Ragas

Purpose-built for evaluating RAG pipelines with metrics like faithfulness, answer relevancy, and context precision. It tells you exactly where your retrieval or generation is failing so you can fix it systematically.

AI ToolFree Tier: Apache 2.0Company: CommunityCategory: Safety & EthicsOpen Source: YesQuick Start: Install with pip install ragas → Prepare your RAG evaluation dataset with questions, answers, and contexts → Run the evaluate function and review metric scores

Ragas

RAG evaluation — faithfulness, precision, recall metrics

Visit Ragas →

Purpose-built for evaluating RAG pipelines with metrics like faithfulness, answer relevancy, and context precision. It tells you exactly where your retrieval or generation is failing so you can fix it systematically.

FREE TIER
Apache 2.0
COMPANY
Community
CATEGORY
Safety & Ethics › Evaluation
OPEN SOURCE
Yes
PRIVACY
RAG-focused
TAGS
evaluationrag

QUICK START

Install with pip install ragas → Prepare your RAG evaluation dataset with questions, answers, and contexts → Run the evaluate function and review metric scores

BEST FOR

  • ▸Developers building and iterating on RAG pipelines needing deep metric analysis.
  • ▸Engineers debugging RAG failures with systematic insights into retrieval/generation.
  • ▸Teams prioritizing open-source tools for robust, detailed RAG performance evaluation.

NOT FOR

  • ✕Users seeking general AI model evaluation beyond RAG-specific performance metrics.
  • ✕Beginners needing simple, high-level feedback for non-RAG language models.
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