Awesome-RAG

Why we included this project

Retrieval-augmented generation has a sprawling ecosystem, and anyone new to it faces a wall of frameworks, vector databases, and technique papers. This curated index cuts through that by grouping the field into practical sections: architecture patterns, Python tooling, evaluation metrics, databases, and production considerations. Each entry links out to authoritative tutorials and runnable implementations, so it works both as a way to learn the fundamentals and as a way to compare options before picking a stack. It is a reference map rather than a tool you deploy, which is exactly what makes it useful to consult alongside the projects it points to.