refactor: unify model_type semantics by introducing sub_type field

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

py/utils/constants.py

@@ -45,8 +45,13 @@ SUPPORTED_MEDIA_EXTENSIONS = {
     "videos": [".mp4", ".webm"],
 }
 
-# Valid Lora types
-VALID_LORA_TYPES = ["lora", "locon", "dora"]
+# Valid sub-types for each scanner type
+VALID_LORA_SUB_TYPES = ["lora", "locon", "dora"]
+VALID_CHECKPOINT_SUB_TYPES = ["checkpoint", "diffusion_model"]
+VALID_EMBEDDING_SUB_TYPES = ["embedding"]
+
+# Backward compatibility alias
+VALID_LORA_TYPES = VALID_LORA_SUB_TYPES
 
 # Supported Civitai model types for user model queries (case-insensitive)
 CIVITAI_USER_MODEL_TYPES = [