ai-cli-launcher

AI-CLI (Python Edition)

🌐 English | 中文 | 日本語 | Deutsch

AI-CLI is a cross-platform terminal launcher for managing multiple AI coding assistants. Seamlessly switch between tools like Kiro CLI, Claude Code, Cursor Agent, and more.

✨ Core Features

🌍 Cross-Platform Support

• Windows: Native support + WSL integration ✅ Fully tested
• Linux: Full support for all major distributions ⚠️ Not fully tested - may have issues
• macOS: Support for Terminal.app and iTerm2 ⚠️ Not fully tested - may have issues

🔄 Deep WSL Integration

• Automatic WSL environment detection
• Automatic Windows ↔ WSL path conversion
• Launch WSL tools from Windows
• Launch Windows tools from WSL

📁 Project Management

• Tree Structure: Organize projects in folders
• Git Worktree: Auto-detect and select Git worktrees
• Environment Variables: Configure per-project environment variables
• Path Normalization: Automatic handling of different platform path formats

⚡ Tool Detection & Management

• Async Detection: Parallel tool detection using async/await
• Smart Caching: Background detection with result caching
• One-Click Install: Press I to install missing tools
• Manual Refresh: Press R to refresh tool list
• Environment Recognition: Auto-detect Windows, WSL, Linux, macOS environments

🎨 User Interface

• Rich UI: Beautiful terminal interface powered by Rich library
• Keyboard Navigation: Full keyboard shortcut support
• Real-time Feedback: Display tool detection and installation progress
• Theme Support: Customizable color themes

🌐 Internationalization

• Multi-language: English, Chinese, Japanese, German
• Auto-detection: Automatically select based on system language
• Configurable: Manually specify language in config file

🚀 Quick Start

Installation

Method 1: Install from PyPI (Recommended)

# Using pip
pip install ai-cli-launcher

# Or using pipx (isolated environment)
pipx install ai-cli-launcher

Method 2: One-Line Installation Script

Windows:

irm https://raw.githubusercontent.com/hyfhot/AI-CLI/master/install.ps1 | iex

Linux/macOS:

curl -fsSL https://raw.githubusercontent.com/hyfhot/AI-CLI/master/install.sh | bash

The script will automatically:

• Check Python installation (requires Python 3.8+)
• Install AI-CLI from PyPI
• Initialize configuration
• Create desktop shortcut (Windows)

Method 3: Install from Source (For Developers)

# Clone repository
git clone https://github.com/hyfhot/AI-CLI.git
cd AI-CLI

# Install in development mode
pip install -e ".[dev]"

Initialize Configuration

ai-cli --init

This creates a default configuration file with common AI tool configurations.

Run

ai-cli

Uninstall

Complete Uninstall (Recommended):

Windows (PowerShell):

ai-cli --uninstall; pip uninstall ai-cli-launcher

Linux/macOS:

ai-cli --uninstall && pip uninstall ai-cli-launcher

Alternative (Step by Step):

# Step 1: Clean up shortcuts and show config location
ai-cli --uninstall

# Step 2: Uninstall the package
pip uninstall ai-cli-launcher

Quick Uninstall:

# Uninstall package only (shortcuts will remain)
pip uninstall ai-cli-launcher

Manual Cleanup (if needed):

• Windows: Delete %APPDATA%\AI-CLI\ and desktop shortcut
• Linux: Delete ~/.config/ai-cli/
• macOS: Delete ~/Library/Application Support/ai-cli/

