mirror of
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Peter W. J. Staar
96d7c7ec79
* feat: route plain-text and Quarto/R Markdown files to the Markdown backend Signed-off-by: Peter Staar <taa@zurich.ibm.com> * updated the README and index.md Signed-off-by: Peter Staar <taa@zurich.ibm.com> * _mime_from_extension: Added a check for extensions in the intersection of XML_USPTO and MD extension lists (currently just txt). These ambiguous extensions get pass — leaving mime=None — so the full content-probing chain (_detect_html_xhtml → _detect_csv → text/plain fallback) runs instead of prematurely assigning text/markdown. _guess_from_content: Removed the elif InputFormat.MD in formats MD fallback for text/plain content. Unrecognised .txt content now correctly returns None. MD is only returned from explicit mime types (text/markdown, text/x-markdown) which come from unambiguous extensions like .md, .text, .qmd, .rmd. Signed-off-by: Peter Staar <taa@zurich.ibm.com> * ran pre-commit Signed-off-by: Peter Staar <taa@zurich.ibm.com> --------- Signed-off-by: Peter Staar <taa@zurich.ibm.com>
6.4 KiB
Vendored
6.4 KiB
Vendored
Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem.
Getting started
🐣 Ready to kick off your Docling journey? Let's dive right into it!
⬇️ Installation
Quickly install Docling in your environment ▶️ Quickstart
Get a jumpstart on basic Docling usage 🧩 Concepts
Learn Docling fundamentals and get a glimpse under the hood 🧑🏽🍳 Examples
Try out recipes for various use cases, including conversion, RAG, and more 🤖 Integrations
Check out integrations with popular AI tools and frameworks 📖 Reference
See more API details
Quickly install Docling in your environment ▶️ Quickstart
Get a jumpstart on basic Docling usage 🧩 Concepts
Learn Docling fundamentals and get a glimpse under the hood 🧑🏽🍳 Examples
Try out recipes for various use cases, including conversion, RAG, and more 🤖 Integrations
Check out integrations with popular AI tools and frameworks 📖 Reference
See more API details
Features
- 🗂️ Parsing of multiple document formats incl. PDF, DOCX, PPTX, XLSX, HTML, WAV, MP3, WebVTT, images (PNG, TIFF, JPEG, ...), LaTeX, plain text, and more
- 📑 Advanced PDF understanding incl. page layout, reading order, table structure, code, formulas, image classification, and more
- 🧬 Unified, expressive DoclingDocument representation format
- ↪️ Various export formats and options, including Markdown, HTML, WebVTT, DocTags and lossless JSON
- 📜 Support of several application-specifc XML schemas incl. USPTO patents, JATS articles, and XBRL financial reports
- 🔒 Local execution capabilities for sensitive data and air-gapped environments
- 🤖 Plug-and-play integrations incl. LangChain, LlamaIndex, Crew AI & Haystack for agentic AI
- 🔍 Extensive OCR support for scanned PDFs and images
- 👓 Support of several Visual Language Models (GraniteDocling)
- 🎙️ Audio support with Automatic Speech Recognition (ASR) models
- 🔌 Connect to any agent using the MCP server
- 💻 Simple and convenient CLI
What's new
- 📤 Structured [information extraction][extraction] [🧪 beta]
- 📑 New layout model (Heron) by default, for faster PDF parsing
- 🔌 MCP server for agentic applications
- 💼 Parsing of XBRL (eXtensible Business Reporting Language) documents for financial reports
- 💬 Parsing of WebVTT (Web Video Text Tracks) files
- 💬 Parsing of LaTeX files
- 📝 Parsing of plain-text files (
.txt,.text) and Markdown supersets (.qmd,.Rmd)
Coming soon
- 📝 Metadata extraction, including title, authors, references & language
- 📝 Chart understanding (Barchart, Piechart, LinePlot, etc)
- 📝 Complex chemistry understanding (Molecular structures)
What's next
🚀 The journey has just begun! Join us and become a part of the growing Docling community.
- :fontawesome-brands-github: GitHub
- :fontawesome-brands-discord: Discord
- :fontawesome-brands-linkedin: LinkedIn
Live assistant
Do you want to leverage the power of AI and get live support on Docling? Try out the Chat with Dosu functionalities provided by our friends at Dosu.
LF AI & Data
Docling is hosted as a project in the LF AI & Data Foundation.
IBM ❤️ Open Source AI
The project was started by the AI for knowledge team at IBM Research Zurich.