# Docling Serve Running [Docling](https://github.com/docling-project/docling) as an API service. ## Usage The API provides two endpoints: one for urls, one for files. This is necessary to send files directly in binary format instead of base64-encoded strings. ### Common parameters On top of the source of file (see below), both endpoints support the same parameters, which are almost the same as the Docling CLI. - `from_format` (List[str]): Input format(s) to convert from. Allowed values: `docx`, `pptx`, `html`, `image`, `pdf`, `asciidoc`, `md`. Defaults to all formats. - `to_formats` (List[str]): Output format(s) to convert to. Allowed values: `md`, `json`, `html`, `text`, `doctags`. Defaults to `md`. - `do_ocr` (bool): If enabled, the bitmap content will be processed using OCR. Defaults to `True`. - `image_export_mode`: Image export mode for the document (only in case of JSON, Markdown or HTML). Allowed values: embedded, placeholder, referenced. Optional, defaults to `embedded`. - `force_ocr` (bool): If enabled, replace any existing text with OCR-generated text over the full content. Defaults to `False`. - `ocr_engine` (str): OCR engine to use. Allowed values: `easyocr`, `tesseract_cli`, `tesseract`, `rapidocr`, `ocrmac`. Defaults to `easyocr`. - `ocr_lang` (List[str]): List of languages used by the OCR engine. Note that each OCR engine has different values for the language names. Defaults to empty. - `pdf_backend` (str): PDF backend to use. Allowed values: `pypdfium2`, `dlparse_v1`, `dlparse_v2`. Defaults to `dlparse_v2`. - `table_mode` (str): Table mode to use. Allowed values: `fast`, `accurate`. Defaults to `fast`. - `abort_on_error` (bool): If enabled, abort on error. Defaults to false. - `return_as_file` (boo): If enabled, return the output as a file. Defaults to false. - `do_table_structure` (bool): If enabled, the table structure will be extracted. Defaults to true. - `include_images` (bool): If enabled, images will be extracted from the document. Defaults to true. - `images_scale` (float): Scale factor for images. Defaults to 2.0. ### URL endpoint The endpoint is `/v1alpha/convert/source`, listening for POST requests of JSON payloads. On top of the above parameters, you must send the URL(s) of the document you want process with either the `http_sources` or `file_sources` fields. The first is fetching URL(s) (optionally using with extra headers), the second allows to provide documents as base64-encoded strings. No `options` is required, they can be partially or completely omitted. Simple payload example: ```json { "http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}] } ```
Complete payload example: ```json { "options": { "from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"], "to_formats": ["md", "json", "html", "text", "doctags"], "image_export_mode": "placeholder", "do_ocr": true, "force_ocr": false, "ocr_engine": "easyocr", "ocr_lang": ["en"], "pdf_backend": "dlparse_v2", "table_mode": "fast", "abort_on_error": false, "return_as_file": false, }, "http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}] } ```
CURL example: ```sh curl -X 'POST' \ 'http://localhost:5001/v1alpha/convert/source' \ -H 'accept: application/json' \ -H 'Content-Type: application/json' \ -d '{ "options": { "from_formats": [ "docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx" ], "to_formats": ["md", "json", "html", "text", "doctags"], "image_export_mode": "placeholder", "do_ocr": true, "force_ocr": false, "ocr_engine": "easyocr", "ocr_lang": [ "fr", "de", "es", "en" ], "pdf_backend": "dlparse_v2", "table_mode": "fast", "abort_on_error": false, "return_as_file": false, "do_table_structure": true, "include_images": true, "images_scale": 2 }, "http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}] }' ```
Python example: ```python import httpx async_client = httpx.AsyncClient(timeout=60.0) url = "http://localhost:5001/v1alpha/convert/source" payload = { "options": { "from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"], "to_formats": ["md", "json", "html", "text", "doctags"], "image_export_mode": "placeholder", "do_ocr": True, "force_ocr": False, "ocr_engine": "easyocr", "ocr_lang": "en", "pdf_backend": "dlparse_v2", "table_mode": "fast", "abort_on_error": False, "return_as_file": False, }, "http_sources": [{"url": "https://arxiv.org/pdf/2206.01062"}] } response = await async_client_client.post(url, json=payload) data = response.json() ```
#### File as base64 The `file_sources` argument in the endpoint allows to send files as base64-encoded strings. When your PDF or other file type is too large, encoding it and passing it inline to curl can lead to an โ€œArgument list too longโ€ error on some systems. To avoid this, we write the JSON request body to a file and have curl read from that file.
