chore(release): bump version to v1.2.1

feat(recipes): add toolbar toggle and settings preview for masonry layout
feat(metadata): collect generation params from Krea two/three stage samplers
2026-09-22 11:34:08 -03:00 · 2026-08-16 19:47:15 +08:00 · 2026-08-16 15:23:30 +08:00 · 2026-08-16 09:53:08 +08:00 · 2026-08-16 09:17:59 +08:00 · 2026-08-15 22:03:54 +08:00
82 changed files with 6488 additions and 747 deletions
@@ -3,6 +3,8 @@ try:  # pragma: no cover - import fallback for pytest collection
    from .py.nodes.lora_loader import LoraLoaderLM, LoraTextLoaderLM
    from .py.nodes.checkpoint_loader import CheckpointLoaderLM
    from .py.nodes.unet_loader import UNETLoaderLM
+    from .py.nodes.random_checkpoint_loader import RandomCheckpointLoaderLM
+    from .py.nodes.random_unet_loader import RandomUNETLoaderLM
    from .py.nodes.trigger_word_toggle import TriggerWordToggleLM
    from .py.nodes.prompt import PromptLM
    from .py.nodes.text import TextLM
@@ -40,6 +42,12 @@ except (
        "py.nodes.checkpoint_loader"
    ).CheckpointLoaderLM
    UNETLoaderLM = importlib.import_module("py.nodes.unet_loader").UNETLoaderLM
+    RandomCheckpointLoaderLM = importlib.import_module(
+        "py.nodes.random_checkpoint_loader"
+    ).RandomCheckpointLoaderLM
+    RandomUNETLoaderLM = importlib.import_module(
+        "py.nodes.random_unet_loader"
+    ).RandomUNETLoaderLM
    TriggerWordToggleLM = importlib.import_module(
        "py.nodes.trigger_word_toggle"
    ).TriggerWordToggleLM
@@ -79,6 +87,8 @@ NODE_CLASS_MAPPINGS = {
    LoraTextLoaderLM.NAME: LoraTextLoaderLM,
    CheckpointLoaderLM.NAME: CheckpointLoaderLM,
    UNETLoaderLM.NAME: UNETLoaderLM,
+    RandomCheckpointLoaderLM.NAME: RandomCheckpointLoaderLM,
+    RandomUNETLoaderLM.NAME: RandomUNETLoaderLM,
    TriggerWordToggleLM.NAME: TriggerWordToggleLM,
    LoraStackerLM.NAME: LoraStackerLM,
    LoraStackCombinerLM.NAME: LoraStackCombinerLM,
@@ -622,6 +622,10 @@
            "label": "Früher Zugriff Updates ausblenden",
            "help": "Nur Early-Access-Updates"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "Aktualisierte Lizenzsymbole verwenden",
            "useNewStyleHelp": "Lizenzberechtigungen mit farbigen Indikatoren (neuer Stil) oder nur Einschränkungssymbolen (klassischer Stil) anzeigen. Orientiert sich am aktuellen CivitAI-Design."
@@ -920,7 +924,9 @@
                "dateAsc": "Älteste",
                "lorasCount": "LoRA-Anzahl",
                "lorasCountDesc": "Meiste",
-                "lorasCountAsc": "Wenigste"
+                "lorasCountAsc": "Wenigste",
+                "opened": "Zuletzt geöffnet",
+                "openedDesc": "Zuletzt geöffnet"
            },
            "refresh": {
                "title": "Rezeptliste aktualisieren",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "Nur Favoriten anzeigen",
                "action": "Favoriten"
+            },
+            "layout": {
+                "title": "Rezepte-Layout",
+                "grid": "Raster-Layout",
+                "masonry": "Masonry-Layout (Pinterest-Stil, behält das Seitenverhältnis des Bildes bei)"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "Gibt {size} frei",
            "title": "Modell löschen",
            "message": "Sind Sie sicher, dass Sie dieses Modell und alle zugehörigen Dateien löschen möchten?",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "Die Datei wird nach 20 Sekunden endgültig gelöscht, sofern Sie nicht rückgängig machen."
        },
        "deleteRecipe": {
-            "recoverableWarning": "Diese Aktion kann 30 Sekunden lang rückgängig gemacht werden."
+            "recoverableWarning": "Diese Aktion kann 20 Sekunden lang rückgängig gemacht werden."
        },
        "excludeModel": {
            "title": "Modell ausschließen",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "Diese Version ist neuer als Ihre neueste lokale Version",
                    "earlyAccess": "Früher Zugriff",
                    "earlyAccessTooltip": "Für diese Version ist derzeit Civitai Early Access erforderlich",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "Ignoriert",
                    "ignoredTooltip": "Für diese Version sind Update-Benachrichtigungen deaktiviert",
                    "onSiteOnly": "Nur On-Site",
@@ -1557,6 +1570,7 @@
                    "download": "Herunterladen",
                    "downloadTooltip": "Diese Version herunterladen",
                    "downloadEarlyAccessTooltip": "Diese Early-Access-Version von Civitai herunterladen",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "Diese Version ist nur für die On-Site-Generierung auf Civitai verfügbar",
                    "delete": "Löschen",
                    "deleteTooltip": "Diese lokale Version löschen",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "Rezept im Workflow ersetzt",
            "recipeFailedToSend": "Fehler beim Senden des Rezepts an den Workflow",
            "noMatchingNodes": "Keine kompatiblen Knoten im aktuellen Workflow verfügbar",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "Kein Zielknoten ausgewählt",
            "modelUpdated": "Modell im Workflow aktualisiert",
            "modelFailed": "Fehler beim Aktualisieren des Modellknotens",
@@ -2119,12 +2134,12 @@
            "copyFailed": "Kopieren fehlgeschlagen"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "Rückgängig",
+            "deleted": "Gelöscht: {name}",
+            "deletedBulk": "{count} Element(e) gelöscht",
+            "expired": "Undo-Fenster abgelaufen. Das Element wurde endgültig gelöscht.",
+            "failed": "Rückgängig machen fehlgeschlagen: {error}",
+            "restored": "Element wiederhergestellt"
        },
        "virtual": {
            "loadFailed": "Fehler beim Laden der Elemente",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "Fehler beim Umbenennen der Datei: {error}",
            "previewUpdated": "Vorschau erfolgreich aktualisiert",
            "previewUploadFailed": "Fehler beim Hochladen des Vorschaubilds",
+            "previewDropInvalid": "Nicht unterstützter Dateityp: {name}. Ziehen Sie stattdessen ein Bild oder ein MP4-Video hinein.",
            "refreshComplete": "{action} abgeschlossen",
            "refreshFailed": "Fehler beim {action} der {type}s",
            "metadataRefreshed": "Metadaten erfolgreich aktualisiert",
@@ -622,6 +622,10 @@
      "label": "Hide Early Access Updates",
      "help": "When enabled, models with only early access updates will not show 'Update available' badge"
    },
+    "hidePaidUpdates": {
+      "label": "Hide Paid Updates",
+      "help": "When enabled, models with only paid updates will not show 'Update available' badge"
+    },
    "licenseIcons": {
      "useNewStyle": "Use updated license icons",
      "useNewStyleHelp": "Display license permissions with colored indicators (new style) or restriction-only icons (classic style). Mirroring the current CivitAI design."
@@ -920,7 +924,9 @@
        "dateAsc": "Oldest",
        "lorasCount": "LoRA Count",
        "lorasCountDesc": "Most",
-        "lorasCountAsc": "Least"
+        "lorasCountAsc": "Least",
+        "opened": "Recently Opened",
+        "openedDesc": "Recently opened"
      },
      "refresh": {
        "title": "Refresh recipe list",
@@ -931,6 +937,11 @@
      "favorites": {
        "title": "Show Favorites Only",
        "action": "Favorites"
+      },
+      "layout": {
+        "title": "Recipes Layout",
+        "grid": "Grid layout",
+        "masonry": "Masonry layout (Pinterest-style, preserves image aspect ratio)"
      }
    },
    "duplicates": {
@@ -1280,10 +1291,10 @@
      "freesSpace": "Frees {size}",
      "title": "Delete Model",
      "message": "Are you sure you want to delete this model and all associated files?",
-      "recoverableWarning": "This will permanently delete the file after 30 seconds unless you undo."
+      "recoverableWarning": "This will permanently delete the file after 20 seconds unless you undo."
    },
    "deleteRecipe": {
-      "recoverableWarning": "This action can be undone for 30 seconds."
+      "recoverableWarning": "This action can be undone for 20 seconds."
    },
    "excludeModel": {
      "title": "Exclude Model",
@@ -1548,6 +1559,8 @@
          "newerTooltip": "This version is newer than your latest local version",
          "earlyAccess": "Early Access",
          "earlyAccessTooltip": "This version currently requires Civitai early access",
+          "paid": "Paid",
+          "paidTooltip": "This version requires payment to download",
          "ignored": "Ignored",
          "ignoredTooltip": "Update notifications are disabled for this version",
          "onSiteOnly": "On-Site Only",
@@ -1557,6 +1570,7 @@
          "download": "Download",
          "downloadTooltip": "Download this version",
          "downloadEarlyAccessTooltip": "Download this early access version from Civitai",
+          "downloadPaidTooltip": "Download this paid version from Civitai",
          "downloadNotAllowedTooltip": "This version is only available for on-site generation on Civitai",
          "delete": "Delete",
          "deleteTooltip": "Delete this local version",
@@ -1726,6 +1740,7 @@
      "recipeReplaced": "Recipe replaced in workflow",
      "recipeFailedToSend": "Failed to send recipe to workflow",
      "noMatchingNodes": "No compatible nodes available in the current workflow",
+      "noPromptTargets": "No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
      "noTargetNodeSelected": "No target node selected",
      "modelUpdated": "Model updated in workflow",
      "modelFailed": "Failed to update model node",
@@ -2189,6 +2204,7 @@
      "fileRenameFailed": "Failed to rename file: {error}",
      "previewUpdated": "Preview updated successfully",
      "previewUploadFailed": "Failed to upload preview image",
+      "previewDropInvalid": "Unsupported file type: {name}. Drop an image or MP4 video instead.",
      "refreshComplete": "{action} complete",
      "refreshFailed": "Failed to {action} {type}s",
      "metadataRefreshed": "Metadata refreshed successfully",
@@ -622,6 +622,10 @@
            "label": "Ocultar actualizaciones de acceso temprano",
            "help": "Solo actualizaciones de acceso temprano"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "Usar iconos de licencia actualizados",
            "useNewStyleHelp": "Mostrar permisos de licencia con indicadores de color (nuevo estilo) o solo iconos de restricción (estilo clásico). Refleja el diseño actual de CivitAI."
@@ -920,7 +924,9 @@
                "dateAsc": "Más antiguo",
                "lorasCount": "Cant. de LoRAs",
                "lorasCountDesc": "Más",
-                "lorasCountAsc": "Menos"
+                "lorasCountAsc": "Menos",
+                "opened": "Abiertos recientemente",
+                "openedDesc": "Abiertos recientemente"
            },
            "refresh": {
                "title": "Actualizar lista de recetas",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "Mostrar solo favoritos",
                "action": "Favoritos"
+            },
+            "layout": {
+                "title": "Diseño de recetas",
+                "grid": "Vista de cuadrícula",
+                "masonry": "Vista masonry (estilo Pinterest, conserva la proporción de aspecto de la imagen)"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "Libera {size}",
            "title": "Eliminar modelo",
            "message": "¿Estás seguro de que quieres eliminar este modelo y todos los archivos asociados?",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "El archivo se eliminará permanentemente después de 20 segundos a menos que deshaga la acción."
        },
        "deleteRecipe": {
-            "recoverableWarning": "Esta acción se puede deshacer durante 30 segundos."
+            "recoverableWarning": "Esta acción se puede deshacer durante 20 segundos."
        },
        "excludeModel": {
            "title": "Excluir modelo",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "Esta versión es más reciente que tu última versión local",
                    "earlyAccess": "Acceso temprano",
                    "earlyAccessTooltip": "Esta versión requiere actualmente acceso temprano de Civitai",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "Ignorada",
                    "ignoredTooltip": "Las notificaciones de actualización están desactivadas para esta versión",
                    "onSiteOnly": "Solo en Sitio",
@@ -1557,6 +1570,7 @@
                    "download": "Descargar",
                    "downloadTooltip": "Descargar esta versión",
                    "downloadEarlyAccessTooltip": "Descargar esta versión de acceso temprano desde Civitai",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "Esta versión solo está disponible para generación en el sitio de Civitai",
                    "delete": "Eliminar",
                    "deleteTooltip": "Eliminar esta versión local",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "Receta reemplazada en el flujo de trabajo",
            "recipeFailedToSend": "Error al enviar receta al flujo de trabajo",
            "noMatchingNodes": "No hay nodos compatibles disponibles en el flujo de trabajo actual",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "No se ha seleccionado ningún nodo de destino",
            "modelUpdated": "Modelo actualizado en el flujo de trabajo",
            "modelFailed": "Error al actualizar nodo de modelo",
@@ -2119,12 +2134,12 @@
            "copyFailed": "Error al copiar"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "Deshacer",
+            "deleted": "Eliminado: {name}",
+            "deletedBulk": "{count} elemento(s) eliminado(s)",
+            "expired": "La ventana de deshacer ha caducado. El elemento se eliminó permanentemente.",
+            "failed": "No se pudo deshacer: {error}",
+            "restored": "Elemento restaurado"
        },
        "virtual": {
            "loadFailed": "Error al cargar elementos",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "Error al renombrar archivo: {error}",
            "previewUpdated": "Vista previa actualizada exitosamente",
            "previewUploadFailed": "Error al subir imagen de vista previa",
+            "previewDropInvalid": "Tipo de archivo no admitido: {name}. Arrastra una imagen o un video MP4 en su lugar.",
            "refreshComplete": "{action} completada",
            "refreshFailed": "Error al {action} {type}s",
            "metadataRefreshed": "Metadatos actualizados exitosamente",
@@ -622,6 +622,10 @@
            "label": "Masquer les mises à jour en accès anticipé",
            "help": "Seulement les mises à jour en accès anticipé"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "Utiliser les icônes de licence mises à jour",
            "useNewStyleHelp": "Afficher les permissions de licence avec des indicateurs colorés (nouveau style) ou des icônes de restriction uniquement (style classique). Reprend le design actuel de CivitAI."
@@ -920,7 +924,9 @@
                "dateAsc": "Plus ancien",
                "lorasCount": "Nombre de LoRAs",
                "lorasCountDesc": "Plus",
-                "lorasCountAsc": "Moins"
+                "lorasCountAsc": "Moins",
+                "opened": "Récemment ouverts",
+                "openedDesc": "Récemment ouverts"
            },
            "refresh": {
                "title": "Actualiser la liste des recipes",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "Afficher uniquement les favoris",
                "action": "Favoris"
+            },
+            "layout": {
+                "title": "Disposition des recettes",
+                "grid": "Disposition en grille",
+                "masonry": "Disposition masonry (style Pinterest, préserve le rapport d'aspect de l'image)"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "Libère {size}",
            "title": "Supprimer le modèle",
            "message": "Êtes-vous sûr de vouloir supprimer ce modèle et tous les fichiers associés ?",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "Le fichier sera définitivement supprimé après 20 secondes, sauf si vous annulez."
        },
        "deleteRecipe": {
-            "recoverableWarning": "Cette action peut être annulée pendant 30 secondes."
+            "recoverableWarning": "Cette action peut être annulée pendant 20 secondes."
        },
        "excludeModel": {
            "title": "Exclure le modèle",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "Cette version est plus récente que votre dernière version locale",
                    "earlyAccess": "Accès anticipé",
                    "earlyAccessTooltip": "Cette version nécessite actuellement l'accès anticipé Civitai",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "Ignorée",
                    "ignoredTooltip": "Les notifications de mise à jour sont désactivées pour cette version",
                    "onSiteOnly": "Uniquement sur Site",
@@ -1557,6 +1570,7 @@
                    "download": "Télécharger",
                    "downloadTooltip": "Télécharger cette version",
                    "downloadEarlyAccessTooltip": "Télécharger cette version en accès anticipé depuis Civitai",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "Cette version n'est disponible que pour la génération sur le site Civitai",
                    "delete": "Supprimer",
                    "deleteTooltip": "Supprimer cette version locale",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "Recipe remplacée dans le workflow",
            "recipeFailedToSend": "Échec de l'envoi de la recipe au workflow",
            "noMatchingNodes": "Aucun nœud compatible disponible dans le workflow actuel",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "Aucun nœud cible sélectionné",
            "modelUpdated": "Modèle mis à jour dans le workflow",
            "modelFailed": "Échec de la mise à jour du nœud modèle",
@@ -2119,12 +2134,12 @@
            "copyFailed": "Échec de la copie"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "Annuler",
+            "deleted": "Supprimé : {name}",
+            "deletedBulk": "{count} élément(s) supprimé(s)",
+            "expired": "La fenêtre d'annulation a expiré. L'élément a été définitivement supprimé.",
+            "failed": "Échec de l'annulation : {error}",
+            "restored": "Élément restauré"
        },
        "virtual": {
            "loadFailed": "Échec du chargement des éléments",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "Échec du renommage du fichier : {error}",
            "previewUpdated": "Aperçu mis à jour avec succès",
            "previewUploadFailed": "Échec du téléchargement de l'image d'aperçu",
+            "previewDropInvalid": "Type de fichier non pris en charge : {name}. Déposez plutôt une image ou une vidéo MP4.",
            "refreshComplete": "{action} terminé",
            "refreshFailed": "Échec de {action} des {type}s",
            "metadataRefreshed": "Métadonnées actualisées avec succès",
@@ -622,6 +622,10 @@
            "label": "הסתר עדכוני גישה מוקדמת",
            "help": "רק עדכוני גישה מוקדמת"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "השתמש בסמלי רישיון מעודכנים",
            "useNewStyleHelp": "הצג הרשאות רישיון עם מחוונים צבעוניים (סגנון חדש) או סמלי הגבלה בלבד (סגנון קלאסי). משקף את העיצוב העדכני של CivitAI."
@@ -920,7 +924,9 @@
                "dateAsc": "הכי ישן",
                "lorasCount": "מספר LoRAs",
                "lorasCountDesc": "הכי הרבה",
-                "lorasCountAsc": "הכי פחות"
+                "lorasCountAsc": "הכי פחות",
+                "opened": "נפתחו לאחרונה",
+                "openedDesc": "נפתחו לאחרונה"
            },
            "refresh": {
                "title": "רענן רשימת מתכונים",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "הצג מועדפים בלבד",
                "action": "מועדפים"
+            },
+            "layout": {
+                "title": "פריסת מתכונים",
+                "grid": "פריסת רשת",
+                "masonry": "פריסת Masonry (בסגנון Pinterest, שומרת על יחס הגובה-רוחב של התמונה)"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "מפנה {size}",
            "title": "מחק מודל",
            "message": "האם אתה בטוח שברצונך למחוק מודל זה וכל הקבצים הנלווים?",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "הקובץ יימחק לצמיתות לאחר 20 שניות, אלא אם תבטלו את הפעולה."
        },
        "deleteRecipe": {
-            "recoverableWarning": "ניתן לבטל פעולה זו תוך 30 שניות."
+            "recoverableWarning": "ניתן לבטל פעולה זו תוך 20 שניות."
        },
        "excludeModel": {
            "title": "החרג מודל",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "גרסה זו חדשה יותר מהגרסה המקומית האחרונה שלך",
                    "earlyAccess": "גישה מוקדמת",
                    "earlyAccessTooltip": "גרסה זו דורשת כרגע גישת Early Access של Civitai",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "התעלם",
                    "ignoredTooltip": "התראות העדכון מושבתות עבור גרסה זו",
                    "onSiteOnly": "רק באתר",
@@ -1557,6 +1570,7 @@
                    "download": "הורדה",
                    "downloadTooltip": "הורד את הגרסה הזו",
                    "downloadEarlyAccessTooltip": "הורד את גרסת ה-Early Access הזו מ-Civitai",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "גרסה זו זמינה רק ליצירה באתר Civitai",
                    "delete": "מחיקה",
                    "deleteTooltip": "מחק את הגרסה המקומית הזו",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "מתכון הוחלף ב-workflow",
            "recipeFailedToSend": "שליחת מתכון ל-workflow נכשלה",
            "noMatchingNodes": "אין צמתים תואמים זמינים ב-workflow הנוכחי",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "לא נבחר צומת יעד",
            "modelUpdated": "מודל עודכן ב-workflow",
            "modelFailed": "עדכון צומת המודל נכשל",
@@ -2119,12 +2134,12 @@
            "copyFailed": "ההעתקה נכשלה"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "בטל",
+            "deleted": "נמחק: {name}",
+            "deletedBulk": "{count} פריטים נמחקו",
+            "expired": "חלון הביטול פג. הפריט נמחק לצמיתות.",
+            "failed": "הביטול נכשל: {error}",
+            "restored": "הפריט שוחזר"
        },
        "virtual": {
            "loadFailed": "טעינת הפריטים נכשלה",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "שינוי שם הקובץ נכשל: {error}",
            "previewUpdated": "התצוגה המקדימה עודכנה בהצלחה",
            "previewUploadFailed": "העלאת תמונת התצוגה המקדימה נכשלה",
+            "previewDropInvalid": "סוג קובץ לא נתמך: {name}. גרור במקום זאת תמונה או סרטון MP4.",
            "refreshComplete": "{action} הושלם",
            "refreshFailed": "{action} של {type}s נכשל",
            "metadataRefreshed": "המטא-דאטה רועננה בהצלחה",
@@ -622,6 +622,10 @@
            "label": "早期アクセス更新を非表示",
            "help": "早期アクセスのみの更新"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "更新されたライセンスアイコンを使用",
            "useNewStyleHelp": "カラーインジケーター付きでライセンス許可を表示（新スタイル）するか、制限のみのアイコンを表示（クラシックスタイル）します。現在のCivitAIデザインを反映しています。"
@@ -920,7 +924,9 @@
                "dateAsc": "古い順",
                "lorasCount": "LoRA数",
                "lorasCountDesc": "多い順",
-                "lorasCountAsc": "少ない順"
+                "lorasCountAsc": "少ない順",
+                "opened": "最近開いた",
+                "openedDesc": "最近開いた"
            },
            "refresh": {
                "title": "レシピリストを更新",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "お気に入りのみ表示",
                "action": "お気に入り"
+            },
+            "layout": {
+                "title": "レシピのレイアウト",
+                "grid": "グリッドレイアウト",
+                "masonry": "メイソンリーレイアウト（Pinterest スタイル、画像のアスペクト比を保持）"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "{size} を解放します",
            "title": "モデルを削除",
            "message": "このモデルと関連するすべてのファイルを削除してもよろしいですか？",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "元に戻さない場合、このファイルは20秒後に完全に削除されます。"
        },
        "deleteRecipe": {
-            "recoverableWarning": "この操作は30秒以内であれば元に戻せます。"
+            "recoverableWarning": "この操作は20秒以内であれば元に戻せます。"
        },
        "excludeModel": {
            "title": "モデルを除外",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "このバージョンはローカルの最新バージョンより新しいです",
                    "earlyAccess": "早期アクセス",
                    "earlyAccessTooltip": "このバージョンは現在 Civitai の早期アクセスが必要です",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "無視中",
                    "ignoredTooltip": "このバージョンの更新通知は無効です",
                    "onSiteOnly": "サイト内のみ",
@@ -1557,6 +1570,7 @@
                    "download": "ダウンロード",
                    "downloadTooltip": "このバージョンをダウンロード",
                    "downloadEarlyAccessTooltip": "Civitai からこの早期アクセス版をダウンロード",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "このバージョンはCivitaiサイト内でのみ利用可能で、ダウンロードはできません",
                    "delete": "削除",
                    "deleteTooltip": "このローカルバージョンを削除",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "レシピがワークフローで置換されました",
            "recipeFailedToSend": "レシピをワークフローに送信できませんでした",
            "noMatchingNodes": "現在のワークフローには互換性のあるノードがありません",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "ターゲットノードが選択されていません",
            "modelUpdated": "モデルがワークフローで更新されました",
            "modelFailed": "モデルノードの更新に失敗しました",
@@ -2119,12 +2134,12 @@
            "copyFailed": "コピーに失敗しました"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "元に戻す",
+            "deleted": "{name} を削除しました",
+            "deletedBulk": "{count} 個のアイテムを削除しました",
+            "expired": "元に戻せる時間が経過しました。アイテムは完全に削除されました。",
+            "failed": "元に戻せませんでした: {error}",
+            "restored": "アイテムを復元しました"
        },
        "virtual": {
            "loadFailed": "アイテムの読み込みに失敗しました",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "ファイル名の変更に失敗しました：{error}",
            "previewUpdated": "プレビューが正常に更新されました",
            "previewUploadFailed": "プレビュー画像のアップロードに失敗しました",
+            "previewDropInvalid": "サポートされていないファイル形式：{name}。画像またはMP4ビデオをドロップしてください。",
            "refreshComplete": "{action} 完了",
            "refreshFailed": "{type}の{action}に失敗しました",
            "metadataRefreshed": "メタデータが正常に更新されました",
@@ -622,6 +622,10 @@
            "label": "얼리 액세스 업데이트 숨기기",
            "help": "얼리 액세스 업데이트만"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "업데이트된 라이선스 아이콘 사용",
            "useNewStyleHelp": "색상 표시기가 있는 라이선스 권한(새 스타일) 또는 제한 전용 아이콘(클래식 스타일)을 표시합니다. 현재 CivitAI 디자인을 반영합니다."
@@ -920,7 +924,9 @@
                "dateAsc": "오래된순",
                "lorasCount": "LoRA 수",
                "lorasCountDesc": "많은순",
-                "lorasCountAsc": "적은순"
+                "lorasCountAsc": "적은순",
+                "opened": "최근에 연",
+                "openedDesc": "최근에 연"
            },
            "refresh": {
                "title": "레시피 목록 새로고침",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "즐겨찾기만 표시",
                "action": "즐겨찾기"
+            },
+            "layout": {
+                "title": "레시피 레이아웃",
+                "grid": "그리드 레이아웃",
+                "masonry": "메이슨리 레이아웃 (Pinterest 스타일, 이미지 종횡비 유지)"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "{size} 확보",
            "title": "모델 삭제",
            "message": "이 모델과 모든 관련 파일을 삭제하시겠습니까?",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "실행 취소하지 않으면 20초 후에 파일이 영구적으로 삭제됩니다."
        },
        "deleteRecipe": {
-            "recoverableWarning": "이 작업은 30초 이내에 실행 취소할 수 있습니다."
+            "recoverableWarning": "이 작업은 20초 이내에 실행 취소할 수 있습니다."
        },
        "excludeModel": {
            "title": "모델 제외",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "이 버전은 로컬의 최신 버전보다 더 새롭습니다",
                    "earlyAccess": "얼리 액세스",
                    "earlyAccessTooltip": "이 버전은 현재 Civitai 얼리 액세스가 필요합니다",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "무시됨",
                    "ignoredTooltip": "이 버전은 업데이트 알림이 비활성화되어 있습니다",
                    "onSiteOnly": "사이트 내 전용",
@@ -1557,6 +1570,7 @@
                    "download": "다운로드",
                    "downloadTooltip": "이 버전 다운로드",
                    "downloadEarlyAccessTooltip": "Civitai에서 이 얼리 액세스 버전 다운로드",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "이 버전은 Civitai 사이트 내에서만 사용 가능하며 다운로드할 수 없습니다",
                    "delete": "삭제",
                    "deleteTooltip": "이 로컬 버전 삭제",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "레시피가 워크플로에서 교체되었습니다",
            "recipeFailedToSend": "레시피를 워크플로로 전송하지 못했습니다",
            "noMatchingNodes": "현재 워크플로에서 호환되는 노드가 없습니다",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "대상 노드가 선택되지 않았습니다",
            "modelUpdated": "모델이 워크플로에서 업데이트되었습니다",
            "modelFailed": "모델 노드 업데이트 실패",
@@ -2119,12 +2134,12 @@
            "copyFailed": "복사 실패"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "실행 취소",
+            "deleted": "{name} 삭제됨",
+            "deletedBulk": "{count}개 항목 삭제됨",
+            "expired": "실행 취소 기간이 만료되었습니다. 항목이 영구적으로 삭제되었습니다.",
+            "failed": "실행 취소 실패: {error}",
+            "restored": "항목이 복원되었습니다"
        },
        "virtual": {
            "loadFailed": "항목 로딩 실패",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "파일 이름 변경 실패: {error}",
            "previewUpdated": "미리보기가 성공적으로 업데이트되었습니다",
            "previewUploadFailed": "미리보기 이미지 업로드 실패",
+            "previewDropInvalid": "지원되지 않는 파일 형식: {name}. 이미지 또는 MP4 동영상을 드롭하세요.",
            "refreshComplete": "{action} 완료",
            "refreshFailed": "{type} {action} 실패",
            "metadataRefreshed": "메타데이터가 성공적으로 새로고침되었습니다",
@@ -622,6 +622,10 @@
            "label": "Скрыть обновления раннего доступа",
            "help": "Только обновления раннего доступа"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "Использовать обновлённые значки лицензии",
            "useNewStyleHelp": "Отображать разрешения лицензии с цветными индикаторами (новый стиль) или только значки ограничений (классический стиль). Соответствует текущему дизайну CivitAI."
@@ -920,7 +924,9 @@
                "dateAsc": "Сначала старые",
                "lorasCount": "Кол-во LoRA",
                "lorasCountDesc": "Больше всего",
-                "lorasCountAsc": "Меньше всего"
+                "lorasCountAsc": "Меньше всего",
+                "opened": "Недавно открытые",
+                "openedDesc": "Недавно открытые"
            },
            "refresh": {
                "title": "Обновить список рецептов",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "Только избранные",
                "action": "Избранное"
+            },
+            "layout": {
+                "title": "Макет рецептов",
+                "grid": "Макет сеткой",
+                "masonry": "Masonry-макет (в стиле Pinterest, сохраняет пропорции изображения)"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "Освобождает {size}",
            "title": "Удалить модель",
            "message": "Вы уверены, что хотите удалить эту модель и все связанные файлы?",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "Файл будет удалён навсегда через 20 секунд, если вы не отмените действие."
        },
        "deleteRecipe": {
-            "recoverableWarning": "Это действие можно отменить в течение 30 секунд."
+            "recoverableWarning": "Это действие можно отменить в течение 20 секунд."
        },
        "excludeModel": {
            "title": "Исключить модель",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "Эта версия новее вашей последней локальной версии",
                    "earlyAccess": "Ранний доступ",
                    "earlyAccessTooltip": "Для этой версии сейчас требуется ранний доступ Civitai",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "Игнорируется",
                    "ignoredTooltip": "Уведомления об обновлениях для этой версии отключены",
                    "onSiteOnly": "Только на Сайте",
@@ -1557,6 +1570,7 @@
                    "download": "Скачать",
                    "downloadTooltip": "Скачать эту версию",
                    "downloadEarlyAccessTooltip": "Скачать эту версию раннего доступа с Civitai",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "Эта версия доступна только для генерации на сайте Civitai",
                    "delete": "Удалить",
                    "deleteTooltip": "Удалить эту локальную версию",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "Рецепт заменён в workflow",
            "recipeFailedToSend": "Не удалось отправить рецепт в workflow",
            "noMatchingNodes": "В текущем workflow нет совместимых узлов",
+            "noPromptTargets": "[TODO: Translate] No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "Целевой узел не выбран",
            "modelUpdated": "Модель обновлена в workflow",
            "modelFailed": "Не удалось обновить узел модели",
@@ -2119,12 +2134,12 @@
            "copyFailed": "Копирование не удалось"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "Отменить",
+            "deleted": "Удалено: {name}",
+            "deletedBulk": "Удалено: {count} шт.",
+            "expired": "Время отмены истекло. Элемент был удалён навсегда.",
+            "failed": "Не удалось отменить: {error}",
+            "restored": "Элемент восстановлен"
        },
        "virtual": {
            "loadFailed": "Не удалось загрузить элементы",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "Не удалось переименовать файл: {error}",
            "previewUpdated": "Превью успешно обновлено",
            "previewUploadFailed": "Не удалось загрузить превью изображение",
+            "previewDropInvalid": "Неподдерживаемый тип файла: {name}. Перетащите вместо этого изображение или видео MP4.",
            "refreshComplete": "{action} завершено",
            "refreshFailed": "Не удалось {action} {type}s",
            "metadataRefreshed": "Метаданные успешно обновлены",
@@ -622,6 +622,10 @@
            "label": "隐藏抢先体验更新",
            "help": "抢先体验更新"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "使用新版许可协议图标",
            "useNewStyleHelp": "以彩色指示器显示许可权限（新样式），或仅显示限制图标（经典样式）。与当前 CivitAI 设计保持一致。"
@@ -920,7 +924,9 @@
                "dateAsc": "最早",
                "lorasCount": "LoRA 数量",
                "lorasCountDesc": "最多",
-                "lorasCountAsc": "最少"
+                "lorasCountAsc": "最少",
+                "opened": "最近打开",
+                "openedDesc": "最近打开"
            },
            "refresh": {
                "title": "刷新配方列表",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "仅显示收藏",
                "action": "收藏"
+            },
+            "layout": {
+                "title": "配方布局",
+                "grid": "网格布局",
+                "masonry": "瀑布流布局（Pinterest 风格，保留图片原始宽高比）"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "释放 {size}",
            "title": "删除模型",
            "message": "你确定要删除此模型及所有相关文件吗？",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "如果不撤销，文件将在 20 秒后被永久删除。"
        },
        "deleteRecipe": {
-            "recoverableWarning": "此操作可在 30 秒内撤销。"
+            "recoverableWarning": "此操作可在 20 秒内撤销。"
        },
        "excludeModel": {
            "title": "排除模型",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "此版本比你本地的最新版本更新",
                    "earlyAccess": "抢先体验",
                    "earlyAccessTooltip": "此版本当前需要 Civitai 抢先体验权限",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "已忽略",
                    "ignoredTooltip": "此版本已关闭更新通知",
                    "onSiteOnly": "仅站内生成",
@@ -1557,6 +1570,7 @@
                    "download": "下载",
                    "downloadTooltip": "下载此版本",
                    "downloadEarlyAccessTooltip": "从 Civitai 下载此抢先体验版本",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "此版本仅在 Civitai 站内可用，无法下载",
                    "delete": "删除",
                    "deleteTooltip": "删除此本地版本",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "配方已替换到工作流",
            "recipeFailedToSend": "发送配方到工作流失败",
            "noMatchingNodes": "当前工作流中没有兼容的节点",
+            "noPromptTargets": "工作流中没有兼容的 prompt 目标节点。\n在 ComfyUI 中右键节点 → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "未选择目标节点",
            "modelUpdated": "模型已更新到工作流",
            "modelFailed": "更新模型节点失败",
@@ -2119,12 +2134,12 @@
            "copyFailed": "复制失败"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "撤销",
+            "deleted": "已删除 {name}",
+            "deletedBulk": "已删除 {count} 个项目",
+            "expired": "撤销窗口已过期，项目已被永久删除。",
+            "failed": "撤销失败：{error}",
+            "restored": "项目已恢复"
        },
        "virtual": {
            "loadFailed": "加载项目失败",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "重命名文件失败：{error}",
            "previewUpdated": "预览图片更新成功",
            "previewUploadFailed": "上传预览图片失败",
+            "previewDropInvalid": "不支持的文件类型：{name}。请拖入图片或 MP4 视频。",
            "refreshComplete": "{action} 完成",
            "refreshFailed": "{action} {type} 失败",
            "metadataRefreshed": "元数据刷新成功",
@@ -622,6 +622,10 @@
            "label": "隱藏搶先體驗更新",
            "help": "搶先體驗更新"
        },
+        "hidePaidUpdates": {
+            "label": "[TODO: Translate] Hide Paid Updates",
+            "help": "[TODO: Translate] When enabled, models with only paid updates will not show 'Update available' badge"
+        },
        "licenseIcons": {
            "useNewStyle": "使用新版許可協議圖標",
            "useNewStyleHelp": "以彩色指示器顯示許可權限（新樣式），或僅顯示限制圖標（經典樣式）。與當前 CivitAI 設計保持一致。"
@@ -920,7 +924,9 @@
                "dateAsc": "最舊",
                "lorasCount": "LoRA 數量",
                "lorasCountDesc": "最多",
-                "lorasCountAsc": "最少"
+                "lorasCountAsc": "最少",
+                "opened": "最近開啟",
+                "openedDesc": "最近開啟"
            },
            "refresh": {
                "title": "重新整理配方列表",
@@ -931,6 +937,11 @@
            "favorites": {
                "title": "僅顯示收藏",
                "action": "收藏"
+            },
+            "layout": {
+                "title": "配方版面",
+                "grid": "網格版面",
+                "masonry": "瀑布流版面（Pinterest 風格，保留圖片原始寬高比）"
            }
        },
        "duplicates": {
@@ -1277,13 +1288,13 @@
            }
        },
        "deleteModel": {
-            "freesSpace": "[TODO: Translate] Frees {size}",
+            "freesSpace": "釋放 {size}",
            "title": "刪除模型",
            "message": "您確定要刪除此模型及所有相關檔案嗎？",
-            "recoverableWarning": "[TODO: Translate] This will permanently delete the file after 30 seconds unless you undo."
+            "recoverableWarning": "如果未復原，檔案將在 20 秒後被永久刪除。"
        },
        "deleteRecipe": {
-            "recoverableWarning": "此操作可在 30 秒內復原。"
+            "recoverableWarning": "此操作可在 20 秒內復原。"
        },
        "excludeModel": {
            "title": "排除模型",
@@ -1548,6 +1559,8 @@
                    "newerTooltip": "此版本比你本地的最新版本更新",
                    "earlyAccess": "搶先體驗",
                    "earlyAccessTooltip": "此版本目前需要 Civitai 搶先體驗權限",
+                    "paid": "[TODO: Translate] Paid",
+                    "paidTooltip": "[TODO: Translate] This version requires payment to download",
                    "ignored": "已忽略",
                    "ignoredTooltip": "此版本已關閉更新通知",
                    "onSiteOnly": "僅站內生成",
@@ -1557,6 +1570,7 @@
                    "download": "下載",
                    "downloadTooltip": "下載此版本",
                    "downloadEarlyAccessTooltip": "從 Civitai 下載此搶先體驗版本",
+                    "downloadPaidTooltip": "[TODO: Translate] Download this paid version from Civitai",
                    "downloadNotAllowedTooltip": "此版本僅在 Civitai 站內可用，無法下載",
                    "delete": "刪除",
                    "deleteTooltip": "刪除此本地版本",
@@ -1726,6 +1740,7 @@
            "recipeReplaced": "配方已取代於工作流",
            "recipeFailedToSend": "傳送配方到工作流失敗",
            "noMatchingNodes": "目前工作流程中沒有相容的節點",
+            "noPromptTargets": "工作流中沒有相容的 prompt 目標節點。\n在 ComfyUI 中右鍵節點 → Mark as → Send Prompt Target",
            "noTargetNodeSelected": "未選擇目標節點",
            "modelUpdated": "模型已更新到工作流",
            "modelFailed": "更新模型節點失敗",
@@ -2119,12 +2134,12 @@
            "copyFailed": "複製失敗"
        },
        "undo": {
-            "action": "[TODO: Translate] Undo",
-            "deleted": "[TODO: Translate] Deleted {name}",
-            "deletedBulk": "[TODO: Translate] Deleted {count} item(s)",
-            "expired": "[TODO: Translate] Undo window expired. The item was permanently deleted.",
-            "failed": "[TODO: Translate] Undo failed: {error}",
-            "restored": "[TODO: Translate] Item restored"
+            "action": "復原",
+            "deleted": "已刪除 {name}",
+            "deletedBulk": "已刪除 {count} 個項目",
+            "expired": "復原視窗已過期，項目已被永久刪除。",
+            "failed": "復原失敗：{error}",
+            "restored": "項目已還原"
        },
        "virtual": {
            "loadFailed": "載入項目失敗",
@@ -2189,6 +2204,7 @@
            "fileRenameFailed": "重新命名檔案失敗：{error}",
            "previewUpdated": "預覽圖片已成功更新",
            "previewUploadFailed": "上傳預覽圖片失敗",
+            "previewDropInvalid": "不支援的檔案類型：{name}。請拖入圖片或 MP4 影片。",
            "refreshComplete": "{action} 完成",
            "refreshFailed": "{action} {type} 失敗",
            "metadataRefreshed": "metadata 已成功刷新",
@@ -214,6 +214,24 @@ class MetadataProcessor:
                    max_denoise = denoise
                    primary_sampler = sampler_info
                    primary_sampler_id = node_id
+
+        # Last resort: any registered sampler. Samplers without a denoise or
+        # add_noise parameter (e.g. multi-stage samplers like KreaTwoStageSampler)
+        # are not caught by the criteria above. Prefer execution order so the
+        # first executed sampler wins, matching the downstream_id branch.
+        if primary_sampler is None:
+            sampler_ids = [
+                node_id
+                for node_id, sampler_info in metadata.get(SAMPLING, {}).items()
+                if sampler_info.get(IS_SAMPLER, False)
+            ]
+            if sampler_ids:
+                if downstream_id and "execution_order" in metadata:
+                    for node_id in metadata["execution_order"]:
+                        if node_id in sampler_ids:
+                            return node_id, metadata[SAMPLING][node_id]
+                primary_sampler_id = sampler_ids[0]
+                primary_sampler = metadata[SAMPLING][sampler_ids[0]]
                
        return primary_sampler_id, primary_sampler
    
@@ -40,7 +40,7 @@ class GenericNodeExtractor(NodeMetadataExtractor):
    * ``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.
+      prompt text, and conditioning inputs are tracked through transforms.
    """

    # Input field names that carry a model path in loader-style nodes.
@@ -73,7 +73,7 @@ class GenericNodeExtractor(NodeMetadataExtractor):
                    _store_checkpoint_metadata(metadata, node_id, name)
                    return

-        # — CONDITIONING encoder detection (CLIPTextEncode, Flux, custom) —
+        # — CONDITIONING encoder / transform detection —
        if "CONDITIONING" in return_types or any("CONDITIONING" in str(t) for t in return_types):
            text = None
            for field in GenericNodeExtractor._TEXT_FIELDS:
@@ -81,12 +81,14 @@ class GenericNodeExtractor(NodeMetadataExtractor):
                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,
-                }
+
+            input_conditionings = _collect_conditioning_inputs(inputs)
+            if text or input_conditionings:
+                prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+                if text:
+                    prompt_metadata["text"] = text
+                if input_conditionings:
+                    prompt_metadata["orig_conditionings"] = input_conditionings

    @staticmethod
    def update(node_id, outputs, metadata, return_types=None):
@@ -98,11 +100,26 @@ class GenericNodeExtractor(NodeMetadataExtractor):
            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
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple or len(output_tuple) < 1:
+            return
+
+        conditioning_index = _first_conditioning_index(return_types)
+        if conditioning_index is None or len(output_tuple) <= conditioning_index:
+            return
+
+        output_conditioning = output_tuple[conditioning_index]
+        if output_conditioning is None:
+            return
+
+        prompt_metadata = metadata[PROMPTS][node_id]
+        prompt_metadata["conditioning"] = output_conditioning
+        _record_conditioning_source(
+            metadata,
+            node_id,
+            output_conditioning,
+            prompt_metadata.get("orig_conditionings", []),
+        )

 class CheckpointLoaderExtractor(NodeMetadataExtractor):
    @staticmethod
@@ -417,6 +434,34 @@ def _first_output_tuple(outputs):
    return None


+def _first_conditioning_index(return_types):
+    """Return the index of the first CONDITIONING output slot, or None."""
+    if not return_types:
+        return None
+    for index, return_type in enumerate(return_types):
+        if "CONDITIONING" in str(return_type):
+            return index
+    return None
+
+
+def _collect_conditioning_inputs(inputs):
+    """Collect conditioning object inputs (``conditioning*`` keys).
+
+    Primitive values (None, str, int, float, bool) are excluded so scalar
+    fields like ``conditioning_strength`` are not mistaken for conditioning
+    objects during provenance tracking.
+    """
+    if not inputs:
+        return []
+    return [
+        value
+        for input_name, value in inputs.items()
+        if input_name.startswith("conditioning")
+        and value is not None
+        and not isinstance(value, (str, int, float, bool))
+    ]
+
+
 def _record_conditioning_source(
    metadata, node_id, output_conditioning, input_conditionings
 ):
@@ -429,6 +474,14 @@ def _record_conditioning_source(
    if not sources:
        return

+    # Identity-preserving selectors return one of their inputs unchanged:
+    # only that input contributed to the output, so record it alone instead
+    # of treating every input as a combination source.
+    for conditioning in sources:
+        if id(conditioning) == id(output_conditioning):
+            sources = [conditioning]
+            break
+
    prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
    prompt_metadata.setdefault("conditioning_sources", []).append(
        {
@@ -508,13 +561,7 @@ class ConditioningCombineExtractor(NodeMetadataExtractor):
        if not inputs:
            return

-        input_conditionings = []
-        for input_name in inputs:
-            if (
-                input_name.startswith("conditioning")
-                and inputs[input_name] is not None
-            ):
-                input_conditionings.append(inputs[input_name])
+        input_conditionings = _collect_conditioning_inputs(inputs)

        if input_conditionings:
            prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
@@ -814,6 +861,65 @@ class TSCKSamplerAdvancedExtractor(KSamplerAdvancedExtractor, TSCSamplerBaseExtr

    # Update method is inherited from TSCSamplerBaseExtractor

+class KreaTwoStageSamplerExtractor(BaseSamplerExtractor):
+    """Extractor for Krea Two/Three Stage Samplers (Auryg/Krea-2-Two-Stage-Sampler).
+
+    The node samples in two (or three) stages with per-stage settings
+    (stage1_steps/stage2_steps, stage1_cfg/stage2_cfg, ...). The canonical
+    metadata fields consumed by ``extract_generation_params`` (steps, cfg,
+    sampler_name, scheduler) are derived from the base stage (stage 1; the
+    three-stage variant reuses stage 1 settings for stage 3), while the full
+    per-stage breakdown is preserved in the raw parameters.
+    """
+
+    # All per-stage parameter keys present on both node variants.
+    _STAGE_PARAM_KEYS = (
+        "stage1_steps", "stage1_cfg", "stage1_sampler_name", "stage1_scheduler",
+        "stage2_steps", "stage2_cfg", "stage2_sampler_name", "stage2_scheduler",
+    )
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        BaseSamplerExtractor.extract_sampling_params(
+            node_id,
+            inputs,
+            metadata,
+            ("seed", "handoff_percent", "stage3_handoff_percent")
+            + KreaTwoStageSamplerExtractor._STAGE_PARAM_KEYS,
+        )
+
+        # Derive the canonical fields expected by extract_generation_params.
+        sampling_params = metadata[SAMPLING][node_id]["parameters"]
+        if "stage1_steps" in sampling_params or "stage2_steps" in sampling_params:
+            sampling_params["steps"] = (
+                (sampling_params.get("stage1_steps") or 0)
+                + (sampling_params.get("stage2_steps") or 0)
+            )
+        if "stage1_cfg" in sampling_params:
+            sampling_params["cfg"] = sampling_params["stage1_cfg"]
+        if "stage1_sampler_name" in sampling_params:
+            sampling_params["sampler_name"] = sampling_params["stage1_sampler_name"]
+        if "stage1_scheduler" in sampling_params:
+            sampling_params["scheduler"] = sampling_params["stage1_scheduler"]
+
+        BaseSamplerExtractor.extract_conditioning(node_id, inputs, metadata)
+
+        # Prefer the final generation resolution; latent dims are the fallback.
+        BaseSamplerExtractor.extract_latent_dimensions(node_id, inputs, metadata)
+        final_width = inputs.get("final_width")
+        final_height = inputs.get("final_height")
+        if final_width and final_height:
+            if SIZE not in metadata:
+                metadata[SIZE] = {}
+            metadata[SIZE][node_id] = {
+                "width": final_width,
+                "height": final_height,
+                "node_id": node_id,
+            }
+
 class LoraLoaderExtractor(NodeMetadataExtractor):
    @staticmethod
    def extract(node_id, inputs, outputs, metadata):
@@ -854,6 +960,37 @@ class ImageSizeExtractor(NodeMetadataExtractor):
            "node_id": node_id
        }

+class KreaDualResolutionSelectorExtractor(NodeMetadataExtractor):
+    """Extract base resolution from Krea Dual Resolution Selector outputs
+    (Auryg/Krea-2-Two-Stage-Sampler).
+
+    The node computes base/final dimensions at runtime from aspect ratio and
+    megapixel settings, so the values are only available in the update phase
+    (outputs: base_width, base_height, final_width, final_height, seed).
+    """
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        # Dimensions are computed at runtime; nothing to do here.
+        pass
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple or len(output_tuple) < 2:
+            return
+        width, height = output_tuple[0], output_tuple[1]
+        if not isinstance(width, int) or not isinstance(height, int):
+            return
+
+        if SIZE not in metadata:
+            metadata[SIZE] = {}
+        metadata[SIZE][node_id] = {
+            "width": width,
+            "height": height,
+            "node_id": node_id,
+        }
+
 class RgthreePowerLoraLoaderExtractor(NodeMetadataExtractor):
    """Extract LoRA metadata from rgthree Power Lora Loader.

@@ -1255,6 +1392,8 @@ NODE_EXTRACTORS = {
    "ClownsharKSampler_Beta": SamplerExtractor,
    "TSC_KSampler": TSCKSamplerExtractor,   # Efficient Nodes
    "TSC_KSamplerAdvanced": TSCKSamplerAdvancedExtractor,  # Efficient Nodes
+    "KreaTwoStageSampler": KreaTwoStageSamplerExtractor,  # Auryg/Krea-2-Two-Stage-Sampler
+    "KreaThreeStageSampler": KreaTwoStageSamplerExtractor,  # Auryg/Krea-2-Two-Stage-Sampler
    "KSamplerBasicPipe": KSamplerBasicPipeExtractor,    # comfyui-impact-pack
    "KSamplerAdvancedBasicPipe": KSamplerAdvancedBasicPipeExtractor,    # comfyui-impact-pack
    "KSampler_inspire_pipe": KSamplerBasicPipeExtractor,    # comfyui-inspire-pack
@@ -1306,6 +1445,7 @@ NODE_EXTRACTORS = {
    "GetNode": GetNodeExtractor,
    # Latent
    "EmptyLatentImage": ImageSizeExtractor,
+    "KreaDualResolutionSelector": KreaDualResolutionSelectorExtractor,  # Auryg/Krea-2-Two-Stage-Sampler
    # Flux
    "FluxGuidance": FluxGuidanceExtractor,      # Add FluxGuidance
    "CFGGuider": CFGGuiderExtractor,            # Add CFGGuider
@@ -8,7 +8,7 @@ cannot drift between the two paths.
 import logging
 from typing import Any, Dict

-from ..utils.utils import model_patcher_to_name
+from ..utils.utils import model_patcher_to_name, sampler_object_to_name
 from .constants import CLIP_SKIP_SENTINEL, METADATA_OVERWRITE_FIELDS

 logger = logging.getLogger(__name__)
@@ -22,7 +22,9 @@ def collect_overwrite_params(values: Dict[str, Any]) -> Dict[str, Any]:
    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.
+    stored as a ComfyUI-style relative path.  The ``sampler`` field likewise
+    accepts a manual string or a wired SAMPLER (KSAMPLER) connection, from
+    which the sampler name is extracted via the sampler function's name.
    """
    result: Dict[str, Any] = {}
    for key in METADATA_OVERWRITE_FIELDS:
@@ -34,6 +36,13 @@ def collect_overwrite_params(values: Dict[str, Any]) -> Dict[str, Any]:
                    "Could not extract model name from wired MODEL input "
                    "(no cached_patcher_init); model metadata overwrite skipped"
                )
+        elif key == "sampler" and not isinstance(value, str):
+            value = sampler_object_to_name(value)
+            if value is None:
+                logger.warning(
+                    "Could not extract sampler name from wired SAMPLER input "
+                    "(unrecognized sampler function); sampler metadata overwrite skipped"
+                )
        if key == "clip_skip":
            if value != CLIP_SKIP_SENTINEL:
                result[key] = value
@@ -71,10 +71,18 @@ class MetadataOverwriteLM:
                    },
                ),
                "sampler": (
-                    "STRING",
+                    "STRING,SAMPLER",
                    {
                        "default": "",
-                        "tooltip": "Sampler name. Only overwrites when non-empty.",
+                        "widgetType": "STRING",
+                        "tooltip": (
+                            "Sampler name. Fill in the name manually or "
+                            "connect a SAMPLER output (e.g. KSamplerSelect) "
+                            "— the sampler name is then extracted "
+                            "automatically. Note: ddim is recorded as "
+                            "euler (ComfyUI internal representation). "
+                            "Only overwrites when non-empty."
+                        ),
                    },
                ),
                "scheduler": (
@@ -164,6 +172,8 @@ class MetadataOverwriteLM:
        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.
+        stored as a ComfyUI-style relative path.  The ``sampler`` field
+        likewise accepts a manual string or a wired SAMPLER (KSAMPLER)
+        connection, from which the sampler name is extracted automatically.
        """
        return (collect_overwrite_params(kwargs),)
@@ -0,0 +1,214 @@
+import logging
+import os
+import random
+from typing import Any, List, Optional, Tuple
+import comfy.sd  # pyright: ignore[reportMissingImports]
+import folder_paths  # pyright: ignore[reportMissingImports]
+from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_comfyui
+
+logger = logging.getLogger(__name__)
+
+
+class RandomCheckpointLoaderLM:
+    """Checkpoint Loader that can randomly pick a checkpoint from the pool
+
+    Loads checkpoints from both standard ComfyUI folders and LoRA Manager's
+    extra folder paths. When select_at_random is enabled, ignores ckpt_name
+    and picks a random checkpoint (optionally filtered by base_model) on
+    every run.
+    """
+
+    NAME = "Random Checkpoint Loader (LoraManager)"
+    CATEGORY = "Lora Manager/loaders"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        # Get list of checkpoint names from scanner (includes extra folder paths)
+        checkpoint_names = cls._get_checkpoint_names()
+        base_models = cls._get_available_base_models()
+        return {
+            "required": {
+                "ckpt_name": (
+                    checkpoint_names,
+                    {"tooltip": "The name of the checkpoint (model) to load."},
+                ),
+                "select_at_random": (
+                    "BOOLEAN",
+                    {
+                        "default": False,
+                        "tooltip": (
+                            "Ignore ckpt_name and pick a random checkpoint from the "
+                            "pool (optionally filtered by base_model) on every run."
+                        ),
+                    },
+                ),
+                "base_model": (
+                    base_models,
+                    {
+                        "default": "Any",
+                        "tooltip": "Restrict random selection to this base model. 'Any' uses the full pool.",
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("MODEL", "CLIP", "VAE", "STRING")
+    RETURN_NAMES = ("MODEL", "CLIP", "VAE", "model_name")
+    OUTPUT_TOOLTIPS = (
+        "The model used for denoising latents.",
+        "The CLIP model used for encoding text prompts.",
+        "The VAE model used for encoding and decoding images to and from latent space.",
+        "The name of the checkpoint that was loaded (useful when select_at_random is enabled).",
+    )
+    FUNCTION = "load_checkpoint"
+
+    @classmethod
+    def IS_CHANGED(cls, ckpt_name, select_at_random=False, base_model="Any"):
+        # Force re-execution on every run while randomizing, since the widget
+        # values themselves don't change between queue runs.
+        if select_at_random:
+            return float("nan")
+        return ckpt_name
+
+    @staticmethod
+    def _run_async(coro_fn):
+        """Run an async fetcher, handling the case where an event loop is already running."""
+        import asyncio
+
+        try:
+            asyncio.get_running_loop()
+            import concurrent.futures
+
+            def run_in_thread():
+                new_loop = asyncio.new_event_loop()
+                asyncio.set_event_loop(new_loop)
+                try:
+                    return new_loop.run_until_complete(coro_fn())
+                finally:
+                    new_loop.close()
+
+            with concurrent.futures.ThreadPoolExecutor() as executor:
+                future = executor.submit(run_in_thread)
+                return future.result()
+        except RuntimeError:
+            return asyncio.run(coro_fn())
+
+    @classmethod
+    def _get_checkpoint_names(cls, base_model: Optional[str] = None) -> List[str]:
+        """Get list of checkpoint names from scanner cache in ComfyUI format (relative path with extension)
+
+        Args:
+            base_model: If given (and not "Any"), only include checkpoints matching this base model.
+        """
+        try:
+            from ..services.service_registry import ServiceRegistry
+
+            async def _get_names():
+                scanner = await ServiceRegistry.get_checkpoint_scanner()
+                cache = await scanner.get_cached_data()
+
+                # Get all model roots for calculating relative paths
+                model_roots = scanner.get_model_roots()
+
+                # Filter only checkpoint type (not diffusion_model) and format names
+                names = []
+                for item in cache.raw_data:
+                    if item.get("sub_type") != "checkpoint":
+                        continue
+                    if (
+                        base_model
+                        and base_model != "Any"
+                        and item.get("base_model") != base_model
+                    ):
+                        continue
+                    file_path = item.get("file_path", "")
+                    # Only offer models that still exist on disk so ComfyUI
+                    # flags missing checkpoints at queue time via
+                    # "value not in list" (the scanner cache can be stale).
+                    if file_path and os.path.exists(file_path):
+                        # Format using relative path with OS-native separator
+                        formatted_name = _format_model_name_for_comfyui(
+                            file_path, model_roots
+                        )
+                        if formatted_name:
+                            names.append(formatted_name)
+
+                return sorted(names)
+
+            return cls._run_async(_get_names)
+        except Exception as e:
+            logger.error(f"Error getting checkpoint names: {e}")
+            return []
+
+    @classmethod
+    def _get_available_base_models(cls) -> List[str]:
+        """Get distinct base_model values present among indexed checkpoints, for the random-selection filter."""
+        try:
+            from ..services.service_registry import ServiceRegistry
+
+            async def _get_base_models():
+                scanner = await ServiceRegistry.get_checkpoint_scanner()
+                cache = await scanner.get_cached_data()
+
+                base_models = set()
+                for item in cache.raw_data:
+                    if item.get("sub_type") != "checkpoint":
+                        continue
+                    base_model = item.get("base_model")
+                    file_path = item.get("file_path", "")
+                    if base_model and file_path and os.path.exists(file_path):
+                        base_models.add(base_model)
+
+                return sorted(base_models)
+
+            return ["Any"] + cls._run_async(_get_base_models)
+        except Exception as e:
+            logger.error(f"Error getting available base models: {e}")
+            return ["Any"]
+
+    def load_checkpoint(
+        self,
+        ckpt_name: str,
+        select_at_random: bool = False,
+        base_model: str = "Any",
+    ) -> Tuple[Any, Any, Any, str]:
+        """Load a checkpoint by name, supporting extra folder paths
+
+        Args:
+            ckpt_name: The name of the checkpoint to load (relative path with extension)
+            select_at_random: If True, ignore ckpt_name and pick randomly from the pool
+            base_model: Restricts random selection to this base model ("Any" = no filter)
+
+        Returns:
+            Tuple of (MODEL, CLIP, VAE, model_name)
+        """
+        if select_at_random:
+            pool = self._get_checkpoint_names(base_model)
+            if not pool:
+                raise FileNotFoundError(
+                    f"No checkpoints found for base model '{base_model}'. "
+                    "Pick a different base model or disable 'select_at_random'."
+                )
+            ckpt_name = random.choice(pool)
+            logger.info(
+                f"[RandomCheckpointLoaderLM] Randomly selected checkpoint: {ckpt_name}"
+            )
+
+        # Get absolute path from cache using ComfyUI-style name
+        ckpt_path, metadata = get_checkpoint_info_absolute(ckpt_name)
+
+        if metadata is None:
+            raise FileNotFoundError(
+                f"Checkpoint '{ckpt_name}' not found in LoRA Manager cache. "
+                "Make sure the checkpoint is indexed and try again."
+            )
+
+        # Load regular checkpoint using ComfyUI's API
+        logger.info(f"Loading checkpoint from: {ckpt_path}")
+        out = comfy.sd.load_checkpoint_guess_config(
+            ckpt_path,
+            output_vae=True,
+            output_clip=True,
+            embedding_directory=folder_paths.get_folder_paths("embeddings"),
+        )
+        return out[:3] + (ckpt_name,)
@@ -0,0 +1,326 @@
+import logging
+import os
+import random
+from typing import Any, List, Optional, Tuple
+import comfy.sd  # pyright: ignore[reportMissingImports]
+from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_comfyui
+
+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 RandomUNETLoaderLM.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 = RandomUNETLoaderLM()
+    model, _unet_name = loader._load_gguf_unet(unet_path, unet_path, weight_dtype)
+    return model
+
+
+class RandomUNETLoaderLM:
+    """UNET Loader that can randomly pick a diffusion model from the pool
+
+    Loads diffusion models/UNets from both standard ComfyUI folders and LoRA
+    Manager's extra folder paths. Supports both regular diffusion models and
+    GGUF format models. When select_at_random is enabled, ignores unet_name
+    and picks a random diffusion model (optionally filtered by base_model)
+    on every run.
+    """
+
+    NAME = "Random Unet Loader (LoraManager)"
+    CATEGORY = "Lora Manager/loaders"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        # Get list of unet names from scanner (includes extra folder paths)
+        unet_names = cls._get_unet_names()
+        base_models = cls._get_available_base_models()
+        return {
+            "required": {
+                "unet_name": (
+                    unet_names,
+                    {"tooltip": "The name of the diffusion model to load."},
+                ),
+                "weight_dtype": (
+                    ["default", "fp8_e4m3fn", "fp8_e4m3fn_fast", "fp8_e5m2"],
+                    {"tooltip": "The dtype to use for the model weights."},
+                ),
+                "select_at_random": (
+                    "BOOLEAN",
+                    {
+                        "default": False,
+                        "tooltip": (
+                            "Ignore unet_name and pick a random diffusion model from "
+                            "the pool (optionally filtered by base_model) on every run."
+                        ),
+                    },
+                ),
+                "base_model": (
+                    base_models,
+                    {
+                        "default": "Any",
+                        "tooltip": "Restrict random selection to this base model. 'Any' uses the full pool.",
+                    },
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("MODEL", "STRING")
+    RETURN_NAMES = ("MODEL", "model_name")
+    OUTPUT_TOOLTIPS = (
+        "The model used for denoising latents.",
+        "The name of the diffusion model that was loaded (useful when select_at_random is enabled).",
+    )
+    FUNCTION = "load_unet"
+
+    @classmethod
+    def IS_CHANGED(
+        cls, unet_name, weight_dtype, select_at_random=False, base_model="Any"
+    ):
+        # Force re-execution on every run while randomizing, since the widget
+        # values themselves don't change between queue runs.
+        if select_at_random:
+            return float("nan")
+        return unet_name
+
+    @staticmethod
+    def _run_async(coro_fn):
+        """Run an async fetcher, handling the case where an event loop is already running."""
+        import asyncio
+
+        try:
+            asyncio.get_running_loop()
+            import concurrent.futures
+
+            def run_in_thread():
+                new_loop = asyncio.new_event_loop()
+                asyncio.set_event_loop(new_loop)
+                try:
+                    return new_loop.run_until_complete(coro_fn())
+                finally:
+                    new_loop.close()
+
+            with concurrent.futures.ThreadPoolExecutor() as executor:
+                future = executor.submit(run_in_thread)
+                return future.result()
+        except RuntimeError:
+            return asyncio.run(coro_fn())
+
+    @classmethod
+    def _get_unet_names(cls, base_model: Optional[str] = None) -> List[str]:
+        """Get list of diffusion model names from scanner cache in ComfyUI format (relative path with extension)
+
+        Args:
+            base_model: If given (and not "Any"), only include models matching this base model.
+        """
+        try:
+            from ..services.service_registry import ServiceRegistry
+
+            async def _get_names():
+                scanner = await ServiceRegistry.get_checkpoint_scanner()
+                cache = await scanner.get_cached_data()
+
+                # Get all model roots for calculating relative paths
+                model_roots = scanner.get_model_roots()
+
+                # Filter only diffusion_model type and format names
+                names = []
+                for item in cache.raw_data:
+                    if item.get("sub_type") != "diffusion_model":
+                        continue
+                    if (
+                        base_model
+                        and base_model != "Any"
+                        and item.get("base_model") != base_model
+                    ):
+                        continue
+                    file_path = item.get("file_path", "")
+                    # Only offer models that still exist on disk so ComfyUI
+                    # flags missing diffusion models at queue time via
+                    # "value not in list" (the scanner cache can be stale).
+                    if file_path and os.path.exists(file_path):
+                        # Format using relative path with OS-native separator
+                        formatted_name = _format_model_name_for_comfyui(
+                            file_path, model_roots
+                        )
+                        if formatted_name:
+                            names.append(formatted_name)
+
+                return sorted(names)
+
+            return cls._run_async(_get_names)
+        except Exception as e:
+            logger.error(f"Error getting unet names: {e}")
+            return []
+
+    @classmethod
+    def _get_available_base_models(cls) -> List[str]:
+        """Get distinct base_model values present among indexed diffusion models, for the random-selection filter."""
+        try:
+            from ..services.service_registry import ServiceRegistry
+
+            async def _get_base_models():
+                scanner = await ServiceRegistry.get_checkpoint_scanner()
+                cache = await scanner.get_cached_data()
+
+                base_models = set()
+                for item in cache.raw_data:
+                    if item.get("sub_type") != "diffusion_model":
+                        continue
+                    base_model = item.get("base_model")
+                    file_path = item.get("file_path", "")
+                    if base_model and file_path and os.path.exists(file_path):
+                        base_models.add(base_model)
+
+                return sorted(base_models)
+
+            return ["Any"] + cls._run_async(_get_base_models)
+        except Exception as e:
+            logger.error(f"Error getting available base models: {e}")
+            return ["Any"]
+
+    def load_unet(
+        self,
+        unet_name: str,
+        weight_dtype: str,
+        select_at_random: bool = False,
+        base_model: str = "Any",
+    ) -> Tuple[Any, ...]:
+        """Load a diffusion model by name, supporting extra folder paths
+
+        Args:
+            unet_name: The name of the diffusion model to load (relative path with extension)
+            weight_dtype: The dtype to use for model weights
+            select_at_random: If True, ignore unet_name and pick randomly from the pool
+            base_model: Restricts random selection to this base model ("Any" = no filter)
+
+        Returns:
+            Tuple of (MODEL, model_name)
+        """
+        import torch
+
+        if select_at_random:
+            pool = self._get_unet_names(base_model)
+            if not pool:
+                raise FileNotFoundError(
+                    f"No diffusion models found for base model '{base_model}'. "
+                    "Pick a different base model or disable 'select_at_random'."
+                )
+            unet_name = random.choice(pool)
+            logger.info(
+                f"[RandomUNETLoaderLM] Randomly selected diffusion model: {unet_name}"
+            )
+
+        # Get absolute path from cache using ComfyUI-style name
+        unet_path, metadata = get_checkpoint_info_absolute(unet_name)
+
+        if metadata is None:
+            raise FileNotFoundError(
+                f"Diffusion model '{unet_name}' not found in LoRA Manager cache. "
+                "Make sure the model is indexed and try again."
+            )
+
+        # Check if it's a GGUF model
+        if unet_path.endswith(".gguf"):
+            return self._load_gguf_unet(unet_path, unet_name, weight_dtype)
+
+        # Load regular diffusion model using ComfyUI's API
+        logger.info(f"Loading diffusion model from: {unet_path}")
+
+        # Build model options based on weight_dtype
+        model_options = {}
+        if weight_dtype == "fp8_e4m3fn":
+            model_options["dtype"] = torch.float8_e4m3fn
+        elif weight_dtype == "fp8_e4m3fn_fast":
+            model_options["dtype"] = torch.float8_e4m3fn
+            model_options["fp8_optimizations"] = True
+        elif weight_dtype == "fp8_e5m2":
+            model_options["dtype"] = torch.float8_e5m2
+
+        model = comfy.sd.load_diffusion_model(unet_path, model_options=model_options)
+        return (model, unet_name)
+
+    def _load_gguf_unet(
+        self, unet_path: str, unet_name: str, weight_dtype: str
+    ) -> Tuple[Any, ...]:
+        """Load a GGUF format diffusion model
+
+        Args:
+            unet_path: Absolute path to the GGUF file
+            unet_name: Name of the model for error messages
+            weight_dtype: The dtype to use for model weights
+
+        Returns:
+            Tuple of (MODEL, model_name)
+        """
+        import torch
+        from .gguf_import_helper import get_gguf_modules
+
+        # Get ComfyUI-GGUF modules using helper (handles various import scenarios)
+        try:
+            loader_module, ops_module, nodes_module = get_gguf_modules()
+            gguf_sd_loader = getattr(loader_module, "gguf_sd_loader")
+            GGMLOps = getattr(ops_module, "GGMLOps")
+            GGUFModelPatcher = getattr(nodes_module, "GGUFModelPatcher")
+        except RuntimeError as e:
+            raise RuntimeError(f"Cannot load GGUF model '{unet_name}'. {str(e)}")
+
+        logger.info(f"Loading GGUF diffusion model from: {unet_path}")
+
+        try:
+            # Load GGUF state dict
+            sd, extra = gguf_sd_loader(unet_path)
+
+            # Prepare kwargs for metadata if supported
+            kwargs = {}
+            import inspect
+
+            valid_params = inspect.signature(
+                comfy.sd.load_diffusion_model_state_dict
+            ).parameters
+            if "metadata" in valid_params:
+                kwargs["metadata"] = extra.get("metadata", {})
+
+            # Setup custom operations with GGUF support
+            ops = GGMLOps()
+
+            # Handle weight_dtype for GGUF models
+            if weight_dtype in ("default", None):
+                ops.Linear.dequant_dtype = None
+            elif weight_dtype in ["target"]:
+                ops.Linear.dequant_dtype = weight_dtype
+            else:
+                ops.Linear.dequant_dtype = getattr(torch, weight_dtype, None)
+
+            # Load the model
+            model = comfy.sd.load_diffusion_model_state_dict(
+                sd, model_options={"custom_operations": ops}, **kwargs
+            )
+
+            if model is None:
+                raise RuntimeError(
+                    f"Could not detect model type for GGUF diffusion model: {unet_path}"
+                )
+
+            # 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, unet_name)
+
+        except Exception as e:
+            logger.error(f"Error loading GGUF diffusion model '{unet_name}': {e}")
+            raise RuntimeError(
+                f"Failed to load GGUF diffusion model '{unet_name}': {str(e)}"
+            )
@@ -11,7 +11,7 @@ import re
 from typing import Dict, List, Any, Optional, Tuple
 from abc import ABC, abstractmethod
 from ..config import config
-from ..utils.constants import VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
+from ..utils.constants import MODEL_WEIGHT_FILE_TYPES, VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
 from ..utils.civitai_utils import rewrite_preview_url

 logger = logging.getLogger(__name__)
@@ -155,9 +155,9 @@ class RecipeMetadataParser(ABC):
            
            # Process file information if available
            if 'files' in civitai_info:
-                # Find the primary model file (type="Model" and primary=true) in the files list
+                # Find the primary model file (weights-type and primary=true) in the files list
                model_file = next((file for file in civitai_info.get('files', []) 
-                                    if file.get('type') == 'Model' and file.get('primary') == True), None)
+                                    if file.get('type') in MODEL_WEIGHT_FILE_TYPES and file.get('primary') == True), None)
                
                if model_file:
                    # Get size
@@ -261,11 +261,21 @@ class RecipeMetadataParser(ABC):
            checkpoint['id'] = civitai_data.get('id', 0)

            if 'files' in civitai_data:
+                # Prefer the file CivitAI marked primary; fall back to any
+                # weights-type file (providers without primary flags).
                model_file = next(
                    (
                        file
                        for file in civitai_data.get('files', [])
-                        if file.get('type') == 'Model'
+                        if file.get('type') in MODEL_WEIGHT_FILE_TYPES
+                        and file.get('primary') is True
+                    ),
+                    None,
+                ) or next(
+                    (
+                        file
+                        for file in civitai_data.get('files', [])
+                        if file.get('type') in MODEL_WEIGHT_FILE_TYPES
                    ),
                    None,
                )
@@ -30,6 +30,7 @@ from ..services.websocket_progress_callback import (
    WebSocketProgressCallback,
 )
 from ..utils.exif_utils import ExifUtils
+from ..utils.constants import MODEL_WEIGHT_FILE_TYPES
 from ..utils.metadata_manager import MetadataManager
 from .model_route_registrar import COMMON_ROUTE_DEFINITIONS, ModelRouteRegistrar
 from .handlers.model_handlers import (
@@ -251,7 +252,7 @@ class BaseModelRoutes(ABC):

    def _find_model_file(self, files):
        """Find the appropriate model file from the files list - can be overridden by subclasses."""
-        return next((file for file in files if file.get("type") in ("Model", "Diffusion Model") and file.get("primary") is True), None)
+        return next((file for file in files if file.get("type") in MODEL_WEIGHT_FILE_TYPES and file.get("primary") is True), None)

    def get_handler(self, name: str) -> Callable[[web.Request], Awaitable[web.StreamResponse]]:
        """Expose handlers for subclasses or tests."""
@@ -2535,6 +2535,7 @@ class ModelUpdateHandler:
            return web.json_response({"success": False, "error": str(exc)}, status=500)

        hide_early_access = False
+        hide_paid = False
        if self._settings is not None:
            try:
                hide_early_access = bool(
@@ -2542,12 +2543,17 @@ class ModelUpdateHandler:
                )
            except Exception:
                pass
+            try:
+                hide_paid = bool(self._settings.get("hide_paid_updates", False))
+            except Exception:
+                pass

        serialized_records = []
        for record in records.values():
            has_update_fn = getattr(record, "has_update", None)
            if callable(has_update_fn) and has_update_fn(
-                hide_early_access=hide_early_access
+                hide_early_access=hide_early_access,
+                hide_paid=hide_paid,
            ):
                serialized_records.append(self._serialize_record(record))

@@ -2701,10 +2707,16 @@ class ModelUpdateHandler:
        if not record or not record.versions:
            return record

-        # Find versions that need enrichment
+        # Find versions that need enrichment. Permanent paid versions are not
+        # early access (mirror _is_early_access_active) and never carry an end
+        # time, so skip them to avoid pointless per-version API calls.
        versions_needing_update = []
        for version in record.versions:
-            if version.is_early_access and not version.early_access_ends_at:
+            if (
+                version.is_early_access
+                and not version.early_access_ends_at
+                and not getattr(version, "is_paid", False)
+            ):
                versions_needing_update.append(version)

        if not versions_needing_update:
@@ -2934,6 +2946,7 @@ class ModelUpdateHandler:
        context = version_context or {}
        # Check user setting for hiding early access versions
        hide_early_access = False
+        hide_paid = False
        if self._settings is not None:
            try:
                hide_early_access = bool(
@@ -2941,6 +2954,10 @@ class ModelUpdateHandler:
                )
            except Exception:
                pass
+            try:
+                hide_paid = bool(self._settings.get("hide_paid_updates", False))
+            except Exception:
+                pass
        return {
            "modelType": record.model_type,
            "modelId": record.model_id,
@@ -2949,7 +2966,10 @@ class ModelUpdateHandler:
            "inLibraryVersionIds": record.in_library_version_ids,
            "lastCheckedAt": record.last_checked_at,
            "shouldIgnore": record.should_ignore_model,
-            "hasUpdate": record.has_update(hide_early_access=hide_early_access),
+            "hasUpdate": record.has_update(
+                hide_early_access=hide_early_access,
+                hide_paid=hide_paid,
+            ),
            "versions": [
                self._serialize_version(version, context.get(version.version_id))
                for version in record.versions
@@ -2968,8 +2988,11 @@ class ModelUpdateHandler:

        # Determine if version is currently in early access
        # Two-phase detection: use exact end time if available, otherwise fallback to basic flag
+        # Mirror _is_early_access_active: permanent paid versions (no end time) are NOT early access
        is_early_access = False
-        if version.early_access_ends_at:
+        if getattr(version, "is_paid", False) and not version.early_access_ends_at:
+            is_early_access = False
+        elif version.early_access_ends_at:
            try:
                from datetime import datetime, timezone

@@ -2984,6 +3007,13 @@ class ModelUpdateHandler:
            # Fallback to basic EA flag from bulk API
            is_early_access = True

+        paid_access_payload = None
+        if getattr(version, "paid_access", None):
+            try:
+                paid_access_payload = json.loads(version.paid_access)
+            except (TypeError, ValueError):
+                paid_access_payload = None
+
        return {
            "versionId": version.version_id,
            "name": version.name,
@@ -2997,6 +3027,8 @@ class ModelUpdateHandler:
            "earlyAccessEndsAt": version.early_access_ends_at,
            "isEarlyAccess": is_early_access,
            "usageControl": version.usage_control,
+            "isPaid": bool(getattr(version, "is_paid", False)),
+            "paidAccess": paid_access_payload,
            "filePath": context.get("file_path"),
            "fileName": context.get("file_name"),
        }
@@ -34,6 +34,7 @@ from ...utils.civitai_utils import (
 )
 from ...utils.constants import NSFW_LEVELS
 from ...utils.exif_utils import ExifUtils
+from ...utils.recipe_open_stats import RecipeOpenStats
 from ...recipes.merger import GenParamsMerger
 from ...recipes.enrichment import RecipeEnricher
 from ...services.websocket_manager import ws_manager as default_ws_manager
@@ -98,6 +99,7 @@ class RecipeHandlerSet:
            "download_shared_recipe": self.sharing.download_shared_recipe,
            "get_recipe_syntax": self.query.get_recipe_syntax,
            "update_recipe": self.management.update_recipe,
+            "record_recipe_open": self.management.record_recipe_open,
            "reconnect_lora": self.management.reconnect_lora,
            "find_duplicates": self.query.find_duplicates,
            "move_recipes_bulk": self.management.move_recipes_bulk,
@@ -1458,6 +1460,33 @@ class RecipeManagementHandler:
            self._logger.error("Error updating recipe: %s", exc, exc_info=True)
            return web.json_response({"error": str(exc)}, status=500)

+    async def record_recipe_open(self, request: web.Request) -> web.Response:
+        """Record that a recipe's detail modal was opened.
+
+        Lightweight fire-and-forget endpoint backing the "Recently Opened"
+        sort. It only writes the timestamp into the separate open-stats file
+        — recipe JSON and EXIF are never touched.
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            recipe_id = request.match_info["recipe_id"]
+            # Skip recording opens for recipes the scanner no longer knows.
+            recipe_json_path = await recipe_scanner.get_recipe_json_path(recipe_id)
+            if not recipe_json_path:
+                return web.json_response(
+                    {"success": False, "error": "Recipe not found"}, status=404
+                )
+
+            RecipeOpenStats().record_open(recipe_id)
+            return web.json_response({"success": True})
+        except Exception as exc:
+            self._logger.error("Error recording recipe open: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
    async def move_recipe(self, request: web.Request) -> web.Response:
        try:
            await self._ensure_dependencies_ready()
@@ -43,6 +43,9 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
    ),
    RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/syntax", "get_recipe_syntax"),
    RouteDefinition("PUT", "/api/lm/recipe/{recipe_id}/update", "update_recipe"),
+    RouteDefinition(
+        "POST", "/api/lm/recipe/{recipe_id}/opened", "record_recipe_open"
+    ),
    RouteDefinition("POST", "/api/lm/recipe/move", "move_recipe"),
    RouteDefinition("POST", "/api/lm/recipes/move-bulk", "move_recipes_bulk"),
    RouteDefinition("POST", "/api/lm/recipe/lora/reconnect", "reconnect_lora"),
@@ -633,6 +633,13 @@ class BaseModelService(ABC):
        except Exception:
            hide_early_access = False

+        # Check user setting for hiding permanent paid updates
+        hide_paid = False
+        try:
+            hide_paid = bool(self.settings.get("hide_paid_updates", False))
+        except Exception:
+            hide_paid = False
+
        records = None
        resolved: Optional[Dict[int, bool]] = None
        if same_base_mode:
@@ -641,7 +648,10 @@ class BaseModelService(ABC):
                try:
                    records = await cast(Awaitable[Any], record_method(self.model_type, ordered_ids))
                    resolved = {
-                        model_id: record.has_update(hide_early_access=hide_early_access)
+                        model_id: record.has_update(
+                            hide_early_access=hide_early_access,
+                            hide_paid=hide_paid,
+                        )
                        for model_id, record in records.items()
                    }
                except Exception as exc:
@@ -663,6 +673,7 @@ class BaseModelService(ABC):
                        self.model_type,
                        ordered_ids,
                        hide_early_access=hide_early_access,
+                        hide_paid=hide_paid,
                    ))
                except Exception as exc:
                    logger.error(
@@ -677,7 +688,10 @@ class BaseModelService(ABC):
        if resolved is None:
            tasks = [
                self.update_service.has_update(
-                    self.model_type, model_id, hide_early_access=hide_early_access
+                    self.model_type,
+                    model_id,
+                    hide_early_access=hide_early_access,
+                    hide_paid=hide_paid,
                )
                for model_id in ordered_ids
            ]
@@ -717,6 +731,7 @@ class BaseModelService(ABC):
                        threshold_version,
                        base_model,
                        hide_early_access=hide_early_access,
+                        hide_paid=hide_paid,
                    )
                else:
                    flag = default_flag
@@ -21,6 +21,7 @@ from .model_metadata_provider import (
 from .downloader import get_downloader
 from .errors import RateLimitError, ResourceNotFoundError
 from ..utils.civitai_utils import resolve_license_payload
+from ..utils.constants import MODEL_WEIGHT_FILE_TYPES

 logger = logging.getLogger(__name__)

