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Icecubesaad/OpenLLM-Studio

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OpenLLM Studio

Run local LLMs without the hassle

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A beautiful, modern desktop application for managing and interacting with local AI models. Run AI entirely on your machine — no data leaves your computer.

┌─────────────────────────────────────┐
│  INSTALLER SIZE         ████████ 5MB│
│  GPU ACCELERATION       ████████ YES │
│  PRIVACY                ████████ 100%│
│  OFFLINE                ████████ YES │
└─────────────────────────────────────┘
  • Tiny installer — 5MB download, binaries fetched on-demand
  • GPU acceleration — Auto-detect and download CUDA/Vulkan/Metal binaries
  • 100% private — Everything runs locally, no data leaves your machine
  • HuggingFace integration — Search and download GGUF models directly
  • AI-powered recommendations — Get model suggestions based on your hardware

Features

🎨 Modern UI

  • Clean, dark-themed interface with smooth animations
  • Intuitive navigation and responsive design
  • Real-time progress indicators for downloads

📚 Model Management

  • My Library: View and manage your downloaded models
  • Browse: Discover curated AI models optimized for local execution
  • HuggingFace Integration: Search and download GGUF models from HuggingFace
  • Model Wizard: AI-powered recommendations based on your hardware

💬 Chat Interface

  • Multi-conversation support
  • Real-time streaming responses
  • Model switching on the fly
  • Conversation history

⚡ Smart Downloads

  • Automatic retry on network failures (up to 3 attempts)
  • Resume capability for interrupted downloads
  • Real-time progress tracking
  • Intelligent error handling

🔧 Advanced Features

  • Hardware detection (GPU, RAM, CPU)
  • On-demand binary downloads for GPU acceleration
  • Optimization settings
  • License management (Pro features)
  • Performance dashboard

Installation

Download Pre-built Binaries

Download the latest release for your platform:

Platform Download Size
Windows OpenLLM-Studio_x64-setup.exe ~5 MB
macOS (Apple Silicon) Coming Soon -
macOS (Intel) Coming Soon -
Linux Coming Soon -

First Run Experience

On first launch, the app will:

  1. Detect your hardware — GPU, RAM, CPU
  2. Recommend the best runtime — CPU, CUDA, Vulkan, or Metal
  3. Download optimized binaries — Only what you need (~100-200 MB)

This keeps the installer tiny while ensuring you get GPU acceleration when available.


Building from Source

Prerequisites

  • Node.js 20.19+ or 22.12+
  • Rust (latest stable)
  • System dependencies (see below)

System Dependencies

Windows

# Install Microsoft Visual Studio C++ Build Tools
# Download from: https://visualstudio.microsoft.com/visual-cpp-build-tools/

macOS

xcode-select --install

Linux (Ubuntu/Debian)

sudo apt update
sudo apt install -y libwebkit2gtk-4.1-dev libappindicator3-dev librsvg2-dev patchelf libgtk-3-dev libayatana-appindicator3-dev

Build Steps

  1. Clone the repository:
git clone https://github.com/Icecubesaad/OpenLLM-Studio.git
cd OpenLLM-Studio
  1. Install dependencies:
npm install
  1. Run in development mode:
npm run tauri dev
  1. Build for production:
npm run tauri build

The built application will be in src-tauri/target/release/bundle/.


Runtime Binaries

OpenLLM Studio uses llama.cpp binaries for local inference. These are downloaded on-demand based on your hardware.

Available Variants

Variant Platform Description
CPU All Pure CPU inference
CUDA 12.4 Windows, Linux NVIDIA GPUs
CUDA 13.1 Windows, Linux NVIDIA GPUs (newer)
Vulkan Windows, Linux AMD/Intel GPUs
Metal macOS Apple Silicon

Manual Download

If you prefer to manually download binaries, get them from the official llama.cpp releases page.

Binary Storage

  • Windows: %APPDATA%\com.openllm.studio\llama-binaries\
  • macOS: ~/Library/Application Support/com.openllm.studio/llama-binaries/
  • Linux: ~/.config/com.openllm.studio/llama-binaries/

Configuration

HuggingFace Token

For accessing private models or increased rate limits:

  1. Go to Settings
  2. Navigate to HuggingFace section
  3. Enter your HF token

Architecture

  • Frontend: React + TypeScript + Tailwind CSS
  • Backend: Rust + Tauri v2
  • Database: SQLite
  • AI Runtime: llama.cpp (on-demand download)
  • Model Recommendations: OpenRouter API

Project Structure

OpenLLM-Studio/
├── src/                    # React frontend
│   ├── components/         # UI components
│   ├── hooks/              # Custom React hooks
│   ├── pages/              # Page components
│   ├── lib/                # Utilities and types
│   └── store/              # State management
├── src-tauri/              # Rust backend
│   ├── src/                # Rust source code
│   ├── migrations/         # Database migrations
│   └── icons/              # App icons
├── .github/workflows/      # CI/CD pipelines
└── public/                 # Static assets

Development

Frontend Development

npm run dev

Backend Development

cd src-tauri
cargo check
cargo test

Type Checking

npm run build

Troubleshooting

GPU Not Detected

  1. Ensure you have the latest GPU drivers installed
  2. For NVIDIA: Install CUDA Toolkit
  3. For AMD: Install latest drivers from AMD Support
  4. Check Settings → General → Hardware Info

Binary Download Fails

  1. Check your internet connection
  2. Try a different variant (Settings → General → Runtime Engine)
  3. Use CPU variant as fallback
  4. Check firewall/proxy settings

Build Errors

  1. Ensure Node.js version is 20.19+ or 22.12+
  2. Clear node_modules: rm -rf node_modules && npm install
  3. Clear Rust build cache: cd src-tauri && cargo clean
  4. Install system dependencies (see above)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

License

MIT License - see LICENSE for details.


Acknowledgments

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Run local AI models privately with GPU acceleration. Modern UI, HuggingFace integration. Built with Tauri + React + Rust.

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