Add Lora Cycler node that cycles through LoRAs sequentially from a filtered pool. Supports configurable sort order, strength settings, and persists cycle progress across workflow save/load.
Backend:
- New LoraCyclerNode with cycle() method
- New /api/lm/loras/cycler-list endpoint
- LoraService.get_cycler_list() for filtered/sorted list
Frontend:
- LoraCyclerWidget with Vue.js component
- useLoraCyclerState composable
- LoraCyclerSettingsView for UI display
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
- 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
- Pass ModelUpdateService to CheckpointService, EmbeddingService, and LoraService constructors
- Add has_update query parameter filter to model listing handler
- Update BaseModelService to accept optional update_service parameter
These changes enable model update functionality across different model types and provide filtering capability for models with available updates.
- Updated all relevant routes in `stats_routes.py` and `update_routes.py` to include the new '/api/lm/' prefix for consistency.
- Modified API endpoint configurations in `apiConfig.js` to reflect the new structure, ensuring all CRUD and bulk operations are correctly routed.
- Adjusted fetch calls in various components and managers to utilize the updated API paths, including recipe, model, and example image operations.
- Ensured all instances of the old API paths were replaced with the new '/api/lm/' prefix across the codebase for uniformity and to prevent broken links.
- Added AutoComplete class to handle input suggestions based on user input.
- Integrated TextAreaCaretHelper for accurate positioning of the dropdown.
- Enhanced dropdown styling with a new color scheme and custom scrollbar.
- Implemented dynamic loading of preview tooltips for selected items.
- Added keyboard navigation support for dropdown items.
- Included functionality to insert selected items into the input field with usage tips.
- Created a separate TextAreaCaretHelper module for managing caret position calculations.
- Added BaseModelRoutes class to handle common routes and logic for model types.
- Created CheckpointRoutes class inheriting from BaseModelRoutes for checkpoint-specific routes.
- Implemented CheckpointService class for handling checkpoint-related data and operations.
- Developed LoraService class for managing LoRA-specific functionalities.
- Introduced ModelServiceFactory to manage service and route registrations for different model types.
- Established methods for fetching, filtering, and formatting model data across services.
- Integrated CivitAI metadata handling within model routes and services.
- Added pagination and filtering capabilities for model data retrieval.
- Implement WebSocket route for initialization progress updates
- Create initialization component with progress bar and stages
- Add styles for initialization UI
- Update base template to include initialization component
- Enhance model scanner to broadcast progress during initialization
- Introduced a new API endpoint to reconnect deleted LoRAs to local files.
- Updated RecipeModal to include UI elements for reconnecting LoRAs, including input fields and buttons.
- Enhanced CSS styles for deleted badges and reconnect containers to improve user experience.
- Implemented event handling for reconnect actions, including input validation and API calls.
- Updated recipe data handling to reflect changes after reconnecting LoRAs.
- Updated LoraRoutes to better check cache initialization status and handle loading states.
- Added logging for successful cache loading and error handling for cache retrieval failures.
- Enhanced base.html and loras.html templates to display a loading spinner and initialization notice during cache setup.
- Improved user experience by ensuring the loading notice is displayed appropriately based on initialization state.
- Removed the logic for fetching and formatting recipes from the cache.
- Updated the response to return an empty list for recipes when no data is present, simplifying the flow.
- Adjusted comments for clarity regarding the new behavior.
