refactor(download): rename locationStep id to downloadLocationStep

The download modal's step shared the 'locationStep' id with the import
modal, so getElementById('locationStep') could resolve to the wrong
element depending on template include order. The import flow relied on
an injected display:block !important rule to work around it.

Rename the download modal's step id and update all references so each
modal owns a unique step id.

.gitignore

@@ -25,6 +25,7 @@ model_cache/
 reasonix.toml
 .reasonix/
 .codegraph/
+.playwright-mcp/
 
 # Vue widgets development cache (but keep build output)
 vue-widgets/node_modules/

AGENTS.md

@@ -31,7 +31,7 @@ COVERAGE_FILE=coverage/backend/.coverage pytest \
   --cov-report=xml:coverage/backend/coverage.xml
 ```
 
-### Frontend Development (Standalone Web UI)
+### Frontend Development (LoRA Manager Web UI)
 
 ```bash
 npm install
@@ -137,7 +137,13 @@ npm run test:coverage       # Generate coverage report
 - Dual mode: ComfyUI plugin (folder_paths) vs standalone (settings.json)
 - Detection: `os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1"`
 - Run `python scripts/sync_translation_keys.py` after adding UI strings to `locales/en.json`
-- Symlinks require normalized paths
+- Symlinks require normalized paths.
+  **Business paths vs real paths**: All stored paths and operation routing use the
+  original paths as they appear under configured model roots — symlinks are NOT
+  resolved. `os.path.realpath` is only for scanner dedup and the symlink cache.
+  Any path passed to `os.remove`/`os.rename`/`shutil.move` or validated by a
+  containment check MUST use the business path (i.e. `os.path.abspath`, not
+  `realpath`).
 
 ## Git / Commit Messages
 
@@ -148,9 +154,9 @@ npm run test:coverage       # Generate coverage report
 
 ## Frontend UI Architecture
 
-### 1. Standalone Web UI
+### 1. LoRA Manager Web UI
 - Location: `./static/` and `./templates/`
-- Tech: Vanilla JS + CSS, served by standalone server
+- Tech: Vanilla JS + CSS, served by the hosting server (ComfyUI app in plugin mode, `standalone.py` in standalone mode)
 - Tests via npm in root directory
 
 ### 2. ComfyUI Custom Node Widgets

__init__.py

@@ -17,6 +17,8 @@ try:  # pragma: no cover - import fallback for pytest collection
     from .py.nodes.lora_cycler import LoraCyclerLM
     from .py.nodes.lora_info import LoraInfoLM
     from .py.nodes.lora_syntax_to_path import LoraSyntaxToPath
+    from .py.nodes.create_hook_lora import CreateHookLoraLM
+    from .py.nodes.metadata_overwrite import MetadataOverwriteLM
     from .py.metadata_collector import init as init_metadata_collector
 except (
     ImportError
@@ -62,6 +64,12 @@ except (
     LoraSyntaxToPath = importlib.import_module(
         "py.nodes.lora_syntax_to_path"
     ).LoraSyntaxToPath
+    CreateHookLoraLM = importlib.import_module(
+        "py.nodes.create_hook_lora"
+    ).CreateHookLoraLM
+    MetadataOverwriteLM = importlib.import_module(
+        "py.nodes.metadata_overwrite"
+    ).MetadataOverwriteLM
     init_metadata_collector = importlib.import_module("py.metadata_collector").init
 
 NODE_CLASS_MAPPINGS = {
@@ -83,6 +91,8 @@ NODE_CLASS_MAPPINGS = {
     LoraCyclerLM.NAME: LoraCyclerLM,
     LoraInfoLM.NAME: LoraInfoLM,
     LoraSyntaxToPath.NAME: LoraSyntaxToPath,
+    CreateHookLoraLM.NAME: CreateHookLoraLM,
+    MetadataOverwriteLM.NAME: MetadataOverwriteLM,
 }
 
 WEB_DIRECTORY = "./web/comfyui"

locales/de.json

@@ -449,6 +449,12 @@
                 "compact": "7 (1080p), 8 (2K), 10 (4K)"
             },
             "displayDensityWarning": "Warnung: Höhere Dichten können bei Systemen mit begrenzten Ressourcen zu Performance-Problemen führen.",
+            "recipesLayout": "Rezepte-Layout",
+            "recipesLayoutHelp": "Wählen Sie, wie Rezeptkarten angeordnet werden: ein einheitliches Raster oder ein Masonry-Layout (Pinterest-Stil), das das Seitenverhältnis jedes Bildes beibehält.",
+            "recipesLayoutOptions": {
+                "grid": "Raster",
+                "masonry": "Masonry"
+            },
             "showFolderSidebar": "Ordner-Seitenleiste anzeigen",
             "showFolderSidebarHelp": "Blenden Sie die Ordner-Navigationsleiste auf den Modellseiten ein oder aus. Wenn deaktiviert, bleiben Seitenleiste und Hoverbereich verborgen.",
             "cardInfoDisplay": "Karten-Info-Anzeige",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "Benutzerdefiniert (OpenAI-kompatibel)"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "Lokale Versionen",
                 "versionsCountDesc": "Meiste Versionen zuerst",
                 "versionsCountAsc": "Wenigste Versionen zuerst",
-        "versionIdDesc": "Neueste Version zuerst"
+                "versionIdDesc": "Neueste Version zuerst",
+                "random": "Zufällig",
+                "randomAction": "Zufällig mischen"
             },
             "refresh": {
                 "title": "Modelliste aktualisieren",
@@ -771,6 +780,8 @@
             "deleteAll": "Ausgewählte löschen",
             "downloadMissingLoras": "Fehlende LoRAs herunterladen",
             "downloadExamples": "Beispielbilder herunterladen",
+            "downloadMissingExamples": "Fehlende herunterladen",
+            "reprocessExamples": "Alle erneut verarbeiten",
             "clear": "Auswahl löschen",
             "skipMetadataRefreshCount": "Überspringen（{count} Modelle）",
             "resumeMetadataRefreshCount": "Fortsetzen（{count} Modelle）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "An Workflow senden (Ersetzen)",
             "openExamples": "Beispiele-Ordner öffnen",
             "downloadExamples": "Beispielbilder herunterladen",
+            "downloadMissingExamples": "Fehlende herunterladen",
+            "reprocessExamples": "Alle erneut verarbeiten",
             "replacePreview": "Vorschau ersetzen",
             "setContentRating": "Inhaltsbewertung festlegen",
             "moveToFolder": "In Ordner verschieben",
@@ -1548,6 +1561,7 @@
                 "empty": "Noch keine Versionshistorie für dieses Modell vorhanden.",
                 "error": "Versionen konnten nicht geladen werden.",
                 "missingModelId": "Für dieses Modell ist keine Civitai-Model-ID vorhanden.",
+                "hfGroupInfo": "Dies ist eine HuggingFace-Modellgruppe. Öffnen Sie die Bibliothek, um alle Versionen im Raster zu sehen.",
                 "confirm": {
                     "delete": "Diese Version aus Ihrer Bibliothek löschen?"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "CSV herunterladen",
             "columnModelName": "Modellname",
             "columnError": "Fehler"
+        },
+        "downloadBatchSummary": {
+            "title": "Zusammenfassung des Batch-Downloads",
+            "statSuccess": "Erfolgreich",
+            "statFailed": "Fehlgeschlagen",
+            "statTotal": "Gesamt",
+            "successMessage": "Alle {count} Modelle erfolgreich heruntergeladen",
+            "completedWithErrors": "Abgeschlossen, aber mit Fehlern",
+            "failed": "Download fehlgeschlagen",
+            "failedItems": "Fehlgeschlagene Elemente ({count})",
+            "columnName": "Modellname",
+            "columnError": "Fehler",
+            "close": "Schließen",
+            "copyReport": "Bericht kopieren",
+            "retryFailed": "Fehlgeschlagene erneut versuchen ({count})"
         }
     },
     "modelTags": {
@@ -1751,6 +1780,12 @@
         "checkingMessage": "Bitte warten Sie, während wir nach der neuesten Version suchen.",
         "showNotifications": "Update-Benachrichtigungen anzeigen",
         "latestBadge": "Neueste",
+        "latestMain": "Main-Branch",
+        "channel": "Update-Kanal",
+        "channels": {
+            "release": "Release",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "Update wird vorbereitet...",
             "installing": "Update wird installiert...",
@@ -1771,6 +1806,15 @@
             "warning": "Warnung: Nightly Builds können experimentelle Funktionen enthalten und könnten instabil sein.",
             "enable": "Nightly Updates aktivieren"
         },
+        "channelSwitch": {
+            "nightlyTitle": "Zu Nightly-Kanal wechseln",
+            "nightlyMessage": "Der Wechsel zu Nightly initialisiert ein Git-Repository und verfolgt die neuesten Commits des main-Branches. Updates sind häufiger, können aber instabil sein. Sie können jederzeit zu Release zurückwechseln.",
+            "releaseTitle": "Zu Release-Kanal wechseln",
+            "releaseMessage": "Der Wechsel zu Release checkt den neuesten stabilen Versions-Tag aus. Sie können jederzeit zu Nightly zurückwechseln.",
+            "switching": "Wechsle zu {channel}-Kanal...",
+            "completed": "Erfolgreich zu {channel}-Kanal gewechselt",
+            "failed": "Kanalwechsel fehlgeschlagen"
+        },
         "banners": {
             "recent": "Neueste Mitteilungen",
             "empty": "Keine aktuellen Banner verfügbar.",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "Voreinstellungsname darf maximal {max} Zeichen haben",
             "presetNameInvalidChars": "Voreinstellungsname enthält ungültige Zeichen",
             "presetNameExists": "Eine Voreinstellung mit diesem Namen existiert bereits",
-      "maxPresetsReached": "Maximal {max} Voreinstellungen erlaubt. Löschen Sie eine, um weitere hinzuzufügen.",
             "presetNotFound": "Voreinstellung nicht gefunden",
             "invalidPreset": "Ungültige Voreinstellungsdaten",
             "deletePresetFailed": "Fehler beim Löschen der Voreinstellung",

locales/en.json

@@ -449,6 +449,12 @@
         "compact": "7 (1080p), 8 (2K), 10 (4K)"
       },
       "displayDensityWarning": "Warning: Higher densities may cause performance issues on systems with limited resources.",
+      "recipesLayout": "Recipes Layout",
+      "recipesLayoutHelp": "Choose how recipe cards are arranged: a uniform grid or a masonry (Pinterest-style) layout that preserves each image's aspect ratio.",
+      "recipesLayoutOptions": {
+        "grid": "Grid",
+        "masonry": "Masonry"
+      },
       "showFolderSidebar": "Show Folder Sidebar",
       "showFolderSidebarHelp": "Toggle the folder navigation sidebar on model pages. When disabled, the sidebar and hover area stay hidden.",
       "cardInfoDisplay": "Card Info Display",
@@ -678,6 +684,7 @@
         "deepseek": "DeepSeek",
         "groq": "Groq",
         "openrouter": "OpenRouter",
+        "google": "Gemini",
         "opencode-go": "OpenCode Go",
         "custom": "Custom (OpenAI-compatible)"
       },
@@ -714,7 +721,9 @@
         "versionsCount": "Local Versions",
         "versionsCountDesc": "Most versions first",
         "versionsCountAsc": "Fewest versions first",
-        "versionIdDesc": "Newest version first"
+        "versionIdDesc": "Newest version first",
+        "random": "Random",
+        "randomAction": "Randomize (shuffle)"
       },
       "refresh": {
         "title": "Refresh model list",
@@ -771,6 +780,8 @@
       "deleteAll": "Delete Selected",
       "downloadMissingLoras": "Download Missing LoRAs",
       "downloadExamples": "Download Example Images",
+      "downloadMissingExamples": "Download Missing",
+      "reprocessExamples": "Re-process All",
       "clear": "Clear Selection",
       "skipMetadataRefreshCount": "Skip ({count} models)",
       "resumeMetadataRefreshCount": "Resume ({count} models)",
@@ -806,6 +817,8 @@
       "sendToWorkflowReplace": "Send to Workflow (Replace)",
       "openExamples": "Open Examples Folder",
       "downloadExamples": "Download Example Images",
+      "downloadMissingExamples": "Download Missing",
+      "reprocessExamples": "Re-process All",
       "replacePreview": "Replace Preview",
       "setContentRating": "Set Content Rating",
       "moveToFolder": "Move to Folder",
@@ -1548,6 +1561,7 @@
         "empty": "No version history available for this model yet.",
         "error": "Failed to load versions.",
         "missingModelId": "This model is missing a Civitai model id.",
+        "hfGroupInfo": "This is a HuggingFace model group. Open the library to see all versions in the grid.",
         "confirm": {
           "delete": "Delete this version from your library?"
         },
@@ -1574,6 +1588,21 @@
       "downloadCsv": "Download CSV",
       "columnModelName": "Model Name",
       "columnError": "Error"
+    },
+    "downloadBatchSummary": {
+      "title": "Batch Download Summary",
+      "statSuccess": "Success",
+      "statFailed": "Failed",
+      "statTotal": "Total",
+      "successMessage": "All {count} models downloaded successfully",
+      "completedWithErrors": "Completed with errors",
+      "failed": "Download failed",
+      "failedItems": "Failed Items ({count})",
+      "columnName": "Model Name",
+      "columnError": "Error",
+      "close": "Close",
+      "copyReport": "Copy Report",
+      "retryFailed": "Retry Failed ({count})"
     }
   },
   "modelTags": {
@@ -1751,6 +1780,12 @@
     "checkingMessage": "Please wait while we check for the latest version.",
     "showNotifications": "Show update notifications",
     "latestBadge": "Latest",
+    "latestMain": "Latest main",
+    "channel": "Update Channel",
+    "channels": {
+      "release": "Release",
+      "nightly": "Nightly"
+    },
     "updateProgress": {
       "preparing": "Preparing update...",
       "installing": "Installing update...",
@@ -1771,6 +1806,15 @@
       "warning": "Warning: Nightly builds may contain experimental features and could be unstable.",
       "enable": "Enable Nightly Updates"
     },
+    "channelSwitch": {
+      "nightlyTitle": "Switch to Nightly Channel",
+      "nightlyMessage": "Switching to Nightly will initialize a Git repository and track the latest main branch commits. Updates will be more frequent but may be unstable. You can switch back to Release at any time.",
+      "releaseTitle": "Switch to Release Channel",
+      "releaseMessage": "Switching to Release will checkout the latest stable release tag. You can switch back to Nightly at any time.",
+      "switching": "Switching to {channel} channel...",
+      "completed": "Successfully switched to {channel} channel",
+      "failed": "Failed to switch channel"
+    },
     "banners": {
       "recent": "Recent messages",
       "empty": "No recent banners yet.",
@@ -2015,7 +2059,6 @@
       "presetNameTooLong": "Preset name must be {max} characters or less",
       "presetNameInvalidChars": "Preset name contains invalid characters",
       "presetNameExists": "A preset with this name already exists",
-      "maxPresetsReached": "Maximum {max} presets allowed. Delete one to add more.",
       "presetNotFound": "Preset not found",
       "invalidPreset": "Invalid preset data",
       "deletePresetFailed": "Failed to delete preset",

locales/es.json

@@ -449,6 +449,12 @@
                 "compact": "7 (1080p), 8 (2K), 10 (4K)"
             },
             "displayDensityWarning": "Advertencia: Densidades más altas pueden causar problemas de rendimiento en sistemas con recursos limitados.",
+            "recipesLayout": "Diseño de recetas",
+            "recipesLayoutHelp": "Elige cómo se organizan las tarjetas de recetas: una cuadrícula uniforme o un diseño masonry (estilo Pinterest) que conserva la proporción de aspecto de cada imagen.",
+            "recipesLayoutOptions": {
+                "grid": "Cuadrícula",
+                "masonry": "Masonry"
+            },
             "showFolderSidebar": "Mostrar barra lateral de carpetas",
             "showFolderSidebarHelp": "Activa o desactiva la barra lateral de navegación de carpetas en las páginas de modelos. Cuando está desactivada, la barra lateral y el área de desplazamiento permanecen ocultas.",
             "cardInfoDisplay": "Visualización de información de tarjeta",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "Personalizado (compatible con OpenAI)"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "Versiones locales",
                 "versionsCountDesc": "Más versiones primero",
                 "versionsCountAsc": "Menos versiones primero",
-        "versionIdDesc": "Versión más nueva primero"
+                "versionIdDesc": "Versión más nueva primero",
+                "random": "Aleatorio",
+                "randomAction": "Aleatorizar (barajar)"
             },
             "refresh": {
                 "title": "Actualizar lista de modelos",
@@ -771,6 +780,8 @@
             "deleteAll": "Eliminar seleccionados",
             "downloadMissingLoras": "Descargar LoRAs faltantes",
             "downloadExamples": "Descargar imágenes de ejemplo",
+            "downloadMissingExamples": "Descargar faltantes",
+            "reprocessExamples": "Reprocesar todo",
             "clear": "Limpiar selección",
             "skipMetadataRefreshCount": "Omitir（{count} modelos）",
             "resumeMetadataRefreshCount": "Reanudar（{count} modelos）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "Enviar al flujo de trabajo (Reemplazar)",
             "openExamples": "Abrir carpeta de ejemplos",
             "downloadExamples": "Descargar imágenes de ejemplo",
+            "downloadMissingExamples": "Descargar faltantes",
+            "reprocessExamples": "Reprocesar todo",
             "replacePreview": "Reemplazar vista previa",
             "setContentRating": "Establecer clasificación de contenido",
             "moveToFolder": "Mover a carpeta",
@@ -1548,6 +1561,7 @@
                 "empty": "Aún no hay historial de versiones para este modelo.",
                 "error": "No se pudieron cargar las versiones.",
                 "missingModelId": "Este modelo no tiene un ID de modelo de Civitai.",
+                "hfGroupInfo": "Este es un grupo de modelos de HuggingFace. Abra la biblioteca para ver todas las versiones en la cuadrícula.",
                 "confirm": {
                     "delete": "¿Eliminar esta versión de tu biblioteca?"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "Descargar CSV",
             "columnModelName": "Nombre del modelo",
             "columnError": "Error"
+        },
+        "downloadBatchSummary": {
+            "title": "Resumen de descarga por lotes",
+            "statSuccess": "Correctos",
+            "statFailed": "Fallidos",
+            "statTotal": "Total",
+            "successMessage": "Todos los {count} modelos se descargaron correctamente",
+            "completedWithErrors": "Completado con errores",
+            "failed": "Descarga fallida",
+            "failedItems": "Elementos fallidos ({count})",
+            "columnName": "Nombre del modelo",
+            "columnError": "Error",
+            "close": "Cerrar",
+            "copyReport": "Copiar informe",
+            "retryFailed": "Reintentar fallidos ({count})"
         }
     },
     "modelTags": {
@@ -1750,7 +1779,13 @@
         "checkingUpdates": "Comprobando actualizaciones...",
         "checkingMessage": "Por favor espera mientras comprobamos la última versión.",
         "showNotifications": "Mostrar notificaciones de actualización",
-    "latestBadge": "Último",
+        "latestBadge": "Última",
+        "latestMain": "Rama main",
+        "channel": "Canal de actualizacion",
+        "channels": {
+            "release": "Release",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "Preparando actualización...",
             "installing": "Instalando actualización...",
@@ -1771,6 +1806,15 @@
             "warning": "Advertencia: Las compilaciones nocturnas pueden contener características experimentales y podrían ser inestables.",
             "enable": "Habilitar actualizaciones nocturnas"
         },
+        "channelSwitch": {
+            "nightlyTitle": "Cambiar a canal Nightly",
+            "nightlyMessage": "Cambiar a Nightly inicializara un repositorio Git y seguira los ultimos commits de la rama main. Las actualizaciones son mas frecuentes pero pueden ser inestables. Puede volver a Release en cualquier momento.",
+            "releaseTitle": "Cambiar a canal Release",
+            "releaseMessage": "Cambiar a Release hara checkout de la ultima etiqueta de version estable. Puede volver a Nightly en cualquier momento.",
+            "switching": "Cambiando a canal {channel}...",
+            "completed": "Cambio a canal {channel} exitoso",
+            "failed": "Error al cambiar de canal"
+        },
         "banners": {
             "recent": "Notificaciones recientes",
             "empty": "No hay banners recientes.",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "El nombre del preajuste debe tener {max} caracteres o menos",
             "presetNameInvalidChars": "El nombre del preajuste contiene caracteres inválidos",
             "presetNameExists": "Ya existe un preajuste con este nombre",
-      "maxPresetsReached": "Máximo {max} preajustes permitidos. Elimine uno para agregar más.",
             "presetNotFound": "Preajuste no encontrado",
             "invalidPreset": "Datos de preajuste inválidos",
             "deletePresetFailed": "Error al eliminar el preajuste",

locales/fr.json

@@ -449,6 +449,12 @@
                 "compact": "7 (1080p), 8 (2K), 10 (4K)"
             },
             "displayDensityWarning": "Attention : Des densités plus élevées peuvent causer des problèmes de performance sur les systèmes avec des ressources limitées.",
+            "recipesLayout": "Disposition des recettes",
+            "recipesLayoutHelp": "Choisissez comment les cartes de recettes sont organisées : une grille uniforme ou une disposition masonry (style Pinterest) qui préserve le rapport d'aspect de chaque image.",
+            "recipesLayoutOptions": {
+                "grid": "Grille",
+                "masonry": "Masonry"
+            },
             "showFolderSidebar": "Afficher la barre latérale des dossiers",
             "showFolderSidebarHelp": "Activez ou désactivez la barre latérale de navigation des dossiers sur les pages de modèles. Lorsqu'elle est désactivée, la barre latérale et la zone de survol restent masquées.",
             "cardInfoDisplay": "Affichage des informations de carte",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "Personnalisé (compatible OpenAI)"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "Versions locales",
                 "versionsCountDesc": "Plus de versions d'abord",
                 "versionsCountAsc": "Moins de versions d'abord",
-        "versionIdDesc": "Version la plus récente d'abord"
+                "versionIdDesc": "Version la plus récente d'abord",
+                "random": "Aléatoire",
+                "randomAction": "Aléatoire (mélanger)"
             },
             "refresh": {
                 "title": "Actualiser la liste des modèles",
@@ -771,6 +780,8 @@
             "deleteAll": "Supprimer la sélection",
             "downloadMissingLoras": "Télécharger les LoRAs manquants",
             "downloadExamples": "Télécharger les images d'exemple",
+            "downloadMissingExamples": "Télécharger les manquantes",
+            "reprocessExamples": "Tout retraiter",
             "clear": "Effacer la sélection",
             "skipMetadataRefreshCount": "Ignorer（{count} modèles）",
             "resumeMetadataRefreshCount": "Reprendre（{count} modèles）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "Envoyer vers le workflow (Remplacer)",
             "openExamples": "Ouvrir le dossier d'exemples",
             "downloadExamples": "Télécharger les images d'exemple",
+            "downloadMissingExamples": "Télécharger les manquantes",
+            "reprocessExamples": "Tout retraiter",
             "replacePreview": "Remplacer l'aperçu",
             "setContentRating": "Définir la classification du contenu",
             "moveToFolder": "Déplacer vers un dossier",
@@ -1548,6 +1561,7 @@
                 "empty": "Aucun historique de versions n'est disponible pour ce modèle pour le moment.",
                 "error": "Échec du chargement des versions.",
                 "missingModelId": "Ce modèle ne possède pas d'identifiant de modèle Civitai.",
+                "hfGroupInfo": "Ceci est un groupe de modèles HuggingFace. Ouvrez la bibliothèque pour voir toutes les versions dans la grille.",
                 "confirm": {
                     "delete": "Supprimer cette version de votre bibliothèque ?"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "Télécharger CSV",
             "columnModelName": "Nom du modèle",
             "columnError": "Erreur"
+        },
+        "downloadBatchSummary": {
+            "title": "Résumé du téléchargement groupé",
+            "statSuccess": "Réussis",
+            "statFailed": "Échoués",
+            "statTotal": "Total",
+            "successMessage": "Les {count} modèles ont été téléchargés avec succès",
+            "completedWithErrors": "Terminé avec des erreurs",
+            "failed": "Échec du téléchargement",
+            "failedItems": "Éléments échoués ({count})",
+            "columnName": "Nom du modèle",
+            "columnError": "Erreur",
+            "close": "Fermer",
+            "copyReport": "Copier le rapport",
+            "retryFailed": "Réessayer les échecs ({count})"
         }
     },
     "modelTags": {
@@ -1750,7 +1779,13 @@
         "checkingUpdates": "Vérification des mises à jour...",
         "checkingMessage": "Veuillez patienter pendant la vérification de la dernière version.",
         "showNotifications": "Afficher les notifications de mise à jour",
-    "latestBadge": "Dernier",
+        "latestBadge": "Dernière",
+        "latestMain": "Branche main",
+        "channel": "Canal de mise a jour",
+        "channels": {
+            "release": "Release",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "Préparation de la mise à jour...",
             "installing": "Installation de la mise à jour...",
@@ -1771,6 +1806,15 @@
             "warning": "Attention : Les versions nightly peuvent contenir des fonctionnalités expérimentales et être instables.",
             "enable": "Activer les mises à jour nightly"
         },
+        "channelSwitch": {
+            "nightlyTitle": "Passer au canal Nightly",
+            "nightlyMessage": "Passer a Nightly initialisera un depot Git et suivra les derniers commits de la branche main. Les mises a jour sont plus frequentes mais peuvent etre instables. Vous pouvez revenir a Release a tout moment.",
+            "releaseTitle": "Passer au canal Release",
+            "releaseMessage": "Passer a Release passera au dernier tag de version stable. Vous pouvez revenir a Nightly a tout moment.",
+            "switching": "Passage au canal {channel}...",
+            "completed": "Basculement vers le canal {channel} reussi",
+            "failed": "Echec du changement de canal"
+        },
         "banners": {
             "recent": "Messages récents",
             "empty": "Aucune bannière récente.",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "Le nom du préréglage doit contenir au maximum {max} caractères",
             "presetNameInvalidChars": "Le nom du préréglage contient des caractères invalides",
             "presetNameExists": "Un préréglage avec ce nom existe déjà",
-      "maxPresetsReached": "Maximum {max} préréglages autorisés. Supprimez-en un pour en ajouter plus.",
             "presetNotFound": "Préréglage non trouvé",
             "invalidPreset": "Données de préréglage invalides",
             "deletePresetFailed": "Échec de la suppression du préréglage",

locales/he.json

@@ -449,6 +449,12 @@
                 "compact": "7 (1080p), 8 (2K), 10 (4K)"
             },
             "displayDensityWarning": "אזהרה: צפיפויות גבוהות יותר עלולות לגרום לבעיות ביצועים במערכות עם משאבים מוגבלים.",
+            "recipesLayout": "פריסת מתכונים",
+            "recipesLayoutHelp": "בחר כיצד יסודרו כרטיסי המתכונים: רשת אחידה או פריסת Masonry (בסגנון Pinterest) השומרת על יחס הגובה-רוחב של כל תמונה.",
+            "recipesLayoutOptions": {
+                "grid": "רשת",
+                "masonry": "Masonry"
+            },
             "showFolderSidebar": "הצג סרגל צד תיקיות",
             "showFolderSidebarHelp": "הפעל או כבה את סרגל הצד לניווט תיקיות בדפי המודל. כאשר הוא כבוי, סרגל הצד ואזור הריחוף נשארים מוסתרים.",
             "cardInfoDisplay": "תצוגת מידע בכרטיס",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "מותאם אישית (תואם OpenAI)"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "גרסאות מקומיות",
                 "versionsCountDesc": "הכי הרבה גרסאות ראשונות",
                 "versionsCountAsc": "הכי מעט גרסאות ראשונות",
-        "versionIdDesc": "גרסה חדשה ביותר ראשונה"
+                "versionIdDesc": "גרסה חדשה ביותר ראשונה",
+                "random": "אקראי",
+                "randomAction": "ערבוב אקראי"
             },
             "refresh": {
                 "title": "רענן רשימת מודלים",
@@ -771,6 +780,8 @@
             "deleteAll": "מחק נבחרים",
             "downloadMissingLoras": "הורדת LoRAs חסרים",
             "downloadExamples": "הורד תמונות דוגמה",
+            "downloadMissingExamples": "הורדת חסרים",
+            "reprocessExamples": "עיבוד מחדש של הכול",
             "clear": "נקה בחירה",
             "skipMetadataRefreshCount": "דילוג（{count} מודלים）",
             "resumeMetadataRefreshCount": "המשך（{count} מודלים）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "שלח ל-Workflow (החלף)",
             "openExamples": "פתח תיקיית דוגמאות",
             "downloadExamples": "הורד תמונות דוגמה",
+            "downloadMissingExamples": "הורדת חסרים",
+            "reprocessExamples": "עיבוד מחדש של הכול",
             "replacePreview": "החלף תצוגה מקדימה",
             "setContentRating": "הגדר דירוג תוכן",
             "moveToFolder": "העבר לתיקייה",
@@ -1548,6 +1561,7 @@
                 "empty": "אין עדיין היסטוריית גרסאות למודל זה.",
                 "error": "טעינת הגרסאות נכשלה.",
                 "missingModelId": "למודל זה אין מזהה מודל של Civitai.",
+                "hfGroupInfo": "זוהי קבוצת דגמים של HuggingFace. פתח את הספרייה כדי לראות את כל הגרסאות ברשת.",
                 "confirm": {
                     "delete": "למחוק גרסה זו מהספרייה שלך?"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "הורד CSV",
             "columnModelName": "שם המודל",
             "columnError": "שגיאה"
+        },
+        "downloadBatchSummary": {
+            "title": "סיכום הורדה בכמות",
+            "statSuccess": "הצליחו",
+            "statFailed": "נכשלו",
+            "statTotal": "סה\"כ",
+            "successMessage": "כל {count} הדגמים הורדו בהצלחה",
+            "completedWithErrors": "הושלם עם שגיאות",
+            "failed": "ההורדה נכשלה",
+            "failedItems": "פריטים שנכשלו ({count})",
+            "columnName": "שם הדגם",
+            "columnError": "שגיאה",
+            "close": "סגור",
+            "copyReport": "העתק דוח",
+            "retryFailed": "נסה שוב ({count})"
         }
     },
     "modelTags": {
@@ -1750,7 +1779,13 @@
         "checkingUpdates": "בודק עדכונים...",
         "checkingMessage": "אנא המתן בזמן שאנו בודקים את הגרסה האחרונה.",
         "showNotifications": "הצג התראות עדכון",
-    "latestBadge": "עדכן",
+        "latestBadge": "אחרון",
+        "latestMain": "ענף main",
+        "channel": "ערוץ עדכון",
+        "channels": {
+            "release": "Release",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "מכין עדכון...",
             "installing": "מתקין עדכון...",
@@ -1771,6 +1806,15 @@
             "warning": "אזהרה: גרסאות ליליות עשויות להכיל תכונות ניסיוניות ועלולות להיות לא יציבות.",
             "enable": "הפעל עדכונים ליליים"
         },
+        "channelSwitch": {
+            "nightlyTitle": "מעבר לערוץ Nightly",
+            "nightlyMessage": "מעבר ל-Nightly יאתחל מאגר Git ויעקוב אחר הקומיטים האחרונים בענף main. העדכונים תכופים יותר אך עשויים להיות לא יציבים. ניתן לחזור ל-Release בכל עת.",
+            "releaseTitle": "מעבר לערוץ Release",
+            "releaseMessage": "מעבר ל-Release יעבור לתגית הגרסה היציבה האחרונה. ניתן לחזור ל-Nightly בכל עת.",
+            "switching": "מעבר לערוץ {channel}...",
+            "completed": "המעבר לערוץ {channel} הושלם",
+            "failed": "החלפת ערוץ נכשלה"
+        },
         "banners": {
             "recent": "הודעות אחרונות",
             "empty": "אין כרגע באנרים אחרונים.",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "שם קביעה מראש חייב להיות {max} תווים או פחות",
             "presetNameInvalidChars": "שם קביעה מראש מכיל תווים לא חוקיים",
             "presetNameExists": "קביעה מראש עם שם זה כבר קיימת",
-      "maxPresetsReached": "מותר מקסימום {max} קביעות מראש. מחק אחת כדי להוסיף עוד.",
             "presetNotFound": "קביעה מראש לא נמצאה",
             "invalidPreset": "נתוני קביעה מראש לא חוקיים",
             "deletePresetFailed": "מחיקת קביעה מראש נכשלה",

locales/ja.json

@@ -449,6 +449,12 @@
                 "compact": "7（1080p）、8（2K）、10（4K）"
             },
             "displayDensityWarning": "警告：高密度設定は、リソースが限られたシステムでパフォーマンスの問題を引き起こす可能性があります。",
+            "recipesLayout": "レシピのレイアウト",
+            "recipesLayoutHelp": "レシピカードの配置方法を選択：均一なグリッド、または各画像のアスペクト比を保持するメイソンリー（Pinterest スタイル）レイアウト。",
+            "recipesLayoutOptions": {
+                "grid": "グリッド",
+                "masonry": "メイソンリー"
+            },
             "showFolderSidebar": "フォルダサイドバーを表示",
             "showFolderSidebarHelp": "モデルページのフォルダナビゲーションサイドバーを表示/非表示にします。無効にするとサイドバーとホバーエリアは表示されません。",
             "cardInfoDisplay": "カード情報表示",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "カスタム（OpenAI 互換）"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "ローカルバージョン数",
                 "versionsCountDesc": "バージョン数の多い順",
                 "versionsCountAsc": "バージョン数の少ない順",
-        "versionIdDesc": "最新バージョン順"
+                "versionIdDesc": "最新バージョン順",
+                "random": "ランダム",
+                "randomAction": "シャッフル（ランダム）"
             },
             "refresh": {
                 "title": "モデルリストを更新",
@@ -771,6 +780,8 @@
             "deleteAll": "選択したものを削除",
             "downloadMissingLoras": "不足している LoRA をダウンロード",
             "downloadExamples": "例画像をダウンロード",
+            "downloadMissingExamples": "不足分をダウンロード",
+            "reprocessExamples": "すべて再処理",
             "clear": "選択をクリア",
             "skipMetadataRefreshCount": "スキップ（{count}モデル）",
             "resumeMetadataRefreshCount": "再開（{count}モデル）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "ワークフローに送信（置換）",
             "openExamples": "例画像フォルダを開く",
             "downloadExamples": "例画像をダウンロード",
+            "downloadMissingExamples": "不足分をダウンロード",
+            "reprocessExamples": "すべて再処理",
             "replacePreview": "プレビューを置換",
             "setContentRating": "コンテンツレーティングを設定",
             "moveToFolder": "フォルダに移動",
@@ -1548,6 +1561,7 @@
                 "empty": "このモデルにはまだバージョン履歴がありません。",
                 "error": "バージョンの読み込みに失敗しました。",
                 "missingModelId": "このモデルにはCivitaiのモデルIDがありません。",
+                "hfGroupInfo": "これは HuggingFace モデルグループです。ライブラリを開いてグリッドですべてのバージョンを表示してください。",
                 "confirm": {
                     "delete": "このバージョンをライブラリから削除しますか？"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "CSVをダウンロード",
             "columnModelName": "モデル名",
             "columnError": "エラー"
+        },
+        "downloadBatchSummary": {
+            "title": "バッチダウンロードの概要",
+            "statSuccess": "成功",
+            "statFailed": "失敗",
+            "statTotal": "合計",
+            "successMessage": "{count} 個のモデルがすべて正常にダウンロードされました",
+            "completedWithErrors": "エラーありで完了",
+            "failed": "ダウンロードに失敗しました",
+            "failedItems": "失敗した項目（{count}）",
+            "columnName": "モデル名",
+            "columnError": "エラー",
+            "close": "閉じる",
+            "copyReport": "レポートをコピー",
+            "retryFailed": "失敗した項目を再試行（{count}）"
         }
     },
     "modelTags": {
@@ -1751,6 +1780,12 @@
         "checkingMessage": "最新バージョンを確認しています。お待ちください。",
         "showNotifications": "更新通知を表示",
         "latestBadge": "最新",
+        "latestMain": "Main ブランチ",
+        "channel": "更新チャンネル",
+        "channels": {
+            "release": "リリース",
+            "nightly": "ナイトリー"
+        },
         "updateProgress": {
             "preparing": "更新を準備中...",
             "installing": "更新をインストール中...",
@@ -1771,6 +1806,15 @@
             "warning": "警告：ナイトリービルドには実験的機能が含まれており、不安定な場合があります。",
             "enable": "ナイトリー更新を有効にする"
         },
+        "channelSwitch": {
+            "nightlyTitle": "ナイトリーチャンネルに切り替え",
+            "nightlyMessage": "ナイトリーに切り替えると、Gitリポジトリが初期化され、mainブランチの最新コミットを追跡します。更新頻度は高くなりますが、不安定な場合があります。いつでもリリース版に戻せます。",
+            "releaseTitle": "リリースチャンネルに切り替え",
+            "releaseMessage": "リリースに切り替えると、最新の安定版タグにチェックアウトされます。いつでもNightlyに戻せます。",
+            "switching": "{channel} チャンネルに切り替え中...",
+            "completed": "{channel} チャンネルに切り替えました",
+            "failed": "チャンネルの切り替えに失敗しました"
+        },
         "banners": {
             "recent": "最近の通知",
             "empty": "最近のバナーはありません。",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "プリセット名は{max}文字以内にしてください",
             "presetNameInvalidChars": "プリセット名に使用できない文字が含まれています",
             "presetNameExists": "同じ名前のプリセットが既に存在します",
-      "maxPresetsReached": "プリセットは最大{max}個までです。追加するには既存のものを削除してください。",
             "presetNotFound": "プリセットが見つかりません",
             "invalidPreset": "無効なプリセットデータです",
             "deletePresetFailed": "プリセットの削除に失敗しました",

