- 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 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.
