Move the 'empty/no LoRA' cycling functionality from the LoRA Pool node
to the Lora Cycler widget for cleaner architecture:
Frontend changes:
- Add include_no_lora field to CyclerConfig interface
- Add includeNoLora state and logic to useLoraCyclerState composable
- Add toggle UI in LoraCyclerSettingsView with special styling
- Show 'No LoRA' entry in LoraListModal when enabled
- Update LoraCyclerWidget to integrate new logic
Backend changes:
- lora_cycler.py reads include_no_lora from config
- Calculate effective_total_count (actual count + 1 when enabled)
- Return empty lora_stack when on No LoRA position
- Return actual LoRA count in total_count (not effective count)
Reverted files to pre-PR state:
- lora_loader.py, lora_pool.py, lora_randomizer.py, lora_stacker.py
- lora_routes.py, lora_service.py
- LoraPoolWidget.vue and related files
Related to PR #861
Co-authored-by: dogatech <dogatech@dogatech.home>
- Change `STRING` input type to `AUTOCOMPLETE_TEXT_LORAS` in LoraManagerLoader, LoraStacker, and WanVideoLoraSelectLM nodes for LoRA syntax input
- Change `STRING` input type to `AUTOCOMPLETE_TEXT_EMBEDDINGS` in PromptLoraManager node for prompt input
- Remove manual multiline, autocomplete, and dynamicPrompts configurations in favor of built-in autocomplete types
- Update placeholder text for consistency across nodes
- Remove unused `setupInputWidgetWithAutocomplete` mock from frontend tests
- Add Vue app cleanup logic to prevent memory leaks in widget management
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.
- 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>.
- Introduced logging to track unexpected formats in LoRA and trigger word data.
- Refactored LoRA processing to support both old and new kwargs formats in LoraLoader and LoraStacker.
- Enhanced trigger word processing to handle different data formats in TriggerWordToggle.
- Improved code readability and maintainability by extracting common logic into helper methods.
