feat(ui): auto-detect HIGH/LOW badges and auto-tag filters (#918)

- Backend auto-tag extraction service: detect HIGH/LOW (Wan-only), I2V/T2V/TI2V,
  Lightning/Turbo from filename, base_model, and CivitAI version name
- HIGH/LOW badge in card footer (inline before version name), color-coded:
  blue for HIGH, teal for LOW; abbreviated to H/L in medium/compact density
- Auto-tag filter panel (I2V, T2V, TI2V, Lightning, Turbo) with tri-state
  include/exclude filtering
- Full filter pipeline: FilterCriteria → ModelFilterSet → baseModelApi params
- AUTO_TAG_GROUPS exported for frontend use
- 19 unit tests for auto-tag extraction edge cases

py/services/lora_service.py

@@ -5,6 +5,7 @@ from typing import Dict, List, Optional
 
 from .base_model_service import BaseModelService
 from .model_query import resolve_sub_type
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import LoraMetadata
 from ..config import config
 
@@ -57,6 +58,7 @@ class LoraService(BaseModelService):
             "civitai": self.filter_civitai_data(
                 lora_data.get("civitai", {}), minimal=True
             ),
+            "auto_tags": lora_data.get("auto_tags") or extract_auto_tags(lora_data),
         }
 
     async def _apply_specific_filters(self, data: List[Dict], **kwargs) -> List[Dict]: