Benchmark Your Way to Better RAG and Agents:Tuning Vector Search with MLflow
Summary
Tuning vector search for RAG and AI agents requires isolating one configuration knob at a time against a fixed evaluation set rather than relying on default settings. Using MLflow retriever evaluation to track metrics like precision@k and nDCG@k lets teams systematically measure and compare the impact of embedding models, chunk sizes, and rerankers side by side.
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