locales/ko.json

@@ -449,6 +449,12 @@
                 "compact": "7개 (1080p), 8개 (2K), 10개 (4K)"
             },
             "displayDensityWarning": "경고: 높은 밀도는 리소스가 제한된 시스템에서 성능 문제를 일으킬 수 있습니다.",
+            "recipesLayout": "레시피 레이아웃",
+            "recipesLayoutHelp": "레시피 카드의 배열 방식을 선택하세요: 균일한 그리드 또는 각 이미지의 종횡비를 유지하는 메이슨리(Pinterest 스타일) 레이아웃.",
+            "recipesLayoutOptions": {
+                "grid": "그리드",
+                "masonry": "메이슨리"
+            },
             "showFolderSidebar": "폴더 사이드바 표시",
             "showFolderSidebarHelp": "모델 페이지에서 폴더 탐색 사이드바를 켜거나 끕니다. 비활성화하면 사이드바와 호버 영역이 표시되지 않습니다.",
             "cardInfoDisplay": "카드 정보 표시",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "사용자 정의 (OpenAI 호환)"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "로컬 버전 수",
                 "versionsCountDesc": "버전 수 많은 순",
                 "versionsCountAsc": "버전 수 적은 순",
-        "versionIdDesc": "최신 버전순"
+                "versionIdDesc": "최신 버전순",
+                "random": "랜덤",
+                "randomAction": "셔플 (무작위)"
             },
             "refresh": {
                 "title": "모델 목록 새로고침",
@@ -771,6 +780,8 @@
             "deleteAll": "선택된 항목 삭제",
             "downloadMissingLoras": "누락된 LoRA 다운로드",
             "downloadExamples": "예시 이미지 다운로드",
+            "downloadMissingExamples": "누락된 것만 다운로드",
+            "reprocessExamples": "모두 다시 처리",
             "clear": "선택 지우기",
             "skipMetadataRefreshCount": "건너뛰기（{count}개 모델）",
             "resumeMetadataRefreshCount": "재개（{count}개 모델）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "워크플로로 전송 (교체)",
             "openExamples": "예시 폴더 열기",
             "downloadExamples": "예시 이미지 다운로드",
+            "downloadMissingExamples": "누락된 것만 다운로드",
+            "reprocessExamples": "모두 다시 처리",
             "replacePreview": "미리보기 교체",
             "setContentRating": "콘텐츠 등급 설정",
             "moveToFolder": "폴더로 이동",
@@ -1548,6 +1561,7 @@
                 "empty": "이 모델에는 아직 버전 기록이 없습니다.",
                 "error": "버전을 불러오지 못했습니다.",
                 "missingModelId": "이 모델에는 Civitai 모델 ID가 없습니다.",
+                "hfGroupInfo": "HuggingFace 모델 그룹입니다. 라이브러리를 열어 그리드에서 모든 버전을 확인하세요.",
                 "confirm": {
                     "delete": "이 버전을 라이브러리에서 삭제하시겠습니까?"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "CSV 다운로드",
             "columnModelName": "모델 이름",
             "columnError": "오류"
+        },
+        "downloadBatchSummary": {
+            "title": "일괄 다운로드 요약",
+            "statSuccess": "성공",
+            "statFailed": "실패",
+            "statTotal": "전체",
+            "successMessage": "{count}개 모델이 모두 성공적으로 다운로드되었습니다",
+            "completedWithErrors": "오류와 함께 완료됨",
+            "failed": "다운로드 실패",
+            "failedItems": "실패한 항목 ({count})",
+            "columnName": "모델 이름",
+            "columnError": "오류",
+            "close": "닫기",
+            "copyReport": "보고서 복사",
+            "retryFailed": "실패 항목 재시도 ({count})"
         }
     },
     "modelTags": {
@@ -1751,6 +1780,12 @@
         "checkingMessage": "최신 버전을 확인하는 동안 잠시 기다려주세요.",
         "showNotifications": "업데이트 알림 표시",
         "latestBadge": "최신",
+        "latestMain": "Main 브랜치",
+        "channel": "업데이트 채널",
+        "channels": {
+            "release": "릴리스",
+            "nightly": "나이틀리"
+        },
         "updateProgress": {
             "preparing": "업데이트 준비 중...",
             "installing": "업데이트 설치 중...",
@@ -1771,6 +1806,15 @@
             "warning": "경고: 나이틀리 빌드는 실험적 기능을 포함할 수 있으며 불안정할 수 있습니다.",
             "enable": "나이틀리 업데이트 활성화"
         },
+        "channelSwitch": {
+            "nightlyTitle": "나이틀리 채널로 전환",
+            "nightlyMessage": "나이틀리로 전환하면 Git 저장소가 초기화되고 main 브랜치의 최신 커밋을 추적합니다. 업데이트 빈도는 높지만 불안정할 수 있습니다. 언제든지 릴리스로 돌아갈 수 있습니다.",
+            "releaseTitle": "릴리스 채널로 전환",
+            "releaseMessage": "릴리스로 전환하면 최신 안정 버전 태그로 체크아웃됩니다. 언제든지 나이틀리로 돌아갈 수 있습니다.",
+            "switching": "{channel} 채널로 전환 중...",
+            "completed": "{channel} 채널로 전환 완료",
+            "failed": "채널 전환 실패"
+        },
         "banners": {
             "recent": "최근 알림",
             "empty": "최근 배너가 없습니다.",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "프리셋 이름은 {max}자 이하여야 합니다",
             "presetNameInvalidChars": "프리셋 이름에 유효하지 않은 문자가 포함되어 있습니다",
             "presetNameExists": "동일한 이름의 프리셋이 이미 존재합니다",
-      "maxPresetsReached": "최대 {max}개의 프리셋만 허용됩니다. 더 추가하려면 기존 것을 삭제하세요.",
             "presetNotFound": "프리셋을 찾을 수 없습니다",
             "invalidPreset": "잘못된 프리셋 데이터입니다",
             "deletePresetFailed": "프리셋 삭제에 실패했습니다",

locales/ru.json

@@ -449,6 +449,12 @@
                 "compact": "7 (1080p), 8 (2K), 10 (4K)"
             },
             "displayDensityWarning": "Предупреждение: Высокая плотность может вызвать проблемы с производительностью на системах с ограниченными ресурсами.",
+            "recipesLayout": "Макет рецептов",
+            "recipesLayoutHelp": "Выберите, как располагаются карточки рецептов: единая сетка или masonry-макет (в стиле Pinterest), сохраняющий пропорции каждого изображения.",
+            "recipesLayoutOptions": {
+                "grid": "Сетка",
+                "masonry": "Masonry"
+            },
             "showFolderSidebar": "Показывать боковую панель папок",
             "showFolderSidebarHelp": "Включает или выключает боковую панель навигации по папкам на страницах моделей. При отключении панель и область наведения скрыты.",
             "cardInfoDisplay": "Отображение информации карточки",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "Пользовательский (совместимый с OpenAI)"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "Локальные версии",
                 "versionsCountDesc": "Сначала больше версий",
                 "versionsCountAsc": "Сначала меньше версий",
-        "versionIdDesc": "Сначала новые версии"
+                "versionIdDesc": "Сначала новые версии",
+                "random": "Случайно",
+                "randomAction": "Перемешать"
             },
             "refresh": {
                 "title": "Обновить список моделей",
@@ -771,6 +780,8 @@
             "deleteAll": "Удалить выбранные",
             "downloadMissingLoras": "Скачать отсутствующие LoRAs",
             "downloadExamples": "Загрузить примеры изображений",
+            "downloadMissingExamples": "Скачать недостающие",
+            "reprocessExamples": "Обработать всё заново",
             "clear": "Очистить выбор",
             "skipMetadataRefreshCount": "Пропустить（{count} моделей）",
             "resumeMetadataRefreshCount": "Возобновить（{count} моделей）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "Отправить в Workflow (Заменить)",
             "openExamples": "Открыть папку примеров",
             "downloadExamples": "Загрузить примеры изображений",
+            "downloadMissingExamples": "Скачать недостающие",
+            "reprocessExamples": "Обработать всё заново",
             "replacePreview": "Заменить превью",
             "setContentRating": "Установить рейтинг контента",
             "moveToFolder": "Переместить в папку",
@@ -1548,6 +1561,7 @@
                 "empty": "Для этой модели пока нет истории версий.",
                 "error": "Не удалось загрузить версии.",
                 "missingModelId": "У этой модели отсутствует идентификатор модели Civitai.",
+                "hfGroupInfo": "Это группа моделей HuggingFace. Откройте библиотеку, чтобы увидеть все версии в сетке.",
                 "confirm": {
                     "delete": "Удалить эту версию из библиотеки?"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "Скачать CSV",
             "columnModelName": "Имя модели",
             "columnError": "Ошибка"
+        },
+        "downloadBatchSummary": {
+            "title": "Сводка пакетной загрузки",
+            "statSuccess": "Успешно",
+            "statFailed": "Ошибки",
+            "statTotal": "Всего",
+            "successMessage": "Все {count} моделей успешно загружены",
+            "completedWithErrors": "Завершено с ошибками",
+            "failed": "Не удалось загрузить",
+            "failedItems": "Неудачные элементы ({count})",
+            "columnName": "Имя модели",
+            "columnError": "Ошибка",
+            "close": "Закрыть",
+            "copyReport": "Скопировать отчёт",
+            "retryFailed": "Повторить неудачные ({count})"
         }
     },
     "modelTags": {
@@ -1750,7 +1779,13 @@
         "checkingUpdates": "Проверка обновлений...",
         "checkingMessage": "Пожалуйста, подождите, пока мы проверяем последнюю версию.",
         "showNotifications": "Показывать уведомления об обновлениях",
-    "latestBadge": "Последний",
+        "latestBadge": "Последняя",
+        "latestMain": "Ветка main",
+        "channel": "Канал обновлений",
+        "channels": {
+            "release": "Релиз",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "Подготовка обновления...",
             "installing": "Установка обновления...",
@@ -1771,6 +1806,15 @@
             "warning": "Предупреждение: Ночные сборки могут содержать экспериментальные функции и могут быть нестабильными.",
             "enable": "Включить ночные обновления"
         },
+        "channelSwitch": {
+            "nightlyTitle": "Переключиться на Nightly",
+            "nightlyMessage": "Переключение на Nightly инициализирует Git-репозиторий и отслеживает последние коммиты ветки main. Обновления чаще, но могут быть нестабильными. Вы можете вернуться к Release в любое время.",
+            "releaseTitle": "Переключиться на Release",
+            "releaseMessage": "Переключение на Release выполнит checkout последнего стабильного тега. Вы можете вернуться к Nightly в любое время.",
+            "switching": "Переключение на канал {channel}...",
+            "completed": "Успешно переключено на канал {channel}",
+            "failed": "Не удалось переключить канал"
+        },
         "banners": {
             "recent": "Недавние уведомления",
             "empty": "Недавних баннеров нет.",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "Имя пресета должно содержать не более {max} символов",
             "presetNameInvalidChars": "Имя пресета содержит недопустимые символы",
             "presetNameExists": "Пресет с таким именем уже существует",
-      "maxPresetsReached": "Допустимо максимум {max} пресетов. Удалите один, чтобы добавить больше.",
             "presetNotFound": "Пресет не найден",
             "invalidPreset": "Недопустимые данные пресета",
             "deletePresetFailed": "Не удалось удалить пресет",

locales/zh-CN.json

@@ -449,6 +449,12 @@
                 "compact": "7（1080p），8（2K），10（4K）"
             },
             "displayDensityWarning": "警告：高密度可能导致资源有限的系统性能下降。",
+            "recipesLayout": "配方布局",
+            "recipesLayoutHelp": "选择配方卡片的排列方式：统一网格，或保留每张图片原始宽高比的瀑布流（Pinterest 风格）布局。",
+            "recipesLayoutOptions": {
+                "grid": "网格",
+                "masonry": "瀑布流"
+            },
             "showFolderSidebar": "显示文件夹侧边栏",
             "showFolderSidebarHelp": "在模型页面启用或禁用文件夹导航侧边栏。关闭后，侧边栏和悬停区域将保持隐藏。",
             "cardInfoDisplay": "卡片信息显示",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "自定义（OpenAI 兼容）"
             },
@@ -714,7 +721,9 @@
                 "versionsCount": "本地版本数",
                 "versionsCountDesc": "版本数从多到少",
                 "versionsCountAsc": "版本数从少到多",
-        "versionIdDesc": "最新版本优先"
+                "versionIdDesc": "最新版本优先",
+                "random": "随机",
+                "randomAction": "随机排序（洗牌）"
             },
             "refresh": {
                 "title": "刷新模型列表",
@@ -771,6 +780,8 @@
             "deleteAll": "删除已选",
             "downloadMissingLoras": "下载缺失的 LoRAs",
             "downloadExamples": "下载示例图片",
+            "downloadMissingExamples": "下载缺失的",
+            "reprocessExamples": "重新处理全部",
             "clear": "清除选择",
             "skipMetadataRefreshCount": "跳过（{count} 个模型）",
             "resumeMetadataRefreshCount": "恢复（{count} 个模型）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "发送到工作流（替换）",
             "openExamples": "打开示例文件夹",
             "downloadExamples": "下载示例图片",
+            "downloadMissingExamples": "下载缺失的",
+            "reprocessExamples": "重新处理全部",
             "replacePreview": "替换预览",
             "setContentRating": "设置内容评级",
             "moveToFolder": "移动到文件夹",
@@ -1548,6 +1561,7 @@
                 "empty": "该模型还没有版本历史。",
                 "error": "加载版本失败。",
                 "missingModelId": "该模型缺少 Civitai 模型 ID。",
+                "hfGroupInfo": "这是一个 HuggingFace 模型组。打开库页面即可在网格中查看所有版本。",
                 "confirm": {
                     "delete": "从库中删除此版本？"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "下载 CSV",
             "columnModelName": "模型名称",
             "columnError": "错误"
+        },
+        "downloadBatchSummary": {
+            "title": "批量下载摘要",
+            "statSuccess": "成功",
+            "statFailed": "失败",
+            "statTotal": "总数",
+            "successMessage": "全部 {count} 个模型下载成功",
+            "completedWithErrors": "已完成，但有错误",
+            "failed": "下载失败",
+            "failedItems": "失败项（{count}）",
+            "columnName": "模型名称",
+            "columnError": "错误",
+            "close": "关闭",
+            "copyReport": "复制报告",
+            "retryFailed": "重试失败项（{count}）"
         }
     },
     "modelTags": {
@@ -1751,6 +1780,12 @@
         "checkingMessage": "请稍候，正在检查最新版本。",
         "showNotifications": "显示更新通知",
         "latestBadge": "最新",
+        "latestMain": "Main 分支",
+        "channel": "更新频道",
+        "channels": {
+            "release": "稳定版",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "正在准备更新...",
             "installing": "正在安装更新...",
@@ -1771,6 +1806,15 @@
             "warning": "警告：Nightly 版本可能包含实验性功能，可能不稳定。",
             "enable": "启用 Nightly 更新"
         },
+        "channelSwitch": {
+            "nightlyTitle": "切换到 Nightly",
+            "nightlyMessage": "切换到 Nightly 将初始化 Git 仓库并跟踪 main 分支的最新提交。更新更频繁但可能不稳定，可随时切回稳定版。",
+            "releaseTitle": "切换到稳定版",
+            "releaseMessage": "切换到稳定版将检出最新的发布标签。可随时切换回每日构建版。",
+            "switching": "正在切换到 {channel} 频道...",
+            "completed": "已切换到 {channel} 频道",
+            "failed": "切换频道失败"
+        },
         "banners": {
             "recent": "最近的通知",
             "empty": "暂无最近的横幅通知。",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "预设名称不能超过 {max} 个字符",
             "presetNameInvalidChars": "预设名称包含无效字符",
             "presetNameExists": "已存在同名预设",
-      "maxPresetsReached": "最多允许 {max} 个预设。删除一个以添加更多。",
             "presetNotFound": "预设未找到",
             "invalidPreset": "无效的预设数据",
             "deletePresetFailed": "删除预设失败",

locales/zh-TW.json

@@ -449,6 +449,12 @@
                 "compact": "7（1080p）、8（2K）、10（4K）"
             },
             "displayDensityWarning": "警告：較高密度可能導致資源有限的系統效能下降。",
+            "recipesLayout": "配方版面",
+            "recipesLayoutHelp": "選擇配方卡片的排列方式：統一網格，或保留每張圖片原始寬高比的瀑布流（Pinterest 風格）版面。",
+            "recipesLayoutOptions": {
+                "grid": "網格",
+                "masonry": "瀑布流"
+            },
             "showFolderSidebar": "顯示資料夾側邊欄",
             "showFolderSidebarHelp": "在模型頁面啟用或停用資料夾導覽側邊欄。停用後，側邊欄與滑鼠懸停區域將保持隱藏。",
             "cardInfoDisplay": "卡片資訊顯示",
@@ -678,6 +684,7 @@
                 "deepseek": "DeepSeek",
                 "groq": "Groq",
                 "openrouter": "OpenRouter",
+                "google": "Gemini",
                 "opencode-go": "OpenCode Go",
                 "custom": "自訂（OpenAI 相容）"
             },
@@ -686,7 +693,7 @@
             "apiBasePlaceholder": "https://api.openai.com/v1",
             "apiKey": "API 金鑰",
             "apiKeyHelp": "LLM 提供者的 API 金鑰。儲存在本地，除您選擇的 LLM 提供者外不會傳送到任何伺服器。",
-      "apiKeyPlaceholder": "[TODO: Translate] sk-...",
+            "apiKeyPlaceholder": "sk-...",
             "apiKeyNotSet": "未設定",
             "apiKeyConfigured": "已設定",
             "apiKeySet": "設定",
@@ -714,7 +721,9 @@
                 "versionsCount": "本地版本數",
                 "versionsCountDesc": "版本數從多到少",
                 "versionsCountAsc": "版本數從少到多",
-        "versionIdDesc": "最新版本優先"
+                "versionIdDesc": "最新版本優先",
+                "random": "隨機",
+                "randomAction": "隨機排序（洗牌）"
             },
             "refresh": {
                 "title": "重新整理模型列表",
@@ -771,6 +780,8 @@
             "deleteAll": "刪除所選",
             "downloadMissingLoras": "下載缺失的 LoRAs",
             "downloadExamples": "下載範例圖片",
+            "downloadMissingExamples": "下載缺少的",
+            "reprocessExamples": "重新處理全部",
             "clear": "清除選取",
             "skipMetadataRefreshCount": "跳過（{count} 個模型）",
             "resumeMetadataRefreshCount": "恢復（{count} 個模型）",
@@ -806,6 +817,8 @@
             "sendToWorkflowReplace": "傳送到工作流（取代）",
             "openExamples": "開啟範例資料夾",
             "downloadExamples": "下載範例圖片",
+            "downloadMissingExamples": "下載缺少的",
+            "reprocessExamples": "重新處理全部",
             "replacePreview": "更換預覽圖",
             "setContentRating": "設定內容分級",
             "moveToFolder": "移動到資料夾",
@@ -1548,6 +1561,7 @@
                 "empty": "此模型尚無版本歷史。",
                 "error": "載入版本失敗。",
                 "missingModelId": "此模型缺少 Civitai 模型 ID。",
+                "hfGroupInfo": "這是一個 HuggingFace 模型組。打開庫頁面即可在網格中查看所有版本。",
                 "confirm": {
                     "delete": "要從庫中刪除此版本嗎？"
                 },
@@ -1574,6 +1588,21 @@
             "downloadCsv": "下載 CSV",
             "columnModelName": "模型名稱",
             "columnError": "錯誤"
+        },
+        "downloadBatchSummary": {
+            "title": "批次下載摘要",
+            "statSuccess": "成功",
+            "statFailed": "失敗",
+            "statTotal": "總數",
+            "successMessage": "全部 {count} 個模型下載成功",
+            "completedWithErrors": "已完成，但有錯誤",
+            "failed": "下載失敗",
+            "failedItems": "失敗項目（{count}）",
+            "columnName": "模型名稱",
+            "columnError": "錯誤",
+            "close": "關閉",
+            "copyReport": "複製報告",
+            "retryFailed": "重試失敗項目（{count}）"
         }
     },
     "modelTags": {
@@ -1751,6 +1780,12 @@
         "checkingMessage": "請稍候，正在檢查最新版本。",
         "showNotifications": "顯示更新通知",
         "latestBadge": "最新",
+        "latestMain": "Main 分支",
+        "channel": "更新頻道",
+        "channels": {
+            "release": "稳定版",
+            "nightly": "Nightly"
+        },
         "updateProgress": {
             "preparing": "正在準備更新...",
             "installing": "正在安裝更新...",
@@ -1771,6 +1806,15 @@
             "warning": "警告：Nightly 版本可能包含實驗性功能且可能不穩定。",
             "enable": "啟用 Nightly 更新"
         },
+        "channelSwitch": {
+            "nightlyTitle": "切换到 Nightly",
+            "nightlyMessage": "切换到 Nightly 将初始化 Git 仓库并跟踪 main 分支的最新提交。更新更频繁但可能不稳定，可随时切回稳定版。",
+            "releaseTitle": "切换到稳定版",
+            "releaseMessage": "切換到穩定版將檢出最新的發布標籤。可隨時切換回每日構建版。",
+            "switching": "正在切換到 {channel} 頻道...",
+            "completed": "已切換到 {channel} 頻道",
+            "failed": "切換頻道失敗"
+        },
         "banners": {
             "recent": "最新通知",
             "empty": "目前沒有最近的橫幅通知。",
@@ -2015,7 +2059,6 @@
             "presetNameTooLong": "預設名稱不能超過 {max} 個字元",
             "presetNameInvalidChars": "預設名稱包含無效字元",
             "presetNameExists": "已存在同名預設",
-      "maxPresetsReached": "最多允許 {max} 個預設。刪除一個以新增更多。",
             "presetNotFound": "預設未找到",
             "invalidPreset": "無效的預設資料",
             "deletePresetFailed": "刪除預設失敗",

py/metadata_collector/constants.py

@@ -1,5 +1,11 @@
 """Constants used by the metadata collector"""
 
+# Sentinel value for clip_skip to distinguish "unconnected / widget default"
+# from "user wired value 0".  Both ComfyUI CLIPSetLastLayer (-24..-1) and
+# A1111 conventions treat 0 as meaningless for clip skipping, but users may
+# explicitly wire 0 to the overwrite node to express "no clip skip / default".
+CLIP_SKIP_SENTINEL = -25
+
 # Metadata categories
 MODELS = "models"
 PROMPTS = "prompts"
@@ -9,6 +15,14 @@ EMBEDDINGS = "embeddings"
 SIZE = "size"
 IMAGES = "images"
 IS_SAMPLER = "is_sampler"  # New constant to mark sampler nodes
+OVERWRITE = "overwrite"  # Manual metadata overwrite from MetadataOverwriteLM node
+
+# Field names that the MetadataOverwriteLM node and its extractor share
+METADATA_OVERWRITE_FIELDS = (
+    "prompt", "negative_prompt", "seed", "steps", "cfg_scale",
+    "sampler", "scheduler", "model", "loras", "size",
+    "clip_skip", "additional_data",
+)
 
 # Complete list of categories to track
-METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES]
+METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES, OVERWRITE]

py/metadata_collector/metadata_hook.py

@@ -83,7 +83,8 @@ class MetadataHook:
                         
                         # Record inputs before execution
                         if node_id is not None:
-                            registry.record_node_execution(node_id, class_type, input_data_all, None)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.record_node_execution(node_id, class_type, input_data_all, None, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
             
@@ -114,7 +115,8 @@ class MetadataHook:
                         
                         # Record outputs after execution
                         if node_id is not None:
-                            registry.update_node_execution(node_id, class_type, results)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.update_node_execution(node_id, class_type, results, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (post-execution): {str(e)}")
             
@@ -136,6 +138,9 @@ class MetadataHook:
                 if hasattr(prompt, 'original_prompt'):
                     registry.set_current_prompt(prompt)
 
+                # Store extra_data for accessing full workflow node properties
+                registry.set_extra_data(extra_data)
+
             # Execute the original function
             return original_execute(*args, **kwargs)
 
@@ -163,7 +168,8 @@ class MetadataHook:
                         class_type = obj.__class__.__name__
                         node_id = unique_id
                         if node_id is not None:
-                            registry.record_node_execution(node_id, class_type, input_data_all, None)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.record_node_execution(node_id, class_type, input_data_all, None, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
 
@@ -180,7 +186,8 @@ class MetadataHook:
                         class_type = obj.__class__.__name__
                         node_id = unique_id
                         if node_id is not None:
-                            registry.update_node_execution(node_id, class_type, results)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.update_node_execution(node_id, class_type, results, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (post-execution): {str(e)}")
 
@@ -202,6 +209,9 @@ class MetadataHook:
                 if hasattr(prompt, 'original_prompt'):
                     registry.set_current_prompt(prompt)
 
+                # Store extra_data for accessing full workflow node properties
+                registry.set_extra_data(extra_data)
+
             # Execute the original function
             return await original_execute(*args, **kwargs)
 

py/metadata_collector/metadata_processor.py

@@ -1,15 +1,68 @@
 import json
+import logging
 import os
 from .constants import IMAGES
 
 # 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"
 
-from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER
+from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER, OVERWRITE
+from .node_extractors import NODE_EXTRACTORS
+
+logger = logging.getLogger(__name__)
+
+# Keys that identify metadata hint marks stored in node.properties.lm_marker_role
+_META_MARK_PREFIX = "meta_"
+_MARK_PRIMARY_MODEL = "primary_model"
+_MARK_PRIMARY_SAMPLER = "primary_sampler"
+_MARK_POSITIVE_PROMPT = "positive_prompt"
+_MARK_NEGATIVE_PROMPT = "negative_prompt"
 
 class MetadataProcessor:
     """Process and format collected metadata"""
 
+    @staticmethod
+    def _get_user_marks(metadata):
+        """Scan workflow nodes (from extra_data.extra_pnginfo.workflow) for user-assigned
+        metadata hint marks stored in node.properties.lm_marker_role.
+
+        Returns a dict mapping mark type keys to node IDs.
+        Example: {'primary_model': '42', 'primary_sampler': '17'}
+        """
+        marks: dict[str, str] = {}
+
+        # Primary source: extra_data.extra_pnginfo.workflow.nodes (has full properties)
+        extra_data = metadata.get("extra_data")
+        if extra_data and isinstance(extra_data, dict):
+            extra_pnginfo = extra_data.get("extra_pnginfo", {})
+            if isinstance(extra_pnginfo, dict):
+                workflow = extra_pnginfo.get("workflow", {})
+                nodes = workflow.get("nodes", [])
+                for node in nodes:
+                    node_id = str(node.get("id", ""))
+                    role = node.get("properties", {}).get("lm_marker_role", "")
+                    if role.startswith(_META_MARK_PREFIX):
+                        mark_type = role[len(_META_MARK_PREFIX):]
+                        if mark_type in marks:
+                            logger.warning(
+                                "Duplicate meta hint '%s': node %s (previous: %s), "
+                                "last match wins",
+                                mark_type, node_id, marks[mark_type],
+                            )
+                        marks[mark_type] = node_id
+
+        # Fallback: try prompt.original_prompt (API-only submissions may not have workflow)
+        if not marks:
+            prompt = metadata.get("current_prompt")
+            if prompt and getattr(prompt, "original_prompt", None):
+                for node_id, node_data in prompt.original_prompt.items():
+                    role = node_data.get("properties", {}).get("lm_marker_role", "")
+                    if role.startswith(_META_MARK_PREFIX):
+                        mark_type = role[len(_META_MARK_PREFIX):]
+                        marks[mark_type] = node_id
+
+        return marks
+
     @staticmethod
     def find_primary_sampler(metadata, downstream_id=None):
         """
@@ -471,17 +524,54 @@ class MetadataProcessor:
             "checkpoint": None,
             "loras": "",
             "size": None,
-            "clip_skip": None
+            "clip_skip": None,
+            "additional_data": "",
         }
         
         # Get the prompt object for node relationship tracing
         prompt = metadata.get("current_prompt")
 
-        # Find the primary KSampler node
+        # ---- User marks: override heuristic inference with user-assigned hints ----
+        user_marks = MetadataProcessor._get_user_marks(metadata)
+
+        # Find the primary KSampler node (user mark takes priority)
+        primary_sampler_id = None
+        primary_sampler = None
+        if _MARK_PRIMARY_SAMPLER in user_marks:
+            marked_id = user_marks[_MARK_PRIMARY_SAMPLER]
+            sampler_data = metadata.get(SAMPLING, {}).get(marked_id)
+            if sampler_data and sampler_data.get(IS_SAMPLER):
+                primary_sampler_id = marked_id
+                primary_sampler = sampler_data
+            else:
+                logger.warning(
+                    "User-marked primary sampler %s has no runtime metadata, "
+                    "falling back to heuristic",
+                    marked_id,
+                )
+        if primary_sampler is None:
             primary_sampler_id, primary_sampler = MetadataProcessor.find_primary_sampler(metadata, id)
 
-        # Directly get checkpoint from metadata instead of tracing
+        # Resolve checkpoint / model (user mark takes priority)
-        # Pass primary_sampler_id to avoid redundant calculation
+        if _MARK_PRIMARY_MODEL in user_marks:
+            marked_id = user_marks[_MARK_PRIMARY_MODEL]
+            if marked_id in metadata.get(MODELS, {}):
+                params["checkpoint"] = metadata[MODELS][marked_id].get("name")
+            else:
+                extra_data = metadata.get("extra_data")
+                extra_pnginfo = extra_data.get("extra_pnginfo", {}) if extra_data and isinstance(extra_data, dict) else {}
+                workflow = extra_pnginfo.get("workflow", {}) if isinstance(extra_pnginfo, dict) else {}
+                node_type = "unknown"
+                for n in workflow.get("nodes", []):
+                    if str(n.get("id", "")) == marked_id:
+                        node_type = n.get("type", "unknown")
+                        break
+                logger.warning(
+                    "User-marked primary model %s (type=%s, registered=%s) has no runtime metadata, "
+                    "falling back to heuristic",
+                    marked_id, node_type, node_type in NODE_EXTRACTORS,
+                )
+        if params["checkpoint"] is None:
             checkpoint = MetadataProcessor.find_primary_checkpoint(metadata, id, primary_sampler_id)
             if checkpoint:
                 params["checkpoint"] = checkpoint
@@ -540,6 +630,21 @@ class MetadataProcessor:
                     # For SamplerCustom, handle any additional parameters
                     MetadataProcessor.handle_custom_advanced_sampler(metadata, prompt, primary_sampler_id, params)
 
+            # ---- User marks: override prompts with explicitly tagged nodes ----
+            prompts_data = metadata.get(PROMPTS, {})
+            if _MARK_POSITIVE_PROMPT in user_marks:
+                pos_id = user_marks[_MARK_POSITIVE_PROMPT]
+                if pos_id in prompts_data:
+                    prompt_text = prompts_data[pos_id].get("text") or prompts_data[pos_id].get("positive_text")
+                    if prompt_text:
+                        params["prompt"] = prompt_text
+            if _MARK_NEGATIVE_PROMPT in user_marks:
+                neg_id = user_marks[_MARK_NEGATIVE_PROMPT]
+                if neg_id in prompts_data:
+                    prompt_text = prompts_data[neg_id].get("text") or prompts_data[neg_id].get("negative_text")
+                    if prompt_text:
+                        params["negative_prompt"] = prompt_text
+
             # Size extraction is same for all sampler types
             # Check if the sampler itself has size information (from latent_image)
             if primary_sampler_id in metadata.get(SIZE, {}):
@@ -569,6 +674,25 @@ class MetadataProcessor:
         if params["clip_skip"] is None:
             params["clip_skip"] = "1"
 
+        # ---- Apply manual metadata overwrites ----
+        for overwrite_info in metadata.get(OVERWRITE, {}).values():
+            overwrite_params = overwrite_info.get("parameters", {})
+            for key, value in overwrite_params.items():
+                if key == "clip_skip":
+                    # Accept any value from overwrite node (sentinel -25 already
+                    # filtered upstream).  Needed because falsy check treats 0
+                    # as "not set" even though 0 is a valid wired input here.
+                    params[key] = value
+                elif value:  # truthy check — only overwrite when user provided a real value
+                    params[key] = value
+
+        # Bridge: the overwrite node exposes the field as "model" (more accurate),
+        # but the internal pipeline key remains "checkpoint" for backward compatibility
+        # with A1111 metadata format and downstream consumers.
+        if params.get("model"):
+            params["checkpoint"] = params["model"]
+            del params["model"]
+
         return params
     
     @staticmethod

py/metadata_collector/metadata_registry.py

@@ -1,7 +1,7 @@
 import time
 from nodes import NODE_CLASS_MAPPINGS  # type: ignore
 from .node_extractors import NODE_EXTRACTORS, GenericNodeExtractor
-from .constants import METADATA_CATEGORIES, IMAGES
+from .constants import METADATA_CATEGORIES, IMAGES, OVERWRITE
 
 
 class MetadataRegistry:
@@ -61,6 +61,7 @@ class MetadataRegistry:
             {
                 "execution_order": [],
                 "current_prompt": None,  # Will store the prompt object
+                "extra_data": None,  # Will store the API extra_data for workflow metadata
                 "timestamp": time.time(),
             }
         )
@@ -75,6 +76,11 @@ class MetadataRegistry:
             # Store the prompt in the metadata for later relationship tracing
             self.prompt_metadata[self.current_prompt_id]["current_prompt"] = prompt
 
+    def set_extra_data(self, extra_data):
+        """Store the API extra_data (contains extra_pnginfo.workflow with node properties)"""
+        if self.current_prompt_id and self.current_prompt_id in self.prompt_metadata:
+            self.prompt_metadata[self.current_prompt_id]["extra_data"] = extra_data
+
     def get_metadata(self, prompt_id=None):
         """Get collected metadata for a prompt"""
         key = prompt_id if prompt_id is not None else self.current_prompt_id
@@ -122,20 +128,28 @@ class MetadataRegistry:
             cache_key = f"{node_id}:{class_type}"
 
             # Check if this node type is relevant for metadata collection
-            if class_type in NODE_EXTRACTORS:
+            if class_type in NODE_EXTRACTORS or cache_key in self.node_cache:
                 # Check if we have cached metadata for this node
                 if cache_key in self.node_cache:
                     cached_data = self.node_cache[cache_key]
 
+                    # Detect bypass (mode=4) / mute (mode=2) — these nodes
+                    # were intentionally disabled and should not contribute
+                    # overwrite values from a previous execution's cache.
+                    node_mode = node_data.get("mode", 0)
+                    node_is_disabled = node_mode in (2, 4)
+
                     # Apply cached metadata to the current metadata
                     for category in self.metadata_categories:
+                        if category == OVERWRITE and node_is_disabled:
+                            continue
                         if category in cached_data and node_id in cached_data[category]:
                             if node_id not in metadata[category]:
                                 metadata[category][node_id] = cached_data[category][
                                     node_id
                                 ]
 
-    def record_node_execution(self, node_id, class_type, inputs, outputs):
+    def record_node_execution(self, node_id, class_type, inputs, outputs, return_types=None):
         """Record information about a node's execution"""
         if not self.current_prompt_id:
             return
@@ -158,17 +172,18 @@ class MetadataRegistry:
 
         # Extract node-specific metadata
         extractor = NODE_EXTRACTORS.get(class_type, GenericNodeExtractor)
-        extractor.extract(
+        if extractor is GenericNodeExtractor:
-            node_id,
+            extractor.extract(node_id, processed_inputs, outputs,
-            processed_inputs,
-            outputs,
                               self.prompt_metadata[self.current_prompt_id],
-        )
+                              return_types=return_types)
+        else:
+            extractor.extract(node_id, processed_inputs, outputs,
+                              self.prompt_metadata[self.current_prompt_id])
 
         # Cache this node's metadata
         self._cache_node_metadata(node_id, class_type)
 
-    def update_node_execution(self, node_id, class_type, outputs):
+    def update_node_execution(self, node_id, class_type, outputs, return_types=None):
         """Update node metadata with output information"""
         if not self.current_prompt_id:
             return
@@ -179,8 +194,16 @@ class MetadataRegistry:
         # Use the same extractor to update with outputs
         extractor = NODE_EXTRACTORS.get(class_type, GenericNodeExtractor)
         if hasattr(extractor, "update"):
+            if extractor is GenericNodeExtractor:
                 extractor.update(
-                node_id, processed_outputs, self.prompt_metadata[self.current_prompt_id]
+                    node_id, processed_outputs,
+                    self.prompt_metadata[self.current_prompt_id],
+                    return_types=return_types,
+                )
+            else:
+                extractor.update(
+                    node_id, processed_outputs,
+                    self.prompt_metadata[self.current_prompt_id],
                 )
 
         # Update the cached metadata for this node

py/metadata_collector/node_extractors.py

@@ -2,7 +2,8 @@ import json
 import os
 import re
 
-from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER
+from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER, OVERWRITE
+from .overwrite_utils import collect_overwrite_params
 
 
 def _store_checkpoint_metadata(metadata, node_id, model_name):
@@ -31,10 +32,77 @@ class NodeMetadataExtractor:
         pass
         
 class GenericNodeExtractor(NodeMetadataExtractor):
-    """Default extractor for nodes without specific handling"""
+    """Fallback extractor with type-signature-based detection.
+
+    When a node is not in the NODE_EXTRACTORS registry, the hook layer
+    passes ``return_types`` from ``obj.RETURN_TYPES``:
+
+    * ``MODEL`` output: common input fields (ckpt_name, unet_name, etc.)
+      are checked for a model file name and stored as checkpoint metadata.
+    * ``CONDITIONING`` output: common text input fields are checked for
+      prompt text and stored as prompt metadata.
+    """
+
+    # Input field names that carry a model path in loader-style nodes.
+    _MODEL_NAME_FIELDS = (
+        "ckpt_name", "unet_name", "model_path", "model_name", "gguf_name",
+    )
+
+    # Extensions used by checkpoint_scanner.py — only record values that look
+    # like real model filenames to avoid capturing unrelated string fields.
+    _MODEL_EXTENSIONS = {
+        ".ckpt", ".pt", ".pt2", ".bin", ".pth", ".safetensors", ".pkl", ".sft", ".gguf",
+    }
+
+    # Input field names that may carry prompt text in encoder-style nodes.
+    _TEXT_FIELDS = ("text", "clip_l", "t5xxl", "prompt", "positive", "negative")
+
     @staticmethod
-    def extract(node_id, inputs, outputs, metadata):
+    def extract(node_id, inputs, outputs, metadata, return_types=None):
-        pass
+        if return_types is None:
+            return
+
+        # — MODEL loader detection (checkpoint / UNET / GGUF) —
+        if "MODEL" in return_types or any("MODEL" in str(t) for t in return_types):
+            for field in GenericNodeExtractor._MODEL_NAME_FIELDS:
+                val = inputs.get(field)
+                if val and isinstance(val, str) and val.strip():
+                    name = val.strip()
+                    if not any(name.lower().endswith(ext) for ext in GenericNodeExtractor._MODEL_EXTENSIONS):
+                        continue
+                    _store_checkpoint_metadata(metadata, node_id, name)
+                    return
+
+        # — CONDITIONING encoder detection (CLIPTextEncode, Flux, custom) —
+        if "CONDITIONING" in return_types or any("CONDITIONING" in str(t) for t in return_types):
+            text = None
+            for field in GenericNodeExtractor._TEXT_FIELDS:
+                val = inputs.get(field)
+                if val and isinstance(val, str) and val.strip():
+                    text = val.strip()
+                    break
+            if text:
+                prompt_data = metadata.setdefault(PROMPTS, {})
+                prompt_data[node_id] = {
+                    "text": text,
+                    "node_id": node_id,
+                }
+
+    @staticmethod
+    def update(node_id, outputs, metadata, return_types=None):
+        if return_types is None:
+            return
+        if "CONDITIONING" not in return_types and not any(
+            "CONDITIONING" in str(t) for t in return_types
+        ):
+            return
+        if node_id not in metadata.get(PROMPTS, {}):
+            return
+        if outputs and isinstance(outputs, list) and len(outputs) > 0:
+            if isinstance(outputs[0], tuple) and len(outputs[0]) > 0:
+                cond = outputs[0][0]
+                if cond is not None:
+                    metadata[PROMPTS][node_id]["conditioning"] = cond
 
 class CheckpointLoaderExtractor(NodeMetadataExtractor):
     @staticmethod
@@ -1154,6 +1222,28 @@ class CR_ApplyControlNetStackExtractor(NodeMetadataExtractor):
                 metadata[PROMPTS][node_id]["positive_encoded"] = transformed_positive
                 metadata[PROMPTS][node_id]["negative_encoded"] = transformed_negative
 
