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Welcome to RAGHub, a living collection of new and emerging frameworks, projects, and resources in the Retrieval-Augmented Generation (RAG) ecosystem. This is a community-driven project for r/RAG, where we aim to catalog the rapid growth of RAG tools and projects that are pushing the boundaries of the field.
Each day, it feels like a new tool or framework emerges, and choosing the right one is becoming more of an art than a science. Is the framework from three months ago still relevant? Or was it just hype, rehashing old concepts with a fresh look? RAGHub exists to help you stay ahead of these changes, providing a platform for the latest innovations in RAG.
If you're looking for proven, mainstream RAG frameworks and techniques, check out the excellent repository by Nir Diamant: RAG Techniques. This repository focuses on more established tools and methods that have already gained traction in the community.
This is a community project, and we welcome contributions from everyone! If you’d like to add a new framework, project, or resource, please check out our Contribution Guidelines for details on how to get started.
