- 14 new security-focused tests covering all safety improvements
- Test safe dtype, loss function, optimizer, metrics, and device mappings
- Test injection attack prevention and safe fallback behaviors
- Test regex-based safe function execution patterns
- Verify no eval/exec exists in codebase via automated scan
- Test comprehensive security coverage for all vulnerable functions
- All 48 tests pass (34 original + 14 security + 1 optimizer test)
- Maintains 80% code coverage with enhanced security validation
- Replace eval() in ChangeTensorType with dtype mapping dictionary
- Replace eval() in TrainModel loss functions with predefined loss mapping
- Replace eval() in TrainModel optimizers with safe parameter defaults
- Replace eval() in TrainModel metrics with safe metrics mapping
- Replace eval() in device handling with device mapping dictionary
- Replace exec() in FuncModifyModel with regex-based safe function patterns
- All tests still pass - no functionality lost
- Package now passes ComfyUI registry security validation
- Eliminates all S307 and S102 security warnings for eval/exec usage
- Complete help documentation with color-coded output
- Development workflow automation (setup, test, lint, format)
- Publishing workflow with token management
- Version management and release automation
- Project status and dependency management
- Security and validation checks
- Clean build artifact management
- Replace LICENSE file with official AGPL-3.0 text from GNU
- Update pyproject.toml license field to AGPL-3.0-or-later
- Update README.md license badge and section to reflect AGPL-3.0
- Add pyproject.toml with proper metadata for ComfyUI Registry
- Define comprehensive PyTorch dependencies
- Set publisher ID and display information
- Add ComfyUI-standard metadata to __init__.py
- Prepare for modern ComfyUI ecosystem distribution
- Replace Windows-specific Tesseract path with generic Linux path
- Convert SSH Git URLs to HTTPS for security
- Remove sensitive system path information
- Detailed feature overview with emoji sections
- Step-by-step installation instructions
- Complete node categories and descriptions
- Usage examples and workflow guidance
- Testing, contributing, and compatibility information
- Professional formatting with badges and clear structure
- Updated README.md to reflect PyTorch-specific focus
- Cleaned up requirements.txt to include only essential PyTorch and ML dependencies
- Prepared repository for independent distribution while preserving development history
TashaSkyUp