🤖 Jarvis AI Assistant

A powerful, voice-controlled AI assistant with advanced automation capabilities, built with Python and PyQt5.

🌟 Features

🎯 Core Capabilities

• Voice Recognition - Hands-free operation with speech-to-text
• Text-to-Speech - Natural voice responses
• Smart Decision Making - AI-powered command categorization using Cohere
• GUI Interface - Modern PyQt5 chat interface

🔧 Automation & Control

• System Commands - Volume control, shutdown, mute/unmute
• Application Control - Open/close apps, web automation
• Web Search - Google search with real-time results
• YouTube Integration - Search and play videos

⏰ Reminder & Timer System

• Set Reminders - "Remind me to call mom at 5:30 PM"
• Timer Functions - "Set a timer for 5 minutes"
• List Management - View active reminders and timers
• Persistent Storage - Data saved across app restarts
• Background Notifications - Voice alerts when time is up

🎨 AI Image Generation

• Text-to-Image - Generate images from descriptions
• Stable Diffusion - High-quality AI art using Hugging Face API
• Auto-Display - Generated images open automatically
• Organized Storage - Images saved in Data/Generated_Images/

💬 Chat & Search

• Conversational AI - Natural language conversations
• Real-time Search - Up-to-date information retrieval
• Chat History - Persistent conversation logs

🐳 Docker Support

• Portable Deployment - Run anywhere with Docker
• GUI & Headless Modes - Flexible deployment options
• Cross-platform - Windows, Linux, Mac compatibility

🚀 Quick Start

1. Clone Repository

git clone https://github.com/Developer-Tanay/Jarvis-Assistant.git
cd Jarvis-Assistent

2. Install Dependencies

pip install -r Requirements.txt

3. Configure Environment

Create a .env file in the root directory:

# Required API Keys
COHERE_API_KEY=your_cohere_api_key_here
HUGGINGFACE_API_KEY=your_huggingface_api_key_here
GROQ_API_KEY=your_groq_api_key_here

# Personal Settings
USERNAME=YourName
ASSISTANT_NAME=Jarvis
INPUT_LANGUAGE=en
ASSISTANT_VOICE=David

4. Run Application

python Main.py

🔑 API Keys Setup

Cohere API (Required)

1. Visit Cohere.ai
2. Sign up for free account
3. Get API key from dashboard
4. Add to .env file

Hugging Face API (For Image Generation)

1. Visit Hugging Face
2. Create account and get access token
3. Add to .env file

Groq API (Optional - Enhanced Performance)

1. Visit Groq
2. Sign up and get API key
3. Add to .env file

🎮 Usage Examples

Voice Commands

Reminders & Timers

"Jarvis, remind me to call mom at 5:30 PM"
"Set a timer for 10 minutes"
"What are my reminders?"
"Show my active timers"

Image Generation

"Generate an image of a sunset over mountains"
"Create a picture of a cute robot"
"Make an image showing a futuristic city"

System Control

"Mute my computer"
"Unmute"
"Shutdown computer"

Web & Search

"Search Google for Python tutorials"
"Play relaxing music on YouTube"
"What's the latest news about AI?"

General Chat

"Hello Jarvis, how are you?"
"Tell me a joke"
"What's the weather like?"

📁 Project Structure

Jarvis-Assistent1/
├── Main.py                 # Main application entry point
├── Requirements.txt        # Python dependencies
├── .env                   # Environment variables (create this)
├── README.md              # This file
├── Backend/               # Core AI and automation modules
│   ├── Model.py          # Decision-making AI (Cohere)
│   ├── Automation.py     # Command execution
│   ├── ReminderTimer.py  # Reminder/timer system
│   ├── ImageGeneration.py # AI image generation
│   ├── Chatbot.py        # Conversational AI
│   ├── SpeechToText.py   # Voice recognition
│   ├── TextToSpeech.py   # Voice synthesis
│   └── RealtimeSearchEngine.py # Web search
├── Frontend/              # User interface
│   ├── GUI.py            # PyQt5 interface
│   └── Files/            # GUI data files
├── Data/                  # Application data
│   ├── ChatLog.json      # Chat history
│   ├── reminders.json    # Active reminders
│   ├── timers.json       # Active timers
│   └── Generated_Images/ # AI-generated images
└── Docker/               # Containerization
    ├── Dockerfile
    ├── docker-compose.yml
    └── run-docker.sh

🐳 Docker Deployment

Quick Docker Setup

# Build and run
docker-compose up --build

# Headless mode (no GUI)
docker-compose --profile headless up jarvis-headless

Windows Docker

# Use provided script
run-docker.bat build
run-docker.bat headless

🔧 Configuration

Voice Settings

Edit .env file:

• INPUT_LANGUAGE - Recognition language (en, es, fr, etc.)
• ASSISTANT_VOICE - TTS voice name

GUI Customization

Modify Frontend/GUI.py for:

• Theme colors
• Window size
• Chat appearance

Command Extensions

Add new commands in:

• Backend/Model.py - For command recognition
• Backend/Automation.py - For command execution

🛠️ Dependencies

Core Libraries

• PyQt5 - GUI framework
• python-dotenv - Environment variables
• cohere - AI decision making
• requests - HTTP requests
• keyboard - System control

Audio & Speech

• pygame - Audio playback
• edge-tts - Text-to-speech
• speech_recognition - Voice input

Web & Automation

• selenium - Web automation
• beautifulsoup4 - Web scraping
• googlesearch-python - Search integration

Image Generation

• Pillow - Image processing
• requests - API communication

⚡ Performance Tips

1. API Response Times

   • Cohere: ~1-2 seconds
   • Image Generation: ~10-30 seconds
   • Voice Recognition: ~2-3 seconds

2. Resource Usage

   • RAM: ~200-400MB
   • CPU: Low usage except during image generation

3. Optimization

   • Use Docker for consistent performance
   • Close unused applications for better voice recognition
   • Ensure stable internet for API calls

🐛 Troubleshooting

Common Issues

Voice Recognition Not Working

# Check microphone permissions
# Ensure pygame is installed
pip install pygame

API Errors (403/401)

• Verify API keys in .env file
• Check API key permissions
• Ensure internet connectivity

Image Generation Fails

• Confirm Hugging Face API key
• Try free model: runwayml/stable-diffusion-v1-5
• Check network connection

GUI Not Loading

# Install PyQt5
pip install PyQt5

Docker Issues

• Ensure Docker Desktop is running
• Use headless mode on Windows
• Check volume mounts for data persistence

Debug Mode

Enable detailed logging by adding to .env:

DEBUG_MODE=True

🔒 Security Notes

• API Keys: Never commit .env file to version control
• Local Data: All conversations stored locally in Data/
• Network: Only communicates with specified AI APIs
• Permissions: Requires microphone access for voice features

🚀 Future Enhancements

• Multi-language support
• Custom wake word detection
• Integration with smart home devices
• Advanced image editing capabilities
• Calendar integration
• Email automation
• Mobile app companion

📄 License

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

🤝 Contributing

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

📧 Support

For issues and questions:

• Open GitHub issue
• Check troubleshooting section
• Review API documentation

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Made with ❤️ for AI automation enthusiasts