chore(release): bump version to v1.1.4

- save_metadata_updates now trims/lowercases/dedupes tags on write
- ModelFilterSet tag matching is now case-insensitive (both include/exclude)
- Removed redundant .lower() calls in tag_update_service.py

.docs/batch-import-design.md

@@ -1,153 +0,0 @@
-# Recipe Batch Import Feature Design
-
-## Overview
-Enable users to import multiple images as recipes in a single operation, rather than processing them individually. This feature addresses the need for efficient bulk recipe creation from existing image collections.
-
-## Architecture
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│                        Frontend                                  │
-├─────────────────────────────────────────────────────────────────┤
-│  BatchImportManager.js                                          │
-│  ├── InputCollector (收集URL列表/目录路径)                        │
-│  ├── ConcurrencyController (自适应并发控制)                       │
-│  ├── ProgressTracker (进度追踪)                                   │
-│  └── ResultAggregator (结果汇总)                                  │
-├─────────────────────────────────────────────────────────────────┤
-│  batch_import_modal.html                                        │
-│  └── 批量导入UI组件                                              │
-├─────────────────────────────────────────────────────────────────┤
-│  batch_import_progress.css                                      │
-│  └── 进度显示样式                                                │
-└─────────────────────────────────────────────────────────────────┘
-                              │
-                              ▼
-┌─────────────────────────────────────────────────────────────────┐
-│                        Backend                                   │
-├─────────────────────────────────────────────────────────────────┤
-│  py/routes/handlers/recipe_handlers.py                          │
-│  ├── start_batch_import() - 启动批量导入                         │
-│  ├── get_batch_import_progress() - 查询进度                      │
-│  └── cancel_batch_import() - 取消导入                            │
-├─────────────────────────────────────────────────────────────────┤
-│  py/services/batch_import_service.py                            │
-│  ├── 自适应并发执行                                              │
-│  ├── 结果汇总                                                    │
-│  └── WebSocket进度广播                                           │
-└─────────────────────────────────────────────────────────────────┘
-```
-
-## API Endpoints
-
-| 端点 | 方法 | 说明 |
-|------|------|------|
-| `/api/lm/recipes/batch-import/start` | POST | 启动批量导入，返回 operation_id |
-| `/api/lm/recipes/batch-import/progress` | GET | 查询进度状态 |
-| `/api/lm/recipes/batch-import/cancel` | POST | 取消导入 |
-
-## Backend Implementation Details
-
-### BatchImportService
-
-Location: `py/services/batch_import_service.py`
-
-Key classes:
-- `BatchImportItem`: Dataclass for individual import item
-- `BatchImportProgress`: Dataclass for tracking progress
-- `BatchImportService`: Main service class
-
-Features:
-- Adaptive concurrency control (adjusts based on success/failure rate)
-- WebSocket progress broadcasting
-- Graceful error handling (individual failures don't stop the batch)
-- Result aggregation
-
-### WebSocket Message Format
-
-```json
-{
-    "type": "batch_import_progress",
-    "operation_id": "xxx",
-    "total": 50,
-    "completed": 23,
-    "success": 21,
-    "failed": 2,
-    "skipped": 0,
-    "current_item": "image_024.png",
-    "status": "running"
-}
-```
-
-### Input Types
-
-1. **URL List**: Array of URLs (http/https)
-2. **Local Paths**: Array of local file paths
-3. **Directory**: Path to directory with optional recursive flag
-
-### Error Handling
-
-- Invalid URLs/paths: Skip and record error
-- Download failures: Record error, continue
-- Metadata extraction failures: Mark as "no metadata"
-- Duplicate detection: Option to skip duplicates
-
-## Frontend Implementation Details (TODO)
-
-### UI Components
-
-1. **BatchImportModal**: Main modal with tabs for URLs/Directory input
-2. **ProgressDisplay**: Real-time progress bar and status
-3. **ResultsSummary**: Final results with success/failure breakdown
-
-### Adaptive Concurrency Controller
-
-```javascript
-class AdaptiveConcurrencyController {
-    constructor(options = {}) {
-        this.minConcurrency = options.minConcurrency || 1;
-        this.maxConcurrency = options.maxConcurrency || 5;
-        this.currentConcurrency = options.initialConcurrency || 3;
-    }
-
-    adjustConcurrency(taskDuration, success) {
-        if (success && taskDuration < 1000 && this.currentConcurrency < this.maxConcurrency) {
-            this.currentConcurrency = Math.min(this.currentConcurrency + 1, this.maxConcurrency);
-        }
-        if (!success || taskDuration > 10000) {
-            this.currentConcurrency = Math.max(this.currentConcurrency - 1, this.minConcurrency);
-        }
-        return this.currentConcurrency;
-    }
-}
-```
-
-## File Structure
-
-```
-Backend (implemented):
-├── py/services/batch_import_service.py            # 后端服务
-├── py/routes/handlers/batch_import_handler.py     # API处理器 (added to recipe_handlers.py)
-├── tests/services/test_batch_import_service.py    # 单元测试
-└── tests/routes/test_batch_import_routes.py       # API集成测试
-
-Frontend (TODO):
-├── static/js/managers/BatchImportManager.js       # 主管理器
-├── static/js/managers/batch/                       # 子模块
-│   ├── ConcurrencyController.js                    # 并发控制
-│   ├── ProgressTracker.js                          # 进度追踪
-│   └── ResultAggregator.js                         # 结果汇总
-├── static/css/components/batch-import-modal.css   # 样式
-└── templates/components/batch_import_modal.html    # Modal模板
-```
-
-## Implementation Status
-
-- [x] Backend BatchImportService
-- [x] Backend API handlers
-- [x] WebSocket progress broadcasting
-- [x] Unit tests
-- [x] Integration tests
-- [ ] Frontend BatchImportManager
-- [ ] Frontend UI components
-- [ ] E2E tests

.github/ISSUE_TEMPLATE/feature_request.md

@@ -13,8 +13,5 @@ A clear and concise description of what the problem is. Ex. I'm always frustrate
 **Describe the solution you'd like**
 A clear and concise description of what you want to happen.
 
-**Describe alternatives you've considered**
-A clear and concise description of any alternative solutions or features you've considered.
-
 **Additional context**
 Add any other context or screenshots about the feature request here.

.gitignore

@@ -12,12 +12,14 @@ coverage/
 .coverage
 model_cache/
 
-# agent
+# agent / dev tooling
 .opencode/
 .claude/
 .sisyphus/
 .codex
 .omo
+reasonix.toml
+.codegraph/
 
 # Vue widgets development cache (but keep build output)
 vue-widgets/node_modules/
@@ -26,3 +28,6 @@ vue-widgets/dist/
 
 # Hypothesis test cache
 .hypothesis/
+
+# Working/research notes (not committed)
+.docs/

.omo/plans/embeddings-hybrid-approach.md

@@ -0,0 +1,181 @@
+# Embeddings Usage Tracking — Hybrid Approach (Plan C)
+
+> **Status**: Reference document for future implementation
+> **Current implementation**: Plan A (prompt text parsing only, see `usage_stats.py:_process_embeddings`)
+> **Next step**: Add Plan B as a supplement when edge-case coverage is needed
+
+## Problem
+
+Embeddings in ComfyUI are not loaded through dedicated ComfyUI nodes like LoRAs or
+Checkpoints. They are resolved during CLIP tokenization when the prompt text contains
+`embedding:<name>` syntax (see `comfy/sd1_clip.py:SDTokenizer.tokenize_with_weights`).
+
+This means the existing metadata_collector hook (which intercepts node execution via
+`_map_node_over_list`) cannot capture embeddings the same way it captures LoRAs and
+checkpoints — there is no "EmbeddingLoader" node to intercept.
+
+## Solution Architecture
+
+The hybrid approach combines **two complementary mechanisms** to capture embedding
+usage from all possible paths.
+
+```
+┌─────────────────────────────────────────────────────────┐
+│                 Plan A (已实现)                          │
+│                                                         │
+│  MetadataRegistry.prompt_metadata["prompts"]            │
+│       │                                                  │
+│       ▼                                                  │
+│  _process_embeddings()                                   │
+│       │                                                  │
+│       ├─ Iterate all prompt node texts                   │
+│       ├─ regex extract "embedding:<name>"                │
+│       ├─ resolve name → sha256 via EmbeddingScanner      │
+│       └─ UsageStats.stats["embeddings"][sha256]++        │
+│                                                         │
+│  Coverage: ~95% — all CLIPTextEncode/Flux/etc nodes     │
+│                                                         │
+│  Gap: Custom nodes that load embeddings programmatically │
+│       without putting embedding:name in prompt text      │
+└─────────────────────────────────────────────────────────┘
+
+                         +
+                         ↓  (future: enable Plan B when needed)
+
+┌─────────────────────────────────────────────────────────┐
+│                 Plan B (未来 — monkey-patch)              │
+│                                                         │
+│  comfy/sd1_clip.py:load_embed()                         │
+│       │                                                  │
+│       ▼                                                  │
+│  Monkey-patch intercepts EVERY embedding file load       │
+│       │                                                  │
+│       ├─ Records embedding_name + success/failure        │
+│       ├─ Associates with current prompt_id (via registry)│
+│       └─ Feeds into UsageStats same as Plan A            │
+│                                                         │
+│  Coverage: 100% — catches ALL embedding loads            │
+│                                                         │
+│  Cost: Requires patching into ComfyUI internals          │
+│        (sd1_clip.py, sdxl_clip.py, some text_encoders)   │
+└─────────────────────────────────────────────────────────┘
+```
+
+## Plan B Detail — Monkey-patch `load_embed`
+
+### Target Function
+
+**`comfy.sd1_clip.load_embed(embedding_name, embedding_directory, embedding_size, embed_key=None)`**
+at line 415 of `sd1_clip.py`.
+
+This is the **single choke point** for all embedding file loads in ComfyUI. Every
+CLIP variant (SD1, SDXL, SD3, Flux) calls this same function.
+
+### Implementation Sketch
+
+```python
+# In metadata_collector/metadata_hook.py (or a new module)
+import comfy.sd1_clip as sd1_clip
+
+_original_load_embed = sd1_clip.load_embed
+
+def _patched_load_embed(embedding_name, embedding_directory, embedding_size, embed_key=None):
+    result = _original_load_embed(
+        embedding_name, embedding_directory, embedding_size, embed_key
+    )
+    if result is not None:
+        _record_embedding_usage(embedding_name)
+    return result
+
+sd1_clip.load_embed = _patched_load_embed
+```
+
+### Prompt ID Association
+
+The challenge is associating the `load_embed` call with the current `prompt_id`.
+Options:
+
+1. **Thread-local / contextvar**: Store current `prompt_id` in a `contextvars.ContextVar`
+   that the metadata_collector sets at the start of each prompt execution.
+
+2. **MetadataRegistry singleton**: The MetadataRegistry already has `current_prompt_id`.
+   The patch can read it directly since both run in the same thread.
+
+3. **Lazy aggregation**: Instead of associating with prompt_id at load time, collect
+   all loaded embedding names in a global set during execution, then flush to
+   UsageStats after the prompt completes.
+
+### Files to Patch
+
+| File | Function | Coverage |
+|------|----------|----------|
+| `comfy/sd1_clip.py:415` | `load_embed()` | Primary — SD1.x, SDXL, SD3, Flux |
+| `comfy/sdxl_clip.py` | Not needed (calls `sd1_clip.SDTokenizer`) | — |
+| `comfy/text_encoders/sd3_clip.py` | Not needed (calls `sd1_clip.SDTokenizer`) | — |
+| `comfy/text_encoders/flux.py` | Not needed (calls `sd1_clip.SDTokenizer`) | — |
+
+The SD1 tokenizer is the base class for all CLIP variants' tokenizers, so patching
+`load_embed` covers them all.
+
+### Edge Cases
+
+| Edge Case | Plan A | Plan B |
+|-----------|--------|--------|
+| `embedding:name` in CLIPTextEncode | ✅ | ✅ |
+| `embedding:name` in CLIPTextEncodeFlux | ✅ | ✅ |
+| `embedding:name` in PromptLM (LoRA Manager) | ✅ | ✅ |
+| `embedding:name` in WAS_Text_to_Conditioning | ✅ | ✅ |
+| Custom node that loads embedding programmatically | ❌ | ✅ |
+| Embedding loaded multiple times in same prompt | ✅ (dedup via set) | ✅ (dedup via set) |
+| Embedding file not found | N/A | ✅ (can log) |
+| Embedding dimension mismatch | N/A | ✅ (can log) |
+| Text encoder with non-standard tokenizer (LLaMA, T5...) | Partial | ✅ (if it calls load_embed) |
+
+## Migration Path: Standalone → Hybrid
+
+### Phase 1 — Plan A (当前状态)
+- Prompt text parsing only
+- No monkey-patching required
+- Covers all standard workflows
+
+### Phase 2 — Enable Plan B (未来工作)
+1. Add monkey-patch of `load_embed` in `metadata_collector/metadata_hook.py` (alongside
+   the existing `_map_node_over_list` hook)
+2. Collect loaded embedding names in a `set()` on the registry
+3. In `UsageStats._process_embeddings()`, merge the Plan A results (from prompt text)
+   with the Plan B results (from the patch)
+4. Add `prompt_data` field on MetadataRegistry to store loaded embeddings per prompt
+
+### Deduplication
+
+```python
+# Merge Plan A + Plan B results in _process_embeddings
+plan_a_names = extract_from_prompt_texts(prompts_data)
+plan_b_names = registry.get_loaded_embeddings(prompt_id)
+
+all_names = plan_a_names | plan_b_names
+```
+
+## Testing the Hybrid
+
+| Scenario | What to verify |
+|----------|---------------|
+| Standard `embedding:name` in prompt | Plan A captures it |
+| Embedding loaded by custom node script | Plan B captures it |
+| Both paths fire for same embedding | No double-counting (dedup) |
+| Embedding name resolves to hash | EmbeddingScanner.get_hash_by_filename works |
+| No embedding scanner available | Graceful skip, no crash |
+| Missing embedding file | Plan B logs warning, Plan A skips gracefully |
+| Empty prompt | No crash, no entries |
+| Standalone mode | Both plans disabled gracefully |
+
+## Key Files Reference
+
+| File | Role |
+|------|------|
+| `py/utils/usage_stats.py` | Core — `_process_embeddings()` for Plan A |
+| `py/metadata_collector/constants.py` | `EMBEDDINGS` category constant |
+| `py/metadata_collector/metadata_hook.py` | Future — monkey-patch for Plan B |
+| `py/services/embedding_scanner.py` | Hash resolution service |
+| `py/routes/stats_routes.py` | Already handles `usage_data.get('embeddings', {})` |
+| `comfy/sd1_clip.py` (ComfyUI) | `load_embed()` — Plan B target |

locales/de.json

@@ -16,10 +16,13 @@
             "help": "Hilfe",
             "add": "Hinzufügen",
             "close": "Schließen",
-            "menu": "Menü"
+            "menu": "Menü",
+            "remove": "Entfernen",
+            "change": "Ändern"
         },
         "status": {
             "loading": "Wird geladen...",
+            "cancelling": "Abbrechen...",
             "unknown": "Unbekannt",
             "date": "Datum",
             "version": "Version",
@@ -111,6 +114,7 @@
             "replacePreview": "Vorschau ersetzen",
             "copyCheckpointName": "Checkpoint-Name kopieren",
             "copyEmbeddingName": "Embedding-Name kopieren",
+            "embeddingNameCopied": "Embedding-Syntax kopiert",
             "sendCheckpointToWorkflow": "An ComfyUI senden",
             "sendEmbeddingToWorkflow": "An ComfyUI senden"
         },
@@ -247,7 +251,18 @@
             "toggle": "Theme wechseln",
             "switchToLight": "Zu hellem Theme wechseln",
             "switchToDark": "Zu dunklem Theme wechseln",
-            "switchToAuto": "Zu automatischem Theme wechseln"
+            "switchToAuto": "Zu automatischem Theme wechseln",
+            "presets": "Theme-Voreinstellungen",
+            "default": "Standard",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "Modus",
+            "light": "Hell",
+            "dark": "Dunkel",
+            "auto": "Auto"
         },
         "actions": {
             "checkUpdates": "Updates prüfen",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Civitai API Key",
         "civitaiApiKeyPlaceholder": "Geben Sie Ihren Civitai API Key ein",
         "civitaiApiKeyHelp": "Wird für die Authentifizierung beim Herunterladen von Modellen von Civitai verwendet",
+        "civitaiApiKeyConfigured": "Konfiguriert",
+        "civitaiApiKeyNotConfigured": "Nicht konfiguriert",
+        "civitaiApiKeySet": "Einrichten",
         "civitaiHost": {
             "label": "Civitai-Host",
             "help": "Wählen Sie aus, welche Civitai-Seite geöffnet wird, wenn Sie „View on Civitai“-Links verwenden.",
@@ -299,6 +317,7 @@
             "downloads": "Downloads",
             "videoSettings": "Video-Einstellungen",
             "layoutSettings": "Layout-Einstellungen",
+            "licenseIcons": "Lizenzsymbole",
             "misc": "Verschiedenes",
             "backup": "Backups",
             "folderSettings": "Standard-Roots",
@@ -445,7 +464,9 @@
                 "modelName": "Modellname",
                 "fileName": "Dateiname"
             },
-            "modelNameDisplayHelp": "Wählen Sie aus, was in der Fußzeile der Modellkarte angezeigt werden soll"
+            "modelNameDisplayHelp": "Wählen Sie aus, was in der Fußzeile der Modellkarte angezeigt werden soll",
+            "cardBlurAmount": "Karten-Overlay-Unschärfe",
+            "cardBlurAmountHelp": "Passen Sie die Unschärfeintensität der Kopf- und Fußzeilen-Overlays auf Modell- und Rezeptkarten an (0 = keine Unschärfe, 20 = maximale Unschärfe)."
         },
         "folderSettings": {
             "activeLibrary": "Aktive Bibliothek",
@@ -577,6 +598,10 @@
             "label": "Früher Zugriff Updates ausblenden",
             "help": "Nur Early-Access-Updates"
         },
+        "licenseIcons": {
+            "useNewStyle": "Aktualisierte Lizenzsymbole verwenden",
+            "useNewStyleHelp": "Lizenzberechtigungen mit farbigen Indikatoren (neuer Stil) oder nur Einschränkungssymbolen (klassischer Stil) anzeigen. Orientiert sich am aktuellen CivitAI-Design."
+        },
         "misc": {
             "includeTriggerWords": "Trigger Words in LoRA-Syntax einschließen",
             "includeTriggerWordsHelp": "Trainierte Trigger Words beim Kopieren der LoRA-Syntax in die Zwischenablage einschließen",
@@ -690,6 +715,7 @@
             "copyAll": "Alle Syntax kopieren",
             "refreshAll": "Alle Metadaten aktualisieren",
             "repairMetadata": "Metadaten der Auswahl reparieren",
+            "reimportMetadata": "Aus Quelle neu importieren",
             "checkUpdates": "Auswahl auf Updates prüfen",
             "moveAll": "Alle in Ordner verschieben",
             "autoOrganize": "Automatisch organisieren",
@@ -737,6 +763,7 @@
             "setContentRating": "Inhaltsbewertung festlegen",
             "moveToFolder": "In Ordner verschieben",
             "repairMetadata": "Metadaten reparieren",
+            "reimportMetadata": "Aus Quelle neu importieren",
             "excludeModel": "Modell ausschließen",
             "restoreModel": "Modell wiederherstellen",
             "deleteModel": "Modell löschen",
@@ -864,6 +891,13 @@
                 "skipped": "Rezept bereits in der neuesten Version, keine Reparatur erforderlich",
                 "failed": "Rezept-Reparatur fehlgeschlagen: {message}",
                 "missingId": "Rezept kann nicht repariert werden: Fehlende Rezept-ID"
+            },
+            "reimport": {
+                "starting": "Rezept wird aus Quelle neu importiert...",
+                "success": "Rezept erfolgreich neu importiert",
+                "noSourceUrl": "Rezept hat keine Quell-URL, Neuimport nicht möglich",
+                "failed": "Neuimport des Rezepts fehlgeschlagen: {message}",
+                "missingId": "Neuimport nicht möglich: Rezept-ID fehlt"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "Stammverzeichnis",
         "collapseAll": "Alle Ordner einklappen",
-        "pinSidebar": "Sidebar anheften",
-        "unpinSidebar": "Sidebar lösen",
+        "hideOnThisPage": "Seitenleiste auf dieser Seite ausblenden",
+        "showSidebar": "Seitenleiste anzeigen",
+        "sidebarHiddenNotification": "Seitenleiste auf der Seite {page} ausgeblendet",
         "switchToListView": "Zur Listenansicht wechseln",
         "switchToTreeView": "Zur Baumansicht wechseln",
         "recursiveOn": "Unterordner einbeziehen",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "Keine Ordner gefunden",
             "dragHint": "Elemente hierher ziehen, um Ordner zu erstellen"
+        },
+        "folderUpdateCheck": {
+            "label": "Auf Updates in diesem Ordner prüfen",
+            "loading": "Prüfe {type}-Updates in diesem Ordner...",
+            "success": "{count} Update(s) für {type}s in diesem Ordner gefunden",
+            "none": "Alle {type}s in diesem Ordner sind aktuell",
+            "error": "Fehler beim Prüfen des Ordners auf {type}-Updates: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "Speicher",
             "insights": "Erkenntnisse"
         },
+        "metrics": {
+            "totalModels": "Modelle gesamt",
+            "totalStorage": "Speicher gesamt",
+            "totalGenerations": "Generationen gesamt",
+            "usageRate": "Nutzungsrate",
+            "loras": "LoRAs",
+            "checkpoints": "Checkpoints",
+            "embeddings": "Embeddings",
+            "uniqueTags": "Einzigartige Tags",
+            "unusedModels": "Ungenutzte Modelle",
+            "avgUsesPerModel": "Ø Nutzungen/Modell"
+        },
         "usage": {
             "mostUsedLoras": "Meistgenutzte LoRAs",
             "mostUsedCheckpoints": "Meistgenutzte Checkpoints",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "Intelligente Erkenntnisse",
-            "recommendations": "Empfehlungen"
+            "recommendations": "Empfehlungen",
+            "noInsights": "Keine Erkenntnisse verfügbar",
+            "unusedLoras": {
+                "high": {
+                    "title": "Hohe Anzahl ungenutzter LoRAs",
+                    "description": "{percent}% Ihrer LoRAs ({count}/{total}) wurden noch nie verwendet.",
+                    "suggestion": "Erwägen Sie, ungenutzte Modelle zu organisieren oder zu archivieren, um Speicherplatz freizugeben."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "Ungenutzte Checkpoints erkannt",
+                    "description": "{percent}% Ihrer Checkpoints ({count}/{total}) wurden noch nie verwendet.",
+                    "suggestion": "Überprüfen Sie nicht mehr benötigte Checkpoints und erwägen Sie deren Entfernung."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "Hohe Anzahl ungenutzter Embeddings",
+                    "description": "{percent}% Ihrer Embeddings ({count}/{total}) wurden noch nie verwendet.",
+                    "suggestion": "Organisieren oder archivieren Sie ungenutzte Embeddings, um Ihre Sammlung zu optimieren."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "Große Sammlung erkannt",
+                    "description": "Ihre Modellsammlung verwendet {size} Speicher.",
+                    "suggestion": "Erwägen Sie externe Speicher- oder Cloud-Lösungen für eine bessere Organisation."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "Aktiver Benutzer",
+                    "description": "Sie haben {count} Generationen abgeschlossen!",
+                    "suggestion": "Entdecken und erstellen Sie weiterhin großartige Inhalte mit Ihren Modellen."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "Sammlungsübersicht",
             "baseModelDistribution": "Basis-Modell-Verteilung",
             "usageTrends": "Nutzungstrends (Letzte 30 Tage)",
-            "usageDistribution": "Nutzungsverteilung"
+            "usageDistribution": "Nutzungsverteilung",
+            "date": "Datum",
+            "usageCount": "Nutzungsanzahl",
+            "fileSizeBytes": "Dateigröße (Bytes)",
+            "models": "Modelle",
+            "loraUsage": "LoRA-Nutzung",
+            "checkpointUsage": "Checkpoint-Nutzung",
+            "embeddingUsage": "Embedding-Nutzung"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Checkpoint",
+            "diffusion_model": "Diffusionsmodell",
+            "embedding": "Embeddings"
+        },
+        "placeholders": {
+            "loading": "Lädt...",
+            "noModels": "Keine Modelle gefunden",
+            "errorLoading": "Fehler beim Laden der Daten",
+            "noStorageData": "Keine Speicherdaten verfügbar",
+            "rootFolder": "Root",
+            "chartLibraryMissing": "Diagramm benötigt Chart.js-Bibliothek"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} Modelle",
+            "chartUsage": "{name}: {size}, {count} Nutzungen",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "Modell von URL herunterladen",
             "titleWithType": "{type} von URL herunterladen",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Geben Sie eine CivitAI- oder CivArchive-URL pro Zeile ein. Unterstützt mehrere URLs für den Batch-Download.",
             "locationPreview": "Download-Speicherort Vorschau",
             "useDefaultPath": "Standardpfad verwenden",
             "useDefaultPathTooltip": "Wenn aktiviert, werden Dateien automatisch mit konfigurierten Pfadvorlagen organisiert",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "Zuvor heruntergeladen, aber derzeit nicht in Ihrer Bibliothek.",
             "alreadyInLibrary": "Bereits in Bibliothek",
             "autoOrganizedPath": "[Automatisch organisiert durch Pfadvorlage]",
+            "fileSelection": {
+                "title": "Dateiformat auswählen",
+                "files": "Dateien",
+                "select": "Datei auswählen"
+            },
             "errors": {
                 "invalidUrl": "Ungültiges Civitai URL-Format",
                 "noVersions": "Keine Versionen für dieses Modell verfügbar"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "Notizen erfolgreich gespeichert",
-                "saveFailed": "Fehler beim Speichern der Notizen"
+                "saveFailed": "Fehler beim Speichern der Notizen",
+                "showMore": "Mehr anzeigen",
+                "showLess": "Weniger anzeigen"
             },
             "usageTips": {
                 "addPresetParameter": "Voreingestellten Parameter hinzufügen...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "Version gelöscht"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "Metadaten abrufen — Zusammenfassung",
+            "statSuccess": "Erfolgreich",
+            "statFailed": "Fehlgeschlagen",
+            "statSkipped": "Übersprungen",
+            "statTotal": "Gesamt geprüft",
+            "statDuration": "Dauer",
+            "successMessage": "Alle {count} {type}s erfolgreich aktualisiert!",
+            "failedItems": "Fehlgeschlagene Elemente ({count})",
+            "close": "Schließen",
+            "copyReport": "Bericht kopieren",
+            "downloadCsv": "CSV herunterladen",
+            "columnModelName": "Modellname",
+            "columnError": "Fehler"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "Dieser Tag existiert bereits"
         }
     },
-    "keyboard": {
-        "navigation": "Tastatur-Navigation:",
-        "shortcuts": {
-            "pageUp": "Eine Seite nach oben scrollen",
-            "pageDown": "Eine Seite nach unten scrollen",
-            "home": "Zum Anfang springen",
-            "end": "Zum Ende springen"
-        }
-    },
     "initialization": {
         "title": "Initialisierung",
         "message": "Ihr Arbeitsbereich wird vorbereitet...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "Keine kompatiblen Knoten im aktuellen Workflow verfügbar",
             "noTargetNodeSelected": "Kein Zielknoten ausgewählt",
             "modelUpdated": "Modell im Workflow aktualisiert",
-            "modelFailed": "Fehler beim Aktualisieren des Modellknotens"
+            "modelFailed": "Fehler beim Aktualisieren des Modellknotens",
+            "embeddingAdded": "Embedding zum Workflow hinzugefügt",
+            "embeddingFailed": "Fehler beim Hinzufügen des Embeddings"
         },
         "nodeSelector": {
             "recipe": "Rezept",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Ersetzen",
             "append": "Anhängen",
             "selectTargetNode": "Zielknoten auswählen",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "Keine Rezept-ID verfügbar",
             "sendToWorkflowFailed": "Fehler beim Senden des Rezepts an den Workflow: {message}",
             "copyFailed": "Fehler beim Kopieren der Rezept-Syntax: {message}",
+            "createError": "Fehler beim Erstellen des Rezepts：{message}",
+            "createFailed": "Fehler beim Erstellen des Rezepts：{error}",
+            "createMissingData": "Erforderliche Daten zum Erstellen des Rezepts fehlen",
+            "created": "Rezept erfolgreich erstellt",
             "noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
             "missingLorasInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
             "preparingForDownloadFailed": "Fehler beim Vorbereiten der LoRAs für den Download",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "Reparatur abgeschlossen: {repaired} repariert, {skipped} übersprungen (von {total})",
             "repairBulkSkipped": "Keine Reparatur für die {total} ausgewählten Rezepte erforderlich",
             "repairBulkFailed": "Reparatur der ausgewählten Rezepte fehlgeschlagen: {message}",
+            "reimporting": "Rezept wird aus Quelle neu importiert...",
+            "reimportSuccess": "Rezept erfolgreich neu importiert",
+            "reimportBulkComplete": "Neuimport abgeschlossen: {completed} importiert, {failed} fehlgeschlagen (von {total})",
+            "reimportBulkFailed": "Neuimport einiger Rezepte fehlgeschlagen",
             "noMissingLorasInSelection": "Keine fehlenden LoRAs in ausgewählten Rezepten gefunden",
             "noLoraRootConfigured": "Kein LoRA-Stammverzeichnis konfiguriert. Bitte legen Sie ein Standard-LoRA-Stammverzeichnis in den Einstellungen fest."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "{successCount} {type}s erfolgreich verschoben",
             "exampleImagesDownloadSuccess": "Beispielbilder erfolgreich heruntergeladen!",
             "exampleImagesDownloadFailed": "Fehler beim Herunterladen der Beispielbilder: {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "In die Zwischenablage kopiert",
+            "downloadStarted": "Download gestartet"
         }
     },
     "doctor": {

locales/en.json

@@ -16,10 +16,13 @@
             "help": "Help",
             "add": "Add",
             "close": "Close",
-            "menu": "Menu"
+            "menu": "Menu",
+            "remove": "Remove",
+            "change": "Change"
         },
         "status": {
             "loading": "Loading...",
+            "cancelling": "Cancelling...",
             "unknown": "Unknown",
             "date": "Date",
             "version": "Version",
@@ -111,6 +114,7 @@
             "replacePreview": "Replace Preview",
             "copyCheckpointName": "Copy checkpoint name",
             "copyEmbeddingName": "Copy embedding name",
+            "embeddingNameCopied": "Embedding syntax copied",
             "sendCheckpointToWorkflow": "Send to ComfyUI",
             "sendEmbeddingToWorkflow": "Send to ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "Toggle theme",
             "switchToLight": "Switch to light theme",
             "switchToDark": "Switch to dark theme",
-            "switchToAuto": "Switch to auto theme"
+            "switchToAuto": "Switch to auto theme",
+            "presets": "Theme Presets",
+            "default": "Default",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "Mode",
+            "light": "Light",
+            "dark": "Dark",
+            "auto": "Auto"
         },
         "actions": {
             "checkUpdates": "Check Updates",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Civitai API Key",
         "civitaiApiKeyPlaceholder": "Enter your Civitai API key",
         "civitaiApiKeyHelp": "Used for authentication when downloading models from Civitai",
+        "civitaiApiKeyConfigured": "Configured",
+        "civitaiApiKeyNotConfigured": "Not configured",
+        "civitaiApiKeySet": "Set up",
         "civitaiHost": {
             "label": "Civitai host",
             "help": "Choose which Civitai site opens when using View on Civitai links.",
@@ -299,6 +317,7 @@
             "downloads": "Downloads",
             "videoSettings": "Video Settings",
             "layoutSettings": "Layout Settings",
+            "licenseIcons": "License Icons",
             "misc": "Miscellaneous",
             "backup": "Backups",
             "folderSettings": "Default Roots",
@@ -445,7 +464,9 @@
                 "modelName": "Model Name",
                 "fileName": "File Name"
             },
-            "modelNameDisplayHelp": "Choose what to display in the model card footer"
+            "modelNameDisplayHelp": "Choose what to display in the model card footer",
+            "cardBlurAmount": "Card Overlay Blur",
+            "cardBlurAmountHelp": "Adjust the blur intensity of the header and footer overlays on model and recipe cards (0 = no blur, 20 = maximum blur)."
         },
         "folderSettings": {
             "activeLibrary": "Active Library",
@@ -577,6 +598,10 @@
             "label": "Hide Early Access Updates",
             "help": "When enabled, models with only early access updates will not show 'Update available' badge"
         },
+        "licenseIcons": {
+            "useNewStyle": "Use updated license icons",
+            "useNewStyleHelp": "Display license permissions with colored indicators (new style) or restriction-only icons (classic style). Mirroring the current CivitAI design."
+        },
         "misc": {
             "includeTriggerWords": "Include Trigger Words in LoRA Syntax",
             "includeTriggerWordsHelp": "Include trained trigger words when copying LoRA syntax to clipboard",
@@ -690,6 +715,7 @@
             "copyAll": "Copy Selected Syntax",
             "refreshAll": "Refresh Selected Metadata",
             "repairMetadata": "Repair Metadata for Selected",
+            "reimportMetadata": "Re-import from Source",
             "checkUpdates": "Check Updates for Selected",
             "moveAll": "Move Selected to Folder",
             "autoOrganize": "Auto-Organize Selected",
@@ -737,6 +763,7 @@
             "setContentRating": "Set Content Rating",
             "moveToFolder": "Move to Folder",
             "repairMetadata": "Repair metadata",
+            "reimportMetadata": "Re-import from Source",
             "excludeModel": "Exclude Model",
             "restoreModel": "Restore Model",
             "deleteModel": "Delete Model",
@@ -864,6 +891,13 @@
                 "skipped": "Recipe already at latest version, no repair needed",
                 "failed": "Failed to repair recipe: {message}",
                 "missingId": "Cannot repair recipe: Missing recipe ID"
+            },
+            "reimport": {
+                "starting": "Re-importing recipe from source...",
+                "success": "Recipe re-imported successfully",
+                "noSourceUrl": "Recipe has no source URL, cannot re-import",
+                "failed": "Failed to re-import recipe: {message}",
+                "missingId": "Cannot re-import recipe: Missing recipe ID"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "Root",
         "collapseAll": "Collapse All Folders",
-        "pinSidebar": "Pin Sidebar",
-        "unpinSidebar": "Unpin Sidebar",
+        "hideOnThisPage": "Hide sidebar on this page",
+        "showSidebar": "Show sidebar",
+        "sidebarHiddenNotification": "Folder sidebar hidden on {page} page",
         "switchToListView": "Switch to List View",
         "switchToTreeView": "Switch to Tree View",
         "recursiveOn": "Include subfolders",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "No folders found",
             "dragHint": "Drag items here to create folders"
+        },
+        "folderUpdateCheck": {
+            "label": "Check for updates in this folder",
+            "loading": "Checking {type} updates for this folder...",
+            "success": "Found {count} update(s) for {type}s in this folder",
+            "none": "All {type}s in this folder are up to date",
+            "error": "Failed to check folder for {type} updates: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "Storage",
             "insights": "Insights"
         },
+        "metrics": {
+            "totalModels": "Total Models",
+            "totalStorage": "Total Storage",
+            "totalGenerations": "Total Generations",
+            "usageRate": "Usage Rate",
+            "loras": "LoRAs",
+            "checkpoints": "Checkpoints",
+            "embeddings": "Embeddings",
+            "uniqueTags": "Unique Tags",
+            "unusedModels": "Unused Models",
+            "avgUsesPerModel": "Avg. Uses/Model"
+        },
         "usage": {
             "mostUsedLoras": "Most Used LoRAs",
             "mostUsedCheckpoints": "Most Used Checkpoints",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "Smart Insights",
-            "recommendations": "Recommendations"
+            "recommendations": "Recommendations",
+            "noInsights": "No insights available",
+            "unusedLoras": {
+                "high": {
+                    "title": "High Number of Unused LoRAs",
+                    "description": "{percent}% of your LoRAs ({count}/{total}) have never been used.",
+                    "suggestion": "Consider organizing or archiving unused models to free up storage space."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "Unused Checkpoints Detected",
+                    "description": "{percent}% of your checkpoints ({count}/{total}) have never been used.",
+                    "suggestion": "Review and consider removing checkpoints you no longer need."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "High Number of Unused Embeddings",
+                    "description": "{percent}% of your embeddings ({count}/{total}) have never been used.",
+                    "suggestion": "Consider organizing or archiving unused embeddings to optimize your collection."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "Large Collection Detected",
+                    "description": "Your model collection is using {size} of storage.",
+                    "suggestion": "Consider using external storage or cloud solutions for better organization."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "Active User",
+                    "description": "You've completed {count} generations so far!",
+                    "suggestion": "Keep exploring and creating amazing content with your models."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "Collection Overview",
             "baseModelDistribution": "Base Model Distribution",
             "usageTrends": "Usage Trends (Last 30 Days)",
-            "usageDistribution": "Usage Distribution"
+            "usageDistribution": "Usage Distribution",
+            "date": "Date",
+            "usageCount": "Usage Count",
+            "fileSizeBytes": "File Size (bytes)",
+            "models": "Models",
+            "loraUsage": "LoRA Usage",
+            "checkpointUsage": "Checkpoint Usage",
+            "embeddingUsage": "Embedding Usage"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Checkpoint",
+            "diffusion_model": "Diffusion Model",
+            "embedding": "Embeddings"
+        },
+        "placeholders": {
+            "loading": "Loading...",
+            "noModels": "No models found",
+            "errorLoading": "Error loading data",
+            "noStorageData": "No storage data available",
+            "rootFolder": "Root",
+            "chartLibraryMissing": "Chart requires Chart.js library"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} models",
+            "chartUsage": "{name}: {size}, {count} uses",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "Download Model from URL",
             "titleWithType": "Download {type} from URL",
-            "url": "Civitai URL",
-            "civitaiUrl": "Civitai URL:",
+            "civitaiUrl": "Civitai URL(s):",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Enter one CivitAI or CivArchive URL per line. Supports multiple URLs for batch download.",
             "locationPreview": "Download Location Preview",
             "useDefaultPath": "Use Default Path",
             "useDefaultPathTooltip": "When enabled, files are automatically organized using configured path templates",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "Previously downloaded, but it is not currently in your library.",
             "alreadyInLibrary": "Already in Library",
             "autoOrganizedPath": "[Auto-organized by path template]",
+            "fileSelection": {
+                "title": "Select File Format",
+                "files": "files",
+                "select": "Select File"
+            },
             "errors": {
                 "invalidUrl": "Invalid Civitai URL format",
                 "noVersions": "No versions available for this model"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "Notes saved successfully",
-                "saveFailed": "Failed to save notes"
+                "saveFailed": "Failed to save notes",
+                "showMore": "Show more",
+                "showLess": "Show less"
             },
             "usageTips": {
                 "addPresetParameter": "Add preset parameter...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "Version deleted"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "Metadata Fetch Summary",
+            "statSuccess": "Success",
+            "statFailed": "Failed",
+            "statSkipped": "Skipped",
+            "statTotal": "Total Scanned",
+            "statDuration": "Duration",
+            "successMessage": "All {count} {type}s updated successfully!",
+            "failedItems": "Failed Items ({count})",
+            "close": "Close",
+            "copyReport": "Copy Report",
+            "downloadCsv": "Download CSV",
+            "columnModelName": "Model Name",
+            "columnError": "Error"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "This tag already exists"
         }
     },
-    "keyboard": {
-        "navigation": "Keyboard Navigation:",
-        "shortcuts": {
-            "pageUp": "Scroll up one page",
-            "pageDown": "Scroll down one page",
-            "home": "Jump to top",
-            "end": "Jump to bottom"
-        }
-    },
     "initialization": {
         "title": "Initializing",
         "message": "Preparing your workspace...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "No compatible nodes available in the current workflow",
             "noTargetNodeSelected": "No target node selected",
             "modelUpdated": "Model updated in workflow",
-            "modelFailed": "Failed to update model node"
+            "modelFailed": "Failed to update model node",
+            "embeddingAdded": "Embedding added to workflow",
+            "embeddingFailed": "Failed to add embedding"
         },
         "nodeSelector": {
             "recipe": "Recipe",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Replace",
             "append": "Append",
             "selectTargetNode": "Select target node",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "No recipe ID available",
             "sendToWorkflowFailed": "Failed to send recipe to workflow: {message}",
             "copyFailed": "Error copying recipe syntax: {message}",
+            "createError": "Error creating recipe: {message}",
+            "createFailed": "Failed to create recipe: {error}",
+            "createMissingData": "Missing required data to create recipe",
+            "created": "Recipe created successfully",
             "noMissingLoras": "No missing LoRAs to download",
             "missingLorasInfoFailed": "Failed to get information for missing LoRAs",
             "preparingForDownloadFailed": "Error preparing LoRAs for download",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
             "repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
             "repairBulkFailed": "Failed to repair selected recipes: {message}",
+            "reimporting": "Re-importing recipe from source...",
+            "reimportSuccess": "Recipe re-imported successfully",
+            "reimportBulkComplete": "Re-import complete: {completed} re-imported, {failed} failed (of {total})",
+            "reimportBulkFailed": "Failed to re-import some recipes",
             "noMissingLorasInSelection": "No missing LoRAs found in selected recipes",
             "noLoraRootConfigured": "No LoRA root directory configured. Please set a default LoRA root in settings."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "Successfully moved {successCount} {type}s",
             "exampleImagesDownloadSuccess": "Successfully downloaded example images!",
             "exampleImagesDownloadFailed": "Failed to download example images: {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "Copied to clipboard",
+            "downloadStarted": "Download started"
         }
     },
     "doctor": {
@@ -2009,4 +2153,4 @@
             "retry": "Retry"
         }
     }
-}
+}

locales/es.json

@@ -16,10 +16,13 @@
             "help": "Ayuda",
             "add": "Añadir",
             "close": "Cerrar",
-            "menu": "Menú"
+            "menu": "Menú",
+            "remove": "Eliminar",
+            "change": "Cambiar"
         },
         "status": {
             "loading": "Cargando...",
+            "cancelling": "Cancelando...",
             "unknown": "Desconocido",
             "date": "Fecha",
             "version": "Versión",
@@ -111,6 +114,7 @@
             "replacePreview": "Reemplazar vista previa",
             "copyCheckpointName": "Copiar nombre del checkpoint",
             "copyEmbeddingName": "Copiar nombre del embedding",
+            "embeddingNameCopied": "Sintaxis de embedding copiada",
             "sendCheckpointToWorkflow": "Enviar a ComfyUI",
             "sendEmbeddingToWorkflow": "Enviar a ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "Cambiar tema",
             "switchToLight": "Cambiar a tema claro",
             "switchToDark": "Cambiar a tema oscuro",
-            "switchToAuto": "Cambiar a tema automático"
+            "switchToAuto": "Cambiar a tema automático",
+            "presets": "Preajustes de tema",
+            "default": "Predeterminado",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "Modo",
+            "light": "Claro",
+            "dark": "Oscuro",
+            "auto": "Auto"
         },
         "actions": {
             "checkUpdates": "Comprobar actualizaciones",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Clave API de Civitai",
         "civitaiApiKeyPlaceholder": "Introduce tu clave API de Civitai",
         "civitaiApiKeyHelp": "Utilizada para autenticación al descargar modelos de Civitai",
+        "civitaiApiKeyConfigured": "Configurado",
+        "civitaiApiKeyNotConfigured": "No configurado",
+        "civitaiApiKeySet": "Configurar",
         "civitaiHost": {
             "label": "Host de Civitai",
             "help": "Elige qué sitio de Civitai se abre al usar los enlaces de \"View on Civitai\".",
@@ -299,6 +317,7 @@
             "downloads": "Descargas",
             "videoSettings": "Configuración de video",
             "layoutSettings": "Configuración de diseño",
+            "licenseIcons": "Iconos de licencia",
             "misc": "Varios",
             "backup": "Copias de seguridad",
             "folderSettings": "Raíces predeterminadas",
@@ -445,7 +464,9 @@
                 "modelName": "Nombre del modelo",
                 "fileName": "Nombre del archivo"
             },
-            "modelNameDisplayHelp": "Elige qué mostrar en el pie de la tarjeta del modelo"
+            "modelNameDisplayHelp": "Elige qué mostrar en el pie de la tarjeta del modelo",
+            "cardBlurAmount": "Desenfoque de superposición de tarjetas",
+            "cardBlurAmountHelp": "Ajuste la intensidad de desenfoque de las superposiciones del encabezado y pie de página en las tarjetas de modelos y recetas (0 = sin desenfoque, 20 = desenfoque máximo)."
         },
         "folderSettings": {
             "activeLibrary": "Biblioteca activa",
@@ -577,6 +598,10 @@
             "label": "Ocultar actualizaciones de acceso temprano",
             "help": "Solo actualizaciones de acceso temprano"
         },
+        "licenseIcons": {
+            "useNewStyle": "Usar iconos de licencia actualizados",
+            "useNewStyleHelp": "Mostrar permisos de licencia con indicadores de color (nuevo estilo) o solo iconos de restricción (estilo clásico). Refleja el diseño actual de CivitAI."
+        },
         "misc": {
             "includeTriggerWords": "Incluir palabras clave en la sintaxis de LoRA",
             "includeTriggerWordsHelp": "Incluir palabras clave entrenadas al copiar la sintaxis de LoRA al portapapeles",
@@ -690,6 +715,7 @@
             "copyAll": "Copiar toda la sintaxis",
             "refreshAll": "Actualizar todos los metadatos",
             "repairMetadata": "Reparar metadatos de la selección",
+            "reimportMetadata": "Reimportar desde origen",
             "checkUpdates": "Comprobar actualizaciones para la selección",
             "moveAll": "Mover todos a carpeta",
             "autoOrganize": "Auto-organizar seleccionados",
@@ -737,6 +763,7 @@
             "setContentRating": "Establecer clasificación de contenido",
             "moveToFolder": "Mover a carpeta",
             "repairMetadata": "Reparar metadatos",
+            "reimportMetadata": "Reimportar desde origen",
             "excludeModel": "Excluir modelo",
             "restoreModel": "Restaurar modelo",
             "deleteModel": "Eliminar modelo",
@@ -864,6 +891,13 @@
                 "skipped": "La receta ya está en la última versión, no se necesita reparación",
                 "failed": "Error al reparar la receta: {message}",
                 "missingId": "No se puede reparar la receta: falta el ID de la receta"
+            },
+            "reimport": {
+                "starting": "Reimportando receta desde origen...",
+                "success": "Receta reimportada exitosamente",
+                "noSourceUrl": "La receta no tiene URL de origen, no se puede reimportar",
+                "failed": "Error al reimportar la receta: {message}",
+                "missingId": "No se puede reimportar la receta: falta el ID"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "Raíz",
         "collapseAll": "Colapsar todas las carpetas",
-        "pinSidebar": "Fijar barra lateral",
-        "unpinSidebar": "Desfijar barra lateral",
+        "hideOnThisPage": "Ocultar barra lateral en esta página",
+        "showSidebar": "Mostrar barra lateral",
+        "sidebarHiddenNotification": "Barra lateral oculta en la página {page}",
         "switchToListView": "Cambiar a vista de lista",
         "switchToTreeView": "Cambiar a vista de árbol",
         "recursiveOn": "Incluir subcarpetas",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "No se encontraron carpetas",
             "dragHint": "Arrastra elementos aquí para crear carpetas"
+        },
+        "folderUpdateCheck": {
+            "label": "Buscar actualizaciones en esta carpeta",
+            "loading": "Buscando actualizaciones de {type} en esta carpeta...",
+            "success": "Se encontraron {count} actualización(es) para {type}s en esta carpeta",
+            "none": "Todos los {type}s en esta carpeta están actualizados",
+            "error": "Error al buscar actualizaciones de {type} en la carpeta: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "Almacenamiento",
             "insights": "Perspectivas"
         },
+        "metrics": {
+            "totalModels": "Total de modelos",
+            "totalStorage": "Almacenamiento total",
+            "totalGenerations": "Generaciones totales",
+            "usageRate": "Tasa de uso",
+            "loras": "LoRAs",
+            "checkpoints": "Puntos de control",
+            "embeddings": "Embeddings",
+            "uniqueTags": "Etiquetas únicas",
+            "unusedModels": "Modelos no usados",
+            "avgUsesPerModel": "Prom. usos/modelo"
+        },
         "usage": {
             "mostUsedLoras": "LoRAs más utilizados",
             "mostUsedCheckpoints": "Checkpoints más utilizados",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "Perspectivas inteligentes",
-            "recommendations": "Recomendaciones"
+            "recommendations": "Recomendaciones",
+            "noInsights": "No hay información disponible",
+            "unusedLoras": {
+                "high": {
+                    "title": "Alta cantidad de LoRAs no utilizadas",
+                    "description": "El {percent}% de tus LoRAs ({count}/{total}) nunca se han utilizado.",
+                    "suggestion": "Considera organizar o archivar modelos no utilizados para liberar espacio."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "Puntos de control no utilizados detectados",
+                    "description": "El {percent}% de tus puntos de control ({count}/{total}) nunca se han utilizado.",
+                    "suggestion": "Revisa y considera eliminar los puntos de control que ya no necesites."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "Alta cantidad de Embeddings no utilizados",
+                    "description": "El {percent}% de tus embeddings ({count}/{total}) nunca se han utilizado.",
+                    "suggestion": "Considera organizar o archivar embeddings no utilizados para optimizar tu colección."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "Colección grande detectada",
+                    "description": "Tu colección de modelos está usando {size} de almacenamiento.",
+                    "suggestion": "Considera usar almacenamiento externo o soluciones en la nube para una mejor organización."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "Usuario activo",
+                    "description": "¡Has completado {count} generaciones hasta ahora!",
+                    "suggestion": "Sigue explorando y creando contenido increíble con tus modelos."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "Resumen de colección",
             "baseModelDistribution": "Distribución de modelo base",
             "usageTrends": "Tendencias de uso (Últimos 30 días)",
-            "usageDistribution": "Distribución de uso"
+            "usageDistribution": "Distribución de uso",
+            "date": "Fecha",
+            "usageCount": "Conteo de uso",
+            "fileSizeBytes": "Tamaño del archivo (bytes)",
+            "models": "Modelos",
+            "loraUsage": "Uso de LoRA",
+            "checkpointUsage": "Uso de Checkpoint",
+            "embeddingUsage": "Uso de Embedding"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Punto de control",
+            "diffusion_model": "Modelo de difusión",
+            "embedding": "Embeddings"
+        },
+        "placeholders": {
+            "loading": "Cargando...",
+            "noModels": "No se encontraron modelos",
+            "errorLoading": "Error al cargar datos",
+            "noStorageData": "No hay datos de almacenamiento disponibles",
+            "rootFolder": "Raíz",
+            "chartLibraryMissing": "El gráfico requiere la librería Chart.js"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} modelos",
+            "chartUsage": "{name}: {size}, {count} usos",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "Descargar modelo desde URL",
             "titleWithType": "Descargar {type} desde URL",
-            "url": "URL de Civitai",
             "civitaiUrl": "URL de Civitai:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Ingrese una URL de CivitAI o CivArchive por línea. Admite múltiples URLs para descarga por lotes.",
             "locationPreview": "Vista previa de ubicación de descarga",
             "useDefaultPath": "Usar ruta predeterminada",
             "useDefaultPathTooltip": "Cuando está habilitado, los archivos se organizan automáticamente usando plantillas de rutas configuradas",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "Descargado anteriormente, pero actualmente no está en tu biblioteca.",
             "alreadyInLibrary": "Ya en la biblioteca",
             "autoOrganizedPath": "[Auto-organizado por plantilla de ruta]",
+            "fileSelection": {
+                "title": "Seleccionar formato de archivo",
+                "files": "archivos",
+                "select": "Seleccionar archivo"
+            },
             "errors": {
                 "invalidUrl": "Formato de URL de Civitai inválido",
                 "noVersions": "No hay versiones disponibles para este modelo"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "Notas guardadas exitosamente",
-                "saveFailed": "Error al guardar notas"
+                "saveFailed": "Error al guardar notas",
+                "showMore": "Mostrar más",
+                "showLess": "Mostrar menos"
             },
             "usageTips": {
                 "addPresetParameter": "Añadir parámetro preestablecido...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "Versión eliminada"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "Resumen de obtención de metadatos",
+            "statSuccess": "Éxito",
+            "statFailed": "Fallido",
+            "statSkipped": "Omitido",
+            "statTotal": "Total escaneado",
+            "statDuration": "Duración",
+            "successMessage": "¡Todos los {count} {type}s actualizados correctamente!",
+            "failedItems": "Elementos fallidos ({count})",
+            "close": "Cerrar",
+            "copyReport": "Copiar informe",
+            "downloadCsv": "Descargar CSV",
+            "columnModelName": "Nombre del modelo",
+            "columnError": "Error"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "Esta etiqueta ya existe"
         }
     },
-    "keyboard": {
-        "navigation": "Navegación por teclado:",
-        "shortcuts": {
-            "pageUp": "Desplazar hacia arriba una página",
-            "pageDown": "Desplazar hacia abajo una página",
-            "home": "Saltar al inicio",
-            "end": "Saltar al final"
-        }
-    },
     "initialization": {
         "title": "Inicializando",
         "message": "Preparando tu espacio de trabajo...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "No hay nodos compatibles disponibles en el flujo de trabajo actual",
             "noTargetNodeSelected": "No se ha seleccionado ningún nodo de destino",
             "modelUpdated": "Modelo actualizado en el flujo de trabajo",
-            "modelFailed": "Error al actualizar nodo de modelo"
+            "modelFailed": "Error al actualizar nodo de modelo",
+            "embeddingAdded": "Embedding añadido al flujo de trabajo",
+            "embeddingFailed": "Error al añadir el embedding"
         },
         "nodeSelector": {
             "recipe": "Receta",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Reemplazar",
             "append": "Añadir",
             "selectTargetNode": "Seleccionar nodo de destino",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "No hay ID de receta disponible",
             "sendToWorkflowFailed": "Error al enviar la receta al flujo de trabajo: {message}",
             "copyFailed": "Error copiando sintaxis de receta: {message}",
+            "createError": "Error al crear la receta：{message}",
+            "createFailed": "Error al crear la receta：{error}",
+            "createMissingData": "Faltan datos necesarios para crear la receta",
+            "created": "Receta creada exitosamente",
             "noMissingLoras": "No hay LoRAs faltantes para descargar",
             "missingLorasInfoFailed": "Error al obtener información de LoRAs faltantes",
             "preparingForDownloadFailed": "Error preparando LoRAs para descarga",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "Reparación completa: {repaired} reparadas, {skipped} omitidas (de {total})",
             "repairBulkSkipped": "No se necesita reparación para ninguna de las {total} recetas seleccionadas",
             "repairBulkFailed": "Error al reparar las recetas seleccionadas: {message}",
+            "reimporting": "Reimportando receta desde origen...",
+            "reimportSuccess": "Receta reimportada exitosamente",
+            "reimportBulkComplete": "Reimportación completa: {completed} reimportadas, {failed} fallidas (de {total})",
+            "reimportBulkFailed": "Error al reimportar algunas recetas",
             "noMissingLorasInSelection": "No se encontraron LoRAs faltantes en las recetas seleccionadas",
             "noLoraRootConfigured": "No se ha configurado el directorio raíz de LoRA. Por favor, establezca un directorio raíz de LoRA predeterminado en la configuración."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "Movidos exitosamente {successCount} {type}s",
             "exampleImagesDownloadSuccess": "¡Imágenes de ejemplo descargadas exitosamente!",
             "exampleImagesDownloadFailed": "Error al descargar imágenes de ejemplo: {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "Copiado al portapapeles",
+            "downloadStarted": "Descarga iniciada"
         }
     },
     "doctor": {

