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.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# Python notebooks
+*.ipynb
+
+# Models
+model

Dockerfile

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+FROM paperspace/fastapi-app-base:2023-06-14
+
+WORKDIR /app
+
+COPY app ./app
+COPY requirements.txt ./
+
+RUN pip3 install -U pip && pip3 install -r requirements.txt
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

LICENSE

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README.md

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----
-title: App
-emoji: 📊
-colorFrom: purple
-colorTo: red
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Run a FastAPI app with a Hugging Face model on Paperspace
+
+## Intro
+
+This is a template for users looking to deploy their own FastAPI app with a Hugging Face model on Paperspace.
+
+- The [FastAPI](https://fastapi.tiangolo.com/lo/) app code is located in `app/main.py`
+- The Dockerfile is used to create an image which was pushed as a public image to [paperspace/fastapi-hf-template-app:2023-06-20](https://hub.docker.com/repository/docker/paperspace/fastapi-hf-template-app)
+- The above image can be deployed to Paperspace using the [app config](https://docs-next.paperspace.com/deploying/app-config) located at `paperspace.yaml`
+
+## Project Structure
+
+```
+├── Dockerfile
+├── requirements.txt
+├── paperspace.yaml
+├── app
+    ├── main.py
+```
+
+## Develop locally
+
+- Install the [Paperspace CLI](https://docs-next.paperspace.com/cli) `curl -fsSL https://paperspace.com/install.sh | sh`
+- Initialize the app `pspace init paperspace-hf -t Paperspace/FastAPI-Hugging-Face-Template-App`. This will create an app locally, clone this GitHub repo as your app template, and remotely link your app to Paperspace so you can add [secrets](https://docs-next.paperspace.com/secrets) and collaborators.
+- Make updates to your application (e.g. application files, Dockerfile, requirements.txt)
+- Change the Hugging Face model used in the app
+- Build a new image by running `docker build -t my-image:tag .`
+- Push image to the container registry of your choice by running `docker push my-image:tag`
+- Update the app config at `paperspace.yaml` with the location of your new image
+- Update the app config with your choice of Hugging Face model. When using integrations, mounts will be located at /opt/integrations/<name>
+- Deploy your application on Paperspace by running [`pspace up`](https://docs-next.paperspace.com/cli/up). Ensure you have the [Paperspace CLI](https://github.com/Paperspace/cli#installation) installed.
+
+## How to deploy
+
+- Install the [Paperspace CLI](https://docs-next.paperspace.com/cli) `curl -fsSL https://paperspace.com/install.sh | sh`
+- Run [`pspace up`](https://docs-next.paperspace.com/cli/up) to deploy your app on Paperspace. This will send the app config at [paperspace.yaml)(paperspace.yaml) to Paperspace, which will spin up your application.
+- Once the application is in a ready state, you can send a translation request to the endpoint using the application URL:
+`curl -X GET '<application-url>/translate?text_input=Hello+world!'`
+
+## Simplify your deployment workflow with GitHub Actions
+
+Use the [Paperspace Deploy Action](https://github.com/Paperspace/deploy-action) to integrate a build/push process into your CI/CD pipeline.
+
+## Benefits of Hugging Face integrations
+
+Hugging Face integrations are a simple way to integrate Hugging Face models into your application while improving start time performance for auto-scaling and production level applications.
+
+A Hugging Face integration happens once at the beginning of each new application deployment (i.e. each app config update). A temporary volume is created, the Hugging Face repo is then cloned into that volume, and that volume is then mounted to your container on startup at `/opt/integrations/<integration-name>`. Any new replicas that are spun up due to auto-scaling will also have the volume mounted to the same path, without having to go through the repo cloning process again, which shortens startup times for each subsequent replica spin up. Learn more about integrations in the [Paperspace docs](https://docs-next.paperspace.com/).
+
+
+
+## Documentation
+
+Learn more about Paperspace apps at our [documentation site](https://docs-next.paperspace.com/apps).

app/main.py

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+from fastapi import FastAPI
+from contextlib import asynccontextmanager
+from transformers import pipeline
+
+# function to return a transformers pipeline for translation
+def get_translation_pipeline():
+    return pipeline('translation', model='/opt/integrations/opus-mt-en-es', tokenizer='/opt/integrations/opus-mt-en-es')
+
+models = {}
+
+# creating an async context manager to define events to take place on startup and shutdown of the FastAPI app
+# more information about lifespan events can be found here: https://fastapi.tiangolo.com/advanced/events/
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    # Load the ML model on startup
+    models['translation'] = get_translation_pipeline()
+    yield
+    # Clean up the ML models and release the resources on shutdown
+    models.clear()
+
+app = FastAPI(lifespan=lifespan)
+
+# startup checks detect if a container has started successfully which will then kickoff the liveness and readiness checks
+@app.get("/startup/", status_code=200)
+def startup_check():
+    return "Startup check succeeded."
+
+# liveness checks detect deployment containers that transition to an unhealthy state and remedy said situations through targeted restarts
+@app.get("/liveness/", status_code=200)
+def liveness_check():
+    return "Liveness check succeeded."
+
+# readiness checks tell our load balancers when a container is ready to receive traffic
+@app.get("/readiness/", status_code=200)
+def readiness_check():
+    return "Readiness check succeeded."
+
+@app.get("/")
+async def root():
+    return {"message": "Welcome to my FastAPI + Hugging Face app!"}
+
+# translate endpoint that takes in an english string and returns the spanish translation
+@app.get("/translate")
+async def translate(text_input: str):
+    return models['translation'](text_input)[0]
+
+
+# Add additional endpoints below

paperspace.yaml

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+apiVersion: v1
+# To disable the application change enabled: false
+enabled: true
+# The name of your project
+name: my-fastapi-hf-app
+# You should replace this with a Docker image you build
+image: paperspace/fastapi-hf-template-app:2023-06-20
+# Using integrations to bring in external resource
+# (e.g. Hugging Face model, S3 bucket)
+integrations:
+  - type: git-lfs # git-lfs used for Hugging Face models
+    name: opus-mt-en-es
+    url: https://huggingface.co/Helsinki-NLP/opus-mt-en-es # English to Spanish translation model
+    path: /opt/integrations/opus-mt-en-es
+# Deploy safely by using health checks, preventing traffic from being 
+# routed to unhealthy instances
+healthChecks:
+  startup:
+    path: /
+    port: 8000
+  readiness:
+    path: /
+    port: 8000
+  liveness:
+    path: /
+    port: 8000
+# The resources section defines the compute resources used by your service. 
+# You can specify a number of replicas, an instance type, and autoscaling 
+# settings here
+resources:
+  replicas: 1
+  machineType: C5
+  # The ports the service is running on inside the above image
+  ports: [8000]
+  autoscaling:
+    enabled: true
+    maxReplicas: 2
+    metrics:
+      - metric: requestDuration
+        summary: average
+        value: 1.2
+      - metric: cpu
+        summary: average
+        value: 75
+
+

requirements.txt

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+# Add library dependencies here
+# Example: torch==2.0.1
+torch==2.0.1
+transformers==4.30.2
+sentencepiece==0.1.99