Evaluation and observabilityOpen sourceUpdated 2026
Ragas
Intermediate · Evaluation framework
Open-source framework for evaluating RAG pipelines and LLM application quality.
Best for
RAG builders who need repeatable retrieval and answer-quality checks.
Why use it
Useful when subjective prompt testing is no longer enough.
Tradeoffs
Evaluation metrics need calibration against your business and source material.
Key features
- RAG evaluation
- Dataset-based checks
- Quality metrics
Alternatives
DeepEval, Phoenix, Langfuse
Where it fits
Ragas belongs in the evaluation and observability layer of an open AI stack. Evaluate it against your model runtime, privacy needs, deployment target, and the amount of operational complexity your team can support.
CategoryEvaluation and observabilityLicenseApache 2.0DeploymentEvaluation frameworkModeCode framework
Ragas GitHub →Recommendation
Use Ragas when your RAG stack needs repeatable evaluation.