Merge branch 'sort-by-usage-count' into main

GEMINI.md

@@ -0,0 +1,84 @@
+# ComfyUI LoRA Manager
+
+## Project Overview
+
+ComfyUI LoRA Manager is a comprehensive extension for ComfyUI that streamlines the organization, downloading, and application of LoRA models. It functions as both a custom node within ComfyUI and a standalone application.
+
+**Key Features:**
+*   **Model Management:** Browse, organize, and download LoRA models (and Checkpoints/Embeddings) from Civitai and CivArchive.
+*   **Visualization:** Preview images, videos, and trigger words.
+*   **Workflow Integration:** "One-click" integration into ComfyUI workflows, preserving generation parameters.
+*   **Recipe System:** Save and share LoRA combinations as "recipes".
+*   **Architecture:** Hybrid Python backend (API, file management) and JavaScript/HTML frontend (Web UI).
+
+## Directory Structure
+
+*   `py/`: Core Python backend source code.
+    *   `lora_manager.py`: Main entry point for the ComfyUI node.
+    *   `routes/`: API route definitions (using `aiohttp` in standalone, or ComfyUI's server).
+    *   `services/`: Business logic (downloading, metadata, scanning).
+    *   `nodes/`: ComfyUI custom node implementations.
+*   `static/`: Frontend static assets (CSS, JS, Images).
+*   `templates/`: HTML templates (Jinja2).
+*   `locales/`: Internationalization JSON files.
+*   `web/comfyui/`: JavaScript extensions specifically for the ComfyUI interface.
+*   `standalone.py`: Entry point for running the manager as a standalone web app.
+*   `tests/`: Backend tests.
+*   `requirements.txt`: Python runtime dependencies.
+*   `package.json`: Frontend development dependencies and test scripts.
+
+## Building and Running
+
+### Prerequisites
+*   Python 3.8+
+*   Node.js (only for running frontend tests)
+
+### Backend Setup
+1.  Install Python dependencies:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+### Running in Standalone Mode
+You can run the manager independently of ComfyUI for development or management purposes.
+```bash
+python standalone.py --port 8188
+```
+
+### Running in ComfyUI
+Ensure the folder is located in `ComfyUI/custom_nodes/`. ComfyUI will automatically load it upon startup.
+
+## Testing
+
+### Backend Tests (Pytest)
+1.  Install development dependencies:
+    ```bash
+    pip install -r requirements-dev.txt
+    ```
+2.  Run tests:
+    ```bash
+    pytest
+    ```
+    *   Coverage reports are generated in `coverage/backend/`.
+
+### Frontend Tests (Vitest)
+1.  Install Node dependencies:
+    ```bash
+    npm install
+    ```
+2.  Run tests:
+    ```bash
+    npm run test
+    ```
+3.  Run coverage:
+    ```bash
+    npm run test:coverage
+    ```
+
+## Development Conventions
+
+*   **Python Style:** Follow PEP 8. Use snake_case for files/functions and PascalCase for classes.
+*   **Frontend:** Standard ES modules. UI components often end in `_widget.js`.
+*   **Configuration:** User settings are stored in `settings.json`. Developers should reference `settings.json.example`.
+*   **Localization:** Update `locales/<lang>.json` and run `scripts/sync_translation_keys.py` when changing UI text.
+*   **Documentation:** Architecture details are in `docs/architecture/` and `IFLOW.md`.

__init__.py

@@ -4,7 +4,7 @@ try:  # pragma: no cover - import fallback for pytest collection
     from .py.nodes.trigger_word_toggle import TriggerWordToggle
     from .py.nodes.prompt import PromptLoraManager
     from .py.nodes.lora_stacker import LoraStacker
-    from .py.nodes.save_image import SaveImage
+    from .py.nodes.save_image import SaveImageLM
     from .py.nodes.debug_metadata import DebugMetadata
     from .py.nodes.wanvideo_lora_select import WanVideoLoraSelect
     from .py.nodes.wanvideo_lora_select_from_text import WanVideoLoraSelectFromText
@@ -24,7 +24,7 @@ except ImportError:  # pragma: no cover - allows running under pytest without pa
     LoraManagerTextLoader = importlib.import_module("py.nodes.lora_loader").LoraManagerTextLoader
     TriggerWordToggle = importlib.import_module("py.nodes.trigger_word_toggle").TriggerWordToggle
     LoraStacker = importlib.import_module("py.nodes.lora_stacker").LoraStacker
-    SaveImage = importlib.import_module("py.nodes.save_image").SaveImage
+    SaveImageLM = importlib.import_module("py.nodes.save_image").SaveImageLM
     DebugMetadata = importlib.import_module("py.nodes.debug_metadata").DebugMetadata
     WanVideoLoraSelect = importlib.import_module("py.nodes.wanvideo_lora_select").WanVideoLoraSelect
     WanVideoLoraSelectFromText = importlib.import_module("py.nodes.wanvideo_lora_select_from_text").WanVideoLoraSelectFromText
@@ -36,7 +36,7 @@ NODE_CLASS_MAPPINGS = {
     LoraManagerTextLoader.NAME: LoraManagerTextLoader,
     TriggerWordToggle.NAME: TriggerWordToggle,
     LoraStacker.NAME: LoraStacker,
-    SaveImage.NAME: SaveImage,
+    SaveImageLM.NAME: SaveImageLM,
     DebugMetadata.NAME: DebugMetadata,
     WanVideoLoraSelect.NAME: WanVideoLoraSelect,
     WanVideoLoraSelectFromText.NAME: WanVideoLoraSelectFromText

locales/de.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "Recipe-Daten reparieren",
+            "loading": "Recipe-Daten werden repariert...",
+            "success": "{count} Rezepte erfolgreich repariert.",
+            "error": "Recipe-Reparatur fehlgeschlagen: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "Ersteller",
                 "title": "Rezept-Titel",
                 "loraName": "LoRA-Dateiname",
-                "loraModel": "LoRA-Modellname"
+                "loraModel": "LoRA-Modellname",
+                "prompt": "Prompt"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "Lizenz",
             "noCreditRequired": "Kein Credit erforderlich",
             "allowSellingGeneratedContent": "Verkauf erlaubt",
+            "noTags": "Keine Tags",
             "clearAll": "Alle Filter löschen"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "Vorschau ersetzen",
             "setContentRating": "Inhaltsbewertung festlegen",
             "moveToFolder": "In Ordner verschieben",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "Modell ausschließen",
             "deleteModel": "Modell löschen",
             "shareRecipe": "Rezept teilen",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "Bitte wählen Sie ein LoRA-Stammverzeichnis aus"
                 }
             },
+            "sort": {
+                "title": "Rezepte sortieren nach...",
+                "name": "Name",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "Datum",
+                "dateDesc": "Neueste",
+                "dateAsc": "Älteste",
+                "lorasCount": "LoRA-Anzahl",
+                "lorasCountDesc": "Meiste",
+                "lorasCountAsc": "Wenigste"
+            },
             "refresh": {
                 "title": "Rezeptliste aktualisieren"
             },
-            "filteredByLora": "Gefiltert nach LoRA"
+            "filteredByLora": "Gefiltert nach LoRA",
+            "favorites": {
+                "title": "Nur Favoriten anzeigen",
+                "action": "Favoriten"
+            }
         },
         "duplicates": {
             "found": "{count} Duplikat-Gruppen gefunden",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
                 "getInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
                 "prepareError": "Fehler beim Vorbereiten der LoRAs für den Download: {message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "Rekursive Suche ist nur in der Baumansicht verfügbar",
         "collapseAllDisabled": "Im Listenmodus nicht verfügbar",
         "dragDrop": {
-            "unableToResolveRoot": "Zielpfad für das Verschieben konnte nicht ermittelt werden."
+            "unableToResolveRoot": "Zielpfad für das Verschieben konnte nicht ermittelt werden.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "Fehlgeschlagene Verschiebungen:\n{failures}",
             "bulkMoveSuccess": "{successCount} {type}s erfolgreich verschoben",
             "exampleImagesDownloadSuccess": "Beispielbilder erfolgreich heruntergeladen!",
-            "exampleImagesDownloadFailed": "Fehler beim Herunterladen der Beispielbilder: {message}"
+            "exampleImagesDownloadFailed": "Fehler beim Herunterladen der Beispielbilder: {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/en.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "Repair recipes data",
+            "loading": "Repairing recipe data...",
+            "success": "Successfully repaired {count} recipes.",
+            "error": "Recipe repair failed: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "Creator",
                 "title": "Recipe Title",
                 "loraName": "LoRA Filename",
-                "loraModel": "LoRA Model Name"
+                "loraModel": "LoRA Model Name",
+                "prompt": "Prompt"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "License",
             "noCreditRequired": "No Credit Required",
             "allowSellingGeneratedContent": "Allow Selling",
+            "noTags": "No tags",
             "clearAll": "Clear All Filters"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "Replace Preview",
             "setContentRating": "Set Content Rating",
             "moveToFolder": "Move to Folder",
+            "repairMetadata": "Repair metadata",
             "excludeModel": "Exclude Model",
             "deleteModel": "Delete Model",
             "shareRecipe": "Share Recipe",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "Please select a LoRA root directory"
                 }
             },
+            "sort": {
+                "title": "Sort recipes by...",
+                "name": "Name",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "Date",
+                "dateDesc": "Newest",
+                "dateAsc": "Oldest",
+                "lorasCount": "LoRA Count",
+                "lorasCountDesc": "Most",
+                "lorasCountAsc": "Least"
+            },
             "refresh": {
                 "title": "Refresh recipe list"
             },
-            "filteredByLora": "Filtered by LoRA"
+            "filteredByLora": "Filtered by LoRA",
+            "favorites": {
+                "title": "Show Favorites Only",
+                "action": "Favorites"
+            }
         },
         "duplicates": {
             "found": "Found {count} duplicate groups",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "No missing LoRAs to download",
                 "getInfoFailed": "Failed to get information for missing LoRAs",
                 "prepareError": "Error preparing LoRAs for download: {message}"
+            },
+            "repair": {
+                "starting": "Repairing recipe metadata...",
+                "success": "Recipe metadata repaired successfully",
+                "skipped": "Recipe already at latest version, no repair needed",
+                "failed": "Failed to repair recipe: {message}",
+                "missingId": "Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "Recursive search is available in tree view only",
         "collapseAllDisabled": "Not available in list view",
         "dragDrop": {
-            "unableToResolveRoot": "Unable to determine destination path for move."
+            "unableToResolveRoot": "Unable to determine destination path for move.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "Failed moves:\n{failures}",
             "bulkMoveSuccess": "Successfully moved {successCount} {type}s",
             "exampleImagesDownloadSuccess": "Successfully downloaded example images!",
-            "exampleImagesDownloadFailed": "Failed to download example images: {message}"
+            "exampleImagesDownloadFailed": "Failed to download example images: {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/es.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "Reparar datos de recetas",
+            "loading": "Reparando datos de recetas...",
+            "success": "Se repararon con éxito {count} recetas.",
+            "error": "Error al reparar recetas: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "Creador",
                 "title": "Título de la receta",
                 "loraName": "Nombre de archivo LoRA",
-                "loraModel": "Nombre del modelo LoRA"
+                "loraModel": "Nombre del modelo LoRA",
+                "prompt": "Prompt"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "Licencia",
             "noCreditRequired": "Sin crédito requerido",
             "allowSellingGeneratedContent": "Venta permitida",
+            "noTags": "Sin etiquetas",
             "clearAll": "Limpiar todos los filtros"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "Reemplazar vista previa",
             "setContentRating": "Establecer clasificación de contenido",
             "moveToFolder": "Mover a carpeta",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "Excluir modelo",
             "deleteModel": "Eliminar modelo",
             "shareRecipe": "Compartir receta",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "Por favor selecciona un directorio raíz de LoRA"
                 }
             },
+            "sort": {
+                "title": "Ordenar recetas por...",
+                "name": "Nombre",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "Fecha",
+                "dateDesc": "Más reciente",
+                "dateAsc": "Más antiguo",
+                "lorasCount": "Cant. de LoRAs",
+                "lorasCountDesc": "Más",
+                "lorasCountAsc": "Menos"
+            },
             "refresh": {
                 "title": "Actualizar lista de recetas"
             },
-            "filteredByLora": "Filtrado por LoRA"
+            "filteredByLora": "Filtrado por LoRA",
+            "favorites": {
+                "title": "Mostrar solo favoritos",
+                "action": "Favoritos"
+            }
         },
         "duplicates": {
             "found": "Se encontraron {count} grupos de duplicados",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "No hay LoRAs faltantes para descargar",
                 "getInfoFailed": "Error al obtener información de LoRAs faltantes",
                 "prepareError": "Error preparando LoRAs para descarga: {message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "La búsqueda recursiva solo está disponible en la vista en árbol",
         "collapseAllDisabled": "No disponible en vista de lista",
         "dragDrop": {
-            "unableToResolveRoot": "No se puede determinar la ruta de destino para el movimiento."
+            "unableToResolveRoot": "No se puede determinar la ruta de destino para el movimiento.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "Movimientos fallidos:\n{failures}",
             "bulkMoveSuccess": "Movidos exitosamente {successCount} {type}s",
             "exampleImagesDownloadSuccess": "¡Imágenes de ejemplo descargadas exitosamente!",
-            "exampleImagesDownloadFailed": "Error al descargar imágenes de ejemplo: {message}"
+            "exampleImagesDownloadFailed": "Error al descargar imágenes de ejemplo: {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/fr.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "Réparer les données de recettes",
+            "loading": "Réparation des données de recettes...",
+            "success": "{count} recettes réparées avec succès.",
+            "error": "Échec de la réparation des recettes : {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "Créateur",
                 "title": "Titre de la recipe",
                 "loraName": "Nom de fichier LoRA",
-                "loraModel": "Nom du modèle LoRA"
+                "loraModel": "Nom du modèle LoRA",
+                "prompt": "Prompt"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "Licence",
             "noCreditRequired": "Crédit non requis",
             "allowSellingGeneratedContent": "Vente autorisée",
+            "noTags": "Aucun tag",
             "clearAll": "Effacer tous les filtres"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "Remplacer l'aperçu",
             "setContentRating": "Définir la classification du contenu",
             "moveToFolder": "Déplacer vers un dossier",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "Exclure le modèle",
             "deleteModel": "Supprimer le modèle",
             "shareRecipe": "Partager la recipe",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "Veuillez sélectionner un répertoire racine LoRA"
                 }
             },
+            "sort": {
+                "title": "Trier les recettes par...",
+                "name": "Nom",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "Date",
+                "dateDesc": "Plus récent",
+                "dateAsc": "Plus ancien",
+                "lorasCount": "Nombre de LoRAs",
+                "lorasCountDesc": "Plus",
+                "lorasCountAsc": "Moins"
+            },
             "refresh": {
                 "title": "Actualiser la liste des recipes"
             },
-            "filteredByLora": "Filtré par LoRA"
+            "filteredByLora": "Filtré par LoRA",
+            "favorites": {
+                "title": "Afficher uniquement les favoris",
+                "action": "Favoris"
+            }
         },
         "duplicates": {
             "found": "Trouvé {count} groupes de doublons",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "Aucun LoRA manquant à télécharger",
                 "getInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
                 "prepareError": "Erreur lors de la préparation des LoRAs pour le téléchargement : {message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "La recherche récursive n'est disponible qu'en vue arborescente",
         "collapseAllDisabled": "Non disponible en vue liste",
         "dragDrop": {
-            "unableToResolveRoot": "Impossible de déterminer le chemin de destination pour le déplacement."
+            "unableToResolveRoot": "Impossible de déterminer le chemin de destination pour le déplacement.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "Échecs de déplacement :\n{failures}",
             "bulkMoveSuccess": "{successCount} {type}s déplacés avec succès",
             "exampleImagesDownloadSuccess": "Images d'exemple téléchargées avec succès !",
-            "exampleImagesDownloadFailed": "Échec du téléchargement des images d'exemple : {message}"
+            "exampleImagesDownloadFailed": "Échec du téléchargement des images d'exemple : {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/he.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "תיקון נתוני מתכונים",
+            "loading": "מתקן נתוני מתכונים...",
+            "success": "תוקנו בהצלחה {count} מתכונים.",
+            "error": "תיקון המתכונים נכשל: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "יוצר",
                 "title": "כותרת מתכון",
                 "loraName": "שם קובץ LoRA",
-                "loraModel": "שם מודל LoRA"
+                "loraModel": "שם מודל LoRA",
+                "prompt": "הנחיה"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "רישיון",
             "noCreditRequired": "ללא קרדיט נדרש",
             "allowSellingGeneratedContent": "אפשר מכירה",
+            "noTags": "ללא תגיות",
             "clearAll": "נקה את כל המסננים"
         },
         "theme": {
@@ -228,6 +236,7 @@
             "videoSettings": "הגדרות וידאו",
             "layoutSettings": "הגדרות פריסה",
             "folderSettings": "הגדרות תיקייה",
+            "priorityTags": "תגיות עדיפות",
             "downloadPathTemplates": "תבניות נתיב הורדה",
             "exampleImages": "תמונות דוגמה",
             "updateFlags": "תגי עדכון",
@@ -235,8 +244,7 @@
             "misc": "שונות",
             "metadataArchive": "מסד נתונים של ארכיון מטא-דאטה",
             "storageLocation": "מיקום ההגדרות",
-            "proxySettings": "הגדרות פרוקסי",
-            "priorityTags": "תגיות עדיפות"
+            "proxySettings": "הגדרות פרוקסי"
         },
         "storage": {
             "locationLabel": "מצב נייד",
@@ -309,6 +317,26 @@
             "defaultEmbeddingRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של embedding להורדות, ייבוא והעברות",
             "noDefault": "אין ברירת מחדל"
         },
+        "priorityTags": {
+            "title": "תגיות עדיפות",
+            "description": "התאם את סדר העדיפות של התגיות עבור כל סוג מודל (לדוגמה: character, concept, style(toon|toon_style))",
+            "placeholder": "character, concept, style(toon|toon_style)",
+            "helpLinkLabel": "פתח עזרה בנושא תגיות עדיפות",
+            "modelTypes": {
+                "lora": "LoRA",
+                "checkpoint": "Checkpoint",
+                "embedding": "Embedding"
+            },
+            "saveSuccess": "תגיות העדיפות עודכנו.",
+            "saveError": "עדכון תגיות העדיפות נכשל.",
+            "loadingSuggestions": "טוען הצעות...",
+            "validation": {
+                "missingClosingParen": "לרשומה {index} חסר סוגר סוגריים.",
+                "missingCanonical": "על הרשומה {index} לכלול שם תגית קנונית.",
+                "duplicateCanonical": "התגית הקנונית \"{tag}\" מופיעה יותר מפעם אחת.",
+                "unknown": "תצורת תגיות העדיפות שגויה."
+            }
+        },
         "downloadPathTemplates": {
             "title": "תבניות נתיב הורדה",
             "help": "הגדר מבני תיקיות לסוגי מודלים שונים בעת הורדה מ-Civitai.",
@@ -320,8 +348,8 @@
                 "byFirstTag": "לפי תגית ראשונה",
                 "baseModelFirstTag": "מודל בסיס + תגית ראשונה",
                 "baseModelAuthor": "מודל בסיס + יוצר",
-                "baseModelAuthorFirstTag": "מודל בסיס + יוצר + תגית ראשונה",
                 "authorFirstTag": "יוצר + תגית ראשונה",
+                "baseModelAuthorFirstTag": "מודל בסיס + יוצר + תגית ראשונה",
                 "customTemplate": "תבנית מותאמת אישית"
             },
             "customTemplatePlaceholder": "הזן תבנית מותאמת אישית (למשל, {base_model}/{author}/{first_tag})",
@@ -409,26 +437,6 @@
             "proxyPassword": "סיסמה (אופציונלי)",
             "proxyPasswordPlaceholder": "password",
             "proxyPasswordHelp": "סיסמה לאימות מול הפרוקסי (אם נדרש)"
-        },
-        "priorityTags": {
-            "title": "תגיות עדיפות",
-            "description": "התאם את סדר העדיפות של התגיות עבור כל סוג מודל (לדוגמה: character, concept, style(toon|toon_style))",
-            "placeholder": "character, concept, style(toon|toon_style)",
-            "helpLinkLabel": "פתח עזרה בנושא תגיות עדיפות",
-            "modelTypes": {
-                "lora": "LoRA",
-                "checkpoint": "Checkpoint",
-                "embedding": "Embedding"
-            },
-            "saveSuccess": "תגיות העדיפות עודכנו.",
-            "saveError": "עדכון תגיות העדיפות נכשל.",
-            "loadingSuggestions": "טוען הצעות...",
-            "validation": {
-                "missingClosingParen": "לרשומה {index} חסר סוגר סוגריים.",
-                "missingCanonical": "על הרשומה {index} לכלול שם תגית קנונית.",
-                "duplicateCanonical": "התגית הקנונית \"{tag}\" מופיעה יותר מפעם אחת.",
-                "unknown": "תצורת תגיות העדיפות שגויה."
-            }
         }
     },
     "loras": {
@@ -521,6 +529,7 @@
             "replacePreview": "החלף תצוגה מקדימה",
             "setContentRating": "הגדר דירוג תוכן",
             "moveToFolder": "העבר לתיקייה",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "החרג מודל",
             "deleteModel": "מחק מודל",
             "shareRecipe": "שתף מתכון",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "אנא בחר ספריית שורש של LoRA"
                 }
             },
+            "sort": {
+                "title": "מיון מתכונים לפי...",
+                "name": "שם",
+                "nameAsc": "א - ת",
+                "nameDesc": "ת - א",
+                "date": "תאריך",
+                "dateDesc": "הכי חדש",
+                "dateAsc": "הכי ישן",
+                "lorasCount": "מספר LoRAs",
+                "lorasCountDesc": "הכי הרבה",
+                "lorasCountAsc": "הכי פחות"
+            },
             "refresh": {
                 "title": "רענן רשימת מתכונים"
             },
-            "filteredByLora": "מסונן לפי LoRA"
+            "filteredByLora": "מסונן לפי LoRA",
+            "favorites": {
+                "title": "הצג מועדפים בלבד",
+                "action": "מועדפים"
+            }
         },
         "duplicates": {
             "found": "נמצאו {count} קבוצות כפולות",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "אין LoRAs חסרים להורדה",
                 "getInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
                 "prepareError": "שגיאה בהכנת LoRAs להורדה: {message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "חיפוש רקורסיבי זמין רק בתצוגת עץ",
         "collapseAllDisabled": "לא זמין בתצוגת רשימה",
         "dragDrop": {
-            "unableToResolveRoot": "לא ניתן לקבוע את נתיב היעד להעברה."
+            "unableToResolveRoot": "לא ניתן לקבוע את נתיב היעד להעברה.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "העברות שנכשלו:\n{failures}",
             "bulkMoveSuccess": "הועברו בהצלחה {successCount} {type}s",
             "exampleImagesDownloadSuccess": "תמונות הדוגמה הורדו בהצלחה!",
-            "exampleImagesDownloadFailed": "הורדת תמונות הדוגמה נכשלה: {message}"
+            "exampleImagesDownloadFailed": "הורדת תמונות הדוגמה נכשלה: {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/ja.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "レシピデータの修復",
+            "loading": "レシピデータを修復中...",
+            "success": "{count} 件のレシピを正常に修復しました。",
+            "error": "レシピの修復に失敗しました: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "作成者",
                 "title": "レシピタイトル",
                 "loraName": "LoRAファイル名",
-                "loraModel": "LoRAモデル名"
+                "loraModel": "LoRAモデル名",
+                "prompt": "プロンプト"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "ライセンス",
             "noCreditRequired": "クレジット不要",
             "allowSellingGeneratedContent": "販売許可",
+            "noTags": "タグなし",
             "clearAll": "すべてのフィルタをクリア"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "プレビューを置換",
             "setContentRating": "コンテンツレーティングを設定",
             "moveToFolder": "フォルダに移動",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "モデルを除外",
             "deleteModel": "モデルを削除",
             "shareRecipe": "レシピを共有",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "LoRAルートディレクトリを選択してください"
                 }
             },
+            "sort": {
+                "title": "レシピの並び替え...",
+                "name": "名前",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "日付",
+                "dateDesc": "新しい順",
+                "dateAsc": "古い順",
+                "lorasCount": "LoRA数",
+                "lorasCountDesc": "多い順",
+                "lorasCountAsc": "少ない順"
+            },
             "refresh": {
                 "title": "レシピリストを更新"
             },
-            "filteredByLora": "LoRAでフィルタ済み"
+            "filteredByLora": "LoRAでフィルタ済み",
+            "favorites": {
+                "title": "お気に入りのみ表示",
+                "action": "お気に入り"
+            }
         },
         "duplicates": {
             "found": "{count} 個の重複グループが見つかりました",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "ダウンロードする不足LoRAがありません",
                 "getInfoFailed": "不足LoRAの情報取得に失敗しました",
                 "prepareError": "ダウンロード用LoRAの準備中にエラー：{message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "再帰検索はツリービューでのみ利用できます",
         "collapseAllDisabled": "リストビューでは利用できません",
         "dragDrop": {
-            "unableToResolveRoot": "移動先のパスを特定できません。"
+            "unableToResolveRoot": "移動先のパスを特定できません。",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "失敗した移動：\n{failures}",
             "bulkMoveSuccess": "{successCount} {type}が正常に移動されました",
             "exampleImagesDownloadSuccess": "例画像が正常にダウンロードされました！",
-            "exampleImagesDownloadFailed": "例画像のダウンロードに失敗しました：{message}"
+            "exampleImagesDownloadFailed": "例画像のダウンロードに失敗しました：{message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/ko.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "레시피 데이터 복구",
+            "loading": "레시피 데이터 복구 중...",
+            "success": "{count}개의 레시피가 성공적으로 복구되었습니다.",
+            "error": "레시피 복구 실패: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "제작자",
                 "title": "레시피 제목",
                 "loraName": "LoRA 파일명",
-                "loraModel": "LoRA 모델명"
+                "loraModel": "LoRA 모델명",
+                "prompt": "프롬프트"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "라이선스",
             "noCreditRequired": "크레딧 표기 없음",
             "allowSellingGeneratedContent": "판매 허용",
+            "noTags": "태그 없음",
             "clearAll": "모든 필터 지우기"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "미리보기 교체",
             "setContentRating": "콘텐츠 등급 설정",
             "moveToFolder": "폴더로 이동",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "모델 제외",
             "deleteModel": "모델 삭제",
             "shareRecipe": "레시피 공유",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "LoRA 루트 디렉토리를 선택해주세요"
                 }
             },
+            "sort": {
+                "title": "레시피 정렬...",
+                "name": "이름",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "날짜",
+                "dateDesc": "최신순",
+                "dateAsc": "오래된순",
+                "lorasCount": "LoRA 수",
+                "lorasCountDesc": "많은순",
+                "lorasCountAsc": "적은순"
+            },
             "refresh": {
                 "title": "레시피 목록 새로고침"
             },
-            "filteredByLora": "LoRA로 필터링됨"
+            "filteredByLora": "LoRA로 필터링됨",
+            "favorites": {
+                "title": "즐겨찾기만 표시",
+                "action": "즐겨찾기"
+            }
         },
         "duplicates": {
             "found": "{count}개의 중복 그룹 발견",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
                 "getInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
                 "prepareError": "LoRA 다운로드 준비 중 오류: {message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "재귀 검색은 트리 보기에서만 사용할 수 있습니다",
         "collapseAllDisabled": "목록 보기에서는 사용할 수 없습니다",
         "dragDrop": {
-            "unableToResolveRoot": "이동할 대상 경로를 확인할 수 없습니다."
+            "unableToResolveRoot": "이동할 대상 경로를 확인할 수 없습니다.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "실패한 이동:\n{failures}",
             "bulkMoveSuccess": "{successCount}개 {type}이(가) 성공적으로 이동되었습니다",
             "exampleImagesDownloadSuccess": "예시 이미지가 성공적으로 다운로드되었습니다!",
-            "exampleImagesDownloadFailed": "예시 이미지 다운로드 실패: {message}"
+            "exampleImagesDownloadFailed": "예시 이미지 다운로드 실패: {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/ru.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "Восстановить данные рецептов",
+            "loading": "Восстановление данных рецептов...",
+            "success": "Успешно восстановлено {count} рецептов.",
+            "error": "Ошибка восстановления рецептов: {message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "Автор",
                 "title": "Название рецепта",
                 "loraName": "Имя файла LoRA",
-                "loraModel": "Название модели LoRA"
+                "loraModel": "Название модели LoRA",
+                "prompt": "Запрос"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "Лицензия",
             "noCreditRequired": "Без указания авторства",
             "allowSellingGeneratedContent": "Продажа разрешена",
+            "noTags": "Без тегов",
             "clearAll": "Очистить все фильтры"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "Заменить превью",
             "setContentRating": "Установить рейтинг контента",
             "moveToFolder": "Переместить в папку",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "Исключить модель",
             "deleteModel": "Удалить модель",
             "shareRecipe": "Поделиться рецептом",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "Пожалуйста, выберите корневую папку LoRA"
                 }
             },
+            "sort": {
+                "title": "Сортировка рецептов...",
+                "name": "Имя",
+                "nameAsc": "А - Я",
+                "nameDesc": "Я - А",
+                "date": "Дата",
+                "dateDesc": "Сначала новые",
+                "dateAsc": "Сначала старые",
+                "lorasCount": "Кол-во LoRA",
+                "lorasCountDesc": "Больше всего",
+                "lorasCountAsc": "Меньше всего"
+            },
             "refresh": {
                 "title": "Обновить список рецептов"
             },
-            "filteredByLora": "Фильтр по LoRA"
+            "filteredByLora": "Фильтр по LoRA",
+            "favorites": {
+                "title": "Только избранные",
+                "action": "Избранное"
+            }
         },
         "duplicates": {
             "found": "Найдено {count} групп дубликатов",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
                 "getInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
                 "prepareError": "Ошибка подготовки LoRAs для загрузки: {message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "Рекурсивный поиск доступен только в режиме дерева",
         "collapseAllDisabled": "Недоступно в виде списка",
         "dragDrop": {
-            "unableToResolveRoot": "Не удалось определить путь назначения для перемещения."
+            "unableToResolveRoot": "Не удалось определить путь назначения для перемещения.",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "Неудачные перемещения:\n{failures}",
             "bulkMoveSuccess": "Успешно перемещено {successCount} {type}s",
             "exampleImagesDownloadSuccess": "Примеры изображений успешно загружены!",
-            "exampleImagesDownloadFailed": "Не удалось загрузить примеры изображений: {message}"
+            "exampleImagesDownloadFailed": "Не удалось загрузить примеры изображений: {message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/zh-CN.json

