#120 · Primary category: AI Tool Directories & Curated Lists
RAGHub
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
Project last updated:07/28/26
GitHub Stars
2.0K
Forks
180
Contributors
61
License
MIT
Why we included this project
Keeping track of RAG tooling is a full-time job these days, and RAGHub tries to make it less exhausting. It's a community-run directory maintained by the r/RAG subreddit, grouping frameworks, evaluation tools, engines, leaderboards, and plain-language resources into sections that are easy to scan. That organization helps when you're deciding between a heavy, full-featured stack like LangChain or LlamaIndex and a lighter option like LightRAG for a quick prototype. The README also spells out the real trade-offs, covering use case, scale, complexity, and integration language, so you get a sense of what fits before you start testing. Since it's a living list rather than a library, you'll still have to pull and run the frameworks yourself, but at least you start with a clear map.
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