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Usage
Install the Responsible AI Checklist CLI using pip:
pip install rai-checklist-cliNote: PyYAML is a dependency. You may need to install it separately if you encounter issues.
The basic syntax for using the CLI is:
rai-checklist [OPTIONS]To generate a default checklist:
rai-checklist generate-
-h, --help: Show help message and exit -
-w, --overwrite: Overwrite existing output file -
-o, --output PATH: Specify output file path -
-f, --format TEXT: Specify output format (md, yaml, json) -
-l, --checklist PATH: Path to custom checklist file -
--project-type TEXT: Specify project type for validation (default, machine_learning, web_application, etc.) -
--config PATH: Path to the configuration file for validation
The tool supports three output formats:
- Markdown (md)
- YAML
- JSON
Specify the format using the -f or --format option:
rai-checklist generate -f yamlTo create a custom template:
rai-checklist create-templateFollow the prompts to name your template and add sections and items.
To use a custom template:
rai-checklist generate -t your_custom_templateTo validate a checklist against project requirements:
rai-checklist validate path/to/your/checklist.yaml --project-type machine_learningThe tool can be integrated into CI/CD pipelines. An example GitHub Actions workflow is provided in the repository.
The tool can be used within Jupyter notebooks. Import the necessary modules:
from rai_checklist_cli.checklist_generator import generate_checklist
import yamlThen use the generate_checklist function to create checklists programmatically.
The tool uses a configuration file located at ~/.rai_checklist_config.yaml. You can specify custom paths or settings in this file.
If you encounter issues:
- Ensure you have the latest version installed
- Check that all dependencies are correctly installed
- Verify that your custom templates or configuration files are correctly formatted
For more help, please open an issue on the GitHub repository.