locales/fr.json

@@ -16,10 +16,13 @@
             "help": "Aide",
             "add": "Ajouter",
             "close": "Fermer",
-            "menu": "Menu"
+            "menu": "Menu",
+            "remove": "Supprimer",
+            "change": "Modifier"
         },
         "status": {
             "loading": "Chargement...",
+            "cancelling": "Annulation...",
             "unknown": "Inconnu",
             "date": "Date",
             "version": "Version",
@@ -111,6 +114,7 @@
             "replacePreview": "Remplacer l'aperçu",
             "copyCheckpointName": "Copier le nom du checkpoint",
             "copyEmbeddingName": "Copier le nom de l'embedding",
+            "embeddingNameCopied": "Syntaxe dembedding copiée",
             "sendCheckpointToWorkflow": "Envoyer vers ComfyUI",
             "sendEmbeddingToWorkflow": "Envoyer vers ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "Basculer le thème",
             "switchToLight": "Passer au thème clair",
             "switchToDark": "Passer au thème sombre",
-            "switchToAuto": "Passer au thème automatique"
+            "switchToAuto": "Passer au thème automatique",
+            "presets": "Préréglages de thème",
+            "default": "Par défaut",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "Mode",
+            "light": "Clair",
+            "dark": "Sombre",
+            "auto": "Auto"
         },
         "actions": {
             "checkUpdates": "Vérifier les mises à jour",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Clé API Civitai",
         "civitaiApiKeyPlaceholder": "Entrez votre clé API Civitai",
         "civitaiApiKeyHelp": "Utilisée pour l'authentification lors du téléchargement de modèles depuis Civitai",
+        "civitaiApiKeyConfigured": "Configuré",
+        "civitaiApiKeyNotConfigured": "Non configuré",
+        "civitaiApiKeySet": "Configurer",
         "civitaiHost": {
             "label": "Hôte Civitai",
             "help": "Choisissez quel site Civitai s'ouvre lorsque vous utilisez les liens « View on Civitai ».",
@@ -299,6 +317,7 @@
             "downloads": "Téléchargements",
             "videoSettings": "Paramètres vidéo",
             "layoutSettings": "Paramètres d'affichage",
+            "licenseIcons": "Icônes de licence",
             "misc": "Divers",
             "backup": "Sauvegardes",
             "folderSettings": "Racines par défaut",
@@ -445,7 +464,9 @@
                 "modelName": "Nom du modèle",
                 "fileName": "Nom du fichier"
             },
-            "modelNameDisplayHelp": "Choisissez ce qui doit être affiché dans le pied de page de la carte du modèle"
+            "modelNameDisplayHelp": "Choisissez ce qui doit être affiché dans le pied de page de la carte du modèle",
+            "cardBlurAmount": "Flou de superposition des cartes",
+            "cardBlurAmountHelp": "Ajustez l'intensité du flou des superpositions d'en-tête et de pied de page sur les cartes de modèles et de recettes (0 = aucun flou, 20 = flou maximal)."
         },
         "folderSettings": {
             "activeLibrary": "Bibliothèque active",
@@ -577,6 +598,10 @@
             "label": "Masquer les mises à jour en accès anticipé",
             "help": "Seulement les mises à jour en accès anticipé"
         },
+        "licenseIcons": {
+            "useNewStyle": "Utiliser les icônes de licence mises à jour",
+            "useNewStyleHelp": "Afficher les permissions de licence avec des indicateurs colorés (nouveau style) ou des icônes de restriction uniquement (style classique). Reprend le design actuel de CivitAI."
+        },
         "misc": {
             "includeTriggerWords": "Inclure les mots-clés dans la syntaxe LoRA",
             "includeTriggerWordsHelp": "Inclure les mots-clés d'entraînement lors de la copie de la syntaxe LoRA dans le presse-papiers",
@@ -690,6 +715,7 @@
             "copyAll": "Copier toute la syntaxe",
             "refreshAll": "Actualiser toutes les métadonnées",
             "repairMetadata": "Réparer les métadonnées de la sélection",
+            "reimportMetadata": "Ré-importer depuis la source",
             "checkUpdates": "Vérifier les mises à jour pour la sélection",
             "moveAll": "Déplacer tout vers un dossier",
             "autoOrganize": "Auto-organiser la sélection",
@@ -737,6 +763,7 @@
             "setContentRating": "Définir la classification du contenu",
             "moveToFolder": "Déplacer vers un dossier",
             "repairMetadata": "Réparer les métadonnées",
+            "reimportMetadata": "Ré-importer depuis la source",
             "excludeModel": "Exclure le modèle",
             "restoreModel": "Restaurer le modèle",
             "deleteModel": "Supprimer le modèle",
@@ -864,6 +891,13 @@
                 "skipped": "Recette déjà à la version la plus récente, aucune réparation nécessaire",
                 "failed": "Échec de la réparation de la recette : {message}",
                 "missingId": "Impossible de réparer la recette : ID de recette manquant"
+            },
+            "reimport": {
+                "starting": "Ré-import de la recette depuis la source...",
+                "success": "Recette ré-importée avec succès",
+                "noSourceUrl": "La recette n'a pas d'URL source, ré-import impossible",
+                "failed": "Échec du ré-import de la recette : {message}",
+                "missingId": "Impossible de ré-importer la recette : ID de recette manquant"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "Racine",
         "collapseAll": "Réduire tous les dossiers",
-        "pinSidebar": "Épingler la barre latérale",
-        "unpinSidebar": "Désépingler la barre latérale",
+        "hideOnThisPage": "Masquer la barre latérale sur cette page",
+        "showSidebar": "Afficher la barre latérale",
+        "sidebarHiddenNotification": "Barre latérale masquée sur la page {page}",
         "switchToListView": "Passer en vue liste",
         "switchToTreeView": "Passer en vue arborescence",
         "recursiveOn": "Inclure les sous-dossiers",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "Aucun dossier trouvé",
             "dragHint": "Faites glisser des éléments ici pour créer des dossiers"
+        },
+        "folderUpdateCheck": {
+            "label": "Vérifier les mises à jour dans ce dossier",
+            "loading": "Vérification des mises à jour {type} dans ce dossier...",
+            "success": "{count} mise(s) à jour trouvée(s) pour les {type}s dans ce dossier",
+            "none": "Tous les {type}s dans ce dossier sont à jour",
+            "error": "Échec de la vérification des mises à jour {type} dans ce dossier : {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "Stockage",
             "insights": "Aperçus"
         },
+        "metrics": {
+            "totalModels": "Total des modèles",
+            "totalStorage": "Stockage total",
+            "totalGenerations": "Générations totales",
+            "usageRate": "Taux d'utilisation",
+            "loras": "LoRAs",
+            "checkpoints": "Points de contrôle",
+            "embeddings": "Embeddings",
+            "uniqueTags": "Tags uniques",
+            "unusedModels": "Modèles inutilisés",
+            "avgUsesPerModel": "Moy. utilisations/modèle"
+        },
         "usage": {
             "mostUsedLoras": "LoRAs les plus utilisés",
             "mostUsedCheckpoints": "Checkpoints les plus utilisés",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "Aperçus intelligents",
-            "recommendations": "Recommandations"
+            "recommendations": "Recommandations",
+            "noInsights": "Aucun aperçu disponible",
+            "unusedLoras": {
+                "high": {
+                    "title": "Nombre élevé de LoRAs inutilisées",
+                    "description": "{percent}% de vos LoRAs ({count}/{total}) n'ont jamais été utilisées.",
+                    "suggestion": "Envisagez d'organiser ou d'archiver les modèles inutilisés pour libérer de l'espace."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "Points de contrôle inutilisés détectés",
+                    "description": "{percent}% de vos points de contrôle ({count}/{total}) n'ont jamais été utilisés.",
+                    "suggestion": "Examinez et envisagez de supprimer les points de contrôle dont vous n'avez plus besoin."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "Nombre élevé d'Embeddings inutilisées",
+                    "description": "{percent}% de vos embeddings ({count}/{total}) n'ont jamais été utilisées.",
+                    "suggestion": "Envisagez d'organiser ou d'archiver les embeddings inutilisées pour optimiser votre collection."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "Grande collection détectée",
+                    "description": "Votre collection de modèles utilise {size} de stockage.",
+                    "suggestion": "Envisagez d'utiliser un stockage externe ou des solutions cloud pour une meilleure organisation."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "Utilisateur actif",
+                    "description": "Vous avez effectué {count} générations jusqu'à présent !",
+                    "suggestion": "Continuez à explorer et à créer du contenu formidable avec vos modèles."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "Aperçu de la collection",
             "baseModelDistribution": "Distribution des modèles de base",
             "usageTrends": "Tendances d'utilisation (30 derniers jours)",
-            "usageDistribution": "Distribution de l'utilisation"
+            "usageDistribution": "Distribution de l'utilisation",
+            "date": "Date",
+            "usageCount": "Nombre d'utilisations",
+            "fileSizeBytes": "Taille du fichier (octets)",
+            "models": "Modèles",
+            "loraUsage": "Utilisation LoRA",
+            "checkpointUsage": "Utilisation Checkpoint",
+            "embeddingUsage": "Utilisation Embedding"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Point de contrôle",
+            "diffusion_model": "Modèle de diffusion",
+            "embedding": "Embeddings"
+        },
+        "placeholders": {
+            "loading": "Chargement...",
+            "noModels": "Aucun modèle trouvé",
+            "errorLoading": "Erreur de chargement des données",
+            "noStorageData": "Aucune donnée de stockage disponible",
+            "rootFolder": "Racine",
+            "chartLibraryMissing": "Le graphique nécessite la bibliothèque Chart.js"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} modèles",
+            "chartUsage": "{name}: {size}, {count} utilisations",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "Télécharger un modèle depuis une URL",
             "titleWithType": "Télécharger {type} depuis une URL",
-            "url": "URL Civitai",
             "civitaiUrl": "URL Civitai :",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Entrez une URL CivitAI ou CivArchive par ligne. Prend en charge plusieurs URLs pour le téléchargement par lot.",
             "locationPreview": "Aperçu de l'emplacement de téléchargement",
             "useDefaultPath": "Utiliser le chemin par défaut",
             "useDefaultPathTooltip": "Lorsque activé, les fichiers sont automatiquement organisés selon les modèles de chemin configurés",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "Déjà téléchargé, mais il n'est actuellement pas dans votre bibliothèque.",
             "alreadyInLibrary": "Déjà dans la bibliothèque",
             "autoOrganizedPath": "[Auto-organisé par modèle de chemin]",
+            "fileSelection": {
+                "title": "Choisir le format de fichier",
+                "files": "fichiers",
+                "select": "Choisir le fichier"
+            },
             "errors": {
                 "invalidUrl": "Format d'URL Civitai invalide",
                 "noVersions": "Aucune version disponible pour ce modèle"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "Notes sauvegardées avec succès",
-                "saveFailed": "Échec de la sauvegarde des notes"
+                "saveFailed": "Échec de la sauvegarde des notes",
+                "showMore": "Afficher plus",
+                "showLess": "Afficher moins"
             },
             "usageTips": {
                 "addPresetParameter": "Ajouter un paramètre prédéfini...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "Version supprimée"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "Récapitulatif de la récupération des métadonnées",
+            "statSuccess": "Réussi",
+            "statFailed": "Échoué",
+            "statSkipped": "Ignoré",
+            "statTotal": "Total scanné",
+            "statDuration": "Durée",
+            "successMessage": "Tous les {count} {type}s mis à jour avec succès !",
+            "failedItems": "Éléments échoués ({count})",
+            "close": "Fermer",
+            "copyReport": "Copier le rapport",
+            "downloadCsv": "Télécharger CSV",
+            "columnModelName": "Nom du modèle",
+            "columnError": "Erreur"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "Ce tag existe déjà"
         }
     },
-    "keyboard": {
-        "navigation": "Navigation au clavier :",
-        "shortcuts": {
-            "pageUp": "Défiler d'une page vers le haut",
-            "pageDown": "Défiler d'une page vers le bas",
-            "home": "Aller en haut",
-            "end": "Aller en bas"
-        }
-    },
     "initialization": {
         "title": "Initialisation",
         "message": "Préparation de votre espace de travail...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "Aucun nœud compatible disponible dans le workflow actuel",
             "noTargetNodeSelected": "Aucun nœud cible sélectionné",
             "modelUpdated": "Modèle mis à jour dans le workflow",
-            "modelFailed": "Échec de la mise à jour du nœud modèle"
+            "modelFailed": "Échec de la mise à jour du nœud modèle",
+            "embeddingAdded": "Embedding ajouté au workflow",
+            "embeddingFailed": "Échec de l'ajout de l'embedding"
         },
         "nodeSelector": {
             "recipe": "Recipe",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Remplacer",
             "append": "Ajouter",
             "selectTargetNode": "Sélectionner le nœud cible",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "Aucun ID de recipe disponible",
             "sendToWorkflowFailed": "Échec de l'envoi de la recette vers le workflow : {message}",
             "copyFailed": "Erreur lors de la copie de la syntaxe de la recipe : {message}",
+            "createError": "Erreur lors de la création du Recipe ：{message}",
+            "createFailed": "Échec de la création du Recipe ：{error}",
+            "createMissingData": "Données requises manquantes pour créer le Recipe",
+            "created": "Recipe créé avec succès",
             "noMissingLoras": "Aucun LoRA manquant à télécharger",
             "missingLorasInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
             "preparingForDownloadFailed": "Erreur lors de la préparation des LoRAs pour le téléchargement",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "Réparation terminée : {repaired} réparée(s), {skipped} ignorée(s) (sur {total})",
             "repairBulkSkipped": "Aucune réparation nécessaire parmi les {total} recettes sélectionnées",
             "repairBulkFailed": "Échec de la réparation des recettes sélectionnées : {message}",
+            "reimporting": "Ré-import de la recette depuis la source...",
+            "reimportSuccess": "Recette ré-importée avec succès",
+            "reimportBulkComplete": "Ré-import terminé : {completed} ré-importé(s), {failed} échec(s) (sur {total})",
+            "reimportBulkFailed": "Échec du ré-import de certaines recettes",
             "noMissingLorasInSelection": "Aucun LoRA manquant trouvé dans les recettes sélectionnées",
             "noLoraRootConfigured": "Aucun répertoire racine LoRA configuré. Veuillez définir un répertoire racine LoRA par défaut dans les paramètres."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "{successCount} {type}s déplacés avec succès",
             "exampleImagesDownloadSuccess": "Images d'exemple téléchargées avec succès !",
             "exampleImagesDownloadFailed": "Échec du téléchargement des images d'exemple : {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "Copié dans le presse-papiers",
+            "downloadStarted": "Téléchargement démarré"
         }
     },
     "doctor": {

locales/he.json

@@ -16,10 +16,13 @@
             "help": "עזרה",
             "add": "הוספה",
             "close": "סגור",
-            "menu": "תפריט"
+            "menu": "תפריט",
+            "remove": "הסר",
+            "change": "שנה"
         },
         "status": {
             "loading": "טוען...",
+            "cancelling": "מבטל...",
             "unknown": "לא ידוע",
             "date": "תאריך",
             "version": "גרסה",
@@ -111,6 +114,7 @@
             "replacePreview": "החלף תצוגה מקדימה",
             "copyCheckpointName": "העתק שם Checkpoint",
             "copyEmbeddingName": "העתק שם Embedding",
+            "embeddingNameCopied": "תחביר Embedding הועתק",
             "sendCheckpointToWorkflow": "שלח ל-ComfyUI",
             "sendEmbeddingToWorkflow": "שלח ל-ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "החלף ערכת נושא",
             "switchToLight": "עבור לערכת נושא בהירה",
             "switchToDark": "עבור לערכת נושא כהה",
-            "switchToAuto": "עבור לערכת נושא אוטומטית"
+            "switchToAuto": "עבור לערכת נושא אוטומטית",
+            "presets": "ערכות נושא מוגדרות",
+            "default": "ברירת מחדל",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "מצב",
+            "light": "בהיר",
+            "dark": "כהה",
+            "auto": "אוטומטי"
         },
         "actions": {
             "checkUpdates": "בדוק עדכונים",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "מפתח API של Civitai",
         "civitaiApiKeyPlaceholder": "הזן את מפתח ה-API שלך מ-Civitai",
         "civitaiApiKeyHelp": "משמש לאימות בעת הורדת מודלים מ-Civitai",
+        "civitaiApiKeyConfigured": "מוגדר",
+        "civitaiApiKeyNotConfigured": "לא מוגדר",
+        "civitaiApiKeySet": "הגדר",
         "civitaiHost": {
             "label": "מארח Civitai",
             "help": "בחר איזה אתר של Civitai ייפתח בעת שימוש בקישורי \"View on Civitai\".",
@@ -299,6 +317,7 @@
             "downloads": "הורדות",
             "videoSettings": "הגדרות וידאו",
             "layoutSettings": "הגדרות פריסה",
+            "licenseIcons": "סמלי רישיון",
             "misc": "שונות",
             "backup": "גיבויים",
             "folderSettings": "תיקיות ברירת מחדל",
@@ -445,7 +464,9 @@
                 "modelName": "שם מודל",
                 "fileName": "שם קובץ"
             },
-            "modelNameDisplayHelp": "בחר מה להציג בכותרת התחתונה של כרטיס המודל"
+            "modelNameDisplayHelp": "בחר מה להציג בכותרת התחתונה של כרטיס המודל",
+            "cardBlurAmount": "עוצמת טשטוש שכבת-על בכרטיס",
+            "cardBlurAmountHelp": "כוונן את עוצמת הטשטוש של שכבת-העל בכותרת ובכותרות תחתונה בכרטיסי מודל ומתכונים (0 = ללא טשטוש, 20 = טשטוש מקסימלי)."
         },
         "folderSettings": {
             "activeLibrary": "ספרייה פעילה",
@@ -577,6 +598,10 @@
             "label": "הסתר עדכוני גישה מוקדמת",
             "help": "רק עדכוני גישה מוקדמת"
         },
+        "licenseIcons": {
+            "useNewStyle": "השתמש בסמלי רישיון מעודכנים",
+            "useNewStyleHelp": "הצג הרשאות רישיון עם מחוונים צבעוניים (סגנון חדש) או סמלי הגבלה בלבד (סגנון קלאסי). משקף את העיצוב העדכני של CivitAI."
+        },
         "misc": {
             "includeTriggerWords": "כלול מילות טריגר בתחביר LoRA",
             "includeTriggerWordsHelp": "כלול מילות טריגר מאומנות בעת העתקת תחביר LoRA ללוח",
@@ -690,6 +715,7 @@
             "copyAll": "העתק את כל התחבירים",
             "refreshAll": "רענן את כל המטא-דאטה",
             "repairMetadata": "תקן מטא-דאטה עבור הנבחרים",
+            "reimportMetadata": "ייבא מחדש ממקור",
             "checkUpdates": "בדוק עדכונים לבחירה",
             "moveAll": "העבר הכל לתיקייה",
             "autoOrganize": "ארגן אוטומטית נבחרים",
@@ -737,6 +763,7 @@
             "setContentRating": "הגדר דירוג תוכן",
             "moveToFolder": "העבר לתיקייה",
             "repairMetadata": "תיקון מטא-דאטה",
+            "reimportMetadata": "ייבא מחדש ממקור",
             "excludeModel": "החרג מודל",
             "restoreModel": "שחזור מודל",
             "deleteModel": "מחק מודל",
@@ -864,6 +891,13 @@
                 "skipped": "המתכון כבר בגרסה העדכנית ביותר, אין צורך בתיקון",
                 "failed": "תיקון המתכון נכשל: {message}",
                 "missingId": "לא ניתן לתקן את המתכון: חסר מזהה מתכון"
+            },
+            "reimport": {
+                "starting": "מייבא מתכון מחדש מהמקור...",
+                "success": "המתכון יובא מחדש בהצלחה",
+                "noSourceUrl": "למתכון אין כתובת מקור, לא ניתן לייבא מחדש",
+                "failed": "ייבוא המתכון מחדש נכשל: {message}",
+                "missingId": "לא ניתן לייבא מחדש: חסר מזהה מתכון"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "שורש",
         "collapseAll": "כווץ את כל התיקיות",
-        "pinSidebar": "נעל סרגל צד",
-        "unpinSidebar": "שחרר סרגל צד",
+        "hideOnThisPage": "הסתר סרגל צד בדף זה",
+        "showSidebar": "הצג סרגל צד",
+        "sidebarHiddenNotification": "סרגל הצד מוסתר בדף {page}",
         "switchToListView": "עבור לתצוגת רשימה",
         "switchToTreeView": "תצוגת עץ",
         "recursiveOn": "כלול תיקיות משנה",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "לא נמצאו תיקיות",
             "dragHint": "גרור פריטים לכאן כדי ליצור תיקיות"
+        },
+        "folderUpdateCheck": {
+            "label": "בדוק עדכונים בתיקייה זו",
+            "loading": "בודק עדכוני {type} בתיקייה זו...",
+            "success": "נמצאו {count} עדכון/ים עבור {type}s בתיקייה זו",
+            "none": "כל ה-{type}s בתיקייה זו מעודכנים",
+            "error": "נכשל בבדיקת עדכוני {type} בתיקייה: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "אחסון",
             "insights": "תובנות"
         },
+        "metrics": {
+            "totalModels": "סה\"כ דגמים",
+            "totalStorage": "סה\"כ אחסון",
+            "totalGenerations": "סה\"כ יצירות",
+            "usageRate": "שיעור שימוש",
+            "loras": "LoRA",
+            "checkpoints": "נקודות ביקורת",
+            "embeddings": "הטמעות",
+            "uniqueTags": "תגיות ייחודיות",
+            "unusedModels": "דגמים שאינם בשימוש",
+            "avgUsesPerModel": "ממוצע שימושים/דגם"
+        },
         "usage": {
             "mostUsedLoras": "LoRAs הנפוצים ביותר",
             "mostUsedCheckpoints": "Checkpoints הנפוצים ביותר",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "תובנות חכמות",
-            "recommendations": "המלצות"
+            "recommendations": "המלצות",
+            "noInsights": "אין תובנות זמינות",
+            "unusedLoras": {
+                "high": {
+                    "title": "כמות גבוהה של LoRAs שאינן בשימוש",
+                    "description": "{percent}% מה-LoRAs שלך ({count}/{total}) מעולם לא נעשה בהם שימוש.",
+                    "suggestion": "שקול לארגן או לאחסן בארכיון מודלים שאינם בשימוש כדי לפנות שטח אחסון."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "התגלו נקודות ביקורת שאינן בשימוש",
+                    "description": "{percent}% מנקודות הביקורת שלך ({count}/{total}) מעולם לא נעשה בהן שימוש.",
+                    "suggestion": "בדוק ושקול להסיר נקודות ביקורת שאינך צריך עוד."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "כמות גבוהה של Embeddings שאינם בשימוש",
+                    "description": "{percent}% מה-Embeddings שלך ({count}/{total}) מעולם לא נעשה בהם שימוש.",
+                    "suggestion": "שקול לארגן או לאחסן בארכיון Embeddings שאינם בשימוש כדי לייעל את האוסף."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "התגלה אוסף גדול",
+                    "description": "אוסף המודלים שלך משתמש ב-{size} של אחסון.",
+                    "suggestion": "שקול להשתמש באחסון חיצוני או בפתרונות ענן לארגון טוב יותר."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "משתמש פעיל",
+                    "description": "השלמת {count} יצירות עד כה!",
+                    "suggestion": "המשך לחקור וליצור תוכן מדהים עם המודלים שלך."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "סקירת אוסף",
             "baseModelDistribution": "התפלגות מודלי בסיס",
             "usageTrends": "מגמות שימוש (30 יום אחרונים)",
-            "usageDistribution": "התפלגות שימוש"
+            "usageDistribution": "התפלגות שימוש",
+            "date": "תאריך",
+            "usageCount": "מספר שימושים",
+            "fileSizeBytes": "גודל קובץ (בתים)",
+            "models": "דגמים",
+            "loraUsage": "שימוש ב-LoRA",
+            "checkpointUsage": "שימוש ב-Checkpoint",
+            "embeddingUsage": "שימוש ב-Embedding"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "נקודת ביקורת",
+            "diffusion_model": "מודל דיפוזיה",
+            "embedding": "הטמעות"
+        },
+        "placeholders": {
+            "loading": "טוען...",
+            "noModels": "לא נמצאו דגמים",
+            "errorLoading": "שגיאה בטעינת נתונים",
+            "noStorageData": "אין נתוני אחסון זמינים",
+            "rootFolder": "שורש",
+            "chartLibraryMissing": "הגרף דורש את ספריית Chart.js"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} דגמים",
+            "chartUsage": "{name}: {size}, {count} שימושים",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "הורד מודל מכתובת URL",
             "titleWithType": "הורד {type} מכתובת URL",
-            "url": "כתובת URL של Civitai",
             "civitaiUrl": "כתובת URL של Civitai:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "יש להזין כתובת URL אחת של CivitAI או CivArchive בכל שורה. תומך במספר כתובות URL להורדה בבת אחת.",
             "locationPreview": "תצוגה מקדימה של מיקום ההורדה",
             "useDefaultPath": "השתמש בנתיב ברירת מחדל",
             "useDefaultPathTooltip": "כאשר מופעל, קבצים מאורגנים אוטומטית באמצעות תבניות נתיב מוגדרות",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "הורד בעבר, אך הוא אינו נמצא כרגע בספרייה שלך.",
             "alreadyInLibrary": "כבר בספרייה",
             "autoOrganizedPath": "[מאורגן אוטומטית לפי תבנית נתיב]",
+            "fileSelection": {
+                "title": "בחר פורמט קובץ",
+                "files": "קבצים",
+                "select": "בחר קובץ"
+            },
             "errors": {
                 "invalidUrl": "פורמט URL של Civitai לא חוקי",
                 "noVersions": "אין גרסאות זמינות למודל זה"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "הערות נשמרו בהצלחה",
-                "saveFailed": "שמירת ההערות נכשלה"
+                "saveFailed": "שמירת ההערות נכשלה",
+                "showMore": "הצג עוד",
+                "showLess": "הצג פחות"
             },
             "usageTips": {
                 "addPresetParameter": "הוסף פרמטר קבוע מראש...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "הגרסה נמחקה"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "סיכום שליפת מטא-דאטה",
+            "statSuccess": "הצלחה",
+            "statFailed": "נכשל",
+            "statSkipped": "דולג",
+            "statTotal": "סה\"כ נסרק",
+            "statDuration": "משך",
+            "successMessage": "כל {count} {type}s עודכנו בהצלחה!",
+            "failedItems": "פריטים נכשלים ({count})",
+            "close": "סגור",
+            "copyReport": "העתק דוח",
+            "downloadCsv": "הורד CSV",
+            "columnModelName": "שם המודל",
+            "columnError": "שגיאה"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "תגית זו כבר קיימת"
         }
     },
-    "keyboard": {
-        "navigation": "ניווט במקלדת:",
-        "shortcuts": {
-            "pageUp": "גלול עמוד אחד למעלה",
-            "pageDown": "גלול עמוד אחד למטה",
-            "home": "קפוץ להתחלה",
-            "end": "קפוץ לסוף"
-        }
-    },
     "initialization": {
         "title": "מאתחל",
         "message": "מכין את סביבת העבודה שלך...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "אין צמתים תואמים זמינים ב-workflow הנוכחי",
             "noTargetNodeSelected": "לא נבחר צומת יעד",
             "modelUpdated": "מודל עודכן ב-workflow",
-            "modelFailed": "עדכון צומת המודל נכשל"
+            "modelFailed": "עדכון צומת המודל נכשל",
+            "embeddingAdded": "Embedding נוסף ל-workflow",
+            "embeddingFailed": "הוספת Embedding נכשלה"
         },
         "nodeSelector": {
             "recipe": "מתכון",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "החלף",
             "append": "הוסף",
             "selectTargetNode": "בחר צומת יעד",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "אין מזהה מתכון זמין",
             "sendToWorkflowFailed": "נכשל שליחת המתכון ל-workflow: {message}",
             "copyFailed": "שגיאה בהעתקת תחביר המתכון: {message}",
+            "createError": "שגיאה ביצירת המתכון：{message}",
+            "createFailed": "יצירת המתכון נכשלה：{error}",
+            "createMissingData": "חסרים נתונים נדרשים ליצירת המתכון",
+            "created": "המתכון נוצר בהצלחה",
             "noMissingLoras": "אין LoRAs חסרים להורדה",
             "missingLorasInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
             "preparingForDownloadFailed": "שגיאה בהכנת LoRAs להורדה",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "התיקון הושלם: {repaired} תוקנו, {skipped} דולגו (מתוך {total})",
             "repairBulkSkipped": "אין צורך בתיקון עבור {total} המתכונים הנבחרים",
             "repairBulkFailed": "תיקון המתכונים הנבחרים נכשל: {message}",
+            "reimporting": "מייבא מתכון מחדש מהמקור...",
+            "reimportSuccess": "המתכון יובא מחדש בהצלחה",
+            "reimportBulkComplete": "ייבוא מחדש הושלם: {completed} יובאו, {failed} נכשלו (מתוך {total})",
+            "reimportBulkFailed": "ייבוא מחדש של חלק מהמתכונים נכשל",
             "noMissingLorasInSelection": "לא נמצאו LoRAs חסרים במתכונים שנבחרו",
             "noLoraRootConfigured": "תיקיית השורש של LoRA לא מוגדרת. אנא הגדר תיקיית שורש LoRA ברירת מחדל בהגדרות."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "הועברו בהצלחה {successCount} {type}s",
             "exampleImagesDownloadSuccess": "תמונות הדוגמה הורדו בהצלחה!",
             "exampleImagesDownloadFailed": "הורדת תמונות הדוגמה נכשלה: {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "הועתק ללוח",
+            "downloadStarted": "ההורדה החלה"
         }
     },
     "doctor": {

locales/ja.json

@@ -16,10 +16,13 @@
             "help": "ヘルプ",
             "add": "追加",
             "close": "閉じる",
-            "menu": "メニュー"
+            "menu": "メニュー",
+            "remove": "削除",
+            "change": "変更"
         },
         "status": {
             "loading": "読み込み中...",
+            "cancelling": "キャンセル中...",
             "unknown": "不明",
             "date": "日付",
             "version": "バージョン",
@@ -111,6 +114,7 @@
             "replacePreview": "プレビューを置換",
             "copyCheckpointName": "checkpoint名をコピー",
             "copyEmbeddingName": "embedding名をコピー",
+            "embeddingNameCopied": "Embedding構文をコピーしました",
             "sendCheckpointToWorkflow": "ComfyUIに送信",
             "sendEmbeddingToWorkflow": "ComfyUIに送信"
         },
@@ -247,7 +251,18 @@
             "toggle": "テーマの切り替え",
             "switchToLight": "ライトテーマに切り替え",
             "switchToDark": "ダークテーマに切り替え",
-            "switchToAuto": "自動テーマに切り替え"
+            "switchToAuto": "自動テーマに切り替え",
+            "presets": "テーマプリセット",
+            "default": "デフォルト",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "モード",
+            "light": "ライト",
+            "dark": "ダーク",
+            "auto": "自動"
         },
         "actions": {
             "checkUpdates": "更新確認",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Civitai APIキー",
         "civitaiApiKeyPlaceholder": "Civitai APIキーを入力してください",
         "civitaiApiKeyHelp": "Civitaiからモデルをダウンロードするときの認証に使用されます",
+        "civitaiApiKeyConfigured": "設定済み",
+        "civitaiApiKeyNotConfigured": "未設定",
+        "civitaiApiKeySet": "設定",
         "civitaiHost": {
             "label": "Civitai ホスト",
             "help": "「View on Civitai」リンクを使うときに開く Civitai サイトを選択します。",
@@ -299,6 +317,7 @@
             "downloads": "ダウンロード",
             "videoSettings": "動画設定",
             "layoutSettings": "レイアウト設定",
+            "licenseIcons": "ライセンスアイコン",
             "misc": "その他",
             "backup": "バックアップ",
             "folderSettings": "デフォルトルート",
@@ -445,7 +464,9 @@
                 "modelName": "モデル名",
                 "fileName": "ファイル名"
             },
-            "modelNameDisplayHelp": "モデルカードのフッターに表示する内容を選択"
+            "modelNameDisplayHelp": "モデルカードのフッターに表示する内容を選択",
+            "cardBlurAmount": "カードオーバーレイのぼかし",
+            "cardBlurAmountHelp": "モデルカードとレシピカードのヘッダー・フッターオーバーレイのぼかし強度を調整します（0 = ぼかしなし、20 = 最大ぼかし）。"
         },
         "folderSettings": {
             "activeLibrary": "アクティブライブラリ",
@@ -577,6 +598,10 @@
             "label": "早期アクセス更新を非表示",
             "help": "早期アクセスのみの更新"
         },
+        "licenseIcons": {
+            "useNewStyle": "更新されたライセンスアイコンを使用",
+            "useNewStyleHelp": "カラーインジケーター付きでライセンス許可を表示（新スタイル）するか、制限のみのアイコンを表示（クラシックスタイル）します。現在のCivitAIデザインを反映しています。"
+        },
         "misc": {
             "includeTriggerWords": "LoRA構文にトリガーワードを含める",
             "includeTriggerWordsHelp": "LoRA構文をクリップボードにコピーする際、学習済みトリガーワードを含めます",
@@ -690,6 +715,7 @@
             "copyAll": "すべての構文をコピー",
             "refreshAll": "すべてのメタデータを更新",
             "repairMetadata": "選択したレシピのメタデータを修復",
+            "reimportMetadata": "ソースから再インポート",
             "checkUpdates": "選択項目の更新を確認",
             "moveAll": "すべてをフォルダに移動",
             "autoOrganize": "自動整理を実行",
@@ -737,6 +763,7 @@
             "setContentRating": "コンテンツレーティングを設定",
             "moveToFolder": "フォルダに移動",
             "repairMetadata": "メタデータを修復",
+            "reimportMetadata": "ソースから再インポート",
             "excludeModel": "モデルを除外",
             "restoreModel": "モデルを復元",
             "deleteModel": "モデルを削除",
@@ -864,6 +891,13 @@
                 "skipped": "レシピはすでに最新バージョンです。修復は不要です",
                 "failed": "レシピの修復に失敗しました: {message}",
                 "missingId": "レシピを修復できません: レシピIDがありません"
+            },
+            "reimport": {
+                "starting": "ソースからレシピを再インポート中...",
+                "success": "レシピの再インポートが完了しました",
+                "noSourceUrl": "レシピにソースURLがありません。再インポートできません",
+                "failed": "レシピの再インポートに失敗しました: {message}",
+                "missingId": "レシピを再インポートできません: レシピIDがありません"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "ルート",
         "collapseAll": "すべてのフォルダを折りたたむ",
-        "pinSidebar": "サイドバーを固定",
-        "unpinSidebar": "サイドバーの固定を解除",
+        "hideOnThisPage": "このページでサイドバーを非表示",
+        "showSidebar": "サイドバーを表示",
+        "sidebarHiddenNotification": "{page}ページでサイドバーが非表示になっています",
         "switchToListView": "リストビューに切り替え",
         "switchToTreeView": "ツリー表示に切り替え",
         "recursiveOn": "サブフォルダーを含める",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "フォルダが見つかりません",
             "dragHint": "ここへアイテムをドラッグしてフォルダを作成します"
+        },
+        "folderUpdateCheck": {
+            "label": "このフォルダのアップデートを確認",
+            "loading": "このフォルダの{type}アップデートを確認中...",
+            "success": "このフォルダの{type}sに{count}件のアップデートが見つかりました",
+            "none": "このフォルダのすべての{type}sは最新です",
+            "error": "フォルダの{type}アップデート確認に失敗しました: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "ストレージ",
             "insights": "インサイト"
         },
+        "metrics": {
+            "totalModels": "モデル総数",
+            "totalStorage": "ストレージ合計",
+            "totalGenerations": "生成回数合計",
+            "usageRate": "使用率",
+            "loras": "LoRA",
+            "checkpoints": "Checkpoint",
+            "embeddings": "Embedding",
+            "uniqueTags": "ユニークタグ",
+            "unusedModels": "未使用モデル",
+            "avgUsesPerModel": "平均使用回数/モデル"
+        },
         "usage": {
             "mostUsedLoras": "最も使用されているLoRA",
             "mostUsedCheckpoints": "最も使用されているCheckpoint",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "スマートインサイト",
-            "recommendations": "推奨事項"
+            "recommendations": "推奨事項",
+            "noInsights": "インサイトはありません",
+            "unusedLoras": {
+                "high": {
+                    "title": "未使用のLoRAが多数あります",
+                    "description": "LoRAの{percent}%（{count}/{total}）が一度も使用されていません。",
+                    "suggestion": "未使用のモデルを整理またはアーカイブしてストレージを解放してください。"
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "未使用のCheckpointを検出",
+                    "description": "Checkpointの{percent}%（{count}/{total}）が一度も使用されていません。",
+                    "suggestion": "不要なCheckpointを確認して削除を検討してください。"
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "未使用のEmbeddingが多数あります",
+                    "description": "Embeddingの{percent}%（{count}/{total}）が一度も使用されていません。",
+                    "suggestion": "未使用のEmbeddingを整理またはアーカイブしてコレクションを最適化してください。"
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "大規模コレクションを検出",
+                    "description": "モデルコレクションが{size}のストレージを使用しています。",
+                    "suggestion": "外部ストレージやクラウドソリューションの使用を検討してください。"
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "アクティブユーザー",
+                    "description": "これまでに{count}回の生成を完了しました！",
+                    "suggestion": "モデルを使って素晴らしいコンテンツを作り続けてください。"
+                }
+            }
         },
         "charts": {
             "collectionOverview": "コレクション概要",
             "baseModelDistribution": "ベースモデル分布",
             "usageTrends": "使用傾向（過去30日）",
-            "usageDistribution": "使用分布"
+            "usageDistribution": "使用分布",
+            "date": "日付",
+            "usageCount": "使用回数",
+            "fileSizeBytes": "ファイルサイズ（バイト）",
+            "models": "モデル",
+            "loraUsage": "LoRA 使用量",
+            "checkpointUsage": "Checkpoint 使用量",
+            "embeddingUsage": "Embedding 使用量"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Checkpoint",
+            "diffusion_model": "拡散モデル",
+            "embedding": "Embedding"
+        },
+        "placeholders": {
+            "loading": "読み込み中...",
+            "noModels": "モデルが見つかりません",
+            "errorLoading": "データ読み込みエラー",
+            "noStorageData": "ストレージデータがありません",
+            "rootFolder": "ルート",
+            "chartLibraryMissing": "Chart.js ライブラリが必要です"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} モデル",
+            "chartUsage": "{name}: {size}, {count} 回使用",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "URLからモデルをダウンロード",
             "titleWithType": "URLから{type}をダウンロード",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL：",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "1行に1つのCivitAIまたはCivArchive URLを入力してください。複数のURLを一括ダウンロードできます。",
             "locationPreview": "ダウンロード場所プレビュー",
             "useDefaultPath": "デフォルトパスを使用",
             "useDefaultPathTooltip": "有効にすると、設定されたパステンプレートを使用してファイルが自動的に整理されます",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "以前にダウンロード済みですが、現在はライブラリにありません。",
             "alreadyInLibrary": "既にライブラリ内",
             "autoOrganizedPath": "[パステンプレートによる自動整理]",
+            "fileSelection": {
+                "title": "ファイル形式を選択",
+                "files": "ファイル",
+                "select": "ファイルを選択"
+            },
             "errors": {
                 "invalidUrl": "無効なCivitai URL形式",
                 "noVersions": "このモデルの利用可能なバージョンがありません"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "メモが正常に保存されました",
-                "saveFailed": "メモの保存に失敗しました"
+                "saveFailed": "メモの保存に失敗しました",
+                "showMore": "もっと見る",
+                "showLess": "折りたたむ"
             },
             "usageTips": {
                 "addPresetParameter": "プリセットパラメータを追加...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "バージョンを削除しました"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "メタデータ取得サマリー",
+            "statSuccess": "成功",
+            "statFailed": "失敗",
+            "statSkipped": "スキップ",
+            "statTotal": "スキャン合計",
+            "statDuration": "所要時間",
+            "successMessage": "すべての{count}件の{type}を正常に更新しました",
+            "failedItems": "失敗したアイテム ({count})",
+            "close": "閉じる",
+            "copyReport": "レポートをコピー",
+            "downloadCsv": "CSVをダウンロード",
+            "columnModelName": "モデル名",
+            "columnError": "エラー"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "このタグは既に存在します"
         }
     },
-    "keyboard": {
-        "navigation": "キーボードナビゲーション：",
-        "shortcuts": {
-            "pageUp": "1ページ上にスクロール",
-            "pageDown": "1ページ下にスクロール",
-            "home": "トップにジャンプ",
-            "end": "ボトムにジャンプ"
-        }
-    },
     "initialization": {
         "title": "初期化中",
         "message": "ワークスペースを準備中...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "現在のワークフローには互換性のあるノードがありません",
             "noTargetNodeSelected": "ターゲットノードが選択されていません",
             "modelUpdated": "モデルがワークフローで更新されました",
-            "modelFailed": "モデルノードの更新に失敗しました"
+            "modelFailed": "モデルノードの更新に失敗しました",
+            "embeddingAdded": "Embeddingをワークフローに追加しました",
+            "embeddingFailed": "Embeddingの追加に失敗しました"
         },
         "nodeSelector": {
             "recipe": "レシピ",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "置換",
             "append": "追加",
             "selectTargetNode": "ターゲットノードを選択",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "レシピIDが利用できません",
             "sendToWorkflowFailed": "ワークフローへのレシピ送信に失敗しました：{message}",
             "copyFailed": "レシピ構文のコピーエラー：{message}",
+            "createError": "レシピ作成中にエラーが発生しました：{message}",
+            "createFailed": "レシピの作成に失敗しました：{error}",
+            "createMissingData": "レシピ作成に必要なデータが不足しています",
+            "created": "レシピを作成しました",
             "noMissingLoras": "ダウンロードする不足LoRAがありません",
             "missingLorasInfoFailed": "不足LoRAの情報取得に失敗しました",
             "preparingForDownloadFailed": "ダウンロード用LoRAの準備中にエラーが発生しました",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "修復完了：{repaired} 件修復、{skipped} 件スキップ（合計 {total} 件）",
             "repairBulkSkipped": "選択した {total} 件のレシピは修復不要です",
             "repairBulkFailed": "選択したレシピの修復に失敗しました：{message}",
+            "reimporting": "ソースからレシピを再インポート中...",
+            "reimportSuccess": "レシピの再インポートが完了しました",
+            "reimportBulkComplete": "再インポート完了：{completed} 件成功、{failed} 件失敗（合計 {total} 件）",
+            "reimportBulkFailed": "一部のレシピの再インポートに失敗しました",
             "noMissingLorasInSelection": "選択したレシピに不足している LoRA が見つかりませんでした",
             "noLoraRootConfigured": "LoRA ルートディレクトリが設定されていません。設定でデフォルトの LoRA ルートを設定してください。"
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "{successCount} {type}が正常に移動されました",
             "exampleImagesDownloadSuccess": "例画像が正常にダウンロードされました！",
             "exampleImagesDownloadFailed": "例画像のダウンロードに失敗しました：{message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "クリップボードにコピーしました",
+            "downloadStarted": "ダウンロードを開始しました"
         }
     },
     "doctor": {

locales/ko.json

@@ -16,10 +16,13 @@
             "help": "도움말",
             "add": "추가",
             "close": "닫기",
-            "menu": "메뉴"
+            "menu": "메뉴",
+            "remove": "제거",
+            "change": "변경"
         },
         "status": {
             "loading": "로딩 중...",
+            "cancelling": "취소 중...",
             "unknown": "알 수 없음",
             "date": "날짜",
             "version": "버전",
@@ -111,6 +114,7 @@
             "replacePreview": "미리보기 교체",
             "copyCheckpointName": "Checkpoint 이름 복사",
             "copyEmbeddingName": "Embedding 이름 복사",
+            "embeddingNameCopied": "Embedding 구문 복사됨",
             "sendCheckpointToWorkflow": "ComfyUI로 전송",
             "sendEmbeddingToWorkflow": "ComfyUI로 전송"
         },
@@ -247,7 +251,18 @@
             "toggle": "테마 토글",
             "switchToLight": "라이트 테마로 전환",
             "switchToDark": "다크 테마로 전환",
-            "switchToAuto": "자동 테마로 전환"
+            "switchToAuto": "자동 테마로 전환",
+            "presets": "테마 프리셋",
+            "default": "기본",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "모드",
+            "light": "라이트",
+            "dark": "다크",
+            "auto": "자동"
         },
         "actions": {
             "checkUpdates": "업데이트 확인",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Civitai API 키",
         "civitaiApiKeyPlaceholder": "Civitai API 키를 입력하세요",
         "civitaiApiKeyHelp": "Civitai에서 모델을 다운로드할 때 인증에 사용됩니다",
+        "civitaiApiKeyConfigured": "설정됨",
+        "civitaiApiKeyNotConfigured": "설정되지 않음",
+        "civitaiApiKeySet": "설정",
         "civitaiHost": {
             "label": "Civitai 호스트",
             "help": "\"View on Civitai\" 링크를 사용할 때 어떤 Civitai 사이트를 열지 선택합니다.",
@@ -299,6 +317,7 @@
             "downloads": "다운로드",
             "videoSettings": "비디오 설정",
             "layoutSettings": "레이아웃 설정",
+            "licenseIcons": "라이선스 아이콘",
             "misc": "기타",
             "backup": "백업",
             "folderSettings": "기본 루트",
@@ -445,7 +464,9 @@
                 "modelName": "모델명",
                 "fileName": "파일명"
             },
-            "modelNameDisplayHelp": "모델 카드 하단에 표시할 내용을 선택하세요"
+            "modelNameDisplayHelp": "모델 카드 하단에 표시할 내용을 선택하세요",
+            "cardBlurAmount": "카드 오버레이 흐림 강도",
+            "cardBlurAmountHelp": "모델 및 레시피 카드의 헤더와 푸터 오버레이 흐림 강도를 조정합니다 (0 = 흐림 없음, 20 = 최대 흐림)."
         },
         "folderSettings": {
             "activeLibrary": "활성 라이브러리",
@@ -577,6 +598,10 @@
             "label": "얼리 액세스 업데이트 숨기기",
             "help": "얼리 액세스 업데이트만"
         },
+        "licenseIcons": {
+            "useNewStyle": "업데이트된 라이선스 아이콘 사용",
+            "useNewStyleHelp": "색상 표시기가 있는 라이선스 권한(새 스타일) 또는 제한 전용 아이콘(클래식 스타일)을 표시합니다. 현재 CivitAI 디자인을 반영합니다."
+        },
         "misc": {
             "includeTriggerWords": "LoRA 문법에 트리거 단어 포함",
             "includeTriggerWordsHelp": "LoRA 문법을 클립보드에 복사할 때 학습된 트리거 단어를 포함합니다",
@@ -690,6 +715,7 @@
             "copyAll": "모든 문법 복사",
             "refreshAll": "모든 메타데이터 새로고침",
             "repairMetadata": "선택한 레시피 메타데이터 복구",
+            "reimportMetadata": "소스에서 다시 가져오기",
             "checkUpdates": "선택 항목 업데이트 확인",
             "moveAll": "모두 폴더로 이동",
             "autoOrganize": "자동 정리 선택",
@@ -737,6 +763,7 @@
             "setContentRating": "콘텐츠 등급 설정",
             "moveToFolder": "폴더로 이동",
             "repairMetadata": "메타데이터 복구",
+            "reimportMetadata": "소스에서 다시 가져오기",
             "excludeModel": "모델 제외",
             "restoreModel": "모델 복원",
             "deleteModel": "모델 삭제",
@@ -864,6 +891,13 @@
                 "skipped": "레시피가 이미 최신 버전입니다. 복구가 필요하지 않습니다",
                 "failed": "레시피 복구 실패: {message}",
                 "missingId": "레시피를 복구할 수 없음: 레시피 ID 누락"
+            },
+            "reimport": {
+                "starting": "소스에서 레시피를 다시 가져오는 중...",
+                "success": "레시피를 다시 가져왔습니다",
+                "noSourceUrl": "레시피에 소스 URL이 없어 다시 가져올 수 없습니다",
+                "failed": "레시피 다시 가져오기 실패: {message}",
+                "missingId": "레시피를 다시 가져올 수 없음: 레시피 ID 누락"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "루트",
         "collapseAll": "모든 폴더 접기",
-        "pinSidebar": "사이드바 고정",
-        "unpinSidebar": "사이드바 고정 해제",
+        "hideOnThisPage": "이 페이지에서 사이드바 숨기기",
+        "showSidebar": "사이드바 표시",
+        "sidebarHiddenNotification": "{page} 페이지에서 사이드바가 숨겨져 있습니다",
         "switchToListView": "목록 보기로 전환",
         "switchToTreeView": "트리 보기로 전환",
         "recursiveOn": "하위 폴더 포함",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "폴더를 찾을 수 없습니다",
             "dragHint": "항목을 여기로 드래그하여 폴더를 만듭니다"
+        },
+        "folderUpdateCheck": {
+            "label": "이 폴더의 업데이트 확인",
+            "loading": "이 폴더의 {type} 업데이트를 확인하는 중...",
+            "success": "이 폴더에서 {type}s에 대한 {count}개 업데이트를 찾았습니다",
+            "none": "이 폴더의 모든 {type}s가 최신 상태입니다",
+            "error": "폴더의 {type} 업데이트 확인 실패: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "저장소",
             "insights": "인사이트"
         },
+        "metrics": {
+            "totalModels": "모델 총계",
+            "totalStorage": "총 저장 공간",
+            "totalGenerations": "총 생성 횟수",
+            "usageRate": "사용률",
+            "loras": "LoRA",
+            "checkpoints": "Checkpoint",
+            "embeddings": "Embedding",
+            "uniqueTags": "고유 태그",
+            "unusedModels": "미사용 모델",
+            "avgUsesPerModel": "모델당 평균 사용"
+        },
         "usage": {
             "mostUsedLoras": "가장 많이 사용된 LoRA",
             "mostUsedCheckpoints": "가장 많이 사용된 Checkpoint",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "스마트 인사이트",
-            "recommendations": "추천"
+            "recommendations": "추천",
+            "noInsights": "인사이트 없음",
+            "unusedLoras": {
+                "high": {
+                    "title": "사용하지 않은 LoRA가 많음",
+                    "description": "LoRA의 {percent}%({count}/{total})가 한 번도 사용되지 않았습니다.",
+                    "suggestion": "사용하지 않는 모델을 정리하거나 보관하여 저장 공간을 확보하세요."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "사용하지 않은 Checkpoint 감지",
+                    "description": "Checkpoint의 {percent}%({count}/{total})가 한 번도 사용되지 않았습니다.",
+                    "suggestion": "더 이상 필요하지 않은 Checkpoint를 검토하고 제거하세요."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "사용하지 않은 Embedding이 많음",
+                    "description": "Embedding의 {percent}%({count}/{total})가 한 번도 사용되지 않았습니다.",
+                    "suggestion": "사용하지 않는 Embedding을 정리하여 컬렉션을 최적화하세요."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "대규모 컬렉션 감지",
+                    "description": "모델 컬렉션이 {size}의 저장 공간을 사용 중입니다.",
+                    "suggestion": "더 나은 관리를 위해 외부 저장소나 클라우드 솔루션을 고려하세요."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "활성 사용자",
+                    "description": "지금까지 {count}번의 생성을 완료했습니다!",
+                    "suggestion": "모델로 계속해서 멋진 콘텐츠를 탐색하고 만들어보세요."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "컬렉션 개요",
             "baseModelDistribution": "베이스 모델 분포",
             "usageTrends": "사용량 트렌드 (최근 30일)",
-            "usageDistribution": "사용량 분포"
+            "usageDistribution": "사용량 분포",
+            "date": "날짜",
+            "usageCount": "사용 횟수",
+            "fileSizeBytes": "파일 크기(바이트)",
+            "models": "모델",
+            "loraUsage": "LoRA 사용량",
+            "checkpointUsage": "Checkpoint 사용량",
+            "embeddingUsage": "Embedding 사용량"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Checkpoint",
+            "diffusion_model": "확산 모델",
+            "embedding": "Embedding"
+        },
+        "placeholders": {
+            "loading": "로딩 중...",
+            "noModels": "모델을 찾을 수 없음",
+            "errorLoading": "데이터 로딩 오류",
+            "noStorageData": "저장 데이터 없음",
+            "rootFolder": "루트",
+            "chartLibraryMissing": "Chart.js 라이브러리가 필요합니다"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count}개 모델",
+            "chartUsage": "{name}: {size}, {count}회 사용",
+            "chartPercentage": "{label}: {value}({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "URL에서 모델 다운로드",
             "titleWithType": "URL에서 {type} 다운로드",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "한 줄에 하나의 CivitAI 또는 CivArchive URL을 입력하세요. 여러 URL을 일괄 다운로드할 수 있습니다.",
             "locationPreview": "다운로드 위치 미리보기",
             "useDefaultPath": "기본 경로 사용",
             "useDefaultPathTooltip": "활성화하면 구성된 경로 템플릿을 사용하여 파일이 자동으로 정리됩니다",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "이전에 다운로드했지만 현재 라이브러리에 없습니다.",
             "alreadyInLibrary": "이미 라이브러리에 있음",
             "autoOrganizedPath": "[경로 템플릿으로 자동 정리됨]",
+            "fileSelection": {
+                "title": "파일 형식 선택",
+                "files": "개 파일",
+                "select": "파일 선택"
+            },
             "errors": {
                 "invalidUrl": "잘못된 Civitai URL 형식",
                 "noVersions": "이 모델에 사용 가능한 버전이 없습니다"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "메모가 성공적으로 저장됨",
-                "saveFailed": "메모 저장 실패"
+                "saveFailed": "메모 저장 실패",
+                "showMore": "더 보기",
+                "showLess": "접기"
             },
             "usageTips": {
                 "addPresetParameter": "프리셋 매개변수 추가...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "버전이 삭제되었습니다"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "메타데이터 가져오기 요약",
+            "statSuccess": "성공",
+            "statFailed": "실패",
+            "statSkipped": "건너뜀",
+            "statTotal": "총 스캔",
+            "statDuration": "소요 시간",
+            "successMessage": "모든 {count}개 {type}이(가) 성공적으로 업데이트되었습니다",
+            "failedItems": "실패한 항목 ({count})",
+            "close": "닫기",
+            "copyReport": "보고서 복사",
+            "downloadCsv": "CSV 다운로드",
+            "columnModelName": "모델 이름",
+            "columnError": "오류"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "이 태그는 이미 존재합니다"
         }
     },
-    "keyboard": {
-        "navigation": "키보드 내비게이션:",
-        "shortcuts": {
-            "pageUp": "한 페이지 위로 스크롤",
-            "pageDown": "한 페이지 아래로 스크롤",
-            "home": "맨 위로 이동",
-            "end": "맨 아래로 이동"
-        }
-    },
     "initialization": {
         "title": "초기화 중",
         "message": "작업공간을 준비하고 있습니다...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "현재 워크플로에서 호환되는 노드가 없습니다",
             "noTargetNodeSelected": "대상 노드가 선택되지 않았습니다",
             "modelUpdated": "모델이 워크플로에서 업데이트되었습니다",
-            "modelFailed": "모델 노드 업데이트 실패"
+            "modelFailed": "모델 노드 업데이트 실패",
+            "embeddingAdded": "Embedding을 워크플로에 추가했습니다",
+            "embeddingFailed": "Embedding 추가 실패"
         },
         "nodeSelector": {
             "recipe": "레시피",
             "lora": "LoRA",
+            "embedding": "임베딩",
             "replace": "교체",
             "append": "추가",
             "selectTargetNode": "대상 노드 선택",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "사용 가능한 레시피 ID가 없습니다",
             "sendToWorkflowFailed": "워크플로우에 레시피 보내기 실패: {message}",
             "copyFailed": "레시피 문법 복사 오류: {message}",
+            "createError": "레시피 생성 중 오류 발생：{message}",
+            "createFailed": "레시피 생성 실패：{error}",
+            "createMissingData": "레시피 생성에 필요한 데이터가 없습니다",
+            "created": "레시피가 생성되었습니다",
             "noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
             "missingLorasInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
             "preparingForDownloadFailed": "LoRA 다운로드 준비 오류",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "복구 완료: {repaired}개 복구, {skipped}개 건너뜀 (총 {total}개)",
             "repairBulkSkipped": "선택한 {total}개 레시피는 복구가 필요하지 않습니다",
             "repairBulkFailed": "선택한 레시피 복구 실패: {message}",
+            "reimporting": "소스에서 레시피를 다시 가져오는 중...",
+            "reimportSuccess": "레시피를 다시 가져왔습니다",
+            "reimportBulkComplete": "다시 가져오기 완료: {completed}개 성공, {failed}개 실패 (총 {total}개)",
+            "reimportBulkFailed": "일부 레시피를 다시 가져오지 못했습니다",
             "noMissingLorasInSelection": "선택한 레시피에서 누락된 LoRA를 찾을 수 없습니다",
             "noLoraRootConfigured": "LoRA 루트 디렉토리가 구성되지 않았습니다. 설정에서 기본 LoRA 루트를 설정하세요."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "{successCount}개 {type}이(가) 성공적으로 이동되었습니다",
             "exampleImagesDownloadSuccess": "예시 이미지가 성공적으로 다운로드되었습니다!",
             "exampleImagesDownloadFailed": "예시 이미지 다운로드 실패: {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "클립보드에 복사됨",
+            "downloadStarted": "다운로드 시작됨"
         }
     },
     "doctor": {

