Docling - Document Processing for Gen AI

Overview

Docling is a powerful Python library developed by IBM Research that simplifies document processing for generative AI applications. With 48,400+ GitHub stars and 159 contributors, Docling excels at parsing diverse document formats—including advanced PDF understanding with layout analysis—and provides seamless integrations with AI frameworks like LangChain, LlamaIndex, and Model Context Protocol (MCP) servers.

Key Features

📄 Multi-Format Document Processing

• 12+ Input Formats: PDF, DOCX, XLSX, PPTX, HTML, Markdown, AsciiDoc, CSV, Images (PNG, JPEG, TIFF), USPTO XML, JATS XML, WebVTT
• Advanced PDF Understanding: Page layout analysis, reading order detection, table structure recognition, code block extraction, mathematical formula parsing, image classification
• Unified Document Representation: All formats parsed into consistent Docling Document structure
• 5+ Export Formats: Markdown, HTML, JSON (lossless), Plain Text, Doctags markup

🤖 AI Ecosystem Integration

• LangChain Official Extension: langchain-docling package with document loaders
• LlamaIndex Integration: Docling Reader + Node Parser for RAG applications
• MCP Server: Model Context Protocol server for agentic applications
• Framework Support: Compatible with Crew AI, Haystack, and other AI frameworks