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

locales/de.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "Kein Credit erforderlich",
             "allowSellingGeneratedContent": "Verkauf erlaubt",
             "noTags": "Keine Tags",
+            "autoTags": "Auto-Tags",
             "noBaseModelMatches": "Keine Basismodelle entsprechen der aktuellen Suche.",
             "clearAll": "Alle Filter löschen",
             "any": "Beliebig",

locales/en.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "No Credit Required",
             "allowSellingGeneratedContent": "Allow Selling",
             "noTags": "No tags",
+            "autoTags": "Auto Tags",
             "noBaseModelMatches": "No base models match the current search.",
             "clearAll": "Clear All Filters",
             "any": "Any",

locales/es.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "Sin crédito requerido",
             "allowSellingGeneratedContent": "Venta permitida",
             "noTags": "Sin etiquetas",
+            "autoTags": "Etiquetas automáticas",
             "noBaseModelMatches": "Ningún modelo base coincide con la búsqueda actual.",
             "clearAll": "Limpiar todos los filtros",
             "any": "Cualquiera",

locales/fr.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "Crédit non requis",
             "allowSellingGeneratedContent": "Vente autorisée",
             "noTags": "Aucun tag",
+            "autoTags": "Auto-Tags",
             "noBaseModelMatches": "Aucun modèle de base ne correspond à la recherche actuelle.",
             "clearAll": "Effacer tous les filtres",
             "any": "N'importe quel",

locales/he.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "ללא קרדיט נדרש",
             "allowSellingGeneratedContent": "אפשר מכירה",
             "noTags": "ללא תגיות",
+            "autoTags": "תגיות אוטומטיות",
             "noBaseModelMatches": "אין מודלי בסיס התואמים לחיפוש הנוכחי.",
             "clearAll": "נקה את כל המסננים",
             "any": "כלשהו",

locales/ja.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "クレジット不要",
             "allowSellingGeneratedContent": "販売許可",
             "noTags": "タグなし",
+            "autoTags": "自動タグ",
             "noBaseModelMatches": "現在の検索に一致するベースモデルはありません。",
             "clearAll": "すべてのフィルタをクリア",
             "any": "いずれか",

locales/ko.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "크레딧 표기 없음",
             "allowSellingGeneratedContent": "판매 허용",
             "noTags": "태그 없음",
+            "autoTags": "자동 태그",
             "noBaseModelMatches": "현재 검색과 일치하는 베이스 모델이 없습니다.",
             "clearAll": "모든 필터 지우기",
             "any": "아무",

locales/ru.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "Без указания авторства",
             "allowSellingGeneratedContent": "Продажа разрешена",
             "noTags": "Без тегов",
+            "autoTags": "Авто-теги",
             "noBaseModelMatches": "Нет базовых моделей, соответствующих текущему поиску.",
             "clearAll": "Очистить все фильтры",
             "any": "Любой",

locales/zh-CN.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "无需署名",
             "allowSellingGeneratedContent": "允许销售",
             "noTags": "无标签",
+            "autoTags": "自动标签",
             "noBaseModelMatches": "没有基础模型符合当前搜索。",
             "clearAll": "清除所有筛选",
             "any": "任一",

locales/zh-TW.json

@@ -233,6 +233,7 @@
             "noCreditRequired": "無需署名",
             "allowSellingGeneratedContent": "允許銷售",
             "noTags": "無標籤",
+            "autoTags": "自動標籤",
             "noBaseModelMatches": "沒有基礎模型符合目前的搜尋。",
             "clearAll": "清除所有篩選",
             "any": "任一",

py/routes/handlers/model_handlers.py

@@ -301,6 +301,15 @@ class ModelListingHandler:
         for tag in exclude_tags:
             if tag:
                 tag_filters[tag] = "exclude"
+
+        auto_tag_filters: Dict[str, str] = {}
+        for tag in request.query.getall("auto_tag_include", []):
+            if tag:
+                auto_tag_filters[tag] = "include"
+        for tag in request.query.getall("auto_tag_exclude", []):
+            if tag:
+                auto_tag_filters[tag] = "exclude"
+
         favorites_only = request.query.get("favorites_only", "false").lower() == "true"
 
