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GenAI

Production RAG with Hybrid Search

Combine dense vector search with BM25 keyword search. Add query rewriting, hypothetical document embedding (HyDE), streaming response, and a full eval suite.

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Project Overview

Combine dense vector search with BM25 keyword search. Add query rewriting, hypothetical document embedding (HyDE), streaming response, and a full eval suite.

You will learn to:

  • Combine dense vector search and BM25 keyword search using Reciprocal Rank Fusion
  • Implement query rewriting to improve retrieval quality for ambiguous queries
  • Apply HyDE (Hypothetical Document Embedding) to boost semantic search precision
  • Build a streaming FastAPI + Streamlit layer on top of a production RAG system
  • Build a streaming FastAPI + Streamlit layer on top of a production RAG system

Technologies You'll Use

pythonjavajavascriptcss

What's Included

  • Detailed Project Requirements
  • Implementation Milestones
  • Submission Checklist
  • Review Guidance
  • Certificate of Completion