@@ -538,10 +539,16 @@ class CivitaiClient:
        return model_versions[0]

    def _extract_primary_model_hash(self, version_entry: Dict[str, Any]) -> Optional[str]:
+        # Prefer the generic "Model" file (most reliable version identity);
+        # fall back to any other weights-type primary.
        for file_info in version_entry.get("files", []):
            if file_info.get("type") == "Model" and file_info.get("primary"):
-                hashes = file_info.get("hashes", {})
-                model_hash = hashes.get("SHA256")
+                model_hash = (file_info.get("hashes", {}) or {}).get("SHA256")
+                if model_hash:
+                    return model_hash
+        for file_info in version_entry.get("files", []):
+            if file_info.get("type") in MODEL_WEIGHT_FILE_TYPES and file_info.get("primary"):
+                model_hash = (file_info.get("hashes", {}) or {}).get("SHA256")
                if model_hash:
                    return model_hash
        return None
@@ -83,6 +83,7 @@ class DownloadCoordinator:
            save_dir=payload.get("model_root"),
            relative_path=payload.get("relative_path", ""),
            use_default_paths=payload.get("use_default_paths", False),
+            use_save_dir_as_root=payload.get("use_save_dir_as_root", False),
            progress_callback=progress_callback,
            download_id=download_id,
            source=payload.get("source"),
@@ -3,6 +3,7 @@
 # reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
 # import cycles. Breaking them would require an architectural refactor.
 import copy
+import json
 import logging
 import os
 import asyncio
@@ -18,6 +19,7 @@ from ..utils.models import LoraMetadata, CheckpointMetadata, EmbeddingMetadata
 from ..utils.constants import (
    CARD_PREVIEW_WIDTH,
    DIFFUSION_MODEL_BASE_MODELS,
+    MODEL_WEIGHT_FILE_TYPES,
    SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS,
    VALID_LORA_TYPES,
 )
@@ -46,6 +48,11 @@ CIVITAI_DOWNLOAD_URL_PREFIXES = (
 )


+# File types that are never the intended download target even when CivitAI
+# marks them primary — configs/archives/workflows are auxiliary artifacts.
+NON_DOWNLOADABLE_PRIMARY_TYPES = ("Config", "Archive", "Workflow", "Training Data")
+
+
 class DownloadManager:
    _instance = None
    _lock = asyncio.Lock()
@@ -217,6 +224,7 @@ class DownloadManager:
        download_id: str | None = None,
        source: str | None = None,
        file_params: Dict[str, Any] | None = None,
+        use_save_dir_as_root: bool = False,
    ) -> Dict[str, Any]:
        """Download model from Civitai with task tracking and concurrency control

@@ -257,6 +265,7 @@ class DownloadManager:
            "save_dir": save_dir,
            "relative_path": relative_path,
            "use_default_paths": bool(use_default_paths),
+            "use_save_dir_as_root": bool(use_save_dir_as_root),
            "source": source,
            "file_params": copy.deepcopy(file_params) if file_params is not None else None,
            "progress": 0,
@@ -287,6 +296,7 @@ class DownloadManager:
                use_default_paths,
                source,
                file_params,
+                use_save_dir_as_root,
            )
        )

@@ -321,6 +331,7 @@ class DownloadManager:
        use_default_paths: bool = False,
        source: str | None = None,
        file_params: Dict[str, Any] | None = None,
+        use_save_dir_as_root: bool = False,
    ):
        """Execute download with semaphore to limit concurrency"""
        # Update status to waiting
@@ -401,6 +412,7 @@ class DownloadManager:
                        ),
                        source,
                        file_params,
+                        use_save_dir_as_root=use_save_dir_as_root,
                    )

                    # Update status based on result
@@ -621,6 +633,7 @@ class DownloadManager:
            "save_dir": info.get("save_dir"),
            "relative_path": info.get("relative_path", ""),
            "use_default_paths": bool(info.get("use_default_paths", False)),
+            "use_save_dir_as_root": bool(info.get("use_save_dir_as_root", False)),
            "source": info.get("source"),
            "file_params": copy.deepcopy(info.get("file_params")),
            "transfer_backend": info.get("transfer_backend", "aria2"),
@@ -643,6 +656,7 @@ class DownloadManager:
            "save_dir": record.get("save_dir"),
            "relative_path": record.get("relative_path", ""),
            "use_default_paths": bool(record.get("use_default_paths", False)),
+            "use_save_dir_as_root": bool(record.get("use_save_dir_as_root", False)),
            "source": record.get("source"),
            "file_params": copy.deepcopy(record.get("file_params")),
            "progress": record.get("progress", 0),
@@ -1001,6 +1015,7 @@ class DownloadManager:
                                        bool(restored.get("use_default_paths", False)),
                                        restored.get("source"),
                                        restored.get("file_params"),
+                                        bool(restored.get("use_save_dir_as_root", False)),
                                    )
                                )
                        continue
@@ -1134,6 +1149,7 @@ class DownloadManager:
        transfer_backend: str = "python",
        source: str | None = None,
        file_params: Dict[str, Any] | None = None,
+        use_save_dir_as_root: bool = False,
    ) -> Dict[str, Any]:
        """Wrapper for original download_from_civitai implementation"""
        try:
@@ -1362,36 +1378,41 @@ class DownloadManager:
            # Handle use_default_paths
            if use_default_paths:
                settings_manager = get_settings_manager()
-                # Set save_dir based on model type
-                if model_type == "checkpoint":
-                    if is_diffusion_model:
-                        default_path = settings_manager.get("default_unet_root")
-                        error_msg = "Default unet root path not set in settings"
-                    else:
-                        default_path = settings_manager.get("default_checkpoint_root")
-                        error_msg = "Default checkpoint root path not set in settings"
-                    if not default_path:
-                        return {
-                            "success": False,
-                            "error": error_msg,
-                        }
-                    save_dir = default_path
-                elif model_type == "lora":
-                    default_path = settings_manager.get("default_lora_root")
-                    if not default_path:
-                        return {
-                            "success": False,
-                            "error": "Default lora root path not set in settings",
-                        }
-                    save_dir = default_path
-                elif model_type == "embedding":
-                    default_path = settings_manager.get("default_embedding_root")
-                    if not default_path:
-                        return {
-                            "success": False,
-                            "error": "Default embedding root path not set in settings",
-                        }
-                    save_dir = default_path
+                # With use_save_dir_as_root, an explicitly provided save_dir is kept
+                # as the base root and the path template is resolved underneath it.
+                # Otherwise fall back to the configured default root, which keeps the
+                # classic "download to default root" behavior for regular downloads.
+                if not save_dir or not use_save_dir_as_root:
+                    # Set save_dir based on model type
+                    if model_type == "checkpoint":
+                        if is_diffusion_model:
+                            default_path = settings_manager.get("default_unet_root")
+                            error_msg = "Default unet root path not set in settings"
+                        else:
+                            default_path = settings_manager.get("default_checkpoint_root")
+                            error_msg = "Default checkpoint root path not set in settings"
+                        if not default_path:
+                            return {
+                                "success": False,
+                                "error": error_msg,
+                            }
+                        save_dir = default_path
+                    elif model_type == "lora":
+                        default_path = settings_manager.get("default_lora_root")
+                        if not default_path:
+                            return {
+                                "success": False,
+                                "error": "Default lora root path not set in settings",
+                            }
+                        save_dir = default_path
+                    elif model_type == "embedding":
+                        default_path = settings_manager.get("default_embedding_root")
+                        if not default_path:
+                            return {
+                                "success": False,
+                                "error": "Default embedding root path not set in settings",
+                            }
+                        save_dir = default_path

                # Calculate relative path using template
                relative_path = self._calculate_relative_path(version_info, model_type)
@@ -1414,24 +1435,48 @@ class DownloadManager:
                # Create directory if it doesn't exist
                os.makedirs(save_dir, exist_ok=True)

-            # Check if this is an early access model
-            if version_info.get("earlyAccessEndsAt"):
-                early_access_date = version_info.get("earlyAccessEndsAt", "")
-                # Convert to a readable date if possible
+            # Check if this is a paid or early access model
+            paid_access = version_info.get("paidAccess")
+            if isinstance(paid_access, str):
+                # Some providers (e.g. CivArchive fallback) carry the DTO as JSON text
                try:
-                    from datetime import datetime
-
-                    date_obj = datetime.fromisoformat(
-                        early_access_date.replace("Z", "+00:00")
-                    )
-                    formatted_date = date_obj.strftime("%Y-%m-%d")
+                    parsed = json.loads(paid_access)
+                    paid_access = parsed if isinstance(parsed, dict) else None
+                except (TypeError, ValueError):
+                    paid_access = None
+            if not isinstance(paid_access, dict):
+                paid_access = None
+            # An empty DTO ({"permanent": false, "endsAt": null}) is not a gate
+            if paid_access and not paid_access.get("permanent") and not paid_access.get("endsAt"):
+                paid_access = None
+            if version_info.get("earlyAccessEndsAt") or paid_access:
+                permanent_paid = bool(paid_access.get("permanent")) if paid_access else False
+                if permanent_paid:
                    early_access_msg = (
-                        f"This model requires payment (until {formatted_date}). "
+                        "This model requires payment. Please ensure you have "
+                        "purchased access and are logged in to Civitai."
                    )
-                except:
-                    early_access_msg = "This model requires payment. "
+                else:
+                    early_access_date = version_info.get("earlyAccessEndsAt")
+                    if not early_access_date and paid_access:
+                        early_access_date = paid_access.get("endsAt")
+                    if not early_access_date:
+                        early_access_date = ""
+                    # Convert to a readable date if possible
+                    try:
+                        from datetime import datetime

-                early_access_msg += "Please ensure you have purchased early access and are logged in to Civitai."
+                        date_obj = datetime.fromisoformat(
+                            early_access_date.replace("Z", "+00:00")
+                        )
+                        formatted_date = date_obj.strftime("%Y-%m-%d")
+                        early_access_msg = (
+                            f"This model requires payment (until {formatted_date}). "
+                        )
+                    except Exception:
+                        early_access_msg = "This model requires payment. "
+
+                    early_access_msg += "Please ensure you have purchased early access and are logged in to Civitai."
                logger.warning(
                    f"Early access model detected: {version_info.get('name', 'Unknown')}"
                )
@@ -1486,7 +1531,7 @@ class DownloadManager:
                            f
                            for f in files
                            if f.get("primary")
-                            and f.get("type") in ("Model", "Negative", "Diffusion Model", "UNet")
+                            and f.get("type") in MODEL_WEIGHT_FILE_TYPES
                        ),
                        None,
                    )
@@ -1526,21 +1571,52 @@ class DownloadManager:
            # Fallback to primary file if no match found
            if not file_info:
                logger.debug("[download] Looking for primary file as fallback")
+                # Prefer a weights-type file CivitAI marked primary; then any
+                # weights-type file (providers without primary flags, e.g.
+                # civarchive); then trust CivitAI's primary flag regardless of
+                # type — newer types like 'Enhancement LoRA' are valid primary
+                # files. Weights files are preferred over non-weights primary
+                # files so a Config/Archive primary never replaces a Model.
                file_info = next(
                    (
                        f
                        for f in files
-                        if f.get("primary") and f.get("type") in ("Model", "Negative", "Diffusion Model", "UNet")
+                        if f.get("primary") and f.get("type") in MODEL_WEIGHT_FILE_TYPES
                    ),
                    None,
                )
                if file_info:
                    logger.debug(
-                        "[download] Fallback primary file selected: id=%s, name=%s",
+                        "[download] Fallback primary file selected (primary + weights): id=%s, name=%s",
                        file_info.get("id"), file_info.get("name"),
                    )
                else:
-                    logger.debug("[download] No primary file found in fallback lookup")
+                    file_info = next(
+                        (f for f in files if f.get("type") in MODEL_WEIGHT_FILE_TYPES),
+                        None,
+                    )
+                    if file_info:
+                        logger.debug(
+                            "[download] Fallback primary file selected (weights type, no primary flag): id=%s, name=%s",
+                            file_info.get("id"), file_info.get("name"),
+                        )
+                    else:
+                        file_info = next(
+                            (
+                                f
+                                for f in files
+                                if f.get("primary")
+                                and f.get("type") not in NON_DOWNLOADABLE_PRIMARY_TYPES
+                            ),
+                            None,
+                        )
+                        if file_info:
+                            logger.debug(
+                                "[download] Fallback primary file selected (trusting CivitAI primary flag): id=%s, name=%s, type=%s",
+                                file_info.get("id"), file_info.get("name"), file_info.get("type"),
+                            )
+                        else:
+                            logger.debug("[download] No primary file found in fallback lookup")

            if not file_info:
                return {"success": False, "error": "No suitable file found in metadata"}
@@ -2761,6 +2837,7 @@ class DownloadManager:
                                bool(persisted.get("use_default_paths", False)),
                                persisted.get("source"),
                                persisted.get("file_params"),
+                                bool(persisted.get("use_save_dir_as_root", False)),
                            ),
                        )
            except Exception as exc:
@@ -6,6 +6,7 @@
 from __future__ import annotations

 import asyncio
+import json
 import logging
 import os
 import sqlite3
@@ -74,6 +75,8 @@ class ModelVersionRecord:
    sort_index: int = 0
    is_early_access: bool = False
    usage_control: Optional[str] = None  # "Download", "Generation", "InternalGeneration"
+    paid_access: Optional[str] = None  # JSON string of the CivitAI paidAccess DTO
+    is_paid: bool = False  # True when paidAccess.permanent is True (permanent paid gate)


@dataclass
@@ -107,13 +110,17 @@ class ModelUpdateRecord:
        return [version.version_id for version in self.versions if version.is_in_library]

    def has_update(
-        self, hide_early_access: bool = False, hide_non_downloadable: bool = True
+        self,
+        hide_early_access: bool = False,
+        hide_non_downloadable: bool = True,
+        hide_paid: bool = False,
    ) -> bool:
        """Return True when a non-ignored remote version newer than the newest local copy is available.

        Args:
            hide_early_access: If True, exclude early access versions from update check.
            hide_non_downloadable: If True, exclude versions that don't allow downloads.
+            hide_paid: If True, exclude permanent paid versions from update check.
        """

        if self.should_ignore_model:
@@ -129,6 +136,7 @@ class ModelUpdateRecord:
                not version.is_in_library
                and not version.should_ignore
                and not (hide_early_access and ModelUpdateRecord._is_early_access_active(version))
+                and not (hide_paid and version.is_paid)
                and not (hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version))
                for version in self.versions
            )
@@ -138,6 +146,8 @@ class ModelUpdateRecord:
                continue
            if hide_early_access and ModelUpdateRecord._is_early_access_active(version):
                continue
+            if hide_paid and version.is_paid:
+                continue
            if hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version):
                continue
            if version.version_id > max_in_library:
@@ -152,6 +162,11 @@ class ModelUpdateRecord:
        1. If exact EA end time available (from single version API), use it for precise check
        2. Otherwise fallback to basic EA flag (from bulk API)
        """
+        # Permanent paid versions are not early access; they are filtered by
+        # hide_paid instead. Only timed gates count as early access.
+        if version.is_paid and not version.early_access_ends_at:
+            return False
+
        # Phase 2: Precise check with exact end time
        if version.early_access_ends_at:
            try:
@@ -178,6 +193,7 @@ class ModelUpdateRecord:
        local_base_model: Optional[str],
        hide_early_access: bool = False,
        hide_non_downloadable: bool = True,
+        hide_paid: bool = False,
    ) -> bool:
        """Return True when a newer remote version with the same base model exists.

@@ -186,6 +202,7 @@ class ModelUpdateRecord:
            local_base_model: The base model to filter by.
            hide_early_access: If True, exclude early access versions from update check.
            hide_non_downloadable: If True, exclude versions that don't allow downloads.
+            hide_paid: If True, exclude permanent paid versions from update check.
        """

        if self.should_ignore_model:
@@ -216,6 +233,8 @@ class ModelUpdateRecord:
                continue
            if hide_early_access and ModelUpdateRecord._is_early_access_active(version):
                continue
+            if hide_paid and version.is_paid:
+                continue
            if hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version):
                continue
            version_base = _normalize_base_model(version.base_model)
@@ -252,6 +271,8 @@ class ModelUpdateService:
            is_in_library INTEGER NOT NULL DEFAULT 0,
            should_ignore INTEGER NOT NULL DEFAULT 0,
            usage_control TEXT,
+            paid_access TEXT,
+            is_paid INTEGER NOT NULL DEFAULT 0,
            PRIMARY KEY (model_id, version_id),
            FOREIGN KEY(model_id) REFERENCES model_update_status(model_id) ON DELETE CASCADE
        );
@@ -491,6 +512,14 @@ class ModelUpdateService:
                "ALTER TABLE model_update_versions "
                "ADD COLUMN usage_control TEXT"
            ),
+            "paid_access": (
+                "ALTER TABLE model_update_versions "
+                "ADD COLUMN paid_access TEXT"
+            ),
+            "is_paid": (
+                "ALTER TABLE model_update_versions "
+                "ADD COLUMN is_paid INTEGER NOT NULL DEFAULT 0"
+            ),
        }

        for column, statement in migrations.items():
@@ -592,6 +621,8 @@ class ModelUpdateService:
                should_ignore INTEGER NOT NULL DEFAULT 0,
                early_access_ends_at TEXT,
                is_early_access INTEGER NOT NULL DEFAULT 0,
+                paid_access TEXT,
+                is_paid INTEGER NOT NULL DEFAULT 0,
                PRIMARY KEY (model_id, version_id),
                FOREIGN KEY(model_id) REFERENCES model_update_status(model_id) ON DELETE CASCADE
            )
@@ -611,6 +642,8 @@ class ModelUpdateService:
            "should_ignore",
            "early_access_ends_at",
            "is_early_access",
+            "paid_access",
+            "is_paid",
        ]
        defaults = {
            "sort_index": "0",
@@ -623,6 +656,8 @@ class ModelUpdateService:
            "should_ignore": "0",
            "early_access_ends_at": "NULL",
            "is_early_access": "0",
+            "paid_access": "NULL",
+            "is_paid": "0",
        }

        select_parts = []
@@ -936,17 +971,30 @@ class ModelUpdateService:
        async with self._lock:
            return self._get_record(model_type, model_id)

-    async def has_update(self, model_type: str, model_id: int, hide_early_access: bool = False) -> bool:
+    async def has_update(
+        self,
+        model_type: str,
+        model_id: int,
+        hide_early_access: bool = False,
+        hide_paid: bool = False,
+    ) -> bool:
        """Determine if a model has updates pending."""

        record = await self.get_record(model_type, model_id)
-        return record.has_update(hide_early_access=hide_early_access) if record else False
+        return (
+            record.has_update(
+                hide_early_access=hide_early_access, hide_paid=hide_paid
+            )
+            if record
+            else False
+        )

    async def has_updates_bulk(
        self,
        model_type: str,
        model_ids: Sequence[int],
        hide_early_access: bool = False,
+        hide_paid: bool = False,
    ) -> Dict[int, bool]:
        """Return update availability for each model id in a single database pass."""

@@ -959,7 +1007,9 @@ class ModelUpdateService:

        return {
            model_id: (
-                records[model_id].has_update(hide_early_access=hide_early_access)
+                records[model_id].has_update(
+                    hide_early_access=hide_early_access, hide_paid=hide_paid
+                )
                if model_id in records
                else False
            )
@@ -1190,6 +1240,7 @@ class ModelUpdateService:
                        "earlyAccessEndsAt": _normalize_string(
                            entry.get("earlyAccessEndsAt")
                        ),
+                        "paidAccess": entry.get("paidAccess"),
                    }
        except RateLimitError:
            raise
@@ -1214,6 +1265,17 @@ class ModelUpdateService:
                    "earlyAccessEndsAt"
                ):
                    version["earlyAccessEndsAt"] = extra["earlyAccessEndsAt"]
+                # Only backfill when the model-level response carries no *active*
+                # paidAccess signal: a present-but-empty DTO (e.g.
+                # {"permanent": false, "endsAt": null}) would otherwise block
+                # the authoritative by-hash data.
+                extra_paid = ModelUpdateService._normalize_paid_access(
+                    extra.get("paidAccess")
+                )
+                if extra_paid and not ModelUpdateService._normalize_paid_access(
+                    version.get("paidAccess")
+                ):
+                    version["paidAccess"] = extra["paidAccess"]

    @staticmethod
    def _collect_hashes_from_response(response: Mapping[str, Any]) -> Dict[int, str]:
@@ -1464,6 +1526,8 @@ class ModelUpdateService:
                    early_access_ends_at=remote_version.early_access_ends_at,
                    is_early_access=remote_version.is_early_access,
                    usage_control=remote_version.usage_control,
+                    paid_access=remote_version.paid_access,
+                    is_paid=remote_version.is_paid,
                )
            )

@@ -1564,6 +1628,18 @@ class ModelUpdateService:
        is_early_access = availability == "EarlyAccess"
        usage_control = _normalize_string(entry.get("usageControl"))

+        # CivitAI's paidAccess DTO ({"permanent": bool, "endsAt": ISO|null})
+        # gates versions behind a paid tier while availability stays "Public".
+        paid_access = self._normalize_paid_access(entry.get("paidAccess"))
+        paid_access_json = json.dumps(paid_access) if paid_access else None
+        is_paid = bool(paid_access.get("permanent")) if paid_access else False
+        if early_access_ends_at is None and paid_access and paid_access.get("endsAt"):
+            early_access_ends_at = _normalize_string(paid_access.get("endsAt"))
+        # Only timed gates are early access; permanent paid versions are not
+        # (consumers filter them via is_paid), so the stored flag stays accurate.
+        if not is_early_access and paid_access and paid_access.get("endsAt"):
+            is_early_access = True
+
        return ModelVersionRecord(
            version_id=version_id,
            name=name,
@@ -1577,8 +1653,36 @@ class ModelUpdateService:
            sort_index=index,
            is_early_access=is_early_access,
            usage_control=usage_control,
+            paid_access=paid_access_json,
+            is_paid=is_paid,
        )

+    @staticmethod
+    def _normalize_paid_access(value) -> Optional[Dict[str, Any]]:
+        """Normalize a CivitAI ``paidAccess`` DTO into a mapping.
+
+        Accepts a dict, None, or a JSON string (as carried by the by-hash
+        enrichment path) and returns ``{"permanent": bool, "endsAt": str|None}``
+        or None when the input carries no paid-access signal.
+        """
+        if value is None:
+            return None
+        if isinstance(value, str):
+            try:
+                parsed = json.loads(value)
+            except (TypeError, ValueError):
+                return None
+            if not isinstance(parsed, dict):
+                return None
+            value = parsed
+        if not isinstance(value, Mapping):
+            return None
+        permanent = bool(value.get("permanent"))
+        ends_at = _normalize_string(value.get("endsAt"))
+        if not permanent and ends_at is None:
+            return None
+        return {"permanent": permanent, "endsAt": ends_at}
+
    def _extract_size_bytes(self, files) -> Optional[int]:
        if not isinstance(files, Iterable):
            return None
@@ -1691,7 +1795,7 @@ class ModelUpdateService:
                    f"""
                    SELECT model_id, version_id, sort_index, name, base_model, released_at,
                           size_bytes, preview_url, is_in_library, should_ignore, early_access_ends_at,
-                           is_early_access, usage_control
+                           is_early_access, usage_control, paid_access, is_paid
                    FROM model_update_versions
                    WHERE model_id IN ({placeholders})
                    ORDER BY model_id ASC, sort_index ASC, version_id ASC
@@ -1720,6 +1824,8 @@ class ModelUpdateService:
                    sort_index=_normalize_int(row["sort_index"]) or 0,
                    is_early_access=bool(row["is_early_access"]),
                    usage_control=row["usage_control"],
+                    paid_access=row["paid_access"],
+                    is_paid=bool(row["is_paid"]),
                )
            )

@@ -1771,13 +1877,19 @@ class ModelUpdateService:
                (record.model_id,),
            )
            for version in record.versions:
+                paid_access_value = (
+                    version.paid_access
+                    if version.paid_access is None
+                    or isinstance(version.paid_access, str)
+                    else json.dumps(version.paid_access)
+                )
                conn.execute(
                    """
                    INSERT INTO model_update_versions (
                        version_id, model_id, sort_index, name, base_model, released_at,
                        size_bytes, preview_url, is_in_library, should_ignore, early_access_ends_at,
-                        is_early_access, usage_control
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                        is_early_access, usage_control, paid_access, is_paid
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                    """,
                    (
                        version.version_id,
@@ -1793,6 +1905,8 @@ class ModelUpdateService:
                        version.early_access_ends_at,
                        1 if version.is_early_access else 0,
                        version.usage_control,
+                        paid_access_value,
+                        1 if version.is_paid else 0,
                    ),
                )
            conn.commit()
@@ -43,7 +43,7 @@ from ..utils import settings_paths
 logger = logging.getLogger(__name__)

 # Undo window in seconds before a staged batch becomes purge-eligible.
-PENDING_DELETE_TTL_SECONDS = 30
+PENDING_DELETE_TTL_SECONDS = 20
 # Hidden staging directory name placed inside each deleted model's own folder
 # (sibling of the model artifacts) and under the settings dir for recipes.
 PENDING_DELETE_DIR_NAME = ".lm-pending-delete"
@@ -8,11 +8,13 @@ import asyncio
 import json
 import logging
 import os
+import random
 import time
 from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Union, cast
 from ..config import config
 from ..utils.constants import VALID_CHECKPOINT_SUB_TYPES, VALID_LORA_TYPES
 from ..utils.file_utils import calculate_autov3
+from ..utils.recipe_open_stats import RecipeOpenStats
 from .recipe_cache import RecipeCache
 from .recipes.errors import RecipeNotFoundError, RecipePersistenceError
 from natsort import natsorted
@@ -34,6 +36,11 @@ logger = logging.getLogger(__name__)
 # explicitly to "diffusion_model" (mirrors Oracle R2-F1).
 _CHECKPOINT_MODEL_TYPE_ALIASES = {"diffusionmodel": "diffusion_model"}

+# Known weight-file extensions stripped by _normalize_filename_key. Names are
+# stored extensionless on both sides, so splitext would misread dotted stems
+# ("my.mix" -> "my") and silently collide distinct models.
+_WEIGHT_FILE_EXTS = (".safetensors", ".ckpt", ".pt", ".pth", ".gguf", ".bin", ".safebin", ".sft")
+

 class RecipeScanner:
    """Service for scanning and managing recipe images"""
@@ -114,6 +121,12 @@ class RecipeScanner:
            self._rematch_autov3_cache: dict[str, dict[str, Any]] | None = None
            self._rematch_autov3_versions: tuple[int, int] | None = None
            self._rematch_autov3_lock = asyncio.Lock()
+            # Normalized filename -> [items] map for the L4 rematch fallback,
+            # rebuilt only when either model scanner's cache_version changes.
+            # Mirrors the build_local_hash_cache version pattern.
+            self._local_filename_cache: dict[str, list[dict[str, Any]]] | None = None
+            self._local_filename_cache_versions: tuple[int, int] | None = None
+            self._local_filename_cache_lock = asyncio.Lock()
            self._initialized = True

    async def build_local_hash_cache(self) -> dict[str, dict[str, Any]]:
@@ -160,6 +173,70 @@ class RecipeScanner:
            self._local_hash_cache_versions = versions
            return cache

+    @staticmethod
+    def _normalize_filename_key(name: str) -> str:
+        """Normalize a file name to a lookup key (basename, lowercase).
+
+        Only known weight-file extensions are stripped — names are stored
+        extensionless on both sides, so splitext would misread dotted stems
+        ("my.mix" -> "my") and collide distinct models.
+        """
+        if not name:
+            return ""
+        basename = os.path.basename(name.replace("\\", "/"))
+        lower = basename.lower()
+        for ext in _WEIGHT_FILE_EXTS:
+            if lower.endswith(ext):
+                basename = basename[: -len(ext)]
+                break
+        return basename.strip().lower()
+
+    async def _build_local_filename_cache(self) -> dict[str, list[dict[str, Any]]]:
+        """Build a version-cached map of normalized file names to local items.
+
+        Keys are lowercase basenames without extension. Values are lists of
+        items (lora + checkpoint, type-blind) sharing that name. Only items
+        with a sha256 are indexed — matching a pending or failed download
+        (empty sha256) would leave the entry without a usable hash. The dict
+        is reused while both scanners' cache_version values are unchanged;
+        concurrent callers share a single build via the lock.
+        """
+        async with self._local_filename_cache_lock:
+            lora_scanner = self._lora_scanner
+            checkpoint_scanner = self._checkpoint_scanner
+            versions = (
+                lora_scanner.cache_version if lora_scanner is not None else 0,
+                checkpoint_scanner.cache_version
+                if checkpoint_scanner is not None
+                else 0,
+            )
+            if (
+                self._local_filename_cache is not None
+                and self._local_filename_cache_versions == versions
+            ):
+                return self._local_filename_cache
+
+            cache: dict[str, list[dict[str, Any]]] = {}
+            for scanner in (lora_scanner, checkpoint_scanner):
+                if scanner is None:
+                    continue
+                data = await scanner.get_cached_data()
+                for item in data.raw_data:
+                    if not isinstance(item, dict):
+                        continue
+                    if not (item.get("sha256") or "").lower():
+                        continue
+                    file_path = item.get("file_path") or ""
+                    file_name = item.get("file_name") or ""
+                    key = self._normalize_filename_key(file_name or file_path)
+                    if not key:
+                        continue
+                    cache.setdefault(key, []).append(item)
+
+            self._local_filename_cache = cache
+            self._local_filename_cache_versions = versions
+            return cache
+
    def _is_rematch_candidate(self, entry: dict[str, Any]) -> bool:
        """Return True when a recipe entry is eligible for local re-matching."""
        if not isinstance(entry, dict):
@@ -168,7 +245,10 @@ class RecipeScanner:
            entry.get("isDeleted") or not entry.get("hash") or not entry.get("file_name")
        )
        has_identifier = (
-            entry.get("hash") or entry.get("modelVersionId") or entry.get("id")
+            entry.get("hash")
+            or entry.get("modelVersionId")
+            or entry.get("id")
+            or entry.get("file_name")
        )
        return bool(unresolved and has_identifier)

@@ -219,6 +299,97 @@ class RecipeScanner:
            self._rematch_autov3_versions = versions
            return cache

+    def _is_type_compatible(self, item: dict[str, Any], *, is_checkpoint: bool) -> bool:
+        """Return True when a local item's type matches the entry kind.
+
+        The L1 hash cache and the L4 filename cache merge lora and checkpoint
+        items and are type-blind, so a match must be verified against the
+        entry kind before it is accepted.
+        """
+        sub_type = (item.get("sub_type") or "").lower()
+        if sub_type:
+            valid = (
+                VALID_CHECKPOINT_SUB_TYPES if is_checkpoint else VALID_LORA_TYPES
+            )
+            return sub_type in valid
+
+        civitai_type = (
+            (item.get("civitai") or {}).get("model", {}) or {}
+        ).get("type", "")
+        if civitai_type:
+            normalized = civitai_type.lower()
+            if is_checkpoint:
+                normalized = _CHECKPOINT_MODEL_TYPE_ALIASES.get(
+                    normalized, normalized
+                )
+                valid = VALID_CHECKPOINT_SUB_TYPES
+            else:
+                valid = VALID_LORA_TYPES
+            return normalized in valid
+        return True
+
+    @staticmethod
+    def _has_positive_type_evidence(item: dict[str, Any]) -> bool:
+        """Return True when the item carries an explicit type marker.
+
+        Lora raw items rarely carry ``sub_type`` (it is only written when
+        metadata provides it), while checkpoint items always do — so for
+        checkpoint slots a type-less candidate is a red flag, not the norm.
+        """
+        if (item.get("sub_type") or "").lower():
+            return True
+        civitai_type = (
+            (item.get("civitai") or {}).get("model", {}) or {}
+        ).get("type", "")
+        return bool(civitai_type)
+
+    def _match_rematch_entry_filename(
+        self,
+        entry: dict[str, Any],
+        recipe_base_model: Optional[str],
+        filename_cache: dict[str, list[dict[str, Any]]],
+        *,
+        is_checkpoint: bool,
+    ) -> Tuple[Optional[dict[str, Any]], Optional[str]]:
+        """Match a recipe entry against local models by file name (L4).
+
+        Conservative fallback used only after the hash (L1), version-index
+        (L2) and computed-autov3 (L3) tiers all failed. Candidates share the
+        entry's normalized file name; a candidate is accepted only when BOTH
+        the recipe base model and the candidate's base model are known and
+        equal (unknown on either side rejects — never guess on missing
+        metadata), the type gate passes, and exactly one candidate survives
+        (ambiguity is a miss). Checkpoint slots additionally require positive
+        type evidence: lora raw items often lack ``sub_type`` while
+        checkpoints always carry it, so a type-less candidate is a red flag
+        there — an unknown-type lora must not be bound into a checkpoint
+        slot.
+
+        Returns:
+            Tuple of (matched item, "L4") — or ``(None, None)``.
+        """
+        entry_name = self._normalize_filename_key(entry.get("file_name") or "")
+        if not entry_name:
+            return (None, None)
+
+        recipe_base = (recipe_base_model or "").strip().lower()
+        matched: list[dict[str, Any]] = []
+        for candidate in filename_cache.get(entry_name, []):
+            candidate_base = (candidate.get("base_model") or "").strip().lower()
+            if not recipe_base or not candidate_base:
+                continue
+            if recipe_base != candidate_base:
+                continue
+            if is_checkpoint and not self._has_positive_type_evidence(candidate):
+                continue
+            if not self._is_type_compatible(candidate, is_checkpoint=is_checkpoint):
+                continue
+            matched.append(candidate)
+
+        if len(matched) != 1:
+            return (None, None)
+        return (matched[0], "L4")
+
    async def _match_rematch_entry(
        self,
        entry: dict[str, Any],
@@ -245,19 +416,23 @@ class RecipeScanner:
        autov3_cache: dict[str, Any],
        *,
        is_checkpoint: bool,
+        filename_cache: Optional[dict[str, list[dict[str, Any]]]] = None,
+        recipe_base_model: Optional[str] = None,
    ) -> Tuple[Optional[dict[str, Any]], Optional[str]]:
-        """Match a recipe entry against local models across three levels.
+        """Match a recipe entry against local models across four levels.

        L1 looks the stored hash up in the type-blind local hash cache; L2
        falls back to the version index via ``modelVersionId`` or ``id``; L3
-        resolves 12-char hashes through the computed AutoV3 cache. Matched
-        items are type-verified against the entry kind before being returned.
+        resolves 12-char hashes through the computed AutoV3 cache; L4
+        (conservative) falls back to the file name when a filename cache is
+        provided. Matched items are type-verified against the entry kind
+        before being returned.

        Returns:
-            Tuple of (matched item, match level) where level is "L1", "L2" or
-            "L3" — or ``(None, None)`` when no usable match exists. A missing
-            local match is an expected outcome (the model may simply not be
-            present locally), not an error.
+            Tuple of (matched item, match level) where level is "L1", "L2",
+            "L3" or "L4" — or ``(None, None)`` when no usable match exists. A
+            missing local match is an expected outcome (the model may simply
+            not be present locally), not an error.
        """
        entry_hash = (entry.get("hash") or "").lower()

@@ -277,33 +452,20 @@ class RecipeScanner:
            item = autov3_cache.get(entry_hash)
            level = "L3" if item is not None else None

+        if item is None and filename_cache is not None:
+            item, level = self._match_rematch_entry_filename(
+                entry,
+                recipe_base_model,
+                filename_cache,
+                is_checkpoint=is_checkpoint,
+            )
+            level = "L4" if item is not None else None
+
        if item is None:
            return (None, None)

-        # Type gate: the L1 cache merges lora and checkpoint items and is
-        # type-blind, so a match must be verified against the entry kind.
-        sub_type = (item.get("sub_type") or "").lower()
-        if sub_type:
-            valid = (
-                VALID_CHECKPOINT_SUB_TYPES if is_checkpoint else VALID_LORA_TYPES
-            )
-            if sub_type not in valid:
-                return (None, None)
-        else:
-            civitai_type = (
-                (item.get("civitai") or {}).get("model", {}) or {}
-            ).get("type", "")
-            if civitai_type:
-                normalized = civitai_type.lower()
-                if is_checkpoint:
-                    normalized = _CHECKPOINT_MODEL_TYPE_ALIASES.get(
-                        normalized, normalized
-                    )
-                    valid = VALID_CHECKPOINT_SUB_TYPES
-                else:
-                    valid = VALID_LORA_TYPES
-                if normalized not in valid:
-                    return (None, None)
+        if not self._is_type_compatible(item, is_checkpoint=is_checkpoint):
+            return (None, None)

        return (item, level)

@@ -615,10 +777,11 @@ class RecipeScanner:
    async def _rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
        """Rematch a single recipe's deleted lora/checkpoint entries locally.

-        Match snapshots (local hash cache + computed autov3 cache) are built
-        BEFORE acquiring the mutation lock — both are read-only snapshots and
-        the version-cached hash dict would otherwise rebuild mid-run if a scan
-        bumps a scanner's cache_version while we hold the lock.
+        Match snapshots (local hash cache, computed autov3 cache, filename
+        cache) are built BEFORE acquiring the mutation lock — all three are
+        read-only snapshots and the version-cached dicts would otherwise
+        rebuild mid-run if a scan bumps a scanner's cache_version while we
+        hold the lock.

        Args:
            recipe_id: ID of the recipe to rematch
@@ -634,6 +797,7 @@ class RecipeScanner:
        """
        local_cache = await self.build_local_hash_cache()
        autov3_cache = await self._build_rematch_autov3_cache()
+        filename_cache = await self._build_local_filename_cache()

        async with self._mutation_lock:
            # Get raw recipe from cache directly to avoid formatted fields
@@ -647,7 +811,7 @@ class RecipeScanner:

            try:
                rematched, _errors, details = await self._rematch_single_recipe(
-                    recipe, local_cache, autov3_cache
+                    recipe, local_cache, autov3_cache, filename_cache
                )
            except RecipePersistenceError as exc:
                logger.error(
@@ -704,6 +868,7 @@ class RecipeScanner:
        recipe: Dict[str, Any],
        local_cache: dict[str, dict[str, Any]],
        autov3_cache: dict[str, dict[str, Any]],
+        filename_cache: Optional[dict[str, list[dict[str, Any]]]] = None,
    ) -> Tuple[int, int, Dict[str, Any]]:
        """Rematch a single recipe's lora/checkpoint entries against local models.

@@ -717,6 +882,8 @@ class RecipeScanner:
            recipe: The recipe dictionary to rematch (modified in-place)
            local_cache: L1 hash cache snapshot (build_local_hash_cache)
            autov3_cache: L3 computed-autov3 cache snapshot
+            filename_cache: L4 filename cache snapshot, or None to disable
+                the filename fallback

        Returns:
            Tuple of (rematched_entries, errors, details). The errors element
@@ -742,7 +909,13 @@ class RecipeScanner:
                if not self._is_rematch_candidate(entry):
                    continue
                item, level = await self._match_rematch_entry_with_level(
-                    entry, local_cache, autov3_cache, is_checkpoint=False
+                    entry,
+                    local_cache,
+                    autov3_cache,
+                    is_checkpoint=False,
+                    filename_cache=filename_cache,
+                    recipe_base_model=entry.get("baseModel")
+                    or recipe.get("base_model"),
                )
                if item is None:
                    details["unresolved"].append(
@@ -768,7 +941,13 @@ class RecipeScanner:
        if isinstance(checkpoint, dict):
            if self._is_rematch_candidate(checkpoint):
                item, level = await self._match_rematch_entry_with_level(
-                    checkpoint, local_cache, autov3_cache, is_checkpoint=True
+                    checkpoint,
+                    local_cache,
+                    autov3_cache,
+                    is_checkpoint=True,
+                    filename_cache=filename_cache,
+                    recipe_base_model=checkpoint.get("baseModel")
+                    or recipe.get("base_model"),
                )
                if item is None:
                    details["unresolved"].append(
@@ -830,12 +1009,13 @@ class RecipeScanner:
    ) -> Dict[str, Any]:
        """Rematch every recipe's deleted lora/checkpoint entries locally.

