Observability & evaluation
Ragas
Composable evaluation metrics and synthetic test-data workflows for RAG and LLM applications.
Overview
Research summary
Ragas helps developers evaluate retrieval-augmented generation and other LLM applications using repeatable datasets and metrics. It provides measures for aspects such as retrieval quality, faithfulness and answer relevance, alongside workflows for generating test data and comparing experiments. Teams can adapt evaluators and model backends to their application rather than relying on a single aggregate benchmark.
The Apache-2.0 Python library is now hosted under the Vibrant Labs GitHub organization, replacing the older explodinggradients repository path. Its role is evaluation and experimentation; it is not a vector database, production tracing backend or application guardrail by itself.
Repository summary
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services unknown
Whether the provider offers paid products or services has not been established.
Licence scope
Implementation
Recorded implementation details and interfaces for Ragas.
Implementation details
Python evaluation library with dataset, metric and experiment workflows.
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
Documentation
Recorded references and research provenance for this entry.
Recorded sources 3
- https://www.ragas.io Project page
- https://github.com/vibrantlabsai/ragas Linked repository · Research reference
- https://docs.ragas.io Documentation · Research reference
Research metadata
- Research date
- 2026-10-01
- Catalogue snapshot
- 2026-10-06
Community & social 1 channels
Communities
- Discorddiscord.gg/5djav8GGNZOfficialDiscussion