@@ -159,6 +159,12 @@
             "success": "Updated license metadata for {count} {typePlural}",
             "none": "All {typePlural} already have license metadata",
             "error": "Failed to refresh license metadata for {typePlural}: {message}"
+        },
+        "repairRecipes": {
+            "label": "修复配方数据",
+            "loading": "正在修复配方数据...",
+            "success": "成功修复了 {count} 个配方。",
+            "error": "配方修复失败：{message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "创作者",
                 "title": "配方标题",
                 "loraName": "LoRA 文件名",
-                "loraModel": "LoRA 模型名称"
+                "loraModel": "LoRA 模型名称",
+                "prompt": "提示词"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "许可证",
             "noCreditRequired": "无需署名",
             "allowSellingGeneratedContent": "允许销售",
+            "noTags": "无标签",
             "clearAll": "清除所有筛选"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "替换预览",
             "setContentRating": "设置内容评级",
             "moveToFolder": "移动到文件夹",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "排除模型",
             "deleteModel": "删除模型",
             "shareRecipe": "分享配方",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "请选择 LoRA 根目录"
                 }
             },
+            "sort": {
+                "title": "配方排序...",
+                "name": "名称",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "时间",
+                "dateDesc": "最新",
+                "dateAsc": "最早",
+                "lorasCount": "LoRA 数量",
+                "lorasCountDesc": "最多",
+                "lorasCountAsc": "最少"
+            },
             "refresh": {
                 "title": "刷新配方列表"
             },
-            "filteredByLora": "按 LoRA 筛选"
+            "filteredByLora": "按 LoRA 筛选",
+            "favorites": {
+                "title": "仅显示收藏",
+                "action": "收藏"
+            }
         },
         "duplicates": {
             "found": "发现 {count} 个重复组",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "没有缺失的 LoRA 可下载",
                 "getInfoFailed": "获取缺失 LoRA 信息失败",
                 "prepareError": "准备下载 LoRA 时出错：{message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "仅在树形视图中可使用递归搜索",
         "collapseAllDisabled": "列表视图下不可用",
         "dragDrop": {
-            "unableToResolveRoot": "无法确定移动的目标路径。"
+            "unableToResolveRoot": "无法确定移动的目标路径。",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "移动失败：\n{failures}",
             "bulkMoveSuccess": "成功移动 {successCount} 个 {type}",
             "exampleImagesDownloadSuccess": "示例图片下载成功！",
-            "exampleImagesDownloadFailed": "示例图片下载失败：{message}"
+            "exampleImagesDownloadFailed": "示例图片下载失败：{message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

locales/zh-TW.json

@@ -154,11 +154,17 @@
             "error": "清理範例圖片資料夾失敗：{message}"
         },
         "fetchMissingLicenses": {
-            "label": "Refresh license metadata",
-            "loading": "Refreshing license metadata for {typePlural}...",
-            "success": "Updated license metadata for {count} {typePlural}",
-            "none": "All {typePlural} already have license metadata",
-            "error": "Failed to refresh license metadata for {typePlural}: {message}"
+            "label": "重新整理授權中繼資料",
+            "loading": "正在重新整理 {typePlural} 的授權中繼資料...",
+            "success": "已更新 {count} 個 {typePlural} 的授權中繼資料",
+            "none": "所有 {typePlural} 已具備授權中繼資料",
+            "error": "重新整理 {typePlural} 授權中繼資料失敗：{message}"
+        },
+        "repairRecipes": {
+            "label": "修復配方資料",
+            "loading": "正在修復配方資料...",
+            "success": "成功修復 {count} 個配方。",
+            "error": "配方修復失敗：{message}"
         }
     },
     "header": {
@@ -188,7 +194,8 @@
                 "creator": "創作者",
                 "title": "配方標題",
                 "loraName": "LoRA 檔案名稱",
-                "loraModel": "LoRA 模型名稱"
+                "loraModel": "LoRA 模型名稱",
+                "prompt": "提示詞"
             }
         },
         "filter": {
@@ -199,6 +206,7 @@
             "license": "授權",
             "noCreditRequired": "無需署名",
             "allowSellingGeneratedContent": "允許銷售",
+            "noTags": "無標籤",
             "clearAll": "清除所有篩選"
         },
         "theme": {
@@ -521,6 +529,7 @@
             "replacePreview": "更換預覽圖",
             "setContentRating": "設定內容分級",
             "moveToFolder": "移動到資料夾",
+            "repairMetadata": "[TODO: Translate] Repair metadata",
             "excludeModel": "排除模型",
             "deleteModel": "刪除模型",
             "shareRecipe": "分享配方",
@@ -591,10 +600,26 @@
                     "selectLoraRoot": "請選擇 LoRA 根目錄"
                 }
             },
+            "sort": {
+                "title": "配方排序...",
+                "name": "名稱",
+                "nameAsc": "A - Z",
+                "nameDesc": "Z - A",
+                "date": "時間",
+                "dateDesc": "最新",
+                "dateAsc": "最舊",
+                "lorasCount": "LoRA 數量",
+                "lorasCountDesc": "最多",
+                "lorasCountAsc": "最少"
+            },
             "refresh": {
                 "title": "重新整理配方列表"
             },
-            "filteredByLora": "已依 LoRA 篩選"
+            "filteredByLora": "已依 LoRA 篩選",
+            "favorites": {
+                "title": "僅顯示收藏",
+                "action": "收藏"
+            }
         },
         "duplicates": {
             "found": "發現 {count} 組重複項",
@@ -620,6 +645,13 @@
                 "noMissingLoras": "無缺少的 LoRA 可下載",
                 "getInfoFailed": "取得缺少 LoRA 資訊失敗",
                 "prepareError": "準備下載 LoRA 時發生錯誤：{message}"
+            },
+            "repair": {
+                "starting": "[TODO: Translate] Repairing recipe metadata...",
+                "success": "[TODO: Translate] Recipe metadata repaired successfully",
+                "skipped": "[TODO: Translate] Recipe already at latest version, no repair needed",
+                "failed": "[TODO: Translate] Failed to repair recipe: {message}",
+                "missingId": "[TODO: Translate] Cannot repair recipe: Missing recipe ID"
             }
         }
     },
@@ -641,7 +673,8 @@
         "recursiveUnavailable": "遞迴搜尋僅能在樹狀檢視中使用",
         "collapseAllDisabled": "列表檢視下不可用",
         "dragDrop": {
-            "unableToResolveRoot": "無法確定移動的目標路徑。"
+            "unableToResolveRoot": "無法確定移動的目標路徑。",
+            "moveUnsupported": "Move is not supported for this item."
         }
     },
     "statistics": {
@@ -1463,7 +1496,8 @@
             "bulkMoveFailures": "移動失敗：\n{failures}",
             "bulkMoveSuccess": "已成功移動 {successCount} 個 {type}",
             "exampleImagesDownloadSuccess": "範例圖片下載成功！",
-            "exampleImagesDownloadFailed": "下載範例圖片失敗：{message}"
+            "exampleImagesDownloadFailed": "下載範例圖片失敗：{message}",
+            "moveFailed": "Failed to move item: {message}"
         }
     },
     "banners": {

py/config.py

@@ -1,11 +1,13 @@
 import os
 import platform
+import threading
 from pathlib import Path
 import folder_paths # type: ignore
-from typing import Any, Dict, Iterable, List, Mapping, Optional, Set
+from typing import Any, Dict, Iterable, List, Mapping, Optional, Set, Tuple
 import logging
 import json
 import urllib.parse
+import time
 
 from .utils.settings_paths import ensure_settings_file, get_settings_dir, load_settings_template
 
@@ -80,6 +82,8 @@ class Config:
         self._path_mappings: Dict[str, str] = {}
         # Normalized preview root directories used to validate preview access
         self._preview_root_paths: Set[Path] = set()
+        # Optional background rescan thread
+        self._rescan_thread: Optional[threading.Thread] = None
         self.loras_roots = self._init_lora_paths()
         self.checkpoints_roots = None
         self.unet_roots = None
@@ -282,56 +286,23 @@ class Config:
     def _load_symlink_cache(self) -> bool:
         cache_path = self._get_symlink_cache_path()
         if not cache_path.exists():
+            logger.info("Symlink cache not found at %s", cache_path)
             return False
 
         try:
             with cache_path.open("r", encoding="utf-8") as handle:
                 payload = json.load(handle)
         except Exception as exc:
-            logger.debug("Failed to load symlink cache %s: %s", cache_path, exc)
+            logger.info("Failed to load symlink cache %s: %s", cache_path, exc)
             return False
 
         if not isinstance(payload, dict):
+            logger.info("Symlink cache payload is not a dict: %s", type(payload))
             return False
 
-        cached_fingerprint = payload.get("fingerprint")
         cached_mappings = payload.get("path_mappings")
-        if not isinstance(cached_fingerprint, dict) or not isinstance(cached_mappings, Mapping):
-            return False
-
-        current_fingerprint = self._build_symlink_fingerprint()
-        cached_roots = cached_fingerprint.get("roots")
-        cached_stats = cached_fingerprint.get("stats")
-        if (
-            not isinstance(cached_roots, list)
-            or not isinstance(cached_stats, Mapping)
-            or sorted(cached_roots) != sorted(current_fingerprint["roots"])  # type: ignore[index]
-        ):
-            return False
-
-        for root in current_fingerprint["roots"]:  # type: ignore[assignment]
-            cached_stat = cached_stats.get(root) if isinstance(cached_stats, Mapping) else None
-            current_stat = current_fingerprint["stats"].get(root)  # type: ignore[index]
-            if not isinstance(cached_stat, Mapping) or not current_stat:
-                return False
-
-            cached_mtime = cached_stat.get("mtime_ns")
-            cached_inode = cached_stat.get("inode")
-            current_mtime = current_stat.get("mtime_ns")
-            current_inode = current_stat.get("inode")
-
-            if cached_inode != current_inode:
-                return False
-
-            if cached_mtime != current_mtime:
-                cached_noise = cached_stat.get("noise_mtime_ns")
-                current_noise = current_stat.get("noise_mtime_ns")
-                if not (
-                    cached_noise
-                    and current_noise
-                    and cached_mtime == cached_noise
-                    and current_mtime == current_noise
-                ):
+        if not isinstance(cached_mappings, Mapping):
+            logger.info("Symlink cache missing path mappings")
             return False
 
         normalized_mappings: Dict[str, str] = {}
@@ -341,6 +312,7 @@ class Config:
             normalized_mappings[self._normalize_path(target)] = self._normalize_path(link)
 
         self._path_mappings = normalized_mappings
+        logger.info("Symlink cache loaded with %d mappings", len(self._path_mappings))
         return True
 
     def _save_symlink_cache(self) -> None:
@@ -353,22 +325,75 @@ class Config:
         try:
             with cache_path.open("w", encoding="utf-8") as handle:
                 json.dump(payload, handle, ensure_ascii=False, indent=2)
+            logger.info("Symlink cache saved to %s with %d mappings", cache_path, len(self._path_mappings))
         except Exception as exc:
-            logger.debug("Failed to write symlink cache %s: %s", cache_path, exc)
+            logger.info("Failed to write symlink cache %s: %s", cache_path, exc)
 
     def _initialize_symlink_mappings(self) -> None:
-        if not self._load_symlink_cache():
+        start = time.perf_counter()
+        cache_loaded = self._load_symlink_cache()
+
+        if cache_loaded:
+            logger.info(
+                "Symlink mappings restored from cache in %.2f ms",
+                (time.perf_counter() - start) * 1000,
+            )
+            self._rebuild_preview_roots()
+            self._schedule_symlink_rescan()
+            return
+
         self._scan_symbolic_links()
         self._save_symlink_cache()
-        else:
-            logger.info("Loaded symlink mappings from cache")
         self._rebuild_preview_roots()
+        logger.info(
+            "Symlink mappings rebuilt and cached in %.2f ms",
+            (time.perf_counter() - start) * 1000,
+        )
 
     def _scan_symbolic_links(self):
         """Scan all symbolic links in LoRA, Checkpoint, and Embedding root directories"""
+        start = time.perf_counter()
+        # Reset mappings before rescanning to avoid stale entries
+        self._path_mappings.clear()
+        self._seed_root_symlink_mappings()
         visited_dirs: Set[str] = set()
         for root in self._symlink_roots():
             self._scan_directory_links(root, visited_dirs)
+        logger.info(
+            "Symlink scan finished in %.2f ms with %d mappings",
+            (time.perf_counter() - start) * 1000,
+            len(self._path_mappings),
+        )
+
+    def _schedule_symlink_rescan(self) -> None:
+        """Trigger a best-effort background rescan to refresh stale caches."""
+
+        if self._rescan_thread and self._rescan_thread.is_alive():
+            return
+
+        def worker():
+            try:
+                self._scan_symbolic_links()
+                self._save_symlink_cache()
+                self._rebuild_preview_roots()
+                logger.info("Background symlink rescan completed")
+            except Exception as exc:  # pragma: no cover - defensive logging
+                logger.info("Background symlink rescan failed: %s", exc)
+
+        thread = threading.Thread(
+            target=worker,
+            name="lora-manager-symlink-rescan",
+            daemon=True,
+        )
+        self._rescan_thread = thread
+        thread.start()
+
+    def _wait_for_rescan(self, timeout: Optional[float] = None) -> None:
+        """Block until the background rescan completes (testing convenience)."""
+
+        thread = self._rescan_thread
+        if thread:
+            thread.join(timeout=timeout)
 
     def _scan_directory_links(self, root: str, visited_dirs: Set[str]):
         """Iteratively scan directory symlinks to avoid deep recursion."""
@@ -434,6 +459,22 @@ class Config:
         self._preview_root_paths.update(self._expand_preview_root(normalized_target))
         self._preview_root_paths.update(self._expand_preview_root(normalized_link))
 
+    def _seed_root_symlink_mappings(self) -> None:
+        """Ensure symlinked root folders are recorded before deep scanning."""
+
+        for root in self._symlink_roots():
+            if not root:
+                continue
+            try:
+                if not self._is_link(root):
+                    continue
+                target_path = os.path.realpath(root)
+                if not os.path.isdir(target_path):
+                    continue
+                self.add_path_mapping(root, target_path)
+            except Exception as exc:
+                logger.debug("Skipping root symlink %s: %s", root, exc)
+
     def _expand_preview_root(self, path: str) -> Set[Path]:
         """Return normalized ``Path`` objects representing a preview root."""
 

py/metadata_collector/metadata_processor.py

@@ -40,7 +40,38 @@ class MetadataProcessor:
                         candidate_samplers[node_id] = metadata[SAMPLING][node_id]
                 
                     # If we found candidate samplers, apply primary sampler logic to these candidates only
-                if candidate_samplers:
+                    
+                    # PRE-PROCESS: Ensure all candidate samplers have their parameters populated
+                    # This is especially important for SamplerCustomAdvanced which needs tracing
+                    prompt = metadata.get("current_prompt")
+                    for node_id in candidate_samplers:
+                        # If a sampler is missing common parameters like steps or denoise, 
+                        # try to populate them using tracing before ranking
+                        sampler_info = candidate_samplers[node_id]
+                        params = sampler_info.get("parameters", {})
+                        
+                        if prompt and (params.get("steps") is None or params.get("denoise") is None):
+                            # Create a temporary params dict to use the handler
+                            temp_params = {
+                                "steps": params.get("steps"),
+                                "denoise": params.get("denoise"),
+                                "sampler": params.get("sampler_name"),
+                                "scheduler": params.get("scheduler")
+                            }
+                            
+                            # Check if it's SamplerCustomAdvanced
+                            if prompt.original_prompt and node_id in prompt.original_prompt:
+                                if prompt.original_prompt[node_id].get("class_type") == "SamplerCustomAdvanced":
+                                    MetadataProcessor.handle_custom_advanced_sampler(metadata, prompt, node_id, temp_params)
+                                    
+                                    # Update the actual parameters with found values
+                                    params["steps"] = temp_params.get("steps")
+                                    params["denoise"] = temp_params.get("denoise")
+                                    if temp_params.get("sampler"):
+                                        params["sampler_name"] = temp_params.get("sampler")
+                                    if temp_params.get("scheduler"):
+                                        params["scheduler"] = temp_params.get("scheduler")
+
                     # Collect potential primary samplers based on different criteria
                     custom_advanced_samplers = []
                     advanced_add_noise_samplers = []
@@ -49,7 +80,6 @@ class MetadataProcessor:
                     high_denoise_id = None
                     
                     # First, check for SamplerCustomAdvanced among candidates
-                    prompt = metadata.get("current_prompt")
                     if prompt and prompt.original_prompt:
                         for node_id in candidate_samplers:
                             node_info = prompt.original_prompt.get(node_id, {})
@@ -77,15 +107,16 @@ class MetadataProcessor:
                     # Combine all potential primary samplers
                     potential_samplers = custom_advanced_samplers + advanced_add_noise_samplers + high_denoise_samplers
                     
-                    # Find the most recent potential primary sampler (closest to downstream node)
-                    for i in range(downstream_index - 1, -1, -1):
+                    # Find the first potential primary sampler (prefer base sampler over refine)
+                    # Use forward search to prioritize the first one in execution order
+                    for i in range(downstream_index):
                         node_id = execution_order[i]
                         if node_id in potential_samplers:
                             return node_id, candidate_samplers[node_id]
                     
-                    # If no potential sampler found from our criteria, return the most recent sampler
+                    # If no potential sampler found from our criteria, return the first sampler
                     if candidate_samplers:
-                        for i in range(downstream_index - 1, -1, -1):
+                        for i in range(downstream_index):
                             node_id = execution_order[i]
                             if node_id in candidate_samplers:
                                 return node_id, candidate_samplers[node_id]
@@ -176,7 +207,10 @@ class MetadataProcessor:
                 found_node_id = input_value[0]  # Connected node_id
                 
                 # If we're looking for a specific node class
-                if target_class and prompt.original_prompt[found_node_id].get("class_type") == target_class:
+                if target_class:
+                    if found_node_id not in prompt.original_prompt:
+                        return None
+                    if prompt.original_prompt[found_node_id].get("class_type") == target_class:
                         return found_node_id
                 
                 # If we're not looking for a specific class, update the last valid node
@@ -185,11 +219,19 @@ class MetadataProcessor:
                 
                 # Continue tracing through intermediate nodes
                 current_node_id = found_node_id
-                # For most conditioning nodes, the input we want to follow is named "conditioning"
-                if "conditioning" in prompt.original_prompt[current_node_id].get("inputs", {}):
+                
+                # Check if current source node exists
+                if current_node_id not in prompt.original_prompt:
+                    return found_node_id if not target_class else None
+                    
+                # Determine which input to follow next on the source node
+                source_node_inputs = prompt.original_prompt[current_node_id].get("inputs", {})
+                if input_name in source_node_inputs:
+                    current_input = input_name
+                elif "conditioning" in source_node_inputs:
                     current_input = "conditioning"
                 else:
-                    # If there's no "conditioning" input, return the current node
+                    # If there's no suitable input to follow, return the current node
                     # if we're not looking for a specific target_class
                     return found_node_id if not target_class else None
             else:
@@ -202,12 +244,89 @@ class MetadataProcessor:
         return last_valid_node if not target_class else None
     
     @staticmethod
-    def find_primary_checkpoint(metadata):
-        """Find the primary checkpoint model in the workflow"""
+    def trace_model_path(metadata, prompt, start_node_id):
+        """
+        Trace the model connection path upstream to find the checkpoint
+        """
+        if not prompt or not prompt.original_prompt:
+            return None
+            
+        current_node_id = start_node_id
+        depth = 0
+        max_depth = 50
+        
+        while depth < max_depth:
+            # Check if current node is a registered checkpoint in our metadata
+            # This handles cached nodes correctly because metadata contains info for all nodes in the graph
+            if current_node_id in metadata.get(MODELS, {}):
+                if metadata[MODELS][current_node_id].get("type") == "checkpoint":
+                    return current_node_id
+            
+            if current_node_id not in prompt.original_prompt:
+                return None
+                
+            node = prompt.original_prompt[current_node_id]
+            inputs = node.get("inputs", {})
+            class_type = node.get("class_type", "")
+            
+            # Determine which input to follow next
+            next_input_name = "model"
+            
+            # Special handling for initial node
+            if depth == 0:
+                if class_type == "SamplerCustomAdvanced":
+                    next_input_name = "guider"
+            
+            # If the specific input doesn't exist, try generic 'model' 
+            if next_input_name not in inputs:
+                if "model" in inputs:
+                    next_input_name = "model"
+                elif "basic_pipe" in inputs:
+                    # Handle pipe nodes like FromBasicPipe by following the pipeline
+                    next_input_name = "basic_pipe"
+                else:
+                    # Dead end - no model input to follow
+                    return None
+            
+            # Get connected node
+            input_val = inputs[next_input_name]
+            if isinstance(input_val, list) and len(input_val) > 0:
+                current_node_id = input_val[0]
+            else:
+                return None
+                
+            depth += 1
+            
+        return None
+
+    @staticmethod
+    def find_primary_checkpoint(metadata, downstream_id=None, primary_sampler_id=None):
+        """
+        Find the primary checkpoint model in the workflow
+        
+        Parameters:
+        - metadata: The workflow metadata
+        - downstream_id: Optional ID of a downstream node to help identify the specific primary sampler
+        - primary_sampler_id: Optional ID of the primary sampler if already known
+        """
         if not metadata.get(MODELS):
             return None
         
-        # In most workflows, there's only one checkpoint, so we can just take the first one
+        # Method 1: Topology-based tracing (More accurate for complex workflows)
+        # First, find the primary sampler if not provided
+        if not primary_sampler_id:
+            primary_sampler_id, _ = MetadataProcessor.find_primary_sampler(metadata, downstream_id)
+        
+        if primary_sampler_id:
+            prompt = metadata.get("current_prompt")
+            if prompt:
+                # Trace back from the sampler to find the checkpoint
+                checkpoint_id = MetadataProcessor.trace_model_path(metadata, prompt, primary_sampler_id)
+                if checkpoint_id and checkpoint_id in metadata.get(MODELS, {}):
+                    return metadata[MODELS][checkpoint_id].get("name")
+            
+        # Method 2: Fallback to the first available checkpoint (Original behavior)
+        # In most simple workflows, there's only one checkpoint, so we can just take the first one
         for node_id, model_info in metadata.get(MODELS, {}).items():
             if model_info.get("type") == "checkpoint":
                 return model_info.get("name")
@@ -311,7 +430,8 @@ class MetadataProcessor:
         primary_sampler_id, primary_sampler = MetadataProcessor.find_primary_sampler(metadata, id)
         
         # Directly get checkpoint from metadata instead of tracing
-        checkpoint = MetadataProcessor.find_primary_checkpoint(metadata)
+        # Pass primary_sampler_id to avoid redundant calculation
+        checkpoint = MetadataProcessor.find_primary_checkpoint(metadata, id, primary_sampler_id)
         if checkpoint:
             params["checkpoint"] = checkpoint
         
@@ -445,6 +565,7 @@ class MetadataProcessor:
                 scheduler_params = metadata[SAMPLING][scheduler_node_id].get("parameters", {})
                 params["steps"] = scheduler_params.get("steps")
                 params["scheduler"] = scheduler_params.get("scheduler")
+                params["denoise"] = scheduler_params.get("denoise")
         
         # 2. Trace sampler input to find KSamplerSelect (only if sampler input exists)
         if "sampler" in sampler_inputs:

py/nodes/save_image.py

@@ -9,7 +9,7 @@ from ..metadata_collector import get_metadata
 from PIL import Image, PngImagePlugin
 import piexif
 
-class SaveImage:
+class SaveImageLM:
     NAME = "Save Image (LoraManager)"
     CATEGORY = "Lora Manager/utils"
     DESCRIPTION = "Save images with embedded generation metadata in compatible format"

py/nodes/utils.py

@@ -103,7 +103,7 @@ def nunchaku_load_lora(model, lora_name, lora_strength):
     
     # Save the transformer temporarily
     model_wrapper.model = None
-    ret_model = copy.deepcopy(model)  # copy everything except the model
+    ret_model = model.clone()
     ret_model_wrapper = ret_model.model.diffusion_model
     
     # Restore the model and set it for the copy

py/recipes/base.py

@@ -37,7 +37,8 @@ class RecipeMetadataParser(ABC):
         """
         pass
     
-    async def populate_lora_from_civitai(self, lora_entry: Dict[str, Any], civitai_info_tuple: Tuple[Dict[str, Any], Optional[str]], 
+    @staticmethod
+    async def populate_lora_from_civitai(lora_entry: Dict[str, Any], civitai_info_tuple: Tuple[Dict[str, Any], Optional[str]], 
                                          recipe_scanner=None, base_model_counts=None, hash_value=None) -> Optional[Dict[str, Any]]:
         """
         Populate a lora entry with information from Civitai API response
@@ -149,7 +150,8 @@ class RecipeMetadataParser(ABC):
             
         return lora_entry
     
-    async def populate_checkpoint_from_civitai(self, checkpoint: Dict[str, Any], civitai_info: Dict[str, Any]) -> Dict[str, Any]:
+    @staticmethod
+    async def populate_checkpoint_from_civitai(checkpoint: Dict[str, Any], civitai_info: Dict[str, Any]) -> Dict[str, Any]:
         """
         Populate checkpoint information from Civitai API response
         
@@ -187,6 +189,7 @@ class RecipeMetadataParser(ABC):
             checkpoint['downloadUrl'] = civitai_data.get('downloadUrl', '')
 
             checkpoint['modelId'] = civitai_data.get('modelId', checkpoint.get('modelId', 0))
+            checkpoint['id'] = civitai_data.get('id', 0)
 
             if 'files' in civitai_data:
                 model_file = next(

py/recipes/enrichment.py

@@ -0,0 +1,216 @@
+import logging
+import json
+import re
+import os
+from typing import Any, Dict, Optional
+from .merger import GenParamsMerger
+from .base import RecipeMetadataParser
+from ..services.metadata_service import get_default_metadata_provider
+
+logger = logging.getLogger(__name__)
+
+class RecipeEnricher:
+    """Service to enrich recipe metadata from multiple sources (Civitai, Embedded, User)."""
+
+    @staticmethod
+    async def enrich_recipe(
+        recipe: Dict[str, Any],
+        civitai_client: Any,
+        request_params: Optional[Dict[str, Any]] = None
+    ) -> bool:
+        """
+        Enrich a recipe dictionary in-place with metadata from Civitai and embedded params.
+        
+        Args:
+            recipe: The recipe dictionary to enrich. Must have 'gen_params' initialized.
+            civitai_client: Authenticated Civitai client instance.
+            request_params: (Optional) Parameters from a user request (e.g. import).
+            
+        Returns:
+            bool: True if the recipe was modified, False otherwise.
+        """
+        updated = False
+        gen_params = recipe.get("gen_params", {})
+        
+        # 1. Fetch Civitai Info if available
+        civitai_meta = None
+        model_version_id = None
+        
+        source_url = recipe.get("source_url") or recipe.get("source_path", "")
+        
+        # Check if it's a Civitai image URL
+        image_id_match = re.search(r'civitai\.com/images/(\d+)', str(source_url))
+        if image_id_match:
+            image_id = image_id_match.group(1)
+            try:
+                image_info = await civitai_client.get_image_info(image_id)
+                if image_info:
+                    # Handle nested meta often found in Civitai API responses
+                    raw_meta = image_info.get("meta")
+                    if isinstance(raw_meta, dict):
+                        if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
+                            civitai_meta = raw_meta["meta"]
+                        else:
+                            civitai_meta = raw_meta
+                    
+                    model_version_id = image_info.get("modelVersionId")
+                    
+                    # If not at top level, check resources in meta
+                    if not model_version_id and civitai_meta:
+                        resources = civitai_meta.get("civitaiResources", [])
+                        for res in resources:
+                            if res.get("type") == "checkpoint":
+                                model_version_id = res.get("modelVersionId")
+                                break
+            except Exception as e:
+                logger.warning(f"Failed to fetch Civitai image info: {e}")
+
+        # 2. Merge Parameters
+        # Priority: request_params > civitai_meta > embedded (existing gen_params)
+        new_gen_params = GenParamsMerger.merge(
+            request_params=request_params,
+            civitai_meta=civitai_meta,
+            embedded_metadata=gen_params
+        )
+        
+        if new_gen_params != gen_params:
+            recipe["gen_params"] = new_gen_params
+            updated = True
+        
+        # 3. Checkpoint Enrichment
+        # If we have a checkpoint entry, or we can find one
+        # Use 'id' (from Civitai version) as a marker that it's been enriched
+        checkpoint_entry = recipe.get("checkpoint")
+        has_full_checkpoint = checkpoint_entry and checkpoint_entry.get("name") and checkpoint_entry.get("id")
+        
+        if not has_full_checkpoint:
+            # Helper to look up values in priority order
+            def start_lookup(keys):
+                for source in [request_params, civitai_meta, gen_params]:
+                    if source:
+                        if isinstance(keys, list):
+                            for k in keys:
+                                if k in source: return source[k]
+                        else:
+                            if keys in source: return source[keys]
+                return None
+
+            target_version_id = model_version_id or start_lookup("modelVersionId")
+            
+            # Also check existing checkpoint entry
+            if not target_version_id and checkpoint_entry:
+                target_version_id = checkpoint_entry.get("modelVersionId") or checkpoint_entry.get("id")
+            
+            # Check for version ID in resources (which might be a string in gen_params)
+            if not target_version_id:
+                # Look in all sources for "Civitai resources"
+                resources_val = start_lookup(["Civitai resources", "civitai_resources", "resources"])
+                if resources_val:
+                    target_version_id = RecipeEnricher._extract_version_id_from_resources({"Civitai resources": resources_val})
+            
+            target_hash = start_lookup(["Model hash", "checkpoint_hash", "hashes"])
+            if not target_hash and checkpoint_entry:
+                target_hash = checkpoint_entry.get("hash") or checkpoint_entry.get("model_hash")
+            
+            # Look for 'Model' which sometimes is the hash or name
+            model_val = start_lookup("Model")
+
+            # Look for Checkpoint name fallback
+            checkpoint_val = checkpoint_entry.get("name") if checkpoint_entry else None
+            if not checkpoint_val:
+                checkpoint_val = start_lookup(["Checkpoint", "checkpoint"])
+
+            checkpoint_updated = await RecipeEnricher._resolve_and_populate_checkpoint(
+                recipe, target_version_id, target_hash, model_val, checkpoint_val
+            )
+            if checkpoint_updated:
+                updated = True
+        else:
+            # Checkpoint exists, no need to sync to gen_params anymore.
+            pass
+        # base_model resolution moved to _resolve_and_populate_checkpoint to support strict formatting
+        return updated
+        
+    @staticmethod
+    def _extract_version_id_from_resources(gen_params: Dict[str, Any]) -> Optional[Any]:
+        """Try to find modelVersionId in Civitai resources parameter."""
+        civitai_resources_raw = gen_params.get("Civitai resources")
+        if not civitai_resources_raw:
+            return None
+            
+        resources_list = None
+        if isinstance(civitai_resources_raw, str):
+            try:
+                resources_list = json.loads(civitai_resources_raw)
+            except Exception:
+                pass
+        elif isinstance(civitai_resources_raw, list):
+            resources_list = civitai_resources_raw
+            
+        if isinstance(resources_list, list):
+            for res in resources_list:
+                if res.get("type") == "checkpoint":
+                    return res.get("modelVersionId")
+        return None
+
+    @staticmethod
+    async def _resolve_and_populate_checkpoint(
+        recipe: Dict[str, Any], 
+        target_version_id: Optional[Any], 
+        target_hash: Optional[str],
+        model_val: Optional[str],
+        checkpoint_val: Optional[str]
+    ) -> bool:
+        """Find checkpoint metadata and populate it in the recipe."""
+        metadata_provider = await get_default_metadata_provider()
+        civitai_info = None
+        
+        if target_version_id:
+            civitai_info = await metadata_provider.get_model_version_info(str(target_version_id))
+        elif target_hash:
+            civitai_info = await metadata_provider.get_model_by_hash(target_hash)
+        else:
+            # Look for 'Model' which sometimes is the hash or name
+            if model_val and len(model_val) == 10: # Likely a short hash
+                civitai_info = await metadata_provider.get_model_by_hash(model_val)
+                
+        if civitai_info and not (isinstance(civitai_info, tuple) and civitai_info[1] == "Model not found"):
+            # If we already have a partial checkpoint, use it as base
+            existing_cp = recipe.get("checkpoint")
+            if existing_cp is None:
+                existing_cp = {}
+            checkpoint_data = await RecipeMetadataParser.populate_checkpoint_from_civitai(existing_cp, civitai_info)
+            # 1. First, resolve base_model using full data before we format it away
+            current_base_model = recipe.get("base_model")
+            resolved_base_model = checkpoint_data.get("baseModel")
+            if resolved_base_model:
+                # Update if empty OR if it matches our generic prefix but is less specific
+                is_generic = not current_base_model or current_base_model.lower() in ["flux", "sdxl", "sd15"]
+                if is_generic and resolved_base_model != current_base_model:
+                    recipe["base_model"] = resolved_base_model
+            
+            # 2. Format according to requirements: type, modelId, modelVersionId, modelName, modelVersionName
+            formatted_checkpoint = {
+                "type": "checkpoint",
+                "modelId": checkpoint_data.get("modelId"),
+                "modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
+                "modelName": checkpoint_data.get("name"), # In base.py, 'name' is populated from civitai_data['model']['name']
+                "modelVersionName": checkpoint_data.get("version") # In base.py, 'version' is populated from civitai_data['name']
+            }
+            # Remove None values
+            recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
+            
+            return True
+        else:
+            # Fallback to name extraction if we don't already have one
+            existing_cp = recipe.get("checkpoint")
+            if not existing_cp or not existing_cp.get("modelName"):
+                cp_name = checkpoint_val
+                if cp_name:
+                    recipe["checkpoint"] = {
+                        "type": "checkpoint",
+                        "modelName": cp_name
+                    }
+                    return True
+                
+        return False

py/recipes/merger.py

@@ -0,0 +1,98 @@
+from typing import Any, Dict, Optional
+import logging
+
+logger = logging.getLogger(__name__)
+
+class GenParamsMerger:
+    """Utility to merge generation parameters from multiple sources with priority."""
+
+    BLACKLISTED_KEYS = {
+        "id", "url", "userId", "username", "createdAt", "updatedAt", "hash", "meta",
+        "draft", "extra", "width", "height", "process", "quantity", "workflow",
+        "baseModel", "resources", "disablePoi", "aspectRatio", "Created Date",
+        "experimental", "civitaiResources", "civitai_resources", "Civitai resources",
+        "modelVersionId", "modelId", "hashes", "Model", "Model hash", "checkpoint_hash",
+        "checkpoint", "checksum", "model_checksum"
+    }
+    
+    NORMALIZATION_MAPPING = {
+        # Civitai specific
+        "cfgScale": "cfg_scale",
+        "clipSkip": "clip_skip",
+        "negativePrompt": "negative_prompt",
+        # Case variations
+        "Sampler": "sampler",
+        "Steps": "steps",
+        "Seed": "seed",
+        "Size": "size",
+        "Prompt": "prompt",
+        "Negative prompt": "negative_prompt",
+        "Cfg scale": "cfg_scale",
+        "Clip skip": "clip_skip",
+        "Denoising strength": "denoising_strength",
+    }
+
+    @staticmethod
+    def merge(
+        request_params: Optional[Dict[str, Any]] = None,
+        civitai_meta: Optional[Dict[str, Any]] = None,
+        embedded_metadata: Optional[Dict[str, Any]] = None
+    ) -> Dict[str, Any]:
+        """
+        Merge generation parameters from three sources.
+        
+        Priority: request_params > civitai_meta > embedded_metadata
+        
+        Args:
+            request_params: Params provided directly in the import request
+            civitai_meta: Params from Civitai Image API 'meta' field
+            embedded_metadata: Params extracted from image EXIF/embedded metadata
+            
+        Returns:
+            Merged parameters dictionary
+        """
+        result = {}
+
+        # 1. Start with embedded metadata (lowest priority)
+        if embedded_metadata:
+            # If it's a full recipe metadata, we use its gen_params
+            if "gen_params" in embedded_metadata and isinstance(embedded_metadata["gen_params"], dict):
+                GenParamsMerger._update_normalized(result, embedded_metadata["gen_params"])
+            else:
+                # Otherwise assume the dict itself contains gen_params
+                GenParamsMerger._update_normalized(result, embedded_metadata)
+
+        # 2. Layer Civitai meta (medium priority)
+        if civitai_meta:
+            GenParamsMerger._update_normalized(result, civitai_meta)
+
+        # 3. Layer request params (highest priority)
+        if request_params:
+            GenParamsMerger._update_normalized(result, request_params)
+
+        # Filter out blacklisted keys and also the original camelCase keys if they were normalized
+        final_result = {}
+        for k, v in result.items():
+            if k in GenParamsMerger.BLACKLISTED_KEYS:
+                continue
+            if k in GenParamsMerger.NORMALIZATION_MAPPING:
+                continue
+            final_result[k] = v
+            
+        return final_result
+
+    @staticmethod
+    def _update_normalized(target: Dict[str, Any], source: Dict[str, Any]) -> None:
+        """Update target dict with normalized keys from source."""
+        for k, v in source.items():
+            normalized_key = GenParamsMerger.NORMALIZATION_MAPPING.get(k, k)
+            target[normalized_key] = v
+            # Also keep the original key for now if it's not the same, 
+            # so we can filter at the end or avoid losing it if it wasn't supposed to be renamed?
+            # Actually, if we rename it, we should probably NOT keep both in 'target' 
+            # because we want to filter them out at the end anyway.
+            if normalized_key != k:
+                # If we are overwriting an existing snake_case key with a camelCase one's value,
+                # that's fine because of the priority order of calls to _update_normalized.
+                pass
+            target[k] = v

py/recipes/parsers/comfy.py

@@ -36,9 +36,6 @@ class ComfyMetadataParser(RecipeMetadataParser):
             # Find all LoraLoader nodes
             lora_nodes = {k: v for k, v in data.items() if isinstance(v, dict) and v.get('class_type') == 'LoraLoader'}
             
-            if not lora_nodes:
-                return {"error": "No LoRA information found in this ComfyUI workflow", "loras": []}
-            
             # Process each LoraLoader node
             for node_id, node in lora_nodes.items():
                 if 'inputs' not in node or 'lora_name' not in node['inputs']:

py/routes/base_recipe_routes.py

@@ -79,26 +79,8 @@ class BaseRecipeRoutes:
             return
 
         app.on_startup.append(self.attach_dependencies)
-        app.on_startup.append(self.prewarm_cache)
         self._startup_hooks_registered = True
 
-    async def prewarm_cache(self, app: web.Application | None = None) -> None:
-        """Pre-load recipe and LoRA caches on startup."""
-
-        try:
-            await self.attach_dependencies(app)
-
-            if self.lora_scanner is not None:
-                await self.lora_scanner.get_cached_data()
-                hash_index = getattr(self.lora_scanner, "_hash_index", None)
-                if hash_index is not None and hasattr(hash_index, "_hash_to_path"):
-                    _ = len(hash_index._hash_to_path)
-
-            if self.recipe_scanner is not None:
-                await self.recipe_scanner.get_cached_data(force_refresh=True)
-        except Exception as exc:
-            logger.error("Error pre-warming recipe cache: %s", exc, exc_info=True)
-
     def to_route_mapping(self) -> Mapping[str, Callable]:
         """Return a mapping of handler name to coroutine for registrar binding."""
 

py/routes/handlers/model_handlers.py

@@ -5,6 +5,7 @@ import asyncio
 import json
 import logging
 import os
+import time
 from dataclasses import dataclass
 from typing import Any, Awaitable, Callable, Dict, Iterable, List, Mapping, Optional
 
@@ -61,6 +62,37 @@ class ModelPageView:
         self._settings = settings_service
         self._server_i18n = server_i18n
         self._logger = logger
+        self._app_version = self._get_app_version()
+
+    def _get_app_version(self) -> str:
+        version = "1.0.0"
+        short_hash = "stable"
+        try:
+            import toml
+            current_file = os.path.abspath(__file__)
+            # Navigate up from py/routes/handlers/model_handlers.py to project root
+            root_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(current_file))))
+            pyproject_path = os.path.join(root_dir, 'pyproject.toml')
+            
+            if os.path.exists(pyproject_path):
+                with open(pyproject_path, 'r', encoding='utf-8') as f:
+                    data = toml.load(f)
+                    version = data.get('project', {}).get('version', '1.0.0').replace('v', '')
+            
+            # Try to get git info for granular cache busting
+            git_dir = os.path.join(root_dir, '.git')
+            if os.path.exists(git_dir):
+                try:
+                    import git
+                    repo = git.Repo(root_dir)
+                    short_hash = repo.head.commit.hexsha[:7]
+                except Exception:
+                    # Fallback if git is not available or not a repo
+                    pass
+        except Exception as e:
+            self._logger.debug(f"Failed to read version info for cache busting: {e}")
+            
+        return f"{version}-{short_hash}"
 
     async def handle(self, request: web.Request) -> web.Response:
         try:
@@ -96,6 +128,7 @@ class ModelPageView:
                 "request": request,
                 "folders": [],
                 "t": self._server_i18n.get_translation,
+                "version": self._app_version,
             }
 
             if not is_initializing:
@@ -128,9 +161,12 @@ class ModelListingHandler:
         self._logger = logger
 
     async def get_models(self, request: web.Request) -> web.Response:
+        start_time = time.perf_counter()
         try:
             params = self._parse_common_params(request)
             result = await self._service.get_paginated_data(**params)
+            
+            format_start = time.perf_counter()
             formatted_result = {
                 "items": [await self._service.format_response(item) for item in result["items"]],
                 "total": result["total"],
@@ -138,6 +174,13 @@ class ModelListingHandler:
                 "page_size": result["page_size"],
                 "total_pages": result["total_pages"],
             }
+            format_duration = time.perf_counter() - format_start
+            
+            duration = time.perf_counter() - start_time
+            self._logger.info(
+                "Request for %s/list took %.3fs (formatting: %.3fs)",
+                self._service.model_type, duration, format_duration
+            )
             return web.json_response(formatted_result)
         except Exception as exc:
             self._logger.error("Error retrieving %ss: %s", self._service.model_type, exc, exc_info=True)

py/routes/handlers/recipe_handlers.py

@@ -5,6 +5,7 @@ import json
 import logging
 import os
 import re
+import asyncio
 import tempfile
 from dataclasses import dataclass
 from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional
@@ -23,6 +24,11 @@ from ...services.recipes import (
     RecipeValidationError,
 )
 from ...services.metadata_service import get_default_metadata_provider
+from ...utils.civitai_utils import rewrite_preview_url
+from ...utils.exif_utils import ExifUtils
+from ...recipes.merger import GenParamsMerger
+from ...recipes.enrichment import RecipeEnricher
+from ...services.websocket_manager import ws_manager as default_ws_manager
 
 Logger = logging.Logger
 EnsureDependenciesCallable = Callable[[], Awaitable[None]]
@@ -55,16 +61,25 @@ class RecipeHandlerSet:
             "delete_recipe": self.management.delete_recipe,
             "get_top_tags": self.query.get_top_tags,
             "get_base_models": self.query.get_base_models,
+            "get_roots": self.query.get_roots,
+            "get_folders": self.query.get_folders,
+            "get_folder_tree": self.query.get_folder_tree,
+            "get_unified_folder_tree": self.query.get_unified_folder_tree,
             "share_recipe": self.sharing.share_recipe,
             "download_shared_recipe": self.sharing.download_shared_recipe,
             "get_recipe_syntax": self.query.get_recipe_syntax,
             "update_recipe": self.management.update_recipe,
             "reconnect_lora": self.management.reconnect_lora,
             "find_duplicates": self.query.find_duplicates,
+            "move_recipes_bulk": self.management.move_recipes_bulk,
             "bulk_delete": self.management.bulk_delete,
             "save_recipe_from_widget": self.management.save_recipe_from_widget,
             "get_recipes_for_lora": self.query.get_recipes_for_lora,
             "scan_recipes": self.query.scan_recipes,
+            "move_recipe": self.management.move_recipe,
+            "repair_recipes": self.management.repair_recipes,
+            "repair_recipe": self.management.repair_recipe,
+            "get_repair_progress": self.management.get_repair_progress,
         }
 