-        Match snapshots (local hash cache + computed autov3 cache) are built
-        ONCE before the loop — both are read-only and the version-cached hash
-        dict would otherwise rebuild mid-run if a scan bumps a scanner's
-        cache_version while the mutation lock is held. ``_schedule_resort`` is
-        called exactly once after the loop: it spawns an asyncio task per call,
-        so per-recipe calls would race one resort task per recipe.
+        Match snapshots (local hash cache, computed autov3 cache, filename
+        cache) are built ONCE before the loop — all three are read-only and
+        the version-cached dicts would otherwise rebuild mid-run if a scan
+        bumps a scanner's cache_version while the mutation lock is held.
+        ``_schedule_resort`` is called exactly once after the loop: it spawns
+        an asyncio task per call, so per-recipe calls would race one resort
+        task per recipe.

        Args:
            progress_callback: Optional callback for progress updates
@@ -856,6 +1036,7 @@ class RecipeScanner:
        # Match snapshots built once and shared by every recipe in the loop.
        local_cache = await self.build_local_hash_cache()
        autov3_cache = await self._build_rematch_autov3_cache()
+        filename_cache = await self._build_local_filename_cache()

        async with self._mutation_lock:
            cache = await self.get_cached_data()
@@ -923,7 +1104,7 @@ class RecipeScanner:
                        )

                    rematched, _errors, details = await self._rematch_single_recipe(
-                        recipe, local_cache, autov3_cache
+                        recipe, local_cache, autov3_cache, filename_cache
                    )
                    if rematched > 0:
                        matched_recipes += 1
@@ -2781,7 +2962,11 @@ class RecipeScanner:
        Args:
            page: Current page number (1-based)
            page_size: Number of items per page
-            sort_by: Sort method ('name' or 'date')
+            sort_by: Sort method ('name', 'date', 'loras_count', 'opened',
+                or 'random' with an optional seed like 'random:abc123'; the
+                part after 'random:' is the shuffle seed, not a direction).
+                'opened' hides recipes that were never opened — it is a
+                "recently opened" view, not a plain reorder
            search: Search term
            filters: Dictionary of filters to apply
            search_options: Dictionary of search options to apply
@@ -2962,7 +3147,7 @@ class RecipeScanner:
                        ]

        # Apply sorting if not already handled by pre-sorted cache
-        if ":" in sort_by or sort_field == "loras_count":
+        if ":" in sort_by or sort_field in ("loras_count", "random", "opened"):
            field, order = (sort_by.split(":") + ["desc"])[:2]
            reverse = order.lower() == "desc"

@@ -2981,10 +3166,30 @@ class RecipeScanner:
                    ),
                    reverse=reverse,
                )
+            elif field == "opened":
+                # "Recently Opened" view: recipes never opened are hidden.
+                # The open stats live outside recipe metadata; see
+                # RecipeOpenStats.
+                opened_map = RecipeOpenStats().get_opened_map()
+                filtered_data = [
+                    item
+                    for item in filtered_data
+                    if opened_map.get(str(item.get("id", ""))) is not None
+                ]
+                filtered_data.sort(
+                    key=lambda x: opened_map.get(str(x.get("id", "")), 0),
+                    reverse=reverse,
+                )
            elif field == "loras_count":
                filtered_data.sort(
                    key=lambda x: len(x.get("loras", [])), reverse=reverse
                )
+            elif field == "random":
+                # Seeded random shuffle: same seed -> same order (stable
+                # pagination across requests), matching the model pages.
+                seed = order if order.lower() not in ("asc", "desc") else None
+                rng = random.Random(seed or "random")
+                rng.shuffle(filtered_data)

        # Calculate pagination
        total_items = len(filtered_data)
@@ -62,6 +62,20 @@ MODEL_FILE_EXTENSIONS = {
    ".gguf",
 }

+# CivitAI ModelFile.type values eligible as the main download file.
+# Mirrors CivitAI's getPrimaryFile() (model-helpers.ts): weight types are
+# preferred, but any file CivitAI marks `primary` is accepted — newer types
+# like 'Enhancement LoRA' (Anima/AIR image-editing LoRAs) are valid primary
+# files despite not being in the traditional weights allowlist.
+MODEL_WEIGHT_FILE_TYPES = (
+    "Model",
+    "Pruned Model",
+    "Negative",
+    "UNet",
+    "Diffusion Model",
+    "Enhancement LoRA",
+)
+
 # Valid sub-types for each scanner type
 VALID_LORA_SUB_TYPES = ["lora", "locon", "dora"]
 VALID_CHECKPOINT_SUB_TYPES = ["checkpoint", "diffusion_model"]
@@ -0,0 +1,161 @@
+"""Track recipe modal open timestamps for the "Recently Opened" sort.
+
+The data is deliberately kept OUTSIDE the recipe metadata files: recording an
+open must be cheap and must never rewrite recipe JSON or EXIF (which the
+generic metadata update path does). A tiny JSON map of
+``recipe_id -> unix timestamp`` lives under
+``{settings_dir}/stats/recipe_last_opened.json`` and is written atomically on
+a short debounce.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import time
+
+from ..utils.settings_paths import get_settings_dir
+
+logger = logging.getLogger(__name__)
+
+
+class RecipeOpenStats:
+    """Persist the last time each recipe was opened in the recipe modal."""
+
+    STATS_FILENAME: str = "recipe_last_opened.json"
+    SAVE_DELAY: float = 1.0  # seconds of debounce between consecutive writes
+
+    _instance: "RecipeOpenStats | None" = None
+    _opened: dict[str, float]
+    _file_mtime: float | None
+    _dirty: bool
+    _lock: asyncio.Lock
+    _save_task: "asyncio.Task[None] | None"
+    _stats_file_path: str
+    _initialized: bool
+
+    def __new__(cls) -> "RecipeOpenStats":
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self) -> None:
+        if getattr(self, "_initialized", False):
+            return
+        self._opened = {}
+        self._file_mtime = None
+        self._dirty = False
+        self._lock = asyncio.Lock()
+        self._save_task = None
+        self._stats_file_path = self._get_stats_file_path()
+        self._load_stats()
+        self._initialized = True
+
+    def _get_stats_file_path(self) -> str:
+        settings_dir = get_settings_dir(create=True)
+        return os.path.join(settings_dir, "stats", self.STATS_FILENAME)
+
+    def _load_stats(self) -> None:
+        """Load the opened map from disk, tolerating corrupt/absent files.
+
+        The mtime is recorded even when parsing fails so a corrupt file is
+        not re-read (and re-logged) on every lookup.
+        """
+        if not os.path.exists(self._stats_file_path):
+            return
+        try:
+            mtime = os.path.getmtime(self._stats_file_path)
+        except OSError:
+            return
+        try:
+            with open(self._stats_file_path, "r", encoding="utf-8") as file_obj:
+                raw = json.load(file_obj)
+            if isinstance(raw, dict):
+                self._opened = {
+                    str(key): float(value)
+                    for key, value in raw.items()
+                    if isinstance(value, (int, float))
+                }
+        except Exception as exc:  # pragma: no cover - defensive logging path
+            logger.error("Error loading recipe open stats: %s", exc)
+            self._opened = {}
+        self._file_mtime = mtime
+
+    def get_opened_map(self) -> dict[str, float]:
+        """Return a copy of ``recipe_id -> last opened timestamp``.
+
+        Refreshes from disk when the file changed since the last load so a
+        second server process (or manual edit) is picked up without restart.
+        """
+        try:
+            if os.path.exists(self._stats_file_path):
+                mtime = os.path.getmtime(self._stats_file_path)
+                if self._file_mtime is None or mtime != self._file_mtime:
+                    self._load_stats()
+        except OSError:
+            pass
+        return dict(self._opened)
+
+    def record_open(self, recipe_id: str) -> None:
+        """Mark a recipe as opened now; persists shortly in the background."""
+        if not recipe_id:
+            return
+        self._opened[str(recipe_id)] = time.time()
+        self._dirty = True
+        if self._save_task is None or self._save_task.done():
+            self._save_task = asyncio.create_task(self._delayed_save())
+
+    async def _delayed_save(self) -> None:
+        """Debounced writer: batches rapid consecutive opens into one write."""
+        await asyncio.sleep(self.SAVE_DELAY)
+        _ = await self.save_stats()
+
+    async def save_stats(self, force: bool = False) -> bool:
+        """Persist the opened map atomically if dirty (or when forced).
+
+        The on-disk map is merged in first so a second process sharing the
+        settings dir does not lose its entries; the larger timestamp wins
+        per recipe.
+        """
+        if not force and not self._dirty:
+            return False
+        async with self._lock:
+            if not force and not self._dirty:
+                return False
+            try:
+                merged = self._merge_with_disk()
+                os.makedirs(os.path.dirname(self._stats_file_path), exist_ok=True)
+                temp_path = f"{self._stats_file_path}.tmp"
+                with open(temp_path, "w", encoding="utf-8") as file_obj:
+                    json.dump(merged, file_obj, indent=2)
+                os.replace(temp_path, self._stats_file_path)
+                self._opened = merged
+                self._file_mtime = os.path.getmtime(self._stats_file_path)
+                self._dirty = False
+                return True
+            except Exception as exc:  # pragma: no cover - defensive logging path
+                logger.error("Error saving recipe open stats: %s", exc, exc_info=True)
+                return False
+
+    def _merge_with_disk(self) -> dict[str, float]:
+        """Merge the in-memory map with the current on-disk map."""
+        disk: dict[str, float] = {}
+        try:
+            if os.path.exists(self._stats_file_path):
+                with open(self._stats_file_path, "r", encoding="utf-8") as file_obj:
+                    raw = json.load(file_obj)
+                if isinstance(raw, dict):
+                    disk = {
+                        str(key): float(value)
+                        for key, value in raw.items()
+                        if isinstance(value, (int, float))
+                    }
+        except Exception as exc:  # pragma: no cover - defensive logging path
+            logger.error("Error reading recipe open stats for merge: %s", exc)
+        merged = dict(disk)
+        for key, value in self._opened.items():
+            merged[key] = max(value, disk.get(key, 0.0))
+        return merged
@@ -323,6 +323,42 @@ def model_patcher_to_name(model_patcher: Any) -> Optional[str]:
    return _abs_model_path_to_name(abs_path)


+def sampler_object_to_name(sampler: Any) -> Optional[str]:
+    """Extract a ComfyUI-style sampler name from a SAMPLER (KSAMPLER) object.
+
+    Standard outputs (KSamplerSelect, most built-in sampler nodes) round-trip
+    losslessly via the underlying sampler function's ``__name__``
+    (``sample_euler`` -> ``euler``). A few edge cases need special-casing
+    because the function name diverges from the ``SAMPLER_NAMES`` entry:
+
+      - ``dpm_fast`` / ``dpm_adaptive`` are local closures inside
+        ``comfy.samplers.ksampler`` (``dpm_fast_function`` / ``dpm_adaptive_function``)
+      - ``uni_pc`` / ``uni_pc_bh2`` use ``sample_unipc`` / ``sample_unipc_bh2``
+
+    ``ddim`` is constructed by ComfyUI as ``euler`` with random inpaint, so
+    the original ``ddim`` name is unrecoverable (extracts as ``euler``).
+    Custom sampler nodes that pass non-``sample_*`` functions return None.
+
+    Returns None when the name cannot be recovered.
+    """
+    sampler_function = getattr(sampler, "sampler_function", None)
+    func_name = getattr(sampler_function, "__name__", None)
+    if not isinstance(func_name, str) or not func_name:
+        return None
+    if func_name == "dpm_fast_function":
+        return "dpm_fast"
+    if func_name == "dpm_adaptive_function":
+        return "dpm_adaptive"
+    if func_name.startswith("sample_"):
+        name = func_name[len("sample_"):]
+        if name == "unipc":
+            return "uni_pc"
+        if name == "unipc_bh2":
+            return "uni_pc_bh2"
+        return name or None
+    return None
+
+
 def _abs_model_path_to_name(abs_path: str) -> str:
    """Convert an absolute model path to a ComfyUI-style relative name.

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.2.0"
+version = "1.2.1"
 license = {file = "LICENSE"}
 dependencies = [
    "aiohttp",
@@ -41,6 +41,11 @@
    border-color: var(--lora-accent);
 }

+.model-card.drag-over {
+    outline: 2px dashed var(--lora-accent);
+    outline-offset: -2px;
+}
+
 .model-card:focus-visible {
    outline: 2px solid var(--lora-accent);
    outline-offset: 2px;
@@ -447,6 +447,19 @@
    border-color: color-mix(in oklch, #F59F00 45%, transparent);
 }

+/* Paid badge - violet tone (#845EF7) to distinguish from early-access amber */
+.version-badge-paid {
+    background: color-mix(in oklch, #845EF7 25%, transparent);
+    color: #7048E8;
+    border-color: color-mix(in oklch, #845EF7 55%, transparent);
+}
+
+[data-theme="dark"] .version-badge-paid {
+    background: color-mix(in oklch, #845EF7 20%, transparent);
+    color: #9775FA;
+    border-color: color-mix(in oklch, #845EF7 45%, transparent);
+}
+
 .version-meta-ea {
    color: #E67700;
    font-weight: 600;
@@ -911,6 +911,93 @@
    outline: none;
 }

+/* Recipes layout segmented control with visual previews */
+.layout-options-control {
+    width: 100%;
+    display: flex;
+    justify-content: flex-end;
+}
+
+.layout-options {
+    display: flex;
+    gap: 6px;
+    width: 100%;
+}
+
+.layout-option {
+    flex: 1;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    gap: 6px;
+    padding: 8px;
+    border-radius: var(--border-radius-sm);
+    border: 1px solid var(--border-color);
+    background-color: var(--lora-surface);
+    color: var(--text-color);
+    cursor: pointer;
+    transition: border-color 0.2s ease, background-color 0.2s ease;
+}
+
+.layout-option:hover,
+.layout-option:focus-visible {
+    border-color: var(--lora-accent);
+    outline: none;
+}
+
+.layout-option.active {
+    border-color: var(--lora-accent);
+    background-color: rgba(from var(--lora-accent) r g b / 0.12);
+    color: var(--lora-accent);
+}
+
+.layout-option-label {
+    font-size: 0.85em;
+    white-space: nowrap;
+}
+
+.layout-option-preview {
+    width: 72px;
+    height: 44px;
+    padding: 4px;
+    border-radius: var(--border-radius-xs);
+    background-color: var(--card-bg);
+    border: 1px solid var(--border-color);
+    box-sizing: border-box;
+}
+
+.layout-option-preview span {
+    background: currentColor;
+    opacity: 0.4;
+    border-radius: 1px;
+}
+
+.layout-preview-grid {
+    display: grid;
+    grid-template-columns: 1fr 1fr;
+    grid-template-rows: 1fr 1fr;
+    gap: 3px;
+}
+
+.layout-preview-masonry {
+    display: flex;
+    gap: 3px;
+    align-items: flex-start;
+}
+
+.layout-preview-masonry span {
+    flex: 1;
+    height: 100%;
+}
+
+.layout-preview-masonry span:nth-child(2) {
+    height: 60%;
+}
+
+.layout-preview-masonry span:nth-child(3) {
+    height: 80%;
+}
+
 /* Range Slider Control */
 .range-control {
    width: 100%;
@@ -107,6 +107,24 @@
    white-space: nowrap;
 }

+.toast-close-btn {
+    flex-shrink: 0;
+    padding: 0 4px;
+    background: transparent;
+    color: var(--text-color);
+    border: none;
+    border-radius: 4px;
+    font-size: 1.1em;
+    line-height: 1;
+    opacity: 0.5;
+    cursor: pointer;
+    transition: opacity 0.2s ease;
+}
+
+.toast-close-btn:hover {
+    opacity: 1;
+}
+
 /* Responsive adjustments */
@media (max-width: 768px) {
    .toast {
@@ -168,6 +168,34 @@
    border-color: var(--lora-accent);
 }

+/* Recipes layout toggle (grid / masonry) — segmented control in the toolbar */
+.layout-toggle-group {
+    display: flex;
+    gap: 0;
+}
+
+.layout-toggle-group .layout-toggle-btn {
+    min-width: 36px;
+    width: 36px;
+    padding: 4px 0;
+    border-radius: 0;
+}
+
+.layout-toggle-group .layout-toggle-btn:first-child {
+    border-radius: var(--border-radius-xs) 0 0 var(--border-radius-xs);
+    border-right: none;
+}
+
+.layout-toggle-group .layout-toggle-btn:last-child {
+    border-radius: 0 var(--border-radius-xs) var(--border-radius-xs) 0;
+}
+
+.layout-toggle-group .layout-toggle-btn:hover,
+.layout-toggle-group .layout-toggle-btn:focus-visible {
+    transform: none;
+    box-shadow: var(--shadow-xs);
+}
+
 /* Keyboard shortcut indicator styling */
 .shortcut-key {
    display: inline-flex;
@@ -1233,7 +1233,7 @@ export class BaseModelApiClient {
        }
    }

-    async downloadModel(modelId, versionId, modelRoot, relativePath, useDefaultPaths = false, downloadId, source = null, fileParams = null) {
+    async downloadModel(modelId, versionId, modelRoot, relativePath, useDefaultPaths = false, downloadId, source = null, fileParams = null, useSaveDirAsRoot = false) {
        try {
            const response = await fetch(DOWNLOAD_ENDPOINTS.download, {
                method: 'POST',
@@ -1244,6 +1244,7 @@ export class BaseModelApiClient {
                    model_root: modelRoot,
                    relative_path: relativePath,
                    use_default_paths: useDefaultPaths,
+                    use_save_dir_as_root: useSaveDirAsRoot,
                    download_id: downloadId,
                    ...(source ? { source } : {}),
                    ...(fileParams ? { file_params: fileParams } : {})
@@ -1,6 +1,7 @@
 import { BaseContextMenu } from './BaseContextMenu.js';
 import { ModelContextMenuMixin } from './ModelContextMenuMixin.js';
 import { showToast, copyToClipboard, sendLoraToWorkflow } from '../../utils/uiHelpers.js';
+import { isModelWeightFile } from '../../utils/modelFileTypes.js';
 import { setSessionItem, removeSessionItem } from '../../utils/storageHelpers.js';
 import { updateRecipeMetadata } from '../../api/recipeApi.js';
 import { state } from '../../state/index.js';
@@ -255,7 +256,7 @@ export class RecipeContextMenu extends BaseContextMenu {
                loras: validLoras.map(lora => {
                    const civitaiInfo = lora.civitaiInfo;
                    const modelFile = civitaiInfo.files ?
-                        civitaiInfo.files.find(file => file.type === 'Model') : null;
+                        civitaiInfo.files.find(file => isModelWeightFile(file.type)) : null;

                    return {
                        // Basic lora info
@@ -1,5 +1,6 @@
 // Recipe Modal Component
 import { showToast, copyToClipboard, sendLoraToWorkflow, sendModelPathToWorkflow, openCivitaiByMetadata, stripLoraTags, sendPromptToWorkflow, sendGenParamsToWorkflow } from '../utils/uiHelpers.js';
+import { isModelWeightFile } from '../utils/modelFileTypes.js';
 import { translate } from '../utils/i18nHelpers.js';
 import { state } from '../state/index.js';
 import { setSessionItem, removeSessionItem, getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
@@ -305,6 +306,14 @@ class RecipeModal {
        modalManager.showModal('recipeModal');

        if (this.recipeId) {
+            // Fire-and-forget: record this open for the "Recently Opened"
+            // sort. Tracking must never disturb the modal, so failures are
+            // swallowed.
+            fetch(`/api/lm/recipe/${encodeURIComponent(this.recipeId)}/opened`, {
+                method: 'POST',
+                keepalive: true,
+            }).catch(() => {});
+
            const hydrationRequestId = ++this.recipeHydrationRequestId;
            const requestEditVersions = this.captureLocalEditVersions();
            this.hydrateRecipeDetails(
@@ -1412,7 +1421,7 @@ class RecipeModal {
                loras: validLoras.map(lora => {
                    const civitaiInfo = lora.civitaiInfo;
                    const modelFile = civitaiInfo.files ?
-                        civitaiInfo.files.find(file => file.type === 'Model') : null;
+                        civitaiInfo.files.find(file => isModelWeightFile(file.type)) : null;

                    return {
                        // Basic lora info
@@ -4,7 +4,7 @@ import { getStorageItem, setStorageItem, removeStorageItem, getSessionItem, setS
 import { showToast, openCivitaiByMetadata } from '../../utils/uiHelpers.js';
 import { performModelUpdateCheck } from '../../utils/updateCheckHelpers.js';
 import { sidebarManager } from '../SidebarManager.js';
-import { initSortDropdown } from './SortDropdown.js';
+import { initSortDropdown, applySortToSelect, randomizeSortValue } from './SortDropdown.js';

 /**
 * PageControls class - Unified control management for model pages
@@ -108,20 +108,20 @@ export class PageControls {
        const sortSelect = document.getElementById('sortSelect');
        if (sortSelect) {
            initSortDropdown(sortSelect);
-            this.applySortToSelect(this.pageState.sortBy);
+            applySortToSelect(this.pageState.sortBy);
            sortSelect.addEventListener('change', async (e) => {
                let value = 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();
+                    value = 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);
+                applySortToSelect(value);
                await this.resetAndReload();
            });
        }
@@ -322,44 +322,6 @@ 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
     */
@@ -374,7 +336,7 @@ export class PageControls {
            // Handle legacy format conversion
            const convertedSort = this.convertLegacySortFormat(savedSort);
            this.pageState.sortBy = convertedSort;
-            this.applySortToSelect(convertedSort);
+            applySortToSelect(convertedSort);
        }
    }
    
@@ -568,7 +530,7 @@ export class PageControls {
        this.pageState.sortBy = restoredSort;
        this.saveSortPreference(restoredSort);
        this._removeVlmSortOption();
-        this.applySortToSelect(restoredSort);
+        applySortToSelect(restoredSort);
        const sortSelect = document.getElementById('sortSelect');
        if (sortSelect) {
            sortSelect.disabled = false;
@@ -620,7 +582,7 @@ export class PageControls {
            const savedGroupedSort = getStorageItem(groupedKey);
            if (savedGroupedSort) {
                this.pageState.sortBy = savedGroupedSort;
-                this.applySortToSelect(savedGroupedSort);
+                applySortToSelect(savedGroupedSort);
            }
        } else {
            // Leaving group mode: persist current sort for next time, restore non-group sort
@@ -628,7 +590,7 @@ export class PageControls {
            const savedNormalSort = getStorageItem(`${this.pageType}_sort`);
            if (savedNormalSort) {
                this.pageState.sortBy = savedNormalSort;
-                this.applySortToSelect(savedNormalSort);
+                applySortToSelect(savedNormalSort);
            }
        }
    }
@@ -913,7 +875,7 @@ export class PageControls {
        }

        if (sortSelect) {
-            this.applySortToSelect(this.pageState.sortBy);
+            applySortToSelect(this.pageState.sortBy);
        }
        if (searchInput) {
            searchInput.value = this.pageState.filters?.search || '';
@@ -18,6 +18,44 @@
 const SORT_GROUP_SELECTOR = '.sort-dropdown-group';
 const ACTIVE_GROUP_SELECTOR = '.sort-dropdown-group.active, .dropdown-group.active';

+/**
+ * Apply a sort value to the page's 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>"
+ */
+export function 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"
+ */
+export function 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;
+}
+
 /**
 * Initialize a decoupled sort dropdown around a native <select>.
 * Idempotent: safe to call more than once on the same element.
@@ -741,6 +741,46 @@ export function createModelCard(model, modelType) {
        configureModelCardVideo(videoElement, autoplayOnHover);
    }

+    // Dropping an image/video onto the card replaces the model preview via the
+    // existing replace-preview endpoint (overwrites file on disk, refreshes card).
+    const preventDragDefaults = (event) => {
+        event.preventDefault();
+        event.stopPropagation();
+    };
+
+    ['dragenter', 'dragover'].forEach((eventName) => {
+        card.addEventListener(eventName, (event) => {
+            preventDragDefaults(event);
+            card.classList.add('drag-over');
+        });
+    });
+
+    card.addEventListener('dragleave', (event) => {
+        preventDragDefaults(event);
+        card.classList.remove('drag-over');
+    });
+
+    card.addEventListener('drop', (event) => {
+        preventDragDefaults(event);
+        card.classList.remove('drag-over');
+
+        const files = event.dataTransfer?.files;
+        if (!files || files.length === 0) return;
+
+        const file = files[0];
+        // Keep in sync with the accept list of the preview file picker (image/* + video/mp4).
+        if (!file.type.startsWith('image/') && file.type !== 'video/mp4') {
+            showToast('toast.api.previewDropInvalid', { name: file.name || '' }, 'error');
+            return;
+        }
+
+        const filePath = card.dataset.filepath;
+        if (!filePath) return;
+
+        // uploadPreview handles loading state, card refresh and error toasts internally.
+        getModelApiClient().uploadPreview(filePath, file);
+    });
+
    return card;
 }

@@ -182,6 +182,10 @@ function isEarlyAccessActive(version) {
    }
 }

+function isPaidPermanent(version) {
+    return version && version.isPaid === true;
+}
+
 function isDownloadAllowed(version) {
    if (!version.usageControl) {
        return true;
@@ -342,6 +346,7 @@ function resolveUpdateAvailability(record, baseModel, currentVersionId) {
    const strategy = state?.global?.settings?.version_grouping;
    const sameBaseMode = strategy === DISPLAY_FILTER_MODES.SAME_BASE;
    const hideEarlyAccess = state?.global?.settings?.hide_early_access_updates;
+    const hidePaid = state?.global?.settings?.hide_paid_updates;

    if (!sameBaseMode) {
        return Boolean(record?.hasUpdate);
@@ -388,6 +393,9 @@ function resolveUpdateAvailability(record, baseModel, currentVersionId) {
        if (hideEarlyAccess && isEarlyAccessActive(version)) {
            return false;
        }
+        if (hidePaid && isPaidPermanent(version)) {
+            return false;
+        }
        if (!isDownloadAllowed(version)) {
            return false;
        }
@@ -469,6 +477,7 @@ function renderRow(version, options) {
    const downloadedBadgeLabel = translate('modals.model.versions.badges.downloaded', {}, 'Downloaded');
    const newerBadgeLabel = translate('modals.model.versions.badges.newer', {}, 'Newer Version');
    const earlyAccessBadgeLabel = translate('modals.model.versions.badges.earlyAccess', {}, 'Early Access');
+    const paidBadgeLabel = translate('modals.model.versions.badges.paid', {}, 'Paid');
    const ignoredBadgeLabel = translate('modals.model.versions.badges.ignored', {}, 'Ignored');
    const versionName = version.name || translate('modals.model.versions.labels.unnamed', {}, 'Untitled Version');

@@ -522,6 +531,16 @@ function renderRow(version, options) {
        }));
    }

+    if (isPaidPermanent(version)) {
+        badges.push(buildBadge(paidBadgeLabel, 'paid', {
+            title: translate(
+                'modals.model.versions.badges.paidTooltip',
+                {},
+                'This version requires payment to download'
+            ),
+        }));
+    }
+
    if (!isDownloadAllowed(version)) {
        const onSiteOnlyBadgeLabel = translate('modals.model.versions.badges.onSiteOnly', {}, 'On-Site Only');
        badges.push(buildBadge(onSiteOnlyBadgeLabel, 'info', {
@@ -564,6 +583,12 @@ function renderRow(version, options) {
                {},
                'This version is only available for on-site generation on Civitai'
            );
+        } else if (isPaidPermanent(version)) {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadPaidTooltip',
+                {},
+                'Download this paid version from Civitai'
+            );
        } else if (isEarlyAccess) {
            downloadTitle = translate(
                'modals.model.versions.actions.downloadEarlyAccessTooltip',
@@ -1307,15 +1332,41 @@ export function initVersionsTab({
        });
    }

-    async function resolveDownloadPathFromCurrentVersion() {
+    function getCurrentInLibraryVersion() {
        if (!normalizedCurrentVersionId || !controller.record?.versions) {
            return null;
        }
-
-        const currentVersion = controller.record.versions.find(
+        return controller.record.versions.find(
            v => v.versionId === normalizedCurrentVersionId && v.isInLibrary && v.filePath
-        );
-        if (!currentVersion?.filePath) {
+        ) || null;
+    }
+
+    function getDownloadPathTemplate() {
+        try {
+            const singularType = modelType.replace(/s$/, '');
+            const templates = state.global?.settings?.download_path_templates;
+            return (templates && templates[singularType]) || '';
+        } catch (error) {
+            return '';
+        }
+    }
+
+    function shouldResolveTemplatePath(targetVersion, pathInfo) {
+        if (!getDownloadPathTemplate() || !pathInfo?.modelRoot) {
+            return false;
+        }
+        const currentVersion = getCurrentInLibraryVersion();
+        const currentBase = normalizeBaseModelName(currentVersion?.baseModel);
+        const targetBase = normalizeBaseModelName(targetVersion?.baseModel);
+        if (!currentBase || !targetBase || currentBase === targetBase) {
+            return false;
+        }
+        return true;
+    }
+
+    async function resolveDownloadPathFromCurrentVersion() {
+        const currentVersion = getCurrentInLibraryVersion();
+        if (!currentVersion) {
            return null;
        }

@@ -1372,10 +1423,13 @@ export function initVersionsTab({

        try {
            const pathInfo = await resolveDownloadPathFromCurrentVersion();
+            const resolveTemplatePath = shouldResolveTemplatePath(version, pathInfo);
            const success = await downloadManager.downloadVersionWithDefaults(modelType, modelId, versionId, {
                versionName: version.name || `#${version.versionId}`,
                modelRoot: pathInfo?.modelRoot || '',
-                targetFolder: pathInfo?.targetFolder || '',
+                targetFolder: resolveTemplatePath ? '' : (pathInfo?.targetFolder || ''),
+                useDefaultPaths: resolveTemplatePath ? true : null,
+                useSaveDirAsRoot: resolveTemplatePath,
            });

            if (success) {
@@ -3,6 +3,7 @@ import { showToast, setupAutoNewlineOnPaste } from '../utils/uiHelpers.js';
 import { state } from '../state/index.js';
 import { LoadingManager } from './LoadingManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
+import { isModelWeightFile } from '../utils/modelFileTypes.js';
 import { getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
 import { FolderTreeManager } from '../components/FolderTreeManager.js';
 import { translate } from '../utils/i18nHelpers.js';
@@ -557,8 +558,7 @@ export class DownloadManager {
            const firstImage = version.images?.find(img => !img.url.endsWith('.mp4'));
            const thumbnailUrl = firstImage ? firstImage.url : '/loras_static/images/no-preview.png';

-            // Count model-type files per version
-            const modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
+            const modelFiles = (version.files || []).filter(f => isModelWeightFile(f.type));
            const primaryFile = modelFiles.find(f => f.primary) || modelFiles[0] || {};
            const fileSize = version.modelSizeKB ?
                (version.modelSizeKB / 1024).toFixed(2) :
@@ -685,7 +685,7 @@ export class DownloadManager {
        if (!version) return;

        this.currentVersion = version;
-        const modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
+        const modelFiles = (version.files || []).filter(f => isModelWeightFile(f.type));

        document.getElementById('versionStep').style.display = 'none';
        document.getElementById('fileSelectionStep').style.display = 'block';
@@ -747,7 +747,7 @@ export class DownloadManager {
            return;
        }

-        const modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
+        const modelFiles = (version.files || []).filter(f => isModelWeightFile(f.type));
        this.selectedFile = modelFiles.find(f => f.id.toString() === selectedRadio.value);

        console.log('[download] confirmFileSelection: selected file id=%s, name="%s", type="%s", metadata=%o',
@@ -912,6 +912,7 @@ export class DownloadManager {
        modelRoot = '',
        targetFolder = '',
        useDefaultPaths = false,
+        useSaveDirAsRoot = false,
        source = null,
        fileParams = null,
        closeModal = false,
@@ -923,7 +924,7 @@ export class DownloadManager {
        }

        const displayName = versionName || `#${versionId}`;
-        const retryParams = { modelId, versionId, versionName, modelRoot, targetFolder, useDefaultPaths, source, fileParams, closeModal: false };
+        const retryParams = { modelId, versionId, versionName, modelRoot, targetFolder, useDefaultPaths, useSaveDirAsRoot, source, fileParams, closeModal: false };
        let ws = null;
        let updateProgress = () => { };
        let cancelled = false;
@@ -995,7 +996,8 @@ export class DownloadManager {
                useDefaultPaths,
                downloadId,
                source,
-                fileParams
+                fileParams,
+                useSaveDirAsRoot
            );

            if (cancelled) {
@@ -1809,7 +1811,9 @@ export class DownloadManager {
        versionName = '', 
        source = null,
        modelRoot = '',
-        targetFolder = ''
+        targetFolder = '',
+        useDefaultPaths = null,
+        useSaveDirAsRoot = false
    } = {}) {
        console.warn('[download] downloadVersionWithDefaults: NO fileParams will be sent — backend will always use primary file. '
            + 'modelType=%s, modelId=%s, versionId=%s, versionName="%s"',
@@ -1824,14 +1828,14 @@ export class DownloadManager {
        this.modelId = modelId ? modelId.toString() : null;
        this.source = source;

-        const useDefaultPaths = !modelRoot;
        return this.executeDownloadWithProgress({
            modelId,
            versionId,
            versionName,
            modelRoot: modelRoot || '',
            targetFolder: targetFolder || '',
-            useDefaultPaths,
+            useDefaultPaths: useDefaultPaths ?? !modelRoot,
+            useSaveDirAsRoot,
            source,
            closeModal: false,
        });
@@ -1017,11 +1017,8 @@ 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 recipes layout setting (segmented control active state)
+        this.updateRecipesLayoutControls(state.global.settings.recipes_layout || 'grid');

        // Set card info display setting
        const cardInfoDisplaySelect = document.getElementById('cardInfoDisplay');
@@ -1064,6 +1061,12 @@ export class SettingsManager {
            hideEarlyAccessUpdatesCheckbox.checked = state.global.settings.hide_early_access_updates || false;
        }

+        // Set hide paid updates setting
+        const hidePaidUpdatesCheckbox = document.getElementById('hidePaidUpdates');
+        if (hidePaidUpdatesCheckbox) {
+            hidePaidUpdatesCheckbox.checked = state.global.settings.hide_paid_updates || false;
+        }
+
        const skipPreviouslyDownloadedModelVersionsCheckbox = document.getElementById('skipPreviouslyDownloadedModelVersions');
        if (skipPreviouslyDownloadedModelVersionsCheckbox) {
            skipPreviouslyDownloadedModelVersionsCheckbox.checked =
@@ -2288,19 +2291,18 @@ export class SettingsManager {
            : element.value;

        try {
+            // Recipes layout has its own shared entry point used by both the
+            // settings modal segmented control and the recipes page toolbar toggle
+            if (settingKey === 'recipes_layout') {
+                return this.saveRecipesLayout(element.value);
+            }
+
            // Update frontend state with mapped keys
            await this.saveSetting(settingKey, value);

            // 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();
@@ -2328,6 +2330,47 @@ export class SettingsManager {
        }
    }

+    /**
+     * Save the recipes page layout (grid | masonry) and rebuild the scroller.
+     * Shared entry point for the settings modal segmented control and the
+     * recipes page toolbar toggle; both stay in sync via
+     * updateRecipesLayoutControls().
+     */
+    async saveRecipesLayout(value) {
+        if (value !== 'grid' && value !== 'masonry') {
+            return;
+        }
+
+        // Update frontend state with mapped keys
+        await this.saveSetting('recipes_layout', value);
+
+        // 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
+        window.dispatchEvent(new CustomEvent('lm:recipes-layout-changed'));
+
+        this.updateRecipesLayoutControls(value);
+    }
+
+    /**
+     * Sync the active state of every recipes layout control
+     * (settings modal segmented control and recipes page toolbar toggle).
+     */
+    updateRecipesLayoutControls(value) {
+        document.querySelectorAll('[data-recipes-layout]').forEach((control) => {
+            const active = control.dataset.recipesLayout === value;
+            control.classList.toggle('active', active);
+            if (control.hasAttribute('aria-pressed')) {
+                control.setAttribute('aria-pressed', String(active));
+            }
+            if (control.hasAttribute('aria-checked')) {
+                control.setAttribute('aria-checked', String(active));
+            }
+        });
+    }
+
    async saveRangeSetting(elementId, displayId, settingKey) {
        const element = document.getElementById(elementId);
        if (!element) return;
@@ -10,7 +10,7 @@ import { DuplicatesManager } from './components/DuplicatesManager.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';
+import { initSortDropdown, applySortToSelect, randomizeSortValue } from './components/controls/SortDropdown.js';

 class RecipePageControls {
    constructor() {
@@ -245,10 +245,20 @@ class RecipeManager {
                this.pageState.sortBy = savedSort;
            }
            initSortDropdown(sortSelect);
-            sortSelect.value = this.pageState.sortBy || 'date:desc';
+            applySortToSelect(this.pageState.sortBy || 'date:desc');
            sortSelect.addEventListener('change', () => {
-                this.pageState.sortBy = sortSelect.value;
-                setStorageItem('recipes_sort', sortSelect.value);
+                let value = sortSelect.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 = randomizeSortValue();
+                }
+                this.pageState.sortBy = value;
+                setStorageItem('recipes_sort', value);
+                // Reset the seeded Random option when switching away from
+                // Random, or re-apply the fresh seed when picking it again.
+                applySortToSelect(value);
                refreshVirtualScroll();
            });
        }
@@ -272,6 +282,30 @@ class RecipeManager {
            });
        }