         search_options = {
@@ -367,6 +376,7 @@ class ModelListingHandler:
             "fuzzy_search": fuzzy_search,
             "base_models": base_models,
             "tags": tag_filters,
+            "auto_tags": auto_tag_filters,
             "tag_logic": tag_logic,
             "search_options": search_options,
             "hash_filters": hash_filters,

py/services/auto_tag_service.py

@@ -0,0 +1,121 @@
+"""
+Auto-tag extraction service for model cards.
+
+Extracts implicit model attributes (HIGH/LOW, I2V/T2V/TI2V, Lightning, Turbo)
+from filename, base_model, and CivitAI version name — no manual tagging required.
+"""
+
+from __future__ import annotations
+
+import re
+from typing import Dict, List, Set
+
+# ── Tag category definitions ──────────────────────────────────────────
+# Each category maps a display label to a regex pattern.
+# Patterns are case-insensitive and matched against filename, base_model,
+# and civitai version name.
+
+# Use (?<![a-zA-Z0-9]) and (?![a-zA-Z0-9]) instead of \b because
+# Python's \b treats underscore as a word character, so \bHIGH\b
+# won't match '_HIGH_' in filenames.
+_B = r"(?<![a-zA-Z0-9])"   # left boundary
+_E = r"(?![a-zA-Z0-9])"    # right boundary
+
+AUTO_TAG_CATEGORIES: Dict[str, str] = {
+    "HIGH":      _B + r"HIGH" + _E,
+    "LOW":       _B + r"(?<!F)LOW" + _E,
+    "I2V":       _B + r"I2V" + _E,
+    "T2V":       _B + r"T2V" + _E,
+    "TI2V":      _B + r"TI2V" + _E,
+    "Lightning": _B + r"Lightning" + _E,
+    "Turbo":     _B + r"Turbo" + _E,
+}
+
+# Tags that belong to the "mode" group (HIGH/LOW)
+MODE_TAGS = {"HIGH", "LOW"}
+
+# Tags that belong to the "video mode" group (I2V/T2V/TI2V)
+VIDEO_MODE_TAGS = {"I2V", "T2V", "TI2V"}
+
+# Tags that belong to the "speed/optimization" group
+SPEED_TAGS = {"Lightning", "Turbo"}
+
+# ── Display category groups (for settings UI) ─────────────────────────
+
+AUTO_TAG_GROUPS = {
+    "mode":   {"HIGH", "LOW"},
+    "video":  {"I2V", "T2V", "TI2V"},
+    "speed":  {"Lightning", "Turbo"},
+}
+
+# Default enabled categories
+DEFAULT_ENABLED_GROUPS = {"mode", "video"}
+
+
+def _collect_sources(model_data: Dict) -> List[str]:
+    """Collect all text sources from model data for tag matching."""
+    sources: List[str] = []
+
+    file_name = model_data.get("file_name", "")
+    if file_name:
+        sources.append(file_name)
+
+    base_model = model_data.get("base_model", "")
+    if base_model:
+        sources.append(base_model)
+
+    civitai = model_data.get("civitai", {})
+    if isinstance(civitai, dict):
+        version_name = civitai.get("name", "")
+        if version_name:
+            sources.append(version_name)
+
+    return sources
+
+
+def extract_auto_tags(model_data: Dict) -> List[str]:
+    """Extract auto-detected tags from model metadata.
+
+    Matches predefined patterns against filename, base_model, and
+    CivitAI version name. Returns a sorted, deduplicated list of tag labels.
+
+    HIGH/LOW tags are only returned when the base_model indicates a Wan
+    family model — no other model architecture uses this distinction.
+
+    Args:
+        model_data: Model metadata dict with keys:
+            file_name, base_model, civitai (with optional 'name' field).
+
+    Returns:
+        Sorted list of unique auto-tag strings (e.g. ["I2V"]).
+    """
+    sources = _collect_sources(model_data)
+    if not sources:
+        return []
+
+    base_model = model_data.get("base_model", "")
+    is_wan = "wan" in base_model.lower()
+
+    found: Set[str] = set()
+
+    for label, pattern in AUTO_TAG_CATEGORIES.items():
+        # HIGH/LOW are Wan-specific — skip for non-Wan to avoid noise
+        if label in ("HIGH", "LOW"):
+            if not is_wan:
+                continue
+            # Use case-insensitive character class + case-sensitive boundary,
+            # so "HighNoise" (camelCase) matches but "highlight" doesn't.
+            # Boundary: not followed by lowercase letter (= word has ended).
+            ci = "".join(f"[{c.lower()}{c.upper()}]" for c in label)
+            if label == "LOW":
+                regex = re.compile(r"(?<![Ff])" + ci + r"(?![a-z])")
+            else:
+                regex = re.compile(ci + r"(?![a-z])")
+        else:
+            regex = re.compile(pattern, re.IGNORECASE)
+        for source in sources:
+            if regex.search(source):
+                found.add(label)
+                break
+
+    return sorted(found)

