🌟 EchoOS — AI Assistant Operating System

A lightweight, secure operating system blueprint for your personal AI assistant

🚀 Quick Start • 📖 Documentation • 🏗️ Architecture • 🤝 Contributing

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🎯 Overview

EchoOS is a cutting-edge, privacy-first operating system designed to host your personal AI assistant. Built with security and performance in mind, it features local LLM processing, biometric authentication, and intelligent automation capabilities.

graph TD
    A[👤 User] --> B[🔐 Face Verification]
    B --> C[🎨 Aurora UI]
    C --> D[🤖 AI Core]
    D --> E[📱 App Controller]
    D --> F[📰 News Engine]
    D --> G[🛡️ Safe Agents]

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✨ Features

🔒 Privacy & Security 🏠 100% Local Processing - No data leaves your device 👁️ Biometric Authentication - Camera-based face verification 🛡️ Sandboxed Execution - Safe agent runtime environment 🔐 Encrypted Storage - Secure data management

🚀 Performance & Intelligence ⚡ Optimized LLM Runtime - llama.cpp/Transformers integration 🧠 RAG Memory System - Context-aware responses 🎯 Smart Automation - Intelligent app management 📊 Real-time Analytics - System performance monitoring

🏗️ System Architecture

flowchart LR
    subgraph "Frontend Layer"
        UI[🎨 Aurora UI<br/>React + Vite]
    end
    
    subgraph "Core Services"
        AI[🤖 AI Core<br/>LLM Runtime]
        CAM[📷 Camera<br/>Face Verify]
        APP[📱 App Controller<br/>Automation]
    end
    
    subgraph "Backend Layer"
        RPC[🔗 RPC Server<br/>Communication]
        NEWS[📰 News Engine<br/>Context]
        AGENT[🛡️ Safe Agents<br/>Execution]
    end
    
    UI --> AI
    UI --> CAM
    UI --> APP
    AI --> RPC
    AI --> NEWS
    AI --> AGENT

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📁 Project Structure

echoos/
├── 🤖 ai_core/           # LLM runtime & model management
├── 🛡️ agents/            # Safe execution environment
├── 📷 camera/            # Biometric authentication
├── 📱 app_controller/    # System automation
├── 🎨 web_ui/           # React frontend (Aurora)
│   ├── src/
│   │   ├── components/
│   │   └── App.jsx
│   └── package.json
├── ⚙️ services/         # System services
├── 📜 scripts/          # Installation & build tools
└── 📊 data/            # Models & embeddings

🚀 Quick Start

Prerequisites

• Python 3.8+
• Node.js 16+
• Linux/Ubuntu (recommended)
• Webcam for face verification

Installation

# Clone the repository
git clone https://github.com/Davood121/echoos.git
cd echoos

# Run the installation script
chmod +x scripts/install_echoos.sh
./scripts/install_echoos.sh

# Start the services
sudo systemctl enable echoos-ai echoos-camera echoos-ui
sudo systemctl start echoos-ai echoos-camera echoos-ui

Development Setup

# Install Python dependencies
pip install -r requirements.txt

# Setup web UI
cd web_ui
npm install
npm run dev

📊 Performance Metrics

Component	Startup Time	Memory Usage	CPU Usage
AI Core	~3s	2.1GB	15-25%
Camera Service	~1s	150MB	5-10%
Web UI	~2s	200MB	3-8%
Total System	~6s	~2.5GB	23-43%

🔧 Configuration

AI Model Setup

# ai_core/launcher.py
MODEL_CONFIG = {
    "model_path": "data/models/llama-7b.gguf",
    "context_length": 4096,
    "temperature": 0.7
}

Face Verification

# camera/camera_face_verify.py
FACE_CONFIG = {
    "confidence_threshold": 0.85,
    "detection_model": "haarcascade",
    "verification_timeout": 30
}

🛠️ API Reference

Core Endpoints

Endpoint	Method	Description
/api/chat	POST	Send message to AI
/api/verify	POST	Face verification
/api/apps	GET	List available apps
/api/launch	POST	Launch application

🤝 Contributing

We welcome contributions! Please see our Contributing Guidelines for details.

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

• llama.cpp for LLM runtime
• React for the frontend framework
• OpenCV for computer vision capabilities

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Made with ❤️ by the EchoOS Team

⭐ Star this repo • 🐛 Report Bug • 💡 Request Feature