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    EvaluationRAG Techniques

    End-to-End RAG Evaluation

    This tutorial walks through building a complete evaluation pipeline for Retrieval-Augmented Generation (RAG) systems. Rather than relying on a single metric, we combine multiple evaluation dimensions - completeness, factual accuracy, and hallucination detection - into a unified pipeline.

    What you'll learn

    • 1
      How to choose evaluation criteria based on real failure patterns
    • 2
      Building custom LLM-as-a-judge metrics for completeness
    • 3
      Using RAGAS for hallucination detection
    • 4
      Assembling a full end-to-end evaluation pipeline

    About this tutorial

    This hands-on Jupyter notebook is part of RAG Techniques, a free open-source repository by Nir Diamant covering rag techniques with runnable code examples and detailed explanations.

    Free and open-sourceRunnable Jupyter notebookActive community support
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