GH Repository · SciPhi-AI
R2R
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
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Pythonpythonretrieval-systemsquestion-answeringsearchretrieval-augmented-generationraglarge-language-modelsartificial-intelligence
R2R is a retrieval-augmented generation (RAG) system described as SoTA and production-ready, built with agentic RAG capabilities and exposed through a RESTful API. It is written in Python and licensed under MIT.
You want a ready-to-deploy RAG backend with a RESTful API rather than building retrieval pipelines yourself.
Use it to
- Deploy a production RAG service behind a REST API
- Answer questions over your documents with agentic retrieval
- Integrate retrieval-augmented search into applications
- Build a question-answering system on your own data
For Developers building AI applications that need retrieval
- Role
- rag
- Language
- Python
- Licence
- MIT
- Forks
- 647
- Open issues
- 111
- Last push
- 2025-11-07
- Latest release
- v0.0.01 · 2024-02-21
topicsragretrieval-augmented-generationlarge-language-modelssearchquestion-answeringpython