 
@@ -148,12 +163,15 @@ class RecipeListingHandler:
             page_size = int(request.query.get("page_size", "20"))
             sort_by = request.query.get("sort_by", "date")
             search = request.query.get("search")
+            folder = request.query.get("folder")
+            recursive = request.query.get("recursive", "true").lower() == "true"
 
             search_options = {
                 "title": request.query.get("search_title", "true").lower() == "true",
                 "tags": request.query.get("search_tags", "true").lower() == "true",
                 "lora_name": request.query.get("search_lora_name", "true").lower() == "true",
                 "lora_model": request.query.get("search_lora_model", "true").lower() == "true",
+                "prompt": request.query.get("search_prompt", "true").lower() == "true",
             }
 
             filters: Dict[str, Any] = {}
@@ -161,6 +179,9 @@ class RecipeListingHandler:
             if base_models:
                 filters["base_model"] = base_models.split(",")
 
+            if request.query.get("favorite", "false").lower() == "true":
+                filters["favorite"] = True
+
             tag_filters: Dict[str, str] = {}
             legacy_tags = request.query.get("tags")
             if legacy_tags:
@@ -192,6 +213,8 @@ class RecipeListingHandler:
                 filters=filters,
                 search_options=search_options,
                 lora_hash=lora_hash,
+                folder=folder,
+                recursive=recursive,
             )
 
             for item in result.get("items", []):
@@ -298,6 +321,58 @@ class RecipeQueryHandler:
             self._logger.error("Error retrieving base models: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def get_roots(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            roots = [recipe_scanner.recipes_dir] if recipe_scanner.recipes_dir else []
+            return web.json_response({"success": True, "roots": roots})
+        except Exception as exc:
+            self._logger.error("Error retrieving recipe roots: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_folders(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            folders = await recipe_scanner.get_folders()
+            return web.json_response({"success": True, "folders": folders})
+        except Exception as exc:
+            self._logger.error("Error retrieving recipe folders: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_folder_tree(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            folder_tree = await recipe_scanner.get_folder_tree()
+            return web.json_response({"success": True, "tree": folder_tree})
+        except Exception as exc:
+            self._logger.error("Error retrieving recipe folder tree: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_unified_folder_tree(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            folder_tree = await recipe_scanner.get_folder_tree()
+            return web.json_response({"success": True, "tree": folder_tree})
+        except Exception as exc:
+            self._logger.error("Error retrieving unified recipe folder tree: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def get_recipes_for_lora(self, request: web.Request) -> web.Response:
         try:
             await self._ensure_dependencies_ready()
@@ -410,6 +485,7 @@ class RecipeManagementHandler:
         analysis_service: RecipeAnalysisService,
         downloader_factory,
         civitai_client_getter: CivitaiClientGetter,
+        ws_manager=default_ws_manager,
     ) -> None:
         self._ensure_dependencies_ready = ensure_dependencies_ready
         self._recipe_scanner_getter = recipe_scanner_getter
@@ -418,6 +494,7 @@ class RecipeManagementHandler:
         self._analysis_service = analysis_service
         self._downloader_factory = downloader_factory
         self._civitai_client_getter = civitai_client_getter
+        self._ws_manager = ws_manager
 
     async def save_recipe(self, request: web.Request) -> web.Response:
         try:
@@ -436,6 +513,7 @@ class RecipeManagementHandler:
                 name=payload["name"],
                 tags=payload["tags"],
                 metadata=payload["metadata"],
+                extension=payload.get("extension"),
             )
             return web.json_response(result.payload, status=result.status)
         except RecipeValidationError as exc:
@@ -444,6 +522,71 @@ class RecipeManagementHandler:
             self._logger.error("Error saving recipe: %s", exc, exc_info=True)
             return web.json_response({"error": str(exc)}, status=500)
 
+    async def repair_recipes(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                return web.json_response({"success": False, "error": "Recipe scanner unavailable"}, status=503)
+
+            # Check if already running
+            if self._ws_manager.get_recipe_repair_progress():
+                return web.json_response({"success": False, "error": "Recipe repair already in progress"}, status=409)
+
+            async def progress_callback(data):
+                await self._ws_manager.broadcast_recipe_repair_progress(data)
+
+            # Run in background to avoid timeout
+            async def run_repair():
+                try:
+                    await recipe_scanner.repair_all_recipes(
+                        progress_callback=progress_callback
+                    )
+                except Exception as e:
+                    self._logger.error(f"Error in recipe repair task: {e}", exc_info=True)
+                    await self._ws_manager.broadcast_recipe_repair_progress({
+                        "status": "error",
+                        "error": str(e)
+                    })
+                finally:
+                    # Keep the final status for a while so the UI can see it
+                    await asyncio.sleep(5)
+                    self._ws_manager.cleanup_recipe_repair_progress()
+
+            asyncio.create_task(run_repair())
+
+            return web.json_response({"success": True, "message": "Recipe repair started"})
+        except Exception as exc:
+            self._logger.error("Error starting recipe repair: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def repair_recipe(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                return web.json_response({"success": False, "error": "Recipe scanner unavailable"}, status=503)
+
+            recipe_id = request.match_info["recipe_id"]
+            result = await recipe_scanner.repair_recipe_by_id(recipe_id)
+            return web.json_response(result)
+        except RecipeNotFoundError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=404)
+        except Exception as exc:
+            self._logger.error("Error repairing single recipe: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_repair_progress(self, request: web.Request) -> web.Response:
+        try:
+            progress = self._ws_manager.get_recipe_repair_progress()
+            if progress:
+                return web.json_response({"success": True, "progress": progress})
+            return web.json_response({"success": False, "message": "No repair in progress"}, status=404)
+        except Exception as exc:
+            self._logger.error("Error getting repair progress: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+
     async def import_remote_recipe(self, request: web.Request) -> web.Response:
         try:
             await self._ensure_dependencies_ready()
@@ -451,10 +594,12 @@ class RecipeManagementHandler:
             if recipe_scanner is None:
                 raise RuntimeError("Recipe scanner unavailable")
             
+            # 1. Parse Parameters
             params = request.rel_url.query
             image_url = params.get("image_url")
             name = params.get("name")
             resources_raw = params.get("resources")
+            
             if not image_url:
                 raise RecipeValidationError("Missing required field: image_url")
             if not name:
@@ -463,27 +608,93 @@ class RecipeManagementHandler:
                 raise RecipeValidationError("Missing required field: resources")
 
             checkpoint_entry, lora_entries = self._parse_resources_payload(resources_raw)
-            gen_params = self._parse_gen_params(params.get("gen_params"))
+            gen_params_request = self._parse_gen_params(params.get("gen_params"))
+            
+            # 2. Initial Metadata Construction
             metadata: Dict[str, Any] = {
                 "base_model": params.get("base_model", "") or "",
                 "loras": lora_entries,
+                "gen_params": gen_params_request or {},
+                "source_url": image_url
             }
+            
             source_path = params.get("source_path")
             if source_path:
                 metadata["source_path"] = source_path
-            if gen_params is not None:
-                metadata["gen_params"] = gen_params
+                
+            # Checkpoint handling
             if checkpoint_entry:
                 metadata["checkpoint"] = checkpoint_entry
-                gen_params_ref = metadata.setdefault("gen_params", {})
-                if "checkpoint" not in gen_params_ref:
-                    gen_params_ref["checkpoint"] = checkpoint_entry
+                # Ensure checkpoint is also in gen_params for consistency if needed by enricher?
+                # Actually enricher looks at metadata['checkpoint'], so this is fine.
+                
+                # Try to resolve base model from checkpoint if not explicitly provided
+                if not metadata["base_model"]:
                     base_model_from_metadata = await self._resolve_base_model_from_checkpoint(checkpoint_entry)
                     if base_model_from_metadata:
                         metadata["base_model"] = base_model_from_metadata
 
             tags = self._parse_tags(params.get("tags"))
-            image_bytes = await self._download_image_bytes(image_url)
+            
+            # 3. Download Image
+            image_bytes, extension, civitai_meta_from_download = await self._download_remote_media(image_url)
+
+            # 4. Extract Embedded Metadata
+            # Note: We still extract this here because Enricher currently expects 'gen_params' to already be populated 
+            # with embedded data if we want it to merge it. 
+            # However, logic in Enricher merges: request > civitai > embedded.
+            # So we should gather embedded params and put them into the recipe's gen_params (as initial state) 
+            # OR pass them to enricher to handle?
+            # The interface of Enricher.enrich_recipe takes `recipe` (with gen_params) and `request_params`.
+            # So let's extract embedded and put it into recipe['gen_params'] but careful not to overwrite request params.
+            # Actually, `GenParamsMerger` which `Enricher` uses handles 3 layers.
+            # But `Enricher` interface is: recipe['gen_params'] (as embedded) + request_params + civitai (fetched internally).
+            # Wait, `Enricher` fetches Civitai info internally based on URL. 
+            # `civitai_meta_from_download` is returned by `_download_remote_media` which might be useful if URL didn't have ID.
+            
+            # Let's extract embedded metadata first
+            embedded_gen_params = {}
+            try:
+                with tempfile.NamedTemporaryFile(suffix=extension, delete=False) as temp_img:
+                    temp_img.write(image_bytes)
+                    temp_img_path = temp_img.name
+                
+                try:
+                    raw_embedded = ExifUtils.extract_image_metadata(temp_img_path)
+                    if raw_embedded:
+                        parser = self._analysis_service._recipe_parser_factory.create_parser(raw_embedded)
+                        if parser:
+                            parsed_embedded = await parser.parse_metadata(raw_embedded, recipe_scanner=recipe_scanner)
+                            if parsed_embedded and "gen_params" in parsed_embedded:
+                                embedded_gen_params = parsed_embedded["gen_params"]
+                        else:
+                            embedded_gen_params = {"raw_metadata": raw_embedded}
+                finally:
+                    if os.path.exists(temp_img_path):
+                        os.unlink(temp_img_path)
+            except Exception as exc:
+                self._logger.warning("Failed to extract embedded metadata during import: %s", exc)
+
+            # Pre-populate gen_params with embedded data so Enricher treats it as the "base" layer
+            if embedded_gen_params:
+                # Merge embedded into existing gen_params (which currently only has request params if any)
+                # But wait, we want request params to override everything.
+                # So we should set recipe['gen_params'] = embedded, and pass request params to enricher.
+                metadata["gen_params"] = embedded_gen_params
+            
+            # 5. Enrich with unified logic
+            # This will fetch Civitai info (if URL matches) and merge: request > civitai > embedded
+            civitai_client = self._civitai_client_getter()
+            await RecipeEnricher.enrich_recipe(
+                recipe=metadata, 
+                civitai_client=civitai_client,
+                request_params=gen_params_request # Pass explicit request params here to override
+            )
+            
+            # If we got civitai_meta from download but Enricher didn't fetch it (e.g. not a civitai URL or failed),
+            # we might want to manually merge it? 
+            # But usually `import_remote_recipe` is used with Civitai URLs.
+            # For now, relying on Enricher's internal fetch is consistent with repair.
 
             result = await self._persistence_service.save_recipe(
                 recipe_scanner=recipe_scanner,
@@ -492,6 +703,7 @@ class RecipeManagementHandler:
                 name=name,
                 tags=tags,
                 metadata=metadata,
+                extension=extension,
             )
             return web.json_response(result.payload, status=result.status)
         except RecipeValidationError as exc:
@@ -541,6 +753,64 @@ class RecipeManagementHandler:
             self._logger.error("Error updating recipe: %s", exc, exc_info=True)
             return web.json_response({"error": str(exc)}, status=500)
 
+    async def move_recipe(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            data = await request.json()
+            recipe_id = data.get("recipe_id")
+            target_path = data.get("target_path")
+            if not recipe_id or not target_path:
+                return web.json_response(
+                    {"success": False, "error": "recipe_id and target_path are required"}, status=400
+                )
+
+            result = await self._persistence_service.move_recipe(
+                recipe_scanner=recipe_scanner,
+                recipe_id=str(recipe_id),
+                target_path=str(target_path),
+            )
+            return web.json_response(result.payload, status=result.status)
+        except RecipeValidationError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=400)
+        except RecipeNotFoundError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=404)
+        except Exception as exc:
+            self._logger.error("Error moving recipe: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def move_recipes_bulk(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            data = await request.json()
+            recipe_ids = data.get("recipe_ids") or []
+            target_path = data.get("target_path")
+            if not recipe_ids or not target_path:
+                return web.json_response(
+                    {"success": False, "error": "recipe_ids and target_path are required"}, status=400
+                )
+
+            result = await self._persistence_service.move_recipes_bulk(
+                recipe_scanner=recipe_scanner,
+                recipe_ids=recipe_ids,
+                target_path=str(target_path),
+            )
+            return web.json_response(result.payload, status=result.status)
+        except RecipeValidationError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=400)
+        except RecipeNotFoundError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=404)
+        except Exception as exc:
+            self._logger.error("Error moving recipes in bulk: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def reconnect_lora(self, request: web.Request) -> web.Response:
         try:
             await self._ensure_dependencies_ready()
@@ -622,6 +892,7 @@ class RecipeManagementHandler:
         name: Optional[str] = None
         tags: list[str] = []
         metadata: Optional[Dict[str, Any]] = None
+        extension: Optional[str] = None
 
         while True:
             field = await reader.next()
@@ -652,6 +923,8 @@ class RecipeManagementHandler:
                     metadata = json.loads(metadata_text)
                 except Exception:
                     metadata = {}
+            elif field.name == "extension":
+                extension = await field.text()
 
         return {
             "image_bytes": image_bytes,
@@ -659,6 +932,7 @@ class RecipeManagementHandler:
             "name": name,
             "tags": tags,
             "metadata": metadata,
+            "extension": extension,
         }
 
     def _parse_tags(self, tag_text: Optional[str]) -> list[str]:
@@ -729,7 +1003,7 @@ class RecipeManagementHandler:
             "exclude": False,
         }
 
-    async def _download_image_bytes(self, image_url: str) -> bytes:
+    async def _download_remote_media(self, image_url: str) -> tuple[bytes, str]:
         civitai_client = self._civitai_client_getter()
         downloader = await self._downloader_factory()
         temp_path = None
@@ -744,15 +1018,31 @@ class RecipeManagementHandler:
                 image_info = await civitai_client.get_image_info(civitai_match.group(1))
                 if not image_info:
                     raise RecipeDownloadError("Failed to fetch image information from Civitai")
-                download_url = image_info.get("url")
-                if not download_url:
+                
+                media_url = image_info.get("url")
+                if not media_url:
                     raise RecipeDownloadError("No image URL found in Civitai response")
                 
+                # Use optimized preview URLs if possible
+                media_type = image_info.get("type")
+                rewritten_url, _ = rewrite_preview_url(media_url, media_type=media_type)
+                if rewritten_url:
+                    download_url = rewritten_url
+                else:
+                    download_url = media_url
+
             success, result = await downloader.download_file(download_url, temp_path, use_auth=False)
             if not success:
                 raise RecipeDownloadError(f"Failed to download image: {result}")
+            
+            # Extract extension from URL
+            url_path = download_url.split('?')[0].split('#')[0]
+            extension = os.path.splitext(url_path)[1].lower()
+            if not extension:
+                extension = ".webp" # Default to webp if unknown
+
             with open(temp_path, "rb") as file_obj:
-                return file_obj.read()
+                return file_obj.read(), extension, image_info.get("meta") if civitai_match and image_info else None
         except RecipeDownloadError:
             raise
         except RecipeValidationError:
@@ -766,6 +1056,7 @@ class RecipeManagementHandler:
                 except FileNotFoundError:
                     pass
 
