mcli-framework 7.7.2

🚀 High-performance CLI framework with Rust extensions, AI chat, and stunning visuals

MCLI

A modern CLI framework with chat capabilities, command management, and extensible architecture.

Features

• 🚀 Modern CLI Framework: Built with Click and Rich for beautiful command-line interfaces
• 💬 AI Chat Integration: Built-in chat capabilities with OpenAI and Anthropic support
• 🔧 Command Management: Dynamic command discovery and registration
• 🎨 Rich UI: Colorful, interactive command-line experience
• 📦 Easy Extension: Simple framework for adding custom commands
• 🛠️ Developer Tools: IPython integration for interactive development
• ⚡ Shell Completion: Full tab completion for bash, zsh, and fish shells

Quick Start

Prerequisites

• Python 3.9 or higher
• UV (recommended) or pip

Installation from PyPI (Recommended)

The easiest way to install mcli is from PyPI:

# Install latest version (includes all features)
pip install mcli-framework

# Or with UV (recommended)
uv pip install mcli-framework

# Optional: GPU support (CUDA required)
pip install "mcli-framework[gpu]"

Note: As of v7.0.0, all features are included by default. GPU support is optional as it requires CUDA.

Self-Update Feature: Once installed from PyPI, you can update mcli to the latest version with:

# Check for updates
mcli self update --check

# Install updates automatically
mcli self update

# Install with confirmation
mcli self update --yes

Installation from Source

For development or if you want to customize mcli:

With UV

# Clone the repository
git clone https://github.com/gwicho38/mcli.git
cd mcli

# Install with UV (recommended)
uv venv
uv pip install -e .

# Or install development dependencies
uv pip install -e ".[dev]"

With pip

# Clone the repository
git clone https://github.com/gwicho38/mcli.git
cd mcli

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install the package
pip install -e .

Usage

# Show available commands
mcli --help

# Start a chat session
mcli chat

# Get version information
mcli version

# Manage the application
mcli self --help

# List available commands
mcli commands

Shell Completion (Optional)

Enable tab completion for faster command discovery:

# Install completion for your shell (auto-detects bash/zsh/fish)
mcli completion install

# Check completion status
mcli completion status

After installation, you'll have full tab completion:

• mcli <TAB> → shows all available commands
• mcli workflow <TAB> → shows workflow subcommands
• mcli workflow politician-trading <TAB> → shows politician-trading options

See SHELL_COMPLETION.md for detailed setup and troubleshooting.

Development Workflow

This project uses UV for fast, reliable Python package management.

Setup Development Environment

# 1. Set up the development environment
make setup

# Or manually with UV
uv venv
uv pip install -e ".[dev]"

# 2. Configure environment variables
cp .env.example .env
# Edit .env with your API keys and configuration

Available Make Commands

# Setup and Installation
make setup                  # Setup UV environment with caching
make install               # Install the package with caching

# Building
make wheel                 # Build Python wheel package
make portable              # Build portable executable
make validate-build        # Validate application for distribution

# Testing
make test                  # Test basic installation and functionality
make test-all              # Run complete test suite (if available)
make validate-build        # Comprehensive build validation

# CI/CD
make ci-trigger-build      # Trigger GitHub Actions build workflow
make ci-trigger-test       # Trigger GitHub Actions test workflow
make ci-watch              # Watch GitHub Actions runs in real-time
make ci-status             # Show GitHub Actions run status

# Maintenance
make clean                 # Clean all build artifacts
make debug                 # Show debug information

Project Structure

mcli/
├── src/mcli/              # Main package source
│   ├── app/               # Application modules
│   │   ├── main.py        # Main CLI entry point
│   │   ├── chat_cmd.py    # Chat command implementation
│   │   └── commands_cmd.py # Command management
│   ├── chat/              # Chat system
│   ├── lib/               # Shared libraries
│   │   ├── api/           # API functionality
│   │   ├── ui/            # UI components
│   │   └── logger/        # Logging utilities
│   └── self/              # Self-management commands
├── tests/                 # Test suite
├── .github/workflows/     # CI/CD workflows
├── pyproject.toml         # Project configuration
├── Makefile              # Build and development commands
└── README.md             # This file

Dependencies

Core Dependencies

• click: Command-line interface creation
• rich: Rich text and beautiful formatting
• requests: HTTP library
• tomli: TOML parser

AI & Chat

• openai: OpenAI API integration
• anthropic: Anthropic API integration

Development Tools

• ipython: Interactive Python shell
• inquirerpy: Interactive command-line prompts

Optional Dependencies

MCLI has been optimized with minimal core dependencies. Install only what you need:

# Chat and AI features
uv pip install -e ".[chat]"

# Video processing
uv pip install -e ".[video]"

# Document processing (PDF, Excel, etc.)
uv pip install -e ".[documents]"

# ML/Trading features
uv pip install -e ".[ml]"

# Database support
uv pip install -e ".[database]"

# Web dashboards
uv pip install -e ".[dashboard]"

# Development tools
uv pip install -e ".[dev]"

# Everything
uv pip install -e ".[all]"

Available extras:

• chat - OpenAI, Anthropic, Ollama support
• async-extras - FastAPI, Redis, advanced async features
• video - OpenCV, image processing
• documents - PDF, Excel processing
• viz - Matplotlib, Plotly visualization
• database - Supabase, SQLAlchemy, PostgreSQL
• ml - PyTorch, MLflow, DVC, trading features
• gpu - CUDA support
• monitoring - Prometheus, Datadog
• streaming - Kafka support
• dashboard - Streamlit dashboards
• web - Flask, FastAPI web frameworks
• dev - Testing, linting, type checking
• all - All optional features

Configuration

MCLI can be configured through environment variables and configuration files.

Environment Setup

1. Copy the environment template:

   cp .env.example .env
   

2. Edit the .env file with your configuration:

   # Required for AI chat functionality
   OPENAI_API_KEY=your-openai-api-key-here
   ANTHROPIC_API_KEY=your-anthropic-api-key-here
   
   # Required for politician trading features
   SUPABASE_URL=https://your-project.supabase.co
   SUPABASE_ANON_KEY=your-supabase-anon-key-here
   SUPABASE_SERVICE_ROLE_KEY=your-supabase-service-role-key-here
   

3. Optional development settings:

   # Enable debug logging
   MCLI_TRACE_LEVEL=1
   MCLI_DEBUG=true
   
   # Performance optimization
   MCLI_AUTO_OPTIMIZE=true
   

See .env.example for a complete list of configuration options.

Creating Custom Commands

MCLI supports dynamic command discovery. Add your commands to the appropriate modules:

import click
from mcli.lib.ui.styling import success

@click.command()
def my_command():
    """My custom command."""
    success("Hello from my custom command!")

CI/CD

The project includes comprehensive CI/CD with GitHub Actions:

• Build Workflow: Multi-platform builds (Ubuntu, macOS)
• Test Workflow: Multi-Python version testing (3.9-3.12)
• Automatic Triggers: Runs on push/PR to main branch
• Manual Triggers: Use make ci-trigger-* commands

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes
4. Run tests: make test
5. Validate build: make validate-build
6. Commit your changes: git commit -am 'Add feature'
7. Push to your fork: git push origin feature-name
8. Create a Pull Request

License

MIT License - see LICENSE for details.

Acknowledgments

• Built with Click for CLI interfaces
• Styled with Rich for beautiful output
• Managed with UV for fast Python packaging