+        // Layout toggle (grid / masonry) — shares the recipes_layout setting with
+        // the settings modal segmented control; active states stay in sync via
+        // settingsManager.updateRecipesLayoutControls() after each save
+        const layoutToggleBtns = document.querySelectorAll('.layout-toggle-btn');
+        if (layoutToggleBtns.length) {
+            const currentLayout = state.global.settings?.recipes_layout || 'grid';
+            layoutToggleBtns.forEach((btn) => {
+                const isActive = btn.dataset.recipesLayout === currentLayout;
+                btn.classList.toggle('active', isActive);
+                btn.setAttribute('aria-pressed', String(isActive));
+                btn.addEventListener('click', async () => {
+                    const layout = btn.dataset.recipesLayout;
+                    if ((state.global.settings?.recipes_layout || 'grid') === layout) {
+                        return;
+                    }
+                    try {
+                        await window.settingsManager?.saveRecipesLayout(layout);
+                    } catch (error) {
+                        console.error('Failed to switch recipes layout:', error);
+                    }
+                });
+            });
+        }
+
        // 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)
@@ -49,6 +49,7 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
    priority_tags: { ...DEFAULT_PRIORITY_TAG_CONFIG },
    version_grouping: 'same_base',
    hide_early_access_updates: false,
+    hide_paid_updates: false,
    auto_organize_exclusions: [],
    metadata_refresh_skip_paths: [],
    skip_previously_downloaded_model_versions: false,
@@ -646,10 +646,17 @@ export class MasonryScroller {
            const pageType = state.currentPageType;

            if (pageType === 'recipes') {
-                placeholderText = `
-                    <p>No recipes found</p>
-                    <p>Add recipe images to your recipes folder to see them here.</p>
-                `;
+                if (String(getCurrentPageState().sortBy).startsWith('opened')) {
+                    placeholderText = `
+                        <p>No recently opened recipes</p>
+                        <p>Recipes you open will appear here.</p>
+                    `;
+                } else {
+                    placeholderText = `
+                        <p>No recipes found</p>
+                        <p>Add recipe images to your recipes folder to see them here.</p>
+                    `;
+                }
            } else if (pageType === 'loras') {
                placeholderText = `
                    <p>No LoRAs found</p>
@@ -699,10 +699,17 @@ export class VirtualScroller {
            const pageType = state.currentPageType;

            if (pageType === 'recipes') {
-                placeholderText = `
-                    <p>No recipes found</p>
-                    <p>Add recipe images to your recipes folder to see them here.</p>
-                `;
+                if (String(getCurrentPageState().sortBy).startsWith('opened')) {
+                    placeholderText = `
+                        <p>No recently opened recipes</p>
+                        <p>Recipes you open will appear here.</p>
+                    `;
+                } else {
+                    placeholderText = `
+                        <p>No recipes found</p>
+                        <p>Add recipe images to your recipes folder to see them here.</p>
+                    `;
+                }
            } else if (pageType === 'loras') {
                placeholderText = `
                    <p>No LoRAs found</p>
@@ -0,0 +1,15 @@
+// CivitAI ModelFile.type values eligible as the main download file.
+// Mirrors the backend constant MODEL_WEIGHT_FILE_TYPES (py/utils/constants.py).
+// Keep both lists in sync when CivitAI introduces new file types.
+export const MODEL_WEIGHT_FILE_TYPES = [
+    'Model',
+    'Pruned Model',
+    'Negative',
+    'UNet',
+    'Diffusion Model',
+    'Enhancement LoRA',
+];
+
+export function isModelWeightFile(type) {
+    return MODEL_WEIGHT_FILE_TYPES.includes(type);
+}
@@ -236,11 +236,11 @@ export function showToast(key, params = {}, type = 'info', fallback = null) {
 * @param {Object} [options]
 * @param {string} [options.actionText] - Label for the action button (button omitted when empty)
 * @param {Function} [options.onAction] - Callback invoked at most once on button click
- * @param {number} [options.durationMs=30000] - How long the toast stays visible
+ * @param {number} [options.durationMs=20000] - How long the toast stays visible
 * @param {boolean} [options.countdown=true] - Show a ticking `(N)s` countdown
 */
 export function showActionToast(key, params = {}, type = 'info', options = {}) {
-  const { actionText, onAction, durationMs = 30000, countdown = true } = options;
+  const { actionText, onAction, durationMs = 20000, countdown = true } = options;

  const isPlainMessage = typeof key === 'string' && /\s/.test(key);
  const message = isPlainMessage ? key : translate(key, params);
@@ -295,6 +295,20 @@ export function showActionToast(key, params = {}, type = 'info', options = {}) {
      }
    }, 1000);
  }
+
+  // Manual close button: hides the toast early without firing onAction. The
+  // backend undo window keeps running and the batch is purged when it expires.
+  const closeBtn = document.createElement('button');
+  closeBtn.type = 'button';
+  closeBtn.className = 'toast-close-btn';
+  closeBtn.textContent = '×';
+  closeBtn.setAttribute('aria-label', translate('common.actions.close'));
+  closeBtn.addEventListener('click', (event) => {
+    event.preventDefault();
+    clearCountdown();
+    dismiss();
+  });
+  toast.append(closeBtn);
 }

 export function restoreFolderFilter() {
@@ -1092,6 +1106,9 @@ export async function sendEmbeddingToWorkflow(embeddingCode, onComplete = null)
    if (!isNodeEnabled(node)) {
      return false;
    }
+    if (node.capabilities?.text_widget_connected === true) {
+      return false;
+    }
    return (
      node.capabilities?.has_text_widget === true ||
      node.marker_role === "send_prompt_target"
@@ -1100,7 +1117,15 @@ export async function sendEmbeddingToWorkflow(embeddingCode, onComplete = null)

  const nodeKeys = Object.keys(textNodes);
  if (nodeKeys.length === 0) {
-    showToast('uiHelpers.workflow.noMatchingNodes', {}, 'warning');
+    showToast(
+      translate(
+        'uiHelpers.workflow.noPromptTargets',
+        {},
+        'No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target'
+      ),
+      {},
+      'warning'
+    );
    return false;
  }

@@ -1152,6 +1177,11 @@ export async function sendPromptToWorkflow(promptText, options = {}) {
    if (!isNodeEnabled(node)) {
      return false;
    }
+    // A node whose text widget is backed by a connected input cannot have its
+    // text changed via the widget — execution reads the linked input.
+    if (node.capabilities?.text_widget_connected === true) {
+      return false;
+    }
    return (
      node.capabilities?.has_text_widget === true ||
      node.marker_role === "send_prompt_target"
@@ -1160,7 +1190,12 @@ export async function sendPromptToWorkflow(promptText, options = {}) {

  const nodeKeys = Object.keys(textNodes);
  if (nodeKeys.length === 0) {
-    showToast(options.missingNodesMessage || 'uiHelpers.workflow.noMatchingNodes', {}, 'warning');
+    const defaultHint = translate(
+      'uiHelpers.workflow.noPromptTargets',
+      {},
+      'No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target'
+    );
+    showToast(options.missingNodesMessage || defaultHint, {}, 'warning');
    return false;
  }

@@ -48,17 +48,20 @@
                            <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>
                            <option value="loras_count:asc">{{ t('recipes.controls.sort.lorasCountAsc') }}</option>
                        </optgroup>
                    {% endif %}
+                    {% if page_id == 'recipes' %}
+                        <optgroup label="{{ t('recipes.controls.sort.opened', default='Recently Opened') }}">
+                            <option value="opened:desc">{{ t('recipes.controls.sort.openedDesc', default='Recently opened') }}</option>
+                        </optgroup>
+                    {% endif %}
+                    <optgroup label="{{ t('loras.controls.sort.random', default='Random') }}">
+                        <option value="random">{{ t('loras.controls.sort.randomAction', default='Randomize (shuffle)') }}</option>
+                    </optgroup>
                </select>
            </div>
            <div title="{% if page_id == 'recipes' %}{{ t('recipes.controls.refresh.title') }}{% else %}{{ t('loras.controls.refresh.title') }}{% endif %}" class="control-group dropdown-group">
@@ -131,6 +134,16 @@
        </div>
        
        <div class="controls-right">
+            {% if page_id == 'recipes' %}
+            <div class="control-group layout-toggle-group" role="group" aria-label="{{ t('recipes.controls.layout.title') }}" title="{{ t('recipes.controls.layout.title') }}">
+                <button type="button" class="layout-toggle-btn" data-recipes-layout="grid" aria-pressed="false" title="{{ t('recipes.controls.layout.grid') }}" aria-label="{{ t('recipes.controls.layout.grid') }}">
+                    <i class="fas fa-th-large" aria-hidden="true"></i>
+                </button>
+                <button type="button" class="layout-toggle-btn" data-recipes-layout="masonry" aria-pressed="false" title="{{ t('recipes.controls.layout.masonry') }}" aria-label="{{ t('recipes.controls.layout.masonry') }}">
+                    <i class="fas fa-columns" aria-hidden="true"></i>
+                </button>
+            </div>
+            {% endif %}
            <div class="control-group doctor-control-group">
                <button id="doctorTriggerBtn" class="doctor-trigger" title="{{ t('doctor.buttonTitle', default='Run diagnostics and common fixes') }}">
                    <i class="fas fa-stethoscope"></i>
@@ -629,16 +629,22 @@
                            <div class="setting-item">
                                <div class="setting-row">
                                    <div class="setting-info">
-                                        <label for="recipesLayout">
+                                        <label id="recipesLayoutLabel">
                                        {{ 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 class="setting-control layout-options-control">
+                                        <div id="recipesLayoutOptions" class="layout-options" role="radiogroup" aria-label="{{ t('settings.layoutSettings.recipesLayout') }}" aria-labelledby="recipesLayoutLabel">
+                                            <button type="button" class="layout-option" data-recipes-layout="grid" onclick="settingsManager.saveRecipesLayout('grid')" role="radio" aria-checked="true">
+                                                <span class="layout-option-preview layout-preview-grid" aria-hidden="true"><span></span><span></span><span></span><span></span></span>
+                                                <span class="layout-option-label">{{ t('settings.layoutSettings.recipesLayoutOptions.grid') }}</span>
+                                            </button>
+                                            <button type="button" class="layout-option" data-recipes-layout="masonry" onclick="settingsManager.saveRecipesLayout('masonry')" role="radio" aria-checked="false">
+                                                <span class="layout-option-preview layout-preview-masonry" aria-hidden="true"><span></span><span></span><span></span></span>
+                                                <span class="layout-option-label">{{ t('settings.layoutSettings.recipesLayoutOptions.masonry') }}</span>
+                                            </button>
+                                        </div>
                                    </div>
                                </div>
                            </div>
@@ -1263,6 +1269,24 @@
                                    </div>
                                </div>
                            </div>
+
+                            <div class="setting-item">
+                                <div class="setting-row">
+                                    <div class="setting-info">
+                                        <label for="hidePaidUpdates">
+                                        {{ t('settings.hidePaidUpdates.label') }}
+                                        <i class="fas fa-info-circle info-icon" data-tooltip="{{ t('settings.hidePaidUpdates.help') }}"></i>
+                                    </label>
+                                    </div>
+                                    <div class="setting-control">
+                                        <label class="toggle-switch">
+                                            <input type="checkbox" id="hidePaidUpdates"
+                                                   onchange="settingsManager.saveToggleSetting('hidePaidUpdates', 'hide_paid_updates')">
+                                            <span class="toggle-slider"></span>
+                                        </label>
+                                    </div>
+                                </div>
+                            </div>
                        </div>
                        
                        <!-- Example Images -->
@@ -1667,7 +1667,7 @@ describe('AutoComplete widget interactions', () => {
    expect(input.value).toBe('looking_to_the_side,');
  });

-  it('shows /af command for loras when active-filters autocomplete is off (default)', async () => {
+  it('shows /activefilters command for loras when active-filters autocomplete is off (default)', async () => {
    const input = document.createElement('textarea');
    input.value = '/';
    input.selectionStart = input.value.length;
@@ -1682,8 +1682,6 @@ describe('AutoComplete widget interactions', () => {
    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');
  });
@@ -1710,11 +1708,11 @@ describe('AutoComplete widget interactions', () => {
    await Promise.resolve();

    const commandNames = autoComplete.items.map((item) => item.command);
-    expect(commandNames).toContain('/af');
+    expect(commandNames).toContain('/activefilters');
    expect(previewTooltipMock.show).not.toHaveBeenCalled();
  });

-  it('shows /noaf command for loras when active-filters autocomplete is on', async () => {
+  it('shows /noactivefilters command for loras when active-filters autocomplete is on', async () => {
    settingGetMock.mockImplementation((key) => {
      if (key === 'loramanager.lora_active_filters_autocomplete') {
        return true;
@@ -1736,8 +1734,6 @@ describe('AutoComplete widget interactions', () => {
    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');
  });
@@ -1766,7 +1762,7 @@ describe('AutoComplete widget interactions', () => {
    expect(settingSetMock).toHaveBeenCalledWith('loramanager.lora_active_filters_autocomplete', true);
  });

-  it('toggles the active-filters setting when /af is accepted', async () => {
+  it('toggles the active-filters setting when /activefilters is accepted', async () => {
    const input = document.createElement('textarea');
    input.value = '/';
    input.selectionStart = input.value.length;
@@ -1782,7 +1778,7 @@ describe('AutoComplete widget interactions', () => {

    input.dispatchEvent(new Event('input', { bubbles: true }));

-    const afItem = autoComplete.items.find((item) => item.command === '/af');
+    const afItem = autoComplete.items.find((item) => item.command === '/activefilters');
    expect(afItem).toBeDefined();

    // Simulate the input being cleared after the command is accepted so the
@@ -0,0 +1,182 @@
+import { describe, it, expect, vi, beforeEach } from 'vitest';
+
+const {
+  MODEL_CARD_MODULE,
+  STATE_MODULE,
+  UI_HELPERS_MODULE,
+  I18N_MODULE,
+  API_CONFIG_MODULE,
+  API_FACTORY_MODULE,
+} = vi.hoisted(() => ({
+  MODEL_CARD_MODULE: new URL('../../../static/js/components/shared/ModelCard.js', import.meta.url).pathname,
+  STATE_MODULE: new URL('../../../static/js/state/index.js', import.meta.url).pathname,
+  UI_HELPERS_MODULE: new URL('../../../static/js/utils/uiHelpers.js', import.meta.url).pathname,
+  I18N_MODULE: new URL('../../../static/js/utils/i18nHelpers.js', import.meta.url).pathname,
+  API_CONFIG_MODULE: new URL('../../../static/js/api/apiConfig.js', import.meta.url).pathname,
+  API_FACTORY_MODULE: new URL('../../../static/js/api/modelApiFactory.js', import.meta.url).pathname,
+}));
+
+const showToastMock = vi.fn();
+const uploadPreviewMock = vi.fn();
+
+vi.mock(STATE_MODULE, () => ({
+  state: {
+    settings: {
+      blur_mature_content: false,
+      model_name_display: 'model_name',
+    },
+    global: {
+      settings: {
+        model_name_display: 'model_name',
+        group_by_model: false,
+        display_density: 'default',
+        model_card_footer_action: 'replace_preview',
+      },
+    },
+    pages: {
+      loras: {
+        previewVersions: new Map(),
+        sortBy: 'name',
+      },
+    },
+    bulkMode: false,
+    selectedLoras: new Set(),
+  },
+  getCurrentPageState: vi.fn(() => ({
+    sortBy: 'name',
+    previewVersions: new Map(),
+  })),
+}));
+
+vi.mock(UI_HELPERS_MODULE, () => ({
+  showToast: showToastMock,
+  openCivitai: vi.fn(),
+  openHuggingFace: vi.fn(),
+  copyToClipboard: vi.fn(),
+  copyLoraSyntax: vi.fn(),
+  sendLoraToWorkflow: vi.fn(),
+  sendEmbeddingToWorkflow: vi.fn(),
+  openExampleImagesFolder: vi.fn(),
+  buildLoraSyntax: vi.fn(),
+  sendModelPathToWorkflow: vi.fn(),
+}));
+
+vi.mock(I18N_MODULE, () => ({
+  translate: vi.fn((key) => key),
+}));
+
+vi.mock(API_CONFIG_MODULE, () => ({
+  MODEL_TYPES: { LORA: 'loras', CHECKPOINT: 'checkpoints', EMBEDDING: 'embeddings' },
+}));
+
+vi.mock(API_FACTORY_MODULE, () => ({
+  getModelApiClient: vi.fn(() => ({ uploadPreview: uploadPreviewMock })),
+}));
+
+describe('ModelCard drag & drop preview upload', () => {
+  let createModelCard;
+
+  beforeEach(async () => {
+    showToastMock.mockReset();
+    uploadPreviewMock.mockReset();
+    ({ createModelCard } = await import(MODEL_CARD_MODULE));
+  });
+
+  function createCard() {
+    const model = {
+      sha256: 'abc123',
+      file_path: '/models/test_lora.safetensors',
+      model_name: 'Test LoRA',
+      file_name: 'test_lora',
+      folder: 'models',
+      modified: 1234567890,
+      file_size: 1024,
+      usage_count: 0,
+      notes: '',
+      base_model: 'SD1.5',
+      favorite: false,
+      exclude: false,
+      hf_url: '',
+      update_available: false,
+      skip_metadata_refresh: false,
+      preview_url: '',
+      preview_nsfw_level: 0,
+      tags: [],
+      civitai: {},
+      sub_type: 'lora',
+    };
+    return createModelCard(model, 'loras');
+  }
+
+  function dispatchDrop(card, files) {
+    const event = new Event('drop', { bubbles: true, cancelable: true });
+    Object.defineProperty(event, 'dataTransfer', { value: { files } });
+    card.dispatchEvent(event);
+    return event;
+  }
+
+  it('uploads the dropped image as the model preview', () => {
+    const card = createCard();
+    const file = new File(['data'], 'preview.png', { type: 'image/png' });
+
+    dispatchDrop(card, [file]);
+
+    expect(uploadPreviewMock).toHaveBeenCalledTimes(1);
+    expect(uploadPreviewMock).toHaveBeenCalledWith('/models/test_lora.safetensors', file);
+  });
+
+  it('supports MP4 video files', () => {
+    const card = createCard();
+    const file = new File(['data'], 'preview.mp4', { type: 'video/mp4' });
+
+    dispatchDrop(card, [file]);
+
+    expect(uploadPreviewMock).toHaveBeenCalledTimes(1);
+  });
+
+  it('rejects unsupported file types with a toast', () => {
+    const card = createCard();
+    const file = new File(['data'], 'notes.txt', { type: 'text/plain' });
+
+    dispatchDrop(card, [file]);
+
+    expect(uploadPreviewMock).not.toHaveBeenCalled();
+    expect(showToastMock).toHaveBeenCalledWith(
+      'toast.api.previewDropInvalid',
+      { name: 'notes.txt' },
+      'error'
+    );
+  });
+
+  it('ignores drops without files', () => {
+    const card = createCard();
+
+    dispatchDrop(card, []);
+
+    expect(uploadPreviewMock).not.toHaveBeenCalled();
+  });
+
+  it('prevents browser default and highlights the card while dragging over', () => {
+    const card = createCard();
+
+    const dragOverEvent = new Event('dragover', { bubbles: true, cancelable: true });
+    card.dispatchEvent(dragOverEvent);
+    expect(dragOverEvent.defaultPrevented).toBe(true);
+    expect(card.classList.contains('drag-over')).toBe(true);
+
+    const dragLeaveEvent = new Event('dragleave', { bubbles: true, cancelable: true });
+    card.dispatchEvent(dragLeaveEvent);
+    expect(dragLeaveEvent.defaultPrevented).toBe(true);
+    expect(card.classList.contains('drag-over')).toBe(false);
+  });
+
+  it('clears the highlight when the drop completes', () => {
+    const card = createCard();
+    const file = new File(['data'], 'preview.png', { type: 'image/png' });
+
+    const event = dispatchDrop(card, [file]);
+
+    expect(event.defaultPrevented).toBe(true);
+    expect(card.classList.contains('drag-over')).toBe(false);
+  });
+});
@@ -0,0 +1,210 @@
+import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
+
+const {
+  MODEL_VERSIONS_MODULE,
+  API_FACTORY_MODULE,
+  DOWNLOAD_MANAGER_MODULE,
+  UI_HELPERS_MODULE,
+  STATE_MODULE,
+  I18N_HELPERS_MODULE,
+  UTILS_MODULE,
+} = vi.hoisted(() => ({
+  MODEL_VERSIONS_MODULE: new URL('../../../static/js/components/shared/ModelVersionsTab.js', import.meta.url).pathname,
+  API_FACTORY_MODULE: new URL('../../../static/js/api/modelApiFactory.js', import.meta.url).pathname,
+  DOWNLOAD_MANAGER_MODULE: new URL('../../../static/js/managers/DownloadManager.js', import.meta.url).pathname,
+  UI_HELPERS_MODULE: new URL('../../../static/js/utils/uiHelpers.js', import.meta.url).pathname,
+  STATE_MODULE: new URL('../../../static/js/state/index.js', import.meta.url).pathname,
+  I18N_HELPERS_MODULE: new URL('../../../static/js/utils/i18nHelpers.js', import.meta.url).pathname,
+  UTILS_MODULE: new URL('../../../static/js/components/shared/utils.js', import.meta.url).pathname,
+}));
+
+const downloadVersionWithDefaults = vi.fn();
+
+vi.mock(DOWNLOAD_MANAGER_MODULE, () => ({
+  downloadManager: {
+    downloadVersionWithDefaults,
+  },
+}));
+
+vi.mock(UI_HELPERS_MODULE, () => ({
+  showToast: vi.fn(),
+  openCivitaiUrl: vi.fn(),
+}));
+
+const stateMock = {
+  global: {
+    settings: {
+      autoplay_on_hover: false,
+      version_grouping: 'any',
+      download_path_templates: {
+        lora: '{base_model}/{first_tag}',
+        checkpoint: '{base_model}/{first_tag}',
+        embedding: '{base_model}/{first_tag}',
+      },
+    },
+  },
+};
+vi.mock(STATE_MODULE, () => ({
+  state: stateMock,
+}));
+
+vi.mock(I18N_HELPERS_MODULE, () => ({
+  translate: vi.fn((_, __, fallback) => fallback ?? ''),
+}));
+
+vi.mock(UTILS_MODULE, () => ({
+  formatFileSize: vi.fn(() => '1 MB'),
+}));
+
+vi.mock(API_FACTORY_MODULE, () => ({
+  getModelApiClient: vi.fn(),
+}));
+
+const LORA_ROOT = '/models/loras';
+
+function buildRecord(targetBaseModel = 'Anima') {
+  return {
+    success: true,
+    record: {
+      shouldIgnore: false,
+      inLibraryVersionIds: [10],
+      versions: [
+        {
+          versionId: 10,
+          name: 'v1.0',
+          baseModel: 'Illustrious',
+          sizeBytes: 1024,
+          isInLibrary: true,
+          shouldIgnore: false,
+          filePath: `${LORA_ROOT}/Illustrious/works/file.safetensors`,
+        },
+        {
+          versionId: 11,
+          name: 'v1.1',
+          baseModel: targetBaseModel,
+          sizeBytes: 2048,
+          isInLibrary: false,
+          shouldIgnore: false,
+        },
+      ],
+    },
+  };
+}
+
+async function renderAndClickDownload({ currentVersionId = 10, record = null } = {}) {
+  const { initVersionsTab } = await import(MODEL_VERSIONS_MODULE);
+  const controller = initVersionsTab({
+    modalId: 'model-versions-modal',
+    modelType: 'loras',
+    modelId: 123,
+    currentVersionId,
+  });
+  await controller.load();
+  const downloadButton = document.querySelector(
+    '.model-version-row[data-version-id="11"] [data-version-action="download"]'
+  );
+  downloadButton?.click();
+  await new Promise(resolve => setTimeout(resolve, 0));
+  return controller;
+}
+
+describe('ModelVersionsTab update download path resolution', () => {
+  let getModelApiClient;
+  let fetchModelUpdateVersions;
+  let fetchModelRoots;
+
+  beforeEach(async () => {
+    vi.resetModules();
+    downloadVersionWithDefaults.mockReset();
+    downloadVersionWithDefaults.mockResolvedValue(true);
+    document.body.innerHTML = `
+      <div id="model-versions-modal">
+        <div id="versions-tab">
+          <div class="model-versions-tab"></div>
+        </div>
+      </div>
+    `;
+    stateMock.global.settings.version_grouping = 'any';
+    stateMock.global.settings.download_path_templates.lora = '{base_model}/{first_tag}';
+    ({ getModelApiClient } = await import(API_FACTORY_MODULE));
+    fetchModelUpdateVersions = vi.fn();
+    fetchModelRoots = vi.fn();
+    fetchModelRoots.mockResolvedValue({ roots: [LORA_ROOT] });
+    getModelApiClient.mockReturnValue({
+      fetchModelUpdateVersions,
+      fetchModelRoots,
+      setModelUpdateIgnore: vi.fn(),
+      setVersionUpdateIgnore: vi.fn(),
+      deleteModel: vi.fn(),
+    });
+  });
+
+  afterEach(() => {
+    document.body.innerHTML = '';
+  });
+
+  it('keeps the current folder when the target version has the same base model', async () => {
+    fetchModelUpdateVersions.mockResolvedValue(buildRecord('Illustrious'));
+
+    await renderAndClickDownload();
+
+    expect(downloadVersionWithDefaults).toHaveBeenCalledWith(
+      'loras', 123, 11,
+      expect.objectContaining({
+        modelRoot: LORA_ROOT,
+        targetFolder: 'Illustrious/works',
+        useDefaultPaths: null,
+        useSaveDirAsRoot: false,
+      })
+    );
+  });
+
+  it('resolves the template path when the target base model differs and a template is configured', async () => {
+    fetchModelUpdateVersions.mockResolvedValue(buildRecord());
+
+    await renderAndClickDownload();
+
+    expect(downloadVersionWithDefaults).toHaveBeenCalledWith(
+      'loras', 123, 11,
+      expect.objectContaining({
+        modelRoot: LORA_ROOT,
+        targetFolder: '',
+        useDefaultPaths: true,
+        useSaveDirAsRoot: true,
+      })
+    );
+  });
+
+  it('keeps the current folder when the target base model differs but no template is configured', async () => {
+    stateMock.global.settings.download_path_templates.lora = '';
+    fetchModelUpdateVersions.mockResolvedValue(buildRecord());
+
+    await renderAndClickDownload();
+
+    expect(downloadVersionWithDefaults).toHaveBeenCalledWith(
+      'loras', 123, 11,
+      expect.objectContaining({
+        modelRoot: LORA_ROOT,
+        targetFolder: 'Illustrious/works',
+        useDefaultPaths: null,
+        useSaveDirAsRoot: false,
+      })
+    );
+  });
+
+  it('falls back to default paths when no local version exists', async () => {
+    fetchModelUpdateVersions.mockResolvedValue(buildRecord());
+
+    await renderAndClickDownload({ currentVersionId: null });
+
+    expect(downloadVersionWithDefaults).toHaveBeenCalledWith(
+      'loras', 123, 11,
+      expect.objectContaining({
+        modelRoot: '',
+        targetFolder: '',
+        useDefaultPaths: null,
+        useSaveDirAsRoot: false,
+      })
+    );
+  });
+});
@@ -1,4 +1,5 @@
 import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
+import { applySortToSelect } from '../../../static/js/components/controls/SortDropdown.js';

 const resetAndReloadMock = vi.fn();
 const getModelApiClientMock = vi.fn();
@@ -190,7 +191,7 @@ describe('Random sort option', () => {
    sortSelect.value = 'random';
    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
    await Promise.resolve();
-    controls.applySortToSelect('name:desc');
+    applySortToSelect('name:desc');

    expect(sortSelect.value).toBe('name:desc');
    expect(randomOpt.value).toBe('random');
@@ -0,0 +1,246 @@
+import { beforeEach, afterEach, describe, expect, it, vi } from "vitest";
+
+const { APP_MODULE, API_MODULE, STYLES_MODULE, REGISTRY_MODULE, appMock, apiMock, registeredExtensions } =
+  vi.hoisted(() => {
+    const registeredExtensions = [];
+    const appMock = {
+      graph: null,
+      registerExtension: (ext) => registeredExtensions.push(ext),
+    };
+    const apiMock = {
+      clientId: "client-1",
+      initialClientId: null,
+      addEventListener: vi.fn(),
+    };
+    return {
+      APP_MODULE: new URL("../../../scripts/app.js", import.meta.url).pathname,
+      API_MODULE: new URL("../../../scripts/api.js", import.meta.url).pathname,
+      STYLES_MODULE: new URL("../../../web/comfyui/lm_styles_loader.js", import.meta.url).pathname,
+      REGISTRY_MODULE: new URL("../../../web/comfyui/workflow_registry.js", import.meta.url).pathname,
+      appMock,
+      apiMock,
+      registeredExtensions,
+    };
+  });
+
+vi.mock(APP_MODULE, () => ({ app: appMock }));
+vi.mock(API_MODULE, () => ({ api: apiMock }));
+vi.mock(STYLES_MODULE, () => ({ ensureLmStyles: vi.fn() }));
+
+function createTextEncodeNode({ linked = false, id = 1 } = {}) {
+  const textWidget = { name: "text", type: "customtext", value: "old prompt", callback: null };
+  return {
+    id,
+    comfyClass: "CLIPTextEncode",
+    title: "CLIP Text Encode",
+    mode: 0,
+    properties: {},
+    widgets: [textWidget, { name: "clip", type: "combo" }],
+    widgets_values: ["old prompt", "clip-1"],
+    inputs: [
+      { name: "text", type: "STRING", widget: textWidget, link: linked ? 101 : null },
+      { name: "clip", type: "CLIP", link: null },
+    ],
+    setDirtyCanvas: vi.fn(),
+    graph: null,
+  };
+}
+
+function createSubgraph({ id = "sub-1", nodes = [] } = {}) {
+  const graph = {
+    id,
+    _nodes: nodes,
+    _subgraphs: new Map(),
+    getNodeById: vi.fn((nodeId) => nodes.find((n) => n.id === nodeId) ?? null),
+    events: { addEventListener: vi.fn() },
+  };
+  for (const node of nodes) {
+    node.graph = graph;
+  }
+  return graph;
+}
+
+function createGraph({ nodes = [], subgraphs = [] } = {}) {
+  const graph = {
+    id: "root",
+    _nodes: nodes,
+    _subgraphs: new Map(),
+    getNodeById: vi.fn((nodeId) => nodes.find((n) => n.id === nodeId) ?? null),
+    events: { addEventListener: vi.fn() },
+  };
+  for (const subgraph of subgraphs) {
+    graph._subgraphs.set(subgraph.id, subgraph);
+  }
+  for (const node of nodes) {
+    node.graph = graph;
+  }
+  return graph;
+}
+
+function lastRegisterPayload(fetchMock) {
+  const calls = fetchMock.mock.calls.filter(
+    ([url]) => url === "/api/lm/register-nodes"
+  );
+  expect(calls.length).toBeGreaterThan(0);
+  return JSON.parse(calls[calls.length - 1][1].body);
+}
+
+describe("LoraManager.WorkflowRegistry", () => {
+  let extension;
+  let fetchMock;
+
+  beforeEach(async () => {
+    vi.resetModules();
+    registeredExtensions.length = 0;
+    appMock.graph = null;
+    apiMock.addEventListener.mockClear();
+    fetchMock = vi.fn().mockResolvedValue({ ok: true });
+    global.fetch = fetchMock;
+    await import(REGISTRY_MODULE);
+    extension = registeredExtensions.find(
+      (ext) => ext.name === "LoraManager.WorkflowRegistry"
+    );
+    expect(extension).toBeDefined();
+  });
+
+  afterEach(() => {
+    delete global.fetch;
+  });
+
+  describe("refreshRegistry", () => {
+    it("registers an unconnected CLIPTextEncode as a text target", async () => {
+      appMock.graph = createGraph({ nodes: [createTextEncodeNode()] });
+
+      await extension.refreshRegistry(true);
+
+      const body = lastRegisterPayload(fetchMock);
+      expect(body.nodes).toHaveLength(1);
+      expect(body.nodes[0].capabilities.has_text_widget).toBe(true);
+      expect(body.nodes[0].capabilities.text_widget_connected).toBe(false);
+    });
+
+    it("excludes a CLIPTextEncode whose text input is connected", async () => {
+      appMock.graph = createGraph({ nodes: [createTextEncodeNode({ linked: true })] });
+
+      await extension.refreshRegistry(true);
+
+      const body = lastRegisterPayload(fetchMock);
+      expect(body.nodes).toHaveLength(1);
+      expect(body.nodes[0].capabilities.has_text_widget).toBe(false);
+      expect(body.nodes[0].capabilities.text_widget_connected).toBe(true);
+    });
+
+    it("registers connection state for nodes inside subgraphs", async () => {
+      const inner = createTextEncodeNode({ linked: true, id: 7 });
+      const subgraph = createSubgraph({ id: "sub-1", nodes: [inner] });
+      appMock.graph = createGraph({ subgraphs: [subgraph] });
+
+      await extension.refreshRegistry(true);
+
+      const body = lastRegisterPayload(fetchMock);
+      expect(body.nodes).toHaveLength(1);
+      expect(body.nodes[0].graph_id).toBe("sub-1");
+      expect(body.nodes[0].node_id).toBe(7);
+      expect(body.nodes[0].capabilities.text_widget_connected).toBe(true);
+    });
+
+    it("re-registers when text_widget_connected changes (fingerprint)", async () => {
+      const node = createTextEncodeNode();
+      appMock.graph = createGraph({ nodes: [node] });
+
+      await extension.refreshRegistry(true);
+      await extension.refreshRegistry();
+      expect(
+        fetchMock.mock.calls.filter(([url]) => url === "/api/lm/register-nodes")
+      ).toHaveLength(1);
+
+      node.inputs[0].link = 101;
+      await extension.refreshRegistry();
+      const body = lastRegisterPayload(fetchMock);
+      expect(body.nodes[0].capabilities.text_widget_connected).toBe(true);
+    });
+  });
+
+  describe("applyWidgetUpdate (inject_text)", () => {
+    it("updates the widget value when the text input is not connected", async () => {
+      const node = createTextEncodeNode();
+      const callback = vi.fn();
+      node.widgets[0].callback = callback;
+      appMock.graph = createGraph({ nodes: [node] });
+      extension.flashWidget = vi.fn();
+
+      await extension.applyWidgetUpdate({
+        node_id: 1,
+        action: "inject_text",
+        value: "hello",
+        mode: "replace",
+      });
+
+      expect(node.widgets[0].value).toBe("hello");
+      expect(node.widgets_values[0]).toBe("hello");
+      expect(callback).toHaveBeenCalledWith("hello");
+    });
+
+    it("skips inject_text when the target widget is connected and self-heals the registry", async () => {
+      const node = createTextEncodeNode({ linked: true });
+      appMock.graph = createGraph({ nodes: [node] });
+      extension.flashWidget = vi.fn();
+      const warnSpy = vi.spyOn(console, "warn").mockImplementation(() => {});
+
+      await extension.applyWidgetUpdate({
+        node_id: 1,
+        graph_id: "root",
+        action: "inject_text",
+        value: "new prompt",
+        mode: "replace",
+      });
+
+      expect(node.widgets[0].value).toBe("old prompt");
+      expect(node.widgets_values[0]).toBe("old prompt");
+      expect(warnSpy).toHaveBeenCalledWith(
+        expect.stringContaining("connected to an input"),
+        expect.anything(),
+        expect.anything()
+      );
+      await vi.waitFor(() => {
+        expect(
+          fetchMock.mock.calls.some(([url]) => url === "/api/lm/register-nodes")
+        ).toBe(true);
+      });
+      warnSpy.mockRestore();
+    });
+  });
+
+  describe("setup link-change hooks", () => {
+    it("hooks root events, existing subgraphs, and future subgraphs", () => {
+      const subgraph = createSubgraph({ id: "sub-1", nodes: [] });
+      const graph = createGraph({ subgraphs: [subgraph] });
+      appMock.graph = graph;
+
+      extension.setup();
+
+      expect(graph.events.addEventListener).toHaveBeenCalledWith(
+        "node:slot-links:changed",
+        expect.any(Function)
+      );
+      expect(graph.events.addEventListener).toHaveBeenCalledWith(
+        "subgraph-created",
+        expect.any(Function)
+      );
+      expect(subgraph.events.addEventListener).toHaveBeenCalledWith(
+        "node:slot-links:changed",
+        expect.any(Function)
+      );
+
+      const createdHandler = graph.events.addEventListener.mock.calls.find(
+        ([name]) => name === "subgraph-created"
+      )[1];
+      const laterSubgraph = createSubgraph({ id: "sub-2", nodes: [] });
+      createdHandler({ subgraph: laterSubgraph });
+      expect(laterSubgraph.events.addEventListener).toHaveBeenCalledWith(
+        "node:slot-links:changed",
+        expect.any(Function)
+      );
+    });
+  });
+});
@@ -530,4 +530,49 @@ describe('SettingsManager recipes layout switch', () => {
        dispatchSpy.mockRestore();
        delete state.virtualScroller;
    });
+
+    it('saveRecipesLayout persists, dispatches the layout event, and syncs controls', async () => {
+        const manager = createManager();
+
+        const gridBtn = document.createElement('button');
+        gridBtn.dataset.recipesLayout = 'grid';
+        gridBtn.setAttribute('aria-pressed', 'false');
+        const masonryBtn = document.createElement('button');
+        masonryBtn.dataset.recipesLayout = 'masonry';
+        masonryBtn.setAttribute('aria-pressed', 'false');
+        masonryBtn.setAttribute('role', 'radio');
+        masonryBtn.setAttribute('aria-checked', 'false');
+        document.body.appendChild(gridBtn);
+        document.body.appendChild(masonryBtn);
+
+        const calculateLayout = vi.fn();
+        state.virtualScroller = { calculateLayout };
+
+        const dispatchSpy = vi.spyOn(window, 'dispatchEvent');
+
+        await manager.saveRecipesLayout('masonry');
+
+        expect(state.global.settings.recipes_layout).toBe('masonry');
+        expect(masonryBtn.classList.contains('active')).toBe(true);
+        expect(masonryBtn.getAttribute('aria-pressed')).toBe('true');
+        expect(masonryBtn.getAttribute('aria-checked')).toBe('true');
+        expect(gridBtn.classList.contains('active')).toBe(false);
+        expect(gridBtn.getAttribute('aria-pressed')).toBe('false');
+
+        const layoutEvent = dispatchSpy.mock.calls
+            .map(([event]) => event)
+            .find(event => event.type === 'lm:recipes-layout-changed');
+        expect(layoutEvent).toBeInstanceOf(CustomEvent);
+        expect(calculateLayout).not.toHaveBeenCalled();
+        expect(showToast).not.toHaveBeenCalled();
+
+        dispatchSpy.mockRestore();
+        delete state.virtualScroller;
+    });
+
+    it('ignores invalid recipes layout values', async () => {
+        const manager = createManager();
+        await manager.saveRecipesLayout('bogus');
+        expect(state.global.settings.recipes_layout).toBeUndefined();
+    });
 });
@@ -0,0 +1,236 @@
+import { describe, it, expect, beforeEach, afterEach, vi } from 'vitest';
+import { renderRecipesPage } from '../utils/pageFixtures.js';
+import { applySortToSelect } from '../../../static/js/components/controls/SortDropdown.js';
+
+const initializeAppMock = vi.fn();
+const initializePageFeaturesMock = vi.fn();
+const getCurrentPageStateMock = vi.fn();
+const getSessionItemMock = vi.fn();
+const removeSessionItemMock = vi.fn();
+const getStorageItemMock = vi.fn();
+const setStorageItemMock = vi.fn();
+const removeStorageItemMock = vi.fn();
+const refreshVirtualScrollMock = vi.fn();
+const refreshRecipesMock = vi.fn();
+
+let importManagerInstance;
+let recipeModalInstance;
+let duplicatesManagerInstance;
+
+const ImportManagerMock = vi.fn(() => importManagerInstance);
+const RecipeModalMock = vi.fn(() => recipeModalInstance);
+const DuplicatesManagerMock = vi.fn(() => duplicatesManagerInstance);
+
+vi.mock('../../../static/js/core.js', () => ({
+  appCore: {
+    initialize: initializeAppMock,
+    initializePageFeatures: initializePageFeaturesMock,
+  },
+}));
+
+vi.mock('../../../static/js/managers/ImportManager.js', () => ({
+  ImportManager: ImportManagerMock,
+}));
+
+vi.mock('../../../static/js/components/RecipeModal.js', () => ({
+  RecipeModal: RecipeModalMock,
+}));
+
+vi.mock('../../../static/js/state/index.js', () => ({
+  getCurrentPageState: getCurrentPageStateMock,
+  state: {
+    currentPageType: 'recipes',
+    global: { settings: {} },
+    virtualScroller: {
+      removeItemByFilePath: vi.fn(),
+      updateSingleItem: vi.fn(),
+      refreshWithData: vi.fn(),
+    },
+  },
+}));
+
+vi.mock('../../../static/js/utils/storageHelpers.js', () => ({
+  getSessionItem: getSessionItemMock,
+  removeSessionItem: removeSessionItemMock,
+  getStorageItem: getStorageItemMock,
+  setStorageItem: setStorageItemMock,
+  removeStorageItem: removeStorageItemMock,
+}));
+
+vi.mock('../../../static/js/components/ContextMenu/index.js', () => ({
+  RecipeContextMenu: vi.fn(),
+}));
+
+vi.mock('../../../static/js/components/DuplicatesManager.js', () => ({
+  DuplicatesManager: DuplicatesManagerMock,
+}));
+
+vi.mock('../../../static/js/utils/infiniteScroll.js', () => ({
+  refreshVirtualScroll: refreshVirtualScrollMock,
+  recreateVirtualScroll: vi.fn(),
+}));
+
+vi.mock('../../../static/js/api/recipeApi.js', () => ({
+  refreshRecipes: refreshRecipesMock,
+  RecipeSidebarApiClient: vi.fn(() => ({
+    apiConfig: { config: { displayName: 'Recipes', supportsMove: true } },
+    fetchUnifiedFolderTree: vi.fn().mockResolvedValue({ success: true, tree: {} }),
+    fetchModelFolders: vi.fn().mockResolvedValue({ success: true, folders: [] }),
+    fetchModelRoots: vi.fn().mockResolvedValue({ roots: ['/recipes'] }),
+    moveBulkModels: vi.fn(),
+    moveSingleModel: vi.fn(),
+  })),
+}));
+
+vi.mock('../../../static/js/components/SidebarManager.js', () => ({
+  sidebarManager: {
+    setHostPageControls: vi.fn(),
+    initialize: vi.fn(async () => {}),
+    refresh: vi.fn(async () => {}),
+    cleanup: vi.fn(),
+  },
+}));
+
+function renderSortSelect() {
+  const sortSelectElement = document.createElement('select');
+  sortSelectElement.id = 'sortSelect';
+  sortSelectElement.innerHTML = `
+    <option value="date:desc">Newest</option>
+    <option value="name:asc">Name A-Z</option>
+    <option value="random">Randomize (shuffle)</option>
+  `;
+  document.body.appendChild(sortSelectElement);
+  return sortSelectElement;
+}
+
+describe('RecipeManager Random sort', () => {
+  let RecipeManager;
+  let pageState;
+
+  beforeEach(async () => {
+    vi.resetModules();
+    vi.clearAllMocks();
+
+    importManagerInstance = { showImportModal: vi.fn() };
+    recipeModalInstance = { showRecipeDetails: vi.fn() };
+    duplicatesManagerInstance = {
+      findDuplicates: vi.fn(),
+      selectLatestDuplicates: vi.fn(),
+      deleteSelectedDuplicates: vi.fn(),
+      confirmDeleteDuplicates: vi.fn(),
+      exitDuplicateMode: vi.fn(),
+    };
+
+    pageState = {
+      sortBy: 'date:desc',
+      searchOptions: undefined,
+      customFilter: undefined,
+      duplicatesMode: false,
+    };
+
+    getCurrentPageStateMock.mockImplementation(() => pageState);
+    initializeAppMock.mockResolvedValue(undefined);
+    initializePageFeaturesMock.mockResolvedValue(undefined);
+    refreshVirtualScrollMock.mockImplementation(() => {});
+    refreshRecipesMock.mockResolvedValue('refreshed');
+    getSessionItemMock.mockImplementation(() => null);
+    removeSessionItemMock.mockImplementation(() => {});
+    getStorageItemMock.mockImplementation(() => null);
+    setStorageItemMock.mockImplementation(() => {});
+
+    renderRecipesPage();
+  });
+
+  afterEach(() => {
+    document.body.innerHTML = '';
+    delete window.recipeManager;
+    delete window.importManager;
+  });
+
+  async function createManager() {
+    ({ RecipeManager } = await import('../../../static/js/recipes.js'));
+    const manager = new RecipeManager();
+    await manager.initialize();
+    return manager;
+  }
+
+  it('generates a seeded sort value when Random is picked', async () => {
+    const sortSelect = renderSortSelect();
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+    await createManager();
+
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+
+    expect(pageState.sortBy).toMatch(/^random:[a-z0-9]+$/);
+    expect(setStorageItemMock).toHaveBeenCalledWith('recipes_sort', pageState.sortBy);
+    expect(randomOpt.value).toBe(pageState.sortBy);
+    expect(sortSelect.value).toBe(pageState.sortBy);
+    expect(refreshVirtualScrollMock).toHaveBeenCalled();
+  });
+
+  it('reshuffles with a fresh seed every time Random is picked again', async () => {
+    const sortSelect = renderSortSelect();
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+    await createManager();
+
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+    const firstSeed = pageState.sortBy;
+
+    sortSelect.value = randomOpt.value;
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+
+    expect(pageState.sortBy).toMatch(/^random:[a-z0-9]+$/);
+    expect(pageState.sortBy).not.toBe(firstSeed);
+  });
+
+  it('restores a persisted seeded random sort on load', async () => {
+    const sortSelect = renderSortSelect();
+    const savedSort = 'random:persistedseed';
+    getStorageItemMock.mockImplementation((key) =>
+      key === 'recipes_sort' ? savedSort : null
+    );
+    await createManager();
+
+    expect(pageState.sortBy).toBe(savedSort);
+    expect(sortSelect.value).toBe(savedSort);
+    expect(sortSelect.querySelector('option[value="random:persistedseed"]')).not.toBeNull();
+  });
+
+  it('applies a non-random sort back to the plain random option', async () => {
+    const sortSelect = renderSortSelect();
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+    await createManager();
+
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+    applySortToSelect('name:asc');
+
+    expect(sortSelect.value).toBe('name:asc');
+    expect(randomOpt.value).toBe('random');
+  });
+
+  it('resets the seeded option when switching away from Random via the change handler', async () => {
+    const sortSelect = renderSortSelect();
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+    await createManager();
+
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+    expect(randomOpt.value).toMatch(/^random:[a-z0-9]+$/);
+
+    sortSelect.value = 'name:asc';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+
+    expect(pageState.sortBy).toBe('name:asc');
+    expect(sortSelect.value).toBe('name:asc');
+    expect(randomOpt.value).toBe('random');
+  });
+});
@@ -163,6 +163,7 @@ describe('RecipeManager', () => {
  afterEach(() => {
    delete window.recipeManager;
    delete window.importManager;
+    delete window.settingsManager;
  });

  it('initializes page controls, restores filters, and wires sort interactions', async () => {
@@ -227,6 +228,38 @@ describe('RecipeManager', () => {
    expect(initializePageFeaturesMock).toHaveBeenCalledTimes(1);
  });