+
     def _safe_int(self, value: Any) -> int:
         try:
             return int(value)

py/routes/recipe_route_registrar.py

@@ -27,16 +27,25 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("DELETE", "/api/lm/recipe/{recipe_id}", "delete_recipe"),
     RouteDefinition("GET", "/api/lm/recipes/top-tags", "get_top_tags"),
     RouteDefinition("GET", "/api/lm/recipes/base-models", "get_base_models"),
+    RouteDefinition("GET", "/api/lm/recipes/roots", "get_roots"),
+    RouteDefinition("GET", "/api/lm/recipes/folders", "get_folders"),
+    RouteDefinition("GET", "/api/lm/recipes/folder-tree", "get_folder_tree"),
+    RouteDefinition("GET", "/api/lm/recipes/unified-folder-tree", "get_unified_folder_tree"),
     RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/share", "share_recipe"),
     RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/share/download", "download_shared_recipe"),
-    RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/syntax", "get_recipe_syntax"),
+    RouteDefinition("GET", "/api/lm/recipes/syntax", "get_recipe_syntax"),
     RouteDefinition("PUT", "/api/lm/recipe/{recipe_id}/update", "update_recipe"),
+    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"),
     RouteDefinition("GET", "/api/lm/recipes/find-duplicates", "find_duplicates"),
     RouteDefinition("POST", "/api/lm/recipes/bulk-delete", "bulk_delete"),
     RouteDefinition("POST", "/api/lm/recipes/save-from-widget", "save_recipe_from_widget"),
     RouteDefinition("GET", "/api/lm/recipes/for-lora", "get_recipes_for_lora"),
     RouteDefinition("GET", "/api/lm/recipes/scan", "scan_recipes"),
+    RouteDefinition("POST", "/api/lm/recipes/repair", "repair_recipes"),
+    RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
+    RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
 )
 
 

py/services/base_model_service.py

@@ -3,6 +3,7 @@ import asyncio
 from typing import Any, Dict, List, Optional, Type, TYPE_CHECKING
 import logging
 import os
+import time
 
 from ..utils.constants import VALID_LORA_TYPES
 from ..utils.models import BaseModelMetadata
@@ -80,6 +81,7 @@ class BaseModelService(ABC):
         **kwargs,
     ) -> Dict:
         """Get paginated and filtered model data"""
+        overall_start = time.perf_counter()
 
         sort_params = self.cache_repository.parse_sort(sort_by)
         if sort_params.key == 'usage':
@@ -87,6 +89,12 @@ class BaseModelService(ABC):
         else:
             sorted_data = await self.cache_repository.fetch_sorted(sort_params)
         
+        t0 = time.perf_counter()
+        sorted_data = await self.cache_repository.fetch_sorted(sort_params)
+        fetch_duration = time.perf_counter() - t0
+        initial_count = len(sorted_data)
+
+        t1 = time.perf_counter()
         if hash_filters:
             filtered_data = await self._apply_hash_filters(sorted_data, hash_filters)
         else:
@@ -116,17 +124,25 @@ class BaseModelService(ABC):
             
             if allow_selling_generated_content is not None:
                 filtered_data = await self._apply_allow_selling_filter(filtered_data, allow_selling_generated_content)
+        filter_duration = time.perf_counter() - t1
+        post_filter_count = len(filtered_data)
 
         annotated_for_filter: Optional[List[Dict]] = None
+        t2 = time.perf_counter()
         if update_available_only:
             annotated_for_filter = await self._annotate_update_flags(filtered_data)
             filtered_data = [
                 item for item in annotated_for_filter
                 if item.get('update_available')
             ]
+        update_filter_duration = time.perf_counter() - t2
+        final_count = len(filtered_data)
 
+        t3 = time.perf_counter()
         paginated = self._paginate(filtered_data, page, page_size)
+        pagination_duration = time.perf_counter() - t3
 
+        t4 = time.perf_counter()
         if update_available_only:
             # Items already include update flags thanks to the pre-filter annotation.
             paginated['items'] = list(paginated['items'])
@@ -134,6 +150,16 @@ class BaseModelService(ABC):
             paginated['items'] = await self._annotate_update_flags(
                 paginated['items'],
             )
+        annotate_duration = time.perf_counter() - t4
+        
+        overall_duration = time.perf_counter() - overall_start
+        logger.info(
+            "%s.get_paginated_data took %.3fs (fetch: %.3fs, filter: %.3fs, update_filter: %.3fs, pagination: %.3fs, annotate: %.3fs). "
+            "Counts: initial=%d, post_filter=%d, final=%d",
+            self.__class__.__name__, overall_duration, fetch_duration, filter_duration, 
+            update_filter_duration, pagination_duration, annotate_duration,
+            initial_count, post_filter_count, final_count
+        )
         return paginated
 
     async def _fetch_with_usage_sort(self, sort_params):

py/services/model_cache.py

@@ -1,4 +1,8 @@
 import asyncio
+import time
+import logging
+
+logger = logging.getLogger(__name__)
 from typing import Any, Dict, List, Optional, Tuple
 from dataclasses import dataclass, field
 from operator import itemgetter
@@ -215,24 +219,25 @@ class ModelCache:
 
     def _sort_data(self, data: List[Dict], sort_key: str, order: str) -> List[Dict]:
         """Sort data by sort_key and order"""
+        start_time = time.perf_counter()
         reverse = (order == 'desc')
         if sort_key == 'name':
             # Natural sort by configured display name, case-insensitive
-            return natsorted(
+            result = natsorted(
                 data,
                 key=lambda x: self._get_display_name(x).lower(),
                 reverse=reverse
             )
         elif sort_key == 'date':
             # Sort by modified timestamp
-            return sorted(
+            result = sorted(
                 data,
                 key=itemgetter('modified'),
                 reverse=reverse
             )
         elif sort_key == 'size':
             # Sort by file size
-            return sorted(
+            result = sorted(
                 data,
                 key=itemgetter('size'),
                 reverse=reverse
@@ -249,16 +254,28 @@ class ModelCache:
             )
         else:
             # Fallback: no sort
-            return list(data)
+            result = list(data)
+        
+        duration = time.perf_counter() - start_time
+        if duration > 0.05:
+            logger.info("ModelCache._sort_data(%s, %s) for %d items took %.3fs", sort_key, order, len(data), duration)
+        return result
 
     async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc') -> List[Dict]:
         """Get sorted data by sort_key and order, using cache if possible"""
         async with self._lock:
             if (sort_key, order) == self._last_sort:
                 return self._last_sorted_data
+            
+            start_time = time.perf_counter()
             sorted_data = self._sort_data(self.raw_data, sort_key, order)
             self._last_sort = (sort_key, order)
             self._last_sorted_data = sorted_data
+            
+            duration = time.perf_counter() - start_time
+            if duration > 0.1:
+                logger.debug("ModelCache.get_sorted_data(%s, %s) took %.3fs", sort_key, order, duration)
+            
             return sorted_data
 
     async def update_name_display_mode(self, display_mode: str) -> None:

py/services/model_query.py

@@ -5,6 +5,10 @@ from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence, Tuple
 
 from ..utils.constants import NSFW_LEVELS
 from ..utils.utils import fuzzy_match as default_fuzzy_match
+import time
+import logging
+
+logger = logging.getLogger(__name__)
 
 
 DEFAULT_CIVITAI_MODEL_TYPE = "LORA"
@@ -115,22 +119,33 @@ class ModelFilterSet:
 
     def apply(self, data: Iterable[Dict[str, Any]], criteria: FilterCriteria) -> List[Dict[str, Any]]:
         """Return items that satisfy the provided criteria."""
+        overall_start = time.perf_counter()
         items = list(data)
+        initial_count = len(items)
 
         if self._settings.get("show_only_sfw", False):
+            t0 = time.perf_counter()
             threshold = self._nsfw_levels.get("R", 0)
             items = [
                 item for item in items
                 if not item.get("preview_nsfw_level") or item.get("preview_nsfw_level") < threshold
             ]
+            sfw_duration = time.perf_counter() - t0
+        else:
+            sfw_duration = 0
 
+        favorites_duration = 0
         if criteria.favorites_only:
+            t0 = time.perf_counter()
             items = [item for item in items if item.get("favorite", False)]
+            favorites_duration = time.perf_counter() - t0
 
+        folder_duration = 0
         folder = criteria.folder
         options = criteria.search_options or {}
         recursive = bool(options.get("recursive", True))
         if folder is not None:
+            t0 = time.perf_counter()
             if recursive:
                 if folder:
                     folder_with_sep = f"{folder}/"
@@ -140,13 +155,20 @@ class ModelFilterSet:
                     ]
             else:
                 items = [item for item in items if item.get("folder") == folder]
+            folder_duration = time.perf_counter() - t0
 
+        base_models_duration = 0
         base_models = criteria.base_models or []
         if base_models:
+            t0 = time.perf_counter()
             base_model_set = set(base_models)
             items = [item for item in items if item.get("base_model") in base_model_set]
+            base_models_duration = time.perf_counter() - t0
 
+        tags_duration = 0
         tag_filters = criteria.tags or {}
+        if tag_filters:
+            t0 = time.perf_counter()
             include_tags = set()
             exclude_tags = set()
             if isinstance(tag_filters, dict):
@@ -161,18 +183,32 @@ class ModelFilterSet:
                 include_tags = {tag for tag in tag_filters if tag}
 
             if include_tags:
+                def matches_include(item_tags):
+                    if not item_tags and "__no_tags__" in include_tags:
+                        return True
+                    return any(tag in include_tags for tag in (item_tags or []))
+
                 items = [
                     item for item in items
-                if any(tag in include_tags for tag in (item.get("tags", []) or []))
+                    if matches_include(item.get("tags"))
                 ]
 
             if exclude_tags:
+                def matches_exclude(item_tags):
+                    if not item_tags and "__no_tags__" in exclude_tags:
+                        return True
+                    return any(tag in exclude_tags for tag in (item_tags or []))
+
                 items = [
                     item for item in items
-                if not any(tag in exclude_tags for tag in (item.get("tags", []) or []))
+                    if not matches_exclude(item.get("tags"))
                 ]
+            tags_duration = time.perf_counter() - t0
 
+        model_types_duration = 0
         model_types = criteria.model_types or []
+        if model_types:
+            t0 = time.perf_counter()
             normalized_model_types = {
                 model_type for model_type in (
                     normalize_civitai_model_type(value) for value in model_types
@@ -184,7 +220,17 @@ class ModelFilterSet:
                     item for item in items
                     if normalize_civitai_model_type(resolve_civitai_model_type(item)) in normalized_model_types
                 ]
+            model_types_duration = time.perf_counter() - t0
 
+        duration = time.perf_counter() - overall_start
+        if duration > 0.1: # Only log if it's potentially slow
+            logger.info(
+                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs). "
+                "Count: %d -> %d",
+                duration, sfw_duration, favorites_duration, folder_duration, 
+                base_models_duration, tags_duration, model_types_duration,
+                initial_count, len(items)
+            )
         return items
 
 

py/services/recipe_cache.py

@@ -7,12 +7,18 @@ from natsort import natsorted
 @dataclass
 class RecipeCache:
     """Cache structure for Recipe data"""
+
     raw_data: List[Dict]
     sorted_by_name: List[Dict]
     sorted_by_date: List[Dict]
+    folders: List[str] | None = None
+    folder_tree: Dict | None = None
 
     def __post_init__(self):
         self._lock = asyncio.Lock()
+        # Normalize optional metadata containers
+        self.folders = self.folders or []
+        self.folder_tree = self.folder_tree or {}
 
     async def resort(self, name_only: bool = False):
         """Resort all cached data views"""

py/services/recipe_scanner.py

@@ -1,7 +1,9 @@
-import os
-import logging
+from __future__ import annotations
+
 import asyncio
 import json
+import logging
+import os
 import time
 from typing import Any, Dict, Iterable, List, Optional, Set, Tuple
 from ..config import config
@@ -14,6 +16,9 @@ from .recipes.errors import RecipeNotFoundError
 from ..utils.utils import calculate_recipe_fingerprint, fuzzy_match
 from natsort import natsorted
 import sys
+import re
+from ..recipes.merger import GenParamsMerger
+from ..recipes.enrichment import RecipeEnricher
 
 logger = logging.getLogger(__name__)
 
@@ -52,6 +57,8 @@ class RecipeScanner:
             cls._instance._civitai_client = None  # Will be lazily initialized
         return cls._instance
     
+    REPAIR_VERSION = 3
+    
     def __init__(
         self,
         lora_scanner: Optional[LoraScanner] = None,
@@ -64,6 +71,7 @@ class RecipeScanner:
             self._initialization_task: Optional[asyncio.Task] = None
             self._is_initializing = False
             self._mutation_lock = asyncio.Lock()
+            self._post_scan_task: Optional[asyncio.Task] = None
             self._resort_tasks: Set[asyncio.Task] = set()
             if lora_scanner:
                 self._lora_scanner = lora_scanner
@@ -84,6 +92,10 @@ class RecipeScanner:
                 task.cancel()
         self._resort_tasks.clear()
 
+        if self._post_scan_task and not self._post_scan_task.done():
+            self._post_scan_task.cancel()
+        self._post_scan_task = None
+
         self._cache = None
         self._initialization_task = None
         self._is_initializing = False
@@ -102,19 +114,223 @@ class RecipeScanner:
             self._civitai_client = await ServiceRegistry.get_civitai_client()
         return self._civitai_client
     
