Andrew-Jang/RAGHub
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
This is a living directory of tools, frameworks, and resources for Retrieval-Augmented Generation (RAG). It helps you navigate the rapidly changing landscape of RAG by providing a curated list of new and emerging solutions. You'll find frameworks for building RAG applications, evaluation tools, and data preparation frameworks. Developers and AI engineers who are building or evaluating RAG systems would use this to stay informed and choose appropriate tools.
1,590 stars.
Use this if you are an AI engineer or developer looking for up-to-date information on RAG frameworks, projects, and resources to build or enhance your LLM applications.
Not ideal if you are looking for a pre-built, ready-to-deploy RAG solution without needing to engage with underlying frameworks or development details.
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Jan 15, 2026
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