+class MetadataOverwriteExtractor(NodeMetadataExtractor):
+    """Extract manually specified metadata from MetadataOverwriteLM node.
+
+    Stores truthy input values under the OVERWRITE category so that
+    extract_generation_params can merge them over the inferred params.
+    """
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        overwrite_params = collect_overwrite_params(inputs)
+
+        if overwrite_params:
+            metadata.setdefault(OVERWRITE, {})
+            metadata[OVERWRITE][node_id] = {
+                "parameters": overwrite_params,
+                "node_id": node_id,
+            }
+
+
 # Registry of node-specific extractors
 # Keys are node class names
 NODE_EXTRACTORS = {
@@ -1221,5 +1311,7 @@ NODE_EXTRACTORS = {
     "CFGGuider": CFGGuiderExtractor,            # Add CFGGuider
     # Image
     "VAEDecode": VAEDecodeExtractor,  # Added VAEDecode extractor
+    # Metadata overwrite
+    "MetadataOverwriteLM": MetadataOverwriteExtractor,
     # Add other nodes as needed
 }

py/metadata_collector/overwrite_utils.py

@@ -0,0 +1,42 @@
+"""Shared helpers for Metadata Overwrite node metadata collection.
+
+Used by both the MetadataOverwriteLM node (execution time) and the
+MetadataOverwriteExtractor (hook time) so the conversion/filtering logic
+cannot drift between the two paths.
+"""
+
+import logging
+from typing import Any, Dict
+
+from ..utils.utils import model_patcher_to_name
+from .constants import CLIP_SKIP_SENTINEL, METADATA_OVERWRITE_FIELDS
+
+logger = logging.getLogger(__name__)
+
+
+def collect_overwrite_params(values: Dict[str, Any]) -> Dict[str, Any]:
+    """Convert node input values into non-default overwrite parameters.
+
+    For most fields, a falsy value (empty string, 0) means "not set" and is
+    skipped.  clip_skip uses a dedicated sentinel (-25) so that a wired value
+    of 0 is preserved.  The ``model`` field accepts either a manual string or
+    a wired MODEL (ModelPatcher) connection; in the latter case the source
+    model name is extracted from the patcher's ``cached_patcher_init`` and
+    stored as a ComfyUI-style relative path.
+    """
+    result: Dict[str, Any] = {}
+    for key in METADATA_OVERWRITE_FIELDS:
+        value = values.get(key)
+        if key == "model" and not isinstance(value, str):
+            value = model_patcher_to_name(value)
+            if value is None:
+                logger.warning(
+                    "Could not extract model name from wired MODEL input "
+                    "(no cached_patcher_init); model metadata overwrite skipped"
+                )
+        if key == "clip_skip":
+            if value != CLIP_SKIP_SENTINEL:
+                result[key] = value
+        elif value:
+            result[key] = value
+    return result

py/nodes/create_hook_lora.py

@@ -0,0 +1,117 @@
+"""Create Hook LoRA (LoraManager) — multi-LoRA hook node compatible with ComfyUI's built-in hook pipeline.
+
+Produces ``("HOOKS",)`` output that chains seamlessly with downstream hook consumers
+(ConditioningSetProperties, SetHookKeyframes, CombineHooks, SetClipHooks, etc.).
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+
+from ..utils.utils import get_lora_info_absolute
+from .utils import (
+    FlexibleOptionalInputType,
+    any_type,
+    apply_lora_syntax_format,
+    get_loras_list,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class CreateHookLoraLM:
+    NAME = "Create Hook LoRA (LoraManager)"
+    CATEGORY = "Lora Manager/hooks"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "text": (
+                    "AUTOCOMPLETE_TEXT_LORAS",
+                    {
+                        "placeholder": "Search LoRAs to add...",
+                        "tooltip": (
+                            "Search and select LoRAs. Each LoRA gets its own "
+                            "model/clip strength. Hooks chain with prev_hooks."
+                        ),
+                    },
+                ),
+            },
+            "optional": FlexibleOptionalInputType(any_type),
+        }
+
+    RETURN_TYPES = ("HOOKS", "STRING", "STRING")
+    RETURN_NAMES = ("HOOKS", "trigger_words", "active_loras")
+    FUNCTION = "create_hook"
+
+    def create_hook(self, text: str, **kwargs):
+        """Create a HookGroup from the selected LoRAs, chained with prev_hooks.
+
+        Each active LoRA from the widget is loaded and wrapped in a WeightHook
+        via :func:`comfy.hooks.create_hook_lora`.  All hooks are combined into a
+        single group and returned alongside trigger words and a human-readable
+        summary of the active LoRAs.
+        """
+        del text  # used by the frontend widget only
+
+        # Lazy imports: comfy is not available in CI/test environment at module level
+        import comfy.hooks  # type: ignore  # noqa: C0415
+        import comfy.utils  # type: ignore  # noqa: C0415
+
+        prev_hooks: comfy.hooks.HookGroup | None = kwargs.get("prev_hooks")
+
+        hook_group = prev_hooks.clone() if prev_hooks is not None else comfy.hooks.HookGroup()
+
+        all_trigger_words: list[str] = []
+        active_loras: list[tuple[str, float, float]] = []
+
+        for lora in get_loras_list(kwargs):
+            if not lora.get("active", False):
+                continue
+
+            lora_name = apply_lora_syntax_format(lora["name"])
+            model_strength = float(lora["strength"])
+            clip_strength = float(lora.get("clipStrength", model_strength))
+
+            # Skip useless no-op entries (both strengths are zero)
+            if model_strength == 0.0 and clip_strength == 0.0:
+                continue
+
+            lora_path, trigger_words = get_lora_info_absolute(lora_name)
+            if not lora_path or not os.path.isfile(lora_path):
+                logger.warning("LoRA '%s' not found — skipping", lora_name)
+                continue
+
+            try:
+                lora_weights = comfy.utils.load_torch_file(lora_path, safe_load=True)
+
+                lora_hooks = comfy.hooks.create_hook_lora(
+                    lora=lora_weights,
+                    strength_model=model_strength,
+                    strength_clip=clip_strength,
+                )
+            except Exception:
+                logger.exception("Failed to load LoRA '%s' — skipping", lora_name)
+                continue
+            hook_group = hook_group.clone_and_combine(lora_hooks)
+
+            active_loras.append((lora_name, model_strength, clip_strength))
+            all_trigger_words.extend(trigger_words)
+
+        # Format trigger words (group mode separator)
+        trigger_words_text = ",, ".join(all_trigger_words) if all_trigger_words else ""
+
+        # Format active LoRAs summary
+        formatted_loras = []
+        for name, model_s, clip_s in active_loras:
+            if abs(model_s - clip_s) > 0.001:
+                formatted_loras.append(
+                    f"<lora:{name}:{model_s}:{clip_s}>"
+                )
+            else:
+                formatted_loras.append(f"<lora:{name}:{model_s}>")
+        active_loras_text = " ".join(formatted_loras)
+
+        return (hook_group, trigger_words_text, active_loras_text)

py/nodes/lora_stack_combiner.py

@@ -1,26 +1,102 @@
+from __future__ import annotations
+
+import inspect
+import re
+from typing import Any
+
+_STACK_INPUT_PATTERN = re.compile(r"^lora_stack(?:_([ab])|(\d+))$")
+
+
+def _is_stack_input(name: str) -> bool:
+    return bool(_STACK_INPUT_PATTERN.match(name))
+
+
+def _stack_slot_number(name: str) -> int:
+    """Numeric slot used to order stack inputs; legacy a/b map to 1/2."""
+    match = _STACK_INPUT_PATTERN.match(name)
+    if not match:
+        return -1
+    letter, digits = match.group(1), match.group(2)
+    if digits is not None:
+        return int(digits)
+    return 1 if letter == "a" else 2
+
+
+class _LoraStackOptionalInputs:
+    """Lookup that preserves explicit optional inputs and dynamic lora_stack slots."""
+
+    def __init__(self, explicit_inputs: dict[str, tuple[str, dict[str, Any]]]) -> None:
+        self._explicit_inputs = explicit_inputs
+
+    def __contains__(self, item: object) -> bool:
+        if not isinstance(item, str):
+            return False
+        return item in self._explicit_inputs or _is_stack_input(item)
+
+    def __getitem__(self, key: str) -> tuple[str, dict[str, Any]]:
+        if key in self._explicit_inputs:
+            return self._explicit_inputs[key]
+        if _is_stack_input(key):
+            return (
+                "LORA_STACK",
+                {
+                    "tooltip": "A LoRA stack to combine. Connect to add more inputs.",
+                },
+            )
+        raise KeyError(key)
+
+
 class LoraStackCombinerLM:
     NAME = "Lora Stack Combiner (LoraManager)"
     CATEGORY = "Lora Manager/stackers"
+    DESCRIPTION = (
+        "Combines multiple LoRA stacks into a single stack. "
+        "Supports dynamic inputs: connect a stack to add more inputs."
+    )
 
     @classmethod
     def INPUT_TYPES(cls):
-        return {
+        optional_inputs: dict[str, tuple[str, dict[str, Any]]] = {
-            "required": {
+            "lora_stack1": (
-                "lora_stack_a": ("LORA_STACK",),
+                "LORA_STACK",
-                "lora_stack_b": ("LORA_STACK",),
+                {
+                    "tooltip": "A LoRA stack to combine. Connect to add more inputs.",
                 },
+            ),
+            "lora_stack2": (
+                "LORA_STACK",
+                {
+                    "tooltip": "A LoRA stack to combine. Connect to add more inputs.",
+                },
+            ),
+        }
+
+        stack = inspect.stack()
+        if len(stack) > 2 and stack[2].function == "get_input_info":
+            optional_inputs = _LoraStackOptionalInputs(optional_inputs)  # type: ignore[assignment]
+
+        return {
+            "required": {},
+            "optional": optional_inputs,
         }
 
     RETURN_TYPES = ("LORA_STACK",)
     RETURN_NAMES = ("LORA_STACK",)
     FUNCTION = "combine_stacks"
 
-    def combine_stacks(self, lora_stack_a, lora_stack_b):
+    def combine_stacks(self, lora_stack1=None, lora_stack2=None, **kwargs):
-        combined_stack = []
+        stacks = {
+            "lora_stack1": lora_stack1,
+            "lora_stack2": lora_stack2,
+        }
+        for key, value in kwargs.items():
+            if _is_stack_input(key) and value is not None:
+                stacks[key] = value
 
-        if lora_stack_a:
+        combined_stack = []
-            combined_stack.extend(lora_stack_a)
+        for key in sorted(stacks, key=_stack_slot_number):
-        if lora_stack_b:
+            stack = stacks[key]
-            combined_stack.extend(lora_stack_b)
+            if stack:
+                combined_stack.extend(stack)
 
         return (combined_stack,)

py/nodes/metadata_overwrite.py

@@ -0,0 +1,169 @@
+"""Metadata Overwrite node — allows users to manually specify generation parameters
+that override the automatically collected/inferred metadata.
+
+Most inputs have falsy defaults (empty string / 0) which are skipped.
+clip_skip uses a sentinel default (-25) so that a wired value of 0 is
+preserved — both ComfyUI and A1111 conventions have no meaningful 0 value,
+but users may wire 0 to express "no clip skip / default".
+"""
+
+from typing import Any
+
+from ..metadata_collector.constants import CLIP_SKIP_SENTINEL as _CLIP_SKIP_SENTINEL
+from ..metadata_collector.overwrite_utils import collect_overwrite_params
+
+
+class MetadataOverwriteLM:
+    NAME = "Metadata Overwrite (LoraManager)"
+    CATEGORY = "Lora Manager/utils"
+    DESCRIPTION = (
+        "Manually specify generation parameters to override automatically collected "
+        "metadata. Only filled/connected inputs will take effect — empty defaults "
+        "are ignored."
+    )
+
+    @classmethod
+    def INPUT_TYPES(cls) -> dict[str, Any]:
+        return {
+            "optional": {
+                "prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": "Positive prompt. Only overwrites when non-empty.",
+                    },
+                ),
+                "negative_prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": "Negative prompt. Only overwrites when non-empty.",
+                    },
+                ),
+                "seed": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 0xFFFFFFFFFFFFFFFF,
+                        "control_after_generate": False,
+                        "tooltip": "Seed value. Only overwrites when > 0.",
+                    },
+                ),
+                "steps": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 10000,
+                        "tooltip": "Number of steps. Only overwrites when > 0.",
+                    },
+                ),
+                "cfg_scale": (
+                    "FLOAT",
+                    {
+                        "default": 0.0,
+                        "min": 0.0,
+                        "max": 100.0,
+                        "tooltip": "CFG scale. Only overwrites when > 0.",
+                    },
+                ),
+                "sampler": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Sampler name. Only overwrites when non-empty.",
+                    },
+                ),
+                "scheduler": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Scheduler name. Only overwrites when non-empty.",
+                    },
+                ),
+                "model": (
+                    "STRING,MODEL",
+                    {
+                        "default": "",
+                        "widgetType": "STRING",
+                        "tooltip": (
+                            "The checkpoint or diffusion model (UNet) used "
+                            "for generation. Fill in the name manually or "
+                            "connect a MODEL output — the model name is then "
+                            "extracted automatically. Only overwrites when "
+                            "non-empty."
+                        ),
+                    },
+                ),
+                "loras": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": (
+                            "LoRA syntax, e.g. <lora:name:strength> "
+                            "or <lora:name:model_strength:clip_strength>, "
+                            "separated by spaces. Only overwrites when non-empty."
+                        ),
+                    },
+                ),
+                "size": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": (
+                            "Image size in WIDTHxHEIGHT format (e.g. 512x768). "
+                            "Only overwrites when non-empty."
+                        ),
+                    },
+                ),
+                "clip_skip": (
+                    "INT",
+                    {
+                        "default": _CLIP_SKIP_SENTINEL,
+                        "min": -25,
+                        "max": 24,
+                        "tooltip": (
+                            "Clip skip (ComfyUI: -24..-1, A1111: 1+). "
+                            "Default -25 means not set — any other value "
+                            "overwrites."
+                        ),
+                    },
+                ),
+                "additional_data": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": (
+                            "Additional data to embed in the image metadata. "
+                            "Inserted between Clip skip and Model hash in the "
+                            "A1111-compatible parameters string. "
+                            'Example: "Copyright": "Some license info"'
+                        ),
+                    },
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("METADATA",)
+    RETURN_NAMES = ("metadata",)
+    FUNCTION = "collect_metadata"
+    OUTPUT_NODE = True
+
+    def collect_metadata(self, **kwargs: Any) -> tuple[dict[str, Any]]:
+        """Collect non-default input values into a metadata dict.
+
+        For most fields, a falsy value (empty string, 0) means "not set"
+        and is skipped.  clip_skip uses a dedicated sentinel (-25) so that
+        a wired value of 0 is preserved and reaches the metadata pipeline.
+
+        The ``model`` field accepts either a manual string or a wired MODEL
+        (ModelPatcher) connection; in the latter case the underlying model
+        name is extracted from the patcher's ``cached_patcher_init`` and
+        stored as a ComfyUI-style relative path.
+        """
+        return (collect_overwrite_params(kwargs),)

py/nodes/save_image.py

@@ -16,6 +16,156 @@ from PIL import Image, PngImagePlugin
 import piexif
 import logging
 
+# Civitai-compatible sampler name mapping: ComfyUI internal → A1111 display name
+CIVITAI_SAMPLER_MAP = {
+    "euler": "Euler",
+    "euler_ancestral": "Euler a",
+    "lms": "LMS",
+    "heun": "Heun",
+    "dpm_2": "DPM2",
+    "dpm_2_ancestral": "DPM2 a",
+    "dpmpp_2s_ancestral": "DPM++ 2S a",
+    "dpmpp_2m": "DPM++ 2M",
+    "dpmpp_sde": "DPM++ SDE",
+    "dpmpp_sde_gpu": "DPM++ SDE",
+    "dpmpp_2m_sde": "DPM++ 2M SDE",
+    "dpmpp_2m_sde_gpu": "DPM++ 2M SDE",
+    "dpmpp_3m_sde": "DPM++ 3M SDE",
+    "dpm_fast": "DPM fast",
+    "dpm_adaptive": "DPM adaptive",
+    "ddim": "DDIM",
+    "plms": "PLMS",
+    "uni_pc_bh2": "UniPC",
+    "uni_pc": "UniPC",
+    "lcm": "LCM",
+}
+
+# Base model display name → AIR URN slug
+# Sourced from civitai source: src/shared/constants/basemodel.constants.ts
+BASE_MODEL_AIR_SLUG = {
+    # Stable Diffusion family
+    "SD 1.4": "sd1",
+    "SD 1.5": "sd1",
+    "SD 1.5 LCM": "sd1",
+    "SD 1.5 Hyper": "sd1",
+    "SD 2.0": "sd2",
+    "SD 2.0 768": "sd2",
+    "SD 2.1": "sd2",
+    "SD 2.1 768": "sd2",
+    "SD 2.1 Unclip": "sd2",
+    "SD 3.0": "sd3",
+    "SD 3.5": "sd35",
+    "SD 3.5 Large": "sd35",
+    "SD 3.5 Large Turbo": "sd35",
+    "SD 3.5 Medium": "sd35",
+    "SDXL 0.9": "sdxl",
+    "SDXL 1.0": "sdxl",
+    "SDXL 1.0 LCM": "sdxl",
+    "SDXL Lightning": "sdxl",
+    "SDXL Hyper": "sdxl",
+    "SDXL Turbo": "sdxl",
+    "SDXL Distilled": "sdxldistilled",
+    "Stable Cascade": "scascade",
+    "Stable Video Diffusion": "svd",
+    "SVD": "svd",
+    "SVD XT": "svdxt",
+
+    # SDXL community fine-tunes
+    "Pony": "pony",
+    "Pony Diffusion": "pony",
+    "Illustrious": "illustrious",
+    "NoobAI": "noobai",
+    "Animagine": "illustrious",
+
+    # Flux family
+    "Flux.1": "flux1",
+    "Flux.1 D": "flux1",
+    "Flux.1 S": "flux1",
+    "Flux.1 Krea": "fluxkrea",
+    "Flux.1 Kontext": "flux1kontext",
+    "Flux.2": "flux2",
+    "Flux.2 D": "flux2",
+    "Flux.2 Klein 9B": "flux2klein_9b",
+    "Flux.2 Klein 9B Base": "flux2klein_9b_base",
+    "Flux.2 Klein 4B": "flux2klein_4b",
+    "Flux.2 Klein 4B Base": "flux2klein_4b_base",
+
+    # Other image models (sorted alphabetically)
+    "AuraFlow": "auraflow",
+    "Chroma": "chroma",
+    "HiDream": "hidream",
+    "HiDream-O1": "hidream-o1",
+    "Hunyuan DiT": "hydit1",
+    "Hunyuan Video": "hyv1",
+    "Kolors": "kolors",
+    "Lumina": "lumina",
+    "Mochi": "mochi",
+    "ODOR": "odor",
+    "PixArt Alpha": "pixarta",
+    "PixArt Sigma": "pixarte",
+    "Playground v2": "playgroundv2",
+    "Playground v2.5": "playgroundv2",
+    "Pony Diffusion V7": "ponyv7",
+
+    # Video models
+    "CogVideoX": "cogvideox",
+    "LTX Video": "ltxv",
+    "LTX Video 2": "ltxv2",
+    "LTX Video 2.3": "ltxv23",
+    "Wan Video": "wanvideo",
+    "Wan Video 1.3B T2V": "wanvideo_13b_t2v",
+    "Wan Video 14B T2V": "wanvideo_14b_t2v",
+    "Wan Video 14B I2V 480p": "wanvideo_14b_i2v_480p",
+    "Wan Video 14B I2V 720p": "wanvideo_14b_i2v_720p",
+
+    # Third-party / proprietary image models
+    "Boogu": "boogu",
+    "Ernie": "ernie",
+    "Grok": "grok",
+    "HappyHorse": "happyhorse",
+    "Ideogram": "ideogram",
+    "Ideogram 4.0": "ideogram",
+    "Imagen": "imagen4",
+    "Imagen 4": "imagen4",
+    "Krea": "krea2",
+    "Krea 2": "krea2",
+    "Lens": "lens",
+    "MAI": "mai",
+    "Nano Banana": "nanobanana",
+    "OpenAI": "openai",
+    "Reve": "reve",
+    "Reve 2": "reve",
+    "Reve 2.1": "reve",
+    "Seedream": "seedream",
+    "Sora": "sora2",
+    "Sora 2": "sora2",
+    "Veo": "veo3",
+    "Veo 2": "veo3",
+    "Veo 3": "veo3",
+    "ZImageTurbo": "zimageturbo",
+    "ZImageBase": "zimagebase",
+    "ZImage": "zimagebase",
+
+    # Third-party video models
+    "Hailuo by MiniMax": "minimax",
+    "Haiper": "haiper",
+    "Kling": "kling",
+    "Lightricks": "lightricks",
+    "Seedance": "seedance",
+    "Vidu": "vidu",
+
+    # Qwen family
+    "Qwen": "qwen",
+    "Qwen 2": "qwen2",
+
+    # Anima
+    "Anima": "anima",
+
+    # Special
+    "Upscaler": "upscaler",
+    "Other": "other",
+}
+
 logger = logging.getLogger(__name__)
 
 
@@ -70,11 +220,29 @@ class SaveImageLM:
                         "tooltip": "Compression quality for JPEG and lossy WebP formats (1-100). Higher values mean better quality but larger files.",
                     },
                 ),
+                "webp_method": (
+                    "INT",
+                    {
+                        "default": 6,
+                        "min": 0,
+                        "max": 6,
+                        "tooltip": "WebP compression method (0-6). 0=fastest/largest, 6=slowest/smallest. Only applies when file_format is 'webp'.",
+                    },
+                ),
+                "jpeg_subsampling": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 2,
+                        "tooltip": "JPEG chroma subsampling level. 0=4:4:4 (best quality), 1=4:2:2, 2=4:2:0 (smallest files). Only applies when file_format is 'jpeg'.",
+                    },
+                ),
                 "embed_workflow": (
                     "BOOLEAN",
                     {
                         "default": False,
-                        "tooltip": "Embeds the complete workflow data into the image metadata. Only works with PNG and WebP formats.",
+                        "tooltip": "When enabled, saved images store the complete workflow. Drag the image back into ComfyUI to restore the original node graph. PNG and WebP only.",
                     },
                 ),
                 "save_with_metadata": (
@@ -84,6 +252,13 @@ class SaveImageLM:
                         "tooltip": "When enabled, embeds generation parameters into the saved image metadata. Disable to skip writing generation metadata.",
                     },
                 ),
+                "add_loras_to_prompt": (
+                    "BOOLEAN",
+                    {
+                        "default": False,
+                        "tooltip": "When enabled, appends the LoRA syntax line (e.g. <lora:name:strength>) after the positive prompt in the saved metadata.",
+                    },
+                ),
                 "add_counter_to_filename": (
                     "BOOLEAN",
                     {
@@ -142,148 +317,197 @@ class SaveImageLM:
 
         return None
 
-    def format_metadata(self, metadata_dict):
+    def _resolve_model_cache_entry(self, scanner_type: str, name: str):
-        """Format metadata in the requested format similar to userComment example"""
+        """Resolve model hash, civitai metadata, and base_model from scanner cache.
-        if not metadata_dict:
+        Returns (hash_str, civitai_dict, base_model_str). All values are empty defaults when not found."""
-            return ""
+        scanner = ServiceRegistry.get_service_sync(scanner_type)
+        if scanner is None or not name:
+            return "", {}, ""
 
-        # Helper function to only add parameter if value is not None
+        entry = self._get_cached_model_by_name(scanner, name)
-        def add_param_if_not_none(param_list, label, value):
+        if entry is None:
-            if value is not None:
+            basename = os.path.splitext(os.path.basename(name))[0]
-                param_list.append(f"{label}: {value}")
+            hash_val = scanner.get_hash_by_filename(basename)
+            return (hash_val or "").lower(), {}, ""
+
+        hash_val = (entry.get("sha256") or "").lower()
+        civitai = entry.get("civitai") or {}
+        base_model = entry.get("base_model") or ""
+        return hash_val, civitai, base_model
+
+    @staticmethod
+    def _get_civitai_sampler_name(sampler_name: str, scheduler: str) -> str:
+        if sampler_name in CIVITAI_SAMPLER_MAP:
+            civitai_name = CIVITAI_SAMPLER_MAP[sampler_name]
+            if scheduler == "karras":
+                civitai_name += " Karras"
+            elif scheduler == "exponential":
+                civitai_name += " Exponential"
+            return civitai_name
+        else:
+            if scheduler and scheduler != "normal":
+                return f"{sampler_name}_{scheduler}"
+            return sampler_name
+
+    @staticmethod
+    def _build_air_string(base_model: str, model_type: str, model_id: int, version_id: int) -> str:
+        slug = BASE_MODEL_AIR_SLUG.get(base_model, "other")
+        type_lower = model_type.lower() if model_type else "other"
+        return f"urn:air:{slug}:{type_lower}:civitai:{model_id}@{version_id}"
+
+    def format_metadata(self, metadata_dict: dict, add_loras_to_prompt: bool = False) -> str:
+        """Format metadata as A1111-compatible parameters string with Hashes JSON and Civitai resources."""
+        if not metadata_dict: return ""
 
-        # Extract the prompt and negative prompt
         prompt = metadata_dict.get("prompt", "")
         negative_prompt = metadata_dict.get("negative_prompt", "")
-
+        steps = metadata_dict.get("steps")
-        # Extract loras from the prompt if present
+        cfg = metadata_dict.get("guidance")
+        if cfg is None:
+            cfg = metadata_dict.get("cfg_scale")
+        if cfg is None:
+            cfg = metadata_dict.get("cfg")
+        seed = metadata_dict.get("seed")
+        size = metadata_dict.get("size")
+        sampler = metadata_dict.get("sampler") or ""
+        scheduler = metadata_dict.get("scheduler") or "normal"
+        checkpoint = metadata_dict.get("checkpoint") or ""
         loras_text = metadata_dict.get("loras", "")
-        lora_hashes = {}
+        clip_skip = metadata_dict.get("clip_skip")
 
-        # If loras are found, add them on a new line after the prompt
+        # Parse LoRA entries from <lora:name:strength> format
+        lora_entries: list[tuple[str, float]] = []
         if loras_text:
-            prompt_with_loras = f"{prompt}\n{loras_text}"
+            for match in re.findall(r"<lora:([^:]+):([^>]+)>", loras_text):
+                lora_name, strength_str = match
+                try:
+                    strength = float(strength_str)
+                except (ValueError, TypeError):
+                    strength = 1.0
+                lora_entries.append((lora_name, strength))
 
-            # Extract lora names from the format <lora:name:strength>
+        # Resolve checkpoint hash and Civitai data from local cache
-            lora_matches = re.findall(r"<lora:([^:]+):([^>]+)>", loras_text)
+        ckpt_hash, ckpt_civitai, ckpt_base_model = "", {}, ""
+        ckpt_display_name = ""
+        if checkpoint:
+            ckpt_hash, ckpt_civitai, ckpt_base_model = self._resolve_model_cache_entry(
+                "checkpoint_scanner", checkpoint
+            )
+            ckpt_display_name = os.path.splitext(os.path.basename(checkpoint))[0]
 
-            # Get hash for each lora
+        # Resolve LoRA hash and Civitai data from local cache
-            for lora_name, strength in lora_matches:
+        loras_data: list[dict] = []
-                hash_value = self.get_lora_hash(lora_name)
+        for lora_name, strength in lora_entries:
-                if hash_value:
+            lora_hash, lora_civitai, lora_base_model = self._resolve_model_cache_entry(
-                    lora_hashes[lora_name] = hash_value
+                "lora_scanner", lora_name
-        else:
+            )
-            prompt_with_loras = prompt
+            loras_data.append({
+                "name": lora_name,
+                "strength": strength,
+                "hash": lora_hash,
+                "civitai": lora_civitai,
+                "base_model": lora_base_model,
+            })
 
-        # Format the first part (prompt and loras)
+        # Build Hashes JSON (A1111 / Civitai standard format)
-        metadata_parts = [prompt_with_loras]
+        hashes: dict[str, str] = {}
+        if ckpt_hash:
+            hashes["model"] = ckpt_hash[:10].upper()
+        for lora in loras_data:
+            if lora["hash"]:
+                hashes[f"LORA:{lora['name']}"] = lora["hash"][:10].upper()
 
-        # Add negative prompt
+        # Build Civitai resources JSON array
-        if negative_prompt:
+        civitai_resources: list[dict] = []
-            metadata_parts.append(f"Negative prompt: {negative_prompt}")
+        if ckpt_civitai.get("id", 0) > 0:
+            ckpt_resource: dict = {}
+            ckpt_type = (ckpt_civitai.get("model") or {}).get("type", "Checkpoint")
+            model_id = ckpt_civitai.get("modelId", 0)
+            version_id = ckpt_civitai.get("id", 0)
+            if model_id and version_id:
+                ckpt_resource["air"] = self._build_air_string(
+                    ckpt_base_model, ckpt_type, int(model_id), int(version_id)
+                )
+            elif version_id:
+                ckpt_resource["modelVersionId"] = int(version_id)
+            if ckpt_civitai.get("name"):
+                ckpt_resource["versionName"] = ckpt_civitai["name"]
+            if ckpt_resource:
+                civitai_resources.append(ckpt_resource)
 
-        # Format the second part (generation parameters)
+        for lora in loras_data:
-        params = []
+            lora_civitai = lora["civitai"]
+            if not lora_civitai or lora_civitai.get("id", 0) <= 0:
+                continue
+            lora_resource: dict = {"weight": lora["strength"]}
+            lora_type = (lora_civitai.get("model") or {}).get("type", "LORA")
+            model_id = lora_civitai.get("modelId", 0)
+            version_id = lora_civitai.get("id", 0)
+            if model_id and version_id:
+                lora_resource["air"] = self._build_air_string(
+                    lora["base_model"], lora_type, int(model_id), int(version_id)
+                )
+            elif version_id:
+                lora_resource["modelVersionId"] = int(version_id)
+            if lora_civitai.get("name"):
+                lora_resource["versionName"] = lora_civitai["name"]
+            civitai_resources.append(lora_resource)
 
-        # Add standard parameters in the correct order
+        sampler_name = CIVITAI_SAMPLER_MAP.get(sampler, sampler) if sampler else None
-        if "steps" in metadata_dict:
-            add_param_if_not_none(params, "Steps", metadata_dict.get("steps"))
 
-        # Combine sampler and scheduler information
-        sampler_name = None
-        scheduler_name = None
-
-        if "sampler" in metadata_dict:
-            sampler = metadata_dict.get("sampler")
-            # Convert ComfyUI sampler names to user-friendly names
-            sampler_mapping = {
-                "euler": "Euler",
-                "euler_ancestral": "Euler a",
-                "dpm_2": "DPM2",
-                "dpm_2_ancestral": "DPM2 a",
-                "heun": "Heun",
-                "dpm_fast": "DPM fast",
-                "dpm_adaptive": "DPM adaptive",
-                "lms": "LMS",
-                "dpmpp_2s_ancestral": "DPM++ 2S a",
-                "dpmpp_sde": "DPM++ SDE",
-                "dpmpp_sde_gpu": "DPM++ SDE",
-                "dpmpp_2m": "DPM++ 2M",
-                "dpmpp_2m_sde": "DPM++ 2M SDE",
-                "dpmpp_2m_sde_gpu": "DPM++ 2M SDE",
-                "ddim": "DDIM",
-            }
-            sampler_name = sampler_mapping.get(sampler, sampler)
-
-        if "scheduler" in metadata_dict:
-            scheduler = metadata_dict.get("scheduler")
         scheduler_mapping = {
-                "normal": "Simple",
+            "normal": "Normal",
             "karras": "Karras",
             "exponential": "Exponential",
             "sgm_uniform": "SGM Uniform",
             "sgm_quadratic": "SGM Quadratic",
         }
-            scheduler_name = scheduler_mapping.get(scheduler, scheduler)
+        scheduler_name = scheduler_mapping.get(scheduler, scheduler) if scheduler else None
 
-        # Add combined sampler and scheduler information
+        # Build output lines
+        prompt_line = prompt if prompt else ""
+        if add_loras_to_prompt and loras_text:
+            prompt_line = f"{prompt_line}\n{loras_text}" if prompt_line else loras_text
+        lines = [prompt_line] if prompt_line else [""]
+        if negative_prompt:
+            lines.append(f"Negative prompt: {negative_prompt}")
+
+        params: list[str] = []
+        if steps is not None:
+            params.append(f"Steps: {steps}")
         if sampler_name:
             if scheduler_name:
                 params.append(f"Sampler: {sampler_name} {scheduler_name}")
             else:
                 params.append(f"Sampler: {sampler_name}")
-
+        if cfg is not None:
-        # CFG scale (Use guidance if available, otherwise fall back to cfg_scale or cfg)
+            params.append(f"CFG scale: {cfg}")
-        if "guidance" in metadata_dict:
+        if seed is not None:
-            add_param_if_not_none(params, "CFG scale", metadata_dict.get("guidance"))
+            params.append(f"Seed: {seed}")
-        elif "cfg_scale" in metadata_dict:
+        if size:
-            add_param_if_not_none(params, "CFG scale", metadata_dict.get("cfg_scale"))
+            params.append(f"Size: {size}")
-        elif "cfg" in metadata_dict:
+        if clip_skip is not None:
-            add_param_if_not_none(params, "CFG scale", metadata_dict.get("cfg"))
+            try:
-
+                params.append(f"Clip skip: {abs(int(clip_skip))}")
-        # Seed
+            except (ValueError, TypeError):
-        if "seed" in metadata_dict:
+                pass
-            add_param_if_not_none(params, "Seed", metadata_dict.get("seed"))
+        additional_data = metadata_dict.get("additional_data", "")
-
+        if additional_data:
-        # Size
+            params.append(additional_data)
-        if "size" in metadata_dict:
+        if ckpt_hash:
-            add_param_if_not_none(params, "Size", metadata_dict.get("size"))
+            params.append(f"Model hash: {ckpt_hash[:10].upper()}")
-
+        if ckpt_display_name:
-        # Model info
+            params.append(f"Model: {ckpt_display_name}")
-        if "checkpoint" in metadata_dict:
+        if hashes:
-            # Ensure checkpoint is a string before processing
+            params.append(f"Hashes: {json.dumps(hashes, separators=(',', ':'))}")
-            checkpoint = metadata_dict.get("checkpoint")
+        params.append("Version: ComfyUI")
-            if checkpoint is not None:
+        if civitai_resources:
-                # Get model hash
-                model_hash = self.get_checkpoint_hash(checkpoint)
-
-                # Extract basename without path
-                checkpoint_name = os.path.basename(checkpoint)
-                # Remove extension if present
-                checkpoint_name = os.path.splitext(checkpoint_name)[0]
-
-                # Add model hash if available
-                if model_hash:
             params.append(
-                        f"Model hash: {model_hash[:10]}, Model: {checkpoint_name}"
+                f"Civitai resources: {json.dumps(civitai_resources, separators=(',', ':'))}"
             )
-                else:
-                    params.append(f"Model: {checkpoint_name}")
 
-        # Add LoRA hashes if available
+        lines.append(", ".join(params))
-        if lora_hashes:
+        return "\n".join(lines)
-            lora_hash_parts = []
-            for lora_name, hash_value in lora_hashes.items():
-                lora_hash_parts.append(f"{lora_name}: {hash_value[:10]}")
-
-            if lora_hash_parts:
-                params.append(f'Lora hashes: "{", ".join(lora_hash_parts)}"')
-
-        # Combine all parameters with commas
-        metadata_parts.append(", ".join(params))
-
-        # Join all parts with a new line
-        return "\n".join(metadata_parts)
 
     # credit to nkchocoai
     # Add format_filename method to handle pattern substitution
@@ -573,10 +797,13 @@ class SaveImageLM:
         extra_pnginfo=None,
         lossless_webp=True,
         quality=100,
+        webp_method=6,
+        jpeg_subsampling=0,
         embed_workflow=False,
         save_with_metadata=True,
         add_counter_to_filename=True,
         save_as_recipe=False,
+        add_loras_to_prompt=False,
     ):
         """Save images with metadata"""
         results = []
@@ -585,7 +812,7 @@ class SaveImageLM:
         raw_metadata = get_metadata()
         metadata_dict = MetadataProcessor.to_dict(raw_metadata, id)
 
-        metadata = self.format_metadata(metadata_dict)
+        metadata = self.format_metadata(metadata_dict, add_loras_to_prompt)
 
         # Process filename_prefix with pattern substitution
         filename_prefix = self.format_filename(filename_prefix, metadata_dict)
@@ -627,15 +854,14 @@ class SaveImageLM:
             elif file_format == "jpeg":
                 file = base_filename + ".jpg"
                 file_extension = ".jpg"
-                save_kwargs = {"quality": quality, "optimize": True}
+                save_kwargs = {"quality": quality, "optimize": True, "subsampling": jpeg_subsampling}
             elif file_format == "webp":
                 file = base_filename + ".webp"
                 file_extension = ".webp"
-                # Add optimization param to control performance
                 save_kwargs = {
                     "quality": quality,
                     "lossless": lossless_webp,
-                    "method": 0,
+                    "method": webp_method,
                 }
             else:
                 raise ValueError(f"Unsupported file format: {file_format}")
@@ -722,10 +948,13 @@ class SaveImageLM:
         extra_pnginfo=None,
         lossless_webp=True,
         quality=100,
+        webp_method=6,
+        jpeg_subsampling=0,
         embed_workflow=False,
         save_with_metadata=True,
         add_counter_to_filename=True,
         save_as_recipe=False,
+        add_loras_to_prompt=False,
     ):
         """Process and save image with metadata"""
         # Make sure the output directory exists
@@ -751,10 +980,13 @@ class SaveImageLM:
             extra_pnginfo,
             lossless_webp,
             quality,
+            webp_method,
+            jpeg_subsampling,
             embed_workflow,
             save_with_metadata,
             add_counter_to_filename,
             save_as_recipe,
+            add_loras_to_prompt,
         )
 
         return {

py/nodes/unet_loader.py

@@ -7,6 +7,21 @@ from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_c
 logger = logging.getLogger(__name__)
 
 
+def _reload_gguf_unet(
+    unet_path: str, weight_dtype: str, disable_dynamic: bool = False
+) -> object:
+    """Reload a GGUF diffusion model from disk (cached_patcher_init factory).
+
+    Mirrors the GGUF branch of UNETLoaderLM.load_unet so ModelPatcher
+    deepclone/dynamic machinery can rebuild GGUF models with the correct
+    GGMLOps. ``disable_dynamic`` is accepted for signature compatibility
+    with core ComfyUI loaders.
+    """
+    loader = UNETLoaderLM()
+    model, = loader._load_gguf_unet(unet_path, unet_path, weight_dtype)
+    return model
+
+
 class UNETLoaderLM:
     """UNET Loader with support for extra folder paths
 
@@ -196,6 +211,12 @@ class UNETLoaderLM:
             # Wrap with GGUFModelPatcher
             model = GGUFModelPatcher.clone(model)
 
+            # Register a reload factory so the MODEL carries its source path
+            # (cached_patcher_init) like core ComfyUI loaders do — required
+            # for model-name extraction downstream and for ModelPatcher
+            # deepclone/dynamic machinery.
+            model.cached_patcher_init = (_reload_gguf_unet, (unet_path, weight_dtype))
+
             return (model,)
 
         except Exception as e:

py/routes/handlers/misc_handlers.py

@@ -1562,6 +1562,11 @@ class SettingsHandler:
                             {"success": False, "error": validation_error}
                         )
 
+                if key == "update_channel" and value not in ("release", "nightly"):
+                    return web.json_response(
+                        {"success": False, "error": "update_channel must be 'release' or 'nightly'"}
+                    )
+
                 if value == "__DELETE__" and key in (
                     "proxy_username",
                     "proxy_password",
@@ -2585,6 +2590,8 @@ class ModelLibraryHandler:
                     status=400,
                 )
 
+            cursor = request.query.get("cursor")
+
             metadata_provider = await self._metadata_provider_factory()
             if not metadata_provider:
                 return web.json_response(
@@ -2593,7 +2600,7 @@ class ModelLibraryHandler:
                 )
 
             try:
-                models = await metadata_provider.get_user_models(username)
+                result = await metadata_provider.get_user_models(username, cursor)
             except NotImplementedError:
                 return web.json_response(
                     {
@@ -2603,14 +2610,35 @@ class ModelLibraryHandler:
                     status=501,
                 )
 
-            if models is None:
+            if result is None:
                 return web.json_response(
                     {"success": False, "error": "Failed to fetch user models"},
                     status=502,
                 )
 
+            if isinstance(result, dict):
+                models = result.get("items")
+                next_cursor = result.get("nextCursor")
+            else:
+                # Defensive: tolerate providers that still return a raw list
+                models = result
+                next_cursor = None
+
             if not isinstance(models, list):
                 models = []
+            if next_cursor is not None and not isinstance(next_cursor, str):
+                next_cursor = str(next_cursor)
+
+            estimated_total = None
+            if cursor is None:
+                get_count = getattr(metadata_provider, "get_creator_model_count", None)
+                if get_count is not None:
+                    try:
+                        estimated_total = await get_count(username)
+                    except Exception:  # best-effort only
+                        estimated_total = None
+                if not isinstance(estimated_total, int):
+                    estimated_total = None
 
             lora_scanner = await self._service_registry.get_lora_scanner()
             checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
@@ -2630,6 +2658,7 @@ class ModelLibraryHandler:
             versions: list[dict] = []
             history_service = await self._get_download_history_service()
             model_ids: list[int] = []
+            model_count = 0
             for model in models:
                 try:
                     model_ids.append(int(model.get("id")))
@@ -2663,6 +2692,8 @@ class ModelLibraryHandler:
                 if model_type not in normalized_allowed_types:
                     continue
 
+                model_count += 1
+
                 scanner = type_scanner_map.get(model_type)
                 if scanner is None:
                     return web.json_response(
@@ -2728,7 +2759,15 @@ class ModelLibraryHandler:
                     )
 
             return web.json_response(
-                {"success": True, "username": username, "versions": versions}
+                {
+                    "success": True,
+                    "username": username,
+                    "versions": versions,
+                    "modelCount": model_count,
+                    "nextCursor": next_cursor,
+                    "hasMore": next_cursor is not None,
+                    "estimatedTotal": estimated_total,
+                }
             )
         except Exception as exc:  # pragma: no cover - defensive logging
             logger.error("Failed to get Civitai user models: %s", exc, exc_info=True)

py/routes/handlers/model_handlers.py

@@ -394,12 +394,14 @@ class ModelListingHandler:
         )
 
