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Václav Vančura 3245e1b8b7 Actor: Enhance README.md with output details

Added detailed information about the Actor's output storage to the `README.md`. This includes specifying where processed documents, processing logs, and dataset records are stored.

Signed-off-by: Václav Vančura <commit@vancura.dev>

2025-03-13 10:38:51 +01:00

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Docling

Docling parses documents and exports them to the desired format with ease and speed.

Features

🗂️ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to HTML, Markdown and JSON (with embedded and referenced images)
📑 Advanced PDF document understanding including page layout, reading order & table structures
🧩 Unified, expressive DoclingDocument representation format
🤖 Plug-and-play integrations incl. LangChain, LlamaIndex, Crew AI & Haystack for agentic AI
🔍 OCR support for scanned PDFs
💻 Simple and convenient CLI

Explore the documentation to discover plenty examples and unlock the full power of Docling!

Coming soon

♾️ Equation & code extraction
📝 Metadata extraction, including title, authors, references & language

Installation

To use Docling, simply install docling from your package manager, e.g. pip:

pip install docling

Works on macOS, Linux and Windows environments. Both x86_64 and arm64 architectures.

More detailed installation instructions are available in the docs.

Getting started

To convert individual documents, use convert(), for example:

from docling.document_converter import DocumentConverter

source = "https://arxiv.org/pdf/2408.09869"  # document per local path or URL
converter = DocumentConverter()
result = converter.convert(source)
print(result.document.export_to_markdown())  # output: "## Docling Technical Report[...]"

More advanced usage options are available in the docs.

Documentation

Check out Docling's documentation, for details on installation, usage, concepts, recipes, extensions, and more.

Examples

Go hands-on with our examples, demonstrating how to address different application use cases with Docling.

Integrations

To further accelerate your AI application development, check out Docling's native integrations with popular frameworks and tools.

Apify Actor

You can run Docling in the cloud without installation using the Docling Actor on Apify platform. Simply provide a document URL and get the processed result:

apify call vancura/docling -i '{
    "documentUrl": "https://arxiv.org/pdf/2408.09869",
    "outputFormat": "markdown",
    "ocr": true
}'

The Actor stores results in:

Processed document in key-value store (OUTPUT_RESULT)
Processing logs (DOCLING_LOG)
Dataset record with result URL and status

Read more about the Docling Actor, including how to use it via the Apify API and CLI.

Get help and support

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

Technical report

For more details on Docling's inner workings, check out the Docling Technical Report.

Contributing

Please read Contributing to Docling for details.

References

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

@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 codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.

IBM ❤️ Open Source AI

Docling has been brought to you by IBM.

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