locales/ru.json

@@ -16,10 +16,13 @@
             "help": "Справка",
             "add": "Добавить",
             "close": "Закрыть",
-            "menu": "Меню"
+            "menu": "Меню",
+            "remove": "Удалить",
+            "change": "Изменить"
         },
         "status": {
             "loading": "Загрузка...",
+            "cancelling": "Отмена...",
             "unknown": "Неизвестно",
             "date": "Дата",
             "version": "Версия",
@@ -111,6 +114,7 @@
             "replacePreview": "Заменить превью",
             "copyCheckpointName": "Копировать имя checkpoint",
             "copyEmbeddingName": "Копировать имя embedding",
+            "embeddingNameCopied": "Синтаксис embedding скопирован",
             "sendCheckpointToWorkflow": "Отправить в ComfyUI",
             "sendEmbeddingToWorkflow": "Отправить в ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "Переключить тему",
             "switchToLight": "Переключить на светлую тему",
             "switchToDark": "Переключить на тёмную тему",
-            "switchToAuto": "Переключить на автоматическую тему"
+            "switchToAuto": "Переключить на автоматическую тему",
+            "presets": "Предустановки тем",
+            "default": "По умолчанию",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "Режим",
+            "light": "Светлый",
+            "dark": "Тёмный",
+            "auto": "Авто"
         },
         "actions": {
             "checkUpdates": "Проверить обновления",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Ключ API Civitai",
         "civitaiApiKeyPlaceholder": "Введите ваш ключ API Civitai",
         "civitaiApiKeyHelp": "Используется для аутентификации при загрузке моделей с Civitai",
+        "civitaiApiKeyConfigured": "Настроен",
+        "civitaiApiKeyNotConfigured": "Не настроен",
+        "civitaiApiKeySet": "Настроить",
         "civitaiHost": {
             "label": "Хост Civitai",
             "help": "Выберите, какой сайт Civitai будет открываться при использовании ссылок «View on Civitai».",
@@ -299,6 +317,7 @@
             "downloads": "Загрузки",
             "videoSettings": "Настройки видео",
             "layoutSettings": "Настройки макета",
+            "licenseIcons": "Значки лицензии",
             "misc": "Разное",
             "backup": "Резервные копии",
             "folderSettings": "Корневые папки",
@@ -445,7 +464,9 @@
                 "modelName": "Название модели",
                 "fileName": "Имя файла"
             },
-            "modelNameDisplayHelp": "Выберите, что отображать в нижней части карточки модели"
+            "modelNameDisplayHelp": "Выберите, что отображать в нижней части карточки модели",
+            "cardBlurAmount": "Размытие наложения карточек",
+            "cardBlurAmountHelp": "Настройте интенсивность размытия наложений верхнего и нижнего колонтитулов на карточках моделей и рецептов (0 = без размытия, 20 = максимальное размытие)."
         },
         "folderSettings": {
             "activeLibrary": "Активная библиотека",
@@ -577,6 +598,10 @@
             "label": "Скрыть обновления раннего доступа",
             "help": "Только обновления раннего доступа"
         },
+        "licenseIcons": {
+            "useNewStyle": "Использовать обновлённые значки лицензии",
+            "useNewStyleHelp": "Отображать разрешения лицензии с цветными индикаторами (новый стиль) или только значки ограничений (классический стиль). Соответствует текущему дизайну CivitAI."
+        },
         "misc": {
             "includeTriggerWords": "Включать триггерные слова в синтаксис LoRA",
             "includeTriggerWordsHelp": "Включать обученные триггерные слова при копировании синтаксиса LoRA в буфер обмена",
@@ -690,6 +715,7 @@
             "copyAll": "Копировать весь синтаксис",
             "refreshAll": "Обновить все метаданные",
             "repairMetadata": "Восстановить метаданные для выбранных",
+            "reimportMetadata": "Переимпортировать из источника",
             "checkUpdates": "Проверить обновления для выбранных",
             "moveAll": "Переместить все в папку",
             "autoOrganize": "Автоматически организовать выбранные",
@@ -737,6 +763,7 @@
             "setContentRating": "Установить рейтинг контента",
             "moveToFolder": "Переместить в папку",
             "repairMetadata": "Восстановить метаданные",
+            "reimportMetadata": "Переимпортировать из источника",
             "excludeModel": "Исключить модель",
             "restoreModel": "Восстановить модель",
             "deleteModel": "Удалить модель",
@@ -864,6 +891,13 @@
                 "skipped": "Рецепт уже последней версии, восстановление не требуется",
                 "failed": "Не удалось восстановить рецепт: {message}",
                 "missingId": "Не удалось восстановить рецепт: отсутствует ID рецепта"
+            },
+            "reimport": {
+                "starting": "Переимпорт рецепта из источника...",
+                "success": "Рецепт успешно переимпортирован",
+                "noSourceUrl": "У рецепта нет URL источника, переимпорт невозможен",
+                "failed": "Не удалось переимпортировать рецепт: {message}",
+                "missingId": "Невозможно переимпортировать рецепт: отсутствует ID"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "Корень",
         "collapseAll": "Свернуть все папки",
-        "pinSidebar": "Закрепить боковую панель",
-        "unpinSidebar": "Открепить боковую панель",
+        "hideOnThisPage": "Скрыть боковую панель на этой странице",
+        "showSidebar": "Показать боковую панель",
+        "sidebarHiddenNotification": "Боковая панель скрыта на странице {page}",
         "switchToListView": "Переключить на вид списка",
         "switchToTreeView": "Переключить на древовидный вид",
         "recursiveOn": "Включать вложенные папки",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "Папки не найдены",
             "dragHint": "Перетащите элементы сюда, чтобы создать папки"
+        },
+        "folderUpdateCheck": {
+            "label": "Проверить обновления в этой папке",
+            "loading": "Проверка обновлений {type} в этой папке...",
+            "success": "Найдено {count} обновление(й) для {type}s в этой папке",
+            "none": "Все {type}s в этой папке актуальны",
+            "error": "Не удалось проверить папку на наличие обновлений {type}: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "Хранение",
             "insights": "Аналитика"
         },
+        "metrics": {
+            "totalModels": "Всего моделей",
+            "totalStorage": "Всего хранилища",
+            "totalGenerations": "Всего генераций",
+            "usageRate": "Коэффициент использования",
+            "loras": "LoRA",
+            "checkpoints": "Контрольные точки",
+            "embeddings": "Эмбеддинги",
+            "uniqueTags": "Уникальные теги",
+            "unusedModels": "Неиспользуемые модели",
+            "avgUsesPerModel": "Сред. использований/модель"
+        },
         "usage": {
             "mostUsedLoras": "Наиболее используемые LoRAs",
             "mostUsedCheckpoints": "Наиболее используемые Checkpoints",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "Умная аналитика",
-            "recommendations": "Рекомендации"
+            "recommendations": "Рекомендации",
+            "noInsights": "Нет доступных данных",
+            "unusedLoras": {
+                "high": {
+                    "title": "Большое количество неиспользуемых LoRA",
+                    "description": "{percent}% ваших LoRA ({count}/{total}) никогда не использовались.",
+                    "suggestion": "Рассмотрите возможность организации или архивирования неиспользуемых моделей для освобождения места."
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "Обнаружены неиспользуемые контрольные точки",
+                    "description": "{percent}% ваших контрольных точек ({count}/{total}) никогда не использовались.",
+                    "suggestion": "Проверьте и удалите ненужные контрольные точки."
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "Большое количество неиспользуемых эмбеддингов",
+                    "description": "{percent}% ваших эмбеддингов ({count}/{total}) никогда не использовались.",
+                    "suggestion": "Организуйте или архивируйте неиспользуемые эмбеддинги для оптимизации коллекции."
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "Обнаружена большая коллекция",
+                    "description": "Ваша коллекция моделей использует {size} хранилища.",
+                    "suggestion": "Рассмотрите внешнее хранилище или облачные решения для лучшей организации."
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "Активный пользователь",
+                    "description": "Вы завершили {count} генераций!",
+                    "suggestion": "Продолжайте исследовать и создавать удивительный контент с вашими моделями."
+                }
+            }
         },
         "charts": {
             "collectionOverview": "Обзор коллекции",
             "baseModelDistribution": "Распределение базовых моделей",
             "usageTrends": "Тенденции использования (за последние 30 дней)",
-            "usageDistribution": "Распределение использования"
+            "usageDistribution": "Распределение использования",
+            "date": "Дата",
+            "usageCount": "Количество использований",
+            "fileSizeBytes": "Размер файла (байты)",
+            "models": "Модели",
+            "loraUsage": "Использование LoRA",
+            "checkpointUsage": "Использование Checkpoint",
+            "embeddingUsage": "Использование Embedding"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Контрольная точка",
+            "diffusion_model": "Диффузионная модель",
+            "embedding": "Эмбеддинги"
+        },
+        "placeholders": {
+            "loading": "Загрузка...",
+            "noModels": "Модели не найдены",
+            "errorLoading": "Ошибка загрузки данных",
+            "noStorageData": "Нет данных о хранилище",
+            "rootFolder": "Корень",
+            "chartLibraryMissing": "Для графика требуется библиотека Chart.js"
+        },
+        "tooltips": {
+            "tagCount": "{tag}: {count} моделей",
+            "chartUsage": "{name}: {size}, {count} использований",
+            "chartPercentage": "{label}: {value} ({pct}%)"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "Скачать модель по URL",
             "titleWithType": "Скачать {type} по URL",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Введите один URL CivitAI или CivArchive в каждой строке. Поддерживается пакетная загрузка нескольких URL.",
             "locationPreview": "Предпросмотр места загрузки",
             "useDefaultPath": "Использовать путь по умолчанию",
             "useDefaultPathTooltip": "При включении файлы автоматически организуются с использованием настроенных шаблонов путей",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "Ранее загружено, но сейчас этого нет в вашей библиотеке.",
             "alreadyInLibrary": "Уже в библиотеке",
             "autoOrganizedPath": "[Автоматически организовано по шаблону пути]",
+            "fileSelection": {
+                "title": "Выбрать формат файла",
+                "files": "файлов",
+                "select": "Выбрать файл"
+            },
             "errors": {
                 "invalidUrl": "Неверный формат URL Civitai",
                 "noVersions": "Нет доступных версий для этой модели"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "Заметки успешно сохранены",
-                "saveFailed": "Не удалось сохранить заметки"
+                "saveFailed": "Не удалось сохранить заметки",
+                "showMore": "Показать больше",
+                "showLess": "Свернуть"
             },
             "usageTips": {
                 "addPresetParameter": "Добавить предустановленный параметр...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "Версия удалена"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "Сводка получения метаданных",
+            "statSuccess": "Успешно",
+            "statFailed": "Ошибка",
+            "statSkipped": "Пропущено",
+            "statTotal": "Всего проверено",
+            "statDuration": "Длительность",
+            "successMessage": "Все {count} {type}s успешно обновлены",
+            "failedItems": "Ошибочные элементы ({count})",
+            "close": "Закрыть",
+            "copyReport": "Копировать отчет",
+            "downloadCsv": "Скачать CSV",
+            "columnModelName": "Имя модели",
+            "columnError": "Ошибка"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "Этот тег уже существует"
         }
     },
-    "keyboard": {
-        "navigation": "Навигация с клавиатуры:",
-        "shortcuts": {
-            "pageUp": "Прокрутить на страницу вверх",
-            "pageDown": "Прокрутить на страницу вниз",
-            "home": "Перейти к началу",
-            "end": "Перейти к концу"
-        }
-    },
     "initialization": {
         "title": "Инициализация",
         "message": "Подготовка вашего рабочего пространства...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "В текущем workflow нет совместимых узлов",
             "noTargetNodeSelected": "Целевой узел не выбран",
             "modelUpdated": "Модель обновлена в workflow",
-            "modelFailed": "Не удалось обновить узел модели"
+            "modelFailed": "Не удалось обновить узел модели",
+            "embeddingAdded": "Embedding добавлен в workflow",
+            "embeddingFailed": "Не удалось добавить embedding"
         },
         "nodeSelector": {
             "recipe": "Рецепт",
             "lora": "LoRA",
+            "embedding": "Эмбеддинг",
             "replace": "Заменить",
             "append": "Добавить",
             "selectTargetNode": "Выберите целевой узел",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "ID рецепта недоступен",
             "sendToWorkflowFailed": "Не удалось отправить рецепт в рабочий процесс: {message}",
             "copyFailed": "Ошибка копирования синтаксиса рецепта: {message}",
+            "createError": "Ошибка при создании рецепта：{message}",
+            "createFailed": "Не удалось создать рецепт：{error}",
+            "createMissingData": "Отсутствуют необходимые данные для создания рецепта",
+            "created": "Рецепт успешно создан",
             "noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
             "missingLorasInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
             "preparingForDownloadFailed": "Ошибка подготовки LoRAs для загрузки",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "Восстановление завершено: {repaired} восстановлено, {skipped} пропущено (из {total})",
             "repairBulkSkipped": "Ни один из {total} выбранных рецептов не требует восстановления",
             "repairBulkFailed": "Не удалось восстановить выбранные рецепты: {message}",
+            "reimporting": "Переимпорт рецепта из источника...",
+            "reimportSuccess": "Рецепт успешно переимпортирован",
+            "reimportBulkComplete": "Переимпорт завершён: {completed} переимпортировано, {failed} ошибок (из {total})",
+            "reimportBulkFailed": "Не удалось переимпортировать некоторые рецепты",
             "noMissingLorasInSelection": "В выбранных рецептах не найдены отсутствующие LoRAs",
             "noLoraRootConfigured": "Корневой каталог LoRA не настроен. Пожалуйста, установите корневой каталог LoRA по умолчанию в настройках."
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "Успешно перемещено {successCount} {type}s",
             "exampleImagesDownloadSuccess": "Примеры изображений успешно загружены!",
             "exampleImagesDownloadFailed": "Не удалось загрузить примеры изображений: {message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "Скопировано в буфер обмена",
+            "downloadStarted": "Загрузка начата"
         }
     },
     "doctor": {

locales/zh-CN.json

@@ -16,10 +16,13 @@
             "help": "帮助",
             "add": "添加",
             "close": "关闭",
-            "menu": "菜单"
+            "menu": "菜单",
+            "remove": "移除",
+            "change": "更换"
         },
         "status": {
             "loading": "加载中...",
+            "cancelling": "取消中...",
             "unknown": "未知",
             "date": "日期",
             "version": "版本",
@@ -111,6 +114,7 @@
             "replacePreview": "替换预览",
             "copyCheckpointName": "复制 Checkpoint 名称",
             "copyEmbeddingName": "复制 Embedding 名称",
+            "embeddingNameCopied": "已复制 Embedding 语法",
             "sendCheckpointToWorkflow": "发送到 ComfyUI",
             "sendEmbeddingToWorkflow": "发送到 ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "切换主题",
             "switchToLight": "切换到浅色主题",
             "switchToDark": "切换到深色主题",
-            "switchToAuto": "切换到自动主题"
+            "switchToAuto": "切换到自动主题",
+            "presets": "主题预设",
+            "default": "默认",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "模式",
+            "light": "浅色",
+            "dark": "深色",
+            "auto": "自动"
         },
         "actions": {
             "checkUpdates": "检查更新",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Civitai API 密钥",
         "civitaiApiKeyPlaceholder": "请输入你的 Civitai API 密钥",
         "civitaiApiKeyHelp": "用于从 Civitai 下载模型时的身份验证",
+        "civitaiApiKeyConfigured": "已配置",
+        "civitaiApiKeyNotConfigured": "未配置",
+        "civitaiApiKeySet": "设置",
         "civitaiHost": {
             "label": "Civitai 站点",
             "help": "选择使用“在 Civitai 中查看”时默认打开的 Civitai 站点。",
@@ -299,6 +317,7 @@
             "downloads": "下载",
             "videoSettings": "视频设置",
             "layoutSettings": "布局设置",
+            "licenseIcons": "许可协议图标",
             "misc": "其他",
             "backup": "备份",
             "folderSettings": "默认根目录",
@@ -445,7 +464,9 @@
                 "modelName": "模型名称",
                 "fileName": "文件名"
             },
-            "modelNameDisplayHelp": "选择在模型卡片底部显示的内容"
+            "modelNameDisplayHelp": "选择在模型卡片底部显示的内容",
+            "cardBlurAmount": "卡片叠加模糊强度",
+            "cardBlurAmountHelp": "调整模型和配方卡片上页眉和页脚叠加层的模糊强度（0 = 无模糊，20 = 最大模糊）。"
         },
         "folderSettings": {
             "activeLibrary": "活动库",
@@ -577,6 +598,10 @@
             "label": "隐藏抢先体验更新",
             "help": "抢先体验更新"
         },
+        "licenseIcons": {
+            "useNewStyle": "使用新版许可协议图标",
+            "useNewStyleHelp": "以彩色指示器显示许可权限（新样式），或仅显示限制图标（经典样式）。与当前 CivitAI 设计保持一致。"
+        },
         "misc": {
             "includeTriggerWords": "复制 LoRA 语法时包含触发词",
             "includeTriggerWordsHelp": "复制 LoRA 语法到剪贴板时包含训练触发词",
@@ -690,6 +715,7 @@
             "copyAll": "复制所选中语法",
             "refreshAll": "刷新所选中元数据",
             "repairMetadata": "修复所选中元数据",
+            "reimportMetadata": "从源重新导入",
             "checkUpdates": "检查所选更新",
             "moveAll": "移动所选中到文件夹",
             "autoOrganize": "自动整理所选模型",
@@ -737,6 +763,7 @@
             "setContentRating": "设置内容评级",
             "moveToFolder": "移动到文件夹",
             "repairMetadata": "修复元数据",
+            "reimportMetadata": "从源重新导入",
             "excludeModel": "排除模型",
             "restoreModel": "恢复模型",
             "deleteModel": "删除模型",
@@ -864,6 +891,13 @@
                 "skipped": "配方已是最新版本，无需修复",
                 "failed": "修复配方失败：{message}",
                 "missingId": "无法修复配方：缺少配方 ID"
+            },
+            "reimport": {
+                "starting": "正在从源重新导入配方...",
+                "success": "配方已从源重新导入成功",
+                "noSourceUrl": "配方没有源URL，无法重新导入",
+                "failed": "重新导入配方失败：{message}",
+                "missingId": "无法重新导入配方：缺少配方ID"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "根目录",
         "collapseAll": "折叠所有文件夹",
-        "pinSidebar": "固定侧边栏",
-        "unpinSidebar": "取消固定侧边栏",
+        "hideOnThisPage": "隐藏此页面侧边栏",
+        "showSidebar": "显示侧边栏",
+        "sidebarHiddenNotification": "{page}页面的文件夹侧边栏已隐藏",
         "switchToListView": "切换到列表视图",
         "switchToTreeView": "切换到树状视图",
         "recursiveOn": "包含子文件夹",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "未找到文件夹",
             "dragHint": "拖拽项目到此处以创建文件夹"
+        },
+        "folderUpdateCheck": {
+            "label": "检查此文件夹的更新",
+            "loading": "正在检查此文件夹中的{type}更新...",
+            "success": "在此文件夹中找到 {count} 个{type}更新",
+            "none": "此文件夹中的所有{type}都是最新版本",
+            "error": "检查文件夹{type}更新失败: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "存储",
             "insights": "洞察"
         },
+        "metrics": {
+            "totalModels": "模型总数",
+            "totalStorage": "总存储空间",
+            "totalGenerations": "总生成次数",
+            "usageRate": "使用率",
+            "loras": "LoRA",
+            "checkpoints": "Checkpoint",
+            "embeddings": "Embedding",
+            "uniqueTags": "唯一标签",
+            "unusedModels": "未使用模型",
+            "avgUsesPerModel": "平均使用次数/模型"
+        },
         "usage": {
             "mostUsedLoras": "最常用 LoRA",
             "mostUsedCheckpoints": "最常用 Checkpoint",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "智能洞察",
-            "recommendations": "推荐"
+            "recommendations": "推荐",
+            "noInsights": "暂无可用洞察",
+            "unusedLoras": {
+                "high": {
+                    "title": "大量未使用的 LoRA",
+                    "description": "你的 LoRA 中有 {percent}%（{count}/{total}）从未被使用过。",
+                    "suggestion": "考虑整理或归档未使用的模型以释放存储空间。"
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "检测到未使用的 Checkpoint",
+                    "description": "你的 Checkpoint 中有 {percent}%（{count}/{total}）从未被使用过。",
+                    "suggestion": "审查并考虑删除不再需要的 Checkpoint。"
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "大量未使用的 Embedding",
+                    "description": "你的 Embedding 中有 {percent}%（{count}/{total}）从未被使用过。",
+                    "suggestion": "考虑整理或归档未使用的 Embedding 以优化你的收藏。"
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "检测到大型收藏",
+                    "description": "你的模型收藏正在使用 {size} 的存储空间。",
+                    "suggestion": "考虑使用外部存储或云解决方案以获得更好的组织。"
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "活跃用户",
+                    "description": "你已经完成了 {count} 次生成！",
+                    "suggestion": "继续探索并用你的模型创作精彩内容。"
+                }
+            }
         },
         "charts": {
             "collectionOverview": "收藏概览",
             "baseModelDistribution": "基础模型分布",
             "usageTrends": "使用趋势（最近30天）",
-            "usageDistribution": "使用分布"
+            "usageDistribution": "使用分布",
+            "date": "日期",
+            "usageCount": "使用次数",
+            "fileSizeBytes": "文件大小（字节）",
+            "models": "模型",
+            "loraUsage": "LoRA 使用量",
+            "checkpointUsage": "Checkpoint 使用量",
+            "embeddingUsage": "Embedding 使用量"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Checkpoint",
+            "diffusion_model": "扩散模型",
+            "embedding": "Embedding"
+        },
+        "placeholders": {
+            "loading": "加载中...",
+            "noModels": "未找到模型",
+            "errorLoading": "数据加载失败",
+            "noStorageData": "暂无存储数据",
+            "rootFolder": "根目录",
+            "chartLibraryMissing": "需要 Chart.js 库来显示图表"
+        },
+        "tooltips": {
+            "tagCount": "{tag}：{count} 个模型",
+            "chartUsage": "{name}：{size}，{count} 次使用",
+            "chartPercentage": "{label}：{value}（{pct}%）"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "从 URL 下载模型",
             "titleWithType": "从 URL 下载 {type}",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "每行输入一个 CivitAI 或 CivArchive URL。支持批量下载多个 URL。",
             "locationPreview": "下载位置预览",
             "useDefaultPath": "使用默认路径",
             "useDefaultPathTooltip": "启用后，文件将自动按配置的路径模板进行整理",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "之前已下载，但当前不在你的库中。",
             "alreadyInLibrary": "已存在于库中",
             "autoOrganizedPath": "【已按路径模板自动整理】",
+            "fileSelection": {
+                "title": "选择文件格式",
+                "files": "个文件",
+                "select": "选择文件"
+            },
             "errors": {
                 "invalidUrl": "无效的 Civitai URL 格式",
                 "noVersions": "此模型没有可用版本"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "备注保存成功",
-                "saveFailed": "备注保存失败"
+                "saveFailed": "备注保存失败",
+                "showMore": "展开",
+                "showLess": "收起"
             },
             "usageTips": {
                 "addPresetParameter": "添加预设参数...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "版本已删除"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "元数据获取摘要",
+            "statSuccess": "成功",
+            "statFailed": "失败",
+            "statSkipped": "已跳过",
+            "statTotal": "总计扫描",
+            "statDuration": "耗时",
+            "successMessage": "全部 {count} 个 {type} 更新成功！",
+            "failedItems": "失败项目 ({count})",
+            "close": "关闭",
+            "copyReport": "复制报告",
+            "downloadCsv": "下载 CSV",
+            "columnModelName": "模型名称",
+            "columnError": "错误"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "该标签已存在"
         }
     },
-    "keyboard": {
-        "navigation": "键盘导航：",
-        "shortcuts": {
-            "pageUp": "向上一页滚动",
-            "pageDown": "向下一页滚动",
-            "home": "跳到顶部",
-            "end": "跳到底部"
-        }
-    },
     "initialization": {
         "title": "初始化",
         "message": "正在准备你的工作空间...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "当前工作流中没有兼容的节点",
             "noTargetNodeSelected": "未选择目标节点",
             "modelUpdated": "模型已更新到工作流",
-            "modelFailed": "更新模型节点失败"
+            "modelFailed": "更新模型节点失败",
+            "embeddingAdded": "Embedding 已追加到工作流",
+            "embeddingFailed": "添加 Embedding 失败"
         },
         "nodeSelector": {
             "recipe": "配方",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "替换",
             "append": "追加",
             "selectTargetNode": "选择目标节点",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "无配方 ID",
             "sendToWorkflowFailed": "发送配方到工作流失败：{message}",
             "copyFailed": "复制配方语法出错：{message}",
+            "createError": "创建配方时出错：{message}",
+            "createFailed": "创建配方失败：{error}",
+            "createMissingData": "缺少创建配方所需的数据",
+            "created": "配方创建成功",
             "noMissingLoras": "没有缺失的 LoRA 可下载",
             "missingLorasInfoFailed": "获取缺失 LoRA 信息失败",
             "preparingForDownloadFailed": "准备下载 LoRA 时出错",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "修复完成：{repaired} 个已修复，{skipped} 个已跳过（共 {total} 个）",
             "repairBulkSkipped": "所选 {total} 个配方无需修复",
             "repairBulkFailed": "修复所选配方失败：{message}",
+            "reimporting": "正在从源重新导入配方...",
+            "reimportSuccess": "配方已从源重新导入成功",
+            "reimportBulkComplete": "重新导入完成：{completed} 个已导入，{failed} 个失败（共 {total} 个）",
+            "reimportBulkFailed": "重新导入某些配方失败",
             "noMissingLorasInSelection": "在选定的配方中未找到缺失的 LoRAs",
             "noLoraRootConfigured": "未配置 LoRA 根目录。请在设置中设置默认的 LoRA 根目录。"
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "成功移动 {successCount} 个 {type}",
             "exampleImagesDownloadSuccess": "示例图片下载成功！",
             "exampleImagesDownloadFailed": "示例图片下载失败：{message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "已复制到剪贴板",
+            "downloadStarted": "下载已开始"
         }
     },
     "doctor": {

locales/zh-TW.json

@@ -16,10 +16,13 @@
             "help": "說明",
             "add": "新增",
             "close": "關閉",
-            "menu": "選單"
+            "menu": "選單",
+            "remove": "移除",
+            "change": "更換"
         },
         "status": {
             "loading": "載入中...",
+            "cancelling": "取消中...",
             "unknown": "未知",
             "date": "日期",
             "version": "版本",
@@ -111,6 +114,7 @@
             "replacePreview": "更換預覽圖",
             "copyCheckpointName": "複製檢查點名稱",
             "copyEmbeddingName": "複製嵌入名稱",
+            "embeddingNameCopied": "已複製 Embedding 語法",
             "sendCheckpointToWorkflow": "傳送到 ComfyUI",
             "sendEmbeddingToWorkflow": "傳送到 ComfyUI"
         },
@@ -247,7 +251,18 @@
             "toggle": "切換主題",
             "switchToLight": "切換至淺色主題",
             "switchToDark": "切換至深色主題",
-            "switchToAuto": "自動主題"
+            "switchToAuto": "自動主題",
+            "presets": "主題預設",
+            "default": "預設",
+            "nord": "Nord",
+            "midnight": "Midnight",
+            "monokai": "Monokai",
+            "dracula": "Dracula",
+            "solarized": "Solarized",
+            "mode": "模式",
+            "light": "淺色",
+            "dark": "深色",
+            "auto": "自動"
         },
         "actions": {
             "checkUpdates": "檢查更新",
@@ -259,6 +274,9 @@
         "civitaiApiKey": "Civitai API 金鑰",
         "civitaiApiKeyPlaceholder": "請輸入您的 Civitai API 金鑰",
         "civitaiApiKeyHelp": "用於從 Civitai 下載模型時的身份驗證",
+        "civitaiApiKeyConfigured": "已設定",
+        "civitaiApiKeyNotConfigured": "未設定",
+        "civitaiApiKeySet": "設定",
         "civitaiHost": {
             "label": "Civitai 站點",
             "help": "選擇使用「在 Civitai 中查看」時預設開啟的 Civitai 站點。",
@@ -299,6 +317,7 @@
             "downloads": "下載",
             "videoSettings": "影片設定",
             "layoutSettings": "版面設定",
+            "licenseIcons": "許可協議圖標",
             "misc": "其他",
             "backup": "備份",
             "folderSettings": "預設根目錄",
@@ -445,7 +464,9 @@
                 "modelName": "模型名稱",
                 "fileName": "檔案名稱"
             },
-            "modelNameDisplayHelp": "選擇在模型卡片底部顯示的內容"
+            "modelNameDisplayHelp": "選擇在模型卡片底部顯示的內容",
+            "cardBlurAmount": "卡片疊加模糊強度",
+            "cardBlurAmountHelp": "調整模型和配方卡片上頁首和頁尾疊加層的模糊強度（0 = 無模糊，20 = 最大模糊）。"
         },
         "folderSettings": {
             "activeLibrary": "使用中的資料庫",
@@ -577,6 +598,10 @@
             "label": "隱藏搶先體驗更新",
             "help": "搶先體驗更新"
         },
+        "licenseIcons": {
+            "useNewStyle": "使用新版許可協議圖標",
+            "useNewStyleHelp": "以彩色指示器顯示許可權限（新樣式），或僅顯示限制圖標（經典樣式）。與當前 CivitAI 設計保持一致。"
+        },
         "misc": {
             "includeTriggerWords": "在 LoRA 語法中包含觸發詞",
             "includeTriggerWordsHelp": "複製 LoRA 語法到剪貼簿時包含訓練觸發詞",
@@ -690,6 +715,7 @@
             "copyAll": "複製全部語法",
             "refreshAll": "刷新全部 metadata",
             "repairMetadata": "修復所選中元數據",
+            "reimportMetadata": "從來源重新匯入",
             "checkUpdates": "檢查所選更新",
             "moveAll": "全部移動到資料夾",
             "autoOrganize": "自動整理所選模型",
@@ -737,6 +763,7 @@
             "setContentRating": "設定內容分級",
             "moveToFolder": "移動到資料夾",
             "repairMetadata": "修復元數據",
+            "reimportMetadata": "從來源重新匯入",
             "excludeModel": "排除模型",
             "restoreModel": "還原模型",
             "deleteModel": "刪除模型",
@@ -864,6 +891,13 @@
                 "skipped": "配方已是最新版本，無需修復",
                 "failed": "修復配方失敗：{message}",
                 "missingId": "無法修復配方：缺少配方 ID"
+            },
+            "reimport": {
+                "starting": "正在從來源重新匯入配方...",
+                "success": "配方已從來源重新匯入成功",
+                "noSourceUrl": "配方沒有來源URL，無法重新匯入",
+                "failed": "重新匯入配方失敗：{message}",
+                "missingId": "無法重新匯入配方：缺少配方ID"
             }
         },
         "batchImport": {
@@ -942,8 +976,9 @@
     "sidebar": {
         "modelRoot": "根目錄",
         "collapseAll": "全部摺疊資料夾",
-        "pinSidebar": "固定側邊欄",
-        "unpinSidebar": "取消固定側邊欄",
+        "hideOnThisPage": "隱藏此頁面側邊欄",
+        "showSidebar": "顯示側邊欄",
+        "sidebarHiddenNotification": "{page}頁面的資料夾側邊欄已隱藏",
         "switchToListView": "切換至列表檢視",
         "switchToTreeView": "切換到樹狀檢視",
         "recursiveOn": "包含子資料夾",
@@ -963,6 +998,13 @@
         "empty": {
             "noFolders": "未找到資料夾",
             "dragHint": "將項目拖到此處以建立資料夾"
+        },
+        "folderUpdateCheck": {
+            "label": "檢查此資料夾的更新",
+            "loading": "正在檢查此資料夾中的{type}更新...",
+            "success": "在此資料夾中找到 {count} 個{type}更新",
+            "none": "此資料夾中的所有{type}都是最新版本",
+            "error": "檢查資料夾{type}更新失敗: {message}"
         }
     },
     "statistics": {
@@ -974,6 +1016,18 @@
             "storage": "儲存空間",
             "insights": "洞察"
         },
+        "metrics": {
+            "totalModels": "模型總數",
+            "totalStorage": "總儲存空間",
+            "totalGenerations": "總生成次數",
+            "usageRate": "使用率",
+            "loras": "LoRA",
+            "checkpoints": "Checkpoint",
+            "embeddings": "Embedding",
+            "uniqueTags": "唯一標籤",
+            "unusedModels": "未使用模型",
+            "avgUsesPerModel": "平均使用次數/模型"
+        },
         "usage": {
             "mostUsedLoras": "最常用的 LoRA",
             "mostUsedCheckpoints": "最常用的 Checkpoint",
@@ -991,13 +1045,77 @@
         },
         "insights": {
             "smartInsights": "智慧洞察",
-            "recommendations": "推薦"
+            "recommendations": "推薦",
+            "noInsights": "暫無可用洞察",
+            "unusedLoras": {
+                "high": {
+                    "title": "大量未使用的 LoRA",
+                    "description": "你的 LoRA 中有 {percent}%（{count}/{total}）從未被使用過。",
+                    "suggestion": "考慮整理或封存未使用的模型以釋放儲存空間。"
+                }
+            },
+            "unusedCheckpoints": {
+                "detected": {
+                    "title": "檢測到未使用的 Checkpoint",
+                    "description": "你的 Checkpoint 中有 {percent}%（{count}/{total}）從未被使用過。",
+                    "suggestion": "審查並考慮刪除不再需要的 Checkpoint。"
+                }
+            },
+            "unusedEmbeddings": {
+                "high": {
+                    "title": "大量未使用的 Embedding",
+                    "description": "你的 Embedding 中有 {percent}%（{count}/{total}）從未被使用過。",
+                    "suggestion": "考慮整理或封存未使用的 Embedding 以優化你的收藏。"
+                }
+            },
+            "collection": {
+                "large": {
+                    "title": "檢測到大型收藏",
+                    "description": "你的模型收藏正在使用 {size} 的儲存空間。",
+                    "suggestion": "考慮使用外部儲存或雲端解決方案以獲得更好的組織。"
+                }
+            },
+            "activity": {
+                "active": {
+                    "title": "活躍用戶",
+                    "description": "你已經完成了 {count} 次生成！",
+                    "suggestion": "繼續探索並用你的模型創作精彩內容。"
+                }
+            }
         },
         "charts": {
             "collectionOverview": "收藏總覽",
             "baseModelDistribution": "基礎模型分布",
             "usageTrends": "使用趨勢（最近 30 天）",
-            "usageDistribution": "使用分布"
+            "usageDistribution": "使用分布",
+            "date": "日期",
+            "usageCount": "使用次數",
+            "fileSizeBytes": "檔案大小（位元組）",
+            "models": "模型",
+            "loraUsage": "LoRA 使用量",
+            "checkpointUsage": "Checkpoint 使用量",
+            "embeddingUsage": "Embedding 使用量"
+        },
+        "modelTypes": {
+            "lora": "LoRA",
+            "locon": "LyCORIS",
+            "dora": "DoRA",
+            "checkpoint": "Checkpoint",
+            "diffusion_model": "擴散模型",
+            "embedding": "Embedding"
+        },
+        "placeholders": {
+            "loading": "載入中...",
+            "noModels": "找不到模型",
+            "errorLoading": "資料載入失敗",
+            "noStorageData": "暫無儲存資料",
+            "rootFolder": "根目錄",
+            "chartLibraryMissing": "需要 Chart.js 函式庫來顯示圖表"
+        },
+        "tooltips": {
+            "tagCount": "{tag}：{count} 個模型",
+            "chartUsage": "{name}：{size}，{count} 次使用",
+            "chartPercentage": "{label}：{value}（{pct}%）"
         }
     },
     "modals": {
@@ -1007,9 +1125,9 @@
         "download": {
             "title": "從網址下載模型",
             "titleWithType": "從網址下載 {type}",
-            "url": "Civitai 網址",
             "civitaiUrl": "Civitai 網址：",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "每行輸入一個 CivitAI 或 CivArchive URL。支援批量下載多個 URL。",
             "locationPreview": "下載位置預覽",
             "useDefaultPath": "使用預設路徑",
             "useDefaultPathTooltip": "啟用後，檔案將依照設定的路徑範本自動整理",
@@ -1031,6 +1149,11 @@
             "downloadedTooltip": "先前已下載，但目前不在你的庫中。",
             "alreadyInLibrary": "已在庫存",
             "autoOrganizedPath": "[依路徑範本自動整理]",
+            "fileSelection": {
+                "title": "選擇檔案格式",
+                "files": "個檔案",
+                "select": "選擇檔案"
+            },
             "errors": {
                 "invalidUrl": "Civitai 網址格式無效",
                 "noVersions": "此模型無可用版本"
@@ -1213,7 +1336,9 @@
             },
             "notes": {
                 "saved": "備註已儲存",
-                "saveFailed": "儲存備註失敗"
+                "saveFailed": "儲存備註失敗",
+                "showMore": "展開",
+                "showLess": "收起"
             },
             "usageTips": {
                 "addPresetParameter": "新增預設參數...",
@@ -1366,6 +1491,21 @@
                     "versionDeleted": "已刪除此版本"
                 }
             }
+        },
+        "metadataFetchSummary": {
+            "title": "元資料獲取摘要",
+            "statSuccess": "成功",
+            "statFailed": "失敗",
+            "statSkipped": "已跳過",
+            "statTotal": "總計掃描",
+            "statDuration": "耗時",
+            "successMessage": "全部 {count} 個 {type} 更新成功！",
+            "failedItems": "失敗項目 ({count})",
+            "close": "關閉",
+            "copyReport": "複製報告",
+            "downloadCsv": "下載 CSV",
+            "columnModelName": "模型名稱",
+            "columnError": "錯誤"
         }
     },
     "modelTags": {
@@ -1379,15 +1519,6 @@
             "duplicate": "此標籤已存在"
         }
     },
-    "keyboard": {
-        "navigation": "鍵盤導覽：",
-        "shortcuts": {
-            "pageUp": "向上捲動一頁",
-            "pageDown": "向下捲動一頁",
-            "home": "跳至頂部",
-            "end": "跳至底部"
-        }
-    },
     "initialization": {
         "title": "初始化",
         "message": "正在準備您的工作區...",
@@ -1475,11 +1606,14 @@
             "noMatchingNodes": "目前工作流程中沒有相容的節點",
             "noTargetNodeSelected": "未選擇目標節點",
             "modelUpdated": "模型已更新到工作流",
-            "modelFailed": "更新模型節點失敗"
+            "modelFailed": "更新模型節點失敗",
+            "embeddingAdded": "Embedding 已附加到工作流",
+            "embeddingFailed": "傳送 Embedding 到工作流失敗"
         },
         "nodeSelector": {
             "recipe": "配方",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "取代",
             "append": "附加",
             "selectTargetNode": "選擇目標節點",
@@ -1656,6 +1790,10 @@
             "noRecipeId": "無配方 ID",
             "sendToWorkflowFailed": "傳送配方到工作流失敗：{message}",
             "copyFailed": "複製配方語法錯誤：{message}",
+            "createError": "建立配方時發生錯誤：{message}",
+            "createFailed": "建立配方失敗：{error}",
+            "createMissingData": "缺少建立配方所需的資料",
+            "created": "配方建立成功",
             "noMissingLoras": "無缺少的 LoRA 可下載",
             "missingLorasInfoFailed": "取得缺少 LoRA 資訊失敗",
             "preparingForDownloadFailed": "準備下載 LoRA 時發生錯誤",
@@ -1697,6 +1835,10 @@
             "repairBulkComplete": "修復完成：{repaired} 個已修復，{skipped} 個已跳過（共 {total} 個）",
             "repairBulkSkipped": "所選 {total} 個配方無需修復",
             "repairBulkFailed": "修復所選配方失敗：{message}",
+            "reimporting": "正在從來源重新匯入配方...",
+            "reimportSuccess": "配方已從來源重新匯入成功",
+            "reimportBulkComplete": "重新匯入完成：{completed} 個已匯入，{failed} 個失敗（共 {total} 個）",
+            "reimportBulkFailed": "重新匯入某些配方失敗",
             "noMissingLorasInSelection": "在選取的食譜中未找到缺失的 LoRAs",
             "noLoraRootConfigured": "未配置 LoRA 根目錄。請在設定中設定預設的 LoRA 根目錄。"
         },
@@ -1914,7 +2056,9 @@
             "bulkMoveSuccess": "已成功移動 {successCount} 個 {type}",
             "exampleImagesDownloadSuccess": "範例圖片下載成功！",
             "exampleImagesDownloadFailed": "下載範例圖片失敗：{message}",
-            "moveFailed": "Failed to move item: {message}"
+            "moveFailed": "Failed to move item: {message}",
+            "copiedToClipboard": "已複製到剪貼簿",
+            "downloadStarted": "下載已開始"
         }
     },
     "doctor": {

py/lora_manager.py

@@ -33,6 +33,7 @@ from .utils.example_images_migration import ExampleImagesMigration
 from .services.websocket_manager import ws_manager
 from .services.example_images_cleanup_service import ExampleImagesCleanupService
 from .middleware.csp_middleware import relax_csp_for_remote_media
+from .middleware.error_middleware import api_json_error
 
 logger = logging.getLogger(__name__)
 
@@ -76,6 +77,11 @@ class LoraManager:
         """Initialize and register all routes using the new refactored architecture"""
         app = PromptServer.instance.app
 
+        # Register JSON error middleware for /api/* routes as the outermost
+        # middleware so it catches errors from all other middlewares.
+        if api_json_error not in app.middlewares:
+            app.middlewares.insert(0, api_json_error)
+
         if relax_csp_for_remote_media not in app.middlewares:
             # Ensure CSP relaxer executes after ComfyUI's block_external_middleware so it can
             # see and extend the restrictive header instead of being overwritten by it.
@@ -189,6 +195,10 @@ class LoraManager:
 
             # Register DownloadManager with ServiceRegistry
             await ServiceRegistry.get_download_manager()
+
+            # Initialize DownloadQueueService for persistent queue/history
+            await ServiceRegistry.get_download_queue_service()
+
             await ServiceRegistry.get_backup_service()
 
             from .services.metadata_service import initialize_metadata_providers
@@ -426,5 +436,14 @@ class LoraManager:
         try:
             logger.info("LoRA Manager: Cleaning up services")
 
+            # Cancel any in-flight scanner initialization tasks so thread-pool
+            # workers (e.g. _initialize_cache_sync) can break out of their loops
+            # when the server shuts down (e.g. Ctrl+C on WSL).
+            for name in ("lora_scanner", "checkpoint_scanner", "embedding_scanner"):
+                scanner = ServiceRegistry.get_service_sync(name)
+                if scanner is not None and hasattr(scanner, "cancel_task"):
+                    scanner.cancel_task()
+                    logger.debug("LoRA Manager: Cancelled %s", name)
+
         except Exception as e:
             logger.error(f"Error during cleanup: {e}", exc_info=True)

py/metadata_collector/constants.py

@@ -5,9 +5,10 @@ MODELS = "models"
 PROMPTS = "prompts"
 SAMPLING = "sampling"
 LORAS = "loras"
+EMBEDDINGS = "embeddings"
 SIZE = "size"
 IMAGES = "images"
 IS_SAMPLER = "is_sampler"  # New constant to mark sampler nodes
 
 # Complete list of categories to track
-METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES]
+METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES]

py/metadata_collector/node_extractors.py

@@ -901,6 +901,55 @@ class LoraLoaderManagerExtractor(NodeMetadataExtractor):
                 "node_id": node_id
             }
 
+class LoraTextLoaderManagerExtractor(NodeMetadataExtractor):
+    """Extract LoRA metadata from LoraTextLoaderLM (LoRA Text Loader).
+
+    The node accepts a `lora_syntax` STRING containing <lora:name:strength> tags
+    (same format as the ComfyUI prompt), plus an optional `lora_stack`.
+    This extractor parses the syntax string using the same regex as the node.
+    """
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        active_loras = []
+
+        # Process lora_stack if available (optional input)
+        if "lora_stack" in inputs:
+            lora_stack = inputs.get("lora_stack", [])
+            for item in lora_stack:
+                # lora_stack entries are (path, model_strength, clip_strength) tuples
+                if isinstance(item, (list, tuple)) and len(item) >= 2:
+                    lora_path = item[0]
+                    model_strength = item[1]
+                    lora_name = os.path.splitext(os.path.basename(lora_path))[0]
+                    active_loras.append({
+                        "name": lora_name,
+                        "strength": round(float(model_strength), 2)
+                    })
+
+        # Process lora_syntax string input
+        if "lora_syntax" in inputs:
+            lora_syntax = inputs.get("lora_syntax", "")
+            if lora_syntax and isinstance(lora_syntax, str):
+                pattern = r"<lora:([^:>]+):([^:>]+)(?::([^:>]+))?>"
+                matches = re.findall(pattern, lora_syntax, re.IGNORECASE)
+                for match in matches:
+                    lora_name = match[0]
+                    model_strength = float(match[1])
+                    active_loras.append({
+                        "name": lora_name,
+                        "strength": round(model_strength, 2)
+                    })
+
+        if active_loras:
+            metadata[LORAS][node_id] = {
+                "lora_list": active_loras,
+                "node_id": node_id
+            }
+
+
 class FluxGuidanceExtractor(NodeMetadataExtractor):
     @staticmethod
     def extract(node_id, inputs, outputs, metadata):
@@ -1146,6 +1195,7 @@ NODE_EXTRACTORS = {
     "UNETLoaderLM": UNETLoaderExtractor,  # LoRA Manager
     "LoraLoader": LoraLoaderExtractor,
     "LoraLoaderLM": LoraLoaderManagerExtractor,
+    "LoraTextLoaderLM": LoraTextLoaderManagerExtractor,
     "RgthreePowerLoraLoader": RgthreePowerLoraLoaderExtractor,
     "TensorRTLoader": TensorRTLoaderExtractor,
     # Conditioning

py/middleware/cache_middleware.py

@@ -16,6 +16,8 @@ IMG_EXTENSIONS = (
     ".tif",
     ".tiff",
     ".webp",
+    ".avif",
+    ".jxl",
     ".mp4"
 )
 

py/middleware/error_middleware.py

@@ -0,0 +1,71 @@
+"""JSON error middleware for API routes.
+
+Ensures all responses to /api/* requests return valid JSON that the
+browser-extension frontend can JSON.parse() without crashing, even when
+the route does not exist (404) or the handler raises an exception (500).
+
+Extension consumers call response.json() unconditionally — an HTML error
+page causes ``SyntaxError: unexpected end of data`` that leaks into the
+popup UI as a toast notification.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Awaitable, Callable
+
+from aiohttp import web
+
+logger = logging.getLogger(__name__)
+
+
+@web.middleware
+async def api_json_error(
+    request: web.Request,
+    handler: Callable[[web.Request], Awaitable[web.Response]],
+) -> web.Response:
+    """Return JSON ``{"success": false, "error": "..."}`` for API errors.
+
+    Only intercepts paths starting with ``/api/`` — all other routes
+    (frontend pages, static files, WebSocket upgrades) pass through
+    unchanged.
+    """
+    if not request.path.startswith("/api/"):
+        return await handler(request)
+
+    try:
+        response = await handler(request)
+        return response
+    except web.HTTPException as exc:
+        # Let redirects (301, 302, 307, 308) propagate — they are not errors.
+        if exc.status < 400:
+            raise
+
+        logger.warning(
+            "API %s %s returned HTTP %d: %s",
+            request.method,
+            request.path,
+            exc.status,
+            exc.reason,
+        )
+
+        return web.json_response(
+            {"success": False, "error": f"{exc.status}: {exc.reason}"},
+            status=exc.status,
+        )
+    except Exception as exc:
+        logger.error(
+            "API %s %s raised unhandled exception: %s",
+            request.method,
+            request.path,
+            exc,
+            exc_info=True,
+        )
+
+        return web.json_response(
+            {
+                "success": False,
+                "error": f"500: Internal Server Error ({type(exc).__name__})",
+            },
+            status=500,
+        )

py/nodes/save_image.py

@@ -11,7 +11,7 @@ from ..metadata_collector.metadata_processor import MetadataProcessor
 from ..metadata_collector import get_metadata
 from ..utils.constants import CARD_PREVIEW_WIDTH
 from ..utils.exif_utils import ExifUtils
-from ..utils.utils import calculate_recipe_fingerprint
+from ..utils.utils import calculate_recipe_fingerprint, sanitize_folder_name
 from PIL import Image, PngImagePlugin
 import piexif
 import logging
@@ -298,7 +298,12 @@ class SaveImageLM:
             key = parts[0]
 
             if key == "seed" and "seed" in metadata_dict:
-                filename = filename.replace(segment, str(metadata_dict.get("seed", "")))
+                seed_value = metadata_dict.get("seed")
+                if seed_value is not None:
+                    filename = filename.replace(segment, str(seed_value))
+                else:
+                    # Fallback if seed was not captured by metadata collector
+                    filename = filename.replace(segment, "0")
             elif key == "width" and "size" in metadata_dict:
                 size = metadata_dict.get("size", "x")
                 w = size.split("x")[0] if isinstance(size, str) else size[0]
@@ -309,12 +314,14 @@ class SaveImageLM:
                 filename = filename.replace(segment, str(h))
             elif key == "pprompt" and "prompt" in metadata_dict:
                 prompt = metadata_dict.get("prompt", "").replace("\n", " ")
+                prompt = sanitize_folder_name(prompt)
                 if len(parts) >= 2:
                     length = int(parts[1])
                     prompt = prompt[:length]
                 filename = filename.replace(segment, prompt.strip())
             elif key == "nprompt" and "negative_prompt" in metadata_dict:
                 prompt = metadata_dict.get("negative_prompt", "").replace("\n", " ")
+                prompt = sanitize_folder_name(prompt)
                 if len(parts) >= 2:
                     length = int(parts[1])
                     prompt = prompt[:length]
@@ -328,6 +335,7 @@ class SaveImageLM:
                     model = "model_unavailable"
                 else:
                     model = os.path.splitext(os.path.basename(model_value))[0]
+                    model = sanitize_folder_name(model)
                 if len(parts) >= 2:
                     length = int(parts[1])
                     model = model[:length]

py/recipes/base.py

@@ -58,9 +58,52 @@ class RecipeMetadataParser(ABC):
             civitai_info, error_msg = civitai_info_tuple if isinstance(civitai_info_tuple, tuple) else (civitai_info_tuple, None)
             
             if not civitai_info or error_msg == "Model not found":
-                # Model not found or deleted
-                lora_entry['isDeleted'] = True
-                lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
+                # CivitAI may fail to resolve a hash that is still being
+                # computed (known CivitAI issue). Before marking as deleted,
+                # try to reconcile with a local model that has the same
+                # filename and matching AutoV3 hash.
+                reconciled = False
+                file_name = lora_entry.get("file_name")
+                if file_name and recipe_scanner and hash_value:
+                    lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+                    if lora_scanner:
+                        try:
+                            # Local import to avoid circular dependency:
+                            # base.py → file_utils → settings_manager → ...
+                            #  → recipe_scanner → enrichment → base.py
+                            from ..utils.file_utils import calculate_autov3  # fmt: skip
+                            cache = await lora_scanner.get_cached_data()
+                            for item in getattr(cache, "raw_data", []):
+                                if item.get("file_name") == file_name:
+                                    local_path = item.get("file_path")
+                                    if local_path and os.path.exists(local_path):
+                                        local_autov3 = calculate_autov3(local_path)
+                                        if local_autov3 and local_autov3 == hash_value:
+                                            lora_entry["existsLocally"] = True
+                                            lora_entry["localPath"] = local_path
+                                            lora_entry["hash"] = item.get("sha256", hash_value)
+                                            if "preview_url" in item:
+                                                lora_entry["thumbnailUrl"] = config.get_preview_static_url(item["preview_url"])
+                                            civ = item.get("civitai") or {}
+                                            if isinstance(civ, dict):
+                                                if civ.get("id") is not None:
+                                                    lora_entry["id"] = civ["id"]
+                                                if civ.get("modelId") is not None:
+                                                    lora_entry["modelId"] = civ["modelId"]
+                                                if civ.get("name"):
+                                                    lora_entry["version"] = civ["name"]
+                                                # model_name is the CivitAI model display
+                                                # name stored directly in the cache column.
+                                                cached_model_name = item.get("model_name")
+                                                if cached_model_name:
+                                                    lora_entry["name"] = cached_model_name
+                                            reconciled = True
+                                            break
+                        except Exception:
+                            pass
+                if not reconciled:
+                    lora_entry['isDeleted'] = True
+                    lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
                 return lora_entry
                 
             # Get model type and validate

py/recipes/enrichment.py

@@ -190,27 +190,42 @@ class RecipeEnricher:
             existing_cp = recipe.get("checkpoint")
             if existing_cp is None:
                 existing_cp = {}
+
+            # Extract baseModel from raw civitai_info before populate_checkpoint_from_civitai
+            # (populate may reject non-checkpoint types and lose this data)
+            base_model_from_civitai: str = ""
+            if isinstance(civitai_info, dict):
+                base_model_from_civitai = civitai_info.get("baseModel", "") or ""
+            elif isinstance(civitai_info, tuple) and len(civitai_info) > 0 and isinstance(civitai_info[0], dict):
+                base_model_from_civitai = civitai_info[0].get("baseModel", "") or ""
+
             checkpoint_data = await RecipeMetadataParser.populate_checkpoint_from_civitai(existing_cp, civitai_info)
-            # 1. First, resolve base_model using full data before we format it away
+
+            # 1. Resolve base_model from checkpoint_data first, then fall back to raw civitai_info
             current_base_model = recipe.get("base_model")
-            resolved_base_model = checkpoint_data.get("baseModel")
+            resolved_base_model = checkpoint_data.get("baseModel") or base_model_from_civitai
             if resolved_base_model:
-                # Update if empty OR if it matches our generic prefix but is less specific
                 is_generic = not current_base_model or current_base_model.lower() in ["flux", "sdxl", "sd15"]
                 if is_generic and resolved_base_model != current_base_model:
                     recipe["base_model"] = resolved_base_model
-            
-            # 2. Format according to requirements: type, modelId, modelVersionId, modelName, modelVersionName
-            formatted_checkpoint = {
-                "type": "checkpoint",
-                "modelId": checkpoint_data.get("modelId"),
-                "modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
-                "modelName": checkpoint_data.get("name"), # In base.py, 'name' is populated from civitai_data['model']['name']
-                "modelVersionName": checkpoint_data.get("version") # In base.py, 'version' is populated from civitai_data['name']
-            }
-            # Remove None values
-            recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
-            
+
+            # 2. Only format and save checkpoint if it has real data (not just type after type rejection)
+            has_checkpoint_data = any([
+                checkpoint_data.get("modelId"),
+                checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
+                checkpoint_data.get("name"),
+                checkpoint_data.get("version"),
+            ])
+            if has_checkpoint_data:
+                formatted_checkpoint = {
+                    "type": "checkpoint",
+                    "modelId": checkpoint_data.get("modelId"),
+                    "modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
+                    "modelName": checkpoint_data.get("name"),
+                    "modelVersionName": checkpoint_data.get("version"),
+                }
+                recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
+
             return True
         else:
             # Fallback to name extraction if we don't already have one

py/recipes/parsers/civitai_image.py

@@ -6,6 +6,7 @@ from typing import Dict, Any, Union
 from ..base import RecipeMetadataParser
 from ..constants import GEN_PARAM_KEYS
 from ...services.metadata_service import get_default_metadata_provider
+from ...config import config
 
 logger = logging.getLogger(__name__)
 
@@ -73,7 +74,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         return False
 
     async def parse_metadata(  # type: ignore[override]
-        self, user_comment, recipe_scanner=None, civitai_client=None
+        self, user_comment, recipe_scanner=None, civitai_client=None,
+        local_cache: dict[str, Any] | None = None,
     ) -> Dict[str, Any]:
         """Parse metadata from Civitai image format
 
@@ -81,6 +83,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             user_comment: The metadata from the image (dict)
             recipe_scanner: Optional recipe scanner service
             civitai_client: Optional Civitai API client (deprecated, use metadata_provider instead)
+            local_cache: Optional dict mapping sha256/autov3 hash → scanner cache item.
+                         When provided, matching models skip CivitAI API calls.
 
         Returns:
             Dict containing parsed recipe data
@@ -210,35 +214,45 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                         }
 
                         # Try to look up base model from the checkpoint hash
-                        if checkpoint_entry["hash"] and metadata_provider:
-                            try:
-                                civitai_info = (
-                                    await metadata_provider.get_model_by_hash(
-                                        checkpoint_entry["hash"]
+                        cp_hash = checkpoint_entry.get("hash")
+                        if cp_hash and metadata_provider:
+                            local_cached = local_cache.get(cp_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    checkpoint_entry, local_cached
+                                )
+                                bm = checkpoint_entry.get("baseModel", "")
+                                if bm and not result["base_model"]:
+                                    result["base_model"] = bm
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(
+                                            cp_hash
+                                        )
+                                    )
+                                    civitai_data, error_msg = (
+                                        (civitai_info, None)
+                                        if not isinstance(civitai_info, tuple)
+                                        else civitai_info
+                                    )
+                                    if civitai_data and error_msg != "Model not found":
+                                        if 'model' in civitai_data and 'name' in civitai_data['model']:
+                                            checkpoint_entry['name'] = civitai_data['model']['name']
+                                        checkpoint_entry['id'] = civitai_data.get('id', 0)
+                                        checkpoint_entry['modelId'] = civitai_data.get('modelId', 0)
+                                        if 'name' in civitai_data:
+                                            checkpoint_entry['version'] = civitai_data['name']
+                                        base_model = civitai_data.get('baseModel', '')
+                                        if base_model:
+                                            checkpoint_entry['baseModel'] = base_model
+                                            if not result['base_model']:
+                                                result['base_model'] = base_model
+                                except Exception as e:
+                                    logger.error(
+                                        f"Error fetching checkpoint info for hash "
+                                        f"{cp_hash}: {e}"
                                     )
-                                )
-                                civitai_data, error_msg = (
-                                    (civitai_info, None)
-                                    if not isinstance(civitai_info, tuple)
-                                    else civitai_info
-                                )
-                                if civitai_data and error_msg != "Model not found":
-                                    if 'model' in civitai_data and 'name' in civitai_data['model']:
-                                        checkpoint_entry['name'] = civitai_data['model']['name']
-                                    checkpoint_entry['id'] = civitai_data.get('id', 0)
-                                    checkpoint_entry['modelId'] = civitai_data.get('modelId', 0)
-                                    if 'name' in civitai_data:
-                                        checkpoint_entry['version'] = civitai_data['name']
-                                    base_model = civitai_data.get('baseModel', '')
-                                    if base_model:
-                                        checkpoint_entry['baseModel'] = base_model
-                                        if not result['base_model']:
-                                            result['base_model'] = base_model
-                            except Exception as e:
-                                logger.error(
-                                    f"Error fetching checkpoint info for hash "
-                                    f"{checkpoint_entry['hash']}: {e}"
-                                )
 
                         if result["model"] is None:
                             result["model"] = checkpoint_entry
@@ -279,34 +293,45 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                         }
 
                         # Try to get info from Civitai if hash is available
-                        if lora_entry["hash"] and metadata_provider:
-                            try:
-                                civitai_info = (
-                                    await metadata_provider.get_model_by_hash(lora_hash)
+                        if lora_hash and metadata_provider:
+                            local_cached = local_cache.get(lora_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    lora_entry, local_cached
                                 )
-
-                                populated_entry = await self.populate_lora_from_civitai(
-                                    lora_entry,
-                                    civitai_info,
-                                    recipe_scanner,
-                                    base_model_counts,
-                                    lora_hash,
-                                )
-
-                                if populated_entry is None:
-                                    continue  # Skip invalid LoRA types
-
-                                lora_entry = populated_entry
-
-                                # If we have a version ID from Civitai, track it for deduplication
-                                if "id" in lora_entry and lora_entry["id"]:
+                                # Track by version ID for deduplication
+                                if lora_entry.get("id"):
                                     added_loras[str(lora_entry["id"])] = len(
                                         result["loras"]
                                     )
-                            except Exception as e:
-                                logger.error(
-                                    f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
-                                )
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(lora_hash)
+                                    )
+
+                                    populated_entry = await self.populate_lora_from_civitai(
+                                        lora_entry,
+                                        civitai_info,
+                                        recipe_scanner,
+                                        base_model_counts,
+                                        lora_hash,
+                                    )
+
+                                    if populated_entry is None:
+                                        continue  # Skip invalid LoRA types
+
+                                    lora_entry = populated_entry
+
+                                    # If we have a version ID from Civitai, track it for deduplication
+                                    if "id" in lora_entry and lora_entry["id"]:
+                                        added_loras[str(lora_entry["id"])] = len(
+                                            result["loras"]
+                                        )
+                                except Exception as e:
+                                    logger.error(
+                                        f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
+                                    )
 
                         # Track by hash if we have it
                         if lora_hash:
@@ -684,3 +709,41 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         except Exception as e:
             logger.error(f"Error parsing Civitai image metadata: {e}", exc_info=True)
             return {"error": str(e), "loras": []}
+
+    @staticmethod
+    def _populate_entry_from_cache(
+        entry: dict[str, Any],
+        cache_item: dict[str, Any],
+    ) -> None:
+        """Fill a lora/checkpoint entry from a scanner cache item.
+
+        Avoids CivitAI API calls for models that exist locally.
+        Mirrors the population logic in
+        ``RecipeMetadataParser.populate_lora_from_civitai()`` but operates
+        entirely on cached data.
+        """
+        civ = cache_item.get("civitai") or {}
+        if isinstance(civ, dict):
+            if civ.get("id") is not None:
+                entry["id"] = civ["id"]
+            if civ.get("modelId") is not None:
+                entry["modelId"] = civ["modelId"]
+            if civ.get("name"):
+                entry["version"] = civ["name"]
+            cached_name = cache_item.get("model_name")
+            if cached_name:
+                entry["name"] = cached_name
+        entry["existsLocally"] = True
+        local_path = cache_item.get("file_path")
+        if local_path:
+            entry["localPath"] = local_path
+        sha256 = cache_item.get("sha256")
+        if sha256:
+            entry["hash"] = sha256
+        if "preview_url" in cache_item:
+            entry["thumbnailUrl"] = config.get_preview_static_url(
+                cache_item["preview_url"]
+            )
+        base_model = cache_item.get("base_model", "")
+        if base_model:
+            entry["baseModel"] = base_model

py/routes/handlers/misc_handlers.py

@@ -49,7 +49,10 @@ from ...utils.constants import (
     VALID_LORA_TYPES,
 )
 from ...utils.civitai_utils import rewrite_preview_url
-from ...utils.example_images_paths import is_valid_example_images_root
+from ...utils.example_images_paths import (
+    find_non_compliant_items_in_example_images_root,
+    is_valid_example_images_root,
+)
 from ...utils.lora_metadata import extract_trained_words
 from ...utils.session_logging import get_standalone_session_log_snapshot
 from ...utils.usage_stats import UsageStats
@@ -1328,6 +1331,9 @@ class SettingsHandler:
             "folder_paths",
             "libraries",
             "active_library",
+            # Sensitive — never expose the actual value to the frontend;
+            # frontend receives a boolean instead (civitai_api_key_set).
+            "civitai_api_key",
         }
     )
 
@@ -1382,6 +1388,9 @@ class SettingsHandler:
                     value = self._settings.get(key)
                     if value is not None:
                         response_data[key] = value
+            # Sensitive fields: only expose a boolean indicating whether set
+            raw_key = self._settings.get("civitai_api_key")
+            response_data["civitai_api_key_set"] = bool(raw_key)
             settings_file = getattr(self._settings, "settings_file", None)
             if settings_file:
                 response_data["settings_file"] = settings_file
@@ -1492,6 +1501,16 @@ class SettingsHandler:
         if not os.path.isdir(folder_path):
             return "Please set a dedicated folder for example images."
         if not self._is_dedicated_example_images_folder(folder_path):
+            offending = find_non_compliant_items_in_example_images_root(folder_path)
+            if offending:
+                items_str = ", ".join(repr(item) for item in offending[:5])
+                if len(offending) > 5:
+                    items_str += f" … and {len(offending) - 5} more"
+                return (
+                    f"The folder contains items that are not valid example image "
+                    f"folders: {items_str}. Please use a dedicated, empty folder "
+                    f"for example images to prevent accidental data loss."
+                )
             return "Please set a dedicated folder for example images."
         return None
 
@@ -3086,6 +3105,7 @@ class NodeRegistryHandler:
             data = await request.json()
             widget_name = data.get("widget_name")
             value = data.get("value")
+            mode = data.get("mode", "replace")
             node_ids = data.get("node_ids")
 
             if not isinstance(widget_name, str) or not widget_name:
@@ -3133,6 +3153,7 @@ class NodeRegistryHandler:
                     "id": parsed_node_id,
                     "widget_name": widget_name,
                     "value": value,
+                    "mode": mode,
                 }
 
                 if graph_identifier is not None:

py/routes/handlers/model_handlers.py

@@ -37,6 +37,7 @@ from ...services.use_cases import (
 )
 from ...services.websocket_manager import WebSocketManager
 from ...services.websocket_progress_callback import WebSocketProgressCallback
+from ...services.download_queue_service import DownloadQueueService
 from ...services.errors import RateLimitError, ResourceNotFoundError
 from ...utils.civitai_utils import resolve_license_payload
 from ...utils.file_utils import calculate_sha256
@@ -1271,6 +1272,14 @@ class ModelQueryHandler:
                     license_flags = (model_data or {}).get("license_flags")
                     if license_flags is not None:
                         response_payload["license_flags"] = int(license_flags)
+                    # Include the user's license icon style preference so the
+                    # ComfyUI tooltip can pick the right set without a separate
+                    # API call.
+                    try:
+                        settings = get_settings_manager()
+                        response_payload["use_new_license_icons"] = settings.get("use_new_license_icons", True)
+                    except Exception:
+                        pass
                 return web.json_response(response_payload)
             return web.json_response(
                 {
@@ -1472,6 +1481,21 @@ class ModelDownloadHandler:
             )
             return web.Response(status=500, text=str(exc))
 
+    async def skip_download_get(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "Download ID is required"}, status=400
+                )
+            result = await self._download_coordinator.skip_download(download_id)
+            return web.json_response(result)
+        except Exception as exc:
+            self._logger.error(
+                "Error skipping download via GET: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def cancel_download_get(self, request: web.Request) -> web.Response:
         try:
             download_id = request.query.get("download_id")
@@ -1552,6 +1576,291 @@ class ModelDownloadHandler:
             )
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    # ------------------------------------------------------------------
+    # Download queue / history handlers
+    # ------------------------------------------------------------------
+
+    async def get_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            service = await DownloadQueueService.get_instance()
+            queue = await service.get_queue()
+            stats = await service.get_stats()
+            return web.json_response({"success": True, "queue": queue, "stats": stats})
+        except Exception as exc:
+            self._logger.error(
+                "Error getting download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def add_to_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            import uuid
+
+            download_id = request.query.get("download_id") or str(uuid.uuid4())
+            model_id_str = request.query.get("model_id")
+            model_version_id_str = request.query.get("model_version_id")
+            model_name = request.query.get("model_name", "")
+            version_name = request.query.get("version_name", "")
+            thumbnail_url = request.query.get("thumbnail_url", "")
+            source = request.query.get("source")
+            file_params_json = request.query.get("file_params")
+
+            model_id = int(model_id_str) if model_id_str else None
+            model_version_id = int(model_version_id_str) if model_version_id_str else None
+            file_params = json.loads(file_params_json) if file_params_json else None
+
+            service = await DownloadQueueService.get_instance()
+            item = await service.add_to_queue(
+                download_id=download_id,
+                model_id=model_id,
+                model_version_id=model_version_id,
+                model_name=model_name,
+                version_name=version_name,
+                thumbnail_url=thumbnail_url,
+                source=source,
+                file_params=file_params,
+            )
+            return web.json_response({"success": True, "item": item})
+        except Exception as exc:
+            self._logger.error(
+                "Error adding to download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def remove_from_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            removed = await service.remove_from_queue(download_id)
+            return web.json_response({"success": removed})
+        except Exception as exc:
+            self._logger.error(
+                "Error removing from download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def move_queue_item_to_top(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            moved = await service.move_to_top(download_id)
+            return web.json_response({"success": moved})
+        except Exception as exc:
+            self._logger.error(
+                "Error moving queue item to top: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def move_queue_item_to_end(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            moved = await service.move_to_end(download_id)
+            return web.json_response({"success": moved})
+        except Exception as exc:
+            self._logger.error(
+                "Error moving queue item to end: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def clear_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            status_filter = request.query.get("status") or None
+            service = await DownloadQueueService.get_instance()
+            cleared = await service.clear_queue(status_filter=status_filter)
+            return web.json_response({"success": True, "cleared": cleared})
+        except Exception as exc:
+            self._logger.error(
+                "Error clearing download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_download_history(self, request: web.Request) -> web.Response:
+        try:
+            limit = min(int(request.query.get("limit", "50")), 500)
+            offset = int(request.query.get("offset", "0"))
+            status_filter = request.query.get("status") or None
+            service = await DownloadQueueService.get_instance()
+            result = await service.get_history(
+                limit=limit, offset=offset, status_filter=status_filter
+            )
+            return web.json_response(
+                {
+                    "success": True,
+                    "items": result["items"],
+                    "total": result["total"],
+                    "limit": result["limit"],
+                    "offset": result["offset"],
+                }
+            )
+        except Exception as exc:
+            self._logger.error(
+                "Error getting download history: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def clear_download_history(self, request: web.Request) -> web.Response:
+        try:
+            status_filter = request.query.get("status") or None
+            service = await DownloadQueueService.get_instance()
+            cleared = await service.clear_history(status_filter=status_filter)
+            return web.json_response({"success": True, "cleared": cleared})
+        except Exception as exc:
+            self._logger.error(
+                "Error clearing download history: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def delete_download_history_item(self, request: web.Request) -> web.Response:
+        try:
+            item_id = int(request.query.get("id", "0"))
+            if not item_id:
+                return web.json_response(
+                    {"success": False, "error": "id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            deleted = await service.delete_history_item(item_id)
+            return web.json_response({"success": deleted})
+        except Exception as exc:
+            self._logger.error(
+                "Error deleting download history item: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def retry_download_from_history(self, request: web.Request) -> web.Response:
+        try:
+            item_id = int(request.query.get("id", "0"))
+            if not item_id:
+                return web.json_response(
+                    {"success": False, "error": "id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            item = await service.retry_from_history(item_id)
+            if item is None:
+                return web.json_response(
+                    {"success": False, "error": "History item not found or not retryable"},
+                    status=404,
+                )
+            return web.json_response({"success": True, "item": item})
+        except Exception as exc:
+            self._logger.error(
+                "Error retrying download from history: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def retry_all_failed_downloads(self, request: web.Request) -> web.Response:
+        try:
+            service = await DownloadQueueService.get_instance()
+            retry_count = await service.retry_all_failed()
+            return web.json_response({"success": True, "retry_count": retry_count})
+        except Exception as exc:
+            self._logger.error(
+                "Error retrying all failed downloads: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def complete_download_in_queue(self, request: web.Request) -> web.Response:
+        """Atomically move a download from queue to history with terminal status."""
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+            status = request.query.get("status", "completed")
+            error = request.query.get("error")
+            file_path = request.query.get("file_path")
+            try:
+                bytes_downloaded = int(request.query.get("bytes_downloaded", "0"))
+            except (TypeError, ValueError):
+                bytes_downloaded = 0
+            total_bytes_raw = request.query.get("total_bytes")
+            total_bytes = int(total_bytes_raw) if total_bytes_raw else None
+            completed_at_raw = request.query.get("completed_at")
+            completed_at = float(completed_at_raw) if completed_at_raw else None
+
+            service = await DownloadQueueService.get_instance()
+            item = await service.complete_download(
+                download_id=download_id,
+                status=status,
+                error=error,
+                file_path=file_path,
+                bytes_downloaded=bytes_downloaded,
+                total_bytes=total_bytes,
+                completed_at=completed_at,
+            )
+            if item is None:
+                return web.json_response(
+                    {"success": False, "error": "Download not found in queue"}, status=404
+                )
+            return web.json_response({"success": True, "item": item})
+        except Exception as exc:
+            self._logger.error(
+                "Error completing download: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_download_stats(self, request: web.Request) -> web.Response:
+        try:
+            service = await DownloadQueueService.get_instance()
+            stats = await service.get_stats()
+            return web.json_response({"success": True, "stats": stats})
+        except Exception as exc:
+            self._logger.error(
+                "Error getting download stats: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def update_download_queue_status(self, request: web.Request) -> web.Response:
+        """Update the status of a queue item (non-terminal transitions).
+
+        Supported transitions include ``queued → downloading``,
+        ``downloading → paused``, ``paused → downloading``, etc.
+        Terminal transitions (``completed``, ``failed``, ``canceled``)
+        should use ``complete_download_in_queue`` instead.
+        """
+        try:
+            download_id = request.query.get("download_id")
+            status = request.query.get("status")
+            if not download_id or not status:
+                return web.json_response(
+                    {
+                        "success": False,
+                        "error": "download_id and status are required",
+                    },
+                    status=400,
+                )
+            service = await DownloadQueueService.get_instance()
+            updated = await service.update_status(download_id, status)
+            if not updated:
+                return web.json_response(
+                    {"success": False, "error": "Download not found in queue"},
+                    status=404,
+                )
+            return web.json_response({"success": True})
+        except Exception as exc:
+            self._logger.error(
+                "Error updating download queue status: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
 
 class ModelCivitaiHandler:
     """CivitAI integration endpoints."""
@@ -1593,7 +1902,9 @@ class ModelCivitaiHandler:
             return web.json_response(result)
         except Exception as exc:
             self._logger.error(
-                "Error in fetch_all_civitai for %ss: %s", self._service.model_type, exc
+                "Error in fetch_all_civitai for %ss: %s",
+                self._service.model_type, exc,
+                exc_info=True,
             )
             return web.Response(text=str(exc), status=500)
 
@@ -1960,6 +2271,10 @@ class ModelUpdateHandler:
         if target_model_ids:
             target_model_ids = sorted(set(target_model_ids))
 
+        folder_path: Optional[str] = payload.get("folder_path")
+        if folder_path is not None and not isinstance(folder_path, str):
+            folder_path = None
+
         provider = await self._get_civitai_provider()
         if provider is None:
             return web.json_response(
@@ -1974,6 +2289,7 @@ class ModelUpdateHandler:
                 provider,
                 force_refresh=force_refresh,
                 target_model_ids=target_model_ids or None,
+                folder_path=folder_path,
             )
             if self._service.scanner.is_cancelled():
                 return web.json_response(
@@ -1996,10 +2312,21 @@ class ModelUpdateHandler:
             self._logger.error("Failed to refresh model updates: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+        hide_early_access = False
+        if self._settings is not None:
+            try:
+                hide_early_access = bool(
+                    self._settings.get("hide_early_access_updates", False)
+                )
+            except Exception:
+                pass
+
         serialized_records = []
         for record in records.values():
             has_update_fn = getattr(record, "has_update", None)
-            if callable(has_update_fn) and has_update_fn():
+            if callable(has_update_fn) and has_update_fn(
+                hide_early_access=hide_early_access
+            ):
                 serialized_records.append(self._serialize_record(record))
 
         return web.json_response(
@@ -2561,9 +2888,24 @@ class ModelHandlerSet:
             "download_model": self.download.download_model,
             "download_model_get": self.download.download_model_get,
             "cancel_download_get": self.download.cancel_download_get,
+            "skip_download_get": self.download.skip_download_get,
             "pause_download_get": self.download.pause_download_get,
             "resume_download_get": self.download.resume_download_get,
             "get_download_progress": self.download.get_download_progress,
+            "get_download_queue": self.download.get_download_queue,
+            "add_to_download_queue": self.download.add_to_download_queue,
+            "remove_from_download_queue": self.download.remove_from_download_queue,
+            "move_queue_item_to_top": self.download.move_queue_item_to_top,
+            "move_queue_item_to_end": self.download.move_queue_item_to_end,
+            "clear_download_queue": self.download.clear_download_queue,
+            "get_download_history": self.download.get_download_history,
+            "clear_download_history": self.download.clear_download_history,
+            "delete_download_history_item": self.download.delete_download_history_item,
+            "retry_download_from_history": self.download.retry_download_from_history,
+            "retry_all_failed_downloads": self.download.retry_all_failed_downloads,
+            "complete_download_in_queue": self.download.complete_download_in_queue,
+            "get_download_stats": self.download.get_download_stats,
+            "update_download_queue_status": self.download.update_download_queue_status,
             "get_civitai_versions": self.civitai.get_civitai_versions,
             "get_civitai_model_by_version": self.civitai.get_civitai_model_by_version,
             "get_civitai_model_by_hash": self.civitai.get_civitai_model_by_hash,

py/routes/handlers/preview_handlers.py

@@ -13,7 +13,7 @@ from ...config import config as global_config
 
 logger = logging.getLogger(__name__)
 
-_CHUNK_SIZE = 256 * 1024  # 256 KB
+_CHUNK_SIZE = 1024 * 1024  # 1 MB — balance between streaming iteration overhead and per-chunk memory
 
 # Video file extensions that bypass native sendfile on Windows
 # to avoid IOCP/ProactorEventLoop crashes during client disconnect.
@@ -55,16 +55,19 @@ class PreviewHandler:
             logger.debug("Preview file not found at %s", str(resolved))
             raise web.HTTPNotFound(text="Preview file not found")
 
-        # Video files: stream manually to avoid Windows native sendfile crash.
-        # aiohttp's FileResponse uses _sendfile_native on Windows (IOCP-based),
-        # which breaks when the client disconnects mid-transfer — this happens
-        # constantly when users scroll through a gallery of animated previews.
-        suffix = resolved.suffix.lower()
-        if suffix in _VIDEO_EXTENSIONS:
-            return await self._stream_file(request, resolved)
-
-        # aiohttp's FileResponse handles range requests and content headers for us.
-        return web.FileResponse(path=resolved, chunk_size=_CHUNK_SIZE)
+        # aiohttp's FileResponse handles range requests, content headers, and
+        # uses kernel sendfile (zero-copy DMA) on Linux/macOS. On Windows it
+        # uses IOCP-based _sendfile_native which can crash when the client
+        # disconnects mid-transfer during fast scrolling. The _stream_file()
+        # fallback is kept for a future compat toggle.
+        #
+        # Set explicit Cache-Control so the browser can cache video (and image)
+        # previews across VirtualScroller recycling cycles. Without this,
+        # Chrome does not cache 206 Partial Content responses for <video>
+        # elements, causing the same video to be re-downloaded on every scroll.
+        resp = web.FileResponse(path=resolved, chunk_size=_CHUNK_SIZE)
+        resp.headers["Cache-Control"] = "public, max-age=86400"
+        return resp
 
     async def _stream_file(
         self, request: web.Request, path: Path
@@ -83,6 +86,10 @@ class PreviewHandler:
         resp.content_type = content_type
         resp.content_length = file_size
 
+        # Allow browser caching: video previews rarely change during a session.
+        # The frontend already appends ?t={version} to bust cache on update.
+        resp.headers["Cache-Control"] = "public, max-age=86400"
+
         await resp.prepare(request)
 
         try:

py/routes/handlers/recipe_handlers.py

@@ -16,7 +16,7 @@ from aiohttp import web
 
 from ...config import config
 from ...services.server_i18n import server_i18n as default_server_i18n
-from ...services.settings_manager import SettingsManager
+from ...services.settings_manager import SettingsManager, get_settings_manager
 from ...services.recipes import (
     RecipeAnalysisService,
     RecipeDownloadError,
@@ -26,7 +26,12 @@ from ...services.recipes import (
     RecipeValidationError,
 )
 from ...services.metadata_service import get_default_metadata_provider
-from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
+from ...utils.civitai_utils import (
+    build_civitai_image_page_url,
+    extract_civitai_image_id,
+    extract_civitai_image_id_from_cdn_url,
+    rewrite_preview_url,
+)
 from ...utils.exif_utils import ExifUtils
 from ...recipes.merger import GenParamsMerger
 from ...recipes.enrichment import RecipeEnricher
@@ -96,6 +101,8 @@ class RecipeHandlerSet:
             "browse_directory": self.batch_import.browse_directory,
             "check_image_exists": self.management.check_image_exists,
             "import_from_url": self.management.import_from_url,
+            "create_from_example": self.management.create_from_example,
+            "reimport_recipe": self.management.reimport_recipe,
         }
 
 
@@ -461,7 +468,11 @@ class RecipeQueryHandler:
             if recipe_scanner is None:
                 raise RuntimeError("Recipe scanner unavailable")
 
-            self._logger.info("Manually triggering recipe cache rebuild")
+            full_rebuild = request.query.get("full_rebuild", "true").lower() == "true"
+            self._logger.info(
+                "Manually triggering recipe cache %s",
+                "full rebuild" if full_rebuild else "refresh",
+            )
             await recipe_scanner.get_cached_data(force_refresh=True)
             return web.json_response(
                 {"success": True, "message": "Recipe cache refreshed successfully"}
@@ -789,6 +800,126 @@ class RecipeManagementHandler:
             self._logger.error("Error repairing single recipe: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def reimport_recipe(self, request: web.Request) -> web.Response:
+        """Delete a recipe and re-import it from its source URL.
+
+        This gives the recipe a fresh start — re-downloads the image from
+        CivitAI, re-parses EXIF metadata with the current parser, and
+        re-resolves LoRAs / checkpoint. User edits (title, tags, favorite)
+        are carried over from the old recipe.
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            recipe_id = request.match_info["recipe_id"]
+            old_recipe = await recipe_scanner.get_recipe_by_id(recipe_id)
+            if not old_recipe:
+                raise RecipeNotFoundError(f"Recipe {recipe_id} not found")
+
+            source_path = old_recipe.get("source_path")
+            if not source_path:
+                return web.json_response(
+                    {
+                        "success": False,
+                        "error": (
+                            "Recipe has no source URL — cannot re-import. "
+                            "Use repair or manual import instead."
+                        ),
+                    },
+                    status=400,
+                )
+
+            user_edits: dict[str, Any] = {}
+            for key in ("title", "tags", "favorite", "preview_nsfw_level"):
+                if key in old_recipe and old_recipe[key] is not None:
+                    user_edits[key] = old_recipe[key]
+            if "tags" in user_edits and not isinstance(user_edits["tags"], list):
+                del user_edits["tags"]
+
+            old_file_path = old_recipe.get("file_path", "")
+            old_folder = os.path.dirname(old_file_path) if old_file_path else None
+
+            image_id = extract_civitai_image_id(source_path)
+            is_local_file = not image_id and os.path.isfile(source_path)
+
+            if not image_id and not is_local_file:
+                return web.json_response(
+                    {
+                        "success": False,
+                        "error": (
+                            "Recipe source is neither a valid CivitAI image URL "
+                            "nor an accessible local file. "
+                            "Use repair or manual import instead."
+                        ),
+                    },
+                    status=400,
+                )
+
+            if is_local_file:
+                return await self._do_reimport_from_local(
+                    source_path,
+                    recipe_scanner,
+                    recipe_id=recipe_id,
+                    target_dir=old_folder,
+                    user_edits=user_edits,
+                    old_title=old_recipe.get("title", ""),
+                )
+
+            async with self._import_semaphore:
+                import_response = await self._do_import_from_url(
+                    source_path,
+                    recipe_scanner,
+                    target_dir=old_folder,
+                )
+
+            await self._persistence_service.delete_recipe(
+                recipe_scanner=recipe_scanner, recipe_id=recipe_id
+            )
+
+            body_bytes = import_response.body
+            if not body_bytes:
+                raise RuntimeError("Re-import returned an empty response")
+            import_body = json.loads(body_bytes.decode())
+            new_recipe_id = import_body.get("recipe_id")
+
+            if new_recipe_id and user_edits:
+                try:
+                    await self._persistence_service.update_recipe(
+                        recipe_scanner=recipe_scanner,
+                        recipe_id=new_recipe_id,
+                        updates=user_edits,
+                    )
+                except Exception as exc:
+                    self._logger.warning(
+                        "Re-import succeeded but failed to carry over "
+                        "user edits for new recipe %s: %s",
+                        new_recipe_id,
+                        exc,
+                    )
+
+            return web.json_response(
+                {
+                    "success": True,
+                    "old_recipe_id": recipe_id,
+                    "recipe_id": new_recipe_id,
+                    "source_path": source_path,
+                }
+            )
+        except RecipeNotFoundError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=404)
+        except RecipeValidationError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=400)
+        except RecipeDownloadError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=400)
+        except Exception as exc:
+            self._logger.error(
+                "Error reimporting recipe: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def get_repair_progress(self, request: web.Request) -> web.Response:
         try:
             progress = self._ws_manager.get_recipe_repair_progress()
@@ -897,6 +1028,7 @@ class RecipeManagementHandler:
             extension,
             civitai_meta_raw,
             model_version_id,
+            _original_image_url,
         ) = await self._download_remote_media(image_url)
 
         # Extract embedded EXIF metadata (offloaded to thread pool in this call)
@@ -975,6 +1107,9 @@ class RecipeManagementHandler:
             civitai_model = civitai_parsed.get("model")
             if civitai_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = civitai_model
+            civitai_base_model = civitai_parsed.get("base_model")
+            if civitai_base_model and not metadata.get("base_model"):
+                metadata["base_model"] = civitai_base_model
         elif parsed_embedded:
             parsed_loras = parsed_embedded.get("loras")
             if parsed_loras and not metadata.get("loras"):
@@ -982,6 +1117,8 @@ class RecipeManagementHandler:
             parsed_model = parsed_embedded.get("model")
             if parsed_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = parsed_model
+            if parsed_embedded.get("base_model") and not metadata.get("base_model"):
+                metadata["base_model"] = parsed_embedded["base_model"]
 
         civitai_client = self._civitai_client_getter()
         await RecipeEnricher.enrich_recipe(
@@ -1304,7 +1441,9 @@ class RecipeManagementHandler:
             "exclude": False,
         }
 
-    async def _download_remote_media(self, image_url: str) -> tuple[bytes, str, Any, Any]:
+    async def _download_remote_media(
+        self, image_url: str
+    ) -> tuple[bytes, str, Any, Any, Optional[str]]:
         civitai_client = self._civitai_client_getter()
         downloader = await self._downloader_factory()
         temp_path = None
@@ -1379,11 +1518,16 @@ class RecipeManagementHandler:
                     if mvids and isinstance(civitai_meta_raw, dict):
                         civitai_meta_raw["modelVersionIds"] = mvids
 
+                original_url = (
+                    image_info.get("url") if civitai_image_id and image_info else None
+                )
+
                 return (
                     file_obj.read(),
                     extension,
                     civitai_meta_raw,
                     model_ver_id,
+                    original_url,
                 )
         except RecipeDownloadError:
             raise
@@ -1453,15 +1597,8 @@ class RecipeManagementHandler:
 
             cache = await recipe_scanner.get_cached_data()
 
-            # Build lookup: image_id -> recipe_id from stored source_path
-            image_to_recipe = {}
-            for recipe in getattr(cache, "raw_data", []):
-                source = recipe.get("source_path")
-                if not source:
-                    continue
-                image_id = extract_civitai_image_id(source)
-                if image_id and image_id not in image_to_recipe:
-                    image_to_recipe[image_id] = recipe.get("id")
+            # Use precomputed image_id_map (built once at cache init)
+            image_to_recipe = getattr(cache, "image_id_map", {})
 
             results = {}
             for img_id in requested_ids:
@@ -1489,25 +1626,30 @@ class RecipeManagementHandler:
             if not image_url:
                 raise RecipeValidationError("Missing required field: image_url")
 
+            force = request.query.get("force", "false").lower() == "true"
+
             image_id = extract_civitai_image_id(image_url)
             if not image_id:
                 raise RecipeValidationError(
                     "Could not extract Civitai image ID from URL"
                 )
 
-            # Check for duplicate (fast, before acquiring semaphore)
-            cache = await recipe_scanner.get_cached_data()
-            for recipe in getattr(cache, "raw_data", []):
-                source = recipe.get("source_path")
-                if source:
-                    existing_id = extract_civitai_image_id(source)
-                    if existing_id == image_id:
-                        return web.json_response({
-                            "success": True,
-                            "recipe_id": recipe.get("id"),
-                            "name": recipe.get("title", ""),
-                            "already_exists": True,
-                        })
+            if not force:
+                cache = await recipe_scanner.get_cached_data()
+                image_to_recipe = getattr(cache, "image_id_map", {})
+                existing_recipe_id = image_to_recipe.get(image_id)
+                if existing_recipe_id:
+                    recipe_name = ""
+                    for recipe in getattr(cache, "raw_data", []):
+                        if str(recipe.get("id", "")) == existing_recipe_id:
+                            recipe_name = recipe.get("title", "") or ""
+                            break
+                    return web.json_response({
+                        "success": True,
+                        "recipe_id": existing_recipe_id,
+                        "name": recipe_name,
+                        "already_exists": True,
+                    })
 
             async with self._import_semaphore:
                 return await self._do_import_from_url(image_url, recipe_scanner)
@@ -1525,6 +1667,9 @@ class RecipeManagementHandler:
         self,
         image_url: str,
         recipe_scanner: Any,
+        *,
+        recipe_id: str | None = None,
+        target_dir: str | None = None,
     ) -> web.Response:
         image_id = extract_civitai_image_id(image_url)
         if not image_id:
@@ -1532,7 +1677,7 @@ class RecipeManagementHandler:
                 "Could not extract Civitai image ID from URL"
             )
 
-        image_bytes, extension, civitai_meta_raw, model_version_id = (
+        image_bytes, extension, civitai_meta_raw, model_version_id, original_image_url = (
             await self._download_remote_media(image_url)
         )
 
@@ -1570,6 +1715,51 @@ class RecipeManagementHandler:
                 "Failed to extract embedded metadata: %s", exc
             )
 
+        if not parsed_embedded and original_image_url:
+            self._logger.debug(
+                "Optimized image has no embedded metadata, "
+                "falling back to original: %s",
+                original_image_url,
+            )
+            try:
+                downloader = await self._downloader_factory()
+                with tempfile.NamedTemporaryFile(
+                    suffix=".png", delete=False
+                ) as tmp:
+                    orig_tmp_path = tmp.name
+                try:
+                    success, _ = await downloader.download_file(
+                        original_image_url, orig_tmp_path, use_auth=False
+                    )
+                    if success:
+                        raw_orig = await asyncio.to_thread(
+                            ExifUtils.extract_image_metadata, orig_tmp_path
+                        )
+                        if raw_orig:
+                            parser = (
+                                self._analysis_service._recipe_parser_factory.create_parser(
+                                    raw_orig
+                                )
+                            )
+                            if parser:
+                                parsed_embedded = await parser.parse_metadata(
+                                    raw_orig, recipe_scanner=recipe_scanner
+                                )
+                                if (
+                                    parsed_embedded
+                                    and "gen_params" in parsed_embedded
+                                ):
+                                    embedded_gen_params = parsed_embedded[
+                                        "gen_params"
+                                    ]
+                finally:
+                    if os.path.exists(orig_tmp_path):
+                        os.unlink(orig_tmp_path)
+            except Exception as exc:
+                self._logger.warning(
+                    "Failed to extract metadata from original image: %s", exc
+                )
+
         # Parse CivitAI API meta to discover all resources from modelVersionIds.
         # Run unconditionally — EXIF parsing succeeds for gen_params but misses
         # LoRAs (modelVersionIds is NOT in the image EXIF).
@@ -1613,6 +1803,9 @@ class RecipeManagementHandler:
             civitai_model = civitai_parsed.get("model")
             if civitai_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = civitai_model
+            civitai_base_model = civitai_parsed.get("base_model")
+            if civitai_base_model and not metadata.get("base_model"):
+                metadata["base_model"] = civitai_base_model
         elif parsed_embedded:
             parsed_loras = parsed_embedded.get("loras")
             if parsed_loras and not metadata.get("loras"):
@@ -1620,6 +1813,8 @@ class RecipeManagementHandler:
             parsed_model = parsed_embedded.get("model")
             if parsed_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = parsed_model
+            if parsed_embedded.get("base_model") and not metadata.get("base_model"):
+                metadata["base_model"] = parsed_embedded["base_model"]
 
         civitai_client = self._civitai_client_getter()
         await RecipeEnricher.enrich_recipe(
@@ -1648,9 +1843,370 @@ class RecipeManagementHandler:
             tags=[],
             metadata=metadata,
             extension=extension,
+            recipe_id=recipe_id,
+            target_dir=target_dir,
         )
         return web.json_response(result.payload, status=result.status)
 
+    async def _do_reimport_from_local(
+        self,
+        file_path: str,
+        recipe_scanner: Any,
+        *,
+        recipe_id: str,
+        target_dir: str | None,
+        user_edits: dict[str, Any],
+        old_title: str,
+    ) -> web.Response:
+        """Re-import a recipe from a local image file.
+
+        Reads the original source file, re-parses its EXIF metadata, saves a
+        fresh recipe, then deletes the old one.
+        """
+        normalized = os.path.normpath(file_path)
+        if not os.path.isfile(normalized):
+            raise RecipeNotFoundError(
+                f"Source file no longer accessible: {normalized}"
+            )
+
+        with open(normalized, "rb") as fh:
+            image_bytes = fh.read()
+
+        extension = os.path.splitext(normalized)[1].lower() or ".png"
+
+        analysis_result = await self._analysis_service.analyze_local_image(
+            file_path=normalized,
+            recipe_scanner=recipe_scanner,
+        )
+        analysis_payload: dict[str, Any] = analysis_result.payload
+
+        gen_params = analysis_payload.get("gen_params") or {}
+        loras = analysis_payload.get("loras") or []
+        checkpoint = analysis_payload.get("checkpoint")
+        base_model = analysis_payload.get("base_model", "")
+
+        metadata: dict[str, Any] = {
+            "base_model": base_model,
+            "loras": loras,
+            "gen_params": gen_params,
+            "source_path": normalized,
+        }
+        if checkpoint:
+            metadata["checkpoint"] = checkpoint
+
+        prompt = (
+            gen_params.get("prompt")
+            or gen_params.get("positivePrompt")
+            or ""
+        )
+        name = " ".join(str(prompt).split()[:10]) if prompt else old_title
+
+        result = await self._persistence_service.save_recipe(
+            recipe_scanner=recipe_scanner,
+            image_bytes=image_bytes,
+            image_base64=analysis_payload.get("image_base64"),
+            name=name,
+            tags=[],
+            metadata=metadata,
+            extension=extension,
+            target_dir=target_dir,
+        )
+
+        await self._persistence_service.delete_recipe(
+            recipe_scanner=recipe_scanner, recipe_id=recipe_id
+        )
+
+        new_recipe_id = result.payload.get("recipe_id")
+        if new_recipe_id and user_edits:
+            try:
+                await self._persistence_service.update_recipe(
+                    recipe_scanner=recipe_scanner,
+                    recipe_id=new_recipe_id,
+                    updates=user_edits,
+                )
+            except Exception as exc:
+                self._logger.warning(
+                    "Re-import (local) succeeded but failed to carry over "
+                    "user edits for recipe %s: %s",
+                    new_recipe_id,
+                    exc,
+                )
+
+        return web.json_response(
+            {
+                "success": True,
+                "old_recipe_id": recipe_id,
+                "recipe_id": new_recipe_id,
+                "source_path": normalized,
+            }
+        )
+
+    async def create_from_example(self, request: web.Request) -> web.Response:
+        """Create a recipe from a model's example image using cached metadata.
+
+        Uses the image's meta data (already cached in .metadata.json from the
+        CivitAI model-versions API) to create a recipe without additional
+        CivitAI API calls.
+
+        If the image metadata doesn't contain any resources of the parent
+        model's type (LoRA-type or Checkpoint), the parent model is
+        auto-populated as a fallback.
+
+        Request body:
+            image_data (dict): The full image object from model-versions API
+                (includes meta, additionalResources, url, etc.)
+            model_hash (str): SHA256 hash of the parent model
+            model_name (str): Filename of the parent model
+            model_type (str): Page type (``"loras"``, ``"checkpoints"``, etc.)
+            local_image_path (str, optional): Local filesystem path to read
+                the image bytes for the recipe preview
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            data = await request.json()
+            image_data = data.get("image_data")
+            model_hash = data.get("model_hash")
+            model_name = data.get("model_name")
+            model_type = data.get("model_type", "")
+
+            if not image_data or not model_hash or not model_name:
+                raise RecipeValidationError(
+                    "Missing required fields: image_data, model_hash, model_name"
+                )
+
+            # Merge nested meta into top level so the parser finds everything.
+            # CivitaiApiMetadataParser expects prompt, seed, resources, etc.
+            # at the top level or wrapped under a "meta" key.
+            inner_meta = image_data.get("meta") or {}
+            parsed_input = {**image_data, **inner_meta}
+            parsed_input.pop("meta", None)
+
+            # Build a local cache of {hash → cache_item} so the parser can
+            # skip CivitAI API calls for models that exist on disk.
+            local_cache: Dict[str, Dict[str, Any]] = {}
+            lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+            if lora_scanner and model_hash:
+                try:
+                    parent_cache_data = await lora_scanner.get_cached_data()
+                    for item in getattr(parent_cache_data, "raw_data", []):
+                        if item.get("sha256", "").lower() == model_hash.lower():
+                            local_cache[model_hash.lower()] = item
+                            # Compute AutoV3 so the parser can also match on
+                            # that hash type (CivitAI metadata resources use
+                            # AutoV3).
+                            file_path = item.get("file_path")
+                            if file_path and os.path.exists(file_path):
+                                try:
+                                    from ...utils.file_utils import (
+                                        calculate_autov3,
+                                    )
+                                    autov3 = calculate_autov3(file_path)
+                                    if autov3:
+                                        local_cache[autov3.lower()] = item
+                                except Exception:
+                                    pass
+                            break
+                except Exception:
+                    pass
+
+            parser = self._analysis_service._recipe_parser_factory.create_parser(
+                parsed_input
+            )
+            if not parser:
+                raise RecipeValidationError("Unable to parse image metadata")
+
+            from ...recipes.parsers.civitai_image import CivitaiApiMetadataParser
+
+            if isinstance(parser, CivitaiApiMetadataParser):
+                parsed = await parser.parse_metadata(
+                    parsed_input,
+                    recipe_scanner=recipe_scanner,
+                    local_cache=local_cache,
+                )
+            else:
+                parsed = await parser.parse_metadata(
+                    parsed_input, recipe_scanner=recipe_scanner
+                )
+
+            loras = list(parsed.get("loras") or [])
+            checkpoint = parsed.get("model")
+            is_lora_type = model_type.startswith("lora")
+            is_ckpt_type = model_type.startswith("checkpoint")
+
+            # Extract parent model metadata from local_cache (used below to
+            # reconcile isDeleted entries and enrich auto-populated ones).
+            parent_civitai_id: int | None = None
+            parent_model_id: int | None = None
+            parent_version_name: str | None = None
+            parent_model_name: str | None = None
+            # Prefer sha256 key; fall back to any cached entry.
+            parent_item = local_cache.get(model_hash.lower()) if model_hash else None
+            if parent_item is None and local_cache:
+                parent_item = next(iter(local_cache.values()))
+            if parent_item:
+                civ = parent_item.get("civitai") or {}
+                if isinstance(civ, dict):
+                    parent_civitai_id = civ.get("id")
+                    parent_model_id = civ.get("modelId")
+                    parent_version_name = civ.get("name")
+                parent_model_name = parent_item.get("model_name")
+
+            # Reconcile isDeleted entries against the parent model.
+            # When the CivitAI hash lookup fails (known issue — hashes not
+            # yet computed), the parser marks the entry isDeleted even though
+            # the model exists locally.
+            if is_lora_type:
+                for lora in loras:
+                    if lora.get("isDeleted") and lora.get("file_name") == model_name:
+                        lora["isDeleted"] = False
+                        lora["existsLocally"] = True
+                        lora["hash"] = model_hash
+                        if parent_civitai_id is not None:
+                            lora["id"] = parent_civitai_id
+                        if parent_model_id is not None:
+                            lora["modelId"] = parent_model_id
+                        if parent_version_name is not None:
+                            lora["version"] = parent_version_name
+                        if parent_model_name is not None:
+                            lora["name"] = parent_model_name
+            elif is_ckpt_type and checkpoint and checkpoint.get("isDeleted"):
+                if checkpoint.get("file_name") == model_name:
+                    checkpoint["isDeleted"] = False
+                    checkpoint["existsLocally"] = True
+                    checkpoint["hash"] = model_hash
+                    if parent_civitai_id is not None:
+                        checkpoint["id"] = parent_civitai_id
+                    if parent_model_id is not None:
+                        checkpoint["modelId"] = parent_model_id
+                    if parent_version_name is not None:
+                        checkpoint["version"] = parent_version_name
+
+            # Auto-populate parent model only when the image metadata didn't
+            # contain any resources of that type.
+            if is_lora_type and not loras:
+                lora_entry = {
+                    "name": model_name,
+                    "type": "lora",
+                    "weight": 1.0,
+                    "hash": model_hash,
+                    "existsLocally": True,
+                    "localPath": None,
+                    "file_name": model_name,
+                    "thumbnailUrl": "/loras_static/images/no-preview.png",
+                    "baseModel": parsed.get("base_model", ""),
+                    "size": 0,
+                    "downloadUrl": "",
+                    "isDeleted": False,
+                }
+                if parent_civitai_id is not None:
+                    lora_entry["id"] = parent_civitai_id
+                if parent_model_id is not None:
+                    lora_entry["modelId"] = parent_model_id
+                if parent_version_name is not None:
+                    lora_entry["version"] = parent_version_name
+                if parent_model_name is not None:
+                    lora_entry["name"] = parent_model_name
+                loras.insert(0, lora_entry)
+            elif is_ckpt_type and not checkpoint:
+                checkpoint = {
+                    "name": model_name,
+                    "type": "checkpoint",
+                    "hash": model_hash,
+                    "file_name": model_name,
+                    "existsLocally": True,
+                    "baseModel": parsed.get("base_model", ""),
+                    "isDeleted": False,
+                }
+                if parent_civitai_id is not None:
+                    checkpoint["id"] = parent_civitai_id
+                if parent_model_id is not None:
+                    checkpoint["modelId"] = parent_model_id
+                if parent_version_name is not None:
+                    checkpoint["version"] = parent_version_name
+                if parent_model_name is not None:
+                    checkpoint["name"] = parent_model_name
+
+            image_url = image_data.get("url") or ""
+            image_id = extract_civitai_image_id_from_cdn_url(image_url)
+            settings_mgr = get_settings_manager()
+            civitai_host = settings_mgr.get("civitai_host") if settings_mgr else None
+            page_url = build_civitai_image_page_url(image_id, host=civitai_host) or image_url
+
+            recipe_metadata: dict[str, Any] = {
+                "base_model": parsed.get("base_model") or "",
+                "loras": loras,
+                "gen_params": parsed.get("gen_params") or {},
+                "source_path": page_url,
+            }
+            nsfw_level = image_data.get("nsfwLevel")
+            if isinstance(nsfw_level, int):
+                recipe_metadata["preview_nsfw_level"] = nsfw_level
+            if checkpoint:
+                recipe_metadata["checkpoint"] = checkpoint
+
+            image_bytes: bytes | None = None
+            extension: str | None = None
+            local_image_path = data.get("local_image_path")
+            if local_image_path and os.path.exists(local_image_path):
+                with open(local_image_path, "rb") as f:
+                    image_bytes = f.read()
+                ext = os.path.splitext(local_image_path)[1].lower()
+                if ext in (".jpg", ".jpeg", ".png", ".webp", ".gif"):
+                    extension = ext
+            elif image_data.get("url"):
+                try:
+                    downloader = await self._downloader_factory()
+                    url = image_data["url"]
+                    tmp = tempfile.NamedTemporaryFile(delete=False)
+                    tmp.close()
+                    success, result = await downloader.download_file(
+                        url, tmp.name, use_auth=False
+                    )
+                    if success:
+                        with open(tmp.name, "rb") as f:
+                            image_bytes = f.read()
+                        url_path = url.split("?")[0].split("#")[0]
+                        ext = os.path.splitext(url_path)[1].lower()
+                        if ext:
+                            extension = ext
+                    if os.path.exists(tmp.name):
+                        os.unlink(tmp.name)
+                except Exception as exc:
+                    self._logger.warning(
+                        "Failed to download image for recipe: %s", exc
+                    )
+
+            prompt = (
+                (parsed.get("gen_params") or {}).get("prompt") or ""
+            )
+            if prompt:
+                name = " ".join(str(prompt).split()[:10])
+            else:
+                name = f"Recipe from {model_name}"
+
+            save_result = await self._persistence_service.save_recipe(
+                recipe_scanner=recipe_scanner,
+                image_bytes=image_bytes,
+                image_base64=None,
+                name=name,
+                tags=[],
+                metadata=recipe_metadata,
+                extension=extension,
+            )
+            return web.json_response(save_result.payload, status=save_result.status)
+
+        except RecipeValidationError as exc:
+            return web.json_response({"error": str(exc)}, status=400)
+        except Exception as exc:
+            self._logger.error(
+                "Error creating recipe from example: %s", exc, exc_info=True
+            )
+            return web.json_response({"error": str(exc)}, status=500)
+
 
 class RecipeAnalysisHandler:
     """Analyze images to extract recipe metadata."""

py/routes/model_route_registrar.py

@@ -101,11 +101,46 @@ COMMON_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/download-model", "download_model"),
     RouteDefinition("GET", "/api/lm/download-model-get", "download_model_get"),
     RouteDefinition("GET", "/api/lm/cancel-download-get", "cancel_download_get"),
+    RouteDefinition("GET", "/api/lm/skip-download", "skip_download_get"),
     RouteDefinition("GET", "/api/lm/pause-download", "pause_download_get"),
     RouteDefinition("GET", "/api/lm/resume-download", "resume_download_get"),
     RouteDefinition(
         "GET", "/api/lm/download-progress/{download_id}", "get_download_progress"
     ),
+    RouteDefinition("GET", "/api/lm/downloads/queue", "get_download_queue"),
+    RouteDefinition("GET", "/api/lm/downloads/queue/add", "add_to_download_queue"),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/remove", "remove_from_download_queue"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/move-to-top", "move_queue_item_to_top"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/move-to-end", "move_queue_item_to_end"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/clear", "clear_download_queue"
+    ),
+    RouteDefinition("GET", "/api/lm/downloads/history", "get_download_history"),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/clear", "clear_download_history"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/delete", "delete_download_history_item"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/retry", "retry_download_from_history"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/retry-all", "retry_all_failed_downloads"
+    ),
+    RouteDefinition("GET", "/api/lm/downloads/stats", "get_download_stats"),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/complete", "complete_download_in_queue"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/status", "update_download_queue_status"
+    ),
     RouteDefinition("POST", "/api/lm/{prefix}/cancel-task", "cancel_task"),
     RouteDefinition("GET", "/{prefix}", "handle_models_page"),
 )

py/routes/recipe_route_registrar.py

@@ -75,6 +75,12 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
         "GET", "/api/lm/recipes/check-image-exists", "check_image_exists"
     ),
     RouteDefinition("GET", "/api/lm/recipes/import-from-url", "import_from_url"),
+    RouteDefinition(
+        "POST", "/api/lm/recipes/create-from-example", "create_from_example"
+    ),
+    RouteDefinition(
+        "POST", "/api/lm/recipe/{recipe_id}/reimport", "reimport_recipe"
+    ),
 )
 
 

py/routes/stats_routes.py

@@ -11,6 +11,8 @@ from ..config import config
 from ..services.settings_manager import get_settings_manager
 from ..services.server_i18n import server_i18n
 from ..services.service_registry import ServiceRegistry
+from ..services.model_query import normalize_sub_type, resolve_sub_type
+from ..utils.constants import VALID_LORA_SUB_TYPES, VALID_CHECKPOINT_SUB_TYPES
 from ..utils.usage_stats import UsageStats
 
 logger = logging.getLogger(__name__)
@@ -140,6 +142,21 @@ class StatsRoutes:
             # Get usage statistics
             usage_data = await self.usage_stats.get_stats()
             
+            # CivitAI model type distribution across all model types
+            # Use the same logic as the filter panel: normalize_sub_type(resolve_sub_type(entry))
+            # with sub-type validation per model type
+            model_types_counter: Counter[str] = Counter()
+            for entry in lora_cache.raw_data:
+                ntype = normalize_sub_type(resolve_sub_type(entry))
+                if ntype and ntype in VALID_LORA_SUB_TYPES:
+                    model_types_counter[ntype] += 1
+            for entry in checkpoint_cache.raw_data:
+                ntype = normalize_sub_type(resolve_sub_type(entry))
+                if ntype and ntype in VALID_CHECKPOINT_SUB_TYPES:
+                    model_types_counter[ntype] += 1
+            # Embeddings: always count as "embedding" regardless of CivitAI sub-type
+            model_types_counter['embedding'] = len(embedding_cache.raw_data)
+            
             return web.json_response({
                 'success': True,
                 'data': {
@@ -154,7 +171,8 @@ class StatsRoutes:
                     'total_generations': usage_data.get('total_executions', 0),
                     'unused_loras': self._count_unused_models(lora_cache.raw_data, usage_data.get('loras', {})),
                     'unused_checkpoints': self._count_unused_models(checkpoint_cache.raw_data, usage_data.get('checkpoints', {})),
-                    'unused_embeddings': self._count_unused_models(embedding_cache.raw_data, usage_data.get('embeddings', {}))
+                    'unused_embeddings': self._count_unused_models(embedding_cache.raw_data, usage_data.get('embeddings', {})),
+                    'model_types_distribution': dict(model_types_counter.most_common())
                 }
             })
             
@@ -459,9 +477,12 @@ class StatsRoutes:
                 if unused_lora_percent > 50:
                     insights.append({
                         'type': 'warning',
-                        'title': 'High Number of Unused LoRAs',
-                        'description': f'{unused_lora_percent:.1f}% of your LoRAs ({unused_loras}/{total_loras}) have never been used.',
-                        'suggestion': 'Consider organizing or archiving unused models to free up storage space.'
+                        'key': 'insights.unusedLoras.high',
+                        'params': {
+                            'percent': f'{unused_lora_percent:.1f}',
+                            'count': str(unused_loras),
+                            'total': str(total_loras)
+                        }
                     })
             
             if total_checkpoints > 0:
@@ -469,9 +490,12 @@ class StatsRoutes:
                 if unused_checkpoint_percent > 30:
                     insights.append({
                         'type': 'warning',
-                        'title': 'Unused Checkpoints Detected',
-                        'description': f'{unused_checkpoint_percent:.1f}% of your checkpoints ({unused_checkpoints}/{total_checkpoints}) have never been used.',
-                        'suggestion': 'Review and consider removing checkpoints you no longer need.'
+                        'key': 'insights.unusedCheckpoints.detected',
+                        'params': {
+                            'percent': f'{unused_checkpoint_percent:.1f}',
+                            'count': str(unused_checkpoints),
+                            'total': str(total_checkpoints)
+                        }
                     })
             
             if total_embeddings > 0:
@@ -479,9 +503,12 @@ class StatsRoutes:
                 if unused_embedding_percent > 50:
                     insights.append({
                         'type': 'warning',
-                        'title': 'High Number of Unused Embeddings',
-                        'description': f'{unused_embedding_percent:.1f}% of your embeddings ({unused_embeddings}/{total_embeddings}) have never been used.',
-                        'suggestion': 'Consider organizing or archiving unused embeddings to optimize your collection.'
+                        'key': 'insights.unusedEmbeddings.high',
+                        'params': {
+                            'percent': f'{unused_embedding_percent:.1f}',
+                            'count': str(unused_embeddings),
+                            'total': str(total_embeddings)
+                        }
                     })
             
             # Storage insights
@@ -492,18 +519,20 @@ class StatsRoutes:
             if total_size > 100 * 1024 * 1024 * 1024:  # 100GB
                 insights.append({
                     'type': 'info',
-                    'title': 'Large Collection Detected',
-                    'description': f'Your model collection is using {self._format_size(total_size)} of storage.',
-                    'suggestion': 'Consider using external storage or cloud solutions for better organization.'
+                    'key': 'insights.collection.large',
+                    'params': {
+                        'size': self._format_size(total_size)
+                    }
                 })
             
             # Recent activity insight
             if usage_data.get('total_executions', 0) > 100:
                 insights.append({
                     'type': 'success',
-                    'title': 'Active User',
-                    'description': f'You\'ve completed {usage_data["total_executions"]} generations so far!',
-                    'suggestion': 'Keep exploring and creating amazing content with your models.'
+                    'key': 'insights.activity.active',
+                    'params': {
+                        'count': str(usage_data['total_executions'])
+                    }
                 })
             
             return web.json_response({

py/routes/update_routes.py

@@ -1,7 +1,6 @@
 import os
 import logging
 import toml
-import git
 import zipfile
 import shutil
 import tempfile
@@ -11,6 +10,7 @@ from typing import Dict, List
 
 from ..utils.settings_paths import ensure_settings_file
 from ..services.downloader import get_downloader
+from ..services.service_registry import ServiceRegistry
 
 logger = logging.getLogger(__name__)
 
@@ -212,8 +212,19 @@ class UpdateRoutes:
 
             zip_path = tmp_zip_path
 
-            # Skip both settings.json, civitai and model cache folder
-            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache'])
+            # Close the downloaded-versions SQLite connection before cleaning,
+            # so that shutil.rmtree() does not fail on Windows (the process
+            # cannot delete a file with an outstanding open handle).
+            try:
+                history_svc = ServiceRegistry._services.get("downloaded_version_history_service")
+                if history_svc is not None:
+                    history_svc.close()
+                    logger.info("Closed downloaded-version history database connection")
+            except Exception:
+                logger.debug("Could not close downloaded-version history database", exc_info=True)
+
+            # Skip settings.json, civitai, model cache and runtime cache folders
+            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache', 'cache', 'wildcards', 'backups', 'stats'])
 
             # Extract ZIP to temp dir
             with tempfile.TemporaryDirectory() as tmp_dir:
@@ -222,16 +233,17 @@ class UpdateRoutes:
                     # Find extracted folder (GitHub ZIP contains a root folder)
                     extracted_root = next(os.scandir(tmp_dir)).path
 
-                    # Copy files, skipping settings.json and civitai folder
+                    # Copy files, skipping user data that should be preserved
+                    skip_items = {'settings.json', 'civitai', 'wildcards', 'backups', 'stats'}
                     for item in os.listdir(extracted_root):
-                        if item == 'settings.json' or item == 'civitai':
+                        if item in skip_items:
                             continue
                         src = os.path.join(extracted_root, item)
                         dst = os.path.join(plugin_root, item)
                         if os.path.isdir(src):
                             if os.path.exists(dst):
                                 shutil.rmtree(dst)
-                            shutil.copytree(src, dst, ignore=shutil.ignore_patterns('settings.json', 'civitai'))
+                            shutil.copytree(src, dst, ignore=shutil.ignore_patterns(*skip_items))
                         else:
                             shutil.copy2(src, dst)
 