         # View-local-versions filter: show all local versions of a specific model
+        # Accepts either a CivitAI modelId (int) or a HF group key like "hf:user/repo"
         civitai_model_id = request.query.get("civitai_model_id")
         if civitai_model_id is not None:
             try:
                 civitai_model_id = int(civitai_model_id)
             except (TypeError, ValueError):
-                civitai_model_id = None
+                # Keep as string — could be an HF group key (e.g. "hf:user/repo")
+                pass
 
         return {
             "page": page,
@@ -537,6 +539,7 @@ class ModelManagementHandler:
                     # Update model_data with new hash
                     model_data["sha256"] = sha256
                     model_data["hash_status"] = "completed"
+                    hash_status = "completed"
                 else:
                     return web.json_response(
                         {"success": False, "error": "No SHA256 hash found"}, status=400
@@ -544,6 +547,32 @@ class ModelManagementHandler:
 
             await MetadataManager.hydrate_model_data(model_data)
 
+            # hydrate_model_data replaces model_data with .metadata.json content,
+            # which may lack sha256. Restore from cache and persist the fix.
+            if not model_data.get("sha256"):
+                if sha256:
+                    model_data["sha256"] = sha256
+                    model_data["hash_status"] = model_data.get("hash_status", hash_status)
+                    data_to_save = model_data.copy()
+                    data_to_save.pop("folder", None)
+                    await MetadataManager.save_metadata(file_path, data_to_save)
+                else:
+                    sha256 = await calculate_sha256(file_path)
+                    if sha256:
+                        model_data["sha256"] = sha256.lower()
+                        model_data["hash_status"] = "completed"
+                        data_to_save = model_data.copy()
+                        data_to_save.pop("folder", None)
+                        await MetadataManager.save_metadata(file_path, data_to_save)
+                    else:
+                        return web.json_response(
+                            {
+                                "success": False,
+                                "error": "Failed to compute SHA256 hash for model",
+                            },
+                            status=500,
+                        )
+
             success, error = await self._metadata_sync.fetch_and_update_model(
                 sha256=model_data["sha256"],
                 file_path=file_path,
@@ -566,7 +595,12 @@ class ModelManagementHandler:
                     {"success": False, "error": OFFLINE_FRIENDLY_MESSAGE},
                     status=503,
                 )
-            self._logger.error("Error fetching from CivitAI: %s", exc, exc_info=True)
+            self._logger.error(
+                "Error fetching from CivitAI for %s: %s",
+                locals().get("file_path", "unknown"),
+                exc,
+                exc_info=True,
+            )
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
     async def relink_civitai(self, request: web.Request) -> web.Response:
@@ -1454,8 +1488,73 @@ class ModelQueryHandler:
             search = request.query.get("search", "").strip()
             limit = min(int(request.query.get("limit", "15")), 100)
             offset = max(0, int(request.query.get("offset", "0")))
+
+            folder = request.query.get("folder")
+            recursive = request.query.get("recursive", "true").lower() == "true"
+            base_models = list(request.query.getall("base_model", []))
+            model_types = list(request.query.getall("model_type", []))
+
+            tag_filters: Dict[str, str] = {}
+            for tag in request.query.getall("tag_include", []):
+                if tag:
+                    tag_filters[tag] = "include"
+            for tag in request.query.getall("tag_exclude", []):
+                if tag:
+                    tag_filters[tag] = "exclude"
+
+            auto_tag_filters: Dict[str, str] = {}
+            for tag in request.query.getall("auto_tag_include", []):
+                if tag:
+                    auto_tag_filters[tag] = "include"
+            for tag in request.query.getall("auto_tag_exclude", []):
+                if tag:
+                    auto_tag_filters[tag] = "exclude"
+
+            tag_logic = request.query.get("tag_logic", "any").lower()
+            if tag_logic not in ("any", "all"):
+                tag_logic = "any"
+
+            credit_required = request.query.get("credit_required")
+            if credit_required is not None:
+                credit_required = credit_required.lower() not in ("false", "0", "")
+
+            allow_selling_generated_content = request.query.get(
+                "allow_selling_generated_content"
+            )
+            if allow_selling_generated_content is not None:
+                allow_selling_generated_content = (
+                    allow_selling_generated_content.lower() not in ("false", "0", "")
+                )
+
+            # The presence of the recursive param (always sent by the loras
+            # widget when filter mode is on) signals that the filter pipeline
+            # must run even when no concrete filter is set, so global settings
+            # like show_only_sfw stay consistent with the list endpoint.
+            apply_filters = (
+                "recursive" in request.query
+                or folder is not None
+                or bool(base_models)
+                or bool(model_types)
+                or bool(tag_filters)
+                or bool(auto_tag_filters)
+                or credit_required is not None
+                or allow_selling_generated_content is not None
+            )
+
             matching_paths = await self._service.search_relative_paths(
-                search, limit, offset
+                search,
+                limit,
+                offset,
+                folder=folder,
+                recursive=recursive,
+                base_models=base_models,
+                model_types=model_types,
+                tags=tag_filters,
+                auto_tags=auto_tag_filters,
+                tag_logic=tag_logic,
+                credit_required=credit_required,
+                allow_selling_generated_content=allow_selling_generated_content,
+                apply_filters=apply_filters,
             )
             return web.json_response(
                 {"success": True, "relative_paths": matching_paths}

py/routes/handlers/recipe_handlers.py

@@ -10,7 +10,7 @@ import asyncio
 import tempfile
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional
+from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional, Tuple
 
 from aiohttp import web
 
@@ -44,6 +44,22 @@ EnsureDependenciesCallable = Callable[[], Awaitable[None]]
 RecipeScannerGetter = Callable[[], Any]
 CivitaiClientGetter = Callable[[], Any]
 
+# Cap concurrent preview-dimension reads across requests. With a cold LRU
+# cache one page can touch up to page_size image files; 16 balances SSD and
+# HDD throughput without starving the event loop.
+_DIMS_READ_SEMAPHORE = asyncio.Semaphore(16)
+
+
+async def _read_preview_dims(path: str) -> Optional[Tuple[int, int]]:
+    """Read preview dimensions off the event loop under the concurrency cap.
+
+    PIL I/O runs in a worker thread so it never blocks the event loop, and the
+    semaphore bounds how many files are opened at once even when many list
+    requests land together.
+    """
+    async with _DIMS_READ_SEMAPHORE:
+        return await asyncio.to_thread(ExifUtils.get_image_dimensions, path)
+
 
 @dataclass(frozen=True)
 class RecipeHandlerSet:
@@ -246,7 +262,8 @@ class RecipeListingHandler:
                 recursive=recursive,
             )
 
-            for item in result.get("items", []):
+            items = result.get("items", [])
+            for item in items:
                 file_path = item.get("file_path")
                 if file_path:
                     item["file_url"] = self.format_recipe_file_url(file_path)
@@ -255,6 +272,26 @@ class RecipeListingHandler:
                 item.setdefault("loras", [])
                 item.setdefault("base_model", "")
 
+            # Batch preview dimension reads with asyncio.gather. The previous
+            # loop awaited asyncio.to_thread once per item, so a page_size=100
+            # request submitted 100 sequential thread calls (50-300ms cold-page
+            # latency). gather runs them concurrently while the semaphore caps
+            # disk opens; dimensions stay omitted (not null) when a preview has
+            # no readable size (video, missing file).
+            to_read = [
+                (i, item.get("file_path"))
+                for i, item in enumerate(items)
+                if item.get("file_path")
+            ]
+            if to_read:
+                dims_list = await asyncio.gather(
+                    *(_read_preview_dims(path) for _, path in to_read)
+                )
+                for (idx, _), dims in zip(to_read, dims_list):
+                    if dims:
+                        item = items[idx]
+                        item["width"], item["height"] = dims
+
             return web.json_response(result)
         except Exception as exc:
             self._logger.error("Error retrieving recipes: %s", exc, exc_info=True)

py/routes/update_routes.py

@@ -38,6 +38,84 @@ def _clean_excludes() -> List[str]:
     return excludes
 
 
+def _stage_preserved_items(plugin_root: str) -> tuple[str, list[str]]:
+    """Move preserved user-data items to a temp directory outside *plugin_root*.
+
+    This ensures that ``git reset --hard``, ``git clean -fd``, and ZIP-based
+    replacement cannot touch these files even when ``-e`` exclusion patterns
+    are mishandled (e.g. on Windows where forward-slash patterns may not
+    match backslash-prefixed paths in some Git builds, or where file locks
+    prevent deletion/recreation).
+
+    Returns:
+        ``(backup_root, staged_names)``: the temp directory path and the
+        list of item names that were successfully moved.
+    """
+    backup_root = tempfile.mkdtemp(prefix='lora_manager_update_')
+    staged: list[str] = []
+    for name in _PRESERVE_DIRS:
+        src = os.path.join(plugin_root, name)
+        if not os.path.lexists(src):
+            continue
+        dst = os.path.join(backup_root, name)
+        try:
+            shutil.move(src, dst)
+            staged.append(name)
+            logger.debug("Staged '%s' for update safety", name)
+        except OSError:
+            # ``shutil.move`` may fail on Windows if a file handle inside
+            # the directory is still open (e.g. a SQLite WAL file). Fall
+            # back to copy-then-remove.
+            logger.debug("Move failed for '%s', falling back to copy", name)
+            try:
+                if os.path.isdir(src) and not os.path.islink(src):
+                    shutil.copytree(src, dst, symlinks=True)
+                    shutil.rmtree(src, ignore_errors=True)
+                else:
+                    shutil.copy2(src, dst)
+                    os.remove(src)
+                staged.append(name)
+                logger.info("Copied (then removed) '%s' for update safety", name)
+            except Exception as exc:
+                logger.warning(
+                    "Could not stage '%s': %s (will rely on git -e / skip lists)", name, exc
+                )
+    return backup_root, staged
+
+
+def _restore_preserved_items(plugin_root: str, backup_root: str, staged: list[str]) -> None:
+    """Move staged items back from *backup_root* into *plugin_root*.
+
+    Any leftover placeholder at the destination (created by git checkout or
+    ZIP extraction) is removed before the move.
+    """
+    for name in staged:
+        src = os.path.join(backup_root, name)
+        dst = os.path.join(plugin_root, name)
+        try:
+            if os.path.lexists(dst):
+                if os.path.isdir(dst) and not os.path.islink(dst):
+                    shutil.rmtree(dst, ignore_errors=True)
+                else:
+                    os.remove(dst)
+            shutil.move(src, dst)
+            logger.debug("Restored '%s' after update", name)
+        except OSError:
+            logger.debug("Move failed restoring '%s', falling back to copy", name)
+            try:
+                if os.path.isdir(src) and not os.path.islink(src):
+                    shutil.copytree(src, dst, symlinks=True, dirs_exist_ok=True)
+                    shutil.rmtree(src, ignore_errors=True)
+                else:
+                    shutil.copy2(src, dst)
+                    os.remove(src)
+                logger.info("Copied '%s' back after update", name)
+            except Exception as exc:
+                logger.error("Failed to restore '%s': %s", name, exc)
+    shutil.rmtree(backup_root, ignore_errors=True)
+
+
+
 class UpdateRoutes:
     """Routes for handling plugin update checks"""
     
@@ -47,6 +125,7 @@ class UpdateRoutes:
         app.router.add_get('/api/lm/check-updates', UpdateRoutes.check_updates)
         app.router.add_get('/api/lm/version-info', UpdateRoutes.get_version_info)
         app.router.add_post('/api/lm/perform-update', UpdateRoutes.perform_update)
+        app.router.add_post('/api/lm/switch-channel', UpdateRoutes.switch_channel)
     
     @staticmethod
     async def check_updates(request):
@@ -65,10 +144,17 @@ class UpdateRoutes:
 
             # Fetch remote version from GitHub
             if nightly:
-                remote_version, changelog = await UpdateRoutes._get_nightly_version()
+                local_hash = git_info.get('short_hash', '')
-                releases = None
+                nightly_version, releases_result = await asyncio.gather(
+                    UpdateRoutes._get_nightly_version(local_hash),
+                    UpdateRoutes._get_remote_version()
+                )
+                remote_version, _, behind_by, commit_date = nightly_version
+                _, changelog, releases = releases_result
             else:
                 remote_version, changelog, releases = await UpdateRoutes._get_remote_version()
+                behind_by = 0
+                commit_date = ''
             
             # Compare versions
             if nightly:
@@ -81,6 +167,10 @@ class UpdateRoutes:
                     remote_version.replace('v', '')
                 )
             
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            plugin_root = os.path.dirname(os.path.dirname(current_dir))
+            has_git = os.path.exists(os.path.join(plugin_root, '.git'))
+
             response_data = {
                 'success': True,
                 'current_version': local_version,
@@ -88,13 +178,13 @@ class UpdateRoutes:
                 'update_available': update_available,
                 'changelog': changelog,
                 'git_info': git_info,
-                'nightly': nightly
+                'nightly': nightly,
+                'has_git': has_git,
+                'releases': releases,
+                'behind_by': behind_by,
+                'commit_date': commit_date
             }
             
-            # Include releases list for stable mode
-            if releases is not None:
-                response_data['releases'] = releases
-            
             return web.json_response(response_data)
             
         except NETWORK_EXCEPTIONS as e:
@@ -126,9 +216,14 @@ class UpdateRoutes:
             # Format: version-short_hash
             version_string = f"{local_version}-{short_hash}"
             
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            plugin_root = os.path.dirname(os.path.dirname(current_dir))
+            has_git = os.path.exists(os.path.join(plugin_root, '.git'))
+
             return web.json_response({
                 'success': True,
-                'version': version_string
+                'version': version_string,
+                'has_git': has_git
             })
             
         except Exception as e:
@@ -156,20 +251,22 @@ class UpdateRoutes:
             if os.path.exists(settings_path):
                 with open(settings_path, 'r', encoding='utf-8') as f:
                     settings_backup = f.read()
-                logger.info("Backed up settings.json")
+                logger.debug("Backed up settings.json (%d bytes)", len(settings_backup))
 
+            staged_backup_dir, staged_items = _stage_preserved_items(plugin_root)
+            try:
                 git_folder = os.path.join(plugin_root, '.git')
                 if os.path.exists(git_folder):
-                # Git update
                     success, new_version = await UpdateRoutes._perform_git_update(plugin_root, nightly)
                 else:
-                # Fallback: Download ZIP and replace files
                     success, new_version = await UpdateRoutes._download_and_replace_zip(plugin_root)
+            finally:
+                _restore_preserved_items(plugin_root, staged_backup_dir, staged_items)
 
             if settings_backup and success:
                 with open(settings_path, 'w', encoding='utf-8') as f:
                     f.write(settings_backup)
-                logger.info("Restored settings.json")
+                logger.debug("Restored settings.json content (%d bytes)", len(settings_backup))
 
             if success:
                 return web.json_response({
@@ -190,6 +287,164 @@ class UpdateRoutes:
                 'error': str(e)
             })
 
+    @staticmethod
+    async def switch_channel(request):
+        """
+        Switch between release and nightly update channels.
+
+        ZIP/CNR install → Nightly: git init + checkout main (one-way upgrade)
+        Git install → Release:   git checkout latest tag (.git preserved)
+        ZIP/CNR install → Release: ZIP download (no .git, stays in ZIP mode)
+        Git install → Nightly:   git checkout main + pull
+        """
+        try:
+            body = await request.json() if request.has_body else {}
+            channel = body.get('channel', '')
+
+            if channel not in ('release', 'nightly'):
+                return web.json_response({
+                    'success': False,
+                    'error': f'Invalid channel: {channel}. Must be "release" or "nightly".'
+                })
+
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            plugin_root = os.path.dirname(os.path.dirname(current_dir))
+
+            settings_path = ensure_settings_file(logger)
+            settings_backup = None
+            if os.path.exists(settings_path):
+                with open(settings_path, 'r', encoding='utf-8') as f:
+                    settings_backup = f.read()
+                logger.debug("Backed up settings.json before channel switch (%d bytes)", len(settings_backup))
+
+            staged_backup_dir, staged_items = _stage_preserved_items(plugin_root)
+            try:
+                git_folder = os.path.join(plugin_root, '.git')
+
+                if channel == 'nightly':
+                    git_backup = None
+                    if os.path.exists(git_folder):
+                        git_backup = UpdateRoutes._backup_git(git_folder, 'nightly')
+
+                    success = False
+                    new_version = ''
+                    try:
+                        if os.path.exists(git_folder):
+                            success, new_version = await UpdateRoutes._perform_git_update(
+                                plugin_root, nightly=True
+                            )
+                        else:
+                            success, new_version = UpdateRoutes._init_git_repo(plugin_root)
+                    finally:
+                        UpdateRoutes._restore_git(git_backup, git_folder, success, 'nightly')
+                else:
+                    success = False
+                    new_version = ''
+                    if os.path.exists(git_folder):
+                        success, new_version = await UpdateRoutes._perform_git_update(
+                            plugin_root, nightly=False
+                        )
+                    else:
+                        tracking_file = os.path.join(plugin_root, '.tracking')
+                        if os.path.exists(tracking_file):
+                            os.remove(tracking_file)
+                        success, new_version = await UpdateRoutes._download_and_replace_zip(plugin_root)
+            finally:
+                _restore_preserved_items(plugin_root, staged_backup_dir, staged_items)
+
+            if settings_backup and success:
+                with open(settings_path, 'w', encoding='utf-8') as f:
+                    f.write(settings_backup)
+                logger.debug("Restored settings.json content after channel switch (%d bytes)", len(settings_backup))
+
+            if success:
+                return web.json_response({
+                    'success': True,
+                    'channel': channel,
+                    'new_version': new_version,
+                    'message': f'Switched to {channel} channel'
+                })
+            else:
+                return web.json_response({
+                    'success': False,
+                    'error': f'Failed to switch to {channel} channel'
+                })
+
+        except Exception as e:
+            logger.error("Failed to switch channel: %s", e, exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            })
+
+    @staticmethod
+    def _init_git_repo(plugin_root: str) -> tuple[bool, str]:
+        """
+        Initialize a Git repository in a ZIP-installed plugin folder.
+        Clones the remote history and checks out main branch.
+        """
+        try:
+            import git
+        except ImportError:
+            logger.error(
+                "GitPython is not available: cannot initialize git repo. "
+                "Install git or set $GIT_PYTHON_GIT_EXECUTABLE to the git binary path."
+            )
+            return False, ""
+
+        clean_excludes = _clean_excludes()
+
+        try:
+            repo = git.Repo.init(plugin_root)
+            origin = repo.create_remote(
+                'origin',
+                'https://github.com/willmiao/ComfyUI-Lora-Manager.git'
+            )
+            origin.fetch()
+
+            repo.create_head('main', origin.refs.main)
+            repo.git.checkout('main', '--force')
+            repo.git.reset('--hard')
+            repo.git.clean('-fd', *clean_excludes)
+
+            tracking_file = os.path.join(plugin_root, '.tracking')
+            if os.path.exists(tracking_file):
+                os.remove(tracking_file)
+                logger.info("Removed .tracking file (now in git mode)")
+
+            new_version = f"main-{repo.head.commit.hexsha[:7]}"
+            logger.info("Initialized git repo on main branch: %s", new_version)
+            return True, new_version
+
+        except Exception as e:
+            logger.error("Failed to initialize git repo: %s", e, exc_info=True)
+            return False, ""
+
+    @staticmethod
+    def _backup_git(git_folder, label):
+        try:
+            backup_dir = tempfile.mkdtemp()
+            backup = os.path.join(backup_dir, '.git')
+            shutil.copytree(git_folder, backup)
+            logger.info("Backed up .git before switching to %s", label)
+            return backup
+        except Exception as e:
+            logger.error("Failed to backup .git before %s switch: %s", label, e)
+            return None
+
+    @staticmethod
+    def _restore_git(git_backup, git_folder, success, label):
+        if git_backup and not success:
+            try:
+                if os.path.exists(git_folder):
+                    shutil.rmtree(git_folder)
+                shutil.copytree(git_backup, git_folder)
+                logger.info("Restored .git after failed %s switch", label)
+            except Exception as e:
+                logger.error("Failed to restore .git after %s switch: %s", label, e)
+        if git_backup:
+            shutil.rmtree(os.path.dirname(git_backup), ignore_errors=True)
+
     @staticmethod
     async def _download_and_replace_zip(plugin_root: str) -> tuple[bool, str]:
         """
@@ -244,8 +499,7 @@ class UpdateRoutes:
             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=list(_PRESERVE_DIRS))
-            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:
@@ -255,7 +509,7 @@ class UpdateRoutes:
                     extracted_root = next(os.scandir(tmp_dir)).path
 
                     # Copy files, skipping user data that should be preserved
-                    skip_items = {'settings.json', 'civitai', 'wildcards', 'backups', 'stats'}
+                    skip_items = set(_PRESERVE_DIRS)
                     for item in os.listdir(extracted_root):
                         if item in skip_items:
                             continue
@@ -272,7 +526,7 @@ 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'}
+                    skip_tracked = set(_PRESERVE_DIRS) - {'settings.json'}
                     for root, dirs, files in os.walk(extracted_root):
                         # Skip user data directories and their contents
                         rel_root = os.path.relpath(root, extracted_root)
@@ -296,6 +550,7 @@ class UpdateRoutes:
             logger.error(f"ZIP update failed: {e}", exc_info=True)
             return False, ""
 
+    @staticmethod
     def _clean_plugin_folder(plugin_root, skip_files=None):
         skip_files = skip_files or []
         for item in os.listdir(plugin_root):
@@ -308,41 +563,54 @@ class UpdateRoutes:
                 os.remove(path)
     
     @staticmethod
-    async def _get_nightly_version() -> tuple[str, List[str]]:
+    async def _get_nightly_version(local_hash: str = "") -> tuple[str, List[str], int, str]:
-        """
-        Fetch latest commit from main branch
-        """
         repo_owner = "willmiao"
         repo_name = "ComfyUI-Lora-Manager"
 
-        # Use GitHub API to fetch the latest commit from main branch
         github_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/commits/main"
 
         try:
             downloader = await get_downloader()
-            success, data = await downloader.make_request('GET', github_url, custom_headers={'Accept': 'application/vnd.github+json'})
+            success, data = await downloader.make_request(
+                'GET', github_url,
+                custom_headers={'Accept': 'application/vnd.github+json'}
+            )
 
             if not success:
-                logger.warning(f"Failed to fetch GitHub commit: {data}")
+                logger.warning("Failed to fetch GitHub commit: %s", data)
-                return "main", []
+                return "main", [], 0, ""
 
-            commit_sha = data.get('sha', '')[:7]  # Short hash
+            commit_sha = data.get('sha', '')[:7]
             commit_message = data.get('commit', {}).get('message', '')
+            commit_date = data.get('commit', {}).get('committer', {}).get('date', '')[:10]
 
-            # Format as "main-{short_hash}"
             version = f"main-{commit_sha}"
-            
-            # Use commit message as changelog
             changelog = [commit_message] if commit_message else []
 
-            return version, changelog
+            behind_by = 0
+            if local_hash and local_hash not in ('unknown', 'stable'):
+                compare_url = (
+                    f"https://api.github.com/repos/{repo_owner}/{repo_name}"
+                    f"/compare/{local_hash}...main"
+                )
+                c_ok, c_data = await downloader.make_request(
+                    'GET', compare_url,
+                    custom_headers={'Accept': 'application/vnd.github+json'}
+                )
+                if c_ok:
+                    if c_data.get('status') in ('ahead', 'diverged'):
+                        behind_by = c_data.get('ahead_by', 0)
+                    else:
+                        behind_by = c_data.get('behind_by', 0)
+
+            return version, changelog, behind_by, commit_date
 
         except NETWORK_EXCEPTIONS as e:
             logger.warning("Unable to reach GitHub for nightly version: %s", e)
-            return "main", []
+            return "main", [], 0, ""
         except Exception as e:
-            logger.error(f"Error fetching nightly version: {e}", exc_info=True)
+            logger.error("Error fetching nightly version: %s", e, exc_info=True)
-            return "main", []
+            return "main", [], 0, ""
     
     @staticmethod
     def _compare_nightly_versions(local_git_info: Dict[str, str], remote_version: str) -> bool:

py/services/base_model_service.py

@@ -1,7 +1,8 @@
 from abc import ABC, abstractmethod
 import asyncio
 import re
-from typing import Any, Dict, List, Optional, Type, TYPE_CHECKING
+import random
+from typing import Any, Dict, List, Optional, Type, Union, TYPE_CHECKING
 import logging
 import os
 import time
@@ -109,12 +110,15 @@ class BaseModelService(ABC):
         if civitai_model_id is not None:
             sorted_data = [
                 item for item in sorted_data
-                if self._extract_model_id(item) == civitai_model_id
+                if self._extract_group_key(item) == civitai_model_id
             ]
             # VLM mode: always sort by version ID descending (newest version first),
             # regardless of the current sort_by preference.
+            # Fall back to modified timestamp for non-CivitAI sources.
             sorted_data.sort(
-                key=lambda x: self._extract_version_id(x) or 0,
+                key=lambda x: self._extract_version_id(x)
+                or x.get("modified", 0)
+                or 0,
                 reverse=True,
             )
 
@@ -129,18 +133,21 @@ class BaseModelService(ABC):
             ufs = self.settings.get("version_grouping", "same_base")
             group_by_base = ufs == "same_base"
 
-            dedup_map = {}  # (modelId [,base_model]) -> (item, version_id)
+            dedup_map = {}  # (modelId [,base_model]) -> (item, version_or_modified)
             version_counter = {}  # same-key -> count
             standalone = []
             for item in sorted_data:
-                mid = self._extract_model_id(item)
+                mid = self._extract_group_key(item)
                 if mid is None:
                     standalone.append(item)
                     continue
                 key = (mid, item.get("base_model") or "") if group_by_base else mid
                 # Count all versions per key
                 version_counter[key] = version_counter.get(key, 0) + 1
-                vid = self._extract_version_id(item) or 0
+                # Prefer CivitAI version_id; fall back to modified timestamp
+                vid = self._extract_version_id(item)
+                if vid is None:
+                    vid = item.get("modified", 0) or 0
                 if key not in dedup_map or vid > dedup_map[key][1]:
                     dedup_map[key] = (item, vid)
             # Attach version_count to each surviving grouped item (shallow copy
@@ -174,16 +181,19 @@ class BaseModelService(ABC):
                 model_groups: Dict[Any, List[Dict]] = {}
                 ungrouped_standalone: List[Dict] = []
                 for item in sorted_data:
-                    mid = self._extract_model_id(item)
+                    mid = self._extract_group_key(item)
                     if mid is None:
                         ungrouped_standalone.append(item)
                         continue
                     key = (mid, item.get("base_model") or "") if group_by_base else mid
                     model_groups.setdefault(key, []).append(item)
-                # Sort versions within each group by version id descending
+                # Sort versions within each group by version id (descending);
+                # fall back to modified timestamp for non-CivitAI sources.
                 for items in model_groups.values():
                     items.sort(
-                        key=lambda x: self._extract_version_id(x) or 0,
+                        key=lambda x: self._extract_version_id(x)
+                        or x.get("modified", 0)
+                        or 0,
                         reverse=True,
                     )
                 # Sort groups by version count
@@ -381,6 +391,12 @@ class BaseModelService(ABC):
                 (item.get("model_name") or item.get("file_name") or "").lower(),
                 item.get("file_path", "").lower(),
             )
+        elif key_name == "random":
+            # Seeded random shuffle: same seed -> same order (stable pagination)
+            rng = random.Random(sort_params.seed or "random")
+            result = list(data)
+            rng.shuffle(result)
+            return result
         elif key_name == "size":
             key_fn = lambda item: (
                 int(item.get("size", 0) or 0),
@@ -697,6 +713,33 @@ class BaseModelService(ABC):
 
         return annotated
 
+    @staticmethod
+    def _extract_hf_group_key(item: Dict) -> Optional[str]:
+        """Extract `hf:{owner}/{repo}` from item's ``hf_url``, or None."""
+        hf_url = item.get("hf_url") if isinstance(item, dict) else None
+        if not hf_url or not isinstance(hf_url, str):
+            return None
+        m = re.match(
+            r"https?://huggingface\.co/([^/]+/[^/]+)", hf_url.strip()
+        )
+        if not m:
+            return None
+        return f"hf:{m.group(1)}"
+
+    @staticmethod
+    def _extract_group_key(item: Dict) -> Union[int, str, None]:
+        """Return the group identity key: CivitAI modelId (int) or HF repo (str).
+
+        Preference order:
+        1. CivitAI ``modelId`` (int)
+        2. HF repo identity ``hf:{owner}/{repo}`` (str)
+        3. ``None`` (no known grouping source)
+        """
+        mid = BaseModelService._extract_model_id(item)
+        if mid is not None:
+            return mid
+        return BaseModelService._extract_hf_group_key(item)
+
     @staticmethod
     def _extract_model_id(item: Dict) -> Optional[int]:
         civitai = item.get("civitai") if isinstance(item, dict) else None
@@ -1216,19 +1259,87 @@ class BaseModelService(ABC):
         )
 
     async def search_relative_paths(
-        self, search_term: str, limit: int = 15, offset: int = 0
+        self,
+        search_term: str,
+        limit: int = 15,
+        offset: int = 0,
+        *,
+        folder: Optional[str] = None,
+        folder_include: Optional[list] = None,
+        folder_exclude: Optional[list] = None,
+        base_models: Optional[list] = None,
+        model_types: Optional[list] = None,
+        tags: Optional[dict] = None,
+        auto_tags: Optional[dict] = None,
+        tag_logic: str = "any",
+        credit_required: Optional[bool] = None,
+        allow_selling_generated_content: Optional[bool] = None,
+        recursive: bool = True,
+        apply_filters: bool = False,
     ) -> List[str]:
-        """Search model relative file paths for autocomplete functionality"""
+        """Search model relative file paths for autocomplete functionality.
+
+        Optional filter kwargs mirror the filters used by the list endpoint
+        (/api/lm/{prefix}/list). When no filter kwargs are provided the
+        behavior is identical to plain token-based path matching.
+        """
         cache = await self.scanner.get_cached_data()
         include_terms, exclude_terms = self._parse_search_tokens(search_term)
 
+        data = cache.raw_data
+        has_filters = any(
+            [
+                apply_filters,
+                folder is not None,
+                folder_include,
+                folder_exclude,
+                base_models,
+                model_types,
+                tags,
+                auto_tags,
+                credit_required is not None,
+                allow_selling_generated_content is not None,
+            ]
+        )
+        if has_filters:
+            # Auto-tags are not stored in the scanner cache — they are computed
+            # on the fly. Pre-compute them only when an auto-tag filter is
+            # active to avoid mutating cache entries unnecessarily.
+            if auto_tags:
+                from .auto_tag_service import extract_auto_tags
+
+                for item in data:
+                    if not item.get("auto_tags"):
+                        item["auto_tags"] = extract_auto_tags(item)
+
+            criteria = FilterCriteria(
+                folder=folder,
+                folder_include=folder_include,
+                folder_exclude=folder_exclude,
+                base_models=base_models,
+                model_types=model_types,
+                tags=tags,
+                auto_tags=auto_tags,
+                search_options={"recursive": recursive},
+                tag_logic=tag_logic,
+            )
+            data = self.filter_set.apply(data, criteria)
+            if credit_required is not None:
+                data = await self._apply_credit_required_filter(
+                    data, credit_required
+                )
+            if allow_selling_generated_content is not None:
+                data = await self._apply_allow_selling_filter(
+                    data, allow_selling_generated_content
+                )
+
         matching_paths = []
 
         # Get model roots for path calculation
         model_roots = self.scanner.get_model_roots()
 
         # Collect all matching paths first (needed for proper sorting and offset)
-        for model in cache.raw_data:
+        for model in data:
             file_path = model.get("file_path", "")
             if not file_path:
                 continue

py/services/civitai_client.py

@@ -2,6 +2,7 @@ import asyncio
 import copy
 import logging
 import os
+import time
 from collections import OrderedDict
 from typing import Any, Optional, Dict, Tuple, List, Sequence
 from .connectivity_guard import (
@@ -19,6 +20,12 @@ from ..utils.civitai_utils import resolve_license_payload
 
 logger = logging.getLogger(__name__)
 
+# Best-effort cache for creator model counts, keyed by lowercase username.
+# Values are (monotonic timestamp, count or None); None results are cached
+# too so repeated failures don't hammer the API.
+_CREATOR_COUNT_CACHE_TTL_SECONDS = 600
+_creator_model_count_cache: Dict[str, Tuple[float, Optional[int]]] = {}
+
 
 class CivitaiClient:
     _instance = None
@@ -743,17 +750,34 @@ class CivitaiClient:
 
         return all_versions if all_versions else None
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(
-        """Fetch all models for a specific Civitai user."""
+        self, username: str, cursor: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        """Fetch one page (up to 100 models) for a specific Civitai user.
+
+        Returns ``{"items": [...], "nextCursor": <str|None>}`` on success,
+        or None on failure. Pass ``cursor`` (from a previous response's
+        ``nextCursor``) to fetch subsequent pages.
+        """
         if not username:
             return None
 
+        params: Dict[str, Any] = {
+            "username": username,
+            "nsfw": "true",
+            "limit": 100,
+            "sort": "Newest",
+            "period": "AllTime",
+        }
+        if cursor:
+            params["cursor"] = cursor
+
         try:
             success, result = await self._make_request(
                 "GET",
                 f"{self.base_url}/models",
                 use_auth=True,
-                params={"username": username, "nsfw": "true"},
+                params=params,
             )
 
             if not success:
@@ -765,7 +789,7 @@ class CivitaiClient:
 
             items = result.get("items") if isinstance(result, dict) else None
             if not isinstance(items, list):
-                return []
+                items = []
 
             for model in items:
                 versions = model.get("modelVersions")
@@ -774,9 +798,68 @@ class CivitaiClient:
                 for version in versions:
                     self._remove_comfy_metadata(version)
 
-            return items
+            next_cursor: Optional[str] = None
+            metadata = result.get("metadata") if isinstance(result, dict) else None
+            if isinstance(metadata, dict):
+                raw_cursor = metadata.get("nextCursor")
+                if raw_cursor is not None:
+                    next_cursor = str(raw_cursor)
+
+            return {"items": items, "nextCursor": next_cursor}
         except RateLimitError:
             raise
         except Exception as exc:  # pragma: no cover - defensive logging
             logger.error("Error fetching models for %s: %s", username, exc)
             return None
+
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        """Best-effort lookup of a creator's published model count.
+
+        Uses the ``/creators`` endpoint (a contains-match query), picking the
+        entry whose username matches exactly (case-insensitive). Returns None
+        on any failure; never raises. Results (including None) are cached
+        for ``_CREATOR_COUNT_CACHE_TTL_SECONDS``.
+        """
+        if not username:
+            return None
+
+        cache_key = username.lower()
+        cached = _creator_model_count_cache.get(cache_key)
+        if cached is not None:
+            cached_at, cached_count = cached
+            if time.monotonic() - cached_at < _CREATOR_COUNT_CACHE_TTL_SECONDS:
+                return cached_count
+
+        count: Optional[int] = None
+        try:
+            success, result = await self._make_request(
+                "GET",
+                f"{self.base_url}/creators",
+                use_auth=True,
+                params={"query": username, "limit": 10},
+            )
+
+            if success and isinstance(result, dict):
+                creators = result.get("items")
+                if isinstance(creators, list):
+                    for creator in creators:
+                        if not isinstance(creator, dict):
+                            continue
+                        creator_name = creator.get("username")
+                        if not isinstance(creator_name, str):
+                            continue
+                        if creator_name.lower() != cache_key:
+                            continue
+                        model_count = creator.get("modelCount")
+                        if isinstance(model_count, (int, float)) and not isinstance(
+                            model_count, bool
+                        ):
+                            count = int(model_count)
+                        break
+        except Exception as exc:  # best-effort only, never propagate
+            logger.debug(
+                "Failed to fetch creator model count for %s: %s", username, exc
+            )
+
+        _creator_model_count_cache[cache_key] = (time.monotonic(), count)
+        return count

py/services/download_manager.py

@@ -1389,7 +1389,17 @@ class DownloadManager:
 
             # Update save directory with relative path if provided
             if relative_path:
+                base_save_dir = save_dir
                 save_dir = os.path.join(save_dir, relative_path)
+                # Security: validate path containment after joining
+                resolved_dir = os.path.abspath(os.path.normpath(save_dir))
+                base_dir = os.path.abspath(os.path.normpath(base_save_dir))
+                if not resolved_dir.startswith(base_dir + os.sep) and resolved_dir != base_dir:
+                    logger.warning(
+                        "Path traversal detected: %s escapes %s",
+                        resolved_dir, base_dir,
+                    )
+                    return {"success": False, "error": "Download path is outside allowed directory"}
                 # Create directory if it doesn't exist
                 os.makedirs(save_dir, exist_ok=True)
 
@@ -1827,6 +1837,9 @@ class DownloadManager:
             model_tags, model_type
         )
 
+        if not first_tag:
+            first_tag = "no tags"  # Default if no tags available
+
         # Format the template with available data
         formatted_path = path_template
         formatted_path = formatted_path.replace("{base_model}", mapped_base_model)
@@ -1842,6 +1855,15 @@ class DownloadManager:
         if model_type == "embedding":
             formatted_path = formatted_path.replace(" ", "_")
 
+        # Sanitize the resolved path to prevent path traversal:
+        # - Strip leading slashes (prevents os.path.join from treating path as absolute)
+        # - Collapse double slashes from empty placeholder substitutions
+        # - Strip trailing slashes for cleanliness
+        formatted_path = formatted_path.lstrip("/")
+        while "//" in formatted_path:
+            formatted_path = formatted_path.replace("//", "/")
+        formatted_path = formatted_path.rstrip("/")
+
         return formatted_path
 
     async def _execute_download(

py/services/download_queue_service.py

@@ -31,7 +31,7 @@ class DownloadQueueService:
     _instance: Optional[DownloadQueueService] = None
     _class_lock: asyncio.Lock = asyncio.Lock()
 
-    _SCHEMA = """
+    _SCHEMA_TABLES = """
         CREATE TABLE IF NOT EXISTS download_queue (
             download_id TEXT PRIMARY KEY,
             model_id INTEGER,
@@ -74,6 +74,9 @@ class DownloadQueueService:
         );
         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);
+    """
+
+    _CREATE_UNIQUE_INDEX = """
         CREATE UNIQUE INDEX IF NOT EXISTS idx_dh_download_id
             ON download_history(download_id) WHERE download_id IS NOT NULL;
     """
@@ -115,10 +118,39 @@ class DownloadQueueService:
         if self._schema_initialized:
             return
         with self._connect() as conn:
-            conn.executescript(self._SCHEMA)
+            conn.executescript(self._SCHEMA_TABLES)
+
+            # Creating the unique index on download_history.download_id can
+            # fail if pre-existing rows have duplicate values (e.g. from a
+            # previous version that lacked the index).  Deduplicate first so
+            # that the migration does not crash on startup.
+            if not self._index_exists(conn, "idx_dh_download_id"):
+                self._remove_duplicate_download_ids(conn)
+                conn.executescript(self._CREATE_UNIQUE_INDEX)
+
             conn.commit()
         self._schema_initialized = True
 
+    @staticmethod
+    def _index_exists(conn: sqlite3.Connection, name: str) -> bool:
+        return conn.execute(
+            "SELECT 1 FROM sqlite_master WHERE type='index' AND name=?",
+            (name,),
+        ).fetchone() is not None
+
+    @staticmethod
+    def _remove_duplicate_download_ids(conn: sqlite3.Connection) -> None:
+        conn.execute("""
+            DELETE FROM download_history
+            WHERE id NOT IN (
+                SELECT MIN(id)
+                FROM download_history
+                WHERE download_id IS NOT NULL
+                GROUP BY download_id
+            )
+            AND download_id IS NOT NULL
+        """)
+
     def get_database_path(self) -> str:
         """Return the resolved database file path."""
         return self._db_path

py/services/llm_service.py

@@ -201,6 +201,11 @@ PROVIDER_PRESETS: Dict[str, Dict[str, Any]] = {
         "api_base": "https://openrouter.ai/api/v1",
         "requires_key": True,
     },
+    "google": {
+        "name": "Gemini",
+        "api_base": "https://generativelanguage.googleapis.com/v1beta/openai",
+        "requires_key": True,
+    },
     "opencode-go": {
         "name": "OpenCode Go",
         "api_base": "https://opencode.ai/zen/go/v1",
@@ -566,18 +571,52 @@ class LLMService:
         if effective_max is None:
             effective_max = 4096
 
