This commit resolves the semantic confusion around the model_type field by
clearly distinguishing between:
- scanner_type: architecture-level (lora/checkpoint/embedding)
- sub_type: business-level subtype (lora/locon/dora/checkpoint/diffusion_model/embedding)
Backend Changes:
- Rename model_type to sub_type in CheckpointMetadata and EmbeddingMetadata
- Add resolve_sub_type() and normalize_sub_type() in model_query.py
- Update checkpoint_scanner to use _resolve_sub_type()
- Update service format_response to include both sub_type and model_type
- Add VALID_*_SUB_TYPES constants with backward compatible aliases
Frontend Changes:
- Add MODEL_SUBTYPE_DISPLAY_NAMES constants
- Keep MODEL_TYPE_DISPLAY_NAMES as backward compatible alias
Testing:
- Add 43 new tests covering sub_type resolution and API response
Documentation:
- Add refactoring todo document to docs/technical/
BREAKING CHANGE: None - full backward compatibility maintained
- 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.
