RAG Evaluation: Beyond Simple Accuracy Metrics

Evaluating RAG systems requires a multi-faceted approach. Here's a comprehensive framework. ## Retrieval Metrics - **Hit Rate**: Did we retrieve relevant documents? - **Mean Reciprocal Rank (MRR)**: How high was the first relevant result? - **NDCG@K**: How well-ranked are all relevant results? ## Generation Metrics - **Faithfulness**: Does the answer match the retrieved context? - **Answer Relevance**: Does the answer address the query? - **Context Precision**: How much of the context was actually used? ## End-to-End Metrics - **User Satisfaction**: Implicit feedback (clicks, dwell time) - **Task Completion**: Did the user get what they needed? - **Error Rate**: Hallucinations, incorrect answers ## Production Monitoring In production, track: - Latency (p50, p95, p99) - Retrieval quality degradation - User feedback loops - Cost per query