<p align="center">
<a href="https://github.com/ds4sd/docling">
<img loading="lazy" alt="Docling" src="https://github.com/DS4SD/docling/raw/main/docs/assets/docling_processing.png" width="100%"/>
</a>
</p>
# Docling
<p align="center">
<a href="https://trendshift.io/repositories/12132" target="_blank"><img src="https://trendshift.io/api/badge/repositories/12132" alt="DS4SD%2Fdocling | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>
[](https://arxiv.org/abs/2408.09869)
[](https://ds4sd.github.io/docling/)
[](https://pypi.org/project/docling/)
[](https://pypi.org/project/docling/)
[](https://python-poetry.org/)
[](https://github.com/psf/black)
[](https://pycqa.github.io/isort/)
[](https://pydantic.dev)
[](https://github.com/pre-commit/pre-commit)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/projects/docling)
Docling parses documents and exports them to the desired format with ease and speed.
## Features
* ποΈ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to HTML, Markdown and JSON (with embedded and referenced images)
* π Advanced PDF document understanding including page layout, reading order & table structures
* π§© Unified, expressive [DoclingDocument](https://ds4sd.github.io/docling/concepts/docling_document/) representation format
* π€ Easy integration with π¦ LlamaIndex & π¦π LangChain for powerful RAG / QA applications
* π OCR support for scanned PDFs
* π» Simple and convenient CLI
Explore the [documentation](https://ds4sd.github.io/docling/) to discover plenty examples and unlock the full power of Docling!
### Coming soon
* βΎοΈ Equation & code extraction
* π Metadata extraction, including title, authors, references & language
* π¦π Native LangChain extension
## Installation
To use Docling, simply install `docling` from your package manager, e.g. pip:
```bash
pip install docling
```
Works on macOS, Linux and Windows environments. Both x86_64 and arm64 architectures.
More [detailed installation instructions](https://ds4sd.github.io/docling/installation/) are available in the docs.
## Getting started
To convert individual documents, use `convert()`, for example:
```python
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](https://ds4sd.github.io/docling/usage/) are available in
the docs.
## Documentation
Check out Docling's [documentation](https://ds4sd.github.io/docling/), for details on
installation, usage, concepts, recipes, extensions, and more.
## Examples
Go hands-on with our [examples](https://ds4sd.github.io/docling/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](https://ds4sd.github.io/docling/integrations/) with popular frameworks
and tools.
## Get help and support
Please feel free to connect with us using the [discussion section](https://github.com/DS4SD/docling/discussions).
## Technical report
For more details on Docling's inner workings, check out the [Docling Technical Report](https://arxiv.org/abs/2408.09869).
## Contributing
Please read [Contributing to Docling](https://github.com/DS4SD/docling/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 codebase is under MIT license.
For individual model usage, please refer to the model licenses found in the original packages.
## IBM β€οΈ Open Source AI
Docling has been brought to you by IBM.
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"description": "<p align=\"center\">\n <a href=\"https://github.com/ds4sd/docling\">\n <img loading=\"lazy\" alt=\"Docling\" src=\"https://github.com/DS4SD/docling/raw/main/docs/assets/docling_processing.png\" width=\"100%\"/>\n </a>\n</p>\n\n# Docling\n\n<p align=\"center\">\n <a href=\"https://trendshift.io/repositories/12132\" target=\"_blank\"><img src=\"https://trendshift.io/api/badge/repositories/12132\" alt=\"DS4SD%2Fdocling | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"/></a>\n</p>\n\n[](https://arxiv.org/abs/2408.09869)\n[](https://ds4sd.github.io/docling/)\n[](https://pypi.org/project/docling/)\n[](https://pypi.org/project/docling/)\n[](https://python-poetry.org/)\n[](https://github.com/psf/black)\n[](https://pycqa.github.io/isort/)\n[](https://pydantic.dev)\n[](https://github.com/pre-commit/pre-commit)\n[](https://opensource.org/licenses/MIT)\n[](https://pepy.tech/projects/docling)\n\nDocling parses documents and exports them to the desired format with ease and speed.\n\n## Features\n\n* \ud83d\uddc2\ufe0f Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to HTML, Markdown and JSON (with embedded and referenced images)\n* \ud83d\udcd1 Advanced PDF document understanding including page layout, reading order & table structures\n* \ud83e\udde9 Unified, expressive [DoclingDocument](https://ds4sd.github.io/docling/concepts/docling_document/) representation format\n* \ud83e\udd16 Easy integration with \ud83e\udd99 LlamaIndex & \ud83e\udd9c\ud83d\udd17 LangChain for powerful RAG / QA applications\n* \ud83d\udd0d OCR support for scanned PDFs\n* \ud83d\udcbb Simple and convenient CLI\n\nExplore the [documentation](https://ds4sd.github.io/docling/) to discover plenty examples and unlock the full power of Docling!\n\n### Coming soon\n\n* \u267e\ufe0f Equation & code extraction\n* \ud83d\udcdd Metadata extraction, including title, authors, references & language\n* \ud83e\udd9c\ud83d\udd17 Native LangChain extension\n\n## Installation\n\nTo use Docling, simply install `docling` from your package manager, e.g. pip:\n```bash\npip install docling\n```\n\nWorks on macOS, Linux and Windows environments. Both x86_64 and arm64 architectures.\n\nMore [detailed installation instructions](https://ds4sd.github.io/docling/installation/) are available in the docs.\n\n## Getting started\n\nTo convert individual documents, use `convert()`, for example:\n\n```python\nfrom docling.document_converter import DocumentConverter\n\nsource = \"https://arxiv.org/pdf/2408.09869\" # document per local path or URL\nconverter = DocumentConverter()\nresult = converter.convert(source)\nprint(result.document.export_to_markdown()) # output: \"## Docling Technical Report[...]\"\n```\n\nMore [advanced usage options](https://ds4sd.github.io/docling/usage/) are available in\nthe docs.\n\n## Documentation\n\nCheck out Docling's [documentation](https://ds4sd.github.io/docling/), for details on\ninstallation, usage, concepts, recipes, extensions, and more.\n\n## Examples\n\nGo hands-on with our [examples](https://ds4sd.github.io/docling/examples/),\ndemonstrating how to address different application use cases with Docling.\n\n## Integrations\n\nTo further accelerate your AI application development, check out Docling's native\n[integrations](https://ds4sd.github.io/docling/integrations/) with popular frameworks\nand tools.\n\n## Get help and support\n\nPlease feel free to connect with us using the [discussion section](https://github.com/DS4SD/docling/discussions).\n\n## Technical report\n\nFor more details on Docling's inner workings, check out the [Docling Technical Report](https://arxiv.org/abs/2408.09869).\n\n## Contributing\n\nPlease read [Contributing to Docling](https://github.com/DS4SD/docling/blob/main/CONTRIBUTING.md) for details.\n\n## References\n\nIf you use Docling in your projects, please consider citing the following:\n\n```bib\n@techreport{Docling,\n author = {Deep Search Team},\n month = {8},\n title = {Docling Technical Report},\n url = {https://arxiv.org/abs/2408.09869},\n eprint = {2408.09869},\n doi = {10.48550/arXiv.2408.09869},\n version = {1.0.0},\n year = {2024}\n}\n```\n\n## License\n\nThe Docling codebase is under MIT license.\nFor individual model usage, please refer to the model licenses found in the original packages.\n\n## IBM \u2764\ufe0f Open Source AI\n\nDocling has been brought to you by IBM.\n",
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