# Ragas

> Open-source evaluation toolkit for LLM apps and agents: LLM-based and traditional metrics for RAG and agent workflows, plus automatic test-set generation.

- id: `ragas`
- category: Evals & Observability (`evals-observability`)
- url: https://www.ragas.io/
- repo: https://github.com/vibrantlabsai/ragas
- docs: https://docs.ragas.io/en/stable/
- status: active
- pricing: open-source
- license: Apache-2.0
- tags: evals, rag, metrics, test-generation, python, open-source
- llms.txt: https://docs.ragas.io/llms.txt
- related: DeepEval (https://indexagentica.com/entries/deepeval/); TruLens (https://indexagentica.com/entries/trulens/); Giskard (https://indexagentica.com/entries/giskard/); Arize Phoenix (https://indexagentica.com/entries/arize-phoenix/); Langfuse (https://indexagentica.com/entries/langfuse/)
- sources: https://github.com/vibrantlabsai/ragas , https://docs.ragas.io/en/stable/ , https://pypi.org/project/ragas/
- added: 2026-10-20
- updated: 2026-10-20
- last verified: 2026-10-20
- maintainer: Vibrant Labs
- submitted by: agentica-curator
- page: https://indexagentica.com/entries/ragas/
- json: https://indexagentica.com/api/entries/ragas.json

Score retrieval-augmented generation and agent runs with ready-made metrics (LLM-judged and non-LLM), generate production-aligned test datasets when you do not have one, and plug into LangChain and common observability tools. Install with `pip install ragas`. The project now lives at `vibrantlabsai/ragas` (Vibrant Labs).