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.
- Added a new optional parameter `custom_prompt` to the SaveImage class methods to allow users to override the default prompt.
- Updated the `format_metadata` method to utilize the custom prompt if provided.
- Modified the `save_images` and `process_image` methods to accept and pass the custom prompt through the workflow processing.
- Updated the INPUT_TYPES to accept multiple images and modified the corresponding processing methods.
- Introduced a new format_filename method to handle dynamic filename generation using metadata patterns.
- Replaced save_workflow_json with embed_workflow for better clarity in saving workflow metadata.
- Improved directory handling and filename generation logic to ensure proper file saving.
- Updated RETURN_TYPES and RETURN_NAMES to include active LoRAs.
- Introduced active_loras list to track active LoRAs and their strengths.
- Formatted active_loras for return as a string in the format <lora:lora_name:strength>.
