restrictive. So "all" < "operation" (and everything else), + # "none" > everything. + def __lt__(self, other: Any) -> bool: + """Compare two granularities.""" + order = [ + OpenTelemetryGranularity.ALL, + OpenTelemetryGranularity.OPERATION_AND_SEGMENT, + OpenTelemetryGranularity.OPERATION, + OpenTelemetryGranularity.NONE, + ] + return order.index(self) < order.index(other) + + +class OpenTelemetryClient(Component): + def __init__(self, system: System): + super().__init__(system) + otel_init( + system.settings.chroma_otel_service_name, + system.settings.chroma_otel_collection_endpoint, + system.settings.chroma_otel_collection_headers, + OpenTelemetryGranularity( + system.settings.chroma_otel_granularity + if system.settings.chroma_otel_granularity + else "none" + ), + ) + + +tracer: Optional[trace.Tracer] = None +granularity: OpenTelemetryGranularity = OpenTelemetryGranularity("none") + + +def otel_init( + otel_service_name: Optional[str], + otel_collection_endpoint: Optional[str], + otel_collection_headers: Optional[Dict[str, str]], + otel_granularity: OpenTelemetryGranularity, +) -> None: + """Initializes module-level state for OpenTelemetry. + + Parameters match the environment variables which configure OTel as documented + at https://docs.trychroma.com/observability. + - otel_service_name: The name of the service for OTel tagging and aggregation. + - otel_collection_endpoint: The endpoint to which OTel spans are sent + (e.g. api.honeycomb.com). + - otel_collection_headers: The headers to send with OTel spans + (e.g. {"x-honeycomb-team": "abc123"}). + - otel_granularity: The granularity of the spans to emit. + """ + if otel_granularity == OpenTelemetryGranularity.NONE: + return + resource = Resource(attributes={SERVICE_NAME: str(otel_service_name)}) + provider = TracerProvider(resource=resource) + provider.add_span_processor( + BatchSpanProcessor( + # TODO: we may eventually want to make this configurable. + OTLPSpanExporter( + endpoint=str(otel_collection_endpoint), + headers=otel_collection_headers, + ) + ) + ) + trace.set_tracer_provider(provider) + + global tracer, granularity + tracer = trace.get_tracer(__name__) + granularity = otel_granularity + + +def trace_method( + trace_name: str, + trace_granularity: OpenTelemetryGranularity, + attributes: Optional[ + Dict[ + str, + Union[ + str, + bool, + float, + int, + Sequence[str], + Sequence[bool], + Sequence[float], + Sequence[int], + ], + ] + ] = None, +) -> Callable[[Callable[..., Any]], Callable[..., Any]]: + """A decorator that traces a method.""" + + def decorator(f: Callable[..., Any]) -> Callable[..., Any]: + @wraps(f) + def wrapper(*args: Any, **kwargs: Dict[Any, Any]) -> Any: + global tracer, granularity + if trace_granularity < granularity: + return f(*args, **kwargs) + if not tracer: + return f(*args, **kwargs) + with tracer.start_as_current_span(trace_name, attributes=attributes): + return f(*args, **kwargs) + + return wrapper + + return decorator + + +def add_attributes_to_current_span( + attributes: Dict[ + str, + Union[ + str, + bool, + float, + int, + Sequence[str], + Sequence[bool], + Sequence[float], + Sequence[int], + ], + ] +) -> None: + """Add attributes to the current span.""" + global tracer, granularity + if granularity == OpenTelemetryGranularity.NONE: + return + if not tracer: + return + span = trace.get_current_span() + span.set_attributes(attributes) diff --git a/chromadb/telemetry/opentelemetry/fastapi.py b/chromadb/telemetry/opentelemetry/fastapi.py new file mode 100644 index 0000000000000000000000000000000000000000..348257945555f7f97a84806950c854d2249a93a1 --- /dev/null +++ b/chromadb/telemetry/opentelemetry/fastapi.py @@ -0,0 +1,10 @@ +from typing import List, Optional +from fastapi import FastAPI +from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor + + +def instrument_fastapi(app: FastAPI, excluded_urls: Optional[List[str]] = None) -> None: + """Instrument FastAPI to emit OpenTelemetry spans.""" + FastAPIInstrumentor.instrument_app( + app, excluded_urls=",".join(excluded_urls) if excluded_urls else None + ) diff --git a/chromadb/telemetry/product/__init__.py b/chromadb/telemetry/product/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..a6fd0d7ad878e1c3821c692d5bbf0b014af7f66e --- /dev/null +++ b/chromadb/telemetry/product/__init__.py @@ -0,0 +1,93 @@ +from abc import abstractmethod +import os +from typing import ClassVar, Dict, Any +import uuid +import chromadb +from chromadb.config import Component +from pathlib import Path +from enum import Enum + +TELEMETRY_WHITELISTED_SETTINGS = [ + "chroma_api_impl", + "is_persistent", + "chroma_server_ssl_enabled", +] + + +class ServerContext(Enum): + NONE = "None" + FASTAPI = "FastAPI" + + +class ProductTelemetryEvent: + max_batch_size: ClassVar[int] = 1 + batch_size: int + + def __init__(self, batch_size: int = 1): + self.batch_size = batch_size + + @property + def properties(self) -> Dict[str, Any]: + return self.__dict__ + + @property + def name(self) -> str: + return self.__class__.__name__ + + # A batch key is used to determine whether two events can be batched together. + # If a TelemetryEvent's max_batch_size > 1, batch_key() and batch() MUST be + # implemented. + # Otherwise they are ignored. + @property + def batch_key(self) -> str: + return self.name + + def batch(self, other: "ProductTelemetryEvent") -> "ProductTelemetryEvent": + raise NotImplementedError + + +class ProductTelemetryClient(Component): + USER_ID_PATH = str(Path.home() / ".cache" / "chroma" / "telemetry_user_id") + UNKNOWN_USER_ID = "UNKNOWN" + SERVER_CONTEXT: ServerContext = ServerContext.NONE + _curr_user_id = None + + @abstractmethod + def capture(self, event: ProductTelemetryEvent) -> None: + pass + + @property + def context(self) -> Dict[str, Any]: + chroma_version = chromadb.__version__ + settings = chromadb.get_settings() + telemetry_settings = {} + for whitelisted in TELEMETRY_WHITELISTED_SETTINGS: + telemetry_settings[whitelisted] = settings[whitelisted] + + self._context = { + "chroma_version": chroma_version, + "server_context": self.SERVER_CONTEXT.value, + **telemetry_settings, + } + return self._context + + @property + def user_id(self) -> str: + if self._curr_user_id: + return self._curr_user_id + + # File access may fail due to permissions or other reasons. We don't want to + # crash so we catch all exceptions. + try: + if not os.path.exists(self.USER_ID_PATH): + os.makedirs(os.path.dirname(self.USER_ID_PATH), exist_ok=True) + with open(self.USER_ID_PATH, "w") as f: + new_user_id = str(uuid.uuid4()) + f.write(new_user_id) + self._curr_user_id = new_user_id + else: + with open(self.USER_ID_PATH, "r") as f: + self._curr_user_id = f.read() + except Exception: + self._curr_user_id = self.UNKNOWN_USER_ID + return self._curr_user_id diff --git a/chromadb/telemetry/product/events.py b/chromadb/telemetry/product/events.py new file mode 100644 index 0000000000000000000000000000000000000000..4e93c0245ebf81ff5c01fded511baa2714ac145d --- /dev/null +++ b/chromadb/telemetry/product/events.py @@ -0,0 +1,239 @@ +from typing import cast, ClassVar +from chromadb.telemetry.product import ProductTelemetryEvent +from chromadb.utils.embedding_functions import get_builtins + + +class ClientStartEvent(ProductTelemetryEvent): + def __init__(self) -> None: + super().__init__() + + +class ClientCreateCollectionEvent(ProductTelemetryEvent): + collection_uuid: str + embedding_function: str + + def __init__(self, collection_uuid: str, embedding_function: str): + super().__init__() + self.collection_uuid = collection_uuid + + embedding_function_names = get_builtins() + + self.embedding_function = ( + embedding_function + if embedding_function in embedding_function_names + else "custom" + ) + + +class CollectionAddEvent(ProductTelemetryEvent): + max_batch_size: ClassVar[int] = 1000 + batch_size: int + collection_uuid: str + add_amount: int + with_documents: int + with_metadata: int + with_uris: int + + def __init__( + self, + collection_uuid: str, + add_amount: int, + with_documents: int, + with_metadata: int, + with_uris: int, + batch_size: int = 1, + ): + super().__init__() + self.collection_uuid = collection_uuid + self.add_amount = add_amount + self.with_documents = with_documents + self.with_metadata = with_metadata + self.with_uris = with_uris + self.batch_size = batch_size + + @property + def batch_key(self) -> str: + return self.collection_uuid + self.name + + def batch(self, other: "ProductTelemetryEvent") -> "CollectionAddEvent": + if not self.batch_key == other.batch_key: + raise ValueError("Cannot batch events") + other = cast(CollectionAddEvent, other) + total_amount = self.add_amount + other.add_amount + return CollectionAddEvent( + collection_uuid=self.collection_uuid, + add_amount=total_amount, + with_documents=self.with_documents + other.with_documents, + with_metadata=self.with_metadata + other.with_metadata, + with_uris=self.with_uris + other.with_uris, + batch_size=self.batch_size + other.batch_size, + ) + + +class CollectionUpdateEvent(ProductTelemetryEvent): + max_batch_size: ClassVar[int] = 100 + batch_size: int + collection_uuid: str + update_amount: int + with_embeddings: int + with_metadata: int + with_documents: int + with_uris: int + + def __init__( + self, + collection_uuid: str, + update_amount: int, + with_embeddings: int, + with_metadata: int, + with_documents: int, + with_uris: int, + batch_size: int = 1, + ): + super().__init__() + self.collection_uuid = collection_uuid + self.update_amount = update_amount + self.with_embeddings = with_embeddings + self.with_metadata = with_metadata + self.with_documents = with_documents + self.with_uris = with_uris + self.batch_size = batch_size + + @property + def batch_key(self) -> str: + return self.collection_uuid + self.name + + def batch(self, other: "ProductTelemetryEvent") -> "CollectionUpdateEvent": + if not self.batch_key == other.batch_key: + raise ValueError("Cannot batch events") + other = cast(CollectionUpdateEvent, other) + total_amount = self.update_amount + other.update_amount + return CollectionUpdateEvent( + collection_uuid=self.collection_uuid, + update_amount=total_amount, + with_documents=self.with_documents + other.with_documents, + with_metadata=self.with_metadata + other.with_metadata, + with_embeddings=self.with_embeddings + other.with_embeddings, + with_uris=self.with_uris + other.with_uris, + batch_size=self.batch_size + other.batch_size, + ) + + +class CollectionQueryEvent(ProductTelemetryEvent): + max_batch_size: ClassVar[int] = 1000 + batch_size: int + collection_uuid: str + query_amount: int + with_metadata_filter: int + with_document_filter: int + n_results: int + include_metadatas: int + include_documents: int + include_uris: int + include_distances: int + + def __init__( + self, + collection_uuid: str, + query_amount: int, + with_metadata_filter: int, + with_document_filter: int, + n_results: int, + include_metadatas: int, + include_documents: int, + include_uris: int, + include_distances: int, + batch_size: int = 1, + ): + super().__init__() + self.collection_uuid = collection_uuid + self.query_amount = query_amount + self.with_metadata_filter = with_metadata_filter + self.with_document_filter = with_document_filter + self.n_results = n_results + self.include_metadatas = include_metadatas + self.include_documents = include_documents + self.include_uris = include_uris + self.include_distances = include_distances + self.batch_size = batch_size + + @property + def batch_key(self) -> str: + return self.collection_uuid + self.name + + def batch(self, other: "ProductTelemetryEvent") -> "CollectionQueryEvent": + if not self.batch_key == other.batch_key: + raise ValueError("Cannot batch events") + other = cast(CollectionQueryEvent, other) + total_amount = self.query_amount + other.query_amount + return CollectionQueryEvent( + collection_uuid=self.collection_uuid, + query_amount=total_amount, + with_metadata_filter=self.with_metadata_filter + other.with_metadata_filter, + with_document_filter=self.with_document_filter + other.with_document_filter, + n_results=self.n_results + other.n_results, + include_metadatas=self.include_metadatas + other.include_metadatas, + include_documents=self.include_documents + other.include_documents, + include_uris=self.include_uris + other.include_uris, + include_distances=self.include_distances + other.include_distances, + batch_size=self.batch_size + other.batch_size, + ) + + +class CollectionGetEvent(ProductTelemetryEvent): + max_batch_size: ClassVar[int] = 100 + batch_size: int + collection_uuid: str + ids_count: int + limit: int + include_metadata: int + include_documents: int + include_uris: int + + def __init__( + self, + collection_uuid: str, + ids_count: int, + limit: int, + include_metadata: int, + include_documents: int, + include_uris: int, + batch_size: int = 1, + ): + super().__init__() + self.collection_uuid = collection_uuid + self.ids_count = ids_count + self.limit = limit + self.include_metadata = include_metadata + self.include_documents = include_documents + self.include_uris = include_uris + self.batch_size = batch_size + + @property + def batch_key(self) -> str: + return self.collection_uuid + self.name + str(self.limit) + + def batch(self, other: "ProductTelemetryEvent") -> "CollectionGetEvent": + if not self.batch_key == other.batch_key: + raise ValueError("Cannot batch events") + other = cast(CollectionGetEvent, other) + total_amount = self.ids_count + other.ids_count + return CollectionGetEvent( + collection_uuid=self.collection_uuid, + ids_count=total_amount, + limit=self.limit, + include_metadata=self.include_metadata + other.include_metadata, + include_documents=self.include_documents + other.include_documents, + include_uris=self.include_uris + other.include_uris, + batch_size=self.batch_size + other.batch_size, + ) + + +class CollectionDeleteEvent(ProductTelemetryEvent): + collection_uuid: str + delete_amount: int + + def __init__(self, collection_uuid: str, delete_amount: int): + super().__init__() + self.collection_uuid = collection_uuid + self.delete_amount = delete_amount diff --git a/chromadb/telemetry/product/posthog.py b/chromadb/telemetry/product/posthog.py new file mode 100644 index 0000000000000000000000000000000000000000..05c46b07256b8dbf5f555dd10a10b79bab219a9b --- /dev/null +++ b/chromadb/telemetry/product/posthog.py @@ -0,0 +1,59 @@ +import posthog +import logging +import sys +from typing import Any, Dict, Set +from chromadb.config import System +from chromadb.telemetry.product import ( + ProductTelemetryClient, + ProductTelemetryEvent, +) +from overrides import override + +logger = logging.getLogger(__name__) + + +class Posthog(ProductTelemetryClient): + def __init__(self, system: System): + if not system.settings.anonymized_telemetry or "pytest" in sys.modules: + posthog.disabled = True + else: + logger.info( + "Anonymized telemetry enabled. See \ + https://docs.trychroma.com/telemetry for more information." + ) + + posthog.project_api_key = "phc_YeUxaojbKk5KPi8hNlx1bBKHzuZ4FDtl67kH1blv8Bh" + posthog_logger = logging.getLogger("posthog") + # Silence posthog's logging + posthog_logger.disabled = True + + self.batched_events: Dict[str, ProductTelemetryEvent] = {} + self.seen_event_types: Set[Any] = set() + + super().__init__(system) + + @override + def capture(self, event: ProductTelemetryEvent) -> None: + if event.max_batch_size == 1 or event.batch_key not in self.seen_event_types: + self.seen_event_types.add(event.batch_key) + self._direct_capture(event) + return + batch_key = event.batch_key + if batch_key not in self.batched_events: + self.batched_events[batch_key] = event + return + batched_event = self.batched_events[batch_key].batch(event) + self.batched_events[batch_key] = batched_event + if batched_event.batch_size >= batched_event.max_batch_size: + self._direct_capture(batched_event) + del self.batched_events[batch_key] + + def _direct_capture(self, event: ProductTelemetryEvent) -> None: + try: + posthog.capture( + self.user_id, + event.name, + {**event.properties, **self.context}, + ) + except Exception as e: + logger.error(f"Failed to send telemetry event {event.name}: {e}") diff --git a/chromadb/test/api/test_types.py b/chromadb/test/api/test_types.py new file mode 100644 index 0000000000000000000000000000000000000000..b11c4b2c79ced947eab577c0c10b10292fd36caf --- /dev/null +++ b/chromadb/test/api/test_types.py @@ -0,0 +1,40 @@ +import pytest +from typing import List, cast +from chromadb.api.types import EmbeddingFunction, Documents, Image, Document, Embeddings +import numpy as np + + +def random_embeddings() -> Embeddings: + return cast(Embeddings, np.random.random(size=(10, 10)).tolist()) + + +def random_image() -> Image: + return np.random.randint(0, 255, size=(10, 10, 3), dtype=np.int32) + + +def random_documents() -> List[Document]: + return [str(random_image()) for _ in range(10)] + + +def test_embedding_function_results_format_when_response_is_valid() -> None: + valid_embeddings = random_embeddings() + + class TestEmbeddingFunction(EmbeddingFunction[Documents]): + def __call__(self, input: Documents) -> Embeddings: + return valid_embeddings + + ef = TestEmbeddingFunction() + assert valid_embeddings == ef(random_documents()) + + +def test_embedding_function_results_format_when_response_is_invalid() -> None: + invalid_embedding = {"error": "test"} + + class TestEmbeddingFunction(EmbeddingFunction[Documents]): + def __call__(self, input: Documents) -> Embeddings: + return cast(Embeddings, invalid_embedding) + + ef = TestEmbeddingFunction() + with pytest.raises(ValueError) as e: + ef(random_documents()) + assert e.type is ValueError diff --git a/chromadb/test/auth/test_basic_auth.py b/chromadb/test/auth/test_basic_auth.py new file mode 100644 index 0000000000000000000000000000000000000000..f064be66335811eac974279f90d23aca35f738c8 --- /dev/null +++ b/chromadb/test/auth/test_basic_auth.py @@ -0,0 +1,12 @@ +import pytest + + +def test_invalid_auth_cred(api_wrong_cred): + with pytest.raises(Exception) as e: + api_wrong_cred.list_collections() + assert "Unauthorized" in str(e.value) + + +def test_server_basic_auth(api_with_server_auth): + cols = api_with_server_auth.list_collections() + assert len(cols) == 0 diff --git a/chromadb/test/auth/test_simple_rbac_authz.py b/chromadb/test/auth/test_simple_rbac_authz.py new file mode 100644 index 0000000000000000000000000000000000000000..ed9eead9c4e5f9c9e3085224659434f12106fbef --- /dev/null +++ b/chromadb/test/auth/test_simple_rbac_authz.py @@ -0,0 +1,325 @@ +import json +import random +import string +from typing import Dict, Any, Tuple +import uuid +import hypothesis.strategies as st +import pytest +from hypothesis import given, settings +from chromadb import AdminClient + +from chromadb.api import AdminAPI, ServerAPI +from chromadb.api.models.Collection import Collection +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Settings, System +from chromadb.test.conftest import _fastapi_fixture + + +valid_action_space = [ + "tenant:create_tenant", + "tenant:get_tenant", + "db:create_database", + "db:get_database", + "db:reset", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "collection:delete_collection", + "collection:update_collection", + "collection:add", + "collection:delete", + "collection:get", + "collection:query", + "collection:peek", + "collection:update", + "collection:upsert", + "collection:count", +] + +role_name = st.text(alphabet=string.ascii_letters, min_size=1, max_size=20) + +user_name = st.text(alphabet=string.ascii_letters, min_size=1, max_size=20) + +actions = st.lists( + st.sampled_from(valid_action_space), min_size=1, max_size=len(valid_action_space) +) + + +@st.composite +def master_user(draw: st.DrawFn) -> Tuple[Dict[str, Any], Dict[str, Any]]: + return { + "role": "__master_role__", + "id": "__master__", + "tenant": DEFAULT_TENANT, + "tokens": [ + { + "token": f"{random.randint(1,1000000)}_" + + draw( + st.text( + alphabet=string.ascii_letters + string.digits, + min_size=1, + max_size=25, + ) + ) + } + for _ in range(2) + ], + }, { + "__master_role__": { + "actions": valid_action_space, + "unauthorized_actions": [], + } + } + + +@st.composite +def user_role_config(draw: st.DrawFn) -> Tuple[Dict[str, Any], Dict[str, Any]]: + role = draw(role_name) + user = draw(user_name) + actions_list = draw(actions) + if any( + action in actions_list + for action in [ + "collection:add", + "collection:delete", + "collection:get", + "collection:query", + "collection:peek", + "collection:update", + "collection:upsert", + "collection:count", + ] + ): + actions_list.append("collection:get_collection") + if any( + action in actions_list + for action in [ + "collection:peek", + ] + ): + actions_list.append("collection:get") + actions_list.extend( + [ + "tenant:get_tenant", + "db:get_database", + ] + ) + unauthorized_actions = set(valid_action_space) - set(actions_list) + _role_config = { + f"{role}": { + "actions": actions_list, + "unauthorized_actions": list(unauthorized_actions), + } + } + + return { + "role": role, + "id": user, + "tenant": DEFAULT_TENANT, + "tokens": [ + { + "token": f"{random.randint(1,1000000)}_" + + draw( + st.text( + alphabet=string.ascii_letters + string.digits, + min_size=1, + max_size=25, + ) + ) + } + for _ in range(2) + ], + }, _role_config + + +@st.composite +def rbac_config(draw: st.DrawFn) -> Dict[str, Any]: + user_roles = draw( + st.lists(user_role_config().filter(lambda t: t[0]), min_size=1, max_size=10) + ) + muser_role = draw(st.lists(master_user(), min_size=1, max_size=1)) + users = [] + roles = [] + for user, role in user_roles: + users.append(user) + roles.append(role) + + for muser, mrole in muser_role: + users.append(muser) + roles.append(mrole) + roles_mapping = {} + for role in roles: + roles_mapping.update(role) + _rbac_config = { + "roles_mapping": roles_mapping, + "users": users, + } + return _rbac_config + + +@st.composite +def token_config(draw: st.DrawFn) -> Dict[str, Any]: + token_header = draw(st.sampled_from(["AUTHORIZATION", "X_CHROMA_TOKEN", None])) + server_provider = draw( + st.sampled_from(["token", "chromadb.auth.token.TokenAuthServerProvider"]) + ) + client_provider = draw( + st.sampled_from(["token", "chromadb.auth.token.TokenAuthClientProvider"]) + ) + server_authz_provider = draw( + st.sampled_from(["chromadb.auth.authz.SimpleRBACAuthorizationProvider"]) + ) + server_credentials_provider = draw(st.sampled_from(["user_token_config"])) + # _rbac_config = draw(rbac_config()) + persistence = draw(st.booleans()) + return { + "token_transport_header": token_header, + "chroma_server_auth_credentials_file": None, + "chroma_server_auth_provider": server_provider, + "chroma_client_auth_provider": client_provider, + "chroma_server_authz_config_file": None, + "chroma_server_auth_credentials_provider": server_credentials_provider, + "chroma_server_authz_provider": server_authz_provider, + "is_persistent": persistence, + } + + +api_executors = { + "db:create_database": lambda api, mapi, aapi: ( + aapi.create_database(f"test-{uuid.uuid4()}") + ), + "db:get_database": lambda api, mapi, aapi: (aapi.get_database(DEFAULT_DATABASE),), + "tenant:create_tenant": lambda api, mapi, aapi: ( + aapi.create_tenant(f"test-{uuid.uuid4()}") + ), + "tenant:get_tenant": lambda api, mapi, aapi: (aapi.get_tenant(DEFAULT_TENANT),), + "db:reset": lambda api, mapi, _: api.reset(), + "db:list_collections": lambda api, mapi, _: api.list_collections(), + "collection:get_collection": lambda api, mapi, _: ( + # pre-condition + mcol := mapi.create_collection(f"test-get-{uuid.uuid4()}"), + api.get_collection(f"{mcol.name}"), + ), + "db:create_collection": lambda api, mapi, _: ( + api.create_collection(f"test-create-{uuid.uuid4()}"), + ), + "db:get_or_create_collection": lambda api, mapi, _: ( + api.get_or_create_collection(f"test-get-or-create-{uuid.uuid4()}") + ), + "collection:delete_collection": lambda api, mapi, _: ( + # pre-condition + mcol := mapi.create_collection(f"test-delete-col-{uuid.uuid4()}"), + api.delete_collection(f"{mcol.name}"), + ), + "collection:update_collection": lambda api, mapi, _: ( + # pre-condition + mcol := mapi.create_collection(f"test-modify-col-{uuid.uuid4()}"), + col := Collection(api, f"{mcol.name}", mcol.id), + col.modify(metadata={"test": "test"}), + ), + "collection:add": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-add-doc-{uuid.uuid4()}"), + col := Collection(api, f"{mcol.name}", mcol.id), + col.add(documents=["test"], ids=["1"]), + ), + "collection:delete": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-delete-doc-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(client=api, name=f"{mcol.name}", id=mcol.id), + col.delete(ids=["1"]), + ), + "collection:get": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-get-doc-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(api, f"{mcol.name}", mcol.id), + col.get(ids=["1"]), + ), + "collection:query": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-query-doc-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(api, f"{mcol.name}", mcol.id), + col.query(query_texts=["test"]), + ), + "collection:peek": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-peek-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(api, f"{mcol.name}", mcol.id), + col.peek(), + ), + "collection:update": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-update-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(api, f"{mcol.name}", mcol.id), + col.update(ids=["1"], documents=["test1"]), + ), + "collection:upsert": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-upsert-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(api, f"{mcol.name}", mcol.id), + col.upsert(ids=["1"], documents=["test1"]), + ), + "collection:count": lambda api, mapi, _: ( + mcol := mapi.create_collection(f"test-count-{uuid.uuid4()}"), + mcol.add(documents=["test"], ids=["1"]), + col := Collection(api, f"{mcol.name}", mcol.id), + col.count(), + ), +} + + +def master_api(_settings: Settings) -> Tuple[ServerAPI, AdminAPI]: + system = System(_settings) + api = system.instance(ServerAPI) + admin_api = AdminClient(api.get_settings()) + system.start() + return api, admin_api + + +@settings(max_examples=10) +@given(token_config=token_config(), rbac_config=rbac_config()) +def test_authz(token_config: Dict[str, Any], rbac_config: Dict[str, Any]) -> None: + authz_config = rbac_config + token_config["chroma_server_authz_config"] = rbac_config + token_config["chroma_server_auth_credentials"] = json.dumps(rbac_config["users"]) + random_user = random.choice( + [user for user in authz_config["users"] if user["id"] != "__master__"] + ) + _master_user = [ + user for user in authz_config["users"] if user["id"] == "__master__" + ][0] + random_token = random.choice(random_user["tokens"])["token"] + api = _fastapi_fixture( + is_persistent=token_config["is_persistent"], + chroma_server_auth_provider=token_config["chroma_server_auth_provider"], + chroma_server_auth_credentials_provider=token_config[ + "chroma_server_auth_credentials_provider" + ], + chroma_server_auth_credentials=token_config["chroma_server_auth_credentials"], + chroma_client_auth_provider=token_config["chroma_client_auth_provider"], + chroma_client_auth_token_transport_header=token_config[ + "token_transport_header" + ], + chroma_server_auth_token_transport_header=token_config[ + "token_transport_header" + ], + chroma_server_authz_provider=token_config["chroma_server_authz_provider"], + chroma_server_authz_config=token_config["chroma_server_authz_config"], + chroma_client_auth_credentials=random_token, + ) + _sys: System = next(api) + _sys.reset_state() + _master_settings = Settings(**dict(_sys.settings)) + _master_settings.chroma_client_auth_credentials = _master_user["tokens"][0]["token"] + _master_api, admin_api = master_api(_master_settings) + _api = _sys.instance(ServerAPI) + _api.heartbeat() + for action in authz_config["roles_mapping"][random_user["role"]]["actions"]: + print(action) + api_executors[action](_api, _master_api, admin_api) # type: ignore + for unauthorized_action in authz_config["roles_mapping"][random_user["role"]][ + "unauthorized_actions" + ]: + with pytest.raises(Exception) as ex: + api_executors[unauthorized_action]( + _api, _master_api, admin_api + ) # type: ignore + assert "Unauthorized" in str(ex) or "Forbidden" in str(ex) diff --git a/chromadb/test/auth/test_token_auth.py b/chromadb/test/auth/test_token_auth.py new file mode 100644 index 0000000000000000000000000000000000000000..50e88e296a90201f0169f39ae6342b3810f2bed1 --- /dev/null +++ b/chromadb/test/auth/test_token_auth.py @@ -0,0 +1,138 @@ +import string +from typing import Dict, Any + +import hypothesis.strategies as st +import pytest +from hypothesis import given, settings + +from chromadb.api import ServerAPI +from chromadb.config import System +from chromadb.test.conftest import _fastapi_fixture + + +@st.composite +def token_config(draw: st.DrawFn) -> Dict[str, Any]: + token_header = draw(st.sampled_from(["AUTHORIZATION", "X_CHROMA_TOKEN", None])) + server_provider = draw( + st.sampled_from(["token", "chromadb.auth.token.TokenAuthServerProvider"]) + ) + client_provider = draw( + st.sampled_from(["token", "chromadb.auth.token.TokenAuthClientProvider"]) + ) + server_credentials_provider = draw( + st.sampled_from( + ["chromadb.auth.token.TokenConfigServerAuthCredentialsProvider"] + ) + ) + token = draw( + st.text( + alphabet=string.digits + string.ascii_letters + string.punctuation, + min_size=1, + max_size=50, + ) + ) + persistence = draw(st.booleans()) + return { + "token_transport_header": token_header, + "chroma_server_auth_credentials": token, + "chroma_client_auth_credentials": token, + "chroma_server_auth_provider": server_provider, + "chroma_client_auth_provider": client_provider, + "chroma_server_auth_credentials_provider": server_credentials_provider, + "is_persistent": persistence, + } + + +@settings(max_examples=10) +@given(token_config()) +def test_fastapi_server_token_auth(token_config: Dict[str, Any]) -> None: + api = _fastapi_fixture( + is_persistent=token_config["is_persistent"], + chroma_server_auth_provider=token_config["chroma_server_auth_provider"], + chroma_server_auth_credentials_provider=token_config[ + "chroma_server_auth_credentials_provider" + ], + chroma_server_auth_credentials=token_config["chroma_server_auth_credentials"], + chroma_client_auth_provider=token_config["chroma_client_auth_provider"], + chroma_client_auth_token_transport_header=token_config[ + "token_transport_header" + ], + chroma_server_auth_token_transport_header=token_config[ + "token_transport_header" + ], + chroma_client_auth_credentials=token_config["chroma_client_auth_credentials"], + ) + _sys: System = next(api) + _sys.reset_state() + _api = _sys.instance(ServerAPI) + _api.heartbeat() + assert _api.list_collections() == [] + + +@st.composite +def random_token(draw: st.DrawFn) -> str: + return draw( + st.text(alphabet=string.ascii_letters + string.digits, min_size=1, max_size=5) + ) + + +@st.composite +def invalid_token(draw: st.DrawFn) -> str: + opposite_alphabet = set(string.printable) - set( + string.digits + string.ascii_letters + string.punctuation + ) + token = draw(st.text(alphabet=list(opposite_alphabet), min_size=1, max_size=50)) + return token + + +@settings(max_examples=10) +@given(tconf=token_config(), inval_tok=invalid_token()) +def test_invalid_token(tconf: Dict[str, Any], inval_tok: str) -> None: + api = _fastapi_fixture( + is_persistent=tconf["is_persistent"], + chroma_server_auth_provider=tconf["chroma_server_auth_provider"], + chroma_server_auth_credentials_provider=tconf[ + "chroma_server_auth_credentials_provider" + ], + chroma_server_auth_credentials=tconf["chroma_server_auth_credentials"], + chroma_server_auth_token_transport_header=tconf["token_transport_header"], + chroma_client_auth_provider=tconf["chroma_client_auth_provider"], + chroma_client_auth_token_transport_header=tconf["token_transport_header"], + chroma_client_auth_credentials=inval_tok, + ) + with pytest.raises(Exception) as e: + _sys: System = next(api) + _sys.reset_state() + _sys.instance(ServerAPI) + assert "Invalid token" in str(e) + + +@settings(max_examples=10) +@given(token_config(), random_token()) +def test_fastapi_server_token_auth_wrong_token( + token_config: Dict[str, Any], random_token: str +) -> None: + api = _fastapi_fixture( + is_persistent=token_config["is_persistent"], + chroma_server_auth_provider=token_config["chroma_server_auth_provider"], + chroma_server_auth_credentials_provider=token_config[ + "chroma_server_auth_credentials_provider" + ], + chroma_server_auth_credentials=token_config["chroma_server_auth_credentials"], + chroma_server_auth_token_transport_header=token_config[ + "token_transport_header" + ], + chroma_client_auth_provider=token_config["chroma_client_auth_provider"], + chroma_client_auth_token_transport_header=token_config[ + "token_transport_header" + ], + chroma_client_auth_credentials=token_config["chroma_client_auth_credentials"] + + random_token, + ) + _sys: System = next(api) + _sys.reset_state() + _api = _sys.instance(ServerAPI) + _api.heartbeat() + with pytest.raises(Exception) as e: + _api.list_collections() + assert "Unauthorized" in str(e) diff --git a/chromadb/test/client/test_cloud_client.py b/chromadb/test/client/test_cloud_client.py new file mode 100644 index 0000000000000000000000000000000000000000..aee869ca1c570e2e10c51e87cfd3ac2d164926ed --- /dev/null +++ b/chromadb/test/client/test_cloud_client.py @@ -0,0 +1,104 @@ +import multiprocessing +from typing import Any, Dict, Generator, Optional, Tuple +import pytest +from chromadb import CloudClient +from chromadb.api import ServerAPI +from chromadb.auth.token import TokenTransportHeader +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT, Settings, System +from chromadb.errors import AuthorizationError + +from chromadb.test.conftest import _await_server, _run_server, find_free_port + +TOKEN_TRANSPORT_HEADER = TokenTransportHeader.X_CHROMA_TOKEN.name +TEST_CLOUD_HOST = "localhost" + + +@pytest.fixture(scope="module") +def valid_token() -> str: + return "valid_token" + + +@pytest.fixture(scope="module") +def mock_cloud_server(valid_token: str) -> Generator[System, None, None]: + chroma_server_auth_provider: str = "chromadb.auth.token.TokenAuthServerProvider" + chroma_server_auth_credentials_provider: str = ( + "chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" + ) + chroma_server_auth_credentials: str = valid_token + chroma_server_auth_token_transport_header: str = TOKEN_TRANSPORT_HEADER + + port = find_free_port() + + args: Tuple[ + int, + bool, + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[Dict[str, Any]], + ] = ( + port, + False, + None, + chroma_server_auth_provider, + chroma_server_auth_credentials_provider, + None, + chroma_server_auth_credentials, + chroma_server_auth_token_transport_header, + None, + None, + None, + ) + ctx = multiprocessing.get_context("spawn") + proc = ctx.Process(target=_run_server, args=args, daemon=True) + proc.start() + + settings = Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + chroma_server_host=TEST_CLOUD_HOST, + chroma_server_http_port=str(port), + chroma_client_auth_provider="chromadb.auth.token.TokenAuthClientProvider", + chroma_client_auth_credentials=valid_token, + chroma_client_auth_token_transport_header=TOKEN_TRANSPORT_HEADER, + ) + + system = System(settings) + api = system.instance(ServerAPI) + system.start() + _await_server(api) + yield system + system.stop() + proc.kill() + + +def test_valid_key(mock_cloud_server: System, valid_token: str) -> None: + valid_client = CloudClient( + tenant=DEFAULT_TENANT, + database=DEFAULT_DATABASE, + api_key=valid_token, + cloud_host=TEST_CLOUD_HOST, + cloud_port=mock_cloud_server.settings.chroma_server_http_port, # type: ignore + enable_ssl=False, + ) + + assert valid_client.heartbeat() + + +def test_invalid_key(mock_cloud_server: System, valid_token: str) -> None: + # Try to connect to the default tenant and database with an invalid token + invalid_token = valid_token + "_invalid" + with pytest.raises(AuthorizationError): + client = CloudClient( + tenant=DEFAULT_TENANT, + database=DEFAULT_DATABASE, + api_key=invalid_token, + cloud_host=TEST_CLOUD_HOST, + cloud_port=mock_cloud_server.settings.chroma_server_http_port, # type: ignore + enable_ssl=False, + ) + client.heartbeat() diff --git a/chromadb/test/client/test_database_tenant.py b/chromadb/test/client/test_database_tenant.py new file mode 100644 index 0000000000000000000000000000000000000000..eb20265331efa9ca74cfb03b72c32b2341a85b45 --- /dev/null +++ b/chromadb/test/client/test_database_tenant.py @@ -0,0 +1,168 @@ +import pytest +from chromadb.api.client import AdminClient, Client +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT + + +def test_database_tenant_collections(client: Client) -> None: + client.reset() + # Create a new database in the default tenant + admin_client = AdminClient.from_system(client._system) + admin_client.create_database("test_db") + + # Create collections in this new database + client.set_tenant(tenant=DEFAULT_TENANT, database="test_db") + client.create_collection("collection", metadata={"database": "test_db"}) + + # Create collections in the default database + client.set_tenant(tenant=DEFAULT_TENANT, database=DEFAULT_DATABASE) + client.create_collection("collection", metadata={"database": DEFAULT_DATABASE}) + + # List collections in the default database + collections = client.list_collections() + assert len(collections) == 1 + assert collections[0].name == "collection" + assert collections[0].metadata == {"database": DEFAULT_DATABASE} + + # List collections in the new database + client.set_tenant(tenant=DEFAULT_TENANT, database="test_db") + collections = client.list_collections() + assert len(collections) == 1 + assert collections[0].metadata == {"database": "test_db"} + + # Update the metadata in both databases to different values + client.set_tenant(tenant=DEFAULT_TENANT, database=DEFAULT_DATABASE) + client.list_collections()[0].modify(metadata={"database": "default2"}) + + client.set_tenant(tenant=DEFAULT_TENANT, database="test_db") + client.list_collections()[0].modify(metadata={"database": "test_db2"}) + + # Validate that the metadata was updated + client.set_tenant(tenant=DEFAULT_TENANT, database=DEFAULT_DATABASE) + collections = client.list_collections() + assert len(collections) == 1 + assert collections[0].metadata == {"database": "default2"} + + client.set_tenant(tenant=DEFAULT_TENANT, database="test_db") + collections = client.list_collections() + assert len(collections) == 1 + assert collections[0].metadata == {"database": "test_db2"} + + # Delete the collections and make sure databases are isolated + client.set_tenant(tenant=DEFAULT_TENANT, database=DEFAULT_DATABASE) + client.delete_collection("collection") + + collections = client.list_collections() + assert len(collections) == 0 + + client.set_tenant(tenant=DEFAULT_TENANT, database="test_db") + collections = client.list_collections() + assert len(collections) == 1 + + client.delete_collection("collection") + collections = client.list_collections() + assert len(collections) == 0 + + +def test_database_collections_add(client: Client) -> None: + client.reset() + + # Create a new database in the default tenant + admin_client = AdminClient.from_system(client._system) + admin_client.create_database("test_db") + + # Create collections in this new database + client.set_database(database="test_db") + coll_new = client.create_collection("collection_new") + + # Create collections in the default database + client.set_database(database=DEFAULT_DATABASE) + coll_default = client.create_collection("collection_default") + + records_new = { + "ids": ["a", "b", "c"], + "embeddings": [[1.0, 2.0, 3.0] for _ in range(3)], + "documents": ["a", "b", "c"], + } + + records_default = { + "ids": ["c", "d", "e"], + "embeddings": [[4.0, 5.0, 6.0] for _ in range(3)], + "documents": ["c", "d", "e"], + } + + # Add to the new coll + coll_new.add(**records_new) # type: ignore + + # Add to the default coll + coll_default.add(**records_default) # type: ignore + + # Make sure the collections are isolated + res = coll_new.get(include=["embeddings", "documents"]) + assert res["ids"] == records_new["ids"] + assert res["embeddings"] == records_new["embeddings"] + assert res["documents"] == records_new["documents"] + + res = coll_default.get(include=["embeddings", "documents"]) + assert res["ids"] == records_default["ids"] + assert res["embeddings"] == records_default["embeddings"] + assert res["documents"] == records_default["documents"] + + +def test_tenant_collections_add(client: Client) -> None: + client.reset() + + # Create two databases with same name in different tenants + admin_client = AdminClient.from_system(client._system) + admin_client.create_tenant("test_tenant1") + admin_client.create_tenant("test_tenant2") + admin_client.create_database("test_db", tenant="test_tenant1") + admin_client.create_database("test_db", tenant="test_tenant2") + + # Create collections in each database with same name + client.set_tenant(tenant="test_tenant1", database="test_db") + coll_tenant1 = client.create_collection("collection") + client.set_tenant(tenant="test_tenant2", database="test_db") + coll_tenant2 = client.create_collection("collection") + + records_tenant1 = { + "ids": ["a", "b", "c"], + "embeddings": [[1.0, 2.0, 3.0] for _ in range(3)], + "documents": ["a", "b", "c"], + } + + records_tenant2 = { + "ids": ["c", "d", "e"], + "embeddings": [[4.0, 5.0, 6.0] for _ in range(3)], + "documents": ["c", "d", "e"], + } + + # Add to the tenant1 coll + coll_tenant1.add(**records_tenant1) # type: ignore + + # Add to the tenant2 coll + coll_tenant2.add(**records_tenant2) # type: ignore + + # Make sure the collections are isolated + res = coll_tenant1.get(include=["embeddings", "documents"]) + assert res["ids"] == records_tenant1["ids"] + assert res["embeddings"] == records_tenant1["embeddings"] + assert res["documents"] == records_tenant1["documents"] + + res = coll_tenant2.get(include=["embeddings", "documents"]) + assert res["ids"] == records_tenant2["ids"] + assert res["embeddings"] == records_tenant2["embeddings"] + assert res["documents"] == records_tenant2["documents"] + + +def test_min_len_name(client: Client) -> None: + client.reset() + + # Create a new database in the default tenant with a name of length 1 + # and expect an error + admin_client = AdminClient.from_system(client._system) + with pytest.raises(Exception): + admin_client.create_database("a") + + # Create a tenant with a name of length 1 and expect an error + with pytest.raises(Exception): + admin_client.create_tenant("a") diff --git a/chromadb/test/client/test_multiple_clients_concurrency.py b/chromadb/test/client/test_multiple_clients_concurrency.py new file mode 100644 index 0000000000000000000000000000000000000000..14054214cbf67bd7fa8fc8e30c1f3f06a9ee1bd0 --- /dev/null +++ b/chromadb/test/client/test_multiple_clients_concurrency.py @@ -0,0 +1,47 @@ +from concurrent.futures import ThreadPoolExecutor +from chromadb.api.client import AdminClient, Client +from chromadb.config import DEFAULT_TENANT + + +def test_multiple_clients_concurrently(client: Client) -> None: + """Tests running multiple clients, each against their own database, concurrently.""" + client.reset() + admin_client = AdminClient.from_system(client._system) + admin_client.create_database("test_db") + + CLIENT_COUNT = 50 + COLLECTION_COUNT = 10 + + # Each database will create the same collections by name, with differing metadata + databases = [f"db{i}" for i in range(CLIENT_COUNT)] + for database in databases: + admin_client.create_database(database) + + collections = [f"collection{i}" for i in range(COLLECTION_COUNT)] + + # Create N clients, each on a seperate thread, each with their own database + def run_target(n: int) -> None: + thread_client = Client( + tenant=DEFAULT_TENANT, + database=databases[n], + settings=client._system.settings, + ) + for collection in collections: + thread_client.create_collection( + collection, metadata={"database": databases[n]} + ) + + with ThreadPoolExecutor(max_workers=CLIENT_COUNT) as executor: + executor.map(run_target, range(CLIENT_COUNT)) + + # Create a final client, which will be used to verify the collections were created + client = Client(settings=client._system.settings) + + # Verify that the collections were created + for database in databases: + client.set_database(database) + seen_collections = client.list_collections() + assert len(seen_collections) == COLLECTION_COUNT + for collection in seen_collections: + assert collection.name in collections + assert collection.metadata == {"database": database} diff --git a/chromadb/test/conftest.py b/chromadb/test/conftest.py new file mode 100644 index 0000000000000000000000000000000000000000..34a1b040dd19df62df48c7274be4851a7b823f3b --- /dev/null +++ b/chromadb/test/conftest.py @@ -0,0 +1,579 @@ +import logging +import multiprocessing +import os +import shutil +import socket +import subprocess +import tempfile +import time +from typing import ( + Any, + Dict, + Generator, + Iterator, + List, + Optional, + Sequence, + Tuple, + Callable, +) + +import hypothesis +import pytest +import uvicorn +from requests.exceptions import ConnectionError +from typing_extensions import Protocol + +import chromadb.server.fastapi +from chromadb.api import ClientAPI, ServerAPI +from chromadb.config import Settings, System +from chromadb.db.mixins import embeddings_queue +from chromadb.ingest import Producer +from chromadb.types import SeqId, SubmitEmbeddingRecord +from chromadb.api.client import Client as ClientCreator + +root_logger = logging.getLogger() +root_logger.setLevel(logging.DEBUG) # This will only run when testing + +logger = logging.getLogger(__name__) + +hypothesis.settings.register_profile( + "dev", + deadline=45000, + suppress_health_check=[ + hypothesis.HealthCheck.data_too_large, + hypothesis.HealthCheck.large_base_example, + hypothesis.HealthCheck.function_scoped_fixture, + ], +) +hypothesis.settings.load_profile(os.getenv("HYPOTHESIS_PROFILE", "dev")) + +NOT_CLUSTER_ONLY = os.getenv("CHROMA_CLUSTER_TEST_ONLY") != "1" + + +def skip_if_not_cluster() -> pytest.MarkDecorator: + return pytest.mark.skipif( + NOT_CLUSTER_ONLY, + reason="Requires Kubernetes to be running with a valid config", + ) + + +def generate_self_signed_certificate() -> None: + config_path = os.path.join( + os.path.dirname(os.path.abspath(__file__)), "openssl.cnf" + ) + print(f"Config path: {config_path}") # Debug print to verify path + if not os.path.exists(config_path): + raise FileNotFoundError(f"Config file not found at {config_path}") + subprocess.run( + [ + "openssl", + "req", + "-x509", + "-newkey", + "rsa:4096", + "-keyout", + "serverkey.pem", + "-out", + "servercert.pem", + "-days", + "365", + "-nodes", + "-subj", + "/CN=localhost", + "-config", + config_path, + ] + ) + + +def find_free_port() -> int: + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + s.bind(("", 0)) + s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) + return s.getsockname()[1] # type: ignore + + +def _run_server( + port: int, + is_persistent: bool = False, + persist_directory: Optional[str] = None, + chroma_server_auth_provider: Optional[str] = None, + chroma_server_auth_credentials_provider: Optional[str] = None, + chroma_server_auth_credentials_file: Optional[str] = None, + chroma_server_auth_credentials: Optional[str] = None, + chroma_server_auth_token_transport_header: Optional[str] = None, + chroma_server_authz_provider: Optional[str] = None, + chroma_server_authz_config_file: Optional[str] = None, + chroma_server_authz_config: Optional[Dict[str, Any]] = None, + chroma_server_ssl_certfile: Optional[str] = None, + chroma_server_ssl_keyfile: Optional[str] = None, +) -> None: + """Run a Chroma server locally""" + if is_persistent and persist_directory: + settings = Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + is_persistent=is_persistent, + persist_directory=persist_directory, + allow_reset=True, + chroma_server_auth_provider=chroma_server_auth_provider, + chroma_server_auth_credentials_provider=chroma_server_auth_credentials_provider, + chroma_server_auth_credentials_file=chroma_server_auth_credentials_file, + chroma_server_auth_credentials=chroma_server_auth_credentials, + chroma_server_auth_token_transport_header=chroma_server_auth_token_transport_header, + chroma_server_authz_provider=chroma_server_authz_provider, + chroma_server_authz_config_file=chroma_server_authz_config_file, + chroma_server_authz_config=chroma_server_authz_config, + ) + else: + settings = Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + is_persistent=False, + allow_reset=True, + chroma_server_auth_provider=chroma_server_auth_provider, + chroma_server_auth_credentials_provider=chroma_server_auth_credentials_provider, + chroma_server_auth_credentials_file=chroma_server_auth_credentials_file, + chroma_server_auth_credentials=chroma_server_auth_credentials, + chroma_server_auth_token_transport_header=chroma_server_auth_token_transport_header, + chroma_server_authz_provider=chroma_server_authz_provider, + chroma_server_authz_config_file=chroma_server_authz_config_file, + chroma_server_authz_config=chroma_server_authz_config, + ) + server = chromadb.server.fastapi.FastAPI(settings) + uvicorn.run( + server.app(), + host="0.0.0.0", + port=port, + log_level="error", + timeout_keep_alive=30, + ssl_keyfile=chroma_server_ssl_keyfile, + ssl_certfile=chroma_server_ssl_certfile, + ) + + +def _await_server(api: ServerAPI, attempts: int = 0) -> None: + try: + api.heartbeat() + except ConnectionError as e: + if attempts > 15: + logger.error("Test server failed to start after 15 attempts") + raise e + else: + logger.info("Waiting for server to start...") + time.sleep(4) + _await_server(api, attempts + 1) + + +def _fastapi_fixture( + is_persistent: bool = False, + chroma_server_auth_provider: Optional[str] = None, + chroma_server_auth_credentials_provider: Optional[str] = None, + chroma_client_auth_provider: Optional[str] = None, + chroma_server_auth_credentials_file: Optional[str] = None, + chroma_client_auth_credentials: Optional[str] = None, + chroma_server_auth_credentials: Optional[str] = None, + chroma_client_auth_token_transport_header: Optional[str] = None, + chroma_server_auth_token_transport_header: Optional[str] = None, + chroma_server_authz_provider: Optional[str] = None, + chroma_server_authz_config_file: Optional[str] = None, + chroma_server_authz_config: Optional[Dict[str, Any]] = None, + chroma_server_ssl_certfile: Optional[str] = None, + chroma_server_ssl_keyfile: Optional[str] = None, +) -> Generator[System, None, None]: + """Fixture generator that launches a server in a separate process, and yields a + fastapi client connect to it""" + + port = find_free_port() + logger.info(f"Running test FastAPI server on port {port}") + ctx = multiprocessing.get_context("spawn") + args: Tuple[ + int, + bool, + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[str], + Optional[Dict[str, Any]], + Optional[str], + Optional[str], + ] = ( + port, + False, + None, + chroma_server_auth_provider, + chroma_server_auth_credentials_provider, + chroma_server_auth_credentials_file, + chroma_server_auth_credentials, + chroma_server_auth_token_transport_header, + chroma_server_authz_provider, + chroma_server_authz_config_file, + chroma_server_authz_config, + chroma_server_ssl_certfile, + chroma_server_ssl_keyfile, + ) + persist_directory = None + if is_persistent: + persist_directory = tempfile.mkdtemp() + args = ( + port, + is_persistent, + persist_directory, + chroma_server_auth_provider, + chroma_server_auth_credentials_provider, + chroma_server_auth_credentials_file, + chroma_server_auth_credentials, + chroma_server_auth_token_transport_header, + chroma_server_authz_provider, + chroma_server_authz_config_file, + chroma_server_authz_config, + chroma_server_ssl_certfile, + chroma_server_ssl_keyfile, + ) + proc = ctx.Process(target=_run_server, args=args, daemon=True) + proc.start() + settings = Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + chroma_server_host="localhost", + chroma_server_http_port=str(port), + allow_reset=True, + chroma_client_auth_provider=chroma_client_auth_provider, + chroma_client_auth_credentials=chroma_client_auth_credentials, + chroma_client_auth_token_transport_header=chroma_client_auth_token_transport_header, + chroma_server_ssl_verify=chroma_server_ssl_certfile, + chroma_server_ssl_enabled=True if chroma_server_ssl_certfile else False, + ) + system = System(settings) + api = system.instance(ServerAPI) + system.start() + _await_server(api) + yield system + system.stop() + proc.kill() + if is_persistent and persist_directory is not None: + if os.path.exists(persist_directory): + shutil.rmtree(persist_directory) + + +def fastapi() -> Generator[System, None, None]: + return _fastapi_fixture(is_persistent=False) + + +def fastapi_persistent() -> Generator[System, None, None]: + return _fastapi_fixture(is_persistent=True) + + +def fastapi_ssl() -> Generator[System, None, None]: + generate_self_signed_certificate() + return _fastapi_fixture( + is_persistent=False, + chroma_server_ssl_certfile="./servercert.pem", + chroma_server_ssl_keyfile="./serverkey.pem", + ) + + +def basic_http_client() -> Generator[System, None, None]: + settings = Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + chroma_server_http_port="8000", + allow_reset=True, + ) + system = System(settings) + api = system.instance(ServerAPI) + _await_server(api) + system.start() + yield system + system.stop() + + +def fastapi_server_basic_auth() -> Generator[System, None, None]: + server_auth_file = os.path.abspath(os.path.join(".", "server.htpasswd")) + with open(server_auth_file, "w") as f: + f.write("admin:$2y$05$e5sRb6NCcSH3YfbIxe1AGu2h5K7OOd982OXKmd8WyQ3DRQ4MvpnZS\n") + for item in _fastapi_fixture( + is_persistent=False, + chroma_server_auth_provider="chromadb.auth.basic.BasicAuthServerProvider", + chroma_server_auth_credentials_provider="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider", + chroma_server_auth_credentials_file="./server.htpasswd", + chroma_client_auth_provider="chromadb.auth.basic.BasicAuthClientProvider", + chroma_client_auth_credentials="admin:admin", + ): + yield item + os.remove(server_auth_file) + + +def fastapi_server_basic_auth_param() -> Generator[System, None, None]: + server_auth_file = os.path.abspath(os.path.join(".", "server.htpasswd")) + with open(server_auth_file, "w") as f: + f.write("admin:$2y$05$e5sRb6NCcSH3YfbIxe1AGu2h5K7OOd982OXKmd8WyQ3DRQ4MvpnZS\n") + for item in _fastapi_fixture( + is_persistent=False, + chroma_server_auth_provider="chromadb.auth.basic.BasicAuthServerProvider", + chroma_server_auth_credentials_provider="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider", + chroma_server_auth_credentials_file="./server.htpasswd", + chroma_client_auth_provider="chromadb.auth.basic.BasicAuthClientProvider", + chroma_client_auth_credentials="admin:admin", + ): + yield item + os.remove(server_auth_file) + + +# TODO we need a generator for auth providers +def fastapi_server_basic_auth_file() -> Generator[System, None, None]: + server_auth_file = os.path.abspath(os.path.join(".", "server.htpasswd")) + with open(server_auth_file, "w") as f: + f.write("admin:$2y$05$e5sRb6NCcSH3YfbIxe1AGu2h5K7OOd982OXKmd8WyQ3DRQ4MvpnZS\n") + for item in _fastapi_fixture( + is_persistent=False, + chroma_server_auth_provider="chromadb.auth.basic.BasicAuthServerProvider", + chroma_server_auth_credentials_provider="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider", + chroma_server_auth_credentials_file="./server.htpasswd", + chroma_client_auth_provider="chromadb.auth.basic.BasicAuthClientProvider", + chroma_client_auth_credentials="admin:admin", + ): + yield item + os.remove(server_auth_file) + + +def fastapi_server_basic_auth_shorthand() -> Generator[System, None, None]: + server_auth_file = os.path.abspath(os.path.join(".", "server.htpasswd")) + with open(server_auth_file, "w") as f: + f.write("admin:$2y$05$e5sRb6NCcSH3YfbIxe1AGu2h5K7OOd982OXKmd8WyQ3DRQ4MvpnZS\n") + for item in _fastapi_fixture( + is_persistent=False, + chroma_server_auth_provider="basic", + chroma_server_auth_credentials_provider="htpasswd_file", + chroma_server_auth_credentials_file="./server.htpasswd", + chroma_client_auth_provider="basic", + chroma_client_auth_credentials="admin:admin", + ): + yield item + os.remove(server_auth_file) + + +def fastapi_server_basic_auth_invalid_cred() -> Generator[System, None, None]: + server_auth_file = os.path.abspath(os.path.join(".", "server.htpasswd")) + with open(server_auth_file, "w") as f: + f.write("admin:$2y$05$e5sRb6NCcSH3YfbIxe1AGu2h5K7OOd982OXKmd8WyQ3DRQ4MvpnZS\n") + for item in _fastapi_fixture( + is_persistent=False, + chroma_server_auth_provider="chromadb.auth.basic.BasicAuthServerProvider", + chroma_server_auth_credentials_provider="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider", + chroma_server_auth_credentials_file="./server.htpasswd", + chroma_client_auth_provider="chromadb.auth.basic.BasicAuthClientProvider", + chroma_client_auth_credentials="admin:admin1", + ): + yield item + os.remove(server_auth_file) + + +def integration() -> Generator[System, None, None]: + """Fixture generator for returning a client configured via environmenet + variables, intended for externally configured integration tests + """ + settings = Settings(allow_reset=True) + system = System(settings) + system.start() + yield system + system.stop() + + +def sqlite() -> Generator[System, None, None]: + """Fixture generator for segment-based API using in-memory Sqlite""" + settings = Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + is_persistent=False, + allow_reset=True, + ) + system = System(settings) + system.start() + yield system + system.stop() + + +def sqlite_persistent() -> Generator[System, None, None]: + """Fixture generator for segment-based API using persistent Sqlite""" + save_path = tempfile.mkdtemp() + settings = Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + allow_reset=True, + is_persistent=True, + persist_directory=save_path, + ) + system = System(settings) + system.start() + yield system + system.stop() + if os.path.exists(save_path): + shutil.rmtree(save_path) + + +def system_fixtures() -> List[Callable[[], Generator[System, None, None]]]: + fixtures = [fastapi, fastapi_persistent, sqlite, sqlite_persistent] + if "CHROMA_INTEGRATION_TEST" in os.environ: + fixtures.append(integration) + if "CHROMA_INTEGRATION_TEST_ONLY" in os.environ: + fixtures = [integration] + if "CHROMA_CLUSTER_TEST_ONLY" in os.environ: + fixtures = [basic_http_client] + return fixtures + + +def system_fixtures_auth() -> List[Callable[[], Generator[System, None, None]]]: + fixtures = [ + fastapi_server_basic_auth_param, + fastapi_server_basic_auth_file, + fastapi_server_basic_auth_shorthand, + ] + return fixtures + + +def system_fixtures_wrong_auth() -> List[Callable[[], Generator[System, None, None]]]: + fixtures = [fastapi_server_basic_auth_invalid_cred] + return fixtures + + +def system_fixtures_ssl() -> List[Callable[[], Generator[System, None, None]]]: + fixtures = [fastapi_ssl] + return fixtures + + +@pytest.fixture(scope="module", params=system_fixtures_wrong_auth()) +def system_wrong_auth( + request: pytest.FixtureRequest, +) -> Generator[ServerAPI, None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="module", params=system_fixtures()) +def system(request: pytest.FixtureRequest) -> Generator[ServerAPI, None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="module", params=system_fixtures_ssl()) +def system_ssl(request: pytest.FixtureRequest) -> Generator[ServerAPI, None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="module", params=system_fixtures_auth()) +def system_auth(request: pytest.FixtureRequest) -> Generator[ServerAPI, None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="function") +def api(system: System) -> Generator[ServerAPI, None, None]: + system.reset_state() + api = system.instance(ServerAPI) + yield api + + +@pytest.fixture(scope="function") +def client(system: System) -> Generator[ClientAPI, None, None]: + system.reset_state() + client = ClientCreator.from_system(system) + yield client + client.clear_system_cache() + + +@pytest.fixture(scope="function") +def client_ssl(system_ssl: System) -> Generator[ClientAPI, None, None]: + system_ssl.reset_state() + client = ClientCreator.from_system(system_ssl) + yield client + client.clear_system_cache() + + +@pytest.fixture(scope="function") +def api_wrong_cred( + system_wrong_auth: System, +) -> Generator[ServerAPI, None, None]: + system_wrong_auth.reset_state() + api = system_wrong_auth.instance(ServerAPI) + yield api + + +@pytest.fixture(scope="function") +def api_with_server_auth(system_auth: System) -> Generator[ServerAPI, None, None]: + _sys = system_auth + _sys.reset_state() + api = _sys.instance(ServerAPI) + yield api + + +# Producer / Consumer fixtures # + + +class ProducerFn(Protocol): + def __call__( + self, + producer: Producer, + topic: str, + embeddings: Iterator[SubmitEmbeddingRecord], + n: int, + ) -> Tuple[Sequence[SubmitEmbeddingRecord], Sequence[SeqId]]: + ... + + +def produce_n_single( + producer: Producer, + topic: str, + embeddings: Iterator[SubmitEmbeddingRecord], + n: int, +) -> Tuple[Sequence[SubmitEmbeddingRecord], Sequence[SeqId]]: + submitted_embeddings = [] + seq_ids = [] + for _ in range(n): + e = next(embeddings) + seq_id = producer.submit_embedding(topic, e) + submitted_embeddings.append(e) + seq_ids.append(seq_id) + return submitted_embeddings, seq_ids + + +def produce_n_batch( + producer: Producer, + topic: str, + embeddings: Iterator[SubmitEmbeddingRecord], + n: int, +) -> Tuple[Sequence[SubmitEmbeddingRecord], Sequence[SeqId]]: + submitted_embeddings = [] + seq_ids: Sequence[SeqId] = [] + for _ in range(n): + e = next(embeddings) + submitted_embeddings.append(e) + seq_ids = producer.submit_embeddings(topic, submitted_embeddings) + return submitted_embeddings, seq_ids + + +def produce_fn_fixtures() -> List[ProducerFn]: + return [produce_n_single, produce_n_batch] + + +@pytest.fixture(scope="module", params=produce_fn_fixtures()) +def produce_fns( + request: pytest.FixtureRequest, +) -> Generator[ProducerFn, None, None]: + yield request.param + + +def pytest_configure(config): # type: ignore + embeddings_queue._called_from_test = True diff --git a/chromadb/test/data_loader/test_data_loader.py b/chromadb/test/data_loader/test_data_loader.py new file mode 100644 index 0000000000000000000000000000000000000000..e63e6d1574ce01936f4cecf03c90858b4d0fed6d --- /dev/null +++ b/chromadb/test/data_loader/test_data_loader.py @@ -0,0 +1,119 @@ +from typing import Dict, Generator, List, Optional, Sequence, Union +import numpy as np +from numpy.typing import NDArray + +import pytest +import chromadb +from chromadb.api.types import URI, DataLoader, Documents, IDs, Image, URIs +from chromadb.api import ServerAPI +from chromadb.test.ef.test_multimodal_ef import hashing_multimodal_ef + + +def encode_data(data: str) -> NDArray[np.uint8]: + return np.array(data.encode()) + + +class DefaultDataLoader(DataLoader[List[Optional[Image]]]): + def __call__(self, uris: Sequence[Optional[URI]]) -> List[Optional[Image]]: + # Convert each URI to a numpy array + return [None if uri is None else encode_data(uri) for uri in uris] + + +def record_set_with_uris(n: int = 3) -> Dict[str, Union[IDs, Documents, URIs]]: + return { + "ids": [f"{i}" for i in range(n)], + "documents": [f"document_{i}" for i in range(n)], + "uris": [f"uri_{i}" for i in range(n)], + } + + +@pytest.fixture() +def collection_with_data_loader( + api: ServerAPI, +) -> Generator[chromadb.Collection, None, None]: + collection = api.create_collection( + name="collection_with_data_loader", + data_loader=DefaultDataLoader(), + embedding_function=hashing_multimodal_ef(), + ) + yield collection + api.delete_collection(collection.name) + + +@pytest.fixture +def collection_without_data_loader( + api: ServerAPI, +) -> Generator[chromadb.Collection, None, None]: + collection = api.create_collection( + name="collection_without_data_loader", + embedding_function=hashing_multimodal_ef(), + ) + yield collection + api.delete_collection(collection.name) + + +def test_without_data_loader( + collection_without_data_loader: chromadb.Collection, + n_examples: int = 3, +) -> None: + record_set = record_set_with_uris(n=n_examples) + + # Can't embed data in URIs without a data loader + with pytest.raises(ValueError): + collection_without_data_loader.add( + ids=record_set["ids"], + uris=record_set["uris"], + ) + + # Can't get data from URIs without a data loader + with pytest.raises(ValueError): + collection_without_data_loader.get(include=["data"]) + + +def test_without_uris( + collection_with_data_loader: chromadb.Collection, n_examples: int = 3 +) -> None: + record_set = record_set_with_uris(n=n_examples) + + collection_with_data_loader.add( + ids=record_set["ids"], + documents=record_set["documents"], + ) + + get_result = collection_with_data_loader.get(include=["data"]) + + assert get_result["data"] is not None + for data in get_result["data"]: + assert data is None + + +def test_data_loader( + collection_with_data_loader: chromadb.Collection, n_examples: int = 3 +) -> None: + record_set = record_set_with_uris(n=n_examples) + + collection_with_data_loader.add( + ids=record_set["ids"], + uris=record_set["uris"], + ) + + # Get with "data" + get_result = collection_with_data_loader.get(include=["data"]) + + assert get_result["data"] is not None + for i, data in enumerate(get_result["data"]): + assert data is not None + assert data == encode_data(record_set["uris"][i]) + + # Query by URI + query_result = collection_with_data_loader.query( + query_uris=record_set["uris"], + n_results=len(record_set["uris"][0]), + include=["data", "uris"], + ) + + assert query_result["data"] is not None + for i, data in enumerate(query_result["data"][0]): + assert data is not None + assert query_result["uris"] is not None + assert data == encode_data(query_result["uris"][0][i]) diff --git a/chromadb/test/db/migrations/00001-migration-1.psql.sql b/chromadb/test/db/migrations/00001-migration-1.psql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a214bae8d5b0d6482fedd18265d4dfc756d47485 --- /dev/null +++ b/chromadb/test/db/migrations/00001-migration-1.psql.sql @@ -0,0 +1,3 @@ +CREATE TABLE table1 ( + name TEXT PRIMARY KEY +); diff --git a/chromadb/test/db/migrations/00001-migration-1.sqlite.sql b/chromadb/test/db/migrations/00001-migration-1.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..a214bae8d5b0d6482fedd18265d4dfc756d47485 --- /dev/null +++ b/chromadb/test/db/migrations/00001-migration-1.sqlite.sql @@ -0,0 +1,3 @@ +CREATE TABLE table1 ( + name TEXT PRIMARY KEY +); diff --git a/chromadb/test/db/migrations/00002-migration-2.psql.sql b/chromadb/test/db/migrations/00002-migration-2.psql.sql new file mode 100644 index 0000000000000000000000000000000000000000..01e4b222af541efb9022d2eeb69e39239faecb34 --- /dev/null +++ b/chromadb/test/db/migrations/00002-migration-2.psql.sql @@ -0,0 +1,3 @@ +CREATE TABLE table2 ( + name TEXT PRIMARY KEY +); diff --git a/chromadb/test/db/migrations/00002-migration-2.sqlite.sql b/chromadb/test/db/migrations/00002-migration-2.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..01e4b222af541efb9022d2eeb69e39239faecb34 --- /dev/null +++ b/chromadb/test/db/migrations/00002-migration-2.sqlite.sql @@ -0,0 +1,3 @@ +CREATE TABLE table2 ( + name TEXT PRIMARY KEY +); diff --git a/chromadb/test/db/migrations/00003-migration-3.psql.sql b/chromadb/test/db/migrations/00003-migration-3.psql.sql new file mode 100644 index 0000000000000000000000000000000000000000..93de09997b36fd1a09fb72ac1270b3433ede5cd9 --- /dev/null +++ b/chromadb/test/db/migrations/00003-migration-3.psql.sql @@ -0,0 +1,3 @@ +CREATE TABLE table3 ( + name TEXT PRIMARY KEY +); diff --git a/chromadb/test/db/migrations/00003-migration-3.sqlite.sql b/chromadb/test/db/migrations/00003-migration-3.sqlite.sql new file mode 100644 index 0000000000000000000000000000000000000000..93de09997b36fd1a09fb72ac1270b3433ede5cd9 --- /dev/null +++ b/chromadb/test/db/migrations/00003-migration-3.sqlite.sql @@ -0,0 +1,3 @@ +CREATE TABLE table3 ( + name TEXT PRIMARY KEY +); diff --git a/chromadb/test/db/migrations/__init__.py b/chromadb/test/db/migrations/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/chromadb/test/db/test_base.py b/chromadb/test/db/test_base.py new file mode 100644 index 0000000000000000000000000000000000000000..8bfaa1f733a08ef4a2f6ccee69dc44739ff8021c --- /dev/null +++ b/chromadb/test/db/test_base.py @@ -0,0 +1,42 @@ +from chromadb.db.base import ParameterValue, get_sql +import pypika + + +def test_value_params_default() -> None: + t = pypika.Table("foo") + + original_query = ( + pypika.Query.from_(t) + .select(t.a, t.b) + .where(t.a == pypika.Parameter("?")) + .where(t.b == pypika.Parameter("?")) + ) + + value_based_query = ( + pypika.Query.from_(t) + .select(t.a, t.b) + .where(t.a == ParameterValue(42)) + .where(t.b == ParameterValue(43)) + ) + sql, values = get_sql(value_based_query) + assert sql == original_query.get_sql() + assert values == (42, 43) + + +def test_value_params_numeric() -> None: + t = pypika.Table("foo") + original_query = ( + pypika.Query.from_(t) + .select(t.a, t.b) + .where(t.a == pypika.NumericParameter(1)) + .where(t.b == pypika.NumericParameter(2)) + ) + value_based_query = ( + pypika.Query.from_(t) + .select(t.a, t.b) + .where(t.a == ParameterValue(42)) + .where(t.b == ParameterValue(43)) + ) + sql, values = get_sql(value_based_query, formatstr=":{}") + assert sql == original_query.get_sql() + assert values == (42, 43) diff --git a/chromadb/test/db/test_hash.py b/chromadb/test/db/test_hash.py new file mode 100644 index 0000000000000000000000000000000000000000..6f09d30e0cb36e7d5773bc59f52107d9e55420b9 --- /dev/null +++ b/chromadb/test/db/test_hash.py @@ -0,0 +1,117 @@ +import os +import pytest +from unittest.mock import patch, MagicMock + +import chromadb +from chromadb.db.impl.sqlite import SqliteDB +from chromadb.config import System, Settings + + +@pytest.mark.parametrize("migrations_hash_algorithm", [None, "md5", "sha256"]) +@patch("chromadb.api.fastapi.FastAPI") +@patch.dict(os.environ, {}, clear=True) +def test_settings_valid_hash_algorithm( + api_mock: MagicMock, migrations_hash_algorithm: str +) -> None: + """ + Ensure that when no hash algorithm or a valid one is provided, the client is set up + with that value + """ + if migrations_hash_algorithm: + settings = chromadb.config.Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + is_persistent=True, + persist_directory="./foo", + migrations_hash_algorithm=migrations_hash_algorithm, + ) + else: + settings = chromadb.config.Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + is_persistent=True, + persist_directory="./foo", + ) + + client = chromadb.Client(settings) + + # Check that the mock was called + assert api_mock.called + + # Retrieve the arguments with which the mock was called + # `call_args` returns a tuple, where the first element is a tuple of positional arguments + # and the second element is a dictionary of keyword arguments. We assume here that + # the settings object is passed as a positional argument. + args, kwargs = api_mock.call_args + passed_settings = args[0] if args else None + + # Check if the default hash algorith was set + expected_migrations_hash_algorithm = migrations_hash_algorithm or "md5" + assert passed_settings + assert ( + getattr(passed_settings.settings, "migrations_hash_algorithm", None) + == expected_migrations_hash_algorithm + ) + client.clear_system_cache() + + +@patch("chromadb.api.fastapi.FastAPI") +@patch.dict(os.environ, {}, clear=True) +def test_settings_invalid_hash_algorithm(mock: MagicMock) -> None: + """ + Ensure that providing an invalid hash results in a raised exception and the client + is not called + """ + with pytest.raises(Exception): + settings = chromadb.config.Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + migrations_hash_algorithm="invalid_hash_alg", + persist_directory="./foo", + ) + + chromadb.Client(settings) + + assert not mock.called + + +@pytest.mark.parametrize("migrations_hash_algorithm", ["md5", "sha256"]) +@patch("chromadb.db.migrations.verify_migration_sequence") +@patch("chromadb.db.migrations.hashlib") +@patch.dict(os.environ, {}, clear=True) +def test_hashlib_alg(hashlib_mock: MagicMock, verify_migration_sequence_mock: MagicMock, migrations_hash_algorithm: str) -> None: + """ + Test that only the appropriate hashlib functions are called + """ + db = SqliteDB( + System( + Settings( + migrations="apply", + allow_reset=True, + migrations_hash_algorithm=migrations_hash_algorithm, + ) + ) + ) + + # replace the real migration application call with a mock we can check + db.apply_migration = MagicMock() # type: ignore [method-assign] + + # we don't want `verify_migration_sequence` to actually run since a) we're not testing that functionality and + # b) db may be cached between tests, and we're changing the algorithm, so it may fail. + # Instead, return a fake unapplied migration (expect `apply_migration` to be called after) + verify_migration_sequence_mock.return_value = ["unapplied_migration"] + + db.start() + + assert db.apply_migration.called + + # Check if the default hash algorith was set + expected_migrations_hash_algorithm = migrations_hash_algorithm or "md5" + + # check that the right algorithm was used + if expected_migrations_hash_algorithm == "md5": + assert hashlib_mock.md5.called + assert not hashlib_mock.sha256.called + elif expected_migrations_hash_algorithm == "sha256": + assert not hashlib_mock.md5.called + assert hashlib_mock.sha256.called + else: + # we only support the algorithms above + assert False diff --git a/chromadb/test/db/test_migrations.py b/chromadb/test/db/test_migrations.py new file mode 100644 index 0000000000000000000000000000000000000000..96df89bebb77252892d4520b5d5d5b287d5baaa2 --- /dev/null +++ b/chromadb/test/db/test_migrations.py @@ -0,0 +1,164 @@ +import pytest +from importlib_resources import files +from typing import Generator, List, Callable +import chromadb.db.migrations as migrations +from chromadb.db.impl.sqlite import SqliteDB +from chromadb.config import System, Settings +from pytest import FixtureRequest +import copy + + +def sqlite() -> Generator[migrations.MigratableDB, None, None]: + """Fixture generator for sqlite DB""" + db = SqliteDB( + System( + Settings( + migrations="none", + allow_reset=True, + ) + ) + ) + db.start() + yield db + + +def db_fixtures() -> List[Callable[[], Generator[migrations.MigratableDB, None, None]]]: + return [sqlite] + + +@pytest.fixture(scope="module", params=db_fixtures()) +def db(request: FixtureRequest) -> Generator[migrations.MigratableDB, None, None]: + yield next(request.param()) + + +# Some Database impls improperly swallow exceptions, test that the wrapper works +def test_exception_propagation(db: migrations.MigratableDB) -> None: + with pytest.raises(Exception): + with db.tx(): + raise (Exception("test exception")) + + +def test_setup_migrations(db: migrations.MigratableDB) -> None: + db.reset_state() + db.setup_migrations() + db.setup_migrations() # idempotent + + with db.tx() as cursor: + rows = cursor.execute("SELECT * FROM migrations").fetchall() + assert len(rows) == 0 + + +def test_migrations(db: migrations.MigratableDB) -> None: + db.initialize_migrations() + + dir = files("chromadb.test.db.migrations") + db_migrations = db.db_migrations(dir) + source_migrations = migrations.find_migrations(dir, db.migration_scope()) + + unapplied_migrations = migrations.verify_migration_sequence( + db_migrations, source_migrations + ) + + assert unapplied_migrations == source_migrations + + with db.tx() as cur: + rows = cur.execute("SELECT * FROM migrations").fetchall() + assert len(rows) == 0 + + with db.tx() as cur: + for m in unapplied_migrations[:-1]: + db.apply_migration(cur, m) + + db_migrations = db.db_migrations(dir) + unapplied_migrations = migrations.verify_migration_sequence( + db_migrations, source_migrations + ) + + assert len(unapplied_migrations) == 1 + assert unapplied_migrations[0]["version"] == 3 + + with db.tx() as cur: + assert len(cur.execute("SELECT * FROM migrations").fetchall()) == 2 + assert len(cur.execute("SELECT * FROM table1").fetchall()) == 0 + assert len(cur.execute("SELECT * FROM table2").fetchall()) == 0 + with pytest.raises(Exception): + cur.execute("SELECT * FROM table3").fetchall() + + with db.tx() as cur: + for m in unapplied_migrations: + db.apply_migration(cur, m) + + db_migrations = db.db_migrations(dir) + unapplied_migrations = migrations.verify_migration_sequence( + db_migrations, source_migrations + ) + + assert len(unapplied_migrations) == 0 + + with db.tx() as cur: + assert len(cur.execute("SELECT * FROM migrations").fetchall()) == 3 + assert len(cur.execute("SELECT * FROM table3").fetchall()) == 0 + + +def test_tampered_migration(db: migrations.MigratableDB) -> None: + db.reset_state() + + db.setup_migrations() + + dir = files("chromadb.test.db.migrations") + source_migrations = migrations.find_migrations(dir, db.migration_scope()) + + db_migrations = db.db_migrations(dir) + + unapplied_migrations = migrations.verify_migration_sequence( + db_migrations, source_migrations + ) + + with db.tx() as cur: + for m in unapplied_migrations: + db.apply_migration(cur, m) + + db_migrations = db.db_migrations(dir) + unapplied_migrations = migrations.verify_migration_sequence( + db_migrations, source_migrations + ) + assert len(unapplied_migrations) == 0 + + inconsistent_version_migrations = copy.deepcopy(source_migrations) + inconsistent_version_migrations[0]["version"] = 2 + + with pytest.raises(migrations.InconsistentVersionError): + migrations.verify_migration_sequence( + db_migrations, inconsistent_version_migrations + ) + + inconsistent_hash_migrations = copy.deepcopy(source_migrations) + inconsistent_hash_migrations[0]["hash"] = "badhash" + + with pytest.raises(migrations.InconsistentHashError): + migrations.verify_migration_sequence( + db_migrations, inconsistent_hash_migrations + ) + + +def test_initialization( + monkeypatch: pytest.MonkeyPatch, db: migrations.MigratableDB +) -> None: + db.reset_state() + dir = files("chromadb.test.db.migrations") + monkeypatch.setattr(db, "migration_dirs", lambda: [dir]) + + assert not db.migrations_initialized() + + with pytest.raises(migrations.UninitializedMigrationsError): + db.validate_migrations() + + db.setup_migrations() + + assert db.migrations_initialized() + + with pytest.raises(migrations.UnappliedMigrationsError): + db.validate_migrations() + + db.apply_migrations() + db.validate_migrations() diff --git a/chromadb/test/db/test_system.py b/chromadb/test/db/test_system.py new file mode 100644 index 0000000000000000000000000000000000000000..3cd2a9954ec92f8a8c695bd822e7e149b3eeabe1 --- /dev/null +++ b/chromadb/test/db/test_system.py @@ -0,0 +1,784 @@ +import os +import shutil +import tempfile +import pytest +from typing import Generator, List, Callable, Dict, Union + +from chromadb.db.impl.grpc.client import GrpcSysDB +from chromadb.db.impl.grpc.server import GrpcMockSysDB +from chromadb.types import Collection, Segment, SegmentScope +from chromadb.db.impl.sqlite import SqliteDB +from chromadb.config import ( + DEFAULT_DATABASE, + DEFAULT_TENANT, + Component, + System, + Settings, +) +from chromadb.db.system import SysDB +from chromadb.db.base import NotFoundError, UniqueConstraintError +from pytest import FixtureRequest +import uuid + +PULSAR_TENANT = "default" +PULSAR_NAMESPACE = "default" + +# These are the sample collections that are used in the tests below. Tests can override +# the fields as needed. + +# HACK: In order to get the real grpc tests passing, we need the topic to use rendezvous +# hashing. This is because the grpc tests use the real grpc sysdb server and the +# rendezvous hashing is done in the segment server. We don't have a easy way to parameterize +# the assignment policy in the grpc tests, so we just use rendezvous hashing for all tests. +# by harcoding the topic to what we expect rendezvous hashing to return with 16 topics. +sample_collections = [ + Collection( + id=uuid.UUID(int=1), + name="test_collection_1", + topic=f"persistent://{PULSAR_TENANT}/{PULSAR_NAMESPACE}/chroma_log_1", + metadata={"test_str": "str1", "test_int": 1, "test_float": 1.3}, + dimension=128, + database=DEFAULT_DATABASE, + tenant=DEFAULT_TENANT, + ), + Collection( + id=uuid.UUID(int=2), + name="test_collection_2", + topic=f"persistent://{PULSAR_TENANT}/{PULSAR_NAMESPACE}/chroma_log_14", + metadata={"test_str": "str2", "test_int": 2, "test_float": 2.3}, + dimension=None, + database=DEFAULT_DATABASE, + tenant=DEFAULT_TENANT, + ), + Collection( + id=uuid.UUID(int=3), + name="test_collection_3", + topic=f"persistent://{PULSAR_TENANT}/{PULSAR_NAMESPACE}/chroma_log_14", + metadata={"test_str": "str3", "test_int": 3, "test_float": 3.3}, + dimension=None, + database=DEFAULT_DATABASE, + tenant=DEFAULT_TENANT, + ), +] + + +class MockAssignmentPolicy(Component): + def assign_collection(self, collection_id: uuid.UUID) -> str: + for collection in sample_collections: + if collection["id"] == collection_id: + return collection["topic"] + raise ValueError(f"Unknown collection ID: {collection_id}") + + +def sqlite() -> Generator[SysDB, None, None]: + """Fixture generator for sqlite DB""" + db = SqliteDB( + System( + Settings( + allow_reset=True, + chroma_collection_assignment_policy_impl="chromadb.test.db.test_system.MockAssignmentPolicy", + ) + ) + ) + db.start() + yield db + db.stop() + + +def sqlite_persistent() -> Generator[SysDB, None, None]: + """Fixture generator for sqlite DB""" + save_path = tempfile.mkdtemp() + db = SqliteDB( + System( + Settings( + allow_reset=True, + is_persistent=True, + persist_directory=save_path, + chroma_collection_assignment_policy_impl="chromadb.test.db.test_system.MockAssignmentPolicy", + ) + ) + ) + db.start() + yield db + db.stop() + if os.path.exists(save_path): + shutil.rmtree(save_path) + + +def grpc_with_mock_server() -> Generator[SysDB, None, None]: + """Fixture generator for sqlite DB that creates a mock grpc sysdb server + and a grpc client that connects to it.""" + system = System( + Settings( + allow_reset=True, + chroma_collection_assignment_policy_impl="chromadb.test.db.test_system.MockAssignmentPolicy", + chroma_server_grpc_port=50051, + ) + ) + system.instance(GrpcMockSysDB) + client = system.instance(GrpcSysDB) + system.start() + client.reset_and_wait_for_ready() + yield client + + +def grpc_with_real_server() -> Generator[SysDB, None, None]: + system = System( + Settings( + allow_reset=True, + chroma_collection_assignment_policy_impl="chromadb.test.db.test_system.MockAssignmentPolicy", + ) + ) + client = system.instance(GrpcSysDB) + system.start() + client.reset_and_wait_for_ready() + yield client + + +def db_fixtures() -> List[Callable[[], Generator[SysDB, None, None]]]: + if "CHROMA_CLUSTER_TEST_ONLY" in os.environ: + return [grpc_with_real_server] + else: + return [sqlite, sqlite_persistent, grpc_with_mock_server] + + +@pytest.fixture(scope="module", params=db_fixtures()) +def sysdb(request: FixtureRequest) -> Generator[SysDB, None, None]: + yield next(request.param()) + + +# region Collection tests +def test_create_get_delete_collections(sysdb: SysDB) -> None: + sysdb.reset_state() + + for collection in sample_collections: + sysdb.create_collection( + id=collection["id"], + name=collection["name"], + metadata=collection["metadata"], + dimension=collection["dimension"], + ) + collection["database"] = DEFAULT_DATABASE + collection["tenant"] = DEFAULT_TENANT + + results = sysdb.get_collections() + results = sorted(results, key=lambda c: c["name"]) + + assert sorted(results, key=lambda c: c["name"]) == sample_collections + + # Duplicate create fails + with pytest.raises(UniqueConstraintError): + sysdb.create_collection( + name=sample_collections[0]["name"], id=sample_collections[0]["id"] + ) + + # Find by name + for collection in sample_collections: + result = sysdb.get_collections(name=collection["name"]) + assert result == [collection] + + # Find by topic + for collection in sample_collections: + result = sysdb.get_collections(topic=collection["topic"]) + assert collection in result + + # Find by id + for collection in sample_collections: + result = sysdb.get_collections(id=collection["id"]) + assert result == [collection] + + # Find by id and topic (positive case) + for collection in sample_collections: + result = sysdb.get_collections(id=collection["id"], topic=collection["topic"]) + assert result == [collection] + + # find by id and topic (negative case) + for collection in sample_collections: + result = sysdb.get_collections(id=collection["id"], topic="other_topic") + assert result == [] + + # Delete + c1 = sample_collections[0] + sysdb.delete_collection(c1["id"]) + + results = sysdb.get_collections() + assert c1 not in results + assert len(results) == len(sample_collections) - 1 + assert sorted(results, key=lambda c: c["name"]) == sample_collections[1:] + + by_id_result = sysdb.get_collections(id=c1["id"]) + assert by_id_result == [] + + # Duplicate delete throws an exception + with pytest.raises(NotFoundError): + sysdb.delete_collection(c1["id"]) + + +def test_update_collections(sysdb: SysDB) -> None: + coll = Collection( + name=sample_collections[0]["name"], + id=sample_collections[0]["id"], + topic=sample_collections[0]["topic"], + metadata=sample_collections[0]["metadata"], + dimension=sample_collections[0]["dimension"], + database=DEFAULT_DATABASE, + tenant=DEFAULT_TENANT, + ) + + sysdb.reset_state() + + sysdb.create_collection( + id=coll["id"], + name=coll["name"], + metadata=coll["metadata"], + dimension=coll["dimension"], + ) + + # Update name + coll["name"] = "new_name" + sysdb.update_collection(coll["id"], name=coll["name"]) + result = sysdb.get_collections(name=coll["name"]) + assert result == [coll] + + # Update topic + coll["topic"] = "new_topic" + sysdb.update_collection(coll["id"], topic=coll["topic"]) + result = sysdb.get_collections(topic=coll["topic"]) + assert result == [coll] + + # Update dimension + coll["dimension"] = 128 + sysdb.update_collection(coll["id"], dimension=coll["dimension"]) + result = sysdb.get_collections(id=coll["id"]) + assert result == [coll] + + # Reset the metadata + coll["metadata"] = {"test_str2": "str2"} + sysdb.update_collection(coll["id"], metadata=coll["metadata"]) + result = sysdb.get_collections(id=coll["id"]) + assert result == [coll] + + # Delete all metadata keys + coll["metadata"] = None + sysdb.update_collection(coll["id"], metadata=None) + result = sysdb.get_collections(id=coll["id"]) + assert result == [coll] + + +def test_get_or_create_collection(sysdb: SysDB) -> None: + sysdb.reset_state() + + # get_or_create = True returns existing collection + collection = sample_collections[0] + + sysdb.create_collection( + id=collection["id"], + name=collection["name"], + metadata=collection["metadata"], + dimension=collection["dimension"], + ) + + result, created = sysdb.create_collection( + name=collection["name"], + id=uuid.uuid4(), + get_or_create=True, + metadata=collection["metadata"], + ) + assert result == collection + + # Only one collection with the same name exists + get_result = sysdb.get_collections(name=collection["name"]) + assert get_result == [collection] + + # get_or_create = True creates new collection + result, created = sysdb.create_collection( + name=sample_collections[1]["name"], + id=sample_collections[1]["id"], + get_or_create=True, + metadata=sample_collections[1]["metadata"], + ) + assert result == sample_collections[1] + + # get_or_create = False creates new collection + result, created = sysdb.create_collection( + name=sample_collections[2]["name"], + id=sample_collections[2]["id"], + get_or_create=False, + metadata=sample_collections[2]["metadata"], + ) + assert result == sample_collections[2] + + # get_or_create = False fails if collection already exists + with pytest.raises(UniqueConstraintError): + sysdb.create_collection( + name=sample_collections[2]["name"], + id=sample_collections[2]["id"], + get_or_create=False, + metadata=collection["metadata"], + ) + + # get_or_create = True overwrites metadata + overlayed_metadata: Dict[str, Union[str, int, float]] = { + "test_new_str": "new_str", + "test_int": 1, + } + result, created = sysdb.create_collection( + name=sample_collections[2]["name"], + id=sample_collections[2]["id"], + get_or_create=True, + metadata=overlayed_metadata, + ) + + assert result["metadata"] == overlayed_metadata + + # get_or_create = False with None metadata does not overwrite metadata + result, created = sysdb.create_collection( + name=sample_collections[2]["name"], + id=sample_collections[2]["id"], + get_or_create=True, + metadata=None, + ) + assert result["metadata"] == overlayed_metadata + + +def test_create_get_delete_database_and_collection(sysdb: SysDB) -> None: + sysdb.reset_state() + + # Create a new database + sysdb.create_database(id=uuid.uuid4(), name="new_database") + + # Create a new collection in the new database + sysdb.create_collection( + id=sample_collections[0]["id"], + name=sample_collections[0]["name"], + metadata=sample_collections[0]["metadata"], + dimension=sample_collections[0]["dimension"], + database="new_database", + ) + + # Create a new collection with the same id but different name in the new database + # and expect an error + with pytest.raises(UniqueConstraintError): + sysdb.create_collection( + id=sample_collections[0]["id"], + name="new_name", + metadata=sample_collections[0]["metadata"], + dimension=sample_collections[0]["dimension"], + database="new_database", + get_or_create=False, + ) + + # Create a new collection in the default database + sysdb.create_collection( + id=sample_collections[1]["id"], + name=sample_collections[1]["name"], + metadata=sample_collections[1]["metadata"], + dimension=sample_collections[1]["dimension"], + ) + + # Check that the new database and collections exist + result = sysdb.get_collections( + name=sample_collections[0]["name"], database="new_database" + ) + assert len(result) == 1 + sample_collections[0]["database"] = "new_database" + assert result[0] == sample_collections[0] + + # Check that the collection in the default database exists + result = sysdb.get_collections(name=sample_collections[1]["name"]) + assert len(result) == 1 + assert result[0] == sample_collections[1] + + # Get for a database that doesn't exist with a name that exists in the new database and expect no results + assert ( + len( + sysdb.get_collections( + name=sample_collections[0]["name"], database="fake_db" + ) + ) + == 0 + ) + + # Delete the collection in the new database + sysdb.delete_collection(id=sample_collections[0]["id"], database="new_database") + + # Check that the collection in the new database was deleted + result = sysdb.get_collections(database="new_database") + assert len(result) == 0 + + # Check that the collection in the default database still exists + result = sysdb.get_collections(name=sample_collections[1]["name"]) + assert len(result) == 1 + assert result[0] == sample_collections[1] + + # Delete the deleted collection in the default database and expect an error + with pytest.raises(NotFoundError): + sysdb.delete_collection(id=sample_collections[0]["id"]) + + # Delete the existing collection in the new database and expect an error + with pytest.raises(NotFoundError): + sysdb.delete_collection(id=sample_collections[1]["id"], database="new_database") + + +def test_create_update_with_database(sysdb: SysDB) -> None: + sysdb.reset_state() + + # Create a new database + sysdb.create_database(id=uuid.uuid4(), name="new_database") + + # Create a new collection in the new database + sysdb.create_collection( + id=sample_collections[0]["id"], + name=sample_collections[0]["name"], + metadata=sample_collections[0]["metadata"], + dimension=sample_collections[0]["dimension"], + database="new_database", + ) + + # Create a new collection in the default database + sysdb.create_collection( + id=sample_collections[1]["id"], + name=sample_collections[1]["name"], + metadata=sample_collections[1]["metadata"], + dimension=sample_collections[1]["dimension"], + ) + + # Update the collection in the default database + sysdb.update_collection( + id=sample_collections[1]["id"], + name="new_name_1", + ) + + # Check that the collection in the default database was updated + result = sysdb.get_collections(id=sample_collections[1]["id"]) + assert len(result) == 1 + assert result[0]["name"] == "new_name_1" + + # Update the collection in the new database + sysdb.update_collection( + id=sample_collections[0]["id"], + name="new_name_0", + ) + + # Check that the collection in the new database was updated + result = sysdb.get_collections( + id=sample_collections[0]["id"], database="new_database" + ) + assert len(result) == 1 + assert result[0]["name"] == "new_name_0" + + # Try to create the collection in the default database in the new database and expect an error + with pytest.raises(UniqueConstraintError): + sysdb.create_collection( + id=sample_collections[1]["id"], + name=sample_collections[1]["name"], + metadata=sample_collections[1]["metadata"], + dimension=sample_collections[1]["dimension"], + database="new_database", + ) + + +def test_get_multiple_with_database(sysdb: SysDB) -> None: + sysdb.reset_state() + + # Create a new database + sysdb.create_database(id=uuid.uuid4(), name="new_database") + + # Create sample collections in the new database + for collection in sample_collections: + sysdb.create_collection( + id=collection["id"], + name=collection["name"], + metadata=collection["metadata"], + dimension=collection["dimension"], + database="new_database", + ) + collection["database"] = "new_database" + + # Get all collections in the new database + result = sysdb.get_collections(database="new_database") + assert len(result) == len(sample_collections) + assert sorted(result, key=lambda c: c["name"]) == sample_collections + + # Get all collections in the default database + result = sysdb.get_collections() + assert len(result) == 0 + + +def test_create_database_with_tenants(sysdb: SysDB) -> None: + sysdb.reset_state() + + # Create a new tenant + sysdb.create_tenant(name="tenant1") + + # Create tenant that already exits and expect an error + with pytest.raises(UniqueConstraintError): + sysdb.create_tenant(name="tenant1") + + with pytest.raises(UniqueConstraintError): + sysdb.create_tenant(name=DEFAULT_TENANT) + + # Create a new database within this tenant and also in the default tenant + sysdb.create_database(id=uuid.uuid4(), name="new_database", tenant="tenant1") + sysdb.create_database(id=uuid.uuid4(), name="new_database") + + # Create a new collection in the new tenant + sysdb.create_collection( + id=sample_collections[0]["id"], + name=sample_collections[0]["name"], + metadata=sample_collections[0]["metadata"], + dimension=sample_collections[0]["dimension"], + database="new_database", + tenant="tenant1", + ) + sample_collections[0]["tenant"] = "tenant1" + sample_collections[0]["database"] = "new_database" + + # Create a new collection in the default tenant + sysdb.create_collection( + id=sample_collections[1]["id"], + name=sample_collections[1]["name"], + metadata=sample_collections[1]["metadata"], + dimension=sample_collections[1]["dimension"], + database="new_database", + ) + + sample_collections[1]["database"] = "new_database" + + # Check that both tenants have the correct collections + result = sysdb.get_collections(database="new_database", tenant="tenant1") + assert len(result) == 1 + assert result[0] == sample_collections[0] + + result = sysdb.get_collections(database="new_database") + assert len(result) == 1 + assert result[0] == sample_collections[1] + + # Creating a collection id that already exists in a tenant that does not have it + # should error + with pytest.raises(UniqueConstraintError): + sysdb.create_collection( + id=sample_collections[0]["id"], + name=sample_collections[0]["name"], + metadata=sample_collections[0]["metadata"], + dimension=sample_collections[0]["dimension"], + database="new_database", + ) + + with pytest.raises(UniqueConstraintError): + sysdb.create_collection( + id=sample_collections[1]["id"], + name=sample_collections[1]["name"], + metadata=sample_collections[1]["metadata"], + dimension=sample_collections[1]["dimension"], + database="new_database", + tenant="tenant1", + ) + + # A new tenant DOES NOT have a default database. This does not error, instead 0 + # results are returned + result = sysdb.get_collections(database=DEFAULT_DATABASE, tenant="tenant1") + assert len(result) == 0 + + +def test_get_database_with_tenants(sysdb: SysDB) -> None: + sysdb.reset_state() + + # Create a new tenant + sysdb.create_tenant(name="tenant1") + + # Get the tenant and check that it exists + result = sysdb.get_tenant(name="tenant1") + assert result["name"] == "tenant1" + + # Get a tenant that does not exist and expect an error + with pytest.raises(NotFoundError): + sysdb.get_tenant(name="tenant2") + + # Create a new database within this tenant + sysdb.create_database(id=uuid.uuid4(), name="new_database", tenant="tenant1") + + # Get the database and check that it exists + result = sysdb.get_database(name="new_database", tenant="tenant1") + assert result["name"] == "new_database" + assert result["tenant"] == "tenant1" + + # Get a database that does not exist in a tenant that does exist and expect an error + with pytest.raises(NotFoundError): + sysdb.get_database(name="new_database1", tenant="tenant1") + + # Get a database that does not exist in a tenant that does not exist and expect an + # error + with pytest.raises(NotFoundError): + sysdb.get_database(name="new_database1", tenant="tenant2") + + +# endregion + +# region Segment tests +sample_segments = [ + Segment( + id=uuid.UUID("00000000-d7d7-413b-92e1-731098a6e492"), + type="test_type_a", + scope=SegmentScope.VECTOR, + topic=None, + collection=sample_collections[0]["id"], + metadata={"test_str": "str1", "test_int": 1, "test_float": 1.3}, + ), + Segment( + id=uuid.UUID("11111111-d7d7-413b-92e1-731098a6e492"), + type="test_type_b", + topic="test_topic_2", + scope=SegmentScope.VECTOR, + collection=sample_collections[1]["id"], + metadata={"test_str": "str2", "test_int": 2, "test_float": 2.3}, + ), + Segment( + id=uuid.UUID("22222222-d7d7-413b-92e1-731098a6e492"), + type="test_type_b", + topic="test_topic_3", + scope=SegmentScope.METADATA, + collection=None, + metadata={"test_str": "str3", "test_int": 3, "test_float": 3.3}, + ), +] + + +def test_create_get_delete_segments(sysdb: SysDB) -> None: + sysdb.reset_state() + + for collection in sample_collections: + sysdb.create_collection( + id=collection["id"], + name=collection["name"], + metadata=collection["metadata"], + dimension=collection["dimension"], + ) + + for segment in sample_segments: + sysdb.create_segment(segment) + + results = sysdb.get_segments() + results = sorted(results, key=lambda c: c["id"]) + + assert results == sample_segments + + # Duplicate create fails + with pytest.raises(UniqueConstraintError): + sysdb.create_segment(sample_segments[0]) + + # Find by id + for segment in sample_segments: + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Find by type + result = sysdb.get_segments(type="test_type_a") + assert result == sample_segments[:1] + + result = sysdb.get_segments(type="test_type_b") + assert sorted(result, key=lambda c: c["id"]) == sample_segments[1:] + + # Find by collection ID + result = sysdb.get_segments(collection=sample_collections[0]["id"]) + assert result == sample_segments[:1] + + # Find by type and collection ID (positive case) + result = sysdb.get_segments( + type="test_type_a", collection=sample_collections[0]["id"] + ) + assert result == sample_segments[:1] + + # Find by type and collection ID (negative case) + result = sysdb.get_segments( + type="test_type_b", collection=sample_collections[0]["id"] + ) + assert result == [] + + # Delete + s1 = sample_segments[0] + sysdb.delete_segment(s1["id"]) + + results = sysdb.get_segments() + assert s1 not in results + assert len(results) == len(sample_segments) - 1 + assert sorted(results, key=lambda c: c["id"]) == sample_segments[1:] + + # Duplicate delete throws an exception + with pytest.raises(NotFoundError): + sysdb.delete_segment(s1["id"]) + + +def test_update_segment(sysdb: SysDB) -> None: + metadata: Dict[str, Union[str, int, float]] = { + "test_str": "str1", + "test_int": 1, + "test_float": 1.3, + } + segment = Segment( + id=uuid.uuid4(), + type="test_type_a", + scope=SegmentScope.VECTOR, + topic="test_topic_a", + collection=sample_collections[0]["id"], + metadata=metadata + ) + + sysdb.reset_state() + for c in sample_collections: + sysdb.create_collection( + id=c["id"], name=c["name"], metadata=c["metadata"], dimension=c["dimension"] + ) + + sysdb.create_segment(segment) + + # Update topic to new value + segment["topic"] = "new_topic" + sysdb.update_segment(segment["id"], topic=segment["topic"]) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Update topic to None + segment["topic"] = None + sysdb.update_segment(segment["id"], topic=segment["topic"]) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Update collection to new value + segment["collection"] = sample_collections[1]["id"] + sysdb.update_segment(segment["id"], collection=segment["collection"]) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Update collection to None + segment["collection"] = None + sysdb.update_segment(segment["id"], collection=segment["collection"]) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Add a new metadata key + metadata["test_str2"] = "str2" + sysdb.update_segment(segment["id"], metadata={"test_str2": "str2"}) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Update a metadata key + metadata["test_str"] = "str3" + sysdb.update_segment(segment["id"], metadata={"test_str": "str3"}) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Delete a metadata key + del metadata["test_str"] + sysdb.update_segment(segment["id"], metadata={"test_str": None}) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + # Delete all metadata keys + segment["metadata"] = None + sysdb.update_segment(segment["id"], metadata=None) + result = sysdb.get_segments(id=segment["id"]) + assert result == [segment] + + +# endregion diff --git a/chromadb/test/ef/test_default_ef.py b/chromadb/test/ef/test_default_ef.py new file mode 100644 index 0000000000000000000000000000000000000000..6d8fb623698a624483ed8066232e93d81a7eee76 --- /dev/null +++ b/chromadb/test/ef/test_default_ef.py @@ -0,0 +1,90 @@ +import shutil +import os +from typing import List, Hashable + +import hypothesis.strategies as st +import onnxruntime +import pytest +from hypothesis import given, settings + +from chromadb.utils.embedding_functions import ONNXMiniLM_L6_V2, _verify_sha256 + + +def unique_by(x: Hashable) -> Hashable: + return x + + +@settings(deadline=None) +@given( + providers=st.lists( + st.sampled_from(onnxruntime.get_all_providers()).filter( + lambda x: x not in onnxruntime.get_available_providers() + ), + unique_by=unique_by, + min_size=1, + ) +) +def test_unavailable_provider_multiple(providers: List[str]) -> None: + with pytest.raises(ValueError) as e: + ef = ONNXMiniLM_L6_V2(preferred_providers=providers) + ef(["test"]) + assert "Preferred providers must be subset of available providers" in str(e.value) + + +@given( + providers=st.lists( + st.sampled_from(onnxruntime.get_all_providers()).filter( + lambda x: x in onnxruntime.get_available_providers() + ), + min_size=1, + unique_by=unique_by, + ) +) +def test_available_provider(providers: List[str]) -> None: + ef = ONNXMiniLM_L6_V2(preferred_providers=providers) + ef(["test"]) + + +def test_warning_no_providers_supplied() -> None: + ef = ONNXMiniLM_L6_V2() + ef(["test"]) + + +@given( + providers=st.lists( + st.sampled_from(onnxruntime.get_all_providers()).filter( + lambda x: x in onnxruntime.get_available_providers() + ), + min_size=1, + ).filter(lambda x: len(x) > len(set(x))) +) +def test_provider_repeating(providers: List[str]) -> None: + with pytest.raises(ValueError) as e: + ef = ONNXMiniLM_L6_V2(preferred_providers=providers) + ef(["test"]) + assert "Preferred providers must be unique" in str(e.value) + + +def test_invalid_sha256() -> None: + ef = ONNXMiniLM_L6_V2() + shutil.rmtree(ef.DOWNLOAD_PATH) # clean up any existing models + with pytest.raises(ValueError) as e: + ef._MODEL_SHA256 = "invalid" + ef(["test"]) + assert "does not match expected SHA256 hash" in str(e.value) + + +def test_partial_download() -> None: + ef = ONNXMiniLM_L6_V2() + shutil.rmtree(ef.DOWNLOAD_PATH, ignore_errors=True) # clean up any existing models + os.makedirs(ef.DOWNLOAD_PATH, exist_ok=True) + path = os.path.join(ef.DOWNLOAD_PATH, ef.ARCHIVE_FILENAME) + with open(path, "wb") as f: # create invalid file to simulate partial download + f.write(b"invalid") + ef._download_model_if_not_exists() # re-download model + assert os.path.exists(path) + assert _verify_sha256( + str(os.path.join(ef.DOWNLOAD_PATH, ef.ARCHIVE_FILENAME)), + ef._MODEL_SHA256, + ) + assert len(ef(["test"])) == 1 diff --git a/chromadb/test/ef/test_multimodal_ef.py b/chromadb/test/ef/test_multimodal_ef.py new file mode 100644 index 0000000000000000000000000000000000000000..82f66fea33e566a7efd4c46566327d2fb0c63993 --- /dev/null +++ b/chromadb/test/ef/test_multimodal_ef.py @@ -0,0 +1,157 @@ +from typing import Generator, cast +import numpy as np +import pytest +import chromadb +from chromadb.api.types import ( + Embeddable, + EmbeddingFunction, + Embeddings, + Image, + Document, +) +from chromadb.test.property.strategies import hashing_embedding_function +from chromadb.test.property.invariants import _exact_distances + + +# A 'standard' multimodal embedding function, which converts inputs to strings +# then hashes them to a fixed dimension. +class hashing_multimodal_ef(EmbeddingFunction[Embeddable]): + def __init__(self) -> None: + self._hef = hashing_embedding_function(dim=10, dtype=np.float_) + + def __call__(self, input: Embeddable) -> Embeddings: + to_texts = [str(i) for i in input] + embeddings = np.array(self._hef(to_texts)) + # Normalize the embeddings + # This is so we can generate random unit vectors and have them be close to the embeddings + embeddings /= np.linalg.norm(embeddings, axis=1, keepdims=True) + return cast(Embeddings, embeddings.tolist()) + + +def random_image() -> Image: + return np.random.randint(0, 255, size=(10, 10, 3), dtype=np.int32) + + +def random_document() -> Document: + return str(random_image()) + + +@pytest.fixture +def multimodal_collection( + default_ef: EmbeddingFunction[Embeddable] = hashing_multimodal_ef(), +) -> Generator[chromadb.Collection, None, None]: + client = chromadb.Client() + collection = client.create_collection( + name="multimodal_collection", embedding_function=default_ef + ) + yield collection + client.clear_system_cache() + + +# Test adding and querying of a multimodal collection consisting of images and documents +def test_multimodal( + multimodal_collection: chromadb.Collection, + default_ef: EmbeddingFunction[Embeddable] = hashing_multimodal_ef(), + n_examples: int = 10, + n_query_results: int = 3, +) -> None: + # Fix numpy's random seed for reproducibility + random_state = np.random.get_state() + np.random.seed(0) + + image_ids = [str(i) for i in range(n_examples)] + images = [random_image() for _ in range(n_examples)] + image_embeddings = default_ef(images) + + document_ids = [str(i) for i in range(n_examples, 2 * n_examples)] + documents = [random_document() for _ in range(n_examples)] + document_embeddings = default_ef(documents) + + # Trying to add a document and an image at the same time should fail + with pytest.raises( + ValueError, match="You can only provide documents or images, not both." + ): + multimodal_collection.add( + ids=image_ids[0], documents=documents[0], images=images[0] + ) + + # Add some documents + multimodal_collection.add(ids=document_ids, documents=documents) + # Add some images + multimodal_collection.add(ids=image_ids, images=images) + + # get() should return all the documents and images + # ids corresponding to images should not have documents + get_result = multimodal_collection.get(include=["documents"]) + assert len(get_result["ids"]) == len(document_ids) + len(image_ids) + for i, id in enumerate(get_result["ids"]): + assert id in document_ids or id in image_ids + assert get_result["documents"] is not None + if id in document_ids: + assert get_result["documents"][i] == documents[document_ids.index(id)] + if id in image_ids: + assert get_result["documents"][i] is None + + # Generate a random query image + query_image = random_image() + query_image_embedding = default_ef([query_image]) + + image_neighbor_indices, _ = _exact_distances( + query_image_embedding, image_embeddings + document_embeddings + ) + # Get the ids of the nearest neighbors + nearest_image_neighbor_ids = [ + image_ids[i] if i < n_examples else document_ids[i % n_examples] + for i in image_neighbor_indices[0][:n_query_results] + ] + + # Generate a random query document + query_document = random_document() + query_document_embedding = default_ef([query_document]) + document_neighbor_indices, _ = _exact_distances( + query_document_embedding, image_embeddings + document_embeddings + ) + nearest_document_neighbor_ids = [ + image_ids[i] if i < n_examples else document_ids[i % n_examples] + for i in document_neighbor_indices[0][:n_query_results] + ] + + # Querying with both images and documents should fail + with pytest.raises(ValueError): + multimodal_collection.query( + query_images=[query_image], query_texts=[query_document] + ) + + # Query with images + query_result = multimodal_collection.query( + query_images=[query_image], n_results=n_query_results, include=["documents"] + ) + + assert query_result["ids"][0] == nearest_image_neighbor_ids + + # Query with documents + query_result = multimodal_collection.query( + query_texts=[query_document], n_results=n_query_results, include=["documents"] + ) + + assert query_result["ids"][0] == nearest_document_neighbor_ids + np.random.set_state(random_state) + + +@pytest.mark.xfail +def test_multimodal_update_with_image( + multimodal_collection: chromadb.Collection, +) -> None: + # Updating an entry with an existing document should remove the documentß + + document = random_document() + image = random_image() + id = "0" + + multimodal_collection.add(ids=id, documents=document) + + multimodal_collection.update(ids=id, images=image) + + get_result = multimodal_collection.get(ids=id, include=["documents"]) + assert get_result["documents"] is not None + assert get_result["documents"][0] is None diff --git a/chromadb/test/ingest/test_producer_consumer.py b/chromadb/test/ingest/test_producer_consumer.py new file mode 100644 index 0000000000000000000000000000000000000000..199afde60de35ee10c0a727611f2879b0d86e8bb --- /dev/null +++ b/chromadb/test/ingest/test_producer_consumer.py @@ -0,0 +1,404 @@ +import asyncio +import os +import shutil +import tempfile +import pytest +from itertools import count +from typing import ( + Generator, + List, + Callable, + Optional, + Dict, + Union, + Iterator, + Sequence, + Tuple, +) +from chromadb.ingest import Producer, Consumer +from chromadb.db.impl.sqlite import SqliteDB +from chromadb.ingest.impl.utils import create_topic_name +from chromadb.test.conftest import ProducerFn +from chromadb.types import ( + SubmitEmbeddingRecord, + Operation, + EmbeddingRecord, + ScalarEncoding, +) +from chromadb.config import System, Settings +from pytest import FixtureRequest, approx +from asyncio import Event, wait_for, TimeoutError +import uuid + + +def sqlite() -> Generator[Tuple[Producer, Consumer], None, None]: + """Fixture generator for sqlite Producer + Consumer""" + system = System(Settings(allow_reset=True)) + db = system.require(SqliteDB) + system.start() + yield db, db + system.stop() + + +def sqlite_persistent() -> Generator[Tuple[Producer, Consumer], None, None]: + """Fixture generator for sqlite_persistent Producer + Consumer""" + save_path = tempfile.mkdtemp() + system = System( + Settings(allow_reset=True, is_persistent=True, persist_directory=save_path) + ) + db = system.require(SqliteDB) + system.start() + yield db, db + system.stop() + if os.path.exists(save_path): + shutil.rmtree(save_path) + + +def pulsar() -> Generator[Tuple[Producer, Consumer], None, None]: + """Fixture generator for pulsar Producer + Consumer. This fixture requires a running + pulsar cluster. You can use bin/cluster-test.sh to start a standalone pulsar and run this test. + Assumes pulsar_broker_url etc is set from the environment variables like PULSAR_BROKER_URL. + """ + system = System( + Settings( + allow_reset=True, + chroma_producer_impl="chromadb.ingest.impl.pulsar.PulsarProducer", + chroma_consumer_impl="chromadb.ingest.impl.pulsar.PulsarConsumer", + ) + ) + producer = system.require(Producer) + consumer = system.require(Consumer) + system.start() + yield producer, consumer + system.stop() + + +def fixtures() -> List[Callable[[], Generator[Tuple[Producer, Consumer], None, None]]]: + fixtures = [sqlite, sqlite_persistent] + if "CHROMA_CLUSTER_TEST_ONLY" in os.environ: + fixtures = [pulsar] + + return fixtures + + +@pytest.fixture(scope="module", params=fixtures()) +def producer_consumer( + request: FixtureRequest, +) -> Generator[Tuple[Producer, Consumer], None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="module") +def sample_embeddings() -> Iterator[SubmitEmbeddingRecord]: + def create_record(i: int) -> SubmitEmbeddingRecord: + vector = [i + i * 0.1, i + 1 + i * 0.1] + metadata: Optional[Dict[str, Union[str, int, float]]] + if i % 2 == 0: + metadata = None + else: + metadata = {"str_key": f"value_{i}", "int_key": i, "float_key": i + i * 0.1} + + record = SubmitEmbeddingRecord( + id=f"embedding_{i}", + embedding=vector, + encoding=ScalarEncoding.FLOAT32, + metadata=metadata, + operation=Operation.ADD, + collection_id=uuid.uuid4(), + ) + return record + + return (create_record(i) for i in count()) + + +class CapturingConsumeFn: + embeddings: List[EmbeddingRecord] + waiters: List[Tuple[int, Event]] + + def __init__(self) -> None: + """A function that captures embeddings and allows you to wait for a certain + number of embeddings to be available. It must be constructed in the thread with + the main event loop + """ + self.embeddings = [] + self.waiters = [] + self._loop = asyncio.get_event_loop() + + def __call__(self, embeddings: Sequence[EmbeddingRecord]) -> None: + self.embeddings.extend(embeddings) + for n, event in self.waiters: + if len(self.embeddings) >= n: + # event.set() is not thread safe, so we need to call it in the main event loop + self._loop.call_soon_threadsafe(event.set) + + async def get(self, n: int, timeout_secs: int = 10) -> Sequence[EmbeddingRecord]: + "Wait until at least N embeddings are available, then return all embeddings" + if len(self.embeddings) >= n: + return self.embeddings[:n] + else: + event = Event() + self.waiters.append((n, event)) + # timeout so we don't hang forever on failure + await wait_for(event.wait(), timeout_secs) + return self.embeddings[:n] + + +def assert_approx_equal(a: Sequence[float], b: Sequence[float]) -> None: + for i, j in zip(a, b): + assert approx(i) == approx(j) + + +def assert_records_match( + inserted_records: Sequence[SubmitEmbeddingRecord], + consumed_records: Sequence[EmbeddingRecord], +) -> None: + """Given a list of inserted and consumed records, make sure they match""" + assert len(consumed_records) == len(inserted_records) + for inserted, consumed in zip(inserted_records, consumed_records): + assert inserted["id"] == consumed["id"] + assert inserted["operation"] == consumed["operation"] + assert inserted["encoding"] == consumed["encoding"] + assert inserted["metadata"] == consumed["metadata"] + + if inserted["embedding"] is not None: + assert consumed["embedding"] is not None + assert_approx_equal(inserted["embedding"], consumed["embedding"]) + + +def full_topic_name(topic_name: str) -> str: + return create_topic_name("default", "default", topic_name) + + +@pytest.mark.asyncio +async def test_backfill( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name = full_topic_name("test_topic") + producer.create_topic(topic_name) + embeddings = produce_fns(producer, topic_name, sample_embeddings, 3)[0] + + consume_fn = CapturingConsumeFn() + consumer.subscribe(topic_name, consume_fn, start=consumer.min_seqid()) + + recieved = await consume_fn.get(3) + assert_records_match(embeddings, recieved) + + +@pytest.mark.asyncio +async def test_notifications( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name = full_topic_name("test_topic") + + producer.create_topic(topic_name) + + embeddings: List[SubmitEmbeddingRecord] = [] + + consume_fn = CapturingConsumeFn() + + consumer.subscribe(topic_name, consume_fn, start=consumer.min_seqid()) + + for i in range(10): + e = next(sample_embeddings) + embeddings.append(e) + producer.submit_embedding(topic_name, e) + received = await consume_fn.get(i + 1) + assert_records_match(embeddings, received) + + +@pytest.mark.asyncio +async def test_multiple_topics( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name_1 = full_topic_name("test_topic_1") + topic_name_2 = full_topic_name("test_topic_2") + producer.create_topic(topic_name_1) + producer.create_topic(topic_name_2) + + embeddings_1: List[SubmitEmbeddingRecord] = [] + embeddings_2: List[SubmitEmbeddingRecord] = [] + + consume_fn_1 = CapturingConsumeFn() + consume_fn_2 = CapturingConsumeFn() + + consumer.subscribe(topic_name_1, consume_fn_1, start=consumer.min_seqid()) + consumer.subscribe(topic_name_2, consume_fn_2, start=consumer.min_seqid()) + + for i in range(10): + e_1 = next(sample_embeddings) + embeddings_1.append(e_1) + producer.submit_embedding(topic_name_1, e_1) + results_2 = await consume_fn_1.get(i + 1) + assert_records_match(embeddings_1, results_2) + + e_2 = next(sample_embeddings) + embeddings_2.append(e_2) + producer.submit_embedding(topic_name_2, e_2) + results_2 = await consume_fn_2.get(i + 1) + assert_records_match(embeddings_2, results_2) + + +@pytest.mark.asyncio +async def test_start_seq_id( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name = full_topic_name("test_topic") + producer.create_topic(topic_name) + + consume_fn_1 = CapturingConsumeFn() + consume_fn_2 = CapturingConsumeFn() + + consumer.subscribe(topic_name, consume_fn_1, start=consumer.min_seqid()) + + embeddings = produce_fns(producer, topic_name, sample_embeddings, 5)[0] + + results_1 = await consume_fn_1.get(5) + assert_records_match(embeddings, results_1) + + start = consume_fn_1.embeddings[-1]["seq_id"] + consumer.subscribe(topic_name, consume_fn_2, start=start) + second_embeddings = produce_fns(producer, topic_name, sample_embeddings, 5)[0] + assert isinstance(embeddings, list) + embeddings.extend(second_embeddings) + results_2 = await consume_fn_2.get(5) + assert_records_match(embeddings[-5:], results_2) + + +@pytest.mark.asyncio +async def test_end_seq_id( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name = full_topic_name("test_topic") + producer.create_topic(topic_name) + + consume_fn_1 = CapturingConsumeFn() + consume_fn_2 = CapturingConsumeFn() + + consumer.subscribe(topic_name, consume_fn_1, start=consumer.min_seqid()) + + embeddings = produce_fns(producer, topic_name, sample_embeddings, 10)[0] + + results_1 = await consume_fn_1.get(10) + assert_records_match(embeddings, results_1) + + end = consume_fn_1.embeddings[-5]["seq_id"] + consumer.subscribe(topic_name, consume_fn_2, start=consumer.min_seqid(), end=end) + + results_2 = await consume_fn_2.get(6) + assert_records_match(embeddings[:6], results_2) + + # Should never produce a 7th + with pytest.raises(TimeoutError): + _ = await wait_for(consume_fn_2.get(7), timeout=1) + + +@pytest.mark.asyncio +async def test_submit_batch( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name = full_topic_name("test_topic") + + embeddings = [next(sample_embeddings) for _ in range(100)] + + producer.create_topic(topic_name) + producer.submit_embeddings(topic_name, embeddings=embeddings) + + consume_fn = CapturingConsumeFn() + consumer.subscribe(topic_name, consume_fn, start=consumer.min_seqid()) + + recieved = await consume_fn.get(100) + assert_records_match(embeddings, recieved) + + +@pytest.mark.asyncio +async def test_multiple_topics_batch( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + + N_TOPICS = 2 + consume_fns = [CapturingConsumeFn() for _ in range(N_TOPICS)] + for i in range(N_TOPICS): + producer.create_topic(full_topic_name(f"test_topic_{i}")) + consumer.subscribe( + full_topic_name(f"test_topic_{i}"), + consume_fns[i], + start=consumer.min_seqid(), + ) + + embeddings_n: List[List[SubmitEmbeddingRecord]] = [[] for _ in range(N_TOPICS)] + + PRODUCE_BATCH_SIZE = 10 + N_TO_PRODUCE = 100 + total_produced = 0 + for i in range(N_TO_PRODUCE // PRODUCE_BATCH_SIZE): + for n in range(N_TOPICS): + embeddings_n[n].extend( + produce_fns( + producer, + full_topic_name(f"test_topic_{n}"), + sample_embeddings, + PRODUCE_BATCH_SIZE, + )[0] + ) + recieved = await consume_fns[n].get(total_produced + PRODUCE_BATCH_SIZE) + assert_records_match(embeddings_n[n], recieved) + total_produced += PRODUCE_BATCH_SIZE + + +@pytest.mark.asyncio +async def test_max_batch_size( + producer_consumer: Tuple[Producer, Consumer], + sample_embeddings: Iterator[SubmitEmbeddingRecord], +) -> None: + producer, consumer = producer_consumer + producer.reset_state() + consumer.reset_state() + topic_name = full_topic_name("test_topic") + max_batch_size = producer.max_batch_size + assert max_batch_size > 0 + + # Make sure that we can produce a batch of size max_batch_size + embeddings = [next(sample_embeddings) for _ in range(max_batch_size)] + consume_fn = CapturingConsumeFn() + consumer.subscribe(topic_name, consume_fn, start=consumer.min_seqid()) + producer.submit_embeddings(topic_name, embeddings=embeddings) + received = await consume_fn.get(max_batch_size, timeout_secs=120) + assert_records_match(embeddings, received) + + embeddings = [next(sample_embeddings) for _ in range(max_batch_size + 1)] + # Make sure that we can't produce a batch of size > max_batch_size + with pytest.raises(ValueError) as e: + producer.submit_embeddings(topic_name, embeddings=embeddings) + assert "Cannot submit more than" in str(e.value) diff --git a/chromadb/test/openssl.cnf b/chromadb/test/openssl.cnf new file mode 100644 index 0000000000000000000000000000000000000000..11704076bd471db52b6fca450d38cd1ad346581c --- /dev/null +++ b/chromadb/test/openssl.cnf @@ -0,0 +1,12 @@ +[req] +distinguished_name = req_distinguished_name +x509_extensions = usr_cert + +[req_distinguished_name] +CN = localhost + +[usr_cert] +subjectAltName = @alt_names + +[alt_names] +DNS.1 = localhost \ No newline at end of file diff --git a/chromadb/test/property/invariants.py b/chromadb/test/property/invariants.py new file mode 100644 index 0000000000000000000000000000000000000000..803cac2ac0756ae34c3db39d28c39c810f1fe8e7 --- /dev/null +++ b/chromadb/test/property/invariants.py @@ -0,0 +1,294 @@ +import math +from chromadb.test.property.strategies import NormalizedRecordSet, RecordSet +from typing import Callable, Optional, Tuple, Union, List, TypeVar, cast +from typing_extensions import Literal +import numpy as np +import numpy.typing as npt +from chromadb.api import types +from chromadb.api.models.Collection import Collection +from hypothesis import note +from hypothesis.errors import InvalidArgument + +from chromadb.utils import distance_functions + +T = TypeVar("T") + + +def wrap(value: Union[T, List[T]]) -> List[T]: + """Wrap a value in a list if it is not a list""" + if value is None: + raise InvalidArgument("value cannot be None") + elif isinstance(value, List): + return value + else: + return [value] + + +def wrap_all(record_set: RecordSet) -> NormalizedRecordSet: + """Ensure that an embedding set has lists for all its values""" + + embedding_list: Optional[types.Embeddings] + if record_set["embeddings"] is None: + embedding_list = None + elif isinstance(record_set["embeddings"], list): + assert record_set["embeddings"] is not None + if len(record_set["embeddings"]) > 0 and not all( + isinstance(embedding, list) for embedding in record_set["embeddings"] + ): + if all(isinstance(e, (int, float)) for e in record_set["embeddings"]): + embedding_list = cast(types.Embeddings, [record_set["embeddings"]]) + else: + raise InvalidArgument("an embedding must be a list of floats or ints") + else: + embedding_list = cast(types.Embeddings, record_set["embeddings"]) + else: + raise InvalidArgument( + "embeddings must be a list of lists, a list of numbers, or None" + ) + + return { + "ids": wrap(record_set["ids"]), + "documents": wrap(record_set["documents"]) + if record_set["documents"] is not None + else None, + "metadatas": wrap(record_set["metadatas"]) + if record_set["metadatas"] is not None + else None, + "embeddings": embedding_list, + } + + +def count(collection: Collection, record_set: RecordSet) -> None: + """The given collection count is equal to the number of embeddings""" + count = collection.count() + normalized_record_set = wrap_all(record_set) + assert count == len(normalized_record_set["ids"]) + + +def _field_matches( + collection: Collection, + normalized_record_set: NormalizedRecordSet, + field_name: Union[ + Literal["documents"], Literal["metadatas"], Literal["embeddings"] + ], +) -> None: + """ + The actual embedding field is equal to the expected field + field_name: one of [documents, metadatas] + """ + result = collection.get(ids=normalized_record_set["ids"], include=[field_name]) + # The test_out_of_order_ids test fails because of this in test_add.py + # Here we sort by the ids to match the input order + embedding_id_to_index = {id: i for i, id in enumerate(normalized_record_set["ids"])} + actual_field = result[field_name] + + if len(normalized_record_set["ids"]) == 0: + assert isinstance(actual_field, list) and len(actual_field) == 0 + return + + # This assert should never happen, if we include metadatas/documents it will be + # [None, None..] if there is no metadata. It will not be just None. + assert actual_field is not None + sorted_field = sorted( + enumerate(actual_field), + key=lambda index_and_field_value: embedding_id_to_index[ + result["ids"][index_and_field_value[0]] + ], + ) + field_values = [field_value for _, field_value in sorted_field] + + expected_field = normalized_record_set[field_name] + if expected_field is None: + # Since an RecordSet is the user input, we need to convert the documents to + # a List since thats what the API returns -> none per entry + expected_field = [None] * len(normalized_record_set["ids"]) # type: ignore + if field_name == "embeddings": + assert np.allclose(np.array(field_values), np.array(expected_field)) + else: + assert field_values == expected_field + + +def ids_match(collection: Collection, record_set: RecordSet) -> None: + """The actual embedding ids is equal to the expected ids""" + normalized_record_set = wrap_all(record_set) + actual_ids = collection.get(ids=normalized_record_set["ids"], include=[])["ids"] + # The test_out_of_order_ids test fails because of this in test_add.py + # Here we sort the ids to match the input order + embedding_id_to_index = {id: i for i, id in enumerate(normalized_record_set["ids"])} + actual_ids = sorted(actual_ids, key=lambda id: embedding_id_to_index[id]) + assert actual_ids == normalized_record_set["ids"] + + +def metadatas_match(collection: Collection, record_set: RecordSet) -> None: + """The actual embedding metadata is equal to the expected metadata""" + normalized_record_set = wrap_all(record_set) + _field_matches(collection, normalized_record_set, "metadatas") + + +def documents_match(collection: Collection, record_set: RecordSet) -> None: + """The actual embedding documents is equal to the expected documents""" + normalized_record_set = wrap_all(record_set) + _field_matches(collection, normalized_record_set, "documents") + + +def embeddings_match(collection: Collection, record_set: RecordSet) -> None: + """The actual embedding documents is equal to the expected documents""" + normalized_record_set = wrap_all(record_set) + _field_matches(collection, normalized_record_set, "embeddings") + + +def no_duplicates(collection: Collection) -> None: + ids = collection.get()["ids"] + assert len(ids) == len(set(ids)) + + +def _exact_distances( + query: types.Embeddings, + targets: types.Embeddings, + distance_fn: Callable[ + [npt.ArrayLike, npt.ArrayLike], float + ] = distance_functions.l2, +) -> Tuple[List[List[int]], List[List[float]]]: + """Return the ordered indices and distances from each query to each target""" + np_query = np.array(query) + np_targets = np.array(targets) + + # Compute the distance between each query and each target, using the distance function + distances = np.apply_along_axis( + lambda query: np.apply_along_axis(distance_fn, 1, np_targets, query), + 1, + np_query, + ) + # Sort the distances and return the indices + return np.argsort(distances).tolist(), distances.tolist() + + +def is_metadata_valid(normalized_record_set: NormalizedRecordSet) -> bool: + if normalized_record_set["metadatas"] is None: + return True + return not any([len(m) == 0 for m in normalized_record_set["metadatas"]]) + + +def ann_accuracy( + collection: Collection, + record_set: RecordSet, + n_results: int = 1, + min_recall: float = 0.99, + embedding_function: Optional[types.EmbeddingFunction] = None, + query_indices: Optional[List[int]] = None, +) -> None: + """Validate that the API performs nearest_neighbor searches correctly""" + normalized_record_set = wrap_all(record_set) + + if len(normalized_record_set["ids"]) == 0: + return # nothing to test here + + embeddings: Optional[types.Embeddings] = normalized_record_set["embeddings"] + have_embeddings = embeddings is not None and len(embeddings) > 0 + if not have_embeddings: + assert embedding_function is not None + assert normalized_record_set["documents"] is not None + assert isinstance(normalized_record_set["documents"], list) + # Compute the embeddings for the documents + embeddings = embedding_function(normalized_record_set["documents"]) + + # l2 is the default distance function + distance_function = distance_functions.l2 + accuracy_threshold = 1e-6 + assert collection.metadata is not None + assert embeddings is not None + if "hnsw:space" in collection.metadata: + space = collection.metadata["hnsw:space"] + # TODO: ip and cosine are numerically unstable in HNSW. + # The higher the dimensionality, the more noise is introduced, since each float element + # of the vector has noise added, which is then subsequently included in all normalization calculations. + # This means that higher dimensions will have more noise, and thus more error. + assert all(isinstance(e, list) for e in embeddings) + dim = len(embeddings[0]) + accuracy_threshold = accuracy_threshold * math.pow(10, int(math.log10(dim))) + + if space == "cosine": + distance_function = distance_functions.cosine + if space == "ip": + distance_function = distance_functions.ip + + # Perform exact distance computation + query_embeddings = ( + embeddings if query_indices is None else [embeddings[i] for i in query_indices] + ) + query_documents = normalized_record_set["documents"] + if query_indices is not None and query_documents is not None: + query_documents = [query_documents[i] for i in query_indices] + + indices, distances = _exact_distances( + query_embeddings, embeddings, distance_fn=distance_function + ) + + query_results = collection.query( + query_embeddings=query_embeddings if have_embeddings else None, + query_texts=query_documents if not have_embeddings else None, + n_results=n_results, + include=["embeddings", "documents", "metadatas", "distances"], + ) + + assert query_results["distances"] is not None + assert query_results["documents"] is not None + assert query_results["metadatas"] is not None + assert query_results["embeddings"] is not None + + # Dict of ids to indices + id_to_index = {id: i for i, id in enumerate(normalized_record_set["ids"])} + missing = 0 + for i, (indices_i, distances_i) in enumerate(zip(indices, distances)): + expected_ids = np.array(normalized_record_set["ids"])[indices_i[:n_results]] + missing += len(set(expected_ids) - set(query_results["ids"][i])) + + # For each id in the query results, find the index in the embeddings set + # and assert that the embeddings are the same + for j, id in enumerate(query_results["ids"][i]): + # This may be because the true nth nearest neighbor didn't get returned by the ANN query + unexpected_id = id not in expected_ids + index = id_to_index[id] + + correct_distance = np.allclose( + distances_i[index], + query_results["distances"][i][j], + atol=accuracy_threshold, + ) + if unexpected_id: + # If the ID is unexpcted, but the distance is correct, then we + # have a duplicate in the data. In this case, we should not reduce recall. + if correct_distance: + missing -= 1 + else: + continue + else: + assert correct_distance + + assert np.allclose(embeddings[index], query_results["embeddings"][i][j]) + if normalized_record_set["documents"] is not None: + assert ( + normalized_record_set["documents"][index] + == query_results["documents"][i][j] + ) + if normalized_record_set["metadatas"] is not None: + assert ( + normalized_record_set["metadatas"][index] + == query_results["metadatas"][i][j] + ) + + size = len(normalized_record_set["ids"]) + recall = (size - missing) / size + + try: + note( + f"recall: {recall}, missing {missing} out of {size}, accuracy threshold {accuracy_threshold}" + ) + except InvalidArgument: + pass # it's ok if we're running outside hypothesis + + assert recall >= min_recall + + # Ensure that the query results are sorted by distance + for distance_result in query_results["distances"]: + assert np.allclose(np.sort(distance_result), distance_result) diff --git a/chromadb/test/property/strategies.py b/chromadb/test/property/strategies.py new file mode 100644 index 0000000000000000000000000000000000000000..89def8ac316a6511aa1a8fa34bf068a6bc7dde96 --- /dev/null +++ b/chromadb/test/property/strategies.py @@ -0,0 +1,626 @@ +import hashlib +import hypothesis +import hypothesis.strategies as st +from typing import Any, Optional, List, Dict, Union, cast +from typing_extensions import TypedDict +import uuid +import numpy as np +import numpy.typing as npt +import chromadb.api.types as types +import re +from hypothesis.strategies._internal.strategies import SearchStrategy +from hypothesis.errors import InvalidDefinition +from hypothesis.stateful import RuleBasedStateMachine + +from dataclasses import dataclass + +from chromadb.api.types import ( + Documents, + Embeddable, + EmbeddingFunction, + Embeddings, + Metadata, +) +from chromadb.types import LiteralValue, WhereOperator, LogicalOperator + +# Set the random seed for reproducibility +np.random.seed(0) # unnecessary, hypothesis does this for us + +# See Hypothesis documentation for creating strategies at +# https://hypothesis.readthedocs.io/en/latest/data.html + +# NOTE: Because these strategies are used in state machines, we need to +# work around an issue with state machines, in which strategies that frequently +# are marked as invalid (i.e. through the use of `assume` or `.filter`) can cause the +# state machine tests to fail with an hypothesis.errors.Unsatisfiable. + +# Ultimately this is because the entire state machine is run as a single Hypothesis +# example, which ends up drawing from the same strategies an enormous number of times. +# Whenever a strategy marks itself as invalid, Hypothesis tries to start the entire +# state machine run over. See https://github.com/HypothesisWorks/hypothesis/issues/3618 + +# Because strategy generation is all interrelated, seemingly small changes (especially +# ones called early in a test) can have an outside effect. Generating lists with +# unique=True, or dictionaries with a min size seems especially bad. + +# Please make changes to these strategies incrementally, testing to make sure they don't +# start generating unsatisfiable examples. + +test_hnsw_config = { + "hnsw:construction_ef": 128, + "hnsw:search_ef": 128, + "hnsw:M": 128, +} + + +class RecordSet(TypedDict): + """ + A generated set of embeddings, ids, metadatas, and documents that + represent what a user would pass to the API. + """ + + ids: Union[types.ID, List[types.ID]] + embeddings: Optional[Union[types.Embeddings, types.Embedding]] + metadatas: Optional[Union[List[types.Metadata], types.Metadata]] + documents: Optional[Union[List[types.Document], types.Document]] + + +class NormalizedRecordSet(TypedDict): + """ + A RecordSet, with all fields normalized to lists. + """ + + ids: List[types.ID] + embeddings: Optional[types.Embeddings] + metadatas: Optional[List[types.Metadata]] + documents: Optional[List[types.Document]] + + +class StateMachineRecordSet(TypedDict): + """ + Represents the internal state of a state machine in hypothesis tests. + """ + + ids: List[types.ID] + embeddings: types.Embeddings + metadatas: List[Optional[types.Metadata]] + documents: List[Optional[types.Document]] + + +class Record(TypedDict): + """ + A single generated record. + """ + + id: types.ID + embedding: Optional[types.Embedding] + metadata: Optional[types.Metadata] + document: Optional[types.Document] + + +# TODO: support arbitrary text everywhere so we don't SQL-inject ourselves. +# TODO: support empty strings everywhere +sql_alphabet = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-_" +safe_text = st.text(alphabet=sql_alphabet, min_size=1) +tenant_database_name = st.text(alphabet=sql_alphabet, min_size=3) + +# Workaround for FastAPI json encoding peculiarities +# https://github.com/tiangolo/fastapi/blob/8ac8d70d52bb0dd9eb55ba4e22d3e383943da05c/fastapi/encoders.py#L104 +safe_text = safe_text.filter(lambda s: not s.startswith("_sa")) +tenant_database_name = tenant_database_name.filter(lambda s: not s.startswith("_sa")) + +safe_integers = st.integers( + min_value=-(2**31), max_value=2**31 - 1 +) # TODO: handle longs +safe_floats = st.floats( + allow_infinity=False, + allow_nan=False, + allow_subnormal=False, + min_value=-1e6, + max_value=1e6, +) # TODO: handle infinity and NAN + +safe_values: List[SearchStrategy[Union[int, float, str, bool]]] = [ + safe_text, + safe_integers, + safe_floats, + st.booleans(), +] + + +def one_or_both( + strategy_a: st.SearchStrategy[Any], strategy_b: st.SearchStrategy[Any] +) -> st.SearchStrategy[Any]: + return st.one_of( + st.tuples(strategy_a, strategy_b), + st.tuples(strategy_a, st.none()), + st.tuples(st.none(), strategy_b), + ) + + +# Temporarily generate only these to avoid SQL formatting issues. +legal_id_characters = ( + "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-_./+" +) + +float_types = [np.float16, np.float32, np.float64] +int_types = [np.int16, np.int32, np.int64] # TODO: handle int types + + +@st.composite +def collection_name(draw: st.DrawFn) -> str: + _collection_name_re = re.compile(r"^[a-zA-Z][a-zA-Z0-9-]{1,60}[a-zA-Z0-9]$") + _ipv4_address_re = re.compile(r"^([0-9]{1,3}\.){3}[0-9]{1,3}$") + _two_periods_re = re.compile(r"\.\.") + + name: str = draw(st.from_regex(_collection_name_re)) + hypothesis.assume(not _ipv4_address_re.match(name)) + hypothesis.assume(not _two_periods_re.search(name)) + + return name + + +collection_metadata = st.one_of( + st.none(), st.dictionaries(safe_text, st.one_of(*safe_values)) +) + + +# TODO: Use a hypothesis strategy while maintaining embedding uniqueness +# Or handle duplicate embeddings within a known epsilon +def create_embeddings( + dim: int, + count: int, + dtype: npt.DTypeLike, +) -> types.Embeddings: + embeddings: types.Embeddings = ( + np.random.uniform( + low=-1.0, + high=1.0, + size=(count, dim), + ) + .astype(dtype) + .tolist() + ) + + return embeddings + + +def create_embeddings_ndarray( + dim: int, + count: int, + dtype: npt.DTypeLike, +) -> np.typing.NDArray[Any]: + return np.random.uniform( + low=-1.0, + high=1.0, + size=(count, dim), + ).astype(dtype) + + +class hashing_embedding_function(types.EmbeddingFunction[Documents]): + def __init__(self, dim: int, dtype: npt.DTypeLike) -> None: + self.dim = dim + self.dtype = dtype + + def __call__(self, input: types.Documents) -> types.Embeddings: + # Hash the texts and convert to hex strings + hashed_texts = [ + list(hashlib.sha256(text.encode("utf-8")).hexdigest()) for text in input + ] + # Pad with repetition, or truncate the hex strings to the desired dimension + padded_texts = [ + text * (self.dim // len(text)) + text[: self.dim % len(text)] + for text in hashed_texts + ] + + # Convert the hex strings to dtype + embeddings: types.Embeddings = np.array( + [[int(char, 16) / 15.0 for char in text] for text in padded_texts], + dtype=self.dtype, + ).tolist() + + return embeddings + + +class not_implemented_embedding_function(types.EmbeddingFunction[Documents]): + def __call__(self, input: Documents) -> Embeddings: + assert False, "This embedding function is not implemented" + + +def embedding_function_strategy( + dim: int, dtype: npt.DTypeLike +) -> st.SearchStrategy[types.EmbeddingFunction[Embeddable]]: + return st.just( + cast(EmbeddingFunction[Embeddable], hashing_embedding_function(dim, dtype)) + ) + + +@dataclass +class Collection: + name: str + id: uuid.UUID + metadata: Optional[types.Metadata] + dimension: int + dtype: npt.DTypeLike + topic: str + known_metadata_keys: types.Metadata + known_document_keywords: List[str] + has_documents: bool = False + has_embeddings: bool = False + embedding_function: Optional[types.EmbeddingFunction[Embeddable]] = None + +@st.composite +def collections( + draw: st.DrawFn, + add_filterable_data: bool = False, + with_hnsw_params: bool = False, + has_embeddings: Optional[bool] = None, + has_documents: Optional[bool] = None, + with_persistent_hnsw_params: bool = False, +) -> Collection: + """Strategy to generate a Collection object. If add_filterable_data is True, then known_metadata_keys and known_document_keywords will be populated with consistent data.""" + + assert not ((has_embeddings is False) and (has_documents is False)) + + name = draw(collection_name()) + metadata = draw(collection_metadata) + dimension = draw(st.integers(min_value=2, max_value=2048)) + dtype = draw(st.sampled_from(float_types)) + + if with_persistent_hnsw_params and not with_hnsw_params: + raise ValueError( + "with_hnsw_params requires with_persistent_hnsw_params to be true" + ) + + if with_hnsw_params: + if metadata is None: + metadata = {} + metadata.update(test_hnsw_config) + if with_persistent_hnsw_params: + metadata["hnsw:batch_size"] = draw(st.integers(min_value=3, max_value=2000)) + metadata["hnsw:sync_threshold"] = draw( + st.integers(min_value=3, max_value=2000) + ) + # Sometimes, select a space at random + if draw(st.booleans()): + # TODO: pull the distance functions from a source of truth that lives not + # in tests once https://github.com/chroma-core/issues/issues/61 lands + metadata["hnsw:space"] = draw(st.sampled_from(["cosine", "l2", "ip"])) + + known_metadata_keys: Dict[str, Union[int, str, float]] = {} + if add_filterable_data: + while len(known_metadata_keys) < 5: + key = draw(safe_text) + known_metadata_keys[key] = draw(st.one_of(*safe_values)) + + if has_documents is None: + has_documents = draw(st.booleans()) + assert has_documents is not None + if has_documents and add_filterable_data: + known_document_keywords = draw(st.lists(safe_text, min_size=5, max_size=5)) + else: + known_document_keywords = [] + + if not has_documents: + has_embeddings = True + else: + if has_embeddings is None: + has_embeddings = draw(st.booleans()) + assert has_embeddings is not None + + embedding_function = draw(embedding_function_strategy(dimension, dtype)) + + return Collection( + id=uuid.uuid4(), + name=name, + topic="topic", + metadata=metadata, + dimension=dimension, + dtype=dtype, + known_metadata_keys=known_metadata_keys, + has_documents=has_documents, + known_document_keywords=known_document_keywords, + has_embeddings=has_embeddings, + embedding_function=embedding_function, + ) + + +@st.composite +def metadata(draw: st.DrawFn, collection: Collection) -> types.Metadata: + """Strategy for generating metadata that could be a part of the given collection""" + # First draw a random dictionary. + metadata: types.Metadata = draw(st.dictionaries(safe_text, st.one_of(*safe_values))) + # Then, remove keys that overlap with the known keys for the coll + # to avoid type errors when comparing. + if collection.known_metadata_keys: + for key in collection.known_metadata_keys.keys(): + if key in metadata: + del metadata[key] # type: ignore + # Finally, add in some of the known keys for the collection + sampling_dict: Dict[str, st.SearchStrategy[Union[str, int, float]]] = { + k: st.just(v) for k, v in collection.known_metadata_keys.items() + } + metadata.update(draw(st.fixed_dictionaries({}, optional=sampling_dict))) # type: ignore + return metadata + + +@st.composite +def document(draw: st.DrawFn, collection: Collection) -> types.Document: + """Strategy for generating documents that could be a part of the given collection""" + + # Blacklist certain unicode characters that affect sqlite processing. + # For example, the null (/x00) character makes sqlite stop processing a string. + blacklist_categories = ("Cc", "Cs") + if collection.known_document_keywords: + known_words_st = st.sampled_from(collection.known_document_keywords) + else: + known_words_st = st.text( + min_size=1, + alphabet=st.characters(blacklist_categories=blacklist_categories), # type: ignore + ) + + random_words_st = st.text( + min_size=1, alphabet=st.characters(blacklist_categories=blacklist_categories) # type: ignore + ) + words = draw(st.lists(st.one_of(known_words_st, random_words_st), min_size=1)) + return " ".join(words) + + +@st.composite +def recordsets( + draw: st.DrawFn, + collection_strategy: SearchStrategy[Collection] = collections(), + id_strategy: SearchStrategy[str] = safe_text, + min_size: int = 1, + max_size: int = 50, +) -> RecordSet: + collection = draw(collection_strategy) + + ids = list( + draw(st.lists(id_strategy, min_size=min_size, max_size=max_size, unique=True)) + ) + + embeddings: Optional[Embeddings] = None + if collection.has_embeddings: + embeddings = create_embeddings(collection.dimension, len(ids), collection.dtype) + metadatas = draw( + st.lists(metadata(collection), min_size=len(ids), max_size=len(ids)) + ) + documents: Optional[Documents] = None + if collection.has_documents: + documents = draw( + st.lists(document(collection), min_size=len(ids), max_size=len(ids)) + ) + + # in the case where we have a single record, sometimes exercise + # the code that handles individual values rather than lists. + # In this case, any field may be a list or a single value. + if len(ids) == 1: + single_id: Union[str, List[str]] = ids[0] if draw(st.booleans()) else ids + single_embedding = ( + embeddings[0] + if embeddings is not None and draw(st.booleans()) + else embeddings + ) + single_metadata: Union[Metadata, List[Metadata]] = ( + metadatas[0] if draw(st.booleans()) else metadatas + ) + single_document = ( + documents[0] if documents is not None and draw(st.booleans()) else documents + ) + return { + "ids": single_id, + "embeddings": single_embedding, + "metadatas": single_metadata, + "documents": single_document, + } + + return { + "ids": ids, + "embeddings": embeddings, + "metadatas": metadatas, + "documents": documents, + } + + +# This class is mostly cloned from from hypothesis.stateful.RuleStrategy, +# but always runs all the rules, instead of using a FeatureStrategy to +# enable/disable rules. Disabled rules cause the entire test to be marked invalida and, +# combined with the complexity of our other strategies, leads to an +# unacceptably increased incidence of hypothesis.errors.Unsatisfiable. +class DeterministicRuleStrategy(SearchStrategy): # type: ignore + def __init__(self, machine: RuleBasedStateMachine) -> None: + super().__init__() # type: ignore + self.machine = machine + self.rules = list(machine.rules()) # type: ignore + + # The order is a bit arbitrary. Primarily we're trying to group rules + # that write to the same location together, and to put rules with no + # target first as they have less effect on the structure. We order from + # fewer to more arguments on grounds that it will plausibly need less + # data. This probably won't work especially well and we could be + # smarter about it, but it's better than just doing it in definition + # order. + self.rules.sort( + key=lambda rule: ( + sorted(rule.targets), + len(rule.arguments), + rule.function.__name__, + ) + ) + + def __repr__(self) -> str: + return "{}(machine={}({{...}}))".format( + self.__class__.__name__, + self.machine.__class__.__name__, + ) + + def do_draw(self, data): # type: ignore + if not any(self.is_valid(rule) for rule in self.rules): + msg = f"No progress can be made from state {self.machine!r}" + raise InvalidDefinition(msg) from None + + rule = data.draw(st.sampled_from([r for r in self.rules if self.is_valid(r)])) + argdata = data.draw(rule.arguments_strategy) + return (rule, argdata) + + def is_valid(self, rule) -> bool: # type: ignore + if not all(precond(self.machine) for precond in rule.preconditions): + return False + + for b in rule.bundles: + bundle = self.machine.bundle(b.name) # type: ignore + if not bundle: + return False + return True + + +def opposite_value(value: LiteralValue) -> SearchStrategy[Any]: + """ + Returns a strategy that will generate all valid values except the input value - testing of $nin + """ + if isinstance(value, float): + return st.floats(allow_nan=False, allow_infinity=False).filter( + lambda x: x != value + ) + elif isinstance(value, str): + return safe_text.filter(lambda x: x != value) + elif isinstance(value, bool): + return st.booleans().filter(lambda x: x != value) + elif isinstance(value, int): + return st.integers(min_value=-(2**31), max_value=2**31 - 1).filter( + lambda x: x != value + ) + else: + return st.from_type(type(value)).filter(lambda x: x != value) + + +@st.composite +def where_clause(draw: st.DrawFn, collection: Collection) -> types.Where: + """Generate a filter that could be used in a query against the given collection""" + + known_keys = sorted(collection.known_metadata_keys.keys()) + + key = draw(st.sampled_from(known_keys)) + value = collection.known_metadata_keys[key] + + legal_ops: List[Optional[str]] = [None, "$eq", "$ne", "$in", "$nin"] + if not isinstance(value, str) and not isinstance(value, bool): + legal_ops.extend(["$gt", "$lt", "$lte", "$gte"]) + if isinstance(value, float): + # Add or subtract a small number to avoid floating point rounding errors + value = value + draw(st.sampled_from([1e-6, -1e-6])) + + op: WhereOperator = draw(st.sampled_from(legal_ops)) + + if op is None: + return {key: value} + elif op == "$in": # type: ignore + if isinstance(value, str) and not value: + return {} + return {key: {op: [value, *[draw(opposite_value(value)) for _ in range(3)]]}} + elif op == "$nin": # type: ignore + if isinstance(value, str) and not value: + return {} + return {key: {op: [draw(opposite_value(value)) for _ in range(3)]}} + else: + return {key: {op: value}} # type: ignore + + +@st.composite +def where_doc_clause(draw: st.DrawFn, collection: Collection) -> types.WhereDocument: + """Generate a where_document filter that could be used against the given collection""" + if collection.known_document_keywords: + word = draw(st.sampled_from(collection.known_document_keywords)) + else: + word = draw(safe_text) + + op: WhereOperator = draw(st.sampled_from(["$contains", "$not_contains"])) + if op == "$contains": + return {"$contains": word} + else: + assert op == "$not_contains" + return {"$not_contains": word} + + +def binary_operator_clause( + base_st: SearchStrategy[types.Where], +) -> SearchStrategy[types.Where]: + op: SearchStrategy[LogicalOperator] = st.sampled_from(["$and", "$or"]) + return st.dictionaries( + keys=op, + values=st.lists(base_st, max_size=2, min_size=2), + min_size=1, + max_size=1, + ) + + +def binary_document_operator_clause( + base_st: SearchStrategy[types.WhereDocument], +) -> SearchStrategy[types.WhereDocument]: + op: SearchStrategy[LogicalOperator] = st.sampled_from(["$and", "$or"]) + return st.dictionaries( + keys=op, + values=st.lists(base_st, max_size=2, min_size=2), + min_size=1, + max_size=1, + ) + + +@st.composite +def recursive_where_clause(draw: st.DrawFn, collection: Collection) -> types.Where: + base_st = where_clause(collection) + where: types.Where = draw(st.recursive(base_st, binary_operator_clause)) + return where + + +@st.composite +def recursive_where_doc_clause( + draw: st.DrawFn, collection: Collection +) -> types.WhereDocument: + base_st = where_doc_clause(collection) + where: types.WhereDocument = draw( + st.recursive(base_st, binary_document_operator_clause) + ) + return where + + +class Filter(TypedDict): + where: Optional[types.Where] + ids: Optional[Union[str, List[str]]] + where_document: Optional[types.WhereDocument] + + +@st.composite +def filters( + draw: st.DrawFn, + collection_st: st.SearchStrategy[Collection], + recordset_st: st.SearchStrategy[RecordSet], + include_all_ids: bool = False, +) -> Filter: + collection = draw(collection_st) + recordset = draw(recordset_st) + + where_clause = draw(st.one_of(st.none(), recursive_where_clause(collection))) + where_document_clause = draw( + st.one_of(st.none(), recursive_where_doc_clause(collection)) + ) + + ids: Optional[Union[List[types.ID], types.ID]] + # Record sets can be a value instead of a list of values if there is only one record + if isinstance(recordset["ids"], str): + ids = [recordset["ids"]] + else: + ids = recordset["ids"] + + if not include_all_ids: + ids = draw(st.one_of(st.none(), st.lists(st.sampled_from(ids)))) + if ids is not None: + # Remove duplicates since hypothesis samples with replacement + ids = list(set(ids)) + + # Test both the single value list and the unwrapped single value case + if ids is not None and len(ids) == 1 and draw(st.booleans()): + ids = ids[0] + + return {"where": where_clause, "where_document": where_document_clause, "ids": ids} diff --git a/chromadb/test/property/test_add.py b/chromadb/test/property/test_add.py new file mode 100644 index 0000000000000000000000000000000000000000..f97e33aa305b06245dbb5407621dcbaa1cfefee2 --- /dev/null +++ b/chromadb/test/property/test_add.py @@ -0,0 +1,185 @@ +import random +import uuid +from random import randint +from typing import cast, List, Any, Dict +import pytest +import hypothesis.strategies as st +from hypothesis import given, settings +from chromadb.api import ServerAPI +from chromadb.api.types import Embeddings, Metadatas +import chromadb.test.property.strategies as strategies +import chromadb.test.property.invariants as invariants +from chromadb.utils.batch_utils import create_batches + +collection_st = st.shared(strategies.collections(with_hnsw_params=True), key="coll") + + +@given(collection=collection_st, record_set=strategies.recordsets(collection_st)) +@settings(deadline=None) +def test_add( + api: ServerAPI, + collection: strategies.Collection, + record_set: strategies.RecordSet, +) -> None: + api.reset() + + # TODO: Generative embedding functions + coll = api.create_collection( + name=collection.name, + metadata=collection.metadata, # type: ignore + embedding_function=collection.embedding_function, + ) + normalized_record_set = invariants.wrap_all(record_set) + + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + coll.add(**normalized_record_set) + return + + coll.add(**record_set) + + invariants.count(coll, cast(strategies.RecordSet, normalized_record_set)) + n_results = max(1, (len(normalized_record_set["ids"]) // 10)) + invariants.ann_accuracy( + coll, + cast(strategies.RecordSet, normalized_record_set), + n_results=n_results, + embedding_function=collection.embedding_function, + ) + + +def create_large_recordset( + min_size: int = 45000, + max_size: int = 50000, +) -> strategies.RecordSet: + size = randint(min_size, max_size) + + ids = [str(uuid.uuid4()) for _ in range(size)] + metadatas = [{"some_key": f"{i}"} for i in range(size)] + documents = [f"Document {i}" for i in range(size)] + embeddings = [[1, 2, 3] for _ in range(size)] + record_set: Dict[str, List[Any]] = { + "ids": ids, + "embeddings": cast(Embeddings, embeddings), + "metadatas": metadatas, + "documents": documents, + } + return cast(strategies.RecordSet, record_set) + + +@given(collection=collection_st) +@settings(deadline=None, max_examples=1) +def test_add_large(api: ServerAPI, collection: strategies.Collection) -> None: + api.reset() + record_set = create_large_recordset( + min_size=api.max_batch_size, + max_size=api.max_batch_size + int(api.max_batch_size * random.random()), + ) + coll = api.create_collection( + name=collection.name, + metadata=collection.metadata, # type: ignore + embedding_function=collection.embedding_function, + ) + normalized_record_set = invariants.wrap_all(record_set) + + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + coll.add(**normalized_record_set) + return + for batch in create_batches( + api=api, + ids=cast(List[str], record_set["ids"]), + embeddings=cast(Embeddings, record_set["embeddings"]), + metadatas=cast(Metadatas, record_set["metadatas"]), + documents=cast(List[str], record_set["documents"]), + ): + coll.add(*batch) + invariants.count(coll, cast(strategies.RecordSet, normalized_record_set)) + + +@given(collection=collection_st) +@settings(deadline=None, max_examples=1) +def test_add_large_exceeding(api: ServerAPI, collection: strategies.Collection) -> None: + api.reset() + record_set = create_large_recordset( + min_size=api.max_batch_size, + max_size=api.max_batch_size + int(api.max_batch_size * random.random()), + ) + coll = api.create_collection( + name=collection.name, + metadata=collection.metadata, # type: ignore + embedding_function=collection.embedding_function, + ) + normalized_record_set = invariants.wrap_all(record_set) + + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + coll.add(**normalized_record_set) + return + with pytest.raises(Exception) as e: + coll.add(**record_set) + assert "exceeds maximum batch size" in str(e.value) + + +# TODO: This test fails right now because the ids are not sorted by the input order +@pytest.mark.xfail( + reason="This is expected to fail right now. We should change the API to sort the \ + ids by input order." +) +def test_out_of_order_ids(api: ServerAPI) -> None: + api.reset() + ooo_ids = [ + "40", + "05", + "8", + "6", + "10", + "01", + "00", + "3", + "04", + "20", + "02", + "9", + "30", + "11", + "13", + "2", + "0", + "7", + "06", + "5", + "50", + "12", + "03", + "4", + "1", + ] + + coll = api.create_collection( + "test", embedding_function=lambda input: [[1, 2, 3] for _ in input] # type: ignore + ) + embeddings: Embeddings = [[1, 2, 3] for _ in ooo_ids] + coll.add(ids=ooo_ids, embeddings=embeddings) + get_ids = coll.get(ids=ooo_ids)["ids"] + assert get_ids == ooo_ids + + +def test_add_partial(api: ServerAPI) -> None: + """Tests adding a record set with some of the fields set to None.""" + + api.reset() + + coll = api.create_collection("test") + # TODO: We need to clean up the api types to support this typing + coll.add( + ids=["1", "2", "3"], + embeddings=[[1, 2, 3], [1, 2, 3], [1, 2, 3]], # type: ignore + metadatas=[{"a": 1}, None, {"a": 3}], # type: ignore + documents=["a", "b", None], # type: ignore + ) + + results = coll.get() + assert results["ids"] == ["1", "2", "3"] + assert results["metadatas"] == [{"a": 1}, None, {"a": 3}] + assert results["documents"] == ["a", "b", None] diff --git a/chromadb/test/property/test_client_url.py b/chromadb/test/property/test_client_url.py new file mode 100644 index 0000000000000000000000000000000000000000..cc5df1e05141df46a6395f7251deac0c78e40b26 --- /dev/null +++ b/chromadb/test/property/test_client_url.py @@ -0,0 +1,134 @@ +from typing import Optional +from urllib.parse import urlparse + +import pytest +from hypothesis import given, strategies as st + +from chromadb.api.fastapi import FastAPI + + +def hostname_strategy() -> st.SearchStrategy[str]: + label = st.text( + alphabet=st.characters(min_codepoint=97, max_codepoint=122), + min_size=1, + max_size=63, + ) + return st.lists(label, min_size=1, max_size=3).map("-".join) + + +tld_list = ["com", "org", "net", "edu"] + + +def domain_strategy() -> st.SearchStrategy[str]: + label = st.text( + alphabet=st.characters(min_codepoint=97, max_codepoint=122), + min_size=1, + max_size=63, + ) + tld = st.sampled_from(tld_list) + return st.tuples(label, tld).map(".".join) + + +port_strategy = st.one_of(st.integers(min_value=1, max_value=65535), st.none()) + +ssl_enabled_strategy = st.booleans() + + +def url_path_strategy() -> st.SearchStrategy[str]: + path_segment = st.text( + alphabet=st.sampled_from("abcdefghijklmnopqrstuvwxyz/-_"), + min_size=1, + max_size=10, + ) + return ( + st.lists(path_segment, min_size=1, max_size=5) + .map("/".join) + .map(lambda x: "/" + x) + ) + + +def is_valid_url(url: str) -> bool: + try: + parsed = urlparse(url) + return all([parsed.scheme, parsed.netloc]) + except Exception: + return False + + +def generate_valid_domain_url() -> st.SearchStrategy[str]: + return st.builds( + lambda url_scheme, hostname, url_path: f"{url_scheme}{hostname}{url_path}", + url_scheme=st.sampled_from(["http://", "https://"]), + hostname=domain_strategy(), + url_path=url_path_strategy(), + ) + + +def generate_invalid_domain_url() -> st.SearchStrategy[str]: + return st.builds( + lambda url_scheme, hostname, url_path: f"{url_scheme}{hostname}{url_path}", + url_scheme=st.builds( + lambda scheme, suffix: f"{scheme}{suffix}", + scheme=st.text(max_size=10), + suffix=st.sampled_from(["://", ":///", ":////", ""]), + ), + hostname=domain_strategy(), + url_path=url_path_strategy(), + ) + + +host_or_domain_strategy = st.one_of( + generate_valid_domain_url(), domain_strategy(), st.sampled_from(["localhost"]) +) + + +@given( + hostname=host_or_domain_strategy, + port=port_strategy, + ssl_enabled=ssl_enabled_strategy, + default_api_path=st.sampled_from(["/api/v1", "/api/v2", None]), +) +def test_url_resolve( + hostname: str, + port: Optional[int], + ssl_enabled: bool, + default_api_path: Optional[str], +) -> None: + _url = FastAPI.resolve_url( + chroma_server_host=hostname, + chroma_server_http_port=port, + chroma_server_ssl_enabled=ssl_enabled, + default_api_path=default_api_path, + ) + assert is_valid_url(_url), f"Invalid URL: {_url}" + assert ( + _url.startswith("https") if ssl_enabled else _url.startswith("http") + ), f"Invalid URL: {_url} - SSL Enabled: {ssl_enabled}" + if hostname.startswith("http"): + assert ":" + str(port) not in _url, f"Port in URL not expected: {_url}" + else: + assert ":" + str(port) in _url, f"Port in URL expected: {_url}" + if default_api_path: + assert _url.endswith(default_api_path), f"Invalid URL: {_url}" + + +@given( + hostname=generate_invalid_domain_url(), + port=port_strategy, + ssl_enabled=ssl_enabled_strategy, + default_api_path=st.sampled_from(["/api/v1", "/api/v2", None]), +) +def test_resolve_invalid( + hostname: str, + port: Optional[int], + ssl_enabled: bool, + default_api_path: Optional[str], +) -> None: + with pytest.raises(ValueError) as e: + FastAPI.resolve_url( + chroma_server_host=hostname, + chroma_server_http_port=port, + chroma_server_ssl_enabled=ssl_enabled, + default_api_path=default_api_path, + ) + assert "Invalid URL" in str(e.value) diff --git a/chromadb/test/property/test_collections.py b/chromadb/test/property/test_collections.py new file mode 100644 index 0000000000000000000000000000000000000000..844476aa8eafc6537b118600de365da14c38fb8a --- /dev/null +++ b/chromadb/test/property/test_collections.py @@ -0,0 +1,246 @@ +import pytest +import logging +import hypothesis.strategies as st +import chromadb.test.property.strategies as strategies +from chromadb.api import ClientAPI +import chromadb.api.types as types +from hypothesis.stateful import ( + Bundle, + RuleBasedStateMachine, + rule, + initialize, + multiple, + consumes, + run_state_machine_as_test, + MultipleResults, +) +from typing import Dict, Optional + + +class CollectionStateMachine(RuleBasedStateMachine): + collections: Bundle[strategies.Collection] + _model: Dict[str, Optional[types.CollectionMetadata]] + + collections = Bundle("collections") + + def __init__(self, api: ClientAPI): + super().__init__() + self._model = {} + self.api = api + + @initialize() + def initialize(self) -> None: + self.api.reset() + self._model = {} + + @rule(target=collections, coll=strategies.collections()) + def create_coll( + self, coll: strategies.Collection + ) -> MultipleResults[strategies.Collection]: + # Metadata can either be None or a non-empty dict + if coll.name in self.model or ( + coll.metadata is not None and len(coll.metadata) == 0 + ): + with pytest.raises(Exception): + c = self.api.create_collection( + name=coll.name, + metadata=coll.metadata, + embedding_function=coll.embedding_function, + ) + return multiple() + + c = self.api.create_collection( + name=coll.name, + metadata=coll.metadata, + embedding_function=coll.embedding_function, + ) + self.set_model(coll.name, coll.metadata) + + assert c.name == coll.name + assert c.metadata == self.model[coll.name] + return multiple(coll) + + @rule(coll=collections) + def get_coll(self, coll: strategies.Collection) -> None: + if coll.name in self.model: + c = self.api.get_collection(name=coll.name) + assert c.name == coll.name + assert c.metadata == self.model[coll.name] + else: + with pytest.raises(Exception): + self.api.get_collection(name=coll.name) + + @rule(coll=consumes(collections)) + def delete_coll(self, coll: strategies.Collection) -> None: + if coll.name in self.model: + self.api.delete_collection(name=coll.name) + self.delete_from_model(coll.name) + else: + with pytest.raises(Exception): + self.api.delete_collection(name=coll.name) + + with pytest.raises(Exception): + self.api.get_collection(name=coll.name) + + @rule() + def list_collections(self) -> None: + colls = self.api.list_collections() + assert len(colls) == len(self.model) + for c in colls: + assert c.name in self.model + + # @rule for list_collections with limit and offset + @rule( + limit=st.integers(min_value=1, max_value=5), + offset=st.integers(min_value=0, max_value=5), + ) + def list_collections_with_limit_offset(self, limit: int, offset: int) -> None: + colls = self.api.list_collections(limit=limit, offset=offset) + total_collections = self.api.count_collections() + + # get all collections + all_colls = self.api.list_collections() + # manually slice the collections based on the given limit and offset + man_colls = all_colls[offset : offset + limit] + + # given limit and offset, make various assertions regarding the total number of collections + if limit + offset > total_collections: + assert len(colls) == max(total_collections - offset, 0) + # assert that our manually sliced collections are the same as the ones returned by the API + assert colls == man_colls + + else: + assert len(colls) == limit + + @rule( + target=collections, + new_metadata=st.one_of(st.none(), strategies.collection_metadata), + coll=st.one_of(consumes(collections), strategies.collections()), + ) + def get_or_create_coll( + self, + coll: strategies.Collection, + new_metadata: Optional[types.Metadata], + ) -> MultipleResults[strategies.Collection]: + # Cases for get_or_create + + # Case 0 + # new_metadata is none, coll is an existing collection + # get_or_create should return the existing collection with existing metadata + # Essentially - an update with none is a no-op + + # Case 1 + # new_metadata is none, coll is a new collection + # get_or_create should create a new collection with the metadata of None + + # Case 2 + # new_metadata is not none, coll is an existing collection + # get_or_create should return the existing collection with updated metadata + + # Case 3 + # new_metadata is not none, coll is a new collection + # get_or_create should create a new collection with the new metadata, ignoring + # the metdata of in the input coll. + + # The fact that we ignore the metadata of the generated collections is a + # bit weird, but it is the easiest way to excercise all cases + + if new_metadata is not None and len(new_metadata) == 0: + with pytest.raises(Exception): + c = self.api.get_or_create_collection( + name=coll.name, + metadata=new_metadata, + embedding_function=coll.embedding_function, + ) + return multiple() + + # Update model + if coll.name not in self.model: + # Handles case 1 and 3 + coll.metadata = new_metadata + else: + # Handles case 0 and 2 + coll.metadata = ( + self.model[coll.name] if new_metadata is None else new_metadata + ) + self.set_model(coll.name, coll.metadata) + + # Update API + c = self.api.get_or_create_collection( + name=coll.name, + metadata=new_metadata, + embedding_function=coll.embedding_function, + ) + + # Check that model and API are in sync + assert c.name == coll.name + assert c.metadata == self.model[coll.name] + return multiple(coll) + + @rule( + target=collections, + coll=consumes(collections), + new_metadata=strategies.collection_metadata, + new_name=st.one_of(st.none(), strategies.collection_name()), + ) + def modify_coll( + self, + coll: strategies.Collection, + new_metadata: types.Metadata, + new_name: Optional[str], + ) -> MultipleResults[strategies.Collection]: + if coll.name not in self.model: + with pytest.raises(Exception): + c = self.api.get_collection(name=coll.name) + return multiple() + + c = self.api.get_collection(name=coll.name) + + if new_metadata is not None: + if len(new_metadata) == 0: + with pytest.raises(Exception): + c = self.api.get_or_create_collection( + name=coll.name, + metadata=new_metadata, + embedding_function=coll.embedding_function, + ) + return multiple() + coll.metadata = new_metadata + self.set_model(coll.name, coll.metadata) + + if new_name is not None: + if new_name in self.model and new_name != coll.name: + with pytest.raises(Exception): + c.modify(metadata=new_metadata, name=new_name) + return multiple() + + prev_metadata = self.model[coll.name] + self.delete_from_model(coll.name) + self.set_model(new_name, prev_metadata) + coll.name = new_name + + c.modify(metadata=new_metadata, name=new_name) + c = self.api.get_collection(name=coll.name) + + assert c.name == coll.name + assert c.metadata == self.model[coll.name] + return multiple(coll) + + def set_model( + self, name: str, metadata: Optional[types.CollectionMetadata] + ) -> None: + model = self.model + model[name] = metadata + + def delete_from_model(self, name: str) -> None: + model = self.model + del model[name] + + @property + def model(self) -> Dict[str, Optional[types.CollectionMetadata]]: + return self._model + + +def test_collections(caplog: pytest.LogCaptureFixture, api: ClientAPI) -> None: + caplog.set_level(logging.ERROR) + run_state_machine_as_test(lambda: CollectionStateMachine(api)) # type: ignore diff --git a/chromadb/test/property/test_collections_with_database_tenant.py b/chromadb/test/property/test_collections_with_database_tenant.py new file mode 100644 index 0000000000000000000000000000000000000000..28ba14f092ad9450054b1325e9a79ba11a98912f --- /dev/null +++ b/chromadb/test/property/test_collections_with_database_tenant.py @@ -0,0 +1,102 @@ +import logging +from typing import Dict, Optional, Tuple +import pytest +from chromadb.api import AdminAPI +import chromadb.api.types as types +from chromadb.api.client import AdminClient, Client +from chromadb.config import DEFAULT_DATABASE, DEFAULT_TENANT +from chromadb.test.property.test_collections import CollectionStateMachine +from hypothesis.stateful import ( + Bundle, + rule, + initialize, + multiple, + run_state_machine_as_test, + MultipleResults, +) +import chromadb.test.property.strategies as strategies + + +class TenantDatabaseCollectionStateMachine(CollectionStateMachine): + """A collection state machine test that includes tenant and database information, + and switches between them.""" + + tenants: Bundle[str] + databases: Bundle[Tuple[str, str]] # database to tenant it belongs to + tenant_to_database_to_model: Dict[ + str, Dict[str, Dict[str, Optional[types.CollectionMetadata]]] + ] + admin_client: AdminAPI + curr_tenant: str + curr_database: str + + tenants = Bundle("tenants") + databases = Bundle("databases") + + def __init__(self, client: Client): + super().__init__(client) + self.api = client + self.admin_client = AdminClient.from_system(client._system) + + @initialize() + def initialize(self) -> None: + self.api.reset() + self.tenant_to_database_to_model = {} + self.curr_tenant = DEFAULT_TENANT + self.curr_database = DEFAULT_DATABASE + self.api.set_tenant(DEFAULT_TENANT, DEFAULT_DATABASE) + self.tenant_to_database_to_model[self.curr_tenant] = {} + self.tenant_to_database_to_model[self.curr_tenant][self.curr_database] = {} + + @rule(target=tenants, name=strategies.tenant_database_name) + def create_tenant(self, name: str) -> MultipleResults[str]: + # Check if tenant already exists + if name in self.tenant_to_database_to_model: + with pytest.raises(Exception): + self.admin_client.create_tenant(name) + return multiple() + + self.admin_client.create_tenant(name) + # When we create a tenant, create a default database for it just for testing + # since the state machine could call collection operations before creating a + # database + self.admin_client.create_database(DEFAULT_DATABASE, tenant=name) + self.tenant_to_database_to_model[name] = {} + self.tenant_to_database_to_model[name][DEFAULT_DATABASE] = {} + return multiple(name) + + @rule(target=databases, name=strategies.tenant_database_name) + def create_database(self, name: str) -> MultipleResults[Tuple[str, str]]: + # If database already exists in current tenant, raise an error + if name in self.tenant_to_database_to_model[self.curr_tenant]: + with pytest.raises(Exception): + self.admin_client.create_database(name, tenant=self.curr_tenant) + return multiple() + + self.admin_client.create_database(name, tenant=self.curr_tenant) + self.tenant_to_database_to_model[self.curr_tenant][name] = {} + return multiple((name, self.curr_tenant)) + + @rule(database=databases) + def set_database_and_tenant(self, database: Tuple[str, str]) -> None: + # Get a database and switch to the database and the tenant it belongs to + database_name = database[0] + tenant_name = database[1] + self.api.set_tenant(tenant_name, database_name) + self.curr_database = database_name + self.curr_tenant = tenant_name + + @rule(tenant=tenants) + def set_tenant(self, tenant: str) -> None: + self.api.set_tenant(tenant, DEFAULT_DATABASE) + self.curr_tenant = tenant + self.curr_database = DEFAULT_DATABASE + + @property + def model(self) -> Dict[str, Optional[types.CollectionMetadata]]: + return self.tenant_to_database_to_model[self.curr_tenant][self.curr_database] + + +def test_collections(caplog: pytest.LogCaptureFixture, client: Client) -> None: + caplog.set_level(logging.ERROR) + run_state_machine_as_test(lambda: TenantDatabaseCollectionStateMachine(client)) # type: ignore diff --git a/chromadb/test/property/test_cross_version_persist.py b/chromadb/test/property/test_cross_version_persist.py new file mode 100644 index 0000000000000000000000000000000000000000..82bfc5f7cda0f57d78645124e8b9492f2fa589ca --- /dev/null +++ b/chromadb/test/property/test_cross_version_persist.py @@ -0,0 +1,326 @@ +from multiprocessing.connection import Connection +import sys +import os +import shutil +import subprocess +import tempfile +from types import ModuleType +from typing import Generator, List, Tuple, Dict, Any, Callable, Type +from hypothesis import given, settings +import hypothesis.strategies as st +import pytest +import json +from urllib import request +from chromadb import config +from chromadb.api import ServerAPI +from chromadb.api.types import Documents, EmbeddingFunction, Embeddings +import chromadb.test.property.strategies as strategies +import chromadb.test.property.invariants as invariants +from packaging import version as packaging_version +import re +import multiprocessing +from chromadb.config import Settings + +MINIMUM_VERSION = "0.4.1" +version_re = re.compile(r"^[0-9]+\.[0-9]+\.[0-9]+$") + +# Some modules do not work across versions, since we upgrade our support for them, and should be explicitly reimported in the subprocess +VERSIONED_MODULES = ["pydantic"] + + +def versions() -> List[str]: + """Returns the pinned minimum version and the latest version of chromadb.""" + url = "https://pypi.org/pypi/chromadb/json" + data = json.load(request.urlopen(request.Request(url))) + versions = list(data["releases"].keys()) + # Older versions on pypi contain "devXYZ" suffixes + versions = [v for v in versions if version_re.match(v)] + versions.sort(key=packaging_version.Version) + return [MINIMUM_VERSION, versions[-1]] + + +def _bool_to_int(metadata: Dict[str, Any]) -> Dict[str, Any]: + metadata.update((k, 1) for k, v in metadata.items() if v is True) + metadata.update((k, 0) for k, v in metadata.items() if v is False) + return metadata + + +def _patch_boolean_metadata( + collection: strategies.Collection, + embeddings: strategies.RecordSet, + settings: Settings, +) -> None: + # Since the old version does not support boolean value metadata, we will convert + # boolean value metadata to int + collection_metadata = collection.metadata + if collection_metadata is not None: + _bool_to_int(collection_metadata) # type: ignore + + if embeddings["metadatas"] is not None: + if isinstance(embeddings["metadatas"], list): + for metadata in embeddings["metadatas"]: + if metadata is not None and isinstance(metadata, dict): + _bool_to_int(metadata) + elif isinstance(embeddings["metadatas"], dict): + metadata = embeddings["metadatas"] + _bool_to_int(metadata) + + +def _patch_telemetry_client( + collection: strategies.Collection, + embeddings: strategies.RecordSet, + settings: Settings, +) -> None: + # chroma 0.4.14 added OpenTelemetry, distinct from ProductTelemetry. Before 0.4.14 + # ProductTelemetry was simply called Telemetry. + settings.chroma_telemetry_impl = "chromadb.telemetry.posthog.Posthog" + + +version_patches: List[ + Tuple[str, Callable[[strategies.Collection, strategies.RecordSet, Settings], None]] +] = [ + ("0.4.3", _patch_boolean_metadata), + ("0.4.14", _patch_telemetry_client), +] + + +def patch_for_version( + version: str, + collection: strategies.Collection, + embeddings: strategies.RecordSet, + settings: Settings, +) -> None: + """Override aspects of the collection and embeddings, before testing, to account for + breaking changes in old versions.""" + + for patch_version, patch in version_patches: + if packaging_version.Version(version) <= packaging_version.Version( + patch_version + ): + patch(collection, embeddings, settings) + + +def api_import_for_version(module: Any, version: str) -> Type: # type: ignore + if packaging_version.Version(version) <= packaging_version.Version("0.4.14"): + return module.api.API # type: ignore + return module.api.ServerAPI # type: ignore + + +def configurations(versions: List[str]) -> List[Tuple[str, Settings]]: + return [ + ( + version, + Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + allow_reset=True, + is_persistent=True, + persist_directory=tempfile.gettempdir() + "/persistence_test_chromadb", + ), + ) + for version in versions + ] + + +test_old_versions = versions() +base_install_dir = tempfile.gettempdir() + "/persistence_test_chromadb_versions" + + +# This fixture is not shared with the rest of the tests because it is unique in how it +# installs the versions of chromadb +@pytest.fixture(scope="module", params=configurations(test_old_versions)) # type: ignore +def version_settings(request) -> Generator[Tuple[str, Settings], None, None]: + configuration = request.param + version = configuration[0] + install_version(version) + yield configuration + # Cleanup the installed version + path = get_path_to_version_install(version) + shutil.rmtree(path) + # Cleanup the persisted data + data_path = configuration[1].persist_directory + if os.path.exists(data_path): + shutil.rmtree(data_path, ignore_errors=True) + + +def get_path_to_version_install(version: str) -> str: + return base_install_dir + "/" + version + + +def get_path_to_version_library(version: str) -> str: + return get_path_to_version_install(version) + "/chromadb/__init__.py" + + +def install_version(version: str) -> None: + # Check if already installed + version_library = get_path_to_version_library(version) + if os.path.exists(version_library): + return + path = get_path_to_version_install(version) + install(f"chromadb=={version}", path) + + +def install(pkg: str, path: str) -> int: + # -q -q to suppress pip output to ERROR level + # https://pip.pypa.io/en/stable/cli/pip/#quiet + print(f"Installing chromadb version {pkg} to {path}") + return subprocess.check_call( + [ + sys.executable, + "-m", + "pip", + "-q", + "-q", + "install", + pkg, + "--target={}".format(path), + ] + ) + + +def switch_to_version(version: str) -> ModuleType: + module_name = "chromadb" + # Remove old version from sys.modules, except test modules + old_modules = { + n: m + for n, m in sys.modules.items() + if n == module_name + or (n.startswith(module_name + ".")) + or n in VERSIONED_MODULES + or (any(n.startswith(m + ".") for m in VERSIONED_MODULES)) + } + for n in old_modules: + del sys.modules[n] + + # Load the target version and override the path to the installed version + # https://docs.python.org/3/library/importlib.html#importing-a-source-file-directly + sys.path.insert(0, get_path_to_version_install(version)) + import chromadb + + assert chromadb.__version__ == version + return chromadb + + +class not_implemented_ef(EmbeddingFunction[Documents]): + def __call__(self, input: Documents) -> Embeddings: + assert False, "Embedding function should not be called" + + +def persist_generated_data_with_old_version( + version: str, + settings: Settings, + collection_strategy: strategies.Collection, + embeddings_strategy: strategies.RecordSet, + conn: Connection, +) -> None: + try: + old_module = switch_to_version(version) + system = old_module.config.System(settings) + api = system.instance(api_import_for_version(old_module, version)) + system.start() + + api.reset() + coll = api.create_collection( + name=collection_strategy.name, + metadata=collection_strategy.metadata, + # In order to test old versions, we can't rely on the not_implemented function + embedding_function=not_implemented_ef(), + ) + coll.add(**embeddings_strategy) + + # Just use some basic checks for sanity and manual testing where you break the new + # version + + check_embeddings = invariants.wrap_all(embeddings_strategy) + # Check count + assert coll.count() == len(check_embeddings["embeddings"] or []) + # Check ids + result = coll.get() + actual_ids = result["ids"] + embedding_id_to_index = {id: i for i, id in enumerate(check_embeddings["ids"])} + actual_ids = sorted(actual_ids, key=lambda id: embedding_id_to_index[id]) + assert actual_ids == check_embeddings["ids"] + # Shutdown system + system.stop() + except Exception as e: + conn.send(e) + raise e + + +# Since we can't pickle the embedding function, we always generate record sets with embeddings +collection_st: st.SearchStrategy[strategies.Collection] = st.shared( + strategies.collections(with_hnsw_params=True, has_embeddings=True), key="coll" +) + + +@given( + collection_strategy=collection_st, + embeddings_strategy=strategies.recordsets(collection_st), +) +@settings(deadline=None) +def test_cycle_versions( + version_settings: Tuple[str, Settings], + collection_strategy: strategies.Collection, + embeddings_strategy: strategies.RecordSet, +) -> None: + # Test backwards compatibility + # For the current version, ensure that we can load a collection from + # the previous versions + version, settings = version_settings + # The strategies can generate metadatas of malformed inputs. Other tests + # will error check and cover these cases to make sure they error. Here we + # just convert them to valid values since the error cases are already tested + if embeddings_strategy["metadatas"] == {}: + embeddings_strategy["metadatas"] = None + if embeddings_strategy["metadatas"] is not None and isinstance( + embeddings_strategy["metadatas"], list + ): + embeddings_strategy["metadatas"] = [ + m if m is None or len(m) > 0 else None # type: ignore + for m in embeddings_strategy["metadatas"] + ] + + patch_for_version(version, collection_strategy, embeddings_strategy, settings) + + # Can't pickle a function, and we won't need them + collection_strategy.embedding_function = None + collection_strategy.known_metadata_keys = {} + + # Run the task in a separate process to avoid polluting the current process + # with the old version. Using spawn instead of fork to avoid sharing the + # current process memory which would cause the old version to be loaded + ctx = multiprocessing.get_context("spawn") + conn1, conn2 = multiprocessing.Pipe() + p = ctx.Process( + target=persist_generated_data_with_old_version, + args=(version, settings, collection_strategy, embeddings_strategy, conn2), + ) + p.start() + p.join() + + if conn1.poll(): + e = conn1.recv() + raise e + + p.close() + + # Switch to the current version (local working directory) and check the invariants + # are preserved for the collection + system = config.System(settings) + api = system.instance(ServerAPI) + system.start() + coll = api.get_collection( + name=collection_strategy.name, + embedding_function=not_implemented_ef(), # type: ignore + ) + invariants.count(coll, embeddings_strategy) + invariants.metadatas_match(coll, embeddings_strategy) + invariants.documents_match(coll, embeddings_strategy) + invariants.ids_match(coll, embeddings_strategy) + invariants.ann_accuracy(coll, embeddings_strategy) + + # Shutdown system + system.stop() diff --git a/chromadb/test/property/test_embeddings.py b/chromadb/test/property/test_embeddings.py new file mode 100644 index 0000000000000000000000000000000000000000..bf3e882184ff3330a7a29caab11dff987617998f --- /dev/null +++ b/chromadb/test/property/test_embeddings.py @@ -0,0 +1,464 @@ +import pytest +import logging +import hypothesis.strategies as st +from hypothesis import given +from typing import Dict, Set, cast, Union, DefaultDict, Any, List +from dataclasses import dataclass +from chromadb.api.types import ID, Include, IDs, validate_embeddings +import chromadb.errors as errors +from chromadb.api import ServerAPI +from chromadb.api.models.Collection import Collection +import chromadb.test.property.strategies as strategies +from hypothesis.stateful import ( + Bundle, + RuleBasedStateMachine, + MultipleResults, + rule, + initialize, + precondition, + consumes, + run_state_machine_as_test, + multiple, + invariant, +) +from collections import defaultdict +import chromadb.test.property.invariants as invariants +import numpy as np + + +traces: DefaultDict[str, int] = defaultdict(lambda: 0) + + +def trace(key: str) -> None: + global traces + traces[key] += 1 + + +def print_traces() -> None: + global traces + for key, value in traces.items(): + print(f"{key}: {value}") + + +dtype_shared_st: st.SearchStrategy[ + Union[np.float16, np.float32, np.float64] +] = st.shared(st.sampled_from(strategies.float_types), key="dtype") + +dimension_shared_st: st.SearchStrategy[int] = st.shared( + st.integers(min_value=2, max_value=2048), key="dimension" +) + + +@dataclass +class EmbeddingStateMachineStates: + initialize = "initialize" + add_embeddings = "add_embeddings" + delete_by_ids = "delete_by_ids" + update_embeddings = "update_embeddings" + upsert_embeddings = "upsert_embeddings" + + +collection_st = st.shared(strategies.collections(with_hnsw_params=True), key="coll") + + +class EmbeddingStateMachine(RuleBasedStateMachine): + collection: Collection + embedding_ids: Bundle[ID] = Bundle("embedding_ids") + + def __init__(self, api: ServerAPI): + super().__init__() + self.api = api + self._rules_strategy = strategies.DeterministicRuleStrategy(self) # type: ignore + + @initialize(collection=collection_st) # type: ignore + def initialize(self, collection: strategies.Collection): + self.api.reset() + self.collection = self.api.create_collection( + name=collection.name, + metadata=collection.metadata, + embedding_function=collection.embedding_function, + ) + self.embedding_function = collection.embedding_function + trace("init") + self.on_state_change(EmbeddingStateMachineStates.initialize) + + self.record_set_state = strategies.StateMachineRecordSet( + ids=[], metadatas=[], documents=[], embeddings=[] + ) + + @rule(target=embedding_ids, record_set=strategies.recordsets(collection_st)) + def add_embeddings(self, record_set: strategies.RecordSet) -> MultipleResults[ID]: + trace("add_embeddings") + self.on_state_change(EmbeddingStateMachineStates.add_embeddings) + + normalized_record_set: strategies.NormalizedRecordSet = invariants.wrap_all( + record_set + ) + + if len(normalized_record_set["ids"]) > 0: + trace("add_more_embeddings") + + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + self.collection.add(**normalized_record_set) + return multiple() + + intersection = set(normalized_record_set["ids"]).intersection( + self.record_set_state["ids"] + ) + if len(intersection) > 0: + # Partially apply the non-duplicative records to the state + new_ids = list(set(normalized_record_set["ids"]).difference(intersection)) + indices = [normalized_record_set["ids"].index(id) for id in new_ids] + filtered_record_set: strategies.NormalizedRecordSet = { + "ids": [normalized_record_set["ids"][i] for i in indices], + "metadatas": [normalized_record_set["metadatas"][i] for i in indices] + if normalized_record_set["metadatas"] + else None, + "documents": [normalized_record_set["documents"][i] for i in indices] + if normalized_record_set["documents"] + else None, + "embeddings": [normalized_record_set["embeddings"][i] for i in indices] + if normalized_record_set["embeddings"] + else None, + } + self.collection.add(**normalized_record_set) + self._upsert_embeddings(cast(strategies.RecordSet, filtered_record_set)) + return multiple(*filtered_record_set["ids"]) + + else: + self.collection.add(**normalized_record_set) + self._upsert_embeddings(cast(strategies.RecordSet, normalized_record_set)) + return multiple(*normalized_record_set["ids"]) + + @precondition(lambda self: len(self.record_set_state["ids"]) > 20) + @rule(ids=st.lists(consumes(embedding_ids), min_size=1, max_size=20)) + def delete_by_ids(self, ids: IDs) -> None: + trace("remove embeddings") + self.on_state_change(EmbeddingStateMachineStates.delete_by_ids) + indices_to_remove = [self.record_set_state["ids"].index(id) for id in ids] + + self.collection.delete(ids=ids) + self._remove_embeddings(set(indices_to_remove)) + + # Removing the precondition causes the tests to frequently fail as "unsatisfiable" + # Using a value < 5 causes retries and lowers the number of valid samples + @precondition(lambda self: len(self.record_set_state["ids"]) >= 5) + @rule( + record_set=strategies.recordsets( + collection_strategy=collection_st, + id_strategy=embedding_ids, + min_size=1, + max_size=5, + ) + ) + def update_embeddings(self, record_set: strategies.RecordSet) -> None: + trace("update embeddings") + self.on_state_change(EmbeddingStateMachineStates.update_embeddings) + + normalized_record_set: strategies.NormalizedRecordSet = invariants.wrap_all( + record_set + ) + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + self.collection.update(**normalized_record_set) + return + + self.collection.update(**record_set) + self._upsert_embeddings(record_set) + + # Using a value < 3 causes more retries and lowers the number of valid samples + @precondition(lambda self: len(self.record_set_state["ids"]) >= 3) + @rule( + record_set=strategies.recordsets( + collection_strategy=collection_st, + id_strategy=st.one_of(embedding_ids, strategies.safe_text), + min_size=1, + max_size=5, + ) + ) + def upsert_embeddings(self, record_set: strategies.RecordSet) -> None: + trace("upsert embeddings") + self.on_state_change(EmbeddingStateMachineStates.upsert_embeddings) + + normalized_record_set: strategies.NormalizedRecordSet = invariants.wrap_all( + record_set + ) + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + self.collection.upsert(**normalized_record_set) + return + + self.collection.upsert(**record_set) + self._upsert_embeddings(record_set) + + @invariant() + def count(self) -> None: + invariants.count( + self.collection, cast(strategies.RecordSet, self.record_set_state) + ) + + @invariant() + def no_duplicates(self) -> None: + invariants.no_duplicates(self.collection) + + @invariant() + def ann_accuracy(self) -> None: + invariants.ann_accuracy( + collection=self.collection, + record_set=cast(strategies.RecordSet, self.record_set_state), + min_recall=0.95, + embedding_function=self.embedding_function, + ) + + @invariant() + def fields_match(self) -> None: + self.record_set_state = cast(strategies.RecordSet, self.record_set_state) + invariants.embeddings_match(self.collection, self.record_set_state) + invariants.metadatas_match(self.collection, self.record_set_state) + invariants.documents_match(self.collection, self.record_set_state) + + def _upsert_embeddings(self, record_set: strategies.RecordSet) -> None: + normalized_record_set: strategies.NormalizedRecordSet = invariants.wrap_all( + record_set + ) + for idx, id in enumerate(normalized_record_set["ids"]): + # Update path + if id in self.record_set_state["ids"]: + target_idx = self.record_set_state["ids"].index(id) + if normalized_record_set["embeddings"] is not None: + self.record_set_state["embeddings"][ + target_idx + ] = normalized_record_set["embeddings"][idx] + else: + assert normalized_record_set["documents"] is not None + assert self.embedding_function is not None + self.record_set_state["embeddings"][ + target_idx + ] = self.embedding_function( + [normalized_record_set["documents"][idx]] + )[ + 0 + ] + if normalized_record_set["metadatas"] is not None: + # Sqlite merges the metadata, as opposed to old + # implementations which overwrites it + record_set_state = self.record_set_state["metadatas"][target_idx] + if record_set_state is not None: + record_set_state = cast( + Dict[str, Union[str, int, float]], record_set_state + ) + record_set_state.update(normalized_record_set["metadatas"][idx]) + if normalized_record_set["documents"] is not None: + self.record_set_state["documents"][ + target_idx + ] = normalized_record_set["documents"][idx] + else: + # Add path + self.record_set_state["ids"].append(id) + if normalized_record_set["embeddings"] is not None: + self.record_set_state["embeddings"].append( + normalized_record_set["embeddings"][idx] + ) + else: + assert self.embedding_function is not None + assert normalized_record_set["documents"] is not None + self.record_set_state["embeddings"].append( + self.embedding_function( + [normalized_record_set["documents"][idx]] + )[0] + ) + if normalized_record_set["metadatas"] is not None: + self.record_set_state["metadatas"].append( + normalized_record_set["metadatas"][idx] + ) + else: + self.record_set_state["metadatas"].append(None) + if normalized_record_set["documents"] is not None: + self.record_set_state["documents"].append( + normalized_record_set["documents"][idx] + ) + else: + self.record_set_state["documents"].append(None) + + def _remove_embeddings(self, indices_to_remove: Set[int]) -> None: + indices_list = list(indices_to_remove) + indices_list.sort(reverse=True) + + for i in indices_list: + del self.record_set_state["ids"][i] + del self.record_set_state["embeddings"][i] + del self.record_set_state["metadatas"][i] + del self.record_set_state["documents"][i] + + def on_state_change(self, new_state: str) -> None: + pass + + +def test_embeddings_state(caplog: pytest.LogCaptureFixture, api: ServerAPI) -> None: + caplog.set_level(logging.ERROR) + run_state_machine_as_test(lambda: EmbeddingStateMachine(api)) # type: ignore + print_traces() + + +def test_multi_add(api: ServerAPI) -> None: + api.reset() + coll = api.create_collection(name="foo") + coll.add(ids=["a"], embeddings=[[0.0]]) + assert coll.count() == 1 + + # after the sqlite refactor - add silently ignores duplicates, no exception is raised + # partial adds are supported - i.e we will add whatever we can in the request + coll.add(ids=["a"], embeddings=[[0.0]]) + + assert coll.count() == 1 + + results = coll.get() + assert results["ids"] == ["a"] + + coll.delete(ids=["a"]) + assert coll.count() == 0 + + +def test_dup_add(api: ServerAPI) -> None: + api.reset() + coll = api.create_collection(name="foo") + with pytest.raises(errors.DuplicateIDError): + coll.add(ids=["a", "a"], embeddings=[[0.0], [1.1]]) + with pytest.raises(errors.DuplicateIDError): + coll.upsert(ids=["a", "a"], embeddings=[[0.0], [1.1]]) + + +def test_query_without_add(api: ServerAPI) -> None: + api.reset() + coll = api.create_collection(name="foo") + fields: Include = ["documents", "metadatas", "embeddings", "distances"] + N = np.random.randint(1, 2000) + K = np.random.randint(1, 100) + results = coll.query( + query_embeddings=np.random.random((N, K)).tolist(), include=fields + ) + for field in fields: + field_results = results[field] + assert field_results is not None + assert all([len(result) == 0 for result in field_results]) + + +def test_get_non_existent(api: ServerAPI) -> None: + api.reset() + coll = api.create_collection(name="foo") + result = coll.get(ids=["a"], include=["documents", "metadatas", "embeddings"]) + assert len(result["ids"]) == 0 + assert len(result["metadatas"]) == 0 + assert len(result["documents"]) == 0 + assert len(result["embeddings"]) == 0 + + +# TODO: Use SQL escaping correctly internally +@pytest.mark.xfail(reason="We don't properly escape SQL internally, causing problems") +def test_escape_chars_in_ids(api: ServerAPI) -> None: + api.reset() + id = "\x1f" + coll = api.create_collection(name="foo") + coll.add(ids=[id], embeddings=[[0.0]]) + assert coll.count() == 1 + coll.delete(ids=[id]) + assert coll.count() == 0 + + +@pytest.mark.parametrize( + "kwargs", + [ + {}, + {"ids": []}, + {"where": {}}, + {"where_document": {}}, + {"where_document": {}, "where": {}}, + ], +) +def test_delete_empty_fails(api: ServerAPI, kwargs: dict): + api.reset() + coll = api.create_collection(name="foo") + with pytest.raises(Exception) as e: + coll.delete(**kwargs) + assert "You must provide either ids, where, or where_document to delete." in str(e) + + +@pytest.mark.parametrize( + "kwargs", + [ + {"ids": ["foo"]}, + {"where": {"foo": "bar"}}, + {"where_document": {"$contains": "bar"}}, + {"ids": ["foo"], "where": {"foo": "bar"}}, + {"ids": ["foo"], "where_document": {"$contains": "bar"}}, + { + "ids": ["foo"], + "where": {"foo": "bar"}, + "where_document": {"$contains": "bar"}, + }, + ], +) +def test_delete_success(api: ServerAPI, kwargs: dict): + api.reset() + coll = api.create_collection(name="foo") + # Should not raise + coll.delete(**kwargs) + + +@given(supported_types=st.sampled_from([np.float32, np.int32, np.int64, int, float])) +def test_autocasting_validate_embeddings_for_compatible_types( + supported_types: List[Any], +) -> None: + embds = strategies.create_embeddings(10, 10, supported_types) + validated_embeddings = validate_embeddings(Collection._normalize_embeddings(embds)) + assert all( + [ + isinstance(value, list) + and all( + [ + isinstance(vec, (int, float)) and not isinstance(vec, bool) + for vec in value + ] + ) + for value in validated_embeddings + ] + ) + + +@given(supported_types=st.sampled_from([np.float32, np.int32, np.int64, int, float])) +def test_autocasting_validate_embeddings_with_ndarray( + supported_types: List[Any], +) -> None: + embds = strategies.create_embeddings_ndarray(10, 10, supported_types) + validated_embeddings = validate_embeddings(Collection._normalize_embeddings(embds)) + assert all( + [ + isinstance(value, list) + and all( + [ + isinstance(vec, (int, float)) and not isinstance(vec, bool) + for vec in value + ] + ) + for value in validated_embeddings + ] + ) + + +@given(unsupported_types=st.sampled_from([str, bool])) +def test_autocasting_validate_embeddings_incompatible_types( + unsupported_types: List[Any], +) -> None: + embds = strategies.create_embeddings(10, 10, unsupported_types) + with pytest.raises(ValueError) as e: + validate_embeddings(Collection._normalize_embeddings(embds)) + + assert "Expected each value in the embedding to be a int or float" in str(e) + + +def test_0dim_embedding_validation() -> None: + embds = [[]] + with pytest.raises(ValueError) as e: + validate_embeddings(embds) + assert "Expected each embedding in the embeddings to be a non-empty list" in str(e) \ No newline at end of file diff --git a/chromadb/test/property/test_filtering.py b/chromadb/test/property/test_filtering.py new file mode 100644 index 0000000000000000000000000000000000000000..9129c023df7dfa982bf992bcd7d41070ffcc6cdf --- /dev/null +++ b/chromadb/test/property/test_filtering.py @@ -0,0 +1,394 @@ +from typing import Any, Dict, List, cast +from hypothesis import given, settings, HealthCheck +import pytest +from chromadb.api import ServerAPI +from chromadb.test.property import invariants +from chromadb.api.types import ( + Document, + Embedding, + Embeddings, + GetResult, + IDs, + Metadata, + Metadatas, + Where, + WhereDocument, +) +import chromadb.test.property.strategies as strategies +import hypothesis.strategies as st +import logging +import random +import re + + +def _filter_where_clause(clause: Where, metadata: Metadata) -> bool: + """Return true if the where clause is true for the given metadata map""" + + key, expr = list(clause.items())[0] + + # Handle the shorthand for equal: {key: val} where val is a simple value + if ( + isinstance(expr, str) + or isinstance(expr, bool) + or isinstance(expr, int) + or isinstance(expr, float) + ): + return _filter_where_clause({key: {"$eq": expr}}, metadata) + + # expr is a list of clauses + if key == "$and": + assert isinstance(expr, list) + return all(_filter_where_clause(clause, metadata) for clause in expr) + + if key == "$or": + assert isinstance(expr, list) + return any(_filter_where_clause(clause, metadata) for clause in expr) + if key == "$in": + assert isinstance(expr, list) + return metadata[key] in expr if key in metadata else False + if key == "$nin": + assert isinstance(expr, list) + return metadata[key] not in expr + + # expr is an operator expression + assert isinstance(expr, dict) + op, val = list(expr.items())[0] + assert isinstance(metadata, dict) + if key not in metadata: + return False + metadata_key = metadata[key] + if op == "$eq": + return key in metadata and metadata_key == val + elif op == "$ne": + return key in metadata and metadata_key != val + elif op == "$in": + return key in metadata and metadata_key in val + elif op == "$nin": + return key in metadata and metadata_key not in val + + # The following conditions only make sense for numeric values + assert isinstance(metadata_key, int) or isinstance(metadata_key, float) + assert isinstance(val, int) or isinstance(val, float) + if op == "$gt": + return (key in metadata) and (metadata_key > val) + elif op == "$gte": + return key in metadata and metadata_key >= val + elif op == "$lt": + return key in metadata and metadata_key < val + elif op == "$lte": + return key in metadata and metadata_key <= val + else: + raise ValueError("Unknown operator: {}".format(key)) + + +def _filter_where_doc_clause(clause: WhereDocument, doc: Document) -> bool: + key, expr = list(clause.items())[0] + + if key == "$and": + assert isinstance(expr, list) + return all(_filter_where_doc_clause(clause, doc) for clause in expr) + if key == "$or": + assert isinstance(expr, list) + return any(_filter_where_doc_clause(clause, doc) for clause in expr) + + # Simple $contains clause + assert isinstance(expr, str) + if key == "$contains": + if not doc: + return False + # SQLite FTS handles % and _ as word boundaries that are ignored so we need to + # treat them as wildcards + if "%" in expr or "_" in expr: + expr = expr.replace("%", ".").replace("_", ".") + return re.search(expr, doc) is not None + return expr in doc + elif key == "$not_contains": + if not doc: + return False + # SQLite FTS handles % and _ as word boundaries that are ignored so we need to + # treat them as wildcards + if "%" in expr or "_" in expr: + expr = expr.replace("%", ".").replace("_", ".") + return re.search(expr, doc) is None + return expr not in doc + else: + raise ValueError("Unknown operator: {}".format(key)) + + +EMPTY_DICT: Dict[Any, Any] = {} +EMPTY_STRING: str = "" + + +def _filter_embedding_set( + record_set: strategies.RecordSet, filter: strategies.Filter +) -> IDs: + """Return IDs from the embedding set that match the given filter object""" + + normalized_record_set = invariants.wrap_all(record_set) + ids = set(normalized_record_set["ids"]) + + filter_ids = filter["ids"] + + if filter_ids is not None: + filter_ids = invariants.wrap(filter_ids) + assert filter_ids is not None + # If the filter ids is an empty list then we treat that as get all + if len(filter_ids) != 0: + ids = ids.intersection(filter_ids) + + for i in range(len(normalized_record_set["ids"])): + if filter["where"]: + metadatas: Metadatas + if isinstance(normalized_record_set["metadatas"], list): + metadatas = normalized_record_set["metadatas"] + else: + metadatas = [EMPTY_DICT] * len(normalized_record_set["ids"]) + filter_where: Where = filter["where"] + if not _filter_where_clause(filter_where, metadatas[i]): + ids.discard(normalized_record_set["ids"][i]) + + if filter["where_document"]: + documents = normalized_record_set["documents"] or [EMPTY_STRING] * len( + normalized_record_set["ids"] + ) + if not _filter_where_doc_clause(filter["where_document"], documents[i]): + ids.discard(normalized_record_set["ids"][i]) + + return list(ids) + + +collection_st = st.shared( + strategies.collections(add_filterable_data=True, with_hnsw_params=True), + key="coll", +) +recordset_st = st.shared( + strategies.recordsets(collection_st, max_size=1000), key="recordset" +) + + +@settings( + suppress_health_check=[ + HealthCheck.function_scoped_fixture, + HealthCheck.large_base_example, + ] +) # type: ignore +@given( + collection=collection_st, + record_set=recordset_st, + filters=st.lists(strategies.filters(collection_st, recordset_st), min_size=1), +) +def test_filterable_metadata_get( + caplog, api: ServerAPI, collection: strategies.Collection, record_set, filters +) -> None: + caplog.set_level(logging.ERROR) + + api.reset() + coll = api.create_collection( + name=collection.name, + metadata=collection.metadata, # type: ignore + embedding_function=collection.embedding_function, + ) + + if not invariants.is_metadata_valid(invariants.wrap_all(record_set)): + with pytest.raises(Exception): + coll.add(**record_set) + return + + coll.add(**record_set) + for filter in filters: + result_ids = coll.get(**filter)["ids"] + expected_ids = _filter_embedding_set(record_set, filter) + assert sorted(result_ids) == sorted(expected_ids) + + +@settings( + suppress_health_check=[ + HealthCheck.function_scoped_fixture, + HealthCheck.large_base_example, + ] +) # type: ignore +@given( + collection=collection_st, + record_set=recordset_st, + filters=st.lists(strategies.filters(collection_st, recordset_st), min_size=1), + limit=st.integers(min_value=1, max_value=10), + offset=st.integers(min_value=0, max_value=10), +) +def test_filterable_metadata_get_limit_offset( + caplog, + api: ServerAPI, + collection: strategies.Collection, + record_set, + filters, + limit, + offset, +) -> None: + caplog.set_level(logging.ERROR) + + api.reset() + coll = api.create_collection( + name=collection.name, + metadata=collection.metadata, # type: ignore + embedding_function=collection.embedding_function, + ) + + if not invariants.is_metadata_valid(invariants.wrap_all(record_set)): + with pytest.raises(Exception): + coll.add(**record_set) + return + + coll.add(**record_set) + for filter in filters: + # add limit and offset to filter + filter["limit"] = limit + filter["offset"] = offset + result_ids = coll.get(**filter)["ids"] + expected_ids = _filter_embedding_set(record_set, filter) + assert sorted(result_ids) == sorted(expected_ids)[offset : offset + limit] + + +@settings( + suppress_health_check=[ + HealthCheck.function_scoped_fixture, + HealthCheck.large_base_example, + ] +) +@given( + collection=collection_st, + record_set=recordset_st, + filters=st.lists( + strategies.filters(collection_st, recordset_st, include_all_ids=True), + min_size=1, + ), +) +def test_filterable_metadata_query( + caplog: pytest.LogCaptureFixture, + api: ServerAPI, + collection: strategies.Collection, + record_set: strategies.RecordSet, + filters: List[strategies.Filter], +) -> None: + caplog.set_level(logging.ERROR) + + api.reset() + coll = api.create_collection( + name=collection.name, + metadata=collection.metadata, # type: ignore + embedding_function=collection.embedding_function, + ) + normalized_record_set = invariants.wrap_all(record_set) + + if not invariants.is_metadata_valid(normalized_record_set): + with pytest.raises(Exception): + coll.add(**record_set) + return + + coll.add(**record_set) + total_count = len(normalized_record_set["ids"]) + # Pick a random vector + random_query: Embedding + if collection.has_embeddings: + assert normalized_record_set["embeddings"] is not None + assert all(isinstance(e, list) for e in normalized_record_set["embeddings"]) + random_query = normalized_record_set["embeddings"][ + random.randint(0, total_count - 1) + ] + else: + assert isinstance(normalized_record_set["documents"], list) + assert collection.embedding_function is not None + random_query = collection.embedding_function( + [normalized_record_set["documents"][random.randint(0, total_count - 1)]] + )[0] + for filter in filters: + result_ids = set( + coll.query( + query_embeddings=random_query, + n_results=total_count, + where=filter["where"], + where_document=filter["where_document"], + )["ids"][0] + ) + expected_ids = set( + _filter_embedding_set( + cast(strategies.RecordSet, normalized_record_set), filter + ) + ) + assert len(result_ids.intersection(expected_ids)) == len(result_ids) + + +def test_empty_filter(api: ServerAPI) -> None: + """Test that a filter where no document matches returns an empty result""" + api.reset() + coll = api.create_collection(name="test") + + test_ids: IDs = ["1", "2", "3"] + test_embeddings: Embeddings = [[1, 1], [2, 2], [3, 3]] + test_query_embedding: Embedding = [1, 2] + test_query_embeddings: Embeddings = [test_query_embedding, test_query_embedding] + + coll.add(ids=test_ids, embeddings=test_embeddings) + + res = coll.query( + query_embeddings=test_query_embedding, + where={"q": {"$eq": 4}}, + n_results=3, + include=["embeddings", "distances", "metadatas"], + ) + assert res["ids"] == [[]] + assert res["embeddings"] == [[]] + assert res["distances"] == [[]] + assert res["metadatas"] == [[]] + + res = coll.query( + query_embeddings=test_query_embeddings, + where={"test": "yes"}, + n_results=3, + ) + assert res["ids"] == [[], []] + assert res["embeddings"] is None + assert res["distances"] == [[], []] + assert res["metadatas"] == [[], []] + + +def test_boolean_metadata(api: ServerAPI) -> None: + """Test that metadata with boolean values is correctly filtered""" + api.reset() + coll = api.create_collection(name="test") + + test_ids: IDs = ["1", "2", "3"] + test_embeddings: Embeddings = [[1, 1], [2, 2], [3, 3]] + test_metadatas: Metadatas = [{"test": True}, {"test": False}, {"test": True}] + + coll.add(ids=test_ids, embeddings=test_embeddings, metadatas=test_metadatas) + + res = coll.get(where={"test": True}) + + assert res["ids"] == ["1", "3"] + + +def test_get_empty(api: ServerAPI) -> None: + """Tests that calling get() with empty filters returns nothing""" + + api.reset() + coll = api.create_collection(name="test") + + test_ids: IDs = ["1", "2", "3"] + test_embeddings: Embeddings = [[1, 1], [2, 2], [3, 3]] + test_metadatas: Metadatas = [{"test": 10}, {"test": 20}, {"test": 30}] + + def check_empty_res(res: GetResult) -> None: + assert len(res["ids"]) == 0 + assert res["embeddings"] is not None + assert len(res["embeddings"]) == 0 + assert res["documents"] is not None + assert len(res["documents"]) == 0 + assert res["metadatas"] is not None + + coll.add(ids=test_ids, embeddings=test_embeddings, metadatas=test_metadatas) + + res = coll.get(ids=["nope"], include=["embeddings", "metadatas", "documents"]) + check_empty_res(res) + res = coll.get( + include=["embeddings", "metadatas", "documents"], where={"test": 100} + ) + check_empty_res(res) diff --git a/chromadb/test/property/test_persist.py b/chromadb/test/property/test_persist.py new file mode 100644 index 0000000000000000000000000000000000000000..e7b1f7017d12d50ad41e21330bfa9929ed4e7bb6 --- /dev/null +++ b/chromadb/test/property/test_persist.py @@ -0,0 +1,227 @@ +import logging +import multiprocessing +from multiprocessing.connection import Connection +from typing import Generator, Callable +from hypothesis import given +import hypothesis.strategies as st +import pytest +import chromadb +from chromadb.api import ClientAPI, ServerAPI +from chromadb.config import Settings, System +import chromadb.test.property.strategies as strategies +import chromadb.test.property.invariants as invariants +from chromadb.test.property.test_embeddings import ( + EmbeddingStateMachine, + EmbeddingStateMachineStates, + collection_st as embedding_collection_st, + trace, +) +from hypothesis.stateful import ( + run_state_machine_as_test, + rule, + precondition, + initialize, +) +import os +import shutil +import tempfile + +CreatePersistAPI = Callable[[], ServerAPI] + +configurations = [ + Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + allow_reset=True, + is_persistent=True, + persist_directory=tempfile.mkdtemp(), + ), +] + + +@pytest.fixture(scope="module", params=configurations) +def settings(request: pytest.FixtureRequest) -> Generator[Settings, None, None]: + configuration = request.param + save_path = configuration.persist_directory + # Create if it doesn't exist + if not os.path.exists(save_path): + os.makedirs(save_path, exist_ok=True) + yield configuration + # Remove if it exists + if os.path.exists(save_path): + shutil.rmtree(save_path, ignore_errors=True) + + +collection_st = st.shared( + strategies.collections(with_hnsw_params=True, with_persistent_hnsw_params=True), + key="coll", +) + + +@given( + collection_strategy=collection_st, + embeddings_strategy=strategies.recordsets(collection_st), +) +def test_persist( + settings: Settings, + collection_strategy: strategies.Collection, + embeddings_strategy: strategies.RecordSet, +) -> None: + system_1 = System(settings) + api_1 = system_1.instance(ServerAPI) + system_1.start() + + api_1.reset() + coll = api_1.create_collection( + name=collection_strategy.name, + metadata=collection_strategy.metadata, + embedding_function=collection_strategy.embedding_function, + ) + + if not invariants.is_metadata_valid(invariants.wrap_all(embeddings_strategy)): + with pytest.raises(Exception): + coll.add(**embeddings_strategy) + return + + coll.add(**embeddings_strategy) + + invariants.count(coll, embeddings_strategy) + invariants.metadatas_match(coll, embeddings_strategy) + invariants.documents_match(coll, embeddings_strategy) + invariants.ids_match(coll, embeddings_strategy) + invariants.ann_accuracy( + coll, + embeddings_strategy, + embedding_function=collection_strategy.embedding_function, + ) + + system_1.stop() + del api_1 + del system_1 + + system_2 = System(settings) + api_2 = system_2.instance(ServerAPI) + system_2.start() + + coll = api_2.get_collection( + name=collection_strategy.name, + embedding_function=collection_strategy.embedding_function, + ) + invariants.count(coll, embeddings_strategy) + invariants.metadatas_match(coll, embeddings_strategy) + invariants.documents_match(coll, embeddings_strategy) + invariants.ids_match(coll, embeddings_strategy) + invariants.ann_accuracy( + coll, + embeddings_strategy, + embedding_function=collection_strategy.embedding_function, + ) + + system_2.stop() + del api_2 + del system_2 + + +def load_and_check( + settings: Settings, + collection_name: str, + record_set: strategies.RecordSet, + conn: Connection, +) -> None: + try: + system = System(settings) + api = system.instance(ServerAPI) + system.start() + + coll = api.get_collection( + name=collection_name, + embedding_function=strategies.not_implemented_embedding_function(), + ) + invariants.count(coll, record_set) + invariants.metadatas_match(coll, record_set) + invariants.documents_match(coll, record_set) + invariants.ids_match(coll, record_set) + invariants.ann_accuracy(coll, record_set) + + system.stop() + except Exception as e: + conn.send(e) + raise e + + +class PersistEmbeddingsStateMachineStates(EmbeddingStateMachineStates): + persist = "persist" + + +class PersistEmbeddingsStateMachine(EmbeddingStateMachine): + def __init__(self, api: ClientAPI, settings: Settings): + self.api = api + self.settings = settings + self.last_persist_delay = 10 + self.api.reset() + super().__init__(self.api) + + @initialize(collection=embedding_collection_st, batch_size=st.integers(min_value=3, max_value=2000), sync_threshold=st.integers(min_value=3, max_value=2000)) # type: ignore + def initialize( + self, collection: strategies.Collection, batch_size: int, sync_threshold: int + ): + self.api.reset() + self.collection = self.api.create_collection( + name=collection.name, + metadata=collection.metadata, + embedding_function=collection.embedding_function, + ) + self.embedding_function = collection.embedding_function + trace("init") + self.on_state_change(EmbeddingStateMachineStates.initialize) + + self.record_set_state = strategies.StateMachineRecordSet( + ids=[], metadatas=[], documents=[], embeddings=[] + ) + + @precondition( + lambda self: len(self.record_set_state["ids"]) >= 1 + and self.last_persist_delay <= 0 + ) + @rule() + def persist(self) -> None: + self.on_state_change(PersistEmbeddingsStateMachineStates.persist) + collection_name = self.collection.name + # Create a new process and then inside the process run the invariants + # TODO: Once we switch off of duckdb and onto sqlite we can remove this + ctx = multiprocessing.get_context("spawn") + conn1, conn2 = multiprocessing.Pipe() + p = ctx.Process( + target=load_and_check, + args=(self.settings, collection_name, self.record_set_state, conn2), + ) + p.start() + p.join() + + if conn1.poll(): + e = conn1.recv() + raise e + + p.close() + + def on_state_change(self, new_state: str) -> None: + if new_state == PersistEmbeddingsStateMachineStates.persist: + self.last_persist_delay = 10 + else: + self.last_persist_delay -= 1 + + def teardown(self) -> None: + self.api.reset() + + +def test_persist_embeddings_state( + caplog: pytest.LogCaptureFixture, settings: Settings +) -> None: + caplog.set_level(logging.ERROR) + api = chromadb.Client(settings) + run_state_machine_as_test( + lambda: PersistEmbeddingsStateMachine(settings=settings, api=api) + ) # type: ignore diff --git a/chromadb/test/property/test_segment_manager.py b/chromadb/test/property/test_segment_manager.py new file mode 100644 index 0000000000000000000000000000000000000000..ff5e057dff4cc8de1d4ef0d602efd6f90d6a8da0 --- /dev/null +++ b/chromadb/test/property/test_segment_manager.py @@ -0,0 +1,128 @@ +import uuid + +import pytest +import chromadb.test.property.strategies as strategies +from unittest.mock import patch +from dataclasses import asdict +import random +from hypothesis.stateful import ( + Bundle, + RuleBasedStateMachine, + rule, + initialize, + multiple, + precondition, + invariant, + run_state_machine_as_test, + MultipleResults, +) +from typing import Dict +from chromadb.segment import ( + VectorReader +) +from chromadb.segment import SegmentManager + +from chromadb.segment.impl.manager.local import LocalSegmentManager +from chromadb.types import SegmentScope +from chromadb.db.system import SysDB +from chromadb.config import System, get_class + +# Memory limit use for testing +memory_limit = 100 + +# Helper class to keep tract of the last use id +class LastUse: + def __init__(self, n: int): + self.n = n + self.store = [] + + def add(self, id: uuid.UUID): + if id in self.store: + self.store.remove(id) + self.store.append(id) + else: + self.store.append(id) + while len(self.store) > self.n: + self.store.pop(0) + return self.store + + def reset(self): + self.store = [] + + +class SegmentManagerStateMachine(RuleBasedStateMachine): + collections: Bundle[strategies.Collection] + collections = Bundle("collections") + collection_size_store: Dict[uuid.UUID, int] = {} + segment_collection: Dict[uuid.UUID, uuid.UUID] = {} + + def __init__(self, system: System): + super().__init__() + self.segment_manager = system.require(SegmentManager) + self.segment_manager.start() + self.segment_manager.reset_state() + self.last_use = LastUse(n=40) + self.collection_created_counter = 0 + self.sysdb = system.require(SysDB) + self.system = system + + @invariant() + def last_queried_segments_should_be_in_cache(self): + cache_sum = 0 + index = 0 + for id in reversed(self.last_use.store): + cache_sum += self.collection_size_store[id] + if cache_sum >= memory_limit and index is not 0: + break + assert id in self.segment_manager.segment_cache[SegmentScope.VECTOR].cache + index += 1 + + @invariant() + @precondition(lambda self: self.system.settings.is_persistent is True) + def cache_should_not_be_bigger_than_settings(self): + segment_sizes = {id: self.collection_size_store[id] for id in self.segment_manager.segment_cache[SegmentScope.VECTOR].cache} + total_size = sum(segment_sizes.values()) + if len(segment_sizes) != 1: + assert total_size <= memory_limit + + @initialize() + def initialize(self) -> None: + self.segment_manager.reset_state() + self.segment_manager.start() + self.collection_created_counter = 0 + self.last_use.reset() + + @rule(target=collections, coll=strategies.collections()) + @precondition(lambda self: self.collection_created_counter <= 50) + def create_segment( + self, coll: strategies.Collection + ) -> MultipleResults[strategies.Collection]: + segments = self.segment_manager.create_segments(asdict(coll)) + for segment in segments: + self.sysdb.create_segment(segment) + self.segment_collection[segment["id"]] = coll.id + self.collection_created_counter += 1 + self.collection_size_store[coll.id] = random.randint(0, memory_limit) + return multiple(coll) + + @rule(coll=collections) + def get_segment(self, coll: strategies.Collection) -> None: + segment = self.segment_manager.get_segment(collection_id=coll.id, type=VectorReader) + self.last_use.add(coll.id) + assert segment is not None + + + @staticmethod + def mock_directory_size(directory: str): + path_id = directory.split("/").pop() + collection_id = SegmentManagerStateMachine.segment_collection[uuid.UUID(path_id)] + return SegmentManagerStateMachine.collection_size_store[collection_id] + + +@patch('chromadb.segment.impl.manager.local.get_directory_size', SegmentManagerStateMachine.mock_directory_size) +def test_segment_manager(caplog: pytest.LogCaptureFixture, system: System) -> None: + system.settings.chroma_memory_limit_bytes = memory_limit + system.settings.chroma_segment_cache_policy = "LRU" + + run_state_machine_as_test( + lambda: SegmentManagerStateMachine(system=system)) diff --git a/chromadb/test/segment/distributed/test_memberlist_provider.py b/chromadb/test/segment/distributed/test_memberlist_provider.py new file mode 100644 index 0000000000000000000000000000000000000000..4acb2b224dcf45f1671e9556104cfb9d71440c7b --- /dev/null +++ b/chromadb/test/segment/distributed/test_memberlist_provider.py @@ -0,0 +1,112 @@ +# Tests the CustomResourceMemberlist provider +import threading +from chromadb.test.conftest import skip_if_not_cluster +from kubernetes import client, config +from chromadb.config import System, Settings +from chromadb.segment.distributed import Memberlist +from chromadb.segment.impl.distributed.segment_directory import ( + CustomResourceMemberlistProvider, + KUBERNETES_GROUP, + KUBERNETES_NAMESPACE, +) +import time + + +# Used for testing to update the memberlist CRD +def update_memberlist(n: int, memberlist_name: str = "test-memberlist") -> Memberlist: + config.load_config() + api_instance = client.CustomObjectsApi() + + members = [{"url": f"10.0.0.{i}"} for i in range(1, n + 1)] + + body = { + "kind": "MemberList", + "metadata": {"name": memberlist_name}, + "spec": {"members": members}, + } + + _ = api_instance.patch_namespaced_custom_object( + group=KUBERNETES_GROUP, + version="v1", + namespace=KUBERNETES_NAMESPACE, + plural="memberlists", + name=memberlist_name, + body=body, + ) + + return [m["url"] for m in members] + + +def compare_memberlists(m1: Memberlist, m2: Memberlist) -> bool: + return sorted(m1) == sorted(m2) + + +@skip_if_not_cluster() +def test_can_get_memberlist() -> None: + # This test assumes that the memberlist CRD is already created with the name "test-memberlist" + system = System(Settings(allow_reset=True)) + provider = system.instance(CustomResourceMemberlistProvider) + provider.set_memberlist_name("test-memberlist") + system.reset_state() + system.start() + + # Update the memberlist + members = update_memberlist(3) + + # Check that the memberlist is updated after a short delay + time.sleep(2) + assert compare_memberlists(provider.get_memberlist(), members) + + system.stop() + + +@skip_if_not_cluster() +def test_can_update_memberlist_multiple_times() -> None: + # This test assumes that the memberlist CRD is already created with the name "test-memberlist" + system = System(Settings(allow_reset=True)) + provider = system.instance(CustomResourceMemberlistProvider) + provider.set_memberlist_name("test-memberlist") + system.reset_state() + system.start() + + # Update the memberlist + members = update_memberlist(3) + + # Check that the memberlist is updated after a short delay + time.sleep(2) + assert compare_memberlists(provider.get_memberlist(), members) + + # Update the memberlist again + members = update_memberlist(5) + + # Check that the memberlist is updated after a short delay + time.sleep(2) + assert compare_memberlists(provider.get_memberlist(), members) + + system.stop() + + +@skip_if_not_cluster() +def test_stop_memberlist_kills_thread() -> None: + # This test assumes that the memberlist CRD is already created with the name "test-memberlist" + system = System(Settings(allow_reset=True)) + provider = system.instance(CustomResourceMemberlistProvider) + provider.set_memberlist_name("test-memberlist") + system.reset_state() + system.start() + + # Make sure a background thread is running + assert len(threading.enumerate()) == 2 + + # Update the memberlist + members = update_memberlist(3) + + # Check that the memberlist is updated after a short delay + time.sleep(2) + assert compare_memberlists(provider.get_memberlist(), members) + + # Stop the system + system.stop() + + # Check to make sure only one thread is running + assert len(threading.enumerate()) == 1 diff --git a/chromadb/test/segment/distributed/test_rendezvous_hash.py b/chromadb/test/segment/distributed/test_rendezvous_hash.py new file mode 100644 index 0000000000000000000000000000000000000000..922ff61c97b989431bd1cb795b8c9e9a0b732fc9 --- /dev/null +++ b/chromadb/test/segment/distributed/test_rendezvous_hash.py @@ -0,0 +1,30 @@ +from chromadb.utils.rendezvous_hash import assign, murmur3hasher + + +def test_rendezvous_hash() -> None: + # Tests the assign works as expected + members = ["a", "b", "c"] + key = "key" + + def mock_hasher(member: str, key: str) -> int: + return members.index(member) # Highest index wins + + assert assign(key, members, mock_hasher) == "c" + + +def test_even_distribution() -> None: + member_count = 10 + tolerance = 25 + nodes = [str(i) for i in range(member_count)] + + # Test if keys are evenly distributed across nodes + key_distribution = {node: 0 for node in nodes} + num_keys = 1000 + for i in range(num_keys): + key = f"key_{i}" + node = assign(key, nodes, murmur3hasher) + key_distribution[node] += 1 + + # Check if keys are somewhat evenly distributed + for node in nodes: + assert abs(key_distribution[node] - num_keys / len(nodes)) < tolerance diff --git a/chromadb/test/segment/test_metadata.py b/chromadb/test/segment/test_metadata.py new file mode 100644 index 0000000000000000000000000000000000000000..1f03d6350f48b4350ef9c02a6e6cb21563823c88 --- /dev/null +++ b/chromadb/test/segment/test_metadata.py @@ -0,0 +1,679 @@ +import os +import shutil +import tempfile +import pytest +from typing import Generator, List, Callable, Iterator, Dict, Optional, Union, Sequence +from chromadb.config import System, Settings +from chromadb.db.base import ParameterValue, get_sql +from chromadb.db.impl.sqlite import SqliteDB +from chromadb.test.conftest import ProducerFn +from chromadb.types import ( + SubmitEmbeddingRecord, + MetadataEmbeddingRecord, + Operation, + ScalarEncoding, + Segment, + SegmentScope, + SeqId, +) +from pypika import Table +from chromadb.ingest import Producer +from chromadb.segment import MetadataReader +import uuid +import time + +from chromadb.segment.impl.metadata.sqlite import SqliteMetadataSegment + +from pytest import FixtureRequest +from itertools import count + + +def sqlite() -> Generator[System, None, None]: + """Fixture generator for sqlite DB""" + settings = Settings(allow_reset=True, is_persistent=False) + system = System(settings) + system.start() + yield system + system.stop() + + +def sqlite_persistent() -> Generator[System, None, None]: + """Fixture generator for sqlite DB""" + save_path = tempfile.mkdtemp() + settings = Settings( + allow_reset=True, is_persistent=True, persist_directory=save_path + ) + system = System(settings) + system.start() + yield system + system.stop() + if os.path.exists(save_path): + shutil.rmtree(save_path) + + +def system_fixtures() -> List[Callable[[], Generator[System, None, None]]]: + return [sqlite, sqlite_persistent] + + +@pytest.fixture(scope="module", params=system_fixtures()) +def system(request: FixtureRequest) -> Generator[System, None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="function") +def sample_embeddings() -> Iterator[SubmitEmbeddingRecord]: + def create_record(i: int) -> SubmitEmbeddingRecord: + vector = [i + i * 0.1, i + 1 + i * 0.1] + metadata: Optional[Dict[str, Union[str, int, float, bool]]] + if i == 0: + metadata = None + else: + metadata = { + "str_key": f"value_{i}", + "int_key": i, + "float_key": i + i * 0.1, + "bool_key": True, + } + if i % 3 == 0: + metadata["div_by_three"] = "true" + if i % 2 == 0: + metadata["bool_key"] = False + metadata["chroma:document"] = _build_document(i) + + record = SubmitEmbeddingRecord( + id=f"embedding_{i}", + embedding=vector, + encoding=ScalarEncoding.FLOAT32, + metadata=metadata, + operation=Operation.ADD, + collection_id=uuid.UUID(int=0), + ) + return record + + return (create_record(i) for i in count()) + + +_digit_map = { + "0": "zero", + "1": "one", + "2": "two", + "3": "three", + "4": "four", + "5": "five", + "6": "six", + "7": "seven", + "8": "eight", + "9": "nine", +} + + +def _build_document(i: int) -> str: + digits = list(str(i)) + return " ".join(_digit_map[d] for d in digits) + + +segment_definition = Segment( + id=uuid.uuid4(), + type="test_type", + scope=SegmentScope.METADATA, + topic="persistent://test/test/test_topic_1", + collection=None, + metadata=None, +) + +segment_definition2 = Segment( + id=uuid.uuid4(), + type="test_type", + scope=SegmentScope.METADATA, + topic="persistent://test/test/test_topic_2", + collection=None, + metadata=None, +) + + +def sync(segment: MetadataReader, seq_id: SeqId) -> None: + # Try for up to 5 seconds, then throw a TimeoutError + start = time.time() + while time.time() - start < 5: + if segment.max_seqid() >= seq_id: + return + time.sleep(0.25) + raise TimeoutError(f"Timed out waiting for seq_id {seq_id}") + + +def test_insert_and_count( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + + topic = str(segment_definition["topic"]) + + max_id = produce_fns(producer, topic, sample_embeddings, 3)[1][-1] + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + sync(segment, max_id) + + assert segment.count() == 3 + + for i in range(3): + max_id = producer.submit_embedding(topic, next(sample_embeddings)) + + sync(segment, max_id) + + assert segment.count() == 6 + + +def assert_equiv_records( + expected: Sequence[SubmitEmbeddingRecord], actual: Sequence[MetadataEmbeddingRecord] +) -> None: + assert len(expected) == len(actual) + sorted_expected = sorted(expected, key=lambda r: r["id"]) + sorted_actual = sorted(actual, key=lambda r: r["id"]) + for e, a in zip(sorted_expected, sorted_actual): + assert e["id"] == a["id"] + assert e["metadata"] == a["metadata"] + + +def test_get( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + topic = str(segment_definition["topic"]) + + embeddings, seq_ids = produce_fns(producer, topic, sample_embeddings, 10) + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + sync(segment, seq_ids[-1]) + + # get with bool key + result = segment.get_metadata(where={"bool_key": True}) + assert len(result) == 5 + + result = segment.get_metadata(where={"bool_key": False}) + assert len(result) == 4 + + # Get all records + results = segment.get_metadata() + assert seq_ids == [r["seq_id"] for r in results] + assert_equiv_records(embeddings, results) + + # get by ID + result = segment.get_metadata(ids=[e["id"] for e in embeddings[0:5]]) + assert_equiv_records(embeddings[0:5], result) + + # Get with limit and offset + # Cannot rely on order(yet), but can rely on retrieving exactly the + # whole set eventually + ret: List[MetadataEmbeddingRecord] = [] + ret.extend(segment.get_metadata(limit=3)) + assert len(ret) == 3 + ret.extend(segment.get_metadata(limit=3, offset=3)) + assert len(ret) == 6 + ret.extend(segment.get_metadata(limit=3, offset=6)) + assert len(ret) == 9 + ret.extend(segment.get_metadata(limit=3, offset=9)) + assert len(ret) == 10 + assert_equiv_records(embeddings, ret) + + # Get with simple where + result = segment.get_metadata(where={"div_by_three": "true"}) + assert len(result) == 3 + + # Get with gt/gte/lt/lte on int keys + result = segment.get_metadata(where={"int_key": {"$gt": 5}}) + assert len(result) == 4 + result = segment.get_metadata(where={"int_key": {"$gte": 5}}) + assert len(result) == 5 + result = segment.get_metadata(where={"int_key": {"$lt": 5}}) + assert len(result) == 4 + result = segment.get_metadata(where={"int_key": {"$lte": 5}}) + assert len(result) == 5 + + # Get with gt/lt on float keys with float values + result = segment.get_metadata(where={"float_key": {"$gt": 5.01}}) + assert len(result) == 5 + result = segment.get_metadata(where={"float_key": {"$lt": 4.99}}) + assert len(result) == 4 + + # Get with gt/lt on float keys with int values + result = segment.get_metadata(where={"float_key": {"$gt": 5}}) + assert len(result) == 5 + result = segment.get_metadata(where={"float_key": {"$lt": 5}}) + assert len(result) == 4 + + # Get with gt/lt on int keys with float values + result = segment.get_metadata(where={"int_key": {"$gt": 5.01}}) + assert len(result) == 4 + result = segment.get_metadata(where={"int_key": {"$lt": 4.99}}) + assert len(result) == 4 + + # Get with $ne + # Returns metadata that has an int_key, but not equal to 5 + result = segment.get_metadata(where={"int_key": {"$ne": 5}}) + assert len(result) == 8 + + # get with multiple heterogenous conditions + result = segment.get_metadata(where={"div_by_three": "true", "int_key": {"$gt": 5}}) + assert len(result) == 2 + + # get with OR conditions + result = segment.get_metadata(where={"$or": [{"int_key": 1}, {"int_key": 2}]}) + assert len(result) == 2 + + # get with AND conditions + result = segment.get_metadata( + where={"$and": [{"int_key": 3}, {"float_key": {"$gt": 5}}]} + ) + assert len(result) == 0 + result = segment.get_metadata( + where={"$and": [{"int_key": 3}, {"float_key": {"$lt": 5}}]} + ) + assert len(result) == 1 + + +def test_fulltext( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + topic = str(segment_definition["topic"]) + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + max_id = produce_fns(producer, topic, sample_embeddings, 100)[1][-1] + + sync(segment, max_id) + + result = segment.get_metadata(where={"chroma:document": "four two"}) + result2 = segment.get_metadata(ids=["embedding_42"]) + assert result == result2 + + # Test single result + result = segment.get_metadata(where_document={"$contains": "four two"}) + assert len(result) == 1 + + # Test not_contains + result = segment.get_metadata(where_document={"$not_contains": "four two"}) + assert len(result) == len( + [i for i in range(1, 100) if "four two" not in _build_document(i)] + ) + + # Test many results + result = segment.get_metadata(where_document={"$contains": "zero"}) + assert len(result) == 9 + + # Test not_contains + result = segment.get_metadata(where_document={"$not_contains": "zero"}) + assert len(result) == len( + [i for i in range(1, 100) if "zero" not in _build_document(i)] + ) + + # test $and + result = segment.get_metadata( + where_document={"$and": [{"$contains": "four"}, {"$contains": "two"}]} + ) + assert len(result) == 2 + assert set([r["id"] for r in result]) == {"embedding_42", "embedding_24"} + + result = segment.get_metadata( + where_document={"$and": [{"$not_contains": "four"}, {"$not_contains": "two"}]} + ) + assert len(result) == len( + [ + i + for i in range(1, 100) + if "four" not in _build_document(i) and "two" not in _build_document(i) + ] + ) + + # test $or + result = segment.get_metadata( + where_document={"$or": [{"$contains": "zero"}, {"$contains": "one"}]} + ) + ones = [i for i in range(1, 100) if "one" in _build_document(i)] + zeros = [i for i in range(1, 100) if "zero" in _build_document(i)] + expected = set([f"embedding_{i}" for i in set(ones + zeros)]) + assert set([r["id"] for r in result]) == expected + + result = segment.get_metadata( + where_document={"$or": [{"$not_contains": "zero"}, {"$not_contains": "one"}]} + ) + assert len(result) == len( + [ + i + for i in range(1, 100) + if "zero" not in _build_document(i) or "one" not in _build_document(i) + ] + ) + + # test combo with where clause (negative case) + result = segment.get_metadata( + where={"int_key": {"$eq": 42}}, where_document={"$contains": "zero"} + ) + assert len(result) == 0 + + # test combo with where clause (positive case) + result = segment.get_metadata( + where={"int_key": {"$eq": 42}}, where_document={"$contains": "four"} + ) + assert len(result) == 1 + + # test partial words + result = segment.get_metadata(where_document={"$contains": "zer"}) + assert len(result) == 9 + + +def test_delete( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + topic = str(segment_definition["topic"]) + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns(producer, topic, sample_embeddings, 10) + max_id = seq_ids[-1] + + sync(segment, max_id) + + assert segment.count() == 10 + results = segment.get_metadata(ids=["embedding_0"]) + assert_equiv_records(embeddings[:1], results) + + # Delete by ID + delete_embedding = SubmitEmbeddingRecord( + id="embedding_0", + embedding=None, + encoding=None, + metadata=None, + operation=Operation.DELETE, + collection_id=uuid.UUID(int=0), + ) + max_id = produce_fns(producer, topic, (delete_embedding for _ in range(1)), 1)[1][ + -1 + ] + + sync(segment, max_id) + + assert segment.count() == 9 + assert segment.get_metadata(ids=["embedding_0"]) == [] + + # Delete is idempotent + max_id = produce_fns(producer, topic, (delete_embedding for _ in range(1)), 1)[1][ + -1 + ] + + sync(segment, max_id) + assert segment.count() == 9 + assert segment.get_metadata(ids=["embedding_0"]) == [] + + # re-add + max_id = producer.submit_embedding(topic, embeddings[0]) + sync(segment, max_id) + assert segment.count() == 10 + results = segment.get_metadata(ids=["embedding_0"]) + + +def test_update( + system: System, sample_embeddings: Iterator[SubmitEmbeddingRecord] +) -> None: + producer = system.instance(Producer) + system.reset_state() + topic = str(segment_definition["topic"]) + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + _test_update(sample_embeddings, producer, segment, topic, Operation.UPDATE) + + # Update nonexisting ID + update_record = SubmitEmbeddingRecord( + id="no_such_id", + metadata={"foo": "bar"}, + embedding=None, + encoding=None, + operation=Operation.UPDATE, + collection_id=uuid.UUID(int=0), + ) + max_id = producer.submit_embedding(topic, update_record) + sync(segment, max_id) + results = segment.get_metadata(ids=["no_such_id"]) + assert len(results) == 0 + assert segment.count() == 3 + + +def test_upsert( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + topic = str(segment_definition["topic"]) + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + _test_update(sample_embeddings, producer, segment, topic, Operation.UPSERT) + + # upsert previously nonexisting ID + update_record = SubmitEmbeddingRecord( + id="no_such_id", + metadata={"foo": "bar"}, + embedding=None, + encoding=None, + operation=Operation.UPSERT, + collection_id=uuid.UUID(int=0), + ) + max_id = produce_fns( + producer=producer, + topic=topic, + embeddings=(update_record for _ in range(1)), + n=1, + )[1][-1] + sync(segment, max_id) + results = segment.get_metadata(ids=["no_such_id"]) + assert results[0]["metadata"] == {"foo": "bar"} + + +def _test_update( + sample_embeddings: Iterator[SubmitEmbeddingRecord], + producer: Producer, + segment: MetadataReader, + topic: str, + op: Operation, +) -> None: + """test code common between update and upsert paths""" + + embeddings = [next(sample_embeddings) for i in range(3)] + + max_id = 0 + for e in embeddings: + max_id = producer.submit_embedding(topic, e) + + sync(segment, max_id) + + results = segment.get_metadata(ids=["embedding_0"]) + assert_equiv_records(embeddings[:1], results) + + # Update embedding with no metadata + update_record = SubmitEmbeddingRecord( + id="embedding_0", + metadata={"chroma:document": "foo bar"}, + embedding=None, + encoding=None, + operation=op, + collection_id=uuid.UUID(int=0), + ) + max_id = producer.submit_embedding(topic, update_record) + sync(segment, max_id) + results = segment.get_metadata(ids=["embedding_0"]) + assert results[0]["metadata"] == {"chroma:document": "foo bar"} + results = segment.get_metadata(where_document={"$contains": "foo"}) + assert results[0]["metadata"] == {"chroma:document": "foo bar"} + + # Update and overrwrite key + update_record = SubmitEmbeddingRecord( + id="embedding_0", + metadata={"chroma:document": "biz buz"}, + embedding=None, + encoding=None, + operation=op, + collection_id=uuid.UUID(int=0), + ) + max_id = producer.submit_embedding(topic, update_record) + sync(segment, max_id) + results = segment.get_metadata(ids=["embedding_0"]) + assert results[0]["metadata"] == {"chroma:document": "biz buz"} + results = segment.get_metadata(where_document={"$contains": "biz"}) + assert results[0]["metadata"] == {"chroma:document": "biz buz"} + results = segment.get_metadata(where_document={"$contains": "foo"}) + assert len(results) == 0 + + # Update and add key + update_record = SubmitEmbeddingRecord( + id="embedding_0", + metadata={"baz": 42}, + embedding=None, + encoding=None, + operation=op, + collection_id=uuid.UUID(int=0), + ) + max_id = producer.submit_embedding(topic, update_record) + sync(segment, max_id) + results = segment.get_metadata(ids=["embedding_0"]) + assert results[0]["metadata"] == {"chroma:document": "biz buz", "baz": 42} + + # Update and delete key + update_record = SubmitEmbeddingRecord( + id="embedding_0", + metadata={"chroma:document": None}, + embedding=None, + encoding=None, + operation=op, + collection_id=uuid.UUID(int=0), + ) + max_id = producer.submit_embedding(topic, update_record) + sync(segment, max_id) + results = segment.get_metadata(ids=["embedding_0"]) + assert results[0]["metadata"] == {"baz": 42} + results = segment.get_metadata(where_document={"$contains": "biz"}) + assert len(results) == 0 + + +def test_limit( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + + topic = str(segment_definition["topic"]) + max_id = produce_fns(producer, topic, sample_embeddings, 3)[1][-1] + + topic2 = str(segment_definition2["topic"]) + max_id2 = produce_fns(producer, topic2, sample_embeddings, 3)[1][-1] + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + segment2 = SqliteMetadataSegment(system, segment_definition2) + segment2.start() + + sync(segment, max_id) + sync(segment2, max_id2) + + assert segment.count() == 3 + + for i in range(3): + max_id = producer.submit_embedding(topic, next(sample_embeddings)) + + sync(segment, max_id) + + assert segment.count() == 6 + + res = segment.get_metadata(limit=3) + assert len(res) == 3 + + # if limit is negative, throw error + with pytest.raises(ValueError): + segment.get_metadata(limit=-1) + + # if offset is more than number of results, return empty list + res = segment.get_metadata(limit=3, offset=10) + assert len(res) == 0 + + +def test_delete_segment( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + topic = str(segment_definition["topic"]) + + segment = SqliteMetadataSegment(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns(producer, topic, sample_embeddings, 10) + max_id = seq_ids[-1] + + sync(segment, max_id) + + assert segment.count() == 10 + results = segment.get_metadata(ids=["embedding_0"]) + assert_equiv_records(embeddings[:1], results) + _id = segment._id + segment.delete() + _db = system.instance(SqliteDB) + t = Table("embeddings") + q = ( + _db.querybuilder() + .from_(t) + .select(t.id) + .where(t.segment_id == ParameterValue(_db.uuid_to_db(_id))) + ) + sql, params = get_sql(q) + with _db.tx() as cur: + res = cur.execute(sql, params) + # assert that the segment is gone + assert len(res.fetchall()) == 0 + + fts_t = Table("embedding_fulltext_search") + q_fts = ( + _db.querybuilder() + .from_(fts_t) + .select() + .where( + fts_t.rowid.isin( + _db.querybuilder() + .from_(t) + .select(t.id) + .where(t.segment_id == ParameterValue(_db.uuid_to_db(_id))) + ) + ) + ) + sql, params = get_sql(q_fts) + with _db.tx() as cur: + res = cur.execute(sql, params) + # assert that all FTS rows are gone + assert len(res.fetchall()) == 0 diff --git a/chromadb/test/segment/test_vector.py b/chromadb/test/segment/test_vector.py new file mode 100644 index 0000000000000000000000000000000000000000..1ba9802c66fd57e4983e59b7df4d6986fc5a07c3 --- /dev/null +++ b/chromadb/test/segment/test_vector.py @@ -0,0 +1,676 @@ +import pytest +from typing import Generator, List, Callable, Iterator, Type, cast +from chromadb.config import System, Settings +from chromadb.test.conftest import ProducerFn +from chromadb.types import ( + SubmitEmbeddingRecord, + VectorQuery, + Operation, + ScalarEncoding, + Segment, + SegmentScope, + SeqId, + Vector, +) +from chromadb.ingest import Producer +from chromadb.segment import VectorReader +import uuid +import time + +from chromadb.segment.impl.vector.local_hnsw import ( + LocalHnswSegment, +) + +from chromadb.segment.impl.vector.local_persistent_hnsw import ( + PersistentLocalHnswSegment, +) + +from chromadb.test.property.strategies import test_hnsw_config +from pytest import FixtureRequest +from itertools import count +import tempfile +import os +import shutil + + +def sqlite() -> Generator[System, None, None]: + """Fixture generator for sqlite DB""" + save_path = tempfile.mkdtemp() + settings = Settings( + allow_reset=True, + is_persistent=False, + persist_directory=save_path, + ) + system = System(settings) + system.start() + yield system + system.stop() + if os.path.exists(save_path): + shutil.rmtree(save_path) + + +def sqlite_persistent() -> Generator[System, None, None]: + """Fixture generator for sqlite DB""" + save_path = tempfile.mkdtemp() + settings = Settings( + allow_reset=True, + is_persistent=True, + persist_directory=save_path, + ) + system = System(settings) + system.start() + yield system + system.stop() + if os.path.exists(save_path): + shutil.rmtree(save_path) + + +# We will excercise in memory, persistent sqlite with both ephemeral and persistent hnsw. +# We technically never expose persitent sqlite with memory hnsw to users, but it's a valid +# configuration, so we test it here. +def system_fixtures() -> List[Callable[[], Generator[System, None, None]]]: + return [sqlite, sqlite_persistent] + + +@pytest.fixture(scope="module", params=system_fixtures()) +def system(request: FixtureRequest) -> Generator[System, None, None]: + yield next(request.param()) + + +@pytest.fixture(scope="function") +def sample_embeddings() -> Iterator[SubmitEmbeddingRecord]: + """Generate a sequence of embeddings with the property that for each embedding + (other than the first and last), it's nearest neighbor is the previous in the + sequence, and it's second nearest neighbor is the subsequent""" + + def create_record(i: int) -> SubmitEmbeddingRecord: + vector = [i**1.1, i**1.1] + record = SubmitEmbeddingRecord( + id=f"embedding_{i}", + embedding=vector, + encoding=ScalarEncoding.FLOAT32, + metadata=None, + operation=Operation.ADD, + collection_id=uuid.UUID(int=0), + ) + return record + + return (create_record(i) for i in count()) + + +def vector_readers() -> List[Type[VectorReader]]: + return [LocalHnswSegment, PersistentLocalHnswSegment] + + +@pytest.fixture(scope="module", params=vector_readers()) +def vector_reader(request: FixtureRequest) -> Generator[Type[VectorReader], None, None]: + yield request.param + + +def create_random_segment_definition() -> Segment: + return Segment( + id=uuid.uuid4(), + type="test_type", + scope=SegmentScope.VECTOR, + topic="persistent://test/test/test_topic_1", + collection=None, + metadata=test_hnsw_config, + ) + + +def sync(segment: VectorReader, seq_id: SeqId) -> None: + # Try for up to 5 seconds, then throw a TimeoutError + start = time.time() + while time.time() - start < 5: + if segment.max_seqid() >= seq_id: + return + time.sleep(0.25) + raise TimeoutError(f"Timed out waiting for seq_id {seq_id}") + + +def test_insert_and_count( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + max_id = produce_fns( + producer=producer, topic=topic, n=3, embeddings=sample_embeddings + )[1][-1] + + segment = vector_reader(system, segment_definition) + segment.start() + + sync(segment, max_id) + + assert segment.count() == 3 + + max_id = produce_fns( + producer=producer, topic=topic, n=3, embeddings=sample_embeddings + )[1][-1] + + sync(segment, max_id) + assert segment.count() == 6 + + +def approx_equal(a: float, b: float, epsilon: float = 0.0001) -> bool: + return abs(a - b) < epsilon + + +def approx_equal_vector(a: Vector, b: Vector, epsilon: float = 0.0001) -> bool: + return all(approx_equal(x, y, epsilon) for x, y in zip(a, b)) + + +def test_get_vectors( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns( + producer=producer, topic=topic, embeddings=sample_embeddings, n=10 + ) + + sync(segment, seq_ids[-1]) + + # Get all items + vectors = segment.get_vectors() + assert len(vectors) == len(embeddings) + vectors = sorted(vectors, key=lambda v: v["id"]) + for actual, expected, seq_id in zip(vectors, embeddings, seq_ids): + assert actual["id"] == expected["id"] + assert approx_equal_vector( + actual["embedding"], cast(Vector, expected["embedding"]) + ) + assert actual["seq_id"] == seq_id + + # Get selected IDs + ids = [e["id"] for e in embeddings[5:]] + vectors = segment.get_vectors(ids=ids) + assert len(vectors) == 5 + vectors = sorted(vectors, key=lambda v: v["id"]) + for actual, expected, seq_id in zip(vectors, embeddings[5:], seq_ids[5:]): + assert actual["id"] == expected["id"] + assert approx_equal_vector( + actual["embedding"], cast(Vector, expected["embedding"]) + ) + assert actual["seq_id"] == seq_id + + +def test_ann_query( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns( + producer=producer, topic=topic, embeddings=sample_embeddings, n=100 + ) + + sync(segment, seq_ids[-1]) + + # Each item is its own nearest neighbor (one at a time) + for e in embeddings: + vector = cast(Vector, e["embedding"]) + query = VectorQuery( + vectors=[vector], + k=1, + allowed_ids=None, + options=None, + include_embeddings=True, + ) + results = segment.query_vectors(query) + assert len(results) == 1 + assert len(results[0]) == 1 + assert results[0][0]["id"] == e["id"] + assert results[0][0]["embedding"] is not None + assert approx_equal_vector(results[0][0]["embedding"], vector) + + # Each item is its own nearest neighbor (all at once) + vectors = [cast(Vector, e["embedding"]) for e in embeddings] + query = VectorQuery( + vectors=vectors, k=1, allowed_ids=None, options=None, include_embeddings=False + ) + results = segment.query_vectors(query) + assert len(results) == len(embeddings) + for r, e in zip(results, embeddings): + assert len(r) == 1 + assert r[0]["id"] == e["id"] + + # Each item's 3 nearest neighbors are itself and the item before and after + test_embeddings = embeddings[1:-1] + vectors = [cast(Vector, e["embedding"]) for e in test_embeddings] + query = VectorQuery( + vectors=vectors, k=3, allowed_ids=None, options=None, include_embeddings=False + ) + results = segment.query_vectors(query) + assert len(results) == len(test_embeddings) + + for r, e, i in zip(results, test_embeddings, range(1, len(test_embeddings))): + assert len(r) == 3 + assert r[0]["id"] == embeddings[i]["id"] + assert r[1]["id"] == embeddings[i - 1]["id"] + assert r[2]["id"] == embeddings[i + 1]["id"] + + +def test_delete( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns( + producer=producer, topic=topic, embeddings=sample_embeddings, n=5 + ) + + sync(segment, seq_ids[-1]) + assert segment.count() == 5 + + delete_record = SubmitEmbeddingRecord( + id=embeddings[0]["id"], + embedding=None, + encoding=None, + metadata=None, + operation=Operation.DELETE, + collection_id=uuid.UUID(int=0), + ) + assert isinstance(seq_ids, List) + seq_ids.append( + produce_fns( + producer=producer, + topic=topic, + n=1, + embeddings=(delete_record for _ in range(1)), + )[1][0] + ) + + sync(segment, seq_ids[-1]) + + # Assert that the record is gone using `count` + assert segment.count() == 4 + + # Assert that the record is gone using `get` + assert segment.get_vectors(ids=[embeddings[0]["id"]]) == [] + results = segment.get_vectors() + assert len(results) == 4 + # get_vectors returns results in arbitrary order + results = sorted(results, key=lambda v: v["id"]) + for actual, expected in zip(results, embeddings[1:]): + assert actual["id"] == expected["id"] + assert approx_equal_vector( + actual["embedding"], cast(Vector, expected["embedding"]) + ) + + # Assert that the record is gone from KNN search + vector = cast(Vector, embeddings[0]["embedding"]) + query = VectorQuery( + vectors=[vector], k=10, allowed_ids=None, options=None, include_embeddings=False + ) + knn_results = segment.query_vectors(query) + assert len(results) == 4 + assert set(r["id"] for r in knn_results[0]) == set(e["id"] for e in embeddings[1:]) + + # Delete is idempotent + seq_ids.append( + produce_fns( + producer=producer, + topic=topic, + n=1, + embeddings=(delete_record for _ in range(1)), + )[1][0] + ) + + sync(segment, seq_ids[-1]) + + assert segment.count() == 4 + + +def _test_update( + producer: Producer, + topic: str, + segment: VectorReader, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + operation: Operation, +) -> None: + """Tests the common code paths between update & upsert""" + + embeddings = [next(sample_embeddings) for i in range(3)] + + seq_ids: List[SeqId] = [] + for e in embeddings: + seq_ids.append(producer.submit_embedding(topic, e)) + + sync(segment, seq_ids[-1]) + assert segment.count() == 3 + + seq_ids.append( + producer.submit_embedding( + topic, + SubmitEmbeddingRecord( + id=embeddings[0]["id"], + embedding=[10.0, 10.0], + encoding=ScalarEncoding.FLOAT32, + metadata=None, + operation=operation, + collection_id=uuid.UUID(int=0), + ), + ) + ) + + sync(segment, seq_ids[-1]) + + # Test new data from get_vectors + assert segment.count() == 3 + results = segment.get_vectors() + assert len(results) == 3 + results = segment.get_vectors(ids=[embeddings[0]["id"]]) + assert results[0]["embedding"] == [10.0, 10.0] + + # Test querying at the old location + vector = cast(Vector, embeddings[0]["embedding"]) + query = VectorQuery( + vectors=[vector], k=3, allowed_ids=None, options=None, include_embeddings=False + ) + knn_results = segment.query_vectors(query)[0] + assert knn_results[0]["id"] == embeddings[1]["id"] + assert knn_results[1]["id"] == embeddings[2]["id"] + assert knn_results[2]["id"] == embeddings[0]["id"] + + # Test querying at the new location + vector = [10.0, 10.0] + query = VectorQuery( + vectors=[vector], k=3, allowed_ids=None, options=None, include_embeddings=False + ) + knn_results = segment.query_vectors(query)[0] + assert knn_results[0]["id"] == embeddings[0]["id"] + assert knn_results[1]["id"] == embeddings[2]["id"] + assert knn_results[2]["id"] == embeddings[1]["id"] + + +def test_update( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + _test_update(producer, topic, segment, sample_embeddings, Operation.UPDATE) + + # test updating a nonexistent record + update_record = SubmitEmbeddingRecord( + id="no_such_record", + embedding=[10.0, 10.0], + encoding=ScalarEncoding.FLOAT32, + metadata=None, + operation=Operation.UPDATE, + collection_id=uuid.UUID(int=0), + ) + seq_id = produce_fns( + producer=producer, + topic=topic, + n=1, + embeddings=(update_record for _ in range(1)), + )[1][0] + + sync(segment, seq_id) + + assert segment.count() == 3 + assert segment.get_vectors(ids=["no_such_record"]) == [] + + +def test_upsert( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + _test_update(producer, topic, segment, sample_embeddings, Operation.UPSERT) + + # test updating a nonexistent record + upsert_record = SubmitEmbeddingRecord( + id="no_such_record", + embedding=[42, 42], + encoding=ScalarEncoding.FLOAT32, + metadata=None, + operation=Operation.UPSERT, + collection_id=uuid.UUID(int=0), + ) + seq_id = produce_fns( + producer=producer, + topic=topic, + n=1, + embeddings=(upsert_record for _ in range(1)), + )[1][0] + + sync(segment, seq_id) + + assert segment.count() == 4 + result = segment.get_vectors(ids=["no_such_record"]) + assert len(result) == 1 + assert approx_equal_vector(result[0]["embedding"], [42, 42]) + + +def test_delete_without_add( + system: System, + vector_reader: Type[VectorReader], +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + assert segment.count() == 0 + + delete_record = SubmitEmbeddingRecord( + id="not_in_db", + embedding=None, + encoding=None, + metadata=None, + operation=Operation.DELETE, + collection_id=uuid.UUID(int=0), + ) + + try: + producer.submit_embedding(topic, delete_record) + except BaseException: + pytest.fail("Unexpected error. Deleting on an empty segment should not raise.") + + +def test_delete_with_local_segment_storage( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns( + producer=producer, topic=topic, embeddings=sample_embeddings, n=5 + ) + + sync(segment, seq_ids[-1]) + assert segment.count() == 5 + + delete_record = SubmitEmbeddingRecord( + id=embeddings[0]["id"], + embedding=None, + encoding=None, + metadata=None, + operation=Operation.DELETE, + collection_id=uuid.UUID(int=0), + ) + assert isinstance(seq_ids, List) + seq_ids.append( + produce_fns( + producer=producer, + topic=topic, + n=1, + embeddings=(delete_record for _ in range(1)), + )[1][0] + ) + + sync(segment, seq_ids[-1]) + + # Assert that the record is gone using `count` + assert segment.count() == 4 + + # Assert that the record is gone using `get` + assert segment.get_vectors(ids=[embeddings[0]["id"]]) == [] + results = segment.get_vectors() + assert len(results) == 4 + # get_vectors returns results in arbitrary order + results = sorted(results, key=lambda v: v["id"]) + for actual, expected in zip(results, embeddings[1:]): + assert actual["id"] == expected["id"] + assert approx_equal_vector( + actual["embedding"], cast(Vector, expected["embedding"]) + ) + + # Assert that the record is gone from KNN search + vector = cast(Vector, embeddings[0]["embedding"]) + query = VectorQuery( + vectors=[vector], k=10, allowed_ids=None, options=None, include_embeddings=False + ) + knn_results = segment.query_vectors(query) + assert len(results) == 4 + assert set(r["id"] for r in knn_results[0]) == set(e["id"] for e in embeddings[1:]) + + # Delete is idempotent + if isinstance(segment, PersistentLocalHnswSegment): + assert os.path.exists(segment._get_storage_folder()) + segment.delete() + assert not os.path.exists(segment._get_storage_folder()) + segment.delete() # should not raise + elif isinstance(segment, LocalHnswSegment): + with pytest.raises(NotImplementedError): + segment.delete() + + +def test_reset_state_ignored_for_allow_reset_false( + system: System, + sample_embeddings: Iterator[SubmitEmbeddingRecord], + vector_reader: Type[VectorReader], + produce_fns: ProducerFn, +) -> None: + producer = system.instance(Producer) + system.reset_state() + segment_definition = create_random_segment_definition() + topic = str(segment_definition["topic"]) + + segment = vector_reader(system, segment_definition) + segment.start() + + embeddings, seq_ids = produce_fns( + producer=producer, topic=topic, embeddings=sample_embeddings, n=5 + ) + + sync(segment, seq_ids[-1]) + assert segment.count() == 5 + + delete_record = SubmitEmbeddingRecord( + id=embeddings[0]["id"], + embedding=None, + encoding=None, + metadata=None, + operation=Operation.DELETE, + collection_id=uuid.UUID(int=0), + ) + assert isinstance(seq_ids, List) + seq_ids.append( + produce_fns( + producer=producer, + topic=topic, + n=1, + embeddings=(delete_record for _ in range(1)), + )[1][0] + ) + + sync(segment, seq_ids[-1]) + + # Assert that the record is gone using `count` + assert segment.count() == 4 + + # Assert that the record is gone using `get` + assert segment.get_vectors(ids=[embeddings[0]["id"]]) == [] + results = segment.get_vectors() + assert len(results) == 4 + # get_vectors returns results in arbitrary order + results = sorted(results, key=lambda v: v["id"]) + for actual, expected in zip(results, embeddings[1:]): + assert actual["id"] == expected["id"] + assert approx_equal_vector( + actual["embedding"], cast(Vector, expected["embedding"]) + ) + + # Assert that the record is gone from KNN search + vector = cast(Vector, embeddings[0]["embedding"]) + query = VectorQuery( + vectors=[vector], k=10, allowed_ids=None, options=None, include_embeddings=False + ) + knn_results = segment.query_vectors(query) + assert len(results) == 4 + assert set(r["id"] for r in knn_results[0]) == set(e["id"] for e in embeddings[1:]) + + if isinstance(segment, PersistentLocalHnswSegment): + if segment._allow_reset: + assert os.path.exists(segment._get_storage_folder()) + segment.reset_state() + assert not os.path.exists(segment._get_storage_folder()) + else: + assert os.path.exists(segment._get_storage_folder()) + segment.reset_state() + assert os.path.exists(segment._get_storage_folder()) diff --git a/chromadb/test/stress/test_many_collections.py b/chromadb/test/stress/test_many_collections.py new file mode 100644 index 0000000000000000000000000000000000000000..29951fa452ae51343f2fe6d330d8bd5a8edec500 --- /dev/null +++ b/chromadb/test/stress/test_many_collections.py @@ -0,0 +1,37 @@ +from typing import List +import numpy as np + +from chromadb.api import ServerAPI +from chromadb.api.models.Collection import Collection + + +def test_many_collections(api: ServerAPI) -> None: + """Test that we can create a large number of collections and that the system + # remains responsive.""" + api.reset() + + N = 10 + D = 10 + + metadata = None + if api.get_settings().is_persistent: + metadata = {"hnsw:batch_size": 3, "hnsw:sync_threshold": 3} + else: + # We only want to test persistent configurations in this way, since the main + # point is to test the file handle limit + return + + num_collections = 10000 + collections: List[Collection] = [] + for i in range(num_collections): + new_collection = api.create_collection( + f"test_collection_{i}", + metadata=metadata, + ) + collections.append(new_collection) + + # Add a few embeddings to each collection + data = np.random.rand(N, D).tolist() + ids = [f"test_id_{i}" for i in range(N)] + for i in range(num_collections): + collections[i].add(ids, data) diff --git a/chromadb/test/test_api.py b/chromadb/test/test_api.py new file mode 100644 index 0000000000000000000000000000000000000000..cb88ed2bb77ed4dda330321ddc998632f9c7d58f --- /dev/null +++ b/chromadb/test/test_api.py @@ -0,0 +1,1501 @@ +# type: ignore +import traceback +import requests +from urllib3.connectionpool import InsecureRequestWarning + +import chromadb +from chromadb.api.fastapi import FastAPI +from chromadb.api.types import QueryResult, EmbeddingFunction, Document +from chromadb.config import Settings +import chromadb.server.fastapi +import pytest +import tempfile +import numpy as np +import os +import shutil +from datetime import datetime, timedelta +from chromadb.utils.embedding_functions import ( + DefaultEmbeddingFunction, +) + +persist_dir = tempfile.mkdtemp() + + +@pytest.fixture +def local_persist_api(): + client = chromadb.Client( + Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + allow_reset=True, + is_persistent=True, + persist_directory=persist_dir, + ), + ) + yield client + client.clear_system_cache() + if os.path.exists(persist_dir): + shutil.rmtree(persist_dir, ignore_errors=True) + + +# https://docs.pytest.org/en/6.2.x/fixture.html#fixtures-can-be-requested-more-than-once-per-test-return-values-are-cached +@pytest.fixture +def local_persist_api_cache_bust(): + client = chromadb.Client( + Settings( + chroma_api_impl="chromadb.api.segment.SegmentAPI", + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_segment_manager_impl="chromadb.segment.impl.manager.local.LocalSegmentManager", + allow_reset=True, + is_persistent=True, + persist_directory=persist_dir, + ), + ) + yield client + client.clear_system_cache() + if os.path.exists(persist_dir): + shutil.rmtree(persist_dir, ignore_errors=True) + + +def approx_equal(a, b, tolerance=1e-6) -> bool: + return abs(a - b) < tolerance + + +def vector_approx_equal(a, b, tolerance: float = 1e-6) -> bool: + if len(a) != len(b): + return False + return all([approx_equal(a, b, tolerance) for a, b in zip(a, b)]) + + +@pytest.mark.parametrize("api_fixture", [local_persist_api]) +def test_persist_index_loading(api_fixture, request): + api = request.getfixturevalue("local_persist_api") + api.reset() + collection = api.create_collection("test") + collection.add(ids="id1", documents="hello") + + api2 = request.getfixturevalue("local_persist_api_cache_bust") + collection = api2.get_collection("test") + + includes = ["embeddings", "documents", "metadatas", "distances"] + nn = collection.query( + query_texts="hello", + n_results=1, + include=["embeddings", "documents", "metadatas", "distances"], + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + +@pytest.mark.parametrize("api_fixture", [local_persist_api]) +def test_persist_index_loading_embedding_function(api_fixture, request): + class TestEF(EmbeddingFunction[Document]): + def __call__(self, input): + return [[1, 2, 3] for _ in range(len(input))] + + api = request.getfixturevalue("local_persist_api") + api.reset() + collection = api.create_collection("test", embedding_function=TestEF()) + collection.add(ids="id1", documents="hello") + + api2 = request.getfixturevalue("local_persist_api_cache_bust") + collection = api2.get_collection("test", embedding_function=TestEF()) + + includes = ["embeddings", "documents", "metadatas", "distances"] + nn = collection.query( + query_texts="hello", + n_results=1, + include=includes, + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + +@pytest.mark.parametrize("api_fixture", [local_persist_api]) +def test_persist_index_get_or_create_embedding_function(api_fixture, request): + class TestEF(EmbeddingFunction[Document]): + def __call__(self, input): + return [[1, 2, 3] for _ in range(len(input))] + + api = request.getfixturevalue("local_persist_api") + api.reset() + collection = api.get_or_create_collection("test", embedding_function=TestEF()) + collection.add(ids="id1", documents="hello") + + api2 = request.getfixturevalue("local_persist_api_cache_bust") + collection = api2.get_or_create_collection("test", embedding_function=TestEF()) + + includes = ["embeddings", "documents", "metadatas", "distances"] + nn = collection.query( + query_texts="hello", + n_results=1, + include=includes, + ) + + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + assert nn["ids"] == [["id1"]] + assert nn["embeddings"] == [[[1, 2, 3]]] + assert nn["documents"] == [["hello"]] + assert nn["distances"] == [[0]] + + +@pytest.mark.parametrize("api_fixture", [local_persist_api]) +def test_persist(api_fixture, request): + api = request.getfixturevalue(api_fixture.__name__) + + api.reset() + + collection = api.create_collection("testspace") + + collection.add(**batch_records) + + assert collection.count() == 2 + + api = request.getfixturevalue(api_fixture.__name__) + collection = api.get_collection("testspace") + assert collection.count() == 2 + + api.delete_collection("testspace") + + api = request.getfixturevalue(api_fixture.