+  it('wires the layout toggle and reflects the saved recipes layout setting', async () => {
+    const gridBtn = document.createElement('button');
+    gridBtn.className = 'layout-toggle-btn';
+    gridBtn.dataset.recipesLayout = 'grid';
+    gridBtn.setAttribute('aria-pressed', 'false');
+    const masonryBtn = document.createElement('button');
+    masonryBtn.className = 'layout-toggle-btn';
+    masonryBtn.dataset.recipesLayout = 'masonry';
+    masonryBtn.setAttribute('aria-pressed', 'false');
+    document.body.appendChild(gridBtn);
+    document.body.appendChild(masonryBtn);
+
+    const saveRecipesLayoutMock = vi.fn().mockResolvedValue();
+    window.settingsManager = { saveRecipesLayout: saveRecipesLayoutMock };
+
+    const manager = new RecipeManager();
+    await manager.initialize();
+
+    // Initial state follows the saved setting (default grid)
+    expect(gridBtn.classList.contains('active')).toBe(true);
+    expect(gridBtn.getAttribute('aria-pressed')).toBe('true');
+    expect(masonryBtn.classList.contains('active')).toBe(false);
+
+    // Clicking the inactive option saves the new layout
+    masonryBtn.dispatchEvent(new Event('click', { bubbles: true }));
+    expect(saveRecipesLayoutMock).toHaveBeenCalledWith('masonry');
+
+    // Clicking the already-active option is a no-op
+    gridBtn.dispatchEvent(new Event('click', { bubbles: true }));
+    expect(saveRecipesLayoutMock).toHaveBeenCalledTimes(1);
+  });
+
  it('skips loading when duplicates mode is active and refreshes otherwise', async () => {
    const manager = new RecipeManager();

@@ -67,7 +67,7 @@ describe('translate() with real en.json locale', () => {
        installWindowI18n();

        expect(translate('modals.deleteModel.recoverableWarning')).toBe(
-            'This will permanently delete the file after 30 seconds unless you undo.',
+            'This will permanently delete the file after 20 seconds unless you undo.',
        );
        expect(translate('modals.deleteModel.freesSpace', { size: '1.2 MB' })).toBe(
            'Frees 1.2 MB',
@@ -324,6 +324,18 @@ describe('MasonryScroller', () => {
    expect(placeholder.textContent).toContain('No recipes found');
  });

+  it('shows the recently-opened empty placeholder under the opened sort', async () => {
+    getCurrentPageState().sortBy = 'opened:desc';
+    const { scroller, grid } = track(createScroller({ items: [] }));
+
+    await scroller.initialize();
+
+    const placeholder = grid.querySelector('#virtualScrollPlaceholder');
+    expect(placeholder).not.toBeNull();
+    expect(placeholder.textContent).toContain('No recently opened recipes');
+    getCurrentPageState().sortBy = '';
+  });
+
  it('dispose removes classes, spacer and event listeners', () => {
    const { scroller, grid } = track(createScroller());

@@ -133,14 +133,14 @@ describe('UI helper DOM utilities', () => {

    const countdown = toast.querySelector('.toast-countdown');
    expect(countdown).not.toBeNull();
-    expect(countdown.textContent).toBe('(30s)');
+    expect(countdown.textContent).toBe('(20s)');

    // Ticking one second updates the countdown text
    vi.advanceTimersByTime(1000);
-    expect(countdown.textContent).toBe('(29s)');
+    expect(countdown.textContent).toBe('(19s)');

    // Drain remaining timers so no state leaks into other tests
-    vi.advanceTimersByTime(30000);
+    vi.advanceTimersByTime(20000);
  });

  it('invokes onAction once and dismisses immediately when the button is clicked', async () => {
@@ -186,6 +186,34 @@ describe('UI helper DOM utilities', () => {
    expect(onAction).toHaveBeenCalledTimes(1);
  });

+  it('dismisses the toast via the close button without firing onAction', async () => {
+    vi.useFakeTimers();
+    translateMock.mockReturnValue('Deleted Demo Model');
+
+    const { showActionToast } = await import(UI_HELPERS_MODULE);
+
+    const onAction = vi.fn();
+    showActionToast('toast.undo.deleted', {}, 'success', {
+      actionText: 'Undo',
+      onAction,
+    });
+
+    const toast = document.querySelector('.toast-container .toast');
+    const countdown = toast.querySelector('.toast-countdown');
+    toast.querySelector('.toast-close-btn').click();
+
+    expect(onAction).not.toHaveBeenCalled();
+    expect(toast.classList.contains('show')).toBe(false);
+
+    // Advancing past the full duration must not tick the countdown further,
+    // throw, or re-dismiss the already-dismissed toast
+    vi.advanceTimersByTime(60000);
+    expect(countdown.textContent).toBe('(20s)');
+
+    toast.dispatchEvent(new Event('transitionend', { bubbles: true }));
+    expect(document.querySelector('.toast-container .toast')).toBeNull();
+  });
+
  it('dismisses the toast when the countdown reaches zero', async () => {
    vi.useFakeTimers();
    translateMock.mockReturnValue('Deleted Demo Model');
@@ -315,6 +343,238 @@ describe('UI helper DOM utilities', () => {
    ]);
  });

+  it('excludes prompt targets whose text widget is connected to an input', async () => {
+    const registryResponse = {
+      success: true,
+      data: {
+        node_count: 4,
+        nodes: {
+          'root:1': {
+            id: 1,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Free Text',
+            type: 'CLIPTextEncode',
+            mode: 0,
+            marker_role: null,
+            capabilities: {
+              has_text_widget: true,
+              text_widget_connected: false,
+              widget_names: ['text', 'clip'],
+            },
+          },
+          'root:2': {
+            id: 2,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Wired Text',
+            type: 'CLIPTextEncode',
+            mode: 0,
+            marker_role: null,
+            capabilities: {
+              has_text_widget: true,
+              text_widget_connected: true,
+              widget_names: ['text', 'clip'],
+            },
+          },
+          'root:3': {
+            id: 3,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Marked But Wired',
+            type: 'KSampler',
+            mode: 0,
+            marker_role: 'send_prompt_target',
+            capabilities: {
+              has_text_widget: false,
+              text_widget_connected: true,
+              widget_names: ['seed'],
+            },
+          },
+          'root:4': {
+            id: 4,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Free Text 2',
+            type: 'CLIPTextEncode',
+            mode: 0,
+            marker_role: null,
+            capabilities: {
+              has_text_widget: true,
+              text_widget_connected: false,
+              widget_names: ['text', 'clip'],
+            },
+          },
+        },
+      },
+    };
+
+    global.fetch = vi.fn().mockResolvedValue({
+      json: async () => registryResponse,
+    });
+
+    document.body.innerHTML = '<div id="nodeSelector"></div>';
+
+    const { sendPromptToWorkflow } = await import(UI_HELPERS_MODULE);
+
+    const result = await sendPromptToWorkflow('a cat');
+
+    expect(result).toBe(true);
+
+    const nodeLabels = Array.from(
+      document.querySelectorAll('#nodeSelector .node-item[data-node-id] span')
+    ).map((span) => span.textContent.trim());
+
+    expect(nodeLabels).toEqual(['#1 Free Text', '#4 Free Text 2']);
+  });
+
+  it('returns false when the only prompt target has its text widget connected', async () => {
+    const registryResponse = {
+      success: true,
+      data: {
+        node_count: 1,
+        nodes: {
+          'root:1': {
+            id: 1,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Wired Text',
+            type: 'CLIPTextEncode',
+            mode: 0,
+            marker_role: null,
+            capabilities: {
+              has_text_widget: true,
+              text_widget_connected: true,
+              widget_names: ['text', 'clip'],
+            },
+          },
+        },
+      },
+    };
+
+    global.fetch = vi.fn().mockResolvedValue({
+      json: async () => registryResponse,
+    });
+
+    document.body.innerHTML = '<div id="nodeSelector"></div>';
+    translateMock.mockReturnValue(
+      'No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target'
+    );
+
+    const { sendPromptToWorkflow } = await import(UI_HELPERS_MODULE);
+
+    const result = await sendPromptToWorkflow('a cat');
+
+    expect(result).toBe(false);
+    expect(document.querySelectorAll('#nodeSelector .node-item').length).toBe(0);
+
+    const toast = document.querySelector('.toast-container .toast');
+    expect(toast).not.toBeNull();
+    expect(toast.textContent).toContain('Mark as');
+    expect(toast.textContent).toContain('Send Prompt Target');
+  });
+
+  it('shows the mark-as hint when no embedding target is available', async () => {
+    const registryResponse = {
+      success: true,
+      data: {
+        node_count: 1,
+        nodes: {
+          'root:1': {
+            id: 1,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Wired Text',
+            type: 'CLIPTextEncode',
+            mode: 0,
+            marker_role: null,
+            capabilities: {
+              has_text_widget: true,
+              text_widget_connected: true,
+              widget_names: ['text', 'clip'],
+            },
+          },
+        },
+      },
+    };
+
+    global.fetch = vi.fn().mockResolvedValue({
+      json: async () => registryResponse,
+    });
+
+    document.body.innerHTML = '<div id="nodeSelector"></div>';
+    translateMock.mockReturnValue(
+      'No compatible prompt targets in the workflow.\nRight-click a node in ComfyUI → Mark as → Send Prompt Target'
+    );
+
+    const { sendEmbeddingToWorkflow } = await import(UI_HELPERS_MODULE);
+
+    const result = await sendEmbeddingToWorkflow('embeddingcode');
+
+    expect(result).toBe(false);
+
+    const toast = document.querySelector('.toast-container .toast');
+    expect(toast).not.toBeNull();
+    expect(toast.textContent).toContain('Send Prompt Target');
+  });
+
+  it('keeps unconnected marker targets in the prompt candidate list', async () => {
+    const registryResponse = {
+      success: true,
+      data: {
+        node_count: 2,
+        nodes: {
+          'root:1': {
+            id: 1,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Marked Target',
+            type: 'KSampler',
+            mode: 0,
+            marker_role: 'send_prompt_target',
+            capabilities: {
+              has_text_widget: false,
+              text_widget_connected: false,
+              widget_names: ['seed'],
+            },
+          },
+          'root:2': {
+            id: 2,
+            graph_id: 'root',
+            graph_name: null,
+            title: 'Marked Target 2',
+            type: 'KSampler',
+            mode: 0,
+            marker_role: 'send_prompt_target',
+            capabilities: {
+              has_text_widget: false,
+              text_widget_connected: false,
+              widget_names: ['seed'],
+            },
+          },
+        },
+      },
+    };
+
+    global.fetch = vi.fn().mockResolvedValue({
+      json: async () => registryResponse,
+    });
+
+    document.body.innerHTML = '<div id="nodeSelector"></div>';
+
+    const { sendPromptToWorkflow } = await import(UI_HELPERS_MODULE);
+
+    const result = await sendPromptToWorkflow('a cat');
+
+    expect(result).toBe(true);
+
+    const nodeLabels = Array.from(
+      document.querySelectorAll('#nodeSelector .node-item[data-node-id] span')
+    ).map((span) => span.textContent.trim());
+
+    expect(nodeLabels).toEqual(['#1 Marked Target', '#2 Marked Target 2']);
+  });
+
  it('opens Civitai links using the preferred host and registers the first-use banner once', async () => {
    const openSpy = vi.fn();
    globalThis.window.open = openSpy;
@@ -471,6 +471,482 @@ def test_conditioning_provenance_recovers_combined_controlnet_prompts(
    assert params["negative_prompt"] == "low quality"


+def test_conditioning_provenance_recovers_transformed_switched_prompts(
+    metadata_registry, monkeypatch
+):
+    prompt_graph = {
+        "encode_pos": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "expected positive", "clip": ["clip", 0]},
+        },
+        "encode_other_pos": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "wrong positive", "clip": ["clip", 0]},
+        },
+        "encode_neg": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "expected negative", "clip": ["clip", 0]},
+        },
+        "encode_other_neg": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "wrong negative", "clip": ["clip", 0]},
+        },
+        "enhancer": {
+            "class_type": "KreaSeedVarianceEnhancer",
+            "inputs": {"conditioning": ["encode_pos", 0]},
+        },
+        "zero_out": {
+            "class_type": "ConditioningZeroOut",
+            "inputs": {"conditioning": ["encode_neg", 0]},
+        },
+        "positive_switch": {
+            "class_type": "ComfySwitchNode",
+            "inputs": {
+                "switch": True,
+                "on_false": ["encode_other_pos", 0],
+                "on_true": ["enhancer", 0],
+            },
+        },
+        "negative_switch": {
+            "class_type": "ComfySwitchNode",
+            "inputs": {
+                "switch": True,
+                "on_false": ["encode_other_neg", 0],
+                "on_true": ["zero_out", 0],
+            },
+        },
+        "sampler": {
+            "class_type": "ClownsharKSampler_Beta",
+            "inputs": {
+                "seed": 123,
+                "steps": 8,
+                "cfg": 1.0,
+                "sampler_name": "linear/euler",
+                "scheduler": "beta57",
+                "denoise": 1.0,
+                "positive": ["positive_switch", 0],
+                "negative": ["negative_switch", 0],
+                "latent_image": {
+                    "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+                },
+            },
+        },
+    }
+    prompt = SimpleNamespace(original_prompt=prompt_graph)
+
+    positive_conditioning = object()
+    other_positive_conditioning = object()
+    negative_conditioning = object()
+    other_negative_conditioning = object()
+    enhanced_conditioning = object()
+    zeroed_conditioning = object()
+
+    monkeypatch.setattr(metadata_processor, "standalone_mode", False)
+
+    metadata_registry.start_collection("prompt-transformed-switch")
+    metadata_registry.set_current_prompt(prompt)
+
+    for node_id, text, conditioning in (
+        ("encode_pos", "expected positive", positive_conditioning),
+        ("encode_other_pos", "wrong positive", other_positive_conditioning),
+        ("encode_neg", "expected negative", negative_conditioning),
+        ("encode_other_neg", "wrong negative", other_negative_conditioning),
+    ):
+        metadata_registry.record_node_execution(
+            node_id, "CLIPTextEncode", {"text": text}, None
+        )
+        metadata_registry.update_node_execution(
+            node_id, "CLIPTextEncode", [(conditioning,)]
+        )
+
+    metadata_registry.record_node_execution(
+        "enhancer",
+        "KreaSeedVarianceEnhancer",
+        {"conditioning": positive_conditioning},
+        None,
+        return_types=("CONDITIONING", "STRING"),
+    )
+    metadata_registry.update_node_execution(
+        "enhancer",
+        "KreaSeedVarianceEnhancer",
+        [(enhanced_conditioning, "diagnostics")],
+        return_types=("CONDITIONING", "STRING"),
+    )
+    metadata_registry.record_node_execution(
+        "zero_out",
+        "ConditioningZeroOut",
+        {"conditioning": negative_conditioning},
+        None,
+        return_types=("CONDITIONING",),
+    )
+    metadata_registry.update_node_execution(
+        "zero_out",
+        "ConditioningZeroOut",
+        [(zeroed_conditioning,)],
+        return_types=("CONDITIONING",),
+    )
+    metadata_registry.record_node_execution(
+        "positive_switch",
+        "ComfySwitchNode",
+        {
+            "switch": True,
+            "on_false": other_positive_conditioning,
+            "on_true": enhanced_conditioning,
+        },
+        None,
+    )
+    metadata_registry.update_node_execution(
+        "positive_switch", "ComfySwitchNode", [(enhanced_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "negative_switch",
+        "ComfySwitchNode",
+        {
+            "switch": True,
+            "on_false": other_negative_conditioning,
+            "on_true": zeroed_conditioning,
+        },
+        None,
+    )
+    metadata_registry.update_node_execution(
+        "negative_switch", "ComfySwitchNode", [(zeroed_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "sampler",
+        "ClownsharKSampler_Beta",
+        {
+            "seed": 123,
+            "steps": 8,
+            "cfg": 1.0,
+            "sampler_name": "linear/euler",
+            "scheduler": "beta57",
+            "denoise": 1.0,
+            "positive": enhanced_conditioning,
+            "negative": zeroed_conditioning,
+            "latent_image": {
+                "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+            },
+        },
+        None,
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-transformed-switch")
+    params = MetadataProcessor.extract_generation_params(metadata)
+
+    assert params["prompt"] == "expected positive"
+    assert params["negative_prompt"] == "expected negative"
+
+
+def test_conditioning_provenance_identity_switch_between_encoders(
+    metadata_registry, monkeypatch
+):
+    """Lock identity-preserving switches placed directly between encoders.
+
+    A switch returns the selected input conditioning verbatim, so provenance
+    must be recovered through object identity without any transform metadata.
+    """
+    prompt_graph = {
+        "encode_pos": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "chosen positive", "clip": ["clip", 0]},
+        },
+        "encode_other_pos": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "unchosen positive", "clip": ["clip", 0]},
+        },
+        "positive_switch": {
+            "class_type": "ComfySwitchNode",
+            "inputs": {
+                "switch": True,
+                "on_false": ["encode_other_pos", 0],
+                "on_true": ["encode_pos", 0],
+            },
+        },
+        "sampler": {
+            "class_type": "ClownsharKSampler_Beta",
+            "inputs": {
+                "seed": 123,
+                "steps": 8,
+                "cfg": 1.0,
+                "sampler_name": "linear/euler",
+                "scheduler": "beta57",
+                "denoise": 1.0,
+                "positive": ["positive_switch", 0],
+                "negative": ["encode_other_pos", 0],
+                "latent_image": {
+                    "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+                },
+            },
+        },
+    }
+    prompt = SimpleNamespace(original_prompt=prompt_graph)
+
+    chosen_conditioning = object()
+    unchosen_conditioning = object()
+
+    monkeypatch.setattr(metadata_processor, "standalone_mode", False)
+
+    metadata_registry.start_collection("prompt-identity-switch")
+    metadata_registry.set_current_prompt(prompt)
+
+    metadata_registry.record_node_execution(
+        "encode_pos", "CLIPTextEncode", {"text": "chosen positive"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_pos", "CLIPTextEncode", [(chosen_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "encode_other_pos", "CLIPTextEncode", {"text": "unchosen positive"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_other_pos", "CLIPTextEncode", [(unchosen_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "positive_switch",
+        "ComfySwitchNode",
+        {
+            "switch": True,
+            "on_false": unchosen_conditioning,
+            "on_true": chosen_conditioning,
+        },
+        None,
+    )
+    metadata_registry.update_node_execution(
+        "positive_switch", "ComfySwitchNode", [(chosen_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "sampler",
+        "ClownsharKSampler_Beta",
+        {
+            "seed": 123,
+            "steps": 8,
+            "cfg": 1.0,
+            "sampler_name": "linear/euler",
+            "scheduler": "beta57",
+            "denoise": 1.0,
+            "positive": chosen_conditioning,
+            "negative": unchosen_conditioning,
+            "latent_image": {
+                "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+            },
+        },
+        None,
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-identity-switch")
+    params = MetadataProcessor.extract_generation_params(metadata)
+
+    assert params["prompt"] == "chosen positive"
+    assert params["negative_prompt"] == "unchosen positive"
+
+
+def test_conditioning_provenance_ignores_scalar_conditioning_fields(
+    metadata_registry, monkeypatch
+):
+    """Scalar fields like ``conditioning_strength`` must not be collected as
+    conditioning objects for unregistered transform nodes."""
+    monkeypatch.setattr(metadata_processor, "standalone_mode", False)
+
+    metadata_registry.start_collection("prompt-scalar-filter")
+    metadata_registry.set_current_prompt(SimpleNamespace(original_prompt={}))
+
+    input_conditioning = object()
+    metadata_registry.record_node_execution(
+        "strength_node",
+        "SomeStrengthTransform",
+        {"conditioning": input_conditioning, "conditioning_strength": 0.8},
+        None,
+        return_types=("CONDITIONING",),
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-scalar-filter")
+    assert metadata[PROMPTS]["strength_node"]["orig_conditionings"] == [
+        input_conditioning
+    ]
+
+
+def test_conditioning_provenance_selector_with_conditioning_named_inputs(
+    metadata_registry, monkeypatch
+):
+    """An identity selector whose inputs use ``conditioning*`` names must not
+    leak the unselected branch's prompt."""
+    prompt_graph = {
+        "encode_a": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "AAA", "clip": ["clip", 0]},
+        },
+        "encode_b": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "BBB", "clip": ["clip", 0]},
+        },
+        "selector": {
+            "class_type": "ConditioningSelector",
+            "inputs": {
+                "conditioning_a": ["encode_a", 0],
+                "conditioning_b": ["encode_b", 0],
+            },
+        },
+        "sampler": {
+            "class_type": "ClownsharKSampler_Beta",
+            "inputs": {
+                "seed": 123,
+                "steps": 8,
+                "cfg": 1.0,
+                "sampler_name": "linear/euler",
+                "scheduler": "beta57",
+                "denoise": 1.0,
+                "positive": ["selector", 0],
+                "negative": ["encode_b", 0],
+                "latent_image": {
+                    "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+                },
+            },
+        },
+    }
+    prompt = SimpleNamespace(original_prompt=prompt_graph)
+
+    conditioning_a = object()
+    conditioning_b = object()
+
+    monkeypatch.setattr(metadata_processor, "standalone_mode", False)
+
+    metadata_registry.start_collection("prompt-selector")
+    metadata_registry.set_current_prompt(prompt)
+
+    metadata_registry.record_node_execution(
+        "encode_a", "CLIPTextEncode", {"text": "AAA"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_a", "CLIPTextEncode", [(conditioning_a,)]
+    )
+    metadata_registry.record_node_execution(
+        "encode_b", "CLIPTextEncode", {"text": "BBB"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_b", "CLIPTextEncode", [(conditioning_b,)]
+    )
+    metadata_registry.record_node_execution(
+        "selector",
+        "ConditioningSelector",
+        {"conditioning_a": conditioning_a, "conditioning_b": conditioning_b},
+        None,
+        return_types=("CONDITIONING",),
+    )
+    metadata_registry.update_node_execution(
+        "selector", "ConditioningSelector", [(conditioning_a,)],
+        return_types=("CONDITIONING",),
+    )
+    metadata_registry.record_node_execution(
+        "sampler",
+        "ClownsharKSampler_Beta",
+        {
+            "seed": 123,
+            "steps": 8,
+            "cfg": 1.0,
+            "sampler_name": "linear/euler",
+            "scheduler": "beta57",
+            "denoise": 1.0,
+            "positive": conditioning_a,
+            "negative": conditioning_b,
+            "latent_image": {
+                "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+            },
+        },
+        None,
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-selector")
+    params = MetadataProcessor.extract_generation_params(metadata)
+
+    assert params["prompt"] == "AAA"
+    assert params["negative_prompt"] == "BBB"
+
+
+def test_conditioning_provenance_uses_conditioning_output_slot(
+    metadata_registry, monkeypatch
+):
+    """Unregistered nodes whose CONDITIONING output is not the first slot
+    must still be tracked through the correct output position.
+
+    The graph's conditioning chain ends at an unexecuted phantom node so the
+    topology fallback in extract_generation_params cannot mask a runtime
+    provenance failure.
+    """
+    prompt_graph = {
+        "diag_node": {
+            "class_type": "DiagThenCond",
+            "inputs": {"conditioning": ["phantom_source", 0]},
+        },
+        "sampler": {
+            "class_type": "ClownsharKSampler_Beta",
+            "inputs": {
+                "seed": 123,
+                "steps": 8,
+                "cfg": 1.0,
+                "sampler_name": "linear/euler",
+                "scheduler": "beta57",
+                "denoise": 1.0,
+                "positive": ["diag_node", 1],
+                "latent_image": {
+                    "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+                },
+            },
+        },
+    }
+    prompt = SimpleNamespace(original_prompt=prompt_graph)
+
+    input_conditioning = object()
+    transformed_conditioning = object()
+
+    monkeypatch.setattr(metadata_processor, "standalone_mode", False)
+
+    metadata_registry.start_collection("prompt-output-slot")
+    metadata_registry.set_current_prompt(prompt)
+
+    metadata_registry.record_node_execution(
+        "encode_pos", "CLIPTextEncode", {"text": "AAA"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_pos", "CLIPTextEncode", [(input_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "diag_node",
+        "DiagThenCond",
+        {"conditioning": input_conditioning},
+        None,
+        return_types=("STRING", "CONDITIONING"),
+    )
+    metadata_registry.update_node_execution(
+        "diag_node",
+        "DiagThenCond",
+        [("diagnostics", transformed_conditioning)],
+        return_types=("STRING", "CONDITIONING"),
+    )
+    metadata_registry.record_node_execution(
+        "sampler",
+        "ClownsharKSampler_Beta",
+        {
+            "seed": 123,
+            "steps": 8,
+            "cfg": 1.0,
+            "sampler_name": "linear/euler",
+            "scheduler": "beta57",
+            "denoise": 1.0,
+            "positive": transformed_conditioning,
+            "negative": input_conditioning,
+            "latent_image": {
+                "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+            },
+        },
+        None,
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-output-slot")
+    params = MetadataProcessor.extract_generation_params(metadata)
+
+    assert params["prompt"] == "AAA"
+
+
 def test_conditioning_provenance_recovers_kj_set_get_prompts(
    metadata_registry, monkeypatch
 ):
@@ -897,6 +1373,97 @@ def test_metadata_overwrite_extractor_empty_inputs(metadata_registry):
    metadata_registry.clear_metadata()


+def _make_ksampler(func_name: str):
+    """Build a duck-typed comfy.samplers.KSAMPLER stub with a named function."""
+    def _sampler_function(*args, **kwargs):
+        pass
+
+    _sampler_function.__name__ = func_name
+    return SimpleNamespace(sampler_function=_sampler_function)
+
+
+def test_metadata_overwrite_extractor_sampler_union(metadata_registry):
+    """Wired SAMPLER objects should be converted to sampler names."""
+    from py.metadata_collector.constants import CLIP_SKIP_SENTINEL
+
+    metadata_registry.start_collection("prompt-ow-sampler")
+    metadata = metadata_registry.prompt_metadata["prompt-ow-sampler"]
+
+    inputs: Dict[str, Any] = {key: "" for key in METADATA_OVERWRITE_FIELDS}
+    inputs.update({"seed": 0, "steps": 0, "cfg_scale": 0.0, "clip_skip": CLIP_SKIP_SENTINEL})
+    inputs["sampler"] = _make_ksampler("sample_euler")
+
+    MetadataOverwriteExtractor.extract("ow-sampler-1", inputs, None, metadata)
+
+    params = metadata[OVERWRITE]["ow-sampler-1"]["parameters"]
+    assert params["sampler"] == "euler"
+
+    metadata_registry.clear_metadata()
+
+
+def test_metadata_overwrite_extractor_sampler_union_special_cases(metadata_registry):
+    """Sampler functions whose names diverge from SAMPLER_NAMES entries."""
+    from py.metadata_collector.constants import CLIP_SKIP_SENTINEL
+
+    metadata_registry.start_collection("prompt-ow-sampler2")
+    metadata = metadata_registry.prompt_metadata["prompt-ow-sampler2"]
+
+    cases = [
+        ("dpm_fast_function", "dpm_fast"),
+        ("dpm_adaptive_function", "dpm_adaptive"),
+        ("sample_unipc", "uni_pc"),
+        ("sample_unipc_bh2", "uni_pc_bh2"),
+        ("sample_dpmpp_2m_sde", "dpmpp_2m_sde"),
+    ]
+    for i, (func_name, expected) in enumerate(cases):
+        inputs: Dict[str, Any] = {key: "" for key in METADATA_OVERWRITE_FIELDS}
+        inputs.update({"seed": 0, "steps": 0, "cfg_scale": 0.0, "clip_skip": CLIP_SKIP_SENTINEL})
+        inputs["sampler"] = _make_ksampler(func_name)
+        MetadataOverwriteExtractor.extract(f"ow-sampler-{i}", inputs, None, metadata)
+
+    params_by_node = {node_id: entry["parameters"] for node_id, entry in metadata[OVERWRITE].items()}
+    for i, (func_name, expected) in enumerate(cases):
+        assert params_by_node[f"ow-sampler-{i}"]["sampler"] == expected, func_name
+
+    metadata_registry.clear_metadata()
+
+
+def test_metadata_overwrite_extractor_sampler_union_unrecognized_skipped(metadata_registry):
+    """Unrecognized sampler functions should skip the field, not crash."""
+    from py.metadata_collector.constants import CLIP_SKIP_SENTINEL
+
+    metadata_registry.start_collection("prompt-ow-sampler3")
+    metadata = metadata_registry.prompt_metadata["prompt-ow-sampler3"]
+
+    inputs: Dict[str, Any] = {key: "" for key in METADATA_OVERWRITE_FIELDS}
+    inputs.update({"seed": 0, "steps": 0, "cfg_scale": 0.0, "clip_skip": CLIP_SKIP_SENTINEL})
+    inputs["sampler"] = _make_ksampler("my_custom_sampler_function")
+
+    MetadataOverwriteExtractor.extract("ow-sampler-unrec", inputs, None, metadata)
+
+    assert not metadata[OVERWRITE]
+
+    metadata_registry.clear_metadata()
+
+
+def test_metadata_overwrite_extractor_sampler_union_no_sampler_function(metadata_registry):
+    """Objects without a sampler_function (e.g. old KUNASampler classes) are skipped."""
+    from py.metadata_collector.constants import CLIP_SKIP_SENTINEL
+
+    metadata_registry.start_collection("prompt-ow-sampler4")
+    metadata = metadata_registry.prompt_metadata["prompt-ow-sampler4"]
+
+    inputs: Dict[str, Any] = {key: "" for key in METADATA_OVERWRITE_FIELDS}
+    inputs.update({"seed": 0, "steps": 0, "cfg_scale": 0.0, "clip_skip": CLIP_SKIP_SENTINEL})
+    inputs["sampler"] = SimpleNamespace()
+
+    MetadataOverwriteExtractor.extract("ow-sampler-nofn", inputs, None, metadata)
+
+    assert not metadata[OVERWRITE]
+
+    metadata_registry.clear_metadata()
+
+
 def test_extract_generation_params_applies_overwrite(metadata_registry, populated_registry, monkeypatch):
    """overwrite values should replace inferred params in extract_generation_params."""
    import py.metadata_collector.metadata_processor as mp
@@ -1046,3 +1613,213 @@ def test_fill_missing_metadata_fills_overwrite_for_muted_node(metadata_registry)
    assert "ow-1" not in metadata.get(OVERWRITE, {})