+        # Use json_schema (not json_object) for broader provider compatibility:
+        # LM Studio and some other OpenAI-compatible servers reject
+        # json_object but accept json_schema.  {"type": "object"} is
+        # functionally equivalent — it accepts any JSON object without
+        # constraining specific fields.
+        response_format = {
+            "type": "json_schema",
+            "json_schema": {
+                "name": "metadata",
+                "schema": {"type": "object"},
+            },
+        }
+
+        try:
             result = await self.chat_completion(
                 messages=messages,
                 model=model,
                 temperature=temperature,
-            response_format={"type": "json_object"},
+                response_format=response_format,
+                max_tokens=effective_max,
+            )
+        except LLMResponseError as e:
+            # Only fall back when the provider rejects the response_format
+            # type value (e.g. "'response_format.type' must be...").  Avoid
+            # catching unrelated 400 errors whose body happens to mention
+            # "response_format" (e.g. "model does not support
+            # response_format restrictions on this endpoint").
+            if "'response_format.type'" not in str(e).lower():
+                raise
+            logger.info(
+                "Provider rejected response_format, retrying without it. "
+                "Falling back to prompt-only JSON mode. Error: %s",
+                e,
+            )
+            result = await self.chat_completion(
+                messages=messages,
+                model=model,
+                temperature=temperature,
+                response_format=None,
                 max_tokens=effective_max,
             )
 
         content = result.get("content", "") or ""
         if not content:
             raise LLMResponseError(
-                "LLM returned empty content in json_object mode. "
+                "LLM returned empty content. "
                 f"Raw response: {json.dumps(result)[:500]}"
             )
 

py/services/model_cache.py

@@ -1,6 +1,7 @@
 import asyncio
 import time
 import logging
+import random
 
 logger = logging.getLogger(__name__)
 from typing import Any, Dict, List, Optional, Tuple
@@ -38,8 +39,8 @@ class ModelCache:
 
     def __post_init__(self):
         self._lock = asyncio.Lock()
-        # Cache for last sort: (sort_key, order) -> sorted list
+        # Cache for last sort: (sort_key, order, seed) -> sorted list
-        self._last_sort: Tuple[str, str] = (None, None)
+        self._last_sort: Tuple[Optional[str], str, Optional[str]] = (None, "asc", None)
         self._last_sorted_data: List[Dict] = []
         self._normalize_raw_data()
         self.name_display_mode = self._normalize_display_mode(self.name_display_mode)
@@ -203,9 +204,9 @@ class ModelCache:
     async def resort(self):
         """Resort cached data according to last sort mode if set"""
         async with self._lock:
-            if self._last_sort != (None, None):
+            if self._last_sort[0] is not None:
-                sort_key, order = self._last_sort
+                sort_key, order, seed = self._last_sort
-                sorted_data = self._sort_data(self.raw_data, sort_key, order)
+                sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
                 self._last_sorted_data = sorted_data
                 # Update folder list
             # else: do nothing
@@ -218,7 +219,7 @@ class ModelCache:
             self.folders = sorted(list(all_folders), key=lambda x: x.lower())
             self.rebuild_version_index()
 
-    def _sort_data(self, data: List[Dict], sort_key: str, order: str) -> List[Dict]:
+    def _sort_data(self, data: List[Dict], sort_key: str, order: str, seed: Optional[str] = None) -> List[Dict]:
         """Sort data by sort_key and order"""
         start_time = time.perf_counter()
         reverse = (order == 'desc')
@@ -265,6 +266,13 @@ class ModelCache:
                 ),
                 reverse=reverse
             )
+        elif sort_key == 'random':
+            # Random shuffle seeded for stable pagination: the same seed
+            # always yields the same order, so successive page requests
+            # stay consistent while browsing.
+            rng = random.Random(seed or 'random')
+            result = list(data)
+            rng.shuffle(result)
         elif sort_key == 'versions_count':
             # Pre-dedup sort: fall back to name sort.
             # Actual re-sort by version_count happens in get_paginated_data after dedup.
@@ -285,15 +293,16 @@ class ModelCache:
             logger.debug("ModelCache._sort_data(%s, %s) for %d items took %.3fs", sort_key, order, len(data), duration)
         return result
 
-    async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc') -> List[Dict]:
+    async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc', seed: Optional[str] = None) -> List[Dict]:
         """Get sorted data by sort_key and order, using cache if possible"""
         async with self._lock:
-            if (sort_key, order) == self._last_sort:
+            cache_key = (sort_key, order, seed)
+            if cache_key == self._last_sort:
                 return self._last_sorted_data
             
             start_time = time.perf_counter()
-            sorted_data = self._sort_data(self.raw_data, sort_key, order)
+            sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
-            self._last_sort = (sort_key, order)
+            self._last_sort = cache_key
             self._last_sorted_data = sorted_data
             
             duration = time.perf_counter() - start_time
@@ -313,8 +322,8 @@ class ModelCache:
             self.name_display_mode = normalized
 
             if self._last_sort[0] == 'name':
-                sort_key, order = self._last_sort
+                sort_key, order, seed = self._last_sort
-                self._last_sorted_data = self._sort_data(self.raw_data, sort_key, order)
+                self._last_sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
 
     async def update_preview_url(self, file_path: str, preview_url: str, preview_nsfw_level: int) -> bool:
         """Update preview_url for a specific model in all cached data

py/services/model_file_service.py

@@ -8,6 +8,7 @@ from abc import ABC, abstractmethod
 from ..utils.utils import calculate_relative_path_for_model, remove_empty_dirs
 from ..utils.constants import AUTO_ORGANIZE_BATCH_SIZE
 from ..services.settings_manager import get_settings_manager
+from ..services.model_lifecycle_service import _require_path_in_library_roots
 
 logger = logging.getLogger(__name__)
 
@@ -493,6 +494,9 @@ class ModelMoveService:
             Dictionary with move result
         """
         try:
+            _require_path_in_library_roots(file_path, self.scanner, label="Source path")
+            _require_path_in_library_roots(target_path, self.scanner, label="Target path")
+
             if use_default_paths:
                 # Find the model in cache to get metadata
                 cache = await self.scanner.get_cached_data()

py/services/model_lifecycle_service.py

@@ -48,6 +48,36 @@ async def delete_model_artifacts(
     return deleted
 
 
+def _require_path_in_library_roots(file_path: str, scanner, *, label: str = "path") -> None:
+    """Raise ``ValueError`` if *file_path* is not inside a configured model root.
+
+    Uses ``os.path.abspath()`` (NOT ``realpath``) to resolve ``..`` and ``.``
+    while preserving symlinks — this keeps the check in business-path space.
+    Skips when the scanner does not expose ``get_model_roots`` or the list
+    is empty.
+    """
+
+    roots = None
+    if hasattr(scanner, "get_model_roots"):
+        try:
+            roots = scanner.get_model_roots()
+        except NotImplementedError:
+            roots = None
+    if not roots:
+        return
+
+    resolved = os.path.abspath(os.path.normpath(file_path))
+
+    for root in roots:
+        root_resolved = os.path.abspath(os.path.normpath(root))
+        if resolved == root_resolved or resolved.startswith(root_resolved + os.sep):
+            return
+
+    raise ValueError(
+        f"{label} '{file_path}' is outside configured library directories"
+    )
+
+
 class ModelLifecycleService:
     """Co-ordinate destructive and mutating model operations."""
 
@@ -74,6 +104,8 @@ class ModelLifecycleService:
         if not file_path:
             raise ValueError("Model path is required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         cache = await self._scanner.get_cached_data()
 
         cached_entry = None
@@ -182,6 +214,8 @@ class ModelLifecycleService:
         if not file_path:
             raise ValueError("Model path is required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         metadata_path = os.path.splitext(file_path)[0] + ".metadata.json"
         metadata = await self._metadata_loader(metadata_path)
         metadata["exclude"] = True
@@ -229,6 +263,8 @@ class ModelLifecycleService:
         if not file_path:
             raise ValueError("Model path is required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         if not os.path.exists(file_path):
             raise ValueError("Model file does not exist")
 
@@ -270,6 +306,9 @@ class ModelLifecycleService:
         if not file_paths:
             raise ValueError("No file paths provided for deletion")
 
+        for path in file_paths:
+            _require_path_in_library_roots(path, self._scanner, label="File path")
+
         return await self._scanner.bulk_delete_models(file_paths)
 
     async def rename_model(
@@ -280,6 +319,8 @@ class ModelLifecycleService:
         if not file_path or not new_file_name:
             raise ValueError("File path and new file name are required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         invalid_chars = {"/", "\\", ":", "*", "?", '"', "<", ">", "|"}
         if any(char in new_file_name for char in invalid_chars):
             raise ValueError("Invalid characters in file name")

py/services/model_metadata_provider.py

@@ -143,10 +143,18 @@ class ModelMetadataProvider(ABC):
         pass
 
     @abstractmethod
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
-        """Fetch models owned by the specified user"""
+        """Fetch one page of models owned by the specified user.
+
+        Returns ``{"items": [...], "nextCursor": <str|None>}`` on success,
+        or None when unsupported/failed. ``cursor`` continues a previous page.
+        """
         pass
 
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        """Published model count for the user; None when unsupported."""
+        return None
+
 class CivitaiModelMetadataProvider(ModelMetadataProvider):
     """Provider that uses Civitai API for metadata"""
     
@@ -175,8 +183,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
     async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
         return await self.client.get_model_version_info(version_id)
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
-        return await self.client.get_user_models(username)
+        return await self.client.get_user_models(username, cursor)
+
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        return await self.client.get_creator_model_count(username)
 
 class CivArchiveModelMetadataProvider(ModelMetadataProvider):
     """Provider that uses CivArchive API for metadata"""
@@ -196,7 +207,7 @@ class CivArchiveModelMetadataProvider(ModelMetadataProvider):
     async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
         return await self.client.get_model_version_info(version_id)
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         """Not supported by CivArchive provider"""
         return None
 
@@ -347,7 +358,7 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
             version_data = await self._get_version_with_model_data(db, model_id, version_id)
             return version_data, None
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         """Listing models by username is not supported for archive database"""
         return None
     
@@ -602,13 +613,14 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         for provider, label in self._iter_providers():
             try:
                 result = await self._call_with_rate_limit(
                     label,
                     provider.get_user_models,
                     username,
+                    cursor=cursor,
                 )
                 if result is not None:
                     return result
@@ -624,6 +636,19 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None
 
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        for provider, label in self._iter_providers():
+            try:
+                result = await provider.get_creator_model_count(username)
+                if result is not None:
+                    return result
+            except Exception as e:
+                logger.debug(
+                    "Provider %s failed for get_creator_model_count: %s", label, e
+                )
+                continue
+        return None
+
     def _iter_providers(self):
         return zip(self.providers, self._provider_labels)
 
@@ -704,13 +729,17 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
             version_id,
         )
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         return await self._rate_limit_helper.run(
             self._label,
             self._provider.get_user_models,
             username,
+            cursor=cursor,
         )
 
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        return await self._provider.get_creator_model_count(username)
+
 class ModelMetadataProviderManager:
     """Manager for selecting and using model metadata providers"""
     
@@ -776,10 +805,20 @@ class ModelMetadataProviderManager:
         except NotImplementedError:
             return None
 
-    async def get_user_models(self, username: str, provider_name: str = None) -> Optional[List[Dict]]:
+    async def get_user_models(
-        """Fetch models owned by the specified user"""
+        self,
+        username: str,
+        provider_name: str = None,
+        cursor: Optional[str] = None,
+    ) -> Optional[Dict]:
+        """Fetch one page of models owned by the specified user"""
         provider = self._get_provider(provider_name)
-        return await provider.get_user_models(username)
+        return await provider.get_user_models(username, cursor)
+
+    async def get_creator_model_count(self, username: str, provider_name: str = None) -> Optional[int]:
+        """Best-effort published model count for the specified user"""
+        provider = self._get_provider(provider_name)
+        return await provider.get_creator_model_count(username)
         
     def _get_provider(self, provider_name: str = None) -> ModelMetadataProvider:
         """Get provider by name or default provider"""

py/services/model_query.py

@@ -85,6 +85,7 @@ class SortParams:
 
     key: str
     order: str
+    seed: Optional[str] = None
 
 
 @dataclass(frozen=True)
@@ -116,7 +117,7 @@ class ModelCacheRepository:
     async def fetch_sorted(self, params: SortParams) -> List[Dict[str, Any]]:
         """Fetch cached data pre-sorted according to ``params``."""
         cache = await self.get_cache()
-        return await cache.get_sorted_data(params.key, params.order)
+        return await cache.get_sorted_data(params.key, params.order, params.seed)
 
     @staticmethod
     def parse_sort(sort_by: str) -> SortParams:
@@ -132,10 +133,17 @@ class ModelCacheRepository:
             sort_key = sort_by.strip().lower() or "name"
             order = "asc"
 
-        if order not in ("asc", "desc"):
+        seed = None
+        if sort_key == "random":
+            # Random sort: the portion after ':' is the shuffle seed.
+            # A stable seed keeps paginated requests consistent; order is
+            # meaningless for a random shuffle.
+            seed = order if order and order not in ("asc", "desc") else None
+            order = "asc"
+        elif order not in ("asc", "desc"):
             order = "asc"
 
-        return SortParams(key=sort_key, order=order)
+        return SortParams(key=sort_key, order=order, seed=seed)
 
 
 class ModelFilterSet:

py/services/model_scanner.py

@@ -14,7 +14,7 @@ from ..utils.metadata_manager import MetadataManager
 from ..utils.civitai_utils import resolve_license_info
 from .model_cache import ModelCache
 from .model_hash_index import ModelHashIndex
-from .model_lifecycle_service import delete_model_artifacts
+from .model_lifecycle_service import delete_model_artifacts, _require_path_in_library_roots
 from .service_registry import ServiceRegistry
 from .websocket_manager import ws_manager
 from .persistent_model_cache import get_persistent_cache
@@ -927,6 +927,25 @@ class ModelScanner:
                 # Update cache data
                 self._cache.raw_data = [item for item in self._cache.raw_data if item['file_path'] not in missing_files]
             
+            dedup_removed = 0
+            seen_paths: set = set()
+            deduped: list = []
+            for item in reversed(self._cache.raw_data):
+                path = item.get('file_path', '')
+                if path not in seen_paths:
+                    seen_paths.add(path)
+                    deduped.append(item)
+                else:
+                    for tag in item.get('tags', []):
+                        if tag in self._tags_count:
+                            self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
+                            if self._tags_count[tag] == 0:
+                                del self._tags_count[tag]
+                    dedup_removed += 1
+            if dedup_removed > 0:
+                self._cache.raw_data = list(reversed(deduped))
+                total_removed += dedup_removed
+            
             # Resort cache if changes were made
             if total_added > 0 or total_removed > 0:
                 # Update folders list
@@ -1352,18 +1371,25 @@ class ModelScanner:
             # Update folder in metadata
             metadata_dict['folder'] = folder
             
-            # Add to cache
+            file_path = metadata_dict.get('file_path', '')
+            if file_path:
+                old_entries = [item for item in self._cache.raw_data if item.get('file_path') == file_path]
+                for old_entry in old_entries:
+                    for tag in old_entry.get('tags', []):
+                        if tag in self._tags_count:
+                            self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
+                            if self._tags_count[tag] == 0:
+                                del self._tags_count[tag]
+                self._hash_index.remove_by_path(file_path)
+                self._cache.raw_data = [item for item in self._cache.raw_data if item.get('file_path') != file_path]
+
+            for tag in metadata_dict.get('tags', []):
+                self._tags_count[tag] = self._tags_count.get(tag, 0) + 1
+
             self._cache.raw_data.append(metadata_dict)
-            self._cache.add_to_version_index(metadata_dict)
 
-            # Resort cache data
             await self._cache.resort()
             
-            # Update folders list
-            all_folders = set(self._cache.folders)
-            all_folders.add(folder)
-            self._cache.folders = sorted(list(all_folders), key=lambda x: x.lower())
-            
             # Update the hash index
             self._hash_index.add_entry(metadata_dict['sha256'], metadata_dict['file_path'])
             await self._persist_current_cache()
@@ -1395,6 +1421,9 @@ class ModelScanner:
             base_name = os.path.splitext(os.path.basename(source_path))[0]
             source_dir = os.path.dirname(source_path)
 
+            _require_path_in_library_roots(source_path, self, label="Source path")
+            _require_path_in_library_roots(target_path, self, label="Target path")
+            
             os.makedirs(target_path, exist_ok=True)
             
             def get_source_hash():
@@ -1723,7 +1752,7 @@ class ModelScanner:
         # ---- Conditional resort (only when sort-key fields changed) ----
         need_resort = False
         _last = cache._last_sort
-        sort_key: Optional[str] = _last[0] if _last != (None, None) else None
+        sort_key: Optional[str] = _last[0] if _last[0] is not None else None
         if sort_key == "name":
             if (
                 old_model_name != desired_entry.get("model_name", "")
@@ -1971,6 +2000,8 @@ class ModelScanner:
                     break
 
                 try:
+                    _require_path_in_library_roots(file_path, self, label="File path")
+
                     target_dir = os.path.dirname(file_path)
                     base_name = os.path.basename(file_path)
                     file_name, main_extension = os.path.splitext(base_name)

py/services/recipe_scanner.py

@@ -21,7 +21,7 @@ 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 ..utils.utils import calculate_recipe_fingerprint
 from natsort import natsorted
 import sys
 import re
@@ -1020,13 +1020,16 @@ class RecipeScanner:
 
         try:
             result = self._fts_index.search(search, fields)
-            # Return None if empty to trigger fuzzy fallback
+            # Return empty set for empty FTS results — do NOT fall back to
-            # Empty FTS results may indicate query syntax issues or need for fuzzy matching
+            # Python fuzzy matching, which freezes the server with 10k+ recipes.
+            # FTS5 prefix matching with unicode61 tokenizer correctly handles
+            # compound tokens (e.g. "illustrious" matches "path/illustrious/model").
+            # If FTS returns nothing, there are genuinely no matching recipes.
             if not result:
-                return None
+                return set()
             return result
         except Exception as exc:
-            logger.debug("FTS search failed, falling back to fuzzy search: %s", exc)
+            logger.debug("FTS search failed, falling back to title-only search: %s", exc)
             return None
 
     def _update_fts_index_for_recipe(
@@ -2079,49 +2082,14 @@ class RecipeScanner:
                         if str(item.get("id", "")) in fts_matching_ids
                     ]
                 else:
-                    # Fallback to fuzzy_match (slower but always available)
+                    # FTS index not yet built — return empty rather than
-                    # Build the search predicate based on search options
+                    # scanning 42k+ items in Python. The FTS background build
-                    def matches_search(item):
+                    # finishes in seconds; by the time a user navigates here
-                        # Search in title if enabled
+                    # and types a search, it is already available.
-                        if search_options.get("title", True):
+                    logger.debug(
-                            if fuzzy_match(str(item.get("title", "")), search):
+                        "FTS index not ready — search '%s' returning empty", search
-                                return True
+                    )
-
+                    filtered_data = []
-                        # Search in tags if enabled
-                        if search_options.get("tags", True) and "tags" in item:
-                            for tag in item["tags"]:
-                                if fuzzy_match(tag, search):
-                                    return True
-
-                        # Search in lora file names if enabled
-                        if search_options.get("lora_name", True) and "loras" in item:
-                            for lora in item["loras"]:
-                                if fuzzy_match(str(lora.get("file_name", "")), search):
-                                    return True
-
-                        # Search in lora model names if enabled
-                        if search_options.get("lora_model", True) and "loras" in item:
-                            for lora in item["loras"]:
-                                if fuzzy_match(str(lora.get("modelName", "")), search):
-                                    return True
-
-                        # Search in prompt and negative_prompt if enabled
-                        if search_options.get("prompt", True) and "gen_params" in item:
-                            gen_params = item["gen_params"]
-                            if fuzzy_match(str(gen_params.get("prompt", "")), search):
-                                return True
-                            if fuzzy_match(
-                                str(gen_params.get("negative_prompt", "")), search
-                            ):
-                                return True
-
-                        # No match found
-                        return False
-
-                    # Filter the data using the search predicate
-                    filtered_data = [
-                        item for item in filtered_data if matches_search(item)
-                    ]
 
             # Apply additional filters
             if filters:

py/services/settings_manager.py

@@ -92,6 +92,7 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "mature_blur_level": "R",
     "autoplay_on_hover": False,
     "display_density": "default",
+    "recipes_layout": "grid",
     "card_info_display": "always",
     "include_trigger_words": False,
     "compact_mode": False,
@@ -1473,10 +1474,12 @@ class SettingsManager:
 
         try:
             common_root = os.path.commonpath([source, target])
-        except ValueError as exc:
+        except ValueError:
-            raise ValueError("Invalid recipes path change") from exc
+            # Windows: paths on different drives share no common root.
+            # A cross-drive move is valid, so treat it as no common root.
+            common_root = None
 
-        if common_root == source:
+        if common_root is not None and common_root == source:
             raise ValueError("Recipes path cannot be moved into a nested directory")
 
         planned_recipe_updates: Dict[str, Dict[str, Any]] = {}

py/services/use_cases/bulk_metadata_refresh_use_case.py

@@ -126,6 +126,7 @@ class BulkMetadataRefreshUseCase:
                         if sha256:
                             model["sha256"] = sha256
                             model["hash_status"] = "completed"
+                            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"})
@@ -148,6 +149,16 @@ class BulkMetadataRefreshUseCase:
                     continue
 
                 await MetadataManager.hydrate_model_data(model)
+
+                # hydrate_model_data replaces model with .metadata.json content,
+                # which may lack sha256. Restore from cache and persist the fix.
+                if not model.get("sha256"):
+                    model["sha256"] = sha256
+                    model["hash_status"] = model.get("hash_status", hash_status)
+                    data_to_save = model.copy()
+                    data_to_save.pop("folder", None)
+                    await MetadataManager.save_metadata(file_path, data_to_save)
+
                 result, error_msg = await self._metadata_sync.fetch_and_update_model(
                     sha256=model["sha256"],
                     file_path=model["file_path"],

py/services/wildcard_service.py

@@ -19,7 +19,7 @@ logger = logging.getLogger(__name__)
 _WILDCARD_PATTERN = re.compile(r"__([\w\s.\-+/*\\]+?)__")
 _OPTION_PATTERN = re.compile(r"{([^{}]*?)}")
 _TRIGGER_WORD_PATTERN = re.compile(r"^trigger_words\d+$")
-_WEIGHTED_OPTION_PATTERN = re.compile(r"^\s*([0-9.]+)::")
+_WEIGHTED_OPTION_PATTERN = re.compile(r"^\s*-?\d+(\.\d+)?::")
 _NUMERIC_PATTERN = re.compile(r"^-?\d+(\.\d+)?$")
 
 
@@ -390,7 +390,7 @@ class WildcardService:
     ) -> str | None:
         keyword = _normalize_wildcard_key(raw_key)
         if keyword in wildcard_dict:
-            return rng.choice(wildcard_dict[keyword])
+            return self._pick_weighted_or_plain(wildcard_dict[keyword], rng)
 
         if "*" in keyword:
             regex_pattern = keyword.replace("*", ".*").replace("+", r"\+")
@@ -400,7 +400,7 @@ class WildcardService:
                 if compiled.match(key):
                     aggregated.extend(values)
             if aggregated:
-                return rng.choice(aggregated)
+                return self._pick_weighted_or_plain(aggregated, rng)
 
         if "/" not in keyword:
             fallback_keyword = _normalize_wildcard_key(f"*/{keyword}")
@@ -409,6 +409,39 @@ class WildcardService:
 
         return None
 
+    def _pick_weighted_or_plain(
+        self, values: list[str], rng: random.Random
+    ) -> str:
+        """Pick a value from the list, respecting N::weight prefix if present.
+
+        When any value in the list uses the ``N::value`` weighted syntax with a
+        weight different from 1, the pick uses weighted random selection.  When
+        no such weighting is present, a plain ``rng.choice`` is used (preserving
+        backward compatibility for unweighted wildcard files).
+
+        In either case the ``N::`` prefix is always stripped from the returned
+        value, matching the behaviour of ``{...}`` option groups.
+        """
+        # Fast path: skip weighting logic entirely when no :: syntax exists
+        if not any("::" in v for v in values):
+            return rng.choice(values)
+
+        weighted_options: list[tuple[float, str]] = []
+        for value in values:
+            weight = 1.0
+            parts = value.split("::", 1)
+            if len(parts) == 2 and _is_numeric_string(parts[0].strip()):
+                weight = float(parts[0].strip())
+            weighted_options.append((weight, value))
+
+        any_weighted = any(w != 1.0 for w, _ in weighted_options)
+        if any_weighted:
+            picked = self._weighted_choice(weighted_options, rng)
+        else:
+            picked = rng.choice(values)
+
+        return self._strip_weight_prefix(picked)
+
 
 def is_trigger_words_input(name: str) -> bool:
     return bool(_TRIGGER_WORD_PATTERN.match(name))

py/utils/constants.py

@@ -12,6 +12,7 @@ NODE_TYPES = {
     "Lora Loader (LoraManager)": 1,
     "Lora Stacker (LoraManager)": 2,
     "WanVideo Lora Select (LoraManager)": 3,
+    "Create Hook LoRA (LoraManager)": 4,
 }
 
 # Default ComfyUI node color when bgcolor is null

py/utils/example_images_download_manager.py

@@ -14,11 +14,16 @@ from ..services.service_registry import ServiceRegistry
 from ..utils.example_images_paths import (
     ExampleImagePathResolver,
     ensure_library_root_exists,
+    get_example_images_root,
+    is_hash_folder,
     uses_library_scoped_folders,
 )
 from ..utils.metadata_manager import MetadataManager
 from .example_images_processor import ExampleImagesProcessor
-from .example_images_metadata import MetadataUpdater
+from .example_images_metadata import (
+    MetadataUpdater,
+    update_cache_from_metadata,
+)
 from ..services.downloader import get_downloader
 from ..services.settings_manager import get_settings_manager
 
@@ -87,6 +92,13 @@ class _DownloadProgress(dict):
         return snapshot
 
 
+# When fewer candidates than this remain in check_pending_models, probe each
+# model folder directly (preserving legacy-folder migration semantics). Above
+# it, build a folder index with a single directory scan so libraries with
+# 100k+ models do not pay one syscall per candidate.
+_BULK_LOOKUP_THRESHOLD = 1000
+
+
 def _model_directory_has_files(path: str) -> bool:
     """Return True when the provided directory exists and contains entries."""
 
@@ -103,6 +115,36 @@ def _model_directory_has_files(path: str) -> bool:
     return False
 
 
+def _build_example_folder_index(output_dir: str) -> dict[str, bool]:
+    """Build a ``{hash: has_files}`` index for a library's example-image folders.
+
+    A single directory scan over the library root replaces ``O(candidates)``
+    per-folder ``os.scandir`` calls, which is required for libraries with
+    100k+ models. Each hash folder is classified by whether it contains any
+    entries, matching the semantics of ``_model_directory_has_files``.
+    """
+
+    index: dict[str, bool] = {}
+    if not output_dir or not os.path.isdir(output_dir):
+        return index
+
+    try:
+        with os.scandir(output_dir) as entries:
+            for entry in entries:
+                name = entry.name
+                if not entry.is_dir() or not is_hash_folder(name):
+                    continue
+                try:
+                    with os.scandir(entry.path) as subentries:
+                        index[name.lower()] = any(subentries)
+                except OSError:
+                    index[name.lower()] = False
+    except OSError:
+        pass
+
+    return index
+
+
 class DownloadManager:
     """Manages downloading example images for models."""
 
@@ -130,6 +172,7 @@ class DownloadManager:
         model_types = data.get("model_types", ["lora", "checkpoint"])
         delay = float(data.get("delay", 0.2))
         force = data.get("force", False)
+        model_hashes = data.get("model_hashes", [])
 
         # Step 2: Validate configuration (fast lookup)
         settings_manager = get_settings_manager()
@@ -199,6 +242,7 @@ class DownloadManager:
                         delay,
                         active_library,
                         force,
+                        model_hashes,
                     )
                 )
 
@@ -410,14 +454,49 @@ class DownloadManager:
             # Calculate pending count: check which models actually need processing.
             # A model is pending if it has a hash, is not already processed or known-failed,
             # and its folder doesn't exist or is empty.
-            pending_hashes = set()
+            candidate_hashes = [
-            for model_hash, model_name in all_models_with_hash:
+                model_hash
-                if model_hash not in processed_models and model_hash not in failed_models:
+                for model_hash, _ in all_models_with_hash
+                if model_hash not in processed_models
+                and model_hash not in failed_models
+            ]
+
+            pending_hashes: set[str] = set()
+            # For small candidate counts the existing per-folder check is fine
+            # and handles legacy folder migration.
+            # For large libraries, scan the library root once and do set lookups.
+            if len(candidate_hashes) <= _BULK_LOOKUP_THRESHOLD or not output_dir:
+                for model_hash in candidate_hashes:
                     model_dir = ExampleImagePathResolver.get_model_folder(
                         model_hash, active_library
                     )
                     if not _model_directory_has_files(model_dir):
                         pending_hashes.add(model_hash)
+            else:
+                folder_index = await asyncio.get_event_loop().run_in_executor(
+                    None, _build_example_folder_index, output_dir
+                )
+                # In multi-library mode, folders that have not been consolidated
+                # into the library root yet (startup migration skipped, failed
+                # move, or created at the legacy path afterwards) still live at
+                # the legacy root/<hash> location. Only scan that root when at
+                # least one candidate is missing from the library-root index, so
+                # the fully-consolidated case does not pay an extra directory
+                # pass on every call.
+                if uses_library_scoped_folders() and any(
+                    not folder_index.get(model_hash, False)
+                    for model_hash in candidate_hashes
+                ):
+                    legacy_root = get_example_images_root()
+                    if legacy_root and legacy_root != output_dir:
+                        legacy_index = await asyncio.get_event_loop().run_in_executor(
+                            None, _build_example_folder_index, legacy_root
+                        )
+                        for hash_key, has_files in legacy_index.items():
+                            folder_index.setdefault(hash_key, has_files)
+                for model_hash in candidate_hashes:
+                    if not folder_index.get(model_hash, False):
+                        pending_hashes.add(model_hash)
 
             pending_count = len(pending_hashes)
 
@@ -500,8 +579,9 @@ class DownloadManager:
         delay,
         library_name,
         force: bool = False,
+        model_hashes: list[str] | None = None,
     ):
-        """Download example images for all models."""
+        """Download example images for all models (or only the given hashes)."""
 
         downloader = await get_downloader()
 
@@ -529,6 +609,18 @@ class DownloadManager:
                         if model.get("sha256"):
                             all_models.append((scanner_type, model, scanner))
 
+            # Restrict to the requested hashes when provided (empty = all models).
+            # Explicit targets are a directed user request, so previously failed
+            # models are retried instead of skipped.
+            explicit_targets = bool(model_hashes)
+            if model_hashes:
+                hash_set = {h.lower() for h in model_hashes}
+                all_models = [
+                    (scanner_type, model, scanner)
+                    for scanner_type, model, scanner in all_models
+                    if model.get("sha256", "").lower() in hash_set
+                ]
+
             # Update total count
             self._progress["total"] = len(all_models)
             logger.debug(f"Found {self._progress['total']} models to process")
@@ -552,6 +644,7 @@ class DownloadManager:
                     downloader,
                     library_name,
                     force,
+                    explicit_targets,
                 )
 
                 # Update progress
@@ -648,6 +741,7 @@ class DownloadManager:
         downloader,
         library_name,
         force: bool = False,
+        explicit_targets: bool = False,
     ):
         """Process a single model download."""
 
@@ -670,8 +764,9 @@ class DownloadManager:
             self._progress["current_model"] = f"{model_name} ({model_hash[:8]})"
             await self._broadcast_progress(status="running")
 
-            # Skip if already in failed models (unless force mode is enabled)
+            # Skip if already in failed models (unless force mode is enabled or
-            if not force and model_hash in self._progress["failed_models"]:
+            # the model was explicitly targeted by hash)
+            if not force and not explicit_targets and model_hash in self._progress["failed_models"]:
                 logger.debug(f"Skipping known failed model: {model_name}")
                 return False
 
@@ -680,6 +775,10 @@ class DownloadManager:
             )
             existing_files = _model_directory_has_files(model_dir)
 
+            # Model-level guard: a populated folder counts as done. Explicitly
+            # targeted models bypass it so the per-image existence pre-check can
+            # fill individual gaps without re-fetching existing files.
+            if not explicit_targets:
                 # Skip if already processed AND directory exists with files
                 if model_hash in self._progress["processed_models"]:
                     if existing_files:
@@ -807,7 +906,7 @@ class DownloadManager:
                         model_name,
                     )
                     # Clear failed_models so non-force runs can retry
-                    if force and model_hash in self._progress["failed_models"]:
+                    if (force or explicit_targets) and model_hash in self._progress["failed_models"]:
                         self._progress["failed_models"].discard(model_hash)
                         logger.info(
                             f"Removed {model_name} from failed_models after force retry with rate-limited images"
@@ -827,7 +926,7 @@ class DownloadManager:
                     )
                 elif success:
                     self._progress["processed_models"].add(model_hash)
-                    if force and model_hash in self._progress["failed_models"]:
+                    if (force or explicit_targets) and model_hash in self._progress["failed_models"]:
                         self._progress["failed_models"].discard(model_hash)
                         logger.info(
                             f"Removed {model_name} from failed_models after successful force retry"
@@ -1343,8 +1442,8 @@ class DownloadManager:
                 await MetadataManager.save_metadata(file_path, model_copy)
 
                 try:
-                    await scanner.update_single_model_cache(
+                    await update_cache_from_metadata(
-                        file_path, file_path, model_data
+                        scanner, file_path, model_copy
                     )
                 except AttributeError:
                     logger.debug(

py/utils/example_images_metadata.py

@@ -1,3 +1,4 @@
+import inspect
 import logging
 import os
 import re
@@ -28,6 +29,31 @@ if TYPE_CHECKING:  # pragma: no cover - import for type checkers only
     from ..services.settings_manager import SettingsManager
 
 
+async def update_cache_from_metadata(
+    scanner: Any, file_path: str, metadata: Dict[str, Any]
+) -> bool:
+    """Update the scanner cache from a metadata dict using the in-place sync path.
+
+    ``sync_cache_from_metadata`` patches the existing cache entry incrementally
+    (tag/hash/version indexes, targeted single-row SQL update) and only resorts
+    when a sort-key field changed. This avoids the ``O(n)`` full-list resort and
+    full cache rewrite that ``update_single_model_cache`` performs on every call,
+    which is critical for libraries with 100k+ models.
+
+    Falls back to the legacy full update when the scanner does not expose an
+    async ``sync_cache_from_metadata`` method.
+
+    Returns:
+        ``True`` if the cache entry was updated, ``False`` otherwise.
+    """
+
+    sync_method = getattr(scanner, "sync_cache_from_metadata", None)
+    if inspect.iscoroutinefunction(sync_method):
+        return await sync_method(file_path, metadata)
+
+    return await scanner.update_single_model_cache(file_path, file_path, metadata)
+
+
 def _build_metadata_sync_service(settings_manager: "SettingsManager") -> MetadataSyncService:
     """Construct a metadata sync service bound to the provided settings."""
 
