Ragas

Toolkit for evaluating LLM applications with objective metrics, test data generation and feedback loops

Observability tool by Ragas

IndexedApache-2.0★ 16,140

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About

Ragas provides LLM-based and traditional metrics for evaluating LLM applications, plus test data generation that builds evaluation datasets covering a range of scenarios. It integrates with LangChain and observability tools, and it supports feedback loops built from production data. It is installed from PyPI as the ragas package.

Use cases: llm-evaluation

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Fact sheet

Category: Evals · open source
Open source: Yesraw.githubusercontent.com
Works with: langchain, llamaindexdocs.ragas.io

Facts read from the vendor's own pages by claude-haiku-5-5 on Oct 24, 2026; a fact is shown only with the page it came from.

Signals

Stars: 16,140
Forks: 1,774
Open issues: 384
Last commit: Feb 24, 2026 (8 months ago)
Last release: Jan 13, 2026 (9 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Packages: pypi ragas
License: Apache-2.0
Repository: github.com/vibrantlabsai/ragas
Website: www.ragas.io
Docs: docs.ragas.io
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: README Website Docs github-graphql

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Cite this page

Ragas. Agent Mart. https://agentmart.dev/observability/ragas (last updated 2026-10-24)