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Agent Evaluation

Testing community

Description

A generative AI-powered framework for testing virtual agents.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

![PyPI - Version](https://img.shields.io/pypi/v/agent-evaluation) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/agent-evaluation) ![GitHub License](https://img.shields.io/github/license/awslabs/agent-evaluation) [![security: bandit](https://img.shields.io/badge/security-bandit-yellow.svg)](https://github.com/PyCQA/bandit) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![Built with Material for MkDocs](https://img.shields.io/badge/Material_for_MkDocs-526CFE?style=for-the-badge&logo=MaterialForMkDocs&logoColor=white)](https://squidfunk.github.io/mkdocs-material/)

Agent Evaluation

Agent Evaluation is a generative AI-powered framework for testing virtual agents.

Internally, Agent Evaluation implements an LLM agent (evaluator) that will orchestrate conversations with your own agent (target) and evaluate the responses during the conversation.

✨ Key features

  • Built-in support for popular AWS services including Amazon Bedrock, Amazon Q Business, and Amazon SageMaker. You can also bring your own agent to test using Agent Evaluation.
  • Orchestrate concurrent, multi-turn conversations with your agent while evaluating its responses.
  • Define hooks to perform additional tasks such as integration testing.
  • Can be incorporated into CI/CD pipelines to expedite the time to delivery while maintaining the stability of agents in production environments.

📚 Documentation

To get started, please visit the full documentation [here](https://awslabs.github.io/agent-evaluation/). To contribute, please refer to [CONTRIBUTING.md](./CONTRIBUTING.md)

👏 Contributors

Shout out to these awesome contributors: