Add support for respecting recommended strength values from LoRA usage_tips
when randomizing LoRA selection.
Features:
- New toggle setting to enable/disable recommended strength respect (default off)
- Scale range slider (0-2, default 0.5-1.0) to adjust recommended values
- Uses recommended strength × random(scale) when feature enabled
- Fallbacks to original Model/Clip Strength range when no recommendation exists
- Clip strength recommendations only apply when using Custom Range mode
Backend changes:
- Parse usage_tips JSON string to extract strength/clipStrength
- Apply scale factor to recommended values during randomization
- Pass new parameters through API route and node
Frontend changes:
- Update RandomizerConfig type with new properties
- Add new UI section with toggle and dual-range slider
- Wire up state management and event handlers
- No layout shift (removed description text)
Tests:
- Add tests for enabled/disabled recommended strength in API routes
- Add test verifying config passed to service
- All existing tests pass
Build: Include compiled Vue widgets
- Add `_preprocess_loras_input` method to handle different widget input formats
- Move core randomization logic to `LoraService` for better separation of concerns
- Update `_select_loras` method to use new service-based approach
- Add comprehensive test fixtures for license filtering scenarios
- Include debug print statement for pool config inspection during development
This refactor improves code organization by centralizing business logic in the service layer while maintaining backward compatibility with existing widget inputs.
- Document dual UI systems: standalone web UI and ComfyUI custom node widgets
- Add ComfyUI widget development guidelines including styling and constraints
- Update terminology in LoraRandomizerNode from 'frontend/backend' to 'fixed/always' for clarity
- Include UI constraints for ComfyUI widgets: minimize vertical space, avoid dynamic height changes, keep UI simple
- Implement LoRA locking to prevent specific LoRAs from being changed during randomization
- Add visual styling for locked state with amber accents and distinct backgrounds
- Introduce `roll_mode` configuration with 'backend' (execute current selection while generating new) and 'frontend' (execute newly generated selection) behaviors
- Move LoraPoolNode to 'Lora Manager/randomizer' category and remove standalone class mappings
- Standardize RETURN_NAMES in LoraRandomizerNode for consistency
- Import and register two new nodes: LoraDemoNode and LoraRandomizerNode
- Update import exception handling for better readability with multi-line formatting
- Add comprehensive documentation file `docs/custom-node-ui-output.md` for UI output usage in custom nodes
- Ensure proper node registration in NODE_CLASS_MAPPINGS for ComfyUI integration
- Maintain backward compatibility with existing node structure and import fallbacks
- Update documentation to reflect new widget filename `lora-manager-widgets.js`
- Remove `LoraManagerDemoNode` import and registration from `__init__.py`
- Translate development guide from Chinese to English for broader accessibility
- Clean up obsolete demo references to align with actual widget implementation
The SaveImage class has been renamed to SaveImageLM to better reflect its purpose within the Lora Manager module. This change ensures consistent naming across import statements, class mappings, and the actual class definition, improving code readability and maintainability.
- Simplify and consolidate the logic for processing trigger words and groups
- Remove redundant code paths and improve maintainability
- Ensure consistent behavior between list and string trigger data inputs
- Preserve existing functionality for strength adjustment and group mode
- Add CheckpointLoaderKJ to NODE_EXTRACTORS mapping for KJNodes support
- Enhance model filename generation in SaveImage to handle different data types
- Add proper type checking and fallback for model metadata values
- Improve robustness when processing checkpoint paths for filename generation
Add `allow_strength_adjustment` parameter to enable mouse wheel adjustment of trigger word strengths. When enabled, strength values are preserved and can be modified interactively. Also improves trigger word parsing by handling whitespace more consistently and adding debug logging for trigger data inspection.
- Extract and preserve strength values from trigger words in format "(word:strength)"
- Maintain strength formatting when filtering active trigger words in both group and individual modes
- Update active state tracking to handle strength-modified words correctly
- Ensure backward compatibility with existing trigger word formats
Remove direct imports of IO type constants from comfy.comfy_types and replace them with string literals "STRING" in input type definitions and return types. This improves code portability and reduces dependency on external type definitions.
Changes made across multiple files:
- Remove `from comfy.comfy_types import IO` imports
- Replace `IO.STRING` with "STRING" in INPUT_TYPES and RETURN_TYPES
- Move CLIPTextEncode import to function scope in prompt.py for better dependency management
This refactor maintains the same functionality while making the code more self-contained and reducing external dependencies.
- Implemented the WanVideo Lora Select node in Python with input handling for low memory loading and LORA syntax processing.
- Updated the JavaScript side to register the new node and manage its widget interactions.
- Enhanced constants files to include the new node type and its corresponding ID.
- Modified existing Lora Loader and Stacker references to accommodate the new node in various workflows and UI components.
- Added example workflow JSON for the new node to demonstrate its usage.