__name__) + assert api.list_collections() == [] + + +def test_heartbeat(api): + heartbeat_ns = api.heartbeat() + assert isinstance(heartbeat_ns, int) + + heartbeat_s = heartbeat_ns // 10**9 + heartbeat = datetime.fromtimestamp(heartbeat_s) + assert heartbeat > datetime.now() - timedelta(seconds=10) + + +def test_max_batch_size(api): + print(api) + batch_size = api.max_batch_size + assert batch_size > 0 + + +def test_pre_flight_checks(api): + if not isinstance(api, FastAPI): + pytest.skip("Not a FastAPI instance") + + resp = requests.get(f"{api._api_url}/pre-flight-checks") + assert resp.status_code == 200 + assert resp.json() is not None + assert "max_batch_size" in resp.json().keys() + + +batch_records = { + "embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "ids": ["https://example.com/1", "https://example.com/2"], +} + + +def test_add(api): + api.reset() + + collection = api.create_collection("testspace") + + collection.add(**batch_records) + + assert collection.count() == 2 + + +def test_get_or_create(api): + api.reset() + + collection = api.create_collection("testspace") + + collection.add(**batch_records) + + assert collection.count() == 2 + + with pytest.raises(Exception): + collection = api.create_collection("testspace") + + collection = api.get_or_create_collection("testspace") + + assert collection.count() == 2 + + +minimal_records = { + "embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "ids": ["https://example.com/1", "https://example.com/2"], +} + + +def test_add_minimal(api): + api.reset() + + collection = api.create_collection("testspace") + + collection.add(**minimal_records) + + assert collection.count() == 2 + + +def test_get_from_db(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**batch_records) + includes = ["embeddings", "documents", "metadatas"] + records = collection.get(include=includes) + for key in records.keys(): + if (key in includes) or (key == "ids"): + assert len(records[key]) == 2 + else: + assert records[key] is None + + +def test_reset_db(api): + api.reset() + + collection = api.create_collection("testspace") + collection.add(**batch_records) + assert collection.count() == 2 + + api.reset() + assert len(api.list_collections()) == 0 + + +def test_get_nearest_neighbors(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**batch_records) + + includes = ["embeddings", "documents", "metadatas", "distances"] + nn = collection.query( + query_embeddings=[1.1, 2.3, 3.2], + n_results=1, + where={}, + include=includes, + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + nn = collection.query( + query_embeddings=[[1.1, 2.3, 3.2]], + n_results=1, + where={}, + include=includes, + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + nn = collection.query( + query_embeddings=[[1.1, 2.3, 3.2], [0.1, 2.3, 4.5]], + n_results=1, + where={}, + include=includes, + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 2 + else: + assert nn[key] is None + + +def test_delete(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**batch_records) + assert collection.count() == 2 + + with pytest.raises(Exception): + collection.delete() + + +def test_delete_with_index(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**batch_records) + assert collection.count() == 2 + collection.query(query_embeddings=[[1.1, 2.3, 3.2]], n_results=1) + + +def test_count(api): + api.reset() + collection = api.create_collection("testspace") + assert collection.count() == 0 + collection.add(**batch_records) + assert collection.count() == 2 + + +def test_modify(api): + api.reset() + collection = api.create_collection("testspace") + collection.modify(name="testspace2") + + # collection name is modify + assert collection.name == "testspace2" + + +def test_modify_error_on_existing_name(api): + api.reset() + + api.create_collection("testspace") + c2 = api.create_collection("testspace2") + + with pytest.raises(Exception): + c2.modify(name="testspace") + + +def test_modify_warn_on_DF_change(api, caplog): + api.reset() + + collection = api.create_collection("testspace") + + with pytest.raises(Exception, match="not supported") as e: + collection.modify(metadata={"hnsw:space": "cosine"}) + + +def test_metadata_cru(api): + api.reset() + metadata_a = {"a": 1, "b": 2} + # Test create metatdata + collection = api.create_collection("testspace", metadata=metadata_a) + assert collection.metadata is not None + assert collection.metadata["a"] == 1 + assert collection.metadata["b"] == 2 + + # Test get metatdata + collection = api.get_collection("testspace") + assert collection.metadata is not None + assert collection.metadata["a"] == 1 + assert collection.metadata["b"] == 2 + + # Test modify metatdata + collection.modify(metadata={"a": 2, "c": 3}) + assert collection.metadata["a"] == 2 + assert collection.metadata["c"] == 3 + assert "b" not in collection.metadata + + # Test get after modify metatdata + collection = api.get_collection("testspace") + assert collection.metadata is not None + assert collection.metadata["a"] == 2 + assert collection.metadata["c"] == 3 + assert "b" not in collection.metadata + + # Test name exists get_or_create_metadata + collection = api.get_or_create_collection("testspace") + assert collection.metadata is not None + assert collection.metadata["a"] == 2 + assert collection.metadata["c"] == 3 + + # Test name exists create metadata + collection = api.get_or_create_collection("testspace2") + assert collection.metadata is None + + # Test list collections + collections = api.list_collections() + for collection in collections: + if collection.name == "testspace": + assert collection.metadata is not None + assert collection.metadata["a"] == 2 + assert collection.metadata["c"] == 3 + elif collection.name == "testspace2": + assert collection.metadata is None + + +def test_increment_index_on(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**batch_records) + assert collection.count() == 2 + + includes = ["embeddings", "documents", "metadatas", "distances"] + # increment index + nn = collection.query( + query_embeddings=[[1.1, 2.3, 3.2]], + n_results=1, + include=includes, + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + +def test_add_a_collection(api): + api.reset() + api.create_collection("testspace") + + # get collection does not throw an error + collection = api.get_collection("testspace") + assert collection.name == "testspace" + + # get collection should throw an error if collection does not exist + with pytest.raises(Exception): + collection = api.get_collection("testspace2") + + +def test_list_collections(api): + api.reset() + api.create_collection("testspace") + api.create_collection("testspace2") + + # get collection does not throw an error + collections = api.list_collections() + assert len(collections) == 2 + + +def test_reset(api): + api.reset() + api.create_collection("testspace") + api.create_collection("testspace2") + + # get collection does not throw an error + collections = api.list_collections() + assert len(collections) == 2 + + api.reset() + collections = api.list_collections() + assert len(collections) == 0 + + +def test_peek(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**batch_records) + assert collection.count() == 2 + + # peek + peek = collection.peek() + for key in peek.keys(): + if key in ["embeddings", "documents", "metadatas"] or key == "ids": + assert len(peek[key]) == 2 + else: + assert peek[key] is None + + +# TEST METADATA AND METADATA FILTERING +# region + +metadata_records = { + "embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "ids": ["id1", "id2"], + "metadatas": [ + {"int_value": 1, "string_value": "one", "float_value": 1.001}, + {"int_value": 2}, + ], +} + + +def test_metadata_add_get_int_float(api): + api.reset() + collection = api.create_collection("test_int") + collection.add(**metadata_records) + + items = collection.get(ids=["id1", "id2"]) + assert items["metadatas"][0]["int_value"] == 1 + assert items["metadatas"][0]["float_value"] == 1.001 + assert items["metadatas"][1]["int_value"] == 2 + assert isinstance(items["metadatas"][0]["int_value"], int) + assert isinstance(items["metadatas"][0]["float_value"], float) + + +def test_metadata_add_query_int_float(api): + api.reset() + collection = api.create_collection("test_int") + collection.add(**metadata_records) + + items: QueryResult = collection.query( + query_embeddings=[[1.1, 2.3, 3.2]], n_results=1 + ) + assert items["metadatas"] is not None + assert items["metadatas"][0][0]["int_value"] == 1 + assert items["metadatas"][0][0]["float_value"] == 1.001 + assert isinstance(items["metadatas"][0][0]["int_value"], int) + assert isinstance(items["metadatas"][0][0]["float_value"], float) + + +def test_metadata_get_where_string(api): + api.reset() + collection = api.create_collection("test_int") + collection.add(**metadata_records) + + items = collection.get(where={"string_value": "one"}) + assert items["metadatas"][0]["int_value"] == 1 + assert items["metadatas"][0]["string_value"] == "one" + + +def test_metadata_get_where_int(api): + api.reset() + collection = api.create_collection("test_int") + collection.add(**metadata_records) + + items = collection.get(where={"int_value": 1}) + assert items["metadatas"][0]["int_value"] == 1 + assert items["metadatas"][0]["string_value"] == "one" + + +def test_metadata_get_where_float(api): + api.reset() + collection = api.create_collection("test_int") + collection.add(**metadata_records) + + items = collection.get(where={"float_value": 1.001}) + assert items["metadatas"][0]["int_value"] == 1 + assert items["metadatas"][0]["string_value"] == "one" + assert items["metadatas"][0]["float_value"] == 1.001 + + +def test_metadata_update_get_int_float(api): + api.reset() + collection = api.create_collection("test_int") + collection.add(**metadata_records) + + collection.update( + ids=["id1"], + metadatas=[{"int_value": 2, "string_value": "two", "float_value": 2.002}], + ) + items = collection.get(ids=["id1"]) + assert items["metadatas"][0]["int_value"] == 2 + assert items["metadatas"][0]["string_value"] == "two" + assert items["metadatas"][0]["float_value"] == 2.002 + + +bad_metadata_records = { + "embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "ids": ["id1", "id2"], + "metadatas": [{"value": {"nested": "5"}}, {"value": [1, 2, 3]}], +} + + +def test_metadata_validation_add(api): + api.reset() + collection = api.create_collection("test_metadata_validation") + with pytest.raises(ValueError, match="metadata"): + collection.add(**bad_metadata_records) + + +def test_metadata_validation_update(api): + api.reset() + collection = api.create_collection("test_metadata_validation") + collection.add(**metadata_records) + with pytest.raises(ValueError, match="metadata"): + collection.update(ids=["id1"], metadatas={"value": {"nested": "5"}}) + + +def test_where_validation_get(api): + api.reset() + collection = api.create_collection("test_where_validation") + with pytest.raises(ValueError, match="where"): + collection.get(where={"value": {"nested": "5"}}) + + +def test_where_validation_query(api): + api.reset() + collection = api.create_collection("test_where_validation") + with pytest.raises(ValueError, match="where"): + collection.query(query_embeddings=[0, 0, 0], where={"value": {"nested": "5"}}) + + +operator_records = { + "embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "ids": ["id1", "id2"], + "metadatas": [ + {"int_value": 1, "string_value": "one", "float_value": 1.001}, + {"int_value": 2, "float_value": 2.002, "string_value": "two"}, + ], +} + + +def test_where_lt(api): + api.reset() + collection = api.create_collection("test_where_lt") + collection.add(**operator_records) + items = collection.get(where={"int_value": {"$lt": 2}}) + assert len(items["metadatas"]) == 1 + + +def test_where_lte(api): + api.reset() + collection = api.create_collection("test_where_lte") + collection.add(**operator_records) + items = collection.get(where={"int_value": {"$lte": 2.0}}) + assert len(items["metadatas"]) == 2 + + +def test_where_gt(api): + api.reset() + collection = api.create_collection("test_where_lte") + collection.add(**operator_records) + items = collection.get(where={"float_value": {"$gt": -1.4}}) + assert len(items["metadatas"]) == 2 + + +def test_where_gte(api): + api.reset() + collection = api.create_collection("test_where_lte") + collection.add(**operator_records) + items = collection.get(where={"float_value": {"$gte": 2.002}}) + assert len(items["metadatas"]) == 1 + + +def test_where_ne_string(api): + api.reset() + collection = api.create_collection("test_where_lte") + collection.add(**operator_records) + items = collection.get(where={"string_value": {"$ne": "two"}}) + assert len(items["metadatas"]) == 1 + + +def test_where_ne_eq_number(api): + api.reset() + collection = api.create_collection("test_where_lte") + collection.add(**operator_records) + items = collection.get(where={"int_value": {"$ne": 1}}) + assert len(items["metadatas"]) == 1 + items = collection.get(where={"float_value": {"$eq": 2.002}}) + assert len(items["metadatas"]) == 1 + + +def test_where_valid_operators(api): + api.reset() + collection = api.create_collection("test_where_valid_operators") + collection.add(**operator_records) + with pytest.raises(ValueError): + collection.get(where={"int_value": {"$invalid": 2}}) + + with pytest.raises(ValueError): + collection.get(where={"int_value": {"$lt": "2"}}) + + with pytest.raises(ValueError): + collection.get(where={"int_value": {"$lt": 2, "$gt": 1}}) + + # Test invalid $and, $or + with pytest.raises(ValueError): + collection.get(where={"$and": {"int_value": {"$lt": 2}}}) + + with pytest.raises(ValueError): + collection.get( + where={"int_value": {"$lt": 2}, "$or": {"int_value": {"$gt": 1}}} + ) + + with pytest.raises(ValueError): + collection.get( + where={"$gt": [{"int_value": {"$lt": 2}}, {"int_value": {"$gt": 1}}]} + ) + + with pytest.raises(ValueError): + collection.get(where={"$or": [{"int_value": {"$lt": 2}}]}) + + with pytest.raises(ValueError): + collection.get(where={"$or": []}) + + with pytest.raises(ValueError): + collection.get(where={"a": {"$contains": "test"}}) + + with pytest.raises(ValueError): + collection.get( + where={ + "$or": [ + {"a": {"$contains": "first"}}, # invalid + {"$contains": "second"}, # valid + ] + } + ) + + +# TODO: Define the dimensionality of these embeddingds in terms of the default record +bad_dimensionality_records = { + "embeddings": [[1.1, 2.3, 3.2, 4.5], [1.2, 2.24, 3.2, 4.5]], + "ids": ["id1", "id2"], +} + +bad_dimensionality_query = { + "query_embeddings": [[1.1, 2.3, 3.2, 4.5], [1.2, 2.24, 3.2, 4.5]], +} + +bad_number_of_results_query = { + "query_embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "n_results": 100, +} + + +def test_dimensionality_validation_add(api): + api.reset() + collection = api.create_collection("test_dimensionality_validation") + collection.add(**minimal_records) + + with pytest.raises(Exception) as e: + collection.add(**bad_dimensionality_records) + assert "dimensionality" in str(e.value) + + +def test_dimensionality_validation_query(api): + api.reset() + collection = api.create_collection("test_dimensionality_validation_query") + collection.add(**minimal_records) + + with pytest.raises(Exception) as e: + collection.query(**bad_dimensionality_query) + assert "dimensionality" in str(e.value) + + +def test_query_document_valid_operators(api): + api.reset() + collection = api.create_collection("test_where_valid_operators") + collection.add(**operator_records) + with pytest.raises(ValueError, match="where document"): + collection.get(where_document={"$lt": {"$nested": 2}}) + + with pytest.raises(ValueError, match="where document"): + collection.query(query_embeddings=[0, 0, 0], where_document={"$contains": 2}) + + with pytest.raises(ValueError, match="where document"): + collection.get(where_document={"$contains": []}) + + # Test invalid $and, $or + with pytest.raises(ValueError): + collection.get(where_document={"$and": {"$unsupported": "doc"}}) + + with pytest.raises(ValueError): + collection.get( + where_document={"$or": [{"$unsupported": "doc"}, {"$unsupported": "doc"}]} + ) + + with pytest.raises(ValueError): + collection.get(where_document={"$or": [{"$contains": "doc"}]}) + + with pytest.raises(ValueError): + collection.get(where_document={"$or": []}) + + with pytest.raises(ValueError): + collection.get( + where_document={ + "$or": [{"$and": [{"$contains": "doc"}]}, {"$contains": "doc"}] + } + ) + + +contains_records = { + "embeddings": [[1.1, 2.3, 3.2], [1.2, 2.24, 3.2]], + "documents": ["this is doc1 and it's great!", "doc2 is also great!"], + "ids": ["id1", "id2"], + "metadatas": [ + {"int_value": 1, "string_value": "one", "float_value": 1.001}, + {"int_value": 2, "float_value": 2.002, "string_value": "two"}, + ], +} + + +def test_get_where_document(api): + api.reset() + collection = api.create_collection("test_get_where_document") + collection.add(**contains_records) + + items = collection.get(where_document={"$contains": "doc1"}) + assert len(items["metadatas"]) == 1 + + items = collection.get(where_document={"$contains": "great"}) + assert len(items["metadatas"]) == 2 + + items = collection.get(where_document={"$contains": "bad"}) + assert len(items["metadatas"]) == 0 + + +def test_query_where_document(api): + api.reset() + collection = api.create_collection("test_query_where_document") + collection.add(**contains_records) + + items = collection.query( + query_embeddings=[1, 0, 0], where_document={"$contains": "doc1"}, n_results=1 + ) + assert len(items["metadatas"][0]) == 1 + + items = collection.query( + query_embeddings=[0, 0, 0], where_document={"$contains": "great"}, n_results=2 + ) + assert len(items["metadatas"][0]) == 2 + + with pytest.raises(Exception) as e: + items = collection.query( + query_embeddings=[0, 0, 0], where_document={"$contains": "bad"}, n_results=1 + ) + assert "datapoints" in str(e.value) + + +def test_delete_where_document(api): + api.reset() + collection = api.create_collection("test_delete_where_document") + collection.add(**contains_records) + + collection.delete(where_document={"$contains": "doc1"}) + assert collection.count() == 1 + + collection.delete(where_document={"$contains": "bad"}) + assert collection.count() == 1 + + collection.delete(where_document={"$contains": "great"}) + assert collection.count() == 0 + + +logical_operator_records = { + "embeddings": [ + [1.1, 2.3, 3.2], + [1.2, 2.24, 3.2], + [1.3, 2.25, 3.2], + [1.4, 2.26, 3.2], + ], + "ids": ["id1", "id2", "id3", "id4"], + "metadatas": [ + {"int_value": 1, "string_value": "one", "float_value": 1.001, "is": "doc"}, + {"int_value": 2, "float_value": 2.002, "string_value": "two", "is": "doc"}, + {"int_value": 3, "float_value": 3.003, "string_value": "three", "is": "doc"}, + {"int_value": 4, "float_value": 4.004, "string_value": "four", "is": "doc"}, + ], + "documents": [ + "this document is first and great", + "this document is second and great", + "this document is third and great", + "this document is fourth and great", + ], +} + + +def test_where_logical_operators(api): + api.reset() + collection = api.create_collection("test_logical_operators") + collection.add(**logical_operator_records) + + items = collection.get( + where={ + "$and": [ + {"$or": [{"int_value": {"$gte": 3}}, {"float_value": {"$lt": 1.9}}]}, + {"is": "doc"}, + ] + } + ) + assert len(items["metadatas"]) == 3 + + items = collection.get( + where={ + "$or": [ + { + "$and": [ + {"int_value": {"$eq": 3}}, + {"string_value": {"$eq": "three"}}, + ] + }, + { + "$and": [ + {"int_value": {"$eq": 4}}, + {"string_value": {"$eq": "four"}}, + ] + }, + ] + } + ) + assert len(items["metadatas"]) == 2 + + items = collection.get( + where={ + "$and": [ + { + "$or": [ + {"int_value": {"$eq": 1}}, + {"string_value": {"$eq": "two"}}, + ] + }, + { + "$or": [ + {"int_value": {"$eq": 2}}, + {"string_value": {"$eq": "one"}}, + ] + }, + ] + } + ) + assert len(items["metadatas"]) == 2 + + +def test_where_document_logical_operators(api): + api.reset() + collection = api.create_collection("test_document_logical_operators") + collection.add(**logical_operator_records) + + items = collection.get( + where_document={ + "$and": [ + {"$contains": "first"}, + {"$contains": "doc"}, + ] + } + ) + assert len(items["metadatas"]) == 1 + + items = collection.get( + where_document={ + "$or": [ + {"$contains": "first"}, + {"$contains": "second"}, + ] + } + ) + assert len(items["metadatas"]) == 2 + + items = collection.get( + where_document={ + "$or": [ + {"$contains": "first"}, + {"$contains": "second"}, + ] + }, + where={ + "int_value": {"$ne": 2}, + }, + ) + assert len(items["metadatas"]) == 1 + + +# endregion + +records = { + "embeddings": [[0, 0, 0], [1.2, 2.24, 3.2]], + "ids": ["id1", "id2"], + "metadatas": [ + {"int_value": 1, "string_value": "one", "float_value": 1.001}, + {"int_value": 2}, + ], + "documents": ["this document is first", "this document is second"], +} + + +def test_query_include(api): + api.reset() + collection = api.create_collection("test_query_include") + collection.add(**records) + + items = collection.query( + query_embeddings=[0, 0, 0], + include=["metadatas", "documents", "distances"], + n_results=1, + ) + assert items["embeddings"] is None + assert items["ids"][0][0] == "id1" + assert items["metadatas"][0][0]["int_value"] == 1 + + items = collection.query( + query_embeddings=[0, 0, 0], + include=["embeddings", "documents", "distances"], + n_results=1, + ) + assert items["metadatas"] is None + assert items["ids"][0][0] == "id1" + + items = collection.query( + query_embeddings=[[0, 0, 0], [1, 2, 1.2]], + include=[], + n_results=2, + ) + assert items["documents"] is None + assert items["metadatas"] is None + assert items["embeddings"] is None + assert items["distances"] is None + assert items["ids"][0][0] == "id1" + assert items["ids"][0][1] == "id2" + + +def test_get_include(api): + api.reset() + collection = api.create_collection("test_get_include") + collection.add(**records) + + items = collection.get(include=["metadatas", "documents"], where={"int_value": 1}) + assert items["embeddings"] is None + assert items["ids"][0] == "id1" + assert items["metadatas"][0]["int_value"] == 1 + assert items["documents"][0] == "this document is first" + + items = collection.get(include=["embeddings", "documents"]) + assert items["metadatas"] is None + assert items["ids"][0] == "id1" + assert approx_equal(items["embeddings"][1][0], 1.2) + + items = collection.get(include=[]) + assert items["documents"] is None + assert items["metadatas"] is None + assert items["embeddings"] is None + assert items["ids"][0] == "id1" + + with pytest.raises(ValueError, match="include"): + items = collection.get(include=["metadatas", "undefined"]) + + with pytest.raises(ValueError, match="include"): + items = collection.get(include=None) + + +# make sure query results are returned in the right order + + +def test_query_order(api): + api.reset() + collection = api.create_collection("test_query_order") + collection.add(**records) + + items = collection.query( + query_embeddings=[1.2, 2.24, 3.2], + include=["metadatas", "documents", "distances"], + n_results=2, + ) + + assert items["documents"][0][0] == "this document is second" + assert items["documents"][0][1] == "this document is first" + + +# test to make sure add, get, delete error on invalid id input + + +def test_invalid_id(api): + api.reset() + collection = api.create_collection("test_invalid_id") + # Add with non-string id + with pytest.raises(ValueError) as e: + collection.add(embeddings=[0, 0, 0], ids=[1], metadatas=[{}]) + assert "ID" in str(e.value) + + # Get with non-list id + with pytest.raises(ValueError) as e: + collection.get(ids=1) + assert "ID" in str(e.value) + + # Delete with malformed ids + with pytest.raises(ValueError) as e: + collection.delete(ids=["valid", 0]) + assert "ID" in str(e.value) + + +def test_index_params(api): + EPS = 1e-12 + # first standard add + api.reset() + collection = api.create_collection(name="test_index_params") + collection.add(**records) + items = collection.query( + query_embeddings=[0.6, 1.12, 1.6], + n_results=1, + ) + assert items["distances"][0][0] > 4 + + # cosine + api.reset() + collection = api.create_collection( + name="test_index_params", + metadata={"hnsw:space": "cosine", "hnsw:construction_ef": 20, "hnsw:M": 5}, + ) + collection.add(**records) + items = collection.query( + query_embeddings=[0.6, 1.12, 1.6], + n_results=1, + ) + assert items["distances"][0][0] > 0 - EPS + assert items["distances"][0][0] < 1 + EPS + + # ip + api.reset() + collection = api.create_collection( + name="test_index_params", metadata={"hnsw:space": "ip"} + ) + collection.add(**records) + items = collection.query( + query_embeddings=[0.6, 1.12, 1.6], + n_results=1, + ) + assert items["distances"][0][0] < -5 + + +def test_invalid_index_params(api): + api.reset() + + with pytest.raises(Exception): + collection = api.create_collection( + name="test_index_params", metadata={"hnsw:foobar": "blarg"} + ) + collection.add(**records) + + with pytest.raises(Exception): + collection = api.create_collection( + name="test_index_params", metadata={"hnsw:space": "foobar"} + ) + collection.add(**records) + + +def test_persist_index_loading_params(api, request): + api = request.getfixturevalue("local_persist_api") + api.reset() + collection = api.create_collection( + "test", + metadata={"hnsw:space": "ip"}, + ) + collection.add(ids="id1", documents="hello") + + api2 = request.getfixturevalue("local_persist_api_cache_bust") + collection = api2.get_collection( + "test", + ) + + assert collection.metadata["hnsw:space"] == "ip" + includes = ["embeddings", "documents", "metadatas", "distances"] + nn = collection.query( + query_texts="hello", + n_results=1, + include=includes, + ) + for key in nn.keys(): + if (key in includes) or (key == "ids"): + assert len(nn[key]) == 1 + else: + assert nn[key] is None + + +def test_add_large(api): + api.reset() + + collection = api.create_collection("testspace") + + # Test adding a large number of records + large_records = np.random.rand(2000, 512).astype(np.float32).tolist() + + collection.add( + embeddings=large_records, + ids=[f"http://example.com/{i}" for i in range(len(large_records))], + ) + + assert collection.count() == len(large_records) + + +# test get_version +def test_get_version(api): + api.reset() + version = api.get_version() + + # assert version matches the pattern x.y.z + import re + + assert re.match(r"\d+\.\d+\.\d+", version) + + +# test delete_collection +def test_delete_collection(api): + api.reset() + collection = api.create_collection("test_delete_collection") + collection.add(**records) + + assert len(api.list_collections()) == 1 + api.delete_collection("test_delete_collection") + assert len(api.list_collections()) == 0 + + +# test default embedding function +def test_default_embedding(): + embedding_function = DefaultEmbeddingFunction() + docs = ["this is a test" for _ in range(64)] + embeddings = embedding_function(docs) + assert len(embeddings) == 64 + + +def test_multiple_collections(api): + embeddings1 = np.random.rand(10, 512).astype(np.float32).tolist() + embeddings2 = np.random.rand(10, 512).astype(np.float32).tolist() + ids1 = [f"http://example.com/1/{i}" for i in range(len(embeddings1))] + ids2 = [f"http://example.com/2/{i}" for i in range(len(embeddings2))] + + api.reset() + coll1 = api.create_collection("coll1") + coll1.add(embeddings=embeddings1, ids=ids1) + + coll2 = api.create_collection("coll2") + coll2.add(embeddings=embeddings2, ids=ids2) + + assert len(api.list_collections()) == 2 + assert coll1.count() == len(embeddings1) + assert coll2.count() == len(embeddings2) + + results1 = coll1.query(query_embeddings=embeddings1[0], n_results=1) + results2 = coll2.query(query_embeddings=embeddings2[0], n_results=1) + + assert results1["ids"][0][0] == ids1[0] + assert results2["ids"][0][0] == ids2[0] + + +def test_update_query(api): + api.reset() + collection = api.create_collection("test_update_query") + collection.add(**records) + + updated_records = { + "ids": [records["ids"][0]], + "embeddings": [[0.1, 0.2, 0.3]], + "documents": ["updated document"], + "metadatas": [{"foo": "bar"}], + } + + collection.update(**updated_records) + + # test query + results = collection.query( + query_embeddings=updated_records["embeddings"], + n_results=1, + include=["embeddings", "documents", "metadatas"], + ) + assert len(results["ids"][0]) == 1 + assert results["ids"][0][0] == updated_records["ids"][0] + assert results["documents"][0][0] == updated_records["documents"][0] + assert results["metadatas"][0][0]["foo"] == "bar" + assert vector_approx_equal( + results["embeddings"][0][0], updated_records["embeddings"][0] + ) + + +def test_get_nearest_neighbors_where_n_results_more_than_element(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**records) + + includes = ["embeddings", "documents", "metadatas", "distances"] + results = collection.query( + query_embeddings=[[1.1, 2.3, 3.2]], + n_results=5, + where={}, + include=includes, + ) + for key in results.keys(): + if key in includes or key == "ids": + assert len(results[key][0]) == 2 + else: + assert results[key] is None + + +def test_invalid_n_results_param(api): + api.reset() + collection = api.create_collection("testspace") + collection.add(**records) + with pytest.raises(TypeError) as exc: + collection.query( + query_embeddings=[[1.1, 2.3, 3.2]], + n_results=-1, + where={}, + include=["embeddings", "documents", "metadatas", "distances"], + ) + assert "Number of requested results -1, cannot be negative, or zero." in str( + exc.value + ) + assert exc.type == TypeError + + with pytest.raises(ValueError) as exc: + collection.query( + query_embeddings=[[1.1, 2.3, 3.2]], + n_results="one", + where={}, + include=["embeddings", "documents", "metadatas", "distances"], + ) + assert "int" in str(exc.value) + assert exc.type == ValueError + + +initial_records = { + "embeddings": [[0, 0, 0], [1.2, 2.24, 3.2], [2.2, 3.24, 4.2]], + "ids": ["id1", "id2", "id3"], + "metadatas": [ + {"int_value": 1, "string_value": "one", "float_value": 1.001}, + {"int_value": 2}, + {"string_value": "three"}, + ], + "documents": [ + "this document is first", + "this document is second", + "this document is third", + ], +} + +new_records = { + "embeddings": [[3.0, 3.0, 1.1], [3.2, 4.24, 5.2]], + "ids": ["id1", "id4"], + "metadatas": [ + {"int_value": 1, "string_value": "one_of_one", "float_value": 1.001}, + {"int_value": 4}, + ], + "documents": [ + "this document is even more first", + "this document is new and fourth", + ], +} + + +def test_upsert(api): + api.reset() + collection = api.create_collection("test") + + collection.add(**initial_records) + assert collection.count() == 3 + + collection.upsert(**new_records) + assert collection.count() == 4 + + get_result = collection.get( + include=["embeddings", "metadatas", "documents"], ids=new_records["ids"][0] + ) + assert vector_approx_equal( + get_result["embeddings"][0], new_records["embeddings"][0] + ) + assert get_result["metadatas"][0] == new_records["metadatas"][0] + assert get_result["documents"][0] == new_records["documents"][0] + + query_result = collection.query( + query_embeddings=get_result["embeddings"], + n_results=1, + include=["embeddings", "metadatas", "documents"], + ) + assert vector_approx_equal( + query_result["embeddings"][0][0], new_records["embeddings"][0] + ) + assert query_result["metadatas"][0][0] == new_records["metadatas"][0] + assert query_result["documents"][0][0] == new_records["documents"][0] + + collection.delete(ids=initial_records["ids"][2]) + collection.upsert( + ids=initial_records["ids"][2], + embeddings=[[1.1, 0.99, 2.21]], + metadatas=[{"string_value": "a new string value"}], + ) + assert collection.count() == 4 + + get_result = collection.get( + include=["embeddings", "metadatas", "documents"], ids=["id3"] + ) + assert vector_approx_equal(get_result["embeddings"][0], [1.1, 0.99, 2.21]) + assert get_result["metadatas"][0] == {"string_value": "a new string value"} + assert get_result["documents"][0] is None + + +# test to make sure add, query, update, upsert error on invalid embeddings input + + +def test_invalid_embeddings(api): + api.reset() + collection = api.create_collection("test_invalid_embeddings") + + # Add with string embeddings + invalid_records = { + "embeddings": [["0", "0", "0"], ["1.2", "2.24", "3.2"]], + "ids": ["id1", "id2"], + } + with pytest.raises(ValueError) as e: + collection.add(**invalid_records) + assert "embedding" in str(e.value) + + # Query with invalid embeddings + with pytest.raises(ValueError) as e: + collection.query( + query_embeddings=[["1.1", "2.3", "3.2"]], + n_results=1, + ) + assert "embedding" in str(e.value) + + # Update with invalid embeddings + invalid_records = { + "embeddings": [[[0], [0], [0]], [[1.2], [2.24], [3.2]]], + "ids": ["id1", "id2"], + } + with pytest.raises(ValueError) as e: + collection.update(**invalid_records) + assert "embedding" in str(e.value) + + # Upsert with invalid embeddings + invalid_records = { + "embeddings": [[[1.1, 2.3, 3.2]], [[1.2, 2.24, 3.2]]], + "ids": ["id1", "id2"], + } + with pytest.raises(ValueError) as e: + collection.upsert(**invalid_records) + assert "embedding" in str(e.value) + + +# test to make sure update shows exception for bad dimensionality + + +def test_dimensionality_exception_update(api): + api.reset() + collection = api.create_collection("test_dimensionality_update_exception") + collection.add(**minimal_records) + + with pytest.raises(Exception) as e: + collection.update(**bad_dimensionality_records) + assert "dimensionality" in str(e.value) + + +# test to make sure upsert shows exception for bad dimensionality + + +def test_dimensionality_exception_upsert(api): + api.reset() + collection = api.create_collection("test_dimensionality_upsert_exception") + collection.add(**minimal_records) + + with pytest.raises(Exception) as e: + collection.upsert(**bad_dimensionality_records) + assert "dimensionality" in str(e.value) + + +def test_ssl_self_signed(client_ssl): + if os.environ.get("CHROMA_INTEGRATION_TEST_ONLY"): + pytest.skip("Skipping test for integration test") + client_ssl.heartbeat() + + +def test_ssl_self_signed_without_ssl_verify(client_ssl): + if os.environ.get("CHROMA_INTEGRATION_TEST_ONLY"): + pytest.skip("Skipping test for integration test") + client_ssl.heartbeat() + _port = client_ssl._server._settings.chroma_server_http_port + with pytest.raises(ValueError) as e: + chromadb.HttpClient(ssl=True, port=_port) + stack_trace = traceback.format_exception( + type(e.value), e.value, e.value.__traceback__ + ) + client_ssl.clear_system_cache() + assert "CERTIFICATE_VERIFY_FAILED" in "".join(stack_trace) + + +def test_ssl_self_signed_with_verify_false(client_ssl): + if os.environ.get("CHROMA_INTEGRATION_TEST_ONLY"): + pytest.skip("Skipping test for integration test") + client_ssl.heartbeat() + _port = client_ssl._server._settings.chroma_server_http_port + with pytest.warns(InsecureRequestWarning) as record: + client = chromadb.HttpClient( + ssl=True, + port=_port, + settings=chromadb.Settings(chroma_server_ssl_verify=False), + ) + client.heartbeat() + client_ssl.clear_system_cache() + assert "Unverified HTTPS request" in str(record[0].message) diff --git a/chromadb/test/test_chroma.py b/chromadb/test/test_chroma.py new file mode 100644 index 0000000000000000000000000000000000000000..9d88ea8cc492a7f2c41f76f1c8c012023322dec4 --- /dev/null +++ b/chromadb/test/test_chroma.py @@ -0,0 +1,112 @@ +import unittest +import os +from unittest.mock import patch, Mock +import pytest +import chromadb +import chromadb.config +from chromadb.db.system import SysDB +from chromadb.ingest import Consumer, Producer + + +class GetDBTest(unittest.TestCase): + @patch("chromadb.db.impl.sqlite.SqliteDB", autospec=True) + def test_default_db(self, mock: Mock) -> None: + system = chromadb.config.System( + chromadb.config.Settings(persist_directory="./foo") + ) + system.instance(SysDB) + assert mock.called + + @patch("chromadb.db.impl.sqlite.SqliteDB", autospec=True) + def test_sqlite_sysdb(self, mock: Mock) -> None: + system = chromadb.config.System( + chromadb.config.Settings( + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + persist_directory="./foo", + ) + ) + system.instance(SysDB) + assert mock.called + + @patch("chromadb.db.impl.sqlite.SqliteDB", autospec=True) + def test_sqlite_queue(self, mock: Mock) -> None: + system = chromadb.config.System( + chromadb.config.Settings( + chroma_sysdb_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_producer_impl="chromadb.db.impl.sqlite.SqliteDB", + chroma_consumer_impl="chromadb.db.impl.sqlite.SqliteDB", + persist_directory="./foo", + ) + ) + system.instance(Producer) + system.instance(Consumer) + assert mock.called + + +class GetAPITest(unittest.TestCase): + @patch("chromadb.api.segment.SegmentAPI", autospec=True) + @patch.dict(os.environ, {}, clear=True) + def test_local(self, mock_api: Mock) -> None: + client = chromadb.Client(chromadb.config.Settings(persist_directory="./foo")) + assert mock_api.called + client.clear_system_cache() + + @patch("chromadb.db.impl.sqlite.SqliteDB", autospec=True) + @patch.dict(os.environ, {}, clear=True) + def test_local_db(self, mock_db: Mock) -> None: + client = chromadb.Client(chromadb.config.Settings(persist_directory="./foo")) + assert mock_db.called + client.clear_system_cache() + + @patch("chromadb.api.fastapi.FastAPI", autospec=True) + @patch.dict(os.environ, {}, clear=True) + def test_fastapi(self, mock: Mock) -> None: + client = chromadb.Client( + chromadb.config.Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + persist_directory="./foo", + chroma_server_host="foo", + chroma_server_http_port="80", + ) + ) + assert mock.called + client.clear_system_cache() + + @patch("chromadb.api.fastapi.FastAPI", autospec=True) + @patch.dict(os.environ, {}, clear=True) + def test_settings_pass_to_fastapi(self, mock: Mock) -> None: + settings = chromadb.config.Settings( + chroma_api_impl="chromadb.api.fastapi.FastAPI", + chroma_server_host="foo", + chroma_server_http_port="80", + chroma_server_headers={"foo": "bar"}, + ) + client = chromadb.Client(settings) + + # Check that the mock was called + assert mock.called + + # Retrieve the arguments with which the mock was called + # `call_args` returns a tuple, where the first element is a tuple of positional arguments + # and the second element is a dictionary of keyword arguments. We assume here that + # the settings object is passed as a positional argument. + args, kwargs = mock.call_args + passed_settings = args[0] if args else None + + # Check if the settings passed to the mock match the settings we used + # raise Exception(passed_settings.settings) + assert passed_settings.settings == settings + client.clear_system_cache() + + +def test_legacy_values() -> None: + with pytest.raises(ValueError): + client = chromadb.Client( + chromadb.config.Settings( + chroma_api_impl="chromadb.api.local.LocalAPI", + persist_directory="./foo", + chroma_server_host="foo", + chroma_server_http_port="80", + ) + ) + client.clear_system_cache() diff --git a/chromadb/test/test_cli.py b/chromadb/test/test_cli.py new file mode 100644 index 0000000000000000000000000000000000000000..c9a29874c4eab5f913c94b727a5858c00fd47d47 --- /dev/null +++ b/chromadb/test/test_cli.py @@ -0,0 +1,27 @@ +from typer.testing import CliRunner + +from chromadb.cli.cli import app +from chromadb.cli.utils import set_log_file_path + +runner = CliRunner() + + +def test_app() -> None: + result = runner.invoke( + app, + [ + "run", + "--path", + "chroma_test_data", + "--port", + "8001", + "--test", + ], + ) + assert "chroma_test_data" in result.stdout + assert "8001" in result.stdout + + +def test_utils_set_log_file_path() -> None: + log_config = set_log_file_path("chromadb/log_config.yml", "test.log") + assert log_config["handlers"]["file"]["filename"] == "test.log" diff --git a/chromadb/test/test_client.py b/chromadb/test/test_client.py new file mode 100644 index 0000000000000000000000000000000000000000..f67293d85864951362bea4364ec1b56362b32200 --- /dev/null +++ b/chromadb/test/test_client.py @@ -0,0 +1,72 @@ +from typing import Generator +from unittest.mock import patch +import chromadb +from chromadb.config import Settings +from chromadb.api import ClientAPI +import chromadb.server.fastapi +import pytest +import tempfile + + +@pytest.fixture +def ephemeral_api() -> Generator[ClientAPI, None, None]: + client = chromadb.EphemeralClient() + yield client + client.clear_system_cache() + + +@pytest.fixture +def persistent_api() -> Generator[ClientAPI, None, None]: + client = chromadb.PersistentClient( + path=tempfile.gettempdir() + "/test_server", + ) + yield client + client.clear_system_cache() + + +@pytest.fixture +def http_api() -> Generator[ClientAPI, None, None]: + with patch("chromadb.api.client.Client._validate_tenant_database"): + client = chromadb.HttpClient() + yield client + client.clear_system_cache() + + +def test_ephemeral_client(ephemeral_api: ClientAPI) -> None: + settings = ephemeral_api.get_settings() + assert settings.is_persistent is False + + +def test_persistent_client(persistent_api: ClientAPI) -> None: + settings = persistent_api.get_settings() + assert settings.is_persistent is True + + +def test_http_client(http_api: ClientAPI) -> None: + settings = http_api.get_settings() + assert settings.chroma_api_impl == "chromadb.api.fastapi.FastAPI" + + +def test_http_client_with_inconsistent_host_settings() -> None: + try: + chromadb.HttpClient(settings=Settings(chroma_server_host="127.0.0.1")) + except ValueError as e: + assert ( + str(e) + == "Chroma server host provided in settings[127.0.0.1] is different to the one provided in HttpClient: [localhost]" + ) + + +def test_http_client_with_inconsistent_port_settings() -> None: + try: + chromadb.HttpClient( + port="8002", + settings=Settings( + chroma_server_http_port="8001", + ), + ) + except ValueError as e: + assert ( + str(e) + == "Chroma server http port provided in settings[8001] is different to the one provided in HttpClient: [8002]" + ) diff --git a/chromadb/test/test_config.py b/chromadb/test/test_config.py new file mode 100644 index 0000000000000000000000000000000000000000..f24af28381f7577fd2ec8007c7b81cb24ca7d89c --- /dev/null +++ b/chromadb/test/test_config.py @@ -0,0 +1,191 @@ +from chromadb.config import Component, System, Settings +from overrides import overrides +from threading import local +import random + +data = local() # use thread local just in case tests ever run in parallel + + +def reset() -> None: + global data + data.starts = [] + data.stops = [] + data.inits = [] + + +class ComponentA(Component): + def __init__(self, system: System): + data.inits += "A" + super().__init__(system) + self.require(ComponentB) + self.require(ComponentC) + + @overrides + def start(self) -> None: + data.starts += "A" + + @overrides + def stop(self) -> None: + data.stops += "A" + + +class ComponentB(Component): + def __init__(self, system: System): + data.inits += "B" + super().__init__(system) + self.require(ComponentC) + self.require(ComponentD) + + @overrides + def start(self) -> None: + data.starts += "B" + + @overrides + def stop(self) -> None: + data.stops += "B" + + +class ComponentC(Component): + def __init__(self, system: System): + data.inits += "C" + super().__init__(system) + self.require(ComponentD) + + @overrides + def start(self) -> None: + data.starts += "C" + + @overrides + def stop(self) -> None: + data.stops += "C" + + +class ComponentD(Component): + def __init__(self, system: System): + data.inits += "D" + super().__init__(system) + + @overrides + def start(self) -> None: + data.starts += "D" + + @overrides + def stop(self) -> None: + data.stops += "D" + + +# Dependency Graph for tests: +# ┌───┐ +# │ A │ +# └┬─┬┘ +# │┌▽──┐ +# ││ B │ +# │└┬─┬┘ +# ┌▽─▽┐│ +# │ C ││ +# └┬──┘│ +# ┌▽───▽┐ +# │ D │ +# └─────┘ + + +def test_leaf_only() -> None: + settings = Settings() + system = System(settings) + + reset() + + d = system.instance(ComponentD) + assert isinstance(d, ComponentD) + + assert data.inits == ["D"] + system.start() + assert data.starts == ["D"] + system.stop() + assert data.stops == ["D"] + + +def test_partial() -> None: + settings = Settings() + system = System(settings) + + reset() + + c = system.instance(ComponentC) + assert isinstance(c, ComponentC) + + assert data.inits == ["C", "D"] + system.start() + assert data.starts == ["D", "C"] + system.stop() + assert data.stops == ["C", "D"] + + +def test_system_startup() -> None: + settings = Settings() + system = System(settings) + + reset() + + a = system.instance(ComponentA) + assert isinstance(a, ComponentA) + + assert data.inits == ["A", "B", "C", "D"] + system.start() + assert data.starts == ["D", "C", "B", "A"] + system.stop() + assert data.stops == ["A", "B", "C", "D"] + + +def test_system_override_order() -> None: + settings = Settings() + system = System(settings) + + reset() + + system.instance(ComponentA) + + # Deterministically shuffle the instances map to prove that topsort is actually + # working and not just implicitly working because of insertion order. + + # This causes the test to actually fail if the deps are not wired up correctly. + random.seed(0) + entries = list(system._instances.items()) + random.shuffle(entries) + system._instances = {k: v for k, v in entries} + + system.start() + assert data.starts == ["D", "C", "B", "A"] + system.stop() + assert data.stops == ["A", "B", "C", "D"] + + +class ComponentZ(Component): + def __init__(self, system: System): + super().__init__(system) + self.require(ComponentC) + + @overrides + def start(self) -> None: + pass + + @overrides + def stop(self) -> None: + pass + + +def test_runtime_dependencies() -> None: + settings = Settings() + system = System(settings) + + reset() + + # Nothing to do, no components were requested prior to start + system.start() + assert data.starts == [] + + # Constructs dependencies and starts them in the correct order + ComponentZ(system) + assert data.starts == ["D", "C"] + system.stop() + assert data.stops == ["C", "D"] diff --git a/chromadb/test/test_multithreaded.py b/chromadb/test/test_multithreaded.py new file mode 100644 index 0000000000000000000000000000000000000000..c0b05e8832436fbd64c517d1b07aae8f59289dfe --- /dev/null +++ b/chromadb/test/test_multithreaded.py @@ -0,0 +1,223 @@ +import multiprocessing +from concurrent.futures import Future, ThreadPoolExecutor, wait +import random +import threading +from typing import Any, Dict, List, Optional, Set, Tuple, cast +import numpy as np + +from chromadb.api import ServerAPI +import chromadb.test.property.invariants as invariants +from chromadb.test.property.strategies import RecordSet +from chromadb.test.property.strategies import test_hnsw_config +from chromadb.types import Metadata + + +def generate_data_shape() -> Tuple[int, int]: + N = random.randint(10, 10000) + D = random.randint(10, 256) + return (N, D) + + +def generate_record_set(N: int, D: int) -> RecordSet: + ids = [str(i) for i in range(N)] + metadatas: List[Dict[str, int]] = [{f"{i}": i} for i in range(N)] + documents = [f"doc {i}" for i in range(N)] + embeddings = np.random.rand(N, D).tolist() + + # Create a normalized record set to compare against + normalized_record_set: RecordSet = { + "ids": ids, + "embeddings": embeddings, + "metadatas": metadatas, # type: ignore + "documents": documents, + } + + return normalized_record_set + + +# Hypothesis is bad at generating large datasets so we manually generate data in +# this test to test multithreaded add with larger datasets +def _test_multithreaded_add(api: ServerAPI, N: int, D: int, num_workers: int) -> None: + records_set = generate_record_set(N, D) + ids = records_set["ids"] + embeddings = records_set["embeddings"] + metadatas = records_set["metadatas"] + documents = records_set["documents"] + + print(f"Adding {N} records with {D} dimensions on {num_workers} workers") + + # TODO: batch_size and sync_threshold should be configurable + api.reset() + coll = api.create_collection(name="test", metadata=test_hnsw_config) + with ThreadPoolExecutor(max_workers=num_workers) as executor: + futures: List[Future[Any]] = [] + total_sent = -1 + while total_sent < len(ids): + # Randomly grab up to 10% of the dataset and send it to the executor + batch_size = random.randint(1, N // 10) + to_send = min(batch_size, len(ids) - total_sent) + start = total_sent + 1 + end = total_sent + to_send + 1 + if embeddings is not None and len(embeddings[start:end]) == 0: + break + future = executor.submit( + coll.add, + ids=ids[start:end], + embeddings=embeddings[start:end] if embeddings is not None else None, + metadatas=metadatas[start:end] if metadatas is not None else None, # type: ignore + documents=documents[start:end] if documents is not None else None, + ) + futures.append(future) + total_sent += to_send + + wait(futures) + + for future in futures: + exception = future.exception() + if exception is not None: + raise exception + + # Check that invariants hold + invariants.count(coll, records_set) + invariants.ids_match(coll, records_set) + invariants.metadatas_match(coll, records_set) + invariants.no_duplicates(coll) + + # Check that the ANN accuracy is good + # On a random subset of the dataset + query_indices = random.sample([i for i in range(N)], 10) + n_results = 5 + invariants.ann_accuracy( + coll, + records_set, + n_results=n_results, + query_indices=query_indices, + ) + + +def _test_interleaved_add_query( + api: ServerAPI, N: int, D: int, num_workers: int +) -> None: + """Test that will use multiple threads to interleave operations on the db and verify they work correctly""" + + api.reset() + coll = api.create_collection(name="test", metadata=test_hnsw_config) + + records_set = generate_record_set(N, D) + ids = cast(List[str], records_set["ids"]) + embeddings = cast(List[float], records_set["embeddings"]) + metadatas = cast(List[Metadata], records_set["metadatas"]) + documents = records_set["documents"] + + added_ids: Set[str] = set() + lock = threading.Lock() + + print(f"Adding {N} records with {D} dimensions on {num_workers} workers") + + def perform_operation( + operation: int, ids_to_modify: Optional[List[str]] = None + ) -> None: + """Perform a random operation on the collection""" + if operation == 0: + assert ids_to_modify is not None + indices_to_modify = [ids.index(id) for id in ids_to_modify] + # Add a subset of the dataset + if len(indices_to_modify) == 0: + return + coll.add( + ids=ids_to_modify, + embeddings=[embeddings[i] for i in indices_to_modify] + if embeddings is not None + else None, + metadatas=[metadatas[i] for i in indices_to_modify] + if metadatas is not None + else None, + documents=[documents[i] for i in indices_to_modify] + if documents is not None + else None, + ) + with lock: + added_ids.update(ids_to_modify) + elif operation == 1: + currently_added_ids = [] + n_results = 5 + with lock: + currently_added_ids = list(added_ids.copy()) + currently_added_indices = [ids.index(id) for id in currently_added_ids] + if ( + len(currently_added_ids) == 0 + or len(currently_added_indices) < n_results + ): + return + # Query the collection, we can't test the results because we want to interleave + # queries and adds. We cannot do so without a lock and serializing the operations + # which would defeat the purpose of this test. Instead we interleave queries and + # adds and check the invariants at the end + query_indices = random.sample( + currently_added_indices, + min(10, len(currently_added_indices)), + ) + query_vectors = [embeddings[i] for i in query_indices] + # Query the collections + coll.query( + query_vectors, + n_results=n_results, + ) + + with ThreadPoolExecutor(max_workers=num_workers) as executor: + futures: List[Future[Any]] = [] + total_sent = -1 + while total_sent < len(ids) - 1: + operation = random.randint(0, 2) + if operation == 0: + # Randomly grab up to 10% of the dataset and send it to the executor + batch_size = random.randint(1, N // 10) + to_send = min(batch_size, len(ids) - total_sent) + start = total_sent + 1 + end = total_sent + to_send + 1 + future = executor.submit(perform_operation, operation, ids[start:end]) + futures.append(future) + total_sent += to_send + elif operation == 1: + future = executor.submit( + perform_operation, + operation, + ) + futures.append(future) + + wait(futures) + + for future in futures: + exception = future.exception() + if exception is not None: + raise exception + + # Check that invariants hold + invariants.count(coll, records_set) + invariants.ids_match(coll, records_set) + invariants.metadatas_match(coll, records_set) + invariants.no_duplicates(coll) + # Check that the ANN accuracy is good + # On a random subset of the dataset + query_indices = random.sample([i for i in range(N)], 10) + n_results = 5 + invariants.ann_accuracy( + coll, + records_set, + n_results=n_results, + query_indices=query_indices, + ) + + +def test_multithreaded_add(api: ServerAPI) -> None: + for i in range(3): + num_workers = random.randint(2, multiprocessing.cpu_count() * 2) + N, D = generate_data_shape() + _test_multithreaded_add(api, N, D, num_workers) + + +def test_interleaved_add_query(api: ServerAPI) -> None: + for i in range(3): + num_workers = random.randint(2, multiprocessing.cpu_count() * 2) + N, D = generate_data_shape() + _test_interleaved_add_query(api, N, D, num_workers) diff --git a/chromadb/test/utils/test_messagid.py b/chromadb/test/utils/test_messagid.py new file mode 100644 index 0000000000000000000000000000000000000000..eff20a1b6fedaf460535f3dc7c4f64a70a27f8f1 --- /dev/null +++ b/chromadb/test/utils/test_messagid.py @@ -0,0 +1,93 @@ +import chromadb.utils.messageid as mid +import pulsar +import hypothesis.strategies as st +from hypothesis import given, settings, note +from typing import Any, Tuple + + +@st.composite +def message_id(draw: st.DrawFn) -> pulsar.MessageId: + ledger_id = draw(st.integers(min_value=0, max_value=2**63 - 1)) + entry_id = draw(st.integers(min_value=0, max_value=2**63 - 1)) + batch_index = draw(st.integers(min_value=(2**31 - 1) * -1, max_value=2**31 - 1)) + partition = draw(st.integers(min_value=(2**31 - 1) * -1, max_value=2**31 - 1)) + return pulsar.MessageId(partition, ledger_id, entry_id, batch_index) + + +@given(message_id=message_id()) +@settings(max_examples=10000) # these are very fast and we want good coverage +def test_roundtrip_formats(message_id: pulsar.MessageId) -> None: + int1 = mid.pulsar_to_int(message_id) + + # Roundtrip int->string and back + str1 = mid.int_to_str(int1) + assert int1 == mid.str_to_int(str1) + + # Roundtrip int->bytes and back + b1 = mid.int_to_bytes(int1) + assert int1 == mid.bytes_to_int(b1) + + # Roundtrip int -> MessageId and back + message_id_result = mid.int_to_pulsar(int1) + assert message_id_result.partition() == message_id.partition() + assert message_id_result.ledger_id() == message_id.ledger_id() + assert message_id_result.entry_id() == message_id.entry_id() + assert message_id_result.batch_index() == message_id.batch_index() + + +def assert_compare(pair1: Tuple[Any, Any], pair2: Tuple[Any, Any]) -> None: + """Helper function: assert that the two pairs of values always compare in the same + way across all comparisons and orderings.""" + + a, b = pair1 + c, d = pair2 + + try: + assert (a > b) == (c > d) + assert (a >= b) == (c >= d) + assert (a < b) == (c < d) + assert (a <= b) == (c <= d) + assert (a == b) == (c == d) + except AssertionError: + note(f"Failed to compare {a} and {b} with {c} and {d}") + note(f"type: {type(a)}") + raise + + +@given(m1=message_id(), m2=message_id()) +@settings(max_examples=10000) # these are very fast and we want good coverage +def test_messageid_comparison(m1: pulsar.MessageId, m2: pulsar.MessageId) -> None: + # MessageID comparison is broken in the Pulsar Python & CPP libraries: + # The partition field is not taken into account, and two MessageIDs with different + # partitions will compare inconsistently (m1 > m2 AND m2 > m1) + # To avoid this, we zero-out the partition field before testing. + m1 = pulsar.MessageId(0, m1.ledger_id(), m1.entry_id(), m1.batch_index()) + m2 = pulsar.MessageId(0, m2.ledger_id(), m2.entry_id(), m2.batch_index()) + + i1 = mid.pulsar_to_int(m1) + i2 = mid.pulsar_to_int(m2) + + # In python, MessageId objects are not comparable directory, but the + # internal generated native object is. + internal1 = m1._msg_id + internal2 = m2._msg_id + + s1 = mid.int_to_str(i1) + s2 = mid.int_to_str(i2) + + # assert that all strings, all ints, and all native objects compare the same + assert_compare((internal1, internal2), (i1, i2)) + assert_compare((internal1, internal2), (s1, s2)) + + +def test_max_values() -> None: + pulsar.MessageId(2**31 - 1, 2**63 - 1, 2**63 - 1, 2**31 - 1) + + +@given( + i1=st.integers(min_value=0, max_value=2**192 - 1), + i2=st.integers(min_value=0, max_value=2**192 - 1), +) +@settings(max_examples=10000) # these are very fast and we want good coverage +def test_string_comparison(i1: int, i2: int) -> None: + assert_compare((i1, i2), (mid.int_to_str(i1), mid.int_to_str(i2))) diff --git a/chromadb/types.py b/chromadb/types.py new file mode 100644 index 0000000000000000000000000000000000000000..fd66f12af6cabdb0eee15234c0477d0e6a8ed1c9 --- /dev/null +++ b/chromadb/types.py @@ -0,0 +1,179 @@ +from typing import Optional, Union, Sequence, Dict, Mapping, List + +from typing_extensions import Literal, TypedDict, TypeVar +from uuid import UUID +from enum import Enum + + +Metadata = Mapping[str, Union[str, int, float, bool]] +UpdateMetadata = Mapping[str, Union[int, float, str, bool, None]] + +# Namespaced Names are mechanically just strings, but we use this type to indicate that +# the intent is for the value to be globally unique and semantically meaningful. +NamespacedName = str + + +class ScalarEncoding(Enum): + FLOAT32 = "FLOAT32" + INT32 = "INT32" + + +class SegmentScope(Enum): + VECTOR = "VECTOR" + METADATA = "METADATA" + + +class Collection(TypedDict): + id: UUID + name: str + topic: str + metadata: Optional[Metadata] + dimension: Optional[int] + tenant: str + database: str + + +class Database(TypedDict): + id: UUID + name: str + tenant: str + + +class Tenant(TypedDict): + name: str + + +class Segment(TypedDict): + id: UUID + type: NamespacedName + scope: SegmentScope + # If a segment has a topic, it implies that this segment is a consumer of the topic + # and indexes the contents of the topic. + topic: Optional[str] + # If a segment has a collection, it implies that this segment implements the full + # collection and can be used to service queries (for it's given scope.) + collection: Optional[UUID] + metadata: Optional[Metadata] + + +# SeqID can be one of three types of value in our current and future plans: +# 1. A Pulsar MessageID encoded as a 192-bit integer +# 2. A Pulsar MessageIndex (a 64-bit integer) +# 3. A SQL RowID (a 64-bit integer) + +# All three of these types can be expressed as a Python int, so that is the type we +# use in the internal Python API. However, care should be taken that the larger 192-bit +# values are stored correctly when persisting to DBs. +SeqId = int + + +class Operation(Enum): + ADD = "ADD" + UPDATE = "UPDATE" + UPSERT = "UPSERT" + DELETE = "DELETE" + + +Vector = Union[Sequence[float], Sequence[int]] + + +class VectorEmbeddingRecord(TypedDict): + id: str + seq_id: SeqId + embedding: Vector + + +class MetadataEmbeddingRecord(TypedDict): + id: str + seq_id: SeqId + metadata: Optional[Metadata] + + +class EmbeddingRecord(TypedDict): + id: str + seq_id: SeqId + embedding: Optional[Vector] + encoding: Optional[ScalarEncoding] + metadata: Optional[UpdateMetadata] + operation: Operation + # The collection the operation is being performed on + # This is optional because in the single node version, + # topics are 1:1 with collections. So consumers of the ingest queue + # implicitly know this mapping. However, in the multi-node version, + # topics are shared between collections, so we need to explicitly + # specify the collection. + # For backwards compatability reasons, we can't make this a required field on + # single node, since data written with older versions of the code won't be able to + # populate it. + collection_id: Optional[UUID] + + +class SubmitEmbeddingRecord(TypedDict): + id: str + embedding: Optional[Vector] + encoding: Optional[ScalarEncoding] + metadata: Optional[UpdateMetadata] + operation: Operation + collection_id: UUID # The collection the operation is being performed on + + +class VectorQuery(TypedDict): + """A KNN/ANN query""" + + vectors: Sequence[Vector] + k: int + allowed_ids: Optional[Sequence[str]] + include_embeddings: bool + options: Optional[Dict[str, Union[str, int, float, bool]]] + + +class VectorQueryResult(TypedDict): + """A KNN/ANN query result""" + + id: str + seq_id: SeqId + distance: float + embedding: Optional[Vector] + + +# Metadata Query Grammar +LiteralValue = Union[str, int, float, bool] +LogicalOperator = Union[Literal["$and"], Literal["$or"]] +WhereOperator = Union[ + Literal["$gt"], + Literal["$gte"], + Literal["$lt"], + Literal["$lte"], + Literal["$ne"], + Literal["$eq"], +] +InclusionExclusionOperator = Union[Literal["$in"], Literal["$nin"]] +OperatorExpression = Union[ + Dict[Union[WhereOperator, LogicalOperator], LiteralValue], + Dict[InclusionExclusionOperator, List[LiteralValue]], +] + +Where = Dict[ + Union[str, LogicalOperator], Union[LiteralValue, OperatorExpression, List["Where"]] +] + +WhereDocumentOperator = Union[ + Literal["$contains"], Literal["$not_contains"], LogicalOperator +] +WhereDocument = Dict[WhereDocumentOperator, Union[str, List["WhereDocument"]]] + + +class Unspecified: + """A sentinel value used to indicate that a value should not be updated""" + + _instance: Optional["Unspecified"] = None + + def __new__(cls) -> "Unspecified": + if cls._instance is None: + cls._instance = super(Unspecified, cls).__new__(cls) + + return cls._instance + + +T = TypeVar("T") +OptionalArgument = Union[T, Unspecified] diff --git a/chromadb/utils/__init__.py b/chromadb/utils/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..fe6bb81853b1ed2b3f2c0b4c9fe5d9cfa5302d28 --- /dev/null +++ b/chromadb/utils/__init__.py @@ -0,0 +1,12 @@ +import importlib +from typing import Type, TypeVar, cast + +C = TypeVar("C") + + +def get_class(fqn: str, type: Type[C]) -> Type[C]: + """Given a fully qualifed class name, import the module and return the class""" + module_name, class_name = fqn.rsplit(".", 1) + module = importlib.import_module(module_name) + cls = getattr(module, class_name) + return cast(Type[C], cls) diff --git a/chromadb/utils/batch_utils.py b/chromadb/utils/batch_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..9c588270f2554dd258a9e531a58afb438f552d32 --- /dev/null +++ b/chromadb/utils/batch_utils.py @@ -0,0 +1,34 @@ +from typing import Optional, Tuple, List +from chromadb.api import BaseAPI +from chromadb.api.types import ( + Documents, + Embeddings, + IDs, + Metadatas, +) + + +def create_batches( + api: BaseAPI, + ids: IDs, + embeddings: Optional[Embeddings] = None, + metadatas: Optional[Metadatas] = None, + documents: Optional[Documents] = None, +) -> List[Tuple[IDs, Embeddings, Optional[Metadatas], Optional[Documents]]]: + _batches: List[ + Tuple[IDs, Embeddings, Optional[Metadatas], Optional[Documents]] + ] = [] + if len(ids) > api.max_batch_size: + # create split batches + for i in range(0, len(ids), api.max_batch_size): + _batches.append( + ( # type: ignore + ids[i : i + api.max_batch_size], + embeddings[i : i + api.max_batch_size] if embeddings else None, + metadatas[i : i + api.max_batch_size] if metadatas else None, + documents[i : i + api.max_batch_size] if documents else None, + ) + ) + else: + _batches.append((ids, embeddings, metadatas, documents)) # type: ignore + return _batches diff --git a/chromadb/utils/data_loaders.py b/chromadb/utils/data_loaders.py new file mode 100644 index 0000000000000000000000000000000000000000..60057e0e5843edb62bff9450f67bee00118967c1 --- /dev/null +++ b/chromadb/utils/data_loaders.py @@ -0,0 +1,24 @@ +import importlib +import multiprocessing +from typing import Optional, Sequence, List +import numpy as np +from chromadb.api.types import URI, DataLoader, Image +from concurrent.futures import ThreadPoolExecutor + + +class ImageLoader(DataLoader[List[Optional[Image]]]): + def __init__(self, max_workers: int = multiprocessing.cpu_count()) -> None: + try: + self._PILImage = importlib.import_module("PIL.Image") + self._max_workers = max_workers + except ImportError: + raise ValueError( + "The PIL python package is not installed. Please install it with `pip install pillow`" + ) + + def _load_image(self, uri: Optional[URI]) -> Optional[Image]: + return np.array(self._PILImage.open(uri)) if uri is not None else None + + def __call__(self, uris: Sequence[Optional[URI]]) -> List[Optional[Image]]: + with ThreadPoolExecutor(max_workers=self._max_workers) as executor: + return list(executor.map(self._load_image, uris)) diff --git a/chromadb/utils/delete_file.py b/chromadb/utils/delete_file.py new file mode 100644 index 0000000000000000000000000000000000000000..4d3e329dae9368ff12b0ab7083006a2233f51dbf --- /dev/null +++ b/chromadb/utils/delete_file.py @@ -0,0 +1,38 @@ +import os +import random +import gc +import time + + +# Borrowed from https://github.com/rogerbinns/apsw/blob/master/apsw/tests.py#L224 +# Used to delete sqlite files on Windows, since Windows file locking +# behaves differently to other operating systems +# This should only be used for test or non-production code, such as in reset_state. +def delete_file(name: str) -> None: + try: + os.remove(name) + except Exception: + pass + + chars = list("abcdefghijklmn") + random.shuffle(chars) + newname = name + "-n-" + "".join(chars) + count = 0 + while os.path.exists(name): + count += 1 + try: + os.rename(name, newname) + except Exception: + if count > 30: + n = list("abcdefghijklmnopqrstuvwxyz") + random.shuffle(n) + final_name = "".join(n) + try: + os.rename( + name, "chroma-to-clean" + final_name + ".deletememanually" + ) + except Exception: + pass + break + time.sleep(0.1) + gc.collect() diff --git a/chromadb/utils/directory.py b/chromadb/utils/directory.py new file mode 100644 index 0000000000000000000000000000000000000000..d470a810ed5e3c22e89d56317f45d2ea09a0e7a4 --- /dev/null +++ b/chromadb/utils/directory.py @@ -0,0 +1,21 @@ +import os + +def get_directory_size(directory: str) -> int: + """ + Calculate the total size of the directory by walking through each file. + + Parameters: + directory (str): The path of the directory for which to calculate the size. + + Returns: + total_size (int): The total size of the directory in bytes. + """ + total_size = 0 + for dirpath, _, filenames in os.walk(directory): + for f in filenames: + fp = os.path.join(dirpath, f) + # skip if it is symbolic link + if not os.path.islink(fp): + total_size += os.path.getsize(fp) + + return total_size \ No newline at end of file diff --git a/chromadb/utils/distance_functions.py b/chromadb/utils/distance_functions.py new file mode 100644 index 0000000000000000000000000000000000000000..e7e77bf7f94cce1812a30a63933e477390dc158b --- /dev/null +++ b/chromadb/utils/distance_functions.py @@ -0,0 +1,22 @@ +""" +These functions match what the spec of hnswlib is. +""" +import numpy as np +from numpy.typing import ArrayLike + + +def l2(x: ArrayLike, y: ArrayLike) -> float: + return np.linalg.norm(x - y) ** 2 + + +def cosine(x: ArrayLike, y: ArrayLike) -> float: + # This epsilon is used to prevent division by zero, and the value is the same + # https://github.com/nmslib/hnswlib/blob/359b2ba87358224963986f709e593d799064ace6/python_bindings/bindings.cpp#L238 + NORM_EPS = 1e-30 + return 1 - np.dot(x, y) / ( + (np.linalg.norm(x) + NORM_EPS) * (np.linalg.norm(y) + NORM_EPS) + ) + + +def ip(x: ArrayLike, y: ArrayLike) -> float: + return 1 - np.dot(x, y) diff --git a/chromadb/utils/embedding_functions.py b/chromadb/utils/embedding_functions.py new file mode 100644 index 0000000000000000000000000000000000000000..ec5fc05e3ee9fd58c4e62f32b542ac11c837373b --- /dev/null +++ b/chromadb/utils/embedding_functions.py @@ -0,0 +1,821 @@ +import hashlib +import logging +from functools import cached_property + +from tenacity import stop_after_attempt, wait_random, retry, retry_if_exception + +from chromadb.api.types import ( + Document, + Documents, + Embedding, + Image, + Images, + EmbeddingFunction, + Embeddings, + is_image, + is_document, +) + +from pathlib import Path +import os +import tarfile +import requests +from typing import TYPE_CHECKING, Any, Dict, List, Mapping, Optional, Union, cast +import numpy as np +import numpy.typing as npt +import importlib +import inspect +import json +import sys + +try: + from chromadb.is_thin_client import is_thin_client +except ImportError: + is_thin_client = False + +if TYPE_CHECKING: + from onnxruntime import InferenceSession + from tokenizers import Tokenizer + +logger = logging.getLogger(__name__) + + +def _verify_sha256(fname: str, expected_sha256: str) -> bool: + sha256_hash = hashlib.sha256() + with open(fname, "rb") as f: + # Read and update hash in chunks to avoid using too much memory + for byte_block in iter(lambda: f.read(4096), b""): + sha256_hash.update(byte_block) + + return sha256_hash.hexdigest() == expected_sha256 + + +class SentenceTransformerEmbeddingFunction(EmbeddingFunction[Documents]): + # Since we do dynamic imports we have to type this as Any + models: Dict[str, Any] = {} + + # If you have a beefier machine, try "gtr-t5-large". + # for a full list of options: https://huggingface.co/sentence-transformers, https://www.sbert.net/docs/pretrained_models.html + def __init__( + self, + model_name: str = "all-MiniLM-L6-v2", + device: str = "cpu", + normalize_embeddings: bool = False, + ): + if model_name not in self.models: + try: + from sentence_transformers import SentenceTransformer + except ImportError: + raise ValueError( + "The sentence_transformers python package is not installed. Please install it with `pip install sentence_transformers`" + ) + self.models[model_name] = SentenceTransformer(model_name, device=device) + self._model = self.models[model_name] + self._normalize_embeddings = normalize_embeddings + + def __call__(self, input: Documents) -> Embeddings: + return cast( + Embeddings, + self._model.encode( + list(input), + convert_to_numpy=True, + normalize_embeddings=self._normalize_embeddings, + ).tolist(), + ) + + +class Text2VecEmbeddingFunction(EmbeddingFunction[Documents]): + def __init__(self, model_name: str = "shibing624/text2vec-base-chinese"): + try: + from text2vec import SentenceModel + except ImportError: + raise ValueError( + "The text2vec python package is not installed. Please install it with `pip install text2vec`" + ) + self._model = SentenceModel(model_name_or_path=model_name) + + def __call__(self, input: Documents) -> Embeddings: + return cast( + Embeddings, self._model.encode(list(input), convert_to_numpy=True).tolist() + ) # noqa E501 + + +class OpenAIEmbeddingFunction(EmbeddingFunction[Documents]): + def __init__( + self, + api_key: Optional[str] = None, + model_name: str = "text-embedding-ada-002", + organization_id: Optional[str] = None, + api_base: Optional[str] = None, + api_type: Optional[str] = None, + api_version: Optional[str] = None, + deployment_id: Optional[str] = None, + default_headers: Optional[Mapping[str, str]] = None, + ): + """ + Initialize the OpenAIEmbeddingFunction. + Args: + api_key (str, optional): Your API key for the OpenAI API. If not + provided, it will raise an error to provide an OpenAI API key. + organization_id(str, optional): The OpenAI organization ID if applicable + model_name (str, optional): The name of the model to use for text + embeddings. Defaults to "text-embedding-ada-002". + api_base (str, optional): The base path for the API. If not provided, + it will use the base path for the OpenAI API. This can be used to + point to a different deployment, such as an Azure deployment. + api_type (str, optional): The type of the API deployment. This can be + used to specify a different deployment, such as 'azure'. If not + provided, it will use the default OpenAI deployment. + api_version (str, optional): The api version for the API. If not provided, + it will use the api version for the OpenAI API. This can be used to + point to a different deployment, such as an Azure deployment. + deployment_id (str, optional): Deployment ID for Azure OpenAI. + default_headers (Mapping, optional): A mapping of default headers to be sent with each API request. + + """ + try: + import openai + except ImportError: + raise ValueError( + "The openai python package is not installed. Please install it with `pip install openai`" + ) + + if api_key is not None: + openai.api_key = api_key + # If the api key is still not set, raise an error + elif openai.api_key is None: + raise ValueError( + "Please provide an OpenAI API key. You can get one at https://platform.openai.com/account/api-keys" + ) + + if api_base is not None: + openai.api_base = api_base + + if api_version is not None: + openai.api_version = api_version + + self._api_type = api_type + if api_type is not None: + openai.api_type = api_type + + if organization_id is not None: + openai.organization = organization_id + + self._v1 = openai.__version__.startswith("1.") + if self._v1: + if api_type == "azure": + self._client = openai.AzureOpenAI( + api_key=api_key, + api_version=api_version, + azure_endpoint=api_base, + default_headers=default_headers, + ).embeddings + else: + self._client = openai.OpenAI( + api_key=api_key, base_url=api_base, default_headers=default_headers + ).embeddings + else: + self._client = openai.Embedding + self._model_name = model_name + self._deployment_id = deployment_id + + def __call__(self, input: Documents) -> Embeddings: + # replace newlines, which can negatively affect performance. + input = [t.replace("\n", " ") for t in input] + + # Call the OpenAI Embedding API + if self._v1: + embeddings = self._client.create( + input=input, model=self._deployment_id or self._model_name + ).data + + # Sort resulting embeddings by index + sorted_embeddings = sorted(embeddings, key=lambda e: e.index) + + # Return just the embeddings + return cast(Embeddings, [result.embedding for result in sorted_embeddings]) + else: + if self._api_type == "azure": + embeddings = self._client.create( + input=input, engine=self._deployment_id or self._model_name + )["data"] + else: + embeddings = self._client.create(input=input, model=self._model_name)[ + "data" + ] + + # Sort resulting embeddings by index + sorted_embeddings = sorted(embeddings, key=lambda e: e["index"]) + + # Return just the embeddings + return cast( + Embeddings, [result["embedding"] for result in sorted_embeddings] + ) + + +class CohereEmbeddingFunction(EmbeddingFunction[Documents]): + def __init__(self, api_key: str, model_name: str = "large"): + try: + import cohere + except ImportError: + raise ValueError( + "The cohere python package is not installed. Please install it with `pip install cohere`" + ) + + self._client = cohere.Client(api_key) + self._model_name = model_name + + def __call__(self, input: Documents) -> Embeddings: + # Call Cohere Embedding API for each document. + return [ + embeddings + for embeddings in self._client.embed( + texts=input, model=self._model_name, input_type="search_document" + ) + ] + + +class HuggingFaceEmbeddingFunction(EmbeddingFunction[Documents]): + """ + This class is used to get embeddings for a list of texts using the HuggingFace API. + It requires an API key and a model name. The default model name is "sentence-transformers/all-MiniLM-L6-v2". + """ + + def __init__( + self, api_key: str, model_name: str = "sentence-transformers/all-MiniLM-L6-v2" + ): + """ + Initialize the HuggingFaceEmbeddingFunction. + + Args: + api_key (str): Your API key for the HuggingFace API. + model_name (str, optional): The name of the model to use for text embeddings. Defaults to "sentence-transformers/all-MiniLM-L6-v2". + """ + self._api_url = f"https://api-inference.huggingface.co/pipeline/feature-extraction/{model_name}" + self._session = requests.Session() + self._session.headers.update({"Authorization": f"Bearer {api_key}"}) + + def __call__(self, input: Documents) -> Embeddings: + """ + Get the embeddings for a list of texts. + + Args: + texts (Documents): A list of texts to get embeddings for. + + Returns: + Embeddings: The embeddings for the texts. + + Example: + >>> hugging_face = HuggingFaceEmbeddingFunction(api_key="your_api_key") + >>> texts = ["Hello, world!", "How are you?"] + >>> embeddings = hugging_face(texts) + """ + # Call HuggingFace Embedding API for each document + return cast( + Embeddings, + self._session.post( + self._api_url, + json={"inputs": input, "options": {"wait_for_model": True}}, + ).json(), + ) + + +class JinaEmbeddingFunction(EmbeddingFunction[Documents]): + """ + This class is used to get embeddings for a list of texts using the Jina AI API. + It requires an API key and a model name. The default model name is "jina-embeddings-v2-base-en". + """ + + def __init__(self, api_key: str, model_name: str = "jina-embeddings-v2-base-en"): + """ + Initialize the JinaEmbeddingFunction. + + Args: + api_key (str): Your API key for the Jina AI API. + model_name (str, optional): The name of the model to use for text embeddings. Defaults to "jina-embeddings-v2-base-en". + """ + self._model_name = model_name + self._api_url = "https://api.jina.ai/v1/embeddings" + self._session = requests.Session() + self._session.headers.update( + {"Authorization": f"Bearer {api_key}", "Accept-Encoding": "identity"} + ) + + def __call__(self, input: Documents) -> Embeddings: + """ + Get the embeddings for a list of texts. + + Args: + texts (Documents): A list of texts to get embeddings for. + + Returns: + Embeddings: The embeddings for the texts. + + Example: + >>> jina_ai_fn = JinaEmbeddingFunction(api_key="your_api_key") + >>> input = ["Hello, world!", "How are you?"] + >>> embeddings = jina_ai_fn(input) + """ + # Call Jina AI Embedding API + resp = self._session.post( + self._api_url, json={"input": input, "model": self._model_name} + ).json() + if "data" not in resp: + raise RuntimeError(resp["detail"]) + + embeddings = resp["data"] + + # Sort resulting embeddings by index + sorted_embeddings = sorted(embeddings, key=lambda e: e["index"]) + + # Return just the embeddings + return cast(Embeddings, [result["embedding"] for result in sorted_embeddings]) + + +class InstructorEmbeddingFunction(EmbeddingFunction[Documents]): + # If you have a GPU with at least 6GB try model_name = "hkunlp/instructor-xl" and device = "cuda" + # for a full list of options: https://github.com/HKUNLP/instructor-embedding#model-list + def __init__( + self, + model_name: str = "hkunlp/instructor-base", + device: str = "cpu", + instruction: Optional[str] = None, + ): + try: + from InstructorEmbedding import INSTRUCTOR + except ImportError: + raise ValueError( + "The InstructorEmbedding python package is not installed. Please install it with `pip install InstructorEmbedding`" + ) + self._model = INSTRUCTOR(model_name, device=device) + self._instruction = instruction + + def __call__(self, input: Documents) -> Embeddings: + if self._instruction is None: + return cast(Embeddings, self._model.encode(input).tolist()) + + texts_with_instructions = [[self._instruction, text] for text in input] + + return cast(Embeddings, self._model.encode(texts_with_instructions).tolist()) + + +# In order to remove dependencies on sentence-transformers, which in turn depends on +# pytorch and sentence-piece we have created a default ONNX embedding function that +# implements the same functionality as "all-MiniLM-L6-v2" from sentence-transformers. +# visit https://github.com/chroma-core/onnx-embedding for the source code to generate +# and verify the ONNX model. +class ONNXMiniLM_L6_V2(EmbeddingFunction[Documents]): + MODEL_NAME = "all-MiniLM-L6-v2" + DOWNLOAD_PATH = Path.home() / ".cache" / "chroma" / "onnx_models" / MODEL_NAME + EXTRACTED_FOLDER_NAME = "onnx" + ARCHIVE_FILENAME = "onnx.tar.gz" + MODEL_DOWNLOAD_URL = ( + "https://chroma-onnx-models.s3.amazonaws.com/all-MiniLM-L6-v2/onnx.tar.gz" + ) + _MODEL_SHA256 = "913d7300ceae3b2dbc2c50d1de4baacab4be7b9380491c27fab7418616a16ec3" + + # https://github.com/python/mypy/issues/7291 mypy makes you type the constructor if + # no args + def __init__(self, preferred_providers: Optional[List[str]] = None) -> None: + # Import dependencies on demand to mirror other embedding functions. This + # breaks typechecking, thus the ignores. + # convert the list to set for unique values + if preferred_providers and not all( + [isinstance(i, str) for i in preferred_providers] + ): + raise ValueError("Preferred providers must be a list of strings") + # check for duplicate providers + if preferred_providers and len(preferred_providers) != len( + set(preferred_providers) + ): + raise ValueError("Preferred providers must be unique") + self._preferred_providers = preferred_providers + try: + # Equivalent to import onnxruntime + self.ort = importlib.import_module("onnxruntime") + except ImportError: + raise ValueError( + "The onnxruntime python package is not installed. Please install it with `pip install onnxruntime`" + ) + try: + # Equivalent to from tokenizers import Tokenizer + self.Tokenizer = importlib.import_module("tokenizers").Tokenizer + except ImportError: + raise ValueError( + "The tokenizers python package is not installed. Please install it with `pip install tokenizers`" + ) + try: + # Equivalent to from tqdm import tqdm + self.tqdm = importlib.import_module("tqdm").tqdm + except ImportError: + raise ValueError( + "The tqdm python package is not installed. Please install it with `pip install tqdm`" + ) + + # Borrowed from https://gist.github.com/yanqd0/c13ed29e29432e3cf3e7c38467f42f51 + # Download with tqdm to preserve the sentence-transformers experience + @retry( + reraise=True, + stop=stop_after_attempt(3), + wait=wait_random(min=1, max=3), + retry=retry_if_exception(lambda e: "does not match expected SHA256" in str(e)), + ) + def _download(self, url: str, fname: str, chunk_size: int = 1024) -> None: + resp = requests.get(url, stream=True) + total = int(resp.headers.get("content-length", 0)) + with open(fname, "wb") as file, self.tqdm( + desc=str(fname), + total=total, + unit="iB", + unit_scale=True, + unit_divisor=1024, + ) as bar: + for data in resp.iter_content(chunk_size=chunk_size): + size = file.write(data) + bar.update(size) + if not _verify_sha256(fname, self._MODEL_SHA256): + # if the integrity of the file is not verified, remove it + os.remove(fname) + raise ValueError( + f"Downloaded file {fname} does not match expected SHA256 hash. Corrupted download or malicious file." + ) + + # Use pytorches default epsilon for division by zero + # https://pytorch.org/docs/stable/generated/torch.nn.functional.normalize.html + def _normalize(self, v: npt.NDArray) -> npt.NDArray: + norm = np.linalg.norm(v, axis=1) + norm[norm == 0] = 1e-12 + return cast(npt.NDArray, v / norm[:, np.newaxis]) + + def _forward(self, documents: List[str], batch_size: int = 32) -> npt.NDArray: + # We need to cast to the correct type because the type checker doesn't know that init_model_and_tokenizer will set the values + self.tokenizer = cast(self.Tokenizer, self.tokenizer) + self.model = cast(self.ort.InferenceSession, self.model) + all_embeddings = [] + for i in range(0, len(documents), batch_size): + batch = documents[i : i + batch_size] + encoded = [self.tokenizer.encode(d) for d in batch] + input_ids = np.array([e.ids for e in encoded]) + attention_mask = np.array([e.attention_mask for e in encoded]) + onnx_input = { + "input_ids": np.array(input_ids, dtype=np.int64), + "attention_mask": np.array(attention_mask, dtype=np.int64), + "token_type_ids": np.array( + [np.zeros(len(e), dtype=np.int64) for e in input_ids], + dtype=np.int64, + ), + } + model_output = self.model.run(None, onnx_input) + last_hidden_state = model_output[0] + # Perform mean pooling with attention weighting + input_mask_expanded = np.broadcast_to( + np.expand_dims(attention_mask, -1), last_hidden_state.shape + ) + embeddings = np.sum(last_hidden_state * input_mask_expanded, 1) / np.clip( + input_mask_expanded.sum(1), a_min=1e-9, a_max=None + ) + embeddings = self._normalize(embeddings).astype(np.float32) + all_embeddings.append(embeddings) + return np.concatenate(all_embeddings) + + @cached_property + def tokenizer(self) -> "Tokenizer": + tokenizer = self.Tokenizer.from_file( + os.path.join( + self.DOWNLOAD_PATH, self.EXTRACTED_FOLDER_NAME, "tokenizer.json" + ) + ) + # max_seq_length = 256, for some reason sentence-transformers uses 256 even though the HF config has a max length of 128 + # https://github.com/UKPLab/sentence-transformers/blob/3e1929fddef16df94f8bc6e3b10598a98f46e62d/docs/_static/html/models_en_sentence_embeddings.html#LL480 + tokenizer.enable_truncation(max_length=256) + tokenizer.enable_padding(pad_id=0, pad_token="[PAD]", length=256) + return tokenizer + + @cached_property + def model(self) -> "InferenceSession": + if self._preferred_providers is None or len(self._preferred_providers) == 0: + if len(self.ort.get_available_providers()) > 0: + logger.debug( + f"WARNING: No ONNX providers provided, defaulting to available providers: " + f"{self.ort.get_available_providers()}" + ) + self._preferred_providers = self.ort.get_available_providers() + elif not set(self._preferred_providers).issubset( + set(self.ort.get_available_providers()) + ): + raise ValueError( + f"Preferred providers must be subset of available providers: {self.ort.get_available_providers()}" + ) + return self.ort.InferenceSession( + os.path.join(self.DOWNLOAD_PATH, self.EXTRACTED_FOLDER_NAME, "model.onnx"), + # Since 1.9 onnyx runtime requires providers to be specified when there are multiple available - https://onnxruntime.ai/docs/api/python/api_summary.html + # This is probably not ideal but will improve DX as no exceptions will be raised in multi-provider envs + providers=self._preferred_providers, + ) + + def __call__(self, input: Documents) -> Embeddings: + # Only download the model when it is actually used + self._download_model_if_not_exists() + return cast(Embeddings, self._forward(input).tolist()) + + def _download_model_if_not_exists(self) -> None: + onnx_files = [ + "config.json", + "model.onnx", + "special_tokens_map.json", + "tokenizer_config.json", + "tokenizer.json", + "vocab.txt", + ] + extracted_folder = os.path.join(self.DOWNLOAD_PATH, self.EXTRACTED_FOLDER_NAME) + onnx_files_exist = True + for f in onnx_files: + if not os.path.exists(os.path.join(extracted_folder, f)): + onnx_files_exist = False + break + # Model is not downloaded yet + if not onnx_files_exist: + os.makedirs(self.DOWNLOAD_PATH, exist_ok=True) + if not os.path.exists( + os.path.join(self.DOWNLOAD_PATH, self.ARCHIVE_FILENAME) + ) or not _verify_sha256( + os.path.join(self.DOWNLOAD_PATH, self.ARCHIVE_FILENAME), + self._MODEL_SHA256, + ): + self._download( + url=self.MODEL_DOWNLOAD_URL, + fname=os.path.join(self.DOWNLOAD_PATH, self.ARCHIVE_FILENAME), + ) + with tarfile.open( + name=os.path.join(self.DOWNLOAD_PATH, self.ARCHIVE_FILENAME), + mode="r:gz", + ) as tar: + tar.extractall(path=self.DOWNLOAD_PATH) + + +def DefaultEmbeddingFunction() -> Optional[EmbeddingFunction[Documents]]: + if is_thin_client: + return None + else: + return ONNXMiniLM_L6_V2() + + +class GooglePalmEmbeddingFunction(EmbeddingFunction[Documents]): + """To use this EmbeddingFunction, you must have the google.generativeai Python package installed and have a PaLM API key.""" + + def __init__(self, api_key: str, model_name: str = "models/embedding-gecko-001"): + if not api_key: + raise ValueError("Please provide a PaLM API key.") + + if not model_name: + raise ValueError("Please provide the model name.") + + try: + import google.generativeai as palm + except ImportError: + raise ValueError( + "The Google Generative AI python package is not installed. Please install it with `pip install google-generativeai`" + ) + + palm.configure(api_key=api_key) + self._palm = palm + self._model_name = model_name + + def __call__(self, input: Documents) -> Embeddings: + return [ + self._palm.generate_embeddings(model=self._model_name, text=text)[ + "embedding" + ] + for text in input + ] + + +class GoogleGenerativeAiEmbeddingFunction(EmbeddingFunction[Documents]): + """To use this EmbeddingFunction, you must have the google.generativeai Python package installed and have a Google API key.""" + + """Use RETRIEVAL_DOCUMENT for the task_type for embedding, and RETRIEVAL_QUERY for the task_type for retrieval.""" + + def __init__( + self, + api_key: str, + model_name: str = "models/embedding-001", + task_type: str = "RETRIEVAL_DOCUMENT", + ): + if not api_key: + raise ValueError("Please provide a Google API key.") + + if not model_name: + raise ValueError("Please provide the model name.") + + try: + import google.generativeai as genai + except ImportError: + raise ValueError( + "The Google Generative AI python package is not installed. Please install it with `pip install google-generativeai`" + ) + + genai.configure(api_key=api_key) + self._genai = genai + self._model_name = model_name + self._task_type = task_type + self._task_title = None + if self._task_type == "RETRIEVAL_DOCUMENT": + self._task_title = "Embedding of single string" + + def __call__(self, input: Documents) -> Embeddings: + return [ + self._genai.embed_content( + model=self._model_name, + content=text, + task_type=self._task_type, + title=self._task_title, + )["embedding"] + for text in input + ] + + +class GoogleVertexEmbeddingFunction(EmbeddingFunction[Documents]): + # Follow API Quickstart for Google Vertex AI + # https://cloud.google.com/vertex-ai/docs/generative-ai/start/quickstarts/api-quickstart + # Information about the text embedding modules in Google Vertex AI + # https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings + def __init__( + self, + api_key: str, + model_name: str = "textembedding-gecko", + project_id: str = "cloud-large-language-models", + region: str = "us-central1", + ): + self._api_url = f"https://{region}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{region}/publishers/goole/models/{model_name}:predict" + self._session = requests.Session() + self._session.headers.update({"Authorization": f"Bearer {api_key}"}) + + def __call__(self, input: Documents) -> Embeddings: + embeddings = [] + for text in input: + response = self._session.post( + self._api_url, json={"instances": [{"content": text}]} + ).json() + + if "predictions" in response: + embeddings.append(response["predictions"]["embeddings"]["values"]) + + return embeddings + + +class OpenCLIPEmbeddingFunction(EmbeddingFunction[Union[Documents, Images]]): + def __init__( + self, model_name: str = "ViT-B-32", checkpoint: str = "laion2b_s34b_b79k" + ) -> None: + try: + import open_clip + except ImportError: + raise ValueError( + "The open_clip python package is not installed. Please install it with `pip install open-clip-torch`. https://github.com/mlfoundations/open_clip" + ) + try: + self._torch = importlib.import_module("torch") + except ImportError: + raise ValueError( + "The torch python package is not installed. Please install it with `pip install torch`" + ) + + try: + self._PILImage = importlib.import_module("PIL.Image") + except ImportError: + raise ValueError( + "The PIL python package is not installed. Please install it with `pip install pillow`" + ) + + model, _, preprocess = open_clip.create_model_and_transforms( + model_name=model_name, pretrained=checkpoint + ) + self._model = model + self._preprocess = preprocess + self._tokenizer = open_clip.get_tokenizer(model_name=model_name) + + def _encode_image(self, image: Image) -> Embedding: + pil_image = self._PILImage.fromarray(image) + with self._torch.no_grad(): + image_features = self._model.encode_image( + self._preprocess(pil_image).unsqueeze(0) + ) + image_features /= image_features.norm(dim=-1, keepdim=True) + return cast(Embedding, image_features.squeeze().tolist()) + + def _encode_text(self, text: Document) -> Embedding: + with self._torch.no_grad(): + text_features = self._model.encode_text(self._tokenizer(text)) + text_features /= text_features.norm(dim=-1, keepdim=True) + return cast(Embedding, text_features.squeeze().tolist()) + + def __call__(self, input: Union[Documents, Images]) -> Embeddings: + embeddings: Embeddings = [] + for item in input: + if is_image(item): + embeddings.append(self._encode_image(cast(Image, item))) + elif is_document(item): + embeddings.append(self._encode_text(cast(Document, item))) + return embeddings + + +class AmazonBedrockEmbeddingFunction(EmbeddingFunction[Documents]): + def __init__( + self, + session: "boto3.Session", # noqa: F821 # Quote for forward reference + model_name: str = "amazon.titan-embed-text-v1", + **kwargs: Any, + ): + """Initialize AmazonBedrockEmbeddingFunction. + + Args: + session (boto3.Session): The boto3 session to use. + model_name (str, optional): Identifier of the model, defaults to "amazon.titan-embed-text-v1" + **kwargs: Additional arguments to pass to the boto3 client. + + Example: + >>> import boto3 + >>> session = boto3.Session(profile_name="profile", region_name="us-east-1") + >>> bedrock = AmazonBedrockEmbeddingFunction(session=session) + >>> texts = ["Hello, world!", "How are you?"] + >>> embeddings = bedrock(texts) + """ + + self._model_name = model_name + + self._client = session.client( + service_name="bedrock-runtime", + **kwargs, + ) + + def __call__(self, input: Documents) -> Embeddings: + accept = "application/json" + content_type = "application/json" + embeddings = [] + for text in input: + input_body = {"inputText": text} + body = json.dumps(input_body) + response = self._client.invoke_model( + body=body, + modelId=self._model_name, + accept=accept, + contentType=content_type, + ) + embedding = json.load(response.get("body")).get("embedding") + embeddings.append(embedding) + return embeddings + + +class HuggingFaceEmbeddingServer(EmbeddingFunction[Documents]): + """ + This class is used to get embeddings for a list of texts using the HuggingFace Embedding server (https://github.com/huggingface/text-embeddings-inference). + The embedding model is configured in the server. + """ + + def __init__(self, url: str): + """ + Initialize the HuggingFaceEmbeddingServer. + + Args: + url (str): The URL of the HuggingFace Embedding Server. + """ + try: + import requests + except ImportError: + raise ValueError( + "The requests python package is not installed. Please install it with `pip install requests`" + ) + self._api_url = f"{url}" + self._session = requests.Session() + + def __call__(self, input: Documents) -> Embeddings: + """ + Get the embeddings for a list of texts. + + Args: + texts (Documents): A list of texts to get embeddings for. + + Returns: + Embeddings: The embeddings for the texts. + + Example: + >>> hugging_face = HuggingFaceEmbeddingServer(url="http://localhost:8080/embed") + >>> texts = ["Hello, world!", "How are you?"] + >>> embeddings = hugging_face(texts) + """ + # Call HuggingFace Embedding Server API for each document + return cast( + Embeddings, self._session.post(self._api_url, json={"inputs": input}).json() + ) + + +# List of all classes in this module +_classes = [ + name + for name, obj in inspect.getmembers(sys.modules[__name__], inspect.isclass) + if obj.__module__ == __name__ +] + + +def get_builtins() -> List[str]: + return _classes diff --git a/chromadb/utils/lru_cache.py b/chromadb/utils/lru_cache.py new file mode 100644 index 0000000000000000000000000000000000000000..e0e4f1c0347867691b7889b3ae5e92cfb7faf5ab --- /dev/null +++ b/chromadb/utils/lru_cache.py @@ -0,0 +1,32 @@ +from collections import OrderedDict +from typing import Any, Callable, Generic, Optional, TypeVar + + +K = TypeVar("K") +V = TypeVar("V") + + +class LRUCache(Generic[K, V]): + """A simple LRU cache implementation, based on the OrderedDict class, which allows + for a callback to be invoked when an item is evicted from the cache.""" + + def __init__(self, capacity: int, callback: Optional[Callable[[K, V], Any]] = None): + self.capacity = capacity + self.cache: OrderedDict[K, V] = OrderedDict() + self.callback = callback + + def get(self, key: K) -> Optional[V]: + if key not in self.cache: + return None + value = self.cache.pop(key) + self.cache[key] = value + return value + + def set(self, key: K, value: V) -> None: + if key in self.cache: + self.cache.pop(key) + elif len(self.cache) == self.capacity: + evicted_key, evicted_value = self.cache.popitem(last=False) + if self.callback: + self.callback(evicted_key, evicted_value) + self.cache[key] = value diff --git a/chromadb/utils/messageid.py b/chromadb/utils/messageid.py new file mode 100644 index 0000000000000000000000000000000000000000..9501f36c7598d575c2a2e6134213993cd9c4dbcc --- /dev/null +++ b/chromadb/utils/messageid.py @@ -0,0 +1,80 @@ +import pulsar + + +def pulsar_to_int(message_id: pulsar.MessageId) -> int: + ledger_id: int = message_id.ledger_id() + entry_id: int = message_id.entry_id() + batch_index: int = message_id.batch_index() + partition: int = message_id.partition() + + # Convert to offset binary encoding to preserve ordering semantics when encoded + # see https://en.wikipedia.org/wiki/Offset_binary + ledger_id = ledger_id + 2**63 + entry_id = entry_id + 2**63 + batch_index = batch_index + 2**31 + partition = partition + 2**31 + + return ledger_id << 128 | entry_id << 64 | batch_index << 32 | partition + + +def int_to_pulsar(message_id: int) -> pulsar.MessageId: + partition = message_id & 0xFFFFFFFF + batch_index = message_id >> 32 & 0xFFFFFFFF + entry_id = message_id >> 64 & 0xFFFFFFFFFFFFFFFF + ledger_id = message_id >> 128 & 0xFFFFFFFFFFFFFFFF + + partition = partition - 2**31 + batch_index = batch_index - 2**31 + entry_id = entry_id - 2**63 + ledger_id = ledger_id - 2**63 + + return pulsar.MessageId(partition, ledger_id, entry_id, batch_index) + + +def int_to_bytes(int: int) -> bytes: + """Convert int to a 24 byte big endian byte string""" + return int.to_bytes(24, "big") + + +def bytes_to_int(bytes: bytes) -> int: + """Convert a 24 byte big endian byte string to an int""" + return int.from_bytes(bytes, "big") + + +# Sorted in lexographic order +base85 = ( + "!#$%&()*+-0123456789;<=>?@ABCDEFGHIJKLMNOP" + + "QRSTUVWXYZ^_`abcdefghijklmnopqrstuvwxyz{|}~" +) + + +# not the most efficient way to do this, see benchmark function below +def _int_to_str(n: int) -> str: + if n < 85: + return base85[n] + else: + return _int_to_str(n // 85) + base85[n % 85] + + +def int_to_str(n: int) -> str: + return _int_to_str(n).rjust(36, "!") # left pad with '!' to 36 chars + + +def str_to_int(s: str) -> int: + return sum(base85.index(c) * 85**i for i, c in enumerate(s[::-1])) + + +# 1m in 5 seconds on a M1 Pro +# Not fast, but not likely to be a bottleneck either +def _benchmark() -> None: + import random + import time + + t0 = time.time() + for i in range(1000000): + x = random.randint(0, 2**192 - 1) + s = int_to_str(x) + if s == "!": # prevent compiler from optimizing out + print("oops") + t1 = time.time() + print(t1 - t0) diff --git a/chromadb/utils/read_write_lock.py b/chromadb/utils/read_write_lock.py new file mode 100644 index 0000000000000000000000000000000000000000..c6863049bd601520dd1bad66cb238cff067b8c75 --- /dev/null +++ b/chromadb/utils/read_write_lock.py @@ -0,0 +1,74 @@ +import threading +from types import TracebackType +from typing import Optional, Type + + +class ReadWriteLock: + """A lock object that allows many simultaneous "read locks", but + only one "write lock." """ + + def __init__(self) -> None: + self._read_ready = threading.Condition(threading.RLock()) + self._readers = 0 + + def acquire_read(self) -> None: + """Acquire a read lock. Blocks only if a thread has + acquired the write lock.""" + self._read_ready.acquire() + try: + self._readers += 1 + finally: + self._read_ready.release() + + def release_read(self) -> None: + """Release a read lock.""" + self._read_ready.acquire() + try: + self._readers -= 1 + if not self._readers: + self._read_ready.notify_all() + finally: + self._read_ready.release() + + def acquire_write(self) -> None: + """Acquire a write lock. Blocks until there are no + acquired read or write locks.""" + self._read_ready.acquire() + while self._readers > 0: + self._read_ready.wait() + + def release_write(self) -> None: + """Release a write lock.""" + self._read_ready.release() + + +class ReadRWLock: + def __init__(self, rwLock: ReadWriteLock): + self.rwLock = rwLock + + def __enter__(self) -> None: + self.rwLock.acquire_read() + + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_value: Optional[BaseException], + traceback: Optional[TracebackType], + ) -> None: + self.rwLock.release_read() + + +class WriteRWLock: + def __init__(self, rwLock: ReadWriteLock): + self.rwLock = rwLock + + def __enter__(self) -> None: + self.rwLock.acquire_write() + + def __exit__( + self, + exc_type: Optional[Type[BaseException]], + exc_value: Optional[BaseException], + traceback: Optional[TracebackType], + ) -> None: + self.rwLock.release_write() diff --git a/chromadb/utils/rendezvous_hash.py b/chromadb/utils/rendezvous_hash.py new file mode 100644 index 0000000000000000000000000000000000000000..0db248f93ac1fb8ac3b16032cfda1ecd847562d6 --- /dev/null +++ b/chromadb/utils/rendezvous_hash.py @@ -0,0 +1,50 @@ +# An implementation of https://en.wikipedia.org/wiki/Rendezvous_hashing +from typing import Callable, List, cast +import mmh3 + +Hasher = Callable[[str, str], int] +Member = str +Members = List[str] +Key = str + + +def assign(key: Key, members: Members, hasher: Hasher) -> Member: + """Assigns a key to a member using the rendezvous hashing algorithm""" + if len(members) == 0: + raise ValueError("Cannot assign key to empty memberlist") + if len(members) == 1: + return members[0] + if key == "": + raise ValueError("Cannot assign empty key") + + max_score = -1 + max_member = None + + for member in members: + score = hasher(member, key) + if score > max_score: + max_score = score + max_member = member + + max_member = cast(Member, max_member) + return max_member + + +def merge_hashes(x: int, y: int) -> int: + """murmurhash3 mix 64-bit""" + acc = x ^ y + acc ^= acc >> 33 + acc = ( + acc * 0xFF51AFD7ED558CCD + ) % 2**64 # We need to mod here to prevent python from using arbitrary size int + acc ^= acc >> 33 + acc = (acc * 0xC4CEB9FE1A85EC53) % 2**64 + acc ^= acc >> 33 + return acc + + +def murmur3hasher(member: Member, key: Key) -> int: + """Hashes the key and member using the murmur3 hashing algorithm""" + member_hash = mmh3.hash64(member, signed=False)[0] + key_hash = mmh3.hash64(key, signed=False)[0] + return merge_hashes(member_hash, key_hash) diff --git a/clients/js/.gitignore b/clients/js/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..c28c5628ab0fdde75c9e72583fc4d8908885d018 --- /dev/null +++ b/clients/js/.gitignore @@ -0,0 +1,8 @@ + +node_modules +.DS_Store +.env + +# parcel related +.parcel-cache +dist diff --git a/clients/js/.prettierignore b/clients/js/.prettierignore new file mode 100644 index 0000000000000000000000000000000000000000..7b85a9d89340c5200c47921cf9d2e7c892fa78e5 --- /dev/null +++ b/clients/js/.prettierignore @@ -0,0 +1,3 @@ +dist +node_modules +src/generated diff --git a/clients/js/.prettierrc.json b/clients/js/.prettierrc.json new file mode 100644 index 0000000000000000000000000000000000000000..0967ef424bce6791893e9a57bb952f80fd536e93 --- /dev/null +++ b/clients/js/.prettierrc.json @@ -0,0 +1 @@ +{} diff --git a/clients/js/DEVELOP.md b/clients/js/DEVELOP.md new file mode 100644 index 0000000000000000000000000000000000000000..c82fd15327ed4d7baf6ba3b30b7702f08b433995 --- /dev/null +++ b/clients/js/DEVELOP.md @@ -0,0 +1,67 @@ +# Develop + +This readme is helpful for local dev. + +### Prereqs: + +- Make sure you have Java installed (for the generator). You can download it from [java.com](https://java.com) +- Make sure you set ALLOW_RESET=True for your Docker Container. If you don't do this, tests won't pass. +``` +environment: + - IS_PERSISTENT=TRUE + - ALLOW_RESET=True +``` +- Make sure you are running the docker backend at localhost:8000 (\*there is probably a way to stand up the fastapi server by itself and programmatically in the loop of generating this, but not prioritizing it for now. It may be important for the release) + +### Generating + +1. `yarn` to install deps +2. `yarn genapi` +3. Examples are in the `examples` folder. There is one for the browser and one for node. Run them with `yarn dev`, eg `cd examples/browser && yarn dev` + +### Running test + +`yarn test` will launch a test docker backend, run a db cleanup and run tests. +`yarn test:run` will run against the docker backend you have running. But CAUTION, it will delete data. This is the easiest and fastest way to run tests. + +### Pushing to npm + +#### Automatically + +##### Increase the version number +1. Create a new PR for the release that upgrades the version in code. Name it `js_release/A.B.C` for production releases and `js_release_alpha/A.B.C` for alpha releases. In the package.json update the version number to the new version. For production releases this is just the version number, for alpha +releases this is the version number with '-alphaX' appended to it. For example, if the current version is 1.0.0, the alpha release would be 1.0.0-alpha1 for the first alpha release, 1.0.0-alpha2 for the second alpha release, etc. +2. Add the "release" label to this PR +3. Once the PR is merged, tag your commit SHA with the release version + +```bash +git tag js_release_A.B.C + +# or for alpha releases: + +git tag js_release_alpha_A.B.C +``` + +4. You need to then wait for the github action for main for `chroma js release` to complete on main. + +##### Perform the release +1. Push your tag to origin to create the release + +```bash + +git push origin js_release_A.B.C + +# or for alpha releases: + +git push origin js_release_alpha_A.B.C +``` +2. This will trigger a Github action which performs the release + +#### Manually +`npm run release` pushes the `package.json` defined packaged to the package manager for authenticated users. It will build, test, and then publish the new version. + + + +### Useful links + +https://gaganpreet.in/posts/hyperproductive-apis-fastapi/ diff --git a/clients/js/LICENSE b/clients/js/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..261eeb9e9f8b2b4b0d119366dda99c6fd7d35c64 --- /dev/null +++ b/clients/js/LICENSE @@ -0,0 +1,201 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. Definitions. + + "License" shall mean the terms and conditions for use, reproduction, + and distribution as defined by Sections 1 through 9 of this document. + + "Licensor" shall mean the copyright owner or entity authorized by + the copyright owner that is granting the License. + + "Legal Entity" shall mean the union of the acting entity and all + other entities that control, are controlled by, or are under common + control with that entity. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/clients/js/README.md b/clients/js/README.md new file mode 100644 index 0000000000000000000000000000000000000000..13020e455426cd450df413f0c80dd7fc3e65c6e4 --- /dev/null +++ b/clients/js/README.md @@ -0,0 +1,43 @@ +## chromadb + +Chroma is the open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs. + +This package gives you a JS/TS interface to talk to a backend Chroma DB over REST. + +[Learn more about Chroma](https://github.com/chroma-core/chroma) + +- [💬 Community Discord](https://discord.gg/MMeYNTmh3x) +- [📖 Documentation](https://docs.trychroma.com/) +- [💡 Colab Example](https://colab.research.google.com/drive/1QEzFyqnoFxq7LUGyP1vzR4iLt9PpCDXv?usp=sharing) +- [🏠 Homepage](https://www.trychroma.com/) + +## Getting started + +Chroma needs to be running in order for this client to talk to it. Please see the [🧪 Usage Guide](https://docs.trychroma.com/usage-guide) to learn how to quickly stand this up. + +## Small example + +```js +import { ChromaClient } from "chromadb"; +const chroma = new ChromaClient({ path: "http://localhost:8000" }); +const collection = await chroma.createCollection({ name: "test-from-js" }); +for (let i = 0; i < 20; i++) { + await collection.add({ + ids: ["test-id-" + i.toString()], + embeddings: [1, 2, 3, 4, 5], + documents: ["test"], + }); +} +const queryData = await collection.query({ + queryEmbeddings: [1, 2, 3, 4, 5], + queryTexts: ["test"], +}); +``` + +## Local development + +[View the Development Readme](./DEVELOP.md) + +## License + +Apache 2.0 diff --git a/clients/js/config.yml b/clients/js/config.yml new file mode 100644 index 0000000000000000000000000000000000000000..8251a42de21494b2145f2e33f693fc024a76ee38 --- /dev/null +++ b/clients/js/config.yml @@ -0,0 +1,5 @@ +# OpenAPI Generator Plus generator configuration +inputPath: openapi.json +outputPath: src/generated +generator: "@openapi-generator-plus/typescript-fetch-client-generator" +# See https://github.com/karlvr/openapi-generator-plus-generators/tree/master/packages/typescript-fetch-node-client#readme for more configuration options diff --git a/clients/js/examples/browser/README.md b/clients/js/examples/browser/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b366b3eedeb3abe78cc57ca88c0a4de19778a074 --- /dev/null +++ b/clients/js/examples/browser/README.md @@ -0,0 +1,16 @@ +## Demo in browser + +Update your settings to add `localhost:3000` to `chroma_server_cors_allow_origins`. + +For example in `docker-compose.yml` + +``` +environment: + - CHROMA_DB_IMPL=clickhouse + - CLICKHOUSE_HOST=clickhouse + - CLICKHOUSE_PORT=8123 + - CHROMA_SERVER_CORS_ALLOW_ORIGINS=["http://localhost:3000"] +``` + +1. `yarn dev` +2. visit `localhost:3000` diff --git a/clients/js/examples/browser/app.ts b/clients/js/examples/browser/app.ts new file mode 100644 index 0000000000000000000000000000000000000000..afc9ddbb7661620b4ed8a4cc254c3f6c9e23d97e --- /dev/null +++ b/clients/js/examples/browser/app.ts @@ -0,0 +1,53 @@ +import { ChromaClient } from '../../src/ChromaClient'; +// import env.ts + +window.onload = async () => { + const chroma = new ChromaClient({ path: "http://localhost:8000" }); + await chroma.reset(); + + const collection = await chroma.createCollection({ name: "test-from-js" }); + console.log("collection", collection); + + // first generate some data + var ids: string[] = []; + var embeddings: Array = []; + var metadatas: Array = []; + for (let i = 0; i < 100; i++) { + ids.push("test-id-" + i.toString()); + embeddings.push([1, 2, 3, 4, 5]); + metadatas.push({ test: "test" }); + } + + let add = await collection.add({ ids, embeddings, metadatas }); + console.log("add", add); + + let count = await collection.count(); + console.log("count", count); + + const queryData = await collection.query({ + queryEmbeddings: [1, 2, 3, 4, 5], + nResults: 5, + where: { test: "test" } + }); + + console.log("queryData", queryData); + + await collection.delete(); + + let count2 = await collection.count(); + console.log("count2", count2); + + const collections = await chroma.listCollections(); + console.log("collections", collections); + + // this code is commented out so that it is easy to see the output on the page if desired + // let node; + // node = document.querySelector("#list-collections-result"); + // node!.innerHTML = `
${JSON.stringify(collections.data, null, 4)}
`; + // node = document.querySelector("#collection-count"); + // node!.innerHTML = `
${count}
`; + // node = document.querySelector("#collection-get"); + // node!.innerHTML = `
${JSON.stringify(getData, null, 4)}
`; + // node = document.querySelector("#collection-query"); + // node!.innerHTML = `
${JSON.stringify(queryData, null, 4)}
`; +}; diff --git a/clients/js/examples/browser/index.html b/clients/js/examples/browser/index.html new file mode 100644 index 0000000000000000000000000000000000000000..08a31a1d8dca6cf33b9240ab13182bc00430064f --- /dev/null +++ b/clients/js/examples/browser/index.html @@ -0,0 +1,35 @@ + + + + + Demo App + + + + +

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+ + + diff --git a/clients/js/examples/browser/package.json b/clients/js/examples/browser/package.json new file mode 100644 index 0000000000000000000000000000000000000000..76aac5290f3b299ac6e36a83e0b9256483e74152 --- /dev/null +++ b/clients/js/examples/browser/package.json @@ -0,0 +1,19 @@ +{ + "name": "example-browser", + "version": "1.0.1", + "description": "example app", + "keywords": [], + "author": "", + "license": "Apache-2.0", + "devDependencies": { + "parcel": "^2.6.0", + "process": "^0.11.10" + }, + "dependencies": { + "chromadb": "file:../.." + }, + "scripts": { + "dev": "parcel ./index.html --port 3000 --no-cache", + "start": "parcel ./index.html --port 3000 --no-cache" + } +} diff --git a/clients/js/examples/browser/yarn.lock b/clients/js/examples/browser/yarn.lock new file mode 100644 index 0000000000000000000000000000000000000000..1fedb43e444eae69df0b0784cc8378a846089750 --- /dev/null +++ b/clients/js/examples/browser/yarn.lock @@ -0,0 +1,1476 @@ +# THIS IS AN AUTOGENERATED FILE. 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chroma.GoogleGenerativeAiEmbeddingFunction({ googleApiKey:"" }); + + const collection = await cc.createCollection({ + name: "test-from-js", + embeddingFunction: google, + }); + + await collection.add({ + ids: ["doc1", "doc2"], + documents: [ + "doc1", + "doc2", + ] + }); + + let count = await collection.count(); + console.log("count", count); + + const googleQuery = new chroma.GoogleGenerativeAiEmbeddingFunction({ googleApiKey:"", taskType: 'RETRIEVAL_QUERY' }); + + const queryCollection = await cc.getCollection({ + name: "test-from-js", + embeddingFunction: googleQuery, + }); + + const query = await collection.query({ + queryTexts: ["doc1"], + nResults: 1 + }); + console.log("query", query); + + console.log("COMPLETED"); + + const collections = await cc.listCollections(); + console.log('collections', collections) + + res.send('Hello World!'); +}); +app.listen(3000, function () { + console.log("Example app listening on port 3000!"); +}); diff --git a/clients/js/examples/node/package.json b/clients/js/examples/node/package.json new file mode 100644 index 0000000000000000000000000000000000000000..03821cfd2fd7dfa54ecdec3c3267ca76228259ad --- /dev/null +++ b/clients/js/examples/node/package.json @@ -0,0 +1,21 @@ +{ + "name": "example-node", + "version": "1.0.0", + "description": "", + "main": "app.js", + "scripts": { + "test": "echo \"Error: no test specified\" && exit 1", + "dev": "node app.js", + "start": "node app.js", + "rebuild": "cd ../.. && yarn && yarn build && cd examples/node && rm -rf node_modules && yarn && yarn dev" + }, + "author": "", + "license": "ISC", + "dependencies": { + "@google/generative-ai": "^0.1.1", + "chromadb": "file:../..", + "cohere-ai": "^5.0.2", + "express": "^4.18.2", + "openai": "^3.1.0" + } +} diff --git a/clients/js/examples/node/yarn.lock b/clients/js/examples/node/yarn.lock new file mode 100644 index 0000000000000000000000000000000000000000..9fb2312c5b8f23c7b0470854f4baabb98b4a09cd --- /dev/null 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0000000000000000000000000000000000000000..398db3f48c8496a3a6c7bb99e059168b7f79511e --- /dev/null +++ b/clients/js/genapi.sh @@ -0,0 +1,31 @@ +#!/usr/bin/env sh + +# curl -s http://localhost:8000/openapi.json | jq > openapi.json +curl -s http://localhost:8000/openapi.json | python -c "import sys, json; print(json.dumps(json.load(sys.stdin), indent=2))" > openapi.json + +if [[ "$OSTYPE" == "darwin"* ]]; then + # macOS + sed -i '' 's/"schema": {}/"schema": {"type": "object"}/g' openapi.json + sed -i '' 's/"items": {}/"items": { "type": "object" }/g' openapi.json + sed -i '' -e 's/"title": "Collection Name"/"title": "Collection Name","type": "string"/g' openapi.json +else + # Linux + sed -i 's/"schema": {}/"schema": {"type": "object"}/g' openapi.json + sed -i 's/"items": {}/"items": { "type": "object" }/g' openapi.json + sed -i -e 's/"title": "Collection Name"/"title": "Collection Name","type": "string"/g' openapi.json +fi + +openapi-generator-plus -c config.yml + +if [[ "$OSTYPE" == "darwin"* ]]; then + sed -i '' -e '/import "whatwg-fetch";/d' -e 's/window.fetch/fetch/g' src/generated/runtime.ts +else + sed -i -e '/import "whatwg-fetch";/d' -e 's/window.fetch/fetch/g' src/generated/runtime.ts +fi + +# Add isomorphic-fetch dependency to runtime.ts +echo "import 'isomorphic-fetch';" > temp.txt +cat src/generated/runtime.ts >> temp.txt +mv temp.txt src/generated/runtime.ts + +rm openapi.json diff --git a/clients/js/jest.config.ts b/clients/js/jest.config.ts new file mode 100644 index 0000000000000000000000000000000000000000..e497b0e8c79f5f1f7352870cc0b605eaf2a49511 --- /dev/null +++ b/clients/js/jest.config.ts @@ -0,0 +1,19 @@ +import type { Config } from "@jest/types"; + +const config: Config.InitialOptions = { + preset: "ts-jest", + testEnvironment: "node", + clearMocks: true, + collectCoverage: false, + testTimeout: 15000, + coverageDirectory: "./test/coverage", + coverageReporters: ["json", "html", "lcov"], + collectCoverageFrom: [ + "./src/**/*.{js,ts}", + "./src/**/*.unit.test.ts", + "!**/node_modules/**", + "!**/vendor/**", + "!**/vendor/**", + ], +}; +export default config; diff --git a/clients/js/openapitools.json b/clients/js/openapitools.json new file mode 100644 index 0000000000000000000000000000000000000000..f524df577135bf7a2416cfe3aac5817b406710f8 --- /dev/null +++ b/clients/js/openapitools.json @@ -0,0 +1,7 @@ +{ + "$schema": "./node_modules/@openapitools/openapi-generator-cli/config.schema.json", + "spaces": 2, + "generator-cli": { + "version": "5.3.1" + } +} diff --git a/clients/js/package.json b/clients/js/package.json new file mode 100644 index 0000000000000000000000000000000000000000..5fa81664bad11cd04912a624f7bb127cb4bc2dd8 --- /dev/null +++ b/clients/js/package.json @@ -0,0 +1,94 @@ +{ + "name": "chromadb", + "version": "1.8.1", + "description": "A JavaScript interface for chroma", + "keywords": [], + "author": "", + "license": "Apache-2.0", + "devDependencies": { + "@openapi-generator-plus/typescript-fetch-client-generator": "^1.5.0", + "@types/jest": "^29.5.0", + "@types/node": "^20.8.10", + "jest": "^29.5.0", + "npm-run-all": "^4.1.5", + "openapi-generator-plus": "^2.6.0", + "openapi-types": "^12.1.3", + "prettier": "2.8.7", + "rimraf": "^5.0.0", + "ts-jest": "^29.1.0", + "ts-node": "^10.9.1", + "tsd": "^0.28.1", + "tsup": "^7.2.0", + "typescript": "^5.0.4" + }, + "type": "module", + "main": "dist/cjs/chromadb.cjs", + "module": "dist/chromadb.legacy-esm.js", + "exports": { + ".": { + "import": { + "types": "./dist/chromadb.d.ts", + "default": "./dist/chromadb.mjs" + }, + "require": { + "types": "./dist/cjs/chromadb.d.cts", + "default": "./dist/cjs/chromadb.cjs" + } + } + }, + "files": [ + "src", + "dist" + ], + "scripts": { + "test": "run-s db:clean db:cleanauth db:run test:runfull db:clean test:runfull-authonly db:cleanauth", + "testnoauth": "run-s db:clean db:run test:runfull db:clean", + "testauth": "run-s db:cleanauth test:runfull-authonly db:cleanauth", + "test:set-port": "cross-env URL=localhost:8001", + "test:run": "jest --runInBand --testPathIgnorePatterns=test/auth.*.test.ts", + "test:run-auth-basic": "jest --runInBand --testPathPattern=test/auth.basic.test.ts", + "test:run-auth-token": "jest --runInBand --testPathPattern=test/auth.token.test.ts", + "test:run-auth-xtoken": "XTOKEN_TEST=true jest --runInBand --testPathPattern=test/auth.token.test.ts", + "test:runfull": "PORT=8001 jest --runInBand --testPathIgnorePatterns=test/auth.*.test.ts", + "test:runfull-authonly": "run-s db:run-auth-basic test:runfull-authonly-basic db:clean db:run-auth-token test:runfull-authonly-token db:clean db:run-auth-xtoken test:runfull-authonly-xtoken db:clean", + "test:runfull-authonly-basic": "PORT=8001 jest --runInBand --testPathPattern=test/auth.basic.test.ts", + "test:runfull-authonly-token": "PORT=8001 jest --runInBand --testPathPattern=test/auth.token.test.ts", + "test:runfull-authonly-xtoken": "PORT=8001 XTOKEN_TEST=true jest --runInBand --testPathPattern=test/auth.token.test.ts", + "test:update": "run-s db:clean db:run && jest --runInBand --updateSnapshot && run-s db:clean", + "db:clean": "cd ../.. && CHROMA_PORT=8001 docker-compose -f docker-compose.test.yml down --volumes", + "db:cleanauth": "cd ../.. && CHROMA_PORT=8001 docker-compose -f docker-compose.test-auth.yml down --volumes", + "db:run": "cd ../.. && CHROMA_PORT=8001 docker-compose -f docker-compose.test.yml up --detach && sleep 5", + "db:run-auth-basic": "cd ../.. && docker run --rm --entrypoint htpasswd httpd:2 -Bbn admin admin > server.htpasswd && echo \"CHROMA_SERVER_AUTH_CREDENTIALS_FILE=/chroma/server.htpasswd\\nCHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider\\nCHROMA_SERVER_AUTH_PROVIDER=chromadb.auth.basic.BasicAuthServerProvider\\nCHROMA_PORT=8001\" > .chroma_env && docker-compose -f docker-compose.test-auth.yml --env-file ./.chroma_env up --detach && sleep 5", + "db:run-auth-token": "cd ../.. && echo \"CHROMA_SERVER_AUTH_CREDENTIALS=test-token\nCHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=chromadb.auth.token.TokenConfigServerAuthCredentialsProvider\nCHROMA_SERVER_AUTH_PROVIDER=chromadb.auth.token.TokenAuthServerProvider\\nCHROMA_PORT=8001\" > .chroma_env && docker-compose -f docker-compose.test-auth.yml --env-file ./.chroma_env up --detach && sleep 5", + "db:run-auth-xtoken": "cd ../.. && echo \"CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER=X_CHROMA_TOKEN\nCHROMA_SERVER_AUTH_CREDENTIALS=test-token\nCHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=chromadb.auth.token.TokenConfigServerAuthCredentialsProvider\nCHROMA_SERVER_AUTH_PROVIDER=chromadb.auth.token.TokenAuthServerProvider\\nCHROMA_PORT=8001\" > .chroma_env && docker-compose -f docker-compose.test-auth.yml --env-file ./.chroma_env up --detach && sleep 5", + "prebuild": "rimraf dist", + "build": "tsup", + "genapi": "./genapi.sh", + "prettier": "prettier --write .", + "release": "run-s build test:run && npm publish", + "release_alpha": "run-s build test:run && npm publish --tag alpha" + }, + "engines": { + "node": ">=14.17.0" + }, + "dependencies": { + "isomorphic-fetch": "^3.0.0", + "cliui": "^8.0.1" + }, + "peerDependencies": { + "@google/generative-ai": "^0.1.1", + "cohere-ai": "^5.0.0 || ^6.0.0 || ^7.0.0", + "openai": "^3.0.0 || ^4.0.0" + }, + "peerDependenciesMeta": { + "@google/generative-ai": { + "optional": true + }, + "cohere-ai": { + "optional": true + }, + "openai": { + "optional": true + } + } +} diff --git a/clients/js/src/AdminClient.ts b/clients/js/src/AdminClient.ts new file mode 100644 index 0000000000000000000000000000000000000000..7de713e8d4e3d0a4592d7dc43a843043906dfbe6 --- /dev/null +++ b/clients/js/src/AdminClient.ts @@ -0,0 +1,272 @@ +import { Configuration, ApiApi as DefaultApi } from "./generated"; +import { handleSuccess, handleError, validateTenantDatabase } from "./utils"; +import { ConfigOptions } from './types'; +import { + AuthOptions, + ClientAuthProtocolAdapter, + IsomorphicFetchClientAuthProtocolAdapter +} from "./auth"; + +const DEFAULT_TENANT = "default_tenant" +const DEFAULT_DATABASE = "default_database" + +// interface for tenant +interface Tenant { + name: string, +} + +// interface for tenant +interface Database { + name: string, +} + +export class AdminClient { + /** + * @ignore + */ + private api: DefaultApi & ConfigOptions; + private apiAdapter: ClientAuthProtocolAdapter|undefined; + public tenant: string = DEFAULT_TENANT; + public database: string = DEFAULT_DATABASE; + + /** + * Creates a new AdminClient instance. + * @param {Object} params - The parameters for creating a new client + * @param {string} [params.path] - The base path for the Chroma API. + * @returns {AdminClient} A new AdminClient instance. + * + * @example + * ```typescript + * const client = new AdminClient({ + * path: "http://localhost:8000" + * }); + * ``` + */ + constructor({ + path, + fetchOptions, + auth, + tenant = DEFAULT_TENANT, + database = DEFAULT_DATABASE + }: { + path?: string, + fetchOptions?: RequestInit, + auth?: AuthOptions, + tenant?: string, + database?: string, + } = {}) { + if (path === undefined) path = "http://localhost:8000"; + this.tenant = tenant; + this.database = database; + + const apiConfig: Configuration = new Configuration({ + basePath: path, + }); + if (auth !== undefined) { + this.apiAdapter = new IsomorphicFetchClientAuthProtocolAdapter(new DefaultApi(apiConfig), auth); + this.api = this.apiAdapter.getApi(); + } else { + this.api = new DefaultApi(apiConfig); + } + + this.api.options = fetchOptions ?? {}; + } + + /** + * Sets the tenant and database for the client. + * + * @param {Object} params - The parameters for setting tenant and database. + * @param {string} params.tenant - The name of the tenant. + * @param {string} params.database - The name of the database. + * + * @returns {Promise} A promise that returns nothing + * @throws {Error} Any issues + * + * @example + * ```typescript + * await adminClient.setTenant({ + * tenant: "my_tenant", + * database: "my_database", + * }); + * ``` + */ + public async setTenant({ + tenant = DEFAULT_TENANT, + database = DEFAULT_DATABASE + }: { + tenant: string, + database?: string, + }): Promise { + await validateTenantDatabase(this, tenant, database); + this.tenant = tenant; + this.database = database; + } + + /** + * Sets the database for the client. + * + * @param {Object} params - The parameters for setting the database. + * @param {string} params.database - The name of the database. + * + * @returns {Promise} A promise that returns nothing + * @throws {Error} Any issues + * + * @example + * ```typescript + * await adminClient.setDatabase({ + * database: "my_database", + * }); + * ``` + */ + public async setDatabase({ + database = DEFAULT_DATABASE + }: { + database?: string, + }): Promise { + await validateTenantDatabase(this, this.tenant, database); + this.database = database; + } + + /** + * Creates a new tenant with the specified properties. + * + * @param {Object} params - The parameters for creating a new tenant. + * @param {string} params.name - The name of the tenant. + * + * @returns {Promise} A promise that resolves to the created tenant. + * @throws {Error} If there is an issue creating the tenant. + * + * @example + * ```typescript + * await adminClient.createTenant({ + * name: "my_tenant", + * }); + * ``` + */ + public async createTenant({ + name, + }: { + name: string, + }): Promise { + const newTenant = await this.api + .createTenant({name}, this.api.options) + .then(handleSuccess) + .catch(handleError); + + // newTenant is null if successful + if (newTenant && newTenant.error) { + throw new Error(newTenant.error); + } + + return {name: name} as Tenant + } + + /** + * Gets a tenant with the specified properties. + * + * @param {Object} params - The parameters for getting a tenant. + * @param {string} params.name - The name of the tenant. + * + * @returns {Promise} A promise that resolves to the tenant. + * @throws {Error} If there is an issue getting the tenant. + * + * @example + * ```typescript + * await adminClient.getTenant({ + * name: "my_tenant", + * }); + * ``` + */ + public async getTenant({ + name, + }: { + name: string, + }): Promise { + const getTenant = await this.api + .getTenant(name, this.api.options) + .then(handleSuccess) + .catch(handleError); + + if (getTenant.error) { + throw new Error(getTenant.error); + } + + return {name: getTenant.name} as Tenant + } + + /** + * Creates a new database with the specified properties. + * + * @param {Object} params - The parameters for creating a new database. + * @param {string} params.name - The name of the database. + * @param {string} params.tenantName - The name of the tenant. + * + * @returns {Promise} A promise that resolves to the created database. + * @throws {Error} If there is an issue creating the database. + * + * @example + * ```typescript + * await adminClient.createDatabase({ + * name: "my_database", + * tenantName: "my_tenant", + * }); + * ``` + */ + public async createDatabase({ + name, + tenantName + }: { + name: string, + tenantName: string, + }): Promise { + const newDatabase = await this.api + .createDatabase(tenantName, {name}, this.api.options) + .then(handleSuccess) + .catch(handleError); + + // newDatabase is null if successful + if (newDatabase && newDatabase.error) { + throw new Error(newDatabase.error); + } + + return {name: name} as Database + } + + /** + * Gets a database with the specified properties. + * + * @param {Object} params - The parameters for getting a database. + * @param {string} params.name - The name of the database. + * @param {string} params.tenantName - The name of the tenant. + * + * @returns {Promise} A promise that resolves to the database. + * @throws {Error} If there is an issue getting the database. + * + * @example + * ```typescript + * await adminClient.getDatabase({ + * name: "my_database", + * tenantName: "my_tenant", + * }); + * ``` + */ + public async getDatabase({ + name, + tenantName + }: { + name: string, + tenantName: string, + }): Promise { + const getDatabase = await this.api + .getDatabase(name, tenantName, this.api.options) + .then(handleSuccess) + .catch(handleError); + + if (getDatabase.error) { + throw new Error(getDatabase.error); + } + + return {name: getDatabase.name} as Database + } + +} diff --git a/clients/js/src/ChromaClient.ts b/clients/js/src/ChromaClient.ts new file mode 100644 index 0000000000000000000000000000000000000000..76edd4e960ea40c89237391a8e1be686e9b805d9 --- /dev/null +++ b/clients/js/src/ChromaClient.ts @@ -0,0 +1,327 @@ +import { IEmbeddingFunction } from './embeddings/IEmbeddingFunction'; +import { Configuration, ApiApi as DefaultApi } from "./generated"; +import { handleSuccess, handleError } from "./utils"; +import { Collection } from './Collection'; +import { ChromaClientParams, CollectionMetadata, CollectionType, ConfigOptions, CreateCollectionParams, DeleteCollectionParams, GetCollectionParams, GetOrCreateCollectionParams, ListCollectionsParams } from './types'; +import { + AuthOptions, + ClientAuthProtocolAdapter, + IsomorphicFetchClientAuthProtocolAdapter +} from "./auth"; +import { DefaultEmbeddingFunction } from './embeddings/DefaultEmbeddingFunction'; +import { AdminClient } from './AdminClient'; + +const DEFAULT_TENANT = "default_tenant" +const DEFAULT_DATABASE = "default_database" + +export class ChromaClient { + /** + * @ignore + */ + private api: DefaultApi & ConfigOptions; + private apiAdapter: ClientAuthProtocolAdapter|undefined; + private tenant: string = DEFAULT_TENANT; + private database: string = DEFAULT_DATABASE; + private _adminClient?: AdminClient + + /** + * Creates a new ChromaClient instance. + * @param {Object} params - The parameters for creating a new client + * @param {string} [params.path] - The base path for the Chroma API. + * @returns {ChromaClient} A new ChromaClient instance. + * + * @example + * ```typescript + * const client = new ChromaClient({ + * path: "http://localhost:8000" + * }); + * ``` + */ + constructor({ + path, + fetchOptions, + auth, + tenant = DEFAULT_TENANT, + database = DEFAULT_DATABASE, + }: ChromaClientParams = {}) { + if (path === undefined) path = "http://localhost:8000"; + this.tenant = tenant; + this.database = database; + + const apiConfig: Configuration = new Configuration({ + basePath: path, + }); + + if (auth !== undefined) { + this.apiAdapter = new IsomorphicFetchClientAuthProtocolAdapter(new DefaultApi(apiConfig), auth); + this.api = this.apiAdapter.getApi(); + } else { + this.api = new DefaultApi(apiConfig); + } + + this._adminClient = new AdminClient({ + path: path, + fetchOptions: fetchOptions, + auth: auth, + tenant: tenant, + database: database + }); + + // TODO: Validate tenant and database on client creation + // this got tricky because: + // - the constructor is sync but the generated api is async + // - we need to inject auth information so a simple rewrite/fetch does not work + + this.api.options = fetchOptions ?? {}; + } + + /** + * Resets the state of the object by making an API call to the reset endpoint. + * + * @returns {Promise} A promise that resolves when the reset operation is complete. + * @throws {Error} If there is an issue resetting the state. + * + * @example + * ```typescript + * await client.reset(); + * ``` + */ + public async reset(): Promise { + return await this.api.reset(this.api.options); + } + + /** + * Returns the version of the Chroma API. + * @returns {Promise} A promise that resolves to the version of the Chroma API. + * + * @example + * ```typescript + * const version = await client.version(); + * ``` + */ + public async version(): Promise { + const response = await this.api.version(this.api.options); + return await handleSuccess(response); + } + + /** + * Returns a heartbeat from the Chroma API. + * @returns {Promise} A promise that resolves to the heartbeat from the Chroma API. + * + * @example + * ```typescript + * const heartbeat = await client.heartbeat(); + * ``` + */ + public async heartbeat(): Promise { + const response = await this.api.heartbeat(this.api.options); + let ret = await handleSuccess(response); + return ret["nanosecond heartbeat"] + } + + /** + * Creates a new collection with the specified properties. + * + * @param {Object} params - The parameters for creating a new collection. + * @param {string} params.name - The name of the collection. + * @param {CollectionMetadata} [params.metadata] - Optional metadata associated with the collection. + * @param {IEmbeddingFunction} [params.embeddingFunction] - Optional custom embedding function for the collection. + * + * @returns {Promise} A promise that resolves to the created collection. + * @throws {Error} If there is an issue creating the collection. + * + * @example + * ```typescript + * const collection = await client.createCollection({ + * name: "my_collection", + * metadata: { + * "description": "My first collection" + * } + * }); + * ``` + */ + public async createCollection({ + name, + metadata, + embeddingFunction + }: CreateCollectionParams): Promise { + + if (embeddingFunction === undefined) { + embeddingFunction = new DefaultEmbeddingFunction(); + } + + const newCollection = await this.api + .createCollection(this.tenant, this.database, { + name, + metadata, + }, this.api.options) + .then(handleSuccess) + .catch(handleError); + + if (newCollection.error) { + throw new Error(newCollection.error); + } + + return new Collection(name, newCollection.id, this.api, metadata, embeddingFunction); + } + + /** + * Gets or creates a collection with the specified properties. + * + * @param {Object} params - The parameters for creating a new collection. + * @param {string} params.name - The name of the collection. + * @param {CollectionMetadata} [params.metadata] - Optional metadata associated with the collection. + * @param {IEmbeddingFunction} [params.embeddingFunction] - Optional custom embedding function for the collection. + * + * @returns {Promise} A promise that resolves to the got or created collection. + * @throws {Error} If there is an issue getting or creating the collection. + * + * @example + * ```typescript + * const collection = await client.getOrCreateCollection({ + * name: "my_collection", + * metadata: { + * "description": "My first collection" + * } + * }); + * ``` + */ + public async getOrCreateCollection({ + name, + metadata, + embeddingFunction + }: GetOrCreateCollectionParams): Promise { + + if (embeddingFunction === undefined) { + embeddingFunction = new DefaultEmbeddingFunction(); + } + + const newCollection = await this.api + .createCollection(this.tenant, this.database, { + name, + metadata, + 'get_or_create': true + }, this.api.options) + .then(handleSuccess) + .catch(handleError); + + if (newCollection.error) { + throw new Error(newCollection.error); + } + + return new Collection( + name, + newCollection.id, + this.api, + newCollection.metadata, + embeddingFunction + ); + } + + /** + * Lists all collections. + * + * @returns {Promise} A promise that resolves to a list of collection names. + * @param {PositiveInteger} [params.limit] - Optional limit on the number of items to get. + * @param {PositiveInteger} [params.offset] - Optional offset on the items to get. + * @throws {Error} If there is an issue listing the collections. + * + * @example + * ```typescript + * const collections = await client.listCollections({ + * limit: 10, + * offset: 0, + * }); + * ``` + */ + public async listCollections({ + limit, + offset, + }: ListCollectionsParams = {}): Promise { + const response = await this.api.listCollections( + this.tenant, + this.database, + limit, + offset, + this.api.options); + return handleSuccess(response); + } + + /** + * Counts all collections. + * + * @returns {Promise} A promise that resolves to the number of collections. + * @throws {Error} If there is an issue counting the collections. + * + * @example + * ```typescript + * const collections = await client.countCollections(); + * ``` + */ + public async countCollections(): Promise { + const response = await this.api.countCollections(this.tenant, this.database, this.api.options); + return handleSuccess(response); + } + + /** + * Gets a collection with the specified name. + * @param {Object} params - The parameters for getting a collection. + * @param {string} params.name - The name of the collection. + * @param {IEmbeddingFunction} [params.embeddingFunction] - Optional custom embedding function for the collection. + * @returns {Promise} A promise that resolves to the collection. + * @throws {Error} If there is an issue getting the collection. + * + * @example + * ```typescript + * const collection = await client.getCollection({ + * name: "my_collection" + * }); + * ``` + */ + public async getCollection({ + name, + embeddingFunction + }: GetCollectionParams): Promise { + const response = await this.api + .getCollection(name, this.tenant, this.database, this.api.options) + .then(handleSuccess) + .catch(handleError); + + if (response.error) { + throw new Error(response.error); + } + + return new Collection( + response.name, + response.id, + this.api, + response.metadata, + embeddingFunction + ); + + } + + /** + * Deletes a collection with the specified name. + * @param {Object} params - The parameters for deleting a collection. + * @param {string} params.name - The name of the collection. + * @returns {Promise} A promise that resolves when the collection is deleted. + * @throws {Error} If there is an issue deleting the collection. + * + * @example + * ```typescript + * await client.deleteCollection({ + * name: "my_collection" + * }); + * ``` + */ + public async deleteCollection({ + name + }: DeleteCollectionParams): Promise { + return await this.api + .deleteCollection(name, this.tenant, this.database, this.api.options) + .then(handleSuccess) + .catch(handleError); + } + +} diff --git a/clients/js/src/CloudClient.ts b/clients/js/src/CloudClient.ts new file mode 100644 index 0000000000000000000000000000000000000000..9ce77d2f59dfe7d53fb13a04f4f652b48db98d9e --- /dev/null +++ b/clients/js/src/CloudClient.ts @@ -0,0 +1,46 @@ + +// create a cloudclient class that takes in an api key and an optional database +// this should wrap ChromaClient and specify the auth scheme correctly + +import { ChromaClient } from "./ChromaClient"; + +interface CloudClientParams { + apiKey?: string; + database?: string; + cloudHost?: string; + cloudPort?: string; +} + +class CloudClient extends ChromaClient{ + + constructor({apiKey, database, cloudHost, cloudPort}: CloudClientParams) { + // If no API key is provided, try to load it from the environment variable + if (!apiKey) { + apiKey = process.env.CHROMA_API_KEY; + } + if (!apiKey) { + throw new Error("No API key provided"); + } + + cloudHost = cloudHost || "https://api.trychroma.com"; + cloudPort = cloudPort || "8000"; + + const path = `${cloudHost}:${cloudPort}`; + + const auth = { + provider: "token", + credentials: apiKey, + providerOptions: { headerType: "X_CHROMA_TOKEN" }, + } + + return new ChromaClient({ + path: path, + auth: auth, + database: database, + }) + + super() + } +} + +export { CloudClient }; diff --git a/clients/js/src/Collection.ts b/clients/js/src/Collection.ts new file mode 100644 index 0000000000000000000000000000000000000000..82fe3facbd94237d16764480f0e7b7343ce16a97 --- /dev/null +++ b/clients/js/src/Collection.ts @@ -0,0 +1,540 @@ +import { + GetResponse, + QueryResponse, + AddResponse, + CollectionMetadata, + ConfigOptions, + GetParams, + AddParams, + UpsertParams, + ModifyCollectionParams, + UpdateParams, + QueryParams, + PeekParams, + DeleteParams +} from "./types"; +import { IEmbeddingFunction } from './embeddings/IEmbeddingFunction'; +import { ApiApi as DefaultApi } from "./generated"; +import { handleError, handleSuccess } from "./utils"; +import { toArray, toArrayOfArrays } from "./utils"; + + +export class Collection { + public name: string; + public id: string; + public metadata: CollectionMetadata | undefined; + /** + * @ignore + */ + private api: DefaultApi & ConfigOptions; + /** + * @ignore + */ + public embeddingFunction: IEmbeddingFunction | undefined; + + /** + * @ignore + */ + constructor( + name: string, + id: string, + api: DefaultApi, + metadata?: CollectionMetadata, + embeddingFunction?: IEmbeddingFunction + ) { + this.name = name; + this.id = id; + this.metadata = metadata; + this.api = api; + if (embeddingFunction !== undefined) + this.embeddingFunction = embeddingFunction; + } + + /** + * @ignore + */ + private setName(name: string): void { + this.name = name; + } + /** + * @ignore + */ + private setMetadata(metadata: CollectionMetadata | undefined): void { + this.metadata = metadata; + } + + /** + * @ignore + */ + private async validate( + require_embeddings_or_documents: boolean, // set to false in the case of Update + ids: string | string[], + embeddings: number[] | number[][] | undefined, + metadatas?: object | object[], + documents?: string | string[], + ) { + + if (require_embeddings_or_documents) { + if ((embeddings === undefined) && (documents === undefined)) { + throw new Error( + "embeddings and documents cannot both be undefined", + ); + } + } + + if ((embeddings === undefined) && (documents !== undefined)) { + const documentsArray = toArray(documents); + if (this.embeddingFunction !== undefined) { + embeddings = await this.embeddingFunction.generate(documentsArray); + } else { + throw new Error( + "embeddingFunction is undefined. Please configure an embedding function" + ); + } + } + if (embeddings === undefined) + throw new Error("embeddings is undefined but shouldnt be"); + + const idsArray = toArray(ids); + const embeddingsArray: number[][] = toArrayOfArrays(embeddings); + + let metadatasArray: object[] | undefined; + if (metadatas === undefined) { + metadatasArray = undefined; + } else { + metadatasArray = toArray(metadatas); + } + + let documentsArray: (string | undefined)[] | undefined; + if (documents === undefined) { + documentsArray = undefined; + } else { + documentsArray = toArray(documents); + } + + // validate all ids are strings + for (let i = 0; i < idsArray.length; i += 1) { + if (typeof idsArray[i] !== "string") { + throw new Error( + `Expected ids to be strings, found ${typeof idsArray[i]} at index ${i}` + ); + } + } + + if ( + (embeddingsArray !== undefined && + idsArray.length !== embeddingsArray.length) || + (metadatasArray !== undefined && + idsArray.length !== metadatasArray.length) || + (documentsArray !== undefined && + idsArray.length !== documentsArray.length) + ) { + throw new Error( + "ids, embeddings, metadatas, and documents must all be the same length" + ); + } + + const uniqueIds = new Set(idsArray); + if (uniqueIds.size !== idsArray.length) { + const duplicateIds = idsArray.filter((item, index) => idsArray.indexOf(item) !== index); + throw new Error( + `Expected IDs to be unique, found duplicates for: ${duplicateIds}`, + ); + } + + return [idsArray, embeddingsArray, metadatasArray, documentsArray] + } + + /** + * Add items to the collection + * @param {Object} params - The parameters for the query. + * @param {ID | IDs} [params.ids] - IDs of the items to add. + * @param {Embedding | Embeddings} [params.embeddings] - Optional embeddings of the items to add. + * @param {Metadata | Metadatas} [params.metadatas] - Optional metadata of the items to add. + * @param {Document | Documents} [params.documents] - Optional documents of the items to add. + * @returns {Promise} - The response from the API. True if successful. + * + * @example + * ```typescript + * const response = await collection.add({ + * ids: ["id1", "id2"], + * embeddings: [[1, 2, 3], [4, 5, 6]], + * metadatas: [{ "key": "value" }, { "key": "value" }], + * documents: ["document1", "document2"] + * }); + * ``` + */ + public async add({ + ids, + embeddings, + metadatas, + documents, + }: AddParams): Promise { + + const [idsArray, embeddingsArray, metadatasArray, documentsArray] = await this.validate( + true, + ids, + embeddings, + metadatas, + documents + ) + + const response = await this.api.add(this.id, + { + // @ts-ignore + ids: idsArray, + embeddings: embeddingsArray as number[][], // We know this is defined because of the validate function + // @ts-ignore + documents: documentsArray, + // @ts-ignore + metadatas: metadatasArray, + }, this.api.options) + .then(handleSuccess) + .catch(handleError); + + return response + } + + /** + * Upsert items to the collection + * @param {Object} params - The parameters for the query. + * @param {ID | IDs} [params.ids] - IDs of the items to add. + * @param {Embedding | Embeddings} [params.embeddings] - Optional embeddings of the items to add. + * @param {Metadata | Metadatas} [params.metadatas] - Optional metadata of the items to add. + * @param {Document | Documents} [params.documents] - Optional documents of the items to add. + * @returns {Promise} - The response from the API. True if successful. + * + * @example + * ```typescript + * const response = await collection.upsert({ + * ids: ["id1", "id2"], + * embeddings: [[1, 2, 3], [4, 5, 6]], + * metadatas: [{ "key": "value" }, { "key": "value" }], + * documents: ["document1", "document2"], + * }); + * ``` + */ + public async upsert({ + ids, + embeddings, + metadatas, + documents, + }: UpsertParams): Promise { + const [idsArray, embeddingsArray, metadatasArray, documentsArray] = await this.validate( + true, + ids, + embeddings, + metadatas, + documents + ) + + const response = await this.api.upsert(this.id, + { + //@ts-ignore + ids: idsArray, + embeddings: embeddingsArray as number[][], // We know this is defined because of the validate function + //@ts-ignore + documents: documentsArray, + //@ts-ignore + metadatas: metadatasArray, + }, + this.api.options + ) + .then(handleSuccess) + .catch(handleError); + + return response + + } + + /** + * Count the number of items in the collection + * @returns {Promise} - The response from the API. + * + * @example + * ```typescript + * const response = await collection.count(); + * ``` + */ + public async count(): Promise { + const response = await this.api.count(this.id, this.api.options); + return handleSuccess(response); + } + + /** + * Modify the collection name or metadata + * @param {Object} params - The parameters for the query. + * @param {string} [params.name] - Optional new name for the collection. + * @param {CollectionMetadata} [params.metadata] - Optional new metadata for the collection. + * @returns {Promise} - The response from the API. + * + * @example + * ```typescript + * const response = await collection.modify({ + * name: "new name", + * metadata: { "key": "value" }, + * }); + * ``` + */ + public async modify({ + name, + metadata + }: ModifyCollectionParams = {}): Promise { + const response = await this.api + .updateCollection( + this.id, + { + new_name: name, + new_metadata: metadata, + }, + this.api.options + ) + .then(handleSuccess) + .catch(handleError); + + this.setName(name || this.name); + this.setMetadata(metadata || this.metadata); + + return response; + } + + /** + * Get items from the collection + * @param {Object} params - The parameters for the query. + * @param {ID | IDs} [params.ids] - Optional IDs of the items to get. + * @param {Where} [params.where] - Optional where clause to filter items by. + * @param {PositiveInteger} [params.limit] - Optional limit on the number of items to get. + * @param {PositiveInteger} [params.offset] - Optional offset on the items to get. + * @param {IncludeEnum[]} [params.include] - Optional list of items to include in the response. + * @param {WhereDocument} [params.whereDocument] - Optional where clause to filter items by. + * @returns {Promise} - The response from the server. + * + * @example + * ```typescript + * const response = await collection.get({ + * ids: ["id1", "id2"], + * where: { "key": "value" }, + * limit: 10, + * offset: 0, + * include: ["embeddings", "metadatas", "documents"], + * whereDocument: { $contains: "value" }, + * }); + * ``` + */ + public async get({ + ids, + where, + limit, + offset, + include, + whereDocument, + }: GetParams = {}): Promise { + let idsArray = undefined; + if (ids !== undefined) idsArray = toArray(ids); + + return await this.api + .aGet(this.id, { + ids: idsArray, + where, + limit, + offset, + //@ts-ignore + include, + where_document: whereDocument, + }, this.api.options) + .then(handleSuccess) + .catch(handleError); + } + + /** + * Update the embeddings, documents, and/or metadatas of existing items + * @param {Object} params - The parameters for the query. + * @param {ID | IDs} [params.ids] - The IDs of the items to update. + * @param {Embedding | Embeddings} [params.embeddings] - Optional embeddings to update. + * @param {Metadata | Metadatas} [params.metadatas] - Optional metadatas to update. + * @param {Document | Documents} [params.documents] - Optional documents to update. + * @returns {Promise} - The API Response. True if successful. Else, error. + * + * @example + * ```typescript + * const response = await collection.update({ + * ids: ["id1", "id2"], + * embeddings: [[1, 2, 3], [4, 5, 6]], + * metadatas: [{ "key": "value" }, { "key": "value" }], + * documents: ["new document 1", "new document 2"], + * }); + * ``` + */ + public async update({ + ids, + embeddings, + metadatas, + documents, + }: UpdateParams): Promise { + if ( + embeddings === undefined && + documents === undefined && + metadatas === undefined + ) { + throw new Error( + "embeddings, documents, and metadatas cannot all be undefined" + ); + } else if (embeddings === undefined && documents !== undefined) { + const documentsArray = toArray(documents); + if (this.embeddingFunction !== undefined) { + embeddings = await this.embeddingFunction.generate(documentsArray); + } else { + throw new Error( + "embeddingFunction is undefined. Please configure an embedding function" + ); + } + } + + // backend expects None if metadatas is undefined + if (metadatas !== undefined) metadatas = toArray(metadatas); + if (documents !== undefined) documents = toArray(documents); + + var resp = await this.api + .update( + this.id, + { + ids: toArray(ids), + embeddings: embeddings ? toArrayOfArrays(embeddings) : undefined, + documents: documents, + metadatas: metadatas + }, + this.api.options + ) + .then(handleSuccess) + .catch(handleError); + + return resp; + } + + /** + * Performs a query on the collection using the specified parameters. + * + * @param {Object} params - The parameters for the query. + * @param {Embedding | Embeddings} [params.queryEmbeddings] - Optional query embeddings to use for the search. + * @param {PositiveInteger} [params.nResults] - Optional number of results to return (default is 10). + * @param {Where} [params.where] - Optional query condition to filter results based on metadata values. + * @param {string | string[]} [params.queryTexts] - Optional query text(s) to search for in the collection. + * @param {WhereDocument} [params.whereDocument] - Optional query condition to filter results based on document content. + * @param {IncludeEnum[]} [params.include] - Optional array of fields to include in the result, such as "metadata" and "document". + * + * @returns {Promise} A promise that resolves to the query results. + * @throws {Error} If there is an issue executing the query. + * @example + * // Query the collection using embeddings + * const results = await collection.query({ + * queryEmbeddings: [[0.1, 0.2, ...], ...], + * nResults: 10, + * where: {"name": {"$eq": "John Doe"}}, + * include: ["metadata", "document"] + * }); + * @example + * ```js + * // Query the collection using query text + * const results = await collection.query({ + * queryTexts: "some text", + * nResults: 10, + * where: {"name": {"$eq": "John Doe"}}, + * include: ["metadata", "document"] + * }); + * ``` + * + */ + public async query({ + queryEmbeddings, + nResults, + where, + queryTexts, + whereDocument, + include, + }: QueryParams): Promise { + if (nResults === undefined) nResults = 10 + if (queryEmbeddings === undefined && queryTexts === undefined) { + throw new Error( + "queryEmbeddings and queryTexts cannot both be undefined" + ); + } else if (queryEmbeddings === undefined && queryTexts !== undefined) { + const queryTextsArray = toArray(queryTexts); + if (this.embeddingFunction !== undefined) { + queryEmbeddings = await this.embeddingFunction.generate(queryTextsArray); + } else { + throw new Error( + "embeddingFunction is undefined. Please configure an embedding function" + ); + } + } + if (queryEmbeddings === undefined) + throw new Error("embeddings is undefined but shouldnt be"); + + const query_embeddingsArray = toArrayOfArrays(queryEmbeddings); + + return await this.api + .getNearestNeighbors(this.id, { + query_embeddings: query_embeddingsArray, + where, + n_results: nResults, + where_document: whereDocument, + //@ts-ignore + include: include, + }, this.api.options) + .then(handleSuccess) + .catch(handleError); + } + + /** + * Peek inside the collection + * @param {Object} params - The parameters for the query. + * @param {PositiveInteger} [params.limit] - Optional number of results to return (default is 10). + * @returns {Promise} A promise that resolves to the query results. + * @throws {Error} If there is an issue executing the query. + * + * @example + * ```typescript + * const results = await collection.peek({ + * limit: 10 + * }); + * ``` + */ + public async peek({ limit }: PeekParams = {}): Promise { + if (limit === undefined) limit = 10; + const response = await this.api.aGet(this.id, { + limit: limit, + }, this.api.options); + return handleSuccess(response); + } + + /** + * Deletes items from the collection. + * @param {Object} params - The parameters for deleting items from the collection. + * @param {ID | IDs} [params.ids] - Optional ID or array of IDs of items to delete. + * @param {Where} [params.where] - Optional query condition to filter items to delete based on metadata values. + * @param {WhereDocument} [params.whereDocument] - Optional query condition to filter items to delete based on document content. + * @returns {Promise} A promise that resolves to the IDs of the deleted items. + * @throws {Error} If there is an issue deleting items from the collection. + * + * @example + * ```typescript + * const results = await collection.delete({ + * ids: "some_id", + * where: {"name": {"$eq": "John Doe"}}, + * whereDocument: {"$contains":"search_string"} + * }); + * ``` + */ + public async delete({ + ids, + where, + whereDocument + }: DeleteParams = {}): Promise { + let idsArray = undefined; + if (ids !== undefined) idsArray = toArray(ids); + return await this.api + .aDelete(this.id, { ids: idsArray, where: where, where_document: whereDocument }, this.api.options) + .then(handleSuccess) + .catch(handleError); + } +} diff --git a/clients/js/src/auth.ts b/clients/js/src/auth.ts new file mode 100644 index 0000000000000000000000000000000000000000..4f833f97d61724eb5f45283fdc8246d5446065f1 --- /dev/null +++ b/clients/js/src/auth.ts @@ -0,0 +1,321 @@ +import {ApiApi as DefaultApi} from "./generated"; + +export interface ClientAuthProvider { + /** + * Abstract method for authenticating a client. + */ + authenticate(): ClientAuthResponse; +} + +export interface ClientAuthConfigurationProvider { + /** + * Abstract method for getting the configuration for the client. + */ + getConfig(): T; +} + +export interface ClientAuthCredentialsProvider { + /** + * Abstract method for getting the credentials for the client. + * @param user + */ + getCredentials(user?: string): T; +} + +enum AuthInfoType { + COOKIE = "cookie", + HEADER = "header", + URL = "url", + METADATA = "metadata" + +} + +export interface ClientAuthResponse { + getAuthInfoType(): AuthInfoType; + + getAuthInfo(): { key: string, value: string }; +} + + +export interface AbstractCredentials { + getCredentials(): T; +} + +export interface ClientAuthProtocolAdapter { + injectCredentials(injectionContext: T): T; + + getApi(): any; +} + + +class SecretStr { + constructor(private readonly secret: string) { + } + + getSecret(): string { + return this.secret; + } +} + +const base64Encode = (str: string): string => { + return Buffer.from(str).toString('base64'); +}; + +class BasicAuthCredentials implements AbstractCredentials { + private readonly credentials: SecretStr; + + constructor(_creds: string) { + this.credentials = new SecretStr(base64Encode(_creds)) + } + + getCredentials(): SecretStr { + //encode base64 + return this.credentials; + } +} + + +class BasicAuthClientAuthResponse implements ClientAuthResponse { + constructor(private readonly credentials: BasicAuthCredentials) { + } + + getAuthInfo(): { key: string; value: string } { + return {key: "Authorization", value: "Basic " + this.credentials.getCredentials().getSecret()}; + } + + getAuthInfoType(): AuthInfoType { + return AuthInfoType.HEADER; + } +} + +export class BasicAuthCredentialsProvider implements ClientAuthCredentialsProvider { + private readonly credentials: BasicAuthCredentials; + + /** + * Creates a new BasicAuthCredentialsProvider. This provider loads credentials from provided text credentials or from the environment variable CHROMA_CLIENT_AUTH_CREDENTIALS. + * @param _creds - The credentials + * @throws {Error} If neither credentials provider or text credentials are supplied. + */ + + constructor(_creds: string | undefined) { + if (_creds === undefined && !process.env.CHROMA_CLIENT_AUTH_CREDENTIALS) throw new Error("Credentials must be supplied via environment variable (CHROMA_CLIENT_AUTH_CREDENTIALS) or passed in as configuration."); + this.credentials = new BasicAuthCredentials((_creds ?? process.env.CHROMA_CLIENT_AUTH_CREDENTIALS) as string); + } + + getCredentials(): BasicAuthCredentials { + return this.credentials; + } +} + +class BasicAuthClientAuthProvider implements ClientAuthProvider { + private readonly credentialsProvider: ClientAuthCredentialsProvider; + + /** + * Creates a new BasicAuthClientAuthProvider. + * @param options - The options for the authentication provider. + * @param options.textCredentials - The credentials for the authentication provider. + * @param options.credentialsProvider - The credentials provider for the authentication provider. + * @throws {Error} If neither credentials provider or text credentials are supplied. + */ + + constructor(options: { + textCredentials: any; + credentialsProvider: ClientAuthCredentialsProvider | undefined + }) { + if (!options.credentialsProvider && !options.textCredentials) { + throw new Error("Either credentials provider or text credentials must be supplied."); + } + this.credentialsProvider = options.credentialsProvider || new BasicAuthCredentialsProvider(options.textCredentials); + } + + authenticate(): ClientAuthResponse { + return new BasicAuthClientAuthResponse(this.credentialsProvider.getCredentials()); + } +} + +class TokenAuthCredentials implements AbstractCredentials { + private readonly credentials: SecretStr; + + constructor(_creds: string) { + this.credentials = new SecretStr(_creds) + } + + getCredentials(): SecretStr { + return this.credentials; + } +} + +export class TokenCredentialsProvider implements ClientAuthCredentialsProvider { + private readonly credentials: TokenAuthCredentials; + + constructor(_creds: string | undefined) { + if (_creds === undefined && !process.env.CHROMA_CLIENT_AUTH_CREDENTIALS) throw new Error("Credentials must be supplied via environment variable (CHROMA_CLIENT_AUTH_CREDENTIALS) or passed in as configuration."); + this.credentials = new TokenAuthCredentials((_creds ?? process.env.CHROMA_CLIENT_AUTH_CREDENTIALS) as string); + } + + getCredentials(): TokenAuthCredentials { + return this.credentials; + } +} + +export class TokenClientAuthProvider implements ClientAuthProvider { + private readonly credentialsProvider: ClientAuthCredentialsProvider; + private readonly providerOptions: { headerType: TokenHeaderType }; + + constructor(options: { + textCredentials: any; + credentialsProvider: ClientAuthCredentialsProvider | undefined, + providerOptions?: { headerType: TokenHeaderType } + }) { + if (!options.credentialsProvider && !options.textCredentials) { + throw new Error("Either credentials provider or text credentials must be supplied."); + } + if (options.providerOptions === undefined || !options.providerOptions.hasOwnProperty("headerType")) { + this.providerOptions = {headerType: "AUTHORIZATION"}; + } else { + this.providerOptions = {headerType: options.providerOptions.headerType}; + } + this.credentialsProvider = options.credentialsProvider || new TokenCredentialsProvider(options.textCredentials); + } + + authenticate(): ClientAuthResponse { + return new TokenClientAuthResponse(this.credentialsProvider.getCredentials(), this.providerOptions.headerType); + } + +} + + +type TokenHeaderType = 'AUTHORIZATION' | 'X_CHROMA_TOKEN'; + +const TokenHeader: Record { key: string; value: string; }> = { + AUTHORIZATION: (value: string) => ({key: "Authorization", value: `Bearer ${value}`}), + X_CHROMA_TOKEN: (value: string) => ({key: "X-Chroma-Token", value: value}) +} + +class TokenClientAuthResponse implements ClientAuthResponse { + constructor(private readonly credentials: TokenAuthCredentials, private readonly headerType: TokenHeaderType = 'AUTHORIZATION') { + } + + getAuthInfo(): { key: string; value: string } { + if (this.headerType === 'AUTHORIZATION') { + return TokenHeader.AUTHORIZATION(this.credentials.getCredentials().getSecret()); + } else if (this.headerType === 'X_CHROMA_TOKEN') { + return TokenHeader.X_CHROMA_TOKEN(this.credentials.getCredentials().getSecret()); + } else { + throw new Error("Invalid header type: " + this.headerType + ". Valid types are: " + Object.keys(TokenHeader).join(", ")); + } + } + + getAuthInfoType(): AuthInfoType { + return AuthInfoType.HEADER; + } +} + + +export class IsomorphicFetchClientAuthProtocolAdapter implements ClientAuthProtocolAdapter { + authProvider: ClientAuthProvider | undefined; + wrapperApi: DefaultApi | undefined; + + /** + * Creates a new adapter of IsomorphicFetchClientAuthProtocolAdapter. + * @param api - The API to wrap. + * @param authConfiguration - The configuration for the authentication provider. + */ + + constructor(private api: DefaultApi, authConfiguration: AuthOptions) { + + switch (authConfiguration.provider) { + case "basic": + this.authProvider = new BasicAuthClientAuthProvider({ + textCredentials: authConfiguration.credentials, + credentialsProvider: authConfiguration.credentialsProvider + }); + break; + case "token": + this.authProvider = new TokenClientAuthProvider({ + textCredentials: authConfiguration.credentials, + credentialsProvider: authConfiguration.credentialsProvider, + providerOptions: authConfiguration.providerOptions + }); + break; + default: + this.authProvider = undefined; + break; + } + if (this.authProvider !== undefined) { + this.wrapperApi = this.wrapMethods(this.api); + } + } + + getApi(): DefaultApi { + return this.wrapperApi ?? this.api; + } + + getAllMethods(obj: any): string[] { + let methods: string[] = []; + let currentObj = obj; + + do { + const objMethods = Object.getOwnPropertyNames(currentObj) + .filter(name => typeof currentObj[name] === 'function' && name !== 'constructor'); + + methods = methods.concat(objMethods); + currentObj = Object.getPrototypeOf(currentObj); + } while (currentObj); + + return methods; + } + + wrapMethods(obj: any): any { + let self = this; + const methodNames = Object.getOwnPropertyNames(Object.getPrototypeOf(obj)) + .filter(name => typeof obj[name] === 'function' && name !== 'constructor'); + + return new Proxy(obj, { + get(target, prop: string) { + if (methodNames.includes(prop)) { + return new Proxy(target[prop], { + apply(fn, thisArg, args) { + const modifiedArgs = args.map(arg => { + if (arg && typeof arg === 'object' && 'method' in arg) { + return self.injectCredentials(arg as RequestInit); + } + return arg; + }); + if (Object.keys(modifiedArgs[modifiedArgs.length - 1]).length === 0) { + modifiedArgs[modifiedArgs.length - 1] = self.injectCredentials({} as RequestInit); + } else { + modifiedArgs[modifiedArgs.length - 1] = self.injectCredentials(modifiedArgs[modifiedArgs.length - 1] as RequestInit); + } + return fn.apply(thisArg, modifiedArgs); + } + }); + } + return target[prop]; + } + }); + } + + injectCredentials(injectionContext: RequestInit): RequestInit { + const authInfo = this.authProvider?.authenticate().getAuthInfo(); + if (authInfo) { + const {key, value} = authInfo; + injectionContext = { + ...injectionContext, + headers: { + [key]: value + }, + } + } + return injectionContext; + } +} + + +export type AuthOptions = { + provider: ClientAuthProvider | string | undefined, + credentialsProvider?: ClientAuthCredentialsProvider | undefined, + configProvider?: ClientAuthConfigurationProvider | undefined, + credentials?: any | undefined, + providerOptions?: any | undefined +} diff --git a/clients/js/src/embeddings/CohereEmbeddingFunction.ts b/clients/js/src/embeddings/CohereEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..2efe45a77c51f83c63e5a309e17a912f216184f9 --- /dev/null +++ b/clients/js/src/embeddings/CohereEmbeddingFunction.ts @@ -0,0 +1,122 @@ +import { IEmbeddingFunction } from "./IEmbeddingFunction"; + +interface CohereAIAPI { + createEmbedding: (params: { + model: string; + input: string[]; + }) => Promise; +} + +class CohereAISDK56 implements CohereAIAPI { + private cohereClient: any; + private apiKey: string; + + constructor(configuration: { apiKey: string }) { + this.apiKey = configuration.apiKey; + } + + private async loadClient() { + if (this.cohereClient) return; + //@ts-ignore + const { default: cohere } = await import("cohere-ai"); + // @ts-ignore + cohere.init(this.apiKey); + this.cohereClient = cohere; + } + + public async createEmbedding(params: { + model: string; + input: string[]; + }): Promise { + await this.loadClient(); + return await this.cohereClient + .embed({ + texts: params.input, + model: params.model, + }) + .then((response: any) => { + return response.body.embeddings; + }); + } +} + +class CohereAISDK7 implements CohereAIAPI { + private cohereClient: any; + private apiKey: string; + + constructor(configuration: { apiKey: string }) { + this.apiKey = configuration.apiKey; + } + + private async loadClient() { + if (this.cohereClient) return; + //@ts-ignore + const cohere = await import("cohere-ai").then((cohere) => { + return cohere; + }); + // @ts-ignore + this.cohereClient = new cohere.CohereClient({ + token: this.apiKey, + }); + } + + public async createEmbedding(params: { + model: string; + input: string[]; + }): Promise { + await this.loadClient(); + return await this.cohereClient + .embed({ texts: params.input, model: params.model }) + .then((response: any) => { + return response.embeddings; + }); + } +} + +export class CohereEmbeddingFunction implements IEmbeddingFunction { + private cohereAiApi?: CohereAIAPI; + private model: string; + private apiKey: string; + constructor({ + cohere_api_key, + model, + }: { + cohere_api_key: string; + model?: string; + }) { + this.model = model || "large"; + this.apiKey = cohere_api_key; + } + + private async initCohereClient() { + if (this.cohereAiApi) return; + try { + // @ts-ignore + this.cohereAiApi = await import("cohere-ai").then((cohere) => { + // @ts-ignore + if (cohere.CohereClient) { + return new CohereAISDK7({ apiKey: this.apiKey }); + } else { + return new CohereAISDK56({ apiKey: this.apiKey }); + } + }); + } catch (e) { + // @ts-ignore + if (e.code === "MODULE_NOT_FOUND") { + throw new Error( + "Please install the cohere-ai package to use the CohereEmbeddingFunction, `npm install -S cohere-ai`" + ); + } + throw e; + } + } + + public async generate(texts: string[]): Promise { + await this.initCohereClient(); + // @ts-ignore + return await this.cohereAiApi.createEmbedding({ + model: this.model, + input: texts, + }); + } +} diff --git a/clients/js/src/embeddings/DefaultEmbeddingFunction.ts b/clients/js/src/embeddings/DefaultEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..6ced79bbd48dcae5c19dad1de42933a9a5ed93db --- /dev/null +++ b/clients/js/src/embeddings/DefaultEmbeddingFunction.ts @@ -0,0 +1,99 @@ +import { IEmbeddingFunction } from "./IEmbeddingFunction"; + +// Dynamically import module +let TransformersApi: Promise; + +export class DefaultEmbeddingFunction implements IEmbeddingFunction { + private pipelinePromise?: Promise | null; + private transformersApi: any; + private model: string; + private revision: string; + private quantized: boolean; + private progress_callback: Function | null; + + /** + * DefaultEmbeddingFunction constructor. + * @param options The configuration options. + * @param options.model The model to use to calculate embeddings. Defaults to 'Xenova/all-MiniLM-L6-v2', which is an ONNX port of `sentence-transformers/all-MiniLM-L6-v2`. + * @param options.revision The specific model version to use (can be a branch, tag name, or commit id). Defaults to 'main'. + * @param options.quantized Whether to load the 8-bit quantized version of the model. Defaults to `false`. + * @param options.progress_callback If specified, this function will be called during model construction, to provide the user with progress updates. + */ + constructor({ + model = "Xenova/all-MiniLM-L6-v2", + revision = "main", + quantized = false, + progress_callback = null, + }: { + model?: string; + revision?: string; + quantized?: boolean; + progress_callback?: Function | null; + } = {}) { + this.model = model; + this.revision = revision; + this.quantized = quantized; + this.progress_callback = progress_callback; + } + + public async generate(texts: string[]): Promise { + await this.loadClient(); + + // Store a promise that resolves to the pipeline + this.pipelinePromise = new Promise(async (resolve, reject) => { + try { + const pipeline = this.transformersApi + + const quantized = this.quantized + const revision = this.revision + const progress_callback = this.progress_callback + + resolve( + await pipeline("feature-extraction", this.model, { + quantized, + revision, + progress_callback, + }) + ); + } catch (e) { + reject(e); + } + }); + + let pipe = await this.pipelinePromise; + let output = await pipe(texts, { pooling: "mean", normalize: true }); + return output.tolist(); + } + + private async loadClient() { + if(this.transformersApi) return; + try { + // eslint-disable-next-line global-require,import/no-extraneous-dependencies + let { pipeline } = await DefaultEmbeddingFunction.import(); + TransformersApi = pipeline; + } catch (_a) { + // @ts-ignore + if (_a.code === 'MODULE_NOT_FOUND') { + throw new Error("Please install the chromadb-default-embed package to use the DefaultEmbeddingFunction, `npm install -S chromadb-default-embed`"); + } + throw _a; // Re-throw other errors + } + this.transformersApi = TransformersApi; + } + + /** @ignore */ + static async import(): Promise<{ + // @ts-ignore + pipeline: typeof import("chromadb-default-embed"); + }> { + try { + // @ts-ignore + const { pipeline } = await import("chromadb-default-embed"); + return { pipeline }; + } catch (e) { + throw new Error( + "Please install chromadb-default-embed as a dependency with, e.g. `yarn add chromadb-default-embed`" + ); + } + } +} diff --git a/clients/js/src/embeddings/GoogleGeminiEmbeddingFunction.ts b/clients/js/src/embeddings/GoogleGeminiEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..a1ab2abe995c8f2ff592be9b23ac7e46ddef1019 --- /dev/null +++ b/clients/js/src/embeddings/GoogleGeminiEmbeddingFunction.ts @@ -0,0 +1,69 @@ +import { IEmbeddingFunction } from "./IEmbeddingFunction"; + +let googleGenAiApi: any; + +export class GoogleGenerativeAiEmbeddingFunction implements IEmbeddingFunction { + private api_key: string; + private model: string; + private googleGenAiApi?: any; + private taskType: string; + + constructor({ googleApiKey, model, taskType }: { googleApiKey: string, model?: string, taskType?: string }) { + // we used to construct the client here, but we need to async import the types + // for the openai npm package, and the constructor can not be async + this.api_key = googleApiKey; + this.model = model || "embedding-001"; + this.taskType = taskType || "RETRIEVAL_DOCUMENT"; + } + + private async loadClient() { + if(this.googleGenAiApi) return; + try { + // eslint-disable-next-line global-require,import/no-extraneous-dependencies + const { googleGenAi } = await GoogleGenerativeAiEmbeddingFunction.import(); + googleGenAiApi = googleGenAi; + // googleGenAiApi.init(this.api_key); + googleGenAiApi = new googleGenAiApi(this.api_key); + } catch (_a) { + // @ts-ignore + if (_a.code === 'MODULE_NOT_FOUND') { + throw new Error("Please install the @google/generative-ai package to use the GoogleGenerativeAiEmbeddingFunction, `npm install -S @google/generative-ai`"); + } + throw _a; // Re-throw other errors + } + this.googleGenAiApi = googleGenAiApi; + } + + public async generate(texts: string[]) { + + await this.loadClient(); + const model = this.googleGenAiApi.getGenerativeModel({ model: this.model}); + const response = await model.batchEmbedContents({ + requests: texts.map((t) => ({ + content: { parts: [{ text: t }] }, + taskType: this.taskType, + })), + }); + const embeddings = response.embeddings.map((e: any) => e.values); + + return embeddings; + } + + /** @ignore */ + static async import(): Promise<{ + // @ts-ignore + googleGenAi: typeof import("@google/generative-ai"); + }> { + try { + // @ts-ignore + const { GoogleGenerativeAI } = await import("@google/generative-ai"); + const googleGenAi = GoogleGenerativeAI; + return { googleGenAi }; + } catch (e) { + throw new Error( + "Please install @google/generative-ai as a dependency with, e.g. `yarn add @google/generative-ai`" + ); + } + } + +} diff --git a/clients/js/src/embeddings/HuggingFaceEmbeddingServerFunction.ts b/clients/js/src/embeddings/HuggingFaceEmbeddingServerFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..dcbc62ecb70ceaffb9c0f1ec7d94e0e16869f15d --- /dev/null +++ b/clients/js/src/embeddings/HuggingFaceEmbeddingServerFunction.ts @@ -0,0 +1,31 @@ +import { IEmbeddingFunction } from "./IEmbeddingFunction"; + +let CohereAiApi: any; + +export class HuggingFaceEmbeddingServerFunction implements IEmbeddingFunction { + private url: string; + + constructor({ url }: { url: string }) { + // we used to construct the client here, but we need to async import the types + // for the openai npm package, and the constructor can not be async + this.url = url; + } + + public async generate(texts: string[]) { + const response = await fetch(this.url, { + method: 'POST', + headers: { + 'Content-Type': 'application/json' + }, + body: JSON.stringify({ 'inputs': texts }) + }); + + if (!response.ok) { + throw new Error(`Failed to generate embeddings: ${response.statusText}`); + } + + const data = await response.json(); + return data; + } + +} diff --git a/clients/js/src/embeddings/IEmbeddingFunction.ts b/clients/js/src/embeddings/IEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..dcc21ab19d9d472822aabbf076d89a4078044d9c --- /dev/null +++ b/clients/js/src/embeddings/IEmbeddingFunction.ts @@ -0,0 +1,3 @@ +export interface IEmbeddingFunction { + generate(texts: string[]): Promise; +} diff --git a/clients/js/src/embeddings/JinaEmbeddingFunction.ts b/clients/js/src/embeddings/JinaEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..a91f94749f8bceb62d31059f50269af18a7768fb --- /dev/null +++ b/clients/js/src/embeddings/JinaEmbeddingFunction.ts @@ -0,0 +1,46 @@ +import { IEmbeddingFunction } from "./IEmbeddingFunction"; + +export class JinaEmbeddingFunction implements IEmbeddingFunction { + private model_name: string; + private api_url: string; + private headers: { [key: string]: string }; + + constructor({ jinaai_api_key, model_name }: { jinaai_api_key: string; model_name?: string }) { + this.model_name = model_name || 'jina-embeddings-v2-base-en'; + this.api_url = 'https://api.jina.ai/v1/embeddings'; + this.headers = { + Authorization: `Bearer ${jinaai_api_key}`, + 'Accept-Encoding': 'identity', + 'Content-Type': 'application/json', + }; + } + + public async generate(texts: string[]) { + try { + const response = await fetch(this.api_url, { + method: 'POST', + headers: this.headers, + body: JSON.stringify({ + input: texts, + model: this.model_name, + }), + }); + + const data = (await response.json()) as { data: any[]; detail: string }; + if (!data || !data.data) { + throw new Error(data.detail); + } + + const embeddings: any[] = data.data; + const sortedEmbeddings = embeddings.sort((a, b) => a.index - b.index); + + return sortedEmbeddings.map((result) => result.embedding); + } catch (error) { + if (error instanceof Error) { + throw new Error(`Error calling Jina AI API: ${error.message}`); + } else { + throw new Error(`Error calling Jina AI API: ${error}`); + } + } + } +} diff --git a/clients/js/src/embeddings/OpenAIEmbeddingFunction.ts b/clients/js/src/embeddings/OpenAIEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..0b4be92eec11635522234dd2ffe8ea79e3fbebdd --- /dev/null +++ b/clients/js/src/embeddings/OpenAIEmbeddingFunction.ts @@ -0,0 +1,151 @@ +import {IEmbeddingFunction} from "./IEmbeddingFunction"; + +let OpenAIApi: any; +let openAiVersion = null; +let openAiMajorVersion = null; + +interface OpenAIAPI { + createEmbedding: (params: { + model: string; + input: string[]; + user?: string; + }) => Promise; +} + +class OpenAIAPIv3 implements OpenAIAPI { + private readonly configuration: any; + private openai: any; + + constructor(configuration: { organization: string, apiKey: string }) { + this.configuration = new OpenAIApi.Configuration({ + organization: configuration.organization, + apiKey: configuration.apiKey, + }); + this.openai = new OpenAIApi.OpenAIApi(this.configuration); + } + + public async createEmbedding(params: { + model: string, + input: string[], + user?: string + }): Promise { + const embeddings: number[][] = []; + const response = await this.openai.createEmbedding({ + model: params.model, + input: params.input, + }).catch((error: any) => { + throw error; + }); + // @ts-ignore + const data = response.data["data"]; + for (let i = 0; i < data.length; i += 1) { + embeddings.push(data[i]["embedding"]); + } + return embeddings + } +} + +class OpenAIAPIv4 implements OpenAIAPI { + private readonly apiKey: any; + private openai: any; + + constructor(apiKey: any) { + this.apiKey = apiKey; + this.openai = new OpenAIApi({ + apiKey: this.apiKey, + }); + } + + public async createEmbedding(params: { + model: string, + input: string[], + user?: string + }): Promise { + const embeddings: number[][] = []; + const response = await this.openai.embeddings.create(params); + const data = response["data"]; + for (let i = 0; i < data.length; i += 1) { + embeddings.push(data[i]["embedding"]); + } + return embeddings + } +} + +export class OpenAIEmbeddingFunction implements IEmbeddingFunction { + private api_key: string; + private org_id: string; + private model: string; + private openaiApi?: OpenAIAPI; + + constructor({openai_api_key, openai_model, openai_organization_id}: { + openai_api_key: string, + openai_model?: string, + openai_organization_id?: string + }) { + // we used to construct the client here, but we need to async import the types + // for the openai npm package, and the constructor can not be async + this.api_key = openai_api_key; + this.org_id = openai_organization_id || ""; + this.model = openai_model || "text-embedding-ada-002"; + } + + private async loadClient() { + // cache the client + if(this.openaiApi) return; + + try { + const { openai, version } = await OpenAIEmbeddingFunction.import(); + OpenAIApi = openai; + let versionVar: string = version; + openAiVersion = versionVar.replace(/[^0-9.]/g, ''); + openAiMajorVersion = parseInt(openAiVersion.split('.')[0]); + } catch (_a) { + // @ts-ignore + if (_a.code === 'MODULE_NOT_FOUND') { + throw new Error("Please install the openai package to use the OpenAIEmbeddingFunction, `npm install -S openai`"); + } + throw _a; // Re-throw other errors + } + + if (openAiMajorVersion > 3) { + this.openaiApi = new OpenAIAPIv4(this.api_key); + } else { + this.openaiApi = new OpenAIAPIv3({ + organization: this.org_id, + apiKey: this.api_key, + }); + } + } + + public async generate(texts: string[]): Promise { + + await this.loadClient(); + + return await this.openaiApi!.createEmbedding({ + model: this.model, + input: texts, + }).catch((error: any) => { + throw error; + }); + } + + /** @ignore */ + static async import(): Promise<{ + // @ts-ignore + openai: typeof import("openai"); + version: string; + }> { + try { + // @ts-ignore + const { default: openai } = await import("openai"); + // @ts-ignore + const { VERSION } = await import('openai/version'); + return { openai, version: VERSION }; + } catch (e) { + throw new Error( + "Please install openai as a dependency with, e.g. `yarn add openai`" + ); + } + } + +} diff --git a/clients/js/src/embeddings/TransformersEmbeddingFunction.ts b/clients/js/src/embeddings/TransformersEmbeddingFunction.ts new file mode 100644 index 0000000000000000000000000000000000000000..aece174b03c7d31ce353c15aeaf7fa41e2436368 --- /dev/null +++ b/clients/js/src/embeddings/TransformersEmbeddingFunction.ts @@ -0,0 +1,99 @@ +import { IEmbeddingFunction } from "./IEmbeddingFunction"; + +// Dynamically import module +let TransformersApi: Promise; + +export class TransformersEmbeddingFunction implements IEmbeddingFunction { + private pipelinePromise?: Promise | null; + private transformersApi: any; + private model: string; + private revision: string; + private quantized: boolean; + private progress_callback: Function | null; + + /** + * TransformersEmbeddingFunction constructor. + * @param options The configuration options. + * @param options.model The model to use to calculate embeddings. Defaults to 'Xenova/all-MiniLM-L6-v2', which is an ONNX port of `sentence-transformers/all-MiniLM-L6-v2`. + * @param options.revision The specific model version to use (can be a branch, tag name, or commit id). Defaults to 'main'. + * @param options.quantized Whether to load the 8-bit quantized version of the model. Defaults to `false`. + * @param options.progress_callback If specified, this function will be called during model construction, to provide the user with progress updates. + */ + constructor({ + model = "Xenova/all-MiniLM-L6-v2", + revision = "main", + quantized = false, + progress_callback = null, + }: { + model?: string; + revision?: string; + quantized?: boolean; + progress_callback?: Function | null; + } = {}) { + this.model = model; + this.revision = revision; + this.quantized = quantized; + this.progress_callback = progress_callback; + } + + public async generate(texts: string[]): Promise { + await this.loadClient(); + + // Store a promise that resolves to the pipeline + this.pipelinePromise = new Promise(async (resolve, reject) => { + try { + const pipeline = this.transformersApi + + const quantized = this.quantized + const revision = this.revision + const progress_callback = this.progress_callback + + resolve( + await pipeline("feature-extraction", this.model, { + quantized, + revision, + progress_callback, + }) + ); + } catch (e) { + reject(e); + } + }); + + let pipe = await this.pipelinePromise; + let output = await pipe(texts, { pooling: "mean", normalize: true }); + return output.tolist(); + } + + private async loadClient() { + if(this.transformersApi) return; + try { + // eslint-disable-next-line global-require,import/no-extraneous-dependencies + let { pipeline } = await TransformersEmbeddingFunction.import(); + TransformersApi = pipeline; + } catch (_a) { + // @ts-ignore + if (_a.code === 'MODULE_NOT_FOUND') { + throw new Error("Please install the @xenova/transformers package to use the TransformersEmbeddingFunction, `npm install -S @xenova/transformers`"); + } + throw _a; // Re-throw other errors + } + this.transformersApi = TransformersApi; + } + + /** @ignore */ + static async import(): Promise<{ + // @ts-ignore + pipeline: typeof import("@xenova/transformers"); + }> { + try { + // @ts-ignore + const { pipeline } = await import("@xenova/transformers"); + return { pipeline }; + } catch (e) { + throw new Error( + "Please install @xenova/transformers as a dependency with, e.g. `yarn add @xenova/transformers`" + ); + } + } +} diff --git a/clients/js/src/generated/README.md b/clients/js/src/generated/README.md new file mode 100644 index 0000000000000000000000000000000000000000..cd962982a2f680d242a13a24835811c77983d21a --- /dev/null +++ b/clients/js/src/generated/README.md @@ -0,0 +1,38 @@ +## API + +This generator creates TypeScript/JavaScript client that utilizes [Fetch API](https://fetch.spec.whatwg.org/). The generated Node module can be used in the following environments: + +Environment +* Node.js +* Webpack +* Browserify + +Language level +* ES5 - you must have a Promises/A+ library installed +* ES6 + +Module system +* CommonJS +* ES6 module system + +It can be used in both TypeScript and JavaScript. In TypeScript, the definition should be automatically resolved via `package.json`. ([Reference](http://www.typescriptlang.org/docs/handbook/typings-for-npm-packages.html)) + +### Building + +To build an compile the typescript sources to javascript use: +``` +npm install +npm run build +``` + +### Publishing + +First build the package then run ```npm publish``` + +### Consuming + +Navigate to the folder of your consuming project and run one of the following commands: + +```shell +npm install PATH_TO_GENERATED_PACKAGE --save +``` diff --git a/clients/js/src/generated/api.ts b/clients/js/src/generated/api.ts new file mode 100644 index 0000000000000000000000000000000000000000..e6b70c4d002a67552b872b43c1253a6aae1df075 --- /dev/null +++ b/clients/js/src/generated/api.ts @@ -0,0 +1,1748 @@ +/* eslint-disable */ +// tslint:disable +/** + * FastAPI + * + * + * OpenAPI spec version: 0.1.0 + * + * + * NOTE: This class is auto generated by OpenAPI Generator+. + * https://github.com/karlvr/openapi-generator-plus + * Do not edit the class manually. + */ + +import { Configuration } from "./configuration"; +import { BASE_PATH, COLLECTION_FORMATS, FetchAPI, FetchArgs, BaseAPI, RequiredError, defaultFetch } from "./runtime"; +import { Api } from "./models"; + +export type FactoryFunction = (configuration?: Configuration, basePath?: string, fetch?: FetchAPI) => T; + +/** + * ApiApi - fetch parameter creator + * @export + */ +export const ApiApiFetchParamCreator = function (configuration?: Configuration) { + return { + /** + * @summary Add + * @param {string} collectionId + * @param {Api.AddEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + add(collectionId: string, request: Api.AddEmbedding, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling add.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling add.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/add` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Delete + * @param {string} collectionId + * @param {Api.DeleteEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + aDelete(collectionId: string, request: Api.DeleteEmbedding, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling aDelete.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling aDelete.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/delete` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Get + * @param {string} collectionId + * @param {Api.GetEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + aGet(collectionId: string, request: Api.GetEmbedding, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling aGet.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling aGet.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/get` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Count + * @param {string} collectionId + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + count(collectionId: string, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling count.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/count` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Count Collections + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + countCollections(tenant: string | undefined, database: string | undefined, options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1/count_collections`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + if (database !== undefined) { + localVarQueryParameter.append('database', String(database)); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Create Collection + * @param {string} [tenant] + * @param {string} [database] + * @param {Api.CreateCollection} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + createCollection(tenant: string | undefined, database: string | undefined, request: Api.CreateCollection, options: RequestInit = {}): FetchArgs { + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling createCollection.'); + } + let localVarPath = `/api/v1/collections`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + if (database !== undefined) { + localVarQueryParameter.append('database', String(database)); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Create Database + * @param {string} [tenant] + * @param {Api.CreateDatabase} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + createDatabase(tenant: string | undefined, request: Api.CreateDatabase, options: RequestInit = {}): FetchArgs { + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling createDatabase.'); + } + let localVarPath = `/api/v1/databases`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Create Tenant + * @param {Api.CreateTenant} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + createTenant(request: Api.CreateTenant, options: RequestInit = {}): FetchArgs { + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling createTenant.'); + } + let localVarPath = `/api/v1/tenants`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Delete Collection + * @param {string} collectionName + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + deleteCollection(collectionName: string, tenant: string | undefined, database: string | undefined, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionName' is not null or undefined + if (collectionName === null || collectionName === undefined) { + throw new RequiredError('collectionName', 'Required parameter collectionName was null or undefined when calling deleteCollection.'); + } + let localVarPath = `/api/v1/collections/{collection_name}` + .replace('{collection_name}', encodeURIComponent(String(collectionName))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'DELETE' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + if (database !== undefined) { + localVarQueryParameter.append('database', String(database)); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Get Collection + * @param {string} collectionName + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getCollection(collectionName: string, tenant: string | undefined, database: string | undefined, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionName' is not null or undefined + if (collectionName === null || collectionName === undefined) { + throw new RequiredError('collectionName', 'Required parameter collectionName was null or undefined when calling getCollection.'); + } + let localVarPath = `/api/v1/collections/{collection_name}` + .replace('{collection_name}', encodeURIComponent(String(collectionName))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + if (database !== undefined) { + localVarQueryParameter.append('database', String(database)); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Get Database + * @param {string} database + * @param {string} [tenant] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getDatabase(database: string, tenant: string | undefined, options: RequestInit = {}): FetchArgs { + // verify required parameter 'database' is not null or undefined + if (database === null || database === undefined) { + throw new RequiredError('database', 'Required parameter database was null or undefined when calling getDatabase.'); + } + let localVarPath = `/api/v1/databases/{database}` + .replace('{database}', encodeURIComponent(String(database))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Get Nearest Neighbors + * @param {string} collectionId + * @param {Api.QueryEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getNearestNeighbors(collectionId: string, request: Api.QueryEmbedding, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling getNearestNeighbors.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling getNearestNeighbors.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/query` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Get Tenant + * @param {string} tenant + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getTenant(tenant: string, options: RequestInit = {}): FetchArgs { + // verify required parameter 'tenant' is not null or undefined + if (tenant === null || tenant === undefined) { + throw new RequiredError('tenant', 'Required parameter tenant was null or undefined when calling getTenant.'); + } + let localVarPath = `/api/v1/tenants/{tenant}` + .replace('{tenant}', encodeURIComponent(String(tenant))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Heartbeat + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + heartbeat(options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1/heartbeat`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary List Collections + * @param {string} [tenant] + * @param {string} [database] + * @param {number} [limit] + * @param {number} [offset] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + listCollections(tenant: string | undefined, database: string | undefined, limit: number | undefined, offset: number | undefined, options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1/collections`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + if (tenant !== undefined) { + localVarQueryParameter.append('tenant', String(tenant)); + } + + if (database !== undefined) { + localVarQueryParameter.append('database', String(database)); + } + + if (limit !== undefined) { + localVarQueryParameter.append('limit', String(limit)); + } + + if (offset !== undefined) { + localVarQueryParameter.append('offset', String(offset)); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Pre Flight Checks + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + preFlightChecks(options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1/pre-flight-checks`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Reset + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + reset(options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1/reset`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Root + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + root(options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Update + * @param {string} collectionId + * @param {Api.UpdateEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + update(collectionId: string, request: Api.UpdateEmbedding, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling update.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling update.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/update` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Update Collection + * @param {string} collectionId + * @param {Api.UpdateCollection} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + updateCollection(collectionId: string, request: Api.UpdateCollection, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling updateCollection.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling updateCollection.'); + } + let localVarPath = `/api/v1/collections/{collection_id}` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'PUT' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Upsert + * @param {string} collectionId + * @param {Api.AddEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + upsert(collectionId: string, request: Api.AddEmbedding, options: RequestInit = {}): FetchArgs { + // verify required parameter 'collectionId' is not null or undefined + if (collectionId === null || collectionId === undefined) { + throw new RequiredError('collectionId', 'Required parameter collectionId was null or undefined when calling upsert.'); + } + // verify required parameter 'request' is not null or undefined + if (request === null || request === undefined) { + throw new RequiredError('request', 'Required parameter request was null or undefined when calling upsert.'); + } + let localVarPath = `/api/v1/collections/{collection_id}/upsert` + .replace('{collection_id}', encodeURIComponent(String(collectionId))); + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'POST' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarHeaderParameter.set('Content-Type', 'application/json'); + + localVarRequestOptions.headers = localVarHeaderParameter; + + if (request !== undefined) { + localVarRequestOptions.body = JSON.stringify(request || {}); + } + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + /** + * @summary Version + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + version(options: RequestInit = {}): FetchArgs { + let localVarPath = `/api/v1/version`; + const localVarPathQueryStart = localVarPath.indexOf("?"); + const localVarRequestOptions: RequestInit = Object.assign({ method: 'GET' }, options); + const localVarHeaderParameter: Headers = options.headers ? new Headers(options.headers) : new Headers(); + const localVarQueryParameter = new URLSearchParams(localVarPathQueryStart !== -1 ? localVarPath.substring(localVarPathQueryStart + 1) : ""); + if (localVarPathQueryStart !== -1) { + localVarPath = localVarPath.substring(0, localVarPathQueryStart); + } + + localVarRequestOptions.headers = localVarHeaderParameter; + + const localVarQueryParameterString = localVarQueryParameter.toString(); + if (localVarQueryParameterString) { + localVarPath += "?" + localVarQueryParameterString; + } + return { + url: localVarPath, + options: localVarRequestOptions, + }; + }, + } +}; + +/** + * ApiApi - functional programming interface + * @export + */ +export const ApiApiFp = function(configuration?: Configuration) { + return { + /** + * @summary Add + * @param {string} collectionId + * @param {Api.AddEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + add(collectionId: string, request: Api.AddEmbedding, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).add(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 201) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Delete + * @param {string} collectionId + * @param {Api.DeleteEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + aDelete(collectionId: string, request: Api.DeleteEmbedding, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).aDelete(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Get + * @param {string} collectionId + * @param {Api.GetEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + aGet(collectionId: string, request: Api.GetEmbedding, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).aGet(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Count + * @param {string} collectionId + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + count(collectionId: string, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).count(collectionId, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Count Collections + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + countCollections(tenant: string | undefined, database: string | undefined, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).countCollections(tenant, database, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Create Collection + * @param {string} [tenant] + * @param {string} [database] + * @param {Api.CreateCollection} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + createCollection(tenant: string | undefined, database: string | undefined, request: Api.CreateCollection, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).createCollection(tenant, database, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Create Database + * @param {string} [tenant] + * @param {Api.CreateDatabase} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + createDatabase(tenant: string | undefined, request: Api.CreateDatabase, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).createDatabase(tenant, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Create Tenant + * @param {Api.CreateTenant} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + createTenant(request: Api.CreateTenant, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).createTenant(request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Delete Collection + * @param {string} collectionName + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + deleteCollection(collectionName: string, tenant: string | undefined, database: string | undefined, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).deleteCollection(collectionName, tenant, database, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Get Collection + * @param {string} collectionName + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getCollection(collectionName: string, tenant: string | undefined, database: string | undefined, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).getCollection(collectionName, tenant, database, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Get Database + * @param {string} database + * @param {string} [tenant] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getDatabase(database: string, tenant: string | undefined, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).getDatabase(database, tenant, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Get Nearest Neighbors + * @param {string} collectionId + * @param {Api.QueryEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getNearestNeighbors(collectionId: string, request: Api.QueryEmbedding, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).getNearestNeighbors(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Get Tenant + * @param {string} tenant + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + getTenant(tenant: string, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).getTenant(tenant, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Heartbeat + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + heartbeat(options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise<{ [name: string]: number }> { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).heartbeat(options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary List Collections + * @param {string} [tenant] + * @param {string} [database] + * @param {number} [limit] + * @param {number} [offset] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + listCollections(tenant: string | undefined, database: string | undefined, limit: number | undefined, offset: number | undefined, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).listCollections(tenant, database, limit, offset, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Pre Flight Checks + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + preFlightChecks(options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).preFlightChecks(options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Reset + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + reset(options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).reset(options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Root + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + root(options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise<{ [name: string]: number }> { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).root(options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Update + * @param {string} collectionId + * @param {Api.UpdateEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + update(collectionId: string, request: Api.UpdateEmbedding, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).update(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Update Collection + * @param {string} collectionId + * @param {Api.UpdateCollection} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + updateCollection(collectionId: string, request: Api.UpdateCollection, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).updateCollection(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Upsert + * @param {string} collectionId + * @param {Api.AddEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + upsert(collectionId: string, request: Api.AddEmbedding, options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).upsert(collectionId, request, options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + if (response.status === 422) { + if (mimeType === 'application/json') { + throw response; + } + throw response; + } + throw response; + }); + }; + }, + /** + * @summary Version + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + version(options?: RequestInit): (fetch?: FetchAPI, basePath?: string) => Promise { + const localVarFetchArgs = ApiApiFetchParamCreator(configuration).version(options); + return (fetch: FetchAPI = defaultFetch, basePath: string = BASE_PATH) => { + return fetch(basePath + localVarFetchArgs.url, localVarFetchArgs.options).then((response) => { + const contentType = response.headers.get('Content-Type'); + const mimeType = contentType ? contentType.replace(/;.*/, '') : undefined; + + if (response.status === 200) { + if (mimeType === 'application/json') { + return response.json() as any; + } + throw response; + } + throw response; + }); + }; + }, + } +}; + +/** + * ApiApi - factory interface + * @export + */ +export const ApiApiFactory: FactoryFunction = function (configuration?: Configuration, basePath?: string, fetch?: FetchAPI) { + return new ApiApi(configuration, basePath, fetch); +}; + +/** + * ApiApi - object-oriented interface + * @export + * @class ApiApi + * @extends {BaseAPI} + */ +export class ApiApi extends BaseAPI { + /** + * @summary Add + * @param {string} collectionId + * @param {Api.AddEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public add(collectionId: string, request: Api.AddEmbedding, options?: RequestInit) { + return ApiApiFp(this.configuration).add(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Delete + * @param {string} collectionId + * @param {Api.DeleteEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public aDelete(collectionId: string, request: Api.DeleteEmbedding, options?: RequestInit) { + return ApiApiFp(this.configuration).aDelete(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Get + * @param {string} collectionId + * @param {Api.GetEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public aGet(collectionId: string, request: Api.GetEmbedding, options?: RequestInit) { + return ApiApiFp(this.configuration).aGet(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Count + * @param {string} collectionId + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public count(collectionId: string, options?: RequestInit) { + return ApiApiFp(this.configuration).count(collectionId, options)(this.fetch, this.basePath); + } + + /** + * @summary Count Collections + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public countCollections(tenant: string | undefined, database: string | undefined, options?: RequestInit) { + return ApiApiFp(this.configuration).countCollections(tenant, database, options)(this.fetch, this.basePath); + } + + /** + * @summary Create Collection + * @param {string} [tenant] + * @param {string} [database] + * @param {Api.CreateCollection} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public createCollection(tenant: string | undefined, database: string | undefined, request: Api.CreateCollection, options?: RequestInit) { + return ApiApiFp(this.configuration).createCollection(tenant, database, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Create Database + * @param {string} [tenant] + * @param {Api.CreateDatabase} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public createDatabase(tenant: string | undefined, request: Api.CreateDatabase, options?: RequestInit) { + return ApiApiFp(this.configuration).createDatabase(tenant, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Create Tenant + * @param {Api.CreateTenant} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public createTenant(request: Api.CreateTenant, options?: RequestInit) { + return ApiApiFp(this.configuration).createTenant(request, options)(this.fetch, this.basePath); + } + + /** + * @summary Delete Collection + * @param {string} collectionName + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public deleteCollection(collectionName: string, tenant: string | undefined, database: string | undefined, options?: RequestInit) { + return ApiApiFp(this.configuration).deleteCollection(collectionName, tenant, database, options)(this.fetch, this.basePath); + } + + /** + * @summary Get Collection + * @param {string} collectionName + * @param {string} [tenant] + * @param {string} [database] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public getCollection(collectionName: string, tenant: string | undefined, database: string | undefined, options?: RequestInit) { + return ApiApiFp(this.configuration).getCollection(collectionName, tenant, database, options)(this.fetch, this.basePath); + } + + /** + * @summary Get Database + * @param {string} database + * @param {string} [tenant] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public getDatabase(database: string, tenant: string | undefined, options?: RequestInit) { + return ApiApiFp(this.configuration).getDatabase(database, tenant, options)(this.fetch, this.basePath); + } + + /** + * @summary Get Nearest Neighbors + * @param {string} collectionId + * @param {Api.QueryEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public getNearestNeighbors(collectionId: string, request: Api.QueryEmbedding, options?: RequestInit) { + return ApiApiFp(this.configuration).getNearestNeighbors(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Get Tenant + * @param {string} tenant + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public getTenant(tenant: string, options?: RequestInit) { + return ApiApiFp(this.configuration).getTenant(tenant, options)(this.fetch, this.basePath); + } + + /** + * @summary Heartbeat + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public heartbeat(options?: RequestInit) { + return ApiApiFp(this.configuration).heartbeat(options)(this.fetch, this.basePath); + } + + /** + * @summary List Collections + * @param {string} [tenant] + * @param {string} [database] + * @param {number} [limit] + * @param {number} [offset] + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public listCollections(tenant: string | undefined, database: string | undefined, limit: number | undefined, offset: number | undefined, options?: RequestInit) { + return ApiApiFp(this.configuration).listCollections(tenant, database, limit, offset, options)(this.fetch, this.basePath); + } + + /** + * @summary Pre Flight Checks + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public preFlightChecks(options?: RequestInit) { + return ApiApiFp(this.configuration).preFlightChecks(options)(this.fetch, this.basePath); + } + + /** + * @summary Reset + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public reset(options?: RequestInit) { + return ApiApiFp(this.configuration).reset(options)(this.fetch, this.basePath); + } + + /** + * @summary Root + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public root(options?: RequestInit) { + return ApiApiFp(this.configuration).root(options)(this.fetch, this.basePath); + } + + /** + * @summary Update + * @param {string} collectionId + * @param {Api.UpdateEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public update(collectionId: string, request: Api.UpdateEmbedding, options?: RequestInit) { + return ApiApiFp(this.configuration).update(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Update Collection + * @param {string} collectionId + * @param {Api.UpdateCollection} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public updateCollection(collectionId: string, request: Api.UpdateCollection, options?: RequestInit) { + return ApiApiFp(this.configuration).updateCollection(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Upsert + * @param {string} collectionId + * @param {Api.AddEmbedding} request + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public upsert(collectionId: string, request: Api.AddEmbedding, options?: RequestInit) { + return ApiApiFp(this.configuration).upsert(collectionId, request, options)(this.fetch, this.basePath); + } + + /** + * @summary Version + * @param {RequestInit} [options] Override http request option. + * @throws {RequiredError} + */ + public version(options?: RequestInit) { + return ApiApiFp(this.configuration).version(options)(this.fetch, this.basePath); + } + +} + +/** + * We sometimes represent dates as strings (in models) and as Dates (in parameters) so this + * function converts them both to a string. + */ +function dateToString(value: Date | string | undefined): string | undefined { + if (value instanceof Date) { + return value.toISOString(); + } else if (typeof value === 'string') { + return value; + } else { + return undefined; + } +} diff --git a/clients/js/src/generated/configuration.ts b/clients/js/src/generated/configuration.ts new file mode 100644 index 0000000000000000000000000000000000000000..f199912bc7f5663e76fe12a544cfe758e2c8c083 --- /dev/null +++ b/clients/js/src/generated/configuration.ts @@ -0,0 +1,66 @@ +/* eslint-disable */ +// tslint:disable +/** + * FastAPI + * + * + * OpenAPI spec version: 0.1.0 + * + * + * NOTE: This class is auto generated by OpenAPI Generator+. + * https://github.com/karlvr/openapi-generator-plus + * Do not edit the class manually. + */ + +export interface ConfigurationParameters { + apiKey?: string | ((name: string) => string | null); + username?: string; + password?: string; + authorization?: string | ((name: string, scopes?: string[]) => string | null); + basePath?: string; +} + +export class Configuration { + /** + * parameter for apiKey security + * @param name security name + * @memberof Configuration + */ + apiKey?: string | ((name: string) => string | null); + /** + * parameter for basic security + * + * @type {string} + * @memberof Configuration + */ + username?: string; + /** + * parameter for basic security + * + * @type {string} + * @memberof Configuration + */ + password?: string; + /** + * parameter for oauth2, openIdConnect or http security + * @param name security name + * @param scopes oauth2 scopes + * @memberof Configuration + */ + authorization?: string | ((name: string, scopes?: string[]) => string | null); + /** + * override base path + * + * @type {string} + * @memberof Configuration + */ + basePath?: string; + + constructor(param: ConfigurationParameters = {}) { + this.apiKey = param.apiKey; + this.username = param.username; + this.password = param.password; + this.authorization = param.authorization; + this.basePath = param.basePath; + } +} diff --git a/clients/js/src/generated/index.ts b/clients/js/src/generated/index.ts new file mode 100644 index 0000000000000000000000000000000000000000..368f485f0a7abe564e7f7400119c840226732388 --- /dev/null +++ b/clients/js/src/generated/index.ts @@ -0,0 +1,19 @@ +/* eslint-disable */ +// tslint:disable +/** + * FastAPI + * + * + * OpenAPI spec version: 0.1.0 + * + * + * NOTE: This class is auto generated by OpenAPI Generator+. + * https://github.com/karlvr/openapi-generator-plus + * Do not edit the class manually. + */ + +export * from "./api"; +export * from "./models"; +export * from "./configuration"; +export { RequiredError } from "./runtime"; +export type { FetchAPI, FetchArgs } from "./runtime"; diff --git a/clients/js/src/generated/models.ts b/clients/js/src/generated/models.ts new file mode 100644 index 0000000000000000000000000000000000000000..661f30ca8992d96d345fbb3e72d66696b63b27e5 --- /dev/null +++ b/clients/js/src/generated/models.ts @@ -0,0 +1,305 @@ +/* eslint-disable */ +// tslint:disable +/** + * FastAPI + * + * + * OpenAPI spec version: 0.1.0 + * + * + * NOTE: This class is auto generated by OpenAPI Generator+. + * https://github.com/karlvr/openapi-generator-plus + * Do not edit the class manually. + */ + +export namespace Api { + export interface Add201Response { + } + + export interface AddEmbedding { + embeddings?: Api.AddEmbedding.Embedding[]; + metadatas?: Api.AddEmbedding.Metadata[]; + documents?: string[]; + uris?: string[]; + ids: string[]; + } + + /** + * @export + * @namespace AddEmbedding + */ + export namespace AddEmbedding { + export interface Embedding { + } + + export interface Metadata { + } + + } + + export interface ADelete200Response { + } + + export interface AGet200Response { + } + + export interface Count200Response { + } + + export interface CountCollections200Response { + } + + export interface CreateCollection { + name: string; + metadata?: Api.CreateCollection.Metadata; + 'get_or_create'?: boolean; + } + + /** + * @export + * @namespace CreateCollection + */ + export namespace CreateCollection { + export interface Metadata { + } + + } + + export interface CreateCollection200Response { + } + + export interface CreateDatabase { + name: string; + } + + export interface CreateDatabase200Response { + } + + export interface CreateTenant { + name: string; + } + + export interface CreateTenant200Response { + } + + export interface DeleteCollection200Response { + } + + export interface DeleteEmbedding { + ids?: string[]; + where?: Api.DeleteEmbedding.Where; + 'where_document'?: Api.DeleteEmbedding.WhereDocument; + } + + /** + * @export + * @namespace DeleteEmbedding + */ + export namespace DeleteEmbedding { + export interface Where { + } + + export interface WhereDocument { + } + + } + + export interface GetCollection200Response { + } + + export interface GetDatabase200Response { + } + + export interface GetEmbedding { + ids?: string[]; + where?: Api.GetEmbedding.Where; + 'where_document'?: Api.GetEmbedding.WhereDocument; + sort?: string; + /** + * @type {number} + * @memberof GetEmbedding + */ + limit?: number; + /** + * @type {number} + * @memberof GetEmbedding + */ + offset?: number; + include?: (Api.GetEmbedding.Include.EnumValueEnum | Api.GetEmbedding.Include.EnumValueEnum2 | Api.GetEmbedding.Include.EnumValueEnum3 | Api.GetEmbedding.Include.EnumValueEnum4 | Api.GetEmbedding.Include.EnumValueEnum5 | Api.GetEmbedding.Include.EnumValueEnum6)[]; + } + + /** + * @export + * @namespace GetEmbedding + */ + export namespace GetEmbedding { + export interface Where { + } + + export interface WhereDocument { + } + + export type Include = Api.GetEmbedding.Include.EnumValueEnum | Api.GetEmbedding.Include.EnumValueEnum2 | Api.GetEmbedding.Include.EnumValueEnum3 | Api.GetEmbedding.Include.EnumValueEnum4 | Api.GetEmbedding.Include.EnumValueEnum5 | Api.GetEmbedding.Include.EnumValueEnum6; + + /** + * @export + * @namespace Include + */ + export namespace Include { + export enum EnumValueEnum { + Documents = 'documents' + } + + export enum EnumValueEnum2 { + Embeddings = 'embeddings' + } + + export enum EnumValueEnum3 { + Metadatas = 'metadatas' + } + + export enum EnumValueEnum4 { + Distances = 'distances' + } + + export enum EnumValueEnum5 { + Uris = 'uris' + } + + export enum EnumValueEnum6 { + Data = 'data' + } + + } + + } + + export interface GetNearestNeighbors200Response { + } + + export interface GetTenant200Response { + } + + export interface HTTPValidationError { + detail?: Api.ValidationError[]; + } + + export interface ListCollections200Response { + } + + export interface PreFlightChecks200Response { + } + + export interface QueryEmbedding { + where?: Api.QueryEmbedding.Where; + 'where_document'?: Api.QueryEmbedding.WhereDocument; + 'query_embeddings': Api.QueryEmbedding.QueryEmbedding2[]; + /** + * @type {number} + * @memberof QueryEmbedding + */ + 'n_results'?: number; + include?: (Api.QueryEmbedding.Include.EnumValueEnum | Api.QueryEmbedding.Include.EnumValueEnum2 | Api.QueryEmbedding.Include.EnumValueEnum3 | Api.QueryEmbedding.Include.EnumValueEnum4 | Api.QueryEmbedding.Include.EnumValueEnum5 | Api.QueryEmbedding.Include.EnumValueEnum6)[]; + } + + /** + * @export + * @namespace QueryEmbedding + */ + export namespace QueryEmbedding { + export interface Where { + } + + export interface WhereDocument { + } + + export interface QueryEmbedding2 { + } + + export type Include = Api.QueryEmbedding.Include.EnumValueEnum | Api.QueryEmbedding.Include.EnumValueEnum2 | Api.QueryEmbedding.Include.EnumValueEnum3 | Api.QueryEmbedding.Include.EnumValueEnum4 | Api.QueryEmbedding.Include.EnumValueEnum5 | Api.QueryEmbedding.Include.EnumValueEnum6; + + /** + * @export + * @namespace Include + */ + export namespace Include { + export enum EnumValueEnum { + Documents = 'documents' + } + + export enum EnumValueEnum2 { + Embeddings = 'embeddings' + } + + export enum EnumValueEnum3 { + Metadatas = 'metadatas' + } + + export enum EnumValueEnum4 { + Distances = 'distances' + } + + export enum EnumValueEnum5 { + Uris = 'uris' + } + + export enum EnumValueEnum6 { + Data = 'data' + } + + } + + } + + export interface Update200Response { + } + + export interface UpdateCollection { + 'new_name'?: string; + 'new_metadata'?: Api.UpdateCollection.NewMetadata; + } + + /** + * @export + * @namespace UpdateCollection + */ + export namespace UpdateCollection { + export interface NewMetadata { + } + + } + + export interface UpdateCollection200Response { + } + + export interface UpdateEmbedding { + embeddings?: Api.UpdateEmbedding.Embedding[]; + metadatas?: Api.UpdateEmbedding.Metadata[]; + documents?: string[]; + uris?: string[]; + ids: string[]; + } + + /** + * @export + * @namespace UpdateEmbedding + */ + export namespace UpdateEmbedding { + export interface Embedding { + } + + export interface Metadata { + } + + } + + export interface Upsert200Response { + } + + export interface ValidationError { + loc: (string | number)[]; + msg: string; + 'type': string; + } + +} diff --git a/clients/js/src/generated/runtime.ts b/clients/js/src/generated/runtime.ts new file mode 100644 index 0000000000000000000000000000000000000000..d73b079b1b4c040cfc0ea37d2de51ae3315933da --- /dev/null +++ b/clients/js/src/generated/runtime.ts @@ -0,0 +1,77 @@ +import 'isomorphic-fetch'; +/* eslint-disable */ +// tslint:disable +/** + * FastAPI + * + * + * OpenAPI spec version: 0.1.0 + * + * + * NOTE: This class is auto generated by OpenAPI Generator+. + * https://github.com/karlvr/openapi-generator-plus + * Do not edit the class manually. + */ + +export const defaultFetch = fetch; +import { Configuration } from "./configuration"; + +export const BASE_PATH = ""; + +/** + * + * @export + */ +export const COLLECTION_FORMATS = { + csv: ",", + ssv: " ", + tsv: "\t", + pipes: "|", +}; + +/** + * + * @export + * @type FetchAPI + */ +export type FetchAPI = typeof defaultFetch; + +/** + * + * @export + * @interface FetchArgs + */ +export interface FetchArgs { + url: string; + options: RequestInit; +} + +/** + * + * @export + * @class BaseAPI + */ +export class BaseAPI { + protected configuration?: Configuration; + + constructor(configuration?: Configuration, protected basePath: string = BASE_PATH, protected fetch: FetchAPI = defaultFetch) { + if (configuration) { + this.configuration = configuration; + this.basePath = configuration.basePath || this.basePath; + } + } +}; + +/** + * + * @export + * @class RequiredError + * @extends {Error} + */ +export class RequiredError extends Error { + constructor(public field: string, msg?: string) { + super(msg); + Object.setPrototypeOf(this, RequiredError.prototype); + this.name = "RequiredError"; + } +} diff --git a/clients/js/src/index.ts b/clients/js/src/index.ts new file mode 100644 index 0000000000000000000000000000000000000000..27316d1164ad410cc42f31641da890db2c735443 --- /dev/null +++ b/clients/js/src/index.ts @@ -0,0 +1,45 @@ +export { ChromaClient } from './ChromaClient'; +export { AdminClient } from './AdminClient'; +export { CloudClient } from './CloudClient'; +export { Collection } from './Collection'; + +export { IEmbeddingFunction } from './embeddings/IEmbeddingFunction'; +export { OpenAIEmbeddingFunction } from './embeddings/OpenAIEmbeddingFunction'; +export { CohereEmbeddingFunction } from './embeddings/CohereEmbeddingFunction'; +export { TransformersEmbeddingFunction } from './embeddings/TransformersEmbeddingFunction'; +export { DefaultEmbeddingFunction } from './embeddings/DefaultEmbeddingFunction'; +export { HuggingFaceEmbeddingServerFunction } from './embeddings/HuggingFaceEmbeddingServerFunction'; +export { JinaEmbeddingFunction } from './embeddings/JinaEmbeddingFunction'; +export { GoogleGenerativeAiEmbeddingFunction } from './embeddings/GoogleGeminiEmbeddingFunction'; + +export { + IncludeEnum, + GetParams, + CollectionType, + CollectionMetadata, + Embedding, + Embeddings, + Metadata, + Metadatas, + Document, + Documents, + ID, + IDs, + Where, + WhereDocument, + GetResponse, + QueryResponse, + ListCollectionsParams, + ChromaClientParams, + CreateCollectionParams, + GetOrCreateCollectionParams, + GetCollectionParams, + DeleteCollectionParams, + AddParams, + UpsertParams, + UpdateParams, + ModifyCollectionParams, + QueryParams, + PeekParams, + DeleteParams +} from './types'; diff --git a/clients/js/src/types.ts b/clients/js/src/types.ts new file mode 100644 index 0000000000000000000000000000000000000000..6c46d52c13312839743e4001c15523a4b653f4dc --- /dev/null +++ b/clients/js/src/types.ts @@ -0,0 +1,156 @@ +import { AuthOptions } from "./auth"; +import { IEmbeddingFunction } from "./embeddings/IEmbeddingFunction"; + +export enum IncludeEnum { + Documents = 'documents', + Embeddings = 'embeddings', + Metadatas = 'metadatas', + Distances = 'distances' +} + +type Number = number; +export type Embedding = Array; +export type Embeddings = Array; + +export type Metadata = Record; +export type Metadatas = Array; + +export type Document = string; +export type Documents = Array; + +export type ID = string; +export type IDs = ID[]; + +export type PositiveInteger = number; + +type LiteralValue = string | number | boolean; +type ListLiteralValue = LiteralValue[]; +type LiteralNumber = number; +type LogicalOperator = "$and" | "$or"; +type InclusionOperator = "$in" | "$nin"; +type WhereOperator = "$gt" | "$gte" | "$lt" | "$lte" | "$ne" | "$eq"; + +type OperatorExpression = { + [key in WhereOperator | InclusionOperator | LogicalOperator ]?: LiteralValue | ListLiteralValue; +}; + +type BaseWhere = { + [key: string]: LiteralValue | OperatorExpression; +}; + +type LogicalWhere = { + [key in LogicalOperator]?: Where[]; +}; + +export type Where = BaseWhere | LogicalWhere; + +type WhereDocumentOperator = "$contains" | LogicalOperator; + +export type WhereDocument = { + [key in WhereDocumentOperator]?: LiteralValue | LiteralNumber | WhereDocument[]; +}; + +export type CollectionType = { + name: string; + id: string; + metadata: Metadata | null; +}; + +export type GetResponse = { + ids: IDs; + embeddings: null | Embeddings; + documents: (null | Document)[]; + metadatas: (null | Metadata)[]; + error: null | string; +}; + +export type QueryResponse = { + ids: IDs[]; + embeddings: null | Embeddings[]; + documents: (null | Document)[][]; + metadatas: (null | Metadata)[][]; + distances: null | number[][]; +} + +export type AddResponse = { + error: string; +} + +export type CollectionMetadata = Record; + +// RequestInit can be used to set Authorization headers and more +// see all options here: https://www.jsdocs.io/package/@types/node-fetch#RequestInit +export type ConfigOptions = { + options?: RequestInit; +}; + +export type GetParams = { + ids?: ID | IDs, + where?: Where, + limit?: PositiveInteger, + offset?: PositiveInteger, + include?: IncludeEnum[], + whereDocument?: WhereDocument +} + +export type ListCollectionsParams = { + limit?: PositiveInteger, + offset?: PositiveInteger, +} + +export type ChromaClientParams = { + path?: string, + fetchOptions?: RequestInit, + auth?: AuthOptions, + tenant?: string, + database?: string, +} + +export type CreateCollectionParams = { + name: string, + metadata?: CollectionMetadata, + embeddingFunction?: IEmbeddingFunction +} + +export type GetOrCreateCollectionParams = CreateCollectionParams + +export type GetCollectionParams = { + name: string; + embeddingFunction?: IEmbeddingFunction +} + +export type DeleteCollectionParams = { + name: string +} + +export type AddParams = { + ids: ID | IDs, + embeddings?: Embedding | Embeddings, + metadatas?: Metadata | Metadatas, + documents?: Document | Documents, +} + +export type UpsertParams = AddParams; +export type UpdateParams = AddParams; + +export type ModifyCollectionParams = { + name?: string, + metadata?: CollectionMetadata +} + +export type QueryParams = { + queryEmbeddings?: Embedding | Embeddings, + nResults?: PositiveInteger, + where?: Where, + queryTexts?: string | string[], + whereDocument?: WhereDocument, // {"$contains":"search_string"} + include?: IncludeEnum[] // ["metadata", "document"] +} + +export type PeekParams = { limit?: PositiveInteger } + +export type DeleteParams = { + ids?: ID | IDs, + where?: Where, + whereDocument?: WhereDocument +} diff --git a/clients/js/src/utils.ts b/clients/js/src/utils.ts new file mode 100644 index 0000000000000000000000000000000000000000..e3ad5361e61f722a785bd86cd9120ecf489816c0 --- /dev/null +++ b/clients/js/src/utils.ts @@ -0,0 +1,99 @@ +import { Api } from "./generated"; +import Count200Response = Api.Count200Response; +import { AdminClient } from "./AdminClient"; + +// a function to convert a non-Array object to an Array +export function toArray(obj: T | Array): Array { + if (Array.isArray(obj)) { + return obj; + } else { + return [obj]; + } +} + +// a function to convert an array to array of arrays +export function toArrayOfArrays( + obj: Array> | Array +): Array> { + if (Array.isArray(obj[0])) { + return obj as Array>; + } else { + return [obj] as Array>; + } +} + +// we need to override constructors to make it work with jest +// https://stackoverflow.com/questions/76007003/jest-tobeinstanceof-expected-constructor-array-received-constructor-array +export function repack(value: unknown): any { + if (Boolean(value) && typeof value === "object") { + if (Array.isArray(value)) { + return new Array(...value); + } else { + return { ...value }; + } + } else { + return value; + } +} + +export async function handleError(error: unknown) { + if (error instanceof Response) { + try { + const res = await (error as Response).json(); + if ("error" in res) { + return { error: res.error }; + } + } catch (e: unknown) { + return { + error: + e && typeof e === "object" && "message" in e + ? e.message + : "unknown error", + }; + } + } + return { error }; +} + +export async function handleSuccess( + response: Response | string | Count200Response +) { + switch (true) { + case response instanceof Response: + return repack(await (response as Response).json()); + case typeof response === "string": + return repack(response as string); // currently version is the only thing that return non-JSON + default: + return repack(response); + } +} + +/** + * Dynamically imports a specified module, providing a workaround for browser environments. + * This function is necessary because we dynamically import optional dependencies + * which can cause issues with bundlers that detect the import and throw an error + * on build time when the dependency is not installed. + * Using this workaround, the dynamic import is only evaluated on runtime + * where we work with try-catch when importing optional dependencies. + * + * @param {string} moduleName - Specifies the module to import. + * @returns {Promise} Returns a Promise that resolves to the imported module. + */ +export async function importOptionalModule(moduleName: string) { + return Function(`return import("${moduleName}")`)(); +} + + +export async function validateTenantDatabase(adminClient: AdminClient, tenant: string, database: string): Promise { + try { + await adminClient.getTenant({name: tenant}); + } catch (error) { + throw new Error(`Error: ${error}, Could not connect to tenant ${tenant}. Are you sure it exists?`); + } + + try { + await adminClient.getDatabase({name: database, tenantName: tenant}); + } catch (error) { + throw new Error(`Error: ${error}, Could not connect to database ${database} for tenant ${tenant}. Are you sure it exists?`); + } +} diff --git a/clients/js/test/add.collections.test.ts b/clients/js/test/add.collections.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..7ac271ff98e93f5a53404491178609d1437ccf0d --- /dev/null +++ b/clients/js/test/add.collections.test.ts @@ -0,0 +1,116 @@ +import { expect, test } from '@jest/globals'; +import chroma from './initClient' +import { DOCUMENTS, EMBEDDINGS, IDS } from './data'; +import { METADATAS } from './data'; +import { IncludeEnum } from "../src/types"; +import {OpenAIEmbeddingFunction} from "../src/embeddings/OpenAIEmbeddingFunction"; +import {CohereEmbeddingFunction} from "../src/embeddings/CohereEmbeddingFunction"; +test("it should add single embeddings to a collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + const ids = "test1"; + const embeddings = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; + const metadatas = { test: "test" }; + await collection.add({ ids, embeddings, metadatas }); + const count = await collection.count(); + expect(count).toBe(1); + var res = await collection.get({ + ids: [ids], include: [ + IncludeEnum.Embeddings, + ] + }); + expect(res.embeddings![0]).toEqual(embeddings); +}); + +test("it should add batch embeddings to a collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS }); + const count = await collection.count(); + expect(count).toBe(3); + var res = await collection.get({ + ids: IDS, include: [ + IncludeEnum.Embeddings, + ] + }); + expect(res.embeddings).toEqual(EMBEDDINGS); // reverse because of the order of the ids +}); + + +if (!process.env.OPENAI_API_KEY) { + test.skip("it should add OpenAI embeddings", async () => { + }); +} else { + test("it should add OpenAI embeddings", async () => { + await chroma.reset(); + const embedder = new OpenAIEmbeddingFunction({ openai_api_key: process.env.OPENAI_API_KEY || "" }) + const collection = await chroma.createCollection({ name: "test" ,embeddingFunction: embedder}); + const embeddings = await embedder.generate(DOCUMENTS); + await collection.add({ ids: IDS, embeddings: embeddings }); + const count = await collection.count(); + expect(count).toBe(3); + var res = await collection.get({ + ids: IDS, include: [ + IncludeEnum.Embeddings, + ] + }); + expect(res.embeddings).toEqual(embeddings); // reverse because of the order of the ids + }); +} + +if (!process.env.COHERE_API_KEY) { + test.skip("it should add Cohere embeddings", async () => { + }); +} else { + test("it should add Cohere embeddings", async () => { + await chroma.reset(); + const embedder = new CohereEmbeddingFunction({ cohere_api_key: process.env.COHERE_API_KEY || "" }) + const collection = await chroma.createCollection({ name: "test" ,embeddingFunction: embedder}); + const embeddings = await embedder.generate(DOCUMENTS); + await collection.add({ ids: IDS, embeddings: embeddings }); + const count = await collection.count(); + expect(count).toBe(3); + var res = await collection.get({ + ids: IDS, include: [ + IncludeEnum.Embeddings, + ] + }); + expect(res.embeddings).toEqual(embeddings); // reverse because of the order of the ids + }); +} + +test("add documents", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + let resp = await collection.add({ ids: IDS, embeddings: EMBEDDINGS, documents: DOCUMENTS }); + expect(resp).toBe(true) + const results = await collection.get({ ids: ["test1"] }); + expect(results.documents[0]).toBe("This is a test"); +}); + +test('It should return an error when inserting duplicate IDs in the same batch', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = IDS.concat(["test1"]) + const embeddings = EMBEDDINGS.concat([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]]) + const metadatas = METADATAS.concat([{ test: 'test1', 'float_value': 0.1 }]) + try { + await collection.add({ ids, embeddings, metadatas }); + } catch (e: any) { + expect(e.message).toMatch('duplicates') + } +}) + + +test('should error on empty embedding', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ["id1"] + const embeddings = [[]] + const metadatas = [{ test: 'test1', 'float_value': 0.1 }] + try { + await collection.add({ ids, embeddings, metadatas }); + } catch (e: any) { + expect(e.message).toMatch('got empty embedding at pos') + } +}) \ No newline at end of file diff --git a/clients/js/test/admin.test.ts b/clients/js/test/admin.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..d0ee72db8c46b64fb4e37dadacdf9c7571f86f62 --- /dev/null +++ b/clients/js/test/admin.test.ts @@ -0,0 +1,50 @@ +import { expect, test } from "@jest/globals"; +import { AdminClient } from "../src/AdminClient"; +import adminClient from "./initAdminClient"; + +test("it should create the admin client connection", async () => { + expect(adminClient).toBeDefined(); + expect(adminClient).toBeInstanceOf(AdminClient); +}); + +test("it should create and get a tenant", async () => { + await adminClient.createTenant({ name: "testTenant" }); + const tenant = await adminClient.getTenant({ name: "testTenant" }); + expect(tenant).toBeDefined(); + expect(tenant).toHaveProperty('name') + expect(tenant.name).toBe("testTenant"); +}) + +test("it should create and get a database for a tenant", async () => { + await adminClient.createTenant({ name: "test3" }); + const database = await adminClient.createDatabase({ name: "test", tenantName: "test3" }); + expect(database).toBeDefined(); + expect(database).toHaveProperty('name') + expect(database.name).toBe("test"); + + const getDatabase = await adminClient.getDatabase({ name: "test", tenantName: "test3" }); + expect(getDatabase).toBeDefined(); + expect(getDatabase).toHaveProperty('name') + expect(getDatabase.name).toBe("test"); +}) + +// test that it can set the tenant and database +test("it should set the tenant and database", async () => { + // doesnt exist so should throw + await expect(adminClient.setTenant({ tenant: "testTenant", database: "testDatabase" })).rejects.toThrow(); + + await adminClient.createTenant({ name: "testTenant!" }); + await adminClient.createDatabase({ name: "test3!", tenantName: "testTenant!" }); + + await adminClient.setTenant({ tenant: "testTenant!", database: "test3!" }); + expect(adminClient.tenant).toBe("testTenant!"); + expect(adminClient.database).toBe("test3!"); + + // doesnt exist so should throw + await expect(adminClient.setDatabase({database: "testDatabase2"})).rejects.toThrow(); + + await adminClient.createDatabase({ name: "testDatabase2", tenantName: "testTenant!" }); + await adminClient.setDatabase({database: "testDatabase2"}) + + expect(adminClient.database).toBe("testDatabase2"); +}) diff --git a/clients/js/test/auth.basic.test.ts b/clients/js/test/auth.basic.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..6253bb758a3fd4b1f4483f81219c0c5cbcbe1294 --- /dev/null +++ b/clients/js/test/auth.basic.test.ts @@ -0,0 +1,33 @@ +import {expect, test} from "@jest/globals"; +import {chromaBasic} from "./initClientWithAuth"; +import chromaNoAuth from "./initClient"; +import { ChromaClient } from "../src/ChromaClient"; + +test("it should get the version without auth needed", async () => { + const version = await chromaNoAuth.version(); + expect(version).toBeDefined(); + expect(version).toMatch(/^[0-9]+\.[0-9]+\.[0-9]+$/); +}); + +test("it should get the heartbeat without auth needed", async () => { + const heartbeat = await chromaNoAuth.heartbeat(); + expect(heartbeat).toBeDefined(); + expect(heartbeat).toBeGreaterThan(0); +}); + +test("it should raise error when non authenticated", async () => { + await expect(chromaNoAuth.listCollections()).rejects.toMatchObject({ + status: 401 + }); +}); + +test('it should list collections', async () => { + await chromaBasic.reset() + let collections = await chromaBasic.listCollections() + expect(collections).toBeDefined() + expect(collections).toBeInstanceOf(Array) + expect(collections.length).toBe(0) + await chromaBasic.createCollection({name: "test"}); + collections = await chromaBasic.listCollections() + expect(collections.length).toBe(1) +}) diff --git a/clients/js/test/auth.token.test.ts b/clients/js/test/auth.token.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..a57ea09e1f51c1114c1994a30132cb24ac9fef9f --- /dev/null +++ b/clients/js/test/auth.token.test.ts @@ -0,0 +1,70 @@ +import {expect, test} from "@jest/globals"; +import {ChromaClient} from "../src/ChromaClient"; +import {chromaTokenDefault, chromaTokenBearer, chromaTokenXToken, cloudClient} from "./initClientWithAuth"; +import chromaNoAuth from "./initClient"; + +test("it should get the version without auth needed", async () => { + const version = await chromaNoAuth.version(); + expect(version).toBeDefined(); + expect(version).toMatch(/^[0-9]+\.[0-9]+\.[0-9]+$/); +}); + +test("it should get the heartbeat without auth needed", async () => { + const heartbeat = await chromaNoAuth.heartbeat(); + expect(heartbeat).toBeDefined(); + expect(heartbeat).toBeGreaterThan(0); +}); + +test("it should raise error when non authenticated", async () => { + await expect(chromaNoAuth.listCollections()).rejects.toMatchObject({ + status: 401 + }); +}); + +if (!process.env.XTOKEN_TEST) { + test('it should list collections with default token config', async () => { + await chromaTokenDefault.reset() + let collections = await chromaTokenDefault.listCollections() + expect(collections).toBeDefined() + expect(collections).toBeInstanceOf(Array) + expect(collections.length).toBe(0) + const collection = await chromaTokenDefault.createCollection({name: "test"}); + collections = await chromaTokenDefault.listCollections() + expect(collections.length).toBe(1) + }) + + test('it should list collections with explicit bearer token config', async () => { + await chromaTokenBearer.reset() + let collections = await chromaTokenBearer.listCollections() + expect(collections).toBeDefined() + expect(collections).toBeInstanceOf(Array) + expect(collections.length).toBe(0) + const collection = await chromaTokenBearer.createCollection({name: "test"}); + collections = await chromaTokenBearer.listCollections() + expect(collections.length).toBe(1) + }) +} else { + + test('it should list collections with explicit x-token token config', async () => { + await chromaTokenXToken.reset() + let collections = await chromaTokenXToken.listCollections() + expect(collections).toBeDefined() + expect(collections).toBeInstanceOf(Array) + expect(collections.length).toBe(0) + const collection = await chromaTokenXToken.createCollection({name: "test"}); + collections = await chromaTokenXToken.listCollections() + expect(collections.length).toBe(1) + }) + + test('it should list collections with explicit x-token token config in CloudClient', async () => { + await cloudClient.reset() + let collections = await cloudClient.listCollections() + expect(collections).toBeDefined() + expect(collections).toBeInstanceOf(Array) + expect(collections.length).toBe(0) + const collection = await cloudClient.createCollection({name: "test"}); + collections = await cloudClient.listCollections() + expect(collections.length).toBe(1) + }) + +} diff --git a/clients/js/test/client.test.ts b/clients/js/test/client.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..512237a245707c91d55667b41f7c079649ac2e80 --- /dev/null +++ b/clients/js/test/client.test.ts @@ -0,0 +1,195 @@ +import { expect, test } from "@jest/globals"; +import { ChromaClient } from "../src/ChromaClient"; +import chroma from "./initClient"; + +test("it should create the client connection", async () => { + expect(chroma).toBeDefined(); + expect(chroma).toBeInstanceOf(ChromaClient); +}); + +test("it should get the version", async () => { + const version = await chroma.version(); + expect(version).toBeDefined(); + expect(version).toMatch(/^[0-9]+\.[0-9]+\.[0-9]+$/); +}); + +test("it should get the heartbeat", async () => { + const heartbeat = await chroma.heartbeat(); + expect(heartbeat).toBeDefined(); + expect(heartbeat).toBeGreaterThan(0); +}); + +test("it should reset the database", async () => { + await chroma.reset(); + const collections = await chroma.listCollections(); + expect(collections).toBeDefined(); + expect(collections).toBeInstanceOf(Array); + expect(collections.length).toBe(0); + + const collection = await chroma.createCollection({ name: "test" }); + const collections2 = await chroma.listCollections(); + expect(collections2).toBeDefined(); + expect(collections2).toBeInstanceOf(Array); + expect(collections2.length).toBe(1); + + await chroma.reset(); + const collections3 = await chroma.listCollections(); + expect(collections3).toBeDefined(); + expect(collections3).toBeInstanceOf(Array); + expect(collections3.length).toBe(0); +}); + +test('it should list collections', async () => { + await chroma.reset() + let collections = await chroma.listCollections() + expect(collections).toBeDefined() + expect(collections).toBeInstanceOf(Array) + expect(collections.length).toBe(0) + const collection = await chroma.createCollection({ name: "test" }); + collections = await chroma.listCollections() + expect(collections.length).toBe(1) +}) + +test('it should get a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const collection2 = await chroma.getCollection({ name: "test" }); + expect(collection).toBeDefined() + expect(collection2).toBeDefined() + expect(collection).toHaveProperty('name') + expect(collection2).toHaveProperty('name') + expect(collection.name).toBe(collection2.name) + expect(collection).toHaveProperty('id') + expect(collection2).toHaveProperty('id') + expect(collection.id).toBe(collection2.id) +}) + +test('it should delete a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + let collections = await chroma.listCollections() + expect(collections.length).toBe(1) + var resp = await chroma.deleteCollection({ name: "test" }); + collections = await chroma.listCollections() + expect(collections.length).toBe(0) +}) + +test('it should add single embeddings to a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = 'test1' + const embeddings = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + const metadatas = { test: 'test' } + await collection.add({ ids, embeddings, metadatas }) + const count = await collection.count() + expect(count).toBe(1) +}) + +test('it should add batch embeddings to a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2', 'test3'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + await collection.add({ ids, embeddings }) + const count = await collection.count() + expect(count).toBe(3) +}) + +test('it should query a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2', 'test3'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + await collection.add({ ids, embeddings }) + const results = await collection.query({ queryEmbeddings: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], nResults: 2 }) + expect(results).toBeDefined() + expect(results).toBeInstanceOf(Object) + // expect(results.embeddings[0].length).toBe(2) + const result: string[] = ['test1', 'test2'] + expect(result).toEqual(expect.arrayContaining(results.ids[0])); + expect(['test3']).not.toEqual(expect.arrayContaining(results.ids[0])); +}) + +test('it should peek a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2', 'test3'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + await collection.add({ ids, embeddings }) + const results = await collection.peek({ limit: 2 }) + expect(results).toBeDefined() + expect(results).toBeInstanceOf(Object) + expect(results.ids.length).toBe(2) + expect(['test1', 'test2']).toEqual(expect.arrayContaining(results.ids)); +}) + +test('it should get a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2', 'test3'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + const metadatas = [{ test: 'test1' }, { test: 'test2' }, { test: 'test3' }] + await collection.add({ ids, embeddings, metadatas }) + const results = await collection.get({ ids: ['test1'] }) + expect(results).toBeDefined() + expect(results).toBeInstanceOf(Object) + expect(results.ids.length).toBe(1) + expect(['test1']).toEqual(expect.arrayContaining(results.ids)); + expect(['test2']).not.toEqual(expect.arrayContaining(results.ids)); + + const results2 = await collection.get({ where: { 'test': 'test1' } }) + expect(results2).toBeDefined() + expect(results2).toBeInstanceOf(Object) + expect(results2.ids.length).toBe(1) +}) + +test('it should delete a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2', 'test3'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + const metadatas = [{ test: 'test1' }, { test: 'test2' }, { test: 'test3' }] + await collection.add({ ids, embeddings, metadatas }) + let count = await collection.count() + expect(count).toBe(3) + var resp = await collection.delete({ where: { 'test': 'test1' } }) + count = await collection.count() + expect(count).toBe(2) +}) + +test('wrong code returns an error', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2', 'test3'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + const metadatas = [{ test: 'test1' }, { test: 'test2' }, { test: 'test3' }] + await collection.add({ ids, embeddings, metadatas }) + // @ts-ignore - supposed to fail + const results = await collection.get({ where: { "test": { "$contains": "hello" } } }); + expect(results.error).toBeDefined() + expect(results.error).toContain("ValueError('Expected where operator") +}) diff --git a/clients/js/test/collection.client.test.ts b/clients/js/test/collection.client.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..0045067c7ea0fe398f1b68f951f6e992986beb40 --- /dev/null +++ b/clients/js/test/collection.client.test.ts @@ -0,0 +1,85 @@ +import { expect, test, beforeEach } from "@jest/globals"; +import chroma from "./initClient"; + +beforeEach(async () => { + await chroma.reset(); +}); + +test("it should list collections", async () => { + let collections = await chroma.listCollections(); + expect(collections).toBeDefined(); + expect(collections).toBeInstanceOf(Array); + expect(collections.length).toBe(0); + const collection = await chroma.createCollection({ name: "test" }); + collections = await chroma.listCollections(); + expect(collections.length).toBe(1); +}); + +test("it should create a collection", async () => { + const collection = await chroma.createCollection({ name: "test" }); + expect(collection).toBeDefined(); + expect(collection).toHaveProperty("name"); + expect(collection).toHaveProperty('id') + expect(collection.name).toBe("test"); + let collections = await chroma.listCollections(); + expect([{ name: "test", metadata: null, id: collection.id, database: "default_database", tenant: "default_tenant" }]).toEqual( + expect.arrayContaining(collections) + ); + expect([{ name: "test2", metadata: null }]).not.toEqual( + expect.arrayContaining(collections) + ); + + await chroma.reset(); + const collection2 = await chroma.createCollection({ name: "test2", metadata: { test: "test" } }); + expect(collection2).toBeDefined(); + expect(collection2).toHaveProperty("name"); + expect(collection2).toHaveProperty('id') + expect(collection2.name).toBe("test2"); + expect(collection2).toHaveProperty("metadata"); + expect(collection2.metadata).toHaveProperty("test"); + expect(collection2.metadata).toEqual({ test: "test" }); + let collections2 = await chroma.listCollections(); + expect([{ name: "test2", metadata: { test: "test" }, id: collection2.id, database: "default_database", tenant: "default_tenant" }]).toEqual( + expect.arrayContaining(collections2) + ); +}); + +test("it should get a collection", async () => { + const collection = await chroma.createCollection({ name: "test" }); + const collection2 = await chroma.getCollection({ name: "test" }); + expect(collection).toBeDefined(); + expect(collection2).toBeDefined(); + expect(collection).toHaveProperty("name"); + expect(collection2).toHaveProperty("name"); + expect(collection.name).toBe(collection2.name); +}); + +// test("it should get or create a collection", async () => { +// await chroma.createCollection("test"); + +// const collection2 = await chroma.getOrCreateCollection("test"); +// expect(collection2).toBeDefined(); +// expect(collection2).toHaveProperty("name"); +// expect(collection2.name).toBe("test"); + +// const collection3 = await chroma.getOrCreateCollection("test3"); +// expect(collection3).toBeDefined(); +// expect(collection3).toHaveProperty("name"); +// expect(collection3.name).toBe("test3"); +// }); + +test("it should delete a collection", async () => { + const collection = await chroma.createCollection({ name: "test" }); + let collections = await chroma.listCollections(); + expect(collections.length).toBe(1); + await chroma.deleteCollection({ name: "test" }); + collections = await chroma.listCollections(); + expect(collections.length).toBe(0); +}); + +// TODO: I want to test this, but I am not sure how to +// test('custom index params', async () => { +// throw new Error('not implemented') +// await chroma.reset() +// const collection = await chroma.createCollection('test', {"hnsw:space": "cosine"}) +// }) diff --git a/clients/js/test/collection.test.ts b/clients/js/test/collection.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..4e4919d49323d5b4081ccf01e01ec16fc17a14ce --- /dev/null +++ b/clients/js/test/collection.test.ts @@ -0,0 +1,69 @@ +import { expect, test } from "@jest/globals"; +import chroma from "./initClient"; + +test("it should modify collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + expect(collection.name).toBe("test"); + expect(collection.metadata).toBeUndefined(); + + await collection.modify({ name: "test2" }); + expect(collection.name).toBe("test2"); + expect(collection.metadata).toBeUndefined(); + + const collection2 = await chroma.getCollection({ name: "test2" }); + expect(collection2.name).toBe("test2"); + expect(collection2.metadata).toBeNull(); + + // test changing name and metadata independently + // and verify there are no side effects + const original_name = "test3"; + const new_name = "test4"; + const original_metadata = { test: "test" }; + const new_metadata = { test: "test2" }; + + const collection3 = await chroma.createCollection({ + name: original_name, + metadata: original_metadata + }); + expect(collection3.name).toBe(original_name); + expect(collection3.metadata).toEqual(original_metadata); + + await collection3.modify({ name: new_name }); + expect(collection3.name).toBe(new_name); + expect(collection3.metadata).toEqual(original_metadata); + + const collection4 = await chroma.getCollection({ name: new_name }); + expect(collection4.name).toBe(new_name); + expect(collection4.metadata).toEqual(original_metadata); + + await collection3.modify({ metadata: new_metadata }); + expect(collection3.name).toBe(new_name); + expect(collection3.metadata).toEqual(new_metadata); + + const collection5 = await chroma.getCollection({ name: new_name }); + expect(collection5.name).toBe(new_name); + expect(collection5.metadata).toEqual(new_metadata); +}); + +test("it should store metadata", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test", metadata: { test: "test" } }); + expect(collection.metadata).toEqual({ test: "test" }); + + // get the collection + const collection2 = await chroma.getCollection({ name: "test" }); + expect(collection2.metadata).toEqual({ test: "test" }); + + // get or create the collection + const collection3 = await chroma.getOrCreateCollection({ name: "test" }); + expect(collection3.metadata).toEqual({ test: "test" }); + + // modify + await collection3.modify({ metadata: { test: "test2" } }); + expect(collection3.metadata).toEqual({ test: "test2" }); + + // get it again + const collection4 = await chroma.getCollection({ name: "test" }); + expect(collection4.metadata).toEqual({ test: "test2" }); +}); diff --git a/clients/js/test/data.ts b/clients/js/test/data.ts new file mode 100644 index 0000000000000000000000000000000000000000..c1abf7186345a22a0008b08112e246ed48f7820c --- /dev/null +++ b/clients/js/test/data.ts @@ -0,0 +1,18 @@ +const IDS = ["test1", "test2", "test3"]; +const EMBEDDINGS = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1], +]; +const METADATAS = [ + { test: "test1", float_value: -2 }, + { test: "test2", float_value: 0 }, + { test: "test3", float_value: 2 }, +]; +const DOCUMENTS = [ + "This is a test", + "This is another test", + "This is a third test", +]; + +export { IDS, EMBEDDINGS, METADATAS, DOCUMENTS }; diff --git a/clients/js/test/delete.collection.test.ts b/clients/js/test/delete.collection.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..a192972b5993da19018014f992cf667af19fbe9a --- /dev/null +++ b/clients/js/test/delete.collection.test.ts @@ -0,0 +1,19 @@ +import { expect, test } from "@jest/globals"; +import chroma from "./initClient"; +import { EMBEDDINGS, IDS, METADATAS } from "./data"; + +test("it should delete a collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS }); + let count = await collection.count(); + expect(count).toBe(3); + var resp = await collection.delete({ where: { test: "test1" } }); + count = await collection.count(); + expect(count).toBe(2); + + var remainingEmbeddings = await collection.get(); + expect(["test2", "test3"]).toEqual( + expect.arrayContaining(remainingEmbeddings.ids) + ); +}); diff --git a/clients/js/test/get.collection.test.ts b/clients/js/test/get.collection.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..4ff88d208ff599bdd91193f64dc7b3dc1986523d --- /dev/null +++ b/clients/js/test/get.collection.test.ts @@ -0,0 +1,64 @@ +import { expect, test } from "@jest/globals"; +import chroma from "./initClient"; +import { DOCUMENTS, EMBEDDINGS, IDS, METADATAS } from "./data"; + +test("it should get a collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS }); + const results = await collection.get({ ids: ["test1"] }); + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(1); + expect(["test1"]).toEqual(expect.arrayContaining(results.ids)); + expect(["test2"]).not.toEqual(expect.arrayContaining(results.ids)); + + const results2 = await collection.get({ where: { test: "test1" } }); + expect(results2).toBeDefined(); + expect(results2).toBeInstanceOf(Object); + expect(results2.ids.length).toBe(1); + expect(["test1"]).toEqual(expect.arrayContaining(results2.ids)); +}); + +test("wrong code returns an error", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS }); + const results = await collection.get({ + where: { + //@ts-ignore supposed to fail + test: { $contains: "hello" }, + } + }); + expect(results.error).toBeDefined(); + expect(results.error).toContain("ValueError"); +}); + +test("it should get embedding with matching documents", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + const results2 = await collection.get({ whereDocument: { $contains: "This is a test" } }); + expect(results2).toBeDefined(); + expect(results2).toBeInstanceOf(Object); + expect(results2.ids.length).toBe(1); + expect(["test1"]).toEqual(expect.arrayContaining(results2.ids)); +}); + +test("test gt, lt, in a simple small way", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS }); + const items = await collection.get({ where: { float_value: { $gt: -1.4 } } }); + expect(items.ids.length).toBe(2); + expect(["test2", "test3"]).toEqual(expect.arrayContaining(items.ids)); +}); + + +test("it should throw an error if the collection does not exist", async () => { + await chroma.reset(); + + await expect( + async () => await chroma.getCollection({ name: "test" }) + ).rejects.toThrow(Error); +}); diff --git a/clients/js/test/initAdminClient.ts b/clients/js/test/initAdminClient.ts new file mode 100644 index 0000000000000000000000000000000000000000..06f420d3d9a5aa5ba9a42bda3e80818d2ae895ff --- /dev/null +++ b/clients/js/test/initAdminClient.ts @@ -0,0 +1,7 @@ +import { AdminClient } from "../src/AdminClient"; + +const PORT = process.env.PORT || "8000"; +const URL = "http://localhost:" + PORT; +const adminClient = new AdminClient({ path: URL }); + +export default adminClient; diff --git a/clients/js/test/initClient.ts b/clients/js/test/initClient.ts new file mode 100644 index 0000000000000000000000000000000000000000..38b32a59ac46f2d6f741f95b53b241ee1e282d2e --- /dev/null +++ b/clients/js/test/initClient.ts @@ -0,0 +1,8 @@ +import { ChromaClient } from "../src/ChromaClient"; + +const PORT = process.env.PORT || "8000"; +const URL = "http://localhost:" + PORT; + +const chroma = new ChromaClient({ path: URL }); + +export default chroma; diff --git a/clients/js/test/initClientWithAuth.ts b/clients/js/test/initClientWithAuth.ts new file mode 100644 index 0000000000000000000000000000000000000000..0fd55c4e7d2449e07c39eca5825ee867d85cb331 --- /dev/null +++ b/clients/js/test/initClientWithAuth.ts @@ -0,0 +1,16 @@ +import {ChromaClient} from "../src/ChromaClient"; +import { CloudClient } from "../src/CloudClient"; + +const PORT = process.env.PORT || "8000"; +const URL = "http://localhost:" + PORT; +export const chromaBasic = new ChromaClient({path: URL, auth: {provider: "basic", credentials: "admin:admin"}}); +export const chromaTokenDefault = new ChromaClient({path: URL, auth: {provider: "token", credentials: "test-token"}}); +export const chromaTokenBearer = new ChromaClient({ + path: URL, + auth: {provider: "token", credentials: "test-token", providerOptions: {headerType: "AUTHORIZATION"}} +}); +export const chromaTokenXToken = new ChromaClient({ + path: URL, + auth: {provider: "token", credentials: "test-token", providerOptions: {headerType: "X_CHROMA_TOKEN"}} +}); +export const cloudClient = new CloudClient({apiKey: "test-token", cloudPort: PORT, cloudHost: "http://localhost"}) diff --git a/clients/js/test/peek.collection.test.ts b/clients/js/test/peek.collection.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..70d7b5674e84c86bae2d7b6f827f6a3ac2248707 --- /dev/null +++ b/clients/js/test/peek.collection.test.ts @@ -0,0 +1,14 @@ +import { expect, test } from "@jest/globals"; +import chroma from "./initClient"; +import { IDS, EMBEDDINGS } from "./data"; + +test("it should peek a collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS }); + const results = await collection.peek({ limit: 2 }); + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(2); + expect(["test1", "test2"]).toEqual(expect.arrayContaining(results.ids)); +}); diff --git a/clients/js/test/query.collection.test.ts b/clients/js/test/query.collection.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..878ed0a71df3c7fb0f23da90e1d675f4d7e806fa --- /dev/null +++ b/clients/js/test/query.collection.test.ts @@ -0,0 +1,156 @@ +import { expect, test } from "@jest/globals"; +import chroma from "./initClient"; +import { IncludeEnum } from "../src/types"; +import { EMBEDDINGS, IDS, METADATAS, DOCUMENTS } from "./data"; + +import { IEmbeddingFunction } from "../src/embeddings/IEmbeddingFunction"; + +export class TestEmbeddingFunction implements IEmbeddingFunction { + + constructor() { } + + public async generate(texts: string[]): Promise { + let embeddings: number[][] = []; + for (let i = 0; i < texts.length; i += 1) { + embeddings.push([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + } + return embeddings; + } +} + +test("it should query a collection", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS }); + const results = await collection.query({ queryEmbeddings: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], nResults: 2 }); + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(["test1", "test2"]).toEqual(expect.arrayContaining(results.ids[0])); + expect(["test3"]).not.toEqual(expect.arrayContaining(results.ids[0])); +}); + +// test where_document +test("it should get embedding with matching documents", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + + const results = await collection.query({ + queryEmbeddings: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + nResults: 3, + whereDocument: { $contains: "This is a test" } + }); + + // it should only return doc1 + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(1); + expect(["test1"]).toEqual(expect.arrayContaining(results.ids[0])); + expect(["test2"]).not.toEqual(expect.arrayContaining(results.ids[0])); + expect(["This is a test"]).toEqual( + expect.arrayContaining(results.documents[0]) + ); + + const results2 = await collection.query({ + queryEmbeddings: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + nResults: 3, + whereDocument: { $contains: "This is a test" }, + include: [IncludeEnum.Embeddings] + }); + + // expect(results2.embeddings[0][0]).toBeInstanceOf(Array); + expect(results2.embeddings![0].length).toBe(1); + expect(results2.embeddings![0][0]).toEqual([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); +}); + + +// test queryTexts +test("it should query a collection with text", async () => { + await chroma.reset(); + let embeddingFunction = new TestEmbeddingFunction(); + const collection = await chroma.createCollection({ name: "test", embeddingFunction: embeddingFunction }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + + const results = await collection.query({ + queryTexts: ["test"], + nResults: 3, + whereDocument: { $contains: "This is a test" } + }); + + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(1); + expect(["test1"]).toEqual(expect.arrayContaining(results.ids[0])); + expect(["test2"]).not.toEqual(expect.arrayContaining(results.ids[0])); + expect(["This is a test"]).toEqual( + expect.arrayContaining(results.documents[0]) + ); +}) + + +test("it should query a collection with text and where", async () => { + await chroma.reset(); + let embeddingFunction = new TestEmbeddingFunction(); + const collection = await chroma.createCollection({ name: "test", embeddingFunction: embeddingFunction }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + + const results = await collection.query({ + queryTexts: ["test"], + nResults: 3, + where: { "float_value" : 2 } + }); + + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(1); + expect(["test3"]).toEqual(expect.arrayContaining(results.ids[0])); + expect(["test2"]).not.toEqual(expect.arrayContaining(results.ids[0])); + expect(["This is a third test"]).toEqual( + expect.arrayContaining(results.documents[0]) + ); +}) + + +test("it should query a collection with text and where in", async () => { + await chroma.reset(); + let embeddingFunction = new TestEmbeddingFunction(); + const collection = await chroma.createCollection({ name: "test", embeddingFunction: embeddingFunction }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + + const results = await collection.query({ + queryTexts: ["test"], + nResults: 3, + where: { "float_value" : { '$in': [2,5,10] }} + }); + + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(1); + expect(["test3"]).toEqual(expect.arrayContaining(results.ids[0])); + expect(["test2"]).not.toEqual(expect.arrayContaining(results.ids[0])); + expect(["This is a third test"]).toEqual( + expect.arrayContaining(results.documents[0]) + ); +}) + +test("it should query a collection with text and where nin", async () => { + await chroma.reset(); + let embeddingFunction = new TestEmbeddingFunction(); + const collection = await chroma.createCollection({ name: "test", embeddingFunction: embeddingFunction }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + + const results = await collection.query({ + queryTexts: ["test"], + nResults: 3, + where: { "float_value" : { '$nin': [-2,0] }} + }); + + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.ids.length).toBe(1); + expect(["test3"]).toEqual(expect.arrayContaining(results.ids[0])); + expect(["test2"]).not.toEqual(expect.arrayContaining(results.ids[0])); + expect(["This is a third test"]).toEqual( + expect.arrayContaining(results.documents[0]) + ); +}) diff --git a/clients/js/test/update.collection.test.ts b/clients/js/test/update.collection.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..e96f21d5b06b2539a6ad5f3f960493c19739f06d --- /dev/null +++ b/clients/js/test/update.collection.test.ts @@ -0,0 +1,67 @@ +import { expect, test } from "@jest/globals"; +import chroma from "./initClient"; +import { IncludeEnum } from "../src/types"; +import { IDS, DOCUMENTS, EMBEDDINGS, METADATAS } from "./data"; + +test("it should get embedding with matching documents", async () => { + await chroma.reset(); + const collection = await chroma.createCollection({ name: "test" }); + await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + + const results = await collection.get({ + ids: ["test1"], + include: [ + IncludeEnum.Embeddings, + IncludeEnum.Metadatas, + IncludeEnum.Documents, + ] + }); + expect(results).toBeDefined(); + expect(results).toBeInstanceOf(Object); + expect(results.embeddings![0]).toEqual([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]); + + await collection.update({ + ids: ["test1"], + embeddings: [[1, 2, 3, 4, 5, 6, 7, 8, 9, 11]], + metadatas: [{ test: "test1new" }], + documents: ["doc1new"] + }); + + const results2 = await collection.get({ + ids: ["test1"], + include: [ + IncludeEnum.Embeddings, + IncludeEnum.Metadatas, + IncludeEnum.Documents, + ] + }); + expect(results2).toBeDefined(); + expect(results2).toBeInstanceOf(Object); + expect(results2.embeddings![0]).toEqual([1, 2, 3, 4, 5, 6, 7, 8, 9, 11]); + expect(results2.metadatas[0]).toEqual({ test: "test1new", float_value: -2 }); + expect(results2.documents[0]).toEqual("doc1new"); +}); + +// this currently fails +// test("it should update metadata or documents to array of Nones", async () => { +// await chroma.reset(); +// const collection = await chroma.createCollection({ name: "test" }); +// await collection.add({ ids: IDS, embeddings: EMBEDDINGS, metadatas: METADATAS, documents: DOCUMENTS }); + +// await collection.update({ +// ids: ["test1"], +// metadatas: [undefined], +// }); + +// const results3 = await collection.get({ +// ids: ["test1"], +// include: [ +// IncludeEnum.Embeddings, +// IncludeEnum.Metadatas, +// IncludeEnum.Documents, +// ] +// }); +// expect(results3).toBeDefined(); +// expect(results3).toBeInstanceOf(Object); +// expect(results3.metadatas[0]).toEqual({}); +// }); diff --git a/clients/js/test/upsert.collections.test.ts b/clients/js/test/upsert.collections.test.ts new file mode 100644 index 0000000000000000000000000000000000000000..9ce00820e2d3992cdd580b741ea8759cc5645c65 --- /dev/null +++ b/clients/js/test/upsert.collections.test.ts @@ -0,0 +1,27 @@ +import { expect, test } from '@jest/globals'; +import chroma from './initClient' + + +test('it should upsert embeddings to a collection', async () => { + await chroma.reset() + const collection = await chroma.createCollection({ name: "test" }); + const ids = ['test1', 'test2'] + const embeddings = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] + ] + await collection.add({ ids, embeddings }) + const count = await collection.count() + expect(count).toBe(2) + + const ids2 = ["test2", "test3"] + const embeddings2 = [ + [1, 2, 3, 4, 5, 6, 7, 8, 9, 15], + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], + ] + + await collection.upsert({ ids: ids2, embeddings: embeddings2 }) + + const count2 = await collection.count() + expect(count2).toBe(3) +}) diff --git a/clients/js/tsconfig.json b/clients/js/tsconfig.json new file mode 100644 index 0000000000000000000000000000000000000000..632127ed70982566fe6b6c032a400e4f6d78f42e --- /dev/null +++ b/clients/js/tsconfig.json @@ -0,0 +1,18 @@ +{ + "include": [ + "src" + ], + "compilerOptions": { + "declaration": true, + "module": "ESNext", + "lib": ["ES2017", "DOM"], + "outDir": "dist/main", + "sourceMap": true, + "target": "ES2017", + "strict": true, + "esModuleInterop": true, + "moduleResolution": "Node", + "forceConsistentCasingInFileNames": true, + "stripInternal": true + } +} diff --git a/clients/js/tsup.config.ts b/clients/js/tsup.config.ts new file mode 100644 index 0000000000000000000000000000000000000000..4b0cd8e264eeb5d61d99ec88c870136300269cb3 --- /dev/null +++ b/clients/js/tsup.config.ts @@ -0,0 +1,32 @@ +import { defineConfig, Options } from 'tsup' +import fs from 'fs' + +export default defineConfig((options: Options) => { + const commonOptions: Partial = { + entry: { + chromadb: 'src/index.ts' + }, + sourcemap: true, + dts: true, + ...options + } + + return [ + { + ...commonOptions, + format: ['esm'], + outExtension: () => ({ js: '.mjs' }), + clean: true, + async onSuccess() { + // Support Webpack 4 by pointing `"module"` to a file with a `.js` extension + fs.copyFileSync('dist/chromadb.mjs', 'dist/chromadb.legacy-esm.js') + } + }, + { + ...commonOptions, + format: 'cjs', + outDir: './dist/cjs/', + outExtension: () => ({ js: '.cjs' }) + } + ] +}) diff --git a/clients/python/README.md b/clients/python/README.md new file mode 100644 index 0000000000000000000000000000000000000000..c5e592bc40de825fd619131c18061d854a665b0f --- /dev/null +++ b/clients/python/README.md @@ -0,0 +1,40 @@ +

+ Chroma logo +

+ +

+ Chroma - the open-source embedding database.
