docs.ragas.ioRAGAS evaluation framework
Without eval data, you can't improve. Here's how I build an eval set from scratch that covers real queries and catches regressions.
Faithfulness, answer relevance, correctness. How to measure whether the LLM is using retrieved context well.
Three of the most used RAG evaluation frameworks. Here's what each one does and when to reach for which.
Hit rate, MRR, recall, NDCG. Which metrics actually tell you something about retrieval quality, and how to interpret them.
Without evaluation, RAG silently rots. Here's why measurement is the difference between a system that stays good and one that degrades invisibly.