R2R – Open-source framework for production-grade RAG
Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade RAG systems. Just a quick reminder: RAG helps Large Language Models (LLMs) use current information and specific knowledge. For example, it allows a programming assistant to use your latest documents to answer questions. The idea is to gather all the relevant information…
R2R – Open-source framework for production-grade RAG launched on February 26, 2024 with 167 votes, #278 of 3,962 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 2 years on.
In plain words
R2R is an open-source framework for building and deploying production-grade Retrieval-Augmented Generation (RAG) systems. It simplifies RAG development by addressing common deployment challenges that typically require complex abstractions. The framework enables large language models to answer questions using current documents and specific knowledge bases, making it suitable for developers building applications like intelligent programming assistants that need access to up-to-date information.
written from the facts on this page · September 2026
From the sources
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API. - SciPhi-AI/R2R
In the maker’s words, at launch
Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade…
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