#python #multi_modal_rag #retrieval_augmented_generation
RAG-Anything is a powerful AI system that helps you search and understand documents containing mixed content like text, images, tables, and math formulas all in one place. It uses smart parsing and analysis to break down complex documents and builds a knowledge graph to connect different types of information. This means you can ask detailed questions about any part of a document—whether text or images—and get clear, accurate answers quickly. It supports many file types like PDFs and Office files, making it ideal for research, technical work, or business reports where you need a unified, easy way to explore rich, multimodal content. This saves you time and effort by avoiding multiple tools and gives you deeper insights from your documents.
https://github.com/HKUDS/RAG-Anything
RAG-Anything is a powerful AI system that helps you search and understand documents containing mixed content like text, images, tables, and math formulas all in one place. It uses smart parsing and analysis to break down complex documents and builds a knowledge graph to connect different types of information. This means you can ask detailed questions about any part of a document—whether text or images—and get clear, accurate answers quickly. It supports many file types like PDFs and Office files, making it ideal for research, technical work, or business reports where you need a unified, easy way to explore rich, multimodal content. This saves you time and effort by avoiding multiple tools and gives you deeper insights from your documents.
https://github.com/HKUDS/RAG-Anything
GitHub
GitHub - HKUDS/RAG-Anything: "RAG-Anything: All-in-One RAG Framework"
"RAG-Anything: All-in-One RAG Framework". Contribute to HKUDS/RAG-Anything development by creating an account on GitHub.