← RAG Systems — Topic Course
Pro topic
Evaluating RAG Quality
Offline metrics and LLM-as-judge patterns that catch silent failures.
Evaluating RAG Quality
Dimensions
- Retrieval: recall@k, MRR, nDCG
- Faithfulness: is the answer supported by context?
- Relevance: does it address the user question?
- Latency/cost: production constraints
Practical advice
Build a golden set of queries. Track regressions when you change chunking or embeddings.
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