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deepeval

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About deepeval

D

deepeval

DeepEval evaluation workflow for AI agents and LLM applications

DeepEval is an agent skill that adds an end-to-end evaluation loop to AI applications, including AI agents and tool-using workflows. When a coding agent follows the skill, it instruments the app so its runs are recorded, then curates a dataset or reuses an existing one. It writes a pytest evaluation suite that is meant to be committed alongside the code, runs the evals, and iterates on the failures they find. The skill is for teams that want to measure and improve an LLM application with repeatable tests rather than by checking outputs by hand. It assumes Python 3.9 or newer and needs deepeval installed with pip in the target project. Metrics and synthetic dataset generation need model credentials. Confident AI reporting, hosted traces and online evals need you to log in with the deepeval CLI first. The skill is published on skills.sh with its source in the confident-ai/deepeval repository on GitHub.

View deepevalAll AI Skills apps
Price
Free
Made by
confident-ai
Category
AI Skills
Website
github.com/confident-ai/deepeval/deepeval