ggufloader 2.0.1

Advanced GGUF Model Loader with Smart Floating Assistant

GGUF Loader

Advanced GGUF Model Loader with Smart Floating Assistant

GGUF Loader is a production-ready Python application that provides a robust GGUF model loader with an innovative Smart Floating Assistant addon. Transform how you work with AI across all your applications with global text selection and processing capabilities.

✨ Key Features

🚀 Smart Floating Assistant

• Global Text Selection: Works across ALL applications (browsers, editors, documents)
• AI-Powered Processing: Summarize and comment on any selected text
• Floating UI: Non-intrusive, always-accessible interface
• Privacy-First: All processing happens locally on your machine

🎯 Core Capabilities

• GGUF Model Support: Load and run any GGUF format model
• Modern GUI: Built with PySide6 for a native desktop experience
• Addon System: Extensible architecture for custom functionality
• Cross-Platform: Works on Windows, macOS, and Linux
• GPU Acceleration: Optional CUDA and Metal support

🔧 Developer-Friendly

• Rich API: Comprehensive addon development framework
• Hot Loading: Load and unload addons without restarting
• Open Source: MIT licensed and community-driven

🚀 Quick Start

Installation

pip install ggufloader

Launch

ggufloader

First Steps

1. Download a GGUF model from Hugging Face
2. Click "Select GGUF Model" in the application
3. Load your model and start chatting
4. Try the Smart Assistant: Select text anywhere and click the ✨ button!

📋 System Requirements

• Python: 3.8 or higher
• RAM: 4GB minimum (8GB+ recommended)
• Storage: 2GB+ free space for models
• OS: Windows 10/11, macOS 10.14+, or Linux (Ubuntu 18.04+)

Platform-Specific Requirements

Windows

• Windows 10 or 11
• Automatically installs pywin32 for enhanced system integration

macOS

• macOS 10.14 (Mojave) or later
• Optional: Install enhanced macOS integration with pip install ggufloader[macos]

Linux

• Ubuntu 18.04+, Fedora 30+, or equivalent
• X11 display server (Wayland support coming soon)
• Optional: Install enhanced Linux integration with pip install ggufloader[linux]

🎮 Usage Examples

Basic Chat

# Launch the application
ggufloader

# Or use programmatically
from ggufloader import addon_main
addon_main()

Smart Floating Assistant Workflow

1. Reading an article → Select key paragraph → Click ✨ → "Summarize"
2. Code review → Select complex function → Click ✨ → "Comment"
3. Email writing → Select draft → Click ✨ → "Comment" for suggestions
4. Research → Select academic text → Click ✨ → "Summarize"

Command Line Options

# Show version
ggufloader --version

# Show help
ggufloader --help

🔧 Advanced Installation

GPU Acceleration

NVIDIA GPU (CUDA)

pip uninstall llama-cpp-python
pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121

Apple Silicon (Metal)

pip uninstall llama-cpp-python
CMAKE_ARGS="-DLLAMA_METAL=on" pip install llama-cpp-python

Platform-Specific Enhanced Features

Windows Enhanced Integration

pip install ggufloader[windows]

macOS Enhanced Integration

pip install ggufloader[macos]

Linux Enhanced Integration

pip install ggufloader[linux]

Performance Monitoring (Optional)

pip install ggufloader[performance]

All Optional Features

pip install ggufloader[all]

Development Installation

git clone https://github.com/GGUFloader/gguf-loader.git
cd gguf-loader
pip install -e .[dev]

📚 Documentation

Quick Links

• Installation Guide - Detailed setup instructions
• Quick Start Guide - Get running in minutes
• Addon Development - Create custom addons
• API Reference - Complete API documentation

Key Documentation Files

• Package Structure - Understanding the codebase
• Smart Floater Example - Learn from the built-in addon

🛠️ Development

Project Structure

ggufloader/
├── __init__.py              # Package initialization
├── gguf_loader_main.py      # Main application entry point
├── addon_manager.py         # Addon system management
├── config.py               # Configuration utilities
├── addons/                 # Built-in addons
├── docs/                   # Documentation
├── models/                 # Model loading components
├── ui/                     # User interface components
└── widgets/                # Custom UI widgets

Creating Addons

# Example addon structure
def register_addon(parent_app):
    """Register addon with the main application"""
    return MyAddonWidget(parent_app)

class MyAddonWidget(QWidget):
    def __init__(self, parent_app):
        super().__init__()
        self.parent_app = parent_app
        # Your addon implementation

🤝 Contributing

We welcome contributions! Here's how to get started:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Make your changes and add tests
4. Run tests: pytest
5. Submit a pull request

Development Setup

git clone https://github.com/GGUFloader/gguf-loader.git
cd gguf-loader
pip install -e .[dev]

📄 License

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

🔗 Links

• Homepage: https://ggufloader.github.io
• Repository: https://github.com/GGUFloader/gguf-loader
• PyPI Package: https://pypi.org/project/ggufloader/
• Bug Reports: https://github.com/GGUFloader/gguf-loader/issues

👨‍💻 Author

Hussain Nazary

• Email: [e-mail]
• GitHub: @GGUFloader

🙏 Acknowledgments

• llama.cpp team for the excellent GGUF format and inference engine
• PySide6 team for the robust GUI framework
• Hugging Face for model hosting and transformers library
• Open source community for continuous support and contributions

📊 Stats

• Language: Python 3.8+
• GUI Framework: PySide6
• AI Backend: llama-cpp-python
• Package Size: ~50MB
• Supported Models: All GGUF format models

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Transform your text workflow with AI-powered assistance! 🚀

Made with ❤️ by the GGUF Loader team