{"slug": "docling", "title": "Docling", "summary": "IBM released Docling, an open-source document processing tool that parses diverse formats including PDF, DOCX, and images, with integrations for generative AI ecosystems like LangChain and LlamaIndex. The tool supports local execution for sensitive data and offers advanced features such as OCR, visual language models, and audio transcription.", "body_md": "Docling simplifies document processing by parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the generative AI ecosystem.\n\n- 🗂️ Parsing of\n[multiple document formats](https://docling-project.github.io/docling/usage/supported_formats/)including PDF, DOCX, PPTX, XLSX, HTML, EPUB, WAV, MP3, WebVTT, Box Notes, email formats (EML, MSG), images (PNG, TIFF, JPEG, ...), LaTeX, DocLang, plain text, and more - 📑 Advanced PDF understanding incl. page layout, reading order, table structure, code, formulas, image classification, and more\n- 🧬 A unified, expressive\n[DoclingDocument](https://docling-project.github.io/docling/concepts/docling_document/)representation format - ↪️ Various\n[export formats](https://docling-project.github.io/docling/usage/supported_formats/)and options, including Markdown, HTML, WebVTT, DocLang,[DocTags](https://arxiv.org/abs/2503.11576)and lossless JSON - 📜 Support for several application-specific XML schemas including\n[DocLang](https://doclang.ai),[USPTO](https://www.uspto.gov/patents)patents,[JATS](https://jats.nlm.nih.gov/)articles, and[XBRL](https://www.xbrl.org/)financial reports. - 🔒 Local execution capabilities for sensitive data and air-gapped environments\n- 🤖 Plug-and-play\n[integrations](https://docling-project.github.io/docling/integrations/)incl. LangChain, LlamaIndex, Crew AI & Haystack for agentic AI - 🔍 Extensive OCR support for scanned PDFs and images\n- 👓 Support for several Visual Language Models, such as (\n[GraniteDocling](https://huggingface.co/ibm-granite/granite-docling-258M)) - 🎙️ Audio support with Automatic Speech Recognition (ASR) models\n- 🔌 Connect to any agent using the\n[MCP server](https://docling-project.github.io/docling/usage/mcp/) - 🌐 Run Docling as a service with the\n[API server](https://docling-project.github.io/docling/usage/api_server/)(docling-serve) - 💻 Simple and convenient CLI\n\n- 🎬 Parsing of video files (MP4, AVI, MOV, MKV, and WebM) with an ASR transcript and representative keyframes\n- 📄 Parsing of ODF (OpenDocument Format) files for text documents (\n`.odt`\n\n), spreadsheets (`.ods`\n\n), and presentations (`.odp`\n\n) - 💼 Parsing of XBRL (eXtensible Business Reporting Language) documents for financial reports\n- 📧 Parsing of email files (\n`.eml`\n\n,`.msg`\n\n) - 📚 Parsing of EPUB (Electronic Publication) files for e-books\n- 📝 Parsing of plain-text files (\n`.txt`\n\n,`.text`\n\n) and Markdown supersets (`.qmd`\n\n,`.Rmd`\n\n) - 📊 Chart understanding (Barchart, Piechart, LinePlot): convert them into tables or code and add detailed descriptions\n\n- 📝 Metadata extraction, including title, authors, references & language\n- 📝 Complex chemistry understanding (Molecular structures)\n\n```\npip install docling\n```\n\nNote:Python 3.9 support was dropped in docling version 2.70.0. Please use Python 3.10 or higher.\n\nWorks on macOS, Linux and Windows environments for both x86_64 and arm64 architectures.\n\nMore [detailed installation instructions](https://docling-project.github.io/docling/getting_started/installation/) are available in the docs.\n\n```\ndocling https://arxiv.org/pdf/2206.01062\n```\n\nThis generates a .md file in the current directory containing structured document content.\n\nYou can also use 🥚[GraniteDocling](https://huggingface.co/ibm-granite/granite-docling-258M) and other VLMs via Docling CLI:\n\n```\ndocling --pipeline vlm --vlm-model granite_docling https://arxiv.org/pdf/2206.01062\npython\nfrom docling.document_converter import DocumentConverter\n\nsource = \"https://arxiv.org/pdf/2408.09869\"  # a document via a 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](https://docling-project.github.io/docling/usage/) and [configuration](https://docling-project.github.io/docling/getting_started/installation/) options.\n\nCheck out Docling's [documentation](https://docling-project.github.io/docling/) for details on\ninstallation, usage, concepts, recipes, extensions, and more.\n\nGo hands-on with our [examples](https://docling-project.github.io/docling/examples/),\ndemonstrating how to address different application use cases with Docling.\n\nTo further accelerate your AI application development, check out Docling's native\n[integrations](https://docling-project.github.io/docling/integrations/) with popular frameworks\nand tools.\n\nPlease feel free to connect with us using the [discussion section](https://github.com/docling-project/docling/discussions).\n\nFor more details on Docling's inner workings, check out the [Docling Technical Report](https://arxiv.org/abs/2408.09869).\n\nPlease read [Contributing to Docling](https://github.com/docling-project/docling/blob/main/CONTRIBUTING.md) for details.\n\nIf you use Docling in your projects, please consider citing the following:\n\n```\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\nThe Docling codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.\n\nDocling is hosted as a project in the [LF AI & Data Foundation](https://lfaidata.foundation/projects/).\n\nThe project was started by the AI for knowledge team at IBM Research Zurich.", "url": "https://wpnews.pro/news/docling", "canonical_source": "https://github.com/docling-project/docling", "published_at": "2026-07-17 12:48:07+00:00", "updated_at": "2026-07-17 12:51:29.314845+00:00", "lang": "en", "topics": ["developer-tools", "artificial-intelligence", "generative-ai", "ai-tools", "ai-infrastructure"], "entities": ["IBM", "Docling", "LangChain", "LlamaIndex", "Crew AI", "Haystack", "GraniteDocling", "Hugging Face"], "alternates": {"html": "https://wpnews.pro/news/docling", "markdown": "https://wpnews.pro/news/docling.md", "text": "https://wpnews.pro/news/docling.txt", "jsonld": "https://wpnews.pro/news/docling.jsonld"}}