py/services/base_model_service.py

@@ -77,6 +77,7 @@ class BaseModelService(ABC):
         base_models: list = None,
         model_types: list = None,
         tags: Optional[Dict[str, str]] = None,
+        auto_tags: Optional[Dict[str, str]] = None,
         search_options: dict = None,
         hash_filters: dict = None,
         favorites_only: bool = False,
@@ -95,6 +96,11 @@ class BaseModelService(ABC):
             sorted_data = await self._fetch_with_usage_sort(sort_params)
         else:
             sorted_data = await self.cache_repository.fetch_sorted(sort_params)
+        # Pre-compute auto_tags for every item — needed for both filtering
+        # and display. Computation is cheap (string regex on 2-3 fields).
+        from .auto_tag_service import extract_auto_tags
+        for item in sorted_data:
+            item["auto_tags"] = extract_auto_tags(item)
         fetch_duration = time.perf_counter() - t0
         initial_count = len(sorted_data)
 
@@ -110,6 +116,7 @@ class BaseModelService(ABC):
                 base_models=base_models,
                 model_types=model_types,
                 tags=tags,
+                auto_tags=auto_tags,
                 favorites_only=favorites_only,
                 search_options=search_options,
                 tag_logic=tag_logic,
@@ -354,6 +361,7 @@ class BaseModelService(ABC):
         base_models: list = None,
         model_types: list = None,
         tags: Optional[Dict[str, str]] = None,
+        auto_tags: Optional[Dict[str, str]] = None,
         favorites_only: bool = False,
         search_options: dict = None,
         tag_logic: str = "any",
@@ -367,6 +375,7 @@ class BaseModelService(ABC):
             base_models=base_models,
             model_types=model_types,
             tags=tags,
+            auto_tags=auto_tags,
             favorites_only=favorites_only,
             search_options=normalized_options,
             tag_logic=tag_logic,

py/services/checkpoint_service.py

@@ -3,6 +3,7 @@ import logging
 from typing import Dict
 
 from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import CheckpointMetadata
 from ..config import config
 
@@ -45,7 +46,8 @@ class CheckpointService(BaseModelService):
             "exclude": bool(checkpoint_data.get("exclude", False)),
             "update_available": bool(checkpoint_data.get("update_available", False)),
             "skip_metadata_refresh": bool(checkpoint_data.get("skip_metadata_refresh", False)),
-            "civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True)
+            "civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True),
+            "auto_tags": checkpoint_data.get("auto_tags") or extract_auto_tags(checkpoint_data),
         }
     
     def find_duplicate_hashes(self) -> Dict:

py/services/embedding_service.py

@@ -3,6 +3,7 @@ import logging
 from typing import Dict
 
 from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import EmbeddingMetadata
 from ..config import config
 