## 📖 Usage

### Command Line Options

```bash
ai-cli                    # Start interactive interface
ai-cli --init             # Initialize configuration file
ai-cli --config           # Edit configuration file
ai-cli --lang zh          # Start with Chinese language
ai-cli --lang ja          # Start with Japanese language
ai-cli --uninstall        # Uninstall AI-CLI
ai-cli --version          # Show version information
ai-cli --help             # Show help information
ai-cli --update           # Upgrade AI-CLI to the latest version

# Direct launch mode (skip project and tool selection UI)
ai-cli -t kiro-cli                          # Launch kiro-cli in current directory
ai-cli -t claude -p "My Project"            # Launch claude in a configured project
ai-cli -t codewhale -d /path/to/project      # Launch codewhale in a specific directory
ai-cli -t kiro-cli --platform wsl           # Launch in WSL environment

Direct Launch Options:

When --tool is provided, AI-CLI skips the interactive UI, runs the tool directly in the current terminal, and exits when the tool exits. Project-specific environment variables are injected if a matching project is found.

Language Options (--lang / -l):

• auto - Auto-detect system language (default)
• en - English
• zh - Chinese (中文)
• ja - Japanese (日本語)
• de - German (Deutsch)

Note: CLI language parameter takes priority over config file settings.

Keyboard Shortcuts

Project Selection Screen

Tool Selection Screen

Workflow

Interactive Mode

1. Launch: Run ai-cli
2. Select Project: Use arrow keys to select a project, press Enter to confirm
3. Select Tool: Choose the AI tool you want to use
4. Start Working: Tool launches in a new window or tab

Direct Launch Mode

Pass --tool to skip the interactive UI and run a tool directly in the current terminal:

# Simplest: launch kiro-cli in the current directory
ai-cli -t kiro-cli

# Launch in a configured project (auto-injects project env vars)
ai-cli -t claude -p "My API Project"

# Launch in a specific directory
ai-cli -t codewhale -d ~/code/myproject

Direct launch mode will:

1. Resolve the project configuration, injecting matching environment variables
2. Run the AI tool in the current terminal window (foreground, not a new window)
3. Exit when the tool exits

Current Directory Awareness

When you launch ai-cli from a terminal:

• If the current directory matches a configured project, that project is automatically selected.
• If the current directory is not a configured project, a "current directory" entry appears at the top of the project list, allowing you to launch a tool without any prior configuration.

🔧 Configuration Guide

Configuration File Location

• Windows: %APPDATA%\AI-CLI\config.json
• Linux: ~/.config/ai-cli/config.json
• macOS: ~/Library/Application Support/ai-cli/config.json

Configuration File Structure

{
  "projects": [
    {
      "type": "folder",
      "name": "My Projects",
      "children": [
        {
          "type": "project",
          "name": "Web App",
          "path": "/path/to/project",
          "env": {
            "API_KEY": "your-api-key",
            "DEBUG": "true"
          }
        }
      ]
    }
  ],
  "tools": [
    {
      "name": "kiro-cli",
      "displayName": "Kiro CLI",
      "windowsInstall": "winget install kiro-cli",
      "wslInstall": "curl -fsSL https://cli.kiro.dev/install | bash",
      "linuxInstall": "curl -fsSL https://cli.kiro.dev/install | bash",
      "macosInstall": "brew install kiro-cli",
      "checkCommand": "kiro-cli --version",
      "url": "https://kiro.dev/cli/"
    }
  ],
  "settings": {
    "language": "auto",
    "terminalEmulator": "default",
    "theme": "default"
  }
}

Project Configuration

Project Types

Folder:

{
  "type": "folder",
  "name": "Project Group Name",
  "children": [...]
}

Project:

{
  "type": "project",
  "name": "Project Name",
  "path": "/absolute/path/to/project",
  "env": {
    "KEY": "value"
  }
}

Environment Variables

Configure independent environment variables for each project:

{
  "type": "project",
  "name": "API Project",
  "path": "/path/to/api",
  "env": {
    "API_KEY": "sk-xxx",
    "API_BASE_URL": "https://api.example.com",
    "DEBUG": "true",
    "LOG_LEVEL": "info"
  }
}

Tool Configuration

Required Fields

• name: Tool command name (used for detection)
• displayName: Display name
• checkCommand: Command to check if tool is installed

Installation Commands (by Platform)

• windowsInstall: Windows native installation command
• wslInstall: WSL environment installation command
• linuxInstall: Linux installation command
• macosInstall: macOS installation command

Optional Fields

• url: Tool's official website (displayed in tool list)

Example Configuration

{
  "name": "cursor",
  "displayName": "Cursor Agent",
  "windowsInstall": "winget install Cursor",