+ This package is for the the Python HTTP client-only library for Chroma. This client connects to the Chroma Server. If that it not what you are looking for, you might want to check out the full library. +

+ + +```bash +pip install chromadb-client # python http-client only library +``` + +To connect to your server and perform operations using the client only library, you can do the following: + +```python +import chromadb +# Example setup of the client to connect to your chroma server +client = chromadb.HttpClient(host="localhost", port=8000) + +collection = client.create_collection("all-my-documents") + +collection.add( + documents=["This is document1", "This is document2"], + metadatas=[{"source": "notion"}, {"source": "google-docs"}], # filter on these! + ids=["doc1", "doc2"], # unique for each doc + embeddings = [[1.2, 2.1, ...], [1.2, 2.1, ...]] +) + +results = collection.query( + query_texts=["This is a query document"], + n_results=2, + # where={"metadata_field": "is_equal_to_this"}, # optional filter + # where_document={"$contains":"search_string"} # optional filter +) +``` +## License + +[Apache 2.0](./LICENSE) diff --git a/clients/python/build_python_thin_client.sh b/clients/python/build_python_thin_client.sh new file mode 100755 index 0000000000000000000000000000000000000000..66e197f22485db88c7b0f92c4adc5e88b62574f8 --- /dev/null +++ b/clients/python/build_python_thin_client.sh @@ -0,0 +1,46 @@ +#!/usr/bin/env bash + +# Define the paths to the existing and new toml files +existing_toml="pyproject.toml" +thin_client_toml="clients/python/pyproject.toml" + +# Define the path to the thin client flag script +is_thin_client_py="clients/python/is_thin_client.py" +is_thin_client_target="chromadb/is_thin_client.py" + +# Define the path to the existing readme and new readme for packaging +existing_readme="README.md" +thin_client_readme="clients/python/README.md" + +# Stage the existing toml file +staged_toml="staged_pyproject.toml" +mv "$existing_toml" "$staged_toml" + +# Stage the existing readme file +staged_readme="staged_README.md" +mv "$existing_readme" "$staged_readme" + +function cleanup { + # Teardown: Remove the new toml file and put the old one back + rm "$existing_toml" + mv "$staged_toml" "$existing_toml" + + rm "$is_thin_client_target" + + # Teardown: Remove the new readme file and put the old one back + rm "$existing_readme" + mv "$staged_readme" "$existing_readme" +} + +trap cleanup EXIT + +# Copy the new toml file in place +cp "$thin_client_toml" "$existing_toml" + +# Copy the thin client flag script in place +cp "$is_thin_client_py" "$is_thin_client_target" + +# Copy the new readme file in place +cp "$thin_client_readme" "$existing_readme" + +python -m build diff --git a/clients/python/integration-test.sh b/clients/python/integration-test.sh new file mode 100755 index 0000000000000000000000000000000000000000..e667f5912373cdc70d19436e0dcf8222b3b0b024 --- /dev/null +++ b/clients/python/integration-test.sh @@ -0,0 +1,31 @@ +#!/usr/bin/env bash + +set -e + +export CHROMA_PORT=8000 + +# Define the path to the thin client flag script +is_thin_client_py="clients/python/is_thin_client.py" +is_thin_client_target="chromadb/is_thin_client.py" + +function cleanup { + rm "$is_thin_client_target" + docker compose -f docker-compose.test.yml down --rmi local --volumes +} + +trap cleanup EXIT + +docker compose -f docker-compose.test.yml up --build -d + +export CHROMA_INTEGRATION_TEST_ONLY=1 +export CHROMA_API_IMPL=chromadb.api.fastapi.FastAPI +export CHROMA_SERVER_HOST=localhost +export CHROMA_SERVER_HTTP_PORT=8000 +export CHROMA_SERVER_NOFILE=65535 + +echo testing: python -m pytest "$@" + +# Copy the thin client flag script in place, uvicorn takes a while to startup inside docker +sleep 5 +cp "$is_thin_client_py" "$is_thin_client_target" +python -m pytest 'chromadb/test/property/' --ignore-glob 'chromadb/test/property/*persist.py' diff --git a/clients/python/is_thin_client.py b/clients/python/is_thin_client.py new file mode 100644 index 0000000000000000000000000000000000000000..e62e86aee16a503e7d038752c366502a9f3029f6 --- /dev/null +++ b/clients/python/is_thin_client.py @@ -0,0 +1 @@ +is_thin_client = True diff --git a/clients/python/pyproject.toml b/clients/python/pyproject.toml new file mode 100644 index 0000000000000000000000000000000000000000..b62c002d095c50c732855666ac96fcc08d936dce --- /dev/null +++ b/clients/python/pyproject.toml @@ -0,0 +1,51 @@ +[project] +name = "chromadb-client" +dynamic = ["version"] + +authors = [ + { name="Jeff Huber", email="jeff@trychroma.com" }, + { name="Anton Troynikov", email="anton@trychroma.com" } +] +description = "Chroma Client." +readme = "README.md" +requires-python = ">=3.8" +classifiers = [ + "Programming Language :: Python :: 3", + "License :: OSI Approved :: Apache Software License", + "Operating System :: OS Independent", +] +dependencies = [ + 'numpy >= 1.22.5', + 'opentelemetry-api>=1.2.0', + 'opentelemetry-exporter-otlp-proto-grpc>=1.2.0', + 'opentelemetry-sdk>=1.2.0', + 'overrides >= 7.3.1', + 'posthog >= 2.4.0', + 'pydantic>=1.9', + 'requests >= 2.28', + 'typing_extensions >= 4.5.0', + 'tenacity>=8.2.3', + 'PyYAML>=6.0.0', +] + +[tool.black] +line-length = 88 +required-version = "23.3.0" # Black will refuse to run if it's not this version. +target-version = ['py38', 'py39', 'py310', 'py311'] + +[tool.pytest.ini_options] +pythonpath = ["."] + +[project.urls] +"Homepage" = "https://github.com/chroma-core/chroma" +"Bug Tracker" = "https://github.com/chroma-core/chroma/issues" + +[build-system] +requires = ["setuptools>=61.0", "setuptools_scm[toml]>=6.2"] +build-backend = "setuptools.build_meta" + +[tool.setuptools_scm] +local_scheme="no-local-version" + +[tool.setuptools] +packages = ["chromadb"] diff --git a/clients/python/requirements.txt b/clients/python/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..1242bf7d7e0fb35c7d0f9405681cc72344b15d6b --- /dev/null +++ b/clients/python/requirements.txt @@ -0,0 +1,11 @@ +numpy >= 1.22.5 +opentelemetry-api>=1.2.0 +opentelemetry-exporter-otlp-proto-grpc>=1.2.0 +opentelemetry-sdk>=1.2.0 +overrides >= 7.3.1 +posthog >= 2.4.0 +pydantic>=1.9 +PyYAML>=6.0.0 +requests >= 2.28 +tenacity>=8.2.3 +typing_extensions >= 4.5.0 diff --git a/clients/python/requirements_dev.txt b/clients/python/requirements_dev.txt new file mode 100644 index 0000000000000000000000000000000000000000..c00e219ccd7502d5989cf3b7e31f08eec2ed5308 --- /dev/null +++ b/clients/python/requirements_dev.txt @@ -0,0 +1,8 @@ +build>=1.0.3 +fastapi>=0.95.2 +hypothesis +hypothesis[numpy] +opentelemetry-instrumentation-fastapi>=0.41b0 +pypika==0.48.9 +pytest +uvicorn[standard]==0.18.3 diff --git a/docker-compose.server.example.yml b/docker-compose.server.example.yml new file mode 100644 index 0000000000000000000000000000000000000000..aa5c288ae717156eac1f2cc60903d4c9b4b86aaa --- /dev/null +++ b/docker-compose.server.example.yml @@ -0,0 +1,22 @@ +version: '3.9' + +networks: + net: + driver: bridge +services: + server: + image: ghcr.io/chroma-core/chroma:latest + environment: + - IS_PERSISTENT=TRUE + volumes: + # Default configuration for persist_directory in chromadb/config.py + # Currently it's located in "/chroma/chroma/" + - chroma-data:/chroma/chroma/ + ports: + - 8000:8000 + networks: + - net + +volumes: + chroma-data: + driver: local diff --git a/docker-compose.test-auth.yml b/docker-compose.test-auth.yml new file mode 100644 index 0000000000000000000000000000000000000000..d3297b5a04fc1c614fb1cf07346cfbee379477ec --- /dev/null +++ b/docker-compose.test-auth.yml @@ -0,0 +1,31 @@ +version: '3.9' + +networks: + test_net: + driver: bridge + +services: + test_server: + build: + context: . + dockerfile: Dockerfile + volumes: + - chroma-data:/chroma/chroma + command: "--workers 1 --host 0.0.0.0 --port 8000 --proxy-headers --log-config chromadb/log_config.yml --timeout-keep-alive 30" + environment: + - ANONYMIZED_TELEMETRY=False + - ALLOW_RESET=True + - IS_PERSISTENT=TRUE + - CHROMA_SERVER_AUTH_CREDENTIALS_FILE=${CHROMA_SERVER_AUTH_CREDENTIALS_FILE} + - CHROMA_SERVER_AUTH_CREDENTIALS=${CHROMA_SERVER_AUTH_CREDENTIALS} + - CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=${CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER} + - CHROMA_SERVER_AUTH_PROVIDER=${CHROMA_SERVER_AUTH_PROVIDER} + - CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER=${CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER} + ports: + - ${CHROMA_PORT}:8000 + networks: + - test_net + +volumes: + chroma-data: + driver: local diff --git a/docker-compose.test.yml b/docker-compose.test.yml new file mode 100644 index 0000000000000000000000000000000000000000..4384bad1982aa01fdec0382a1386d01f4e81b7d7 --- /dev/null +++ b/docker-compose.test.yml @@ -0,0 +1,26 @@ +version: '3.9' + +networks: + test_net: + driver: bridge + +services: + test_server: + build: + context: . + dockerfile: Dockerfile + volumes: + - chroma-data:/chroma/chroma + command: "--workers 1 --host 0.0.0.0 --port 8000 --proxy-headers --log-config chromadb/log_config.yml --timeout-keep-alive 30" + environment: + - ANONYMIZED_TELEMETRY=False + - ALLOW_RESET=True + - IS_PERSISTENT=TRUE + ports: + - ${CHROMA_PORT}:8000 + networks: + - test_net + +volumes: + chroma-data: + driver: local diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000000000000000000000000000000000000..20d096569070548e66f4d22a86e523eabb9e6a64 --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,39 @@ +version: '3.9' + +networks: + net: + driver: bridge + +services: + server: + image: server + build: + context: . + dockerfile: Dockerfile + volumes: + # Be aware that indexed data are located in "/chroma/chroma/" + # Default configuration for persist_directory in chromadb/config.py + # Read more about deployments: https://docs.trychroma.com/deployment + - chroma-data:/chroma/chroma + command: "--workers 1 --host 0.0.0.0 --port 8000 --proxy-headers --log-config chromadb/log_config.yml --timeout-keep-alive 30" + environment: + - IS_PERSISTENT=TRUE + - CHROMA_SERVER_AUTH_PROVIDER=${CHROMA_SERVER_AUTH_PROVIDER} + - CHROMA_SERVER_AUTH_CREDENTIALS_FILE=${CHROMA_SERVER_AUTH_CREDENTIALS_FILE} + - CHROMA_SERVER_AUTH_CREDENTIALS=${CHROMA_SERVER_AUTH_CREDENTIALS} + - CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=${CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER} + - CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER=${CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER} + - PERSIST_DIRECTORY=${PERSIST_DIRECTORY:-/chroma/chroma} + - CHROMA_OTEL_EXPORTER_ENDPOINT=${CHROMA_OTEL_EXPORTER_ENDPOINT} + - CHROMA_OTEL_EXPORTER_HEADERS=${CHROMA_OTEL_EXPORTER_HEADERS} + - CHROMA_OTEL_SERVICE_NAME=${CHROMA_OTEL_SERVICE_NAME} + - CHROMA_OTEL_GRANULARITY=${CHROMA_OTEL_GRANULARITY} + - CHROMA_SERVER_NOFILE=${CHROMA_SERVER_NOFILE} + ports: + - 8000:8000 + networks: + - net + +volumes: + chroma-data: + driver: local diff --git a/docs/CIP_2_Auth_Providers_Proposal.md b/docs/CIP_2_Auth_Providers_Proposal.md new file mode 100644 index 0000000000000000000000000000000000000000..6bc437a1e9423806e5b02ce99436196b45ee5f10 --- /dev/null +++ b/docs/CIP_2_Auth_Providers_Proposal.md @@ -0,0 +1,190 @@ +# CIP-2: Auth Providers Proposal + +## Status + +Current Status: `Accepted` + +## **Motivation** + +Currently, Chroma does not provide any authentication mechanism. This CIP proposes to +add authentication abstractions and basic authentication mechanisms to Chroma. + +There are intrinsic and extrinsic motivations for this CIP. The intrinsic motivation +is to provide a secure way to access Chroma as adoption grows and the team is gearing up to release a cloud offering. +The extrinsic motivation is driven by the community which is deploying Chroma in both public and private clouds and +in test and production environments. The community has expressed the need for authentication and authorization. + +> Observation: We consider the Auth to be applicable to client-server mode. + +## **Public Interfaces** + +Changes to the public interface are related to the `Settings` class where we introduce new optional attributes to +control server and client-side auth providers. + +## **Proposed Changes** + +We propose two abstraction groups, one for the server-side and another for the client-side. In +addition we also introduce a FastAPI/startlette middleware adapter which will allow using the server-side abstractions +in the context of FastAPI. For client-side we rely on `requests` + +### Architecture Overview + +Architecture Overview: + +![cip-2-arch.png](assets/cip-2-arch.png) + +Request Sequence: + +![cip-2-seq.png](assets/cip-2-seq.png) + +### Constraints + +This section provides the architectural constraints for the authentication framework. The constraints are set of +restrictions we impose to make the design simpler and more robust. + +- There must be at most one active client-side auth provider +- There must be at most one active client-side credentials provider +- There must be at most one active server-side auth provider +- There must be at most one active server-side auth configuration provider +- There must be at most one active server-side auth credentials provider + +### Core Concepts + +- Auth Provider - an abstraction that provides authentication functionality for either client or server-side. The + provider is responsible for validating client credentials using (if available) configuration and credentials + providers. The auth provider is also responsible for carrying the Chroma-leg of any authentication flow. +- Auth Configuration Provider - an abstraction that provides configuration for auth providers. The configuration can be + loaded from a file, env vars or programmatically. The configuration is used for validating and/or accessing user + credentials. Examples: secret key for JWT token based auth, DB URL for DB based auth, etc. Depending on sensitivity of + the information stored in the configuration, the provider should implement the necessary interfaces to access such + information in a secure way. +- Auth Credentials Provider - an abstraction that provides credentials for auth providers. The credentials can be + loaded from a file, env vars or programmatically. The credentials are used for validating client-side credentials (for + sever-side auth) and retrieving or generating client-side credentials (for client-side auth). + +#### Abstractions + +##### Server-Side + +We suggest multiple abstractions on the server-side to allow for easy integration with different auth providers. +We suggest the following abstractions: + +> Note: All abstractions are defined under `chromadb.auth` package + +- `ServerAuthProvider` - this is the base server auth provider abstraction that allows any server implementation of + Chroma to support variety of auth providers. The main responsibility of the auth provider is to orchestrate the auth + flow by gluing together the auth configuration and credentials providers. +- `ChromaAuthMiddleware` - The auth middleware is effectively an adapter responsible for providing server specific + implementation of the auth middleware. This includes three general types of operations - forwarding authentication to + the auth provider, instrumenting the server if needed to support a specific auth flow, ignore certain + actions/operations (e.g. in REST this would be verb+path) that should not be authenticated. +- `ServerAuthenticationRequest` - An abstraction for querying for authentication data from server specific + implementation. +- `ServerAuthenticationResponse` - An abstraction for returning authentication data to server specific implementation. +- `ServerAuthConfigurationProvider` - this is the base abstraction for auth configuration providers. The provider is + responsible for loading auth configuration from a file, env vars or programmatically. +- `AbstractCredentials` - base abstraction for credentials encapsulation from server to Auth Credentials Provider. +- `ServerAuthCredentialsProvider` - this is the base abstraction for auth credentials providers. The provider is + responsible for verifying client credentials. + +##### Client-Side + +We suggest multiple abstractions on the client-side to allow for easy integration with different auth providers. + +- `ClientAuthProvider` - this is the base client auth provider abstraction that allows any client implementation of + Chroma to support variety of auth providers. The main responsibility of the auth provider is to orchestrate the auth + flow by gluing together the auth configuration and credentials providers, and any possible auth workflows (e.g. OAuth) +- `ClientAuthConfigurationProvider` - this is the base abstraction for auth configuration providers. The provider is + responsible for loading auth configuration from a file, env vars or programmatically. +- `ClientAuthCredentialsProvider` - this is the base abstraction for auth credentials providers. The provider is + responsible for verifying client credentials. +- `AbstractCredentials` - base abstraction for credentials encapsulation from client to Auth Credentials Provider. +- `ClientAuthProtocolAdapter` - this is an abstraction that allows for client-side auth providers to communicate with + backends using variety of protocols and libraries (e.g. `requests`, `gRPC` etc). The adapter is responsible for + translating the auth requests to generated by the credentials provider to a protocol specific message. + +#### Workflows + +##### Server-Side + +![cip-2-server-side-wf.png](assets/cip-2-server-side-wf.png) + +##### Client-Side + +![cip-2-client-side-wf.png](assets/cip-2-client-side-wf.png) + +### Configuration + +#### Server-side + +TBD + +#### Client-side + + + +### Reasoning + +- Server-side abstraction - it is very useful as the intention is to support a variety of auth providers. +- Client-side abstraction - similar reasoning but from client's perspective. It will allow for both standard and + non-standard auth provider plugins to be added without further impacting the client side +- Backend (fastAPI) adapter - this is a backend-specific way of loading server-side auth provider plugins. It will also + serve as a template/blueprint when it comes to introducing the auth plugins to another backend framework (e.g. Flask) + +We also propose that each auth provider on either side must be configurable via three main methods depending on +developer preference: + +- File-base - a configuration file that provides the requisite config and credentials (recommended for production) +- Env - configuration through environment variables (this can also apply for the file-based config, which can be + specified in env var) +- Programmatically - provide requisite configuration through CLI or directly in code (it is left for the developer to + decide how such configuration is loaded and made available to the auth provider) - this is possibly the least secure + and should be used for testing + +The intention is to start with two minimal but useful Auth providers: + +- Basic Auth - base64 encoded user and password credentials. The credentials will be static in nature and defined via + auth provider config +- Token - A simple static token implementation + +Both of the above providers will rely on the `Authorization` header to achieve their functionality. + +> Both initial providers are there to help introduce a bear minimum security but are not recommended for production use + +Further work: + +- Introduction of JWT and mTLS auth providers +- API Keys +- Chroma managed user store - this would be similar to what standard DBMS’ are doing today - maintain a table with users + and salted password hashes +- K8s RBAC integration (for cloud-native deployments) +- GCP service accounts? +- SPIFFE and SPIRE integrations +- Go and Java client-side auth providers (for other impl like Rust and Ruby, we need to discuss with respective + maintainers) + +> Note: this CIP intentionally does not tackle authZ but acknowledges that authN and authZ must work in tandem in future +> releases + +## **Compatibility, Deprecation, and Migration Plan** + +This change, introducing a pluggable auth framework is not impacting compatibility of existing deployments and users can +upgrade and use the new framework without the need for migration. + +No deprecations. + +## **Test Plan** + +We will introduce a new set of tests to verify both client and server-side auth providers. + +## **Rejected Alternatives** + +We have considered direct middleware Auth or existing third-party libraries for FastAPI integration with auth providers, +but that will create a dependency for Chroma on FastAPI itself. + +We have also considered using OAuth 2.0 or OIDC however the challenge there is that both of these protocols are +generally intended for User (human) auth whereas in our case we have a system-to-system auth. That said there still +might be room for either of these protocols, but further more in-depth use case analysis is required. + +Relying entirely on external providers, while this is possible not providing out-of-the-box integrated auth capabilities +is a non-starter for many enterprise customers. diff --git a/docs/CIP_4_In_Nin_Metadata_Filters.md b/docs/CIP_4_In_Nin_Metadata_Filters.md new file mode 100644 index 0000000000000000000000000000000000000000..e9a0911e69e65bf1a18f478178fb38d790f8b5f9 --- /dev/null +++ b/docs/CIP_4_In_Nin_Metadata_Filters.md @@ -0,0 +1,61 @@ +# CIP-4: In and Not In Metadata Filters Proposal + +## Status + +Current Status: `Under Discussion` + +## **Motivation** + +Currently, Chroma does not provide a way to filter metadata through `in` and `not in`. This appears to be a frequent ask +from community members. + +## **Public Interfaces** + +The changes will affect the following public interfaces: + +- `Where` and `OperatorExpression` + classes - https://github.com/chroma-core/chroma/blob/48700dd07f14bcfd8b206dc3b2e2795d5531094d/chromadb/types.py#L125-L129 +- `collection.get()` +- `collection.query()` + +## **Proposed Changes** + +We suggest the introduction of two new operators `$in` and `$nin` that will be used to filter metadata. We call these +operators `InclusionExclusionOperator`. + +We suggest the following new operator definition: + +```python +InclusionExclusionOperator = Union[Literal["$in"], Literal["$nin"]] +``` + +Additionally, we suggest that those operators are added to `OperatorExpression` for seamless integration with +existing `Where` semantics: + +```python +OperatorExpression = Union[ + Dict[Union[WhereOperator, LogicalOperator], LiteralValue], + Dict[InclusionExclusionOperator, List[LiteralValue]], +] +``` + +An example of a query using the new operators would be: + +```python +collection.query(query_texts=query, + where={"$and": [{"author": {'$in': ['john', 'jill']}}, {"article_type": {"$eq": "blog"}}]}, + n_results=3) +``` + +## **Compatibility, Deprecation, and Migration Plan** + +The change is compatible with existing release 0.4.x. + +## **Test Plan** + +Property tests will be updated to ensure boundary conditions are covered as well as interoperability with existing `Where` +operators. + +## **Rejected Alternatives** + +N/A diff --git a/docs/CIP_5_Large_Batch_Handling_Improvements.md b/docs/CIP_5_Large_Batch_Handling_Improvements.md new file mode 100644 index 0000000000000000000000000000000000000000..9b03d080f0f85849ba841661290ab85c45e677f6 --- /dev/null +++ b/docs/CIP_5_Large_Batch_Handling_Improvements.md @@ -0,0 +1,59 @@ +# CIP-5: Large Batch Handling Improvements Proposal + +## Status + +Current Status: `Under Discussion` + +## **Motivation** + +As users start putting Chroma in its paces and storing ever-increasing datasets, we must ensure that errors +related to significant and potentially expensive batches are handled gracefully. This CIP proposes to add a new +setting, `max_batch_size` API, on the local segment API and use it to split large batches into smaller ones. + +## **Public Interfaces** + +The following interfaces are impacted: + +- New Server API endpoint - `/pre-flight-checks` +- New `max_batch_size` property on the `API` interface +- Updated `_add`, `_update` and `_upsert` methods on `chromadb.api.segment.SegmentAPI` +- Updated `_add`, `_update` and `_upsert` methods on `chromadb.api.fastapi.FastAPI` +- New utility library `batch_utils.py` +- New exception raised when batch size exceeds `max_batch_size` + +## **Proposed Changes** + +We propose the following changes: + +- The new `max_batch_size` property is now available in the `API` interface. The property relies on the + underlying `Producer` class + to fetch the actual value. The property will be implemented by both `chromadb.api.segment.SegmentAPI` + and `chromadb.api.fastapi.FastAPI` +- `chromadb.api.segment.SegmentAPI` will implement the `max_batch_size` property by fetching the value from the + `Producer` class. +- `chromadb.api.fastapi.FastAPI` will implement the `max_batch_size` by fetching it from a new `/pre-flight-checks` + endpoint on the Server. +- New `/pre-flight-checks` endpoint on the Server will return a dictionary with pre-flight checks the client must + fulfil to integrate with the server side. For now, we propose using this only for `max_batch_size`, but we can + add more checks in the future. The pre-flight checks will be only fetched once per client and cached for the duration + of the client's lifetime. +- Updated `_add`, `_update` and `_upsert` method on `chromadb.api.segment.SegmentAPI` to validate batch size. +- Updated `_add`, `_update` and `_upsert` method on `chromadb.api.fastapi.FastAPI` to validate batch size (client-side + validation) +- New utility library `batch_utils.py` will contain the logic for splitting batches into smaller ones. + +## **Compatibility, Deprecation, and Migration Plan** + +The change will be fully compatible with existing implementations. The changes will be transparent to the user. + +## **Test Plan** + +New tests: + +- Batch splitting tests for `chromadb.api.segment.SegmentAPI` +- Batch splitting tests for `chromadb.api.fastapi.FastAPI` +- Tests for `/pre-flight-checks` endpoint + +## **Rejected Alternatives** + +N/A diff --git a/docs/CIP_6_OpenTelemetry_Monitoring.md b/docs/CIP_6_OpenTelemetry_Monitoring.md new file mode 100644 index 0000000000000000000000000000000000000000..4c36e3b49e8d088fa119f691bcb10e91d611f035 --- /dev/null +++ b/docs/CIP_6_OpenTelemetry_Monitoring.md @@ -0,0 +1,41 @@ +# CIP 6: OpenTelemetry Monitoring + +## **Status** + +Current status: `Under Discussion` + +## **Motivation** + +Chroma currently has very little observability, only offering basic logging. Using Chroma in a high-performance production context requires the ability to understand how Chroma is behaving and responding to requests. + +## **Public Interfaces** + +The changes will affect the following: + +- Logging output +- Several new CLI flags + +## **Proposed Changes** + +We propose to instrument Chroma with [OpenTelemetry](https://opentelemetry.io/docs/instrumentation/python/) (OTel), the most prevalent open-source observability standard. OTel's Python libraries are considered stable for traces and metrics. We will create several layers of observability, configurable with command-line flags. + +- Chroma's default behavior will remain the same: events will be logged to the console with configurable severity levels. +- We will add a flag, `--opentelemetry-mode={api, sdk}` to instruct Chroma to export OTel data in either [API or SDK mode](https://stackoverflow.com/questions/72963553/opentelemetry-api-vs-sdk). +- We will add another flag, `--opentelemtry-detail={partial, full}`, to specify the level of detail desired from OTel. + - With `partial` detail, Chroma's top-level API calls will produce a single span. This mode is suitable for end-users of Chroma who are not intimately familiar with its operation but use it as part of their production system. + - `full` detail will emit spans for Chroma's sub-operations, enabling Chroma maintainers to monitor performance and diagnose issues. +- For now Chroma's OTel integrations will need to be specified with environment variables. As the [OTel file configuration project](https://github.com/MrAlias/otel-schema/pull/44) matures we will integrate support for file-based OTel configuration. + +## **Compatibility, Deprecation, and Migration Plan** + +This change adds no new default-on functionality. + +## **Test Plan** + +Observability logic and output will be tested on both single-node and distributed Chroma to confirm that metrics are exported properly and traces correctly identify parent spans across function and service boundaries. + +## **Rejected Alternatives** + +### Prometheus metrics + +Prometheus metrics offer similar OSS functionality to OTel. However the Prometheus standard is older and belongs to a single open-source project; OTel is designed for long-term cross-compatibility between *all* observability backends. As such, OTel output can easily be ingested by Prometheus users so there is no loss of functionality or compatibility. diff --git a/docs/CIP_Chroma_Improvment_Proposals.md b/docs/CIP_Chroma_Improvment_Proposals.md new file mode 100644 index 0000000000000000000000000000000000000000..13d4fa5096df1625b6d8f42730550d8fbc10ba8a --- /dev/null +++ b/docs/CIP_Chroma_Improvment_Proposals.md @@ -0,0 +1,63 @@ +# CIP Chroma Improvement Proposals + +## Purpose + +We want to make Chroma a core architectural component for users. Core architectural +elements can't break compatibility or shift functionality from release to release. +As a result each new major feature or public api has to be done in a way that we can stick +with it going forward. + +This means when making this kind of change we need to think through what we are doing as +best we can prior to release. And as we go forward we need to stick to our decisions as +much as possible. All technical decisions have pros and cons so it is important we +capture the thought process that leads to a decision or design to avoid flip-flopping +needlessly. + +Hopefully we can make these proportional in effort to their magnitude — small changes +should just need a couple brief paragraphs, whereas large changes need detailed design +discussions. + +This process also isn't meant to discourage incompatible changes — proposing an +incompatible change is totally legitimate. Sometimes we will have made a mistake and +the best path forward is a clean break that cleans things up and gives us a good +foundation going forward. Rather this is intended to avoid accidentally introducing +half thought-out interfaces and protocols that cause needless heartburn when changed. +Likewise the definition of "compatible" is itself squishy: small details like which +errors are thrown when are clearly part of the contract but may need to change in some +circumstances, likewise performance isn't part of the public contract but dramatic +changes may break use cases. So we just need to use good judgement about how big the +impact of an incompatibility will be and how big the payoff is. + +## What is considered a "major change" that needs a CIP? + +- Any of the following should be considered a major change: + - Any major new feature, subsystem, or piece of functionality + - Any change that impacts the public interfaces of the project + +What are the "public interfaces" of the project? + +All of the following are public interfaces that people build around: + +- Index or Metadata storage format +- The network protocol +- The api behavior +- Configuration, especially client configuration +- Monitoring +- Command line tools and arguments + +## What should be included in a CIP? + +A CIP should contain the following sections: + +- Motivation: describe the problem to be solved +- Impact: describe what percentage of users do we think will be impacted by the proposed change. +- Proposed Change: describe the new thing you want to do. This may be fairly extensive and have large subsections of its own. Or it may be a few sentences, depending on the scope of the change. +- New or Changed Public Interfaces: impact to any of the "compatibility commitments" described above. We want to call these out in particular so everyone thinks about them. +- Migration Plan and Compatibility: if this feature requires additional support for a no-downtime upgrade describe how that will work +- Rejected Alternatives: What are the other alternatives you considered and why are they worse? The goal of this section is to help people understand why this is the best solution now, and also to prevent churn in the future when old alternatives are reconsidered. + +## Who should initiate the CIP? + +Anyone can initiate a CIP - we welcome ideas about how to improve Chroma, the core +Chroma team will review, provide feedback, and come to a decision on if the proposal +makes sense for the long term direction of Chroma. diff --git a/docs/assets/cip-2-arch.png b/docs/assets/cip-2-arch.png new file mode 100644 index 0000000000000000000000000000000000000000..68f30ac6c5cd5b2209c0f1529b2d7235c831034c Binary files /dev/null and b/docs/assets/cip-2-arch.png differ diff --git a/docs/assets/cip-2-client-side-wf.png b/docs/assets/cip-2-client-side-wf.png new file mode 100644 index 0000000000000000000000000000000000000000..82d49898f8804b8b1482f9a4bfee2d7eb0e74473 Binary files /dev/null and b/docs/assets/cip-2-client-side-wf.png differ diff --git a/docs/assets/cip-2-seq.png b/docs/assets/cip-2-seq.png new file mode 100644 index 0000000000000000000000000000000000000000..a42dc8ec7c452fd086149418a1cfbf8430615473 Binary files /dev/null and b/docs/assets/cip-2-seq.png differ diff --git a/docs/assets/cip-2-server-side-wf.png b/docs/assets/cip-2-server-side-wf.png new file mode 100644 index 0000000000000000000000000000000000000000..a4acb6d8893a63105cde4180be44104eb48949c7 Binary files /dev/null and b/docs/assets/cip-2-server-side-wf.png differ diff --git a/docs/cip/CIP-01022024_SSL_Verify_Client_Config.md b/docs/cip/CIP-01022024_SSL_Verify_Client_Config.md new file mode 100644 index 0000000000000000000000000000000000000000..2448af11c88e098d91eddc7863c4143c2e999724 --- /dev/null +++ b/docs/cip/CIP-01022024_SSL_Verify_Client_Config.md @@ -0,0 +1,68 @@ +# CIP-01022024 SSL Verify Client Config + +## Status + +Current Status: `Under Discussion` + +## Motivation + +The motivation for this change is to enhance security and flexibility in Chroma's client API. Users need the ability to +configure SSL contexts to trust custom CA certificates or self-signed certificates, which is not straightforward with +the current setup. This capability is crucial for organizations that operate their own CA or for developers who need to +test their applications in environments where certificates from a recognized CA are not available or practical. + +The suggested change entails a server-side certificate be available, but this CIP does not prescribe how such +certificate should be configured or obtained. In our testing, we used a self-signed certificate generated with +`openssl` and configured the client to trust the certificate. We also experiment with a SSL-terminated proxy server. +Both of approaches yielded the same results. + +> **IMPORTANT:** It should be noted that we do not recommend or encourage the use of self-signed certificates in +> production environments. + +We also provide a sample notebook that to help the reader run a local Chroma server with a self-signed certificate and +configure the client to trust the certificate. The notebook can be found +in [assets/CIP-01022024-test_self_signed.ipynb](./assets/CIP-01022024-test_self_signed.ipynb). + +## Public Interfaces + +> **Note:** The following changes are only applicable to Chroma HttpClient. + +New settings variable `chroma_server_ssl_verify` accepting either a boolean or a path to a certificate file. If the +value is a path to a certificate file, the file will be used to verify the server's certificate. If the value is a +boolean, the SSL certificate verification can be bypassed (`false`) or enforced (`true`). + +The value is passed as `verify` parameter to `requests.Session` of the `FastAPI` client. See +requests [documentation](https://requests.readthedocs.io/en/latest/user/advanced/#ssl-cert-verification) for +more details. + +Example Usage: + +```python +import chromadb +from chromadb import Settings +client = chromadb.HttpClient(host="localhost",port="8443",ssl=True, settings=Settings(chroma_server_ssl_verify='./servercert.pem')) +# or with boolean +client = chromadb.HttpClient(host="localhost",port="8443",ssl=True, settings=Settings(chroma_server_ssl_verify=False)) +``` + +### Resources + +- https://requests.readthedocs.io/en/latest/api/#requests.request +- https://www.geeksforgeeks.org/ssl-certificate-verification-python-requests/ + +## Proposed Changes + +The proposed changes are mentioned in the public interfaces. + +## Compatibility, Deprecation, and Migration Plan + +The change is not backward compatible from client's perspective as the lack of the feature in prior clients will cause +an error when passing the new settings parameter. Server-side is not affected by this change. + +## Test Plan + +API tests with SSL verification enabled and a self-signed certificate. + +## Rejected Alternatives + +N/A diff --git a/docs/cip/CIP-10112023_Authorization.md b/docs/cip/CIP-10112023_Authorization.md new file mode 100644 index 0000000000000000000000000000000000000000..1be1e4c51b6338282666b4b6954d32ec8feab500 --- /dev/null +++ b/docs/cip/CIP-10112023_Authorization.md @@ -0,0 +1,299 @@ +# CIP-10112023: Authorization + +## Status + +Current Status: `Under Discussion` + +## **Motivation** + +The motivation for introducing an authorization feature in Chroma is to address the lack of a proper authorization model that many users are struggling with, especially those who deploy production apps. Additionally, as Chroma is gearing up for production-grade deployments out of the box, it is essential to have a proper authorization model in place for distributed and hosted Chroma instances. + +## **Public Interfaces** + +No changes to public interfaces are proposed in this CIP. + +## **Proposed Changes** + +In this CIP we propose the introduction of abstractions necessary for implementing a multi-user authorization scheme in a pluggable way. We also propose a baseline implementation of such a scheme which will be shipped with Chroma as a default authorization provider. + +It is important to keep in mind that the client/server interaction in Chroma is meant to be stateless, as such the Authorization approach must also follow the same principle. This means that the server must not store any state about the user's authorization. The authorization decision must be made on a per-request basis. + +The diagram below illustrates the levels of abstractions we introduce: + +![Server-Side Authorization Workflow](assets/CIP-10112023_Authorization_Workflow.png) + +- (1) Client Sends Request to Chroma Server +- (2) Authentication Middleware intercepts the request +- (3a) Authentication Provider attempts to authenticate the user +- (3b) Authentication Provider returns success (with user identity) or failure +- (3c) Authentication Middleware returns success or failure to server +- (4) Server passes the request with user identity to the Authorization Middleware +- (5) Authorization Middleware creates Authorization Request Context +- (6) Authorization Context Decorator (at API endpoint) intercepts the call and using Authorization Request Context creates an Authorization Context that is then passed to the Authorization Provider +- (7)Authorization Context Decorator raises and error if the Authorization Provider returns a failure or passes the request to the API endpoint if the Authorization Provider returns success +- (8a) Request is passed to the API endpoint for execution +- (8b) Response is returned to the client + +In the above diagram we highlight the new abstractions we introduce in this CIP and we also demonstrate the interop with the existing Authentication + +### Concepts + +#### Basic Authorization Terms + +##### User + +A user is an entity that can perform actions on resources. A user can be a human or a machine. + +##### Resource + +A resource is an entity that can be acted upon. A resource can be a database, a collection, a document. + +> Note: In this release we do not support document as a resource. + +##### Action + +An action is an operation that can be performed on a resource. An action can be `read`, `write`, `delete`, `update`, `create`, `list`, `count`, `query`, `peek`, `get`, `add`, `upsert`, `get_or_create`. Actions are resource specific. + +##### Role + +A role is a collection of actions that a user can perform on a resource. This pertains to RBAC or Role Based Access Control. + +#### Chroma Authorization Terms + +##### ServerAuthorizationProvider + +The `ServerAuthorizationProvider` is a class that abstracts a provider that will authorize requests to the Chroma server (FastAPI). In practical terms the provider will integrate with an external authorization service (e.g. Auth0, Okta, Permit.io etc.) and will be responsible for allowing or denying the user request. + +In our baseline implementation we will provide a simple file-based RBAC authorization provider that will read authorization configuration from a YAML file. + +##### ServerAuthzConfigurationProvider + +The `ServerAuthzConfigurationProvider` is a class that abstracts a the configuration needed for authorization provider to work. In practice that implies, reading secrets from environment variables, reading configuration from a file, or reading configuration from a database or secrets file, or even KMS. + +In our baseline implementation the AuthzConfigurationProvider will read configuration from a YAML file that contains the authorization configuration. + +##### ServerAuthorizationRequest + +The `ServerAuthorizationRequest` encapsulates the authorization context. + +##### ServerAuthorizationResponse + +Authorization response provides authorization provider evaluation response. It returns a boolean response indicating whether the request is allowed or denied. + +##### ChromaAuthzMiddleware + +The `ChromaAuthzMiddleware` is an abstraction for the server-side middleware. At the time of writing we only support FastAPI. The middleware interface supports several methods: + +- `authorize` - authorizes the request against the authorization provider. +- `ignore_operation` - determines whether or not the operation should be ignored by the middleware +- `instrument_server` - an optional method for additional server instrumentation. For example, header injection. + +##### AuthorizationError + +Error thrown when an authorization request is disallowed/denied by the authorization provider. Depending on authorization provider's implementation such error may also be thrown when the authorization provider is not available or an internal error ocurred. + +Client semantics of this error is a 403 Unauthorized error being returned over HTTP interface. + +##### AuthorizationContext + +The AuthorizationContext is composed of three components as defined in #Basic Authorization Terms: + +- User +- Resource +- Action + + +```json +{ +"user": {"id": "API Token or User Id"}, +"resource": {"namespace": "*", "id": "collection_id","type": "database"}, +"action": {"id":"get_or_create"}, +} +``` + +We intentionally want to keep this as minimal as possible to avoid any unnecessary complexity and to allow users to easily understand the authorization model. However the context is just an abstraction of the above representation and each authorization provider will need to implement the above and if necessary extend it to support additional information. + +We propose the following classes to represent the above: + +```python +@dataclass +class AuthzUser: + id: Optional[str] + attributes: Optional[Dict[str, Any]] = None + claims: Optional[Dict[str, Any]] = None + + +@dataclass +class AuthzResource: + id: Optional[str] + type: Optional[str] + namespace: Optional[str] + attributes: Optional[Dict[str, Any]] = None + + +@dataclass +class AuthzAction: + id: str + attributes: Optional[Dict[str, Any]] = None + + +@dataclass +class AuthorizationContext: + user: AuthzUser + resource: AuthzResource + action: AuthzAction + +``` + +##### User Identity + +In this CIP we also introduce a handover or bridge mechanism from authentication to authorization which we term `User Identity`. The object is meant to encapsulate the user identity and possibly also claims, roles and attributes in the future. + +```python +class UserIdentity(EnforceOverrides, ABC): + @abstractmethod + def get_user_id(self) -> str: + ... +``` + +### Baseline Implementation + +In this section we propose a minimal implementation example of the authorization framework which will also ship in Chroma as a default authorization provider and a reference implementation. Our reference implementation relies on static configuration files in YAML format. + +We introduce the following implementations: + +- `LocalUserConfigAuthorizationConfigurationProvider` - a simple authz configuration to read the yaml configuration file. +- `SimpleRBACAuthorizationProvider` - a simple RBAC authorization provider that reads the configuration from the configuration provider, creates a list of tuples for every user and his role action mappings (e.g. `('user@example.com','tenant_x', 'db', 'list_collections')`) and evaluates the authorization request against the list of tuples. + +#### Authentication and Authorization Config Scheme + +In our baseline implementation we propose the following configuration scheme: + +```yaml +resource_type_action: # This is here just for reference + - tenant:create_tenant + - tenant:get_tenant + - db:create_database + - db:get_database + - db:reset + - db:list_collections + - collection:get_collection + - db:create_collection + - db:get_or_create_collection + - collection:delete_collection + - collection:update_collection + - collection:add + - collection:delete + - collection:get + - collection:query + - collection:peek #from API perspective this is the same as collection:get + - collection:count + - collection:update + - collection:upsert + +roles_mapping: + admin: + actions: + [ + "tenant:create_tenant", + "tenant:get_tenant", + "db:create_database", + "db:get_database", + "db:reset", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "db:get_or_create_collection", + "collection:delete_collection", + "collection:update_collection", + "collection:add", + "collection:delete", + "collection:get", + "collection:query", + "collection:peek", + "collection:update", + "collection:upsert", + "collection:count", + ] + write: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "db:get_or_create_collection", + "collection:delete_collection", + "collection:update_collection", + "collection:add", + "collection:delete", + "collection:get", + "collection:query", + "collection:peek", + "collection:update", + "collection:upsert", + "collection:count", + ] + db_read: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "db:get_or_create_collection", + "collection:delete_collection", + "collection:update_collection", + ] + collection_read: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "db:list_collections", + "collection:get_collection", + "collection:get", + "collection:query", + "collection:peek", + "collection:count", + ] + collection_x_read: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "collection:get_collection", + "collection:get", + "collection:query", + "collection:peek", + "collection:count", + ] + resources: [""] #not yet supported +users: + - id: user@example.com + role: admin + tenant: my_tenant + tokens: + - token: test-token-admin + secret: my_api_secret # not yet supported + - id: Anonymous + role: db_read + tokens: + - token: my_api_token + secret: my_api_secret + +``` + +## **Compatibility, Deprecation, and Migration Plan** + +This CIP is backwards compatible with older versions of Chroma clients. + +## **Test Plan** + +Property and Integration tests. + +## **Rejected Alternatives** + +We considered several alternatives that are more vendor specific (such az Auth0, Okta, Permit.io etc.), but we decided to go with a more generic approach that will allow users to be able to extend the authorization framework to support additional features and providers. diff --git a/docs/cip/CIP-1_Allow_Filtering_for_Collections.md b/docs/cip/CIP-1_Allow_Filtering_for_Collections.md new file mode 100644 index 0000000000000000000000000000000000000000..6671390fc90999116045ffc89968ff364c72757f --- /dev/null +++ b/docs/cip/CIP-1_Allow_Filtering_for_Collections.md @@ -0,0 +1,54 @@ +# CIP-1 Allow Filtering for Collections + +## Status + +Current Status: Under Discussion + +## Motivation + +Currently operations on getting collections does not yet support filtering based on its +metadata, as a result, users have to perform filtering after getting the collection. +This is inconvenient to the users as they have to perform the filtering in the +application and inefficient as extra bandwidth are consumed when transferring data +between client and server. + +We should allow for getting a collection based on a filtering of its metadata. For +example, users could handle cases like wanting to get all collections belonging to a +specific id or a specific collection metadata field value. + +## Public Interfaces + +The public facing change is on the `list_collection` API. Specifically, we would like to +change the following API to add an optional `where` parameter in the API class. + +```python +def list_collections(self) -> Sequence[Collection]: # original +def list_collections(self, where: Optional[Where] = {}) # after the change +``` + +## Proposed Changes + +The proposed changes are mentioned in the public interfaces. + +## Compatibility, Deprecation, and Migration Plan + +This change is backward compatible. + +## Test Plan + +We plan to modify unit tests to accommodate the change and use system tests to verify +this API change is backward compatible. + +## Rejected Alternatives + +- An alternative solution would be adding new APIs similar to + +```python +def get_collection( +self, +name: str, +embedding_function: Optional[EmbeddingFunction] = ef.DefaultEmbeddingFunction(), +) -> Collection: +``` + +We decided to not go with it to reduce the user's burden to learn new APIs. diff --git a/docs/cip/assets/CIP-01022024-test_self_signed.ipynb b/docs/cip/assets/CIP-01022024-test_self_signed.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..d607b51824b762864f176bf8c1f60359044d0009 --- /dev/null +++ b/docs/cip/assets/CIP-01022024-test_self_signed.ipynb @@ -0,0 +1,119 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Generate a Certificate\n", + "\n", + "```bash\n", + "openssl req -new -newkey rsa:2048 -sha256 -days 365 -nodes -x509 \\\n", + " -keyout ./serverkey.pem \\\n", + " -out ./servercert.pem \\\n", + " -subj \"/O=Chroma/C=US\" \\\n", + " -config chromadb/test/openssl.cnf\n", + "```\n", + "\n", + "> Note: The above command should be executed at the root of the repo (openssl.cnf uses relative path)\n" + ], + "metadata": { + "collapsed": false + }, + "id": "faa8cefb6825fe83" + }, + { + "cell_type": "markdown", + "source": [ + "# Start the server\n", + "\n", + "```bash\n", + "uvicorn chromadb.app:app --workers 1 --host 0.0.0.0 --port 8443 \\\n", + " --proxy-headers --log-config chromadb/log_config.yml --ssl-keyfile ./serverkey.pem --ssl-certfile ./servercert.pem\n", + "```" + ], + "metadata": { + "collapsed": false + }, + "id": "e084285e11c3747d" + }, + { + "cell_type": "markdown", + "source": [ + "# Test with cert as SSL verify string" + ], + "metadata": { + "collapsed": false + }, + "id": "130df9c0a6d67b52" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "initial_id", + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from chromadb import Settings\n", + "import chromadb\n", + "client = chromadb.HttpClient(host=\"localhost\",port=\"8443\",ssl=True, settings=Settings(chroma_server_ssl_verify='./servercert.pem'))\n", + "print(client.heartbeat())" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Test with cert as SSL verify boolean" + ], + "metadata": { + "collapsed": false + }, + "id": "8223d0100df06ec4" + }, + { + "cell_type": "code", + "outputs": [], + "source": [ + "from chromadb import Settings\n", + "import chromadb\n", + "client = chromadb.HttpClient(host=\"localhost\",port=\"8443\",ssl=True, settings=Settings(chroma_server_ssl_verify=False))\n", + "print(client.heartbeat())" + ], + "metadata": { + "collapsed": false + }, + "id": "f7cf299721741c1", + "execution_count": null + }, + { + "cell_type": "code", + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + }, + "id": "6231ac2ac38383c2" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/README.md b/examples/README.md new file mode 100644 index 0000000000000000000000000000000000000000..7b6da2326db1474764a66ce7e3f194437ebd5900 --- /dev/null +++ b/examples/README.md @@ -0,0 +1,64 @@ +## Examples + +> Searching for community contributions! Join the [#contributing](https://discord.com/channels/1073293645303795742/1074711539724058635) Discord Channel to discuss. + +This folder will contain an ever-growing set of examples. + +The key with examples is that they should *always* work. The failure mode of examples folders is that they get quickly deprecated. + +Examples are: +- Easy to maintain +- Easy to maintain examples are __simple__ +- Use case examples are fine, technology is better + +``` +folder structure +- basic_functionality - notebooks with simple walkthroughs +- advanced_functionality - notebooks with advanced walkthroughs +- deployments - how to deploy places +- use_with - chroma + ___, where ___ can be langchain, nextjs, etc +- data - common data for examples +``` + +> 💡 Feel free to open a PR with an example you would like to see + +### Basic Functionality +- [x] Examples of using different embedding models +- [x] Local persistance demo +- [x] Where filtering demo + +### Advanced Functionality +- [ ] Clustering +- [ ] Projections +- [ ] Fine tuning + +### Use With + +#### LLM Application Code +- [ ] Langchain +- [ ] LlamaIndex +- [ ] Semantic Kernal + +#### App Frameworks +- [ ] Streamlit +- [ ] Gradio +- [ ] Nextjs +- [ ] Rails +- [ ] FastAPI + +#### Inference Services +- [ ] Brev.dev +- [ ] Banana.dev +- [ ] Modal + +### LLM providers/services +- [ ] OpenAI +- [ ] Anthropic +- [ ] Cohere +- [ ] Google PaLM +- [ ] Hugging Face + +*** + +### Inspiration +- The [OpenAI Cookbook](https://github.com/openai/openai-cookbook) gets a lot of things right diff --git a/examples/advanced/hadrware-optimized-image.md b/examples/advanced/hadrware-optimized-image.md new file mode 100644 index 0000000000000000000000000000000000000000..41aad017719097b1d9ce511d38e78ce67ad6b755 --- /dev/null +++ b/examples/advanced/hadrware-optimized-image.md @@ -0,0 +1,10 @@ +# Building Hardware Optimized ChromaDB Image + +The default Chroma DB image comes with binary distribution of hnsw lib which is not optimized to take advantage of +certain CPU architectures (Intel-based) with AVX support. This can be improved by building an image with hnsw rebuilt +from source. To do that run: + +```bash +docker build -t chroma-test1 --build-arg REBUILD_HNSWLIB=true --no-cache . +``` + diff --git a/examples/basic_functionality/alternative_embeddings.ipynb b/examples/basic_functionality/alternative_embeddings.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..e069cdd4d94172c96ac621873a96e00b7a97b8a9 --- /dev/null +++ b/examples/basic_functionality/alternative_embeddings.ipynb @@ -0,0 +1,325 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + " # Alternative Embeddings\n", + " \n", + " This notebook demonstrates how to use alternative embedding functions.\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import chromadb" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "client = chromadb.Client()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from chromadb.utils import embedding_functions" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Using OpenAI Embeddings. This assumes you have the openai package installed\n", + "openai_ef = embedding_functions.OpenAIEmbeddingFunction(\n", + " api_key=\"OPENAI_KEY\", # Replace with your own OpenAI API key\n", + " model_name=\"text-embedding-ada-002\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new chroma collection\n", + "openai_collection = client.get_or_create_collection(name=\"openai_embeddings\", embedding_function=openai_ef)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "openai_collection.add(\n", + " documents=[\"This is a document\", \"This is another document\"],\n", + " metadatas=[{\"source\": \"my_source\"}, {\"source\": \"my_source\"}],\n", + " ids=[\"id1\", \"id2\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': [['id1', 'id2']],\n", + " 'distances': [[0.1385088860988617, 0.2017185091972351]],\n", + " 'metadatas': [[{'source': 'my_source'}, {'source': 'my_source'}]],\n", + " 'embeddings': None,\n", + " 'documents': [['This is a document', 'This is another document']]}" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results = openai_collection.query(\n", + " query_texts=[\"This is a query document\"],\n", + " n_results=2\n", + ")\n", + "results" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Using Cohere Embeddings. This assumes you have the cohere package installed\n", + "cohere_ef = embedding_functions.CohereEmbeddingFunction(\n", + " api_key=\"COHERE_API_KEY\", \n", + " model_name=\"large\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new chroma collection\n", + "cohere_collection = client.create_collection(name=\"cohere_embeddings\", embedding_function=cohere_ef)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "cohere_collection.add(\n", + " documents=[\"This is a document\", \"This is another document\"],\n", + " metadatas=[{\"source\": \"my_source\"}, {\"source\": \"my_source\"}],\n", + " ids=[\"id1\", \"id2\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': [['id1', 'id2']],\n", + " 'embeddings': None,\n", + " 'documents': [['This is a document', 'This is another document']],\n", + " 'metadatas': [[{'source': 'my_source'}, {'source': 'my_source'}]],\n", + " 'distances': [[4343.1328125, 5653.28759765625]]}" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results = cohere_collection.query(\n", + " query_texts=[\"This is a query document\"],\n", + " n_results=2\n", + ")\n", + "results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Using Instructor models. The embedding function requires the InstructorEmbedding package. \n", + "# To install it, run pip install InstructorEmbedding\n", + "\n", + "\n", + "#uses base model and cpu\n", + "instructor_ef = embedding_functions.InstructorEmbeddingFunction() \n", + "\n", + "# For task specific embeddings, add an instruction\n", + "# instructor_ef = embedding_functions.InstructorEmbeddingFunction(\n", + "# instruction=\"Represent the Wikipedia document for retrieval: \"\n", + "# )\n", + "\n", + "# Uses hkunlp/instructor-xl model and GPU\n", + "#instructor_ef = embedding_functions.InstructorEmbeddingFunction(model_name=\"hkunlp/instructor-xl\", device=\"cuda\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a collection with the instructor embedding function\n", + "instructor_collection = client.create_collection(name=\"instructor_embeddings\", embedding_function=instructor_ef)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "instructor_collection.add(\n", + " documents=[\"This is a document\", \"This is another document\"],\n", + " metadatas=[{\"source\": \"my_source\"}, {\"source\": \"my_source\"}],\n", + " ids=[\"id1\", \"id2\"]\n", + ")\n", + "\n", + "# Adding documents with an instruction\n", + "# instructor_ef = embedding_functions.InstructorEmbeddingFunction(\n", + "# instruction=\"Represent the Science sentence: \"\n", + "# )\n", + "# instructor_collection = client.create_collection(name=\"instructor_embeddings\", embedding_function=instructor_ef)\n", + "# instructor_collection.add(documents=[\"Parton energy loss in QCD matter\"], ids=[\"id1\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "results = instructor_collection.query(\n", + " query_texts=[\"This is a query document\"],\n", + " n_results=2\n", + ")\n", + "results\n", + "\n", + "# Querying with an instruction\n", + "# instructor_ef = embedding_functions.InstructorEmbeddingFunction(instruction=\"Represent the Wikipedia question for retrieving supporting documents: \")\n", + "# instructor_collection = client.get_collection(name=\"instructor_embeddings\", embedding_function=instructor_ef)\n", + "# results = instructor_collection.query(query_texts=[\"where is the food stored in a yam plant\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Using HuggingFace models. The embedding function a huggingface api_key\n", + "huggingface_ef = embedding_functions.HuggingFaceEmbeddingFunction(\n", + " api_key=\"HUGGINGFACE_API_KEY\", # Replace with your own HuggingFace API key\n", + " model_name=\"sentence-transformers/all-MiniLM-L6-v2\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new HuggingFace collection\n", + "huggingface_collection = client.create_collection(name=\"huggingface_embeddings\", embedding_function=huggingface_ef)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "huggingface_collection.add(\n", + " documents=[\"This is a document\", \"This is another document\"],\n", + " metadatas=[{\"source\": \"my_source\"}, {\"source\": \"my_source\"}],\n", + " ids=[\"id1\", \"id2\"]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': [['id1', 'id2']],\n", + " 'embeddings': None,\n", + " 'documents': [['This is a document', 'This is another document']],\n", + " 'metadatas': [[{'source': 'my_source'}, {'source': 'my_source'}]],\n", + " 'distances': [[0.7111215591430664, 1.010978102684021]]}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "results = huggingface_collection.query(\n", + " query_texts=[\"This is a query document\"],\n", + " n_results=2\n", + ")\n", + "results" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.8" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/basic_functionality/assets/auh-sequence.png b/examples/basic_functionality/assets/auh-sequence.png new file mode 100644 index 0000000000000000000000000000000000000000..d674328f688206b8b99c4c7c03695d4349986eb0 Binary files /dev/null and b/examples/basic_functionality/assets/auh-sequence.png differ diff --git a/examples/basic_functionality/assets/auth-architecture.png b/examples/basic_functionality/assets/auth-architecture.png new file mode 100644 index 0000000000000000000000000000000000000000..33d049acdd36d4a19132fff5673853311f4f47f1 Binary files /dev/null and b/examples/basic_functionality/assets/auth-architecture.png differ diff --git a/examples/basic_functionality/authz/README.md b/examples/basic_functionality/authz/README.md new file mode 100644 index 0000000000000000000000000000000000000000..b85693acc3670b0100d31ecff8e7cf8fb8875e22 --- /dev/null +++ b/examples/basic_functionality/authz/README.md @@ -0,0 +1,155 @@ +# Authorization + +## Configuration + +### Resource Actions + +```yaml +resource_type_action: # This is here just for reference + - tenant:create_tenant + - tenant:get_tenant + - db:create_database + - db:get_database + - db:reset + - db:list_collections + - collection:get_collection + - db:create_collection + - db:get_or_create_collection + - collection:delete_collection + - collection:update_collection + - collection:add + - collection:delete + - collection:get + - collection:query + - collection:peek #from API perspective this is the same as collection:get + - collection:count + - collection:update + - collection:upsert +``` + +### Role Mapping + +Following are the role mappings where we define roles and the actions they can perform. The actions spaces is taken from the resource actions defined above. + +> **Note**: We also plan to support resource level authorization soon but for now only RBAC is available. + +```yaml +roles_mapping: + admin: + actions: + [ + db:list_collections, + collection:get_collection, + db:create_collection, + db:get_or_create_collection, + collection:delete_collection, + collection:update_collection, + collection:add, + collection:delete, + collection:get, + collection:query, + collection:peek, + collection:update, + collection:upsert, + collection:count, + ] + write: + actions: + [ + db:list_collections, + collection:get_collection, + db:create_collection, + db:get_or_create_collection, + collection:delete_collection, + collection:update_collection, + collection:add, + collection:delete, + collection:get, + collection:query, + collection:peek, + collection:update, + collection:upsert, + collection:count, + ] + db_read: + actions: + [ + db:list_collections, + collection:get_collection, + db:create_collection, + db:get_or_create_collection, + collection:delete_collection, + collection:update_collection, + ] + collection_read: + actions: + [ + db:list_collections, + collection:get_collection, + collection:get, + collection:query, + collection:peek, + collection:count, + ] + collection_x_read: + actions: + [ + collection:get_collection, + collection:get, + collection:query, + collection:peek, + collection:count, + ] + resources: [""] #not yet supported +``` + +You can update the roll mapping as per your requirements. + +### Users + +Last piece of the puzzle is the user configuration. Here we define the user id, role and the tokens they can use to authenticate. + +> **Note**: In our example we use both AuthN and AuthZ where AuthN verifies whether a token is valid e.g. user has that token and AuthZ verifies whether the user has the right role to perform the action. + +```yaml +users: + - id: user@example.com + role: admin + tokens: + - token: test-token-admin + secret: my_api_secret # not yet supported + - id: Anonymous + role: admin + tokens: + - token: my_api_token + secret: my_api_secret +``` + +## Starting the Server + +```bash +IS_PERSISTENT=1 \ +CHROMA_SERVER_AUTHZ_PROVIDER="chromadb.auth.authz.SimpleRBACAuthorizationProvider" \ +CHROMA_SERVER_AUTH_CREDENTIALS_FILE=examples/basic_functionality/authz/authz.yaml \ +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="user_token_config" \ +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.token.TokenAuthServerProvider" \ +CHROMA_SERVER_AUTHZ_CONFIG_FILE=examples/basic_functionality/authz/authz.yaml \ +uvicorn chromadb.app:app --workers 1 --host 0.0.0.0 --port 8000 --proxy-headers --log-config chromadb/log_config.yml --reload --timeout-keep-alive 30 +``` + +## Testing the authorization + +```python +import chromadb +from chromadb.config import Settings + +client = chromadb.HttpClient("http://localhost:8000/", + settings=Settings(chroma_client_auth_provider="chromadb.auth.token.TokenAuthClientProvider", + chroma_client_auth_credentials="test-token-admin")) + +client.list_collections() +collection = client.get_or_create_collection("test_collection") + +collection.add(documents=["test"],ids=["1"]) +collection.get() +``` diff --git a/examples/basic_functionality/authz/authz.ipynb b/examples/basic_functionality/authz/authz.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..97abebd5785cff46505a6909e0d9139247c5651b --- /dev/null +++ b/examples/basic_functionality/authz/authz.ipynb @@ -0,0 +1,95 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/Users/tazarov/experiments/chroma-experiments/authz-tenant-db-hook\n" + ] + }, + { + "data": { + "text/plain": [ + "{'ids': ['1'],\n", + " 'embeddings': None,\n", + " 'metadatas': [None],\n", + " 'documents': ['test21']}" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%cd ../../../\n", + "import chromadb\n", + "from chromadb.config import Settings\n", + "\n", + "client = chromadb.HttpClient(\"http://localhost:8000/\",\n", + " settings=Settings(chroma_client_auth_provider=\"chromadb.auth.token.TokenAuthClientProvider\",\n", + " chroma_client_auth_credentials=\"test-token-admin\"))\n", + "\n", + "client.list_collections()\n", + "collection = client.get_or_create_collection(\"test_collection\")\n", + "\n", + "collection.add(documents=[\"test21\"],ids=[\"1\"])\n", + "collection.get(ids=[\"1\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "ename": "HTTPError", + "evalue": "400 Client Error: Bad Request for url: http://localhost:8000/api/v1/collections/4487accd-6160-454c-a5f2-26d6e87ce5ef/upsert", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mHTTPError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/Users/tazarov/experiments/chroma-experiments/chroma-authz/examples/basic_functionality/authz/authz.ipynb Cell 2\u001b[0m line \u001b[0;36m6\n\u001b[1;32m 2\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mchromadb\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mapi\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mmodels\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mCollection\u001b[39;00m \u001b[39mimport\u001b[39;00m Collection\n\u001b[1;32m 5\u001b[0m col \u001b[39m=\u001b[39m Collection(client, \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mtest-upsert-\u001b[39m\u001b[39m{\u001b[39;00muuid\u001b[39m.\u001b[39muuid4()\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m, uuid\u001b[39m.\u001b[39muuid4())\n\u001b[0;32m----> 6\u001b[0m col\u001b[39m.\u001b[39;49mupsert(documents\u001b[39m=\u001b[39;49m[\u001b[39m\"\u001b[39;49m\u001b[39mtest\u001b[39;49m\u001b[39m\"\u001b[39;49m],ids\u001b[39m=\u001b[39;49m[\u001b[39m\"\u001b[39;49m\u001b[39m1\u001b[39;49m\u001b[39m\"\u001b[39;49m])\n", + "File \u001b[0;32m~/experiments/chroma-experiments/chroma-authz/chromadb/api/models/Collection.py:299\u001b[0m, in \u001b[0;36mCollection.upsert\u001b[0;34m(self, ids, embeddings, metadatas, documents)\u001b[0m\n\u001b[1;32m 283\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"Update the embeddings, metadatas or documents for provided ids, or create them if they don't exist.\u001b[39;00m\n\u001b[1;32m 284\u001b[0m \n\u001b[1;32m 285\u001b[0m \u001b[39mArgs:\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 292\u001b[0m \u001b[39m None\u001b[39;00m\n\u001b[1;32m 293\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 295\u001b[0m ids, embeddings, metadatas, documents \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_validate_embedding_set(\n\u001b[1;32m 296\u001b[0m ids, embeddings, metadatas, documents\n\u001b[1;32m 297\u001b[0m )\n\u001b[0;32m--> 299\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_client\u001b[39m.\u001b[39;49m_upsert(\n\u001b[1;32m 300\u001b[0m collection_id\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mid,\n\u001b[1;32m 301\u001b[0m ids\u001b[39m=\u001b[39;49mids,\n\u001b[1;32m 302\u001b[0m embeddings\u001b[39m=\u001b[39;49membeddings,\n\u001b[1;32m 303\u001b[0m metadatas\u001b[39m=\u001b[39;49mmetadatas,\n\u001b[1;32m 304\u001b[0m documents\u001b[39m=\u001b[39;49mdocuments,\n\u001b[1;32m 305\u001b[0m )\n", + "File \u001b[0;32m~/experiments/chroma-experiments/chroma-authz/chromadb/api/fastapi.py:382\u001b[0m, in \u001b[0;36m_upsert\u001b[0;34m(self, collection_id, ids, embeddings, metadatas, documents)\u001b[0m\n\u001b[1;32m 379\u001b[0m batch \u001b[39m=\u001b[39m (ids, embeddings, metadatas, documents)\n\u001b[1;32m 380\u001b[0m validate_batch(batch, {\u001b[39m\"\u001b[39m\u001b[39mmax_batch_size\u001b[39m\u001b[39m\"\u001b[39m: \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmax_batch_size})\n\u001b[1;32m 381\u001b[0m resp \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_submit_batch(\n\u001b[0;32m--> 382\u001b[0m batch, \u001b[39m\"\u001b[39m\u001b[39m/collections/\u001b[39m\u001b[39m\"\u001b[39m \u001b[39m+\u001b[39m \u001b[39mstr\u001b[39m(collection_id) \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m/update\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 383\u001b[0m )\n\u001b[1;32m 384\u001b[0m resp\u001b[39m.\u001b[39mraise_for_status()\n\u001b[1;32m 385\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mTrue\u001b[39;00m\n", + "File \u001b[0;32m~/experiments/chroma-experiments/chroma-authz/venv/lib/python3.11/site-packages/requests/models.py:1021\u001b[0m, in \u001b[0;36mResponse.raise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1016\u001b[0m http_error_msg \u001b[39m=\u001b[39m (\n\u001b[1;32m 1017\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstatus_code\u001b[39m}\u001b[39;00m\u001b[39m Server Error: \u001b[39m\u001b[39m{\u001b[39;00mreason\u001b[39m}\u001b[39;00m\u001b[39m for url: \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39murl\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[1;32m 1018\u001b[0m )\n\u001b[1;32m 1020\u001b[0m \u001b[39mif\u001b[39;00m http_error_msg:\n\u001b[0;32m-> 1021\u001b[0m \u001b[39mraise\u001b[39;00m HTTPError(http_error_msg, response\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m)\n", + "\u001b[0;31mHTTPError\u001b[0m: 400 Client Error: Bad Request for url: http://localhost:8000/api/v1/collections/4487accd-6160-454c-a5f2-26d6e87ce5ef/upsert" + ] + } + ], + "source": [ + "import uuid\n", + "from chromadb.api.models.Collection import Collection\n", + "\n", + "col = Collection(client, f\"test-upsert-{uuid.uuid4()}\", uuid.uuid4())\n", + "col.upsert(documents=[\"test\"],ids=[\"1\"])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/basic_functionality/authz/authz.yaml b/examples/basic_functionality/authz/authz.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1e07a0ec9e405bac5e3d85583ee0abcc2e708fda --- /dev/null +++ b/examples/basic_functionality/authz/authz.yaml @@ -0,0 +1,113 @@ +resource_type_action: # This is here just for reference + - tenant:create_tenant + - tenant:get_tenant + - db:create_database + - db:get_database + - db:reset + - db:list_collections + - collection:get_collection + - db:create_collection + - db:get_or_create_collection + - collection:delete_collection + - collection:update_collection + - collection:add + - collection:delete + - collection:get + - collection:query + - collection:peek #from API perspective this is the same as collection:get + - collection:count + - collection:update + - collection:upsert + +roles_mapping: + admin: + actions: + [ + "tenant:create_tenant", + "tenant:get_tenant", + "db:create_database", + "db:get_database", + "db:reset", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "db:get_or_create_collection", + "collection:delete_collection", + "collection:update_collection", + "collection:add", + "collection:delete", + "collection:get", + "collection:query", + "collection:peek", + "collection:update", + "collection:upsert", + "collection:count", + ] + write: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "db:get_or_create_collection", + "collection:delete_collection", + "collection:update_collection", + "collection:add", + "collection:delete", + "collection:get", + "collection:query", + "collection:peek", + "collection:update", + "collection:upsert", + "collection:count", + ] + db_read: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "db:list_collections", + "collection:get_collection", + "db:create_collection", + "db:get_or_create_collection", + "collection:delete_collection", + "collection:update_collection", + ] + collection_read: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "db:list_collections", + "collection:get_collection", + "collection:get", + "collection:query", + "collection:peek", + "collection:count", + ] + collection_x_read: + actions: + [ + "tenant:get_tenant", + "db:get_database", + "collection:get_collection", + "collection:get", + "collection:query", + "collection:peek", + "collection:count", + ] + resources: [""] #not yet supported +users: + - id: user@example.com + role: admin + tenant: my_tenant + tokens: + - token: test-token-admin + secret: my_api_secret # not yet supported + - id: Anonymous + role: db_read + tokens: + - token: my_api_token + secret: my_api_secret diff --git a/examples/basic_functionality/client_auth.ipynb b/examples/basic_functionality/client_auth.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b7f89f09bb2876b3a31886a0668c08ec107cdabb --- /dev/null +++ b/examples/basic_functionality/client_auth.ipynb @@ -0,0 +1,394 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Chroma Authentication\n", + "\n", + "This tutorial aims to explain how authentication can be setup in Chroma.\n", + "\n", + "> **Important**: The concept of authentication is only applicable to Client/Server deployments. If you are using Chroma in a standalone mode, authentication is not applicable.\n", + "\n", + "## Concepts\n", + "\n", + "### Architecture Overview\n", + "\n", + "![Authentication Architecture](assets/auth-architecture.png \"Authentication Architecture\")\n", + "\n", + "### Authentication Flow (Sequence)\n", + "\n", + "The authentication sequence is applied for every request. It is important to understand that credential computation or retrieval (e.g. from external auth providers) is only done once for the first authenticated request. Subsequent requests will use the same credentials.\n", + "\n", + "The authentication flow is as follows:\n", + "\n", + "![Authentication Flow](assets/auh-sequence.png \"Authentication Flow\")\n", + "\n", + "### Preemptive Authentication\n", + "\n", + "In its current release the authentication in Chroma works in a preemptive mode. This means that the client is responsible for sending the authentication information on every request. The server will not challenge the client for authentication.\n", + "\n", + "> **Warning**: There are security risks involved with preemptive authentication in that the client might unintentionally send credentials to malicious or unintended server. When deploying authentication users are encouraged to use HTTPS (always verify server certs), to use secure providers (e.g. JWT) \n", + "> and apply good security practices.\n", + "\n", + "### Authentication Provider\n", + "\n", + "Authentication in Chroma is handled by Authentication Providers. Providers are pluggable modules that allow Chroma to abstract the authentication mechanism from the rest of the system.\n", + "\n", + "Chroma ships with the following build-in providers:\n", + "- Basic Authentication\n", + "- JWT Authentication (work in progress)\n", + "\n", + "### Client-side Authentication\n", + "\n", + "Client-side authentication refers to the process of preparing and communicating credentials information on the client-side and sending that information the Chroma server.\n", + "\n", + "### Server-side Authentication\n", + "\n", + "Server-side authentication refers to the process of validating the credentials information received from the client and authenticating the client.\n" + ], + "metadata": { + "collapsed": false + }, + "id": "eae631e46b4c1115" + }, + { + "cell_type": "markdown", + "source": [ + "## Configuration\n", + "\n", + "### Server Configuration\n", + "\n", + "In order for the server to provide auth it needs several pieces of information and depending on the authentication provider you may or may not need to provide all of them.\n", + "\n", + "- `CHROMA_SERVER_AUTH_PROVIDER` - It indicates the authentication provider class to use. In this case we are using the `chromadb.auth.basic.BasicAuthServerProvider` class (it is also possible to use `basic` as a shorthand).\n", + "- `CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER` - The credentials provider is a way for the server to validate the provided auth information from the client. You can use `chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider` to validate against a file in htpasswd format (user:password) - single line with bcrypt hash for password. Alternatively you can use a shorthand to load providers (e.g. `htpasswd_file` for `chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider`).\n", + "- `CHROMA_SERVER_AUTH_CREDENTIALS_FILE` - The path to the credentials file in case the credentials provider requires it. In this case we are using the `chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider` provider which requires a file path.\n", + "\n", + "\n", + "### Client Configuration\n", + "\n", + "Similarly on the client side we need to provide the following configuration parameters:\n", + "\n", + "- `CHROMA_CLIENT_AUTH_PROVIDER` - It indicates the authentication provider class to use. In this case we are using the `chromadb.auth.basic.BasicAuthClientProvider` class or `basic` shorthand.\n", + "- `CHROMA_CLIENT_AUTH_CREDENTIALS` - The auth credentials to be passed to the provider. In this case we are using the `admin:admin` credentials as we'll be using Basic Auth.\n" + ], + "metadata": { + "collapsed": false + }, + "id": "87d45f79aed65e21" + }, + { + "cell_type": "markdown", + "source": [ + "## Setting Up\n", + "\n", + "### Before You Begin\n", + "\n", + "Make sure you have either `chromadb` or `chromadb-client` installed. You can do that by running the following command:\n", + "\n", + "```bash\n", + "pip install chromadb\n", + "```\n", + "or\n", + "\n", + "```bash\n", + "pip install chromadb-client\n", + "```\n", + "\n", + "Make sure Chroma Server is running. Use one of the following methods to start the server:\n", + "\n", + "From the command line:\n", + "\n", + "> Note: The below options will configure the server to use Basic Authentication with the username `admin` and password `admin`.\n", + "\n", + "```bash\n", + "export CHROMA_USER=admin\n", + "export CHROMA_PASSWORD=admin\n", + "docker run --rm --entrypoint htpasswd httpd:2 -Bbn ${CHROMA_USER} ${CHROMA_PASSWORD} > server.htpasswd\n", + "CHROMA_SERVER_AUTH_CREDENTIALS_FILE=\"./server.htpasswd\" \\\n", + "CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=\"chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider\" \\\n", + "CHROMA_SERVER_AUTH_PROVIDER=\"chromadb.auth.basic.BasicAuthServerProvider\" \\\n", + "uvicorn chromadb.app:app --workers 1 --host 0.0.0.0 --port 8000 --proxy-headers --log-config log_config.yml\n", + "```\n", + "\n", + "With Docker Compose:\n", + "\n", + "> Note: You need to clone the git repository first and run the command from the repository root.\n", + "\n", + "```bash\n", + "export CHROMA_USER=admin\n", + "export CHROMA_PASSWORD=admin\n", + "docker run --rm --entrypoint htpasswd httpd:2 -Bbn ${CHROMA_USER} ${CHROMA_PASSWORD} > server.htpasswd\n", + "cat << EOF > .env\n", + "CHROMA_SERVER_AUTH_CREDENTIALS_FILE=\"/chroma/server.htpasswd\"\n", + "CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=\"chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider\"\n", + "CHROMA_SERVER_AUTH_PROVIDER=\"chromadb.auth.basic.BasicAuthServerProvider\"\n", + "EOF\n", + "docker-compose up -d --build \n", + "```\n" + ], + "metadata": { + "collapsed": false + }, + "id": "af49d8c78f2f7347" + }, + { + "cell_type": "markdown", + "source": [ + "## Basic Authentication" + ], + "metadata": { + "collapsed": false + }, + "id": "fc77d909233f2645" + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [ + { + "data": { + "text/plain": "[]" + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import chromadb\n", + "from chromadb import Settings\n", + "\n", + "client = chromadb.HttpClient(\n", + " settings=Settings(chroma_client_auth_provider=\"chromadb.auth.basic.BasicAuthClientProvider\",\n", + " chroma_client_auth_credentials=\"admin:admin\"))\n", + "client.heartbeat() # this should work with or without authentication - it is a public endpoint\n", + "\n", + "client.get_version() # this should work with or without authentication - it is a public endpoint\n", + "\n", + "client.list_collections() # this is a protected endpoint and requires authentication\n", + "\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-08-22T00:33:16.354523Z", + "start_time": "2023-08-22T00:33:15.715736Z" + } + }, + "id": "8f9307acce25f672" + }, + { + "cell_type": "markdown", + "source": [ + "#### Verifying Authentication (Negative Test)" + ], + "metadata": { + "collapsed": false + }, + "id": "6b75f04e59cb1d42" + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "As expected, you are not authorized to access protected endpoints.\n" + ] + } + ], + "source": [ + "# Try to access a protected endpoint without authentication\n", + "import sys\n", + "\n", + "client = chromadb.HttpClient()\n", + "try:\n", + " client.list_collections()\n", + "except Exception as e:\n", + " if \"Unauthorized\" in str(e):\n", + " print(\"As expected, you are not authorized to access protected endpoints.\", file=sys.stderr)\n", + " else:\n", + " raise e" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-08-22T00:33:19.119718Z", + "start_time": "2023-08-22T00:33:19.097558Z" + } + }, + "id": "c0c3240ed4d70a79" + }, + { + "cell_type": "markdown", + "source": [ + "## Token Authentication\n", + "\n", + "> Note: Tokens must be valid ASCII strings.\n", + "\n", + "### Default Token (`Authorization` with `Bearer`)" + ], + "metadata": { + "collapsed": false + }, + "id": "390aed41f019649b" + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "ename": "ConnectionError", + "evalue": "HTTPConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /api/v1 (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 61] Connection refused'))", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mConnectionRefusedError\u001B[0m Traceback (most recent call last)", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connection.py:174\u001B[0m, in \u001B[0;36mHTTPConnection._new_conn\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 173\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m--> 174\u001B[0m conn \u001B[38;5;241m=\u001B[39m \u001B[43mconnection\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mcreate_connection\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m 175\u001B[0m \u001B[43m \u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_dns_host\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mport\u001B[49m\u001B[43m)\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mtimeout\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mextra_kw\u001B[49m\n\u001B[1;32m 176\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 178\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m SocketTimeout:\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/util/connection.py:95\u001B[0m, in \u001B[0;36mcreate_connection\u001B[0;34m(address, timeout, source_address, socket_options)\u001B[0m\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m err \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[0;32m---> 95\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m err\n\u001B[1;32m 97\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m socket\u001B[38;5;241m.\u001B[39merror(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mgetaddrinfo returns an empty list\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/util/connection.py:85\u001B[0m, in \u001B[0;36mcreate_connection\u001B[0;34m(address, timeout, source_address, socket_options)\u001B[0m\n\u001B[1;32m 84\u001B[0m sock\u001B[38;5;241m.\u001B[39mbind(source_address)\n\u001B[0;32m---> 85\u001B[0m \u001B[43msock\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mconnect\u001B[49m\u001B[43m(\u001B[49m\u001B[43msa\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 86\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m sock\n", + "\u001B[0;31mConnectionRefusedError\u001B[0m: [Errno 61] Connection refused", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001B[0;31mNewConnectionError\u001B[0m Traceback (most recent call last)", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connectionpool.py:714\u001B[0m, in \u001B[0;36mHTTPConnectionPool.urlopen\u001B[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001B[0m\n\u001B[1;32m 713\u001B[0m \u001B[38;5;66;03m# Make the request on the httplib connection object.\u001B[39;00m\n\u001B[0;32m--> 714\u001B[0m httplib_response \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_make_request\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m 715\u001B[0m \u001B[43m \u001B[49m\u001B[43mconn\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 716\u001B[0m \u001B[43m \u001B[49m\u001B[43mmethod\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 717\u001B[0m \u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 718\u001B[0m \u001B[43m \u001B[49m\u001B[43mtimeout\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mtimeout_obj\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 719\u001B[0m \u001B[43m \u001B[49m\u001B[43mbody\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mbody\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 720\u001B[0m \u001B[43m \u001B[49m\u001B[43mheaders\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mheaders\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 721\u001B[0m \u001B[43m \u001B[49m\u001B[43mchunked\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mchunked\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 722\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 724\u001B[0m \u001B[38;5;66;03m# If we're going to release the connection in ``finally:``, then\u001B[39;00m\n\u001B[1;32m 725\u001B[0m \u001B[38;5;66;03m# the response doesn't need to know about the connection. Otherwise\u001B[39;00m\n\u001B[1;32m 726\u001B[0m \u001B[38;5;66;03m# it will also try to release it and we'll have a double-release\u001B[39;00m\n\u001B[1;32m 727\u001B[0m \u001B[38;5;66;03m# mess.\u001B[39;00m\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connectionpool.py:415\u001B[0m, in \u001B[0;36mHTTPConnectionPool._make_request\u001B[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001B[0m\n\u001B[1;32m 414\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m--> 415\u001B[0m \u001B[43mconn\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrequest\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmethod\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mhttplib_request_kw\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 417\u001B[0m \u001B[38;5;66;03m# We are swallowing BrokenPipeError (errno.EPIPE) since the server is\u001B[39;00m\n\u001B[1;32m 418\u001B[0m \u001B[38;5;66;03m# legitimately able to close the connection after sending a valid response.\u001B[39;00m\n\u001B[1;32m 419\u001B[0m \u001B[38;5;66;03m# With this behaviour, the received response is still readable.\u001B[39;00m\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connection.py:244\u001B[0m, in \u001B[0;36mHTTPConnection.request\u001B[0;34m(self, method, url, body, headers)\u001B[0m\n\u001B[1;32m 243\u001B[0m headers[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mUser-Agent\u001B[39m\u001B[38;5;124m\"\u001B[39m] \u001B[38;5;241m=\u001B[39m _get_default_user_agent()\n\u001B[0;32m--> 244\u001B[0m \u001B[38;5;28;43msuper\u001B[39;49m\u001B[43m(\u001B[49m\u001B[43mHTTPConnection\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m)\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrequest\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmethod\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mbody\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mbody\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mheaders\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mheaders\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/http/client.py:1282\u001B[0m, in \u001B[0;36mHTTPConnection.request\u001B[0;34m(self, method, url, body, headers, encode_chunked)\u001B[0m\n\u001B[1;32m 1281\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124;03m\"\"\"Send a complete request to the server.\"\"\"\u001B[39;00m\n\u001B[0;32m-> 1282\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_send_request\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmethod\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mbody\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mheaders\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mencode_chunked\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/http/client.py:1328\u001B[0m, in \u001B[0;36mHTTPConnection._send_request\u001B[0;34m(self, method, url, body, headers, encode_chunked)\u001B[0m\n\u001B[1;32m 1327\u001B[0m body \u001B[38;5;241m=\u001B[39m _encode(body, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mbody\u001B[39m\u001B[38;5;124m'\u001B[39m)\n\u001B[0;32m-> 1328\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mendheaders\u001B[49m\u001B[43m(\u001B[49m\u001B[43mbody\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mencode_chunked\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencode_chunked\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/http/client.py:1277\u001B[0m, in \u001B[0;36mHTTPConnection.endheaders\u001B[0;34m(self, message_body, encode_chunked)\u001B[0m\n\u001B[1;32m 1276\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m CannotSendHeader()\n\u001B[0;32m-> 1277\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_send_output\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmessage_body\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mencode_chunked\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencode_chunked\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/http/client.py:1037\u001B[0m, in \u001B[0;36mHTTPConnection._send_output\u001B[0;34m(self, message_body, encode_chunked)\u001B[0m\n\u001B[1;32m 1036\u001B[0m \u001B[38;5;28;01mdel\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_buffer[:]\n\u001B[0;32m-> 1037\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msend\u001B[49m\u001B[43m(\u001B[49m\u001B[43mmsg\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 1039\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m message_body \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[1;32m 1040\u001B[0m \n\u001B[1;32m 1041\u001B[0m \u001B[38;5;66;03m# create a consistent interface to message_body\u001B[39;00m\n", + "File \u001B[0;32m~/.pyenv/versions/3.10.10/lib/python3.10/http/client.py:975\u001B[0m, in \u001B[0;36mHTTPConnection.send\u001B[0;34m(self, data)\u001B[0m\n\u001B[1;32m 974\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mauto_open:\n\u001B[0;32m--> 975\u001B[0m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mconnect\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 976\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connection.py:205\u001B[0m, in \u001B[0;36mHTTPConnection.connect\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 204\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mconnect\u001B[39m(\u001B[38;5;28mself\u001B[39m):\n\u001B[0;32m--> 205\u001B[0m conn \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_new_conn\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 206\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_prepare_conn(conn)\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connection.py:186\u001B[0m, in \u001B[0;36mHTTPConnection._new_conn\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 185\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m SocketError \u001B[38;5;28;01mas\u001B[39;00m e:\n\u001B[0;32m--> 186\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m NewConnectionError(\n\u001B[1;32m 187\u001B[0m \u001B[38;5;28mself\u001B[39m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mFailed to establish a new connection: \u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m\"\u001B[39m \u001B[38;5;241m%\u001B[39m e\n\u001B[1;32m 188\u001B[0m )\n\u001B[1;32m 190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m conn\n", + "\u001B[0;31mNewConnectionError\u001B[0m: : Failed to establish a new connection: [Errno 61] Connection refused", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001B[0;31mMaxRetryError\u001B[0m Traceback (most recent call last)", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/requests/adapters.py:489\u001B[0m, in \u001B[0;36mHTTPAdapter.send\u001B[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001B[0m\n\u001B[1;32m 488\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m chunked:\n\u001B[0;32m--> 489\u001B[0m resp \u001B[38;5;241m=\u001B[39m \u001B[43mconn\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43murlopen\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m 490\u001B[0m \u001B[43m \u001B[49m\u001B[43mmethod\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mrequest\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmethod\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 491\u001B[0m \u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 492\u001B[0m \u001B[43m \u001B[49m\u001B[43mbody\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mrequest\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mbody\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 493\u001B[0m \u001B[43m \u001B[49m\u001B[43mheaders\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mrequest\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mheaders\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 494\u001B[0m \u001B[43m \u001B[49m\u001B[43mredirect\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 495\u001B[0m \u001B[43m \u001B[49m\u001B[43massert_same_host\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 496\u001B[0m \u001B[43m \u001B[49m\u001B[43mpreload_content\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 497\u001B[0m \u001B[43m \u001B[49m\u001B[43mdecode_content\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\n\u001B[1;32m 498\u001B[0m \u001B[43m \u001B[49m\u001B[43mretries\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmax_retries\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 499\u001B[0m \u001B[43m \u001B[49m\u001B[43mtimeout\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mtimeout\u001B[49m\u001B[43m,\u001B[49m\n\u001B[1;32m 500\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 502\u001B[0m \u001B[38;5;66;03m# Send the request.\u001B[39;00m\n\u001B[1;32m 503\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/connectionpool.py:798\u001B[0m, in \u001B[0;36mHTTPConnectionPool.urlopen\u001B[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001B[0m\n\u001B[1;32m 796\u001B[0m e \u001B[38;5;241m=\u001B[39m ProtocolError(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mConnection aborted.\u001B[39m\u001B[38;5;124m\"\u001B[39m, e)\n\u001B[0;32m--> 798\u001B[0m retries \u001B[38;5;241m=\u001B[39m \u001B[43mretries\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mincrement\u001B[49m\u001B[43m(\u001B[49m\n\u001B[1;32m 799\u001B[0m \u001B[43m \u001B[49m\u001B[43mmethod\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43merror\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43me\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m_pool\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m_stacktrace\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43msys\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mexc_info\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;241;43m2\u001B[39;49m\u001B[43m]\u001B[49m\n\u001B[1;32m 800\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 801\u001B[0m retries\u001B[38;5;241m.\u001B[39msleep()\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/urllib3/util/retry.py:592\u001B[0m, in \u001B[0;36mRetry.increment\u001B[0;34m(self, method, url, response, error, _pool, _stacktrace)\u001B[0m\n\u001B[1;32m 591\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m new_retry\u001B[38;5;241m.\u001B[39mis_exhausted():\n\u001B[0;32m--> 592\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m MaxRetryError(_pool, url, error \u001B[38;5;129;01mor\u001B[39;00m ResponseError(cause))\n\u001B[1;32m 594\u001B[0m log\u001B[38;5;241m.\u001B[39mdebug(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mIncremented Retry for (url=\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m): \u001B[39m\u001B[38;5;132;01m%r\u001B[39;00m\u001B[38;5;124m\"\u001B[39m, url, new_retry)\n", + "\u001B[0;31mMaxRetryError\u001B[0m: HTTPConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /api/v1 (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 61] Connection refused'))", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001B[0;31mConnectionError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[0;32mIn[3], line 6\u001B[0m\n\u001B[1;32m 2\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m \u001B[38;5;21;01mchromadb\u001B[39;00m \u001B[38;5;28;01mimport\u001B[39;00m Settings\n\u001B[1;32m 4\u001B[0m client \u001B[38;5;241m=\u001B[39m chromadb\u001B[38;5;241m.\u001B[39mHttpClient(\n\u001B[1;32m 5\u001B[0m settings\u001B[38;5;241m=\u001B[39mSettings(chroma_client_auth_provider\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtoken\u001B[39m\u001B[38;5;124m\"\u001B[39m, chroma_client_auth_credentials\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtest-token\u001B[39m\u001B[38;5;124m\"\u001B[39m))\n\u001B[0;32m----> 6\u001B[0m \u001B[43mclient\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mheartbeat\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;66;03m# this should work with or without authentication - it is a public endpoint\u001B[39;00m\n\u001B[1;32m 8\u001B[0m client\u001B[38;5;241m.\u001B[39mget_version() \u001B[38;5;66;03m# this should work with or without authentication - it is a public endpoint\u001B[39;00m\n\u001B[1;32m 10\u001B[0m client\u001B[38;5;241m.\u001B[39mlist_collections() \u001B[38;5;66;03m# this is a protected endpoint and requires authentication\u001B[39;00m\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/chromadb/api/fastapi.py:84\u001B[0m, in \u001B[0;36mFastAPI.heartbeat\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 81\u001B[0m \u001B[38;5;129m@override\u001B[39m\n\u001B[1;32m 82\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mheartbeat\u001B[39m(\u001B[38;5;28mself\u001B[39m) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m \u001B[38;5;28mint\u001B[39m:\n\u001B[1;32m 83\u001B[0m \u001B[38;5;250m \u001B[39m\u001B[38;5;124;03m\"\"\"Returns the current server time in nanoseconds to check if the server is alive\"\"\"\u001B[39;00m\n\u001B[0;32m---> 84\u001B[0m resp \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_session\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_api_url\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 85\u001B[0m raise_chroma_error(resp)\n\u001B[1;32m 86\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28mint\u001B[39m(resp\u001B[38;5;241m.\u001B[39mjson()[\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mnanosecond heartbeat\u001B[39m\u001B[38;5;124m\"\u001B[39m])\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/requests/sessions.py:600\u001B[0m, in \u001B[0;36mSession.get\u001B[0;34m(self, url, **kwargs)\u001B[0m\n\u001B[1;32m 592\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124mr\u001B[39m\u001B[38;5;124;03m\"\"\"Sends a GET request. Returns :class:`Response` object.\u001B[39;00m\n\u001B[1;32m 593\u001B[0m \n\u001B[1;32m 594\u001B[0m \u001B[38;5;124;03m:param url: URL for the new :class:`Request` object.\u001B[39;00m\n\u001B[1;32m 595\u001B[0m \u001B[38;5;124;03m:param \\*\\*kwargs: Optional arguments that ``request`` takes.\u001B[39;00m\n\u001B[1;32m 596\u001B[0m \u001B[38;5;124;03m:rtype: requests.Response\u001B[39;00m\n\u001B[1;32m 597\u001B[0m \u001B[38;5;124;03m\"\"\"\u001B[39;00m\n\u001B[1;32m 599\u001B[0m kwargs\u001B[38;5;241m.\u001B[39msetdefault(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mallow_redirects\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28;01mTrue\u001B[39;00m)\n\u001B[0;32m--> 600\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrequest\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43mGET\u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43murl\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/requests/sessions.py:587\u001B[0m, in \u001B[0;36mSession.request\u001B[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001B[0m\n\u001B[1;32m 582\u001B[0m send_kwargs \u001B[38;5;241m=\u001B[39m {\n\u001B[1;32m 583\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mtimeout\u001B[39m\u001B[38;5;124m\"\u001B[39m: timeout,\n\u001B[1;32m 584\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mallow_redirects\u001B[39m\u001B[38;5;124m\"\u001B[39m: allow_redirects,\n\u001B[1;32m 585\u001B[0m }\n\u001B[1;32m 586\u001B[0m send_kwargs\u001B[38;5;241m.\u001B[39mupdate(settings)\n\u001B[0;32m--> 587\u001B[0m resp \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msend\u001B[49m\u001B[43m(\u001B[49m\u001B[43mprep\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43msend_kwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 589\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m resp\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/chromadb/auth/providers.py:123\u001B[0m, in \u001B[0;36mRequestsClientAuthProtocolAdapter._Session.send\u001B[0;34m(self, request, **kwargs)\u001B[0m\n\u001B[1;32m 118\u001B[0m \u001B[38;5;129m@override\u001B[39m\n\u001B[1;32m 119\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21msend\u001B[39m(\n\u001B[1;32m 120\u001B[0m \u001B[38;5;28mself\u001B[39m, request: requests\u001B[38;5;241m.\u001B[39mPreparedRequest, \u001B[38;5;241m*\u001B[39m\u001B[38;5;241m*\u001B[39mkwargs: Any\n\u001B[1;32m 121\u001B[0m ) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m requests\u001B[38;5;241m.\u001B[39mResponse:\n\u001B[1;32m 122\u001B[0m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_protocol_adapter\u001B[38;5;241m.\u001B[39minject_credentials(request)\n\u001B[0;32m--> 123\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;43msuper\u001B[39;49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msend\u001B[49m\u001B[43m(\u001B[49m\u001B[43mrequest\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/requests/sessions.py:701\u001B[0m, in \u001B[0;36mSession.send\u001B[0;34m(self, request, **kwargs)\u001B[0m\n\u001B[1;32m 698\u001B[0m start \u001B[38;5;241m=\u001B[39m preferred_clock()\n\u001B[1;32m 700\u001B[0m \u001B[38;5;66;03m# Send the request\u001B[39;00m\n\u001B[0;32m--> 701\u001B[0m r \u001B[38;5;241m=\u001B[39m \u001B[43madapter\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msend\u001B[49m\u001B[43m(\u001B[49m\u001B[43mrequest\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 703\u001B[0m \u001B[38;5;66;03m# Total elapsed time of the request (approximately)\u001B[39;00m\n\u001B[1;32m 704\u001B[0m elapsed \u001B[38;5;241m=\u001B[39m preferred_clock() \u001B[38;5;241m-\u001B[39m start\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/requests/adapters.py:565\u001B[0m, in \u001B[0;36mHTTPAdapter.send\u001B[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001B[0m\n\u001B[1;32m 561\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28misinstance\u001B[39m(e\u001B[38;5;241m.\u001B[39mreason, _SSLError):\n\u001B[1;32m 562\u001B[0m \u001B[38;5;66;03m# This branch is for urllib3 v1.22 and later.\u001B[39;00m\n\u001B[1;32m 563\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m SSLError(e, request\u001B[38;5;241m=\u001B[39mrequest)\n\u001B[0;32m--> 565\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mConnectionError\u001B[39;00m(e, request\u001B[38;5;241m=\u001B[39mrequest)\n\u001B[1;32m 567\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m ClosedPoolError \u001B[38;5;28;01mas\u001B[39;00m e:\n\u001B[1;32m 568\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mConnectionError\u001B[39;00m(e, request\u001B[38;5;241m=\u001B[39mrequest)\n", + "\u001B[0;31mConnectionError\u001B[0m: HTTPConnectionPool(host='localhost', port=8000): Max retries exceeded with url: /api/v1 (Caused by NewConnectionError(': Failed to establish a new connection: [Errno 61] Connection refused'))" + ] + } + ], + "source": [ + "import chromadb\n", + "from chromadb import Settings\n", + "\n", + "client = chromadb.HttpClient(\n", + " settings=Settings(chroma_client_auth_provider=\"token\", chroma_client_auth_credentials=\"test-token\"))\n", + "client.heartbeat() # this should work with or without authentication - it is a public endpoint\n", + "\n", + "client.get_version() # this should work with or without authentication - it is a public endpoint\n", + "\n", + "client.list_collections() # this is a protected endpoint and requires authentication\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-08-28T16:44:30.289045Z", + "start_time": "2023-08-28T16:44:29.878090Z" + } + }, + "id": "b218beb03ae1582e" + }, + { + "cell_type": "markdown", + "source": [ + "### X-Chroma-Token" + ], + "metadata": { + "collapsed": false + }, + "id": "c8234687c5afe521" + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [ + { + "ename": "Exception", + "evalue": "{\"error\":\"Unauthorized\"}", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mHTTPError\u001B[0m Traceback (most recent call last)", + "File \u001B[0;32m~/PycharmProjects/chroma-core/chromadb/api/fastapi.py:410\u001B[0m, in \u001B[0;36mraise_chroma_error\u001B[0;34m(resp)\u001B[0m\n\u001B[1;32m 409\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[0;32m--> 410\u001B[0m \u001B[43mresp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mraise_for_status\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 411\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m requests\u001B[38;5;241m.\u001B[39mHTTPError:\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/venv/lib/python3.10/site-packages/requests/models.py:1021\u001B[0m, in \u001B[0;36mResponse.raise_for_status\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 1020\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m http_error_msg:\n\u001B[0;32m-> 1021\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m HTTPError(http_error_msg, response\u001B[38;5;241m=\u001B[39m\u001B[38;5;28mself\u001B[39m)\n", + "\u001B[0;31mHTTPError\u001B[0m: 401 Client Error: Unauthorized for url: http://localhost:8000/api/v1/collections", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001B[0;31mException\u001B[0m Traceback (most recent call last)", + "Cell \u001B[0;32mIn[2], line 11\u001B[0m\n\u001B[1;32m 7\u001B[0m client\u001B[38;5;241m.\u001B[39mheartbeat() \u001B[38;5;66;03m# this should work with or without authentication - it is a public endpoint\u001B[39;00m\n\u001B[1;32m 9\u001B[0m client\u001B[38;5;241m.\u001B[39mget_version() \u001B[38;5;66;03m# this should work with or without authentication - it is a public endpoint\u001B[39;00m\n\u001B[0;32m---> 11\u001B[0m \u001B[43mclient\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mlist_collections\u001B[49m\u001B[43m(\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;66;03m# this is a protected endpoint and requires authentication\u001B[39;00m\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/chromadb/api/fastapi.py:92\u001B[0m, in \u001B[0;36mFastAPI.list_collections\u001B[0;34m(self)\u001B[0m\n\u001B[1;32m 90\u001B[0m \u001B[38;5;250m\u001B[39m\u001B[38;5;124;03m\"\"\"Returns a list of all collections\"\"\"\u001B[39;00m\n\u001B[1;32m 91\u001B[0m resp \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_session\u001B[38;5;241m.\u001B[39mget(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_api_url \u001B[38;5;241m+\u001B[39m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124m/collections\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[0;32m---> 92\u001B[0m \u001B[43mraise_chroma_error\u001B[49m\u001B[43m(\u001B[49m\u001B[43mresp\u001B[49m\u001B[43m)\u001B[49m\n\u001B[1;32m 93\u001B[0m json_collections \u001B[38;5;241m=\u001B[39m resp\u001B[38;5;241m.\u001B[39mjson()\n\u001B[1;32m 94\u001B[0m collections \u001B[38;5;241m=\u001B[39m []\n", + "File \u001B[0;32m~/PycharmProjects/chroma-core/chromadb/api/fastapi.py:412\u001B[0m, in \u001B[0;36mraise_chroma_error\u001B[0;34m(resp)\u001B[0m\n\u001B[1;32m 410\u001B[0m resp\u001B[38;5;241m.\u001B[39mraise_for_status()\n\u001B[1;32m 411\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m requests\u001B[38;5;241m.\u001B[39mHTTPError:\n\u001B[0;32m--> 412\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m (\u001B[38;5;167;01mException\u001B[39;00m(resp\u001B[38;5;241m.\u001B[39mtext))\n", + "\u001B[0;31mException\u001B[0m: {\"error\":\"Unauthorized\"}" + ] + } + ], + "source": [ + "import chromadb\n", + "from chromadb import Settings\n", + "\n", + "client = chromadb.HttpClient(\n", + " settings=Settings(chroma_client_auth_provider=\"token\", chroma_client_auth_credentials=\"test-token\",\n", + " chroma_client_auth_token_transport_header=\"X_CHROMA_TOKEN\"))\n", + "client.heartbeat() # this should work with or without authentication - it is a public endpoint\n", + "\n", + "client.get_version() # this should work with or without authentication - it is a public endpoint\n", + "\n", + "client.list_collections() # this is a protected endpoint and requires authentication" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-08-28T14:25:12.858416Z", + "start_time": "2023-08-28T14:25:12.629618Z" + } + }, + "id": "93485c3175d1e2c7" + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + }, + "id": "29d28a25e85f95af" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/basic_functionality/in_not_in_filtering.ipynb b/examples/basic_functionality/in_not_in_filtering.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..3076d4a3585cea66ec3e1cc64e3df43480dc82a7 --- /dev/null +++ b/examples/basic_functionality/in_not_in_filtering.ipynb @@ -0,0 +1,149 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "initial_id", + "metadata": { + "collapsed": true, + "ExecuteTime": { + "end_time": "2023-08-30T12:48:38.227653Z", + "start_time": "2023-08-30T12:48:27.744069Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Number of requested results 10 is greater than number of elements in index 3, updating n_results = 3\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'ids': [['1', '3']], 'distances': [[0.28824201226234436, 1.017508625984192]], 'metadatas': [[{'author': 'john'}, {'author': 'jill'}]], 'embeddings': None, 'documents': [['Article by john', 'Article by Jill']]}\n", + "{'ids': ['1', '3'], 'embeddings': None, 'metadatas': [{'author': 'john'}, {'author': 'jill'}], 'documents': ['Article by john', 'Article by Jill']}\n" + ] + } + ], + "source": [ + "import chromadb\n", + "\n", + "from chromadb.utils import embedding_functions\n", + "\n", + "sentence_transformer_ef = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=\"all-MiniLM-L6-v2\")\n", + "\n", + "\n", + "client = chromadb.Client()\n", + "# client.heartbeat()\n", + "# client.reset()\n", + "collection = client.get_or_create_collection(\"test-where-list\", embedding_function=sentence_transformer_ef)\n", + "collection.add(documents=[\"Article by john\", \"Article by Jack\", \"Article by Jill\"],\n", + " metadatas=[{\"author\": \"john\"}, {\"author\": \"jack\"}, {\"author\": \"jill\"}], ids=[\"1\", \"2\", \"3\"])\n", + "\n", + "query = [\"Give me articles by john\"]\n", + "res = collection.query(query_texts=query,where={'author': {'$in': ['john', 'jill']}}, n_results=10)\n", + "print(res)\n", + "\n", + "res_get = collection.get(where={'author': {'$in': ['john', 'jill']}})\n", + "print(res_get)\n" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Interactions with existing Where operators" + ], + "metadata": { + "collapsed": false + }, + "id": "752cef843ba2f900" + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [ + { + "data": { + "text/plain": "{'ids': [['1']],\n 'distances': [[0.28824201226234436]],\n 'metadatas': [[{'article_type': 'blog', 'author': 'john'}]],\n 'embeddings': None,\n 'documents': [['Article by john']]}" + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "collection.upsert(documents=[\"Article by john\", \"Article by Jack\", \"Article by Jill\"],\n", + " metadatas=[{\"author\": \"john\",\"article_type\":\"blog\"}, {\"author\": \"jack\",\"article_type\":\"social\"}, {\"author\": \"jill\",\"article_type\":\"paper\"}], ids=[\"1\", \"2\", \"3\"])\n", + "\n", + "collection.query(query_texts=query,where={\"$and\":[{\"author\": {'$in': ['john', 'jill']}},{\"article_type\":{\"$eq\":\"blog\"}}]}, n_results=3)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-08-30T12:48:49.974353Z", + "start_time": "2023-08-30T12:48:49.938985Z" + } + }, + "id": "ca56cda318f9e94d" + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "data": { + "text/plain": "{'ids': [['1', '3']],\n 'distances': [[0.28824201226234436, 1.017508625984192]],\n 'metadatas': [[{'article_type': 'blog', 'author': 'john'},\n {'article_type': 'paper', 'author': 'jill'}]],\n 'embeddings': None,\n 'documents': [['Article by john', 'Article by Jill']]}" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "collection.query(query_texts=query,where={\"$or\":[{\"author\": {'$in': ['john']}},{\"article_type\":{\"$in\":[\"paper\"]}}]}, n_results=3)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2023-08-30T12:48:53.501431Z", + "start_time": "2023-08-30T12:48:53.481571Z" + } + }, + "id": "f10e79ec90c797c1" + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + }, + "id": "d97b8b6dd96261d0" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/examples/basic_functionality/local_persistence.ipynb b/examples/basic_functionality/local_persistence.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..e05d638824c4cc949d1a83eff1308cab66272a24 --- /dev/null +++ b/examples/basic_functionality/local_persistence.ipynb @@ -0,0 +1,188 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Local Peristence Demo\n", + "This notebook demonstrates how to configure Chroma to persist to disk, then load it back in. " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import chromadb" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new Chroma client with persistence enabled. \n", + "persist_directory = \"db\"\n", + "\n", + "client = chromadb.PersistentClient(path=persist_directory)\n", + "\n", + "# Create a new chroma collection\n", + "collection_name = \"peristed_collection\"\n", + "collection = client.get_or_create_collection(name=collection_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Add some data to the collection\n", + "collection.add(\n", + " embeddings=[\n", + " [1.1, 2.3, 3.2],\n", + " [4.5, 6.9, 4.4],\n", + " [1.1, 2.3, 3.2],\n", + " [4.5, 6.9, 4.4],\n", + " [1.1, 2.3, 3.2],\n", + " [4.5, 6.9, 4.4],\n", + " [1.1, 2.3, 3.2],\n", + " [4.5, 6.9, 4.4],\n", + " ],\n", + " metadatas=[\n", + " {\"uri\": \"img1.png\", \"style\": \"style1\"},\n", + " {\"uri\": \"img2.png\", \"style\": \"style2\"},\n", + " {\"uri\": \"img3.png\", \"style\": \"style1\"},\n", + " {\"uri\": \"img4.png\", \"style\": \"style1\"},\n", + " {\"uri\": \"img5.png\", \"style\": \"style1\"},\n", + " {\"uri\": \"img6.png\", \"style\": \"style1\"},\n", + " {\"uri\": \"img7.png\", \"style\": \"style1\"},\n", + " {\"uri\": \"img8.png\", \"style\": \"style1\"},\n", + " ],\n", + " documents=[\"doc1\", \"doc2\", \"doc3\", \"doc4\", \"doc5\", \"doc6\", \"doc7\", \"doc8\"],\n", + " ids=[\"id1\", \"id2\", \"id3\", \"id4\", \"id5\", \"id6\", \"id7\", \"id8\"],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new client with the same settings\n", + "client = chromadb.PersistentClient(path=persist_directory)\n", + "\n", + "# Load the collection\n", + "collection = client.get_collection(collection_name)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'ids': [['id1']], 'distances': [[5.1159076593562386e-15]], 'metadatas': [[{'style': 'style1', 'uri': 'img1.png'}]], 'embeddings': None, 'documents': [['doc1']]}\n" + ] + } + ], + "source": [ + "# Query the collection\n", + "results = collection.query(\n", + " query_embeddings=[[1.1, 2.3, 3.2]],\n", + " n_results=1\n", + ")\n", + "\n", + "print(results)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': ['id1', 'id2', 'id3', 'id4', 'id5', 'id6', 'id7', 'id8'],\n", + " 'embeddings': [[1.100000023841858, 2.299999952316284, 3.200000047683716],\n", + " [4.5, 6.900000095367432, 4.400000095367432],\n", + " [1.100000023841858, 2.299999952316284, 3.200000047683716],\n", + " [4.5, 6.900000095367432, 4.400000095367432],\n", + " [1.100000023841858, 2.299999952316284, 3.200000047683716],\n", + " [4.5, 6.900000095367432, 4.400000095367432],\n", + " [1.100000023841858, 2.299999952316284, 3.200000047683716],\n", + " [4.5, 6.900000095367432, 4.400000095367432]],\n", + " 'metadatas': [{'style': 'style1', 'uri': 'img1.png'},\n", + " {'style': 'style2', 'uri': 'img2.png'},\n", + " {'style': 'style1', 'uri': 'img3.png'},\n", + " {'style': 'style1', 'uri': 'img4.png'},\n", + " {'style': 'style1', 'uri': 'img5.png'},\n", + " {'style': 'style1', 'uri': 'img6.png'},\n", + " {'style': 'style1', 'uri': 'img7.png'},\n", + " {'style': 'style1', 'uri': 'img8.png'}],\n", + " 'documents': ['doc1', 'doc2', 'doc3', 'doc4', 'doc5', 'doc6', 'doc7', 'doc8']}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "collection.get(include=[\"embeddings\", \"metadatas\", \"documents\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "# Clean up\n", + "! rm -rf db" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "chroma", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.8" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "88f09714c9334832bac29166716f9f6a879ee2a4ed4822c1d4120cb2393b58dd" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/basic_functionality/start_here.ipynb b/examples/basic_functionality/start_here.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..1487e491a5ae3680f0bdd5991e618fc50bca04c0 --- /dev/null +++ b/examples/basic_functionality/start_here.ipynb @@ -0,0 +1,268 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Basic embedding retrieval with Chroma\n", + "\n", + "This notebook demonstrates the most basic use of Chroma to store and retrieve information using embeddings. This core building block is at the heart of many powerful AI applications.\n", + "\n", + "## What are embeddings?\n", + "\n", + "Embeddings are the A.I-native way to represent any kind of data, making them the perfect fit for working with all kinds of A.I-powered tools and algorithms. They can represent text, images, and soon audio and video.\n", + "\n", + "To create an embedding, data is fed into an embedding model, which outputs vectors of numbers. The model is trained in such a way that 'similar' data, e.g. text with similar meanings, or images with similar content, will produce vectors which are nearer to one another, than those which are dissimilar.\n", + "\n", + "## Embeddings and retrieval\n", + "\n", + "We can use the similarity property of embeddings to search for and retrieve information. For example, we can find documents relevant to a particular topic, or images similar to a given image. Rather than searching for keywords or tags, we can search by finding data with similar semantic meaning.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "%pip install -Uq chromadb numpy datasets tqdm ipywidgets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example Dataset\n", + "\n", + "As a demonstration we use the [SciQ dataset](https://arxiv.org/abs/1707.06209), available from [HuggingFace](https://huggingface.co/datasets/sciq).\n", + "\n", + "Dataset description, from HuggingFace:\n", + "\n", + "> The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided.\n", + "\n", + "In this notebook, we will demonstrate how to retrieve supporting evidence for a given question.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of questions with support: 10481\n" + ] + } + ], + "source": [ + "# Get the SciQ dataset from HuggingFace\n", + "from datasets import load_dataset\n", + "\n", + "dataset = load_dataset(\"sciq\", split=\"train\")\n", + "\n", + "# Filter the dataset to only include questions with a support\n", + "dataset = dataset.filter(lambda x: x[\"support\"] != \"\")\n", + "\n", + "print(\"Number of questions with support: \", len(dataset))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Loading the data into Chroma\n", + "\n", + "Chroma comes with a built-in embedding model, which makes it simple to load text. \n", + "We can load the SciQ dataset into Chroma with just a few lines of code.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Import Chroma and instantiate a client. The default Chroma client is ephemeral, meaning it will not save to disk.\n", + "import chromadb\n", + "\n", + "client = chromadb.Client()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Create a new Chroma collection to store the supporting evidence. We don't need to specify an embedding fuction, and the default will be used.\n", + "collection = client.create_collection(\"sciq_supports\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "6a36ed0079c34128bb4c007feacc6ad1", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Adding documents: 0%| | 0/11 [00:00 Note: Logical operators can be nested" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-11T18:45:52.663345Z", + "start_time": "2023-08-11T18:42:50.970414Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': ['1', '2'],\n", + " 'embeddings': None,\n", + " 'metadatas': [{'author': 'john'}, {'author': 'jack'}],\n", + " 'documents': ['Article by john', 'Article by Jack'],\n", + " 'uris': None,\n", + " 'data': None}" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Or Logical Operator Filtering\n", + "# import chromadb\n", + "client = chromadb.Client()\n", + "collection = client.get_or_create_collection(\"test-where-list\")\n", + "collection.add(documents=[\"Article by john\", \"Article by Jack\", \"Article by Jill\"],\n", + " metadatas=[{\"author\": \"john\"}, {\"author\": \"jack\"}, {\"author\": \"jill\"}], ids=[\"1\", \"2\", \"3\"])\n", + "\n", + "collection.get(where={\"$or\": [{\"author\": \"john\"}, {\"author\": \"jack\"}]})\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-11T18:49:31.174811Z", + "start_time": "2023-08-11T18:49:31.056618Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': ['1'],\n", + " 'embeddings': None,\n", + " 'metadatas': [{'author': 'john', 'category': 'chroma'}],\n", + " 'documents': ['Article by john'],\n", + " 'uris': None,\n", + " 'data': None}" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# And Logical Operator Filtering\n", + "collection = client.get_or_create_collection(\"test-where-list\")\n", + "collection.upsert(documents=[\"Article by john\", \"Article by Jack\", \"Article by Jill\"],\n", + " metadatas=[{\"author\": \"john\",\"category\":\"chroma\"}, {\"author\": \"jack\",\"category\":\"ml\"}, {\"author\": \"jill\",\"category\":\"lifestyle\"}], ids=[\"1\", \"2\", \"3\"])\n", + "collection.get(where={\"$and\": [{\"category\": \"chroma\"}, {\"author\": \"john\"}]})" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-11T18:49:35.758816Z", + "start_time": "2023-08-11T18:49:35.741477Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': [],\n", + " 'embeddings': None,\n", + " 'metadatas': [],\n", + " 'documents': [],\n", + " 'uris': None,\n", + " 'data': None}" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# And logical that doesn't match anything\n", + "collection.get(where={\"$and\": [{\"category\": \"chroma\"}, {\"author\": \"jill\"}]})" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-11T18:49:40.463045Z", + "start_time": "2023-08-11T18:49:40.450240Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': ['1'],\n", + " 'embeddings': None,\n", + " 'metadatas': [{'author': 'john', 'category': 'chroma'}],\n", + " 'documents': ['Article by john'],\n", + " 'uris': None,\n", + " 'data': None}" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Combined And and Or Logical Operator Filtering\n", + "collection.get(where={\"$and\": [{\"category\": \"chroma\"}, {\"$or\": [{\"author\": \"john\"}, {\"author\": \"jack\"}]}]})" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "ExecuteTime": { + "end_time": "2023-08-11T18:51:12.328062Z", + "start_time": "2023-08-11T18:51:12.315943Z" + }, + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': ['1'],\n", + " 'embeddings': None,\n", + " 'metadatas': [{'author': 'john', 'category': 'chroma'}],\n", + " 'documents': ['Article by john'],\n", + " 'uris': None,\n", + " 'data': None}" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "collection.get(where_document={\"$contains\": \"Article\"},where={\"$and\": [{\"category\": \"chroma\"}, {\"$or\": [{\"author\": \"john\"}, {\"author\": \"jack\"}]}]})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.6" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "2395417914bce3169eff793a7d01bf858f95b138000d8d354eed93ead856f5e6" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/chat_with_your_documents/README.md b/examples/chat_with_your_documents/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f9e31e71652a76cacd8275cbadfb857e4232798e --- /dev/null +++ b/examples/chat_with_your_documents/README.md @@ -0,0 +1,53 @@ +# Chat with your documents + +This folder contains a (very) minimal, self-contained example of how to make an application to chat with your documents, using Chroma and OpenAI's API. +It uses the 2022 and 2023 U.S state of the union addresses as example documents. + +## How it works + +The basic flow is as follows: + +0. The text documents in the `documents` folder are loaded line by line, then embedded and stored in a Chroma collection. + +1. When the user submits a question, it gets embedded using the same model as the documents, and the lines most relevant to the query are retrieved by Chroma. +2. The user-submitted question is passed to OpenAI's API, along with the extra context retrieved by Chroma. The OpenAI API generates generates a response. +3. The response is displayed to the user, along with the lines used as extra context. + +## Running the example + +You will need an OpenAI API key to run this demo. You can [get one here](https://platform.openai.com/account/api-keys). + +Install dependencies and run the example: + +```bash +# Install dependencies +pip install -r requirements.txt + +# Load the example documents into Chroma +python load_data.py + +# Run the chatbot +python main.py +``` + +Example output: + +``` +Query: What was said about the pandemic? + +Thinking... + +Based on the given context, several points were made about the pandemic. First, it is described as punishing, indicating the severity and impact it had on various aspects of life. It is mentioned that schools were closed and everything was being shut down in response to the COVID crisis, suggesting the significant measures taken to combat the virus. + +The context then shifts to discussing the progress made in the fight against the pandemic itself. While no specific details are provided, it is implied that there has been progress, though the extent of it is unclear. + +Additionally, it is stated that children were already facing struggles before the pandemic, such as bullying, violence, trauma, and the negative effects of social media. This suggests that these issues were likely exacerbated by the pandemic. + +The context then mentions a spike in violent crime in 2020, which is attributed to the first year of the pandemic. This implies that there was an increase in violent crime during that time period, but the underlying causes or specific details are not provided. + +Lastly, it is mentioned that the pandemic also disrupted global supply chains. Again, no specific details are given, but this suggests that the pandemic had negative effects on the movement and availability of goods and resources at a global level. + +In conclusion, based on the provided context, it is stated that the pandemic has been punishing and has resulted in the closure of schools and the shutdown of various activities. Progress is mentioned in fighting against the pandemic, though the specifics are not given. The pandemic is also said to have worsened pre-existing issues such as bullying and violence among children, and disrupted global supply chains. +``` + +You can replace the example text documents in the `documents` folder with your own documents, and the chatbot will use those instead. diff --git a/examples/chat_with_your_documents/documents/state_of_the_union_2022.txt b/examples/chat_with_your_documents/documents/state_of_the_union_2022.txt new file mode 100644 index 0000000000000000000000000000000000000000..7cb2a02c313d8d11cea68eda148946abed32eaa9 --- /dev/null +++ b/examples/chat_with_your_documents/documents/state_of_the_union_2022.txt @@ -0,0 +1,723 @@ +Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans. + +Last year COVID-19 kept us apart. This year we are finally together again. + +Tonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. + +With a duty to one another to the American people to the Constitution. + +And with an unwavering resolve that freedom will always triumph over tyranny. + +Six days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated. + +He thought he could roll into Ukraine and the world would roll over. Instead he met a wall of strength he never imagined. + +He met the Ukrainian people. + +From President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world. + +Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. + +In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. + +Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world. + +Please rise if you are able and show that, Yes, we the United States of America stand with the Ukrainian people. + +Throughout our history we’ve learned this lesson when dictators do not pay a price for their aggression they cause more chaos. + +They keep moving. + +And the costs and the threats to America and the world keep rising. + +That’s why the NATO Alliance was created to secure peace and stability in Europe after World War 2. + +The United States is a member along with 29 other nations. + +It matters. American diplomacy matters. American resolve matters. + +Putin’s latest attack on Ukraine was premeditated and unprovoked. + +He rejected repeated efforts at diplomacy. + +He thought the West and NATO wouldn’t respond. And he thought he could divide us at home. Putin was wrong. We were ready. Here is what we did. + +We prepared extensively and carefully. + +We spent months building a coalition of other freedom-loving nations from Europe and the Americas to Asia and Africa to confront Putin. + +I spent countless hours unifying our European allies. We shared with the world in advance what we knew Putin was planning and precisely how he would try to falsely justify his aggression. + +We countered Russia’s lies with truth. + +And now that he has acted the free world is holding him accountable. + +Along with twenty-seven members of the European Union including France, Germany, Italy, as well as countries like the United Kingdom, Canada, Japan, Korea, Australia, New Zealand, and many others, even Switzerland. + +We are inflicting pain on Russia and supporting the people of Ukraine. Putin is now isolated from the world more than ever. + +Together with our allies –we are right now enforcing powerful economic sanctions. + +We are cutting off Russia’s largest banks from the international financial system. + +Preventing Russia’s central bank from defending the Russian Ruble making Putin’s $630 Billion “war fund” worthless. + +We are choking off Russia’s access to technology that will sap its economic strength and weaken its military for years to come. + +Tonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more. + +The U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs. + +We are joining with our European allies to find and seize your yachts your luxury apartments your private jets. We are coming for your ill-begotten gains. + +And tonight I am announcing that we will join our allies in closing off American air space to all Russian flights – further isolating Russia – and adding an additional squeeze –on their economy. The Ruble has lost 30% of its value. + +The Russian stock market has lost 40% of its value and trading remains suspended. Russia’s economy is reeling and Putin alone is to blame. + +Together with our allies we are providing support to the Ukrainians in their fight for freedom. Military assistance. Economic assistance. Humanitarian assistance. + +We are giving more than $1 Billion in direct assistance to Ukraine. + +And we will continue to aid the Ukrainian people as they defend their country and to help ease their suffering. + +Let me be clear, our forces are not engaged and will not engage in conflict with Russian forces in Ukraine. + +Our forces are not going to Europe to fight in Ukraine, but to defend our NATO Allies – in the event that Putin decides to keep moving west. + +For that purpose we’ve mobilized American ground forces, air squadrons, and ship deployments to protect NATO countries including Poland, Romania, Latvia, Lithuania, and Estonia. + +As I have made crystal clear the United States and our Allies will defend every inch of territory of NATO countries with the full force of our collective power. + +And we remain clear-eyed. The Ukrainians are fighting back with pure courage. But the next few days weeks, months, will be hard on them. + +Putin has unleashed violence and chaos. But while he may make gains on the battlefield – he will pay a continuing high price over the long run. + +And a proud Ukrainian people, who have known 30 years of independence, have repeatedly shown that they will not tolerate anyone who tries to take their country backwards. + +To all Americans, I will be honest with you, as I’ve always promised. A Russian dictator, invading a foreign country, has costs around the world. + +And I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. + +Tonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world. + +America will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies. + +These steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming. + +But I want you to know that we are going to be okay. + +When the history of this era is written Putin’s war on Ukraine will have left Russia weaker and the rest of the world stronger. + +While it shouldn’t have taken something so terrible for people around the world to see what’s at stake now everyone sees it clearly. + +We see the unity among leaders of nations and a more unified Europe a more unified West. And we see unity among the people who are gathering in cities in large crowds around the world even in Russia to demonstrate their support for Ukraine. + +In the battle between democracy and autocracy, democracies are rising to the moment, and the world is clearly choosing the side of peace and security. + +This is a real test. It’s going to take time. So let us continue to draw inspiration from the iron will of the Ukrainian people. + +To our fellow Ukrainian Americans who forge a deep bond that connects our two nations we stand with you. + +Putin may circle Kyiv with tanks, but he will never gain the hearts and souls of the Ukrainian people. + +He will never extinguish their love of freedom. He will never weaken the resolve of the free world. + +We meet tonight in an America that has lived through two of the hardest years this nation has ever faced. + +The pandemic has been punishing. + +And so many families are living paycheck to paycheck, struggling to keep up with the rising cost of food, gas, housing, and so much more. + +I understand. + +I remember when my Dad had to leave our home in Scranton, Pennsylvania to find work. I grew up in a family where if the price of food went up, you felt it. + +That’s why one of the first things I did as President was fight to pass the American Rescue Plan. + +Because people were hurting. We needed to act, and we did. + +Few pieces of legislation have done more in a critical moment in our history to lift us out of crisis. + +It fueled our efforts to vaccinate the nation and combat COVID-19. It delivered immediate economic relief for tens of millions of Americans. + +Helped put food on their table, keep a roof over their heads, and cut the cost of health insurance. + +And as my Dad used to say, it gave people a little breathing room. + +And unlike the $2 Trillion tax cut passed in the previous administration that benefitted the top 1% of Americans, the American Rescue Plan helped working people—and left no one behind. + +And it worked. It created jobs. Lots of jobs. + +In fact—our economy created over 6.5 Million new jobs just last year, more jobs created in one year +than ever before in the history of America. + +Our economy grew at a rate of 5.7% last year, the strongest growth in nearly 40 years, the first step in bringing fundamental change to an economy that hasn’t worked for the working people of this nation for too long. + +For the past 40 years we were told that if we gave tax breaks to those at the very top, the benefits would trickle down to everyone else. + +But that trickle-down theory led to weaker economic growth, lower wages, bigger deficits, and the widest gap between those at the top and everyone else in nearly a century. + +Vice President Harris and I ran for office with a new economic vision for America. + +Invest in America. Educate Americans. Grow the workforce. Build the economy from the bottom up +and the middle out, not from the top down. + +Because we know that when the middle class grows, the poor have a ladder up and the wealthy do very well. + +America used to have the best roads, bridges, and airports on Earth. + +Now our infrastructure is ranked 13th in the world. + +We won’t be able to compete for the jobs of the 21st Century if we don’t fix that. + +That’s why it was so important to pass the Bipartisan Infrastructure Law—the most sweeping investment to rebuild America in history. + +This was a bipartisan effort, and I want to thank the members of both parties who worked to make it happen. + +We’re done talking about infrastructure weeks. + +We’re going to have an infrastructure decade. + +It is going to transform America and put us on a path to win the economic competition of the 21st Century that we face with the rest of the world—particularly with China. + +As I’ve told Xi Jinping, it is never a good bet to bet against the American people. + +We’ll create good jobs for millions of Americans, modernizing roads, airports, ports, and waterways all across America. + +And we’ll do it all to withstand the devastating effects of the climate crisis and promote environmental justice. + +We’ll build a national network of 500,000 electric vehicle charging stations, begin to replace poisonous lead pipes—so every child—and every American—has clean water to drink at home and at school, provide affordable high-speed internet for every American—urban, suburban, rural, and tribal communities. + +4,000 projects have already been announced. + +And tonight, I’m announcing that this year we will start fixing over 65,000 miles of highway and 1,500 bridges in disrepair. + +When we use taxpayer dollars to rebuild America – we are going to Buy American: buy American products to support American jobs. + +The federal government spends about $600 Billion a year to keep the country safe and secure. + +There’s been a law on the books for almost a century +to make sure taxpayers’ dollars support American jobs and businesses. + +Every Administration says they’ll do it, but we are actually doing it. + +We will buy American to make sure everything from the deck of an aircraft carrier to the steel on highway guardrails are made in America. + +But to compete for the best jobs of the future, we also need to level the playing field with China and other competitors. + +That’s why it is so important to pass the Bipartisan Innovation Act sitting in Congress that will make record investments in emerging technologies and American manufacturing. + +Let me give you one example of why it’s so important to pass it. + +If you travel 20 miles east of Columbus, Ohio, you’ll find 1,000 empty acres of land. + +It won’t look like much, but if you stop and look closely, you’ll see a “Field of dreams,” the ground on which America’s future will be built. + +This is where Intel, the American company that helped build Silicon Valley, is going to build its $20 billion semiconductor “mega site”. + +Up to eight state-of-the-art factories in one place. 10,000 new good-paying jobs. + +Some of the most sophisticated manufacturing in the world to make computer chips the size of a fingertip that power the world and our everyday lives. + +Smartphones. The Internet. Technology we have yet to invent. + +But that’s just the beginning. + +Intel’s CEO, Pat Gelsinger, who is here tonight, told me they are ready to increase their investment from +$20 billion to $100 billion. + +That would be one of the biggest investments in manufacturing in American history. + +And all they’re waiting for is for you to pass this bill. + +So let’s not wait any longer. Send it to my desk. I’ll sign it. + +And we will really take off. + +And Intel is not alone. + +There’s something happening in America. + +Just look around and you’ll see an amazing story. + +The rebirth of the pride that comes from stamping products “Made In America.” The revitalization of American manufacturing. + +Companies are choosing to build new factories here, when just a few years ago, they would have built them overseas. + +That’s what is happening. Ford is investing $11 billion to build electric vehicles, creating 11,000 jobs across the country. + +GM is making the largest investment in its history—$7 billion to build electric vehicles, creating 4,000 jobs in Michigan. + +All told, we created 369,000 new manufacturing jobs in America just last year. + +Powered by people I’ve met like JoJo Burgess, from generations of union steelworkers from Pittsburgh, who’s here with us tonight. + +As Ohio Senator Sherrod Brown says, “It’s time to bury the label “Rust Belt.” + +It’s time. + +But with all the bright spots in our economy, record job growth and higher wages, too many families are struggling to keep up with the bills. + +Inflation is robbing them of the gains they might otherwise feel. + +I get it. That’s why my top priority is getting prices under control. + +Look, our economy roared back faster than most predicted, but the pandemic meant that businesses had a hard time hiring enough workers to keep up production in their factories. + +The pandemic also disrupted global supply chains. + +When factories close, it takes longer to make goods and get them from the warehouse to the store, and prices go up. + +Look at cars. + +Last year, there weren’t enough semiconductors to make all the cars that people wanted to buy. + +And guess what, prices of automobiles went up. + +So—we have a choice. + +One way to fight inflation is to drive down wages and make Americans poorer. + +I have a better plan to fight inflation. + +Lower your costs, not your wages. + +Make more cars and semiconductors in America. + +More infrastructure and innovation in America. + +More goods moving faster and cheaper in America. + +More jobs where you can earn a good living in America. + +And instead of relying on foreign supply chains, let’s make it in America. + +Economists call it “increasing the productive capacity of our economy.” + +I call it building a better America. + +My plan to fight inflation will lower your costs and lower the deficit. + +17 Nobel laureates in economics say my plan will ease long-term inflationary pressures. Top business leaders and most Americans support my plan. And here’s the plan: + +First – cut the cost of prescription drugs. Just look at insulin. One in ten Americans has diabetes. In Virginia, I met a 13-year-old boy named Joshua Davis. + +He and his Dad both have Type 1 diabetes, which means they need insulin every day. Insulin costs about $10 a vial to make. + +But drug companies charge families like Joshua and his Dad up to 30 times more. I spoke with Joshua’s mom. + +Imagine what it’s like to look at your child who needs insulin and have no idea how you’re going to pay for it. + +What it does to your dignity, your ability to look your child in the eye, to be the parent you expect to be. + +Joshua is here with us tonight. Yesterday was his birthday. Happy birthday, buddy. + +For Joshua, and for the 200,000 other young people with Type 1 diabetes, let’s cap the cost of insulin at $35 a month so everyone can afford it. + +Drug companies will still do very well. And while we’re at it let Medicare negotiate lower prices for prescription drugs, like the VA already does. + +Look, the American Rescue Plan is helping millions of families on Affordable Care Act plans save $2,400 a year on their health care premiums. Let’s close the coverage gap and make those savings permanent. + +Second – cut energy costs for families an average of $500 a year by combatting climate change. + +Let’s provide investments and tax credits to weatherize your homes and businesses to be energy efficient and you get a tax credit; double America’s clean energy production in solar, wind, and so much more; lower the price of electric vehicles, saving you another $80 a month because you’ll never have to pay at the gas pump again. + +Third – cut the cost of child care. Many families pay up to $14,000 a year for child care per child. + +Middle-class and working families shouldn’t have to pay more than 7% of their income for care of young children. + +My plan will cut the cost in half for most families and help parents, including millions of women, who left the workforce during the pandemic because they couldn’t afford child care, to be able to get back to work. + +My plan doesn’t stop there. It also includes home and long-term care. More affordable housing. And Pre-K for every 3- and 4-year-old. + +All of these will lower costs. + +And under my plan, nobody earning less than $400,000 a year will pay an additional penny in new taxes. Nobody. + +The one thing all Americans agree on is that the tax system is not fair. We have to fix it. + +I’m not looking to punish anyone. But let’s make sure corporations and the wealthiest Americans start paying their fair share. + +Just last year, 55 Fortune 500 corporations earned $40 billion in profits and paid zero dollars in federal income tax. + +That’s simply not fair. That’s why I’ve proposed a 15% minimum tax rate for corporations. + +We got more than 130 countries to agree on a global minimum tax rate so companies can’t get out of paying their taxes at home by shipping jobs and factories overseas. + +That’s why I’ve proposed closing loopholes so the very wealthy don’t pay a lower tax rate than a teacher or a firefighter. + +So that’s my plan. It will grow the economy and lower costs for families. + +So what are we waiting for? Let’s get this done. And while you’re at it, confirm my nominees to the Federal Reserve, which plays a critical role in fighting inflation. + +My plan will not only lower costs to give families a fair shot, it will lower the deficit. + +The previous Administration not only ballooned the deficit with tax cuts for the very wealthy and corporations, it undermined the watchdogs whose job was to keep pandemic relief funds from being wasted. + +But in my administration, the watchdogs have been welcomed back. + +We’re going after the criminals who stole billions in relief money meant for small businesses and millions of Americans. + +And tonight, I’m announcing that the Justice Department will name a chief prosecutor for pandemic fraud. + +By the end of this year, the deficit will be down to less than half what it was before I took office. + +The only president ever to cut the deficit by more than one trillion dollars in a single year. + +Lowering your costs also means demanding more competition. + +I’m a capitalist, but capitalism without competition isn’t capitalism. + +It’s exploitation—and it drives up prices. + +When corporations don’t have to compete, their profits go up, your prices go up, and small businesses and family farmers and ranchers go under. + +We see it happening with ocean carriers moving goods in and out of America. + +During the pandemic, these foreign-owned companies raised prices by as much as 1,000% and made record profits. + +Tonight, I’m announcing a crackdown on these companies overcharging American businesses and consumers. + +And as Wall Street firms take over more nursing homes, quality in those homes has gone down and costs have gone up. + +That ends on my watch. + +Medicare is going to set higher standards for nursing homes and make sure your loved ones get the care they deserve and expect. + +We’ll also cut costs and keep the economy going strong by giving workers a fair shot, provide more training and apprenticeships, hire them based on their skills not degrees. + +Let’s pass the Paycheck Fairness Act and paid leave. + +Raise the minimum wage to $15 an hour and extend the Child Tax Credit, so no one has to raise a family in poverty. + +Let’s increase Pell Grants and increase our historic support of HBCUs, and invest in what Jill—our First Lady who teaches full-time—calls America’s best-kept secret: community colleges. + +And let’s pass the PRO Act when a majority of workers want to form a union—they shouldn’t be stopped. + +When we invest in our workers, when we build the economy from the bottom up and the middle out together, we can do something we haven’t done in a long time: build a better America. + +For more than two years, COVID-19 has impacted every decision in our lives and the life of the nation. + +And I know you’re tired, frustrated, and exhausted. + +But I also know this. + +Because of the progress we’ve made, because of your resilience and the tools we have, tonight I can say +we are moving forward safely, back to more normal routines. + +We’ve reached a new moment in the fight against COVID-19, with severe cases down to a level not seen since last July. + +Just a few days ago, the Centers for Disease Control and Prevention—the CDC—issued new mask guidelines. + +Under these new guidelines, most Americans in most of the country can now be mask free. + +And based on the projections, more of the country will reach that point across the next couple of weeks. + +Thanks to the progress we have made this past year, COVID-19 need no longer control our lives. + +I know some are talking about “living with COVID-19”. Tonight – I say that we will never just accept living with COVID-19. + +We will continue to combat the virus as we do other diseases. And because this is a virus that mutates and spreads, we will stay on guard. + +Here are four common sense steps as we move forward safely. + +First, stay protected with vaccines and treatments. We know how incredibly effective vaccines are. If you’re vaccinated and boosted you have the highest degree of protection. + +We will never give up on vaccinating more Americans. Now, I know parents with kids under 5 are eager to see a vaccine authorized for their children. + +The scientists are working hard to get that done and we’ll be ready with plenty of vaccines when they do. + +We’re also ready with anti-viral treatments. If you get COVID-19, the Pfizer pill reduces your chances of ending up in the hospital by 90%. + +We’ve ordered more of these pills than anyone in the world. And Pfizer is working overtime to get us 1 Million pills this month and more than double that next month. + +And we’re launching the “Test to Treat” initiative so people can get tested at a pharmacy, and if they’re positive, receive antiviral pills on the spot at no cost. + +If you’re immunocompromised or have some other vulnerability, we have treatments and free high-quality masks. + +We’re leaving no one behind or ignoring anyone’s needs as we move forward. + +And on testing, we have made hundreds of millions of tests available for you to order for free. + +Even if you already ordered free tests tonight, I am announcing that you can order more from covidtests.gov starting next week. + +Second – we must prepare for new variants. Over the past year, we’ve gotten much better at detecting new variants. + +If necessary, we’ll be able to deploy new vaccines within 100 days instead of many more months or years. + +And, if Congress provides the funds we need, we’ll have new stockpiles of tests, masks, and pills ready if needed. + +I cannot promise a new variant won’t come. But I can promise you we’ll do everything within our power to be ready if it does. + +Third – we can end the shutdown of schools and businesses. We have the tools we need. + +It’s time for Americans to get back to work and fill our great downtowns again. People working from home can feel safe to begin to return to the office. + +We’re doing that here in the federal government. The vast majority of federal workers will once again work in person. + +Our schools are open. Let’s keep it that way. Our kids need to be in school. + +And with 75% of adult Americans fully vaccinated and hospitalizations down by 77%, most Americans can remove their masks, return to work, stay in the classroom, and move forward safely. + +We achieved this because we provided free vaccines, treatments, tests, and masks. + +Of course, continuing this costs money. + +I will soon send Congress a request. + +The vast majority of Americans have used these tools and may want to again, so I expect Congress to pass it quickly. + +Fourth, we will continue vaccinating the world. + +We’ve sent 475 Million vaccine doses to 112 countries, more than any other nation. + +And we won’t stop. + +We have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life. + +Let’s use this moment to reset. Let’s stop looking at COVID-19 as a partisan dividing line and see it for what it is: A God-awful disease. + +Let’s stop seeing each other as enemies, and start seeing each other for who we really are: Fellow Americans. + +We can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together. + +I recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. + +They were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. + +Officer Mora was 27 years old. + +Officer Rivera was 22. + +Both Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers. + +I spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves. + +I’ve worked on these issues a long time. + +I know what works: Investing in crime preventionand community police officers who’ll walk the beat, who’ll know the neighborhood, and who can restore trust and safety. + +So let’s not abandon our streets. Or choose between safety and equal justice. + +Let’s come together to protect our communities, restore trust, and hold law enforcement accountable. + +That’s why the Justice Department required body cameras, banned chokeholds, and restricted no-knock warrants for its officers. + +That’s why the American Rescue Plan provided $350 Billion that cities, states, and counties can use to hire more police and invest in proven strategies like community violence interruption—trusted messengers breaking the cycle of violence and trauma and giving young people hope. + +We should all agree: The answer is not to Defund the police. The answer is to FUND the police with the resources and training they need to protect our communities. + +I ask Democrats and Republicans alike: Pass my budget and keep our neighborhoods safe. + +And I will keep doing everything in my power to crack down on gun trafficking and ghost guns you can buy online and make at home—they have no serial numbers and can’t be traced. + +And I ask Congress to pass proven measures to reduce gun violence. Pass universal background checks. Why should anyone on a terrorist list be able to purchase a weapon? + +Ban assault weapons and high-capacity magazines. + +Repeal the liability shield that makes gun manufacturers the only industry in America that can’t be sued. + +These laws don’t infringe on the Second Amendment. They save lives. + +The most fundamental right in America is the right to vote – and to have it counted. And it’s under assault. + +In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections. + +We cannot let this happen. + +Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. + +Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. + +One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. + +And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence. + +A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. + +And if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. + +We can do both. At our border, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. + +We’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers. + +We’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. + +We’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders. + +We can do all this while keeping lit the torch of liberty that has led generations of immigrants to this land—my forefathers and so many of yours. + +Provide a pathway to citizenship for Dreamers, those on temporary status, farm workers, and essential workers. + +Revise our laws so businesses have the workers they need and families don’t wait decades to reunite. + +It’s not only the right thing to do—it’s the economically smart thing to do. + +That’s why immigration reform is supported by everyone from labor unions to religious leaders to the U.S. Chamber of Commerce. + +Let’s get it done once and for all. + +Advancing liberty and justice also requires protecting the rights of women. + +The constitutional right affirmed in Roe v. Wade—standing precedent for half a century—is under attack as never before. + +If we want to go forward—not backward—we must protect access to health care. Preserve a woman’s right to choose. And let’s continue to advance maternal health care in America. + +And for our LGBTQ+ Americans, let’s finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong. + +As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. + +While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice. + +And soon, we’ll strengthen the Violence Against Women Act that I first wrote three decades ago. It is important for us to show the nation that we can come together and do big things. + +So tonight I’m offering a Unity Agenda for the Nation. Four big things we can do together. + +First, beat the opioid epidemic. + +There is so much we can do. Increase funding for prevention, treatment, harm reduction, and recovery. + +Get rid of outdated rules that stop doctors from prescribing treatments. And stop the flow of illicit drugs by working with state and local law enforcement to go after traffickers. + +If you’re suffering from addiction, know you are not alone. I believe in recovery, and I celebrate the 23 million Americans in recovery. + +Second, let’s take on mental health. Especially among our children, whose lives and education have been turned upside down. + +The American Rescue Plan gave schools money to hire teachers and help students make up for lost learning. + +I urge every parent to make sure your school does just that. And we can all play a part—sign up to be a tutor or a mentor. + +Children were also struggling before the pandemic. Bullying, violence, trauma, and the harms of social media. + +As Frances Haugen, who is here with us tonight, has shown, we must hold social media platforms accountable for the national experiment they’re conducting on our children for profit. + +It’s time to strengthen privacy protections, ban targeted advertising to children, demand tech companies stop collecting personal data on our children. + +And let’s get all Americans the mental health services they need. More people they can turn to for help, and full parity between physical and mental health care. + +Third, support our veterans. + +Veterans are the best of us. + +I’ve always believed that we have a sacred obligation to equip all those we send to war and care for them and their families when they come home. + +My administration is providing assistance with job training and housing, and now helping lower-income veterans get VA care debt-free. + +Our troops in Iraq and Afghanistan faced many dangers. + +One was stationed at bases and breathing in toxic smoke from “burn pits” that incinerated wastes of war—medical and hazard material, jet fuel, and more. + +When they came home, many of the world’s fittest and best trained warriors were never the same. + +Headaches. Numbness. Dizziness. + +A cancer that would put them in a flag-draped coffin. + +I know. + +One of those soldiers was my son Major Beau Biden. + +We don’t know for sure if a burn pit was the cause of his brain cancer, or the diseases of so many of our troops. + +But I’m committed to finding out everything we can. + +Committed to military families like Danielle Robinson from Ohio. + +The widow of Sergeant First Class Heath Robinson. + +He was born a soldier. Army National Guard. Combat medic in Kosovo and Iraq. + +Stationed near Baghdad, just yards from burn pits the size of football fields. + +Heath’s widow Danielle is here with us tonight. They loved going to Ohio State football games. He loved building Legos with their daughter. + +But cancer from prolonged exposure to burn pits ravaged Heath’s lungs and body. + +Danielle says Heath was a fighter to the very end. + +He didn’t know how to stop fighting, and neither did she. + +Through her pain she found purpose to demand we do better. + +Tonight, Danielle—we are. + +The VA is pioneering new ways of linking toxic exposures to diseases, already helping more veterans get benefits. + +And tonight, I’m announcing we’re expanding eligibility to veterans suffering from nine respiratory cancers. + +I’m also calling on Congress: pass a law to make sure veterans devastated by toxic exposures in Iraq and Afghanistan finally get the benefits and comprehensive health care they deserve. + +And fourth, let’s end cancer as we know it. + +This is personal to me and Jill, to Kamala, and to so many of you. + +Cancer is the #2 cause of death in America–second only to heart disease. + +Last month, I announced our plan to supercharge +the Cancer Moonshot that President Obama asked me to lead six years ago. + +Our goal is to cut the cancer death rate by at least 50% over the next 25 years, turn more cancers from death sentences into treatable diseases. + +More support for patients and families. + +To get there, I call on Congress to fund ARPA-H, the Advanced Research Projects Agency for Health. + +It’s based on DARPA—the Defense Department project that led to the Internet, GPS, and so much more. + +ARPA-H will have a singular purpose—to drive breakthroughs in cancer, Alzheimer’s, diabetes, and more. + +A unity agenda for the nation. + +We can do this. + +My fellow Americans—tonight , we have gathered in a sacred space—the citadel of our democracy. + +In this Capitol, generation after generation, Americans have debated great questions amid great strife, and have done great things. + +We have fought for freedom, expanded liberty, defeated totalitarianism and terror. + +And built the strongest, freest, and most prosperous nation the world has ever known. + +Now is the hour. + +Our moment of responsibility. + +Our test of resolve and conscience, of history itself. + +It is in this moment that our character is formed. Our purpose is found. Our future is forged. + +Well I know this nation. + +We will meet the test. + +To protect freedom and liberty, to expand fairness and opportunity. + +We will save democracy. + +As hard as these times have been, I am more optimistic about America today than I have been my whole life. + +Because I see the future that is within our grasp. + +Because I know there is simply nothing beyond our capacity. + +We are the only nation on Earth that has always turned every crisis we have faced into an opportunity. + +The only nation that can be defined by a single word: possibilities. + +So on this night, in our 245th year as a nation, I have come to report on the State of the Union. + +And my report is this: the State of the Union is strong—because you, the American people, are strong. + +We are stronger today than we were a year ago. + +And we will be stronger a year from now than we are today. + +Now is our moment to meet and overcome the challenges of our time. + +And we will, as one people. + +One America. + +The United States of America. + +May God bless you all. May God protect our troops. diff --git a/examples/chat_with_your_documents/documents/state_of_the_union_2023.txt b/examples/chat_with_your_documents/documents/state_of_the_union_2023.txt new file mode 100644 index 0000000000000000000000000000000000000000..a2ad0b30506f48e8c13f3c5f0426170b54e930fb --- /dev/null +++ b/examples/chat_with_your_documents/documents/state_of_the_union_2023.txt @@ -0,0 +1,667 @@ +Mr. Speaker, Madam Vice President, our First Lady and Second Gentleman — good to see you guys up there — members of Congress — + +And, by the way, Chief Justice, I may need a court order. She gets to go to the game tomorr- — next week. I have to stay home. We got to work something out here. + +Members of the Cabinet, leaders of our military, Chief Justice, Associate Justices, and retired Justices of the Supreme Court, and to you, my fellow Americans: + +You know, I start tonight by congratulating the 118th Congress and the new Speaker of the House, Kevin McCarthy. + +Speaker, I don’t want to ruin your reputation, but I look forward to working with you. + +And I want to congratulate the new Leader of the House Democrats, the first African American Minority Leader in history, Hakeem Jeffries. + +He won despite the fact I campaigned for him. + +Congratulations to the longest-serving Leader in the history of the United States Senate, Mitch McConnell. Where are you, Mitch? + +And congratulations to Chuck Schumer, another — you know, another term as Senate Minority [Majority] Leader. You know, I think you — only this time you have a slightly bigger majority, Mr. Leader. And you’re the Majority Leader. About that much bigger? Yeah. + +Well, I tell you what — I want to give specolec- — special recognition to someone who I think is going to be considered the greatest Speaker in the history of the House of Representatives: Nancy Pelosi. + +Folks, the story of America is a story of progress and resilience, of always moving forward, of never, ever giving up. It’s a story unique among all nations. + +We’re the only country that has emerged from every crisis we’ve ever entered stronger than we got into it. + +Look, folks, that’s what we’re doing again. + +Two years ago, the economy was reeling. I stand here tonight, after we’ve created, with the help of many people in this room, 12 million new jobs — more jobs created in two years than any President has created in four years — because of you all, because of the American people. + +Two years ago — and two years ago, COVID had shut down — our businesses were closed, our schools were robbed of so much. And today, COVID no longer controls our lives. + +And two years ago, our democracy faced its greatest threat since the Civil War. And today, though bruised, our democracy remains unbowed and unbroken. + +As we gather here tonight, we’re writing the next chapter in the great American story — a story of progress and resilience. + +When world leaders ask me to define America — and they do, believe it or not — I say I can define it in one word, and I mean this: possibilities. We don’t think anything is beyond our capacity. Everything is a possibility. + +You know, we’re often told that Democrats and Republicans can’t work together. But over the past two years, we proved the cynics and naysayers wrong. + +Yes, we disagreed plenty. And yes, there were times when Democrats went alone. + +But time and again, Democrats and Republicans came together. Came together to defend a stronger and safer Europe. You came together to pass one in a gen- — one-in-a-generation — once-in-a-generation infrastructure law building bridges connecting our nation and our people. We came together to pass one the most significant law ever helping victims exposed to toxic burn pits. And, in fact — it’s important. + +And, in fact, I signed over 300 bipartisan pieces of legislation since becoming President, from reauthorizing the Violence Against Women Act to the Electoral Count Reform Act, the Respect for Marriage Act that protects the right to marry the person you love. + +And to my Republican friends, if we could work together in the last Congress, there’s no reason we can’t work together and find consensus on important things in this Congress as well. + +I think — folks, you all are just as informed as I am, but I think the people sent us a clear message: Fighting for the sake of fighting, power for the sake of power, conflict for the sake of conflict gets us nowhere. + +That’s always been my vision of our country, and I know it’s many of yours: to restore the soul of this nation; to rebuild the backbone of America, America’s middle class; and to unite the country. + +That’s always been my vision for the country. To restore the soul of the nation. To rebuild the backbone of America - the middle class. To unite the country. + +We’ve been sent here to finish the job, in my view. + +For decades, the middle class has been hollowed out in more than — and not in one administration, but for a long time. Too many good-paying manufacturing jobs moved overseas. Factories closed down. Once-thriving cities and towns that many of you represent became shadows of what they used to be. And along the way, something else we lost: pride, our sense of self-worth. + +I ran for President to fundamentally change things. To make sure the economy works for everyone so we can all feel that pride in what we do. To build an economy from the bottom up and the middle out, not from the top down. Because when the middle class does well, the poor have a ladder up and the wealthy still do very well. We all do well. + +I know a lot of you always kid me for always quoting my dad. But my dad used to say, “Joey, a job is about a lot more than a paycheck.” He really would say this. “It’s about a lot more than a paycheck. It’s about your dignity. It’s about respect. It’s about being able to look your kid in the eye and say, ‘Honey, it’s going to be okay’ and mean it.” + +Well, folks, so let’s look at the results. We’re not finished yet, by any stretch of the imagination. But unemployment rate is at 3.4 percent –- a 50-year low. And near record — and near record unemployment — near record unemployment for Black and Hispanic workers. + +We’ve already created, with your help, 800,000 good-paying manufacturing jobs — the fastest growth in 40 years. + +And where is it written — where is it written that America can’t lead the world in manufacturing? And I don’t know where that’s written. + +For too many decades, we imported projects and exported jobs. Now, thanks to what you’ve all done, we’re exporting American products and creating American jobs. + +Folks, inflation — inflation has been a global problem because the pandemic dirup- — disrupted our supply chains, and Putin’s unfair and brutal war in Ukraine disrupted ener- — energy supplied as well as food supplies, blocking all that grain in Ukraine. + +But we’re better positioned than any country on Earth right now. But we have more to do. + +But here at home, inflation is coming down. Here at home, gas prices are down $1.50 from their peak. + +Food inflation is coming down — not fast enough, but coming down. + +Inflation has fallen every month for the last six months, while take-home pay has gone up. + +Additionally, over the last two years, a record 10 million Americans applied to start new businesses. Ten million. + +And, by the way, every time — every time someone starts a small business, it’s an act of hope. + +And, Madam Vice President, I want to thank you for leading that effort to ensure that small businesses have access to capital and the historic laws we enacted that are going to just come into being. + +Standing here last year, I shared with you a story of American genius and possibilities. + +Semiconductors — small computer chips the size of a fingerprint that power everything from cellphones to automobiles and so much more. These chips were invented in America. Let’s get that straight: They were invented in America. + +And we used to make 40 percent of the world’s chips. In the last several decades, we lost our edge. We’re down to only producing 10 percent. + +We all saw what happened during the pandemic when chip factories shut down overseas. + +Today’s automobiles need 3,000 chips — each of those automobiles — but American automobiles [automakers] couldn’t make enough cars because there weren’t enough chips. + +Car prices went up. People got laid off. So did everything from refrigerators to cellphones. + +We can never let that happen again. + +That’s why — that’s why we came together to pass the bipartisan CHIPS and Science Act. + +Folks, I know I’ve been criticized for saying this, but I’m not changing my view. We’re going to make sure the supply chain for America begins in America — the supply chain begins in America. + +And we’ve already created — we’ve already created 800,000 new manufacturing jobs without this law, before the law kicks in. + +With this new law, we’re going to create hundreds of thousands of new jobs across the country. And I mean all across the country, throughout — not just the coast, but through the middle of the country as well. + +That’s going to come from companies that have announced more than $300 billion in investments in American manufacturing over the next few years. + +Outside of Columbus, Ohio, Intel is building semiconductor factories on a thousand acres — literally a field of dreams. + +It’s going to create 10,000 jobs, that one investment; 7,000 construction jobs; 3,000 jobs in those factories once they’re finished. They call them factors. Jobs paying an average of $130,000 a year, and many do not require a college degree. + +Jobs — because we worked together, these jobs where people don’t have to leave home to search for opportunity. + +And it’s just getting started. + +Think about the new homes, the small businesses, the big — the medium-sized businesses. So much more that’s going to be needed to support those three thou- — those 3,000 permanent jobs and the factories that are going to be built. + +Talk to mayors and governors, Democrats and Republicans, and they’ll tell you what this means for their communities. + +We’re seeing these fields of dreams transform the Heartland. But to maintain the strongest economy in the world, we need the best infrastructure in the world. + +And, folks, as you all know, we used to be number one in the world in infrastructure. We’ve sunk to 13th in the world. The United States of America — 13th in the world in infrastructure, modern infrastructure. + +But now we’re coming back because we came together and passed the Bipartisan Infrastructure Law — the largest investment in infrastructure since President Eisenhower’s Interstate Highway System. + +Folks, already we’ve funded over 20,000 projects, including major airports from Boston to Atlanta to Portland — projects that are going to put thousands of people to work rebuilding our highways, our bridges, our railroads, our tunnels, ports, airports, clean water, high-speed Internet all across America — urban, rural, Tribal. + +And, folks, we’re just getting started. We’re just getting started. + +And I mean this sincerely: I want to thank my Republican friends who voted for the law. And my Republican friends who voted against it as well — but I’m still — I still get asked to fund the projects in those districts as well, but don’t worry. I promised I’d be a President for all Americans. We’ll fund these projects. And I’ll see you at the groundbreaking. + +Look, this law — this law will further unite all of America. + +Projects like the Brent Spence Bridge in Kentucky over the Ohio River. Built 60 years ago. Badly in need of repairs. One of the nation’s most congested freight routes, carrying $2 billion worth of freight every single day across the Ohio River. + +And, folks, we’ve been talking about fixing it for decades, but we’re really finally going to get it done. + +I went there last month with Democrats and Republicans in — from both states — to deliver a commitment of $1.6 billion for this project. + +And while I was there, I met a young woman named Saria, who’s here tonight. I don’t know where Saria is. Is she up in the box? I don’t know. Saria, how are you? + +Well, Saria — for 30 years — for 30 years — I learned — she told me she’d been a proud member of the Iron workers Local 44, known as — — known as the “Cowboys in the Sky” — — the folks who built — who built Cincinnati’s skyline. + +Saria said she can’t wait to be 10 stories above the Ohio River building that new bridge. God bless her. That’s pride. + +And that’s what we’re also building — we’re building back pride. + +Look, we’re also replacing poisonous lead pipes that go into 10 million homes in America, 400,000 schools and childcare centers so every child in America — every child in American can drink the water, instead of having permanent damage to their brain. + +Look, we’re making sure — — we’re making sure that every community — every community in America has access to affordable, high-speed Internet. + +No parent should have to drive by a McDonald’s parking lot to help their — do their homework online with their kids, which many — thousands were doing across the country. + +And when we do these projects — and, again, I get criticized about this, but I make no excuses for it — we’re going to buy American. We’re going to buy American. + +Folks — — and it’s totally — it’s totally consistent with international trade rules. Buy American has been the law since 1933. But for too long, past administrations — Democrat and Republican — have fought to get around it. Not anymore. + +Tonight, I’m also announcing new standards to require all construction materials used in federal infra- — infrastructure projects to be made in America. Made in America. I mean it. Lumber, glass, drywall, fiber-optic cable. + +And on my watch, American roads, bridges, and American highways are going to be made with American products as well. + +Folks, my economic plan is about investing in places and people that have been forgotten. So many of you listening tonight, I know you feel it. So many of you felt like you’ve just simply been forgotten. Amid the economic upheaval of the past four decades, too many people have been left behind and treated like they’re invisible. + +Maybe that’s you, watching from home. You remember the jobs that went away. You remember them, don’t you? + +The folks at home remember them. You wonder whether the path even exists anymore for your children to get ahead without having to move away. + +Well, that’s why — I get that. That’s why we’re building an economy where no one is left behind. + +Jobs are coming back, pride is coming back because of choices we made in the last several years. + +You know, this is, in my view, a blue-collar blueprint to rebuild America and make a real difference in your lives at home. + +For example, too many of you lay in bed at night, like my dad did, staring at the ceiling, wondering what in God’s name happens if yo- — if your spouse gets cancer or your child gets deadly ill or if something happens to you. What are you going — are you going to have the money to pay for those medical bills? Are you going to have to sell the house or try to get a second mortgage on it? + +I get it. I get it. + +With the Inflation Reduction Act that I signed into law, we’re taking on powerful interests to bring healthcare costs down so you can sleep better at night with more security. + +You know, we pay more for prescription drugs than any nation in the world. Let me say it again: We pay more for prescription drugs than any major nation on Earth. + +For example, 1 in 10 Americans has diabetes. Many of you in this chamber do and in the audience. But every day, millions need insulin to control their diabetes so they can literally stay alive. Insulin has been around for over 100 years. The guy who invented it didn’t even patent it because he wanted it to be available for everyone. + +It costs the drug companies roughly $10 a vial to make that insulin. Package it and all, you may get up to $13. But Big Pharma has been unfairly charging people hundreds of dollars — $4- to $500 a month — making rec- — record profits. Not anymore. Not anymore. + +So — so many things that we did are only now coming to fruition. We said we were doing this and we said we’d pass the law to do it, but people didn’t know because the law didn’t take effect until January 1 of this year. + +We capped the cost of insulin at $35 a month for seniors on Medicare. But people are just finding out. I’m sure you’re getting the same calls I’m getting. + +We capped insulin for seniors at $35 per month. It’s time to do it for everyone. + +Look, there are millions of other Americans who do not — are not on Medicare, including 200,000 young people with Type 1 diabetes who need these insulin — need this insulin to stay alive. + +Let’s finish the job this time. Let’s cap the cost of insulin for everybody at $35. + +Folks — and Big Pharma is still going to do very well, I promise you all. I promise you they’re going to do very well. + +This law also — this law also caps — and it won’t even go into effect until 2025. It costs [caps] out-of-pocket drug costs for seniors on Medicare at a maximum of $2,000 a year. You don’t have to pay more than $2,000 a year, no matter how much your drug costs are. Because you know why? You all know it. + +Many of you, like many of my family, have cancer. You know the drugs can range from $10-, $11-, $14-, $15,000 for the cancer drugs. + +And if drug prices rise faster than inflation, drug companies are going to have to pay Medicare back the difference. + +And we’re finally — we’re finally giving Medicare the power to negotiate drug prices. + +Bringing down — bringing down prescription drug costs doesn’t just save seniors money, it cuts the federal deficit by billions of dollars — — by hundreds of billions of dollars because these prescription drugs are drugs purchased by Medicare to make — keep their commitment to the seniors. + +Well, guess what? Instead of paying 4- or 500 bucks a month, you’re paying 15. That’s a lot of savings for the federal government. + +And, by the way, why wouldn’t we want that? + +Now, some members here are threatening — and I know it’s not an official party position, so I’m not going to exaggerate — but threatening to repeal the Inflation Reduction Act. + +As my coach — that’s okay. That’s fair. As my football coach used to say, “Lots of luck in your senior year.” + +Make no mistake, if you try anything to raise the cost of prescription drugs, I will veto it. + +And, look, I’m pleased to say that more Americans health — have health insurance now than ever in history. A record 16 million people are enrolled in the Affordable Care Act. + +And thanks — thanks to the law I signed last year, saving — millions are saving $800 a year on their premiums. + +And, by the way, that law was written — and the benefit expires in 2025. So, my plea to some of you, at least in this audience: Let’s finish the job and make those savings permanent. Expand coverage on Medicaid. + +Look, the Inflation Reduction Act is also the most significant investment ever in climate change — ever. Lowering utility bills, creating American jobs, leading the world to a clean energy future. + +I visited the devastating aftermath of record floods, droughts, storms, and wildfires from Arizona to New Mexico to all the way up to the Canadian border. + +More timber has been burned that I’ve observed from helicopters than the entire state of Missouri. And we don’t have global warming? Not a problem. + +In addition to emergency recovery from Puerto Rico to Florida to Idaho, we’re rebuilding for the long term. + +New electric grids that are able to weather major storms and not — prevent those fire — forest fires. Roads and water systems to withstand the next big flood. Clean energy to cut pollution and create jobs in communities often left behind. + +We’re going to build 500,000 electric vehicle charging stations, installed across the country by tens of thousands of IBEW workers. + +And we’re helping families save more than $1,000 a year with tax credits to purchase of electric vehicles and efficient — and efficient appliances — energy-efficient appliances. + +Historic conservation efforts to be responsible stewards of our land. + +Let’s face reality. The climate crisis doesn’t care if you’re in a red or a blue state. It’s an existential threat. + +We have an obligation not to ourselves, but to our children and grandchildren to confront it. + +I’m proud of how the — how America, at last, is stepping up to the challenge. We’re still going to need oil and gas for a while, but guess what — — no, we do — but there’s so much more to do. We got to finish the job. + +And we pay for these investments in our future by finally making the wealthiest and biggest corporations begin to pay their fair share. Just begin. + +Look, I’m a capitalist. I’m a capitalist. But pay your fair share. + +I think a lot of you at home — a lot of you at home agree with me and many people that you know: The tax system is not fair. It is not fair. + +Look, the idea that in 2020, 55 of the largest corporations in America, the Fortune 500, made $40 billion in profits and paid zero in federal taxes? Zero. + +Folks, it’s simply not fair. + +But now, because of the law I signed, billion-dollar companies have to pay a minimum of 15 percent. God love them. Fifteen percent. That’s less than a nurse pays. + +Let me be crystal clear. I said at the very beginning: Under my plans, as long as I’m President, nobody earning less than $400,000 will pay an additional penny in taxes. Nobody. Not one penny. + +But let’s finish the job. There’s more to do. + +We have to reward work, not just wealth. Pass my proposal for the billionaire minimum tax. You know, there’s a thousand billionaires in America — it’s up from about 600 at the beginning of my term — but no billionaire should be paying a lower tax rate than a school teacher or a firefighter. No, I mean it. Think about it. + +We made every wealthy corporation pay a minimum tax. It’s time to do the same for billionaires. + +I mean, look, I know you all aren’t enthusiastic about that, but think about it. Think about it. + +Have you noticed — Big Oil just reported its profits. Record profits. Last year, they made $200 billion in the midst of a global energy crisis. I think it’s outrageous. + +Why? They invested too little of that profit to increase domestic production. And when I talked to a couple of them, they say, “We were afraid you were going to shut down all the oil wells and all the oil refineries anyway, so why should we invest in them?” I said, “We’re going to need oil for at least another decade, and that’s going to exceed…” — and beyond that. We’re going to need it. Production. + +If they had, in fact, invested in the production to keep gas prices down — instead they used the record profits to buy back their own stock, rewarding their CEOs and shareholders. + +Corporations ought to do the right thing. + +That’s why I propose we quadruple the tax on corporate stock buybacks and encourage long- — — long-term investments. They’ll still make considerable profit. + +Let’s finish the job and close the loopholes that allow the very wealthy to avoid paying their taxes. + +Instead of cutting the number of audits for wealthy taxpayers, I just signed a law to reduce the deficit by $114 billion by cracking down on wealthy tax cheats. That’s being fiscally responsible. + +In the last two years, my administration has cut the deficit by more than $1.7 trillion –- the largest deficit reduction in American history. + +Under the previous administration, the American deficit went up four years in a row. + +Because of those record deficits, no President added more to the national debt in any four years than my predecessor. + +Nearly 25 percent of the entire national debt that took over 200 years to accumulate was added by just one administration alone — the last one. They’re the facts. Check it out. Check it out. + +How did Congress respond to that debt? They did the right thing. They lifted the debt ceiling three times without preconditions or crisis. They paid the American bill to prevent an economic disaster of the country. + +So, tonight I’m asking the Congress to follow suit. Let us commit here tonight that the full faith and credit of the United States of America will never, ever be questioned. + +So my — many of — some of my Republican friends want to take the economy hostage — I get it — unless I agree to their economic plans. All of you at home should know what those plans are. + +Instead of making the wealthy pay their fair share, some Republicans — some Republicans want Medicare and Social Security to sunset. I’m not saying it’s a majority — + +Let me give you — + +Anybody who doubts it, contact my office. I’ll give you a copy. I’ll give you a copy of the proposal. + +That means Congress doesn’t vote — + +Well, I’m glad to see — no, I tell you, I enjoy conversion. + +You know, it means if Congress doesn’t keep the programs the way they are, they’d go away. + +Other Republicans say — I’m not saying it’s a majority of you. I don’t even think it’s a significant — + +— but it’s being proposed by individuals. + +I’m not — politely not naming them, but it’s being proposed by some of you. + +Look, folks, the idea is that we’re not going to be — we’re not going to be moved into being threatened to default on the debt if we don’t respond. + +Folks — so, folks, as we all apparently agree, Social Security and Medicare is off the — off the books now, right? They’re not to be touched? + +All right. All right. We got unanimity! Social Security and Medicare are a lifeline for millions of seniors. Americans have to pay into them from the very first paycheck they’ve started. + +So, tonight, let’s all agree — and we apparently are — let’s stand up for seniors. Stand up and show them we will not cut Social Security. We will not cut Medicare. + +President Biden wants to strengthen social security and medicare. House Republicans are threatening to cut them. + +Those benefits belong to the American people. They earned it. And if anyone tries to cut Social Security — which apparently no one is going to do — and if anyone tries to cut Medicare, I’ll stop them. I’ll veto it. + +And, look, I’m not going to allow them to take away — be taken away. Not today. Not tomorrow. Not ever. + +But apparently, it’s not going to be a problem. + +Next month, when I offer my fiscal plan, I ask my Republican friends to lay down their plan as well. I really mean it. Let’s sit down together and discuss our mutual plans together. Let’s do that. + +I can tell you, the plan I’m going to show you is going to cut the deficit by another $2 trillion. And it won’t cut a single bit of Medicare or Social Security. + +In fact, we’re going to extend the Medicare Trust Fund at least two decades, because that’s going to be the next argument: how do we make — keep it solvent. Right? + +Well, I will not raise taxes on anyone making under 400 grand. But we’ll pay for it the way we talked about tonight: by making sure that the wealthy and big corporations pay their fair share. + +Look — look, look, here’s — here’s the deal. They aren’t just taking advantage of the tax code, they’re taking advantage of you, the American consumer. + +Here’s my message to all of you out there: I have your back. We’re already preventing Americans who are [from] receiving surprise medical bills, stopping 1 billion dollar [1 million] surprise bills per month so far. + +We’re protecting seniors’ life savings by cracking down on nursing homes that commit fraud, endanger patient safety, or prescribe drugs that are not needed. + +Millions of Americans can now save thousands of dollars because they can finally get a hearing aid over the counter without a prescription. + +Look, capitalism without competition is not capitalism. It’s extortion. It’s exploitation. + +Last year, I cracked down, with the help of many of you, on foreign shipping companies that were making you pay higher prices for every good coming into the country. + +I signed a bipartisan bill that cut shipping costs by 90 percent, helping American farmers, businessmen, and consumers. + +Let’s finish the job. Pass the bipartisan legislation to strengthen and — to strengthen antitrust enforcement and forbeg — and prevent big online platforms from giving their own products an unfair advantage. + +My administration is also taking on junk fees, those hidden surcharges too many companies use to make you pay more. + +For example, we’re making airlines show you the full ticket price upfront, refund your money if your flight is cancelled or delayed. We’ve reduced exorbitant bank overdrafts by saving consumers more than $1 billion a year. + +We’re cutting credit card late fees by 75 percent, from $30 to $8. + +Look, junk fees may not matter to the very wealthy, but they matter to most other folks in homes like the one I grew up in, like many of you did. They add up to hundreds of dollars a month. They make it harder for you to pay your bills or afford that family trip. + +I know how unfair it feels when a company overcharges you and gets away with it. Not anymore. + +We’ve written a bill to stop it all. It’s called the Junk Fee Prevention Act. We’re going to ban surprise resort fees that hotels charge on your bill. Those fees can cost you up to $90 a night at hotels that aren’t even resorts. + +It’s time to end excessive serve fees for concert tickets. Pass the Junk Fee Prevention Act. + +We — the idea that cable, Internet, and cellphone companies can charge you $200 or more if you decide to switch to another provider. Give me a break. + +We can stop service fees on tickets to concerts and sporting events and make companies disclose all the fees upfront. + +And we’ll prohibit airlines from charging $50 roundtrip for a family just to be able to sit together. Baggage fees are bad enough. Airlines can’t treat your child like a piece of baggage. + +Americans are tired of being — we’re tired of being played for suckers. + +So pass — pass the Junk Fee Prevention Act so companies stop ripping us off. + +For too long, workers have been getting stiffed, but not anymore. We’re going to be — we’re beginning to restore the dignity of work. + +For example, I — I should have known this, but I didn’t until two years ago: Thirty million workers have to sign non-compete agreements for the jobs they take. Thirty million. So a cashier at a burger place can’t walk across town and take the same job at another burger place and make a few bucks more. + +It just changed. Well, they just changed it because we exposed it. That was part of the deal, guys. Look it up. But not anymore. + +We’re banning those agreements so companies have to compete for workers and pay them what they’re worth. + +And I must tell you, this is bound to get a response from my friends on my left, with the right. + +I’m so sick and tired of companies breaking the law by preventing workers from organizing. Pass the PRO Act! Because businesses have a right — workers have a right to form a union. And let’s guarantee all workers have a living wage. + +Let’s make sure working parents can afford to raise a family with sick days, paid family and medical leave, affordable childcare. That’s going to enable millions of more people to go and stay at work. + +And let’s restore the full Child Tax Credit — — which gave tens of millions of parents some breathing room and cut child poverty in half to the lowest level in history. + +And, by the way, when we do all of these things, we increase productivity, we increase economic growth. + +So let’s finish the job and get more families access to affordable, quality housing. + +Let’s get seniors who want to stay in their homes the care they need to do so. Let’s give more breathing room to millions of family caregivers looking after their loved ones. + +Pass my plan so we get seniors and people with disabilities the home care services they need — — and support the workers who are doing God’s work. + +These plans are fully paid for, and we can afford to do them. + +Restoring the dignity of work means making education an affordable ticket to the middle class. + +You know, when we made public education — 12 years of it — universal in the last century, we made the best-educated, best-paid — we became the best-education, best-paid nation in the world. + +But the rest of the world has caught up. It has caught up. + +Jill, my wife, who teaches full-time, has an expression. I hope I get it right, kid. “Any nation that out-educates is going to out-compete us.” Any nation that out-educates is going to out-compete us. + +Folks, we all know 12 years of education is not enough to win the economic competition of the 21st century. If we want to have the best-educated workforce, let’s finish the job by providing access to preschool for three and four years old. Studies show that children who go to preschool are nearly 50 percent more likely to finish high school and go on to earn a two- or four-year degree, no matter their background they came from. + +Let’s give public school teachers a raise. + +We’re making progress by reducing student debt, increasing Pell Grants for working and middle-class families. + +Let’s finish the job and connect students to career opportunities starting in high school, provide access to two years of community college — the best career training in America, in addition to being a pathway to a four-year degree. + +Let’s offer every American a path to a good career, whether they go to college or not. + +And, folks — folks, in the midst of the COVID crisis, when schools were closed and we were shutting down everything, let’s recognize how far we came in the fight against the pandemic itself. + +While the virus is not gone, thanks to the resilience of the American people and the ingenuity of medicine, we’ve broken the COVID grip on us. + +COVID deaths are down by 90 percent. We’ve saved millions of lives and opened up our country — we opened our country back up. And soon, we’ll end the public health emergency. + +But — that’s called a public health emergency. + +But we’ll remember the toll and pain that’s never going to go away. More than a million Americans lost their lives to COVID. A million. Families grieving. Children orphaned. Empty chairs at the dining room table constantly reminding you that she used to sit there. Remembering them, we remain vigilant. + +We still need to monitor dozens of variants and support new vaccines and treatments. So Congress needs to fund these efforts and keep America safe. + +And as we emerge from this crisis stronger, we’re also — got to double down prosecuting criminals who stole relief money meant to keep workers and small businesses afloat. + +Before I came to office, you remember, during that campaign, the big issue was about inspector generals who would protect taxpayers’ dollars, who were sidelined. They were fired. Many people said, “We don’t need them.” And fraud became rampant. + +Last year, I told you the watchdogs are back. Since then — since then, we’ve recovered billions of taxpayers’ dollars. + +Now let’s triple the anti-fraud strike force going after these criminals, double the statute of limitations on these crimes, and crack down on identity fraud by criminal syndicates stealing billions of dollars — billions of dollars from the American people. + +And the data shows that for every dollar we put into fighting fraud, the taxpayer will get back at least 10 times as much. It matters. It matters. + +Look, COVID left its scars, like the spike in violent crime in 2020 — the first year of the pandemic. We have an obligation to make sure all people are safe. + +Public safety depends on public trust, as all of us know. But too often, that trust is violated. + +Joining us tonight are the parents of Tyre Nichols — welcome — who had to bury Tyre last week. + +As many of you personally know, there’s no words to describe the heartache or grief of losing a child. But imagine — imagine if you lost that child at the hands of the law. Imagine having to worry whether your son or daughter came home from walking down the street or playing in the park or just driving a car. + +Most of us in here have never had to have “the talk” — “the talk” — that brown and Black parents have had to have with their children. + +Beau, Hunter, Ashley — my children — I never had to have the talk with them. I never had to tell them, “If a police officer pulls you over, turn your interior lights on right away. Don’t reach for your license. Keep your hands on the steering wheel.” + +Imagine having to worry like that every single time your kid got in a car. + +Here’s what Tyre’s mother shared with me when I spoke to her, when I asked her how she finds the courage to carry on and speak out. With the faith of God, she said her son was, quote, “a beautiful soul” and “something good will come of this.” + +Imagine how much courage and character that takes. + +It’s up to us, to all of us. We all want the same thing: neighborhoods free of violence, law enfircement [sic] — law enforcement who earns the community’s trust. Just as every cop, when they pin on that badge in the morning, has a right to be able to go home at night, so does everybody else out there. Our children have a right to come home safely. + +Equal protection under the law is a covenant we have with each other in America. + +We know police officers put their lives on the line every single night and day. And we know we ask them, in many cases, to do too much — to be counselors, social workers, psychologists — responding to drug overdoses, mental health crises, and so much more. In one sense, we ask much too much of them. + +I know most cops and their families are good, decent, honorable people — the vast majority. And they risk — and they risk their lives every time they put that shield on. + +But what happened to Tyre in Memphis happens too often. We have to do better. Give law enforcement the real training they need. Hold them to higher standards. Help them to succeed in keeping them safe. + +We also need more first responders and professionals to address the growing mental health, substance abuse challenges. More resources to reduce violent crime and gun crime. More community intervention programs. More investments in housing, education, and job training. All this can help prevent violence in the first place. + +And when police officers or police departments violate the public trust, they must be held accountable. + +With the support — with the support of families of victims, civil rights groups, and law enforcement, I signed an executive order for all federal officers, banning chokeholds, restricting no-knock warrants, and other key elements of the George Floyd Act. + +Let’s commit ourselves to make the words of Tyler’s [Tyre’s] mom true: Something good must come from this. Something good. + +And all of us — all of us — folks, it’s difficult, but it’s simple: All of us in the cha- — in this chamber, we need to rise to this moment. We can’t turn away. Let’s do what we know in our hearts that we need to do. Let’s come together to finish the job on police reform. Do something. Do something. + +Ban assault weapons. + +That was the plea of parents who lost their children in Uvalde — I met with every one of them — “Do something about gun violence.” Thank God — thank God we did, passing the most sweeping gun safety law in three decades. + +That includes things like — that the majority of responsible gun owners already support: enhanced background checks for 18- to 21 years old, red-flag laws keeping guns out of the hands of people who are a danger to themselves and others. + +But we know our work is not done. Joining us tonight is Brandon Tsay, a 26-year-old hero. + +Brandon put his college dreams on hold — to be at his mom’s side — his mom’s side when she was dying from cancer. And Brandon — Brandon now works at the dance studio started by his grandparents. + +And two weeks ago, during the Lunar New Year celebrations, he heard the studio door close, and he saw a man standing there pointing a semi-automatic pistol at him. He thought he was going to die, but he thought about the people inside. + +In that instant, he found the courage to act and wrestled the semi-automatic pistol away from the gunman who had already killed 11 people in another dance studio. Eleven. + +He saved lives. It’s time we do the same. + +Ban assault weapons now! Ban them now! Once and for all. + +I led the fight to do that in 1994. And in 10 years that ban was law, mass shootings went down. After we let it expire in a Republican administration, mass shootings tripled. + +Let’s finish the job and ban these assault weapons. + +And let’s also come together on immigration. Make it a bipartisan issue once again. + +We know — we now have a record number of personnel working to secure the border, arresting 8,000 human smugglers, seizing over 23,000 pounds of fentanyl in just the last several months. + +We’ve launched a new border plan last month. Unlawful migration from Cuba, Haiti, Nicaragua, and Venezuela has come down 97 percent as a consequence of that. + +But American border problems won’t be fixed until Congress acts. If we don’t pass my comprehensive immigration reform, at least pass my plan to provide the equipment and officers to secure the border — and a pathway to citizenship for DREAMers, those on temporary status, farmworkers, essential workers. + +Here in the People’s House, it’s our duty to protect all the people’s rights and freedoms. Congress must restore the right and — + +Congress must restore the right that was taken away in Roe v. Wade — and protect Roe v. Wade. Give every woman the constitutional right. + +The Vice President and I are doing everything to protect access to reproductive healthcare and safeguard patient safety. But already, more than a dozen states are enforcing extreme abortion bans. + +Make no mistake about it: If Congress passes a national ban, I will veto it. + +It’s time to pass the Equality Act. + +But let’s also pass — let’s also pass the bipartisan Equality Act to ensure LBG- — LGBTQ Americans, especially transgender young people, can live with safety and dignity. + +Our strength — our strength is not just the example of our power, but the power of our example. Let’s remember, the world is watching. + +I spoke from this chamber one year ago, just days after Vladimir Putin unleashed his brutal attack against Ukraine, a murderous assault, evoking images of death and destruction Europe suffered in World War Two. + +Putin’s invasion has been a test for the ages — a test for America, a test for the world. Would we stand for the most basic of principles? Would we stand for sovereignty? Would we stand for the right of people to live free of tyranny? Would we stand for the defense of democracy? For such defense matters to us because it keeps peace and prevents open season on would-be aggressors that threatens our prosperity. + +One year later, we know the answer. Yes, we would. And we did. We did. + +And together, we did what America always does at our best. We led. We united NATO. We built a global coalition. We stood against Putin’s aggression. We stood with the Ukrainian people. + +Tonight, we’re once again joined by Ukrainians’ Ambassador to the United States. She represents not her — just her nation but the courage of her people. Ambassador is — our Ambassador is here, united in our — we’re united in our support of your country. + +Will you stand so we can all take a look at you? Thank you. Because we’re going to stand with you as long as it takes. + +Our nation is working for more freedom, more dignity, and more — more peace, not just in Europe, but everywhere. + +Before I came to office, the story was about how the People’s Republic of China was increasing its power and America was failing in the world. Not anymore. + +We made clear and I made clear in my personal conversations, which have been many, with President Xi that we seek competition, not conflict. But I will make no apologies that we’re investing and — to make America stronger. + +Investing in American innovation and industries that will define the future that China intends to be dominating. + +Investing in our alliances and working with our allies to protect advanced technologies so they will not be used against us. + +Modernizing our military to safeguard stability and determine — deter aggression. + +Today, we’re in the strongest position in decades to compete with China or anyone else in the world. Anyone else in the world. + +And I’m committed — I’m committed to work with China where we can advance American interests and benefit the world. But make no mistake about it: As we made clear last week, if China threatens our sovereignty, we will act to protect our country. And we did. + +Look, let’s be clear: Winning the competition should unite all of us. + +We face serious challenges across the world. But in the past two years, democracies have become stronger, not weaker. Autocracies have grown weaker, not stronger. + +Name me a world leader who’d change places with Xi Jinping. Name me one. Name me one. + +America is rallying the world to meet those challenges — from climate to global health to food insecurity to terrorism to territorial aggression. + +Allies are stepping up, spending more, and doing more. Look, the bridges we’re forming between partners in the Pacific and those in the Atlantic. And those who bet against America are learning how wrong they are. It’s never, ever been a good bet to bet against America. Never. + +Well — + +When I came to office, most assured that bipartisanship — assumed — was impossible. But I never believed it. That’s why a year ago, I offered a Unity Agenda to the nation as I stood here. + +We made real progress together. + +We passed the law making it easier for doctors to prescribe effective treatments for opioid addiction. + +We passed the gun safety law, making historic investments in mental health. + +We launched the ARPA-H drive for breakthroughs in the fight against cancer, Alzheimer’s, and diabetes, and so much more. + +We passed the Heath Robinson PACT Act, named after the late Iraq War veteran whose story about exposure to toxic burn pits I shared here last year. + +And I understand something about those burn pits. + +But there is so much more to do. And we can do it together. + +Joining us tonight is a father named Doug from Newton, New Hampshire. He wrote Jill, my wife, a letter — and me as well — about his courageous daughter, Courtney. A contagious laugh. His sister’s best friend — her sister’s best friend. + +He shared a story all too familiar to millions of Americans and many of you in the audience. Courtney discovered pills in high school. It spiraled into addiction and eventually death from a fentanyl overdose. She was just 20 years old. + +Describing the last eight years without her, Doug said, “There is no worse pain.” Yet, their family has turned pain into purpose, working to end the stigma and change laws. He told us he wants to “start a journey towards American recovery.” + +Doug, we’re with you. Fentanyl is killing more than 70,000 Americans a year. Big — + +Big — you got it. + +So let’s launch a major surge to stop fentanyl production and the sale and trafficking. With more drug detection machines, inspection cargo, stop pills and powder at the border. Working with couriers, like FedEx, to inspect more packages for drugs. Strong penalties to crack down on fentanyl trafficking. + +Second, let’s do more on mental health, especially for our children. When millions of young people are struggling with bullying, violence, trauma, we owe them greater access to mental health care at their schools. + +We must finally hold social media companies accountable for experimenting they’re doing — running [on] children for profit. + +And it’s time to pass bipartisan legislation to stop Big Tech from collecting personal data on kids and teenagers online, ban targeted advertising to children, and impose stricter limits on the personal data that companies collect on all of us. + +Third, let’s do more to keep this nation’s one fully sacred obligation: to equip those we send into harm’s way and care for them and their families when they come home. + +Job training, job placement for veterans and their spouses as they come to — return to civilian life. Helping veterans to afford their rent, because no one should be homeless in America, especially someone who served the country. + +Denis McDoungin [sic] — Denis McDonough is here, of the VA. We had our first real discussion when I asked him to take the job. I’m glad he did. We were losing up to 25 veterans a day on suicide. Now we’re losing 17 a day to the silent scourge of suicide. Seventeen veterans a day are committing suicide, more than all the people being killed in the wars. + +Folks, VA — VA is doing everything it can, including expanding mental health screening, proven programs that recruits veterans to help other veterans understand what they’re going through, get them the help they need. We got to do more. + +And fourth, last year, Jill and I reignited the Cancer Moonshot that I was able to start with, and President Obama asked me to lead our administration on this issue. + +Our goal is to cut the cancer death rates at least by 50 percent in the next 25 years, turn more cancers from death sentences to treatable diseases, provide more support for patients and their families. + +It’s personal to so many of us — so many of us in this audience. + +Joining us are Maurice and Kandice, an Irishman and a daughter of immigrants from Panama. They met and fell in love in New York City and got married in the same chapel as Jill and I got married in New York City. Kindred spirits. + +He wrote us a letter about his little daughter, Ava. And I saw her just before I came over. She was just a year old when she was diagnosed with a rare kidney disease — cancer. After 26 blood transfusions, 11 rounds of radiation, 8 rounds of cheno [sic] — chemo, 1 kidney removed, given a 5 percent survival rate. + +He wrote how, in the darkest moments, he thought, “If she goes, I can’t stay.” + +Many of you have been through that as well. Jill and I understand that, like so many of you. + +And he read Jill’s book describing our family’s cancer journey and how we tried to steal moments of joy where we could with Beau. + +For them, that glimmer of joy was the half-smile of their baby girl. It meant everything to them. They never gave up hope, and little Ava never gave up hope. She turns four next month. + +They just found out Ava is beating the odds and is on her way to being cured of cancer. And she’s watching from the White House tonight, if she’s not asleep already. + +For the lives we can save — for the lives we can save and the lives we have lost, let this be a truly American moment that rallies the country and the world together and prove that we can still do big things. + +Twenty years ago, under the leadership of President Bush and countless advocates and champions, he undertook a bipartisan effort through PEPFAR to transform the global fight against HIV/AIDS. It’s been a huge success. He thought big. He thought large. He moved! + +I believe we can do the same thing with cancer. Let’s end cancer as we know it and cure some cancers once and for all. + +Folks, there’s one reason why we’ve been able to do all of these things: our democracy itself. It’s the most fundamental thing of all. With democracy, everything is possible. Without it, nothing is. + +Over the last few years, our democracy has been threatened and attacked, put at risk — put to the test in this very room on January the 6th. + +And then, just a few months ago, an unhinged Big Lie assailant unleashed a political violence at the home of the then-Speaker of the House of Representatives, using the very same language the insurrectionists used as they stalked these halls and chanted on January 6th. + +Here tonight, in this chamber, is the man who bears the scars of that brutal attack but is as tough and as strong and as resilient as they get: my friend, Paul Pelosi. Paul, stand up. + +But such a heinous act should have never happened. We must all speak out. There is no place for political violence in America. + +We have to protect the right to vote, not suppress the — that fundamental right. Honor the results of our elections, not subvert the will of the people. We have to uphold the rule of the law and restore trust in our institutions of democracy. And we must give hate and extremism in any form no safe harbor. + +Democracy must not be a partisan issue. It’s an American issue. + +Every generation of Americans have faced a moment where they have been called to protect our democracy, defend it, stand up for it. And this is our moment. + +My fellow Americans, we meet tonight at an inflection point, one of those moments that only a few generations ever face, where the direction we now take is going to decide the course of this nation for decades to come. + +We’re not bystanders of history. We’re not powerless before the forces that confront us. It’s within our power of We the People. + +We’re facing the test of our time. We have to be the nation we’ve always been at our best: optimistic, hopeful, forward-looking. A nation that embraces light over dark, hope over fear, unity over division, stability over chaos. + +We have to see each other not as enemies, but as fellow Americans. We’re a good people. The only nation in the world built on an idea — the only one. Other nations are defined by geography, ethnicity, but we’re the only nation based on an idea that all of us, every one of us, is created equal in the image of God. A nation that stands as a beacon to the world. A nation in a new age of possibilities. + +So I have come to fulfil my constitutional obligation to report on the state of the Union. And here is my — my report: Because the soul of this nation is strong, because the backboken [sic] — backbone of this nation is strong, because the people of this nation are strong, the state of the Union is strong. + +Because the soul of this nation is strong. Because the backbone of this nation is strong. Because the people of this nation are strong. The State of the Union is Strong. + +I’m not new to this place. I stand here tonight having served as long as about any one of you who have ever served here. But I’ve never been more optimistic about our future — about the future of America. + +We just have to remember who we are. We’re the United States of America. And there’s nothing — nothing beyond our capacity if we do it together. + +God bless you all. And may God protect our troops. Thank you. diff --git a/examples/chat_with_your_documents/load_data.py b/examples/chat_with_your_documents/load_data.py new file mode 100644 index 0000000000000000000000000000000000000000..b9ffdbb116a8653da47ee6e229b021f61a977757 --- /dev/null +++ b/examples/chat_with_your_documents/load_data.py @@ -0,0 +1,91 @@ +import os +import argparse + +from tqdm import tqdm + +import chromadb + + +def main( + documents_directory: str = "documents", + collection_name: str = "documents_collection", + persist_directory: str = ".", +) -> None: + # Read all files in the data directory + documents = [] + metadatas = [] + files = os.listdir(documents_directory) + for filename in files: + with open(f"{documents_directory}/{filename}", "r") as file: + for line_number, line in enumerate( + tqdm((file.readlines()), desc=f"Reading {filename}"), 1 + ): + # Strip whitespace and append the line to the documents list + line = line.strip() + # Skip empty lines + if len(line) == 0: + continue + documents.append(line) + metadatas.append({"filename": filename, "line_number": line_number}) + + # Instantiate a persistent chroma client in the persist_directory. + # Learn more at docs.trychroma.com + client = chromadb.PersistentClient(path=persist_directory) + + # If the collection already exists, we just return it. This allows us to add more + # data to an existing collection. + collection = client.get_or_create_collection(name=collection_name) + + # Create ids from the current count + count = collection.count() + print(f"Collection already contains {count} documents") + ids = [str(i) for i in range(count, count + len(documents))] + + # Load the documents in batches of 100 + for i in tqdm( + range(0, len(documents), 100), desc="Adding documents", unit_scale=100 + ): + collection.add( + ids=ids[i : i + 100], + documents=documents[i : i + 100], + metadatas=metadatas[i : i + 100], # type: ignore + ) + + new_count = collection.count() + print(f"Added {new_count - count} documents") + + +if __name__ == "__main__": + # Read the data directory, collection name, and persist directory + parser = argparse.ArgumentParser( + description="Load documents from a directory into a Chroma collection" + ) + + # Add arguments + parser.add_argument( + "--data_directory", + type=str, + default="documents", + help="The directory where your text files are stored", + ) + parser.add_argument( + "--collection_name", + type=str, + default="documents_collection", + help="The name of the Chroma collection", + ) + parser.add_argument( + "--persist_directory", + type=str, + default="chroma_storage", + help="The directory where you want to store the Chroma collection", + ) + + # Parse arguments + args = parser.parse_args() + + main( + documents_directory=args.data_directory, + collection_name=args.collection_name, + persist_directory=args.persist_directory, + ) diff --git a/examples/chat_with_your_documents/main.py b/examples/chat_with_your_documents/main.py new file mode 100644 index 0000000000000000000000000000000000000000..dcc631beb7831bda42e9f17abe4664a0dbc3b138 --- /dev/null +++ b/examples/chat_with_your_documents/main.py @@ -0,0 +1,142 @@ +import argparse +import os +from typing import List, Dict +from openai.types.chat import ChatCompletionMessageParam +import openai +import chromadb + + +def build_prompt(query: str, context: List[str]) -> List[ChatCompletionMessageParam]: + """ + Builds a prompt for the LLM. # + + This function builds a prompt for the LLM. It takes the original query, + and the returned context, and asks the model to answer the question based only + on what's in the context, not what's in its weights. + + More information: https://platform.openai.com/docs/guides/chat/introduction + + Args: + query (str): The original query. + context (List[str]): The context of the query, returned by embedding search. + + Returns: + A prompt for the LLM (List[ChatCompletionMessageParam]). + """ + + system: ChatCompletionMessageParam = { + "role": "system", + "content": "I am going to ask you a question, which I would like you to answer" + "based only on the provided context, and not any other information." + "If there is not enough information in the context to answer the question," + 'say "I am not sure", then try to make a guess.' + "Break your answer up into nicely readable paragraphs.", + } + user: ChatCompletionMessageParam = { + "role": "user", + "content": f"The question is {query}. Here is all the context you have:" + f'{(" ").join(context)}', + } + + return [system, user] + + +def get_chatGPT_response(query: str, context: List[str], model_name: str) -> str: + """ + Queries the GPT API to get a response to the question. + + Args: + query (str): The original query. + context (List[str]): The context of the query, returned by embedding search. + + Returns: + A response to the question. + """ + response = openai.chat.completions.create( + model=model_name, + messages=build_prompt(query, context), + ) + + return response.choices[0].message.content # type: ignore + + +def main( + collection_name: str = "documents_collection", persist_directory: str = "." +) -> None: + + # Check if the OPENAI_API_KEY environment variable is set. Prompt the user to set it if not. + if "OPENAI_API_KEY" not in os.environ: + openai.api_key = input( + "Please enter your OpenAI API Key. You can get it from https://platform.openai.com/account/api-keys\n" + ) + + # Ask what model to use + model_name = "gpt-3.5-turbo" + answer = input(f"Do you want to use GPT-4? (y/n) (default is {model_name}): ") + if answer == "y": + model_name = "gpt-4" + + # Instantiate a persistent chroma client in the persist_directory. + # This will automatically load any previously saved collections. + # Learn more at docs.trychroma.com + client = chromadb.PersistentClient(path=persist_directory) + + # Get the collection. + collection = client.get_collection(name=collection_name) + + # We use a simple input loop. + while True: + # Get the user's query + query = input("Query: ") + if len(query) == 0: + print("Please enter a question. Ctrl+C to Quit.