    metadata_registry.clear_metadata()
+
+
+def test_krea_two_stage_sampler_prompt_and_params_collected(
+    metadata_registry, monkeypatch
+):
+    """KreaTwoStageSampler should be recognized as the primary sampler and
+    contribute the prompt, canonical sampling params, and final resolution."""
+    prompt_graph = {
+        "encode_pos": {
+            "class_type": "PromptLM",
+            "inputs": {"text": "krea masterpiece", "clip": ["clip", 0]},
+        },
+        "encode_neg": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": "low quality", "clip": ["clip", 0]},
+        },
+        "sampler": {
+            "class_type": "KreaTwoStageSampler",
+            "inputs": {
+                "seed": 42,
+                "handoff_percent": 16.67,
+                "stage1_steps": 52,
+                "stage1_cfg": 4.0,
+                "stage1_sampler_name": "euler",
+                "stage1_scheduler": "simple",
+                "stage2_steps": 12,
+                "stage2_cfg": 1.0,
+                "stage2_sampler_name": "euler",
+                "stage2_scheduler": "simple",
+                "final_width": 2048,
+                "final_height": 2048,
+                "upscale_method": "bislerp",
+                "positive": ["encode_pos", 0],
+                "negative": ["encode_neg", 0],
+                "latent_image": {
+                    "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+                },
+            },
+        },
+    }
+    prompt = SimpleNamespace(original_prompt=prompt_graph)
+
+    pos_conditioning = object()
+    neg_conditioning = object()
+
+    monkeypatch.setattr(metadata_processor, "standalone_mode", False)
+
+    metadata_registry.start_collection("krea-two-stage")
+    metadata_registry.set_current_prompt(prompt)
+
+    metadata_registry.record_node_execution(
+        "encode_pos", "PromptLM", {"text": "krea masterpiece"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_pos", "PromptLM", [(pos_conditioning, "krea masterpiece")]
+    )
+    metadata_registry.record_node_execution(
+        "encode_neg", "CLIPTextEncode", {"text": "low quality"}, None
+    )
+    metadata_registry.update_node_execution(
+        "encode_neg", "CLIPTextEncode", [(neg_conditioning,)]
+    )
+    metadata_registry.record_node_execution(
+        "sampler",
+        "KreaTwoStageSampler",
+        {
+            "seed": 42,
+            "handoff_percent": 16.67,
+            "stage1_steps": 52,
+            "stage1_cfg": 4.0,
+            "stage1_sampler_name": "euler",
+            "stage1_scheduler": "simple",
+            "stage2_steps": 12,
+            "stage2_cfg": 1.0,
+            "stage2_sampler_name": "euler",
+            "stage2_scheduler": "simple",
+            "final_width": 2048,
+            "final_height": 2048,
+            "upscale_method": "bislerp",
+            "positive": pos_conditioning,
+            "negative": neg_conditioning,
+            "latent_image": {
+                "samples": types.SimpleNamespace(shape=(1, 4, 16, 16))
+            },
+        },
+        None,
+    )
+
+    metadata = metadata_registry.get_metadata("krea-two-stage")
+
+    sampler_data = metadata[SAMPLING]["sampler"]
+    assert sampler_data["is_sampler"] is True
+    parameters = sampler_data["parameters"]
+    assert parameters["seed"] == 42
+    assert parameters["steps"] == 64
+    assert parameters["cfg"] == 4.0
+    assert parameters["sampler_name"] == "euler"
+    assert parameters["scheduler"] == "simple"
+    assert parameters["stage1_steps"] == 52
+    assert parameters["stage2_cfg"] == 1.0
+
+    assert metadata[SIZE]["sampler"] == {
+        "width": 2048,
+        "height": 2048,
+        "node_id": "sampler",
+    }
+
+    prompt_results = MetadataProcessor.match_conditioning_to_prompts(
+        metadata, "sampler"
+    )
+    assert prompt_results["prompt"] == "krea masterpiece"
+    assert prompt_results["negative_prompt"] == "low quality"
+
+    params = MetadataProcessor.extract_generation_params(metadata)
+    assert params["prompt"] == "krea masterpiece"
+    assert params["negative_prompt"] == "low quality"
+    assert params["seed"] == 42
+    assert params["steps"] == 64
+    assert params["cfg_scale"] == 4.0
+    assert params["sampler"] == "euler"
+    assert params["scheduler"] == "simple"
+    assert params["size"] == "2048x2048"
+
+
+def test_krea_three_stage_sampler_uses_stage1_canonical_fields(metadata_registry):
+    """KreaThreeStageSampler reuses stage 1 settings for stage 3, so canonical
+    fields map from stage 1 and the total counts both sampling stages."""
+    metadata_registry.start_collection("krea-three-stage")
+    metadata_registry.set_current_prompt(SimpleNamespace(original_prompt={}))
+
+    metadata_registry.record_node_execution(
+        "sampler",
+        "KreaThreeStageSampler",
+        {
+            "seed": 7,
+            "handoff_percent": 16.67,
+            "stage3_handoff_percent": 83.33,
+            "stage1_steps": 52,
+            "stage1_cfg": 4.0,
+            "stage1_sampler_name": "euler",
+            "stage1_scheduler": "simple",
+            "stage2_steps": 12,
+            "stage2_cfg": 1.0,
+            "stage2_sampler_name": "euler",
+            "stage2_scheduler": "simple",
+            "final_width": 1024,
+            "final_height": 2048,
+            "upscale_method": "bislerp",
+            "positive": object(),
+            "negative": object(),
+            "latent_image": {"samples": types.SimpleNamespace(shape=(1, 4, 8, 16))},
+        },
+        None,
+    )
+
+    metadata = metadata_registry.get_metadata("krea-three-stage")
+
+    sampler_data = metadata[SAMPLING]["sampler"]
+    assert sampler_data["is_sampler"] is True
+    parameters = sampler_data["parameters"]
+    assert parameters["seed"] == 7
+    assert parameters["stage3_handoff_percent"] == 83.33
+    assert parameters["steps"] == 64
+    assert parameters["cfg"] == 4.0
+    assert parameters["sampler_name"] == "euler"
+    assert parameters["scheduler"] == "simple"
+
+    # Final resolution takes precedence over the latent dimensions (64x128).
+    assert metadata[SIZE]["sampler"] == {
+        "width": 1024,
+        "height": 2048,
+        "node_id": "sampler",
+    }
+
+
+def test_krea_dual_resolution_selector_extracts_size_from_outputs(
+    metadata_registry,
+):
+    """KreaDualResolutionSelector computes dimensions at runtime, so the base
+    resolution is recorded from its outputs in the update phase."""
+    metadata_registry.start_collection("krea-selector")
+    metadata_registry.set_current_prompt(SimpleNamespace(original_prompt={}))
+
+    metadata_registry.record_node_execution(
+        "selector",
+        "KreaDualResolutionSelector",
+        {
+            "aspect_ratio": "1:1",
+            "base_megapixels": 1.0,
+            "final_megapixels": 2.0,
+            "multiple": 16,
+            "random_seed": 123,
+        },
+        None,
+        return_types=("INT", "INT", "INT", "INT", "INT"),
+    )
+    metadata_registry.update_node_execution(
+        "selector",
+        "KreaDualResolutionSelector",
+        [(1024, 1024, 2048, 2048, 123)],
+        return_types=("INT", "INT", "INT", "INT", "INT"),
+    )
+
+    metadata = metadata_registry.get_metadata("krea-selector")
+
+    assert metadata[SIZE]["selector"] == {
+        "width": 1024,
+        "height": 1024,
+        "node_id": "selector",
+    }
@@ -0,0 +1,179 @@
+"""Tests for the Random Checkpoint/Unet Loader nodes' base-model filtering and
+random-selection behavior.
+"""
+
+import pytest
+
+from py.nodes.random_checkpoint_loader import RandomCheckpointLoaderLM
+from py.nodes.random_unet_loader import RandomUNETLoaderLM
+
+
+class _FakeCache:
+    def __init__(self, raw_data):
+        self.raw_data = raw_data
+
+
+class _FakeScanner:
+    def __init__(self, raw_data, model_roots):
+        self._raw_data = raw_data
+        self._model_roots = model_roots
+
+    async def get_cached_data(self, force_refresh=False):
+        return _FakeCache(self._raw_data)
+
+    def get_model_roots(self):
+        return self._model_roots
+
+
+@pytest.fixture
+def base_model_library(tmp_path, monkeypatch):
+    from py.services.service_registry import ServiceRegistry
+
+    illustrious = tmp_path / "illustrious.safetensors"
+    illustrious.write_bytes(b"x")
+    flux = tmp_path / "flux.safetensors"
+    flux.write_bytes(b"x")
+    missing = tmp_path / "missing.safetensors"  # referenced but never created
+
+    raw_data = [
+        {
+            "sub_type": "checkpoint",
+            "file_path": str(illustrious),
+            "base_model": "Illustrious",
+        },
+        {"sub_type": "checkpoint", "file_path": str(flux), "base_model": "Flux.1 D"},
+        {
+            "sub_type": "checkpoint",
+            "file_path": str(missing),
+            "base_model": "SDXL 1.0",
+        },
+        {
+            "sub_type": "diffusion_model",
+            "file_path": str(flux),
+            "base_model": "Flux.1 D",
+        },
+    ]
+
+    async def _fake_scanner():
+        return _FakeScanner(raw_data, [str(tmp_path)])
+
+    monkeypatch.setattr(ServiceRegistry, "get_checkpoint_scanner", _fake_scanner)
+    return tmp_path
+
+
+def test_checkpoint_names_drop_deleted_files(tmp_path, monkeypatch):
+    from py.services.service_registry import ServiceRegistry
+
+    existing = tmp_path / "keep.safetensors"
+    existing.write_bytes(b"x")
+    deleted = tmp_path / "deleted.safetensors"  # referenced but never created
+
+    raw_data = [
+        {"sub_type": "checkpoint", "file_path": str(existing)},
+        {"sub_type": "checkpoint", "file_path": str(deleted)},
+        # Wrong type must stay excluded by the sub_type filter.
+        {"sub_type": "diffusion_model", "file_path": str(existing)},
+    ]
+
+    async def _fake_scanner():
+        return _FakeScanner(raw_data, [str(tmp_path)])
+
+    monkeypatch.setattr(ServiceRegistry, "get_checkpoint_scanner", _fake_scanner)
+    assert RandomCheckpointLoaderLM._get_checkpoint_names() == ["keep.safetensors"]
+
+
+def test_unet_names_drop_deleted_files(tmp_path, monkeypatch):
+    from py.services.service_registry import ServiceRegistry
+
+    existing = tmp_path / "keep.safetensors"
+    existing.write_bytes(b"x")
+    deleted = tmp_path / "deleted.safetensors"
+
+    raw_data = [
+        {"sub_type": "diffusion_model", "file_path": str(existing)},
+        {"sub_type": "diffusion_model", "file_path": str(deleted)},
+        {"sub_type": "checkpoint", "file_path": str(existing)},
+    ]
+
+    async def _fake_scanner():
+        return _FakeScanner(raw_data, [str(tmp_path)])
+
+    monkeypatch.setattr(ServiceRegistry, "get_checkpoint_scanner", _fake_scanner)
+    assert RandomUNETLoaderLM._get_unet_names() == ["keep.safetensors"]
+
+
+def test_checkpoint_names_empty_when_scanner_fails(tmp_path, monkeypatch):
+    from py.services.service_registry import ServiceRegistry
+
+    def _boom():
+        raise RuntimeError("scanner not available")
+
+    monkeypatch.setattr(ServiceRegistry, "get_checkpoint_scanner", _boom)
+    assert RandomCheckpointLoaderLM._get_checkpoint_names() == []
+
+
+def test_checkpoint_available_base_models(base_model_library):
+    # "SDXL 1.0" is excluded because its file no longer exists on disk.
+    assert RandomCheckpointLoaderLM._get_available_base_models() == [
+        "Any",
+        "Flux.1 D",
+        "Illustrious",
+    ]
+
+
+def test_checkpoint_names_filtered_by_base_model(base_model_library):
+    assert RandomCheckpointLoaderLM._get_checkpoint_names("Illustrious") == [
+        "illustrious.safetensors"
+    ]
+    assert RandomCheckpointLoaderLM._get_checkpoint_names("Any") == [
+        "flux.safetensors",
+        "illustrious.safetensors",
+    ]
+
+
+def test_unet_available_base_models(base_model_library):
+    assert RandomUNETLoaderLM._get_available_base_models() == ["Any", "Flux.1 D"]
+
+
+def test_load_checkpoint_random_selection_uses_pool(base_model_library, monkeypatch):
+    from py.nodes import random_checkpoint_loader as random_checkpoint_loader_module
+
+    monkeypatch.setattr(
+        random_checkpoint_loader_module,
+        "get_checkpoint_info_absolute",
+        lambda name: (str(base_model_library / name), {"file_path": name}),
+    )
+    monkeypatch.setattr(
+        random_checkpoint_loader_module.comfy.sd,
+        "load_checkpoint_guess_config",
+        lambda *a, **k: ("MODEL", "CLIP", "VAE", None),
+        raising=False,
+    )
+
+    node = RandomCheckpointLoaderLM()
+    result = node.load_checkpoint(
+        "ignored.safetensors", select_at_random=True, base_model="Illustrious"
+    )
+    # Only one checkpoint matches "Illustrious", so the random pick is deterministic here.
+    assert result[3] == "illustrious.safetensors"
+
+
+def test_load_checkpoint_random_selection_raises_when_pool_empty(base_model_library):
+    node = RandomCheckpointLoaderLM()
+    with pytest.raises(FileNotFoundError, match="No checkpoints found"):
+        node.load_checkpoint(
+            "ignored.safetensors", select_at_random=True, base_model="SDXL 1.0"
+        )
+
+
+def test_checkpoint_is_changed_forces_rerun_when_random():
+    assert RandomCheckpointLoaderLM.IS_CHANGED(
+        "a.safetensors", select_at_random=True, base_model="Any"
+    ) != RandomCheckpointLoaderLM.IS_CHANGED(
+        "a.safetensors", select_at_random=True, base_model="Any"
+    )
+    assert RandomCheckpointLoaderLM.IS_CHANGED(
+        "a.safetensors", select_at_random=False, base_model="Any"
+    ) == RandomCheckpointLoaderLM.IS_CHANGED(
+        "a.safetensors", select_at_random=False, base_model="Any"
+    )
@@ -593,3 +593,103 @@ async def test_fetch_missing_license_data_filters_model_ids(monkeypatch):
    assert len(payload["updated"]) == 1
    assert provider_calls == [[20]]
    assert len(saved) == 1
+
+
+def test_serialize_version_permanent_paid_is_not_early_access():
+    """Permanent paid versions (is_paid, no end date) must not be flagged as
+    early access, mirroring _is_early_access_active in the update service."""
+    version = ModelVersionRecord(
+        version_id=7, name="v7", base_model=None, released_at=None, size_bytes=None,
+        preview_url=None, is_in_library=False, should_ignore=False,
+        early_access_ends_at=None, is_early_access=True, usage_control="Download",
+        paid_access=json.dumps({"permanent": True, "endsAt": None}), is_paid=True,
+    )
+    serialized = ModelUpdateHandler._serialize_version(version, None)
+    assert serialized["isEarlyAccess"] is False
+    assert serialized["isPaid"] is True
+    assert serialized["paidAccess"] == {"permanent": True, "endsAt": None}
+
+
+def test_serialize_version_timed_paid_is_early_access():
+    """Timed paid gates (endsAt in the future) stay flagged as early access."""
+    version = ModelVersionRecord(
+        version_id=8, name="v8", base_model=None, released_at=None, size_bytes=None,
+        preview_url=None, is_in_library=False, should_ignore=False,
+        early_access_ends_at="2099-01-01T00:00:00.000Z", is_early_access=True,
+        usage_control="Download",
+        paid_access=json.dumps({"permanent": False, "endsAt": "2099-01-01T00:00:00.000Z"}),
+        is_paid=False,
+    )
+    serialized = ModelUpdateHandler._serialize_version(version, None)
+    assert serialized["isEarlyAccess"] is True
+    assert serialized["isPaid"] is False
+
+
+def test_serialize_version_malformed_paid_access_does_not_crash():
+    """A malformed paid_access row must degrade to None instead of failing
+    the whole versions-list response."""
+    version = ModelVersionRecord(
+        version_id=10, name="v10", base_model=None, released_at=None, size_bytes=None,
+        preview_url=None, is_in_library=False, should_ignore=False,
+        early_access_ends_at=None, is_early_access=True, usage_control=None,
+        paid_access="{not json", is_paid=False,
+    )
+    serialized = ModelUpdateHandler._serialize_version(version, None)
+    assert serialized["paidAccess"] is None
+    assert serialized["isEarlyAccess"] is True
+
+
+async def test_enrich_early_access_details_skips_permanent_paid(monkeypatch):
+    """Permanent paid versions must not trigger per-version CivitAI fetches in
+    _enrich_early_access_details: they are not early access and can never get
+    an end time, so enriching them is wasted API traffic."""
+    record = ModelUpdateRecord(
+        model_type="lora",
+        model_id=1,
+        versions=[
+            ModelVersionRecord(
+                version_id=100, name="paid", base_model=None, released_at=None,
+                size_bytes=None, preview_url=None, is_in_library=False,
+                should_ignore=False, early_access_ends_at=None,
+                is_early_access=True, usage_control="Download",
+                paid_access='{"permanent": true, "endsAt": null}', is_paid=True,
+            ),
+            ModelVersionRecord(
+                version_id=200, name="ea", base_model=None, released_at=None,
+                size_bytes=None, preview_url=None, is_in_library=False,
+                should_ignore=False, early_access_ends_at=None,
+                is_early_access=True, usage_control="Download",
+                paid_access=None, is_paid=False,
+            ),
+        ],
+        last_checked_at=1.0,
+        should_ignore_model=False,
+    )
+
+    fetched: list[int] = []
+
+    async def fake_version_info(version_id: str):
+        fetched.append(int(version_id))
+        return {"earlyAccessEndsAt": "2099-01-01T00:00:00.000Z"}, None
+
+    provider = SimpleNamespace(get_model_version_info=fake_version_info)
+
+    async def metadata_selector(name):
+        assert name == "civitai_api"
+        return provider
+
+    handler = ModelUpdateHandler(
+        service=DummyService(SimpleNamespace(raw_data=[], version_index={})),
+        update_service=SimpleNamespace(),
+        metadata_provider_selector=metadata_selector,
+        settings_service=SimpleNamespace(get=lambda *_: False),
+        logger=logging.getLogger(__name__),
+    )
+
+    enriched = await handler._enrich_early_access_details(record)
+
+    # Only the timed EA version (200) is fetched; the permanent paid one (100) is skipped.
+    assert fetched == [200]
+    enriched_map = {v.version_id: v for v in enriched.versions}
+    assert enriched_map[200].early_access_ends_at == "2099-01-01T00:00:00.000Z"
+    assert enriched_map[100].early_access_ends_at is None
@@ -82,7 +82,9 @@ class StubUpdateService:
        self.bulk_calls = []
        self.bulk_error = bulk_error

-    async def has_updates_bulk(self, model_type, model_ids, hide_early_access: bool = False):
+    async def has_updates_bulk(
+        self, model_type, model_ids, hide_early_access: bool = False, hide_paid: bool = False
+    ):
        self.bulk_calls.append((model_type, list(model_ids)))
        if self.bulk_error:
            raise RuntimeError("bulk failure")
@@ -94,7 +96,9 @@ class StubUpdateService:
            results[model_id] = result
        return results

-    async def has_update(self, model_type, model_id, hide_early_access: bool = False):
+    async def has_update(
+        self, model_type, model_id, hide_early_access: bool = False, hide_paid: bool = False
+    ):
        self.calls.append((model_type, model_id))
        result = self.decisions.get(model_id, False)
        if isinstance(result, Exception):
@@ -123,10 +123,7 @@ def metadata_provider(monkeypatch):
    class DummyProvider:
        def __init__(self):
            self.calls = []
-
-        async def get_model_version(self, model_id, model_version_id):
-            self.calls.append((model_id, model_version_id))
-            return {
+            self.payload = {
                "id": 42,
                "model": {"type": "LoRA", "tags": ["fantasy"]},
                "baseModel": "BaseModel",
@@ -141,6 +138,10 @@ def metadata_provider(monkeypatch):
                ],
            }

+        async def get_model_version(self, model_id, model_version_id):
+            self.calls.append((model_id, model_version_id))
+            return self.payload
+
    provider = DummyProvider()
    monkeypatch.setattr(
        download_manager,
@@ -233,6 +234,217 @@ async def test_successful_download_uses_defaults(
    assert captured["download_urls"] == ["https://example.invalid/file.safetensors"]


+@pytest.mark.asyncio
+async def test_download_accepts_enhancement_lora_primary_file(
+    monkeypatch, scanners, metadata_provider, tmp_path
+):
+    """A version whose only file has type 'Enhancement LoRA' (Anima/AIR
+    image-editing LoRAs) must download — previously failed with
+    "No suitable file found in metadata" because the type was missing from
+    the primary-file weights allowlist."""
+    manager = DownloadManager()
+    metadata_provider.payload = {
+        "id": 3219121,
+        "model": {"type": "LORA", "tags": ["style"]},
+        "baseModel": "Anima",
+        "creator": {"username": "Deskup"},
+        "files": [
+            {
+                "id": 3100968,
+                "type": "Enhancement LoRA",
+                "primary": True,
+                "name": "deskup-anima-edit-general.safetensors",
+                "sizeKB": 358501.13,
+                "downloadUrl": "https://example.invalid/deskup-anima-edit-general.safetensors",
+            }
+        ],
+    }
+
+    captured = {}
+
+    async def fake_execute_download(self, **kwargs):
+        captured.update(
+            {
+                "download_urls": kwargs["download_urls"],
+                "model_type": kwargs["model_type"],
+            }
+        )
+        return {"success": True}
+
+    monkeypatch.setattr(
+        DownloadManager, "_execute_download", fake_execute_download, raising=False
+    )
+
+    result = await manager.download_from_civitai(
+        model_id=2850692,
+        model_version_id=3219121,
+        save_dir=str(tmp_path),
+        use_default_paths=True,
+        progress_callback=None,
+        source=None,
+    )
+
+    assert result["success"] is True
+    assert captured["model_type"] == "lora"
+    assert captured["download_urls"] == [
+        "https://example.invalid/deskup-anima-edit-general.safetensors"
+    ]
+
+
+@pytest.mark.asyncio
+async def test_download_falls_back_to_civitai_primary_flag_regardless_of_type(
+    monkeypatch, scanners, metadata_provider, tmp_path
+):
+    """If no weights-type file exists, trust CivitAI's `primary` flag on any
+    file — mirrors CivitAI's getPrimaryFile() which never excludes a file by
+    type."""
+    manager = DownloadManager()
+    metadata_provider.payload = {
+        "id": 77,
+        "model": {"type": "LORA", "tags": ["concept"]},
+        "baseModel": "Anima",
+        "creator": {"username": "Author"},
+        "files": [
+            {
+                "id": 100,
+                "type": "Other",
+                "primary": True,
+                "name": "custom-type-lora.safetensors",
+                "downloadUrl": "https://example.invalid/custom-type-lora.safetensors",
+            }
+        ],
+    }
+
+    captured = {}
+
+    async def fake_execute_download(self, **kwargs):
+        captured["download_urls"] = kwargs["download_urls"]
+        return {"success": True}
+
+    monkeypatch.setattr(
+        DownloadManager, "_execute_download", fake_execute_download, raising=False
+    )
+
+    result = await manager.download_from_civitai(
+        model_version_id=77,
+        save_dir=str(tmp_path),
+        use_default_paths=True,
+        progress_callback=None,
+        source=None,
+    )
+
+    assert result["success"] is True
+    assert captured["download_urls"] == [
+        "https://example.invalid/custom-type-lora.safetensors"
+    ]
+
+
+@pytest.mark.asyncio
+async def test_download_prefers_weights_file_over_non_weights_primary(
+    monkeypatch, scanners, metadata_provider, tmp_path
+):
+    """A Config/Archive-type primary must never replace an existing weights
+    file — the weights file wins even without the primary flag."""
+    manager = DownloadManager()
+    metadata_provider.payload = {
+        "id": 78,
+        "model": {"type": "LORA", "tags": ["concept"]},
+        "baseModel": "BaseModel",
+        "creator": {"username": "Author"},
+        "files": [
+            {
+                "id": 201,
+                "type": "Config",
+                "primary": True,
+                "name": "config.json",
+                "downloadUrl": "https://example.invalid/config.json",
+            },
+            {
+                "id": 202,
+                "type": "Model",
+                "primary": False,
+                "name": "weights.safetensors",
+                "downloadUrl": "https://example.invalid/weights.safetensors",
+            },
+        ],
+    }
+
+    captured = {}
+
+    async def fake_execute_download(self, **kwargs):
+        captured["download_urls"] = kwargs["download_urls"]
+        return {"success": True}
+
+    monkeypatch.setattr(
+        DownloadManager, "_execute_download", fake_execute_download, raising=False
+    )
+
+    result = await manager.download_from_civitai(
+        model_version_id=78,
+        save_dir=str(tmp_path),
+        use_default_paths=True,
+        progress_callback=None,
+        source=None,
+    )
+
+    assert result["success"] is True
+    assert captured["download_urls"] == [
+        "https://example.invalid/weights.safetensors"
+    ]
+
+
+@pytest.mark.asyncio
+async def test_download_keeps_save_dir_when_use_save_dir_as_root(
+    monkeypatch, scanners, metadata_provider, tmp_path
+):
+    """use_default_paths with use_save_dir_as_root resolves the template under
+    the provided save_dir instead of switching to the default root."""
+    manager = DownloadManager()
+
+    captured = {}
+
+    async def fake_execute_download(
+        self,
+        *,
+        download_urls,
+        save_dir,
+        metadata,
+        version_info,
+        relative_path,
+        progress_callback,
+        model_type,
+        download_id,
+        transfer_backend=None,
+    ):
+        captured.update(
+            {
+                "save_dir": Path(save_dir),
+                "relative_path": relative_path,
+                "model_type": model_type,
+            }
+        )
+        return {"success": True}
+
+    monkeypatch.setattr(
+        DownloadManager, "_execute_download", fake_execute_download, raising=False
+    )
+
+    custom_root = tmp_path / "custom_root"
+    result = await manager.download_from_civitai(
+        model_version_id=99,
+        save_dir=str(custom_root),
+        use_default_paths=True,
+        use_save_dir_as_root=True,
+        progress_callback=None,
+        source=None,
+    )
+
+    assert result["success"] is True
+    assert captured["relative_path"] == "MappedModel/fantasy"
+    assert captured["save_dir"] == custom_root / "MappedModel" / "fantasy"
+    assert captured["model_type"] == "lora"
+
+
@pytest.mark.asyncio
 async def test_successful_download_schedules_auto_example_images(
    monkeypatch, scanners, metadata_provider, tmp_path
@@ -618,6 +830,7 @@ async def test_resume_download_restores_persisted_aria2_task(monkeypatch, tmp_pa
        use_default_paths=False,
        source=None,
        file_params=None,
+        use_save_dir_as_root=False,
    ):
        created.update(
            {
@@ -1037,6 +1250,7 @@ async def test_download_uses_captured_backend_when_settings_change(
        transfer_backend="python",
        source=None,
        file_params=None,
+        use_save_dir_as_root=False,
    ):
        captured["transfer_backend"] = transfer_backend
        return {"success": True}
@@ -59,7 +59,17 @@ class NotFoundProvider:
        return {}


-def make_version(version_id, *, in_library, base_model=None, should_ignore=False):
+def make_version(
+    version_id,
+    *,
+    in_library,
+    base_model=None,
+    should_ignore=False,
+    early_access_ends_at=None,
+    is_early_access=False,
+    is_paid=False,
+    paid_access=None,
+):
    return ModelVersionRecord(
        version_id=version_id,
        name=None,
@@ -69,6 +79,10 @@ def make_version(version_id, *, in_library, base_model=None, should_ignore=False
        preview_url=None,
        is_in_library=in_library,
        should_ignore=should_ignore,
+        early_access_ends_at=early_access_ends_at,
+        is_early_access=is_early_access,
+        is_paid=is_paid,
+        paid_access=paid_access,
    )


@@ -622,3 +636,165 @@ async def test_refresh_folder_filter_considers_cross_folder_versions(tmp_path):
    # has_update must be True (version 20 > max_in_library=15)
    assert record.has_update() is True

+
+def test_extract_single_version_paid_access_timed(tmp_path):
+    """A timed paidAccess gate (permanent=False + future endsAt) is detected
+    as early access while availability stays 'Public'."""
+    db_path = tmp_path / "updates.sqlite"
+    service = ModelUpdateService(str(db_path))
+
+    entry = {
+        "id": 42,
+        "name": "v1 paid",
+        "availability": "Public",
+        "paidAccess": {
+            "permanent": False,
+            "endsAt": "2026-08-22T18:30:00.000Z",
+        },
+        "files": [],
+        "images": [],
+    }
+
+    version = service._extract_single_version(entry, index=0)
+
+    assert version is not None
+    assert version.is_early_access is True
+    assert version.early_access_ends_at == "2026-08-22T18:30:00.000Z"
+    assert version.is_paid is False
+    assert version.paid_access is not None
+
+
+def test_extract_single_version_paid_access_permanent(tmp_path):
+    """A permanent paidAccess gate (permanent=True, no endsAt) is detected and
+    flagged as paid but is NOT early access and carries no end date."""
+    db_path = tmp_path / "updates.sqlite"
+    service = ModelUpdateService(str(db_path))
+
+    entry = {
+        "id": 42,
+        "name": "v1 paid",
+        "availability": "Public",
+        "paidAccess": {"permanent": True, "endsAt": None},
+        "files": [],
+        "images": [],
+    }
+
+    version = service._extract_single_version(entry, index=0)
+
+    assert version is not None
+    assert version.is_early_access is False
+    assert version.is_paid is True
+    assert version.early_access_ends_at is None
+    assert version.paid_access is not None
+
+
+def test_normalize_paid_access_accepts_json_string():
+    """The by-hash enrichment path may hand paidAccess to _normalize_paid_access
+    as a JSON string; both the permanent and timed shapes must normalize."""
+    service = ModelUpdateService.__new__(ModelUpdateService)
+
+    permanent = ModelUpdateService._normalize_paid_access(
+        '{"permanent": true, "endsAt": null}'
+    )
+    assert permanent == {"permanent": True, "endsAt": None}
+
+    timed = ModelUpdateService._normalize_paid_access(
+        '{"permanent": false, "endsAt": "2026-08-22T18:30:00.000Z"}'
+    )
+    assert timed == {"permanent": False, "endsAt": "2026-08-22T18:30:00.000Z"}
+
+    empty = ModelUpdateService._normalize_paid_access(
+        '{"permanent": false, "endsAt": null}'
+    )
+    assert empty is None
+
+    malformed = ModelUpdateService._normalize_paid_access("{not json")
+    assert malformed is None
+
+
+def test_has_update_for_base_hide_paid():
+    """hide_paid also suppresses permanent paid versions in the same-base
+    update path (has_update_for_base)."""
+    record = make_record(
+        make_version(5, in_library=True, base_model="illustrious"),
+        make_version(
+            7,
+            in_library=False,
+            base_model="illustrious",
+            is_paid=True,
+            paid_access='{"permanent": true, "endsAt": null}',
+        ),
+    )
+
+    assert record.has_update_for_base(5, "illustrious") is True
+    assert record.has_update_for_base(5, "illustrious", hide_paid=True) is False
+
+
+def test_has_update_hide_paid():
+    """hide_paid suppresses update flags raised by a permanent paid version."""
+    record = make_record(
+        make_version(5, in_library=True),
+        make_version(
+            7,
+            in_library=False,
+            is_paid=True,
+            paid_access='{"permanent": true, "endsAt": null}',
+        ),
+    )
+
+    assert record.has_update() is True
+    assert record.has_update(hide_paid=True) is False
+
+
+def test_has_update_hide_early_access_paid_timed():
+    """hide_early_access suppresses a newer timed paidAccess version."""
+    record = make_record(
+        make_version(5, in_library=True),
+        make_version(
+            7,
+            in_library=False,
+            is_early_access=True,
+            early_access_ends_at="2099-01-01T00:00:00Z",
+        ),
+    )
+
+    assert record.has_update() is True
+    assert record.has_update(hide_early_access=True) is False
+
+
+
+def test_build_record_from_remote_preserves_paid_fields(tmp_path):
+    """_build_record_from_remote must carry paid_access/is_paid from the
+    parsed remote versions into the rebuilt record, or the refresh path
+    silently drops paid data before persistence."""
+    db_path = tmp_path / "updates.sqlite"
+    service = ModelUpdateService(str(db_path))
+
+    remote_version = ModelVersionRecord(
+        version_id=7,
+        name="v7",
+        base_model=None,
+        released_at=None,
+        size_bytes=None,
+        preview_url=None,
+        is_in_library=False,
+        should_ignore=False,
+        early_access_ends_at=None,
+        is_early_access=True,
+        usage_control="Download",
+        paid_access='{"permanent": true, "endsAt": null}',
+        is_paid=True,
+    )
+
+    record = service._build_record_from_remote(
+        model_type="lora",
+        model_id=123,
+        local_versions=[],
+        remote_versions=[remote_version],
+        existing=None,
+        timestamp=1.0,
+    )
+
+    rebuilt = record.versions[0]
+    assert rebuilt.paid_access == '{"permanent": true, "endsAt": null}'
+    assert rebuilt.is_paid is True
@@ -1047,6 +1047,106 @@ async def test_get_paginated_data_sorting(recipe_scanner):
    assert [i["id"] for i in res["items"]] == ["C", "A", "B"]


+@pytest.mark.asyncio
+async def test_get_paginated_data_random_sort(recipe_scanner):
+    scanner, _ = recipe_scanner
+
+    # Add test recipes
+    for rid, title in [("A", "Alpha"), ("B", "Beta"), ("C", "Gamma")]:
+        await scanner.add_recipe(
+            {
+                "id": rid,
+                "title": title,
+                "created_date": 10.0,
+                "loras": [{}],
+                "file_path": f"{rid.lower()}.png",
+            }
+        )
+
+    await asyncio.sleep(0)
+    await _wait_for_resort(scanner)
+
+    # Same seed -> same order (deterministic, stable pagination)
+    res1 = await scanner.get_paginated_data(
+        page=1, page_size=10, sort_by="random:seed123"
+    )
+    res2 = await scanner.get_paginated_data(
+        page=1, page_size=10, sort_by="random:seed123"
+    )
+    ids1 = [i["id"] for i in res1["items"]]
+    ids2 = [i["id"] for i in res2["items"]]
+    assert ids1 == ids2
+    assert sorted(ids1) == ["A", "B", "C"]
+
+    # Plain "random" (no seed) also returns the full set
+    res3 = await scanner.get_paginated_data(page=1, page_size=10, sort_by="random")
+    assert sorted(i["id"] for i in res3["items"]) == ["A", "B", "C"]
+
+    # Stable pagination: page1 + page2 with the same seed concatenate to the
+    # full seeded order, with no duplicates across pages
+    p1 = await scanner.get_paginated_data(
+        page=1, page_size=2, sort_by="random:seed123"
+    )
+    p2 = await scanner.get_paginated_data(
+        page=2, page_size=2, sort_by="random:seed123"
+    )
+    combined = [i["id"] for i in p1["items"]] + [i["id"] for i in p2["items"]]
+    assert combined == ids1
+    assert len(set(combined)) == 3
+
+
+@pytest.mark.asyncio
+async def test_get_paginated_data_opened_sort(recipe_scanner, monkeypatch):
+    scanner, _ = recipe_scanner
+
+    for rid, title in [("A", "Alpha"), ("B", "Beta"), ("C", "Gamma")]:
+        await scanner.add_recipe(
+            {
+                "id": rid,
+                "title": title,
+                "created_date": 10.0,
+                "loras": [{}],
+                "file_path": f"{rid.lower()}.png",
+            }
+        )
+
+    await asyncio.sleep(0)
+    await _wait_for_resort(scanner)
+
+    class _FakeStats:
+        def get_opened_map(self):
+            return {"B": 300.0, "C": 200.0}
+
+    monkeypatch.setattr(
+        "py.services.recipe_scanner.RecipeOpenStats", lambda: _FakeStats()
+    )
+
+    # Never-opened A is hidden from the view; B (300) > C (200)
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="opened:desc")
+    assert [i["id"] for i in res["items"]] == ["B", "C"]
+    assert res["total"] == 2
+
+    # ASC: C (200) < B (300)
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="opened:asc")
+    assert [i["id"] for i in res["items"]] == ["C", "B"]
+
+    # Plain "opened" (no direction) behaves like desc by default
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="opened")
+    assert [i["id"] for i in res["items"]] == ["B", "C"]
+
+    # When nothing was opened the view is empty (not a fallback reorder)
+    class _EmptyStats:
+        def get_opened_map(self):
+            return {}
+
+    monkeypatch.setattr(
+        "py.services.recipe_scanner.RecipeOpenStats", lambda: _EmptyStats()
+    )
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="opened:desc")
+    assert res["items"] == []
+    assert res["total"] == 0
+
+
 async def test_build_image_id_map_filters_correctly(recipe_scanner):
    """Only recipes with valid CivitAI source_path appear in image_id_map.

@@ -1783,9 +1883,10 @@ async def test_is_rematch_candidate_rejects_healthy_entry(tmp_path: Path):
    assert not scanner._is_rematch_candidate({"hash": "abc", "file_name": "m.safetensors"})


-async def test_is_rematch_candidate_rejects_no_identifier(tmp_path: Path):
+async def test_is_rematch_candidate_file_name_only_is_identifier(tmp_path: Path):
    scanner, _, _ = _make_rematch_scanner([], [], tmp_path)
-    assert not scanner._is_rematch_candidate({"isDeleted": True, "file_name": "m.safetensors"})
+    # file_name alone is now an identifier (enables the L4 filename fallback)
+    assert scanner._is_rematch_candidate({"isDeleted": True, "file_name": "m.safetensors"})
    assert not scanner._is_rematch_candidate({"isDeleted": True})


@@ -2120,6 +2221,481 @@ async def test_match_rematch_type_gate_lora_accepts_lora_typed_item(tmp_path: Pa
        assert matched is not None


+# _match_rematch_entry — L4 filename fallback (conservative)
+
+
+async def test_match_rematch_entry_l4_filename_hit(tmp_path: Path):
+    item = _rematch_item(
+        sha256=("T1" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, lora, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert matched is lora._cache.raw_data[0]
+    assert level == "L4"
+
+
+async def test_match_rematch_entry_l4_filename_normalized_key(tmp_path: Path):
+    # case, path and extension differences are normalized on both sides
+    item = _rematch_item(
+        sha256=("T2" * 32).lower(),
+        sub_type="lora",
+        base_model="SDXL",
+        file_name="My_Mix.safetensors",
+    )
+    scanner, lora, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "subdir/my_mix", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="sdxl",
+    )
+
+    assert matched is lora._cache.raw_data[0]
+    assert level == "L4"
+
+
+async def test_match_rematch_entry_l4_dotted_stem_no_collision(tmp_path: Path):
+    # "my.mix" (dotted stem) and "my" are distinct names — splitext-style
+    # stripping would collapse both to "my" and bind the wrong model as a
+    # unique candidate.
+    item = _rematch_item(
+        sha256=("T2A" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="my.mix",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "my", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_extension_bearing_entry_reconciled(tmp_path: Path):
+    # extension-bearing entry names reconcile with extensionless items
+    item = _rematch_item(
+        sha256=("T2B" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="my.mix.v1",
+    )
+    scanner, lora, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "my.mix.v1.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert matched is lora._cache.raw_data[0]
+    assert level == "L4"
+
+
+async def test_match_rematch_entry_l4_base_model_mismatch_rejects(tmp_path: Path):
+    item = _rematch_item(
+        sha256=("T3" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SDXL",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_recipe_base_model_unknown_rejects(tmp_path: Path):
+    item = _rematch_item(
+        sha256=("T4" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_item_base_model_unknown_rejects(tmp_path: Path):
+    item = _rematch_item(
+        sha256=("T5" * 32).lower(), sub_type="lora", file_name="detail.safetensors"
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_ambiguous_same_base_model_rejects(tmp_path: Path):
+    items = [
+        _rematch_item(
+            sha256=("T6" * 32).lower(),
+            sub_type="lora",
+            base_model="SD 1.5",
+            file_name="detail.safetensors",
+        ),
+        _rematch_item(
+            sha256=("T7" * 32).lower(),
+            sub_type="lora",
+            base_model="SD 1.5",
+            file_name="detail.safetensors",
+        ),
+    ]
+    scanner, _, _ = _make_rematch_scanner(items, [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_ambiguity_resolved_by_base_model(tmp_path: Path):
+    sdxl_item = _rematch_item(
+        sha256=("T8" * 32).lower(),
+        sub_type="lora",
+        base_model="SDXL",
+        file_name="detail.safetensors",
+    )
+    sd15_item = _rematch_item(
+        sha256=("T9" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, lora, _ = _make_rematch_scanner([sdxl_item, sd15_item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SDXL",
+    )
+
+    assert matched is lora._cache.raw_data[0]
+    assert level == "L4"
+
+
+async def test_match_rematch_entry_l4_type_gate_rejects(tmp_path: Path):
+    # a checkpoint-typed item with a matching name must not satisfy a lora entry
+    item = _rematch_item(
+        sha256=("TA" * 32).lower(),
+        sub_type="checkpoint",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_checkpoint_slot_rejects_type_less_candidate(
+    tmp_path: Path,
+):
+    # lora raw items often carry no sub_type; an unknown-type candidate must
+    # not be bound into a checkpoint slot
+    item = _rematch_item(
+        sha256=("TA1" * 32).lower(),
+        base_model="SD 1.5",
+        file_name="realistic.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "realistic.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=True,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_checkpoint_slot_accepts_typed_candidate(
+    tmp_path: Path,
+):
+    item = _rematch_item(
+        sha256=("TA2" * 32).lower(),
+        sub_type="checkpoint",
+        base_model="SD 1.5",
+        file_name="realistic.safetensors",
+    )
+    scanner, _, checkpoint = _make_rematch_scanner([], [item], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "realistic.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=True,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert matched is checkpoint._cache.raw_data[0]
+    assert level == "L4"
+
+
+async def test_match_rematch_entry_l4_lora_slot_accepts_type_less_candidate(tmp_path: Path):
+    # asymmetry: lora slots still accept type-less candidates (the norm for
+    # lora raw items); checkpoint items always carry sub_type, so the type
+    # gate alone protects the reverse direction
+    item = _rematch_item(
+        sha256=("TA3" * 32).lower(), base_model="SD 1.5", file_name="detail.safetensors"
+    )
+    scanner, lora, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "detail.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert matched is lora._cache.raw_data[0]
+    assert level == "L4"
+
+
+async def test_rematch_l4_entry_base_model_preferred_over_recipe(tmp_path: Path, monkeypatch):
+    # a Pony lora inside an SD 1.5 recipe matches via its own baseModel
+    item = _rematch_item(
+        sha256=("TB1" * 32).lower(),
+        sub_type="lora",
+        base_model="Pony",
+        file_name="pony.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+    saved, _ = await _spy_rematch_persistence(scanner, monkeypatch)
+    await _spy_fts(scanner, monkeypatch)
+
+    recipe: Dict[str, Any] = {
+        "id": "r1",
+        "base_model": "SD 1.5",
+        "loras": [
+            {"file_name": "pony.safetensors", "isDeleted": True, "baseModel": "Pony"}
+        ],
+    }
+    rematched, _errors, details = await scanner._rematch_single_recipe(
+        recipe, {}, {}, filename_cache
+    )
+
+    assert rematched == 1
+    assert details["matched"][0]["match_level"] == "L4"
+    assert recipe["loras"][0]["hash"] == ("TB1" * 32).lower()
+    assert saved == [recipe]
+
+
+async def test_rematch_l4_entry_base_model_missing_falls_back_to_recipe(
+    tmp_path: Path, monkeypatch
+):
+    # without entry-level baseModel the recipe-level gate governs: a Pony
+    # candidate must not match an SD 1.5 recipe
+    item = _rematch_item(
+        sha256=("TB2" * 32).lower(),
+        sub_type="lora",
+        base_model="Pony",
+        file_name="pony.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+    await _spy_rematch_persistence(scanner, monkeypatch)
+    await _spy_fts(scanner, monkeypatch)
+
+    recipe: Dict[str, Any] = {
+        "id": "r1",
+        "base_model": "SD 1.5",
+        "loras": [{"file_name": "pony.safetensors", "isDeleted": True}],
+    }
+    rematched, _errors, details = await scanner._rematch_single_recipe(
+        recipe, {}, {}, filename_cache
+    )
+
+    assert rematched == 0
+    assert details["unresolved"] == [{"type": "lora", "entry": "pony.safetensors"}]
+
+
+async def test_match_rematch_entry_l4_no_filename_hit(tmp_path: Path):
+    item = _rematch_item(
+        sha256=("TB" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="other.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"file_name": "missing.safetensors", "isDeleted": True},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l4_entry_without_file_name_skipped(tmp_path: Path):
+    item = _rematch_item(
+        sha256=("TC" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, _, _ = _make_rematch_scanner([item], [], tmp_path)
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"isDeleted": True, "hash": ""},
+        {},
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert (matched, level) == (None, None)
+
+
+async def test_match_rematch_entry_l1_wins_over_l4_filename(tmp_path: Path):
+    # a valid stored hash resolves via L1 even when the filename would match
+    sha256 = ("TD" * 32).lower()
+    l1_item = _rematch_item(
+        sha256=sha256, sub_type="lora", base_model="SD 1.5", file_name="l1-item.safetensors"
+    )
+    l4_item = _rematch_item(
+        sha256=("TE" * 32).lower(),
+        sub_type="lora",
+        base_model="SD 1.5",
+        file_name="detail.safetensors",
+    )
+    scanner, lora, _ = _make_rematch_scanner([l1_item, l4_item], [], tmp_path)
+    local_cache = await scanner.build_local_hash_cache()
+    filename_cache = await scanner._build_local_filename_cache()
+
+    matched, level = await scanner._match_rematch_entry_with_level(
+        {"hash": sha256, "file_name": "detail.safetensors", "isDeleted": True},
+        local_cache,
+        {},
+        is_checkpoint=False,
+        filename_cache=filename_cache,
+        recipe_base_model="SD 1.5",
+    )
+
+    assert matched is lora._cache.raw_data[0]
+    assert level == "L1"
+
+
+# _build_local_filename_cache
+
+
+async def test_build_local_filename_cache_normalized_keys_sha256_only(tmp_path: Path):
+    lora_items = [
+        _rematch_item(sha256=("TF" * 32).lower(), file_name="Case.Mix.safetensors"),
+        _rematch_item(sha256="", file_name="no-hash.safetensors"),  # skipped
+    ]
+    checkpoint_items = [
+        _rematch_item(
+            sha256=("TG" * 32).lower(), sub_type="checkpoint", file_name="Base.safetensors"
+        )
+    ]
+    scanner, lora, checkpoint = _make_rematch_scanner(
+        lora_items, checkpoint_items, tmp_path
+    )
+
+    result = await scanner._build_local_filename_cache()
+
+    assert set(result) == {"case.mix", "base"}
+    assert len(result["case.mix"]) == 1
+    assert result["case.mix"][0] is lora._cache.raw_data[0]
+    # checkpoint items are indexed too (type-blind cache)
+    assert result["base"][0] is checkpoint._cache.raw_data[0]
+
+
 # _build_rematch_autov3_cache


