Ted AI Assistant

A miniaturized version of JARVIS from Iron Man - an AI personal assistant that can communicate via voice, carry out desktop tasks, understand visual information through a camera, and speak through your speakers.

🚀 NEW: Full J.A.R.V.I.S Upgrade Path Available!

See: JARVIS_SYSTEM_RESEARCH.md - Comprehensive 65-question research document
See: TED_UPGRADE_ROADMAP.md - Step-by-step upgrade plan

Current Features

• 🎤 Voice Interaction: Speech-to-Text and Text-to-Speech capabilities
• 🖥️ Desktop Automation: Control applications, files, and system operations
• 👁️ Computer Vision: AI-powered visual understanding through your camera
• 🧠 Natural Language Understanding: Interpret and execute complex commands
• 🔊 Audio Output: Natural-sounding voice responses

Planned Enhancements (Coming Soon)

• 🤖 Local LLM Integration: Mistral 7B for advanced conversational AI
• 🧠 Persistent Memory: Remember past conversations and preferences
• 📧 Email Integration: Send, read, and manage emails via Gmail API
• 📅 Calendar Management: Schedule events and get reminders
• 🌐 Web Search: Real-time information retrieval from the internet
• ⏰ Proactive Assistance: Morning briefings, event reminders, smart suggestions
• 👂 Wake Word Detection: "Hey Ted" activation
• 🎯 Personalization: Learn your preferences and habits

Project Structure

ted_assistant/
├── modules/           # Core functional modules
│   ├── stt.py        # Speech-to-Text module
│   ├── tts.py        # Text-to-Speech module
│   ├── computer_vision.py  # Computer Vision module
│   ├── desktop_automation.py  # Desktop Automation module
│   └── ai_core.py    # Central AI Core (NLU, decision-making)
├── utils/            # Helper utilities
├── config/           # Configuration files
└── main.py           # Main application entry point

Installation

1. Clone or download this repository

2. Install Python 3.8 or higher

   • Download from python.org

3. Install dependencies

   pip install -r requirements.txt

4. Download Vosk model (for offline speech recognition)

   • Visit Vosk Models
   • Download a model for your language (e.g., vosk-model-small-en-us-0.15)
   • Extract it to ted_assistant/config/vosk_model/

5. Download spaCy language model

   python -m spacy download en_core_web_sm

Usage

Run Ted with:

python main.py

Basic Commands

• "Hey Ted, what time is it?"
• "Open my browser"
• "What do you see?" (activates camera)
• "Create a new folder called Projects"
• "Search for Python tutorials"

Configuration

Edit ted_assistant/config/settings.py to customize:

• Voice settings (speed, volume)
• Wake word preferences
• API keys (if using cloud services)
• Camera settings

Development Roadmap

Current Status

• Project structure setup
• Basic voice interaction (STT + TTS)
• Desktop automation commands
• Computer vision integration
• Basic NLU with pattern matching
• GUI interface

Upgrade Path (See TED_UPGRADE_ROADMAP.md)

• Local LLM integration (Ollama + Mistral 7B)
• Advanced NLU with semantic understanding
• Persistent memory system (SQLite + ChromaDB)
• Email integration (Gmail API)
• Calendar integration (Google Calendar API)
• Web search and information retrieval
• Proactive assistance with scheduling
• Wake word detection
• User preference learning
• Multi-language support

Requirements

• Operating System: Windows 10/11, macOS 10.14+, or Linux
• Python: 3.8 or higher
• Hardware:
  • Microphone
  • Speakers
  • Webcam (for computer vision features)
  • Recommended: GPU for real-time computer vision

📚 Documentation

Core Documentation

• README.md - This file, project overview
• QUICKSTART.md - 5-minute setup guide
• INSTALLATION.md - Detailed installation instructions
• EXAMPLES.md - Command examples and usage guide

Advanced Documentation (NEW)

• JARVIS_SYSTEM_RESEARCH.md - 📖 3900+ lines comprehensive research

  • Complete technical blueprint for J.A.R.V.I.S-like system
  • 65 research questions answered with Python implementations
  • Architecture, NLP, voice, automation, APIs, memory, security
  • Code examples, cost analysis, library comparisons

• TED_UPGRADE_ROADMAP.md - 🗺️ Step-by-step upgrade plan

  • 7 phases from current state to full J.A.R.V.I.S capabilities
  • Week-by-week implementation guide
  • Complete code examples for each feature
  • Testing checklist and success criteria

Development Documentation

• Ted_Development_Notes.md - Technical notes
• PROJECT_SUMMARY.md - Project completion status
• WORKFLOW.md - Development workflow

Notes

• For the best experience with voice quality, consider using cloud-based TTS services (requires API keys)
• Computer vision features may require a GPU for real-time processing
• Some desktop automation features may require administrator privileges
• NEW: The JARVIS_SYSTEM_RESEARCH.md document provides a complete blueprint for upgrading Ted to a full-featured AI assistant

Getting Started with Upgrades

Ready to enhance Ted with advanced capabilities?

1. Review the Research: Read JARVIS_SYSTEM_RESEARCH.md to understand all possibilities
2. Follow the Roadmap: Use TED_UPGRADE_ROADMAP.md for step-by-step implementation
3. Start with Phase 1: Install Ollama and integrate local LLM (Week 1-2)
4. Build Incrementally: Each phase adds new capabilities while maintaining existing features

Estimated time to full J.A.R.V.I.S-like system: 8-10 weeks
Estimated ongoing cost: $0-30/month (mostly free with local processing)

License

This project is for educational and personal use.

Acknowledgments

Inspired by JARVIS from the Iron Man movies. Built with Python and various open-source libraries.

Research powered by: OpenAI Whisper, Ollama, ChromaDB, spaCy, LangChain, and many other amazing open-source projects.