DeepEval
used in
0
stacks
Open-source LLM evaluation framework with pytest-style testing and 50+ research-backed metrics, maintained by Confident AI.
Provides metrics such as faithfulness, answer relevancy, contextual precision/recall, hallucination, bias, and toxicity, most implemented as LLM-as-judge evaluators. Tests are written like pytest unit tests, making it a common fit for CI/CD pipelines, and evaluations run locally in your own environment. Confident AI is the optional cloud platform layered on top, adding test management, observability, and team analytics with free and per-seat paid tiers.
Strengths
- 50+ research-backed metrics covering RAG, agents, and safety dimensions
- Pytest-style API designed for unit testing LLM apps in CI/CD
- Local-first execution; cloud platform is optional
- Includes synthetic test data generation and red-teaming capabilities
Tradeoffs
- LLM-as-judge metrics consume judge-model tokens and can vary between runs
- Documentation and feature set steer users toward the commercial Confident AI platform