• Godot ExecuTorch Module
  • Overview
  • Installation
  • Usage in Godot
    • Basic Setup
    • Running Inference
    • Using MCP Tools
    • Performance Monitoring
  • Module Architecture
    • Core Components
    • Class Hierarchy
  • Module Integration Benefits
  • Development
    • Testing the Module
  • Deployment
  • Troubleshooting
    • Common Issues

Godot ExecuTorch Module

This project is currently in early development and is NOT ready for production use.

⚠️ IMPORTANT: NOTHING CURRENTLY WORKS ⚠️

This is a concept/prototype module intended to integrate ExecuTorch machine learning inference capabilities into Godot Engine with built-in MCP (Model Context Protocol) support.

Current Status:

• 🔴 Nothing is implemented - this is concept documentation only
• 🔴 API is completely unstable and subject to breaking changes
• 🔴 No working code - placeholder implementations only
• 🔴 No testing - may not even compile
• 🔴 No official releases - use at your own risk
• 🔴 Documentation describes planned features that don't exist yet

Planned Features (NOT IMPLEMENTED):

• ExecuTorchRuntime class for model loading and inference
• Built-in MCP (Model Context Protocol) server
• GDScript integration with native performance
• Cross-platform model execution
• Performance monitoring and benchmarking
• Linear regression and other model type support

TODO - Build System Integration:

• 🔧 Compile ExecuTorch separately and use its compilation database (compile_commands.json) to figure out how to properly build with SCons
• 🔧 Extract build flags and dependencies from ExecuTorch's CMake configuration
• 🔧 Port CMake settings to SCons for proper Godot module integration
• 🔧 Handle third-party dependencies (XNNPACK, etc.) in Godot's build system

Do not use this in:

• Production games or applications
• Commercial projects
• Critical systems
• Any project expecting working functionality

This is for experimentation, planning, and development reference only!