@@ -45,7 +46,8 @@ class EmbeddingService(BaseModelService):
             "exclude": bool(embedding_data.get("exclude", False)),
             "update_available": bool(embedding_data.get("update_available", False)),
             "skip_metadata_refresh": bool(embedding_data.get("skip_metadata_refresh", False)),
-            "civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True)
+            "civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True),
+            "auto_tags": embedding_data.get("auto_tags") or extract_auto_tags(embedding_data),
         }
     
     def find_duplicate_hashes(self) -> Dict:

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]:

py/services/model_query.py

@@ -96,6 +96,7 @@ class FilterCriteria:
     folder_exclude: Optional[Sequence[str]] = None
     base_models: Optional[Sequence[str]] = None
     tags: Optional[Dict[str, str]] = None
+    auto_tags: Optional[Dict[str, str]] = None
     favorites_only: bool = False
     search_options: Optional[Dict[str, Any]] = None
     model_types: Optional[Sequence[str]] = None
@@ -359,10 +360,37 @@ class ModelFilterSet:
                 ]
             model_types_duration = time.perf_counter() - t0
 
+        auto_tags_duration = 0
+        auto_tag_filters = criteria.auto_tags or {}
+        if auto_tag_filters:
+            t0 = time.perf_counter()
+            include_at = set()
+            exclude_at = set()
+            for tag, state in auto_tag_filters.items():
+                if not tag:
+                    continue
+                if state == "exclude":
+                    exclude_at.add(tag)
+                else:
+                    include_at.add(tag)
+
+            if include_at:
+                items = [
+                    item for item in items
+                    if any(tag in include_at for tag in (item.get("auto_tags") or []))
+                ]
+
+            if exclude_at:
+                items = [
+                    item for item in items
+                    if not any(tag in exclude_at for tag in (item.get("auto_tags") or []))
+                ]
+            auto_tags_duration = time.perf_counter() - t0
+
         duration = time.perf_counter() - overall_start
         if duration > 0.1:  # Only log if it's potentially slow
             logger.debug(
-                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs). "
+                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs, auto_tags: %.3fs). "
                 "Count: %d -> %d",
                 duration,
                 sfw_duration,
@@ -371,6 +399,7 @@ class ModelFilterSet:
                 base_models_duration,
                 tags_duration,
                 model_types_duration,
+                auto_tags_duration,
                 initial_count,
                 len(items),
             )

static/css/components/card.css

@@ -507,21 +507,96 @@
     background: rgba(0,0,0,0.18); /* Optional: subtle background for contrast */
 }
 
+/* Version row — flex container for badges + version names */
+.version-row {
+    display: flex;
+    flex-wrap: wrap;
+    align-items: center;
+    gap: 3px;
+    margin-top: 2px;
+}
+
+/* Badge + version-name binding: they wrap as a single unit */
+.badge-version-unit {
+    display: inline-flex;
+    align-items: center;
+    gap: 3px;
+    min-width: 0;
+    flex-shrink: 0;
+}
+
 /* Medium density adjustments for version name */
 .medium-density .version-name {
     font-size: 0.8em;
 }
 
+.medium-density .badge-version-unit .version-name {
+    max-width: 90px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
 /* Compact density adjustments for version name */
 .compact-density .version-name {
     font-size: 0.75em;
 }
 
