refactor: Implement base model routes and services for LoRA and Checkpoint

- 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.

py/routes/misc_routes.py

@@ -633,9 +633,8 @@ class MiscRoutes:
                 }, status=400)
             
             # Get both lora and checkpoint scanners
-            registry = ServiceRegistry.get_instance()
-            lora_scanner = await registry.get_lora_scanner()
-            checkpoint_scanner = await registry.get_checkpoint_scanner()
+            lora_scanner = await ServiceRegistry.get_lora_scanner()
+            checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
             
             # If modelVersionId is provided, check for specific version
             if model_version_id_str: