How do you evaluate a RAG system?

RAG evaluation requires measuring both retrieval quality and generation quality separately and end-to-end. For retrieval, use recall at k, precision at k, and mean reciprocal rank on a labeled query-document evaluation set. For generation, measure faithfulness to retrieved context, answer relevance to the query, and optionally answer correctness against reference answers. Frameworks like RAGAS, TruLens, and DeepEval automate these measurements. Build a domain-specific evaluation set of at least 100 to 500 query-answer pairs from real user traffic for meaningful results.