Docling Serve

Running Docling as an API service.

📚 Docling Serve documentation

• Learning how to configure the webserver
• Get to know all runtime options of the API
• Explore useful deployment examples
• And more

Note

Migration to the v1 API. Docling Serve now has a stable v1 API. Read more on the migration to v1.

Getting started

Install the docling-serve package and run the server.

# Using the python package
pip install "docling-serve[ui]"
docling-serve run --enable-ui

# Using container images, e.g. with Podman
podman run -p 5001:5001 -e DOCLING_SERVE_ENABLE_UI=1 quay.io/docling-project/docling-serve

The server is available at

• API http://127.0.0.1:5001
• API documentation http://127.0.0.1:5001/docs
• UI playground http://127.0.0.1:5001/ui

Try it out with a simple conversion:

curl -X 'POST' \
  'http://localhost:5001/v1/convert/source' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
    "http_sources": [{"url": "https://arxiv.org/pdf/2501.17887"}]
  }'

Container images

Available container images:

Name	Description	Arch	Size
ghcr.io/docling-project/docling-serve quay.io/docling-project/docling-serve	Simple image for Docling Serve, installing all packages from the official pypi.org index.	linux/amd64, linux/arm64	3.6 GB (arm64) 8.7 GB (amd64)
ghcr.io/docling-project/docling-serve-cpu quay.io/docling-project/docling-serve-cpu	Cpu-only image which installs torch from the pytorch cpu index.	linux/amd64, linux/arm64	3.6 GB
ghcr.io/docling-project/docling-serve-cu124 quay.io/docling-project/docling-serve-cu124	Cuda 12.4 image which installs torch from the pytorch cu124 index.	linux/amd64	8.7 GB
ghcr.io/docling-project/docling-serve-cu126 quay.io/docling-project/docling-serve-cu126	Cuda 12.6 image which installs torch from the pytorch cu126 index.	linux/amd64	8.7 GB
ghcr.io/docling-project/docling-serve-cu128 quay.io/docling-project/docling-serve-cu128	Cuda 12.8 image which installs torch from the pytorch cu128 index.	linux/amd64	8.7 GB

Coming soon: docling-serve-slim images will reduce the size by skipping the model weights download.

Demonstration UI

An easy to use UI is available at the /ui endpoint.

Get help and support

Please feel free to connect with us using the discussion section.

Contributing

Please read Contributing to Docling Serve for details.

References

If you use Docling in your projects, please consider citing the following:

@techreport{Docling,
  author = {Docling Contributors},
  month = {1},
  title = {Docling: An Efficient Open-Source Toolkit for AI-driven Document Conversion},
  url = {https://arxiv.org/abs/2501.17887},
  eprint = {2501.17887},
  doi = {10.48550/arXiv.2501.17887},
  version = {2.0.0},
  year = {2025}
}

License

The Docling Serve codebase is under MIT license.

IBM ❤️ Open Source AI

Docling has been brought to you by IBM.