-/* Hide civitai version name when setting is disabled */
+.compact-density .badge-version-unit .version-name {
-body.hide-card-version .civitai-version {
+    max-width: 70px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
+.medium-density .version-row {
+    gap: 2px;
+}
+
+/* HIGH / LOW badges — shown inline before version name in card footer */
+.hl-badge {
+    display: inline-block;
+    font-size: 0.7em;
+    font-weight: 600;
+    line-height: 1.1;
+    padding: 1px 5px;
+    border-radius: var(--border-radius-xs);
+    border: 1px solid rgba(255, 255, 255, 0.2);
+    white-space: nowrap;
+}
+
+.hl-badge--high {
+    color: oklch(75% 0.12 230);
+    background: oklch(55% 0.15 240 / 0.25);
+    border-color: oklch(60% 0.18 250 / 0.3);
+}
+
+.hl-badge--low {
+    color: oklch(78% 0.10 185);
+    background: oklch(50% 0.10 190 / 0.25);
+    border-color: oklch(55% 0.12 195 / 0.3);
+}
+
+.medium-density .hl-badge {
+    font-size: 0.65em;
+}
+
+.compact-density .hl-badge {
+    font-size: 0.62em;
+    padding: 0px 4px;
+}
+
+/* Hide version-related elements when setting is disabled */
+body.hide-card-version .civitai-version,
+body.hide-card-version .hl-badge {
     display: none;
 }
 
+/* Compact density adjustments for version name */
+.compact-density .version-name {
+    font-size: 0.75em;
+}
+
 /* Prevent text selection on cards and interactive elements */
 .model-card,
 .model-card *,

static/js/api/baseModelApi.js

@@ -978,6 +978,16 @@ export class BaseModelApiClient {
                 });
             }
 
+            if (pageState.filters.autoTags && Object.keys(pageState.filters.autoTags).length > 0) {
+                Object.entries(pageState.filters.autoTags).forEach(([tag, state]) => {
+                    if (state === 'include') {
+                        params.append('auto_tag_include', tag);
+                    } else if (state === 'exclude') {
+                        params.append('auto_tag_exclude', tag);
+                    }
+                });
+            }
+
             if (pageState.filters.baseModel && pageState.filters.baseModel.length > 0) {
                 // Check for empty wildcard marker - if present, no models should match
                 const EMPTY_WILDCARD_MARKER = '__EMPTY_WILDCARD_RESULT__';

static/js/components/shared/ModelCard.js

@@ -644,8 +644,23 @@ export function createModelCard(model, modelType) {
             <div class="card-footer">
                 <div class="model-info">
                     <span class="model-name" title="${getDisplayName(model).replace(/"/g, '&quot;')}">${getDisplayName(model)}</span>
-                    <div>
+                    <div class="version-row">
-                        ${model.civitai?.name ? `<span class="version-name civitai-version">${model.civitai.name}</span>` : ''}
+                        ${(() => {
+                            const autoTags = model.auto_tags || [];
+                            const hlTags = autoTags.filter(t => t === 'HIGH' || t === 'LOW');
+                            const hasVersionName = model.civitai?.name;
+                            if (!hlTags.length && !hasVersionName) return '';
+                            const density = state.global.settings.display_density || 'default';
+                            const shortLabels = density === 'medium' || density === 'compact';
+                            const badges = hlTags.map(t => {
+                                const cls = t === 'HIGH' ? 'hl-badge hl-badge--high' : 'hl-badge hl-badge--low';
+                                const label = shortLabels ? (t === 'HIGH' ? 'H' : 'L') : t;
+                                const titleAttr = shortLabels ? ` title="${t}"` : '';
+                                return `<span class="${cls}"${titleAttr}>${label}</span>`;
+                            }).join('');
+                            const versionHtml = hasVersionName ? `<span class="version-name civitai-version">${model.civitai.name}</span>` : '';
+                            return `<span class="badge-version-unit">${badges}${versionHtml}</span>`;
+                        })()}
                         ${hasUsageCount ? `<span class="version-name" title="${translate('modelCard.usage.timesUsed', {}, 'Times used')}">${model.usage_count}×</span>` : ''}
                     </div>
                 </div>

static/js/managers/FilterManager.js

@@ -70,6 +70,9 @@ export class FilterManager {
         // Initialize tag logic toggle
         this.initializeTagLogicToggle();
 