@@ -103,7 +129,7 @@ class MetadataUpdater:
                 progress['refreshed_models'].add(model_hash)
             
             async def update_cache_func(old_path, new_path, metadata):
-                return await scanner.update_single_model_cache(old_path, new_path, metadata)
+                return await update_cache_from_metadata(scanner, new_path, metadata)
 
             await MetadataManager.hydrate_model_data(model_data)
             success, error = await _get_metadata_sync_service().fetch_and_update_model(
@@ -234,6 +260,7 @@ class MetadataUpdater:
                 
                 # Save metadata to .metadata.json file
                 file_path = model.get('file_path')
+                model_copy: Optional[Dict[str, Any]] = None
                 try:
                     model_copy = model.copy()
                     model_copy.pop('folder', None)
@@ -242,13 +269,17 @@ class MetadataUpdater:
                 except Exception as e:
                     logger.error(f"Failed to save metadata for {model.get('model_name')}: {str(e)}")
 
-                # Save updated metadata to scanner cache
+                # Save updated metadata to scanner cache. sync_cache_from_metadata
-                success = await scanner.update_single_model_cache(file_path, file_path, model)
+                # returns False both for "already in sync" and for actual failures,
-                if success:
+                # so the cache sync result is deliberately not treated as an error;
+                # the return value reflects whether the metadata was persisted.
+                if file_path and model_copy is not None:
+                    await update_cache_from_metadata(scanner, file_path, model_copy)
                     logger.info(f"Successfully updated metadata for {model.get('model_name')} with {len(images)} local examples")
                     return True
-                else:
+
                 logger.warning(f"Failed to update metadata for {model.get('model_name')}")
+                return False
             
             return False
         except Exception as e:
@@ -336,6 +367,7 @@ class MetadataUpdater:
             
             # Save metadata to .metadata.json file
             file_path = model_data.get('file_path')
+            model_copy: Optional[Dict[str, Any]] = None
             if file_path:
                 try:
                     model_copy = model_data.copy()
@@ -346,8 +378,8 @@ class MetadataUpdater:
                     logger.error(f"Failed to save metadata: {str(e)}")
 
             # Save updated metadata to scanner cache
-            if file_path:
+            if file_path and model_copy is not None:
-                await scanner.update_single_model_cache(file_path, file_path, model_data)
+                await update_cache_from_metadata(scanner, file_path, model_copy)
 
             # Get regular images array (might be None)
             regular_images = civitai_data.get('images', [])
@@ -475,13 +507,19 @@ class MetadataUpdater:
             return False
 
         model_folder = get_model_folder(model_hash)
-        if not model_folder:
+        if not model_folder or not os.path.isdir(model_folder):
             return False
 
         civitai = getattr(metadata, "civitai", None)
         if not isinstance(civitai, dict):
             return False
 
+        # Read the directory listing once so every image entry reuses it.
+        try:
+            dir_entries = os.listdir(model_folder)
+        except OSError:
+            dir_entries = []
+
         has_changes = False
 
         custom_images = civitai.get("customImages")
@@ -493,22 +531,13 @@ class MetadataUpdater:
                 if not img_id:
                     continue
 
-                if not os.path.isdir(model_folder):
-                    stale.append(idx)
-                else:
-                    found = False
-                    try:
                 prefix = f"custom_{img_id}"
-                        for fname in os.listdir(model_folder):
+                found = any(
-                            if fname.startswith(prefix) and os.path.isfile(
+                    f.startswith(prefix) and os.path.isfile(
-                                os.path.join(model_folder, fname)
+                        os.path.join(model_folder, f)
-                            ):
+                    )
-                                found = True
+                    for f in dir_entries
-                                break
+                )
-                    except OSError:
-                        stale.append(idx)
-                        continue
-
                 if not found:
                     stale.append(idx)
 
@@ -532,21 +561,8 @@ class MetadataUpdater:
                     # is gone.
                     continue
 
-                if not os.path.isdir(model_folder):
-                    stale.append(idx)
-                else:
-                    found = False
-                    try:
                 prefix = f"image_{idx}."
-                        for fname in os.listdir(model_folder):
+                if not any(f.startswith(prefix) for f in dir_entries):
-                            if fname.startswith(prefix):
-                                found = True
-                                break
-                    except OSError:
-                        stale.append(idx)
-                        continue
-
-                    if not found:
                     stale.append(idx)
 
             if stale:

py/utils/example_images_migration.py

@@ -3,11 +3,19 @@ import logging
 import os
 import re
 import json
+import shutil
 from ..services.settings_manager import get_settings_manager
 from ..services.service_registry import ServiceRegistry
-from ..utils.example_images_paths import iter_library_roots
+from ..utils.example_images_paths import (
+    get_example_images_root,
+    is_hash_folder,
+    iter_library_roots,
+    uses_library_scoped_folders,
+    _library_folder_has_only_hash_dirs,
+)
 from ..utils.metadata_manager import MetadataManager
 from ..utils.example_images_processor import ExampleImagesProcessor
+from ..utils.example_images_metadata import update_cache_from_metadata
 from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
 
 logger = logging.getLogger(__name__)
@@ -36,6 +44,90 @@ settings = _SettingsProxy()
 class ExampleImagesMigration:
     """Handles migrations for example images naming conventions"""
     
+    @staticmethod
+    def _consolidate_library_folders():
+        """Move hash folders from library-named subdirectories back to root.
+
+        When a user switches from multi-library mode back to single-library
+        mode, example images previously stored under e.g.
+        ``<root>/default/<hash>/`` need to be moved back to
+        ``<root>/<hash>/``.  Running this once at startup removes the need
+        for ``get_model_folder()`` to perform directory scans on every
+        request.
+        """
+        if uses_library_scoped_folders():
+            return
+
+        root = get_example_images_root()
+        if not root or not os.path.isdir(root):
+            return
+
+        moved: list[str] = []
+        cleaned: list[str] = []
+
+        try:
+            for entry in os.listdir(root):
+                # Fast regex checks first — no filesystem I/O.
+                if is_hash_folder(entry) or entry == "_deleted":
+                    continue
+
+                entry_path = os.path.join(root, entry)
+                if not os.path.isdir(entry_path):
+                    continue
+                if not _library_folder_has_only_hash_dirs(entry_path):
+                    continue
+
+                try:
+                    for hash_entry in os.listdir(entry_path):
+                        hash_path = os.path.join(entry_path, hash_entry)
+                        if not os.path.isdir(hash_path) or not is_hash_folder(hash_entry):
+                            continue
+                        target = os.path.join(root, hash_entry)
+                        if not os.path.exists(target):
+                            try:
+                                shutil.move(hash_path, target)
+                                moved.append(hash_entry)
+                            except (OSError, shutil.Error) as exc:
+                                logger.error(
+                                    "Failed to move '%s' → '%s': %s",
+                                    hash_path, target, exc,
+                                )
+                except OSError as exc:
+                    logger.error(
+                        "Failed to list library subdirectory '%s': %s",
+                        entry_path, exc,
+                    )
+
+                try:
+                    remaining = os.listdir(entry_path)
+                except OSError:
+                    remaining = []
+                if not remaining:
+                    try:
+                        os.rmdir(entry_path)
+                        cleaned.append(entry)
+                    except OSError as exc:
+                        logger.debug(
+                            "Could not remove empty library dir '%s': %s",
+                            entry_path, exc,
+                        )
+        except OSError as exc:
+            logger.error(
+                "Failed to list example images root during consolidation: %s",
+                exc,
+            )
+
+        if moved:
+            logger.info(
+                "Consolidated %d example image folder(s) to root",
+                len(moved),
+            )
+        if cleaned:
+            logger.info(
+                "Removed %d empty library directories",
+                len(cleaned),
+            )
+
     @staticmethod
     async def check_and_run_migrations():
         """Check if migrations are needed and run them in background"""
@@ -44,6 +136,10 @@ class ExampleImagesMigration:
             logger.debug("No example images path configured or path doesn't exist, skipping migrations")
             return
 
+        # Run library-to-root consolidation once at startup so the hot
+        # path (get_model_folder) stays a pure-path computation.
+        ExampleImagesMigration._consolidate_library_folders()
+
         for library_name, library_path in iter_library_roots():
             if not library_path or not os.path.exists(library_path):
                 continue
@@ -326,7 +422,7 @@ class ExampleImagesMigration:
                         await MetadataManager.save_metadata(file_path, model_copy)
                         
                         # Update scanner cache
-                        await scanner.update_single_model_cache(file_path, file_path, model_metadata)
+                        await update_cache_from_metadata(scanner, file_path, model_copy)
                         
                         updated_models += 1
                     except Exception as e:

py/utils/example_images_paths.py

@@ -83,7 +83,12 @@ def ensure_library_root_exists(library_name: Optional[str] = None) -> str:
 
 
 def get_model_folder(model_hash: str, library_name: Optional[str] = None) -> str:
-    """Return the folder path for a model's example images."""
+    """Return the folder path for a model's example images.
+
+    Multi-library ↔ single-library consolidation is handled once at startup by
+    ``ExampleImagesMigration._consolidate_library_folders`` — this function is a
+    pure path computation on the hot path (no directory scans).
+    """
 
     if not model_hash:
         return ""
@@ -113,35 +118,6 @@ def get_model_folder(model_hash: str, library_name: Optional[str] = None) -> str
                     exc,
                 )
                 return legacy_folder
-    elif not os.path.exists(resolved_folder):
-        # Reverse migration: when consolidating from multi-library to
-        # single-library mode (e.g. after "default" was cleaned up), look
-        # for existing example images inside library-named subdirectories
-        # and bring them back to the root level.
-        root = get_example_images_root()
-        if root:
-            try:
-                for entry in os.listdir(root):
-                    entry_path = os.path.join(root, entry)
-                    if not os.path.isdir(entry_path):
-                        continue
-                    if is_hash_folder(entry) or entry == "_deleted":
-                        continue
-                    if not _library_folder_has_only_hash_dirs(entry_path):
-                        continue
-                    legacy = os.path.join(entry_path, normalized_hash)
-                    if os.path.exists(legacy):
-                        shutil.move(legacy, resolved_folder)
-                        logger.info(
-                            "Consolidated example images from '%s' to '%s'",
-                            legacy, resolved_folder,
-                        )
-                        break
-            except OSError as exc:
-                logger.error(
-                    "Failed to consolidate example images during "
-                    "library merge: %s", exc,
-                )
 
     return resolved_folder
 

py/utils/example_images_processor.py

@@ -9,7 +9,7 @@ from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
 from ..services.service_registry import ServiceRegistry
 from ..services.settings_manager import get_settings_manager
 from ..utils.example_images_paths import get_model_folder, get_model_relative_path
-from .example_images_metadata import MetadataUpdater
+from .example_images_metadata import MetadataUpdater, update_cache_from_metadata
 from ..utils.metadata_manager import MetadataManager
 
 logger = logging.getLogger(__name__)
@@ -113,6 +113,26 @@ class ExampleImagesProcessor:
         message = str(error).lower()
         return '404' in message or 'file not found' in message
 
+    @staticmethod
+    def _example_image_file_exists(model_dir: str, index: int, media_type_hint: str | None = None) -> bool:
+        """Return True when the file that would be written for a media index already exists.
+
+        The final filename (``image_{index}{extension}``) depends on the downloaded
+        content, so the extension cannot be known ahead of time. The post-download
+        check skips the write when the exact target file exists; this pre-check
+        approximates that with the candidate extensions for the media type (videos
+        only when the metadata hints at a video) so the network request is avoided
+        for files that already exist on disk.
+        """
+        if media_type_hint == "video":
+            extensions = SUPPORTED_MEDIA_EXTENSIONS['videos']
+        else:
+            extensions = SUPPORTED_MEDIA_EXTENSIONS['images']
+        return any(
+            os.path.exists(os.path.join(model_dir, f"image_{index}{ext}"))
+            for ext in extensions
+        )
+
     @staticmethod
     async def download_model_images(model_hash, model_name, model_images, model_dir, optimize, downloader):
         """Download images for a single model
@@ -140,6 +160,11 @@ class ExampleImagesProcessor:
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
 
+            # Skip the download when the file already exists on disk
+            if ExampleImagesProcessor._example_image_file_exists(model_dir, i, image.get("type")):
+                logger.debug("File already exists, skipping download for %s", image_url)
+                continue
+
             # Download the file first to determine the actual file type
             try:
                 logger.debug(f"Downloading media file {i} for {model_name}")
@@ -229,6 +254,11 @@ class ExampleImagesProcessor:
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
 
+            # Skip the download when the file already exists on disk
+            if ExampleImagesProcessor._example_image_file_exists(model_dir, i, image.get("type")):
+                logger.debug("File already exists, skipping download for %s", image_url)
+                continue
+
             async def _attempt_download() -> tuple:
                 logger.debug("Downloading media file %s for %s", i, model_name)
                 return await downloader.download_to_memory(
@@ -644,7 +674,7 @@ class ExampleImagesProcessor:
                     }, status=500)
             
                 # Update cache
-                await scanner.update_single_model_cache(file_path, file_path, model_data)
+                await update_cache_from_metadata(scanner, file_path, model_data)
             
             # Get regular images array (might be None)
             regular_images = civitai_data.get('images', [])
@@ -759,7 +789,7 @@ class ExampleImagesProcessor:
                 model_copy = model_data.copy()
                 model_copy.pop('folder', None)
                 await MetadataManager.save_metadata(file_path, model_copy)
-                await scanner.update_single_model_cache(file_path, file_path, model_data)
+                await update_cache_from_metadata(scanner, file_path, model_copy)
 
             return web.json_response({
                 'success': True,

py/utils/exif_utils.py

@@ -1,9 +1,10 @@
+import functools
 import json
 import logging
 import os
 import struct
 from io import BytesIO
-from typing import Any, Optional
+from typing import Any, Optional, Tuple
 
 import piexif
 from PIL import Image, PngImagePlugin
@@ -17,6 +18,22 @@ except ImportError:
 
 logger = logging.getLogger(__name__)
 
+
+@functools.lru_cache(maxsize=2048)
+def _get_image_dimensions_cached(path: str, _mtime_ns: int, _size: int) -> Optional[Tuple[int, int]]:
+    """Return ``(width, height)`` for ``path``, or ``None`` on any failure.
+
+    The ``_mtime_ns`` and ``_size`` arguments are part of the cache key only;
+    they invalidate the entry when the file is replaced with a new image, so a
+    stale preview never serves outdated dimensions.
+    """
+    try:
+        with Image.open(path) as img:
+            return img.size
+    except Exception:
+        return None
+
+
 class ExifUtils:
     """Utility functions for working with EXIF data in images"""
 
@@ -422,6 +439,25 @@ class ExifUtils:
             # Metadata is in the middle of the string
             return user_comment[:recipe_marker_index] + user_comment[next_line_index:]
             
+    @staticmethod
+    def get_image_dimensions(image_path: str) -> Optional[Tuple[int, int]]:
+        """Return ``(width, height)`` for an image, or ``None`` if unavailable.
+
+        Video containers (``.mp4``/``.webm``/``.avi``) and formats PIL cannot
+        read (``.avif``/``.jxl``) return ``None`` before PIL is invoked.
+        Missing or corrupt files return ``None``. Never raises.
+        """
+        try:
+            ext = os.path.splitext(image_path)[1].lower()
+            if ext in ('.mp4', '.webm', '.avi', '.avif', '.jxl'):
+                return None
+            stat = os.stat(image_path)
+            return _get_image_dimensions_cached(
+                image_path, stat.st_mtime_ns, stat.st_size
+            )
+        except Exception:
+            return None
+
     @staticmethod
     def optimize_image(image_data, target_width=250, format='webp', quality=85, preserve_metadata=False):
         """

py/utils/utils.py

@@ -1,7 +1,7 @@
 from difflib import SequenceMatcher
 import os
 import re
-from typing import Dict
+from typing import Any, Dict, List, Optional
 from ..services.service_registry import ServiceRegistry
 from ..config import config
 from ..services.settings_manager import get_settings_manager
@@ -294,6 +294,53 @@ def _format_model_name_for_comfyui(file_path: str, model_roots: list) -> str:
     return os.path.basename(file_path)
 
 
+def model_patcher_to_name(model_patcher: Any) -> Optional[str]:
+    """Extract a ComfyUI-style model name from a MODEL (ModelPatcher) object.
+
+    Core ComfyUI loaders record the absolute weight file path on the patcher's
+    ``cached_patcher_init`` attribute:
+      - load_checkpoint_guess_config -> (fn, (ckpt_path, ...), index)
+      - load_diffusion_model -> (fn, (unet_path, model_options))
+    Patcher clones (LoRA loaders, model merges, ...) preserve the attribute,
+    so the name is recoverable anywhere downstream of a core loader — including
+    from LoRA Manager's own loaders (CheckpointLoaderLM / UNETLoaderLM), which
+    call the same core load functions.
+
+    The absolute path is converted to the ComfyUI-style relative name used by
+    the metadata pipeline (covering standard ComfyUI roots and LoRA Manager
+    extra folder paths).
+
+    Returns None when the path cannot be recovered (e.g. third-party loaders
+    that never set ``cached_patcher_init``).
+    """
+    init = getattr(model_patcher, "cached_patcher_init", None)
+    if not isinstance(init, (tuple, list)) or len(init) < 2:
+        return None
+    args = init[1]
+    abs_path = args[0] if args else None
+    if not isinstance(abs_path, str) or not abs_path:
+        return None
+    return _abs_model_path_to_name(abs_path)
+
+
+def _abs_model_path_to_name(abs_path: str) -> str:
+    """Convert an absolute model path to a ComfyUI-style relative name.
+
+    Tries standard ComfyUI model roots plus LoRA Manager extra folder paths;
+    falls back to the bare filename.
+    """
+    try:
+        roots: List[str] = list(config.base_models_roots or [])
+        roots.extend(config.extra_checkpoints_roots or [])
+        roots.extend(config.extra_unet_roots or [])
+        formatted = _format_model_name_for_comfyui(abs_path, roots)
+        if formatted:
+            return formatted
+    except Exception:
+        pass
+    return os.path.basename(abs_path)
+
+
 def fuzzy_match(text: str, pattern: str, threshold: float = 0.85) -> bool:
     """
     Check if text matches pattern using fuzzy matching.
@@ -488,6 +535,12 @@ def calculate_relative_path_for_model(
     if model_type == "embedding":
         formatted_path = formatted_path.replace(" ", "_")
 
+    # Sanitize the resolved path to prevent path traversal
+    formatted_path = formatted_path.lstrip("/")
+    while "//" in formatted_path:
+        formatted_path = formatted_path.replace("//", "/")
+    formatted_path = formatted_path.rstrip("/")
+
     return formatted_path
 
 

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.1.8"
+version = "1.2.0"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

static/css/components/card.css

@@ -31,6 +31,10 @@
     overflow: hidden;
 }
 
+.card-grid.masonry-layout .model-card {
+    aspect-ratio: auto;
+}
+
 .model-card:hover {
     transform: translateY(-2px);
     box-shadow: var(--shadow-md);

static/css/components/download-batch-summary.css

@@ -0,0 +1,67 @@
+/* Batch Download Summary Modal — component styles only.
+   Stat cards and failure table styles are shared with the metadata refresh
+   result modal (metadata-refresh-result.css) and are not redefined here. */
+
+.download-batch-summary-modal {
+    max-width: 700px;
+}
+
+.summary-header {
+    display: flex;
+    align-items: center;
+    gap: var(--space-2);
+    margin: var(--space-2) 0;
+}
+
+.summary-header i {
+    font-size: 1.4em;
+}
+
+.summary-header.success i {
+    color: var(--color-success);
+}
+
+.summary-header.warning i {
+    color: var(--color-warning);
+}
+
+.summary-header.error i {
+    color: var(--color-error);
+}
+
+.summary-title {
+    font-weight: var(--weight-semibold);
+    color: var(--lora-text);
+}
+
+.summary-hint {
+    margin-left: auto;
+    font-size: var(--text-xs);
+    color: var(--text-secondary);
+}
+
+.btn-retry {
+    display: inline-flex;
+    align-items: center;
+    gap: var(--space-1);
+    background: var(--lora-accent, #4f46e5);
+    color: #fff;
+    border: none;
+    border-radius: var(--border-radius-sm);
+    padding: var(--space-2) var(--space-3);
+    cursor: pointer;
+    font-weight: var(--weight-semibold);
+}
+
+.btn-retry:hover {
+    background: var(--lora-accent-hover, #4338ca);
+}
+
+.failure-link {
+    color: var(--lora-accent, #4f46e5);
+    text-decoration: none;
+}
+
+.failure-link:hover {
+    text-decoration: underline;
+}

static/css/components/import-modal.css

@@ -1,4 +1,35 @@
 /* Import Modal Styles */
+
+/* Sticky footer layout: fixed header, scrollable step content, pinned action buttons.
+   Ensures Back/Import buttons stay visible on short viewports (e.g. 1080p or 150% zoom). */
+#importModal .modal-content {
+    display: flex;
+    flex-direction: column;
+    overflow: hidden; /* The active step scrolls instead of the whole modal */
+}
+
+#importModal .modal-header {
+    flex-shrink: 0;
+}
+
+#importModal .import-step {
+    flex: 1 1 auto;
+    min-height: 0; /* Allow the step to shrink and scroll within the flex container */
+    overflow-y: auto;
+    overflow-x: hidden;
+    scrollbar-gutter: stable;
+}
+
+#importModal .import-step .modal-actions {
+    position: sticky;
+    bottom: 0;
+    z-index: 1;
+    background: var(--lora-surface);
+    border-top: 1px solid var(--lora-border);
+    padding-top: var(--space-2);
+    padding-bottom: var(--space-1);
+}
+
 .import-step {
     margin: var(--space-2) 0;
     transition: none !important;

static/css/components/modal/_base.css

@@ -151,6 +151,7 @@ body.modal-open {
 .support-section,
 .changelog-section,
 .update-info,
+.update-channels,
 .info-item,
 .path-preview {
     background: var(--surface-subtle);

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

@@ -93,15 +93,13 @@
 .update-content {
     display: flex;
     flex-direction: column;
-    gap: var(--space-3);
+    gap: var(--space-2);
 }
 
 .update-info {
     display: flex;
     justify-content: space-between;
     align-items: center;
-    border-radius: var(--border-radius-sm);
-    padding: var(--space-3);
 }
 
 .update-info .version-info {
@@ -175,7 +173,6 @@
     border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
-    margin: var(--space-2) 0;
 }
 
 [data-theme="dark"] .update-progress {
@@ -233,11 +230,6 @@
 }
 
 /* Changelog section */
-.changelog-section {
-    border-radius: var(--border-radius-sm);
-    padding: var(--space-3);
-}
-
 .changelog-section h3 {
     margin-top: 0;
     margin-bottom: var(--space-2);
@@ -349,6 +341,131 @@
     text-decoration: underline;
 }
 
+/* Channel Toggle */
+.update-channels {
+}
+
+.channels-label {
+    font-size: 0.9em;
+    color: var(--text-color);
+    opacity: 0.8;
+    margin-bottom: 8px;
+}
+
+.channel-toggle {
+    display: flex;
+    gap: 0;
+    background: var(--lora-surface);
+    border-radius: 8px;
+    padding: 3px;
+    width: fit-content;
+}
+
+.channel-btn {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 8px 20px;
+    border: none;
+    border-radius: 6px;
+    background: transparent;
+    color: var(--text-secondary, #999);
+    cursor: pointer;
+    font-size: 0.9em;
+    font-weight: 500;
+    transition: all 0.2s ease;
+    white-space: nowrap;
+}
+
+.channel-btn:hover {
+    color: var(--text-primary, #ddd);
+    background: rgba(255, 255, 255, 0.04);
+}
+
+.channel-btn.active {
+    background: var(--lora-accent, #4285F4);
+    color: #fff;
+    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.2);
+}
+
+.channel-btn.active i {
+    color: #fff;
+}
+
+.channel-btn i {
+    font-size: 0.85em;
+}
+
+/* Channel Switch Confirmation Overlay */
+.channel-switch-overlay {
+    position: fixed;
+    inset: 0;
+    background: rgba(0, 0, 0, 0.6);
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    z-index: 10000;
+    backdrop-filter: blur(2px);
+}
+
+.channel-switch-dialog {
+    background: var(--lora-surface);
+    border: 1px solid var(--border-color, rgba(255, 255, 255, 0.1));
+    border-radius: 12px;
+    padding: 28px 32px;
+    max-width: 420px;
+    width: 90%;
+    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.4);
+}
+
+.channel-switch-dialog h3 {
+    margin: 0 0 12px;
+    font-size: 1.1em;
+    color: var(--text-primary, #eee);
+}
+
+.channel-switch-dialog p {
+    margin: 0 0 24px;
+    font-size: 0.9em;
+    color: var(--text-secondary, #aaa);
+    line-height: 1.6;
+}
+
+.channel-switch-actions {
+    display: flex;
+    justify-content: flex-end;
+    gap: 10px;
+}
+
+.channel-switch-cancel {
+    padding: 8px 18px;
+    border: 1px solid var(--border-color, rgba(255, 255, 255, 0.1));
+    border-radius: 6px;
+    background: transparent;
+    color: var(--text-secondary, #aaa);
+    cursor: pointer;
+    font-size: 0.9em;
+}
+
+.channel-switch-cancel:hover {
+    background: rgba(255, 255, 255, 0.04);
+}
+
+.channel-switch-confirm {
+    padding: 8px 18px;
+    border: none;
+    border-radius: 6px;
+    background: var(--lora-accent, #4285F4);
+    color: #fff;
+    cursor: pointer;
+    font-size: 0.9em;
+    font-weight: 500;
+}
+
+.channel-switch-confirm:hover {
+    opacity: 0.9;
+}
+
 /* Update preferences section */
 .update-preferences {
     border-top: 1px solid var(--lora-border);

static/css/components/search-filter.css

@@ -145,13 +145,14 @@
     position: fixed;
     right: 20px;
     top: 50px; /* Position below header */
-    width: 366px;
+    width: 420px;
     background-color: var(--card-bg);
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-base);
     box-shadow: var(--shadow-md);
     z-index: var(--z-overlay);
     padding: 16px;
+    box-sizing: border-box; /* Include padding in max-height calculation */
     transition: transform 0.3s ease, opacity 0.3s ease;
     transform-origin: top right;
     max-height: calc(100vh - 70px); /* Adjusted for header height */
@@ -563,7 +564,7 @@
     align-items: center;
     gap: 6px;
     white-space: nowrap;
-    max-width: 120px; /* Prevent long names from breaking layout */
+    max-width: 180px; /* Prevent long names from breaking layout */
     overflow: hidden;
     text-overflow: ellipsis;
 }

static/css/style.css

@@ -41,6 +41,7 @@
 @import 'components/sidebar.css'; /* Add sidebar component */
 @import 'components/media-viewer.css';
 @import 'components/metadata-refresh-result.css';
+@import 'components/download-batch-summary.css';
 
 .initialization-notice {
     display: flex;

static/js/api/apiConfig.js

@@ -49,10 +49,6 @@ export const MODEL_CONFIG = {
  * @returns {Object} Object containing all API endpoints for the model type
  */
 export function getApiEndpoints(modelType) {
-    if (!Object.values(MODEL_TYPES).includes(modelType)) {
-        throw new Error(`Invalid model type: ${modelType}`);
-    }
-
     return {
         // Base CRUD operations
         list: `/api/lm/${modelType}/list`,
@@ -188,7 +184,8 @@ export const DOWNLOAD_ENDPOINTS = {
     downloadGet: '/api/lm/download-model-get',
     cancelGet: '/api/lm/cancel-download-get',
     progress: '/api/lm/download-progress',
-    exampleImages: '/api/lm/force-download-example-images' // New endpoint for downloading example images
+    exampleImages: '/api/lm/force-download-example-images', // Re-process example images ignoring previous status
+    exampleImagesMissing: '/api/lm/download-example-images' // Download only missing example images
 };
 
 // Hugging Face API endpoints

static/js/api/baseModelApi.js

@@ -1641,7 +1641,7 @@ export class BaseModelApiClient {
         }
     }
 
-    async downloadExampleImages(modelHashes, modelTypes = null) {
+    async downloadExampleImages(modelHashes, modelTypes = null, { force = true } = {}) {
         let ws = null;
 
         await state.loadingManager.showWithProgress(async (loading) => {
@@ -1700,8 +1700,13 @@ export class BaseModelApiClient {
                 // Determine optimize setting
                 const optimize = state.global?.settings?.optimize_example_images ?? true;
 
+                // force=false routes to the regular endpoint, which skips already-processed models
+                const endpoint = force
+                    ? DOWNLOAD_ENDPOINTS.exampleImages
+                    : DOWNLOAD_ENDPOINTS.exampleImagesMissing;
+
                 // Make the API request to start the download process
-                const response = await fetch(DOWNLOAD_ENDPOINTS.exampleImages, {
+                const response = await fetch(endpoint, {
                     method: 'POST',
                     headers: {
                         'Content-Type': 'application/json'
@@ -1710,6 +1715,7 @@ export class BaseModelApiClient {
                         model_hashes: modelHashes,
                         output_dir: outputDir,
                         optimize: optimize,
+                        force: force,
                         model_types: modelTypes || [this.apiConfig.config.singularName]
                     })
                 });

static/js/components/ContextMenu/BulkContextMenu.js

@@ -137,11 +137,10 @@ export class BulkContextMenu extends BaseContextMenu {
             downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
         }
 
-        const downloadExampleImagesItem = this.menu.querySelector('[data-action="download-example-images"]');
+        const downloadExampleImagesSubmenu = this.menu.querySelector('[data-has-submenu="download-example-images"]');
-        if (downloadExampleImagesItem) {
+        if (downloadExampleImagesSubmenu) {
             // Show on model pages (loras, checkpoints, embeddings), hide on recipes
-            const modelPages = ['loras', 'checkpoints', 'embeddings'];
+            downloadExampleImagesSubmenu.style.display = ['loras', 'checkpoints', 'embeddings'].includes(currentModelType) ? 'flex' : 'none';
-            downloadExampleImagesItem.style.display = modelPages.includes(currentModelType) ? 'flex' : 'none';
         }
 
         const skipMetadataRefreshItem = this.menu.querySelector('[data-action="skip-metadata-refresh"]');
@@ -294,8 +293,11 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;
+            case 'download-missing-example-images':
+                this.handleDownloadExampleImages({ force: false });
+                break;
             case 'download-example-images':
-                this.handleDownloadExampleImages();
+                this.handleDownloadExampleImages({ force: true });
                 break;
             case 'clear':
                 bulkManager.clearSelection();
@@ -340,7 +342,7 @@ export class BulkContextMenu extends BaseContextMenu {
         await bulkMissingLoraDownloadManager.downloadMissingLoras(selectedRecipes);
     }
 
-    async handleDownloadExampleImages() {
+    async handleDownloadExampleImages({ force = true } = {}) {
         if (state.selectedModels.size === 0) {
             return;
         }
@@ -361,7 +363,7 @@ export class BulkContextMenu extends BaseContextMenu {
 
         try {
             const apiClient = getModelApiClient();
-            await apiClient.downloadExampleImages([...hashes]);
+            await apiClient.downloadExampleImages([...hashes], null, { force });
         } catch (error) {
             console.error('Bulk download example images failed:', error);
         }

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -347,7 +347,10 @@ export const ModelContextMenuMixin = {
                 openExampleImagesFolder(this.currentCard.dataset.sha256);
                 return true;
             case 'download-examples':
-                this.downloadExampleImages();
+                this.downloadExampleImages(false);
+                return true;
+            case 'download-examples-force':
+                this.downloadExampleImages(true);
                 return true;
             case 'civitai':
                 if (this.currentCard.dataset.from_civitai === 'true') {
@@ -378,7 +381,7 @@ export const ModelContextMenuMixin = {
     },
 
     // Download example images method
-    async downloadExampleImages() {
+    async downloadExampleImages(force = false) {
         const modelHash = this.currentCard.dataset.sha256;
         if (!modelHash) {
             showToast('toast.contextMenu.missingHash', {}, 'error');
@@ -387,7 +390,7 @@ export const ModelContextMenuMixin = {
 
         try { 
             const apiClient = getModelApiClient();
-            await apiClient.downloadExampleImages([modelHash]);
+            await apiClient.downloadExampleImages([modelHash], null, { force });
         } catch (error) {
             console.error('Error downloading example images:', error);
         }

static/js/components/ContextMenu/RecipeContextMenu.js

@@ -260,8 +260,9 @@ export class RecipeContextMenu extends BaseContextMenu {
                         strength: lora.strength || 1.0,
 
                         // Model identifiers
+                        modelId: lora.modelId || lora.model_id || civitaiInfo.modelId,
                         hash: modelFile?.hashes?.SHA256?.toLowerCase() || lora.hash,
-                        modelVersionId: civitaiInfo.id || lora.modelVersionId,
+                        id: civitaiInfo.id || lora.modelVersionId,
 
                         // Metadata
                         thumbnailUrl: civitaiInfo.images?.[0]?.url || '',

static/js/components/DownloadBatchSummaryModal.js

@@ -0,0 +1,340 @@
+import { translate } from '../utils/i18nHelpers.js';
+import { showToast, openHuggingFace } from '../utils/uiHelpers.js';
+
+/**
+ * Escape HTML entities in a string to prevent injection when interpolating into innerHTML.
+ * Safe for both text content and attribute values (quotes are escaped too).
+ * @param {string} str - The string to escape
+ * @returns {string} - The escaped string
+ */
+function _escapeHtml(str) {
+    if (!str) return '';
+    const div = document.createElement('div');
+    div.textContent = str;
+    return div.innerHTML.replace(/"/g, '"').replace(/'/g, ''');
+}
+
+/**
+ * Resolve the display name of a failed download entry.
+ * Prefers the resolved name carried on the entry, then known item fields,
+ * then derives a name from the item URL as a last resort.
+ * @param {Object} entry - The failed entry ({ item, error, name? })
+ * @returns {string} - The best available display name
+ */
+function _resolveItemName(entry) {
+    if (entry?.name) {
+        return entry.name;
+    }
+    const item = entry?.item ?? entry;
+    const direct = item?.displayName || item?.name || item?.file_name || item?.filename || item?.selectedVersion?.name;
+    if (direct) {
+        return direct;
+    }
+    if (item?.url) {
+        try {
+            const segments = new URL(item.url).pathname.split('/').filter(Boolean);
+            if (segments.length > 0) {
+                return decodeURIComponent(segments[segments.length - 1]);
+            }
+        } catch (e) {
+            // Unparseable URL — fall through to 'Unknown'
+        }
+    }
+    return 'Unknown';
+}
+
+/**
+ * Resolve the URL to open for a failed item — always the original item URL.
+ * @param {Object} item - The failed item payload
+ * @returns {string|null} - A URL string, or null when nothing is available
+ */
+function _resolveItemUrl(item) {
+    return item?.url || null;
+}
+
+/**
+ * Format a raw failure error into a concise human-readable message.
+ * Unwraps JSON envelopes and extracts HTTP status/body details when present.
+ * @param {*} error - The raw error (usually a string)
+ * @returns {string} - The formatted error message
+ */
+function _formatError(error) {
+    if (!error) {
+        return 'Unknown error';
+    }
+    let base = typeof error === 'string' ? error : String(error);
+
+    // Unwrap JSON envelope: { "success": false, "error": "...", ... }
+    try {
+        const parsed = JSON.parse(base);
+        if (parsed && typeof parsed.error === 'string' && parsed.error) {
+            base = parsed.error;
+        }
+    } catch (e) {
+        // Not a JSON envelope — keep the raw string
+    }
+
+    // Extract HTTP status and JSON body details, e.g. "status=403 body={...}"
+    let result = base;
+    const statusMatch = base.match(/status=(\d{3})/);
+    const bodyMatch = base.match(/body=(\{.*\})/s);
+    if (bodyMatch) {
+        try {
+            const body = JSON.parse(bodyMatch[1]);
+            const detail = (typeof body?.message === 'string' && body.message)
+                || (typeof body?.error === 'string' && body.error)
+                || null;
+            if (detail) {
+                const status = statusMatch ? statusMatch[1] : null;
+                result = `${status ? `HTTP ${status} — ` : ''}${detail}`;
+            }
+        } catch (e) {
+            // Body is not valid JSON — keep the base string
+        }
+    }
+
+    // Truncate overly long messages
+    if (result.length > 220) {
+        result = result.slice(0, 220) + '…';
+    }
+    return result;
+}
+
+/**
+ * Build a plain-text report of the batch download results.
+ * @param {number} total - Total number of models attempted
+ * @param {number} completed - Number of models successfully downloaded
+ * @param {Array} failedItems - Array of failed items ({ item, error })
+ * @returns {string} - The report text
+ */
+function _buildReportText(total, completed, failedItems) {
+    const lines = [
+        '=== Batch Download Report ===',
+        `Date: ${new Date().toLocaleString()}`,
+        `Total: ${total}`,
+        `Successfully downloaded: ${completed}`,
+        `Failed: ${failedItems.length}`,
+        '',
+    ];
+    if (failedItems.length > 0) {
+        lines.push('--- Failed Items ---');
+        failedItems.forEach((entry, i) => {
+            const name = _resolveItemName(entry);
+            const error = _formatError(entry?.error);
+            lines.push(`${i + 1}. ${name} — ${error}`);
+            const itemUrl = _resolveItemUrl(entry?.item ?? entry);
+            if (itemUrl) {
+                lines.push(`   URL: ${itemUrl}`);
+            }
+        });
+        lines.push('');
+    }
+    lines.push('====================');
+    return lines.join('\n');
+}
+
+/**
+ * Handle a successful clipboard write: confirm via toast and briefly swap the
+ * trigger button to a "Copied!" state.
+ * @param {HTMLElement|null} btn - The button that triggered the copy action
+ */
+function _onCopyReportSuccess(btn) {
+    showToast('toast.api.copiedToClipboard', {}, 'success');
+    if (btn) {
+        const origHTML = btn.innerHTML;
+        btn.innerHTML = '<i class="fas fa-check"></i> Copied!';
+        setTimeout(() => { btn.innerHTML = origHTML; }, 2000);
+    }
+}
+
+/**
+ * Fallback for environments without the async Clipboard API (e.g. insecure
+ * contexts over LAN http where `navigator.clipboard` is undefined): copy via a
+ * hidden textarea and `document.execCommand('copy')`.
+ * @param {string} text - The report text to copy
+ */
+function _copyReportWithExecCommand(text) {
+    const textarea = document.createElement('textarea');
+    textarea.value = text;
+    document.body.appendChild(textarea);
+    textarea.select();
+    document.execCommand('copy');
+    document.body.removeChild(textarea);
+    showToast('toast.api.copiedToClipboard', {}, 'success');
+}
+
+/**
+ * Copy the batch download report to the clipboard.
+ * Uses the async Clipboard API when available, otherwise falls back to a hidden
+ * textarea + execCommand so the action still works in insecure contexts.
+ * @param {HTMLElement} btn - The button that triggered the copy action
+ * @param {number} total - Total number of models attempted
+ * @param {number} completed - Number of models successfully downloaded
+ * @param {Array} failedItems - Array of failed items
+ */
+function _copyReport(btn, total, completed, failedItems) {
+    const text = _buildReportText(total, completed, failedItems);
+    if (navigator.clipboard && typeof navigator.clipboard.writeText === 'function') {
+        navigator.clipboard.writeText(text)
+            .then(() => _onCopyReportSuccess(btn))
+            .catch(() => _copyReportWithExecCommand(text));
+    } else {
+        _copyReportWithExecCommand(text);
+    }
+}
+
+/**
+ * Show the batch download summary modal after a batch download completes.
+ * Mirrors the Metadata Fetch Summary modal lifecycle: the modal element is
+ * appended directly to document.body and removed on close; it is not
+ * registered with ModalManager.
+ * @param {Object} options - Summary options
+ * @param {number} options.total - Total number of models attempted
+ * @param {number} options.completed - Number of models successfully downloaded
+ * @param {Array} options.failedItems - Array of failed items ({ item, error })
+ * @param {Function} options.onRetry - Callback invoked with failedItems to retry the failed subset
+ */
+export function showDownloadBatchSummary({ total, completed, failedItems, onRetry }) {
+    const failures = failedItems || [];
+    const failedCount = failures.length;
+
+    // 3-state summary header semantics (mirrors BatchImportManager results header)
+    let headerState;
+    let headerIcon;
+    let headerText;
+    if (completed === 0) {
+        headerState = 'error';
+        headerIcon = 'fa-times-circle';
+        headerText = translate('modals.downloadBatchSummary.failed', {}, 'Download failed');
+    } else if (failedCount > 0) {
+        headerState = 'warning';
+        headerIcon = 'fa-exclamation-circle';
+        headerText = translate('modals.downloadBatchSummary.completedWithErrors', {}, 'Completed with errors');
+    } else {
+        headerState = 'success';
+        headerIcon = 'fa-check-circle';
+        headerText = translate('modals.downloadBatchSummary.successMessage', { count: completed }, 'All ' + completed + ' models downloaded successfully');
+    }
+
+    // Build failure table rows
+    const failureRows = failures.map((entry, i) => {
+        const item = entry?.item ?? entry;
+        const name = _resolveItemName(entry);
+        const itemUrl = _resolveItemUrl(item);
+        const rawError = entry?.error ? String(entry.error) : '';
+        const error = _formatError(entry?.error);
+        const nameCell = itemUrl
+            ? `<td class="failure-name"><a href="#" class="failure-link" data-action="open-model" data-index="${i}" title="${_escapeHtml(itemUrl)}">${_escapeHtml(name)}</a></td>`
+            : `<td class="failure-name" title="${_escapeHtml(name)}">${_escapeHtml(name)}</td>`;
+        return `<tr>
+                <td class="failure-index">${i + 1}</td>
+                ${nameCell}
+                <td class="failure-error" title="${_escapeHtml(rawError)}">${_escapeHtml(error)}</td>
+            </tr>`;
+    }).join('');
+
+    const modalHtml = `
+        <div id="downloadBatchSummaryModal" class="modal" style="display: block;">
+            <div class="modal-content download-batch-summary-modal">
+                <button class="close" data-action="close-modal">&times;</button>
+
+                <h2>${translate('modals.downloadBatchSummary.title', {}, 'Batch Download Summary')}</h2>
+
+                <div class="summary-header ${headerState}">
+                    <i class="fas ${headerIcon}"></i>
+                    <span class="summary-title">${headerText}</span>
+                    <span class="summary-hint">${completed}/${total}</span>
+                </div>
+
+                <div class="refresh-summary-stats">
+                    <div class="stat-card stat-card-success">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.downloadBatchSummary.statSuccess', {}, 'Success')}</span>
+                            <span class="stat-card-value">${completed}</span>
+                        </div>
+                    </div>
+                    <div class="stat-card stat-card-failure">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.downloadBatchSummary.statFailed', {}, 'Failed')}</span>
+                            <span class="stat-card-value">${failedCount}</span>
+                        </div>
+                    </div>
+                    <div class="stat-card stat-card-total">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.downloadBatchSummary.statTotal', {}, 'Total')}</span>
+                            <span class="stat-card-value">${total}</span>
+                        </div>
+                    </div>
+                </div>
+
+                ${failedCount > 0 ? `
+                <div class="refresh-failures-section">
+                    <h4><i class="fas fa-exclamation-triangle"></i> ${translate('modals.downloadBatchSummary.failedItems', { count: failedCount }, 'Failed Items (' + failedCount + ')')}</h4>
+                    <div class="failure-table-wrapper">
+                        <table class="failure-table">
+                            <thead>
+                                <tr>
+                                    <th>#</th>
+                                    <th>${translate('modals.downloadBatchSummary.columnName', {}, 'Model Name')}</th>
+                                    <th>${translate('modals.downloadBatchSummary.columnError', {}, 'Error')}</th>
+                                </tr>
+                            </thead>
+                            <tbody>${failureRows}</tbody>
+                        </table>
+                    </div>
+                </div>
+                ` : `
+                <div class="refresh-success-message">
+                    <i class="fas fa-check-circle"></i> ${translate('modals.downloadBatchSummary.successMessage', { count: completed }, 'All ' + completed + ' models downloaded successfully')}
+                </div>
+                `}
+
+                <div class="modal-actions">
+                    ${failedCount > 0 ? `
+                    <button class="btn-retry" data-action="retry-failed"><i class="fas fa-redo"></i> ${translate('modals.downloadBatchSummary.retryFailed', { count: failedCount }, 'Retry Failed (' + failedCount + ')')}</button>
+                    <button class="secondary-btn" data-action="copy-report"><i class="fas fa-copy"></i> ${translate('modals.downloadBatchSummary.copyReport', {}, 'Copy Report')}</button>
+                    ` : ''}
+                    <button class="cancel-btn" data-action="close-modal">${translate('modals.downloadBatchSummary.close', {}, 'Close')}</button>
+                </div>
+            </div>
+        </div>
+    `;
+
+    const existing = document.getElementById('downloadBatchSummaryModal');
+    if (existing) existing.remove();
+
+    const container = document.createElement('div');
+    container.innerHTML = modalHtml;
+    const modal = container.firstElementChild;
+    document.body.appendChild(modal);
+
+    modal.addEventListener('click', (e) => {
+        const actionEl = e.target.closest('[data-action]');
+        const action = actionEl?.dataset.action;
+        if (!action) return;
+        e.preventDefault();
+
+        switch (action) {
+            case 'close-modal':
+                modal.remove();
+                break;
+            case 'retry-failed':
+                modal.remove();
+                if (typeof onRetry === 'function') {
+                    onRetry(failures);
+                }
+                break;
+            case 'copy-report':
+                _copyReport(actionEl, total, completed, failures);
+                break;
+            case 'open-model': {
+                // Keep the modal open; just open the item's original URL in a new tab
+                const entry = failures[Number(actionEl.dataset.index)];
+                const item = entry?.item;
+                if (!item?.url) break;
+                openHuggingFace(item.url);
+                break;
+            }
+        }
+    });
+}

static/js/components/DuplicatesManager.js

@@ -2,6 +2,7 @@
 import { showToast } from '../utils/uiHelpers.js';
 import { RecipeCard } from './RecipeCard.js';
 import { state, getCurrentPageState } from '../state/index.js';
+import { recreateVirtualScroll } from '../utils/infiniteScroll.js';
 
 export class DuplicatesManager {
     constructor(recipeManager) {
@@ -71,7 +72,7 @@ export class DuplicatesManager {
         this.updateSelectedCount();
     }
     
