AI-powered test automation agent
Project description
AI Test Agent
An AI-powered test automation agent that analyzes code, generates tests, and produces detailed reports.
Features
- Project Analysis: Analyzes project structure and identifies components for testing
- Test Generation: Generates comprehensive tests for various programming languages
- Test Execution: Runs tests and collects results
- Reporting: Produces detailed test reports in multiple formats
- Coverage Analysis: Generates code coverage reports
- CLI Interface: Command-line interface for easy integration
- Docker Support: Containerized for easy deployment
Supported Languages
- Python
- JavaScript/TypeScript
- Java
Installation
Option 1: Pip / Pipx (recommended)
Install the CLI globally so it is available from any project directory.
pipx install ai-test-agent
# or, if you are working from a checked-out repo
pipx install .
You can also install into an existing virtual environment:
pip install ai-test-agent
Option 2: Using Poetry (development)
git clone https://github.com/yourusername/ai-test-agent.git
cd ai-test-agent
poetry install
Using Docker
docker build -t ai-test-agent .
docker run -it ai-test-agent
Quickstart Workflow
-
Initialize your project
From inside the project directory you want the agent to manage:ai-test-agent initThis creates
.aitestagent/config.jsonwith sensible defaults (paths, thresholds, model names).
Reruninitat any time to regenerate or adjust the manifest. -
Analyze the codebase
When inside an initialized project, you no longer need to repeat--project-path:ai-test-agent analyze
Results are written to the configured analysis output path (defaults to
analysis.json). -
Generate tests
ai-test-agent generateTests are written to the configured tests directory (defaults to
tests/). -
Execute tests
ai-test-agent runTest results and coverage thresholds respect the manifest configuration.
-
Produce a report
ai-test-agent report -
Run everything end-to-end
ai-test-agent all
If you prefer to override any setting ad-hoc (e.g., a different output path), pass the flag and it will override the manifest for that invocation.
Commands At a Glance
| Command | Description |
|---|---|
ai-test-agent init |
Create .aitestagent/config.json in the current project. |
ai-test-agent analyze |
Parse the project and write the structural analysis. |
ai-test-agent generate |
Generate tests into the configured output directory. |
ai-test-agent run |
Execute tests, collect results, and enforce coverage thresholds. |
ai-test-agent report |
Build an HTML report from stored results. |
ai-test-agent all |
Run analyze → generate → run → report in one go. |
ai-test-agent debug |
Attempt iterative fixes when tests fail. |
ai-test-agent interactive |
(Placeholder) Future interactive workflow. |
From outside an initialized project, you can still supply paths explicitly, e.g.:
ai-test-agent analyze --project-path /path/to/project
For a detailed option reference, see docs/CLI_REFERENCE.md.
Project Manifest
The manifest created by init lives at .aitestagent/config.json and stores relative paths
and defaults for:
- project root
- tests/analysis/results/report output paths
- coverage thresholds
- default LLM model
Feel free to edit this file directly or rerun ai-test-agent init to regenerate it.
All commands look for the manifest in the current directory or any parent directory.
Configuration
Additional runtime settings can be provided via environment variables (particularly for LLM access):
- OLLAMA_HOST: Host for Ollama service
- OLLAMA_PORT: Port for Ollama service
- DEFAULT_MODEL: Default LLM model to use
The CLI will also create .aitestagent/.env.example during init for convenience.
Contributing
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests
- Submit a pull request
Project details
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