# Feature Request: Enhanced run_comfyui.bat with Automated Dependency Checking and CUDA PyTorch Detection

## Problem

Windows users often encounter frustrating issues when setting up ComfyUI:

1. **Missing Dependencies**: Users encounter cryptic `ModuleNotFoundError` messages when dependencies are missing, requiring manual troubleshooting and installation
2. **CPU-Only PyTorch**: Many users accidentally install CPU-only PyTorch, which prevents GPU acceleration and causes significant performance issues without clear indication of the problem
3. **Poor Error Messages**: Existing error messages don't provide clear guidance on how to resolve issues, leaving users to search forums and documentation
4. **Installation Confusion**: Users are unsure which dependencies are required vs optional, and whether they should install in virtual environments

These issues create a poor first-time user experience and increase support burden.

## Proposed Solution

Enhance the `run_comfyui.bat` startup script to:

- **Automated Dependency Checking**: Check all critical Python dependencies before launching ComfyUI, with clear prompts for missing packages
- **CUDA PyTorch Detection**: Automatically detect CPU-only PyTorch installations and offer to install the CUDA-enabled version
- **User-Friendly Error Messages**: Provide clear, actionable error messages with specific troubleshooting steps
- **Virtual Environment Guidance**: Detect virtual environments and provide appropriate warnings and guidance
- **Progress Feedback**: Show progress bars during installations for better user experience

## Benefits

- **Reduced Support Burden**: Common setup issues are caught and resolved automatically
- **Better User Experience**: Windows users get clear guidance instead of cryptic errors
- **GPU Support**: Automatically ensures users have CUDA-enabled PyTorch for optimal performance
- **Professional Appearance**: Polished interface with clear formatting and helpful prompts

## Implementation Details

The enhancement would:
- Check for missing dependencies using `importlib.util.find_spec()`
- Separate critical vs optional dependencies
- Detect CPU-only PyTorch by checking version string for "+cpu" indicator
- Provide interactive prompts for installation options
- Maintain full backward compatibility with existing functionality

## Additional Notes

- All installations would be optional (users can cancel at any time)
- The script would warn users about system Python vs virtual environment implications
- All existing functionality would be preserved
- The enhancement is designed to be safe and non-destructive

## Status

I have a complete PR ready to submit if this feature is desired. The implementation includes comprehensive dependency checking, CUDA PyTorch auto-installation, user-friendly error handling, and has been tested in various scenarios.

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**Note**: This addresses common user pain points that may not have been formally reported as issues, but are frequently encountered in the community (especially on Discord/Matrix support channels).