\n") + continue + print(f"\nThinking using {model_name}...\n") + + # Query the collection to get the 5 most relevant results + results = collection.query( + query_texts=[query], n_results=5, include=["documents", "metadatas"] + ) + + sources = "\n".join( + [ + f"{result['filename']}: line {result['line_number']}" + for result in results["metadatas"][0] # type: ignore + ] + ) + + # Get the response from GPT + response = get_chatGPT_response(query, results["documents"][0], model_name) # type: ignore + + # Output, with sources + print(response) + print("\n") + print(f"Source documents:\n{sources}") + print("\n") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Load documents from a directory into a Chroma collection" + ) + + parser.add_argument( + "--persist_directory", + type=str, + default="chroma_storage", + help="The directory where you want to store the Chroma collection", + ) + parser.add_argument( + "--collection_name", + type=str, + default="documents_collection", + help="The name of the Chroma collection", + ) + + # Parse arguments + args = parser.parse_args() + + main( + collection_name=args.collection_name, + persist_directory=args.persist_directory, + ) diff --git a/examples/chat_with_your_documents/requirements.txt b/examples/chat_with_your_documents/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..61a378d9ea4575fe7ad4bfa30e48c77cf6c57b68 --- /dev/null +++ b/examples/chat_with_your_documents/requirements.txt @@ -0,0 +1,3 @@ +chromadb>=0.4.4 +openai>=1.7.2 +tqdm diff --git a/examples/deployments/aws-terraform/README.md b/examples/deployments/aws-terraform/README.md new file mode 100644 index 0000000000000000000000000000000000000000..332cfd7265cb32a17cad69623ac39389906fae76 --- /dev/null +++ b/examples/deployments/aws-terraform/README.md @@ -0,0 +1,170 @@ +# AWS EC2 Basic Deployment + +This is an example deployment to AWS EC2 Compute using [terraform](https://www.terraform.io/). + +This deployment will do the following: + +- Create a security group with required ports open (22 and 8000) +- Create EC2 instance with Ubuntu 22 and deploy Chroma using docker compose +- Create a data volume for Chroma data +- Mount the data volume to the EC2 instance +- Format the data volume with ext4 +- Start Chroma + +## Requirements + +- [Terraform CLI v1.3.4+](https://developer.hashicorp.com/terraform/tutorials/gcp-get-started/install-cli) + +## Deployment with terraform + +This deployment uses Ubuntu 22 as foundation, but you'd like to use a different AMI (non-Debian based image) you may have to adjust the startup script. + +To find AWS EC2 AMIs you can use: + +```bash +# 099720109477 is Canonical +aws ec2 describe-images \ + --owners 099720109477 \ + --filters 'Name=name,Values=ubuntu/images/*/ubuntu-jammy*' \ + --query 'sort_by(Images,&CreationDate)[-1].ImageId' +``` + +### 2. Init your terraform state +```bash +terraform init +``` + +### 3. Deploy your application + +Generate SSH key to use with your chroma instance (so you can login to the EC2): + +> Note: This is optional. You can use your own existing SSH key if you prefer. + +```bash +ssh-keygen -t RSA -b 4096 -C "Chroma AWS Key" -N "" -f ./chroma-aws && chmod 400 ./chroma-aws +``` + +Set up your Terraform variables and deploy your instance: + +```bash +#AWS access key +export TF_VAR_AWS_ACCESS_KEY= +#AWS secret access key +export TF_VAR_AWS_SECRET_ACCESS_KEY= +#path to the public key you generated above (or can be different if you want to use your own key) +export TF_ssh_public_key="./chroma-aws.pub" +#path to the private key you generated above (or can be different if you want to use your own key) - used for formatting the Chroma data volume +export TF_ssh_private_key="./chroma-aws" +#set the chroma release to deploy +export TF_VAR_chroma_release=0.4.12 +# AWS region to deploy the chroma instance to +export TF_VAR_region="us-west-1" +#enable public access to the chroma instance on port 8000 +export TF_VAR_public_access="true" +#enable basic auth for the chroma instance +export TF_VAR_enable_auth="true" +#The auth type to use for the chroma instance (token or basic) +export TF_VAR_auth_type="token" +#optional - if you want to restore from a snapshot +export TF_VAR_chroma_data_restore_from_snapshot_id="" +#optional - if you want to snapshot the data volume before destroying the instance +export TF_VAR_chroma_data_volume_snapshot_before_destroy="true" +terraform apply -auto-approve +``` +> Note: Basic Auth is supported by Chroma v0.4.7+ + +### 4. Check your public IP and that Chroma is running + +Get the public IP of your instance + +```bash +terraform output instance_public_ip +``` + +Check that chroma is running (It should take up several minutes for the instance to be ready) + +```bash +export instance_public_ip=$(terraform output instance_public_ip | sed 's/"//g') +curl -v http://$instance_public_ip:8000/api/v1/heartbeat +``` + +#### 4.1 Checking Auth + +##### Token +When token auth is enabled you can check the get the credentials from Terraform state by running: + +```bash +terraform output chroma_auth_token +``` + +You should see something of the form: + +```bash +PVcQ4qUUnmahXwUgAf3UuYZoMlos6MnF +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_token | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v http://$instance_public_ip:8000/api/v1/collections -H "Authorization: Bearer ${CHROMA_AUTH}" +``` + +##### Basic +When basic auth is enabled you can check the get the credentials from Terraform state by running: + +```bash +terraform output chroma_auth_basic +``` + +You should see something of the form: + +```bash +chroma:VuA8I}QyNrm0@QLq +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_basic | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v http://$instance_public_ip:8000/api/v1/collections -u "${CHROMA_AUTH}" +``` + +> Note: Without `-u` you should be getting 401 Unauthorized response + +#### 4.2 Connect (ssh) to your instance + + +To SSH to your instance: + +```bash +ssh -i ./chroma-aws ubuntu@$instance_public_ip +``` + +### 5. Destroy your Chroma instance + +You will need to change `prevent_destroy` to `false` in the `aws_ebs_volume` in `chroma.tf`. + +```bash +terraform destroy -auto-approve +``` + +## Extras + +You can visualize your infrastructure with: + +```bash +terraform graph | dot -Tsvg > graph.svg +``` + +>Note: You will need graphviz installed for this to work diff --git a/examples/deployments/aws-terraform/chroma.tf b/examples/deployments/aws-terraform/chroma.tf new file mode 100644 index 0000000000000000000000000000000000000000..bd44c62e3196fa62f2694ba2fe501ef45a6d0983 --- /dev/null +++ b/examples/deployments/aws-terraform/chroma.tf @@ -0,0 +1,158 @@ +terraform { + required_providers { + aws = { + source = "hashicorp/aws" + version = "~> 5.0" + } + } +} + +# Define provider +variable "AWS_ACCESS_KEY" {} +variable "AWS_SECRET_ACCESS_KEY" {} + +provider "aws" { + access_key = var.AWS_ACCESS_KEY + secret_key = var.AWS_SECRET_ACCESS_KEY + region = var.region +} + +# Create security group +resource "aws_security_group" "chroma_sg" { + name = "chroma-cluster-sg" + description = "Security group for the cluster nodes" + + ingress { + from_port = 22 + to_port = 22 + protocol = "tcp" + cidr_blocks = var.mgmt_source_ranges + } + + dynamic "ingress" { + for_each = var.public_access ? [1] : [] + content { + from_port = var.chroma_port + to_port = 8000 + protocol = "tcp" + cidr_blocks = var.source_ranges + } + } + + egress { + from_port = 0 + to_port = 0 + protocol = "-1" + cidr_blocks = ["0.0.0.0/0"] + ipv6_cidr_blocks = ["::/0"] + } + + tags = local.tags +} + +resource "aws_key_pair" "chroma-keypair" { + key_name = "chroma-keypair" # Replace with your desired key pair name + public_key = file(var.ssh_public_key) # Replace with the path to your public key file +} + +data "aws_ami" "ubuntu" { + most_recent = true + + filter { + name = "name" + values = ["ubuntu/images/hvm-ssd/ubuntu-jammy*"] + } + + filter { + name = "virtualization-type" + values = ["hvm"] + } + filter { + name = "architecture" + values = ["x86_64"] + } + + owners = ["099720109477"] # Canonical +} +# Create EC2 instances +resource "aws_instance" "chroma_instance" { + ami = data.aws_ami.ubuntu.id + instance_type = var.instance_type + key_name = "chroma-keypair" + security_groups = [aws_security_group.chroma_sg.name] + + user_data = data.template_file.user_data.rendered + + tags = local.tags + + ebs_block_device { + device_name = "/dev/sda1" + volume_size = var.chroma_instance_volume_size # size in GBs + } +} + + +resource "aws_ebs_volume" "chroma-volume" { + availability_zone = aws_instance.chroma_instance.availability_zone + size = var.chroma_data_volume_size + final_snapshot = var.chroma_data_volume_snapshot_before_destroy + snapshot_id = var.chroma_data_restore_from_snapshot_id + + tags = local.tags + + lifecycle { + prevent_destroy = true + } +} + +locals { + cleaned_volume_id = replace(aws_ebs_volume.chroma-volume.id, "-", "") +} + +locals { + restore_from_snapshot = length(var.chroma_data_restore_from_snapshot_id) == 0 ? false : true +} + +resource "aws_volume_attachment" "chroma_volume_attachment" { + device_name = "/dev/sdh" + volume_id = aws_ebs_volume.chroma-volume.id + instance_id = aws_instance.chroma_instance.id + provisioner "remote-exec" { + inline = [ + "if [ -z \"${local.restore_from_snapshot}\" ]; then export VOLUME_ID=${local.cleaned_volume_id} && sudo mkfs -t ext4 /dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}'); fi", + "sudo mkdir /chroma-data", + "export VOLUME_ID=${local.cleaned_volume_id} && sudo mount /dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}') /chroma-data", + "export VOLUME_ID=${local.cleaned_volume_id} && cat <> /dev/null", + "/dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}') /chroma-data ext4 defaults,nofail,discard 0 0", + "EOF", + ] + + connection { + host = aws_instance.chroma_instance.public_ip + type = "ssh" + user = "ubuntu" + private_key = file(var.ssh_private_key) + } + } + depends_on = [aws_instance.chroma_instance, aws_ebs_volume.chroma-volume] +} + + +output "instance_public_ip" { + value = aws_instance.chroma_instance.public_ip +} + +output "instance_private_ip" { + value = aws_instance.chroma_instance.private_ip +} + +output "chroma_auth_token" { + value = random_password.chroma_token.result + sensitive = true +} + + +output "chroma_auth_basic" { + value = "${local.basic_auth_credentials.username}:${local.basic_auth_credentials.password}" + sensitive = true +} diff --git a/examples/deployments/aws-terraform/startup.sh b/examples/deployments/aws-terraform/startup.sh new file mode 100644 index 0000000000000000000000000000000000000000..239e27da0fb2bd277fac8dfb43e0ecb6f85eef85 --- /dev/null +++ b/examples/deployments/aws-terraform/startup.sh @@ -0,0 +1,53 @@ +#! /bin/bash + +# Note: This is run as root + +cd ~ +export enable_auth="${enable_auth}" +export basic_auth_credentials="${basic_auth_credentials}" +export auth_type="${auth_type}" +export token_auth_credentials="${token_auth_credentials}" +apt-get update -y +apt-get install -y ca-certificates curl gnupg lsb-release +mkdir -m 0755 -p /etc/apt/keyrings +curl -fsSL https://download.docker.com/linux/ubuntu/gpg | gpg --dearmor -o /etc/apt/keyrings/docker.gpg +echo \ + "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \ + $(lsb_release -cs) stable" | tee /etc/apt/sources.list.d/docker.list > /dev/null +apt-get update -y +chmod a+r /etc/apt/keyrings/docker.gpg +apt-get update -y +apt-get install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin git +usermod -aG docker ubuntu +git clone https://github.com/chroma-core/chroma.git && cd chroma +git fetch --tags +git checkout tags/${chroma_release} + +if [ "$${enable_auth}" = "true" ] && [ "$${auth_type}" = "basic" ] && [ ! -z "$${basic_auth_credentials}" ]; then + username=$(echo $basic_auth_credentials | cut -d: -f1) + password=$(echo $basic_auth_credentials | cut -d: -f2) + docker run --rm --entrypoint htpasswd httpd:2 -Bbn $username $password > server.htpasswd + cat < .env +CHROMA_SERVER_AUTH_CREDENTIALS_FILE="/chroma/server.htpasswd" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.basic.BasicAuthServerProvider" +EOF +fi + +if [ "$${enable_auth}" = "true" ] && [ "$${auth_type}" = "token" ] && [ ! -z "$${token_auth_credentials}" ]; then + cat < .env +CHROMA_SERVER_AUTH_CREDENTIALS="$${token_auth_credentials}" \ +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.token.TokenAuthServerProvider" +EOF +fi + +cat < docker-compose.override.yaml +version: '3.8' +services: + server: + volumes: + - /chroma-data:/chroma/chroma +EOF + +COMPOSE_PROJECT_NAME=chroma docker compose up -d --build diff --git a/examples/deployments/aws-terraform/variables.tf b/examples/deployments/aws-terraform/variables.tf new file mode 100644 index 0000000000000000000000000000000000000000..e7b7cd9b6700fe58b0a29da64121db4d6157eb83 --- /dev/null +++ b/examples/deployments/aws-terraform/variables.tf @@ -0,0 +1,139 @@ +variable "chroma_release" { + description = "The chroma release to deploy" + type = string + default = "0.4.12" +} + +#TODO this should be updated to point to https://raw.githubusercontent.com/chroma-core/chroma/main/examples/deployments/common/startup.sh in the repo +data "http" "startup_script_remote" { + url = "https://raw.githubusercontent.com/chroma-core/chroma/main/examples/deployments/aws-terraform/startup.sh" +} + +data "template_file" "user_data" { + template = data.http.startup_script_remote.response_body + + vars = { + chroma_release = var.chroma_release + enable_auth = var.enable_auth + auth_type = var.auth_type + basic_auth_credentials = "${local.basic_auth_credentials.username}:${local.basic_auth_credentials.password}" + token_auth_credentials = random_password.chroma_token.result + } +} + +variable "region" { + description = "AWS Region" + type = string + default = "us-west-1" +} + +variable "instance_type" { + description = "AWS EC2 Instance Type" + type = string + default = "t3.medium" +} + + +variable "public_access" { + description = "Enable public ingress on port 8000" + type = bool + default = true // or true depending on your needs +} + +variable "enable_auth" { + description = "Enable authentication" + type = bool + default = true // or false depending on your needs +} + +variable "auth_type" { + description = "Authentication type" + type = string + default = "token" // or token depending on your needs + validation { + condition = contains(["basic", "token"], var.auth_type) + error_message = "The auth type must be either basic or token" + } +} + +resource "random_password" "chroma_password" { + length = 16 + special = true + lower = true + upper = true +} + +resource "random_password" "chroma_token" { + length = 32 + special = false + lower = true + upper = true +} + + +locals { + basic_auth_credentials = { + username = "chroma" + password = random_password.chroma_password.result + } + token_auth_credentials = { + token = random_password.chroma_token.result + } + tags = [ + "chroma", + "release-${replace(var.chroma_release, ".", "")}", + ] +} + +variable "ssh_public_key" { + description = "SSH Public Key" + type = string + default = "./chroma-aws.pub" +} +variable "ssh_private_key" { + description = "SSH Private Key" + type = string + default = "./chroma-aws" +} + +variable "chroma_instance_volume_size" { + description = "The size of the instance volume - the root volume" + type = number + default = 30 +} + +variable "chroma_data_volume_size" { + description = "EBS Volume Size of the attached data volume where your chroma data is stored" + type = number + default = 20 +} + +variable "chroma_data_volume_snapshot_before_destroy" { + description = "Take a snapshot of the chroma data volume before destroying it" + type = bool + default = false +} + +variable "chroma_data_restore_from_snapshot_id" { + description = "Restore the chroma data volume from a snapshot" + type = string + default = null +} + +variable "chroma_port" { + default = "8000" + description = "The port that chroma listens on" + type = string +} + +variable "source_ranges" { + default = ["0.0.0.0/0", "::/0"] + type = list(string) + description = "List of CIDR ranges to allow through the firewall" +} + +variable "mgmt_source_ranges" { + default = ["0.0.0.0/0", "::/0"] + type = list(string) + description = "List of CIDR ranges to allow for management of the Chroma instance. This is used for SSH incoming traffic filtering" +} diff --git a/examples/deployments/common/startup.sh b/examples/deployments/common/startup.sh new file mode 100644 index 0000000000000000000000000000000000000000..d9902da7b12527441141dd5755bd3ec8dd5491cf --- /dev/null +++ b/examples/deployments/common/startup.sh @@ -0,0 +1,53 @@ +#! /bin/bash + +# Note: This is run as root + +cd ~ +export enable_auth="${enable_auth}" +export basic_auth_credentials="${basic_auth_credentials}" +export auth_type="${auth_type}" +export token_auth_credentials="${token_auth_credentials}" +apt-get update -y +apt-get install -y ca-certificates curl gnupg lsb-release +mkdir -m 0755 -p /etc/apt/keyrings +curl -fsSL https://download.docker.com/linux/ubuntu/gpg | gpg --dearmor -o /etc/apt/keyrings/docker.gpg +echo \ + "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \ + $(lsb_release -cs) stable" | tee /etc/apt/sources.list.d/docker.list > /dev/null +apt-get update -y +chmod a+r /etc/apt/keyrings/docker.gpg +apt-get update -y +apt-get install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin git +usermod -aG docker ubuntu +git clone https://github.com/chroma-core/chroma.git && cd chroma +git fetch --tags +git checkout tags/${chroma_release} + +if [ "$${enable_auth}" = "true" ] && [ "$${auth_type}" = "basic" ] && [ ! -z "$${basic_auth_credentials}" ]; then + username=$(echo $basic_auth_credentials | cut -d: -f1) + password=$(echo $basic_auth_credentials | cut -d: -f2) + docker run --rm --entrypoint htpasswd httpd:2 -Bbn $username $password > server.htpasswd + cat < .env +CHROMA_SERVER_AUTH_CREDENTIALS_FILE="/chroma/server.htpasswd" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.basic.BasicAuthServerProvider" +EOF +fi + +if [ "$${enable_auth}" = "true" ] && [ "$${auth_type}" = "token" ] && [ ! -z "$${token_auth_credentials}" ]; then + cat < .env +CHROMA_SERVER_AUTH_CREDENTIALS="$${token_auth_credentials}" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.token.TokenAuthServerProvider" +EOF +fi + +cat < docker-compose.override.yaml +version: '3.8' +services: + server: + volumes: + - /chroma-data:/chroma/chroma +EOF + +COMPOSE_PROJECT_NAME=chroma docker compose up -d --build diff --git a/examples/deployments/do-terraform/README.md b/examples/deployments/do-terraform/README.md new file mode 100644 index 0000000000000000000000000000000000000000..80957bdd8100febdb1e7afe730a0f4e8500e925e --- /dev/null +++ b/examples/deployments/do-terraform/README.md @@ -0,0 +1,163 @@ +# Digital Ocean Droplet Deployment + +This is an example deployment using Digital Ocean Droplet using [terraform](https://www.terraform.io/). + +This deployment will do the following: + +- 🔥 Create a firewall with required ports open (22 and 8000) +- 🐳 Create Droplet with Ubuntu 22 and deploy Chroma using docker compose +- 💿 Create a data volume for Chroma data +- 🗻 Mount the data volume to the Droplet instance +- ✏️ Format the data volume with ext4 +- 🏃‍ Start Chroma + +## Requirements + +- [Terraform CLI v1.3.4+](https://developer.hashicorp.com/terraform/tutorials/gcp-get-started/install-cli) + +## Deployment with terraform + +This deployment uses Ubuntu 22 as foundation, but you'd like to use a different image for your Droplet ( +see https://slugs.do-api.dev/ for a list of available images) + +### Configuration Options + + +### 1. Init your terraform state + +```bash +terraform init +``` + +### 2. Deploy your application + +Generate SSH key to use with your chroma instance (so you can log in to the Droplet): + +> Note: This is optional. You can use your own existing SSH key if you prefer. + +```bash +ssh-keygen -t RSA -b 4096 -C "Chroma DO Key" -N "" -f ./chroma-do && chmod 400 ./chroma-do +``` + +Set up your Terraform variables and deploy your instance: + +```bash +#take note of this as it must be present in all of the subsequent steps +export TF_VAR_do_token= +#path to the public key you generated above (or can be different if you want to use your own key) +export TF_ssh_public_key="./chroma-do.pub" +#path to the private key you generated above (or can be different if you want to use your own key) - used for formatting the Chroma data volume +export TF_ssh_private_key="./chroma-do" +#set the chroma release to deploy +export TF_VAR_chroma_release="0.4.12" +# DO region to deploy the chroma instance to +export TF_VAR_region="ams2" +#enable public access to the chroma instance on port 8000 +export TF_VAR_public_access="true" +#enable basic auth for the chroma instance +export TF_VAR_enable_auth="true" +#The auth type to use for the chroma instance (token or basic) +export TF_VAR_auth_type="token" +terraform apply -auto-approve +``` + +> Note: Basic Auth is supported by Chroma v0.4.7+ + +### 4. Check your public IP and that Chroma is running + +Get the public IP of your instance + +```bash +terraform output instance_public_ip +``` + +Check that chroma is running (It should take up several minutes for the instance to be ready) + +```bash +export instance_public_ip=$(terraform output instance_public_ip | sed 's/"//g') +curl -v http://$instance_public_ip:8000/api/v1/heartbeat +``` + +#### 4.1 Checking Auth + +##### Token + +When token auth is enabled you can check the get the credentials from Terraform state by running: + +```bash +terraform output chroma_auth_token +``` + +You should see something of the form: + +```bash +PVcQ4qUUnmahXwUgAf3UuYZoMlos6MnF +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_token | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v http://$instance_public_ip:8000/api/v1/collections -H "Authorization: Bearer ${CHROMA_AUTH}" +``` + +##### Basic + +When basic auth is enabled you can check the get the credentials from Terraform state by running: + +```bash +terraform output chroma_auth_basic +``` + +You should see something of the form: + +```bash +chroma:VuA8I}QyNrm0@QLq +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_basic | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v http://$instance_public_ip:8000/api/v1/collections -u "${CHROMA_AUTH}" +``` + +> Note: Without `-u` you should be getting 401 Unauthorized response + +#### 4.2 SSH to your instance + +To SSH to your instance: + +```bash +ssh -i ./chroma-do root@$instance_public_ip +``` + +### 5. Destroy your Chroma instance + +```bash +terraform destroy -auto-approve +``` + +## Extras + +You can visualize your infrastructure with: + +```bash +terraform graph | dot -Tsvg > graph.svg +``` + +> Note: You will need graphviz installed for this to work + +### Digital Ocean Resource Types + +Refs: https://slugs.do-api.dev/ diff --git a/examples/deployments/do-terraform/chroma.tf b/examples/deployments/do-terraform/chroma.tf new file mode 100644 index 0000000000000000000000000000000000000000..79960c80fe995418b05edb5bd26de23e21ea3918 --- /dev/null +++ b/examples/deployments/do-terraform/chroma.tf @@ -0,0 +1,133 @@ +terraform { + required_providers { + digitalocean = { + source = "digitalocean/digitalocean" + version = "~> 2.0" + } + } +} + +# Define provider +variable "do_token" {} + +# Configure the DigitalOcean Provider +provider "digitalocean" { + token = var.do_token +} + + +resource "digitalocean_firewall" "chroma_firewall" { + name = "chroma-firewall" + + droplet_ids = [digitalocean_droplet.chroma_instance.id] + + inbound_rule { + protocol = "tcp" + port_range = "22" + source_addresses = var.mgmt_source_ranges + } + + dynamic "inbound_rule" { + for_each = var.public_access ? [1] : [] + content { + protocol = "tcp" + port_range = var.chroma_port + source_addresses = var.source_ranges + } + } + + outbound_rule { + protocol = "tcp" + port_range = "1-65535" + destination_addresses = ["0.0.0.0/0", "::/0"] + } + + outbound_rule { + protocol = "icmp" + port_range = "1-65535" + destination_addresses = ["0.0.0.0/0", "::/0"] + } + + outbound_rule { + protocol = "udp" + port_range = "1-65535" + destination_addresses = ["0.0.0.0/0", "::/0"] + } + + tags = local.tags + +} + +resource "digitalocean_ssh_key" "chroma_keypair" { + name = "chroma_keypair" + public_key = file(var.ssh_public_key) +} + + +#Create Droplet +resource "digitalocean_droplet" "chroma_instance" { + image = var.instance_image + name = "chroma" + region = var.region + size = var.instance_type + ssh_keys = [digitalocean_ssh_key.chroma_keypair.fingerprint] + + user_data = data.template_file.user_data.rendered + + tags = local.tags +} + + +resource "digitalocean_volume" "chroma_volume" { + region = digitalocean_droplet.chroma_instance.region + name = "chroma-volume" + size = var.chroma_data_volume_size + description = "Chroma data volume" + tags = local.tags +} + +resource "digitalocean_volume_attachment" "chroma_data_volume_attachment" { + droplet_id = digitalocean_droplet.chroma_instance.id + volume_id = digitalocean_volume.chroma_volume.id + + provisioner "remote-exec" { + inline = [ + "export VOLUME_ID=${digitalocean_volume.chroma_volume.name} && sudo mkfs -t ext4 /dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}')", + "sudo mkdir /chroma-data", + "export VOLUME_ID=${digitalocean_volume.chroma_volume.name} && sudo mount /dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}') /chroma-data", + "cat <> /dev/null", + "/dev/disk/by-id/scsi-0DO_Volume_${digitalocean_volume.chroma_volume.name} /chroma-data ext4 defaults,nofail,discard 0 0", + "EOF", + ] + + connection { + host = digitalocean_droplet.chroma_instance.ipv4_address + type = "ssh" + user = "root" + private_key = file(var.ssh_private_key) + } + } +} + + +output "instance_public_ip" { + value = digitalocean_droplet.chroma_instance.ipv4_address + description = "The public IP address of the Chroma instance" +} + +output "instance_private_ip" { + value = digitalocean_droplet.chroma_instance.ipv4_address_private + description = "The private IP address of the Chroma instance" +} + +output "chroma_auth_token" { + description = "The Chroma static auth token" + value = random_password.chroma_token.result + sensitive = true +} + +output "chroma_auth_basic" { + description = "The Chroma basic auth credentials" + value = "${local.basic_auth_credentials.username}:${local.basic_auth_credentials.password}" + sensitive = true +} diff --git a/examples/deployments/do-terraform/variables.tf b/examples/deployments/do-terraform/variables.tf new file mode 100644 index 0000000000000000000000000000000000000000..75ce6dc9a37f6a93bec5d55fa6abd44f031560c6 --- /dev/null +++ b/examples/deployments/do-terraform/variables.tf @@ -0,0 +1,126 @@ +variable "instance_image" { + description = "The image to use for the instance" + type = string + default = "ubuntu-22-04-x64" +} +variable "chroma_release" { + description = "The chroma release to deploy" + type = string + default = "0.4.12" +} + +data "http" "startup_script_remote" { + url = "https://raw.githubusercontent.com/chroma-core/chroma/main/examples/deployments/common/startup.sh" +} + +data "template_file" "user_data" { + template = data.http.startup_script_remote.response_body + + vars = { + chroma_release = var.chroma_release + enable_auth = var.enable_auth + auth_type = var.auth_type + basic_auth_credentials = "${local.basic_auth_credentials.username}:${local.basic_auth_credentials.password}" + token_auth_credentials = random_password.chroma_token.result + } +} + +variable "region" { + description = "DO Region" + type = string + default = "nyc2" +} + +variable "instance_type" { + description = "Droplet size" + type = string + default = "s-2vcpu-4gb" +} + + +variable "public_access" { + description = "Enable public ingress on port 8000" + type = bool + default = true // or false depending on your needs +} + +variable "enable_auth" { + description = "Enable authentication" + type = bool + default = true // or false depending on your needs +} + +variable "auth_type" { + description = "Authentication type" + type = string + default = "token" // or basic depending on your needs + validation { + condition = contains(["basic", "token"], var.auth_type) + error_message = "The auth type must be either basic or token" + } +} + +resource "random_password" "chroma_password" { + length = 16 + special = true + lower = true + upper = true +} + +resource "random_password" "chroma_token" { + length = 32 + special = false + lower = true + upper = true +} + + +locals { + basic_auth_credentials = { + username = "chroma" + password = random_password.chroma_password.result + } + token_auth_credentials = { + token = random_password.chroma_token.result + } + tags = [ + "chroma", + "release-${replace(var.chroma_release, ".", "")}", + ] +} + +variable "ssh_public_key" { + description = "SSH Public Key" + type = string + default = "./chroma-do.pub" +} +variable "ssh_private_key" { + description = "SSH Private Key" + type = string + default = "./chroma-do" +} + +variable "chroma_data_volume_size" { + description = "EBS Volume Size of the attached data volume where your chroma data is stored" + type = number + default = 20 +} + + +variable "chroma_port" { + default = "8000" + description = "The port that chroma listens on" + type = string +} + +variable "source_ranges" { + default = ["0.0.0.0/0", "::/0"] + type = list(string) + description = "List of CIDR ranges to allow through the firewall" +} + +variable "mgmt_source_ranges" { + default = ["0.0.0.0/0", "::/0"] + type = list(string) + description = "List of CIDR ranges to allow for management of the Chroma instance. This is used for SSH incoming traffic filtering" +} diff --git a/examples/deployments/google-cloud-compute/README.md b/examples/deployments/google-cloud-compute/README.md new file mode 100644 index 0000000000000000000000000000000000000000..ea25613baf466ce9deb8eb41647b83cdefcda9bc --- /dev/null +++ b/examples/deployments/google-cloud-compute/README.md @@ -0,0 +1,137 @@ +# Google Cloud Compute Deployment + +This is an example deployment to Google Cloud Compute using [terraform](https://www.terraform.io/) + +## Requirements + +- [gcloud CLI](https://cloud.google.com/sdk/gcloud) +- [Terraform CLI v1.3.4+](https://developer.hashicorp.com/terraform/tutorials/gcp-get-started/install-cli) +- [Terraform GCP provider](https://registry.terraform.io/providers/hashicorp/google/latest/docs) + +## Deployment with terraform + +### 1. Auth to your Google Cloud project + +```bash +gcloud auth application-default login +``` + +### 2. Init your terraform state + +```bash +terraform init +``` + +### 3. Deploy your application + +> **WARNING**: GCP Terraform provider does not allow use of variables in the lifecycle of the volume. By default, the +> template does not prevent deletion of the volume however if you plan to use this template for production deployment you +> may consider change the value of `prevent_destroy` to `true` in `chroma.tf` file. + +Generate SSH key to use with your chroma instance (so you can SSH to the GCP VM): + +> Note: This is optional. You can use your own existing SSH key if you prefer. + +```bash +ssh-keygen -t RSA -b 4096 -C "Chroma AWS Key" -N "" -f ./chroma-aws && chmod 400 ./chroma-aws +``` + +```bash +export TF_VAR_project_id= #take note of this as it must be present in all of the subsequent steps +export TF_ssh_public_key="./chroma-aws.pub" #path to the public key you generated above (or can be different if you want to use your own key) +export TF_ssh_private_key="./chroma-aws" #path to the private key you generated above (or can be different if you want to use your own key) - used for formatting the Chroma data volume +export TF_VAR_chroma_release="0.4.9" #set the chroma release to deploy +export TF_VAR_zone="us-central1-a" # AWS region to deploy the chroma instance to +export TF_VAR_public_access="true" #enable public access to the chroma instance on port 8000 +export TF_VAR_enable_auth="true" #enable basic auth for the chroma instance +export TF_VAR_auth_type="token" #The auth type to use for the chroma instance (token or basic) +terraform apply -auto-approve +``` + +### 4. Check your public IP and that Chroma is running + +> Note: Depending on your instance type it might take a few minutes for the instance to be ready + +Get the public IP of your instance (it should also be printed out after successful `terraform apply`): + +```bash +terraform output instance_public_ip +``` + +Check that chroma is running: + +```bash +export instance_public_ip=$(terraform output instance_public_ip | sed 's/"//g') +curl -v http://$instance_public_ip:8000/api/v1/heartbeat +``` + +#### 4.1 Checking Auth + +##### Token + +When token auth is enabled (this is the default option) you can check the get the credentials from Terraform state by +running: + +```bash +terraform output chroma_auth_token +``` + +You should see something of the form: + +```bash +PVcQ4qUUnmahXwUgAf3UuYZoMlos6MnF +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_token | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v http://$instance_public_ip:8000/api/v1/collections -H "Authorization: Bearer ${CHROMA_AUTH}" +``` + +##### Basic + +When basic auth is enabled you can check the get the credentials from Terraform state by running: + +```bash +terraform output chroma_auth_basic +``` + +You should see something of the form: + +```bash +chroma:VuA8I}QyNrm0@QLq +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_basic | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v http://$instance_public_ip:8000/api/v1/collections -u "${CHROMA_AUTH}" +``` + +> Note: Without `-u` you should be getting 401 Unauthorized response + +#### 4.2 SSH to your instance + +To SSH to your instance: + +```bash +ssh -i ./chroma-aws debian@$instance_public_ip +``` + +### 5. Destroy your application + +```bash +terraform destroy -auto-approve +``` diff --git a/examples/deployments/google-cloud-compute/chroma.tf b/examples/deployments/google-cloud-compute/chroma.tf new file mode 100644 index 0000000000000000000000000000000000000000..f49fc59cfe37f6201bc0916844c0a488232ff97f --- /dev/null +++ b/examples/deployments/google-cloud-compute/chroma.tf @@ -0,0 +1,129 @@ +terraform { + required_providers { + google = { + source = "hashicorp/google" + version = "~> 4.80.0" + } + } +} + +resource "google_compute_instance" "chroma" { + project = var.project_id + name = "chroma-1" + machine_type = var.machine_type + zone = var.zone + + tags = local.tags + + labels = var.labels + + + boot_disk { + initialize_params { + image = var.image + size = var.chroma_instance_volume_size #size in GB + } + } + + attached_disk { + source = google_compute_disk.chroma.id + device_name = var.chroma_data_volume_device_name + mode = "READ_WRITE" + } + + network_interface { + network = "default" + + access_config { + // Ephemeral public IP + } + } + + metadata = { + ssh-keys = "${var.vm_user}:${file(var.ssh_public_key)}" + } + + metadata_startup_script = templatefile("${path.module}/startup.sh", { + chroma_release = var.chroma_release, + enable_auth = var.enable_auth, + auth_type = var.auth_type, + basic_auth_credentials = "${local.basic_auth_credentials.username}:${local.basic_auth_credentials.password}", + token_auth_credentials = random_password.chroma_token.result, + }) + + provisioner "remote-exec" { + inline = [ + "export VOLUME_ID=${var.chroma_data_volume_device_name} && sudo mkfs -t ext4 /dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}')", + "sudo mkdir /chroma-data", + "export VOLUME_ID=${var.chroma_data_volume_device_name} && sudo mount /dev/$(lsblk -o +SERIAL | grep $VOLUME_ID | awk '{print $1}') /chroma-data" + ] + + connection { + host = google_compute_instance.chroma.network_interface[0].access_config[0].nat_ip + type = "ssh" + user = var.vm_user + private_key = file(var.ssh_private_key) + } + } +} + + +resource "google_compute_disk" "chroma" { + project = var.project_id + name = "chroma-data" + type = var.disk_type + zone = var.zone + labels = var.labels + size = var.chroma_data_volume_size #size in GB + + lifecycle { + prevent_destroy = false #WARNING: You need to configure this manually as the provider does not support it yet + } +} + +#resource "google_compute_attached_disk" "vm_attached_disk" { +# disk = google_compute_disk.chroma.id +# instance = google_compute_instance.chroma.self_link +# +#} + + + +resource "google_compute_firewall" "default" { + project = var.project_id + name = "chroma-firewall" + network = "default" + + allow { + protocol = "icmp" #allow ping + } + + dynamic "allow" { + for_each = var.public_access ? [1] : [] + content { + protocol = "tcp" + ports = [var.chroma_port] + } + } + + source_ranges = var.source_ranges + + target_tags = local.tags +} + + +output "instance_public_ip" { + description = "The public IP address of the instance." + value = google_compute_instance.chroma.network_interface[0].access_config[0].nat_ip +} + +output "chroma_auth_token" { + value = random_password.chroma_token.result + sensitive = true +} + + +output "chroma_auth_basic" { + value = "${local.basic_auth_credentials.username}:${local.basic_auth_credentials.password}" + sensitive = true +} diff --git a/examples/deployments/google-cloud-compute/main.tf b/examples/deployments/google-cloud-compute/main.tf new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/examples/deployments/google-cloud-compute/startup.sh b/examples/deployments/google-cloud-compute/startup.sh new file mode 100644 index 0000000000000000000000000000000000000000..38e3d4c386f38c001217f10c9b67193168ade4b4 --- /dev/null +++ b/examples/deployments/google-cloud-compute/startup.sh @@ -0,0 +1,53 @@ +#! /bin/bash + +# Note: This is run as root + +cd ~ +export enable_auth="${enable_auth}" +export basic_auth_credentials="${basic_auth_credentials}" +export auth_type="${auth_type}" +export token_auth_credentials="${token_auth_credentials}" +apt-get update -y +apt-get install -y ca-certificates curl gnupg lsb-release +mkdir -m 0755 -p /etc/apt/keyrings +curl -fsSL https://download.docker.com/linux/debian/gpg | gpg --dearmor -o /etc/apt/keyrings/docker.gpg +echo \ + "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/debian \ + $(lsb_release -cs) stable" | tee /etc/apt/sources.list.d/docker.list > /dev/null +apt-get update -y +chmod a+r /etc/apt/keyrings/docker.gpg +apt-get update -y +apt-get install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin git +usermod -aG docker debian +git clone https://github.com/chroma-core/chroma.git && cd chroma +git fetch --tags +git checkout tags/${chroma_release} + +if [ "$${enable_auth}" = "true" ] && [ "$${auth_type}" = "basic" ] && [ ! -z "$${basic_auth_credentials}" ]; then + username=$(echo $basic_auth_credentials | cut -d: -f1) + password=$(echo $basic_auth_credentials | cut -d: -f2) + docker run --rm --entrypoint htpasswd httpd:2 -Bbn $username $password > server.htpasswd + cat < .env +CHROMA_SERVER_AUTH_CREDENTIALS_FILE="/chroma/server.htpasswd" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.providers.HtpasswdFileServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.basic.BasicAuthServerProvider" +EOF +fi + +if [ "$${enable_auth}" = "true" ] && [ "$${auth_type}" = "token" ] && [ ! -z "$${token_auth_credentials}" ]; then + cat < .env +CHROMA_SERVER_AUTH_CREDENTIALS="$${token_auth_credentials}" +CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER="chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" +CHROMA_SERVER_AUTH_PROVIDER="chromadb.auth.token.TokenAuthServerProvider" +EOF +fi + +cat < docker-compose.override.yaml +version: '3.8' +services: + server: + volumes: + - /chroma-data:/chroma/chroma +EOF + +COMPOSE_PROJECT_NAME=chroma docker compose up -d --build diff --git a/examples/deployments/google-cloud-compute/variables.tf b/examples/deployments/google-cloud-compute/variables.tf new file mode 100644 index 0000000000000000000000000000000000000000..0147ce49aa42d73afcf08890ec9354131feab122 --- /dev/null +++ b/examples/deployments/google-cloud-compute/variables.tf @@ -0,0 +1,142 @@ +variable "project_id" { + type = string + description = "The project id to deploy to" +} +variable "chroma_release" { + description = "The chroma release to deploy" + type = string + default = "0.4.9" +} + +variable "zone" { + type = string + default = "us-central1-a" +} + +variable "image" { + default = "debian-cloud/debian-11" + description = "The image to use for the instance" + type = string +} + +variable "vm_user" { + default = "debian" + description = "The user to use for connecting to the instance. This is usually the default image user" + type = string +} + +variable "machine_type" { + type = string + default = "e2-small" +} + +variable "public_access" { + description = "Enable public ingress on port 8000" + type = bool + default = true // or true depending on your needs +} + +variable "enable_auth" { + description = "Enable authentication" + type = bool + default = true // or false depending on your needs +} + +variable "auth_type" { + description = "Authentication type" + type = string + default = "token" // or token depending on your needs + validation { + condition = contains(["basic", "token"], var.auth_type) + error_message = "The auth type must be either basic or token" + } +} + +resource "random_password" "chroma_password" { + length = 16 + special = true + lower = true + upper = true +} + +resource "random_password" "chroma_token" { + length = 32 + special = false + lower = true + upper = true +} + + +locals { + basic_auth_credentials = { + username = "chroma" + password = random_password.chroma_password.result + } + token_auth_credentials = { + token = random_password.chroma_token.result + } + tags = [ + "chroma", + "release-${replace(var.chroma_release, ".", "")}", + ] +} + +variable "ssh_public_key" { + description = "SSH Public Key" + type = string + default = "./chroma-aws.pub" +} +variable "ssh_private_key" { + description = "SSH Private Key" + type = string + default = "./chroma-aws" +} + +variable "chroma_instance_volume_size" { + description = "The size of the instance volume - the root volume" + type = number + default = 30 +} + +variable "chroma_data_volume_size" { + description = "Volume Size of the attached data volume where your chroma data is stored" + type = number + default = 20 +} + +variable "chroma_data_volume_device_name" { + default = "chroma-disk-0" + description = "The device name of the chroma data volume" + type = string +} + +variable "prevent_chroma_data_volume_delete" { + description = "Prevent the chroma data volume from being deleted when the instance is terminated" + type = bool + default = false +} + +variable "disk_type" { + default = "pd-ssd" + description = "The type of disk to use for the instance. Can be either pd-standard or pd-ssd" +} + +variable "labels" { + default = { + environment = "dev" + } + description = "Labels to apply to all resources in this example" + type = map(string) +} + +variable "chroma_port" { + default = "8000" + description = "The port that chroma listens on" + type = string +} + +variable "source_ranges" { + default = ["0.0.0.0/0"] + type = list(string) + description = "List of CIDR ranges to allow through the firewall" +} diff --git a/examples/deployments/render-terraform/README.md b/examples/deployments/render-terraform/README.md new file mode 100644 index 0000000000000000000000000000000000000000..eab333cbeea4ed7a9311943fff2e89d43164bff4 --- /dev/null +++ b/examples/deployments/render-terraform/README.md @@ -0,0 +1,118 @@ +# Render.com Deployment + +This is an example deployment to Render.com using [terraform](https://www.terraform.io/) + +## Requirements + +- [Terraform CLI v1.3.4+](https://developer.hashicorp.com/terraform/tutorials/gcp-get-started/install-cli) +- [Terraform Render provider](https://registry.terraform.io/providers/jackall3n/render/latest/docs) + +## Deployment with terraform + +### 1. Init your terraform state + +```bash +terraform init +``` + +### 3. Deploy your application + +```bash +# Your Render.com API token. IMPORTANT: The API does not work with Free plan. +export TF_VAR_render_api_token= +# Your Render.com user email +export TF_VAR_render_user_email= +#set the chroma release to deploy +export TF_VAR_chroma_release="0.4.13" +# the region to deploy to. At the time of writing only oregon and frankfurt are available +export TF_VAR_region="oregon" +#enable basic auth for the chroma instance +export TF_VAR_enable_auth="true" +#The auth type to use for the chroma instance (token or basic) +export TF_VAR_auth_type="token" +terraform apply -auto-approve +``` + +### 4. Check your public IP and that Chroma is running + +> Note: It might take couple minutes for the instance to boot up + +Get the public IP of your instance (it should also be printed out after successful `terraform apply`): + +```bash +terraform output instance_url +``` + +Check that chroma is running: + +```bash +export instance_public_ip=$(terraform output instance_url | sed 's/"//g') +curl -v $instance_public_ip/api/v1/heartbeat +``` + +#### 4.1 Checking Auth + +##### Token + +When token auth is enabled (this is the default option) you can check the get the credentials from Terraform state by +running: + +```bash +terraform output chroma_auth_token +``` + +You should see something of the form: + +```bash +PVcQ4qUUnmahXwUgAf3UuYZoMlos6MnF +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_token | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v $instance_public_ip/api/v1/collections -H "Authorization: Bearer ${CHROMA_AUTH}" +``` + +##### Basic + +When basic auth is enabled you can check the get the credentials from Terraform state by running: + +```bash +terraform output chroma_auth_basic +``` + +You should see something of the form: + +```bash +chroma:VuA8I}QyNrm0@QLq +``` + +You can then export these credentials: + +```bash +export CHROMA_AUTH=$(terraform output chroma_auth_basic | sed 's/"//g') +``` + +Using the credentials: + +```bash +curl -v https://$instance_public_ip:8000/api/v1/collections -u "${CHROMA_AUTH}" +``` + +> Note: Without `-u` you should be getting 401 Unauthorized response + +#### 4.2 SSH to your instance + +To connect to your instance via SSH you need to go to Render.com service dashboard. + +### 5. Destroy your application + +```bash +terraform destroy +``` diff --git a/examples/deployments/render-terraform/chroma.tf b/examples/deployments/render-terraform/chroma.tf new file mode 100644 index 0000000000000000000000000000000000000000..441fa356a449582e31f380ff7b661c167f7ae5db --- /dev/null +++ b/examples/deployments/render-terraform/chroma.tf @@ -0,0 +1,88 @@ +terraform { + required_providers { + render = { + source = "jackall3n/render" + version = "~> 1.3.0" + } + } +} + +variable "render_api_token" { + sensitive = true +} + +variable "render_user_email" { + sensitive = true +} + +provider "render" { + api_key = var.render_api_token +} + +data "render_owner" "render_owner" { + email = var.render_user_email +} + +resource "render_service" "chroma" { + name = "chroma" + owner = data.render_owner.render_owner.id + type = "web_service" + auto_deploy = true + + env_vars = concat([{ + key = "IS_PERSISTENT" + value = "1" + }, + { + key = "PERSIST_DIRECTORY" + value = var.chroma_data_volume_mount_path + }, + ], + var.enable_auth ? [{ + key = "CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER" + value = "chromadb.auth.token.TokenConfigServerAuthCredentialsProvider" + }, + { + key = "CHROMA_SERVER_AUTH_CREDENTIALS" + value = "${local.token_auth_credentials.token}" + }, + { + key = "CHROMA_SERVER_AUTH_PROVIDER" + value = var.auth_type + }] : [] + ) + + image = { + owner_id = data.render_owner.render_owner.id + image_path = "${var.chroma_image_reg_url}:${var.chroma_release}" + } + + web_service_details = { + env = "image" + plan = var.render_plan + region = var.region + health_check_path = "/api/v1/heartbeat" + disk = { + name = var.chroma_data_volume_device_name + mount_path = var.chroma_data_volume_mount_path + size_gb = var.chroma_data_volume_size + } + docker = { + command = "uvicorn chromadb.app:app --reload --workers 1 --host 0.0.0.0 --port 80 --log-config chromadb/log_config.yml --timeout-keep-alive 30" + path = "./Dockerfile" + } + } +} + +output "service_id" { + value = render_service.chroma.id +} + +output "instance_url" { + value = render_service.chroma.web_service_details.url +} + +output "chroma_auth_token" { + value = random_password.chroma_token.result + sensitive = true +} diff --git a/examples/deployments/render-terraform/sqlite_version.patch b/examples/deployments/render-terraform/sqlite_version.patch new file mode 100644 index 0000000000000000000000000000000000000000..aa19837a916696ceb74dc7da1398f3192b1b5c35 --- /dev/null +++ b/examples/deployments/render-terraform/sqlite_version.patch @@ -0,0 +1,29 @@ +diff --git a/chromadb/__init__.py b/chromadb/__init__.py +index 0ff5244a..450aaf0d 100644 +--- a/chromadb/__init__.py ++++ b/chromadb/__init__.py +@@ -55,21 +55,9 @@ except ImportError: + IN_COLAB = False + + if sqlite3.sqlite_version_info < (3, 35, 0): +- if IN_COLAB: +- # In Colab, hotswap to pysqlite-binary if it's too old +- import subprocess +- import sys +- +- subprocess.check_call( +- [sys.executable, "-m", "pip", "install", "pysqlite3-binary"] +- ) +- __import__("pysqlite3") +- sys.modules["sqlite3"] = sys.modules.pop("pysqlite3") +- else: +- raise RuntimeError( +- "\033[91mYour system has an unsupported version of sqlite3. Chroma requires sqlite3 >= 3.35.0.\033[0m\n" +- "\033[94mPlease visit https://docs.trychroma.com/troubleshooting#sqlite to learn how to upgrade.\033[0m" +- ) ++ __import__('pysqlite3') ++ import sys ++ sys.modules['sqlite3'] = sys.modules.pop('pysqlite3') + + + def configure(**kwargs) -> None: # type: ignore diff --git a/examples/deployments/render-terraform/variables.tf b/examples/deployments/render-terraform/variables.tf new file mode 100644 index 0000000000000000000000000000000000000000..2acde15274abf345b917a05cb3ed89c2da9d97d6 --- /dev/null +++ b/examples/deployments/render-terraform/variables.tf @@ -0,0 +1,70 @@ +variable "chroma_image_reg_url" { + description = "The URL of the chroma-core image registry (e.g. docker.io/chromadb/chroma). The URL must also include the image itself without the tag." + type = string + default = "docker.io/chromadb/chroma" +} + +variable "chroma_release" { + description = "The chroma release to deploy" + type = string + default = "0.4.13" +} + +variable "region" { + type = string + default = "oregon" +} + +variable "render_plan" { + default = "starter" + description = "The Render plan to use. This determines the size of the machine. NOTE: Terraform Render provider uses Render's API which requires at least starter plan." + type = string +} + +variable "enable_auth" { + description = "Enable authentication" + type = bool + default = true // or false depending on your needs +} + +variable "auth_type" { + description = "Authentication type" + type = string + default = "token" // or token depending on your needs + validation { + condition = contains([ "token"], var.auth_type) + error_message = "Only token is supported as auth type" + } +} + +resource "random_password" "chroma_token" { + length = 32 + special = false + lower = true + upper = true +} + + +locals { + token_auth_credentials = { + token = random_password.chroma_token.result + } +} + +variable "chroma_data_volume_size" { + description = "The size of the attached data volume in GB." + type = number + default = 20 +} + +variable "chroma_data_volume_device_name" { + default = "chroma-disk-0" + description = "The device name of the chroma data volume" + type = string +} + +variable "chroma_data_volume_mount_path" { + default = "/chroma-data" + description = "The mount path of the chroma data volume" + type = string +} diff --git a/examples/gemini/README.md b/examples/gemini/README.md new file mode 100644 index 0000000000000000000000000000000000000000..9985fc742b4c988e19ae32aa8ce70ee5811f932d --- /dev/null +++ b/examples/gemini/README.md @@ -0,0 +1,53 @@ +# Chat with your documents + +This folder contains a (very) minimal, self-contained example of how to make an application to chat with your documents, using Chroma and Google Gemini's API. +It uses the 2022 and 2023 U.S state of the union addresses as example documents. + +## How it works + +The basic flow is as follows: + +0. The text documents in the `documents` folder are loaded line by line, then embedded and stored in a Chroma collection. + +1. When the user submits a question, it gets embedded using the same model as the documents, and the lines most relevant to the query are retrieved by Chroma. +2. The user-submitted question is passed to Google Gemini's API, along with the extra context retrieved by Chroma. The Google Gemini API generates a response. +3. The response is displayed to the user, along with the lines used as extra context. + +## Running the example + +You will need an Google API key to run this demo. + +Install dependencies and run the example: + +```bash +# Install dependencies +pip install -r requirements.txt + +# Load the example documents into Chroma +python load_data.py + +# Run the chatbot +python main.py +``` + +Example output: + +``` +Query: What was said about the pandemic? + +Thinking... + +Based on the given context, several points were made about the pandemic. First, it is described as punishing, indicating the severity and impact it had on various aspects of life. It is mentioned that schools were closed and everything was being shut down in response to the COVID crisis, suggesting the significant measures taken to combat the virus. + +The context then shifts to discussing the progress made in the fight against the pandemic itself. While no specific details are provided, it is implied that there has been progress, though the extent of it is unclear. + +Additionally, it is stated that children were already facing struggles before the pandemic, such as bullying, violence, trauma, and the negative effects of social media. This suggests that these issues were likely exacerbated by the pandemic. + +The context then mentions a spike in violent crime in 2020, which is attributed to the first year of the pandemic. This implies that there was an increase in violent crime during that time period, but the underlying causes or specific details are not provided. + +Lastly, it is mentioned that the pandemic also disrupted global supply chains. Again, no specific details are given, but this suggests that the pandemic had negative effects on the movement and availability of goods and resources at a global level. + +In conclusion, based on the provided context, it is stated that the pandemic has been punishing and has resulted in the closure of schools and the shutdown of various activities. Progress is mentioned in fighting against the pandemic, though the specifics are not given. The pandemic is also said to have worsened pre-existing issues such as bullying and violence among children, and disrupted global supply chains. +``` + +You can replace the example text documents in the `documents` folder with your own documents, and the chatbot will use those instead. diff --git a/examples/gemini/documents/state_of_the_union_2022.txt b/examples/gemini/documents/state_of_the_union_2022.txt new file mode 100644 index 0000000000000000000000000000000000000000..7cb2a02c313d8d11cea68eda148946abed32eaa9 --- /dev/null +++ b/examples/gemini/documents/state_of_the_union_2022.txt @@ -0,0 +1,723 @@ +Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans. + +Last year COVID-19 kept us apart. This year we are finally together again. + +Tonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. + +With a duty to one another to the American people to the Constitution. + +And with an unwavering resolve that freedom will always triumph over tyranny. + +Six days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated. + +He thought he could roll into Ukraine and the world would roll over. Instead he met a wall of strength he never imagined. + +He met the Ukrainian people. + +From President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world. + +Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. + +In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. + +Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world. + +Please rise if you are able and show that, Yes, we the United States of America stand with the Ukrainian people. + +Throughout our history we’ve learned this lesson when dictators do not pay a price for their aggression they cause more chaos. + +They keep moving. + +And the costs and the threats to America and the world keep rising. + +That’s why the NATO Alliance was created to secure peace and stability in Europe after World War 2. + +The United States is a member along with 29 other nations. + +It matters. American diplomacy matters. American resolve matters. + +Putin’s latest attack on Ukraine was premeditated and unprovoked. + +He rejected repeated efforts at diplomacy. + +He thought the West and NATO wouldn’t respond. And he thought he could divide us at home. Putin was wrong. We were ready. Here is what we did. + +We prepared extensively and carefully. + +We spent months building a coalition of other freedom-loving nations from Europe and the Americas to Asia and Africa to confront Putin. + +I spent countless hours unifying our European allies. We shared with the world in advance what we knew Putin was planning and precisely how he would try to falsely justify his aggression. + +We countered Russia’s lies with truth. + +And now that he has acted the free world is holding him accountable. + +Along with twenty-seven members of the European Union including France, Germany, Italy, as well as countries like the United Kingdom, Canada, Japan, Korea, Australia, New Zealand, and many others, even Switzerland. + +We are inflicting pain on Russia and supporting the people of Ukraine. Putin is now isolated from the world more than ever. + +Together with our allies –we are right now enforcing powerful economic sanctions. + +We are cutting off Russia’s largest banks from the international financial system. + +Preventing Russia’s central bank from defending the Russian Ruble making Putin’s $630 Billion “war fund” worthless. + +We are choking off Russia’s access to technology that will sap its economic strength and weaken its military for years to come. + +Tonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more. + +The U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs. + +We are joining with our European allies to find and seize your yachts your luxury apartments your private jets. We are coming for your ill-begotten gains. + +And tonight I am announcing that we will join our allies in closing off American air space to all Russian flights – further isolating Russia – and adding an additional squeeze –on their economy. The Ruble has lost 30% of its value. + +The Russian stock market has lost 40% of its value and trading remains suspended. Russia’s economy is reeling and Putin alone is to blame. + +Together with our allies we are providing support to the Ukrainians in their fight for freedom. Military assistance. Economic assistance. Humanitarian assistance. + +We are giving more than $1 Billion in direct assistance to Ukraine. + +And we will continue to aid the Ukrainian people as they defend their country and to help ease their suffering. + +Let me be clear, our forces are not engaged and will not engage in conflict with Russian forces in Ukraine. + +Our forces are not going to Europe to fight in Ukraine, but to defend our NATO Allies – in the event that Putin decides to keep moving west. + +For that purpose we’ve mobilized American ground forces, air squadrons, and ship deployments to protect NATO countries including Poland, Romania, Latvia, Lithuania, and Estonia. + +As I have made crystal clear the United States and our Allies will defend every inch of territory of NATO countries with the full force of our collective power. + +And we remain clear-eyed. The Ukrainians are fighting back with pure courage. But the next few days weeks, months, will be hard on them. + +Putin has unleashed violence and chaos. But while he may make gains on the battlefield – he will pay a continuing high price over the long run. + +And a proud Ukrainian people, who have known 30 years of independence, have repeatedly shown that they will not tolerate anyone who tries to take their country backwards. + +To all Americans, I will be honest with you, as I’ve always promised. A Russian dictator, invading a foreign country, has costs around the world. + +And I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. + +Tonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world. + +America will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies. + +These steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming. + +But I want you to know that we are going to be okay. + +When the history of this era is written Putin’s war on Ukraine will have left Russia weaker and the rest of the world stronger. + +While it shouldn’t have taken something so terrible for people around the world to see what’s at stake now everyone sees it clearly. + +We see the unity among leaders of nations and a more unified Europe a more unified West. And we see unity among the people who are gathering in cities in large crowds around the world even in Russia to demonstrate their support for Ukraine. + +In the battle between democracy and autocracy, democracies are rising to the moment, and the world is clearly choosing the side of peace and security. + +This is a real test. It’s going to take time. So let us continue to draw inspiration from the iron will of the Ukrainian people. + +To our fellow Ukrainian Americans who forge a deep bond that connects our two nations we stand with you. + +Putin may circle Kyiv with tanks, but he will never gain the hearts and souls of the Ukrainian people. + +He will never extinguish their love of freedom. He will never weaken the resolve of the free world. + +We meet tonight in an America that has lived through two of the hardest years this nation has ever faced. + +The pandemic has been punishing. + +And so many families are living paycheck to paycheck, struggling to keep up with the rising cost of food, gas, housing, and so much more. + +I understand. + +I remember when my Dad had to leave our home in Scranton, Pennsylvania to find work. I grew up in a family where if the price of food went up, you felt it. + +That’s why one of the first things I did as President was fight to pass the American Rescue Plan. + +Because people were hurting. We needed to act, and we did. + +Few pieces of legislation have done more in a critical moment in our history to lift us out of crisis. + +It fueled our efforts to vaccinate the nation and combat COVID-19. It delivered immediate economic relief for tens of millions of Americans. + +Helped put food on their table, keep a roof over their heads, and cut the cost of health insurance. + +And as my Dad used to say, it gave people a little breathing room. + +And unlike the $2 Trillion tax cut passed in the previous administration that benefitted the top 1% of Americans, the American Rescue Plan helped working people—and left no one behind. + +And it worked. It created jobs. Lots of jobs. + +In fact—our economy created over 6.5 Million new jobs just last year, more jobs created in one year +than ever before in the history of America. + +Our economy grew at a rate of 5.7% last year, the strongest growth in nearly 40 years, the first step in bringing fundamental change to an economy that hasn’t worked for the working people of this nation for too long. + +For the past 40 years we were told that if we gave tax breaks to those at the very top, the benefits would trickle down to everyone else. + +But that trickle-down theory led to weaker economic growth, lower wages, bigger deficits, and the widest gap between those at the top and everyone else in nearly a century. + +Vice President Harris and I ran for office with a new economic vision for America. + +Invest in America. Educate Americans. Grow the workforce. Build the economy from the bottom up +and the middle out, not from the top down. + +Because we know that when the middle class grows, the poor have a ladder up and the wealthy do very well. + +America used to have the best roads, bridges, and airports on Earth. + +Now our infrastructure is ranked 13th in the world. + +We won’t be able to compete for the jobs of the 21st Century if we don’t fix that. + +That’s why it was so important to pass the Bipartisan Infrastructure Law—the most sweeping investment to rebuild America in history. + +This was a bipartisan effort, and I want to thank the members of both parties who worked to make it happen. + +We’re done talking about infrastructure weeks. + +We’re going to have an infrastructure decade. + +It is going to transform America and put us on a path to win the economic competition of the 21st Century that we face with the rest of the world—particularly with China. + +As I’ve told Xi Jinping, it is never a good bet to bet against the American people. + +We’ll create good jobs for millions of Americans, modernizing roads, airports, ports, and waterways all across America. + +And we’ll do it all to withstand the devastating effects of the climate crisis and promote environmental justice. + +We’ll build a national network of 500,000 electric vehicle charging stations, begin to replace poisonous lead pipes—so every child—and every American—has clean water to drink at home and at school, provide affordable high-speed internet for every American—urban, suburban, rural, and tribal communities. + +4,000 projects have already been announced. + +And tonight, I’m announcing that this year we will start fixing over 65,000 miles of highway and 1,500 bridges in disrepair. + +When we use taxpayer dollars to rebuild America – we are going to Buy American: buy American products to support American jobs. + +The federal government spends about $600 Billion a year to keep the country safe and secure. + +There’s been a law on the books for almost a century +to make sure taxpayers’ dollars support American jobs and businesses. + +Every Administration says they’ll do it, but we are actually doing it. + +We will buy American to make sure everything from the deck of an aircraft carrier to the steel on highway guardrails are made in America. + +But to compete for the best jobs of the future, we also need to level the playing field with China and other competitors. + +That’s why it is so important to pass the Bipartisan Innovation Act sitting in Congress that will make record investments in emerging technologies and American manufacturing. + +Let me give you one example of why it’s so important to pass it. + +If you travel 20 miles east of Columbus, Ohio, you’ll find 1,000 empty acres of land. + +It won’t look like much, but if you stop and look closely, you’ll see a “Field of dreams,” the ground on which America’s future will be built. + +This is where Intel, the American company that helped build Silicon Valley, is going to build its $20 billion semiconductor “mega site”. + +Up to eight state-of-the-art factories in one place. 10,000 new good-paying jobs. + +Some of the most sophisticated manufacturing in the world to make computer chips the size of a fingertip that power the world and our everyday lives. + +Smartphones. The Internet. Technology we have yet to invent. + +But that’s just the beginning. + +Intel’s CEO, Pat Gelsinger, who is here tonight, told me they are ready to increase their investment from +$20 billion to $100 billion. + +That would be one of the biggest investments in manufacturing in American history. + +And all they’re waiting for is for you to pass this bill. + +So let’s not wait any longer. Send it to my desk. I’ll sign it. + +And we will really take off. + +And Intel is not alone. + +There’s something happening in America. + +Just look around and you’ll see an amazing story. + +The rebirth of the pride that comes from stamping products “Made In America.” The revitalization of American manufacturing. + +Companies are choosing to build new factories here, when just a few years ago, they would have built them overseas. + +That’s what is happening. Ford is investing $11 billion to build electric vehicles, creating 11,000 jobs across the country. + +GM is making the largest investment in its history—$7 billion to build electric vehicles, creating 4,000 jobs in Michigan. + +All told, we created 369,000 new manufacturing jobs in America just last year. + +Powered by people I’ve met like JoJo Burgess, from generations of union steelworkers from Pittsburgh, who’s here with us tonight. + +As Ohio Senator Sherrod Brown says, “It’s time to bury the label “Rust Belt.” + +It’s time. + +But with all the bright spots in our economy, record job growth and higher wages, too many families are struggling to keep up with the bills. + +Inflation is robbing them of the gains they might otherwise feel. + +I get it. That’s why my top priority is getting prices under control. + +Look, our economy roared back faster than most predicted, but the pandemic meant that businesses had a hard time hiring enough workers to keep up production in their factories. + +The pandemic also disrupted global supply chains. + +When factories close, it takes longer to make goods and get them from the warehouse to the store, and prices go up. + +Look at cars. + +Last year, there weren’t enough semiconductors to make all the cars that people wanted to buy. + +And guess what, prices of automobiles went up. + +So—we have a choice. + +One way to fight inflation is to drive down wages and make Americans poorer. + +I have a better plan to fight inflation. + +Lower your costs, not your wages. + +Make more cars and semiconductors in America. + +More infrastructure and innovation in America. + +More goods moving faster and cheaper in America. + +More jobs where you can earn a good living in America. + +And instead of relying on foreign supply chains, let’s make it in America. + +Economists call it “increasing the productive capacity of our economy.” + +I call it building a better America. + +My plan to fight inflation will lower your costs and lower the deficit. + +17 Nobel laureates in economics say my plan will ease long-term inflationary pressures. Top business leaders and most Americans support my plan. And here’s the plan: + +First – cut the cost of prescription drugs. Just look at insulin. One in ten Americans has diabetes. In Virginia, I met a 13-year-old boy named Joshua Davis. + +He and his Dad both have Type 1 diabetes, which means they need insulin every day. Insulin costs about $10 a vial to make. + +But drug companies charge families like Joshua and his Dad up to 30 times more. I spoke with Joshua’s mom. + +Imagine what it’s like to look at your child who needs insulin and have no idea how you’re going to pay for it. + +What it does to your dignity, your ability to look your child in the eye, to be the parent you expect to be. + +Joshua is here with us tonight. Yesterday was his birthday. Happy birthday, buddy. + +For Joshua, and for the 200,000 other young people with Type 1 diabetes, let’s cap the cost of insulin at $35 a month so everyone can afford it. + +Drug companies will still do very well. And while we’re at it let Medicare negotiate lower prices for prescription drugs, like the VA already does. + +Look, the American Rescue Plan is helping millions of families on Affordable Care Act plans save $2,400 a year on their health care premiums. Let’s close the coverage gap and make those savings permanent. + +Second – cut energy costs for families an average of $500 a year by combatting climate change. + +Let’s provide investments and tax credits to weatherize your homes and businesses to be energy efficient and you get a tax credit; double America’s clean energy production in solar, wind, and so much more; lower the price of electric vehicles, saving you another $80 a month because you’ll never have to pay at the gas pump again. + +Third – cut the cost of child care. Many families pay up to $14,000 a year for child care per child. + +Middle-class and working families shouldn’t have to pay more than 7% of their income for care of young children. + +My plan will cut the cost in half for most families and help parents, including millions of women, who left the workforce during the pandemic because they couldn’t afford child care, to be able to get back to work. + +My plan doesn’t stop there. It also includes home and long-term care. More affordable housing. And Pre-K for every 3- and 4-year-old. + +All of these will lower costs. + +And under my plan, nobody earning less than $400,000 a year will pay an additional penny in new taxes. Nobody. + +The one thing all Americans agree on is that the tax system is not fair. We have to fix it. + +I’m not looking to punish anyone. But let’s make sure corporations and the wealthiest Americans start paying their fair share. + +Just last year, 55 Fortune 500 corporations earned $40 billion in profits and paid zero dollars in federal income tax. + +That’s simply not fair. That’s why I’ve proposed a 15% minimum tax rate for corporations. + +We got more than 130 countries to agree on a global minimum tax rate so companies can’t get out of paying their taxes at home by shipping jobs and factories overseas. + +That’s why I’ve proposed closing loopholes so the very wealthy don’t pay a lower tax rate than a teacher or a firefighter. + +So that’s my plan. It will grow the economy and lower costs for families. + +So what are we waiting for? Let’s get this done. And while you’re at it, confirm my nominees to the Federal Reserve, which plays a critical role in fighting inflation. + +My plan will not only lower costs to give families a fair shot, it will lower the deficit. + +The previous Administration not only ballooned the deficit with tax cuts for the very wealthy and corporations, it undermined the watchdogs whose job was to keep pandemic relief funds from being wasted. + +But in my administration, the watchdogs have been welcomed back. + +We’re going after the criminals who stole billions in relief money meant for small businesses and millions of Americans. + +And tonight, I’m announcing that the Justice Department will name a chief prosecutor for pandemic fraud. + +By the end of this year, the deficit will be down to less than half what it was before I took office. + +The only president ever to cut the deficit by more than one trillion dollars in a single year. + +Lowering your costs also means demanding more competition. + +I’m a capitalist, but capitalism without competition isn’t capitalism. + +It’s exploitation—and it drives up prices. + +When corporations don’t have to compete, their profits go up, your prices go up, and small businesses and family farmers and ranchers go under. + +We see it happening with ocean carriers moving goods in and out of America. + +During the pandemic, these foreign-owned companies raised prices by as much as 1,000% and made record profits. + +Tonight, I’m announcing a crackdown on these companies overcharging American businesses and consumers. + +And as Wall Street firms take over more nursing homes, quality in those homes has gone down and costs have gone up. + +That ends on my watch. + +Medicare is going to set higher standards for nursing homes and make sure your loved ones get the care they deserve and expect. + +We’ll also cut costs and keep the economy going strong by giving workers a fair shot, provide more training and apprenticeships, hire them based on their skills not degrees. + +Let’s pass the Paycheck Fairness Act and paid leave. + +Raise the minimum wage to $15 an hour and extend the Child Tax Credit, so no one has to raise a family in poverty. + +Let’s increase Pell Grants and increase our historic support of HBCUs, and invest in what Jill—our First Lady who teaches full-time—calls America’s best-kept secret: community colleges. + +And let’s pass the PRO Act when a majority of workers want to form a union—they shouldn’t be stopped. + +When we invest in our workers, when we build the economy from the bottom up and the middle out together, we can do something we haven’t done in a long time: build a better America. + +For more than two years, COVID-19 has impacted every decision in our lives and the life of the nation. + +And I know you’re tired, frustrated, and exhausted. + +But I also know this. + +Because of the progress we’ve made, because of your resilience and the tools we have, tonight I can say +we are moving forward safely, back to more normal routines. + +We’ve reached a new moment in the fight against COVID-19, with severe cases down to a level not seen since last July. + +Just a few days ago, the Centers for Disease Control and Prevention—the CDC—issued new mask guidelines. + +Under these new guidelines, most Americans in most of the country can now be mask free. + +And based on the projections, more of the country will reach that point across the next couple of weeks. + +Thanks to the progress we have made this past year, COVID-19 need no longer control our lives. + +I know some are talking about “living with COVID-19”. Tonight – I say that we will never just accept living with COVID-19. + +We will continue to combat the virus as we do other diseases. And because this is a virus that mutates and spreads, we will stay on guard. + +Here are four common sense steps as we move forward safely. + +First, stay protected with vaccines and treatments. We know how incredibly effective vaccines are. If you’re vaccinated and boosted you have the highest degree of protection. + +We will never give up on vaccinating more Americans. Now, I know parents with kids under 5 are eager to see a vaccine authorized for their children. + +The scientists are working hard to get that done and we’ll be ready with plenty of vaccines when they do. + +We’re also ready with anti-viral treatments. If you get COVID-19, the Pfizer pill reduces your chances of ending up in the hospital by 90%. + +We’ve ordered more of these pills than anyone in the world. And Pfizer is working overtime to get us 1 Million pills this month and more than double that next month. + +And we’re launching the “Test to Treat” initiative so people can get tested at a pharmacy, and if they’re positive, receive antiviral pills on the spot at no cost. + +If you’re immunocompromised or have some other vulnerability, we have treatments and free high-quality masks. + +We’re leaving no one behind or ignoring anyone’s needs as we move forward. + +And on testing, we have made hundreds of millions of tests available for you to order for free. + +Even if you already ordered free tests tonight, I am announcing that you can order more from covidtests.gov starting next week. + +Second – we must prepare for new variants. Over the past year, we’ve gotten much better at detecting new variants. + +If necessary, we’ll be able to deploy new vaccines within 100 days instead of many more months or years. + +And, if Congress provides the funds we need, we’ll have new stockpiles of tests, masks, and pills ready if needed. + +I cannot promise a new variant won’t come. But I can promise you we’ll do everything within our power to be ready if it does. + +Third – we can end the shutdown of schools and businesses. We have the tools we need. + +It’s time for Americans to get back to work and fill our great downtowns again. People working from home can feel safe to begin to return to the office. + +We’re doing that here in the federal government. The vast majority of federal workers will once again work in person. + +Our schools are open. Let’s keep it that way. Our kids need to be in school. + +And with 75% of adult Americans fully vaccinated and hospitalizations down by 77%, most Americans can remove their masks, return to work, stay in the classroom, and move forward safely. + +We achieved this because we provided free vaccines, treatments, tests, and masks. + +Of course, continuing this costs money. + +I will soon send Congress a request. + +The vast majority of Americans have used these tools and may want to again, so I expect Congress to pass it quickly. + +Fourth, we will continue vaccinating the world. + +We’ve sent 475 Million vaccine doses to 112 countries, more than any other nation. + +And we won’t stop. + +We have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life. + +Let’s use this moment to reset. Let’s stop looking at COVID-19 as a partisan dividing line and see it for what it is: A God-awful disease. + +Let’s stop seeing each other as enemies, and start seeing each other for who we really are: Fellow Americans. + +We can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together. + +I recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. + +They were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. + +Officer Mora was 27 years old. + +Officer Rivera was 22. + +Both Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers. + +I spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves. + +I’ve worked on these issues a long time. + +I know what works: Investing in crime preventionand community police officers who’ll walk the beat, who’ll know the neighborhood, and who can restore trust and safety. + +So let’s not abandon our streets. Or choose between safety and equal justice. + +Let’s come together to protect our communities, restore trust, and hold law enforcement accountable. + +That’s why the Justice Department required body cameras, banned chokeholds, and restricted no-knock warrants for its officers. + +That’s why the American Rescue Plan provided $350 Billion that cities, states, and counties can use to hire more police and invest in proven strategies like community violence interruption—trusted messengers breaking the cycle of violence and trauma and giving young people hope. + +We should all agree: The answer is not to Defund the police. The answer is to FUND the police with the resources and training they need to protect our communities. + +I ask Democrats and Republicans alike: Pass my budget and keep our neighborhoods safe. + +And I will keep doing everything in my power to crack down on gun trafficking and ghost guns you can buy online and make at home—they have no serial numbers and can’t be traced. + +And I ask Congress to pass proven measures to reduce gun violence. Pass universal background checks. Why should anyone on a terrorist list be able to purchase a weapon? + +Ban assault weapons and high-capacity magazines. + +Repeal the liability shield that makes gun manufacturers the only industry in America that can’t be sued. + +These laws don’t infringe on the Second Amendment. They save lives. + +The most fundamental right in America is the right to vote – and to have it counted. And it’s under assault. + +In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections. + +We cannot let this happen. + +Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. + +Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. + +One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. + +And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence. + +A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. + +And if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. + +We can do both. At our border, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. + +We’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers. + +We’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. + +We’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders. + +We can do all this while keeping lit the torch of liberty that has led generations of immigrants to this land—my forefathers and so many of yours. + +Provide a pathway to citizenship for Dreamers, those on temporary status, farm workers, and essential workers. + +Revise our laws so businesses have the workers they need and families don’t wait decades to reunite. + +It’s not only the right thing to do—it’s the economically smart thing to do. + +That’s why immigration reform is supported by everyone from labor unions to religious leaders to the U.S. Chamber of Commerce. + +Let’s get it done once and for all. + +Advancing liberty and justice also requires protecting the rights of women. + +The constitutional right affirmed in Roe v. Wade—standing precedent for half a century—is under attack as never before. + +If we want to go forward—not backward—we must protect access to health care. Preserve a woman’s right to choose. And let’s continue to advance maternal health care in America. + +And for our LGBTQ+ Americans, let’s finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong. + +As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. + +While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice. + +And soon, we’ll strengthen the Violence Against Women Act that I first wrote three decades ago. It is important for us to show the nation that we can come together and do big things. + +So tonight I’m offering a Unity Agenda for the Nation. Four big things we can do together. + +First, beat the opioid epidemic. + +There is so much we can do. Increase funding for prevention, treatment, harm reduction, and recovery. + +Get rid of outdated rules that stop doctors from prescribing treatments. And stop the flow of illicit drugs by working with state and local law enforcement to go after traffickers. + +If you’re suffering from addiction, know you are not alone. I believe in recovery, and I celebrate the 23 million Americans in recovery. + +Second, let’s take on mental health. Especially among our children, whose lives and education have been turned upside down. + +The American Rescue Plan gave schools money to hire teachers and help students make up for lost learning. + +I urge every parent to make sure your school does just that. And we can all play a part—sign up to be a tutor or a mentor. + +Children were also struggling before the pandemic. Bullying, violence, trauma, and the harms of social media. + +As Frances Haugen, who is here with us tonight, has shown, we must hold social media platforms accountable for the national experiment they’re conducting on our children for profit. + +It’s time to strengthen privacy protections, ban targeted advertising to children, demand tech companies stop collecting personal data on our children. + +And let’s get all Americans the mental health services they need. More people they can turn to for help, and full parity between physical and mental health care. + +Third, support our veterans. + +Veterans are the best of us. + +I’ve always believed that we have a sacred obligation to equip all those we send to war and care for them and their families when they come home. + +My administration is providing assistance with job training and housing, and now helping lower-income veterans get VA care debt-free. + +Our troops in Iraq and Afghanistan faced many dangers. + +One was stationed at bases and breathing in toxic smoke from “burn pits” that incinerated wastes of war—medical and hazard material, jet fuel, and more. + +When they came home, many of the world’s fittest and best trained warriors were never the same. + +Headaches. Numbness. Dizziness. + +A cancer that would put them in a flag-draped coffin. + +I know. + +One of those soldiers was my son Major Beau Biden. + +We don’t know for sure if a burn pit was the cause of his brain cancer, or the diseases of so many of our troops. + +But I’m committed to finding out everything we can. + +Committed to military families like Danielle Robinson from Ohio. + +The widow of Sergeant First Class Heath Robinson. + +He was born a soldier. Army National Guard. Combat medic in Kosovo and Iraq. + +Stationed near Baghdad, just yards from burn pits the size of football fields. + +Heath’s widow Danielle is here with us tonight. They loved going to Ohio State football games. He loved building Legos with their daughter. + +But cancer from prolonged exposure to burn pits ravaged Heath’s lungs and body. + +Danielle says Heath was a fighter to the very end. + +He didn’t know how to stop fighting, and neither did she. + +Through her pain she found purpose to demand we do better. + +Tonight, Danielle—we are. + +The VA is pioneering new ways of linking toxic exposures to diseases, already helping more veterans get benefits. + +And tonight, I’m announcing we’re expanding eligibility to veterans suffering from nine respiratory cancers. + +I’m also calling on Congress: pass a law to make sure veterans devastated by toxic exposures in Iraq and Afghanistan finally get the benefits and comprehensive health care they deserve. + +And fourth, let’s end cancer as we know it. + +This is personal to me and Jill, to Kamala, and to so many of you. + +Cancer is the #2 cause of death in America–second only to heart disease. + +Last month, I announced our plan to supercharge +the Cancer Moonshot that President Obama asked me to lead six years ago. + +Our goal is to cut the cancer death rate by at least 50% over the next 25 years, turn more cancers from death sentences into treatable diseases. + +More support for patients and families. + +To get there, I call on Congress to fund ARPA-H, the Advanced Research Projects Agency for Health. + +It’s based on DARPA—the Defense Department project that led to the Internet, GPS, and so much more. + +ARPA-H will have a singular purpose—to drive breakthroughs in cancer, Alzheimer’s, diabetes, and more. + +A unity agenda for the nation. + +We can do this. + +My fellow Americans—tonight , we have gathered in a sacred space—the citadel of our democracy. + +In this Capitol, generation after generation, Americans have debated great questions amid great strife, and have done great things. + +We have fought for freedom, expanded liberty, defeated totalitarianism and terror. + +And built the strongest, freest, and most prosperous nation the world has ever known. + +Now is the hour. + +Our moment of responsibility. + +Our test of resolve and conscience, of history itself. + +It is in this moment that our character is formed. Our purpose is found. Our future is forged. + +Well I know this nation. + +We will meet the test. + +To protect freedom and liberty, to expand fairness and opportunity. + +We will save democracy. + +As hard as these times have been, I am more optimistic about America today than I have been my whole life. + +Because I see the future that is within our grasp. + +Because I know there is simply nothing beyond our capacity. + +We are the only nation on Earth that has always turned every crisis we have faced into an opportunity. + +The only nation that can be defined by a single word: possibilities. + +So on this night, in our 245th year as a nation, I have come to report on the State of the Union. + +And my report is this: the State of the Union is strong—because you, the American people, are strong. + +We are stronger today than we were a year ago. + +And we will be stronger a year from now than we are today. + +Now is our moment to meet and overcome the challenges of our time. + +And we will, as one people. + +One America. + +The United States of America. + +May God bless you all. May God protect our troops. diff --git a/examples/gemini/documents/state_of_the_union_2023.txt b/examples/gemini/documents/state_of_the_union_2023.txt new file mode 100644 index 0000000000000000000000000000000000000000..a2ad0b30506f48e8c13f3c5f0426170b54e930fb --- /dev/null +++ b/examples/gemini/documents/state_of_the_union_2023.txt @@ -0,0 +1,667 @@ +Mr. Speaker, Madam Vice President, our First Lady and Second Gentleman — good to see you guys up there — members of Congress — + +And, by the way, Chief Justice, I may need a court order. She gets to go to the game tomorr- — next week. I have to stay home. We got to work something out here. + +Members of the Cabinet, leaders of our military, Chief Justice, Associate Justices, and retired Justices of the Supreme Court, and to you, my fellow Americans: + +You know, I start tonight by congratulating the 118th Congress and the new Speaker of the House, Kevin McCarthy. + +Speaker, I don’t want to ruin your reputation, but I look forward to working with you. + +And I want to congratulate the new Leader of the House Democrats, the first African American Minority Leader in history, Hakeem Jeffries. + +He won despite the fact I campaigned for him. + +Congratulations to the longest-serving Leader in the history of the United States Senate, Mitch McConnell. Where are you, Mitch? + +And congratulations to Chuck Schumer, another — you know, another term as Senate Minority [Majority] Leader. You know, I think you — only this time you have a slightly bigger majority, Mr. Leader. And you’re the Majority Leader. About that much bigger? Yeah. + +Well, I tell you what — I want to give specolec- — special recognition to someone who I think is going to be considered the greatest Speaker in the history of the House of Representatives: Nancy Pelosi. + +Folks, the story of America is a story of progress and resilience, of always moving forward, of never, ever giving up. It’s a story unique among all nations. + +We’re the only country that has emerged from every crisis we’ve ever entered stronger than we got into it. + +Look, folks, that’s what we’re doing again. + +Two years ago, the economy was reeling. I stand here tonight, after we’ve created, with the help of many people in this room, 12 million new jobs — more jobs created in two years than any President has created in four years — because of you all, because of the American people. + +Two years ago — and two years ago, COVID had shut down — our businesses were closed, our schools were robbed of so much. And today, COVID no longer controls our lives. + +And two years ago, our democracy faced its greatest threat since the Civil War. And today, though bruised, our democracy remains unbowed and unbroken. + +As we gather here tonight, we’re writing the next chapter in the great American story — a story of progress and resilience. + +When world leaders ask me to define America — and they do, believe it or not — I say I can define it in one word, and I mean this: possibilities. We don’t think anything is beyond our capacity. Everything is a possibility. + +You know, we’re often told that Democrats and Republicans can’t work together. But over the past two years, we proved the cynics and naysayers wrong. + +Yes, we disagreed plenty. And yes, there were times when Democrats went alone. + +But time and again, Democrats and Republicans came together. Came together to defend a stronger and safer Europe. You came together to pass one in a gen- — one-in-a-generation — once-in-a-generation infrastructure law building bridges connecting our nation and our people. We came together to pass one the most significant law ever helping victims exposed to toxic burn pits. And, in fact — it’s important. + +And, in fact, I signed over 300 bipartisan pieces of legislation since becoming President, from reauthorizing the Violence Against Women Act to the Electoral Count Reform Act, the Respect for Marriage Act that protects the right to marry the person you love. + +And to my Republican friends, if we could work together in the last Congress, there’s no reason we can’t work together and find consensus on important things in this Congress as well. + +I think — folks, you all are just as informed as I am, but I think the people sent us a clear message: Fighting for the sake of fighting, power for the sake of power, conflict for the sake of conflict gets us nowhere. + +That’s always been my vision of our country, and I know it’s many of yours: to restore the soul of this nation; to rebuild the backbone of America, America’s middle class; and to unite the country. + +That’s always been my vision for the country. To restore the soul of the nation. To rebuild the backbone of America - the middle class. To unite the country. + +We’ve been sent here to finish the job, in my view. + +For decades, the middle class has been hollowed out in more than — and not in one administration, but for a long time. Too many good-paying manufacturing jobs moved overseas. Factories closed down. Once-thriving cities and towns that many of you represent became shadows of what they used to be. And along the way, something else we lost: pride, our sense of self-worth. + +I ran for President to fundamentally change things. To make sure the economy works for everyone so we can all feel that pride in what we do. To build an economy from the bottom up and the middle out, not from the top down. Because when the middle class does well, the poor have a ladder up and the wealthy still do very well. We all do well. + +I know a lot of you always kid me for always quoting my dad. But my dad used to say, “Joey, a job is about a lot more than a paycheck.” He really would say this. “It’s about a lot more than a paycheck. It’s about your dignity. It’s about respect. It’s about being able to look your kid in the eye and say, ‘Honey, it’s going to be okay’ and mean it.” + +Well, folks, so let’s look at the results. We’re not finished yet, by any stretch of the imagination. But unemployment rate is at 3.4 percent –- a 50-year low. And near record — and near record unemployment — near record unemployment for Black and Hispanic workers. + +We’ve already created, with your help, 800,000 good-paying manufacturing jobs — the fastest growth in 40 years. + +And where is it written — where is it written that America can’t lead the world in manufacturing? And I don’t know where that’s written. + +For too many decades, we imported projects and exported jobs. Now, thanks to what you’ve all done, we’re exporting American products and creating American jobs. + +Folks, inflation — inflation has been a global problem because the pandemic dirup- — disrupted our supply chains, and Putin’s unfair and brutal war in Ukraine disrupted ener- — energy supplied as well as food supplies, blocking all that grain in Ukraine. + +But we’re better positioned than any country on Earth right now. But we have more to do. + +But here at home, inflation is coming down. Here at home, gas prices are down $1.50 from their peak. + +Food inflation is coming down — not fast enough, but coming down. + +Inflation has fallen every month for the last six months, while take-home pay has gone up. + +Additionally, over the last two years, a record 10 million Americans applied to start new businesses. Ten million. + +And, by the way, every time — every time someone starts a small business, it’s an act of hope. + +And, Madam Vice President, I want to thank you for leading that effort to ensure that small businesses have access to capital and the historic laws we enacted that are going to just come into being. + +Standing here last year, I shared with you a story of American genius and possibilities. + +Semiconductors — small computer chips the size of a fingerprint that power everything from cellphones to automobiles and so much more. These chips were invented in America. Let’s get that straight: They were invented in America. + +And we used to make 40 percent of the world’s chips. In the last several decades, we lost our edge. We’re down to only producing 10 percent. + +We all saw what happened during the pandemic when chip factories shut down overseas. + +Today’s automobiles need 3,000 chips — each of those automobiles — but American automobiles [automakers] couldn’t make enough cars because there weren’t enough chips. + +Car prices went up. People got laid off. So did everything from refrigerators to cellphones. + +We can never let that happen again. + +That’s why — that’s why we came together to pass the bipartisan CHIPS and Science Act. + +Folks, I know I’ve been criticized for saying this, but I’m not changing my view. We’re going to make sure the supply chain for America begins in America — the supply chain begins in America. + +And we’ve already created — we’ve already created 800,000 new manufacturing jobs without this law, before the law kicks in. + +With this new law, we’re going to create hundreds of thousands of new jobs across the country. And I mean all across the country, throughout — not just the coast, but through the middle of the country as well. + +That’s going to come from companies that have announced more than $300 billion in investments in American manufacturing over the next few years. + +Outside of Columbus, Ohio, Intel is building semiconductor factories on a thousand acres — literally a field of dreams. + +It’s going to create 10,000 jobs, that one investment; 7,000 construction jobs; 3,000 jobs in those factories once they’re finished. They call them factors. Jobs paying an average of $130,000 a year, and many do not require a college degree. + +Jobs — because we worked together, these jobs where people don’t have to leave home to search for opportunity. + +And it’s just getting started. + +Think about the new homes, the small businesses, the big — the medium-sized businesses. So much more that’s going to be needed to support those three thou- — those 3,000 permanent jobs and the factories that are going to be built. + +Talk to mayors and governors, Democrats and Republicans, and they’ll tell you what this means for their communities. + +We’re seeing these fields of dreams transform the Heartland. But to maintain the strongest economy in the world, we need the best infrastructure in the world. + +And, folks, as you all know, we used to be number one in the world in infrastructure. We’ve sunk to 13th in the world. The United States of America — 13th in the world in infrastructure, modern infrastructure. + +But now we’re coming back because we came together and passed the Bipartisan Infrastructure Law — the largest investment in infrastructure since President Eisenhower’s Interstate Highway System. + +Folks, already we’ve funded over 20,000 projects, including major airports from Boston to Atlanta to Portland — projects that are going to put thousands of people to work rebuilding our highways, our bridges, our railroads, our tunnels, ports, airports, clean water, high-speed Internet all across America — urban, rural, Tribal. + +And, folks, we’re just getting started. We’re just getting started. + +And I mean this sincerely: I want to thank my Republican friends who voted for the law. And my Republican friends who voted against it as well — but I’m still — I still get asked to fund the projects in those districts as well, but don’t worry. I promised I’d be a President for all Americans. We’ll fund these projects. And I’ll see you at the groundbreaking. + +Look, this law — this law will further unite all of America. + +Projects like the Brent Spence Bridge in Kentucky over the Ohio River. Built 60 years ago. Badly in need of repairs. One of the nation’s most congested freight routes, carrying $2 billion worth of freight every single day across the Ohio River. + +And, folks, we’ve been talking about fixing it for decades, but we’re really finally going to get it done. + +I went there last month with Democrats and Republicans in — from both states — to deliver a commitment of $1.6 billion for this project. + +And while I was there, I met a young woman named Saria, who’s here tonight. I don’t know where Saria is. Is she up in the box? I don’t know. Saria, how are you? + +Well, Saria — for 30 years — for 30 years — I learned — she told me she’d been a proud member of the Iron workers Local 44, known as — — known as the “Cowboys in the Sky” — — the folks who built — who built Cincinnati’s skyline. + +Saria said she can’t wait to be 10 stories above the Ohio River building that new bridge. God bless her. That’s pride. + +And that’s what we’re also building — we’re building back pride. + +Look, we’re also replacing poisonous lead pipes that go into 10 million homes in America, 400,000 schools and childcare centers so every child in America — every child in American can drink the water, instead of having permanent damage to their brain. + +Look, we’re making sure — — we’re making sure that every community — every community in America has access to affordable, high-speed Internet. + +No parent should have to drive by a McDonald’s parking lot to help their — do their homework online with their kids, which many — thousands were doing across the country. + +And when we do these projects — and, again, I get criticized about this, but I make no excuses for it — we’re going to buy American. We’re going to buy American. + +Folks — — and it’s totally — it’s totally consistent with international trade rules. Buy American has been the law since 1933. But for too long, past administrations — Democrat and Republican — have fought to get around it. Not anymore. + +Tonight, I’m also announcing new standards to require all construction materials used in federal infra- — infrastructure projects to be made in America. Made in America. I mean it. Lumber, glass, drywall, fiber-optic cable. + +And on my watch, American roads, bridges, and American highways are going to be made with American products as well. + +Folks, my economic plan is about investing in places and people that have been forgotten. So many of you listening tonight, I know you feel it. So many of you felt like you’ve just simply been forgotten. Amid the economic upheaval of the past four decades, too many people have been left behind and treated like they’re invisible. + +Maybe that’s you, watching from home. You remember the jobs that went away. You remember them, don’t you? + +The folks at home remember them. You wonder whether the path even exists anymore for your children to get ahead without having to move away. + +Well, that’s why — I get that. That’s why we’re building an economy where no one is left behind. + +Jobs are coming back, pride is coming back because of choices we made in the last several years. + +You know, this is, in my view, a blue-collar blueprint to rebuild America and make a real difference in your lives at home. + +For example, too many of you lay in bed at night, like my dad did, staring at the ceiling, wondering what in God’s name happens if yo- — if your spouse gets cancer or your child gets deadly ill or if something happens to you. What are you going — are you going to have the money to pay for those medical bills? Are you going to have to sell the house or try to get a second mortgage on it? + +I get it. I get it. + +With the Inflation Reduction Act that I signed into law, we’re taking on powerful interests to bring healthcare costs down so you can sleep better at night with more security. + +You know, we pay more for prescription drugs than any nation in the world. Let me say it again: We pay more for prescription drugs than any major nation on Earth. + +For example, 1 in 10 Americans has diabetes. Many of you in this chamber do and in the audience. But every day, millions need insulin to control their diabetes so they can literally stay alive. Insulin has been around for over 100 years. The guy who invented it didn’t even patent it because he wanted it to be available for everyone. + +It costs the drug companies roughly $10 a vial to make that insulin. Package it and all, you may get up to $13. But Big Pharma has been unfairly charging people hundreds of dollars — $4- to $500 a month — making rec- — record profits. Not anymore. Not anymore. + +So — so many things that we did are only now coming to fruition. We said we were doing this and we said we’d pass the law to do it, but people didn’t know because the law didn’t take effect until January 1 of this year. + +We capped the cost of insulin at $35 a month for seniors on Medicare. But people are just finding out. I’m sure you’re getting the same calls I’m getting. + +We capped insulin for seniors at $35 per month. It’s time to do it for everyone. + +Look, there are millions of other Americans who do not — are not on Medicare, including 200,000 young people with Type 1 diabetes who need these insulin — need this insulin to stay alive. + +Let’s finish the job this time. Let’s cap the cost of insulin for everybody at $35. + +Folks — and Big Pharma is still going to do very well, I promise you all. I promise you they’re going to do very well. + +This law also — this law also caps — and it won’t even go into effect until 2025. It costs [caps] out-of-pocket drug costs for seniors on Medicare at a maximum of $2,000 a year. You don’t have to pay more than $2,000 a year, no matter how much your drug costs are. Because you know why? You all know it. + +Many of you, like many of my family, have cancer. You know the drugs can range from $10-, $11-, $14-, $15,000 for the cancer drugs. + +And if drug prices rise faster than inflation, drug companies are going to have to pay Medicare back the difference. + +And we’re finally — we’re finally giving Medicare the power to negotiate drug prices. + +Bringing down — bringing down prescription drug costs doesn’t just save seniors money, it cuts the federal deficit by billions of dollars — — by hundreds of billions of dollars because these prescription drugs are drugs purchased by Medicare to make — keep their commitment to the seniors. + +Well, guess what? Instead of paying 4- or 500 bucks a month, you’re paying 15. That’s a lot of savings for the federal government. + +And, by the way, why wouldn’t we want that? + +Now, some members here are threatening — and I know it’s not an official party position, so I’m not going to exaggerate — but threatening to repeal the Inflation Reduction Act. + +As my coach — that’s okay. That’s fair. As my football coach used to say, “Lots of luck in your senior year.” + +Make no mistake, if you try anything to raise the cost of prescription drugs, I will veto it. + +And, look, I’m pleased to say that more Americans health — have health insurance now than ever in history. A record 16 million people are enrolled in the Affordable Care Act. + +And thanks — thanks to the law I signed last year, saving — millions are saving $800 a year on their premiums. + +And, by the way, that law was written — and the benefit expires in 2025. So, my plea to some of you, at least in this audience: Let’s finish the job and make those savings permanent. Expand coverage on Medicaid. + +Look, the Inflation Reduction Act is also the most significant investment ever in climate change — ever. Lowering utility bills, creating American jobs, leading the world to a clean energy future. + +I visited the devastating aftermath of record floods, droughts, storms, and wildfires from Arizona to New Mexico to all the way up to the Canadian border. + +More timber has been burned that I’ve observed from helicopters than the entire state of Missouri. And we don’t have global warming? Not a problem. + +In addition to emergency recovery from Puerto Rico to Florida to Idaho, we’re rebuilding for the long term. + +New electric grids that are able to weather major storms and not — prevent those fire — forest fires. Roads and water systems to withstand the next big flood. Clean energy to cut pollution and create jobs in communities often left behind. + +We’re going to build 500,000 electric vehicle charging stations, installed across the country by tens of thousands of IBEW workers. + +And we’re helping families save more than $1,000 a year with tax credits to purchase of electric vehicles and efficient — and efficient appliances — energy-efficient appliances. + +Historic conservation efforts to be responsible stewards of our land. + +Let’s face reality. The climate crisis doesn’t care if you’re in a red or a blue state. It’s an existential threat. + +We have an obligation not to ourselves, but to our children and grandchildren to confront it. + +I’m proud of how the — how America, at last, is stepping up to the challenge. We’re still going to need oil and gas for a while, but guess what — — no, we do — but there’s so much more to do. We got to finish the job. + +And we pay for these investments in our future by finally making the wealthiest and biggest corporations begin to pay their fair share. Just begin. + +Look, I’m a capitalist. I’m a capitalist. But pay your fair share. + +I think a lot of you at home — a lot of you at home agree with me and many people that you know: The tax system is not fair. It is not fair. + +Look, the idea that in 2020, 55 of the largest corporations in America, the Fortune 500, made $40 billion in profits and paid zero in federal taxes? Zero. + +Folks, it’s simply not fair. + +But now, because of the law I signed, billion-dollar companies have to pay a minimum of 15 percent. God love them. Fifteen percent. That’s less than a nurse pays. + +Let me be crystal clear. I said at the very beginning: Under my plans, as long as I’m President, nobody earning less than $400,000 will pay an additional penny in taxes. Nobody. Not one penny. + +But let’s finish the job. There’s more to do. + +We have to reward work, not just wealth. Pass my proposal for the billionaire minimum tax. You know, there’s a thousand billionaires in America — it’s up from about 600 at the beginning of my term — but no billionaire should be paying a lower tax rate than a school teacher or a firefighter. No, I mean it. Think about it. + +We made every wealthy corporation pay a minimum tax. It’s time to do the same for billionaires. + +I mean, look, I know you all aren’t enthusiastic about that, but think about it. Think about it. + +Have you noticed — Big Oil just reported its profits. Record profits. Last year, they made $200 billion in the midst of a global energy crisis. I think it’s outrageous. + +Why? They invested too little of that profit to increase domestic production. And when I talked to a couple of them, they say, “We were afraid you were going to shut down all the oil wells and all the oil refineries anyway, so why should we invest in them?” I said, “We’re going to need oil for at least another decade, and that’s going to exceed…” — and beyond that. We’re going to need it. Production. + +If they had, in fact, invested in the production to keep gas prices down — instead they used the record profits to buy back their own stock, rewarding their CEOs and shareholders. + +Corporations ought to do the right thing. + +That’s why I propose we quadruple the tax on corporate stock buybacks and encourage long- — — long-term investments. They’ll still make considerable profit. + +Let’s finish the job and close the loopholes that allow the very wealthy to avoid paying their taxes. + +Instead of cutting the number of audits for wealthy taxpayers, I just signed a law to reduce the deficit by $114 billion by cracking down on wealthy tax cheats. That’s being fiscally responsible. + +In the last two years, my administration has cut the deficit by more than $1.7 trillion –- the largest deficit reduction in American history. + +Under the previous administration, the American deficit went up four years in a row. + +Because of those record deficits, no President added more to the national debt in any four years than my predecessor. + +Nearly 25 percent of the entire national debt that took over 200 years to accumulate was added by just one administration alone — the last one. They’re the facts. Check it out. Check it out. + +How did Congress respond to that debt? They did the right thing. They lifted the debt ceiling three times without preconditions or crisis. They paid the American bill to prevent an economic disaster of the country. + +So, tonight I’m asking the Congress to follow suit. Let us commit here tonight that the full faith and credit of the United States of America will never, ever be questioned. + +So my — many of — some of my Republican friends want to take the economy hostage — I get it — unless I agree to their economic plans. All of you at home should know what those plans are. + +Instead of making the wealthy pay their fair share, some Republicans — some Republicans want Medicare and Social Security to sunset. I’m not saying it’s a majority — + +Let me give you — + +Anybody who doubts it, contact my office. I’ll give you a copy. I’ll give you a copy of the proposal. + +That means Congress doesn’t vote — + +Well, I’m glad to see — no, I tell you, I enjoy conversion. + +You know, it means if Congress doesn’t keep the programs the way they are, they’d go away. + +Other Republicans say — I’m not saying it’s a majority of you. I don’t even think it’s a significant — + +— but it’s being proposed by individuals. + +I’m not — politely not naming them, but it’s being proposed by some of you. + +Look, folks, the idea is that we’re not going to be — we’re not going to be moved into being threatened to default on the debt if we don’t respond. + +Folks — so, folks, as we all apparently agree, Social Security and Medicare is off the — off the books now, right? They’re not to be touched? + +All right. All right. We got unanimity! Social Security and Medicare are a lifeline for millions of seniors. Americans have to pay into them from the very first paycheck they’ve started. + +So, tonight, let’s all agree — and we apparently are — let’s stand up for seniors. Stand up and show them we will not cut Social Security. We will not cut Medicare. + +President Biden wants to strengthen social security and medicare. House Republicans are threatening to cut them. + +Those benefits belong to the American people. They earned it. And if anyone tries to cut Social Security — which apparently no one is going to do — and if anyone tries to cut Medicare, I’ll stop them. I’ll veto it. + +And, look, I’m not going to allow them to take away — be taken away. Not today. Not tomorrow. Not ever. + +But apparently, it’s not going to be a problem. + +Next month, when I offer my fiscal plan, I ask my Republican friends to lay down their plan as well. I really mean it. Let’s sit down together and discuss our mutual plans together. Let’s do that. + +I can tell you, the plan I’m going to show you is going to cut the deficit by another $2 trillion. And it won’t cut a single bit of Medicare or Social Security. + +In fact, we’re going to extend the Medicare Trust Fund at least two decades, because that’s going to be the next argument: how do we make — keep it solvent. Right? + +Well, I will not raise taxes on anyone making under 400 grand. But we’ll pay for it the way we talked about tonight: by making sure that the wealthy and big corporations pay their fair share. + +Look — look, look, here’s — here’s the deal. They aren’t just taking advantage of the tax code, they’re taking advantage of you, the American consumer. + +Here’s my message to all of you out there: I have your back. We’re already preventing Americans who are [from] receiving surprise medical bills, stopping 1 billion dollar [1 million] surprise bills per month so far. + +We’re protecting seniors’ life savings by cracking down on nursing homes that commit fraud, endanger patient safety, or prescribe drugs that are not needed. + +Millions of Americans can now save thousands of dollars because they can finally get a hearing aid over the counter without a prescription. + +Look, capitalism without competition is not capitalism. It’s extortion. It’s exploitation. + +Last year, I cracked down, with the help of many of you, on foreign shipping companies that were making you pay higher prices for every good coming into the country. + +I signed a bipartisan bill that cut shipping costs by 90 percent, helping American farmers, businessmen, and consumers. + +Let’s finish the job. Pass the bipartisan legislation to strengthen and — to strengthen antitrust enforcement and forbeg — and prevent big online platforms from giving their own products an unfair advantage. + +My administration is also taking on junk fees, those hidden surcharges too many companies use to make you pay more. + +For example, we’re making airlines show you the full ticket price upfront, refund your money if your flight is cancelled or delayed. We’ve reduced exorbitant bank overdrafts by saving consumers more than $1 billion a year. + +We’re cutting credit card late fees by 75 percent, from $30 to $8. + +Look, junk fees may not matter to the very wealthy, but they matter to most other folks in homes like the one I grew up in, like many of you did. They add up to hundreds of dollars a month. They make it harder for you to pay your bills or afford that family trip. + +I know how unfair it feels when a company overcharges you and gets away with it. Not anymore. + +We’ve written a bill to stop it all. It’s called the Junk Fee Prevention Act. We’re going to ban surprise resort fees that hotels charge on your bill. Those fees can cost you up to $90 a night at hotels that aren’t even resorts. + +It’s time to end excessive serve fees for concert tickets. Pass the Junk Fee Prevention Act. + +We — the idea that cable, Internet, and cellphone companies can charge you $200 or more if you decide to switch to another provider. Give me a break. + +We can stop service fees on tickets to concerts and sporting events and make companies disclose all the fees upfront. + +And we’ll prohibit airlines from charging $50 roundtrip for a family just to be able to sit together. Baggage fees are bad enough. Airlines can’t treat your child like a piece of baggage. + +Americans are tired of being — we’re tired of being played for suckers. + +So pass — pass the Junk Fee Prevention Act so companies stop ripping us off. + +For too long, workers have been getting stiffed, but not anymore. We’re going to be — we’re beginning to restore the dignity of work. + +For example, I — I should have known this, but I didn’t until two years ago: Thirty million workers have to sign non-compete agreements for the jobs they take. Thirty million. So a cashier at a burger place can’t walk across town and take the same job at another burger place and make a few bucks more. + +It just changed. Well, they just changed it because we exposed it. That was part of the deal, guys. Look it up. But not anymore. + +We’re banning those agreements so companies have to compete for workers and pay them what they’re worth. + +And I must tell you, this is bound to get a response from my friends on my left, with the right. + +I’m so sick and tired of companies breaking the law by preventing workers from organizing. Pass the PRO Act! Because businesses have a right — workers have a right to form a union. And let’s guarantee all workers have a living wage. + +Let’s make sure working parents can afford to raise a family with sick days, paid family and medical leave, affordable childcare. That’s going to enable millions of more people to go and stay at work. + +And let’s restore the full Child Tax Credit — — which gave tens of millions of parents some breathing room and cut child poverty in half to the lowest level in history. + +And, by the way, when we do all of these things, we increase productivity, we increase economic growth. + +So let’s finish the job and get more families access to affordable, quality housing. + +Let’s get seniors who want to stay in their homes the care they need to do so. Let’s give more breathing room to millions of family caregivers looking after their loved ones. + +Pass my plan so we get seniors and people with disabilities the home care services they need — — and support the workers who are doing God’s work. + +These plans are fully paid for, and we can afford to do them. + +Restoring the dignity of work means making education an affordable ticket to the middle class. + +You know, when we made public education — 12 years of it — universal in the last century, we made the best-educated, best-paid — we became the best-education, best-paid nation in the world. + +But the rest of the world has caught up. It has caught up. + +Jill, my wife, who teaches full-time, has an expression. I hope I get it right, kid. “Any nation that out-educates is going to out-compete us.” Any nation that out-educates is going to out-compete us. + +Folks, we all know 12 years of education is not enough to win the economic competition of the 21st century. If we want to have the best-educated workforce, let’s finish the job by providing access to preschool for three and four years old. Studies show that children who go to preschool are nearly 50 percent more likely to finish high school and go on to earn a two- or four-year degree, no matter their background they came from. + +Let’s give public school teachers a raise. + +We’re making progress by reducing student debt, increasing Pell Grants for working and middle-class families. + +Let’s finish the job and connect students to career opportunities starting in high school, provide access to two years of community college — the best career training in America, in addition to being a pathway to a four-year degree. + +Let’s offer every American a path to a good career, whether they go to college or not. + +And, folks — folks, in the midst of the COVID crisis, when schools were closed and we were shutting down everything, let’s recognize how far we came in the fight against the pandemic itself. + +While the virus is not gone, thanks to the resilience of the American people and the ingenuity of medicine, we’ve broken the COVID grip on us. + +COVID deaths are down by 90 percent. We’ve saved millions of lives and opened up our country — we opened our country back up. And soon, we’ll end the public health emergency. + +But — that’s called a public health emergency. + +But we’ll remember the toll and pain that’s never going to go away. More than a million Americans lost their lives to COVID. A million. Families grieving. Children orphaned. Empty chairs at the dining room table constantly reminding you that she used to sit there. Remembering them, we remain vigilant. + +We still need to monitor dozens of variants and support new vaccines and treatments. So Congress needs to fund these efforts and keep America safe. + +And as we emerge from this crisis stronger, we’re also — got to double down prosecuting criminals who stole relief money meant to keep workers and small businesses afloat. + +Before I came to office, you remember, during that campaign, the big issue was about inspector generals who would protect taxpayers’ dollars, who were sidelined. They were fired. Many people said, “We don’t need them.” And fraud became rampant. + +Last year, I told you the watchdogs are back. Since then — since then, we’ve recovered billions of taxpayers’ dollars. + +Now let’s triple the anti-fraud strike force going after these criminals, double the statute of limitations on these crimes, and crack down on identity fraud by criminal syndicates stealing billions of dollars — billions of dollars from the American people. + +And the data shows that for every dollar we put into fighting fraud, the taxpayer will get back at least 10 times as much. It matters. It matters. + +Look, COVID left its scars, like the spike in violent crime in 2020 — the first year of the pandemic. We have an obligation to make sure all people are safe. + +Public safety depends on public trust, as all of us know. But too often, that trust is violated. + +Joining us tonight are the parents of Tyre Nichols — welcome — who had to bury Tyre last week. + +As many of you personally know, there’s no words to describe the heartache or grief of losing a child. But imagine — imagine if you lost that child at the hands of the law. Imagine having to worry whether your son or daughter came home from walking down the street or playing in the park or just driving a car. + +Most of us in here have never had to have “the talk” — “the talk” — that brown and Black parents have had to have with their children. + +Beau, Hunter, Ashley — my children — I never had to have the talk with them. I never had to tell them, “If a police officer pulls you over, turn your interior lights on right away. Don’t reach for your license. Keep your hands on the steering wheel.” + +Imagine having to worry like that every single time your kid got in a car. + +Here’s what Tyre’s mother shared with me when I spoke to her, when I asked her how she finds the courage to carry on and speak out. With the faith of God, she said her son was, quote, “a beautiful soul” and “something good will come of this.” + +Imagine how much courage and character that takes. + +It’s up to us, to all of us. We all want the same thing: neighborhoods free of violence, law enfircement [sic] — law enforcement who earns the community’s trust. Just as every cop, when they pin on that badge in the morning, has a right to be able to go home at night, so does everybody else out there. Our children have a right to come home safely. + +Equal protection under the law is a covenant we have with each other in America. + +We know police officers put their lives on the line every single night and day. And we know we ask them, in many cases, to do too much — to be counselors, social workers, psychologists — responding to drug overdoses, mental health crises, and so much more. In one sense, we ask much too much of them. + +I know most cops and their families are good, decent, honorable people — the vast majority. And they risk — and they risk their lives every time they put that shield on. + +But what happened to Tyre in Memphis happens too often. We have to do better. Give law enforcement the real training they need. Hold them to higher standards. Help them to succeed in keeping them safe. + +We also need more first responders and professionals to address the growing mental health, substance abuse challenges. More resources to reduce violent crime and gun crime. More community intervention programs. More investments in housing, education, and job training. All this can help prevent violence in the first place. + +And when police officers or police departments violate the public trust, they must be held accountable. + +With the support — with the support of families of victims, civil rights groups, and law enforcement, I signed an executive order for all federal officers, banning chokeholds, restricting no-knock warrants, and other key elements of the George Floyd Act. + +Let’s commit ourselves to make the words of Tyler’s [Tyre’s] mom true: Something good must come from this. Something good. + +And all of us — all of us — folks, it’s difficult, but it’s simple: All of us in the cha- — in this chamber, we need to rise to this moment. We can’t turn away. Let’s do what we know in our hearts that we need to do. Let’s come together to finish the job on police reform. Do something. Do something. + +Ban assault weapons. + +That was the plea of parents who lost their children in Uvalde — I met with every one of them — “Do something about gun violence.” Thank God — thank God we did, passing the most sweeping gun safety law in three decades. + +That includes things like — that the majority of responsible gun owners already support: enhanced background checks for 18- to 21 years old, red-flag laws keeping guns out of the hands of people who are a danger to themselves and others. + +But we know our work is not done. Joining us tonight is Brandon Tsay, a 26-year-old hero. + +Brandon put his college dreams on hold — to be at his mom’s side — his mom’s side when she was dying from cancer. And Brandon — Brandon now works at the dance studio started by his grandparents. + +And two weeks ago, during the Lunar New Year celebrations, he heard the studio door close, and he saw a man standing there pointing a semi-automatic pistol at him. He thought he was going to die, but he thought about the people inside. + +In that instant, he found the courage to act and wrestled the semi-automatic pistol away from the gunman who had already killed 11 people in another dance studio. Eleven. + +He saved lives. It’s time we do the same. + +Ban assault weapons now! Ban them now! Once and for all. + +I led the fight to do that in 1994. And in 10 years that ban was law, mass shootings went down. After we let it expire in a Republican administration, mass shootings tripled. + +Let’s finish the job and ban these assault weapons. + +And let’s also come together on immigration. Make it a bipartisan issue once again. + +We know — we now have a record number of personnel working to secure the border, arresting 8,000 human smugglers, seizing over 23,000 pounds of fentanyl in just the last several months. + +We’ve launched a new border plan last month. Unlawful migration from Cuba, Haiti, Nicaragua, and Venezuela has come down 97 percent as a consequence of that. + +But American border problems won’t be fixed until Congress acts. If we don’t pass my comprehensive immigration reform, at least pass my plan to provide the equipment and officers to secure the border — and a pathway to citizenship for DREAMers, those on temporary status, farmworkers, essential workers. + +Here in the People’s House, it’s our duty to protect all the people’s rights and freedoms. Congress must restore the right and — + +Congress must restore the right that was taken away in Roe v. Wade — and protect Roe v. Wade. Give every woman the constitutional right. + +The Vice President and I are doing everything to protect access to reproductive healthcare and safeguard patient safety. But already, more than a dozen states are enforcing extreme abortion bans. + +Make no mistake about it: If Congress passes a national ban, I will veto it. + +It’s time to pass the Equality Act. + +But let’s also pass — let’s also pass the bipartisan Equality Act to ensure LBG- — LGBTQ Americans, especially transgender young people, can live with safety and dignity. + +Our strength — our strength is not just the example of our power, but the power of our example. Let’s remember, the world is watching. + +I spoke from this chamber one year ago, just days after Vladimir Putin unleashed his brutal attack against Ukraine, a murderous assault, evoking images of death and destruction Europe suffered in World War Two. + +Putin’s invasion has been a test for the ages — a test for America, a test for the world. Would we stand for the most basic of principles? Would we stand for sovereignty? Would we stand for the right of people to live free of tyranny? Would we stand for the defense of democracy? For such defense matters to us because it keeps peace and prevents open season on would-be aggressors that threatens our prosperity. + +One year later, we know the answer. Yes, we would. And we did. We did. + +And together, we did what America always does at our best. We led. We united NATO. We built a global coalition. We stood against Putin’s aggression. We stood with the Ukrainian people. + +Tonight, we’re once again joined by Ukrainians’ Ambassador to the United States. She represents not her — just her nation but the courage of her people. Ambassador is — our Ambassador is here, united in our — we’re united in our support of your country. + +Will you stand so we can all take a look at you? Thank you. Because we’re going to stand with you as long as it takes. + +Our nation is working for more freedom, more dignity, and more — more peace, not just in Europe, but everywhere. + +Before I came to office, the story was about how the People’s Republic of China was increasing its power and America was failing in the world. Not anymore. + +We made clear and I made clear in my personal conversations, which have been many, with President Xi that we seek competition, not conflict. But I will make no apologies that we’re investing and — to make America stronger. + +Investing in American innovation and industries that will define the future that China intends to be dominating. + +Investing in our alliances and working with our allies to protect advanced technologies so they will not be used against us. + +Modernizing our military to safeguard stability and determine — deter aggression. + +Today, we’re in the strongest position in decades to compete with China or anyone else in the world. Anyone else in the world. + +And I’m committed — I’m committed to work with China where we can advance American interests and benefit the world. But make no mistake about it: As we made clear last week, if China threatens our sovereignty, we will act to protect our country. And we did. + +Look, let’s be clear: Winning the competition should unite all of us. + +We face serious challenges across the world. But in the past two years, democracies have become stronger, not weaker. Autocracies have grown weaker, not stronger. + +Name me a world leader who’d change places with Xi Jinping. Name me one. Name me one. + +America is rallying the world to meet those challenges — from climate to global health to food insecurity to terrorism to territorial aggression. + +Allies are stepping up, spending more, and doing more. Look, the bridges we’re forming between partners in the Pacific and those in the Atlantic. And those who bet against America are learning how wrong they are. It’s never, ever been a good bet to bet against America. Never. + +Well — + +When I came to office, most assured that bipartisanship — assumed — was impossible. But I never believed it. That’s why a year ago, I offered a Unity Agenda to the nation as I stood here. + +We made real progress together. + +We passed the law making it easier for doctors to prescribe effective treatments for opioid addiction. + +We passed the gun safety law, making historic investments in mental health. + +We launched the ARPA-H drive for breakthroughs in the fight against cancer, Alzheimer’s, and diabetes, and so much more. + +We passed the Heath Robinson PACT Act, named after the late Iraq War veteran whose story about exposure to toxic burn pits I shared here last year. + +And I understand something about those burn pits. + +But there is so much more to do. And we can do it together. + +Joining us tonight is a father named Doug from Newton, New Hampshire. He wrote Jill, my wife, a letter — and me as well — about his courageous daughter, Courtney. A contagious laugh. His sister’s best friend — her sister’s best friend. + +He shared a story all too familiar to millions of Americans and many of you in the audience. Courtney discovered pills in high school. It spiraled into addiction and eventually death from a fentanyl overdose. She was just 20 years old. + +Describing the last eight years without her, Doug said, “There is no worse pain.” Yet, their family has turned pain into purpose, working to end the stigma and change laws. He told us he wants to “start a journey towards American recovery.” + +Doug, we’re with you. Fentanyl is killing more than 70,000 Americans a year. Big — + +Big — you got it. + +So let’s launch a major surge to stop fentanyl production and the sale and trafficking. With more drug detection machines, inspection cargo, stop pills and powder at the border. Working with couriers, like FedEx, to inspect more packages for drugs. Strong penalties to crack down on fentanyl trafficking. + +Second, let’s do more on mental health, especially for our children. When millions of young people are struggling with bullying, violence, trauma, we owe them greater access to mental health care at their schools. + +We must finally hold social media companies accountable for experimenting they’re doing — running [on] children for profit. + +And it’s time to pass bipartisan legislation to stop Big Tech from collecting personal data on kids and teenagers online, ban targeted advertising to children, and impose stricter limits on the personal data that companies collect on all of us. + +Third, let’s do more to keep this nation’s one fully sacred obligation: to equip those we send into harm’s way and care for them and their families when they come home. + +Job training, job placement for veterans and their spouses as they come to — return to civilian life. Helping veterans to afford their rent, because no one should be homeless in America, especially someone who served the country. + +Denis McDoungin [sic] — Denis McDonough is here, of the VA. We had our first real discussion when I asked him to take the job. I’m glad he did. We were losing up to 25 veterans a day on suicide. Now we’re losing 17 a day to the silent scourge of suicide. Seventeen veterans a day are committing suicide, more than all the people being killed in the wars. + +Folks, VA — VA is doing everything it can, including expanding mental health screening, proven programs that recruits veterans to help other veterans understand what they’re going through, get them the help they need. We got to do more. + +And fourth, last year, Jill and I reignited the Cancer Moonshot that I was able to start with, and President Obama asked me to lead our administration on this issue. + +Our goal is to cut the cancer death rates at least by 50 percent in the next 25 years, turn more cancers from death sentences to treatable diseases, provide more support for patients and their families. + +It’s personal to so many of us — so many of us in this audience. + +Joining us are Maurice and Kandice, an Irishman and a daughter of immigrants from Panama. They met and fell in love in New York City and got married in the same chapel as Jill and I got married in New York City. Kindred spirits. + +He wrote us a letter about his little daughter, Ava. And I saw her just before I came over. She was just a year old when she was diagnosed with a rare kidney disease — cancer. After 26 blood transfusions, 11 rounds of radiation, 8 rounds of cheno [sic] — chemo, 1 kidney removed, given a 5 percent survival rate. + +He wrote how, in the darkest moments, he thought, “If she goes, I can’t stay.” + +Many of you have been through that as well. Jill and I understand that, like so many of you. + +And he read Jill’s book describing our family’s cancer journey and how we tried to steal moments of joy where we could with Beau. + +For them, that glimmer of joy was the half-smile of their baby girl. It meant everything to them. They never gave up hope, and little Ava never gave up hope. She turns four next month. + +They just found out Ava is beating the odds and is on her way to being cured of cancer. And she’s watching from the White House tonight, if she’s not asleep already. + +For the lives we can save — for the lives we can save and the lives we have lost, let this be a truly American moment that rallies the country and the world together and prove that we can still do big things. + +Twenty years ago, under the leadership of President Bush and countless advocates and champions, he undertook a bipartisan effort through PEPFAR to transform the global fight against HIV/AIDS. It’s been a huge success. He thought big. He thought large. He moved! + +I believe we can do the same thing with cancer. Let’s end cancer as we know it and cure some cancers once and for all. + +Folks, there’s one reason why we’ve been able to do all of these things: our democracy itself. It’s the most fundamental thing of all. With democracy, everything is possible. Without it, nothing is. + +Over the last few years, our democracy has been threatened and attacked, put at risk — put to the test in this very room on January the 6th. + +And then, just a few months ago, an unhinged Big Lie assailant unleashed a political violence at the home of the then-Speaker of the House of Representatives, using the very same language the insurrectionists used as they stalked these halls and chanted on January 6th. + +Here tonight, in this chamber, is the man who bears the scars of that brutal attack but is as tough and as strong and as resilient as they get: my friend, Paul Pelosi. Paul, stand up. + +But such a heinous act should have never happened. We must all speak out. There is no place for political violence in America. + +We have to protect the right to vote, not suppress the — that fundamental right. Honor the results of our elections, not subvert the will of the people. We have to uphold the rule of the law and restore trust in our institutions of democracy. And we must give hate and extremism in any form no safe harbor. + +Democracy must not be a partisan issue. It’s an American issue. + +Every generation of Americans have faced a moment where they have been called to protect our democracy, defend it, stand up for it. And this is our moment. + +My fellow Americans, we meet tonight at an inflection point, one of those moments that only a few generations ever face, where the direction we now take is going to decide the course of this nation for decades to come. + +We’re not bystanders of history. We’re not powerless before the forces that confront us. It’s within our power of We the People. + +We’re facing the test of our time. We have to be the nation we’ve always been at our best: optimistic, hopeful, forward-looking. A nation that embraces light over dark, hope over fear, unity over division, stability over chaos. + +We have to see each other not as enemies, but as fellow Americans. We’re a good people. The only nation in the world built on an idea — the only one. Other nations are defined by geography, ethnicity, but we’re the only nation based on an idea that all of us, every one of us, is created equal in the image of God. A nation that stands as a beacon to the world. A nation in a new age of possibilities. + +So I have come to fulfil my constitutional obligation to report on the state of the Union. And here is my — my report: Because the soul of this nation is strong, because the backboken [sic] — backbone of this nation is strong, because the people of this nation are strong, the state of the Union is strong. + +Because the soul of this nation is strong. Because the backbone of this nation is strong. Because the people of this nation are strong. The State of the Union is Strong. + +I’m not new to this place. I stand here tonight having served as long as about any one of you who have ever served here. But I’ve never been more optimistic about our future — about the future of America. + +We just have to remember who we are. We’re the United States of America. And there’s nothing — nothing beyond our capacity if we do it together. + +God bless you all. And may God protect our troops. Thank you. diff --git a/examples/gemini/load_data.py b/examples/gemini/load_data.py new file mode 100644 index 0000000000000000000000000000000000000000..8e14b4b3b36d81693c3e6651676e345ef65566e0 --- /dev/null +++ b/examples/gemini/load_data.py @@ -0,0 +1,106 @@ +import os +import argparse + +from tqdm import tqdm + +import chromadb +from chromadb.utils import embedding_functions +import google.generativeai as genai + + +def main( + documents_directory: str = "documents", + collection_name: str = "documents_collection", + persist_directory: str = ".", +) -> None: + # Read all files in the data directory + documents = [] + metadatas = [] + files = os.listdir(documents_directory) + for filename in files: + with open(f"{documents_directory}/{filename}", "r") as file: + for line_number, line in enumerate( + tqdm((file.readlines()), desc=f"Reading {filename}"), 1 + ): + # Strip whitespace and append the line to the documents list + line = line.strip() + # Skip empty lines + if len(line) == 0: + continue + documents.append(line) + metadatas.append({"filename": filename, "line_number": line_number}) + + # Instantiate a persistent chroma client in the persist_directory. + # Learn more at docs.trychroma.com + client = chromadb.PersistentClient(path=persist_directory) + + google_api_key = None + if "GOOGLE_API_KEY" not in os.environ: + gapikey = input("Please enter your Google API Key: ") + genai.configure(api_key=gapikey) + google_api_key = gapikey + else: + google_api_key = os.environ["GOOGLE_API_KEY"] + + # create embedding function + embedding_function = embedding_functions.GoogleGenerativeAIEmbeddingFunction(api_key=google_api_key) + + # If the collection already exists, we just return it. This allows us to add more + # data to an existing collection. + collection = client.get_or_create_collection( + name=collection_name, embedding_function=embedding_function + ) + + # Create ids from the current count + count = collection.count() + print(f"Collection already contains {count} documents") + ids = [str(i) for i in range(count, count + len(documents))] + + # Load the documents in batches of 100 + for i in tqdm( + range(0, len(documents), 100), desc="Adding documents", unit_scale=100 + ): + collection.add( + ids=ids[i : i + 100], + documents=documents[i : i + 100], + metadatas=metadatas[i : i + 100], # type: ignore + ) + + new_count = collection.count() + print(f"Added {new_count - count} documents") + + +if __name__ == "__main__": + # Read the data directory, collection name, and persist directory + parser = argparse.ArgumentParser( + description="Load documents from a directory into a Chroma collection" + ) + + # Add arguments + parser.add_argument( + "--data_directory", + type=str, + default="documents", + help="The directory where your text files are stored", + ) + parser.add_argument( + "--collection_name", + type=str, + default="documents_collection", + help="The name of the Chroma collection", + ) + parser.add_argument( + "--persist_directory", + type=str, + default="chroma_storage", + help="The directory where you want to store the Chroma collection", + ) + + # Parse arguments + args = parser.parse_args() + + main( + documents_directory=args.data_directory, + collection_name=args.collection_name, + persist_directory=args.persist_directory, + ) diff --git a/examples/gemini/main.py b/examples/gemini/main.py new file mode 100644 index 0000000000000000000000000000000000000000..b163e3bbbb1650fa581689bb3cc369d1df7f7cd4 --- /dev/null +++ b/examples/gemini/main.py @@ -0,0 +1,143 @@ +import argparse +import os +from typing import List + +import google.generativeai as genai +import chromadb +from chromadb.utils import embedding_functions + +model = genai.GenerativeModel("gemini-pro") + + +def build_prompt(query: str, context: List[str]) -> str: + """ + Builds a prompt for the LLM. # + + This function builds a prompt for the LLM. It takes the original query, + and the returned context, and asks the model to answer the question based only + on what's in the context, not what's in its weights. + + Args: + query (str): The original query. + context (List[str]): The context of the query, returned by embedding search. + + Returns: + A prompt for the LLM (str). + """ + + base_prompt = { + "content": "I am going to ask you a question, which I would like you to answer" + " based only on the provided context, and not any other information." + " If there is not enough information in the context to answer the question," + ' say "I am not sure", then try to make a guess.' + " Break your answer up into nicely readable paragraphs.", + } + user_prompt = { + "content": f" The question is '{query}'. Here is all the context you have:" + f'{(" ").join(context)}', + } + + # combine the prompts to output a single prompt string + system = f"{base_prompt['content']} {user_prompt['content']}" + + return system + + +def get_gemini_response(query: str, context: List[str]) -> str: + """ + Queries the Gemini API to get a response to the question. + + Args: + query (str): The original query. + context (List[str]): The context of the query, returned by embedding search. + + Returns: + A response to the question. + """ + + response = model.generate_content(build_prompt(query, context)) + + return response.text + + +def main( + collection_name: str = "documents_collection", persist_directory: str = "." +) -> None: + # Check if the GOOGLE_API_KEY environment variable is set. Prompt the user to set it if not. + google_api_key = None + if "GOOGLE_API_KEY" not in os.environ: + gapikey = input("Please enter your Google API Key: ") + genai.configure(api_key=gapikey) + google_api_key = gapikey + else: + google_api_key = os.environ["GOOGLE_API_KEY"] + + # Instantiate a persistent chroma client in the persist_directory. + # This will automatically load any previously saved collections. + # Learn more at docs.trychroma.com + client = chromadb.PersistentClient(path=persist_directory) + + # create embedding function + embedding_function = embedding_functions.GoogleGenerativeAIEmbeddingFunction(api_key=google_api_key, task_type="RETRIEVAL_QUERY") + + # Get the collection. + collection = client.get_collection( + name=collection_name, embedding_function=embedding_function + ) + + # We use a simple input loop. + while True: + # Get the user's query + query = input("Query: ") + if len(query) == 0: + print("Please enter a question. Ctrl+C to Quit.\n") + continue + print("\nThinking...\n") + + # Query the collection to get the 5 most relevant results + results = collection.query( + query_texts=[query], n_results=5, include=["documents", "metadatas"] + ) + + sources = "\n".join( + [ + f"{result['filename']}: line {result['line_number']}" + for result in results["metadatas"][0] # type: ignore + ] + ) + + # Get the response from Gemini + response = get_gemini_response(query, results["documents"][0]) # type: ignore + + # Output, with sources + print(response) + print("\n") + print(f"Source documents:\n{sources}") + print("\n") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Load documents from a directory into a Chroma collection" + ) + + parser.add_argument( + "--persist_directory", + type=str, + default="chroma_storage", + help="The directory where you want to store the Chroma collection", + ) + parser.add_argument( + "--collection_name", + type=str, + default="documents_collection", + help="The name of the Chroma collection", + ) + + # Parse arguments + args = parser.parse_args() + + main( + collection_name=args.collection_name, + persist_directory=args.persist_directory, + ) diff --git a/examples/gemini/requirements.txt b/examples/gemini/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..f7c6d44b3574e620a567bb4dfd9511d259d53d75 --- /dev/null +++ b/examples/gemini/requirements.txt @@ -0,0 +1,3 @@ +chromadb>=0.4.18 +google.generativeai +tqdm diff --git a/examples/multimodal/multimodal_retrieval.ipynb b/examples/multimodal/multimodal_retrieval.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..253951a2919ee6ee3ea9ef9a5f231466ef943585 --- /dev/null +++ b/examples/multimodal/multimodal_retrieval.ipynb @@ -0,0 +1,514 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Multimodal Retrieval\n", + "\n", + "Chroma supports multimodal collections, i.e. collections which contain, and can be queried by, multiple modalities of data.\n", + "\n", + "This notebook shows an example of how to create and query a collection with both text and images, using Chroma's built-in features. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dataset\n", + "\n", + "We us a small subset of the [coco object detection dataset](https://huggingface.co/datasets/detection-datasets/coco), hosted on HuggingFace. \n", + "\n", + "We download a small fraction of all the images in the dataset locally, and use it to create a multimodal collection." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import os\n", + "from datasets import load_dataset\n", + "from matplotlib import pyplot as plt\n", + "\n", + "dataset = load_dataset(path=\"detection-datasets/coco\", name=\"coco\", split=\"train\", streaming=True)\n", + "\n", + "IMAGE_FOLDER = \"images\"\n", + "N_IMAGES = 20\n", + "\n", + "# For plotting\n", + "plot_cols = 5\n", + "plot_rows = N_IMAGES // plot_cols\n", + "fig, axes = plt.subplots(plot_rows, plot_cols, figsize=(plot_rows*2, plot_cols*2))\n", + "axes = axes.flatten()\n", + "\n", + "# Write the images to a folder\n", + "dataset_iter = iter(dataset)\n", + "os.makedirs(IMAGE_FOLDER, exist_ok=True)\n", + "for i in range(N_IMAGES):\n", + " image = next(dataset_iter)['image']\n", + " axes[i].imshow(image)\n", + " axes[i].axis(\"off\")\n", + "\n", + " image.save(f\"images/{i}.jpg\")\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Ingesting multimodal data\n", + "\n", + "Chroma supports multimodal collections by referencing external URIs for data types other than text.\n", + "All you have to do is specify a data loader when creating the collection, and then provide the URI for each entry. \n", + "\n", + "For this example, we are only adding images, though you can also add text." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Creating a multi-modal collection\n", + "\n", + "First we create the default Chroma client. " + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "import chromadb\n", + "client = chromadb.Client()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next we specify an embedding function and a data loader.\n", + "\n", + "The built-in `OpenCLIPEmbeddingFunction` works with both text and image data. The `ImageLoader` is a simple data loader that loads images from a local directory." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "from chromadb.utils.embedding_functions import OpenCLIPEmbeddingFunction\n", + "from chromadb.utils.data_loaders import ImageLoader\n", + "\n", + "embedding_function = OpenCLIPEmbeddingFunction()\n", + "image_loader = ImageLoader()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We create a collection with the embedding function and data loader." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "collection = client.create_collection(\n", + " name='multimodal_collection', \n", + " embedding_function=embedding_function, \n", + " data_loader=image_loader)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Adding multi-modal data\n", + "\n", + "We add image data to the collection using the image URIs. The data loader and embedding functions we specified earlier will ingest data from the provided URIs automatically. " + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "# Get the uris to the images\n", + "image_uris = sorted([os.path.join(IMAGE_FOLDER, image_name) for image_name in os.listdir(IMAGE_FOLDER)])\n", + "ids = [str(i) for i in range(len(image_uris))]\n", + "\n", + "collection.add(ids=ids, uris=image_uris)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Querying a multi-modal collection\n", + "\n", + "We can query the collection using text as normal, since the `OpenCLIPEmbeddingFunction` works with both text and images." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Querying with text:" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Querying for \"Animals\"\n", + "\n", + "retrieved = collection.query(query_texts=[\"animals\"], include=['data'], n_results=3)\n", + "for img in retrieved['data'][0]:\n", + " plt.imshow(img)\n", + " plt.axis(\"off\")\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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ua0QDLouGzuK6LmVZorWmLEs818NxwTTdPKDLetrjSmtNXWscV6Ich7KsmM1m1LVmOBgwzxfs7e2ztbVFEPgsFvMu6FnNYEVZVniei+/79OIef/bP/jkODvYZDkYcHOxx7txFwjBgMNhgsZjjSQjDANcNKPIKJQ37+7uEoUeyXCCk4Pz5V3FcxR/+0R8SxDG/9uv/M3/tr/01jh8/hmnx3R/h9bYyqbt/5AqAbb/MN+ZB3V0a3iuzuuN+03bzWKl+2r/b3X43d+uD9SO0jNUotszu5TLh4oWL3Z/TLGFtbcTa2lqnsfN9n62tre72crkkzzLm8zmj0Yjlckld1yil2NnZwfO8Tl6jlOUxmaYD2OooPc8DoKorkjQB6AKe1eSp7lj3PA+jDXVtEEh0bSiLmiiMWV/fZG20jtEwPpywXC4wNgUiCHyKIqeuK5QSBIFPFIVEPZeLl17B9eDRxx7iQx9+gMEgYGNjyGIx5YknPsJnP/NZTI3ljPkes9mYskj5p//kf+Tv/J2/zW/9q3/FxsYGfuChdcWXvvRFer0evu9jdCveFpgWF/4RXG+7u3cvBvnR3492xL2C0KqWb/X+u7dntO5wJ1tca7QxKEfY1NscdfzueN7dmd0H6327jNFNtgxFobly+SqO4zGdzsiyjH4/oiwLlFIYYxiNRjiO02VIvV6Pg4MDjDHM53M8z6MoCpIk4fnnn2d9fR1jDHEcI4TAdxRRHDGbzQhDW9ZpY7pSbn19nes3ruA4Fi/yfYsfKaWaDKq2pWFVIMQRd68tIfM8b9wUPHzfs+RQrRGCLljGcdxts65r5osDJpPbbI+P8cx3vspyseT+Bx7g6rULuL7h9t5VinKdxSJFSiut8n2Pk6d20Npw4eKrPPvsMwyHA+qqZHd/jzAasL1zgsVizqDfw5WKWmswFnf7UTw93nKQ6jhMTdl3z2D1BuWe/dP3oR3c+WjkCg5lhGg1E4Al/SnH+VPfen0v1xuNX3y3gr5oLkB1rSnLgi984Q+5eXOX5TLFdWE06rO3dxshbBDQ2rKzr127xvr6encbIAjDrrQry7J7jRbHqquKqN9HKUUYhuRFbntdzePjOEYpRVVVFEXVHeda6y4Lq+vaAvWOJU9WlS1X67oiTXOKoiLLGmcFP6Aoc4LQa/SGElkKlCMoyoxsngMGRynCIGD/4BZSSra219nYGHHx4nkru6lrxgcT1oZrTCaHRGFAFAUM+hHnzp2nyCuSJCVNlsRxSKU1BsXe3i57e/ucOnmSsqpRAhzHu+f3/KNwUX9bmdRq8LlbTNzyXFa7eO3/b+Qb9YaYlGgyppXHddtgpdRU6o7nfLBev97O7Nd7HcDv1kGtTd1kxNZd4GB/TFlWTYllhcC1rqlK63Dg+z7j8bjDkbryDYiiCCklZVni+z5RFOG6Vu+XJAlVVXF4eEiap0RxTFXVICwQHoYhk8mEKI7oxTHT2cS+v87R4Ah7tUD6kYi4fR+9Xo8kSbrXzNKUOI66YzZJkgact0TSNousjaAqNcPhkKIs6cUjysIghYeuNE4UUuYV6+sbZFlKUeSMx3vcvHkdrSFNcpSyrHjHlQxHQz729I9ze++Q+XxuzxMkSgnqskY6dxI+f1TOmbecirQl2r3sV+4VdO4VoO7182avt/q4Fh84YhiIrhRYfb0P1jtb9wpm7/ZwayEs/hMEIY888iHqygLT/X6f+XzK4eFBhwUdHh6yWCzY3t6mLEsmk4ntznF0bLakzDaIxHHM+vo6ynGoqpKqri0I3wDni+WSjY0NyrIkzTLCKMJxnM4doQ2EcRxz//3326xIKowRCCEJw4h+f0gUxRiDpTIoBz8IEQKKIqeqSrSucRzV4GMlYAXJjgqQMiCK1thYP0G/t8mL37uIFBFbm6cYDY6hhMfV166gq4oiS8nShOlkTF3muI6i34vZ3txsgnfN9773AtpoDg4OuHLlqiWfFhVCyNd1935Uhpe/9XpJiDsym5YG0P0vX++B9FaCUfu41cdLJdHS8qM0zQVXWHKnQAIKIdQdpeePyg5/y8vc9dPd2Zri1RhTU9aWWV0bQ20M2hhqampTo02NoYbmx+gSTGVvmwp0hdEldWVB3bsN+losxl79DQaDNhXG1A1zuqLW5R33tVnC6o/W9R3vG6xpnBS2e9bvRzzyoQep65LNzQ02N7eI4yFxNLAEzUZUG0VRwzmy+FAQBNS6ptYVx0/soByJ77tsbKyTFxlgKMocIcELQuK4x3y+wAsC4jhG1zWj4QDPdVhMJ0ynY4bDAb1ejOMosiylLAuSZMmVK5epqhJHSaQx6KpCAHVVMp1McByHfr9PWVkWfF1pyqJiuUjI0pyyqKjKiqqsqcoaRzloDXlecvHia+ze3ufq1WsIIQn8gKee+hhKOZw6fYKf/OlP8dGnnmQwHBFFPYIgwhjZkUN9z8d3A25cv854fIjvOXz5y1/iN37j18nzFNexj6sFlNqyGWu9YkWzeli9D0+jt+8n1ZZ7gHxdBiU7YO6Nunx3bOsef7NXQsuTtZtsX89u376GQjVB6l7b/NO97oxcQkgbmBqQ1jKb6QIGQqDMEcandU1RFCyXS9IkIctzC0bXR0xo29lycByF79sTut/v4bpuBxrb0qXV2x21ue13oBpvJXNXc2PlfaMASV0bpJCcve8Mx3a28JQCYYjCAWm6REqr4ZvP5115tVwuiaLIljRYBngUhbzwwnep65rbu7dsiXja614zL2tcLyAIbba0WCwQQuA6CoFBSUEc9zhx6gSvvfYaBwcHHVYFNJm8pCpKe0E2hroskUJYtwQMZVVRliVCSdIkwxjr0Km1RtBeYAVGY7NGY22I0zTDc13SdAlIBoMBX/7Kl9jZ2eHY8U2u3bjMcpk2UiBBWYIQBt93OH7iJK7jkCYZRV4xm0w598rLeF7AYx/+EK7jUhYVUkjysmzwNU1ZFPTC4Ig4/T5WYr1j+fQblXj3ClJv9tx7bquBt1qqgRCv394qTvVvy7o7WbT2S3WD1dkwbrQGoZBCUVaa6WTCbDrn6tWrXLhwgevXr7O/v898NmeZLCkLi/EYBHVtqKuqK7EAXNej3+8zGo0YDPucPn2CBx98kDNnzjAaDen3BzhCdYLw1oBQStvttdmURqn2gmK/XIvzHCXox49v8e/9e3+J3/lXv81yuST0ffYXSza3NjqeVJvdtd7kw+GQWtuMcW9vr/N/6vf7GGOYTqddkGn5UmEYdgF1sVh0XlB1XZNmKefPnyfPc+I47pjhd+NSAtBYR868KABwXFsmCilwXY9KG9IkwWiQwgEkSjqNzFQ1HUSXoihRSrJcLhiN1vjoRz/Gd7/7XT784Ud54oknuXr11aZzuCBNM3QNcdxnsUjw3BDXCTk8OCBJUjY2tvCDgDjuEwQRa2sbOI7DzWs32b29yyMffRSJzZIvXbrE2VOnGA6H9lh6HzMUfqguCEdX9+9PsHyzbt+R20HTKcRmDKubEkKi7qH8/tO87lXSSnl0khkDRV5w9eo1nv/udzn/6gXOnz/Pwf5hJ7B13OYk0zaaKKlWiLOgtfXoTpIMpSTGwMHBIVJeRQisRlIIAt/n9OnTPPzwwzz2kY/wxBOPs7G+hut6SGkDkME021gluzVqcGHvk1Kga8BItDYUZYkxGtdzcVyHwWBAkiQsl0s8z+ta/kopBoMB169fI+pFXL9+vfF6cllbW2M2m3WPm0wm+J7HYrFAKclDDz3ChYvnGY/HTCaTBnD37H4xml6vh+d5jMfjjr3eYlQGqIoCoVQziMGaMCrH6ZjtZVniOR6LeomUDkJIirxASacLeFKqhkoRc+rUaSaTKb/0i7/EuXOvIgTs7t7m+PFjhCGcO/diI7C3Gd329g4nT/gkScHtWweMx4eMhhFVqRlPdtk0gn4fXnrpFR558GGuXLnK9uYmaZKQK4c/+MIX8D2Phx94cPUbed8mU+84SK3e1/2/Quhs738z7tIbZVJtMtU9r8vQRGNK3zy2M8N7HxbSP+C6w8/a3mH/6+62+0brijRNOPfKeb761a/xzDPPcfPGLbIsRwjLsNa1QEoPpWxw0p1mDrRuzAqbzEZrGzyEsJlVmxHVtWnwqdpigVpw7twFXn31In/wB39Mr9fjQx/6EJ/+9Kd49NFHOXXqOEIobMUpm/d9dBwcGSU337k0nD59EgEkSYojFQJB1pA16wb07vf7zXurmUwmbG9vc2v3FsvlEt/3AUjT1JIZm8/p+z4YSxcAxcHBQUNZcMiyjDAMiaIQ6UnKqmSxWLBYLDrmehug6rrG1BqjDUpZaCJJElzPg7Ikyy34XtU1y7RozPEaMz9lg1WbCdZ1zebmJqdOnSJNU86cOc33vvcCN2/eIkns57x06RKHhzfJ8wzP85FK8eMf/yT/8X/0V/n1X/9NvvLlrxLHfT7zmc+yXEy5dvMG657PZz7zWW7cuMkTTzzJcDhEa1jf2ODgcMzO8R2yNOXa5Svw8z/fyNlWA9T7LUT9EKbFtLfbzOf7kTnvltbcve3W59oGPFssW6zl6MSCIx3fn1YCZws4H+1zuXK/LaGuXbvGN7/5Vf7oj/6Yy5evUhQVIG2JIVXzuw0upmoAcAyqKWO6fd1dBPQ9pE93SqAcx5ZNZVkBNFyimjTNODwc88wzz7K9vclHPvIRfvZn/wwPPPAAURziug7GtCPHrGuFlAqjm5PEwKVLr3VTXG7cvMGZ06c7PZ4QgjRNu8ynfX9lOeLy5csEgTWha4cttKVcC7wPBuuURU6SJKRZSlVVHeXB9/0GhK4ZDKxpXpqmGGO6snf1+PQ8D8ezHCu3KT2rum6CT0VeFATKx/dbxntNi41FUYRSkul0yqlTJxHCcOnSRQaDIY7jUlU1T//Y08RRzDe+8TUcx+6nyWSCkh6XLl3k+eef5cKFV0nSheUMKsF4ckCaJmxtb/ORjzxGXdX24nXuHHmW8uyz3+HG7g3mizlSSn7xF38RpRy7j7RtikghcNT7rzp5Rx7nb5hVCWh5JKvPeTPN372C2WrZuHoi2ZRXdJIFKf50AOf3zgRNc1LLBhvRncTjwoVL/O7v/i5f/9rXmU4P7ZXdcTG16bprWlt8SjesbiEEorlqojXougkOrb1Hu9dNk/WYJjCufnet5QSNrbPtrlYNYKyUnbaSpgnXrl3nm9/8Jk888Tg//dM/xVMf+yj9fkxd6zueaytNgdE116/fbE58t9meYrFYdGzy9iKXpimbm5sURcGt27c6jEopRVmWzOdziqJgbW2NJLFl7mg0wvdcbt++zcHBAULYDKsoCjY3NxmPD6lMSZJaXtVwOCRNU1r6izHGNg4cgxKyc0hYW19vKAwpRVkihKTX66GLnLxIGj6fbSAEQYCuNXmeEfdCXnzxex0gb3WHUx555EMkyZK1tRGPPPIISTLFGM1ikeB6LuPJIf/kn/5jtDYox4Asmc/H3Lp5nc2dY3zikx/n5Zdf5Pc//3v88R/9IWdPneHJJ57k1Zdf4dbBbbIs4+TJk9y8cYMg8BmOrN1Lr9+nasTQ77dA9QONtHpdVrRiUreKWbUt7Dfqxr0uYK0Eq6PA1QCuTWa1Olz0T8taDVYGg1S2RKlrKMuaZ5/9Dp/73O/z9a9/gyzNLRhcWqC2LrW9IhrdmbtZjyOQpu46sQBKSpwGX6qrupkfBzRzDG3geP331VwummDhdBcOpWxmZgW01pnSdR1u3rzJdDrhwoULfOy5j/Hn/vyf5f7772vKQBswlVLUFSRJxuXLl1GO073/vMiZTidkWUYQBJ2TZhRFnD59mi9+8YtsbW1ROtaobjAYUJYlu7u7XUdwOp2ytrZGkecMB33yPOfs2bMsFnPCMOSVV15qfM+VLf/yrJOvtJhWW/oNBgPyNKNuZDm+7xOEoQ2ELV2jqpCORAiNPdft/b1eH8dRzOcJrmf3j5SKsrBZqdX1WQnOY489xt7eHhsbfa5de43Fwo7g8n2Pzc11XNfl/PkLPPDAaWpdc+nyy4SRh+cpLlx4hcliQRAq6rJkMt3nO89+izIvKPOCtdGIg4MDPve5z5EXBceOH2exXPCf/ef/GcePH39f6mF/oHLvdWVfixmtZFv3OtjfbFurNIeuW9R1HlYwDSmtcR53Zmo/qut12VRTqtS65twrr/LP/tmv8cwz36EqNULYEqWqalzlU+Ylta5RygYQ3/NwXQfPc1COgy/t1VEIrOi0iUTt91LrmgpBaazlSJIsGw+nvLnAgFK2OyWkc0cpan2/lXWkdBSWfiAoihLHUSRJyqVLr7G7u8ur58/xZ3/uZ/n0T36atfUBSjlNZmUzk1s3byLacspxSJZHLO7VkWC9Xq8jdkplL1RhGJJlWQec53nOYrHA9312dnbY2xsTRSFKKfI8Z319vdtmkiRsb2/ysY9/jH/12/+KIAi6DmfbFbSDGDLqusJpgknb3auqCkc5GNeQ5RlZlhEHiqqykhubrWrSbEmtSxwhWSymIFzKwu6/5dJma5PJmOVywWAw4OLFCyyXCWVpzfT6/R7b25tMJmPinst0voeUkKUlSvjcuHmVw8kBw7V1O/DBdciLlKvjQzzHJc1q6+m+sUlRWp3jYrngkQ99iFfOnWPn+PH3/sB/C+sHyqRW/9ZmUqueUnf/vcOkVjKm9n9zj222eFR7W0qB0bLj8ayWez9KAaqTIYoGmxF2nHxLJLBTdwyXrlziN3/jX/ClL/0b8tSOEtfassVaTKisE3zPIwhioihEyHYQaUMDECCpcZRs+D12t+um9LOYkkYagascerHHxnofo22WtVwumc1mLJdLqjKlFs1UEuUgGlqAwaCLGtF011zPQ1QVRVEANgjVuuaVV15lb2+PS69d5jOf/Uk+9MiHCIIQrQ27u/sWMO71SJOEKIzIsozNjQ1qo1kmS6RSzOZzpLKWLGEQ2E6g63YeUJ7n2UkszUrTlDCM6EUFk8mEosgpiox+P25KMYnBcHt3lxdfepFaV4zHC3w/6MpY13XZ2toiyzPKIkcLqOojgqvN7I8qB6M1xghL7mxsYGpdk2c5UkmSpeWnOSrA830818NgcFwX3/d4/rvPM58vkEKQZzlPPP4EO8d3cBzB17/+NYypCcOYw8N9fN8jDCPSJKeoKsqqYJkt8byA9dE6RVHwxJOPc+3KVe67/zif/qmfYnd3l1defdXaMM/n9Hs9ju8cPyrzdNO4aZpVrPzXNa7eQ4D9HY+0gnsFrCNA+877jx5vaE4QIY66CisYVVtSSNHqA+12W/xCCNGo12XX3ftRClAAurKlmeMKjKkaSNV+/VUJyyTjX3/uX/O//NZvcvvWbQI3oK7B1DXCSAvSKp9+P2YQW19t5ThgahzHwXXd7vvSWlMaW9ppbf3BV6ftSFcS+A5BQ6IV2CzL1IK6hJHf4/gwJEtTFknGOMlZLJZkWYqQDm4QYDDURoM21CWI2mZuXhhQ1zVVWVLnObphxH/pS1/m9q1dPvvZz/L00x9jfX2N8WSfqswRRMymU4QQ9KOeJagjWMwTagwoieu7zKYT4sCzbPIGswI6A7vjx49z9epVjDEslwt8R3F4MKUqC4SEg4N961SAJi9zsiLj4mvnKYoUQ01RNp7oAvwgYLGc2OAnNUYqqrKkqsuOSxV5EYF0kSsE1rIApex3N5styLIC3/cpS4OjAspKo01JnpccP36czc1NDg8P2d/fx/d9RqMRJoOr125w/sIlHnnkERYLK385fvwExqQY7bNMKoLQQ2faZpNGo5FEgc+pEycpqoLpcs6jTz7O7sFNFumSD334YfI8I0lyTh0/xYcefAgqjRZNk6Y53bUxWEXN0TQmAbyXqNUPPAvnzuznjQPU6uPlSmB5IyC9rX7uCdJz1O36UVxCCVwlqHWJQTfXJiuROH/+NX7lV/4h333+e3hegC+GVHmJqQ2CmsB36Pdj4ihAYPAcO8PNdd3OwK2oKuq6sCdSVVEJpyF+QkuktB3CakW6UmGwQS7wA0Lfxw8CJIK6qvAMDLyAtZ2Isio5PJywf3jIbD5HyEavJi0loqo0uC7g4DoK15GkSdIN5azrmhdfeok0tWOnPv0TP8Hzz38Xx3FIs6xTM1RVxWKxIOrHaF3jOi55kaOkaiQyNb1ehBOGjMdj+v1+Z4Y3GAwahrzg8PCQ7bUtWyLXFUm6ZHNrk9l8RhAEnVYvy7LOKcHO0rPeVNZuuCaOewRBSJ4Xnc9US09ot2E7n9aJoXVlaEH9u62KrJtCjes63LhxszHQq4njCCEgyxKO7WxzeDBhPp/xnecWZFnKsWM7RLHPL/7iL/DSSy9x6/Y10mxpMzJjqKqaqi4pyowLF89T5AVhGDJfzPjOc8/y6IcfZbGYM5tP+IVf+IsURcJXv/pVfuInPoWQCulaNYGQooNUWlSYlf/fq/VD40m1mdHd99+92i+qDUz3ClBCtFhWi0+9XokvlXxPU84f5hLCUNdlh7lpbUjTjN/5nc/xP/6jf0pVajwVUCUSbTRGa4LQZ309wvM0QSjxvQaHM32LL2RJk4u1OJ6DE7j4UlEZD4PsLg4GezJ13CsMRpTUuqDIc5IsYzJdIIDA9+nFMVHcJ3IdqrpCOoITJ3c4dnybZZJy/eZNDvYPkUrZksWNMaamyAp0MyU4iiLbBWsClRBw5eqV7uTd2tqiPxqymM1Z31hnPpshpMWafD9oPMEt0L63t8ew38dVyvKUoqjDllpg/fr1613pV9c1RVmwtr6GwbBMlvR6Pfb394miyHbucpeqzmidObXWHct9dYhoe6y3gaYNQnkjL1o1gWwDcvuY1ksKrAODki6O7xHFEcZo5vOptRUWuhlUotnbu42u6ThqWtu5hOfPv8p8PqMoSvb39jCi6KbWuK4Caq5fv4rjuAz6A9JswVe+8iWiKOZrX/9qpyT43c/9NmdOn+HRRx/j1fMvcziZ8uijj7G5sWHPQ+4S+LYDB97DU++HSua0Xbk3+Fu73oB4eefjX49NrWwAEK+jH/woLVt2WfmJrjVXrlzlV//+P+Bb33oWzw2RCBbLJaJ2CEOP0eYGw2GAcmpcrwZRUpb2ZK9q3474crxusrOUsiNsSiFwhQ/i6AQDuq5reyLVWiAdie9HxD1NXVcUeUGapuweToEpvucwGsaEUQwYPOk2wXPEZDrh+rXrHI7HCO3akVDGUBUFOeB6XjecczabUZYljuNw5dpVlFJ87GMf4y//5b/MF77wBcos5/DwEKdhaE8mY6q6xtE2u8rThJ2tLebTKePxIZvHjxOGIWVZkuc5VVUdZZWNTnEQ9umPLEbUSl3W19c5nB42JWkFUiCEzZAcx8UYmw1Z8Nxy0Kwm0boorAacdjJye9FVSpGmaRes2vva7dmAXdPr9fjok09x6dKF7uLVOiVEUdSRchE1s/mYOI5ZLCcNuXUGgHIk2tiyM0mWDPrWINBy4WrGkwMcx0VKwWIxQwjJfD7B9x3G4wl7e7e4cfMqzz77TQ4XCR997Sn+6n/yV1FSooTEIFmhQL7n6x2Ve28Ent8r47k7SHWz8t50u+1zoWvv0WRfDRjcasHe7529VYPA7jZW+6Xrim9+49v8yt/7VW5cv4XnuNRFQZEXBK5kuOEyHPYJwwDlWCwuWaZUlZ0LJ5XC8YPuyr7601652y6onVUoVjLYlYNOAKYJAHlOlmVNVuDi+bb0ybKMLEu4fuMmnueysbHBYDAgjuyQzNB3GcQh0+mUV89dp8gKgjDEGEldWewmTVOGwyFSOYwnhxwcHlKWJYN+n+985zs8/fTT/NJf+kt8/Wtf4+Jrl3Aam5TxbIIUR9mMUoosz7vO32w2I4qiLug6jkOv1+PWrVt3cKuEI5hM7Al++/btjgvlOA61rjG6xnEkRVF2nUKvkdO4rstkMulEzq1Upg1QcKdzROsKumppHDSDHtogZ43oBBcvXmQ2n3ZkV2OsYV9ZVkRhjEA0QdJ0jYKqqqxbSNNkCfwQmqZLK55unUNtlmkxRBtYtS3/5jO0qZhOF7iuQusCJ+7z8qsvMZmP6ff6OFKhjBVHyzY5kO9T4Lxdd1+N3+gxb3T7dXnRGzDGj4iERzIY+3z7b9Xw7kdhVY1w14KxGq0Nv/Nb/5r//h/+I6qyxlUueZqC1kSBz8ZGn/7QxXUlZZUynWXUNTiujxf08FzfcopE1Z1MbTmxWmrUVUVVZ7ZUaDAT0+INbekiBFJ4KOUR+D5RGGKAoigYTyckWQpSEMUxgzggSZbcuHGT5XLJ5sYGw+GAUb9HHAYM4pidzdM8+53nORgfMhiOMKUgzzKU65KkGevrG2g0k8mY2WLOjVs3cVyXbz/zDE89+SSf/smfJM9zLr7yKlVZsba+zny5oMgLtra32Nu9RZ7nbIxG7O/vMVpb6+gE/X6/c+k8c+YM3/ve97qs6mD/wGZF2kpqlKM6vV9e5KR5ihQ+Uigc5XZM+uFgSFEWYEC6gqqu8DxrEdxOLhYNhtYGLSEsQ7693ZaKLRfKstPtSK1lMqOqSurabsfFQdfWACRN0oYZ7yCEJfdWVU3gh03wc3jooYe4fu0aeZ6R5VmT+ZUddaNdRstm7p/umPNKScvH09bjXZclca/P3/rb/19+9md+jvtOnwUjOLFzElc51BgU95aivVuJwtvmSb1Z2dfpRt/ksa97zl237wyCLW9qBfdqftQ9/Kvej6sFU1vtl1KKyXTOP/iH/5AvfP4PMLVAaEGeZwhjGA57bKwPCEKXmpzZYkZZ2W6QdZyMbGknHVzHIQxNsy9s67vIbRbUWt+WVYU2Oa3kpbXTvfsQE7gILMCrmpLE9T0G/diSIIucyXhCXRYMhuv0ekOm0zFXr14jXaxx8sRxtjY3qaMeh4cLPvuZn+S5557n1YuXGI42QEqyPEdIhzCKOXHyJAg4PDjgcDzp5C8vvfwyWmt+7ud+js3ROpdeOc9iZvlSjnIJwxApbGBIlglbW1v4vR5ZlnVdPqUUWZYBEIZhZ5boeV6XhY+nY3tcSdHx0VzHRQjZnfxhaEmjjz/+OC+//DI3b9602Y6uyfO8CzhtZ3F15HqLQ4WhDSZtltqWpY7jkBdZE9w0eZ4CEsdxKUtNVQlAWlcKAWEQUFU1uhZN8KlxHOsOmixzhoMNkjShLA8pG5O7IIgpirwh22qKwqCty0yjxTRICY5yG7WALTXTNKFIU/7R//APUdLlJz71af5X/8l/SgkYXeMJhXoPK5e3bR/c/n733+wvcCdL/Ptv6173H/3QBChzdJvG4/xHJJNa/Zxaa3Z3d/nv/v7f5ytf/hqu61vnxqpCItjcWGNrY4DjwmKZkJY1Qjp4no8fhLh+AEgc3x78UipEmVDkWQfc1rX13jbYOW1teRIEcRcktTqyxe1+NOhaUxcFZVGQN6aDtTH0+n0Ggz5xFLGcJyxmM4yAzY1t0uWC8eGEqihBG86ePctouMXu7i6f+uQn8IOQl189TxANiKOYZZYzmUzxA4/777+fqqqYjMdIZc3eXMfh3KuvohyHH3v6xxiEMV/6ypcx0AWfNhPJi5zjx3c4nM85PDzEa3CvNE0Zj8cA7OzsYIzh8PYBUS9iY2ODa9evsb29jTaa8XTMzs4Oi+WCPC+aMsylqkrKsmRvb5/XXrNk1DzP8Ty3swtu8a2W9tB2WS37vu5M+pIk6YKoEDYoOo5Dni+RSiKltSVupxxHUY9HHj7NzZs3OTzYw3FdirzCcR08z2M0GjV4m3WM6PdH9HtDzp17Bc+LSJIlnudSlRqMxHE8jKmQkoaCAllakGUFjmNhgCiKybKcsrbZoKlqQBJFfW7u3mY8n1DVlgy8ORoROs4bHuc/7PWOyZz3vP8u0HyFAXbH4+8Fnd8duO6Iex1B9Aigl/L91907yoDvBPrb8mtvb4+/+Tf/Js9857uEYcxytkRXlmi5vr7OsWNrVGXCYrFAG4UUPaIoxAt8pBJ4gWu5OUpTmZR0kWIWecd9UkrhuQ14i0CbZlhAaeiHQ9upUkcjn1svJWOsj1RdlVR1RaU1tdGUdcV8Puf6tWsMRyNOnz7DsD+iF/eZjg9ZLuaEQYSrHKaTMRcuXAIjeeLJJ3n00Q9z/sIFPvuZn0I6Ls+/8BKj9Q2CIGCZpBweHhJFAfedPcsrWcZ0MmXPDwiCgKqsuHjxIkoLHn74YQ5nE27v3aYoCuazWYMd2cnFeZM1qqakUo6D1po0TTt/816vx3g8Jq9yVGPjG8qA0A+ZzqdkjZjYEkuhqsqu62gMvPLKq9bjKgzJ8oKqth5ccRyTJAlCiC5A2SkxNUEQdBnWYDCgKIqOEtG6IAhpqR9g/aiq0uA6LroyOMqjLDRSOPheYDEyxxI/19c3uX3rFk999CnOnz9PVVa8/PIrgCFLc8Igoj+wWZTjOBhtcF0P09BJsjzFaIPjNo6dddXgbg5lniOVIktSykpTlJrvPPccf/9XfoWirEEq/vp/+r/h1Pb20SEuGozq9en5D2W9zTHrd4LAr+/cNe4FHIHEr3ujnRXg93s9SetnejdAL4VVfr8fG3ym1nbspdCAPQCLsmQynvI3/u//DedevYDrBiznC6o6Y7QWsbU5IvBckmJGXdSY2sWPYlzPx/McXFcShwFKSvLckCcpeVlgtD1o/DDEcZuTVFqtmXKsJe7G5ibJIsMNfbSum2yqGfRqNBKJQSNrF1FJpHZxjaHIC7IsQ9Sa9cEQXdUc3N4ljvtEkc1I2uEItVCsbR3n4OCAly5epg4Nn/3Jn+KjH32El194iV/6uZ+imE44f/UG68dPkZU1k/GYfhyxubHBfafPcO7cOQ4PD4njGNd12T88sPiaq3jiYx/l+s0bXL16lcxJ8VyP6eGEUydPWfpGWeA0Qxla//LBYMCgZ99rsljiBJ6dpiIgjELm8zlSCgLX42BvHwS4gZ3s0jo9VFXFZDJtyqCKLMsJwwB8F0Pd+VP1elFjM5xRVSVhGFAUeeOuIBvrGJud2ZK0yaqMi64rlPJwlIukpioL8jrlpZe+Q5KkbG6OKMoltckpK02a1wQHsHVsnb2DqxiRMhhtM1g/ycWLF3GDCuVJtMgw0mZfWhugRvqGos4QCqR0kEJRVQVCaIoioRcNKLKIIjPoynpluTpAJzXPfvVbrI3W+MQnPkHoO+TGWiR7jocSK2Fk9dT+IQWptz0cdPX26v9H7+tet1d+BK/bzt0/q89+wzfe+Bx9v9LyvV2mY9CbzmbFsLe7x3/z3/w/eOG730MJh2y5RArN9uY6x48dI2jU+HlegnKI+gOCKG5cFuNuwECSJCTNyHEhBGEQ0B8MiHt2tHcYhni+h3IUBkN/MOiIjXmed9yzVsC76lklGsymzQiCMOi2ub6+zsbGBo6SZFnKeHxIkiwYDHrs7ByzeEZVsL6xRlHmXDh/keeee46trS0+8YlPMJ1O+cu//O+ztrbG+PCQjfV1AMaHdqrJxsYG6+vrZFnG7u5uZ5Vy6/Ytrt+4zu7eHj/7cz/HsWPHSBJLANXGdMZ2LeWgzSaDIOjsaHpxTOD7BH7QlYFFUdDv99nc3Oomy0gpLBZT5B0nSSnZaCAtwOz73lFnTcoOb/J9n8FgsIJ/CYzRzfAFyxC3w02tnXHnTdVkakpJHEdZ6xpjp8mUZYHve5RVK8vZpD/o0+vZ7G13d5fDpjv66vlX6cU9ZrM5w+EaAsF8tiRNUoq8pMjLRgNYdMdkm9FJqXCdAN+LSNMK66IqGoqMIMsT8jy1paKp8QOX+XxOVYEULnVtGiuad2+94+7evQLNGz3+zjt4Xex5fafgjYNOK2B+H4q1ARoGubW8KIuSg4N9/vbf+ts8/9wL9OM+s9kSSc3maI2t7XUQhjRd2vHdnk8QxPhBjHJcXN/Fcy3fJk+SRswriOO4ERErhON2Epe2fAuCoJGDLDtuTlna0sMar1Vdt6mjcEiBro/8pOraliytE0BLaiwb14TWDqXf73PixAn29vbIsozRcMQ8HfPd736PE1s7fOrHP8WPf+LH+fJXv8lf+eV/n7/1936VqsgYDgfMp1MmkwlhGHL69Gnm8zmz2YzJZGJLoqpmd2+vGwr6Uz/901y9cpXd3V36vR5CSXw/oBfHzKYz8jwnjSKqhh/Vdu4MoByHXi/u9o2UNuiUpc1uhPTRyfIOCkEbkBzHoaoUcRxT13bfRVHU0BnKrtxuRddpmiJQHRWgxQVbTK3tBLZ0EaDRHVreXJZZn3rf96irEt8PuguT5U5ZDHI8HjfvXfLVr34NJe32p9PZyvFgu3iycbb1fY8o8qkKjakNStomiUDZCsURpGnWTMYRHZbWcr6+/vWv841vfpvP/JmfwWjNJz/x45w8cfLocid+aAlUt97RmPV73f+Wt3OPj3BPwPyej+HI9E6+3xApu5QySGmnlKRpyt/9u3+P7zz7PHHUYzqe4kjF2VMn2NkaoauCZDEHY6kFYW+A44d4YYTfyDsWi4V1ptQ1cRxbr/HBgCAMcBouVNvJK4qiA3GFaB0NEm5cv47ruJ39SBzH3ajydny567gdt6rlFbmuS7/f74iKYRQRxRFhFDY4xpzxZIzjKnaOH7MnVV0x6I84HE/55ref5dbubeL+gMee+AhxL+LTn/okt29ew29A5DYwAWxsbGCMYTwek2UZZVlw69Ytrt+4QdbIZT75E5+iP+gzGAzY3dtj73Cf6WzWSVqqRpKimmELl157jcD3ybMMR9lr8mg0bNw3l13HzZIsHeq66rKfLEubKTo2K0rTpAPu24yspX4YYxo5jGiOA9vY8TwrVSmK4g5PrCAIcBwr7/G8lixqXRS0aQOYoKrLLvOtqoqDgwMmk0lTatqgtJgvyLKcLCtYLJaNI6jNBoqitFYwWncSF9d1GAz6DIcjgjDEcwOU9DHaBQMbG+s89tijOM4RDchm4BW3b9/CcXyypKIXD3n++RfvApBN9++Htd5WPnI3TeDNyrbV++7cyPcr8ZoHAasFbpsag73qS6HQq92p1mHhPVxHurejDKT9csqi4Fd+5Vf5+te+gef6TA8n9KKIE8eOMejFlEVGkWcoqfC8gMFgRBT2UMoBIUgz60I5m81wlGI4GBBFEb7nH8kzpKTI8+4gbnlSr732GsaYLsClWdYNq6zr6o5WebuttnMEMJtZTZvned1nc10X3/PwPBdjNEmaUJQFWZayu7uLUooTJ0/gBz5FUTMabnD9+k3+8I/+GOU6nDhxnLLI+Hf+nZ9nfdhnb9eSKVtLFYDNzc3OVXMymWCM5Wrt7e1x7fp1prMpDz70II888giub4PDpBkn1ZZ5tdbM53OWi2X3OQ8PD/F8y8xP07STsczn826Ipu2sCRxH4XkuQWAxvNbEz3WdhkDcuooeyWKKorBBPAzxPLc7poui6DJOoCFe0nUCt7Y26fWiRuqSYIzusjHT4LG9uNfRF1psrA16ZVl2msG25LIlo23iSKmsW4hUgHVUsDY8S+677zS9XkhdVeR5QZaW1CWcPXsWz3PJ84zpdNoYFIqOyhCGAY88/DAbGxsslymz2dyW29hOcGU0pa6oG8rLUVn7zs/Pt51J3cto7m7zuzct/3jj4LayxTs+VBeom19UY9ViVoLDn8RqD7oWZNWNE2ZRVfzL/+W3+MM/+GN8NyRPMkLf59jWOqNBRFmklFWJVJIojun1BrjKIwxC4jgkSRacP3+O6XRix0k1eEdLCqzrmrIoLYemOTlt69zppvkmSdKVaVpr6u4EUffc/0abLmjdvHmz81RSSnXBS2vdnaxHWYAtmcbjQ4QQHD++g1IeQjg4XsD3XnqZb3772/T6PZ766JNMDvb4+Z/9LEVTsriuay19G1/yjY0NAA4ODkjSBCNgmSyZTCdMZzOSNOXJpz5KXuQ4ni3l2vc3n1sjuxMnTrC2tkbdWPo6jtO0/2F9fR0pFSdOnKAsy84zve1OW6timqGgEXEcoRwFGDzfauOMPnKRABqawbLTDrZ4WPu67XenlC0Zjx8/bn2m0EgliKKQwaDf2CJDrxcRRQGu5yCk6AJR+397HnYiZ2gkQZaC0pbmqxl1VVobYyEEvu8xn0+Zzg5RDvi+gxCGH//ExxkOB5w9e4bbt2+xs7PDxsY6g8EA3/eaMjdEKsEXv/hHfO5zv8MXv/THTGczKm2odI3GWOqK1k2n80ie9K4HqbvXvTKmewWm17l3vsV15/PawNh0C9+gJHyvV8t5WVW5l0XNv/k3X+Wf//PfwBjFcpEgheTY1iajfoSpU4oqR7oeUW9AGPXxvZBef4CSgiJNSBYTQt9KQtoDUzZga1mVHZXAEhxV9/ptidFmI+3tu0vpO/+3v7cYxvXr11lbW2M0GlkAPQi6cghheTZRFHLixHHW1oYEgYfvuyTJksnEcpW2NneoKoPr+mgEX/vG1xlPDhkMewSey8ef+ihroxHL5ZL19XWSJGnA2Iq1tTXbkUsSprMZtdYkacp4MmFvb4/ZfM5gOORDjz5KVdf0+/3uM68SK5PUWvdmaUavGXFVlpaJfv36NeI47spegI2NTXzfw3FlhysqRyIkSGkZ2VmWUJZ55zMFdJlme7xWDWa32g1vM562EdFmj7Op7RzW2kpcjNF4nttkZqphs5ediqDVC7b6P6DJcj1c12/wRoOUDsZYkmhRVJRlTVnV2OuUzYpefOm7zOaHnD6zw9p6j4cePktVZyTpEq1r8jxjNBo0zrBl49desFjMcR3I0illlfLAA2dwPckymaGNJq8LaqBqcLh2rbpAvN31AwmM2/vfLPi0oGH7mHdaq3Y2F2LF6uVPOFC1QWoVCH31/CX+zv/v72NqW4q5jsf25jprwz5FvqSsMoTj4Pd6RGEfKV0CP0QKmMwmpOkcX2p62+tEvQ2UEp12zmiN6zh4vt/sB44mv3DEeI7jmL29Pcs5qirMHc2XOwO8jf2ik8Hs7e3x8Y9/vMsE2v3uebZrmBdZJ6mwV3RLrF0ul02HMmdzc5skSdjbu0kQuFy9fo3nvvscP/OZn+HxjzzKM99+hs9+9jP8s1//je7EXS6tG2iv12M4tJjRdDphuDZCNmWd32QlQgiefvppvvzlL2OaANv6nk8mE5aLBRjDaDQiWSZcvXKFWtjgk+c5eZ5z8+ZNRqMR0+mU06dPW08upSw+2GB3VVV1J1dbUssmYFiKiV1tILJBz6WsFLo+2smtv1fr7tk5K0jwPDtFZnd3DykUvh82RM+CMLSnZxv0gDvmAHYnvTnK7Fo94apjgxDCOodKqGvbOQxCl14UcXv3GqYGx5FcuPAKdTN4w/M8Xnvtte7ztVXD2toa58+/TFUt8X3I8hn/n//2/0mlDX/lP/gPOXP6LIeTW9Rlyc5wk8Fg0O2/9oLwdtcPHKS+399XM6K3E0mtGLbFfSxztnuJt5mVvZtrtTszHo/57/7er5BlBXVlUNJh0OszGgypqpQ8T/A9gT/ogxciHBfPDTEIZrMZVVGwPhxgdE5tpJ064turp2mEs45rdWHa6M5Xq9237T5p5SFteahrw2rWZNrBDC1fTVg95KVLlzhx4kQHxrer3a6jFMZzsSPWLXPZaUqhqnLJsoz9/V2kGnD8+AnSbEFRWrLjs888y1NPPEkYBPSiiKc/9jF+53O/z+HhIceOHSNN047B3dICkiRluVwSxzF5VjOdzYgPD3Fdl82NDT75yU9y/vyrzBYWQ2vLRqfXo8gL6spOivGcHtPFEtUIcuM45vDwABrLmsVigR9Yy2WhrVQkDH3KUjaNiFZGUiOFLXURkqLIuyy085TC0O/HJMscoJPntGX6qt+/co54VBan8rumhZSq+zxt1tQGnpY0emRsaJDN+DI7bstmMMboLoi7rkthKpSCIPBxHIOhwnEkRgoOJ7v4vqI/3OBwPLbZnZRsbGx0zqwAeZHxwveeI4p9PC/g5VdeIO4PUK7Pr/3zf0ZRlpRVzSd/7BOM/JjTp0/z2GOPddDDO1GKvOVyrza21jRCNGPj29v2p8aghcEIgxYaLTRGGKQjMdKgm39GvHn5d3R/63DoIHCxXoCWeiBEhcWX38NgZe76ae82VjBclCm//uv/lFdfvoI0AdkyZRSH7Gz1ESInLRJq10X21/CDHpHj0Qt9lKhYzg+o64xeP7QY1XCNMIoIXcFiOiFPEm7d2LWTcLVsnEslRgigDRh1A7zaYJYmGXXVBneJaQ6Q1moEjjA1ISBJ7RjvEyeON92lGiFrhLQArjE0jqhYVwbloDXUNfheTJpU3LxxQJrWpMspnqPYXN+iLkCKgJu3Dnjp3KsEg4DtM5tQZnzyySdxKkOZlWAUSZKTpDl+4+ddlQXJYtmp75fLJWmWskyW3N7b46Mfe4rR+jq9YECWFGRJQZGVpEmG47ogBVmRk1U5ju9Zp1CtEUrZCcRVRW0MeVWiHIcoCPAdh14Y4kg73qlsmOKu6yCass8KtzXQ2D0bQ20MOBI3DNBS0ht6DEYBcd8DWaOxAm9rmeNQVpBlFePDGYt5hucGlEWLbRrypiGilEtdgaN8MA5h0KeuBLpW1JXEUTFSeDiu9bAXkm7Qg5ACz3fRxlJiRJ3ju8oOhNWSsoQsrwmjXuPn1SdJJ2id4bkQBh6m1pRFie+GeE5EuqypCoEuJHlaIrUgmc2Rdc3h7V3GuwckkyVXL1/jY5/8cc4++ABGSjR0dtO6mV1o9FtLWt46JtWy3jteprjzpzuXzR3P0c2IJQSNTunONPSOl1jBuNoN2N9XrG1pxymJO+gM72nAalYrRK3rim9/+1v8i3/5L/A9lzRN6MUh21vrKIW94kpFbzAiiPoo5dGLY9CaZLlA64peL8L3fRzXRQhbYigJge+hpOT27V0m4ymu69lJueLIC72NmlLKZgy46K7sLVDeSjHgyL6j/QwgOP/qq5w8eQrPa1rxuqJl/Nv9S5PBAbR+Sg5SOly4cJGrV69x4sRJqrJmd/cWeZ6yvrbGaLiGEJI0zXnp5VeYL5dsHz9Gmiz5qZ/4NLqqKHLrtmkZ2w3x0fPAGJaLBbopPYuiYJkklFXFMlniuC5nz57l5ImTbG1uEfhBc3zJDsepqorFcsFiuQQEYWO+53oeWZ43OJuV1QgEVVFSFgWL2YL9vT372TmaTqTNkbGgMXRdNc/3QQiSNGU6nzGfz0jSJX7gsbY2ZDAc4AdNMFEgpKEqLV5Esz0Q1LW+o3Sz01U1RVl0nVnrZGDswFApG/mTWRmGYai19aSybgjWFUE2n1XXutP1lUXNZDLjytVr7O7tUeQFUgiWSztWSylJWZTdj9HaerbXGl3bScyOcljOF/ZnluAqj8l4ypWrV4l7PSvFWrEJErJJ599iZfW2untvdvvu++/VDfxB2pA20B155LwfRu9Y5nDF/t4+v/qr/4AoiimKJYKSnZ1N/NCKYGttiOIeUdBr2L2WUNiCxWEYNg6UVtVuD8iaoii5fPkyVVXx4IMP8tprr5EkSWNodmTBsbqf25JjMBgAEARBg/Esu++hLC343nYCx+MxZVVx9uwZi1k0/J/XLUM32l4phzRNeP7555nP5zz11EcpipxBMzZqsZjjeS6bm5sd2Hv58mscHBzieT7Hjm2xsbHG+saINEutW6iuLbWhKIiiiH6/3/lbtdhQW3rkec5yueTs2fvQTSfJEiXbwac0k4kjXNcy6ff397qA3XpCeZ5HlmVcv36dw8NDiqKknfJsO8jWNdU6F7idU4LneXiu3+xT0egfrcf4crEkTXOWy5SiKMmLgsViSpYtkLJGygrHORoY2o7TCgK/Y7nb0WQVUgmC0MXzBK4nyYslUmlGox5nzpyk1wuAGikFdrq0oCyLJpjVTbBubI5X+FytZ5glqlpyrgXhA5aLFN8LuXL5Gjdu3CSKIqI4wHEEUhkcR5BlCWm2JEnmzKbTrkQNw4hTJ8/wqU/+BPefvc8eNk2/q3WE1XX9uuTmzdZbPtNXg829eE53t7XvNmH7YWQ57Rbaq+Sf2GreSHsy/Nqv/To3b9yiKmvyfM7W9pDBICLN7VXfDyKiqI9SLq7y8TyfJEmalr7bCU8ttmN5MJ7vMxwOOHXqNFeuXOmwlMuXLx+9jbsyz7rW3Xs6c+YMDz/8MKdPn7Y4k9uOojJdW7gdJ56lKceOHTsCXN9g31rsSyClw82bt/jGN75FHEecPmPZ4q7rUJYFw2GfPE9J04R+v7cyvy7l6tWr1JVmOBwghOaBB+5vZs5Z8au9iFmxb6uhWy5tgHUc547hn4vFgtFo1JEa22kxxhiq7kQ8EmD7vt8x3Hu9Hll25JzZYjyu41LXmuViSZblFEXZVACqwZRs9mA5SAqlXLQ2FEVlA1xtMx2BQ13RBKslWZZQlClSaVwfhCrt8IRGBmPBdMHGxjo7O8fY3t5qRnBBnieUVQYNzBGELkLWJOkM5Vj8LAxtkyRNE376p3+KEydOdEErz/OmMWA5U2251U4ccl2PwWBIHPfw3IA4HlIUNe0cgTRNrMZPaqQ0lFWGUjRkTxqKhsVHn3rqaf7CX/gFPvPTP81wMGhkukdZk2hthd4G4fNtn+ldynZPPOn1j18lOr6VYPWmf2/+pJR8q0H4h7bM6j9zJLR+/vnv8vnPf4EwjJnPF/R7HltbQ2pTUJQFju8TRDFCOPiuVd63J5DjOI2MYYrWmizLOzay73lobdjZOcapk6e4desWx48fZ39/j+l0auUeRnfvzgYn3bHGfd/n6tWraK25cOFC5x7ZZhEtraDX67G+scH62jq64f84TZZxFASbY0xYg/4XX3yZr371a526HwyD4YDBcMDJU8cZrQ2ptR3z7fseg8GgA/fPn7+I1jAYDpgvZjz50ccxpraAt+t05ELPtZlce9VvwekW6J5MJo1fes3Ozs6dusMgQCrZmM7VzXiqkl6vx97eXtcFDcOoY+uvr6+zvr6B7weoxh6nxTaMFlSVxYeCIAQDWZaTJG2nzukkRI5yCIMIUJRlTbK0JawtPQuKKqPWOdoU9Pqh5ShJC2IjNI4rWCxnuJ5kY3PE1vY6W9vrnD59gs2tNeLYR4iaokyZzg6AGs9XDTPeDnEYDPoIYTpCquc5RFFImmQsFwnT6Zyq0tSVLftcx6MX9ynykvl82Vi7QJsh2oTA0OvFRLHfMNYHHQu/LC2b/vDwkG9+85t8/vNf4NatXRyp0HVFsliwv7fPuXPnSNIEhDUOfKs11Vvu7q0GmtXbd65Ot9Kt1cB0BNS+GWDe/v3ODM3W6DSM9eY98N6xEFptVl1XuK41HVssFvyTf/JPqCo7hdbSDdZwHZjNEmqjiYI+XhDgKMvY1lXJYj7Hcz3CZuSTEKwEGQ8llSV7NrjE8ePHKYqay5cvc2xnhwsXLjAcfoy6tjP7Wlav5/mkaca1a9e4/7772dnZQUrJ2vo6WZpxOD7gxIkTzXaPvgtrOCcp8jtLyPYEbBt9SZLw7He+w80bN3jk4UcYT8b4vt/QEQyuqxppiYPnOmSZ9WFfW1uzY8zrkr3dA9I0pe/HCGE4c+YUrqsoypyoF5OmKetrdvR3HPeYNVlTm3W2XcDlcslyuWQ+n/PAAw/wzDPfbljyFgqYzWdN9uSxvb3Nrd2DjvC6v7/PaG2I7/scHOx1tAYppS3AjCGKYpLM0i1cz8Ux9oKSVjloOwhEKkVVW796XWpc30VKh7KsqLISz3OgCRZh6OK4drJxntuhGcvlgjD0gSOawnK5aLqcBcbYrCkIPBbLOWVZNaW+RggLe1R1gRBOw7GyEqcLFy50JbEtd4+mTbf0h7aD67pupwUUQlAV8MlPfpJz584xGAyYTifNBU43Y+ehrjTLZULcs04dWZbj+wqDZrGYceLEMdbXhnzh87/PrVu3mUzGHBwekqYpv/zLv8x999/fibLVW8iTfqgTjC3Q+vbCxlspA9uHHAXK955+YHlZprE5sfX+V77yFV588SU8z2d8OObkyZNsrA3tEMmyIuoN6A0GGG1lJ44rWMwSlASnueI7jupM0tqTpS27DLaEU1I0gapgfHiIkMaeaKM+tuNpswx73xrb21sIYaen+H5gXR3rqns9y2y2F5T2c7VguNZVo7yXXdtcSZcrV67x/PPfxQ8CHnroYfb29vnwox9iZ2cHrevOJK4sc1xX4nquVeAXeTfxJcutg8Hu7X22HllntNYnrwyDYY+Dw8UdeInnel2ZWBRFh0u1YHiSJEynU+bzOQ+euR/XdXnllVd47LEPs1gsSJZL0iwhTR0ODvZ54KEPMZtNbTamNZPJBCHo5CzGGBbzJQcHBzb4VJowjDAG5rNlQ6iVBH6I7/pkjVtClmfN3ENrN5znBaoprZRy8TwHo2sW8xQh60Z6I5HKBtPJdGynLo/WKIqMutYEYcCyESdLZcvfOI6sSwaQpVak3Hpcua6DVFYcXNUF09mYIPRwHGnHppUanacNyC8azyzbBU6SrLG2GVKWFaNjIy5evMDW1gaf/vRP8u1vf5tLly41nDt7tdKVxvMj6gqiIMZxPBzHJc0KPE/x+S/8Hs8//ywHt252Pl/D0YjJZML//Ju/yWKx4NHHHuOv/PIvc/r4ie977v1AE4zvzqZaHs7q+qHKVszRJI73MotqXhwhjG2j1obZbMq//Jf/EhCNz1DM5uY2UljHRN/3ieIYKR2EEgSBR54n1JWdqOs0ZEhj6Jwm78gam7JSKQeMvdIeP36cMAzwA4fNzQ2UoqF0yA6rWVtbZ7FYEAYRi8WSKOrhSEVZFmxubtqg17F/j7qo2hgcx0VrMCte3UVRcO6VF7ly5RobG1soxyVNcz7+8R8njiNa+xfPczuNl+NIfN+hKEqSJGVry5r3LZdzsixnf/8A/VDFYNBjfzxjMOizfzjrnBqqytIqpJAdjyjLMobD4R3zBS3hc0pd15w8ebIBv8cdcAw0mj6PJEmYzeaEYcCsGR01Go2YTMad+LdqGgZtNlWWVrStGnmLVApdG5ZJyuOPf4SLly6CgDRLsfSfdpyYlTvZ6S/Wwrksc4QwKGUvDrZk8tjYWLOzDoOAwPgsFgvS1GZadv5fyWw2I4573bHS6w2asfJFI4QuyAvbFR0Oh0yb4araaFzpNheRuqGN2P3SSqhu377N+vp6s29CjKkJAsXlyxe7kVlWSuTge5H1QReAkdbfrKhIs5Qw1DiuIu4F1HXGcjmlKit0rVkkSw4PDzEC9g4OGAwH7O7t8hv/4jf5P/wX/+X3PfPeEZnzjTKpuwH7H7aublW39N4vG4BbEPYLX/gCr732Gr4fkKYFx7aPNSTKBGGgNxjgByEaiAKf2lSk6QLXsZhai6+0vCZL2LuTQNna/4LAaTyod3aO4biKui5xGt8osAzwY8d27DCAsrL2LnnGwcEBa6M1TDOzrSU02u9pheqxIupWypYs169f59Klyxzsjzl9+j6KoiSO+zz44P0NkC1p7Z2NqSlLbd+X206rUeR5ihCCILAYWJkWjMeTpoMX4syXHNve5vzFK90J1OrMpJL4vt9Z9bb7pWVdtyLh2WzG008/zbe+9a3msUXnyGmzLzr7Eq01vbjH7t5tpJTEcdw4LlQMen3qMLJzDJMER7ngCtLcTudZ3xiRZyVrJ9b5M3/mZ9k/OGDR2OGURQXSBkXRMMvb0VRgkMppLg41bhMg1tb6uK5qZEHTzjbG8xyWy5zx+ADP8wkC61NV5JZSsr+/TxBE9PsDkiRjsVjiNbjb7du3CMOw0W5KkmTZSKvAUREAg8EQISRhGBFFPdI0a44JyaAfsXdwgHIk4/EBxigmkylPPP4xtraOMR5PmE0WzGYzhDJUVcba2hppmoCpSbMlURSxu3eTellbM0KtkQ21hcZf33EdHn/iybd05r1jxvlbAc7bkuLu53y/bMu2LCUIO2UXFAIXIVwEDnZyxlvuYP5A68jdQFPrGoxgb++Q3/6tzxH4MUWe47uStVGEowqSpcZxYwI/RkmFFIrA85jPphaU9gIcz7UTerXl2FgQ3HaNTMMrk8J6ZtIwhssiYziIkAKEqQl9n6ouQZkGl6oIAp/r129QVhUHB2PLgSlmGG27aK08QSqr+hfYMfa1rlGO25QuDlWpuXTpCjdv3eL++x4gCgckScLDDz7MxvZmI0tq9orWKEdRayu9iMIeZV0hpf2eqqpuzNI8HNeBFGazObXRDSdMsLm5gWkm20hpcZ7a1DhK0e/3O8V/eyK1Yu66rhmPJyzShOM7O2xtb7F76xZZ4/qwSBZsbW/R68cs5wl5njUYKQx6fVzHQWAoRdm4UfikaYrn+SyTBOUohDCsbR4jzzOuXnsNgeTDjzzEP/7H/5CzZ8+SpnPbvcttSZ+kCabQKKFAW/KrcgRSGrRJ6Q967OzsWO6VkkynU2sXEwR40RHj3FEueV6SJiW5NEhpy+nR2hpR1CdNUxB2orH1JEu6hoi9QFkaSxzFeK6PNobSusHgeC5FXrC3v48RppkxaHA9j8V8ynDQ5+DgkDyv2dw8hjGS4XCd48dPcfXabY4fP8WZk5KP/djH+PrXv8J0Puag3iOIQmvFXAh85bNgRlUbgiBGSMcGciS60Nx36gyL2eQtnYM/NFlM86g7Hrcq1Tha5nXZ1t2PsZWIRIi6CVIGcFDCMs8tGdG87vXe7aV1hatCvvjFL7O/N8FzPfJsztkzxwh8ECYB4RL3hijpIQ24jiJPEsq8QGvBZLakrwWua0upOI47MLMtwYRQVt4g7WgPrUvLUVnlnOkaJQQV1idIN9NDqqpiPptTVYbJZIajXAb9GN/3mizQEv/aseqqOWlro5HNuO+XXn4ZVzo8+eTH7Nw16dCLewz6fYSC1QuPErJhvxtcx455Mlo2qn+b0dR1SdDITgDSNKMoSxzlWJFw3AMDVd7M6qOmNhphZEeYtGWqg1KWBlBVlmpRlCWz5YIH4oj1jQ3GhwdEOrQBSEqm8zl7431GcY8sTSmKgl6vZ8d21RpHOjjKIUsydK/fXZR0rZktp4RhwOHBHkHo24A1GnDt+ms88cSj7O3tk2cJnmutdquqwpOWzS6FQvo+vb5Hr+fh+gIhrFZjNr2FlIo43sBRHsYVZFmJMUU3ScaWd5KisPiR6/k4bkBRVMRxTNFMg7aZr+wcFpSyur9ez2+aDFaEnWU5nkfT6SxIs6UFr+M+rmu7wTdu3KTnOYhAEAYRo2FMWWnWRmsM19a4eesWG5ubbB/b4rEPfZhkueSxRx/nhRe+y9XXbrAx2mGtt4nWmjRbopRhuch44IEHSZKcyWRGv9/j6aefwlOKP/r9z/Pv/sIvfd/z7k+eEXmPJYS4swAxpqFatOXen8SkGBs8xuNDfv/3fo/A90jTBM9zGQ6HBEFAmuZNJycA0bo/uk2pYjWIYRiSF1bX1ZYfLT1gdXV0BwFVXTfdJNl2xaGRI9nxSRWOctC6ZjAYWD+l5YLhcEgYhYzWRhislAlpxcTKcVGOS22sPGSxSPjWN5/lm998hl7c5/HHn+jIhYNBj7gXIuWqBvCIrNue2Ku6rFYvBla/1oLgUspO5Nty6EajEUZrEEe2MW3ruxVXrxr6tfdbzE5xeHhIXVWcPn3GTrypa6q6JmrsfaWUJMuE2WzWdUKTJOnsf3u9nsWlyqLTmNmlKEtNEPRQMmBr8zhB0Gc+yzj3ykWuX79lQeiybuxrZNNdBOWA40Ach03Hs6auDWVpCIM+jhNweDhBa4PvB03H2pbFRVGyWCQNjmSHu7YeVMaYjr7Sip5VE9SUcm1nsbIYlNGW0yaEIs8t5qarkjLPqYoCU9dI7JTpXhQReC6u4xOGPX7mZ/4sP/mTP2l5boFDXWdsba/x0svPsXNii8ee/DA/8ZlPMlwf8NCHH+Ln/vzP8ed/4c9jlGGyGHPt5lWyLMf1HC5feY3JZMKZM6cJw4AgDPjSl/4Nh4fjt3TmvaMJxu1655yn15eAdz2zC1GmIYN1I+iFsB023mPgvGG8f/Nb3+bK1asEXkRR5OzsbHXeS2DtWRF2oKnvWzJilqW0E5e1sR2e1W7VvZZAdPhXWxYZcxf9zRyJhWUDjg8GA86cOcOxY8fx/YDJZMpgEDcnoM1M7GtajowQktdeu8Qr5y6xXBYMBn1Go/VO6ycdqzVrlA0rqNnKe72LPmJ5VUfKgDzP6ff7XeBqcTOLLVkrXqCxr1VHTRlzNNK85Ta1gbF1Im0Jnrdu3+bEyRNddjGfz9ACpKPwQw9HWy8pO4DBYl0ADzzwAIvFguVyiaMkRWnHsmtjiKMe6+sbSMchSzOKqqLMKxzpslhkFEXJ2bMPcPHSeUa9IVVVMJmMWd8YNsHO4nPLZIExddORS9jaOkae5WRZvsKhqhqJVd1ZztjZeR5llXU0gbq2QXtjY615XN589zVpkjdZZkXbxZPS5fBw0vG0xuPx0aj3wmJvURRycHCA1jVpmpPnFd/+9rO4rkOSLJnPp1TaymKCSLI/vsmv/fr/xI0bNzh37hw/9ZM/xS/8xb9og/sfaRxP2dHvTbDfPLZOkhTs7d1qDAczHn/8Izz77LNv6dR720FqtTx7q6XW3SXgvbuCqzXgPV+5k8bIpgx6N8PUvUD/Mq/43O/+HlIKqqpAORZPCQKfPF8SBFEzWtyC477vM5/PMEbbFLzfs1+cts6Kvu+zXC7p9Xqv25faWKO6lgGuj95Yx6608Vs2Ac3ypCwBdIcsy0iSJWtr67i+Y+U5lWa5tEBqmlpG9fXr19jb30cKnw9/+CM4SloOVxQ14LjCGFuyKU++Lkq12Uxr52EDoOiCSpuZrNqVtPhSa/LWBmuz8tm11nbyUBOwWppGqztsn98q62/fvs1DDz7YsMAlvX7MIk3IS0tfGIZxlzU5jsN0OuXw8NBa4DTUhzzPKSvbGYyjGNcPkMJhPkvo9wb0+7YDG/o+V65cQkrFxYsXkcoOcRDScP/9Z1kmC6IooigyFstZY67Xa8qwIRiHPEsxWpBlxYprQd3wl8B11R1Ta4zRzXsPuwGow+GQ2WzaKQ0sf69CCNXs59qO0nLsvg9ia/zXUi6SJKGuCjbWT9ggKaEXDKlrTRhHHB7us1jOmM+nFHVKHEcgBV/4w9/l9OmzbG5skVUp337+WxxM92026MDuwS4oQet1ZSk7JYWu+M//6v8WIQS/93uf62yjv996y0GqLU3gHkHl3Vji6HUtjC5xlNMc+A4tofPdXG1AblnzL774Mq+88gqe5zKbzhkNR7ie1aUtljWDXoxsPHs8L0DrmqLIiWKrzQObquuGCHr16lWMMZ0B22g06pwkk8SWkqtmYULYUk0KQdlQBFrqQFXppjxQIGyLe21thOt6FJX1Crc8oseIooirVw87iY0U1sI4SVI21kfs7OzgqNaGpbIMdPQdFJC2bIIjVcFqx9KeNCsZYPP3NlDVtWWZ37h50zYMaAmkBqOrLuitPn+VVtBmG0VRWLeC0kpSer0e0+mEsirIihyNsT7hfoAQosumhBCcOnWKg4ODJtu1ndDhaMBwOAQESZbjurabePr0Gcqq5MUXX2S5mLK+NsJUNb7vkuVLlOPT7/dYLO0gid3dWxRFTtyLCIKALLNaPs8NydMZSZJRm4LWTtv3/W6fteLwtpyzSgDd+HVZhnw7ecbSV1w2N4+zv7fPcpkzGAwJw4jd3T2bpTaWOtvbNvtqB3Ssr69332dVVWxsbFBlmizPObh2hbLKMWiGwx5+oAgjB41uJEFw7fprHDu2SVmWfPuZb6FrjRCW1xYGIW4QdN1XC+L3kMqwv7ffaAvf2nn4thjnPxT9nRDfP8CIleZ42yAU3Z8aMue7m0ndzZKvqoqvfu3rlKUdYZ3nKesbZwkCHykFgR+glNu9Z+uwmCOV7EYiWR6QZTCfPn2a++67jyzLmM/nTCYTDg4OAIjjmLP3nUVK62PejuxucSopBJ7vs1gu2N+3J5kd0GDN4l544QXOnj3LcDiwangJW9tbfOe551COw/deeolbN28ihMR1PO67/zRKOVw4f5FjxzZQSiIlTRZlEBik0MBRgGkvWqu+3VYUXXQHPtAJWA8ODphOpx221JZrv/kb/4Kf/3P/zgrvztxh5NcGqDYgrnoyGXPk9R02Bn8bGxsURU5/0Of23m2ywjodSCE7UNoq/NfY3NxESsmNGzcQQjCZTOg3AumqqvEaUbJyHL79zNf57J/5M/zyX/lL/OEffJ40WeAIGI/HRHFIVRVIGTOdjjkcH+J7IdpAmqRdQLfDJyR5aVULoWdpAwirifS8gLKsmy5dbB1Ai7r5HkQj4bFE3KpRJPT6PYqiZDods0zmRHFAUWYUZU4YeoShjzGCILDTstM0pa5qK5mpazsRJk2Joog0SXCEg5Q1xpQURUYYB0SRjx9aVUGR5whq0uWC2WRCmmbM5wukcDHaui6EXgDasFjx8FJKkRcpn/vcv2Y2XTSj5N/aKKwfaILxOwlaLcb0Rtu/43bHMxCNPUYDnL8D46y3u1av4lJKZrMZ3/j6N/E8nzzPCKOgsVexGEvLA6pq3Yg5ZYcD2S+qHZOkcJXVhbXjp3q9XnNyFQ2eYE/uWluiXGvEb/2erKxlOply48YNTp86S5ZnvPrqeT7ykY90bpy9Xq8pm2qMhKLM0Ubzta9/vQkkCtfxuf+BBxmNRownhzz40H289NILxLHPzvaWDUS1Y+1CMBYgdvUdGXV7FU6ShMPDQ/I8Z+fESaqq6sqpOI47AXPrZY4QeK7Hz/zMZztAmKZBshqE2qB0JNM5kmW1gXGxXLK1sWE5Rr7V/LmNoFopRVEVlA1tYblcdhmKxa+O9IzJcs5isWS0NsJxHPrDAYeH+zgObG5tcv3GJUYjn9FawGBojeeyfIrrWrHtbD7FoPF9D2GU1SFmdiLwcDiwoHhe4yibRWhsyRo3bhTLpWW2u5FLlmbNxcCxU41N3TlftOdBEATMZzPrIRUptrbXWcyXlI2LhlIOgXFxXI+iSCnzugvURTPYwbo5uE0ZGJAuFkhlGK312DmxSa1rFosZs9kUKSVRL0Yi2du9jaNclJA40qUsKlzHp5YGtHXjiHsRcRxSlgVh6OM0/vg3b92kyOu33AB7R3P3ftgkzXu8yh0BymIw3RtANR2qd7PgvFur+L3vfY+bN2/RiyMmE1sWWTazT1Uc+VDrsiRqRj61gt8OT6NhlpvWTeAIc2mtettZdnVds0yXvPjii5w9e5bt7WPsHxxw8bVLPHD/A1y6/Br333c/URQzGA557ZLtoFiZilXU17UlQOZFxcVLl6DRCCrHod8bsrW5zdr6BoeHYzbW1xkMIpbLGS+//CKB91FGo1HTwJAo6VKUJUk2Z7FYMB6P7ejyZuho2wLv9XrNEErr6mh5R1bi0o7Yau2kPd/j8See4NwrF+1X2yjk9V3Z0urxtopRtb/ruu7ex86xHSbjMVobgjCkqEpqLNYjm6EPbRma5zn7+/vddns9m0V5nmdFzNNDEBpkxYmTWyzThO+++AxoWz6HYcj2sTWKwmY38/kcpeyAinQJjoJer89w2CMMvaarmVHXUBYVQRgyHA6Zz+fdsSZE6waqGpwsxfW8xmtd4ft+o6GzU3Ac17q25kVCUVp3AUSF57lEcUzgexweju3QDKmgGVgqBfR7sX1NoCoKxpMxus4ZjAa4vtUazsdTirLoMMWyLAkch7qsMSgUgrooCb0IpdxGx6oZDdaodEEYhmxsrhEEHrdu3eTGjWscP75DHI24dPHyWzoX31a5t3pStV/s93vO3cuWe+p1j2tTfRANYRF7eyU+WZKj6OaHvZtLSmlBx6Yb9Y1vftOm3Mbyl6IwIAo84igiFxm1NpSl7Va5rkeaLrtOlPU4Kul2R1fOtmO67B9aAWybMYRRj1qDH0RkeUGWF5w+fZqyqpnNFgyGI6gFVWOc5nm+vXI3AlIp7eSXS1eusb+/j9bW0rjf6xFFMa6ryLMEJQ29XoDnKZ584nH6vR5G0/C0sNQAI5gvlrx8/lwzSSVmtG7xiCxNyfOc6WxBUdZsHztOWZWEQUiyTJtEzE5cLuLIjo537MmFgdli0WFVzV6hruom7TYNuC5px8O3YHKLyRggLwqquqI/HLBY2myi0hV1VdELraGgbd+nNqg6irwpTR3XaQL1CCEF88UCrWuorNVu3Ivs5OaDfWbzQ6DoCJ+6tsesMRAEIWmaWOG3Us2cwgBtNJPprJtSraQLCIqyoEU+bBmaEEURjuM2ti9YD6tmLp8d0+52dI7hcEBVVwhheW9aaztD0XUsFlkUSBkQRQFKCYo0JQxCTF0jtGY2maBrzc7ODsvFgjxJUa6myFMoBaSGMPapapt1CamQjktaFXjS6RxKXcdjNBxRFBWuA3Go2N7e5sbuTWbTRTNJSLNYLplNl/R6Q/q9lKd/7Km3dC6+LeAc3h429XYeZ5nWR5iV0KZhcd3ZdpeOspM1Otbzu7dc13ZXDg8PeeG738Nxrd2F40j6kU/sO/jKgO+R5TVFbSyz2rGyEiWPKAZ1rbvOlNEa2QVqc0fQt04Ciro2mEpQF4bFNCFzCnRpiIO+7ZZJjyrX+H7A4aGVT2ysbzIeH1IWpSUa5jnXrl1jPi6gdhn2Y7a2NghDj7gXNNYbAa4rAYlAETo+aEuhoHFKMMbYkVhK4Pg9q4Nb2quz6zjgBLjSR/k2c/Q8D1e7JIsUXUEvGoKGjfUN6qog8B0kYCrr0z6ZTa39tITK1CipENpgat1xpFpnUWMq7Gy61i3zqNNXa43r+5S6RjiKSDq4bh9HCpZ5Sn8woKhK4jBkfXOTa9euoYWdbNIb9Dl19gyXL79GVVsp0tlTZ7l27SrJskAYxdbGMZJkTlHlzOcpaVrhqMBeS4XVsmWZthchJ8HxY8aTXYRwEMLBabynHGVJt9KpyfIlBkNetJm3w2KRgBEI4eB6qiHiOrRB2XGasWZN88T3fKrSAvzpMqHX6xOHEXVZUuQp/V7IfDZn0O9TFKUl5QrRuClYPeJ8OmcwGKHcgsEwYraYUBv7WebJBMeNiIKYOB6yu3sb4/soYDKb4yqfvfEBujacOX2Grc0tXj33KmVtj+l+3zp8FrlhuUyxU21Knv3OV4D/4/c9D9+2VcsPu6u3ut2OTf1G5aQ4en3zHjGlpJRcvnyZvb09PLfHLJkR+A5B46aplIOsquZAFZ3pmhAW9G5lGK3P05Hd610fbQX/aj9rVRX4vsuJEzvNIMxDrl69zEMPPcTW1iYvvfQ91jfWKPKCRx/7MJZ9rLjvvvtJlhl7e3tMJ3PQDqdOnWJjcwPPU0SRFSlb7MyWc7IhE97rPa3e9hxF5VgNWrpcUDoOcS9mNBgwHA1xlLL2xY5itLaG43hN+Vt3Znr9fq/hT1mB7GxmpTtK2q5dO5l51berBeqNMR1uZ9/TEZk0SRK8ZmjocjFn0O/Z8V6zKcpxOifUtpy2ALkF8IMgYGdnh2vXrlKWRdNxjTDY0vnixYucPHmCNEnJq4Kq1BhjPyuN3fPe/gFSGnzftc4AykOIAmMknuuS5xW6NqRVhuNYTCsIfDzP6fyd2otWnuco6WCEQ5olTfB3G9DcdiOFhKpaEAZ2yGccW0cCu18NjmPxueUytbddjzTLWSYJy+WS4XBIUSRYJ1JNb9CjrBcskhQjJEiDUILNYxsgFEEUoXXN2nofoSUKhyAsoZZUlWZrY5utrW3SJKHX6/HUj32CjY115vMZv/u7/5owipjNZ6Sp5Xb1ev23dA6+o+7eu0E/uJMn9Ubbf/PBoz/M1bbRpZQ899xz1mXSjS1mFMedYZzv+yRZSStp8Zry0L5bmoOq6sBmrWvuFQza1+w84DHdcMXWgXJnZ6dzpXzkkUfsJBJh1e9SKqqq5vr161y9ep0kSQn8kLW1LXa2dxpDOIcg8Agje2LQnIC2W3qnZ/y9ljGaKPY4e9+pzjSvDb4tRrRYLKjzHCFcy7xuBonWdYUUBkPdyDcUWZ6jkezv73cBPS8KS750LPC8Op159btph222Uptu5p4x9Ho9jLaTjIfDgdX/mZqDgyNPqb29vY7BXjWuDxcvXrJZvLCfVSrbpU0Sy5C/ceMmQRBTJTVu4OL7IVK4trslLUXG813iOESbgjQtESjrS19qXMcnCv1G7KyQyqcoKrxmOELLFm+/T9vSlzjKxaApy6ojAgthnUaN5g5f9CiKGI/Hd1j/WBKttbIuy5K1tbWGqjFtXDvtPlwmc/zIsb77VEjHkCc5m8c2WaYZST6xFjOui84MWV6ipCQMe6RJie8H/Af/wX/IP/mf/nG3/SDwuHTpEo888iHOnz9HHPdYLOYoJbl+/cZbOhd/IMb5D2O1QefOq6aAe3Qn2xT/vXxfdV3z4osvdmxgmva/o5xmzppPfTDpruaO45An6R16PK2PPoxt6d9LnC26k8/yoQxB6PP4E48TxzGu5zBaG7G1tYlUNt0PQg9DiXUgKClLzZUrV/C8ACkrqsqwvbWD73sEgWen4roOypFNcGpGhwsDph0G8Mar34vZ2Fy3XbXGSUFQo1dY06HvkFYFSrWZobVxmc8t6VBKSdxrpywvUW7A3t5et0eqsoQwRApJ3nSpVtnrLX2hBb/bn9aDK8tzfN8n81zyTDKbzYkCn/VNywmaTqf4vs/Nmzfv4CUJIbpO5GIxI4x8zp17icVy0XxvtqQMo5A8q/E8RZqmzOcHtIMvHMchTVOM0QwG9sTNsgrPs/rHhx56BBCcP3+hmerblK5UXaeyVQSEodt8VtvosF1UywtrL552lp2P1Tdqy72qbQbVYnDLpXVDKIqCzPGJ4gjpqI5h7viOFTiHIUZoiqpCKIdksSDqB3iBT1qkeKGkVhVFmeLLHklakCc1RWZw1yxovrd3wK/+yj9gd/cWnuuwP57w6qv2vHn44YdxHJf5fI7vhTjNOK+3st4WBeH7ZTH3+ts76gSaI+KiBZlFd58NYk6DmfCuVXxt0JxMJly/fh3HdboMyY7NVkRR3LDPK4yxujrHtfoppSx2JpoOZTtE02LBR2PN28DcZiJtJuUoh17P8q7aNrzrWlC9Kqqu/BHSgvVVVXH79h55nlMUFRhJGEW4rk+vHxAEPr7vdS6NbfPUGLrRQqsHzd1luB1aYLMj0DjqqDy1E0hKfM/tLEKsTUtpB2D6LvlBjjE1YRjgeR5VVVLkBY5QHfO4rMquFK617ixX7vAub7KeuzWDrZVLy0uqmla7lNKSNxtLlJbO0Wa21pvd5Rd/8Rc5duwYn//877NczlksZhhqqipDKQtcf+pTP8Hu3j67e3sIYbG3wcBmKUZrhqMhe3t7VFVJXZuGAa4py5paGLa3txux9CskyRI7905htXUlLVO8PfYsx8zq8IqixHUVUthGjC2XS6LIaRolR0Tb9vO1BFGttfUwD2OSJCHLc5TjMIj77O7eQirJ+sbQUlsWCxxHUdWNB7pjMIWmQuN4gt4wwjc9dLrEVAVrww3KDJJlSl1pXn75FXpxQFUW1Ejuu+8+Xn31VV555RXm8wVKuV2G98YV053rbQepu++71+PuPtC/32PuxrtM09Hpni2Ofum6QO+RcO/69evMZjPsdBRbHriOg9PMYisK27WzWIrbnbhS3nmVj+OwCUYG1QTg1Qwyy7LuRGxLnLb1Y3V/R1mmUpYo6nouuq7JspwXXniRJMk4c+YM16/fJIxidnZ2iOOQIHDxfRe3nc32ugj//S8+9qRRXRtj9bvtpDFaWw+sZs6bMboBfXXD3bFj1KW0wSFJU3RWNC6Urc9VG8w1RVF2Y+bbQN5eKI6yVFuWi4a+UVVlM1QzYzjoMRgMmByWHBweMp/P6ff7zGazO7Ky9fV1zp07x6VLlyxAr0uEsETIIHCYzezI+s3NLW7evE0U9qjqgs3NDTY21rhw8TxlUbF/cJs0TRr6QIUx0O/3mU5mbG9v8cyz32I6maIcZd05ZWCDVmUoiwrft+Jia1Htdhm1HXFmpVX2+HObrp5stH+2AaFrux2MVWUUeYmjbEaWJCmObLrHRjcj5AX9YZ8g8JuZgiVKCoq8QAlFVRl6bkB/EGJkgRYFVZmjyDm2s8munpAsEoQOieM+w/4QhCHL5gS+x8FkxrPPPksURfh+wNraRkOzKYnCiNls+pbOwbfV3Xu3wPPXr3sEv+Y+e3V89yNUe7JcvnyZPM8ZjWIm0yme66IchzAIiKKIPJ80IHdF3Isb0DNrZug55LmdYNta9rbBt92faWqn9LYq9460qORdfc2jjMp2Ae3Qgtu397l48QKbm9ucONHn8GAMGPqDmOMntnBdDz+QeK66Y7+9nQT3yBXgHriVFkhUw/0yYGRj/AY0ZnxpmlDrmixPOXV6B9d1WCwWKCW5ceMmeVHg+j2MNg2Fw05sKRoMpS3HWkb7Kj7aZqBtNpU35ZA1xLO4nu+5eMo+Po5jJpMJrRuq7/v8zM/8DJcvX2Y+WxD3QjY2NkjSKXVdkKQJYRggpc/nP/95ytL6Y/V6EadOH+fKlUs4LkfTanwHXRuqygbXsswJI5/x5IDBoI/n20y5dgHj4PteI/PJ0NrQC0LKyn7Gra0NkrSw3T6saNh+Vg+E6KQxRW6xODvt2ulAecvZsgZ4ruMyXyyoqpLR2ghbmhg2Nm231/LqapLlLmVRkOc55AZHCXq9kFoYaio836EuS+bJhMGgz3I+w/d8Hv/Ix9hYWyfNlpw8sc3LL7/I7f1nGY2sxAgMGxsbPPLwhxmNRjzzzDMdsP/91tvKpO5Fqnsrz3u7f2/Lu3ut1mnRnunf9+Xf8Wqv0JcuXeoym7IoCPwQx3HwfB/f9ynLosuG3EYC0qbcRVk0+jc6axJjLLdkMV+wu7trsaUgYGtrq8sS7UloH3vHfhHtYFTr/Hj+/HkWi5SHH/pww68yjRbNDvb0PIWQpvHUbigbDe/J1G/+3bXBsg0OLZYm7trpXScTgTZtU8B0uEkQ+Jas2GQ9lgekmI7nBH7AK6+c60p5663uNRy1vBvA0M4HbL3OV3212sDlN8aBrei4dToQTU07nU07SkmbjQVBQFmWvPbaa5w8eZKr9TWOHdtmNj+gKDKq2hCGAVlaUJUFZQmu67Oxsc54vM/5868wm4/Z2Bixvn6CxSKhrgxZVjCbWueLDjuT1s9cCmt2d2xnkyJzyNLc3i9VQyJd4no2c6qqiuFwxGJhu3Or49YDJ8CgG2G5LTdbCdKqjUubieomQ3ddj83NDbIsAaGZz6fM5xrlCPI8Q1eSOAgoMttdzJOCycEMPxIIx5DVOVQVvbDH4e6EkydPU6TWhSHLrAvHs88+y7Vrl4njuPNVv//+B/iLf/GXGA5G/PZv/w5aQxjGb+lcfNvl3vfnSa0GsqMrdvuUe8ti3mB74vV/b8dZvXuc9yN8Jssyrl27jhCWCb3aRXEaUzVb7tlSYzyesL4x6AYtBkFAlqbNXDLN7u4u+/t71FXNaDhia2u7C3R3t9yN0XekO215CIbJZMzLL7/C2toaj3/kya6zJZUgbxTyta7xfLfhOlndXcsifb3lSsPsvxfGJ+4cS/a6TMocdTG1thi8cm3AbDG5xWJB3fg7tV7uWZ4RBg4vv/xyU/64pHlJENh2fr7ixtl2n1rOVBAERy9vjkrPdshlGIYkywXL5cJa5UpBWRRIpagbEbZu5s71epY7BDAarnF4OO6woH5oXyeMQrLEBsMwDO0IMmMdTre3N5gvpswXM5R02do6hhQOYTAjSVPiKCKKIxaLOUVZUOS2rO8PYoKNTZaLlMl0gh3qWXXNIa01h4djgqRonBrsvq/qCoHBNFIrqxEtwIBSdloNxpCmuR3QIJS13sGQuzlJsuTcq6+iTc2xY5ssl3Ncz6FKCoaDvnXx0NCLe3i+R9gP2R/fZjoeE0QSLezI9TgKGd2/w9rwDNcvH5AkSy6/dom6LnjowbOWYNsMbDUI1tZGPP/cc/z4Jz7J8RPHGQxGXLly5S2dkW97WswqDeHuTOr1satlkUN7Ilg/7Lsfd+cpY4xpavGmHseh1qIhR1rwWcgaeLc0fPZ917VmfDhD4KMrZYW2xnpw+75vFfZGU+qaEs3G+ojFYkaWFY0ezILoRV5x9epVwF49Qt8lTSqmkz2MqTFoHnzw/k7LJCXU2oCxt7W2pLq61ly/fo3bt3e578wDrK2N0E3543sOeVlT1QKNIPAs2U4YrKOpOQpS1l/u6MsSQiAbp4kOc1r5v6wLaq0J/RBTtxlWA1q7kjzLUK4krRNqofGcGJ2XjWAWqgrKsmZrcwvPkSSzKUmxZJnnHE6m6Nqz+9cIpBOQ1hWTbEZFSTsqS+u6EWjboGtMTV2X1LVDXZfkRUpRZuRZSpYlSGnj82Ix4+TxHULfwXH8Zn/45DU8+qGP8MBDD/DHf/zHSOcW/8X/7n/Pb/7mbzAezxGmR5ZCP47QlcYxmhNbW/z/qfvvIMuy+74T/Jxz/fMvfVZl+a6qdmi0QTcAkoBIAAJIDockSIpWlETtjrTaWY5mJcUqJtbFbszEasiVNNKQK8qSKynoQYoEQAJEwzQ82qB9ddkumz7z+evN2T/OvS+zqqvR1WA3yD0R2V2Z+fK9++6753d/5mv+j//gH/LEl5/g4sULhNGEIk/I4og8S2l22/ijmIOH5vjhH/+vOX/+PM8++yzbvXUdxEVOXIRkWcKiN8+pE8d5+aUzGIYqS1oddKMwQVtUOfgTf2qProoCoUAg0Um2JEsUFKY281QO999/PzeuX8d1OtiOTeD7CGXz2KOP8PQ3vkxOCtIGaZD4Jv7AoKBAFZLRbsihZRtpFLQ6Bkk2RKYhppkzO7NAvx9g23Um/ja1wy7t2kGW5u9i48aYV6+8gDRjFhbmePq5r1DkJtKwsR0TRMrnn/hjms0G7RmDd7zjAVZv7LC6ev2OduO3BUF4fbzUrdLAt/5l1dPa/5jbUGdu/6pTMOfb2xLbO8YkSRgMdHMvL9NWUTbFgWnjNitTa8d1yBNdjhZFznDYp93uIASlwL6ertVrTdyyXHRcC5QiTiIKpeV8dcW016CuSpQLFy5gmianT5/WqpJZVk7STAolCRMfhS6z6vUGwLSBr9/T/sHELUMQFJCXxdreudaI+wEvvPgi3ZkZ7jp+11TiQwhdThimoRn1QkzF/RR6CrqzvYsUulTudjr6Zzs7SGnyyisXyPIc09aNYG1WIIniiCRNQOlyU1uhh1T675XCgsafac/D3NZ9KNuxqdV0U7ZZmiz0+j0MqTlrntdgNNrl0OEjJGnEvffdjSLh8c8+zvXVS5w6fZT1jVepNWySOCTNYhzLJUszjh07wo3VK1x69SyWbTGe5IRBhCEspKldjlcOHWA0HjLYHXDh7HmyJCP2I62uKSSdZgfbttjd2uUzlz+NPwlQKkdIgyxNsEpTWEOaCEkpPqilXJIkpVA5aQn5qJQFut1Z5ueW8DyPtbUb+MGE++67H9u2GQwGbG5u8uWvfBmLlEJpvalWo06carBwr6+99drdLnGSYdsQRSlJltAfDXC9Gm3XxbEVhrSx611cp861a9d45qlznD59isfe/RBnzj7L5cuXEcrDcepkKUShT62uhydJXPDsN1/kTz/5BVy7xaOPvfeOduRbrMz5rdUNbtd4f93S8ZanEmWNt7cJ1Ns64NMgSl9jecqmbFXmGRWWqQxSlNgW07SmtkJZluF53rRUOn36VEm+1Q10VeTTjZ7lGaYlKQqtzqhLGD26fvbZZ6fN44MHD7K4uLiHFTJNpMqRhklWaDxW1UdqtrSQnlH1b97onFdloQCQ07MbxSlbm7t4bp00yfnyl75CvVHj1KlTLC8vlgqXquy5mSiVU5S9j6LICYIJUgo8zykzBS221pld5MWXz6DQon3a309iGILA1w1zshzP0sOEMAynwXq/RIxSugz0XGd6Xip2v+d5tFotJuMhrusRJwmDQa/EjDksLM5w+MgSo8kmP/rj388n//T3tO6XDHE8zYUM/ADTlHh1m/MXzpIWPrabY1sOpmnwox/9CZ579jm2t9dRQqtPhtGET37iEyVXL8aQkjRJsL0aRZYzjiINQRE13WeLI1zP1Qh2odVdK9yZJqorpNTnWQ8iwmmgdhyHY8eOkmcFV668yvHjxzBNydWrl7nv/vswTUmrVceQiq31q/q9eB5R4hMEEVIauJ5FmqQolTLxM5zUIC1y8iIhV9BseviTmJUDh7ly5QYz3RZXL68jqPHe736IjY1VtvvbSKlYXFzClG3CQBGFKUePHWEy6bO1tU6WRnztq0/TbMzw3/3iL3Do0NE72ovfMTDnm8FLVQHpNT+Dm7KYtxuGMBgMygBh6QKwJDhLscfEr0bzZl4pEWq6ieu5WKZJGEUIBZat3VhkCSNQZBTTfk6hXXyTGO1Gq/s5Vy5cKu2LXJaXl5mbm5s25q1SXsNQCsVer8y2bSzToN1qTUsyDdX61rQj/dj9aHhJUSgG/WEJCHTY2dmZZkMvvvAiTz/9FIcPH+Lw4UNT41HLskgyhe0YjCdjhNROJnNzHRCq1MwSbO/scv3GmjbVLHLdKzMEWZqSxBGiUBR5gVN3StncvLR0Zyqlq30BYwzDKnFZMYEf0O/3tRRwUkmW6N+laarBmoFPmkW8evkcf/THv8to3GO3v00Q+mztBji2zW5vB4Fgfm6eLM1pd2ZYWlzm7ntP8PkvfoqNjQ1O3fVOTt11N70dLXS3trFGp+uQFzFCeRRpThxEGrJiu8zPzBInCVEIwhQIw6XTaSOE1u6qHLKl1E1snZkKQE71o3QZWEFdRCn9q/FxtbrN1Wuvlk7ONnke89i7H+aLX/wiq2vXIAtp19tM/CFJmmHZtlaYNUBZkjgJcEyPOC3IigKv7mHIgtEgZG5ukWNHT7C+us1dx+9mOOxz/foNvvzVx1lenifLfIRQOHaNMMjJ0oKl5Xn6/W12e9tkWYzMJY1Gk0azxvkL51AI7r3/2Bvuw+9YkHqjaeDNtBhe0xyvfq8bzN8ZGMR4PC4vchtZTruKfdicJNHKioZpIpIUTaXQ+BPDkORFJVim9gTkhEAVKYhian6piZ43l9GaniGmY/KlpaXp9KaSzbBME/KYTGnTUsvSvLxWs0mtXkPl6TRQ3fTObnvutLidnmsoVKEIAp/t7W3yXDEYDpjpzuHYku3tbUzTYn5+nsFghOvucNddJ6Y9FaV0phuGPtIQJGmI6y6UllvXaTUbvPLKBaJYK0zmWYZh6uOP45A0iUu1izLolVO+NE21NneqsVDVxM8wLIRYnsrCVIMMx7YYDAa0W41SVljfCKRQpGnEcLzLmTMvYNoK0xa4NUGcZsRpguVIigzd1JOK0WRAd6bFy2deIE01WPK+++4nihMsy8H3A4qiYDwZYxgFIgchJDXXK006QhzbIYkTVMmVm4z7VEaoWgffmIojVmYL+novpkGpmt5pwLCegl67dhXbtlhZWWEyGeH7eniwunqDl19+kY2NDbI0wSTHD7T9umlrh+N2u0VSgmMN08LAIU5ihNBl5mg0KOVg4Itf+CK93T7bS8s0Gh6eZ3Pj0gXG/jr1WoNWU5vPpmlGGAWsb/QJowDHs6gbWtq6KEJqdXj2ua+QFz7f/wPf+4Y78dsGc77pzOhNrwqTUzmH6J9WY9i3O0jpCz2mUhHV2tF74MdqI1R6PEWp4iBFdczFVOa26p1UVAbTEBTF3uP2XlODPXWTNGd5eZlWq0Wj0cB13ZIGYU/7EQiN95SlYIRhaL2hhYV53RdTCsM0NeSAb00S16KC+gmFEOW4P2Y0GukpWbOBaRqaaG3btNstBoMhUgqOHj1WKjSOWFpa0hPLJCHLEiaTMbNzHQqVMZlol2LDMHn5zFkQpn6/SmEKkEIRhaEOlrkmGgNT3FOFODcMo6SfaFR3s9nCsrRuue3YGgvV7+GVJHBVZPT7PQqlP0fbsUEU2skni1ACojRBGALTtnRDvFBYjsPObg/XcQmLgI0ti9FoSL1eZ2lxge3tHZ5+8gX6/T6j8QDHsYmSCCFyTGFR5AkKbeFlGAbb21q7qjJLSNOMOE6me0uL/xUlhy/blz2p6YRTS0pXgn4ai1Mpv66vr0/hGZPJhAsXzk9hGa7rsrJ0gH6JEdOuyZqa0mg0tM9eMqTmdQGB45j0dnvkeYZhWDi2S2rnLC3OM+j3CcIR7U6NlUOLpGlEECSowicKxiglGU+G2G5OreZx4sQR4jhiONSyyTu9a4Dka09u89/zD99wL37bmdTtM6MKiLP3GLh5c3xbNBn03VkaJVv/7cMfTJcQe9rS+vX3Ia3Lpnqe5yVNQV9kaZpiu3KKZxICDEOQpkUZpIQOtqIa2asyK9R3qjzTnSDbdpiEPsAUI7Rfb2lKUaJ8LrSzTFVqttttjfa2HYTKQcop9eX1llICgZ6cVtjNmZkZPvCB72NtbZ0rV69y5do1WvUW7XarNADIufvu+9jd7WGaBp5XIwxDag0b39fHn2URrjtDoTKGQx/TNLl65SqbW7sUSmjJHUkZVHOSJJxitEzLnhokVDeJPembPRWDWk2DaEejEXmWlgMKqzRvyOh22vj+RPPSckqFSJN+b4DlCoTMyFRCrgpc1wMlKQqJIxyKIsM0tejcYNBnPIoQRYuHHriX8+cuMh6PEAIaTd1TiqIJfhjheTmyLDOlEDi1OjklGVgI8vIzq6zq9XvOp+/TcWxt/+S6U7OIPa2xvZs3VNi5ajqoH1c57IzHmnu4tLREp91lfWNTo8+tHISJZblMJn6Z0YEwDLI0w6vVSbOUYDImT3N2tneQgjLb9QnihJEfY9lQr8/SqFlsberKw3YU3TkHz9P29EnqY1omzZZHGPoURUa73WUw6N3RXnzTUi37151kM/s39+tx/+40cEkppkhs8TZHqmqjTBu05X+rn/m+PwVoVgz+JElo1b19WKc98wGAylRBFRlFoZUWDakxRdu9XTY3tzh86AhFobWEhEinU8HqmG46h0JXI/pbbY9eFAVezUXlGnPzRsoGe+/XQAqTNNOkVtf1yswlYW5+hu5shwfe+QDXr67xyiuvkOcpx48f07InRV5mNuC6NdIkJYojsjSk02mTJBGua+MHE5aXDvLZz3wOhaFxS4UqAY6CJInI80xDRku4SaVhDuxlkOWqmuiaC5gxGo3Y2lin0+lMs8+sLBGrm0RWWkK5kYtCkGUFShUUQI6Bn+fYlonKBaM0xjJs+v0hjYbW3fK8Nqac48XnL9KZ8bAdE8PMCeMCpSSOU2fiJ6R5zmynw4GDBzlx4jgvvvgS4/GoRNInZTmqTRqqQFTJGSul8EpMmed5U9nlSi+88hzcOw95eT3J8poUpXBegut61Ot1BJKLF18lDPSAI8sLoihBCJ84SQBNpTFMyezcIo16ncAfa6hNnjLo7+J5NigHaRkomZHEPmkGeWqTJSbN+gxpFtJoKVpthyyTJHFCGCTYtsAwXLIMRsMRluWSlvi0N1p/Lgfj20/3Xvu4PVrFa//mzjMrNSVX6p7H2903r4T4buqM6X5UqemdJAmiHPFLIUuRfFdjn0q0uGFoGk/1M40Bq55N4vshN26sMhyMsCyH0chncXEJQQymmFJCblKunB6TmmZShmGQ5IW23UbjzLI8w7X05O8Nl5Kala8UluWUz67QuCRtFy4NybFjxzh+/Dhra6soVVCvN9jd3aHRaCClHpVv7fRAUSpJukipAaiWaXHlyhU2NjZQ1DXEVFbYrULboAuNQ7M9TfmoAlSlMnArZ1ApXe5oFYgUx3UJgoA4Cgn8CfV6nbm5Gd1YL336HMfRvofSIsti/T6FIMsVucqQwpu6J0sAYRBFMUJamIbLf/v3/j7veux+gmjAF574E77ytc+TbofEUYZl1XCdFKtmkGQ5270e4yCk1+ujlBbxKwqlWQEqxHEtoljrYBlmncGgD4A0HI39SiIMU+C4+nzU6holXyiBYQryIi0Du6HL+5KrNx4NNL/UtBn0hwR+SN2RGIYFeV4Ck8GfBDiex8rKCgq4sbHJeDLWKqpRSBJHHD50kP7uFih9HeRFgjAKTFMHw+2tHqaYIU0iGm1Dc/1Ewtamj2FYhEHEzMwchiyY6SxS83SmPze3dEc78S22Wb957UdQ7//Z/ufcT7LdyxB0GbAfcV5lNoY0MOS+rvrbFKlUidHROk3awz4HPeoHcpWRFwlxlODapjZ6TCLyrIXn6uxCP49WvcyyAt1OUyBtCgW94YBrV67q0lIKCqnoj3ZpdXT/x3W0zOxecNIB46ZzKSRK6SC5fuMqwdhnY3WT5aUFlIKsCui3gSDsp70UIidVqWblG5RqBCUVRhXlyyoMM6VQWqg/SwsUglqjwWDQ59CRFUaTEXk8JE9CGq6JikMKIUnDgvpsm88+8QzjXPPVJCBVScJOC4pcUKlJSMPUG6nS7BECIavyWJdNhmEghaBRc7EtE6EUnusSxzGWaaKA4WhCYzihOzvL6toqwgRhFEyCEYYpMJQizTKQIJWJVAZhECCF1sAyDc15tB0LFQneed9xDh+f4eyF53nii59jMNim1xuRphLD8JDSIUly2jNN8rwgDkOiSQyF1jUvUvRUtzBJRUpWaJjCfG0e3V8ytPNyUSBUVgZeB8/VpOU0CTFNmzyDNI6rT0iX6WUf1DAMLNtiptslL3KtRGFbKMMgSiOkNKnVHZaWl9ja2iJNEza31ul2u5hKK6dG6YTmTJOscAiKEGULJmFAXdZwLZcki0jynDAIkVZBvRETxjHCMRmF2k8xVj4tr4klMppdwX333c3FCxfp90MG/SHN1uId7cXvyHTv1iD1RtQasS84UfVe0D0eWU3A3q6D3bd0k1pnVJZlA4Ik01icKIyIwkjr/RgWUohpM9S2XSaTcelYontM1URIAyAzbqxtsrO9rdHE5XTPtEwOrxwkyxOktMhzMdUFgtdmnUKANAyt6pjnXLl8lSzN2N7aYm52hnrDK5nt5k1nrIIrVM9nmlr90bK0bpEqsych9gKZEEIHLplDrjOgqgfWtJs0mloQcDIZIUWOKlJ0O8xmOBzh1Jpcv77G6voWSLscMpTHUyhyVNkP0z6C+t97ZgyWtKb/rnqfenRv4rkOge9TFDm1Wo0gCJiZmWEwGCCkZHNrG8+xsSyttNlsNhmNx9PBgmXVyIqMmusRBjFmKZkilFEmqxJT2pjSYmtrk9/9vd8iCCfs7G4yM9Om3Z7hwIFDhEHCjRtrGIbJ9/2VD7C5ucGzzz6H1/C0yoVlMx5Ppq7DjueSlni68XhMo17HKt97MPERCry6S5Lq6Wan0y1vWBJDGqUDckZRtkF0TysttflN0kyXytqkdgyFzXDkY5oGQZCwsHiQxYUDbG5ukiZa1lgDbyOkUXIxpSKIA2zHwjTq5EVBkmYkSU6OwvMaIHOaTZuu3dAyMIZBGCW02m3SRLMVdnu7vPTSiwghGI+GzM/PkSTxHe3D74yC3L5VlS633tlvRkWXX/syKyh7OBVR9m1eSummtc409uyt0kRfGHFS2nEXZTlkGhSlgWMFxjMMszxufZrjOGYw6PPyyy/T6/XK9NkAVbC4uEir2WAymdBsNqnVvD0Zklt7UXsnroQ0lBSVEj/V7c5MG8f7zUVvfn/qpunj/qz21sftvZyePiZJqks718GQgiLLKPKM8WiIQBH4PrbjooAgiojTDGlaPPX0M1P6x/4MugLF7jcZLYqCvNgzIN2vvVWtatJXya8YhkGn05k+3i2VKhYWFnDsJnEEgZ/Tai5gWy0cq40/ziF3cJ0uM90FbWppWhS5hojozN1AFYo4illfX6fVbnLsmMb3DAYD3vOe95BlBTdWVwlDXc4JTHq7I+bmFkoql1a8oMTEOY6+gXlejSjSk8vBYMjE90li3UvSvTadSea5JqWPhmNGwxFhqNU1TNOCKfhX80hnZ2dxXY801SJ6erpoYpl1LLNOFCpGw5iNtR4njt/LybvuxZQeNa/DysHDWs8eSJOUIsvIkhRTmhoFX027c23LpRVfbXZ2dtnZ2SaOE3w/IIoSoignz0ApkyRWTMYJSaxIEygKSRLfmTvo2x6k9m+wKkDtd7K9XbB6zRfVpEwy7Zt+BwJVo9GcTkkUqvQ+q6ZKeSmhoTeLUwrCRZEWmq+Q2PuDb57njEbjEoeU4zg2piFZXl5ie2sLyzRZOXgQu6SZaDxMOgWN3u4cVZs8TVM6nTaWZbGwsKCVHFONqbldR6py7dWSJuPSYZl92cprA1T1XrWMrTYe0FmmQRRoEbQ41M7LSRyTF4rh2KfVneHFl8/QH440/scwb4JeVMG4yvCq46uC0v6sb/8qigK3FNGrrLIqAnKea7XS4XCI53k4tofr1EiTgl5viJQOApN2e45mc4a5mSV2tnfxJ36JBteT5KqU0qwCrZn1Z3/2aSzL4PTpk2xvb3P27FmyLMWxHaSQnDx5io9//E8Iw4RjR0/w6KPv1jcvV2tUeTUbIXVQjqKoPO7qc9Za7VEUkefFNBBLKfGDEN8PmEx8fN8vby5yWuJVgoC6f2dh2w7tdpeHHnyEdmuGBx98mBPH7+Keu+/l7/w3f5djx45z9eo1zp27gO+HvPD8C2xsaj89z/FI4wRbWljSROUFYRASRTFJ2f/L0ozAD4jjmNnZOZxSIcT3A3x/gj8ZMx5PMA1La3BlBXGUsry8jG3ZzM/P3dE+fFuD1O0CDnDT3fP2VJnXOdh9vDl4e+OUYUiajQaO4+4ldOhJUBhGpEnGZBKilBbGt8rSMI72TBerKUzFancch0ajrvs+KFzHZnZ2hvW1NQ6tHGTlwAFUkd8ka1tRcqrn2r+RQZeOosQ1eF5tilOq0N/atUa+5pxrpU2bRqPB2toao+FwqmS5P0jtDw4668pLnXBdfqEUcRSRRAFFlqKyhLREho/GEwzbYeyHvHL+IrlSGKaFQN00TJnSi3jtVBW4bZCqGunNRkML6JXgzirgep43PY8Ac/NdEDmKlOFwl7vvvovHHnsXhiHodFp87/f9FY4cPkKr2Z6Kx+WlOUKRFWRpjsr11G0yGfE7v/vbPPvss9NJnet6DIYjDh06zN2n7yVNcsJQm7Z+/nOf00EzSfD9MVmWIKQuW6MwQRVCGzeYNrZlU6839XWValkfrcrp0Kg3tFomlW+jBnvatvbiq+RpikLR7cywvHQAgUEcZyRxyjsfvIf3ftej3HPfXRw+usRwtIMfDHA9g3bHo9Wu0Rv06fUHqAI8yyX2I2I/JIkSbZShtOOLBpPqzKpeaxAEIUJqET7HcbVKiJHSanvkRYxhgpAFUeyTZAFBOGA42rqjvfimG+ffehp3M07qduvWu3SVDdzcQC8Fo1RFfdnbnNNgNv3d27OKQlGr12g0Gmxv75bocv2ak4nP0vwM49GEONLj5lqjgTQEaarH8c1mA8PUoneTyQQp97Ipz3WYm9P6UVevXOHkXSeYnenqZj1gSFBFhiwnNVoSWGv13Bz0K5qQ9qRzHJtWq1Wex4pIvKdgWfWXKvpMFTwXFxd56qmn+Z73ffdN08RKk0iU/bYwishUQZYljEYT5mbmyPOc8aBPlkUkcYApFFGSaOBkrnDrLs8+/xJRnFEpjeZ5WrrT3Lyqz7bSolKV9gt7N7z9rjFCCNqdDkEQsLi4SBRFBEGgR+7lY03TZGtrC2sZ0nxCs+Uyv9DlkUceYH1jHdNUNJo11taus729hWVZdDqdaZZTldt6IqeD3oMPvpO1tVVWV28ghDbpTJKClYOHeMc7HmRmZpZGs8E999zDmTMvI8rjSJJo70ZRKKThYFi6FMzSjCTRWuM6UzUQQhFGmk6SZ/ozNQwdlIoixnFcVKFBnUpVumQLmIat+2Lf90FM0+Lc2fMkScrv/N5/xHNdlpaX+PgnLpAVE6QSRMkI09TmrmnuahOL0RjXcUjSGCkkpjRIswJVUPL8CsIwZzTuM7cwA6LAVEqrfHgWzXZGra71qLa3e/jBEMd2cF0DwywYDHewrbfYwfhOgZhvhErf/zyv1we5zbPqx5ZBqhw0vc29KX3XnJ+f4+rV65o0a5skUTjVsJ5EAUEQYZiSyWRCreYwioNyo9RwbIfxeITj2CXS2sAwXGYslzBKuH71Cvfddx+tpnY3EdXIf18G47ou58+f1yYAnsfRo0eByllGIOSe4YNSTJ1Y0jRFGiVSXou2TDOz/QEIoNPpYNkWzz77LI899tj0d1XGVumCV/idjfUtOq02AJPxkCJPSeMY8owoCRGGQRiE1Ftdrt1Y49LlayDllEPAvptSFXD2A1anmZRQ00HJ/n5UdW7qZaN5c3NzWuJWQR32bgpFURAnEVmagBSYpsF/+s//Edd1mZ2f4/z585w5+woi1+6DlSU6HRgOhlOisMp1KSYNQbvTYn3jBlIabGxskOeCbnsOpWB5eZnZ2Q6nT5/i0qVzbO8EuK5NUVjEiaQohKZSSZMsSUmLoiRXW6WUsIZKWIbW0a/YDPozsQjDSA9ylD4X/kRTclzXxfM8kjjTki031rh08VVOn74by3SI4wDDVFx69RxQcU91EI6ilDj2yXON+xNIfWxRQqNZR+WKRqNFnETYjqNhONEEIRVRFFOrOeSZrgKCIMTxbJQHCEo6UKolZlSO76c0GnVazdod7cS3XQXhzv7u9R5TNc8FKLEnYwLT3vrbtYTQZgIHDh5EPfVNDRq0TLJEEAQhYRjjmJLBYMjMXJfJZMTi0iKhlRLHGphXq9c04rbUfNJTpy5SGsRRzOnTp2m3WiRxhFWWgKAzoIrE3O/3S2sgl5mZGYbD4dRKHRRxEoAqqNQsi9LKyXFMHKM0XkBP96rNfWv/xzRN7rv3Xl4+8zLf/OY3efTRR6fqlZWqgGEY2KZJgaQ706Xu1elt75BFEWmaUOQpeZZAnhFEEY5TYzQa8+JLZyiEAEo/vuk1okrEvbopS6pWxVXb/7Pquqn0yStDjGqDjsfaAt6yLGZmZgiCAKW09ZNj17AsD4Rgd2dIzW2T5jlnXr6kPxMDVg4vsLO1Sbc7w+bm5pQjWR2fHnIohsPBlF+nbxYGUjoUeY9PfvJP+NznPs9gtMZzzz/N4tI8u72tMpsWWKY2RzCETa40kdyyLF2SF7q5blc28FGMMPTkrgrelEDXhfkFBoOhpu/YNtLUOL2dnR2SOGN1dY0b19cIgpjV1Q2iOEKpDCF0KT4zO8NkPNbYPglhGKCUQEgd/Iq8wBASx7SQhSAKtN371tY27VYb27KZnT/MeNzHtHS5KgxJmmaMJz7SkOzuRiRhThwVFKmgvzvi4IElWh2XLA8ZDsI72otvaZC6g0TrNX/7egHr5iBVVndlI/M7RYsxTZPjx45NDRdytMusUho1e/jQQXZ3ezRbDXIyJpMxtuWQpSmjkc6g2u02u7u7CCFKnz6bMIyZmdHWUKhCKxqwh0USaAhllmVcuXKlNCHVFAttZLA36arX65r/lgPosuzq1aucPHkcLShqlnIt8qastZr6VZuw1Wpx+vRpnn/+eS5evMjy8nJJK9ETQtu2tRJpKVc77A9JkhhV5ERBACohS2KU0hIyRZHzytmz+GGItDz28KS6JVBtuP3r1undfsrRzQjrjFqtxvz8vO6FCE0G397eJimzkAq9DaX9eZCTRKLM6EwOrhziyJEjWLbNF77wRCkoZ5KnGb2dXZr1hqaj5FpMxihLniIvOHv2FebmZqdZaVGAY9vMzs4R+EmZ6UguXDhLnudT4nNWqoJCTpYphCWowMlpmqEKVX6BW3MxhUGSxeXf6PNimiaHDx3h0Ucf5ZlnnuXixYs0Ww38YFIGZUkYRHzjG09imS6zs3OsHDyMZdv0B1vcuHEN27YY9kPSrEAKE0uadFraVBShhXpUoUiymCLLiIKAcRiw3dul3m6S5Tn+xMd0jJJTqL0h0zyj3mhg2za7u31AIpVFkZtksSJNLbY3fSajCEWM47zF5d7+Rubrr5svum+VMe1ddKLsQe0rE6mAixJte6MBdUroqK8f+nb1/PeXqwWHDh3AdS3iNJoyxclzBqMhK8UyURgyGU9oNuuMd4fMLR8pQW4Bo4nP7OwsrU6HIs+pSMeOS6mNXqCEWZI4S1nkQr/lPFfs7A7x/RjDkKysLNPr7XL06HHyQvPCdLmkJzx5kTE7N4vrusRJTBTpvpDr1qgUP/ef+1ub8JZt43k1HnroYV544QVa7Y7WhFICy7RRwiDNFXkhCP2AMBhBlhAHY0ypOWJCKH1stTavnLvI6kYP03JJkhTDtJH7UCXTpvy+jLhQua52KY+r/PiLMlMslEKUEAXHcbAtm92dbYo049VLFwHtzmKZBv5kTBLr6WWzUWfx8AF65YjfcVwW5uc5fvw473r0Xfy1v/YT/O7v/z5f/dITOG6XIkvwnAYznVm2tzcpcIjjhDTPEKLg4IFFujMdLMtka3sLy3J417vey3d9918hSwVPPfUMzz/7dba2tzAMENIkL7JScE5guyZhEEIiyx5PpkUKhcLzHJI4pChyTFsyCROkUZp/2BZCGKSZ4vHHv8B47OM4DYaDEImBa9YxMTl918nSNMThyOGjvOe93821q9cJByOaVpvxeIhSZQYmIBj7eDUP17LJZE6n00Yi2N7cIheCMEqwPBfb1Q5Jo9EY23To706wHYNWxyVOAxCQhCmBXzAapRrzVUTUag2EUhRZQqe1iFIFfpAzHgR3tCPf0p0uhHzDr+qqrL6vMqT9P5vOfBHoOGqUf5YjqpvKbWzB36J3se8YBQdXDtDpNjEMRaF0qp0XBUmWstPfpdlqsrm+gSwgCxMmvo/r1VBCEMYJfhjiOC7SMFFIskKUeCaDosjw/bFungpQUpBVUEohuXz5OrV6i0azw/rGFt2ZOUQpn1ymSfv+DzOzXdKSOT8aT0qcjHlThluVLRUUZBqwCoU0DBzX49777seybKIkxas3MS2HJM1BGPhBQOBPEEVKEo5QWUgcjpASkizHchtcvrHLlRvbCMNFKe0hKMqhgB4IipK4swca1Q1yDfPQaH/9MeRKPwohUTA1yqzX6hhSEvgBYeCTJrGeGuYZaaIdYjzXoea5BL6PYUKrVcO2DaJozOGjB8nykGefe4rDR5b57/7+3+P//v/4f+K4bQzTw3XrxFFMrVbDdR0My8SPQnKlqHkanLm9vaWHEI7Dux57FKTBi6+8wuFjx/iB7/9xVOGwsHAQ07R1t1Fl2K5Bo+nheCaGEBw/dozv/8gPMDe7wKmT9+A4NWzXI4hCkjzFdjXH0DAsojgjCGLAYDjyGY0CwjClyARpXJCnBWkSs7gwi2MLstRnY+Mqv/4ffo0//ZP/wtb6BvOzM3z0R36E7/ve91OvuziuRa3mYkiFV3eoeVpjant3m6Qo6C4sMre8THtmDoUshy4OpqG5eQIHgc1wMKLIMlQmCUY5KnFQqcSSNisHlvBcSb1u4tUM+v0eWQrxnWE5v/0g9e3QZN7Ek9/2xxoc+a3LxLdySSmZn58vm9UCoQwEJkppmsvW1jaWbZFmCTu720gT+r0doNBgzDxjMh5pE4JabZ/ZAkhhYNsOUpoEfqhH3IVGN0tpcv7cBVzXIQgmdLsdsizlwIFlsjyj4rrtDz666az7M9KQhGFYSsm8FgR6u2mfkLIcb+8J6PvjEaE/KXtYBeNhjzwaU6QBgT8iy2KiOCYtFJMowqnXuba2zrlz528y8NzvkXcr3KA6nur/VRCdtgOgxCwJLd2iFKahLcWiKMJ1HGq1ms5YW61pSTw7OzslfSdJzJUrl9C28gVxEuI4Bvfee5okDfm3/+5f0+/v8q53Pcz/8D/8Y2zbZn1jowzm2tyiIu9mWc7ly9c5f+4S/iQiClNmZxd4+cw5pDSYn53jg9/3Qd773vcwNzfL0tISs7OzpTaUhcBgONBtgbm5OeI44tVXL2Ka+rVqtZpG4GcKpTQgOEkShsMhhhQsLS1OdbEWFueYX5jlwMoSh44e4JHHHsRyDZ785tcZTnqE6YT+aIconeA1bY7ff5S7HzrNsXuPEoqQRMTImsRpOyRmRqAikDmWLanVPLpdrTArhaGxTrUGAhPPrWNZDllaEMcp/f6QWq1Fo9FGFbpnG0UxpiVZPrBAveFyYOUAp+4+xXgyQhgKPxiRpG9xT+rtCgqv97y3es4Bpdvrd4IQs7eR9cj5Qb729W+gcgthSnIjpchTojhhfWOD5aV5NrY3qDePUeQpu9ubzC8sEhQ5cRwxHo/pdrvYtk0cxwhVMBzp4FVtrP18uiRJ2NnZptmcZWZmBt/XgcpxbPIiR1u+p2WppjEzum8hp/xGz/PwfS2Noorbs82r4JEkCXmR4zgOWZZNN3g1LYoiDS6MgjFZrHE+WRqTJjFJlpEXUG91ubGxySsXXqVQ9hQEu59Ws/+83i5wwh4jQR9b+b3QU0HT0M13KQSWZWGblsYOJRG1mpaJcRyHbrdLnufU6/XpOQjDAMdz6HRa9Aa7BKHPf/rP/5G//b/529S8Gv/xP/0G73ro3bzjvnfyPe/7Lv7wY7+DKTNcr2x0m1rHyXE8HLdGGKd4XpuVQyscP3oKU9p85UtfY3FR00xUlvLIIw/x5FNfRZHR6XTJsqTEM5nEcU6aDErzzl0sy+XatWvkeUG9XtMwAqlJxfPzLdrtDrs7PfqDHmEQMT8/x0d/7KM8/dQzXLx0Aa9msNXPMF2FgYHtGHQ7XSzbIfAjwjDi2Re/xovnbD7+Zx/Dq7lIx8BwdRadRQlKSdq1FoYAKbWqQ15ojJjrumSZQhUFnufoNoDlgBJEQYzlFCRxrqfX3RmyTGFaCX44IlqbMD8/i+c5zM3PkOUZQTDBMO+suXzHmdTrATPfqvWa573N0++X6fhOrKph+8ADD9BpdyhKI0xZ1pwK2NjaIlcFhmWytrmBZUoCf8JkOMBzHUwpCYOA4XAIaE3qvFAEQUQcp4CkVmsAkjzXnm293oBms8V4POLQoRV2d3c4cOBAWcppRYVKBK1aFdC1Ug9tt9sMh0MqZ+Bb31cFQ6iAohW4s6KkmIaBaQii0CcYj0jjiDgYk8cj0nBMlkSEcUyaK0y3xurmDmfOXSIpFSn3pJXN6Wu+0bBk733sKT4AU8lm3aTOaTWb5GnG7u6uVjyo+GIloLEScrMsa6qQ4PtjbNskSXVz/4//+A8ZT4b8yq/8Sy5cPEe70+TG6g0+9ge/j+s6vPPBBxgMB8RxgmM75EVBs9FkcXGJLFcYhkO90aFWa/OOdzzMkZVjNBstBr0+X3riCXx/zKVXLxJGAWEYYFs23e4MNa9BzWsisCgKNZVGjqKQbrfFgYNLpaGsYDIOieOERx99lHq9xsTXqpvSgLvvvotXXnmZzc010jwkKgIykeC2bExPkImY1e3rjMMBx08f5siJg5y86wCtumCmZVNzBDUbDDJMcuq2SadRw7IkpmXQbDVQKodyKq0UxFGKUgZxpB2RVQGTcYhteXhugyzVVYLjulqd1kZnTeGEnd4OV69fZbe/C0LRaNdwa3eWI70pB+M7a56/dUuXL3vf6wtelHfYt/e1K4yNEIKDBw9y4sQJNjefQ1pa56hQCgNJmqVcvbHKsaNH2NraYNjfpdvusLF2g6PHjuHYNlEcE4YakVuvN/C8mmacl7IhVTno+z6WZTE7O0u3M8NgMCptuyWzczPTC1oIUGqvEV9ZVFWAQynF1PhSB9q991RlNxW0oNrI0jRLRLim/ezsbGNIzbRP04QkilBFQpGEJElKGOcU0sKtNbmxvsm5C5eJ4wzTsm/iG8LNeLlbS73953taepb/rpQ5pdwb0xumTbvVZmVlhYvnz09VJpVS05J6d3d3qtxZZaaua4OA9fU1lFI8+uijXLx4kdF4zGc/+1l++Ed+hO/+rvfz5Dee5vd/97eZnelw+PAhXn31VTqzM5iWzcGDK4RRTJrn1Jstjh07wWTs81/+8OM0Gg1+/Md/HNM0WDl4kJm5Dp/93KdYXbtSls8x3e4sN65vkGeKItdjeyUq7qQGD6dJUmrWU+rYF3z9619HCP2ZDgZ9LMvk6rXL7O7u4gc+3dkOlmuQZjEHV5YZjfsMBj0M0yUIJ7x85kVmOjPI2KdlG8RJimXJUrtfEGc5nqeddVIKgjAGZRIEMWmiA0/lneg42mDjwIElVg4e48wrr2AYBfWGQaES/EnMaBRQq3kIUZSW8WbJT9RqDF7NLd9jdkd78S0fkb21mdb+Bjr7EOffAQwCe3f1er3Ou9/9GI5jUhQZsrIYSlMUBru7QwZDn5nZRXa2tgj8Cd12k1cvXqDIsz1dbj9gNBojhCy5Ti55rjWAsvJCkdIkywrGkwndbhev5nHy1F2lBrYosUN7iHMNvNzDGmVZhmmYU1rNeDyeiqVVyPUKrOmUtlpV1pKmGa7jlvK/MZcuXODGtatkcUSWxMShX264BISJ5dS4emOD8xeuEUcZntsgT28P1N1/XbweZ/NWTqcsAaBSgWWYGELzBZcWF1leXGRubo4811lgFGnCbZIkjEajkujtTMXj0pJiIoWBaTpkWYEojTN7vQG/9du/y6//+q9z5Mgh/s7f+d8ShgHdbofl5UUm4wmdTpdarc7EnzA7P8ePfvSjHFw5zE/99M/QbDbJ0pRnnn4KKRSHDh0gzxKWlhZLepJ2Jn755VcwDYdjx07y7nd/D/fc/U5azZnp59/v7xCEE5TKSNKIotDI7iRJEAImk7H+Po1YXbtOFPvUajZ5nlKvN8izgp2dXRr1Bq5bo9ls4joeUZRojt1kROpP6NZrzLXaRKMJRZSR+QnxOIZU4E+iKZzFtl3iWEM6PM/Dq7kIqZAmvOe9j/Ghv/oB5mZnmZmdoVarUavVaTbrfPAD38vygSUsxyZKYiZ+QJLm5EogTX1DbLabLCz9JZBq+bYDVcWSp2qmctOFXYm3vJHky593VT0bwzB47LHH+J3f/Rirq2tlWZVjmhZplmHZFhcuXeORRx6m3WqxvraKZRq0mg2uXH6VA4eO4LoufhCBkPR6Cd1OG9vWMiwaIa3lh3d2dlhYWMA0TeIoxqt51Go1siylEqDTkzktnWKZDlobXfvPVcz/PM85efJkuYF1IKvei1lOyKrgkOfayw1ge3eXLInx/QlFntPptomjgCxJyPKEKEowLA+n1ubSlTXOX7yiTSDtOnGYYBkmmbiZ+7dfnme/qgHcPoPaT32SQt8QbNsmjRNmZ2fZWF/Hn0yYnZmhv9sjiHzSNGUymWgysaOb0qCDVq1WI0kypLQwTQfynJnuHEuLB/jmc89imjY/9VM/w+c++zj/r3/yP/HO++8r+0da8mV9cxvfDxj7IQjwwwmWbfGBD36A4WDEz/zMz2BIQbfbYnFhliKPOXP2ZSa+DioVf/DkyeM89uh7+asf+gEajSbffOZpvvSlL/C1r30Jw9DBNi8ypEQrEYgcIYwSpKr5ie1OE8exysEECKG0LNDAIY4iRsMheZoxGAxKhoEFhYTC4OFHHiHLcm6srrOxtY1Csrml+2GeV9ea61nGJAhoNDoUuaJW87AsC8s2qNs2k8kYw4BPffoTPP6Zz3Po0BEUOVeuXqXV9mjUmzSaLg+88z4uXlVEUcq1qzcYTwKkYWMYCZZllC5C/h3tw++YW0y17pReUyGk9XRo/52YtxVpftsjEYLl5SUeffRBNrfWpiWXNEwkkjQtsCyTl14+z3vvO0SehKytrTK/sESr2eDG9evMzM/TaLYJwghlWwwGw6l0rOt6RGHIOJhMJ1JBEOg7oesSBL5umueZ7hMIINWlTGrkVA1zISSdTmdamrdarbJcVtN+0/4G/X69pjCKmQQBKs8ZDfrkWc7s7AxZHBJHAXmWEoYBjXYbpM1zL7zC6mZPo7gxodCaT0WaIuybE/TX6mDt9aaqALU/aO575NQtp0qelxcX8X2fJI5pt9q0O20ma2OEEHQ6HSaTyXQQcfjwYXZ2drAsi9EwIE1yajWteXTPPffz2GOP8Y4HHuTZZ5/jyW88Tb1eZ331Ot989hk211aZnelS82rMzHTp9XoYlo3XqHNgZZlH3vUwjXqLV868wg985CNYpkHNs7h06Tx//PE/4uWz59jd3Zmi1mdn55ibXWA0mnDlyjU+99kv0Gq2OHv2EgiTme4sUTwmCHXmq1AUpepmnits26LZrJPnGUlS4LpOiT4RSMNAFCaO5UJRMOyNSeKc2dkOo+GYIIhY6C6w3tsljGJ2BgN2x2PyXKIMkzQvsA0bpE0cjGnU22Rpjm17BP4I13XpdFpsbq4hDZ3RWaZNkaeMRh22dzZRQhttZFnKU09/HcetMQp3cd06Xq2OlFqRIYoCtJXOraq3r7/etM36t3riW3//rdHket1eFqSc7qnXyrzs/7u3e9K3/zVs2+J93/PdfOELn2c4mpTlXoacOryAH4ScPXuBe+89zfr6BpubW8zOL2iS8sYGURAyMzdHlqbkaaqRxpmeqg2HI1qtFiCI44Si0CoJZqnGACAdbQxQFDl5KdqvsU7aPEHbPiU06nWklAShz+zMHIaxF/DzYs8eKc00qTVJEuJyVD8ZjUDlSAP8yYQkDPAnY7IkYfnAAYZhzJmzL9If+ThOjSQtEOQIpbSC5+t8Jvszp9c0xWVFlpZTrh7oQYntaH33KeBVSg4ePMhoMGQy0SjrrCypTdPUJgvSwHYcTNOk0WyyubGBKrTUiGU6HD58hHvuPo2UGUsHuhzcmeWpZ55hbe0Gk9GYhx54kBtXr1HkiiSOqdVchqMxtqMNTi3TYuXACl/84pf53r/yvWRZznPPPcsXPv9Z1teu0+22+aEf+iE+8YmPc/36DUDQ7cxy+PBRFuaXEQJc1+H8uYuYho1teVpdwvSwrJQ8TxFCkmYxeSZxXQ8hJJZtagUFIUlTbYVlWSZCGqRxSV7OK8iZwXgYEEcZeQbbW322tsa4rovjeMwuHWB7u0+eK6Qw2R72S134OlmakqYZw8EmSoCb2gThGGROEIUUqmBhYYE4UuzubpPnKYapp8zD0QTPlUyCmKRIydKIEydOcvDgCltbW1y4cE5zLLOUMI7uaB++6SB1u2borWs/H+uNouVtH1NmTEpo3FD1GNM0p3vgVsmSt3rdelc3DJMH3/kAD7zjAb7xjaeJ4xzb9CjyqNz8KQjB9jDnpXPXOHXqJNtbm2xt7TAzkzHXbjEY7LA+3mV2eQVhOUyiEDNLyVSBH0d4qs7MglYWEEWBLPKpdYsOMgIpDC1gZgiwQQkdGJRS9Ht98jwlCGKkYbAwPw8yI1P2NKOiRKenUUQY+qRZorWfUp8kGKPygiROicKYIodeb8jGxiZ3nbiL6xtDzl1fx/djHKdeliSFBmXKqjwvVS3Y+5z2XzPT6R17ZZ8oIQaVb3JRFCXgVRsDxKVjr2WaDEZ9+v0d4ihm7De07ZhhEMQRrnAxSp++azeus765oWEIUYhjSiJ/gus2WDmwTLtjYNdHbF74Ji+c+wxGTTAOV4kT+MpXvsaRA8dpNRrE0QDPkUiRIFSGoQSpn3PuzHlsw+GF51/gK1/5KtvbO5w+dZr3v//DHD58gE9+6mMMB2NQNpbp8q5H3ocQAt8PePjhAzz2D/4eSSR45pnneP755/j617/Kbm+HPHNJshzTdMvzWCmVqhIKoAnkWk9KITDIi5SsGJf0JZckLZDSYTyOsSwH16kRJxAnMBhOaDYFUUmUtyyLhaV5Ks/InY0UYdnYjoMfjlEiJyekN84wTYPZpQUc6WIJh7AYkRURucqJw5zFpQPkEx/bbWOaJsPVG8iGZDT0sa0t0jTANAtMU0NnsuRtCFJ3uu4kkL3e46fBQejekyp5XprE+R0XEt1bSuHVanz4wx/m+edfQqmkbHqbSJmiihwkZAX0eiPOnDnHPXefZDIZsbu7QxiMWVpapCgybly7Qq3R0tiZXDKKQsbjMYN+j8WlJc3rA2y3RtVL2gND7sOQKY3Ipmygj0vZ3CDWnnlpoZAUGLIoLbtT8iwlzWJUkZHG2qwgiWNQKWHoazpNrgOi78e4tTonTp7m2vUbrG/tkJsOrutOy8X9QM0qS7pV3QBea8ZReSpOv781gyrL07w0Q11eXmZzY4PBYIApDQSwu6MhCG6jVrLv9SR0ZmaGZrNJmqZatte2IcvJ8oxmu8lXvvplMjHEa+UkxZgojqk32nz393wXX3j8qxw+egRLWBRKIU0TQ9lls13huXVGoxG/9Vu/hWEYDIdj3vnOd/KzP/sznDx5F6ahnarHI58TJ+7Ctuo88cSXCPyQo8eOcObMy/zO7/wu9UaN/+r7/2uuXrvE+973Xh599CE++9nP8MrZl7ixegVEQc1r6F5h9XGXN+ogCKbnO45jTbmhIApTVE1imnapWqF7mF7NwfcnCCR5VuD7AULseUkmSVoSjBWFAs+ra9eYfIZC6IzNth1arRZuzcMRFlmUEkYTjdkrtGXW3/m7f4f/8Ov/X9Y3NnFdl0OHD3Do0CGu37jKmTNrZFlCq92kKCBNCor8Lebu3cm6tQR7MyXZTX0KKprtzasCL+5XvPyOrXIDPvroo9x///08/fSz+u5TagWlWVVjm2S5YjCc8NwLL3HvPaeYcebp97a4fPUy83OzLC/M4E8CNm5cxvNq1JotbAP8OMUfj6l5WuEwTzOkoSVsESXh1thzp0GAIUoEtxB6+jTxaTSajCdjhsNRaY4ZU+R5SRnRuk9ROCHPUu3mGwZMxiOkIcizgihOMC2XTneWre0+l86d0z9z6+QlpupWQbw7WZVUjP6MtdbV7cp5y7J0s7nchCeOH9c4sSSh1+uxMDePaRi0WxoRvba1QZIkNBqNqSLC0tISV69encIumvUaUlhcu3YVy5UMRn16kxEvnHma5QPLDIYTPHfM3EKXQmQYlkQakKS6XyeESZ4L0jSj0a4zHo85dOgQP/dzf5377rsXw6jchuHy5cu89OIr/PW//jfw/ZAnnvgyK4cO0O12+chHPszsXJdf+qX/mX/9b3+V7/nu76bRdLnv/rvpzrR4/PEmf/CHN5Dl8CFNNDUnTVOazea0ZwlM/61ZBlqALo4zhNA2abZtIYTmd9q2SRCEFIViMg5otfUEMAw1UFcISRBMoDAIQj1RtF0bz2sShoHmbxaKjfVNTKCIE6ShddSjKKbTafPlr3yZIJjwyCMPMRgOGPS3sWzJ93//R1hbW+VrX/ua9qCMdabYbM7e0XXztmVS3+oivh1G5uaAVlpA3cTzExjGt2bNv+1LQaej+w0XLl5md6ePUgrLMilUpqdkucI0NJixCGOeefY5Tp06ztKBg2xvb7K5s82o32N+dpbF2Q4TP2C4u4MwTBrtNp5r408mU47U/o2tz1V1/sqxvbWnuum6HqPxiFq9zmAwJCgisjzHFIIkjkiTiDxNyNMYiow4mOgJS1EgBSRRToGg057Bj1JeOX+Rza0e0nTIhEUSp6XGvLgpu9sPvtwvSLf/c61UP2+d6t063dufRcVJgutp+sva2hpZlpWa2ha2ZVGoYqoz3+12UUrh+z5BEHDw4EGdieV5OT6vYUgLP4yIEp+8iBiMtjm4slxaqwcsLC6Tp4ql2RXCUUYaJRRFrvWcEAhpkOU5w+GQD33oQ/z0T/8M9Vod295Tby2KgosXL+A4dR5++F28+OJLOI7D0tIiKysHcRwbIQUPPfQQTz/9JT7+yT/An0T8w3/wjzhwYIX3vOc9/OmnPkkQTIjiGMsqS70SZhEEwU0BXZO0JXmJuypUqedU6uznecZ4MigxhzpDNk0LQ1r6WIQ28tBTX5soCBAGmJaB59bIcp09BoGWLQ7jkIZrcWTlIFmu2N0d4Dg1rly5yktnXsGyHF54/nncmsN43OPJp4acPfsKzWarxGIltJodwiCiUWvc0bb7czkYT0/S66xbG92vt279nVKafqormf39DN0kloK3H815myUNzdl77LFH+a73fhef+cxnmfgTpKn7RAooMlBIhAFJGmNZ8OJLZ1hcnOXu03eRpDGT3W1Wb1zHdT063VnmZjpEScp4OGDQ71OrN/BqdRLbxbYs5D78UIUsr0jBmZ/uA3nqTa6KHKUyhv2xbkyTY0qBFBCHusTLkghTSqSCOEkohKTZniErCq5cXeXa6gZxVmBYLklegNSSHEVJsangDPshBtXaf+OoroH9Jqnfatpn2/ZU2900DWZnZ3EseypVU2VLtVoNyzQJg0D70BXaJFTTiHxeeeUVxuMxlfaUkII4jfEaLqPJhLtOHmdtO2d18yomBobhcX31KnW3xQc+9H6++fWXePnFl0nTgLSU+zUMQX/QY25+hqWlJWa6XRCCItcctjzPGI9HfOMbT3Ly5Cna7TbXrl3loYfeSXemg1fTuK2nn3qS1dUbvHzmBSzTZHZmHmEoFDnPPPMUYRiQ5wWO7SINpTOZfXLSwFRGR59QkNIkSbLyRq6J+to0NCfNUlAZSbwH9p0IHXQsy8QybU3SzjIEBY5tEUYpSZISlCYRwgAhC4RUHD9xhNMnThAEKYPB82SZIo5SHLtGq92aysbMzHSnUjpRFJMkGd3OLA8//C6+8uWvsLH+NskH327dCth7o8e/0XPryd5rH/cX2pMCVFHdcSx+8id/gueff5F8oyCItPmAqUzCLCZTGaIA07JAKkzbZWu7z2D4LHedOM7y8iFevXCOnf4WUabY6g1wXZdGs0mzroXZIn9Mv7erg4xh4JZYoYoMDFUzPSdLU67fuKHlY+fmGPZ2NJpcannhNI7w44isnCgKoFCKsR9Sq9VotOfIFFy9scn11VXSrCArBNpWS6EoXaPLknN/BrunCvpaLNTrATfLszn9e02+NUttdn1JpmlKtzujffUaDebn52m3Wjz55JPcc/pulpaWWF1dJY4Tms3mVODuwx/+MH/2Z3+GtoDqMCy127M8RxiSYX8Hr2Fx5folkmKI7ZiYygQs5udnyDPFf/zPv4GlauQqIVMxce4zDgd4XodavY1h6NJoPBlz4cIFNtY3mUx8oihmMvE5c+YMp06d5l/8i3/Jc88/w113HefggXnyIufJp77K//LP/zlZnuM4JpPJBHvi8LnPfoZ3vevdrK7dwHFsFBlFkZYSOt7UZCLLsqnNWYW2T7OizFYNDEOSZQl5pgcalqW5m0JoCzIhNMq7yFUppmdMAwjoKmA4HAEmo1GA43rMzs0QRBOkkSMtiyQJCQKfJEFPE9GvEQYJzaakVmsShOPydwZZWmCZknqtyUc+8gNIoXt5pmnd0b57S8q9t6fkKgOeEtMSZ2rC8J1Popi2q5WGBhw6dJCf/umf4t/8239HnEbaTgiF7ZYCeXmKwMBAUBQChE2c5Lz48gWutzxqrs3MwjK265ImmjYRRRGWZWLbNpZp4tVq+oIsCrI8JvLDEn8vEFLz2bI0wTQNjhxY1BduGiIKhcyzEp2cYcqcQhQkeTrVmarXW7S6C4RBzOXVddY3tgnjRJcOSms3KSHK1ytQSkyVQ2+XEe2HklQN8/3Z0/41LfP2/XtKfTEM3QwvHV9sx2Y8HrO5uYlpGMzMzBCFId/85jdptVra5SaNGY1GLCws8PTTT0+1yA8ePMhwOCwtygWW7VCre1hOztgfEsS7WJ5BkmTU63WyImUwHNGsz9HfGtBuNDEsk3qrieVIwignK3yyzOHTn/404/GY06fu5oF3vkNre7seX//6N/iTP/kkP/iDP8AXvvBZJpMBV69d5Ff/1b9gfn6WtfV1anWH9fUNwnBYNt+HPP3MM9y4scarr75Klicg8hITpaauMbqkd6eBfHqzUAXS0JxJKQVxXGAYuhIxXYcijxBSogqB43haSbVQKFUQ5LEGBhcFnueiiowsLTBMrTiRJAWGNJmd7WJYGUkeUKiMzY1NolhfRzMzB1heWmE4GnPu/Dksx6Dmtdjd2aLdbpd9shTHMTh4YIXz589z4MABdnZ27mjn/bmD1O0wT292vfbvSo2hKSPmZvOBv5glprrieTlt/OAHv5eXz5zhs5//HINhH2lIhAQTiUoleZFTZKUlFxKlJKZhMBzH7A7HhGnBgSWX+YUlyFP8yZgo8CmSiNy2SZKQcfnqVU+HsmleUWN0jmOQpDFFXmBaplYLkIrJRCOxg3SCZdk0anWazTaFkgzGAZfOXmR7p18GJwOwph6DUlbCg0ojv6sSnJszo6rkuDV7mh7v7c6kEBhGpRu2t5RSZQal+0v9wQDLsgjK3owQGn0+Go/otDulmYPi0KFDPPDAA1y6dGnK26vI05XxZhzHiJIpUKt7hKHPOByx2J5j4ofYaYIQWvAt8TOWlucx0NCTJAvxGg7DcYjKPMJJzsGDy/zcz/4stXqDxx9/HN8PeN/3vJ+vfOXLHDlymOGwz+nTJ3n6ma/gugZ5EfGff/PXabe7+JMA25bEsUESp5imYH19ja3NTSb+BMe1UCpDyIwkybBt76ae3359+jzXhqCmbcH084Es01bqUqYoZWIZFmmeYZpWKWddnX6FbdnkWawhLtIiikJmZrq0WzVqjTqjyS5BEjO30KTu2eRhRr8/JAwLwkAQBps8/OB38dBDyxw7fpI0j7h48Rw721tEkXa3kSJnaXGW2dlZLl68yMLC/NRS/o3WW5pJ3S5IvR5WSu3772udQ4TG39ySSf3FBqlKzlZvDA3Ic/nZn/1pXr3yKhcvpoz9sf6dBMsyyFJKvphECgNplE1j00EUgt3BhN1en7prszDXZWV5kfmZLkkcEkYBcRJPS7Mik8iqJ2EYUOi8xhCQJSUMIcuII70RDdPENk2ajRqGbJIkCb3BmLWtq+z0RgzHEZkyENJCWh5ZXvYADQOlivKTKUqVukJ/6Xc3/TxvtSTb3xivgJnFvt/f1BZAf/pVBuU4ztQ7TuPhBHNzs8Rxgud5tNtteru7jEZaXO348eOMBkOGwxFhmtDtdHBdd9rX0r2rnLm5OUajEXES0+52CGOfKI7ATjFNk/X1TQzDYbe3y9GjKxjCIM8TOvNtrl+9QhQNCeIRCkgzwWz3sLYls0y8modpGLznPe/l3/+7f89TTz3NubPn+Zmf+Rkefvgh/uwzf0oY+Xi1BT7zmU+RJBHbcYRh2iRxShwmJYwgAQSWp70b0zTGtg0NFjb2enRV8K3OldZXy8ubgiRLs9JS3S7BvRmj0VibxyoBQt8EtJCfS5rG+IG+kYHAkAamKTm4coiZ7hx3nTzFYDjg7Pk+hmniT0Z4ykIqjce65557UbnHq6+u8cUnvsxf/5s/z2OPvpvnXvgm41HAsaN3Tffu0aPHOHjwAL/5m7/Jiy++iBBMDTPeaH3bbjH7v3+jKd5NQWxfkKn+rHgNpGCfCFqZTumpjzP9m7+IYCUNXUNXKilKKQ4fXubnf/av8Su/8qsIlTIZ5ygUlmEiRUJCRJHn5EI3tqUBQkkMTBAGSpoEcc7l6z2urfdpNOrMzMww2/HozrhTArDGOeWvFaszi1J6WJZwBVm6uyRM/Alr66ts7MBgGDDxJ4DWYhK2hVGZcuYphr6aygBV9ZbKoFTCLG/tSd3uBqSU0k16FMU+S6xqBCIUCFWgisrey8UyTa2LnufYllUinrX5gyklRZ6TxNo5ul6v4zgOkyAgzjPcuodEsXr9GuPxmDSOEErhWCZJGGpjgjAgyRJ629uYtonITcy8TqEsVDqi3vVw6xbjQUCjPss7H3yQlYNHOf/qKqloYddbRPGELBszCDaZac/ipzskeYhhunTas/zsz/xNfvmXfpk0yThx4hjdroeUIUpNOHv2BaIwx7YaGlqSxMTRGKXqWJaHUjmGKUmzTDfiC0gzRVEY5EJhS6Uz5MzGtg1cp0YURvrGVxTULAtbSSzDJC8KLFvqjJiCJM5IsoSm5SKdlHrdodGolVQsAzHMSulnSSEK7KWIQsX004LtUYvZToPl+RqWFKxe3iHYauB1POyFOqNRzMEDB1haUrTbM1y5dJnaffewenUdMklesilqXoPZzixXLl3hzCsvkqY+0lCY5p2pqnxbmdSd0F1e7/cKqHRk7wSRvv9v9xuD3snrvZXrdq9VFFoS993vfjfr6+v89m//NnkWMpn4UOLUtI9aSpom5HlGUZQNTqkzsizTrilCaDv3wXDEcDTiushxjQLX9ajXa1MBOj39shBCa4IroZ2IsywjSRLG4zHD4XD6szzPyUUTIS0tzaGUNhS9NbMRN1tMVe8PuClDuvXzupUYfGuT/FaYSOUAY0g5fT+e593UEA7DkE6nM7VOb7fbZWY1N9WNGgwG2LaN6zjEYcBgoIcPVllmbm9tlUaemnScjGI9+JCyxBA5BJMxgR9iWArTaRBMRjh2jes3XuXGjWtEqRYmVGmG65p49SaWaWLbJuPJgEtXLnJ05W7qbpOzZ89x5cpVXMflX/wv/xJkRhAOSXNACUzTQwibNNXIbmlaUBhkuSaO54kCcqQhsGx7SoGJEy2pY5v6Z3EYk5kmnufgT4KyCtE3G8dzcaRBGEcUKsdxbaQpCMMQy5YIU1vc9/s9pDRwXQ/PcykKDXGQhiQYR9RqbUxpkWc5jUaDIPSZ73aRpiSNYvzdIV53icGw4CMf+X6+7wMHEJi8cuYsf/iHv8dwNKQ708SyOszNaUu4J598inrdw3VdbFswHPWwnbdYT+qtWkKUrabbXMDf+u/2U3L+YjKpW1c13rZtmx/8wR/k+vXrfOlLTwPg+5PStFHjqKQUZJm2HUrTFCn1JEY3l/X7K4qMQhUURU5WCMLMxA9jtnf3tJHg5sxUlQ39oshRhb7jaoKxW/auyhKOvUbr/sbr/sC0n3AMsF9Y73aN8epYXqNgUOQ3fb77v6oxumPb078dDAZTF5yKj2gYBouLi3qDWRZ5aTu/uro6VRUoioKTJ08yHg44d05zwur1Ouvr6wyHw5tUT23b0Rrujst4MiKMfTBSGq0WzaarMWCmYDDcwffHmKaN42pc0XDkk0wyikIDWRv1NjPtJV599QInjtzNTm+X3/2932V2fo6f//mfY9DrgwFPPvklNjbWdaArBK1umzRNcVxBlJg4do177rmH5557tgxIOSrTWZXjmJgmpHlOmsZYhoFtW6RxrEm6jkO94RJHMShVmnfkOhNTWscpybTMSq1ex7QtpCmI42gKPJ1MdAYl2JuwUtRIxgWYGddevUq34RHFCVeuX8NwPEJ/zCQaYqynLCws8/wLT/ORD/8Qp0/dxV13HeU9732ET336Tzl39hyW5bC5uUkYBoRhxCOPPMTFS+fZ7W2WVdHbmEn9edf+C/hOM6mbR9l7GlN/kavarEopWq0Wf+tv/S0Gg4AXX3yZPM+Ik6jkoqmyb2ABe4aV2nBATKcrVY/GMLSLSJaCknslsnkL5UQjz/d0pJRSIKUetwuBKjXB8yKZZjBV43V/YIE9Lz7YO9cVDurW4HW7dTv4yf7PuQo81WawLWuqCBpF0TSLsm0bpRTr6+u4rsvRo0dxHIdnn312qiiglKLZbDI7O8vW1hZ5qiVcer3eVMiv2WxO5ZCzLNNlsqldbWzPpiClUILAjxj7Q+YWOuSFQgowjIJGs85kMiEMQ4pCY9Gs8thH4z6mYWM58NVvPMErL79Kb7jL/+3/8n/l2NGjvPrqFfKi4I/++A/IC0mSZqgC2p15Tp48yVNPf4XuzCL333c373/f93D23EuART5MyPKCJImQhiqHI4qiyEmSGNtWpYxLRp5Lap5LngmyrCBXoLIUQxUayGmU5aOspHhSRJGWMsBZ2d8qME1rKsud5xkqlbSabRr1Nnmmp3hJmuN6LlmSIZyMuq0lWQxpcubMK2xvDSgKjYX60Ic+CKBBxVnB4uIyjuMyHI74+tefxPNsojABJI5t39E+u+MgdWv/6c9ban3rTKoixuw1y/c3zb9TelJvtPQHm0/v7HNzc/zCL/xN/tdf+VUMU7CzszO16s7zakKncVZVRqWnMxp/pcfIuvENAsMxyfO9YKadbPVdE1X28ijdjE0DKXSWaRh6AlkIfX4saaHUXi+rChj6tbObzEL345/201/2BzDYO/c36XxVn1EhXpNtVRpW1eSvMmoYj8eljnqE53mlkoPWb69UDs6cOUOWZbRarWlQy/Oc3d1dap4HRU6v12NmZuYmkKNWlxiWwFAT27Jx6x5REjEzN8fuYBPLNGg3m8RxzGQcEwQxSuUsLGjRO0Na1GsdKHzSrKBIQ2oNG9uV/MEf/Y728ssdfvwnPsrJ08eQ6Mnqb/z6b3Dl6qsgFSfuOo4ha/zUT/40Dz30EA+88z7yIuKzn/0k//Mv/RP6/T4rKwep1b0SepDqzFjpz9kwzKnCaFE66ZiWJhbbjoFlSeJMf4YTf4JpWSRpohUMPI8kTajZtSlQ1nEcwlCrXxhyz7Y+zxUWFrbh0tvZpd1uMBwOUYXE9VqkVoJd87BNj1Z9jnc+8BCe12QyiTh29ASj0YiN9R5PPfksy8srxHHE6uoNHMfj+PHjbG9v0243MQzJaNwjL+5MmfNNB6n9643Alfsv7mmJsu/3rx9g1LSk24+j0c8JQu6RU/8iVzUSh72s6uixI/ztv/0L/Kt/9Ws4jsPq6qpuZEcJSZJNpW6rBjagU/04Rhp7WuXaESbXmkFVKlUU037e9PNQuhkP+bTfp8tpNT1/hdKSKHtuNWoKDKyOe3+wqYLWraRguDlI7afr6MMryqCZTy9+y7Ko1Wo3vUaFHrcti0ZpJrm+vs6pU6cAprrrnudx9uxZLMuiXq+Xmu0666zkgcejEXXPLU1S97TfK7nbqhxXSpGkCSI2aLZa5LliMBxzsLVAnucMBmOSyMT3tdjcoD+hVqsxMzPD9WvrSFnDMU0yZdCZMWk1G1iG5MbqdZbnD/HAgydBRKxtbDG32GDxQBPjbMIPffhDPPLwY3zs9z/JPfeeZjDY5cbaKo8//icMB5uYpjac2NjYIE4ipCydm41qSmqSJhm2ZZUOOaGefpZwjTzV6htIU4sg2pae+lomlatQrV7DdmwsU0v5SOmWzs+a42eZBpPJBKUEc3OLWrgwC4liQAharRmiMEeaBo5rsTR3CMfo8JEP/wgn77qb7e0eZ89e4OrldaIo4sTxe3jXow9x/cYlXnj+JZaWFjlx4hStZouvfu0rHDq0wquXL3LkyOE72mdverp3uwbpm1lVT+rNrteWe38Zly7dTp68i1/8xf8Dv/Zrv4YQgu3tHVBBmQVo8JyQVRYCoPtIOo3PdPaE0pnQPgsvIUv1AFHlmiApbj0EDW2S+28ORnmnzG/KmqoNfatyQfXY17y7fZ/97cwdlFIUSmGVz1s1xStYQNX0dhyHbqcDgO/7RFFEvV5nd3eXw4cP0+v1pn0ox9Hse8dxpj8bj8dTZ2Wz1GhvNBqloUE0tYgHpnbrlmUhpGAwGNAb9Dh0eIVGvYXvRwwnuzieqfWcTIGQKWmWEscRa2urjMcTJuOURn2G+aUW9aYiiMY4Vs7BlRnuOX2cINrhy1+/zPXrN1hcWCLMNjl57yJeI2ccbHLg0Cz/5Jf/R4Z9n4XFOd793nfzlS9+gTCYcPjQEa5dv0rNq2sIQhZrW6uiIM8ktu1S9+q4rk0cJTSbLSgKoihEIojiaEpvMQyDnd4ulm2TpCmeYxGnMQU5cZSWQ5rKZUjpMtLSN9o8176WfjgiiIYIK8W2asw1DgImr145z8nTh/jRH/lxas4cc3NL9HpDBAb33XsP9VqDj33s9zh1+iQnjp8gjIa8+92P0esNUYVifX2DM2deQamMTrfFc8+9cEe76k3rSe3//5v5m5t/ePO3d9KXqgCG+wPUX2Spd/ul0cGua3P69En+0T/6B/zar/0bTMOi3x/S7w8ASZYnKJVPp3qgmf+y0BPMotBZkVByT0GzyqK4uew2uDVYQHUBVt/neTwdVlTBvir9btc43//8rze1u5UovP/fRukfV9E5qtcZj8fTQHPgwAGkEFy/fh0hBP1+f9pbq8pg0zS1D10ZOD3Pm5aIQgg9HbQs7GkmsHdtVK9r2/bU6jwvFFKauK5Nlhe4jgdGTrczS0FG4GdIQ5HlEctzcxxcmdWE4tEA01IYBng1l4m/jT/xWVywqNUdtvvX+be/8S+wTZckydnc3GD5QJc483n2xRt88cuPc2DxND/4X/0wp08+QBxH/LN//ssUueKHfuhHqNdr/NmffYr+YBfTNPT0VYJlCdK00Hg7G4QwEULTTOo1T2unj8cstNsU5fDl5KlTXL12lc3tLZBCa9qjUFmKyJPpNSelZjYkSVpqU2W4bg0/HNNo2iytzAAKy6hz6q57+eiP/hS/9Mv/E9cuXeA3fv03+Pu/+H8ijn2ajQ7NZhsh4PKVi6ytX6XeNKk33s83v/lN7r3nPh566CFM0yEKY44fO0GhMh588B2cP3/ujnbVt83du5Om9+2CiN4s+75/ExCE/39YOo3Wpdbhw4f4xV/8b/mDj/0xTz31DI1Gk+3tHaLYJ4r8Us+HaYCQQiBMk6IQKCVBuShZoAo1zVJUCRVWooQMFyk3Be5pvw6dcSmB6Wr0eJVF7c+Iq1X1pmAvs9pfou0PRFVDff9jq/LPtm1qnku9VtMKjCXmybbtqQ6V53m4jkMYhtPfN5tN2u22Bl7GMe12W/dMSoCnUz7eNE2azSa9Xk9nZ1JOlQ6q8q5CrpumOfX/E0LQbLZIiwLDMugPeiR5hO0ZjCY9pCXodGYRMuPA3BIHVjoUhJiWYG6+wYXeKrOzC9i2wSCIyIsc05JM/AH93jbr65s4lkur0SYvIm5s7qDIWFxYxPEaGHbB8soCO/0t/tk//2f0etvcc+JuThw/Sa+/y+HDRxmPx+XnpDCFxJAWSiVEUcrRw/Ps7u5iWy5hGOM6LqrQaPFWq4XX8rhxY5XnXngW0zKp12tIQ3Dk2DGu37hOEATksZaf1r3IfKq11Wzo814UBUES4CiFY+qS2hQN4jjjG1/7JoNdH5VLdne2WVjsMj/fwbJcDJmTFwUrKwscPDTPyVNHOHP2ea5cuUwUxWxv77J6YxPD0IyG1dVVBoP+W48435/i39qwvm0wUq+T8ajXkodf+9cVnmqvQV5ZN5kmqEIhjL98QUu/zwTT0OBFUBw4sMTf+Bs/zfLSIp//whepeR69Xp/d3R5xEpWuIAm6p6TF9bUUa0GeaYdXaeppn1RCt8qV7mPoE3nztK/6fm/KoMhzXf5UOLPqo9Flkc7+ipzp8yqh0ceGKad9Lf38aEgDuaa17BtgGKZJo9HAcWsIOUsmQ6J8G+lGuC2LdqNBfzMli0xqVgOBhh4cP36c4XA4VTYYj8d0Op1pY11rvAfTyeDOzs5UubMqgRv1JmEYEscxCwsLDIdDfN+fNuoNwyCMU8K4h1vzEKkijANaMzVmF9rUA0kYT0jzMZ2ZJt2ZLr2+T5YlJTIblAS3XoCI8EwPz/DYXuvjT3zyvMCQNocPHSbPUyaTEdubKZ1Ok4EhGY36eF7Gn37qY7z44nnCKObHf+JH2V3tsbmxycWLF/GcOqoQpFkCKsOybBARpqxzeOUIv/iLf59//Wv/iv5gm5Mnj/ETP/5RnnryST77+OMMR0MG/jpKFAgykjQhS3PyQrB2Y620X88xKDCEgSVdff5kRrPl4jgCw/AYD0MsIZCZwDDrtL0WlumQJj3m5g1MK+LEiWMUhcn/+5d+lQ984K9SbzY5fPgIjWaDMFE88u73sb6+ipI2c3PzJdtCUqs7jEYjFBlxMiLc2aVW8+5oX72lGuffzhL7/lutaakx/X6/4J2YKlP+RU/39q8qQAg0SFMvhVCCZrPBD//wD3Hw4AE+/vFPaJKo5TAY9IhiizSNyLKEJNWZAKnuGxiG5mNJIVDlKPnWAA6KUtRaM7dkKZJ308HtyS7vTXL03bSa+oHENKxy49+c7e6ViXsvmReaeFox2S3LplZvYJo2eWGiTMHRwyt05gxefuklVtev4tBBYCNL/p/jOHpgIOUUzySEmPaQ6vX6tIFe9c8OHjw4nZqORiNapQKntlPXDsFLS0vTvlWr1dKbQ6HJ247NYLiL7drYtsVwNECYBY2GVkGVUnDl6hWSJMZxHOp1/fqnTp3ANAz8iU+R50hhEvopEocoCbnrrmP0dodkeUKt3qSb6/5SngtqNQ/bNrh4+WU6M3X+7v/uFzh79gJp0eOJLz9PEERkaUFehOR5UqpcCIocDLOg3bXozNSJkhHSKHjowQeZn1/Etuo0GnP0+htIJ0MaOos3DJMMTUoejYYUBSRJjGeDYZoIaWJaFlmeEkQTChzSTOF4DjXbpchzsrQgSwuCPOLF4Te5fPUCveE2ftgnDBVFYXH+wnkKpfjZn/t53v/+97O4uMAP/uAP4ocT1ldv8PQ3vsZP/dRPcvrU3Vy9do2Pfez3efa5Z5j4Qw2xeKsR568XDN6uIDEtJ6o+h2HsJQd/OeLS66wqSFXZlMZJmZbBY+9+FwcOLPGpT3+OV145S6fTYGtrk/F4RF442KlDmiZkeVpSQ8om976SkCmF6PYo71t7ShrwuUen2f8FVflmloFITbOtothfFmqemBSaKiPNUtSv0Ij5RqNBvV6fklfvfcdhfv4XPsrjT/w+L599Cs9z8KwaYV/fXizbYjwakySJlqQts6V2uz3tjwCEYTgtESvJ3OXlZbIsY3NzU8Mr9hGPDcOg3+9P+2H1ep3BYKCpMUmCZZtMJmPyoiDyY+J0QpRNmFtsk/kRBw4uAAorAD+ISNKQMPKZm12g2+2SZTnjcUjNsRmMAwI/oii0euj66i6tVoM8zciznInfp1bzSNKUWs2lN1jH82osH5jljz7+m4yGE9oNg+ZsTn+8jmnVSAufAgND2kx8DQ9QcsjSIWh2YpYOuYwHBe/97kc5efw0RW5x+dImOzs9VGqglEnN9UiKlDxPUCX2DiEwLYO0iJFkOlOXWiRPGikFGtaS5hmj8VjTlCyLre0tms0GUsJgmCBkhjQzFhY7pKni0KFlfuzHfoJP/Mmn+NrXP8cP/8hHefe738Plq5f5+B//Mf3+Ls+/8Dznzp3TN47JiEbDw7KVHg7coTnon4u7d+vGuPXx3/66+fmqICUr4rz4y5VF3bxuhmWIabNb450OHT7Az/3cT/Lc8y/wuc9+gVrdo9/rs7m5CUoihYWtILcz0jQqg0nJfBfV9E376OmYpS3fYS9LuvVLCEoU8h5g09B1W9nvAtPU6PS9IEapMV8qzWuUY6n1ZeA4DkVR4DgOrueQ5RmGafCRH/gIP/bXfoTZBY+nXnC4vnoZx6zRbczSjwYYuaDdarE73KHRaDAYDOj3+9OMZzQaTQnHVcYXxzErKyvTwFRJBfu+T7PZJAp8fN+nwq1V8IPt7W0OHTqElFKTgS2T/qCHVapj1mp1VJwhkNTrTcLQx3FN2p06k8kQISwc2wXAth0gJY5ywnFInivazUWuXbtOkqZsMGRzo8/C4hy7vS1qTZPZ2RkUOVIqXNcmCEacv3BG3xQQvOP+01y5fJWVI/NsbYxA5BimpQ1MC4FhWBw81kU6Iz7/5T/EciNsL+PKtXMcPnyEo0cP8ZM/9ZP0hztcuvIcMockjrFcG0NaZFITw4UEy5AkKRRCkKmCPEkw7RzHFhRCkKocp1bHKhyKrODAgWP83b/7i3ziE3/E5uYGUewTBENcz+XAwXnm5hZJs4zPff5PECJlONrl3/yb/w///j/8B2Zn5pFSZ2/PPfdNPvjBD7Hb20EIjRnb2LhOEI4Jo7fJd+87ERiUqlDaUG3AvXLvLwPW/HWW2l8jTX9YZiOqxMQU1Bsu3/Vd7+bkyRN86Utf4dlvPs/CwiK7u322t3cJfB8tfm9PgX1ZpiU3CpVT2Vrpqd8exQVuRo7vBaoyMyr2DizPVYlAVxiikveFJEn38G1CoqaEZgPDNEEoMpVRc3VfIy9yOrNtHnnkYc6fP0d/uM3lay/xwrltnnzqyzQaHgYuURRTr9VJAzBMSb/fY+XwCqPRaIrAr1yIK1R6hYyvgKeuq/FQs7OzXLlyhWazSVEU0+yrapRX4FCAra0thBC4rjPtYyWJHsn3+30MB6Ioxqu3MK2MQmVIaXD02FG2NreZn1+k5jVZXV0jimJswyWNc1y3wdraLihHN6yUDSjW13bxajWKPKe3O6bZahCGPq1Wl5rXptfbJcxDap7LCy+8yuzMHLmQdGdqLC42WF/bYm1tEykkdc8gVzGb22tcv3EVVUiksvniVz7NxYvnWTl4F+957P2cvucoG1tXiOIIw1D4k4A0S0mzhIIc2zbx6jWadh1DuEwmmqxdq9eRZkLN81g5NMdwEJCNTdyax6WL6zz5jRfJc5dmc4Fe/1UUNkmiuHTpClcuX+fkqVMszC8yHG5gGiaPPfoIw0HIzu6QdrdNngRl6T3i4sWL7Oxs4UwMHZxETpqGd7St7jhI3YqLmW7BfaPq/RnV6zbO72DlhZY9NQ172gvZG3lrMOdb3Rt7O5feHGpKfaGcnM3NzfJjP/bDPPzwI3ztq9/g/PlLdDszDEcjNjbWCUMfy7RJ0gjLshFCad2oIiunQBl5JqYo7UpvvHrNig5SBapqEgc3QweU0r00fZzFtNGuVIFlatcURabpETVLC6ulIxpOnYW5WT74oe/mi198gmvXriDMgP/yx5eJ8zH9wQ5CSj2aTzUK3vM8olhvon6/z+HDh6fCdBXtJQiCqflABUXY3NzU2lJlWVg9tpogdjod4jjG9/1pmRhF0R42q6ZL6SgKabSahHGgibyWoFGvMRqOcZKMRtPD9lxcp8by8kHSRGuGJ0lK4IdYjRqmaTHoj/EnMYZhYlsegR/rTJ8cVcSoMCUKYWd7QqfbxrZMgmBCHBlau1waDAJBOA4ocgFI4nidIPCxbK2u2WhKoiRmHIY06nXqtRqj4YjVjVc5e+4llhYOcfX6K1xbu8L3vO99fOPJb3D69F28dOZFxv4Qkpy8UGR5hqLAdesEvpZ8ARgOE2bnG2R5xmQyodOZ4aM/+fOEfsInPv4nbG/5/PhHf47f+u3fpMhtLKNOuzXH4ZWDhEHI4ZXjnDp1isceqyOwuX59C/NYk2Z9hvFkl6ee9hkOR3zuc19gbe0G8/Oz5EVMs9UkzXzyonZH++dt5+7dSYC6lSIjqn7OtFTaM5B8s8/9HV3i9oGzQpgLobl0igKlSn4dcOTIQQ4e/BG2t3o8//wLvPjiGTqdJjs7O/R6u8hIap1qFJYhUEapUpDnJCKaYouqUf2tTADLcnBdY8rb26OOiCkJOkkKkkQfE0rQ6XZYWJin1WrieQ6O43Dh0jn6/joHDh6k2+0gpG7Yf+rxjxHHEUdOzCKtkO2dMdLUwaXuegx2E8a9GCP3WJhvkSRRSXQ16PV6Uz5Zv9+f8viqa6LT6eA4zjQz2g99yPOcpIQ3WJY1DUppmnLgwAF6vR6+72uKT54SJ9rmKU2124pt2xgW2LZLrjIcW1Hkgu2tAWm6S6PewLJcajW3nG4rDNNgPAigzM7SVJ9LPZnUjXOFRaOtjR/yDMKg4ODyPEI59Hd9bWM2jPGsGs16hyN3HWVjY50rVy9RUCBNxfLiDPWGxciPSBJFZKaEYY84ChmPJ1iGw3ZvjdEzPd5x32NkYY6QBTdWrxEnEb4/Rpo6K200akjLYDwcEQUZUhmYpgF5TDAaU6vXmO82MIQBRkFrpslf/f4PIaXN45/7An/1wz/Ar/2bS9QbLmGckGWK3Z0+n/7TP0MIyfd8z/u499538t73uPR6Ac888xJSGjz04MN4nketVufs2TNs72yysXlNm2WEIwzzzhKNt0Tj/Fv9/s0GqT1OWMXvuHm69Jc/gdqP1NYlqu6VKNJE27ObFmBQAjfVtLG5fGCBpeUP8p73Psa1a9d57tmXuHjxItvbO2xtbU/LGs2qVyBzTDO7bZm0vyfleR7dbneaXYWh9vmrNrWenGlPNtM0OHLkGPPzsximfj+KjMNHjjG3VGejd4FmU/dvanUXIRTCkgS+ojtnMJn0kNJia3ubxaV50qRgOPCJfEnbbeC6Dv3eNkJArVZDCMF4PNb4qlpt6vZSkYNbrRb9vnbXjaJomj1VMixxyfmr+lFCaFT5oUOHpn2tbrfL7nBb2zTZlibspjFGBBaS3V6PJI2oJRaOa+O6LZJ4zMbGbvleE7I0Y2lpEaFM0jQiSXJs28VCEoYRQZijKPA8B4VunDfqLQzTYtAf8NJLL5VyO3X6g4gk8TFaFtJsc+ruw0yCXQoV0WzVmZ1bZLe3QRjpzG7GbbG7s4PvT6CAmlsHYTAeR0xIEcKgQCuLrq1dIykSanWXOI1oNOogFFEUo7IcyzDwbJ2lZnmOIW2KLCMOI/q9Hb7+5OeY7c5Tr7c5dvQUs3MteoNNvJpJkvqYAnZ3N8mzhFrd4etf/yKvnH2Bf/yP/8+kiSTPLR588B6efvopvvd7f3DqdvPBD3yIL37pc3zik3/I+uY1arU6Qr6W1XC79bYHqTv52/2PmU6s9nWe9iOc//KvUnIXrfMjhEEYxmxt7hIEIXGcsrg8w8LibAkaKEm/peJnlme0OzXe2b2H+++7l+3tPteurnL23DnOnb3AxsYW/d4AhMCxLTAm7Oxsc+3atekEcH/pXWGFKnss27YRQvu1+X4ACEwTPLdOnoNtm8x057QOVhboO24ZWOfbbbbGCVHaZxwOSZVNlsU4roUrC8bhFlmRIcQ8juPhOh7DUY/JOKThzlNv1LFsi6LQTXbTNKcSLaA5ewsLC9Trda5evQpo9cZut8vi4iIXL16k3+/T7XZZWVnh8uXLDIdDGjVNTK64iZ7nsbW1hWmaU8CoaZrkhdbRysognqbaPdozXJrNFqYpCfwAgY3r1PHcBuPxiMAfYNsmWZ4iVMHMbIf1tU2KIiOM4rK3l9Fq1XFcE0WG16yDklpv3NTTLE84xElEp9PWzfRaTlxs86nHf4/BYIK0MwpiJsGIJE1pdZo4rkKYMbWmSaMxS1FIokmGbTYJxjmd9gKmUefKxlm2t9c0to2CPNfuOaAIghBpSGxpoDAxDRPyAqEMilQ364e9PnGQ8eWvfgqE5NiRkyTZhNXNy5z9wlnSPKIg4vjRoyzOLHPxzEWKIsQwHDY2LvObv/XvELh85CM/imEKFha6SGHpIYttMRxOeO65F+n1BiwuLDO/0OH6jSt3tKPedE/q1oDzer2hWyk0Nz3u9WJWlSkJNHFW7qkgSClLoqyelAmhKp2EO30Lb/m6tQenSyW5Ty9Lo5fGkwmXr13VWcVwwmg8pNvt4Dq2DmeiktNVWJVlUaEwDMny8gzLSzM8+uj9xEnO1uYur756mStXrrC9vUVWBFy8eJGtrS3iOL7JZqoK7pZtIw0DhPYwtGwbhJYjFlIyOzePZ83ynsfeyz33HebZF55ha2sV0zLL5zHIC5NGo4WJw/WrV5GG0OUBBlkiyBLdWE+TmFF/lyDMSJJt6m2TuWUDSxUYKBzHpd1pkWR6MhgEAbu7u1iWRZqmtNttdnZ2dNO89N5Lk4RBr48EsiSlSDPq7RZpmlJvNGjUPI2oLhHz9bqWWen1eiwsLGg340GKFBaWKynSSIvjmdBoNnFde9qP63Q62JaJkFoiZWvLLzc77Gzv0Ki3oJAooQNKd7ZRHneH2dkZBsM+UeRT5LpUDcOYydjHMk0WFmeJ40jrQQHD8RDHnaVQku5MhyiKUCplON7Gsb2SV9jDsFLarRnqtRaqsOilE8Yjn2ZzhtmFDp/57ONM+iGN+jy+PyHPE+bmumR5iGErsnRCmkckmUWj7uB5Fv1+gJQCU1r0dkdkmaLmNYjzmJpXJ/Qjdrd7HF45wuVLl5FpQRBFrN1YZ2e1x3BnhGlBlntYlsG1K1dYmFthMhxw3+kHWJxZ4uKrV4GCp55+kp2dLV45+yJ+MKE70ySJMw4dPHpH++xN96Rerzl+O/LxrQFKSm0bUNwS2PQkaU+1U29ybd0kKtlaqTe9rqCqbOXObJrfzlURXStEvsp1kBCGolAl304I2p0OqjBJc4mUFhJdYpWgcRBi6loLipt8CgSaD2eaHDm6wJGjC6Tpw8RxTJYr/uk//ac8//zztx1uVP0wBSVqfw87I6R2hWl3Orzrwffy3//9/z2FCHnmhSfAiLCcJnEMlukQxyDwsGkjshooxdq1Hq7nEIQhrXaHdqdFnoa4tZS8gDAIWVxx8OomeVSALxiOJprDKARra2ssLy9r9cfS0DNNU+666y4Mw+DrX/86vu/j2TZZnGJJg26zhWvZCKVvnMPhEFNoTFU14avKwsOHD089CbMUlNJedJZt0G7VkQb0ez3iUFKv1SlEhrQEPjnNZgOv5rCyskQSa+MBlC6JpYRjJzSNpSgUluMiDOgPemRZzmgc4KYmtpUSx8nU0HRzc428yEmTRD+/67G1OcCQWrEyywOQEfWGzXg0RhURswsurU4LKRyGgyFJLLBMjzCekKuMeHXMYOLjWF0Ugkazw+HDh2i2PL76tSeQRoZXszEyGPkRoDF7tiPJM4cwSAh8nWnOzMyiVJuiEDhGE0vWuP/uB9le7/HU018jTyA2cvxohFCSySQgiiMWFmaRWLz33d/FqROnSaKUzz7+BJ/6zOMkScLxE0fpdFp8/0e+n09/+k8Z9gOypOADH/i+O9pjdxyk9kt0vJGm1P4R+H46TdUofqM1fd59PSkhtLmlfl6mwesvelVCclWZde3qNUzbZna2g+1Y0+zFNC0Mw2V+fo5Oq4ZhVJpLOod6M6sizuoSRk0BjRXfbj/vToM597Kq6lirMlCP512cVsCz5z7F5SvnGARXSFSGQw1T2Li2SxqltOptZrpLnL/wKsF4QpTEbO/s0mg12d7ZJUoy7TxSpOzuTmg06gR+hJA5KoPYjzHdjEazzc5OD9NUU9OF6pgdx+Ghhx5iZ2dH24oLwezMLKPBEFNIbNtmc3OTwXiEENqTT3Pe9lRHq77d6dOnOXfuHKZpkiSxDtVS4dZcTMvAcW1GI0meZmRZynAywrQNDEOQJClL1gJRmDAaTbAtFyxj2u8bjSZT6Z0szYnCEXGcYJoWqhCMRyG+v47rOJiWwYEDB7lx4xpQYNmG7luNAwQmnuNgSIPuzBymlZKkgZaNrnWoNw3yIiSOcmy7hkAR+DGWZeC6JpPJkGbHpe7mtJo2/iRhbqnOc8+9SKEkpqwThQUTPyKLC1AZYRCXTAFFHCfkuaLm1RgMxnQ6TVZXrzEeRWSZ4sDyQQzTYDgaaNnfoY8lbeq1JmkRYViSRruFMASXrlziS1/5BteubdBqzTG3uMyRw0fwai6O63D36dNECbTaTR5//DN84pNP8LM//d+84fX+bfWk3ig43e5nVQ9ASDnVynkzr1fJm7zZDf12rv39Hyklq6urnD9/nuF4RKfT4fiJoxxcOYgUmnKSF9pLrVJCLBPI11mvlcO5Fdahp1bZtGFcBabX6ECpvZvL/seBzq4cx+GFs19kI/gyRZaTEGFYdf07r4bKCsLxEJWntLszpHlBFEfMzs8ShA5JFrO0vEStXufateuoIqfZaCMNE6UKHLvO1vYEM+3QWuiQxJQ+hSE3btyYZnhFUTAajTh//jzLy8sopW3TFbrJPh5oTp4fBkgp6bY6RHGILGVooyhiMtE6UFpRs5hiqdrtJuNggMoywiBlHKa02g06nRbthpYZDtOErDQPkAKuXV2l0+2SpYp6rQZKEmQhURiXva9a2ZYwGI18bNshTbSbcVEoiiJBYKIU7O72CcOQRrOGZZkYhsBxZ/AnEdvbPSxL4oeS2XmPvIhoNdukacigrx2H01QxGU9o1NvMzc2V4nU28wszoFJsM2Vxsc7q9ZBvPPk5ers+jt0iClOUksx2VvB9PbBI04I00e9VCpt6zQYMojBl1V9FSoM4jrh69Qq/8qv/61T+WkvnuBjSJC1SnLoHIiNVGVEW8anHP8X1a+ssLqxw/ORd3HP/vSwtLnP//fdRFPozN0yXhx9+D6dOvYM/+qM/vqN99qZE7/Y3sPdnVNW63e/239WLonhNqfd669YgVXHj9JPyF4LovN37rQLE7u4uV65coVB69D4YDPjmM89x6dUrHDlyFGmYxEmEYcop9URzuyrQ6s1Lv/3XD1L7m+Rwsx75flXNaYld3KzMWT1HlX0UjsE47BFMYuruLEiPNM0ZjXeJQx/TTDh33qS72GVhsUOU9mh3PQ4fnyeKwxK7lnHiroNcPHeFXOVIaTIaaWdflINt1zBNlzjUipFpqtU1jx8/zmAw+P8x96fPkmb3fSf2Oec8e+557626tfeCRjdAgDsJEiQlUSspaSTN5hl7Iib8zuH/RRF2WPJMhMOvHDMK2yNafqGxKHIkiiu4YW10A71VV3VV3T33fPaz+MV5Mquq0SAKICDOibhdfe/NzPvkk8/zO7/lu3RQiIYnT57w8OFDmg4n5eOs24vdCSE4PDpChgF5viWKoj10IU19fyoIAtI0ZTqd8tZbb3H33l200WRZjIoB6zwUwSnK0mt9pUmGsQ4hfbdzs5mT5xVSBNTVFVGUEEURBwdHVFVN27Ysl0tGozFxlGKMJQwjnBMURU0cJ4RhgpSOy4srwjjobJwcVdWQZQOODo+Zzz7wn5ewhHFLVa9pW02/NybfliwWK65fv4HRkidPzjg4OEQIH5QvLs8JAsu1oz7feudtdCsYjDPKpqEqtoRhRpb1SNKQqgwpy4o0jWhbTV17OWHbTZ6DwDfVPdzFG30cHk4Iw4DLqwvu3r2LdS0WQVHWZL2Y7XbFtiwp6oqoF3N855jxeMjgIOHhyTt85Rtf4l//29/gp3/q57BO8Odf+zPe/NY3we3ktL/3+oHKvac30vM9p0+SANl9v//dJ7z2s9OoZ2U/dpidPTzBAsI9H7D+I68dYPLZAFEUBQ8fPvSASmepmwrdGsqqIi8rhsMJo8kEKRXOtc+ck50ywYsH7mfPrZSSsir3oMfdeXtWsM5z/z7Z6nwnI7xer3FG0xYNm+WWQRYSColoNIEICWONUBX3H36ddNUjGzqOjnukfXjvgzc5vH5AFEWUVcVwMGY8GdDUKUXRcOPoGkFYIydjHn272I+klVJMp94Tb7vd7ku07XZLGIY8fvx4rz3Vy3qcLtccHByw3W5ptGY+nxPEXnGzKDx4s65r+v0+ZVlSliUXFxe0rdcnPz09Q0lJU7cM+33WqzXGKEygEM73BttWYx2kaUKcBBwfHxOGIWdnF/T7Q5qmZees8tRezLFarYijZH8NW+uQIkCpEN0alAzIsj7G1gTK03qOjo7I0j5lqTmYXmO7XREGlvVqTW+Q0DaaJjQslwW4iPWqQqBwNuDqckmWpYSRYjyasFouOX2SMxyMCJXyTs1ZydFRn8uLGcYZWuOnuXledLrm3mnbGv++4zjpWB6KNA0py5rRcMJrn36Vqio5PXvMnbt3mM+v2OQlaabYbNZEccx4PKVu6s7iXXPn7jFvf/urGGfR2pBvKx49eQ9rFNYIvvDzv8QXv/grDIejF7ruf2Du3os8/pN//mK35Mef/53fv/Ch/FDWLng+K/a2y04ePnzIYrHobqoWo1vaVlOWFcaAs/5C2Anr71wy/EXx4m/k45vCs8fw7GOeHVzsMqlPyoJ3wT9NU1ZVyOWqwRrBdjkjjRrGvUPSwYCm2bJdnTIcxZx/9BG9Qcb4IGW9vSKIYTodkKQZeVESqJB7L9/iza8/xlg65PeW7XIO9GiamsViThD6XtR0OqUsS7Iso6oqRqPRniRc7ZQRpKRtGkyc+PfTelni9WbjcUy63SsfLDvXY2MMH3zwAf1+nzRNO8R+QL7dECQBUZRSVluEiwiyCBwM+ilFVWGtoa67DM5ZDg8Pscb3Quu6wpiI4bDPYrFkOOyT5wXLlT9moQVt2yBEiG49mbdpwSEoq4Is80DV9Son37ZYI2gaAwTeFDROiMMEIQLq0hJHfdrG7PXXBd5MtSw2COHt1eMoZXZZ8IScw6Mxw6GhP+xTlFuyYYAA6mZNmiY0Tctms2YwGO1Brr6c7DT3y5LDwylB4CE0V7MLcJAkEfl2S9O03Lx5m1/9m3+b3/3d/8B7738bayRNpYnigNF4yDZfMx732BZL6mrLzZtH/MIXfhlnAz56eEJTr7m8eMTXv/Zn/Nznfvx7Xvc/MOL8k+gVP/TVRTPf4P1fD07q2UHAw4cPOTs7I4qizpmkwVpNUZYURYlSCcbuGuxeh6mqKprObEBK9QOfP9cdy660208YnXs6yXNPDS2eFagD9kDOOI4ZBGNWm0uiNOHGzQPOTs+4XD6gN3wFERmuja+zyWceE5V2DrphSJr2cAScnc2RKmKxnBNYS5r1eOX6PepmRpwkiEGCyxPW6yXGtqyXa8rS26fvsp8gCLh58+a+ER4G/gbbqSVcnF8AdOanvpzaYb82mw3z+dw/r9NV35kXBEFAmvQZWgfKu6u0zuCsYjAY07ZeZykdpFRNjQq8izBYqsrS6/WJ4wTnSoSIsE7T6prxZOgxaKsQrRvC0NOflHIUeUEUR8RJisBvUgLFZl3ubcxVUBFFGbp1OCtpa3/s1oQ4J6krS783II0lVdWyWV1gtEWJkCAMqOuCpq0RWEI1JE4U200JosQJS9brEUeRN7Qoa+IkYhqM0a3uzkvYaZyH5EVBnESUVUlVVQRBQFFuuLzUTKdTsl7K/Q/ve2PWbYvTkk+98jpPHj1hfrXCmBqjQ5SUPDj/gKouPdJdKG5/7hZ//Id/xGh4SK83YjIe8e9++7ef57r+BesvTYv5UasR7DBS/2uhwDxb7p2fn3N6erqfKFlrMVZTViWr1YqrqyWnp5c8fvyEe6/co9dLSXsx1w+OuHXjOr2+5y79wOewIw5/XI/8WatzAKnkc1nYbmPJssxP0KQkX644mPSYHEZEieFTnz5kPk8JAkNZtBD0aYwkDBJWq5zrx9e4fu02i+Wa87M1m02FkJo46tO0Z7StREjL/HKGdVsG8W2ODm+Rhn1wQ+q2YTDw9u9e78l526gw5PDwkOVySVlVxFFEXdc0bQPCy6LsCMTZoI+UksVi0cEB7F6jahecdmVZEMSUxZw4yji9fEKYKaI44OpywWg4QoWK9WrlSbBJSJbF9PopON/7EUKSZQmtViwWl5RlSJb1OvusDCWv0bQtdVX7vmQoCUO177N56ozPkLQGrQVgSQYpWRJzcXHpDVyloio9CHg+27KYbYnikChMCVQMzlGWhsQFSBJCFdA0GhF6kCrCsxiKvGG79ZzD4WBEIAdUVbHnaYJBiABrNdqAMRqlYsJObidJYoQApTwZ3Dv4+A3t+tF1HnzwkD/4w9/3ZG0nqMqGQCrqoiQMAtpaYmpBlCQ8+fCMy4s5i8sK3XzEK6+8Blry6iuvvtBl/gOpIHycwvLszz/xXvr4z7/H/ehf0oLosESIp70bsetdiWce+x9nPQuNWC1XfPjhh/ubQElF2zSsV17LvChKijxnNl/xmc98lul0irWa+x/cZzmbc/f2LZI0Ye8O84nLAh0+jKfqmE+XV930eum78sTtCcdae7stb8POvsz0vTE8sLJzBwbNYnGBIcC4LVLB4dENijzHOMNscUUURbzy8h3v1CIEdalZLSq0hs2mQklNG2mG/ZDhYEjVbr2bjoUAxbCXIp2CwQhtBYvFek9p6fV6PvBkGUEQeGXN7jiFkCRJCiPHcrWk0o13LokjqqpEBUEnrQxpN9nLej1PVO71fCBbztHaK0qMRhNmqyukVNy9c5vD6Zj33n2XdJBw/cYRSRICliCQ5HlB3dTUtSaKMpqmIutlFHmBtZq69uTdwTCjaRriWHL9+JCHH56Ds9RdgAtUhLMS3WjiMKZtvNloHEUcHd6gKitm8wvOz9YEoeDmjdsEskZISxTGFEXJZHJAVWqWizW6tfR7Gav1iigMUYGl10uoG0ugfKmZJAPqImc5bwmDkNYYotDbpAVR5AUW8VO7KIpoao2xhjAKvXejFGw2W1QQUFcNo1FKXlScPDmjymE6PuLy6px8ndPrDynyDW0DKnBkSZ8o6nF2esFiXjMaTglVyH/1X/3nSBHy53/+Ff7RP/ovXui++74hCM8Gpo9TVT4pG/iOKaB4vkT8+JTKAzsdjoZAxuAinA06uVPjg5STeCDnf7wIJcDLFuP7Eh89fMh2vSGOYwKp9mVVHKcMB6brMzi0brhz9xZ37txGCMfh0QFpFLNcrrlx4wYylM9AEXbn0+E5gLb72VPQp0exg9enctT1Fm0aEGavqOm1pHdN+QCtK9+0DTOUCLqyMyIMA5I0AeHQ1qFtQFGEbHPHG2+84ptpVCSpR8CPhinnl0+oKoPRirZxhEGf1eIMbM1kGqECzTAdQGiYb06xjUJVIYE2xD3NfHFJjeTycrmfaqZpSp7n+4CfZRm3bt1iuVgRqJhWGzbbnKapyFs/HQtQJElMXVcEUbwve2UQEsaOqtkgVABSeTnkoMHie4Rt64jCHuPRhDzfsN1eMJoGyAiEUrRtiRBgWkGv36duYLUoKIuK0biPswW9Xh/nLFVd4mgpqxXT6ZjBqM+rr3yKfFWx2RRYI0mTPkVRsVlsUaGXwEY6FIIoFFw7GvP4kSQQESCRFspti24qwlhy7egmV5dzRoM+6+UpUSho6hzRi8jSkCgS5MUKGzmyOOTGtWPOz66YDq5RrS4oi5bWWWxgwPiSv5clXnyuNlRFjdYOqx0iAd3UaOdI0x5WxjS1RqqU6dFtpJT8jV/+O3z9K29x69YNyqrh/PyC5WrNcJgB3t3GGENer6laQ38w5tf+/n/O6ekjvvmtt/nVX/1b/MIXf5nDa8cvdO/9QG4xL9pA/+THfWdg+Y6J4HN0F984/atHbnamnUJweXnJ2dnZnq3/bI9q9z7SNGM0GnHvpVc5Pr6Bt2RvPNUEt8f0TCbj/et//O990jGAV+pEeG0q57z+uZIR2tXPKGr6Br0xDXUjyPMCIQLiOMCYbhePM5SUXS9FsphvsbahN4h4/OiCIPQqCSpQTCYHrBZbrGuJogxjLU1ds92s0Nry2qc+TRR7SZe2KPjo0WM2RcPt45dIsgw996oLCCjyouPZebT+drslSZJ9X2/nEqM6EOZgMKBpG5I04qa7ydnZaaeU+VTBU0q5l3IpimIvjLfru23WG+I4YluUvh8YSPI8J449SPjqckV/1EeFHrEehoooiknjlOOjjM3yIWWxpSzX3Lx1QJLEFEVOkXu5FikVVWmwuuX3f++P0ZV//SztU1UeNtEbZNR1gXUOYT0MYzFf8qu/+qskcY//8X/8f3nxQec17uMkwVrN40dPCIOEzWbb9Wa9tHRdN7RtgwoiDg4O0LpFBb4Zrl3Dex+8DS6k1V7zPpAt2mqiMCbNYuqqJd/6cwXetFaFoG1L07SEoQYEZVmiVMDZ2Qm9Xp93332HLEv5kz/5Ew4Ox52pa8tms+mcl8eowDI8SPixH7uLEgNeeeUl/pv/5r/m/PyEL3/5qzQ1/N7v/QH/xX/697/nnffC3ejvIAC/YND4OGThk572SZAFIZ/+PSUl8q84SO30wwWwzfM9UvrZbPK5IN5lnLdv3yLp5FP27itd6bZcLrss8i8GdT73nfTHok2DdRqtwTlF23pcktcub7xYnmvQpmK73XB2dsYHH9znwYcPOD099aP8pu5kY7w1961bt+j3h4RBwqA/JU3HBKqPbWPOnmy4vCgoC8dmVbNY5DgrMcZx+/Yd8jxnu/XB5/j6De7eucft2/fo90cM+mO224L1eoOUgs1mhcPuVRgODg5YLpfUdb2f7O1UOIMgZLlckiYp168fc3x8TK+XdWJ3W3+TdnzFOI59cHvGgGFHkZFSEoUhCMfh4dTz1oKA7aZEiogkHqFkxnpZsllXBCqllw0pipq8KNDal17j8YDtdst6vSHLBrz88qs4q9huamZXW5paUJUelKp1g7GaovTZblWVgCBNMnTrS0UQ/PN//n/ld3/vd+n3U4xpqarCOwc7S9N4zqFSMYv5miIv9xCCoihBCLQ2NE2DVJ7o7NAMhynGljTtGqFq4sQyGIakmcBRUzfFnui948ju/k1Tb+a63W46E1ZL09as1yu22zXatPziL/4C168fUZY51vnScEfy3uHwJpMR14+P0Kbl3Xff4Wtf+yoHhwf82q/9Gnfv3uNf/+v/+YXuvR/IiOH7gSN85+M+GRf0yeDNp2Xl/xoa57vS1VtRPW+WuvvdjsunlCKMQqIo3kuoCOGwjUF00IPNZusZ+p054yevp+dBSO/sIoTXo8q3Obr1Nu2j0Zjz83M/lRI+8O0UPAUhcRxhraAsC9pW07YNjhZHQ5K8RFFumc0v0Lom6w1YLOcA6NaSZX1wkkF/ijYledlQlg1CeP/AoihYrecMhjHjcZ8HDz8iHY5JE6/kWK5XxHHmlS0Tr+5ZVTVJ4qV5r1+/zna7pd/3tt7f+ta3WC6XrNdr7t65R9Q1z+M46gYV3qYqTdPuvXjBv7qun9Of2n1OO5MHhyPLEqRy9AcpcRxx984tHj96xHK+Ioi9dTnOsrjaMr9cMh6PGQwHvPryS1RVTVVXzBYrBoMhVdXgrAAX0NZeSUKIhH5vQpakrFcbyjL3ktCR4vbtmzx58oTBYOh7XZXmqllwdbXk8PCIrJfS6hqlYoRwRFGMEIo07bNcrGlbX/5rbfZ4uCz0Jg/aNUjnoQSVLmhszdHxhNVqTZb5AU1vZgxghQABAABJREFUILGtx1mtVjOwEbp9OgxSSuKEn6Tv5KGNMURxiBCS4bDPf/1f/1d86qXP8OjDU1brBU+ePEJKun6f76HWdYMTDZeXlyTxhE9/+jWqquSrX/0Kg2HGjeNb3Lt394fvYPz9YKR265Mzrk+2w3q+Ed+Vex0uyUf558nEvo/jb9od8vvjtt8/iuWAtmn2H+yz58VYs1ME9x+YY7+L+2PuApm1COdH6avVmjg53GdS/t9dg3wX/Pz/11XN2dkpN29eY7We8+/+/b/n+NqnOHly2gUvDysIwwiHQSmP2YnTHpPJIUHgG6rbbY4QUNUFjx49RCpDZZbcvnOAlHA1u0R3vDRjHXlumE6PMEbTNl5EL89LptMxo/GAslxx7dp1lqsrTp6cs5rNuBH1qLUiX5dEbYLssr0wdgyHA1ZruwehLhYL4jjmzp07eyiBtZZB3zvBnJ6e4pxjtV4wn8+9wUHTkGUZRVHsy76qqijLsitfnl5/SilknNLohkQ5WqeRSnutp+WC2dUMrALhCMIIFUjyTU2aJRR5jdaW6XRMECgylWHclKr0P1/pLUVeYYzFaA8lwCmyLO02ArDGsd4sUUoyGo2YzRZ0gzis9KX5fD7b02V8d2PHwVSMxxM264I0TVivffZorcQ6Q9NUxGkGEqqmwjnNdrtGKRiMBqS9iCz15ynJBMIq2sYyu9gghecZ7tyGWl0TJR4FnmXZXkzRWksYep5g01T0+xknp49p2orhaMDh4ZT5fMbjJw/Z+zsKw2az5a1vvk1xT7Je5fzdv/d3+I3f+J94/fU3+Ou/8nd47bVXXuie+4EhCC8SDJ4lvO6+f9HnPjVb8N9+EjLb25ZXe2VGrTVh+GJQ++93+ZjhO2XP+g8+RRl3Jp48jx/blYV7rh7P13ar1ZrDo2mXIj/L9/nO4P7gwYf86Z/+Mb/8K7/A4ycPWSyuuHf3c/z9f/Dr/OEf/iGTyYh3333HB237dDIoOgVOpRRSKOJY0+unJMkRi+UlRbllcJDsBxM3bh5RVQXbbe6tkLKYusn9Tu4UWvuLWggoiq1n1YcBm/UW18+4efMWw+GElojV7JSgmwFIoTowpKdjVGW199oLgmA/lZzNZkwmE1rd7nFcRVFAB2TcKWF609EQY9y+1KiqyisnpClhGFLXNVVVEnQbWJLEKBzVZs02L3ypl0RUpQ/KcRQRxwnCFWxWGwolUAryzZa6qZCBR3RXVU0UxRjjN5Gdm1EYBhSFRgjJnTt3sNZycXHJxfkl680KlVdUZYOUAVVVE8fhHqpgnSGOQ+qmQiCoyoowjJnP5wxHQ64uZ0SRR+xr0zAa9fwkUlrCKMSBd2bOYrSuWSzn9Pt96qaibitMbtG1pW0dCD94ElJ2NJkWqxuaxhK4YH+Or107QndSz71+yttvv8l73/qAr/zZN5hOJ7zyyku8//67nJ6eEAQ+y9O6wImWyeERugnZrLfEccK/+3e/jdYlaRbz3vvf4id/+sde6N77kcsHw8fKxBd/Vte7eYqcflb1UgjYbDb8y3/5L/mFX/gFPvvZz+5r4R/FekY1Zc8//CR3lt173QWy5wGU/ssrE/jnbzZrTzzt97/LX34arCaTCZ/97BtcXp7zpS/9IWfn59y+9Qb/7X/7v+MLX/hZ/uk//afspFm8OYACAoRUSBl4vXLr9qaf/X5G1r/JYnHJZjMjSDKSJPLBBouz3v59Nptx/dpNmqbyZpG62fe7hqMRQaiom5J7917ugIAR3/72u2wKR7G2XOtdo09KEISIQJJImM3maO1BhUVRMBgMGI/HvrciJZeXl3z+8z/BZDxlsZgjBCRpvO/VHB15R98dTmxnY+Wc64T9BHmed1roCiVDn4E0LUaWxKkgThLG/QPm6YazJ1dUZY7RmrbRBCpEEqIbTW0bmrol68VY7WgwCDqbLwmDfh8pFXlR8NGjD8E5Dg9uU1UFURTS72c4d0CaDFjMtx6fpHdgWh8kgtAHniCQJKmn4FRlTdNsOyyWbz7P53Na3eKcIIoUcRIQRAorvfPxYJShlKOs8k4dQyGkQqmQstwQyQQpQGIRBCRRRBxFWKtpmwojJUIqtG666XHFYjknjr3fwLvvvUO+qolURpxEezWPIAgIQoUx2lOUGsfV5QprYgI5xjnFjZtHPHryAd/+9pusVku+8PO/xOde/+z3vPd+aMqc8J0l4cdhC9+J8/mL/h4gn+/7PP+3vLjZF77wBW7evPliL/pDWJ5DuKO1PPWw2wWmfcDiY+XuPpB5bXIpVac1DsvliizrfQLR+Pn3fHR0yHCUcjU7o2lqlssZX//Gl/mZn/kJojjYi6k99f4DXNC5xDwzuHAQhAqHxZqWi4tzNC2j6QGLeU7baIzdlUwBcdSnLFukDIliiQoD38EXGm0aVustk8mEsqwYDaeYZuOpIusWZTKqqmXSH5EkKUZYbFnR6pYwjPaTufV6zcOHD1FK0ev1EELQNk/NJYIgYLFYADAcemxXWZadHx/7CWHTleJN0+zR5845tpuSMPEGB0QtKjBU1Yo2jRkMExZzSdM6rG073a+WtukwcIGXHLZWIJTywMUgwBqLkIKmrRmNhggZ0zSCXi+jqkrCMCDNEm/JHoy5vFjwxS/+Ep9548e5/8FH/NZv/SatqTt0ve9bWaf3PMzRaEwUeczYYnEFeK880PT6MXVT0OqGOOvTtD7A1XWJlDAajrHOUuQVSSLp9UY4Y+glQ59J5jll0Xq4QdsShgJjGiwhOK//vt1uWK3maNPStjHgN4AgDBkPR1xcnPP48Ue+5yehLGuiKPKuz7ohTQbcufUpPvPGT9K0NUfXBlzOPkIog5AtP/dzP/FC99z3j5P6ix70SX2rrkT6QTKp7kWfmX6Jp39DeF8vD0SL2VlgeV+4XXn28df6yy/H84Tq7/iyPpOR+4N+GrT88zvlAaWwzls2XV1dcXx87KEWHWbKv8qzJa7/N459+l8UBQL49jtv88//u3/Gj3/+Jz1EYv/QruHuRCcb4jrAo4cmyI5mJKQkjBSBjDh5fMVoNMCaoJuYWZpGo7VDOIt1miDwNt5RGBCGfsddr9Ysl94x+ObNGzhdEagE4RxRGCOlomm8YcLl4oqrxSVSyH2jfFfSffWrX+3ULEuiKGK9XnH79h2CQNG2zb53NR6P2W43AJ3sjS+pi6LYB6ZngaHXjq5x8uSCyaRP3rTEg5jeJEZKKPOGgJA7d4+pcsNitka3ju228hI7YcBo2MfYlm2+wkkQoerOncLaFiH8JGy9XnmJYXkIcczp6RnT7ZC6afj8536CIq9Zrdb86Z/8KQ8ePGGXXG82G1qtyHoxUeQVNHzmG7PZVFhnKDYbBv3hPqOUUqB1w3abU+uaKEvQxtudBaEkyTIePzonDCLKyhIEKWGY8uTxOW0tyZIxrRJo6+3sW914lyARoAIPnl2v13uFUmMMQei9L199+VVeffkN/vhLX2K51J4T2Ppg640vFL1+jx/77OcZja7hnONnfvqn+ff/4d8wGg3RpuLv/r2/xfnlE16988Pk7j2rOPfdIs13Q06LZ3BPHwd3dutZOyYhlG9AYhGiRcjO6dQpv4NjgJawB0l2RNNEpFmAE3n3VzL8Ddp2j//hVLUf58rtpnnPurBYKzB6J8HyFHAqhAepSumQSuNMi1IevFeVms2moD8a+McIiwAUT228wLvNWCt4/dM/yc/81CPSXsr/9G/+J+6fPCCvC9grerYeEBtotKuJZYaSCiUsQoGwIG1IGPTYNjk1W0aDIevTOYOBYjQcUteVp3O0LYFS6LZCCIFpIg8I1ZCvDVkvZNCfcHFxgZRwcXaBNRn5UhLWMUqASgxa1bSyoTYFUlmM8edlp1Kwy6iyLNtnQQhHf5CR51tW6+Wep1dVNbPZgrquECIgShLiTq6l7CyvdKsJhMQ0LS/fuct6tiFUgkE/Q2WOzWoLUpCmIa1eML7uMG0fkoTFfEMSOpwV9PtDpFAYo3BN4T9HLEI6xuM+i8WczWaLFDFGpzR1wq3PfI7bN6f8+9/5X1gvWobDPm+/9W2qsuHN2dcIg4TFfI0KJQhL21bESQrgQcAuIt80FNs1/d7ES5oYQVUZ6mZFv+/dmXERgQyIVIqucm8CGkbUeUMTQMiQYqUJVMwGRS8VrK8qmkoRX1NIJxBomsYiREhTJWQjLwc8Go67THXDeDKhrHK0rrl584jGFvz2f/ifMdpRtCVZktFWHk5htPMW7brho9O3uaNKnpy9R9Fccf/Bfdq24tr1Q7729TcZDDO++NO//j3vu+8bJ+W/+eSvZzFU38/X7vU/CYv1F2OIJFGUYo3FD3h+dJO93dv8eL/p2R6UD15PS8FdtrI7rN3R7QCXzwa65XKFkl4m2O76SsD+BAiBcRbTyf9+/id+gihOGPSHzGdzXrr7MiDxyVRnpOp2mdnz53JnGdY0DVkvY3o4BQE3b96k1+thrdmbGszn831j2/eiaqJIYm0nD2MVvWxKLz1A0ke4nifDbnOUCFAioJcNePml11AyIQp76EYQqHDPw9sNPOLYQzHatuXg4IA09TCB5XLJycnJc+fe9598Jmis1/TafQZ5njMcDvfDlA8++KAr+6AoKpq6RWvYbkrm8y2z2RqtJUVRdj2hiKyXkPVShLQIaYkTRRA6ev2Ig6MRh0djsl5Mf5CRJCG9fkIQQBgJnpx8xB/80R+gjaY1hiCKyLI+QZjw9/7erzMYjonixHPuhCSM4o5oHlCVtbcgS7Nus4a6qva8xDCI9t6CaZrR7w8wGnQbsF036NYxHo8YjjIODlNUWLItHrPOH2F0y+HhAePxEN02SPl0INU0Xh+/zAvWyxUPP3xAU9f0ez2cdSRxQr/XZzlfea33QY/P//iPMZ2OSTqeo4oUg1EfIR1SKZbLFd/85je4vDrjrbe/ymp9RdPWFEXBm994m+Prd17o3vtLpRjf2Sf6/gXtnn3uJ0MWOkjCJ8QfKQLOzy8RR4LJNPHp8w5f9UMWxtu9s92NsDvmvdJAd4C2o87slAjg4/CKTtFzl1s6izWeQrM7XLkbGnzsGAQCqRS6rjDW8lu/9Vv8w3/wn9CPBjz48BFxlPq+yZ4y5DpEutt/7Y5biKfSx3EU0ZtMyNfVvh+y2Wxo25YsyxgOh6RpilSgTUVVO4q88nInRUNZWKJwSF3mKJESxxuSxDeZwzDGWsnhwQ2enJxQ5BYhMpq69mJ4+P6HlJLj42Ourq729laXl5f8q3/1r/aYnd31dXV1xWq12mOFiqokVIHPsropnjGaKAj3Bg/bbUVPhVRlzbZtEEpSNZZBP0U3Ifna4fBQlrIskCLAOku53TKZTnCuoTcUXDuasN1ucdSsN1fEScTR9RFhkDKTS4q8wVLS68UkaeDddhDEccaN4zGvvvoaf/SHX0bKiEFfUbc1AoXAO6soGVOWta8anKCqvJGqUo71akUUK5LEY86K3A8phAzQxmGspK4NdrkiSSXDSUAQD9nmEmdrjG1odYs2vt2gPCwYhP/MZdBBH4Cqw6U1Tds5b2uslaRp0sFrHCdPnhAEktVqjRSK/iBFCuVvFuno90e0bU1RLmlaRRj7z2s4HJDEA3rp4Qvde/9Rpnsvsj4Z0f4XZ1J10/CNr79F+arizt0pSgQ873v3Qz9I3DNBCp7nHu6neMIHq51M8A5hToehMl2w6PQxcVjiKNx7i0okwonvULKwgHVeBuX68TH/5D/9z3jp5dt89tXP8Kd/8mX+H+//DwghQXhirnMSYT04T0ixR8zvApRzjqZuqJuGpq6xWu797nZKAmma7oOBQGJMQNVoqtJQ5FvqekkSZ0gRsM0L76yiSqwzmNaSG0ccRmjTslqtSdKUqNXkRUmceJDmrndkjNn3qLTWKKW4fv066/Xan6/OTLTX6zEej/el4mQy4frRtT1K3St4VkQDD0cZDIbkG0NZeOOKs8sLsuGAIEg4PVmQZRGSIUIZZGoZjyHflmw2K9I0BdEymfa5HnmaTdYbsVwuWSznTCYT+v0hi/mcwSih0TlClqT9KXne0rQtWT9DSEVZNfyf/0//DOMUIAmF54MqFVIUDUVRd+fa0TbetdpiQBhUEKACQRhGVFWB1t4MNoocSRohkFjTYFoPNymLGoQkCCTTad/rSJ2XWOfNUNumIYojbl677vW9lMVZgema+DuAprOCUMWApCkbbOfNKJ0g6nlpFp+Rua7x71UfAkLWyy2TgwHGWrSuuHnrNs4EZL2Uv/u3/yFf+Lm/9kK33QuXe5+UJX1S2fa91ieVe5+EKH/2+12v6lkzFIejKjUfffSERx+d0ram66n/CHWnutLsWXzU7j3s+lK7RvmzoFXxbK/O7YCoEmO8642zBmfNriuP0w6s82/YWVynnCdwSATWaLIk4TOvv8716RE3jo75ws/+vD+PUnU5mc8mhfPDht3xWeclnHcg2CAIMNqw2W7ZbDZcXl6yWq32gXg6naK15uLiguVyS1PFpPERRodEYYYUgqJcMZyEvPGZWwzHgCz5mZ/7LP/4P/173Lo9RamWy6vHrDczVGBJUj9Z3L1+WXppm+12u+9N5nm+hyTkubeViuOYl156ieHQ21nlec5gMCAKoz3CPE6SDtjrsyLv0nJG0/iAMRgMSNMUoz0JvG0dUdSnqfzprqqK7WbrjVJVRF03DAY9lHI4WrQp0aZiMEw5OBhzeDgliiS37xwjREu/H2IpqZotaS+itS3L5YL1ZsPb3/42eVWy2S4xrmWbbzpAqwUniMKUutI0tUapjnYlHHHsXYhv3bzVwUJipAy7SR/gDHmx9sj/1ZbVoqQqBbbtUW4Dim1IFh9x795delnmgw+2c6+2PrvSLXVTYY0hUJIkionDiNFgiDWOQIbEUUIap2Bhu9lycXbOarEgUIqmaVhtVjRtTWtawjgkjGI2mzXaNISxYLm8YLG8otfLSOKEL3/5Ky902/1AUi0v+rvvB6X+8ZJIdCOuHQZDa0cQ7JQoNVJJ3n33Pm1jefDhY5raEEZd8/37B8d/7+PjaeN897W7yT15+CktYE843vkG8nyW5WVmVEfbAGd115DthhL+mqXRNXXttbSrri/R7/fJsowwCAh6PdTHpp7GGgLh9gMKIXg+y+MpfdsYgwwl0+mEJ49zNpstvZ43YNgZGMxmMzwIMiHftrQVVMWGprE4V+OA4TihrNe89OqY67duo+11siSkblYMhhG5a1kszwgjg6OhabdEUcB6vWY0Gu0diafTKVdXV/vS7uHDh53UjNoPKMqyxBizx0QNh0Pmy6WXlDEGozVZltHv9dCNL1fXyxW93gFGSPp9ya34Bto6Hj2+oGk8yTaUkkrnlFVOXWuSuOfVCnAYA0VeYqmIogDnfA7saTktUnqBwcl0RFHmLOZLynoDwl+zVV2RFx64qVSILTR1s0E4UM+4+ygVEEUxeb6haWp6fY95EtLb3nteYoCwgiSROGe8C450xIlABSEgcC7g5NGazdISxf78bZcVB6OKJEmQSntZ3zynqrfPXRfOepOGuq5JkhRrHUnkgbFlVVLkNUEgUR3LozEtQTe9lkqhrcFiWa4W9LMeaRYQBg5na2/Kalq+9e03efub79E0gr/91/7D97z3/srLvU8a5+9/3t3gYgfu6cCdSvkm7kcPn3j8jmtZrRr6o5gXVft70eN6bnU3+y6bAvY3z/PkYv9wJZ+qYz59PZ/lGOOJvVq3tG3FyeNHfHT/Q9brLbOLuRfO2y5YrVa0bUsYhty6dZP1esNnf+yz/Mqv/Ar9wQDhNNb4L61bkB717nZTKD7mxbdr1ncB1Vh//Mc3jjHtOUBXRkR7ztxutN+2Dme3pKEHH37+x9/g6NqI5eqcqt5Q1WuMlSBiLi+uKFY1Svu+xqde/jQXl3PatubGzeu88+0POjK03vegrq6unvt+B0XwiqeeojEcDveN481mQ6+zX086VLpSitFohDXe9UXgTSrCMODqck7QS3HSZxLjcQ/drmjagqoCEbakSY+6Kjk/XxAGiQe3rmq0Lcl6PqB7rBzkecVm7TWrrGlRgWDQ75OmCUL43pIKGtbbGYGKiVJJlsUMxj7DaPKWKAwxRqONpChynANtNP1+ihCeN5fnWx4+/JDxaNpdO8674TjDZDIkCCVBLBF4ET/tNFXZYI1CqaaDFATEShPIPnGUIrHk+QahNFJCGPaQIsDoyk+CpcJozexyw3g8psi9lv7R0SFGa68okW8RwgemsizpDQc44VBBSL/XA+sZAXEcUDfQ1A0CQxRqRFATvmDT+IcK5nyR5/xF2dXHy8ZdgBJCEO51lwTatHiir0WKgNVyw8nJBbfv3uMHSaM+6Zg+8Tg7dLPW+jkk+S5z8hmW2VNjduz8Z1/TdY45zhqk6IKcMbz7zrd58+vfZLVYk8Y9EDAYpKRpwo3DI1QQ8NrLn+LDD+/zza98jVfu3CMMAopyyWazxciAVlc+OAmLV140iL0u1e4teJzUPvA7x3q9pq4qP9bGZwjz+ZztdgvAwcEBm82GO3eO6A8yoijkrbfeJOsLPnz4DkJYpgcTNps189kSpfroxmErR2AgTcakyYjjaz0ePX7MsD9lMLhEqWAfjDabjS/Xup5YEAQdz222n/5FUUSaevxOVVX0+33foF/a/bkOA5+h9bKMpm3pT6esFis2rc9s8nxNNvE8veE44eBgyvn5BXmxRGlBkvQ4mA7ZrhxNZci3WxZzzWgSE0cpbW2JYj9hWy23hGHMduM5c/1BSlXlpGlC2oupqgKlQobDHkIEGK1JUokxLcNxSO4gjRPvSCO9aYM2LUkS0h+kCGFJ05gw9PLBXoJG0zSaJInIMk9ez4stZVUQx/56CcOE8UTSNhUOQ5wIpKgJVEZdanAKKRVBGHU8T6/W6RB72tFO/VQI0en3R13FYIiCiLpsSaKM1rTgDNNphsFSt57/l/ZSIuldaaqyJQhTkp6X3BHCIANLGP2Ig9T3W8p9t+c+V959xxP9f3a/M9YrAODg9PSUz372Da5PX+P/+xu/T1nkWGNRn+QP9UNY+wDzjLkmPE+N2bmH7NbOX/ApVMF2mYvXExLK28YrJRgO+3zmjddZXK25dfMug0GPti06/JGXyH1w/z6r5RIlJP/qX/4GYRiwmD3m6MZNVJISBBI/TOrcH3yr3Qf3HWdwB2PojrksK1brNXVVMup7y6UdtWS9XnP9+vV9ZvPap+8xW93HaMfLnzqkKGdst0uCIOajByden0oM2Cxb2sYSupj+YEISZDS1IgpTrl+7y3JR0O8PWa1We+qKUop+v8/9+/f3Ol2bjQdsehsof40URbFX8ez1eoSBp4yURbmfVlprvdX6ekPTNMzmc+7eOaI2c8pyTelKsmHGdlszHh0SJ0+xbYvFCqyfnI1HR4RhyLZYIBDkeUsYlVTVpUffRxl11eKcQevam6EW3oKqdWdcOzwiTVP6gxFNo7maXZL2vGHsdltz7foBzijm8yVRJIniiP6gh+lkXYIA6qYgjuMOirGlbey+vDRdyWadI8uG5HnJZDxFm5agCwJxGhLHHm5S1w1to4AQoy1hEAMagUV3vMxeP0FKTymyxuCsJU1SqtJzZHVjuHX9FrOrGY1uKMuayjT0BxlOCaQKsA7y7ZbClQgC2sYSBCFhFCCkQfUjTFujTf1C995fSbn38YD0rE8cQKACMA4RKmpjaJWgEWCwhDiUs+j1hof//W9x/Ms/yz/6L7/ILF9gpaLGELgWZQS6CyQS8x39rme/981us+flaa33o/A0SUizjG+++U1+73f+kMFgwGDQRwTda6inZZ6Qvtp0QqCNfu49Cuf89E77bEtKBUJgrcBZyfvvfoBtWxSCi7MPuTgTxGmfuqo5PDrcN5V7vZTJZMJ6vaKuSgbZbRrjOBhPcK1BNxohQxwCi0TjA6RQAovBYUDhewfGgzptKcFqWlMQqCHbVUDbtNSVRJuaQWa5efsQEa0I0x6zswsCFWJlRNKbcnExJ4kzrPBgS+QC0CBC6roikikfffSQV159FdAY6x1jdsGkbVtGo5Ef7XcBcjKZcHFx2XnclYAjTgJMF0DquiLLegQqJJSKTTehdB3ReLlcMhyOuLy8ZDAeIkLfzLXGW21ZLK0WXF0saGpNLxmx1VuiQBFHIdlQEaYtSSxpcUSJIo5T6tqx3UoOpiOMdrS6JUlipgdTqrpABQm6aMm3LZuooKpKsl7E9GDA9Gjqdb6spKxy0nRMqBJeCm8yn63BQWNqnDXeDqrRCCTC4ZVLtSBQKUqqDuaiaFsvUNfv9wiEYbve0B8kWNNSFwVK9pkMjsiXF1SVQQqJ1luU8nShVpvnRBvzjmhtkWgDQoWoICKMIQhDfu3v/zr/2f/mf8t/99//33jrrW8grEHVXv1BOogIUS6kKRqEiEmyiH6i2JYrnGvpDzLqyuBQaJu8ULz4oaogvEh29Rc9b7cTOmd989hagjBEhQGttQRCIJylrWrWqxWv/x/+CW/9P/89/a8/4jN/92fBCIK2BWVZBwJpJVHXL5JSUjfeBWMHsmy1RkmvPiBwNG1LWRT80R/9Eb/zO7+DUop//I//ETdu3OSdb32L+x/cZzqd8OlPfxqtWp8pKfkMXuoZ8nE3QdubJOyodF3JKLoAJZzn8yVJws17d7k6P8dZQxynlLUhzVLW6yWj0ZD12usbnZw85vDokCxLyFeXRGnciZN1si4dLcY58Qx2zE9EHT6YRnHkA3KjUSJARim6NZimRjf+5ovjCOtqbt66QdNsuZrnLNctOEEQRWht8Kgu2U2nIm+rLixhKBllA4bxmDTsc3U5Z7Va+iwPizHtvvntBda2PHnyBCEEw6F3FB4NRzRNw2g0RCkJwqGU5O7d2zx8+Ji6qri8vKKqi/153n0WxvqyLAgDGmdZrxc4CXleotIIaz3OTiBp6gpMRZjElEWFNcKX49LStBVaN+htRaD6lGVDEKTEcc9Tc5xXBm11xWjUYzAYoJREitwTuHshg2FMkilWqzlRFKONZjQekS+3zPIFgUpI0oj1qsAYtx/GaANpkmE7pQUpVTca9g461gmC0A+KNuslvX5C01RUpSbNEgKlMK3DtKBkyjq/IvFeDh2/se0gJj5zHQ0n1HXNZrMhTbPOQNQPR6xzHN+4wcnpKf/sn/9zvv7mW/T6KfW62UNasA7TGpAWp/3G6IygyAt/zUUBRedI3R8MsZ0J6fdaP9RMapehfL9rl9Xs+go+K+k4Z1r7CC0kaI3sRvJv/+mfM7mM+cV/8vf593/4x+h33uezP/cGrh+gVUtqAtBd78U5mrpCCNBVA86yzX2T8snjRx3gr+bhw4eY1mdRL92+gwP+/E/+1Kfs/QGf/5xnbJdlTpJECOHJwvuSz+4ixK78e7pL7Th71lqfZQkBUiA6+MFoNOKdd99hkGY0VcFms+X45m2vQHB8nY8+esjNmzcoy4IkDXGuZbXeMOj1eHJ6xmB6tLfJ2n8egOj6eO4ZMOSu8e8f63mGUTJAhjGnj+cINK0pyVLLrdu3sbalqmrmV2uG42tsNxtwjtViibWSo8MDhsMJeV4wu9qi9ZZhb7Q/lvV67Y05OyXQbbkBvFtNFEUUHZXlWScef3N4Ltgbn/k0ZZlzdXXBZDLh3t17pGmPt99+Z/9ed4YO4MGhO4hCFEX7vp+X1w1I4gAtWrIsRThJGveYXS2pq5YoSghkzGgU+WyyrjzVyViUjMjSiLJ66v4bhIKiWNE0DSroo01NmoX0+gccHIx99mdqtps1beMY9Hu0TUGWpFTBFiFa1usVvd6YOIn8uD8M0a2E1httRGFEkobk24pe5t19EAIhLE1TE8Uho1Gf4bCPsT2vVhEGWNsghKNuKi++10n4NHWDUmHXV2U/mVZy68GxRbH/7KIo2gsMTqdT3n77bVoHrTEM+lNOHpdo3TDo9xASdOPVGBxQ1iUqAm1a4ixAt97owWOpau7du/dC8eGHXu79ZRrsz5KYhRQo6WEIgRAI7ftNonEszy74xV/4ItWXnvBb//f/gc/+g79DngjeOXlAT2qEbdmuc7QIOTk9oW0q2qbl/Pyca9eOuLy8QkpJksTkeUEYBgTSX4jj8ZgsjFFJtm8getPEGoxhMpmyWK1o6orAhnunEmsttptAekKvn559XIjP9xK8YiQWhLM43VLVBS+/9BLL2YzeZIJ1jvnikvFkzKNHDzg8nDCbnaN1y9HREZvtktFoRJXnDIZDev3eflS/+1CF33SROzBph8LfZXiejBsQhCF57qdFHnHcEoQNw3FC3a5o9ZiqMoyGU8qyoN8fUFUNYRiRxBm9npfZ3azX9PsZYZgQBSlOw2q1Ig0H+/5XWeVe28j4wOwJqZLT09M9Nmu73XJwcICUnoT89ttvU1UlSRpycHjQORN76s5wMMCtzf551lqKouDg4IAPPviAa9eueQlhJGEc4hrHerMhGyRcXFxiWksS9dCNxgoPzcg3a3rZEGskxdYbP1jXcnE+RwhFEMacnpwyGvfoDSLCWJGFKecX5xhTc3Q05fqNKevNJXHjM9a6ahAiYDnPcc6DLIeDAWmSgVgghWMwzLAGtlvvUGOMIYi8l1+/nyEENE2Bax3G+qlckkQc3zgkSQVVtcFYzWCYkcQpSokuwLZe/DCOicKEQAVkWQ8hJEXhlVqfJWgDe2OMOI4ZDLz44AcffEBZlhzfukle5nzw/rcJQ4luDav1in7WRwUK3e7syQRhGBBGCXVbYV2DsS2TgwlpllKWBS+yfuiZ1LPr+82qdqN8IQQIh3UWiWR1NUfUDevZjHa95Mtf+kPK7ZpP/bW/yS+99mt8+V/8G1774k9x//33yc2KOjZspSQmZRAGrFcL0ixj1O8RAMpZTKsp24aD6RSjDePRkJOTEwZpxuz8goPDQz786BH3XnqJq/MLrl+/zmKxYDwaYnWNbnwpYbtp3U5h4CmXz0sEP6txtWueW2c7xQLnM0PnL4YHDz7k5vXrVGVOVdf0BgOKYsPdu7c4Pz/n8OgAsB2+aMj5+SlREHdSHS2t0Xst+KcBij1L6JlPZn++0zTl4OCARmvOLxbEsaSsV9y8dci9lydEscUYiMMeZaGZz2YM+oIo8pKyOMHV5RWbdU5dNxhruXXzEKP9pC3XFb1YoZ3xGVsUom1LURb73pFzjsFgwGw224sWzudz6qrZB3lrDboVXFxc8OTxCUEQMRpNOD07YzQa7KeuQngJ3WdlWqIoIlQhVev1wYV0aGO9eoa0FNsCKQOctmzXBUEQUWwrrHGInWKnFGxXBSoICBNLGPm+0raYMxonBGHEnTvXvavxaEDWC9hsWlrtMVZ5XnH92k3iOOPy8gpjKuJI0TaaMPQa/lL4lkFRbLDWy7IYbdAC4ljhnCbL/HtK01EHy/CmpIiGXj+mKDXWNYRRj8l0TF1p8m1NmqXY2u7FAZ1zVFW53xiUUgTK213tJqy7z2J3TXsoR8hmvcJi0G3jDVKFB4bWTUVdaeIoI8lihoOYtJdQVTm1dt5F2kAv65Fkse+PvsD6gSytvtdjvtfjPr4+SfIE6ZBC4qzlrW++Sb3dUq6XHA76ZL0UXRd86//zm7S/9EV+8n//D/mD/8v/wGs//iqLm2DGKf2tQ9ZQ1Dnj0ajzvdfk2y1hEBLSqYZqg9WacluAdVycnzPo97Fac+/OHYrNlsPplPVyycFkxPnpEw6Pjjg5PeXW3XsIZbFCoE2X5rqdHfszPL0O74UQ3a7FftInpEC3LScnJ9x76R51kRNFoVd4rEpu3rzJ+fk5URzSNDWbzZrJZMJi4d16DY7ZYkbcG+6zI7E7hh3qnKeigUIIVBDg8TaGoijJt1ucFKRpwmI5ZzwakqYJSgU8efKQKMyoCj/dMq1AyRCBByaenl4QqIg0zbBW0OQ5s/mCQIQo29JPxl66NkoYjUds8zVhEiKV3BOXh8NhJ3sc7p2X27Zls90wnUyJ44iylCRpgta6cyfxjjyr5cb3U0Yjrq6u9jdTURR7lHpd10ynh5xdPCHL+mzrJUWxRSpJU7WEYUxbG9pWE8UpzgrKovJZUxAhpcChyVKJChWN9S7VaTri7GLJwVFGGCp6vQzwf3+73dAf9Lm6XLBZF0ynR1gLcRzR6/Uoy5Lr14+w1vHwwUe0bUUUeh2wwaCP1gIlA4xuCJSk18s6M1nLZrMhigKyLGW7zVEqZLOZE8chTd0ym81pGsOw792Zd6YUjW7QzgepKBJEUbTvY/rkwDsH7QLZs5LccRxzeHjIw4cPuby4YDQeMhmPuH3nFmEYcHZ2RlP7jVLT0LaGIYo4DkiSEZnJOkMKLwszCFLMjyJIfTzwfK/S7kVKv2fpJU8zEU8XEUKghKCfJPTDkCYOyeKAJoI4DdFJw8lv/zHypRk//X/8LzlfnzFcXDJoEu4vLpgc3mQx3xIGA6qqYjweM5/PmEzGnDx5wu07d3jy5DE3rt9gPptxeHDI+fk5N2/e4MmTJ9y+fYcnT064ffs2m/WayWTAeNBDOMvx8XXfD0jSp9TgPbLbPve+oCvzrO70qY3XksJRVQ3CGobDPhcXZ0jnmIyGnJ2dMxhP2Wy29PsD2rZGa68OsMMOjUZjNnnRIY2fyhp7OkzXY91/ZF1m6nb4M/9TY3xmlg4SojhkMhnhnKWXjWhrR5FbKlGTbw26AesEZa5xTrOYn6C1YTQa0wqHbhxNpWl1yeH0AOccdd3Qi0aAp5wMh0PuvXyPJycnnJ2dMZlMqKqK5XJJHMfdqNzbWB1MD4iTBBV4PtrLr9zjzTffJE0ziqKkqWuCwIvkTSaTfYbwLOB2Pp/vG/FlWeHqFpl4C680SeklfVYLL2+rjaOtW7K0RzbpsVysMdpgsMRxQK/XJ0gUST+iP4i5eeuAm7dHOFq2Wy/0VxQ1TWNwYstoNOLWzbuUkwajfRazWi0YjnoMRjFKCQaDPi+9fJfHj55QloU/xxa0hlprnDUkccBisSTrJVhrOqtz71ajteXifMa161PCSFHkF6RJn0DFNK3BOcF6vcEY1ymBRghEpwXfdhzJoGtD5J35g9i3DnZ8yoODA05OTvw1ZgV1WRNHEcvZgmyQIiUEsWIwSlEqoq5KqrpgNtPe6Tn2ZG8hLc5ayqogiF9MSfevHHEOHw9QXUNXWLAeE1JWBdKBcQaNYJ6vveTDYZ/g5Snv/NlXCR/Puf0TL/FRBheRZhPDUIBQkrptmC/mpFkKHTxAKMlytSSKYxrdIpQiLwt6gz5FVTE9POTk7JSbt2/x4cMHvPHGp3ny6D6ffv0NPvjwAYfXb7DceAPKIE7Q+ikKfdeT2u1QHrvzLGreeRxTV9o667rpypAHH7yP1R5ZfXF5xXDo8URJEnN2dsLtO7eoqpLZbIaU53z1G1/n8PoN+sPJ3sppzx/svvYUI+u6vtnzzXQHlNUaFQboNqTfG9HWivV6idMJYZqSpeBiyXK5Jgp7zK5m1JUlCCLKomWzrmhbXzr0B6lHhi9qcJDnW25cv8mrr77Ko8cPmc1m+x7Jw4cP92VE03jr9fl83jnshOi25c6dO1RVsW+EbzY5TdPQas14PGGxWHB1dbVH5t+5c4fVarXHTPX7fT768AkigKZtEcJ2+uSWJE07g9eIPC86zp+mbTUqkGBMh31zHuejHK0uaLUhLxRSGYSUTCYTIEBgyLcVcaqYz3LENKWq2q7M14xGPbTJyYs10mUUhQ+Qk+mIQeuYzbbMZnP6vTFSSKqixDlFWeYoJQlCSVVVnoTcGnCStnFcXeaAwVgYDoc4GxAGSSdGaKnKmlhFfgJbFCjlMXHeZCFCSUWgxN7UZJdF7TYO79Ljp45hGPFjn/lxTs8fU9cNTVtyeP2Ag8Mpj05OuLqagbDUlQYBVSVxwg8EglCAbL0V/Y57+D3WXypIfb+Z1SetjweoHRLaGu1lH/DkRYljvVqgognbpkJIx1CFyJtHHH3xiG/+v/8t1+4c0mSOx/NL+nGPcuPNN4t6y8HRAcv1ksFgwNnFGcfHx6xWK64dX+P89Jzp9ID5bMZwOOTqasbB4QEyUGyLnJdefonLqyuiMODrX/sK9175lN8Rx1Oq1ux7IDsFzH0m9QxvzitjdiRf48Xn6qYiEIL5/IqvfeXL3L5xzDe+/jWSOMZYx9n5ktt3bvHBBx/w6quv8ODBhwzfGmCtYbVacuv2bdabDa2Fca1x+IZlEEQ+OHXYrF14dF0mtTs+ISXW7KRmtB+3NwkX25aLizmDQYRxjiCQVGXFfLby42w2WC3opZ6se3l55Xs9TpKmGbdvT8B4WZlYxWjrs7yPPnrE6dkpceaNDI6Pj5nNZmRZxhtvvMF77723V0EYDAZobairmpOTJxwcHOw1ovr9PtZscM7R62UcZlMePXq0L/WiKGI6nXak6CVt60ftebX12Zbw5qhN0+CMIIpiFrOV7+c5i9EtUgTornktpaCpWurQD3DiUDIYjllvlji8Jntda9J4yGy2YjKeIlxF1usTRz1GwwOCUFBWa5p2Q5wI+sMxZ4+2LIqSpqmJ45TJ+JAk6VOXhsW8ABcShrEPRK1htVozGg+QUlHXBXVlyLIBdd1QVQ1KCYxtsFbQ72dI0bJcrJAy6IT7DDdu3KBtWx4/frIHJbsOGyilDwc7pHmWZT6AB8EeLtI0DVbD/Q8eoE1NfxTzuc//GGWbUzUFRblGKkPaSxlO+6zWW6qqojHal8SDpJNebtlsVi8UI144SD3rkPJsgPnLrk8qi4QEGUgkYE2DbitM0yCsRlhNHCrP3C4MPzm9w5f++D9w8J//Iid3Mw7SiMv7M3rHB1wsF4ynPcp5zo3jY9aLBTZNWS0WTMdjIqWoyxJjWooqJ+0lFHXB5HDMo8cPuXPnDvPFAhWNiJKILBkgo4SyrhmPR6w2a6yQhEJ6xK7vAmGModXGAyalQEYhzmmstp38hfYuwkZjreXb3/4W33zrm7z99jexbcvBdNppFgXMZlccXTvi4UcPyXoZcZJ25NMhRVFydHCIE4o48k3WIPAqQQiBEwKDwzmNcA6jHVZ6/BRYrDO0uiaME2Qg6MUBtg1Yr2qKvKTAIJUjOcg4XZwTRSFRz09lBoMhWhuMNvSyjKqquHZ4xOHRIZWeY7UgCGOStM+y3FJrjc23TCYjlvMrzi/mhEFEvzfAGC9M56dL3j7JwzwyxuMRxhoePHjIweGUwWDMo48eI4SkLAuMGTMajbh///6+n3X//n1u3LhBkiRkmTcSlZ0qAlisNrSuBRwykrRNjbYNvSSjLn2zvmkar7kk5d5gQLea4+MJJBXa1F2vp8fjR6dIEXDVViwXBcJF3LjVJ8839HoxTjiEVMSpQIW+YVzkJRKHFA5tNFJrZqsFcZTy+udfotiUtE3Lh++eY7RiMBhSFAXrpQ8ggUq94J8xXvepbrDWEYc9rHasFyW6djgNMvDEc6NCZqsFRwdHSKW8ZVjTdphEt3cKD0JvPmqcpWpqXv/067zz7jv+/OJobQVNy2Q8YbPZcnY65+LqjM12SZwoEIZNtSQYCCbTMZcXM5LI9xPrwuCsRAhF1fyQEeffTarlu63v9ru/SPLl6f/70i4KI5zT3Lh2xMXZCf24hxIO27YsZpdoYREVmHHEz/z45/jN/+XfcvO1l+lfu8Z6m5P1MzbrNW1Vc/rkCQeTCWVR8qmXX2GxWDCdTrk8O+PeKy9zcn5Kr9enLkqatkKFkqv5FVmW8dGjB2htqRtNXRUMBwPe+uZvc/P2Xa7mC7741/8mdIJpTevdT4qy4Pzykpt373HY6QYJ4eXs2nqnbmn51ttv8/4H7zMeT2jbmiSOGfR7ICVK+l5THMcM7XCPBVKBItn9v7Ro6ycmvg/jUe+CHfodpLAESiKIu/5Z5QX8U4UMJEEYY7TFVJ4+kUQBgezhnGUyGdOL+9y7c8/78WFI+wlBJJFK4Iyl2VTotkUKL6YWiIiqaen1B8wXa9KsT5xlONvS6oq2KQkD33j3Rpl5V2K1KCU7naiqmzQlnovX63N6cs69e/cYjycURUFVVVxeXRB1/Y6yLPcN38ViwXA47PpAK+IoYTgccDW/JM1ipJVexK81bLdrhOiCdtsynR5R5BXbbY7WpsMTWdK0T5zEBD0v5VwUHpc2ndzk4nyGkgGjYYRuLYvFkiCEolzRGqiqLc5ZBoMhw9GEpirpZT1k2QAh623B/GLNq6/eI8+XBIEjCCzXbwy5/96l71M1ljBMPEzEQpx4HXqtG7RpvBGt8oa0+WZDHKSonkBJxybX1MJxenlBWZbEYYQ0oCsPShbCN9fXxcbTuJRECol1jsvZFf3BgMVigbGW/jBGSYcTGqVC3nrzPYoiJwgdh0dDJtMBcRJxcX7p5ZAR1FWL0Q4sLGZLpHQkyV9kivt0/Uh9977f13maVfkPwTnf2F2tlywWc64dHXByckpv2MPOrqiaEofh53/xZ/n//dt/jcHRmIZe2Mfalps3b7CanZP1e/6iHY/ZFjl12xCnCV/52le5e/cuv/f7v08YxyyXS/r9Pu+//z79fp/1er3vc1xdXdEfjFgu5gz6PfJ8w+VsQastn3rjgigb0BovJVJVNZdXV8wWK7R1vPnmNxj2MgIpGA97xLGibVo2mzUffPABaZLirCWJQ2TXw0pTP2XaNTCHwyHOuedwV17moyXCS2c8BZN+/BxLjPZulKoDS4JHEe+05+u6oTKWpm47xU2Pzr+6WnJ5dcWg74Xt0g5wWOQlzjoCqXzvqDFcXFxQ1zUHN4fUVUOsNBLvjFtXFcfXD3lw/z0Gw4y8LPYKEkGgGE+mndqmd0fxUr6aqqo5ODjg2rVrPHnyhGvXrpEkCe+///4e3lGW5f487Uo7rbXfLIqCMPRB7Nr1a6y3KwTCT3udxgpL2xp6/QxhZef26xiNR4xGXoVzNrtESEeaZmxWBcMoZrlYU5YVO2S/1ZaDozFHR9dpdct6c46uK6rcohvHal1w8+Z1pFBcnV+xXm+ZDA7ZbivK2qBUyjALcU3AfLUmizx2L8DL9tZ1i0B3n7HP2v2AyU+Ik9R7T/Z7PaqyRgaCKI4wpqasSg8ZcYKyKCHOGE/HzOq53xy0wQqBaz32zbtdW6qqoq5rVqsVL7/88n4aaHSBtoa2KZDSm0KMRiPiWJHEwb4H5p2XN37SOBhzdnrF9GDcWW3R+Td+7/UjVUF40dfZNTh31AYhIVAhxlqkFGS9lCgJ6Q16zJdzEJIgirCtJq+3/M7v/w6ziyfcuH2Ti6tT9PoKi+TBh/eJA8np6ROuHR3xm7/5m7z22mu89dZbfO7zn+dbb7/NBx98wNV8jgpDqqp8TkfJOcd06m+e3Qd0fHyd1Wrp8VVOkCQRH330Ea9/9sepW72/6XXbMruc8at/62/z6quv0lY52/WautyimwIl4e1vftMrGwaBLyvU7tkOKRTOiT1mZQcq9R9wF6SUREmHdRIj1b739fElpdjjucKwU+rs0PJae3VLY6CtWsIwwRpvXtF2gvphpLi4mIO0pIMebdOiW43VHuyq287tuDVcnl9S6i2vvPwqkghi40tN06K1F91LkpQw9ChnT15Ou+FAgjEtceylTH7hF77Io0ePSZKEw8NDLi4uODk5YTKZ7CELWmseP/aP2TXfd1CG3WOapqGqKtq2YTwesc23JEmKNg11W3UM/wCcVz7V2nLjxhFXlzMODg64uDwnEJLlckmYKkrT0DaaLB0wHA45O/cSN/P5kjhO2G62tFrTtC1FXpNkAa12zK42hJFkPBpy69aINBrSaoelBhFQFYYnD86JhKIyNePBkNOrC6rWIIQijhOM9jItQiqE8BuWDARCggpgMOxRlQXGtshAMBj2CErvGm1ay4W+IA0DbNNwOJl4R+uyQqoA3SHB67raD2F2feL79+/vBxxSGsJAYR0d9i3i9u1bXFye+mvJQq+fEagQrdfUlWbjCrKsh24dVZkTdn6EL7J+pEHqRftX36GE0PGUTAdUW60WPDl5woOH95FKEi/9lC6MQwbjPg++eUlebfmjP/sS4xvXuH9ywvXjmywuFyRxSJHn3pc+TXnzm98kjiJOT09BCNYbr5ejwojl0gPooijcWzDVdc147NUp6bKc6XSK1ZpQBVgE88Xcc+e60W0ce++xo0MvLWKMR0dPphMeP1zS1A3LxRVtq5lOpt6Ky1oCKQiDAPBOM7vpxw6Q+Kz6AvjgIzBYJNuy+a7neNf8xYlnbK14CkS1FoFEyhAlQ8qyRreWOPayv1XZAp3VvYMoDKnykuFwyMHkkNOTU4/OT1KklAwHPQJCetkA1+Ssl1uSOOHJyWOSNGW5XDEeTzuZloLLy3lnGd5gOhmenbZ60zS89957/vNLEk5PT5nP51RVtZ8+7YCb3pg02Nu377KqnRffo0ePGE9GnpuWpQgkceyVKsMw5vbd25ydnHF5MWO52BDHXuwtiVOMbVmvN6hC4ZQkCkOK9Ypy25LnZZfVWMq8QApJGGSdIoCjn0xA9GnrAqct83bpFROCGothPOlhtGS9WIMxLBY5f+dv/A3y5YaPnlyQ9ftIGVAUFQ5LmsU452VdlPK0JhUqjNMs13PiNCSKvc5Uv9/HCc1yuUAZwSBNyeKI5WJOmg4ACKOIvK5pjMFp462t8MawQeDtzXZA2SAIqKuaNE5w1nS/q1itlggBddOCUGzWBWGYIvDGtNYKer1BR8Fpybell2Z+gfUfHYKw5+Y914N6RkNKiE6KwisFOGf50p98iccfPSBJYgxQlB6N/Ut//W/xzbff4sGTj6BpiHoJmzInTiKKMmcyGaObhvF4vD/B0+l0f6OPx2M/aegQ436MzP4mEd0usftXKgXOS9MqIUAqVBjToriaXXF47brHIklJr9fj+miM7DhrSeh39V3GWOQ5x9eve2kZ56WDpfA+ckp6YJ3XKveQjJ3cy25E7Es//1whFVW7Qhuf0Tx7np/+P8+cYzw9xtp9edl2QbdpWtrGT3qUCikrTxhWSnbi/bKTBskYDccIBNZ4PlgcxBxfOyZKQgbZiLbRtFWD0Zrp8YSjowMuLz2BeiemF0UhSgXEYcTrr7/OV7/6la4hblivV3sThrqu9yqeSZJQVdV+KpUkCVEUcXV1BcDh4eHemn0nORPHETLwekm9rMe9l+6hQsU7771LGCZ89rOf51tvvsVysQQhO7xW6/tGUtG2ddd+wMu6tC3GaozxkBOpOjFDbQmTmLryE8QoVqyWJUoZZCAw0rLdep2prO+NLdq2YjSaMp1mlGHN4XBI21b8xE9+ng9OnnC+9HpOTdN0WDBLkkQY2xDHATKExpSEQUzV5IyGY6q8IYiUdxgWDu00gVIMsgFlWXhYjwop65Io7RM6R6gCTNOpMJinyiG7TXI8HnuN9zRmtVx6McLI95bKsiDNvKRMUXqArRSK4+ObbNY58/lTSIjo1DKmkx+yEcNflvLy8fW8VMrH/hYCJYIOx2O8vIXTXFytGB8cEmcp2oEMFIPxiChNmF47ZFVsEYFkkMSEIkQZSZBKpJLdCN4RSkkQhljjS0khPYt/pyktpG8YSuUDg9oHCNmh4LsyS4BFEsYJRobeWrrDnYAnvO5ML5MkReGhB36X1/T7fZ+JGU0UhR4ygPP0COnR6W7vu/e8DvyO0Lwv95AE6/wZCePn155LKPyuu8NmIfxEZwfes8bf9EHojSmffa0wCrFOk+cFWZbhLCxmC3ppD6u9asVLL73MZz/7We7f/xBnII0zirAkDLxYfxAE9PsDZrMrNpuSXq+PEF50rdfr0e/3uX37Ng8efEgQBHz00SNAdOXfhjzPSZKEsizJsmyvRbXTlur1evsManfOptMp6/Xawy86mefpwQEXF5eMxiOaumWz2fClP/oTVIe6lkJQaw1OUhQVUu1Q2aqbRnhPvl7a8w7FpqWsij3mKJCBt4gM/WZbbhuyXkiRF2iTMxpnYBXD/oDVeoUQkvV2QWtbRABJHPEnX/4zdNtSt3XXH/JBUkrpCdS6QilBUW4JrSAdxsRhiLMCIR0q8r3A3qDHydkjojj0TXZlMdJSmxbq0uPGwhYhvDZ+lqW0XTBsmoam8U7Wux5fv9+nbbryM+rAs1gvPtgpmFjjEIGiaRufaOBpYDtoQxz7gdjO4PV7rR9pJvWige3jWZVXFGBnJ4BUgiSNibMEiwCl/A0sFa22RGlGXlX0R0MqZwmFIpIRoZE4YZGh2t/kz9bau1TWlzrBPmN5NnN57kuJDvDmJWOcUFgnGBwccf3mXZbrDcvFjKqq/Q7fTUyUkgRCotsaYy2BDBgPR4RBgDHaT96El20RPGNFr8Lnzs/u/3dZkudbObR5Wg5+0vJBjz0S2zfR/WtVncgdzkt3qMDLl5RljlSKLIu9NTmOtmlAwJ1bdyjLkrOTs64cnjAZTzmYHvKLX/gis4sFi/kCYzY43H5Mfu3aEavVknfffQ+tHWnaKUkGAZeXl5SlZ9Tv+GQHB1OaRu/Luh2BeDAYsF6v99brbev7WLdu3eLhw4f7c1OW5R6EqJQgjnwDverMSJumYbPJ/aQur5BYrLHEnaa30TvZF4NzHhojpCCUijRNSJKYovCmnHGUYIzuMkuHMT6zdBb/vRakSQ8VpBxMhxwcjgmUIItHJD3vn/fgwSMa23I+n7OpCv7wz79CXtaoKOkqgQilBEoJWm1J0pjQwGjaY3jQQ8mQi/MrP0HVmvV2RRD6/pAAZCQptgXpqEe/8YqZw/EI4ySb1Za03ydNvbnGLkt9uiH6kq+qKkxrumzbB0Lf1/T8v7ZtyHPf58vSkPVmhRf9cIThTjvfoHVDWf0VEIz/ovVs6fHd1v5mFIIgUB2OyJ+gtJd6o8U4QxtJWbVo42hazXh6QBoGaAxZ6ANHIiJiESFDj7ly7Dh1qpOxsH7XlJ6Gq0Tog4+Q+9JwB4ego5HIQCJF51mHwwmFUCH90bhjk7f0+32uZnPf1O0a3VL4TEJJxWQ8wVQ5oezUWhA4TIew8plaJ/6Ak8H+nOwyz2e/V0ohhUEbty8lv9uSQoIUBEHoidHGep81BEEYEAUBznjwpHM+o1QKjNE4fAbo/dcEH374IVmaebXKbUGWZkRhyO3btxgM+qRRj7XYYJwhVJKm9pzD3/u932O5XAIQRzEXFxekacJms+bo2iFZlpLn2z14sK5rtlsv47JzkNn1pTYbPyofDAb7zWYHQWiahul0ihCCy8vLzro959rxdS4vL/35kJLLq1lXwhnSLKOtS6Tw5bQUEd5BG4z25VyglBc2xGJ0Q9uClD6zDaMIKQRatxiMd5ex3iy2bXy/ajjsIXF87sd+nKvZOW9+7VtYZ+mPHIEagkxZLFfoGmQyoKkdYazQRu+HBEoJpIIwDJBSkGY9glAxm1/uYRbLxZptvmU6HXfqEg3GaWQv8srSStEfD0n7cHm2oKxbVBCiW816teLpbejL4yRJ+PSnP83du3e5f/8+s6s5baNpmhpQHhRs7f55u8wvjATOGU9HcmCtpixzmrYmy5Ku//q91185Lebj/Sn/byca1zWTh8MBKnBIFXC1WHtkdVOTJDEvvfwyV9EJCq+SKYLAazUTEBiBVAIRPM2GVKCekn47Lzolgy5Nfur4+7QHJLrSz4MjvYKn830jqUAq4iThw0cnPHpyQlXmJGnGxeUVMoj4gz/4A4bDAc409JKYo8MxWRITqY4eIzqwoNb+dYXAO8d4ZU3RnRBrdIeLUgjp+Y1SeCE4abwtu+24Xr4B5Tr1A4GxFuMMWG/L0DS+HPI3o0A3hjAQnTaWQYqAfr/HcDhiNrvqfNMMWhsCpYjCgLqscNZydHjIq6+8ytHhIW9+4+uEgULrlsVyiRCOIPRTtsvLS6qq4t69l7oyTmK05uTkhLb1u+qufzcYeM2k5XLFcDhisVhwcXGxB2t6GRBv+nlyckqW+YB29+7d/Qajtebo6IjlctlpIY2oq8oz/TudLyn8+Q2Ut/Wy1m8k2hhwNVKqDiflRQK99IlGmxat7f5z2mXm/oLu+lKhQred3LSznS6UpBfEfP0bb5Lna5RI0LphOc9p2hOuHV+nOXK0Dcwv1mihAYMKBaPxgLppUNJvakIKjHUY41guN1TthihsmU4jDg6mpLHn0wnlCIWk3NSoEOqqRbqANAw8t0/4DK9uDMJJrPXAX+usp1FZQ12VnJ2ecvfObaT0G14ceVVNa3Rnj2b3m/Lh4REIy2qzJAxDpgdjlssVDk1de8lj3bT7/un3Wj8ynNT3Q5n5pOzKOIsMfLqR9HrEaYw2BoPk8ckFvSxl2A9568ETslGGkgFZlKIQSAdYD2CURiGcZ68LwEk/ZhYSn1F0InVBN1Ld0SR8DwekAiE7BLeMfXDogpTspnsiCCjrhtc/81nee+89giBmkz9mNEn5lb/+K4yGPTA15WZJ25TErUVZsFLiAoVTCrmnsVj/ZSHoxuLOWUQQYo0f5wddmauEwKiQOPESuq6tURgwNU5IjAMtwAiHUOzlY/xQQmA1CCRJmHAwGXF/vkFYgXMaZ1ry9ZqX7t5lNpuxXK78tGgYcXBwxHZdsFpueO1Tn+Knf/qn+P3f/V2crXn3nW9w/fhVzq9OmUwmNMYH/5s3b7FYLLqeiocFXD8+YrPZUJQNZqs7lciAum72FuxnZ+eUZcnt27f3jfFd2Q6Qph5Vboxhu93uaR6Xl5f0er29Xbtpau9l6LyETBLHhKGiaXao7wYhFRZQYdCVxjUiEIRRiAol1hqMcP5zc95MYwejiKLEl0jOegpKG1Brj0qXgSOIJS4QFLpBr4zfUJFsNltvSOBq1qFA6pZyvcXpll6WkfYzwjgAYYmMIggDisK7Hreto80dSqW4qgUXUm1qEhXRyyK22yVGN2w2/rxkhARSYkrDarNmdrXGGMWgN8ZoiRWCUPjeIU5jdIvAEqmIKt/we//h31FVJW0jUCIGIYijxFuudYKGAp9x9kd9ZAZHBxPqqmQ4SdistuSrijiMca0ikL0XijV/5ZnUd1vOOd8LEJYk8ZrNF48fEyUZWZbRass3vvZVAqWYzc4ZD8ZsFzNuXr/BaDjcZxRRkCCQnlS8y4oCsdPPxOG4ml0wX8wYDsYcHvjplBdXkUhBJyXgEGHke0bON92tE6ACGiu8hMrBAcPBkDAKef311zm+eZMoDD3aHOHtlwqHQhMJBYHCCDDOIZVCOAfGIowF6cd9DkegvK0TSnkyqFKoDo5gOqOFMI6fM1jw5S1gP65x5Z7u/MJnEQLBgwcPGQyHe4Kv1pq/92t/k5s3bzEajfkX/+JfkKYxb3zmVd5885tI5Um1v/TLv0JbV1RNxXIxRwhwZ6dEUcR2uyVJkr3B6K5ke+WVVzg7O/Pj7Lp+Oj2VkjRN98qQ1to9any9Xnc4Ko+l2/WUdiUJwPHxMYvFgtlsxmKxQGvNyy+/zM6vb5NvmUynCCnZdkYDQRDsM2uc2GepO4nnIAg6vztF09ZgIEl9QPIIeR8sPWfSl6kCQa0bgsBLnwhliROPw+tHGVXZEGcJkQxJkhQpLUkSduqefsJa1w1CRBgdYFxLGEjCMADrUMLDA5zxzjFYX/4557DGUZYNWRYThTGDwciDTa139Nn93hjJbLZASqibHOsE1kCUxGjr5YSCKMRaSZzEIPAkevzgKAxUN6GtCELvXOyxfJ6eE0QBQerI1ys/jYwT+v0eSkTMrtYEUYgKXwzW9EPHSf1lp37QaQUI76/X1D7V/OCD97w7rQMZJKRZn4cfPiAKAm4e36AqtpimJVCQJiFKxigpaa0hiEIgREhojfbNPuuNH1abFfcfv8tiNWfYH5P0U8YHYxQhrnODkjuLcultqPY1uwzQTiCcpNhu+cY3vkEYhLz26U8ThBH37t4ljmICJcAYdGOQSH9hOrDCg+HCrqktnA+iqjN00NIHauNgmeecXV6yXG6YLRYdYtoy7sUc37jB5dUVQRjR2NqXoaIzKRKdAsIeH/WMs42x1HVFVVWA180+OTlBSoUQ8Lu/+7udMsGQ5XLB0bUDLmZX/Pqv/wPOzy548OFH/O7v/m7nHdgig4AgDKiqisPDQ5IkYT6fk2UZg8GAa9eu8ZWvfIXNZtOZanocz25y5xn2IaPRaD+VW61W3LhxA601eZ5T1zX9fp/FYrFH3+8cZPI8Z7FY0Ov1CIKAzWazByHeu3ObppO6KavqKadvL7fsQOwcgJ7ySXcGsGVZeheWUO1LZWMMUeShAW3b7j0Cre0kcbw6M9ZadCvYrHO09VQKGSRU1ZayrIkTRag9zKM/HDAY1MSRoyo9Zsnoln5vQp6vMVbTy/q0bYOQgl4voWlqPNPVG5nWlcYa5yk8Kub6tWOapqZpvA7+Nt8QhRlJKun3R+AU63WO0RatfaCTnbGtdZq8KAgC1bVMVGfo0eBoEcLR6w06G7SFdxK3fmJu6g1VAxYv393vD+kNUpbrNa2uPaTnBdYPNUj9MAIU0Im0CXTrd6ef/dmf4/btm3zt619jU1TEQUi+zXnt3msYrVnPl0wnI37qp3+Cfr/vm9HGEcgAKSuuFue8/+F9lJQMRn2ElHzq05/iy1/5MhcX52T9hMNbI6wWfO3tL1PUNa+99Iaf8qgInO9FSVGj5NMJG6IjSpYN9+7d5a1vvcP0eESoJKqXEihB29QIFxAp6fFf3VRSOIhCbwIBvv6XUiCsR5031mClY7XJ+cpXv8Y779/n4mrBcrOlrFvCyF+c48BLAAspiZKUbVl1zJhODoadCujzJG4pJU0niFZVFcZqfzFpTRDA3bt3iKKQR48+Yra84qWX7rHZbFgt1/ybf/ub9LMhr3/6Dc7Pznnv3Xd93yaK2eYFbdMwHA7RWjMYeOng+Xy+x6EtFgvSNGW73e6zlH6/T7/f32dUO1fjHaxiZw4KnqWfZdk+4HpRuylN09Dr9TpQqJcn3vWlLi8uKJvae/bV9f5vNx3wU1uDVMFzGZRzpkNY++AZxaHXAeuOTwix/1vw1HpLCoHCj+Ih8uJ6TUscZ95pOwyYXa6xTUscBwz6I1pTUlUNeV5y+/YdLs8X4CocLSDRdYMzluGgU0EoCi+/EmdeyjoAKQPyvMDuzT5gOvXa6XEcIgNLoAIODydo7bidXicKU9arnKvZ1kMbKo0UkrYrjXeuxG3d7q8hD+KENA3p94dcv37MarUhjhKytO8b5cbSS0Ms3uxUKl/mCxUzPhhycnpBW/2IjRj+IjjBJ/3u4z97Tir4mec+pXwodPMUyHj79m2Ob9zg7Xfe5U//7KsoFWGagIPxEb/0hb9GFElwlijyGKgw9m4mUexYPFp47Zu2RirfqL5cndO2DYaWdV4iQ3xNX1u+/e63WK9K7t35FAejI9IkJcsGOCuwutMZwvMKkzhmWzVMxiN+7LNvkCQJWrdIFeKM8f2PKKapCqRQSCG98JjzfntCeDkVGQh0a32fy0DVNPzJV77MW9/6tm/IN5pbd1/m+kt9LucLHJIiz5GbGVJJyqqi1da3XbpSb6cpJdgNKPxuuz//+AFFECh6cUpV1wjZYqzhycljb+mVJdR1xcnpY8ADA+Mw5d33P2C53PDzP/tzzGdz/sbf+GucnT3ma1/7Krr16pFJ4vsVy+WSLMv2Jd5O1nd38+8cind65ACbzYbz8/PnPPjiOPYk7qbZS4c8BbaqfQm4s0fzzfclZVnSTxPapuH8/ByHzySzLCNoW9brdYePE+gOU7YLQm3b7stPP4l9/hp/ViBuP5xREmH8xpMkCRZfagspaCpLVXr2QiBDQFIWDUhLFCmKomS7OaGuDUpFtK1g0B8RJxFCesXQZ2k/UvoekOp6jh5E6st4bQ11banrnGvXpoRhTF1XlEXNcDiiaQxluaXXj4kTiW5LnAhAhkSBd4Ku65rVck0YeohLHEVIJHHkLd21abm4OCfPS6QKuHXrJl/5ytdIkhF9HGmSECVjNluf5cZpH4dlMM7I0h8yLeb7WZ+Ej/p48PqkzOxpkPKi/UkUUlVrvv3Ot7k4P+XlV17hjTfe4OJywaPHpzx6eMZkdEh/MMbhPeqtNQQqwDpJ0suoXMXnP/9jbLYrtDV8/c2vs7NH0taz5YNIeFa/iNG1YllVvPf+ExRf8dK4SY/hcMBnPvMKP/8zP0MUJwirkUGnx2M02BbhDNvNitV6C8LfNP3+AIWfytlWI+jUEa03OlWim9QYQ5R6jeqrxZLf+9If89YH73F5dcXxzdu8dHhErz9AW0FvdEDdav78z/+MG6m3VhpODriaL7xKpxBPBe94io/yPxb7cm+HhTHGdrIfjqzXI8syJpMRi8WMVjc0uiYJYno9T8+4nF3RNob33v+Aq6s5URDwW7/926zXS+I49J9dku6xNbusZheITk9PsdbukeM7OktRFPvroGm8KJ73lWv2ZdmzgWqX5ewCxS7Y7QLMLtMKQ88DNcbQ6/VQgWI2n5OkKU2nBQbeNcXh9n9rR2faI73xmKmYeJ9t7cThkiTZB0ucQ1hJWxSUZYmxPiMJgtB7Sirh1SmMl5OuG0O/HxN0iPjttqBtWoq2wbQWnCRL+0gaksi/tyiR3igU5a+xwNHUhkH/gHxb+RI467Pd5IAmDAPSxnlLrdY74GzW3jV6Mply+/axl5LeVFy7dtzxWEecnJzghEYGATeuX0dKSbktqPKqm7Yarq6u6PX6NE3Fhx9+QBQpWl1hnCIvS+rWB1yl6ADOFql6JOmPWAXh+1kfF7bb/ey7LY9lEiA0URzx6quv0ssSVsslDx499uYB0ynH4xvUumBTzhmOU9769jfYbFa89qnXOTy4zqZccnr2iKwXMrtaoALFweRoP0K+ffcuzsHl1TlHvSlGS5Jen0pJbtw8xtgAayT9/gCH4IOTOd985zf4ws/+FD/zk58nDry88Wg45Go2p5eELNY1VVlwcXnFfLHg6mrGoNcjEBAI+Gu//EUC6WVUhTAo4UCCU4IWy8PzE/74z77Ct977kIv5ik+//jmuXz9muV7jZAjOoqRCasPdO3fZnn6EUAHbvCCKE8pqV+7BrpRE7Mbku/P71Ol3F6i0Np2GeMvZ+RmnZ485unbIZrvGWs1kOsI4w2azxlqoGg9MzYsCNeijVEDW63kPO9gDMnfl2O7v7Mq5XeN5p7a5Q5VPp1OKovDyKh0lpt/vI4TYI/pHo9H+b+xoRrsSdu+YsyfD+nLW4hiPx75R3/rAptt2X04aZzHGb5JSPQ1wvpTzxy4kexWJXYnnXYeSfdahtdfRT8KQOE73aP8g9Hgi1UGUtTU4JxF4pH9VNZRVS6+XEQSexFsWGyQhVxdLTGtJs4i6KdlsViSJ13mPQh9MrahxVhHHQ9rGorUkS4es1xt6/RRnJWXhfSVBohsQIuxgH5rj42PKsuTomsfqWVFhqTi+eUBv4DcoZzvrMOtYzTc42wAVaZpyeNjJCzvD0bUJ42mfbOCD0/vv3QcCnIWBFly7dohxmupHDeZ8Ub2ojweoZzFR361k3FEYdhfS6ckJDx8+4PDo0PcmdElVVxhZcv32MYNpwPnlfd5670+ZzS55cvk+r3/6xzg/n1Guc6qypCwLVusVWS+jblsmU89v0rVl1J9gakdVN6ybFePJDQ+kVBFOggkCj0kJ+4TDiA8enVFWNX/9iz+PsZrRcMjrn3qV+XxOlMyp6ooPHzzk3suv8rf+1t8hCSMCKVjNZySxJ7YqKTt0ud9VkfDk9Iw//cZXeXh5wWyb8+rrn+PajRtUVY2QXqfIl0qWUEpuHV/n0XrhHVesodFeu4e9Fmd3PrtgZMwO28M+UOxu7G2ee4MD5/zIXUXUTcXh4QGb7YrWNEgRePCjdV1W4IcTy+UKa0ynERTty6SdocKun7SjRQwGA5bLpe9xrVadCqcPOJvNhs3Gq27uspOmadhut/v342+sZn89aa3Zbrf7npXWnsO4KzezLCOUAqEkQkrqrtFt7LPKGxLZZZnP9qV2Gldaa+I46vpSbp/t7f7ezpx1l+WhwQqPPm+1RUgftGUQEEYhNJa6NKhAorVHqCPaDqIRc+3adYq8pti0BCpiudiS5xIpHVZL6tJrk9emReuWIPYAyraeoUSCM7BcbgDlVUa1IxRecG+73VJXi45YHdDLQrbbksvLCyYHKUkSsVrP6WUZSZJycDikqlqQjrzccHo6o98bIoQgz7f0+31WqyVJGnlkeSTYFmu0UkQh9AZjFvM1WK+0kW9ywkAi9HcHHz+7/lKZ1PdDe/lumdSuN/Xsz/30xOIwVHXN+cU5Z2enNG1DrS3LdQ5CcevuEScXH/Lt+3/KJr/CuprKLLlaaLbfWJLEfUQdoWvjyywVgVPcuH6T2WLORx897up7cKbFiRDdaN/4Ezn9UeoRw87gpMIFsW9+K8n51YKvvfkWX/iZH0cCo2Gf0aDHS6+9xuc+/xN84Qu/xLaoCLsdXTc1cRx31kWSHZpZCIEVgm2+5Stf/zqXyyXf+Pa3+Kmf/kUOx8c02qGiBFs3CCFRQqKNwRnLcr4g6WVsHj/m6HAKogOkPv1EPHpCPA1czj1/7neuwAbnXaKDAF0ZwjjG4YjSmFE4JowC1ust1igm0zFRkHB2ek5dNV5Yvy5J4whjLNYIkiTZU1mE8Jy5o6MjgL2s7y4DyrIMrfVe6ncXWJxzz00ed7y93eh/l714Pli8hyTs+lhlWbLZbLh2dESoJEVVksYxZVX6QNo05Hnuz0cH3BXSq3B6Y1c60Gizvzal9GDWXRna6/VAsMeAIXyvsmk1VuwwWUkXjFqwGiFcB3+IaZsahyGOxX5bcZZOx9wQBjG68edIKotUjigMUVJR1960NUwU2mm0hrYuSBMvO9zULQcHh2hdUhQFk8mEKMqwxvdl27buGBeKy4sZTWO4uLzk1p1jJofePVqGAhFA2eRY052DQKCCEGctvX6/y3hb6saQpSlFkdO6llYqdLPFGkGcZCg8B/by/JJ+P6GX/oht1r/XelGw53N8vWdQu5IQoSwEhmAIWzFjO18wHv//qfuzJ9vSM70P+33DGveY45nq1FyFAgrVaPSAbjSaItmSKUoMOyxdmGLQtCJo2X+MLxxy6NJ3NhXhQRdySBTVJEV0kw2wu0Gg0UADVUABNZw65+Sce1zzN/jiW2tnnkIBKEo9gCsio7Ly7NyZufba73rf532GO2zbAqlyvv5Hf0qcCMrqmijuiCLP/uwYITSRSpA+GKhV2w4hUu7ee41tuWaxKimqGktCVUhmkzFebINtcdSw3j7BUZIknlTP0EbghcRThc2JT0FEvPPeU+I454tvvk6WSHxXg6nxyjO6f4erdQhbdD0bfjYboSOPxO4M56TQdK3jvR+fcn7R8mfvnHP3hV8lzo6Q3tKKiMbHGD3CycAgd0LTqAimMU8+/BFOQdmU4FokIQZdSoUVCoPqeTIAsvep6u1ZpAh6ON+hVUQkY+7du8tqmXNwOOf09CnCCY72j4IY1IRiXhVbTFQjZEvdrom0QkYRTjpEJDGlxVlYr7bgAzs5TXLiKGU8HtM2hs1my2q13HVRQ1cy+HbVdR3ErF3HbDbbfX3AnPI85/j4uA916J6xsVFKsVqtdtIYD5RVidSKzWbdF8eABcZJ8OeqmgYtBThDJAXIwJ/yxhJJDULQ1cETa7I/pW5bLBahBaZrUb0EJJjmWbpNeMMaa6GzZElG1Tlc52j7LaBQHUJYTNsghSDLI5QIA+HZyRld26GlAmWDy4FSmL770FphrKBuPXGaY5oO532Q6fiGbJRRV46urXEetMq5vL5gPJlijUNFGR6JsY7lqsE6gVIJTQWP3luTjxNGoxFdZ3rtpabrLEmcUYw6pgcZwguEC1v0Yl2RRzFd0VCvSnSacFV1jMch6CJNYpy1WGNoG8+2NYz3Ph2ZU/78h9wUnY9//Ns87uMi4tuP//jXe5XfbhwRQrC3t4cHNtsNk8mEpqn5jd8M1IS2bYKcwYTQya5r2G43XF1domKBjAkETRl0asGMrAYnEFZSFZa6FNQVSDK0yuhax/npRfi98IPKJHQ/UuK8oLOe7739LnXrcT5GqBwpZGCji8BcV73n+ECeFCLIVATheTpj2RQljx4/5vTsnKZpefjw+YBvdDWmbYIw2bR0TcNmvaQqtnRtw2azYTabce/ePeaz+TOd7GDPcpvIOeBQzrrQqXq3c2mQArquZjoZ8w/+wd/n9PQUT/AbH4Ifoyh0hUkS75wGxuOcKI7I8wznwziq5I176GCpcnBwsOM9BTeEMdPpdNf1DL/nbSypqqpdEMAwvg0WOlLKXULMTuLTj7C3x7AoiijLkqIMHKth+2etpe27sMEryVrzTMc/jH2BJGl337NaLmnrmlhFgXOLQCJQQhJrTZampFmCkMGMzgvPerPuqR6hOCqtUCrYrgRpjUagkTIi0imjfIySgdgJwVanbQ0gekJvWP/n+QhjLEppol2kVyjUL738EkoH1wQdBexrcbWgKirqIiQwFZst5XZLV1eU2w3OdCgh6OoanMd1Dm+hrQ3lpqLa1kRKc3V5ybbY9mN8g5QRTWNwVmAMaJUgjUN7SVc1VNuCsihomrp3vJjQ9bjlzzv+QhOMbx+ftOEbvv7x7x+mEy8Cs/iDDz4MGqMsZ7WqEN4TRSlKei7PT5iMM3TkSJJJSMmQiroK4LjWkuPZAdu1YbG5DMTBchOIojWYxoP1OKeJ0yBRaduSKBYBJ8CDCDwPJcB1FufDuOGdYL3d8u3vvs3f+PJv4lEoumAO11tqYIKxHNwUOSmDTk4KiReCi8srNtuCp6envPLKa4BD4AL7XCm08HgliLUkjlOckEgryWLNRV1zevKE+3eOdkJPGNj0t18bdsD5zb+EN2aaJkil6Izhz773p3zw4btU1YbpLGxsTk/XjCdj2na989ca3tyDAHX3ehIwLbhxXH3uuec4OTlBCMH19TUAhwcHNE3Ner3escrTNN1ZJw+2K3DD5h40e2VZ7rZqw+Zw2BI6FwrvAJgLIcJGT3iyUc56ve7tcWKWyyWiD2jwsEt//riX0m0PNIHE24EaE1jXoZOzwbO7P7V5HwDaNM1udKVj56zqXFiAKBkhlCLSUXCfKDoW9abHqQAU3hOSqhPd87TCjcP34nvrLAhPksTQhLSigM95sjylbRq8dUxG0z52LAjpq6pC9dbDQliEjEjThDzPuLw64/pqQZ5npCJC+Ig0julaS9cG0bA1jmW7RnuFs6BR7M8PECpwA/fycRA0C0VbNzRdg3GG/YN9pFJUdfUz68lw/KVt9+BnF6pnOikfPGpC5yEpywrra6zzxFFMXTtMV/F7X/2nSOmQylKUBVEsKMstveEJkUrw0hDFDU0nePzBOdY4Xnj+AavFmq62SDIwwcLXGIurOryCuq7Y29+jrK/xXmK8oHFDlp4mjlK0UORxyo8++DG//EufZ5yl4F0Yyfp1tLAe37OM+7OBkgSCKB5jLSfnF5xfXeM8HN05hjijsS156qlRGOGxrUUhiFS4q4at4oj5a6+hlSCNFN7dLBx8MNC6dU5vvR4E6UdT14zGI0bjlLqpee7hA777Z99lvVn0ViTBmbMzHVdXl0zGc7absJEbiuHA1xEiRCAV2wLVJchY7mQul5eXO8+n2SxgHQg4Pj5mswmeQlEU7Tqd2zY5g0/XsCEESNNgXbJYLDg+Pn7GZ2qgGSyXy91msK5r9ucTsjwPIHyPQ83mc+p+G7kpCuIoubXRY8fRG8ZjY0wv1QqmbbJfgMhY9gLiOHjzW4/Qgs50/c02/N7WW4JtoMR6i22CR5Tos/OcDQqDrgu4lOlcWFZAL3QWWNdhrSPLwvo//G6GtrUIMWwkHdvtlovLc9I0pm62JElCsWkIKdvhubuuZTTOiKNg/Ni2FTKPiGPNbDoL5zUZkyY5WjrquqNsCkwHzjqKbYUSmqbtEE4RaUXdOqRKaVvH5998jdV6yUdPHmOdwXQtrQkhG847Ovvn3EndLiCf5nGf9NjbBeo2JvUT3ZQPbGnTdUilggGbMTjbMmTVSxMkAevVNa2pyEcxaZIGnouS1E3LZrvAS0OWdVycbpBRRj7KUVpy584RzdTTVRIvIq6WVwgcSarpvGM2GaF0y+X1h8FjSSnqNriFWg9ShPDFLsnxbsrZ1WPGL72C6AInykuJRiOVR9geg5IyaMOsRUfBiK9Y1azLgqvFknw8JopjWm/RSuCdAWERQoMI+Xe4rh89w93Qe8/du3eR3mGsoen5RR8fuW/jUMOyIk3TkIQ7SoiTiNU6EB/v3r1D1zXEcUS9CakswQDN4m28s+cd3AYG/VvTNGRpRtu43YZvsPmN42CF/NFHH3H37t3d5q4oCl544QXatt05aQ7fG+LUwwZusG4ZCkgURdy/f5/tNiQFX1xc9NhJshvpZrNZ/3cHI7zYOUajEcaanqrhdziWtRarbE+2vXE3HcbIgYsllEQq1VsEByY3wrNer0Lijgnmbo0wdLYjSkKkvPcepdWuaBlreh+zXonQj+NdF8JIw407KAm0VFjbUlUlSguiSPVgviSKJFGc0JqKrjeZUyp42AfpjEVrQARnzkAREZjOEMca2xlWy5I4kcHCuWnYrNehe5UJtpNcrlZoFVOUNd5LvBXMZ/tIoajKBiUcpnWUVUXbOLI0p7Et77/7I9I8JYliXBfO7XQ6YTabh0Sjtv5UtedTF6ln7Cj+Zxw/q3jdfu7AUwmcHmuhazu6LrBobxMR83zEehnu+LL1IdKpl3asNhs89Fq/luVyQ5LkeKtw3lI1BbX3mAb29x/w0ouvoBO4vL7g0aP3oHOcXzxiPMmCjYoH6SWpVqAkTWswxiNJKX3J4uopf/iNjJdfeQ7ErTFB3IwJth/vQtGg5y5LNkVB2zmWm4LDB8+HbYvtpTK7k9e/iSxEKgR1nl5dYYTGbC/wxtDWvdF9U/c/QwY3COyzHWr/pM65fhsWxqLl+prNdsPDhw/6xwuWyxXjyQStYq6vryiKEi3ZCXpvb2aH0cr3X8/zfDemDa+x64tEiJ8K0epRFHF8fMxHH31EHMfPrP+rqtoVt4GDNJArB63ckOQzbAqHsIoB12r6bmW93gTzJ9iBwUKInTwn6p9X7owK1Q77ur3UCcuOcH7KokCIMUrL3tzOEVxGx3j6LrBtwpY0iRG9w4AQQfCO8zhvcV3ApZwdRkpFmJM8qneNqJsWgSBNI2BIFw6M9SiOqBvJZlOEwiQU43HOdDpGa0/dGOqmQsiEUZ5Qlg1KhptppDVFWWFMQ5YllEWNs7DdVkQ6ZbNqiXTKql4HXZ73JInCdMEvyzoQSpFkCc6DNZbGNmgBy/WaqClJRzmzfM6Y4MYxnMsk/gUic378+Dhwfps/BezufoP/tpDBbgXCxV43FZ2x5N4zn8y4vDaU24a6a6iaChkpUIK6LRDes1mH9bhEoCPobEOShPbUq4qL5SNWq2uUlmQjjXYZo/EdLq8v6WywdBEGqA35eIz2tjeAC4xgZy0fPnqf29ykwPQmePLsGN4uAG09P8o4R1nXtNZR1A0PR2PaLujyGgGtMZAEUbXSGi8F51cXnF1csigNZWPJKHFdx94sCHVVD54OTpz+1s++/WbzPgD3pjGs1yGe6eHDB8GdUym225I0zbi8WAAQxyPwLULonbg2SRKqKuAKeR8QOtjbDuNRHMe9Ds7vjATzPGezXXN9fc3R0RGPHj0K0pS+KCRJ8ow+z1q7w7+SJNklwDx+/JgHDx6Q5znn5+cAu+IzHo9J07S3bnHYTlJst2FZ0YPtWmvqptmt+3f2PLdumvIWzhdOHDjjiZSgNZaqKPriKWmqhrZt2NvfQ0YSLyFVgYYxGucY2+FCEid7+3PKbRm4TZ0jTXIs9Fy24NnkcUhFSH6RwXjPY0G4IM4VhqbpaDrI8pyj40OaOigIoj7QNM0ixklK1HgiP6VtDFVZIqWiKkrwKVpECKlJoxypPM46YplRbBqkiDGypakbojimMy1NTxAe3qtCCIqqwNmAdg5kikhLGm/BdHRYVBRe/1mWUTU1dfUL4Mz5SUD6x+kGP0E/6I/A+g1Shaqs8MICspeazGg7S1tULBdLurbD4rEe0mSCIbCnVaSo1iV0BqFjvBDUdYlxLXvxmDTP2XSXXD05Y5aPqYqOpm7ZlAVN25JmCft7hzt/5iyCtuiwOIw3tMYyzucor1lebyg2VfAd16rvooaoLtMXjlB0tQB6/VjbdXgEQqlQYAjxT1VVc37+FBfnrGvDOM+Z5zFnJyc8+ugJMpujsxGLqyVNVeBMQxLH1OUW4ngHQt0GfaXsbZR7V4fBJrZpwhj9uc99nidPntA0LVeX15S2pGlC6KTQIV9u+FsGIHtnwdwD6ddXVxyO7gCBnbxarXYBCsPvMZ1OWSyudgDyEKs+gMpXV1fAjRB6GLmGDm4ISS2Kgg8//JDRaMTe3h51XRPHMUVRsLe3tyt2AT9y1G3L3mzGcrXs1/US63q7FqC17U/gUEOBfaYbdaHzGayCw9jbBeNCIdE6Ih1lO4Z8uLHWuxuH7a+nJNV91JdB6dCdSRncPQNAHhxqjWkZT3Lme2OcbyiKLVIBogPR4rwI7ps2vJZZNiJJIoSwVFVBnHr29iasLmpOTk5RMuGzb7wRsFZjefToEUWxJU0FkRDk2ZjDgymnTy/Zbiucl2idYHp+mjGGpjFIKfrtryBJNEJJOtOiB918pMnylPFoRGvakP+ngllh1zSM818gP6mfNur9NCpDuBBsTzRUgOjJc82O7eucRTiH1hGR9XRNjZAa58K0dHW1IkljqEG6CC1idKxpbEs2UgjtWBVXeK9QPma99hRlhZRBCjPK9qjqhicfXfebFJiMZ1TVBpQkzSLaaotwGoXGWkHbgEscng6nQqFyvaulEGFMsM4SKXqyYHBS8FJQVjXf/s53SPIxWT5inCU8evKYq22LUwmvvvIK5WZBpCJmewfYKGfv8A6d7mibCoVjze3FxE3h33UJ3IzLgyQmiiISpWiWFd/+k2+jdSgE4z7GPSTQBlxMSk0cq90WzfsgNRl4SlEUUZVVj4ulu8I1sNqrqtqNV1JKrq6uePHFF2maZvf/NyxvtcOL4jgO/Kp+zEvTlKJnyFtrWa1Wuw5ss9k8k2Y8eFKZNuj3hucrqyoQRXuMLuju5DOynUELOOBvw6gupSSJEpI4piyLQBUwgQbjnKUuK1SuccKx3q6J0gjbuycU2xAeoSPd5+TlO5O/OMroukBRGCyno1ghpAYcdVOgNaRZdPN7JBEeSVEEsvB0OqOuG4qyI048nVkTNRbvW9J0wuHBDEGQV3WtQYqIe3ceUJRF4MI5h2kLVouKsuh6EbTAeUBKvLfEOvxMoLf18cwP5oxGGW1bB8lL0yKIsRJa7+icDc6iSrJarXY446c5/q2L1M/Clm4/5ufhV4OI8+Ns9HCxaLxXWAxdF1IxYpFSloY0S7C2I07Bi5hW2pCAIYI30mQ6xdQWLRT1tsY0DhVF6AymsxSEBmno2hZpY7rOUVUG19XEcUrX67jqpiLN4nAxKRWSO2RLNNYUZUkWZcznM+IoxjmBlgnf/d43+I03P0+WT/rzA0JpnKuJJUgcsfBUPgYsEVW4y6oJ6dELqG5LqmDTeGqtmd6/x/3JEdvCEicjtBDU5QJDwd5EcDCucVHER4/OyPMJQoRgS+8DGBs4OOy6mNCI9yTS3fkPnYnSe9y7f8hmU1JsAxa0WK2IkiiMGMqSpTnFtsV6gRCOJItRcW99LARN0xGnGVpLlJbUVYV1HUJ6nDcI6YmTiLPzU7qu3eFVQ6rOYLg3FIi2bXtz/253fQyeTdbaXTEC2G63uwIcx/Euref6+pqQAD1jsy24urruwWWNUq63Cg74DNLvOFPD9e1vgeu761QIiqZGCGiMpbUhVmwICNmUNeuTgoODA+Ik3fmRNU0TmNoI6qZFi5imboPVDhJjm1uvT3BlrZoCFXnifAwK6q4jTiKkUj3XSrJabTDGEkXB3ylOfejGnCPLcpq2pKo8nTIc3Lkbtt5d79UvFUkeM57vc2A9Jx99FAB6FVJnhBrsfkyPYQgcFhUR4tmVZTKboBRU9WaHtyph0aLGOsnioiBORkRygncK6xriJCTqfJrj36pIfbxAfbwL+jTavI/zTj4uk9k9zoFQgrZtqJt6N7cncUySSqp2jdIxrTGsNmu0jpjvzXebEW89zngm0xlZniOEo6w30I9TWsd0XVCOC6/oTEdVr0mTGKUlTVOTZhHOtmgVkyQqrJalZO9wHgihVcV6syZNcqSo+Wf/4n/kO//6X/Of/+f/Bcl0HxElqN4JM9AOPIgwtyvviHyLdh3OWNbLFdXlh2Aa7PQ+8zv3ye2KrmzZFpbRaI/Li3OyVFAV5wgD4/iItiu5e3cf13qapkbrqJ/0ni3+g1H+YOUydFNt2zGZ5ozTEVUdiLBxEqNVcCeVWmJtR5algWipXC8x2QYv8+swtikZfu7hwREjGYI9T+q+2PUGdbPZjPU6dD3T6ZTHjx8zm812TpovvPDCDm8aiujAnwJ2d9+BIzUEXwzSmGEEHegKt6ktZVGSpClis6Fru11whSdACkL2rgbmRqw8dGLDNTqEqUqtw5LGud41IYy7uw2ukHTGsFlt+85MY1qDaW0/JAbAPoxz0HXVbuESdILBj16GmQ7n7M54bpTnNFVNFAfsKOpjrJIk8Js60+K9Q+twuRljGeXT4Nk1CYk+h3tHZFEOXjGfHVC1htl8n7Ora6pNxWb9QU8itURxGLeFDHQgZ3uMrI+uam1HsQ1J3oiAfSopGOcjEi1ZbyrKokCrLFz3OrD84zQkOX2a4y8dOP8kGsLw9eG/4TE9KTFMLlhjsQTOTtOCpWWcpj04mzCf71EURc+kFnRt4K0MI4e1Lc53ZFmClLpfZzuapqUsyrBxMR15FhNFCqVSBGFrtV4H3Gs6mgLhRA9s+KapaJqWKMqYjKasNgWL1Zq704PdeBBHGiU8zoOxHqkMsWuJXIO2NcrWUG9IfIfAUJsK6g3Xj9+j7jxKZ0yfF5jijM22wvst6XTCKO744MOnJFFGHuc9SZSbc+tvn+NnbzBDIrO1hu22QMeOKJn0GrQYazyjPGc0GrFYXYOHq8tLtMhouwYh4PjoqOcrLYmjCNO5EGrh/Y4ukKbpLoR1sDyJ45jT01MAyjJQHPb393fUhqFjGigMs9mM8XhMWZa7jSLQvzHznYh5IIEOJMrBUUFKGciEPQ9rMplwcXn5jN2y7I0IvXx2TB6A+2EBYHrLG2C36tda7c7p7qbbR/5453cfYRwMARDeeejxL9tnQHon+g4vFDohCJ2xcWil0CJGoLEG2iYoAFplKYuKPB8hhCDSMQhPUWyx1pDnWaDLRDFJnDIeTdEqIsty9ucHGAPj2R5CRkwmY9qu3WFk1vkQ2SVCylAURRCJ8P7rgiuE1grhFVKEjABnbRDQC8UoHyFETLkNdAchJVEsMT6kxyj178B273axGu5Yt1nnwZM7CGq3RUEUZaj+LmZpSWSwGInjmNVqzSgfc3l5RdcZvA8tc123yNYgpEPKcMEVRdGLfSV5njMejcjzlOaWmNX7IEOII0WWzsCDFDFCONq2xpgGhCAfZbStC9ayccR/+Dt/h/FkSmsMWex7U/so3HnwGOcRwiG8QTqL9A7lHUqEla4SDqwhQYbQTe+R3pCIhky3dLbiuQdHPPfcPicnHyHEwCDv9Xre3pxXbi8obs5/oHcEb+TBMz1kodkek1KgPEpqpJDMJyE1JktSnBOIzuGdxXRduNikRKuod3YQOB/cDIYNX1mWlGW5G+ekDK4C8/kcY8xui1f1ONHtbnvYFC6Xy2c4X8OIODDTh5814F6DT/vgq743DWTO4edD/4YaaAltu6MX3I6yv31NDtu/gco38MSM6XbUjiHYVSpJmqQYazGd2YmfB92hEEF1UBQlg7wi/M2D5UzAxSIZg4iIdYZ3sFpsQUBdtYiRDsXOB8yvLKv++xxxFKPzEWma9N1rRJqNuX//IcW6oK4a5H6EUp7NZkuS5lxdXhHHEV3wcSGKQycnelK16MXTSim88VhjUVJgOstysSGKAvVByEBh6JqWJM3Z25uHpVXb0NmGzpaoWCP7XMmfd/ylFKnbHdPtC/D2x43X9G0GerBt2W42FNuSo8MZddMwnqQoKVE6omk6yrLhzvGdoMB3wUY16gMQmjqwm7UGIT2daXvTenrr2pimrmiriq5tieOYNA5v3IH46Huc6uJyyYOHdzHOMZ+OKMuCqqqZTvapK0vTGk7PL7h3/3lUFt4Awtjg/+TBeYv3ApzEoDBC40SElzFexhjC3cYJTeckQiQoGYqbxWDpePDCfaazhNZbmr6wWFOT6XzHYI+Gbam/OZ8DcD4Uq9BhBqGttZL5/oTr6yvwYdRNohzTWUigrRpefP6FQKhsLXVdUZQbpJA473jpxZdYrwqcFWipacrgMjBs4wYM6baFygCSDxYng8TlNrt7wJwWiwVJkpBlGW3vXBBoElsODw93Tp0DWD5o/pxzuwSZcZZieq1iVdW786J6wL01XR/p5XY0Cq31znt9KJCyD8cINJKbbmq4ZoebbRJlNFVIAI7jGNPZXUhDua12m8OmDonRw802/F7hOg5YYjgvVRFG2CQJ2kgX+XAdWYd39LHwDaPRKLjTOo+SEVXZUpUtdb1kOqv4/p+9Q56NmGQTLi+vWFyvWKw3IUMyCjYysk+bzrIE5w3WBilN+Js90guU6F1BZQTOBzDdWdo6TCuJTthu1tSNIYpivADnWqJYopOYLAvM9k9z/C/yk/okRvmnecxAbtwJXt2NIX6ShBbQM7CjPbPZnNF4j6o0aJ0QxynGQ5aM2KxKptMpZVlTFmXgangwhK0avWWulAodBWP5IQlmsVjhHIzyFGy320CFFt8RaY2xhslkijWQJlNWi5I4VQh02GCFEC3msxl/62/9x7x87xWOju6gdNxvk4JIx9jAj4mUpHMSLWMimeJ0htMZjY+orcILhZEphphtAzqNsNLSCkinYyaHhyxXF6ja0bqYOHF4E8Y2KcJfdnOyn92ghsJ1Y+YWBJ5BkCvkBKRis9wyyic4Gy64RtU0VcPl6TlN2/K3/uP/iOeff55vfusb/PEf/3Eo5ii8l2iVgje0XYdWQde2t7dHmqY7DyghxG67N9i5DGxzYBfQcNsv6jYNYLvd7mxb2rbl9PR0R0wdCtsgYB6KjRCCy6srVC+Qlkrh1zepObvC1G8nh3SZoeMbfgcpJY4hFqyPRhM3OkalVL+dbJ+R8Qyj7/A87taYOcSn3bYgDrSDm/BN+kWHVhJjHFUVxu3B0kb2HLiBna9U6NTaNhSIrvXUTUWeTcmy0U6+c3mxQOuI0WhCkuU0tiPvsUelQ0dmTHdTpBH92G4RLtgpQfD96kzTv0bszocxFkfb2yFJPBIhIU1S4kiTJH/O9sE/CyT/accnAee3pRrDxXf7Tuu9D7HjBNMwY4JvjyAm0glRklBstxjfMM1CQWrqBuc8xjisDYZsaZpTVzW2C51U0wTnQ6UEIksZRh1rPWVR4k1DmqQBy4pjEJKm7lgsVmxWNVonoOZEjhB6GHt0JBiNJkgVUzWGLJsyme2joyQUJSBSCgs7r6ayromyFOMsbYi+waFQUQJS01mD9ZLOC0hitl1FNomJ8phiVXNydkaexiyWS8ptzcHelKps+xsCOz0XtzCp20zz/oXp3RAsQjru33+OyV5O3dXUZdObp1mO9g+5d+cOv/Xl3wRvcd7y/R++g5Lw+MMPyZOYzabA55bRaEykM6TUFMsVdc8Wn81mWBssTAYPqeHNP51OkVLu9HvDSnq73e5woGH8C5HsgXc1XD9DKsx8Pt99T7BKYedllSRJGBm7lrqqabuWyfTGZE/1N9LOBEXAIHIetouhewk3Tudcv9EibNZu+UdJFW4UxgaTPOlDl+l9yE9UovdIN8EBIwD/FqXVrSIXOGzO297J0+NtSCPy3ofxugmpMjoK+YTeWJI4wgtLFMU93hrY+G1jcbYlzydMJhp88FTLsjFd1aKkJMtybB20dMXu5hE6qKZtSBK9C5sYjSaM8hGm7Q32OoGUYLoGQQDMm7rEmrrfagZHiOE11ZGiKWuUnuG9penWn6r2/IWPez+NBzX82yBNAHZbnUGfFTZxFmODzW6SpDRtiye4AayWawbvpHBBhTX4aDQljhKur5boKEKqcOfTSvayAt8D5Yaus0RSsX94B6UU19cL6rrrHx+RxHlQqosYfNprCMNdT2lF1wZ8KVIZ1kiMA+OeZSsPq3QQ6CRFCVDeoDEoa7B1wf2jA3xm0Fia7JhkvIeeO6JEMDsYUbUbDg5eC+BmWfHBpgCdYowNm6tJCC7dFSVu3A52bPd+3AuUF0GSpoxGCb/927/N5eKMp6dPg3OEjNmbTcB5Ls4vmI4m/PIvv8X/8x/91zx58pSXXnqRN9/8HL//+3/ASy+9FNwg1lumk3h3Jx2NRmRZttveDTwq7/2uoxo6iCRJdiN/nudBnd8TRIMtT7PziLrNn0rTlDRNuXPnDtvtdjfuDWTP2zjn0dEx51cXSCvp+gTnKIqYzecBkK8rrDW7TnT4fYYORykVyKaSHvcLtsKhewrs7nDjDSnYiQ5e7E3T7Lywui7EkA3XhlSaYXs33LS1DoXP9LCEEwJvh6lE4EJeLkJ4oiiMXAO9JI57//emw3ThxhFHCUVxDQR6ymZTsTc7QGcavEDrmMk4wjhLluWU6wVt15JlMVEcE8chzfri4pLZbIZWEctqSRRJZvO9wNPyjqLY0JkGpVK8Dy4eaZqSpCld14ablbMY62hqi48Vq6vNp6ohf+mM809ilw+t8tBWWh/eVLLHLwfNW9cZvAt5fF1Xk6QJXWeoqoYoiplMptR1S9cauna7u8ikFGRZhFTgvUFrtdMDJklKqjXFtkRJRZ6Naaolk/GEJMmQIkYKjVQxtckpqiVxOiLLg01qFMUhH00ZkBFKB4O04e+8Lan46PFj5nt7jJOEVLRoUzFJ4KV7hzz34B6HmWecRWz1HjbK2I8KolTw/qN3+R/+yX9L0xS89fpv8uTDx9yZzTkrzyjqGh1pXn31VT5678mOjPlJuF94UYabQ5CHaJ1zcXHO+fU5i8UypN3UgVdUrDZ8/q03mYwnCC/4wltvsn9njulafu1XfxXTGd5//0NefvVVPnj/CUJEWBPa/9v+4kO6cBRFTKdTNpvNbnTb39/fyV0ePnzIo0eP+vE9hBgMXc3QdQ+M56HYDWkz3vsgHu49igZQWynFer1mkmchqqkvFMPIOzzemiDAHV6vAXS/XeiUUkgdeBzh3yxtGwS7vh/9wpbOY1pDnCRBKtN0gToT9SncxmCNQ0bxjsKwo4zIQOK0NmBA1oTwjt3I5UKicqQVZR3wIu+Ckd54PA3jslBY62lbgzVgOouOYp48OWVvMmN5tWSc53gXzmFjOq6XS5AKU2/wPnAOdZTyla98BecMX/3q79N1Lavliq5tGY9GONtRFg11E7R/Sgmm0xBnb4xFqMDEN8YQJTHj8RSpAo5cbDu69mdPYsPxV7Td+8liZe2NyZgQEMUidCVGoFWOMZ6ua9BRhFIaZILwAaj13oeoHQGx1tBvuNIkBhVm/Fhr4kihBP1FVJLoCEmE7xyJCOApWPI0QRiDUoZplmGlonOecWw5OjjC+xYhOhwBFNVAZxRKxTgU1ofRS6hwYcmelzSaThjPJkRdRVtXPP7wMZui5X40oW4r7PWWi6Zk7TR103JVryjbAqsM4npBW254+1vfwiLZlgXrcsUsViAilmenpFnMtuxAarwEryTeOYQP/OBQNG0/3nQIpTi/vuZ/+r3fR0pBV3tEBHXdsi0LtuWGP/3ut3nxxeeQwjCfTTm7POPozl0e3nnA9Quvcnf/Ln/t3/ub/Jf/t/+KKI6x2lOW7Mam9Xq929LduXNnJ3nRWrNYLJjNZjth8MnJyQ5bUkrtOq4hgHN4nps4J8nR0dFO/zcA7wNrvWmaHcdKRTE6jmjalshrxpMx682G9XaNUhKkpzENWmlmsxmr1YquM8Q6DnQIY6iahkRokC6oFxqD8UEoLJBkUYwSinw0pu1gtVqiI8jyCO9750wFXgtAop3sI8UkTVcHx4NIo4QgUhrTtXS+F5qLQFdAhbRgh0BITRynREnEcn2NQAS74izpuVptANkFdMZwcfKE7fU1o3zEK7/+JV7/zBu0bcfV4or//h//dzSmQ5hAlZlOMhANH3z4Q77w1hf58m9+mfff+wAcjKYTivWa7XZFY4KovzEdaZ6TtGB9RAc40aC9IkpjWmfwZQUO9qf7XF1e0dq/4CL1s8a4n/19w+M+Lo8JmxIIWHfbVcRJgrcafEwcSYypepMxRZQmGOPoOofWwXVwuVjheiwoz/MgBpWglQJrgr2FUmipiHxMWzm8BuEETVNT2oZklKC8w1U1wgTGeGlLdJah/QpXlmgZ412HFA1VuaHuBHF6SBYlWOv44NEjptMJh4cHIXYaQArm+3s4LM7XtL7j8cUl//KffZVqU5BnOSqJWTcVMk2xVcX9PKd1HT6CO1HMZDwhE4qnl1eMspxZlvLl51/EKk2J5O0u3M2ccHjhwzpdEJixzoQ1d78xFUJQdx1REuxHxmlOcR00i0macufeMfPZmM++/hpRJFkur/k33/gGr7/xBk8fPeH+wV3efP1zXF+v2CzWeBsKiHUhm21YiAz6vqETyPOcPM85OzujrutdhzXYwQC78XgYAwdB89AdDaNcmqYcHx8D7ADzwQN9KGplWTKfz7HO4bwjzdKAIxFAX+NCUU/zOOTuWUfZlBhn+k69QxFiwow12MqQZILxZC+w8bcO2xqUl0RSkaiESTLiyeYapQTZKGYyjdk7OCAfj7lcrHn85Jy2M6SkWGPxPnDphA6urtYYmqpCiTBi2l6y21lD1nMDnYc4yTDW0RU1Sii6tiWKJNa1ZGlGkuVUVUeapSGvTziE7yiLDX/6p9+hrBqW6xVxrJnOxjhvwSYsV+fUTcF4ojg5/YhIJXzp17/CKy++ysXFGbEQfOdb3+LDJ49J04x0PKKoKrI8p9xW/chs0dKG3D0dIYSk2FY442mqgA92Tfupas1fSSd1+/g4udN7H9abQmOt53Ofe5P/4z/8PxHFceBqyIARdNbgTUfXdsHvScBquQoktgGkLks22y1d22LbhrrYYPvtUZy0eBSbbUW1XLE/mtJsFjSbGkzHNErJRAIypqkdl9fnpBFoGaHQCAxCdaA9Uoe7jjIGAfzu7/6PfOlLX2J/f383KtxsiSTraoktrzl6/pDx8YiDe3OaumWyN6c5PyOdjOhahZGCSCniSDFXE4rthvlsj6gMuXbHewe8dv8FLjdbKiRx6zE+WNlqEaxuhAXUEMkUiILDhi+JYtquxjaGL3/xV1DGcHZ+zjid8OKD5zg6OuT5Bw+YjydcnJzz0vOvBLviO3e5uLhAILm6WvDBo8cBe2kaWmN2XdTwt+/v76O15urqCu9DmvGwzRuK1CB9GbZxQ3c1mNYBO0LosJU7Pz/nW9/6FtPplPV6vXNdWCwW3Lt3b+ey8ODBg+AMStgqR3HUA7mapgts9YP9A5QMFkFFUeKMpWtDXLntOpQKvCxj2l6YDWmWhICFtkVYycFkn/loxmZdMJ/PuV6cYa2lLEsOj/dROuL48BAlEy6vl0zFmOViSd21dKYh0QlhoaPwVuOtw7oW2QcYCDxSeLI0BN+6HisTQuLbBuE8tgtk01YatFPMJlPqOuCW9+7f5zOfeYOm6ZjNDkEoDo6OEAqm8ylZnpLoCf/8n/9jEB2ma4h1EsZFqZkcTDg42KNtDRerklLqHpOy6MUVr738Ah+8+wPaqmKcJqQiI1U5UZxhhORcOhZtQW1aJvM9Krf8VDXiL71IfXzM+2QGeuB4OO+ZzQ546/OHJGmGVIo4TkIumdakOtp1X0oHIqFUOmxdwrPjhA86MeGxbY0zhrZpKKuaqm65uLzGd4ZqseDd93/EYnnJ5ZOnNMs1soPVZkNMTKYyRiOJFhFt1ZImIZk2yWJElOKcZDbKg+ul8xweHlLXFVGfLDJgGs47tvWWP/32N7BNC7nCS0VrLVtXs2jWZHHvRZVEYfNSNjw4OiSOFCmC/ShhL5uyaQUxGtGE7iV2isaECGzlCMUo9HHBb7tnIcqedOmdRzh4eP8Br7/yEr/02sv8v/+//w2//pu/wXMPnydNUmajGQezPe7MjzndP+TJxWMaqTg+PCKOkluCWEGcBJmSh1vr+I6qqjg8POTu3bucnZ3tXvv5fM7h4SFRFLHZbHaylgFoHjZ8EJjpw5ZvoIkIIVitVjtMaiB+DmJjCPbT9+7d4/z8HKFuQPGd/i8NMpzTs1P253tkWb5zQpBywJ5C5FQcJWEk0xoBu9W6yjISFRP7GCF7smacgm9RsWMyz8jzMVpHHB4ecf/eQ6zxmFXNN7/1TaIkQbUeqWVgcOMZjUKh70yL61NrBhcKISRSQNU0CCSTcSAkdyYoMrSMwQoQwY9tNp1TlxVRHOOcZ7Fcc3znIXGS4j3UTUXbORanFzw4irlzfIxxMdaW3Dm6Q7EJmK+SiijSIBSfffNNrLdoBft7U370zvd46/VXcasrrk5PmcYJuYgRRpJkCZuuQzQO6QM5e7EuSMazT1Uz/so7KXiWlhAOCQi8c3zw4Ud858++x2azRYiQf7febMlHI5RQQRgKRHFEmqRMptMgME1TxpMxs70Z89mUV19+yCSf4q0hSy1Hx0mwGI4/ZDaZMcoyfsPWIBz/zT/6r/ngez/AlS0vvvYGpBmPr85YbB7TVoa6rLFdidIp6SRlvn+M9TlWuKDpusXpEQKm0yl1HeKVJtMx7z96wnd/8C7lekOeZERSs90WNOcXtNZhE0PTNWxqSaQkqYx4crlkHCXYdYmIMgoDyWSPZDxh6uG6bPBC9B/ghMdKjxXB9kZHEc72rGkPwgcR6nQy5iu/8WXyOKJaLflP/td/B4tgfX3Na7/yaxSbgndOzjFNx3PP3ef6+prnHz7PaDxGCcWbb77JP/sXXyWKItarNdd9SMGDBw9o+lSUAUe6vr7eeZynaUqWZbdirwSnp6c7eczAeRrkLhBioyaTyc4cbxgp4WaTOmziIBTBtm354Q9/yGQyYbNd78TWA641Go9o2xaHRfcp01pItJDEWdwX9Bu/dO8F1nhWqzVJp4ljTawjRtM9MpnRVb0sRHkm0wllvebg4Ig794+4f/8+sYpo6o4fvv1D3v72t8mTmNoYjFdESYJOgpe46RraPulFKY8UFmM9kYqIIkVtHEqEv9NZh5JBmHww3yfNUi6vrunamkinREqR9U6oo9GYN+/cxxhBFKesNxuSbMRLe/s0bY2tGu4cHfHyq29R1yve+MznWF6XjLIRUgi6tiHTkmSs+fKvfp6iKJhNp1TLa7J8SjY+YHagSIRAY0FFdAIqY+iswxo4Ojjm/HpJtf1zdub8NMdt2cJPw6dCIfpk0udNkeoV+x6EUMRRgrVbwNG0hjwbkyQ5kbzZZOGhrjvq+voZvMx6j3WGz77+Cn/vf/e/JUvSABrLwGMZjUf8X/7L/yvnV5fUtkVrgWw7osaSq4S2KNibTfn7/+d/yP7xmO995/t8+5vf4vFH76FkS2sr1l2D0imdEtB2Ow7O1772df7aX/sKxhguLi6o65rzizOKqqOzmjjbo2o6ThaLwO6WwUjNiJa6bUmiiL35iKLpWDYVC2FJlKGtWg73jkgjidosubheYoWmwmO1wmuJigLxr7Ee5QexrUQpHXRgSiOI0DK4FZw9Lbh3MKftO82TJ0+4fvFF3vneO+zN9vnC57+AkPDFL36RpqqxxoCEqlqzXCwDSN8z/WeTyQ74HkDwi4sLLi8vd7jTYLlyfX0dvqfP0Buuh4FdPgQ1DNfUEAB627J4GO0H6sGwsTs4OODk5ISzszMmkwmdbXuRsNsRTAchcWuCT/5kNOklPYHdLaXEWc9kMqGqasaTMWWzDYuGNlwv3kuKYoNMJEHaL/E26ASvrxeM98bMD/YCBy+JWFxc8O473ydPFK1tibVGqAyvNZGOQ5qMksE9QYieV+YYjcYIFJPJjEuzoKoa2rZjnGfgWhIdciMbYZBoqqLEZZbzkxOKsmR8f4QTMJvtYQwgNPfuP0TrQQqj6LrgInHn+C4PHvwSo2zMvSPBellQFCv+9DvfZHv+EbE3lG1H5wVf+NUvgYiojOK6FFwsLW1XkqQNd+7exziLy1NcUdKWFbKoee74Hln2l0Dm/KRjl1bysZHu48/189jq3rteEd4b/1uH89A2HWkywnvRb+M+Lk5mx7MKZLsgjEzSPPjyCNE7EXjaruVqecnv/cuvsm4anArSFWUMD+YH3JkfcvLejxEf/Ig/evd7vPDyPd767Bf4m//R3+Gf/OP/lvfe+x5xKqmdIZESkcRoqfm7f/fvMp/P+K3f+vLuDTbgI2fvn7JZl2xWFUmcUpUdOhrh6NhuC+qmoawMWZqjjOCy3dB2NTpS5KMc0hGtTDi1DrqSs9U51kOSTWiVpDaWRIhAClRglcfL2+c1iF1xvSQkiomE4rVXXubV55/j0clT3vvwA+Z7oRXvbMfJ2RNefOF5njx9zLYpeP3V13h6csLDBw8Jyb4JTgrOr6577kyyEwPnec5sNuP999/f+USt12vu3r270+xtt9sdGXPAsgagfBj3BmB8eM6B5Dlo4QawfSh0k8mENE25vLxkPB6z3W6pm8C/0lLv+EoDM7xpGlrrkC5EU0VxRFPVJEmgucg+2LXYFqCD4NYS+FJ1YxglYwAkCi8FQniSOGK+t8dstsd8vo9WEV3b8sGPfkwMaAltY4jSGO8UXkQoocOiA9k7KgRX2iTWvPm5t7h75x53ju/yT/7J77JdF4zyPCgZtObw4JCiCD7kaZzTVF1IUG5bTNsx39tj/+AAHcVBKC01SsWs1xt0HNF1ocuO4wg8qD5wxHUWayybzZary0v+V7/5JShWWBVzsd6wXq1xSAwxRuVclo7zqwXRrObCBTcSLRRdbZBa07UN0ln2Rn9Fpnc/j4X+aQ+PRWtFXZdstmusu7lDDq29eMbqIXRe3t3o/px3fSyQYDIdIbXY2ZRoHZI3lqsrNpslQqV0XQPSI73n/PyMxfklTiiaYk2BxTjDetHwr37va7z5mVcoi4a2tlivSGOFcBIVa957+z2ePHnM3/7b/+Hu7j94fqdJgvQebwwy8aRJxOXlNUFk6hjnGVmWs1ysaKjZ258Ry4S2a7i8vqZomhBr5RryLCNKIvCCoutQcYS0IbVYelAelO8dJAkjXk9DD3pE2zEdjfnSr/0a++MQZHn/3gN+/MGH1E3D2z98m+neBAmU7ZYHD+/xb/7kT7i8uuL5Bw9pmhD68MKLL/Bnb7+NtZbxeMQ4H+34UYM8xTlHURS7YjOdTtnb20NKycXFBUqpnf3weh2YyJPJZNcZDRKXAWsKHlHTnfldkiScnJzsrF6GuPbNZsPx8TGTyYT33v9x4Fz1NrZCChKVhK8ZTdc1rNdrxuNJX0DLnYbP9UlFzrc7bCts2RoiFWQkXddBC6Z1GBqccMRJTJJmWB+Y6aZpKNZrYqUYpymT8ZSzq3UI+ETRtg6ExTmDdY4oysCGkfO1V97gs5/9HG3b8cLzL/Hejz8gTVK0dCGgw4XEGQDpQvQWjv5mFHF0fIy1jqquUSrlzt0HXF0tqJuOeT5CiCgUxv4ySZMMSaBENHVH17SU24JHH53QrTcUneHp5RUvfOZzIcSha0kSHTiJUgAJOsppTINUEcd3jpjkY548+oir6wvuHB99qlrwF5K7N4xun4aS8EmHx/cFyNK0FU1T431oRdN0FC4GJfGEyCARfnj/zf5m4+EcnpDscf/+/b5wBZGkFw5jG07PnyKcJRaB6yIluLZFGIu1BicVxDGr62vWFwsWsxUP797j7W9/nzde+gw//vHbrK8XdBtFJmJ0b9E7RHAP5mP3799nvV7z8ssvc3H+Y/b3RiyuFyAlDx8e9+TEDmcCrnJ+tiUZT3C0SOWZZilpNEUQVOdtZ4iUZNFsSeIUvMYZh/ICZT2RBRmMDsLF6xwStUuDtdagpUQCk9EYZ0Mh6DrLg+ee4zd++yu8/cO3aZsa5wzbes3X/+hr3L3zgK7rWK1WpEnGbLa363aGEE9jzE6ft1gsaNt2JxIe8KK2bXfd0+CsOZA+h0DQPM+DD3m/3RuPx7tOfdDXCSG4vLxkPp+zv7/PcrnckUkHsucAlCOCXEbpkPnmOgeq90WXgsODA2xnSdOsz8QLo3AgDwfvcKSirmqiOASVKh22bACmMyQ6o2sahAyRUU1fbOI4oSwrEnwIEE1SDg/C5m25bkBqjAvC3Z7LDl7hjEB6TZTETEdzvIU8HTEej4PrhIDxaES1XQSfqiRFqpi2tSgZCgwymBDuHxyw3W4xVhLHguVySdt2eC/YbAq2RcmDvQnbVdh+4oP7gfchBUciyPOM958uUD5muW1YFZ4HPiLPUoRtSGjIqRjT0W0lyUhRrhrkJGKS5jy4f49Hj97n/vP3sfqvwE/qxgPqWa3Yx5urTypez37Nh+gnH0BB64J7onUWqSStadEyweEQfiiON1o16wb2r8RZQ56FGTtsuzwe29vAwHq1CMkZQ+eBAhXR1h15kqOTlI3pmE7njOIRkY55+tFjtHQ8/+DXKbcd42zGdLqHFpJIa7q2pa6q/vOGSGtircIGLlJsrq+QpiaNBBbPerNgW5QIqUjjFCkkd+4fYXzYKgWuTsxyvSSNEiajCcY0bK63yHESZBU+dGJaipCq6wIpTwYUHRw4EXyzvXA4L/BIyrIJnKXNmmmeA543Xnqdx08f89EP3mP/cJ+mbdh6xysvv8Lh4RHLxQqlZAij9I7nn3vAN//kW0wnI+JYUxUVURQFUHU2Y7lc7kzquq5jb29vB2pXVbUT8w5um8N2bsjPG3zKB2F6WZZ98nJK13W7gjjQD8bj8TNbP60DMTJSis4atFBBQGs9bdeAgEhrsjSDCKJeMygQtE1Lmiq0UsEsT0UkOmIyyVCpwYsGSUQUa5zRRCrGKodVipgIa4Mmsakburqh7AxSpmT5hMVmy+n5JQaJ7QwGhfMChESphEhqdByHsA8XPKdwFtPWPP7wgxDBbsI4lWc5h4eHLJfbgDdxE8UVeEqQRho9GVOUDbaDsmhxhIiu9XbNYnHN9eM1wtc8eLCP7DmNpjMorXF4oiQhiqc4l4IV5DphXVTszcZ4Z0gjQRaBch1pOuUrv/4lvvp7X8U1HcV6y3e/8x2cc+wd7FPWxaeqK3/O496Nd9ENafNjj/jY136SfhC+V6sg/jXGYToTxjQvaF1YwTZt3XcFYf4XQ0vle8MxQgGQeMZpxmQUBS2bNxjXERHRNTXVOkg0ah/EvqZ1SBmR7R+jo7DdGVuLqRtKG0BFlUmch5PVlnhyzPnFBZ0uaGQDncCZliyOME2DtCGI4fTshOBs2OG7jmpbInvAdl0Gs/tIx6zLjs16ywsPn8OZEilDOspqtaKoW1ScsqhK4lFMPIqomzWIDiVT0JamMxCp4AbpPEYIYlKE0zhRYFWLkwYVZ3graRrHd7/zvTCuektXNLz7nXd4/OEjnHUcJnt0jaMVnueef4715gylBO+99y770wOODo+ZjnKyWDOejhDYnWHd7cKjlNqFeA6SlyEfcADRVS9Lcc5R1/VuvJ/P5ztC52BoN3Rsg7/61dUVeW/Sdzs+q2kaLs7PuX80ZzZKObu6QI0ThII8T0ldTFvXREoxysc0VS8rMUGorpTebRm1VkRSME0T7t0Zs2qekM1ybKuxtUWS0lUdidSsut5u11mqYkMzHqFVQtcKtiZmHO1RKUmT1lRFHWQzKsJb8P5mAWVdixUdSjkuFk/YP0pJoxTvWiIhGcVjvLF00qJijfU2+Il3VQgzEcHzP05S7u5PSfMJWT5jsSz5N9/6Dkk+YnW9YVNs+f47b8P6gs995kXwLwavft+iouD+YKWmdQIpQKeCESlN43C0qDjQaGQywsVjXJLS6RISwy/92lucn19jOst2WzBJx1ydnDOZ/AIFMfy84+Nj4rDqlUrsEmbbpkFFCaKXdkgZVOXBCqU/fP+Zu+EFaeWZznLoS5p1Duc8nXGYzrNZlyipEULttoRaSUa9MZm1ltFkvFPzV1W105Y9efwRL774IqenJ0RaIQBjLU3XkY5G1G3Thy84PvjwQz7/+c8TacXKW05NQ+wcWZQwScf41qKspK5b9kZzqotrSgIInKYpWkccHBz1fCHD6ekZaZqSj+KQWCI9UoZMtnAebjal3jv8rRw/78N2DStJ0z3mezOyeU6LQ1uIhUQdjIi0gkgxViMq2/K9D37AcTZBesF0ckDbOE5Pr1iuNzgbEUcTvAvrd2st8/l8Z1MyWP8O9r9N0+yKz0D+jKJoJ40azvXtDmwoeHme7zAuIQSz2Wzna35ycrLL5JNSBmfRxYJ1EiGEJsvGeAvbbcFLd15GeE+kdLAO0TkX55fPGO8NlIWhK7PO0LZQbiume4es12u6xiPahonO0MognEe5DGMbpIhYL1fM9qaQGMazFCtWfPD0gtFkRpbEmKZFSejaEil1oBYIEISlh5Ax1tZ8/V//Id5b3vzsZ9GxBunxyqO1IhsFQ8FBm3njaw9FsWVvf58ojjk8OESoBO8jlssFM6Fo244kTnDGolzAzrzzWONIY4WSoRvXIgAG88mUOM0RYsqPfvzDUOS1oi7rQHWwFuGhrhvef/99xuM+rMP6fkxvGY1yyvIXKGb99vHTgPXbGzoIoLcUCmeDA6QxhihOcKYLPt0yeNNAr/YPrIXdW9O5XsEuBG+++RoIx7bYoqVHqQghFG1jKYuGJMmpWvPMG+Xq6mqHn6zXay4uLkjTlNFoxMXFBes+5fWtt95iNpsxn8+RUrLabvilX/kihwdBnzTKM1ASVIhyj/OEunMgEnAS34JoHbYx1E1DOhphhWdTlHgNaZrRNuEFltIyyscslkv29g7CRqoJo0o8HoHXeBfEqsOZCUXK4r3uR92bNF7vPHVdsNksWV1fkGcjMqVZbjc8/vB97t49Bg2dMDTOcH11zbVPmYzGTMdzDg+PuLy45PTsCus0Wo8wznJy+sFu0zb4Pg08oyF8AeDJkyc7UDxJkl3ay229XpIkvRQqbHJvx2fdeDLFO2rD0MUtl8ud82eSJHTGQe/RnU8ynn/4Ivfu3KdrG0ZpgnceLWOuLq931+FgKzNsHcPXDC+99ipv/cpnuNqcsfj+22A0EQmJloiuABzK50TC4VzH4uIcT0U6iohjhY8L0lTy8N5znJ9ecl1fEY8UWoJzHTqRu1fPmYAJdcZS1TUnZ6fcf3APFUussKDBYpiM94nTlNWqwPWk1+D9r4njpHdwEFhn0CoiijSjPOfunbtUHz4CAVmS026X2K6HV0yAEXb2xyhiFdO1DUVZg7esFwuSw31iHbFpNuRpTqxjVE93qaqa2UwR6Yiqq4NPfqRRWvfC6p9//JWHgw7HbZ6UkEGr5D18+cu/xRe+8CvBXkTpm1bYgSPos3ZFiuC5HPykgo3HeDLh7vFROClCY7sOrRVXl1dUVcvv/M7f4ld/9Te5Wi7YbDZsNxuuFwvW6zWbzYayLHfYSVM3VMV2lxuGc3gTeCqRlGgpeHLylH/5r/4lf+/v/Wc8ffKEtz7/ebqmYf/okOV2jfUjZAMTn6M9NNuSpqpxCiosK1uhRilLaUgrDz6s4bfbuic2djgn8EoiRfAVF0AS5Tgr+m7qFueAIRh0MD8HgaRtO0ZphlSe2XxEbiWicnSbklefe5765ClRWaBjgXINy8tTsiiiwLNe10jh2BQLkmSE1J58HMzb2qajaVqkDPl6s9mMH/3oRzurE6UUk0lI0zk6OuLtt99m3tulDB3S7QTh+XzOZrPZyYoGR86hgJRlubNwGSQ0g4HikOd3cX5OVXWMxqGj3t8/5PjOEU3bUG+3dFLy2ddfZ7Op+MEP3uXj7hVDRwWBHaC0Yr3acn25QdqUetsxGmnGWQy6Iok0ai1AJtS2w6oRQlqasqauPXESqDBdaZjlc0avjEMnZQzL1ZK266iqYE8jVYLtOW5t2/L06WNeffVl5vtzrLC0riHVEUfHR2T5iIuLt0nTnLbpbojOUcCkrGtx3mBsi9bBgbbcbpjkOUpr0jjBKIkNBEVcvynXItAy8CARrJdLjPd0bQNYTNeyXa9R/RRkO4N3gUFflhUhJTt4vq3XG5Ik5jhJmU7Hn6pe/DkXqR4UGv7vU9IRfmLcG+gEwKuvvsr+/l6/ZfB9kQo/xkt/66cB3FgRD8ZvjrCCdc4jhcRiMcaRZSPyfMzB3iFIek6K6CUQducDVVVV0ABuNpydne3M/KuqYr1eM5/PieNgbG+N4cUXX+SP/vgP+eD993n1tVcDeKkUL7/8cj8qjhFCkcQ5bVXjZUQ00ngtqE2NzDWthHQyQXYVRVGxXm2J4qgnLQZAFx9CSMOJCH7uoo8Ip3ce3RFnB1GxDMXd2uAQWtcVh3sp43HKdrUmHmeQpzztrllFNSfrJQdHM1pfs9Ul+wdH2E2LE9CYK6SK8LbDCIPUQctoXUMU3dikDB3JG2+8wWq12nVV6/Wa8/PzPjVF7nL1hvM+bEiHYNHhGhlem0GUfFt6MzDRrbU7gbFSiqqumR3OiZMEpTQnT09Yrpbcu3dMsd3Qllvu3z3mnfUHO9Z6sLHRu2J4s7F2KB1y98bpmHZkyXxHLCVHe1OwliiyHOxP6JyhcxoZK6yE86trHp+ckU9mjCYzUjVCKYnzHSpSrDdL9qZz1puCzbJCxDFaCZSEWKtgIt11PHr04c4OqO1aRlnG9dU1k96qumu7XZc5eIkVxZYfvPt9VKSYz45YXC/YbpehsJ2dsLe/T1NsMc5Qdw3GW1xPu1FRMIm0Jjh3nnz4lLprd8uTKI5YrpZEMmZ/74iuMyG1SFo++9k3eeutX0YQ8a+//oc0fce7Wq74z/7u3/1U9eHP1QVhN3P9L3zOoYuCm3DNQPuHG4Pcm0SZ29+vpKTtgjuitZZtGXyisiwLSS1CYK0n0jFJGpGlSQBa+7vH7u8agPy+aAYHRrP72fQi2FAvPddXCz788EOenpzx67/+JX7vq1/l137114JkQUh+8M73g5fSasU/+C/+IUVRst1sODs75clHH7FaLKiKgsXVNdfXV1RVh0PhnUHrGClUSGPp7+hlWSNliAcqig2IEFnVtg15nhHILmEJIftFghBDwQofWims67hanFPUJcZL7t09Zl1vmb5wwNiM6LqC2XiP+CAi1jHjDIRWOCUoqgYnGrqyxooaHQnW60WvFBA7szqlFE+ePME5x3w+3/lETafTZ8Dvj4+DTdNwcnLC3bt3iaLoGWO7AVQHdgkxg38YBKrBgG8Fr3WPsQapJMd3jnDOcLA/J48lZ0+fMhllXF2e74rS7UI4APo3DppBqH24P2eSZKyuNmyuF0RY0jzGU+FEgXaQEgjCTmhSNGZrqK2BtmWbXzGbTlivr+lsSxQHV02cRUtJFmdh9JMSa32v1fOsV0tOTi4QQiFFhDVBND2dToniK4qiJqifPIMPW6w07/74ezx5+ojZ9AgpUpR2KGk53J+SZjGxFmyEwUqLlZYOg0oCCXOxWXB2ecrZ5SmNqXBCoKMQ/LFcL/sOOGJWV2zLEkRIvsnznP29fT772c/yJ9/6Dt739BcdMZvNP1Vd+IUAzj/p8PImL65rWzp6oiZ+RztwUuywcvp/V1qBh6ePn7LdbpCxDicry5lOZsQ6oaoa0jjCmC54TyFw7uaJPln0fCP7uX04P5BDJUJ4Ls/OefOtN/mjr32dR++/z8PnHuKdpatrXJqRjjL+vV/+NXCe0nacXJxzdXWN6yyualG1xVctm6bk3JWs1ys26w1FWXBxcUlRFGw2QYpSVgVFdUESp0jlsK5GyGdtcGAIERhuAnKHBRjbAQmTccY4ErjGMjENq82a58YjqtJifYI2joMkJ81ylqqjbCqU1iS5xhJhrjdMplNWq3XYxhpDHAd+0mq12sWdp2nKxcUFe3t7ADt8b+BEXV9fP+PgOej6BjLsAAbfdljYeeL3rPEhjn0ofpPJhCzLqNuaeT5DKsizlLopOHn6EdcXp/iuo9guOTs73RWjT7oOhAgayOl0ghQOqSxeG2LZoEWD62p0KnG+j6zyLpBqCakuM53wcP+I2kiEg1He4d0Vo6xhW25BSLQWKB0j5IhiW7FdlijtiRNJLD3CWkzTMh/PWMQF223NJM25urqiKOsQliqCpGa4DKJIs7+3R9Ne4HwXwj/liDSecnH+GGsFUjp+6fNv8Gfv1aTzFBKobElLi1eaotnw+PQRT84eBR6XVNSmwjuLFILzy0vSJGc03qN1BhXHTCZjjLF85zvfBS93YRqXVxdIKfne977Pf/Kf/vxa8AtapIZ+5aZQSSHQsu+idqOcHBoGICSqhgDP0OVs1luMcHRdcDd87ZXXmU8jtpuCaG+MdCJYrliF6S1aRd8l3e4+wjU7pP72OWr4cIeKI5yDrmtp24bnn3tIomP+D3//f08UaSKlMNYikZiu42B2jz/+v/9/mFaOHy4veL9Y8Opv/grp4QFN20HrUM5hpGaUThiPJnSH3a5AGnMT33R9fcE/+n/9VzjbkSQCrQVCDAzO4TzenLPwBuzF294jvEdpgfMdpiuQHuqyZTJJmM9GKNHSKUOxXuGlYLGtcNGY/fkhm7ai3CxwQlDXAWDNsz2WwqBSsdvADuNX+BX8jmQ5FIJhCzckEd/WcUZRRJZlLBaLZ0a7JEk4ODhgs9n09ilmB8APQP0w+l1eXmKMoS62ZHmCkJ6y2mBMzexwD2FnFOslVbmiLLbPCJSHbm1wVhh8yTfrLXnu0VQob9jfS1AmZbW4pNp4oljROU2eJnjbsV5ekcQJk+mMVx/e4Xq1BR0xn7XUzRZsw14uSLOc0/MldSuZzvbIspT1suVgPmN2MAUsRVWB0HTO0NaGLB6DC5bITbtEECyOoijevQ+c86RpwuGDO6RxzvX1luloRl176rKkLjtef+0V/ubf+Bv8P/5/jg+evMvj849AG7ZFxXP3XmG5ueajpx/SmJrOOQwiOCL0uIzwkghPnGeISBNLxWiU8vTJCV33GEEUgkpHKVIo1ust3/72tz9VNfhzJnPefH57avr4BAU3IPmzwuJb309wSxxy0QYgUwTtS+/frZ5hijrjd3fiO0d3OTo47l0QA0ZjelKcMV2gdFobipRwCHR4lLx5ymFUelY4Tb9VFMgkwvZdA32KyPHhIR9++IjZdMrqesH9+/cCpuEs8+mU7WbNwydr7l40fPvPvsnj+oqHL72EmEwolKDVBFKn1GjT9g6R3c6JcsBfgg2u5a23Phswq0jSdr1SXzx7JgPHzIEL2YPQe2x7QWfa4NwwUmy7GuctXd1gt0/AGRQep1qk99w9ust+eo+Ty1OIItJkilcp+JLVoiA9ukOSjGlMsFIZfs/btr6D1cpA5hwsXcqy3FkDD1u9ruuYz+fUdb3bDg7A+nBOBjD9trB4iFpPkpi6bnYFz+PDGwvHdDZBEPSho1HOhx+83y9JHFHMra3ejag5UFp6P3McbbdFC4eykvEkpVg7nOlQIsaKHJxCWElETBrFNMWWbV1xvVqRT8b4vZTRyLOtSmSkiBLF3r6mqgXWhey78Vhz/94RCIf1ISRBiIiVaohVhCdszkxX0nSOOAkxV501SBWRxGNctQl+4zmYrmU2n3Dn8IjL8w1ttSFOdFB4eEuSx1RNxdPzE9abBd9t3uYLn12yWC3C72A7hFYIBE0XlkdxFOMRxGlKmgVTvtF0RJZmfdzYiOX1hkhH7M3nwcWhLoMZ5ac4/gKA849/7j/2+c8neApAowKJ04Lphu8buhvd689CJNMQXDg8TdO0BBAdvOnN8iNF3daoOMY7h2k9VgiEiIMnkA4dhr0Fc0kpAgOYAXjuf27//yHIMZAmvZAIJfnH/+JfcP/4AS88/yo/eOc97jx4Dq8NJBbpV/hVwYff/p/Ynm3BtkjXUm+3ZJ0n7iBtHbpsaE3NOrb803/6u7z99ts8fPiQv/23//bOB8k5g7MdUwVRnmGtQQmJV5rbMUgSj3UWL2UQr4qQj9YbCoPrKNZXZAnEbYVxDd414Ds65/Ayhijj+Rdep60Mf/bj91E6QjQCyLg6X2EbQxLDaGo5v7revcZDBPqQgTekxAxmdqPRaBciOuTGDVq5OI4Zj8dcXl6ilNpJb8bj8Y4/NWwEhfAkSYwxHQcHexTFhqLYYExw9lyvluyPD8mjCWiLlJ754RHeW0b7RywuF5ysPV6PkbpFRzGtLbF1II0KEYI8pdSk2rI36iiqFa0GKwQoyyjSVIXlzmQfUzZUzYrtpmU+mWKkZFUZVkVN0RpKk+P8nHY7xWWSTaXoqi3HWjGOJMfTnMp4is7yzvKUs1WExJLFmliFSKl6a4hkCdLj2pbMgxYHWA0uv+Dk/Jyke4F5+ZA9u0RcrlkcS+qiZX8yJkpGaN0hREVnGmprMJGEzuPKhmyWIcuSr/zqb3Fv7z4vZXf5W299hXe+/z3+1Tf/BbUoEFJibPA0Q2hyL5kozSv3HzAZj8n6BPEoihFFjdtajkYpD+YTTk5POconn6qq/MKMe7e7qbChC7N0U9e7dA8pxc6EzDm7u4PeYEU32Ev4kLtiEuj9LXjXd0qeogj2HsZ0iG5Y1YrdG2rYkAghQlbb7nvpuUceqSTgdoTDt9/5Pm+89gZKKb70pV/HCou1jrfe+gKq2aLynO9dXKKWhgKDHqd45+icZYvDSUMnS4ytsJsb25dhozj8ftZa8CFFdrNeE2dhA2qtRUUf35h+/GTffOJdcJaIvcDXHZNxxqZowvrahFDULItYnFxRbAMWtS221LXl4Ogun/nMG5z8/tfYO7iDkpq2DW6OUkqOj4/50Y9+xGw22yUYP336dBdvVRTFLix0AM0H7d5QiAb/qLqud0VsYKoPlIXRKMM5x/V1hemdQQcNn7VBSuVwID35OOf04gnpOLhgJlGClpLz0/Pg3+QcXdsvFbqOOIppmhrnQpBqZ2q8tbR1SzIfsa43mK5jMkmxJjDnL69X5KOUxx+dgzO9z3rodLN8zCQbs60aLq4uiEcKNVFEUU5VV1RNQ1s1GKmxOkZpyWiWU6yXLNYbsiTFdB7rI9I8Z1MYIj3DxzHSnzMm4djexWwveO71H/LaL33I4jrh5MmMrDygrVoKt6GeNSRxjL7VoVtjee3oHv6Fl5nvxYAhjxRNU7DYVjx3/3l+6ctf5N2zP2O9uSDLRkRRilQpdWOJo5y27Vhv1myLgqS3mwkhqA3ZKGW5usZ5j3Udi+XVp6oNvzBF6pnD36TYDt7Xg8k+sCP7DdyZ4evDVubZxFm5IwsOo6AQgsVisfPEDnsQtzNnG5wLBoB2+JlChrEu3NmjPk4osLlDBLdgvjfFC0Nnai7Pz5kf7aNizWq94uTH7/K551/AHh5xWl9xXhuaSGM8gbMjDB2WRtQ40TJSmq985St88Ytf3Ll77tJNrEWKIN0QIni8OxvoCOJW5+oH14MhxnvoZIUAH6K+6rrDbioyJI2toQvnI9ExZdXhnaFYLkK3GGvu37/Hb/zGbzOdHfL1P/wmzsLTx2eMPrNPmkzAmx1tI47jXZLxgE0NFi1CiB0Jc6AqDI97Jsml37gNNsODTfB8Pme1Wu4Y6wPQPhSz/f19rq+Dv9hic00+T9EmuLh2bY13lmq9RjnJ9uoSjAEHxhkiBUZ6jGlDAIjWQRbjwxhpugphDUWfnmKWW0aEEbVuG0gkB4dztJLEkUJHCZ85eoXDu89xudyw3pbc38/YNmtM1JFNIlxTIBqDFhGN9ZTOMxrnCBVCYhfLivnePt22QeuM1q7wUlL6NSpNGNUTslXG85M9smiGuW5Yf6Q5ayY82SR8zoabftPWdFVLGo0Cn0kGvFRKwYN8gpnu4XzJYrumWV2hZwky9pi4Qyj4lV97C5oCUEidcO/+i6T5jLpxXFwtidM0eGTZNviXaU2eZ7v4LaU1+GFx8/OPX8giFdgHjjiOOD4+7lv6cLFueu8hIQRpmoa1a6R7xwN2uNEgTDZdh+1zzbrO9L5UrpdrDAGQbreuHYD626kkgVSnsF2zoz2UZej0ojhCCN9vCj1//Xf+BtWm4OnTR8wmM7yzmNYRxxnLVUWczZn+9d8kNR79w3fxZYWcTaAzpMIhuhrRtQx+3MBO8jFgI9Bn6WGpqg5rPELdyCG4BY7jb52X/rx6Z0EEXCGJ05AkayzOOOrSYpFUdYWOYzabmtWixVrJeDYlEsFf6f0P3ufs/E/4g699gzSd4gnsfWdFsIDpHVK7ruPy8nLXAQ46xCGmKssyDg8Pd3SF4UYznU5p23bnHTUEL5RluStit1OCgR0oP9yAyrIkigKx92T1lHUxIsqCUsG0HbZrcE2DtaBMA8YQyRjng31zpAQeS6QVQ5x6lqV9yKfF1i31csN4PIbWko4T2q7l7v174U1tDEISAjKFwHi4vDrj7R+8i9Qxk+wuMhWstitWlWMcR4xUgvcK6/oATmMDfy5SyDjGR5p8muF9ivFnlFWDSDyybcnMHRIf0S5Pmasxp2cZj7ZHLGcplbtmfbbCtJbJ3hyNDklLzqOExJoOrQQ0DdMoZtMsiYVjcXFKkkwYZVPqaoFOFPuTDCMM2WhCNpqzXK94/PgMLxMcms985g3yLMW22900AuwahqFrVn81mFQ4bo9uH//855ndwc0fA540SxiNM7wPGNF4MsKYw/4NKXuA88ZC9uOUgaEbCqPhTREDduvmG/cGdgJXYwxN01DXFW0bAh88kiFpJQCwhFTZftwzxvDgwQOk9cRWIJzH4IiSlNVqRd06RJTx2f/0f8Mf/ckfo8ea+OQSxinCOTI8lB2RMXit2Hp2IPHtczd8HjLeBMY4olQihO7/tlujcxDC9Da4vUxmwAaFwFpBU1nqouFgtofHkKYxNYraWmorgoxIR9TG0WwL6trQtFDXwQ7W6iAEz7MRQlzRdYbDw8OdQR3cyFmGBJghdThNU87OzojjmDzPQyfSc5OGbWDXdbviBOwoBsYYRqMxxhjOzs4oioLJZMJ8Pt99z8ByT/OEstpypPbBgDWW6WhCbT1JJBkdHrJ59ASpQ3daNTWN65Cyj0JTOlBJOkfXWSajKVVbcv/OfbSUxCpGO0XdGpwXOGPZ25/12ZGebVlQ1S2T8ZzD40PW6y1ewmKzojYGHSnWmwadxSS913tdWZomhEAoqfEq4tHTc9Jkiu1qrIPVekOajYlsTHJkadQpy84jXU7ZemxsSbOCrF0xTe5QuRblI3CCSIfEY+FanDUI7xBZTOE79DhllAQp2tXZE9J0y3q7BelIpWA+HhOrYAWz3WxYLrbodEw2mvG5Nz+HwKNFuKkOXfHuJspPX5h90vE/25nz0zzu9pvq1iOewXp+2vMOxeDmecN/gyWHfOaxQxjDLf4lAz41/Nvt3+/muYYT9uxjhp8fWtQD6DeBnbmJaaqqcjcSBtA9vHl+96tf5eXnX+LD77/D7/z1v0HrDJGEdbFFxjFnVwt+8O0fc766YrNc46xFJzGtCduVWjm8CpYdwt2MOgODeyhYAMbYYCHbGJKMHqsLfLEb3Z7Hi5Dy7OkQgRvY/40CvGI63Q8OkvM5+/t71E1JfHXF3mHQBz59egIIqrJknCRUVYt3IVllPJ5QlobxaAyCnfdTXde7bmpwPIAglq7rmizLdtfBIDQewhaGu+3h4eHuxjPgcIP4d7D9jSJNUVS7gjgQOAdSaNM0ZHnGnFmw8728oq4q2qri4d27zPMU5T3WdLz+youk4wkISVFWXC+WrDZb4iRFSEkUJbz+yvMc76dcXJxhW89kPA2W1F1HVTbM9w5pmxbTliw2FUJ5WtvSdi1KRazKiiTLscst27qj7ByVgWq1ZZ6OaFTYCEoyZrMxJ1dLqsIgpMcazXq9pU1aXnrhBZbXNWm8RfuGVAnKdk7lp+ikBtGxtpIoypCNJq0b2sojiVmvS5arLdl4H6U1Chtw0aahihQrCeV6xXwShyj2JMVVDbmFSZaDkowme1gvkTLipZde5eBOw/nlmtOLK6SKmc2mIUOwv9kM9tVaD92y/wky9k87fiHHvXAMHZG79fnPPoR4lj4AP7k5/Gnf96zebejKeKaghu5JkCThRQAfMLOuCUBwWfKd777Nr/3yl/jG+R/w/o/f45XPvIoVjqOjQ+aTObJz7EcjFounFI8vmB/sBcU4ltp3NHHY0LmmI7OfnELctm3w5W46vBN9sKoPCnr17AZViKA3c9bjZTiXu3PjPFrH3L/3POkkxXjYNjXrdUNlFX5d0XUtk71D8J40G9Nta/b25gQ/7AJ8KCLbYkO6WrJaL5iM0x3QXxTF7vceuqSu6zg/P2dvb480TXfavBsRr929BoNP+iAiHh4fRRFN0zCbTXfY1xB5NdAVttswbtxN7zLNR+w99zwnJyd4A4qIq4sFfjJilifEUUyWp1wvr7i6vEIojYpT7hwdcHzvPi+8+BJRFLNaXnF68YRy2+CMoFzXxHsZVWlojcCqiE1boXXOpqnRiaZqHJ31JAim2QjpJIfH90FAUZZk8yP29jPu7R1yZzxnPppStg3JdMxkdsTde/cQSvMv/+DrRHqPUT7lr//1f5+29GwWW7p6g9KOoq1ATIjimM4/Rh1ck2UXiOaY69MKcW/Kar2mbi3x5YK7z7+EjiK6rsW2LdvFgkXVsnGC0oDZVowix0gpZCfpyopEwd69B7Qu4t7dB4zGM+J0hLxacnK+7L3gS5yzbBU7o8PwIambdjcpDa/zzzv+HShSn/y1n1V7frI7+3mF6ie7uUDL8jsJydABDrwpYwImslwuqJvgceSdx1pBpFO8l8HNUAg6a/nGn/wJr778KvcP7/GlX/11vvCZz7HcrjlbXPHR+Qn5dEIUJTijgpkmHiHMT+02B31ZXbd4F0YyehyrZ0rsOkp6u5ZhQ+U9OIJcx3SOxfUat1rixA1FwHuHcIamaZlOR1RVwSSf0JqEq+tF0EJGEc55jO2QOmJbLJlMMu7eucP19dWOeDmEKgzd0CA32Ww2rNdr6rpmf39/B3oP6cODTm+4qJVSuwt72AoOd+oB0xrGSe/97ucaY8giyTjJmGQTxumErm2ZpCnrxQU+zxBScfr0KV56Ii0RUjCe5BzfvU82mtDUFU3b8vTklLOTU3AGLTyRFBRFS5QkyCRjVbacLtYooXFYVCKJswSrFFXZsi0XaK8Y5xPqoqNpIqZ6TpZOkEwwXcxyWaOSCCESXnvpc9R1i1QxkZrwuV9+g8X1ktlkH9N2SO+Joj3WjSWKTxnFG7Q5xhvLg4cVr33OsL6SfPDBgtrcI5vMsVXNR2dnrL/+dQ7390giTVVs+R/+u/+eBsV4mrBeN3SpI5pmONNiG0+iNWtnGckII1KKVmArwyyRlHXgdcWRJooTpFQkcbQzKxwWH88sosS/00XqdjfgeZZB3X/2CVPiTbcxJM18uhF10Al+/HcIhMSaoiiC3W1RUVVlD9iG0U/IABQLIUizlFdeeo3NpkJKzXPPPRe2fsr3PK2GKIlotGAbQ50qlrbmw5Mn6BNBKiOOZgccTfeoO08lHbfpEIM9SZIkvZeSZDqZAsGpMqjehy3ojXYPEXhTA94W8L0+p1Aq2s7Qlg0eSVGWWGNCXqAMiciXT89pu5qFXxDJETpKcNITJ1nvfmpRUUTb1rz+mVcot9UzWXqfxNxOkmQ3sg131aGQDcGgbds+Q9qcTIL3+Hq93sVbDccQfTVsbwdX0KIoQqJyXbFZbuiqjrYzOGNpthXVdkOqJWo6Yj6fsi02RKMMLxRxpHn80Uc8ePg8nQ2WzT967z3wjvl4jGsbFqsNWivS0QjZOlKh8TJCyARrW6q6ZZQIyqoF64iFZ1MWwSzOSdZly7J8zP7ePst0TbtYsTceY7Dk+1M2yy2mc0z39hklU9bLEmsEP/rBj0KIrhdY3VCImqk9IGoVdI/JvKN4+7N8/6M7lJRU7YaL5ZIkzYnSlNloxGQ8ZjqbUW/XOGP54KOPaEzEwdGUqlkyem6fqjGYtiNLRqg0ZnIwxUQxWo2IszFxmtH10eyBhJuGRYOOiOIMpfXu3dxZH67RfuSJ0+RTvT//QjzOf86juD1aDV3Ks98qe3q/4xvf/D5plnP33jGTccZ0MibqwxkllqFTGFjlg+LfeR/wF+uQUmEcQajpw4+XCKTwCB/mcdP79ZRlw9X1NZtiG9bjPb6RJAlxMkKlObPRGK1jhE8otzVPn35EFBmQnv/gd34L7wz/wd/5bbJ5gjMOaRMOR3dZXWzonmuxrcMbTblpkZ3ilYevUldl0EElEYVr8NKDk2gZ44Sj7Vqk1HgMnTVUbUNXV1RV3WNVTUi7lQ4hfb8kCHFLUnQIFJGMET4O7GJhQXikhsPjuzjThFzAUU7XtSyXK7IkCziC0CRxjjGGoqyYH+9zdXVNVxUUVUmSZjhgMp4yyqeslxuapiHP8x3Haej8RqPRbss3sMoH3tOANQ0dkxCSOE5QKtyFj4+Peh5VRF2X1HVBHEts15GnGeMsx1hLXVZIBG0dwmCzyZTrbcnVcoUUEm8Nzhik8KRRSl0amgSSNCHSHcZ7vJIs10uEUDx6/13GaY7pDPtZxKIsabqKrm1IRjnOWaqmIZOSbrPGNw2VCltlrQSibIjqFuE9e9PgL+aMxZotaQLJKAGzobq4QjhJ3UISZ5RXS64uznA42mZNPp6xagqEivj6H3yAUhqnJEp7EmPJ8ggrNSaacHx4n4vTDruW6HTK3uFneP2l+8G7XEqkkkS+Q7oOazuIIkb7+8zimNPTp7RtjY4aHtzbJ08z5rM5o3xEnqVMshlxnIKzNFXB+XqLMYbJeNxrLDUqilE6viUvu6kPOwsY/ee83fs0BejTbO5++tef/Vog4WnazrLcXHJyfkFTdygJh3sz3nj9Vfbmo+CzLYL/edSzg5XSiB6YE3icafF9bLvQCueDd09XVSyuLri4uGa1rrDWhjtBGlb+4+keVVVRNzWLdUGeCZJMIaTCdwZnBUmaYw043yFky/d/8A4HhzNeeuE+1hvwGolgPt3j4uKcy6tzvvb7f8jF2TXbzZbVeklnWrIsCS+aCGOKQIDrHQwEtF3bb7U6oiRCKkkSKdIswyNIRnlfnO3uRQ0NlcB5g7AeITWuB+OFd0gVuCqdMaSxRsgA0tfbLcbWlLXtHQAG0zeJdYb1ZkVnOqI47cMOEpDBx8s5z2azAdh1Q9Za7ty5g/eexWLBfD6nKIrdWOe9pyzLXdc00BOscZjOkudZj18lwQU10kwmY1arJU1TIUWIjt9sNkGK09u0mC4JSdPO4REordmsVszGE2pfohA471A6pANvNwVeeFpnMMYTJSER2XaGtqlQCBSe8SglTRLWpsXYsDyJdRScTE1HWxZUokICMk3CtSkEXdOwvLgkUsF7H9swGo2RXU3TGPACj6JrQ56eMRbrOuIkwtmW06ePaTuDF2Gxkuaj4LDQOXwn6eIarxVlVcP6ilpUZJMcHUXsSYlpaw72ZhhrcMBmu8FORzhn8EKwrUqeP5zz3INf5vrqGiUlo3zKJB+RZ2PuHt/lww8/QFiBVltW6w1VVbN3cMh0OmU6CSnNQgaDR9V3yTfb+hsO3Mc9u37W8Ys57nmPlB6pPG+//V0ePT0jH025d/c+d+8cUTWWb3zrT6mqgul0wuc//1nu37+H8wLpBc6GN7dH4UXgqnhncQ4++ugpJ6fnLBdLmrpimudMZ3P294/6YhdImc5BVbW0xuG85Ifv/pivfe1raO25e/eIUTritVc/z97smNneHOc1zim+92fv8EtfeJPolRRsB1JhO0MUSV565SHL1SUnF4/J8ikjlbMsrrg8P0MAkVZY24WRBUma5qw3G7Is5fz8PHj3RKGQxUnC/t4cVS156eVXmO4f9qfuk2VHwwg43AqCcaDbyUtMZ+hswXwyx5Eitd3FlmuVhIj7KGWzbji+d4/33/+Q1WpDmmY47wOPzFo2m82u2Ay8J4CiKHZbykFqMiTI3M6+u80+D7KncCEPmsVBTxey9oKOjt4IsWmanT3xkPsX8K+G/f19lJI0dc2du3fRSjLJR+AsbdNwcXZK01Xk4xTTQVMWmJ6+EkmFR2Csw0mQAortFimCkBprQUjaQRFgDMYCzoLpMFIxyrPQvUPgJyFRkUapiLY1oYgqjXXgCNehFzCbzYliTWctmRdMo5SmM3gk14ug60QIrFGY1iNxaGlZLZ8Sac945Im04Pp6wVK8yGazDgoGE25OSRoCL5q2pWlqzh49phyPQkcEXJ+fs41jrAna09FoFJj8va4yjsudMWSSpsSxQ0cRit4nq78OhutwWI78rM3+x49fzCIlPM4Hmv5idU2cxMz3Zhhv+fCjxwQ0xXP/4UOSyZRvfucd/uQ77/DmZ1/j+Qf3SJMI7/pBMBCrwXt+95/+M1abkqOju8zn+0Qq6rElqJrgQeU92N4PXEcR1nmiOOULv/xFXnzpRb7xja+zWl1yer7h6mrN5z/3RfZmM8YTTZR4nNdMJwdYKzCNIY8i4iwhSWMezA/5V1//5/z40Y9I0gnHh4e8/JmXGE9T1ssldVEgRSCHWgsPX3hInuWcX5yzWFwSxcHkLthjBO1iksQ8eHAfr24Ayp84nQKEkEhxA0BLJcHekFiN7YhiTZLGCAGdaW9adSmomwrnPE3TcXp6ihSDsDdwjuIke6YLGqgIWuvddnSz2eB9oHNMJpMdvlaW5Y6cG0XRjqcWx/EOKQxbwpC1p7Xqwf1w0SuhdyP54Iow+J8PBTE4dobFwtXiiroINiPeWdI4QYggtXJVjdKKNM1x9DBA0yIShSQw/uM8wRqDcZY8y5iOx3RNSFuO45jJKCcRGmtMUEg6h+ss3nriOMKa4CGeTwNloqwarPPBBUMq4rgJKgLn6VyL85ZIxwRt6RZrPePJlLoq6JoKZAjxHOcj1utLhK+JY8f9uwe89fnX8L7lD//1ScDmnGf/8DAIuU1HrCNkf8OajEY83D8IndMop24aojgiH41ouo5tseXDDz6grWtM14GQ5KMRo3EoXnESZEjOh+Ql/QkLqdsF6pOu1U86/lyK1KdZ83+a57ghLHq8N6AEDstitUbGCXfv3idSGd6GZLJ3fvQedd1wdDDnc599ne+/82N+/KMP+OIX3uT48CD4TymQWuGsYbtdc3R4F9nbmRrtEaj+5xp8F+xehAomeF3doKMI01f/yXjGy6+8zO/93o85PTllb3aHr339D7h75w5/83e+gpQO23mSOOfy4pqu3nL/+B4qSVCRpO0qEAbja7yVPDkvOb2QHMzn3HtwzPXFFaZpqKsKYw2rzQqhBGW97aU3Xbg48Mz0mEhJIhmA4ub29gzoffpuILuPLQactWgZ7t4PHz6kqpY4Ou7cuYPWmhf6rLWB6X59fU2WZjRlh+/z+b73/bfxztM2LVFsdt3QAIgPr+sA+Btjdjq+wUNqCE0YOFLD32CMIU0yyjIk5gxpM0VRkOf5MyPE4MJprWU0Gu1IoAMgL6VktjfBdi0XFwbrPUVTESsdPL+JmIzH4GPiRIX4pr5QSil3NjECUNZgTEsSxdw9ukNVlJgujMVpmhGpQIMIDG4dTBj7TjFgioqqKgOCWjWBya40cawROmZbFDRFEQBnH24WwblX9gTWYD2kVEgeirQMnXUs2ZuP2azOcNaRRjnrq4Lv/+mPiLSgqxQX3TlaRywW1+g46sm1MdaGuDVnLU1ZEFnLennNeDJBK8FmvWI6n+G9ZTwZMTo+QnqBF4I4SXj8OOgxg0NDsBGR8qaTHnhvt+Vq/zbHX3knNVxIPykwDqm79x7cYzQ/QOiEsq1xzhPriKLYst4Gzs3Vu5f86Xe/y1ufe4Ov/MaX+Fdf/2Nee+UVXnnpRbKxDM6eWvPGG5/lnXfeZTY/IMtTxpMpq3WBs7YHk0Pyr+wtilUUoeMorOEnE3CWLM9ZrBYs/v/U/dmzZcl13gn+3H1PZ75DzJkZkZnICSCmBEmQBCWwCI6iVFKZdb2oH1Sql36r17buv6PN+qmsH/qhy0rWXZqpUqlEUoRIgJhJAEQi58yIjOHO98x7cPd+WO777HMigExQJIHaZjfiDufss7dv9+Vrfetb37o85fJigVE96rpkuXqV5brCe0VjLf/5P3+VX/n85+S+VPBWmpq6qrDe4n1DkmYkJuHR8REaeOrGLXpZzgd372Eay737d7l7713quqY3KERDGkeeZfSKnNGwj6lD9tGr4Fr7YKCUGFy6QR6b2r1wOGt57913WZcilXJ5vsaEBRlrGKMi5vXr13BNxfl0SlU1Ih7YK5gvl1SVhGrT2bR18WOWbr1et0B5ZIuXZdkqJESOVBe/yLKMy+mlGMYQBhoTgVcxYmLkpPYvdqKJ4Pvh4WGrqx6xr/V6xWw+ZzQaoo3GKg9a4xSs65Kil9IfjVmv1mFuiheWZQVZnuO8o1kvyUzwGIDBeEyR5XjnmEw8RZ7TNJaTy0vyLG/r4larNRrFoD8gKxb0ez3qZg14dJpTlhVee0aTffFuQ3nQ2fk5jbUM8yzce02vV5BmCVcO9qjqmrIq8QqW83MmoxFNVYCT5qKLaUqRF/SylFVTSmOTYHy1kQa6BH00rRRHDx8xz3OU1qxWa5RR5L0e4/EY5TzPP/scN2/ckO7IQQX3/bsftDpcSmmUluweO2FdXOddw/VRjv8iI/VhZS4f1cPqVuxvDo1HWNzjvR4WicvLqkIlMNofMdwbYxvRScJ51nXNH//pV/nEx1/kdHrJ3T/9Gp///KfY35NU9UsvvsT9Dx4xvbzEOk1lHY1VKA1ZpttiWJ0YlDF4PL1en7v37/KnX/0TelnBbHaC9xZjFHVVgU64d/8es/mc69f2+af//T/FGMe1qwMmgwIflCrzpAAUk8keV64ccno5o65Liiyn6PewVc39hw9JjOHa9euyo3qZUCMzoKkqcI48G3DlcJ9hf0C/yLm2d52rV6/x3v2HUq8YPakPObQ2KITrdTm9lJpGFFXlGAxFIL9bWrJc1ZRlQ1MFXMi6tlZOa81oNKYoChbLJevVpj15VDOIRitO5qg3Fb2upOO9AC24OhyNqKp1eDamxZqkFlMwj1W9bjtGx9AxVgPE8pu4mNEKpwCtqRsJ8SvXsJqvyeqEylp8Y/HW4W1oMpsY1nVD1TRYWzPo9dDGcDFdUq5L+nkhXqCVtvJJYijrEo+X7GSWUhiDQpPkOUUAlpWXe50MJ1jvWCyXDEcj2SSUwnrH5GCfpmnY39vDGEO1Fq9sPptz9cqVUBZUcf/hPbQyHOxfZbksybMBlxdz7t17SJHs0c8Uh/2SdblmuVqRZqmE1rbBNiGLnWqKyYBUS61q42oSlYKSjLExiizRzGcz8qygDhjk3t6eFI07j8OiAeUNOLVlI7qqpz9J9PVT96TisV1zp9EmpbEe62SS6DTFVo7Z+SXWiiD8sDdkf39CXVZkWcHlhZDoXn/7Ljdv3OCZZ27x5T/9Op//hc9wuDehKHr8yq/8El/+z3/Kaj3HG0MxEIwjS0X3xqQJSuuwm8mDevHlF5gvF7z5g7dwbkmapfQGRRveOW/J8pz7jx7y7/63f84/+L3f4Z13/pLPf+7TFElBkmWBm5Qwmy1wjSVPEpz1bfGswdAAdW15++499vYmKKM4PTpBA+P+gF//r77I9PyCar3m1o3rHB4ecjAcUDUC/iZJQuI+/OFLWGVJEvG2kiSloRLJmiTD+YqqkrByb38kBoaavEgpsiEmyzg9PccYaTkubr10h5nN55RJwuHhYdtKHWhJnLGsKG4IUQnBe98qb3aB1sQYivE4yK+cUVUV168/zb1792gaCRXH43EIN4qWEAoiTzwajYQg6ippQBE8q9pabBgHhcFkKcPJmMQYsp5BO1jOFwyHAy5nU2pr8UZT1zBdrMmyHGcdSqWsaid8MOeYLyU8W1VLyqrCrNcCqtcNdd2Q5wWDwZB6uaSfCNSwWK1Bi+deVhXVco7ShrzIyYqcQvdk40QxHA3x1uGaBu8a6nLFeDTkyt4hoKTd2HiPJC2Yr1e4xKF6ihdeeIGr44T5fMZitWJ/fx/rHcfHx8wWc9I05WCyx52nbnL18JDlcsmDIKsTNxhvHfP5HKMNWfASTSgU7vf76CidFENxpR8zSl35549qqH4mjNRG9TIWHUpzUEDA3jRlWVcoo7h64wp4i7MNpmnAV+S5oW4qwW00aJXy6OyC6arkU688xx9/+au8+ulP8NLHnmVvMuGLf/fv8B/+8D8xm0+lI0fWp/EN3goIa4zBJIbFasHDR494+ulbXL9xlZSM2fyI/SsF3/nWN7k4m3OxXjIa7GOt5erVa4xGA77+ja/y+V/8FL1+j2ZlUSgePjzi5lNXuLycc3l+CcaQmJQ8y7HOs16VJFlO0zhMojifTsm05/ad2zz44AO0UdKue7lkGNUPB5Ka9yhGo/s0VgTxPuyhRm0u5yxpknLz5k2KvgkL2fLgwQPOzy/Y39/DKUOe9+kNEgajAhpPFUKGs/MTTCLdkq11rcxvZIJHFngsGAbxjLMsazGq6DFFGZoYinjvKfKCdVlilzV5LjWA0qV4SJ7noQ5M8LguYTSeL2YnF4uF6HJ7qe9TWvh00jrNk6Qpg2GP/f0DQFGv1ti6FHxFWgnJuUFA6rzHaDhkvVqzv7ePd5aqrNBKwrn1esmNvWtMxmM8mvOzC+aLBUVvQJpmOK84PjpiXVYiPx3qVE2asFzMWdeiTFo1Fd5DmkgTCpxIFTZ1hWsacGNWywWL2QzXKBrXMF+sccqT9Qpm5Rk2WdAkOSt/zvm5yDRbZ3n4aI1HvNkmdH65cuUKSS9j7Wqs9owP9/DWkSiRJjJakWqN0fJsnZeejwCTyYS86AUFVEAZGrcpIu5m9WBjrD7K8RMbqQ+3fk/+4N33bSxr/DnIA6uA9DqPRkpLyuWStNcTVU0cxijRPMdTritq6yirCovo/xjjaSqRavnmX7zG53/hs/zlG++wWNS8+qkX2d/b47d/49f5g//0Bxw/eJ364BqjvSsiv9ozokvugMRw7/77fOWrf0y1XlNXmhs3DqmrBZ///Bf46p9+jcWswtmKIs949PCIlz/+Ev/xP/4HvvCFz9M0BBDR8/57bzIYataLNU1VYzK4nM25vLhgOByRpBmuqUm0RmmNbRSVS3A1vPjKJ3nqxjX2Dg7p5Tm+rKCpuXh0zOr8knVVM51d4nwDKnYr9ngHeGH4eiXJAO0cOBuyfRL2aa1JTMpsPmWxXLBarLh5/QbjkHL2eE5PTlhmS4w3jId7JM/knJ1dSjY0GIVHR49IgyjdfD5vuVARh4gNGSI+Jby0vOVSxYmstQ54UwNeQsDlckVZVvR6Pc7OzsnzQjr2Aq62LBanbanSaDQKnyuSNVobcqWoPJiiwCca31RgPQZFT6cMfEqzqhiMR2QmYVo1ZL0elbVkRY9ESXfqRCUcHhwwHk+YXl5KprGy0sxWJ5R1FbJmAxRatN+LQnSVTEJZCt9tUOTko4HIDHmPdY48z9jT+8wXC0BoNGUpJUpaadBQrUspdLdwPluQ5ymjQY5JDdrL3BFirydNUllfDlarNUVSUFtPVTfoxLBcrVBaUQyG0llptWZ1v5T539QYHTYzW3Px9jmDfi80oUgwOqXX73P7mdtkqUZ5B7ZGp4JL+aC75kJCw1sra8HINQqh9G9ABeFHGagNDrXbYioaoCfJBsei2c3PUaGg1UHyUK3XLBqHn6/xWnabLJGWQkmq6feG9Pop2qxYrs6Egm/l8+oG1o3jP33lW/ydz3+O9965h7eez33mFSbDIV/6u1/gP/7R/8r84oiqMYz29mnWNYnXZEWGUpqnn3mak+P74Cru3r/LyekDsI5vf+PPUS7sJE7Yy8v5nGvXb3Dr1i2+990f8Ntf+nWaZklZruj3M5aLOcormsoyGI8oywpnHbPpJUUh4GRja/AN/SJnVSmqpubu/Ues1msG/T4v3blDhkdV0vpIG43TmnldkiSK2stziEbKE2QPQvcQ5Z2w7K3HpAbbOM7PLzm/sEynFxitSVSGURnKGcplzenpKatZSaqWvP/u+1y5co2sKFguVsLs9x7rRYNpsVySaMXl5SVlWbZUgm4HmF6vx6NHj1itVtLJZb1ucQ2tdacZqDTiXF2uAvdphbWS3dJaU5Y1iTEMB0N6PUeaZkG2R7TDLi4uMSbh4OCQajZFA2kvp8KhE402Bm0dCZqMhMXlnPl80dIWlFJh1mp6gc9VNiWzy0umFxcAbaGzMYbSi8eYpSlYRarEq0hUQlZk1E0NiaFX5KT7E3R4b1VVKK1ZrqSxqW0Eu+v3+wz6m0YVg8EAPxay73K5bL3W8WiItw3WefCQNX3q2tJUCuN7UOcY1ycv+ug0Zy9NQWvW5ZrpbCbE3LzHurakVjHYC80dGmn+ifKoRFP5mnm5oFrVDHsjev2CdbkCV9PUazQOb4XzpZQoMDhiOZQ4FmFShvrRn0K499dBRdicKzTqdB5XO1zicE5hm4pKlaJ2rhwX6kJKN4z0H4uSEKIhpTB5hveWP/mTr/JLr77KvQ/uUlcrfv5zn2Jv/ypf+o2/z3/4j3/I6ckjjIY0sHhBwq6Dw2v81m//HhcX5wy/+S2+9c1vkSjNfLEkUZqqrBj2B8ROJcZbvviFX+by7IymEpzIOodOMi5mCxZVQ9Yf4UnwwctBK1ZlyfLoiH6/R5IYBoOcxMgzzXo5i+WSr3/rW8wuLvjUKx9nfziERnTOTZKA0ljXkcBBo5QT/o8XZU7xK4L77R2NFcrFaDSSEpEQHsWs3GopeBle0Sv64BXXb9ykqhumsylplqHXIrK3Wi5JMgHS+4Nrgl2EFHRRFMEbWjKZiGRKxJGi/EoM/YpCQOhI6lytVhwcHDAYDFq54SiEl+c5SQDlh0PxBiIYH4H7CKJfrGZUNAx7OaqqKCNPRyvINMm4x7ViD6U10+mUqEVWlqUQWiOYbW1b3LxcLgHa8HU+nzMcDqXD8XTGbCZ4XF3XQUIYDg8PQ5LAo4ymCmFuv99vOWZR/SHqoEU6Rew9CLSlRkki7dqkMUSNc6DqhuEoZ11WmLOLNrRfLhe4oNyR9woZqxAWa60Z9vukXgWhwJz5YobzDWW5DPiSYTAYkpma1WJF04gnvC4r5osF/T54X+GCF7daN0KOBkyayH0Ejp5SIYHxEY6/gW4xH6005sOPSFxEDFXjpCmCik1CHWgbWq/bsPtE6WC5DK8cTbUiTXNMkvCnf/Y1/u4vf54P7t5F/8UP+exnPs5wuM/v/e7f41//m9/n7OgBvdEee1ev4ozGWtFoXjeO0d5V/t7v/n1e/ezP881vfJ3vfOtbzC6mVE1NkiY477hz547s0Cj0UzexTYNzmrOLc5K8YFmVFKMJOu1xdHLRepHGGLLcMNmbAI6T0xO8UuRJnyRBauyUJklT3r57jwePTvilV3+eZ566BRosgEmkXMc7VKyFFEseDE1o9RXC6iRJhDSrwGsxlFlQEIgAd+QeSdgk31vnUNpwfHLCYvUO6/WarCgo1xWFUgz6feqqYjgcSo+1E+kVGJVOI92gKESDSWvNeDxujePp6SlXr14ltlNvmoaDg4OWXhANR0w4NN7j00xY00FBIbbHqqqKRQidrBEvfJgXVBacSmV8EkNvOCAd9cnTjFEIfc7PzxkOhy0NIzY0jVnI6XTaYmeRIBuNWBz/KjScEPwsaWVqYnF1Ge6/KApGoxH7+/stEVV4V2Lcp9NpW984Go1ahndMApxfnLMXetx5T6gzLSiKXniGjizPmU3PyEIz3MQkbdfodSVUkKLXY5gWnJ2csLc/IctyUMLhWi6X1FWD95okyRgOpFnGYrFkPJ6EagKZH856bONxrpKwTmu8IoDptF/+r5uC8KO8pB/3+10D9WQRvMcPhSwa5QCvQ5iipSzZQwBb8F5a7EjmKJO43UWVzaBJqaFpVnhS0jzlj//kz/jFz32Od9+/R1nVfOFXX6Uoevzub/0mv/+//nsuL85AwWC8x3AyoWkcqIym0dS+4fbtZ3n66dv8zu/8Pd556y3e+OFrfPD+XZIklbLo4M4qpUiNwXsYjycM9B6khm989y9Y1Y5bTz9HmiUsFjPKakVeJNx65imU8szLFUfHx0x6I/KAxSmdsq4b8FA2Jf/hy3/Cq5/5DM89fZUkS1msS2rrpG5RqZbIqQjcr0DuVcFzc3jBHBKDCvK48iJZYImRxZikOcK0Ujgc67qirhrRsS4K3PSS+XxOYlLSJGE2nVGtV1u96yLuBLQhoPe+1YeKCw8kC3hxccH5+TkHBwftOWLYGGkNcS5Z61pPJBJJI/custKLIpfylKYhqS2qbhh5weisBu0s8+kla5NQrctWkyoa1ehVDQaDNmv5wQcftM1H42cOBgNpv1WuaYLY4mK13lKHZbFkXTfBYJWt0b64uGixuigEOJlMtkLi6HEOBgOGw2FbCrRer1mnCauyxFrPeJJSlVUr0VtXFWmSUgfPdDweY53FeU+apTTOtomM0q0ZDAZBEsezWq4pehkHB4eiUls2JEbkhMqmYV1VKKOxXsqBpBmtxnqHUhtCpwoqHFhRQDDGtO3qPuz4a2WcC560qRVre+WpjYwvbKRkn8SZ6DLPlQbrBJuwVtpbt69zHpUonI+lFxtPyoeaLTmfeFkqUVg0Jk/56re+yS+8+hkeHB/zx1/+Ol/45c+xtzfh7/3u7/Av/vW/YXZxBiiyLCftDViWNT5JSI1nMV9jEk2a9/j4pz7FJz/5SerVisuTM4ncEDuqUTR1g9KG07NTHpyecOvObQajMdeu3WQ82SPLUvYPDqUKXdlWE/vwyjVc7VjNFyzKNf3RmGJgSDPBiaz1rKqKP/nGN7n38Aq3bz/D/eNj0iynXFeomBnVwk7VxJZfvm0n75V0wKmtBa1ZVSVZoASoYOEcqu1EHNtoj3o5s/mSoVakeUZtLXmWU1cNWhsODg6oylUruxLnQgxjYtYthirRy4gM9WjARqPRVueYODdiZ5N4SM9DmQOz2azlYcVyHFGIaOgrg7IKvaxIG+hlPSzQJLBclNRlRZOmLKbzllgaBfviYl8sFq2McaQ5eO8ZDAYArWfTK3rkedpe72q1Yj6fM5lM2jGITUauXJHi3Mhqj6VDMRyOBj56pc65NuSLY5plmeB4TgyD857VctHpCK0DbpaEekEpK2r5UkFQ0DtZJ3meBT0vWUe2cSQm486dGxgtBeer5SrQEAxJIuU2cV2L0TaoAOSLEdis8+g1p+ZvSKrlx3lBdd0EUbVtNcm2XmzHcu7qdm//UYzO+++/S2U9adEnSzPyNCVLQ7lBVaNN0mZxFNKAQWsTCmMN3lmRXnUN3iuMycj6BV/9xjf59Cdf5uj4mK9+7Zt84ZdeZTye8I/+63/IP/+X/5LZ+RlaGYZ70FioVYVTDp0aTJpAokgTjcGTWJEQtk2DQRacrRucBxV2xTfee4fBoIdWXkoMlKZsJBunQuYGL80nD67e5ODgGk0lHtXR6Rnr+Zx+f0i/GIjB0aKZ9cbd9zm+uBApEcfGk+qMp7PCpldqUyXjgdpZnIK79+9hjCYvilZJwvkQVi9lQTnvQ0dmTVPb1likaUqv6OHskvF4RJbmnJ3VbRfhmOHr9/ttP73YABRocakYSsWuPsPhsCV/xtKZ69evs16vW4A9Gov9/f2WwR7DwmEgpKZpitEaM18zznJ8XTFfLKUg2nusgWIyxPQKahSEuRrDvG5E0DW40dB6L63kY2YyTVPWZUlZhUUexjPNcurG0swWuLCh1lUdyn50+1kxrLx7927rLcUmqpFrtlgsWv2sLMtIswyTZaxmM4oiJc8y5vNF22QkGkrdlNR1JV6rlqRAz/cYDIftM768uGBvMmk93bhmvbdUpfQs1FpAb+cALRvdoD9ow03nwdaNNC8N46fbORn6ZP60lDlFtXJDxANay7p7/PiQz6O0w/qKv/zBdzk9v0QnIuqWZxlFlpKlKb29EUXRpyh6DIcjkb0IrqV1LngQVrp74Gh8Iw0+UQwmfV5743V+7e/8Cm/+8DX+/HsFn/7UJ5hMxvzDv//3+ef/4l9xfP8+zkExmIgLi8N6T+M9eEVVOwZ5hq0rmrpmkOY4r2gsVHVDr8ipmprhYICzDXvjIUePPmC+XNIb7gUZFhPS16JuUDmH8gqjNTqD68/cYXT1Oqt1SV3VwuK1nryXg/OkJmFRVqzXl2R5zmo6wykjhL+wYxmdbPAoJcZNwjtP1TR8/4c/IElTlBZLJoXIglHhveySiSgt9tIEvMZbx/HpCWVZMhwMw47bMFtVrRxHURT0ej2AjfxK4FhFj6kb/sXuxHHxxXbszrlWF13UUDehUZZmUo4znbaGImI+FxcXkjEFiqbBAxfrBaWrUNqgkwSvwODIkqAr3/Hyu95f3FC7EUF3Xkcj0i3z6pZ7dQtr29ZqiFJqvM9YZB1D5Sh5E9/vvW/Jq5HJ3zQNi7omT01L63j46CHeK9JM1FrlPqRPYWOlvMar4PGbjQMRGf9HR0ftuo3GOk0zZtO5SBzVJUmiGQwcJkno9QbUTSNughIbkGYGw2Y8I+lTafleGO0/BSMlnYQf50PthnYfRo333tE0JSYxWF9hXU21rvEOFt5jlCLRGvsoEXkWrcnzgiRJwUtzgL39PcajPXrDhKyXkvb6JJnwXoqiwKMYTAZMDvZ45tln+f4P38Dj+ewnP8Hh/h6//Vu/wb/4l/+Wi5MTRhZ6/SHOGHzj8Uo4H0p7lmVJgTST/O53/wKvCxJjUHheeenFUMnvGPZzqnLJZNhj7aVFu9ad1lMEw+1DS3nlQEnphs4KRkUfo0QszZc1ykkl/YqGTGncuuK9N94K7ncQwAds0ki777bQOD4sAS6tl6p1pxUWj61lMRtjWAcdKe8hSQxmrYT+4DVpkqATQ14U1KFJRMSHgLYxZ9Qfj1hLlGWJ4V5Zlq3BAcGsohcVmytEiZbVatUauwjum0Rvle/MZjO01uzv77fKnpPJBNWsyXo5ZbWibDzLpsK6kizJsLYk8T3yvB9kmGmN1I8qiI0hYXxtN9mQpimuVT8FtwN9WNsILGKlwDgSWGHTOzIavRiJxO+j4YyKEUpJ1tYooYFY6/DoIP2S8ejRMUmSMBqNGGUCYBOvCbmutt19ljHMMvJUDFlrbBtpcCsbQIHzvdCaXVHVDSYR7askEaMINalJyJIU4j00m/ZwaPGiMX+LmFQ8dh/oLnj+pDq/JxkqrTWJMlTW4qxwMJwPHYmtZK8aBbWVtCgmpXJQIzfflBVnx484ODjg8NoeV69f4erhFfYOr6JNwtHREfePjki1of/bX+LwYMJyeYO//MEbTIYjPvbcHZ5+6ha/9/d+m3/9b/89Ux8ee28Pnzhs40TqxHu0UzhjcE3DYjHl+69/n7/zd77I3ngISvg6RVbw2Vc/R5qljCZj5l6zdqKTvlUZ7gnGRUpyrLekWUHiPeuypKrX4kUWOa4Wo52h0c4LQy3yeoLaaTyca9gEegqUpmkcSZaQpTmf+Pgn0ammsaJvbq3FI92R25+9w1tL4mE2m5MoQ2pSGldTrtcc7h8yGPQ5XZ+34VvEWaLyQfSwIiYyGo3o9Xptj7zYpTjOlRgaXlxccHh42KbgI6Yj2SLxmhvbUPQKprMZ88WCi8tLhoOBGGpnIU+5eftp9hLNwtVYrVBG4+sGZR2ZMiTekOikNRQx7d/1omJSQmnVJhdQhPtKgoFJSGImy3uSsAYiuTF287GVeMy1rreUAuJXyyMM3lfXG+t6d0YrvG1EHqWXBiqKoqlDD0rn6fcHjEcFLshee5A55hqOjo9kWqSG/cOrQqQOLHvbNEJnCXPJ6IRGBYw3bE5pKiU7CtHaT0yCs9HjlGu0jQ33Da6RTSr925APfnLItqnR2X3dk17/pF55AATaQWoU1q5ld1dGBs86JIvgMSrDV6ASUcA0RjFMEr74a7/Kb/7Gr3H72TtcuXJNZGuthC7OOd555z2+853vUF1MuXPrFtWqwnj4yp99g6IouHb9Cs9/7Dl+57d+jX/7+/8W7SrspEcxNjhKfANJklPXUGtHquCll5/j3aML/uW//Vf8n/7hP+TKwR5aaY6OTli5ivrcsfJglWEw6NM0YoTrugbnRFs8z/BWmmx6rahrAaDrtWAuKi9IBgMwKetqRbNaUi1XDPKCVBkqG5MXwjVTJCjV4JF7l6GWkDjVPQb5hF/83K9SGIv2a2azOdPptBWviwC41hqtDEqnHB8f8+DBA1TjKdK8XcBS/Nu0NIGYRo8p89jM9bnnnuP73/9+i5UALev86tWrAG1b9si3iqByvJbomQFY73BA1QiTOssyjk9PcHgmkwmNteTXbzJLihBqSvgjhk48ApJEjFYw5NokOK1pgtFRWqOMEWxFJipWKVSQwBV1T4cKyQlNvZnPOqgAhPBGaTFGmerLczA5WolBlMS2Ds/LgRKPuGXjGxMMhnCfjDHUtqG0K7I0FZ6UD7ijVyRpjlUK0oQsER6cCBQK5rioGuyqonIl/VzuWRvhviVKkZhMYAUtm3KWZlTasFYOndYk2pElijQRw1RXDUmSo9NMCMPGtPetlSbPJFtcVhWJf5L9ePz4a/akZPC6Gbq/6uF9jNFFgmNdVjjrUfhAVNQ4V+NtQ2JSjDbUVc2nPvlZ/of/4f/Cq6/+HAqL0jLgwtuIrrPj5s1bHB5e5dGjI8qy4uOvvMLrP/whidb86Ve+yq//+hc5ONjnpZdfpm4a/u3v/3u8PoKkR9JP0ElGtbb00wHgMYnlrffe5rd++0v84R/8EecXpzxz6wZpqDlbNRXDwz2euvkMF7O3aEpLkhoOr1zjwf17UhfVGzCfzVgv12ijabwQHUWPXZECTVkyC7VqdVlRrpfML6e48R4gDO1d71VarceNQlIMm51aauQGhaZIR1y/8RRRQXO5XDKfz7m4vOTy4oLpdMb0UsK3/f19Hj582HYpjuHbZDLhIrCxuz3XIknz1q1bLT8qcqXaImtjWq8pAtNRIC9mzqLHEYH2yWTSYjcR04nXNJvNMMZw4+ZNjlczlrVIsGwoATp4GsKIlnYVch7pWCxZsSyQEFW4pzyQH61zUvlgtmVypeQok0LbTnQRi28JY2KUDqUrHq8VaSFEXu8RCRXvwDZo5zBKYRJpUuoCXw3nWK5W1E0FmaJWgX6jhF9YaUtJjfcVF6sZV3MhPJusoEhSGtuQKk0/zzG1R1lPkiZ4JVgSSppsFFmGdxKqWyNSyT2rkF7XAr3glRRqJ6JiKiQhi+uErEmWkhWik+XV30Bz0I92RPR+Y6j+yqdB4UJ3iUF/RJ475tMZdVmTh9hX6xStpK98Wa74xMc/yf/t//5/5dnbNwERdJP+cI7lch1YusKgFrAwYdAfsVpUTPbhxRdexDY/xGjFf/7PX+FLX/oio+GQn/vkz3Fxcckf/uEfc/femmw44PmXPsne/k2KbICmpCqXPP/yC6zKOa9+7tPcOLwmiQSgLmtmizk3nnmGL/zyF7nz3Mf5oz/+Mov5nOMHR+wN91gs5pwdnVFVJednZwxHfenvVwj/pyorUq1p6obpfM5yvqAs19RNRZ6mDPt9lPe0kGAYextrEIheaiz43GRdjdEonVA1NetqDYqwEDy9wZjJwVVZgMDd997jf//f//dWMiUyxaNhixIpaZq22lHR+1kul/zgBz/g4OCgxZiiYdFac3Z2JrIwgTMlsidJS6aMIG4Mi3q9Hnt7e2itW49rsVjgnBOd+AhUWysKD96KEdfyO+djYickEpSnCcC+LSXklYJZBVaAYeUU87rEeddm5NIdgB001iVbGe1oFIuioCgKwZZQrOaXLdbkL+eAhFo64DeZsqSBCBkVVbVSlLE4OTWkOqWoS5RvJNrQmsZZBsMxvVc+QT7ocfXaNT71859hsVxhrafIeyHss1hb4VyFNoq93oQsySirkulsRhM2iljc7bwjtZoUg6fA+gaHSB17o0jQNE7mnDFRhkfCXB2SCc5L/W2kCX3Y8bPpSQVMxSQpEtaJCz+eJNiyFrUCNFCFfvaGLOnxm7/5JYoiZzZb0Fys6fUynFPUteXyYsp0OgU0Jux8w+EIpUSO5e57H3BwsM8LH/sY3/v+9xiPJ/zJn/wZf/fX/g5ZmvArX/gC6+U5f/ynf0K9gr/45nd44UXFnTvPkxU5FXB+eQGmR54XnJwe8dS1m+K1KM3+5IDlfM1kX/PUtVv8g9/5Pb72tT/jzTdeJxkMcZVlen5JuV7hG4u2YNcrdJNKIXVZcjGTDjZNCMEypRjt7dPPCylvSDJW66rdHFyoj+waqehJdTcRrQ0mLVBkmABdNU1DogU0XVUW7y04y+XlJScnJ5ycnLBcLhmPx8QWVcaYts9dnudkWdZiTPHvr776KtPptAW6YzauK90RM3vRk+v1em3GKzLXB4NBm8GLzPReT1Qhzs/P24Ufs2XXrxxsq4Va6RLk8SK5Egiu1hlcYtpriQzzuha9dW2SNivVL4oAH9jgHSE1k0j4qbzHO9WC5o0Tpc3lShjlOhhgHzKoEn5u2rFpoymMIQ88MmkZL8zu8/OzthxnVDXcuJjhGivt3k0SMneGK1rj5jXrkznvHC9wTjK6g8EIrQ1pokgMKCxawWqyR7q3T6YVB8B4/xCv4N7yPqtyTZImpCYVzEkbnDZYrWiQSoQky8NY+dDNSbz7LVFDr4O3+tHMz1+LkdrO1v2X1+/JhBVJiN/57b/H+/fvc3p2xvnZBYvLGeuFtCwqMsGpvIMi73N8csR/+A//G70ixTlLXa0ZjfZI0oy6ip1JJEOR5zmj0ZjxeMLe3h5Jqjl6dMJwNOTll17kq3/2NayDP/zDL/Nbv/VfkRjDb37p17Cu5lt/8QOuj25y/733uDydcvvZ6xS9ktPTM95+7z43r93Ermueuf4UAE1VkfeH2KrBKCFJ7g1H/O5v/hZHn/w0f/7n38au1sx6fcxgIOFKteby4oTz2XHYlQzUDSmSRd3b3+djL3yMj338ZT7x8sd5/513+O43vr0VxoWHAwgeQCfs6GYUe/0eea/Yen4ptJ5SHrJLtq744Q9/2OJVt27d2qq5W61WbQYuy7I27Itejdaau3fvtjto5D/Furd+v8/x8TH9fp/Dw8PWa4o1fJHU2JUn7rLPI6lyPp+3Id9qtWIyGXOlN97aPH3itwBqvHidbflGm2iQ/1yoJHBA3aEhWGdb79FZh/OhnEh5lArfe0k8tJ6sDTyjxJAGGkTtaoy3Us8LAfvSODLWzmKs4IoJKcvVknVVSUjlPfpihj2b0VQNDo0PwLn1nsv5nDpwpR7YBJOmWJTAIB60cqTKU6SGXp6hklQanRqDyTN0FsK/xIR+AQoz7lNnmr0rVyBLSAY9dJZjQoMJrVPhUynV4oldsD/OGfu3RUHYxj8+mj7Mj8r4bX6vJIvgHJ/5zKt85nO/AKGYN9UJ5XLNfDrlZH7Ow/sPOT4+5vz8gjfffJ3333uHyXgEeJIAAtZNg21cGLBMSli0JssKDg4OuHnzOjdv3ODw8BCcp6otn/rUp/nK1/6MNCv4T1/+Gl/69V9F6Yzf+Z3f5eTsknffO+bqgRTbHt3/gBdfvsVzz73Im+/cJ80Lnr11RxYF8PFXPo7JMpZ1RblYUDnH5cWUt996i9nskkcPH3J6ckxdlqzqEttY+oOCKwcHjAZ9Ls4vUMD1W0/xyssv87lXP8fLL77I3sEB58s55XLFg/fvkmcZy8Vy+6mqDVfNd8a8O2mMNmi1KfxsM1k48kGPuqrxrma+vOT+/ftYK51krl69yvHxcWsMYvt3oA3BYmgXuUCxYWgUU5vNZsznG5b3YDBgMpls8YViLVtkgUeDCBtAOcukDVmXrhAxr9VyRba/R2IMSZq0RdaRCuHxQskI2cLuGMRBbO2Ld5AKgA1iTKKGkg2Lz3kHRrKPSqv2OuMc9076QjZIltg2lrJct8W4myaungZNbT3eNtSlo6nWeGspsgQQLC0bFqzKNXUqm5GtGlCa88spbz96D6cVjfc0aYIDrNL4UISvnKVIFIVSPH/nNp9Yj9DLGqekOL/RCowWA64VddMw78Gy0FwsZszqGpdmqDRjMBoyGU/Yn0wY9HukqQaMlKcpyZgqLdQIHXpDfpTjZ0r0rnt4p0iSnGefvYbJMsqyolyXuMZRrdYcTA64yk2ef+5j9EOfutl0xp9/59t877vflV0YaJq6zZQ4QfOkENd5KRMwCZPJmGtXrrC/f8De4SGvfOITXL9xk1/+5V/hD/7oj1is1nz9G3/B51/9JIqGv/8Pfo//6X/6Z9x9/w3GwytcffoZhlkflWSkaQ+jU55++jYqdAXBO6r1Eucd/+yf/S+8/uablOuK05MTqmodwFVwtkEhGZQ8T5nsj3nhhRf4zV//Ep/8uZ/j5o0bZGmKd8JWPj87xRQFh3v7ojMVGM6xFXzrRYXF4mN2T202BFFXNKRBQC5kzXFagxdagsZTZAnfeetNTk9PGQ6HUv/VYYP3+/2WczMej7m8vGxJmZeXl22mL6oZRFZ4FMcDWgwrMqpjyUzMEA6Hw7YkpluyEhnoUb0hlmfEEHCxWOK9CiFO5CWZkB0LpTsAyrTeTkAu5LzBQ1JKBYPmtr1RH8H2BKc0HifYVyyeJIDZLQUkeGFIssHkGj8YtZwqeXRSymR1QuNViNg3/DLnfJsRTZVDXR2jViWusczOL6mqmjNnOBsleCNZSlLJ3nltIAD8riopXcP5esVIVcxTB0oSBWQGp0Cn4jA4PKrISQtIM0VSZAwHAxa1pfYwW6xYzFecPDoiSxOSLKXXK9o2WBECiEkH7z6aU/MzYaRgx1B5cUe1NlxezsCI15MmGWmeovoj8iSl0hbnGrxzVGXJZDLi5s3rfOFXfoWHDx9Sris8NdY1GG3o9Qb0en1msxnn5xe8++57HD16xJtv/JB333qL4WjMweEhf/naD7l56yle/rmP8+lPf5ZvfOs7vPnOPcbDMS+/fIeDg0P+2//2v+b/9T/+v3nt+99Ge8udp67jG8/0Ysl0vAIvmRGvPM4KtWAxn/Kd73yd2WxBlub0ioTJaJ/EaCbjES+++CI3b1zjY89/jOc/9jwHV68wmYzRaJLE0NQNzjahvlpIlg7BjbQUR0loGITslO9qIkWPSsLNrieVmCR0hY70EdBeSlJ6oUxFdI6a1hhEzCjynbyX5pyxAULM5rWdVpRq+VDdEpBIJIRNLVps1BCB8xg6ei9aSrF9etSsiiHFxcXFVilLWZZMJhMAbGKgKIRGYG1LJciMEF2dk4pL74MhCuPlrGTZdLAv3jXga0wIEyOzHCWkSh1C7TyVMDZSCpwTEcZop7TSOG9DFnEThrsgSBi9X+sbUqzQFpTB6lCHqRST0RBjtHhu+xMhlnhYLVYslktuNZZnXnmZVVWJnvuywgJr61iVlSRklnP6WpED10Z7MDkg3duXjjne4ZzFaSmZyoucw8MrjPeGoBW6N+CybHj7g4conaC1QTtH4h1aKWpnw2bhWa0q6tqSpLVQLH4CvPq/yEj9VYHx7bdtfD6laB8sXrgzy9UKpzQmWWKUERar86Q6pTaWNDEkiZbaM1OQ9A2H+wd87GMvYHRC3SxpbNXqI61Wa4bDAVor3nrrDZSGqi5ZVUtmiznHJyfceb7BJAmrumYwfIe812MxX/Cf/vgbjEY9bj015HB/wn/3T/4x/8//x/9Ikct1VbXjN3/zt6VK3EqKOWZlrG3IUsPv/e7vCA42OeDw8ICrVw8Zj0bs7+2xNxkHNURZqE5LLZ5tGmmLnSa4UH7grGOxXFCu6y0gPE22i4SjayR/D5O/M0kiQJsYI6A5AQD2GpIE0UKXivWLszPqum69qFjOEr0cYwxnZ2et0YndYGBTQiKel3BlIuHTGNNiU/G8sfYvekYRP1oul20IGWsHsyxjOBxyenraEklj/V80bPlwhC6kGYZT0sFXQdsAVAyQk4xfuF6tNSrRGK07m2hDoqV9uHMb/C6OpQtSJYnKWw/NhHt3AaiP/Q+ber0V8siGYgNZVN6TJRp8s6EvhGSI2tpoNMZL/0NnLXvFkP3eGOs9zz+V4ULzCW+ksqBBOF54j2oaUmdJnSUDmkyRBlmYxkr1we3bt0Vxtcjp9wdkjWVoMkqnefPefallVSmpSUjxGO/RCpKwQWol6zOud+fFWzV/3W3W/2aPDRYVF5d1FqM104uLsKsIbmJMuqk1CgvaGKm6NmaTudNa3pPqhMTkGJXR7+XkeZ+qKjk7P+bgcMR6fcnTd67jvGF/b5/RaMSnP/NZnnvuObKswDaySzrr+PrXv85bP/xLnrn1a6T5kKeeGvN//if/mO9+9y8oOcEnllvDHlolKBdCChSvvfUWRb/g2Wef4b//p/+EyXBElsT76OBzIBMHKbPxKGm1rhJw0RMSXo1JDXt7+62X1Bv28EkwAkphMBgcCSLvG0HxyJuKixCCKgXCXBZqgiIWabvIPLYN9+6+3xIpu805Y687pRSDwQCTFMxmUku4rqSf3mQwAQX9wZDpdE6vlxMr+EejURvixQzhaDSSRppWsmrWNhRFxmq15ujoIUmShNb0SZsNjJ5cxL4k1BM86/rh1dbQFGkWMnsy6huMyoUvArcsPhn5faRtJLoQEFvHORuMk3cYBUmqgSDZg2pxKcN2YwKjMoh+W9g0jDFBOywJ415jnfDD2uvRok5B6915audRiWBkaEUdBCBdN+xXItuTtGtO4U2KTqSxrNOKDB2UbaFeWZ65fZtbV+9scEynIDHMlaFqKu4/PEE7j0fK13wAy1UA8BVglacJOmcmyAd7J5pTH+X4KRmpxxGzXU5VfPDz+SxMjgDuao0OpQvKqADEmY6REo3laKgSnQXX3NE0FY2tWCxm3L9/X0DcNOXq1WtM9q5w7do1XnzxJW4/c1t2jEx6qDkn/JxXX301FMwqrPVY6/nEJz7FaDTitR/+QHbXENqBSLUYk3D16jWKQUHR67G3v0+mTctnkUO8F4Vns7WqzSiFb7qZu5iRciFzE+uiImeJ4JW6AAyrnbEFWZRReSBNDKnZLLhYviKvk/s/Oz/fUiCIAPpkMtl637pcBH6UZPk+8YlPYK3l+OiUhw+PyPM+3jmWy7JVrIwGJEqsRPmW1WrZXivQaix127h3G5JGftZ8Pmc+n1MUBXfu3BEvNHg+Typ4B4KCx3Ynk8drTWVxx7KR6P1prUlD3Z+A5JtmmPF1u4HHVg/E1pAIbywmFsCJ5lMn1B6Px9y8eYOyrHj77bdZzOdtyUnc5E2iO6dW7Sd2D6Vom1LgpVzHxmcBFP0hTz99GxOY6vEc2qQobZienjGdztp6TKV0CL1dC5THz2+TNMa0z/pHPYfd42fEk9o+QoUPzvlQ8xXkW0OWQGsxRBgeq3nqalUppTBKAEznLHVdUjcl8/kspLP7YaAMk8k+w+GYumqYThfUtaff9yRJSp71KPIBn/rkAe/fvcdivgqtoIS9XlUOY3IxispQVmu0TlHIYh6PxqhUsAtRJJBdcZMS3yZadkehe0RmdzQG3nvSfCP5C2wtMHjSeWlf1y5apcnyHINrs2Vdg6e15rXXXmM2nbI3GbbjHc8fX5vnOcPhkLOzqQj5G/G6IogeDd9yucS7lDRNWkUE0S+yrZe2XC5ZrWA8HrUZwVi0rJRqmeqyaegW6+oSSauq4sqVKxwcHAh3yGxn2bpj4SPNg43xge0uJ9FIxU0w/v1JYyuZt06Y18mo7p6/m0lUSrVcsxaj0oLXRZXSp556iiRJePDgIaenpxJOdRZ8vJddqkncdLavMxiR4O2pzkZx584dhgFv7GqDpWmGR3F6eoa1jjy0V+9651vnVpsMZ3csPypc9DNppCKG4pxlvRYt5TRUZiulUYTB0BswWKkdIyUvjiKeOGdprPSWE4XBGjykaU7RG4DXrFc1q1XF8fEpg37Jql+FcCJvw5xyXbNalqENtiXLUuoa1ivJRmnlyLIErVOqspEFk6WcX57T612V2iodjWp3oWxjdUr5xygdXWA5ejKr6RSgLeB90oPfNVFxwURvpdfLOTw8xDcitxuzbXFSO+f48pe/TBn0hZqmYbVacevWLc7OzlqmuSwki2pLXio+8YmP87WvfY3bt2+39XsgPf3iYooyK00j4xUbMxSFdDy+vLxs7z3W70WqgXiCvRbHil7VzZs3OT4+BmjpF12jsV3Eu5lvXQ8qjkF3kcmz2S51if93F15c6D/OY4jzdddIdUX9orG1OLyDPCs4OTmlKivefec9CcutQ7FNK2ka+5ghSNNkBwOL49GE6zGYkHnr9XpcuXqNJnrUAftSSJKhrCqOj09CdGMwOglseBlTF0LnXcMcnYquh/phx9+okXoy6/zJF7b7OlnAvjVS8cG1AndKY8x2y+a4w2/vkuEzvVTKN01NVZWAIk2ldbZC+FOgpLU0Btt46toGYLYiSdKWAX3//iNpmJBKZqjI+3z6U69S1zWL6TH/6l/9K5xV9Pojev0Bv/kbv8mzzz9HUWRyTi2YhfdPcsn5kb+LDzmmcp2TcoSmbuiFnmexBi4eseK9W0PWPV/XK4vnjun7+LemaXjw4AFpmrRUA+9FkfLRo0etUqRMZhiNhpydnaK15r333mO9XnPv3j2ytACkBfrx0QP6/V6r371er9uMX2zHHkF3EAb8o0eP2s4z1tqWdR6NVWSHR3rD0dFRe49xF3/S/Xfn367xid9v5ue2MYrnjvOw1fAy26+LBnHXk+j+PY57dw5LZxyp2UsSxfHxCWdn54iMjei6m8zggocZv7reW7jb1kB1eWDxOUv4LGKHtm64eetAmiZoTR0SJK2Ou3OsVyXlugpGMp7bowwButCYZHtddkXuPqqBgp+wpVX3eLKrpui+7Ee5c4+xop90Jg0oR1mug6SJ6RioMJGAJE0FLETi6+6Dwm9F/SFUsiHMkTAoMWmInxuaJjQ9dNIeW7yDtF0AaZYwn82DOkCfNEvbHV7Ae0VdlZydnaBUSllJx1opHUmwVgomKqVE+kVtClCV3k5FR7zzSSHC5jVBqzwxWyUf3fhfFo5tx33zLDeflSSiD6X8ZoeLBb7GGP7gD/6AxWJBvz9gMBjwzjvv4L3n6OgIY8xWhxbtpa+bqGaucF5wqfV6zWg4wZiU9XqFda4tANZamjGcnZ21XV9kjBOm0wuAxwxv9DjEuG4oDtFY1HXNYDBoeXDJkLAAALjxSURBVFtdAbvuwozejJx3wwyPY95VxZRzSwFwdyx3N2M537YHFT3QzfizY0TYwuR2PbnIm4rQgDEiA5SF4l8V6pk2r5XXq0As8SGkiFm2zfmTcM8bFn+apdy4cTNkXMVzipiT9w6jxbvt3l+8l6g/1m1Y1TXQ3fv/qMdPPdx7HD8hrB8ZmLqpqCrhOUG3iFOYu6ajatiNh9uf2/XYBTAjHhN4Mc7haRDBPktdV9R1RZVmQvgMQnJpJp5WWS3wNK3x6oK4y/mMq1cPqWsYDvfY299nvS6xHrI8ld3FSlV71wsUBm43rexR+vG4ftuQKRHCc0Ie3N2p4gJ0QcvHx8/oTK6yLFku18wXc4Y9AWy9921nk7qu+Yu/+AvxFsIkjKn/GL7t7e213tRoNGKxrCjLFfPFlNyn9Pv9tnDYGJETEYla15bRRLnf6InEpMl0OpV7CCFIpD9EQyWLWsYitm+P1IWIbw2HQyEO7uCWcexjyEXYOLpHZL5vPjOWzMixi/Nsjk3pzG54Hb2YrQ2187o4R+X7rke2ea3WAqorpfHKodkA9krtQAnO4b3AIsakAdeL3ptrvegkSXDec/XqdXr9ASjpPqSDTlZLeNWGk5OzMO5mZ/MLd+8tYLfWZHcD7d73hx0/dSMFTwLZIjvXh4VS4XScjB2Pw9PyPVCKJBGxjW0jJeeSl2h2F3y0+uBpbOSx1DRNRVUlrQeXJIYkke4kAh4mYYJHQyUNS1erRajMz1BK0sTrdUllLVUtTSIbRWhwulHRjCHDZvF48I+DvNvjBI2TUAfPj3zw3UXgAw+oG6Y47zk/v2B6LvcmSpqZdODRqm3kefXqFR48eEDTNBRFIT32+n1pvlBVrT65MKOFz5Xn0m5qMBhw7+596npNUQzY29/n/Oy0NRLxGmO5S7f4OMtE7kZoCVK0HBe9GMum3SQiPhbZ6bdu3ZLQ2G9wJRFq2zSY2MWEuuFQFz/ZfG3zzLqh28agbBIQXSwsSijH6++GZbsYWfwsUFvX12pLRaDab7zueETgXeaSxigF6vGwd2P0Aj7WNIzH4/Z6Y8gf71OHxMf5+fmWPHI04ErFeeZQulMK1HFG4rz7PzZwTjRccrMbXCG6jMHYeNcpJVB4t+2CSy02bVlMzAx2XWh5g0f5OEkiviCLLapaOmeoatd6GUlQI0yDtyUV6gmurjCJocgLUBl7kz1WqyWJE9ylaHK0d+RpQppmbZsmYWVHOkEojdDbC6c7UeNDPjo+4tq1a6zWq864bVLj7UTqLKbdbFO/lzPsD9F+oz++Wq25uJB2VcfHx+1nJknCYDBo9Zr6/X4L2kfp3uVKirmTNKGqalarkxb3asOC8HM0QovFor2nWA6jg+hfXNCx2UIkf0YMKGa+Yiq83+8DUtj8C7/wC8FT2O5QFL+P3mdM9++ONWwWlXhcm/m5u9i3PAnXPOYxdI1QNwvdNZRxw4rnlC2lC/JLO3f5DItSIj2Di6Gcp2ksxFawqsvFk+RAkqYoRMZYBPbABPA7HRTsHRygTBK8LQNagKbGWlCa84tLyrKmaURPayOfA9FnkIZybmfs/NYc/KjHX9lI7VrHH/e63cP7blgSsQA6BkK1UZptGnAe65vWG4JI7fBtJOe9xyoXqv3bV2zCPR8kNJzF2WCgQswuA2zwWuO1w2uN0xavG9p0s9WBb6SwZUO5XKNQNLrCJAl1BG6pSbOcJE2xFlbrBbPZlKwqSJIM33hUklBZME1DUnnSzJKmljQNXC8MiQIdurLIPQU9HmdJ0wTbSKZttazwTiajGGIxy1GEzFmNDr9TWuGp8c61ixYvYXSvX+DtCruUHTAzmjTpc3p8xHq5YFAUpGqDLURjMp/Puby8bDWg8jynqZfU1ZrBcEBVSjp9vSxxFrI0YzGbi0RIwEC6CzUSQ2P4KKFbhdYJi8UqGEgb8JKoqb4xLrHzsbWW8Xi85Z12DXMXTI8eibXRwEccZtfj3szlbrImAtDiYadBoK+bPZMwLHrt0qxEE3vUxYgx4jmx488mBN1wtJRKWsMqa8uiNaLphIjWoeX5R4ux8bJ8oBpIzz3nbSihUphE2O6T8YQ00XJOJ/cjrdliw4aE87NTvG+QpJ8P1+/RekMaVhDmpcI7JYXZ7GCsH2o95PgvAs4fN0C7ZLEnGaguBtU9TxxM+QpWK8TTrgN2x89RbdFnK5cacJdu/2bBdbavy4XPjjG+fAVp2CdkC3UwYgSCnm0abF3jvSTTN+JeCZhagFxtyIwhy9IW/E/Thtqk6CzDNI7ESHFvZuU1WZ6GsNKQaE3iCeFgMOZatKKjVnZT1ZydXXDr1i2MNjTBcG2GPRhf18gGoDxKJQKytsZGDHWvJ4XRRS4KA+VKEgjf/va3qKtKCpi9fHae560ci9YbhU2Q9t/geOGFj2Gt5dGjI0ajMcvlisQk5FmOwoTXbdomxfKXLMtaz2k6nbaAdVWVLTv97OxMPLVAeYhZQKFT9KjruuVmxW41JklbHtUut24XE2rxPvN4OLdLG4jzOXaoiW22xCuiXdjd9z8p0xU/5/EQapsS0U1ObScTouEVvKn1nDtzX++EhEmyKTdqGqnBvH79mtQDduo1lYq1hlIje3l52cId3dAYIhyyCSm7r/HBYHbxso9y/EyEe90sQTuIyoMS5UDvbegDp4mZCDE9TXAaVCBHKumQioKQ3lcuiD53ju4Aht+g1GY33s3KtNbfizGKHW67r4n4UpLJbuacpXGWNC1YrZcoDMaUgvNUKUmaBQ5WindpmPiWxhi0lg7CuUlprCdJdQcoVazKGqWhXJe8+eabvPTSi8HbkKxSxOXiojOJoXG+ncRaaTFWweNodb21odfrS0eQodTVvfbaawyHQ/qDQauSGbGfJuAXsbB3Mpm02VGlQgulwOlS0Nb3ZVnBdHZOmiZbXYnTNKUshYUe+/V5LzrlsXeftbZtGiohthjN2PY8kjlbFniaUpYVKhS7xufZDT+7dIJdMuJutrT7u/h58f+YvYth8e5c6y5m+Vy7tdnHRSyZONVu4t3XdDGlaNC617ZbKbDrKOyGpdH7y/Oc27dv0+v3OllIcDYaV3l9VVWsVust4w6PJxC2MbzN9f5Vjp+6keo+oM3h2y/vXUsMi+FW8IXwVCGUkywdIduw8bhCr7nHdK7ibhT/j624ovtu2785p9rfeyciZ+W6lKJbpVouiXEiOO+VsHedk10lMSJZbHRCkoTQJUkxaUaaJtR1QlPnZHkqkrNtBsriMnC2xCSaPM9EujUxIRHgefTwYUsx6DKxZZJvQg3nLR4XSKSmZbzHxgzOecp1jUukfs+ERRYnYlTGjMXAkbgZWyVFbk+WCeF2sZhz586d9u/9/oDLy2nLOi/LugW9u+qd8ZzRGMZMWJpKhjAuxs19blL2sSloNIyRgiCGSsTY0lS3r4/hWZx30aOIRiouqC7oHY/djNWuh7ULg3QXdPS+4nPbGCSJJgRX2sxP76PXT/uZ0ShuJYjCWoqKE13ca3NN2zWbXcjm4OCA0WgkGudespx1VRPhDh9oFycnJwBb5+5mKrtrenfDf5J39VGOn9hIfdQT/yTv6e5acTdBdQ1L/P0GMwAv/e+IxEiIXVBAGm1GoFGMGp2Jsm3RN7ySbcyh+54W3LKexlaUlWknhbjvIbWtE0zwkNIkRWvF5eUsgOQNpkkwSUpiK2yT0NSCL1VV0hIV0zQlSTzWQlmuBeMIaeNSxx3W8cabb3FweMjl5VRCz07Rr1bRADlx8wPW573HW9cuEoCmdixXa7IE0iBdosIYHB4c8uD+A6qyZLVaUjWiYdTv95nP522BbwSu67qiKHpkWcpoNObKlStcXFxulfMsl4uQaRIcbbFYMBqNUEq1xM62O3II14qiYD6ft+Uve3t7LdVAKdWSN4uiaLWorl+/3mZPUY/v9F1jFT3haADifIweQlyU3axopJ5052/3/F06xe6ilGLqWC2hOp8bN+d4jRHq2Jy/C6zH7GGrtx4IvV2DLnPCYpvtxEvXiFy5ckU808RQlpWEqkkCXoVrFa/15OQkOA6btds19N373x2T3c/8qMffSCOG9qfOhXbd5nh0b2DXkAVIKjQl1KFIOO7+rv04paUwMnJD5HO2+Sy7NrK7e8nX5hri97vpZ9g0bowLrvuA4oTIihFp6KqbZRnrlSzcyHQ3xmDSjCwryPOMpknahR3LQiTj5ZnOzpnPZzz33LMsFwtRlVSbcTw7P+OpGzep61pkNaIwmxcqnVKh15urUS3wKuQ+8RIl/JtOl/R7fUocRS6p+cRoLi7Oef/u3SAg6KmqUsijgTcUFTAjH6ksS/r9AUr1sNaRZRl7e3s8ePAQ2ChsWuswCW1x82w2a0mX3exXmqYBj6qYTCatAYseW8TFkiTh4cOHbUMHrUXhs8WjjME6tryo+ExjWBZf1/WonrS5dr2lJ4U03b/tzu8YZkYDFhNI8XoiY1/mM60XE18f/49rq1stEOdnbF/ffU/r7XUMRNfAHh4etmMfs6XyGukCEz3W1WoVBAThSes8hpqRZrHrhXbHZTdc/HHHTwSc7z60JwPnT/7gH3dBjwOXYK0iSTJefOFl7t9/wHK5Ci25JTPlvZcsmjZ4FXabDhdGJoCHTuscFxfAlo5N3BLiQG5d2db9SGoXUVNo4tAF8TkXW4UP2muIp1iXS7QW7ATlsGvLOqTtm0YWu7MydsYYkjSlyHugFev1in4vI00SRkHkrKykGFcji2yxWEjR7s7kaY3oDoDa/bu1lvlizvl5SpYoqnWKUpAYzTe+8Q3u37/P9WtXWa+XzGeeMgDYVVXx7LPPslgshFoRPB1Z4CL3cnJywrvvvkfTNNy4cYPzs0uyLAsdpJuWCxW9lajiGY1PNBoRjK6qCu99iwcOh0P6/T6Xl5es1+u2ZCcC+tHIxfAlGogu+3s3JOpiVfHvu3N1N8R5Evcobmjx++4527/70Eg03ZBMvfdtITnKkYbOSF1drRjubntgtKFelLyJz1jkXxTe2yde8/7+fnuNLWmzszyicZeMq6cocvB+a6Nu8c/ONe5uBLvUl792I/VXOboPJf7c/d2ucdr6vZdix1df/UU+//kUo8WNLcuK6XTKo0dSAb5arZnNpqzXK6Q9TyMGSm3qqbrXAtv4QjtQT4hIN9e17ZHt4g7ikqvWCHYLgatgUKRYehEAVk9d1YhRSnAunNMRYv8EwSfg8vKS89Mjev2C/f199vYm1HXFwcE+zlaB07RsyzfquooX1ZlAcgvtz2o7M7VcrujlOU2SsHQrEqNIEsX3v/+X7E32WCwXaGBdrpnN51y5coX1es18Pm/Di36/z3q95uLign4/x1rXdiWOciyRrV5VFf1B3gLMcZeOoLlU+D8gz3Oqqmrbrk8mE05OTtow++rVq20BcryXyJWKOFXc0ePCjHNit7btSVjSY3Ok83OcV/Fcu2TQbiuv6EE9hoEpTVmuWyMQi6M35UyOuqlJTLrlAUVPZNfj63r8XR5W9Hp15+/xGq9fv85kMmmNu3W2A4IJzivXQtvfME3TlhAc76uLIUaPqmvQu97TLnb1YcffCnDe9cK6Ll/3Yrs/gyJJJBX+//v//i8451sAdjQac3hwhSuH13n2zgv0+0OR/LAldb1mNr/g7OyIR0ePOD8/YzqdtlrQIOQ0wXTi1YUwaMcD7P45wvWxIDiKo8HGgwJp+liVdauzFB/KbHbZ3mfT1HinWC5XnJ2ecX5+wfnZZUjdqhDaJmR5QlEkXLlyhapcMh6PWMwueeuNNWmasH+wz2Qy4fj4iDzPWqmT7vXHCYL30l6ps0gi+O6cYzGfY5Qi1QatfJAqXnP3/fdxzrOYz+n3e+2CiuUnl5eXTCaT1rMSgySs8zzPOxk6uLy4RCnFer2mqmp6/azt/hLPeXl5SZ7nLaWhC0rLBiX3GLvPRNWD2OQhZvrizh0XjVJKiIhsA+LdzaqLLe3O3e7RNTrROHXVIrp4T5zXsRYx/r5dA8BwOODatWttQiJ22K5ruTfvFNa61oBFQ99NbHS/4v11AfRIo7F201VZKanPvHbt2lZ45jeNG9u5L+PWBNXVRNq674SdXZxpdwOIn/eThHjd4ycyUk8Cwz7s+PAQcfP7jSEL1AMaTs4esVquqGqRVomM8TRN6RVj0kwyP3t7Y/b2Jhwc7HFweIXbd15gMOhDaOW0mF/y6OiU6XTK0aMjjk+Omc/mNHWDtRVp4gPXRaR+40MIyXlQUk8nO4dFBWBeBOV94C45kiSlrhry3JGmQiuIi221WvP+e3d5//33mU4vKcuKWHbTNkmQ0UAph7drsk9/ivfee53lasnh4RU+9rHnMSbhvbvv8tzzH+P0bM7zzz9HXTdYixBGvd7kN1W4BxXapEszevkZRVOXrBYzUZTUwhrWCi4vT3n//XcAz3w24/jIUZY1Xgk4u7e3R1VVzOdzrl271u7EZVlycXHBdPoXAV+T2reLywvG4wkm0QzTftBM2pA4JVmQtJ5ZNHzGGObzOfv7+61My2QywVrL22+/zfXr16jLtbRjQrC0LISRAHVjBdfUYkhiKBTDybiId72q3Tnc9QCiceuW83Q9togNpiFTBsINiq284jX0+gOeunWLg4MD4s7Zni+GY15RVTVFUXB8fMybb74JqK1QNhpC1WYEfSvV0t4DwhULZoN1WXHt6lXyoteOj0AmQTOdDdBRVTWLxZLFfEESmOjOb2O10dBFgx3D0d1w8MfZgB91/JUwqZ/kQ3Zj9Y9yeO9wNGjjODgcUw7zLbdSODoll7MjrHXBCwHxwKTcJM+kS0V/OGKyv8/B/j6TvT0ODm9x+85LDAY9tNLM50suL445PrrLgwcPODs7wzlFVTaoMLGEn+XxWFDC1HWR4xJoDpoNkFnVMb0taqCLxYy33nqXN994i9WqFrDfW3QoY/BYrLdbD1ErD96yXE1ZrqdMZzOUdri3Gq5dF6MwnV8wm65omoqLiwvSRBa4s64tAPbeBkJrJG6Kp+a9tPwyyrNaTNEqGFpbkWWGu3ffwSRi4YqiR1NbmrrBa5ELjvpNsW1VvPemaUgSIV3G4mFZsKmUByUJWS/F15vsU+yOu1qtcE60ySMIHid9NFBdImVRFEwvp9haPDKjFKPBgP5gSNU0QYNMoc0ma9f1cCLIHPXVI37TxZzi4nsSltINt6KnsMG7JFMXPW7RRLdhg03Y39/n6aefbomxG2PXtItersNTFD1OTk54++13qKq6ldOJobwPm/cuIL0LsmfZhueWpiLlrJRuDbiTKYfvNPBQSqKMo0ePhFitLHXneuP5dykdXc+pG/J1x/CjOjt/6zypH+dSt66w1mi2Y/04GfI8bzvepqmEFrZxWCdZvsZKqrWslswXU5qH97dSssZsWiv1+n0O9ve5cnjIwWTCz796p93BLy8vOTo+5sGDB8ymM5xrSPPtDF/32l1gxhdFwWQ8DuGeNKr88pf/M2dnF8QyCNs0KP141mNrEXhHkQ9ITEZdSWfb0WiA8yXHJ/dJ05TX3/oBn3jp5+n1C46OH4LyWNegdNYaUtps4CZlLmC0awmZD+7fZzTeY7I3xtmaqjK8/vrrzOdzJuMx1q7DAjQcXrvC/v5+iw1571ksFiwWC6yN+ltZ+7yilIsxppVhib8/OTnhypUrrWccSZggDG7JFoqCwvn5eWsEYgcaoRvU4b4Sev0+o/GYdVUxmexR9PohLBP6Slz8kXi5y42KCy0+g00I5rYWXPQSdudwN6yJxy4nab1e8/TTT/PUU0+1SYFugqAruSP4pmBu77//PpGo2v2s7Tq/bU5W935iRrbbuSeSYbf4XWobc4tebuRH7Ya4u2PQndO7YWAc68fhnR9//FTInD8OoFRKgdpkCXdByTiYzjmqWkorBIDWqESR+DSENlIDZkNI5qyI3tV1Td2sODmdYY8sb7/lcBYMSWvAYrvu/f19rl+7yWR8wOXlOdP5o/YaI+Gwi5nELFKSbHrcr1Yrzs5OMSbDO9mt5OFshxCxHKTlkqDYH43Jsj6ErstJqllXC3SSkvcSVuUF3/zm11mvVzhnuXbtkNlsHnCLEqU8SSLXk2dF61nI7mzIMvFQv/nNb3LrqWf4xM99HOUds1nJ/fv3A+40ZblYcbB3iLWWK1euMBqNqOua+/fviwcXFAW6nsTZ2Rn9fr/lfjnnuLy85ODgIMjDLNtuxLEF+2oltXkRL4lAbSSRxgzeNkYljTCV1ozGY3SSsp7O0GYZzjfEs8lstThdZz51kwjdjFU0ZLuKp93Uetdz6J47YlbdRdo0Dbdv3+aZZ55p7yH+vZuti38zxjCbTXnrrbdYLpfttXRfF41uN9yM1xM3ini+mJ2u65obN25w7dq1rbkbM467YW/E/eJrIwUkjkG3lGfX8Owaoy42/dfuSf0kONRPejxmVT1tyrxrmLqHLPBOOyI8Un8nHTbQmijWlWiFV4JX9ItecHmFRe0B13i8VW39n3MlDx7c5d4H74pBMglJasiLTcp3Pp+3pRq7rmvM9kVw1znJ1DnvsdaBkjZHXV5ONx2vlHR70TplMV+T5z2yQmry6rqk6Bk8DYeHEx7drXnzzTc4Pz9vQefIXG4aAUqbpsZZT1lWRCMl3qVM8rpquHHrKamv01BWK5arFYN+j9OTU7yDuqnbUpTFYtGGHJGnVBRFS8KMf4seSzRSEYtRSrXGKHKt4s+x2WiUfokgfTxPl1wZQ1vvPav1GodiOp1ydn7BnWefZ7laMxrvyYZWNW2tWjxHpCFEgxLVToFQJFw/Vj7TBajjV+QGbV6zMWRdL+2ZZ57hmWee2Xp/9FS6a6CrBf/222+3WdR4308yrN0kQFxTMYKInyWheNLy07qJiYhrwcYAxvOfnZ1RVVXbvLVr/DZr8fGs3ZNwvicZrA87fiaM1JOsbwTvnjRJNi/stsEWnCcyYSNLN7J35XPEgIjulA+7q8YkHq+74Zsi76fg051r2+yW0QOAbe2euAiMkQLVLgvcWYfWKUpLLVRc5JEIGV1yrTWNbxj2BjRNHdz0nDTLSEzKYDCkqUuuXr3G8mJKXTckSUpV1cGIit4VqGCodDBaoTjZbcaju2CtbairmrOzYxRwcXGB1gqljXhB+/usVqstYxKvP4YiG8Z8bMm0kX5er9ecn5+j1KYjSpRoEUE8MSKx517sQCws9WW7IXTP6wEb8LZHjx6RZjnL5YrFYsUPfvAaXhmRbnE1sAlv2mxWC2xvvBTvfZtJjKFoNIrdxdY1WHGRx/NEYnH0iO7cucP169cfw7u654ufF72qN998k8VisWXEuhtibGsfjUX8Of4uGsB43YPBoM08xzBb1srGwMX76F7nw4cPqaoqbLgbyeF4D/F9XT5U16t7koMRvcCPcvyth3tdi/tjXhSKYLfBN+jesCeKfcXfe0/gDkTm+5MGKUyK8DnEshlVd/76I0idPn3sfHHyxN1MSgY8idq48YR0vweMltq+JNl0Au5madrzWEtZLiibCuk51wOn2Nu7wnrVsH9wjfFkj4NBwYMHD3jjjTexHozOSNpGjEI/MEEWRYWsUFR7lILiHmkqnst0OmPQz4OHocICzTg7PWc0GNPrFcxms3YiRy8ncp+ioZrNZly/fp3FYhG6x5y1ntB4PG6fZ6SGRMMU8axIZ+hiXl1QOM9zVqtVq0Ml3plmuSrJHFjnuXHzJr3BkOFohLWWPMukaavbCLnFxbRL6IxJgWgk4/0+CfTdNVSSdZNi8Hi+mzdvcv369S3caHcexQ0uNlR9/fXXOT4+Js97m4iBDUjdBaK7Y9PFS+Nr4n3Ga7xy5QpJkrTY3uN8Qr31XB49erSVPOhict3zd0P+LsXjSev9byTc+6scP8nF/SjDtevadr2q7QogFQiMnZ/xKGI91OOfp1T8i2/5II9/fvsdiu1rgO1dKFb8e+ewgUEei2c3n6lDXd3GzY5h0NZOjcO6Eutkwa5Xa0ySYK3j2eee4wu/+quUVUUv2+P09JRnn32BH/zgB0yn04BfKNKkoFckFL2E4WBIvz8I7YciniNAf5bm2MZycXHO8dGa8/MTTk6O0VpC3WvXrpOFtuFaKebzees99nq9FlTVWrfZ1xiiXF5ebnkYcQHF+45jGL2FaDzW63Xbgdh7v4VJSaZw1Y6ZUoail5GiWK1KiqLHneee5+j4WBaf0qxWM3zAsbo4Sjx3/IqeSJQN7s6/LuUgeijOucfUVbuh0DPPPMOtW7e2Mni7UUEXy8qyjPv37/PBBx9sdXXuelLdMYufF6+xG9ZtxkeFYvaaa9euCuWB7RKf9jO8VAzE+51Op+0cjr/rJo3i8+p2k45r4UclF+K5PurxU1dB+HFH1yB1F3A8WvvQ/l5tvm1JmhvjsnVuBbENkBiodOvvcXh9OL/viHp1J1mcmM45Tk5OuHOnbBdkDBO6O50kBiTV3CUQxrKH1iuzFXUDk8keg0GfxlrK0tLrj0jMgA/unUsnEabBu+jx8Vd+ru3eslwuuLycUlcVStvQaohQEFy01zYYDBn0hxS9AdpovKtZLmfs7+8znV5SVdIVZDiQVvCWul0YEbQFWt6RMaYt8O0ylLvsZGMMG80l04aOcdJ3vZXVatW2rxoOh63hihLCzjmSVDpX50WPsmrQScLxyQlJkpJmkgEuzCjQAOR6Y0F0N4SJIWT04KPRithUN2nS1bDqHjIXxFA8++yzXL9+vfWOuvN3N6KIfzs9PeXtt99uF36SpI/Nua6B63o1XYyz+x65RsXe3oSbN2+2hibOv+51dMfeOcfR0VG7+QBbBipe964ntnutXY/qr0Lo/CmFewC7DygseKNbUls3zRkxptblRuFD3Vx3QDbRoGQJ1RNNlCQQfRzojv7U5gXyT2RmwwYnc8Foxc/TKBrruHfvAb/8yxl53qOslpLNc5uKdq2NRKmhI3NdSzhx5cohN2/eJM9z+v2+yOSuZixmx5xfTtFaBW8kIc9S3nj9Db71zT9nXVbYAGijROPdmLCoAr3AJAm9Imcy2WM0GgUdch9wsIbz8/PAvSlI04Tp5QVltWIyHkorbyetvfYnezhnWVfr9tnEBZ5lWdtIQcLHtK2vi7SCbiYr4nkRHI/KBVkmDUOd2+zYkQ/VZVnPZrOt8CpLU5qmJmlEdULJpMI5S5okLFdLjN7mNUUPqCiKtunoLuUlLqYuBuMDnOBbGoMkKSIuJxgE3LhxnavXrrJer1Bas1wutoyIGOTN/I9A+VtvvUVs5y5AteCm4ZXtWom8K/GaRA44zq3GNh3qiSJNDDY8p2goIgj+mOHwakNOdq7FEOMzj6RR5zv0mdBFvK4qGhu8OL2RWxYpIRmbtmg6PqePcHxkI9W1zv8lh8chMixx4IMapjLYqkZkVkTm1jmp/5LUqWpvMHZ5UTqywGWydN3icGacUk+8ZqUCwzeEhV1J4/je3cMGDMwGPnzMkFnrWa4sJ+cLsrQP3qB8gnRG8RizGeYo2mcby43rN3n++edAwXw+4/z8lJdeeoks6+NtiRruYUxKWa6YTqekKTTVOUWaMq0vqVdLnDZkAQCv6hW+8u0u7Jwj1zmrlcfaMy4vN+U5EduI/KYsMzgn2M3e3h5NXVHkuWRDq0q8zvDInHOt6mV8v4QUaWtM4qKOIV0sDo7YU2Ttl+WKPE+Zz6fUdUnT9NpmDFBQllXr9UWjMp1OKYqC5XJJkRcMegWrco1RYOuaIs9xdcVwNKZarUiMwduaxjePhXjd+dD1duPP0QNseVyNB5KwcTQBZWhIEjAmJc9Tbty8ERQuDWna2/qMbmglNZqbUqHvf/8vOTk5aesXy7JGEkLNznVt8DNR0bS4BqwWzXGC3It46xprJasbCbIx7N7F10CMXF3JM1wul62gYTTiMRJwLlAetKdpKpRK0SZ6V1b4ii5ECwguGhtYeG9bMb2PcvxMhHvOuZY/5FxQigy4zZUrV3jnnfc6rmnU5tbo0LBgN1PzJFe6mx7tvq77f/d4Ip7WTo7NjhszZsfHJ7hOWlkKNbMtD9A5FxKSnqeffprnn3+Ot99+m9V6wfm5KFW+9NJLKKUoqzVnZyesyxUf+9jzDCcjlNI8enhMbS394Yj5qkIbzXw+3yIFdgHTpmlYLtaP1ZfFEAwIgK1Fm01qPw1kv8ViTpYKgxygbOpWzzwyxLMsYzqdtmTNiIfEYl8Zp03XZVGzqKjrml6v10r9xkzaJtPZtAsk0h92cazxeIwNGIzzklW7fv0a2ogMsw+lMq7jtXT/j9e2iznFz+hijzKPRAVjXdasVkvquqTf7zEcDXC+4dr1p7h582Y7B2NX5O05GXSkEFJtlmW88cYbnJ6etmHoBgfTW/OtWzjcUgDQwQMVEb00TYPxEGPlvWdvb9IKFMYQ8ElzPH5uXdfM5/N2vmwZNP847SHCFbu0iu262U1IuLtJ/LjjZ8JIbcBA3/Zysx4GgwGvvPIKb731dsvhkISzQnqsB9fTucd2xfj/k77vvq6b1XnSNW0fsktZu3lA3oN3jrOzU1CK1XrF2dlZKKFxbemF9150yJ3j9u3bvPLKK9y5cxtjDN/+zjep65qiyNqdbm9vwsXFQ5RyfPe7f87h4SGHh1fJ84IvfvE3+OEP3mI6/Tbns/MWP4mTS8ZyA+o2zTZrWinVejbRsBlj6PeLVlmgDjSAOnRoKbM1k8ke+XpTANxtdtn1nGLBbxdLjFm7iCVZ2wR5Gd9m6mIRbbyeum42xj1M+EjsjN5a3dTgbCckDt5KU1MUOYkRcqnZCS8ithQ9zm4qffNsfWsgtwDpxGOShKIY4VyfuqnwruHOs8/yzDNPh4W6yfp152c3Kxd//8Ybb3B0dMR4PG47Ocfnaa1QQ1ovBtpQe5PGd+Bsy4urmyp4OhvAvN/vbz3rrpHrrgWFJk2EevP++++jlHhgW4krHE2zLQq5S3ztUhR2k0Lx57g2Puz4mTBS0Tqfn5/zla98hd/6rd8CLQXFsf5LcB3dYgJaGZyvHjvPrpcUv9+NvXcN2O7xRCOlNlyrOIFB0zRVu+t8+Y+/jNbQ2JqiSDg5fbRRfLRS9/bUU09hjOHs7Ixbt27y/t3DUDO48WwaPOcX5+R5xnK9YN/vUzcN47097t77gNF4wisf/wQPj4X1vQmRtgmwSZKglWBVXTC4a7TSNGU0HnDt6iHXr13n7OyMo0ePAuBbsFoumU5n9II0b8ScIrbknGtZ45FxHoHlaMyipxTDQdjUF0a+VDQWSqlwftNO6HhE0itICDmbTpmMhjRh0keBwf2DfQaD/gZPtI4WdglGIvK5NnjS9vjF7yN2I4alwbq6fU7Oy3g89/xzXLt2LWRqNc4qUBqtElBOitS9CkkehVYJXsPJyQkffPBBe9/RW4zkTUjb+Ra/dtP93kvX4SxLAk7rsVa4ctETG42GW4YpZuN2Qz6haYiR6fKjosEJI7iVydzlicV5EMe61bnvfP6P8uSedPw1kzkjP+knO7TWeCfKjd/5zp/zpd/4Ugt0yuSNVjyK24FFWi91Gb0/yiPa/fpxv3/S++L9+1Aw6jvurlLS1biqNql3paFpStJ00vJsJAR03Lp1i7IsGQwGTKciTXLjxg3ee+898rzo4EWW5WoVug0r0iyjP+hzenzJH3/vP1GuBddLsk3zgbj4dhsCjEd79Hq9Vi009qkTLaoVdV2zXq05Oz/nwf0HXF5esr+3F4TsZiQmweO5f/8+KjHt+ePnSfjWtOTOWMIRPyd6FFE3Khqp5XK51T9vMpm02UHxJhKaZr2188edvSxLwYi0knb3SjFfzEF5xuMRBwd7Qd9e8BHtJYcbryXiZ9Gj6RrIGLp0jW4cT2trkkS3CZskSXj22We5detWe76mcWKE3GYubjJeOsj+eM7OLnjzzTefGIp3C5u7xikai2jErJXC77oOIXLoFlMUOd4LnnZ45YA8z7DOAZuExC5wrpSS13haqeZIKejysKJn3r2vrlHfzfTF98cNJ3rTf2Ph3o+3fhsC5Y87nmTGnJeuIC+99JLgHGGSXF5eMptNyfOi9aYi6I3bFIn+qLDtSRhEHJwneVM/ytPyyEYoD8h26vYUdVW3u12WZTz33LOYRHFwMOZ73/9zub+QpRoOh6zXa374wx/yyU/+HGdnpzz77LO888479Hqxhm0Z2MM5g8EolLrIfY7GA/qDHovlGU3tyVW+hdd0Q4m4iwl2IhhDF5/rhlBKe9JTHXTZ9QZfcB6npMX69PISq2gVMOOYx0r+6L5HykDUiprP520GrVtMG8mCcYxjm6ruM4pAe8wSRpLner1uJ/xioSgCG10pMMkmgxQxnkxvjE406HGRdg1AXGTdRFFcqGLgfBuGKqV4/vnnuX79BpGvhVetuFz0+iM1pptYmM/nvPfee63XFMOluPjj85MFv9Fi725GbfGz0TR1jbcxbPVB5kZz4+Z1nnrqFkpDotOW5d41EFs0AaRJx/HxcYsNRsMe7zlNExI2IVw08vHnruhj9Ny7ayp+1sZb/PHHTz3c8yFFqZVpu+LiNzvegwcPePDgYYdsJwWriUnJMoM2G/dy102PR/w+WvgI5HWPJ3lZW0C81rgwWZwLLr1zJEkEB8WrS7MU5yzL2ZKDgzHrdeQDafb29kLWZMVrr73GzZs3GE/GTKdTfvd3f5f3339XQq/RNZLkJnXTcHp6zMHhFaytQSkaVzPeGzIcDTE65fJy0Xb27YYs0f0WL6lqvYS4COMEMka0lQ6v7FPkKVrptoW29540y1guFmRZRq/fxyl44YUXePDgAdPpFBDXfX9/n+FwyGq1YjKZMJ/POTs7I01TBgORVI6fJV7QppN0DB1i6UtMlRuTsLe316p2eu9bkmgMOeuqos40dukFk9Ga4XCAcw3rVRUW8aZMJ4amXZJtF9Pr4inx6Br/um5IUvFmXnjhRa5evSbSz0poMfFt2+eIuI1Fa0NV1bz++htMp9PHnkv0oOL75dr01uLeJXc2TY0KUIRQE0LG2yQcHOwTe+Q597gwX5wr7dwJEtwxE/z4vQRaDd3rM60HH7G7rufVdR6iYYoZ6I9y/NSNlAyu4DWx8n21WglP3MHR0RF1XbFaRb5IBBak5i7ujF3RtNjBpBv3RqPTNT7b1/G4J9V1VXEOpyLnY1Ow6b0KBkJ4TFVZcffuXZ7/2HN893vfYzq9bHeu2BElFid/7Wtf44tf/CLOOc7OzlpcZzAYMBgM+OIXf4P/+X/+/+C94BsPHj7g+OiIW7eeorGOIu+xWGxIjdFYbfCyMFTObi20yKqOVIL9/X3SRFQtZ1PhIEUcIk+l7CXPcvb391mW67YUJUmSLU8odnEBMUgPHz7cmuDr9ZqDg4Pw2c1WD79uNjKGAlqb1gPbLfWIXsd4MqHIDXWQas7yIng+PrQBA50YEm/aELcbyj9pTnTDq0hk7IaDYmQzLs4vmV7OKfK+9FE0aaBLJO3cjHNWKUjTjOVywWuvvcbFxWXIyLk2FO4u5nhd8hzY8kDj9UZvSMp+YvG18MOquuTqtcNgsKNEy7Y4X/fZtCC6E8G9WP4Un9EGyJf2aF1ibNfAdvltu0fXU+wmeT7s+KkbKTxBHkIG4qmnbrWxe1mVPHwonUY2O13okupc0BR3bQggAy9p2zhgcTFFvCQass1uIuoC3QcWzyMdjUOGxnvQCttYbMdQKdU1AJAXOTeuX6coCl584QWsrbh37x7GGIqgDnDjxg0eHT3i4cMHfOc73+YXf+kXWC1X1LWk5T/44AOKXo+68Uz2DzFJSlM1PDw6wnvLdCHdVW7dHHB+fgaoTvgZQhXnW9mNrqJEd+er65rVaiUUhGrF4eE+Rw8fce3a1VbVIGYBLy8vOT09JeuLXnl06bMs4+LiguFw2HpDo9FIBAf7/bYFlWBNdQukj0aDliS5uwgiZhTDpJidisXNsV1WZHfbZk1eCKN7Xa6xthHFByXGPdGKVVm1OMN6vd5SAQC2wilga4HG+03TVKgxOFarknfffR/pZmTQSoxqEsPlRLyGotiw+3u9Hufn50ync9JU2sQLJicctc1YbBZzlm3Cu7bMRR5mS6btFT1irWDcONI05dlnn23XjpwutsjaGIp4tIbaieb9fD7fogns0jHkvrcx266XFg3S7gYQcbsuBebDjr/RllZPfoWBnao7E26038v5R//wH5DlGegGhW4XiTBW4w0HXMWJFxaZtpEF21hLUwtVwQc3mNYVV20JhxivlCRJyZKuJ2YE9DQaXMAswo7okeyHcgnKgXIa5T2J9mgsDsdgPOQzr34alOWHb72GTjSNt1y/dYNnn/0Y5+cnnE+P+OC+43x2yoNHH3BwcEBd1tSuBqOobYlJFXv7vRBWKVZLafv0/nv32d/fo6ktxjQsFyu0SqgrhzbC2E5MQtNUshDyDIWibmo8FqWT8L9HG+lmUxQZy+Uc6SbvMUYJRqY0iVFtfd54PA7FyFOyLGsZ49ETEJrBGq0Vg0GPqlqT50JqlfEX8l9ZJlup/W6xK2zCVaEUWNbrJZOJGCZR+JROz846nIP9vSss5itOTs4p8gHOgkPC7Kp0pNoEFrrMkUh36OIl3RrKLrAbvUpRXZC50LLLcVRVGTzUFOt063WB5/JSwrFdJYUsyzA6w9YepxrSNOETn3wFcFgrXuFiOefhwyMSk25Wl9t0cymCoa2qErSsA+sdDrh162myvE+WZ2HNKGyzLa8Sx3kby1UcHR21FAeg9fSiJwePNzyNBvZJR9dzi/r03Qzwhx0/kXzwhx8fDpx7H1ne8R3b1jx6Oa7j/ldV3fKk2hIBr8GL29k9dgfKey9eUOdzIhkxfqZSShZjCIMidtINIbMsw6tNQXFXS6j7wGazGd/+zrf57ve+A8pycXGKSaSLy/n5OYvF9+j1c1586SVefOlFVqt1CwqnacZkssfh4QEffHAPlJStXL16lQ8++KAtI7m8mEnYlKaMhkMW86WQRxFjLVSJYMh3MJbuLhfvP45TYhKGw2GLGw0GA5TzWGNaY9SlNsTJ5r1nPB63Xpn3tgV4I0EzekG9XhG4P3arZCYausgdstayWi2xNmuxtdhLr65r4aJ532Ysvfc899zzLJZ/KdetFSZ0s24akYLWnTApzrMYAsYjjlX8zGiooleltW4rqGKPxG6aPTbpWK9Xrece50m3Xq5pGpLIK8Lx8sufDDQBgRSyLOPNt96gqS0keuvZxeuLG7jzHkJre63Eu71x40YY3+jNuHZtdmGM3bngLdy7d68N47sYUouL7SzzbtIhnr+L78Vz/ygK0IcdP/1wr3NsAMRA1gzH5mZVm0WTpoWSdere+GNpTaUes5u7JT7ivm6yU93XAe2k1qG1ugmLVhadlHGIS+5JjGFdrvFOkeWbFHaaZqDEfVdKU5YVZVmF0KRm0O9TNw1aGYZD8RjWpRAq+/0+n/rUp1BK0u+/+PmfZzAYbImXCe6Q4328t4gBeLxzqJ00fneiyi64qc8yxpAlsvOfX5ySpRl7kwm9wYDleoN5xfAy4mDRkFgr+liRkR49iEg3ODg4aPk3XRA4dpiJiycarZhdi9mm6I1EL0x5zcOHD/nsZz/LJz/5Sfb29ijXJSYuMK9orMAA0TDG9Ho0GNHw7iYfNhm2mHHcFM/GbGM3HNtVyux6hl2Mq65r0qTBaM31GzfYP5gEA5oAmpOTcz64d4T3tCTS+Pyi59LidN5RN6LzXlUVh4eHjEajdt3EOajVRr/qcQ9KjnW5ZjqdthnbbtZuuyB5+727QHx3PXfXWddDexI2/KTjZ8JIdTMVEHZ3v2205GY773GB8s82H+OxzJ3aDkDjZIqfqbW0Zld62yh2vxeSYB0TH1tHN2uUZRlVXQqm4BvqxjIcDjg6kszTbDYlSVKGyZA7t5/j9u3bzGYzvvnNb7Jey4KdTuf84C9/yHI1R5uG2WzWXud4PGZvb488zzk/P28XRZIYynWDTjWw4TGJMXbtuMUJs4tFxNfGMFgp1Vl8AS9yjl5RUDUbHe4uGL9cLlvPt2kE64qeX/RYYkYuEkDjAur1egwGg7a5aFTIjM8pvr4rCyL1hhlai3Gbzud873vf49nnnheD2dSUAf9IsgKjxBuKjPV4zbs8oK73BDwW/gmreyMt3O0p2PUeujSLrnZTDHG01lhXked9nn76FsvlgjTNsdbjrOf99+5RlVGksGnHO35W10gZo1vtf5FjubaFPbZhW7PNZ9olsAJbGHCc/9Erbg1WR/4obmpPyhh2ExRdfKpL/vwox99Kc9APO3Yt7sZzenIWToU2VfiNNlH8v/s98ETD8qSHo/zjGb7u99Gt3r3W6H21sb5W1HVFmgqoKyn4fpDWLcnzlL/8y+/z7//9v6ff73Pnzh0mk0n7GQ8fPuTq1atML6fkPdV6ay+//DLvvPMOk8mEd955RwpsF4sQ2mlowf9uxfyT72l3F42JAhHrk88cj8chpG0oigmLxYKHDx+SFj36/T4PHjxoNZei0RqPx4HnZbdCoUj2jK2812sJcaPiw+Xl5RbXJpJTY5iYZRnz+VxC3fDaGObp9llI1m1//0DCeaUxIXT3XkTwvPccHR1tGaeu8YuGJS7KqJja9WDE2CYte77X67XGIXoe3cREHJ8YPnazhcZYbr/yEr1eQV1vNpb33n2XR4+OyPMezomyQDcL2uUhdY1NbKQaM6zxWUejEJ91fPa7oZdSiqNHR+21b6/FzXrQyrTF5vGIgHjXKHYjmyc6B/9HCfeedKEbF3M7vem98Kps0LUWMPvxwY8DIfgXrZcUB/wx4+kfR9K61j9myIQgqB97XbxmkPMIu7fC2YamUeztT3hwf8VyuWR/f48XXvyYNC6dTTk6fsj+wSSeDaU9l9NzqnpNFXbrPM95880322xOXPzGGFbLFbFjitx7t41R7MW2c7ud+9/FpqLnM5lMxO3P8hajMsZw7cYNjo+PW6B8EThUUaEgEkZ3qQddbCpea1VVzGYzer1e64nuisNFQxg3gy6+U9c1Wimqco1JUm7cuMGVw0NZYEqRpCl13VDbJe+9915L04hhVzddvmuo4t+7XqNkkTdeQp7nvPLKK1stseK9N43UJkbNKoDpdNred9M03Lx5hWtXr4d7lmcwnU65d+9eIH5WmGRTFxfvv1sn1+v1RB5FS3/Cj3/84+0c3/W8tEq2nnX8Wxcnm823NcB2OVKyXFx7vfE18driZ0siIWmvtYt97V7Dhx0/dSP1ow7vHgfdIArdSdYOb1tDtrsztIZKPdkz6h4hxH4szOuGoNYK5UHtkNO6QH1d12R5RpIY1muL057GVoCn1y9YrUQx83M//1neeedNprPzQEgFG3bhxXIWtHgU63LZAs6Xl5e8/fbbfP3r3+CZZ54W5YPGQtNti7W57shUFqP1eKlQxOXie2UyibEYDAas12tOTk4YD4dSmmQtaVCNPD09pSiKdneMygZKqVDvJ6D0arVqwfZYghONK9CWtsRduyiKrWdeliWj0ajVP4/GxBjTcsLyPCdLDHVgW88XcwlvlcKGspQkzVF2GyCPRrdLMdjymt2m1CiCxxGAjkbMOccPfvCDlvHfTbT0er0tr6bLTYtjlaUGrZOQ+ZTP/uCDu9RNSWISrBWtqMFgsDUfu4bAe48J9zAej9tuyE963vjt+d99/tZaLi8vWx2waGTi37sGOI4DsGXo43yIhit6krsY5m495ocdP5NGSjCijQqidBWu5S9KhWyrZK52w7v4fft7OWF7dBfn9mdu3gvbWI14UgJQ7noh3cGWReDk2pQny1JmswVVVXHjxnU+uPeA2WzGjetXeeb2UyyWMw6v7AENV64ecHx8hHMVWVZQVWUbeoxGI+7evUtd1xweHnB2doZtXAC4Rd/b2gZlusDo9jh82KG1pq4qbt28SZqmnJ+eURSFCOJlGUWvx8XFBVmv34Y33YUSeUxN0zAY9Frt842R32RDowGKOFT0oCLuFid0LGLuGqZ+v89gMGhZ6JFT5JXgQ94JTrlcLqlqSXOvq4Y8MbiQSo/PLRqXqNHebWCw67kAbdjWNK7l3q1Wq9Z7jBhL5ORFvlI3fI0G4/nnnyc1OTY8Hustx8fHvPPOO4xGQ5bLBVrDai3qnLtqCjF5Y4zI0Uxnl3z2s599rASle3gXS3U2c71rmB8+fEhVbjzW3ZBsE6ZJa7a4acS5EI1+Nwu5e44uaP5T4kn99R1KSZgjGkWOqqrxXij5TdPgbBz0J2crurjRbiy3u3C75Qzdv8dBTJKExBjKeqfL8E7op7WI2Skl9Wt9lbe94YRrYrh37y7vvf8uzz77DHt7YnzS1HDv3vvM5zP29w9wznJwIA04b9++zdnZWcsMj/fV2JrDKwdcnJyFi443Kl1vfSg3UgrYnaw7YW+cVMPRqF1c0fsZ9vsYvcnOrdfrx1L24/G4o60uRbhKqZYbFLGn+FnGGPb391sjFLGamPGLgHS/32+fqTGmpSnE9w2HQxSi75QVgjFdTi9JkrS956qusQ6U1a3B2yXuxmvqFjfDJkztgunCpVKPhZ/xXrsSNl0PIsrU1HXNzZs3JUREYRuHsO8r3nnnnfD8guJnYtBKdO0Hg0GbHYvhZRx/j+fg4ICDg4MtPKgLfWgtWu9dADz+Phqk4+NjknRTGN31ntq1omStaLN5bzcruium1+VVtfWgO47Ahx0/gZH66O7ZT3o87oIKOJfnBb/yK1/gK1/5CiboApXlmsY2OOtYreuWT+Wcw3pHY0U0zzlRHUhRraSm1gq8wtLxsgDlFd4F8ByNDiC09hrjNKr27B/sc7o8CyJwOU0jvKamEd6ItIWQSZWmBUotKEuLbeRvs9mUg8MJ88U5r732OkXeo98fsjcec3ZyxLvvvMt4PKG4chOnwNcK18B8sSIvUpb1mude/hgP7t8HrclMxmgwZDVd0TTnwox3NYrIWYklRFJ1H43SLpkv7vLSBitnuViFDJ1jOByB88xmC/q9noS8TrJ3/X4/7KIVRZFRlismk1EwMkngTG1KmbwXHfbVaokxSatv1O2zF1USoveRpClVXYEWfMkooTs4a+n3+uRZhm0sy8aR6wSTSEmKFNduAFtpgtpI5sxtqhCEfW1pmoqmUSGruK0j3iUyimGStudxrnZ5SxFDE8pA1sFoxGYKgbHHU089jTFp0NgH7TX37j1gvV6htaEsG5QyWAteCe9qtVp0II+I88jmsVqtePbZ59AqQYqchaLTavh7j20caNBKtR6Pd06krL0Y5Hq5FoFAvZPAUk5Ubr0PeLBDNdsKIt3ax13jEz3qJ4H3H+X4W+8W89He40mMVIb/43/8j/nUpz7J7/+732exkAYD3gvAWZey29d10xqpqq7aLEvV1ILZWGHpxjg5TRIJFdkYRac34ZvzkKSGpq5RJsjsliuef/453nn7bdbrMpR8rDAmFQMXDGvR66ONDsZOsmbCB6o5OJgwm894/fXXuXH9FkUv5fTkmLoSL8No+UxnFeW6YjabMtwbsqrmNK7m+OSI0XjErRsjDiYHvPGDN1gslngfyoZijWjApx5z9zuTouvmd3e9shRwfr1eB9WGgUi1OE+apJRNRWw8Gj2w6FXs7e2hteboSNjpUhYiypvR02gay2w2B3xLc4icHGttW0pjjOhyX86m5FlGnmX4DmHRWYttghEg7uqu1T/vknLxwvCOIHxZlsxmsyA0WLRhVNPo1kjFlH70BHw4R8xWRigi4ivRAxOPUYxyd2F2GdtvvvmWjDuefl9C46Pjo9YLE7xPvHIXjFSUwhFjsCk5sVYSDVeuXJGfmw32E72baNBkA5cjKjXIeCrOTs9EScGoQH6OXmbY6JRCeVH9cG57XnW5VPF93czej/LIPurxMxXutRYWsIGPY63is5/9LK+88gr/7t/9Pt/+zreD2mCFTwPW0cjgR1CxqkQRoK5qnHdY5yjXJSh5fbkucT6muz2Nl3bsaPGqQOEUWAwq0agkZV6vWS4XfOYzn+Eb3/gm6/WKosjFk1Lx+mXh9Qe9sJv7EJ6sqGtHWVaB07RmNp+izRDnPS+99BLTyykoKKuS8WiPxWKBUo7LizMeHN/nxq0bNNZydHzBF/+bX+W73/ke09lFGypZK7rREBo+hMM5jzKPK7bvutzee9KAucQOxUmScHp6ynq1ZjQasX9wgLuQBRC1zaNRiYYmcpHiOaMO+mw2k/BxOOTi4uKxSvloEC4vL9vModIbPGs2n2OUFg9MKZq6aTHJ6BkppdrzdkHxeI9disBoNNrSbYpHfE9XUjguMgntthd/DG/ieSMOFbs5b4xz0+JYs9lMeFNGc3Z22l5rr9drS3OiF1ZVpZRpBQMYQfxo9Oq65s7tO+2YPenZysYrG3UM5ZSOHjegpOzJGAOJxjq3FZbFcz4Gk3Qwp3i9u9m+rsHqJj9+kuOnbqR2d/f4pZVoXMtr5Cb/0T/6b/j0Zz7NH/3RH/Hw4QO8CfIYHrwX19U1FpsXOCu1e423oDZyuavVCjvcpJ2ttdTOUTlLHUokbDBgOguyGYFJfvToiF7R55d+6Zf41re+vaktUwHbMSKVcX5+HlLyCcvVHBBP5/LygqvXrlI3S07PjtjbH2KM4Znbtzk7P+PNN97iYN9yOZOW6cNRj7IpgYZ1KcqVCsV3v/sd3n//Luv1ol143nu00a3A/ZanJKP72Lj7nR3z4vKSPBU6wTB0ljk/PWM2m7FcLKnKEqd9m6mKEzl22T05OWE2m9HvD1sqA8BwOGQ6neKcYzgcyvmWK2Lb87h4p9Mpo9GoHb8yhG3Rwxj2JcuVpFnb0YSmgbqrnKBb4xM3vd2F3WXddxdjXTdbJTMRS4rvEZxOGkh0qxa6IHUEs5NEtZ/ZzZTFuSC1l1VrVCMGGJMIEdcqiiLwqOqW2R8NwXK5JEmSVhE0GuktLLUzDio0po3PXO6vpgqZXOccuM3fu8Z411PqGu74u+6xm4ns3tPuJvJhx0/dSMG2odJah9DMo5VhU4eWo7Xi2TvP8d/9kzt881vf5Ctf+wbz2RznPXVlQXl0Zmgqx2otIVSebkofYocTH4qPopveftmgcOAddd3QBLWDqhGd6UTBgwcP6Pf7fOELX+Bb3/pmAPQFd0jTMNnqBvAtaO6cJ0mC5K5SZFnCoimZL2dM51PyXsFnX32V5WLJuloxGoxANYyGA1bnC65fv8qiFPpCYjLmyynrcsF6vdwClvGK2laIcmQc0+1Cqx+HA+R5zmgw5Pj4mIP9/dYr6PV6zGYzHj16xGh/3E7+qqralkdRUSH+H4H209PTNnyKryuKIhQdbySMl8tlC5yDLORevx/aUW1KZKLHF3G2eN0RVI+hXjy6bOluBX78fdegG5NsYVkRwO+GKd5vuHMxGdCt7xPVUDGusc6w27I9z/NWsI+gydTt6xevcVNHuqkj7FIC4gZ7584d8iInknidc+04xK+2PMdLjWoXc1NKMqHr9RrlEeihA3x38aZ4dIH3rpcax637++73XQ9qNzP+446fKSPVxvABd+jC23G3iTH5L/z8L3LrhRf4zp//OW+8/gaLhXgVKIUuUoZj0eP2qwpXVWT9HouyhEDKTJJUarl6OX09aHfjOFEaaynDA1ut1qA8NbYtbi2Kgp//+Z/n7XfeoixF3bLoSWpehXT+YFiEkKdguZwzHPY5v7hg/8oe0+UFjZNw9M++9mc8/9zzXL1+jbfffJP9/Qnz+QxtDJPJmP6wz7CWBg8mMUwvL9tSiF5ecP9+1G3SW7tTl38TJ9wWQXULK9gQL+P//X6f/b096qrCO89iuaC01ZZWV/RI40SPIUjc5ZVSbdYpSRKOj4/DNYwA3+qcd1nTsQwmhj2xVKapBLDP8pzBYMDlxYUsQE9bnhIF87picvGe4zmjwYqvb8NLta0d3p2T3YWW59kWVhXPHz+zKHLqetMIVQVPPoZ8IDytfi9vF3c0aNHD2CxgtSX5HP8WGf2j0SgkbrbLXeL/XYPilYR7iTEkJhbGS1YvTaV3X2pEQjhihDGj2M2Kdg3Prkcp826743P3nrpZyZ8JI/Wj4tiua7gLsMUFo0P2o/NOlHJ4r4k70OHhIV/41S/w1DPP8MYbr7Ms16xi2rhpqOoavyxxtWiP584GILtsw4jaO9AerUQ1MUkMiUpIvGHQL2jqmv3BgNpaZrbGmI3XYBLNs8/e4fz8LEwwzXxet5SDLE0lTa6gbgTXOTk94vD6PlHQ3yvP8ckJZ2dn1FVJWhgc0m9tPp/z/Esf4+zilCbspnXVsHYK7Q29fo/LMzEqkq2h9U42Rsmjtp2pH/28nKdsylZHCsA1ssP3+z1RHVWu9Ri8F35U/HxRQpAatcFg0MoBx0XaVT0Qz7ZoJ2/Ur+r1BEju9XqCG3pP0uEuxdq3Lt5RlWVb7xfvPX7fxUK62FWcezGkiwupC4TvSvV2X5+GZxsXc+RGRS8n4jRAG35GQ9pm10LSIBrpGJbG9RA9IdgoqEbPc7FYcPPmzfYatEkeW1ddTlJ7v4hxaOK69J6LYOxDX7ktrGnjZW7oA92i8IiJ7m6G3U2hLQTvXFNXlufDjr/x7N7uhewarSdhUqioaOg3X8rjvUYpT1RISK0nzfvsD4YUSQYeiryg8Y6yrshVj+wgwaiNJvY84CdlADbLqkJZi68bmqrCKo32CTSW9boky9JQDhEBVRl4k5hgjGpGo2FIzVu0Ftf7+OSIq9euoQ1U1ZosNyglIdB8MUUnYJ2UQ6Qhe7VeL0m8ompK1vWa1ark/ffuYmmobIWznqa2ZFokOBbTGYnuhesSBYVuSNDO2QiQdsZ594hZonVZslwsMAHnyJKUw8NDWYjO4bXn/Py89QryXMpmIpBeFDlpmrc40za/aKO0GScvbADoGCLFer69g/12fuR5Dk7wMFvX1I1giAQPRkLITceaOO+6pMJopLqGKy6kmCmL1xLDxjhvNp7j9rhFTygC7fK5jytzdEtDWkzMbd4TwfXus+lmXncNcFEUHBwchBpEhX/CLtR1AIAggd2p5fSexXLZ4oWusShn2qx39Hx+lNcUv38SPhd/js8vesTd1zxpHj7p+Fv3pODJqfHuQAgQhfwfCIqxXkg8KdGWyq1nOV/w51/5Ov3REOugQfhRvSwnLwoaZDfOUsm8HI6HEN3eJME6S1muWa4WNGWFdkBjWU3nNIkoLzir0Sj6WT9MFmlZJRNcs16LV6WNsNKrsmrvR1LZKY3NmM0u6PcHlOWawbAnIKYSuVatNb1+nyTx6ECHyLOC+XxJmiehG5LofjsrYm9aG6qy6kzybfExMaxW+DCKrQn/xGcVWhVZ51rJlLVbBT6NNAz1RhoxxIYSxhjG43HrJV2/fqPtk9gFrvv9fotvyeR3W9cS1VXn8zlKKZFaBnpB2dJ7TxEziGXVGpLofUR8qHvOuFsrJUXau3PSmI0WWPRkYui3y/COc1Pes8GFuqB3BL6j6uYueNwtp2kXcidsjB5ZXCNy/WxdS/TQrl+/zmQyaekF1m1C9xhqdT0c5xxNVP+Ma01JVm+1WkmG3Dl8JTr9aZq2BntjfDeGrxvieu+3Nsdtg71tLLtG7G9APvij8hoe5+Js/zWqCWxerdqdz4e2O2B0qDz3Hq1CGQwK54PipgdNyjf/7E84uveQj//cJ0hyRWUrvE5RRrFczOnnPZzzpFmOVQbratarVesFoUTHO53s473DiKWBWyHjU9XUVSltzr3oQFXlGsoV3lm5TpsznZ7TVA1potgfDlCqZrWYk6cZSnnqyuOLATZNmVWWXtoDJ6qk5XrJ8aMH7O1NWK8amiajbhwmSfGlPMy8yKlcRWLSwKIWFVCthY6htUjY+q0x9+2Tk8Xh6RZTq6hjEyaUbWrRHlUwv7ygqRu0kdS4SVPmqwXWSxjb7/exTSPGxlo0kKQpvSzFu4bLqdTQee957rnnaOoK7yxaQdEruLi4pOj1ttL4h4eH3L37vjxnZ5nPK2J7qF5R0DRSktIfjJjNZlS1qIx2w7q4MLsGJ4ZvWuuW49Tr9drFH2VUxuMxSiVE4bqyXLfen7Qrb9oyrXjO3WhBFrXU3nWzgniZ2866QCyW8Y7XGxd2NAoR60vSpN2wPYKbOe+Z7E1QWlHVNcZIe7Ouge5SMaJhSLShccHzcQ5tDEePHlHbTXdp7aXMZtfj6dIbdoHxaEDjvUQoJR7dbOpu5vmjHP/FRmo7Ft38fjeM634fiZUA2oSHKN4nzjtWyxVnp6c888wzrfpBfJBahUmN4u4HD/jTr/wZSWpQ3lMuFvR6efBELIlWGAvWQoKUpeg0odaK1XoBqYRBJZpGZ9Rhp7GA04raWcwgpzKe/dENcm2Ee2XFODVVxWI+o65K+nsj7r7/Pk25YrEoGY0HDPo9lNJcnJ1hjKJX9JnPawbFUOgRTRPqyRQEcfvBaI+TkxOKokeaJ1SB2dtUDanJAn5hURqKfs78rGwZ49ZJwXV8VnFX9SFi9mHMIylSyYOSv3lHuV5i64aDvTF7wzFlWXJ6cY51DU3taNwGp7l//wPSwDeqyrUQUasKX0u34DTQCyaTCevVAoVjOOixXC4pciF5lusKpWmVT09PTwG4ceM6aZZwcT6lqS21qlkuVoxHI9Iko3GOxnmyvKC2omzZ7/db0L27MKOhiGFeF5T2Xigpi8Wi/TmKxRElqvGsVhslV8HiNt5DDNN2YY2mqfF1tXUdQLsJd4H2Lvgew+hIkvU40ky8GqU1jW0YjUfSuaddNxEW2S547xoXpYS0mYSxaYKRnc3nmCQJihGb7tdd6kU8YvF01xjuhnTdRMMurtUNAX9UlPWk46813Ns1VB/+2sfTlFprRuMR+3t7W8zhqDOttW4r6n//3/0bpotLRsMBDkeSJayrNdZWDIY9HB5cTdNYqtpijPCBnLOUZU0UTEudhmVJkaU4NBjNuqrAJCQqJXEViRM5WoPFZPKwmiSlZwwCjNcYpXjtO9/lYP+Qo+Njkqcynn76aQaToXCabMmsmpGmCdJkMmmLM0EyW6PRqMVvIuclAs+xEDYCtHdu3+FczXhvLoJzRidUTU23k0fMWrU7Ok/2cGMIUK7XjA4O20U4Go3QiSErCmH0V1XgpXnKlWQcrwa2c9PYVowvkkF7vV4LiMcdVkIzCbUTLUJyzqkW+ymKgtV6Kd2bl2vyIqNQOY2tOTp+1Ga7sjxFNbIoIhGym9GKOFc3sxTnE0jYmuc5h4eH7dg451o5mchQ72a6ouKoNJMYtQ0ouppRxhhM5zPjwu5eTxdY74ZDEYiOzz16iPFZWmu5devWllifc9uS3E9aa/Hohrbn5+dtK7RoXKL31fXm4tyJAHg3+RDnWRzzroHaNdzx526W76Mcf82YVNi1+dG0d2G/bqd0d6vPjTFotjtKxCxIzLJ85Stf4cGDe5TV8v/f3n81W7ZkV5rY52LpLY+KiCsSNzPRSVRXdVdbkcZHmpEvtPqjNPIHtBmfWGYUzeoGYIWuYhWYApl5Ragjt1h7SRd88OXr7Ii8QAYyE2w8XDcLi4gjt3CfPueYY4xJbjRZnjDaNnCSkmc/aSmCQf44hhd5GCx1Xc8SjnEcwVkqrUmEoO8HhFYoF4Sepu/Zak3fDchUUSYFSks8jl5IdBrwB+kdl9sNo7Hc3j9weXWF8Y5XX34BOA71jq4/cfnqktu3b9BScjgcsDZY0G6moBw7LeEmey5hDofDB+BrxI6CNOeZyXse+MPffi67Pk7ZP3hf/DNxbxxH2jr4RCmteNrtWF9csFgG25btehM2sbV0bcvj4xOb9TqUy1qjpGKz2cxdwhigIs5lrWU04+QHFkiUWRbcHphwsbZp0EmgEywWiymDcTw+hpmAcSKzMYZ6op9Ek/94uGPJd35g4msU99Y5xhLLlohfnQupPw4s0QL43C0gvsaB/f9hy/48W4qP5xzU/7jUixhdPKIxy7q4uJj3bvz4lPB9/4n8nkZVfMz39/dzZzE+znO31fMzGs/heafu/OvOA+n5czpf51/7qaA5/C/AkxJCIoX/YIN8nJYqqWayXvyac+2SUop/+2//Lf+H//3/joeHe+7v72namk22DVM2Tkf0JJ3p+hbhAwaxXq8np8d8mtSryDMJ1uDHHi08vTMkQmFMwJ50mmDHAYzFj5BUEjsMeAkJDm8sox1ReEw3cHl1zXffvSY7nfjZF1+GzSQFeVVQ9wdkKnnz7g1fvPwMgKurq5kUuVwuz7pSiuB3zTyLcLvdUtf1zGF68/o1x3333PJ2cVjFOWYQfaX+4SAVS+rZZXKiGRRFyf3uiaZpEDK8T4tFYMoPWUaTJDSnJtgcE0pK6+xcQjVNQ1VVbLfB1SFu3mH0M8AcA2NZlhwOe3a7HUKI6Wc47u7ek6YZYpI1hdH1lro+kE1dvXOr4hh04or7KO6v+BrHvXeePZxfls9j082c5cVLNdIBIs3i4+DnzkiU50HyvNSJWU382fF7zz2djDGh5EsSTqcTP/nJTz7IeiLeFfSCvyt1iv8/z+Tiebq/v/8AbI+vxTP14UNrlY8xqvPvO28yfNi8+dCp87w0/NT1Tz7S6pytGp+QmYYexCcV+S/PaWbAnOZbd0qBz9+YNE3RylNVX/LVV38WDqh37A87Xr/+jvv7e3a7HXhJVZXkeTHZ1makqSVNsrk7ZawjzRKs92RVTtt1oCWrcs3xeCRJU6rlAt95EinxCHaHHVmRo31gk+dFzvvXr5FCcH11zeFw4Onhgbo+sFwtWC8qzLjg7u4teZry+vXr+TWJzycerOB2mXFxETpo8SBEomI8VOc4obUWqdQsMP2+cjoe3nNcJijzMyQCa6fDNZWHWZbh8VxdXnI41R8IhYuioJum7uR5Fi4WIUjOulOn0wnvg2zmfCyUEIK+C4TZZ+wnDEjtupblcknfdxTTePmQtQwzbWG/35OmgVD5WbXAezu7KsRAe56dnOvnzikA5+VYfE0+HhQQvz7+jPOMKUIP8cBFSxqtNXyEVcWfc94NjFlyzE7iOYmPRwiBkGAmeojWYaJzfNwxowlj3Z7JkeeZ3Xzu4IPgZq3l4eFhDuDnFIcYyM67ivH/5yXqOfUg4lnnz+8cwol7758UOP996VkEGT8G2J9fyGjDO4l8J1fFODyxaRqEEIEcKEQwL/ue6H3+ONIsI0wUDl0uKSVX1y+5vAqWrE3TUO92PNzdstvt6doDfdcg5fOGLQpNkkmMC6zxJE1JyoJg4+EpFhVah/Hj1o9IfJgLuFzihedpX3NxsaVtO8RoOT7t+fzLH2H6ETuM7O8fybVEWUlqLU9v3uKNmQmBEbyt63oua4J1ScA+Inlxs9nMJUwMat55dKJnGQZewEcShundmd+j7wMtw6aFJNFkZQnW0TVtEPtmKYf6iNQaMY37vr+/D7jEtCG11rRNS1mUoQuaJLPOzPtgXxIHSkSuUjIF5XgAo0zmfPKOx7NcrMiylPfv35+Zzhn0xFM7HPYoPekNF4sPfsf5IYqHMQaA870Uy5+IV51Op3lKc5ZlFEUx/+7zIPdxuRalK9570imoRRZ+LD3h2RU0EkZjgDz3rZoDzMQR7LqOm5ub55Fvc1MkgOaxm3j+8Y/3gZqyw9ikOPfEimc17pOPL7b4mOLP/DgzjI//vDo6F19/XEL+L1jufUgahA+7Dd6HjZckyXzo4pOMpmDWWoo8J0ufJ4p8XzYmRJB9gJzMwZ79dcapC7hcZFystnz1ox/TtsHn+q/+6i9JEk1VFTgvGMYWBKhEk+fF8yRgIemHjuViQZYGhf5QBI3ZqW0wY/AWuliteXl1zdfffE0mA53h/dt3/NkXXyIFbIqSX/3H/8SPv/ocgWGjU8aioGkDSzrKR6KI9vkmD8EgkiW11jRNQ1mW8+2dpRlpYqn9aS4NzomEH7zuZ6/fx0CqEIGvlaYZidZ0Q0NVhoBz2O/pzUgiABdu8/1+HxocU9mX6ITa1ggBh8MeodVc7kXMzblnp4NxHHF+GrIqohd7SlVVYdAlzOLj81LIGDNnK/FnCiFm/CYCuvFwnFMQzs38YoYVs67I5o5lVpzvd84A/7hc/Dg7iE6kcX+2bTtjZHHwQnQxEELMUpNzJve51Oi5/BKoSScZoYGPD7t3DuOfk4GPy7xwMpkvFQhTYc6zwPhcY7YUM67z7Ov8530cuM4DdsxI4+P5uGkTv/ZT1580SH38ez9OCWHytlHPDojx86vVCggdrvp0ou+Cv3VM68/BvemnwzT8Mbx4gWrgnECp9JnaYIPHd5aWfPXVT/jVr36FdaG1a8zUzheSTX5Btap4fAgSlzLPqZKSoe/p+xapFV4KBmcmrk/Y3DjH/e0tizxHmEAuFUpx3B/4r3/2M65XG9rFmne//pq/+NmPKT77nOG71zzWAceZGwVS0rbtfGNnWUrbdnM3L2YQkbHdNA1a6flgPUsQvk8P9bu36sfApjVh2KSLY9CrBZW1dGPAeraXl+wPB4ZhoKlPwZJlwpsEYsKJCN5TSn4QIOLzihdRlmW0MbBM2KHWiuPxePaIQ7s/z7Mp6wiY1eXlBd57+qHnVJ9QSuIHM5fC5/SD80MYH0/MRmPgiHszll9x38bHHjVzH4PsMcBEW5aIVQXWfY41ZnbiPM8svPdzdhx/x8dlYQwA5/KZqqqoqup38K3w9R78c4b34Tl5PpxuesxxAvX5XojPLSYK56Xa+R79PiwplszxtTuHaM6/J/6O+O9PDVSfHKSeI+Gnfscz+/T8Qbk40GD6GufcXC8LBHmWkaUpZjD0Xc8oR9KJJwJ8MAzU2slzSIhJ+iEJ/fEpWEmFwOKd5fHhif/L//n/xPXNhlevbnjz5lsQUFUF42Ax/UCLYJzEwn3Xk6cZ1gUJQtu2ZGXJarlGCI8bDc6a8DysIy9yhPfgwDrP/e09r8uKdVHw2csX/Ppwzy9+/nM+++yaY30kSzOaU4OzDq3DGxzr+r7rWW82FEXObrejKPLgrCCgbTvMaJHSM47TAVR6loh8WBI/82c+XuebJF4WzjvafiRVmnYKQNZ73t/fPt/4zlEWBel6Tde28aWfW9pZkjC0ATwfhmE2/ou2KzpJgl/RGYM6zvaz1sIUSKqy5PJiO8EAksvLLcHrO+ynRGtWk53Mvm6xPkyDE4BQCjt1NMV8UMJntQ7DWZMknbMb70ODIfL34kEKbX6PtWGgRcBmIEmDeZ/zJjDx00BD0TpQLNquRUmBdYaizKeAOSK8xxO+L89DdjyeYTfnflFyJqcGEudmvX7OZGLmIhVOugkamVr7zoMMxOdzbFLwLD3qupaubVEy+JULgv4xlrzn7PHfPf8TrDOJmqUQYYKS9/MUbYFASYlUcjIK8MFGaep62rPO5qesT1P4AcE+OE4eiWQ3Pvjz8fr49p5fMB+eiJy8oKaye+KUB2ZsmeckauryGRtsTuP3IIKOS0q0CpNVvAArwuFAiJBWGYsm5e9+/mv+41//DdtlRSYcw+mJ4bSn1ALtHN6OGAaavsYpi0+hNg2NGFDLDFdoTCqRVlLoEj8IUl2wWqxxzrM/HPn2u9e8v70n8TlKZOSLJe8f7/nlb37JalXxr//Nv+bt4Z7/9O5rqsstfRfY48EPS2BHR5pktKcOrRLwnjzT5FnC0HXgPVomjL0hURnOCBKZkegwUFIKNZM0n98vDzyLQc///hDTmPgz1nI8HudyKnCdFOv1GmMsOEeZJHSnmu5UsygLyjyfhOBhf3gB1nus8wip8EKCDNOYh9HQDyMIiUrDROi4cdq2DRtyKl/sMNIcjkjnyHXKsqhQXiKdQDqJGxzSSYq0QuqEwVikTvFC4oVidB4nBKiEwQb3TqUCMbhpWpqmpa5PTHx8jLF4oTBeoJIM6zxt3zGaAYFDSUeSCK6uVlQLzWKZkiQez4jHIKQPWkwJeIdnJEkFCEPb1Yymx9gBj8XYgaarp0GywYE02AQ5+mGYGgpgnWUcRsq84OryilQnSMR04EOTAzcFLRE46UKErCqo+cIfKUApQZZolIC2rmlPNcI7vDF4a9BSkCiJPeOEnZePMfMUIpw9bw3COZQAJQBnEc5N5YwlURItRPictTgzogThd9rwO535E8tiPsYx/jHr+8Cy7wPR5s8LAUKS5jmRNwMCR+j8RezLWxci9XRjemfRSqBxvL99x//93/07FsWKX/7i5ySpYLutUGnKcnPBTxdLur6nPjX0xtLWTWgBe0+eZuRpGgz0mgbjPZmQyMQwmh6EoRs6dseOfhhYrpfIcaS6voB3e5x1jKPg4uaC12/e8O+Hnv/uX/9LvvjyK/7uzTf87Ec/5b/87c+Dm6W1eAw6EXTdM+YkRYl3krJc8HD/SFWm4AWJTmibYFFblgvawzjjGH/IexNXLBsuLy5Cp28c2e12eALwfXd7y2a7oZhEt33f8/DwQF3Xc/NjvvnPMIq4uSN9JJb5SSQE+mfW9DiOZGmCn0DYcRxJ0iRgY4cDFxeXpGlG8GMPfubOWso0ZZFn2K6dzQ6lDJlRkmVo52m6I8RyzVqkkiQ6OG1YGzhptg+Z7bFvkQJ0ouepKM45lIa3bx5CwCbQRMw4jTjPxeS8qien0jCKCgHOTFbALmASfd8wmpHFomSxUGj1PJpqxnbEM5YWnSHOu3fnhMjzjPjjDHluGvBMln18fPzAtyrP83kmYMzu4JkTdQ7mO+ewZkTLZznPx+c6Vj3xe8+xqfPHd85D+4fWPypIfQzK/b718YM///ucO/F9fyOfCYZ8MGY93BwegU6yyQbYI7zl4f6O+/fvaPZ7yjSl0LB/eMvVdsFiXfLi1Q1CeVDhjnn/5h0OgUqLueTUzgWMQwXrijJPwVnMMNL1T7RdR9t3VOt1GOqpNU5Ahmfz4orrNzu8FCRlRlFmbIsvqR/u+b/9u/8HskoYDHzzzXe8evWSh4cHttsNWZZyfX01W85ut1seH3e07Yk8z2DSDCZJHrImGUDnyN6OHadzC40/ZBVlgZ6yVYsIfuHeUywr+mHAWcvgwnSYCFzH6cRx81lrQzYEfIwjnks/VDJxamzABEMG4Cc9YBhrYa1FGDEPh0jTbMZ5xtHw4uYFo7GURUqeKIa+5enh4SzbsFRFiZISX6RIHSgDXdvNU2+89/NUGmtGVstlCEITqN71PcvVmvV6zfF4QooE3LO9sXNBMzmOQT83jnYa1BBmL4bOcE47nBgGg5SxCwanU+igholIdgbaI24Uu4plWX4wzv0coI5n6e8FzONrP2kshRA8Pj7On4+qgLZt56AUg8t5w+AcW9YTSfrcLSJeTPDsCPExkP9x0+ZPTkGIP/QfG6jOv+7874+/9+OvcWdPIFL+pfoQMAzuAQopHG/ffMv/9O//B7rjkc9vrrjf7Tk+PaJUwmgGlCxJEsXgTJgikxeIJEMRZAVaaczQ4ceBdVkijcGNIxiD8A5tDXLoSa1luVxQVCUOxzD26CSlblvyJOO/+2/+goenJ+qxI9EJF9sFF0XJz3/xc5zxXF6/4s3br1kuSzabJevNhrquOdY7drsd/+pf/SuOx5r7+1vGQYGXZFk5m6adTg1JkqLUs4Ti/D35Y1bonlUoKckXQcP2/v6Oduh4+eIFQgqyKRuKwy/j44ods9PphOfZFiWqBCLYHMmiM3vePk9ZFmcga9P3ZHnCcrVkHIIU4+npiaqqZmJvxOHKVUFaplSrkhevrsE5EqXBOdpTw5s3b/jt3/02iHV5Zl3HTltxseby8pKx60i0AhHwHmM9WZohlaY5dSRZyjgYqqIIAXsMJorWjlgRXV4HVsvgCiGFCKWi1lCkZDpQEZgyX0ePNTJMuh5HBvn8PqZJAj4QWONw0HNOUwxmH2dPMcN65tIx41hMgSX454fvqes6DH+dfqadSL3nMpePuU9CBK4jPDufnmfz8NwRjY/7vDEAz4D8p6w/qrt3/qDgQ37F/OLwuwznjwPUx4xU5xxCPXNZzm8NMQGCxhj+/f/w/+bt23e0bc3Dwx1jW5NKgegbLpcLikQzjD3eDGSpou07vNZIldAPliTJGYcBMxiQFm8d19tLLhYVd6+/Q44GKQXLssAOgkIIhFSBizRadrsj2WKBNSOVV5SXN0hj+ezmkn17wiNY5iWm61Fa8je/+C8c3t8yTjyfYbD85je/ZrFYsN8fePXqFcvlkl/84hd0XY8SFafTicViwTgOLBaL2bsp3OS/y1f5+DU+f63PL5fvC2yC4MqopZpxqZubG7yAcrmkPh5m7dq5gdv54AEhJXa0rNfruc1+bn378YGK5Vcs69MkYej7GY/pp4wtSRLqupmtULTWjMOATBNefH7D+tUl+92OutmjRMA0h74jK1P+/L/5Cy5eXc8yFgiHy1hLOWn+iiJDqwAIj2MI1l0/ZaoGRtPjT+H3D22Nx9H1XRg1JTyXVxcc6z3D0HM83jIMfsqEgnhaRRLyRDTtuw7voVosMOMI/plwKWVwIt2s1wip5pl70UL5vLT/3U7fs13PuRTIOYdwfrZ4jgHu3JZ5DoDfE0A+OMtSzljix78D+CCz+r6MKq5zG5x/aP3BZM7fh1F9XCd//L3nDz6KFs+JcmKyOfXe461HS4WdLFl/85tf87d/+7e4wbIsUvwouVwvkeuK/cM9izIn1Qmdc9gx2I9kSYpAAhKtUk77HWPbYoeRZVEwdB1FliKt4eH9e8o8I69KTNeilSbJJYzhVgye54JNmqPQdMOImFr/wlu6vmGRJeg0xQ49mI6rixX/8i9+xl//4j+jlOR4rBEIvvrqxyyqBY/LR7768Vf84ue/QKuENM0wQ7w9Q+fo1By52F7QdeHmk8J98Bqfg+N/3/sSP/7xRYIQjOPAqBRFmrHf7bm4uMBLwfu7W1QaunJlms4e4XF4Qgw2Wmvs6YRSmrquZ13YeUt95sbBxG4XGGuR4pnpnCQJcnqcciJEhkk0A8fjEaX0hKUUaCUZvcMJEInm4uWLMLhgGBkPgt45hqElLQsSn00l6jD9foNMNUrJMIjDhVItzzN0lrIqS7yU09Shgcf9I11TU5UpwzhgjUEqQZJqDod7pBJkWeggVouE9+/ecazrYIsiFTrRM4Wk73rSdMGiWk7lpmPn/TzO6uXLl5hxYLXZznKZ80v74/fyfA/E/3/89YlW3N7ezu/HOdcpBrVEqqlT/szXil/77IcVunTnF+N5EAU+CFDn67yr93GS8/etPziT+rjk+5iw9ffe1t8TsD7GLPCQKAUu3GpCCL7+9rdorbm/v+f169dslys2VcFhv6fQGw5HwcP9HUPXMXQDD3XL0LZYM9Jbw9CPbDY5XmtA8Hh7T65Cl8m0J8bjkcF5xjJjUZTgBE56BufomyYA9KMjTYPndFUUQJB+JB6w4U087p8gEVgzYNoTiZQoZ8ikI9WW68sF6JSrq5uZGPntt6959eoVbdPz/v0dq9UKrVu6pg83OJZqUTIMHYtVwf2jRQhLkkmk/FAb9X3AKd+jkD//WiFCQa21RknJ/nBAiPA8H54en7EJH0i3q9VqdjeIgPfMtdEB1YolYcTM4uOZS4gPLrHnx2MnmY6dMmk7cZQCjiOnwNdPoHLD9csXHB52DE1PnuQ448BLhtFgnEenGWmaoDqLnuCCYjpsSin2+wNCBya2Kkv6aT8e9ntSneC9I8kUq9WWP/vyM4ahw5pu3ter1RKd6NCllbFMshhjefXyJVIEj/z6VM9Z6DiO3Fxfk+oqcOH6bg4CZiqNE60Yh4CHxYw0Wjb/Q5f+eVkV/x/LPSHEBwB5bGycB7ioF/04gJyTV5175jzNOOT3BJ+POZLx95yTuD9l/cnInB9nVh/f5r+vFIkPvus6FmWJ6w0e+L/+9/89Qkj+5b/8l1g3oIVks1zSNA2//O0vUUpx/fKGgx3RSpJoRZpmNH3N/eMTWsDoLE9PO4r1BeUyZ+h7tPMs8gTTnEhwlKsF+/2O3e17dohn/oqAsihZrdfotOIwjlwvl0il6U4nRjuS6QQlBUPvuVou6b2hcQO9GTDOYsaBp3pPuS753/6v/xXfvt/xi19+zf39PdfX1/TdwGZzwX/4D/+BvhtQ24Q0ychyR9OesG7k6uqSrlN4P+D8SJolFGWC9+33vtkf3qa/+379zkYncHPyPEcVkqENco5T07BYLWma0DlLpwEAUspZ3qFUIGJqHcbRD2f7O0pCojwkfizPMsYJk4rcJ3i+kQUe78I8xXJivyuVzEzw+/uHMMzSONyhxx17ZJKQFjmmGSiSgnSdMVpD1/dIIVFJhpr2h1aKLM9YrDdTsNrjUh0gAWPxSgUhuTFcX1xTZhneOk51O81IDNY0u6cjUmryLEcnQT6VpClJosiSMNprvXpWTMwaQhtM5+KcQjOOWOcYx4G2bdms17x//567h0f+j5st2+32gxLqPIP5+ML5uMyav8YzXyxCfOhnFfeEJSg5Pg4i52x4KQicwLOzH3G+yLWKnbvznxM/dm5Z8ynrDw5S33djS3FGmJpIYt+jOT773olK4D3jaPjVr37JX/3VX/Hy+ob+UHP7/j2r1Yp/82/+Df0ptG3fvXvH/cM9Q9+zTCyJUvTNCS0g02EycdN2k52qwLgwsLI+njgeDkilGIae/cMDhVtTKoGaxnlvVyu26zUeUEkwVxuM4Xg68XCs8blDAsf3bxHWgjGkUlClKalSeGvJPSRSUugU5UMrv3cjF+sleltxezzwcPdAU3dkScHYW7YX15jR8fS4D0B5krPdSPIs4Cpd11AUr5DSsj88IYSjKJJphNaHKfn5Tfv7bqrzjR2Imp6Hx0e8dSiC33ncxMMwgHcstluklDOfCp5tdCKYbY0j0clkwhe8jpRS5FmOVHL2YzrHMLQK3TQbjeII3Lf1as2Qj5NwN50ztCC4zhj7Hn9S2GNHaw4kRc5ys+bYPpGVJeVqQYIkSwNzfZgmARlrabpAISmKgmq5wiSaZLHADgPL9QrbthweHwL3SYIdx+BWKhLGwQRKEGBMz+kw4L2Ypml70hSqRWDjSyXDSPipcZCmGQJI0uBz76eD74VnWZX82Zdf8ud//uecTjX/6W9/wW63mxwpipnwGhrdfi7NpAwTluL5s1NTQU2DYqWQ+EmpEC+WZ5XC8+xBKSReTJiWkDM9xBqL8wEbTJTCu+dhoLODhJKBv+WCrXbYY+Fhxvc57tHzr/l965OD1LlOKW7wc9AMIHDzAqHPC4ET4YWTXiAcaKEw3mGmAJboDCUUzjiG4cR//pv/zPFxh20arpY5n19VLIqc3/7Hv2T3+MToRkYcq+2apPAkIsEZw/GwR2pNmkgkjub4RKoTtHQ4NzLaIw+3v0GpFrob+rplKz0L40itZDCGJAscKescoxkxgw0WK1lKNvn3dDZs0vq4xztHVeQoAZaewQNKcDuMGPOsZ5JokuqKsetwJ4V/SrnhmsfuQGN7ZCq5vLxkV+9QyqG9YZ16Xrz6nK9/+wZTluxOB4QdkcqBNOSlRmpHmv1u1/S8C/QxTnHetTnvxoQNEwz/ZJoH8p8M3u3FcoGzhjKbujhK0nQtj7snvA8Sj27okVqRZCkOTy4SYokpnMB4AxbsaJFIEpnghi5wojzICXOpD3vW63XQSZogP3p4eJxF130/kKYJQngWi4LTqUHIkrZtUFjuv/0tp90TP/vpT7i+uEQOBnls2JYlo2xJ0hSL59T3jAiSRYWWAiM8gxnoBg9eUKWaVHju9g/U+wdGO5Av1lTrC9ylh6amShK6vsc7gbSWrg8UDbwmkRLhHC2B1jCeenSnGLoeiaDIw/BaM47oNKEbBrIix3vI0oS82vDb335HphJeXF7jhoHXX3890yIWVTVnNkopRmvwwgeyp9Jh7yuNt2HisjU26CubHjNYhA+ThaaR3cjJf80B0ntwnkwn82ix2KHVSqOlmjJcN/9R+jnYKPWsnxyHYRpGGpIRpRRaPNu5zBSjP1WQiuu8TDhPNaUMT9gLIHJd/cSX8aDFJBZVEufCbfOXf/0/cjqe8Nax3z3x2atXfPbymqFryAhmdKnS/PoXP2ccRxbLiixJsGakHToMGYtFGKwQ/K8tOklp+x4tFRcXlxwe3rPNF/Rm5OHdLfuHJ9I04/MXL2kxOJVgnEe4qRUug1LeOItQin4Y2B8OgEeLSa5RrYI/tQisd7wNYKKzrLKS0VjU1H3y3mP6AYzjdDzx21/+ite39zzWNYuLNcMokAoe3t6S5ymmDanw3/3614wdLFdrjPC0/UCSa6KXdZYFgPX7MIo/5D0VIg5/SGnbE1VZzh+XSs6KeSnlrBeMYHl0LmjbFiHELBIWIrzX3gdX1DRNpiADxj5nfX3fU5ZhyMWz2RsonXxgnaLOKCjx/0EmJamPR37ykx/juldcrJYha6iPOA9NfSJJJE0QSYHWqCxjHA+IRFPfP9Fbgyo3dP3AyfdI03J4vEUnEt91WJ3R64br7Yb7oaVtGgKhtmK9WpMX5ZxZDuPIqT2FQz2J350xDF0fOpaTd3pzagJ5uMpwk3+5yjJ+8+ZblIdEKqwxXF9fs16v0Vrz5vXr0BWsynnuXprnIVxMNj3B3lqy3WzJJxfXqqyoT0eMHUC4eXCDnLV04TVNtJ5sXwzjGPdVGA4SsiI7BZfnkvAcBzvHn3SipxJQzMHueejpp3X24I9gnH8fcI6IlV0csRMImN55HBI1aYSEFvz1//iX/Of/z99SFQu22y0//eorttsVp3rP+zc1x+OBqsj59vWb+cbQOgkWtn2PmhwHsjynHweUCF5G3RDm7F1uL8B5Vss1yjtunx6wHhyC65cvcIlmf2pwbU0iNalUE4eFgEcpCdajtGK1XqGlpPChVPSDQUwtYykd3gbyYZZkCJEyCoMZLGM7zZrrR9rjgbdv33Ha71DKUlQKIQeUVghvkMIHUfHhSNv2GOvRaYE1PQjFMBiyssAajxAJico47OvfeR/+MXyp85LdTnwlqcRMbgxt/o48y1BKkkxYQ+iwqRl0jcGmruupdMvmPRIpCMAHJUDEZqLLQ5w2E0W6Eaj17pksGDP2+HWLxQIhJVpp7u7vSRUs8yx0w6Rkvc0DT24wmDrYr6R5wWJd4GykGwxI50Em3N89cHh6IJGWi1XJn11dY9yISDLSsgzuFwJc01FpTbVcctgfeTg1bLYX9MNINpW0Ok9ZLldYZxE+DKnITJgFWU0ZhNgfEFLMZXKapFys13THE7ev39KNhj//8Y9ZVssAtt+84OrqGu/DaxlHrQkZxGJpFljpp/o4SZz2vDnsqcqCzWbD3d0DfdeHsixCA9O5jfshct6CMLz5ICt/9n8LTYKYnHwswj73zfqYOnE+5uxT1x8UpOIT+p1/+9C+jIEKYBwG8iSlPTUMTcvd7Rt+/etfApL/zb/+b1Fi6jJ0DY93LU+7B+rDDmUMbx/f0DUtcgI5jTEIFYJeojRd15MVBo/ACRisZbO9oD7WrC8vcaPh6IKjQHP/nr4b+YuvviKbBMNJmkCS0DcN+92OYWIC53lOUZYYa4LhXVWFm/54CoDu9Pwin8X7AHh6JLYbQvBynkVecmxOfPvtN7x++5ZjU3Pz4oaffnHN6mbLN6+/47vb9zw93pIlikGpMLbJOrKs4O52h8oShtHiB0Pfj+AVWqSMvcdb9wdnUh+XgUpJBOEWTibGsx0HtJIURc6pPqBkMYtgI0vZez8bvT07OQQbmeA5BYhgDChlACilFODja+dnKCHesBEjadsg1D0ej1hrWa1WM2cuynD6rqNarcjLjH7osUNDUx+QPgivs7xE65RKKT57+RLjgj4uMOI91hq8cXRth+k7rrKEz16+pMg1Sgu8hMGH/V+UBcZa1mkW9nnTclGVjNbhug7loTseOLUtrkiww0A/DoCgqEqsdzgCObNtG3SesJ0wPutcuPikQGtJlqeMzvFw/8D7N+/pup53b9/PHKdw2GXAt6RCZzlKeBaLkqurq5C9Ss/d7Wu67sjx+MTbt08cjweyPMMT+UyhGxqPrJ8GgiCC4FxOmJrgzFnCgRLPcxPhQ87TOYk0Bq1otXOe4PzJeVLft8nP/56j8sRY9S5sRi0kx92Ov/2P/4nmeAQ3MNZHNpsLHt++Zb8/Tk/GM4wBJO6aE4skw7lgYRH8h0KKmasM4Vxgg8uCLMvxSnJoTjRtR9P3nLqWN+/eYcaRQ1fTdC3bm2v+25/8BGkdpu+5WV/ghhEtJK1OGVfruXx5eHjAex8shgnt6N3TE2I05FkWhiw6i7OOnMmaw6vAfvcu2Oxaw8PuiV/83S952D1SrhZ8/nJLVuR0Y8Pdr97x/v6exXrD7vEBIRW2HyizHCUkTdsF5byStE1Dkq3omx4sCCvo6hYtk9/7Hv19XdffWVOZsFivaduGoWuB8Br0XRv8s4ow7WWz2cwZT0z340ioYG88MJrwnj1/jQjSDPfsHxb9pbz3c8CKlIUYhLI0lHzR7iXanMThmN988w3H0zEQKw87qixhXZVkSYrH03Yt3jUYqXk6HUDKQJOQAZyXHprjkfvbO1brFZfrimwccGNwZ3UCdJbRtT1M5nrbsgrgs07wQrA7HHASTm2HHQyvrq+QWRomaCdZ6PpphdAKYwMU4KVCCM1CB86VFgJnLEpY3r99j+9HCqmoD0fyPMw5bJpmtpk5Tb7uIfuXqDQDZ3n16gYlBXmeUHc133z7NUJ4Xr54MQd4Y0y4oEWQy8TBGsJPZ3nWyAYw/NyW5twLP1IQYgD6WLQeAfrzvXdOXYgE39+3/lFkzvMHcJ7Ox8PtjAuiT+cQOJrTieZ45Jd/+194ePee/cMD66og0fDmt79hHN1kNyLIi4zRdAx9O3mIB47KaC3WW5TQ8+ThoR/I8oR8sQAhgp6uC37k3W6g6Xu+fv1d0G1dLqmuNqRJSg+s0gzageZxR+oFUmsyJbAqqO8XiwXjMKCEnMsUkQdWcmd7Hvd7uq4jL8K4qrv6OOsHdaJZyBQh4O37t7x+95ZyUfKTf/FfUa2q4GypBUpY6rpgu96g05z98cjhUPPQPGG85+nuASkUSkCZJ2xXC8xoODYNgoCDlXlBkabg+xmojLfW30fx+PjjH3RnXejOjsOAd471esXQd5RlwdPDPUpI2uZEmldzKzm2s2MmFC2hF4sFbdvQ99GMLmrAnoH8aElyLquIJWbc7EnyPG14u93inON4PD6PFpfB4lgnmvpU86PPXqB8IIj2Y0+igs5Rpxn9ZOvjZHAukAScqK9P5Erx+Y9e0NcNwoyMjQ+DXo1CJBrjBqQUWNOjsoD9CK3pTM2p62iHgdFaEJLlesUiy9AqobMhG3TtwOAdRVUGsuRgWfgg25FNj566fv3o0AJ+dP2S4dQwdgOmEBgPwzhg7IBUgr7vqOsTbduQZTlZXuC7FmdGfvrTP8N7S9P0SOH52c9+Rt83eOfp+j3OW8aRSSI0XR5TUPJeIP0z8/08I1JKzmV6wC8/nAoTy7hztnuMFzEYzaTSM5fSP2mQ+piUFTdnxAuMMWivGdqG3379W377219zPOyod0+kUpIJwabM0N5SP+w4HE9IqXFOIJTEafBmwA49WaJZFCXd0DI6yzCMDGZE6dDitOPI6B2DPTJaz/5UI1KNzlK2V9eUyyXOWlaLJV0iqDYr1GCwg+U09thTyypJSLXCWYMXCusC2HjaHciTDDMMCBt8ZCQC5aGsSjabDcY5ur5nGA1JPzCaYGHcti33xx3OGpwQfPlnP+Lq5pLFqsILG0Y4pRqcZV0taZuOU9uiK0mlSi6rbXBl6MPoqvrwmqGFXCtG6/FjsKXNkgwtJIX842luM33Bh6aGGXusMYhEkiSaw36HkpKsKumGYRbDAhRFMbtdnlvfBnwpmcH4c/vceJOfu27GzXs+2cU5N+n6BNXUzQre7yl5njMMA9988w1pmtANXShNlGJVlJRZRn04kKU5w2hBeFSisVgMLlQ3wmF8T2c6VosteZaxXpQoqRjGgXEi50rrcCKQHIVSON9jBfTeg5SUWYrWCuMhryrKqkQIGLsOrEV5EJPch36gn2yjpVSkUpFbT9121KdTGIQ7+c1LAVJCWWSgNVIuJ63kSNOccM5zOBzouo6277HeIqTjt1//mmVVcXV9QZoETlhVVeA8TeN42j8BDiF8GCXmJwnaNOlJyagHPL/M5Byksiw8dmOeM+Dzzv/HDIDzQBVxx/i5fzJZzMc8nJkpawx3t2+5v7vjcNzz/vU3vH/7hnVVYr1HaoVOU/b1ga5pcKPFeolKUqTUNId9MNp0BtNbGmocoS0aW+VJkmDaQHzLtOLU9dw9PtKMA6vLLYk1LDdrchU6U4MxlKKkMooqLRBDz8P9HYfHB8zFltUqWGlopRBjwCdOXU+qkwB2EigUidIgYSBsWpynUCmZTCiTkn4caZqWtEwoV5sA6ucpzhmsG2EMPkPpNKzUk+CsR1nFMqmoVAULQdv3tFVHNww8Pj6y/Rf/Kw6nmt3xQIZmXVWkOiFPUrxxNE33900y+qT38/y9lCLIRCwKP5n6F1nG1XbD4+MDX37xBb/+zW8xxkw2v8P8/p+7G8R9EWUzseN1nuaHci54s5+Xi3HTxqwwTVPwbu4g9pMxm3PBijhYoiyCzc3QohOFF577h/uA70SCkxAkQqKEQCnPaeg4NTV2HHDjwPG44/hoqMqSslqQpBlFtQh+WP65+eMJwXhwfSBiekd3OuKlpFqvyfPgCCumQ9uPBp0lk+9X6PY661iVi/D5pmGUEjvtjyxLOXVdyOjLkhFH0zeUyQJjRw7HkfV6zakxlFXBYnkTBNsTZWP/9BQulDRhv98jCNjtcrFAK82rV6+4vLpifzjwtNvRdu2cNUXBvvEBTY7Sp3MaS6QkGGPJMj1zpGImD8wwwPnwlPgzzu2Sm6aZR4f9vvXJQerjXxhazQN3d3e8efOGx8dHDrf3vLy+Js8zFkXBqchJtcAPI6YfqJsTY9+EGtgYpE6ReIQLkT1LUpwfMMPAKAYsjtFbVKrYbLckSnG0O6y11Mcjjx0cTidklnCV5qg0Jc1ymqZFa0m1WHGZVrgmiD7v371lHDo8htPYc7F5wegNdd1S6pRTXQcphHVh2q8Lbo9OBKGxxWBj+xyBcaFb6K1DW1AyISHcnGK0SO9ItUaKwNdyo8X5HiczjBPYLijxE6lYr1ehPS4Fu+OBqsyDBnBRsl4taaZR4ApJ33SgBVar7xG8/OPWjB/IwAC+vLzEOzMNKl2we3rCTZvu8y++4O3tw0zeizfoOI2/GsdxwkwGjBknt4bnvZKmGiEC/hiziXNv7FjaNU0THpeSMwYTsSh4VtivVisuLi9p21ACPj090WnFqioo0gzvBUIorPUo69FKcOoGEil49eJFMGkbR3zbIYyhHnqawy58vU7BBwJqVSzQE0s+z7LAqUEgvCPJclSekS8WKK0Yho7ROYxSkCkGa5BeBK5SohAGuqGdy2DrDAiHTBN0kdI1h2AAmEo622HHgcwGqsHxeGS3e6Iocqw19H3Yl23XYvEURcowjCSpnk0inXW03YASBp1qVKK4eXHFZrvmWB85NSfqpsHY4DCqfHDVXCxKsiz8nnOnjcBhNnNy0p8Rfj9eMYuOeyRmVLHyquv6k/bop5d7s67O8fjwyF/95f9E17ac6prTKQzbXOeS3dvfIKzgeDywXVQYbzl1LabtkW1HojWtHRmdI8GC0og0zKbrlaDxAqkSUjHS9h1KSpTLUAKMd5ycZe8seVGwuNoimhN5mVOsCsqiYF0WVEJhesM2W9J1NXd3bxnrmnFosOMQCH3DyNEKbFow5jI4g242yCSlPhyDS0EfsCnvwyirVIZbQCYaKQSp0qw3G5q2pe96+mHAtv1kIRPY921vUYnCiwwrLF5kDL2hKkp8pkmTwMzWOqM/1YxmJBMJySjwHbjesbCKXGaBgCcDR0YpwSlP4bvDRDwO7HOQoS0tonOEJFRToXQNiVNoQjxPOvYYKRiEJJGCXElkljCYPcYf0LnGuJZUpvzZzQWnU4dx0HYOOSoW6TIEEzlQlDnj2CKlQsgQdIdxBAWjH2exrLHBnhnvpwCQopVi7AeyPAu+UtIzuhatFOtVSVGsw8DRadzVy5cvyZMUlwmuLi7QMuBmx4c9JwR5lrNYLsm1xqeCtutpuwA+lyLBYdFpikxKJIJUjgzOoJDYYcQNhixRZKkFHHVTI1XCAIFnhSAtctLVktF6hmFEeIFAIeO0IxdoLMaY8PyswVhLmmVYN+J9aAIY58hVwiqvEMbR1adASfjsmsN+R9uGUV/RZiVmlUopBALtIUky8iQLpoHDGCREUwltxpG2m2YEqmDjfLFZsVqUs9Vzc2o41aeQFVkDdsRMmXCIQZP8xXisn4KWf7YF5hzjnAKSnEB5P3XF3RiybeeZ3C/+hEGqb078z3/zH3h8fCRRCuUdhVYsry6Q15e8e/eG12/vWKY5ZVrSn06UywVeJfRmRI4jcug5nmpcqiiKKmwIE8pAKSTCCxKhkdKzvdxSDANv7+7IsiWjsTwc9jTjwOLiks3lBb0FkSjKMiVLNVmi6I5HurrBdJb67pF6ODIOLclkjJclCe040Hc9SiWgM8gVRZrM4k5VBF/qPMs4Hg4M/cBCl2ilsd5jPKSJRiQpD/vdxCkJVAmpNd4YRJKQ5TnWObI8Z7SGx90Tzjm26wsWVcXT4xNhXFFPN0mAuvYY5tS1PWMbuo95ViJ1COSjHYJ3tFZ4cZo2RsynxLRPnjlqZ9fMWZDi7N/h4w6PF548SbgsS26u11hteTge8ELRnwaUYzIB7NAqJVEisPrxpLlEqBypBIVOcT6wyUczUmhJmmX040BZFDQKtNShm+ShyNNgQexGtPTByjbPscLhdDJJWiRlpllWa5bV54DnYrulOdYUqyXLPEdKybIoZwtifLj16/2ekw1Gbjc3NyRSITwkShOMJMJhU0lK4iRuNGilWV2u2axWtE2LkAJjc0YHqdC0xqATSblahYM6lTOrakmSpHz9+hsAlhM+OvR9mMo8tf0zKZBJ4BcJKfHGUB+PSGC9CMFIwqRtdHM5dZ5pxi6fsw5nDHY0H+gkh74nz3O6LmRuUgm8n2AC72cmf5YkVEXBdr3GGkdd1zRNE7BJ+IjrFrrYIPHO4af3EClmBdwckIzF8axuUFKG69E9e9z/SYPUX/+//p9YZ8mA/cN9aEn7QKobuo7jYY9vG0wh6EbwxmKNRZYZKEnvDCLS9/PAsB2GATk6EqnI0oxx7MmEYLVaMyjNrqsZpaKznsPjI14prl68olhUZHmBqGvcAJkU+KHjeDph+h7bmxCkDjVOxjQWTNfhZADJNbCsFhzNiFQa6yx5WVIfjxgczoQ3frnZTBqp4DmNDl0ZqzV5WSL9xB2a1OM+MdjOs+9aEmfQSQIuIS8KLidrWZWmjNZRrZZcX13R9g19FyYveyERWoGS5HmBSnSY8yc8KlEYa7DOBhD/4grxl3/3qW/hP7gSrZHO8eL6ip998QIlRoy0rC82aJ3RHtogIXE1q3WGR1HXHfWp4dS1ZFnK5nLDclFhDwH4N9ZgrcOLsGl301DP/d4x4Fmt1oFAStC2eeco84BTrBYLxNS29z6o+BMVXBryLHhqaRzrRcVQdxM+lTE54JOl6VwilnlOaka6vscMI4MNnvGJ1kF4PA1DVSKlHzo0gvVqhTeO/dMeY20gTCqJk0HaZZ2lLCqkkGRFRtN2ofvqBWmS8dlnn/HNN9/M2F30AYs4XaRZxLJZiMAHC6PmmQ35ootmkiTzUNSZaDuG11kEgd0H2s1hGKiqaqYHSBXA79i8OB+hFqkdUTi+3W7ZbDazC2rbtgzDMP8JMhz5AVh+7poQtJeBFF2W5WypbP3zqHbv/exK8fvWJwepb3/5c4qi4Fgf6dsW5wypTsjSwJ1InQMhqZ92CK8g0fR9x+ZyTZrnZFKyuNjSHY60XR/S1WmIgukHxn5guVpTVRW7w5F39Q6PZ0CQKEVaFqw3W5IsQybBUF9YQ4oj8Zb2VHPc7ehPDd6CtwLhJTpLwARgcex6nFKzprDe7zkOI8WiZNef6O/ukFKyWi4RhBHhqgji2cfHR66ursKb4KEbBqQPWZBSkpMNhE4lQeUpyTQlxFrPaex5PO5Zr9YUVRXm5enwuh27lvv7e7quCZvGGZyUpGWJHiefpqldfGobEJ4kS7DG0Qz974i3/9AlnCcRgkWekQoRnCi0YxSeYbRUqxVaQT0OLBY5UiiaVY5zmyBk1YHmGmgB5XOQcj5oIa2lyiRZnvHqes0og7A7S9N5rqFWKkzosXb2QPdCYMYxlONCokRogSeLkizNqMqK5ZcrzBBKSe88p7qeSpAgs3HGoNKEVRXmBKKidbE705B5hq4mzzKSVONGi0IgVBhkOlobRpoZw67pWG63lFWFRYTJKyJABsMwsFqvGcZhmjbDB8NFI/8rdjnrOli4LBZBeRFpHHmeo7Wepjn3czCIltHn3TGlJHkRZkZGQDr+6bouCKirin7oPrCYnln93s+mhYlOn6154AP7YjON6TLOg1BBTG6fGerRTjgEr0BTcNYyTj8/dAwl4FFSBbO/T1ifHKS644HT7jGk0XiEd0jhEcbRT0ZnbhhD295ZUEE4LGTgjqzynHF/YPf6HbIzJEIghcJJj51Ex7enPbRH6qZFpinVYkG5XXI5TW6tFovJ1VJz+/6WTEo2mzVYw/54pD8cQoppIdEZOg2kvWEYGbuJf5WEEdjbizAiSRnLdrulaRRP0yYqFhVpkpIWAQw2wpMtSjobxvYkOqH3BFZzWWGdZXUV/jam43g4hFree+xouL68pKtP+GNNohVZEsqew+HA/rBHa4VzJkhP8hzGgUQotJ2sMaY0/aK6nr7W0g8946n74D06p4l8byD6ewBOCFNacI5MB4mQ6XpUoXB2hNFT5jnWjOS6CA4FCNJlBoi5hJnHwZcKCHP4BhOsSAI+Fx5vnufIJEVqFcpuIREyYRwNWnuyNA5pCJeJSHLMGLhNwRli4FDXLPKcoevYjyHICiEoiyJkIx6aaRJx0zQkLifLQiEcZgQ+6yK8ByEFpRBoJfHGYoyj64cw/QYffOuzjHYcKVYLtpcXIMOUGWctbdcQ3QgeHh7wwnN1dUU/lVwxA4ocsWjZGycYR2qFc471ej0Pu4Bnl4n9fj/LiD6wvclztFSz7xSE4BLnAUb5UczcovHeue42dt7MaOYpx+f7JWZ8eZ4Hyo33AS4hmalI518XcLMhlLBKsd2EDHEYglmgMYZmmhD0+9YnByktCbSBSToiBThDoP27IDoMNawMnQIRnnjXdVjvePP2LYd37ygGg+7NVNI4jBAMcqST4BJNviy4eHVNqcJgyDzLQiaVBJlBkaY8Pj6yyFKKRPH+zXcoZ2EwZEJhhMdJpi7SswXJaAxplobH6x1N13JqTrT9wNs3byjLkOoOw8DDwwOXl5e0fRjOmaQpRaJBJGBMcHiQweXh6RiGLCop6foOhCXNAku7ygu8gMEZVhcbDvsDSZLTjAN13wUDNGcRQpOWZRBe45EywzmCp5EJr1Wep6yWC/Is43DYk9oSI9SkMg+bNequPl7nZMnzz59vQAR463HGg4Miz+km3V6SZTCGEsykF/R9F8apa4WSgipfgAdVBj2fVeOMSyTkVKsFxlmKcYRIOHVhIGnoyAbfc+9caNVP2GCeZQhvEcgw3syHrFqmGVRLxnZASo0RHWp6fl3bBiBZaawxYdz5YoGbOl3GGzrRzTiJng5ukeTha6VE5xJnLKPWeAEi0bRjj0gTklSxvr7GyzBrLkvCYW5OIUhVyyX7wzE4hk4Tb/q+5/r6es5arLWUZTmz7iNvLH48cs601hyPR66vr7m4uCBNU56enijLch4DL0Qw1bvYbOZSsaqqOdDEsrDrOvyED0Wmf5QxzVYrUpLnAdOK5WbEomJHLgRHO5eN56PU0zQN5olTc0QpiTEDy+VymvEnwsxNIWYi8J80SBlr8SIIC71zQYc0WiTPhlgGg/duHgCZZ+k0PKDm7t079DCSS4FPNUaA8RaSlGSZs768gCLBpwnLaknpgyTFGUOepmgZJAyubTje3QbHRu/omoZXVxcsrq55vLsL/BAh8UhGH1L+0Rm++NGXHI97uqcBg6O3BpRkNIbr5Yr7u7d458PYpqrk9vaWJE1mnd9qtWI0HiazLpckNKeaqiyRUtE0p3DLDy1FVlC9KKdpvTmjMdSnmsV6xWgsxofDWK2W043Tsbq4wNqRvuvxwlFmBcJEYafEmpHdqaF0jrSqAl4xAajfJ/j+1DVz3pxHqRQpNFpnlEVGqRd4JWjqjlRlKJ+S6IqLZcoi2/P69Tcc9k9cXwUht0dgBw+VCBiTn4ZzJhMOYsbJTFAynDqafc1ys0Z6CS4ArUkZcCIzKfn1JCwfu3GaKxgyBzdCazrSNCcrCvTkmxR90YdxIFEaM7XB8ZAkKWmWorSaAN7QJg+uBcHjylsXGOVCoLRCZUFeky6XjD4MmrUSdKKQXsxKiDTJuHu4pz6dKMuSNA28ryhfaduWNE2p6xpjzOxXHwmx1to5YETeWAxccfJzkiSs12sWiwVlWQacx1qEDINFY6kXs6PlMgzTCANWxex80E10ljBX8Vlzaa0lm2CKOGk6rpgJOufAO7wJQHgkeaZpEjAmIdBSBrsmBKtFRZaGOZJyCqpSSlL9T+CC0BkztzadM/MGUlKglcJ5j5saTUKAmVqt0jn2Tzv6tmOR5dRjS+sHdJpTrZZsr28oNyt0nmEnH6pUKOSERQkpEM6ETToMHB4fOb6/DS9UWXJ1cUWWpOzu7mjrFu8EXsppXlroWlWrJeuLLXdP9/Q4Tk2LU5K0LPh8s6VrGm4urxj6AS0Vj3cPZElColOGyUZktVyxf9rTNic8PpifScHh8ZFqUaGn1Hl0LpQLzrFerWiaBmMN1XqJB3obSG7tMJBl4c2rVkvqNsxqS8qMuq5RLvhiW+MYmpbL7ZZ8tcSOA7up89NPQ1P/mCAVl3MSj8JYwEvGwZHqhHG0bNaXDKcBM3pc03M6Hun7E5vlkotVBQ66ug6Wy46QYieTbk9AlmfoJEV7BWPQg+XFikW2xDmL1JoiK1ktt4xmJJkuQ7CBZyYVSiUkMkHJBGs8TiiKcsF2e4FUwXUyYFkJeZZxqutQKhKyXKaWuZmyG+TkrJGmrKpA/jX9AMrh0wA298agvUIpzSg97WjYXF8hlMa64BnuTTi4yWS9PEzlVuQSRY5XOgH5UYMYx0Y559jtdqxWK+KYcyEEm80G7z3raXIxMJfTXdcFB9Xp+9Mk0Deie2cs686xqzhyPmZRcXRV5DFFq+f6WH/gmNl13YyTRXA9gvHnZOB0yp6sMfM05KLMybKgPBjGAenkVBbKDxjtv299uq5ChdtncG4y0RIIHX5RN027sBPnZRhHnFTU9ZEXNxd0bYszFpkLFq+uUFXColxQFSWJSsjSnCLJgl6uHxlPAy5ReBK8Gdk/7Xh4947+eEQ5jx17XtzcMFTBx8cMI/vdgbEfwuhp5zETjrBarznVR45dQzv2XNxc8aosefHZy6lU9ThjSNKc0ftJ0JlxfXPDm3dv8QJOxxpvQ7DIVNgkfhzZXl6i14qHx0eqquR4OFIkGaYLHJWxGzHGkeclaZ7ztHtC6IQyLxgntrX3lnYYgqI9Lzk1NUhJ0/ckaY5KFJcXLzDDwO6wZ1lV6CzDOYuaNuP5+kODFEJM8iCBkAmntqWzBpQgkQbvQApF3dR4N6KUo22OKBlsahRh80khcJ3H988TUEzX4dQ4AewKqcK0aZUkCKFQUoesRoD3EqkCljiaFi8C/qV1gvcSM5m1LRYr8CLYo+SBENv3PT4OxBChvMjzPJSRKpknBYcpy47D8YixlqzIUVqRJ1mgOwgJQmIAmaSYCTYoViusCMZwZhgYbUeqUhSSQxP4aqvVisFYTscjRREsUmIXrW3bmRTddR3L5RJjDHmez1bMcVAnPGNn5yB5LLGGYaAsS+q6DjKcqUQex5HD4TBRD0IwK8uSd+/eohPN4XD4oBSMwS7unRi8ogtokiRzhy7iZOMwBN3ghLVFzyjvpvfbjAjAuTEMq5CSpm1QSlNOLHMhP62zB/8YxnmiccIhEo+SDqUsQji8UzgjguCwH3GEsdqIabggUC3XrFYbbi4uyS4qGm1RSMqsIEEjjSfTGf2pZWwH9rs9XgWJi/OOu8db7m/fUwqJtY5FVSImhfjh8Qlpp+mwSlEsKtrjHqElXo14DfvuRP3tNyy2W7786isur294eNzhh5HRdKwXS2SSUCoFWiGk5PWbN5jpTcqznLEf0TqhLAvSLMP7MMXlccIIvPeBhGjdfGN6PN3QUxTlbDuSJilZkoLzU9q/wnvHfr/j4eGRNEs57Gu2F5ekacHpdCRNB9JEc/3iBdYE+xiAp/o01/j/kGXLuaD4/N+xnBAidOb6cYQ8pbq5JteBE2XHkdOxoRtbhqElX+Xk+QIzduRFTt83YRin95zqhkQnaKsCRjXhUt6E5+rx0yCMESMlOgtlRH/qEVKRFwVapSED9xIlJdaGktkaS9e04X2QmuViSVkUWOtxUgbgWAwMdmQcesTUtDicTiRKURY5SulAN8jy8Li8CH5VUkwGemD6FovAKYnIEnya0nQt1XqNsQI5isCYlwnD0DNMbq3h0PkAASyWpOv1Bx7wMUgppSiKgrIs6bsuWCoTmgqLaoF3niwJqgeHxRlL24XhDVJIyqrEjIaiLBi6EJSd5wNfpxjsnHPs93vqusZaR1Ems5xICDF93FJV1VzaxUk/OtGMZpxwXTNdLsFV1Zhw4WitqaoqgO5Ssat3dG1HmgV7I7zDCYe1jqEfca4nTUL30Fs3i8z/ZEEq4lGrdYm3kv5U4y0IMoTX+BHk4MMEkzynFZ5yWTKakc3lJVlZkVYVUnsukiDDKNIcQZjC0p9aTqcTXRM4V8L3LJYlusg4ticWqwW5ATFajPG8v3vATId9keckyyXj0HFxfclxbCARdGbgYfeILnK++NGXrNYbyqpicFAtlwgvWVYpzhrunp6C/cflVbjJhKQosjBhVizo+57VaoHzfpq31gZsoApDAuq6ZrVaBf3a5MuT5zl1fWSIYKWxrNYlgwkb4+npiaZpyPOcxWIVnn87sFisWS03tG3HZrXm5cuX3N29x5gw2DFsqKm85vePsIpkzxiYPg5eYXMKpBbs2pqH9oRyBvVg8cYwdMEd8/rmmu1VKEOGsac51SQ6R2sFOMgDLUD0Pc2pAZ5ZxUpJvA/YplKKsixIkuD3vVo8l3THQ40bPRcXl+hccf/0jqEO/Ca8QxoHdPQHi+9OeCGxuiRNU9quw1lDXhQMXYuXUJXZ1OgJTGel86B3M54sBekdylsUwfbaahk8xoSALKXabKArKIqKcTQkJGgRyqDm1M4at77vUZP+cGhbunFgvV7PzYoITMNz1lNkIcvTSrGsFjNPaRxCVyzyi9I0RehQzhZZTmPDxdCPw5S5mDPgO59w4NPcTIkA/X6/54svvpg96quq4vHxcbbficM0wkh3S9e11HUdpFK9nwOas5Pofxjp+4Cn1fWJNM1wzrNahb1sxmH2dN9sQhZ3PNas12sA+n74pNjz6d09IXFChBtk7MJUWaHwU5rnnMdrSS9BKxEU4aslTis2VUWSZSitkXg0IrTYUWADX+T9m9ecjqfQzXKOVKd0pw5GQ9d0aJnQN0PYpFripABpwDvSbBkA/Kqi6QackAyjxUlNUVV8/sWXbC8uAEGiE4qymuQLIrB5pcSYQFoLB0rNtft6vZ5SbDPfVNfX18GloK5ZLBazS2VM3ff7/dyK/eyzz8LYq6lmf//+PV4EBnbTNPPPi5qmzTTRuK7roJRPU8ZxZLlcAX7Sb+24urqa+FN/rHovrPBahIx0d9hzuVpghGd0hnQRwN3fvH7N/WEXNqoP+EaSJzMtQloHKkEoWF2UIWD78JjToiBNs0CI9QSHUwz9YJBCUhQl1nZAMNmzztIeG6z1jGPg3qQ6wRJKaG/74JKgNM0Ix/fvkFKwWi5wQuBk2CNCJaHbJ8H54KggkoR+CH5ZEZ+agWWtsM7RjiNSCJJhxFnHMIzEmXPHKQDHDDYSJyNRM3bTYsm1mTzyYyYbAwET5uRcYHnHTlr8WASwo1g3TuWJ5V+0rAmDU+u5jIzi7vPO3DgGeOH29nbmM0EoT8dx5PHxcf6dcVBGpEtEIXGU4kRQ3XsfSLVa0/d9eG1FdNHVlJNyI5I+Ly8vgTD95/379x9cmP9g7PnkTWw9OEFThwipZIK3HksYUU4q6N1IZwZSq7gsLxCppipKpJ7mkjkfjN6NxWAQ2iK8Z//0xOHxka5t8M6SJylSVWghMT74HA39gDIjynik1AilkcIGD+tTjU4SFqsVx7ZFJjmu71ltLvjyqy8oqyqA4F3Pt7/9mjRJWC5WLJcr0jSjbZu5To9i6dVqNdf+l5eXFEXJ8Xicb6fjMchXAE6nE5eXl3PQiS1g5xyHaYZdnKaSJAlCaU5TBhV/jlJqHqcdbE0StErmtFyIcLCTJGG3ewo/336akf2nLCkEUgTR6+ZiyzB0KCUo1guKxZJ+GEj7EYxnd2oxY88wPiJkmD2Hd3PXKlcJQiqSIqftOq4//9HctTJm5HissURpkiLRKYe6pjm1lGU47N0wkGSazWbDWJSc6ppEKbqmxdpJC+YMFkMrLS9e3LBZr1Eq+J1bMzVuYgDyNsAQ8hlEtjYM22CSa7jgGA0qeNkvtlu80jCMHA5hmOtquZiNGIGZuxTLqOhWuliEzKjv++nCkbPq//yAbzYbrLVsNhtOp9M8OTrSEaLkar1ez13CeLirqprxpIhrxc9H+g+EYLrdXnBq6nmfd11H13VT1uRmnlb0mL+8vJwv7bjfYzNgUS1o20BDiYTVKNEpy5LHx0fMOJIkgQhaFAXH45G6ruffFceUfcr69CDlPNILtAojbYTwDN0QgE+V0x5O1G4kXy1YbDakixLjQ3dNWBsU79bCZHXSdR1P7Yn6eKA5HnDO4Mc+dO2EYOxHlNTIRM/2ph6JcQZpPUI6slRh/UjbWzJZcep7OmOQSYbtDZvNJcvFCq0lWggedzvqpx1SSDbVkqrI8Qj6rqM348yojX5F2+12HuAZ2sQBEL+/vw8axiSZp/R672dsKvJAYnb14sULHh4e5k4JUlJWiw/4KMfjcf7+pmm4uXnBfndgGLtJdvDsUhrkDvGt+9NQzoNwNMy5QwSPr319YKEq6sMTdROoFb51ZHnGdrul6zv6vqU3gV6gtWLftNweG8qynNnVp6d9+JkiDP8UQlCkBUW5DJ3g0eCsJStLZKIZzBh8kJZL8jKjuMrZPTzy+ttv6QcTNH9CQJDnscozVllBlWQcDgf6ugHr8b3FKRmkZaliNJZxv8cDaZqTiHB5IoIsSGnJaehxCBSCfjSMwxguRXwQ4B6PvLi5ng/kdrudWeNRHmKdJUsTDofgaOAmM8VI1Zm7fEpxf38/u17e39/P7HDnnsmxwQ7YzxegEGEorbWBiBwvy3jB7XY7NpvNDHg/Pj7y8HBPUYZgkabp/Lhj5zFmSTHYPD4+cnl5SVVVnE6nmQBa1zVd281ZfswkIyUi7vHQEV8EwvIUyCM29/j4SFmWf3rtXji8GZ99/hXWjbRNE7RyxjEah16UbKsty+2GNMtCVyhPJ+awB2Mww0jfdLR1Q1MfGfoej2McepQEb80sDnWRam8sCIJeaOjJdYpINH4SaAbJQ0pnDM6MoBTdMPAX/+K/DjfRMHLc1+yf9uwenjD9QJrlHPd7HJ7RO6TS8013cXHB4XCgqqr5xn14eGCxqPjyyy9JkoTb21suLy/nboi1duau7Ha7D7yPILBsb25uaNuWh4cHVpsNOklnpnEMVsYY0jRls9mw3+9DplUfJguV7SQebSmKMAo8bJLw/px7fJ13a6aYM3/uvBsYPx/M5xKUDip9qRU6yVkqaLoGJyTVeokSmrIskFrSDcH8bbCONA0TfJKpZC02a6RSHOqaalGBEFxfB4rH0+4pZAlVwcPTjmpRcWrbadIMczmR5zmtN2zshrrrKYqC5cUFeVmSJgl379+H170ssb3hcPdAu5smLyODDtOH8t5Yg8tUUB14zzgE33FnHWW5IM1ysjxn3zWMSPKiJKsqZKoR3pMkKWaymj5ndceMIPpbzX5YbsK3bLCWjnymOBXn8fGRtg20kuViOV9gkaQZHUfrup6hhSg3Gcdx7hpG1vrl5WUIzlMW1nUBM43B8Pr6mrZr5+DUdd2MbUZ5Tgw2UWcYL+ZotxJLz7Is2e/2FEU576UotYnfD4GSEIPm4XDgcDhwc3PDdrvl4eFh1lr+SYOUdQ6hNav1ljfv3vBUN3RDQPmzIme5XCDSLIyEynKyPLBPvXMM3YDr+wCO748MbRtwLG+mF2GygiHU3dY5sslRQOYpQieMvg/qaxUsXYVWdKNl8GC6HushV2GD/exn/xXjaBnalvrxQHc60Bxq7GDQQrJdLtls1qiyADOyPx559eLVDCgCtG07v5AhJfa8f/+ePM9n/OHp6Ymu62Yeytdff005jYKKuFY8dHF22eXlJV481/WxFCyKYjaNU0qxWq1CJzAPwtQIaiZTGxmW7Ha7T2btft+KGElkQSPCMMnD8YhWnu12Q5qnHE4NWmnKcoEaQyfsdAqlr8cFUW6isd4hhaCYLJiTosA4j/OOb757zXqzQSUpQjk662isRRjLyYy8+Pwz2q5hv99jtaQeO+qHnvv9fhYDp1qhJLjTCVUEKcipaUiNox1GbBpY1NZ5DseGJA1ETOcFDoHO8jBIwwebmnG0jNYincd2I6MXFKvA2VNZiiWQFLspGyqLYual5XGYx5RNCyFmtjgi2NNE7CleaLF8ipmGd57vvvtuHjIRbZLX6zV1XZPnAeR/fHyc+UxxX0Ws6PwyjIEyZubj9BhipzmUfdsZYgieYUvW6zXH45F3794xjmPIglar+THFvRIzpXihx45lfP7RgdU5x+PTE0X+TBZtmoaHh4cZvzKTvO1T1icHqXJZ0Q09f/uLX3JsTngpKZdLZKKDydbEuRDIMDXVBb4ExqK857Df83h7hx8HEhlU54JoUyoRUuNNmAcmhEJnGYv1mv3QBqxAgFeBrW51kL8M7YhQiv2pRiaKq82G9WqFEPDNr/+O7WpNd3wCOyIspEKhpGIxZUwnO3L38J4XNy/n8q2u6zkVvby8JE3TOduBQLzLsmwGw2O9XZblDJLGtH8YBlarFVkWyqP7+3vatqVuwqigruuoqopXr15xe3sbOD2Ttsp7eHh85MWLayDAKfE2haAwDzcc/BFxal5CyaAmEAT84vhIezphrKHMAu2i3u0YmmFSyHekaYJzQQYEkCSaYegxduRx/8hyuQwdocUC7xz7436avZfyeKgRacooBY+nmh9f/gw9lDRuZLuoCCObBjJdhH3kHEPfcdjvwTlevbzh4f4BJUBngX/TD8M0pFUyChBZghEyTNnpLYmSCGdnQN97T9O2nHqDRbC8vkDnBaMLPunWObpTjTcWKeDx8ZE8L2agPILLwNxFe3x8RGnN1c313ECJRMmQAeczhvVwezdfVPGCigEsXmKRaX4+fzB27yI8sduFZkZc2+123o+RDxVLuf1+j5RyDqjnPvURS43YVPxcvIhfvHhB3/cc9sc5u4uXcgxa4xhoC13bkqWh9NRa8/LlyxmQ/+KLL+YZjZ+yPj2TwjM6F9LEqqJYLNB5GKJJIpGpBsdkp6FwxoB1COB0PPL0+MDQd2RKAiZwVAgDRIUIJlyBqBeIe6jgapjkOYvNBj9aHD29tUgnUWlCud6ikoRye4HONDcvX1FOs+ucGTg+PSLHHi1AI5HCg7BkScow9PRYtjdX6DylHEMavlwu5xstSRIeHh7o+56f/vSnNE3N27dvQ/u5aWbpQex8RMX6rGMSgsPhQFEUAUycrCsiryZmWJeXl7x48WJOjUP6HASyx2M+lQ0pq9WKpjlRFDkePwGx0cXnj1vOB1Lm/rBnt9uxKILPu3eWU3fAjAWZTmltgzEDSapw3qIThdZqDliLRUU/jnggL3KcC6JspSTWWbo+iM7zRYWUYVTZz7Yb/r+//CVJmrDdrjjWNc5bNusLEHpyr5TILCVfLlmUBU5IXn75BW/fvOFgB1S2IF2u2R9rsqJkkRVY5xmModgukcOIHXr80JMkOgzQVJK0CJQULGTVgnxZMjpLPw6BcLmoeLi9Y1VUVEWJkIL+jDAZKQKxnFuv16xWK5wIdiuXl5dz6bTf77m6uqLrurkTHA9q7LCdu97GsquqKvI8Z7lczl3gc6eCCJQ3TRNmEYpnzV0UKUsZRlPFsixN0xmqiMEjSndieRcZ6VLKufsX6S+xHI3Um+g5FakQZVXOnceIT0aP8+PxOGein7I+OUi144hMNNvtBmQYqS20AhRChSmyWkgwBusMXdcGPMV7msMxiEE9jGbAa4GWSdDYTXYZXT+Eg6I0gzVkIUGlbbsgfPWC7dU115fXoCR11+B9UDrnRQ7C0w89iyzD9B1lohlODWWWIgkjvr0Is9iqakHTNtR2pBWW/W7PzfKSsipx3nPYPXE4HsL4ou2WzQQyeh+wm+isGH2hiyJgCQhYLBZcrNdBaOvcZJjW46zj1DQMw0i1XHJ3fz8DojHrioGvbQPutFwtORz2U4qfTIEuYhLrQIbzUYUWA1X894e31PfdWuelYgTwi7xAqcDVaU51GOYqFUVeTJ3GA0qH1D7LAwdpuVwipeDu7i6UqalmvVmFGXKTaLvrBlarBXme8/S0I8nLoOuTgruHe7IipypLnIeu74Mtbj/g7YDWir7t6NqW1XLJcrvluN9jEGxvbmj7E1/fvqc+Naw2Gy6rklN7Yr3dIkdFVlWsdcrYdUgcqQz2L8fjiaYbGHFU6zVSq6Du15rEe/J1xn73hBCSpm1JdcANy6rk6emJ1AXSYpbns9vCMAzc3d+z3m4QQvD1118H19qphPv2229n2Us74U9CBNvmahwwowlA/2S/kmYZx+MR5yxZHmwc6mM9016ccyyWQR4kpODrb76mLKu5PDT2zHc+1XOGFe1fIGRm2+2WPM95/fo1WuvgpT7BDEopLi4uZj6YnvBThMA6y263Q2lFOomt+ynr8y6U30+7XSBw4hmGkFHWTf3J5JlPDlL5xSbUpwISncxTIqKx+jAMmL7GTvYWdV0HbEMq3DjiR4f0AiMkFolzAgVIF0iixoyIRDEKg5WC1g807QklBJVOYbHkyz/7MUVZ0rYdQieI3LJYrgIFwnnefv0d75/2DMcDNA0ljtF2+IkDk2qNTjPyaoFxAyuRssgk9w9PHOqARY1jh1AqYBVa048jgzE87UOK74TATvKHCCb2xiCnW8J6GIxlGA1N11NMQwuc94zWUVQZyQSOR/+f2PWI/JZwk/Zkmebi4uXc/gW4vr6hrmtub++5u3vEeTsFoOAdHsDxSVQ72QSDmm/bGLDiJo48FmcMiU5xxrJaLhnbYNCWZimL5QqkDAF2tcSLMArs1ISb9/3d5HuOwgnFfvcYRLmTyHa5DKzkYQzv6fZizdgZrBnojz39Idysx3YXeEQoirRADKFp0tYBBC4vLgKWYi1JWYYxZjolUwlXLzI2xkwky5DRSC8o0jBZZ1SC7GJLmoaDNvY99/sDItM459HrnG7sEGaY2/JZUbBZbjj4w/w69UOPH0euX7wI01rGgbTIOZ5qqqoKukul2O/3M+M8AuzAnLVERnj0fBrMSD/hQUJKzBicOjabNXVTMwwjx1PNZX6Jl+CEnxtTSZbihQ8lu5IIFYKH1BLvQKXPE4SjZ3wEyCM21LbtnLHFkjAC9VESk6bpxKsy1OZEkibodI0UgqZtkUnAm/Ii5/LqisfHHaf6SDsM5HlK1zVsNoHv5+1Ikqd/2iCVpAHP0UqRKE2iwr+1UsHYbBh5vLufOnbQ9aF1LpIUZ90M3EmhwAaLUaHCoEbCEQsDMp1l9I50euERgusXV1z7EMjq0xGtEy4ut+y7HRcXW5z1nI4ndrsn+sORVZoiZWhRCzdOXBkJzrJZr8iLnHGEbuw41Q1DP3BxFfCnt2/fzl2wvu/57LPPePv2LcvlMtiTnA1CjBhBZOXG2v18aGbstFxcXMyi0cinial0kiQsFguAWRR6OBxZLMoZh4o8nIeHh/n3B3kDHwSePwRID9+rpm5jQpKkdKfDdJAmMHrCykImFHha79+/J8sybm5ucM7NpMWbm5cIIebX7O7uYZZtBPdMxXJZcJpGn19fX8+atHzKSmLzQWrF9fU19/f3MxD99PTEYrGYOEQN1jq22y3GGF69esXT09Pcvr+8vJzKDDMDy8djzTfffMvhcOAv/uIv2O12DMNIUYYSNJYu8X2Jl1Fd1ygZCJVRdGut5enpiWEa9wXMUpGIWUUsyHvPxcXFzCQ/7/pFrlye5+G8TfsslpBpmnJ3d8fl5SVxzHx8jrFkS5KEFy9ezOTP+PsjxuWnkjBiTpHyEmkDdV1/MEU6DoHtum6etByw2UnQbexc6qYq+JlfX4Ty9nQ4kkqJKAqa+oj0IMM0UqqqRE/j5T9lfXKQSpMENY130jIwxfePO7pTQ56mDP1A37S0bYPUenJDELjJa8p7H25g5xFBOIVHBHKdC+Onm6aht4ZyUSGEx9oREKSJRk+gbJblLJfBFvV23/P+/R3LxZI0yRiGcfKDNghnUcKjvJl8rBUwkhdhTltvYnmZsFiseHp6mm+bWJNHMmbUQMVAoJSauy8Rm4gcmLZtPwDVI5FvHMc54wzZxXK2i41BMfCjbmYyYFnm82aMpWDTNPNmijwVYOZqfWqQitjHh5IazzDhLeMwkmg56REt/WhQKhyGyIrPsowvvvhi9tXu+37qHh3IssBZChKYcgb8o14sS4IjZ+wGRWA4dkDHceTu/m52K4h4RlEUs8XIbrcDgt7sPAOI7gBt2/L4+Mh6vQ5e41Ngj1KQV69ezZ21cRzZrDezEVvkI0XcZrkMc++6rmXRlTM2FFv/Ukru7+/n5/jxpJTIWarrevaGWq1WczYbcai4x+Lzq+t+/vkR7I6k3+j4mSTJvBcjVBD3UMzAkySZfdhjYIzk0rh/YxYYH9NuFzLbNE1pmmZ2dFAyXDbxcTRNw8XFxQycX11dBS7X8UhZFGxWa/q+JZsmgi/KBanWgTP4CeuTg9SiKIMMwXls39PVJ3Z3D7THGjkJNZ0MGZKb/KaUevbtsYTRVdKHUTsAznpGEfx5jAeVpGw2a7aXF5RVTpaHFyQvCvquZ7FakCYp3dDS9S0/+tGfsVqtJ5Jd0AT1CDBdEDd6ixJTJ8dZhFSMZuBXv/47VFWyuroE4zCjmQ3GFovFB63Uc9OySDmoqor1ej3fdjHDiQ6MMRuIZM7o8RPn1Z1za+JNG8u+GORi1tV1gdkb8Y7zQZqLquJcl/eHrpi1WOtmwDVNU071AaUVSZpNB7Tj4uJi3sQ/+tGPZvmFEIL9fj87TUYZyW73ODlLjrRtAwhubm642Gzpu466rnl8fJw5NrHL1HUdt7e3XL+4mW//mDG0bcurV69mNnOSBDKitXbqwOVhEvV0Mdze3nI6BVD58fGJh4cHlssVWZaTpvnEz1LzoYmEy1gGlWU5Zyar5YrDtLejNOV4PM7vT8wI4+sQs6H9fj8H4N1uNxviff7553jveXp6mkmTkYsX/7/dbmdvqnPf8ehUEDvQsZMXaSVKKbqum7vPy6ri9vaWqqq4urqag2mkIKRpynK5pK7rGYuKFUFksHvv2ay3aBVcVZ0LzbH2FKbw9MPIIHsgDPUYx5Gr7Za6DmWvdZbuFAKemSbH/L716d29cURPvsSHxyeaQ83YdoFjMoQW8Sg8ItGE1OV5Pp+UEnRQPnsbsN5p7DzWB/eCzcWW5WaFylLSLCFJgy4tSkmUShj6gVPTsFwuefnyM1YXG8bRcNzXmNFgjcU6gzeGMCVLILyYQEYXaBRmxMjgbNAPI0JK0iRDTwS6KEPpuo7Ly0tev349lwnX19eBKf/0xGq14vXr15OubjlvjKZp5rIwcmRihyU6DmRZNvNNol6vKIo5owh2G3ukXKOUmo3OIgku8nS+/e71vIniRvo+PdQ50fPvA9CNGcEHrs3l5QVu7EgTTZomDGdWI9G4P5YUaZrOso14cIBZMhGfZzi0i/kx1scjj4+Ps20tPGsmY8D/6quvGG2wsw0B5nE+XHd3dzP4u1io+UCfe3HH7PL6+hoQlGXF/f0D63V4vVer9RzclstleO0nQm28PHa7HWVZcnFxMYPBsYzabDZzYIsfm3VrEwN7tVrhvaeuA2YlpeTu7m4OKF9//fX8uKPSIQacmO3EFn/TNB8Mb/Dez3Yr513luBfi5ZGmKWoKmLELCMw8q6j7k1JyOBzmfRkzyfv7e9I0nS/noRvomnbes5GS8/btWxaLBcV2GwQBY4e10PftfHkfj0fqtpvF0H/SIPXuu9coIRj7nr4JwQlrJxLmhDl5D87hJzD82aA9GOZJIZCJCn49KgQupySL7ZrlZk2aZ3OqqxI1vVgwjJb7+wessXzxxY/4yY8DgG6cw3uLMZY8L0AI0jQBbxDjOElsJL3z6LxElwvK9YZqe8Wx62jajlNzYrFcBpsSQis4dKgCO/f29jaQ0yYqf7y9n56e8N5TVdV8o0UGb9w0kUke0+nImbq7u2Oz2cybsW3buXyMqfpyuZizuZht1HX9gfg0ul+e2wD/Q5Yt8LsZ1/P3hE5bLC29GYKY9thSLJbBivfs911cXMwSisjjieQ8rRPyvJiC+Xri3oTgdTrV7PcHJHzAEYqZVCx5g+Ok5ObyBqUUj4+P86GL7eu40WP5EkvLiKvEoBAkP56maUl0ynI1zQkcRsxoSdIkDNTQasrMnnlJkRt0nPyhtNYURTFfGlGIniQJzXSBAtze3s4l4MXFBcXkaS+lnK1RIu4VS/rzKS7RJI84VWkiGnddNxOMIw2hruuZfX6Oe0bicVEUDH3P3e3tHNiilCaOx4q4VWSVr9fr+fdWVTVXGGFvLjnVJ7q2pY+E0NWK5WLBqWnCgAUR5iA4wpj7tgvzKF+8fBW6u/rTbFrgHxGkMiUZh5GuaRAupELGGrwPs7UiBhWdBQIHSs6eMdYb/GRGh5LoPKNcL1luN+RlEWa3JSnZNINP5+k0KiqAa1dXL3n58hWXl1dhysapoyhzrHW8fPEZD/e3zypwN86YlNcpxguUziErUWXFw+FAVpTkUoa5ZpPUIG6ceHicc3z11Vd8++23M78klmKxWxMJd2VZslgsZjAzkvYitSBqqKII95x6AIG6EHlWgfRXsN8/zQz4eOtUVcVyuWS5XPLNt98BHwapc0D/H7OsDSPtT6dTyIgSNQGbQUZSVBVv3rydhaeRI/bu3bu5axhfn+PxNOMbTdNOViH5jM8Nw8B6uaCu6zlriYTDPM/nJoRxdgatzzthq9Vqfg0DDtjNYtvT6TQfqhhwlVL0ncE5H+gi9bPN7jga0jSjLMpwsOSzy2lUC8QS7nA4BC/7rpnxmDdv3sz4T/y+OHoqZkvRJjjinjEDiSsazUVoITLLAxZ0YrFYzGzvCBV47z8IdLHEjdytWGrGSzPu1fi9sZscM7jFIujsuq6bH2M8CzFxiHhWXR8p8xIzBqvmagLgk2n6j7UWj0NqS9O35HmBJqHrB97f34c44dUn0/s+3eO8G0Kd5hzOeYyxc4YUO3fCg3Qu6IG9RCBmXZAHrDVIrSnXi+AxVRXoPCOdXhCpFIlOJhDRAZrV6oIsS1E6CVyjU3ijfvWrn5NkgRX+zdffoISfZ48FCNjhvQNdIXUKaY6uVjSThYtKUlZFjpYSqRS9Gbm/v6dpGj7//HO6rpuBw9hRiWULMHOCYgkXbTRmE7npNospdqz3I3B+Op0mn6g72rb9IGUP5M8HwM+gbmToxlsvMtulVPPG+2OWlBIpJEMfSIxFUs3t8rppKPphJq5Gn6T7+3usDR5XsWsVyqMFp9OJzz77HO8d9/f3PD3tKMuCsqx4+/YNXdex3+9ZLpdcX18HTdhEdpxlOvhZR1mW5Qfjnc7LxO12O2cBESQ/zwpub28R4tlVoizLeQBCURRz4FRaIpEfjA6P3a34PUpK2jabGyNVVc3lb9TDrVarGVeL710MPLH9H4PN6XSaVQbxMcUzEy67Yv739fU1aZrO4veIdV1eXk6+6uFij7ysiMnFkuzly5fc39/PAH1sdBRFMQuWY6UQS7O2bUO37nSa3/cizWmbBikE26nkHYeBoiyxxtAPA+vNkrrbk2QJXnhOzQkpNchAB3LA09T4+H3rk4OUm7y5hQ+H39ghdO3wM29QOYkjtP7R0SLDIQkperZakZYVi4steVViwxQHjPcIpaiPJ3rZsd1csFytAutbJ2RZIABmeZhP7zzUp5bLYk2WZRR5zmq54OspgMQN5nAkWY7XOZ99+RVJWbGrG0Y7Mjw98XA3UhU5eZHPvJE4UBGYcYCqqlitVjw+Ps6UgohDdV03g8rRX+pwOMwbNWYIb9++nTduNMyD5y7SZrOZwdb9fs/9/T3LyRYkCpZfvnxJkiS8efOGw+HA//w3f/M7lIc/NFh5H0TdTdtwOjWUmaZpWi4uNgilUElCUZRzlyc6TK5WK16+fDljF8fjkUW14bNXXzAOIUC/fPEZr1+/RskwsEAKzdPTbm6XV1VF3/fc3NzMGUWSJOhEU1SBhhFb+LHci+Wx1nruwEar3Fj6RMqDFDK4HiRBBxkuF0+SZGF0VRdwII8nkWLuXMVSNDppRquZrms4Ho947+dDHg/909PTbAsc7WniBVaW5WzlAsFXyRjD4XAgjp2K+zBiS8PQ03XtjG0dDgfKspyB7B/96EdAyIBjpnoun4r2wNZa/NQdBWZsK+63WBlE54qYaRlj5i5klOPsncCNQT3hfJit1/c97amZ8b3j4cioRrI0J8tyDnVDmuYTrCLQeMqpNP59S/g/9gr+Yf2wflg/rH/C9Y8HL35YP6wf1g/r/4/rhyD1w/ph/bD+Wa8fgtQP64f1w/pnvX4IUj+sH9YP65/1+iFI/bB+WD+sf9brhyD1w/ph/bD+Wa8fgtQP64f1w/pnvX4IUj+sH9YP65/1+iFI/bB+WD+sf9br/wdxHH9Rdon+ywAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Querying for \"Vehicles\"\n", + "\n", + "retrieved = collection.query(query_texts=[\"vehicles\"], include=['data'], n_results=3)\n", + "for img in retrieved['data'][0]:\n", + " plt.imshow(img)\n", + " plt.axis(\"off\")\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Querying for \"Street Scenes\"\n", + "\n", + "retrieved = collection.query(query_texts=[\"street scene\"], include=['data'], n_results=3)\n", + "for img in retrieved['data'][0]:\n", + " plt.imshow(img)\n", + " plt.axis(\"off\")\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can also query by images directly, by using the `query_images` field in the `collection.query` method." + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Query Image\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from PIL import Image\n", + "import numpy as np\n", + "\n", + "query_image = np.array(Image.open(f\"{IMAGE_FOLDER}/1.jpg\"))\n", + "print(\"Query Image\")\n", + "plt.imshow(query_image)\n", + "plt.axis('off')\n", + "plt.show()\n", + "\n", + "print(\"Results\")\n", + "retrieved = collection.query(query_images=[query_image], include=['data'], n_results=5)\n", + "for img in retrieved['data'][0][1:]:\n", + " plt.imshow(img)\n", + " plt.axis(\"off\")\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And we can query by URI too, by using the `query_uris` field in the `collection.query` method. The URIs we query by don't necessarily have to be in the collection! " + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "query_uri = image_uris[1]\n", + "\n", + "query_result = collection.query(query_uris=query_uri, include=['data'], n_results=5)\n", + "for img in query_result['data'][0][1:]:\n", + " plt.imshow(img)\n", + " plt.axis(\"off\")\n", + " plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## What's Next? \n", + "\n", + "Multi-modal retrieval is powerful extension to basic text retrieval. As AI systems begin to understand more types of data, like images, audio, and video, we can store and query them alongside documents and text to build even more powerful applications. \n", + "\n", + "Join our community to learn more and get help with your projects: [Discord](https://discord.gg/MMeYNTmh3x) | [Twitter](https://twitter.com/trychroma)\n", + "\n", + "Contribute to Chroma, including new multi-modal embedding functions and data loaders on [GitHub](https://github.com/chroma-core/chroma)\n", + "\n", + "We are [hiring](https://trychroma.notion.site/careers-chroma-9d017c3007c7478ebd85bad854101497?pvs=4)! " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "chroma", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/observability/README.md b/examples/observability/README.md new file mode 100644 index 0000000000000000000000000000000000000000..d81f8911484b858a547d086257141163dad8ff78 --- /dev/null +++ b/examples/observability/README.md @@ -0,0 +1,10 @@ +# Observability + +## Local Observability Stack + +To run the Chroma with local observability stack (OpenTelemetry + Zipkin), +run the following command from the root of the repository: + +```bash +docker compose -f examples/observability/docker-compose.local-observability.yml up --build -d +``` diff --git a/examples/observability/docker-compose.local-observability.yml b/examples/observability/docker-compose.local-observability.yml new file mode 100644 index 0000000000000000000000000000000000000000..173d8875a9fcb97fc672fa77b2588f94b11eabc5 --- /dev/null +++ b/examples/observability/docker-compose.local-observability.yml @@ -0,0 +1,52 @@ +version: '3.9' +networks: + net: + +services: + zipkin: + image: openzipkin/zipkin + ports: + - "9411:9411" # you can access Zipkin UI at http://localhost:9411 + depends_on: [otel-collector] + networks: + - net + otel-collector: + image: otel/opentelemetry-collector-contrib + command: ["--config=/etc/otel-collector-config.yaml"] + volumes: + - ${PWD}/examples/observability/otel-collector-config.yaml:/etc/otel-collector-config.yaml + ports: + - "4317:4317" # OTLP + - "55681:55681" # Legacy + networks: + - net + server: + image: server + build: + context: ${PWD} + dockerfile: Dockerfile + volumes: + - ${PWD}/:/chroma + # Be aware that indexed data are located in "/chroma/chroma/" + # Default configuration for persist_directory in chromadb/config.py + command: uvicorn chromadb.app:app --reload --workers 1 --host 0.0.0.0 --port 8000 --log-config chromadb/log_config.yml + environment: + - IS_PERSISTENT=TRUE + - CHROMA_SERVER_AUTH_PROVIDER=${CHROMA_SERVER_AUTH_PROVIDER} + - CHROMA_SERVER_AUTH_CREDENTIALS_FILE=${CHROMA_SERVER_AUTH_CREDENTIALS_FILE} + - CHROMA_SERVER_AUTH_CREDENTIALS=${CHROMA_SERVER_AUTH_CREDENTIALS} + - CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=${CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER} + - PERSIST_DIRECTORY=${PERSIST_DIRECTORY:-/chroma/chroma} + - CHROMA_OTEL_COLLECTION_ENDPOINT=http://otel-collector:4317/ + - CHROMA_OTEL_EXPORTER_HEADERS=${CHROMA_OTEL_EXPORTER_HEADERS} + - CHROMA_OTEL_SERVICE_NAME=${CHROMA_OTEL_SERVICE_NAME:-chroma} + - CHROMA_OTEL_GRANULARITY=${CHROMA_OTEL_GRANULARITY:-all} + ports: + - 8000:8000 + depends_on: [otel-collector] + networks: + - net + +volumes: + backups: + driver: local diff --git a/examples/observability/otel-collector-config.yaml b/examples/observability/otel-collector-config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..cce02b6bf5c8cfdded1852e3270372f164c2ccfc --- /dev/null +++ b/examples/observability/otel-collector-config.yaml @@ -0,0 +1,16 @@ +receivers: + otlp: + protocols: + grpc: + http: + +exporters: + logging: + zipkin: + endpoint: "http://zipkin:9411/api/v2/spans" + +service: + pipelines: + traces: + receivers: [otlp] + exporters: [zipkin] diff --git a/examples/server_side_embeddings/huggingface/docker-compose.yml b/examples/server_side_embeddings/huggingface/docker-compose.yml new file mode 100644 index 0000000000000000000000000000000000000000..d7c05b16f78ff70688aa757b3c6f90133ca98920 --- /dev/null +++ b/examples/server_side_embeddings/huggingface/docker-compose.yml @@ -0,0 +1,48 @@ +version: '3.9' + +networks: + net: + driver: bridge + +services: + server: + image: server + build: + context: ${PWD} + dockerfile: Dockerfile + volumes: + - ${PWD}/:/chroma + # Be aware that indexed data are located in "/chroma/chroma/" + # Default configuration for persist_directory in chromadb/config.py + command: uvicorn chromadb.app:app --reload --workers 1 --host 0.0.0.0 --port 8000 --log-config chromadb/log_config.yml --timeout-keep-alive 30 + environment: + - IS_PERSISTENT=TRUE + - CHROMA_SERVER_AUTH_PROVIDER=${CHROMA_SERVER_AUTH_PROVIDER} + - CHROMA_SERVER_AUTH_CREDENTIALS_FILE=${CHROMA_SERVER_AUTH_CREDENTIALS_FILE} + - CHROMA_SERVER_AUTH_CREDENTIALS=${CHROMA_SERVER_AUTH_CREDENTIALS} + - CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=${CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER} + - PERSIST_DIRECTORY=${PERSIST_DIRECTORY:-/chroma/chroma} + - CHROMA_OTEL_EXPORTER_ENDPOINT=${CHROMA_OTEL_EXPORTER_ENDPOINT} + - CHROMA_OTEL_EXPORTER_HEADERS=${CHROMA_OTEL_EXPORTER_HEADERS} + - CHROMA_OTEL_SERVICE_NAME=${CHROMA_OTEL_SERVICE_NAME} + - CHROMA_OTEL_GRANULARITY=${CHROMA_OTEL_GRANULARITY} + - CHROMA_SERVER_NOFILE=${CHROMA_SERVER_NOFILE} + ports: + - 8000:8000 + networks: + - net + embedding_server: + image: ${EMBEDDING_IMAGE:-ghcr.io/huggingface/text-embeddings-inference:cpu-0.3.0} #default image with CPU support + command: --model-id ${ST_MODEL:-BAAI/bge-small-en-v1.5} --revision ${ST_MODEL_REVISION:-main} #configure model and model revision paramters + ports: + - 8001:80 + platform: linux/amd64 #right now the images are only available for linux + networks: + - net + volumes: + - hfmodels:/data #by default we create a volume for the models. +volumes: + backups: + driver: local + hfmodels: + driver: local diff --git a/examples/server_side_embeddings/huggingface/test.ipynb b/examples/server_side_embeddings/huggingface/test.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..beb26ccf8e97bcd1502be5730316caf1bb9c6b85 --- /dev/null +++ b/examples/server_side_embeddings/huggingface/test.ipynb @@ -0,0 +1,94 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Prior to running the below make sure that you have an HF server running:\n", + "\n", + "You can run:\n", + "\n", + "```bash\n", + "docker compose -f examples/server_side_embeddings/huggingface/docker-compose.yml up -d\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/Users/tazarov/experiments/chroma-experiments/1367_hugging_face_embedding_server\n" + ] + } + ], + "source": [ + "%cd ../../../" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'ids': [['test']],\n", + " 'distances': [[0.0]],\n", + " 'embeddings': None,\n", + " 'metadatas': [[None]],\n", + " 'documents': [['test']],\n", + " 'uris': None,\n", + " 'data': None}" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import chromadb\n", + "\n", + "from chromadb.utils.embedding_functions import HuggingFaceEmbeddingServer\n", + "\n", + "\n", + "ef = HuggingFaceEmbeddingServer(url=\"http://localhost:8001/embed\")\n", + "\n", + "client = chromadb.HttpClient(\"http://localhost:8000/\")\n", + "\n", + "col=client.get_or_create_collection(\"test\",embedding_function=ef)\n", + "\n", + "col.add(documents=[\"test\"],ids=[\"test\"])\n", + "\n", + "col.query(query_texts=[\"test\"])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.2" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/use_with/cohere/cohere_js.js b/examples/use_with/cohere/cohere_js.js new file mode 100644 index 0000000000000000000000000000000000000000..7fe8669160299b0a9ee44fdda21d0da507057224 --- /dev/null +++ b/examples/use_with/cohere/cohere_js.js @@ -0,0 +1,81 @@ +/* + +## Cohere + +First run Chroma + +``` +git clone git@github.com:chroma-core/chroma.git +cd chroma +chroma run --path /chroma_db_path +``` + +Then install chroma and cohere +``` +npm install chromadb +npm install cohere-ai +``` + +Then set your API KEY + +### Basic Example + +*/ + +// import chroma +const chroma = require("chromadb"); +const cohere = require("cohere-ai"); + +const main = async () => { + + const COHERE_API_KEY = "COHERE_API_KEY"; + + const client = new chroma.ChromaClient({ path: "http://localhost:8000" }); + await client.reset(); + + const cohereAIEmbedder = new chroma.CohereEmbeddingFunction({ cohere_api_key: COHERE_API_KEY }); + + const collection = await client.createCollection({ + name: "cohere_js", + embeddingFunction: cohereAIEmbedder + }); + + await collection.add({ + ids: ["1", "2", "3"], + documents: ["I like apples", "I like bananas", "I like oranges"], + metadatas: [{ "fruit": "apple" }, { "fruit": "banana" }, { "fruit": "orange" }], + }); + + console.log(await collection.query({ + queryTexts: ["citrus"], + nResults: 1 + })); + + // Multilingual Example + + const cohereAIMulitlingualEmbedder = new chroma.CohereEmbeddingFunction({ cohere_api_key: COHERE_API_KEY, model: "multilingual-22-12" }); + + const collection_multilingual = await client.createCollection({ + name: "cohere_js_multilingual", + embeddingFunction: cohereAIMulitlingualEmbedder + }); + + // # 나는 오렌지를 좋아한다 is "I like oranges" in Korean + multilingual_texts = ['Hello from Cohere!', 'مرحبًا من كوهير!', + 'Hallo von Cohere!', 'Bonjour de Cohere!', + '¡Hola desde Cohere!', 'Olá do Cohere!', + 'Ciao da Cohere!', '您好,来自 Cohere!', + 'कोहेरे से नमस्ते!', '나는 오렌지를 좋아한다'] + + let ids = Array.from({ length: multilingual_texts.length }, (_, i) => String(i)); + + await collection.add({ + ids: ids, + documents: multilingual_texts + }) + + console.log(await collection.query({ queryTexts: ["citrus"], nResults: 1 })) + +} + +main(); diff --git a/examples/use_with/cohere/cohere_python.ipynb b/examples/use_with/cohere/cohere_python.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..4969ec5c26d60cad2368990489b9642332dcf182 --- /dev/null +++ b/examples/use_with/cohere/cohere_python.ipynb @@ -0,0 +1,151 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Cohere\n", + "\n", + "This notebook demonstrates how to use Cohere Embeddings with Chroma.\n", + "\n", + "If you have not already, [create a Cohere account](https://dashboard.cohere.ai/welcome/register) and get your API Key.\n", + "\n", + "First a basic example:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.1.2\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49m/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip\u001b[0m\n", + "\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.1.2\u001b[0m\n", + "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49m/Library/Developer/CommandLineTools/usr/bin/python3 -m pip install --upgrade pip\u001b[0m\n" + ] + } + ], + "source": [ + "! pip install chromadb --quiet\n", + "! pip install cohere --quiet" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import getpass\n", + "\n", + "os.environ[\"COHERE_API_KEY\"] = getpass.getpass(\"Cohere API Key:\")" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'ids': [['3']], 'embeddings': None, 'documents': [['I like oranges']], 'metadatas': [[{'fruit': 'orange'}]], 'distances': [[6729.3291015625]]}\n" + ] + } + ], + "source": [ + "import chromadb\n", + "from chromadb.utils import embedding_functions\n", + "\n", + "cohere_ef = embedding_functions.CohereEmbeddingFunction(api_key=os.environ[\"COHERE_API_KEY\"], model_name=\"large\")\n", + "\n", + "client = chromadb.Client()\n", + "collection = client.create_collection(\"cohere_python\", embedding_function=cohere_ef)\n", + "\n", + "collection.add(\n", + " ids=[\"1\", \"2\", \"3\"],\n", + " documents=[\"I like apples\", \"I like bananas\", \"I like oranges\"],\n", + " metadatas=[{\"fruit\": \"apple\"}, {\"fruit\": \"banana\"}, {\"fruit\": \"orange\"}],\n", + ")\n", + "\n", + "print(collection.query(query_texts=[\"citrus\"], n_results=1))\n" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Multilingual Example\n", + "\n", + "Cohere can support many languages! In this example we store text in many languages, and then query in English." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'ids': [['9']], 'embeddings': None, 'documents': [['나는 오렌지를 좋아한다']], 'metadatas': [[None]], 'distances': [[30.728900909423828]]}\n" + ] + } + ], + "source": [ + "cohere_mutlilingual = embedding_functions.CohereEmbeddingFunction(\n", + " api_key=os.environ[\"COHERE_API_KEY\"], \n", + " model_name=\"multilingual-22-12\")\n", + "\n", + "# 나는 오렌지를 좋아한다 is \"I like oranges\" in Korean\n", + "multilingual_texts = [ 'Hello from Cohere!', 'مرحبًا من كوهير!', \n", + " 'Hallo von Cohere!', 'Bonjour de Cohere!', \n", + " '¡Hola desde Cohere!', 'Olá do Cohere!', \n", + " 'Ciao da Cohere!', '您好,来自 Cohere!',\n", + " 'कोहेरे से नमस्ते!', '나는 오렌지를 좋아한다' ]\n", + "\n", + "collection = client.create_collection(\"cohere_multilingual\", embedding_function=cohere_mutlilingual)\n", + "\n", + "collection.add(\n", + " ids=[str(i) for i in range(len(multilingual_texts))],\n", + " documents=multilingual_texts\n", + ")\n", + "\n", + "print(collection.query(query_texts=[\"citrus\"], n_results=1))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/examples/use_with/cohere/package.json b/examples/use_with/cohere/package.json new file mode 100644 index 0000000000000000000000000000000000000000..5762f8fba99498c832b08050d3317cad5e277ed4 --- /dev/null +++ b/examples/use_with/cohere/package.json @@ -0,0 +1,6 @@ +{ + "dependencies": { + "chromadb": "^1.5.3", + "cohere-ai": "^6.2.2" + } +} diff --git a/go/coordinator/Dockerfile b/go/coordinator/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..a86f5cc258f084970ab8bfb1f3c2e59d2aa6d1c7 --- /dev/null +++ b/go/coordinator/Dockerfile @@ -0,0 +1,31 @@ +FROM golang:1.20-alpine3.18 as build + +RUN apk add --no-cache make git build-base bash + +ENV PATH=$PATH:/go/bin +ADD ./go/coordinator /src/chroma-coordinator + +RUN cd /src/chroma-coordinator \ + && make + +FROM alpine:3.17.3 + +RUN apk add --no-cache bash bash-completion jq findutils + +# As of 6 Dec 2023, the atlas package isn't in Alpine's main package manager, only +# testing. So we have to add the testing repository to get it. +RUN apk add \ + --no-cache \ + --repository http://dl-cdn.alpinelinux.org/alpine/edge/testing \ + --repository http://dl-cdn.alpinelinux.org/alpine/edge/main \ + atlas + +RUN mkdir /chroma-coordinator +WORKDIR /chroma-coordinator + +COPY --from=build /src/chroma-coordinator/bin/chroma /chroma-coordinator/bin/chroma +ENV PATH=$PATH:/chroma-coordinator/bin + +COPY --from=build /src/chroma-coordinator/migrations /chroma-coordinator/migrations + +CMD /bin/bash diff --git a/go/coordinator/Makefile b/go/coordinator/Makefile new file mode 100644 index 0000000000000000000000000000000000000000..8fb52e4bb748c3528a591b61bb8a360bc4cff51d --- /dev/null +++ b/go/coordinator/Makefile @@ -0,0 +1,16 @@ +.PHONY: build +build: + go build -v -o bin/chroma ./cmd + +test: build + go test -cover -race ./... + +lint: + #brew install golangci-lint + golangci-lint run + +clean: + rm -f bin/chroma + +docker: + docker build -t chroma-coordinator:latest . diff --git a/go/coordinator/atlas.hcl b/go/coordinator/atlas.hcl new file mode 100644 index 0000000000000000000000000000000000000000..2883c58d65e82f14a4bc8c30c62b1130228baca1 --- /dev/null +++ b/go/coordinator/atlas.hcl @@ -0,0 +1,24 @@ +data "external_schema" "gorm" { + program = [ + "go", + "run", + "-mod=mod", + "ariga.io/atlas-provider-gorm", + "load", + "--path", "./internal/metastore/db/dbmodel", + "--dialect", "postgres", + ] +} + +env "gorm" { + src = data.external_schema.gorm.url + dev = "postgres://localhost:5432/dev?sslmode=disable" + migration { + dir = "file://migrations" + } + format { + migrate { + diff = "{{ sql . \" \" }}" + } + } +} diff --git a/go/coordinator/cmd/flag/flag.go b/go/coordinator/cmd/flag/flag.go new file mode 100644 index 0000000000000000000000000000000000000000..4ca7960dbc7f356c24809bc4dc83cf4fddd7b8ea --- /dev/null +++ b/go/coordinator/cmd/flag/flag.go @@ -0,0 +1,15 @@ +package flag + +import ( + "fmt" + + "github.com/spf13/cobra" +) + +const ( + DefaultGRPCPort = 50051 +) + +func GRPCAddr(cmd *cobra.Command, conf *string) { + cmd.Flags().StringVarP(conf, "grpc-addr", "g", fmt.Sprintf("0.0.0.0:%d", DefaultGRPCPort), "GRPC service bind address") +} diff --git a/go/coordinator/cmd/grpccoordinator/cmd.go b/go/coordinator/cmd/grpccoordinator/cmd.go new file mode 100644 index 0000000000000000000000000000000000000000..8859790b56c879eb6f421d6252d790d654a4984c --- /dev/null +++ b/go/coordinator/cmd/grpccoordinator/cmd.go @@ -0,0 +1,64 @@ +package grpccoordinator + +import ( + "io" + "time" + + "github.com/chroma/chroma-coordinator/cmd/flag" + "github.com/chroma/chroma-coordinator/internal/grpccoordinator" + "github.com/chroma/chroma-coordinator/internal/grpccoordinator/grpcutils" + "github.com/chroma/chroma-coordinator/internal/utils" + "github.com/spf13/cobra" +) + +var ( + conf = grpccoordinator.Config{ + GrpcConfig: &grpcutils.GrpcConfig{}, + } + + Cmd = &cobra.Command{ + Use: "coordinator", + Short: "Start a coordinator", + Long: `Long description`, + Run: exec, + } +) + +func init() { + + // GRPC + flag.GRPCAddr(Cmd, &conf.GrpcConfig.BindAddress) + + // System Catalog + Cmd.Flags().StringVar(&conf.SystemCatalogProvider, "system-catalog-provider", "memory", "System catalog provider") + Cmd.Flags().StringVar(&conf.Username, "username", "root", "MetaTable username") + Cmd.Flags().StringVar(&conf.Password, "password", "", "MetaTable password") + Cmd.Flags().StringVar(&conf.Address, "db-address", "127.0.0.1", "MetaTable db address") + Cmd.Flags().IntVar(&conf.Port, "db-port", 5432, "MetaTable db port") + Cmd.Flags().StringVar(&conf.DBName, "db-name", "", "MetaTable db name") + Cmd.Flags().IntVar(&conf.MaxIdleConns, "max-idle-conns", 10, "MetaTable max idle connections") + Cmd.Flags().IntVar(&conf.MaxOpenConns, "max-open-conns", 10, "MetaTable max open connections") + + // Pulsar + Cmd.Flags().StringVar(&conf.PulsarAdminURL, "pulsar-admin-url", "http://localhost:8080", "Pulsar admin url") + Cmd.Flags().StringVar(&conf.PulsarURL, "pulsar-url", "pulsar://localhost:6650", "Pulsar url") + Cmd.Flags().StringVar(&conf.PulsarTenant, "pulsar-tenant", "default", "Pulsar tenant") + Cmd.Flags().StringVar(&conf.PulsarNamespace, "pulsar-namespace", "default", "Pulsar namespace") + + // Notification + Cmd.Flags().StringVar(&conf.NotificationStoreProvider, "notification-store-provider", "memory", "Notification store provider") + Cmd.Flags().StringVar(&conf.NotifierProvider, "notifier-provider", "memory", "Notifier provider") + Cmd.Flags().StringVar(&conf.NotificationTopic, "notification-topic", "chroma-notification", "Notification topic") + + // Memberlist + Cmd.Flags().StringVar(&conf.KubernetesNamespace, "kubernetes-namespace", "chroma", "Kubernetes namespace") + Cmd.Flags().StringVar(&conf.WorkerMemberlistName, "worker-memberlist-name", "worker-memberlist", "Worker memberlist name") + Cmd.Flags().StringVar(&conf.AssignmentPolicy, "assignment-policy", "rendezvous", "Assignment policy") + Cmd.Flags().DurationVar(&conf.WatchInterval, "watch-interval", 60*time.Second, "Watch interval") +} + +func exec(*cobra.Command, []string) { + utils.RunProcess(func() (io.Closer, error) { + return grpccoordinator.New(conf) + }) +} diff --git a/go/coordinator/cmd/main.go b/go/coordinator/cmd/main.go new file mode 100644 index 0000000000000000000000000000000000000000..0b7cfa7b54d7cf112169a77518cf72b932f988e7 --- /dev/null +++ b/go/coordinator/cmd/main.go @@ -0,0 +1,37 @@ +package main + +import ( + "fmt" + "os" + + "github.com/chroma/chroma-coordinator/cmd/grpccoordinator" + "github.com/chroma/chroma-coordinator/internal/utils" + "github.com/rs/zerolog" + "github.com/spf13/cobra" + "go.uber.org/automaxprocs/maxprocs" +) + +var ( + rootCmd = &cobra.Command{ + Use: "chroma", + Short: "Chroma root command", + Long: `Chroma root command`, + } +) + +func init() { + rootCmd.AddCommand(grpccoordinator.Cmd) +} + +func main() { + utils.LogLevel = zerolog.DebugLevel + utils.ConfigureLogger() + if _, err := maxprocs.Set(); err != nil { + _, _ = fmt.Fprintln(os.Stderr, err) + os.Exit(1) + } + if err := rootCmd.Execute(); err != nil { + _, _ = fmt.Fprintln(os.Stderr, err) + os.Exit(1) + } +} diff --git a/go/coordinator/go.mod b/go/coordinator/go.mod new file mode 100644 index 0000000000000000000000000000000000000000..93b04935f57f67bdfe2ba4e084fef48670a99ed6 --- /dev/null +++ b/go/coordinator/go.mod @@ -0,0 +1,112 @@ +module github.com/chroma/chroma-coordinator + +go 1.20 + +require ( + ariga.io/atlas-provider-gorm v0.1.1 + github.com/apache/pulsar-client-go v0.9.1-0.20231030094548-620ecf4addfb + github.com/google/uuid v1.3.1 + github.com/pingcap/log v1.1.0 + github.com/rs/zerolog v1.31.0 + github.com/spf13/cobra v1.7.0 + github.com/stretchr/testify v1.8.4 + go.uber.org/automaxprocs v1.5.3 + go.uber.org/zap v1.26.0 + google.golang.org/grpc v1.58.3 + google.golang.org/protobuf v1.31.0 + gorm.io/driver/sqlite v1.5.4 + gorm.io/gorm v1.25.5 + k8s.io/apimachinery v0.28.3 + k8s.io/client-go v0.28.3 + pgregory.net/rapid v1.1.0 +) + +require ( + github.com/99designs/go-keychain v0.0.0-20191008050251-8e49817e8af4 // indirect + github.com/99designs/keyring v1.2.1 // indirect + github.com/AthenZ/athenz v1.10.39 // indirect + github.com/DataDog/zstd v1.5.0 // indirect + github.com/ardielle/ardielle-go v1.5.2 // indirect + github.com/beorn7/perks v1.0.1 // indirect + github.com/bits-and-blooms/bitset v1.4.0 // indirect + github.com/cespare/xxhash/v2 v2.2.0 // indirect + github.com/danieljoos/wincred v1.1.2 // indirect + github.com/dvsekhvalnov/jose2go v1.5.0 // indirect + github.com/godbus/dbus v0.0.0-20190726142602-4481cbc300e2 // indirect + github.com/golang-jwt/jwt v3.2.1+incompatible // indirect + github.com/golang/snappy v0.0.1 // indirect + github.com/gsterjov/go-libsecret v0.0.0-20161001094733-a6f4afe4910c // indirect + github.com/klauspost/compress v1.14.4 // indirect + github.com/linkedin/goavro/v2 v2.9.8 // indirect + github.com/matttproud/golang_protobuf_extensions v1.0.1 // indirect + github.com/mtibben/percent v0.2.1 // indirect + github.com/pierrec/lz4 v2.0.5+incompatible // indirect + github.com/prometheus/client_golang v1.11.1 // indirect + github.com/prometheus/client_model v0.2.0 // indirect + github.com/prometheus/common v0.26.0 // indirect + github.com/prometheus/procfs v0.6.0 // indirect + github.com/sirupsen/logrus v1.8.1 // indirect + go.uber.org/atomic v1.9.0 // indirect + golang.org/x/mod v0.11.0 // indirect + gorm.io/driver/mysql v1.5.2 // indirect +) + +require ( + ariga.io/atlas-go-sdk v0.1.1-0.20231001054405-7edfcfc14f1c // indirect + github.com/davecgh/go-spew v1.1.1 // indirect + github.com/emicklei/go-restful/v3 v3.9.0 // indirect + github.com/evanphx/json-patch v4.12.0+incompatible // indirect + github.com/go-logr/logr v1.2.4 // indirect + github.com/go-openapi/jsonpointer v0.19.6 // indirect + github.com/go-openapi/jsonreference v0.20.2 // indirect + github.com/go-openapi/swag v0.22.3 // indirect + github.com/go-sql-driver/mysql v1.7.1 // indirect + github.com/gogo/protobuf v1.3.2 // indirect + github.com/golang/protobuf v1.5.3 // indirect + github.com/google/gnostic-models v0.6.8 // indirect + github.com/google/go-cmp v0.5.9 // indirect + github.com/google/gofuzz v1.2.0 // indirect + github.com/inconshreveable/mousetrap v1.1.0 // indirect + github.com/jackc/pgpassfile v1.0.0 // indirect + github.com/jackc/pgservicefile v0.0.0-20221227161230-091c0ba34f0a // indirect + github.com/jackc/pgx/v5 v5.3.1 // indirect + github.com/jinzhu/inflection v1.0.0 // indirect + github.com/jinzhu/now v1.1.5 // indirect + github.com/josharian/intern v1.0.0 // indirect + github.com/json-iterator/go v1.1.12 // indirect + github.com/mailru/easyjson v0.7.7 // indirect + github.com/mattn/go-colorable v0.1.13 // indirect + github.com/mattn/go-isatty v0.0.19 // indirect + github.com/mattn/go-sqlite3 v1.14.17 // indirect + github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect + github.com/modern-go/reflect2 v1.0.2 // indirect + github.com/munnerz/goautoneg v0.0.0-20191010083416-a7dc8b61c822 // indirect + github.com/pkg/errors v0.9.1 // indirect + github.com/pmezard/go-difflib v1.0.0 // indirect + github.com/rogpeppe/go-internal v1.11.0 // indirect + github.com/spaolacci/murmur3 v1.1.0 + github.com/spf13/pflag v1.0.5 // indirect + github.com/stretchr/objx v0.5.1 // indirect + go.uber.org/multierr v1.11.0 // indirect + golang.org/x/crypto v0.15.0 // indirect + golang.org/x/net v0.18.0 // indirect + golang.org/x/oauth2 v0.10.0 // indirect + golang.org/x/sys v0.14.0 // indirect + golang.org/x/term v0.14.0 // indirect + golang.org/x/text v0.14.0 // indirect + golang.org/x/time v0.3.0 // indirect + google.golang.org/appengine v1.6.7 // indirect + google.golang.org/genproto/googleapis/rpc v0.0.0-20231016165738-49dd2c1f3d0b // indirect + gopkg.in/inf.v0 v0.9.1 // indirect + gopkg.in/natefinch/lumberjack.v2 v2.2.1 // indirect + gopkg.in/yaml.v2 v2.4.0 // indirect + gopkg.in/yaml.v3 v3.0.1 // indirect + gorm.io/driver/postgres v1.5.2 + k8s.io/api v0.28.3 + k8s.io/klog/v2 v2.100.1 // indirect + k8s.io/kube-openapi v0.0.0-20230717233707-2695361300d9 // indirect + k8s.io/utils v0.0.0-20230406110748-d93618cff8a2 // indirect + sigs.k8s.io/json v0.0.0-20221116044647-bc3834ca7abd // indirect + sigs.k8s.io/structured-merge-diff/v4 v4.2.3 // indirect + sigs.k8s.io/yaml v1.3.0 // indirect +) diff --git a/go/coordinator/go.sum b/go/coordinator/go.sum new file mode 100644 index 0000000000000000000000000000000000000000..15390626451c00f255729d38b66bbcdbd1ade283 --- /dev/null +++ b/go/coordinator/go.sum @@ -0,0 +1,424 @@ +ariga.io/atlas-go-sdk v0.1.1-0.20231001054405-7edfcfc14f1c h1:jvi4KB/7DmYYT+Wy2TFImccaBU0+dw7V8Un67NDGuio= +ariga.io/atlas-go-sdk v0.1.1-0.20231001054405-7edfcfc14f1c/go.mod h1:MLvZ9QwZx1KhI6+8XguxHPUPm0/PTTUr46S5GQAe9WI= +ariga.io/atlas-provider-gorm v0.1.1 h1:Y0VsZCQkXJRYIJxenn2BM6sW2u9SkTca5mLvJumqrgE= +ariga.io/atlas-provider-gorm v0.1.1/go.mod h1:jb8uYcN+ul8Nf7OVzi5Vd2y+SQXrI4dHYBEUCiCi/6Q= +cloud.google.com/go v0.34.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw= +github.com/99designs/go-keychain v0.0.0-20191008050251-8e49817e8af4 h1:/vQbFIOMbk2FiG/kXiLl8BRyzTWDw7gX/Hz7Dd5eDMs= +github.com/99designs/go-keychain v0.0.0-20191008050251-8e49817e8af4/go.mod h1:hN7oaIRCjzsZ2dE+yG5k+rsdt3qcwykqK6HVGcKwsw4= +github.com/99designs/keyring v1.2.1 h1:tYLp1ULvO7i3fI5vE21ReQuj99QFSs7lGm0xWyJo87o= +github.com/99designs/keyring v1.2.1/go.mod h1:fc+wB5KTk9wQ9sDx0kFXB3A0MaeGHM9AwRStKOQ5vOA= +github.com/AthenZ/athenz v1.10.39 h1:mtwHTF/v62ewY2Z5KWhuZgVXftBej1/Tn80zx4DcawY= +github.com/AthenZ/athenz v1.10.39/go.mod h1:3Tg8HLsiQZp81BJY58JBeU2BR6B/H4/0MQGfCwhHNEA= +github.com/BurntSushi/toml v0.3.1/go.mod h1:xHWCNGjB5oqiDr8zfno3MHue2Ht5sIBksp03qcyfWMU= +github.com/DataDog/zstd v1.5.0 h1:+K/VEwIAaPcHiMtQvpLD4lqW7f0Gk3xdYZmI1hD+CXo= +github.com/DataDog/zstd v1.5.0/go.mod h1:g4AWEaM3yOg3HYfnJ3YIawPnVdXJh9QME85blwSAmyw= +github.com/alecthomas/template v0.0.0-20160405071501-a0175ee3bccc/go.mod h1:LOuyumcjzFXgccqObfd/Ljyb9UuFJ6TxHnclSeseNhc= +github.com/alecthomas/template v0.0.0-20190718012654-fb15b899a751/go.mod h1:LOuyumcjzFXgccqObfd/Ljyb9UuFJ6TxHnclSeseNhc= +github.com/alecthomas/units v0.0.0-20151022065526-2efee857e7cf/go.mod h1:ybxpYRFXyAe+OPACYpWeL0wqObRcbAqCMya13uyzqw0= +github.com/alecthomas/units v0.0.0-20190717042225-c3de453c63f4/go.mod h1:ybxpYRFXyAe+OPACYpWeL0wqObRcbAqCMya13uyzqw0= +github.com/alecthomas/units v0.0.0-20190924025748-f65c72e2690d/go.mod h1:rBZYJk541a8SKzHPHnH3zbiI+7dagKZ0cgpgrD7Fyho= +github.com/apache/pulsar-client-go v0.9.1-0.20231030094548-620ecf4addfb h1:8c0g4Cu5LHyKuRseT9mJDaCFQZOm2LBUjD3FVesdEJw= +github.com/apache/pulsar-client-go v0.9.1-0.20231030094548-620ecf4addfb/go.mod h1:Ea/yiZA7plgiaWRyOuO1B0k5/hjpl1thmiKig+D9PBQ= +github.com/ardielle/ardielle-go v1.5.2 h1:TilHTpHIQJ27R1Tl/iITBzMwiUGSlVfiVhwDNGM3Zj4= +github.com/ardielle/ardielle-go v1.5.2/go.mod h1:I4hy1n795cUhaVt/ojz83SNVCYIGsAFAONtv2Dr7HUI= +github.com/ardielle/ardielle-tools v1.5.4/go.mod h1:oZN+JRMnqGiIhrzkRN9l26Cej9dEx4jeNG6A+AdkShk= +github.com/aws/aws-sdk-go v1.32.6/go.mod h1:5zCpMtNQVjRREroY7sYe8lOMRSxkhG6MZveU8YkpAk0= +github.com/benbjohnson/clock v1.1.0/go.mod h1:J11/hYXuz8f4ySSvYwY0FKfm+ezbsZBKZxNJlLklBHA= +github.com/beorn7/perks v0.0.0-20180321164747-3a771d992973/go.mod h1:Dwedo/Wpr24TaqPxmxbtue+5NUziq4I4S80YR8gNf3Q= +github.com/beorn7/perks v1.0.0/go.mod h1:KWe93zE9D1o94FZ5RNwFwVgaQK1VOXiVxmqh+CedLV8= +github.com/beorn7/perks v1.0.1 h1:VlbKKnNfV8bJzeqoa4cOKqO6bYr3WgKZxO8Z16+hsOM= +github.com/beorn7/perks v1.0.1/go.mod h1:G2ZrVWU2WbWT9wwq4/hrbKbnv/1ERSJQ0ibhJ6rlkpw= +github.com/bits-and-blooms/bitset v1.4.0 h1:+YZ8ePm+He2pU3dZlIZiOeAKfrBkXi1lSrXJ/Xzgbu8= +github.com/bits-and-blooms/bitset v1.4.0/go.mod h1:gIdJ4wp64HaoK2YrL1Q5/N7Y16edYb8uY+O0FJTyyDA= +github.com/cespare/xxhash/v2 v2.1.1/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs= +github.com/cespare/xxhash/v2 v2.2.0 h1:DC2CZ1Ep5Y4k3ZQ899DldepgrayRUGE6BBZ/cd9Cj44= +github.com/cespare/xxhash/v2 v2.2.0/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs= +github.com/coreos/go-systemd/v22 v22.5.0/go.mod h1:Y58oyj3AT4RCenI/lSvhwexgC+NSVTIJ3seZv2GcEnc= +github.com/cpuguy83/go-md2man/v2 v2.0.2/go.mod h1:tgQtvFlXSQOSOSIRvRPT7W67SCa46tRHOmNcaadrF8o= +github.com/creack/pty v1.1.9/go.mod h1:oKZEueFk5CKHvIhNR5MUki03XCEU+Q6VDXinZuGJ33E= +github.com/danieljoos/wincred v1.1.2 h1:QLdCxFs1/Yl4zduvBdcHB8goaYk9RARS2SgLLRuAyr0= +github.com/danieljoos/wincred v1.1.2/go.mod h1:GijpziifJoIBfYh+S7BbkdUTU4LfM+QnGqR5Vl2tAx0= +github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c= +github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38= +github.com/dimfeld/httptreemux v5.0.1+incompatible h1:Qj3gVcDNoOthBAqftuD596rm4wg/adLLz5xh5CmpiCA= +github.com/dimfeld/httptreemux v5.0.1+incompatible/go.mod h1:rbUlSV+CCpv/SuqUTP/8Bk2O3LyUV436/yaRGkhP6Z0= +github.com/dvsekhvalnov/jose2go v1.5.0 h1:3j8ya4Z4kMCwT5nXIKFSV84YS+HdqSSO0VsTQxaLAeM= +github.com/dvsekhvalnov/jose2go v1.5.0/go.mod h1:QsHjhyTlD/lAVqn/NSbVZmSCGeDehTB/mPZadG+mhXU= +github.com/emicklei/go-restful/v3 v3.9.0 h1:XwGDlfxEnQZzuopoqxwSEllNcCOM9DhhFyhFIIGKwxE= +github.com/emicklei/go-restful/v3 v3.9.0/go.mod h1:6n3XBCmQQb25CM2LCACGz8ukIrRry+4bhvbpWn3mrbc= +github.com/evanphx/json-patch v4.12.0+incompatible h1:4onqiflcdA9EOZ4RxV643DvftH5pOlLGNtQ5lPWQu84= +github.com/evanphx/json-patch v4.12.0+incompatible/go.mod h1:50XU6AFN0ol/bzJsmQLiYLvXMP4fmwYFNcr97nuDLSk= +github.com/fsnotify/fsnotify v1.4.9 h1:hsms1Qyu0jgnwNXIxa+/V/PDsU6CfLf6CNO8H7IWoS4= +github.com/go-kit/kit v0.8.0/go.mod h1:xBxKIO96dXMWWy0MnWVtmwkA9/13aqxPnvrjFYMA2as= +github.com/go-kit/kit v0.9.0/go.mod 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+sigs.k8s.io/structured-merge-diff/v4 v4.2.3/go.mod h1:qjx8mGObPmV2aSZepjQjbmb2ihdVs8cGKBraizNC69E= +sigs.k8s.io/yaml v1.3.0 h1:a2VclLzOGrwOHDiV8EfBGhvjHvP46CtW5j6POvhYGGo= +sigs.k8s.io/yaml v1.3.0/go.mod h1:GeOyir5tyXNByN85N/dRIT9es5UQNerPYEKK56eTBm8= diff --git a/go/coordinator/internal/common/component.go b/go/coordinator/internal/common/component.go new file mode 100644 index 0000000000000000000000000000000000000000..67555ebb2f2b330c47463d6b0723f2d98ab616c0 --- /dev/null +++ b/go/coordinator/internal/common/component.go @@ -0,0 +1,7 @@ +package common + +// Compoent is the base class for difference components of the system +type Component interface { + Start() error + Stop() error +} diff --git a/go/coordinator/internal/common/constants.go b/go/coordinator/internal/common/constants.go new file mode 100644 index 0000000000000000000000000000000000000000..72276524b9a6c845cee8c8294c40e9f4007374d3 --- /dev/null +++ b/go/coordinator/internal/common/constants.go @@ -0,0 +1,6 @@ +package common + +const ( + DefaultTenant = "default_tenant" + DefaultDatabase = "default_database" +) diff --git a/go/coordinator/internal/common/errors.go b/go/coordinator/internal/common/errors.go new file mode 100644 index 0000000000000000000000000000000000000000..0275e2b6574b1367f27288a240c7eb681f9673e2 --- /dev/null +++ b/go/coordinator/internal/common/errors.go @@ -0,0 +1,37 @@ +package common + +import ( + "errors" +) + +var ( + // Tenant errors + ErrTenantNotFound = errors.New("tenant not found") + ErrTenantUniqueConstraintViolation = errors.New("tenant unique constraint violation") + + // Database errors + ErrDatabaseNotFound = errors.New("database not found") + ErrDatabaseUniqueConstraintViolation = errors.New("database unique constraint violation") + + // Collection errors + ErrCollectionNotFound = errors.New("collection not found") + ErrCollectionIDFormat = errors.New("collection id format error") + ErrCollectionNameEmpty = errors.New("collection name is empty") + ErrCollectionTopicEmpty = errors.New("collection topic is empty") + ErrCollectionUniqueConstraintViolation = errors.New("collection unique constraint violation") + ErrCollectionDeleteNonExistingCollection = errors.New("delete non existing collection") + + // Collection metadata errors + ErrUnknownCollectionMetadataType = errors.New("collection metadata value type not supported") + ErrInvalidMetadataUpdate = errors.New("invalid metadata update, reest metadata true and metadata value not empty") + + // Segment errors + ErrSegmentIDFormat = errors.New("segment id format error") + ErrInvalidTopicUpdate = errors.New("invalid topic update, reset topic true and topic value not empty") + ErrInvalidCollectionUpdate = errors.New("invalid collection update, reset collection true and collection value not empty") + ErrSegmentUniqueConstraintViolation = errors.New("unique constraint violation") + ErrSegmentDeleteNonExistingSegment = errors.New("delete non existing segment") + + // Segment metadata errors + ErrUnknownSegmentMetadataType = errors.New("segment metadata value type not supported") +) diff --git a/go/coordinator/internal/coordinator/apis.go b/go/coordinator/internal/coordinator/apis.go new file mode 100644 index 0000000000000000000000000000000000000000..24cb1a5ee13afc23383c8a3eb9df3681b916e7f7 --- /dev/null +++ b/go/coordinator/internal/coordinator/apis.go @@ -0,0 +1,187 @@ +package coordinator + +import ( + "context" + "errors" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +// ICoordinator is an interface that defines the methods for interacting with the +// Chroma Coordinator. It is designed in a way that can be run standalone without +// spinning off the GRPC service. +type ICoordinator interface { + common.Component + ResetState(ctx context.Context) error + CreateCollection(ctx context.Context, createCollection *model.CreateCollection) (*model.Collection, error) + GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenantID string, dataName string) ([]*model.Collection, error) + DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error + UpdateCollection(ctx context.Context, updateCollection *model.UpdateCollection) (*model.Collection, error) + CreateSegment(ctx context.Context, createSegment *model.CreateSegment) error + GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*model.Segment, error) + DeleteSegment(ctx context.Context, segmentID types.UniqueID) error + UpdateSegment(ctx context.Context, updateSegment *model.UpdateSegment) (*model.Segment, error) + CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase) (*model.Database, error) + GetDatabase(ctx context.Context, getDatabase *model.GetDatabase) (*model.Database, error) + CreateTenant(ctx context.Context, createTenant *model.CreateTenant) (*model.Tenant, error) + GetTenant(ctx context.Context, getTenant *model.GetTenant) (*model.Tenant, error) +} + +func (s *Coordinator) ResetState(ctx context.Context) error { + return s.meta.ResetState(ctx) +} + +func (s *Coordinator) CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase) (*model.Database, error) { + database, err := s.meta.CreateDatabase(ctx, createDatabase) + if err != nil { + return nil, err + } + return database, nil +} + +func (s *Coordinator) GetDatabase(ctx context.Context, getDatabase *model.GetDatabase) (*model.Database, error) { + database, err := s.meta.GetDatabase(ctx, getDatabase) + if err != nil { + return nil, err + } + return database, nil +} + +func (s *Coordinator) CreateTenant(ctx context.Context, createTenant *model.CreateTenant) (*model.Tenant, error) { + tenant, err := s.meta.CreateTenant(ctx, createTenant) + if err != nil { + return nil, err + } + return tenant, nil +} + +func (s *Coordinator) GetTenant(ctx context.Context, getTenant *model.GetTenant) (*model.Tenant, error) { + tenant, err := s.meta.GetTenant(ctx, getTenant) + if err != nil { + return nil, err + } + return tenant, nil +} + +func (s *Coordinator) CreateCollection(ctx context.Context, createCollection *model.CreateCollection) (*model.Collection, error) { + collectionTopic, err := s.assignCollection(createCollection.ID) + if err != nil { + return nil, err + } + createCollection.Topic = collectionTopic + log.Info("apis create collection", zap.Any("collection", createCollection)) + collection, err := s.meta.AddCollection(ctx, createCollection) + if err != nil { + return nil, err + } + return collection, nil +} + +func (s *Coordinator) GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*model.Collection, error) { + return s.meta.GetCollections(ctx, collectionID, collectionName, collectionTopic, tenantID, databaseName) +} + +func (s *Coordinator) DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error { + return s.meta.DeleteCollection(ctx, deleteCollection) +} + +func (s *Coordinator) UpdateCollection(ctx context.Context, collection *model.UpdateCollection) (*model.Collection, error) { + return s.meta.UpdateCollection(ctx, collection) +} + +func (s *Coordinator) CreateSegment(ctx context.Context, segment *model.CreateSegment) error { + if err := verifyCreateSegment(segment); err != nil { + return err + } + err := s.meta.AddSegment(ctx, segment) + if err != nil { + return err + } + return nil +} + +func (s *Coordinator) GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*model.Segment, error) { + return s.meta.GetSegments(ctx, segmentID, segmentType, scope, topic, collectionID) +} + +func (s *Coordinator) DeleteSegment(ctx context.Context, segmentID types.UniqueID) error { + return s.meta.DeleteSegment(ctx, segmentID) +} + +func (s *Coordinator) UpdateSegment(ctx context.Context, updateSegment *model.UpdateSegment) (*model.Segment, error) { + segment, err := s.meta.UpdateSegment(ctx, updateSegment) + if err != nil { + return nil, err + } + return segment, nil +} + +func verifyCreateCollection(collection *model.CreateCollection) error { + if collection.ID.String() == "" { + return errors.New("collection ID cannot be empty") + } + if err := verifyCollectionMetadata(collection.Metadata); err != nil { + return err + } + return nil +} + +func verifyCollectionMetadata(metadata *model.CollectionMetadata[model.CollectionMetadataValueType]) error { + if metadata == nil { + return nil + } + for _, value := range metadata.Metadata { + switch (value).(type) { + case *model.CollectionMetadataValueStringType: + case *model.CollectionMetadataValueInt64Type: + case *model.CollectionMetadataValueFloat64Type: + default: + return common.ErrUnknownCollectionMetadataType + } + } + return nil +} + +func verifyUpdateCollection(collection *model.UpdateCollection) error { + if collection.ID.String() == "" { + return errors.New("collection ID cannot be empty") + } + if err := verifyCollectionMetadata(collection.Metadata); err != nil { + return err + } + return nil +} + +func verifyCreateSegment(segment *model.CreateSegment) error { + if err := verifySegmentMetadata(segment.Metadata); err != nil { + return err + } + return nil +} + +func VerifyUpdateSegment(segment *model.UpdateSegment) error { + if err := verifySegmentMetadata(segment.Metadata); err != nil { + return err + } + return nil +} + +func verifySegmentMetadata(metadata *model.SegmentMetadata[model.SegmentMetadataValueType]) error { + if metadata == nil { + return nil + } + for _, value := range metadata.Metadata { + switch (value).(type) { + case *model.SegmentMetadataValueStringType: + case *model.SegmentMetadataValueInt64Type: + case *model.SegmentMetadataValueFloat64Type: + default: + return common.ErrUnknownSegmentMetadataType + } + } + return nil +} diff --git a/go/coordinator/internal/coordinator/apis_test.go b/go/coordinator/internal/coordinator/apis_test.go new file mode 100644 index 0000000000000000000000000000000000000000..62ff01ecec058816c5da8e6c8d4e6e6a5620eae7 --- /dev/null +++ b/go/coordinator/internal/coordinator/apis_test.go @@ -0,0 +1,957 @@ +package coordinator + +import ( + "context" + "sort" + "testing" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbcore" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/google/uuid" + "github.com/stretchr/testify/assert" + "pgregory.net/rapid" +) + +// TODO: This is not complete yet. We need to add more tests for the other APIs. +// We will deprecate the example based tests once we have enough tests here. +func testCollection(t *rapid.T) { + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewSimpleAssignmentPolicy("test-tenant", "test-topic") + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + t.Repeat(map[string]func(*rapid.T){ + "create_collection": func(t *rapid.T) { + stringValue := generateCollectionStringMetadataValue(t) + intValue := generateCollectionInt64MetadataValue(t) + floatValue := generateCollectionFloat64MetadataValue(t) + + metadata := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + metadata.Add("string_value", stringValue) + metadata.Add("int_value", intValue) + metadata.Add("float_value", floatValue) + + collection := rapid.Custom[*model.CreateCollection](func(t *rapid.T) *model.CreateCollection { + return &model.CreateCollection{ + ID: types.MustParse(rapid.StringMatching(`[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}`).Draw(t, "collection_id")), + Name: rapid.String().Draw(t, "collection_name"), + Metadata: nil, + } + }).Draw(t, "collection") + + _, err := c.CreateCollection(ctx, collection) + if err != nil { + if err == common.ErrCollectionNameEmpty && collection.Name == "" { + t.Logf("expected error for empty collection name") + } else if err == common.ErrCollectionTopicEmpty { + t.Logf("expected error for empty collection topic") + } else { + t.Fatalf("error creating collection: %v", err) + } + } + if err == nil { + // verify the correctness + collectionList, err := c.GetCollections(ctx, collection.ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + if err != nil { + t.Fatalf("error getting collections: %v", err) + } + if len(collectionList) != 1 { + t.Fatalf("More than 1 collection with the same collection id") + } + for _, collectionReturned := range collectionList { + if collection.ID != collectionReturned.ID { + t.Fatalf("collection id is the right value") + } + } + } + }, + }) +} + +func testSegment(t *rapid.T) { + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewSimpleAssignmentPolicy("test-tenant", "test-topic") + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + + stringValue := generateSegmentStringMetadataValue(t) + intValue := generateSegmentInt64MetadataValue(t) + floatValue := generateSegmentFloat64MetadataValue(t) + + metadata := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + metadata.Set("string_value", stringValue) + metadata.Set("int_value", intValue) + metadata.Set("float_value", floatValue) + + testTopic := "test-segment-topic" + t.Repeat(map[string]func(*rapid.T){ + "create_segment": func(t *rapid.T) { + segment := rapid.Custom[*model.CreateSegment](func(t *rapid.T) *model.CreateSegment { + return &model.CreateSegment{ + ID: types.MustParse(rapid.StringMatching(`[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}`).Draw(t, "segment_id")), + Type: "test-segment-type", + Scope: "test-segment-scope", + Topic: &testTopic, + Metadata: nil, + CollectionID: types.MustParse(rapid.StringMatching(`[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}`).Draw(t, "collection_id")), + } + }).Draw(t, "segment") + + err := c.CreateSegment(ctx, segment) + if err != nil { + t.Fatalf("error creating segment: %v", err) + } + }, + }) +} + +func generateCollectionStringMetadataValue(t *rapid.T) model.CollectionMetadataValueType { + return &model.CollectionMetadataValueStringType{ + Value: rapid.String().Draw(t, "string_value"), + } +} + +func generateCollectionInt64MetadataValue(t *rapid.T) model.CollectionMetadataValueType { + return &model.CollectionMetadataValueInt64Type{ + Value: rapid.Int64().Draw(t, "int_value"), + } +} + +func generateCollectionFloat64MetadataValue(t *rapid.T) model.CollectionMetadataValueType { + return &model.CollectionMetadataValueFloat64Type{ + Value: rapid.Float64().Draw(t, "float_value"), + } +} + +func generateSegmentStringMetadataValue(t *rapid.T) model.SegmentMetadataValueType { + return &model.SegmentMetadataValueStringType{ + Value: rapid.String().Draw(t, "string_value"), + } +} + +func generateSegmentInt64MetadataValue(t *rapid.T) model.SegmentMetadataValueType { + return &model.SegmentMetadataValueInt64Type{ + Value: rapid.Int64().Draw(t, "int_value"), + } +} + +func generateSegmentFloat64MetadataValue(t *rapid.T) model.SegmentMetadataValueType { + return &model.SegmentMetadataValueFloat64Type{ + Value: rapid.Float64().Draw(t, "float_value"), + } +} + +func TestAPIs(t *testing.T) { + // rapid.Check(t, testCollection) + // rapid.Check(t, testSegment) +} + +func SampleCollections(t *testing.T, tenantID string, databaseName string) []*model.Collection { + dimension := int32(128) + metadata1 := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + metadata1.Add("test_str", &model.CollectionMetadataValueStringType{Value: "str1"}) + metadata1.Add("test_int", &model.CollectionMetadataValueInt64Type{Value: 1}) + metadata1.Add("test_float", &model.CollectionMetadataValueFloat64Type{Value: 1.3}) + + metadata2 := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + metadata2.Add("test_str", &model.CollectionMetadataValueStringType{Value: "str2"}) + metadata2.Add("test_int", &model.CollectionMetadataValueInt64Type{Value: 2}) + metadata2.Add("test_float", &model.CollectionMetadataValueFloat64Type{Value: 2.3}) + + metadata3 := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + metadata3.Add("test_str", &model.CollectionMetadataValueStringType{Value: "str3"}) + metadata3.Add("test_int", &model.CollectionMetadataValueInt64Type{Value: 3}) + metadata3.Add("test_float", &model.CollectionMetadataValueFloat64Type{Value: 3.3}) + sampleCollections := []*model.Collection{ + { + ID: types.MustParse("93ffe3ec-0107-48d4-8695-51f978c509dc"), + Name: "test_collection_1", + Topic: "test_topic_1", + Metadata: metadata1, + Dimension: &dimension, + Created: true, + TenantID: tenantID, + DatabaseName: databaseName, + }, + { + ID: types.MustParse("f444f1d7-d06c-4357-ac22-5a4a1f92d761"), + Name: "test_collection_2", + Topic: "test_topic_2", + Metadata: metadata2, + Dimension: nil, + Created: true, + TenantID: tenantID, + DatabaseName: databaseName, + }, + { + ID: types.MustParse("43babc1a-e403-4a50-91a9-16621ba29ab0"), + Name: "test_collection_3", + Topic: "test_topic_3", + Metadata: metadata3, + Dimension: nil, + Created: true, + TenantID: tenantID, + DatabaseName: databaseName, + }, + } + return sampleCollections +} + +type MockAssignmentPolicy struct { + collections []*model.Collection +} + +func NewMockAssignmentPolicy(collecions []*model.Collection) *MockAssignmentPolicy { + return &MockAssignmentPolicy{ + collections: collecions, + } +} + +func (m *MockAssignmentPolicy) AssignCollection(collectionID types.UniqueID) (string, error) { + for _, collection := range m.collections { + if collection.ID == collectionID { + return collection.Topic, nil + } + } + return "", common.ErrCollectionNotFound +} + +func TestCreateGetDeleteCollections(t *testing.T) { + + sampleCollections := SampleCollections(t, common.DefaultTenant, common.DefaultDatabase) + + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + + for _, collection := range sampleCollections { + c.CreateCollection(ctx, &model.CreateCollection{ + ID: collection.ID, + Name: collection.Name, + Topic: collection.Topic, + Metadata: collection.Metadata, + Dimension: collection.Dimension, + TenantID: collection.TenantID, + DatabaseName: collection.DatabaseName, + }) + } + + results, err := c.GetCollections(ctx, types.NilUniqueID(), nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + + sort.Slice(results, func(i, j int) bool { + return results[i].Name < results[j].Name + }) + + assert.Equal(t, sampleCollections, results) + + // Duplicate create fails + _, err = c.CreateCollection(ctx, &model.CreateCollection{ + ID: sampleCollections[0].ID, + Name: sampleCollections[0].Name, + TenantID: common.DefaultTenant, + DatabaseName: common.DefaultDatabase, + }) + assert.Error(t, err) + + // Find by name + for _, collection := range sampleCollections { + result, err := c.GetCollections(ctx, types.NilUniqueID(), &collection.Name, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{collection}, result) + } + + // Find by topic + for _, collection := range sampleCollections { + result, err := c.GetCollections(ctx, types.NilUniqueID(), nil, &collection.Topic, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{collection}, result) + } + + // Find by id + for _, collection := range sampleCollections { + result, err := c.GetCollections(ctx, collection.ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{collection}, result) + } + + // Find by id and topic (positive case) + for _, collection := range sampleCollections { + result, err := c.GetCollections(ctx, collection.ID, nil, &collection.Topic, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{collection}, result) + } + + // find by id and topic (negative case) + for _, collection := range sampleCollections { + otherTopic := "other topic" + result, err := c.GetCollections(ctx, collection.ID, nil, &otherTopic, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Empty(t, result) + } + + // Delete + c1 := sampleCollections[0] + deleteCollection := &model.DeleteCollection{ + ID: c1.ID, + DatabaseName: common.DefaultDatabase, + TenantID: common.DefaultTenant, + } + err = c.DeleteCollection(ctx, deleteCollection) + assert.NoError(t, err) + + results, err = c.GetCollections(ctx, types.NilUniqueID(), nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + + assert.NotContains(t, results, c1) + assert.Len(t, results, len(sampleCollections)-1) + assert.ElementsMatch(t, results, sampleCollections[1:]) + byIDResult, err := c.GetCollections(ctx, c1.ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Empty(t, byIDResult) + + // Duplicate delete throws an exception + err = c.DeleteCollection(ctx, deleteCollection) + assert.Error(t, err) +} + +func TestUpdateCollections(t *testing.T) { + sampleCollections := SampleCollections(t, common.DefaultTenant, common.DefaultDatabase) + + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + + coll := &model.Collection{ + Name: sampleCollections[0].Name, + ID: sampleCollections[0].ID, + Topic: sampleCollections[0].Topic, + Metadata: sampleCollections[0].Metadata, + Dimension: sampleCollections[0].Dimension, + Created: false, + TenantID: sampleCollections[0].TenantID, + DatabaseName: sampleCollections[0].DatabaseName, + } + + c.CreateCollection(ctx, &model.CreateCollection{ + ID: coll.ID, + Name: coll.Name, + Topic: coll.Topic, + Metadata: coll.Metadata, + Dimension: coll.Dimension, + TenantID: coll.TenantID, + DatabaseName: coll.DatabaseName, + }) + + // Update name + coll.Name = "new_name" + result, err := c.UpdateCollection(ctx, &model.UpdateCollection{ID: coll.ID, Name: &coll.Name}) + assert.NoError(t, err) + assert.Equal(t, coll, result) + resultList, err := c.GetCollections(ctx, types.NilUniqueID(), &coll.Name, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{coll}, resultList) + + // Update topic + coll.Topic = "new_topic" + result, err = c.UpdateCollection(ctx, &model.UpdateCollection{ID: coll.ID, Topic: &coll.Topic}) + assert.NoError(t, err) + assert.Equal(t, coll, result) + resultList, err = c.GetCollections(ctx, types.NilUniqueID(), nil, &coll.Topic, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{coll}, resultList) + + // Update dimension + newDimension := int32(128) + coll.Dimension = &newDimension + result, err = c.UpdateCollection(ctx, &model.UpdateCollection{ID: coll.ID, Dimension: coll.Dimension}) + assert.NoError(t, err) + assert.Equal(t, coll, result) + resultList, err = c.GetCollections(ctx, coll.ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{coll}, resultList) + + // Reset the metadata + newMetadata := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + newMetadata.Add("test_str2", &model.CollectionMetadataValueStringType{Value: "str2"}) + coll.Metadata = newMetadata + result, err = c.UpdateCollection(ctx, &model.UpdateCollection{ID: coll.ID, Metadata: coll.Metadata}) + assert.NoError(t, err) + assert.Equal(t, coll, result) + resultList, err = c.GetCollections(ctx, coll.ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{coll}, resultList) + + // Delete all metadata keys + coll.Metadata = nil + result, err = c.UpdateCollection(ctx, &model.UpdateCollection{ID: coll.ID, Metadata: coll.Metadata, ResetMetadata: true}) + assert.NoError(t, err) + assert.Equal(t, coll, result) + resultList, err = c.GetCollections(ctx, coll.ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, []*model.Collection{coll}, resultList) +} + +func TestCreateUpdateWithDatabase(t *testing.T) { + sampleCollections := SampleCollections(t, common.DefaultTenant, common.DefaultDatabase) + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + _, err = c.CreateDatabase(ctx, &model.CreateDatabase{ + ID: types.MustParse("00000000-d7d7-413b-92e1-731098a6e492").String(), + Name: "new_database", + Tenant: common.DefaultTenant, + }) + assert.NoError(t, err) + + c.CreateCollection(ctx, &model.CreateCollection{ + ID: sampleCollections[0].ID, + Name: sampleCollections[0].Name, + Topic: sampleCollections[0].Topic, + Metadata: sampleCollections[0].Metadata, + Dimension: sampleCollections[0].Dimension, + TenantID: sampleCollections[0].TenantID, + DatabaseName: "new_database", + }) + + c.CreateCollection(ctx, &model.CreateCollection{ + ID: sampleCollections[1].ID, + Name: sampleCollections[1].Name, + Topic: sampleCollections[1].Topic, + Metadata: sampleCollections[1].Metadata, + Dimension: sampleCollections[1].Dimension, + TenantID: sampleCollections[1].TenantID, + DatabaseName: sampleCollections[1].DatabaseName, + }) + + newName1 := "new_name_1" + c.UpdateCollection(ctx, &model.UpdateCollection{ + ID: sampleCollections[1].ID, + Name: &newName1, + }) + + result, err := c.GetCollections(ctx, sampleCollections[1].ID, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, 1, len(result)) + assert.Equal(t, "new_name_1", result[0].Name) + + newName0 := "new_name_0" + c.UpdateCollection(ctx, &model.UpdateCollection{ + ID: sampleCollections[0].ID, + Name: &newName0, + }) + result, err = c.GetCollections(ctx, sampleCollections[0].ID, nil, nil, common.DefaultTenant, "new_database") + assert.NoError(t, err) + assert.Equal(t, 1, len(result)) + assert.Equal(t, "new_name_0", result[0].Name) +} + +func TestGetMultipleWithDatabase(t *testing.T) { + sampleCollections := SampleCollections(t, common.DefaultTenant, "new_database") + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + _, err = c.CreateDatabase(ctx, &model.CreateDatabase{ + ID: types.MustParse("00000000-d7d7-413b-92e1-731098a6e492").String(), + Name: "new_database", + Tenant: common.DefaultTenant, + }) + assert.NoError(t, err) + + for _, collection := range sampleCollections { + c.CreateCollection(ctx, &model.CreateCollection{ + ID: collection.ID, + Name: collection.Name, + Topic: collection.Topic, + Metadata: collection.Metadata, + Dimension: collection.Dimension, + TenantID: common.DefaultTenant, + DatabaseName: "new_database", + }) + } + result, err := c.GetCollections(ctx, types.NilUniqueID(), nil, nil, common.DefaultTenant, "new_database") + assert.NoError(t, err) + assert.Equal(t, len(sampleCollections), len(result)) + sort.Slice(result, func(i, j int) bool { + return result[i].Name < result[j].Name + }) + assert.Equal(t, sampleCollections, result) + + result, err = c.GetCollections(ctx, types.NilUniqueID(), nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Equal(t, 0, len(result)) +} + +func TestCreateDatabaseWithTenants(t *testing.T) { + sampleCollections := SampleCollections(t, common.DefaultTenant, common.DefaultDatabase) + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + + // Create a new tenant + _, err = c.CreateTenant(ctx, &model.CreateTenant{ + Name: "tenant1", + }) + assert.NoError(t, err) + + // Create tenant that already exits and expect an error + _, err = c.CreateTenant(ctx, &model.CreateTenant{ + Name: "tenant1", + }) + assert.Error(t, err) + + // Create tenant that already exits and expect an error + _, err = c.CreateTenant(ctx, &model.CreateTenant{ + Name: common.DefaultTenant, + }) + assert.Error(t, err) + + // Create a new database within this tenant and also in the default tenant + _, err = c.CreateDatabase(ctx, &model.CreateDatabase{ + ID: types.MustParse("33333333-d7d7-413b-92e1-731098a6e492").String(), + Name: "new_database", + Tenant: "tenant1", + }) + assert.NoError(t, err) + + _, err = c.CreateDatabase(ctx, &model.CreateDatabase{ + ID: types.MustParse("44444444-d7d7-413b-92e1-731098a6e492").String(), + Name: "new_database", + Tenant: common.DefaultTenant, + }) + assert.NoError(t, err) + + // Create a new collection in the new tenant + _, err = c.CreateCollection(ctx, &model.CreateCollection{ + ID: sampleCollections[0].ID, + Name: sampleCollections[0].Name, + Topic: sampleCollections[0].Topic, + Metadata: sampleCollections[0].Metadata, + Dimension: sampleCollections[0].Dimension, + TenantID: "tenant1", + DatabaseName: "new_database", + }) + assert.NoError(t, err) + + // Create a new collection in the default tenant + c.CreateCollection(ctx, &model.CreateCollection{ + ID: sampleCollections[1].ID, + Name: sampleCollections[1].Name, + Topic: sampleCollections[1].Topic, + Metadata: sampleCollections[1].Metadata, + Dimension: sampleCollections[1].Dimension, + TenantID: common.DefaultTenant, + DatabaseName: "new_database", + }) + + // Check that both tenants have the correct collections + expected := []*model.Collection{sampleCollections[0]} + expected[0].TenantID = "tenant1" + expected[0].DatabaseName = "new_database" + result, err := c.GetCollections(ctx, types.NilUniqueID(), nil, nil, "tenant1", "new_database") + assert.NoError(t, err) + assert.Equal(t, 1, len(result)) + assert.Equal(t, expected[0], result[0]) + + expected = []*model.Collection{sampleCollections[1]} + expected[0].TenantID = common.DefaultTenant + expected[0].DatabaseName = "new_database" + result, err = c.GetCollections(ctx, types.NilUniqueID(), nil, nil, common.DefaultTenant, "new_database") + assert.NoError(t, err) + assert.Equal(t, 1, len(result)) + assert.Equal(t, expected[0], result[0]) + + // A new tenant DOES NOT have a default database. This does not error, instead 0 + // results are returned + result, err = c.GetCollections(ctx, types.NilUniqueID(), nil, nil, "tenant1", common.DefaultDatabase) + assert.Error(t, err) + assert.Nil(t, result) +} + +func TestCreateGetDeleteTenants(t *testing.T) { + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(nil) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + + // Create a new tenant + _, err = c.CreateTenant(ctx, &model.CreateTenant{ + Name: "tenant1", + }) + assert.NoError(t, err) + + // Create tenant that already exits and expect an error + _, err = c.CreateTenant(ctx, &model.CreateTenant{ + Name: "tenant1", + }) + assert.Error(t, err) + + // Create tenant that already exits and expect an error + _, err = c.CreateTenant(ctx, &model.CreateTenant{ + Name: common.DefaultTenant, + }) + assert.Error(t, err) + + // Get the tenant and check that it exists + result, err := c.GetTenant(ctx, &model.GetTenant{Name: "tenant1"}) + assert.NoError(t, err) + assert.Equal(t, "tenant1", result.Name) + + // Get a tenant that does not exist and expect an error + _, err = c.GetTenant(ctx, &model.GetTenant{Name: "tenant2"}) + assert.Error(t, err) + + // Create a new database within this tenant + _, err = c.CreateDatabase(ctx, &model.CreateDatabase{ + ID: types.MustParse("33333333-d7d7-413b-92e1-731098a6e492").String(), + Name: "new_database", + Tenant: "tenant1", + }) + assert.NoError(t, err) + + // Get the database and check that it exists + databaseResult, err := c.GetDatabase(ctx, &model.GetDatabase{ + Name: "new_database", + Tenant: "tenant1", + }) + assert.NoError(t, err) + assert.Equal(t, "new_database", databaseResult.Name) + assert.Equal(t, "tenant1", databaseResult.Tenant) + + // Get a database that does not exist in a tenant that does exist and expect an error + _, err = c.GetDatabase(ctx, &model.GetDatabase{ + Name: "new_database1", + Tenant: "tenant1", + }) + assert.Error(t, err) + + // Get a database that does not exist in a tenant that does not exist and expect an + // error + _, err = c.GetDatabase(ctx, &model.GetDatabase{ + Name: "new_database1", + Tenant: "tenant2", + }) + assert.Error(t, err) +} + +func SampleSegments(t *testing.T, sampleCollections []*model.Collection) []*model.Segment { + metadata1 := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + metadata1.Set("test_str", &model.SegmentMetadataValueStringType{Value: "str1"}) + metadata1.Set("test_int", &model.SegmentMetadataValueInt64Type{Value: 1}) + metadata1.Set("test_float", &model.SegmentMetadataValueFloat64Type{Value: 1.3}) + + metadata2 := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + metadata2.Set("test_str", &model.SegmentMetadataValueStringType{Value: "str2"}) + metadata2.Set("test_int", &model.SegmentMetadataValueInt64Type{Value: 2}) + metadata2.Set("test_float", &model.SegmentMetadataValueFloat64Type{Value: 2.3}) + + metadata3 := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + metadata3.Set("test_str", &model.SegmentMetadataValueStringType{Value: "str3"}) + metadata3.Set("test_int", &model.SegmentMetadataValueInt64Type{Value: 3}) + metadata3.Set("test_float", &model.SegmentMetadataValueFloat64Type{Value: 3.3}) + + testTopic2 := "test_topic_2" + testTopic3 := "test_topic_3" + sampleSegments := []*model.Segment{ + { + ID: types.MustParse("00000000-d7d7-413b-92e1-731098a6e492"), + Type: "test_type_a", + Topic: nil, + Scope: "VECTOR", + CollectionID: sampleCollections[0].ID, + Metadata: metadata1, + }, + { + ID: types.MustParse("11111111-d7d7-413b-92e1-731098a6e492"), + Type: "test_type_b", + Topic: &testTopic2, + Scope: "VECTOR", + CollectionID: sampleCollections[1].ID, + Metadata: metadata2, + }, + { + ID: types.MustParse("22222222-d7d7-413b-92e1-731098a6e492"), + Type: "test_type_b", + Topic: &testTopic3, + Scope: "METADATA", + CollectionID: types.NilUniqueID(), + Metadata: metadata3, // This segment is not assigned to any collection + }, + } + return sampleSegments +} + +func TestCreateGetDeleteSegments(t *testing.T) { + sampleCollections := SampleCollections(t, common.DefaultTenant, common.DefaultDatabase) + + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + + for _, collection := range sampleCollections { + c.CreateCollection(ctx, &model.CreateCollection{ + ID: collection.ID, + Name: collection.Name, + Topic: collection.Topic, + Metadata: collection.Metadata, + Dimension: collection.Dimension, + TenantID: collection.TenantID, + DatabaseName: collection.DatabaseName, + }) + } + + sampleSegments := SampleSegments(t, sampleCollections) + for _, segment := range sampleSegments { + c.CreateSegment(ctx, &model.CreateSegment{ + ID: segment.ID, + Type: segment.Type, + Topic: segment.Topic, + Scope: segment.Scope, + CollectionID: segment.CollectionID, + Metadata: segment.Metadata, + }) + } + + results, err := c.GetSegments(ctx, types.NilUniqueID(), nil, nil, nil, types.NilUniqueID()) + sort.Slice(results, func(i, j int) bool { + return results[i].ID.String() < results[j].ID.String() + }) + assert.NoError(t, err) + assert.Equal(t, sampleSegments, results) + + // Duplicate create fails + err = c.CreateSegment(ctx, &model.CreateSegment{ + ID: sampleSegments[0].ID, + Type: sampleSegments[0].Type, + Topic: sampleSegments[0].Topic, + Scope: sampleSegments[0].Scope, + CollectionID: sampleSegments[0].CollectionID, + Metadata: sampleSegments[0].Metadata, + }) + assert.Error(t, err) + + // Find by id + for _, segment := range sampleSegments { + result, err := c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + } + + // Find by type + testTypeA := "test_type_a" + result, err := c.GetSegments(ctx, types.NilUniqueID(), &testTypeA, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, sampleSegments[:1], result) + + testTypeB := "test_type_b" + result, err = c.GetSegments(ctx, types.NilUniqueID(), &testTypeB, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.ElementsMatch(t, result, sampleSegments[1:]) + + // Find by collection ID + result, err = c.GetSegments(ctx, types.NilUniqueID(), nil, nil, nil, sampleCollections[0].ID) + assert.NoError(t, err) + assert.Equal(t, sampleSegments[:1], result) + + // Find by type and collection ID (positive case) + result, err = c.GetSegments(ctx, types.NilUniqueID(), &testTypeA, nil, nil, sampleCollections[0].ID) + assert.NoError(t, err) + assert.Equal(t, sampleSegments[:1], result) + + // Find by type and collection ID (negative case) + result, err = c.GetSegments(ctx, types.NilUniqueID(), &testTypeB, nil, nil, sampleCollections[0].ID) + assert.NoError(t, err) + assert.Empty(t, result) + + // Delete + s1 := sampleSegments[0] + err = c.DeleteSegment(ctx, s1.ID) + assert.NoError(t, err) + + results, err = c.GetSegments(ctx, types.NilUniqueID(), nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.NotContains(t, results, s1) + assert.Len(t, results, len(sampleSegments)-1) + assert.ElementsMatch(t, results, sampleSegments[1:]) + + // Duplicate delete throws an exception + err = c.DeleteSegment(ctx, s1.ID) + assert.Error(t, err) +} + +func TestUpdateSegment(t *testing.T) { + sampleCollections := SampleCollections(t, common.DefaultTenant, common.DefaultDatabase) + + db := dbcore.ConfigDatabaseForTesting() + ctx := context.Background() + assignmentPolicy := NewMockAssignmentPolicy(sampleCollections) + c, err := NewCoordinator(ctx, assignmentPolicy, db, nil, nil) + if err != nil { + t.Fatalf("error creating coordinator: %v", err) + } + c.ResetState(ctx) + + testTopic := "test_topic_a" + + metadata := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + metadata.Set("test_str", &model.SegmentMetadataValueStringType{Value: "str1"}) + metadata.Set("test_int", &model.SegmentMetadataValueInt64Type{Value: 1}) + metadata.Set("test_float", &model.SegmentMetadataValueFloat64Type{Value: 1.3}) + + segment := &model.Segment{ + ID: types.UniqueID(uuid.New()), + Type: "test_type_a", + Scope: "VECTOR", + Topic: &testTopic, + CollectionID: sampleCollections[0].ID, + Metadata: metadata, + } + + for _, collection := range sampleCollections { + _, err := c.CreateCollection(ctx, &model.CreateCollection{ + ID: collection.ID, + Name: collection.Name, + Topic: collection.Topic, + Metadata: collection.Metadata, + Dimension: collection.Dimension, + TenantID: collection.TenantID, + DatabaseName: collection.DatabaseName, + }) + + assert.NoError(t, err) + } + + c.CreateSegment(ctx, &model.CreateSegment{ + ID: segment.ID, + Type: segment.Type, + Topic: segment.Topic, + Scope: segment.Scope, + CollectionID: segment.CollectionID, + Metadata: segment.Metadata, + }) + + // Update topic to new value + newTopic := "new_topic" + segment.Topic = &newTopic + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Topic: segment.Topic, + }) + result, err := c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Update topic to None + segment.Topic = nil + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Topic: segment.Topic, + ResetTopic: true, + }) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Update collection to new value + segment.CollectionID = sampleCollections[1].ID + newCollecionID := segment.CollectionID.String() + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Collection: &newCollecionID, + }) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Update collection to None + segment.CollectionID = types.NilUniqueID() + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Collection: nil, + ResetCollection: true, + }) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Add a new metadata key + segment.Metadata.Set("test_str2", &model.SegmentMetadataValueStringType{Value: "str2"}) + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Metadata: segment.Metadata}) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Update a metadata key + segment.Metadata.Set("test_str", &model.SegmentMetadataValueStringType{Value: "str3"}) + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Metadata: segment.Metadata}) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Delete a metadata key + segment.Metadata.Remove("test_str") + newMetadata := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + newMetadata.Set("test_str", nil) + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Metadata: newMetadata}) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) + + // Delete all metadata keys + segment.Metadata = nil + c.UpdateSegment(ctx, &model.UpdateSegment{ + ID: segment.ID, + Metadata: segment.Metadata, + ResetMetadata: true}, + ) + result, err = c.GetSegments(ctx, segment.ID, nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Equal(t, []*model.Segment{segment}, result) +} diff --git a/go/coordinator/internal/coordinator/assignment_policy.go b/go/coordinator/internal/coordinator/assignment_policy.go new file mode 100644 index 0000000000000000000000000000000000000000..6976d6a96525568d31627bab8cae570fe7792131 --- /dev/null +++ b/go/coordinator/internal/coordinator/assignment_policy.go @@ -0,0 +1,77 @@ +package coordinator + +import ( + "fmt" + + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/chroma/chroma-coordinator/internal/utils" +) + +type CollectionAssignmentPolicy interface { + AssignCollection(collectionID types.UniqueID) (string, error) +} + +// SimpleAssignmentPolicy is a simple assignment policy that assigns a 1 collection to 1 +// topic based on the id of the collection. +type SimpleAssignmentPolicy struct { + tenantID string + topicNS string +} + +func NewSimpleAssignmentPolicy(tenantID string, topicNS string) *SimpleAssignmentPolicy { + return &SimpleAssignmentPolicy{ + tenantID: tenantID, + topicNS: topicNS, + } +} + +func (s *SimpleAssignmentPolicy) AssignCollection(collectionID types.UniqueID) (string, error) { + return createTopicName(s.tenantID, s.topicNS, collectionID.String()), nil +} + +func createTopicName(tenantID string, topicNS string, log_name string) string { + return fmt.Sprintf("persistent://%s/%s/%s", tenantID, topicNS, log_name) +} + +// RendezvousAssignmentPolicy is an assignment policy that assigns a collection to a topic +// For now it assumes there are 16 topics and uses the rendezvous hashing algorithm to +// assign a collection to a topic. + +var Topics = [16]string{ + "chroma_log_0", + "chroma_log_1", + "chroma_log_2", + "chroma_log_3", + "chroma_log_4", + "chroma_log_5", + "chroma_log_6", + "chroma_log_7", + "chroma_log_8", + "chroma_log_9", + "chroma_log_10", + "chroma_log_11", + "chroma_log_12", + "chroma_log_13", + "chroma_log_14", + "chroma_log_15", +} + +type RendezvousAssignmentPolicy struct { + tenantID string + topicNS string +} + +func NewRendezvousAssignmentPolicy(tenantID string, topicNS string) *RendezvousAssignmentPolicy { + return &RendezvousAssignmentPolicy{ + tenantID: tenantID, + topicNS: topicNS, + } +} + +func (r *RendezvousAssignmentPolicy) AssignCollection(collectionID types.UniqueID) (string, error) { + assignment, error := utils.Assign(collectionID.String(), Topics[:], utils.Murmur3Hasher) + if error != nil { + return "", error + } + return createTopicName(r.tenantID, r.topicNS, assignment), nil +} diff --git a/go/coordinator/internal/coordinator/coordinator.go b/go/coordinator/internal/coordinator/coordinator.go new file mode 100644 index 0000000000000000000000000000000000000000..2f3c02cff2668b2cf1bd5aeb049e4d7d5255f05c --- /dev/null +++ b/go/coordinator/internal/coordinator/coordinator.go @@ -0,0 +1,76 @@ +package coordinator + +import ( + "context" + "log" + + "github.com/chroma/chroma-coordinator/internal/metastore" + "github.com/chroma/chroma-coordinator/internal/metastore/coordinator" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dao" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbcore" + "github.com/chroma/chroma-coordinator/internal/notification" + "github.com/chroma/chroma-coordinator/internal/types" + "gorm.io/gorm" +) + +var _ ICoordinator = (*Coordinator)(nil) + +// Coordinator is the implemenation of ICoordinator. It is the top level component. +// Currently, it only has the system catalog related APIs and will be extended to +// support other functionalities such as membership managed and propagation. +type Coordinator struct { + ctx context.Context + collectionAssignmentPolicy CollectionAssignmentPolicy + meta IMeta + notificationProcessor notification.NotificationProcessor +} + +func NewCoordinator(ctx context.Context, assignmentPolicy CollectionAssignmentPolicy, db *gorm.DB, notificationStore notification.NotificationStore, notifier notification.Notifier) (*Coordinator, error) { + s := &Coordinator{ + ctx: ctx, + collectionAssignmentPolicy: assignmentPolicy, + } + + notificationProcessor := notification.NewSimpleNotificationProcessor(ctx, notificationStore, notifier) + + var catalog metastore.Catalog + // TODO: move this to server.go + if db == nil { + catalog = coordinator.NewMemoryCatalogWithNotification(notificationStore) + } else { + txnImpl := dbcore.NewTxImpl() + metaDomain := dao.NewMetaDomain() + catalog = coordinator.NewTableCatalogWithNotification(txnImpl, metaDomain, notificationStore) + } + meta, err := NewMetaTable(s.ctx, catalog) + if err != nil { + return nil, err + } + meta.SetNotificationProcessor(notificationProcessor) + + s.meta = meta + s.notificationProcessor = notificationProcessor + + return s, nil +} + +func (s *Coordinator) Start() error { + err := s.notificationProcessor.Start() + if err != nil { + log.Printf("Failed to start notification processor: %v", err) + return err + } + return nil +} + +func (s *Coordinator) Stop() error { + err := s.notificationProcessor.Stop() + if err != nil { + log.Printf("Failed to stop notification processor: %v", err) + } + return nil +} + +func (c *Coordinator) assignCollection(collectionID types.UniqueID) (string, error) { + return c.collectionAssignmentPolicy.AssignCollection(collectionID) +} diff --git a/go/coordinator/internal/coordinator/meta.go b/go/coordinator/internal/coordinator/meta.go new file mode 100644 index 0000000000000000000000000000000000000000..f6f2df7584e49a7bb9638176fc2748bd72f00a0d --- /dev/null +++ b/go/coordinator/internal/coordinator/meta.go @@ -0,0 +1,414 @@ +package coordinator + +import ( + "context" + "sync" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/notification" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +// IMeta is an interface that defines methods for the cache of the catalog. +type IMeta interface { + ResetState(ctx context.Context) error + AddCollection(ctx context.Context, createCollection *model.CreateCollection) (*model.Collection, error) + GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*model.Collection, error) + DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error + UpdateCollection(ctx context.Context, updateCollection *model.UpdateCollection) (*model.Collection, error) + AddSegment(ctx context.Context, createSegment *model.CreateSegment) error + GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*model.Segment, error) + DeleteSegment(ctx context.Context, segmentID types.UniqueID) error + UpdateSegment(ctx context.Context, updateSegment *model.UpdateSegment) (*model.Segment, error) + CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase) (*model.Database, error) + GetDatabase(ctx context.Context, getDatabase *model.GetDatabase) (*model.Database, error) + CreateTenant(ctx context.Context, createTenant *model.CreateTenant) (*model.Tenant, error) + GetTenant(ctx context.Context, getTenant *model.GetTenant) (*model.Tenant, error) + SetNotificationProcessor(notificationProcessor notification.NotificationProcessor) +} + +// MetaTable is an implementation of IMeta. It loads the system catalog during startup +// and caches in memory. The implmentation needs to make sure that the in memory cache +// is consistent with the system catalog. +// +// Operations of MetaTable are protected by a read write lock and are thread safe. +type MetaTable struct { + ddLock sync.RWMutex + ctx context.Context + catalog metastore.Catalog + segmentsCache map[types.UniqueID]*model.Segment + tenantDatabaseCollectionCache map[string]map[string]map[types.UniqueID]*model.Collection + tenantDatabaseCache map[string]map[string]*model.Database + notificationProcessor notification.NotificationProcessor +} + +var _ IMeta = (*MetaTable)(nil) + +func NewMetaTable(ctx context.Context, catalog metastore.Catalog) (*MetaTable, error) { + mt := &MetaTable{ + ctx: ctx, + catalog: catalog, + segmentsCache: make(map[types.UniqueID]*model.Segment), + tenantDatabaseCollectionCache: make(map[string]map[string]map[types.UniqueID]*model.Collection), + tenantDatabaseCache: make(map[string]map[string]*model.Database), + } + if err := mt.reloadWithLock(); err != nil { + return nil, err + } + return mt, nil +} + +func (mt *MetaTable) reloadWithLock() error { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + return mt.reload() +} + +func (mt *MetaTable) reload() error { + tenants, err := mt.catalog.GetAllTenants(mt.ctx, 0) + if err != nil { + return err + } + for _, tenant := range tenants { + tenantID := tenant.Name + mt.tenantDatabaseCollectionCache[tenantID] = make(map[string]map[types.UniqueID]*model.Collection) + mt.tenantDatabaseCache[tenantID] = make(map[string]*model.Database) + } + // reload databases + databases, err := mt.catalog.GetAllDatabases(mt.ctx, 0) + if err != nil { + return err + } + for _, database := range databases { + databaseName := database.Name + tenantID := database.Tenant + mt.tenantDatabaseCollectionCache[tenantID][databaseName] = make(map[types.UniqueID]*model.Collection) + mt.tenantDatabaseCache[tenantID][databaseName] = database + } + for tenantID, databases := range mt.tenantDatabaseCollectionCache { + for databaseName := range databases { + collections, err := mt.catalog.GetCollections(mt.ctx, types.NilUniqueID(), nil, nil, tenantID, databaseName) + if err != nil { + return err + } + for _, collection := range collections { + mt.tenantDatabaseCollectionCache[tenantID][databaseName][collection.ID] = collection + } + } + } + + oldSegments, err := mt.catalog.GetSegments(mt.ctx, types.NilUniqueID(), nil, nil, nil, types.NilUniqueID(), 0) + if err != nil { + return err + } + // reload is idempotent + mt.segmentsCache = make(map[types.UniqueID]*model.Segment) + for _, segment := range oldSegments { + mt.segmentsCache[segment.ID] = segment + } + return nil +} + +func (mt *MetaTable) SetNotificationProcessor(notificationProcessor notification.NotificationProcessor) { + mt.notificationProcessor = notificationProcessor +} + +func (mt *MetaTable) ResetState(ctx context.Context) error { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + if err := mt.catalog.ResetState(ctx); err != nil { + return err + } + mt.segmentsCache = make(map[types.UniqueID]*model.Segment) + mt.tenantDatabaseCache = make(map[string]map[string]*model.Database) + mt.tenantDatabaseCollectionCache = make(map[string]map[string]map[types.UniqueID]*model.Collection) + + if err := mt.reload(); err != nil { + return err + } + return nil +} + +func (mt *MetaTable) CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase) (*model.Database, error) { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + tenant := createDatabase.Tenant + databaseName := createDatabase.Name + if _, ok := mt.tenantDatabaseCache[tenant]; !ok { + log.Error("tenant not found", zap.Any("tenant", tenant)) + return nil, common.ErrTenantNotFound + } + if _, ok := mt.tenantDatabaseCache[tenant][databaseName]; ok { + log.Error("database already exists", zap.Any("database", databaseName)) + return nil, common.ErrDatabaseUniqueConstraintViolation + } + database, err := mt.catalog.CreateDatabase(ctx, createDatabase, createDatabase.Ts) + if err != nil { + log.Info("create database failed", zap.Error(err)) + return nil, err + } + mt.tenantDatabaseCache[tenant][databaseName] = database + mt.tenantDatabaseCollectionCache[tenant][databaseName] = make(map[types.UniqueID]*model.Collection) + return database, nil +} + +func (mt *MetaTable) GetDatabase(ctx context.Context, getDatabase *model.GetDatabase) (*model.Database, error) { + mt.ddLock.RLock() + defer mt.ddLock.RUnlock() + + tenant := getDatabase.Tenant + databaseName := getDatabase.Name + if _, ok := mt.tenantDatabaseCache[tenant]; !ok { + log.Error("tenant not found", zap.Any("tenant", tenant)) + return nil, common.ErrTenantNotFound + } + if _, ok := mt.tenantDatabaseCache[tenant][databaseName]; !ok { + log.Error("database not found", zap.Any("database", databaseName)) + return nil, common.ErrDatabaseNotFound + } + + return mt.tenantDatabaseCache[tenant][databaseName], nil +} + +func (mt *MetaTable) CreateTenant(ctx context.Context, createTenant *model.CreateTenant) (*model.Tenant, error) { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + tenantName := createTenant.Name + if _, ok := mt.tenantDatabaseCache[tenantName]; ok { + log.Error("tenant already exists", zap.Any("tenant", tenantName)) + return nil, common.ErrTenantUniqueConstraintViolation + } + tenant, err := mt.catalog.CreateTenant(ctx, createTenant, createTenant.Ts) + if err != nil { + return nil, err + } + mt.tenantDatabaseCache[tenantName] = make(map[string]*model.Database) + mt.tenantDatabaseCollectionCache[tenantName] = make(map[string]map[types.UniqueID]*model.Collection) + return tenant, nil +} + +func (mt *MetaTable) GetTenant(ctx context.Context, getTenant *model.GetTenant) (*model.Tenant, error) { + mt.ddLock.RLock() + defer mt.ddLock.RUnlock() + tenantID := getTenant.Name + if _, ok := mt.tenantDatabaseCache[tenantID]; !ok { + log.Error("tenant not found", zap.Any("tenant", tenantID)) + return nil, common.ErrTenantNotFound + } + return &model.Tenant{Name: tenantID}, nil +} + +func (mt *MetaTable) AddCollection(ctx context.Context, createCollection *model.CreateCollection) (*model.Collection, error) { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + tenantID := createCollection.TenantID + databaseName := createCollection.DatabaseName + if _, ok := mt.tenantDatabaseCollectionCache[tenantID]; !ok { + log.Error("tenant not found", zap.Any("tenantID", tenantID)) + return nil, common.ErrTenantNotFound + } + if _, ok := mt.tenantDatabaseCollectionCache[tenantID][databaseName]; !ok { + log.Error("database not found", zap.Any("databaseName", databaseName)) + return nil, common.ErrDatabaseNotFound + } + collection, err := mt.catalog.CreateCollection(ctx, createCollection, createCollection.Ts) + if err != nil { + log.Error("create collection failed", zap.Error(err)) + return nil, err + } + mt.tenantDatabaseCollectionCache[tenantID][databaseName][collection.ID] = collection + log.Info("collection added", zap.Any("collection", mt.tenantDatabaseCollectionCache[tenantID][databaseName][collection.ID])) + + triggerMessage := notification.TriggerMessage{ + Msg: model.Notification{ + CollectionID: collection.ID.String(), + Type: model.NotificationTypeCreateCollection, + Status: model.NotificationStatusPending, + }, + ResultChan: make(chan error), + } + mt.notificationProcessor.Trigger(ctx, triggerMessage) + return collection, nil +} + +func (mt *MetaTable) GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*model.Collection, error) { + mt.ddLock.RLock() + defer mt.ddLock.RUnlock() + + // There are three cases + // In the case of getting by id, we do not care about the tenant and database name. + // In the case of getting by name, we need the fully qualified path of the collection which is the tenant/database/name. + // In the case of getting by topic, we need the fully qualified path of the collection which is the tenant/database/topic. + collections := make([]*model.Collection, 0, len(mt.tenantDatabaseCollectionCache)) + if collectionID != types.NilUniqueID() { + // Case 1: getting by id + // Due to how the cache is constructed, we iterate over the whole cache to find the collection. + // This is not efficient but it is not a problem for now because the number of collections is small. + // HACK warning. TODO: fix this when we remove the cache. + for _, search_databases := range mt.tenantDatabaseCollectionCache { + for _, search_collections := range search_databases { + for _, collection := range search_collections { + if model.FilterCollection(collection, collectionID, collectionName, collectionTopic) { + collections = append(collections, collection) + } + } + } + } + } else { + // Case 2 & 3: getting by name or topic + // Note: The support for case 3 is not correct here, we shouldn't require the database name and tenant to get by topic. + if _, ok := mt.tenantDatabaseCollectionCache[tenantID]; !ok { + log.Error("tenant not found", zap.Any("tenantID", tenantID)) + return nil, common.ErrTenantNotFound + } + if _, ok := mt.tenantDatabaseCollectionCache[tenantID][databaseName]; !ok { + return nil, common.ErrDatabaseNotFound + } + for _, collection := range mt.tenantDatabaseCollectionCache[tenantID][databaseName] { + if model.FilterCollection(collection, collectionID, collectionName, collectionTopic) { + collections = append(collections, collection) + } + } + } + log.Info("meta collections", zap.Any("collections", collections)) + return collections, nil + +} + +func (mt *MetaTable) DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + tenantID := deleteCollection.TenantID + databaseName := deleteCollection.DatabaseName + collectionID := deleteCollection.ID + if _, ok := mt.tenantDatabaseCollectionCache[tenantID]; !ok { + log.Error("tenant not found", zap.Any("tenantID", tenantID)) + return common.ErrTenantNotFound + } + if _, ok := mt.tenantDatabaseCollectionCache[tenantID][databaseName]; !ok { + log.Error("database not found", zap.Any("databaseName", databaseName)) + return common.ErrDatabaseNotFound + } + collections := mt.tenantDatabaseCollectionCache[tenantID][databaseName] + + if _, ok := collections[collectionID]; !ok { + log.Error("collection not found", zap.Any("collectionID", collectionID)) + return common.ErrCollectionDeleteNonExistingCollection + } + + if err := mt.catalog.DeleteCollection(ctx, deleteCollection); err != nil { + return err + } + delete(collections, collectionID) + log.Info("collection deleted", zap.Any("collection", deleteCollection)) + + triggerMessage := notification.TriggerMessage{ + Msg: model.Notification{ + CollectionID: collectionID.String(), + Type: model.NotificationTypeDeleteCollection, + Status: model.NotificationStatusPending, + }, + ResultChan: make(chan error), + } + mt.notificationProcessor.Trigger(ctx, triggerMessage) + return nil +} + +func (mt *MetaTable) UpdateCollection(ctx context.Context, updateCollection *model.UpdateCollection) (*model.Collection, error) { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + var oldCollection *model.Collection + for tenant := range mt.tenantDatabaseCollectionCache { + for database := range mt.tenantDatabaseCollectionCache[tenant] { + for _, collection := range mt.tenantDatabaseCollectionCache[tenant][database] { + if collection.ID == updateCollection.ID { + oldCollection = collection + break + } + } + } + } + if oldCollection == nil { + log.Error("collection not found", zap.Any("collectionID", updateCollection.ID)) + return nil, common.ErrCollectionNotFound + } + + updateCollection.DatabaseName = oldCollection.DatabaseName + updateCollection.TenantID = oldCollection.TenantID + + collection, err := mt.catalog.UpdateCollection(ctx, updateCollection, updateCollection.Ts) + if err != nil { + return nil, err + } + mt.tenantDatabaseCollectionCache[collection.TenantID][collection.DatabaseName][collection.ID] = collection + log.Info("collection updated", zap.Any("collection", collection)) + return collection, nil +} + +func (mt *MetaTable) AddSegment(ctx context.Context, createSegment *model.CreateSegment) error { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + segment, err := mt.catalog.CreateSegment(ctx, createSegment, createSegment.Ts) + if err != nil { + return err + } + mt.segmentsCache[createSegment.ID] = segment + log.Info("segment added", zap.Any("segment", segment)) + return nil +} + +func (mt *MetaTable) GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*model.Segment, error) { + mt.ddLock.RLock() + defer mt.ddLock.RUnlock() + + segments := make([]*model.Segment, 0, len(mt.segmentsCache)) + for _, segment := range mt.segmentsCache { + if model.FilterSegments(segment, segmentID, segmentType, scope, topic, collectionID) { + segments = append(segments, segment) + } + } + log.Info("meta get segments", zap.Any("segments", segments)) + return segments, nil +} + +func (mt *MetaTable) DeleteSegment(ctx context.Context, segmentID types.UniqueID) error { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + if _, ok := mt.segmentsCache[segmentID]; !ok { + return common.ErrSegmentDeleteNonExistingSegment + } + + if err := mt.catalog.DeleteSegment(ctx, segmentID); err != nil { + log.Error("delete segment failed", zap.Error(err)) + return err + } + delete(mt.segmentsCache, segmentID) + log.Info("segment deleted", zap.Any("segmentID", segmentID)) + return nil +} + +func (mt *MetaTable) UpdateSegment(ctx context.Context, updateSegment *model.UpdateSegment) (*model.Segment, error) { + mt.ddLock.Lock() + defer mt.ddLock.Unlock() + + segment, err := mt.catalog.UpdateSegment(ctx, updateSegment, updateSegment.Ts) + if err != nil { + log.Error("update segment failed", zap.Error(err)) + return nil, err + } + mt.segmentsCache[updateSegment.ID] = segment + log.Info("segment updated", zap.Any("segment", segment)) + return segment, nil +} diff --git a/go/coordinator/internal/coordinator/meta_test.go b/go/coordinator/internal/coordinator/meta_test.go new file mode 100644 index 0000000000000000000000000000000000000000..d40ddf4ea3398d06b11232f42e4dc75e053be61f --- /dev/null +++ b/go/coordinator/internal/coordinator/meta_test.go @@ -0,0 +1,94 @@ +package coordinator + +import ( + "context" + "testing" + + "github.com/chroma/chroma-coordinator/internal/metastore/coordinator" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" + "pgregory.net/rapid" +) + +func testMeta(t *rapid.T) { + catalog := coordinator.NewMemoryCatalog() + mt, err := NewMetaTable(context.Background(), catalog) + if err != nil { + t.Fatalf("error creating meta table: %v", err) + } + t.Repeat(map[string]func(*rapid.T){ + "generate_collection": func(t *rapid.T) { + collection := rapid.Custom[*model.CreateCollection](func(t *rapid.T) *model.CreateCollection { + return &model.CreateCollection{ + ID: genCollectinID(t), + Name: rapid.String().Draw(t, "name"), + // Dimension: rapid.Int32().Draw(t, "dimension"), + Metadata: rapid.Custom[*model.CollectionMetadata[model.CollectionMetadataValueType]](func(t *rapid.T) *model.CollectionMetadata[model.CollectionMetadataValueType] { + return &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: rapid.MapOf[string, model.CollectionMetadataValueType](rapid.StringMatching(`[a-zA-Z0-9_]+`), drawMetadata(t)).Draw(t, "metadata"), + } + }).Draw(t, "metadata"), + } + }).Draw(t, "collection") + if _, err := mt.catalog.CreateCollection(context.Background(), collection, 0); err != nil { + t.Fatalf("error creating collection: %v", err) + } + }, + "reload": func(t *rapid.T) { + if err := mt.reload(); err != nil { + t.Fatalf("error reloading meta table: %v", err) + } + }, + "add_collection": func(t *rapid.T) { + if err := mt.reload(); err != nil { + t.Fatalf("error reloading meta table: %v", err) + } + collection := rapid.Custom[*model.CreateCollection](func(t *rapid.T) *model.CreateCollection { + return &model.CreateCollection{ + ID: genCollectinID(t), + Name: rapid.String().Draw(t, "name"), + //Dimension: rapid.Int32().Draw(t, "dimension"), + Metadata: rapid.Custom[*model.CollectionMetadata[model.CollectionMetadataValueType]](func(t *rapid.T) *model.CollectionMetadata[model.CollectionMetadataValueType] { + return &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: rapid.MapOf[string, model.CollectionMetadataValueType](rapid.StringMatching(`[a-zA-Z0-9_]+`), drawMetadata(t)).Draw(t, "metadata"), + } + }).Draw(t, "metadata"), + } + }).Draw(t, "collection") + + if _, err := mt.AddCollection(context.Background(), collection); err != nil { + t.Fatalf("error adding collection: %v", err) + } + }, + }) +} + +func drawMetadata(t *rapid.T) *rapid.Generator[model.CollectionMetadataValueType] { + return rapid.OneOf[model.CollectionMetadataValueType]( + rapid.Custom[model.CollectionMetadataValueType](func(t *rapid.T) model.CollectionMetadataValueType { + return &model.CollectionMetadataValueStringType{ + Value: rapid.String().Draw(t, "string_value"), + } + }), + rapid.Custom[model.CollectionMetadataValueType](func(t *rapid.T) model.CollectionMetadataValueType { + return &model.CollectionMetadataValueInt64Type{ + Value: rapid.Int64().Draw(t, "int_value"), + } + }), + rapid.Custom[model.CollectionMetadataValueType](func(t *rapid.T) model.CollectionMetadataValueType { + return &model.CollectionMetadataValueFloat64Type{ + Value: rapid.Float64().Draw(t, "float_value"), + } + }), + ) +} + +func genCollectinID(t *rapid.T) types.UniqueID { + return rapid.Custom[types.UniqueID](func(t *rapid.T) types.UniqueID { + return types.MustParse(rapid.StringMatching(`[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}`).Draw(t, "uuid")) + }).Draw(t, "collection_id") +} + +func TestMeta(t *testing.T) { + // rapid.Check(t, testMeta) +} diff --git a/go/coordinator/internal/grpccoordinator/collection_service.go b/go/coordinator/internal/grpccoordinator/collection_service.go new file mode 100644 index 0000000000000000000000000000000000000000..faaf6b4dbf9e3d74a0ba3d7a9e995af4ef0abf5f --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/collection_service.go @@ -0,0 +1,224 @@ +package grpccoordinator + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" + "google.golang.org/protobuf/types/known/emptypb" +) + +const errorCode = 500 +const successCode = 200 +const success = "ok" + +func (s *Server) ResetState(context.Context, *emptypb.Empty) (*coordinatorpb.ChromaResponse, error) { + res := &coordinatorpb.ChromaResponse{} + err := s.coordinator.ResetState(context.Background()) + if err != nil { + res.Status = failResponseWithError(err, errorCode) + return res, err + } + setResponseStatus(successCode) + return res, nil +} + +// Cases for get_or_create + +// Case 0 +// new_metadata is none, coll is an existing collection +// get_or_create should return the existing collection with existing metadata +// Essentially - an update with none is a no-op + +// Case 1 +// new_metadata is none, coll is a new collection +// get_or_create should create a new collection with the metadata of None + +// Case 2 +// new_metadata is not none, coll is an existing collection +// get_or_create should return the existing collection with updated metadata + +// Case 3 +// new_metadata is not none, coll is a new collection +// get_or_create should create a new collection with the new metadata, ignoring +// the metdata of in the input coll. + +// The fact that we ignore the metadata of the generated collections is a +// bit weird, but it is the easiest way to excercise all cases +func (s *Server) CreateCollection(ctx context.Context, req *coordinatorpb.CreateCollectionRequest) (*coordinatorpb.CreateCollectionResponse, error) { + res := &coordinatorpb.CreateCollectionResponse{} + createCollection, err := convertToCreateCollectionModel(req) + if err != nil { + log.Error("error converting to create collection model", zap.Error(err)) + res.Collection = &coordinatorpb.Collection{ + Id: req.Id, + Name: req.Name, + Dimension: req.Dimension, + Metadata: req.Metadata, + Tenant: req.Tenant, + Database: req.Database, + } + res.Created = false + res.Status = failResponseWithError(err, successCode) + return res, nil + } + collection, err := s.coordinator.CreateCollection(ctx, createCollection) + if err != nil { + log.Error("error creating collection", zap.Error(err)) + res.Collection = &coordinatorpb.Collection{ + Id: req.Id, + Name: req.Name, + Dimension: req.Dimension, + Metadata: req.Metadata, + Tenant: req.Tenant, + Database: req.Database, + } + res.Created = false + if err == common.ErrCollectionUniqueConstraintViolation { + res.Status = failResponseWithError(err, 409) + } else { + res.Status = failResponseWithError(err, errorCode) + } + return res, nil + } + res.Collection = convertCollectionToProto(collection) + res.Created = collection.Created + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) GetCollections(ctx context.Context, req *coordinatorpb.GetCollectionsRequest) (*coordinatorpb.GetCollectionsResponse, error) { + collectionID := req.Id + collectionName := req.Name + collectionTopic := req.Topic + tenantID := req.Tenant + databaseName := req.Database + + res := &coordinatorpb.GetCollectionsResponse{} + + parsedCollectionID, err := types.ToUniqueID(collectionID) + if err != nil { + log.Error("collection id format error", zap.String("collectionpd.id", *collectionID)) + res.Status = failResponseWithError(common.ErrCollectionIDFormat, errorCode) + return res, nil + } + + collections, err := s.coordinator.GetCollections(ctx, parsedCollectionID, collectionName, collectionTopic, tenantID, databaseName) + if err != nil { + log.Error("error getting collections", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Collections = make([]*coordinatorpb.Collection, 0, len(collections)) + for _, collection := range collections { + collectionpb := convertCollectionToProto(collection) + res.Collections = append(res.Collections, collectionpb) + } + log.Info("collection service collections", zap.Any("collections", res.Collections)) + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) DeleteCollection(ctx context.Context, req *coordinatorpb.DeleteCollectionRequest) (*coordinatorpb.ChromaResponse, error) { + collectionID := req.GetId() + res := &coordinatorpb.ChromaResponse{} + parsedCollectionID, err := types.Parse(collectionID) + if err != nil { + log.Error(err.Error(), zap.String("collectionpd.id", collectionID)) + res.Status = failResponseWithError(common.ErrCollectionIDFormat, errorCode) + return res, nil + } + deleteCollection := &model.DeleteCollection{ + ID: parsedCollectionID, + TenantID: req.GetTenant(), + DatabaseName: req.GetDatabase(), + } + err = s.coordinator.DeleteCollection(ctx, deleteCollection) + if err != nil { + log.Error(err.Error(), zap.String("collectionpd.id", collectionID)) + if err == common.ErrCollectionDeleteNonExistingCollection { + res.Status = failResponseWithError(err, 404) + } else { + res.Status = failResponseWithError(err, errorCode) + } + return res, nil + } + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) UpdateCollection(ctx context.Context, req *coordinatorpb.UpdateCollectionRequest) (*coordinatorpb.ChromaResponse, error) { + res := &coordinatorpb.ChromaResponse{} + + collectionID := req.Id + parsedCollectionID, err := types.ToUniqueID(&collectionID) + if err != nil { + log.Error("collection id format error", zap.String("collectionpd.id", collectionID)) + res.Status = failResponseWithError(common.ErrCollectionIDFormat, errorCode) + return res, nil + } + + updateCollection := &model.UpdateCollection{ + ID: parsedCollectionID, + Name: req.Name, + Topic: req.Topic, + Dimension: req.Dimension, + } + + resetMetadata := req.GetResetMetadata() + updateCollection.ResetMetadata = resetMetadata + metadata := req.GetMetadata() + // Case 1: if resetMetadata is true, then delete all metadata for the collection + // Case 2: if resetMetadata is true and metadata is not nil -> THIS SHOULD NEVER HAPPEN + // Case 3: if resetMetadata is false, and the metadata is not nil - set the metadata to the value in metadata + // Case 4: if resetMetadata is false and metadata is nil, then leave the metadata as is + if resetMetadata { + if metadata != nil { + log.Error("reset metadata is true and metadata is not nil", zap.Any("metadata", metadata)) + res.Status = failResponseWithError(common.ErrInvalidMetadataUpdate, errorCode) + return res, nil + } else { + updateCollection.Metadata = nil + } + } else { + if metadata != nil { + modelMetadata, err := convertCollectionMetadataToModel(metadata) + if err != nil { + log.Error("error converting collection metadata to model", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + updateCollection.Metadata = modelMetadata + } else { + updateCollection.Metadata = nil + } + } + + _, err = s.coordinator.UpdateCollection(ctx, updateCollection) + if err != nil { + log.Error("error updating collection", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + + res.Status = setResponseStatus(successCode) + return res, nil +} + +func failResponseWithError(err error, code int32) *coordinatorpb.Status { + return &coordinatorpb.Status{ + Reason: err.Error(), + Code: code, + } +} + +func setResponseStatus(code int32) *coordinatorpb.Status { + return &coordinatorpb.Status{ + Reason: success, + Code: code, + } +} diff --git a/go/coordinator/internal/grpccoordinator/collection_service_test.go b/go/coordinator/internal/grpccoordinator/collection_service_test.go new file mode 100644 index 0000000000000000000000000000000000000000..390b08f7607537be465846a3daa8b1a8451f2b5e --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/collection_service_test.go @@ -0,0 +1,125 @@ +package grpccoordinator + +import ( + "context" + "testing" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/grpccoordinator/grpcutils" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbcore" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "pgregory.net/rapid" +) + +// CreateCollection +// Collection created successfully are visible to ListCollections +// Collection created should have the right metadata, the metadata should be a flat map, with keys as strings and values as strings, ints, or floats +// Collection created should have the right name +// Collection created should have the right ID +// Collection created should have the right topic +// Collection created should have the right timestamp +func testCollection(t *rapid.T) { + db := dbcore.ConfigDatabaseForTesting() + s, err := NewWithGrpcProvider(Config{ + AssignmentPolicy: "simple", + SystemCatalogProvider: "memory", + NotificationStoreProvider: "memory", + NotifierProvider: "memory", + Testing: true}, grpcutils.Default, db) + if err != nil { + t.Fatalf("error creating server: %v", err) + } + var state []*coordinatorpb.Collection + var collectionsWithErrors []*coordinatorpb.Collection + + t.Repeat(map[string]func(*rapid.T){ + "create_collection": func(t *rapid.T) { + stringValue := generateStringMetadataValue(t) + intValue := generateInt64MetadataValue(t) + floatValue := generateFloat64MetadataValue(t) + getOrCreate := false + + createCollectionRequest := rapid.Custom[*coordinatorpb.CreateCollectionRequest](func(t *rapid.T) *coordinatorpb.CreateCollectionRequest { + return &coordinatorpb.CreateCollectionRequest{ + Id: rapid.StringMatching(`[0-9a-f]{8}-[0-9a-f]{4}-4[0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}`).Draw(t, "collection_id"), + Name: rapid.String().Draw(t, "collection_name"), + Metadata: &coordinatorpb.UpdateMetadata{ + Metadata: map[string]*coordinatorpb.UpdateMetadataValue{ + "string_value": stringValue, + "int_value": intValue, + "float_value": floatValue, + }, + }, + GetOrCreate: &getOrCreate, + } + }).Draw(t, "create_collection_request") + + ctx := context.Background() + res, err := s.CreateCollection(ctx, createCollectionRequest) + if err != nil { + if err == common.ErrCollectionNameEmpty && createCollectionRequest.Name == "" { + t.Logf("expected error for empty collection name") + collectionsWithErrors = append(collectionsWithErrors, res.Collection) + } else if err == common.ErrCollectionTopicEmpty { + t.Logf("expected error for empty collection topic") + collectionsWithErrors = append(collectionsWithErrors, res.Collection) + // TODO: check the topic name not empty + } else { + t.Fatalf("error creating collection: %v", err) + collectionsWithErrors = append(collectionsWithErrors, res.Collection) + } + } + + getCollectionsRequest := coordinatorpb.GetCollectionsRequest{ + Id: &createCollectionRequest.Id, + } + if err == nil { + // verify the correctness + GetCollectionsResponse, err := s.GetCollections(ctx, &getCollectionsRequest) + if err != nil { + t.Fatalf("error getting collections: %v", err) + } + collectionList := GetCollectionsResponse.GetCollections() + if len(collectionList) != 1 { + t.Fatalf("More than 1 collection with the same collection id") + } + for _, collection := range collectionList { + if collection.Id != createCollectionRequest.Id { + t.Fatalf("collection id is the right value") + } + } + state = append(state, res.Collection) + } + }, + "get_collections": func(t *rapid.T) { + }, + }) +} + +func generateStringMetadataValue(t *rapid.T) *coordinatorpb.UpdateMetadataValue { + return &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_StringValue{ + StringValue: rapid.String().Draw(t, "string_value"), + }, + } +} + +func generateInt64MetadataValue(t *rapid.T) *coordinatorpb.UpdateMetadataValue { + return &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_IntValue{ + IntValue: rapid.Int64().Draw(t, "int_value"), + }, + } +} + +func generateFloat64MetadataValue(t *rapid.T) *coordinatorpb.UpdateMetadataValue { + return &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_FloatValue{ + FloatValue: rapid.Float64().Draw(t, "float_value"), + }, + } +} + +func TestCollection(t *testing.T) { + // rapid.Check(t, testCollection) +} diff --git a/go/coordinator/internal/grpccoordinator/grpcutils/config.go b/go/coordinator/internal/grpccoordinator/grpcutils/config.go new file mode 100644 index 0000000000000000000000000000000000000000..15ed30dbd320ca5086fbdf8b40f5478fb690c385 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/grpcutils/config.go @@ -0,0 +1,15 @@ +package grpcutils + +type GrpcConfig struct { + // BindAddress is the address to bind the GRPC server to. + BindAddress string + + // GRPC mTLS config + CertPath string + KeyPath string + CAPath string +} + +func (c *GrpcConfig) MTLSEnabled() bool { + return c.CertPath != "" && c.KeyPath != "" && c.CAPath != "" +} diff --git a/go/coordinator/internal/grpccoordinator/grpcutils/config_test.go b/go/coordinator/internal/grpccoordinator/grpcutils/config_test.go new file mode 100644 index 0000000000000000000000000000000000000000..ada7d1bd77e59f0315ec779808968e46e56b6a9e --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/grpcutils/config_test.go @@ -0,0 +1,37 @@ +package grpcutils + +import "testing" + +func TestGrpcConfig_TLSEnabled(t *testing.T) { + // Create a list of configs and expected check result (true/false) + cfgs := []*GrpcConfig{ + { + CertPath: "cert", + KeyPath: "key", + CAPath: "ca", + }, + { + CertPath: "", + KeyPath: "", + CAPath: "", + }, + { + CertPath: "cert", + KeyPath: "", + CAPath: "ca", + }, + { + CertPath: "", + KeyPath: "key", + CAPath: "ca", + }, + } + expected := []bool{true, false, false, false} + + // Iterate through the list of configs and check if the result matches the expected result + for i, cfg := range cfgs { + if cfg.MTLSEnabled() != expected[i] { + t.Errorf("Expected %v, got %v", expected[i], cfg.MTLSEnabled()) + } + } +} diff --git a/go/coordinator/internal/grpccoordinator/grpcutils/service.go b/go/coordinator/internal/grpccoordinator/grpcutils/service.go new file mode 100644 index 0000000000000000000000000000000000000000..e721f2158f9c6acba2be4e0207429a7ed79c9b11 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/grpcutils/service.go @@ -0,0 +1,102 @@ +package grpcutils + +import ( + "crypto/tls" + "crypto/x509" + "io" + "net" + "os" + + "github.com/pingcap/log" + "go.uber.org/zap" + "google.golang.org/grpc" + "google.golang.org/grpc/credentials" +) + +const ( + maxGrpcFrameSize = 256 * 1024 * 1024 + + ReadinessProbeService = "chroma-readiness" +) + +type GrpcServer interface { + io.Closer + + Port() int +} + +type GrpcProvider interface { + StartGrpcServer(name string, grpcConfig *GrpcConfig, registerFunc func(grpc.ServiceRegistrar)) (GrpcServer, error) +} + +var Default = &defaultProvider{} + +type defaultProvider struct { +} + +func (d *defaultProvider) StartGrpcServer(name string, grpcConfig *GrpcConfig, registerFunc func(grpc.ServiceRegistrar)) (GrpcServer, error) { + return newDefaultGrpcProvider(name, grpcConfig, registerFunc) +} + +type defaultGrpcServer struct { + io.Closer + server *grpc.Server + port int +} + +func newDefaultGrpcProvider(name string, grpcConfig *GrpcConfig, registerFunc func(grpc.ServiceRegistrar)) (GrpcServer, error) { + var opts []grpc.ServerOption + opts = append(opts, grpc.MaxRecvMsgSize(maxGrpcFrameSize)) + if grpcConfig.MTLSEnabled() { + cert, err := tls.LoadX509KeyPair(grpcConfig.CertPath, grpcConfig.KeyPath) + if err != nil { + return nil, err + } + + ca := x509.NewCertPool() + caBytes, err := os.ReadFile(grpcConfig.CAPath) + if err != nil { + return nil, err + } + if !ca.AppendCertsFromPEM(caBytes) { + return nil, err + } + + tlsConfig := &tls.Config{ + Certificates: []tls.Certificate{cert}, + ClientCAs: ca, + ClientAuth: tls.RequireAndVerifyClientCert, + } + + opts = append(opts, grpc.Creds(credentials.NewTLS(tlsConfig))) + } + + c := &defaultGrpcServer{ + server: grpc.NewServer(opts...), + } + registerFunc(c.server) + + listener, err := net.Listen("tcp", grpcConfig.BindAddress) + if err != nil { + return nil, err + } + + c.port = listener.Addr().(*net.TCPAddr).Port + + log.Info("Started Grpc server") + if err := c.server.Serve(listener); err != nil { + log.Fatal("Failed to start serving", zap.Error(err)) + } + + return c, nil +} + +func (c *defaultGrpcServer) Port() int { + return c.port +} + +func (c *defaultGrpcServer) Close() error { + c.server.GracefulStop() + log.Info("Stopped Grpc server") + return nil +} diff --git a/go/coordinator/internal/grpccoordinator/proto_model_convert.go b/go/coordinator/internal/grpccoordinator/proto_model_convert.go new file mode 100644 index 0000000000000000000000000000000000000000..18c4fd307ab24423516fd9d31fff8fd0fb180c16 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/proto_model_convert.go @@ -0,0 +1,227 @@ +package grpccoordinator + +import ( + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +func convertCollectionMetadataToModel(collectionMetadata *coordinatorpb.UpdateMetadata) (*model.CollectionMetadata[model.CollectionMetadataValueType], error) { + if collectionMetadata == nil { + return nil, nil + } + + metadata := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + for key, value := range collectionMetadata.Metadata { + switch v := (value.Value).(type) { + case *coordinatorpb.UpdateMetadataValue_StringValue: + metadata.Add(key, &model.CollectionMetadataValueStringType{Value: v.StringValue}) + case *coordinatorpb.UpdateMetadataValue_IntValue: + metadata.Add(key, &model.CollectionMetadataValueInt64Type{Value: v.IntValue}) + case *coordinatorpb.UpdateMetadataValue_FloatValue: + metadata.Add(key, &model.CollectionMetadataValueFloat64Type{Value: v.FloatValue}) + default: + log.Error("collection metadata value type not supported", zap.Any("metadata value", value)) + return nil, common.ErrUnknownCollectionMetadataType + } + } + log.Debug("collection metadata in model", zap.Any("metadata", metadata)) + return metadata, nil +} + +func convertCollectionToProto(collection *model.Collection) *coordinatorpb.Collection { + if collection == nil { + return nil + } + + collectionpb := &coordinatorpb.Collection{ + Id: collection.ID.String(), + Name: collection.Name, + Topic: collection.Topic, + Dimension: collection.Dimension, + Tenant: collection.TenantID, + Database: collection.DatabaseName, + } + if collection.Metadata == nil { + return collectionpb + } + + metadatapb := convertCollectionMetadataToProto(collection.Metadata) + collectionpb.Metadata = metadatapb + return collectionpb +} + +func convertCollectionMetadataToProto(collectionMetadata *model.CollectionMetadata[model.CollectionMetadataValueType]) *coordinatorpb.UpdateMetadata { + if collectionMetadata == nil { + return nil + } + metadatapb := &coordinatorpb.UpdateMetadata{ + Metadata: make(map[string]*coordinatorpb.UpdateMetadataValue), + } + for key, value := range collectionMetadata.Metadata { + switch v := (value).(type) { + case *model.CollectionMetadataValueStringType: + metadatapb.Metadata[key] = &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_StringValue{ + StringValue: v.Value, + }, + } + case *model.CollectionMetadataValueInt64Type: + metadatapb.Metadata[key] = &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_IntValue{ + IntValue: v.Value, + }, + } + case *model.CollectionMetadataValueFloat64Type: + metadatapb.Metadata[key] = &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_FloatValue{ + FloatValue: v.Value, + }, + } + default: + log.Error("collection metadata value type not supported", zap.Any("metadata value", value)) + } + } + return metadatapb +} + +func convertToCreateCollectionModel(req *coordinatorpb.CreateCollectionRequest) (*model.CreateCollection, error) { + collectionID, err := types.ToUniqueID(&req.Id) + if err != nil { + log.Error("collection id format error", zap.String("collectionpd.id", req.Id)) + return nil, common.ErrCollectionIDFormat + } + + metadatapb := req.Metadata + metadata, err := convertCollectionMetadataToModel(metadatapb) + if err != nil { + return nil, err + } + + return &model.CreateCollection{ + ID: collectionID, + Name: req.Name, + Dimension: req.Dimension, + Metadata: metadata, + GetOrCreate: req.GetGetOrCreate(), + TenantID: req.GetTenant(), + DatabaseName: req.GetDatabase(), + }, nil +} + +func convertSegmentMetadataToModel(segmentMetadata *coordinatorpb.UpdateMetadata) (*model.SegmentMetadata[model.SegmentMetadataValueType], error) { + if segmentMetadata == nil { + return nil, nil + } + + metadata := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + for key, value := range segmentMetadata.Metadata { + if value.Value == nil { + log.Info("segment metadata value is nil", zap.String("key", key)) + metadata.Set(key, nil) + continue + } + switch v := (value.Value).(type) { + case *coordinatorpb.UpdateMetadataValue_StringValue: + metadata.Set(key, &model.SegmentMetadataValueStringType{Value: v.StringValue}) + case *coordinatorpb.UpdateMetadataValue_IntValue: + metadata.Set(key, &model.SegmentMetadataValueInt64Type{Value: v.IntValue}) + case *coordinatorpb.UpdateMetadataValue_FloatValue: + metadata.Set(key, &model.SegmentMetadataValueFloat64Type{Value: v.FloatValue}) + default: + log.Error("segment metadata value type not supported", zap.Any("metadata value", value)) + return nil, common.ErrUnknownSegmentMetadataType + } + } + return metadata, nil +} + +func convertSegmentToProto(segment *model.Segment) *coordinatorpb.Segment { + if segment == nil { + return nil + } + scope := coordinatorpb.SegmentScope_value[segment.Scope] + segmentSceope := coordinatorpb.SegmentScope(scope) + segmentpb := &coordinatorpb.Segment{ + Id: segment.ID.String(), + Type: segment.Type, + Scope: segmentSceope, + Topic: segment.Topic, + Collection: nil, + Metadata: nil, + } + + collectionID := segment.CollectionID + if collectionID != types.NilUniqueID() { + collectionIDString := collectionID.String() + segmentpb.Collection = &collectionIDString + } + + if segment.Metadata == nil { + return segmentpb + } + + metadatapb := convertSegmentMetadataToProto(segment.Metadata) + segmentpb.Metadata = metadatapb + log.Debug("segment", zap.Any("segment", segmentpb)) + return segmentpb +} + +func convertSegmentMetadataToProto(segmentMetadata *model.SegmentMetadata[model.SegmentMetadataValueType]) *coordinatorpb.UpdateMetadata { + metadatapb := &coordinatorpb.UpdateMetadata{ + Metadata: make(map[string]*coordinatorpb.UpdateMetadataValue), + } + + for key, value := range segmentMetadata.Metadata { + switch v := value.(type) { + case *model.SegmentMetadataValueStringType: + metadatapb.Metadata[key] = &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_StringValue{StringValue: v.Value}, + } + case *model.SegmentMetadataValueInt64Type: + metadatapb.Metadata[key] = &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_IntValue{IntValue: v.Value}, + } + case *model.SegmentMetadataValueFloat64Type: + metadatapb.Metadata[key] = &coordinatorpb.UpdateMetadataValue{ + Value: &coordinatorpb.UpdateMetadataValue_FloatValue{FloatValue: v.Value}, + } + default: + log.Error("segment metadata value type not supported", zap.Any("metadata value", value)) + } + } + return metadatapb +} + +func convertSegmentToModel(segmentpb *coordinatorpb.Segment) (*model.CreateSegment, error) { + segmentID, err := types.ToUniqueID(&segmentpb.Id) + if err != nil { + log.Error("segment id format error", zap.String("segment.id", segmentpb.Id)) + return nil, common.ErrSegmentIDFormat + } + + collectionID, err := types.ToUniqueID(segmentpb.Collection) + if err != nil { + log.Error("collection id format error", zap.String("collectionpd.id", *segmentpb.Collection)) + return nil, common.ErrCollectionIDFormat + } + + metadatapb := segmentpb.Metadata + metadata, err := convertSegmentMetadataToModel(metadatapb) + if err != nil { + log.Error("convert segment metadata to model error", zap.Error(err)) + return nil, err + } + + return &model.CreateSegment{ + ID: segmentID, + Type: segmentpb.Type, + Scope: segmentpb.Scope.String(), + Topic: segmentpb.Topic, + CollectionID: collectionID, + Metadata: metadata, + }, nil +} diff --git a/go/coordinator/internal/grpccoordinator/proto_model_convert_test.go b/go/coordinator/internal/grpccoordinator/proto_model_convert_test.go new file mode 100644 index 0000000000000000000000000000000000000000..9cfa2f0632fe442db4ca6a5296be009a9e28ece7 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/proto_model_convert_test.go @@ -0,0 +1,201 @@ +package grpccoordinator + +import ( + "testing" + + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/stretchr/testify/assert" +) + +func TestConvertCollectionMetadataToModel(t *testing.T) { + // Test case 1: collectionMetadata is nil + metadata, err := convertCollectionMetadataToModel(nil) + assert.Nil(t, metadata) + assert.Nil(t, err) + + // Test case 2: collectionMetadata is not nil + collectionMetadata := &coordinatorpb.UpdateMetadata{ + Metadata: map[string]*coordinatorpb.UpdateMetadataValue{ + "key1": { + Value: &coordinatorpb.UpdateMetadataValue_StringValue{ + StringValue: "value1", + }, + }, + "key2": { + Value: &coordinatorpb.UpdateMetadataValue_IntValue{ + IntValue: 123, + }, + }, + "key3": { + Value: &coordinatorpb.UpdateMetadataValue_FloatValue{ + FloatValue: 3.14, + }, + }, + }, + } + metadata, err = convertCollectionMetadataToModel(collectionMetadata) + assert.NotNil(t, metadata) + assert.Nil(t, err) + assert.Equal(t, "value1", metadata.Get("key1").(*model.CollectionMetadataValueStringType).Value) + assert.Equal(t, int64(123), metadata.Get("key2").(*model.CollectionMetadataValueInt64Type).Value) + assert.Equal(t, 3.14, metadata.Get("key3").(*model.CollectionMetadataValueFloat64Type).Value) +} + +func TestConvertCollectionToProto(t *testing.T) { + // Test case 1: collection is nil + collectionpb := convertCollectionToProto(nil) + assert.Nil(t, collectionpb) + + // Test case 2: collection is not nil + dimention := int32(10) + collection := &model.Collection{ + ID: types.NewUniqueID(), + Name: "test_collection", + Topic: "test_topic", + Dimension: &dimention, + Metadata: &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: map[string]model.CollectionMetadataValueType{ + "key1": &model.CollectionMetadataValueStringType{Value: "value1"}, + "key2": &model.CollectionMetadataValueInt64Type{Value: 123}, + "key3": &model.CollectionMetadataValueFloat64Type{Value: 3.14}, + }, + }, + } + collectionpb = convertCollectionToProto(collection) + assert.NotNil(t, collectionpb) + assert.Equal(t, collection.ID.String(), collectionpb.Id) + assert.Equal(t, collection.Name, collectionpb.Name) + assert.Equal(t, collection.Topic, collectionpb.Topic) + assert.Equal(t, collection.Dimension, collectionpb.Dimension) + assert.NotNil(t, collectionpb.Metadata) + assert.Equal(t, "value1", collectionpb.Metadata.Metadata["key1"].GetStringValue()) + assert.Equal(t, int64(123), collectionpb.Metadata.Metadata["key2"].GetIntValue()) + assert.Equal(t, 3.14, collectionpb.Metadata.Metadata["key3"].GetFloatValue()) +} + +func TestConvertCollectionMetadataToProto(t *testing.T) { + // Test case 1: collectionMetadata is nil + metadatapb := convertCollectionMetadataToProto(nil) + assert.Nil(t, metadatapb) + + // Test case 2: collectionMetadata is not nil + collectionMetadata := &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: map[string]model.CollectionMetadataValueType{ + "key1": &model.CollectionMetadataValueStringType{Value: "value1"}, + "key2": &model.CollectionMetadataValueInt64Type{Value: 123}, + "key3": &model.CollectionMetadataValueFloat64Type{Value: 3.14}, + }, + } + metadatapb = convertCollectionMetadataToProto(collectionMetadata) + assert.NotNil(t, metadatapb) + assert.Equal(t, "value1", metadatapb.Metadata["key1"].GetStringValue()) + assert.Equal(t, int64(123), metadatapb.Metadata["key2"].GetIntValue()) + assert.Equal(t, 3.14, metadatapb.Metadata["key3"].GetFloatValue()) +} + +func TestConvertToCreateCollectionModel(t *testing.T) { + // Test case 1: id is not a valid UUID + req := &coordinatorpb.CreateCollectionRequest{ + Id: "invalid_uuid", + } + collectionMetadata, err := convertToCreateCollectionModel(req) + assert.Nil(t, collectionMetadata) + assert.NotNil(t, err) + + // Test case 2: everything is valid + testDimension := int32(10) + req = &coordinatorpb.CreateCollectionRequest{ + Id: "e9e9d6c8-9e1a-4c5c-9b8c-8f6f5e5d5d5d", + Name: "test_collection", + Metadata: &coordinatorpb.UpdateMetadata{ + Metadata: map[string]*coordinatorpb.UpdateMetadataValue{ + "key1": { + Value: &coordinatorpb.UpdateMetadataValue_StringValue{ + StringValue: "value1", + }, + }, + "key2": { + Value: &coordinatorpb.UpdateMetadataValue_IntValue{ + IntValue: 123, + }, + }, + "key3": { + Value: &coordinatorpb.UpdateMetadataValue_FloatValue{ + FloatValue: 3.14, + }, + }, + }, + }, + Dimension: &testDimension, + } + collectionMetadata, err = convertToCreateCollectionModel(req) + assert.NotNil(t, collectionMetadata) + assert.Nil(t, err) + assert.Equal(t, "e9e9d6c8-9e1a-4c5c-9b8c-8f6f5e5d5d5d", collectionMetadata.ID.String()) + assert.Equal(t, "test_collection", collectionMetadata.Name) + assert.Equal(t, int32(10), *collectionMetadata.Dimension) + assert.NotNil(t, collectionMetadata.Metadata) + assert.Equal(t, "value1", collectionMetadata.Metadata.Get("key1").(*model.CollectionMetadataValueStringType).Value) + assert.Equal(t, int64(123), collectionMetadata.Metadata.Get("key2").(*model.CollectionMetadataValueInt64Type).Value) + assert.Equal(t, 3.14, collectionMetadata.Metadata.Get("key3").(*model.CollectionMetadataValueFloat64Type).Value) +} + +func TestConvertSegmentMetadataToModel(t *testing.T) { + // Test case 1: segmentMetadata is nil + metadata, err := convertSegmentMetadataToModel(nil) + assert.Nil(t, metadata) + assert.Nil(t, err) + + // Test case 2: segmentMetadata is not nil + segmentMetadata := &coordinatorpb.UpdateMetadata{ + Metadata: map[string]*coordinatorpb.UpdateMetadataValue{ + "key1": { + Value: &coordinatorpb.UpdateMetadataValue_StringValue{ + StringValue: "value1", + }, + }, + "key2": { + Value: &coordinatorpb.UpdateMetadataValue_IntValue{ + IntValue: 123, + }, + }, + "key3": { + Value: &coordinatorpb.UpdateMetadataValue_FloatValue{ + FloatValue: 3.14, + }, + }, + }, + } + metadata, err = convertSegmentMetadataToModel(segmentMetadata) + assert.NotNil(t, metadata) + assert.Nil(t, err) + assert.Equal(t, "value1", metadata.Get("key1").(*model.SegmentMetadataValueStringType).Value) + assert.Equal(t, int64(123), metadata.Get("key2").(*model.SegmentMetadataValueInt64Type).Value) + assert.Equal(t, 3.14, metadata.Get("key3").(*model.SegmentMetadataValueFloat64Type).Value) +} + +func TestConvertSegmentToProto(t *testing.T) { + // Test case 1: segment is nil + segmentpb := convertSegmentToProto(nil) + assert.Nil(t, segmentpb) + + // Test case 2: segment is not nil + testTopic := "test_topic" + segment := &model.Segment{ + ID: types.NewUniqueID(), + Type: "test_type", + Scope: "METADATA", + Topic: &testTopic, + Metadata: nil, + } + segmentpb = convertSegmentToProto(segment) + assert.NotNil(t, segmentpb) + assert.Equal(t, segment.ID.String(), segmentpb.Id) + assert.Equal(t, segment.Type, segmentpb.Type) + assert.Equal(t, coordinatorpb.SegmentScope_METADATA, segmentpb.Scope) + assert.Equal(t, segment.Topic, segmentpb.Topic) + assert.Nil(t, segmentpb.Collection) + assert.Nil(t, segmentpb.Metadata) +} diff --git a/go/coordinator/internal/grpccoordinator/segment_service.go b/go/coordinator/internal/grpccoordinator/segment_service.go new file mode 100644 index 0000000000000000000000000000000000000000..b2d3be5e4ff2df0febbd4378708c3ffdc3fbd0d9 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/segment_service.go @@ -0,0 +1,151 @@ +package grpccoordinator + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +func (s *Server) CreateSegment(ctx context.Context, req *coordinatorpb.CreateSegmentRequest) (*coordinatorpb.ChromaResponse, error) { + segmentpb := req.GetSegment() + + res := &coordinatorpb.ChromaResponse{} + + segment, err := convertSegmentToModel(segmentpb) + if err != nil { + log.Error("convert segment to model error", zap.Error(err)) + res.Status = failResponseWithError(common.ErrSegmentIDFormat, errorCode) + return res, nil + } + + err = s.coordinator.CreateSegment(ctx, segment) + if err != nil { + if err == common.ErrSegmentUniqueConstraintViolation { + log.Error("segment id already exist", zap.Error(err)) + res.Status = failResponseWithError(err, 409) + return res, nil + } + log.Error("create segment error", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Status = setResponseStatus(successCode) + + return res, nil +} + +func (s *Server) GetSegments(ctx context.Context, req *coordinatorpb.GetSegmentsRequest) (*coordinatorpb.GetSegmentsResponse, error) { + segmentID := req.Id + segmentType := req.Type + scope := req.Scope + topic := req.Topic + collectionID := req.Collection + res := &coordinatorpb.GetSegmentsResponse{} + + parsedSegmentID, err := types.ToUniqueID(segmentID) + if err != nil { + log.Error("segment id format error", zap.String("segment.id", *segmentID)) + res.Status = failResponseWithError(common.ErrSegmentIDFormat, errorCode) + return res, nil + } + + parsedCollectionID, err := types.ToUniqueID(collectionID) + if err != nil { + log.Error("collection id format error", zap.String("collectionpd.id", *collectionID)) + res.Status = failResponseWithError(common.ErrCollectionIDFormat, errorCode) + return res, nil + } + var scopeValue *string + if scope == nil { + scopeValue = nil + } else { + scopeString := scope.String() + scopeValue = &scopeString + } + segments, err := s.coordinator.GetSegments(ctx, parsedSegmentID, segmentType, scopeValue, topic, parsedCollectionID) + if err != nil { + log.Error("get segments error", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + + segmentpbList := make([]*coordinatorpb.Segment, 0, len(segments)) + for _, segment := range segments { + segmentpb := convertSegmentToProto(segment) + segmentpbList = append(segmentpbList, segmentpb) + } + res.Segments = segmentpbList + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) DeleteSegment(ctx context.Context, req *coordinatorpb.DeleteSegmentRequest) (*coordinatorpb.ChromaResponse, error) { + segmentID := req.GetId() + res := &coordinatorpb.ChromaResponse{} + parsedSegmentID, err := types.Parse(segmentID) + if err != nil { + log.Error(err.Error(), zap.String("segment.id", segmentID)) + res.Status = failResponseWithError(common.ErrSegmentIDFormat, errorCode) + return res, nil + } + err = s.coordinator.DeleteSegment(ctx, parsedSegmentID) + if err != nil { + if err == common.ErrSegmentDeleteNonExistingSegment { + log.Error(err.Error(), zap.String("segment.id", segmentID)) + res.Status = failResponseWithError(err, 404) + return res, nil + } + log.Error(err.Error(), zap.String("segment.id", segmentID)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) UpdateSegment(ctx context.Context, req *coordinatorpb.UpdateSegmentRequest) (*coordinatorpb.ChromaResponse, error) { + res := &coordinatorpb.ChromaResponse{} + updateSegment := &model.UpdateSegment{ + ID: types.MustParse(req.Id), + ResetTopic: req.GetResetTopic(), + ResetCollection: req.GetResetCollection(), + ResetMetadata: req.GetResetMetadata(), + } + topic := req.GetTopic() + if topic == "" { + updateSegment.Topic = nil + } else { + updateSegment.Topic = &topic + } + collection := req.GetCollection() + if collection == "" { + updateSegment.Collection = nil + } else { + updateSegment.Collection = &collection + } + metadata := req.GetMetadata() + if metadata == nil { + updateSegment.Metadata = nil + } else { + modelMetadata, err := convertSegmentMetadataToModel(metadata) + if err != nil { + log.Error("convert segment metadata to model error", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + updateSegment.Metadata = modelMetadata + } + _, err := s.coordinator.UpdateSegment(ctx, updateSegment) + if err != nil { + log.Error("update segment error", zap.Error(err)) + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Status = setResponseStatus(successCode) + return res, nil +} diff --git a/go/coordinator/internal/grpccoordinator/server.go b/go/coordinator/internal/grpccoordinator/server.go new file mode 100644 index 0000000000000000000000000000000000000000..4205a47153b60d5967901d6c65b2e421eddaa7f0 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/server.go @@ -0,0 +1,232 @@ +package grpccoordinator + +import ( + "context" + "errors" + "time" + + "github.com/apache/pulsar-client-go/pulsar" + "github.com/chroma/chroma-coordinator/internal/coordinator" + "github.com/chroma/chroma-coordinator/internal/grpccoordinator/grpcutils" + "github.com/chroma/chroma-coordinator/internal/memberlist_manager" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dao" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbcore" + "github.com/chroma/chroma-coordinator/internal/notification" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "github.com/chroma/chroma-coordinator/internal/utils" + "github.com/pingcap/log" + "go.uber.org/zap" + "google.golang.org/grpc" + "google.golang.org/grpc/health" + "gorm.io/gorm" +) + +type Config struct { + // GrpcConfig config + GrpcConfig *grpcutils.GrpcConfig + + // System catalog provider + SystemCatalogProvider string + + // MetaTable config + Username string + Password string + Address string + Port int + DBName string + MaxIdleConns int + MaxOpenConns int + + // Notification config + NotificationStoreProvider string + NotifierProvider string + NotificationTopic string + + // Pulsar config + PulsarAdminURL string + PulsarURL string + PulsarTenant string + PulsarNamespace string + + // Kubernetes config + KubernetesNamespace string + WorkerMemberlistName string + + // Assignment policy config can be "simple" or "rendezvous" + AssignmentPolicy string + + // Watcher config + WatchInterval time.Duration + + // Config for testing + Testing bool +} + +// Server wraps Coordinator with GRPC services. +// +// When Testing is set to true, the GRPC services will not be intialzed. This is +// convenient for end-to-end property based testing. +type Server struct { + coordinatorpb.UnimplementedSysDBServer + coordinator coordinator.ICoordinator + grpcServer grpcutils.GrpcServer + healthServer *health.Server +} + +func New(config Config) (*Server, error) { + if config.SystemCatalogProvider == "memory" { + return NewWithGrpcProvider(config, grpcutils.Default, nil) + } else if config.SystemCatalogProvider == "database" { + dBConfig := dbcore.DBConfig{ + Username: config.Username, + Password: config.Password, + Address: config.Address, + Port: config.Port, + DBName: config.DBName, + MaxIdleConns: config.MaxIdleConns, + MaxOpenConns: config.MaxOpenConns, + } + db, err := dbcore.Connect(dBConfig) + if err != nil { + return nil, err + } + return NewWithGrpcProvider(config, grpcutils.Default, db) + } else { + return nil, errors.New("invalid system catalog provider, only memory and database are supported") + } +} + +func NewWithGrpcProvider(config Config, provider grpcutils.GrpcProvider, db *gorm.DB) (*Server, error) { + ctx := context.Background() + s := &Server{ + healthServer: health.NewServer(), + } + + var assignmentPolicy coordinator.CollectionAssignmentPolicy + if config.AssignmentPolicy == "simple" { + log.Info("Using simple assignment policy") + assignmentPolicy = coordinator.NewSimpleAssignmentPolicy(config.PulsarTenant, config.PulsarNamespace) + } else if config.AssignmentPolicy == "rendezvous" { + log.Info("Using rendezvous assignment policy") + err := utils.CreateTopics(config.PulsarAdminURL, config.PulsarTenant, config.PulsarNamespace, coordinator.Topics[:]) + if err != nil { + log.Error("Failed to create topics", zap.Error(err)) + return nil, err + } + assignmentPolicy = coordinator.NewRendezvousAssignmentPolicy(config.PulsarTenant, config.PulsarNamespace) + } else { + return nil, errors.New("invalid assignment policy, only simple and rendezvous are supported") + } + + var notificationStore notification.NotificationStore + if config.NotificationStoreProvider == "memory" { + log.Info("Using memory notification store") + notificationStore = notification.NewMemoryNotificationStore() + } else if config.NotificationStoreProvider == "database" { + txnImpl := dbcore.NewTxImpl() + metaDomain := dao.NewMetaDomain() + notificationStore = notification.NewDatabaseNotificationStore(txnImpl, metaDomain) + } else { + return nil, errors.New("invalid notification store provider, only memory and database are supported") + } + + var notifier notification.Notifier + var client pulsar.Client + var producer pulsar.Producer + if config.NotifierProvider == "memory" { + log.Info("Using memory notifier") + notifier = notification.NewMemoryNotifier() + } else if config.NotifierProvider == "pulsar" { + log.Info("Using pulsar notifier") + pulsarNotifier, pulsarClient, pulsarProducer, err := createPulsarNotifer(config.PulsarURL, config.NotificationTopic) + notifier = pulsarNotifier + client = pulsarClient + producer = pulsarProducer + if err != nil { + log.Error("Failed to create pulsar notifier", zap.Error(err)) + return nil, err + } + } else { + return nil, errors.New("invalid notifier provider, only memory and pulsar are supported") + } + + if client != nil { + defer client.Close() + } + if producer != nil { + defer producer.Close() + } + + coordinator, err := coordinator.NewCoordinator(ctx, assignmentPolicy, db, notificationStore, notifier) + if err != nil { + return nil, err + } + s.coordinator = coordinator + s.coordinator.Start() + if !config.Testing { + memberlist_manager, err := createMemberlistManager(config) + if err != nil { + return nil, err + } + + // Start the memberlist manager + err = memberlist_manager.Start() + if err != nil { + return nil, err + } + + s.grpcServer, err = provider.StartGrpcServer("coordinator", config.GrpcConfig, func(registrar grpc.ServiceRegistrar) { + coordinatorpb.RegisterSysDBServer(registrar, s) + }) + if err != nil { + return nil, err + } + } + return s, nil +} + +func createMemberlistManager(config Config) (*memberlist_manager.MemberlistManager, error) { + // TODO: Make this configuration + log.Info("Starting memberlist manager") + memberlist_name := config.WorkerMemberlistName + namespace := config.KubernetesNamespace + clientset, err := utils.GetKubernetesInterface() + if err != nil { + return nil, err + } + dynamicClient, err := utils.GetKubernetesDynamicInterface() + if err != nil { + return nil, err + } + nodeWatcher := memberlist_manager.NewKubernetesWatcher(clientset, namespace, "worker", config.WatchInterval) + memberlistStore := memberlist_manager.NewCRMemberlistStore(dynamicClient, namespace, memberlist_name) + memberlist_manager := memberlist_manager.NewMemberlistManager(nodeWatcher, memberlistStore) + return memberlist_manager, nil +} + +func createPulsarNotifer(pulsarURL string, notificationTopic string) (*notification.PulsarNotifier, pulsar.Client, pulsar.Producer, error) { + client, err := pulsar.NewClient(pulsar.ClientOptions{ + URL: pulsarURL, + }) + if err != nil { + log.Error("Failed to create pulsar client", zap.Error(err)) + return nil, nil, nil, err + } + + producer, err := client.CreateProducer(pulsar.ProducerOptions{ + Topic: notificationTopic, + }) + if err != nil { + log.Error("Failed to create producer", zap.Error(err)) + return nil, nil, nil, err + } + + notifier := notification.NewPulsarNotifier(producer) + return notifier, client, producer, nil +} + +func (s *Server) Close() error { + s.healthServer.Shutdown() + s.coordinator.Stop() + return nil +} diff --git a/go/coordinator/internal/grpccoordinator/tenant_database_service.go b/go/coordinator/internal/grpccoordinator/tenant_database_service.go new file mode 100644 index 0000000000000000000000000000000000000000..eb36b3de949a02baf889932b7862a996a4859e20 --- /dev/null +++ b/go/coordinator/internal/grpccoordinator/tenant_database_service.go @@ -0,0 +1,91 @@ +package grpccoordinator + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" +) + +func (s *Server) CreateDatabase(ctx context.Context, req *coordinatorpb.CreateDatabaseRequest) (*coordinatorpb.ChromaResponse, error) { + res := &coordinatorpb.ChromaResponse{} + createDatabase := &model.CreateDatabase{ + ID: req.GetId(), + Name: req.GetName(), + Tenant: req.GetTenant(), + } + _, err := s.coordinator.CreateDatabase(ctx, createDatabase) + if err != nil { + if err == common.ErrDatabaseUniqueConstraintViolation { + res.Status = failResponseWithError(err, 409) + return res, nil + } + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) GetDatabase(ctx context.Context, req *coordinatorpb.GetDatabaseRequest) (*coordinatorpb.GetDatabaseResponse, error) { + res := &coordinatorpb.GetDatabaseResponse{} + getDatabase := &model.GetDatabase{ + Name: req.GetName(), + Tenant: req.GetTenant(), + } + database, err := s.coordinator.GetDatabase(ctx, getDatabase) + if err != nil { + if err == common.ErrDatabaseNotFound || err == common.ErrTenantNotFound { + res.Status = failResponseWithError(err, 404) + return res, nil + } + res.Status = failResponseWithError(err, errorCode) + } + res.Database = &coordinatorpb.Database{ + Id: database.ID, + Name: database.Name, + Tenant: database.Tenant, + } + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) CreateTenant(ctx context.Context, req *coordinatorpb.CreateTenantRequest) (*coordinatorpb.ChromaResponse, error) { + res := &coordinatorpb.ChromaResponse{} + createTenant := &model.CreateTenant{ + Name: req.GetName(), + } + _, err := s.coordinator.CreateTenant(ctx, createTenant) + if err != nil { + if err == common.ErrTenantUniqueConstraintViolation { + res.Status = failResponseWithError(err, 409) + return res, nil + } + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Status = setResponseStatus(successCode) + return res, nil +} + +func (s *Server) GetTenant(ctx context.Context, req *coordinatorpb.GetTenantRequest) (*coordinatorpb.GetTenantResponse, error) { + res := &coordinatorpb.GetTenantResponse{} + getTenant := &model.GetTenant{ + Name: req.GetName(), + } + tenant, err := s.coordinator.GetTenant(ctx, getTenant) + if err != nil { + if err == common.ErrTenantNotFound { + res.Status = failResponseWithError(err, 404) + return res, nil + } + res.Status = failResponseWithError(err, errorCode) + return res, nil + } + res.Tenant = &coordinatorpb.Tenant{ + Name: tenant.Name, + } + res.Status = setResponseStatus(successCode) + return res, nil +} diff --git a/go/coordinator/internal/memberlist_manager/memberlist_manager.go b/go/coordinator/internal/memberlist_manager/memberlist_manager.go new file mode 100644 index 0000000000000000000000000000000000000000..3da53fbc3b999c9a37a01ad1aaf24774f21b1fc8 --- /dev/null +++ b/go/coordinator/internal/memberlist_manager/memberlist_manager.go @@ -0,0 +1,119 @@ +package memberlist_manager + +import ( + "context" + "errors" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/pingcap/log" + "go.uber.org/zap" + "k8s.io/client-go/util/workqueue" +) + +// A memberlist manager is responsible for managing the memberlist for a +// coordinator. A memberlist consists of a store and a watcher. The store +// is responsible for storing the memberlist in a persistent store, and the +// watcher is responsible for watching the nodes in the cluster and updating +// the store accordingly. Concretely, the memberlist manager reconciles between these +// and the store is backed by a Kubernetes custom resource, and the watcher is a +// kubernetes watch on pods with a given label. + +type IMemberlistManager interface { + common.Component +} + +type MemberlistManager struct { + workqueue workqueue.RateLimitingInterface // workqueue for the coordinator + nodeWatcher IWatcher // node watcher for the coordinator + memberlistStore IMemberlistStore // memberlist store for the coordinator +} + +func NewMemberlistManager(nodeWatcher IWatcher, memberlistStore IMemberlistStore) *MemberlistManager { + queue := workqueue.NewRateLimitingQueue(workqueue.DefaultControllerRateLimiter()) + + return &MemberlistManager{ + workqueue: queue, + nodeWatcher: nodeWatcher, + memberlistStore: memberlistStore, + } +} + +func (m *MemberlistManager) Start() error { + m.nodeWatcher.RegisterCallback(func(nodeIp string) { + m.workqueue.Add(nodeIp) + }) + err := m.nodeWatcher.Start() + if err != nil { + return err + } + go m.run() + return nil +} + +func (m *MemberlistManager) run() { + for { + interface_key, shutdown := m.workqueue.Get() + if shutdown { + log.Info("Shutting down memberlist manager") + break + } + + key, ok := interface_key.(string) + if !ok { + log.Error("Error while asserting workqueue key to string") + m.workqueue.Done(key) + continue + } + + nodeUpdate, err := m.nodeWatcher.GetStatus(key) + if err != nil { + log.Error("Error while getting status of node", zap.Error(err)) + m.workqueue.Done(key) + continue + } + + err = m.reconcile(key, nodeUpdate) + if err != nil { + log.Error("Error while reconciling memberlist", zap.Error(err)) + } + + m.workqueue.Done(key) + } +} + +func (m *MemberlistManager) reconcile(nodeIp string, status Status) error { + memberlist, resourceVersion, err := m.memberlistStore.GetMemberlist(context.Background()) + if err != nil { + return err + } + if memberlist == nil { + return errors.New("Memberlist recieved is nil") + } + exists := false + // Loop through the memberlist and generate a new one based on the update + // If we find the node in the existing list and the status is Ready, we add it to the new list + // If we find the node in the existing list and the status is NotReady, we don't add it to the new list + // If we don't find the node in the existing list and the status is Ready, we add it to the new list + newMemberlist := Memberlist{} + for _, node := range *memberlist { + if node == nodeIp { + if status == Ready { + newMemberlist = append(newMemberlist, node) + } + // Else here implies the node is not ready, so we don't add it to the new memberlist + exists = true + } else { + // This update doesn't pertains to this node, so we just add it to the new memberlist + newMemberlist = append(newMemberlist, node) + } + } + if !exists && status == Ready { + newMemberlist = append(newMemberlist, nodeIp) + } + return m.memberlistStore.UpdateMemberlist(context.TODO(), &newMemberlist, resourceVersion) +} + +func (m *MemberlistManager) Stop() error { + m.workqueue.ShutDown() + return nil +} diff --git a/go/coordinator/internal/memberlist_manager/memberlist_manager_test.go b/go/coordinator/internal/memberlist_manager/memberlist_manager_test.go new file mode 100644 index 0000000000000000000000000000000000000000..4a26fdd484b1dab315aa572b5764e3f08f140e07 --- /dev/null +++ b/go/coordinator/internal/memberlist_manager/memberlist_manager_test.go @@ -0,0 +1,209 @@ +package memberlist_manager + +import ( + "context" + "reflect" + "testing" + "time" + + "github.com/chroma/chroma-coordinator/internal/utils" + "github.com/stretchr/testify/assert" + v1 "k8s.io/api/core/v1" + metav1 "k8s.io/apimachinery/pkg/apis/meta/v1" + "k8s.io/apimachinery/pkg/runtime" + "k8s.io/client-go/dynamic/fake" + "k8s.io/client-go/kubernetes" +) + +func TestNodeWatcher(t *testing.T) { + clientset, err := utils.GetTestKubenertesInterface() + if err != nil { + panic(err) + } + + // Create a node watcher + node_watcher := NewKubernetesWatcher(clientset, "chroma", "worker", 60*time.Second) + node_watcher.Start() + + // create some fake pods to test the watcher + clientset.CoreV1().Pods("chroma").Create(context.TODO(), &v1.Pod{ + ObjectMeta: metav1.ObjectMeta{ + Name: "test-pod", + Namespace: "chroma", + Labels: map[string]string{ + "member-type": "worker", + }, + }, + Status: v1.PodStatus{ + PodIP: "10.0.0.1", + Conditions: []v1.PodCondition{ + { + Type: v1.PodReady, + Status: v1.ConditionTrue, + }, + }, + }, + }, metav1.CreateOptions{}) + + // Get the status of the node + retryUntilCondition(t, func() bool { + node_status, err := node_watcher.GetStatus("10.0.0.1") + if err != nil { + t.Fatalf("Error getting node status: %v", err) + } + return node_status == Ready + }, 10, 1*time.Second) + + // Add a not ready pod + clientset.CoreV1().Pods("chroma").Create(context.TODO(), &v1.Pod{ + ObjectMeta: metav1.ObjectMeta{ + Name: "test-pod-2", + Namespace: "chroma", + Labels: map[string]string{ + "member-type": "worker", + }, + }, + Status: v1.PodStatus{ + PodIP: "10.0.0.2", + Conditions: []v1.PodCondition{ + { + Type: v1.PodReady, + Status: v1.ConditionFalse, + }, + }, + }, + }, metav1.CreateOptions{}) + + retryUntilCondition(t, func() bool { + node_status, err := node_watcher.GetStatus("10.0.0.2") + if err != nil { + t.Fatalf("Error getting node status: %v", err) + } + return node_status == NotReady + }, 10, 1*time.Second) + +} + +func TestMemberlistStore(t *testing.T) { + memberlistName := "test-memberlist" + namespace := "chroma" + memberlist := &Memberlist{} + cr_memberlist := memberlistToCr(memberlist, namespace, memberlistName, "0") + + // Following the assumptions of the real system, we initialize the CR with no members. + dynamicClient := fake.NewSimpleDynamicClient(runtime.NewScheme(), cr_memberlist) + + memberlist_store := NewCRMemberlistStore(dynamicClient, namespace, memberlistName) + memberlist, _, err := memberlist_store.GetMemberlist(context.TODO()) + if err != nil { + t.Fatalf("Error getting memberlist: %v", err) + } + // assert the memberlist is empty + assert.Equal(t, Memberlist{}, *memberlist) + + // Add a member to the memberlist + memberlist_store.UpdateMemberlist(context.TODO(), &Memberlist{"10.0.0.1", "10.0.0.2"}, "0") + memberlist, _, err = memberlist_store.GetMemberlist(context.TODO()) + if err != nil { + t.Fatalf("Error getting memberlist: %v", err) + } + assert.Equal(t, Memberlist{"10.0.0.1", "10.0.0.2"}, *memberlist) +} + +func createFakePod(ip string, clientset kubernetes.Interface) { + clientset.CoreV1().Pods("chroma").Create(context.TODO(), &v1.Pod{ + ObjectMeta: metav1.ObjectMeta{ + Name: ip, + Namespace: "chroma", + Labels: map[string]string{ + "member-type": "worker", + }, + }, + Status: v1.PodStatus{ + PodIP: ip, + Conditions: []v1.PodCondition{ + { + Type: v1.PodReady, + Status: v1.ConditionTrue, + }, + }, + }, + }, metav1.CreateOptions{}) +} + +func deleteFakePod(ip string, clientset kubernetes.Interface) { + clientset.CoreV1().Pods("chroma").Delete(context.TODO(), ip, metav1.DeleteOptions{}) +} + +func TestMemberlistManager(t *testing.T) { + memberlist_name := "test-memberlist" + namespace := "chroma" + initialMemberlist := &Memberlist{} + initialCrMemberlist := memberlistToCr(initialMemberlist, namespace, memberlist_name, "0") + + // Create a fake kubernetes client + clientset, err := utils.GetTestKubenertesInterface() + if err != nil { + t.Fatalf("Error getting kubernetes client: %v", err) + } + + // Create a fake dynamic client + dynamicClient := fake.NewSimpleDynamicClient(runtime.NewScheme(), initialCrMemberlist) + + // Create a node watcher + nodeWatcher := NewKubernetesWatcher(clientset, namespace, "worker", 60*time.Second) + + // Create a memberlist store + memberlistStore := NewCRMemberlistStore(dynamicClient, namespace, memberlist_name) + + // Create a memberlist manager + memberlist_manager := NewMemberlistManager(nodeWatcher, memberlistStore) + + // Start the memberlist manager + err = memberlist_manager.Start() + if err != nil { + t.Fatalf("Error starting memberlist manager: %v", err) + } + + // Add a ready pod + createFakePod("10.0.0.49", clientset) + + // Get the memberlist + retryUntilCondition(t, func() bool { + return getMemberlistAndCompare(t, memberlistStore, Memberlist{"10.0.0.49"}) + }, 10, 1*time.Second) + + // Add another ready pod + createFakePod("10.0.0.50", clientset) + + // Get the memberlist + retryUntilCondition(t, func() bool { + return getMemberlistAndCompare(t, memberlistStore, Memberlist{"10.0.0.49", "10.0.0.50"}) + }, 10, 1*time.Second) + + // Delete a pod + deleteFakePod("10.0.0.49", clientset) + + // Get the memberlist + retryUntilCondition(t, func() bool { + return getMemberlistAndCompare(t, memberlistStore, Memberlist{"10.0.0.50"}) + }, 10, 1*time.Second) +} + +func retryUntilCondition(t *testing.T, f func() bool, retry_count int, retry_interval time.Duration) { + for i := 0; i < retry_count; i++ { + if f() { + return + } + time.Sleep(retry_interval) + } + t.Fatalf("Condition not met after %d retries", retry_count) +} + +func getMemberlistAndCompare(t *testing.T, memberlistStore IMemberlistStore, expected_memberlist Memberlist) bool { + memberlist, _, err := memberlistStore.GetMemberlist(context.TODO()) + if err != nil { + t.Fatalf("Error getting memberlist: %v", err) + } + return reflect.DeepEqual(expected_memberlist, *memberlist) +} diff --git a/go/coordinator/internal/memberlist_manager/memberlist_store.go b/go/coordinator/internal/memberlist_manager/memberlist_store.go new file mode 100644 index 0000000000000000000000000000000000000000..0567897f46e4bad0253673ec1cb23def6dc4c401 --- /dev/null +++ b/go/coordinator/internal/memberlist_manager/memberlist_store.go @@ -0,0 +1,93 @@ +package memberlist_manager + +import ( + "context" + + metav1 "k8s.io/apimachinery/pkg/apis/meta/v1" + "k8s.io/apimachinery/pkg/apis/meta/v1/unstructured" + "k8s.io/apimachinery/pkg/runtime/schema" + "k8s.io/client-go/dynamic" +) + +type IMemberlistStore interface { + GetMemberlist(ctx context.Context) (return_memberlist *Memberlist, resourceVersion string, err error) + UpdateMemberlist(ctx context.Context, memberlist *Memberlist, resourceVersion string) error +} + +type Memberlist []string + +type CRMemberlistStore struct { + dynamicClient dynamic.Interface + coordinatorNamespace string + memberlistCustomResource string +} + +func NewCRMemberlistStore(dynamicClient dynamic.Interface, coordinatorNamespace string, memberlistCustomResource string) *CRMemberlistStore { + return &CRMemberlistStore{ + dynamicClient: dynamicClient, + coordinatorNamespace: coordinatorNamespace, + memberlistCustomResource: memberlistCustomResource, + } +} + +func (s *CRMemberlistStore) GetMemberlist(ctx context.Context) (return_memberlist *Memberlist, resourceVersion string, err error) { + gvr := getGvr() + unstrucuted, err := s.dynamicClient.Resource(gvr).Namespace(s.coordinatorNamespace).Get(ctx, s.memberlistCustomResource, metav1.GetOptions{}) + if err != nil { + return nil, "", err + } + cr := unstrucuted.UnstructuredContent() + members := cr["spec"].(map[string]interface{})["members"] + memberlist := Memberlist{} + if members == nil { + // Empty memberlist + return &memberlist, unstrucuted.GetResourceVersion(), nil + } + cast_members := members.([]interface{}) + for _, member := range cast_members { + member_map := member.(map[string]interface{}) + memberlist = append(memberlist, member_map["url"].(string)) + } + return &memberlist, unstrucuted.GetResourceVersion(), nil +} + +func (s *CRMemberlistStore) UpdateMemberlist(ctx context.Context, memberlist *Memberlist, resourceVersion string) error { + gvr := getGvr() + unstructured := memberlistToCr(memberlist, s.coordinatorNamespace, s.memberlistCustomResource, resourceVersion) + _, err := s.dynamicClient.Resource(gvr).Namespace("chroma").Update(context.TODO(), unstructured, metav1.UpdateOptions{}) + if err != nil { + return err + } + return nil +} + +func getGvr() schema.GroupVersionResource { + gvr := schema.GroupVersionResource{Group: "chroma.cluster", Version: "v1", Resource: "memberlists"} + return gvr +} + +func memberlistToCr(memberlist *Memberlist, namespace string, memberlistName string, resourceVersion string) *unstructured.Unstructured { + members := []interface{}{} + for _, member := range *memberlist { + members = append(members, map[string]interface{}{ + "url": member, + }) + } + + resource := &unstructured.Unstructured{ + Object: map[string]interface{}{ + "apiVersion": "chroma.cluster/v1", + "kind": "MemberList", + "metadata": map[string]interface{}{ + "name": memberlistName, + "namespace": namespace, + "resourceVersion": resourceVersion, + }, + "spec": map[string]interface{}{ + "members": members, + }, + }, + } + + return resource +} diff --git a/go/coordinator/internal/memberlist_manager/node_watcher.go b/go/coordinator/internal/memberlist_manager/node_watcher.go new file mode 100644 index 0000000000000000000000000000000000000000..d534620eeb9ef38cb47f628214624a3f6618102d --- /dev/null +++ b/go/coordinator/internal/memberlist_manager/node_watcher.go @@ -0,0 +1,188 @@ +package memberlist_manager + +import ( + "errors" + "sync" + "time" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/pingcap/log" + "go.uber.org/zap" + v1 "k8s.io/api/core/v1" + metav1 "k8s.io/apimachinery/pkg/apis/meta/v1" + "k8s.io/apimachinery/pkg/labels" + "k8s.io/client-go/informers" + "k8s.io/client-go/kubernetes" + "k8s.io/client-go/tools/cache" +) + +type NodeWatcherCallback func(node_ip string) + +type IWatcher interface { + common.Component + RegisterCallback(callback NodeWatcherCallback) + GetStatus(node_ip string) (Status, error) +} + +type Status int + +// Enum for status +const ( + Ready Status = iota + NotReady + Unknown +) + +const MemberLabel = "member-type" + +type KubernetesWatcher struct { + mu sync.Mutex + stopCh chan struct{} + isRunning bool + clientSet kubernetes.Interface // clientset for the coordinator + informer cache.SharedIndexInformer // informer for the coordinator + callbacks []NodeWatcherCallback + ipToKey map[string]string + informerHandle cache.ResourceEventHandlerRegistration +} + +func NewKubernetesWatcher(clientset kubernetes.Interface, coordinator_namespace string, pod_label string, resyncPeriod time.Duration) *KubernetesWatcher { + labelSelector := labels.SelectorFromSet(map[string]string{MemberLabel: pod_label}) + factory := informers.NewSharedInformerFactoryWithOptions(clientset, resyncPeriod, informers.WithNamespace(coordinator_namespace), informers.WithTweakListOptions(func(options *metav1.ListOptions) { options.LabelSelector = labelSelector.String() })) + podInformer := factory.Core().V1().Pods().Informer() + ipToKey := make(map[string]string) + + w := &KubernetesWatcher{ + isRunning: false, + clientSet: clientset, + informer: podInformer, + ipToKey: ipToKey, + } + + return w +} + +func (w *KubernetesWatcher) Start() error { + if w.isRunning { + return errors.New("watcher is already running") + } + + registration, err := w.informer.AddEventHandler(cache.ResourceEventHandlerFuncs{ + AddFunc: func(obj interface{}) { + key, err := cache.MetaNamespaceKeyFunc(obj) + objPod, ok := obj.(*v1.Pod) + if !ok { + log.Error("Error while asserting object to pod") + } + if err == nil { + ip := objPod.Status.PodIP + w.mu.Lock() + w.ipToKey[ip] = key + w.mu.Unlock() + w.notify(ip) + } else { + log.Error("Error while getting key from object", zap.Error(err)) + } + }, + UpdateFunc: func(oldObj, newObj interface{}) { + key, err := cache.MetaNamespaceKeyFunc(newObj) + objPod, ok := newObj.(*v1.Pod) + if !ok { + log.Error("Error while asserting object to pod") + } + if err == nil { + ip := objPod.Status.PodIP + w.ipToKey[ip] = key + w.notify(ip) + } else { + log.Error("Error while getting key from object", zap.Error(err)) + } + }, + DeleteFunc: func(obj interface{}) { + _, err := cache.DeletionHandlingMetaNamespaceKeyFunc(obj) + objPod, ok := obj.(*v1.Pod) + if !ok { + log.Error("Error while asserting object to pod") + } + if err == nil { + ip := objPod.Status.PodIP + // The contract for GetStatus is that if the ip is not in this map, then it returns NotReady + delete(w.ipToKey, ip) + w.notify(ip) + } else { + log.Error("Error while getting key from object", zap.Error(err)) + } + }, + }) + if err != nil { + return err + } + + w.informerHandle = registration + + w.stopCh = make(chan struct{}) + w.isRunning = true + + go w.informer.Run(w.stopCh) + + if !cache.WaitForCacheSync(w.stopCh, w.informer.HasSynced) { + log.Error("Failed to sync cache") + } + + return nil +} + +// Stop the kubernetes watcher +func (w *KubernetesWatcher) Stop() error { + // Stop generating updates + if !w.isRunning { + return errors.New("watcher is not running") + } + + err := w.informer.RemoveEventHandler(w.informerHandle) + + close(w.stopCh) + w.isRunning = false + return err +} + +// Register a queue +func (w *KubernetesWatcher) RegisterCallback(callback NodeWatcherCallback) { + w.callbacks = append(w.callbacks, callback) +} + +func (w *KubernetesWatcher) notify(update string) { + for _, callback := range w.callbacks { + callback(update) + } +} + +func (w *KubernetesWatcher) GetStatus(node_ip string) (Status, error) { + w.mu.Lock() + key, ok := w.ipToKey[node_ip] + w.mu.Unlock() + if !ok { + return NotReady, nil + } + + obj, exists, err := w.informer.GetIndexer().GetByKey(key) + if err != nil { + return Unknown, err + } + if !exists { + return Unknown, errors.New("node does not exist") + } + + pod, ok := obj.(*v1.Pod) + if !ok { + return Unknown, errors.New("object is not a pod") + } + conditions := pod.Status.Conditions + for _, condition := range conditions { + if condition.Type == v1.PodReady && condition.Status == v1.ConditionTrue { + return Ready, nil + } + } + return NotReady, nil + +} diff --git a/go/coordinator/internal/metastore/catalog.go b/go/coordinator/internal/metastore/catalog.go new file mode 100644 index 0000000000000000000000000000000000000000..8a54ebbf910226047467cf34c690175516acc81f --- /dev/null +++ b/go/coordinator/internal/metastore/catalog.go @@ -0,0 +1,29 @@ +package metastore + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" +) + +// Catalog defines methods for system catalog +// +//go:generate mockery --name=Catalog +type Catalog interface { + ResetState(ctx context.Context) error + CreateCollection(ctx context.Context, createCollection *model.CreateCollection, ts types.Timestamp) (*model.Collection, error) + GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*model.Collection, error) + DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error + UpdateCollection(ctx context.Context, updateCollection *model.UpdateCollection, ts types.Timestamp) (*model.Collection, error) + CreateSegment(ctx context.Context, createSegment *model.CreateSegment, ts types.Timestamp) (*model.Segment, error) + GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID, ts types.Timestamp) ([]*model.Segment, error) + DeleteSegment(ctx context.Context, segmentID types.UniqueID) error + UpdateSegment(ctx context.Context, segmentInfo *model.UpdateSegment, ts types.Timestamp) (*model.Segment, error) + CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase, ts types.Timestamp) (*model.Database, error) + GetDatabases(ctx context.Context, getDatabase *model.GetDatabase, ts types.Timestamp) (*model.Database, error) + GetAllDatabases(ctx context.Context, ts types.Timestamp) ([]*model.Database, error) + CreateTenant(ctx context.Context, createTenant *model.CreateTenant, ts types.Timestamp) (*model.Tenant, error) + GetTenants(ctx context.Context, getTenant *model.GetTenant, ts types.Timestamp) (*model.Tenant, error) + GetAllTenants(ctx context.Context, ts types.Timestamp) ([]*model.Tenant, error) +} diff --git a/go/coordinator/internal/metastore/coordinator/memory_catalog.go b/go/coordinator/internal/metastore/coordinator/memory_catalog.go new file mode 100644 index 0000000000000000000000000000000000000000..439911cb754294ab9b178dd22f18fbf67367a7af --- /dev/null +++ b/go/coordinator/internal/metastore/coordinator/memory_catalog.go @@ -0,0 +1,370 @@ +package coordinator + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/notification" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +// MemoryCatalog is a reference implementation of Catalog interface to ensure the +// application logic is correctly implemented. +type MemoryCatalog struct { + segments map[types.UniqueID]*model.Segment + tenantDatabaseCollections map[string]map[string]map[types.UniqueID]*model.Collection + tenantDatabases map[string]map[string]*model.Database + store notification.NotificationStore +} + +var _ metastore.Catalog = (*MemoryCatalog)(nil) + +func NewMemoryCatalog() *MemoryCatalog { + memoryCatalog := MemoryCatalog{ + segments: make(map[types.UniqueID]*model.Segment), + tenantDatabaseCollections: make(map[string]map[string]map[types.UniqueID]*model.Collection), + tenantDatabases: make(map[string]map[string]*model.Database), + } + // Add a default tenant and database + memoryCatalog.tenantDatabases[common.DefaultTenant] = make(map[string]*model.Database) + memoryCatalog.tenantDatabases[common.DefaultTenant][common.DefaultDatabase] = &model.Database{ + ID: types.NilUniqueID().String(), + Name: common.DefaultDatabase, + Tenant: common.DefaultTenant, + } + memoryCatalog.tenantDatabaseCollections[common.DefaultTenant] = make(map[string]map[types.UniqueID]*model.Collection) + memoryCatalog.tenantDatabaseCollections[common.DefaultTenant][common.DefaultDatabase] = make(map[types.UniqueID]*model.Collection) + return &memoryCatalog +} + +func NewMemoryCatalogWithNotification(store notification.NotificationStore) *MemoryCatalog { + memoryCatalog := NewMemoryCatalog() + memoryCatalog.store = store + return memoryCatalog +} + +func (mc *MemoryCatalog) ResetState(ctx context.Context) error { + mc.segments = make(map[types.UniqueID]*model.Segment) + mc.tenantDatabases = make(map[string]map[string]*model.Database) + mc.tenantDatabases[common.DefaultTenant] = make(map[string]*model.Database) + mc.tenantDatabases[common.DefaultTenant][common.DefaultDatabase] = &model.Database{ + ID: types.NilUniqueID().String(), + Name: common.DefaultDatabase, + Tenant: common.DefaultTenant, + } + mc.tenantDatabaseCollections[common.DefaultTenant] = make(map[string]map[types.UniqueID]*model.Collection) + mc.tenantDatabaseCollections[common.DefaultTenant][common.DefaultDatabase] = make(map[types.UniqueID]*model.Collection) + return nil +} + +func (mc *MemoryCatalog) CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase, ts types.Timestamp) (*model.Database, error) { + tenant := createDatabase.Tenant + databaseName := createDatabase.Name + if _, ok := mc.tenantDatabases[tenant]; !ok { + log.Error("tenant not found", zap.String("tenant", tenant)) + return nil, common.ErrTenantNotFound + } + if _, ok := mc.tenantDatabases[tenant][databaseName]; ok { + log.Error("database already exists", zap.String("database", databaseName)) + return nil, common.ErrDatabaseUniqueConstraintViolation + } + mc.tenantDatabases[tenant][databaseName] = &model.Database{ + ID: createDatabase.ID, + Name: createDatabase.Name, + Tenant: createDatabase.Tenant, + } + mc.tenantDatabaseCollections[tenant][databaseName] = make(map[types.UniqueID]*model.Collection) + log.Info("database created", zap.Any("database", mc.tenantDatabases[tenant][databaseName])) + return mc.tenantDatabases[tenant][databaseName], nil +} + +func (mc *MemoryCatalog) GetDatabases(ctx context.Context, getDatabase *model.GetDatabase, ts types.Timestamp) (*model.Database, error) { + tenant := getDatabase.Tenant + databaseName := getDatabase.Name + if _, ok := mc.tenantDatabases[tenant]; !ok { + log.Error("tenant not found", zap.String("tenant", tenant)) + return nil, common.ErrTenantNotFound + } + if _, ok := mc.tenantDatabases[tenant][databaseName]; !ok { + log.Error("database not found", zap.String("database", databaseName)) + return nil, common.ErrDatabaseNotFound + } + log.Info("database found", zap.Any("database", mc.tenantDatabases[tenant][databaseName])) + return mc.tenantDatabases[tenant][databaseName], nil +} + +func (mc *MemoryCatalog) GetAllDatabases(ctx context.Context, ts types.Timestamp) ([]*model.Database, error) { + databases := make([]*model.Database, 0) + for _, database := range mc.tenantDatabases { + for _, db := range database { + databases = append(databases, db) + } + } + return databases, nil +} + +func (mc *MemoryCatalog) CreateTenant(ctx context.Context, createTenant *model.CreateTenant, ts types.Timestamp) (*model.Tenant, error) { + tenant := createTenant.Name + if _, ok := mc.tenantDatabases[tenant]; ok { + log.Error("tenant already exists", zap.String("tenant", tenant)) + return nil, common.ErrTenantUniqueConstraintViolation + } + mc.tenantDatabases[tenant] = make(map[string]*model.Database) + mc.tenantDatabaseCollections[tenant] = make(map[string]map[types.UniqueID]*model.Collection) + return &model.Tenant{Name: tenant}, nil +} + +func (mc *MemoryCatalog) GetTenants(ctx context.Context, getTenant *model.GetTenant, ts types.Timestamp) (*model.Tenant, error) { + tenant := getTenant.Name + if _, ok := mc.tenantDatabases[tenant]; !ok { + log.Error("tenant not found", zap.String("tenant", tenant)) + return nil, common.ErrTenantNotFound + } + return &model.Tenant{Name: tenant}, nil +} + +func (mc *MemoryCatalog) GetAllTenants(ctx context.Context, ts types.Timestamp) ([]*model.Tenant, error) { + tenants := make([]*model.Tenant, 0, len(mc.tenantDatabases)) + for tenant := range mc.tenantDatabases { + tenants = append(tenants, &model.Tenant{Name: tenant}) + } + return tenants, nil +} + +func (mc *MemoryCatalog) CreateCollection(ctx context.Context, createCollection *model.CreateCollection, ts types.Timestamp) (*model.Collection, error) { + collectionName := createCollection.Name + tenantID := createCollection.TenantID + databaseName := createCollection.DatabaseName + + if _, ok := mc.tenantDatabaseCollections[tenantID]; !ok { + log.Error("tenant not found", zap.String("tenant", tenantID)) + return nil, common.ErrTenantNotFound + } + if _, ok := mc.tenantDatabaseCollections[tenantID][databaseName]; !ok { + log.Error("database not found", zap.String("database", databaseName)) + return nil, common.ErrDatabaseNotFound + } + // Check if the collection already by global id + for tenant := range mc.tenantDatabaseCollections { + for database := range mc.tenantDatabaseCollections[tenant] { + collections := mc.tenantDatabaseCollections[tenant][database] + if _, ok := collections[createCollection.ID]; ok { + if tenant != tenantID || database != databaseName { + log.Info("collection already exists", zap.Any("collection", collections[createCollection.ID])) + return nil, common.ErrCollectionUniqueConstraintViolation + } else if !createCollection.GetOrCreate { + return nil, common.ErrCollectionUniqueConstraintViolation + } + } + + } + } + // Check if the collection already exists in database by colllection name + collections := mc.tenantDatabaseCollections[tenantID][databaseName] + for _, collection := range collections { + if collection.Name == collectionName { + log.Info("collection already exists", zap.Any("collection", collections[createCollection.ID])) + if createCollection.GetOrCreate { + if createCollection.Metadata != nil { + // For getOrCreate, update the metadata + collection.Metadata = createCollection.Metadata + } + return collection, nil + } else { + return nil, common.ErrCollectionUniqueConstraintViolation + } + } + } + collection := &model.Collection{ + ID: createCollection.ID, + Name: createCollection.Name, + Topic: createCollection.Topic, + Dimension: createCollection.Dimension, + Metadata: createCollection.Metadata, + Created: true, + TenantID: createCollection.TenantID, + DatabaseName: createCollection.DatabaseName, + } + log.Info("collection created", zap.Any("collection", collection)) + collections[collection.ID] = collection + return collection, nil +} + +func (mc *MemoryCatalog) GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*model.Collection, error) { + if _, ok := mc.tenantDatabaseCollections[tenantID]; !ok { + log.Error("tenant not found", zap.String("tenant", tenantID)) + return nil, common.ErrTenantNotFound + } + if _, ok := mc.tenantDatabaseCollections[tenantID][databaseName]; !ok { + log.Error("database not found", zap.String("database", databaseName)) + return nil, common.ErrDatabaseNotFound + } + collections := make([]*model.Collection, 0, len(mc.tenantDatabaseCollections[tenantID][databaseName])) + for _, collection := range mc.tenantDatabaseCollections[tenantID][databaseName] { + if model.FilterCollection(collection, collectionID, collectionName, collectionTopic) { + collections = append(collections, collection) + } + } + return collections, nil +} + +func (mc *MemoryCatalog) DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error { + tenantID := deleteCollection.TenantID + databaseName := deleteCollection.DatabaseName + collectionID := deleteCollection.ID + if _, ok := mc.tenantDatabaseCollections[tenantID]; !ok { + log.Error("tenant not found", zap.String("tenant", tenantID)) + return common.ErrTenantNotFound + } + if _, ok := mc.tenantDatabaseCollections[tenantID][databaseName]; !ok { + log.Error("database not found", zap.String("database", databaseName)) + return common.ErrDatabaseNotFound + } + collections := mc.tenantDatabaseCollections[tenantID][databaseName] + if _, ok := collections[collectionID]; !ok { + log.Error("collection not found", zap.String("collection", collectionID.String())) + return common.ErrCollectionDeleteNonExistingCollection + } + delete(collections, collectionID) + log.Info("collection deleted", zap.String("collection", collectionID.String())) + mc.store.AddNotification(ctx, model.Notification{ + CollectionID: collectionID.String(), + Type: model.NotificationTypeDeleteCollection, + Status: model.NotificationStatusPending, + }) + return nil +} + +func (mc *MemoryCatalog) UpdateCollection(ctx context.Context, updateCollection *model.UpdateCollection, ts types.Timestamp) (*model.Collection, error) { + collectionID := updateCollection.ID + var oldCollection *model.Collection + for tenant := range mc.tenantDatabaseCollections { + for database := range mc.tenantDatabaseCollections[tenant] { + log.Info("database", zap.Any("database", database)) + collections := mc.tenantDatabaseCollections[tenant][database] + if _, ok := collections[collectionID]; ok { + oldCollection = collections[collectionID] + } + } + } + + topic := updateCollection.Topic + if topic != nil { + oldCollection.Topic = *topic + } + name := updateCollection.Name + if name != nil { + oldCollection.Name = *name + } + if updateCollection.Dimension != nil { + oldCollection.Dimension = updateCollection.Dimension + } + + // Case 1: if resetMetadata is true, then delete all metadata for the collection + // Case 2: if resetMetadata is true and metadata is not nil -> THIS SHOULD NEVER HAPPEN + // Case 3: if resetMetadata is false, and the metadata is not nil - set the metadata to the value in metadata + // Case 4: if resetMetadata is false and metadata is nil, then leave the metadata as is + resetMetadata := updateCollection.ResetMetadata + if resetMetadata { + oldCollection.Metadata = nil + } else { + if updateCollection.Metadata != nil { + oldCollection.Metadata = updateCollection.Metadata + } + } + tenantID := oldCollection.TenantID + databaseName := oldCollection.DatabaseName + mc.tenantDatabaseCollections[tenantID][databaseName][oldCollection.ID] = oldCollection + // Better to return a copy of the collection to avoid being modified by others. + log.Debug("collection metadata", zap.Any("metadata", oldCollection.Metadata)) + return oldCollection, nil +} + +func (mc *MemoryCatalog) CreateSegment(ctx context.Context, createSegment *model.CreateSegment, ts types.Timestamp) (*model.Segment, error) { + if _, ok := mc.segments[createSegment.ID]; ok { + return nil, common.ErrSegmentUniqueConstraintViolation + } + + segment := &model.Segment{ + ID: createSegment.ID, + Topic: createSegment.Topic, + Type: createSegment.Type, + Scope: createSegment.Scope, + CollectionID: createSegment.CollectionID, + Metadata: createSegment.Metadata, + } + mc.segments[createSegment.ID] = segment + log.Debug("segment created", zap.Any("segment", segment)) + return segment, nil +} + +func (mc *MemoryCatalog) GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID, ts types.Timestamp) ([]*model.Segment, error) { + segments := make([]*model.Segment, 0, len(mc.segments)) + for _, segment := range mc.segments { + if model.FilterSegments(segment, segmentID, segmentType, scope, topic, collectionID) { + segments = append(segments, segment) + } + } + return segments, nil +} + +func (mc *MemoryCatalog) DeleteSegment(ctx context.Context, segmentID types.UniqueID) error { + if _, ok := mc.segments[segmentID]; !ok { + return common.ErrSegmentDeleteNonExistingSegment + } + + delete(mc.segments, segmentID) + return nil +} + +func (mc *MemoryCatalog) UpdateSegment(ctx context.Context, updateSegment *model.UpdateSegment, ts types.Timestamp) (*model.Segment, error) { + // Case 1: if ResetTopic is true and topic is nil, then set the topic to nil + // Case 2: if ResetTopic is true and topic is not nil -> THIS SHOULD NEVER HAPPEN + // Case 3: if ResetTopic is false and topic is not nil - set the topic to the value in topic + // Case 4: if ResetTopic is false and topic is nil, then leave the topic as is + oldSegment := mc.segments[updateSegment.ID] + topic := updateSegment.Topic + if updateSegment.ResetTopic { + if topic == nil { + oldSegment.Topic = nil + } + } else { + if topic != nil { + oldSegment.Topic = topic + } + } + collection := updateSegment.Collection + if updateSegment.ResetCollection { + if collection == nil { + oldSegment.CollectionID = types.NilUniqueID() + } + } else { + if collection != nil { + parsedCollectionID, err := types.ToUniqueID(collection) + if err != nil { + return nil, err + } + oldSegment.CollectionID = parsedCollectionID + } + } + resetMetadata := updateSegment.ResetMetadata + if resetMetadata { + oldSegment.Metadata = nil + } else { + if updateSegment.Metadata != nil { + for key, value := range updateSegment.Metadata.Metadata { + if value == nil { + oldSegment.Metadata.Remove(key) + } else { + oldSegment.Metadata.Set(key, value) + } + } + } + } + mc.segments[updateSegment.ID] = oldSegment + return oldSegment, nil +} diff --git a/go/coordinator/internal/metastore/coordinator/memory_catalog_test.go b/go/coordinator/internal/metastore/coordinator/memory_catalog_test.go new file mode 100644 index 0000000000000000000000000000000000000000..c7f4b2d60404c5d648f676eeba55497e009b0457 --- /dev/null +++ b/go/coordinator/internal/metastore/coordinator/memory_catalog_test.go @@ -0,0 +1,138 @@ +package coordinator + +import ( + "context" + "testing" + + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/notification" + "github.com/chroma/chroma-coordinator/internal/types" +) + +const ( + defaultTenant = "default_tenant" + defaultDatabase = "default_database" +) + +func TestMemoryCatalog(t *testing.T) { + ctx := context.Background() + store := notification.NewMemoryNotificationStore() + mc := NewMemoryCatalogWithNotification(store) + + // Test CreateCollection + coll := &model.CreateCollection{ + ID: types.NewUniqueID(), + Name: "test-collection-name", + // Topic: "test-collection-topic", + Metadata: &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: map[string]model.CollectionMetadataValueType{ + "test-metadata-key": &model.CollectionMetadataValueStringType{Value: "test-metadata-value"}, + }, + }, + TenantID: defaultTenant, + DatabaseName: defaultDatabase, + } + collection, err := mc.CreateCollection(ctx, coll, types.Timestamp(0)) + if err != nil { + t.Fatalf("unexpected error creating collection: %v", err) + } + // Test GetCollections + collections, err := mc.GetCollections(ctx, coll.ID, &coll.Name, nil, defaultTenant, defaultDatabase) + if err != nil { + t.Fatalf("unexpected error getting collections: %v", err) + } + if len(collections) != 1 { + t.Fatalf("expected 1 collection, got %d", len(collections)) + } + if collections[0] != collection { + t.Fatalf("expected collection %+v, got %+v", coll, collections[0]) + } + + // Test DeleteCollection + deleteCollection := &model.DeleteCollection{ + ID: coll.ID, + DatabaseName: defaultDatabase, + TenantID: defaultTenant, + } + if err := mc.DeleteCollection(ctx, deleteCollection); err != nil { + t.Fatalf("unexpected error deleting collection: %v", err) + } + + // Test CreateSegment + testTopic := "test-segment-topic" + createSegment := &model.CreateSegment{ + ID: types.NewUniqueID(), + Type: "test-segment-type", + Scope: "test-segment-scope", + Topic: &testTopic, + CollectionID: coll.ID, + Metadata: &model.SegmentMetadata[model.SegmentMetadataValueType]{ + Metadata: map[string]model.SegmentMetadataValueType{ + "test-metadata-key": &model.SegmentMetadataValueStringType{Value: "test-metadata-value"}, + }, + }, + } + segment, err := mc.CreateSegment(ctx, createSegment, types.Timestamp(0)) + if err != nil { + t.Fatalf("unexpected error creating segment: %v", err) + } + if len(mc.segments) != 1 { + t.Fatalf("expected 1 segment, got %d", len(mc.segments)) + } + + if mc.segments[createSegment.ID] != segment { + t.Fatalf("expected segment with ID %q, got %+v", createSegment.ID, mc.segments[createSegment.ID]) + } + + // Test GetSegments + segments, err := mc.GetSegments(ctx, createSegment.ID, &createSegment.Type, &createSegment.Scope, createSegment.Topic, coll.ID, types.Timestamp(0)) + if err != nil { + t.Fatalf("unexpected error getting segments: %v", err) + } + if len(segments) != 1 { + t.Fatalf("expected 1 segment, got %d", len(segments)) + } + if segments[0] != segment { + t.Fatalf("expected segment %+v, got %+v", createSegment, segments[0]) + } + + // Test CreateCollection + coll = &model.CreateCollection{ + ID: types.NewUniqueID(), + Name: "test-collection-name", + // Topic: "test-collection-topic", + Metadata: &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: map[string]model.CollectionMetadataValueType{ + "test-metadata-key": &model.CollectionMetadataValueStringType{Value: "test-metadata-value"}, + }, + }, + TenantID: defaultTenant, + DatabaseName: defaultDatabase, + } + collection, err = mc.CreateCollection(ctx, coll, types.Timestamp(0)) + if err != nil { + t.Fatalf("unexpected error creating collection: %v", err) + } + + // Test GetCollections + collections, err = mc.GetCollections(ctx, coll.ID, &coll.Name, nil, defaultTenant, defaultDatabase) + if err != nil { + t.Fatalf("unexpected error getting collections: %v", err) + } + if len(collections) != 1 { + t.Fatalf("expected 1 collection, got %d", len(collections)) + } + if collections[0] != collection { + t.Fatalf("expected collection %+v, got %+v", coll, collections[0]) + } + + // Test DeleteCollection + deleteCollection = &model.DeleteCollection{ + ID: coll.ID, + DatabaseName: defaultDatabase, + TenantID: defaultTenant, + } + if err := mc.DeleteCollection(ctx, deleteCollection); err != nil { + t.Fatalf("unexpected error deleting collection: %v", err) + } +} diff --git a/go/coordinator/internal/metastore/coordinator/model_db_convert.go b/go/coordinator/internal/metastore/coordinator/model_db_convert.go new file mode 100644 index 0000000000000000000000000000000000000000..f5fb51bcaeaf068db4dced6635ffed526e3bfec7 --- /dev/null +++ b/go/coordinator/internal/metastore/coordinator/model_db_convert.go @@ -0,0 +1,181 @@ +package coordinator + +import ( + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +func convertCollectionToModel(collectionAndMetadataList []*dbmodel.CollectionAndMetadata) []*model.Collection { + if collectionAndMetadataList == nil { + return nil + } + collections := make([]*model.Collection, 0, len(collectionAndMetadataList)) + for _, collectionAndMetadata := range collectionAndMetadataList { + collection := &model.Collection{ + ID: types.MustParse(collectionAndMetadata.Collection.ID), + Name: *collectionAndMetadata.Collection.Name, + Topic: *collectionAndMetadata.Collection.Topic, + Dimension: collectionAndMetadata.Collection.Dimension, + TenantID: collectionAndMetadata.TenantID, + DatabaseName: collectionAndMetadata.DatabaseName, + Ts: collectionAndMetadata.Collection.Ts, + } + collection.Metadata = convertCollectionMetadataToModel(collectionAndMetadata.CollectionMetadata) + collections = append(collections, collection) + } + log.Debug("collection to model", zap.Any("collections", collections)) + return collections +} + +func convertCollectionMetadataToModel(collectionMetadataList []*dbmodel.CollectionMetadata) *model.CollectionMetadata[model.CollectionMetadataValueType] { + metadata := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + if collectionMetadataList == nil { + log.Debug("collection metadata to model", zap.Any("collectionMetadata", nil)) + return nil + } else { + for _, collectionMetadata := range collectionMetadataList { + if collectionMetadata.Key != nil { + switch { + case collectionMetadata.StrValue != nil: + metadata.Add(*collectionMetadata.Key, &model.CollectionMetadataValueStringType{Value: *collectionMetadata.StrValue}) + case collectionMetadata.IntValue != nil: + metadata.Add(*collectionMetadata.Key, &model.CollectionMetadataValueInt64Type{Value: *collectionMetadata.IntValue}) + case collectionMetadata.FloatValue != nil: + metadata.Add(*collectionMetadata.Key, &model.CollectionMetadataValueFloat64Type{Value: *collectionMetadata.FloatValue}) + default: + } + } + } + if metadata.Empty() { + metadata = nil + } + log.Debug("collection metadata to model", zap.Any("collectionMetadata", metadata)) + return metadata + } + +} + +func convertCollectionMetadataToDB(collectionID string, metadata *model.CollectionMetadata[model.CollectionMetadataValueType]) []*dbmodel.CollectionMetadata { + if metadata == nil { + log.Debug("collection metadata to db", zap.Any("collectionMetadata", nil)) + return nil + } + dbCollectionMetadataList := make([]*dbmodel.CollectionMetadata, 0, len(metadata.Metadata)) + for key, value := range metadata.Metadata { + keyCopy := key + dbCollectionMetadata := &dbmodel.CollectionMetadata{ + CollectionID: collectionID, + Key: &keyCopy, + } + switch v := (value).(type) { + case *model.CollectionMetadataValueStringType: + dbCollectionMetadata.StrValue = &v.Value + case *model.CollectionMetadataValueInt64Type: + dbCollectionMetadata.IntValue = &v.Value + case *model.CollectionMetadataValueFloat64Type: + dbCollectionMetadata.FloatValue = &v.Value + default: + log.Error("unknown collection metadata type", zap.Any("value", v)) + } + dbCollectionMetadataList = append(dbCollectionMetadataList, dbCollectionMetadata) + } + log.Debug("collection metadata to db", zap.Any("collectionMetadata", dbCollectionMetadataList)) + return dbCollectionMetadataList +} + +func convertSegmentToModel(segmentAndMetadataList []*dbmodel.SegmentAndMetadata) []*model.Segment { + if segmentAndMetadataList == nil { + return nil + } + segments := make([]*model.Segment, 0, len(segmentAndMetadataList)) + for _, segmentAndMetadata := range segmentAndMetadataList { + segment := &model.Segment{ + ID: types.MustParse(segmentAndMetadata.Segment.ID), + Type: segmentAndMetadata.Segment.Type, + Scope: segmentAndMetadata.Segment.Scope, + Topic: segmentAndMetadata.Segment.Topic, + Ts: segmentAndMetadata.Segment.Ts, + } + if segmentAndMetadata.Segment.CollectionID != nil { + segment.CollectionID = types.MustParse(*segmentAndMetadata.Segment.CollectionID) + } else { + segment.CollectionID = types.NilUniqueID() + } + + segment.Metadata = convertSegmentMetadataToModel(segmentAndMetadata.SegmentMetadata) + segments = append(segments, segment) + } + log.Debug("segment to model", zap.Any("segments", segments)) + return segments +} + +func convertSegmentMetadataToModel(segmentMetadataList []*dbmodel.SegmentMetadata) *model.SegmentMetadata[model.SegmentMetadataValueType] { + if segmentMetadataList == nil { + return nil + } else { + metadata := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + for _, segmentMetadata := range segmentMetadataList { + if segmentMetadata.Key != nil { + switch { + case segmentMetadata.StrValue != nil: + metadata.Set(*segmentMetadata.Key, &model.SegmentMetadataValueStringType{Value: *segmentMetadata.StrValue}) + case segmentMetadata.IntValue != nil: + metadata.Set(*segmentMetadata.Key, &model.SegmentMetadataValueInt64Type{Value: *segmentMetadata.IntValue}) + case segmentMetadata.FloatValue != nil: + metadata.Set(*segmentMetadata.Key, &model.SegmentMetadataValueFloat64Type{Value: *segmentMetadata.FloatValue}) + default: + } + } + } + if metadata.Empty() { + metadata = nil + } + log.Debug("segment metadata to model", zap.Any("segmentMetadata", nil)) + return metadata + } +} + +func convertSegmentMetadataToDB(segmentID string, metadata *model.SegmentMetadata[model.SegmentMetadataValueType]) []*dbmodel.SegmentMetadata { + if metadata == nil { + log.Debug("segment metadata db", zap.Any("segmentMetadata", nil)) + return nil + } + dbSegmentMetadataList := make([]*dbmodel.SegmentMetadata, 0, len(metadata.Metadata)) + for key, value := range metadata.Metadata { + keyCopy := key + dbSegmentMetadata := &dbmodel.SegmentMetadata{ + SegmentID: segmentID, + Key: &keyCopy, + } + switch v := (value).(type) { + case *model.SegmentMetadataValueStringType: + dbSegmentMetadata.StrValue = &v.Value + case *model.SegmentMetadataValueInt64Type: + dbSegmentMetadata.IntValue = &v.Value + case *model.SegmentMetadataValueFloat64Type: + dbSegmentMetadata.FloatValue = &v.Value + default: + log.Error("unknown segment metadata type", zap.Any("value", v)) + } + dbSegmentMetadataList = append(dbSegmentMetadataList, dbSegmentMetadata) + } + log.Debug("segment metadata db", zap.Any("segmentMetadata", dbSegmentMetadataList)) + return dbSegmentMetadataList +} + +func convertDatabaseToModel(dbDatabase *dbmodel.Database) *model.Database { + return &model.Database{ + ID: dbDatabase.ID, + Name: dbDatabase.Name, + Tenant: dbDatabase.TenantID, + } +} + +func convertTenantToModel(dbTenant *dbmodel.Tenant) *model.Tenant { + return &model.Tenant{ + Name: dbTenant.ID, + } +} diff --git a/go/coordinator/internal/metastore/coordinator/model_db_convert_test.go b/go/coordinator/internal/metastore/coordinator/model_db_convert_test.go new file mode 100644 index 0000000000000000000000000000000000000000..67da68b1a76a3d00359cc7a8a94324eed2336e6d --- /dev/null +++ b/go/coordinator/internal/metastore/coordinator/model_db_convert_test.go @@ -0,0 +1,158 @@ +package coordinator + +import ( + "sort" + "testing" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/stretchr/testify/assert" +) + +func TestConvertCollectionMetadataToModel(t *testing.T) { + // Test case 1: collectionMetadataList is nil + modelCollectionMetadata := convertCollectionMetadataToModel(nil) + assert.Nil(t, modelCollectionMetadata) + + // Test case 2: collectionMetadataList is empty + collectionMetadataList := []*dbmodel.CollectionMetadata{} + modelCollectionMetadata = convertCollectionMetadataToModel(collectionMetadataList) + assert.Nil(t, modelCollectionMetadata) +} + +func TestConvertCollectionMetadataToDB(t *testing.T) { + // Test case 1: metadata is nil + dbCollectionMetadataList := convertCollectionMetadataToDB("collectionID", nil) + assert.Nil(t, dbCollectionMetadataList) + + // Test case 2: metadata is not nil but empty + metadata := &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: map[string]model.CollectionMetadataValueType{}, + } + dbCollectionMetadataList = convertCollectionMetadataToDB("collectionID", metadata) + assert.NotNil(t, dbCollectionMetadataList) + assert.Len(t, dbCollectionMetadataList, 0) + + // Test case 3: metadata is not nil and contains values + metadata = &model.CollectionMetadata[model.CollectionMetadataValueType]{ + Metadata: map[string]model.CollectionMetadataValueType{ + "key1": &model.CollectionMetadataValueStringType{Value: "value1"}, + "key2": &model.CollectionMetadataValueInt64Type{Value: 123}, + "key3": &model.CollectionMetadataValueFloat64Type{Value: 3.14}, + }, + } + dbCollectionMetadataList = convertCollectionMetadataToDB("collectionID", metadata) + sort.Slice(dbCollectionMetadataList, func(i, j int) bool { + return *dbCollectionMetadataList[i].Key < *dbCollectionMetadataList[j].Key + }) + assert.NotNil(t, dbCollectionMetadataList) + assert.Len(t, dbCollectionMetadataList, 3) + assert.Equal(t, "collectionID", dbCollectionMetadataList[0].CollectionID) + assert.Equal(t, "key1", *dbCollectionMetadataList[0].Key) + assert.Equal(t, "value1", *dbCollectionMetadataList[0].StrValue) + assert.Nil(t, dbCollectionMetadataList[0].IntValue) + assert.Nil(t, dbCollectionMetadataList[0].FloatValue) + assert.Equal(t, "collectionID", dbCollectionMetadataList[1].CollectionID) + assert.Equal(t, "key2", *dbCollectionMetadataList[1].Key) + assert.Nil(t, dbCollectionMetadataList[1].StrValue) + assert.Equal(t, int64(123), *dbCollectionMetadataList[1].IntValue) + assert.Nil(t, dbCollectionMetadataList[1].FloatValue) + assert.Equal(t, "collectionID", dbCollectionMetadataList[2].CollectionID) + assert.Equal(t, "key3", *dbCollectionMetadataList[2].Key) + assert.Nil(t, dbCollectionMetadataList[2].StrValue) + assert.Nil(t, dbCollectionMetadataList[2].IntValue) + assert.Equal(t, 3.14, *dbCollectionMetadataList[2].FloatValue) +} +func TestConvertSegmentToModel(t *testing.T) { + // Test case 1: segmentAndMetadataList is nil + modelSegments := convertSegmentToModel(nil) + assert.Nil(t, modelSegments) + + // Test case 2: segmentAndMetadataList is empty + segmentAndMetadataList := []*dbmodel.SegmentAndMetadata{} + modelSegments = convertSegmentToModel(segmentAndMetadataList) + assert.Empty(t, modelSegments) + + // Test case 3: segmentAndMetadataList contains one segment with all fields set + segmentID := types.MustParse("515fc331-e117-4b86-bd84-85341128c337") + segmentTopic := "segment_topic" + collectionID := "d9a75e2e-2929-45c4-af06-75b15630edd0" + segmentAndMetadata := &dbmodel.SegmentAndMetadata{ + Segment: &dbmodel.Segment{ + ID: segmentID.String(), + Type: "segment_type", + Scope: "segment_scope", + Topic: &segmentTopic, + CollectionID: &collectionID, + }, + SegmentMetadata: []*dbmodel.SegmentMetadata{}, + } + segmentAndMetadataList = []*dbmodel.SegmentAndMetadata{segmentAndMetadata} + modelSegments = convertSegmentToModel(segmentAndMetadataList) + assert.Len(t, modelSegments, 1) + assert.Equal(t, segmentID, modelSegments[0].ID) + assert.Equal(t, "segment_type", modelSegments[0].Type) + assert.Equal(t, "segment_scope", modelSegments[0].Scope) + assert.Equal(t, "segment_topic", *modelSegments[0].Topic) + assert.Equal(t, types.MustParse(collectionID), modelSegments[0].CollectionID) + assert.Nil(t, modelSegments[0].Metadata) +} + +func TestConvertSegmentMetadataToModel(t *testing.T) { + // Test case 1: segmentMetadataList is nil + modelSegmentMetadata := convertSegmentMetadataToModel(nil) + assert.Nil(t, modelSegmentMetadata) + + // Test case 2: segmentMetadataList is empty + segmentMetadataList := []*dbmodel.SegmentMetadata{} + modelSegmentMetadata = convertSegmentMetadataToModel(segmentMetadataList) + assert.Empty(t, modelSegmentMetadata) + + // Test case 3: segmentMetadataList contains one segment metadata with all fields set + segmentID := types.MustParse("515fc331-e117-4b86-bd84-85341128c337") + strKey := "strKey" + strValue := "strValue" + segmentMetadata := &dbmodel.SegmentMetadata{ + SegmentID: segmentID.String(), + Key: &strKey, + StrValue: &strValue, + } + segmentMetadataList = []*dbmodel.SegmentMetadata{segmentMetadata} + modelSegmentMetadata = convertSegmentMetadataToModel(segmentMetadataList) + assert.Len(t, modelSegmentMetadata.Keys(), 1) + assert.Equal(t, &model.SegmentMetadataValueStringType{Value: strValue}, modelSegmentMetadata.Get(strKey)) +} +func TestConvertCollectionToModel(t *testing.T) { + // Test case 1: collectionAndMetadataList is nil + modelCollections := convertCollectionToModel(nil) + assert.Nil(t, modelCollections) + + // Test case 2: collectionAndMetadataList is empty + collectionAndMetadataList := []*dbmodel.CollectionAndMetadata{} + modelCollections = convertCollectionToModel(collectionAndMetadataList) + assert.Empty(t, modelCollections) + + // Test case 3: collectionAndMetadataList contains one collection with all fields set + collectionID := types.MustParse("d9a75e2e-2929-45c4-af06-75b15630edd0") + collectionName := "collection_name" + collectionTopic := "collection_topic" + collectionDimension := int32(3) + collectionAndMetadata := &dbmodel.CollectionAndMetadata{ + Collection: &dbmodel.Collection{ + ID: collectionID.String(), + Name: &collectionName, + Topic: &collectionTopic, + Dimension: &collectionDimension, + }, + CollectionMetadata: []*dbmodel.CollectionMetadata{}, + } + collectionAndMetadataList = []*dbmodel.CollectionAndMetadata{collectionAndMetadata} + modelCollections = convertCollectionToModel(collectionAndMetadataList) + assert.Len(t, modelCollections, 1) + assert.Equal(t, collectionID, modelCollections[0].ID) + assert.Equal(t, collectionName, modelCollections[0].Name) + assert.Equal(t, collectionTopic, modelCollections[0].Topic) + assert.Equal(t, collectionDimension, *modelCollections[0].Dimension) + assert.Nil(t, modelCollections[0].Metadata) +} diff --git a/go/coordinator/internal/metastore/coordinator/table_catalog.go b/go/coordinator/internal/metastore/coordinator/table_catalog.go new file mode 100644 index 0000000000000000000000000000000000000000..4bd0d7f1244fb8c0ac81567e54c009191558db1d --- /dev/null +++ b/go/coordinator/internal/metastore/coordinator/table_catalog.go @@ -0,0 +1,564 @@ +package coordinator + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/notification" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +// The catalog backed by databases using GORM. +type Catalog struct { + metaDomain dbmodel.IMetaDomain + txImpl dbmodel.ITransaction + store notification.NotificationStore +} + +func NewTableCatalog(txImpl dbmodel.ITransaction, metaDomain dbmodel.IMetaDomain) *Catalog { + return &Catalog{ + txImpl: txImpl, + metaDomain: metaDomain, + } +} + +func NewTableCatalogWithNotification(txImpl dbmodel.ITransaction, metaDomain dbmodel.IMetaDomain, store notification.NotificationStore) *Catalog { + catalog := NewTableCatalog(txImpl, metaDomain) + catalog.store = store + return catalog +} + +var _ metastore.Catalog = (*Catalog)(nil) + +func (tc *Catalog) ResetState(ctx context.Context) error { + return tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + err := tc.metaDomain.CollectionDb(txCtx).DeleteAll() + if err != nil { + log.Error("error reset collection db", zap.Error(err)) + return err + } + err = tc.metaDomain.CollectionMetadataDb(txCtx).DeleteAll() + if err != nil { + log.Error("error reest collection metadata db", zap.Error(err)) + return err + } + err = tc.metaDomain.SegmentDb(txCtx).DeleteAll() + if err != nil { + log.Error("error reset segment db", zap.Error(err)) + return err + } + err = tc.metaDomain.SegmentMetadataDb(txCtx).DeleteAll() + if err != nil { + log.Error("error reset segment metadata db", zap.Error(err)) + return err + } + err = tc.metaDomain.DatabaseDb(txCtx).DeleteAll() + if err != nil { + log.Error("error reset database db", zap.Error(err)) + return err + } + + err = tc.metaDomain.DatabaseDb(txCtx).Insert(&dbmodel.Database{ + ID: types.NilUniqueID().String(), + Name: common.DefaultDatabase, + TenantID: common.DefaultTenant, + }) + if err != nil { + log.Error("error inserting default database", zap.Error(err)) + return err + } + + err = tc.metaDomain.TenantDb(txCtx).DeleteAll() + if err != nil { + log.Error("error reset tenant db", zap.Error(err)) + return err + } + err = tc.metaDomain.TenantDb(txCtx).Insert(&dbmodel.Tenant{ + ID: common.DefaultTenant, + }) + if err != nil { + log.Error("error inserting default tenant", zap.Error(err)) + return err + } + + return nil + }) +} + +func (tc *Catalog) CreateDatabase(ctx context.Context, createDatabase *model.CreateDatabase, ts types.Timestamp) (*model.Database, error) { + var result *model.Database + + err := tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + dbDatabase := &dbmodel.Database{ + ID: createDatabase.ID, + Name: createDatabase.Name, + TenantID: createDatabase.Tenant, + Ts: ts, + } + err := tc.metaDomain.DatabaseDb(txCtx).Insert(dbDatabase) + if err != nil { + log.Error("error inserting database", zap.Error(err)) + return err + } + databaseList, err := tc.metaDomain.DatabaseDb(txCtx).GetDatabases(createDatabase.Tenant, createDatabase.Name) + if err != nil { + log.Error("error getting database", zap.Error(err)) + return err + } + result = convertDatabaseToModel(databaseList[0]) + return nil + }) + if err != nil { + log.Error("error creating database", zap.Error(err)) + return nil, err + } + log.Info("database created", zap.Any("database", result)) + return result, nil +} + +func (tc *Catalog) GetDatabases(ctx context.Context, getDatabase *model.GetDatabase, ts types.Timestamp) (*model.Database, error) { + databases, err := tc.metaDomain.DatabaseDb(ctx).GetDatabases(getDatabase.Tenant, getDatabase.Name) + if err != nil { + return nil, err + } + if len(databases) == 0 { + return nil, common.ErrDatabaseNotFound + } + result := make([]*model.Database, 0, len(databases)) + for _, database := range databases { + result = append(result, convertDatabaseToModel(database)) + } + return result[0], nil +} + +func (tc *Catalog) GetAllDatabases(ctx context.Context, ts types.Timestamp) ([]*model.Database, error) { + databases, err := tc.metaDomain.DatabaseDb(ctx).GetAllDatabases() + if err != nil { + log.Error("error getting all databases", zap.Error(err)) + return nil, err + } + result := make([]*model.Database, 0, len(databases)) + for _, database := range databases { + result = append(result, convertDatabaseToModel(database)) + } + return result, nil +} + +func (tc *Catalog) CreateTenant(ctx context.Context, createTenant *model.CreateTenant, ts types.Timestamp) (*model.Tenant, error) { + var result *model.Tenant + + err := tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + dbTenant := &dbmodel.Tenant{ + ID: createTenant.Name, + Ts: ts, + } + err := tc.metaDomain.TenantDb(txCtx).Insert(dbTenant) + if err != nil { + return err + } + tenantList, err := tc.metaDomain.TenantDb(txCtx).GetTenants(createTenant.Name) + if err != nil { + return err + } + result = convertTenantToModel(tenantList[0]) + return nil + }) + if err != nil { + return nil, err + } + return result, nil +} + +func (tc *Catalog) GetTenants(ctx context.Context, getTenant *model.GetTenant, ts types.Timestamp) (*model.Tenant, error) { + tenants, err := tc.metaDomain.TenantDb(ctx).GetTenants(getTenant.Name) + if err != nil { + log.Error("error getting tenants", zap.Error(err)) + return nil, err + } + if (len(tenants)) == 0 { + log.Error("tenant not found", zap.Error(err)) + return nil, common.ErrTenantNotFound + } + result := make([]*model.Tenant, 0, len(tenants)) + for _, tenant := range tenants { + result = append(result, convertTenantToModel(tenant)) + } + return result[0], nil +} + +func (tc *Catalog) GetAllTenants(ctx context.Context, ts types.Timestamp) ([]*model.Tenant, error) { + tenants, err := tc.metaDomain.TenantDb(ctx).GetAllTenants() + if err != nil { + log.Error("error getting all tenants", zap.Error(err)) + return nil, err + } + result := make([]*model.Tenant, 0, len(tenants)) + for _, tenant := range tenants { + result = append(result, convertTenantToModel(tenant)) + } + return result, nil +} + +func (tc *Catalog) CreateCollection(ctx context.Context, createCollection *model.CreateCollection, ts types.Timestamp) (*model.Collection, error) { + var result *model.Collection + + err := tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + // insert collection + databaseName := createCollection.DatabaseName + tenantID := createCollection.TenantID + databases, err := tc.metaDomain.DatabaseDb(txCtx).GetDatabases(tenantID, databaseName) + if err != nil { + log.Error("error getting database", zap.Error(err)) + return err + } + if len(databases) == 0 { + log.Error("database not found", zap.Error(err)) + return common.ErrDatabaseNotFound + } + + collectionName := createCollection.Name + existing, err := tc.metaDomain.CollectionDb(txCtx).GetCollections(types.FromUniqueID(createCollection.ID), &collectionName, nil, tenantID, databaseName) + if err != nil { + log.Error("error getting collection", zap.Error(err)) + return err + } + if len(existing) != 0 { + if createCollection.GetOrCreate { + collection := convertCollectionToModel(existing)[0] + if createCollection.Metadata != nil && !createCollection.Metadata.Equals(collection.Metadata) { + updatedCollection, err := tc.UpdateCollection(ctx, &model.UpdateCollection{ + ID: collection.ID, + Metadata: createCollection.Metadata, + TenantID: tenantID, + DatabaseName: databaseName, + }, ts) + if err != nil { + log.Error("error updating collection", zap.Error(err)) + } + result = updatedCollection + } else { + result = collection + } + return nil + } else { + return common.ErrCollectionUniqueConstraintViolation + } + } + + dbCollection := &dbmodel.Collection{ + ID: createCollection.ID.String(), + Name: &createCollection.Name, + Topic: &createCollection.Topic, + Dimension: createCollection.Dimension, + DatabaseID: databases[0].ID, + Ts: ts, + } + + err = tc.metaDomain.CollectionDb(txCtx).Insert(dbCollection) + if err != nil { + log.Error("error inserting collection", zap.Error(err)) + return err + } + // insert collection metadata + metadata := createCollection.Metadata + dbCollectionMetadataList := convertCollectionMetadataToDB(createCollection.ID.String(), metadata) + if len(dbCollectionMetadataList) != 0 { + err = tc.metaDomain.CollectionMetadataDb(txCtx).Insert(dbCollectionMetadataList) + if err != nil { + return err + } + } + // get collection + collectionList, err := tc.metaDomain.CollectionDb(txCtx).GetCollections(types.FromUniqueID(createCollection.ID), nil, nil, tenantID, databaseName) + if err != nil { + log.Error("error getting collection", zap.Error(err)) + return err + } + result = convertCollectionToModel(collectionList)[0] + result.Created = true + + notificationRecord := &dbmodel.Notification{ + CollectionID: result.ID.String(), + Type: dbmodel.NotificationTypeCreateCollection, + Status: dbmodel.NotificationStatusPending, + } + err = tc.metaDomain.NotificationDb(txCtx).Insert(notificationRecord) + if err != nil { + return err + } + return nil + }) + if err != nil { + log.Error("error creating collection", zap.Error(err)) + return nil, err + } + log.Info("collection created", zap.Any("collection", result)) + return result, nil +} + +func (tc *Catalog) GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string, tenandID string, databaseName string) ([]*model.Collection, error) { + collectionAndMetadataList, err := tc.metaDomain.CollectionDb(ctx).GetCollections(types.FromUniqueID(collectionID), collectionName, collectionTopic, tenandID, databaseName) + if err != nil { + return nil, err + } + collections := convertCollectionToModel(collectionAndMetadataList) + return collections, nil +} + +func (tc *Catalog) DeleteCollection(ctx context.Context, deleteCollection *model.DeleteCollection) error { + return tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + collectionID := deleteCollection.ID + err := tc.metaDomain.CollectionDb(txCtx).DeleteCollectionByID(collectionID.String()) + if err != nil { + return err + } + err = tc.metaDomain.CollectionMetadataDb(txCtx).DeleteByCollectionID(collectionID.String()) + if err != nil { + return err + } + notificationRecord := &dbmodel.Notification{ + CollectionID: collectionID.String(), + Type: dbmodel.NotificationTypeDeleteCollection, + Status: dbmodel.NotificationStatusPending, + } + err = tc.metaDomain.NotificationDb(txCtx).Insert(notificationRecord) + if err != nil { + return err + } + return nil + }) +} + +func (tc *Catalog) UpdateCollection(ctx context.Context, updateCollection *model.UpdateCollection, ts types.Timestamp) (*model.Collection, error) { + var result *model.Collection + + err := tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + dbCollection := &dbmodel.Collection{ + ID: updateCollection.ID.String(), + Name: updateCollection.Name, + Topic: updateCollection.Topic, + Dimension: updateCollection.Dimension, + Ts: ts, + } + err := tc.metaDomain.CollectionDb(txCtx).Update(dbCollection) + if err != nil { + return err + } + + // Case 1: if ResetMetadata is true, then delete all metadata for the collection + // Case 2: if ResetMetadata is true and metadata is not nil -> THIS SHOULD NEVER HAPPEN + // Case 3: if ResetMetadata is false, and the metadata is not nil - set the metadata to the value in metadata + // Case 4: if ResetMetadata is false and metadata is nil, then leave the metadata as is + metadata := updateCollection.Metadata + resetMetadata := updateCollection.ResetMetadata + if resetMetadata { + if metadata != nil { // Case 2 + return common.ErrInvalidMetadataUpdate + } else { // Case 1 + err = tc.metaDomain.CollectionMetadataDb(txCtx).DeleteByCollectionID(updateCollection.ID.String()) + if err != nil { + return err + } + } + } else { + if metadata != nil { // Case 3 + err = tc.metaDomain.CollectionMetadataDb(txCtx).DeleteByCollectionID(updateCollection.ID.String()) + if err != nil { + return err + } + dbCollectionMetadataList := convertCollectionMetadataToDB(updateCollection.ID.String(), metadata) + if len(dbCollectionMetadataList) != 0 { + err = tc.metaDomain.CollectionMetadataDb(txCtx).Insert(dbCollectionMetadataList) + if err != nil { + return err + } + } + } + } + databaseName := updateCollection.DatabaseName + tenantID := updateCollection.TenantID + collectionList, err := tc.metaDomain.CollectionDb(txCtx).GetCollections(types.FromUniqueID(updateCollection.ID), nil, nil, tenantID, databaseName) + if err != nil { + return err + } + result = convertCollectionToModel(collectionList)[0] + return nil + }) + if err != nil { + return nil, err + } + log.Info("collection updated", zap.Any("collection", result)) + return result, nil +} + +func (tc *Catalog) CreateSegment(ctx context.Context, createSegment *model.CreateSegment, ts types.Timestamp) (*model.Segment, error) { + var result *model.Segment + + err := tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + // insert segment + collectionString := createSegment.CollectionID.String() + dbSegment := &dbmodel.Segment{ + ID: createSegment.ID.String(), + CollectionID: &collectionString, + Type: createSegment.Type, + Scope: createSegment.Scope, + Ts: ts, + } + if createSegment.Topic != nil { + dbSegment.Topic = createSegment.Topic + } + err := tc.metaDomain.SegmentDb(txCtx).Insert(dbSegment) + if err != nil { + log.Error("error inserting segment", zap.Error(err)) + return err + } + // insert segment metadata + metadata := createSegment.Metadata + if metadata != nil { + dbSegmentMetadataList := convertSegmentMetadataToDB(createSegment.ID.String(), metadata) + if len(dbSegmentMetadataList) != 0 { + err = tc.metaDomain.SegmentMetadataDb(txCtx).Insert(dbSegmentMetadataList) + if err != nil { + log.Error("error inserting segment metadata", zap.Error(err)) + return err + } + } + } + // get segment + segmentList, err := tc.metaDomain.SegmentDb(txCtx).GetSegments(createSegment.ID, nil, nil, nil, types.NilUniqueID()) + if err != nil { + log.Error("error getting segment", zap.Error(err)) + return err + } + result = convertSegmentToModel(segmentList)[0] + return nil + }) + if err != nil { + log.Error("error creating segment", zap.Error(err)) + return nil, err + } + log.Info("segment created", zap.Any("segment", result)) + return result, nil +} + +func (tc *Catalog) GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID, ts types.Timestamp) ([]*model.Segment, error) { + segmentAndMetadataList, err := tc.metaDomain.SegmentDb(ctx).GetSegments(segmentID, segmentType, scope, topic, collectionID) + if err != nil { + return nil, err + } + segments := make([]*model.Segment, 0, len(segmentAndMetadataList)) + for _, segmentAndMetadata := range segmentAndMetadataList { + segment := &model.Segment{ + ID: types.MustParse(segmentAndMetadata.Segment.ID), + Type: segmentAndMetadata.Segment.Type, + Scope: segmentAndMetadata.Segment.Scope, + Topic: segmentAndMetadata.Segment.Topic, + Ts: segmentAndMetadata.Segment.Ts, + } + + if segmentAndMetadata.Segment.CollectionID != nil { + segment.CollectionID = types.MustParse(*segmentAndMetadata.Segment.CollectionID) + } else { + segment.CollectionID = types.NilUniqueID() + } + segment.Metadata = convertSegmentMetadataToModel(segmentAndMetadata.SegmentMetadata) + segments = append(segments, segment) + } + return segments, nil +} + +func (tc *Catalog) DeleteSegment(ctx context.Context, segmentID types.UniqueID) error { + return tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + err := tc.metaDomain.SegmentDb(txCtx).DeleteSegmentByID(segmentID.String()) + if err != nil { + log.Error("error deleting segment", zap.Error(err)) + return err + } + err = tc.metaDomain.SegmentMetadataDb(txCtx).DeleteBySegmentID(segmentID.String()) + if err != nil { + log.Error("error deleting segment metadata", zap.Error(err)) + return err + } + return nil + }) +} + +func (tc *Catalog) UpdateSegment(ctx context.Context, updateSegment *model.UpdateSegment, ts types.Timestamp) (*model.Segment, error) { + var result *model.Segment + + err := tc.txImpl.Transaction(ctx, func(txCtx context.Context) error { + // update segment + dbSegment := &dbmodel.UpdateSegment{ + ID: updateSegment.ID.String(), + Topic: updateSegment.Topic, + ResetTopic: updateSegment.ResetTopic, + Collection: updateSegment.Collection, + ResetCollection: updateSegment.ResetCollection, + } + + err := tc.metaDomain.SegmentDb(txCtx).Update(dbSegment) + if err != nil { + return err + } + + // Case 1: if ResetMetadata is true, then delete all metadata for the collection + // Case 2: if ResetMetadata is true and metadata is not nil -> THIS SHOULD NEVER HAPPEN + // Case 3: if ResetMetadata is false, and the metadata is not nil - set the metadata to the value in metadata + // Case 4: if ResetMetadata is false and metadata is nil, then leave the metadata as is + metadata := updateSegment.Metadata + resetMetadata := updateSegment.ResetMetadata + if resetMetadata { + if metadata != nil { // Case 2 + return common.ErrInvalidMetadataUpdate + } else { // Case 1 + err := tc.metaDomain.SegmentMetadataDb(txCtx).DeleteBySegmentID(updateSegment.ID.String()) + if err != nil { + return err + } + } + } else { + if metadata != nil { // Case 3 + err := tc.metaDomain.SegmentMetadataDb(txCtx).DeleteBySegmentIDAndKeys(updateSegment.ID.String(), metadata.Keys()) + if err != nil { + log.Error("error deleting segment metadata", zap.Error(err)) + return err + } + newMetadata := model.NewSegmentMetadata[model.SegmentMetadataValueType]() + for _, key := range metadata.Keys() { + if metadata.Get(key) == nil { + metadata.Remove(key) + } else { + newMetadata.Set(key, metadata.Get(key)) + } + } + dbSegmentMetadataList := convertSegmentMetadataToDB(updateSegment.ID.String(), newMetadata) + if len(dbSegmentMetadataList) != 0 { + err = tc.metaDomain.SegmentMetadataDb(txCtx).Insert(dbSegmentMetadataList) + if err != nil { + return err + } + } + } + } + + // get segment + segmentList, err := tc.metaDomain.SegmentDb(txCtx).GetSegments(updateSegment.ID, nil, nil, nil, types.NilUniqueID()) + if err != nil { + log.Error("error getting segment", zap.Error(err)) + return err + } + result = convertSegmentToModel(segmentList)[0] + return nil + }) + if err != nil { + log.Error("error updating segment", zap.Error(err)) + return nil, err + } + log.Debug("segment updated", zap.Any("segment", result)) + return result, nil +} diff --git a/go/coordinator/internal/metastore/coordinator/table_catalog_test.go b/go/coordinator/internal/metastore/coordinator/table_catalog_test.go new file mode 100644 index 0000000000000000000000000000000000000000..f40cddffd380bd0b902255041578f2b905eaa0fd --- /dev/null +++ b/go/coordinator/internal/metastore/coordinator/table_catalog_test.go @@ -0,0 +1,136 @@ +package coordinator + +import ( + "context" + "testing" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel/mocks" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/stretchr/testify/assert" + "github.com/stretchr/testify/mock" +) + +func TestCatalog_CreateCollection(t *testing.T) { + // create a mock transaction implementation + mockTxImpl := &mocks.ITransaction{} + + // create a mock meta domain implementation + mockMetaDomain := &mocks.IMetaDomain{} + + // create a new catalog instance + catalog := NewTableCatalog(mockTxImpl, mockMetaDomain) + + // create a mock collection + metadata := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + metadata.Add("test_key", &model.CollectionMetadataValueStringType{Value: "test_value"}) + collection := &model.CreateCollection{ + ID: types.MustParse("00000000-0000-0000-0000-000000000001"), + Name: "test_collection", + Metadata: metadata, + } + + // create a mock timestamp + ts := types.Timestamp(1234567890) + + // mock the insert collection method + name := "test_collection" + mockTxImpl.On("Transaction", context.Background(), mock.Anything).Return(nil) + mockMetaDomain.On("CollectionDb", context.Background()).Return(&mocks.ICollectionDb{}) + mockMetaDomain.CollectionDb(context.Background()).(*mocks.ICollectionDb).On("Insert", &dbmodel.Collection{ + ID: "00000000-0000-0000-0000-000000000001", + Name: &name, + // Topic: "test_topic", + Ts: ts, + }).Return(nil) + + // mock the insert collection metadata method + testKey := "test_key" + testValue := "test_value" + mockMetaDomain.On("CollectionMetadataDb", context.Background()).Return(&mocks.ICollectionMetadataDb{}) + mockMetaDomain.CollectionMetadataDb(context.Background()).(*mocks.ICollectionMetadataDb).On("Insert", []*dbmodel.CollectionMetadata{ + { + CollectionID: "00000000-0000-0000-0000-000000000001", + Key: &testKey, + StrValue: &testValue, + Ts: ts, + }, + }).Return(nil) + + // call the CreateCollection method + _, err := catalog.CreateCollection(context.Background(), collection, ts) + + // assert that the method returned no error + assert.NoError(t, err) + + // assert that the mock methods were called as expected + mockMetaDomain.AssertExpectations(t) +} + +func TestCatalog_GetCollections(t *testing.T) { + // create a mock meta domain implementation + mockMetaDomain := &mocks.IMetaDomain{} + + // create a new catalog instance + catalog := NewTableCatalog(nil, mockMetaDomain) + + // create a mock collection ID + collectionID := types.MustParse("00000000-0000-0000-0000-000000000001") + + // create a mock collection name + collectionName := "test_collection" + + // create a mock collection topic + collectionTopic := "test_topic" + + // create a mock collection and metadata list + name := "test_collection" + testKey := "test_key" + testValue := "test_value" + collectionAndMetadataList := []*dbmodel.CollectionAndMetadata{ + { + Collection: &dbmodel.Collection{ + ID: "00000000-0000-0000-0000-000000000001", + Name: &name, + Topic: &collectionTopic, + Ts: types.Timestamp(1234567890), + }, + CollectionMetadata: []*dbmodel.CollectionMetadata{ + { + CollectionID: "00000000-0000-0000-0000-000000000001", + Key: &testKey, + StrValue: &testValue, + Ts: types.Timestamp(1234567890), + }, + }, + }, + } + + // mock the get collections method + mockMetaDomain.On("CollectionDb", context.Background()).Return(&mocks.ICollectionDb{}) + mockMetaDomain.CollectionDb(context.Background()).(*mocks.ICollectionDb).On("GetCollections", types.FromUniqueID(collectionID), &collectionName, &collectionTopic, common.DefaultTenant, common.DefaultDatabase).Return(collectionAndMetadataList, nil) + + // call the GetCollections method + collections, err := catalog.GetCollections(context.Background(), collectionID, &collectionName, &collectionTopic, defaultTenant, defaultDatabase) + + // assert that the method returned no error + assert.NoError(t, err) + + // assert that the collections were returned as expected + metadata := model.NewCollectionMetadata[model.CollectionMetadataValueType]() + metadata.Add("test_key", &model.CollectionMetadataValueStringType{Value: "test_value"}) + assert.Equal(t, []*model.Collection{ + { + ID: types.MustParse("00000000-0000-0000-0000-000000000001"), + Name: "test_collection", + Topic: collectionTopic, + Ts: types.Timestamp(1234567890), + Metadata: metadata, + }, + }, collections) + + // assert that the mock methods were called as expected + mockMetaDomain.AssertExpectations(t) +} diff --git a/go/coordinator/internal/metastore/db/dao/collection.go b/go/coordinator/internal/metastore/db/dao/collection.go new file mode 100644 index 0000000000000000000000000000000000000000..b21da7a9f76543d64de8f6d942a744a5568afef7 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/collection.go @@ -0,0 +1,160 @@ +package dao + +import ( + "database/sql" + + "go.uber.org/zap" + "gorm.io/gorm" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/pingcap/log" +) + +type collectionDb struct { + db *gorm.DB +} + +var _ dbmodel.ICollectionDb = &collectionDb{} + +func (s *collectionDb) DeleteAll() error { + return s.db.Where("1 = 1").Delete(&dbmodel.Collection{}).Error +} + +func (s *collectionDb) GetCollections(id *string, name *string, topic *string, tenantID string, databaseName string) ([]*dbmodel.CollectionAndMetadata, error) { + var collections []*dbmodel.CollectionAndMetadata + + query := s.db.Table("collections"). + Select("collections.id, collections.name, collections.topic, collections.dimension, collections.database_id, databases.name, databases.tenant_id, collection_metadata.key, collection_metadata.str_value, collection_metadata.int_value, collection_metadata.float_value"). + Joins("LEFT JOIN collection_metadata ON collections.id = collection_metadata.collection_id"). + Joins("INNER JOIN databases ON collections.database_id = databases.id"). + Order("collections.id") + + query = query.Where("databases.name = ?", databaseName) + + query = query.Where("databases.tenant_id = ?", tenantID) + + if id != nil { + query = query.Where("collections.id = ?", *id) + } + if topic != nil { + query = query.Where("collections.topic = ?", *topic) + } + if name != nil { + query = query.Where("collections.name = ?", *name) + } + + rows, err := query.Rows() + if err != nil { + return nil, err + } + defer rows.Close() + + var currentCollectionID string = "" + var metadata []*dbmodel.CollectionMetadata + var currentCollection *dbmodel.CollectionAndMetadata + + for rows.Next() { + var ( + collectionID string + collectionName string + collectionTopic string + collectionDimension sql.NullInt32 + collectionDatabaseID string + databaseName string + databaseTenantID string + key sql.NullString + strValue sql.NullString + intValue sql.NullInt64 + floatValue sql.NullFloat64 + ) + + err := rows.Scan(&collectionID, &collectionName, &collectionTopic, &collectionDimension, &collectionDatabaseID, &databaseName, &databaseTenantID, &key, &strValue, &intValue, &floatValue) + if err != nil { + log.Error("scan collection failed", zap.Error(err)) + return nil, err + } + if collectionID != currentCollectionID { + currentCollectionID = collectionID + metadata = nil + + currentCollection = &dbmodel.CollectionAndMetadata{ + Collection: &dbmodel.Collection{ + ID: collectionID, + Name: &collectionName, + Topic: &collectionTopic, + DatabaseID: collectionDatabaseID, + }, + CollectionMetadata: metadata, + TenantID: databaseTenantID, + DatabaseName: databaseName, + } + if collectionDimension.Valid { + currentCollection.Collection.Dimension = &collectionDimension.Int32 + } else { + currentCollection.Collection.Dimension = nil + } + + if currentCollectionID != "" { + collections = append(collections, currentCollection) + } + } + + collectionMetadata := &dbmodel.CollectionMetadata{ + CollectionID: collectionID, + } + + if key.Valid { + collectionMetadata.Key = &key.String + } else { + collectionMetadata.Key = nil + } + + if strValue.Valid { + collectionMetadata.StrValue = &strValue.String + } else { + collectionMetadata.StrValue = nil + } + if intValue.Valid { + collectionMetadata.IntValue = &intValue.Int64 + } else { + collectionMetadata.IntValue = nil + } + if floatValue.Valid { + collectionMetadata.FloatValue = &floatValue.Float64 + } else { + collectionMetadata.FloatValue = nil + } + + metadata = append(metadata, collectionMetadata) + currentCollection.CollectionMetadata = metadata + } + log.Info("collections", zap.Any("collections", collections)) + return collections, nil +} + +func (s *collectionDb) DeleteCollectionByID(collectionID string) error { + return s.db.Where("id = ?", collectionID).Delete(&dbmodel.Collection{}).Error +} + +func (s *collectionDb) Insert(in *dbmodel.Collection) error { + return s.db.Create(&in).Error +} + +func generateCollectionUpdatesWithoutID(in *dbmodel.Collection) map[string]interface{} { + ret := map[string]interface{}{} + if in.Name != nil { + ret["name"] = *in.Name + } + if in.Topic != nil { + ret["topic"] = *in.Topic + } + if in.Dimension != nil { + ret["dimension"] = *in.Dimension + } + return ret +} + +func (s *collectionDb) Update(in *dbmodel.Collection) error { + updates := generateCollectionUpdatesWithoutID(in) + return s.db.Model(&dbmodel.Collection{}).Where("id = ?", in.ID).Updates(updates).Error +} diff --git a/go/coordinator/internal/metastore/db/dao/collection_metadata.go b/go/coordinator/internal/metastore/db/dao/collection_metadata.go new file mode 100644 index 0000000000000000000000000000000000000000..0f9ba00057ecd46ae8a4cb5010912d61ba2b16e3 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/collection_metadata.go @@ -0,0 +1,26 @@ +package dao + +import ( + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "gorm.io/gorm" + "gorm.io/gorm/clause" +) + +type collectionMetadataDb struct { + db *gorm.DB +} + +func (s *collectionMetadataDb) DeleteAll() error { + return s.db.Where("1 = 1").Delete(&dbmodel.CollectionMetadata{}).Error +} + +func (s *collectionMetadataDb) DeleteByCollectionID(collectionID string) error { + return s.db.Where("collection_id = ?", collectionID).Delete(&dbmodel.CollectionMetadata{}).Error +} + +func (s *collectionMetadataDb) Insert(in []*dbmodel.CollectionMetadata) error { + return s.db.Clauses(clause.OnConflict{ + Columns: []clause.Column{{Name: "collection_id"}, {Name: "key"}}, + DoUpdates: clause.AssignmentColumns([]string{"str_value", "int_value", "float_value"}), + }).Create(in).Error +} diff --git a/go/coordinator/internal/metastore/db/dao/collection_test.go b/go/coordinator/internal/metastore/db/dao/collection_test.go new file mode 100644 index 0000000000000000000000000000000000000000..1c2da046ec01aed1748be5dcfc56f56a640ab45a --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/collection_test.go @@ -0,0 +1,95 @@ +package dao + +import ( + "testing" + + "github.com/pingcap/log" + "go.uber.org/zap" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/stretchr/testify/assert" + "gorm.io/driver/sqlite" + "gorm.io/gorm" +) + +func TestCollectionDb_GetCollections(t *testing.T) { + db, err := gorm.Open(sqlite.Open(":memory:"), &gorm.Config{}) + assert.NoError(t, err) + + err = db.AutoMigrate(&dbmodel.Tenant{}, &dbmodel.Database{}, &dbmodel.Collection{}, &dbmodel.CollectionMetadata{}) + db.Model(&dbmodel.Tenant{}).Create(&dbmodel.Tenant{ + ID: common.DefaultTenant, + }) + + databaseID := types.NilUniqueID().String() + db.Model(&dbmodel.Database{}).Create(&dbmodel.Database{ + ID: databaseID, + Name: common.DefaultDatabase, + TenantID: common.DefaultTenant, + }) + + assert.NoError(t, err) + name := "test_name" + topic := "test_topic" + collection := &dbmodel.Collection{ + ID: types.NewUniqueID().String(), + Name: &name, + Topic: &topic, + DatabaseID: databaseID, + } + err = db.Create(collection).Error + assert.NoError(t, err) + + testKey := "test" + testValue := "test" + metadata := &dbmodel.CollectionMetadata{ + CollectionID: collection.ID, + Key: &testKey, + StrValue: &testValue, + } + err = db.Create(metadata).Error + assert.NoError(t, err) + + collectionDb := &collectionDb{ + db: db, + } + + query := db.Table("collections").Select("collections.id") + rows, err := query.Rows() + assert.NoError(t, err) + for rows.Next() { + var collectionID string + err = rows.Scan(&collectionID) + assert.NoError(t, err) + log.Info("collectionID", zap.String("collectionID", collectionID)) + } + collections, err := collectionDb.GetCollections(nil, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Len(t, collections, 1) + assert.Equal(t, collection.ID, collections[0].Collection.ID) + assert.Equal(t, collection.Name, collections[0].Collection.Name) + assert.Equal(t, collection.Topic, collections[0].Collection.Topic) + assert.Len(t, collections[0].CollectionMetadata, 1) + assert.Equal(t, metadata.Key, collections[0].CollectionMetadata[0].Key) + assert.Equal(t, metadata.StrValue, collections[0].CollectionMetadata[0].StrValue) + + // Test when filtering by ID + collections, err = collectionDb.GetCollections(nil, nil, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Len(t, collections, 1) + assert.Equal(t, collection.ID, collections[0].Collection.ID) + + // Test when filtering by name + collections, err = collectionDb.GetCollections(nil, collection.Name, nil, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Len(t, collections, 1) + assert.Equal(t, collection.ID, collections[0].Collection.ID) + + // Test when filtering by topic + collections, err = collectionDb.GetCollections(nil, nil, collection.Topic, common.DefaultTenant, common.DefaultDatabase) + assert.NoError(t, err) + assert.Len(t, collections, 1) + assert.Equal(t, collection.ID, collections[0].Collection.ID) +} diff --git a/go/coordinator/internal/metastore/db/dao/common.go b/go/coordinator/internal/metastore/db/dao/common.go new file mode 100644 index 0000000000000000000000000000000000000000..c67cea6c7597d3decded21bd5382c3288bb1f491 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/common.go @@ -0,0 +1,42 @@ +package dao + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbcore" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" +) + +type metaDomain struct{} + +func NewMetaDomain() *metaDomain { + return &metaDomain{} +} + +func (*metaDomain) DatabaseDb(ctx context.Context) dbmodel.IDatabaseDb { + return &databaseDb{dbcore.GetDB(ctx)} +} + +func (*metaDomain) TenantDb(ctx context.Context) dbmodel.ITenantDb { + return &tenantDb{dbcore.GetDB(ctx)} +} + +func (*metaDomain) CollectionDb(ctx context.Context) dbmodel.ICollectionDb { + return &collectionDb{dbcore.GetDB(ctx)} +} + +func (*metaDomain) CollectionMetadataDb(ctx context.Context) dbmodel.ICollectionMetadataDb { + return &collectionMetadataDb{dbcore.GetDB(ctx)} +} + +func (*metaDomain) SegmentDb(ctx context.Context) dbmodel.ISegmentDb { + return &segmentDb{dbcore.GetDB(ctx)} +} + +func (*metaDomain) SegmentMetadataDb(ctx context.Context) dbmodel.ISegmentMetadataDb { + return &segmentMetadataDb{dbcore.GetDB(ctx)} +} + +func (*metaDomain) NotificationDb(ctx context.Context) dbmodel.INotificationDb { + return ¬ificationDb{dbcore.GetDB(ctx)} +} diff --git a/go/coordinator/internal/metastore/db/dao/database.go b/go/coordinator/internal/metastore/db/dao/database.go new file mode 100644 index 0000000000000000000000000000000000000000..0d02dca484b1c09814006f80aece8c8fc06fe4a5 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/database.go @@ -0,0 +1,46 @@ +package dao + +import ( + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/pingcap/log" + "go.uber.org/zap" + "gorm.io/gorm" +) + +type databaseDb struct { + db *gorm.DB +} + +var _ dbmodel.IDatabaseDb = &databaseDb{} + +func (s *databaseDb) DeleteAll() error { + return s.db.Where("1 = 1").Delete(&dbmodel.Database{}).Error +} + +func (s *databaseDb) GetAllDatabases() ([]*dbmodel.Database, error) { + var databases []*dbmodel.Database + query := s.db.Table("databases") + + if err := query.Find(&databases).Error; err != nil { + return nil, err + } + return databases, nil +} + +func (s *databaseDb) GetDatabases(tenantID string, databaseName string) ([]*dbmodel.Database, error) { + var databases []*dbmodel.Database + query := s.db.Table("databases"). + Select("databases.id, databases.name, databases.tenant_id"). + Where("databases.name = ?", databaseName). + Where("databases.tenant_id = ?", tenantID) + + if err := query.Find(&databases).Error; err != nil { + log.Error("GetDatabases", zap.Error(err)) + return nil, err + } + return databases, nil +} + +func (s *databaseDb) Insert(database *dbmodel.Database) error { + return s.db.Create(database).Error +} diff --git a/go/coordinator/internal/metastore/db/dao/notification.go b/go/coordinator/internal/metastore/db/dao/notification.go new file mode 100644 index 0000000000000000000000000000000000000000..cfd6bfdfbbf3871ca7a491753d566c54b9377c37 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/notification.go @@ -0,0 +1,42 @@ +package dao + +import ( + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "gorm.io/gorm" +) + +type notificationDb struct { + db *gorm.DB +} + +var _ dbmodel.INotificationDb = ¬ificationDb{} + +func (s *notificationDb) DeleteAll() error { + return s.db.Where("1 = 1").Delete(&dbmodel.Notification{}).Error +} + +func (s *notificationDb) Delete(id []int64) error { + return s.db.Where("id IN ?", id).Delete(&dbmodel.Notification{}).Error +} + +func (s *notificationDb) Insert(in *dbmodel.Notification) error { + return s.db.Create(in).Error +} + +func (s *notificationDb) GetNotificationByCollectionID(collectionID string) ([]*dbmodel.Notification, error) { + var notifications []*dbmodel.Notification + err := s.db.Where("collection_id = ? AND status = ?", collectionID, dbmodel.NotificationStatusPending).Find(¬ifications).Error + if err != nil { + return nil, err + } + return notifications, nil +} + +func (s *notificationDb) GetAllPendingNotifications() ([]*dbmodel.Notification, error) { + var notifications []*dbmodel.Notification + err := s.db.Where("status = ?", dbmodel.NotificationStatusPending).Find(¬ifications).Error + if err != nil { + return nil, err + } + return notifications, nil +} diff --git a/go/coordinator/internal/metastore/db/dao/segment.go b/go/coordinator/internal/metastore/db/dao/segment.go new file mode 100644 index 0000000000000000000000000000000000000000..c4c3842e2784017aef0c7588e0066f1036c9a09e --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/segment.go @@ -0,0 +1,184 @@ +package dao + +import ( + "database/sql" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" + "gorm.io/gorm" +) + +type segmentDb struct { + db *gorm.DB +} + +func (s *segmentDb) DeleteAll() error { + return s.db.Where("1=1").Delete(&dbmodel.Segment{}).Error +} + +func (s *segmentDb) DeleteSegmentByID(id string) error { + return s.db.Where("id = ?", id).Delete(&dbmodel.Segment{}).Error +} + +func (s *segmentDb) Insert(in *dbmodel.Segment) error { + err := s.db.Create(&in).Error + + if err != nil { + log.Error("insert segment failed", zap.String("segmentID", in.ID), zap.Int64("ts", in.Ts), zap.Error(err)) + return err + } + + return nil +} + +func (s *segmentDb) GetSegments(id types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*dbmodel.SegmentAndMetadata, error) { + var segments []*dbmodel.SegmentAndMetadata + + query := s.db.Table("segments"). + Select("segments.id, segments.collection_id, segments.type, segments.scope, segments.topic, segment_metadata.key, segment_metadata.str_value, segment_metadata.int_value, segment_metadata.float_value"). + Joins("LEFT JOIN segment_metadata ON segments.id = segment_metadata.segment_id"). + Order("segments.id") + + if id != types.NilUniqueID() { + query = query.Where("id = ?", id.String()) + } + if segmentType != nil { + query = query.Where("type = ?", segmentType) + } + if scope != nil { + query = query.Where("scope = ?", scope) + } + if topic != nil { + query = query.Where("topic = ?", topic) + } + if collectionID != types.NilUniqueID() { + query = query.Where("collection_id = ?", collectionID.String()) + } + + rows, err := query.Rows() + if err != nil { + log.Error("get segments failed", zap.String("segmentID", id.String()), zap.String("segmentType", *segmentType), zap.String("scope", *scope), zap.String("collectionTopic", *topic), zap.Error(err)) + return nil, err + } + defer rows.Close() + + var currentSegmentID string = "" + var metadata []*dbmodel.SegmentMetadata + var currentSegment *dbmodel.SegmentAndMetadata + + for rows.Next() { + var ( + segmentID string + collectionID sql.NullString + segmentType string + scope string + topic sql.NullString + key sql.NullString + strValue sql.NullString + intValue sql.NullInt64 + floatValue sql.NullFloat64 + ) + + err := rows.Scan(&segmentID, &collectionID, &segmentType, &scope, &topic, &key, &strValue, &intValue, &floatValue) + if err != nil { + log.Error("scan segment failed", zap.Error(err)) + } + if segmentID != currentSegmentID { + currentSegmentID = segmentID + metadata = nil + + currentSegment = &dbmodel.SegmentAndMetadata{ + Segment: &dbmodel.Segment{ + ID: segmentID, + Type: segmentType, + Scope: scope, + }, + SegmentMetadata: metadata, + } + if collectionID.Valid { + currentSegment.Segment.CollectionID = &collectionID.String + } else { + currentSegment.Segment.CollectionID = nil + } + + if topic.Valid { + currentSegment.Segment.Topic = &topic.String + } else { + currentSegment.Segment.Topic = nil + } + + if currentSegmentID != "" { + segments = append(segments, currentSegment) + } + + } + segmentMetadata := &dbmodel.SegmentMetadata{ + SegmentID: segmentID, + } + if key.Valid { + segmentMetadata.Key = &key.String + } else { + segmentMetadata.Key = nil + } + + if strValue.Valid { + segmentMetadata.StrValue = &strValue.String + } else { + segmentMetadata.StrValue = nil + } + + if intValue.Valid { + segmentMetadata.IntValue = &intValue.Int64 + } else { + segmentMetadata.IntValue = nil + } + + if floatValue.Valid { + segmentMetadata.FloatValue = &floatValue.Float64 + } else { + segmentMetadata.FloatValue = nil + } + + metadata = append(metadata, segmentMetadata) + currentSegment.SegmentMetadata = metadata + } + log.Info("get segments success", zap.Any("segments", segments)) + return segments, nil +} + +func generateSegmentUpdatesWithoutID(in *dbmodel.UpdateSegment) map[string]interface{} { + // Case 1: if ResetTopic is true and topic is nil, then set the topic to nil + // Case 2: if ResetTopic is true and topic is not nil -> THIS SHOULD NEVER HAPPEN + // Case 3: if ResetTopic is false and topic is not nil - set the topic to the value in topic + // Case 4: if ResetTopic is false and topic is nil, then leave the topic as is + log.Info("generate segment updates without id", zap.Any("in", in)) + ret := map[string]interface{}{} + if in.ResetTopic { + if in.Topic == nil { + ret["topic"] = nil + } + } else { + if in.Topic != nil { + ret["topic"] = *in.Topic + } + } + + if in.ResetCollection { + if in.Collection == nil { + ret["collection_id"] = nil + } + } else { + if in.Collection != nil { + ret["collection_id"] = *in.Collection + } + } + log.Info("generate segment updates without id", zap.Any("updates", ret)) + return ret +} + +func (s *segmentDb) Update(in *dbmodel.UpdateSegment) error { + updates := generateSegmentUpdatesWithoutID(in) + return s.db.Model(&dbmodel.Segment{}).Where("id = ?", in.ID).Updates(updates).Error +} diff --git a/go/coordinator/internal/metastore/db/dao/segment_metadata.go b/go/coordinator/internal/metastore/db/dao/segment_metadata.go new file mode 100644 index 0000000000000000000000000000000000000000..14d4d2ec2d041de170e9e090ed554911210fa3db --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/segment_metadata.go @@ -0,0 +1,35 @@ +package dao + +import ( + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "gorm.io/gorm" + "gorm.io/gorm/clause" +) + +type segmentMetadataDb struct { + db *gorm.DB +} + +func (s *segmentMetadataDb) DeleteAll() error { + return s.db.Where("1 = 1").Delete(&dbmodel.SegmentMetadata{}).Error +} + +func (s *segmentMetadataDb) DeleteBySegmentID(segmentID string) error { + return s.db.Where("segment_id = ?", segmentID).Delete(&dbmodel.SegmentMetadata{}).Error +} + +func (s *segmentMetadataDb) DeleteBySegmentIDAndKeys(segmentID string, keys []string) error { + return s.db. + Where("segment_id = ?", segmentID). + Where("`key` IN ?", keys). + Delete(&dbmodel.SegmentMetadata{}).Error +} + +func (s *segmentMetadataDb) Insert(in []*dbmodel.SegmentMetadata) error { + return s.db.Clauses( + clause.OnConflict{ + Columns: []clause.Column{{Name: "segment_id"}, {Name: "key"}}, + DoUpdates: clause.AssignmentColumns([]string{"str_value", "int_value", "float_value", "ts"}), + }, + ).Create(in).Error +} diff --git a/go/coordinator/internal/metastore/db/dao/segment_test.go b/go/coordinator/internal/metastore/db/dao/segment_test.go new file mode 100644 index 0000000000000000000000000000000000000000..34522869faaf3530b2ddb4e235efa92bc61d7579 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/segment_test.go @@ -0,0 +1,89 @@ +package dao + +import ( + "testing" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/stretchr/testify/assert" + "gorm.io/driver/sqlite" + "gorm.io/gorm" +) + +func TestSegmentDb_GetSegments(t *testing.T) { + db, err := gorm.Open(sqlite.Open(":memory:"), &gorm.Config{}) + assert.NoError(t, err) + + err = db.AutoMigrate(&dbmodel.Segment{}, &dbmodel.SegmentMetadata{}) + assert.NoError(t, err) + + uniqueID := types.NewUniqueID() + collectionID := uniqueID.String() + testTopic := "test_topic" + segment := &dbmodel.Segment{ + ID: uniqueID.String(), + CollectionID: &collectionID, + Type: "test_type", + Scope: "test_scope", + Topic: &testTopic, + } + err = db.Create(segment).Error + assert.NoError(t, err) + + testKey := "test" + testValue := "test" + metadata := &dbmodel.SegmentMetadata{ + SegmentID: segment.ID, + Key: &testKey, + StrValue: &testValue, + } + err = db.Create(metadata).Error + assert.NoError(t, err) + + segmentDb := &segmentDb{ + db: db, + } + + // Test when all parameters are nil + segments, err := segmentDb.GetSegments(types.NilUniqueID(), nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Len(t, segments, 1) + assert.Equal(t, segment.ID, segments[0].Segment.ID) + assert.Equal(t, segment.CollectionID, segments[0].Segment.CollectionID) + assert.Equal(t, segment.Type, segments[0].Segment.Type) + assert.Equal(t, segment.Scope, segments[0].Segment.Scope) + assert.Equal(t, segment.Topic, segments[0].Segment.Topic) + assert.Len(t, segments[0].SegmentMetadata, 1) + assert.Equal(t, metadata.Key, segments[0].SegmentMetadata[0].Key) + assert.Equal(t, metadata.StrValue, segments[0].SegmentMetadata[0].StrValue) + + // Test when filtering by ID + segments, err = segmentDb.GetSegments(types.MustParse(segment.ID), nil, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Len(t, segments, 1) + assert.Equal(t, segment.ID, segments[0].Segment.ID) + + // Test when filtering by type + segments, err = segmentDb.GetSegments(types.NilUniqueID(), &segment.Type, nil, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Len(t, segments, 1) + assert.Equal(t, segment.ID, segments[0].Segment.ID) + + // Test when filtering by scope + segments, err = segmentDb.GetSegments(types.NilUniqueID(), nil, &segment.Scope, nil, types.NilUniqueID()) + assert.NoError(t, err) + assert.Len(t, segments, 1) + assert.Equal(t, segment.ID, segments[0].Segment.ID) + + // Test when filtering by topic + segments, err = segmentDb.GetSegments(types.NilUniqueID(), nil, nil, segment.Topic, types.NilUniqueID()) + assert.NoError(t, err) + assert.Len(t, segments, 1) + assert.Equal(t, segment.ID, segments[0].Segment.ID) + + // Test when filtering by collection ID + segments, err = segmentDb.GetSegments(types.NilUniqueID(), nil, nil, nil, types.MustParse(*segment.CollectionID)) + assert.NoError(t, err) + assert.Len(t, segments, 1) + assert.Equal(t, segment.ID, segments[0].Segment.ID) +} diff --git a/go/coordinator/internal/metastore/db/dao/tenant.go b/go/coordinator/internal/metastore/db/dao/tenant.go new file mode 100644 index 0000000000000000000000000000000000000000..3fe759082ecfc0957f79e5c22330079ed6d2b2da --- /dev/null +++ b/go/coordinator/internal/metastore/db/dao/tenant.go @@ -0,0 +1,38 @@ +package dao + +import ( + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "gorm.io/gorm" +) + +type tenantDb struct { + db *gorm.DB +} + +var _ dbmodel.ITenantDb = &tenantDb{} + +func (s *tenantDb) DeleteAll() error { + return s.db.Where("1 = 1").Delete(&dbmodel.Tenant{}).Error +} + +func (s *tenantDb) GetAllTenants() ([]*dbmodel.Tenant, error) { + var tenants []*dbmodel.Tenant + + if err := s.db.Find(&tenants).Error; err != nil { + return nil, err + } + return tenants, nil +} + +func (s *tenantDb) GetTenants(tenantID string) ([]*dbmodel.Tenant, error) { + var tenants []*dbmodel.Tenant + + if err := s.db.Where("id = ?", tenantID).Find(&tenants).Error; err != nil { + return nil, err + } + return tenants, nil +} + +func (s *tenantDb) Insert(tenant *dbmodel.Tenant) error { + return s.db.Create(tenant).Error +} diff --git a/go/coordinator/internal/metastore/db/dbcore/core.go b/go/coordinator/internal/metastore/db/dbcore/core.go new file mode 100644 index 0000000000000000000000000000000000000000..95d2885dfc401ff578297c58587ff22dbef351d3 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbcore/core.go @@ -0,0 +1,158 @@ +package dbcore + +import ( + "context" + "fmt" + "reflect" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/types" + "github.com/pingcap/log" + "go.uber.org/zap" + "gorm.io/driver/postgres" + "gorm.io/driver/sqlite" + "gorm.io/gorm" + "gorm.io/gorm/logger" +) + +var ( + globalDB *gorm.DB +) + +type DBConfig struct { + Username string + Password string + Address string + Port int + DBName string + MaxIdleConns int + MaxOpenConns int +} + +func Connect(cfg DBConfig) (*gorm.DB, error) { + dsn := fmt.Sprintf("host=%s user=%s password=%s dbname=%s port=%d sslmode=require", + cfg.Address, cfg.Username, cfg.Password, cfg.DBName, cfg.Port) + + ormLogger := logger.Default + ormLogger.LogMode(logger.Info) + db, err := gorm.Open(postgres.Open(dsn), &gorm.Config{ + Logger: ormLogger, + CreateBatchSize: 100, + }) + if err != nil { + log.Error("fail to connect db", + zap.String("host", cfg.Address), + zap.String("database", cfg.DBName), + zap.Error(err)) + return nil, err + } + + idb, err := db.DB() + if err != nil { + log.Error("fail to create db instance", + zap.String("host", cfg.Address), + zap.String("database", cfg.DBName), + zap.Error(err)) + return nil, err + } + idb.SetMaxIdleConns(cfg.MaxIdleConns) + idb.SetMaxOpenConns(cfg.MaxOpenConns) + + globalDB = db + + log.Info("db connected success", + zap.String("host", cfg.Address), + zap.String("database", cfg.DBName), + zap.Error(err)) + + return db, nil +} + +// SetGlobalDB Only for test +func SetGlobalDB(db *gorm.DB) { + globalDB = db +} + +type ctxTransactionKey struct{} + +func CtxWithTransaction(ctx context.Context, tx *gorm.DB) context.Context { + if ctx == nil { + ctx = context.Background() + } + return context.WithValue(ctx, ctxTransactionKey{}, tx) +} + +type txImpl struct{} + +func NewTxImpl() *txImpl { + return &txImpl{} +} + +func (*txImpl) Transaction(ctx context.Context, fn func(txctx context.Context) error) error { + db := globalDB.WithContext(ctx) + + return db.Transaction(func(tx *gorm.DB) error { + txCtx := CtxWithTransaction(ctx, tx) + return fn(txCtx) + }) +} + +func GetDB(ctx context.Context) *gorm.DB { + iface := ctx.Value(ctxTransactionKey{}) + + if iface != nil { + tx, ok := iface.(*gorm.DB) + if !ok { + log.Error("unexpect context value type", zap.Any("type", reflect.TypeOf(tx))) + return nil + } + + return tx + } + + return globalDB.WithContext(ctx) +} + +func ConfigDatabaseForTesting() *gorm.DB { + db, err := gorm.Open(sqlite.Open(":memory:"), &gorm.Config{ + Logger: logger.Default.LogMode(logger.Info), + }) + if err != nil { + panic("failed to connect database") + } + SetGlobalDB(db) + // Setup tenant related tables + db.Migrator().DropTable(&dbmodel.Tenant{}) + db.Migrator().CreateTable(&dbmodel.Tenant{}) + db.Model(&dbmodel.Tenant{}).Create(&dbmodel.Tenant{ + ID: common.DefaultTenant, + }) + + // Setup database related tables + db.Migrator().DropTable(&dbmodel.Database{}) + db.Migrator().CreateTable(&dbmodel.Database{}) + + db.Model(&dbmodel.Database{}).Create(&dbmodel.Database{ + ID: types.NilUniqueID().String(), + Name: common.DefaultDatabase, + TenantID: common.DefaultTenant, + }) + + // Setup collection related tables + db.Migrator().DropTable(&dbmodel.Collection{}) + db.Migrator().DropTable(&dbmodel.CollectionMetadata{}) + db.Migrator().CreateTable(&dbmodel.Collection{}) + db.Migrator().CreateTable(&dbmodel.CollectionMetadata{}) + + // Setup segment related tables + db.Migrator().DropTable(&dbmodel.Segment{}) + db.Migrator().DropTable(&dbmodel.SegmentMetadata{}) + db.Migrator().CreateTable(&dbmodel.Segment{}) + db.Migrator().CreateTable(&dbmodel.SegmentMetadata{}) + + // Setup notification related tables + db.Migrator().DropTable(&dbmodel.Notification{}) + db.Migrator().CreateTable(&dbmodel.Notification{}) + return db +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/collection.go b/go/coordinator/internal/metastore/db/dbmodel/collection.go new file mode 100644 index 0000000000000000000000000000000000000000..46f00474d4e187dfa1bc97a95f69bb4ae61c3b0a --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/collection.go @@ -0,0 +1,39 @@ +package dbmodel + +import ( + "time" + + "github.com/chroma/chroma-coordinator/internal/types" +) + +type Collection struct { + ID string `gorm:"id;primaryKey"` + Name *string `gorm:"name;unique"` + Topic *string `gorm:"topic"` + Dimension *int32 `gorm:"dimension"` + DatabaseID string `gorm:"database_id"` + Ts types.Timestamp `gorm:"ts;type:bigint;default:0"` + IsDeleted bool `gorm:"is_deleted;type:bool;default:false"` + CreatedAt time.Time `gorm:"created_at;type:timestamp;not null;default:current_timestamp"` + UpdatedAt time.Time `gorm:"updated_at;type:timestamp;not null;default:current_timestamp"` +} + +func (v Collection) TableName() string { + return "collections" +} + +type CollectionAndMetadata struct { + Collection *Collection + CollectionMetadata []*CollectionMetadata + TenantID string + DatabaseName string +} + +//go:generate mockery --name=ICollectionDb +type ICollectionDb interface { + GetCollections(collectionID *string, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*CollectionAndMetadata, error) + DeleteCollectionByID(collectionID string) error + Insert(in *Collection) error + Update(in *Collection) error + DeleteAll() error +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/collection_metadata.go b/go/coordinator/internal/metastore/db/dbmodel/collection_metadata.go new file mode 100644 index 0000000000000000000000000000000000000000..29303453c5da8c3a1c90c100ad8e30de3c52b43c --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/collection_metadata.go @@ -0,0 +1,29 @@ +package dbmodel + +import ( + "time" + + "github.com/chroma/chroma-coordinator/internal/types" +) + +type CollectionMetadata struct { + CollectionID string `gorm:"collection_id;primaryKey"` + Key *string `gorm:"key;primaryKey"` + StrValue *string `gorm:"str_value"` + IntValue *int64 `gorm:"int_value"` + FloatValue *float64 `gorm:"float_value"` + Ts types.Timestamp `gorm:"ts;type:bigint;default:0"` + CreatedAt time.Time `gorm:"created_at;type:timestamp;not null;default:current_timestamp"` + UpdatedAt time.Time `gorm:"updated_at;type:timestamp;not null;default:current_timestamp"` +} + +func (v CollectionMetadata) TableName() string { + return "collection_metadata" +} + +//go:generate mockery --name=ICollectionMetadataDb +type ICollectionMetadataDb interface { + DeleteByCollectionID(collectionID string) error + Insert(in []*CollectionMetadata) error + DeleteAll() error +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/common.go b/go/coordinator/internal/metastore/db/dbmodel/common.go new file mode 100644 index 0000000000000000000000000000000000000000..d188193ae1846b36adee091ff0fd3248c952581a --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/common.go @@ -0,0 +1,23 @@ +package dbmodel + +import ( + "context" + + _ "ariga.io/atlas-provider-gorm/gormschema" +) + +//go:generate mockery --name=IMetaDomain +type IMetaDomain interface { + DatabaseDb(ctx context.Context) IDatabaseDb + TenantDb(ctx context.Context) ITenantDb + CollectionDb(ctx context.Context) ICollectionDb + CollectionMetadataDb(ctx context.Context) ICollectionMetadataDb + SegmentDb(ctx context.Context) ISegmentDb + SegmentMetadataDb(ctx context.Context) ISegmentMetadataDb + NotificationDb(ctx context.Context) INotificationDb +} + +//go:generate mockery --name=ITransaction +type ITransaction interface { + Transaction(ctx context.Context, fn func(txCtx context.Context) error) error +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/database.go b/go/coordinator/internal/metastore/db/dbmodel/database.go new file mode 100644 index 0000000000000000000000000000000000000000..6cac848b4236ada52e13ccbf093aab0cecba9b2d --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/database.go @@ -0,0 +1,29 @@ +package dbmodel + +import ( + "time" + + "github.com/chroma/chroma-coordinator/internal/types" +) + +type Database struct { + ID string `gorm:"id;primaryKey;unique"` + Name string `gorm:"name;type:varchar(128);not_null;uniqueIndex:idx_tenantid_name"` + TenantID string `gorm:"tenant_id;type:varchar(128);not_null;uniqueIndex:idx_tenantid_name"` + Ts types.Timestamp `gorm:"ts;type:bigint;default:0"` + IsDeleted bool `gorm:"is_deleted;type:bool;default:false"` + CreatedAt time.Time `gorm:"created_at;type:timestamp;not null;default:current_timestamp"` + UpdatedAt time.Time `gorm:"updated_at;type:timestamp;not null;default:current_timestamp"` +} + +func (v Database) TableName() string { + return "databases" +} + +//go:generate mockery --name=IDatabaseDb +type IDatabaseDb interface { + GetAllDatabases() ([]*Database, error) + GetDatabases(tenantID string, databaseName string) ([]*Database, error) + Insert(in *Database) error + DeleteAll() error +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/ICollectionDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/ICollectionDb.go new file mode 100644 index 0000000000000000000000000000000000000000..109db42818bcaef88a8e57489d1f2b4c05f3c7b7 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/ICollectionDb.go @@ -0,0 +1,109 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// ICollectionDb is an autogenerated mock type for the ICollectionDb type +type ICollectionDb struct { + mock.Mock +} + +// DeleteAll provides a mock function with given fields: +func (_m *ICollectionDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteCollectionByID provides a mock function with given fields: collectionID +func (_m *ICollectionDb) DeleteCollectionByID(collectionID string) error { + ret := _m.Called(collectionID) + + var r0 error + if rf, ok := ret.Get(0).(func(string) error); ok { + r0 = rf(collectionID) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// GetCollections provides a mock function with given fields: collectionID, collectionName, collectionTopic, tenantID, databaseName +func (_m *ICollectionDb) GetCollections(collectionID *string, collectionName *string, collectionTopic *string, tenantID string, databaseName string) ([]*dbmodel.CollectionAndMetadata, error) { + ret := _m.Called(collectionID, collectionName, collectionTopic, tenantID, databaseName) + + var r0 []*dbmodel.CollectionAndMetadata + var r1 error + if rf, ok := ret.Get(0).(func(*string, *string, *string, string, string) ([]*dbmodel.CollectionAndMetadata, error)); ok { + return rf(collectionID, collectionName, collectionTopic, tenantID, databaseName) + } + if rf, ok := ret.Get(0).(func(*string, *string, *string, string, string) []*dbmodel.CollectionAndMetadata); ok { + r0 = rf(collectionID, collectionName, collectionTopic, tenantID, databaseName) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.CollectionAndMetadata) + } + } + + if rf, ok := ret.Get(1).(func(*string, *string, *string, string, string) error); ok { + r1 = rf(collectionID, collectionName, collectionTopic, tenantID, databaseName) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// Insert provides a mock function with given fields: in +func (_m *ICollectionDb) Insert(in *dbmodel.Collection) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.Collection) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// Update provides a mock function with given fields: in +func (_m *ICollectionDb) Update(in *dbmodel.Collection) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.Collection) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewICollectionDb creates a new instance of ICollectionDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewICollectionDb(t interface { + mock.TestingT + Cleanup(func()) +}) *ICollectionDb { + mock := &ICollectionDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/ICollectionMetadataDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/ICollectionMetadataDb.go new file mode 100644 index 0000000000000000000000000000000000000000..87d71909b064a8288ea9d3628d50f634797b3ded --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/ICollectionMetadataDb.go @@ -0,0 +1,69 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// ICollectionMetadataDb is an autogenerated mock type for the ICollectionMetadataDb type +type ICollectionMetadataDb struct { + mock.Mock +} + +// DeleteAll provides a mock function with given fields: +func (_m *ICollectionMetadataDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteByCollectionID provides a mock function with given fields: collectionID +func (_m *ICollectionMetadataDb) DeleteByCollectionID(collectionID string) error { + ret := _m.Called(collectionID) + + var r0 error + if rf, ok := ret.Get(0).(func(string) error); ok { + r0 = rf(collectionID) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// Insert provides a mock function with given fields: in +func (_m *ICollectionMetadataDb) Insert(in []*dbmodel.CollectionMetadata) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func([]*dbmodel.CollectionMetadata) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewICollectionMetadataDb creates a new instance of ICollectionMetadataDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewICollectionMetadataDb(t interface { + mock.TestingT + Cleanup(func()) +}) *ICollectionMetadataDb { + mock := &ICollectionMetadataDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/IDatabaseDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/IDatabaseDb.go new file mode 100644 index 0000000000000000000000000000000000000000..4bb8c5fa50c20808e1438213d4f9277dd37db138 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/IDatabaseDb.go @@ -0,0 +1,107 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// IDatabaseDb is an autogenerated mock type for the IDatabaseDb type +type IDatabaseDb struct { + mock.Mock +} + +// DeleteAll provides a mock function with given fields: +func (_m *IDatabaseDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// GetAllDatabases provides a mock function with given fields: +func (_m *IDatabaseDb) GetAllDatabases() ([]*dbmodel.Database, error) { + ret := _m.Called() + + var r0 []*dbmodel.Database + var r1 error + if rf, ok := ret.Get(0).(func() ([]*dbmodel.Database, error)); ok { + return rf() + } + if rf, ok := ret.Get(0).(func() []*dbmodel.Database); ok { + r0 = rf() + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.Database) + } + } + + if rf, ok := ret.Get(1).(func() error); ok { + r1 = rf() + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// GetDatabases provides a mock function with given fields: tenantID, databaseName +func (_m *IDatabaseDb) GetDatabases(tenantID string, databaseName string) ([]*dbmodel.Database, error) { + ret := _m.Called(tenantID, databaseName) + + var r0 []*dbmodel.Database + var r1 error + if rf, ok := ret.Get(0).(func(string, string) ([]*dbmodel.Database, error)); ok { + return rf(tenantID, databaseName) + } + if rf, ok := ret.Get(0).(func(string, string) []*dbmodel.Database); ok { + r0 = rf(tenantID, databaseName) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.Database) + } + } + + if rf, ok := ret.Get(1).(func(string, string) error); ok { + r1 = rf(tenantID, databaseName) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// Insert provides a mock function with given fields: in +func (_m *IDatabaseDb) Insert(in *dbmodel.Database) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.Database) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewIDatabaseDb creates a new instance of IDatabaseDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewIDatabaseDb(t interface { + mock.TestingT + Cleanup(func()) +}) *IDatabaseDb { + mock := &IDatabaseDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/IMetaDomain.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/IMetaDomain.go new file mode 100644 index 0000000000000000000000000000000000000000..0ee94c373e94182d49f58e2af965e7d1aa5f4466 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/IMetaDomain.go @@ -0,0 +1,141 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + context "context" + + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// IMetaDomain is an autogenerated mock type for the IMetaDomain type +type IMetaDomain struct { + mock.Mock +} + +// CollectionDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) CollectionDb(ctx context.Context) dbmodel.ICollectionDb { + ret := _m.Called(ctx) + + var r0 dbmodel.ICollectionDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.ICollectionDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.ICollectionDb) + } + } + + return r0 +} + +// CollectionMetadataDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) CollectionMetadataDb(ctx context.Context) dbmodel.ICollectionMetadataDb { + ret := _m.Called(ctx) + + var r0 dbmodel.ICollectionMetadataDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.ICollectionMetadataDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.ICollectionMetadataDb) + } + } + + return r0 +} + +// DatabaseDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) DatabaseDb(ctx context.Context) dbmodel.IDatabaseDb { + ret := _m.Called(ctx) + + var r0 dbmodel.IDatabaseDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.IDatabaseDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.IDatabaseDb) + } + } + + return r0 +} + +// NotificationDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) NotificationDb(ctx context.Context) dbmodel.INotificationDb { + ret := _m.Called(ctx) + + var r0 dbmodel.INotificationDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.INotificationDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.INotificationDb) + } + } + + return r0 +} + +// SegmentDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) SegmentDb(ctx context.Context) dbmodel.ISegmentDb { + ret := _m.Called(ctx) + + var r0 dbmodel.ISegmentDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.ISegmentDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.ISegmentDb) + } + } + + return r0 +} + +// SegmentMetadataDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) SegmentMetadataDb(ctx context.Context) dbmodel.ISegmentMetadataDb { + ret := _m.Called(ctx) + + var r0 dbmodel.ISegmentMetadataDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.ISegmentMetadataDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.ISegmentMetadataDb) + } + } + + return r0 +} + +// TenantDb provides a mock function with given fields: ctx +func (_m *IMetaDomain) TenantDb(ctx context.Context) dbmodel.ITenantDb { + ret := _m.Called(ctx) + + var r0 dbmodel.ITenantDb + if rf, ok := ret.Get(0).(func(context.Context) dbmodel.ITenantDb); ok { + r0 = rf(ctx) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(dbmodel.ITenantDb) + } + } + + return r0 +} + +// NewIMetaDomain creates a new instance of IMetaDomain. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewIMetaDomain(t interface { + mock.TestingT + Cleanup(func()) +}) *IMetaDomain { + mock := &IMetaDomain{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/INotificationDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/INotificationDb.go new file mode 100644 index 0000000000000000000000000000000000000000..b5b9f77b394913b2321e5d5276da54448bcb951e --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/INotificationDb.go @@ -0,0 +1,121 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// INotificationDb is an autogenerated mock type for the INotificationDb type +type INotificationDb struct { + mock.Mock +} + +// Delete provides a mock function with given fields: id +func (_m *INotificationDb) Delete(id []int64) error { + ret := _m.Called(id) + + var r0 error + if rf, ok := ret.Get(0).(func([]int64) error); ok { + r0 = rf(id) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteAll provides a mock function with given fields: +func (_m *INotificationDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// GetAllPendingNotifications provides a mock function with given fields: +func (_m *INotificationDb) GetAllPendingNotifications() ([]*dbmodel.Notification, error) { + ret := _m.Called() + + var r0 []*dbmodel.Notification + var r1 error + if rf, ok := ret.Get(0).(func() ([]*dbmodel.Notification, error)); ok { + return rf() + } + if rf, ok := ret.Get(0).(func() []*dbmodel.Notification); ok { + r0 = rf() + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.Notification) + } + } + + if rf, ok := ret.Get(1).(func() error); ok { + r1 = rf() + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// GetNotificationByCollectionID provides a mock function with given fields: collectionID +func (_m *INotificationDb) GetNotificationByCollectionID(collectionID string) ([]*dbmodel.Notification, error) { + ret := _m.Called(collectionID) + + var r0 []*dbmodel.Notification + var r1 error + if rf, ok := ret.Get(0).(func(string) ([]*dbmodel.Notification, error)); ok { + return rf(collectionID) + } + if rf, ok := ret.Get(0).(func(string) []*dbmodel.Notification); ok { + r0 = rf(collectionID) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.Notification) + } + } + + if rf, ok := ret.Get(1).(func(string) error); ok { + r1 = rf(collectionID) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// Insert provides a mock function with given fields: in +func (_m *INotificationDb) Insert(in *dbmodel.Notification) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.Notification) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewINotificationDb creates a new instance of INotificationDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewINotificationDb(t interface { + mock.TestingT + Cleanup(func()) +}) *INotificationDb { + mock := &INotificationDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/ISegmentDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/ISegmentDb.go new file mode 100644 index 0000000000000000000000000000000000000000..1a519766bbab0772d75461ffa1acb6e00b534877 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/ISegmentDb.go @@ -0,0 +1,111 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" + + types "github.com/chroma/chroma-coordinator/internal/types" +) + +// ISegmentDb is an autogenerated mock type for the ISegmentDb type +type ISegmentDb struct { + mock.Mock +} + +// DeleteAll provides a mock function with given fields: +func (_m *ISegmentDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteSegmentByID provides a mock function with given fields: id +func (_m *ISegmentDb) DeleteSegmentByID(id string) error { + ret := _m.Called(id) + + var r0 error + if rf, ok := ret.Get(0).(func(string) error); ok { + r0 = rf(id) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// GetSegments provides a mock function with given fields: id, segmentType, scope, topic, collectionID +func (_m *ISegmentDb) GetSegments(id types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*dbmodel.SegmentAndMetadata, error) { + ret := _m.Called(id, segmentType, scope, topic, collectionID) + + var r0 []*dbmodel.SegmentAndMetadata + var r1 error + if rf, ok := ret.Get(0).(func(types.UniqueID, *string, *string, *string, types.UniqueID) ([]*dbmodel.SegmentAndMetadata, error)); ok { + return rf(id, segmentType, scope, topic, collectionID) + } + if rf, ok := ret.Get(0).(func(types.UniqueID, *string, *string, *string, types.UniqueID) []*dbmodel.SegmentAndMetadata); ok { + r0 = rf(id, segmentType, scope, topic, collectionID) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.SegmentAndMetadata) + } + } + + if rf, ok := ret.Get(1).(func(types.UniqueID, *string, *string, *string, types.UniqueID) error); ok { + r1 = rf(id, segmentType, scope, topic, collectionID) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// Insert provides a mock function with given fields: _a0 +func (_m *ISegmentDb) Insert(_a0 *dbmodel.Segment) error { + ret := _m.Called(_a0) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.Segment) error); ok { + r0 = rf(_a0) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// Update provides a mock function with given fields: _a0 +func (_m *ISegmentDb) Update(_a0 *dbmodel.UpdateSegment) error { + ret := _m.Called(_a0) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.UpdateSegment) error); ok { + r0 = rf(_a0) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewISegmentDb creates a new instance of ISegmentDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewISegmentDb(t interface { + mock.TestingT + Cleanup(func()) +}) *ISegmentDb { + mock := &ISegmentDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/ISegmentMetadataDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/ISegmentMetadataDb.go new file mode 100644 index 0000000000000000000000000000000000000000..24c56b6d8351e85f7ba0bc6c63646b2ed61aaa97 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/ISegmentMetadataDb.go @@ -0,0 +1,83 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// ISegmentMetadataDb is an autogenerated mock type for the ISegmentMetadataDb type +type ISegmentMetadataDb struct { + mock.Mock +} + +// DeleteAll provides a mock function with given fields: +func (_m *ISegmentMetadataDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteBySegmentID provides a mock function with given fields: segmentID +func (_m *ISegmentMetadataDb) DeleteBySegmentID(segmentID string) error { + ret := _m.Called(segmentID) + + var r0 error + if rf, ok := ret.Get(0).(func(string) error); ok { + r0 = rf(segmentID) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteBySegmentIDAndKeys provides a mock function with given fields: segmentID, keys +func (_m *ISegmentMetadataDb) DeleteBySegmentIDAndKeys(segmentID string, keys []string) error { + ret := _m.Called(segmentID, keys) + + var r0 error + if rf, ok := ret.Get(0).(func(string, []string) error); ok { + r0 = rf(segmentID, keys) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// Insert provides a mock function with given fields: in +func (_m *ISegmentMetadataDb) Insert(in []*dbmodel.SegmentMetadata) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func([]*dbmodel.SegmentMetadata) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewISegmentMetadataDb creates a new instance of ISegmentMetadataDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewISegmentMetadataDb(t interface { + mock.TestingT + Cleanup(func()) +}) *ISegmentMetadataDb { + mock := &ISegmentMetadataDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/ITenantDb.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/ITenantDb.go new file mode 100644 index 0000000000000000000000000000000000000000..fe54c815037afedf21d1221d693080620d303b3f --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/ITenantDb.go @@ -0,0 +1,107 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + dbmodel "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + mock "github.com/stretchr/testify/mock" +) + +// ITenantDb is an autogenerated mock type for the ITenantDb type +type ITenantDb struct { + mock.Mock +} + +// DeleteAll provides a mock function with given fields: +func (_m *ITenantDb) DeleteAll() error { + ret := _m.Called() + + var r0 error + if rf, ok := ret.Get(0).(func() error); ok { + r0 = rf() + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// GetAllTenants provides a mock function with given fields: +func (_m *ITenantDb) GetAllTenants() ([]*dbmodel.Tenant, error) { + ret := _m.Called() + + var r0 []*dbmodel.Tenant + var r1 error + if rf, ok := ret.Get(0).(func() ([]*dbmodel.Tenant, error)); ok { + return rf() + } + if rf, ok := ret.Get(0).(func() []*dbmodel.Tenant); ok { + r0 = rf() + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.Tenant) + } + } + + if rf, ok := ret.Get(1).(func() error); ok { + r1 = rf() + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// GetTenants provides a mock function with given fields: tenantID +func (_m *ITenantDb) GetTenants(tenantID string) ([]*dbmodel.Tenant, error) { + ret := _m.Called(tenantID) + + var r0 []*dbmodel.Tenant + var r1 error + if rf, ok := ret.Get(0).(func(string) ([]*dbmodel.Tenant, error)); ok { + return rf(tenantID) + } + if rf, ok := ret.Get(0).(func(string) []*dbmodel.Tenant); ok { + r0 = rf(tenantID) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*dbmodel.Tenant) + } + } + + if rf, ok := ret.Get(1).(func(string) error); ok { + r1 = rf(tenantID) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// Insert provides a mock function with given fields: in +func (_m *ITenantDb) Insert(in *dbmodel.Tenant) error { + ret := _m.Called(in) + + var r0 error + if rf, ok := ret.Get(0).(func(*dbmodel.Tenant) error); ok { + r0 = rf(in) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewITenantDb creates a new instance of ITenantDb. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewITenantDb(t interface { + mock.TestingT + Cleanup(func()) +}) *ITenantDb { + mock := &ITenantDb{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/mocks/ITransaction.go b/go/coordinator/internal/metastore/db/dbmodel/mocks/ITransaction.go new file mode 100644 index 0000000000000000000000000000000000000000..79c20ef3228273e824371babd145d5191b56a2d5 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/mocks/ITransaction.go @@ -0,0 +1,42 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + context "context" + + mock "github.com/stretchr/testify/mock" +) + +// ITransaction is an autogenerated mock type for the ITransaction type +type ITransaction struct { + mock.Mock +} + +// Transaction provides a mock function with given fields: ctx, fn +func (_m *ITransaction) Transaction(ctx context.Context, fn func(context.Context) error) error { + ret := _m.Called(ctx, fn) + + var r0 error + if rf, ok := ret.Get(0).(func(context.Context, func(context.Context) error) error); ok { + r0 = rf(ctx, fn) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// NewITransaction creates a new instance of ITransaction. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewITransaction(t interface { + mock.TestingT + Cleanup(func()) +}) *ITransaction { + mock := &ITransaction{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/notification.go b/go/coordinator/internal/metastore/db/dbmodel/notification.go new file mode 100644 index 0000000000000000000000000000000000000000..4ce22f2f2e4811f383dc4bf55468b1300d666498 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/notification.go @@ -0,0 +1,26 @@ +package dbmodel + +type Notification struct { + ID int64 `gorm:"id;primaryKey;autoIncrement"` + CollectionID string `gorm:"collection_id"` + Type string `gorm:"notification_type"` + Status string `gorm:"status"` +} + +const ( + NotificationTypeCreateCollection = "create_collection" + NotificationTypeDeleteCollection = "delete_collection" +) + +const ( + NotificationStatusPending = "pending" +) + +//go:generate mockery --name=IOutBoxDb +type INotificationDb interface { + DeleteAll() error + Delete(id []int64) error + Insert(in *Notification) error + GetAllPendingNotifications() ([]*Notification, error) + GetNotificationByCollectionID(collectionID string) ([]*Notification, error) +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/segment.go b/go/coordinator/internal/metastore/db/dbmodel/segment.go new file mode 100644 index 0000000000000000000000000000000000000000..0967436e11e8b17fceeb79d3d00f81d365a19d74 --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/segment.go @@ -0,0 +1,45 @@ +package dbmodel + +import ( + "time" + + "github.com/chroma/chroma-coordinator/internal/types" +) + +type Segment struct { + ID string `gorm:"id;primaryKey"` + Type string `gorm:"type;type:string;not null"` + Scope string `gorm:"scope"` + Topic *string `gorm:"topic"` + Ts types.Timestamp `gorm:"ts;type:bigint;default:0"` + IsDeleted bool `gorm:"is_deleted;type:bool;default:false"` + CreatedAt time.Time `gorm:"created_at;type:timestamp;not null;default:current_timestamp"` + UpdatedAt time.Time `gorm:"updated_at;type:timestamp;not null;default:current_timestamp"` + CollectionID *string `gorm:"collection_id"` +} + +func (s Segment) TableName() string { + return "segments" +} + +type SegmentAndMetadata struct { + Segment *Segment + SegmentMetadata []*SegmentMetadata +} + +type UpdateSegment struct { + ID string + Topic *string + ResetTopic bool + Collection *string + ResetCollection bool +} + +//go:generate mockery --name=ISegmentDb +type ISegmentDb interface { + GetSegments(id types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) ([]*SegmentAndMetadata, error) + DeleteSegmentByID(id string) error + Insert(*Segment) error + Update(*UpdateSegment) error + DeleteAll() error +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/segment_metadata.go b/go/coordinator/internal/metastore/db/dbmodel/segment_metadata.go new file mode 100644 index 0000000000000000000000000000000000000000..bbd11eaa39bf78bed3ff77d16a66a0aba939be3e --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/segment_metadata.go @@ -0,0 +1,30 @@ +package dbmodel + +import ( + "time" + + "github.com/chroma/chroma-coordinator/internal/types" +) + +type SegmentMetadata struct { + SegmentID string `gorm:"segment_id;primaryKey"` + Key *string `gorm:"key;primaryKey"` + StrValue *string `gorm:"str_value"` + IntValue *int64 `gorm:"int_value"` + FloatValue *float64 `gorm:"float_value"` + Ts types.Timestamp `gorm:"ts;type:bigint;default:0"` + CreatedAt time.Time `gorm:"created_at;type:timestamp;not null;default:current_timestamp"` + UpdatedAt time.Time `gorm:"updated_at;type:timestamp;not null;default:current_timestamp"` +} + +func (SegmentMetadata) TableName() string { + return "segment_metadata" +} + +//go:generate mockery --name=ISegmentMetadataDb +type ISegmentMetadataDb interface { + DeleteBySegmentID(segmentID string) error + DeleteBySegmentIDAndKeys(segmentID string, keys []string) error + Insert(in []*SegmentMetadata) error + DeleteAll() error +} diff --git a/go/coordinator/internal/metastore/db/dbmodel/tenant.go b/go/coordinator/internal/metastore/db/dbmodel/tenant.go new file mode 100644 index 0000000000000000000000000000000000000000..bb15ed5153eff17b18139feeec7c35629d44caaf --- /dev/null +++ b/go/coordinator/internal/metastore/db/dbmodel/tenant.go @@ -0,0 +1,27 @@ +package dbmodel + +import ( + "time" + + "github.com/chroma/chroma-coordinator/internal/types" +) + +type Tenant struct { + ID string `gorm:"id;primaryKey;unique"` + Ts types.Timestamp `gorm:"ts;type:bigint;default:0"` + IsDeleted bool `gorm:"is_deleted;type:bool;default:false"` + CreatedAt time.Time `gorm:"created_at;type:timestamp;not null;default:current_timestamp"` + UpdatedAt time.Time `gorm:"updated_at;type:timestamp;not null;default:current_timestamp"` +} + +func (v Tenant) TableName() string { + return "tenants" +} + +//go:generate mockery --name=ITenantDb +type ITenantDb interface { + GetAllTenants() ([]*Tenant, error) + GetTenants(tenantID string) ([]*Tenant, error) + Insert(in *Tenant) error + DeleteAll() error +} diff --git a/go/coordinator/internal/metastore/mocks/Catalog.go b/go/coordinator/internal/metastore/mocks/Catalog.go new file mode 100644 index 0000000000000000000000000000000000000000..5926bc768f0d13c8e43ab8ce19bd49241a4badba --- /dev/null +++ b/go/coordinator/internal/metastore/mocks/Catalog.go @@ -0,0 +1,204 @@ +// Code generated by mockery v2.33.3. DO NOT EDIT. + +package mocks + +import ( + context "context" + + mock "github.com/stretchr/testify/mock" + + model "github.com/chroma/chroma-coordinator/internal/model" + + types "github.com/chroma/chroma-coordinator/internal/types" +) + +// Catalog is an autogenerated mock type for the Catalog type +type Catalog struct { + mock.Mock +} + +// CreateCollection provides a mock function with given fields: ctx, collectionInfo, ts +func (_m *Catalog) CreateCollection(ctx context.Context, collectionInfo *model.CreateCollection, ts int64) (*model.Collection, error) { + ret := _m.Called(ctx, collectionInfo, ts) + + var r0 *model.Collection + var r1 error + if rf, ok := ret.Get(0).(func(context.Context, *model.CreateCollection, int64) (*model.Collection, error)); ok { + return rf(ctx, collectionInfo, ts) + } + if rf, ok := ret.Get(0).(func(context.Context, *model.CreateCollection, int64) *model.Collection); ok { + r0 = rf(ctx, collectionInfo, ts) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(*model.Collection) + } + } + + if rf, ok := ret.Get(1).(func(context.Context, *model.CreateCollection, int64) error); ok { + r1 = rf(ctx, collectionInfo, ts) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// CreateSegment provides a mock function with given fields: ctx, segmentInfo, ts +func (_m *Catalog) CreateSegment(ctx context.Context, segmentInfo *model.CreateSegment, ts int64) (*model.Segment, error) { + ret := _m.Called(ctx, segmentInfo, ts) + + var r0 *model.Segment + var r1 error + if rf, ok := ret.Get(0).(func(context.Context, *model.CreateSegment, int64) (*model.Segment, error)); ok { + return rf(ctx, segmentInfo, ts) + } + if rf, ok := ret.Get(0).(func(context.Context, *model.CreateSegment, int64) *model.Segment); ok { + r0 = rf(ctx, segmentInfo, ts) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(*model.Segment) + } + } + + if rf, ok := ret.Get(1).(func(context.Context, *model.CreateSegment, int64) error); ok { + r1 = rf(ctx, segmentInfo, ts) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// DeleteCollection provides a mock function with given fields: ctx, collectionID +func (_m *Catalog) DeleteCollection(ctx context.Context, collectionID types.UniqueID) error { + ret := _m.Called(ctx, collectionID) + + var r0 error + if rf, ok := ret.Get(0).(func(context.Context, types.UniqueID) error); ok { + r0 = rf(ctx, collectionID) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// DeleteSegment provides a mock function with given fields: ctx, segmentID +func (_m *Catalog) DeleteSegment(ctx context.Context, segmentID types.UniqueID) error { + ret := _m.Called(ctx, segmentID) + + var r0 error + if rf, ok := ret.Get(0).(func(context.Context, types.UniqueID) error); ok { + r0 = rf(ctx, segmentID) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// GetCollections provides a mock function with given fields: ctx, collectionID, collectionName, collectionTopic +func (_m *Catalog) GetCollections(ctx context.Context, collectionID types.UniqueID, collectionName *string, collectionTopic *string) ([]*model.Collection, error) { + ret := _m.Called(ctx, collectionID, collectionName, collectionTopic) + + var r0 []*model.Collection + var r1 error + if rf, ok := ret.Get(0).(func(context.Context, types.UniqueID, *string, *string) ([]*model.Collection, error)); ok { + return rf(ctx, collectionID, collectionName, collectionTopic) + } + if rf, ok := ret.Get(0).(func(context.Context, types.UniqueID, *string, *string) []*model.Collection); ok { + r0 = rf(ctx, collectionID, collectionName, collectionTopic) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*model.Collection) + } + } + + if rf, ok := ret.Get(1).(func(context.Context, types.UniqueID, *string, *string) error); ok { + r1 = rf(ctx, collectionID, collectionName, collectionTopic) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// GetSegments provides a mock function with given fields: ctx, segmentID, segmentType, scope, topic, collectionID, ts +func (_m *Catalog) GetSegments(ctx context.Context, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID, ts int64) ([]*model.Segment, error) { + ret := _m.Called(ctx, segmentID, segmentType, scope, topic, collectionID, ts) + + var r0 []*model.Segment + var r1 error + if rf, ok := ret.Get(0).(func(context.Context, types.UniqueID, *string, *string, *string, types.UniqueID, int64) ([]*model.Segment, error)); ok { + return rf(ctx, segmentID, segmentType, scope, topic, collectionID, ts) + } + if rf, ok := ret.Get(0).(func(context.Context, types.UniqueID, *string, *string, *string, types.UniqueID, int64) []*model.Segment); ok { + r0 = rf(ctx, segmentID, segmentType, scope, topic, collectionID, ts) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).([]*model.Segment) + } + } + + if rf, ok := ret.Get(1).(func(context.Context, types.UniqueID, *string, *string, *string, types.UniqueID, int64) error); ok { + r1 = rf(ctx, segmentID, segmentType, scope, topic, collectionID, ts) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// ResetState provides a mock function with given fields: ctx +func (_m *Catalog) ResetState(ctx context.Context) error { + ret := _m.Called(ctx) + + var r0 error + if rf, ok := ret.Get(0).(func(context.Context) error); ok { + r0 = rf(ctx) + } else { + r0 = ret.Error(0) + } + + return r0 +} + +// UpdateCollection provides a mock function with given fields: ctx, collectionInfo, ts +func (_m *Catalog) UpdateCollection(ctx context.Context, collectionInfo *model.UpdateCollection, ts int64) (*model.Collection, error) { + ret := _m.Called(ctx, collectionInfo, ts) + + var r0 *model.Collection + var r1 error + if rf, ok := ret.Get(0).(func(context.Context, *model.UpdateCollection, int64) (*model.Collection, error)); ok { + return rf(ctx, collectionInfo, ts) + } + if rf, ok := ret.Get(0).(func(context.Context, *model.UpdateCollection, int64) *model.Collection); ok { + r0 = rf(ctx, collectionInfo, ts) + } else { + if ret.Get(0) != nil { + r0 = ret.Get(0).(*model.Collection) + } + } + + if rf, ok := ret.Get(1).(func(context.Context, *model.UpdateCollection, int64) error); ok { + r1 = rf(ctx, collectionInfo, ts) + } else { + r1 = ret.Error(1) + } + + return r0, r1 +} + +// NewCatalog creates a new instance of Catalog. It also registers a testing interface on the mock and a cleanup function to assert the mocks expectations. +// The first argument is typically a *testing.T value. +func NewCatalog(t interface { + mock.TestingT + Cleanup(func()) +}) *Catalog { + mock := &Catalog{} + mock.Mock.Test(t) + + t.Cleanup(func() { mock.AssertExpectations(t) }) + + return mock +} diff --git a/go/coordinator/internal/model/collection.go b/go/coordinator/internal/model/collection.go new file mode 100644 index 0000000000000000000000000000000000000000..6e242b7fc67d65d4b40330f06fba5e2b8c431960 --- /dev/null +++ b/go/coordinator/internal/model/collection.go @@ -0,0 +1,61 @@ +package model + +import ( + "github.com/chroma/chroma-coordinator/internal/types" +) + +type Collection struct { + ID types.UniqueID + Name string + Topic string + Dimension *int32 + Metadata *CollectionMetadata[CollectionMetadataValueType] + Created bool + TenantID string + DatabaseName string + Ts types.Timestamp +} + +type CreateCollection struct { + ID types.UniqueID + Name string + Topic string + Dimension *int32 + Metadata *CollectionMetadata[CollectionMetadataValueType] + GetOrCreate bool + TenantID string + DatabaseName string + Ts types.Timestamp +} + +type DeleteCollection struct { + ID types.UniqueID + TenantID string + DatabaseName string + Ts types.Timestamp +} + +type UpdateCollection struct { + ID types.UniqueID + Name *string + Topic *string + Dimension *int32 + Metadata *CollectionMetadata[CollectionMetadataValueType] + ResetMetadata bool + TenantID string + DatabaseName string + Ts types.Timestamp +} + +func FilterCollection(collection *Collection, collectionID types.UniqueID, collectionName *string, collectionTopic *string) bool { + if collectionID != types.NilUniqueID() && collectionID != collection.ID { + return false + } + if collectionName != nil && *collectionName != collection.Name { + return false + } + if collectionTopic != nil && *collectionTopic != collection.Topic { + return false + } + return true +} diff --git a/go/coordinator/internal/model/collection_metadata.go b/go/coordinator/internal/model/collection_metadata.go new file mode 100644 index 0000000000000000000000000000000000000000..9e22d5f276a97fcbd5b9b332e7278908245fbe61 --- /dev/null +++ b/go/coordinator/internal/model/collection_metadata.go @@ -0,0 +1,92 @@ +package model + +type CollectionMetadataValueType interface { + IsCollectionMetadataValueType() + Equals(other CollectionMetadataValueType) bool +} + +type CollectionMetadataValueStringType struct { + Value string +} + +func (s *CollectionMetadataValueStringType) IsCollectionMetadataValueType() {} + +func (s *CollectionMetadataValueStringType) Equals(other CollectionMetadataValueType) bool { + if o, ok := other.(*CollectionMetadataValueStringType); ok { + return s.Value == o.Value + } + return false +} + +type CollectionMetadataValueInt64Type struct { + Value int64 +} + +func (s *CollectionMetadataValueInt64Type) IsCollectionMetadataValueType() {} + +func (s *CollectionMetadataValueInt64Type) Equals(other CollectionMetadataValueType) bool { + if o, ok := other.(*CollectionMetadataValueInt64Type); ok { + return s.Value == o.Value + } + return false +} + +type CollectionMetadataValueFloat64Type struct { + Value float64 +} + +func (s *CollectionMetadataValueFloat64Type) IsCollectionMetadataValueType() {} + +func (s *CollectionMetadataValueFloat64Type) Equals(other CollectionMetadataValueType) bool { + if o, ok := other.(*CollectionMetadataValueFloat64Type); ok { + return s.Value == o.Value + } + return false +} + +type CollectionMetadata[T CollectionMetadataValueType] struct { + Metadata map[string]T +} + +func NewCollectionMetadata[T CollectionMetadataValueType]() *CollectionMetadata[T] { + return &CollectionMetadata[T]{ + Metadata: make(map[string]T), + } +} + +func (m *CollectionMetadata[T]) Add(key string, value T) { + m.Metadata[key] = value +} + +func (m *CollectionMetadata[T]) Get(key string) T { + return m.Metadata[key] +} + +func (m *CollectionMetadata[T]) Remove(key string) { + delete(m.Metadata, key) +} + +func (m *CollectionMetadata[T]) Empty() bool { + return len(m.Metadata) == 0 +} + +func (m *CollectionMetadata[T]) Equals(other *CollectionMetadata[T]) bool { + if m == nil && other == nil { + return true + } + if m == nil && other != nil { + return false + } + if m != nil && other == nil { + return false + } + if len(m.Metadata) != len(other.Metadata) { + return false + } + for key, value := range m.Metadata { + if otherValue, ok := other.Metadata[key]; !ok || !value.Equals(otherValue) { + return false + } + } + return true +} diff --git a/go/coordinator/internal/model/database.go b/go/coordinator/internal/model/database.go new file mode 100644 index 0000000000000000000000000000000000000000..ad23e3f14c6c530654e6bbf7353304580ad40061 --- /dev/null +++ b/go/coordinator/internal/model/database.go @@ -0,0 +1,24 @@ +package model + +import "github.com/chroma/chroma-coordinator/internal/types" + +type Database struct { + ID string + Name string + Tenant string + Ts types.Timestamp +} + +type CreateDatabase struct { + ID string + Name string + Tenant string + Ts types.Timestamp +} + +type GetDatabase struct { + ID string + Name string + Tenant string + Ts types.Timestamp +} diff --git a/go/coordinator/internal/model/notification.go b/go/coordinator/internal/model/notification.go new file mode 100644 index 0000000000000000000000000000000000000000..ac50c44fa358fca7a98b5008dabda462b82be1d6 --- /dev/null +++ b/go/coordinator/internal/model/notification.go @@ -0,0 +1,17 @@ +package model + +const ( + NotificationTypeCreateCollection = "create_collection" + NotificationTypeDeleteCollection = "delete_collection" +) + +const ( + NotificationStatusPending = "pending" +) + +type Notification struct { + ID int64 + CollectionID string + Type string + Status string +} diff --git a/go/coordinator/internal/model/segment.go b/go/coordinator/internal/model/segment.go new file mode 100644 index 0000000000000000000000000000000000000000..8fa93f10cca651b4f0112ab92ad8f5c4d2913f19 --- /dev/null +++ b/go/coordinator/internal/model/segment.go @@ -0,0 +1,66 @@ +package model + +import ( + "github.com/chroma/chroma-coordinator/internal/types" +) + +type Segment struct { + ID types.UniqueID + Type string + Scope string + Topic *string + CollectionID types.UniqueID + Metadata *SegmentMetadata[SegmentMetadataValueType] + Ts types.Timestamp +} + +type CreateSegment struct { + ID types.UniqueID + Type string + Scope string + Topic *string + CollectionID types.UniqueID + Metadata *SegmentMetadata[SegmentMetadataValueType] + Ts types.Timestamp +} + +type UpdateSegment struct { + ID types.UniqueID + Topic *string + ResetTopic bool + Collection *string + ResetCollection bool + Metadata *SegmentMetadata[SegmentMetadataValueType] + ResetMetadata bool + Ts types.Timestamp +} + +type GetSegments struct { + ID types.UniqueID + Type *string + Scope *string + Topic *string + CollectionID types.UniqueID +} + +func FilterSegments(segment *Segment, segmentID types.UniqueID, segmentType *string, scope *string, topic *string, collectionID types.UniqueID) bool { + if segmentID != types.NilUniqueID() && segment.ID != segmentID { + return false + } + if segmentType != nil && segment.Type != *segmentType { + return false + } + + if scope != nil && segment.Scope != *scope { + return false + } + + if topic != nil && *segment.Topic != *topic { + return false + } + + if collectionID != types.NilUniqueID() && segment.CollectionID != collectionID { + return false + } + return true +} diff --git a/go/coordinator/internal/model/segment_metadata.go b/go/coordinator/internal/model/segment_metadata.go new file mode 100644 index 0000000000000000000000000000000000000000..eda7497063d675a67d83debb82aa248267c7a813 --- /dev/null +++ b/go/coordinator/internal/model/segment_metadata.go @@ -0,0 +1,57 @@ +package model + +type SegmentMetadataValueType interface { + IsSegmentMetadataValueType() +} + +type SegmentMetadataValueStringType struct { + Value string +} + +func (s *SegmentMetadataValueStringType) IsSegmentMetadataValueType() {} + +type SegmentMetadataValueInt64Type struct { + Value int64 +} + +func (s *SegmentMetadataValueInt64Type) IsSegmentMetadataValueType() {} + +type SegmentMetadataValueFloat64Type struct { + Value float64 +} + +func (s *SegmentMetadataValueFloat64Type) IsSegmentMetadataValueType() {} + +type SegmentMetadata[T SegmentMetadataValueType] struct { + Metadata map[string]T +} + +func NewSegmentMetadata[T SegmentMetadataValueType]() *SegmentMetadata[T] { + return &SegmentMetadata[T]{ + Metadata: make(map[string]T), + } +} + +func (m *SegmentMetadata[T]) Set(key string, value T) { + m.Metadata[key] = value +} + +func (m *SegmentMetadata[T]) Get(key string) T { + return m.Metadata[key] +} + +func (m *SegmentMetadata[T]) Remove(key string) { + delete(m.Metadata, key) +} + +func (m *SegmentMetadata[T]) Keys() []string { + keys := make([]string, 0, len(m.Metadata)) + for k := range m.Metadata { + keys = append(keys, k) + } + return keys +} + +func (m *SegmentMetadata[T]) Empty() bool { + return len(m.Metadata) == 0 +} diff --git a/go/coordinator/internal/model/tenant.go b/go/coordinator/internal/model/tenant.go new file mode 100644 index 0000000000000000000000000000000000000000..191d781d00a33d6f0e182a415250c72a258b268e --- /dev/null +++ b/go/coordinator/internal/model/tenant.go @@ -0,0 +1,17 @@ +package model + +import "github.com/chroma/chroma-coordinator/internal/types" + +type Tenant struct { + Name string +} + +type CreateTenant struct { + Name string + Ts types.Timestamp +} + +type GetTenant struct { + Name string + Ts types.Timestamp +} diff --git a/go/coordinator/internal/notification/database_notification_store.go b/go/coordinator/internal/notification/database_notification_store.go new file mode 100644 index 0000000000000000000000000000000000000000..93411ff39738903991a76412d5f9bfc1441ad723 --- /dev/null +++ b/go/coordinator/internal/notification/database_notification_store.go @@ -0,0 +1,95 @@ +package notification + +import ( + "context" + "sort" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/model" +) + +type DatabaseNotificationStore struct { + metaDomain dbmodel.IMetaDomain + txImpl dbmodel.ITransaction +} + +var _ NotificationStore = &DatabaseNotificationStore{} + +func NewDatabaseNotificationStore(txImpl dbmodel.ITransaction, metaDomain dbmodel.IMetaDomain) *DatabaseNotificationStore { + return &DatabaseNotificationStore{ + metaDomain: metaDomain, + txImpl: txImpl, + } +} + +func (d *DatabaseNotificationStore) GetAllPendingNotifications(ctx context.Context) (map[string][]model.Notification, error) { + notifications, err := d.metaDomain.NotificationDb(ctx).GetAllPendingNotifications() + if err != nil { + return nil, err + } + + notificationMap := make(map[string][]model.Notification) + for _, notification := range notifications { + notificationMap[notification.CollectionID] = append(notificationMap[notification.CollectionID], model.Notification{ + ID: notification.ID, + CollectionID: notification.CollectionID, + Type: notification.Type, + Status: notification.Status, + }) + // sort notifications by ID, this is ok because of the small number of notifications + sort.Slice(notificationMap[notification.CollectionID], func(i, j int) bool { + return notificationMap[notification.CollectionID][i].ID < notificationMap[notification.CollectionID][j].ID + }) + } + return notificationMap, nil +} + +func (d *DatabaseNotificationStore) GetNotifications(ctx context.Context, collectionID string) ([]model.Notification, error) { + notifications, err := d.metaDomain.NotificationDb(ctx).GetNotificationByCollectionID(collectionID) + if err != nil { + return nil, err + } + + var result []model.Notification + for _, notification := range notifications { + result = append(result, model.Notification{ + ID: notification.ID, + CollectionID: notification.CollectionID, + Type: notification.Type, + Status: notification.Status, + }) + } + // sort notifications by ID, this is ok because of the small number of notifications + sort.Slice(result, func(i, j int) bool { + return result[i].ID < result[j].ID + }) + return result, nil +} + +func (d *DatabaseNotificationStore) AddNotification(ctx context.Context, notification model.Notification) error { + return d.txImpl.Transaction(ctx, func(ctx context.Context) error { + err := d.metaDomain.NotificationDb(ctx).Insert(&dbmodel.Notification{ + CollectionID: notification.CollectionID, + Type: notification.Type, + Status: notification.Status, + }) + if err != nil { + return err + } + return nil + }) +} + +func (d *DatabaseNotificationStore) RemoveNotifications(ctx context.Context, notification []model.Notification) error { + return d.txImpl.Transaction(ctx, func(ctx context.Context) error { + ids := make([]int64, 0, len(notification)) + for _, n := range notification { + ids = append(ids, n.ID) + } + err := d.metaDomain.NotificationDb(ctx).Delete(ids) + if err != nil { + return err + } + return nil + }) +} diff --git a/go/coordinator/internal/notification/database_notification_store_test.go b/go/coordinator/internal/notification/database_notification_store_test.go new file mode 100644 index 0000000000000000000000000000000000000000..d2e9fa91f2cabfbe845989765260ce795849cf09 --- /dev/null +++ b/go/coordinator/internal/notification/database_notification_store_test.go @@ -0,0 +1,192 @@ +package notification + +import ( + "context" + "reflect" + "testing" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel/mocks" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/stretchr/testify/mock" +) + +func TestDatabaseNotificationStore_GetAllPendingNotifications(t *testing.T) { + // Create a mock implementation of dbmodel.IMetaDomain + mockMetaDomain := &mocks.IMetaDomain{} + + // Create a mock implementation of dbmodel.ITransaction + mockTxImpl := &mocks.ITransaction{} + + // Create a new instance of DatabaseNotificationStore + store := NewDatabaseNotificationStore(mockTxImpl, mockMetaDomain) + + // Create a mock context + ctx := context.Background() + + notification1 := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification2 := model.Notification{ID: 2, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification3 := model.Notification{ID: 3, CollectionID: "collection2", Status: model.NotificationStatusPending} + // Define the expected result + + expectedResult := map[string][]model.Notification{ + "collection1": {notification1, notification2}, + "collection2": {notification3}, + } + + dbNotification1 := dbmodel.Notification{ID: 1, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + dbNotification2 := dbmodel.Notification{ID: 2, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + dbNotification3 := dbmodel.Notification{ID: 3, CollectionID: "collection2", Status: dbmodel.NotificationStatusPending} + + expectedDBResult := []*dbmodel.Notification{&dbNotification1, &dbNotification2, &dbNotification3} + + // Set up the mock implementation to return the expected result + // mockTxImpl.On("Transaction", context.Background(), mock.Anything).Return(nil) + mockMetaDomain.On("NotificationDb", context.Background()).Return(&mocks.INotificationDb{}) + mockMetaDomain.NotificationDb(context.Background()).(*mocks.INotificationDb).On("GetAllPendingNotifications").Return(expectedDBResult, nil) + + // Call the method under test + result, err := store.GetAllPendingNotifications(ctx) + + // Assert the result + if err != nil { + t.Errorf("Unexpected error: %v", err) + } + + if len(result) != len(expectedResult) { + t.Errorf("Unexpected result length. Expected: %d, Got: %d", len(expectedResult), len(result)) + } + + // Compare the actual result with the expected result + if !reflect.DeepEqual(result, expectedResult) { + t.Errorf("Unexpected result. Got: %v, Want: %v", result, expectedResult) + } + + // Verify that the mock implementation was called as expected + mockMetaDomain.AssertExpectations(t) + mockTxImpl.AssertExpectations(t) +} + +func TestDatabaseNotificationStore_GetNotifications(t *testing.T) { + // Create a mock implementation of dbmodel.IMetaDomain + mockMetaDomain := &mocks.IMetaDomain{} + + // Create a mock implementation of dbmodel.ITransaction + mockTxImpl := &mocks.ITransaction{} + + // Create a new instance of DatabaseNotificationStore + store := NewDatabaseNotificationStore(mockTxImpl, mockMetaDomain) + + // Create a mock context + ctx := context.Background() + + notification1 := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification2 := model.Notification{ID: 2, CollectionID: "collection1", Status: model.NotificationStatusPending} + // Define the expected result + + expectedResult := []model.Notification{notification1, notification2} + + dbNotification1 := dbmodel.Notification{ID: 1, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + dbNotification2 := dbmodel.Notification{ID: 2, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + + expectedDBResult := []*dbmodel.Notification{&dbNotification1, &dbNotification2} + + // Set up the mock implementation to return the expected result + // mockTxImpl.On("Transaction", context.Background(), mock.Anything).Return(nil) + mockMetaDomain.On("NotificationDb", context.Background()).Return(&mocks.INotificationDb{}) + mockMetaDomain.NotificationDb(context.Background()).(*mocks.INotificationDb).On("GetNotificationByCollectionID", "collection1").Return(expectedDBResult, nil) + + // Call the method under test + result, err := store.GetNotifications(ctx, "collection1") + + // Assert the result + if err != nil { + t.Errorf("Unexpected error: %v", err) + } + + if len(result) != len(expectedResult) { + t.Errorf("Unexpected result length. Expected: %d, Got: %d", len(expectedResult), len(result)) + } + + // Compare the actual result with the expected result + if !reflect.DeepEqual(result, expectedResult) { + t.Errorf("Unexpected result. Got: %v, Want: %v", result, expectedResult) + } + + // Verify that the mock implementation was called as expected + mockMetaDomain.AssertExpectations(t) + mockTxImpl.AssertExpectations(t) +} + +func TestDatabaseNotificationStore_AddNotification(t *testing.T) { + // Create a mock implementation of dbmodel.IMetaDomain + mockMetaDomain := &mocks.IMetaDomain{} + + // Create a mock implementation of dbmodel.ITransaction + mockTxImpl := &mocks.ITransaction{} + + // Create a new instance of DatabaseNotificationStore + store := NewDatabaseNotificationStore(mockTxImpl, mockMetaDomain) + + // Create a mock context + ctx := context.Background() + + notification1 := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + + dbNotification1 := dbmodel.Notification{ID: 1, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + + // Set up the mock implementation to return the expected result + mockTxImpl.On("Transaction", context.Background(), mock.Anything).Return(nil) + mockMetaDomain.On("NotificationDb", context.Background()).Return(&mocks.INotificationDb{}) + mockMetaDomain.NotificationDb(context.Background()).(*mocks.INotificationDb).On("AddNotification", &dbNotification1).Return(nil) + + // Call the method under test + err := store.AddNotification(ctx, notification1) + + // Assert the result + if err != nil { + t.Errorf("Unexpected error: %v", err) + } + + // Verify that the mock implementation was called as expected + mockMetaDomain.AssertExpectations(t) + mockTxImpl.AssertExpectations(t) +} + +func TestDatabaseNotificationStore_RemoveNotifications(t *testing.T) { + // Create a mock implementation of dbmodel.IMetaDomain + mockMetaDomain := &mocks.IMetaDomain{} + + // Create a mock implementation of dbmodel.ITransaction + mockTxImpl := &mocks.ITransaction{} + + // Create a new instance of DatabaseNotificationStore + store := NewDatabaseNotificationStore(mockTxImpl, mockMetaDomain) + + // Create a mock context + ctx := context.Background() + + notification1 := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification2 := model.Notification{ID: 2, CollectionID: "collection1", Status: model.NotificationStatusPending} + + dbNotification1 := dbmodel.Notification{ID: 1, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + dbNotification2 := dbmodel.Notification{ID: 2, CollectionID: "collection1", Status: dbmodel.NotificationStatusPending} + + // Set up the mock implementation to return the expected result + mockTxImpl.On("Transaction", context.Background(), mock.Anything).Return(nil) + mockMetaDomain.On("NotificationDb", context.Background()).Return(&mocks.INotificationDb{}) + mockMetaDomain.NotificationDb(context.Background()).(*mocks.INotificationDb).On("DeleteNotification", &dbNotification1).Return(nil) + mockMetaDomain.NotificationDb(context.Background()).(*mocks.INotificationDb).On("DeleteNotification", &dbNotification2).Return(nil) + + // Call the method under test + err := store.RemoveNotifications(ctx, []model.Notification{notification1, notification2}) + + // Assert the result + if err != nil { + t.Errorf("Unexpected error: %v", err) + } + + // Verify that the mock implementation was called as expected + mockMetaDomain.AssertExpectations(t) + mockTxImpl.AssertExpectations(t) +} diff --git a/go/coordinator/internal/notification/memory_notification_store.go b/go/coordinator/internal/notification/memory_notification_store.go new file mode 100644 index 0000000000000000000000000000000000000000..e6168d9a3ca84b6e22a00aa4b819f2e95d417fc7 --- /dev/null +++ b/go/coordinator/internal/notification/memory_notification_store.go @@ -0,0 +1,65 @@ +package notification + +import ( + "context" + "sort" + + "github.com/chroma/chroma-coordinator/internal/model" +) + +type MemoryNotificationStore struct { + notifications map[string][]model.Notification +} + +var _ NotificationStore = &MemoryNotificationStore{} + +func NewMemoryNotificationStore() *MemoryNotificationStore { + return &MemoryNotificationStore{ + notifications: make(map[string][]model.Notification), + } +} + +func (m *MemoryNotificationStore) GetAllPendingNotifications(ctx context.Context) (map[string][]model.Notification, error) { + result := make(map[string][]model.Notification) + for collectionID, notifications := range m.notifications { + for _, notification := range notifications { + if notification.Status == model.NotificationStatusPending { + result[collectionID] = append(result[collectionID], notification) + } + } + // sort notifications by ID + sort.Slice(result[collectionID], func(i, j int) bool { + return result[collectionID][i].ID < result[collectionID][j].ID + }) + } + return result, nil +} + +func (m *MemoryNotificationStore) GetNotifications(ctx context.Context, collectionID string) ([]model.Notification, error) { + notifications, ok := m.notifications[collectionID] + if !ok { + return nil, nil + } + // sort notifications by ID + sort.Slice(notifications, func(i, j int) bool { + return notifications[i].ID < notifications[j].ID + }) + return notifications, nil +} + +func (m *MemoryNotificationStore) AddNotification(ctx context.Context, notification model.Notification) error { + m.notifications[notification.CollectionID] = append(m.notifications[notification.CollectionID], notification) + return nil +} + +func (m *MemoryNotificationStore) RemoveNotifications(ctx context.Context, notifications []model.Notification) error { + for _, notification := range notifications { + for i, n := range m.notifications[notification.CollectionID] { + if n.ID == notification.ID { + m.notifications[notification.CollectionID] = append(m.notifications[notification.CollectionID][:i], m.notifications[notification.CollectionID][i+1:]...) + break + } + } + } + return nil +} diff --git a/go/coordinator/internal/notification/memory_notification_store_test.go b/go/coordinator/internal/notification/memory_notification_store_test.go new file mode 100644 index 0000000000000000000000000000000000000000..17734898f3d5014b067ed2c50196dc82836c87dc --- /dev/null +++ b/go/coordinator/internal/notification/memory_notification_store_test.go @@ -0,0 +1,145 @@ +package notification + +import ( + "context" + "reflect" + "testing" + + "github.com/chroma/chroma-coordinator/internal/model" +) + +func TestMemoryNotificationStore_GetAllPendingNotifications(t *testing.T) { + // Create a new MemoryNotificationStore + store := NewMemoryNotificationStore() + + // Create some test notifications + notification1 := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification2 := model.Notification{ID: 2, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification3 := model.Notification{ID: 3, CollectionID: "collection2", Status: model.NotificationStatusPending} + + // Add the test notifications to the store + store.AddNotification(context.Background(), notification1) + store.AddNotification(context.Background(), notification2) + store.AddNotification(context.Background(), notification3) + + // Get all pending notifications + notifications, err := store.GetAllPendingNotifications(context.Background()) + if err != nil { + t.Errorf("Error getting pending notifications: %v", err) + } + + // Define the expected result + expected := map[string][]model.Notification{ + "collection1": {notification1, notification2}, + "collection2": {notification3}, + } + + // Compare the actual result with the expected result + if !reflect.DeepEqual(notifications, expected) { + t.Errorf("Unexpected result. Got: %v, Want: %v", notifications, expected) + } +} + +func TestMemoryNotificationStore_GetNotifications(t *testing.T) { + // Create a new MemoryNotificationStore + store := NewMemoryNotificationStore() + + // Create some test notifications + notification1 := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification2 := model.Notification{ID: 2, CollectionID: "collection1", Status: model.NotificationStatusPending} + notification3 := model.Notification{ID: 3, CollectionID: "collection2", Status: model.NotificationStatusPending} + notification4 := model.Notification{ID: 4, CollectionID: "collection2", Status: model.NotificationStatusPending} + + // Add the test notifications to the store + store.AddNotification(context.Background(), notification1) + store.AddNotification(context.Background(), notification2) + + // Add the test notifications to the store, in reverse order + store.AddNotification(context.Background(), notification4) + store.AddNotification(context.Background(), notification3) + + // Get notifications for collection1 + notifications, err := store.GetNotifications(context.Background(), "collection1") + if err != nil { + t.Errorf("Error getting notifications: %v", err) + } + + // Define the expected result + expected := []model.Notification{notification1, notification2} + + // Compare the actual result with the expected result + if !reflect.DeepEqual(notifications, expected) { + t.Errorf("Unexpected result. Got: %v, Want: %v", notifications, expected) + } + + // Get notifications for collection2 + notifications, err = store.GetNotifications(context.Background(), "collection2") + if err != nil { + t.Errorf("Error getting notifications: %v", err) + } + expected = []model.Notification{notification3, notification4} + if !reflect.DeepEqual(notifications, expected) { + t.Errorf("Unexpected result. Got: %v, Want: %v", notifications, expected) + } +} + +func TestMemoryNotificationStore_AddNotification(t *testing.T) { + // Create a new MemoryNotificationStore + store := NewMemoryNotificationStore() + + // Create a test notification + notification := model.Notification{ID: 1, CollectionID: "collection1", Status: model.NotificationStatusPending} + + // Add the test notification to the store + err := store.AddNotification(context.Background(), notification) + if err != nil { + t.Errorf("Error adding notification: %v", err) + } + + // Get all pending notifications + notifications, err := store.GetAllPendingNotifications(context.Background()) + if err != nil { + t.Errorf("Error getting pending notifications: %v", err) + } + + // Define the expected result + expected := map[string][]model.Notification{ + "collection1": {notification}, + } + + // Compare the actual result with the expected result + if !reflect.DeepEqual(notifications, expected) { + t.Errorf("Unexpected result. Got: %v, Want: %v", notifications, expected) + } +} + +func TestMemoryNotificationStore_RemoveNotification(t *testing.T) { + // Create a new MemoryNotificationStore + store := NewMemoryNotificationStore() + + // Create a test notification + notification := model.Notification{ID: 1, CollectionID: "collection1"} + + // Add the test notification to the store + store.AddNotification(context.Background(), notification) + + // Remove the test notification from the store + err := store.RemoveNotifications(context.Background(), []model.Notification{notification}) + if err != nil { + t.Errorf("Error removing notification: %v", err) + } + + // Get all pending notifications + notifications, err := store.GetAllPendingNotifications(context.Background()) + if err != nil { + t.Errorf("Error getting pending notifications: %v", err) + } + + // Define the expected result + expected := map[string][]model.Notification{} + + // Compare the actual result with the expected result + if !reflect.DeepEqual(notifications, expected) { + t.Errorf("Unexpected result. Got: %v, Want: %v", notifications, expected) + } +} diff --git a/go/coordinator/internal/notification/notification_processor.go b/go/coordinator/internal/notification/notification_processor.go new file mode 100644 index 0000000000000000000000000000000000000000..e9113dc000dac01b06bd8fa04189b70044fb9d34 --- /dev/null +++ b/go/coordinator/internal/notification/notification_processor.go @@ -0,0 +1,138 @@ +package notification + +import ( + "context" + "sync/atomic" + + "github.com/chroma/chroma-coordinator/internal/common" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/pingcap/log" + "go.uber.org/zap" +) + +type NotificationProcessor interface { + common.Component + Process(ctx context.Context) error + Trigger(ctx context.Context, triggerMsg TriggerMessage) +} + +type SimpleNotificationProcessor struct { + ctx context.Context + store NotificationStore + notifer Notifier + channel chan TriggerMessage + doneChannel chan bool + running atomic.Bool +} + +type TriggerMessage struct { + Msg model.Notification + ResultChan chan error +} + +const triggerChannelSize = 1000 + +var _ NotificationProcessor = &SimpleNotificationProcessor{} + +func NewSimpleNotificationProcessor(ctx context.Context, store NotificationStore, notifier Notifier) *SimpleNotificationProcessor { + return &SimpleNotificationProcessor{ + ctx: ctx, + store: store, + notifer: notifier, + channel: make(chan TriggerMessage, triggerChannelSize), + doneChannel: make(chan bool), + } +} + +func (n *SimpleNotificationProcessor) Start() error { + // During startup, first sending all pending notifications in the store to the notification topic + log.Info("Starting notification processor") + err := n.sendPendingNotifications(n.ctx) + if err != nil { + log.Error("Failed to send pending notifications", zap.Error(err)) + return err + } + n.running.Store(true) + go n.Process(n.ctx) + return nil +} + +func (n *SimpleNotificationProcessor) Stop() error { + n.running.Store(false) + n.doneChannel <- true + return nil +} + +func (n *SimpleNotificationProcessor) Process(ctx context.Context) error { + log.Info("Waiting for new notifications") + for { + select { + case triggerMsg := <-n.channel: + msg := triggerMsg.Msg + log.Info("Received notification", zap.Any("msg", msg)) + running := n.running.Load() + log.Info("Notification processor is running", zap.Bool("running", running)) + // We need to block here until the notifications are sent successfully + for running { + // Check the notification store if this notification is already processed + // If it is already processed, just return + // If it is not processed, send notifications and remove from the store + notifications, err := n.store.GetNotifications(ctx, msg.CollectionID) + if err != nil { + log.Error("Failed to get notifications", zap.Error(err)) + triggerMsg.ResultChan <- err + continue + } + if len(notifications) == 0 { + log.Info("No pending notifications found") + triggerMsg.ResultChan <- nil + break + } + log.Info("Got notifications from notification store", zap.Any("notifications", notifications)) + err = n.notifer.Notify(ctx, notifications) + if err != nil { + log.Error("Failed to send pending notifications", zap.Error(err)) + } else { + n.store.RemoveNotifications(ctx, notifications) + log.Info("Rmove notifications from notification store", zap.Any("notifications", notifications)) + triggerMsg.ResultChan <- nil + break + } + } + case <-n.doneChannel: + log.Info("Stopping notification processor") + return nil + } + } +} + +func (n *SimpleNotificationProcessor) Trigger(ctx context.Context, triggerMsg TriggerMessage) { + log.Info("Triggering notification", zap.Any("msg", triggerMsg.Msg)) + if len(n.channel) == triggerChannelSize { + log.Error("Notification channel is full, dropping notification", zap.Any("msg", triggerMsg.Msg)) + triggerMsg.ResultChan <- nil + return + } + n.channel <- triggerMsg +} + +func (n *SimpleNotificationProcessor) sendPendingNotifications(ctx context.Context) error { + notificationMap, err := n.store.GetAllPendingNotifications(ctx) + if err != nil { + log.Error("Failed to get all pending notifications", zap.Error(err)) + return err + } + for collectionID, notifications := range notificationMap { + log.Info("Sending pending notifications", zap.Any("collectionID", collectionID), zap.Any("notifications", notifications)) + for { + err = n.notifer.Notify(ctx, notifications) + if err != nil { + log.Error("Failed to send pending notifications", zap.Error(err)) + } else { + n.store.RemoveNotifications(ctx, notifications) + break + } + } + } + return nil +} diff --git a/go/coordinator/internal/notification/notification_processor_test.go b/go/coordinator/internal/notification/notification_processor_test.go new file mode 100644 index 0000000000000000000000000000000000000000..23c85d27eb897e7e45614eddcee2da4d9aed98e8 --- /dev/null +++ b/go/coordinator/internal/notification/notification_processor_test.go @@ -0,0 +1,139 @@ +package notification + +import ( + "context" + "testing" + + "github.com/chroma/chroma-coordinator/internal/metastore/db/dao" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbcore" + "github.com/chroma/chroma-coordinator/internal/metastore/db/dbmodel" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "google.golang.org/protobuf/proto" + "gorm.io/driver/sqlite" + "gorm.io/gorm" + "gorm.io/gorm/logger" +) + +func TestSimpleNotificationProcessor(t *testing.T) { + ctx := context.Background() + db := setupDatabase() + txnImpl := dbcore.NewTxImpl() + metaDomain := dao.NewMetaDomain() + notificationStore := NewDatabaseNotificationStore(txnImpl, metaDomain) + notifier := NewMemoryNotifier() + notificationProcessor := NewSimpleNotificationProcessor(ctx, notificationStore, notifier) + notificationProcessor.Start() + + notification := model.Notification{ + CollectionID: "collection1", + Type: model.NotificationTypeDeleteCollection, + Status: model.NotificationStatusPending, + } + resultChan := make(chan error) + triggerMsg := TriggerMessage{ + Msg: notification, + ResultChan: resultChan, + } + notificationStore.AddNotification(ctx, notification) + notificationProcessor.Trigger(ctx, triggerMsg) + + // Wait for the notification to be processed. + err := <-resultChan + if err != nil { + t.Errorf("Failed to process notification %v", err) + } + if len(notifier.queue) != 1 { + t.Errorf("Notification is not sent by the notifier") + } + for _, msg := range notifier.queue { + newMsgPb := coordinatorpb.Notification{} + err := proto.Unmarshal(msg.Payload, &newMsgPb) + if err != nil { + t.Errorf("Failed to unmarshal message %v", err) + } + newMsg := model.Notification{ + CollectionID: newMsgPb.CollectionId, + Type: newMsgPb.Type, + Status: newMsgPb.Status, + } + if err != nil { + t.Errorf("Failed to unmarshal message %v", err) + } + if newMsg.CollectionID != notification.CollectionID { + t.Errorf("CollectionID is not equal %v, %v", newMsg.CollectionID, notification.CollectionID) + } + if newMsg.Type != notification.Type { + t.Errorf("Type is not equal %v, %v", newMsg.Type, notification.Type) + } + if newMsg.Status != notification.Status { + t.Errorf("Status is not equal, %v, %v", newMsg.Status, notification.Status) + } + } + notificationProcessor.Stop() + cleanupDatabase(db) +} + +func TestSimpleNotificationProcessorWithExistingNotification(t *testing.T) { + ctx := context.Background() + db := setupDatabase() + txnImpl := dbcore.NewTxImpl() + metaDomain := dao.NewMetaDomain() + notificationStore := NewDatabaseNotificationStore(txnImpl, metaDomain) + notifier := NewMemoryNotifier() + notificationProcessor := NewSimpleNotificationProcessor(ctx, notificationStore, notifier) + + notification := model.Notification{ + CollectionID: "collection1", + Type: model.NotificationTypeDeleteCollection, + Status: model.NotificationStatusPending, + } + // Only add to the notification store, but not trigger it. + notificationStore.AddNotification(ctx, notification) + + notificationProcessor.Start() + + if len(notifier.queue) != 1 { + t.Errorf("Notification is not sent by the notifier") + } + for _, msg := range notifier.queue { + newMsgPb := coordinatorpb.Notification{} + err := proto.Unmarshal(msg.Payload, &newMsgPb) + if err != nil { + t.Errorf("Failed to unmarshal message %v", err) + } + newMsg := model.Notification{ + CollectionID: newMsgPb.CollectionId, + Type: newMsgPb.Type, + Status: newMsgPb.Status, + } + if newMsg.CollectionID != notification.CollectionID { + t.Errorf("CollectionID is not equal %v, %v", newMsg.CollectionID, notification.CollectionID) + } + if newMsg.Type != notification.Type { + t.Errorf("Type is not equal %v, %v", newMsg.Type, notification.Type) + } + if newMsg.Status != notification.Status { + t.Errorf("Status is not equal, %v, %v", newMsg.Status, notification.Status) + } + } + notificationProcessor.Stop() + cleanupDatabase(db) +} + +func setupDatabase() *gorm.DB { + db, err := gorm.Open(sqlite.Open(":memory:"), &gorm.Config{ + Logger: logger.Default.LogMode(logger.Info), + }) + if err != nil { + panic("failed to connect database") + } + dbcore.SetGlobalDB(db) + db.Migrator().CreateTable(&dbmodel.Notification{}) + return db +} + +func cleanupDatabase(db *gorm.DB) { + db.Migrator().DropTable(&dbmodel.Notification{}) + dbcore.SetGlobalDB(nil) +} diff --git a/go/coordinator/internal/notification/notification_store.go b/go/coordinator/internal/notification/notification_store.go new file mode 100644 index 0000000000000000000000000000000000000000..6e0434ffa5b116bd0e14d0bd38c8e2b46759ccc5 --- /dev/null +++ b/go/coordinator/internal/notification/notification_store.go @@ -0,0 +1,14 @@ +package notification + +import ( + "context" + + "github.com/chroma/chroma-coordinator/internal/model" +) + +type NotificationStore interface { + GetAllPendingNotifications(ctx context.Context) (map[string][]model.Notification, error) + GetNotifications(ctx context.Context, collecitonID string) ([]model.Notification, error) + AddNotification(ctx context.Context, notification model.Notification) error + RemoveNotifications(ctx context.Context, notifications []model.Notification) error +} diff --git a/go/coordinator/internal/notification/notifier.go b/go/coordinator/internal/notification/notifier.go new file mode 100644 index 0000000000000000000000000000000000000000..ce19bb62c5eedbe71f7a97cd8cd411ca9b3b1359 --- /dev/null +++ b/go/coordinator/internal/notification/notifier.go @@ -0,0 +1,94 @@ +package notification + +import ( + "context" + + "github.com/apache/pulsar-client-go/pulsar" + "github.com/chroma/chroma-coordinator/internal/model" + "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb" + "github.com/pingcap/log" + "go.uber.org/zap" + "google.golang.org/protobuf/proto" +) + +type Notifier interface { + Notify(ctx context.Context, notifications []model.Notification) error +} + +type PulsarNotifier struct { + producer pulsar.Producer +} + +var _ Notifier = &PulsarNotifier{} + +func NewPulsarNotifier(producer pulsar.Producer) *PulsarNotifier { + return &PulsarNotifier{ + producer: producer, + } +} + +func (p *PulsarNotifier) Notify(ctx context.Context, notifications []model.Notification) error { + for _, notification := range notifications { + notificationPb := coordinatorpb.Notification{ + CollectionId: notification.CollectionID, + Type: notification.Type, + Status: notification.Status, + } + payload, err := proto.Marshal(¬ificationPb) + if err != nil { + log.Error("Failed to marshal notification", zap.Error(err)) + return err + } + message := &pulsar.ProducerMessage{ + Key: notification.CollectionID, + Payload: payload, + } + // Since the number of notifications is small, we can send them synchronously + // for now. This is easy to reason about hte order of notifications. + // + // As follow up optimizations, we can send them asynchronously in batches and + // track failed messages. + _, err = p.producer.Send(ctx, message) + if err != nil { + log.Error("Failed to send message", zap.Error(err)) + return err + } + log.Info("Published message", zap.Any("message", message)) + + } + return nil +} + +type MemoryNotifier struct { + queue []pulsar.ProducerMessage +} + +var _ Notifier = &MemoryNotifier{} + +func NewMemoryNotifier() *MemoryNotifier { + return &MemoryNotifier{ + queue: make([]pulsar.ProducerMessage, 0), + } +} + +func (m *MemoryNotifier) Notify(ctx context.Context, notifications []model.Notification) error { + for _, notification := range notifications { + notificationPb := coordinatorpb.Notification{ + CollectionId: notification.CollectionID, + Type: notification.Type, + Status: notification.Status, + } + payload, err := proto.Marshal(¬ificationPb) + if err != nil { + log.Error("Failed to marshal notification", zap.Error(err)) + return err + } + message := pulsar.ProducerMessage{ + Key: notification.CollectionID, + Payload: payload, + } + m.queue = append(m.queue, message) + log.Info("Published message", zap.Any("message", message)) + } + return nil +} diff --git a/go/coordinator/internal/proto/coordinatorpb/chroma.pb.go b/go/coordinator/internal/proto/coordinatorpb/chroma.pb.go new file mode 100644 index 0000000000000000000000000000000000000000..3cec5eefe06258b8c16556b542479c013d4c508d --- /dev/null +++ b/go/coordinator/internal/proto/coordinatorpb/chroma.pb.go @@ -0,0 +1,1725 @@ +// Code generated by protoc-gen-go. DO NOT EDIT. +// versions: +// protoc-gen-go v1.31.0 +// protoc v4.23.4 +// source: chromadb/proto/chroma.proto + +package coordinatorpb + +import ( + protoreflect "google.golang.org/protobuf/reflect/protoreflect" + protoimpl "google.golang.org/protobuf/runtime/protoimpl" + reflect "reflect" + sync "sync" +) + +const ( + // Verify that this generated code is sufficiently up-to-date. + _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) + // Verify that runtime/protoimpl is sufficiently up-to-date. + _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) +) + +type Operation int32 + +const ( + Operation_ADD Operation = 0 + Operation_UPDATE Operation = 1 + Operation_UPSERT Operation = 2 + Operation_DELETE Operation = 3 +) + +// Enum value maps for Operation. +var ( + Operation_name = map[int32]string{ + 0: "ADD", + 1: "UPDATE", + 2: "UPSERT", + 3: "DELETE", + } + Operation_value = map[string]int32{ + "ADD": 0, + "UPDATE": 1, + "UPSERT": 2, + "DELETE": 3, + } +) + +func (x Operation) Enum() *Operation { + p := new(Operation) + *p = x + return p +} + +func (x Operation) String() string { + return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) +} + +func (Operation) Descriptor() protoreflect.EnumDescriptor { + return file_chromadb_proto_chroma_proto_enumTypes[0].Descriptor() +} + +func (Operation) Type() protoreflect.EnumType { + return &file_chromadb_proto_chroma_proto_enumTypes[0] +} + +func (x Operation) Number() protoreflect.EnumNumber { + return protoreflect.EnumNumber(x) +} + +// Deprecated: Use Operation.Descriptor instead. +func (Operation) EnumDescriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{0} +} + +type ScalarEncoding int32 + +const ( + ScalarEncoding_FLOAT32 ScalarEncoding = 0 + ScalarEncoding_INT32 ScalarEncoding = 1 +) + +// Enum value maps for ScalarEncoding. +var ( + ScalarEncoding_name = map[int32]string{ + 0: "FLOAT32", + 1: "INT32", + } + ScalarEncoding_value = map[string]int32{ + "FLOAT32": 0, + "INT32": 1, + } +) + +func (x ScalarEncoding) Enum() *ScalarEncoding { + p := new(ScalarEncoding) + *p = x + return p +} + +func (x ScalarEncoding) String() string { + return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) +} + +func (ScalarEncoding) Descriptor() protoreflect.EnumDescriptor { + return file_chromadb_proto_chroma_proto_enumTypes[1].Descriptor() +} + +func (ScalarEncoding) Type() protoreflect.EnumType { + return &file_chromadb_proto_chroma_proto_enumTypes[1] +} + +func (x ScalarEncoding) Number() protoreflect.EnumNumber { + return protoreflect.EnumNumber(x) +} + +// Deprecated: Use ScalarEncoding.Descriptor instead. +func (ScalarEncoding) EnumDescriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{1} +} + +type SegmentScope int32 + +const ( + SegmentScope_VECTOR SegmentScope = 0 + SegmentScope_METADATA SegmentScope = 1 +) + +// Enum value maps for SegmentScope. +var ( + SegmentScope_name = map[int32]string{ + 0: "VECTOR", + 1: "METADATA", + } + SegmentScope_value = map[string]int32{ + "VECTOR": 0, + "METADATA": 1, + } +) + +func (x SegmentScope) Enum() *SegmentScope { + p := new(SegmentScope) + *p = x + return p +} + +func (x SegmentScope) String() string { + return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) +} + +func (SegmentScope) Descriptor() protoreflect.EnumDescriptor { + return file_chromadb_proto_chroma_proto_enumTypes[2].Descriptor() +} + +func (SegmentScope) Type() protoreflect.EnumType { + return &file_chromadb_proto_chroma_proto_enumTypes[2] +} + +func (x SegmentScope) Number() protoreflect.EnumNumber { + return protoreflect.EnumNumber(x) +} + +// Deprecated: Use SegmentScope.Descriptor instead. +func (SegmentScope) EnumDescriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{2} +} + +type Status struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Reason string `protobuf:"bytes,1,opt,name=reason,proto3" json:"reason,omitempty"` + Code int32 `protobuf:"varint,2,opt,name=code,proto3" json:"code,omitempty"` // TODO: What is the enum of this code? +} + +func (x *Status) Reset() { + *x = Status{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[0] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Status) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Status) ProtoMessage() {} + +func (x *Status) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[0] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Status.ProtoReflect.Descriptor instead. +func (*Status) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{0} +} + +func (x *Status) GetReason() string { + if x != nil { + return x.Reason + } + return "" +} + +func (x *Status) GetCode() int32 { + if x != nil { + return x.Code + } + return 0 +} + +type ChromaResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Status *Status `protobuf:"bytes,1,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *ChromaResponse) Reset() { + *x = ChromaResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[1] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *ChromaResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*ChromaResponse) ProtoMessage() {} + +func (x *ChromaResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[1] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use ChromaResponse.ProtoReflect.Descriptor instead. +func (*ChromaResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{1} +} + +func (x *ChromaResponse) GetStatus() *Status { + if x != nil { + return x.Status + } + return nil +} + +type Vector struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Dimension int32 `protobuf:"varint,1,opt,name=dimension,proto3" json:"dimension,omitempty"` + Vector []byte `protobuf:"bytes,2,opt,name=vector,proto3" json:"vector,omitempty"` + Encoding ScalarEncoding `protobuf:"varint,3,opt,name=encoding,proto3,enum=chroma.ScalarEncoding" json:"encoding,omitempty"` +} + +func (x *Vector) Reset() { + *x = Vector{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[2] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Vector) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Vector) ProtoMessage() {} + +func (x *Vector) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[2] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Vector.ProtoReflect.Descriptor instead. +func (*Vector) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{2} +} + +func (x *Vector) GetDimension() int32 { + if x != nil { + return x.Dimension + } + return 0 +} + +func (x *Vector) GetVector() []byte { + if x != nil { + return x.Vector + } + return nil +} + +func (x *Vector) GetEncoding() ScalarEncoding { + if x != nil { + return x.Encoding + } + return ScalarEncoding_FLOAT32 +} + +type Segment struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Type string `protobuf:"bytes,2,opt,name=type,proto3" json:"type,omitempty"` + Scope SegmentScope `protobuf:"varint,3,opt,name=scope,proto3,enum=chroma.SegmentScope" json:"scope,omitempty"` + Topic *string `protobuf:"bytes,4,opt,name=topic,proto3,oneof" json:"topic,omitempty"` // TODO should channel <> segment binding exist here? + // If a segment has a collection, it implies that this segment implements the full + // collection and can be used to service queries (for it's given scope.) + Collection *string `protobuf:"bytes,5,opt,name=collection,proto3,oneof" json:"collection,omitempty"` + Metadata *UpdateMetadata `protobuf:"bytes,6,opt,name=metadata,proto3,oneof" json:"metadata,omitempty"` +} + +func (x *Segment) Reset() { + *x = Segment{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[3] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Segment) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Segment) ProtoMessage() {} + +func (x *Segment) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[3] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Segment.ProtoReflect.Descriptor instead. +func (*Segment) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{3} +} + +func (x *Segment) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *Segment) GetType() string { + if x != nil { + return x.Type + } + return "" +} + +func (x *Segment) GetScope() SegmentScope { + if x != nil { + return x.Scope + } + return SegmentScope_VECTOR +} + +func (x *Segment) GetTopic() string { + if x != nil && x.Topic != nil { + return *x.Topic + } + return "" +} + +func (x *Segment) GetCollection() string { + if x != nil && x.Collection != nil { + return *x.Collection + } + return "" +} + +func (x *Segment) GetMetadata() *UpdateMetadata { + if x != nil { + return x.Metadata + } + return nil +} + +type Collection struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Name string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"` + Topic string `protobuf:"bytes,3,opt,name=topic,proto3" json:"topic,omitempty"` + Metadata *UpdateMetadata `protobuf:"bytes,4,opt,name=metadata,proto3,oneof" json:"metadata,omitempty"` + Dimension *int32 `protobuf:"varint,5,opt,name=dimension,proto3,oneof" json:"dimension,omitempty"` + Tenant string `protobuf:"bytes,6,opt,name=tenant,proto3" json:"tenant,omitempty"` + Database string `protobuf:"bytes,7,opt,name=database,proto3" json:"database,omitempty"` +} + +func (x *Collection) Reset() { + *x = Collection{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[4] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Collection) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Collection) ProtoMessage() {} + +func (x *Collection) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[4] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Collection.ProtoReflect.Descriptor instead. +func (*Collection) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{4} +} + +func (x *Collection) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *Collection) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +func (x *Collection) GetTopic() string { + if x != nil { + return x.Topic + } + return "" +} + +func (x *Collection) GetMetadata() *UpdateMetadata { + if x != nil { + return x.Metadata + } + return nil +} + +func (x *Collection) GetDimension() int32 { + if x != nil && x.Dimension != nil { + return *x.Dimension + } + return 0 +} + +func (x *Collection) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +func (x *Collection) GetDatabase() string { + if x != nil { + return x.Database + } + return "" +} + +type Database struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Name string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"` + Tenant string `protobuf:"bytes,3,opt,name=tenant,proto3" json:"tenant,omitempty"` +} + +func (x *Database) Reset() { + *x = Database{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[5] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Database) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Database) ProtoMessage() {} + +func (x *Database) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[5] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Database.ProtoReflect.Descriptor instead. +func (*Database) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{5} +} + +func (x *Database) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *Database) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +func (x *Database) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +type Tenant struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` +} + +func (x *Tenant) Reset() { + *x = Tenant{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[6] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Tenant) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Tenant) ProtoMessage() {} + +func (x *Tenant) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[6] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Tenant.ProtoReflect.Descriptor instead. +func (*Tenant) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{6} +} + +func (x *Tenant) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +type UpdateMetadataValue struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + // Types that are assignable to Value: + // + // *UpdateMetadataValue_StringValue + // *UpdateMetadataValue_IntValue + // *UpdateMetadataValue_FloatValue + Value isUpdateMetadataValue_Value `protobuf_oneof:"value"` +} + +func (x *UpdateMetadataValue) Reset() { + *x = UpdateMetadataValue{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[7] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *UpdateMetadataValue) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*UpdateMetadataValue) ProtoMessage() {} + +func (x *UpdateMetadataValue) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[7] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use UpdateMetadataValue.ProtoReflect.Descriptor instead. +func (*UpdateMetadataValue) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{7} +} + +func (m *UpdateMetadataValue) GetValue() isUpdateMetadataValue_Value { + if m != nil { + return m.Value + } + return nil +} + +func (x *UpdateMetadataValue) GetStringValue() string { + if x, ok := x.GetValue().(*UpdateMetadataValue_StringValue); ok { + return x.StringValue + } + return "" +} + +func (x *UpdateMetadataValue) GetIntValue() int64 { + if x, ok := x.GetValue().(*UpdateMetadataValue_IntValue); ok { + return x.IntValue + } + return 0 +} + +func (x *UpdateMetadataValue) GetFloatValue() float64 { + if x, ok := x.GetValue().(*UpdateMetadataValue_FloatValue); ok { + return x.FloatValue + } + return 0 +} + +type isUpdateMetadataValue_Value interface { + isUpdateMetadataValue_Value() +} + +type UpdateMetadataValue_StringValue struct { + StringValue string `protobuf:"bytes,1,opt,name=string_value,json=stringValue,proto3,oneof"` +} + +type UpdateMetadataValue_IntValue struct { + IntValue int64 `protobuf:"varint,2,opt,name=int_value,json=intValue,proto3,oneof"` +} + +type UpdateMetadataValue_FloatValue struct { + FloatValue float64 `protobuf:"fixed64,3,opt,name=float_value,json=floatValue,proto3,oneof"` +} + +func (*UpdateMetadataValue_StringValue) isUpdateMetadataValue_Value() {} + +func (*UpdateMetadataValue_IntValue) isUpdateMetadataValue_Value() {} + +func (*UpdateMetadataValue_FloatValue) isUpdateMetadataValue_Value() {} + +type UpdateMetadata struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Metadata map[string]*UpdateMetadataValue `protobuf:"bytes,1,rep,name=metadata,proto3" json:"metadata,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"` +} + +func (x *UpdateMetadata) Reset() { + *x = UpdateMetadata{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[8] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *UpdateMetadata) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*UpdateMetadata) ProtoMessage() {} + +func (x *UpdateMetadata) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[8] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use UpdateMetadata.ProtoReflect.Descriptor instead. +func (*UpdateMetadata) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{8} +} + +func (x *UpdateMetadata) GetMetadata() map[string]*UpdateMetadataValue { + if x != nil { + return x.Metadata + } + return nil +} + +type SubmitEmbeddingRecord struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Vector *Vector `protobuf:"bytes,2,opt,name=vector,proto3,oneof" json:"vector,omitempty"` + Metadata *UpdateMetadata `protobuf:"bytes,3,opt,name=metadata,proto3,oneof" json:"metadata,omitempty"` + Operation Operation `protobuf:"varint,4,opt,name=operation,proto3,enum=chroma.Operation" json:"operation,omitempty"` + CollectionId string `protobuf:"bytes,5,opt,name=collection_id,json=collectionId,proto3" json:"collection_id,omitempty"` +} + +func (x *SubmitEmbeddingRecord) Reset() { + *x = SubmitEmbeddingRecord{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[9] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *SubmitEmbeddingRecord) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*SubmitEmbeddingRecord) ProtoMessage() {} + +func (x *SubmitEmbeddingRecord) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[9] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use SubmitEmbeddingRecord.ProtoReflect.Descriptor instead. +func (*SubmitEmbeddingRecord) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{9} +} + +func (x *SubmitEmbeddingRecord) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *SubmitEmbeddingRecord) GetVector() *Vector { + if x != nil { + return x.Vector + } + return nil +} + +func (x *SubmitEmbeddingRecord) GetMetadata() *UpdateMetadata { + if x != nil { + return x.Metadata + } + return nil +} + +func (x *SubmitEmbeddingRecord) GetOperation() Operation { + if x != nil { + return x.Operation + } + return Operation_ADD +} + +func (x *SubmitEmbeddingRecord) GetCollectionId() string { + if x != nil { + return x.CollectionId + } + return "" +} + +type VectorEmbeddingRecord struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + SeqId []byte `protobuf:"bytes,2,opt,name=seq_id,json=seqId,proto3" json:"seq_id,omitempty"` + Vector *Vector `protobuf:"bytes,3,opt,name=vector,proto3" json:"vector,omitempty"` // TODO: we need to rethink source of truth for vector dimensionality and encoding +} + +func (x *VectorEmbeddingRecord) Reset() { + *x = VectorEmbeddingRecord{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[10] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *VectorEmbeddingRecord) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*VectorEmbeddingRecord) ProtoMessage() {} + +func (x *VectorEmbeddingRecord) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[10] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use VectorEmbeddingRecord.ProtoReflect.Descriptor instead. +func (*VectorEmbeddingRecord) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{10} +} + +func (x *VectorEmbeddingRecord) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *VectorEmbeddingRecord) GetSeqId() []byte { + if x != nil { + return x.SeqId + } + return nil +} + +func (x *VectorEmbeddingRecord) GetVector() *Vector { + if x != nil { + return x.Vector + } + return nil +} + +type VectorQueryResult struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + SeqId []byte `protobuf:"bytes,2,opt,name=seq_id,json=seqId,proto3" json:"seq_id,omitempty"` + Distance float64 `protobuf:"fixed64,3,opt,name=distance,proto3" json:"distance,omitempty"` + Vector *Vector `protobuf:"bytes,4,opt,name=vector,proto3,oneof" json:"vector,omitempty"` +} + +func (x *VectorQueryResult) Reset() { + *x = VectorQueryResult{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[11] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *VectorQueryResult) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*VectorQueryResult) ProtoMessage() {} + +func (x *VectorQueryResult) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[11] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use VectorQueryResult.ProtoReflect.Descriptor instead. +func (*VectorQueryResult) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{11} +} + +func (x *VectorQueryResult) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *VectorQueryResult) GetSeqId() []byte { + if x != nil { + return x.SeqId + } + return nil +} + +func (x *VectorQueryResult) GetDistance() float64 { + if x != nil { + return x.Distance + } + return 0 +} + +func (x *VectorQueryResult) GetVector() *Vector { + if x != nil { + return x.Vector + } + return nil +} + +type VectorQueryResults struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Results []*VectorQueryResult `protobuf:"bytes,1,rep,name=results,proto3" json:"results,omitempty"` +} + +func (x *VectorQueryResults) Reset() { + *x = VectorQueryResults{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[12] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *VectorQueryResults) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*VectorQueryResults) ProtoMessage() {} + +func (x *VectorQueryResults) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[12] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use VectorQueryResults.ProtoReflect.Descriptor instead. +func (*VectorQueryResults) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{12} +} + +func (x *VectorQueryResults) GetResults() []*VectorQueryResult { + if x != nil { + return x.Results + } + return nil +} + +type GetVectorsRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Ids []string `protobuf:"bytes,1,rep,name=ids,proto3" json:"ids,omitempty"` + SegmentId string `protobuf:"bytes,2,opt,name=segment_id,json=segmentId,proto3" json:"segment_id,omitempty"` +} + +func (x *GetVectorsRequest) Reset() { + *x = GetVectorsRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[13] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetVectorsRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetVectorsRequest) ProtoMessage() {} + +func (x *GetVectorsRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[13] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetVectorsRequest.ProtoReflect.Descriptor instead. +func (*GetVectorsRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{13} +} + +func (x *GetVectorsRequest) GetIds() []string { + if x != nil { + return x.Ids + } + return nil +} + +func (x *GetVectorsRequest) GetSegmentId() string { + if x != nil { + return x.SegmentId + } + return "" +} + +type GetVectorsResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Records []*VectorEmbeddingRecord `protobuf:"bytes,1,rep,name=records,proto3" json:"records,omitempty"` +} + +func (x *GetVectorsResponse) Reset() { + *x = GetVectorsResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[14] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetVectorsResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetVectorsResponse) ProtoMessage() {} + +func (x *GetVectorsResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[14] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetVectorsResponse.ProtoReflect.Descriptor instead. +func (*GetVectorsResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{14} +} + +func (x *GetVectorsResponse) GetRecords() []*VectorEmbeddingRecord { + if x != nil { + return x.Records + } + return nil +} + +type QueryVectorsRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Vectors []*Vector `protobuf:"bytes,1,rep,name=vectors,proto3" json:"vectors,omitempty"` + K int32 `protobuf:"varint,2,opt,name=k,proto3" json:"k,omitempty"` + AllowedIds []string `protobuf:"bytes,3,rep,name=allowed_ids,json=allowedIds,proto3" json:"allowed_ids,omitempty"` + IncludeEmbeddings bool `protobuf:"varint,4,opt,name=include_embeddings,json=includeEmbeddings,proto3" json:"include_embeddings,omitempty"` + SegmentId string `protobuf:"bytes,5,opt,name=segment_id,json=segmentId,proto3" json:"segment_id,omitempty"` // TODO: options as in types.py, its currently unused so can add later +} + +func (x *QueryVectorsRequest) Reset() { + *x = QueryVectorsRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[15] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *QueryVectorsRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*QueryVectorsRequest) ProtoMessage() {} + +func (x *QueryVectorsRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[15] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use QueryVectorsRequest.ProtoReflect.Descriptor instead. +func (*QueryVectorsRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{15} +} + +func (x *QueryVectorsRequest) GetVectors() []*Vector { + if x != nil { + return x.Vectors + } + return nil +} + +func (x *QueryVectorsRequest) GetK() int32 { + if x != nil { + return x.K + } + return 0 +} + +func (x *QueryVectorsRequest) GetAllowedIds() []string { + if x != nil { + return x.AllowedIds + } + return nil +} + +func (x *QueryVectorsRequest) GetIncludeEmbeddings() bool { + if x != nil { + return x.IncludeEmbeddings + } + return false +} + +func (x *QueryVectorsRequest) GetSegmentId() string { + if x != nil { + return x.SegmentId + } + return "" +} + +type QueryVectorsResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Results []*VectorQueryResults `protobuf:"bytes,1,rep,name=results,proto3" json:"results,omitempty"` +} + +func (x *QueryVectorsResponse) Reset() { + *x = QueryVectorsResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_chroma_proto_msgTypes[16] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *QueryVectorsResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*QueryVectorsResponse) ProtoMessage() {} + +func (x *QueryVectorsResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_chroma_proto_msgTypes[16] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use QueryVectorsResponse.ProtoReflect.Descriptor instead. +func (*QueryVectorsResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_chroma_proto_rawDescGZIP(), []int{16} +} + +func (x *QueryVectorsResponse) GetResults() []*VectorQueryResults { + if x != nil { + return x.Results + } + 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file_chromadb_proto_chroma_proto_rawDescGZIP() []byte { + file_chromadb_proto_chroma_proto_rawDescOnce.Do(func() { + file_chromadb_proto_chroma_proto_rawDescData = protoimpl.X.CompressGZIP(file_chromadb_proto_chroma_proto_rawDescData) + }) + return file_chromadb_proto_chroma_proto_rawDescData +} + +var file_chromadb_proto_chroma_proto_enumTypes = make([]protoimpl.EnumInfo, 3) +var file_chromadb_proto_chroma_proto_msgTypes = make([]protoimpl.MessageInfo, 18) +var file_chromadb_proto_chroma_proto_goTypes = []interface{}{ + (Operation)(0), // 0: chroma.Operation + (ScalarEncoding)(0), // 1: chroma.ScalarEncoding + (SegmentScope)(0), // 2: chroma.SegmentScope + (*Status)(nil), // 3: chroma.Status + (*ChromaResponse)(nil), // 4: chroma.ChromaResponse + (*Vector)(nil), // 5: chroma.Vector + (*Segment)(nil), // 6: chroma.Segment + (*Collection)(nil), // 7: chroma.Collection + (*Database)(nil), // 8: chroma.Database + (*Tenant)(nil), // 9: chroma.Tenant + (*UpdateMetadataValue)(nil), // 10: chroma.UpdateMetadataValue + (*UpdateMetadata)(nil), // 11: chroma.UpdateMetadata + (*SubmitEmbeddingRecord)(nil), // 12: chroma.SubmitEmbeddingRecord + (*VectorEmbeddingRecord)(nil), // 13: chroma.VectorEmbeddingRecord + (*VectorQueryResult)(nil), // 14: chroma.VectorQueryResult + (*VectorQueryResults)(nil), // 15: chroma.VectorQueryResults + (*GetVectorsRequest)(nil), // 16: chroma.GetVectorsRequest + (*GetVectorsResponse)(nil), // 17: chroma.GetVectorsResponse + (*QueryVectorsRequest)(nil), // 18: chroma.QueryVectorsRequest + (*QueryVectorsResponse)(nil), // 19: chroma.QueryVectorsResponse + nil, // 20: chroma.UpdateMetadata.MetadataEntry +} +var file_chromadb_proto_chroma_proto_depIdxs = []int32{ + 3, // 0: chroma.ChromaResponse.status:type_name -> chroma.Status + 1, // 1: chroma.Vector.encoding:type_name -> chroma.ScalarEncoding + 2, // 2: chroma.Segment.scope:type_name -> chroma.SegmentScope + 11, // 3: chroma.Segment.metadata:type_name -> chroma.UpdateMetadata + 11, // 4: chroma.Collection.metadata:type_name -> chroma.UpdateMetadata + 20, // 5: chroma.UpdateMetadata.metadata:type_name -> chroma.UpdateMetadata.MetadataEntry + 5, // 6: chroma.SubmitEmbeddingRecord.vector:type_name -> chroma.Vector + 11, // 7: chroma.SubmitEmbeddingRecord.metadata:type_name -> chroma.UpdateMetadata + 0, // 8: chroma.SubmitEmbeddingRecord.operation:type_name -> chroma.Operation + 5, // 9: chroma.VectorEmbeddingRecord.vector:type_name -> chroma.Vector + 5, // 10: chroma.VectorQueryResult.vector:type_name -> chroma.Vector + 14, // 11: chroma.VectorQueryResults.results:type_name -> chroma.VectorQueryResult + 13, // 12: chroma.GetVectorsResponse.records:type_name -> chroma.VectorEmbeddingRecord + 5, // 13: chroma.QueryVectorsRequest.vectors:type_name -> chroma.Vector + 15, // 14: chroma.QueryVectorsResponse.results:type_name -> chroma.VectorQueryResults + 10, // 15: chroma.UpdateMetadata.MetadataEntry.value:type_name -> chroma.UpdateMetadataValue + 16, // 16: chroma.VectorReader.GetVectors:input_type -> chroma.GetVectorsRequest + 18, // 17: chroma.VectorReader.QueryVectors:input_type -> chroma.QueryVectorsRequest + 17, // 18: chroma.VectorReader.GetVectors:output_type -> chroma.GetVectorsResponse + 19, // 19: chroma.VectorReader.QueryVectors:output_type -> chroma.QueryVectorsResponse + 18, // [18:20] is the sub-list for method output_type + 16, // [16:18] is the sub-list for method input_type + 16, // [16:16] is the sub-list for extension type_name + 16, // [16:16] is the sub-list for extension extendee + 0, // [0:16] is the sub-list for field type_name +} + +func init() { file_chromadb_proto_chroma_proto_init() } +func file_chromadb_proto_chroma_proto_init() { + if File_chromadb_proto_chroma_proto != nil { + return + } + if !protoimpl.UnsafeEnabled { + file_chromadb_proto_chroma_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Status); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*ChromaResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Vector); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Segment); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Collection); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Database); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Tenant); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*UpdateMetadataValue); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[8].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*UpdateMetadata); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[9].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*SubmitEmbeddingRecord); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[10].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*VectorEmbeddingRecord); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[11].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*VectorQueryResult); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[12].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*VectorQueryResults); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[13].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetVectorsRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[14].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetVectorsResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[15].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*QueryVectorsRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_chroma_proto_msgTypes[16].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*QueryVectorsResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + } + file_chromadb_proto_chroma_proto_msgTypes[3].OneofWrappers = []interface{}{} + file_chromadb_proto_chroma_proto_msgTypes[4].OneofWrappers = []interface{}{} + file_chromadb_proto_chroma_proto_msgTypes[7].OneofWrappers = []interface{}{ + (*UpdateMetadataValue_StringValue)(nil), + (*UpdateMetadataValue_IntValue)(nil), + (*UpdateMetadataValue_FloatValue)(nil), + } + file_chromadb_proto_chroma_proto_msgTypes[9].OneofWrappers = []interface{}{} + file_chromadb_proto_chroma_proto_msgTypes[11].OneofWrappers = []interface{}{} + type x struct{} + out := protoimpl.TypeBuilder{ + File: protoimpl.DescBuilder{ + GoPackagePath: reflect.TypeOf(x{}).PkgPath(), + RawDescriptor: file_chromadb_proto_chroma_proto_rawDesc, + NumEnums: 3, + NumMessages: 18, + NumExtensions: 0, + NumServices: 1, + }, + GoTypes: file_chromadb_proto_chroma_proto_goTypes, + DependencyIndexes: file_chromadb_proto_chroma_proto_depIdxs, + EnumInfos: file_chromadb_proto_chroma_proto_enumTypes, + MessageInfos: file_chromadb_proto_chroma_proto_msgTypes, + }.Build() + File_chromadb_proto_chroma_proto = out.File + file_chromadb_proto_chroma_proto_rawDesc = nil + file_chromadb_proto_chroma_proto_goTypes = nil + file_chromadb_proto_chroma_proto_depIdxs = nil +} diff --git a/go/coordinator/internal/proto/coordinatorpb/chroma_grpc.pb.go b/go/coordinator/internal/proto/coordinatorpb/chroma_grpc.pb.go new file mode 100644 index 0000000000000000000000000000000000000000..09283123121b4f26cdb17aefb655d73d7db5ede1 --- /dev/null +++ b/go/coordinator/internal/proto/coordinatorpb/chroma_grpc.pb.go @@ -0,0 +1,146 @@ +// Code generated by protoc-gen-go-grpc. DO NOT EDIT. +// versions: +// - protoc-gen-go-grpc v1.3.0 +// - protoc v4.23.4 +// source: chromadb/proto/chroma.proto + +package coordinatorpb + +import ( + context "context" + grpc "google.golang.org/grpc" + codes "google.golang.org/grpc/codes" + status "google.golang.org/grpc/status" +) + +// This is a compile-time assertion to ensure that this generated file +// is compatible with the grpc package it is being compiled against. +// Requires gRPC-Go v1.32.0 or later. +const _ = grpc.SupportPackageIsVersion7 + +const ( + VectorReader_GetVectors_FullMethodName = "/chroma.VectorReader/GetVectors" + VectorReader_QueryVectors_FullMethodName = "/chroma.VectorReader/QueryVectors" +) + +// VectorReaderClient is the client API for VectorReader service. +// +// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream. +type VectorReaderClient interface { + GetVectors(ctx context.Context, in *GetVectorsRequest, opts ...grpc.CallOption) (*GetVectorsResponse, error) + QueryVectors(ctx context.Context, in *QueryVectorsRequest, opts ...grpc.CallOption) (*QueryVectorsResponse, error) +} + +type vectorReaderClient struct { + cc grpc.ClientConnInterface +} + +func NewVectorReaderClient(cc grpc.ClientConnInterface) VectorReaderClient { + return &vectorReaderClient{cc} +} + +func (c *vectorReaderClient) GetVectors(ctx context.Context, in *GetVectorsRequest, opts ...grpc.CallOption) (*GetVectorsResponse, error) { + out := new(GetVectorsResponse) + err := c.cc.Invoke(ctx, VectorReader_GetVectors_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *vectorReaderClient) QueryVectors(ctx context.Context, in *QueryVectorsRequest, opts ...grpc.CallOption) (*QueryVectorsResponse, error) { + out := new(QueryVectorsResponse) + err := c.cc.Invoke(ctx, VectorReader_QueryVectors_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +// VectorReaderServer is the server API for VectorReader service. +// All implementations must embed UnimplementedVectorReaderServer +// for forward compatibility +type VectorReaderServer interface { + GetVectors(context.Context, *GetVectorsRequest) (*GetVectorsResponse, error) + QueryVectors(context.Context, *QueryVectorsRequest) (*QueryVectorsResponse, error) + mustEmbedUnimplementedVectorReaderServer() +} + +// UnimplementedVectorReaderServer must be embedded to have forward compatible implementations. +type UnimplementedVectorReaderServer struct { +} + +func (UnimplementedVectorReaderServer) GetVectors(context.Context, *GetVectorsRequest) (*GetVectorsResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method GetVectors not implemented") +} +func (UnimplementedVectorReaderServer) QueryVectors(context.Context, *QueryVectorsRequest) (*QueryVectorsResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method QueryVectors not implemented") +} +func (UnimplementedVectorReaderServer) mustEmbedUnimplementedVectorReaderServer() {} + +// UnsafeVectorReaderServer may be embedded to opt out of forward compatibility for this service. +// Use of this interface is not recommended, as added methods to VectorReaderServer will +// result in compilation errors. +type UnsafeVectorReaderServer interface { + mustEmbedUnimplementedVectorReaderServer() +} + +func RegisterVectorReaderServer(s grpc.ServiceRegistrar, srv VectorReaderServer) { + s.RegisterService(&VectorReader_ServiceDesc, srv) +} + +func _VectorReader_GetVectors_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(GetVectorsRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(VectorReaderServer).GetVectors(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: VectorReader_GetVectors_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(VectorReaderServer).GetVectors(ctx, req.(*GetVectorsRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _VectorReader_QueryVectors_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(QueryVectorsRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(VectorReaderServer).QueryVectors(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: VectorReader_QueryVectors_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(VectorReaderServer).QueryVectors(ctx, req.(*QueryVectorsRequest)) + } + return interceptor(ctx, in, info, handler) +} + +// VectorReader_ServiceDesc is the grpc.ServiceDesc for VectorReader service. +// It's only intended for direct use with grpc.RegisterService, +// and not to be introspected or modified (even as a copy) +var VectorReader_ServiceDesc = grpc.ServiceDesc{ + ServiceName: "chroma.VectorReader", + HandlerType: (*VectorReaderServer)(nil), + Methods: []grpc.MethodDesc{ + { + MethodName: "GetVectors", + Handler: _VectorReader_GetVectors_Handler, + }, + { + MethodName: "QueryVectors", + Handler: _VectorReader_QueryVectors_Handler, + }, + }, + Streams: []grpc.StreamDesc{}, + Metadata: "chromadb/proto/chroma.proto", +} diff --git a/go/coordinator/internal/proto/coordinatorpb/coordinator.pb.go b/go/coordinator/internal/proto/coordinatorpb/coordinator.pb.go new file mode 100644 index 0000000000000000000000000000000000000000..be93392c30494a9265f8711727319b6e9ef0ac33 --- /dev/null +++ b/go/coordinator/internal/proto/coordinatorpb/coordinator.pb.go @@ -0,0 +1,1865 @@ +// Code generated by protoc-gen-go. DO NOT EDIT. +// versions: +// protoc-gen-go v1.31.0 +// protoc v4.23.4 +// source: chromadb/proto/coordinator.proto + +package coordinatorpb + +import ( + protoreflect "google.golang.org/protobuf/reflect/protoreflect" + protoimpl "google.golang.org/protobuf/runtime/protoimpl" + emptypb "google.golang.org/protobuf/types/known/emptypb" + reflect "reflect" + sync "sync" +) + +const ( + // Verify that this generated code is sufficiently up-to-date. + _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) + // Verify that runtime/protoimpl is sufficiently up-to-date. + _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) +) + +type CreateDatabaseRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Name string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"` + Tenant string `protobuf:"bytes,3,opt,name=tenant,proto3" json:"tenant,omitempty"` +} + +func (x *CreateDatabaseRequest) Reset() { + *x = CreateDatabaseRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[0] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *CreateDatabaseRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*CreateDatabaseRequest) ProtoMessage() {} + +func (x *CreateDatabaseRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[0] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use CreateDatabaseRequest.ProtoReflect.Descriptor instead. +func (*CreateDatabaseRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{0} +} + +func (x *CreateDatabaseRequest) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *CreateDatabaseRequest) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +func (x *CreateDatabaseRequest) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +type GetDatabaseRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` + Tenant string `protobuf:"bytes,2,opt,name=tenant,proto3" json:"tenant,omitempty"` +} + +func (x *GetDatabaseRequest) Reset() { + *x = GetDatabaseRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[1] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetDatabaseRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetDatabaseRequest) ProtoMessage() {} + +func (x *GetDatabaseRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[1] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetDatabaseRequest.ProtoReflect.Descriptor instead. +func (*GetDatabaseRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{1} +} + +func (x *GetDatabaseRequest) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +func (x *GetDatabaseRequest) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +type GetDatabaseResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Database *Database `protobuf:"bytes,1,opt,name=database,proto3" json:"database,omitempty"` + Status *Status `protobuf:"bytes,2,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *GetDatabaseResponse) Reset() { + *x = GetDatabaseResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[2] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetDatabaseResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetDatabaseResponse) ProtoMessage() {} + +func (x *GetDatabaseResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[2] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetDatabaseResponse.ProtoReflect.Descriptor instead. +func (*GetDatabaseResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{2} +} + +func (x *GetDatabaseResponse) GetDatabase() *Database { + if x != nil { + return x.Database + } + return nil +} + +func (x *GetDatabaseResponse) GetStatus() *Status { + if x != nil { + return x.Status + } + return nil +} + +type CreateTenantRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Name string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"` // Names are globally unique +} + +func (x *CreateTenantRequest) Reset() { + *x = CreateTenantRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[3] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *CreateTenantRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*CreateTenantRequest) ProtoMessage() {} + +func (x *CreateTenantRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[3] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use CreateTenantRequest.ProtoReflect.Descriptor instead. +func (*CreateTenantRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{3} +} + +func (x *CreateTenantRequest) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +type GetTenantRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` +} + +func (x *GetTenantRequest) Reset() { + *x = GetTenantRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[4] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetTenantRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetTenantRequest) ProtoMessage() {} + +func (x *GetTenantRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[4] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetTenantRequest.ProtoReflect.Descriptor instead. +func (*GetTenantRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{4} +} + +func (x *GetTenantRequest) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +type GetTenantResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Tenant *Tenant `protobuf:"bytes,1,opt,name=tenant,proto3" json:"tenant,omitempty"` + Status *Status `protobuf:"bytes,2,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *GetTenantResponse) Reset() { + *x = GetTenantResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[5] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetTenantResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetTenantResponse) ProtoMessage() {} + +func (x *GetTenantResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[5] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetTenantResponse.ProtoReflect.Descriptor instead. +func (*GetTenantResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{5} +} + +func (x *GetTenantResponse) GetTenant() *Tenant { + if x != nil { + return x.Tenant + } + return nil +} + +func (x *GetTenantResponse) GetStatus() *Status { + if x != nil { + return x.Status + } + return nil +} + +type CreateSegmentRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Segment *Segment `protobuf:"bytes,1,opt,name=segment,proto3" json:"segment,omitempty"` +} + +func (x *CreateSegmentRequest) Reset() { + *x = CreateSegmentRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[6] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *CreateSegmentRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*CreateSegmentRequest) ProtoMessage() {} + +func (x *CreateSegmentRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[6] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use CreateSegmentRequest.ProtoReflect.Descriptor instead. +func (*CreateSegmentRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{6} +} + +func (x *CreateSegmentRequest) GetSegment() *Segment { + if x != nil { + return x.Segment + } + return nil +} + +type DeleteSegmentRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` +} + +func (x *DeleteSegmentRequest) Reset() { + *x = DeleteSegmentRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[7] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *DeleteSegmentRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*DeleteSegmentRequest) ProtoMessage() {} + +func (x *DeleteSegmentRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[7] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use DeleteSegmentRequest.ProtoReflect.Descriptor instead. +func (*DeleteSegmentRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{7} +} + +func (x *DeleteSegmentRequest) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +type GetSegmentsRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id *string `protobuf:"bytes,1,opt,name=id,proto3,oneof" json:"id,omitempty"` + Type *string `protobuf:"bytes,2,opt,name=type,proto3,oneof" json:"type,omitempty"` + Scope *SegmentScope `protobuf:"varint,3,opt,name=scope,proto3,enum=chroma.SegmentScope,oneof" json:"scope,omitempty"` + Topic *string `protobuf:"bytes,4,opt,name=topic,proto3,oneof" json:"topic,omitempty"` + Collection *string `protobuf:"bytes,5,opt,name=collection,proto3,oneof" json:"collection,omitempty"` // Collection ID +} + +func (x *GetSegmentsRequest) Reset() { + *x = GetSegmentsRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[8] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetSegmentsRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetSegmentsRequest) ProtoMessage() {} + +func (x *GetSegmentsRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[8] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetSegmentsRequest.ProtoReflect.Descriptor instead. +func (*GetSegmentsRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{8} +} + +func (x *GetSegmentsRequest) GetId() string { + if x != nil && x.Id != nil { + return *x.Id + } + return "" +} + +func (x *GetSegmentsRequest) GetType() string { + if x != nil && x.Type != nil { + return *x.Type + } + return "" +} + +func (x *GetSegmentsRequest) GetScope() SegmentScope { + if x != nil && x.Scope != nil { + return *x.Scope + } + return SegmentScope_VECTOR +} + +func (x *GetSegmentsRequest) GetTopic() string { + if x != nil && x.Topic != nil { + return *x.Topic + } + return "" +} + +func (x *GetSegmentsRequest) GetCollection() string { + if x != nil && x.Collection != nil { + return *x.Collection + } + return "" +} + +type GetSegmentsResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Segments []*Segment `protobuf:"bytes,1,rep,name=segments,proto3" json:"segments,omitempty"` + Status *Status `protobuf:"bytes,2,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *GetSegmentsResponse) Reset() { + *x = GetSegmentsResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[9] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetSegmentsResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetSegmentsResponse) ProtoMessage() {} + +func (x *GetSegmentsResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[9] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetSegmentsResponse.ProtoReflect.Descriptor instead. +func (*GetSegmentsResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{9} +} + +func (x *GetSegmentsResponse) GetSegments() []*Segment { + if x != nil { + return x.Segments + } + return nil +} + +func (x *GetSegmentsResponse) GetStatus() *Status { + if x != nil { + return x.Status + } + return nil +} + +type UpdateSegmentRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + // Types that are assignable to TopicUpdate: + // + // *UpdateSegmentRequest_Topic + // *UpdateSegmentRequest_ResetTopic + TopicUpdate isUpdateSegmentRequest_TopicUpdate `protobuf_oneof:"topic_update"` + // Types that are assignable to CollectionUpdate: + // + // *UpdateSegmentRequest_Collection + // *UpdateSegmentRequest_ResetCollection + CollectionUpdate isUpdateSegmentRequest_CollectionUpdate `protobuf_oneof:"collection_update"` + // Types that are assignable to MetadataUpdate: + // + // *UpdateSegmentRequest_Metadata + // *UpdateSegmentRequest_ResetMetadata + MetadataUpdate isUpdateSegmentRequest_MetadataUpdate `protobuf_oneof:"metadata_update"` +} + +func (x *UpdateSegmentRequest) Reset() { + *x = UpdateSegmentRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[10] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *UpdateSegmentRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*UpdateSegmentRequest) ProtoMessage() {} + +func (x *UpdateSegmentRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[10] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use UpdateSegmentRequest.ProtoReflect.Descriptor instead. +func (*UpdateSegmentRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{10} +} + +func (x *UpdateSegmentRequest) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (m *UpdateSegmentRequest) GetTopicUpdate() isUpdateSegmentRequest_TopicUpdate { + if m != nil { + return m.TopicUpdate + } + return nil +} + +func (x *UpdateSegmentRequest) GetTopic() string { + if x, ok := x.GetTopicUpdate().(*UpdateSegmentRequest_Topic); ok { + return x.Topic + } + return "" +} + +func (x *UpdateSegmentRequest) GetResetTopic() bool { + if x, ok := x.GetTopicUpdate().(*UpdateSegmentRequest_ResetTopic); ok { + return x.ResetTopic + } + return false +} + +func (m *UpdateSegmentRequest) GetCollectionUpdate() isUpdateSegmentRequest_CollectionUpdate { + if m != nil { + return m.CollectionUpdate + } + return nil +} + +func (x *UpdateSegmentRequest) GetCollection() string { + if x, ok := x.GetCollectionUpdate().(*UpdateSegmentRequest_Collection); ok { + return x.Collection + } + return "" +} + +func (x *UpdateSegmentRequest) GetResetCollection() bool { + if x, ok := x.GetCollectionUpdate().(*UpdateSegmentRequest_ResetCollection); ok { + return x.ResetCollection + } + return false +} + +func (m *UpdateSegmentRequest) GetMetadataUpdate() isUpdateSegmentRequest_MetadataUpdate { + if m != nil { + return m.MetadataUpdate + } + return nil +} + +func (x *UpdateSegmentRequest) GetMetadata() *UpdateMetadata { + if x, ok := x.GetMetadataUpdate().(*UpdateSegmentRequest_Metadata); ok { + return x.Metadata + } + return nil +} + +func (x *UpdateSegmentRequest) GetResetMetadata() bool { + if x, ok := x.GetMetadataUpdate().(*UpdateSegmentRequest_ResetMetadata); ok { + return x.ResetMetadata + } + return false +} + +type isUpdateSegmentRequest_TopicUpdate interface { + isUpdateSegmentRequest_TopicUpdate() +} + +type UpdateSegmentRequest_Topic struct { + Topic string `protobuf:"bytes,2,opt,name=topic,proto3,oneof"` +} + +type UpdateSegmentRequest_ResetTopic struct { + ResetTopic bool `protobuf:"varint,3,opt,name=reset_topic,json=resetTopic,proto3,oneof"` +} + +func (*UpdateSegmentRequest_Topic) isUpdateSegmentRequest_TopicUpdate() {} + +func (*UpdateSegmentRequest_ResetTopic) isUpdateSegmentRequest_TopicUpdate() {} + +type isUpdateSegmentRequest_CollectionUpdate interface { + isUpdateSegmentRequest_CollectionUpdate() +} + +type UpdateSegmentRequest_Collection struct { + Collection string `protobuf:"bytes,4,opt,name=collection,proto3,oneof"` +} + +type UpdateSegmentRequest_ResetCollection struct { + ResetCollection bool `protobuf:"varint,5,opt,name=reset_collection,json=resetCollection,proto3,oneof"` +} + +func (*UpdateSegmentRequest_Collection) isUpdateSegmentRequest_CollectionUpdate() {} + +func (*UpdateSegmentRequest_ResetCollection) isUpdateSegmentRequest_CollectionUpdate() {} + +type isUpdateSegmentRequest_MetadataUpdate interface { + isUpdateSegmentRequest_MetadataUpdate() +} + +type UpdateSegmentRequest_Metadata struct { + Metadata *UpdateMetadata `protobuf:"bytes,6,opt,name=metadata,proto3,oneof"` +} + +type UpdateSegmentRequest_ResetMetadata struct { + ResetMetadata bool `protobuf:"varint,7,opt,name=reset_metadata,json=resetMetadata,proto3,oneof"` +} + +func (*UpdateSegmentRequest_Metadata) isUpdateSegmentRequest_MetadataUpdate() {} + +func (*UpdateSegmentRequest_ResetMetadata) isUpdateSegmentRequest_MetadataUpdate() {} + +type CreateCollectionRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Name string `protobuf:"bytes,2,opt,name=name,proto3" json:"name,omitempty"` + Metadata *UpdateMetadata `protobuf:"bytes,3,opt,name=metadata,proto3,oneof" json:"metadata,omitempty"` + Dimension *int32 `protobuf:"varint,4,opt,name=dimension,proto3,oneof" json:"dimension,omitempty"` + GetOrCreate *bool `protobuf:"varint,5,opt,name=get_or_create,json=getOrCreate,proto3,oneof" json:"get_or_create,omitempty"` + Tenant string `protobuf:"bytes,6,opt,name=tenant,proto3" json:"tenant,omitempty"` + Database string `protobuf:"bytes,7,opt,name=database,proto3" json:"database,omitempty"` +} + +func (x *CreateCollectionRequest) Reset() { + *x = CreateCollectionRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[11] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *CreateCollectionRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*CreateCollectionRequest) ProtoMessage() {} + +func (x *CreateCollectionRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[11] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use CreateCollectionRequest.ProtoReflect.Descriptor instead. +func (*CreateCollectionRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{11} +} + +func (x *CreateCollectionRequest) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *CreateCollectionRequest) GetName() string { + if x != nil { + return x.Name + } + return "" +} + +func (x *CreateCollectionRequest) GetMetadata() *UpdateMetadata { + if x != nil { + return x.Metadata + } + return nil +} + +func (x *CreateCollectionRequest) GetDimension() int32 { + if x != nil && x.Dimension != nil { + return *x.Dimension + } + return 0 +} + +func (x *CreateCollectionRequest) GetGetOrCreate() bool { + if x != nil && x.GetOrCreate != nil { + return *x.GetOrCreate + } + return false +} + +func (x *CreateCollectionRequest) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +func (x *CreateCollectionRequest) GetDatabase() string { + if x != nil { + return x.Database + } + return "" +} + +type CreateCollectionResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Collection *Collection `protobuf:"bytes,1,opt,name=collection,proto3" json:"collection,omitempty"` + Created bool `protobuf:"varint,2,opt,name=created,proto3" json:"created,omitempty"` + Status *Status `protobuf:"bytes,3,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *CreateCollectionResponse) Reset() { + *x = CreateCollectionResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[12] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *CreateCollectionResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*CreateCollectionResponse) ProtoMessage() {} + +func (x *CreateCollectionResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[12] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use CreateCollectionResponse.ProtoReflect.Descriptor instead. +func (*CreateCollectionResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{12} +} + +func (x *CreateCollectionResponse) GetCollection() *Collection { + if x != nil { + return x.Collection + } + return nil +} + +func (x *CreateCollectionResponse) GetCreated() bool { + if x != nil { + return x.Created + } + return false +} + +func (x *CreateCollectionResponse) GetStatus() *Status { + if x != nil { + return x.Status + } + return nil +} + +type DeleteCollectionRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Tenant string `protobuf:"bytes,2,opt,name=tenant,proto3" json:"tenant,omitempty"` + Database string `protobuf:"bytes,3,opt,name=database,proto3" json:"database,omitempty"` +} + +func (x *DeleteCollectionRequest) Reset() { + *x = DeleteCollectionRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[13] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *DeleteCollectionRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*DeleteCollectionRequest) ProtoMessage() {} + +func (x *DeleteCollectionRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[13] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use DeleteCollectionRequest.ProtoReflect.Descriptor instead. +func (*DeleteCollectionRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{13} +} + +func (x *DeleteCollectionRequest) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *DeleteCollectionRequest) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +func (x *DeleteCollectionRequest) GetDatabase() string { + if x != nil { + return x.Database + } + return "" +} + +type GetCollectionsRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id *string `protobuf:"bytes,1,opt,name=id,proto3,oneof" json:"id,omitempty"` + Name *string `protobuf:"bytes,2,opt,name=name,proto3,oneof" json:"name,omitempty"` + Topic *string `protobuf:"bytes,3,opt,name=topic,proto3,oneof" json:"topic,omitempty"` + Tenant string `protobuf:"bytes,4,opt,name=tenant,proto3" json:"tenant,omitempty"` + Database string `protobuf:"bytes,5,opt,name=database,proto3" json:"database,omitempty"` +} + +func (x *GetCollectionsRequest) Reset() { + *x = GetCollectionsRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[14] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetCollectionsRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetCollectionsRequest) ProtoMessage() {} + +func (x *GetCollectionsRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[14] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetCollectionsRequest.ProtoReflect.Descriptor instead. +func (*GetCollectionsRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{14} +} + +func (x *GetCollectionsRequest) GetId() string { + if x != nil && x.Id != nil { + return *x.Id + } + return "" +} + +func (x *GetCollectionsRequest) GetName() string { + if x != nil && x.Name != nil { + return *x.Name + } + return "" +} + +func (x *GetCollectionsRequest) GetTopic() string { + if x != nil && x.Topic != nil { + return *x.Topic + } + return "" +} + +func (x *GetCollectionsRequest) GetTenant() string { + if x != nil { + return x.Tenant + } + return "" +} + +func (x *GetCollectionsRequest) GetDatabase() string { + if x != nil { + return x.Database + } + return "" +} + +type GetCollectionsResponse struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Collections []*Collection `protobuf:"bytes,1,rep,name=collections,proto3" json:"collections,omitempty"` + Status *Status `protobuf:"bytes,2,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *GetCollectionsResponse) Reset() { + *x = GetCollectionsResponse{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[15] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *GetCollectionsResponse) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*GetCollectionsResponse) ProtoMessage() {} + +func (x *GetCollectionsResponse) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[15] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use GetCollectionsResponse.ProtoReflect.Descriptor instead. +func (*GetCollectionsResponse) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{15} +} + +func (x *GetCollectionsResponse) GetCollections() []*Collection { + if x != nil { + return x.Collections + } + return nil +} + +func (x *GetCollectionsResponse) GetStatus() *Status { + if x != nil { + return x.Status + } + return nil +} + +type UpdateCollectionRequest struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id string `protobuf:"bytes,1,opt,name=id,proto3" json:"id,omitempty"` + Topic *string `protobuf:"bytes,2,opt,name=topic,proto3,oneof" json:"topic,omitempty"` + Name *string `protobuf:"bytes,3,opt,name=name,proto3,oneof" json:"name,omitempty"` + Dimension *int32 `protobuf:"varint,4,opt,name=dimension,proto3,oneof" json:"dimension,omitempty"` + // Types that are assignable to MetadataUpdate: + // + // *UpdateCollectionRequest_Metadata + // *UpdateCollectionRequest_ResetMetadata + MetadataUpdate isUpdateCollectionRequest_MetadataUpdate `protobuf_oneof:"metadata_update"` +} + +func (x *UpdateCollectionRequest) Reset() { + *x = UpdateCollectionRequest{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[16] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *UpdateCollectionRequest) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*UpdateCollectionRequest) ProtoMessage() {} + +func (x *UpdateCollectionRequest) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[16] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use UpdateCollectionRequest.ProtoReflect.Descriptor instead. +func (*UpdateCollectionRequest) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{16} +} + +func (x *UpdateCollectionRequest) GetId() string { + if x != nil { + return x.Id + } + return "" +} + +func (x *UpdateCollectionRequest) GetTopic() string { + if x != nil && x.Topic != nil { + return *x.Topic + } + return "" +} + +func (x *UpdateCollectionRequest) GetName() string { + if x != nil && x.Name != nil { + return *x.Name + } + return "" +} + +func (x *UpdateCollectionRequest) GetDimension() int32 { + if x != nil && x.Dimension != nil { + return *x.Dimension + } + return 0 +} + +func (m *UpdateCollectionRequest) GetMetadataUpdate() isUpdateCollectionRequest_MetadataUpdate { + if m != nil { + return m.MetadataUpdate + } + return nil +} + +func (x *UpdateCollectionRequest) GetMetadata() *UpdateMetadata { + if x, ok := x.GetMetadataUpdate().(*UpdateCollectionRequest_Metadata); ok { + return x.Metadata + } + return nil +} + +func (x *UpdateCollectionRequest) GetResetMetadata() bool { + if x, ok := x.GetMetadataUpdate().(*UpdateCollectionRequest_ResetMetadata); ok { + return x.ResetMetadata + } + return false +} + +type isUpdateCollectionRequest_MetadataUpdate interface { + isUpdateCollectionRequest_MetadataUpdate() +} + +type UpdateCollectionRequest_Metadata struct { + Metadata *UpdateMetadata `protobuf:"bytes,5,opt,name=metadata,proto3,oneof"` +} + +type UpdateCollectionRequest_ResetMetadata struct { + ResetMetadata bool `protobuf:"varint,6,opt,name=reset_metadata,json=resetMetadata,proto3,oneof"` +} + +func (*UpdateCollectionRequest_Metadata) isUpdateCollectionRequest_MetadataUpdate() {} + +func (*UpdateCollectionRequest_ResetMetadata) isUpdateCollectionRequest_MetadataUpdate() {} + +type Notification struct { + state protoimpl.MessageState + sizeCache protoimpl.SizeCache + unknownFields protoimpl.UnknownFields + + Id int64 `protobuf:"varint,1,opt,name=id,proto3" json:"id,omitempty"` + CollectionId string `protobuf:"bytes,2,opt,name=collection_id,json=collectionId,proto3" json:"collection_id,omitempty"` + Type string `protobuf:"bytes,3,opt,name=type,proto3" json:"type,omitempty"` + Status string `protobuf:"bytes,4,opt,name=status,proto3" json:"status,omitempty"` +} + +func (x *Notification) Reset() { + *x = Notification{} + if protoimpl.UnsafeEnabled { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[17] + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + ms.StoreMessageInfo(mi) + } +} + +func (x *Notification) String() string { + return protoimpl.X.MessageStringOf(x) +} + +func (*Notification) ProtoMessage() {} + +func (x *Notification) ProtoReflect() protoreflect.Message { + mi := &file_chromadb_proto_coordinator_proto_msgTypes[17] + if protoimpl.UnsafeEnabled && x != nil { + ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) + if ms.LoadMessageInfo() == nil { + ms.StoreMessageInfo(mi) + } + return ms + } + return mi.MessageOf(x) +} + +// Deprecated: Use Notification.ProtoReflect.Descriptor instead. +func (*Notification) Descriptor() ([]byte, []int) { + return file_chromadb_proto_coordinator_proto_rawDescGZIP(), []int{17} +} + +func (x *Notification) GetId() int64 { + if x != nil { + return x.Id + } + return 0 +} + +func (x *Notification) GetCollectionId() string { + if x != nil { + return x.CollectionId + } + return "" +} + +func (x *Notification) GetType() string { + if x != nil { + return x.Type + } + return "" +} + +func (x *Notification) GetStatus() string { + if x != nil { + return x.Status + } + return "" +} + +var File_chromadb_proto_coordinator_proto protoreflect.FileDescriptor + +var 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(*GetDatabaseResponse)(nil), // 2: chroma.GetDatabaseResponse + (*CreateTenantRequest)(nil), // 3: chroma.CreateTenantRequest + (*GetTenantRequest)(nil), // 4: chroma.GetTenantRequest + (*GetTenantResponse)(nil), // 5: chroma.GetTenantResponse + (*CreateSegmentRequest)(nil), // 6: chroma.CreateSegmentRequest + (*DeleteSegmentRequest)(nil), // 7: chroma.DeleteSegmentRequest + (*GetSegmentsRequest)(nil), // 8: chroma.GetSegmentsRequest + (*GetSegmentsResponse)(nil), // 9: chroma.GetSegmentsResponse + (*UpdateSegmentRequest)(nil), // 10: chroma.UpdateSegmentRequest + (*CreateCollectionRequest)(nil), // 11: chroma.CreateCollectionRequest + (*CreateCollectionResponse)(nil), // 12: chroma.CreateCollectionResponse + (*DeleteCollectionRequest)(nil), // 13: chroma.DeleteCollectionRequest + (*GetCollectionsRequest)(nil), // 14: chroma.GetCollectionsRequest + (*GetCollectionsResponse)(nil), // 15: chroma.GetCollectionsResponse + (*UpdateCollectionRequest)(nil), // 16: chroma.UpdateCollectionRequest + (*Notification)(nil), // 17: chroma.Notification + (*Database)(nil), // 18: chroma.Database + (*Status)(nil), // 19: chroma.Status + (*Tenant)(nil), // 20: chroma.Tenant + (*Segment)(nil), // 21: chroma.Segment + (SegmentScope)(0), // 22: chroma.SegmentScope + (*UpdateMetadata)(nil), // 23: chroma.UpdateMetadata + (*Collection)(nil), // 24: chroma.Collection + (*emptypb.Empty)(nil), // 25: google.protobuf.Empty + (*ChromaResponse)(nil), // 26: chroma.ChromaResponse +} +var file_chromadb_proto_coordinator_proto_depIdxs = []int32{ + 18, // 0: chroma.GetDatabaseResponse.database:type_name -> chroma.Database + 19, // 1: chroma.GetDatabaseResponse.status:type_name -> chroma.Status + 20, // 2: chroma.GetTenantResponse.tenant:type_name -> chroma.Tenant + 19, // 3: chroma.GetTenantResponse.status:type_name -> chroma.Status + 21, // 4: chroma.CreateSegmentRequest.segment:type_name -> chroma.Segment + 22, // 5: chroma.GetSegmentsRequest.scope:type_name -> chroma.SegmentScope + 21, // 6: chroma.GetSegmentsResponse.segments:type_name -> chroma.Segment + 19, // 7: chroma.GetSegmentsResponse.status:type_name -> chroma.Status + 23, // 8: chroma.UpdateSegmentRequest.metadata:type_name -> chroma.UpdateMetadata + 23, // 9: chroma.CreateCollectionRequest.metadata:type_name -> chroma.UpdateMetadata + 24, // 10: chroma.CreateCollectionResponse.collection:type_name -> chroma.Collection + 19, // 11: chroma.CreateCollectionResponse.status:type_name -> chroma.Status + 24, // 12: chroma.GetCollectionsResponse.collections:type_name -> chroma.Collection + 19, // 13: chroma.GetCollectionsResponse.status:type_name -> chroma.Status + 23, // 14: chroma.UpdateCollectionRequest.metadata:type_name -> chroma.UpdateMetadata + 0, // 15: chroma.SysDB.CreateDatabase:input_type -> chroma.CreateDatabaseRequest + 1, // 16: chroma.SysDB.GetDatabase:input_type -> chroma.GetDatabaseRequest + 3, // 17: chroma.SysDB.CreateTenant:input_type -> chroma.CreateTenantRequest + 4, // 18: chroma.SysDB.GetTenant:input_type -> chroma.GetTenantRequest + 6, // 19: chroma.SysDB.CreateSegment:input_type -> chroma.CreateSegmentRequest + 7, // 20: chroma.SysDB.DeleteSegment:input_type -> chroma.DeleteSegmentRequest + 8, // 21: chroma.SysDB.GetSegments:input_type -> chroma.GetSegmentsRequest + 10, // 22: chroma.SysDB.UpdateSegment:input_type -> chroma.UpdateSegmentRequest + 11, // 23: chroma.SysDB.CreateCollection:input_type -> chroma.CreateCollectionRequest + 13, // 24: chroma.SysDB.DeleteCollection:input_type -> chroma.DeleteCollectionRequest + 14, // 25: chroma.SysDB.GetCollections:input_type -> chroma.GetCollectionsRequest + 16, // 26: chroma.SysDB.UpdateCollection:input_type -> chroma.UpdateCollectionRequest + 25, // 27: chroma.SysDB.ResetState:input_type -> google.protobuf.Empty + 26, // 28: chroma.SysDB.CreateDatabase:output_type -> chroma.ChromaResponse + 2, // 29: chroma.SysDB.GetDatabase:output_type -> chroma.GetDatabaseResponse + 26, // 30: chroma.SysDB.CreateTenant:output_type -> chroma.ChromaResponse + 5, // 31: chroma.SysDB.GetTenant:output_type -> chroma.GetTenantResponse + 26, // 32: chroma.SysDB.CreateSegment:output_type -> chroma.ChromaResponse + 26, // 33: chroma.SysDB.DeleteSegment:output_type -> chroma.ChromaResponse + 9, // 34: chroma.SysDB.GetSegments:output_type -> chroma.GetSegmentsResponse + 26, // 35: chroma.SysDB.UpdateSegment:output_type -> chroma.ChromaResponse + 12, // 36: chroma.SysDB.CreateCollection:output_type -> chroma.CreateCollectionResponse + 26, // 37: chroma.SysDB.DeleteCollection:output_type -> chroma.ChromaResponse + 15, // 38: chroma.SysDB.GetCollections:output_type -> chroma.GetCollectionsResponse + 26, // 39: chroma.SysDB.UpdateCollection:output_type -> chroma.ChromaResponse + 26, // 40: chroma.SysDB.ResetState:output_type -> chroma.ChromaResponse + 28, // [28:41] is the sub-list for method output_type + 15, // [15:28] is the sub-list for method input_type + 15, // [15:15] is the sub-list for extension type_name + 15, // [15:15] is the sub-list for extension extendee + 0, // [0:15] is the sub-list for field type_name +} + +func init() { file_chromadb_proto_coordinator_proto_init() } +func file_chromadb_proto_coordinator_proto_init() { + if File_chromadb_proto_coordinator_proto != nil { + return + } + file_chromadb_proto_chroma_proto_init() + if !protoimpl.UnsafeEnabled { + file_chromadb_proto_coordinator_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*CreateDatabaseRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetDatabaseRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetDatabaseResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*CreateTenantRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetTenantRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetTenantResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*CreateSegmentRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*DeleteSegmentRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[8].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetSegmentsRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[9].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetSegmentsResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[10].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*UpdateSegmentRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[11].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*CreateCollectionRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[12].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*CreateCollectionResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[13].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*DeleteCollectionRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[14].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetCollectionsRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[15].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*GetCollectionsResponse); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[16].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*UpdateCollectionRequest); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + file_chromadb_proto_coordinator_proto_msgTypes[17].Exporter = func(v interface{}, i int) interface{} { + switch v := v.(*Notification); i { + case 0: + return &v.state + case 1: + return &v.sizeCache + case 2: + return &v.unknownFields + default: + return nil + } + } + } + file_chromadb_proto_coordinator_proto_msgTypes[8].OneofWrappers = []interface{}{} + file_chromadb_proto_coordinator_proto_msgTypes[10].OneofWrappers = []interface{}{ + (*UpdateSegmentRequest_Topic)(nil), + (*UpdateSegmentRequest_ResetTopic)(nil), + (*UpdateSegmentRequest_Collection)(nil), + (*UpdateSegmentRequest_ResetCollection)(nil), + (*UpdateSegmentRequest_Metadata)(nil), + (*UpdateSegmentRequest_ResetMetadata)(nil), + } + file_chromadb_proto_coordinator_proto_msgTypes[11].OneofWrappers = []interface{}{} + file_chromadb_proto_coordinator_proto_msgTypes[14].OneofWrappers = []interface{}{} + file_chromadb_proto_coordinator_proto_msgTypes[16].OneofWrappers = []interface{}{ + (*UpdateCollectionRequest_Metadata)(nil), + (*UpdateCollectionRequest_ResetMetadata)(nil), + } + type x struct{} + out := protoimpl.TypeBuilder{ + File: protoimpl.DescBuilder{ + GoPackagePath: reflect.TypeOf(x{}).PkgPath(), + RawDescriptor: file_chromadb_proto_coordinator_proto_rawDesc, + NumEnums: 0, + NumMessages: 18, + NumExtensions: 0, + NumServices: 1, + }, + GoTypes: file_chromadb_proto_coordinator_proto_goTypes, + DependencyIndexes: file_chromadb_proto_coordinator_proto_depIdxs, + MessageInfos: file_chromadb_proto_coordinator_proto_msgTypes, + }.Build() + File_chromadb_proto_coordinator_proto = out.File + file_chromadb_proto_coordinator_proto_rawDesc = nil + file_chromadb_proto_coordinator_proto_goTypes = nil + file_chromadb_proto_coordinator_proto_depIdxs = nil +} diff --git a/go/coordinator/internal/proto/coordinatorpb/coordinator_grpc.pb.go b/go/coordinator/internal/proto/coordinatorpb/coordinator_grpc.pb.go new file mode 100644 index 0000000000000000000000000000000000000000..ed123f9f3a6f610bcac0b166391c6893c939ec44 --- /dev/null +++ b/go/coordinator/internal/proto/coordinatorpb/coordinator_grpc.pb.go @@ -0,0 +1,554 @@ +// Code generated by protoc-gen-go-grpc. DO NOT EDIT. +// versions: +// - protoc-gen-go-grpc v1.3.0 +// - protoc v4.23.4 +// source: chromadb/proto/coordinator.proto + +package coordinatorpb + +import ( + context "context" + grpc "google.golang.org/grpc" + codes "google.golang.org/grpc/codes" + status "google.golang.org/grpc/status" + emptypb "google.golang.org/protobuf/types/known/emptypb" +) + +// This is a compile-time assertion to ensure that this generated file +// is compatible with the grpc package it is being compiled against. +// Requires gRPC-Go v1.32.0 or later. +const _ = grpc.SupportPackageIsVersion7 + +const ( + SysDB_CreateDatabase_FullMethodName = "/chroma.SysDB/CreateDatabase" + SysDB_GetDatabase_FullMethodName = "/chroma.SysDB/GetDatabase" + SysDB_CreateTenant_FullMethodName = "/chroma.SysDB/CreateTenant" + SysDB_GetTenant_FullMethodName = "/chroma.SysDB/GetTenant" + SysDB_CreateSegment_FullMethodName = "/chroma.SysDB/CreateSegment" + SysDB_DeleteSegment_FullMethodName = "/chroma.SysDB/DeleteSegment" + SysDB_GetSegments_FullMethodName = "/chroma.SysDB/GetSegments" + SysDB_UpdateSegment_FullMethodName = "/chroma.SysDB/UpdateSegment" + SysDB_CreateCollection_FullMethodName = "/chroma.SysDB/CreateCollection" + SysDB_DeleteCollection_FullMethodName = "/chroma.SysDB/DeleteCollection" + SysDB_GetCollections_FullMethodName = "/chroma.SysDB/GetCollections" + SysDB_UpdateCollection_FullMethodName = "/chroma.SysDB/UpdateCollection" + SysDB_ResetState_FullMethodName = "/chroma.SysDB/ResetState" +) + +// SysDBClient is the client API for SysDB service. +// +// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream. +type SysDBClient interface { + CreateDatabase(ctx context.Context, in *CreateDatabaseRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + GetDatabase(ctx context.Context, in *GetDatabaseRequest, opts ...grpc.CallOption) (*GetDatabaseResponse, error) + CreateTenant(ctx context.Context, in *CreateTenantRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + GetTenant(ctx context.Context, in *GetTenantRequest, opts ...grpc.CallOption) (*GetTenantResponse, error) + CreateSegment(ctx context.Context, in *CreateSegmentRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + DeleteSegment(ctx context.Context, in *DeleteSegmentRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + GetSegments(ctx context.Context, in *GetSegmentsRequest, opts ...grpc.CallOption) (*GetSegmentsResponse, error) + UpdateSegment(ctx context.Context, in *UpdateSegmentRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + CreateCollection(ctx context.Context, in *CreateCollectionRequest, opts ...grpc.CallOption) (*CreateCollectionResponse, error) + DeleteCollection(ctx context.Context, in *DeleteCollectionRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + GetCollections(ctx context.Context, in *GetCollectionsRequest, opts ...grpc.CallOption) (*GetCollectionsResponse, error) + UpdateCollection(ctx context.Context, in *UpdateCollectionRequest, opts ...grpc.CallOption) (*ChromaResponse, error) + ResetState(ctx context.Context, in *emptypb.Empty, opts ...grpc.CallOption) (*ChromaResponse, error) +} + +type sysDBClient struct { + cc grpc.ClientConnInterface +} + +func NewSysDBClient(cc grpc.ClientConnInterface) SysDBClient { + return &sysDBClient{cc} +} + +func (c *sysDBClient) CreateDatabase(ctx context.Context, in *CreateDatabaseRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_CreateDatabase_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) GetDatabase(ctx context.Context, in *GetDatabaseRequest, opts ...grpc.CallOption) (*GetDatabaseResponse, error) { + out := new(GetDatabaseResponse) + err := c.cc.Invoke(ctx, SysDB_GetDatabase_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) CreateTenant(ctx context.Context, in *CreateTenantRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_CreateTenant_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) GetTenant(ctx context.Context, in *GetTenantRequest, opts ...grpc.CallOption) (*GetTenantResponse, error) { + out := new(GetTenantResponse) + err := c.cc.Invoke(ctx, SysDB_GetTenant_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) CreateSegment(ctx context.Context, in *CreateSegmentRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_CreateSegment_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) DeleteSegment(ctx context.Context, in *DeleteSegmentRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_DeleteSegment_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) GetSegments(ctx context.Context, in *GetSegmentsRequest, opts ...grpc.CallOption) (*GetSegmentsResponse, error) { + out := new(GetSegmentsResponse) + err := c.cc.Invoke(ctx, SysDB_GetSegments_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) UpdateSegment(ctx context.Context, in *UpdateSegmentRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_UpdateSegment_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) CreateCollection(ctx context.Context, in *CreateCollectionRequest, opts ...grpc.CallOption) (*CreateCollectionResponse, error) { + out := new(CreateCollectionResponse) + err := c.cc.Invoke(ctx, SysDB_CreateCollection_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) DeleteCollection(ctx context.Context, in *DeleteCollectionRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_DeleteCollection_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) GetCollections(ctx context.Context, in *GetCollectionsRequest, opts ...grpc.CallOption) (*GetCollectionsResponse, error) { + out := new(GetCollectionsResponse) + err := c.cc.Invoke(ctx, SysDB_GetCollections_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) UpdateCollection(ctx context.Context, in *UpdateCollectionRequest, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_UpdateCollection_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +func (c *sysDBClient) ResetState(ctx context.Context, in *emptypb.Empty, opts ...grpc.CallOption) (*ChromaResponse, error) { + out := new(ChromaResponse) + err := c.cc.Invoke(ctx, SysDB_ResetState_FullMethodName, in, out, opts...) + if err != nil { + return nil, err + } + return out, nil +} + +// SysDBServer is the server API for SysDB service. +// All implementations must embed UnimplementedSysDBServer +// for forward compatibility +type SysDBServer interface { + CreateDatabase(context.Context, *CreateDatabaseRequest) (*ChromaResponse, error) + GetDatabase(context.Context, *GetDatabaseRequest) (*GetDatabaseResponse, error) + CreateTenant(context.Context, *CreateTenantRequest) (*ChromaResponse, error) + GetTenant(context.Context, *GetTenantRequest) (*GetTenantResponse, error) + CreateSegment(context.Context, *CreateSegmentRequest) (*ChromaResponse, error) + DeleteSegment(context.Context, *DeleteSegmentRequest) (*ChromaResponse, error) + GetSegments(context.Context, *GetSegmentsRequest) (*GetSegmentsResponse, error) + UpdateSegment(context.Context, *UpdateSegmentRequest) (*ChromaResponse, error) + CreateCollection(context.Context, *CreateCollectionRequest) (*CreateCollectionResponse, error) + DeleteCollection(context.Context, *DeleteCollectionRequest) (*ChromaResponse, error) + GetCollections(context.Context, *GetCollectionsRequest) (*GetCollectionsResponse, error) + UpdateCollection(context.Context, *UpdateCollectionRequest) (*ChromaResponse, error) + ResetState(context.Context, *emptypb.Empty) (*ChromaResponse, error) + mustEmbedUnimplementedSysDBServer() +} + +// UnimplementedSysDBServer must be embedded to have forward compatible implementations. +type UnimplementedSysDBServer struct { +} + +func (UnimplementedSysDBServer) CreateDatabase(context.Context, *CreateDatabaseRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method CreateDatabase not implemented") +} +func (UnimplementedSysDBServer) GetDatabase(context.Context, *GetDatabaseRequest) (*GetDatabaseResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method GetDatabase not implemented") +} +func (UnimplementedSysDBServer) CreateTenant(context.Context, *CreateTenantRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method CreateTenant not implemented") +} +func (UnimplementedSysDBServer) GetTenant(context.Context, *GetTenantRequest) (*GetTenantResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method GetTenant not implemented") +} +func (UnimplementedSysDBServer) CreateSegment(context.Context, *CreateSegmentRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method CreateSegment not implemented") +} +func (UnimplementedSysDBServer) DeleteSegment(context.Context, *DeleteSegmentRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method DeleteSegment not implemented") +} +func (UnimplementedSysDBServer) GetSegments(context.Context, *GetSegmentsRequest) (*GetSegmentsResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method GetSegments not implemented") +} +func (UnimplementedSysDBServer) UpdateSegment(context.Context, *UpdateSegmentRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method UpdateSegment not implemented") +} +func (UnimplementedSysDBServer) CreateCollection(context.Context, *CreateCollectionRequest) (*CreateCollectionResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method CreateCollection not implemented") +} +func (UnimplementedSysDBServer) DeleteCollection(context.Context, *DeleteCollectionRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method DeleteCollection not implemented") +} +func (UnimplementedSysDBServer) GetCollections(context.Context, *GetCollectionsRequest) (*GetCollectionsResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method GetCollections not implemented") +} +func (UnimplementedSysDBServer) UpdateCollection(context.Context, *UpdateCollectionRequest) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method UpdateCollection not implemented") +} +func (UnimplementedSysDBServer) ResetState(context.Context, *emptypb.Empty) (*ChromaResponse, error) { + return nil, status.Errorf(codes.Unimplemented, "method ResetState not implemented") +} +func (UnimplementedSysDBServer) mustEmbedUnimplementedSysDBServer() {} + +// UnsafeSysDBServer may be embedded to opt out of forward compatibility for this service. +// Use of this interface is not recommended, as added methods to SysDBServer will +// result in compilation errors. +type UnsafeSysDBServer interface { + mustEmbedUnimplementedSysDBServer() +} + +func RegisterSysDBServer(s grpc.ServiceRegistrar, srv SysDBServer) { + s.RegisterService(&SysDB_ServiceDesc, srv) +} + +func _SysDB_CreateDatabase_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(CreateDatabaseRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).CreateDatabase(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_CreateDatabase_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).CreateDatabase(ctx, req.(*CreateDatabaseRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_GetDatabase_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(GetDatabaseRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).GetDatabase(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_GetDatabase_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).GetDatabase(ctx, req.(*GetDatabaseRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_CreateTenant_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(CreateTenantRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).CreateTenant(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_CreateTenant_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).CreateTenant(ctx, req.(*CreateTenantRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_GetTenant_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(GetTenantRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).GetTenant(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_GetTenant_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).GetTenant(ctx, req.(*GetTenantRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_CreateSegment_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(CreateSegmentRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).CreateSegment(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_CreateSegment_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).CreateSegment(ctx, req.(*CreateSegmentRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_DeleteSegment_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(DeleteSegmentRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).DeleteSegment(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_DeleteSegment_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).DeleteSegment(ctx, req.(*DeleteSegmentRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_GetSegments_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(GetSegmentsRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).GetSegments(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_GetSegments_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).GetSegments(ctx, req.(*GetSegmentsRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_UpdateSegment_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(UpdateSegmentRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).UpdateSegment(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_UpdateSegment_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).UpdateSegment(ctx, req.(*UpdateSegmentRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_CreateCollection_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(CreateCollectionRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).CreateCollection(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_CreateCollection_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).CreateCollection(ctx, req.(*CreateCollectionRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_DeleteCollection_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(DeleteCollectionRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).DeleteCollection(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_DeleteCollection_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).DeleteCollection(ctx, req.(*DeleteCollectionRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_GetCollections_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(GetCollectionsRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).GetCollections(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_GetCollections_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).GetCollections(ctx, req.(*GetCollectionsRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_UpdateCollection_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(UpdateCollectionRequest) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).UpdateCollection(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_UpdateCollection_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).UpdateCollection(ctx, req.(*UpdateCollectionRequest)) + } + return interceptor(ctx, in, info, handler) +} + +func _SysDB_ResetState_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) { + in := new(emptypb.Empty) + if err := dec(in); err != nil { + return nil, err + } + if interceptor == nil { + return srv.(SysDBServer).ResetState(ctx, in) + } + info := &grpc.UnaryServerInfo{ + Server: srv, + FullMethod: SysDB_ResetState_FullMethodName, + } + handler := func(ctx context.Context, req interface{}) (interface{}, error) { + return srv.(SysDBServer).ResetState(ctx, req.(*emptypb.Empty)) + } + return interceptor(ctx, in, info, handler) +} + +// SysDB_ServiceDesc is the grpc.ServiceDesc for SysDB service. +// It's only intended for direct use with grpc.RegisterService, +// and not to be introspected or modified (even as a copy) +var SysDB_ServiceDesc = grpc.ServiceDesc{ + ServiceName: "chroma.SysDB", + HandlerType: (*SysDBServer)(nil), + Methods: []grpc.MethodDesc{ + { + MethodName: "CreateDatabase", + Handler: _SysDB_CreateDatabase_Handler, + }, + { + MethodName: "GetDatabase", + Handler: _SysDB_GetDatabase_Handler, + }, + { + MethodName: "CreateTenant", + Handler: _SysDB_CreateTenant_Handler, + }, + { + MethodName: "GetTenant", + Handler: _SysDB_GetTenant_Handler, + }, + { + MethodName: "CreateSegment", + Handler: _SysDB_CreateSegment_Handler, + }, + { + MethodName: "DeleteSegment", + Handler: _SysDB_DeleteSegment_Handler, + }, + { + MethodName: "GetSegments", + Handler: _SysDB_GetSegments_Handler, + }, + { + MethodName: "UpdateSegment", + Handler: _SysDB_UpdateSegment_Handler, + }, + { + MethodName: "CreateCollection", + Handler: _SysDB_CreateCollection_Handler, + }, + { + MethodName: "DeleteCollection", + Handler: _SysDB_DeleteCollection_Handler, + }, + { + MethodName: "GetCollections", + Handler: _SysDB_GetCollections_Handler, + }, + { + MethodName: "UpdateCollection", + Handler: _SysDB_UpdateCollection_Handler, + }, + { + MethodName: "ResetState", + Handler: _SysDB_ResetState_Handler, + }, + }, + Streams: []grpc.StreamDesc{}, + Metadata: "chromadb/proto/coordinator.proto", +} diff --git a/go/coordinator/internal/types/types.go b/go/coordinator/internal/types/types.go new file mode 100644 index 0000000000000000000000000000000000000000..ee9754c7a154a5820e04a881b4b43b470398f1ab --- /dev/null +++ b/go/coordinator/internal/types/types.go @@ -0,0 +1,58 @@ +package types + +import ( + "math" + + "github.com/google/uuid" +) + +type Timestamp = int64 + +const MaxTimestamp = Timestamp(math.MaxInt64) + +type UniqueID uuid.UUID + +func NewUniqueID() UniqueID { + return UniqueID(uuid.New()) +} + +func (id UniqueID) String() string { + return uuid.UUID(id).String() +} + +func MustParse(s string) UniqueID { + return UniqueID(uuid.MustParse(s)) +} + +func Parse(s string) (UniqueID, error) { + id, err := uuid.Parse(s) + return UniqueID(id), err +} + +func NilUniqueID() UniqueID { + return UniqueID(uuid.Nil) +} + +func ToUniqueID(idString *string) (UniqueID, error) { + if idString != nil { + id, err := Parse(*idString) + if err != nil { + return NilUniqueID(), err + } else { + return id, nil + } + } else { + return NilUniqueID(), nil + } +} + +func FromUniqueID(id UniqueID) *string { + var idStringPointer *string + if id != NilUniqueID() { + idString := id.String() + idStringPointer = &idString + } else { + idStringPointer = nil + } + return idStringPointer +} diff --git a/go/coordinator/internal/utils/integration.go b/go/coordinator/internal/utils/integration.go new file mode 100644 index 0000000000000000000000000000000000000000..44f225d7847310750fb952e09704ec195be3b71d --- /dev/null +++ b/go/coordinator/internal/utils/integration.go @@ -0,0 +1,25 @@ +package utils + +import ( + "os" + "testing" +) + +const environmentVariable = "CHROMA_KUBERNETES_INTEGRATION" + +// ShouldRunTests checks if the tests should be run based on an environment variable. +func ShouldRunIntegrationTests() bool { + // Get the environment variable. + envVarValue := os.Getenv(environmentVariable) + // Return true if the environment variable is set to "true", "yes", or "1". + return envVarValue == "true" || envVarValue == "yes" || envVarValue == "1" +} + +// This helper function can be used to skip tests if the environment variable is not set appropriately. +func RunKubernetesIntegrationTest(t *testing.T, testFunc func(t *testing.T)) { + if ShouldRunIntegrationTests() { + testFunc(t) + } else { + t.Skipf("Skipping test because environment variable %s is not set to run tests", environmentVariable) + } +} diff --git a/go/coordinator/internal/utils/kubernetes.go b/go/coordinator/internal/utils/kubernetes.go new file mode 100644 index 0000000000000000000000000000000000000000..b2784cbf46235d062056b6d2a81e9339a5e2326a --- /dev/null +++ b/go/coordinator/internal/utils/kubernetes.go @@ -0,0 +1,50 @@ +package utils + +import ( + "k8s.io/client-go/dynamic" + "k8s.io/client-go/kubernetes" + "k8s.io/client-go/kubernetes/fake" + "k8s.io/client-go/rest" +) + +func GetTestKubenertesInterface() (kubernetes.Interface, error) { + clientset := fake.NewSimpleClientset() + return clientset, nil +} + +func getKubernetesConfig() (*rest.Config, error) { + config, err := rest.InClusterConfig() + if err != nil { + return nil, err + } + return config, nil + +} + +func GetKubernetesDynamicInterface() (dynamic.Interface, error) { + clientConfig, err := getKubernetesConfig() + if err != nil { + return nil, err + } + + // Create the dynamic client for the memberlist custom resource + dynamic_client, err := dynamic.NewForConfig(clientConfig) + if err != nil { + panic(err.Error()) + } + return dynamic_client, nil +} + +func GetKubernetesInterface() (kubernetes.Interface, error) { + config, err := getKubernetesConfig() + if err != nil { + return nil, err + } + // Create a clientset for the coordinator + clientset, err := kubernetes.NewForConfig(config) + if err != nil { + return nil, err + } + + return clientset, nil +} diff --git a/go/coordinator/internal/utils/log.go b/go/coordinator/internal/utils/log.go new file mode 100644 index 0000000000000000000000000000000000000000..9026179a9262643688375b57a44430b4aeb39acc --- /dev/null +++ b/go/coordinator/internal/utils/log.go @@ -0,0 +1,51 @@ +package utils + +import ( + "encoding/json" + "os" + "time" + + "github.com/rs/zerolog" + "github.com/rs/zerolog/log" + "github.com/rs/zerolog/pkgerrors" + "google.golang.org/protobuf/encoding/protojson" + pb "google.golang.org/protobuf/proto" +) + +const DefaultLogLevel = zerolog.InfoLevel + +var ( + // LogLevel Used for flags + LogLevel zerolog.Level + // LogJson Used for flags + LogJson bool +) + +func ConfigureLogger() { + zerolog.TimeFieldFormat = time.RFC3339Nano + zerolog.ErrorStackMarshaler = pkgerrors.MarshalStack + + protoMarshal := protojson.MarshalOptions{ + EmitUnpopulated: true, + } + zerolog.InterfaceMarshalFunc = func(i any) ([]byte, error) { + if m, ok := i.(pb.Message); ok { + return protoMarshal.Marshal(m) + } + return json.Marshal(i) + } + + log.Logger = zerolog.New(os.Stdout). + With(). + Timestamp(). + Stack(). + Logger() + + if !LogJson { + log.Logger = log.Output(zerolog.ConsoleWriter{ + Out: os.Stdout, + TimeFormat: time.StampMicro, + }) + } + zerolog.SetGlobalLevel(LogLevel) +} diff --git a/go/coordinator/internal/utils/pulsar_admin.go b/go/coordinator/internal/utils/pulsar_admin.go new file mode 100644 index 0000000000000000000000000000000000000000..c8258ecbf54c67efd30443a6d9060444daff4a59 --- /dev/null +++ b/go/coordinator/internal/utils/pulsar_admin.go @@ -0,0 +1,44 @@ +package utils + +import ( + "github.com/pingcap/log" + "go.uber.org/zap" + + "github.com/apache/pulsar-client-go/pulsaradmin" + pulsar_utils "github.com/apache/pulsar-client-go/pulsaradmin/pkg/utils" +) + +// This function creates topics in Pulsar. It takes in a list of topics and creates them in pulsar. +// It assumes that the tenant and namespace already exist in Pulsar. +func CreateTopics(pulsarAdminURL string, tenant string, namespace string, topics []string) error { + cfg := &pulsaradmin.Config{ + WebServiceURL: pulsarAdminURL, + } + admin, err := pulsaradmin.NewClient(cfg) + if err != nil { + log.Error("Failed to create pulsar admin client", zap.Error(err)) + return err + } + + for _, topic := range topics { + topicSchema := "persistent://" + tenant + "/" + namespace + "/" + topic + topicName, err := pulsar_utils.GetTopicName(topicSchema) + if err != nil { + log.Error("Failed to get topic name", zap.Error(err)) + return err + } + metadata, err := admin.Topics().GetMetadata(*topicName) + if err != nil { + log.Info("Failed to get topic metadata, needs to create", zap.Error(err)) + } else { + log.Info("Topic already exists", zap.String("topic", topic), zap.Any("metadata", metadata)) + continue + } + err = admin.Topics().Create(*topicName, 0) + if err != nil { + log.Error("Failed to create topic", zap.Error(err)) + return err + } + } + return nil +} diff --git a/go/coordinator/internal/utils/rendezvous_hash.go b/go/coordinator/internal/utils/rendezvous_hash.go new file mode 100644 index 0000000000000000000000000000000000000000..374d78594cba9346e3ff1b2d49caae4c20d4cd01 --- /dev/null +++ b/go/coordinator/internal/utils/rendezvous_hash.go @@ -0,0 +1,62 @@ +package utils + +import ( + "errors" + + "github.com/spaolacci/murmur3" +) + +type Hasher = func(member string, key string) uint64 +type Member = string +type Members = []Member +type Key = string + +// assign assigns a key to a member using the rendezvous hashing algorithm. +func Assign(key Key, members Members, hasher Hasher) (Member, error) { + if len(members) == 0 { + return "", errors.New("cannot assign key to empty member list") + } + if len(members) == 1 { + return members[0], nil + } + if key == "" { + return "", errors.New("cannot assign empty key") + } + + maxScore := uint64(0) + var maxMember Member + + for _, member := range members { + score := hasher(string(member), string(key)) + if score > maxScore { + maxScore = score + maxMember = member + } + } + + return maxMember, nil +} + +func mergeHashes(a uint64, b uint64) uint64 { + acc := a ^ b + acc ^= acc >> 33 + acc *= 0xff51afd7ed558ccd + acc ^= acc >> 33 + acc *= 0xc4ceb9fe1a85ec53 + acc ^= acc >> 33 + return acc +} + +// NOTE: The python implementation of murmur3 may differ from the golang implementation. +// For now, this is fine since go and python don't need to agree on any hashing schemes +// but if we ever need to agree on a hashing scheme, we should verify that the implementations +// are the same. +func Murmur3Hasher(member string, key string) uint64 { + hasher := murmur3.New64() + hasher.Write([]byte(member)) + memberHash := hasher.Sum64() + hasher.Reset() + hasher.Write([]byte(key)) + keyHash := hasher.Sum64() + return mergeHashes(memberHash, keyHash) +} diff --git a/go/coordinator/internal/utils/rendezvous_hash_test.go b/go/coordinator/internal/utils/rendezvous_hash_test.go new file mode 100644 index 0000000000000000000000000000000000000000..282e7ca286b60aa8160111004f1cbdb418b0515f --- /dev/null +++ b/go/coordinator/internal/utils/rendezvous_hash_test.go @@ -0,0 +1,62 @@ +package utils + +import ( + "fmt" + "math" + "testing" +) + +func mockHasher(member string, key string) uint64 { + members := []string{"a", "b", "c"} + for i, m := range members { + if m == member { + return uint64(i) + } + } + return 0 +} + +func TestRendezvousHash(t *testing.T) { + members := []string{"a", "b", "c"} + key := "key" + + // Test that the assign function returns the expected result + node, error := Assign(key, members, mockHasher) + + if error != nil { + t.Errorf("Assign() returned an error: %v", error) + } + + if node != "c" { + t.Errorf("Assign() = %v, want %v", node, "c") + } +} + +func TestEvenDistribution(t *testing.T) { + memberCount := 10 + tolerance := 25 + var nodes []string + for i := 0; i < memberCount; i++ { + nodes = append(nodes, fmt.Sprint(i+'0')) // Convert int to string + } + + keyDistribution := make(map[string]int) + numKeys := 1000 + + // Test if keys are evenly distributed across nodes + for i := 0; i < numKeys; i++ { + key := "key_" + fmt.Sprint(i) + node, err := Assign(key, nodes, Murmur3Hasher) + if err != nil { + t.Errorf("Assign() returned an error: %v", err) + } + keyDistribution[node]++ + } + + // Check if keys are somewhat evenly distributed + for _, count := range keyDistribution { + if math.Abs(float64(count-numKeys/memberCount)) > float64(tolerance) { + t.Errorf("Key distribution is uneven: %v", keyDistribution) + } + } +} diff --git a/go/coordinator/internal/utils/run.go b/go/coordinator/internal/utils/run.go new file mode 100644 index 0000000000000000000000000000000000000000..f0ab638969d04cace7af5bd0f5d6340e846d097d --- /dev/null +++ b/go/coordinator/internal/utils/run.go @@ -0,0 +1,19 @@ +package utils + +import ( + "io" + + "github.com/rs/zerolog/log" +) + +func RunProcess(startProcess func() (io.Closer, error)) { + process, err := startProcess() + if err != nil { + log.Fatal().Err(err). + Msg("Failed to start the process") + } + + WaitUntilSignal( + process, + ) +} diff --git a/go/coordinator/internal/utils/signal.go b/go/coordinator/internal/utils/signal.go new file mode 100644 index 0000000000000000000000000000000000000000..88b1faba95af7de4d7c4e3632b4f3c86493dde61 --- /dev/null +++ b/go/coordinator/internal/utils/signal.go @@ -0,0 +1,35 @@ +package utils + +import ( + "io" + "os" + "os/signal" + "syscall" + + "github.com/rs/zerolog/log" +) + +func WaitUntilSignal(closers ...io.Closer) { + c := make(chan os.Signal, 1) + signal.Notify(c, os.Interrupt, syscall.SIGTERM) + + sig := <-c + log.Info(). + Str("signal", sig.String()). + Msg("Received signal, exiting") + + code := 0 + for _, closer := range closers { + if err := closer.Close(); err != nil { + log.Error(). + Err(err). + Msg("Failed when shutting down server") + os.Exit(1) + } + } + + if code == 0 { + log.Info().Msg("Shutdown Completed") + } + os.Exit(code) +} diff --git a/go/coordinator/migrations/20231116210409.sql b/go/coordinator/migrations/20231116210409.sql new file mode 100644 index 0000000000000000000000000000000000000000..bb9c8d8a00c4204426ca24546841cb15999be37c --- /dev/null +++ b/go/coordinator/migrations/20231116210409.sql @@ -0,0 +1,74 @@ +-- Create "collection_metadata" table +CREATE TABLE "public"."collection_metadata" ( + "collection_id" text NOT NULL, + "key" text NOT NULL, + "str_value" text NULL, + "int_value" bigint NULL, + "float_value" numeric NULL, + "ts" bigint NULL DEFAULT 0, + "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updated_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + PRIMARY KEY ("collection_id", "key") +); +-- Create "collections" table +CREATE TABLE "public"."collections" ( + "id" text NOT NULL, + "name" text NULL, + "topic" text NULL, + "dimension" integer NULL, + "database_id" text NULL, + "ts" bigint NULL DEFAULT 0, + "is_deleted" boolean NULL DEFAULT false, + "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updated_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + PRIMARY KEY ("id") +); +-- Create index "collections_name_key" to table: "collections" +CREATE UNIQUE INDEX "collections_name_key" ON "public"."collections" ("name"); +-- Create "databases" table +CREATE TABLE "public"."databases" ( + "id" text NOT NULL, + "name" character varying(128) NULL, + "tenant_id" character varying(128) NULL, + "ts" bigint NULL DEFAULT 0, + "is_deleted" boolean NULL DEFAULT false, + "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updated_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + PRIMARY KEY ("id") +); +-- Create index "idx_tenantid_name" to table: "databases" +CREATE UNIQUE INDEX "idx_tenantid_name" ON "public"."databases" ("name", "tenant_id"); +-- Create "segment_metadata" table +CREATE TABLE "public"."segment_metadata" ( + "segment_id" text NOT NULL, + "key" text NOT NULL, + "str_value" text NULL, + "int_value" bigint NULL, + "float_value" numeric NULL, + "ts" bigint NULL DEFAULT 0, + "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updated_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + PRIMARY KEY ("segment_id", "key") +); +-- Create "segments" table +CREATE TABLE "public"."segments" ( + "id" text NOT NULL, + "type" text NOT NULL, + "scope" text NULL, + "topic" text NULL, + "ts" bigint NULL DEFAULT 0, + "is_deleted" boolean NULL DEFAULT false, + "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updated_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "collection_id" text NULL, + PRIMARY KEY ("id") +); +-- Create "tenants" table +CREATE TABLE "public"."tenants" ( + "id" text NOT NULL, + "ts" bigint NULL DEFAULT 0, + "is_deleted" boolean NULL DEFAULT false, + "created_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + "updated_at" timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, + PRIMARY KEY ("id") +); diff --git a/go/coordinator/migrations/20231129183041.sql b/go/coordinator/migrations/20231129183041.sql new file mode 100644 index 0000000000000000000000000000000000000000..2a31ebb48778466cc4bdbe68ad0f9d372ff27f94 --- /dev/null +++ b/go/coordinator/migrations/20231129183041.sql @@ -0,0 +1,8 @@ +-- Create "notifications" table +CREATE TABLE "public"."notifications" ( + "id" bigserial NOT NULL, + "collection_id" text NULL, + "type" text NULL, + "status" text NULL, + PRIMARY KEY ("id") +); diff --git a/go/coordinator/migrations/atlas.sum b/go/coordinator/migrations/atlas.sum new file mode 100644 index 0000000000000000000000000000000000000000..d4ee513fa90418f4b7f8898e1fb3960ea8a39f2b --- /dev/null +++ b/go/coordinator/migrations/atlas.sum @@ -0,0 +1,3 @@ +h1:j28ectYxexGfQz/LClD7yYVUHAfIcPHlboAJ1Qw0G7I= +20231116210409.sql h1:vwZRvrXrUMOuDykEaheyEzsnNCpmH73x0QEefzUtf8o= +20231129183041.sql h1:FglI5Hjf7kqvjCsSYWkK2IGS2aThQBaVhpg9WekhNEA= diff --git a/idl/chromadb/proto/chroma.proto b/idl/chromadb/proto/chroma.proto new file mode 100644 index 0000000000000000000000000000000000000000..5676c0efb745063a283aa37263a058418779e06a --- /dev/null +++ b/idl/chromadb/proto/chroma.proto @@ -0,0 +1,136 @@ +syntax = "proto3"; + +package chroma; + +option go_package = "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb"; + +message Status { + string reason = 1; + int32 code = 2; // TODO: What is the enum of this code? +} + +message ChromaResponse { + Status status = 1; +} + +// Types here should mirror chromadb/types.py + +enum Operation { + ADD = 0; + UPDATE = 1; + UPSERT = 2; + DELETE = 3; +} + +enum ScalarEncoding { + FLOAT32 = 0; + INT32 = 1; +} + +message Vector { + int32 dimension = 1; + bytes vector = 2; + ScalarEncoding encoding = 3; +} + +enum SegmentScope { + VECTOR = 0; + METADATA = 1; +} + +message Segment { + string id = 1; + string type = 2; + SegmentScope scope = 3; + optional string topic = 4; // TODO should channel <> segment binding exist here? + // If a segment has a collection, it implies that this segment implements the full + // collection and can be used to service queries (for it's given scope.) + optional string collection = 5; + optional UpdateMetadata metadata = 6; +} + +message Collection { + string id = 1; + string name = 2; + string topic = 3; + optional UpdateMetadata metadata = 4; + optional int32 dimension = 5; + string tenant = 6; + string database = 7; +} + +message Database { + string id = 1; + string name = 2; + string tenant = 3; +} + +message Tenant { + string name = 1; +} + +message UpdateMetadataValue { + oneof value { + string string_value = 1; + int64 int_value = 2; + double float_value = 3; + } +} + +message UpdateMetadata { + map metadata = 1; +} + +message SubmitEmbeddingRecord { + string id = 1; + optional Vector vector = 2; + optional UpdateMetadata metadata = 3; + Operation operation = 4; + string collection_id = 5; +} + +message VectorEmbeddingRecord { + string id = 1; + bytes seq_id = 2; + Vector vector = 3; // TODO: we need to rethink source of truth for vector dimensionality and encoding +} + +message VectorQueryResult { + string id = 1; + bytes seq_id = 2; + float distance = 3; + optional Vector vector = 4; +} + +message VectorQueryResults { + repeated VectorQueryResult results = 1; +} + +/* Vector Reader Interface */ + +service VectorReader { + rpc GetVectors(GetVectorsRequest) returns (GetVectorsResponse) {} + rpc QueryVectors(QueryVectorsRequest) returns (QueryVectorsResponse) {} +} + +message GetVectorsRequest { + repeated string ids = 1; + string segment_id = 2; +} + +message GetVectorsResponse { + repeated VectorEmbeddingRecord records = 1; +} + +message QueryVectorsRequest { + repeated Vector vectors = 1; + int32 k = 2; + repeated string allowed_ids = 3; + bool include_embeddings = 4; + string segment_id = 5; + // TODO: options as in types.py, its currently unused so can add later +} + +message QueryVectorsResponse { + repeated VectorQueryResults results = 1; +} diff --git a/idl/chromadb/proto/coordinator.proto b/idl/chromadb/proto/coordinator.proto new file mode 100644 index 0000000000000000000000000000000000000000..79abd73acf69ba201b3b2d9cbff900c15abfa29f --- /dev/null +++ b/idl/chromadb/proto/coordinator.proto @@ -0,0 +1,144 @@ +syntax = "proto3"; + +package chroma; +option go_package = "github.com/chroma/chroma-coordinator/internal/proto/coordinatorpb"; + +import "chromadb/proto/chroma.proto"; +import "google/protobuf/empty.proto"; + +message CreateDatabaseRequest { + string id = 1; + string name = 2; + string tenant = 3; +} + +message GetDatabaseRequest { + string name = 1; + string tenant = 2; +} + +message GetDatabaseResponse { + Database database = 1; + Status status = 2; +} + +message CreateTenantRequest { + string name = 2; // Names are globally unique +} + +message GetTenantRequest { + string name = 1; +} + +message GetTenantResponse { + Tenant tenant = 1; + Status status = 2; +} + + +message CreateSegmentRequest { + Segment segment = 1; +} + +message DeleteSegmentRequest { + string id = 1; +} + +message GetSegmentsRequest { + optional string id = 1; + optional string type = 2; + optional SegmentScope scope = 3; + optional string topic = 4; + optional string collection = 5; // Collection ID +} + +message GetSegmentsResponse { + repeated Segment segments = 1; + Status status = 2; +} + + +message UpdateSegmentRequest { + string id = 1; + oneof topic_update { + string topic = 2; + bool reset_topic = 3; + } + oneof collection_update { + string collection = 4; + bool reset_collection = 5; + } + oneof metadata_update { + UpdateMetadata metadata = 6; + bool reset_metadata = 7; + } +} + +message CreateCollectionRequest { + string id = 1; + string name = 2; + optional UpdateMetadata metadata = 3; + optional int32 dimension = 4; + optional bool get_or_create = 5; + string tenant = 6; + string database = 7; +} + +message CreateCollectionResponse { + Collection collection = 1; + bool created = 2; + Status status = 3; +} + +message DeleteCollectionRequest { + string id = 1; + string tenant = 2; + string database = 3; +} + +message GetCollectionsRequest { + optional string id = 1; + optional string name = 2; + optional string topic = 3; + string tenant = 4; + string database = 5; +} + +message GetCollectionsResponse { + repeated Collection collections = 1; + Status status = 2; +} + +message UpdateCollectionRequest { + string id = 1; + optional string topic = 2; + optional string name = 3; + optional int32 dimension = 4; + oneof metadata_update { + UpdateMetadata metadata = 5; + bool reset_metadata = 6; + } +} + +message Notification { + int64 id = 1; + string collection_id = 2; + string type = 3; + string status = 4; +} + +service SysDB { + rpc CreateDatabase(CreateDatabaseRequest) returns (ChromaResponse) {} + rpc GetDatabase(GetDatabaseRequest) returns (GetDatabaseResponse) {} + rpc CreateTenant(CreateTenantRequest) returns (ChromaResponse) {} + rpc GetTenant(GetTenantRequest) returns (GetTenantResponse) {} + rpc CreateSegment(CreateSegmentRequest) returns (ChromaResponse) {} + rpc DeleteSegment(DeleteSegmentRequest) returns (ChromaResponse) {} + rpc GetSegments(GetSegmentsRequest) returns (GetSegmentsResponse) {} + rpc UpdateSegment(UpdateSegmentRequest) returns (ChromaResponse) {} + rpc CreateCollection(CreateCollectionRequest) returns (CreateCollectionResponse) {} + rpc DeleteCollection(DeleteCollectionRequest) returns (ChromaResponse) {} + rpc GetCollections(GetCollectionsRequest) returns (GetCollectionsResponse) {} + rpc UpdateCollection(UpdateCollectionRequest) returns (ChromaResponse) {} + rpc ResetState(google.protobuf.Empty) returns (ChromaResponse) {} +} diff --git a/idl/makefile b/idl/makefile new file mode 100644 index 0000000000000000000000000000000000000000..18cbc1977ba4a62f75c8de9dbdde370028f42815 --- /dev/null +++ b/idl/makefile @@ -0,0 +1,22 @@ +.PHONY: proto + +proto_python: + @echo "Generating gRPC code for python..." + @python -m grpc_tools.protoc -I ./ --python_out=. --pyi_out=. --grpc_python_out=. ./chromadb/proto/*.proto + @mv chromadb/proto/*.py ../chromadb/proto/ + @mv chromadb/proto/*.pyi ../chromadb/proto/ + @echo "Done" + +proto_go: + @echo "Generating gRPC code for golang..." + @protoc \ + --go_out=../go/coordinator/internal/proto/coordinatorpb \ + --go_opt paths=source_relative \ + --plugin protoc-gen-go="${GOPATH}/bin/protoc-gen-go" \ + --go-grpc_out=../go/coordinator/internal/proto/coordinatorpb \ + --go-grpc_opt paths=source_relative \ + --plugin protoc-gen-go-grpc="${GOPATH}/bin/protoc-gen-go-grpc" \ + chromadb/proto/*.proto + @mv ../go/coordinator/internal/proto/coordinatorpb/chromadb/proto/*.go ../go/coordinator/internal/proto/coordinatorpb/ + @rm -rf ../go/coordinator/internal/proto/coordinatorpb/chromadb + @echo "Done" diff --git a/k8s/WARNING.md b/k8s/WARNING.md new file mode 100644 index 0000000000000000000000000000000000000000..7933f8a712a1437279d7140656b41033acd32724 --- /dev/null +++ b/k8s/WARNING.md @@ -0,0 +1,3 @@ +# These kubernetes manifests are UNDER ACTIVE DEVELOPMENT and are not yet ready for production use. +# They will be used for the upcoming distributed version of chroma. They are not even ready +# for testing yet. Please do not use them unless you are working on the distributed version of chroma. diff --git a/k8s/cr/worker_memberlist_cr.yaml b/k8s/cr/worker_memberlist_cr.yaml new file mode 100644 index 0000000000000000000000000000000000000000..bc4df07f535742dd098f98d985fb7e9f3b8b51f8 --- /dev/null +++ b/k8s/cr/worker_memberlist_cr.yaml @@ -0,0 +1,48 @@ +# These kubernetes manifests are UNDER ACTIVE DEVELOPMENT and are not yet ready for production use. +# They will be used for the upcoming distributed version of chroma. They are not even ready +# for testing yet. Please do not use them unless you are working on the distributed version of chroma. + +# Create a memberlist called worker-memberlist +apiVersion: chroma.cluster/v1 +kind: MemberList +metadata: + name: worker-memberlist + namespace: chroma +spec: + members: + +--- + +apiVersion: rbac.authorization.k8s.io/v1 +kind: ClusterRole +metadata: + name: worker-memberlist-reader +rules: +- apiGroups: + - chroma.cluster + resources: + - memberlists + verbs: + - get + - list + - watch + # TODO: FIX THIS LEAKY PERMISSION + - create + - update + - patch + - delete + +--- + +apiVersion: rbac.authorization.k8s.io/v1 +kind: ClusterRoleBinding +metadata: + name: worker-memberlist-reader-binding +roleRef: + apiGroup: rbac.authorization.k8s.io + kind: ClusterRole + name: worker-memberlist-reader +subjects: +- kind: ServiceAccount + name: default + namespace: chroma diff --git a/k8s/crd/memberlist_crd.yaml b/k8s/crd/memberlist_crd.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9d31706aad21a8eda9340ea71ea3940bb29e1ac8 --- /dev/null +++ b/k8s/crd/memberlist_crd.yaml @@ -0,0 +1,36 @@ +# These kubernetes manifests are UNDER ACTIVE DEVELOPMENT and are not yet ready for production use. +# They will be used for the upcoming distributed version of chroma. They are not even ready +# for testing yet. Please do not use them unless you are working on the distributed version of chroma. + +apiVersion: apiextensions.k8s.io/v1 +kind: CustomResourceDefinition +metadata: + name: memberlists.chroma.cluster +spec: + group: chroma.cluster + versions: + - name: v1 + served: true + storage: true + schema: + openAPIV3Schema: + type: object + properties: + spec: + type: object + properties: + members: + type: array + items: + type: object + properties: + url: # Rename to ip + type: string + pattern: '^((25[0-5]|(2[0-4]|1\d|[1-9]|)\d)\.?\b){4}$' + scope: Namespaced + names: + plural: memberlists + singular: memberlist + kind: MemberList + shortNames: + - ml diff --git a/k8s/deployment/kubernetes.yaml b/k8s/deployment/kubernetes.yaml new file mode 100644 index 0000000000000000000000000000000000000000..b1f9baabdd0b1d16fc915490b2698df02e71e119 --- /dev/null +++ b/k8s/deployment/kubernetes.yaml @@ -0,0 +1,221 @@ +# These kubernetes manifests are UNDER ACTIVE DEVELOPMENT and are not yet ready for production use. +# They will be used for the upcoming distributed version of chroma. They are not even ready +# for testing yet. Please do not use them unless you are working on the distributed version of chroma. + +apiVersion: v1 +kind: Namespace +metadata: + name: chroma + +--- + +apiVersion: v1 +kind: Service +metadata: + name: pulsar + namespace: chroma +spec: + ports: + - name: pulsar-port + port: 6650 + targetPort: 6650 + - name: admin-port + port: 8080 + targetPort: 8080 + selector: + app: pulsar + type: ClusterIP + +--- + +# TODO: Should be stateful set locally or managed via terraform into streamnative for cloud deployment +apiVersion: apps/v1 +kind: Deployment +metadata: + name: pulsar + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: pulsar + template: + metadata: + labels: + app: pulsar + spec: + containers: + - name: pulsar + image: apachepulsar/pulsar + command: [ "/pulsar/bin/pulsar", "standalone" ] + env: + # This is needed by github actions. We force this to be lower everywehre for now. + # Since real deployments will configure/use pulsar this way. + - name: PULSAR_MEM + value: "-Xms128m -Xmx512m" + ports: + - containerPort: 6650 + - containerPort: 8080 + volumeMounts: + - name: pulsardata + mountPath: /pulsar/data + # readinessProbe: + # httpGet: + # path: /admin/v2/brokers/health + # port: 8080 + # initialDelaySeconds: 10 + # periodSeconds: 5 + # livenessProbe: + # httpGet: + # path: /admin/v2/brokers/health + # port: 8080 + # initialDelaySeconds: 20 + # periodSeconds: 10 + volumes: + - name: pulsardata + emptyDir: {} + +--- + +apiVersion: v1 +kind: Service +metadata: + name: server + namespace: chroma +spec: + ports: + - name: server + port: 8000 + targetPort: 8000 + selector: + app: server + type: LoadBalancer + +--- + +apiVersion: apps/v1 +kind: Deployment +metadata: + name: server + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: server + template: + metadata: + labels: + app: server + spec: + containers: + - name: server + image: server + imagePullPolicy: IfNotPresent + ports: + - containerPort: 8000 + volumeMounts: + - name: chroma + mountPath: /test + env: + - name: IS_PERSISTENT + value: "TRUE" + - name: CHROMA_PRODUCER_IMPL + value: "chromadb.ingest.impl.pulsar.PulsarProducer" + - name: CHROMA_CONSUMER_IMPL + value: "chromadb.ingest.impl.pulsar.PulsarConsumer" + - name: CHROMA_SEGMENT_MANAGER_IMPL + value: "chromadb.segment.impl.manager.distributed.DistributedSegmentManager" + - name: PULSAR_BROKER_URL + value: "pulsar.chroma" + - name: PULSAR_BROKER_PORT + value: "6650" + - name: PULSAR_ADMIN_PORT + value: "8080" + - name: ALLOW_RESET + value: "TRUE" + - name: CHROMA_SYSDB_IMPL + value: "chromadb.db.impl.grpc.client.GrpcSysDB" + - name: CHROMA_SERVER_GRPC_PORT + value: "50051" + - name: CHROMA_COORDINATOR_HOST + value: "coordinator.chroma" + readinessProbe: + httpGet: + path: /api/v1/heartbeat + port: 8000 + initialDelaySeconds: 10 + periodSeconds: 5 + # livenessProbe: + # httpGet: + # path: /healthz + # port: 8000 + # initialDelaySeconds: 20 + # periodSeconds: 10 + # Ephemeral for now + volumes: + - name: chroma + emptyDir: {} + +--- + +# apiVersion: v1 +# kind: PersistentVolumeClaim +# metadata: +# name: index-data +# namespace: chroma +# spec: +# accessModes: +# - ReadWriteOnce +# resources: +# requests: +# storage: 1Gi + +apiVersion: apps/v1 +kind: Deployment +metadata: + name: coordinator + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: coordinator + template: + metadata: + labels: + app: coordinator + spec: + containers: + - command: + - "chroma" + - "coordinator" + - "--pulsar-admin-url=http://pulsar.chroma:8080" + - "--pulsar-url=pulsar://pulsar.chroma:6650" + - "--notifier-provider=pulsar" + image: chroma-coordinator + imagePullPolicy: IfNotPresent + name: coordinator + ports: + - containerPort: 50051 + name: grpc + resources: + limits: + cpu: 100m + memory: 128Mi + +--- + +apiVersion: v1 +kind: Service +metadata: + name: coordinator + namespace: chroma +spec: + ports: + - name: grpc + port: 50051 + targetPort: grpc + selector: + app: coordinator + type: ClusterIP diff --git a/k8s/deployment/segment-server.yaml b/k8s/deployment/segment-server.yaml new file mode 100644 index 0000000000000000000000000000000000000000..33af91d13141d132ad86c3faec6d57d753488e0a --- /dev/null +++ b/k8s/deployment/segment-server.yaml @@ -0,0 +1,87 @@ +apiVersion: v1 +kind: Service +metadata: + name: segment-server + namespace: chroma +spec: + ports: + - name: segment-server-port + port: 50051 + targetPort: 50051 + selector: + app: segment-server + type: ClusterIP + +--- + +apiVersion: apps/v1 +kind: Deployment +metadata: + name: segment-server + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: segment-server + template: + metadata: + labels: + app: segment-server + member-type: worker + spec: + containers: + - name: segment-server + image: worker + imagePullPolicy: IfNotPresent + command: ["cargo", "run"] + ports: + - containerPort: 50051 + volumeMounts: + - name: chroma + mountPath: /index_data + env: + - name: CHROMA_WORKER__PULSAR_URL + value: pulsar://pulsar.chroma:6650 + - name: CHROMA_WORKER__PULSAR_NAMESPACE + value: default + - name: CHROMA_WORKER__PULSAR_TENANT + value: default + - name: CHROMA_WORKER__MY_IP + valueFrom: + fieldRef: + fieldPath: status.podIP + # livenessProbe: + # grpc: + # port: 50051 + # initialDelaySeconds: 10 + volumes: + - name: chroma + emptyDir: {} + +--- + +apiVersion: rbac.authorization.k8s.io/v1 +kind: Role +metadata: + namespace: chroma + name: pod-watcher +rules: +- apiGroups: [""] + resources: ["pods"] + verbs: ["get", "list", "watch"] + +--- +apiVersion: rbac.authorization.k8s.io/v1 +kind: RoleBinding +metadata: + name: pod-watcher-binding + namespace: chroma +subjects: +- kind: ServiceAccount + name: default + namespace: chroma +roleRef: + kind: Role + name: pod-watcher + apiGroup: rbac.authorization.k8s.io diff --git a/k8s/dev/coordinator.yaml b/k8s/dev/coordinator.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ce897d44c82b500430a14476ac13aa830978c67c --- /dev/null +++ b/k8s/dev/coordinator.yaml @@ -0,0 +1,42 @@ +apiVersion: apps/v1 +kind: Deployment +metadata: + name: coordinator + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: coordinator + template: + metadata: + labels: + app: coordinator + spec: + containers: + - command: + - "chroma" + - "coordinator" + - "--pulsar-admin-url=http://pulsar.chroma:8080" + - "--pulsar-url=pulsar://pulsar.chroma:6650" + - "--notifier-provider=pulsar" + image: coordinator + imagePullPolicy: IfNotPresent + name: coordinator + ports: + - containerPort: 50051 + name: grpc +--- +apiVersion: v1 +kind: Service +metadata: + name: coordinator + namespace: chroma +spec: + ports: + - name: grpc + port: 50051 + targetPort: grpc + selector: + app: coordinator + type: ClusterIP \ No newline at end of file diff --git a/k8s/dev/pulsar.yaml b/k8s/dev/pulsar.yaml new file mode 100644 index 0000000000000000000000000000000000000000..4038ecda209304d7ebc23a6fd44dc631de162e72 --- /dev/null +++ b/k8s/dev/pulsar.yaml @@ -0,0 +1,45 @@ +apiVersion: apps/v1 +kind: Deployment +metadata: + name: pulsar + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: pulsar + template: + metadata: + labels: + app: pulsar + spec: + containers: + - name: pulsar + image: apachepulsar/pulsar + command: [ "/pulsar/bin/pulsar", "standalone" ] + ports: + - containerPort: 6650 + - containerPort: 8080 + volumeMounts: + - name: pulsardata + mountPath: /pulsar/data + volumes: + - name: pulsardata + emptyDir: {} +--- +apiVersion: v1 +kind: Service +metadata: + name: pulsar + namespace: chroma +spec: + ports: + - name: pulsar-port + port: 6650 + targetPort: 6650 + - name: admin-port + port: 8080 + targetPort: 8080 + selector: + app: pulsar + type: ClusterIP \ No newline at end of file diff --git a/k8s/dev/server.yaml b/k8s/dev/server.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9d76314e693eb6fe6e305e244a3f2ca1d1551f88 --- /dev/null +++ b/k8s/dev/server.yaml @@ -0,0 +1,52 @@ +apiVersion: apps/v1 +kind: Deployment +metadata: + name: server + namespace: chroma +spec: + replicas: 2 + selector: + matchLabels: + app: server + template: + metadata: + labels: + app: server + spec: + containers: + - name: server + image: server + imagePullPolicy: IfNotPresent + ports: + - containerPort: 8000 + volumeMounts: + - name: chroma + mountPath: /test + env: + - name: IS_PERSISTENT + value: "TRUE" + - name: CHROMA_PRODUCER_IMPL + value: "chromadb.ingest.impl.pulsar.PulsarProducer" + - name: CHROMA_CONSUMER_IMPL + value: "chromadb.ingest.impl.pulsar.PulsarConsumer" + - name: CHROMA_SEGMENT_MANAGER_IMPL + value: "chromadb.segment.impl.manager.distributed.DistributedSegmentManager" + - name: PULSAR_BROKER_URL + value: "pulsar.chroma" + - name: PULSAR_BROKER_PORT + value: "6650" + - name: PULSAR_ADMIN_PORT + value: "8080" + - name: ALLOW_RESET + value: "TRUE" + - name: CHROMA_SYSDB_IMPL + value: "chromadb.db.impl.grpc.client.GrpcSysDB" + - name: CHROMA_SERVER_GRPC_PORT + value: "50051" + - name: CHROMA_COORDINATOR_HOST + value: "coordinator.chroma" + volumes: + - name: chroma + emptyDir: {} + + diff --git a/k8s/dev/setup.yaml b/k8s/dev/setup.yaml new file mode 100644 index 0000000000000000000000000000000000000000..d9e1d95cc151be8a33479492a242cfa71941dee4 --- /dev/null +++ b/k8s/dev/setup.yaml @@ -0,0 +1,100 @@ +kind: Namespace +apiVersion: v1 +metadata: + name: chroma +--- +apiVersion: rbac.authorization.k8s.io/v1 +kind: ClusterRole +metadata: + name: memberlist-reader +rules: +- apiGroups: + - chroma.cluster + resources: + - memberlists + verbs: + - get + - list + - watch + - create + - update + - patch + - delete +--- +apiVersion: rbac.authorization.k8s.io/v1 +kind: ClusterRoleBinding +metadata: + name: memberlist-reader +roleRef: + apiGroup: rbac.authorization.k8s.io + kind: ClusterRole + name: memberlist-reader +subjects: +- kind: ServiceAccount + name: default + namespace: chroma +--- +apiVersion: rbac.authorization.k8s.io/v1 +kind: Role +metadata: + namespace: chroma + name: pod-list-role +rules: +- apiGroups: [""] + resources: ["pods"] + verbs: ["get", "list", "watch"] +--- +apiVersion: rbac.authorization.k8s.io/v1 +kind: RoleBinding +metadata: + name: pod-list-role-binding + namespace: chroma +subjects: +- kind: ServiceAccount + name: default + namespace: chroma +roleRef: + kind: Role + name: pod-list-role + apiGroup: rbac.authorization.k8s.io +--- +apiVersion: apiextensions.k8s.io/v1 +kind: CustomResourceDefinition +metadata: + name: memberlists.chroma.cluster +spec: + group: chroma.cluster + versions: + - name: v1 + served: true + storage: true + schema: + openAPIV3Schema: + type: object + properties: + spec: + type: object + properties: + members: + type: array + items: + type: object + properties: + url: # Rename to ip + type: string + pattern: '^((25[0-5]|(2[0-4]|1\d|[1-9]|)\d)\.?\b){4}$' + scope: Namespaced + names: + plural: memberlists + singular: memberlist + kind: MemberList + shortNames: + - ml +--- +apiVersion: chroma.cluster/v1 +kind: MemberList +metadata: + name: worker-memberlist + namespace: chroma +spec: + members: \ No newline at end of file diff --git a/k8s/dev/worker.yaml b/k8s/dev/worker.yaml new file mode 100644 index 0000000000000000000000000000000000000000..82b4c9d905ba0e9200a76087508c678aca3a42a4 --- /dev/null +++ b/k8s/dev/worker.yaml @@ -0,0 +1,40 @@ +apiVersion: apps/v1 +kind: Deployment +metadata: + name: worker + namespace: chroma +spec: + replicas: 1 + selector: + matchLabels: + app: worker + template: + metadata: + labels: + app: worker + member-type: worker + spec: + containers: + - name: worker + image: worker + imagePullPolicy: IfNotPresent + command: ["cargo", "run"] + ports: + - containerPort: 50051 + volumeMounts: + - name: chroma + mountPath: /index_data + env: + - name: CHROMA_WORKER__PULSAR_URL + value: pulsar://pulsar.chroma:6650 + - name: CHROMA_WORKER__PULSAR_NAMESPACE + value: default + - name: CHROMA_WORKER__PULSAR_TENANT + value: default + - name: CHROMA_WORKER__MY_IP + valueFrom: + fieldRef: + fieldPath: status.podIP + volumes: + - name: chroma + emptyDir: {} \ No newline at end of file diff --git a/k8s/test/coordinator_service.yaml b/k8s/test/coordinator_service.yaml new file mode 100644 index 0000000000000000000000000000000000000000..37334b121878082156d99bc65ed98347204bd561 --- /dev/null +++ b/k8s/test/coordinator_service.yaml @@ -0,0 +1,13 @@ +apiVersion: v1 +kind: Service +metadata: + name: coordinator-lb + namespace: chroma +spec: + ports: + - name: grpc + port: 50051 + targetPort: 50051 + selector: + app: coordinator + type: LoadBalancer diff --git a/k8s/test/minio.yaml b/k8s/test/minio.yaml new file mode 100644 index 0000000000000000000000000000000000000000..148c5170fd8502f97cf00ddb7cc384c458079ef9 --- /dev/null +++ b/k8s/test/minio.yaml @@ -0,0 +1,52 @@ +apiVersion: apps/v1 +kind: Deployment +metadata: + name: minio-deployment + namespace: chroma +spec: + selector: + matchLabels: + app: minio + strategy: + type: Recreate + template: + metadata: + labels: + app: minio + spec: + volumes: + - name: minio + emptyDir: {} + containers: + - name: minio + image: minio/minio:latest + args: + - server + - /storage + env: + - name: MINIO_ACCESS_KEY + value: "minio" + - name: MINIO_SECRET_KEY + value: "minio123" + ports: + - containerPort: 9000 + hostPort: 9000 + volumeMounts: + - name: minio + mountPath: /storage + +--- + +apiVersion: v1 +kind: Service +metadata: + name: minio-lb + namespace: chroma +spec: + ports: + - name: http + port: 9000 + targetPort: 9000 + selector: + app: minio + type: LoadBalancer diff --git a/k8s/test/pulsar_service.yaml b/k8s/test/pulsar_service.yaml new file mode 100644 index 0000000000000000000000000000000000000000..56ff6440db2968823138d92658c8d1d22a45ecc9 --- /dev/null +++ b/k8s/test/pulsar_service.yaml @@ -0,0 +1,20 @@ +# These kubernetes manifests are UNDER ACTIVE DEVELOPMENT and are not yet ready for production use. +# They will be used for the upcoming distributed version of chroma. They are not even ready +# for testing yet. Please do not use them unless you are working on the distributed version of chroma. + +apiVersion: v1 +kind: Service +metadata: + name: pulsar-lb + namespace: chroma +spec: + ports: + - name: pulsar-port + port: 6650 + targetPort: 6650 + - name: admin-port + port: 8080 + targetPort: 8080 + selector: + app: pulsar + type: LoadBalancer diff --git a/k8s/test/segment_server_service.yml b/k8s/test/segment_server_service.yml new file mode 100644 index 0000000000000000000000000000000000000000..7463333deef8709478d037166edceb9c3c1f2322 --- /dev/null +++ b/k8s/test/segment_server_service.yml @@ -0,0 +1,13 @@ +apiVersion: v1 +kind: Service +metadata: + name: segment-server-lb + namespace: chroma +spec: + ports: + - name: segment-server-port + port: 50052 + targetPort: 50051 + selector: + app: segment-server + type: LoadBalancer diff --git a/k8s/test/test_memberlist_cr.yaml b/k8s/test/test_memberlist_cr.yaml new file mode 100644 index 0000000000000000000000000000000000000000..174e19ccef53149c47b47007c9d09e3fd07fb52e --- /dev/null +++ b/k8s/test/test_memberlist_cr.yaml @@ -0,0 +1,48 @@ +# These kubernetes manifests are UNDER ACTIVE DEVELOPMENT and are not yet ready for production use. +# They will be used for the upcoming distributed version of chroma. They are not even ready +# for testing yet. Please do not use them unless you are working on the distributed version of chroma. + +# Create a memberlist called worker-memberlist +apiVersion: chroma.cluster/v1 +kind: MemberList +metadata: + name: test-memberlist + namespace: chroma +spec: + members: + +--- + +apiVersion: rbac.authorization.k8s.io/v1 +kind: ClusterRole +metadata: + name: test-memberlist-reader +rules: +- apiGroups: + - chroma.cluster + resources: + - memberlists + verbs: + - get + - list + - watch + # TODO: FIX THIS LEAKY PERMISSION + - create + - update + - patch + - delete + +--- + +apiVersion: rbac.authorization.k8s.io/v1 +kind: ClusterRoleBinding +metadata: + name: test-memberlist-reader-binding +roleRef: + apiGroup: rbac.authorization.k8s.io + kind: ClusterRole + name: test-memberlist-reader +subjects: +- kind: ServiceAccount + name: default + namespace: chroma diff --git a/pull_request_template.md b/pull_request_template.md new file mode 100644 index 0000000000000000000000000000000000000000..b7fbdce6fc6830f8586e332878ad86c30cbd57cc --- /dev/null +++ b/pull_request_template.md @@ -0,0 +1,15 @@ +## Description of changes + +*Summarize the changes made by this PR.* + - Improvements & Bug fixes + - ... + - New functionality + - ... + +## Test plan +*How are these changes tested?* + +- [ ] Tests pass locally with `pytest` for python, `yarn test` for js + +## Documentation Changes +*Are all docstrings for user-facing APIs updated if required? Do we need to make documentation changes in the [docs repository](https://github.com/chroma-core/docs)?* diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000000000000000000000000000000000000..01aa0d8663bc1aac35c275dab175a5cbaa1054cc --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,81 @@ +[project] +name = "chromadb" +dynamic = ["version"] + +authors = [ + { name="Jeff Huber", email="jeff@trychroma.com" }, + { name="Anton Troynikov", email="anton@trychroma.com" } +] +description = "Chroma." +readme = "README.md" +requires-python = ">=3.8" +classifiers = [ + "Programming Language :: Python :: 3", + "License :: OSI Approved :: Apache Software License", + "Operating System :: OS Independent", +] +dependencies = [ + 'build >= 1.0.3', + 'requests >= 2.28', + 'pydantic >= 1.9', + 'chroma-hnswlib==0.7.3', + 'fastapi >= 0.95.2', + 'uvicorn[standard] >= 0.18.3', + 'numpy >= 1.22.5', + 'posthog >= 2.4.0', + 'typing_extensions >= 4.5.0', + 'pulsar-client>=3.1.0', + 'onnxruntime >= 1.14.1', + 'opentelemetry-api>=1.2.0', + 'opentelemetry-exporter-otlp-proto-grpc>=1.2.0', + 'opentelemetry-instrumentation-fastapi>=0.41b0', + 'opentelemetry-sdk>=1.2.0', + 'tokenizers >= 0.13.2', + 'pypika >= 0.48.9', + 'tqdm >= 4.65.0', + 'overrides >= 7.3.1', + 'importlib-resources', + 'graphlib_backport >= 1.0.3; python_version < "3.9"', + 'grpcio >= 1.58.0', + 'bcrypt >= 4.0.1', + 'typer >= 0.9.0', + 'kubernetes>=28.1.0', + 'tenacity>=8.2.3', + 'PyYAML>=6.0.0', + 'mmh3>=4.0.1', +] + +[tool.black] +line-length = 88 +required-version = "23.3.0" # Black will refuse to run if it's not this version. +target-version = ['py38', 'py39', 'py310', 'py311'] + +[tool.pytest.ini_options] +pythonpath = ["."] + +[tool.mypy] +ignore_errors = false + +[[tool.mypy.overrides]] +module = ["chromadb.proto.*"] +ignore_errors = true + +[project.scripts] +chroma = "chromadb.cli.cli:app" + +[project.urls] +"Homepage" = "https://github.com/chroma-core/chroma" +"Bug Tracker" = "https://github.com/chroma-core/chroma/issues" + +[build-system] +requires = ["setuptools>=61.0", "setuptools_scm[toml]>=6.2"] +build-backend = "setuptools.build_meta" + +[tool.setuptools_scm] +local_scheme="no-local-version" + +[tool.setuptools] +packages = ["chromadb"] + +[tool.setuptools.package-data] +chromadb = ["*.yml"] diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..3e99734fd3a8fa5b8884e30c11b6a5fe96cbe17a --- /dev/null +++ b/requirements.txt @@ -0,0 +1,27 @@ +bcrypt==4.0.1 +chroma-hnswlib==0.7.3 +fastapi>=0.95.2 +graphlib_backport==1.0.3; python_version < '3.9' +grpcio>=1.58.0 +importlib-resources +kubernetes>=28.1.0 +mmh3>=4.0.1 +numpy>=1.22.5 +onnxruntime>=1.14.1 +opentelemetry-api>=1.2.0 +opentelemetry-exporter-otlp-proto-grpc>=1.2.0 +opentelemetry-instrumentation-fastapi>=0.41b0 +opentelemetry-sdk>=1.2.0 +overrides==7.3.1 +posthog==2.4.0 +pulsar-client==3.1.0 +pydantic>=1.9 +pypika==0.48.9 +PyYAML>=6.0.0 +requests==2.28.1 +tenacity>=8.2.3 +tokenizers==0.13.2 +tqdm>=4.65.0 +typer>=0.9.0 +typing_extensions>=4.5.0 +uvicorn[standard]==0.18.3 diff --git a/requirements_dev.txt b/requirements_dev.txt new file mode 100644 index 0000000000000000000000000000000000000000..4dce86e2efe3cd15ba5a0404df86818c699a4163 --- /dev/null +++ b/requirements_dev.txt @@ -0,0 +1,13 @@ +black==23.3.0 # match what's in pyproject.toml +build +grpcio-tools +httpx +hypothesis +hypothesis[numpy] +mypy-protobuf +pre-commit +pytest +pytest-asyncio +setuptools_scm +types-protobuf +types-requests==2.30.0.0 diff --git a/rust/worker/.gitignore b/rust/worker/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..b83d22266ac8aa2f8df2edef68082c789727841d --- /dev/null +++ b/rust/worker/.gitignore @@ -0,0 +1 @@ +/target/ diff --git a/rust/worker/Cargo.toml b/rust/worker/Cargo.toml new file mode 100644 index 0000000000000000000000000000000000000000..25a3b2d099ee57724b58f8318c29f91c69a4cebf --- /dev/null +++ b/rust/worker/Cargo.toml @@ -0,0 +1,41 @@ +[package] +name = "worker" +version = "0.1.0" +edition = "2021" + +[[bin]] +name = "worker" +path = "src/bin/worker.rs" + +[dependencies] +tonic = "0.10" +prost = "0.12" +prost-types = "0.12" +tokio = { version = "1.0", features = ["macros", "rt-multi-thread"] } +tokio-util = "0.7.10" +rand = "0.8.5" +rayon = "1.8.0" +async-trait = "0.1.74" +uuid = { version = "1.6.1", features = ["v4", "fast-rng", "macro-diagnostics"] } +figment = { version = "0.10.12", features = ["env", "yaml", "test"] } +serde = { version = "1.0.193", features = ["derive"] } +serde_json = "1.0.108" +futures = "0.3" +num_cpus = "1.16.0" +pulsar = "6.1.0" +murmur3 = "0.5.2" +thiserror = "1.0.50" +num-bigint = "0.4.4" +tempfile = "3.8.1" +schemars = "0.8.16" +kube = { version = "0.87.1", features = ["runtime", "derive"] } +k8s-openapi = { version = "0.20.0", features = ["latest"] } +bytes = "1.5.0" +parking_lot = "0.12.1" +aws-sdk-s3 = "1.5.0" +aws-smithy-types = "1.1.0" +aws-config = { version = "1.1.2", features = ["behavior-version-latest"] } + +[build-dependencies] +tonic-build = "0.10" +cc = "1.0" diff --git a/rust/worker/Dockerfile b/rust/worker/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..2e3802787e1e99da32e3dcd052780a429555fa55 --- /dev/null +++ b/rust/worker/Dockerfile @@ -0,0 +1,21 @@ +FROM rust:1.74.1 as builder +ARG CHROMA_KUBERNETES_INTEGRATION=0 +ENV CHROMA_KUBERNETES_INTEGRATION $CHROMA_KUBERNETES_INTEGRATION + +WORKDIR / +RUN git clone https://github.com/chroma-core/hnswlib.git + +WORKDIR /chroma/ +COPY . . + +ENV PROTOC_ZIP=protoc-25.1-linux-x86_64.zip +RUN curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v25.1/$PROTOC_ZIP \ + && unzip -o $PROTOC_ZIP -d /usr/local bin/protoc \ + && unzip -o $PROTOC_ZIP -d /usr/local 'include/*' \ + && rm -f $PROTOC_ZIP + +RUN cargo build + +WORKDIR /chroma/rust/worker + +CMD ["cargo", "run"] diff --git a/rust/worker/README b/rust/worker/README new file mode 100644 index 0000000000000000000000000000000000000000..e09a7db4f4cb109055c960e4b06ad3f33042c92f --- /dev/null +++ b/rust/worker/README @@ -0,0 +1,7 @@ +# Readme + + + + +### Rust version +Use rust 1.74.0 or greater. diff --git a/rust/worker/bindings.cpp b/rust/worker/bindings.cpp new file mode 100644 index 0000000000000000000000000000000000000000..982d14dd5d8e2f022f29018c903d2d400c13caf5 --- /dev/null +++ b/rust/worker/bindings.cpp @@ -0,0 +1,203 @@ +// Assumes that chroma-hnswlib is checked out at the same level as chroma +#include "../../../hnswlib/hnswlib/hnswlib.h" + +template +class Index +{ +public: + std::string space_name; + int dim; + size_t seed; + + bool normalize; + bool index_inited; + + hnswlib::HierarchicalNSW *appr_alg; + hnswlib::SpaceInterface *l2space; + + Index(const std::string &space_name, const int dim) : space_name(space_name), dim(dim) + { + if (space_name == "l2") + { + l2space = new hnswlib::L2Space(dim); + normalize = false; + } + if (space_name == "ip") + { + l2space = new hnswlib::InnerProductSpace(dim); + // For IP, we expect the vectors to be normalized + normalize = false; + } + if (space_name == "cosine") + { + l2space = new hnswlib::InnerProductSpace(dim); + normalize = true; + } + appr_alg = NULL; + index_inited = false; + } + + ~Index() + { + delete l2space; + if (appr_alg) + { + delete appr_alg; + } + } + + void init_index(const size_t max_elements, const size_t M, const size_t ef_construction, const size_t random_seed, const bool allow_replace_deleted, const bool is_persistent_index, const std::string &persistence_location) + { + if (index_inited) + { + std::runtime_error("Index already inited"); + } + appr_alg = new hnswlib::HierarchicalNSW(l2space, max_elements, M, ef_construction, random_seed, allow_replace_deleted, normalize, is_persistent_index, persistence_location); + appr_alg->ef_ = 10; // This is a default value for ef_ + index_inited = true; + } + + void load_index(const std::string &path_to_index, const bool allow_replace_deleted, const bool is_persistent_index) + { + if (index_inited) + { + std::runtime_error("Index already inited"); + } + appr_alg = new hnswlib::HierarchicalNSW(l2space, path_to_index, false, 0, allow_replace_deleted, normalize, is_persistent_index); + index_inited = true; + } + + void persist_dirty() + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + appr_alg->persistDirty(); + } + + void add_item(const data_t *data, const hnswlib::labeltype id, const bool replace_deleted = false) + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + appr_alg->addPoint(data, id); + } + + void get_item(const hnswlib::labeltype id, data_t *data) + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + std::vector ret_data = appr_alg->template getDataByLabel(id); // This checks if id is deleted + for (int i = 0; i < dim; i++) + { + data[i] = ret_data[i]; + } + } + + int mark_deleted(const hnswlib::labeltype id) + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + appr_alg->markDelete(id); + return 0; + } + + void knn_query(const data_t *query_vector, const size_t k, hnswlib::labeltype *ids, data_t *distance) + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + std::priority_queue> res = appr_alg->searchKnn(query_vector, k); + if (res.size() < k) + { + // TODO: This is ok and we should return < K results, but for maintining compatibility with the old API we throw an error for now + std::runtime_error("Not enough results"); + } + int total_results = std::min(res.size(), k); + for (int i = total_results - 1; i >= 0; i--) + { + std::pair res_i = res.top(); + ids[i] = res_i.second; + distance[i] = res_i.first; + res.pop(); + } + } + + int get_ef() + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + return appr_alg->ef_; + } + + void set_ef(const size_t ef) + { + if (!index_inited) + { + std::runtime_error("Index not inited"); + } + appr_alg->ef_ = ef; + } +}; + +extern "C" +{ + Index *create_index(const char *space_name, const int dim) + { + return new Index(space_name, dim); + } + + void init_index(Index *index, const size_t max_elements, const size_t M, const size_t ef_construction, const size_t random_seed, const bool allow_replace_deleted, const bool is_persistent_index, const char *persistence_location) + { + index->init_index(max_elements, M, ef_construction, random_seed, allow_replace_deleted, is_persistent_index, persistence_location); + } + + void load_index(Index *index, const char *path_to_index, const bool allow_replace_deleted, const bool is_persistent_index) + { + index->load_index(path_to_index, allow_replace_deleted, is_persistent_index); + } + + void persist_dirty(Index *index) + { + index->persist_dirty(); + } + + void add_item(Index *index, const float *data, const hnswlib::labeltype id, const bool replace_deleted) + { + index->add_item(data, id); + } + + void get_item(Index *index, const hnswlib::labeltype id, float *data) + { + index->get_item(id, data); + } + + int mark_deleted(Index *index, const hnswlib::labeltype id) + { + return index->mark_deleted(id); + } + + void knn_query(Index *index, const float *query_vector, const size_t k, hnswlib::labeltype *ids, float *distance) + { + index->knn_query(query_vector, k, ids, distance); + } + + int get_ef(Index *index) + { + return index->appr_alg->ef_; + } + + void set_ef(Index *index, const size_t ef) + { + index->set_ef(ef); + } +} diff --git a/rust/worker/build.rs b/rust/worker/build.rs new file mode 100644 index 0000000000000000000000000000000000000000..25235b5c6b097a8dc45889149d0ea33012c63990 --- /dev/null +++ b/rust/worker/build.rs @@ -0,0 +1,36 @@ +fn main() -> Result<(), Box> { + // Compile the protobuf files in the chromadb proto directory. + tonic_build::configure().compile( + &[ + "../../idl/chromadb/proto/chroma.proto", + "../../idl/chromadb/proto/coordinator.proto", + ], + &["../../idl/"], + )?; + + // Compile the hnswlib bindings. + cc::Build::new() + .cpp(true) + .file("bindings.cpp") + .flag("-std=c++11") + .flag("-Ofast") + .flag("-DHAVE_CXX0X") + .flag("-fpic") + .flag("-ftree-vectorize") + .compile("bindings"); + + // Set a compile flag based on an environment variable that tells us if we should + // run the cluster tests + let run_cluster_tests_env_var = std::env::var("CHROMA_KUBERNETES_INTEGRATION"); + match run_cluster_tests_env_var { + Ok(val) => { + let lowered = val.to_lowercase(); + if lowered == "true" || lowered == "1" { + println!("cargo:rustc-cfg=CHROMA_KUBERNETES_INTEGRATION"); + } + } + Err(_) => {} + } + + Ok(()) +} diff --git a/rust/worker/chroma_config.yaml b/rust/worker/chroma_config.yaml new file mode 100644 index 0000000000000000000000000000000000000000..32e5165924d8d0f4b94876918c786aecf729868f --- /dev/null +++ b/rust/worker/chroma_config.yaml @@ -0,0 +1,31 @@ +# Default configuration for Chroma worker +# In the long term, every service should have an entry in this file +# and this can become the global configuration file for Chroma +# for now we nest it in the worker directory + +worker: + my_ip: "10.244.0.9" + my_port: 50051 + num_indexing_threads: 4 + pulsar_url: "pulsar://127.0.0.1:6650" + pulsar_tenant: "default" + pulsar_namespace: "default" + kube_namespace: "chroma" + assignment_policy: + RendezvousHashing: + hasher: Murmur3 + memberlist_provider: + CustomResource: + memberlist_name: "worker-memberlist" + queue_size: 100 + ingest: + queue_size: 10000 + sysdb: + Grpc: + host: "coordinator.chroma" + port: 50051 + segment_manager: + storage_path: "./tmp/segment_manager/" + storage: + S3: + bucket: "chroma-storage" diff --git a/rust/worker/src/assignment/assignment_policy.rs b/rust/worker/src/assignment/assignment_policy.rs new file mode 100644 index 0000000000000000000000000000000000000000..bde70b266250af1bb8cd1b4ed2181acfb3dfa374 --- /dev/null +++ b/rust/worker/src/assignment/assignment_policy.rs @@ -0,0 +1,101 @@ +use crate::{ + config::{Configurable, WorkerConfig}, + errors::ChromaError, +}; + +use super::{ + config::{AssignmentPolicyConfig, HasherType}, + rendezvous_hash::{assign, AssignmentError, Murmur3Hasher}, +}; +use async_trait::async_trait; + +/* +=========================================== +Interfaces +=========================================== +*/ + +/// AssignmentPolicy is a trait that defines how to assign a key to a set of members. +/// # Notes +/// This trait mirrors the go and python versions of the assignment policy +/// interface. +/// # Methods +/// - assign: Assign a key to a topic. +/// - get_members: Get the members that can be assigned to. +/// - set_members: Set the members that can be assigned to. +/// # Notes +/// An assignment policy is not responsible for creating the topics it assigns to. +/// It is the responsibility of the caller to ensure that the topics exist. +/// An assignment policy must be Send. +pub(crate) trait AssignmentPolicy: Send { + fn assign(&self, key: &str) -> Result; + fn get_members(&self) -> Vec; + fn set_members(&mut self, members: Vec); +} + +/* +=========================================== +Implementation +=========================================== +*/ + +pub(crate) struct RendezvousHashingAssignmentPolicy { + hasher: Murmur3Hasher, + members: Vec, +} + +impl RendezvousHashingAssignmentPolicy { + // Rust beginners note + // The reason we take String and not &str is because we need to put the strings into our + // struct, and we can't do that with references so rather than clone the strings, we just + // take ownership of them and put the responsibility on the caller to clone them if they + // need to. This is the general pattern we should follow in rust - put the burden of cloning + // on the caller, and if they don't need to clone, they can pass ownership. + pub(crate) fn new( + pulsar_tenant: String, + pulsar_namespace: String, + ) -> RendezvousHashingAssignmentPolicy { + return RendezvousHashingAssignmentPolicy { + hasher: Murmur3Hasher {}, + members: vec![], + }; + } + + pub(crate) fn set_members(&mut self, members: Vec) { + self.members = members; + } +} + +#[async_trait] +impl Configurable for RendezvousHashingAssignmentPolicy { + async fn try_from_config(worker_config: &WorkerConfig) -> Result> { + let assignment_policy_config = match &worker_config.assignment_policy { + AssignmentPolicyConfig::RendezvousHashing(config) => config, + }; + let hasher = match assignment_policy_config.hasher { + HasherType::Murmur3 => Murmur3Hasher {}, + }; + return Ok(RendezvousHashingAssignmentPolicy { + hasher: hasher, + members: vec![], + }); + } +} + +impl AssignmentPolicy for RendezvousHashingAssignmentPolicy { + fn assign(&self, key: &str) -> Result { + let topics = self.get_members(); + let topic = assign(key, topics, &self.hasher); + return topic; + } + + fn get_members(&self) -> Vec { + // This is not designed to be used frequently for now, nor is the number of members + // expected to be large, so we can just clone the members + return self.members.clone(); + } + + fn set_members(&mut self, members: Vec) { + self.members = members; + } +} diff --git a/rust/worker/src/assignment/config.rs b/rust/worker/src/assignment/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..af4b9b590f65bc0b33be11c266cfbdee00c9b19e --- /dev/null +++ b/rust/worker/src/assignment/config.rs @@ -0,0 +1,28 @@ +use serde::Deserialize; + +#[derive(Deserialize)] +/// The type of hasher to use. +/// # Options +/// - Murmur3: The murmur3 hasher. +pub(crate) enum HasherType { + Murmur3, +} + +#[derive(Deserialize)] +/// The configuration for the assignment policy. +/// # Options +/// - RendezvousHashing: The rendezvous hashing assignment policy. +/// # Notes +/// See config.rs in the root of the worker crate for an example of how to use +/// config files to configure the worker. +pub(crate) enum AssignmentPolicyConfig { + RendezvousHashing(RendezvousHashingAssignmentPolicyConfig), +} + +#[derive(Deserialize)] +/// The configuration for the rendezvous hashing assignment policy. +/// # Fields +/// - hasher: The type of hasher to use. +pub(crate) struct RendezvousHashingAssignmentPolicyConfig { + pub(crate) hasher: HasherType, +} diff --git a/rust/worker/src/assignment/mod.rs b/rust/worker/src/assignment/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..7ed1525f0bcf814fe6f2946160d344a269d5fe07 --- /dev/null +++ b/rust/worker/src/assignment/mod.rs @@ -0,0 +1,3 @@ +pub(crate) mod assignment_policy; +pub(crate) mod config; +mod rendezvous_hash; diff --git a/rust/worker/src/assignment/rendezvous_hash.rs b/rust/worker/src/assignment/rendezvous_hash.rs new file mode 100644 index 0000000000000000000000000000000000000000..0a9a7564e88800827e6b3e9346eae41b0f3c429f --- /dev/null +++ b/rust/worker/src/assignment/rendezvous_hash.rs @@ -0,0 +1,173 @@ +// This implementation mirrors the rendezvous hash implementation +// in the go and python services. +// The go implementation is located go/internal/utils/rendezvous_hash.go +// The python implementation is located chromadb/utils/rendezvous_hash.py + +use crate::errors::{ChromaError, ErrorCodes}; +use std::io::Cursor; +use thiserror::Error; + +use murmur3::murmur3_x64_128; + +/// A trait for hashing a member and a key to a score. +pub(crate) trait Hasher { + fn hash(&self, member: &str, key: &str) -> Result; +} + +/// Error codes for assignment +#[derive(Error, Debug)] +pub(crate) enum AssignmentError { + #[error("Cannot assign empty key")] + EmptyKey, + #[error("No members to assign to")] + NoMembers, + #[error("Error hashing member")] + HashError, +} + +impl ChromaError for AssignmentError { + fn code(&self) -> ErrorCodes { + match self { + AssignmentError::EmptyKey => ErrorCodes::InvalidArgument, + AssignmentError::NoMembers => ErrorCodes::InvalidArgument, + AssignmentError::HashError => ErrorCodes::Internal, + } + } +} + +/// Assign a key to a member using the rendezvous hash algorithm. +/// # Arguments +/// - key: The key to assign. +/// - members: The members to assign to. +/// - hasher: The hasher to use. +/// # Returns +/// The member that the key was assigned to. +/// # Errors +/// - If the key is empty. +/// - If there are no members to assign to. +/// - If there is an error hashing a member. +/// # Notes +/// This implementation mirrors the rendezvous hash implementation +/// in the go and python services. +pub(crate) fn assign( + key: &str, + members: impl IntoIterator>, + hasher: &H, +) -> Result { + if key.is_empty() { + return Err(AssignmentError::EmptyKey); + } + + let mut iterated = false; + let mut max_score = u64::MIN; + let mut max_member = None; + + for member in members { + if !iterated { + iterated = true; + } + let score = hasher.hash(member.as_ref(), key); + let score = match score { + Ok(score) => score, + Err(err) => return Err(AssignmentError::HashError), + }; + if score > max_score { + max_score = score; + max_member = Some(member); + } + } + + if !iterated { + return Err(AssignmentError::NoMembers); + } + + match max_member { + Some(max_member) => return Ok(max_member.as_ref().to_string()), + None => return Err(AssignmentError::NoMembers), + } +} + +fn merge_hashes(x: u64, y: u64) -> u64 { + let mut acc = x ^ y; + acc ^= acc >> 33; + acc = acc.wrapping_mul(0xFF51AFD7ED558CCD); + acc ^= acc >> 33; + acc = acc.wrapping_mul(0xC4CEB9FE1A85EC53); + acc ^= acc >> 33; + acc +} + +pub(crate) struct Murmur3Hasher {} + +impl Hasher for Murmur3Hasher { + fn hash(&self, member: &str, key: &str) -> Result { + let member_hash = murmur3_x64_128(&mut Cursor::new(member), 0); + let key_hash = murmur3_x64_128(&mut Cursor::new(key), 0); + // The murmur library returns a 128 bit hash, but we only need 64 bits, grab the first 64 bits + match (member_hash, key_hash) { + (Ok(member_hash), Ok(key_hash)) => { + let member_hash_64 = member_hash as u64; + let key_hash_64 = key_hash as u64; + let merged = merge_hashes(member_hash_64, key_hash_64); + return Ok(merged); + } + _ => return Err(AssignmentError::HashError), + }; + } +} + +#[cfg(test)] +mod tests { + use super::*; + + struct MockHasher {} + + impl Hasher for MockHasher { + fn hash(&self, member: &str, _key: &str) -> Result { + match member { + "a" => Ok(1), + "b" => Ok(2), + "c" => Ok(3), + _ => Err(AssignmentError::HashError), + } + } + } + + #[test] + fn test_assign() { + let members = vec!["a", "b", "c"]; + let hasher = MockHasher {}; + let key = "key"; + let member = assign(key, members, &hasher).unwrap(); + assert_eq!(member, "c".to_string()); + } + + #[test] + fn test_even_distribution() { + let member_count = 10; + let tolerance = 25; + let mut nodes = Vec::with_capacity(member_count); + let hasher = Murmur3Hasher {}; + + for i in 0..member_count { + let member = format!("member{}", i); + nodes.push(member); + } + + let mut counts = vec![0; member_count]; + let num_keys = 1000; + for i in 0..num_keys { + let key = format!("key_{}", i); + let member = assign(&key, &nodes, &hasher).unwrap(); + let index = nodes.iter().position(|x| *x == member).unwrap(); + counts[index] += 1; + } + + let expected = num_keys / member_count; + for i in 0..member_count { + let count = counts[i]; + let diff = count - expected as i32; + assert!(diff.abs() < tolerance); + } + } +} diff --git a/rust/worker/src/bin/worker.rs b/rust/worker/src/bin/worker.rs new file mode 100644 index 0000000000000000000000000000000000000000..16428d244ff56568c30ea55098f009081775e75f --- /dev/null +++ b/rust/worker/src/bin/worker.rs @@ -0,0 +1,6 @@ +use worker::worker_entrypoint; + +#[tokio::main] +async fn main() { + worker_entrypoint().await; +} diff --git a/rust/worker/src/config.rs b/rust/worker/src/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..7583bf0114e499f0856894c8dbaaedbee8aba14c --- /dev/null +++ b/rust/worker/src/config.rs @@ -0,0 +1,320 @@ +use async_trait::async_trait; +use figment::providers::{Env, Format, Serialized, Yaml}; +use serde::Deserialize; + +use crate::errors::ChromaError; + +const DEFAULT_CONFIG_PATH: &str = "./chroma_config.yaml"; +const ENV_PREFIX: &str = "CHROMA_"; + +#[derive(Deserialize)] +/// # Description +/// The RootConfig for all chroma services this is a YAML file that +/// is shared between all services, and secondarily, fields can be +/// populated from environment variables. The environment variables +/// are prefixed with CHROMA_ and are uppercase. Values in the envionment +/// variables take precedence over values in the YAML file. +/// By default, it is read from the current working directory, +/// with the filename chroma_config.yaml. +pub(crate) struct RootConfig { + // The root config object wraps the worker config object so that + // we can share the same config file between multiple services. + pub worker: WorkerConfig, +} + +impl RootConfig { + /// # Description + /// Load the config from the default location. + /// # Returns + /// The config object. + /// # Panics + /// - If the config file cannot be read. + /// - If the config file is not valid YAML. + /// - If the config file does not contain the required fields. + /// - If the config file contains invalid values. + /// - If the environment variables contain invalid values. + /// # Notes + /// The default location is the current working directory, with the filename chroma_config.yaml. + /// The environment variables are prefixed with CHROMA_ and are uppercase. + /// Values in the envionment variables take precedence over values in the YAML file. + pub(crate) fn load() -> Self { + return Self::load_from_path(DEFAULT_CONFIG_PATH); + } + + /// # Description + /// Load the config from a specific location. + /// # Arguments + /// - path: The path to the config file. + /// # Returns + /// The config object. + /// # Panics + /// - If the config file cannot be read. + /// - If the config file is not valid YAML. + /// - If the config file does not contain the required fields. + /// - If the config file contains invalid values. + /// - If the environment variables contain invalid values. + /// # Notes + /// The environment variables are prefixed with CHROMA_ and are uppercase. + /// Values in the envionment variables take precedence over values in the YAML file. + pub(crate) fn load_from_path(path: &str) -> Self { + // Unfortunately, figment doesn't support environment variables with underscores. So we have to map and replace them. + // Excluding our own environment variables, which are prefixed with CHROMA_. + let mut f = figment::Figment::from(Env::prefixed("CHROMA_").map(|k| match k { + k if k == "num_indexing_threads" => k.into(), + k if k == "my_ip" => k.into(), + k => k.as_str().replace("__", ".").into(), + })); + if std::path::Path::new(path).exists() { + f = figment::Figment::from(Yaml::file(path)).merge(f); + } + // Apply defaults - this seems to be the best way to do it. + // https://github.com/SergioBenitez/Figment/issues/77#issuecomment-1642490298 + f = f.join(Serialized::default( + "worker.num_indexing_threads", + num_cpus::get(), + )); + let res = f.extract(); + match res { + Ok(config) => return config, + Err(e) => panic!("Error loading config: {}", e), + } + } +} + +#[derive(Deserialize)] +/// # Description +/// The primary config for the worker service. +/// ## Description of parameters +/// - my_ip: The IP address of the worker service. Used for memberlist assignment. Must be provided +/// - num_indexing_threads: The number of indexing threads to use. If not provided, defaults to the number of cores on the machine. +/// - pulsar_tenant: The pulsar tenant to use. Must be provided. +/// - pulsar_namespace: The pulsar namespace to use. Must be provided. +/// - assignment_policy: The assignment policy to use. Must be provided. +/// # Notes +/// In order to set the enviroment variables, you must prefix them with CHROMA_WORKER__. +/// For example, to set my_ip, you would set CHROMA_WORKER__MY_IP. +/// Each submodule that needs to be configured from the config object should implement the Configurable trait and +/// have its own field in this struct for its Config struct. +pub(crate) struct WorkerConfig { + pub(crate) my_ip: String, + pub(crate) my_port: u16, + pub(crate) num_indexing_threads: u32, + pub(crate) pulsar_tenant: String, + pub(crate) pulsar_namespace: String, + pub(crate) pulsar_url: String, + pub(crate) kube_namespace: String, + pub(crate) assignment_policy: crate::assignment::config::AssignmentPolicyConfig, + pub(crate) memberlist_provider: crate::memberlist::config::MemberlistProviderConfig, + pub(crate) ingest: crate::ingest::config::IngestConfig, + pub(crate) sysdb: crate::sysdb::config::SysDbConfig, + pub(crate) segment_manager: crate::segment::config::SegmentManagerConfig, + pub(crate) storage: crate::storage::config::StorageConfig, +} + +/// # Description +/// A trait for configuring a struct from a config object. +/// # Notes +/// This trait is used to configure structs from the config object. +/// Components that need to be configured from the config object should implement this trait. +#[async_trait] +pub(crate) trait Configurable { + async fn try_from_config(worker_config: &WorkerConfig) -> Result> + where + Self: Sized; +} + +#[cfg(test)] +mod tests { + use super::*; + use figment::Jail; + + #[test] + fn test_config_from_default_path() { + Jail::expect_with(|jail| { + let _ = jail.create_file( + "chroma_config.yaml", + r#" + worker: + my_ip: "192.0.0.1" + my_port: 50051 + num_indexing_threads: 4 + pulsar_tenant: "public" + pulsar_namespace: "default" + pulsar_url: "pulsar://localhost:6650" + kube_namespace: "chroma" + assignment_policy: + RendezvousHashing: + hasher: Murmur3 + memberlist_provider: + CustomResource: + memberlist_name: "worker-memberlist" + queue_size: 100 + ingest: + queue_size: 100 + sysdb: + Grpc: + host: "localhost" + port: 50051 + segment_manager: + storage_path: "/tmp" + storage: + S3: + bucket: "chroma" + "#, + ); + let config = RootConfig::load(); + assert_eq!(config.worker.my_ip, "192.0.0.1"); + assert_eq!(config.worker.num_indexing_threads, 4); + assert_eq!(config.worker.pulsar_tenant, "public"); + assert_eq!(config.worker.pulsar_namespace, "default"); + assert_eq!(config.worker.kube_namespace, "chroma"); + Ok(()) + }); + } + + #[test] + fn test_config_from_specific_path() { + Jail::expect_with(|jail| { + let _ = jail.create_file( + "random_path.yaml", + r#" + worker: + my_ip: "192.0.0.1" + my_port: 50051 + num_indexing_threads: 4 + pulsar_tenant: "public" + pulsar_namespace: "default" + pulsar_url: "pulsar://localhost:6650" + kube_namespace: "chroma" + assignment_policy: + RendezvousHashing: + hasher: Murmur3 + memberlist_provider: + CustomResource: + memberlist_name: "worker-memberlist" + queue_size: 100 + ingest: + queue_size: 100 + sysdb: + Grpc: + host: "localhost" + port: 50051 + segment_manager: + storage_path: "/tmp" + storage: + S3: + bucket: "chroma" + + "#, + ); + let config = RootConfig::load_from_path("random_path.yaml"); + assert_eq!(config.worker.my_ip, "192.0.0.1"); + assert_eq!(config.worker.num_indexing_threads, 4); + assert_eq!(config.worker.pulsar_tenant, "public"); + assert_eq!(config.worker.pulsar_namespace, "default"); + assert_eq!(config.worker.kube_namespace, "chroma"); + Ok(()) + }); + } + + #[test] + #[should_panic] + fn test_config_missing_required_field() { + Jail::expect_with(|jail| { + let _ = jail.create_file( + "chroma_config.yaml", + r#" + worker: + num_indexing_threads: 4 + "#, + ); + let _ = RootConfig::load(); + Ok(()) + }); + } + + #[test] + fn test_missing_default_field() { + Jail::expect_with(|jail| { + let _ = jail.create_file( + "chroma_config.yaml", + r#" + worker: + my_ip: "192.0.0.1" + my_port: 50051 + pulsar_tenant: "public" + pulsar_namespace: "default" + kube_namespace: "chroma" + pulsar_url: "pulsar://localhost:6650" + assignment_policy: + RendezvousHashing: + hasher: Murmur3 + memberlist_provider: + CustomResource: + memberlist_name: "worker-memberlist" + queue_size: 100 + ingest: + queue_size: 100 + sysdb: + Grpc: + host: "localhost" + port: 50051 + segment_manager: + storage_path: "/tmp" + storage: + S3: + bucket: "chroma" + + "#, + ); + let config = RootConfig::load(); + assert_eq!(config.worker.my_ip, "192.0.0.1"); + assert_eq!(config.worker.num_indexing_threads, num_cpus::get() as u32); + Ok(()) + }); + } + + #[test] + fn test_config_with_env_override() { + Jail::expect_with(|jail| { + let _ = jail.set_env("CHROMA_WORKER__MY_IP", "192.0.0.1"); + let _ = jail.set_env("CHROMA_WORKER__MY_PORT", 50051); + let _ = jail.set_env("CHROMA_WORKER__PULSAR_TENANT", "A"); + let _ = jail.set_env("CHROMA_WORKER__PULSAR_NAMESPACE", "B"); + let _ = jail.set_env("CHROMA_WORKER__KUBE_NAMESPACE", "C"); + let _ = jail.set_env("CHROMA_WORKER__PULSAR_URL", "pulsar://localhost:6650"); + let _ = jail.create_file( + "chroma_config.yaml", + r#" + worker: + assignment_policy: + RendezvousHashing: + hasher: Murmur3 + memberlist_provider: + CustomResource: + memberlist_name: "worker-memberlist" + queue_size: 100 + ingest: + queue_size: 100 + sysdb: + Grpc: + host: "localhost" + port: 50051 + segment_manager: + storage_path: "/tmp" + storage: + S3: + bucket: "chroma" + "#, + ); + let config = RootConfig::load(); + assert_eq!(config.worker.my_ip, "192.0.0.1"); + assert_eq!(config.worker.my_port, 50051); + assert_eq!(config.worker.num_indexing_threads, num_cpus::get() as u32); + assert_eq!(config.worker.pulsar_tenant, "A"); + assert_eq!(config.worker.pulsar_namespace, "B"); + assert_eq!(config.worker.kube_namespace, "C"); + Ok(()) + }); + } +} diff --git a/rust/worker/src/errors.rs b/rust/worker/src/errors.rs new file mode 100644 index 0000000000000000000000000000000000000000..c28d39ba9b766b797b6bd41079d57e139bedf1a3 --- /dev/null +++ b/rust/worker/src/errors.rs @@ -0,0 +1,46 @@ +// Defines 17 standard error codes based on the error codes defined in the +// gRPC spec. https://grpc.github.io/grpc/core/md_doc_statuscodes.html +// Custom errors can use these codes in order to allow for generic handling + +use std::error::Error; + +pub(crate) enum ErrorCodes { + // OK is returned on success, we use "Success" since Ok is a keyword in Rust. + Success = 0, + // CANCELLED indicates the operation was cancelled (typically by the caller). + Cancelled = 1, + // UNKNOWN indicates an unknown error. + UNKNOWN = 2, + // INVALID_ARGUMENT indicates client specified an invalid argument. + InvalidArgument = 3, + // DEADLINE_EXCEEDED means operation expired before completion. + DeadlineExceeded = 4, + // NOT_FOUND means some requested entity (e.g., file or directory) was not found. + NotFound = 5, + // ALREADY_EXISTS means an entity that we attempted to create (e.g., file or directory) already exists. + AlreadyExists = 6, + // PERMISSION_DENIED indicates the caller does not have permission to execute the specified operation. + PermissionDenied = 7, + // UNAUTHENTICATED indicates the request does not have valid authentication credentials for the operation. + UNAUTHENTICATED = 16, + // RESOURCE_EXHAUSTED indicates some resource has been exhausted, perhaps a per-user quota, or perhaps the entire file system is out of space. + ResourceExhausted = 8, + // FAILED_PRECONDITION indicates operation was rejected because the system is not in a state required for the operation's execution. + FailedPrecondition = 9, + // ABORTED indicates the operation was aborted. + Aborted = 10, + // OUT_OF_RANGE means operation was attempted past the valid range. + OutOfRange = 11, + // UNIMPLEMENTED indicates operation is not implemented or not supported/enabled. + Unimplemented = 12, + // INTERNAL errors are internal errors. + Internal = 13, + // UNAVAILABLE indicates service is currently unavailable. + Unavailable = 14, + // DATA_LOSS indicates unrecoverable data loss or corruption. + DataLoss = 15, +} + +pub(crate) trait ChromaError: Error { + fn code(&self) -> ErrorCodes; +} diff --git a/rust/worker/src/index/hnsw.rs b/rust/worker/src/index/hnsw.rs new file mode 100644 index 0000000000000000000000000000000000000000..49eb5efb2c9614461961964827205d91a9ea9816 --- /dev/null +++ b/rust/worker/src/index/hnsw.rs @@ -0,0 +1,560 @@ +use std::ffi::CString; +use std::ffi::{c_char, c_int}; + +use crate::errors::{ChromaError, ErrorCodes}; + +use super::{Index, IndexConfig, PersistentIndex}; +use crate::types::{Metadata, MetadataValue, MetadataValueConversionError, Segment}; +use thiserror::Error; + +// https://doc.rust-lang.org/nomicon/ffi.html#representing-opaque-structs +#[repr(C)] +struct IndexPtrFFI { + _data: [u8; 0], + _marker: core::marker::PhantomData<(*mut u8, core::marker::PhantomPinned)>, +} + +// TODO: Make this config: +// - Watchable - for dynamic updates +// - Have a notion of static vs dynamic config +// - Have a notion of default config +// - HNSWIndex should store a ref to the config so it can look up the config values. +// deferring this for a config pass +#[derive(Clone, Debug)] +pub(crate) struct HnswIndexConfig { + pub(crate) max_elements: usize, + pub(crate) m: usize, + pub(crate) ef_construction: usize, + pub(crate) ef_search: usize, + pub(crate) random_seed: usize, + pub(crate) persist_path: String, +} + +#[derive(Error, Debug)] +pub(crate) enum HnswIndexFromSegmentError { + #[error("Missing config `{0}`")] + MissingConfig(String), +} + +impl ChromaError for HnswIndexFromSegmentError { + fn code(&self) -> ErrorCodes { + crate::errors::ErrorCodes::InvalidArgument + } +} + +impl HnswIndexConfig { + pub(crate) fn from_segment( + segment: &Segment, + persist_path: &std::path::Path, + ) -> Result> { + let persist_path = match persist_path.to_str() { + Some(persist_path) => persist_path, + None => { + return Err(Box::new(HnswIndexFromSegmentError::MissingConfig( + "persist_path".to_string(), + ))) + } + }; + let metadata = match &segment.metadata { + Some(metadata) => metadata, + None => { + // TODO: This should error, but the configuration is not stored correctly + // after the configuration is refactored to be always stored and doesn't rely on defaults we can fix this + return Ok(HnswIndexConfig { + max_elements: 1000, + m: 16, + ef_construction: 100, + ef_search: 10, + random_seed: 0, + persist_path: persist_path.to_string(), + }); + // return Err(Box::new(HnswIndexFromSegmentError::MissingConfig( + // "metadata".to_string(), + // ))) + } + }; + + fn get_metadata_value_as<'a, T>( + metadata: &'a Metadata, + key: &str, + ) -> Result> + where + T: TryFrom<&'a MetadataValue, Error = MetadataValueConversionError>, + { + let res = match metadata.get(key) { + Some(value) => T::try_from(value), + None => { + return Err(Box::new(HnswIndexFromSegmentError::MissingConfig( + key.to_string(), + ))) + } + }; + match res { + Ok(value) => Ok(value), + Err(e) => Err(Box::new(e)), + } + } + + let max_elements = get_metadata_value_as::(metadata, "hsnw:max_elements")?; + let m = get_metadata_value_as::(metadata, "hnsw:m")?; + let ef_construction = get_metadata_value_as::(metadata, "hnsw:ef_construction")?; + let ef_search = get_metadata_value_as::(metadata, "hnsw:ef_search")?; + return Ok(HnswIndexConfig { + max_elements: max_elements as usize, + m: m as usize, + ef_construction: ef_construction as usize, + ef_search: ef_search as usize, + random_seed: 0, + persist_path: persist_path.to_string(), + }); + } +} + +#[repr(C)] +/// The HnswIndex struct. +/// # Description +/// This struct wraps a pointer to the C++ HnswIndex class and presents a safe Rust interface. +/// # Notes +/// This struct is not thread safe for concurrent reads and writes. Callers should +/// synchronize access to the index between reads and writes. +pub(crate) struct HnswIndex { + ffi_ptr: *const IndexPtrFFI, + dimensionality: i32, +} + +// Make index sync, we should wrap index so that it is sync in the way we expect but for now this implements the trait +unsafe impl Sync for HnswIndex {} +unsafe impl Send for HnswIndex {} + +#[derive(Error, Debug)] + +pub(crate) enum HnswIndexInitError { + #[error("No config provided")] + NoConfigProvided, + #[error("Invalid distance function `{0}`")] + InvalidDistanceFunction(String), + #[error("Invalid path `{0}`. Are you sure the path exists?")] + InvalidPath(String), +} + +impl ChromaError for HnswIndexInitError { + fn code(&self) -> ErrorCodes { + crate::errors::ErrorCodes::InvalidArgument + } +} + +impl Index for HnswIndex { + fn init( + index_config: &IndexConfig, + hnsw_config: Option<&HnswIndexConfig>, + ) -> Result> { + match hnsw_config { + None => return Err(Box::new(HnswIndexInitError::NoConfigProvided)), + Some(config) => { + let distance_function_string: String = + index_config.distance_function.clone().into(); + + let space_name = match CString::new(distance_function_string) { + Ok(space_name) => space_name, + Err(e) => { + return Err(Box::new(HnswIndexInitError::InvalidDistanceFunction( + e.to_string(), + ))) + } + }; + + let ffi_ptr = + unsafe { create_index(space_name.as_ptr(), index_config.dimensionality) }; + + let path = match CString::new(config.persist_path.clone()) { + Ok(path) => path, + Err(e) => return Err(Box::new(HnswIndexInitError::InvalidPath(e.to_string()))), + }; + + unsafe { + init_index( + ffi_ptr, + config.max_elements, + config.m, + config.ef_construction, + config.random_seed, + true, + true, + path.as_ptr(), + ); + } + + let hnsw_index = HnswIndex { + ffi_ptr: ffi_ptr, + dimensionality: index_config.dimensionality, + }; + hnsw_index.set_ef(config.ef_search); + Ok(hnsw_index) + } + } + } + + fn add(&self, id: usize, vector: &[f32]) { + unsafe { add_item(self.ffi_ptr, vector.as_ptr(), id, false) } + } + + fn query(&self, vector: &[f32], k: usize) -> (Vec, Vec) { + let mut ids = vec![0usize; k]; + let mut distance = vec![0.0f32; k]; + unsafe { + knn_query( + self.ffi_ptr, + vector.as_ptr(), + k, + ids.as_mut_ptr(), + distance.as_mut_ptr(), + ); + } + return (ids, distance); + } + + fn get(&self, id: usize) -> Option> { + unsafe { + let mut data: Vec = vec![0.0f32; self.dimensionality as usize]; + get_item(self.ffi_ptr, id, data.as_mut_ptr()); + return Some(data); + } + } +} + +impl PersistentIndex for HnswIndex { + fn save(&self) -> Result<(), Box> { + unsafe { persist_dirty(self.ffi_ptr) }; + Ok(()) + } + + fn load(path: &str, index_config: &IndexConfig) -> Result> { + let distance_function_string: String = index_config.distance_function.clone().into(); + let space_name = match CString::new(distance_function_string) { + Ok(space_name) => space_name, + Err(e) => { + return Err(Box::new(HnswIndexInitError::InvalidDistanceFunction( + e.to_string(), + ))) + } + }; + let ffi_ptr = unsafe { create_index(space_name.as_ptr(), index_config.dimensionality) }; + let path = match CString::new(path.to_string()) { + Ok(path) => path, + Err(e) => return Err(Box::new(HnswIndexInitError::InvalidPath(e.to_string()))), + }; + unsafe { + load_index(ffi_ptr, path.as_ptr(), true, true); + } + let hnsw_index = HnswIndex { + ffi_ptr: ffi_ptr, + dimensionality: index_config.dimensionality, + }; + Ok(hnsw_index) + } +} + +impl HnswIndex { + pub fn set_ef(&self, ef: usize) { + unsafe { set_ef(self.ffi_ptr, ef as c_int) } + } + + pub fn get_ef(&self) -> usize { + unsafe { get_ef(self.ffi_ptr) as usize } + } +} + +#[link(name = "bindings", kind = "static")] +extern "C" { + fn create_index(space_name: *const c_char, dim: c_int) -> *const IndexPtrFFI; + + fn init_index( + index: *const IndexPtrFFI, + max_elements: usize, + M: usize, + ef_construction: usize, + random_seed: usize, + allow_replace_deleted: bool, + is_persistent: bool, + path: *const c_char, + ); + + fn load_index( + index: *const IndexPtrFFI, + path: *const c_char, + allow_replace_deleted: bool, + is_persistent_index: bool, + ); + + fn persist_dirty(index: *const IndexPtrFFI); + + fn add_item(index: *const IndexPtrFFI, data: *const f32, id: usize, replace_deleted: bool); + fn get_item(index: *const IndexPtrFFI, id: usize, data: *mut f32); + fn knn_query( + index: *const IndexPtrFFI, + query_vector: *const f32, + k: usize, + ids: *mut usize, + distance: *mut f32, + ); + + fn get_ef(index: *const IndexPtrFFI) -> c_int; + fn set_ef(index: *const IndexPtrFFI, ef: c_int); + +} + +#[cfg(test)] +pub mod test { + use super::*; + + use crate::index::types::DistanceFunction; + use crate::index::utils; + use rand::Rng; + use rayon::prelude::*; + use rayon::ThreadPoolBuilder; + use tempfile::tempdir; + + #[test] + fn it_initializes_and_can_set_get_ef() { + let n = 1000; + let d: usize = 960; + let tmp_dir = tempdir().unwrap(); + let persist_path = tmp_dir.path().to_str().unwrap().to_string(); + let distance_function = DistanceFunction::Euclidean; + let mut index = HnswIndex::init( + &IndexConfig { + dimensionality: d as i32, + distance_function: distance_function, + }, + Some(&HnswIndexConfig { + max_elements: n, + m: 16, + ef_construction: 100, + ef_search: 10, + random_seed: 0, + persist_path: persist_path, + }), + ); + match index { + Err(e) => panic!("Error initializing index: {}", e), + Ok(index) => { + assert_eq!(index.get_ef(), 10); + index.set_ef(100); + assert_eq!(index.get_ef(), 100); + } + } + } + + #[test] + fn it_can_add_parallel() { + let n = 10; + let d: usize = 960; + let distance_function = DistanceFunction::InnerProduct; + let tmp_dir = tempdir().unwrap(); + let persist_path = tmp_dir.path().to_str().unwrap().to_string(); + let index = HnswIndex::init( + &IndexConfig { + dimensionality: d as i32, + distance_function: distance_function, + }, + Some(&HnswIndexConfig { + max_elements: n, + m: 16, + ef_construction: 100, + ef_search: 100, + random_seed: 0, + persist_path: persist_path, + }), + ); + + let index = match index { + Err(e) => panic!("Error initializing index: {}", e), + Ok(index) => index, + }; + + let ids: Vec = (0..n).collect(); + + // Add data in parallel, using global pool for testing + ThreadPoolBuilder::new() + .num_threads(12) + .build_global() + .unwrap(); + + let mut rng: rand::prelude::ThreadRng = rand::thread_rng(); + let mut datas = Vec::new(); + for i in 0..n { + let mut data: Vec = Vec::new(); + for i in 0..960 { + data.push(rng.gen()); + } + datas.push(data); + } + + (0..n).into_par_iter().for_each(|i| { + let data = &datas[i]; + index.add(ids[i], data); + }); + + // Get the data and check it + let mut i = 0; + for id in ids { + let actual_data = index.get(id); + match actual_data { + None => panic!("No data found for id: {}", id), + Some(actual_data) => { + assert_eq!(actual_data.len(), d); + for j in 0..d { + // Floating point epsilon comparison + assert!((actual_data[j] - datas[i][j]).abs() < 0.00001); + } + } + } + i += 1; + } + } + + #[test] + fn it_can_add_and_basic_query() { + let n = 1; + let d: usize = 960; + let distance_function = DistanceFunction::Euclidean; + let tmp_dir = tempdir().unwrap(); + let persist_path = tmp_dir.path().to_str().unwrap().to_string(); + let index = HnswIndex::init( + &IndexConfig { + dimensionality: d as i32, + distance_function: distance_function, + }, + Some(&HnswIndexConfig { + max_elements: n, + m: 16, + ef_construction: 100, + ef_search: 100, + random_seed: 0, + persist_path: persist_path, + }), + ); + + let index = match index { + Err(e) => panic!("Error initializing index: {}", e), + Ok(index) => index, + }; + assert_eq!(index.get_ef(), 100); + + let data: Vec = utils::generate_random_data(n, d); + let ids: Vec = (0..n).collect(); + + (0..n).into_iter().for_each(|i| { + let data = &data[i * d..(i + 1) * d]; + index.add(ids[i], data); + }); + + // Get the data and check it + let mut i = 0; + for id in ids { + let actual_data = index.get(id); + match actual_data { + None => panic!("No data found for id: {}", id), + Some(actual_data) => { + assert_eq!(actual_data.len(), d); + for j in 0..d { + // Floating point epsilon comparison + assert!((actual_data[j] - data[i * d + j]).abs() < 0.00001); + } + } + } + i += 1; + } + + // Query the data + let query = &data[0..d]; + let (ids, distances) = index.query(query, 1); + assert_eq!(ids.len(), 1); + assert_eq!(distances.len(), 1); + assert_eq!(ids[0], 0); + assert_eq!(distances[0], 0.0); + } + + #[test] + fn it_can_persist_and_load() { + let n = 1000; + let d: usize = 960; + let distance_function = DistanceFunction::Euclidean; + let tmp_dir = tempdir().unwrap(); + let persist_path = tmp_dir.path().to_str().unwrap().to_string(); + let index = HnswIndex::init( + &IndexConfig { + dimensionality: d as i32, + distance_function: distance_function.clone(), + }, + Some(&HnswIndexConfig { + max_elements: n, + m: 32, + ef_construction: 100, + ef_search: 100, + random_seed: 0, + persist_path: persist_path.clone(), + }), + ); + + let index = match index { + Err(e) => panic!("Error initializing index: {}", e), + Ok(index) => index, + }; + + let data: Vec = utils::generate_random_data(n, d); + let ids: Vec = (0..n).collect(); + + (0..n).into_iter().for_each(|i| { + let data = &data[i * d..(i + 1) * d]; + index.add(ids[i], data); + }); + + // Persist the index + let res = index.save(); + match res { + Err(e) => panic!("Error saving index: {}", e), + Ok(_) => {} + } + + // Load the index + let index = HnswIndex::load( + &persist_path, + &IndexConfig { + dimensionality: d as i32, + distance_function: distance_function, + }, + ); + + let index = match index { + Err(e) => panic!("Error loading index: {}", e), + Ok(index) => index, + }; + // TODO: This should be set by the load + index.set_ef(100); + + // Query the data + let query = &data[0..d]; + let (ids, distances) = index.query(query, 1); + assert_eq!(ids.len(), 1); + assert_eq!(distances.len(), 1); + assert_eq!(ids[0], 0); + assert_eq!(distances[0], 0.0); + + // Get the data and check it + let mut i = 0; + for id in ids { + let actual_data = index.get(id); + match actual_data { + None => panic!("No data found for id: {}", id), + Some(actual_data) => { + assert_eq!(actual_data.len(), d); + for j in 0..d { + assert_eq!(actual_data[j], data[i * d + j]); + } + } + } + i += 1; + } + } +} diff --git a/rust/worker/src/index/mod.rs b/rust/worker/src/index/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..ddaf8d737a4662d4eb6a5053f562d0c765b0f4ba --- /dev/null +++ b/rust/worker/src/index/mod.rs @@ -0,0 +1,7 @@ +mod hnsw; +mod types; +mod utils; + +// Re-export types +pub(crate) use hnsw::*; +pub(crate) use types::*; diff --git a/rust/worker/src/index/types.rs b/rust/worker/src/index/types.rs new file mode 100644 index 0000000000000000000000000000000000000000..7af440c947c891472c3b7f17f2f7510612a67de9 --- /dev/null +++ b/rust/worker/src/index/types.rs @@ -0,0 +1,135 @@ +use crate::errors::{ChromaError, ErrorCodes}; +use crate::types::{MetadataValue, Segment}; +use thiserror::Error; + +#[derive(Clone, Debug)] +pub(crate) struct IndexConfig { + pub(crate) dimensionality: i32, + pub(crate) distance_function: DistanceFunction, +} + +#[derive(Error, Debug)] +pub(crate) enum IndexConfigFromSegmentError { + #[error("No space defined")] + NoSpaceDefined, +} + +impl ChromaError for IndexConfigFromSegmentError { + fn code(&self) -> ErrorCodes { + match self { + IndexConfigFromSegmentError::NoSpaceDefined => ErrorCodes::InvalidArgument, + } + } +} + +impl IndexConfig { + pub(crate) fn from_segment( + segment: &Segment, + dimensionality: i32, + ) -> Result> { + let space = match segment.metadata { + Some(ref metadata) => match metadata.get("hnsw:space") { + Some(MetadataValue::Str(space)) => space, + _ => "l2", + }, + None => "l2", + }; + match DistanceFunction::try_from(space) { + Ok(distance_function) => Ok(IndexConfig { + dimensionality: dimensionality, + distance_function: distance_function, + }), + Err(e) => Err(Box::new(e)), + } + } +} + +/// The index trait. +/// # Description +/// This trait defines the interface for a KNN index. +/// # Methods +/// - `init` - Initialize the index with a given dimension and distance function. +/// - `add` - Add a vector to the index. +/// - `query` - Query the index for the K nearest neighbors of a given vector. +pub(crate) trait Index { + fn init( + index_config: &IndexConfig, + custom_config: Option<&C>, + ) -> Result> + where + Self: Sized; + fn add(&self, id: usize, vector: &[f32]); + fn query(&self, vector: &[f32], k: usize) -> (Vec, Vec); + fn get(&self, id: usize) -> Option>; +} + +/// The persistent index trait. +/// # Description +/// This trait defines the interface for a persistent KNN index. +/// # Methods +/// - `save` - Save the index to a given path. Configuration of the destination is up to the implementation. +/// - `load` - Load the index from a given path. +/// # Notes +/// This defines a rudimentary interface for saving and loading indices. +/// TODO: Right now load() takes IndexConfig because we don't implement save/load of the config. +pub(crate) trait PersistentIndex: Index { + fn save(&self) -> Result<(), Box>; + fn load(path: &str, index_config: &IndexConfig) -> Result> + where + Self: Sized; +} + +/// The distance function enum. +/// # Description +/// This enum defines the distance functions supported by indices in Chroma. +/// # Variants +/// - `Euclidean` - The Euclidean or l2 norm. +/// - `Cosine` - The cosine distance. Specifically, 1 - cosine. +/// - `InnerProduct` - The inner product. Specifically, 1 - inner product. +/// # Notes +/// See https://docs.trychroma.com/usage-guide#changing-the-distance-function +#[derive(Clone, Debug)] +pub(crate) enum DistanceFunction { + Euclidean, + Cosine, + InnerProduct, +} + +#[derive(Error, Debug)] +pub(crate) enum DistanceFunctionError { + #[error("Invalid distance function `{0}`")] + InvalidDistanceFunction(String), +} + +impl ChromaError for DistanceFunctionError { + fn code(&self) -> ErrorCodes { + match self { + DistanceFunctionError::InvalidDistanceFunction(_) => ErrorCodes::InvalidArgument, + } + } +} + +impl TryFrom<&str> for DistanceFunction { + type Error = DistanceFunctionError; + + fn try_from(value: &str) -> Result { + match value { + "l2" => Ok(DistanceFunction::Euclidean), + "cosine" => Ok(DistanceFunction::Cosine), + "ip" => Ok(DistanceFunction::InnerProduct), + _ => Err(DistanceFunctionError::InvalidDistanceFunction( + value.to_string(), + )), + } + } +} + +impl Into for DistanceFunction { + fn into(self) -> String { + match self { + DistanceFunction::Euclidean => "l2".to_string(), + DistanceFunction::Cosine => "cosine".to_string(), + DistanceFunction::InnerProduct => "ip".to_string(), + } + } +} diff --git a/rust/worker/src/index/utils.rs b/rust/worker/src/index/utils.rs new file mode 100644 index 0000000000000000000000000000000000000000..35d27a76e849e16e4b2394bb9ace5e37852f0021 --- /dev/null +++ b/rust/worker/src/index/utils.rs @@ -0,0 +1,13 @@ +use rand::Rng; + +pub(super) fn generate_random_data(n: usize, d: usize) -> Vec { + let mut rng: rand::prelude::ThreadRng = rand::thread_rng(); + let mut data = vec![0.0f32; n * d]; + // Generate random data + for i in 0..n { + for j in 0..d { + data[i * d + j] = rng.gen(); + } + } + return data; +} diff --git a/rust/worker/src/ingest/config.rs b/rust/worker/src/ingest/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..b7647cfe30ee23f299061d6c399495817955cf8d --- /dev/null +++ b/rust/worker/src/ingest/config.rs @@ -0,0 +1,6 @@ +use serde::Deserialize; + +#[derive(Deserialize)] +pub(crate) struct IngestConfig { + pub(crate) queue_size: usize, +} diff --git a/rust/worker/src/ingest/ingest.rs b/rust/worker/src/ingest/ingest.rs new file mode 100644 index 0000000000000000000000000000000000000000..bacf627cb76c7f326ac3312c6cd85f01fc063620 --- /dev/null +++ b/rust/worker/src/ingest/ingest.rs @@ -0,0 +1,417 @@ +use async_trait::async_trait; +use bytes::Bytes; +use futures::{StreamExt, TryStreamExt}; +use prost::Message; +use std::{ + collections::{HashMap, HashSet}, + fmt::Debug, + sync::{Arc, RwLock}, +}; + +use crate::{ + assignment::{ + self, + assignment_policy::{self, AssignmentPolicy}, + }, + chroma_proto, + config::{Configurable, WorkerConfig}, + errors::{ChromaError, ErrorCodes}, + memberlist::{CustomResourceMemberlistProvider, Memberlist}, + sysdb::sysdb::{GrpcSysDb, SysDb}, + system::{Component, ComponentContext, ComponentHandle, Handler, Receiver, StreamHandler}, + types::{EmbeddingRecord, EmbeddingRecordConversionError, SeqId}, +}; + +use pulsar::{Consumer, DeserializeMessage, Payload, Pulsar, SubType, TokioExecutor}; +use thiserror::Error; + +use super::message_id::PulsarMessageIdWrapper; + +/// An ingest component is responsible for ingesting data into the system from the log +/// stream. +/// # Notes +/// The only current implementation of the ingest is the Pulsar ingest. +pub(crate) struct Ingest { + assignment_policy: RwLock>, + assigned_topics: RwLock>, + topic_to_handle: RwLock>>, + queue_size: usize, + my_ip: String, + pulsar_tenant: String, + pulsar_namespace: String, + pulsar: Pulsar, + sysdb: Box, + scheduler: Option)>>>, +} + +impl Component for Ingest { + fn queue_size(&self) -> usize { + return self.queue_size; + } +} + +impl Debug for Ingest { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + f.debug_struct("Ingest") + .field("queue_size", &self.queue_size) + .finish() + } +} + +#[derive(Error, Debug)] +pub(crate) enum IngestConfigurationError { + #[error(transparent)] + PulsarError(#[from] pulsar::Error), +} + +impl ChromaError for IngestConfigurationError { + fn code(&self) -> ErrorCodes { + match self { + IngestConfigurationError::PulsarError(_e) => ErrorCodes::Internal, + } + } +} + +// TODO: Nest the ingest assignment policy inside the ingest component config so its +// specific to the ingest component and can be used here +#[async_trait] +impl Configurable for Ingest { + async fn try_from_config(worker_config: &WorkerConfig) -> Result> { + let assignment_policy = assignment_policy::RendezvousHashingAssignmentPolicy::new( + worker_config.pulsar_tenant.clone(), + worker_config.pulsar_namespace.clone(), + ); + + println!("Pulsar connection url: {}", worker_config.pulsar_url); + let pulsar = match Pulsar::builder(worker_config.pulsar_url.clone(), TokioExecutor) + .build() + .await + { + Ok(pulsar) => pulsar, + Err(e) => { + return Err(Box::new(IngestConfigurationError::PulsarError(e))); + } + }; + + // TODO: Sysdb should have a dynamic resolution in sysdb + let sysdb = GrpcSysDb::try_from_config(worker_config).await; + let sysdb = match sysdb { + Ok(sysdb) => sysdb, + Err(err) => { + return Err(err); + } + }; + + let ingest = Ingest { + assignment_policy: RwLock::new(Box::new(assignment_policy)), + assigned_topics: RwLock::new(vec![]), + topic_to_handle: RwLock::new(HashMap::new()), + queue_size: worker_config.ingest.queue_size, + my_ip: worker_config.my_ip.clone(), + pulsar: pulsar, + pulsar_tenant: worker_config.pulsar_tenant.clone(), + pulsar_namespace: worker_config.pulsar_namespace.clone(), + sysdb: Box::new(sysdb), + scheduler: None, + }; + Ok(ingest) + } +} + +impl Ingest { + fn get_topics(&self) -> Vec { + // This mirrors the current python and go code, which assumes a fixed set of topics + let mut topics = Vec::with_capacity(16); + for i in 0..16 { + let topic = format!( + "persistent://{}/{}/chroma_log_{}", + self.pulsar_tenant, self.pulsar_namespace, i + ); + topics.push(topic); + } + return topics; + } + + pub(crate) fn subscribe( + &mut self, + scheduler: Box)>>, + ) { + self.scheduler = Some(scheduler); + } +} + +#[async_trait] +impl Handler for Ingest { + async fn handle(&mut self, msg: Memberlist, ctx: &ComponentContext) { + let mut new_assignments = HashSet::new(); + let candidate_topics: Vec = self.get_topics(); + println!( + "Performing assignment for topics: {:?}. My ip: {}", + candidate_topics, self.my_ip + ); + // Scope for assigner write lock to be released so we don't hold it over await + { + let mut assigner = match self.assignment_policy.write() { + Ok(assigner) => assigner, + Err(err) => { + println!("Failed to read assignment policy: {:?}", err); + return; + } + }; + + // Use the assignment policy to assign topics to this worker + assigner.set_members(msg); + for topic in candidate_topics.iter() { + let assignment = assigner.assign(topic); + let assignment = match assignment { + Ok(assignment) => assignment, + Err(err) => { + // TODO: Log error + continue; + } + }; + if assignment == self.my_ip { + new_assignments.insert(topic); + } + } + } + + // Compute the topics we need to add/remove + let mut to_remove = Vec::new(); + let mut to_add = Vec::new(); + + // Scope for assigned topics read lock to be released so we don't hold it over await + { + let assigned_topics_handle = self.assigned_topics.read(); + match assigned_topics_handle { + Ok(assigned_topics) => { + // Compute the diff between the current assignments and the new assignments + for topic in assigned_topics.iter() { + if !new_assignments.contains(topic) { + to_remove.push(topic.to_string()); + } + } + for topic in new_assignments.iter() { + if !assigned_topics.contains(*topic) { + to_add.push(topic.to_string()); + } + } + } + Err(err) => { + // TODO: Log error and handle lock poisoning + } + } + } + + // Unsubscribe from topics we no longer need to listen to + for topic in to_remove.iter() { + match self.topic_to_handle.write() { + Ok(mut topic_to_handle) => { + let handle = topic_to_handle.remove(topic); + match handle { + Some(mut handle) => { + handle.stop(); + } + None => { + // TODO: This should log an error + println!("No handle found for topic: {}", topic); + } + } + } + Err(err) => { + // TODO: Log an error and handle lock poisoning + } + } + } + + // Subscribe to new topics + for topic in to_add.iter() { + // Do the subscription and register the stream to this ingest component + let consumer: Consumer = self + .pulsar + .consumer() + .with_topic(topic.to_string()) + .with_subscription_type(SubType::Exclusive) + .build() + .await + .unwrap(); + println!("Created consumer for topic: {}", topic); + + let scheduler = match &self.scheduler { + Some(scheduler) => scheduler.clone(), + None => { + // TODO: log error + return; + } + }; + + let ingest_topic_component = + PulsarIngestTopic::new(consumer, self.sysdb.clone(), scheduler); + + let handle = ctx.system.clone().start_component(ingest_topic_component); + + // Bookkeep the handle so we can shut the stream down later + match self.topic_to_handle.write() { + Ok(mut topic_to_handle) => { + topic_to_handle.insert(topic.to_string(), handle); + } + Err(err) => { + // TODO: log error and handle lock poisoning + println!("Failed to write topic to handle: {:?}", err); + } + } + } + } +} + +impl DeserializeMessage for chroma_proto::SubmitEmbeddingRecord { + type Output = Self; + + fn deserialize_message(payload: &Payload) -> chroma_proto::SubmitEmbeddingRecord { + // Its a bit strange to unwrap here, but the pulsar api doesn't give us a way to + // return an error, so we have to panic if we can't decode the message + // also we are forced to clone since the api doesn't give us a way to borrow the bytes + // TODO: can we not clone? + // TODO: I think just typing this to Result<> would allow errors to propagate + let record = + chroma_proto::SubmitEmbeddingRecord::decode(Bytes::from(payload.data.clone())).unwrap(); + return record; + } +} + +struct PulsarIngestTopic { + consumer: RwLock>>, + sysdb: Box, + scheduler: Box)>>, +} + +impl Debug for PulsarIngestTopic { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + f.debug_struct("PulsarIngestTopic").finish() + } +} + +impl PulsarIngestTopic { + fn new( + consumer: Consumer, + sysdb: Box, + scheduler: Box)>>, + ) -> Self { + PulsarIngestTopic { + consumer: RwLock::new(Some(consumer)), + sysdb: sysdb, + scheduler: scheduler, + } + } +} + +impl Component for PulsarIngestTopic { + fn queue_size(&self) -> usize { + 1000 + } + + fn on_start(&mut self, ctx: &ComponentContext) -> () { + println!("Starting PulsarIngestTopic for topic"); + let stream = match self.consumer.write() { + Ok(mut consumer_handle) => consumer_handle.take(), + Err(err) => { + println!("Failed to take consumer handle: {:?}", err); + None + } + }; + let stream = match stream { + Some(stream) => stream, + None => { + return; + } + }; + let stream = stream.then(|result| async { + match result { + Ok(msg) => { + println!( + "PulsarIngestTopic received message with id: {:?}", + msg.message_id + ); + // Convert the Pulsar Message to an EmbeddingRecord + let proto_embedding_record = msg.deserialize(); + let id = msg.message_id; + let seq_id: SeqId = PulsarMessageIdWrapper(id).into(); + let embedding_record: Result = + (proto_embedding_record, seq_id).try_into(); + match embedding_record { + Ok(embedding_record) => { + return Some(Box::new(embedding_record)); + } + Err(err) => { + // TODO: Handle and log + println!("PulsarIngestTopic received error while performing conversion: {:?}", err); + } + } + None + } + Err(err) => { + // TODO: Log an error + println!("PulsarIngestTopic received error: {:?}", err); + // Put this on a dead letter queue, this concept does not exist in our + // system yet + None + } + } + }); + self.register_stream(stream, ctx); + } +} + +#[async_trait] +impl Handler>> for PulsarIngestTopic { + async fn handle( + &mut self, + message: Option>, + _ctx: &ComponentContext, + ) -> () { + // Use the sysdb to tenant id for the embedding record + let embedding_record = match message { + Some(embedding_record) => embedding_record, + None => { + return; + } + }; + + // TODO: Cache this + let coll = self + .sysdb + .get_collections(Some(embedding_record.collection_id), None, None, None, None) + .await; + + let coll = match coll { + Ok(coll) => coll, + Err(err) => { + println!( + "PulsarIngestTopic received error while fetching collection: {:?}", + err + ); + return; + } + }; + + let coll = match coll.first() { + Some(coll) => coll, + None => { + println!("PulsarIngestTopic received empty collection"); + return; + } + }; + + let tenant_id = &coll.tenant; + + let _ = self + .scheduler + .send((tenant_id.clone(), embedding_record)) + .await; + + // TODO: Handle res + } +} + +#[async_trait] +impl StreamHandler>> for PulsarIngestTopic {} diff --git a/rust/worker/src/ingest/message_id.rs b/rust/worker/src/ingest/message_id.rs new file mode 100644 index 0000000000000000000000000000000000000000..3ac3d05a1eafc07a74e788a728bc6c08b2d6fdaf --- /dev/null +++ b/rust/worker/src/ingest/message_id.rs @@ -0,0 +1,48 @@ +use std::ops::Deref; + +// mirrors chromadb/utils/messageid.py +use num_bigint::BigInt; +use pulsar::{consumer::data::MessageData, proto::MessageIdData}; + +use crate::types::SeqId; + +pub(crate) struct PulsarMessageIdWrapper(pub(crate) MessageData); + +impl Deref for PulsarMessageIdWrapper { + type Target = MessageIdData; + + fn deref(&self) -> &Self::Target { + &self.0.id + } +} + +pub(crate) fn pulsar_to_int(message_id: PulsarMessageIdWrapper) -> SeqId { + let ledger_id = message_id.ledger_id; + let entry_id = message_id.entry_id; + let batch_index = message_id.batch_index.unwrap_or(0); + let partition = message_id.partition.unwrap_or(0); + + let mut ledger_id = BigInt::from(ledger_id); + let mut entry_id = BigInt::from(entry_id); + let mut batch_index = BigInt::from(batch_index); + let mut partition = BigInt::from(partition); + + // Convert to offset binary encoding to preserve ordering semantics when encoded + // see https://en.wikipedia.org/wiki/Offset_binary + ledger_id = ledger_id + BigInt::from(2).pow(63); + entry_id = entry_id + BigInt::from(2).pow(63); + batch_index = batch_index + BigInt::from(2).pow(31); + partition = partition + BigInt::from(2).pow(31); + + let res = ledger_id << 128 | entry_id << 96 | batch_index << 64 | partition; + res +} + +// We can't use From because we don't own the type +// So the pattern is to wrap it in a newtype and implement TryFrom for that +// And implement Dereference for the newtype to the underlying type +impl From for SeqId { + fn from(message_id: PulsarMessageIdWrapper) -> Self { + return pulsar_to_int(message_id); + } +} diff --git a/rust/worker/src/ingest/mod.rs b/rust/worker/src/ingest/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..ae7aaf8d7b52703517b06339a91931ef989b31d2 --- /dev/null +++ b/rust/worker/src/ingest/mod.rs @@ -0,0 +1,8 @@ +pub(crate) mod config; +mod ingest; +mod message_id; +mod scheduler; + +// Re-export the ingest provider for use in the worker +pub(crate) use ingest::*; +pub(crate) use scheduler::*; diff --git a/rust/worker/src/ingest/scheduler.rs b/rust/worker/src/ingest/scheduler.rs new file mode 100644 index 0000000000000000000000000000000000000000..770e9bb0bbf63db9a48bf61328c4f361c5998b68 --- /dev/null +++ b/rust/worker/src/ingest/scheduler.rs @@ -0,0 +1,212 @@ +// A scheduler recieves embedding records for a given batch of documents +// and schedules them to be ingested to the segment manager + +use crate::{ + system::{Component, ComponentContext, Handler, Receiver}, + types::EmbeddingRecord, +}; +use async_trait::async_trait; +use rand::prelude::SliceRandom; +use rand::Rng; +use std::{ + collections::{btree_map::Range, HashMap}, + fmt::{Debug, Formatter, Result}, + sync::Arc, +}; + +pub(crate) struct RoundRobinScheduler { + // The segment manager to schedule to, a segment manager is a component + // segment_manager: SegmentManager + curr_wake_up: Option>, + tenant_to_queue: HashMap>>, + new_tenant_channel: Option>, + subscribers: Option>>>>, +} + +impl Debug for RoundRobinScheduler { + fn fmt(&self, f: &mut Formatter<'_>) -> Result { + f.debug_struct("Scheduler").finish() + } +} + +impl RoundRobinScheduler { + pub(crate) fn new() -> Self { + RoundRobinScheduler { + curr_wake_up: None, + tenant_to_queue: HashMap::new(), + new_tenant_channel: None, + subscribers: Some(Vec::new()), + } + } + + pub(crate) fn subscribe(&mut self, subscriber: Box>>) { + match self.subscribers { + Some(ref mut subscribers) => { + subscribers.push(subscriber); + } + None => {} + } + } +} + +impl Component for RoundRobinScheduler { + fn queue_size(&self) -> usize { + 1000 + } + + fn on_start(&mut self, ctx: &ComponentContext) { + let sleep_sender = ctx.sender.clone(); + let (new_tenant_tx, mut new_tenant_rx) = tokio::sync::mpsc::channel(1000); + self.new_tenant_channel = Some(new_tenant_tx); + let cancellation_token = ctx.cancellation_token.clone(); + let subscribers = self.subscribers.take(); + let mut subscribers = match subscribers { + Some(subscribers) => subscribers, + None => { + // TODO: log + error + return; + } + }; + tokio::spawn(async move { + let mut tenant_queues: HashMap< + String, + tokio::sync::mpsc::Receiver>, + > = HashMap::new(); + loop { + // TODO: handle cancellation + let mut did_work = false; + for tenant_queue in tenant_queues.values_mut() { + match tenant_queue.try_recv() { + Ok(message) => { + // Randomly pick a subscriber to send the message to + // This serves as a crude load balancing between available threads + // Future improvements here could be + // - Use a work stealing scheduler + // - Use rayon + // - We need to enforce partial order over writes to a given key + // so we need a mechanism to ensure that all writes to a given key + // occur in order + let mut subscriber = None; + { + let mut rng = rand::thread_rng(); + subscriber = subscribers.choose_mut(&mut rng); + } + match subscriber { + Some(subscriber) => { + let res = subscriber.send(message).await; + } + None => {} + } + did_work = true; + } + Err(tokio::sync::mpsc::error::TryRecvError::Empty) => { + continue; + } + Err(_) => { + // TODO: Handle a erroneous channel + // log an error + continue; + } + }; + } + + match new_tenant_rx.try_recv() { + Ok(new_tenant_message) => { + tenant_queues.insert(new_tenant_message.tenant, new_tenant_message.channel); + } + Err(tokio::sync::mpsc::error::TryRecvError::Empty) => { + // no - op + } + Err(_) => { + // TODO: handle erroneous channel + // log an error + continue; + } + }; + + if !did_work { + // Send a sleep message to the sender + let (wake_tx, wake_rx) = tokio::sync::oneshot::channel(); + let sleep_res = sleep_sender.send(SleepMessage { sender: wake_tx }).await; + let wake_res = wake_rx.await; + } + } + }); + } +} + +#[async_trait] +impl Handler<(String, Box)> for RoundRobinScheduler { + async fn handle( + &mut self, + message: (String, Box), + _ctx: &ComponentContext, + ) { + let (tenant, embedding_record) = message; + // Check if the tenant is already in the tenant set, if not we need to inform the scheduler loop + // of a new tenant + if self.tenant_to_queue.get(&tenant).is_none() { + // Create a new channel for the tenant + let (sender, reciever) = tokio::sync::mpsc::channel(1000); + // Add the tenant to the tenant set + self.tenant_to_queue.insert(tenant.clone(), sender); + // Send the new tenant message to the scheduler loop + let new_tenant_channel = match self.new_tenant_channel { + Some(ref mut channel) => channel, + None => { + // TODO: this is an error + // It should always be populated by on_start + return; + } + }; + let res = new_tenant_channel + .send(NewTenantMessage { + tenant: tenant.clone(), + channel: reciever, + }) + .await; + // TODO: handle this res + } + + // Send the embedding record to the tenant's channel + let res = self + .tenant_to_queue + .get(&tenant) + .unwrap() + .send(embedding_record) + .await; + // TODO: handle this res + + // Check if the scheduler is sleeping, if so wake it up + // TODO: we need to init with a wakeup otherwise we are off by one + if self.curr_wake_up.is_some() { + // Send a wake up message to the scheduler loop + let res = self.curr_wake_up.take().unwrap().send(WakeMessage {}); + // TOOD: handle this res + } + } +} + +#[async_trait] +impl Handler for RoundRobinScheduler { + async fn handle(&mut self, message: SleepMessage, _ctx: &ComponentContext) { + // Set the current wake up channel + self.curr_wake_up = Some(message.sender); + } +} + +/// Used by round robin scheduler to wake its scheduler loop +#[derive(Debug)] +struct WakeMessage {} + +/// The round robin scheduler will sleep when there is no work to be done and send a sleep message +/// this allows the manager to wake it up when there is work to be scheduled +#[derive(Debug)] +struct SleepMessage { + sender: tokio::sync::oneshot::Sender, +} + +struct NewTenantMessage { + tenant: String, + channel: tokio::sync::mpsc::Receiver>, +} diff --git a/rust/worker/src/lib.rs b/rust/worker/src/lib.rs new file mode 100644 index 0000000000000000000000000000000000000000..ae7ea7dc7d522fdaf25c63fe0ed6a832e5f89cc2 --- /dev/null +++ b/rust/worker/src/lib.rs @@ -0,0 +1,103 @@ +mod assignment; +mod config; +mod errors; +mod index; +mod ingest; +mod memberlist; +mod segment; +mod server; +mod storage; +mod sysdb; +mod system; +mod types; + +use config::Configurable; +use memberlist::MemberlistProvider; + +use crate::sysdb::sysdb::SysDb; + +mod chroma_proto { + tonic::include_proto!("chroma"); +} + +pub async fn worker_entrypoint() { + let config = config::RootConfig::load(); + // Create all the core components and start them + // TODO: This should be handled by an Application struct and we can push the config into it + // for now we expose the config to pub and inject it into the components + + // The two root components are ingest, and the gRPC server + let mut system: system::System = system::System::new(); + + let mut ingest = match ingest::Ingest::try_from_config(&config.worker).await { + Ok(ingest) => ingest, + Err(err) => { + println!("Failed to create ingest component: {:?}", err); + return; + } + }; + + let mut memberlist = + match memberlist::CustomResourceMemberlistProvider::try_from_config(&config.worker).await { + Ok(memberlist) => memberlist, + Err(err) => { + println!("Failed to create memberlist component: {:?}", err); + return; + } + }; + + let mut scheduler = ingest::RoundRobinScheduler::new(); + + let segment_manager = match segment::SegmentManager::try_from_config(&config.worker).await { + Ok(segment_manager) => segment_manager, + Err(err) => { + println!("Failed to create segment manager component: {:?}", err); + return; + } + }; + + let mut segment_ingestor_receivers = + Vec::with_capacity(config.worker.num_indexing_threads as usize); + for _ in 0..config.worker.num_indexing_threads { + let segment_ingestor = segment::SegmentIngestor::new(segment_manager.clone()); + let segment_ingestor_handle = system.start_component(segment_ingestor); + let recv = segment_ingestor_handle.receiver(); + segment_ingestor_receivers.push(recv); + } + + let mut worker_server = match server::WorkerServer::try_from_config(&config.worker).await { + Ok(worker_server) => worker_server, + Err(err) => { + println!("Failed to create worker server component: {:?}", err); + return; + } + }; + worker_server.set_segment_manager(segment_manager.clone()); + + // Boot the system + // memberlist -> ingest -> scheduler -> NUM_THREADS x segment_ingestor -> segment_manager + // server <- segment_manager + + for recv in segment_ingestor_receivers { + scheduler.subscribe(recv); + } + + let mut scheduler_handler = system.start_component(scheduler); + ingest.subscribe(scheduler_handler.receiver()); + + let mut ingest_handle = system.start_component(ingest); + let recv = ingest_handle.receiver(); + memberlist.subscribe(recv); + let mut memberlist_handle = system.start_component(memberlist); + + let server_join_handle = tokio::spawn(async move { + crate::server::WorkerServer::run(worker_server).await; + }); + + // Join on all handles + let _ = tokio::join!( + ingest_handle.join(), + memberlist_handle.join(), + scheduler_handler.join(), + ); +} diff --git a/rust/worker/src/memberlist/config.rs b/rust/worker/src/memberlist/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..d6aaf2c8682e0fbcfaa1359f54cf694d90adf60b --- /dev/null +++ b/rust/worker/src/memberlist/config.rs @@ -0,0 +1,27 @@ +use serde::Deserialize; + +#[derive(Deserialize)] +/// The type of memberlist provider to use +/// # Options +/// - CustomResource: Use a custom resource to get the memberlist +pub(crate) enum MemberlistProviderType { + CustomResource, +} + +/// The configuration for the memberlist provider. +/// # Options +/// - CustomResource: Use a custom resource to get the memberlist +#[derive(Deserialize)] +pub(crate) enum MemberlistProviderConfig { + CustomResource(CustomResourceMemberlistProviderConfig), +} + +/// The configuration for the custom resource memberlist provider. +/// # Fields +/// - memberlist_name: The name of the custom resource to use for the memberlist. +/// - queue_size: The size of the queue to use for the channel. +#[derive(Deserialize)] +pub(crate) struct CustomResourceMemberlistProviderConfig { + pub(crate) memberlist_name: String, + pub(crate) queue_size: usize, +} diff --git a/rust/worker/src/memberlist/memberlist_provider.rs b/rust/worker/src/memberlist/memberlist_provider.rs new file mode 100644 index 0000000000000000000000000000000000000000..ea58228ae980d5a977f9dfb54bae3ba885c68a1a --- /dev/null +++ b/rust/worker/src/memberlist/memberlist_provider.rs @@ -0,0 +1,268 @@ +use std::sync::Arc; +use std::{fmt::Debug, sync::RwLock}; + +use super::config::{CustomResourceMemberlistProviderConfig, MemberlistProviderConfig}; +use crate::system::{Receiver, Sender}; +use crate::{ + config::{Configurable, WorkerConfig}, + errors::{ChromaError, ErrorCodes}, + system::{Component, ComponentContext, Handler, StreamHandler}, +}; +use async_trait::async_trait; +use futures::{StreamExt, TryStreamExt}; +use k8s_openapi::api::events::v1::Event; +use kube::{ + api::Api, + config, + runtime::{watcher, watcher::Error as WatchError, WatchStreamExt}, + Client, CustomResource, +}; +use schemars::JsonSchema; +use serde::{Deserialize, Serialize}; +use thiserror::Error; +use tokio_util::sync::CancellationToken; + +/* =========== Basic Types ============== */ +pub(crate) type Memberlist = Vec; + +#[async_trait] +pub(crate) trait MemberlistProvider: Component + Configurable { + fn subscribe(&mut self, receiver: Box + Send>) -> (); +} + +/* =========== CRD ============== */ +#[derive(CustomResource, Clone, Debug, Deserialize, Serialize, JsonSchema)] +#[kube( + group = "chroma.cluster", + version = "v1", + kind = "MemberList", + root = "MemberListKubeResource", + namespaced +)] +pub(crate) struct MemberListCrd { + pub(crate) members: Vec, +} + +// Define the structure for items in the members array +#[derive(Clone, Debug, Deserialize, Serialize, JsonSchema)] +pub(crate) struct Member { + pub(crate) url: String, +} + +/* =========== CR Provider ============== */ +pub(crate) struct CustomResourceMemberlistProvider { + memberlist_name: String, + kube_client: Client, + kube_ns: String, + memberlist_cr_client: Api, + queue_size: usize, + current_memberlist: RwLock, + subscribers: Vec + Send>>, +} + +impl Debug for CustomResourceMemberlistProvider { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + f.debug_struct("CustomResourceMemberlistProvider") + .field("memberlist_name", &self.memberlist_name) + .field("kube_ns", &self.kube_ns) + .field("queue_size", &self.queue_size) + .finish() + } +} + +#[derive(Error, Debug)] +pub(crate) enum CustomResourceMemberlistProviderConfigurationError { + #[error("Failed to load kube client")] + FailedToLoadKubeClient(#[from] kube::Error), +} + +impl ChromaError for CustomResourceMemberlistProviderConfigurationError { + fn code(&self) -> crate::errors::ErrorCodes { + match self { + CustomResourceMemberlistProviderConfigurationError::FailedToLoadKubeClient(e) => { + ErrorCodes::Internal + } + } + } +} + +#[async_trait] +impl Configurable for CustomResourceMemberlistProvider { + async fn try_from_config(worker_config: &WorkerConfig) -> Result> { + let my_config = match &worker_config.memberlist_provider { + MemberlistProviderConfig::CustomResource(config) => config, + }; + let kube_client = match Client::try_default().await { + Ok(client) => client, + Err(err) => { + return Err(Box::new( + CustomResourceMemberlistProviderConfigurationError::FailedToLoadKubeClient(err), + )) + } + }; + let memberlist_cr_client = Api::::namespaced( + kube_client.clone(), + &worker_config.kube_namespace, + ); + + let c: CustomResourceMemberlistProvider = CustomResourceMemberlistProvider { + memberlist_name: my_config.memberlist_name.clone(), + kube_ns: worker_config.kube_namespace.clone(), + kube_client: kube_client, + memberlist_cr_client: memberlist_cr_client, + queue_size: my_config.queue_size, + current_memberlist: RwLock::new(vec![]), + subscribers: vec![], + }; + Ok(c) + } +} + +impl CustomResourceMemberlistProvider { + fn new( + memberlist_name: String, + kube_client: Client, + kube_ns: String, + queue_size: usize, + ) -> Self { + let memberlist_cr_client = + Api::::namespaced(kube_client.clone(), &kube_ns); + CustomResourceMemberlistProvider { + memberlist_name: memberlist_name, + kube_ns: kube_ns, + kube_client: kube_client, + memberlist_cr_client: memberlist_cr_client, + queue_size: queue_size, + current_memberlist: RwLock::new(vec![]), + subscribers: vec![], + } + } + + fn connect_to_kube_stream(&self, ctx: &ComponentContext) { + let memberlist_cr_client = + Api::::namespaced(self.kube_client.clone(), &self.kube_ns); + + let stream = watcher(memberlist_cr_client, watcher::Config::default()) + .default_backoff() + .applied_objects(); + let stream = stream.then(|event| async move { + match event { + Ok(event) => { + let event = event; + println!("Kube stream event: {:?}", event); + Some(event) + } + Err(err) => { + println!("Error acquiring memberlist: {}", err); + None + } + } + }); + self.register_stream(stream, ctx); + } + + async fn notify_subscribers(&self) -> () { + let curr_memberlist = match self.current_memberlist.read() { + Ok(curr_memberlist) => curr_memberlist.clone(), + Err(err) => { + // TODO: Log error and attempt recovery + return; + } + }; + + for subscriber in self.subscribers.iter() { + let _ = subscriber.send(curr_memberlist.clone()).await; + } + } +} + +impl Component for CustomResourceMemberlistProvider { + fn queue_size(&self) -> usize { + self.queue_size + } + + fn on_start(&mut self, ctx: &ComponentContext) { + self.connect_to_kube_stream(ctx); + } +} + +#[async_trait] +impl Handler> for CustomResourceMemberlistProvider { + async fn handle( + &mut self, + event: Option, + _ctx: &ComponentContext, + ) { + match event { + Some(memberlist) => { + println!("Memberlist event in CustomResourceMemberlistProvider. Name: {:?}. Members: {:?}", memberlist.metadata.name, memberlist.spec.members); + let name = match &memberlist.metadata.name { + Some(name) => name, + None => { + // TODO: Log an error + return; + } + }; + if name != &self.memberlist_name { + return; + } + let memberlist = memberlist.spec.members; + let memberlist = memberlist + .iter() + .map(|member| member.url.clone()) + .collect::>(); + { + let curr_memberlist_handle = self.current_memberlist.write(); + match curr_memberlist_handle { + Ok(mut curr_memberlist) => { + *curr_memberlist = memberlist; + } + Err(err) => { + // TODO: Log an error + } + } + } + // Inform subscribers + self.notify_subscribers().await; + } + None => { + // Stream closed or error + } + } + } +} + +impl StreamHandler> for CustomResourceMemberlistProvider {} + +#[async_trait] +impl MemberlistProvider for CustomResourceMemberlistProvider { + fn subscribe(&mut self, sender: Box + Send>) -> () { + self.subscribers.push(sender); + } +} + +#[cfg(test)] +mod tests { + use crate::system::System; + + use super::*; + + #[tokio::test] + #[cfg(CHROMA_KUBERNETES_INTEGRATION)] + async fn it_can_work() { + // TODO: This only works if you have a kubernetes cluster running locally with a memberlist + // We need to implement a test harness for this. For now, it will silently do nothing + // if you don't have a kubernetes cluster running locally and only serve as a reminder + // and demonstration of how to use the memberlist provider. + let kube_ns = "chroma".to_string(); + let kube_client = Client::try_default().await.unwrap(); + let memberlist_provider = CustomResourceMemberlistProvider::new( + "worker-memberlist".to_string(), + kube_client.clone(), + kube_ns.clone(), + 10, + ); + let mut system = System::new(); + let handle = system.start_component(memberlist_provider); + } +} diff --git a/rust/worker/src/memberlist/mod.rs b/rust/worker/src/memberlist/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..14512b0202332374e7147f650aa002588f95f061 --- /dev/null +++ b/rust/worker/src/memberlist/mod.rs @@ -0,0 +1,5 @@ +pub(crate) mod config; +mod memberlist_provider; + +// Re-export the memberlist provider for use in the worker +pub(crate) use memberlist_provider::*; diff --git a/rust/worker/src/segment/config.rs b/rust/worker/src/segment/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..56374670e6c4eb1d3b9620ac7f3bf243337fb8dc --- /dev/null +++ b/rust/worker/src/segment/config.rs @@ -0,0 +1,9 @@ +use serde::Deserialize; + +/// The configuration for the custom resource memberlist provider. +/// # Fields +/// - storage_path: The path to use for temporary storage in the segment manager, if needed. +#[derive(Deserialize)] +pub(crate) struct SegmentManagerConfig { + pub(crate) storage_path: String, +} diff --git a/rust/worker/src/segment/distributed_hnsw_segment.rs b/rust/worker/src/segment/distributed_hnsw_segment.rs new file mode 100644 index 0000000000000000000000000000000000000000..d6f9ca265251413b18ab7076025de6dfe2f1d34d --- /dev/null +++ b/rust/worker/src/segment/distributed_hnsw_segment.rs @@ -0,0 +1,136 @@ +use num_bigint::BigInt; +use parking_lot::{Mutex, RwLock, RwLockUpgradableReadGuard, RwLockWriteGuard}; +use std::collections::HashMap; +use std::sync::atomic::AtomicUsize; +use std::sync::Arc; + +use crate::errors::ChromaError; +use crate::index::{HnswIndex, HnswIndexConfig, Index, IndexConfig}; +use crate::types::{EmbeddingRecord, Operation, Segment, VectorEmbeddingRecord}; + +pub(crate) struct DistributedHNSWSegment { + index: Arc>, + id: AtomicUsize, + user_id_to_id: Arc>>, + id_to_user_id: Arc>>, + index_config: IndexConfig, + hnsw_config: HnswIndexConfig, +} + +impl DistributedHNSWSegment { + pub(crate) fn new( + index_config: IndexConfig, + hnsw_config: HnswIndexConfig, + ) -> Result> { + let hnsw_index = HnswIndex::init(&index_config, Some(&hnsw_config)); + let hnsw_index = match hnsw_index { + Ok(index) => index, + Err(e) => { + // TODO: log + handle an error that we failed to init the index + return Err(e); + } + }; + let index = Arc::new(RwLock::new(hnsw_index)); + return Ok(DistributedHNSWSegment { + index: index, + id: AtomicUsize::new(0), + user_id_to_id: Arc::new(RwLock::new(HashMap::new())), + id_to_user_id: Arc::new(RwLock::new(HashMap::new())), + index_config: index_config, + hnsw_config, + }); + } + + pub(crate) fn from_segment( + segment: &Segment, + persist_path: &std::path::Path, + dimensionality: usize, + ) -> Result, Box> { + let index_config = IndexConfig::from_segment(&segment, dimensionality as i32)?; + let hnsw_config = HnswIndexConfig::from_segment(segment, persist_path)?; + Ok(Box::new(DistributedHNSWSegment::new( + index_config, + hnsw_config, + )?)) + } + + pub(crate) fn write_records(&self, records: Vec>) { + for record in records { + let op = Operation::try_from(record.operation); + match op { + Ok(Operation::Add) => { + // TODO: make lock xor lock + match &record.embedding { + Some(vector) => { + let next_id = self.id.fetch_add(1, std::sync::atomic::Ordering::SeqCst); + self.user_id_to_id + .write() + .insert(record.id.clone(), next_id); + self.id_to_user_id + .write() + .insert(next_id, record.id.clone()); + println!("Segment adding item: {}", next_id); + self.index.read().add(next_id, &vector); + } + None => { + // TODO: log an error + println!("No vector found in record"); + } + } + } + Ok(Operation::Upsert) => {} + Ok(Operation::Update) => {} + Ok(Operation::Delete) => {} + Err(_) => { + println!("Error parsing operation"); + } + } + } + } + + pub(crate) fn get_records(&self, ids: Vec) -> Vec> { + let mut records = Vec::new(); + let user_id_to_id = self.user_id_to_id.read(); + let index = self.index.read(); + for id in ids { + let internal_id = match user_id_to_id.get(&id) { + Some(internal_id) => internal_id, + None => { + // TODO: Error + return records; + } + }; + let vector = index.get(*internal_id); + match vector { + Some(vector) => { + let record = VectorEmbeddingRecord { + id: id, + seq_id: BigInt::from(0), + vector, + }; + records.push(Box::new(record)); + } + None => { + // TODO: error + } + } + } + return records; + } + + pub(crate) fn query(&self, vector: &[f32], k: usize) -> (Vec, Vec) { + let index = self.index.read(); + let mut return_user_ids = Vec::new(); + let (ids, distances) = index.query(vector, k); + let user_ids = self.id_to_user_id.read(); + for id in ids { + match user_ids.get(&id) { + Some(user_id) => return_user_ids.push(user_id.clone()), + None => { + // TODO: error + } + }; + } + return (return_user_ids, distances); + } +} diff --git a/rust/worker/src/segment/mod.rs b/rust/worker/src/segment/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..5b56f40422f05deb1622f7201524e005ae61e6c0 --- /dev/null +++ b/rust/worker/src/segment/mod.rs @@ -0,0 +1,7 @@ +pub(crate) mod config; +mod distributed_hnsw_segment; +mod segment_ingestor; +mod segment_manager; + +pub(crate) use segment_ingestor::*; +pub(crate) use segment_manager::*; diff --git a/rust/worker/src/segment/segment_ingestor.rs b/rust/worker/src/segment/segment_ingestor.rs new file mode 100644 index 0000000000000000000000000000000000000000..e22abdd9eada75578587b1d9e857f4f7775793a8 --- /dev/null +++ b/rust/worker/src/segment/segment_ingestor.rs @@ -0,0 +1,48 @@ +// A segment ingestor is a component that ingests embeddings into a segment +// Its designed to consume from a async_channel that guarantees exclusive consumption +// They are spawned onto a dedicated thread runtime since ingesting is cpu bound + +use async_trait::async_trait; +use std::{fmt::Debug, sync::Arc}; + +use crate::{ + system::{Component, ComponentContext, ComponentRuntime, Handler}, + types::EmbeddingRecord, +}; + +use super::segment_manager::{self, SegmentManager}; + +pub(crate) struct SegmentIngestor { + segment_manager: SegmentManager, +} + +impl Component for SegmentIngestor { + fn queue_size(&self) -> usize { + 1000 + } + fn runtime() -> ComponentRuntime { + ComponentRuntime::Dedicated + } +} + +impl Debug for SegmentIngestor { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + f.debug_struct("SegmentIngestor").finish() + } +} + +impl SegmentIngestor { + pub(crate) fn new(segment_manager: SegmentManager) -> Self { + SegmentIngestor { + segment_manager: segment_manager, + } + } +} + +#[async_trait] +impl Handler> for SegmentIngestor { + async fn handle(&mut self, message: Box, ctx: &ComponentContext) { + println!("INGEST: ID of embedding is {}", message.id); + self.segment_manager.write_record(message).await; + } +} diff --git a/rust/worker/src/segment/segment_manager.rs b/rust/worker/src/segment/segment_manager.rs new file mode 100644 index 0000000000000000000000000000000000000000..314a5b99cdfd6ebd42dc88ff85d62aa2ac46223c --- /dev/null +++ b/rust/worker/src/segment/segment_manager.rs @@ -0,0 +1,252 @@ +use crate::{ + config::{Configurable, WorkerConfig}, + errors::ChromaError, + sysdb::sysdb::{GrpcSysDb, SysDb}, + types::VectorQueryResult, +}; +use async_trait::async_trait; +use k8s_openapi::api::node; +use num_bigint::BigInt; +use parking_lot::{ + MappedRwLockReadGuard, RwLock, RwLockReadGuard, RwLockUpgradableReadGuard, RwLockWriteGuard, +}; +use std::collections::HashMap; +use std::sync::Arc; +use uuid::Uuid; + +use super::distributed_hnsw_segment::DistributedHNSWSegment; +use crate::types::{EmbeddingRecord, MetadataValue, Segment, SegmentScope, VectorEmbeddingRecord}; + +#[derive(Clone)] +pub(crate) struct SegmentManager { + inner: Arc, + sysdb: Box, +} + +/// +struct Inner { + vector_segments: RwLock>>, + collection_to_segment_cache: RwLock>>>, + storage_path: Box, +} + +impl SegmentManager { + pub(crate) fn new(sysdb: Box, storage_path: &std::path::Path) -> Self { + SegmentManager { + inner: Arc::new(Inner { + vector_segments: RwLock::new(HashMap::new()), + collection_to_segment_cache: RwLock::new(HashMap::new()), + storage_path: Box::new(storage_path.to_owned()), + }), + sysdb: sysdb, + } + } + + pub(crate) async fn write_record(&mut self, record: Box) { + let collection_id = record.collection_id; + let mut target_segment = None; + // TODO: don't assume 1:1 mapping between collection and segment + { + let segments = self.get_segments(&collection_id).await; + target_segment = match segments { + Ok(found_segments) => { + if found_segments.len() == 0 { + return; // TODO: handle no segment found + } + Some(found_segments[0].clone()) + } + Err(_) => { + // TODO: throw an error and log no segment found + return; + } + }; + } + + let target_segment = match target_segment { + Some(segment) => segment, + None => { + // TODO: throw an error and log no segment found + return; + } + }; + + println!("Writing to segment id {}", target_segment.id); + + let segment_cache = self.inner.vector_segments.upgradable_read(); + match segment_cache.get(&target_segment.id) { + Some(segment) => { + segment.write_records(vec![record]); + } + None => { + let mut segment_cache = RwLockUpgradableReadGuard::upgrade(segment_cache); + + let new_segment = DistributedHNSWSegment::from_segment( + &target_segment, + &self.inner.storage_path, + // TODO: Don't unwrap - throw an error + record.embedding.as_ref().unwrap().len(), + ); + + match new_segment { + Ok(new_segment) => { + new_segment.write_records(vec![record]); + segment_cache.insert(target_segment.id, new_segment); + } + Err(e) => { + println!("Failed to create segment error {}", e); + // TODO: fail and log an error - failed to create/init segment + } + } + } + } + } + + pub(crate) async fn get_records( + &self, + segment_id: &Uuid, + ids: Vec, + ) -> Result>, &'static str> { + // TODO: Load segment if not in cache + let segment_cache = self.inner.vector_segments.read(); + match segment_cache.get(segment_id) { + Some(segment) => { + return Ok(segment.get_records(ids)); + } + None => { + return Err("No segment found"); + } + } + } + + pub(crate) async fn query_vector( + &self, + segment_id: &Uuid, + vectors: &[f32], + k: usize, + include_vector: bool, + ) -> Result>, &'static str> { + let segment_cache = self.inner.vector_segments.read(); + match segment_cache.get(segment_id) { + Some(segment) => { + let mut results = Vec::new(); + let (ids, distances) = segment.query(vectors, k); + for (id, distance) in ids.iter().zip(distances.iter()) { + let fetched_vector = match include_vector { + true => Some(segment.get_records(vec![id.clone()])), + false => None, + }; + + let mut target_record = None; + if include_vector { + target_record = match fetched_vector { + Some(fetched_vectors) => { + if fetched_vectors.len() == 0 { + return Err("No vector found"); + } + let mut target_vec = None; + for vec in fetched_vectors.into_iter() { + if vec.id == *id { + target_vec = Some(vec); + break; + } + } + target_vec + } + None => { + return Err("No vector found"); + } + }; + } + + let ret_vec = match target_record { + Some(target_record) => Some(target_record.vector), + None => None, + }; + + let result = Box::new(VectorQueryResult { + id: id.to_string(), + seq_id: BigInt::from(0), + distance: *distance, + vector: ret_vec, + }); + results.push(result); + } + return Ok(results); + } + None => { + return Err("No segment found"); + } + } + } + + async fn get_segments( + &mut self, + collection_uuid: &Uuid, + ) -> Result>>, &'static str> { + let cache_guard = self.inner.collection_to_segment_cache.read(); + // This lets us return a reference to the segments with the lock. The caller is responsible + // dropping the lock. + let segments = RwLockReadGuard::try_map(cache_guard, |cache| { + return cache.get(&collection_uuid); + }); + match segments { + Ok(segments) => { + return Ok(segments); + } + Err(_) => { + // Data was not in the cache, so we need to get it from the database + // Drop the lock since we need to upgrade it + // Mappable locks cannot be upgraded, so we need to drop the lock and re-acquire it + // https://github.com/Amanieu/parking_lot/issues/83 + drop(segments); + + let segments = self + .sysdb + .get_segments( + None, + None, + Some(SegmentScope::VECTOR), + None, + Some(collection_uuid.clone()), + ) + .await; + match segments { + Ok(segments) => { + let mut cache_guard = self.inner.collection_to_segment_cache.write(); + let mut arc_segments = Vec::new(); + for segment in segments { + arc_segments.push(Arc::new(segment)); + } + cache_guard.insert(collection_uuid.clone(), arc_segments); + let cache_guard = RwLockWriteGuard::downgrade(cache_guard); + let segments = RwLockReadGuard::map(cache_guard, |cache| { + // This unwrap is safe because we just inserted the segments into the cache and currently, + // there is no way to remove segments from the cache. + return cache.get(&collection_uuid).unwrap(); + }); + return Ok(segments); + } + Err(e) => { + return Err("Failed to get segments for collection from SysDB"); + } + } + } + } + } +} + +#[async_trait] +impl Configurable for SegmentManager { + async fn try_from_config(worker_config: &WorkerConfig) -> Result> { + // TODO: Sysdb should have a dynamic resolution in sysdb + let sysdb = GrpcSysDb::try_from_config(worker_config).await; + let sysdb = match sysdb { + Ok(sysdb) => sysdb, + Err(err) => { + return Err(err); + } + }; + let path = std::path::Path::new(&worker_config.segment_manager.storage_path); + Ok(SegmentManager::new(Box::new(sysdb), path)) + } +} diff --git a/rust/worker/src/server.rs b/rust/worker/src/server.rs new file mode 100644 index 0000000000000000000000000000000000000000..1ecc6ba2e705716f32e7e9e073afaaa06c0eff71 --- /dev/null +++ b/rust/worker/src/server.rs @@ -0,0 +1,188 @@ +use std::f32::consts::E; + +use crate::chroma_proto; +use crate::chroma_proto::{ + GetVectorsRequest, GetVectorsResponse, QueryVectorsRequest, QueryVectorsResponse, +}; +use crate::config::{Configurable, WorkerConfig}; +use crate::errors::ChromaError; +use crate::segment::SegmentManager; +use crate::types::ScalarEncoding; +use async_trait::async_trait; +use kube::core::request; +use tonic::{transport::Server, Request, Response, Status}; +use uuid::Uuid; + +pub struct WorkerServer { + segment_manager: Option, + port: u16, +} + +#[async_trait] +impl Configurable for WorkerServer { + async fn try_from_config(config: &WorkerConfig) -> Result> { + Ok(WorkerServer { + segment_manager: None, + port: config.my_port, + }) + } +} + +impl WorkerServer { + pub(crate) async fn run(worker: WorkerServer) -> Result<(), Box> { + let addr = format!("[::]:{}", worker.port).parse().unwrap(); + println!("Worker listening on {}", addr); + let server = Server::builder() + .add_service(chroma_proto::vector_reader_server::VectorReaderServer::new( + worker, + )) + .serve(addr) + .await?; + println!("Worker shutting down"); + + Ok(()) + } + + pub(crate) fn set_segment_manager(&mut self, segment_manager: SegmentManager) { + self.segment_manager = Some(segment_manager); + } +} + +#[tonic::async_trait] +impl chroma_proto::vector_reader_server::VectorReader for WorkerServer { + async fn get_vectors( + &self, + request: Request, + ) -> Result, Status> { + let request = request.into_inner(); + let segment_uuid = match Uuid::parse_str(&request.segment_id) { + Ok(uuid) => uuid, + Err(_) => { + return Err(Status::invalid_argument("Invalid UUID")); + } + }; + + let segment_manager = match self.segment_manager { + Some(ref segment_manager) => segment_manager, + None => { + return Err(Status::internal("No segment manager found")); + } + }; + + let records = match segment_manager + .get_records(&segment_uuid, request.ids) + .await + { + Ok(records) => records, + Err(e) => { + return Err(Status::internal(format!("Error getting records: {}", e))); + } + }; + + let mut proto_records = Vec::new(); + for record in records { + let sed_id_bytes = record.seq_id.to_bytes_le(); + let dim = record.vector.len(); + let proto_vector = (record.vector, ScalarEncoding::FLOAT32, dim).try_into(); + match proto_vector { + Ok(proto_vector) => { + let proto_record = chroma_proto::VectorEmbeddingRecord { + id: record.id, + seq_id: sed_id_bytes.1, + vector: Some(proto_vector), + }; + proto_records.push(proto_record); + } + Err(e) => { + return Err(Status::internal(format!("Error converting vector: {}", e))); + } + } + } + + let resp = chroma_proto::GetVectorsResponse { + records: proto_records, + }; + + Ok(Response::new(resp)) + } + + async fn query_vectors( + &self, + request: Request, + ) -> Result, Status> { + let request = request.into_inner(); + let segment_uuid = match Uuid::parse_str(&request.segment_id) { + Ok(uuid) => uuid, + Err(_) => { + return Err(Status::invalid_argument("Invalid Segment UUID")); + } + }; + + let segment_manager = match self.segment_manager { + Some(ref segment_manager) => segment_manager, + None => { + return Err(Status::internal("No segment manager found")); + } + }; + + let mut proto_results_for_all = Vec::new(); + for proto_query_vector in request.vectors { + let (query_vector, encoding) = match proto_query_vector.try_into() { + Ok((vector, encoding)) => (vector, encoding), + Err(e) => { + return Err(Status::internal(format!("Error converting vector: {}", e))); + } + }; + + let results = match segment_manager + .query_vector( + &segment_uuid, + &query_vector, + request.k as usize, + request.include_embeddings, + ) + .await + { + Ok(results) => results, + Err(e) => { + return Err(Status::internal(format!("Error querying segment: {}", e))); + } + }; + + let mut proto_results = Vec::new(); + for query_result in results { + let proto_result = chroma_proto::VectorQueryResult { + id: query_result.id, + seq_id: query_result.seq_id.to_bytes_le().1, + distance: query_result.distance, + vector: match query_result.vector { + Some(vector) => { + match (vector, ScalarEncoding::FLOAT32, query_vector.len()).try_into() { + Ok(proto_vector) => Some(proto_vector), + Err(e) => { + return Err(Status::internal(format!( + "Error converting vector: {}", + e + ))); + } + } + } + None => None, + }, + }; + proto_results.push(proto_result); + } + + let vector_query_results = chroma_proto::VectorQueryResults { + results: proto_results, + }; + proto_results_for_all.push(vector_query_results); + } + + let resp = chroma_proto::QueryVectorsResponse { + results: proto_results_for_all, + }; + + return Ok(Response::new(resp)); + } +} diff --git a/rust/worker/src/storage/config.rs b/rust/worker/src/storage/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..85811d7150906847624dff751fc3528f9b6b62f3 --- /dev/null +++ b/rust/worker/src/storage/config.rs @@ -0,0 +1,20 @@ +use serde::Deserialize; + +#[derive(Deserialize)] +/// The configuration for the chosen storage. +/// # Options +/// - S3: The configuration for the s3 storage. +/// # Notes +/// See config.rs in the root of the worker crate for an example of how to use +/// config files to configure the worker. +pub(crate) enum StorageConfig { + S3(S3StorageConfig), +} + +#[derive(Deserialize)] +/// The configuration for the s3 storage type +/// # Fields +/// - bucket: The name of the bucket to use. +pub(crate) struct S3StorageConfig { + pub(crate) bucket: String, +} diff --git a/rust/worker/src/storage/mod.rs b/rust/worker/src/storage/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..eb89db1025e703b3101bca08fe63fd3429062c4d --- /dev/null +++ b/rust/worker/src/storage/mod.rs @@ -0,0 +1,9 @@ +use async_trait::async_trait; +pub(crate) mod config; +pub(crate) mod s3; + +#[async_trait] +trait Storage { + async fn get(&self, key: &str, path: &str) -> Result<(), String>; + async fn put(&self, key: &str, path: &str) -> Result<(), String>; +} diff --git a/rust/worker/src/storage/s3.rs b/rust/worker/src/storage/s3.rs new file mode 100644 index 0000000000000000000000000000000000000000..f78767e4896e324856f2780cad3b34211b753b50 --- /dev/null +++ b/rust/worker/src/storage/s3.rs @@ -0,0 +1,216 @@ +// Presents an interface to a storage backend such as s3 or local disk. +// The interface is a simple key-value store, which maps to s3 well. +// For now the interface fetches a file and stores it at a specific +// location on disk. This is not ideal for s3, but it is a start. + +// Ideally we would support streaming the file from s3 to the index +// but the current implementation of hnswlib makes this complicated. +// Once we move to our own implementation of hnswlib we can support +// streaming from s3. + +use super::{config::StorageConfig, Storage}; +use crate::config::{Configurable, WorkerConfig}; +use crate::errors::ChromaError; +use async_trait::async_trait; +use aws_sdk_s3; +use aws_sdk_s3::error::SdkError; +use aws_sdk_s3::operation::create_bucket::CreateBucketError; +use aws_smithy_types::byte_stream::ByteStream; +use std::clone::Clone; +use std::io::Write; + +#[derive(Clone)] +struct S3Storage { + bucket: String, + client: aws_sdk_s3::Client, +} + +impl S3Storage { + fn new(bucket: &str, client: aws_sdk_s3::Client) -> S3Storage { + return S3Storage { + bucket: bucket.to_string(), + client: client, + }; + } + + async fn create_bucket(&self) -> Result<(), String> { + // Creates a public bucket with default settings in the region. + // This should only be used for testing and in production + // the bucket should be provisioned ahead of time. + let res = self + .client + .create_bucket() + .bucket(self.bucket.clone()) + .send() + .await; + match res { + Ok(_) => { + println!("created bucket {}", self.bucket); + return Ok(()); + } + Err(e) => match e { + SdkError::ServiceError(err) => match err.into_err() { + CreateBucketError::BucketAlreadyExists(msg) => { + println!("bucket already exists: {}", msg); + return Ok(()); + } + CreateBucketError::BucketAlreadyOwnedByYou(msg) => { + println!("bucket already owned by you: {}", msg); + return Ok(()); + } + e => { + println!("error: {}", e.to_string()); + return Err::<(), String>(e.to_string()); + } + }, + _ => { + println!("error: {}", e); + return Err::<(), String>(e.to_string()); + } + }, + } + } +} + +#[async_trait] +impl Configurable for S3Storage { + async fn try_from_config(config: &WorkerConfig) -> Result> { + match &config.storage { + StorageConfig::S3(s3_config) => { + let config = aws_config::load_from_env().await; + let client = aws_sdk_s3::Client::new(&config); + + let storage = S3Storage::new(&s3_config.bucket, client); + return Ok(storage); + } + } + } +} + +#[async_trait] +impl Storage for S3Storage { + async fn get(&self, key: &str, path: &str) -> Result<(), String> { + let mut file = std::fs::File::create(path); + let res = self + .client + .get_object() + .bucket(self.bucket.clone()) + .key(key) + .send() + .await; + match res { + Ok(mut res) => { + match file { + Ok(mut file) => { + while let bytes = res.body.next().await { + match bytes { + Some(bytes) => match bytes { + Ok(bytes) => { + file.write_all(&bytes).unwrap(); + } + Err(e) => { + println!("error: {}", e); + return Err::<(), String>(e.to_string()); + } + }, + None => { + // Stream is done + return Ok(()); + } + } + } + } + Err(e) => { + println!("error: {}", e); + return Err::<(), String>(e.to_string()); + } + } + return Ok(()); + } + Err(e) => { + println!("error: {}", e); + return Err::<(), String>(e.to_string()); + } + } + } + + async fn put(&self, key: &str, path: &str) -> Result<(), String> { + // Puts from a file on disk to s3. + let bytestream = ByteStream::from_path(path).await; + match bytestream { + Ok(bytestream) => { + let res = self + .client + .put_object() + .bucket(self.bucket.clone()) + .key(key) + .body(bytestream) + .send() + .await; + match res { + Ok(_) => { + println!("put object {} to bucket {}", key, self.bucket); + return Ok(()); + } + Err(e) => { + println!("error: {}", e); + return Err::<(), String>(e.to_string()); + } + } + } + Err(e) => { + println!("error: {}", e); + return Err::<(), String>(e.to_string()); + } + } + } +} + +#[cfg(test)] +mod tests { + use super::*; + use tempfile::tempdir; + + #[tokio::test] + #[cfg(CHROMA_KUBERNETES_INTEGRATION)] + async fn test_get() { + // Set up credentials assuming minio is running locally + let cred = aws_sdk_s3::config::Credentials::new( + "minio", + "minio123", + None, + None, + "loaded-from-env", + ); + + // Set up s3 client + let config = aws_sdk_s3::config::Builder::new() + .endpoint_url("http://127.0.0.1:9000".to_string()) + .credentials_provider(cred) + .behavior_version_latest() + .region(aws_sdk_s3::config::Region::new("us-east-1")) + .force_path_style(true) + .build(); + let client = aws_sdk_s3::Client::from_conf(config); + + let storage = S3Storage { + bucket: "test".to_string(), + client: client, + }; + storage.create_bucket().await.unwrap(); + + // Write some data to a test file, put it in s3, get it back and verify its contents + let tmp_dir = tempdir().unwrap(); + let persist_path = tmp_dir.path().to_str().unwrap().to_string(); + + let test_data = "test data"; + let test_file_in = format!("{}/test_file_in", persist_path); + let test_file_out = format!("{}/test_file_out", persist_path); + std::fs::write(&test_file_in, test_data).unwrap(); + storage.put("test", &test_file_in).await.unwrap(); + storage.get("test", &test_file_out).await.unwrap(); + + let contents = std::fs::read_to_string(test_file_out).unwrap(); + assert_eq!(contents, test_data); + } +} diff --git a/rust/worker/src/sysdb/config.rs b/rust/worker/src/sysdb/config.rs new file mode 100644 index 0000000000000000000000000000000000000000..63cbf3ad689a19116f2318b222aa253d5474b3fe --- /dev/null +++ b/rust/worker/src/sysdb/config.rs @@ -0,0 +1,12 @@ +use serde::Deserialize; + +#[derive(Deserialize)] +pub(crate) struct GrpcSysDbConfig { + pub(crate) host: String, + pub(crate) port: u16, +} + +#[derive(Deserialize)] +pub(crate) enum SysDbConfig { + Grpc(GrpcSysDbConfig), +} diff --git a/rust/worker/src/sysdb/mod.rs b/rust/worker/src/sysdb/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..1db5510f89389719962a1124f0167106e8c6f9c4 --- /dev/null +++ b/rust/worker/src/sysdb/mod.rs @@ -0,0 +1,2 @@ +pub(crate) mod config; +pub(crate) mod sysdb; diff --git a/rust/worker/src/sysdb/sysdb.rs b/rust/worker/src/sysdb/sysdb.rs new file mode 100644 index 0000000000000000000000000000000000000000..ba8be18fdf55ce99ebfac366cef487e48abc9b64 --- /dev/null +++ b/rust/worker/src/sysdb/sysdb.rs @@ -0,0 +1,259 @@ +use async_trait::async_trait; +use uuid::Uuid; + +use crate::chroma_proto; +use crate::config::{Configurable, WorkerConfig}; +use crate::types::{CollectionConversionError, SegmentConversionError}; +use crate::{ + chroma_proto::sys_db_client, + errors::{ChromaError, ErrorCodes}, + types::{Collection, Segment, SegmentScope}, +}; +use thiserror::Error; + +use super::config::SysDbConfig; + +const DEFAULT_DATBASE: &str = "default_database"; +const DEFAULT_TENANT: &str = "default_tenant"; + +#[async_trait] +pub(crate) trait SysDb: Send + Sync + SysDbClone { + async fn get_collections( + &mut self, + collection_id: Option, + topic: Option, + name: Option, + tenant: Option, + database: Option, + ) -> Result, GetCollectionsError>; + + async fn get_segments( + &mut self, + id: Option, + r#type: Option, + scope: Option, + topic: Option, + collection: Option, + ) -> Result, GetSegmentsError>; +} + +// We'd like to be able to clone the trait object, so we need to use the +// "clone box" pattern. See https://stackoverflow.com/questions/30353462/how-to-clone-a-struct-storing-a-boxed-trait-object#comment48814207_30353928 +// https://chat.openai.com/share/b3eae92f-0b80-446f-b79d-6287762a2420 +pub(crate) trait SysDbClone { + fn clone_box(&self) -> Box; +} + +impl SysDbClone for T +where + T: 'static + SysDb + Clone, +{ + fn clone_box(&self) -> Box { + Box::new(self.clone()) + } +} + +impl Clone for Box { + fn clone(&self) -> Box { + self.clone_box() + } +} + +#[derive(Clone)] +// Since this uses tonic transport channel, cloning is cheap. Each client only supports +// one inflight request at a time, so we need to clone the client for each requester. +pub(crate) struct GrpcSysDb { + client: sys_db_client::SysDbClient, +} + +#[derive(Error, Debug)] +pub(crate) enum GrpcSysDbError { + #[error("Failed to connect to sysdb")] + FailedToConnect(#[from] tonic::transport::Error), +} + +impl ChromaError for GrpcSysDbError { + fn code(&self) -> ErrorCodes { + match self { + GrpcSysDbError::FailedToConnect(_) => ErrorCodes::Internal, + } + } +} + +#[async_trait] +impl Configurable for GrpcSysDb { + async fn try_from_config(worker_config: &WorkerConfig) -> Result> { + match &worker_config.sysdb { + SysDbConfig::Grpc(my_config) => { + let host = &my_config.host; + let port = &my_config.port; + println!("Connecting to sysdb at {}:{}", host, port); + let connection_string = format!("http://{}:{}", host, port); + let client = sys_db_client::SysDbClient::connect(connection_string).await; + match client { + Ok(client) => { + return Ok(GrpcSysDb { client: client }); + } + Err(e) => { + return Err(Box::new(GrpcSysDbError::FailedToConnect(e))); + } + } + } + } + } +} + +#[async_trait] +impl SysDb for GrpcSysDb { + async fn get_collections( + &mut self, + collection_id: Option, + topic: Option, + name: Option, + tenant: Option, + database: Option, + ) -> Result, GetCollectionsError> { + // TODO: move off of status into our own error type + let collection_id_str; + match collection_id { + Some(id) => { + collection_id_str = Some(id.to_string()); + } + None => { + collection_id_str = None; + } + } + + let res = self + .client + .get_collections(chroma_proto::GetCollectionsRequest { + id: collection_id_str, + topic: topic, + name: name, + tenant: if tenant.is_some() { + tenant.unwrap() + } else { + DEFAULT_TENANT.to_string() + }, + database: if database.is_some() { + database.unwrap() + } else { + DEFAULT_DATBASE.to_string() + }, + }) + .await; + + match res { + Ok(res) => { + let collections = res.into_inner().collections; + + let collections = collections + .into_iter() + .map(|proto_collection| proto_collection.try_into()) + .collect::, CollectionConversionError>>(); + + match collections { + Ok(collections) => { + return Ok(collections); + } + Err(e) => { + return Err(GetCollectionsError::ConversionError(e)); + } + } + } + Err(e) => { + return Err(GetCollectionsError::FailedToGetCollections(e)); + } + } + } + + async fn get_segments( + &mut self, + id: Option, + r#type: Option, + scope: Option, + topic: Option, + collection: Option, + ) -> Result, GetSegmentsError> { + let res = self + .client + .get_segments(chroma_proto::GetSegmentsRequest { + // TODO: modularize + id: if id.is_some() { + Some(id.unwrap().to_string()) + } else { + None + }, + r#type: r#type, + scope: if scope.is_some() { + Some(scope.unwrap() as i32) + } else { + None + }, + topic: topic, + collection: if collection.is_some() { + Some(collection.unwrap().to_string()) + } else { + None + }, + }) + .await; + match res { + Ok(res) => { + let segments = res.into_inner().segments; + let converted_segments = segments + .into_iter() + .map(|proto_segment| proto_segment.try_into()) + .collect::, SegmentConversionError>>(); + + match converted_segments { + Ok(segments) => { + return Ok(segments); + } + Err(e) => { + return Err(GetSegmentsError::ConversionError(e)); + } + } + } + Err(e) => { + return Err(GetSegmentsError::FailedToGetSegments(e)); + } + } + } +} + +#[derive(Error, Debug)] +// TODO: This should use our sysdb errors from the proto definition +// We will have to do an error uniformization pass at some point +pub(crate) enum GetCollectionsError { + #[error("Failed to fetch")] + FailedToGetCollections(#[from] tonic::Status), + #[error("Failed to convert proto collection")] + ConversionError(#[from] CollectionConversionError), +} + +impl ChromaError for GetCollectionsError { + fn code(&self) -> ErrorCodes { + match self { + GetCollectionsError::FailedToGetCollections(_) => ErrorCodes::Internal, + GetCollectionsError::ConversionError(_) => ErrorCodes::Internal, + } + } +} + +#[derive(Error, Debug)] +pub(crate) enum GetSegmentsError { + #[error("Failed to fetch")] + FailedToGetSegments(#[from] tonic::Status), + #[error("Failed to convert proto segment")] + ConversionError(#[from] SegmentConversionError), +} + +impl ChromaError for GetSegmentsError { + fn code(&self) -> ErrorCodes { + match self { + GetSegmentsError::FailedToGetSegments(_) => ErrorCodes::Internal, + GetSegmentsError::ConversionError(_) => ErrorCodes::Internal, + } + } +} diff --git a/rust/worker/src/system/executor.rs b/rust/worker/src/system/executor.rs new file mode 100644 index 0000000000000000000000000000000000000000..c50ac4a56fa339a2654c90b4f3bce9eb3fcdec33 --- /dev/null +++ b/rust/worker/src/system/executor.rs @@ -0,0 +1,79 @@ +use std::sync::Arc; + +use tokio::select; + +use crate::system::ComponentContext; + +use super::{ + sender::{Sender, Wrapper}, + system::System, + Component, +}; + +struct Inner +where + C: Component, +{ + pub(super) sender: Sender, + pub(super) cancellation_token: tokio_util::sync::CancellationToken, + pub(super) system: System, +} + +#[derive(Clone)] +/// # Description +/// The executor holds the context for a components execution and is responsible for +/// running the components handler methods +pub(super) struct ComponentExecutor +where + C: Component, +{ + inner: Arc>, + handler: C, +} + +impl ComponentExecutor +where + C: Component + Send + 'static, +{ + pub(super) fn new( + sender: Sender, + cancellation_token: tokio_util::sync::CancellationToken, + handler: C, + system: System, + ) -> Self { + ComponentExecutor { + inner: Arc::new(Inner { + sender, + cancellation_token, + system, + }), + handler, + } + } + + pub(super) async fn run(&mut self, mut channel: tokio::sync::mpsc::Receiver>) { + loop { + select! { + _ = self.inner.cancellation_token.cancelled() => { + break; + } + message = channel.recv() => { + match message { + Some(mut message) => { + message.handle(&mut self.handler, + &ComponentContext{ + system: self.inner.system.clone(), + sender: self.inner.sender.clone(), + cancellation_token: self.inner.cancellation_token.clone(), + } + ).await; + } + None => { + // TODO: Log error + } + } + } + } + } + } +} diff --git a/rust/worker/src/system/mod.rs b/rust/worker/src/system/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..32ad862f768edd55e9dc82d375b6539a853faca3 --- /dev/null +++ b/rust/worker/src/system/mod.rs @@ -0,0 +1,9 @@ +mod executor; +mod sender; +mod system; +mod types; + +// Re-export types +pub(crate) use sender::*; +pub(crate) use system::*; +pub(crate) use types::*; diff --git a/rust/worker/src/system/sender.rs b/rust/worker/src/system/sender.rs new file mode 100644 index 0000000000000000000000000000000000000000..df2e1bc5587d5c361f33b256c834019e24d28f80 --- /dev/null +++ b/rust/worker/src/system/sender.rs @@ -0,0 +1,169 @@ +use std::fmt::Debug; + +use super::{Component, ComponentContext, Handler}; +use async_trait::async_trait; +use thiserror::Error; + +// Message Wrapper +#[derive(Debug)] +pub(crate) struct Wrapper +where + C: Component, +{ + wrapper: Box>, +} + +impl Wrapper { + pub(super) async fn handle(&mut self, component: &mut C, ctx: &ComponentContext) -> () { + self.wrapper.handle(component, ctx).await; + } +} + +#[async_trait] +pub(super) trait WrapperTrait: Debug + Send +where + C: Component, +{ + async fn handle(&mut self, component: &mut C, ctx: &ComponentContext) -> (); +} + +#[async_trait] +impl WrapperTrait for Option +where + C: Component + Handler, + M: Debug + Send + 'static, +{ + async fn handle(&mut self, component: &mut C, ctx: &ComponentContext) -> () { + if let Some(message) = self.take() { + component.handle(message, ctx).await; + } + } +} + +pub(crate) fn wrap(message: M) -> Wrapper +where + C: Component + Handler, + M: Debug + Send + 'static, +{ + Wrapper { + wrapper: Box::new(Some(message)), + } +} + +// Sender + +pub(crate) struct Sender +where + C: Component + Send + 'static, +{ + pub(super) sender: tokio::sync::mpsc::Sender>, +} + +impl Sender +where + C: Component + Send + 'static, +{ + pub(super) fn new(sender: tokio::sync::mpsc::Sender>) -> Self { + Sender { sender } + } + + pub(crate) async fn send(&self, message: M) -> Result<(), ChannelError> + where + C: Component + Handler, + M: Debug + Send + 'static, + { + let res = self.sender.send(wrap(message)).await; + match res { + Ok(_) => Ok(()), + Err(_) => Err(ChannelError::SendError), + } + } +} + +impl Clone for Sender +where + C: Component, +{ + fn clone(&self) -> Self { + Sender { + sender: self.sender.clone(), + } + } +} + +// Reciever Traits + +#[async_trait] +pub(crate) trait Receiver: Send + Sync + ReceiverClone { + async fn send(&self, message: M) -> Result<(), ChannelError>; +} + +trait ReceiverClone { + fn clone_box(&self) -> Box>; +} + +impl Clone for Box> { + fn clone(&self) -> Box> { + self.clone_box() + } +} + +impl ReceiverClone for T +where + T: 'static + Receiver + Clone, +{ + fn clone_box(&self) -> Box> { + Box::new(self.clone()) + } +} + +// Reciever Impls + +pub(super) struct ReceiverImpl +where + C: Component, +{ + pub(super) sender: tokio::sync::mpsc::Sender>, +} + +impl Clone for ReceiverImpl +where + C: Component, +{ + fn clone(&self) -> Self { + ReceiverImpl { + sender: self.sender.clone(), + } + } +} + +impl ReceiverImpl +where + C: Component, +{ + pub(super) fn new(sender: tokio::sync::mpsc::Sender>) -> Self { + ReceiverImpl { sender } + } +} + +#[async_trait] +impl Receiver for ReceiverImpl +where + C: Component + Handler, + M: Send + Debug + 'static, +{ + async fn send(&self, message: M) -> Result<(), ChannelError> { + let res = self.sender.send(wrap(message)).await; + match res { + Ok(_) => Ok(()), + Err(_) => Err(ChannelError::SendError), + } + } +} + +// Errors +#[derive(Error, Debug)] +pub enum ChannelError { + #[error("Failed to send message")] + SendError, +} diff --git a/rust/worker/src/system/system.rs b/rust/worker/src/system/system.rs new file mode 100644 index 0000000000000000000000000000000000000000..238da52a0eebe934c91bb46c98e884e497e4f1b5 --- /dev/null +++ b/rust/worker/src/system/system.rs @@ -0,0 +1,115 @@ +use std::fmt::Debug; +use std::sync::Arc; + +use futures::Stream; +use futures::StreamExt; +use tokio::runtime::Builder; +use tokio::{pin, select}; + +use super::ComponentRuntime; +// use super::executor::StreamComponentExecutor; +use super::sender::{self, Sender, Wrapper}; +use super::{executor, ComponentContext}; +use super::{executor::ComponentExecutor, Component, ComponentHandle, Handler, StreamHandler}; +use std::sync::Mutex; + +#[derive(Clone)] +pub(crate) struct System { + inner: Arc>, +} + +struct Inner {} + +impl System { + pub(crate) fn new() -> System { + System { + inner: Arc::new(Mutex::new(Inner {})), + } + } + + pub(crate) fn start_component(&mut self, mut component: C) -> ComponentHandle + where + C: Component + Send + 'static, + { + let (tx, rx) = tokio::sync::mpsc::channel(component.queue_size()); + let sender = Sender::new(tx); + let cancel_token = tokio_util::sync::CancellationToken::new(); + let _ = component.on_start(&ComponentContext { + system: self.clone(), + sender: sender.clone(), + cancellation_token: cancel_token.clone(), + }); + let mut executor = ComponentExecutor::new( + sender.clone(), + cancel_token.clone(), + component, + self.clone(), + ); + + match C::runtime() { + ComponentRuntime::Global => { + let join_handle = tokio::spawn(async move { executor.run(rx).await }); + return ComponentHandle::new(cancel_token, Some(join_handle), sender); + } + ComponentRuntime::Dedicated => { + println!("Spawning on dedicated thread"); + // Spawn on a dedicated thread + let mut rt = Builder::new_current_thread().enable_all().build().unwrap(); + let join_handle = std::thread::spawn(move || { + rt.block_on(async move { executor.run(rx).await }); + }); + // TODO: Implement Join for dedicated threads + return ComponentHandle::new(cancel_token, None, sender); + } + } + } + + pub(super) fn register_stream(&self, stream: S, ctx: &ComponentContext) + where + C: StreamHandler + Handler, + M: Send + Debug + 'static, + S: Stream + Send + Stream + 'static, + { + let ctx = ComponentContext { + system: self.clone(), + sender: ctx.sender.clone(), + cancellation_token: ctx.cancellation_token.clone(), + }; + tokio::spawn(async move { stream_loop(stream, &ctx).await }); + } +} + +async fn stream_loop(stream: S, ctx: &ComponentContext) +where + C: StreamHandler + Handler, + M: Send + Debug + 'static, + S: Stream + Send + Stream + 'static, +{ + pin!(stream); + loop { + select! { + _ = ctx.cancellation_token.cancelled() => { + break; + } + message = stream.next() => { + match message { + Some(message) => { + let res = ctx.sender.send(message).await; + match res { + Ok(_) => {} + Err(e) => { + println!("Failed to send message: {:?}", e); + // TODO: switch to logging + // Terminate the stream + break; + } + } + }, + None => { + break; + } + } + } + } + } +} diff --git a/rust/worker/src/system/types.rs b/rust/worker/src/system/types.rs new file mode 100644 index 0000000000000000000000000000000000000000..9c2cd4635615bda27f8ea52bed5292a55b871b70 --- /dev/null +++ b/rust/worker/src/system/types.rs @@ -0,0 +1,204 @@ +use std::{fmt::Debug, sync::Arc}; + +use async_trait::async_trait; +use futures::Stream; +use tokio::select; + +use super::{ + executor::ComponentExecutor, sender::Sender, system::System, Receiver, ReceiverImpl, Wrapper, +}; + +#[derive(Debug, PartialEq)] +/// The state of a component +/// A component can be running or stopped +/// A component is stopped when it is cancelled +/// A component can be run with a system +pub(crate) enum ComponentState { + Running, + Stopped, +} + +#[derive(Debug, PartialEq)] +pub(crate) enum ComponentRuntime { + Global, + Dedicated, +} + +/// A component is a processor of work that can be run in a system. +/// It has a queue of messages that it can process. +/// Others can send messages to the component. +/// A component can be stopped using its handle. +/// It is a data object, and stores some parameterization +/// for how the system should run it. +/// # Methods +/// - queue_size: The size of the queue to use for the component before it starts dropping messages +/// - on_start: Called when the component is started +pub(crate) trait Component: Send + Sized + Debug + 'static { + fn queue_size(&self) -> usize; + fn runtime() -> ComponentRuntime { + ComponentRuntime::Global + } + fn on_start(&mut self, ctx: &ComponentContext) -> () {} +} + +/// A handler is a component that can process messages of a given type. +/// # Methods +/// - handle: Handle a message +#[async_trait] +pub(crate) trait Handler +where + Self: Component + Sized + 'static, +{ + async fn handle(&mut self, message: M, ctx: &ComponentContext) -> (); +} + +/// A stream handler is a component that can process messages of a given type from a stream. +/// # Methods +/// - handle: Handle a message from a stream +/// - register_stream: Register a stream to be processed, this is provided and you do not need to implement it +pub(crate) trait StreamHandler +where + Self: Component + 'static + Handler, + M: Send + Debug + 'static, +{ + fn register_stream(&self, stream: S, ctx: &ComponentContext) -> () + where + S: Stream + Send + Stream + 'static, + { + ctx.system.register_stream(stream, ctx); + } +} + +/// A component handle is a handle to a component that can be used to stop it. +/// and introspect its state. +/// # Fields +/// - cancellation_token: A cancellation token that can be used to stop the component +/// - state: The state of the component +/// - join_handle: The join handle for the component, used to join on the component +pub(crate) struct ComponentHandle { + cancellation_token: tokio_util::sync::CancellationToken, + state: ComponentState, + join_handle: Option>, + sender: Sender, +} + +impl ComponentHandle { + pub(super) fn new( + cancellation_token: tokio_util::sync::CancellationToken, + // Components with a dedicated runtime do not have a join handle + // and instead use a one shot channel to signal completion + // TODO: implement this + join_handle: Option>, + sender: Sender, + ) -> Self { + ComponentHandle { + cancellation_token: cancellation_token, + state: ComponentState::Running, + join_handle: join_handle, + sender: sender, + } + } + + pub(crate) fn stop(&mut self) { + self.cancellation_token.cancel(); + self.state = ComponentState::Stopped; + } + + pub(crate) async fn join(&mut self) { + match self.join_handle.take() { + Some(handle) => { + handle.await; + } + None => return, + }; + } + + pub(crate) fn state(&self) -> &ComponentState { + return &self.state; + } + + pub(crate) fn receiver(&self) -> Box + Send> + where + C: Handler, + M: Send + Debug + 'static, + { + let sender = self.sender.sender.clone(); + Box::new(ReceiverImpl::new(sender)) + } +} + +/// The component context is passed to all Component Handler methods +pub(crate) struct ComponentContext +where + C: Component + 'static, +{ + pub(crate) system: System, + pub(crate) sender: Sender, + pub(crate) cancellation_token: tokio_util::sync::CancellationToken, +} + +#[cfg(test)] +mod tests { + use super::*; + use async_trait::async_trait; + use futures::stream; + + use std::sync::atomic::{AtomicUsize, Ordering}; + + #[derive(Debug)] + struct TestComponent { + queue_size: usize, + counter: Arc, + } + + impl TestComponent { + fn new(queue_size: usize, counter: Arc) -> Self { + TestComponent { + queue_size: queue_size, + counter: counter, + } + } + } + + #[async_trait] + impl Handler for TestComponent { + async fn handle(&mut self, message: usize, _ctx: &ComponentContext) -> () { + self.counter.fetch_add(message, Ordering::SeqCst); + } + } + + impl StreamHandler for TestComponent {} + + impl Component for TestComponent { + fn queue_size(&self) -> usize { + return self.queue_size; + } + + fn on_start(&mut self, ctx: &ComponentContext) -> () { + let test_stream = stream::iter(vec![1, 2, 3]); + self.register_stream(test_stream, ctx); + } + } + + #[tokio::test] + async fn it_can_work() { + let mut system = System::new(); + let counter = Arc::new(AtomicUsize::new(0)); + let component = TestComponent::new(10, counter.clone()); + let mut handle = system.start_component(component); + handle.sender.send(1).await.unwrap(); + handle.sender.send(2).await.unwrap(); + handle.sender.send(3).await.unwrap(); + // yield to allow the component to process the messages + tokio::task::yield_now().await; + handle.stop(); + // Yield to allow the component to stop + tokio::task::yield_now().await; + assert_eq!(*handle.state(), ComponentState::Stopped); + // With the streaming data and the messages we should have 12 + assert_eq!(counter.load(Ordering::SeqCst), 12); + let res = handle.sender.send(4).await; + // Expect an error because the component is stopped + assert!(res.is_err()); + } +} diff --git a/rust/worker/src/types/collection.rs b/rust/worker/src/types/collection.rs new file mode 100644 index 0000000000000000000000000000000000000000..2dd495a5afcc29160e775103fd9a75431079ef83 --- /dev/null +++ b/rust/worker/src/types/collection.rs @@ -0,0 +1,88 @@ +use super::{Metadata, MetadataValueConversionError}; +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use thiserror::Error; +use uuid::Uuid; + +#[derive(Debug, PartialEq)] +pub(crate) struct Collection { + pub(crate) id: Uuid, + pub(crate) name: String, + pub(crate) topic: String, + pub(crate) metadata: Option, + pub(crate) dimension: Option, + pub(crate) tenant: String, + pub(crate) database: String, +} + +#[derive(Error, Debug)] +pub(crate) enum CollectionConversionError { + #[error("Invalid UUID")] + InvalidUuid, + #[error(transparent)] + MetadataValueConversionError(#[from] MetadataValueConversionError), +} + +impl ChromaError for CollectionConversionError { + fn code(&self) -> crate::errors::ErrorCodes { + match self { + CollectionConversionError::InvalidUuid => ErrorCodes::InvalidArgument, + CollectionConversionError::MetadataValueConversionError(e) => e.code(), + } + } +} + +impl TryFrom for Collection { + type Error = CollectionConversionError; + + fn try_from(proto_collection: chroma_proto::Collection) -> Result { + let collection_uuid = match Uuid::try_parse(&proto_collection.id) { + Ok(uuid) => uuid, + Err(_) => return Err(CollectionConversionError::InvalidUuid), + }; + let collection_metadata: Option = match proto_collection.metadata { + Some(proto_metadata) => match proto_metadata.try_into() { + Ok(metadata) => Some(metadata), + Err(e) => return Err(CollectionConversionError::MetadataValueConversionError(e)), + }, + None => None, + }; + Ok(Collection { + id: collection_uuid, + name: proto_collection.name, + topic: proto_collection.topic, + metadata: collection_metadata, + dimension: proto_collection.dimension, + tenant: proto_collection.tenant, + database: proto_collection.database, + }) + } +} + +#[cfg(test)] +mod test { + use super::*; + + #[test] + fn test_collection_try_from() { + let proto_collection = chroma_proto::Collection { + id: "00000000-0000-0000-0000-000000000000".to_string(), + name: "foo".to_string(), + topic: "bar".to_string(), + metadata: None, + dimension: None, + tenant: "baz".to_string(), + database: "qux".to_string(), + }; + let converted_collection: Collection = proto_collection.try_into().unwrap(); + assert_eq!(converted_collection.id, Uuid::nil()); + assert_eq!(converted_collection.name, "foo".to_string()); + assert_eq!(converted_collection.topic, "bar".to_string()); + assert_eq!(converted_collection.metadata, None); + assert_eq!(converted_collection.dimension, None); + assert_eq!(converted_collection.tenant, "baz".to_string()); + assert_eq!(converted_collection.database, "qux".to_string()); + } +} diff --git a/rust/worker/src/types/embedding_record.rs b/rust/worker/src/types/embedding_record.rs new file mode 100644 index 0000000000000000000000000000000000000000..14957a8534951a1565a33e61a711ae72602f6bcf --- /dev/null +++ b/rust/worker/src/types/embedding_record.rs @@ -0,0 +1,281 @@ +use super::{ + ConversionError, Operation, OperationConversionError, ScalarEncoding, + ScalarEncodingConversionError, SeqId, UpdateMetadata, UpdateMetadataValueConversionError, +}; +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use thiserror::Error; +use uuid::Uuid; + +#[derive(Debug)] +pub(crate) struct EmbeddingRecord { + pub(crate) id: String, + pub(crate) seq_id: SeqId, + pub(crate) embedding: Option>, // NOTE: we only support float32 embeddings for now + pub(crate) encoding: Option, + pub(crate) metadata: Option, + pub(crate) operation: Operation, + pub(crate) collection_id: Uuid, +} + +pub(crate) type SubmitEmbeddingRecordWithSeqId = (chroma_proto::SubmitEmbeddingRecord, SeqId); + +#[derive(Error, Debug)] +pub(crate) enum EmbeddingRecordConversionError { + #[error("Invalid UUID")] + InvalidUuid, + #[error(transparent)] + DecodeError(#[from] ConversionError), + #[error(transparent)] + OperationConversionError(#[from] OperationConversionError), + #[error(transparent)] + ScalarEncodingConversionError(#[from] ScalarEncodingConversionError), + #[error(transparent)] + UpdateMetadataValueConversionError(#[from] UpdateMetadataValueConversionError), + #[error(transparent)] + VectorConversionError(#[from] VectorConversionError), +} + +impl_base_convert_error!(EmbeddingRecordConversionError, { + EmbeddingRecordConversionError::InvalidUuid => ErrorCodes::InvalidArgument, + EmbeddingRecordConversionError::OperationConversionError(inner) => inner.code(), + EmbeddingRecordConversionError::ScalarEncodingConversionError(inner) => inner.code(), + EmbeddingRecordConversionError::UpdateMetadataValueConversionError(inner) => inner.code(), + EmbeddingRecordConversionError::VectorConversionError(inner) => inner.code(), +}); + +impl TryFrom for EmbeddingRecord { + type Error = EmbeddingRecordConversionError; + + fn try_from( + proto_submit_with_seq_id: SubmitEmbeddingRecordWithSeqId, + ) -> Result { + let proto_submit = proto_submit_with_seq_id.0; + let seq_id = proto_submit_with_seq_id.1; + let op = match proto_submit.operation.try_into() { + Ok(op) => op, + Err(e) => return Err(EmbeddingRecordConversionError::OperationConversionError(e)), + }; + + let collection_uuid = match Uuid::try_parse(&proto_submit.collection_id) { + Ok(uuid) => uuid, + Err(_) => return Err(EmbeddingRecordConversionError::InvalidUuid), + }; + + let (embedding, encoding) = match proto_submit.vector { + Some(proto_vector) => match proto_vector.try_into() { + Ok((embedding, encoding)) => (Some(embedding), Some(encoding)), + Err(e) => return Err(EmbeddingRecordConversionError::VectorConversionError(e)), + }, + // If there is no vector, there is no encoding + None => (None, None), + }; + + let metadata: Option = match proto_submit.metadata { + Some(proto_metadata) => match proto_metadata.try_into() { + Ok(metadata) => Some(metadata), + Err(e) => { + return Err( + EmbeddingRecordConversionError::UpdateMetadataValueConversionError(e), + ) + } + }, + None => None, + }; + + Ok(EmbeddingRecord { + id: proto_submit.id, + seq_id: seq_id, + embedding: embedding, + encoding: encoding, + metadata: metadata, + operation: op, + collection_id: collection_uuid, + }) + } +} + +/* +=========================================== +Vector +=========================================== +*/ +impl TryFrom for (Vec, ScalarEncoding) { + type Error = VectorConversionError; + + fn try_from(proto_vector: chroma_proto::Vector) -> Result { + let out_encoding: ScalarEncoding = match proto_vector.encoding.try_into() { + Ok(encoding) => encoding, + Err(e) => return Err(VectorConversionError::ScalarEncodingConversionError(e)), + }; + + if out_encoding != ScalarEncoding::FLOAT32 { + // We only support float32 embeddings for now + return Err(VectorConversionError::UnsupportedEncoding); + } + + let out_vector = vec_to_f32(&proto_vector.vector); + match (out_vector, out_encoding) { + (Ok(vector), encoding) => Ok((vector.to_vec(), encoding)), + _ => Err(VectorConversionError::DecodeError( + ConversionError::DecodeError, + )), + } + } +} + +#[derive(Error, Debug)] +pub(crate) enum VectorConversionError { + #[error("Invalid byte length, must be divisible by 4")] + InvalidByteLength, + #[error(transparent)] + ScalarEncodingConversionError(#[from] ScalarEncodingConversionError), + #[error("Unsupported encoding")] + UnsupportedEncoding, + #[error(transparent)] + DecodeError(#[from] ConversionError), +} + +impl_base_convert_error!(VectorConversionError, { + VectorConversionError::InvalidByteLength => ErrorCodes::InvalidArgument, + VectorConversionError::UnsupportedEncoding => ErrorCodes::InvalidArgument, + VectorConversionError::ScalarEncodingConversionError(inner) => inner.code(), +}); + +/// Converts a vector of bytes to a vector of f32s +/// # WARNING +/// - This will only work if the machine is little endian since protobufs are little endian +/// - TODO: convert to big endian if the machine is big endian +/// # Notes +/// This method internally uses unsafe code to convert the bytes to f32s +fn vec_to_f32(bytes: &[u8]) -> Result<&[f32], VectorConversionError> { + // Transmutes a vector of bytes into vector of f32s + + if bytes.len() % 4 != 0 { + return Err(VectorConversionError::InvalidByteLength); + } + + unsafe { + let (pre, mid, post) = bytes.align_to::(); + if pre.len() != 0 || post.len() != 0 { + return Err(VectorConversionError::InvalidByteLength); + } + return Ok(mid); + } +} + +fn f32_to_vec(vector: &[f32]) -> Vec { + unsafe { + std::slice::from_raw_parts( + vector.as_ptr() as *const u8, + vector.len() * std::mem::size_of::(), + ) + } + .to_vec() +} + +impl TryFrom<(Vec, ScalarEncoding, usize)> for chroma_proto::Vector { + type Error = VectorConversionError; + + fn try_from( + (vector, encoding, dimension): (Vec, ScalarEncoding, usize), + ) -> Result { + let proto_vector = chroma_proto::Vector { + vector: f32_to_vec(&vector), + encoding: encoding as i32, + dimension: dimension as i32, + }; + Ok(proto_vector) + } +} + +/* +=========================================== +Vector Embedding Record +=========================================== +*/ + +#[derive(Debug)] +pub(crate) struct VectorEmbeddingRecord { + pub(crate) id: String, + pub(crate) seq_id: SeqId, + pub(crate) vector: Vec, +} + +/* +=========================================== +Vector Query Result +=========================================== + */ + +#[derive(Debug)] +pub(crate) struct VectorQueryResult { + pub(crate) id: String, + pub(crate) seq_id: SeqId, + pub(crate) distance: f32, + pub(crate) vector: Option>, +} + +#[cfg(test)] +mod tests { + use std::collections::HashMap; + + use num_bigint::BigInt; + + use super::*; + use crate::{chroma_proto, types::UpdateMetadataValue}; + + fn as_byte_view(input: &[f32]) -> Vec { + unsafe { + std::slice::from_raw_parts( + input.as_ptr() as *const u8, + input.len() * std::mem::size_of::(), + ) + } + .to_vec() + } + + #[test] + fn test_embedding_record_try_from() { + let mut metadata = chroma_proto::UpdateMetadata { + metadata: HashMap::new(), + }; + metadata.metadata.insert( + "foo".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::IntValue(42)), + }, + ); + let proto_vector = chroma_proto::Vector { + vector: as_byte_view(&[1.0, 2.0, 3.0]), + encoding: chroma_proto::ScalarEncoding::Float32 as i32, + dimension: 3, + }; + let proto_submit = chroma_proto::SubmitEmbeddingRecord { + id: "00000000-0000-0000-0000-000000000000".to_string(), + vector: Some(proto_vector), + metadata: Some(metadata), + operation: chroma_proto::Operation::Add as i32, + collection_id: "00000000-0000-0000-0000-000000000000".to_string(), + }; + let converted_embedding_record: EmbeddingRecord = + EmbeddingRecord::try_from((proto_submit, BigInt::from(42))).unwrap(); + assert_eq!(converted_embedding_record.id, Uuid::nil().to_string()); + assert_eq!(converted_embedding_record.seq_id, BigInt::from(42)); + assert_eq!( + converted_embedding_record.embedding, + Some(vec![1.0, 2.0, 3.0]) + ); + assert_eq!( + converted_embedding_record.encoding, + Some(ScalarEncoding::FLOAT32) + ); + let metadata = converted_embedding_record.metadata.unwrap(); + assert_eq!(metadata.len(), 1); + assert_eq!(metadata.get("foo").unwrap(), &UpdateMetadataValue::Int(42)); + assert_eq!(converted_embedding_record.operation, Operation::Add); + assert_eq!(converted_embedding_record.collection_id, Uuid::nil()); + } +} diff --git a/rust/worker/src/types/metadata.rs b/rust/worker/src/types/metadata.rs new file mode 100644 index 0000000000000000000000000000000000000000..73f4c749e1ebc69bfd46a705b9cdb730d8610ca0 --- /dev/null +++ b/rust/worker/src/types/metadata.rs @@ -0,0 +1,262 @@ +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use std::collections::HashMap; +use thiserror::Error; + +#[derive(Debug, PartialEq)] +pub(crate) enum UpdateMetadataValue { + Int(i32), + Float(f64), + Str(String), + None, +} + +#[derive(Error, Debug)] +pub(crate) enum UpdateMetadataValueConversionError { + #[error("Invalid metadata value, valid values are: Int, Float, Str, Bool, None")] + InvalidValue, +} + +impl ChromaError for UpdateMetadataValueConversionError { + fn code(&self) -> crate::errors::ErrorCodes { + match self { + UpdateMetadataValueConversionError::InvalidValue => ErrorCodes::InvalidArgument, + } + } +} + +impl TryFrom<&chroma_proto::UpdateMetadataValue> for UpdateMetadataValue { + type Error = UpdateMetadataValueConversionError; + + fn try_from(value: &chroma_proto::UpdateMetadataValue) -> Result { + match &value.value { + Some(chroma_proto::update_metadata_value::Value::IntValue(value)) => { + Ok(UpdateMetadataValue::Int(*value as i32)) + } + Some(chroma_proto::update_metadata_value::Value::FloatValue(value)) => { + Ok(UpdateMetadataValue::Float(*value)) + } + Some(chroma_proto::update_metadata_value::Value::StringValue(value)) => { + Ok(UpdateMetadataValue::Str(value.clone())) + } + _ => Err(UpdateMetadataValueConversionError::InvalidValue), + } + } +} + +/* +=========================================== +MetadataValue +=========================================== +*/ + +#[derive(Debug, PartialEq)] +pub(crate) enum MetadataValue { + Int(i32), + Float(f64), + Str(String), +} + +impl TryFrom<&MetadataValue> for i32 { + type Error = MetadataValueConversionError; + + fn try_from(value: &MetadataValue) -> Result { + match value { + MetadataValue::Int(value) => Ok(*value), + _ => Err(MetadataValueConversionError::InvalidValue), + } + } +} + +impl TryFrom<&MetadataValue> for f64 { + type Error = MetadataValueConversionError; + + fn try_from(value: &MetadataValue) -> Result { + match value { + MetadataValue::Float(value) => Ok(*value), + _ => Err(MetadataValueConversionError::InvalidValue), + } + } +} + +impl TryFrom<&MetadataValue> for String { + type Error = MetadataValueConversionError; + + fn try_from(value: &MetadataValue) -> Result { + match value { + MetadataValue::Str(value) => Ok(value.clone()), + _ => Err(MetadataValueConversionError::InvalidValue), + } + } +} + +#[derive(Error, Debug)] +pub(crate) enum MetadataValueConversionError { + #[error("Invalid metadata value, valid values are: Int, Float, Str")] + InvalidValue, +} + +impl ChromaError for MetadataValueConversionError { + fn code(&self) -> crate::errors::ErrorCodes { + match self { + MetadataValueConversionError::InvalidValue => ErrorCodes::InvalidArgument, + } + } +} + +impl TryFrom<&chroma_proto::UpdateMetadataValue> for MetadataValue { + type Error = MetadataValueConversionError; + + fn try_from(value: &chroma_proto::UpdateMetadataValue) -> Result { + match &value.value { + Some(chroma_proto::update_metadata_value::Value::IntValue(value)) => { + Ok(MetadataValue::Int(*value as i32)) + } + Some(chroma_proto::update_metadata_value::Value::FloatValue(value)) => { + Ok(MetadataValue::Float(*value)) + } + Some(chroma_proto::update_metadata_value::Value::StringValue(value)) => { + Ok(MetadataValue::Str(value.clone())) + } + _ => Err(MetadataValueConversionError::InvalidValue), + } + } +} + +/* +=========================================== +UpdateMetadata +=========================================== +*/ + +pub(crate) type UpdateMetadata = HashMap; + +impl TryFrom for UpdateMetadata { + type Error = UpdateMetadataValueConversionError; + + fn try_from(proto_metadata: chroma_proto::UpdateMetadata) -> Result { + let mut metadata = UpdateMetadata::new(); + for (key, value) in proto_metadata.metadata.iter() { + let value = match value.try_into() { + Ok(value) => value, + Err(_) => return Err(UpdateMetadataValueConversionError::InvalidValue), + }; + metadata.insert(key.clone(), value); + } + Ok(metadata) + } +} + +/* +=========================================== +Metadata +=========================================== +*/ + +pub(crate) type Metadata = HashMap; + +impl TryFrom for Metadata { + type Error = MetadataValueConversionError; + + fn try_from(proto_metadata: chroma_proto::UpdateMetadata) -> Result { + let mut metadata = Metadata::new(); + for (key, value) in proto_metadata.metadata.iter() { + let maybe_value: Result = value.try_into(); + if maybe_value.is_err() { + return Err(MetadataValueConversionError::InvalidValue); + } + let value = maybe_value.unwrap(); + metadata.insert(key.clone(), value); + } + Ok(metadata) + } +} + +#[cfg(test)] +mod tests { + use super::*; + + #[test] + fn test_update_metadata_try_from() { + let mut proto_metadata = chroma_proto::UpdateMetadata { + metadata: HashMap::new(), + }; + proto_metadata.metadata.insert( + "foo".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::IntValue(42)), + }, + ); + proto_metadata.metadata.insert( + "bar".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::FloatValue(42.0)), + }, + ); + proto_metadata.metadata.insert( + "baz".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::StringValue( + "42".to_string(), + )), + }, + ); + let converted_metadata: UpdateMetadata = proto_metadata.try_into().unwrap(); + assert_eq!(converted_metadata.len(), 3); + assert_eq!( + converted_metadata.get("foo").unwrap(), + &UpdateMetadataValue::Int(42) + ); + assert_eq!( + converted_metadata.get("bar").unwrap(), + &UpdateMetadataValue::Float(42.0) + ); + assert_eq!( + converted_metadata.get("baz").unwrap(), + &UpdateMetadataValue::Str("42".to_string()) + ); + } + + #[test] + fn test_metadata_try_from() { + let mut proto_metadata = chroma_proto::UpdateMetadata { + metadata: HashMap::new(), + }; + proto_metadata.metadata.insert( + "foo".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::IntValue(42)), + }, + ); + proto_metadata.metadata.insert( + "bar".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::FloatValue(42.0)), + }, + ); + proto_metadata.metadata.insert( + "baz".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::StringValue( + "42".to_string(), + )), + }, + ); + let converted_metadata: Metadata = proto_metadata.try_into().unwrap(); + assert_eq!(converted_metadata.len(), 3); + assert_eq!( + converted_metadata.get("foo").unwrap(), + &MetadataValue::Int(42) + ); + assert_eq!( + converted_metadata.get("bar").unwrap(), + &MetadataValue::Float(42.0) + ); + assert_eq!( + converted_metadata.get("baz").unwrap(), + &MetadataValue::Str("42".to_string()) + ); + } +} diff --git a/rust/worker/src/types/mod.rs b/rust/worker/src/types/mod.rs new file mode 100644 index 0000000000000000000000000000000000000000..edda924c42c91791458e12a960374d78fd504fb8 --- /dev/null +++ b/rust/worker/src/types/mod.rs @@ -0,0 +1,19 @@ +#[macro_use] +mod types; +mod collection; +mod embedding_record; +mod metadata; +mod operation; +mod scalar_encoding; +mod segment; +mod segment_scope; + +// Re-export the types module, so that we can use it as a single import in other modules. +pub use collection::*; +pub use embedding_record::*; +pub use metadata::*; +pub use operation::*; +pub use scalar_encoding::*; +pub use segment::*; +pub use segment_scope::*; +pub use types::*; diff --git a/rust/worker/src/types/operation.rs b/rust/worker/src/types/operation.rs new file mode 100644 index 0000000000000000000000000000000000000000..581e5c39f8eb2c836b540bd53bf6e9427fa213b9 --- /dev/null +++ b/rust/worker/src/types/operation.rs @@ -0,0 +1,73 @@ +use super::ConversionError; +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use thiserror::Error; + +#[derive(Debug, PartialEq)] +pub(crate) enum Operation { + Add, + Update, + Upsert, + Delete, +} + +#[derive(Error, Debug)] +pub(crate) enum OperationConversionError { + #[error("Invalid operation, valid operations are: Add, Upsert, Update, Delete")] + InvalidOperation, + #[error(transparent)] + DecodeError(#[from] ConversionError), +} + +impl_base_convert_error!(OperationConversionError, { + OperationConversionError::InvalidOperation => ErrorCodes::InvalidArgument, +}); + +impl TryFrom for Operation { + type Error = OperationConversionError; + + fn try_from(op: chroma_proto::Operation) -> Result { + match op { + chroma_proto::Operation::Add => Ok(Operation::Add), + chroma_proto::Operation::Upsert => Ok(Operation::Upsert), + chroma_proto::Operation::Update => Ok(Operation::Update), + chroma_proto::Operation::Delete => Ok(Operation::Delete), + _ => Err(OperationConversionError::InvalidOperation), + } + } +} + +impl TryFrom for Operation { + type Error = OperationConversionError; + + fn try_from(op: i32) -> Result { + let maybe_op = chroma_proto::Operation::try_from(op); + match maybe_op { + Ok(op) => match op { + chroma_proto::Operation::Add => Ok(Operation::Add), + chroma_proto::Operation::Upsert => Ok(Operation::Upsert), + chroma_proto::Operation::Update => Ok(Operation::Update), + chroma_proto::Operation::Delete => Ok(Operation::Delete), + _ => Err(OperationConversionError::InvalidOperation), + }, + Err(_) => Err(OperationConversionError::DecodeError( + ConversionError::DecodeError, + )), + } + } +} + +#[cfg(test)] +mod tests { + use super::*; + use crate::chroma_proto; + + #[test] + fn test_operation_try_from() { + let proto_op = chroma_proto::Operation::Add; + let converted_op: Operation = proto_op.try_into().unwrap(); + assert_eq!(converted_op, Operation::Add); + } +} diff --git a/rust/worker/src/types/scalar_encoding.rs b/rust/worker/src/types/scalar_encoding.rs new file mode 100644 index 0000000000000000000000000000000000000000..afcaf6b2e30cdf67905c2f983715740d8739ae75 --- /dev/null +++ b/rust/worker/src/types/scalar_encoding.rs @@ -0,0 +1,66 @@ +use super::ConversionError; +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use thiserror::Error; + +#[derive(Debug, PartialEq)] +pub(crate) enum ScalarEncoding { + FLOAT32, + INT32, +} + +#[derive(Error, Debug)] +pub(crate) enum ScalarEncodingConversionError { + #[error("Invalid encoding, valid encodings are: Float32, Int32")] + InvalidEncoding, + #[error(transparent)] + DecodeError(#[from] ConversionError), +} + +impl_base_convert_error!(ScalarEncodingConversionError, { + ScalarEncodingConversionError::InvalidEncoding => ErrorCodes::InvalidArgument, +}); + +impl TryFrom for ScalarEncoding { + type Error = ScalarEncodingConversionError; + + fn try_from(encoding: chroma_proto::ScalarEncoding) -> Result { + match encoding { + chroma_proto::ScalarEncoding::Float32 => Ok(ScalarEncoding::FLOAT32), + chroma_proto::ScalarEncoding::Int32 => Ok(ScalarEncoding::INT32), + _ => Err(ScalarEncodingConversionError::InvalidEncoding), + } + } +} + +impl TryFrom for ScalarEncoding { + type Error = ScalarEncodingConversionError; + + fn try_from(encoding: i32) -> Result { + let maybe_encoding = chroma_proto::ScalarEncoding::try_from(encoding); + match maybe_encoding { + Ok(encoding) => match encoding { + chroma_proto::ScalarEncoding::Float32 => Ok(ScalarEncoding::FLOAT32), + chroma_proto::ScalarEncoding::Int32 => Ok(ScalarEncoding::INT32), + _ => Err(ScalarEncodingConversionError::InvalidEncoding), + }, + Err(_) => Err(ScalarEncodingConversionError::DecodeError( + ConversionError::DecodeError, + )), + } + } +} + +#[cfg(test)] +mod tests { + use super::*; + + #[test] + fn test_scalar_encoding_try_from() { + let proto_encoding = chroma_proto::ScalarEncoding::Float32; + let converted_encoding: ScalarEncoding = proto_encoding.try_into().unwrap(); + assert_eq!(converted_encoding, ScalarEncoding::FLOAT32); + } +} diff --git a/rust/worker/src/types/segment.rs b/rust/worker/src/types/segment.rs new file mode 100644 index 0000000000000000000000000000000000000000..02e3dcd44349b15a52b58f66e5918346d2685934 --- /dev/null +++ b/rust/worker/src/types/segment.rs @@ -0,0 +1,129 @@ +use super::{Metadata, MetadataValueConversionError, SegmentScope, SegmentScopeConversionError}; +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use thiserror::Error; +use uuid::Uuid; + +#[derive(Debug, PartialEq)] +pub(crate) enum SegmentType { + HnswDistributed, +} + +#[derive(Debug, PartialEq)] +pub(crate) struct Segment { + pub(crate) id: Uuid, + pub(crate) r#type: SegmentType, + pub(crate) scope: SegmentScope, + pub(crate) topic: Option, + pub(crate) collection: Option, + pub(crate) metadata: Option, +} + +#[derive(Error, Debug)] +pub(crate) enum SegmentConversionError { + #[error("Invalid UUID")] + InvalidUuid, + #[error(transparent)] + MetadataValueConversionError(#[from] MetadataValueConversionError), + #[error(transparent)] + SegmentScopeConversionError(#[from] SegmentScopeConversionError), + #[error("Invalid segment type")] + InvalidSegmentType, +} + +impl ChromaError for SegmentConversionError { + fn code(&self) -> crate::errors::ErrorCodes { + match self { + SegmentConversionError::InvalidUuid => ErrorCodes::InvalidArgument, + SegmentConversionError::InvalidSegmentType => ErrorCodes::InvalidArgument, + SegmentConversionError::SegmentScopeConversionError(e) => e.code(), + SegmentConversionError::MetadataValueConversionError(e) => e.code(), + } + } +} + +impl TryFrom for Segment { + type Error = SegmentConversionError; + + fn try_from(proto_segment: chroma_proto::Segment) -> Result { + let segment_uuid = match Uuid::try_parse(&proto_segment.id) { + Ok(uuid) => uuid, + Err(_) => return Err(SegmentConversionError::InvalidUuid), + }; + let collection_uuid = match proto_segment.collection { + Some(collection_id) => match Uuid::try_parse(&collection_id) { + Ok(uuid) => Some(uuid), + Err(_) => return Err(SegmentConversionError::InvalidUuid), + }, + // The UUID can be none in the local version of chroma but not distributed + None => return Err(SegmentConversionError::InvalidUuid), + }; + let segment_metadata: Option = match proto_segment.metadata { + Some(proto_metadata) => match proto_metadata.try_into() { + Ok(metadata) => Some(metadata), + Err(e) => return Err(SegmentConversionError::MetadataValueConversionError(e)), + }, + None => None, + }; + let scope: SegmentScope = match proto_segment.scope.try_into() { + Ok(scope) => scope, + Err(e) => return Err(SegmentConversionError::SegmentScopeConversionError(e)), + }; + + let segment_type = match proto_segment.r#type.as_str() { + "urn:chroma:segment/vector/hnsw-distributed" => SegmentType::HnswDistributed, + _ => { + return Err(SegmentConversionError::InvalidUuid); + } + }; + + Ok(Segment { + id: segment_uuid, + r#type: segment_type, + scope: scope, + topic: proto_segment.topic, + collection: collection_uuid, + metadata: segment_metadata, + }) + } +} + +#[cfg(test)] +mod tests { + use std::collections::HashMap; + + use super::*; + use crate::types::MetadataValue; + + #[test] + fn test_segment_try_from() { + let mut metadata = chroma_proto::UpdateMetadata { + metadata: HashMap::new(), + }; + metadata.metadata.insert( + "foo".to_string(), + chroma_proto::UpdateMetadataValue { + value: Some(chroma_proto::update_metadata_value::Value::IntValue(42)), + }, + ); + let proto_segment = chroma_proto::Segment { + id: "00000000-0000-0000-0000-000000000000".to_string(), + r#type: "urn:chroma:segment/vector/hnsw-distributed".to_string(), + scope: chroma_proto::SegmentScope::Vector as i32, + topic: Some("test".to_string()), + collection: Some("00000000-0000-0000-0000-000000000000".to_string()), + metadata: Some(metadata), + }; + let converted_segment: Segment = proto_segment.try_into().unwrap(); + assert_eq!(converted_segment.id, Uuid::nil()); + assert_eq!(converted_segment.r#type, SegmentType::HnswDistributed); + assert_eq!(converted_segment.scope, SegmentScope::VECTOR); + assert_eq!(converted_segment.topic, Some("test".to_string())); + assert_eq!(converted_segment.collection, Some(Uuid::nil())); + let metadata = converted_segment.metadata.unwrap(); + assert_eq!(metadata.len(), 1); + assert_eq!(metadata.get("foo").unwrap(), &MetadataValue::Int(42)); + } +} diff --git a/rust/worker/src/types/segment_scope.rs b/rust/worker/src/types/segment_scope.rs new file mode 100644 index 0000000000000000000000000000000000000000..d2c1fb5392f3ce2609104db87bf5add6eafedaa9 --- /dev/null +++ b/rust/worker/src/types/segment_scope.rs @@ -0,0 +1,70 @@ +use super::ConversionError; +use crate::{ + chroma_proto, + errors::{ChromaError, ErrorCodes}, +}; +use thiserror::Error; + +#[derive(Debug, PartialEq)] +pub(crate) enum SegmentScope { + VECTOR, + METADATA, +} + +#[derive(Error, Debug)] +pub(crate) enum SegmentScopeConversionError { + #[error("Invalid segment scope, valid scopes are: Vector, Metadata")] + InvalidScope, + #[error(transparent)] + DecodeError(#[from] ConversionError), +} + +impl_base_convert_error!(SegmentScopeConversionError, { + SegmentScopeConversionError::InvalidScope => ErrorCodes::InvalidArgument, +}); + +impl TryFrom for SegmentScope { + type Error = SegmentScopeConversionError; + + fn try_from(scope: chroma_proto::SegmentScope) -> Result { + match scope { + chroma_proto::SegmentScope::Vector => Ok(SegmentScope::VECTOR), + chroma_proto::SegmentScope::Metadata => Ok(SegmentScope::METADATA), + _ => Err(SegmentScopeConversionError::InvalidScope), + } + } +} + +impl TryFrom for SegmentScope { + type Error = SegmentScopeConversionError; + + fn try_from(scope: i32) -> Result { + let maybe_scope = chroma_proto::SegmentScope::try_from(scope); + match maybe_scope { + Ok(scope) => match scope { + chroma_proto::SegmentScope::Vector => Ok(SegmentScope::VECTOR), + chroma_proto::SegmentScope::Metadata => Ok(SegmentScope::METADATA), + _ => Err(SegmentScopeConversionError::InvalidScope), + }, + Err(_) => Err(SegmentScopeConversionError::DecodeError( + ConversionError::DecodeError, + )), + } + } +} + +#[cfg(test)] +mod tests { + use super::*; + + #[test] + fn test_segment_scope_try_from() { + let proto_scope = chroma_proto::SegmentScope::Vector; + let converted_scope: SegmentScope = proto_scope.try_into().unwrap(); + assert_eq!(converted_scope, SegmentScope::VECTOR); + + let proto_scope = chroma_proto::SegmentScope::Metadata; + let converted_scope: SegmentScope = proto_scope.try_into().unwrap(); + assert_eq!(converted_scope, SegmentScope::METADATA); + } +} diff --git a/rust/worker/src/types/types.rs b/rust/worker/src/types/types.rs new file mode 100644 index 0000000000000000000000000000000000000000..e87337cc5112e41d1db4ad6cd3d30036b1ddbfd3 --- /dev/null +++ b/rust/worker/src/types/types.rs @@ -0,0 +1,36 @@ +use crate::errors::{ChromaError, ErrorCodes}; +use num_bigint::BigInt; +use thiserror::Error; + +/// A macro for easily implementing match arms for a base error type with common errors. +/// Other types can wrap it and still implement the ChromaError trait +/// without boilerplate. +macro_rules! impl_base_convert_error { + ($err:ty, { $($variant:pat => $action:expr),* $(,)? }) => { + impl ChromaError for $err { + fn code(&self) -> ErrorCodes { + match self { + Self::DecodeError(inner) => inner.code(), + // Handle custom variants + $( $variant => $action, )* + } + } + } + }; +} + +#[derive(Error, Debug)] +pub(crate) enum ConversionError { + #[error("Error decoding protobuf message")] + DecodeError, +} + +impl ChromaError for ConversionError { + fn code(&self) -> crate::errors::ErrorCodes { + match self { + ConversionError::DecodeError => ErrorCodes::Internal, + } + } +} + +pub(crate) type SeqId = BigInt; diff --git a/yarn.lock b/yarn.lock new file mode 100644 index 0000000000000000000000000000000000000000..4a5801883d149bce5126709c3ad90fc60a4d657f --- /dev/null +++ b/yarn.lock @@ -0,0 +1,2 @@ +# THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY. +# yarn lockfile v1