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LABINTERMEDIATE

Advanced RAG Patterns

Implement reranking and hybrid search to significantly improve RAG retrieval quality with measurable metrics.

60 minutes
ai-infrastructure/rag
Advanced RAG Patterns - Platform Engineering Hands-On Lab Icon

Lab Overview

This hands-on lab teaches you advanced RAG techniques that dramatically improve answer quality.

You'll learn to:

  • Implement reranking with cross-encoder models
  • Compare retrieval quality metrics with and without reranking
  • Build hybrid search combining semantic and keyword matching
  • Optimize retrieval pipelines for precision and latency

These techniques transform basic RAG into production-grade systems.

What You'll Learn

Implement reranking with cross-encoder models to improve retrieval precision

Measure and compare retrieval quality using precision and recall metrics

Build hybrid search combining semantic embeddings with BM25 keyword matching

Optimize RAG pipelines for latency and quality tradeoffs

Prerequisites

rag-api-service

Technologies Covered

ragrerankingcross-encoderhybrid-searchbm25evaluationpython

Part of a Course

This lab is part of the RAG Architectures and Vector Databases course

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