221 deepeval(1) - Kailash Tool Reference
221.1 deepeval
deepeval - DeepEval — LLM evaluation framework with unit-test-style metrics (G-Eval, faithfulness, bias).
| Layer | DEFENCE |
| Category | d-03-assurance-evals-benchmarks |
| Safety class | safe |
| Licence | Apache-2.0 |
| Upstream | github.com/confident-ai/deepeval |
221.1.1 NAME
deepeval - DeepEval — LLM evaluation framework with unit-test-style metrics (G-Eval, faithfulness, bias).
221.1.2 SYNOPSIS & usage
Derived from the upstream README at generation time; verify against --help where the tool is installed.
pip install -U deepevaldeepeval login221.1.3 DESCRIPTION (upstream)
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 research to run evals via metrics such as G-Eval, task completion, answer relevancy, hallucination, etc., which use LLM-as-a-judge and other NLP models that run locally on your machine. Whether you’re building AI agents, RAG pipelines, or chatbots, implemented via LangChain or OpenAI, DeepEval has you covered. With it, you can easily evaluate: - LLM apps end-to-end as black boxes - Complete agent trajectories across every decision and action - **Individual agent steps
221.1.4 SEE ALSO
- Category: d-03-assurance-evals-benchmarks in the category directory (sister tools listed there).
ref: pin - verified 2026-10-14