Windows Voice Control AI Assistant

An intelligent voice assistant that controls Windows applications and generates content through speech commands.

Features

• Voice Control - Control Windows apps using natural speech
• AI Integration - Generate content using voice commands
• Modern UI - Material Design inspired interface
• Command Logging - Track all voice commands and actions
• Extensible - Easy to add new commands and features

Quick Start

Prerequisites

• Python 3.9 or higher
• Windows 10/11
• Working microphone

Installation

# Clone the repository
git clone git@github.com:shahidx0x/windows-voice-control-ai-assistant.git

# Navigate to project directory
cd windows-voice-ai

# Create virtual environment
python -m venv venv

# Activate virtual environment
.\venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run the application
python main.py

Project Structure

ai-ass/
├── src/
│   ├── gui/              # GUI components
│   ├── services/         # Core services
│   └── utils/           # Utility functions
├── logs/                # Log files
└── main.py             # Entry point

Usage

1. Select your microphone from the dropdown
2. Click "Give Command" button
3. Speak your command clearly
4. Watch the log area for results

Voice Commands

Command	Action
"open [app]"	Opens specified application
"close [app]"	Closes specified application
"generate [type]"	Generates content
"minimize all"	Minimizes all windows

Development

Setting up dev environment

# Install dev dependencies
pip install -r requirements.txt

# Run tests
python -m pytest tests/

Future Work & Progress

GPT Model Integration

• Online GPT Integration

  • OpenAI GPT API integration for advanced language processing
  • Real-time content generation and complex queries
  • Adaptive response handling based on context

• Offline GPT Implementation

  • Local GPT model deployment for offline functionality
  • Optimized smaller models for basic commands
  • Reduced latency and increased privacy
  • No internet dependency for core features

Planned Improvements

• Hybrid mode switching between online/offline models
• Model compression techniques for better performance
• Custom training for Windows-specific commands
• Automatic model updates and versioning

License

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