infiniflow/ragflow
RAGFlow is an agent-native database: a Retrieval-Augmented Generation (RAG) engine that grew into context infrastructure.
What it is
💡 What is RAGFlow? 🎮 Get Started 🔥 Latest Updates 🌟 Key Features 🔎 System Architecture 🏠 Local Deployment 📚 Documentation 📜 Roadmap 🏄 Community 🙌 Contributing RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged context engine and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.
When to use it
Reach for ragflow when you need semantic search, embeddings, scraping or turning documents into LLM-ready data — it's written in Go and fits stacks tagged agent-harness, agent-native-database, agentic-ai, agentic-retrieval.