+        // Create auto-tag filter section (I2V, T2V, TI2V, Lightning, Turbo)
+        this.createAutoTagFilters();
+
         // Add click handler for filter button
         if (this.filterButton) {
             this.filterButton.addEventListener('click', () => {
@@ -480,6 +483,58 @@ export class FilterManager {
         }
     }
 
+    AUTO_TAG_FILTER_TAGS = ['I2V', 'T2V', 'TI2V', 'Lightning', 'Turbo'];
+
+    createAutoTagFilters() {
+        const container = document.getElementById('autoTagFilterTags');
+        if (container) return;
+
+        const modelTypeSection = document.getElementById('modelTypeTags')?.closest('.filter-section');
+        if (!modelTypeSection) return;
+
+        const section = document.createElement('div');
+        section.className = 'filter-section';
+        section.innerHTML = `
+            <h4>${translate('header.filter.autoTags', {}, 'Auto Tags')}</h4>
+            <div class="filter-tags" id="autoTagFilterTags"></div>
+        `;
+        modelTypeSection.parentNode.insertBefore(section, modelTypeSection.nextSibling);
+
+        const tagsContainer = document.getElementById('autoTagFilterTags');
+        this.AUTO_TAG_FILTER_TAGS.forEach(tag => {
+            const el = document.createElement('div');
+            el.className = 'filter-tag auto-tag-filter';
+            el.dataset.autoTag = tag;
+            el.textContent = tag;
+
+            // Restore previous state
+            const state = (this.filters.autoTags && this.filters.autoTags[tag]) || 'none';
+            this._applyTriState(el, state);
+
+            el.addEventListener('click', async () => {
+                const current = (this.filters.autoTags && this.filters.autoTags[tag]) || 'none';
+                const next = current === 'none' ? 'include' : current === 'include' ? 'exclude' : 'none';
+                if (!this.filters.autoTags) this.filters.autoTags = {};
+                if (next === 'none') {
+                    delete this.filters.autoTags[tag];
+                } else {
+                    this.filters.autoTags[tag] = next;
+                }
+                this._applyTriState(el, next);
+                this.updateActiveFiltersCount();
+                await this.applyFilters(false);
+            });
+
+            tagsContainer.appendChild(el);
+        });
+    }
+
+    _applyTriState(el, state) {
+        el.classList.remove('active', 'exclude');
+        if (state === 'include') el.classList.add('active');
+        else if (state === 'exclude') el.classList.add('exclude');
+    }
+
     toggleFilterPanel() {
         if (this.filterPanel) {
             const isHidden = this.filterPanel.classList.contains('hidden');
@@ -540,6 +595,13 @@ export class FilterManager {
             this.updateLicenseSelections();
         }
         this.updateModelTypeSelections();
+
+        const autoTagEls = document.querySelectorAll('.auto-tag-filter');
+        autoTagEls.forEach(el => {
+            const tag = el.dataset.autoTag;
+            const state = (this.filters.autoTags && this.filters.autoTags[tag]) || 'none';
+            this._applyTriState(el, state);
+        });
     }
 
     updateModelTypeSelections() {
@@ -556,11 +618,12 @@ export class FilterManager {
 
     updateActiveFiltersCount() {
         const tagFilterCount = this.filters.tags ? Object.keys(this.filters.tags).length : 0;
+        const autoTagFilterCount = this.filters.autoTags ? Object.keys(this.filters.autoTags).length : 0;
         const licenseFilterCount = this.filters.license ? Object.keys(this.filters.license).length : 0;
         const modelTypeFilterCount = this.filters.modelTypes.length;
         // Exclude EMPTY_WILDCARD_MARKER from base model count
         const baseModelCount = this.filters.baseModel.filter(m => m !== EMPTY_WILDCARD_MARKER).length;
-        const totalActiveFilters = baseModelCount + tagFilterCount + licenseFilterCount + modelTypeFilterCount;
+        const totalActiveFilters = baseModelCount + tagFilterCount + autoTagFilterCount + licenseFilterCount + modelTypeFilterCount;
 
