Feanor - AI Development Acceleration Platform

A powerful desktop tool that enables seamless interaction with local AI models through LM Studio integration. Feanor is designed to accelerate the development of AI tools and agents, providing a comprehensive environment for creating, testing, and deploying AI-powered solutions. Whether you're building custom tools or orchestrating AI agent swarms, Feanor provides the foundation for rapid AI development.

Features

• Modern Desktop Interface: Built with PyQt6 and Electron for a responsive native experience
• LM Studio Integration: Direct connection to LM Studio for local AI model inference
• Tool Integration System: Extensible architecture supporting various tools:
  • File Analysis
  • PDF Reading
  • Web Scraping
  • Git Repository Analysis
  • Text Extraction
• Real-time Chat: Responsive chat interface with support for:
  • Drag and drop file attachments
  • Message history
  • Tool selection and execution
  • Markdown rendering
• Proxy System: FastAPI-based proxy server for handling LM Studio communication

Upcoming Features Roadmap

• Tool Generation

  • Automated tool creation from natural language descriptions
  • Tool validation and testing framework
  • Tool marketplace for sharing and discovery

• ComfyUI Integration

  • Seamless integration with ComfyUI workflows
  • Custom node creation and management
  • Visual workflow builder for AI pipelines

• Agent Creation

  • Agent personality customization
  • Skill and capability definition
  • Training and fine-tuning interface
  • Agent testing and validation suite

• Fellowships (AI Agent Swarms)

  • Multi-agent orchestration
  • Inter-agent communication protocols
  • Task distribution and management
  • Swarm behavior monitoring

Additional Features Under Consideration

• Knowledge Base Integration

  • Vector database support
  • Document ingestion pipeline
  • Automated knowledge extraction

• Model Management

  • Local model repository
  • Model performance metrics
  • A/B testing framework

• Workflow Automation

  • Visual pipeline builder
  • Task scheduling and automation
  • Event-driven triggers

• Development Tools

  • Integrated debugging tools
  • Performance profiling
  • Code generation assistance

• Deployment Management

  • Container orchestration
  • Environment management
  • Version control integration

Technical Stack

• Frontend:
  • PyQt6 for native UI
  • Electron for cross-platform compatibility
  • TailwindCSS for styling
• Backend:
  • FastAPI for the proxy server
  • Python 3.x
  • TypeScript for Electron integration

Project Structure

├── Backend/             # Backend server components
│   └── lmstudio_proxy.py    # LM Studio proxy server
├── UI/                  # UI components and assets
│   ├── components/      # React components
│   ├── hooks/          # Custom React hooks
│   ├── lib/            # Shared utilities
│   ├── public/         # Static assets
│   ├── services/       # API services
│   ├── types/          # TypeScript type definitions
│   └── styles.css      # Global styles
├── src/                # Electron main process
│   ├── main.js         # Main process entry
│   ├── preload.js      # Preload scripts
│   └── renderer.js     # Renderer process
└── various config files # (package.json, tsconfig.json, etc.)

Setup and Installation

1. Install dependencies:

   # Install Node.js dependencies
   npm install
   
   # Install Python dependencies
   pip install -r requirements.txt

2. Configure LM Studio:

   • Install LM Studio
   • Configure it to run on port 4891 (default LM Studio port)
   • Ensure LM Studio is running before starting the application

3. Start the application:

   # Start the proxy server (from project root)
   # This will run on port 4892 and connect to LM Studio on port 4891
   python Backend/lmstudio_proxy.py
   
   # In a new terminal, start the Electron application
   npm start

4. Development Setup:

   # Build Tailwind CSS
   npm run build:css
   
   # Watch for CSS changes (optional)
   npm run build:css -- --watch

Development

• Adding New Tools:

  1. Define tool in Backend/tools_config.json
  2. Implement handler in Backend/tools/ directory
  3. Register in Backend/tool_handlers.py

• UI Modifications:

  • React components in UI/components/
  • Styles in UI/styles.css
  • TypeScript types in UI/types/
  • API services in UI/services/

Architecture

Component Overview

1. Frontend (UI/):

   • React components for user interface
   • TypeScript for type safety
   • Tailwind CSS for styling
   • Electron renderer process integration

2. Proxy Server (Backend/lmstudio_proxy.py):

   • FastAPI server running on port 4892
   • Manages communication with LM Studio
   • Handles tool execution requests
   • Provides health checking

3. Tool System:

   • Configurable via Backend/tools_config.json
   • Extensible architecture
   • Support for async operations
   • Built-in tools:
     • File Analysis
     • PDF Reading
     • Web Scraping
     • Git Repository Analysis
     • Text Extraction

Contributing

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

License

ISC License

Requirements

• Python 3.x
• Node.js
• LM Studio
• Modern web browser
• Windows/macOS/Linux