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AI Agents · Lesson

RAG Evaluation (RAGAS, Recall@K)

Measure faithfulness, answer relevance, context precision, and recall@K to know if changes help.

You Cannot Improve What You Cannot Measure

RAG has many knobs: chunk size, top-K, re-ranker, prompt, model. Without metrics, every change is guesswork.

Key Metrics for RAG

  1. Retrieval: did we fetch the right chunks?
  2. Faithfulness: does the answer stay grounded in the chunks?
  3. Answer relevance: does the answer address the question?
  4. Context precision/recall: ratio of useful chunks fetched

All lessons in this course

  1. Re-ranking with Cross-Encoders
  2. HyDE: Hypothetical Document Embeddings
  3. Multi-Vector Retrieval (ColBERT)
  4. RAG Evaluation (RAGAS, Recall@K)
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