         if (this.activeFiltersCount) {
             if (totalActiveFilters > 0) {
@@ -652,6 +715,7 @@ export class FilterManager {
             ...this.filters,
             baseModel: [],
             tags: {},
+            autoTags: {},
             license: {},
             modelTypes: [],
             tagLogic: 'any'
@@ -721,6 +785,7 @@ export class FilterManager {
 
     hasActiveFilters() {
         const tagCount = this.filters.tags ? Object.keys(this.filters.tags).length : 0;
+        const autoTagCount = this.filters.autoTags ? Object.keys(this.filters.autoTags).length : 0;
         const licenseCount = this.filters.license ? Object.keys(this.filters.license).length : 0;
         const modelTypeCount = this.filters.modelTypes.length;
         // Exclude EMPTY_WILDCARD_MARKER from base model count
@@ -728,6 +793,7 @@ export class FilterManager {
         return (
             baseModelCount > 0 ||
             tagCount > 0 ||
+            autoTagCount > 0 ||
             licenseCount > 0 ||
             modelTypeCount > 0
         );
@@ -739,6 +805,7 @@ export class FilterManager {
             ...source,
             baseModel: Array.isArray(source.baseModel) ? [...source.baseModel] : [],
             tags: this.normalizeTagFilters(source.tags),
+            autoTags: this.normalizeTagFilters(source.autoTags),
             license: this.shouldShowLicenseFilters() ? this.normalizeLicenseFilters(source.license) : {},
             modelTypes: this.normalizeModelTypeFilters(source.modelTypes),
             tagLogic: source.tagLogic || 'any'
@@ -822,6 +889,7 @@ export class FilterManager {
             ...this.filters,
             baseModel: [...(this.filters.baseModel || [])],
             tags: { ...(this.filters.tags || {}) },
+            autoTags: { ...(this.filters.autoTags || {}) },
             license: { ...(this.filters.license || {}) },
             modelTypes: [...(this.filters.modelTypes || [])],
             tagLogic: this.filters.tagLogic || 'any'

static/js/utils/constants.js

@@ -500,6 +500,18 @@ export function clearDynamicBaseModels() {
     dynamicBaseModelsTimestamp = null;
 }
 
+export const AUTO_TAG_GROUPS = {
+    mode: new Set(['HIGH', 'LOW']),
+    video: new Set(['I2V', 'T2V', 'TI2V']),
+    speed: new Set(['Lightning', 'Turbo']),
+};
+
+export const AUTO_TAG_GROUP_LABELS = {
+    mode: 'High / Low',
+    video: 'I2V / T2V / TI2V',
+    speed: 'Lightning / Turbo',
+};
+
 /**
  * Check if dynamic base models cache is valid
  * @returns {boolean}