@@ -239,15 +251,17 @@ class UpdateRoutes:
                     # for ComfyUI Manager to work properly
                     tracking_info_file = os.path.join(plugin_root, '.tracking')
                     tracking_files = []
+                    skip_tracked = {'civitai', 'wildcards', 'backups', 'stats'}
                     for root, dirs, files in os.walk(extracted_root):
-                        # Skip civitai folder and its contents
+                        # Skip user data directories and their contents
                         rel_root = os.path.relpath(root, extracted_root)
-                        if rel_root == 'civitai' or rel_root.startswith('civitai' + os.sep):
+                        top_dir = rel_root.split(os.sep)[0] if rel_root != '.' else ''
+                        if top_dir in skip_tracked:
                             continue
                         for file in files:
                             rel_path = os.path.relpath(os.path.join(root, file), extracted_root)
-                            # Skip settings.json and any file under civitai
-                            if rel_path == 'settings.json' or rel_path.startswith('civitai' + os.sep):
+                            # Skip settings.json and any file under user data dirs
+                            if rel_path == 'settings.json' or rel_path.split(os.sep)[0] in skip_tracked:
                                 continue
                             tracking_files.append(rel_path.replace("\\", "/"))
                     with open(tracking_info_file, "w", encoding='utf-8') as file:
@@ -342,6 +356,15 @@ class UpdateRoutes:
         Returns:
             tuple: (success, new_version)
         """
+        try:
+            import git
+        except ImportError:
+            logger.error(
+                "GitPython is not available: the git executable was not found in PATH. "
+                "Install git or set $GIT_PYTHON_GIT_EXECUTABLE to the git binary path."
+            )
+            return False, ""
+
         try:
             # Open the Git repository
             repo = git.Repo(plugin_root)
@@ -438,6 +461,7 @@ class UpdateRoutes:
             if not os.path.exists(os.path.join(plugin_root, '.git')):
                 return git_info
 
+            import git
             repo = git.Repo(plugin_root)
             commit = repo.head.commit
             git_info['commit_hash'] = commit.hexsha

py/services/aria2_downloader.py

@@ -14,12 +14,30 @@ from typing import Any, Dict, Optional, Tuple
 
 import aiohttp
 
-from .downloader import DownloadProgress, get_downloader
+from .downloader import DownloadProgress, get_downloader, is_ssl_cert_verify_error
 from .aria2_transfer_state import Aria2TransferStateStore
 from .settings_manager import get_settings_manager
 
 logger = logging.getLogger(__name__)
 
+def _try_certifi_ca_path() -> str | None:
+    """Return the certifi CA bundle path if available, else None."""
+    try:
+        import certifi  # type: ignore[import-untyped]
+
+        path = certifi.where()
+        if os.path.isfile(path):
+            logger.debug(
+                "aria2 --ca-certificate: using certifi CA bundle at %s", path
+            )
+            return path
+    except ImportError:
+        pass
+
+    logger.debug("aria2 --ca-certificate: certifi not available")
+    return None
+
+
 CIVITAI_DOWNLOAD_URL_PREFIXES = (
     "https://civitai.com/api/download/",
     "https://civitai.red/api/download/",
@@ -391,6 +409,15 @@ class Aria2Downloader:
                     f"Failed to resolve authenticated Civitai redirect: status={response.status} body={body[:300]}"
                 )
         except aiohttp.ClientError as exc:
+            if is_ssl_cert_verify_error(exc):
+                logger.error(
+                    "SSL certificate verification failed during Civitai redirect "
+                    "resolution for %s. This is usually caused by an outdated CA "
+                    "certificate bundle. Recommended fixes:\n"
+                    "  1. pip install --upgrade certifi\n"
+                    "  2. pip install pip-system-certs",
+                    url,
+                )
             raise Aria2Error(
                 f"Failed to resolve authenticated Civitai redirect: {exc}"
             ) from exc
@@ -414,6 +441,11 @@ class Aria2Downloader:
                 f"--rpc-listen-port={self._rpc_port}",
                 f"--rpc-secret={self._rpc_secret}",
                 "--check-certificate=true",
+                # Point aria2 at certifi's CA bundle when available so it uses
+                # the same certificate store as Python downloads.
+                *((
+                    f"--ca-certificate={ca_cert}",
+                ) if (ca_cert := _try_certifi_ca_path()) else ()),
                 "--allow-overwrite=true",
                 "--auto-file-renaming=false",
                 "--file-allocation=none",

py/services/backup_service.py

@@ -141,6 +141,16 @@ class BackupService:
                     )
                 )
 
+        stats_path = os.path.join(get_settings_dir(create=True), "stats", "lora_manager_stats.json")
+        if os.path.exists(stats_path):
+            targets.append(
+                (
+                    "usage_stats",
+                    "stats/lora_manager_stats.json",
+                    stats_path,
+                )
+            )
+
         return targets
 
     @staticmethod
@@ -348,6 +358,8 @@ class BackupService:
         if kind == "model_update":
             filename = os.path.basename(archive_member)
             return str(Path(get_cache_file_path(CacheType.MODEL_UPDATE, create_dir=True)).parent / filename)
+        if kind == "usage_stats":
+            return os.path.join(get_settings_dir(create=True), "stats", "lora_manager_stats.json")
         return None
 
     async def create_auto_snapshot_if_due(self) -> Optional[dict[str, Any]]:

py/services/civarchive_client.py

@@ -186,6 +186,22 @@ class CivArchiveClient:
         if "metadata" in file_data:
             transformed["metadata"] = file_data["metadata"]
 
+        # Infer metadata.format from filename extension
+        name = transformed.get("name")
+        if name and isinstance(name, str):
+            lower_name = name.lower()
+            if lower_name.endswith(".safetensors"):
+                inferred_format = "SafeTensor"
+            elif lower_name.endswith(".ckpt"):
+                inferred_format = "PickleTensor"
+            else:
+                inferred_format = None
+            if inferred_format:
+                if "metadata" not in transformed:
+                    transformed["metadata"] = {}
+                if isinstance(transformed["metadata"], dict):
+                    transformed["metadata"].setdefault("format", inferred_format)
+
         if file_data.get("modelVersionId") is not None:
             transformed["modelVersionId"] = file_data.get("modelVersionId")
         elif file_data.get("model_version_id") is not None:
@@ -213,6 +229,20 @@ class CivArchiveClient:
         for file_data in candidates:
             if isinstance(file_data, dict):
                 transformed_files.append(self._transform_file_entry(file_data))
+
+        # Sort: .safetensors first, .ckpt second, others last
+        # so the backend fallback (no file_params) prefers safetensors
+        def _sort_key(f: Dict) -> int:
+            fname = f.get("name") or ""
+            if isinstance(fname, str):
+                lower = fname.lower()
+                if lower.endswith(".safetensors"):
+                    return 0
+                elif lower.endswith(".ckpt"):
+                    return 1
+            return 2
+
+        transformed_files.sort(key=_sort_key)
         return transformed_files
 
     def _transform_version(

py/services/download_coordinator.py

@@ -110,6 +110,23 @@ class DownloadCoordinator:
 
         return result
 
+    async def skip_download(self, download_id: str) -> Dict[str, Any]:
+        """Skip a download while preserving all partial files on disk."""
+        download_manager = await self._download_manager_factory()
+        result = await download_manager.skip_download(download_id)
+
+        await self._ws_manager.broadcast_download_progress(
+            download_id,
+            {
+                "status": "skipped",
+                "progress": 0,
+                "download_id": download_id,
+                "message": "Download skipped by user (partial files preserved)",
+            },
+        )
+
+        return result
+
     async def pause_download(self, download_id: str) -> Dict[str, Any]:
         """Pause an active download and notify listeners."""
 

py/services/download_manager.py

@@ -29,6 +29,7 @@ from .metadata_service import get_default_metadata_provider, get_metadata_provid
 from .downloader import get_downloader, DownloadProgress, DownloadStreamControl
 from .aria2_downloader import Aria2Error, get_aria2_downloader
 from .aria2_transfer_state import Aria2TransferStateStore
+from .download_queue_service import DownloadQueueService
 
 # Download to temporary file first
 import tempfile
@@ -360,6 +361,15 @@ class DownloadManager:
                     if self._active_downloads[task_id].get("transfer_backend") == "aria2":
                         await self._persist_aria2_state(task_id)
 
+                # Update SQLite queue status to 'downloading'
+                try:
+                    queue_service = await DownloadQueueService.get_instance()
+                    await queue_service.update_status(task_id, "downloading")
+                except Exception:
+                    logger.warning(
+                        "Failed to update queue status for %s", task_id, exc_info=True
+                    )
+
                 # Use original download implementation
                 try:
                     # Check for cancellation before starting
@@ -396,6 +406,22 @@ class DownloadManager:
                         if self._active_downloads[task_id].get("transfer_backend") == "aria2":
                             await self._persist_aria2_state(task_id)
 
+                    # Move queue item to history on completion
+                    try:
+                        queue_service = await DownloadQueueService.get_instance()
+                        await queue_service.complete_download(
+                            download_id=task_id,
+                            status=result.get("status", "completed") if result.get("success") else "failed",
+                            error=result.get("error") if not result.get("success") else None,
+                            file_path=result.get("file_path"),
+                            bytes_downloaded=self._active_downloads.get(task_id, {}).get("bytes_downloaded", 0),
+                            total_bytes=self._active_downloads.get(task_id, {}).get("total_bytes"),
+                        )
+                    except Exception:
+                        logger.warning(
+                            "Failed to complete queue item for %s", task_id, exc_info=True
+                        )
+
                     return result
                 except asyncio.CancelledError:
                     # Handle cancellation
@@ -404,6 +430,19 @@ class DownloadManager:
                         self._active_downloads[task_id]["bytes_per_second"] = 0.0
                         if self._active_downloads[task_id].get("transfer_backend") == "aria2":
                             await self._persist_aria2_state(task_id)
+
+                    # Move queue item to history as canceled
+                    try:
+                        queue_service = await DownloadQueueService.get_instance()
+                        await queue_service.complete_download(
+                            download_id=task_id,
+                            status="canceled",
+                        )
+                    except Exception:
+                        logger.warning(
+                            "Failed to cancel queue item for %s", task_id, exc_info=True
+                        )
+
                     logger.info(f"Download cancelled for task {task_id}")
                     raise
                 except Exception as e:
@@ -417,6 +456,22 @@ class DownloadManager:
                         self._active_downloads[task_id]["bytes_per_second"] = 0.0
                         if self._active_downloads[task_id].get("transfer_backend") == "aria2":
                             await self._persist_aria2_state(task_id)
+
+                    # Move queue item to history as failed
+                    try:
+                        queue_service = await DownloadQueueService.get_instance()
+                        await queue_service.complete_download(
+                            download_id=task_id,
+                            status="failed",
+                            error=str(e),
+                            bytes_downloaded=self._active_downloads.get(task_id, {}).get("bytes_downloaded", 0),
+                            total_bytes=self._active_downloads.get(task_id, {}).get("total_bytes"),
+                        )
+                    except Exception:
+                        logger.warning(
+                            "Failed to complete queue item for %s", task_id, exc_info=True
+                        )
+
                     return {"success": False, "error": str(e)}
         finally:
             # Schedule cleanup of download record after delay
@@ -2404,6 +2459,89 @@ class DownloadManager:
                 self._download_tasks.pop(download_id, None)
                 await self._aria2_state_store.remove(download_id)
 
+    async def skip_download(self, download_id: str) -> Dict:
+        """Skip a download while preserving all partial files on disk.
+
+        Removes all in-memory tracking (asyncio task, semaphore, active/pause
+        state) but keeps partial files (.part / .aria2) on disk so that a
+        subsequent download-model-get request for the same save path can
+        auto-resume from the preserved partial download.
+
+        Args:
+            download_id: The unique identifier of the download task
+
+        Returns:
+            Dict: Status of the skip operation
+        """
+        await self._restore_persisted_downloads()
+
+        if download_id not in self._download_tasks and download_id not in self._active_downloads:
+            return {"success": False, "error": "Download task not found"}
+
+        download_info = self._active_downloads.get(download_id)
+        task = self._download_tasks.get(download_id)
+        active_statuses = {"queued", "waiting", "downloading", "paused", "cancelling"}
+        if task is None and (
+            not isinstance(download_info, dict)
+            or download_info.get("status") not in active_statuses
+        ):
+            return {"success": False, "error": "Download task not found"}
+
+        backend = (
+            self._active_downloads.get(download_id, {}).get("transfer_backend")
+            or "python"
+        )
+
+        try:
+            # For aria2: pause the transfer rather than force-removing it, so
+            # the .aria2 control file stays on disk for future resume
+            if backend == "aria2":
+                try:
+                    aria2_downloader = await get_aria2_downloader()
+                    pause_result = await aria2_downloader.pause_download(download_id)
+                    if not pause_result.get("success"):
+                        logger.warning(
+                            "Failed to pause aria2 transfer for %s during skip: %s",
+                            download_id,
+                            pause_result.get("error"),
+                        )
+                except Exception as exc:
+                    logger.warning(
+                        "Failed to pause aria2 transfer for %s during skip: %s",
+                        download_id,
+                        exc,
+                    )
+
+            # Cancel the asyncio task so the semaphore slot is released
+            if task is not None:
+                task.cancel()
+
+            # Resume pause event so the task can exit cleanly
+            pause_control = self._pause_events.get(download_id)
+            if pause_control is not None:
+                pause_control.resume()
+
+            # Wait briefly for task to acknowledge cancellation
+            if task is not None:
+                try:
+                    await asyncio.wait_for(asyncio.shield(task), timeout=2.0)
+                except (asyncio.CancelledError, asyncio.TimeoutError):
+                    pass
+
+            logger.info(f"Download skipped for task {download_id} (partial files preserved)")
+            return {"success": True, "message": "Download skipped successfully"}
+        except Exception as e:
+            logger.error(f"Error skipping download: {e}", exc_info=True)
+            return {"success": False, "error": str(e)}
+        finally:
+            # Clean up local in-memory tracking only - NO file deletion
+            self._pause_events.pop(download_id, None)
+            self._download_tasks.pop(download_id, None)
+            if download_id in self._active_downloads:
+                del self._active_downloads[download_id]
+            # Preserve aria2 state store entry so the partial download
+            # info survives restarts and can be resumed later
+
     async def pause_download(self, download_id: str) -> Dict:
         """Pause an active download without losing progress."""
 

py/services/download_queue_service.py

@@ -0,0 +1,871 @@
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import sqlite3
+import time
+from typing import Any, Optional
+
+from ..utils.cache_paths import get_cache_base_dir
+
+logger = logging.getLogger(__name__)
+
+
+def _resolve_database_path() -> str:
+    base_dir = get_cache_base_dir(create=True)
+    history_dir = os.path.join(base_dir, "download_history")
+    os.makedirs(history_dir, exist_ok=True)
+    return os.path.join(history_dir, "download_queue.sqlite")
+
+
+class DownloadQueueService:
+    """Persistent download queue and history manager backed by SQLite.
+
+    Provides a singleton interface for managing a download queue and
+    corresponding history table, both stored in a single SQLite database
+    under the cache directory.
+    """
+
+    _instance: Optional[DownloadQueueService] = None
+    _class_lock: asyncio.Lock = asyncio.Lock()
+
+    _SCHEMA = """
+        CREATE TABLE IF NOT EXISTS download_queue (
+            download_id TEXT PRIMARY KEY,
+            model_id INTEGER,
+            model_version_id INTEGER,
+            model_name TEXT NOT NULL DEFAULT '',
+            version_name TEXT DEFAULT '',
+            thumbnail_url TEXT DEFAULT '',
+            source TEXT,
+            file_params TEXT,
+            status TEXT NOT NULL DEFAULT 'queued',
+            priority INTEGER DEFAULT 0,
+            progress INTEGER DEFAULT 0,
+            bytes_downloaded INTEGER DEFAULT 0,
+            total_bytes INTEGER,
+            bytes_per_second REAL DEFAULT 0.0,
+            error TEXT,
+            file_path TEXT,
+            added_at REAL NOT NULL,
+            started_at REAL,
+            completed_at REAL
+        );
+        CREATE INDEX IF NOT EXISTS idx_dq_status ON download_queue(status);
+        CREATE INDEX IF NOT EXISTS idx_dq_added ON download_queue(added_at);
+
+        CREATE TABLE IF NOT EXISTS download_history (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            download_id TEXT,
+            model_id INTEGER,
+            model_version_id INTEGER,
+            model_name TEXT NOT NULL DEFAULT '',
+            version_name TEXT DEFAULT '',
+            thumbnail_url TEXT DEFAULT '',
+            status TEXT NOT NULL,
+            error TEXT,
+            file_path TEXT,
+            bytes_downloaded INTEGER DEFAULT 0,
+            total_bytes INTEGER,
+            completed_at REAL NOT NULL,
+            is_already_exists INTEGER DEFAULT 0
+        );
+        CREATE INDEX IF NOT EXISTS idx_dh_completed ON download_history(completed_at DESC);
+        CREATE INDEX IF NOT EXISTS idx_dh_status ON download_history(status);
+    """
+
+    @classmethod
+    async def get_instance(cls) -> DownloadQueueService:
+        """Return the singleton instance, creating it if necessary."""
+        async with cls._class_lock:
+            if cls._instance is None:
+                cls._instance = cls()
+                await cls._instance.deduplicate()
+            return cls._instance
+
+    def __init__(self, db_path: Optional[str] = None) -> None:
+        self._db_path = db_path or _resolve_database_path()
+        self._lock = asyncio.Lock()
+        self._conn: Optional[sqlite3.Connection] = None
+        self._schema_initialized = False
+        self._ensure_directory()
+        self._initialize_schema()
+
+    def _ensure_directory(self) -> None:
+        directory = os.path.dirname(self._db_path)
+        if directory:
+            os.makedirs(directory, exist_ok=True)
+
+    def _connect(self) -> sqlite3.Connection:
+        conn = sqlite3.connect(self._db_path, check_same_thread=False)
+        conn.row_factory = sqlite3.Row
+        return conn
+
+    def _get_conn(self) -> sqlite3.Connection:
+        if self._conn is None:
+            self._conn = sqlite3.connect(self._db_path, check_same_thread=False)
+            self._conn.row_factory = sqlite3.Row
+        return self._conn
+
+    def _initialize_schema(self) -> None:
+        if self._schema_initialized:
+            return
+        with self._connect() as conn:
+            conn.executescript(self._SCHEMA)
+            conn.commit()
+        self._schema_initialized = True
+
+    def get_database_path(self) -> str:
+        """Return the resolved database file path."""
+        return self._db_path
+
+    def close(self) -> None:
+        """Close the persistent SQLite connection, if open.
+
+        This is called before plugin update operations to release the
+        database file lock on Windows, allowing ``shutil.rmtree()`` to
+        succeed when the cache resides inside the plugin directory.
+        """
+        if self._conn is not None:
+            try:
+                self._conn.close()
+            except Exception:
+                pass
+            finally:
+                self._conn = None
+
+    # ------------------------------------------------------------------
+    # Queue methods
+    # ------------------------------------------------------------------
+
+    async def add_to_queue(
+        self,
+        download_id: str,
+        model_id: Optional[int] = None,
+        model_version_id: Optional[int] = None,
+        model_name: str = "",
+        version_name: str = "",
+        thumbnail_url: str = "",
+        source: Optional[str] = None,
+        file_params: Optional[dict[str, Any]] = None,
+    ) -> dict[str, Any]:
+        """Insert a new download into the queue.
+
+        Returns the inserted row as a dict (or an empty dict if the
+        download_id already exists).
+        """
+        now = time.time()
+        file_params_json = json.dumps(file_params) if file_params is not None else None
+
+        async with self._lock:
+            conn = self._get_conn()
+            conn.execute(
+                """
+                INSERT OR IGNORE INTO download_queue (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, source, file_params,
+                    status, priority, added_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 'queued', 0, ?)
+                """,
+                (
+                    download_id,
+                    model_id,
+                    model_version_id,
+                    model_name,
+                    version_name,
+                    thumbnail_url,
+                    source,
+                    file_params_json,
+                    now,
+                ),
+            )
+            conn.commit()
+            row = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+
+        return dict(row) if row else {}
+
+    async def get_queue(self) -> list[dict[str, Any]]:
+        """Return all items in the queue ordered by priority then added time."""
+        async with self._lock:
+            conn = self._get_conn()
+            rows = conn.execute(
+                "SELECT * FROM download_queue ORDER BY priority DESC, added_at ASC"
+            ).fetchall()
+        return [dict(row) for row in rows]
+
+    async def get_queued_count(self) -> int:
+        """Return the number of items with status ``'queued'``."""
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT COUNT(*) AS cnt FROM download_queue WHERE status = 'queued'"
+            ).fetchone()
+        return row["cnt"] if row else 0
+
+    async def update_status(
+        self,
+        download_id: str,
+        status: str,
+        **extra: Any,
+    ) -> bool:
+        """Update the status and/or extra fields of a queue item.
+
+        Accepted extra keyword arguments:
+        ``progress``, ``error``, ``file_path``, ``bytes_downloaded``,
+        ``total_bytes``, ``bytes_per_second``.
+
+        Returns ``True`` if a row was updated.
+        """
+        allowed_extra = {
+            "progress",
+            "error",
+            "file_path",
+            "bytes_downloaded",
+            "total_bytes",
+            "bytes_per_second",
+        }
+
+        set_clauses: list[str] = ["status = ?"]
+        params: list[Any] = [status]
+        now = time.time()
+
+        if status in ("downloading",):
+            set_clauses.append("started_at = COALESCE(started_at, ?)")
+            params.append(now)
+        if status in ("completed", "failed", "canceled"):
+            set_clauses.append("completed_at = ?")
+            params.append(now)
+
+        for key, value in extra.items():
+            if key in allowed_extra:
+                set_clauses.append(f"{key} = ?")
+                params.append(value)
+
+        params.append(download_id)
+
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                f"UPDATE download_queue SET {', '.join(set_clauses)} "
+                "WHERE download_id = ?",
+                params,
+            )
+            conn.commit()
+        return cursor.rowcount > 0
+
+    async def remove_from_queue(self, download_id: str) -> bool:
+        """Remove a single item from the queue by download_id.
+
+        Returns ``True`` if a row was deleted.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                "DELETE FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            )
+            conn.commit()
+        return cursor.rowcount > 0
+
+    async def move_to_top(self, download_id: str) -> bool:
+        """Move an item to the front of the queue (highest priority).
+
+        Returns ``True`` if the item was found and updated.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT priority FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+            if row is None:
+                return False
+
+            max_row = conn.execute(
+                "SELECT MAX(priority) AS mx FROM download_queue"
+            ).fetchone()
+            max_priority: int = max_row["mx"] if max_row["mx"] is not None else 0
+
+            conn.execute(
+                "UPDATE download_queue SET priority = ? WHERE download_id = ?",
+                (max_priority + 1, download_id),
+            )
+            conn.commit()
+        return True
+
+    async def move_to_end(self, download_id: str) -> bool:
+        """Move an item to the end of the queue (lowest priority).
+
+        Returns ``True`` if the item was found and updated.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT priority FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+            if row is None:
+                return False
+
+            min_row = conn.execute(
+                "SELECT MIN(priority) AS mn FROM download_queue"
+            ).fetchone()
+            min_priority: int = min_row["mn"] if min_row["mn"] is not None else 0
+
+            conn.execute(
+                "UPDATE download_queue SET priority = ? WHERE download_id = ?",
+                (min_priority - 1, download_id),
+            )
+            conn.commit()
+        return True
+
+    async def clear_queue(self, status_filter: Optional[str] = None) -> int:
+        """Remove items from the queue.
+
+        When *status_filter* is provided only items with that status are
+        deleted.  Returns the number of deleted rows.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            if status_filter is not None:
+                cursor = conn.execute(
+                    "DELETE FROM download_queue WHERE status = ?",
+                    (status_filter,),
+                )
+            else:
+                cursor = conn.execute("DELETE FROM download_queue")
+            conn.commit()
+        return cursor.rowcount
+
+    async def complete_download(
+        self,
+        download_id: str,
+        status: str = "completed",
+        error: Optional[str] = None,
+        file_path: Optional[str] = None,
+        bytes_downloaded: int = 0,
+        total_bytes: Optional[int] = None,
+        completed_at: Optional[float] = None,
+    ) -> Optional[dict[str, Any]]:
+        """Atomically move a download from the queue into the history table.
+
+        Looks up the queue record by ``download_id``, deletes it from the
+        queue, and inserts a corresponding history entry with the given
+        terminal status (``completed``, ``failed``, or ``canceled``).
+
+        When *completed_at* is provided it is used as the completion
+        timestamp; otherwise ``time.time()`` is used.
+
+        Returns the original queue record (before deletion) on success,
+        or ``None`` if the download was not found in the queue.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+            if row is None:
+                return None
+
+            now = completed_at if completed_at is not None else time.time()
+            conn.execute(
+                "DELETE FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            )
+            conn.execute(
+                """
+                INSERT INTO download_history (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, status, error, file_path,
+                    bytes_downloaded, total_bytes, completed_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    row["download_id"],
+                    row["model_id"],
+                    row["model_version_id"],
+                    row["model_name"],
+                    row["version_name"],
+                    row["thumbnail_url"],
+                    status,
+                    error,
+                    file_path,
+                    bytes_downloaded,
+                    total_bytes,
+                    now,
+                ),
+            )
+            conn.commit()
+        return dict(row)
+
+    async def pop_next_download(self) -> Optional[dict[str, Any]]:
+        """Atomically fetch and mark the next queued item as ``downloading``.
+
+        The item with the highest priority (and earliest ``added_at``
+        among ties) whose status is ``'queued'`` is selected, set to
+        ``'downloading'``, and returned as a dict.  Returns ``None`` if
+        the queue is empty.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                """
+                SELECT * FROM download_queue
+                WHERE status = 'queued'
+                ORDER BY priority DESC, added_at ASC
+                LIMIT 1
+                """
+            ).fetchone()
+            if row is None:
+                return None
+
+            download_id = row["download_id"]
+            now = time.time()
+            conn.execute(
+                "UPDATE download_queue SET status = 'downloading', "
+                "started_at = COALESCE(started_at, ?) "
+                "WHERE download_id = ?",
+                (now, download_id),
+            )
+            conn.commit()
+            updated = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+
+        return dict(updated) if updated else None
+
+    # ------------------------------------------------------------------
+    # History methods
+    # ------------------------------------------------------------------
+
+    async def add_to_history(
+        self,
+        download_id: Optional[str] = None,
+        model_id: Optional[int] = None,
+        model_version_id: Optional[int] = None,
+        model_name: str = "",
+        version_name: str = "",
+        thumbnail_url: str = "",
+        status: str = "completed",
+        error: Optional[str] = None,
+        file_path: Optional[str] = None,
+        bytes_downloaded: int = 0,
+        total_bytes: Optional[int] = None,
+        is_already_exists: int = 0,
+    ) -> int:
+        """Insert a record into the download history.
+
+        Returns the ``id`` (AUTOINCREMENT primary key) of the newly
+        inserted row.
+        """
+        now = time.time()
+
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                """
+                INSERT INTO download_history (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, status, error, file_path,
+                    bytes_downloaded, total_bytes, completed_at, is_already_exists
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    download_id,
+                    model_id,
+                    model_version_id,
+                    model_name,
+                    version_name,
+                    thumbnail_url,
+                    status,
+                    error,
+                    file_path,
+                    bytes_downloaded,
+                    total_bytes,
+                    now,
+                    is_already_exists,
+                ),
+            )
+            conn.commit()
+        return cursor.lastrowid or 0
+
+    async def get_history(
+        self,
+        limit: int = 50,
+        offset: int = 0,
+        status_filter: Optional[str] = None,
+    ) -> dict[str, Any]:
+        """Return a page of download history entries.
+
+        Returns a dict with keys ``items``, ``total``, ``limit``, and
+        ``offset``.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+
+            if status_filter is not None:
+                count_row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history WHERE status = ?",
+                    (status_filter,),
+                ).fetchone()
+                rows = conn.execute(
+                    "SELECT * FROM download_history WHERE status = ? "
+                    "ORDER BY completed_at DESC LIMIT ? OFFSET ?",
+                    (status_filter, limit, offset),
+                ).fetchall()
+            else:
+                count_row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history"
+                ).fetchone()
+                rows = conn.execute(
+                    "SELECT * FROM download_history "
+                    "ORDER BY completed_at DESC LIMIT ? OFFSET ?",
+                    (limit, offset),
+                ).fetchall()
+
+        return {
+            "items": [dict(row) for row in rows],
+            "total": count_row["cnt"] if count_row else 0,
+            "limit": limit,
+            "offset": offset,
+        }
+
+    async def delete_history_item(self, id: int) -> bool:
+        """Delete a single history entry by its *id*.
+
+        Returns ``True`` if a row was deleted.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                "DELETE FROM download_history WHERE id = ?",
+                (id,),
+            )
+            conn.commit()
+        return cursor.rowcount > 0
+
+    async def clear_history(
+        self,
+        status_filter: Optional[str] = None,
+        before_timestamp: Optional[float] = None,
+    ) -> int:
+        """Remove history entries matching the optional filters.
+
+        Both ``status_filter`` and ``before_timestamp`` can be combined
+        (AND logic).  Returns the number of deleted rows.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+
+            clauses: list[str] = []
+            params: list[Any] = []
+
+            if status_filter is not None:
+                clauses.append("status = ?")
+                params.append(status_filter)
+            if before_timestamp is not None:
+                clauses.append("completed_at < ?")
+                params.append(before_timestamp)
+
+            where = ""
+            if clauses:
+                where = " WHERE " + " AND ".join(clauses)
+
+            cursor = conn.execute(
+                f"DELETE FROM download_history{where}",
+                params,
+            )
+            conn.commit()
+        return cursor.rowcount
+
+    async def get_history_count(self, status_filter: Optional[str] = None) -> int:
+        """Return the number of history entries, optionally filtered by status."""
+        async with self._lock:
+            conn = self._get_conn()
+            if status_filter is not None:
+                row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history WHERE status = ?",
+                    (status_filter,),
+                ).fetchone()
+            else:
+                row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history"
+                ).fetchone()
+        return row["cnt"] if row else 0
+
+    # ------------------------------------------------------------------
+    # Retry
+    # ------------------------------------------------------------------
+
+    async def retry_from_history(self, item_id: int) -> Optional[dict[str, Any]]:
+        """Re-queue a failed or canceled download from history.
+
+        Looks up the history record by its primary key.  If the status is
+        ``failed`` or ``canceled`` a new queue entry is created with the
+        same model metadata and a fresh download id, and the original
+        history entry is **deleted** to prevent exponential growth when
+        the retried item is later canceled or fails again and re-retried.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT * FROM download_history WHERE id = ?",
+                (item_id,),
+            ).fetchone()
+            if row is None:
+                return None
+            status = str(row["status"])
+            if status not in ("failed", "canceled"):
+                return None
+
+            import uuid
+
+            new_id = str(uuid.uuid4())
+            now = time.time()
+            conn.execute(
+                """
+                INSERT INTO download_queue (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, source, file_params,
+                    status, priority, added_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, NULL, 'queued', 0, ?)
+                """,
+                (
+                    new_id,
+                    row["model_id"],
+                    row["model_version_id"],
+                    row["model_name"],
+                    row["version_name"],
+                    row["thumbnail_url"],
+                    "retry",
+                    now,
+                ),
+            )
+            conn.execute(
+                "DELETE FROM download_history WHERE id = ?",
+                (item_id,),
+            )
+            conn.commit()
+            queued = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (new_id,),
+            ).fetchone()
+
+        return dict(queued) if queued else None
+
+    async def retry_all_failed(self) -> int:
+        """Re-queue all failed and canceled downloads from history.
+
+        Each history entry is **deleted** after being re-queued so that
+        repeated retry-all calls do not cause exponential growth.
+
+        Returns the number of items that were re-queued.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            rows = conn.execute(
+                "SELECT * FROM download_history WHERE status IN ('failed', 'canceled')"
+            ).fetchall()
+            if not rows:
+                return 0
+
+            import uuid
+
+            now = time.time()
+            count = 0
+            for row in rows:
+                new_id = str(uuid.uuid4())
+                conn.execute(
+                    """
+                    INSERT INTO download_queue (
+                        download_id, model_id, model_version_id, model_name,
+                        version_name, thumbnail_url, source, file_params,
+                        status, priority, added_at
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, NULL, 'queued', 0, ?)
+                    """,
+                    (
+                        new_id,
+                        row["model_id"],
+                        row["model_version_id"],
+                        row["model_name"],
+                        row["version_name"],
+                        row["thumbnail_url"],
+                        "retry",
+                        now,
+                    ),
+                )
+                conn.execute(
+                    "DELETE FROM download_history WHERE id = ?",
+                    (row["id"],),
+                )
+                count += 1
+            conn.commit()
+
+        return count
+
+    # ------------------------------------------------------------------
+    # Stats
+    # ------------------------------------------------------------------
+
+    async def get_stats(self) -> dict[str, int]:
+        """Return aggregate counts across both tables.
+
+        Returns a dict with keys ``queued``, ``downloading``, ``paused``
+        (all from the queue table) and ``completed``, ``failed``,
+        ``canceled`` (all from the history table).
+        """
+        async with self._lock:
+            conn = self._get_conn()
+
+            queue_rows = conn.execute(
+                "SELECT status, COUNT(*) AS cnt FROM download_queue GROUP BY status"
+            ).fetchall()
+            queue_stats: dict[str, int] = {}
+            for row in queue_rows:
+                queue_stats[str(row["status"])] = row["cnt"]
+
+            history_rows = conn.execute(
+                "SELECT status, COUNT(*) AS cnt FROM download_history GROUP BY status"
+            ).fetchall()
+            history_stats: dict[str, int] = {}
+            for row in history_rows:
+                history_stats[str(row["status"])] = row["cnt"]
+
+        return {
+            "queued": queue_stats.get("queued", 0),
+            "downloading": queue_stats.get("downloading", 0),
+            "paused": queue_stats.get("paused", 0),
+            "completed": history_stats.get("completed", 0),
+            "failed": history_stats.get("failed", 0),
+            "canceled": history_stats.get("canceled", 0),
+        }
+
+    # ------------------------------------------------------------------
+    # Deduplication (one-time cleanup for bug #980)
+    # ------------------------------------------------------------------
+
+    async def deduplicate(self) -> dict[str, int]:
+        """Remove duplicate entries caused by the retry-amplification bug.
+
+        The bug (issue #980) caused the same download to appear N times in
+        both the queue and history tables when ``retry_all_failed`` was
+        called repeatedly without deleting the original history rows.
+
+        This method is called **once** when the singleton is first created.
+        It is idempotent — after the first run there will be no duplicates
+        to remove, so subsequent calls are a no-op.
+
+        Returns a dict with the count of removed rows per table.
+        """
+        result: dict[str, int] = {
+            "removed_history": 0,
+            "removed_queue": 0,
+            "removed_orphan_queue": 0,
+        }
+
+        async with self._lock:
+            conn = self._get_conn()
+
+            # 1. History: for each (model_id, model_version_id, status) triplet
+            #    keep only the row with the highest id (most recently inserted).
+            conn.execute("""
+                DELETE FROM download_history
+                WHERE id NOT IN (
+                    SELECT MAX(id)
+                    FROM download_history
+                    GROUP BY model_id, model_version_id, status
+                )
+            """)
+            result["removed_history"] = conn.execute(
+                "SELECT changes()"
+            ).fetchone()[0]
+
+            # 2. Cross-status dedup: for each (model_id, model_version_id),
+            #    keep only the entry with the highest-priority terminal status.
+            #    Priority: completed (3) > failed (2) > canceled (1).
+            #    This prevents the same model version from having both a
+            #    'failed' and a 'canceled' entry (or a 'completed' alongside
+            #    either) after the bug-created duplicates are removed.
+            conn.execute("""
+                DELETE FROM download_history
+                WHERE id NOT IN (
+                    SELECT dh.id
+                    FROM download_history dh
+                    INNER JOIN (
+                        SELECT model_id, model_version_id,
+                               MAX(CASE status
+                                   WHEN 'completed' THEN 3
+                                   WHEN 'failed' THEN 2
+                                   WHEN 'canceled' THEN 1
+                                   ELSE 0
+                               END) AS best_prio
+                        FROM download_history
+                        GROUP BY model_id, model_version_id
+                    ) best
+                    ON dh.model_id = best.model_id
+                   AND dh.model_version_id = best.model_version_id
+                   AND CASE dh.status
+                           WHEN 'completed' THEN 3
+                           WHEN 'failed' THEN 2
+                           WHEN 'canceled' THEN 1
+                           ELSE 0
+                       END = best.best_prio
+                    GROUP BY dh.model_id, dh.model_version_id
+                    HAVING dh.id = MAX(dh.id)
+                )
+            """)
+            result["removed_history"] += conn.execute(
+                "SELECT changes()"
+            ).fetchone()[0]
+
+            # 3. Queue: for each (model_id, model_version_id) keep only the
+            #    row with the latest added_at (most recently enqueued).
+            conn.execute("""
+                DELETE FROM download_queue
+                WHERE rowid NOT IN (
+                    SELECT MAX(rowid)
+                    FROM download_queue
+                    WHERE status IN ('queued', 'downloading', 'paused', 'waiting')
+                    GROUP BY model_id, model_version_id
+                )
+                AND status IN ('queued', 'downloading', 'paused', 'waiting')
+            """)
+            result["removed_queue"] = conn.execute(
+                "SELECT changes()"
+            ).fetchone()[0]
+
+            # 4. Remove orphaned queue entries — items that were re-queued
+            #    (source='retry') but whose model version already has a
+            #    terminal history entry. These are artifacts of the buggy
+            #    retry cycle that were never cleaned up.
+            conn.execute("""
+                DELETE FROM download_queue
+                WHERE source = 'retry'
+                AND (model_id, model_version_id) IN (
+                    SELECT model_id, model_version_id
+                    FROM download_history
+                    WHERE status IN ('failed', 'canceled')
+                )
+                AND status IN ('queued', 'waiting')
+            """)
+            result["removed_orphan_queue"] = conn.execute(
+                "SELECT changes()"
+            ).fetchone()[0]
+
+            conn.commit()
+
+        logger.info(
+            "Deduplicate: removed %s history rows, %s queue rows, "
+            "%s orphaned queue rows",
+            result["removed_history"],
+            result["removed_queue"],
+            result["removed_orphan_queue"],
+        )
+        return result

py/services/downloaded_version_history_service.py

@@ -96,6 +96,21 @@ class DownloadedVersionHistoryService:
     def get_database_path(self) -> str:
         return self._db_path
 
+    def close(self) -> None:
+        """Close the persistent SQLite connection, if open.
+
+        This is called before plugin update operations to release the
+        database file lock on Windows, allowing ``shutil.rmtree()`` to
+        succeed when the cache resides inside the plugin directory.
+        """
+        if self._conn is not None:
+            try:
+                self._conn.close()
+            except Exception:
+                pass
+            finally:
+                self._conn = None
+
     def _get_active_library_name(self) -> str | None:
         try:
             value = self._settings.get_active_library_name()

py/services/downloader.py

@@ -13,6 +13,7 @@ This module provides a centralized download service with:
 import os
 import logging
 import asyncio
+import ssl
 import aiohttp
 from collections import deque
 from dataclasses import dataclass
@@ -31,6 +32,20 @@ from .errors import RateLimitError
 logger = logging.getLogger(__name__)
 
 
+def is_ssl_cert_verify_error(exc: BaseException) -> bool:
+    """Check if an exception represents an SSL certificate verification failure.
+
+    Matches ``ssl.SSLCertVerificationError``, ``aiohttp.ClientConnectorCertificateError``
+    (which wraps the former), and falls back to the standard OpenSSL error text.
+    """
+    if isinstance(exc, ssl.SSLCertVerificationError):
+        return True
+    cert_error = getattr(exc, "certificate_error", None)
+    if isinstance(cert_error, ssl.SSLCertVerificationError):
+        return True
+    return "CERTIFICATE_VERIFY_FAILED" in str(exc)
+
+
 @dataclass(frozen=True)
 class DownloadProgress:
     """Snapshot of a download transfer at a moment in time."""
@@ -241,7 +256,9 @@ class Downloader:
                 self._session = None
 
         # Check for app-level proxy settings
-        proxy_url = None
+        proxy_url = None  # http(s) proxy, passed via the per-request `proxy=` kwarg
+        socks_proxy_url = None  # SOCKS proxy, handled via aiohttp-socks connector
+        app_proxy_active = False
         settings_manager = get_settings_manager()
         if settings_manager.get("proxy_enabled", False):
             proxy_host = settings_manager.get("proxy_host", "").strip()
@@ -253,9 +270,19 @@ class Downloader:
             if proxy_host and proxy_port:
                 # Build proxy URL
                 if proxy_username and proxy_password:
-                    proxy_url = f"{proxy_type}://{proxy_username}:{proxy_password}@{proxy_host}:{proxy_port}"
+                    full_proxy_url = f"{proxy_type}://{proxy_username}:{proxy_password}@{proxy_host}:{proxy_port}"
                 else:
-                    proxy_url = f"{proxy_type}://{proxy_host}:{proxy_port}"
+                    full_proxy_url = f"{proxy_type}://{proxy_host}:{proxy_port}"
+
+                app_proxy_active = True
+                # aiohttp cannot tunnel SOCKS via the per-request `proxy=` kwarg
+                # (it would send HTTP to the SOCKS port and fail parsing the
+                # SOCKS handshake reply). SOCKS must be handled by an
+                # aiohttp-socks ProxyConnector instead.
+                if proxy_type.startswith("socks"):
+                    socks_proxy_url = full_proxy_url
+                else:
+                    proxy_url = full_proxy_url
 
                 logger.debug(
                     f"Using app-level proxy: {proxy_type}://{proxy_host}:{proxy_port}"
@@ -265,14 +292,41 @@ class Downloader:
             logger.debug(
                 "Proxy mode: system-level proxy (trust_env) will be used if configured in environment."
             )
+        # Build SSL context: prefer certifi's CA bundle for broader
+        # CA coverage across different Python environments (especially
+        # embedded/compatibility Python builds).
+        try:
+            import certifi  # type: ignore[import-untyped]
+
+            ca_path = certifi.where()
+            ssl_context = ssl.create_default_context(cafile=ca_path)
+            logger.debug("SSL: using certifi CA bundle at %s", ca_path)
+        except (ImportError, FileNotFoundError, ValueError, OSError):
+            ssl_context = ssl.create_default_context()
+            logger.debug("SSL: certifi unavailable; using system default CA bundle")
+
         # Optimize TCP connection parameters
-        connector = aiohttp.TCPConnector(
-            ssl=True,
+        connector_kwargs = dict(
+            ssl=ssl_context,
             limit=8,  # Concurrent connections
             ttl_dns_cache=300,  # DNS cache timeout
             force_close=False,  # Keep connections for reuse
             enable_cleanup_closed=True,
         )
+        if socks_proxy_url:
+            # Route all traffic through the SOCKS proxy via aiohttp-socks. The
+            # connector tunnels every connection, so no per-request `proxy=` is
+            # used (and must not be — see self._proxy_url below).
+            try:
+                from aiohttp_socks import ProxyConnector
+            except ImportError as e:  # pragma: no cover
+                raise RuntimeError(
+                    "A SOCKS proxy is configured but the 'aiohttp-socks' package "
+                    "is not installed. Install it with: pip install aiohttp-socks"
+                ) from e
+            connector = ProxyConnector.from_url(socks_proxy_url, **connector_kwargs)
+        else:
+            connector = aiohttp.TCPConnector(**connector_kwargs)
 
         # Configure timeout parameters
         timeout = aiohttp.ClientTimeout(
@@ -283,12 +337,14 @@ class Downloader:
 
         self._session = aiohttp.ClientSession(
             connector=connector,
-            trust_env=proxy_url
-            is None,  # Only use system proxy if no app-level proxy is set
+            # Only fall back to system/env proxy when no app-level proxy is active
+            trust_env=not app_proxy_active,
             timeout=timeout,
         )
 
-        # Store proxy URL for use in requests
+        # Store proxy URL for per-request use. Stays None for SOCKS because the
+        # ProxyConnector already tunnels everything; passing proxy= for SOCKS
+        # would re-trigger the original aiohttp parse error.
         self._proxy_url = proxy_url
         self._session_created_at = datetime.now()
 
@@ -736,6 +792,17 @@ class Downloader:
                 DownloadRestartRequested,
             ) as e:
                 retry_count += 1
+
+                if is_ssl_cert_verify_error(e):
+                    logger.error(
+                        "SSL certificate verification failed when connecting to %s. "
+                        "This is usually caused by an outdated CA certificate bundle "
+                        "in the Python environment. Recommended fixes:\n"
+                        "  1. pip install --upgrade certifi\n"
+                        "  2. pip install pip-system-certs",
+                        url,
+                    )
+
                 logger.warning(
                     f"Network error during download (attempt {retry_count}/{self.max_retries + 1}): {e}"
                 )

py/services/metadata_sync_service.py

@@ -216,13 +216,19 @@ class MetadataSyncService:
             provider_used: Optional[str] = None
             last_error: Optional[str] = None
             civitai_api_not_found = False
+            any_rate_limited = False
 
             for provider_name, provider in provider_attempts:
                 try:
                     civitai_metadata_candidate, error = await provider.get_model_by_hash(sha256)
                 except RateLimitError as exc:
-                    exc.provider = exc.provider or (provider_name or provider.__class__.__name__)
-                    raise
+                    logger.warning(
+                        "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                        provider_name or provider.__class__.__name__,
+                        exc.retry_after or 0,
+                    )
+                    any_rate_limited = True
+                    continue
                 except Exception as exc:  # pragma: no cover - defensive logging
                     logger.error("Provider %s failed for hash %s: %s", provider_name, sha256, exc)
                     civitai_metadata_candidate, error = None, str(exc)
@@ -258,6 +264,14 @@ class MetadataSyncService:
                     model_data["last_checked_at"] = datetime.now().timestamp()
                     needs_save = True
 
+                # When the model was already classified as "not on CivitAI" via
+                # .metadata.json (civitai_deleted=True) but the SQLite cache is
+                # stale (because the pre-fix code never persisted these flags),
+                # ensure the flags are written to the scanner cache + SQLite.
+                if not needs_save and model_data.get("civitai_deleted") is True:
+                    model_data["last_checked_at"] = datetime.now().timestamp()
+                    needs_save = True
+
                 # Save metadata if any state was updated
                 if needs_save:
                     data_to_save = model_data.copy()
@@ -266,6 +280,7 @@ class MetadataSyncService:
                     if "last_checked_at" not in data_to_save:
                         data_to_save["last_checked_at"] = datetime.now().timestamp()
                     await self._metadata_manager.save_metadata(file_path, data_to_save)
+                    await update_cache_func(file_path, file_path, data_to_save)
 
                 default_error = (
                     "CivitAI model is deleted and metadata archive DB is not enabled"
@@ -276,17 +291,18 @@ class MetadataSyncService:
                 )
 
                 resolved_error = last_error or default_error
+                if any_rate_limited and "Rate limited" not in resolved_error:
+                    resolved_error = "Rate limited"
                 if is_expected_offline_error(resolved_error):
                     resolved_error = OFFLINE_FRIENDLY_MESSAGE
 
                 error_msg = (
                     f"Error fetching metadata: {resolved_error} "
-                    f"(model_name={model_data.get('model_name', '')})"
+                    f"(file={os.path.basename(file_path)}, sha256={sha256})"
                 )
-                if is_expected_offline_error(resolved_error):
-                    logger.info(error_msg)
-                else:
-                    logger.error(error_msg)
+                # Use case layer (BulkMetadataRefreshUseCase) logs failed models at WARNING level,
+                # so this level is demoted to DEBUG to avoid duplicate user-visible logging.
+                logger.debug(error_msg)
                 return False, error_msg
 
             model_data["from_civitai"] = True
@@ -411,7 +427,18 @@ class MetadataSyncService:
         metadata = await metadata_loader(metadata_path)
 
         for key, value in updates.items():
-            if isinstance(value, dict) and isinstance(metadata.get(key), dict):
+            if key == "tags" and isinstance(value, list):
+                # Normalize tags: trim, lowercase, deduplicate
+                normalized = []
+                seen = set()
+                for tag in value:
+                    if isinstance(tag, str):
+                        t = tag.strip().lower()
+                        if t and t not in seen:
+                            normalized.append(t)
+                            seen.add(t)
+                metadata[key] = normalized
+            elif isinstance(value, dict) and isinstance(metadata.get(key), dict):
                 metadata[key].update(value)
             else:
                 metadata[key] = value

py/services/model_metadata_provider.py

@@ -65,7 +65,14 @@ class _RateLimitRetryHelper:
                 return await func(*args, **kwargs)
             except RateLimitError as exc:
                 attempt += 1
-                if attempt >= self._retry_limit:
+
+                # Determine effective retry limit based on rate-limit magnitude
+                effective_retry_limit = self._retry_limit  # default: 3
+                if exc.retry_after is not None and exc.retry_after >= 120.0:
+                    # Long rate-limit window (>=2 min) — retries are futile
+                    effective_retry_limit = 1  # total 1 attempt = 0 retries
+
+                if attempt >= effective_retry_limit:
                     exc.provider = exc.provider or label
                     raise
 
@@ -81,7 +88,11 @@ class _RateLimitRetryHelper:
 
     def _calculate_delay(self, retry_after: Optional[float], attempt: int) -> float:
         if retry_after is not None:
-            return min(self._max_delay, max(0.0, retry_after))
+            # Cap at 1800s (30 min) as a safety ceiling. The old 30s cap was
+            # too low — CivArchive can return retry_after ~1500s, causing all
+            # retries to fail. A generous ceiling protects against pathological
+            # server values while still respecting the server's guidance.
+            return min(1800.0, max(0.0, retry_after))
 
         base_delay = self._base_delay * (2 ** max(0, attempt - 1))
         jitter_span = base_delay * self._jitter_ratio
@@ -474,8 +485,12 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result:
                     return result, error
             except RateLimitError as exc:
-                exc.provider = exc.provider or label
-                raise exc
+                logger.warning(
+                    "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                    label,
+                    exc.retry_after or 0,
+                )
+                continue
             except Exception as e:
                 logger.debug("Provider %s failed for get_model_by_hash: %s", label, e)
                 continue
@@ -493,16 +508,12 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result:
                     return result
             except RateLimitError as exc:
-                if not_found_confirmed:
-                    logger.debug(
-                        "Suppressing rate limit from %s for model %s: "
-                        "already confirmed as not found by another provider",
-                        label,
-                        model_id,
-                    )
-                    return None
-                exc.provider = exc.provider or label
-                raise exc
+                logger.warning(
+                    "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                    label,
+                    exc.retry_after or 0,
+                )
+                continue
             except ResourceNotFoundError:
                 not_found_confirmed = True
                 logger.debug(
@@ -528,8 +539,12 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result:
                     return result
             except RateLimitError as exc:
-                exc.provider = exc.provider or label
-                raise exc
+                logger.warning(
+                    "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                    label,
+                    exc.retry_after or 0,
+                )
+                continue
             except Exception as e:
                 logger.debug("Provider %s failed for get_model_version: %s", label, e)
                 continue
@@ -546,8 +561,12 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result:
                     return result, error
             except RateLimitError as exc:
-                exc.provider = exc.provider or label
-                raise exc
+                logger.warning(
+                    "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                    label,
+                    exc.retry_after or 0,
+                )
+                continue
             except Exception as e:
                 logger.debug("Provider %s failed for get_model_version_info: %s", label, e)
                 continue
@@ -568,8 +587,12 @@ class FallbackMetadataProvider(ModelMetadataProvider):
             except NotImplementedError:
                 continue
             except RateLimitError as exc:
-                exc.provider = exc.provider or label
-                raise exc
+                logger.warning(
+                    "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                    label,
+                    exc.retry_after or 0,
+                )
+                continue
             except Exception as e:
                 logger.debug(
                     "Provider %s failed for get_model_versions_by_hashes: %s",
@@ -590,8 +613,12 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result is not None:
                     return result
             except RateLimitError as exc:
-                exc.provider = exc.provider or label
-                raise exc
+                logger.warning(
+                    "Provider %s is rate-limited (retry_after=%.0fs); skipping to next provider",
+                    label,
+                    exc.retry_after or 0,
+                )
+                continue
             except Exception as e:
                 logger.debug("Provider %s failed for get_user_models: %s", label, e)
                 continue

py/services/model_query.py

@@ -294,12 +294,14 @@ class ModelFilterSet:
                 for tag, state in tag_filters.items():
                     if not tag:
                         continue
+                    # Normalize to lowercase for case-insensitive matching
+                    normalized = tag.strip().lower()
                     if state == "exclude":
-                        exclude_tags.add(tag)
+                        exclude_tags.add(normalized)
                     else:
-                        include_tags.add(tag)
+                        include_tags.add(normalized)
             else:
-                include_tags = {tag for tag in tag_filters if tag}
+                include_tags = {tag.strip().lower() for tag in tag_filters if tag}
 
             if include_tags:
                 tag_logic = criteria.tag_logic.lower() if criteria.tag_logic else "any"
@@ -318,13 +320,17 @@ class ModelFilterSet:
                                 return True
                             # Otherwise, check if all non-special tags match
                             if non_special_tags:
-                                return all(tag in (item_tags or []) for tag in non_special_tags)
+                                # Case-insensitive: normalize item tags too
+                                normalized_item_tags = {t.strip().lower() for t in (item_tags or []) if isinstance(t, str)}
+                                return all(tag in normalized_item_tags for tag in non_special_tags)
                             return True
-                        # Normal case: all tags must match
-                        return all(tag in (item_tags or []) for tag in non_special_tags)
+                        # Normal case: all tags must match (case-insensitive)
+                        normalized_item_tags = {t.strip().lower() for t in (item_tags or []) if isinstance(t, str)}
+                        return all(tag in normalized_item_tags for tag in non_special_tags)
                     else:
-                        # OR logic (default): item must have ANY include tag
-                        return any(tag in include_tags for tag in (item_tags or []))
+                        # OR logic (default): item must have ANY include tag (case-insensitive)
+                        normalized_item_tags = {t.strip().lower() for t in (item_tags or []) if isinstance(t, str)}
+                        return bool(normalized_item_tags & include_tags)
 
                 items = [item for item in items if matches_include(item.get("tags"))]
 
@@ -333,7 +339,9 @@ class ModelFilterSet:
                 def matches_exclude(item_tags):
                     if not item_tags and "__no_tags__" in exclude_tags:
                         return True
-                    return any(tag in exclude_tags for tag in (item_tags or []))
+                    # Case-insensitive: normalize item tags
+                    normalized_item_tags = {t.strip().lower() for t in (item_tags or []) if isinstance(t, str)}
+                    return bool(normalized_item_tags & exclude_tags)
 
                 items = [
                     item for item in items if not matches_exclude(item.get("tags"))

py/services/model_scanner.py

@@ -532,6 +532,13 @@ class ModelScanner:
         if not scan_result or not getattr(self, '_persistent_cache', None):
             return
 
+        if self.is_cancelled():
+            logger.info(
+                f"{self.model_type.capitalize()} Scanner: Skipping _save_persistent_cache "
+                "after cancellation"
+            )
+            return
+
         hash_snapshot = self._build_hash_index_snapshot(scan_result.hash_index)
         loop = asyncio.get_event_loop()
         try:
@@ -705,14 +712,20 @@ class ModelScanner:
             # Determine the page type based on model type
             # Scan for new data
             scan_result = await self._gather_model_data()
-            await self._apply_scan_result(scan_result)
-            await self._save_persistent_cache(scan_result)
-            await self._sync_download_history(scan_result.raw_data, source='scan')
+            if not self.is_cancelled():
+                await self._apply_scan_result(scan_result)
+                await self._save_persistent_cache(scan_result)
+                await self._sync_download_history(scan_result.raw_data, source='scan')
 
-            logger.info(
-                f"{self.model_type.capitalize()} Scanner: Cache initialization completed in {time.time() - start_time:.2f} seconds, "
-                f"found {len(scan_result.raw_data)} models"
-            )
+                logger.info(
+                    f"{self.model_type.capitalize()} Scanner: Cache initialization completed in {time.time() - start_time:.2f} seconds, "
+                    f"found {len(scan_result.raw_data)} models"
+                )
+            else:
+                logger.info(
+                    f"{self.model_type.capitalize()} Scanner: Cache initialization cancelled "
+                    f"after {time.time() - start_time:.2f} seconds"
+                )
         except Exception as e:
             logger.error(f"{self.model_type.capitalize()} Scanner: Error initializing cache: {e}")
             # Ensure cache is at least an empty structure on error
@@ -1067,8 +1080,11 @@ class ModelScanner:
 
         model_data = self._build_cache_entry(metadata, folder=normalized_folder)
 
-        # Compute SHA256 hash when metadata provided none (e.g., CivitAI API response has empty hashes)
-        if not model_data.get('sha256') and file_path:
+        # Compute SHA256 hash when metadata provided none (e.g., CivitAI API response has empty hashes).
+        # Respect hash_status='pending' (set by CheckpointScanner for large models) to defer
+        # hash calculation until on-demand — avoids reading entire checkpoint files at startup.
+        hash_status = model_data.get('hash_status', '')
+        if not model_data.get('sha256') and hash_status != 'pending' and file_path:
             try:
                 logger.info(f"Computing SHA256 hash for {file_path} (was empty from metadata)")
                 sha256 = await calculate_sha256(file_path)
@@ -1093,6 +1109,13 @@ class ModelScanner:
         if scan_result is None:
             return
 
+        if self.is_cancelled():
+            logger.info(
+                f"{self.model_type.capitalize()} Scanner: Skipping _apply_scan_result "
+                "after cancellation"
+            )
+            return
+
         self._hash_index = scan_result.hash_index
         self._tags_count = dict(scan_result.tags_count)
         self._excluded_models = list(scan_result.excluded_models)
@@ -1761,6 +1784,13 @@ class ModelScanner:
         """
         if not file_paths or self._cache is None:
             return False
+
+        if self.is_cancelled():
+            logger.info(
+                f"{self.model_type.capitalize()} Scanner: Skipping cache update "
+                "after cancelled bulk delete"
+            )
+            return False
             
         try:
             # Get all models that need to be removed from cache

py/services/model_update_service.py

@@ -689,6 +689,7 @@ class ModelUpdateService:
         *,
         force_refresh: bool = False,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, ModelUpdateRecord]:
         """Refresh update information for every model present in the cache."""
         scanner.reset_cancellation()
@@ -703,6 +704,7 @@ class ModelUpdateService:
         local_versions = await self._collect_local_versions(
             scanner,
             target_model_ids=target_filter,
+            folder_path=folder_path,
         )
         total_models = len(local_versions)
         if total_models == 0:
@@ -1276,6 +1278,7 @@ class ModelUpdateService:
         scanner,
         *,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, List[int]]:
         cache = await scanner.get_cached_data()
         mapping: Dict[int, set[int]] = {}
@@ -1288,7 +1291,19 @@ class ModelUpdateService:
             if not target_set:
                 return {}
 
+        normalized_folder = None
+        if folder_path is not None:
+            normalized_folder = folder_path.replace("\\", "/").strip("/")
+
         for item in cache.raw_data:
+            # Apply folder filter first (cheapest check)
+            if normalized_folder is not None:
+                if not isinstance(item, dict):
+                    continue
+                item_folder = (item.get("folder") or "").replace("\\", "/").strip("/")
+                if item_folder != normalized_folder and not item_folder.startswith(normalized_folder + "/"):
+                    continue
+
             civitai = item.get("civitai") if isinstance(item, dict) else None
             if not isinstance(civitai, dict):
                 continue

py/services/persistent_recipe_cache.py

@@ -12,7 +12,7 @@ import logging
 import os
 import sqlite3
 import threading
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import Dict, List, Optional, Set, Tuple
 
 from ..utils.cache_paths import CacheType, resolve_cache_path_with_migration
@@ -26,6 +26,8 @@ class PersistedRecipeData:
 
     raw_data: List[Dict]
     file_stats: Dict[str, Tuple[float, int]]  # json_path -> (mtime, size)
+    image_id_map: Dict[str, str] = field(default_factory=dict)
+    """Precomputed mapping of civitai image_id → recipe_id."""
 
 
 class PersistentRecipeCache:
@@ -116,6 +118,20 @@ class PersistentRecipeCache:
                     if not rows:
                         return None
 
+                    # Restore precomputed image_id_map if available
+                    image_id_map: Dict[str, str] = {}
+                    try:
+                        meta_row = conn.execute(
+                            "SELECT value FROM cache_metadata WHERE key = ?",
+                            ("image_id_map",),
+                        ).fetchone()
+                        if meta_row:
+                            parsed = json.loads(meta_row["value"])
+                            if isinstance(parsed, dict):
+                                image_id_map = parsed
+                    except Exception:
+                        pass  # missing or corrupt — rebuilt on next cache refresh
+
                 finally:
                     conn.close()
         except FileNotFoundError:
@@ -138,14 +154,24 @@ class PersistentRecipeCache:
                     row["file_size"] or 0,
                 )
 
-        return PersistedRecipeData(raw_data=raw_data, file_stats=file_stats)
+        return PersistedRecipeData(
+            raw_data=raw_data,
+            file_stats=file_stats,
+            image_id_map=image_id_map,
+        )
 
-    def save_cache(self, recipes: List[Dict], json_paths: Optional[Dict[str, str]] = None) -> None:
+    def save_cache(
+        self,
+        recipes: List[Dict],
+        json_paths: Optional[Dict[str, str]] = None,
+        image_id_map: Optional[Dict[str, str]] = None,
+    ) -> None:
         """Save all recipes to SQLite cache.
 
         Args:
             recipes: List of recipe dictionaries to persist.
             json_paths: Optional mapping of recipe_id -> json_path for file stats.
+            image_id_map: Optional precomputed civitai image_id → recipe_id mapping.
         """
         if not self.is_enabled():
             return
@@ -186,6 +212,12 @@ class PersistentRecipeCache:
                             recipe_rows,
                         )
 
+                    # Persist image_id_map for O(1) lookups on cache load
+                    conn.execute(
+                        "INSERT OR REPLACE INTO cache_metadata (key, value) VALUES (?, ?)",
+                        ("image_id_map", json.dumps(image_id_map or {})),
+                    )
+
                     conn.commit()
                     logger.debug("Persisted %d recipes to cache", len(recipe_rows))
                 finally:
@@ -273,6 +305,29 @@ class PersistentRecipeCache:
         except Exception as exc:
             logger.debug("Failed to remove recipe %s from cache: %s", recipe_id, exc)
 
+    def save_image_id_map(self, image_id_map: Dict[str, str]) -> None:
+        """Persist the image_id_map to cache_metadata without rewriting the full cache.
+
+        This is called after ``add_recipe`` / ``remove_recipe`` mutations so
+        the persistent copy does not go stale between full ``save_cache`` calls.
+        """
+        if not self.is_enabled() or not self._schema_initialized:
+            return
+
+        try:
+            with self._db_lock:
+                conn = self._connect()
+                try:
+                    conn.execute(
+                        "INSERT OR REPLACE INTO cache_metadata (key, value) VALUES (?, ?)",
+                        ("image_id_map", json.dumps(image_id_map)),
+                    )
+                    conn.commit()
+                finally:
+                    conn.close()
+        except Exception as exc:
+            logger.debug("Failed to persist image_id_map: %s", exc)
+
     def get_indexed_recipe_ids(self) -> Set[str]:
         """Return all recipe IDs in the cache.
 

py/services/recipe_cache.py

@@ -1,6 +1,6 @@
 import asyncio
 from typing import Iterable, List, Dict, Optional
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from operator import itemgetter
 from natsort import natsorted
 
@@ -14,6 +14,15 @@ class RecipeCache:
     sorted_by_date: List[Dict]
     folders: List[str] | None = None
     folder_tree: Dict | None = None
+    image_id_map: Dict[str, str] = field(default_factory=dict)
+    """Mapping of civitai image_id → recipe_id, precomputed at cache build time.
+
+    Built once during cache initialization (O(n)) so that
+    ``check_image_exists`` and ``import_from_url`` duplicate checks
+    can look up image_id in O(1) instead of scanning all recipes.
+    Recipes imported from local files have no valid civitai image_id
+    and are naturally excluded from this map.
+    """
 
     def __post_init__(self):
         self._lock = asyncio.Lock()

py/services/recipe_scanner.py

@@ -20,6 +20,7 @@ from .metadata_service import get_default_metadata_provider
 from .checkpoint_scanner import CheckpointScanner
 from .settings_manager import get_settings_manager
 from .recipes.errors import RecipeNotFoundError
+from ..utils.civitai_utils import extract_civitai_image_id
 from ..utils.utils import calculate_recipe_fingerprint, fuzzy_match
 from natsort import natsorted
 import sys
@@ -532,7 +533,21 @@ class RecipeScanner:
                     self._sort_cache_sync()
                     # Backfill source_path from JSON files if missing (schema migration)
                     if self._backfill_source_path_if_needed(recipes, json_paths):
-                        self._persistent_cache.save_cache(recipes, json_paths)
+                        self._cache.image_id_map = self._build_image_id_map()
+                        self._persistent_cache.save_cache(
+                            recipes, json_paths, self._cache.image_id_map
+                        )
+                    else:
+                        # Use persisted map, or rebuild if empty (e.g. first startup
+                        # after deploying the image_id_map feature).
+                        if persisted.image_id_map:
+                            self._cache.image_id_map = dict(persisted.image_id_map)
+                        else:
+                            self._cache.image_id_map = self._build_image_id_map()
+                            if self._cache.image_id_map:
+                                self._persistent_cache.save_image_id_map(
+                                    self._cache.image_id_map
+                                )
                     return self._cache
                 else:
                     # Partial update: some files changed
@@ -545,8 +560,11 @@ class RecipeScanner:
                     self._sort_cache_sync()
                     # Backfill source_path from JSON files if missing (schema migration)
                     self._backfill_source_path_if_needed(recipes, json_paths)
+                    self._cache.image_id_map = self._build_image_id_map()
                     # Persist updated cache
-                    self._persistent_cache.save_cache(recipes, json_paths)
+                    self._persistent_cache.save_cache(
+                        recipes, json_paths, self._cache.image_id_map
+                    )
                     return self._cache
 
             # Fall back to full directory scan
@@ -558,9 +576,12 @@ class RecipeScanner:
             self._cache.raw_data = recipes
             self._update_folder_metadata(self._cache)
             self._sort_cache_sync()
+            self._cache.image_id_map = self._build_image_id_map()
 
             # Persist for next startup
-            self._persistent_cache.save_cache(recipes, json_paths)
+            self._persistent_cache.save_cache(
+                recipes, json_paths, self._cache.image_id_map
+            )
 
             return self._cache
         except Exception as e:
@@ -832,6 +853,28 @@ class RecipeScanner:
         except Exception as e:
             logger.error(f"Error sorting recipe cache: {e}")
 
+    def _build_image_id_map(self) -> Dict[str, str]:
+        """Build civitai image_id → recipe_id mapping from cached recipes.
+
+        Only recipes with a valid CivitAI image URL source_path produce an
+        entry.  Recipes imported from local files are naturally excluded.
+        """
+        mapping: Dict[str, str] = {}
+        if not self._cache:
+            return mapping
+        for recipe in getattr(self._cache, "raw_data", []):
+            if not isinstance(recipe, dict):
+                continue
+            source = recipe.get("source_path")
+            if not source:
+                continue
+            image_id = extract_civitai_image_id(source)
+            if image_id and image_id not in mapping:
+                recipe_id = recipe.get("id")
+                if recipe_id is not None:
+                    mapping[image_id] = str(recipe_id)
+        return mapping
+
     async def _wait_for_lora_scanner(self) -> None:
         """Ensure the LoRA scanner has initialized before recipe enrichment."""
 
@@ -1296,11 +1339,20 @@ class RecipeScanner:
         # Update FTS index
         self._update_fts_index_for_recipe(recipe_data, "add")
 
+        source = recipe_data.get("source_path")
+        if source:
+            image_id = extract_civitai_image_id(source)
+            if image_id:
+                recipe_id_value = recipe_data.get("id")
+                if recipe_id_value is not None:
+                    cache.image_id_map[image_id] = str(recipe_id_value)
+
         # Persist to SQLite cache
         if self._persistent_cache:
             recipe_id = str(recipe_data.get("id", ""))
             json_path = self._json_path_map.get(recipe_id, "")
             self._persistent_cache.update_recipe(recipe_data, json_path)
+            self._persistent_cache.save_image_id_map(cache.image_id_map)
 
     async def remove_recipe(self, recipe_id: str) -> bool:
         """Remove a recipe from the cache by ID."""
@@ -1319,9 +1371,15 @@ class RecipeScanner:
         # Update FTS index
         self._update_fts_index_for_recipe(recipe_id, "remove")
 
+        # Remove any image_id entry pointing to this recipe
+        stale = [k for k, v in cache.image_id_map.items() if v == recipe_id]
+        for k in stale:
+            del cache.image_id_map[k]
+
         # Remove from SQLite cache
         if self._persistent_cache:
             self._persistent_cache.remove_recipe(recipe_id)
+            self._persistent_cache.save_image_id_map(cache.image_id_map)
             self._json_path_map.pop(recipe_id, None)
 
         return True
@@ -1332,14 +1390,21 @@ class RecipeScanner:
         cache = await self.get_cached_data()
         removed = await cache.bulk_remove(recipe_ids, resort=False)
         if removed:
+            removed_ids = {str(r.get("id", "")) for r in removed}
+            stale = [k for k, v in cache.image_id_map.items() if v in removed_ids]
+            for k in stale:
+                del cache.image_id_map[k]
+
             self._schedule_resort()
-            # Update FTS index and persistent cache for each removed recipe
             for recipe in removed:
                 recipe_id = str(recipe.get("id", ""))
                 self._update_fts_index_for_recipe(recipe_id, "remove")
                 if self._persistent_cache:
                     self._persistent_cache.remove_recipe(recipe_id)
                     self._json_path_map.pop(recipe_id, None)
+
+            if self._persistent_cache:
+                self._persistent_cache.save_image_id_map(cache.image_id_map)
         return len(removed)
 
     async def scan_all_recipes(self) -> List[Dict]:

py/services/recipes/analysis_service.py

@@ -176,6 +176,24 @@ class RecipeAnalysisService:
                     self._exif_utils.extract_image_metadata, temp_path
                 )
 
+            if not metadata and civitai_image_id and image_info:
+                original_url = image_info.get("url")
+                if original_url:
+                    self._logger.debug(
+                        "Optimized image lacks embedded metadata, "
+                        "falling back to original image: %s",
+                        original_url,
+                    )
+                    orig_temp_path = self._create_temp_path(suffix=".png")
+                    try:
+                        await self._download_image(original_url, orig_temp_path)
+                        metadata = await asyncio.to_thread(
+                            self._exif_utils.extract_image_metadata,
+                            orig_temp_path,
+                        )
+                    finally:
+                        self._safe_cleanup(orig_temp_path)
+
             result = await self._parse_metadata(
                 metadata or {},
                 recipe_scanner=recipe_scanner,

py/services/recipes/persistence_service.py

@@ -49,8 +49,18 @@ class RecipePersistenceService:
         tags: Iterable[str],
         metadata: Optional[dict[str, Any]],
         extension: str | None = None,
+        recipe_id: str | None = None,
+        target_dir: str | None = None,
     ) -> PersistenceResult:
-        """Persist a user uploaded recipe."""
+        """Persist a user uploaded recipe.
+
+        Args:
+            recipe_id: If provided, reuse this ID instead of generating a new
+                UUID. Used by re-import to preserve the original recipe identity.
+            target_dir: If provided, save recipe files to this directory instead
+                of the default recipes_dir. Used by re-import to preserve the
+                original folder location.
+        """
 
         missing_fields = []
         if not name:
@@ -63,10 +73,10 @@ class RecipePersistenceService:
             )
 
         resolved_image_bytes = self._resolve_image_bytes(image_bytes, image_base64)
-        recipes_dir = recipe_scanner.recipes_dir
+        recipes_dir = target_dir or recipe_scanner.recipes_dir
         os.makedirs(recipes_dir, exist_ok=True)
 
-        recipe_id = str(uuid.uuid4())
+        recipe_id = recipe_id or str(uuid.uuid4())
         
         # Handle video formats by bypassing optimization and metadata embedding
         is_video = extension in [".mp4", ".webm"]
@@ -115,6 +125,22 @@ class RecipePersistenceService:
         if metadata.get("source_path"):
             recipe_data["source_path"] = metadata.get("source_path")
 
+        nsfw_level = metadata.get("preview_nsfw_level")
+        if nsfw_level is not None and isinstance(nsfw_level, int):
+            recipe_data["preview_nsfw_level"] = nsfw_level
+
+        # Compute recipe folder relative to recipes root, mirroring
+        # RecipeScanner._calculate_folder() which is only called during scan/load.
+        if recipe_scanner.recipes_dir:
+            recipe_file_dir = os.path.dirname(normalized_image_path)
+            try:
+                relative_folder = os.path.relpath(recipe_file_dir, recipe_scanner.recipes_dir)
+                if relative_folder in (".", ""):
+                    relative_folder = ""
+                recipe_data["folder"] = relative_folder.replace(os.path.sep, "/")
+            except Exception:
+                recipe_data["folder"] = ""
+
         json_filename = f"{recipe_id}.recipe.json"
         json_path = os.path.join(recipes_dir, json_filename)
         json_path = os.path.normpath(json_path)

py/services/service_registry.py

@@ -188,6 +188,25 @@ class ServiceRegistry:
             logger.debug(f"Created and registered {service_name}")
             return service
 
+    @classmethod
+    async def get_download_queue_service(cls):
+        """Get or create the download queue service."""
+        service_name = "download_queue_service"
+
+        if service_name in cls._services:
+            return cls._services[service_name]
+
+        async with cls._get_lock(service_name):
+            if service_name in cls._services:
+                return cls._services[service_name]
+
+            from .download_queue_service import DownloadQueueService
+
+            service = await DownloadQueueService.get_instance()
+            cls._services[service_name] = service
+            logger.debug(f"Created and registered {service_name}")
+            return service
+
     @classmethod
     async def get_backup_service(cls):
         """Get or create the backup service."""

py/services/settings_manager.py

@@ -91,7 +91,6 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "autoplay_on_hover": False,
     "display_density": "default",
     "card_info_display": "always",
-    "show_folder_sidebar": True,
     "include_trigger_words": False,
     "compact_mode": False,
     "priority_tags": DEFAULT_PRIORITY_TAG_CONFIG.copy(),
@@ -106,6 +105,7 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "download_skip_base_models": [],
     "backup_auto_enabled": True,
     "backup_retention_count": 5,
+    "use_new_license_icons": True,
 }
 
 
@@ -134,6 +134,9 @@ class SettingsManager:
         self._template_path = (
             Path(__file__).resolve().parents[2] / "settings.json.example"
         )
+        # Known placeholder value in settings.json.example; any file containing
+        # this value should be treated as "not configured".
+        self._TEMPLATE_PLACEHOLDER_API_KEY = "your_civitai_api_key_here"
         self.settings = self._load_settings()
         self._migrate_setting_keys()
         self._ensure_default_settings()
@@ -165,6 +168,12 @@ class SettingsManager:
                     self._original_disk_payload = copy.deepcopy(data)
                     if self._matches_template_payload(data):
                         self._preserve_disk_template = True
+                    # Clean up the template placeholder so it is not treated
+                    # as a real key (affects both the frontend boolean and
+                    # the downloader's Authorization header).
+                    placeholder = self._TEMPLATE_PLACEHOLDER_API_KEY
+                    if data.get("civitai_api_key") == placeholder:
+                        data["civitai_api_key"] = ""
                 return data
             except json.JSONDecodeError as exc:
                 logger.error("Failed to parse settings.json: %s", exc)

py/services/tag_update_service.py

@@ -36,9 +36,9 @@ class TagUpdateService:
             if isinstance(tag, str) and tag.strip():
                 # Convert all tags to lowercase to avoid case sensitivity issues on Windows
                 normalized = tag.strip().lower()
-                if normalized.lower() not in existing_lower:
+                if normalized not in existing_lower:
                     existing_tags.append(normalized)
-                    existing_lower.append(normalized.lower())
+                    existing_lower.append(normalized)
                     tags_added.append(normalized)
 
         metadata["tags"] = existing_tags

py/services/use_cases/bulk_metadata_refresh_use_case.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import logging
+import time
 from typing import Any, Dict, List, Optional, Protocol, Sequence
 
 from ..metadata_sync_service import MetadataSyncService
@@ -62,26 +63,48 @@ class BulkMetadataRefreshUseCase:
         ]
 
         total_to_process = len(to_process)
+        initial_skipped = total_models - total_to_process  # models excluded from fetch queue
         processed = 0
         success = 0
+        skipped_count = initial_skipped
+        handled_count = initial_skipped
         needs_resort = False
+        start_time = time.monotonic()
+        failures: List[Dict[str, str]] = []
 
         self._service.scanner.reset_cancellation()
 
         async def emit(status: str, **extra: Any) -> None:
             if progress_callback is None:
                 return
-            payload = {"status": status, "total": total_to_process, "processed": processed, "success": success}
+            payload = {
+                "status": status,
+                "total": total_models,
+                "processed": processed,
+                "success": success,
+                "failure_count": len(failures),
+                "skipped_count": skipped_count,
+                "handled": handled_count,
+                "elapsed_seconds": int(time.monotonic() - start_time),
+            }
+            # Only include full failure details in terminal emits (completed,
+            # cancelled, rate_limited) to avoid serializing the list on every
+            # per-model progress update.
+            if failures and status in ("completed", "cancelled", "rate_limited"):
+                payload["failures"] = failures
             payload.update(extra)
             await progress_callback.on_progress(payload)
 
         await emit("started")
 
+        RATE_LIMIT_ABORT_THRESHOLD = 3
+        consecutive_rate_limits = 0
+
         for model in to_process:
             if self._service.scanner.is_cancelled():
                 self._logger.info("Bulk metadata refresh cancelled by user")
                 await emit("cancelled", processed=processed, success=success)
-                return {"success": False, "message": "Operation cancelled", "processed": processed, "updated": success, "total": total_models}
+                return {"success": False, "message": "Operation cancelled", "processed": processed, "updated": success, "total": total_models, "failures": failures, "failure_count": len(failures), "skipped_count": skipped_count, "elapsed_seconds": int(time.monotonic() - start_time)}
             try:
                 original_name = model.get("model_name")
 
@@ -101,31 +124,76 @@ class BulkMetadataRefreshUseCase:
                             model["hash_status"] = "completed"
                         else:
                             self._logger.error(f"Failed to calculate hash for {file_path}")
+                            failures.append({"name": model.get("model_name", file_path or "Unknown"), "error": "Failed to calculate hash"})
                             processed += 1
+                            handled_count += 1
                             continue
                     else:
                         self._logger.warning(f"Scanner does not support lazy hash calculation for {file_path}")
+                        skipped_count += 1
                         processed += 1
+                        handled_count += 1
                         continue
 
                 # Skip models without valid hash
                 if not model.get("sha256"):
                     self._logger.warning(f"Skipping model without hash: {file_path}")
+                    skipped_count += 1
                     processed += 1
+                    handled_count += 1
                     continue
 
                 await MetadataManager.hydrate_model_data(model)
-                result, _ = await self._metadata_sync.fetch_and_update_model(
+                result, error_msg = await self._metadata_sync.fetch_and_update_model(
                     sha256=model["sha256"],
                     file_path=model["file_path"],
                     model_data=model,
                     update_cache_func=self._service.scanner.update_single_model_cache,
                 )
+
+                if not result and error_msg and "Rate limited" in error_msg:
+                    consecutive_rate_limits += 1
+                else:
+                    consecutive_rate_limits = 0
+
+                if not result:
+                    current_name = model.get("model_name", file_path or "Unknown")
+                    failures.append({"name": current_name, "error": error_msg or "Unknown error"})
+                    self._logger.warning("Failed to fetch metadata for %s: %s", current_name, error_msg)
+
+                if consecutive_rate_limits >= RATE_LIMIT_ABORT_THRESHOLD:
+                    # The current model was attempted and failed due to rate limiting;
+                    # count it before aborting so the summary is consistent.
+                    processed += 1
+                    handled_count += 1
+                    self._logger.warning(
+                        "Bulk metadata refresh aborted: %d consecutive rate limits detected. "
+                        "Processed %d/%d models.",
+                        consecutive_rate_limits,
+                        processed,
+                        total_to_process,
+                    )
+                    await emit(
+                        "rate_limited",
+                    )
+                    return {
+                        "success": False,
+                        "message": f"Rate limit detected; {total_to_process - processed} models skipped",
+                        "processed": processed,
+                        "updated": success,
+                        "total": total_models,
+                        "failures": failures,
+                        "failure_count": len(failures),
+                        "skipped_count": skipped_count,
+                        "elapsed_seconds": int(time.monotonic() - start_time),
+                    }
+
                 if result:
                     success += 1
                     if original_name != model.get("model_name"):
                         needs_resort = True
                 processed += 1
+                handled_count += 1
                 await emit(
                     "processing",
                     processed=processed,
@@ -134,6 +202,9 @@ class BulkMetadataRefreshUseCase:
                 )
             except Exception as exc:  # pragma: no cover - logging path
                 processed += 1
+                handled_count += 1
+                current_name = model.get("model_name", model.get("file_path", "Unknown"))
+                failures.append({"name": current_name, "error": str(exc)})
                 self._logger.error(
                     "Error fetching CivitAI data for %s: %s",
                     model.get("file_path"),
@@ -150,7 +221,7 @@ class BulkMetadataRefreshUseCase:
             f"{success} of {processed} processed {self._service.model_type}s (total: {total_models})"
         )
 
-        return {"success": True, "message": message, "processed": processed, "updated": success, "total": total_models}
+        return {"success": True, "message": message, "processed": processed, "updated": success, "total": total_models, "failures": failures, "failure_count": len(failures), "skipped_count": skipped_count, "elapsed_seconds": int(time.monotonic() - start_time)}
 
     @staticmethod
     def _is_in_skip_path(folder: str, skip_paths: List[str]) -> bool:

py/utils/civitai_utils.py

@@ -66,6 +66,46 @@ def build_civitai_model_page_url(
     return None
 
 
+_RE_CDN_IMAGE_ID = re.compile(r"/(\d+)\.(?:jpeg|jpg|png|webp|gif)(?:\?|#|$)")
+
+
+def extract_civitai_image_id_from_cdn_url(url: str | None) -> str | None:
+    """Extract the numeric image ID from a Cloudflare CDN image URL.
+
+    CivitAI image CDN URLs follow the pattern::
+
+        https://image.civitai.com/{cf_uuid}/{params}/{image_id}.{ext}
+
+    The image database ID is always the last path segment (minus extension)
+    because ``getEdgeUrl(…, name=id.toString())`` embeds it explicitly
+    in the model-versions REST API response.
+    """
+    if not url:
+        return None
+    match = _RE_CDN_IMAGE_ID.search(url)
+    return match.group(1) if match else None
+
+
+def build_civitai_image_page_url(
+    image_id: str | int | None,
+    *,
+    host: str | None = None,
+) -> str | None:
+    """Build a Civitai image page URL.
+
+    Returns something like ``https://civitai.com/images/12345``.
+    The host is resolved through :func:`normalize_civitai_page_host` and
+    therefore respects the user's ``civitai_host`` setting.
+    """
+    if not image_id:
+        return None
+    normalized_host = normalize_civitai_page_host(host)
+    normalized_id = str(image_id).strip()
+    if not normalized_id:
+        return None
+    return urlunparse(("https", normalized_host, f"/images/{normalized_id}", "", "", ""))
+
+
 def _parse_supported_civitai_page_url(url: str | None):
     if not url:
         return None
@@ -328,8 +368,10 @@ def rewrite_preview_url(
 
 
 __all__ = [
+    "build_civitai_image_page_url",
     "build_license_flags",
     "extract_civitai_image_id",
+    "extract_civitai_image_id_from_cdn_url",
     "extract_civitai_page_host",
     "extract_civitai_model_url_parts",
     "is_supported_civitai_page_host",

py/utils/constants.py

@@ -31,6 +31,8 @@ PREVIEW_EXTENSIONS = [
     ".mp4",
     ".gif",
     ".webm",
+    ".avif",
+    ".jxl",
 ]
 
 # Card preview image width
@@ -41,7 +43,7 @@ EXAMPLE_IMAGE_WIDTH = 832
 
 # Supported media extensions for example downloads
 SUPPORTED_MEDIA_EXTENSIONS = {
-    "images": [".jpg", ".jpeg", ".png", ".webp", ".gif"],
+    "images": [".jpg", ".jpeg", ".png", ".webp", ".gif", ".avif", ".jxl"],
     "videos": [".mp4", ".webm"],
 }
 
@@ -101,8 +103,34 @@ DEFAULT_PRIORITY_TAG_CONFIG = {
 DIFFUSION_MODEL_BASE_MODELS = frozenset(
     [
         "Anima",
-        "ZImageTurbo",
-        "ZImageBase",
+        # Flux series — DiT architecture, loaded via UNETLoader in ComfyUI
+        "Flux.1 D",
+        "Flux.1 S",
+        "Flux.1 Krea",
+        "Flux.1 Kontext",
+        "Flux.2 D",
+        "Flux.2 Klein 9B",
+        "Flux.2 Klein 9B-base",
+        "Flux.2 Klein 4B",
+        "Flux.2 Klein 4B-base",
+        # Non-UNet / DiT image diffusion models
+        "AuraFlow",
+        "Chroma",
+        "HiDream",
+        "Hunyuan 1",
+        "Kolors",
+        "Lumina",
+        "PixArt a",
+        "PixArt E",
+        # Video diffusion models
+        "CogVideoX",
+        "Hunyuan Video",
+        "LTXV",
+        "LTXV2",
+        "LTXV 2.3",
+        "Mochi",
+        "SVD",
+        "Wan Video",
         "Wan Video 1.3B t2v",
         "Wan Video 14B t2v",
         "Wan Video 14B i2v 480p",
@@ -112,9 +140,13 @@ DIFFUSION_MODEL_BASE_MODELS = frozenset(
         "Wan Video 2.2 T2V-A14B",
         "Wan Video 2.5 T2V",
         "Wan Video 2.5 I2V",
-        "CogVideoX",
-        "Mochi",
+        # Other diffusion models
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
         "Qwen",
+        "ZImageBase",
+        "ZImageTurbo",
     ]
 )
 

py/utils/example_images_paths.py

@@ -12,6 +12,18 @@ from ..services.settings_manager import get_settings_manager
 
 _HEX_PATTERN = re.compile(r"[a-fA-F0-9]{64}")
 
+# Filesystem/metadata files that are never created by the example images system
+# and are safe to ignore during validation. The cleanup service only operates on
+# directories, so these files pose no data-loss risk.
+_SAFE_FILENAMES: frozenset[str] = frozenset({
+    ".DS_Store",       # macOS folder metadata
+    "Thumbs.db",       # Windows thumbnail cache
+    "desktop.ini",     # Windows folder customization
+    ".localized",      # macOS folder name localization
+    ".gitkeep",        # Placeholder to keep empty dirs in git
+    ".gitignore",      # Git ignore rules
+})
+
 logger = logging.getLogger(__name__)
 
 
@@ -180,6 +192,22 @@ def is_hash_folder(name: str) -> bool:
     return bool(_HEX_PATTERN.fullmatch(name or ""))
 
 
+def _is_safe_ignorable_entry(item: str, item_path: str) -> bool:
+    """Return True if *item* is a harmless system/hidden file we can skip.
+
+    These files are never created by the example images system and are safe to
+    ignore because the cleanup/delete operations only act on **directories**,
+    never on individual files (other than ``.download_progress.json``).
+    """
+    if item in _SAFE_FILENAMES:
+        return True
+    # Hide Unix hidden files (dotfiles) that are regular files,
+    # since the cleanup system never deletes or moves files.
+    if item.startswith(".") and os.path.isfile(item_path):
+        return True
+    return False
+
+
 def is_valid_example_images_root(folder_path: str) -> bool:
     """Check whether a folder looks like a dedicated example images root."""
 
@@ -190,9 +218,16 @@ def is_valid_example_images_root(folder_path: str) -> bool:
 
     for item in items:
         item_path = os.path.join(folder_path, item)
+
+        # .download_progress.json is an expected metadata file — check before
+        # the generic dotfile rule so it stays explicitly documented.
         if item == ".download_progress.json" and os.path.isfile(item_path):
             continue
 
+        # Skip harmless system/hidden files — cleanup only touches directories
+        if _is_safe_ignorable_entry(item, item_path):
+            continue
+
         if os.path.isdir(item_path):
             if is_hash_folder(item):
                 continue
@@ -211,6 +246,41 @@ def is_valid_example_images_root(folder_path: str) -> bool:
     return True
 
 
+def find_non_compliant_items_in_example_images_root(folder_path: str) -> list[str]:
+    """Return the names of items that prevent *folder_path* from being a valid
+    example images root, or an empty list if the folder is valid.
+
+    This mirrors ``is_valid_example_images_root`` but **returns** the offending
+    names instead of a boolean, so callers can produce actionable error messages.
+    """
+    try:
+        items = os.listdir(folder_path)
+    except OSError as exc:
+        return [f"<cannot list directory: {exc}>"]
+
+    offending: list[str] = []
+
+    for item in items:
+        item_path = os.path.join(folder_path, item)
+
+        # Same skip rules as is_valid_example_images_root
+        if item == ".download_progress.json" and os.path.isfile(item_path):
+            continue
+        if _is_safe_ignorable_entry(item, item_path):
+            continue
+        if os.path.isdir(item_path):
+            if is_hash_folder(item):
+                continue
+            if item == "_deleted":
+                continue
+            if _library_folder_has_only_hash_dirs(item_path):
+                continue
+
+        offending.append(item)
+
+    return offending
+
+
 def _library_folder_has_only_hash_dirs(path: str) -> bool:
     """Return True when a library subfolder only contains hash folders or metadata files."""
 

py/utils/example_images_processor.py

@@ -62,6 +62,10 @@ class ExampleImagesProcessor:
                 return '.gif'
             elif content.startswith(b'RIFF') and b'WEBP' in content[:12]:
                 return '.webp'
+            elif len(content) >= 12 and content[4:8] == b'ftyp' and b'avif' in content[8:24]:
+                return '.avif'
+            elif content.startswith(b'\x00\x00\x00\x0cJXL \x0d\x0a\x87\x0a'):
+                return '.jxl'
             elif content.startswith(b'\x00\x00\x00\x18ftypmp4') or content.startswith(b'\x00\x00\x00\x20ftypmp4'):
                 return '.mp4'
             elif content.startswith(b'\x1A\x45\xDF\xA3'):
@@ -75,6 +79,8 @@ class ExampleImagesProcessor:
                 'image/png': '.png',
                 'image/gif': '.gif',
                 'image/webp': '.webp',
+                'image/avif': '.avif',
+                'image/jxl': '.jxl',
                 'video/mp4': '.mp4',
                 'video/webm': '.webm',
                 'video/quicktime': '.mov'

py/utils/exif_utils.py

@@ -1,17 +1,125 @@
 import json
 import logging
 import os
+import struct
 from io import BytesIO
 from typing import Any, Optional
 
 import piexif
 from PIL import Image, PngImagePlugin
 
+try:
+    import brotli
+    _BROTLI_AVAILABLE = True
+except ImportError:
+    brotli = None
+    _BROTLI_AVAILABLE = False
+
 logger = logging.getLogger(__name__)
 
 class ExifUtils:
     """Utility functions for working with EXIF data in images"""
 
+    @staticmethod
+    def _parse_isobmff_boxes(data: bytes, offset: int = 0) -> list[dict]:
+        boxes = []
+        while offset + 8 <= len(data):
+            size = struct.unpack('>I', data[offset:offset + 4])[0]
+            box_type = data[offset + 4:offset + 8]
+            if size == 0:
+                break
+            if size < 8 or offset + size > len(data):
+                break
+            box_data = data[offset + 8:offset + size]
+            boxes.append({'type': box_type, 'data': box_data, 'size': size})
+            offset += size
+        return boxes
+
+    @staticmethod
+    def _is_jxl_container(data: bytes) -> bool:
+        if len(data) < 32:
+            return False
+        return (
+            struct.unpack('>I', data[:4])[0] == 12
+            and data[4:8] == b'JXL '
+            and data[8:12] == bytes([0x0d, 0x0a, 0x87, 0x0a])
+            and struct.unpack('>I', data[12:16])[0] >= 16
+            and data[16:20] == b'ftyp'
+            and data[20:24] == b'jxl '
+        )
+
+    @staticmethod
+    def _is_avif_container(data: bytes) -> bool:
+        if len(data) < 16:
+            return False
+        for box in ExifUtils._parse_isobmff_boxes(data):
+            if box['type'] == b'ftyp' and b'avif' in box['data']:
+                return True
+        return False
+
+    # Max decompressed size for brotli metadata (2 MB)
+    _BROTLI_MAX_DECOMPRESSED = 2 * 1024 * 1024
+
+    @staticmethod
+    def _extract_isobmff_brotli(image_path: str) -> Optional[dict]:
+        try:
+            with open(image_path, 'rb') as f:
+                data = f.read()
+        except Exception:
+            return None
+
+        if ExifUtils._is_jxl_container(data):
+            boxes = ExifUtils._parse_isobmff_boxes(data, offset=12)
+        elif ExifUtils._is_avif_container(data):
+            boxes = ExifUtils._parse_isobmff_boxes(data)
+        else:
+            return None
+
+        brob = None
+        for box in boxes:
+            if box['type'] == b'brob':
+                brob = box
+                break
+        if brob is None:
+            return None
+
+        payload = brob['data']
+        if payload[:4] != b'comf':
+            return None
+        compressed = payload[4:]
+
+        if _BROTLI_AVAILABLE:
+            try:
+                decompressed = brotli.decompress(compressed)
+                if len(decompressed) > ExifUtils._BROTLI_MAX_DECOMPRESSED:
+                    logger.warning(
+                        "Brotli metadata too large (%d bytes, max %d), ignoring",
+                        len(decompressed),
+                        ExifUtils._BROTLI_MAX_DECOMPRESSED,
+                    )
+                    decompressed = None
+            except Exception:
+                decompressed = None
+        else:
+            decompressed = None
+
+        raw = decompressed if decompressed is not None else compressed
+        try:
+            meta = json.loads(raw.decode('utf-8'))
+        except Exception:
+            return None
+
+        result = {"parameters": None, "prompt": None, "workflow": None, "comment": None}
+        if isinstance(meta.get("prompt"), (dict, list)):
+            result["prompt"] = json.dumps(meta["prompt"])
+        elif isinstance(meta.get("prompt"), str):
+            result["prompt"] = meta["prompt"]
+        if isinstance(meta.get("workflow"), (dict, list)):
+            result["workflow"] = json.dumps(meta["workflow"])
+        elif isinstance(meta.get("workflow"), str):
+            result["workflow"] = meta["workflow"]
+        return result
+
     @staticmethod
     def _decode_user_comment(user_comment: Any) -> Optional[str]:
         if user_comment is None:
@@ -43,6 +151,12 @@ class ExifUtils:
             "comment": None,
         }
 
+        ext = os.path.splitext(image_path)[1].lower()
+        if ext in ('.avif', '.jxl'):
+            brotli_meta = ExifUtils._extract_isobmff_brotli(image_path)
+            if brotli_meta:
+                return brotli_meta
+
         with Image.open(image_path) as img:
             info = getattr(img, "info", {}) or {}
 
@@ -149,7 +263,6 @@ class ExifUtils:
             Optional[str]: Extracted metadata or None if not found
         """
         try:
-            # Skip for video files
             if image_path:
                 ext = os.path.splitext(image_path)[1].lower()
                 if ext in ['.mp4', '.webm']:
@@ -177,10 +290,9 @@ class ExifUtils:
             str: Path to the updated image
         """
         try:
-            # Skip for video files
             if image_path:
                 ext = os.path.splitext(image_path)[1].lower()
-                if ext in ['.mp4', '.webm']:
+                if ext in ['.mp4', '.webm', '.avif', '.jxl']:
                     return image_path
 
             metadata_fields = ExifUtils._load_structured_metadata(image_path)
@@ -212,10 +324,9 @@ class ExifUtils:
     def append_recipe_metadata(image_path, recipe_data) -> str:
         """Append recipe metadata to an image's EXIF data"""
         try:
-            # Skip for video files
             if image_path:
                 ext = os.path.splitext(image_path)[1].lower()
-                if ext in ['.mp4', '.webm']:
+                if ext in ['.mp4', '.webm', '.avif', '.jxl']:
                     return image_path
 
             # First, extract existing metadata
@@ -327,10 +438,9 @@ class ExifUtils:
             Tuple of (optimized_image_data, extension)
         """
         try:
-            # Skip for video files early if it's a file path
             if isinstance(image_data, str) and os.path.exists(image_data):
                 ext = os.path.splitext(image_data)[1].lower()
-                if ext in ['.mp4', '.webm']:
+                if ext in ['.mp4', '.webm', '.avif', '.jxl']:
                     try:
                         with open(image_data, 'rb') as f:
                             return f.read(), ext

py/utils/file_utils.py

@@ -1,7 +1,10 @@
 
 import hashlib
+import json
 import logging
 import os
+import struct
+from typing import Any
 
 from .constants import (
     CARD_PREVIEW_WIDTH,
@@ -31,14 +34,101 @@ def _get_hash_chunk_size_bytes() -> int:
 
 
 async def calculate_sha256(file_path: str) -> str:
-    """Calculate SHA256 hash of a file"""
+    """Calculate SHA256 hash of a file (full file content).
+
+    Uses ``posix_fadvise`` with ``POSIX_FADV_DONTNEED`` to avoid polluting the OS page
+    cache — critical on WSL where cached file pages live inside the VM and are not
+    accounted for in guest ``used`` memory, causing VmmemWSL to balloon.
+
+    On Windows/macOS where ``posix_fadvise`` is not available the hint is silently
+    skipped.
+    """
     sha256_hash = hashlib.sha256()
     chunk_size = _get_hash_chunk_size_bytes()
     with open(file_path, "rb") as f:
+        fd = f.fileno()
         for byte_block in iter(lambda: f.read(chunk_size), b""):
             sha256_hash.update(byte_block)
+        # Evict pages after reading so the data doesn't linger in the kernel page
+        # cache — on WSL this otherwise appears as unreclaimable VmmemWSL growth.
+        # Guard against platforms (Windows, macOS) that lack posix_fadvise.
+        if hasattr(os, "posix_fadvise") and hasattr(os, "POSIX_FADV_DONTNEED"):
+            os.posix_fadvise(fd, 0, 0, os.POSIX_FADV_DONTNEED)
     return sha256_hash.hexdigest()
 
+
+def calculate_autov2(file_path: str) -> str:
+    """Calculate CivitAI AutoV2 hash.
+
+    AutoV2 is the first 10 characters of the full file SHA256.
+    Used by CivitAI as a shortened file identifier.
+
+    Reference: https://developer.civitai.com/site/reference/model-versions
+    """
+    full_hash = hashlib.sha256()
+    chunk_size = _get_hash_chunk_size_bytes()
+    with open(file_path, "rb") as f:
+        for byte_block in iter(lambda: f.read(chunk_size), b""):
+            full_hash.update(byte_block)
+    return full_hash.hexdigest()[:10]
+
+
+def read_safetensors_metadata(file_path: str) -> dict[str, Any]:
+    """Read the ``__metadata__`` dict from a safetensors file header.
+
+    Safetensors file format:
+      - 8 bytes: header length (little-endian 64-bit)
+      - N bytes: UTF-8 JSON header
+      - The header JSON contains a ``__metadata__`` key holding arbitrary metadata.
+
+    Returns an empty dict if the file is not a valid safetensors file or has no
+    metadata.
+    """
+    try:
+        with open(file_path, "rb") as f:
+            header_len_bytes = f.read(8)
+            if len(header_len_bytes) < 8:
+                return {}
+            header_len = struct.unpack("<Q", header_len_bytes)[0]
+            header_bytes = f.read(header_len)
+            if len(header_bytes) < header_len:
+                return {}
+            header = json.loads(header_bytes.decode("utf-8"))
+            return header.get("__metadata__", {})
+    except (OSError, json.JSONDecodeError, UnicodeDecodeError, struct.error, MemoryError, Exception):
+        return {}
+
+
+def calculate_autov3(file_path: str) -> str | None:
+    """Calculate CivitAI AutoV3 hash from a safetensors file.
+
+    AutoV3 is extracted from the safetensors file's embedded metadata, not
+    computed from the file bytes directly. The orchestrator reads the
+    ``sshs_model_hash`` (kohya-ss format) or ``modelspec.hash_sha256`` field
+    from the safetensors header and stores the first 12 characters.
+
+    The embedded hash itself is the SHA256 of the file after skipping the
+    8-byte header length + JSON header (a.k.a. the addnet hash / tensor-only
+    hash).
+
+    Reference:
+      - CivitAI DB trigger: ``SUBSTRING(NEW.hash FROM 1 FOR 12)``
+      - https://developer.civitai.com/site/reference/model-versions
+
+    Returns ``None`` when no AutoV3 hash can be determined (e.g. the file is
+    not safetensors, or the metadata doesn't contain a recognised hash field).
+    """
+    metadata = read_safetensors_metadata(file_path)
+    if not metadata:
+        return None
+
+    embedded_hash = metadata.get("sshs_model_hash") or metadata.get("modelspec.hash_sha256")
+    if embedded_hash and isinstance(embedded_hash, str) and len(embedded_hash) >= 12:
+        return embedded_hash[:12]
+
+    return None
+
+
 def find_preview_file(base_name: str, dir_path: str) -> str:
     """Find preview file for given base name in directory.
 

py/utils/session_logging.py

@@ -64,6 +64,27 @@ def _build_log_file_path(settings_file: str | None, started_at: datetime) -> str
     return os.path.join(log_dir, f"standalone-session-{timestamp}.log")
 
 
+_KEEP_LOG_COUNT = 3
+
+
+def _prune_old_logs(log_dir: str) -> None:
+    """Remove older session log files, keeping only the ``_KEEP_LOG_COUNT`` newest."""
+    try:
+        files = [
+            os.path.join(log_dir, name)
+            for name in os.listdir(log_dir)
+            if name.startswith("standalone-session-") and name.endswith(".log")
+        ]
+    except OSError:
+        return
+    files.sort(key=os.path.getmtime, reverse=True)
+    for path in files[_KEEP_LOG_COUNT:]:
+        try:
+            os.remove(path)
+        except OSError:
+            pass
+
+
 def setup_standalone_session_logging(settings_file: str | None) -> StandaloneSessionLogState:
     global _session_state
 
@@ -90,6 +111,7 @@ def setup_standalone_session_logging(settings_file: str | None) -> StandaloneSes
             file_handler.set_name(_FILE_HANDLER_NAME)
             file_handler.setFormatter(formatter)
             root_logger.addHandler(file_handler)
+            _prune_old_logs(os.path.dirname(log_file_path))
 
         _session_state = StandaloneSessionLogState(
             started_at=started_at,

py/utils/usage_stats.py

@@ -1,4 +1,5 @@
 import os
+import re
 import json
 import time
 import asyncio
@@ -9,6 +10,7 @@ from typing import Dict, Set
 
 from ..config import config
 from ..services.service_registry import ServiceRegistry
+from ..utils.settings_paths import get_settings_dir
 
 # Check if running in standalone mode
 standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
@@ -16,14 +18,18 @@ standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.en
 # Define constants locally to avoid dependency on conditional imports
 MODELS = "models"
 LORAS = "loras"
+EMBEDDINGS = "embeddings"
+PROMPTS = "prompts"
 
 if not standalone_mode:
     from ..metadata_collector.metadata_registry import MetadataRegistry
     # Import constants from metadata_collector to ensure consistency, but we have fallbacks defined above
     try:
-        from ..metadata_collector.constants import MODELS as _MODELS, LORAS as _LORAS
+        from ..metadata_collector.constants import MODELS as _MODELS, LORAS as _LORAS, EMBEDDINGS as _EMBEDDINGS, PROMPTS as _PROMPTS
         MODELS = _MODELS
         LORAS = _LORAS
+        EMBEDDINGS = _EMBEDDINGS
+        PROMPTS = _PROMPTS
     except ImportError:
         pass  # Use the local definitions
 
@@ -65,6 +71,7 @@ class UsageStats:
         self.stats = {
             "checkpoints": {},  # sha256 -> { total: count, history: { date: count } }
             "loras": {},        # sha256 -> { total: count, history: { date: count } }
+            "embeddings": {},   # sha256 -> { total: count, history: { date: count } }
             "total_executions": 0,
             "last_save_time": 0
         }
@@ -77,6 +84,7 @@ class UsageStats:
         
         # Load existing stats if available
         self._stats_file_path = self._get_stats_file_path()
+        self._migrate_from_old_location()
         self._load_stats()
         
         # Save interval in seconds
@@ -89,14 +97,38 @@ class UsageStats:
         logger.debug("Usage statistics tracker initialized")
     
     def _get_stats_file_path(self) -> str:
-        """Get the path to the stats JSON file"""
+        """Get the path to the stats JSON file in the settings directory."""
+        settings_dir = get_settings_dir(create=True)
+        return os.path.join(settings_dir, "stats", self.STATS_FILENAME)
+
+    @staticmethod
+    def _get_old_stats_file_path() -> str:
+        """Get the legacy stats file path in the first lora root directory."""
         if not config.loras_roots or len(config.loras_roots) == 0:
-            # If no lora roots are available, we can't save stats
-            # This will be handled by the caller
-            raise RuntimeError("No LoRA root directories configured. Cannot initialize usage statistics.")
-        
-        # Use the first lora root
-        return os.path.join(config.loras_roots[0], self.STATS_FILENAME)
+            return ""
+        return os.path.join(config.loras_roots[0], UsageStats.STATS_FILENAME)
+
+    def _migrate_from_old_location(self) -> None:
+        """Migrate stats file from old location (first lora root) to new location (settings_dir/stats/)."""
+        new_path = self._stats_file_path
+        if os.path.exists(new_path):
+            return
+
+        old_path = self._get_old_stats_file_path()
+        if not old_path or not os.path.exists(old_path):
+            return
+
+        try:
+            os.makedirs(os.path.dirname(new_path), exist_ok=True)
+            shutil.copy2(old_path, new_path)
+            logger.info("Migrated usage stats from %s to %s", old_path, new_path)
+            try:
+                os.remove(old_path)
+                logger.info("Cleaned up old stats file: %s", old_path)
+            except Exception as e:
+                logger.warning("Failed to remove old stats file %s: %s", old_path, e)
+        except Exception as e:
+            logger.error("Failed to migrate usage stats from %s to %s: %s", old_path, new_path, e)
     
     def _backup_old_stats(self):
         """Backup the old stats file before conversion"""
@@ -115,6 +147,7 @@ class UsageStats:
         new_stats = {
             "checkpoints": {},
             "loras": {},
+            "embeddings": {},
             "total_executions": old_stats.get("total_executions", 0),
             "last_save_time": old_stats.get("last_save_time", time.time())
         }
@@ -142,21 +175,27 @@ class UsageStats:
                     }
                 }
         
+        # Convert embedding stats (if present in old format)
+        if "embeddings" in old_stats and isinstance(old_stats["embeddings"], dict):
+            for hash_id, count in old_stats["embeddings"].items():
+                new_stats["embeddings"][hash_id] = {
+                    "total": count,
+                    "history": {
+                        today: count
+                    }
+                }
+        
         logger.info("Successfully converted stats from old format to new format with history")
         return new_stats
     
     def _is_old_format(self, stats):
         """Check if the stats are in the old format (direct count values)"""
         # Check if any lora or checkpoint entry is a direct number instead of an object
-        if "loras" in stats and isinstance(stats["loras"], dict):
-            for hash_id, data in stats["loras"].items():
-                if isinstance(data, (int, float)):
-                    return True
-                
-        if "checkpoints" in stats and isinstance(stats["checkpoints"], dict):
-            for hash_id, data in stats["checkpoints"].items():
-                if isinstance(data, (int, float)):
-                    return True
+        for category in ("loras", "checkpoints", "embeddings"):
+            if category in stats and isinstance(stats[category], dict):
+                for hash_id, data in stats[category].items():
+                    if isinstance(data, (int, float)):
+                        return True
         
         return False
     
@@ -182,6 +221,9 @@ class UsageStats:
                         if "loras" in loaded_stats and isinstance(loaded_stats["loras"], dict):
                             self.stats["loras"] = loaded_stats["loras"]
                         
+                        if "embeddings" in loaded_stats and isinstance(loaded_stats["embeddings"], dict):
+                            self.stats["embeddings"] = loaded_stats["embeddings"]
+                        
                         if "total_executions" in loaded_stats:
                             self.stats["total_executions"] = loaded_stats["total_executions"]
                         
@@ -304,6 +346,10 @@ class UsageStats:
         if LORAS in metadata and isinstance(metadata[LORAS], dict):
             await self._process_loras(metadata[LORAS], today)
 
+        # Process embeddings — parse prompt text for embedding:name references
+        if PROMPTS in metadata and isinstance(metadata[PROMPTS], dict):
+            await self._process_embeddings(metadata[PROMPTS], today)
+
     def _increment_usage_counter(self, category: str, stat_key: str, today_date: str) -> None:
         """Increment usage counters for a resolved stats key."""
         if stat_key not in self.stats[category]:
@@ -510,6 +556,55 @@ class UsageStats:
         except Exception as e:
             logger.error(f"Error processing LoRA usage: {e}", exc_info=True)
     
+    @staticmethod
+    def _extract_embedding_names(prompt_text: str) -> set:
+        """Parse embedding:name references from prompt text.
+
+        ComfyUI's SDTokenizer resolves ``embedding:<name>`` during tokenization
+        (see ``sd1_clip.py _try_get_embedding``).  This mirrors the same pattern
+        to extract embedding file names from the captured prompt strings.
+        """
+        if not prompt_text:
+            return set()
+        # Matches ``embedding:name`` where name is alphanumeric plus _ . - /
+        names = re.findall(r"embedding:([a-zA-Z0-9_.\-/]+)", prompt_text)
+        return set(names)
+
+    async def _process_embeddings(self, prompts_data, today_date):
+        """Extract embedding usage from prompt texts and record it.
+
+        Iterates every prompt node's text field captured by the metadata
+        collector, extracts ``embedding:<name>`` references, resolves each
+        name to its SHA256 hash via the embedding scanner, and increments
+        usage counters.
+        """
+        try:
+            embedding_scanner = await ServiceRegistry.get_embedding_scanner()
+            if not embedding_scanner:
+                logger.warning("Embedding scanner not available for usage tracking")
+                return
+
+            seen_names = set()
+            for _node_id, prompt_data in prompts_data.items():
+                if not isinstance(prompt_data, dict):
+                    continue
+                for text_field in ("text", "positive_text", "negative_text"):
+                    text = prompt_data.get(text_field)
+                    if isinstance(text, str):
+                        seen_names.update(self._extract_embedding_names(text))
+
+            for emb_name in seen_names:
+                emb_hash = embedding_scanner.get_hash_by_filename(emb_name)
+                if emb_hash:
+                    self._increment_usage_counter("embeddings", emb_hash, today_date)
+                else:
+                    logger.debug(
+                        "No hash found for embedding '%s', skipping usage tracking",
+                        emb_name,
+                    )
+        except Exception as e:
+            logger.error("Error processing embedding usage: %s", e, exc_info=True)
+
     async def get_stats(self):
         """Get current usage statistics"""
         return self.stats
@@ -522,6 +617,9 @@ class UsageStats:
         elif model_type == "lora":
             if sha256 in self.stats["loras"]:
                 return self.stats["loras"][sha256]["total"]
+        elif model_type == "embedding":
+            if sha256 in self.stats["embeddings"]:
+                return self.stats["embeddings"][sha256]["total"]
         return 0
     
     async def process_execution(self, prompt_id):

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.9"
+version = "1.1.4"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

requirements.txt

@@ -1,4 +1,5 @@
 aiohttp
+aiohttp-socks
 jinja2
 safetensors
 piexif
@@ -12,3 +13,5 @@ aiosqlite
 beautifulsoup4
 platformdirs
 pyyaml
+# brotli — ISOBMFF (AVIF/JXL) metadata decompression
+brotli>=1.2.0

scripts/migrate_legacy_metadata.py

@@ -34,6 +34,8 @@ import sys
 from pathlib import Path
 from typing import Any
 
+from platformdirs import user_config_dir
+
 logging.basicConfig(
     level=logging.INFO,
     format="%(asctime)s - %(levelname)s - %(message)s",
@@ -53,10 +55,7 @@ def resolve_settings_path() -> Path:
         if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
             return portable
 
