Great Resources for Learning and Implementing Retrieval-Augmented Generation (RAG)
In this post, we will explore several excellent resources for understanding Retrieval-Augmented Generation (RAG). The post is structured as a step-by-step learning journey. This is intended to be a regularly updated list.
101 - Basic introductions
a) Microsoft’s Generative AI for Beginners RAG chapter
b) AWS short article What is RAG
c) NVidia’s introduction blog
201 - Depth over introductions
a) NVidia’s Technical Brief
b) NVidia’s Building RAG Agents with LLMs
c) Google’s Cloud Skills Boost course
d) LLamaIndex Understanding RAG
301 - In depth explorations
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Blogs
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OpenRAG paper
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Output Evaluation paper
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Data to SQL paper
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ReACT paper
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ReWoo paper
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Tree retrievals
- Raptor Tree retrieval paper
- RAGFlow github repo
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Knowledge graphs
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KG Retriever paper
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GraphRAG Survey paper
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Microsoft GraphRag
- Intro - blog
- Github repo
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Fast GraphRAG github repo
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LightRAG github repo
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NanoGraph github repo
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GraphDB backends
- Neo4j NaLLM github repo
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HippoRAG (graph + pagerank)
- HippoRAG github repo
- HippoRAG paper
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Interleaving Retrieval with Chain-of-Thought Reasoning
- IRCoT github repo
- IRCoT paper
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Memory based RAG
- Paper at arxiv
- MemoRAG github repo
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File document processing
- WDoc github repo
- Paperless-NGX docs
- Docling github repo
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ReRank
- FlashRank github repo
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Code Search
- Sourcegraph website
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Frameworks: UI/API
- RAG to Riches
- R2R github repo
- R2R Docs website
- Doc Chat with UI
- Kotaemon github repo
- Timescale PostGreSQL AI github repo
- RAG to Riches
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Collections
- Retrieval LM Papers github repo
- Awesome RAG github repo