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XIBE-CHAT CLI - AI-powered terminal assistant for text and image generation

Project description

XIBE-CHAT CLI 🚀

AI-powered terminal assistant for text and image generation

PyPI version Python 3.8+ License: MIT

A beautiful, feature-rich CLI application that brings AI text and image generation directly to your terminal. Built with Python and featuring a rich interface powered by Rich library.

✨ Features

🤖 AI Text Generation

  • Multiple AI Models: Choose from various text generation models
  • Conversation Memory: Maintains context across multiple exchanges
  • Rich Formatting: Beautiful markdown rendering with syntax highlighting
  • Model Switching: Change models on the fly without losing chat history

🖼️ AI Image Generation

  • Enhanced Prompts: AI automatically improves your prompts for better results
  • Multiple Models: Support for flux, kontext, turbo, nanobanana, and more
  • High Quality: 1024x1024 resolution with safety filtering
  • Private Generation: Images not shared in public feeds

💾 Smart Memory System

  • Model Preferences: Remembers your preferred AI models
  • Auto-Load: Uses saved preferences on startup
  • Easy Reset: Reset preferences anytime with /reset

🎨 Beautiful Interface

  • Rich Terminal UI: Beautiful ASCII art logo and colorful interface
  • Multi-line Input: Support for multi-line messages with Ctrl+N
  • Command System: Intuitive slash commands for all features
  • Cross-Platform: Works on Windows, macOS, and Linux

🚀 Quick Start

Installation

Via pip (recommended):

pip install xibe-chat-cli

Run the CLI:

xibe-chat
# or use the short alias
xibe

One-line Install Script

# Download and run installer
python -c "import urllib.request; exec(urllib.request.urlopen('https://raw.githubusercontent.com/iotserver24/xibe-chat-cli/main/install.py').read())"

📖 Usage

Basic Commands

# Start the CLI
xibe-chat

# Chat with AI
You: Hello! How are you?

# Generate images
You: img: a beautiful sunset over mountains

# Get help
You: /help

Available Commands

Command Description
/help Show all commands and usage
/clear Clear terminal and show logo
/new Start a new chat session
/reset Reset saved model preferences
/image-settings View image generation settings
models Show available AI models
switch Change AI models
exit/quit End the session

Input Methods

  • Normal Text: Just type and press Enter
  • Multi-line: Press Ctrl+N for new lines, Enter to send
  • Image Generation: Prefix with img: (e.g., img: cute cat)

⚙️ Configuration

API Token (Optional but Recommended)

Set your API token for better rate limits and premium features:

# Windows
set API_TOKEN=your_token_here

# macOS/Linux
export API_TOKEN=your_token_here

Model Preferences

Your preferred models are automatically saved in xibe_chat_config.json:

{
  "text_model": "mistral",
  "image_model": "flux",
  "last_updated": "2024-01-15T10:30:45.123456"
}

🖼️ Image Generation Features

Enhanced API Parameters

  • Enhance: AI improves your prompts automatically
  • Safe Mode: Strict NSFW filtering enabled
  • Private: Images not shared publicly
  • High Quality: 1024x1024 resolution
  • No Watermarks: Clean images (with API token)

Available Models

  • flux: High-quality general purpose
  • kontext: Image-to-image editing
  • turbo: Fast generation
  • nanobanana: Advanced image editing
  • gptimage: GPT-powered generation

🔧 Development

Setup Development Environment

# Clone the repository
git clone https://github.com/iotserver24/xibe-chat-cli.git
cd xibe-chat-cli

# Install in development mode
pip install -e .

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

Building from Source

# Build package
python -m build

# Install locally
pip install dist/xibe_chat_cli-1.0.0-py3-none-any.whl

Creating Executables

# Install PyInstaller
pip install pyinstaller

# Create executable
pyinstaller --onefile --name xibe-chat xibe_chat.py

📦 Requirements

  • Python 3.8+
  • pyfiglet
  • python-dotenv
  • requests
  • rich
  • prompt-toolkit

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

📄 License

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

🙏 Acknowledgments

📞 Support


Made with ❤️ by iotserver24

Star this repository if you find it helpful!

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