Building Efficient RAG Systems with Binary Quantization
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A multi-agent legal assistant using binary quantization queries 50 million vectors in under 30ms, processes user input, retrieves context, generates responses, evaluates quality, performs web searches, and synthesizes answers with citations through Streamlit.
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