Skip to main content

SDK and CLI for parsing PDF, DOCX, HTML, and more, to a unified document representation for powering downstream workflows such as gen AI applications.

Project description

Docling

Docling

arXiv Docs PyPI version Python Poetry Code style: black Imports: isort Pydantic v2 pre-commit License MIT

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

Features

  • 🗂️ Reads popular document formats (PDF, DOCX, PPTX, Images, HTML, AsciiDoc, Markdown) and exports to Markdown and JSON
  • 📑 Advanced PDF document understanding including page layout, reading order & table structures
  • 🧩 Unified, expressive DoclingDocument representation format
  • 📝 Metadata extraction, including title, authors, references & language
  • 🤖 Seamless LlamaIndex 🦙 & LangChain 🦜🔗 integration for powerful RAG / QA applications
  • 🔍 OCR support for scanned PDFs
  • 💻 Simple and convenient CLI

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

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[...]"

Check out Getting started. You will find lots of tuning options to leverage all the advanced capabilities.

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

docling-2.4.0.tar.gz (64.5 kB view details)

Uploaded Source

Built Distribution

docling-2.4.0-py3-none-any.whl (83.7 kB view details)

Uploaded Python 3

File details

Details for the file docling-2.4.0.tar.gz.

File metadata

  • Download URL: docling-2.4.0.tar.gz
  • Upload date:
  • Size: 64.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/6.5.0-1025-azure

File hashes

Hashes for docling-2.4.0.tar.gz
Algorithm Hash digest
SHA256 5edf628c85a3aadf5081b96089d2ee82854e067c842917319ed9590e043e42e5
MD5 dd96ce3cef8b730c9e1c32569ad4c184
BLAKE2b-256 ec7fd7e0fd062dde1ef605cd53a3202592f850fcaa96929ee53da31a945b9486

See more details on using hashes here.

Provenance

File details

Details for the file docling-2.4.0-py3-none-any.whl.

File metadata

  • Download URL: docling-2.4.0-py3-none-any.whl
  • Upload date:
  • Size: 83.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.10.12 Linux/6.5.0-1025-azure

File hashes

Hashes for docling-2.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 2c67b1f0ea534ee4292a0521dda1d0fd0b05a1d726d19995a45df34c85c64850
MD5 6150f17aabb1a6fbe18fa3bfff314a8f
BLAKE2b-256 cff67fb481324225cbfe6c1906eece28254eec4673eb9be20022024f27554175

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page