RAGAs

➺ Evaluation Focus:

  • Retrieval accuracy
  • Answer relevance
  • Context utilization
  • Source attribution

    • ➺ Key Metrics:

    Retrieval Metrics
  • Precision@K
  • Recall@K
  • Mean Reciprocal Rank
  • NDCG scores

    • ➺ Answer Quality:

  • Context relevance
  • Answer correctness
  • Faithfulness
  • Completeness 

    • ➺ System Performance:

  • Query latency
  • Resource usage
  • Cache efficiency
  • Throughput rates 

    • ➺ Implementation Example:

    python

    # RAGAS evaluation from ragas import evaluate_rag

    metrics = evaluate_rag(
    questions=test_questions,
    contexts=retrieved_contexts,
    answers=generated_answers,

    metrics=[
    ContextRelevancy(),
    AnswerCorrectness(),
    Faithfulness()
    ]
    )