-    config_home = os.environ.get("XDG_CONFIG_HOME")
-    if config_home:
-        return Path(config_home).expanduser() / APP_NAME / "settings.json"
-    return Path.home() / ".config" / APP_NAME / "settings.json"
+    return Path(user_config_dir(APP_NAME, appauthor=False)) / "settings.json"
 
 
 def load_json(path: Path) -> dict[str, Any]:

scripts/restore_suffixed_filenames.py

@@ -0,0 +1,403 @@
+#!/usr/bin/env python3
+"""
+Restore original filenames by removing leftover 4-char hash suffixes.
+
+When LoRA Manager's old duplicate filename resolver ran, it appended
+``-{first4ofSHA256}`` to duplicate filenames, e.g.::
+
+    my_lora.safetensors  →  my_lora-a3f7.safetensors
+
+With full-path LoRA syntax now available (``<lora:subfolder/name:1.0>``),
+these suffixes are unnecessary.  This script detects such files and, with
+your confirmation, restores their original names.
+
+The same suffix pattern is also used by the download conflict handler
+(``{name}-{hash}.{ext}``).  To avoid false positives, this script skips
+any file whose original name already exists in the same directory — those
+were likely added by a download conflict, not the old resolver.
+
+Usage::
+
+    # Detect only (dry-run, default)
+    python scripts/restore_suffixed_filenames.py
+
+    # Detect + restore (with confirmation prompt)
+    python scripts/restore_suffixed_filenames.py --apply
+
+After restoring filenames, run **Rebuild Cache** in the LoRA Manager
+Doctor panel to refresh the model cache.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import re
+import sys
+from pathlib import Path
+from typing import Any
+
+from platformdirs import user_config_dir
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(message)s",
+)
+logger = logging.getLogger(__name__)
+
+APP_NAME = "ComfyUI-LoRA-Manager"
+MODEL_EXTENSIONS = {".safetensors", ".ckpt", ".pt", ".pth", ".bin"}
+PREVIEW_EXTENSIONS = {
+    ".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp",
+    ".mp4", ".webm", ".mov",
+}
+
+# Matches filenames like "my_lora-a3f7.safetensors"
+# Groups: (base_name, 4-char-hex, extension)
+_SUFFIX_RE = re.compile(r"^(.+)-([0-9a-f]{4})(\.[^.]+)$")
+
+
+# ── helpers (copied from migrate_legacy_metadata.py for consistency) ──────────
+
+
+def resolve_settings_path() -> Path:
+    repo_root = Path(__file__).parent.parent.resolve()
+    portable = repo_root / "settings.json"
+    if portable.exists():
+        payload = _load_json(portable)
+        if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
+            return portable
+
+    return Path(user_config_dir(APP_NAME, appauthor=False)) / "settings.json"
+
+
+def _load_json(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("r", encoding="utf-8") as f:
+            return json.load(f)
+    except (FileNotFoundError, json.JSONDecodeError, OSError):
+        return {}
+
+
+def _expand_path(value: str) -> str:
+    return str(Path(value).expanduser().resolve(strict=False))
+
+
+def _normalize_path_list(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [_expand_path(value)] if value else []
+    if isinstance(value, list):
+        return [_expand_path(item) for item in value if isinstance(item, str) and item]
+    return []
+
+
+def _dedupe(values: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for value in values:
+        if value not in seen:
+            result.append(value)
+            seen.add(value)
+    return result
+
+
+def get_model_roots(settings: dict[str, Any]) -> dict[str, list[str]]:
+    """Extract model folder roots from LoRA Manager settings.
+
+    Returns ``{model_type: [path, ...]}`` where *model_type* is one of
+    ``loras``, ``checkpoints``, ``embeddings``, ``unet``, etc.
+
+    Both primary (``folder_paths``) and extra (``extra_folder_paths``)
+    paths are included.  Extra paths can be configured via the UI at
+    Settings → Model Libraries → Extra Folder Paths.
+    """
+    roots: dict[str, list[str]] = {}
+    active_library = settings.get("active_library") or "default"
+    sources = [settings]
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict):
+        sources.insert(0, library)
+    for source in sources:
+        # Primary folder paths.
+        folder_paths = source.get("folder_paths")
+        if isinstance(folder_paths, dict):
+            for key, value in folder_paths.items():
+                roots.setdefault(key, []).extend(_normalize_path_list(value))
+        # Extra folder paths (Settings → Model Libraries → Extra Folder Paths).
+        extra_folder_paths = source.get("extra_folder_paths")
+        if isinstance(extra_folder_paths, dict):
+            for key, value in extra_folder_paths.items():
+                roots.setdefault(key, []).extend(_normalize_path_list(value))
+    for default_key, folder_key in (
+        ("default_lora_root", "loras"),
+        ("default_checkpoint_root", "checkpoints"),
+        ("default_unet_root", "unet"),
+        ("default_embedding_root", "embeddings"),
+    ):
+        value = settings.get(default_key)
+        if isinstance(value, str) and value:
+            roots.setdefault(folder_key, []).append(_expand_path(value))
+    return {key: _dedupe(values) for key, values in roots.items()}
+
+
+def find_model_files(directory: Path) -> list[Path]:
+    """Recursively find all model files in *directory*."""
+    files: list[Path] = []
+    for ext in MODEL_EXTENSIONS:
+        files.extend(directory.rglob(f"*{ext}"))
+    return files
+
+
+# ── core detection logic ──────────────────────────────────────────────────────
+
+
+def check_file(path: Path) -> tuple[str, str, str] | None:
+    """If *path* matches the suffix pattern, return ``(base_name, hex, ext)``.
+
+    Returns ``None`` when:
+    * The filename does not match the pattern, or
+    * The original name (without the suffix) already exists in the same
+      directory (likely a download-conflict rename, not a doctor rename).
+    """
+    match = _SUFFIX_RE.match(path.name)
+    if not match:
+        return None
+
+    base_name = match.group(1)
+    hex_part = match.group(2)
+    extension = match.group(3)
+    orig_name = base_name + extension
+    orig_path = path.with_name(orig_name)
+
+    # Safety: skip if the original name already exists.
+    if orig_path.exists():
+        return None
+
+    return base_name, hex_part, extension
+
+
+def scan_roots(
+    roots: dict[str, list[str]],
+) -> dict[str, list[tuple[Path, str, str, str]]]:
+    """Scan all model roots and return detected files grouped by model type.
+
+    Returns ``{model_type: [(full_path, base_name, hex, ext), ...]}``.
+    """
+    results: dict[str, list[tuple[Path, str, str, str]]] = {}
+
+    for model_type, root_list in roots.items():
+        type_results: list[tuple[Path, str, str, str]] = []
+        for root in root_list:
+            root_path = Path(root)
+            if not root_path.is_dir():
+                continue
+            for model_file in find_model_files(root_path):
+                match = check_file(model_file)
+                if match:
+                    type_results.append((model_file, *match))
+        if type_results:
+            results[model_type] = type_results
+
+    return results
+
+
+def rename_file(
+    path: Path, base_name: str, extension: str, dry_run: bool
+) -> bool:
+    """Rename *path* to ``{base_name}{extension}``.
+
+    Also renames sidecar files (``.metadata.json``, ``.civitai.info``) and
+    preview images.  Returns ``True`` on success.
+    """
+    new_path = path.with_name(base_name + extension)
+    old_stem = path.with_suffix("")  # /dir/base_name-hex  (no ext)
+    new_stem = new_path.with_suffix("")  # /dir/base_name  (no ext)
+
+    if dry_run:
+        logger.info("  would rename:  %s", path.name)
+        logger.info("             ->  %s", new_path.name)
+        return True
+
+    try:
+        os.rename(path, new_path)
+    except OSError as exc:
+        logger.error("  FAILED to rename %s: %s", path.name, exc)
+        return False
+
+    # Rename sidecar metadata files.
+    for suffix in (".metadata.json", ".civitai.info"):
+        old_sidecar = old_stem.with_name(old_stem.name + suffix)
+        new_sidecar = new_stem.with_name(new_stem.name + suffix)
+        if old_sidecar.exists():
+            try:
+                os.rename(old_sidecar, new_sidecar)
+            except OSError as exc:
+                logger.warning("  could not rename sidecar %s: %s", old_sidecar.name, exc)
+
+    # Rename preview images.
+    for preview_ext in PREVIEW_EXTENSIONS:
+        old_preview = old_stem.with_name(old_stem.name + preview_ext)
+        new_preview = new_stem.with_name(new_stem.name + preview_ext)
+        if old_preview.exists():
+            try:
+                os.rename(old_preview, new_preview)
+            except OSError as exc:
+                logger.warning("  could not rename preview %s: %s", old_preview.name, exc)
+
+    logger.info("  renamed: %s  ->  %s", path.name, new_path.name)
+    return True
+
+
+# ── report helpers ────────────────────────────────────────────────────────────
+
+
+def print_report(results: dict[str, list[tuple[Path, str, str, str]]]) -> int:
+    """Print a human-readable report of detected files.  Returns total count."""
+    if not results:
+        logger.info("No leftover suffixed filenames detected.")
+        return 0
+
+    total = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        total += len(entries)
+        label = model_type.capitalize()
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  %s  (%d file(s))", label, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            logger.info("  %s  →  %s%s", path.name, base_name, ext)
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Total: %d file(s) with leftover suffixes.", total)
+    logger.info("=" * 50)
+    return total
+
+
+def prompt_user(count: int) -> bool:
+    """Ask the user whether to proceed with the rename."""
+    try:
+        answer = input(
+            f"\nRestore {count} file(s) to their original names? [y/N] "
+        ).strip().lower()
+    except (EOFError, KeyboardInterrupt):
+        print()
+        return False
+    return answer in ("y", "yes")
+
+
+# ── main ──────────────────────────────────────────────────────────────────────
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Detect and restore model filenames that have leftover "
+            "4-character hash suffixes from the old conflict resolver."
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=(
+            "Examples:\n"
+            "  python scripts/restore_suffixed_filenames.py\n"
+            "  python scripts/restore_suffixed_filenames.py --apply\n"
+            "  python scripts/restore_suffixed_filenames.py --apply --yes\n"
+        ),
+    )
+    parser.add_argument(
+        "--apply",
+        action="store_true",
+        help="Actually rename files (with confirmation prompt unless --yes is given)",
+    )
+    parser.add_argument(
+        "--yes", "-y",
+        action="store_true",
+        help="Skip confirmation prompt (implies --apply)",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Detect only — show what would be renamed without making changes",
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        action="store_true",
+        help="Enable debug-level logging",
+    )
+    args = parser.parse_args()
+
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+
+    # Resolve settings.
+    settings_path = resolve_settings_path()
+    logger.info("Settings: %s", settings_path)
+    settings = _load_json(settings_path)
+    if not settings:
+        logger.error("Could not load settings.json.  Is LoRA Manager configured?")
+        return 1
+
+    roots = get_model_roots(settings)
+    if not roots:
+        logger.error("No model folders found in settings.")
+        return 1
+
+    # Log which roots are being scanned.
+    for model_type, root_list in roots.items():
+        for root in root_list:
+            logger.info("Scanning %s: %s", model_type, root)
+
+    # Detect.
+    results = scan_roots(roots)
+    total = print_report(results)
+
+    if total == 0:
+        return 0
+
+    # Determine mode.
+    dry_run = not args.apply and not args.yes
+
+    if dry_run:
+        logger.info("\n[Dry-run mode — no files modified]")
+        logger.info("Run with --apply to restore filenames.")
+        return 0
+
+    # Confirm unless --yes.
+    if not args.yes:
+        if not prompt_user(total):
+            logger.info("Aborted.")
+            return 0
+
+    # Rename.
+    logger.info("")
+    success = 0
+    fail = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  Restoring %s  (%d file(s))", model_type, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            ok = rename_file(path, base_name, ext, dry_run=False)
+            if ok:
+                success += 1
+            else:
+                fail += 1
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Done: %d restored, %d failed.", success, fail)
+    logger.info("=" * 50)
+    logger.info("")
+    logger.info("  ⚠  Please run Rebuild Cache in the LoRA Manager")
+    logger.info("     Doctor panel to refresh the model cache.")
+
+    return 0 if fail == 0 else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

standalone.py

@@ -2,6 +2,7 @@ import os
 import sys
 import json
 from py.middleware.cache_middleware import cache_control
+from py.middleware.error_middleware import api_json_error
 from py.utils.settings_paths import ensure_settings_file
 
 # Set environment variable to indicate standalone mode
@@ -157,7 +158,7 @@ class StandaloneServer:
     def __init__(self):
         self.app = web.Application(
             logger=logger,
-            middlewares=[cache_control],
+            middlewares=[api_json_error, cache_control],
             client_max_size=256 * 1024 * 1024,
             handler_args={
                 "max_field_size": HEADER_SIZE_LIMIT,

static/css/base.css

@@ -1,21 +1,20 @@
+@import 'tokens/index.css';
+
 html,
 body {
     margin: 0;
     padding: 0;
     height: 100%;
     overflow: hidden;
-    /* Disable default scrolling */
 }
 
-/* 针对Firefox */
 * {
     scrollbar-width: thin;
-    scrollbar-color: var(--border-color) transparent;
+    scrollbar-color: var(--border-base) transparent;
 }
 
-/* 针对Webkit browsers (Chrome, Safari等) */
 ::-webkit-scrollbar {
-    width: 8px;
+    width: var(--scrollbar-width, 8px);
 }
 
 ::-webkit-scrollbar-track {
@@ -24,116 +23,128 @@ body {
 }
 
 ::-webkit-scrollbar-thumb {
-    background-color: var(--border-color);
-    border-radius: 4px;
+    background-color: var(--border-base);
+    border-radius: var(--radius-xs);
 }
 
 :root {
-    --bg-color: #ffffff;
-    --text-color: #333333;
-    --text-muted: #6c757d;
-    --card-bg: #ffffff;
-    --border-color: #e0e0e0;
     --header-height: 48px;
-
-    /* Color Components */
-    --lora-accent-l: 68%;
-    --lora-accent-c: 0.28;
-    --lora-accent-h: 256;
-    --lora-warning-l: 75%;
-    --lora-warning-c: 0.25;
-    --lora-warning-h: 80;
-    --lora-success-l: 70%;
-    --lora-success-c: 0.2;
-    --lora-success-h: 140;
-
-    /* Composed Colors */
-    --lora-accent: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
-    --lora-surface: oklch(97% 0 0 / 0.95);
-    --lora-border: oklch(72% 0.03 256 / 0.45);
-    --lora-text: oklch(95% 0.02 256);
-    --lora-error: oklch(75% 0.32 29);
-    --lora-error-bg: color-mix(in oklch, var(--lora-error) 20%, transparent);
-    --lora-error-border: color-mix(in oklch, var(--lora-error) 50%, transparent);
-    --lora-warning: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
-    --lora-success: oklch(var(--lora-success-l) var(--lora-success-c) var(--lora-success-h));
-    --badge-update-bg: oklch(72% 0.2 220);
-    --badge-update-text: oklch(28% 0.03 220);
-    --badge-update-glow: oklch(72% 0.2 220 / 0.28);
-    --badge-skip-refresh-bg: oklch(82% 0.12 45);
-    --badge-skip-refresh-text: oklch(35% 0.02 45);
-    --badge-skip-refresh-glow: oklch(82% 0.12 45 / 0.15);
-
-    /* Spacing Scale */
-    --space-1: calc(8px * 1);
-    --space-2: calc(8px * 2);
-    --space-3: calc(8px * 3);
-    --space-4: calc(8px * 4);
-
-    /* Z-index Scale */
-    --z-base: 10;
-    --z-header: 100;
-    --z-modal: 1000;
-    --z-overlay: 2000;
-
-    /* Border Radius */
-    --border-radius-base: 12px;
-    --border-radius-md: 12px;
-    --border-radius-sm: 8px;
-    --border-radius-xs: 4px;
-
     --scrollbar-width: 8px;
-    /* 添加滚动条宽度变量 */
 
-    /* Shortcut styles */
-    --shortcut-bg: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.12);
-    --shortcut-border: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.25);
-    --shortcut-text: var(--text-color);
+    --shortcut-bg: var(--color-accent-subtle);
+    --shortcut-border: var(--color-accent-border);
+    --shortcut-text: var(--text-primary);
+
+    --lora-accent-transparent: var(--color-accent-transparent);
+
+    /* Legacy spacing aliases: 8px base grid to match existing component usage */
+    --space-1: 8px;
+    --space-2: 16px;
+    --space-3: 24px;
+    --space-4: 32px;
+
+    /* Legacy border-radius aliases to match existing component usage */
+    --border-radius-xs: 4px;
+    --border-radius-sm: 6px;
+    --border-radius-base: 8px;
+    --border-radius-md: 12px;
+    --border-radius-lg: 16px;
+}
+
+:root {
+    --bg-color: var(--bg-base);
+    --text-color: var(--text-primary);
+    --text-muted: var(--text-secondary);
+    --card-bg: var(--surface-base);
+    --border-color: var(--border-base);
+
+    --lora-accent: var(--color-accent);
+    --lora-surface: var(--bg-elevated);
+    --lora-border: var(--border-subtle);
+    --lora-text: var(--text-primary);
+    --lora-error: var(--color-error);
+    --lora-error-bg: var(--color-error-bg);
+    --lora-error-border: var(--color-error-border);
+    --lora-warning: var(--color-warning);
+    --lora-success: var(--color-success);
+
+    --badge-update-bg: var(--color-info-bg);
+    --badge-update-text: var(--color-info-text);
+    --badge-update-glow: var(--color-info-glow);
+    --badge-skip-refresh-bg: var(--color-skip-refresh-bg);
+    --badge-skip-refresh-text: var(--color-skip-refresh-text);
+    --badge-skip-refresh-glow: var(--color-skip-refresh-glow);
+}
+
+[data-theme="dark"] {
+    --bg-color: var(--bg-base);
+    --text-color: var(--text-primary);
+    --text-muted: var(--text-secondary);
+    --card-bg: var(--surface-base);
+    --border-color: var(--border-base);
+
+    --lora-accent: var(--color-accent);
+    --lora-surface: var(--bg-elevated);
+    --lora-border: var(--border-subtle);
+    --lora-text: var(--text-primary);
+    --lora-error: var(--color-error);
+    --lora-error-bg: var(--color-error-bg);
+    --lora-error-border: var(--color-error-border);
+    --lora-warning: var(--color-warning);
+    --lora-success: var(--color-success);
+
+    --badge-update-bg: var(--color-info-bg);
+    --badge-update-text: var(--color-info-text);
+    --badge-update-glow: var(--color-info-glow);
+    --badge-skip-refresh-bg: var(--color-skip-refresh-bg);
+    --badge-skip-refresh-text: var(--color-skip-refresh-text);
+    --badge-skip-refresh-glow: var(--color-skip-refresh-glow);
 }
 
 html[data-theme="dark"] {
-    background-color: #1a1a1a !important;
+    background-color: var(--bg-base) !important;
     color-scheme: dark;
 }
 
 html[data-theme="light"] {
-    background-color: #ffffff !important;
+    background-color: var(--bg-base) !important;
     color-scheme: light;
 }
 
-[data-theme="dark"] {
-    --bg-color: #1a1a1a;
-    --text-color: #e0e0e0;
-    --text-muted: #a0a0a0;
-    --card-bg: #2d2d2d;
-    --border-color: #404040;
-
-    --lora-accent: oklch(68% 0.28 256);
-    --lora-surface: oklch(25% 0.02 256 / 0.98);
-    --lora-border: oklch(90% 0.02 256 / 0.15);
-    --lora-text: oklch(98% 0.02 256);
-    --lora-warning: oklch(75% 0.25 80);
-    /* Modified to be used with oklch() */
-    --lora-error-bg: color-mix(in oklch, var(--lora-error) 15%, transparent);
-    --lora-error-border: color-mix(in oklch, var(--lora-error) 40%, transparent);
-    --badge-update-bg: oklch(62% 0.18 220);
-    --badge-update-text: oklch(98% 0.02 240);
-    --badge-update-glow: oklch(62% 0.18 220 / 0.4);
-    --badge-skip-refresh-bg: oklch(82% 0.12 45);
-    --badge-skip-refresh-text: oklch(98% 0.02 45);
-    --badge-skip-refresh-glow: oklch(82% 0.12 45 / 0.15);
-}
-
 body {
-    font-family: 'Segoe UI', sans-serif;
-    background: var(--bg-color);
-    color: var(--text-color);
+    font-family: var(--font-body);
+    background: var(--bg-base);
+    color: var(--text-primary);
     display: flex;
     flex-direction: column;
     padding-top: 0;
-    /* Remove the padding-top */
 }
 
 .hidden {
     display: none !important;
-}
+}
+
+:focus-visible {
+    outline: 2px solid var(--color-accent);
+    outline-offset: 2px;
+}
+
+button:focus:not(:focus-visible),
+input:focus:not(:focus-visible),
+select:focus:not(:focus-visible) {
+    outline: none;
+}
+
+@media (prefers-reduced-motion: reduce) {
+    *,
+    *::before,
+    *::after {
+        animation-duration: 0.01ms !important;
+        animation-iteration-count: 1 !important;
+        transition-duration: 0.01ms !important;
+    }
+
+    html {
+        scroll-behavior: auto !important;
+    }
+}

static/css/components/alphabet-bar.css

@@ -46,7 +46,7 @@
     flex-direction: column;
     gap: 6px;
     align-items: center;
-    box-shadow: 2px 0 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-side);
     max-height: 80vh;
     overflow-y: auto;
     scrollbar-width: thin;
@@ -75,7 +75,7 @@
     width: 20px;
     height: 40px;
     align-self: center;
-    box-shadow: 2px 0 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-side);
 }
 
 .toggle-alphabet-bar:hover {
@@ -99,7 +99,7 @@
     min-width: 24px;
     text-align: center;
     font-size: 0.85em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     border: 1px solid var(--border-color);
 }
 
@@ -107,7 +107,7 @@
     background: var(--lora-accent);
     color: white;
     transform: scale(1.1);
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 .letter-chip.active {

static/css/components/banner.css

@@ -68,7 +68,7 @@
     text-decoration: none;
     font-size: 0.85em;
     font-weight: 500;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     white-space: nowrap;
     border: 1px solid transparent;
 }
@@ -102,7 +102,7 @@
     color: white;
     border-color: var(--lora-accent);
     transform: translateY(-1px);
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 /* Tertiary Action Button */
@@ -133,7 +133,7 @@
     display: flex;
     align-items: center;
     justify-content: center;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     font-size: 0.8em;
 }
 

static/css/components/batch-import-modal.css

@@ -76,7 +76,7 @@
     display: flex;
     align-items: center;
     justify-content: center;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     background: var(--bg-color);
 }
 
@@ -166,7 +166,7 @@
     background: var(--card-bg);
     color: var(--text-color);
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 .back-btn:hover {
@@ -237,7 +237,7 @@
     padding: 8px 10px;
     border-radius: var(--border-radius-xs);
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     border: 1px solid transparent;
 }
 
@@ -349,8 +349,8 @@
 }
 
 .progress-percentage {
-    font-size: 1.2em;
-    font-weight: 600;
+    font-size: var(--text-lg);
+    font-weight: var(--weight-semibold);
     color: var(--lora-accent);
 }
 
@@ -365,9 +365,9 @@
 
 .progress-bar {
     height: 100%;
-    background: linear-gradient(90deg, var(--lora-accent), oklch(from var(--lora-accent) calc(l + 0.1) c h));
-    border-radius: 4px;
-    transition: width 0.3s ease;
+    background: var(--lora-accent);
+    border-radius: var(--border-radius-xs);
+    transition: width var(--transition-base);
 }
 
 /* Progress Stats */
@@ -389,27 +389,26 @@
 }
 
 .stat-item.success {
-    border-left: 3px solid #00B87A;
+    border-left: 4px solid var(--color-success);
 }
 
 .stat-item.failed {
-    border-left: 3px solid var(--lora-error);
+    border-left: 4px solid var(--color-error);
 }
 
 .stat-item.skipped {
-    border-left: 3px solid var(--lora-warning);
+    border-left: 4px solid var(--color-warning);
 }
 
 .stat-label {
-    font-size: 0.8em;
-    color: var(--text-color);
-    opacity: 0.7;
+    font-size: var(--text-xs);
+    color: var(--text-secondary);
     margin-bottom: 4px;
 }
 
 .stat-value {
-    font-size: 1.4em;
-    font-weight: 600;
+    font-size: var(--text-lg);
+    font-weight: var(--weight-semibold);
     color: var(--text-color);
 }
 
@@ -425,8 +424,7 @@
 }
 
 .current-item-label {
-    color: var(--text-color);
-    opacity: 0.7;
+    color: var(--text-secondary);
     flex-shrink: 0;
 }
 
@@ -449,27 +447,29 @@
 }
 
 .results-header {
-    text-align: center;
+    display: flex;
+    align-items: center;
+    gap: var(--space-2);
     margin-bottom: var(--space-3);
 }
 
 .results-icon {
-    font-size: 3em;
-    color: #00B87A;
-    margin-bottom: var(--space-1);
+    font-size: var(--text-xl);
+    color: var(--color-success);
+    flex-shrink: 0;
 }
 
 .results-icon.warning {
-    color: var(--lora-warning);
+    color: var(--color-warning);
 }
 
 .results-icon.error {
-    color: var(--lora-error);
+    color: var(--color-error);
 }
 
 .results-title {
-    font-size: 1.3em;
-    font-weight: 600;
+    font-size: var(--text-lg);
+    font-weight: var(--weight-semibold);
     color: var(--text-color);
 }
 
@@ -493,27 +493,26 @@
 }
 
 .result-card.success {
-    border-left: 3px solid #00B87A;
+    border-left: 4px solid var(--color-success);
 }
 
 .result-card.failed {
-    border-left: 3px solid var(--lora-error);
+    border-left: 4px solid var(--color-error);
 }
 
 .result-card.skipped {
-    border-left: 3px solid var(--lora-warning);
+    border-left: 4px solid var(--color-warning);
 }
 
 .result-label {
-    font-size: 0.8em;
-    color: var(--text-color);
-    opacity: 0.7;
+    font-size: var(--text-xs);
+    color: var(--text-secondary);
     margin-bottom: 4px;
 }
 
 .result-value {
-    font-size: 1.4em;
-    font-weight: 600;
+    font-size: var(--text-lg);
+    font-weight: var(--weight-semibold);
     color: var(--text-color);
 }
 
@@ -527,13 +526,13 @@
     display: flex;
     align-items: center;
     justify-content: center;
-    gap: 8px;
-    padding: 10px;
+    gap: var(--space-2);
+    padding: var(--space-2);
     cursor: pointer;
     color: var(--lora-accent);
-    font-weight: 500;
+    font-weight: var(--weight-medium);
     border-radius: var(--border-radius-xs);
-    transition: background 0.2s;
+    transition: background var(--transition-base);
 }
 
 .details-toggle:hover {
@@ -541,7 +540,7 @@
 }
 
 .details-toggle i {
-    transition: transform 0.2s;
+    transition: transform var(--transition-base);
 }
 
 .details-toggle.expanded i {
@@ -561,10 +560,10 @@
 .result-item {
     display: flex;
     align-items: center;
-    gap: 10px;
-    padding: 10px 12px;
+    gap: var(--space-2);
+    padding: var(--space-2) var(--space-3);
     border-bottom: 1px solid var(--border-color);
-    font-size: 0.9em;
+    font-size: var(--text-sm);
 }
 
 .result-item:last-child {
@@ -572,28 +571,23 @@
 }
 
 .result-item-status {
-    width: 24px;
-    height: 24px;
-    border-radius: 50%;
     display: flex;
     align-items: center;
     justify-content: center;
-    font-size: 0.8em;
+    font-size: var(--text-sm);
+    flex-shrink: 0;
 }
 
 .result-item-status.success {
-    background: oklch(from #00B87A l c h / 0.2);
-    color: #00B87A;
+    color: var(--color-success);
 }
 
 .result-item-status.failed {
-    background: oklch(from var(--lora-error) l c h / 0.2);
-    color: var(--lora-error);
+    color: var(--color-error);
 }
 
 .result-item-status.skipped {
-    background: oklch(from var(--lora-warning) l c h / 0.2);
-    color: var(--lora-warning);
+    color: var(--color-warning);
 }
 
 .result-item-info {
@@ -610,8 +604,8 @@
 }
 
 .result-item-error {
-    font-size: 0.8em;
-    color: var(--lora-error);
+    font-size: var(--text-xs);
+    color: var(--color-error);
     margin-top: 2px;
 }
 
@@ -661,11 +655,11 @@
 
 /* Completed State */
 .batch-progress-container.completed .progress-bar {
-    background: #00B87A;
+    background: var(--color-success);
 }
 
 .batch-progress-container.completed .status-icon {
-    color: #00B87A;
+    color: var(--color-success);
 }
 
 .batch-progress-container.completed .status-icon i {

static/css/components/card.css

@@ -1,12 +1,12 @@
-/* 卡片网格布局 */
+/* Card grid layout */
 .card-grid {
     display: grid;
     grid-template-columns: repeat(auto-fill, minmax(260px, 1fr)); /* Base size */
     gap: 12px; /* Consistent gap for both row and column spacing */
     row-gap: 20px; /* Increase vertical spacing between rows */
     margin-top: var(--space-2);
-    padding-top: 4px; /* 添加顶部内边距，为悬停动画提供空间 */
-    padding-bottom: 4px; /* 添加底部内边距，为悬停动画提供空间 */
+    padding-top: 4px;
+    padding-bottom: 4px;
     width: 100%; /* Ensure it takes full width of container */
     max-width: 1400px; /* Base container width */
     margin-left: auto;
@@ -19,7 +19,7 @@
     border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-base);
     backdrop-filter: blur(16px);
-    transition: transform 160ms ease-out;
+    transition: transform var(--transition-fast) ease-out, box-shadow var(--transition-fast) ease-out, border-color var(--transition-fast) ease-out;
     aspect-ratio: 896/1152; /* Preserve aspect ratio */
     max-width: 260px; /* Base size */
     min-width: 200px; /* Prevent cards from becoming too narrow */
@@ -33,7 +33,8 @@
 
 .model-card:hover {
     transform: translateY(-2px);
-    background: oklch(100% 0 0 / 0.6);
+    box-shadow: var(--shadow-md);
+    border-color: var(--lora-accent);
 }
 
 .model-card:focus-visible {
@@ -277,7 +278,7 @@
     left: 0;
     right: 0;
     background: linear-gradient(transparent 15%, oklch(0% 0 0 / 0.75));
-    backdrop-filter: blur(8px);
+    backdrop-filter: blur(var(--card-blur-amount, 8px));
     color: white;
     padding: var(--space-1);
     display: flex;
@@ -293,7 +294,7 @@
     left: 0;
     right: 0;
     background: linear-gradient(oklch(0% 0 0 / 0.75), transparent 85%);
-    backdrop-filter: blur(8px);
+    backdrop-filter: blur(var(--card-blur-amount, 8px));
     color: white;
     padding: var(--space-1);
     display: flex;
@@ -353,21 +354,26 @@
 }
 
 .card-actions {
+    flex-shrink: 0;
     display: flex;
-    gap: var(--space-1); /* Use gap instead of margin for spacing between icons */
-    align-items: center;
+    gap: var(--space-1);
+    align-items: flex-end;
+    align-self: flex-end;
 }
 
-.card-actions i:hover {
+.card-actions i:hover,
+.card-actions i:focus-visible {
     opacity: 0.9;
     transform: scale(1.1);
     background-color: rgba(255, 255, 255, 0.1);
+    outline: 2px solid var(--lora-accent);
+    outline-offset: 2px;
+    border-radius: var(--border-radius-xs);
 }
 
-/* Style for active favorites */
 .favorite-active {
-    color: #ffc107 !important; /* Gold color for favorites */
-    text-shadow: 0 0 5px rgba(255, 193, 7, 0.5);
+    color: var(--favorite-color) !important;
+    text-shadow: 0 0 5px var(--favorite-glow);
 }
 
 @media (max-width: 1200px) {
@@ -391,14 +397,6 @@
     }
 }
 
-.card-actions {
-    flex-shrink: 0;  /* Prevent actions from shrinking */
-    display: flex;
-    gap: var(--space-1);
-    align-items: flex-end; /* 将图标靠下对齐 */
-    align-self: flex-end; /* 将整个actions容器靠下对齐 */
-}
-
 .model-link {
     margin-top: var(--space-1);
 }
@@ -411,9 +409,13 @@
     text-shadow: none;
 }
 
-.model-link a:hover {
+.model-link a:hover,
+.model-link a:focus-visible {
     opacity: 0.8;
     text-decoration: none;
+    outline: 2px solid var(--lora-accent);
+    outline-offset: 2px;
+    border-radius: var(--border-radius-xs);
 }
 
 /* Updated model name to fix text cutoff issues */
@@ -438,7 +440,7 @@
 
 .base-model {
     display: inline-block;
-    background: #f0f0f0;
+    background: var(--surface-hover, oklch(95% 0 0));
     padding: 2px 6px;
     border-radius: var(--border-radius-xs);
     margin-right: 6px;

static/css/components/duplicates.css

@@ -5,14 +5,14 @@
     position: sticky; /* Keep the sticky position */
     top: var(--space-1);
     width: 100%;
-    background-color: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.1); /* Use accent color with low opacity */
+    background-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.1); /* Use accent color with low opacity */
     color: var(--text-color);
-    border-top: 1px solid oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.3); /* Add top border with accent color */
-    border-bottom: 1px solid oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.4); /* Make bottom border stronger */
+    border-top: 1px solid oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.3); /* Add top border with accent color */
+    border-bottom: 1px solid oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.4); /* Make bottom border stronger */
     z-index: var(--z-overlay);
     padding: 12px 0;
-    box-shadow: 0 3px 10px rgba(0, 0, 0, 0.2); /* Stronger shadow */
-    transition: all 0.3s ease;
+    box-shadow: var(--shadow-lg); /* Stronger shadow */
+    transition: var(--transition-slow);
     margin-bottom: 20px;
 }
 
@@ -41,7 +41,7 @@
 
 .duplicates-banner i.fa-exclamation-triangle {
     font-size: 18px;
-    color: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    color: oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
 }
 
 .duplicates-banner .banner-actions {
@@ -65,12 +65,12 @@
     align-items: center;
     justify-content: center;
     gap: 6px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .duplicates-banner button.btn-exit-mode:hover {
     background-color: var(--bg-color);
-    border-color: var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h);
+    border-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
     transform: translateY(-1px);
 }
 
@@ -86,16 +86,16 @@
     background: var(--card-bg);
     color: var(--text-color);
     font-size: 0.85em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     cursor: pointer;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05);
+    box-shadow: var(--shadow-xs);
 }
 
 .duplicates-banner button:hover {
-    border-color: var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h);
+    border-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
     background: var(--bg-color);
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 .duplicates-banner button.btn-exit {
@@ -117,12 +117,12 @@
 /* Duplicate groups */
 .duplicate-group {
     position: relative;
-    border: 2px solid oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    border: 2px solid oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
     border-radius: var(--border-radius-base);
     padding: 16px;
     margin-bottom: 24px;
     background: var(--card-bg);
-    box-shadow: 0 2px 6px rgba(0, 0, 0, 0.12); /* Add subtle shadow to groups */
+    box-shadow: var(--shadow-md); /* Add subtle shadow to groups */
     /* Add responsive width settings to match banner */
     max-width: 1400px;
     margin-left: auto;
@@ -152,7 +152,7 @@
     display: flex;
     justify-content: space-between;
     align-items: center;
-    border-left: 4px solid oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h)); /* Add accent border on the left */
+    border-left: 4px solid oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h)); /* Add accent border on the left */
 }
 
 .duplicate-group-header span:last-child {
@@ -173,17 +173,17 @@
     background: var(--card-bg);
     color: var(--text-color);
     font-size: 0.85em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     cursor: pointer;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05);
+    box-shadow: var(--shadow-xs);
     margin-left: 8px;
 }
 
 .duplicate-group-header button:hover {
-    border-color: var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h);
+    border-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
     background: var(--bg-color);
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 .card-group-container {
@@ -230,34 +230,34 @@
     justify-content: center;
     cursor: pointer;
     z-index: 1;
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
-    transition: all 0.2s ease;
+    box-shadow: var(--shadow-sm);
+    transition: var(--transition-base);
 }
 
 .group-toggle-btn:hover {
-    border-color: var(--lora-accent-l) var(--lora-accent-c) var (--lora-accent-h);
+    border-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 /* Duplicate card styling */
 .model-card.duplicate {
     position: relative;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .model-card.duplicate:hover {
-    border-color: var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h);
+    border-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
 }
 
 .model-card.duplicate.latest {
     border-style: solid;
-    border-color: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    border-color: oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
 }
 
 .model-card.duplicate-selected {
-    border: 2px solid oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
-    box-shadow: 0 0 8px rgba(0, 0, 0, 0.2);
+    border: 2px solid oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
+    box-shadow: var(--shadow-md);
 }
 
 .model-card .selector-checkbox {
@@ -276,7 +276,7 @@
     position: absolute;
     top: 10px;
     left: 10px;
-    background: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
+    background: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
     color: white;
     font-size: 12px;
     padding: 2px 6px;
@@ -290,7 +290,7 @@
     background-color: var(--card-bg);
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
-    box-shadow: 0 2px 10px rgba(0,0,0,0.2);
+    box-shadow: var(--shadow-lg);
     padding: 10px;
     z-index: 1000;
     max-width: 350px;
@@ -328,7 +328,7 @@
     margin-top: 8px;
     padding-top: 8px;
     border-top: 1px dashed var(--border-color);
-    color: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    color: oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
     font-weight: bold;
     word-break: break-all; /* Ensure long hashes wrap properly */
 }
@@ -351,12 +351,12 @@
 }
 
 .verification-badge.verified {
-    background-color: oklch(70% 0.2 140); /* Green for verified */
+    background-color: var(--color-success); /* Green for verified */
     color: white;
 }
 
 .verification-badge.mismatch {
-    background-color: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    background-color: oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
     color: white;
 }
 
@@ -366,7 +366,7 @@
 
 /* Hash Mismatch Styling */
 .model-card.duplicate.hash-mismatch {
-    border: 2px dashed oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    border: 2px dashed oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
     opacity: 0.85;
     position: relative;
 }
@@ -380,8 +380,8 @@
     bottom: 0;
     background: repeating-linear-gradient(
         45deg,
-        oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h) / 0.05),
-        oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h) / 0.05) 10px,
+        oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h) / 0.05),
+        oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h) / 0.05) 10px,
         transparent 10px,
         transparent 20px
     );
@@ -398,7 +398,7 @@
     position: absolute;
     top: 10px;
     left: 10px; /* Changed from right:10px to left:10px */
-    background: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    background: oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
     color: white;
     font-size: 12px;
     padding: 3px 8px;
@@ -417,7 +417,7 @@
     margin-top: 8px;
     padding-top: 8px;
     border-top: 1px dashed var(--border-color);
-    color: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
+    color: oklch(var(--color-warning-l) var(--color-warning-c) var(--color-warning-h));
     font-weight: bold;
 }
 
@@ -432,12 +432,12 @@
     border-radius: var(--border-radius-xs);
     font-size: 0.85em;
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .btn-verify-hashes:hover {
     background: var(--bg-color);
-    border-color: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
+    border-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
     transform: translateY(-1px);
 }
 
@@ -461,7 +461,7 @@
     position: absolute;
     top: -8px; /* Moved closer to button */
     right: -8px; /* Moved closer to button */
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.15); /* Softer shadow */
+    box-shadow: var(--shadow-sm); /* Softer shadow */
     transition: transform 0.2s ease, opacity 0.2s ease;
 }
 
@@ -493,12 +493,12 @@
     cursor: help;
     font-size: 16px;
     margin-left: 8px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .help-icon:hover {
     opacity: 1;
-    color: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
+    color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h));
 }
 
 /* Help tooltip */
@@ -511,7 +511,7 @@
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
     padding: 12px 16px;
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15);
+    box-shadow: var(--shadow-elevated);
     z-index: var(--z-overlay);
     font-size: 0.9em;
     margin-top: 10px;
@@ -572,16 +572,16 @@
 
 /* In dark mode, add additional distinction */
 html[data-theme="dark"] .duplicates-banner {
-    box-shadow: 0 3px 12px rgba(0, 0, 0, 0.4); /* Stronger shadow in dark mode */
-    background-color: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.15); /* Slightly stronger background in dark mode */
+    box-shadow: var(--shadow-dark-lg); /* Stronger shadow in dark mode */
+    background-color: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.15); /* Slightly stronger background in dark mode */
 }
 
 html[data-theme="dark"] .duplicate-group {
-    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.25); /* Stronger shadow in dark mode */
+    box-shadow: var(--shadow-lg); /* Stronger shadow in dark mode */
 }
 
 html[data-theme="dark"] .help-tooltip {
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3);
+    box-shadow: var(--shadow-elevated);
 }
 
 /* Styles for disabled controls during duplicates mode */
@@ -598,11 +598,11 @@ html[data-theme="dark"] .help-tooltip {
     background: var(--lora-accent);
     color: white;
     border-color: var(--lora-accent);
-    box-shadow: 0 0 0 2px oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.25);
+    box-shadow: 0 0 0 2px oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.25);
     position: relative;
     z-index: 5;
 }
 
 #findDuplicatesBtn.active:hover {
-    background: oklch(calc(var(--lora-accent-l) - 5%) var(--lora-accent-c) var(--lora-accent-h));
+    background: oklch(calc(var(--color-accent-l) - 5%) var(--color-accent-c) var(--color-accent-h));
 }

static/css/components/filter-indicator.css

@@ -7,22 +7,22 @@
     color: white;
     border-radius: var(--border-radius-xs);
     padding: 4px 10px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     border: 1px solid var(--lora-accent);
     cursor: pointer;
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-sm);
     font-size: 0.85em;
 }
 
 .control-group .filter-active:hover {
     opacity: 0.92;
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.15);
+    box-shadow: var(--shadow-md);
 }
 
 .control-group .filter-active:active {
     transform: translateY(0);
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-sm);
 }
 
 .control-group .filter-active i.fa-filter {
@@ -59,9 +59,9 @@
 
 /* Animation for filter indicator */
 @keyframes filterPulse {
-    0% { transform: scale(1); box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); }
-    50% { transform: scale(1.03); box-shadow: 0 3px 8px rgba(0, 0, 0, 0.15); }
-    100% { transform: scale(1); box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); }
+    0% { transform: scale(1); box-shadow: var(--shadow-sm); }
+    50% { transform: scale(1.03); box-shadow: var(--shadow-lg); }
+    100% { transform: scale(1); box-shadow: var(--shadow-sm); }
 }
 
 .filter-active.animate {

static/css/components/header.css

@@ -7,7 +7,7 @@
   height: 48px;
   /* Reduced height */
   width: 100%;
-  box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+  box-shadow: var(--shadow-md);
   /* Slightly stronger shadow */
 }
 
@@ -134,14 +134,14 @@
   background: var(--input-bg, var(--card-bg));
   border: 1px solid var(--border-color);
   border-radius: var(--border-radius-sm, 6px);
-  transition: all 0.2s ease;
-  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
+  transition: border-color var(--transition-base), box-shadow var(--transition-base);
+  box-shadow: var(--shadow-header);
   overflow: hidden;
 }
 
 .header-search .search-container:focus-within {
   border-color: var(--lora-accent);
-  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08), 0 0 0 1px var(--lora-accent);
+  box-shadow: var(--shadow-header), 0 0 0 1px var(--lora-accent);
 }
 
 .header-search input {
@@ -183,7 +183,7 @@
   color: var(--text-muted);
   cursor: pointer;
   border-radius: var(--border-radius-xs, 4px);
-  transition: all 0.2s ease;
+  transition: background-color var(--transition-base), color var(--transition-base);
 }
 
 .header-search .search-options-toggle {
@@ -191,9 +191,11 @@
 }
 
 .header-search .search-options-toggle:hover,
-.header-search .search-filter-toggle:hover {
-  background: var(--lora-surface-hover, oklch(95% 0.02 256));
-  color: var(--lora-accent);
+.header-search .search-filter-toggle:hover,
+.header-search .search-filter-toggle:focus-visible {
+    background: var(--lora-surface-hover, oklch(95% 0.02 256));
+    color: var(--lora-accent);
+    outline: none;
 }
 
 .header-search .filter-badge {
@@ -269,7 +271,7 @@
   align-items: center;
   justify-content: center;
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: background-color var(--transition-base), color var(--transition-base), transform var(--transition-base);
   position: relative;
 }
 
@@ -281,7 +283,6 @@
 
 .theme-toggle {
   position: relative;
-  /* Ensure relative positioning for the container */
 }
 
 .theme-toggle .light-icon,
@@ -291,17 +292,14 @@
   top: 50%;
   left: 50%;
   transform: translate(-50%, -50%);
-  /* Center perfectly */
   opacity: 0;
   transition: opacity 0.3s ease;
 }
 
-/* Default state shows dark icon */
 .theme-toggle .dark-icon {
   opacity: 1;
 }
 
-/* Light theme shows light icon */
 .theme-toggle.theme-light .light-icon {
   opacity: 1;
 }
@@ -311,7 +309,6 @@
   opacity: 0;
 }
 
-/* Dark theme shows dark icon */
 .theme-toggle.theme-dark .dark-icon {
   opacity: 1;
 }
@@ -321,7 +318,6 @@
   opacity: 0;
 }
 
-/* Auto theme shows auto icon */
 .theme-toggle.theme-auto .auto-icon {
   opacity: 1;
 }
@@ -331,6 +327,201 @@
   opacity: 0;
 }
 
+.theme-popover {
+  display: none;
+  position: fixed;
+  background: var(--surface-base, #ffffff);
+  border: 1px solid var(--border-base, #e0e0e0);
+  border-radius: var(--radius-md, 8px);
+  box-shadow: var(--shadow-xl, 0 4px 16px rgba(0, 0, 0, 0.15));
+  padding: 12px;
+  min-width: 220px;
+  z-index: calc(var(--z-overlay) + 1);
+  animation: theme-popover-in 0.15s ease-out;
+}
+
+.theme-popover.active {
+  display: block;
+}
+
+@keyframes theme-popover-in {
+  from {
+    opacity: 0;
+    transform: translateY(-4px);
+  }
+  to {
+    opacity: 1;
+    transform: translateY(0);
+  }
+}
+
+.theme-popover-section {
+  display: flex;
+  flex-direction: column;
+  gap: 8px;
+}
+
+.theme-popover-label {
+  font-size: 0.7rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.05em;
+  color: var(--text-secondary, #6c757d);
+}
+
+.theme-popover-divider {
+  height: 1px;
+  background: var(--border-base, #e0e0e0);
+  margin: 10px 0;
+}
+
+.theme-popover-modes {
+  display: flex;
+  gap: 6px;
+}
+
+.theme-mode-btn {
+  flex: 1;
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  gap: 4px;
+  padding: 8px 4px;
+  border: 1px solid var(--border-base, #e0e0e0);
+  border-radius: var(--radius-sm, 6px);
+  background: var(--surface-elevated, #ffffff);
+  color: var(--text-primary, #333333);
+  cursor: pointer;
+  font-size: 0.75rem;
+  transition: background-color var(--transition-base, 200ms ease),
+              border-color var(--transition-base, 200ms ease),
+              color var(--transition-base, 200ms ease);
+}
+
+.theme-mode-btn i {
+  font-size: 0.9rem;
+}
+
+.theme-mode-btn:hover {
+  background: var(--surface-hover, oklch(95% 0.02 256));
+  border-color: var(--color-accent, oklch(68% 0.28 256));
+}
+
+.theme-mode-btn.active {
+  background: var(--color-accent-subtle, oklch(68% 0.28 256 / 0.12));
+  border-color: var(--color-accent, oklch(68% 0.28 256));
+  color: var(--color-accent, oklch(68% 0.28 256));
+}
+
+.theme-popover-presets {
+  display: grid;
+  grid-template-columns: repeat(3, 1fr);
+  gap: 6px;
+}
+
+.theme-preset-btn {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  gap: 4px;
+  padding: 8px 4px;
+  border: 1px solid var(--border-base, #e0e0e0);
+  border-radius: var(--radius-sm, 6px);
+  background: var(--surface-elevated, #ffffff);
+  color: var(--text-primary, #333333);
+  cursor: pointer;
+  font-size: 0.7rem;
+  transition: background-color var(--transition-base, 200ms ease),
+              border-color var(--transition-base, 200ms ease),
+              color var(--transition-base, 200ms ease);
+}
+
+.theme-preset-btn:hover {
+  background: var(--surface-hover, oklch(95% 0.02 256));
+  border-color: var(--color-accent, oklch(68% 0.28 256));
+}
+
+.theme-preset-btn.active {
+  background: var(--color-accent-subtle, oklch(68% 0.28 256 / 0.12));
+  border-color: var(--color-accent, oklch(68% 0.28 256));
+  color: var(--color-accent, oklch(68% 0.28 256));
+}
+
+.preset-swatch {
+  display: inline-block;
+  width: 22px;
+  height: 22px;
+  border-radius: var(--radius-xs, 4px);
+  border: 1px solid var(--border-subtle, oklch(72% 0.03 256 / 0.45));
+  flex-shrink: 0;
+  transition: transform var(--transition-base, 200ms ease),
+              box-shadow var(--transition-base, 200ms ease);
+}
+
+/* Solid accent colors — each swatch shows the theme's accent color directly.
+   This matches the app's flat, token-driven design language instead of using
+   decorative gradients that clash with the matte aesthetic. */
+
+.preset-swatch-default {
+  background: oklch(68% 0.28 256);
+}
+
+.preset-swatch-nord {
+  background: oklch(62% 0.18 213);
+}
+
+.preset-swatch-midnight {
+  background: oklch(52% 0.15 300);
+}
+
+.preset-swatch-monokai {
+  background: oklch(72% 0.24 190);
+}
+
+.preset-swatch-dracula {
+  background: oklch(68% 0.24 265);
+}
+
+.preset-swatch-solarized {
+  background: oklch(55% 0.18 175);
+}
+
+.theme-preset-btn.active .preset-swatch {
+  box-shadow: 0 0 0 2px var(--color-accent, oklch(68% 0.28 256));
+}
+
+.theme-preset-btn:hover .preset-swatch {
+  transform: scale(1.08);
+}
+
+/* Dark mode: use each preset's dark-mode accent lightness for visibility.
+   These match the --color-accent-l values from [data-theme="dark"][data-theme-preset="..."]
+   in tokens/colors.css so the swatch accurately previews what the theme looks like. */
+
+[data-theme="dark"] .preset-swatch-default {
+  background: oklch(68% 0.28 256);
+}
+
+[data-theme="dark"] .preset-swatch-nord {
+  background: oklch(68% 0.18 213);
+}
+
+[data-theme="dark"] .preset-swatch-midnight {
+  background: oklch(68% 0.14 300);
+}
+
+[data-theme="dark"] .preset-swatch-monokai {
+  background: oklch(72% 0.24 190);
+}
+
+[data-theme="dark"] .preset-swatch-dracula {
+  background: oklch(72% 0.24 265);
+}
+
+[data-theme="dark"] .preset-swatch-solarized {
+  background: oklch(60% 0.18 175);
+}
+
 /* Badge styling */
 .update-badge {
   position: absolute;
@@ -341,7 +532,7 @@
   background-color: var(--lora-error);
   border-radius: 50%;
   border: 2px solid var(--card-bg);
-  transition: all 0.2s ease;
+  transition: opacity var(--transition-base);
   pointer-events: none;
   opacity: 0;
 }
@@ -362,13 +553,22 @@
   align-items: center;
   justify-content: center;
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: background-color var(--transition-base), color var(--transition-base);
   flex-shrink: 0;
 }
 
-.hamburger-menu-btn:hover {
-  background: var(--lora-accent);
-  color: white;
+.hamburger-menu-btn:hover,
+.hamburger-menu-btn:focus-visible {
+    background: var(--lora-surface-hover, oklch(95% 0.02 256));
+    color: var(--lora-accent);
+    outline: none;
+}
+
+.hamburger-dropdown .dropdown-item:hover,
+.hamburger-dropdown .dropdown-item:focus-visible {
+    background: var(--lora-surface-hover, oklch(95% 0.02 256));
+    color: var(--lora-accent);
+    outline: none;
 }
 
 /* Hamburger dropdown menu */
@@ -381,7 +581,7 @@
   background: var(--card-bg);
   border: 1px solid var(--border-color);
   border-radius: var(--border-radius-sm, 6px);
-  box-shadow: 0 4px 16px rgba(0, 0, 0, 0.15);
+  box-shadow: var(--shadow-toast);
   padding: 0.5rem;
   min-width: 160px;
   z-index: var(--z-dropdown, 200);
@@ -401,7 +601,7 @@
   border-radius: var(--border-radius-xs, 4px);
   color: var(--text-color);
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: background-color var(--transition-base), color var(--transition-base);
   font-size: 0.9rem;
   white-space: nowrap;
 }

static/css/components/import-modal.css

@@ -211,7 +211,7 @@
 
 .lora-item.is-early-access {
     background: rgba(0, 184, 122, 0.05);
-    border-left: 4px solid #00B87A;
+    border-left: 4px solid var(--color-success);
 }
 
 .lora-item.missing-locally {
@@ -310,7 +310,7 @@
 
 .missing-lora-item.is-early-access {
     background: rgba(0, 184, 122, 0.05);
-    border-left: 3px solid #00B87A;
+    border-left: 3px solid var(--color-success);
     padding-left: 10px;
 }
 
@@ -630,7 +630,7 @@
     gap: 12px;
     padding: 12px 16px;
     background: rgba(0, 184, 122, 0.1);
-    border: 1px solid #00B87A;
+    border: 1px solid var(--color-success);
     border-radius: var(--border-radius-sm);
     color: var(--text-color);
     margin-bottom: var(--space-2);
@@ -646,7 +646,7 @@
 
 /* Specific styling for the early access warning container in import modal */
 .early-access-warning .warning-icon {
-    color: #00B87A;
+    color: var(--color-success);
     font-size: 1.2em;
 }
 
@@ -757,7 +757,7 @@
     position: relative;
     border-radius: var(--border-radius-sm);
     overflow: hidden;
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
     transition: transform 0.2s ease;
 }
 

static/css/components/initialization.css

@@ -176,7 +176,7 @@
   background: rgba(var(--lora-accent), 0.05);
   border-radius: var(--border-radius-base);
   padding: var(--space-2);
-  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.05);
+  box-shadow: var(--shadow-sm);
 }
 
 .tips-header {

static/css/components/keyboard-nav.css

@@ -1,96 +0,0 @@
-/* Keyboard navigation indicator and help */
-.keyboard-nav-hint {
-    display: inline-flex;
-    align-items: center;
-    justify-content: center;
-    position: relative;
-    width: 32px;
-    height: 32px;
-    border-radius: 50%;
-    background: var(--card-bg);
-    border: 1px solid var(--border-color);
-    color: var(--text-color);
-    cursor: help;
-    transition: all 0.2s ease;
-    margin-left: 8px;
-}
-
-.keyboard-nav-hint:hover {
-    background: var(--lora-accent);
-    color: white;
-    transform: translateY(-2px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
-}
-
-.keyboard-nav-hint i {
-    font-size: 14px;
-}
-
-/* Tooltip styling */
-.tooltip {
-    position: relative;
-}
-
-.tooltip .tooltiptext {
-    visibility: hidden;
-    width: 240px;
-    background-color: var(--lora-surface);
-    color: var(--text-color);
-    text-align: center;
-    border-radius: var(--border-radius-xs);
-    padding: 8px;
-    position: absolute;
-    z-index: 9999; /* Ensure tooltip appears above cards */
-    right: 120%; /* Position tooltip to the left of the icon */
-    top: 50%; /* Vertically center */
-    transform: translateY(-15%); /* Vertically center */
-    opacity: 0;
-    transition: opacity 0.3s;
-    box-shadow: 0 3px 8px rgba(0, 0, 0, 0.15);
-    border: 1px solid var(--lora-border);
-    font-size: 0.85em;
-    line-height: 1.4;
-}
-
-.tooltip .tooltiptext::after {
-    content: "";
-    position: absolute;
-    top: 50%; /* Vertically center arrow */
-    left: 100%; /* Arrow on the right side */
-    margin-top: -5px;
-    border-width: 5px;
-    border-style: solid;
-    border-color: transparent transparent transparent var(--lora-border); /* Arrow points right */
-}
-
-.tooltip:hover .tooltiptext {
-    visibility: visible;
-    opacity: 1;
-}
-
-/* Keyboard shortcuts table */
-.keyboard-shortcuts {
-    width: 100%;
-    border-collapse: collapse;
-    margin-top: 5px;
-}
-
-.keyboard-shortcuts td {
-    padding: 4px;
-    text-align: left;
-}
-
-.keyboard-shortcuts td:first-child {
-    font-weight: bold;
-    width: 40%;
-}
-
-.key {
-    display: inline-block;
-    background: var(--bg-color);
-    border: 1px solid var(--border-color);
-    border-radius: 3px;
-    padding: 1px 5px;
-    font-size: 0.8em;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.08);
-}

static/css/components/loading.css

@@ -18,7 +18,7 @@
     border-radius: var(--border-radius-base);
     text-align: center;
     border: 1px solid var(--lora-border);
-    width: min(400px, 90vw); /* 固定最大宽度，但保持响应式 */
+    width: min(400px, 90vw);
 }
 
 .loading-spinner {
@@ -33,7 +33,7 @@
 
 .loading-status {
     margin-bottom: 1rem;
-    color: var(--text-color); /* 使用主题文本颜色 */
+    color: var(--text-color);
     white-space: nowrap;
     overflow: hidden;
     text-overflow: ellipsis;
@@ -42,11 +42,11 @@
 }
 
 .progress-container {
-    width: 280px; /* 固定进度条宽度 */
-    background-color: var(--lora-border); /* 使用主题边框颜色 */
+    width: 280px;
+    background-color: var(--lora-border);
     border-radius: 4px;
     overflow: hidden;
-    margin: 0 auto; /* 居中显示 */
+    margin: 0 auto;
 }
 
 .progress-bar {

static/css/components/lora-modal/description.css

@@ -62,7 +62,7 @@
 }
 
 .model-description-content code {
-  font-family: monospace;
+  font-family: var(--font-mono);
   font-size: 0.9em;
   background: rgba(0, 0, 0, 0.05);
   padding: 0.1em 0.3em;

static/css/components/lora-modal/lora-modal.css

@@ -72,6 +72,10 @@
     margin-left: auto;
 }
 
+.modal-header-actions .license-permissions {
+    margin-left: auto;
+}
+
 .license-restrictions {
     display: flex;
     align-items: center;
@@ -95,6 +99,41 @@
     transform: translateY(-1px);
 }
 
+/* Set 2 — New style permission indicators */
+.license-permissions {
+    display: flex;
+    gap: 4px;
+    align-items: center;
+}
+
+.license-icon-new {
+    width: 22px;
+    height: 22px;
+    display: inline-block;
+    border-radius: 4px;
+    background-color: var(--text-muted);
+    -webkit-mask: var(--license-icon-image) center/contain no-repeat;
+    mask: var(--license-icon-image) center/contain no-repeat;
+    transition: background-color 0.2s ease, transform 0.2s ease;
+    cursor: default;
+    outline: 2px solid transparent;
+    outline-offset: 1px;
+}
+
+.license-icon-new.allowed {
+    background-color: var(--color-success, #40c057);
+    outline-color: color-mix(in oklch, var(--color-success, #40c057) 30%, transparent);
+}
+
+.license-icon-new.denied {
+    background-color: var(--color-error, #fa5252);
+    outline-color: color-mix(in oklch, var(--color-error, #fa5252) 30%, transparent);
+}
+
+.license-icon-new:hover {
+    transform: translateY(-1px);
+}
+
 /* Info Grid */
 .info-grid {
     display: grid;
@@ -105,14 +144,14 @@
 
 .info-item {
     padding: var(--space-2);
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid rgba(0, 0, 0, 0.1);
     border-radius: var(--border-radius-sm);
 }
 