  "wslInstall": "curl -fsSL https://cursor.sh/install | bash",
  "linuxInstall": "curl -fsSL https://cursor.sh/install | bash",
  "macosInstall": "brew install --cask cursor",
  "checkCommand": "cursor --version",
  "url": "https://cursor.sh"
}

Settings Options

language

• auto: Auto-detect system language (default)
• en: English
• zh: Chinese
• ja: Japanese
• de: German

terminalEmulator

• default: Use system default terminal (default)
• wt: Windows Terminal (Windows only)
• iterm: iTerm2 (macOS only)
• gnome-terminal: GNOME Terminal (Linux only)
• konsole: Konsole (Linux only)

theme

• default: Default dark theme
• More themes coming in future versions

🏗️ Project Architecture

Directory Structure

ai_cli/
├── __init__.py        # Package initialization
├── cli.py             # CLI entry point
├── app.py             # Main application logic
├── models.py          # Data models
├── config.py          # Configuration management
├── utils.py           # Path conversion utilities
├── core/              # Core functionality modules
│   ├── __init__.py
│   ├── tools.py       # Tool detection
│   ├── projects.py    # Project management
│   ├── git.py         # Git integration
│   └── installer.py   # Tool installation
├── ui/                # User interface modules
│   ├── __init__.py
│   ├── theme.py       # Theme configuration
│   ├── menu.py        # Menu rendering
│   └── input.py       # Keyboard input handling
├── platform/          # Platform adapter modules
│   ├── __init__.py
│   ├── base.py        # Abstract base class
│   ├── windows.py     # Windows adapter
│   ├── linux.py       # Linux adapter
│   ├── macos.py       # macOS adapter
│   └── factory.py     # Platform factory
└── i18n/              # Internationalization modules
    ├── __init__.py
    └── manager.py     # Language manager

Core Module Descriptions

models.py - Data Models

Defines all data structures:

• Config: Main configuration object
• Settings: Settings options
• ProjectNode: Project node (supports tree structure)
• Tool: Tool object
• ToolConfig: Tool configuration
• ToolEnvironment: Tool runtime environment enum

config.py - Configuration Management

• Cross-platform config file path handling
• Config file loading and saving
• Migration from legacy config versions
• Default config creation

app.py - Main Application

• Application main loop
• Project selection logic
• Tool selection logic
• Tool launch logic
• Project and folder CRUD operations

core/tools.py - Tool Detection

• Async parallel tool detection
• Platform-specific detection logic
• Windows native tool detection
• WSL tool detection
• Tool cache management

core/git.py - Git Integration

• Detect Git worktrees
• Display branch status
• Interactive worktree selection

core/installer.py - Tool Installation

• Select installation command by platform
• Execute installation process
• Post-installation path updates
• Find installed tools

ui/menu.py - Menu Rendering

• Render project tree
• Render tool list
• Display breadcrumb navigation
• Clear screen and refresh

ui/input.py - Keyboard Input

• Cross-platform keyboard input handling
• Different implementations for Windows and Unix
• Text input support
• Special key handling

platform/ - Platform Adapters

• Abstract platform interface
• Windows-specific implementation (Windows Terminal support)
• Linux-specific implementation (multiple terminal support)
• macOS-specific implementation (iTerm2 support)
• Platform factory pattern

i18n/manager.py - Internationalization

• Language detection
• Translation dictionary management
• Text retrieval interface

🔍 Advanced Features

Git Worktree Support

When a project path is a Git worktree, AI-CLI will:

1. Auto-detect all worktrees
2. Display branch and status for each worktree
3. Allow selection of the worktree to use
4. Show ahead/behind commit counts for branches

WSL Path Conversion

AI-CLI automatically handles path conversion between Windows and WSL:

• Windows path: C:\Users\username\project
• WSL path: /mnt/c/Users/username/project

Conversion is bidirectional, supporting:

• Launch WSL tools from Windows
• Launch Windows tools from WSL

Async Tool Detection

Tool detection uses async parallel processing:

1. On Startup: Quickly display interface, detect tools in background
2. Caching: Detection results are cached to avoid repeated checks
3. Refresh: Press R to clear cache and re-detect

Environment Variable Injection

Environment variables configured for each project are injected when launching tools:

{
  "type": "project",
  "name": "API Project",
  "path": "/path/to/api",
  "env": {
    "API_KEY": "sk-xxx",
    "DEBUG": "true"
  }
}

When launching a tool, these environment variables are added to the tool's runtime environment.

🧪 Testing

Running Tests

# Run all tests
pytest

# Run specific test file
pytest tests/test_models.py