-    exitDuplicateMode() {
+    async exitDuplicateMode() {
         this.inDuplicateMode = false;
         this.selectedForDeletion.clear();
         
@@ -94,9 +95,17 @@ export class DuplicatesManager {
             recipeGrid.innerHTML = '';
         }
         
-        // Re-enable virtual scrolling
+        // Re-enable virtual scrolling, or apply a layout switch deferred
+        // while duplicates mode was active (enabling the old scroller first
+        // would let its pending rAF render repopulate the grid after the
+        // new scroller is created, leaving orphaned/overlapping cards).
+        if (state.pendingLayoutRecreate) {
+            state.pendingLayoutRecreate = false;
+            await recreateVirtualScroll('recipes');
+        } else if (state.virtualScroller) {
             state.virtualScroller.enable();
         }
+    }
     
     renderDuplicateGroups() {
         const recipeGrid = document.getElementById('recipeGrid');

static/js/components/RecipeModal.js

@@ -1421,6 +1421,7 @@ class RecipeModal {
                         strength: lora.strength || 1.0,
 
                         // Model identifiers
+                        modelId: lora.modelId || lora.model_id || civitaiInfo.modelId,
                         hash: modelFile?.hashes?.SHA256?.toLowerCase() || lora.hash,
                         id: civitaiInfo.id || lora.modelVersionId,
 

static/js/components/controls/PageControls.js

@@ -108,10 +108,20 @@ export class PageControls {
         const sortSelect = document.getElementById('sortSelect');
         if (sortSelect) {
             initSortDropdown(sortSelect);
-            sortSelect.value = this.pageState.sortBy;
+            this.applySortToSelect(this.pageState.sortBy);
             sortSelect.addEventListener('change', async (e) => {
-                this.pageState.sortBy = e.target.value;
+                let value = e.target.value;
-                this.saveSortPreference(e.target.value);
+                if (value.startsWith('random')) {
+                    // Every pick of Random reshuffles the list: generate a
+                    // fresh seed so the backend keeps a stable order across
+                    // paginated requests.
+                    value = this._randomizeSortValue();
+                }
+                this.pageState.sortBy = value;
+                this.saveSortPreference(value);
+                // Reset the seeded Random option when switching away from
+                // Random, or re-apply the fresh seed when picking it again.
+                this.applySortToSelect(value);
                 await this.resetAndReload();
             });
         }
@@ -312,6 +322,44 @@ export class PageControls {
         }
     }
     
+    /**
+     * Apply a sort value to the native sort <select>, keeping the Random
+     * option's value in sync when the persisted value carries a seed
+     * (e.g. "random:abc123"). Must be used instead of assigning
+     * sortSelect.value directly whenever the value may be a seeded random
+     * sort, otherwise the native select has no matching option.
+     * @param {string} sortValue - Sort value like "name:asc" or "random:<seed>"
+     */
+    applySortToSelect(sortValue) {
+        const sortSelect = document.getElementById('sortSelect');
+        if (!sortSelect) return;
+        const randomOpt = sortSelect.querySelector('option[value="random"], option[value^="random:"]');
+        if (randomOpt) {
+            randomOpt.value = String(sortValue).startsWith('random') ? sortValue : 'random';
+        }
+        sortSelect.value = sortValue;
+    }
+
+    /**
+     * Generate a fresh seeded random sort value ("random:<seed>") and keep
+     * the native <select> in sync so its value matches the persisted sort
+     * string and the dropdown shows the selected label.
+     * @returns {string} The new sort value, e.g. "random:abc123xyz"
+     */
+    _randomizeSortValue() {
+        const seed = Math.random().toString(36).slice(2, 12);
+        const value = `random:${seed}`;
+        const sortSelect = document.getElementById('sortSelect');
+        if (sortSelect) {
+            const randomOpt = sortSelect.querySelector('option[value="random"], option[value^="random:"]');
+            if (randomOpt) {
+                randomOpt.value = value;
+            }
+            sortSelect.value = value;
+        }
+        return value;
+    }
+
     /**
      * Load sort preference from storage
      */
@@ -326,10 +374,7 @@ export class PageControls {
             // Handle legacy format conversion
             const convertedSort = this.convertLegacySortFormat(savedSort);
             this.pageState.sortBy = convertedSort;
-            const sortSelect = document.getElementById('sortSelect');
+            this.applySortToSelect(convertedSort);
-            if (sortSelect) {
-                sortSelect.value = convertedSort;
-            }
         }
     }
     
@@ -523,9 +568,9 @@ export class PageControls {
         this.pageState.sortBy = restoredSort;
         this.saveSortPreference(restoredSort);
         this._removeVlmSortOption();
+        this.applySortToSelect(restoredSort);
         const sortSelect = document.getElementById('sortSelect');
         if (sortSelect) {
-            sortSelect.value = restoredSort;
             sortSelect.disabled = false;
         }
     }
@@ -575,10 +620,7 @@ export class PageControls {
             const savedGroupedSort = getStorageItem(groupedKey);
             if (savedGroupedSort) {
                 this.pageState.sortBy = savedGroupedSort;
-                const sortSelect = document.getElementById('sortSelect');
+                this.applySortToSelect(savedGroupedSort);
-                if (sortSelect) {
-                    sortSelect.value = savedGroupedSort;
-                }
             }
         } else {
             // Leaving group mode: persist current sort for next time, restore non-group sort
@@ -586,10 +628,7 @@ export class PageControls {
             const savedNormalSort = getStorageItem(`${this.pageType}_sort`);
             if (savedNormalSort) {
                 this.pageState.sortBy = savedNormalSort;
-                const sortSelect = document.getElementById('sortSelect');
+                this.applySortToSelect(savedNormalSort);
-                if (sortSelect) {
-                    sortSelect.value = savedNormalSort;
-                }
             }
         }
     }
@@ -874,7 +913,7 @@ export class PageControls {
         }
 
         if (sortSelect) {
-            sortSelect.value = this.pageState.sortBy;
+            this.applySortToSelect(this.pageState.sortBy);
         }
         if (searchInput) {
             searchInput.value = this.pageState.filters?.search || '';

static/js/components/controls/SortDropdown.js

@@ -96,7 +96,16 @@ export function initSortDropdown(select) {
     };
 
     const choose = (value) => {
-        if (select.value === value) return;
+        if (select.value === value) {
+            // Re-picking the already-selected option is normally a no-op,
+            // matching native <select> behavior. The seeded Random sort is
+            // the exception: clicking it again should reshuffle, so let the
+            // change handler (PageControls) generate a fresh seed.
+            if (String(value).startsWith('random')) {
+                select.dispatchEvent(new Event('change', { bubbles: true }));
+            }
+            return;
+        }
         select.value = value;
         select.dispatchEvent(new Event('change', { bubbles: true }));
     };
@@ -277,9 +286,10 @@ export function initSortDropdown(select) {
     }
 
     // Rebuild the menu when <option>s change (VLM adds/removes a temporary
-    // option at runtime).
+    // option at runtime, and the seeded Random sort option gets a new value
+    // attribute each time it is picked).
     const observer = new MutationObserver(() => buildMenu());
-    observer.observe(select, { childList: true });
+    observer.observe(select, { childList: true, subtree: true, attributes: true, attributeFilter: ['value'] });
 
     buildMenu();
     group.dataset.sortReady = '1';

static/js/components/shared/ModelCard.js

@@ -489,6 +489,12 @@ export function createModelCard(model, modelType) {
     const modelId = civitaiData?.modelId ?? civitaiData?.model_id;
     if (modelId !== undefined && modelId !== null && modelId !== '') {
         card.dataset.modelId = modelId;
+    } else if (model.hf_url) {
+        // For HF-only models, derive a group key from hf_url for version grouping
+        const match = model.hf_url.match(/https?:\/\/huggingface\.co\/([^/]+\/[^/]+)/);
+        if (match) {
+            card.dataset.modelId = 'hf:' + match[1];
+        }
     }
 
     // LoRA specific data

static/js/components/shared/ModelModal.js

@@ -473,7 +473,14 @@ export async function showModelModal(model, modelType) {
     const loadingExamplesText = translate('modals.model.loading.examples', {}, 'Loading examples...');
 
     const loadingVersionsText = translate('modals.model.loading.versions', {}, 'Loading versions...');
-    const civitaiModelId = modelWithFullData.civitai?.modelId || '';
+    // Use CivitAI modelId, or derive HF group key for HF-only models
+    let civitaiModelId = modelWithFullData.civitai?.modelId || '';
+    if (!civitaiModelId && modelWithFullData.hf_url) {
+        const match = modelWithFullData.hf_url.match(/https?:\/\/huggingface\.co\/([^/]+\/[^/]+)/);
+        if (match) {
+            civitaiModelId = 'hf:' + match[1];
+        }
+    }
     const civitaiVersionId = modelWithFullData.civitai?.id || '';
     const navAriaLabel = translate('modals.model.navigation.label', {}, 'Model navigation');
     const previousTitle = translate('modals.model.navigation.previousWithShortcut', {}, 'Previous model (←)');
@@ -885,7 +892,8 @@ function setupEventHandlers(filePath, modelType) {
             case 'view-creator':
                 const username = target.dataset.username;
                 if (username) {
-                    window.open(`https://civitai.com/user/${username}`, '_blank');
+                    const host = state.global.settings.civitai_host || 'civitai.com';
+                    window.open(`https://${host}/user/${username}`, '_blank');
                 }
                 break;
             case 'open-file-location':

static/js/components/shared/ModelVersionsTab.js

@@ -950,6 +950,26 @@ export function initVersionsTab({
             renderErrorState(container, translate('modals.model.versions.missingModelId', {}, 'This model is missing a Civitai model id.'));
             return;
         }
+        // HF group keys (e.g. "hf:user/repo") are not real CivitAI model IDs —
+        // skip the remote API call and show a helpful message instead.
+        const isHfGroupKey = typeof modelId === 'string' && modelId.startsWith('hf:');
+        if (isHfGroupKey) {
+            controller.isLoading = false;
+            controller.hasLoaded = true;
+            controller.record = null;
+            const hfMsg = translate(
+                'modals.model.versions.hfGroupInfo',
+                {},
+                'This is a HuggingFace model group. Open the library to see all versions in the grid.'
+            );
+            container.innerHTML = `
+                <div class="versions-empty-state">
+                    <i class="fas fa-info-circle"></i>
+                    <p>${escapeHtml(hfMsg)}</p>
+                </div>
+            `;
+            return;
+        }
         if (controller.hasLoaded && !forceRefresh) {
             return;
         }

static/js/managers/BulkManager.js

@@ -27,6 +27,8 @@ export class BulkManager {
 
         // Drag detection properties
         this.dragThreshold = 5; // Pixels to move before considering it a drag
+        this.dragDelayMs = 100; // Minimum hold time before a drag is treated as a marquee
+        this.minMarqueeSize = 10; // Minimum drag box (px) before a marquee counts as a selection
         this.mouseDownTime = 0;
         this.mouseDownPosition = { x: 0, y: 0 };
 
@@ -88,7 +90,7 @@ export class BulkManager {
                 moveAll: true,
                 autoOrganize: false,
                 deleteAll: true,
-                setContentRating: false,
+                setContentRating: true,
                 skipMetadataRefresh: false,
                 setFavorite: true,
                 unfavorite: true,
@@ -173,6 +175,19 @@ export class BulkManager {
         });
 
         eventManager.addHandler('mousemove', 'bulkManager-marquee-move', (e) => {
+            // Only track marquee/drag while the left button is physically held.
+            // mouseup can be missed (release outside the window, focus loss, driver quirks),
+            // so mousemove must verify the button state itself instead of relying on it.
+            if (!(e.buttons & 1)) {
+                if (this.isMarqueeActive) {
+                    this.endMarqueeSelection(e);
+                } else {
+                    this.mouseDownTime = 0;
+                    this.isDragging = false;
+                }
+                return false;
+            }
+
             if (this.isMarqueeActive) {
                 this.lastClientX = e.clientX;
                 this.lastClientY = e.clientY;
@@ -184,7 +199,10 @@ export class BulkManager {
                 const dy = e.clientY - this.mouseDownPosition.y;
                 const distance = Math.sqrt(dx * dx + dy * dy);
 
-                if (distance >= this.dragThreshold) {
+                // Require both enough movement AND enough hold time so quick
+                // click jitter from micro-movement input devices is not a marquee.
+                const heldTime = Date.now() - this.mouseDownTime;
+                if (heldTime >= this.dragDelayMs && distance >= this.dragThreshold) {
                     this.isDragging = true;
                     this.startMarqueeSelection(e, true);
                 }
@@ -1510,14 +1528,18 @@ export class BulkManager {
         let failureCount = 0;
 
         try {
-            const apiClient = getModelApiClient();
+            const isRecipesPage = state.currentPageType === 'recipes';
             for (const filePath of targets) {
                 if (cancelled) {
                     showToast('toast.api.operationCancelled', {}, 'info');
                     break;
                 }
                 try {
-                    await apiClient.saveModelMetadata(filePath, { preview_nsfw_level: level });
+                    if (isRecipesPage) {
+                        await updateRecipeMetadata(filePath, { preview_nsfw_level: level });
+                    } else {
+                        await getModelApiClient().saveModelMetadata(filePath, { preview_nsfw_level: level });
+                    }
                     successCount++;
                 } catch (error) {
                     failureCount++;
@@ -1958,9 +1980,31 @@ export class BulkManager {
         // Remove visual feedback class
         document.body.classList.remove('marquee-selecting');
 
+        // Compute the actual drag box size in document coordinates, matching how
+        // updateMarqueeSelectionFromPosition tracks the rectangle. Client-space
+        // size would wrongly flag auto-scroll marquees (tiny pointer movement,
+        // large document-space box) as accidental clicks.
+        const container = document.querySelector('.page-content');
+        const scrollX = container?.scrollLeft || 0;
+        const scrollY = container?.scrollTop || 0;
+        const dragWidth = Math.abs((e.clientX + scrollX) - this.marqueeStartDoc.x);
+        const dragHeight = Math.abs((e.clientY + scrollY) - this.marqueeStartDoc.y);
+        const isTinyMarquee = dragWidth < this.minMarqueeSize && dragHeight < this.minMarqueeSize;
+
         // Get selection count
         const selectionCount = state.selectedModels.size;
 
+        // A tiny box (e.g. click jitter that happened to graze a card) is treated
+        // as an accidental click: undo any selection and leave bulk mode.
+        if (isTinyMarquee) {
+            this.clearSelection();
+            if (state.bulkMode) {
+                this.toggleBulkMode();
+            }
+            this.initialSelectedModels.clear();
+            return;
+        }
+
         // If no models were selected, exit bulk mode
         if (selectionCount === 0) {
             if (state.bulkMode) {

static/js/managers/DownloadManager.js

@@ -6,8 +6,9 @@ import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
 import { getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
 import { FolderTreeManager } from '../components/FolderTreeManager.js';
 import { translate } from '../utils/i18nHelpers.js';
-import { extractCivitaiModelUrlParts } from '../utils/civitaiUtils.js';
+import { buildCivitaiUrl, extractCivitaiModelUrlParts, normalizeCivitaiPageHost } from '../utils/civitaiUtils.js';
 import { formatFileSize } from '../utils/formatters.js';
+import { showDownloadBatchSummary } from '../components/DownloadBatchSummaryModal.js';
 
 export class DownloadManager {
     constructor() {
@@ -158,6 +159,7 @@ export class DownloadManager {
         this.modelVersionId = null;
         this.source = null;
         this.selectedFile = null;
+        this._isDiffusionModel = false;
 
         this.selectedFolder = '';
         this.batchModels = [];
@@ -233,6 +235,9 @@ export class DownloadManager {
 
                 if (this.modelVersionId) {
                     this.currentVersion = this.versions.find(v => v.id.toString() === this.modelVersionId);
+                } else {
+                    // No explicit version id in the URL → default to the latest version (Civitai returns newest first)
+                    this.currentVersion = this.versions[0];
                 }
 
                 this.showVersionStep();
@@ -426,6 +431,9 @@ export class DownloadManager {
             await this.retrieveVersionsForModel(this.modelId, this.source);
             if (this.modelVersionId) {
                 this.currentVersion = this.versions.find(v => v.id.toString() === this.modelVersionId);
+            } else {
+                // No explicit version id → default to the latest version (Civitai returns newest first)
+                this.currentVersion = this.versions[0];
             }
             this.showVersionStep();
         } catch (error) {
@@ -746,7 +754,7 @@ export class DownloadManager {
             this.selectedFile?.id, this.selectedFile?.name, this.selectedFile?.type, this.selectedFile?.metadata);
 
         document.getElementById('fileSelectionStep').style.display = 'none';
-        document.getElementById('locationStep').style.display = 'block';
+        document.getElementById('downloadLocationStep').style.display = 'block';
         this.proceedToLocationContent();
     }
 
@@ -780,31 +788,47 @@ export class DownloadManager {
         }
 
         document.querySelectorAll('.download-step').forEach(step => step.style.display = 'none');
-        document.getElementById('locationStep').style.display = 'block';
+        document.getElementById('downloadLocationStep').style.display = 'block';
         await this.proceedToLocationContent();
     }
 
     async proceedToLocationContent() {
 
         try {
-            // Fetch model roots
+            const _isDiffusionModel = this.selectedFile
-            const rootsData = await this.apiClient.fetchModelRoots();
+                ? (this.selectedFile.type === 'UNet' || this.selectedFile.type === 'Diffusion Model')
+                : (this.currentVersion?.files || []).some(
+                    f => f.type === 'UNet' || f.type === 'Diffusion Model'
+                );
+            this._isDiffusionModel = _isDiffusionModel;
+
+            let rootsData;
+            if (this._isDiffusionModel && this.apiClient.modelType === 'checkpoints') {
+                rootsData = await this.apiClient.fetchModelRoots('diffusion_model');
+            } else {
+                rootsData = await this.apiClient.fetchModelRoots();
+            }
             const modelRoot = document.getElementById('modelRoot');
             modelRoot.innerHTML = rootsData.roots.map(root =>
                 `<option value="${root}">${root}</option>`
             ).join('');
 
-            // Set default root if available
+            const singularType = this._isDiffusionModel
-            const singularType = this.apiClient.modelType.replace(/s$/, '');
+                ? 'unet'
+                : this.apiClient.modelType.replace(/s$/, '');
             const defaultRootKey = `default_${singularType}_root`;
             const defaultRoot = state.global.settings[defaultRootKey];
-            console.log(`Default root for ${this.apiClient.modelType}:`, defaultRoot);
+            console.log(`Default root for ${singularType}:`, defaultRoot);
             console.log('Available roots:', rootsData.roots);
             if (defaultRoot && rootsData.roots.includes(defaultRoot)) {
                 console.log(`Setting default root: ${defaultRoot}`);
                 modelRoot.value = defaultRoot;
             }
 
+            const subtypeDisplay = this._isDiffusionModel ? 'Diffusion Model' : this.apiClient.apiConfig.config.displayName;
+            document.getElementById('modelRootLabel').textContent =
+                translate('modals.download.selectTypeRoot', { type: subtypeDisplay });
+
             // Set autocomplete="off" on folderPath input
             const folderPathInput = document.getElementById('folderPath');
             if (folderPathInput) {
@@ -861,6 +885,26 @@ export class DownloadManager {
         this.updateTargetPath();
     }
 
+    /**
+     * Synthesize a clickable URL for a single-download failure entry.
+     * Single downloads have no pasted URL, so the modal link is derived from
+     * the model/version ids (CivitAI) or the HF repo/file (HuggingFace).
+     */
+    _buildSingleItemUrl({ modelId, versionId, source, repo = null, filename = null }) {
+        if (source === 'huggingface' && repo) {
+            const base = `https://huggingface.co/${encodeURI(repo)}`;
+            return filename ? `${base}/blob/${encodeURI('main')}/${encodeURI(filename)}` : base;
+        }
+        if (modelId) {
+            return buildCivitaiUrl({
+                modelId,
+                versionId,
+                host: normalizeCivitaiPageHost(state?.global?.settings?.civitai_host),
+            });
+        }
+        return null;
+    }
+
     async executeDownloadWithProgress({
         modelId,
         versionId,
@@ -879,6 +923,7 @@ export class DownloadManager {
         }
 
         const displayName = versionName || `#${versionId}`;
+        const retryParams = { modelId, versionId, versionName, modelRoot, targetFolder, useDefaultPaths, source, fileParams, closeModal: false };
         let ws = null;
         let updateProgress = () => { };
         let cancelled = false;
@@ -967,6 +1012,26 @@ export class DownloadManager {
                 return true;
             }
 
+            if (!response?.success) {
+                this.loadingManager.setStatus(translate('modals.download.status.finalizing'));
+                showDownloadBatchSummary({
+                    total: 1,
+                    completed: 0,
+                    failedItems: [{
+                        item: {
+                            modelId,
+                            versionId,
+                            source,
+                            url: this._buildSingleItemUrl({ modelId, versionId, source }),
+                        },
+                        error: response?.error || 'Unknown error',
+                        name: displayName,
+                    }],
+                    onRetry: () => this.executeDownloadWithProgress(retryParams),
+                });
+                return false;
+            }
+
             showToast('toast.loras.downloadCompleted', {}, 'success');
 
             if (closeModal) {
@@ -1001,7 +1066,21 @@ export class DownloadManager {
                 console.log('Download cancelled by user:', downloadId);
             } else {
                 console.error('Failed to download model version:', error);
-                showToast('toast.downloads.downloadError', { message: error?.message }, 'error');
+                showDownloadBatchSummary({
+                    total: 1,
+                    completed: 0,
+                    failedItems: [{
+                        item: {
+                            modelId,
+                            versionId,
+                            source,
+                            url: this._buildSingleItemUrl({ modelId, versionId, source }),
+                        },
+                        error: error?.message || 'Unknown error',
+                        name: displayName,
+                    }],
+                    onRetry: () => this.executeDownloadWithProgress(retryParams),
+                });
             }
             return false;
         } finally {
@@ -1016,14 +1095,16 @@ export class DownloadManager {
         }
     }
 
-    async _downloadHfSingle({ modelRoot, targetFolder, useDefaultPaths }) {
+    async _downloadHfSingle({ modelRoot, targetFolder, useDefaultPaths, files = null }) {
         modalManager.closeModal('downloadModal');
         this.loadingManager.restoreProgressBar();
-        const totalFiles = this.hfSelectedFiles.length;
+        const filesToDownload = files || this.hfSelectedFiles;
+        const totalFiles = filesToDownload.length;
         const updateProgress = this.loadingManager.showDownloadProgress(totalFiles);
 
         let cancelled = false;
         let currentDownloadId = null;
+        const failedFiles = [];
 
         this.loadingManager.showCancelButton(async () => {
             if (cancelled) return;
@@ -1042,7 +1123,7 @@ export class DownloadManager {
             for (let i = 0; i < totalFiles; i++) {
                 if (cancelled) break;
 
-                const filename = this.hfSelectedFiles[i];
+                const filename = filesToDownload[i];
                 updateProgress(0, completedDownloads, filename);
                 this.loadingManager.setStatus(`Downloading ${filename}...`);
 
@@ -1088,6 +1169,31 @@ export class DownloadManager {
                     if (response?.success) {
                         completedDownloads++;
                         updateProgress(100, completedDownloads, filename);
+                    } else {
+                        failedFiles.push({
+                            item: {
+                                source: 'huggingface',
+                                repo: this.hfRepoId,
+                                filename,
+                                url: this._buildSingleItemUrl({ source: 'huggingface', repo: this.hfRepoId, filename }),
+                            },
+                            error: response?.error || 'Unknown error',
+                            name: filename,
+                        });
+                    }
+                } catch (err) {
+                    if (!cancelled) {
+                        console.error(`Failed to download HF file ${filename}:`, err);
+                        failedFiles.push({
+                            item: {
+                                source: 'huggingface',
+                                repo: this.hfRepoId,
+                                filename,
+                                url: this._buildSingleItemUrl({ source: 'huggingface', repo: this.hfRepoId, filename }),
+                            },
+                            error: err?.message || 'Unknown error',
+                            name: filename,
+                        });
                     }
                 } finally {
                     ws.close();
@@ -1097,11 +1203,27 @@ export class DownloadManager {
             if (cancelled) {
                 showToast('toast.downloads.downloadStopped', {}, 'info',
                     `Download cancelled. ${completedDownloads} item(s) completed.`);
-            } else {
-                showToast('toast.loras.downloadCompleted', {}, 'success');
-            }
                 await resetAndReload(true);
                 return true;
+            }
+            if (failedFiles.length === 0) {
+                showToast('toast.loras.downloadCompleted', {}, 'success');
+                await resetAndReload(true);
+                return true;
+            }
+            showDownloadBatchSummary({
+                total: totalFiles,
+                completed: completedDownloads,
+                failedItems: failedFiles,
+                onRetry: () => this._downloadHfSingle({
+                    modelRoot,
+                    targetFolder,
+                    useDefaultPaths,
+                    files: failedFiles.map((f) => f.item.filename),
+                }),
+            });
+            await resetAndReload(true);
+            return false;
         } catch (error) {
             if (!cancelled) {
                 console.error('Failed to download HF model:', error);
@@ -1441,7 +1563,7 @@ export class DownloadManager {
     }
 
     backToVersions() {
-        document.getElementById('locationStep').style.display = 'none';
+        document.getElementById('downloadLocationStep').style.display = 'none';
         if (this.isBatchMode) {
             document.getElementById('batchPreviewStep').style.display = 'block';
         } else {
@@ -1531,6 +1653,10 @@ export class DownloadManager {
 
         modalManager.closeModal('downloadModal');
 
+        return this.executeBatchDownload(downloadItems, { modelRoot, targetFolder, useDefaultPaths });
+    }
+
+    async executeBatchDownload(downloadItems, { modelRoot, targetFolder, useDefaultPaths }) {
         const batchDownloadId = Date.now().toString();
         const wsProtocol = window.location.protocol === 'https:' ? 'wss://' : 'ws://';
         const ws = new WebSocket(`${wsProtocol}${window.location.host}/ws/download-progress?id=${batchDownloadId}`);
@@ -1541,6 +1667,7 @@ export class DownloadManager {
         let completedDownloads = 0;
         let failedDownloads = 0;
         let cancelled = false;
+        const failedItems = [];
 
         loadingManager.showCancelButton(async () => {
             if (cancelled) return;
@@ -1641,6 +1768,7 @@ export class DownloadManager {
 
                 if (!response.success) {
                     failedDownloads++;
+                    failedItems.push({ item, error: response.error || 'Unknown error', name });
                 } else {
                     completedDownloads++;
                     updateProgress(100, completedDownloads, '');
@@ -1649,6 +1777,7 @@ export class DownloadManager {
                 if (!cancelled) {
                     console.error(`Failed to download ${name}:`, err);
                     failedDownloads++;
+                    failedItems.push({ item, error: err?.message || 'Unknown error', name });
                 }
             }
         }
@@ -1662,10 +1791,15 @@ export class DownloadManager {
         } else if (failedDownloads === 0) {
             showToast('toast.loras.allDownloadSuccessful', { count: completedDownloads }, 'success');
         } else {
-            showToast('toast.loras.downloadPartialSuccess', {
+            showDownloadBatchSummary({
-                completed: completedDownloads,
                 total: downloadItems.length,
-            }, 'warning');
+                completed: completedDownloads,
+                failedItems,
+                onRetry: (failed) => this.executeBatchDownload(
+                    failed.map((f) => f.item),
+                    { modelRoot, targetFolder, useDefaultPaths }
+                ),
+            });
         }
 
         await resetAndReload(true);
@@ -1776,13 +1910,15 @@ export class DownloadManager {
         const modelRoot = document.getElementById('modelRoot').value;
         const config = this.apiClient.apiConfig.config;
 
-        let fullPath = modelRoot || translate('modals.download.selectTypeRoot', { type: config.displayName });
+        const subtypeDisplay = this._isDiffusionModel ? 'Diffusion Model' : config.displayName;
+        let fullPath = modelRoot || translate('modals.download.selectTypeRoot', { type: subtypeDisplay });
 
         if (modelRoot) {
             if (this.useDefaultPath) {
-                // Show actual template path
                 try {
-                    const singularType = this.apiClient.modelType.replace(/s$/, '');
+                    const singularType = this._isDiffusionModel
+                        ? 'unet'
+                        : this.apiClient.modelType.replace(/s$/, '');
                     const templates = state.global.settings.download_path_templates;
                     const template = templates[singularType];
                     fullPath += `/${template}`;

static/js/managers/FilterManager.js

@@ -729,10 +729,12 @@ export class FilterManager {
         const pageState = getCurrentPageState();
         const storageKey = `${this.currentPage}_filters`;
 
-        // Save filters to localStorage (exclude EMPTY_WILDCARD_MARKER)
+        // Save filters to localStorage (exclude EMPTY_WILDCARD_MARKER and transient search)
         const filtersSnapshot = this.cloneFilters();
         // Don't persist EMPTY_WILDCARD_MARKER - it's a runtime-only marker
         filtersSnapshot.baseModel = filtersSnapshot.baseModel.filter(m => m !== EMPTY_WILDCARD_MARKER);
+        // Don't persist search - it's transient and managed by SearchManager
+        delete filtersSnapshot.search;
         setStorageItem(storageKey, filtersSnapshot);
 
         // Update state with current filters
@@ -984,6 +986,7 @@ export class FilterManager {
     }
 
     cloneFilters() {
+        const pageState = getCurrentPageState();
         return {
             ...this.filters,
             baseModel: [...(this.filters.baseModel || [])],
@@ -991,7 +994,8 @@ export class FilterManager {
             autoTags: { ...(this.filters.autoTags || {}) },
             license: { ...(this.filters.license || {}) },
             modelTypes: [...(this.filters.modelTypes || [])],
-            tagLogic: this.filters.tagLogic || 'any'
+            tagLogic: this.filters.tagLogic || 'any',
+            search: pageState?.filters?.search ?? ''
         };
     }
 

static/js/managers/FilterPresetManager.js

@@ -6,7 +6,6 @@ import { state } from '../state/index.js';
 // Constants for preset management
 const PRESETS_STORAGE_VERSION = 'v1';
 const MAX_PRESET_NAME_LENGTH = 30;
-const MAX_PRESETS_COUNT = 10;
 
 // Marker for when wildcard patterns resolve to no matches
 // This ensures we return empty results instead of all models
@@ -362,15 +361,6 @@ export class FilterPresetManager {
             }
         }
 
-        if (presets.length >= MAX_PRESETS_COUNT) {
-            showToast(
-                translate('toast.error.maxPresetsReached', { max: MAX_PRESETS_COUNT }, `Maximum ${MAX_PRESETS_COUNT} presets allowed. Delete one to add more.`),
-                {},
-                'error'
-            );
-            return false;
-        }
-
         const preset = {
             name: trimmedName,
             filters: this.filterManager.cloneFilters(),
@@ -613,17 +603,6 @@ export class FilterPresetManager {
             return;
         }
 
-        // Check max presets limit before showing input
-        const presets = this.loadPresets();
-        if (presets.length >= MAX_PRESETS_COUNT) {
-            showToast(
-                translate('toast.error.maxPresetsReached', { max: MAX_PRESETS_COUNT }, `Maximum ${MAX_PRESETS_COUNT} presets allowed. Delete one to add more.`),
-                {},
-                'error'
-            );
-            return;
-        }
-
         this.isInlineNamingActive = true;
 
         const presetsContainer = document.getElementById('filterPresets');

static/js/managers/SettingsManager.js

@@ -1017,6 +1017,12 @@ export class SettingsManager {
             displayDensitySelect.value = state.global.settings.display_density || 'default';
         }
 
+        // Set recipes layout setting
+        const recipesLayoutSelect = document.getElementById('recipesLayout');
+        if (recipesLayoutSelect) {
+            recipesLayoutSelect.value = state.global.settings.recipes_layout || 'grid';
+        }
+
         // Set card info display setting
         const cardInfoDisplaySelect = document.getElementById('cardInfoDisplay');
         if (cardInfoDisplaySelect) {
@@ -1517,11 +1523,20 @@ export class SettingsManager {
         return data;
     }
 
+    showNoRootsPlaceholder(select) {
+        select.innerHTML = '';
+        const option = document.createElement('option');
+        option.value = '';
+        option.textContent = translate('settings.folderSettings.noDefault', {}, 'No Default');
+        select.appendChild(option);
+        select.disabled = true;
+    }
+
     async loadLoraRoots() {
-        try {
         const defaultLoraRootSelect = document.getElementById('defaultLoraRoot');
         if (!defaultLoraRootSelect) return;
 
+        try {
             // Fetch lora roots
             const response = await fetch('/api/lm/loras/roots');
             if (!response.ok) {
@@ -1530,10 +1545,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No LoRA roots found');
+                this.showNoRootsPlaceholder(defaultLoraRootSelect);
+                return;
             }
 
             defaultLoraRootSelect.innerHTML = '';
+            defaultLoraRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1548,15 +1565,16 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading LoRA roots:', error);
+            this.showNoRootsPlaceholder(defaultLoraRootSelect);
             showToast('toast.settings.loraRootsFailed', { message: error.message }, 'error');
         }
     }
 
     async loadCheckpointRoots() {
-        try {
         const defaultCheckpointRootSelect = document.getElementById('defaultCheckpointRoot');
         if (!defaultCheckpointRootSelect) return;
 
+        try {
             // Fetch checkpoint roots (checkpoint paths only, not unet)
             const response = await fetch('/api/lm/checkpoints/checkpoints_roots');
             if (!response.ok) {
@@ -1565,10 +1583,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No checkpoint roots found');
+                this.showNoRootsPlaceholder(defaultCheckpointRootSelect);
+                return;
             }
 
             defaultCheckpointRootSelect.innerHTML = '';
+            defaultCheckpointRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1583,15 +1603,16 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading checkpoint roots:', error);
+            this.showNoRootsPlaceholder(defaultCheckpointRootSelect);
             showToast('toast.settings.checkpointRootsFailed', { message: error.message }, 'error');
         }
     }
 
     async loadUnetRoots() {
-        try {
         const defaultUnetRootSelect = document.getElementById('defaultUnetRoot');
         if (!defaultUnetRootSelect) return;
 
+        try {
             // Fetch unet roots (diffusion model paths only)
             const response = await fetch('/api/lm/checkpoints/unet_roots');
             if (!response.ok) {
@@ -1600,10 +1621,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No diffusion model roots found');
+                this.showNoRootsPlaceholder(defaultUnetRootSelect);
+                return;
             }
 
             defaultUnetRootSelect.innerHTML = '';
+            defaultUnetRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1618,15 +1641,16 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading diffusion model roots:', error);
+            this.showNoRootsPlaceholder(defaultUnetRootSelect);
             showToast('toast.settings.unetRootsFailed', { message: error.message }, 'error');
         }
     }
 
     async loadEmbeddingRoots() {
-        try {
         const defaultEmbeddingRootSelect = document.getElementById('defaultEmbeddingRoot');
         if (!defaultEmbeddingRootSelect) return;
 
+        try {
             // Fetch embedding roots
             const response = await fetch('/api/lm/embeddings/roots');
             if (!response.ok) {
@@ -1635,10 +1659,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No embedding roots found');
+                this.showNoRootsPlaceholder(defaultEmbeddingRootSelect);
+                return;
             }
 
             defaultEmbeddingRootSelect.innerHTML = '';
+            defaultEmbeddingRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1653,6 +1679,7 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading embedding roots:', error);
+            this.showNoRootsPlaceholder(defaultEmbeddingRootSelect);
             showToast('toast.settings.embeddingRootsFailed', { message: error.message }, 'error');
         }
     }
@@ -2267,6 +2294,13 @@ export class SettingsManager {
             // Apply frontend settings immediately
             this.applyFrontendSettings();
 
+            // Dispatch layout change event; the scroller instance is about to be rebuilt,
+            // so calculateLayout() must NOT run on the old instance here
+            if (settingKey === 'recipes_layout') {
+                window.dispatchEvent(new CustomEvent('lm:recipes-layout-changed'));
+                return;
+            }
+
             // Recalculate layout when display density changes
             if (settingKey === 'display_density' && state.virtualScroller) {
                 state.virtualScroller.calculateLayout();

static/js/managers/UpdateService.js

@@ -6,6 +6,7 @@ import {
     setStoredVersionInfo,
     isVersionMatch
 } from '../utils/storageHelpers.js';
+import { state } from '../state/index.js';
 import { bannerService } from './BannerService.js';
 import { translate } from '../utils/i18nHelpers.js';
 
@@ -24,7 +25,11 @@ export class UpdateService {
         this.updateNotificationsEnabled = getStorageItem('show_update_notifications', true);
         this.lastCheckTime = parseInt(getStorageItem('last_update_check') || '0');
         this.isUpdating = false;
-        this.nightlyMode = getStorageItem('nightly_updates', false);
+        this.channelMode = null;
+        this.hasGit = false;
+        this.nightlyNotifyDate = getStorageItem('nightly_notify_date', '');
+        this.nightlyBadgeShown = false;
+        this.progressKeepVisible = false;
         this.currentVersionInfo = null;
         this.versionMismatch = false;
         this.activeNotificationTab = 'updates';
@@ -49,43 +54,180 @@ export class UpdateService {
             updateBtn.addEventListener('click', () => this.performUpdate());
         }
         
-        // Register event listener for nightly update toggle
+        this.wireChannelButtons();
-        const nightlyCheckbox = document.getElementById('nightlyUpdateToggle');
-        if (nightlyCheckbox) {
-            nightlyCheckbox.checked = this.nightlyMode;
-            nightlyCheckbox.addEventListener('change', (e) => {
-                this.nightlyMode = e.target.checked;
-                setStorageItem('nightly_updates', e.target.checked);
-                this.updateNightlyWarning();
-                this.updateModalContent();
-                // Re-check for updates when switching channels
-                this.manualCheckForUpdates();
-            });
-            this.updateNightlyWarning();
-        }
 
         this.setupNotificationCenter();
         window.addEventListener('lm:banner-history-updated', this.handleBannerHistoryUpdated);
         this.updateTabBadges();
         
         // Perform update check if needed
+        this.checkVersionInfo().then(() => {
             this.checkForUpdates().then(() => {
-            // Ensure badges are updated after checking
                 this.updateBadgeVisibility();
             });
+        });
 
-        // Immediately update modal content with current values (even if from default)
         this.updateModalContent();
-        
-        // Check version info for mismatch after loading basic info
-        this.checkVersionInfo();
     }
     
