LLM Evaluation & Benchmarking: Metrics, Frameworks & Production Testing

RAG systems integrate retrieval and generation, requiring evaluation across both components and the entire pipeline. The process involves analyzing the flow from query to answer through retrieval, reranking, and generation. Key evaluation layers include retrieval quality using precision@k and MRR, generation quality focusing on faithfulness and hallucinations, and end-to-end answer correctness. This comprehensive approach ensures production observability by utilizing offline benchmarks and real-time monitoring to maintain high performance and accuracy in RAG deployments.