GH Repository · infiniflow
ragflow
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
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pythonharness-engineeringaidockerai-agentsllm-appsagentic-aipython/uvagentic-retrievalcontext-engineeringGocontext-managementretrieval-augmented-generationagentic-searchgoragknowledge-compilationagent-appcontext-engineagent-harness
RAGFlow is an open-source Retrieval-Augmented Generation engine that combines RAG pipelines with agent capabilities to serve as a context layer for LLMs. It is written in Go and Python, ships with Docker tooling, and includes AGENTS.md and CLAUDE.md files for agent integration.
You want a self-hostable RAG engine that also exposes agentic retrieval and context management rather than only document search.
Use it to
- Build retrieval-augmented LLM applications
- Run a self-hosted RAG engine via Docker
- Add agentic search and retrieval to agent workflows
- Manage context fed to LLM apps
- Integrate with coding agents via AGENTS.md and CLAUDE.md
For Developers building RAG pipelines and agentic LLM applications
- Role
- agent-app
- Language
- Go
- Licence
- Apache-2.0
- Forks
- 10,741
- Open issues
- 1,167
- Last push
- 2026-09-15
- Latest release
- v0.1.0 · 2024-04-15
topicsragretrieval-augmented-generationllm-appsai-agentscontext-engineagentic-search