🔧 Step 4: Testing Framework for the AI Agent System

[arcane-engine[bot]]

This issue is dedicated to setting up a comprehensive testing framework for the AI agent system, ensuring its reliability and robustness.

Bigger Context

A solid testing framework is essential for verifying the functionality and performance of the AI agent system. It supports the project's goal by ensuring that each iteration of the system is reliable and effective in addressing the problem of AI replacing human labor.

Implementation Strategy

1. Unit Testing: Develop unit tests for all components using pytest, covering core functionalities such as iteration execution, self-awareness, and self-improvement logic.
2. Integration Testing: Implement tests that verify the interaction between different components of the system.
3. Continuous Testing: Set up tox for automating tests across different environments, specifically targeting Python 11.

Acceptance Criteria

• All core components of the system are covered by unit tests.
• Integration tests confirm the correct interaction between system components.
• The testing framework is integrated with tox for automated testing across environments.

For more context, refer back to the main ticket: Issue #1

[mlamina]

/pilot We already have tox in place. Make sure there's a Github action which runs tox and makes the results available for PR checks. The action should run on commits to main and on pull request commits

[arcane-engine[bot]]

I've successfully added a GitHub Action to run tox on pull requests and commits to the main branch. The action is configured to run in an Ubuntu environment with Python versions 3.8, 3.9, and 3.10. This setup ensures that tox is executed automatically, and the results are available for PR checks. The configuration is now part of the project in the .github/workflows/tox_test.yml file.

PR: ✨ Add GitHub Action for tox testing in Python 3.8, 3.9, and 3.10

If you require further changes, continue our conversation over there!

📋Task Log