tests/test_auto_tag_service.py

@@ -0,0 +1,151 @@
+import pytest
+import sys
+import os
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "py"))
+
+from services.auto_tag_service import extract_auto_tags, AUTO_TAG_CATEGORIES
+
+
+class TestExtractAutoTags:
+    def test_file_name_high_i2v(self):
+        result = extract_auto_tags({
+            "file_name": "Shirt_lift_Wan2.2_14B_I2V_HIGH_v1.0",
+            "base_model": "Wan Video 2.2 I2V-A14B",
+            "civitai": {},
+        })
+        assert set(result) == {"HIGH", "I2V"}
+
+    def test_file_name_t2v_low(self):
+        result = extract_auto_tags({
+            "file_name": "my_wan_t2v_low_v2",
+            "base_model": "Wan 2.1",
+            "civitai": {},
+        })
+        assert set(result) == {"LOW", "T2V"}
+
+    def test_file_name_ti2v_high(self):
+        result = extract_auto_tags({
+            "file_name": "wan_ti2v_high_quality",
+            "base_model": "Wan 2.2",
+            "civitai": {},
+        })
+        assert set(result) == {"HIGH", "TI2V"}
+
+    def test_file_name_lightning_turbo(self):
+        result = extract_auto_tags({
+            "file_name": "sdxl_lightning_turbo_v3",
+            "base_model": "SDXL",
+            "civitai": {},
+        })
+        assert set(result) == {"Lightning", "Turbo"}
+
+    def test_base_model_source(self):
+        result = extract_auto_tags({
+            "file_name": "my_lora_v1",
+            "base_model": "Wan Video 2.2 I2V-A14B",
+            "civitai": {},
+        })
+        assert "I2V" in result
+
+    def test_civitai_name_source(self):
+        result = extract_auto_tags({
+            "file_name": "model_v1",
+            "base_model": "Wan",
+            "civitai": {"name": "HIGH Quality"},
+        })
+        assert "HIGH" in result
+
+    def test_no_false_match_flow(self):
+        result = extract_auto_tags({
+            "file_name": "flux_dev_model",
+            "base_model": "Flux.1 D",
+            "civitai": {},
+        })
+        assert "LOW" not in result
+
+    def test_no_false_match_glow(self):
+        result = extract_auto_tags({
+            "file_name": "glow_style_lora",
+            "base_model": "SDXL",
+            "civitai": {},
+        })
+        assert "LOW" not in result
+
+    def test_high_low_only_for_wan(self):
+        """HIGH/LOW should not appear for non-Wan models even in filename."""
+        result = extract_auto_tags({
+            "file_name": "my_model_high_quality_v2",
+            "base_model": "Flux.1 D",
+            "civitai": {"name": "HIGH"},
+        })
+        assert "HIGH" not in result
+        assert "LOW" not in result
+
+    def test_no_distilled(self):
+        result = extract_auto_tags({
+            "file_name": "ltx-2.3-22b-distilled-lora-384",
+            "base_model": "LTXV 2.3",
+            "civitai": {},
+        })
+        assert result == []
+
+    def test_empty(self):
+        result = extract_auto_tags({
+            "file_name": "generic_lora_v1",
+            "base_model": "SDXL",
+            "civitai": {},
+        })
+        assert result == []
+
+    def test_missing_fields(self):
+        result = extract_auto_tags({})
+        assert result == []
+
+    def test_dash_separated(self):
+        result = extract_auto_tags({
+            "file_name": "wan-i2v-high-v2",
+            "base_model": "Wan 2.2",
+            "civitai": {},
+        })
+        assert set(result) == {"HIGH", "I2V"}
+
+    def test_dot_separated(self):
+        result = extract_auto_tags({
+            "file_name": "wan.i2v.high.v2",
+            "base_model": "Wan 2.2",
+            "civitai": {},
+        })
+        assert set(result) == {"HIGH", "I2V"}
+
+    def test_case_insensitive(self):
+        result = extract_auto_tags({
+            "file_name": "WAN_i2v_High",
+            "base_model": "Wan 2.2",
+            "civitai": {},
+        })
+        assert set(result) == {"HIGH", "I2V"}
+
+
+class TestAutoTagCategories:
+    def test_all_patterns_compile(self):
+        import re
+        for label, pattern in AUTO_TAG_CATEGORIES.items():
+            re.compile(pattern, re.IGNORECASE)
+
+    def test_mode_group_tags(self):
+        from services.auto_tag_service import MODE_TAGS
+        assert "HIGH" in MODE_TAGS
+        assert "LOW" in MODE_TAGS
+
+    def test_video_group_tags(self):
+        from services.auto_tag_service import VIDEO_MODE_TAGS
+        assert "I2V" in VIDEO_MODE_TAGS
+        assert "T2V" in VIDEO_MODE_TAGS
+        assert "TI2V" in VIDEO_MODE_TAGS
+
+    def test_default_enabled_groups(self):
+        from services.auto_tag_service import DEFAULT_ENABLED_GROUPS
+        assert "mode" in DEFAULT_ENABLED_GROUPS
+        assert "video" in DEFAULT_ENABLED_GROUPS
+        assert "speed" not in DEFAULT_ENABLED_GROUPS