| Name | ai-test-agent JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | AI-powered test automation agent |
| upload_time | 2025-10-20 23:33:33 |
| maintainer | None |
| docs_url | None |
| author | Your Name |
| requires_python | <4.0,>=3.12 |
| license | None |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 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.
```bash
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:
```bash
pip install ai-test-agent
```
### Option 2: Using Poetry (development)
```bash
git clone https://github.com/yourusername/ai-test-agent.git
cd ai-test-agent
poetry install
```
## Using Docker
```bash
docker build -t ai-test-agent .
docker run -it ai-test-agent
```
## Quickstart Workflow
1. **Initialize your project**
From inside the project directory you want the agent to manage:
```bash
ai-test-agent init
```
This creates `.aitestagent/config.json` with sensible defaults (paths, thresholds, model names).
Rerun `init` at any time to regenerate or adjust the manifest.
2. **Analyze the codebase**
When inside an initialized project, you no longer need to repeat `--project-path`:
```bash
ai-test-agent analyze
```
Results are written to the configured analysis output path (defaults to `analysis.json`).
3. **Generate tests**
```bash
ai-test-agent generate
```
Tests are written to the configured tests directory (defaults to `tests/`).
4. **Execute tests**
```bash
ai-test-agent run
```
Test results and coverage thresholds respect the manifest configuration.
5. **Produce a report**
```bash
ai-test-agent report
```
6. **Run everything end-to-end**
```bash
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.:
```bash
ai-test-agent analyze --project-path /path/to/project
```
For a detailed option reference, see [`docs/CLI_REFERENCE.md`](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
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"description": "# AI Test Agent\n\nAn AI-powered test automation agent that analyzes code, generates tests, and produces detailed reports.\n\n## Features\n\n- **Project Analysis**: Analyzes project structure and identifies components for testing\n- **Test Generation**: Generates comprehensive tests for various programming languages\n- **Test Execution**: Runs tests and collects results\n- **Reporting**: Produces detailed test reports in multiple formats\n- **Coverage Analysis**: Generates code coverage reports\n- **CLI Interface**: Command-line interface for easy integration\n- **Docker Support**: Containerized for easy deployment\n\n## Supported Languages\n\n- Python\n- JavaScript/TypeScript\n- Java\n\n## Installation\n\n### Option 1: Pip / Pipx (recommended)\n\nInstall the CLI globally so it is available from any project directory.\n\n```bash\npipx install ai-test-agent\n# or, if you are working from a checked-out repo\npipx install .\n```\n\nYou can also install into an existing virtual environment:\n\n```bash\npip install ai-test-agent\n```\n\n### Option 2: Using Poetry (development)\n\n```bash\ngit clone https://github.com/yourusername/ai-test-agent.git\ncd ai-test-agent\npoetry install\n```\n\n## Using Docker\n```bash\ndocker build -t ai-test-agent .\ndocker run -it ai-test-agent\n```\n\n## Quickstart Workflow\n\n1. **Initialize your project** \n From inside the project directory you want the agent to manage:\n ```bash\n ai-test-agent init\n ```\n This creates `.aitestagent/config.json` with sensible defaults (paths, thresholds, model names). \n Rerun `init` at any time to regenerate or adjust the manifest.\n\n2. **Analyze the codebase** \n When inside an initialized project, you no longer need to repeat `--project-path`:\n ```bash\n ai-test-agent analyze\n ```\n Results are written to the configured analysis output path (defaults to `analysis.json`).\n\n3. **Generate tests**\n ```bash\n ai-test-agent generate\n ```\n Tests are written to the configured tests directory (defaults to `tests/`).\n\n4. **Execute tests**\n ```bash\n ai-test-agent run\n ```\n Test results and coverage thresholds respect the manifest configuration.\n\n5. **Produce a report**\n ```bash\n ai-test-agent report\n ```\n\n6. **Run everything end-to-end**\n ```bash\n ai-test-agent all\n ```\n\nIf 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.\n\n## Commands At a Glance\n\n| Command | Description |\n| ------- | ----------- |\n| `ai-test-agent init` | Create `.aitestagent/config.json` in the current project. |\n| `ai-test-agent analyze` | Parse the project and write the structural analysis. |\n| `ai-test-agent generate` | Generate tests into the configured output directory. |\n| `ai-test-agent run` | Execute tests, collect results, and enforce coverage thresholds. |\n| `ai-test-agent report` | Build an HTML report from stored results. |\n| `ai-test-agent all` | Run analyze \u2192 generate \u2192 run \u2192 report in one go. |\n| `ai-test-agent debug` | Attempt iterative fixes when tests fail. |\n| `ai-test-agent interactive` | (Placeholder) Future interactive workflow. |\n\nFrom outside an initialized project, you can still supply paths explicitly, e.g.:\n```bash\nai-test-agent analyze --project-path /path/to/project\n```\n\nFor a detailed option reference, see [`docs/CLI_REFERENCE.md`](docs/CLI_REFERENCE.md).\n\n## Project Manifest\n\nThe manifest created by `init` lives at `.aitestagent/config.json` and stores relative paths\nand defaults for:\n\n- project root\n- tests/analysis/results/report output paths\n- coverage thresholds\n- default LLM model\n\nFeel free to edit this file directly or rerun `ai-test-agent init` to regenerate it. \nAll commands look for the manifest in the current directory or any parent directory.\n\n## Configuration\n\nAdditional runtime settings can be provided via environment variables (particularly for LLM access):\n\n - **OLLAMA_HOST**: Host for Ollama service\n - **OLLAMA_PORT**: Port for Ollama service\n - **DEFAULT_MODEL**: Default LLM model to use\n\nThe CLI will also create `.aitestagent/.env.example` during `init` for convenience.\n\n### Contributing\n - Fork the repository\n - Create a feature branch\n - Make your changes\n - Add tests\n - Submit a pull request\n\n",
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