CURL steps: ```sh # 1. Base64-encode the file B64_DATA=$(base64 -w 0 /path/to/file/pdf-to-convert.pdf) # 2. Build the JSON with your options cat < /tmp/request_body.json { "options": { }, "file_sources": [{ "base64_string": "${B64_DATA}", "filename": "pdf-to-convert.pdf" }] } EOF # 3. POST the request to the docling service curl -X POST "localhost:5001/v1alpha/convert/source" \ -H "Content-Type: application/json" \ -d @/tmp/request_body.json ```
### File endpoint The endpoint is: `/v1alpha/convert/file`, listening for POST requests of Form payloads (necessary as the files are sent as multipart/form data). You can send one or multiple files.
CURL example: ```sh curl -X 'POST' \ 'http://127.0.0.1:5001/v1alpha/convert/file' \ -H 'accept: application/json' \ -H 'Content-Type: multipart/form-data' \ -F 'ocr_engine=easyocr' \ -F 'pdf_backend=dlparse_v2' \ -F 'from_formats=pdf' \ -F 'from_formats=docx' \ -F 'force_ocr=false' \ -F 'image_export_mode=embedded' \ -F 'ocr_lang=en' \ -F 'ocr_lang=pl' \ -F 'table_mode=fast' \ -F 'files=@2206.01062v1.pdf;type=application/pdf' \ -F 'abort_on_error=false' \ -F 'to_formats=md' \ -F 'to_formats=text' \ -F 'return_as_file=false' \ -F 'do_ocr=true' ```
Python example: ```python import httpx async_client = httpx.AsyncClient(timeout=60.0) url = "http://localhost:5001/v1alpha/convert/file" parameters = { "from_formats": ["docx", "pptx", "html", "image", "pdf", "asciidoc", "md", "xlsx"], "to_formats": ["md", "json", "html", "text", "doctags"], "image_export_mode": "placeholder", "do_ocr": True, "force_ocr": False, "ocr_engine": "easyocr", "ocr_lang": ["en"], "pdf_backend": "dlparse_v2", "table_mode": "fast", "abort_on_error": False, "return_as_file": False } current_dir = os.path.dirname(__file__) file_path = os.path.join(current_dir, '2206.01062v1.pdf') files = { 'files': ('2206.01062v1.pdf', open(file_path, 'rb'), 'application/pdf'), } response = await async_client.post(url, files=files, data={"parameters": json.dumps(parameters)}) assert response.status_code == 200, "Response should be 200 OK" data = response.json() ```
### Response format The response can be a JSON Document or a File. - If you process only one file, the response will be a JSON document with the following format: ```jsonc { "document": { "md_content": "", "json_content": {}, "html_content": "", "text_content": "", "doctags_content": "" }, "status": "", "processing_time": 0.0, "timings": {}, "errors": [] } ``` Depending on the value you set in `output_formats`, the different items will be populated with their respective results or empty. `processing_time` is the Docling processing time in seconds, and `timings` (when enabled in the backend) provides the detailed timing of all the internal Docling components. - If you set the parameter `return_as_file` to True, the response will be a zip file. - If multiple files are generated (multiple inputs, or one input but multiple outputs with `return_as_file` True), the response will be a zip file. ## Run docling-serve Clone the repository and run the following from within the cloned directory root. ```bash python -m venv venv source venv/bin/activate pip install "docling-serve[ui]" docling-serve run --enable-ui ``` ## Helpers - A full Swagger UI is available at the `/docs` endpoint. ![swagger.png](img/swagger.png) - An easy to use UI is available at the `/ui` endpoint. ![ui-input.png](img/ui-input.png) ![ui-output.png](img/ui-output.png) ## Development ### CPU only ```sh # Install uv if not already available curl -LsSf https://astral.sh/uv/install.sh | sh # Install dependencies uv sync --extra cpu ``` ### Cuda GPU For GPU support use the following command: ```sh # Install dependencies uv sync ``` ### Gradio UI and different OCR backends `/ui` endpoint using `gradio` and different OCR backends can be enabled via package extras: ```sh # Enable ui and rapidocr uv sync --extra ui --extra rapidocr ``` ```sh # Enable tesserocr uv sync --extra tesserocr ``` See `[project.optional-dependencies]` section in `pyproject.toml` for full list of options and runtime options with `uv run docling-serve --help`. ### Run the server The `docling-serve` executable is a convenient script for launching the webserver both in development and production mode. ```sh # Run the server in development mode # - reload is enabled by default # - listening on the 127.0.0.1 address # - ui is enabled by default docling-serve dev # Run the server in production mode # - reload is disabled by default # - listening on the 0.0.0.0 address # - ui is disabled by default docling-serve run ``` ### Options The `docling-serve` executable allows is controlled with both command line options and environment variables.
