genai-electron

Version: 0.3.0 | Status: Production Ready - LLM & Image Generation

Electron-specific library for managing local AI model servers (llama.cpp, stable-diffusion.cpp). Handles platform-specific operations to run AI models locally. Complements genai-lite for API abstraction.

Features

• ✅ System detection - Auto-detect RAM, CPU, GPU, VRAM capabilities
• ✅ Model management - Download GGUF models with progress tracking and metadata extraction
• ✅ LLM server - Manage llama-server lifecycle with auto-configuration
• ✅ Image generation - Local image generation via stable-diffusion.cpp
• ✅ Resource orchestration - Automatic LLM offload/reload when memory constrained
• ✅ Binary management - Automatic binary download with GPU variant testing (CUDA→Vulkan→CPU)
• ✅ TypeScript-first - Full type safety, zero runtime dependencies

Installation

npm install genai-electron
npm install electron@>=25.0.0  # Peer dependency

Quick Start

import { app } from 'electron';
import { systemInfo, modelManager, llamaServer } from 'genai-electron';

app.whenReady().then(async () => {
  // Detect capabilities
  const caps = await systemInfo.detect();
  console.log('RAM:', (caps.memory.total / 1024 ** 3).toFixed(1), 'GB');

  // Download model (if needed)
  await modelManager.downloadModel({
    source: 'url',
    url: 'https://huggingface.co/TheBloke/Llama-2-7B-GGUF/resolve/main/llama-2-7b.Q4_K_M.gguf',
    name: 'Llama 2 7B',
    type: 'llm'
  });

  // Start server with auto-config
  await llamaServer.start({
    modelId: 'llama-2-7b',
    port: 8080
  });

  console.log('Server ready on port 8080');
});

Use with genai-lite for AI interactions (chat, image generation).

Documentation

📚 Complete Documentation - Full API reference, guides, and examples

Quick Links:

• Installation & Setup
• System Detection
• Model Management
• LLM Server
• Image Generation
• TypeScript Reference
• Troubleshooting

Example App

See electron-control-panel for a full-featured reference implementation.

Platform Support

• macOS: 11+ (Intel, Apple Silicon with Metal)
• Windows: 10+ (64-bit, CPU and CUDA)
• Linux: Ubuntu 20.04+, Debian 11+, Fedora 35+ (CPU, CUDA, ROCm)

License

MIT License - see LICENSE file for details.

Related Projects

• genai-lite - Lightweight API abstraction for AI providers (cloud and local)