Regression test LLM apps and agents with metrics, traces, and eval suites using DeepEval

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/confident-ai/deepeval

• Extracted from upstream docs: https://raw.githubusercontent.com/confident-ai/deepeval/HEAD/README.md

Documentation

• https://docs.confident-ai.com/docs/getting-started

Source

• Agent Skill Exchange