ragas logo

ragas

vibrantlabsai/ragas

Supercharge Your LLM Application Evaluations 🚀

GraphCanon updated today · GitHub synced today · 34 views this month

15k stars1.6k forksLast push 5mo Python Apache-2.0

Decision brief

Ragas is a Python-based tool designed to enhance the evaluation process of Large Language Model (LLM) applications through specialized workflows and performance insights.

Good fit when

  • When you need advanced tools tailored for evaluating LLM applications, as RAGAS offers specific optimizations not found in generic testing frameworks.
  • If your project requires deep performance insights into AI-driven systems to ensure accuracy and reliability.

Avoid when

  • If your application does not involve Large Language Models or if the evaluation needs are basic; RAGAS is optimized for LLM-specific evaluations which may be overkill for simpler systems.
  • For projects that require real-time monitoring or continuous testing of live models where more dynamic observability tools might offer better support.
Requirements:
Min 4 GB RAM

Observed Jul 11, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Slowing (176d since push)
As of today
Provenance
Not a fork · Organization account
As of today
Security (OSV)
No lockfile
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install ragas
PyPI

How it fits your stack(10)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Provides tools for evaluating Large Language Model applications, likely optimizing evaluation workflows and providing insights into the performance of AI-driven systems.

Capability facts

CLI
CLI entrypoint

Source: pyproject.toml:[project.scripts] · Aug 20, 2026

Languages
python

Source: github.language+pyproject.toml · Aug 20, 2026

Categories

Graph entities

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Aug 20, 2026)

pip install ragas
Source link

Tags

README

:shield: Installation

Pypi:

pip install ragas

Alternatively, from source:

pip install git+https://github.com/vibrantlabsai/ragas

For agents

This page has a .md twin and JSON over the API.

Was this helpful?

Anonymous feedback helps us improve pages and translations.