hhhuang/CAG
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
This project helps AI application developers quickly generate responses from large language models (LLMs) when working with a defined set of knowledge. It takes a collection of documents (your knowledge base) and an LLM, then outputs generated answers to user questions. AI engineers and researchers working on knowledge-intensive applications will find this useful.
1,471 stars. No commits in the last 6 months.
Use this if you need to build LLM applications that provide fast, reliable answers from a specific body of knowledge that fits within the model's context window.
Not ideal if your application requires referencing an extremely large, dynamic knowledge base that cannot be preloaded into the LLM's context.
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Python
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MIT
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Last pushed
May 26, 2025
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