# infiniflow/ragflow

> RAGFlow is an agent-native database: a Retrieval-Augmented Generation (RAG) engine that grew into context infrastructure.

- GitHub: https://github.com/infiniflow/ragflow
- Website: https://ragflow.io
- Category: RAG, Search & Data (https://ideas.asveas.com/c/rag)
- Tags: agent-harness, agent-native-database, agentic-ai, agentic-retrieval, agentic-search, ai, ai-agents, context-engine, context-engineering, context-management, harness-engineering, knowledge-compilation, rag, retrieval-harness
- Language: Go · License: Apache-2.0
- Stars: 94,036 · Forks: 11,305 · Open issues: 1,270
- Last push: 2026-11-11 (today)
- Vibe score: 95/100

## 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.

## Maintenance
infiniflow/ragflow looks very actively maintained: the last push was today (2026-11-11), with 94,036 stars and 1,270 open issues.

## Quick start
```bash
git clone https://github.com/infiniflow/ragflow.git
```

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Source: https://ideas.asveas.com/r/infiniflow/ragflow · Catalog: https://ideas.asveas.com/llms.txt