@@ -2989,6 +3565,7 @@ async def test_rematch_all_recipes_per_recipe_error_continues_loop(
        recipe: Dict[str, Any],
        local_cache: dict[str, Any],
        autov3_cache: dict[str, Any],
+        filename_cache=None,
    ) -> tuple[int, int, dict[str, Any]]:
        if recipe.get("id") == "boom":
            raise RuntimeError("kaboom")
@@ -3046,12 +3623,13 @@ async def test_rematch_all_recipes_holds_mutation_lock(tmp_path: Path, monkeypat
        recipe: Dict[str, Any],
        local_cache: dict[str, Any],
        autov3_cache: dict[str, Any],
-    ) -> tuple[int, int]:
+        filename_cache=None,
+    ) -> tuple[int, int, dict[str, Any]]:
        nonlocal entered
        if recipe.get("id") == "r0":
            entered = True
            await release.wait()
-        return await original(recipe, local_cache, autov3_cache)
+        return await original(recipe, local_cache, autov3_cache, filename_cache)

    monkeypatch.setattr(scanner, "_rematch_single_recipe", blocking_single)

@@ -3171,6 +3749,8 @@ async def test_rematch_bulk_generic_exception_continues(tmp_path: Path, monkeypa
        autov3_cache: dict[str, Any],
        *,
        is_checkpoint: bool,
+        filename_cache=None,
+        recipe_base_model=None,
    ) -> Any:
        nonlocal calls
        calls += 1
@@ -0,0 +1,159 @@
+import asyncio
+import contextlib
+import json
+from pathlib import Path
+
+import pytest
+
+from py.utils import recipe_open_stats as stats_module
+from py.utils.recipe_open_stats import RecipeOpenStats
+
+
+async def _finalize(tasks) -> None:
+    for task in tasks:
+        task.cancel()
+        with contextlib.suppress(asyncio.CancelledError):
+            await task
+    RecipeOpenStats._instance = None
+
+
+def _prepare(tmp_path: Path, monkeypatch: pytest.MonkeyPatch):
+    RecipeOpenStats._instance = None
+    settings_dir = tmp_path / "settings"
+    settings_dir.mkdir(parents=True, exist_ok=True)
+    monkeypatch.setattr(
+        stats_module, "get_settings_dir", lambda create=True: str(settings_dir)
+    )
+    created_tasks = []
+    real_create_task = stats_module.asyncio.create_task
+
+    def _track_task(coro):
+        task = real_create_task(coro)
+        created_tasks.append(task)
+        return task
+
+    monkeypatch.setattr(stats_module.asyncio, "create_task", _track_task)
+    return RecipeOpenStats(), created_tasks, settings_dir
+
+
+async def _wait_for_save(stats_file: Path) -> None:
+    for _ in range(100):
+        if stats_file.exists():
+            return
+        await asyncio.sleep(0.01)
+    raise AssertionError("Recipe open stats file was never written")
+
+
+@pytest.mark.asyncio
+async def test_record_open_persists_timestamp(tmp_path, monkeypatch):
+    stats, tasks, settings_dir = _prepare(tmp_path, monkeypatch)
+    stats_file = settings_dir / "stats" / RecipeOpenStats.STATS_FILENAME
+
+    stats.record_open("abc-123")
+    await _wait_for_save(stats_file)
+
+    data = json.loads(stats_file.read_text(encoding="utf-8"))
+    assert isinstance(data["abc-123"], float)
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_record_open_updates_existing_entry(tmp_path, monkeypatch):
+    stats, tasks, settings_dir = _prepare(tmp_path, monkeypatch)
+    stats_file = settings_dir / "stats" / RecipeOpenStats.STATS_FILENAME
+
+    stats.record_open("r1")
+    await _wait_for_save(stats_file)
+    first = json.loads(stats_file.read_text(encoding="utf-8"))["r1"]
+
+    await asyncio.sleep(0.01)
+    stats.record_open("r1")
+    await stats.save_stats(force=True)
+
+    second = json.loads(stats_file.read_text(encoding="utf-8"))["r1"]
+    assert second > first
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_get_opened_map_reloads_on_file_change(tmp_path, monkeypatch):
+    stats, tasks, settings_dir = _prepare(tmp_path, monkeypatch)
+    stats_file = settings_dir / "stats" / RecipeOpenStats.STATS_FILENAME
+
+    stats.record_open("r1")
+    await _wait_for_save(stats_file)
+
+    stats_file.write_text(json.dumps({"r2": 500.0}), encoding="utf-8")
+    opened_map = stats.get_opened_map()
+    assert opened_map == {"r2": 500.0}
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_save_merges_entries_written_by_another_process(tmp_path, monkeypatch):
+    stats, tasks, settings_dir = _prepare(tmp_path, monkeypatch)
+    stats_file = settings_dir / "stats" / RecipeOpenStats.STATS_FILENAME
+
+    stats.record_open("r1")
+    await _wait_for_save(stats_file)
+    first_ts = json.loads(stats_file.read_text(encoding="utf-8"))["r1"]
+
+    # Another process writes its own entry plus a newer timestamp for r1
+    stats_file.write_text(
+        json.dumps({"r1": first_ts + 100000.0, "r2": 500.0}), encoding="utf-8"
+    )
+
+    stats.record_open("r3")
+    await stats.save_stats(force=True)
+
+    data = json.loads(stats_file.read_text(encoding="utf-8"))
+    # r2 from the other process survives; r1 keeps the newer disk timestamp;
+    # r3 from this process is added
+    assert data["r1"] == first_ts + 100000.0
+    assert data["r2"] == 500.0
+    assert isinstance(data["r3"], float)
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_get_opened_map_returns_copy(tmp_path, monkeypatch):
+    stats, tasks, _ = _prepare(tmp_path, monkeypatch)
+    stats.record_open("r1")
+
+    opened_map = stats.get_opened_map()
+    opened_map["injected"] = 1.0
+    assert "injected" not in stats.get_opened_map()
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_missing_stats_file_returns_empty_map(tmp_path, monkeypatch):
+    stats, tasks, _ = _prepare(tmp_path, monkeypatch)
+    assert stats.get_opened_map() == {}
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_save_stats_skips_when_not_dirty(tmp_path, monkeypatch):
+    stats, tasks, settings_dir = _prepare(tmp_path, monkeypatch)
+    stats_file = settings_dir / "stats" / RecipeOpenStats.STATS_FILENAME
+
+    assert await stats.save_stats() is False
+    assert not stats_file.exists()
+    await _finalize(tasks)
+
+
+@pytest.mark.asyncio
+async def test_load_ignores_corrupt_file(tmp_path, monkeypatch):
+    settings_dir = tmp_path / "settings"
+    settings_dir.mkdir(parents=True, exist_ok=True)
+    stats_file = settings_dir / "stats" / RecipeOpenStats.STATS_FILENAME
+    stats_file.parent.mkdir(parents=True, exist_ok=True)
+    stats_file.write_text("{not valid json", encoding="utf-8")
+
+    monkeypatch.setattr(
+        stats_module, "get_settings_dir", lambda create=True: str(settings_dir)
+    )
+    RecipeOpenStats._instance = None
+    stats = RecipeOpenStats()
+    assert stats.get_opened_map() == {}
@@ -78,7 +78,17 @@ const updateHasTextState = () => {
  hasText.value = textareaRef.value ? textareaRef.value.value.length > 0 : false
 }

-const onInput = () => {
+const onInput = (event: Event) => {
+  // A clear via execCommand captures the full-text selection in the browser's
+  // undo entry; Ctrl+Z restores the content together with that selection.
+  // Collapse the caret so the restored text is not left selected.
+  if ((event as InputEvent).inputType === 'historyUndo') {
+    const ta = textareaRef.value
+    if (ta && ta.selectionStart === 0 && ta.selectionEnd === ta.value.length) {
+      ta.setSelectionRange(ta.value.length, ta.value.length)
+    }
+  }
+
  // Update hasText state
  updateHasTextState()
  
@@ -156,20 +166,44 @@ const setupWidgetOnSetValue = () => {
  }
 }

+/**
+ * Clear the textarea contents.
+ *
+ * Uses a trusted editing command (execCommand: select all + replace with
+ * empty string) so the browser records the clear as an undoable edit —
+ * Ctrl+Z with focus in the textarea restores the cleared text. Falls back
+ * to a plain programmatic clear when execCommand is unavailable (e.g. jsdom
+ * test environment), which is not undoable via native Ctrl+Z.
+ */
 const clearText = () => {
-  if (textareaRef.value) {
-    textareaRef.value.value = ''
-    hasText.value = false
-    textareaRef.value.focus()
-    
-    // Trigger callback with empty value
-    if (typeof props.widget.callback === 'function') {
-      props.widget.callback('')
-    }
-    
-    // Dispatch input event to ensure autocomplete handles the change
-    textareaRef.value.dispatchEvent(new Event('input'))
+  const ta = textareaRef.value
+  if (!ta || ta.value.length === 0) return
+
+  // Select all + replace via a trusted edit command so the browser pushes an
+  // undo entry that restores the full previous content.
+  ta.focus()
+  ta.setSelectionRange(0, ta.value.length)
+  let ok = false
+  try {
+    // Guarded for engines without execCommand (jsdom); some engines also
+    // throw instead of returning false for unsupported commands.
+    ok = typeof document.execCommand === 'function' && document.execCommand('insertText', false, '')
+  } catch {
+    ok = false
  }
+
+  if (ok) {
+    // execCommand fired a trusted 'input' event → onInput already synced
+    // hasText, called the widget callback, and notified the autocomplete.
+    hasText.value = false
+    return
+  }
+
+  // Fallback: execCommand unavailable (jsdom / unsupported browser) — plain
+  // programmatic clear. The dispatched input event keeps onInput, the widget
+  // callback, and the autocomplete in sync.
+  ta.value = ''
+  ta.dispatchEvent(new Event('input'))
 }

 onMounted(() => {
@@ -0,0 +1,136 @@
+/**
+ * Tests for AutocompleteTextWidget — clear button behavior.
+ *
+ * The clear button must clear the textarea through a trusted editing command
+ * (execCommand) so the browser records an undo entry and Ctrl+Z (with focus
+ * in the textarea) can restore the cleared content. jsdom's execCommand is a
+ * no-op that returns false, so the fallback manual-clear path is exercised by
+ * default; the execCommand path is covered by emulating the browser edit.
+ */
+
+import { nextTick } from 'vue'
+import { shallowMount } from '@vue/test-utils'
+import { describe, expect, it, vi, afterEach } from 'vitest'
+import AutocompleteTextWidget from '@/components/AutocompleteTextWidget.vue'
+
+function createMockWidget() {
+  return {
+    callback: vi.fn(),
+    onSetValue: undefined,
+    inputEl: undefined,
+    metadataWidget: undefined,
+    name: 'text',
+  }
+}
+
+function mountWidget() {
+  const widget = createMockWidget()
+  const node = { id: 1 }
+  const wrapper = shallowMount(AutocompleteTextWidget, {
+    props: { widget, node, modelType: 'prompt' },
+    // Attach to the document so jsdom implements real focus behavior
+    attachTo: document.body,
+  })
+  return { wrapper, widget }
+}
+
+afterEach(() => {
+  document.body.innerHTML = ''
+  delete (document as unknown as { execCommand?: unknown }).execCommand
+})
+
+describe('AutocompleteTextWidget clear button', () => {
+  it('is hidden when the textarea is empty and appears once text is entered', async () => {
+    const { wrapper } = mountWidget()
+
+    expect(wrapper.find('.clear-button').exists()).toBe(false)
+
+    await wrapper.find('textarea').setValue('hello <lora:foo:1>')
+
+    expect(wrapper.find('.clear-button').exists()).toBe(true)
+  })
+
+  it('clears the textarea via the fallback path when execCommand is unavailable', async () => {
+    const { wrapper, widget } = mountWidget()
+    const textarea = wrapper.find('textarea')
+
+    await textarea.setValue('hello <lora:foo:1>')
+    expect(widget.callback).toHaveBeenLastCalledWith('hello <lora:foo:1>')
+
+    // jsdom does not define document.execCommand at all, so the availability
+    // guard fails and the fallback manual clear runs: value reset + synthetic
+    // input event.
+    await wrapper.find('.clear-button').trigger('click')
+
+    expect((textarea.element as HTMLTextAreaElement).value).toBe('')
+    expect(wrapper.find('.clear-button').exists()).toBe(false)
+    expect(widget.callback).toHaveBeenLastCalledWith('')
+    // Focus returns to the textarea so Ctrl+Z can trigger native undo
+    expect(document.activeElement).toBe(textarea.element)
+  })
+
+  it('clears through a trusted execCommand edit so the browser records an undo entry', async () => {
+    const { wrapper, widget } = mountWidget()
+    const textarea = wrapper.find('textarea')
+
+    await textarea.setValue('hello world')
+    widget.callback.mockClear()
+
+    // Emulate Chromium: replace the selection with the given text, then fire
+    // a trusted input event that Vue and the autocomplete listeners observe.
+    // jsdom has no document.execCommand, so define it for this test.
+    const execMock = vi.fn((_cmd: string, _showUI: boolean, value: string) => {
+      const ta = document.activeElement as HTMLTextAreaElement | null
+      if (!ta || ta.tagName !== 'TEXTAREA') return false
+      ta.value = String(value ?? '')
+      ta.dispatchEvent(new Event('input', { bubbles: true }))
+      return true
+    })
+    Object.defineProperty(document, 'execCommand', { configurable: true, value: execMock })
+
+    await wrapper.find('.clear-button').trigger('click')
+
+    expect(execMock).toHaveBeenCalledWith('insertText', false, '')
+    expect((textarea.element as HTMLTextAreaElement).value).toBe('')
+    // Callback is driven by the trusted input event (exactly once, no double call)
+    expect(widget.callback).toHaveBeenCalledTimes(1)
+    expect(widget.callback).toHaveBeenCalledWith('')
+    expect(wrapper.find('.clear-button').exists()).toBe(false)
+  })
+
+  it('collapses the selection when Ctrl+Z restores the cleared text', async () => {
+    const { wrapper, widget } = mountWidget()
+    const textarea = wrapper.find('textarea')
+    const ta = textarea.element as HTMLTextAreaElement
+
+    await textarea.setValue('hello world')
+    widget.callback.mockClear()
+
+    // Clear via the trusted edit path (emulated Chromium)
+    Object.defineProperty(document, 'execCommand', {
+      configurable: true,
+      value: vi.fn(() => {
+        ta.value = ''
+        ta.dispatchEvent(new Event('input', { bubbles: true }))
+        return true
+      }),
+    })
+    await wrapper.find('.clear-button').trigger('click')
+
+    // Simulate the browser's undo: restore the text and the captured
+    // full-text selection, then fire the historyUndo input event
+    ta.value = 'hello world'
+    ta.setSelectionRange(0, ta.value.length)
+    ta.dispatchEvent(
+      Object.assign(new Event('input', { bubbles: true }), { inputType: 'historyUndo' })
+    )
+    await nextTick()
+
+    expect(ta.value).toBe('hello world')
+    // The restored text must not remain selected — caret collapsed to the end
+    expect(ta.selectionStart).toBe(ta.value.length)
+    expect(ta.selectionEnd).toBe(ta.value.length)
+    expect(wrapper.find('.clear-button').exists()).toBe(true)
+    expect(widget.callback).toHaveBeenLastCalledWith('hello world')
+  })
+})
@@ -33,14 +33,14 @@ const TAG_COMMANDS = {
    '/embedding': { type: 'embedding', label: 'Embeddings' },
    ...WILDCARD_COMMANDS,
    // Autocomplete toggle commands - only show one based on current state
-    '/ac': {
+    '/autocomplete': {
        type: 'toggle_setting',
        settingId: 'loramanager.prompt_tag_autocomplete',
        value: true,
        label: 'Autocomplete: ON',
        condition: () => !getPromptTagAutocompletePreference()
    },
-    '/noac': {
+    '/noautocomplete': {
        type: 'toggle_setting',
        settingId: 'loramanager.prompt_tag_autocomplete',
        value: false,
@@ -50,26 +50,7 @@ const TAG_COMMANDS = {
 };

 // Command definitions for LoRA active-filters search
-// Aliases (/activefilters, /noactivefilters) mirror /emb ↔ /embedding
 const LORAS_COMMANDS = {
-    '/af': {
-        type: 'toggle_setting',
-        settingId: 'loramanager.lora_active_filters_autocomplete',
-        value: true,
-        label: 'Active Filters: ON',
-        feedbackSummary: 'Active Filters Search: ON',
-        feedbackDetail: 'LoRA autocomplete now searches within the active filters of the LoRA Manager page.',
-        condition: () => !getLoraActiveFiltersAutocompletePreference()
-    },
-    '/noaf': {
-        type: 'toggle_setting',
-        settingId: 'loramanager.lora_active_filters_autocomplete',
-        value: false,
-        label: 'Active Filters: OFF',
-        feedbackSummary: 'Active Filters Search: OFF',
-        feedbackDetail: 'LoRA autocomplete searches the full library again.',
-        condition: () => getLoraActiveFiltersAutocompletePreference()
-    },
    '/activefilters': {
        type: 'toggle_setting',
        settingId: 'loramanager.lora_active_filters_autocomplete',
@@ -761,7 +742,7 @@ class AutoComplete {
            searchTerm = (match[1] || '').trim();
        }

-        // For loras model type, check if we're in command mode (/af, /noaf)
+        // For loras model type, check if we're in command mode (/activefilters, /noactivefilters)
        if (this.modelType === 'loras') {
            const commandResult = this._parseCommandInput(rawSearchTerm);

@@ -773,7 +754,7 @@ class AutoComplete {
                this._showCommandList(commandResult.commandFilter);
                return;
            } else if (commandResult.command?.type === 'toggle_setting') {
-                // Handle toggle setting command (/af, /noaf)
+                // Handle toggle setting command (/activefilters, /noactivefilters)
                this._handleToggleSettingCommand(commandResult.command);
                return;
            } else if (commandResult.command) {
@@ -813,7 +794,7 @@ class AutoComplete {
                    this._showCommandList(commandResult.commandFilter);
                    return;
                } else if (commandResult.command?.type === 'toggle_setting') {
-                    // Handle toggle setting command (/ac, /noac)
+                    // Handle toggle setting command (/autocomplete, /noautocomplete)
                    this._handleToggleSettingCommand(commandResult.command);
                    return;
                } else if (commandResult.command) {
@@ -2866,7 +2847,7 @@ class AutoComplete {
    }

    /**
-     * Handle toggle setting command (/ac, /noac)
+     * Handle toggle setting command (e.g., /autocomplete, /activefilters)
     * @param {Object} command - The toggle command with settingId and value
     */
    async _handleToggleSettingCommand(command) {
@@ -36,7 +36,11 @@ function isMapLike(collection) {
    return collection && typeof collection.entries === "function" && typeof collection.values === "function";
 }

-function getChildGraphs(graph) {
+/**
+ * Return the subgraph LGraph instances nested under `graph`, across both
+ * Map-like and plain-object `_subgraphs` containers.
+ */
+export function getChildGraphs(graph) {
    if (!graph || !graph._subgraphs) {
        return [];
    }
@@ -2118,14 +2118,14 @@ to { transform: rotate(360deg);
  padding: 20px 0;
 }

-.autocomplete-text-widget[data-v-55e3316e] {
+.autocomplete-text-widget[data-v-4e322fec] {
  background: transparent;
  height: 100%;
  display: flex;
  flex-direction: column;
  box-sizing: border-box;
 }
-.input-wrapper[data-v-55e3316e] {
+.input-wrapper[data-v-4e322fec] {
  position: relative;
  flex: 1;
  display: flex;
@@ -2133,7 +2133,7 @@ to { transform: rotate(360deg);
 }

 /* Canvas mode styles (default) - matches built-in comfy-multiline-input */
-.text-input[data-v-55e3316e] {
+.text-input[data-v-4e322fec] {
  flex: 1;
  width: 100%;
  background-color: var(--comfy-input-bg, #222);
@@ -2152,7 +2152,7 @@ to { transform: rotate(360deg);
 }

 /* Vue DOM mode styles - matches built-in p-textarea in Vue DOM mode */
-.text-input.vue-dom-mode[data-v-55e3316e] {
+.text-input.vue-dom-mode[data-v-4e322fec] {
  background-color: var(--color-charcoal-400, #313235);
  color: #fff;
  padding: 8px 12px 30px 12px;  /* Reserve bottom space for clear button */
@@ -2161,12 +2161,12 @@ to { transform: rotate(360deg);
  font-size: 12px;
  font-family: inherit;
 }
-.text-input[data-v-55e3316e]:focus {
+.text-input[data-v-4e322fec]:focus {
  outline: none;
 }

 /* Clear button styles */
-.clear-button[data-v-55e3316e] {
+.clear-button[data-v-4e322fec] {
  position: absolute;
  right: 6px;
  bottom: 6px;  /* Changed from top to bottom */
@@ -2189,31 +2189,31 @@ to { transform: rotate(360deg);
 }

 /* Show clear button when hovering over input wrapper */
-.input-wrapper:hover .clear-button[data-v-55e3316e] {
+.input-wrapper:hover .clear-button[data-v-4e322fec] {
  opacity: 0.7;
  pointer-events: auto;
 }
-.clear-button[data-v-55e3316e]:hover {
+.clear-button[data-v-4e322fec]:hover {
  opacity: 1;
  background: rgba(255, 100, 100, 0.8);
 }
-.clear-button svg[data-v-55e3316e] {
+.clear-button svg[data-v-4e322fec] {
  width: 12px;
  height: 12px;
 }

 /* Vue DOM mode adjustments for clear button */
-.text-input.vue-dom-mode ~ .clear-button[data-v-55e3316e] {
+.text-input.vue-dom-mode ~ .clear-button[data-v-4e322fec] {
  right: 8px;
  bottom: 10px;  /* Changed from top to bottom, adjusted for Vue DOM padding */
  width: 20px;
  height: 20px;
  background: rgba(107, 114, 128, 0.6);
 }
-.text-input.vue-dom-mode ~ .clear-button[data-v-55e3316e]:hover {
+.text-input.vue-dom-mode ~ .clear-button[data-v-4e322fec]:hover {
  background: oklch(62% 0.18 25);
 }
-.text-input.vue-dom-mode ~ .clear-button svg[data-v-55e3316e] {
+.text-input.vue-dom-mode ~ .clear-button svg[data-v-4e322fec] {
  width: 14px;
  height: 14px;
 }
@@ -15168,7 +15168,13 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
    const updateHasTextState = () => {
      hasText.value = textareaRef.value ? textareaRef.value.value.length > 0 : false;
    };
-    const onInput = () => {
+    const onInput = (event) => {
+      if (event.inputType === "historyUndo") {
+        const ta = textareaRef.value;
+        if (ta && ta.selectionStart === 0 && ta.selectionEnd === ta.value.length) {
+          ta.setSelectionRange(ta.value.length, ta.value.length);
+        }
+      }
      updateHasTextState();
      if (textareaRef.value && typeof props.widget.callback === "function") {
        props.widget.callback(textareaRef.value.value);
@@ -15215,15 +15221,22 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
      }
    };
    const clearText = () => {
-      if (textareaRef.value) {
-        textareaRef.value.value = "";
-        hasText.value = false;
-        textareaRef.value.focus();
-        if (typeof props.widget.callback === "function") {
-          props.widget.callback("");
-        }
-        textareaRef.value.dispatchEvent(new Event("input"));
+      const ta = textareaRef.value;
+      if (!ta || ta.value.length === 0) return;
+      ta.focus();
+      ta.setSelectionRange(0, ta.value.length);
+      let ok = false;
+      try {
+        ok = typeof document.execCommand === "function" && document.execCommand("insertText", false, "");
+      } catch {
+        ok = false;
      }
+      if (ok) {
+        hasText.value = false;
+        return;
+      }
+      ta.value = "";
+      ta.dispatchEvent(new Event("input"));
    };
    onMounted(() => {
      if (textareaRef.value) {
@@ -15316,7 +15329,7 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
    };
  }
 });
-const AutocompleteTextWidget = /* @__PURE__ */ _export_sfc(_sfc_main$1, [["__scopeId", "data-v-55e3316e"]]);
+const AutocompleteTextWidget = /* @__PURE__ */ _export_sfc(_sfc_main$1, [["__scopeId", "data-v-4e322fec"]]);
 const _hoisted_1 = { class: "lora-info-tabs" };
 const _hoisted_2 = { class: "tab-content notes-tab" };
 const _hoisted_3 = { class: "info-field" };
@@ -1,6 +1,6 @@
 import { app } from "../../scripts/app.js";
 import { api } from "../../scripts/api.js";
-import { getAllGraphNodes, getNodeReference, getNodeFromGraph, chainCallback, getLinkFromGraph } from "./utils.js";
+import { getAllGraphNodes, getNodeReference, getNodeFromGraph, getChildGraphs, chainCallback, getLinkFromGraph } from "./utils.js";
 import { ensureLmStyles } from "./lm_styles_loader.js";

 const DEBOUNCE_DELAY = 500;
@@ -155,6 +155,54 @@ function tryResolvePrimitiveConnection(node, widgetName) {
    return isPrimitiveNodeType(originNode) ? originNode : null;
 }

+/**
+ * Resolve the widget that "send prompt" targets on `node`: the first
+ * string-typed widget, falling back to the first non-hidden widget.
+ * Shared by `isPromptWidgetConnected` and `applyWidgetUpdate` so the
+ * candidate-set logic and the write path cannot drift apart.
+ *
+ * @param {Object} node - LiteGraph node instance
+ * @returns {Object|null} - the target widget, or null when none is suitable
+ */
+function resolveTextWidget(node) {
+    if (!node || !Array.isArray(node.widgets)) {
+        return null;
+    }
+
+    const TEXT_TYPES = new Set(["string", "customtext"]);
+    return (
+        node.widgets.find((w) => {
+            const t = typeof w?.type === "string" ? w.type.toLowerCase() : "";
+            return TEXT_TYPES.has(t) || t.includes("string");
+        }) ??
+        node.widgets.find((w) => w?.name && !w.name.startsWith("_")) ??
+        null
+    );
+}
+
+/**
+ * True when the widget that "send prompt" would update on `node` is backed by
+ * a connected input — ComfyUI execution reads the linked input, so updating
+ * the widget would be a silent no-op. Such nodes must not be offered as
+ * prompt/embedding send targets.
+ *
+ * @param {Object} node - LiteGraph node instance
+ * @returns {boolean}
+ */
+function isPromptWidgetConnected(node) {
+    if (!node || !Array.isArray(node.inputs)) {
+        return false;
+    }
+
+    const targetWidget = resolveTextWidget(node);
+    if (!targetWidget?.name) {
+        return false;
+    }
+
+    const slotIndex = findInputSlotForWidget(node, targetWidget.name);
+    return slotIndex >= 0 && node.inputs[slotIndex]?.link != null;
+}
+
 app.registerExtension({
    name: "LoraManager.WorkflowRegistry",

@@ -209,6 +257,45 @@ app.registerExtension({
            this._log("failed to chain LiteGraph hooks: %s", e.message);
        }

+        // Link connect/disconnect changes whether a widget is externally driven
+        // (e.g. CLIP Text Encode "text" wired to another node), which affects
+        // the text-send candidate set — re-register on connection changes.
+        const hookLinkChanges = (targetGraph) => {
+            if (!targetGraph) {
+                return false;
+            }
+            if (typeof targetGraph.events?.addEventListener === "function") {
+                targetGraph.events.addEventListener("node:slot-links:changed", () =>
+                    scheduleRefresh("link")
+                );
+                return true;
+            }
+            // Classic litegraph: structural edits (incl. link connect/disconnect)
+            // flow through beforeChange/afterChange.
+            chainCallback(targetGraph, "onAfterChange", () => scheduleRefresh("afterChange"));
+            return true;
+        };
+
+        try {
+            if (hookLinkChanges(graph)) {
+                hooksInstalled += 1;
+                // Links wired inside a subgraph dispatch on that subgraph's own
+                // graph events, not the root's — hook existing and future subgraphs.
+                for (const subgraph of getChildGraphs(graph)) {
+                    if (hookLinkChanges(subgraph)) {
+                        hooksInstalled += 1;
+                    }
+                }
+                graph.events?.addEventListener?.("subgraph-created", (event) => {
+                    if (hookLinkChanges(event?.subgraph)) {
+                        hooksInstalled += 1;
+                    }
+                });
+            }
+        } catch (e) {
+            this._log("failed to hook graph link changes: %s", e.message);
+        }
+
        if (typeof api.addEventListener === "function") {
            try {
                api.addEventListener("graphChanged", () => scheduleRefresh("graphChanged"));
@@ -251,6 +338,14 @@ app.registerExtension({
                const hasTextWidget = TEXT_CAPABLE_CLASSES.has(node.comfyClass);
                const markerRole = node.properties?.lm_marker_role ?? null;

+                // A prompt-capable node whose text widget is wired to another
+                // node cannot have its text changed via the widget — execution
+                // reads the linked input. Drop it from text-send candidates.
+                const textWidgetConnected =
+                    hasTextWidget || markerRole === "send_prompt_target"
+                        ? isPromptWidgetConnected(node)
+                        : false;
+
                if (!supportsLora && !hasTargetWidget && !hasTextWidget && !markerRole) {
                    continue;
                }
@@ -275,7 +370,8 @@ app.registerExtension({
                    marker_role: markerRole,
                    capabilities: {
                        supports_lora: supportsLora,
-                        has_text_widget: hasTextWidget,
+                        has_text_widget: hasTextWidget && !textWidgetConnected,
+                        text_widget_connected: textWidgetConnected,
                        widget_names: widgetNames,
                    },
                });
@@ -286,8 +382,10 @@ app.registerExtension({
            // Content-based dedup: skip POST if identical to last sent payload,
            // unless forced (e.g. responding to a lora_registry_refresh WS message
            // where the backend explicitly requests a re-registration).
+            // text_widget_connected is part of the fingerprint so that link
+            // connect/disconnect changes re-register the affected nodes.
            const fingerprint = JSON.stringify(
-                workflowNodes.map(n => `${n.graph_id}:${n.node_id}|${n.marker_role ?? ""}|${n.mode ?? 0}`).sort()
+                workflowNodes.map(n => `${n.graph_id}:${n.node_id}|${n.marker_role ?? ""}|${n.mode ?? 0}|${n.capabilities.text_widget_connected}`).sort()
            );
            if (!force && fingerprint === this._lastFingerprint) {
                return;
@@ -349,28 +447,30 @@ app.registerExtension({
        let targetWidget = null;

        if (action === "inject_text") {
-            // Find the first text-capable widget by type.
-            // Normalise to lowercase for case-insensitive matching.
-            const TEXT_TYPES = new Set(["string", "customtext"]);
-            targetWidget = node.widgets.find((w) => {
-                const t = typeof w?.type === "string" ? w.type.toLowerCase() : "";
-                if (TEXT_TYPES.has(t)) return true;
-                // Broad fallback for unknown composite types.
-                if (t.includes("string")) {
-                    return true;
-                }
-                return false;
-            });
+            targetWidget = resolveTextWidget(node);
            if (!targetWidget) {
-                // Last resort: pick the first widget that is not a hidden/internal type
-                targetWidget = node.widgets.find((w) => w?.name && !w.name.startsWith("_"));
-                if (!targetWidget) {
-                    console.warn(
-                        "LoRA Manager: no suitable widget for inject_text on node",
-                        node.id
-                    );
-                    return;
-                }
+                console.warn(
+                    "LoRA Manager: no suitable widget for inject_text on node",
+                    node.id
+                );
+                return;
+            }
+
+            // The widget is backed by a connected input: ComfyUI execution
+            // reads the linked value, so updating the widget is a no-op.
+            // Guard against stale registry entries (e.g. a link was just
+            // connected before the registry refresh debounce elapsed).
+            const slotIndex = findInputSlotForWidget(node, targetWidget.name);
+            if (slotIndex >= 0 && node.inputs[slotIndex]?.link != null) {
+                console.warn(
+                    "LoRA Manager: widget '%s' on node %d is connected to an input; widget value cannot be changed",
+                    targetWidget.name,
+                    node.id
+                );
+                // Self-heal the registry so the node drops out of the
+                // send-target list instead of being offered again.
+                this.refreshRegistry(true);
+                return;
            }
        } else if (widgetName) {
            // Legacy: find widget by name
Author	SHA1	Message	Date
Will Miao	94dd08646d	chore(release): bump version to v1.2.1	2026-08-16 19:47:15 +08:00
Will Miao	658f88ca48	feat(recipes): add toolbar toggle and settings preview for masonry layout	2026-08-16 15:23:30 +08:00
Will Miao	f53352efb2	feat(metadata): collect generation params from Krea two/three stage samplers	2026-08-16 09:53:08 +08:00
Will Miao	38809a9d1b	feat(recipes): add filename fallback tier to recipe rematch	2026-08-16 09:17:59 +08:00
Will Miao	395682509c	feat(autocomplete): replace /af and /ac toggle abbreviations with full command names	2026-08-15 22:03:54 +08:00
Will Miao	ef3e7d7bf4	feat(update): detect CivitAI paidAccess versions and add hide paid updates (#1060 ) CivitAI's PaidAccess cutover deprecated the availability=EarlyAccess and earlyAccessEndsAt signals; gated versions now report availability=Public with a paidAccess DTO that LoRA Manager previously ignored, so "Hide Early Access Updates" missed paid/early-access models and downloads failed with 401. Parse and persist paidAccess from model-level, bulk, and by-hash responses; treat timed paid gates as early access and permanent paid versions as a distinct is_paid state; add a hide_paid_updates setting with a "Paid" badge in the versions tab; warn before downloading gated versions. Includes SQLite migration, i18n for all locales, and backend/frontend tests.	2026-08-15 18:08:14 +08:00
Will Miao	c85b6b64a1	feat(recipes): add recently opened sort with modal open tracking Track recipe modal opens in a separate stats file (never touching recipe JSON/EXIF), expose a fire-and-forget POST endpoint, and add an 'opened' sort that hides never-opened recipes as a true recently-opened view. Includes i18n for all locales and backend/frontend tests.	2026-08-15 11:37:46 +08:00
Will Miao	34c87d4934	refactor(sort): extract seeded random sort helpers into SortDropdown	2026-08-15 09:53:28 +08:00
Will Miao	93472e5d67	feat(recipes): add sort by random option with seeded stable pagination	2026-08-15 09:50:46 +08:00
Will Miao	ae185ee714	fix(loaders): correct random checkpoint loader return type annotation load_checkpoint returns a 4-tuple (MODEL, CLIP, VAE, model_name) since the random loader exposes the selected model name; the annotation still claimed a 3-tuple.	2026-08-15 08:51:39 +08:00
Martial Michel	795036275a	feat(loaders): add random model selection by base model to checkpoint/unet loaders Add dedicated Random Checkpoint/Unet Loader (LoraManager) nodes that pick a random model from the indexed pool on every run, optionally filtered by base_model, and expose the selected model name via a STRING output.	2026-08-15 08:48:57 +08:00
Will Miao	d43ab6e32f	fix(vue-widgets): make text widget clear button undoable via Ctrl+Z (#1056 )	2026-08-14 23:16:12 +08:00
Will Miao	280181f92e	feat(metadata-overwrite): support wired SAMPLER input on sampler field The sampler field now accepts either a manual string or a SAMPLER connection. When wired, the sampler name is extracted from the KSAMPLER object's sampler_function __name__ (sample_euler -> euler), with special-casing for dpm_fast/dpm_adaptive local closures and uni_pc/uni_pc_bh2 function names. - sampler input declared as "STRING,SAMPLER" with widgetType STRING, mirroring the existing model field union pattern - shared collect_overwrite_params() handles the non-str branch so the node and the metadata extractor conversion logic stay in sync; unrecognized sampler functions are logged and skipped - note: ddim is constructed by ComfyUI as euler with random inpaint, so the ddim name is unrecoverable and extracts as euler	2026-08-14 15:21:28 +08:00
Will Miao	f8d98934ad	feat(ui): set preview via drag and drop on model cards (#1034 )	2026-08-14 13:01:10 +08:00
Will Miao	303cca0d85	fix(download): accept newer CivitAI file types for primary file selection Downloads failed with "No suitable file found in metadata" for models whose only file uses newer CivitAI file types (e.g. 'Enhancement LoRA' for Anima/AIR image-editing LoRAs) because the primary-file allowlist only covered legacy types. - unify the weights-type allowlist as MODEL_WEIGHT_FILE_TYPES (py/utils/constants.py) and apply it across download, recipe and metadata-refresh lookups - mirror CivitAI's getPrimaryFile() semantics: prefer weights-type primary, fall back to weights files, then trust CivitAI's primary flag (excluding non-downloadable artifacts like Config/Archive/Workflow) - mirror the allowlist in the frontend via shared isModelWeightFile() helper - add regression tests for the Enhancement LoRA primary-file download, primary-flag fallback and weights-over-non-weights-primary preference	2026-08-12 21:14:23 +08:00
Will Miao	c2f16784b3	fix(metadata): keep identity selectors from leaking unselected prompts	2026-08-12 19:44:43 +08:00
Will Miao	5bc6d8286c	fix(metadata): exclude scalar fields from conditioning provenance inputs	2026-08-12 19:18:46 +08:00
Luna_K	3f8381ffee	Fix prompt tracking through conditioning transforms	2026-08-12 19:16:30 +08:00
Will Miao	1ca99294c9	feat(delete): shorten undo window to 20s and make undo toast dismissible	2026-08-12 19:15:03 +08:00
Will Miao	680f0a57f5	fix(update): resolve template path when updating to a different base model (#1059 ) Version-tab updates reused the current version's folder, so updating a LoRA to a version with a different base model (e.g. Illustrious -> Anima) ignored the download path template and landed in the old version's directory. When the target version's base model differs from the current local version and a path template is configured, re-resolve the template under the same model root. The backend keeps an explicitly provided root when use_save_dir_as_root is set, so regular downloads still use the default root.	2026-08-12 18:45:54 +08:00
Will Miao	94e3f54571	feat(workflow): exclude text-capable nodes with connected text from send targets CLIP Text Encode and friends whose text widget is backed by a connected input cannot have their text changed via the widget (execution reads the linked input), so sending to them was a silent no-op. - Registry: compute text_widget_connected capability from the widget's backing input link state; has_text_widget drops to false when wired; include the flag in the registration fingerprint so link changes re-register the affected nodes - Registry: hook link connect/disconnect (graph events on new litegraph, onAfterChange fallback for classic) on root and subgraphs, plus subgraph-created for future subgraphs - applyWidgetUpdate: skip inject_text when the target widget is connected and self-heal the registry instead of writing a value that is ignored - Web UI: drop text_widget_connected nodes from prompt/embedding send candidates; show a Mark as -> Send Prompt Target hint toast when no candidates remain (new uiHelpers.workflow.noPromptTargets key, synced to all locales; zh-CN/zh-TW translated) - Extract shared resolveTextWidget() used by both the candidate-set logic and the write path so the two cannot drift apart - Tests: workflow registry connection-state registration, subgraph handling, fingerprint re-registration, inject_text write/skip paths, setup link-change hooks; uiHelpers candidate filtering and hint toast	2026-08-12 16:50:07 +08:00