RAGAS

Ragas evaluates LangChain RAG pipelines end-to-end — pass chain outputs to Ragas metrics for faithfulness, relevance, and groundedness scores.

→ Automated quality metrics for LangChain RAG pipelines, runnable in CI to catch retrieval regressions before they reach production.

Ragas evaluates LlamaIndex pipeline outputs using retrieval and generation quality metrics against the source documents.

→ Automated quality scoring for LlamaIndex RAG — faithfulness, context relevance, and answer correctness measurable in CI.

Ragas uploads evaluation scores directly to Langfuse as trace scores, linking eval results to the specific traces they evaluated.

→ Eval results pinned to the exact traces that generated them — jump from a poor metric score directly to the failing trace.