Overview
Research summary
DeepEval is a Python framework for testing the behavior of applications built with language models. It provides test cases, configurable scoring metrics, synthetic evaluation datasets, and integrations with development and continuous integration workflows. Evaluations can cover complete applications, individual components, and agent trajectories, including tool calls and retrieval. Developers can combine model judges with other metrics and select their evaluation model. This entry covers the Apache-2.0 library; the separately operated Confident AI platform adds hosted reporting and production workflows.
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 available
The provider offers paid products or services. Free options may also be available.
Commercial offering checked 2026-10-02.
Licence scope
Implementation
Recorded implementation details and interfaces for DeepEval.
Implementation details
Python evaluation library, tracing integrations, and test CLI
- 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 6
- https://deepeval.com Project page · Research reference
- https://github.com/confident-ai/deepeval Linked repository · Research reference
- https://github.com/confident-ai/deepeval/blob/main/README.md Research reference
- https://github.com/confident-ai/deepeval/blob/main/LICENSE.md Research reference
- https://deepeval.com/ Commercial offering evidence
- https://www.confident-ai.com/pricing Commercial offering evidence
Research metadata
- Research date
- 2026-10-02
- Catalogue snapshot
- 2026-10-06
Community & social 3 channels
Communities
- Discorddiscord.gg/3SEyvpgu2fOfficial
- Redditwww.reddit.com/r/deepevalOfficial
Social & updates
- Xx.com/deepevalOfficial
Related tools
Editorially linked entries to explore alongside DeepEval. This is not a ranking.