`docling-serve` help message ```sh $ docling-serve dev --help Usage: docling-serve dev [OPTIONS] Run a Docling Serve app in development mode. ๐Ÿงช This is equivalent to docling-serve run but with reload enabled and listening on the 127.0.0.1 address. Options can be set also with the corresponding ENV variable, with the exception of --enable-ui, --host and --reload. โ•ญโ”€ Options โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฎ โ”‚ --host TEXT The host to serve on. For local development in localhost โ”‚ โ”‚ use 127.0.0.1. To enable public access, e.g. in a โ”‚ โ”‚ container, use all the IP addresses available with โ”‚ โ”‚ 0.0.0.0. โ”‚ โ”‚ [default: 127.0.0.1] โ”‚ โ”‚ --port INTEGER The port to serve on. [default: 5001] โ”‚ โ”‚ --reload --no-reload Enable auto-reload of the server when (code) files โ”‚ โ”‚ change. This is resource intensive, use it only during โ”‚ โ”‚ development. โ”‚ โ”‚ [default: reload] โ”‚ โ”‚ --root-path TEXT The root path is used to tell your app that it is being โ”‚ โ”‚ served to the outside world with some path prefix set up โ”‚ โ”‚ in some termination proxy or similar. โ”‚ โ”‚ --proxy-headers --no-proxy-headers Enable/Disable X-Forwarded-Proto, X-Forwarded-For, โ”‚ โ”‚ X-Forwarded-Port to populate remote address info. โ”‚ โ”‚ [default: proxy-headers] โ”‚ โ”‚ --artifacts-path PATH If set to a valid directory, the model weights will be โ”‚ โ”‚ loaded from this path. โ”‚ โ”‚ [default: None] โ”‚ โ”‚ --enable-ui --no-enable-ui Enable the development UI. [default: enable-ui] โ”‚ โ”‚ --help Show this message and exit. โ”‚ โ•ฐโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ•ฏ ```
#### Environment variables The environment variables controlling the `uvicorn` execution can be specified with the `UVICORN_` prefix: - `UVICORN_WORKERS`: Number of workers to use. - `UVICORN_RELOAD`: If `True`, this will enable auto-reload when you modify files, useful for development. The environment variables controlling specifics of the Docling Serve app can be specified with the `DOCLING_SERVE_` prefix: - `DOCLING_SERVE_ARTIFACTS_PATH`: if set Docling will use only the local weights of models, for example `/opt/app-root/src/.cache/docling/models`. - `DOCLING_SERVE_ENABLE_UI`: If `True`, The Gradio UI will be available at `/ui`. Others: - `TESSDATA_PREFIX`: Tesseract data location, example `/usr/share/tesseract/tessdata/`. ## Get help and support Please feel free to connect with us using the [discussion section](https://github.com/docling-project/docling/discussions). ## Contributing Please read [Contributing to Docling Serve](https://github.com/docling-project/docling-serve/blob/main/CONTRIBUTING.md) for details. ## References If you use Docling in your projects, please consider citing the following: ```bib @techreport{Docling, author = {Deep Search Team}, month = {8}, title = {Docling Technical Report}, url = {https://arxiv.org/abs/2408.09869}, eprint = {2408.09869}, doi = {10.48550/arXiv.2408.09869}, version = {1.0.0}, year = {2024} } ``` ## License The Docling Serve codebase is under MIT license. ## IBM โค๏ธ Open Source AI Docling has been brought to you by IBM.