What It Does
Ragas provides automated evaluation metrics for retrieval-augmented generation (RAG) systems. It measures both the retrieval quality and generation quality of RAG pipelines, enabling systematic improvement without expensive human evaluation.
Key Features
Ragas offers faithfulness scoring (hallucination detection), answer relevancy measurement, context precision and recall, automated test dataset generation, integration with LangChain and LlamaIndex, custom metric definition, and comprehensive evaluation reports.
When To Use It
Use Ragas when building RAG systems that need quality measurement, during development for iterating on retrieval and generation, for regression testing in CI/CD pipelines, or when you need to compare different RAG configurations systematically.
Alternatives
DeepEval provides broader LLM evaluation beyond RAG. TruLens offers evaluation with explainability. Phoenix provides observability-focused evaluation. For custom evaluation needs, direct LLM-as-judge approaches may provide more flexibility.