-    updateNightlyWarning() {
+    wireChannelButtons() {
-        const warning = document.getElementById('nightlyWarning');
+        const releaseBtn = document.getElementById('channelRelease');
-        if (warning) {
+        const nightlyBtn = document.getElementById('channelNightly');
-            warning.style.display = this.nightlyMode ? 'flex' : 'none';
+        if (releaseBtn) {
+            releaseBtn.addEventListener('click', () => this.switchChannel('release'));
         }
+        if (nightlyBtn) {
+            nightlyBtn.addEventListener('click', () => this.switchChannel('nightly'));
+        }
+    }
+
+    async switchChannel(channel) {
+        if (channel === this.channelMode) {
+            return;
+        }
+        if (this.isUpdating) {
+            return;
+        }
+        if (!this.hasGit && channel === 'nightly') {
+            const confirmed = await this._confirmChannelSwitch(
+                'update.channelSwitch.nightlyTitle',
+                'update.channelSwitch.nightlyMessage'
+            );
+            if (!confirmed) return;
+        }
+        if (this.hasGit && channel === 'release') {
+            const confirmed = await this._confirmChannelSwitch(
+                'update.channelSwitch.releaseTitle',
+                'update.channelSwitch.releaseMessage'
+            );
+            if (!confirmed) return;
+        }
+
+        try {
+            this.isUpdating = true;
+            this.showUpdateProgress(true);
+            this.updateProgress(10, translate('update.channelSwitch.switching', { channel }));
+
+            const response = await fetch('/api/lm/switch-channel', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ channel })
+            });
+
+            const data = await response.json();
+
+            if (data.success) {
+                this.channelMode = channel;
+                // Persist channel preference to settings.json
+                fetch('/api/lm/settings', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ update_channel: channel })
+                }).then(r => {
+                    if (!r.ok) console.warn('Failed to persist update channel:', r.status);
+                }).catch(e => console.warn('Failed to persist update channel:', e));
+                await this.checkForUpdates({ force: true });
+                this.updateModalContent();
+                this.updateChannelUI();
+                this._showSwitchCompleteMessage(data.new_version);
+                this.progressKeepVisible = true;
+            } else {
+                throw new Error(data.error || translate('update.channelSwitch.failed'));
+            }
+        } catch (error) {
+            console.error('Channel switch failed:', error);
+            this.updateProgress(0, translate('update.channelSwitch.failed'));
+        } finally {
+            if (this.progressKeepVisible) {
+                this.isUpdating = false;
+                this.progressKeepVisible = false;
+            } else {
+                setTimeout(() => {
+                    this.showUpdateProgress(false);
+                    this.isUpdating = false;
+                }, 2000);
+            }
+        }
+    }
+
+    updateChannelUI() {
+        const releaseBtn = document.getElementById('channelRelease');
+        const nightlyBtn = document.getElementById('channelNightly');
+
+        if (releaseBtn) {
+            releaseBtn.classList.toggle('active', this.channelMode === 'release');
+        }
+        if (nightlyBtn) {
+            nightlyBtn.classList.toggle('active', this.channelMode === 'nightly');
+        }
+    }
+
+    _resolveChannelFromSettings() {
+        const stored = state?.global?.settings?.update_channel;
+        if (stored === 'nightly' || stored === 'release') {
+            return stored;
+        }
+        if (!this.hasGit) {
+            return 'release';
+        }
+        if (this.gitInfo?.branch === 'detached') {
+            return 'release';
+        }
+        return 'nightly';
+    }
+
+    async _confirmChannelSwitch(titleKey, messageKey) {
+        return new Promise((resolve) => {
+            const title = translate(titleKey);
+            const message = translate(messageKey);
+            const cancelText = translate('common.cancel');
+            const confirmText = translate('common.confirm');
+
+            const overlay = document.createElement('div');
+            overlay.className = 'channel-switch-overlay';
+            overlay.innerHTML = `
+                <div class="channel-switch-dialog">
+                    <h3>${title}</h3>
+                    <p>${message}</p>
+                    <div class="channel-switch-actions">
+                        <button class="secondary-btn channel-switch-cancel">${cancelText}</button>
+                        <button class="primary-btn channel-switch-confirm">${confirmText}</button>
+                    </div>
+                </div>
+            `;
+
+            const dismiss = (result) => {
+                document.removeEventListener('keydown', onKeydown);
+                overlay.remove();
+                resolve(result);
+            };
+
+            const onKeydown = (e) => {
+                if (e.key === 'Escape') {
+                    e.stopPropagation();
+                    e.preventDefault();
+                    dismiss(false);
+                }
+            };
+
+            document.addEventListener('keydown', onKeydown, { capture: true });
+
+            overlay.addEventListener('click', (e) => {
+                if (e.target === overlay) {
+                    dismiss(false);
+                }
+            });
+
+            overlay.querySelector('.channel-switch-cancel').addEventListener('click', () => {
+                dismiss(false);
+            });
+
+            overlay.querySelector('.channel-switch-confirm').addEventListener('click', () => {
+                dismiss(true);
+            });
+
+            document.body.appendChild(overlay);
+        });
     }
 
     setupNotificationCenter() {
@@ -355,6 +497,18 @@ export class UpdateService {
     }
     
     async checkForUpdates({ force = false } = {}) {
+        let needsMigration = false;
+        if (this.channelMode === null) {
+            const stored = state?.global?.settings?.update_channel;
+            if (stored === 'nightly' || stored === 'release') {
+                this.channelMode = stored;
+            } else if (!this.hasGit) {
+                this.channelMode = 'release';
+                needsMigration = true;
+            }
+            // hasGit=true with no stored value: wait for gitInfo.branch
+        }
+
         if (!force && !this.updateNotificationsEnabled) {
             return;
         }
@@ -373,7 +527,8 @@ export class UpdateService {
 
         try {
             // Call backend API to check for updates with nightly flag
-            const response = await fetch(`/api/lm/check-updates?nightly=${this.nightlyMode}`);
+            const nightly = (this.channelMode ?? (this.hasGit ? 'nightly' : 'release')) === 'nightly';
+            const response = await fetch(`/api/lm/check-updates?nightly=${nightly}`);
             const data = await response.json();
             
             if (data.success) {
@@ -381,17 +536,35 @@ export class UpdateService {
                 this.latestVersion = data.latest_version || "v0.0.0";
                 this.updateInfo = data;
                 this.gitInfo = data.git_info || this.gitInfo;
+                this.hasGit = data.has_git || false;
 
-                // Explicitly set update availability based on version comparison
+                if (needsMigration || this.channelMode === null) {
-                this.updateAvailable = this.isNewerVersion(this.latestVersion, this.currentVersion);
+                    this.channelMode = this._resolveChannelFromSettings();
+                    if (state?.global?.settings) {
+                        state.global.settings.update_channel = this.channelMode;
+                    }
+                    fetch('/api/lm/settings', {
+                        method: 'POST',
+                        headers: { 'Content-Type': 'application/json' },
+                        body: JSON.stringify({ update_channel: this.channelMode })
+                    }).then(r => {
+                        if (!r.ok) console.warn('Failed to persist update channel:', r.status);
+                    }).catch(e => console.warn('Failed to persist update channel:', e));
+                }
+
+                this.updateAvailable = data.update_available;
+
+                // Nightly channel: surface the update badge at most once per calendar day.
+                if (this.updateAvailable && this.channelMode === 'nightly' && this.nightlyNotifyDate !== this._getTodayKey()) {
+                    this._markNightlyNotified();
+                }
 
-                // Update last check time
                 this.lastCheckTime = now;
                 setStorageItem('last_update_check', now.toString());
 
-                // Update UI
                 this.updateBadgeVisibility();
                 this.updateModalContent();
+                this.updateChannelUI();
 
                 console.log("Update check complete:", {
                     currentVersion: this.currentVersion,
@@ -436,6 +609,28 @@ export class UpdateService {
         return false;
     }
 
+    _getTodayKey() {
+        const now = new Date();
+        const month = String(now.getMonth() + 1).padStart(2, '0');
+        const day = String(now.getDate()).padStart(2, '0');
+        return `${now.getFullYear()}-${month}-${day}`;
+    }
+
+    _isNightlyBadgeAllowed() {
+        if (this.channelMode !== 'nightly') {
+            return true;
+        }
+        // Keep the badge visible for the rest of the session once shown, but do
+        // not show it again on later sessions within the same calendar day.
+        return this.nightlyNotifyDate !== this._getTodayKey() || this.nightlyBadgeShown;
+    }
+
+    _markNightlyNotified() {
+        this.nightlyNotifyDate = this._getTodayKey();
+        this.nightlyBadgeShown = true;
+        setStorageItem('nightly_notify_date', this.nightlyNotifyDate);
+    }
+    
     updateBadgeVisibility() {
         const updateToggle = document.querySelector('.update-toggle');
         const updateBadge = document.querySelector('.update-toggle .update-badge');
@@ -443,9 +638,12 @@ export class UpdateService {
             ? bannerService.getUnreadBannerCount()
             : 0;
 
+        // Force updating badges visibility based on current state
+        const shouldShowUpdate = this.updateNotificationsEnabled && this.updateAvailable && this._isNightlyBadgeAllowed();
+
         if (updateToggle) {
             let tooltipKey = 'header.actions.notifications';
-            if (this.updateNotificationsEnabled && this.updateAvailable) {
+            if (shouldShowUpdate) {
                 tooltipKey = 'update.updateAvailable';
             } else if (unreadBanners > 0) {
                 tooltipKey = 'update.tabs.messages';
@@ -453,8 +651,6 @@ export class UpdateService {
             updateToggle.title = translate(tooltipKey);
         }
 
-        // Force updating badges visibility based on current state
-        const shouldShowUpdate = this.updateNotificationsEnabled && this.updateAvailable;
         const shouldShow = shouldShowUpdate || unreadBanners > 0;
 
         if (updateBadge) {
@@ -482,9 +678,32 @@ export class UpdateService {
         
         if (currentVersionEl) currentVersionEl.textContent = this.currentVersion;
         
+        const newVersionLabel = modal.querySelector('.new-version .label');
+        if (newVersionLabel) {
+            newVersionLabel.textContent = (this.updateInfo?.nightly)
+                ? `${translate('update.latestMain')}:`
+                : `${translate('update.newVersion')}:`;
+        }
+
         if (newVersionEl) {
+            if (this.updateInfo?.nightly) {
+                const behind = this.updateInfo.behind_by || 0;
+                const remoteHash = this.latestVersion.replace('main-', '');
+                const localHash = this.gitInfo.short_hash || '';
+                const date = this.updateInfo.commit_date || '';
+                const datePart = date ? ` · ${date}` : '';
+
+                if (behind > 0) {
+                    newVersionEl.textContent = `${behind} commit${behind !== 1 ? 's' : ''} behind main (${remoteHash}${datePart})`;
+                } else if (localHash !== remoteHash) {
+                    newVersionEl.textContent = `Behind main (${remoteHash}${datePart})`;
+                } else {
+                    newVersionEl.textContent = `Up to date (${remoteHash}${datePart})`;
+                }
+            } else {
                 newVersionEl.textContent = this.latestVersion;
             }
+        }
         
         // Update update button state
         const updateBtn = modal.querySelector('#updateBtn');
@@ -599,10 +818,14 @@ export class UpdateService {
         // Update GitHub link to point to the specific release if available
         const githubLink = modal.querySelector('.update-link');
         if (githubLink && this.latestVersion) {
+            if (this.updateInfo?.nightly) {
+                githubLink.href = 'https://github.com/willmiao/ComfyUI-Lora-Manager/commits/main';
+            } else {
                 const versionTag = this.latestVersion.replace(/^v/, '');
                 githubLink.href = `https://github.com/willmiao/ComfyUI-Lora-Manager/releases/tag/v${versionTag}`;
             }
         }
+    }
     
     async performUpdate() {
         if (!this.updateAvailable || this.isUpdating) {
@@ -623,7 +846,7 @@ export class UpdateService {
                     'Content-Type': 'application/json'
                 },
                 body: JSON.stringify({
-                    nightly: this.nightlyMode
+                    nightly: this.channelMode === 'nightly'
                 })
             });
             
@@ -699,6 +922,25 @@ export class UpdateService {
         }
     }
 
+    _showSwitchCompleteMessage(version) {
+        this.showUpdateProgress(true);
+        this.updateProgress(100, '');
+        const progressText = document.getElementById('updateProgressText');
+        if (progressText) {
+            progressText.innerHTML = `
+                <div style="text-align: center; color: var(--lora-success);">
+                    <i class="fas fa-check-circle" style="margin-right: 8px;"></i>
+                    ${translate('update.completion.successMessage', { version })}
+                    <br><br>
+                    <div style="opacity: 0.95; color: var(--lora-error); font-size: 1em;">
+                        ${translate('update.completion.restartMessage')}<br>
+                        ${translate('update.completion.reloadMessage')}
+                    </div>
+                </div>
+            `;
+        }
+    }
+
     showUpdateCompleteMessage(newVersion) {
         const modal = document.getElementById('updateModal');
         if (!modal) return;
@@ -771,6 +1013,7 @@ export class UpdateService {
 
         // Update the modal content immediately with current data
         this.updateModalContent();
+        this.updateChannelUI();
         this.renderRecentBanners();
 
         // Show the modal with current data
@@ -801,8 +1044,8 @@ export class UpdateService {
             
             if (data.success) {
                 this.currentVersionInfo = data.version;
+                this.hasGit = data.has_git || false;
 
-                // Check if version matches stored version
                 this.versionMismatch = !isVersionMatch(this.currentVersionInfo);
                 
                 if (this.versionMismatch) {

static/js/managers/import/DownloadManager.js

@@ -3,6 +3,7 @@ import { translate } from '../../utils/i18nHelpers.js';
 import { getModelApiClient } from '../../api/modelApiFactory.js';
 import { MODEL_TYPES } from '../../api/apiConfig.js';
 import { getStorageItem } from '../../utils/storageHelpers.js';
+import { state } from '../../state/index.js';
 
 export class DownloadManager {
     constructor(importManager) {
@@ -125,11 +126,25 @@ export class DownloadManager {
                 showToast('toast.recipes.nameSaved', { name: this.importManager.recipeName }, 'success');
             }
 
-            // Close modal
             modalManager.closeModal('importModal');
 
-            // Refresh the recipe
+            if (isDownloadOnly && state.virtualScroller) {
-            window.recipeManager.loadRecipes(true);
+                const recipeId = this.importManager.recipeId;
+                try {
+                    const detailRes = await fetch(`/api/lm/recipe/${encodeURIComponent(recipeId)}`);
+                    if (detailRes.ok) {
+                        const updated = await detailRes.json();
+                        state.virtualScroller.updateSingleItem(updated.file_path, updated);
+                    } else {
+                        throw new Error(`API returned ${detailRes.status}`);
+                    }
+                } catch (e) {
+                    console.warn('Failed to update recipe card in-place, falling back to reload:', e);
+                    await window.recipeManager.loadRecipes({ resetPage: true, preserveScroll: true });
+                }
+            } else {
+                window.recipeManager.loadRecipes({ resetPage: true, preserveScroll: true });
+            }
 
         } catch (error) {
             console.error('Error:', error);

static/js/managers/import/ImportStepManager.js

@@ -47,11 +47,8 @@ export class ImportStepManager {
                 targetStep.offsetHeight;
             }
             
-            // Scroll modal content to top
+            // Scroll the active step back to top (steps scroll independently of the modal shell)
-            const modalContent = document.querySelector('#importModal .modal-content');
+            targetStep.scrollTop = 0;
-            if (modalContent) {
-                modalContent.scrollTop = 0;
-            }
         }
     }
 }

static/js/recipes.js

@@ -7,7 +7,7 @@ import { state, getCurrentPageState } from './state/index.js';
 import { getStorageItem, setStorageItem, getSessionItem, removeSessionItem } from './utils/storageHelpers.js';
 import { RecipeContextMenu } from './components/ContextMenu/index.js';
 import { DuplicatesManager } from './components/DuplicatesManager.js';
-import { refreshVirtualScroll } from './utils/infiniteScroll.js';
+import { refreshVirtualScroll, recreateVirtualScroll } from './utils/infiniteScroll.js';
 import { refreshRecipes, RecipeSidebarApiClient } from './api/recipeApi.js';
 import { sidebarManager } from './components/SidebarManager.js';
 import { initSortDropdown } from './components/controls/SortDropdown.js';
@@ -272,6 +272,20 @@ class RecipeManager {
             });
         }
 
+        // Rebuild the scroller on layout switch; in duplicates mode defer until
+        // exitDuplicateMode re-enables the scroller (direct recreation would dispose
+        // the old instance while initializeVirtualScroll skips duplicates mode)
+        window.addEventListener('lm:recipes-layout-changed', () => {
+            const pageState = getCurrentPageState();
+            if (pageState.duplicatesMode) {
+                state.pendingLayoutRecreate = true;
+                return;
+            }
+            if (typeof recreateVirtualScroll === 'function') {
+                recreateVirtualScroll('recipes');
+            }
+        });
+
         // Initialize dropdown functionality for refresh button
         this.initDropdowns();
     }

static/js/state/index.js

@@ -38,6 +38,7 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
     card_blur_amount: 8,
     autoplay_on_hover: false,
     display_density: 'default',
+    recipes_layout: 'grid',
     card_info_display: 'always',
     model_name_display: 'model_name',
     lora_syntax_format: 'legacy',

static/js/utils/VirtualScroller.js

@@ -483,10 +483,18 @@ export class VirtualScroller {
         element.style.width = `${this.itemWidth}px`;
         element.style.height = `${this.itemHeight}px`;
 
-        // Remove max-width constraint from model-card to allow dynamic sizing
+        // Remove max-width/min-width constraints from the model-card to allow
-        const modelCard = element.querySelector('.model-card');
+        // dynamic sizing. The card is either the item element itself (e.g.
+        // RecipeCard returns the .model-card root) or a descendant (ModelCard).
+        // Without this, the CSS min-width of 200px forces compact-density cards
+        // wider than their allocated column, and the last column gets clipped
+        // by the grid's overflow-x: hidden.
+        const modelCard = element.classList.contains('model-card')
+            ? element
+            : element.querySelector('.model-card');
         if (modelCard) {
             modelCard.style.maxWidth = 'none';
+            modelCard.style.minWidth = '0';
         }
 
         return element;

static/js/utils/constants.js

@@ -333,6 +333,7 @@ export const PATH_TEMPLATE_PLACEHOLDERS = [
 export const DEFAULT_PATH_TEMPLATES = {
     lora: '{base_model}/{first_tag}',
     checkpoint: '{base_model}',
+    unet: '{base_model}',
     embedding: '{first_tag}'
 };
 
@@ -369,21 +370,24 @@ export function getMatureBlurThreshold(settings = {}) {
 export const NODE_TYPES = {
     LORA_LOADER: 1,
     LORA_STACKER: 2,
-    WAN_VIDEO_LORA_SELECT: 3
+    WAN_VIDEO_LORA_SELECT: 3,
+    HOOK_LORA: 4
 };
 
 // Node type names to IDs mapping
 export const NODE_TYPE_NAMES = {
     "Lora Loader (LoraManager)": NODE_TYPES.LORA_LOADER,
     "Lora Stacker (LoraManager)": NODE_TYPES.LORA_STACKER,
-    "WanVideo Lora Select (LoraManager)": NODE_TYPES.WAN_VIDEO_LORA_SELECT
+    "WanVideo Lora Select (LoraManager)": NODE_TYPES.WAN_VIDEO_LORA_SELECT,
+    "Create Hook LoRA (LoraManager)": NODE_TYPES.HOOK_LORA
 };
 
 // Node type icons
 export const NODE_TYPE_ICONS = {
     [NODE_TYPES.LORA_LOADER]: "fas fa-l",
     [NODE_TYPES.LORA_STACKER]: "fas fa-s",
-    [NODE_TYPES.WAN_VIDEO_LORA_SELECT]: "fas fa-w"
+    [NODE_TYPES.WAN_VIDEO_LORA_SELECT]: "fas fa-w",
+    [NODE_TYPES.HOOK_LORA]: "fas fa-h"
 };
 
 // Default ComfyUI node color when bgcolor is null

static/js/utils/infiniteScroll.js

@@ -1,5 +1,6 @@
 import { state, getCurrentPageState } from '../state/index.js';
 import { VirtualScroller } from './VirtualScroller.js';
+import { MasonryScroller } from './MasonryScroller.js';
 import { createModelCard, setupModelCardEventDelegation } from '../components/shared/ModelCard.js';
 import { getModelApiClient } from '../api/modelApiFactory.js';
 import { showToast } from './uiHelpers.js';
@@ -141,8 +142,14 @@ async function initializeVirtualScroll(pageType) {
             throw new Error(`Required components not available for ${pageType} page`);
         }
 
+        // Masonry applies to the recipes page only; the read pattern mirrors
+        // VirtualScroller.js (display_density).
+        const useMasonry = pageType === 'recipes'
+            && (state.global.settings?.recipes_layout ?? 'grid') === 'masonry';
+        const ScrollerClass = useMasonry ? MasonryScroller : VirtualScroller;
+
         // Initialize virtual scroller with renamed container elements
-        state.virtualScroller = new VirtualScroller({
+        state.virtualScroller = new ScrollerClass({
             gridElement: grid,
             containerElement: gridContainer,
             scrollContainer: scrollContainer,
@@ -250,3 +257,19 @@ export async function refreshVirtualScroll(options = {}) {
         }
     }
 }
+
+// Rebuild the virtual scroller from scratch (used for layout switching).
+// refreshVirtualScroll only resets the existing instance, so it cannot swap
+// the scroller class. Keyboard navigation must be cleaned up first:
+// setupKeyboardNavigation appends a new document keydown listener on every
+// initializeVirtualScroll call and never removes the previous one.
+export async function recreateVirtualScroll(pageType) {
+    cleanupKeyboardNavigation();
+
+    if (state.virtualScroller) {
+        state.virtualScroller.dispose();
+        state.virtualScroller = null;
+    }
+
+    await initializeVirtualScroll(pageType);
+}

static/js/utils/uiHelpers.js

@@ -356,6 +356,8 @@ export function updatePanelPositions() {
 
   if (filterPanel) {
     filterPanel.style.top = `${topPosition}px`;
+    // Clamp panel height to the viewport below the header
+    filterPanel.style.maxHeight = `calc(100vh - ${topPosition + 10}px)`;
   }
 
   // Adjust panel horizontal position based on the search container

templates/checkpoints.html

@@ -32,7 +32,12 @@
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Media / Preview -->
     <div class="context-menu-item" data-action="preview"><i class="fas fa-folder-open"></i> {{ t('loras.contextMenu.openExamples') }}</div>
-    <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }}</div>
+    <div class="context-menu-item has-submenu" data-has-submenu="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }} <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadMissingExamples') }}</div>
+            <div class="context-menu-item" data-action="download-examples-force"><i class="fas fa-redo-alt"></i> {{ t('loras.contextMenu.reprocessExamples') }}</div>
+        </div>
+    </div>
     <div class="context-menu-item" data-action="replace-preview"><i class="fas fa-image"></i> {{ t('loras.contextMenu.replacePreview') }}</div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Attributes -->

templates/components/context_menu.html

@@ -44,8 +44,18 @@
     <div class="context-menu-item" data-action="preview">
         <i class="fas fa-folder-open"></i> <span>{{ t('loras.contextMenu.openExamples') }}</span>
     </div>
+    <div class="context-menu-item has-submenu" data-has-submenu="download-examples">
+        <i class="fas fa-download"></i>
+        <span>{{ t('loras.contextMenu.downloadExamples') }}</span>
+        <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
             <div class="context-menu-item" data-action="download-examples">
-        <i class="fas fa-download"></i> <span>{{ t('loras.contextMenu.downloadExamples') }}</span>
+                <i class="fas fa-download"></i> <span>{{ t('loras.contextMenu.downloadMissingExamples') }}</span>
+            </div>
+            <div class="context-menu-item" data-action="download-examples-force">
+                <i class="fas fa-redo-alt"></i> <span>{{ t('loras.contextMenu.reprocessExamples') }}</span>
+            </div>
+        </div>
     </div>
     <div class="context-menu-item" data-action="replace-preview">
         <i class="fas fa-image"></i> <span>{{ t('loras.contextMenu.replacePreview') }}</span>
@@ -136,8 +146,18 @@
     </div>
     <div class="context-menu-section" data-section="download">
         <div class="context-menu-section-header">{{ t('loras.bulkOperations.sections.download') }}</div>
+        <div class="context-menu-item has-submenu" data-has-submenu="download-example-images">
+            <i class="fas fa-download"></i>
+            <span>{{ t('loras.bulkOperations.downloadExamples') }}</span>
+            <i class="fas fa-chevron-right submenu-arrow"></i>
+            <div class="context-submenu">
+                <div class="context-menu-item" data-action="download-missing-example-images">
+                    <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingExamples') }}</span>
+                </div>
                 <div class="context-menu-item" data-action="download-example-images">
-            <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadExamples') }}</span>
+                    <i class="fas fa-redo-alt"></i> <span>{{ t('loras.bulkOperations.reprocessExamples') }}</span>
+                </div>
+            </div>
         </div>
         <div class="context-menu-item" data-action="download-missing-loras">
             <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingLoras') }}</span>

templates/components/controls.html

@@ -48,6 +48,11 @@
                             <option value="versions_count:asc">{{ t('loras.controls.sort.versionsCountAsc', default='Fewest versions first') }}</option>
                         </optgroup>
                     {% endif %}
+                    {% if page_id != 'recipes' %}
+                        <optgroup label="{{ t('loras.controls.sort.random', default='Random') }}">
+                            <option value="random">{{ t('loras.controls.sort.randomAction', default='Randomize (shuffle)') }}</option>
+                        </optgroup>
+                    {% endif %}
                     {% if page_id == 'recipes' %}
                         <optgroup label="{{ t('recipes.controls.sort.lorasCount') }}">
                             <option value="loras_count:desc">{{ t('recipes.controls.sort.lorasCountDesc') }}</option>

templates/components/modals/download_modal.html

@@ -60,7 +60,7 @@
         </div>
 
         <!-- Step 3: Location Selection -->
-        <div class="download-step" id="locationStep" style="display: none;">
+        <div class="download-step" id="downloadLocationStep" style="display: none;">
             <div class="location-selection">
                 <!-- Path preview with inline toggle -->
                 <div class="path-preview">

templates/components/modals/settings_modal.html

@@ -202,6 +202,7 @@
                                             <option value="deepseek">{{ t('settings.aiProvider.providerOptions.deepseek') }}</option>
                                             <option value="groq">{{ t('settings.aiProvider.providerOptions.groq') }}</option>
                                             <option value="openrouter">{{ t('settings.aiProvider.providerOptions.openrouter') }}</option>
+                                            <option value="google">{{ t('settings.aiProvider.providerOptions.google') }}</option>
                                             <option value="opencode-go">{{ t('settings.aiProvider.providerOptions.opencode-go') }}</option>
                                             <option value="custom">{{ t('settings.aiProvider.providerOptions.custom') }}</option>
                                         </select>
@@ -625,6 +626,23 @@
                                 </div>
                             </div>
 
+                            <div class="setting-item">
+                                <div class="setting-row">
+                                    <div class="setting-info">
+                                        <label for="recipesLayout">
+                                        {{ t('settings.layoutSettings.recipesLayout') }}
+                                        <i class="fas fa-info-circle info-icon" data-tooltip="{{ t('settings.layoutSettings.recipesLayoutHelp') }}"></i>
+                                    </label>
+                                    </div>
+                                    <div class="setting-control select-control">
+                                        <select id="recipesLayout" onchange="settingsManager.saveSelectSetting('recipesLayout', 'recipes_layout')">
+                                            <option value="grid">{{ t('settings.layoutSettings.recipesLayoutOptions.grid') }}</option>
+                                            <option value="masonry">{{ t('settings.layoutSettings.recipesLayoutOptions.masonry') }}</option>
+                                        </select>
+                                    </div>
+                                </div>
+                            </div>
+
                             <div class="setting-item">
                                 <div class="setting-row">
                                     <div class="setting-info">

templates/components/modals/update_modal.html

@@ -19,6 +19,20 @@
         <div class="notification-panels">
             <div class="notification-panel active" id="updatesPanel" role="tabpanel" aria-labelledby="updatesTab" aria-hidden="false" tabindex="0" data-notification-panel="updates">
                 <div class="update-content">
+
+                    <!-- Channel Selector -->
+                    <div class="update-channels" id="updateChannels">
+                        <div class="channels-label">{{ t('update.channel') }}</div>
+                        <div class="channel-toggle">
+                            <button type="button" class="channel-btn" data-channel="release" id="channelRelease">
+                                <i class="fas fa-tag"></i> {{ t('update.channels.release') }}
+                            </button>
+                            <button type="button" class="channel-btn" data-channel="nightly" id="channelNightly">
+                                <i class="fas fa-moon"></i> {{ t('update.channels.nightly') }}
+                            </button>
+                        </div>
+                    </div>
+
                     <div class="update-info">
                         <div class="version-info">
                             <div class="current-version">

templates/embeddings.html

@@ -32,7 +32,12 @@
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Media / Preview -->
     <div class="context-menu-item" data-action="preview"><i class="fas fa-folder-open"></i> {{ t('loras.contextMenu.openExamples') }}</div>
-    <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }}</div>
+    <div class="context-menu-item has-submenu" data-has-submenu="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }} <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadMissingExamples') }}</div>
+            <div class="context-menu-item" data-action="download-examples-force"><i class="fas fa-redo-alt"></i> {{ t('loras.contextMenu.reprocessExamples') }}</div>
+        </div>
+    </div>
     <div class="context-menu-item" data-action="replace-preview"><i class="fas fa-image"></i> {{ t('loras.contextMenu.replacePreview') }}</div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Attributes -->

tests/conftest.py

@@ -85,6 +85,7 @@ sys.modules['comfy.utils'] = comfy_mock.utils
 sys.modules['comfy.sd'] = comfy_mock.sd
 sys.modules['comfy.model_management'] = comfy_mock.model_management
 sys.modules['comfy.comfy_types'] = comfy_mock.comfy_types
+sys.modules['comfy.hooks'] = MockModule("comfy.hooks")
 
 execution_mock = MockModule("execution")
 execution_mock.PromptExecutor = mock.MagicMock()

tests/frontend/api/recipeApi.bulk.test.js

@@ -38,6 +38,7 @@ vi.mock('../../../static/js/state/index.js', () => {
 vi.mock('../../../static/js/utils/infiniteScroll.js', () => ({
   captureScrollPosition: captureScrollPositionMock,
   restoreScrollPosition: restoreScrollPositionMock,
+  recreateVirtualScroll: vi.fn(),
 }));
 
 import {

tests/frontend/components/autocomplete.behavior.test.js

@@ -1666,4 +1666,374 @@ describe('AutoComplete widget interactions', () => {
     // Entire phrase should be replaced with selected tag
     expect(input.value).toBe('looking_to_the_side,');
   });
+
+  it('shows /af command for loras when active-filters autocomplete is off (default)', async () => {
+    const input = document.createElement('textarea');
+    input.value = '/';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input, 'loras', { showPreview: false, minChars: 1 });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    const commandNames = autoComplete.items.map((item) => item.command);
+    expect(commandNames).toContain('/af');
+    expect(commandNames).not.toContain('/noaf');
+    expect(commandNames).toContain('/activefilters');
+    expect(commandNames).not.toContain('/noactivefilters');
+  });
+
+  it('does not trigger preview for command items when selecting the loras command list', async () => {
+    // Regression: with showPreview enabled (the default for loras widgets), the
+    // auto-selected first command item was passed to showPreviewForItem() as a
+    // relative path, crashing on relativePath.split.
+    const input = document.createElement('textarea');
+    input.value = '/';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input, 'loras', { showPreview: true, minChars: 1 });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    // Allow the async preview tooltip import to resolve
+    await Promise.resolve();
+    await Promise.resolve();
+
+    const commandNames = autoComplete.items.map((item) => item.command);
+    expect(commandNames).toContain('/af');
+    expect(previewTooltipMock.show).not.toHaveBeenCalled();
+  });
+
+  it('shows /noaf command for loras when active-filters autocomplete is on', async () => {
+    settingGetMock.mockImplementation((key) => {
+      if (key === 'loramanager.lora_active_filters_autocomplete') {
+        return true;
+      }
+      return undefined;
+    });
+
+    const input = document.createElement('textarea');
+    input.value = '/';
+    input.selectionStart = input.value.length;
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input, 'loras', { showPreview: false, minChars: 1 });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    const commandNames = autoComplete.items.map((item) => item.command);
+    expect(commandNames).toContain('/noaf');
+    expect(commandNames).not.toContain('/af');
+    expect(commandNames).toContain('/noactivefilters');
+    expect(commandNames).not.toContain('/activefilters');
+  });
+
+  it('toggles the active-filters setting when /activefilters alias is used', async () => {
+    const input = document.createElement('textarea');
+    input.value = '/activefilters';
+    input.selectionStart = input.value.length;
+    input.focus = vi.fn();
+    input.setSelectionRange = vi.fn();
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/activefilters');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input, 'loras', { showPreview: false, minChars: 1 });
+
+    const commandResult = autoComplete._parseCommandInput('/activefilters');
+    expect(commandResult.command).toBeDefined();
+    expect(commandResult.command.type).toBe('toggle_setting');
+    expect(commandResult.command.value).toBe(true);
+
+    await autoComplete._handleToggleSettingCommand(commandResult.command);
+
+    expect(settingSetMock).toHaveBeenCalledWith('loramanager.lora_active_filters_autocomplete', true);
+  });
+
+  it('toggles the active-filters setting when /af is accepted', async () => {
+    const input = document.createElement('textarea');
+    input.value = '/';
+    input.selectionStart = input.value.length;
+    input.focus = vi.fn();
+    input.setSelectionRange = vi.fn();
+    document.body.append(input);
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('/');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    const autoComplete = new AutoComplete(input, 'loras', { showPreview: false, minChars: 1 });
+
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    const afItem = autoComplete.items.find((item) => item.command === '/af');
+    expect(afItem).toBeDefined();
+
+    // Simulate the input being cleared after the command is accepted so the
+    // cleared-token input event does not re-trigger command parsing.
+    caretHelperInstance.getBeforeCursor.mockReturnValue('');
+    await autoComplete._handleToggleSettingCommand(afItem);
+
+    expect(settingSetMock).toHaveBeenCalledWith('loramanager.lora_active_filters_autocomplete', true);
+  });
+
+  it('appends active filter params to loras autocomplete requests when enabled', async () => {
+    vi.useFakeTimers();
+
+    settingGetMock.mockImplementation((key) => {
+      if (key === 'loramanager.lora_active_filters_autocomplete') {
+        return true;
+      }
+      return undefined;
+    });
+
+    localStorage.setItem('lora_manager_loras_filters', JSON.stringify({
+      baseModel: ['SD 1.5'],
+      tags: { anime: 'include', nsfw: 'exclude', __no_tags__: 'exclude' },
+      autoTags: { I2V: 'include' },
+      modelTypes: ['standard'],
+      tagLogic: 'all',
+      license: { noCredit: 'include', allowSelling: 'exclude' },
+    }));
+    localStorage.setItem('lora_manager_loras_activeFolder', 'MyLoras');
+    localStorage.setItem('lora_manager_loras_recursiveSearch', 'true');
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, relative_paths: ['models/example.safetensors'] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('example');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'loras', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = 'example';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    const calledUrl = fetchApiMock.mock.calls[0][0];
+    expect(calledUrl).toContain('/lm/loras/relative-paths?search=example&limit=100');
+    expect(calledUrl).toContain('folder=MyLoras');
+    expect(calledUrl).toContain('recursive=true');
+    expect(calledUrl).toContain('tag_include=anime');
+    expect(calledUrl).toContain('tag_exclude=nsfw');
+    expect(calledUrl).toContain('tag_exclude=__no_tags__');
+    expect(calledUrl).toContain('auto_tag_include=I2V');
+    expect(calledUrl).toContain('tag_logic=all');
+    expect(calledUrl).toContain('credit_required=false');
+    expect(calledUrl).toContain('allow_selling_generated_content=false');
+    const parsed = new URL(calledUrl, 'https://example.com');
+    expect(parsed.searchParams.get('base_model')).toBe('SD 1.5');
+    expect(parsed.searchParams.get('model_type')).toBe('standard');
+  });
+
+  it('keeps the default loras autocomplete URL when active-filters mode is off', async () => {
+    vi.useFakeTimers();
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, relative_paths: ['models/example.safetensors'] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('example');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'loras', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = 'example';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    expect(fetchApiMock).toHaveBeenCalledWith('/lm/loras/relative-paths?search=example&limit=100');
+  });
+
+  it('sends the filter-pipeline signal even when no filters are stored', async () => {
+    // Regression: with filter mode on but no folder/filters stored, the request
+    // carried no params, so the backend skipped the filter pipeline and global
+    // settings like show_only_sfw diverged from the list endpoint.
+    vi.useFakeTimers();
+
+    settingGetMock.mockImplementation((key) => {
+      if (key === 'loramanager.lora_active_filters_autocomplete') {
+        return true;
+      }
+      return undefined;
+    });
+
+    localStorage.removeItem('lora_manager_loras_filters');
+    localStorage.removeItem('lora_manager_loras_activeFolder');
+    localStorage.removeItem('lora_manager_loras_recursiveSearch');
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, relative_paths: ['models/example.safetensors'] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('example');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'loras', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = 'example';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    const calledUrl = fetchApiMock.mock.calls[0][0];
+    expect(calledUrl).toContain('recursive=true');
+  });
+
+  it('omits folder param when active folder is root and recursion is enabled', async () => {
+    vi.useFakeTimers();
+
+    settingGetMock.mockImplementation((key) => {
+      if (key === 'loramanager.lora_active_filters_autocomplete') {
+        return true;
+      }
+      return undefined;
+    });
+
+    localStorage.setItem('lora_manager_loras_filters', JSON.stringify({
+      baseModel: ['SD 1.5'],
+      tags: { anime: 'include' },
+    }));
+    localStorage.setItem('lora_manager_loras_activeFolder', '');
+    localStorage.removeItem('lora_manager_loras_recursiveSearch');
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, relative_paths: ['models/example.safetensors'] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('example');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'loras', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = 'example';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    const calledUrl = fetchApiMock.mock.calls[0][0];
+    expect(calledUrl).not.toContain('folder=');
+    expect(calledUrl).toContain('recursive=true');
+  });
+
+  it('sends an empty folder param for root with recursion disabled, mirroring the page list', async () => {
+    vi.useFakeTimers();
+
+    settingGetMock.mockImplementation((key) => {
+      if (key === 'loramanager.lora_active_filters_autocomplete') {
+        return true;
+      }
+      return undefined;
+    });
+
+    localStorage.setItem('lora_manager_loras_filters', JSON.stringify({
+      baseModel: ['SD 1.5'],
+      tags: { anime: 'include' },
+    }));
+    localStorage.setItem('lora_manager_loras_activeFolder', '');
+    localStorage.setItem('lora_manager_loras_recursiveSearch', 'false');
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, relative_paths: ['models/example.safetensors'] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('example');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'loras', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = 'example';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    const calledUrl = fetchApiMock.mock.calls[0][0];
+    expect(calledUrl).toContain('folder=');
+    expect(calledUrl).toContain('recursive=false');
+    const parsed = new URL(calledUrl, 'https://example.com');
+    expect(parsed.searchParams.get('folder')).toBe('');
+  });
+
+  it('applies the active folder even when no filter-panel filters are set', async () => {
+    // Regression: folder was skipped when lora_manager_loras_filters was
+    // missing because the filters key gate returned early.
+    vi.useFakeTimers();
+
+    settingGetMock.mockImplementation((key) => {
+      if (key === 'loramanager.lora_active_filters_autocomplete') {
+        return true;
+      }
+      return undefined;
+    });
+
+    localStorage.removeItem('lora_manager_loras_filters');
+    localStorage.setItem('lora_manager_loras_activeFolder', 'Flux.1 D/style');
+
+    fetchApiMock.mockResolvedValue({
+      json: () => Promise.resolve({ success: true, relative_paths: ['Flux.1 D/style/3D_Fairytales.safetensors'] }),
+    });
+
+    caretHelperInstance.getBeforeCursor.mockReturnValue('3D');
+    caretHelperInstance.getCursorOffset.mockReturnValue({ left: 15, top: 25 });
+
+    const input = document.createElement('textarea');
+    document.body.append(input);
+
+    const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
+    new AutoComplete(input, 'loras', { debounceDelay: 0, showPreview: false, minChars: 1 });
+
+    input.value = '3D';
+    input.dispatchEvent(new Event('input', { bubbles: true }));
+
+    await vi.runAllTimersAsync();
+    await Promise.resolve();
+
+    const calledUrl = fetchApiMock.mock.calls[0][0];
+    expect(calledUrl).toContain('folder=Flux.1+D%2Fstyle');
+    expect(calledUrl).toContain('recursive=true');
+  });
 });

tests/frontend/components/contextMenu.interactions.test.js

@@ -2155,4 +2155,35 @@ describe('Interaction-level regression coverage', () => {
     excludedItem.dispatchEvent(new Event('click', { bubbles: true }));
     expect(window.pageControls.enterExcludedView).toHaveBeenCalledTimes(1);
   });
+
+  it('routes single-model example downloads to missing-only and force paths', async () => {
+    document.body.innerHTML = `
+      <div id="loraContextMenu" class="context-menu">
+        <div class="context-menu-item has-submenu" data-has-submenu="download-examples">
+          <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples"></div>
+            <div class="context-menu-item" data-action="download-examples-force"></div>
+          </div>
+        </div>
+      </div>
+    `;
+
+    const { LoraContextMenu } = await import('../../../static/js/components/ContextMenu/LoraContextMenu.js');
+    const contextMenu = new LoraContextMenu();
+
+    const card = document.createElement('div');
+    card.className = 'model-card';
+    card.dataset.filepath = '/models/test.safetensors';
+    card.dataset.sha256 = 'abc123hash';
+    document.body.appendChild(card);
+
+    contextMenu.showMenu(100, 100, card);
+
+    document.querySelector('[data-action="download-examples"]').dispatchEvent(new Event('click', { bubbles: true }));
+    expect(downloadExampleImagesApiMock).toHaveBeenCalledWith(['abc123hash'], null, { force: false });
+
+    contextMenu.showMenu(100, 100, card);
+    document.querySelector('[data-action="download-examples-force"]').dispatchEvent(new Event('click', { bubbles: true }));
+    expect(downloadExampleImagesApiMock).toHaveBeenCalledWith(['abc123hash'], null, { force: true });
+  });
 });