DocAILab/XRAG

XRAG evaluates core components of RAG systems: indexing, retrieval, and generation. Using standard datasets it compares different module implementations, revealing their strengths and weaknesses.

// KEY FEATURES

• Measures latency and throughput of document indexing in various formats.
• Compares search accuracy (recall, MRR) for vector and hybrid retrievers.
• Evaluates answer generation quality using faithfulness and answer relevance metrics.
• Provides scripts for experiments with LlamaIndex and LLMs (GPT‑4, Claude, Llama).

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