GitHub - HKUDS/RAG-Anything: "RAG-Anything: All-in-One RAG Framework"
2 days ago
- #ai-framework
- #multimodal-rag
- #document-processing
- RAG-Anything is an All-in-One Multimodal Document Processing RAG system built on LightRAG, designed to handle diverse content like text, images, tables, and equations in modern documents.
- Key features include an End-to-End Multimodal Pipeline, Universal Document Support, Specialized Content Analysis, a Multimodal Knowledge Graph, Adaptive Processing Modes, Direct Content List Insertion, and Hybrid Intelligent Retrieval.
- The system utilizes a multi-stage pipeline with components like MinerU Integration, Adaptive Content Decomposition, and Universal Format Support, along with modality-aware processors for visual content, structured data, and mathematical expressions.
- It offers multiple query methods: Pure Text Queries, VLM Enhanced Queries for automatic image analysis, and Multimodal Queries for enhanced queries with specific content analysis.
- Installation is possible via pip (e.g., 'pip install raganything') with optional dependencies for extended format support, and it supports integration with existing LightRAG instances and direct insertion of pre-parsed content lists.
- RAG-Anything supports multiple parsers (MinerU, Docling, PaddleOCR), various document and content types, and includes practical demos in the examples/ directory, with a technical report released and community milestones like reaching 1k+ GitHub stars.