使用 DeepEval 对 LLM 应用和代理进行回归测试，包含指标、追踪和评估套件
Run repeatable eval suites against prompts, RAG pipelines, and agents so regressions surface before release.
Prerequisites
Python or Node.js, API access to an LLM judge or compatible local models, CI optional
Installation
Use the upstream install or setup path that matches your environment:
- pip install -U deepeval
Requirements and caveats from upstream:
- Deepeval works with Python>=3.9+.
- python
Basic usage or getting-started notes:
- <a href="#-quickstart">Getting Started</a> |
- DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating large-language model systems. It is similar to Pytest but specialized for unit testing LLM apps. DeepEval incorporates the latest r...
- 📐 Large variety of ready-to-use LLM eval metrics (all with explanations) powered by ANY LLM of your choice, statistical methods, or NLP models that run locally on your machine covering all use cases:
- Source: https://github.com/1991513ccie-png/skills
- Extracted from upstream docs: https://raw.githubusercontent.com/confident-ai/deepeval/HEAD/README.md
Documentation
- https://docs.confident-ai.com/docs/getting-started
