Automate the application of best practices to your git repositories
SLIM CLI is a command-line tool designed to infuse SLIM best practices seamlessly with your development workflow. It fetches and applies structured SLIM best practices directly into your Git repositories. The tool leverages artificial intelligence capabilities to customize and tailor the application of SLIM best practices based on your repository's specifics.
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📺 View demonstration videos and detailed tutorials
- Modern CLI Interface: List, patch, and infuse SLIM best practices into your Git repository workflow using a seamless terminal interface
- Rich Terminal Experience: Colored output with emojis, progress indicators, and interactive commands with dry-run mode support
- Fetches the latest SLIM best practices dynamically from SLIM's registry the moment they change
- Patches and pushes, SLIM best practices to your repository and pushes up to your Git remote (i.e. GitHub) - all automatically
- AI Enabled: 100+ AI models to automatically infuse best practices using AI customization for your repository
- Extensible Architecture: Easy-to-extend best practice system with centralized mapping and YAML configuration
- Features
- Contents
- Quick Start
- Generate Documentation
- Discover and Manage AI Models
- Changelog
- Frequently Asked Questions (FAQ)
- Contributing
- License
- Support
This guide provides a quick way to get started with our project. Please see our docs for a more comprehensive overview.
- Python 3.9+
- Git
- Optional: LiteLLM for enhanced AI model support (automatically installed with slim-cli)
- Optional: API keys for cloud AI models - if using cloud models, set the appropriate environment variable:
# Use the slim models setup command to see provider-specific instructions slim models setup <provider> # Example: slim models setup openai # Example: slim models setup anthropic
- Optional: For local AI models (e.g., Ollama), follow the setup instructions:
slim models setup ollama
As the SLIM CLI is written in Python, you'll need Python 3.9 or later. Usually, you'll want to create a virtual environment in order to isolate the dependencies of SLIM from other Python-using applications. Install into that environment using pip:
pip install slim-cli
This installs the latest SLIM CLI and its dependencies from the Python Package Index. The new console script slim is now ready for use. Confirm by running either:
slim --version
slim --help
To upgrade:
pip install --upgrade slim-cli
Or select a specific version, such as X.Y.Z:
pip install slim-cli==X.Y.Z
The following commands demonstrate the core SLIM CLI functionality. Use slim --help for a complete list of options.
Global Options:
-
--version,-v: Show version and exit -
--dry-run,-d: Preview operations without making changes -
--logging,-l: Set logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)# Using long form slim --logging DEBUG apply --best-practice-ids readme # Using shorthand slim -l DEBUG apply -b readme # Preview changes without executing (dry run) slim -d apply -b readme -r <YOUR_GITHUB_REPO_URL>
SLIM CLI provides convenient shorthand options for commonly used arguments:
-bfor--best-practice-ids- Specify best practice aliases-rfor--repo-urls- Specify repository URLs-dfor--dry-run- Preview changes without applying them-lfor--logging- Set logging level-mfor--commit-message- Custom commit message (apply-deploy and deploy commands)
Examples:
# Using full argument names
slim apply --best-practice-ids readme --repo-urls https://github.com/user/repo
# Using shorthands (equivalent)
slim apply -b readme -r https://github.com/user/repo
# Multiple values with shorthands
slim apply -b readme -b governance-small -r https://github.com/org/repo1 -r https://github.com/org/repo2Available Commands:
-
list - List all available best practices from the SLIM registry
slim list
-
apply - Apply best practices to git repositories
Key Options:
--best-practice-ids,-b: Best practice aliases (required)--repo-urls,-r: Repository URLs (cannot be used with --repo-dir)--repo-dir: Local repository directory [no shorthand]--use-ai: AI model for customization [no shorthand]--output-dir: Output directory (required for docs-website) [no shorthand]
# Basic usage - clone to temp folder and apply README template slim apply --best-practice-ids readme --repo-urls <YOUR_GITHUB_REPO_URL> # Using shorthand for best-practice-ids and repo-urls slim apply -b readme -r <YOUR_GITHUB_REPO_URL> # Apply multiple best practices (repeat -b for each) slim apply -b secrets-github -b secrets-precommit -r <YOUR_GITHUB_REPO_URL> # Apply with AI customization using cloud model slim apply -b readme -r <YOUR_GITHUB_REPO_URL> --use-ai anthropic/claude-3-5-sonnet-20241022 # Apply with local AI model slim apply -b readme -r <YOUR_GITHUB_REPO_URL> --use-ai ollama/llama3.1 # Apply to multiple repositories slim apply -b readme -r https://github.com/org/repo1 -r https://github.com/org/repo2 # Apply using a list of repositories from a file slim apply -b governance-small --repo-urls-file repos.txt # Generate documentation website slim apply -b docs-website -r <YOUR_GITHUB_REPO_URL> --output-dir /path/to/docs-site --use-ai openai/gpt-4o
-
apply-deploy - Apply and deploy best practices in one step (creates branch and pushes to remote)
Key Options:
--best-practice-ids,-b: Best practice aliases (required)--commit-message,-m: Custom commit message--remote: Remote name or URL (defaults to 'origin') [no shorthand]--repo-urls,-r: Repository URLs
# Basic usage slim apply-deploy --best-practice-ids readme --repo-urls <YOUR_GITHUB_REPO_URL> # Using shorthand options slim apply-deploy -b readme -r <YOUR_GITHUB_REPO_URL> # With custom commit message using shorthand slim apply-deploy -b readme -r <YOUR_GITHUB_REPO_URL> -m "Add comprehensive README documentation" # Multiple best practices with shorthand slim apply-deploy -b readme -b governance-small -r <YOUR_GITHUB_REPO_URL>
-
deploy - Deploy previously applied best practices (commit and push)
Key Options:
--best-practice-ids,-b: Best practice aliases (required)--commit-message,-m: Custom commit message--repo-dir: Repository directory [no shorthand]--remote: Remote name (defaults to 'origin') [no shorthand]
# Basic usage slim deploy --best-practice-ids readme --repo-dir /path/to/repo --remote origin --commit-message "Apply SLIM best practices" # Using shorthand options slim deploy -b readme --repo-dir /path/to/repo -m "Apply SLIM best practices" # Deploy multiple best practices with shorthand slim deploy -b readme -b governance-small --repo-dir /path/to/repo
-
models - Discover and configure AI models
# List all available models slim models list # Get model recommendations for specific tasks slim models recommend slim models recommend --task documentation --tier premium # Get setup instructions for a provider slim models setup anthropic slim models setup openai # Validate model configuration slim models validate openai/gpt-4o
SLIM CLI can generate comprehensive Docusaurus documentation sites for your repositories using AI.
