couchbase-examples/rag-demo
A RAG demo using LangChain that allows you to chat with your uploaded PDF documents
Implements dual vector search strategies—Couchbase's Hyperscale/Composite Vector Indexes via SQL++ queries and Full Text Search service—each optimized for different filtering patterns. Built on Streamlit with LangChain integration, it includes LLM response caching in Couchbase to eliminate duplicate OpenAI API calls, and provides side-by-side comparison between RAG-augmented and pure LLM answers for the same questions.
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Language
Python
License
MIT
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Last pushed
Mar 03, 2026
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