HKUDS / RAG-Anything

# 🚀 RAG-Anything: All-in-One RAG Framework
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## 🎉 News
- [X] [2026.06]🎯📢 🎉 LightRAG enables multimodal RAG through native integration of RAG-Anything.
- [X] [2025.10]🎯📢 🚀 We have released the technical report of RAG-Anything. Access it now to explore our latest research findings.
- [X] [2025.08]🎯📢 🔍 RAG-Anything now features **VLM-Enhanced Query** mode! When documents include images, the system seamlessly integrates them into VLM for advanced multimodal analysis, combining visual and textual context for deeper insights.
- [X] [2025.07]🎯📢 RAG-Anything now features a context configuration module, enabling intelligent integration of relevant contextual information to enhance multimodal content processing.
- [X] [2025.07]🎯📢 🚀 RAG-Anything now supports multimodal query capabilities, enabling enhanced RAG with seamless processing of text, images, tables, and equations.
- [X] [2025.07]🎯📢 🎉 RAG-Anything has reached 1k🌟 stars on GitHub! Thank you for your incredible support and valuable contributions to the project.
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## 🌟 System Overview
*Next-Generation Multimodal Intelligence*
Modern documents increasingly contain diverse multimodal content—text, images, tables, equations, charts, and multimedia—that traditional text-focused RAG systems cannot effectively process. **RAG-Anything** addresses this challenge as a comprehensive **All-in-One Multimodal Document Processing RAG system** built on LightRAG.
As a unified solution, RAG-Anything **eliminates the need for multiple specialized tools**. It provides **seamless processing and querying across all content modalities** within a single integrated framework. Unlike conventional RAG approaches that struggle with non-textual elements, our all-in-one system delivers **comprehensive multimodal retrieval capabilities**.
Users can query documents containing **interleaved text**, **visual diagrams**, **structured tables**, and **mathematical formulations** through **one cohesive interface**. This consolidated approach makes RAG-Anything particularly valuable for academic research, technical documentation, financial reports, and enterprise knowledge management where rich, mixed-content documents demand a **unified processing framework**.
### 🎯 Key Features
- **🔄 End-to-End Multimodal Pipeline** - Complete workflow from document ingestion and parsing to intelligent multimodal query answering
- **📄 Universal Document Support** - Seamless processing of PDFs, Office documents, images, and diverse file formats
- **🧠 Specialized Content Analysis** - Dedicated processors for images, tables, mathematical equations, and heterogeneous content types
- **🔗 Multimodal Knowledge Graph** - Automatic entity extraction and cross-modal relationship discovery for enhanced understanding
- **⚡ Adaptive Processing Modes** - Flexible MinerU-based parsing or direct multimodal content injection workflows
- **📋 Direct Content List Insertion** - Bypass document parsing by directly inserting pre-parsed content lists from external sources