# Generate documentation with cloud AI (recommended)
slim apply -b docs-website -r <YOUR_GITHUB_REPO_URL> --output-dir /path/to/docs-site --use-ai openai/gpt-4o
# Generate documentation with local AI
slim apply -b docs-website -r <YOUR_GITHUB_REPO_URL> --output-dir /path/to/docs-site --use-ai ollama/llama3.1- Cloud Models (Recommended):
openai/gpt-4o,anthropic/claude-3-5-sonnet-20241022,openai/gpt-4o-mini - Local Models:
ollama/llama3.1,ollama/gemma3(lower quality, not recommended for production)
Use slim models recommend --task documentation to get personalized recommendations.
The documentation generator creates:
- Overview: Project description and features
- Installation: Setup instructions
- API Reference: Auto-generated from source code
- Development: Workflow and coding standards
- Contributing: Guidelines for contributors
cd /path/to/output
npm install
npm start # View at http://localhost:3000📖 For detailed documentation generation guidance, see the SLIM CLI documentation guide
SLIM CLI supports 100+ AI models through LiteLLM integration. Use the models command to discover, configure, and validate AI models.
# List all available models
slim models list
slim models list --provider anthropic
# Get model recommendations
slim models recommend # Default: documentation, balanced
slim models recommend --task documentation --tier premium
slim models recommend --task code_generation --tier fast
# Get setup instructions for providers
slim models setup anthropic
slim models setup openai
slim models setup ollama
# Validate model configuration
slim models validate openai/gpt-4o- Cloud Premium: OpenAI, Anthropic Claude, Google Gemini
- Cloud Fast: Groq, Together AI, Cohere, Perplexity
- Local/Private: Ollama, VLLM, LM Studio, GPT4All
- Enterprise: Azure OpenAI, AWS Bedrock, Google Vertex AI
Use slim models setup <provider> to see provider-specific instructions. Common examples:
# OpenAI
export OPENAI_API_KEY="sk-..."
# Anthropic Claude
export ANTHROPIC_API_KEY="sk-ant-..."
# Ollama (local models) - no API key needed
ollama serveSee our CHANGELOG.md for a history of our changes.
See our releases page for our key versioned releases.
Questions about our project? Please see our: FAQ
Interested in contributing to our project? Please see our: CONTRIBUTING.md.
For a detailed understanding of the codebase architecture, including component design, data flow, and extension points, see our ARCHITECTURE.md.
Specifically, see our section on architecture and extensions if you'd like to add support for a new best practice from SLIM or a new command.
For guidance on how to interact with our team, please see our code of conduct located at: CODE_OF_CONDUCT.md
For guidance on our governance approach, including decision-making process and our various roles, please see our governance model at: GOVERNANCE.md
If you're working on slim-cli itself, you'll want to run it in editable mode so your changes are immediately reflected.
UV is a fast Python package manager that simplifies dependency management and virtual environment handling. It's our recommended tool for local development.
# Install UV (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone the repo
git clone https://github.com/NASA-AMMOS/slim-cli.git
cd slim-cli
# UV automatically creates and manages the virtual environment
# Install all dependencies and the package in editable mode
uv sync
# Run the CLI locally with UV
uv run slim --help
uv run slim --version
# Run tests
uv run pytest tests/If you prefer the traditional approach:
# Clone the repo
git clone https://github.com/NASA-AMMOS/slim-cli.git
cd slim-cli
# Create and activate a virtual environment
python3 -m venv .venv
source .venv/bin/activate
# Install in editable mode
pip install --editable .
# Run the CLI locally
slim --help
slim --versionUse this method if:
- You're adding new features or fixing bugs in the CLI
- You're contributing to the SLIM project
- You want to test changes before publishing
We use pytest for testing. For detailed information about our testing framework, test structure, and how to run tests, please refer to our TESTING.md document.
# Run all tests
uv run pytest tests/
# Run a specific test file
uv run pytest tests/jpl/slim/test_cli.py
# Run tests with verbose output
uv run pytest -v -s# Install pytest (if not already installed)
pip install pytest
# Run all tests
pytest
# Run tests with verbose output
pytest -v -sTo publish a new version of SLIM CLI to the Python Package Index, typically you'll update the VERSION.txt file; then do:
pip install build wheel twine
python3 -m build .
twine upload dist/*(Note: this can and should eventually be automated with GitHub Actions.)
See our: LICENSE