# Run specific test
pytest tests/test_models.py::TestConfig::test_from_dict

# Show verbose output
pytest -v

# Show print output
pytest -s

Test Coverage

# Run tests with coverage report
pytest --cov=ai_cli

# Generate HTML coverage report
pytest --cov=ai_cli --cov-report=html

# View report
open htmlcov/index.html  # macOS
xdg-open htmlcov/index.html  # Linux
start htmlcov/index.html  # Windows

Test File Descriptions

• test_models.py: Data model tests
• test_config.py: Configuration management tests
• test_utils.py: Path conversion tests
• test_platform.py: Platform adapter tests
• test_git.py: Git integration tests
• test_tools.py: Tool detection tests
• test_projects.py: Project management tests
• test_ui.py: UI component tests
• test_app.py: Application integration tests
• test_cli.py: CLI entry point tests

📝 Development Guide

Requirements

• Python: 3.8 or higher
• Dependencies:
  • rich: Terminal UI rendering
  • prompt-toolkit: Keyboard input handling
  • click: CLI framework
  • platformdirs: Cross-platform paths

Development Environment Setup

# 1. Clone repository
git clone https://github.com/hyfhot/AI-CLI.git
cd AI-CLI

# 2. Create Python version worktree (if needed)
git worktree add ../ai-cli-multi-platform python-migration
cd ../ai-cli-multi-platform

# 3. Create virtual environment (recommended)
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# Linux/macOS:
source venv/bin/activate

# 4. Install development dependencies
pip install -e ".[dev]"

# 5. Run tests to verify environment
pytest

Code Style

Project follows PEP 8 style guide:

# Install code checking tools
pip install flake8 black mypy

# Run code checks
flake8 ai_cli tests

# Auto-format code
black ai_cli tests

# Type checking
mypy ai_cli

Adding New Tools

Add new tool configuration in config.json:

{
  "name": "new-tool",
  "displayName": "New Tool",
  "windowsInstall": "winget install new-tool",
  "wslInstall": "curl -fsSL https://example.com/install | bash",
  "linuxInstall": "curl -fsSL https://example.com/install | bash",
  "macosInstall": "brew install new-tool",
  "checkCommand": "new-tool --version",
  "url": "https://example.com"
}

Adding New Languages

Add translations in ai_cli/i18n/manager.py:

translations = {
    'new_lang': {
        'app_title': 'AI-CLI',
        'select_project': 'Select Project',
        # ... other translations
    }
}

Debugging Tips

# Enable debug mode
ai-cli --debug

# Use Python debugger
python -m pdb -m ai_cli.cli

# View detailed logs
import logging
logging.basicConfig(level=logging.DEBUG)

🐛 Troubleshooting

Windows Issues

Issue: Cannot detect Windows Terminal

# Solution: Ensure Windows Terminal is installed
winget install Microsoft.WindowsTerminal

Issue: WSL tool detection fails

# Solution: Ensure WSL is enabled
wsl --install

Linux Issues

Issue: Terminal emulator detection fails

# Solution: Install supported terminal
sudo apt install gnome-terminal  # Ubuntu/Debian
sudo dnf install gnome-terminal  # Fedora

macOS Issues

Issue: iTerm2 not detected

# Solution: Ensure iTerm2 is installed
brew install --cask iterm2

General Issues

Issue: Config file corrupted

# Solution: Reinitialize configuration
ai-cli --init

Issue: Tool detection cache stale

# Solution: Press R key in tool selection screen to refresh

🤝 Contributing

We welcome all forms of contribution!

Ways to Contribute

1. Report Bugs: Submit issues on GitHub Issues
2. Feature Requests: Propose new feature ideas
3. Code Contributions: Submit Pull Requests
4. Documentation: Improve docs and examples
5. Translations: Add new language support

Pull Request Process

1. Fork the project
2. Create feature branch (git checkout -b feature/AmazingFeature)
3. Commit changes (git commit -m 'Add some AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open Pull Request

Commit Convention

Follow Conventional Commits:

feat: Add new feature
fix: Fix bug
docs: Documentation update
style: Code formatting
refactor: Code refactoring
test: Test related
chore: Build/toolchain updates

📄 License

This project is licensed under the MIT License - see LICENSE file for details.

🔗 Related Links

• Original Project: AI-CLI (PowerShell Edition)
• Documentation: docs/
• Issue Tracker: GitHub Issues
• Changelog: CHANGELOG.md

🙏 Acknowledgments

Thanks to these open source projects:

• Rich - Powerful terminal UI library
• Prompt Toolkit - Interactive command-line tools
• Click - Python CLI framework
• platformdirs - Cross-platform directory paths

📊 Project Status

• Version: Beta
• Python Version: 3.8+
• Platforms: Windows, Linux, macOS
• Maintenance: Actively developed

🗺️ Roadmap

• Support more AI tools
• Plugin system
• Config file validation
• More theme options
• Tool usage statistics
• Cloud config sync
• Project template support

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Made with ❤️ by AI-CLI Team