Project Aegis (Aegis OTA)

Aegis OTA is a powerful, cross-platform system monitoring and AI-assisted IDE application built with Rust and Slint UI. It allows users to monitor system resources in real-time, manage connected devices, and seamlessly interact with top-tier AI models (Google Gemini, OpenAI, Anthropic, and local Ollama instances) to generate code and process commands.

Features

• System Pulse: Real-time monitoring of CPU usage, Memory usage, CPU Frequency, and Temperature. Visualized using dynamic sparkline graphs.
• Connected Devices: Automatically detects and displays connected drives/devices with their active status.
• AI-Assisted IDE: Integrated text editor and terminal to write code or run commands.
• Multi-Provider AI Integration: Connect to Google Gemini, OpenAI (GPT-4o), Anthropic (Claude 3.5), or a local Ollama server directly from the UI.
• Dynamic Syntax Highlighting: AI generated output is formatted and color-coded.
• Fast & Native: Built on Rust with native TLS for lightning-fast, secure API requests.

Project Structure

graph TD
    A[Project Aegis] --> B(src)
    A --> C(ui)
    A --> D(Cargo.toml)
    A --> E(build.rs)
    B --> F[main.rs]
    C --> G[main.slint]
    
    style A fill:#1e1e1e,stroke:#007acc,stroke-width:2px,color:#fff
    style B fill:#252526,stroke:#333,color:#fff
    style C fill:#252526,stroke:#333,color:#fff
    style F fill:#37373d,stroke:#333,color:#fff
    style G fill:#37373d,stroke:#333,color:#fff

Directory Layout

• src/main.rs: Contains the core Rust logic, Tokio async runtime, system resource polling (sysinfo), and the HTTP client for AI requests (reqwest).
• ui/main.slint: Contains the declarative UI code written in Slint, including components like Sparkline, DarkComboBox, and MainWindow.
• build.rs: The build script responsible for compiling the Slint UI into Rust during the build process.
• Cargo.toml: Dependency configurations and project metadata.

System Architecture

sequenceDiagram
    participant User
    participant SlintUI as Slint UI (Frontend)
    participant RustBackend as Rust Core (Backend)
    participant SysInfo as SysInfo Poller
    participant AI as AI Providers (Gemini/OpenAI/Anthropic/Ollama)

    User->>SlintUI: Types Prompt & Clicks Send
    SlintUI->>RustBackend: Trigger `on_command_entered` callback
    RustBackend->>AI: Async HTTP POST (reqwest + native-tls)
    AI-->>RustBackend: JSON Response
    RustBackend->>SlintUI: Update `ai_responses` Model
    SlintUI-->>User: Display AI Output

    loop Every 1 second
        SysInfo->>RustBackend: Fetch CPU/Memory metrics
        RustBackend->>SlintUI: Update `system_pulse`
    end

Getting Started

Prerequisites

• Rust Toolchain (Cargo, rustc)
• A valid API Key for any of the supported AI providers (Optional, but required for cloud AI usage).

Building and Running

1. Clone or download the repository.
2. Open a terminal in the project root.
3. Build the application:

   cargo build
   

4. Run the application:

   cargo run
   

Setting up AI Providers

1. Launch the application.
2. Click on the ⚙ Settings button in the middle panel.
3. Select your preferred AI Provider.
4. Enter your API Key in the designated field.
5. Click Verify API Key to ensure connectivity.
6. Click Save & Close.
7. Start typing in the terminal input field and hit Send.

Tech Stack

• Rust - Core language
• Slint - Declarative UI framework
• Tokio - Asynchronous runtime
• reqwest - HTTP Client (with native-tls)
• sysinfo - System metrics retrieval
• syntect - Syntax highlighting engine

License

This project is open-source and available under standard MIT licensing terms.