-/* 调整深色主题下的样式 */
+/* Dark theme info item styles */
 [data-theme="dark"] .info-item {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid var(--lora-border);
 }
 
@@ -140,18 +179,70 @@
 
 /* Add specific styles for notes content */
 .info-item.notes .editable-field [contenteditable] {
-    height: 60px; /* Keep initial modal layout stable regardless of note length */
-    min-height: 60px; /* Increase height for multiple lines */
-    max-height: 420px; /* Limit maximum height */
-    overflow: auto; /* Enable scrolling and resize handle for long content */
-    resize: vertical; /* Allow manual vertical resizing */
-    white-space: pre-wrap; /* Preserve line breaks */
-    line-height: 1.5; /* Improve readability */
-    padding: 8px 12px; /* Slightly increase padding */
+    min-height: 60px;
+    white-space: pre-wrap;
+    line-height: 1.5;
+    padding: 8px 12px;
+}
+
+/* Notes expand/collapse — collapsed by default; only applies when JS detects long content */
+.info-item.notes .editable-field {
+    position: relative;
+    max-height: none;
+    overflow: visible;
+}
+
+.info-item.notes .editable-field.collapsed {
+    max-height: 80px;
+    overflow: hidden;
+}
+
+/* Gradient fade overlay hint when collapsed */
+.info-item.notes .editable-field.collapsed::after {
+    content: '';
+    position: absolute;
+    bottom: 0;
+    left: 0;
+    right: 0;
+    height: 28px;
+    background: linear-gradient(transparent, var(--bg-color));
+    pointer-events: none;
+}
+
+/* Notes header row — label left, toggle button right */
+.notes-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+}
+
+/* Toggle button — icon only, inline with the label */
+.notes-toggle-btn {
+    display: none;  /* shown by JS when content exceeds threshold */
+    align-items: center;
+    justify-content: center;
+    width: 26px;
+    height: 26px;
+    padding: 0;
+    border: none;
+    background: none;
+    color: var(--lora-accent);
+    cursor: pointer;
+    border-radius: 4px;
+    transition: background 0.15s;
+    flex-shrink: 0;
+}
+
+.notes-toggle-btn:hover {
+    background: rgba(66, 153, 225, 0.1);
+}
+
+.notes-toggle-btn i {
+    font-size: 0.85em;
 }
 
 .file-path {
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-size: 0.9em;
 }
 
@@ -219,13 +310,13 @@
     }
 }
 
-/* 修改 back-to-top 按钮样式，使其固定在 modal 内部 */
+/* Back-to-top button pinned inside modal */
 .modal-content .back-to-top {
-    position: sticky; /* 改用 sticky 定位 */
-    float: right; /* 使用 float 确保按钮在右侧 */
-    bottom: 20px; /* 距离底部的距离 */
-    margin-right: 20px; /* 右侧间距 */
-    margin-top: -56px; /* 负边距确保不占用额外空间 */
+    position: sticky;
+    float: right;
+    bottom: 20px;
+    margin-right: 20px;
+    margin-top: -56px;
     width: 36px;
     height: 36px;
     border-radius: 50%;
@@ -239,7 +330,7 @@
     opacity: 0;
     visibility: hidden;
     transform: translateY(10px);
-    transition: all 0.3s ease;
+    transition: opacity var(--transition-slow), visibility var(--transition-slow), transform var(--transition-slow);
     z-index: 10;
 }
 
@@ -282,7 +373,7 @@
     outline: none;
 }
 
-/* 合并编辑按钮样式 */
+/* Consolidated edit button styles */
 .edit-model-name-btn,
 .edit-file-name-btn,
 .edit-base-model-btn,
@@ -295,7 +386,7 @@
     cursor: pointer;
     padding: 2px 5px;
     border-radius: var(--border-radius-xs);
-    transition: all 0.2s ease;
+    transition: opacity var(--transition-base), background-color var(--transition-base);
     margin-left: var(--space-1);
 }
 
@@ -317,7 +408,7 @@
 .edit-base-model-btn:hover,
 .edit-model-description-btn:hover,
 .edit-version-name-btn:hover {
-    opacity: 0.8 !important;
+    opacity: 0.8;
     background: rgba(0, 0, 0, 0.05);
 }
 
@@ -335,7 +426,7 @@
 }
 
 .base-wrapper {
-    flex: 2;  /* 分配更多空间给base model */
+    flex: 2;  /* Allocate more space to base model */
 }
 
 /* Base model display and editing styles */
@@ -378,7 +469,7 @@
 }
 
 .size-wrapper span {
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-size: 0.9em;
     opacity: 0.9;
 }
@@ -395,7 +486,7 @@
     margin: 0;
     padding: var(--space-1);
     border-radius: var(--border-radius-xs);
-    font-size: 1.5em !important;
+    font-size: 1.5em;
     font-weight: 600;
     line-height: 1.2;
     color: var(--text-color);
@@ -431,7 +522,7 @@
     color: var(--text-color);
     cursor: pointer;
     font-size: 0.95em;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     opacity: 0.7;
     position: relative;
 }
@@ -836,18 +927,18 @@
     align-items: center;
     gap: 10px;
     padding: 2px 10px;
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid rgba(0, 0, 0, 0.1);
     border-radius: var(--border-radius-sm);
     max-width: fit-content;
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 [data-theme="dark"] .creator-info,
 [data-theme="dark"] .civitai-view,
 [data-theme="dark"] .modal-send-btn {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid var(--lora-border);
 }
 
@@ -906,14 +997,14 @@
     align-items: center;
     gap: 6px;
     padding: 6px 12px;
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid rgba(0, 0, 0, 0.1);
     border-radius: var(--border-radius-sm);
     color: var(--text-color);
     cursor: pointer;
     font-weight: 500;
     font-size: 0.9em;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 .civitai-view i {
@@ -929,18 +1020,18 @@
     align-items: center;
     gap: 6px;
     padding: 6px 12px;
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid rgba(0, 0, 0, 0.1);
     border-radius: var(--border-radius-sm);
     color: var(--text-color);
     cursor: pointer;
     font-weight: 500;
     font-size: 0.9em;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 [data-theme="dark"] .modal-send-btn {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid var(--lora-border);
 }
 

static/css/components/lora-modal/preset-tags.css

@@ -28,7 +28,7 @@
   border-radius: var(--border-radius-xs);
   padding: calc(var(--space-1) * 0.5) var(--space-1);
   gap: var(--space-1);
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
 }
 
 .preset-tag span {
@@ -40,7 +40,7 @@
   color: var(--text-color);
   opacity: 0.5;
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
 }
 
 .preset-tag:hover {

static/css/components/lora-modal/showcase.css

@@ -111,8 +111,8 @@
   align-items: center;
   justify-content: center;
   cursor: pointer;
-  transition: all 0.2s ease;
-  box-shadow: 0 2px 5px rgba(0, 0, 0, 0.15);
+  transition: var(--transition-base);
+  box-shadow: var(--shadow-md);
   padding: 0;
   position: relative;
   overflow: hidden;
@@ -120,7 +120,7 @@
 
 .media-control-btn:hover {
   transform: translateY(-2px);
-  box-shadow: 0 3px 7px rgba(0, 0, 0, 0.2);
+  box-shadow: var(--shadow-lg);
 }
 
 .media-control-btn.set-preview-btn:hover {
@@ -141,8 +141,9 @@
   border-color: var(--lora-error);
 }
 
-/* Disabled state for delete button */
-.media-control-btn.example-delete-btn.disabled {
+/* Disabled state for delete and create-recipe buttons */
+.media-control-btn.example-delete-btn.disabled,
+.media-control-btn.create-recipe-btn.disabled {
   opacity: 0.5;
   cursor: not-allowed;
 }
@@ -204,7 +205,7 @@
   z-index: 5;
   max-height: 50%; /* Reduced to take less space */
   overflow-y: auto;
-  box-shadow: 0 -2px 8px rgba(0, 0, 0, 0.1);
+  box-shadow: var(--shadow-inset-top);
   opacity: 0;
   pointer-events: none;
 }
@@ -219,7 +220,7 @@
 /* Adjust to dark theme */
 [data-theme="dark"] .image-metadata-panel {
   background: var(--card-bg);
-  box-shadow: 0 -2px 8px rgba(0, 0, 0, 0.3);
+  box-shadow: var(--shadow-inset-top);
 }
 
 .metadata-content {
@@ -296,7 +297,7 @@
 
 .metadata-prompt {
   color: var(--text-color);
-  font-family: monospace;
+  font-family: var(--font-mono);
   font-size: 0.85em;
   white-space: pre-wrap;
 }
@@ -311,7 +312,7 @@
   opacity: 0.6;
   cursor: pointer;
   padding: 3px;
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
 }
 
 .copy-prompt-btn:hover {
@@ -408,7 +409,7 @@
   border-radius: var(--border-radius-sm);
   padding: var(--space-4);
   text-align: center;
-  transition: all 0.3s ease;
+  transition: var(--transition-slow);
   background: var(--lora-surface);
   cursor: pointer;
 }
@@ -454,9 +455,9 @@
 }
 
 .import-formats {
-  font-size: 0.8em !important;
-  opacity: 0.6 !important;
-  margin-top: var(--space-2) !important;
+  font-size: 0.8em;
+  opacity: 0.6;
+  margin-top: var(--space-2);
 }
 
 .select-files-btn {
@@ -470,7 +471,7 @@
   display: flex;
   align-items: center;
   gap: 8px;
-  transition: all 0.2s;
+  transition: var(--transition-base);
 }
 
 .select-files-btn:hover {
@@ -480,7 +481,7 @@
 
 /* For dark theme */
 [data-theme="dark"] .import-container {
-  background: rgba(255, 255, 255, 0.03);
+  background: var(--surface-subtle);
 }
 
 /* Setup Guidance State - When example images path is not configured */

static/css/components/lora-modal/tag.css

@@ -17,17 +17,22 @@
   flex-wrap: nowrap;
   gap: 6px;
   align-items: center;
+  min-width: 0;
+  overflow: hidden;
 }
 
 .model-tag-compact {
   /* Updated styles to match info-item appearance */
-  background: rgba(0, 0, 0, 0.03);
+  background: var(--surface-subtle);
   border: 1px solid rgba(0, 0, 0, 0.1);
   border-radius: var(--border-radius-xs);
   padding: 2px 8px;
   font-size: 0.75em;
   color: var(--text-color);
   white-space: nowrap;
+  max-width: 150px;
+  overflow: hidden;
+  text-overflow: ellipsis;
 }
 
 /* Style for empty tags placeholder */
@@ -45,7 +50,7 @@
 
 /* Adjust dark theme tag styles */
 [data-theme="dark"] .model-tag-compact {
-  background: rgba(255, 255, 255, 0.03);
+  background: var(--surface-subtle);
   border: 1px solid var(--lora-border);
 }
 
@@ -73,14 +78,14 @@
   background: var(--card-bg);
   border: 1px solid var(--border-color);
   border-radius: var(--border-radius-sm);
-  box-shadow: 0 3px 8px rgba(0, 0, 0, 0.15);
+  box-shadow: var(--shadow-lg);
   padding: 10px 14px;
   max-width: 400px;
   z-index: 10;
   opacity: 0;
   visibility: hidden;
   transform: translateY(-4px);
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
   pointer-events: none;
 }
 
@@ -101,7 +106,7 @@
 
 .tooltip-tag {
   /* Updated styles to match info-item appearance */
-  background: rgba(0, 0, 0, 0.03);
+  background: var(--surface-hover);
   border: 1px solid rgba(0, 0, 0, 0.1);
   border-radius: var(--border-radius-xs);
   padding: 3px 8px;
@@ -111,15 +116,16 @@
 
 /* Adjust dark theme tooltip tag styles */
 [data-theme="dark"] .tooltip-tag {
-  background: rgba(255, 255, 255, 0.03);
+  background: var(--surface-hover);
   border: 1px solid var(--lora-border);
 }
 
 /* Model Tags Edit Mode */
 .model-tags-header {
   display: flex;
-  justify-content: space-between;
+  justify-content: flex-start;
   align-items: center;
+  overflow: hidden;
 }
 
 .edit-tags-btn {
@@ -130,8 +136,9 @@
   cursor: pointer;
   padding: 2px 5px;
   border-radius: var(--border-radius-xs);
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
   margin-left: var(--space-1);
+  flex-shrink: 0;
 }
 
 .edit-tags-btn.visible,

static/css/components/lora-modal/triggerwords.css

@@ -1,14 +1,14 @@
 /* Update Trigger Words styles */
 .info-item.trigger-words {
   padding: var(--space-2);
-  background: rgba(0, 0, 0, 0.03);
+  background: var(--surface-subtle);
   border: 1px solid rgba(0, 0, 0, 0.1);
   border-radius: var(--border-radius-sm);
 }
 
-/* 调整 trigger words 样式 */
+/* Trigger words styles */
 [data-theme="dark"] .info-item.trigger-words {
-  background: rgba(255, 255, 255, 0.03);
+  background: var(--surface-subtle);
   border: 1px solid var(--lora-border);
 }
 
@@ -48,7 +48,7 @@
   border-radius: var(--border-radius-xs);
   padding: 4px 8px;
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
   gap: 6px;
   position: relative;
 }

static/css/components/lora-modal/versions.css

@@ -146,7 +146,7 @@
     background: color-mix(in oklch, var(--card-bg) 92%, var(--bg-color) 8%);
     border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.04);
+    box-shadow: var(--shadow-xs);
     transition: border-color 0.2s ease, box-shadow 0.2s ease, transform 0.2s ease;
 }
 
@@ -156,7 +156,7 @@
 
 .model-version-row:hover {
     transform: translateY(-1px);
-    box-shadow: 0 4px 16px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-xl);
 }
 
 .model-version-row.is-clickable {
@@ -186,7 +186,7 @@
     height: 88px;
     border-radius: var(--border-radius-xs);
     overflow: hidden;
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-hover);
     display: flex;
     align-items: center;
     justify-content: center;

static/css/components/media-viewer.css

@@ -61,7 +61,7 @@
   max-height: 85vh;
   object-fit: contain;
   border-radius: 4px;
-  box-shadow: 0 4px 24px rgba(0, 0, 0, 0.4);
+  box-shadow: var(--shadow-dark-lg);
 }
 
 .media-viewer-video {

static/css/components/menu.css

@@ -5,7 +5,7 @@
     border-radius: var(--border-radius-xs);
     padding: 4px 0;
     min-width: 180px;
-    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.2);
+    box-shadow: var(--shadow-dropdown);
     z-index: 1000;
     display: none;
     backdrop-filter: blur(10px);
@@ -21,9 +21,11 @@
     background: var(--lora-surface);
 }
 
-.context-menu-item:hover {
+.context-menu-item:hover,
+.context-menu-item:focus-visible {
     background-color: var(--lora-accent);
     color: var(--lora-text);
+    outline: none;
 }
 
 .context-menu-separator {
@@ -32,6 +34,12 @@
     margin: 4px 0;
 }
 
+/* Lighter separator between category groups (vs the full separator before destructive) */
+.context-menu-separator.menu-section-break {
+    opacity: 0.4;
+    margin: 3px 0;
+}
+
 .context-menu-item.delete-item {
     color: var(--danger-color);
 }
@@ -75,7 +83,7 @@
     border-radius: var(--border-radius-xs);
     padding: 0;
     min-width: 200px;
-    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.2);
+    box-shadow: var(--shadow-dropdown);
     z-index: 1001;
     backdrop-filter: blur(10px);
 }
@@ -108,7 +116,7 @@
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-base);
     padding: 16px;
-    box-shadow: 0 4px 20px rgba(0, 0, 0, 0.2);
+    box-shadow: var(--shadow-modal);
     z-index: var(--z-modal);
     width: 300px;
     display: none;
@@ -162,7 +170,7 @@
     border: 1px solid var(--border-color);
     color: var(--text-color);
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .nsfw-level-btn:hover {
@@ -186,7 +194,7 @@
     max-width: 350px;
     max-height: 400px;
     overflow-y: auto;
-    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.2);
+    box-shadow: var(--shadow-dropdown);
     z-index: var(--z-overlay);
     display: none;
     backdrop-filter: blur(10px);

static/css/components/metadata-refresh-result.css

@@ -0,0 +1,171 @@
+/* Metadata Refresh Result Modal — component styles only */
+
+.metadata-refresh-result-modal {
+    max-width: 700px;
+}
+
+.refresh-summary-stats {
+    display: flex;
+    flex-wrap: wrap;
+    gap: var(--space-2);
+    margin: var(--space-3) 0;
+}
+
+.stat-card {
+    display: flex;
+    align-items: center;
+    gap: var(--space-2);
+    padding: var(--space-2) var(--space-3);
+    border-radius: var(--border-radius-sm);
+    background: var(--surface-subtle);
+    border-left: 4px solid transparent;
+    font-size: var(--text-sm);
+    flex: 1;
+    min-width: 130px;
+}
+
+.stat-card-body {
+    display: flex;
+    flex-direction: column;
+    min-width: 0;
+}
+
+.stat-card-label {
+    font-size: var(--text-xs);
+    color: var(--text-secondary);
+    line-height: var(--leading-tight);
+}
+
+.stat-card-value {
+    font-weight: var(--weight-bold);
+    font-size: var(--text-lg);
+    color: var(--lora-text);
+    line-height: var(--leading-tight);
+}
+
+.stat-card-success {
+    border-left-color: var(--color-success);
+}
+
+.stat-card-failure {
+    border-left-color: var(--color-error);
+}
+
+.stat-card-skipped {
+    border-left-color: var(--color-warning);
+}
+
+.stat-card-total {
+    border-left-color: var(--lora-border);
+}
+
+.stat-card-time {
+    border-left-color: var(--lora-border);
+}
+
+.refresh-failures-section {
+    margin-bottom: var(--space-3);
+}
+
+.refresh-failures-section h4 {
+    margin: 0 0 var(--space-2) 0;
+    font-size: var(--text-base);
+    color: var(--color-error);
+    display: flex;
+    align-items: center;
+    gap: var(--space-1);
+}
+
+.refresh-failures-section h4 i {
+    font-size: 0.9em;
+}
+
+.failure-table-wrapper {
+    max-height: 300px;
+    overflow-y: auto;
+    border: 1px solid var(--lora-border);
+    border-radius: var(--border-radius-sm);
+}
+
+.failure-table {
+    width: 100%;
+    border-collapse: collapse;
+    font-size: var(--text-sm);
+}
+
+.failure-table th {
+    position: sticky;
+    top: 0;
+    background: var(--lora-surface);
+    border-bottom: 1px solid var(--lora-border);
+    padding: var(--space-1) var(--space-2);
+    text-align: left;
+    font-weight: var(--weight-semibold);
+    color: var(--text-secondary);
+    z-index: 1;
+}
+
+.failure-table td {
+    padding: var(--space-1) var(--space-2);
+    border-bottom: 1px solid var(--lora-border);
+    vertical-align: top;
+}
+
+.failure-table tr:last-child td {
+    border-bottom: none;
+}
+
+.failure-table tr:hover td {
+    background: var(--surface-subtle);
+}
+
+.failure-index {
+    width: 30px;
+    text-align: center;
+    color: var(--text-secondary);
+}
+
+.failure-name {
+    max-width: 300px;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    font-family: var(--font-mono);
+    font-size: var(--text-xs);
+}
+
+.failure-error {
+    color: var(--color-error);
+    font-size: var(--text-xs);
+}
+
+.refresh-success-message {
+    display: flex;
+    align-items: center;
+    gap: var(--space-2);
+    padding: var(--space-3);
+    margin-bottom: var(--space-3);
+    background: var(--surface-subtle);
+    border-left: 4px solid var(--color-success);
+    color: var(--lora-text);
+    border-radius: var(--border-radius-sm);
+    font-weight: var(--weight-medium);
+}
+
+.refresh-success-message i {
+    font-size: 1.2em;
+    flex-shrink: 0;
+    color: var(--color-success);
+}
+
+[data-theme="dark"] .failure-table th {
+    background: var(--lora-surface);
+}
+
+[data-theme="dark"] .failure-table td {
+    border-bottom-color: var(--lora-border);
+}
+
+[data-theme="dark"] .failure-table tr:hover td {
+    background: var(--surface-subtle);
+}

static/css/components/modal/_base.css

@@ -1,4 +1,4 @@
-/* modal 基础样式 */
+/* Modal base styles */
 .modal {
     display: none;
     position: fixed;
@@ -6,19 +6,19 @@
     left: 0;
     width: 100%;
     height: calc(100% - var(--header-height, 48px)); /* Adjust height to exclude header */
-    background: rgba(0, 0, 0, 0.2); /* 调整为更淡的半透明黑色 */
+    background: rgba(0, 0, 0, 0.2);
     z-index: var(--z-modal);
     overflow: auto; /* Change from hidden to auto to allow scrolling */
 }
 
-/* 当模态窗口打开时，禁止body滚动 */
+/* Prevent body scroll when modal is open */
 body.modal-open {
     position: fixed;
     width: 100%;
-    padding-right: var(--scrollbar-width, 0px); /* 补偿滚动条消失导致的页面偏移 */
+    padding-right: var(--scrollbar-width, 0px);
 }
 
-/* modal-content 样式 */
+/* Modal content styles */
 .modal-content {
     position: relative;
     max-width: 800px;
@@ -29,12 +29,9 @@ body.modal-open {
     border-radius: var(--border-radius-base);
     padding: var(--space-3);
     border: 1px solid var(--lora-border);
-    box-shadow: 
-        0 4px 6px -1px rgba(0, 0, 0, 0.1),
-        0 2px 4px -1px rgba(0, 0, 0, 0.06),
-        0 10px 15px -3px rgba(0, 0, 0, 0.05);
+    box-shadow: var(--shadow-md);
     overflow-y: auto;
-    overflow-x: hidden; /* 防止水平滚动条 */
+    overflow-x: hidden;
     scrollbar-gutter: stable both-edges; /* Reserve space to prevent layout shift when scrollbar toggles */
 }
 
@@ -42,10 +39,10 @@ body.modal-open {
     min-height: 480px;
 }
 
-/* 当 modal 打开时锁定 body */
+/* Lock body when modal is open */
 body.modal-open {
-    overflow: hidden !important; /* 覆盖 base.css 中的 scroll */
-    padding-right: var(--scrollbar-width, 8px); /* 使用滚动条宽度作为补偿 */
+    overflow: hidden !important;
+    padding-right: var(--scrollbar-width, 8px);
 }
 
 @keyframes modalFadeIn {
@@ -67,12 +64,25 @@ body.modal-open {
 }
 
 .cancel-btn, .delete-btn, .exclude-btn, .confirm-btn {
-    padding: 8px var(--space-2);
-    border-radius: 6px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    gap: var(--space-1);
+    padding: var(--space-1) var(--space-2);
+    border-radius: var(--border-radius-sm);
     border: none;
     cursor: pointer;
     font-weight: 500;
+    font-size: 0.95em;
     min-width: 100px;
+    transition: background-color var(--transition-base), opacity var(--transition-base), transform var(--transition-fast);
+}
+
+.cancel-btn:active,
+.delete-btn:active,
+.exclude-btn:active,
+.confirm-btn:active {
+    transform: scale(0.98);
 }
 
 .cancel-btn {
@@ -92,16 +102,20 @@ body.modal-open {
     color: white;
 }
 
-.cancel-btn:hover {
+.cancel-btn:hover,
+.cancel-btn:focus-visible {
     background: var(--lora-border);
 }
 
-.delete-btn:hover {
-    opacity: 0.9;
+.delete-btn:hover,
+.delete-btn:focus-visible {
+    background: oklch(from var(--lora-error) l c h / 85%);
 }
 
-.exclude-btn:hover, .confirm-btn:hover {
-    opacity: 0.9;
+.exclude-btn:hover,
+.exclude-btn:focus-visible,
+.confirm-btn:hover,
+.confirm-btn:focus-visible {
     background: oklch(from var(--lora-accent, #4f46e5) l c h / 85%);
 }
 
@@ -121,47 +135,41 @@ body.modal-open {
     font-size: 1.5em;
     cursor: pointer;
     opacity: 0.7;
-    transition: opacity 0.2s;
+    transition: opacity var(--transition-base);
     z-index: 10;
 }
 
-.close:hover {
+.close:hover,
+.close:focus-visible {
     opacity: 1;
+    outline: 2px solid var(--lora-accent);
+    outline-offset: 2px;
+    border-radius: var(--border-radius-xs);
 }
 
-/* 统一各个 section 的样式 */
+/* Unified section styles */
 .support-section,
 .changelog-section,
 .update-info,
 .info-item,
 .path-preview {
-    background: rgba(0, 0, 0, 0.03);
-    border: 1px solid rgba(0, 0, 0, 0.1);
+    background: var(--surface-subtle);
+    border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
 }
 
-/* 深色主题统一样式 */
+/* Dark theme unified styles */
 [data-theme="dark"] .modal-content {
     background: var(--lora-surface);
     border: 1px solid var(--lora-border);
 }
 
-[data-theme="dark"] .support-section,
-[data-theme="dark"] .changelog-section,
-[data-theme="dark"] .update-info,
-[data-theme="dark"] .info-item,
-[data-theme="dark"] .path-preview,
-[data-theme="dark"] #bulkDownloadMissingLorasModal .bulk-download-loras-preview {
-    background: rgba(255, 255, 255, 0.03);
-    border: 1px solid var(--lora-border);
-}
-
 .primary-btn {
     display: flex;
     align-items: center;
     gap: 8px;
-    padding: 8px 16px;
+    padding: var(--space-1) var(--space-2);
     background-color: var(--lora-accent);
     color: var(--lora-text);
     border: none;
@@ -171,9 +179,11 @@ body.modal-open {
     font-size: 0.95em;
 }
 
-.primary-btn:hover {
+.primary-btn:hover,
+.primary-btn:focus-visible {
     background-color: oklch(from var(--lora-accent) l c h / 85%);
     color: var(--lora-text);
+    outline: none;
 }
 
 /* Secondary button styles */
@@ -181,19 +191,21 @@ body.modal-open {
     display: flex;
     align-items: center;
     gap: 8px;
-    padding: 8px 16px;
+    padding: var(--space-1) var(--space-2);
     background-color: var(--card-bg);
-    color: var (--text-color);
+    color: var(--text-color);
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     font-size: 0.95em;
 }
 
-.secondary-btn:hover {
+.secondary-btn:hover,
+.secondary-btn:focus-visible {
     background-color: var(--border-color);
     color: var(--text-color);
+    outline: none;
 }
 
 /* Disabled button styles */
@@ -244,7 +256,7 @@ button:disabled,
     display: flex;
     align-items: center;
     gap: 8px;
-    padding: 8px 16px;
+    padding: var(--space-1) var(--space-2);
     background-color: var(--lora-error);
     color: white;
     border: none;
@@ -254,25 +266,22 @@ button:disabled,
     font-size: 0.95em;
 }
 
-.danger-btn:hover {
+.danger-btn:hover,
+.danger-btn:focus-visible {
     background-color: oklch(from var(--lora-error) l c h / 85%);
     color: white;
+    outline: none;
 }
 
 /* Metadata archive status styles */
 .metadata-archive-status {
-    background: rgba(0, 0, 0, 0.03);
-    border: 1px solid rgba(0, 0, 0, 0.1);
+    background: var(--surface-subtle);
+    border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
     margin-bottom: var(--space-2);
 }
 
-[data-theme="dark"] .metadata-archive-status {
-    background: rgba(255, 255, 255, 0.03);
-    border: 1px solid var(--lora-border);
-}
-
 .archive-status-item {
     display: flex;
     justify-content: space-between;
@@ -312,17 +321,12 @@ button:disabled,
 }
 
 .backup-status {
-    background: rgba(0, 0, 0, 0.03);
-    border: 1px solid rgba(0, 0, 0, 0.1);
+    background: var(--surface-subtle);
+    border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-3);
 }
 
-[data-theme="dark"] .backup-status {
-    background: rgba(255, 255, 255, 0.03);
-    border: 1px solid var(--lora-border);
-}
-
 .backup-summary-grid {
     display: grid;
     grid-template-columns: repeat(auto-fit, minmax(160px, 1fr));
@@ -331,17 +335,12 @@ button:disabled,
 }
 
 .backup-summary-card {
-    background: rgba(255, 255, 255, 0.5);
-    border: 1px solid rgba(0, 0, 0, 0.06);
+    background: var(--lora-surface);
+    border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
 }
 
-[data-theme="dark"] .backup-summary-card {
-    background: rgba(255, 255, 255, 0.02);
-    border-color: rgba(255, 255, 255, 0.05);
-}
-
 .backup-summary-label {
     color: var(--text-color);
     font-size: 0.85rem;
@@ -404,14 +403,9 @@ button:disabled,
 }
 
 .backup-location-details {
-    border: 1px solid rgba(0, 0, 0, 0.1);
+    border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
-    background: rgba(0, 0, 0, 0.02);
-}
-
-[data-theme="dark"] .backup-location-details {
-    border-color: var(--lora-border);
-    background: rgba(255, 255, 255, 0.02);
+    background: var(--surface-subtle);
 }
 
 .backup-location-details summary {
@@ -442,16 +436,12 @@ button:disabled,
     max-width: 100%;
     padding: 6px 8px;
     border-radius: var(--border-radius-sm);
-    background: rgba(0, 0, 0, 0.05);
+    background: var(--surface-subtle);
     color: var(--text-color);
     overflow-wrap: anywhere;
     word-break: break-word;
 }
 
-[data-theme="dark"] .backup-location-path {
-    background: rgba(255, 255, 255, 0.05);
-}
-
 @media (max-width: 768px) {
     .backup-status-row {
         grid-template-columns: 1fr;
@@ -519,8 +509,8 @@ button:disabled,
 }
 
 #bulkDownloadMissingLorasModal .bulk-download-loras-preview {
-    background: rgba(0, 0, 0, 0.03);
-    border: 1px solid rgba(0, 0, 0, 0.1);
+    background: var(--surface-subtle);
+    border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-3);
     margin-bottom: var(--space-3);
@@ -578,7 +568,7 @@ button:disabled,
     align-items: flex-start;
     gap: var(--space-2);
     padding: var(--space-2);
-    background: rgba(59, 130, 246, 0.1);
+    background: oklch(from var(--lora-accent) l c h / 0.1);
     border-radius: var(--border-radius-sm);
     font-size: 0.9em;
     color: var(--text-color);

static/css/components/modal/delete-modal.css

@@ -51,7 +51,7 @@
     background: var(--lora-surface);
     padding: 2px 6px;
     border-radius: 3px;
-    font-family: monospace;
+    font-family: var(--font-mono);
     border: 1px solid var(--lora-border);
 }
 

static/css/components/modal/doctor-modal.css

@@ -48,8 +48,7 @@
     padding: var(--space-3);
     border-radius: var(--border-radius-sm);
     border: 1px solid var(--lora-border);
-    background: rgba(0, 0, 0, 0.03);
-    box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
 }
 
 .doctor-kicker {
@@ -128,7 +127,7 @@
 
 .doctor-issue-card {
     border: 1px solid rgba(0, 0, 0, 0.1);
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border-radius: var(--border-radius-sm);
     padding: var(--space-3);
     box-shadow: none;
@@ -242,7 +241,7 @@
 
 [data-theme="dark"] .doctor-hero,
 [data-theme="dark"] .doctor-issue-card {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
     border-color: var(--lora-border);
     box-shadow: none;
 }

static/css/components/modal/download-modal.css

@@ -37,7 +37,7 @@
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     background: var(--bg-color);
     margin: 1px;
     position: relative;
@@ -45,7 +45,7 @@
 
 .version-item:hover {
     border-color: var(--lora-accent);
-    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
     z-index: 1;
 }
 
@@ -156,7 +156,7 @@
     background: var(--bg-color);
     color: var(--text-color);
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     display: flex;
     align-items: center;
     justify-content: center;
@@ -225,7 +225,7 @@
     padding: 4px 8px;
     border-radius: var(--border-radius-xs);
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     color: var(--text-color);
     opacity: 0.7;
     text-decoration: none;
@@ -272,7 +272,7 @@
     padding: 4px 8px;
     cursor: pointer;
     border-radius: var(--border-radius-xs);
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     position: relative;
 }
 
@@ -293,7 +293,7 @@
     justify-content: center;
     cursor: pointer;
     border-radius: 2px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .tree-expand-icon:hover {
@@ -364,7 +364,7 @@
     color: var(--text-color);
     cursor: pointer;
     font-size: 0.8em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .create-folder-form button.confirm {
@@ -404,7 +404,7 @@
 .path-display {
     padding: var(--space-1);
     color: var(--text-color);
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-size: 0.9em;
     line-height: 1.4;
     white-space: pre-wrap;
@@ -453,7 +453,7 @@
     right: 0;
     bottom: 0;
     background-color: var(--border-color);
-    transition: all 0.3s ease;
+    transition: var(--transition-slow);
     border-radius: 18px;
 }
 
@@ -465,9 +465,9 @@
     left: 3px;
     bottom: 3px;
     background-color: white;
-    transition: all 0.3s ease;
+    transition: var(--transition-slow);
     border-radius: 50%;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.2);
+    box-shadow: var(--shadow-xs);
 }
 
 .inline-toggle-container .toggle-switch input:checked+.toggle-slider {
@@ -502,4 +502,323 @@
     opacity: 0.5;
     pointer-events: none;
     user-select: none;
+}
+
+/* File Count Badge on Version Items */
+.file-select-badge {
+    display: inline-flex;
+    align-items: center;
+    gap: 4px;
+    padding: 2px 8px;
+    border-radius: 10px;
+    background: oklch(var(--lora-accent) / 0.18);
+    color: var(--lora-accent);
+    font-size: inherit;
+    font-weight: 600;
+    cursor: pointer;
+    transition: var(--transition-base);
+    border: 1px solid oklch(var(--lora-accent) / 0.35);
+    user-select: none;
+    box-shadow: 0 1px 2px oklch(var(--lora-accent) / 0.1);
+}
+
+.file-select-badge:hover {
+    background: oklch(var(--lora-accent) / 0.3);
+    border-color: var(--lora-accent);
+    transform: scale(1.05);
+    box-shadow: 0 2px 6px oklch(var(--lora-accent) / 0.2);
+}
+
+.file-select-badge:active {
+    transform: scale(0.98);
+}
+
+.file-select-badge i {
+    font-size: 0.9em;
+}
+
+.file-select-badge .badge-arrow {
+    margin-left: 2px;
+    font-size: 0.65em;
+    opacity: 0.7;
+}
+
+/* File Selection Step */
+.file-selection-header {
+    margin-bottom: var(--space-3);
+}
+
+.file-selection-header h3 {
+    margin: 0 0 4px 0;
+    font-size: 1.1em;
+    color: var(--text-color);
+}
+
+.file-selection-version-name {
+    font-size: 0.9em;
+    color: var(--text-color);
+    opacity: 0.7;
+}
+
+.file-selection-list {
+    max-height: 360px;
+    overflow-y: auto;
+    margin: var(--space-2) 0;
+    display: flex;
+    flex-direction: column;
+    gap: 8px;
+}
+
+.file-option {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    padding: 12px;
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-sm);
+    cursor: pointer;
+    transition: var(--transition-base);
+    background: var(--bg-color);
+}
+
+.file-option:hover {
+    border-color: var(--lora-accent);
+    box-shadow: var(--shadow-sm);
+}
+
+.file-option.selected {
+    border: 2px solid var(--lora-accent);
+    background: oklch(var(--lora-accent) / 0.05);
+}
+
+.file-option-radio {
+    flex-shrink: 0;
+}
+
+.file-option-radio input[type="radio"] {
+    width: 16px;
+    height: 16px;
+    accent-color: var(--lora-accent);
+    cursor: pointer;
+}
+
+.file-option-info {
+    flex: 1;
+    min-width: 0;
+}
+
+.file-option-tags {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 6px;
+    margin-bottom: 4px;
+}
+
+.file-tag {
+    display: inline-block;
+    padding: 2px 7px;
+    border-radius: 4px;
+    font-size: 0.8em;
+    font-weight: 500;
+    line-height: 1.4;
+}
+
+.file-tag.format {
+    background: oklch(var(--lora-accent) / 0.1);
+    color: var(--lora-accent);
+}
+
+.file-tag.fp {
+    background: oklch(0.6 0.15 250 / 0.1);
+    color: oklch(0.55 0.15 250);
+}
+
+.file-tag.size {
+    background: oklch(0.55 0.1 160 / 0.1);
+    color: oklch(0.5 0.12 160);
+}
+
+.file-option-name {
+    font-size: 0.8em;
+    color: var(--text-color);
+    opacity: 0.6;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    margin-top: 2px;
+}
+
+.file-option-size {
+    font-size: 0.9em;
+    color: var(--text-color);
+    white-space: nowrap;
+    font-variant-numeric: tabular-nums;
+}
+
+/* Dark theme adjustments */
+[data-theme="dark"] .file-option {
+    background: var(--lora-surface);
+}
+
+[data-theme="dark"] .file-tag.fp {
+    background: oklch(0.55 0.12 250 / 0.15);
+    color: oklch(0.7 0.12 250);
+}
+
+[data-theme="dark"] .file-tag.size {
+    background: oklch(0.5 0.08 160 / 0.15);
+    color: oklch(0.65 0.08 160);
+}
+
+/* Textarea for multi-URL input */
+#modelUrl {
+    width: 100%;
+    padding: 8px;
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-xs);
+    background: var(--bg-color);
+    color: var(--text-color);
+    font-family: var(--font-mono);
+    font-size: 0.9em;
+    resize: vertical;
+    line-height: 1.5;
+}
+
+.input-hint {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    color: var(--text-color);
+    opacity: 0.7;
+    font-size: 0.85em;
+    margin-top: 6px;
+}
+
+.input-hint i {
+    color: var(--lora-accent);
+}
+
+/* Batch Preview List */
+.batch-preview-list {
+    max-height: 400px;
+    overflow-y: auto;
+    margin: var(--space-2) 0;
+    display: flex;
+    flex-direction: column;
+    gap: 1px;
+    background: var(--border-color);
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-sm);
+}
+
+.batch-preview-item {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    padding: 10px 12px;
+    background: var(--bg-color);
+}
+
+.batch-preview-item:first-child {
+    border-radius: var(--border-radius-sm) var(--border-radius-sm) 0 0;
+}
+
+.batch-preview-item:last-child {
+    border-radius: 0 0 var(--border-radius-sm) var(--border-radius-sm);
+}
+
+.batch-preview-item:only-child {
+    border-radius: var(--border-radius-sm);
+}
+
+.batch-preview-thumbnail {
+    width: 48px;
+    height: 48px;
+    flex-shrink: 0;
+    border-radius: var(--border-radius-xs);
+    overflow: hidden;
+    background: var(--lora-surface);
+}
+
+.batch-preview-thumbnail img {
+    width: 100%;
+    height: 100%;
+    object-fit: cover;
+}
+
+.batch-preview-icon {
+    width: 48px;
+    height: 48px;
+    flex-shrink: 0;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    color: var(--lora-error);
+    font-size: 1.2em;
+}
+
+.batch-preview-info {
+    flex: 1;
+    min-width: 0;
+}
+
+.batch-preview-name {
+    font-weight: 500;
+    color: var(--text-color);
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
+.batch-preview-meta {
+    display: flex;
+    gap: 8px;
+    font-size: 0.85em;
+    color: var(--text-color);
+    opacity: 0.7;
+    margin-top: 2px;
+}
+
+.batch-preview-error-text {
+    color: var(--lora-error);
+    opacity: 1;
+}
+
+.batch-preview-local-badge {
+    color: var(--lora-accent);
+    opacity: 1;
+}
+
+.batch-preview-local {
+    opacity: 0.6;
+}
+
+.batch-preview-change-version {
+    flex-shrink: 0;
+    font-size: 0.85em;
+    padding: 4px 10px;
+}
+
+.batch-preview-remove {
+    flex-shrink: 0;
+    background: none;
+    border: none;
+    color: var(--text-color);
+    opacity: 0.5;
+    cursor: pointer;
+    padding: 4px 8px;
+    font-size: 1em;
+}
+
+.batch-preview-remove:hover {
+    opacity: 1;
+    color: var(--lora-error);
+}
+
+.batch-preview-error {
+    background: oklch(0.5 0.15 25 / 0.05);
+}
+
+[data-theme="dark"] .batch-preview-item {
+    background: var(--lora-surface);
 }

static/css/components/modal/example-access-modal.css

@@ -20,12 +20,12 @@
     border: 1px solid var(--lora-border);
     background-color: var(--lora-surface);
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 .example-option-btn:hover {
     transform: translateY(-2px);
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
     border-color: var(--lora-accent);
 }
 
@@ -68,5 +68,5 @@
 
 /* Dark theme adjustments */
 [data-theme="dark"] .example-option-btn:hover {
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.25);
+    box-shadow: var(--shadow-elevated);
 }

static/css/components/modal/help-modal.css

@@ -32,7 +32,7 @@
   color: var(--text-color);
   cursor: pointer;
   font-weight: 500;
-  transition: all 0.2s;
+  transition: var(--transition-base);
   opacity: 0.7;
 }
 
@@ -150,7 +150,7 @@
   margin-left: 8px;
   vertical-align: middle;
   animation: fadeIn 0.5s ease-in-out;
-  box-shadow: 0 1px 3px rgba(0, 0, 0, 0.2);
+  box-shadow: var(--shadow-sm);
   text-transform: uppercase;
   letter-spacing: 0.5px;
 }
@@ -164,7 +164,7 @@
 
 /* Dark theme adjustments for new content badge */
 [data-theme="dark"] .new-content-badge {
-  box-shadow: 0 1px 3px rgba(0, 0, 0, 0.4);
+  box-shadow: var(--shadow-lg);
 }
 
 /* Update video list styles */
@@ -210,7 +210,7 @@
   margin-left: 10px;
   vertical-align: middle;
   animation: fadeIn 0.5s ease-in-out;
-  box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+  box-shadow: var(--shadow-md);
 }
 
 .update-date-badge i {
@@ -225,7 +225,7 @@
 
 /* Dark theme adjustments */
 [data-theme="dark"] .update-date-badge {
-  box-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
+  box-shadow: var(--shadow-md);
 }
 
 /* Privacy-friendly video embed styles */
@@ -281,7 +281,7 @@
   border-radius: var(--border-radius-sm);
   font-weight: 500;
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: var(--transition-base);
   background-color: var(--lora-accent);
   color: white;
   text-decoration: none;
@@ -303,5 +303,5 @@
 
 /* Dark theme adjustments */
 [data-theme="dark"] .video-container {
-  background-color: rgba(255, 255, 255, 0.03);
+  background-color: var(--surface-hover);
 }

static/css/components/modal/settings-modal.css

@@ -10,7 +10,7 @@
     align-items: center;
     justify-content: center;
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .settings-toggle:hover {
@@ -81,7 +81,7 @@
     font-weight: 500;
     cursor: pointer;
     border-radius: var(--border-radius-xs);
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     margin-bottom: 4px;
 }
 
@@ -154,7 +154,7 @@
     background-color: var(--lora-surface);
     color: var(--text-color);
     font-size: 0.9em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .settings-search-input:focus {
@@ -183,7 +183,7 @@
     justify-content: center;
     font-size: 0.7em;
     opacity: 0.6;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .settings-search-clear:hover {
@@ -289,7 +289,7 @@
     align-items: center;
     justify-content: center;
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     text-decoration: none;
     position: relative;
 }
@@ -335,7 +335,12 @@
     }
 }
 
-/* API key input specific styles */
+/* API key input — CSS masking (prevents Chrome password manager triggers) */
+.api-key-masked {
+    -webkit-text-security: disc;
+}
+
+/* API key input specific styles (shared with proxy password) */
 .api-key-input {
     width: 100%; /* Take full width of parent */
     position: relative;
@@ -345,7 +350,7 @@
 
 .api-key-input input {
     width: 100%;
-    padding: 6px 40px 6px 10px; /* Add left padding */
+    padding: 6px 40px 6px 10px; /* Right padding for eye button */
     height: 32px;
     box-sizing: border-box;
     border-radius: var(--border-radius-xs);
@@ -353,6 +358,13 @@
     background-color: var(--lora-surface);
     color: var(--text-color);
     font-size: 0.95em;
+    transition: border-color 0.2s ease, box-shadow 0.2s ease;
+}
+
+.api-key-input input:focus {
+    border-color: var(--lora-accent);
+    outline: none;
+    box-shadow: 0 0 0 2px rgba(var(--lora-accent-rgb, 79, 70, 229), 0.1);
 }
 
 .api-key-input .toggle-visibility {
@@ -364,12 +376,98 @@
     opacity: 0.6;
     cursor: pointer;
     padding: 4px 8px;
+    transition: opacity 0.2s ease;
 }
 
 .api-key-input .toggle-visibility:hover {
     opacity: 1;
 }
 
+/* API key item — stack status/edit views vertically for smooth cross-fade */
+.api-key-item .setting-control {
+    flex-direction: column;
+    align-items: flex-end;
+}
+
+/* API key status display (shown when not editing) */
+.api-key-status {
+    display: flex;
+    align-items: center;
+    gap: 10px;
+    width: 100%;
+    justify-content: flex-end;
+    transition: opacity 0.2s ease, transform 0.2s ease, max-height 0.25s ease;
+    max-height: 80px;
+    overflow: hidden;
+}
+
+.api-key-status.is-hidden {
+    opacity: 0;
+    max-height: 0;
+    transform: translateY(-4px);
+    pointer-events: none;
+    margin: 0;
+}
+
+.api-key-status-text {
+    display: inline-flex;
+    align-items: center;
+    gap: 4px;
+    font-size: 0.95em;
+    white-space: nowrap;
+    transition: color 0.2s ease;
+}
+
+/* Status color modifiers — replace inline styles */
+.api-key-status--configured .fa-check-circle {
+    color: var(--lora-success);
+}
+
+.api-key-status--unconfigured .fa-times-circle {
+    color: var(--lora-error);
+}
+
+/* Utility classes for status icon colors (used by JS) */
+.text-success {
+    color: var(--lora-success);
+}
+
+.text-error {
+    color: var(--lora-error);
+}
+
+/* API key inline edit container — flex row with input + buttons */
+.api-key-edit {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    width: 100%;
+    justify-content: flex-end;
+    transition: opacity 0.2s ease, transform 0.2s ease, max-height 0.25s ease;
+    max-height: 80px;
+    overflow: hidden;
+}
+
+.api-key-edit.is-hidden {
+    opacity: 0;
+    max-height: 0;
+    transform: translateY(-4px);
+    pointer-events: none;
+    margin: 0;
+}
+
+.api-key-edit .api-key-input {
+    flex: 1;
+    min-width: 0;
+}
+
+.api-key-edit .primary-btn,
+.api-key-edit .secondary-btn {
+    height: 32px;
+    flex-shrink: 0;
+    white-space: nowrap;
+}
+
 /* Text input wrapper styles for consistent input styling */
 .text-input-wrapper {
     width: 100%;
@@ -582,7 +680,7 @@
 }
 
 .priority-tags-example code {
-    font-family: var(--code-font, ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, 'Liberation Mono', 'Courier New', monospace);
+    font-family: var(--font-mono);
     background-color: rgba(var(--lora-accent-rgb, 79, 70, 229), 0.12);
     padding: 2px 6px;
     border-radius: var(--border-radius-xs);
@@ -614,7 +712,7 @@
     border-bottom: 2px solid transparent;
     color: var(--text-color);
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     opacity: 0.7;
 }
 
@@ -813,6 +911,120 @@
     outline: none;
 }
 
+/* Range Slider Control */
+.range-control {
+    width: 100%;
+    display: flex;
+    align-items: center;
+    gap: 10px;
+    justify-content: flex-end;
+}
+
+.range-control input[type="range"] {
+    --range-fill: 40%;
+    width: 120px;
+    height: 6px;
+    -webkit-appearance: none;
+    appearance: none;
+    background: linear-gradient(
+        to right,
+        var(--lora-accent) 0%,
+        var(--lora-accent) var(--range-fill),
+        var(--border-color) var(--range-fill),
+        var(--border-color) 100%
+    );
+    border-radius: var(--radius-full);
+    outline: none;
+    cursor: pointer;
+    flex-shrink: 0;
+    transition: background 0.3s ease;
+}
+
+.range-control input[type="range"]:focus-visible {
+    outline: none;
+}
+
+.range-control input[type="range"]::-webkit-slider-thumb {
+    -webkit-appearance: none;
+    appearance: none;
+    width: 18px;
+    height: 18px;
+    border-radius: 50%;
+    background: var(--lora-accent);
+    cursor: pointer;
+    border: 2px solid var(--lora-surface);
+    box-shadow: var(--shadow-md);
+    transition: transform var(--transition-bounce), box-shadow 0.2s ease;
+}
+
+.range-control input[type="range"]::-webkit-slider-thumb:hover {
+    transform: scale(1.2);
+    box-shadow: var(--shadow-md), 0 0 0 4px var(--color-accent-subtle);
+}
+
+.range-control input[type="range"]::-webkit-slider-thumb:active {
+    transform: scale(1.1);
+    box-shadow: var(--shadow-md), 0 0 0 6px var(--color-accent-subtle);
+}
+
+.range-control input[type="range"]:focus-visible::-webkit-slider-thumb {
+    box-shadow: var(--shadow-md), 0 0 0 3px var(--color-accent-subtle);
+}
+
+.range-control input[type="range"]::-moz-range-thumb {
+    width: 18px;
+    height: 18px;
+    border-radius: 50%;
+    background: var(--lora-accent);
+    cursor: pointer;
+    border: 2px solid var(--lora-surface);
+    box-shadow: var(--shadow-md);
+    transition: transform var(--transition-bounce), box-shadow 0.2s ease;
+}
+
+.range-control input[type="range"]::-moz-range-thumb:hover {
+    transform: scale(1.2);
+    box-shadow: var(--shadow-md), 0 0 0 4px var(--color-accent-subtle);
+}
+
+.range-control input[type="range"]::-moz-range-thumb:active {
+    transform: scale(1.1);
+    box-shadow: var(--shadow-md), 0 0 0 6px var(--color-accent-subtle);
+}
+
+.range-control input[type="range"]::-moz-range-track {
+    height: 6px;
+    border-radius: var(--radius-full);
+    background: var(--border-color);
+}
+
+.range-control .range-value {
+    min-width: 36px;
+    text-align: center;
+    font-size: 0.85em;
+    font-weight: 700;
+    color: var(--lora-accent);
+    font-variant-numeric: tabular-nums;
+    background: var(--surface-subtle);
+    padding: 2px 8px;
+    border-radius: var(--border-radius-xs);
+    letter-spacing: 0.02em;
+}
+
+[data-theme="dark"] .range-control input[type="range"] {
+    background: linear-gradient(
+        to right,
+        var(--lora-accent) 0%,
+        var(--lora-accent) var(--range-fill),
+        rgba(255, 255, 255, 0.15) var(--range-fill),
+        rgba(255, 255, 255, 0.15) 100%
+    );
+}
+
+[data-theme="dark"] .range-control input[type="range"]::-moz-range-track {
+    background: rgba(255, 255, 255, 0.15);
+}
+
 /* Toggle Switch */
 .toggle-switch {
     position: relative;
@@ -927,19 +1139,19 @@ input:checked + .toggle-slider:before {
 
 /* Path Template Settings Styles */
 .template-preview {
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid rgba(0, 0, 0, 0.1);
     border-radius: var(--border-radius-xs);
     padding: var(--space-1);
     margin-top: 8px;
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-size: 0.9em;
     color: var(--lora-accent);
     display: none;
 }
 
 [data-theme="dark"] .template-preview {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid var(--lora-border);
 }
 
@@ -974,7 +1186,7 @@ input:checked + .toggle-slider:before {
     border-radius: var(--border-radius-xs);
     cursor: pointer;
     font-size: 0.9em;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     height: 32px; /* Match other control heights */
 }
 
@@ -1030,7 +1242,7 @@ input:checked + .toggle-slider:before {
     display: flex;
     align-items: center;
     justify-content: center;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 .remove-mapping-btn:hover {
@@ -1146,7 +1358,7 @@ input:checked + .toggle-slider:before {
     color: white;
     padding: 2px 6px;
     border-radius: 3px;
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-size: 1em;
     font-weight: 500;
 }
@@ -1175,7 +1387,7 @@ input:checked + .toggle-slider:before {
     background-color: var(--lora-surface);
     color: var(--text-color);
     font-size: 0.95em;
-    font-family: monospace;
+    font-family: var(--font-mono);
     height: 24px;
     transition: border-color 0.2s;
 }
@@ -1277,7 +1489,7 @@ input:checked + .toggle-slider:before {
     border-radius: 6px;
     font-size: 14px;
     font-weight: normal;
-    font-family: 'Segoe UI', system-ui, -apple-system, sans-serif;
+    font-family: var(--font-body);
     white-space: normal;
     max-width: 220px;
     width: max-content;
@@ -1287,7 +1499,7 @@ input:checked + .toggle-slider:before {
     pointer-events: none;
     z-index: 10000;
     line-height: 1.4;
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3);
+    box-shadow: var(--shadow-elevated);
     text-transform: none;
 }
 
@@ -1309,7 +1521,7 @@ input:checked + .toggle-slider:before {
 /* Dark theme adjustments for tooltip - Fully opaque */
 [data-theme="dark"] .info-icon[data-tooltip]::after {
     background: rgba(40, 40, 40, 0.95);
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.5);
+    box-shadow: var(--shadow-dark-lg);
 }
 
 /* Extra Folder Paths - Single input layout */
@@ -1361,7 +1573,7 @@ input:checked + .toggle-slider:before {
     display: flex;
     align-items: center;
     justify-content: center;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     flex-shrink: 0;
 }
 

static/css/components/modal/support-modal.css

@@ -58,8 +58,6 @@
 }
 
 .support-section {
-    background: rgba(0, 0, 0, 0.02);
-    border: 1px solid rgba(0, 0, 0, 0.08);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
     margin-bottom: var(--space-2);
@@ -102,7 +100,7 @@
     border-radius: var(--border-radius-sm);
     text-decoration: none;
     color: var(--text-color);
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .social-link:hover {
@@ -122,14 +120,14 @@
     border-radius: var(--border-radius-sm);
     text-decoration: none;
     font-weight: 500;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     margin-top: var(--space-1);
 }
 
 .kofi-button:hover {
     background: #E04946;
     transform: translateY(-2px);
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 /* Patreon button style */
@@ -144,14 +142,14 @@
     border-radius: var(--border-radius-sm);
     text-decoration: none;
     font-weight: 500;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     margin-top: var(--space-1);
 }
 
 .patreon-button:hover {
     background: #E04946;
     transform: translateY(-2px);
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 /* QR Code section styles */
@@ -191,7 +189,7 @@
     max-width: 80%;
     height: auto;
     border-radius: var(--border-radius-sm);
-    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
     border: 1px solid var(--lora-border);
     aspect-ratio: 1/1; /* Ensure proper aspect ratio for the square QR code */
 }
@@ -214,7 +212,7 @@
     align-items: center;
     justify-content: center;
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .support-toggle:hover {
@@ -258,12 +256,12 @@
     color: white; /* Icon color changes to white on hover */
 }
 
-/* 增强hover状态的视觉反馈 */
+/* Enhanced hover visual feedback */
 .social-link:hover,
 .update-link:hover,
 .folder-item:hover {
     border-color: var(--lora-accent);
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 /* Supporters Section Styles */
@@ -349,14 +347,14 @@
     border: 1px solid var(--border-color);
     border-left: 3px solid var(--lora-accent);
     border-radius: var(--border-radius-sm);
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     cursor: default;
 }
 
 .supporter-special-card:hover {
     border-color: var(--lora-accent);
     border-left-color: var(--lora-accent);
-    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-header);
     transform: translateX(4px);
 }
 
@@ -441,7 +439,7 @@
     font-size: 0.95em;
     color: var(--text-color);
     opacity: 0.85;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     white-space: nowrap;
     cursor: default;
 }

static/css/components/modal/update-modal.css

@@ -123,7 +123,7 @@
 }
 
 .version-number {
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-weight: 600;
 }
 
@@ -136,7 +136,7 @@
     font-size: 0.85em;
     opacity: 0.7;
     margin-top: 4px;
-    font-family: monospace;
+    font-family: var(--font-mono);
     color: var(--text-color);
 }
 
@@ -160,7 +160,7 @@
     border-radius: var(--border-radius-sm);
     text-decoration: none;
     color: var(--text-color);
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .update-link:hover {
@@ -171,7 +171,7 @@
 
 /* Update progress styles */
 .update-progress {
-    background: rgba(0, 0, 0, 0.03);
+    background: var(--surface-subtle);
     border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
@@ -179,7 +179,7 @@
 }
 
 [data-theme="dark"] .update-progress {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
 }
 
 .progress-info {
@@ -234,8 +234,6 @@
 
 /* Changelog section */
 .changelog-section {
-    background: rgba(0, 0, 0, 0.02);
-    border: 1px solid rgba(0, 0, 0, 0.08);
     border-radius: var(--border-radius-sm);
     padding: var(--space-3);
 }
@@ -334,7 +332,7 @@
     background: rgba(0, 0, 0, 0.05);
     padding: 2px 4px;
     border-radius: 3px;
-    font-family: monospace;
+    font-family: var(--font-mono);
     font-size: 0.9em;
 }
 
@@ -429,7 +427,7 @@
 }
 
 [data-theme="dark"] .banner-history-item {
-    background: rgba(255, 255, 255, 0.03);
+    background: var(--surface-subtle);
 }
 
 .banner-history-title {