+    async def repair_all_recipes(
+        self, 
+        progress_callback: Optional[Callable[[Dict], Any]] = None
+    ) -> Dict[str, Any]:
+        """Repair all recipes by enrichment with Civitai and embedded metadata.
+        
+        Args:
+            persistence_service: Service for saving updated recipes
+            progress_callback: Optional callback for progress updates
+            
+        Returns:
+            Dict summary of repair results
+        """
+        async with self._mutation_lock:
+            cache = await self.get_cached_data()
+            all_recipes = list(cache.raw_data)
+            total = len(all_recipes)
+            repaired_count = 0
+            skipped_count = 0
+            errors_count = 0
+            
+            civitai_client = await self._get_civitai_client()
+            
+            for i, recipe in enumerate(all_recipes):
+                try:
+                    # Report progress
+                    if progress_callback:
+                        await progress_callback({
+                            "status": "processing",
+                            "current": i + 1,
+                            "total": total,
+                            "recipe_name": recipe.get("name", "Unknown")
+                        })
+                    
+                    if await self._repair_single_recipe(recipe, civitai_client):
+                        repaired_count += 1
+                    else:
+                        skipped_count += 1
+                    
+                except Exception as e:
+                    logger.error(f"Error repairing recipe {recipe.get('file_path')}: {e}")
+                    errors_count += 1
+            
+            # Final progress update
+            if progress_callback:
+                await progress_callback({
+                    "status": "completed",
+                    "repaired": repaired_count,
+                    "skipped": skipped_count,
+                    "errors": errors_count,
+                    "total": total
+                })
+                
+            return {
+                "success": True,
+                "repaired": repaired_count,
+                "skipped": skipped_count,
+                "errors": errors_count,
+                "total": total
+            }
+
+    async def repair_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
+        """Repair a single recipe by its ID.
+        
+        Args:
+            recipe_id: ID of the recipe to repair
+            
+        Returns:
+            Dict summary of repair result
+        """
+        async with self._mutation_lock:
+            # Get raw recipe from cache directly to avoid formatted fields
+            cache = await self.get_cached_data()
+            recipe = next((r for r in cache.raw_data if str(r.get('id', '')) == recipe_id), None)
+            
+            if not recipe:
+                raise RecipeNotFoundError(f"Recipe {recipe_id} not found")
+            
+            civitai_client = await self._get_civitai_client()
+            success = await self._repair_single_recipe(recipe, civitai_client)
+            
+            # If successfully repaired, we should return the formatted version for the UI
+            return {
+                "success": True,
+                "repaired": 1 if success else 0,
+                "skipped": 0 if success else 1,
+                "recipe": await self.get_recipe_by_id(recipe_id) if success else recipe
+            }
+
+    async def _repair_single_recipe(self, recipe: Dict[str, Any], civitai_client: Any) -> bool:
+        """Internal helper to repair a single recipe object.
+        
+        Args:
+            recipe: The recipe dictionary to repair (modified in-place)
+            civitai_client: Authenticated Civitai client
+            
+        Returns:
+            bool: True if recipe was repaired or updated, False if skipped
+        """
+        # 1. Skip if already at latest repair version
+        if recipe.get("repair_version", 0) >= self.REPAIR_VERSION:
+            return False
+            
+        # 2. Identification: Is repair needed?
+        has_checkpoint = "checkpoint" in recipe and recipe["checkpoint"] and recipe["checkpoint"].get("name")
+        gen_params = recipe.get("gen_params", {})
+        has_prompt = bool(gen_params.get("prompt"))
+        
+        needs_repair = not has_checkpoint or not has_prompt
+        
+        if not needs_repair:
+            # Even if no repair needed, we mark it with version if it was processed
+            # Always update and save because if we are here, the version is old (checked in step 1)
+            recipe["repair_version"] = self.REPAIR_VERSION
+            await self._save_recipe_persistently(recipe)
+            return True
+        
+        # 3. Use Enricher to repair/enrich
+        try:
+            updated = await RecipeEnricher.enrich_recipe(recipe, civitai_client)
+        except Exception as e:
+            logger.error(f"Error enriching recipe {recipe.get('id')}: {e}")
+            updated = False
+
+        # 4. Mark version and save if updated or just marking version
+        # If we updated it, OR if the version is old (which we know it is if we are here), save it.
+        # Actually, if we are here and updated is False, it means we tried to repair but couldn't/didn't need to.
+        # But we still want to mark it as processed so we don't try again until version bump.
+        if updated or recipe.get("repair_version", 0) < self.REPAIR_VERSION:
+            recipe["repair_version"] = self.REPAIR_VERSION
+            await self._save_recipe_persistently(recipe)
+            return True
+            
+        return False
+
+    async def _save_recipe_persistently(self, recipe: Dict[str, Any]) -> bool:
+        """Helper to save a recipe to both JSON and EXIF metadata."""
+        recipe_id = recipe.get("id")
+        if not recipe_id:
+            return False
+
+        recipe_json_path = await self.get_recipe_json_path(recipe_id)
+        if not recipe_json_path:
+            return False
+
+        try:
+            # 1. Sanitize for storage (remove runtime convenience fields)
+            clean_recipe = self._sanitize_recipe_for_storage(recipe)
+
+            # 2. Update the original dictionary so that we persist the clean version
+            # globally if needed, effectively overwriting it in-place.
+            recipe.clear()
+            recipe.update(clean_recipe)
+
+            # 3. Save JSON
+            with open(recipe_json_path, 'w', encoding='utf-8') as f:
+                json.dump(recipe, f, indent=4, ensure_ascii=False)
+
+            # 4. Update EXIF if image exists
+            image_path = recipe.get('file_path')
+            if image_path and os.path.exists(image_path):
+                from ..utils.exif_utils import ExifUtils
+                ExifUtils.append_recipe_metadata(image_path, recipe)
+            
+            return True
+        except Exception as e:
+            logger.error(f"Error persisting recipe {recipe_id}: {e}")
+            return False
+
+
+    def _sanitize_recipe_for_storage(self, recipe: Dict[str, Any]) -> Dict[str, Any]:
+        """Create a clean copy of the recipe without runtime convenience fields."""
+        import copy
+        clean = copy.deepcopy(recipe)
+        
+        # 0. Clean top-level runtime fields
+        for key in ("file_url", "created_date_formatted", "modified_formatted"):
+            clean.pop(key, None)
+
+        # 1. Clean LORAs
+        if "loras" in clean and isinstance(clean["loras"], list):
+            for lora in clean["loras"]:
+                # Fields to remove (runtime only)
+                for key in ("inLibrary", "preview_url", "localPath"):
+                    lora.pop(key, None)
+                
+                # Normalize weight/strength if mapping is desired (standard in persistence_service)
+                if "weight" in lora and "strength" not in lora:
+                    lora["strength"] = float(lora.pop("weight"))
+                    
+        # 2. Clean Checkpoint
+        if "checkpoint" in clean and isinstance(clean["checkpoint"], dict):
+            cp = clean["checkpoint"]
+            # Fields to remove (runtime only)
+            for key in ("inLibrary", "localPath", "preview_url", "thumbnailUrl", "size", "downloadUrl"):
+                cp.pop(key, None)
+                
+        return clean
+    
     async def initialize_in_background(self) -> None:
         """Initialize cache in background using thread pool"""
         try:
+            await self._wait_for_lora_scanner()
+
             # Set initial empty cache to avoid None reference errors
             if self._cache is None:
                 self._cache = RecipeCache(
                     raw_data=[],
                     sorted_by_name=[],
-                    sorted_by_date=[]
+                    sorted_by_date=[],
+                    folders=[],
+                    folder_tree={},
                 )
             
             # Mark as initializing to prevent concurrent initializations
             self._is_initializing = True
+            self._initialization_task = asyncio.current_task()
             
             try:
                 # Start timer
@@ -126,11 +342,14 @@ class RecipeScanner:
                     None,  # Use default thread pool
                     self._initialize_recipe_cache_sync  # Run synchronous version in thread
                 )
+                if cache is not None:
+                    self._cache = cache
                 
                 # Calculate elapsed time and log it
                 elapsed_time = time.time() - start_time
                 recipe_count = len(cache.raw_data) if cache and hasattr(cache, 'raw_data') else 0
                 logger.info(f"Recipe cache initialized in {elapsed_time:.2f} seconds. Found {recipe_count} recipes")
+                self._schedule_post_scan_enrichment()
             finally:
                 # Mark initialization as complete regardless of outcome
                 self._is_initializing = False
@@ -207,6 +426,7 @@ class RecipeScanner:
                 
                 # Update cache with the collected data
                 self._cache.raw_data = recipes
+                self._update_folder_metadata(self._cache)
                 
                 # Create a simplified resort function that doesn't use await
                 if hasattr(self._cache, "resort"):
@@ -237,12 +457,97 @@ class RecipeScanner:
             # Clean up the event loop
             loop.close()
 
+    async def _wait_for_lora_scanner(self) -> None:
+        """Ensure the LoRA scanner has initialized before recipe enrichment."""
+
+        if not getattr(self, "_lora_scanner", None):
+            return
+
+        lora_scanner = self._lora_scanner
+        cache_ready = getattr(lora_scanner, "_cache", None) is not None
+
+        # If cache is already available, we can proceed
+        if cache_ready:
+            return
+
+        # Await an existing initialization task if present
+        task = getattr(lora_scanner, "_initialization_task", None)
+        if task and hasattr(task, "done") and not task.done():
+            try:
+                await task
+            except Exception:  # pragma: no cover - defensive guard
+                pass
+            if getattr(lora_scanner, "_cache", None) is not None:
+                return
+
+        # Otherwise, request initialization and proceed once it completes
+        try:
+            await lora_scanner.initialize_in_background()
+        except Exception as exc:  # pragma: no cover - defensive guard
+            logger.debug("Recipe Scanner: LoRA init request failed: %s", exc)
+
+    def _schedule_post_scan_enrichment(self) -> None:
+        """Kick off a non-blocking enrichment pass to fill remote metadata."""
+
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            return
+
+        if self._post_scan_task and not self._post_scan_task.done():
+            return
+
+        async def _run_enrichment():
+            try:
+                await self._enrich_cache_metadata()
+            except asyncio.CancelledError:
+                raise
+            except Exception as exc:  # pragma: no cover - defensive guard
+                logger.error("Recipe Scanner: error during post-scan enrichment: %s", exc, exc_info=True)
+
+        self._post_scan_task = loop.create_task(_run_enrichment(), name="recipe_cache_enrichment")
+
+    async def _enrich_cache_metadata(self) -> None:
+        """Perform remote metadata enrichment after the initial scan."""
+
+        cache = self._cache
+        if cache is None or not getattr(cache, "raw_data", None):
+            return
+
+        for index, recipe in enumerate(list(cache.raw_data)):
+            try:
+                metadata_updated = await self._update_lora_information(recipe)
+                if metadata_updated:
+                    recipe_id = recipe.get("id")
+                    if recipe_id:
+                        recipe_path = os.path.join(self.recipes_dir, f"{recipe_id}.recipe.json")
+                        if os.path.exists(recipe_path):
+                            try:
+                                self._write_recipe_file(recipe_path, recipe)
+                            except Exception as exc:  # pragma: no cover - best-effort persistence
+                                logger.debug("Recipe Scanner: could not persist recipe %s: %s", recipe_id, exc)
+            except asyncio.CancelledError:
+                raise
+            except Exception as exc:  # pragma: no cover - defensive logging
+                logger.error("Recipe Scanner: error enriching recipe %s: %s", recipe.get("id"), exc, exc_info=True)
+
+            if index % 10 == 0:
+                await asyncio.sleep(0)
+
+        try:
+            await cache.resort()
+        except Exception as exc:  # pragma: no cover - defensive logging
+            logger.debug("Recipe Scanner: error resorting cache after enrichment: %s", exc)
+
     def _schedule_resort(self, *, name_only: bool = False) -> None:
         """Schedule a background resort of the recipe cache."""
 
         if not self._cache:
             return
 
+        # Keep folder metadata up to date alongside sort order
+        self._update_folder_metadata()
+
         async def _resort_wrapper() -> None:
             try:
                 await self._cache.resort(name_only=name_only)
@@ -253,6 +558,75 @@ class RecipeScanner:
         self._resort_tasks.add(task)
         task.add_done_callback(lambda finished: self._resort_tasks.discard(finished))
 
+    def _calculate_folder(self, recipe_path: str) -> str:
+        """Calculate a normalized folder path relative to ``recipes_dir``."""
+
+        recipes_dir = self.recipes_dir
+        if not recipes_dir:
+            return ""
+
+        try:
+            recipe_dir = os.path.dirname(os.path.normpath(recipe_path))
+            relative_dir = os.path.relpath(recipe_dir, recipes_dir)
+            if relative_dir in (".", ""):
+                return ""
+            return relative_dir.replace(os.path.sep, "/")
+        except Exception:
+            return ""
+
+    def _build_folder_tree(self, folders: list[str]) -> dict:
+        """Build a nested folder tree structure from relative folder paths."""
+
+        tree: dict[str, dict] = {}
+        for folder in folders:
+            if not folder:
+                continue
+
+            parts = folder.split("/")
+            current_level = tree
+
+            for part in parts:
+                if part not in current_level:
+                    current_level[part] = {}
+                current_level = current_level[part]
+
+        return tree
+
+    def _update_folder_metadata(self, cache: RecipeCache | None = None) -> None:
+        """Ensure folder lists and tree metadata are synchronized with cache contents."""
+
+        cache = cache or self._cache
+        if cache is None:
+            return
+
+        folders: set[str] = set()
+        for item in cache.raw_data:
+            folder_value = item.get("folder", "")
+            if folder_value is None:
+                folder_value = ""
+            if folder_value == ".":
+                folder_value = ""
+            normalized = str(folder_value).replace("\\", "/")
+            item["folder"] = normalized
+            folders.add(normalized)
+
+        cache.folders = sorted(folders, key=lambda entry: entry.lower())
+        cache.folder_tree = self._build_folder_tree(cache.folders)
+
+    async def get_folders(self) -> list[str]:
+        """Return a sorted list of recipe folders relative to the recipes root."""
+
+        cache = await self.get_cached_data()
+        self._update_folder_metadata(cache)
+        return cache.folders
+
+    async def get_folder_tree(self) -> dict:
+        """Return a hierarchical tree of recipe folders for sidebar navigation."""
+
+        cache = await self.get_cached_data()
+        self._update_folder_metadata(cache)
+        return cache.folder_tree
+
     @property
     def recipes_dir(self) -> str:
         """Get path to recipes directory"""
@@ -269,11 +643,14 @@ class RecipeScanner:
         """Get cached recipe data, refresh if needed"""
         # If cache is already initialized and no refresh is needed, return it immediately
         if self._cache is not None and not force_refresh:
+            self._update_folder_metadata()
             return self._cache
 
         # If another initialization is already in progress, wait for it to complete
         if self._is_initializing and not force_refresh:
-            return self._cache or RecipeCache(raw_data=[], sorted_by_name=[], sorted_by_date=[])
+            return self._cache or RecipeCache(
+                raw_data=[], sorted_by_name=[], sorted_by_date=[], folders=[], folder_tree={}
+            )
 
         # If force refresh is requested, initialize the cache directly
         if force_refresh:
@@ -291,11 +668,14 @@ class RecipeScanner:
                         self._cache = RecipeCache(
                             raw_data=raw_data,
                             sorted_by_name=[],
-                            sorted_by_date=[]
+                            sorted_by_date=[],
+                            folders=[],
+                            folder_tree={},
                         )
 
                         # Resort cache
                         await self._cache.resort()
+                        self._update_folder_metadata(self._cache)
                         
                         return self._cache
                     
@@ -305,7 +685,9 @@ class RecipeScanner:
                         self._cache = RecipeCache(
                             raw_data=[],
                             sorted_by_name=[],
-                            sorted_by_date=[]
+                            sorted_by_date=[],
+                            folders=[],
+                            folder_tree={},
                         )
                         return self._cache
                     finally:
@@ -316,7 +698,9 @@ class RecipeScanner:
                 logger.error(f"Unexpected error in get_cached_data: {e}")
         
         # Return the cache (may be empty or partially initialized)
-        return self._cache or RecipeCache(raw_data=[], sorted_by_name=[], sorted_by_date=[])
+        return self._cache or RecipeCache(
+            raw_data=[], sorted_by_name=[], sorted_by_date=[], folders=[], folder_tree={}
+        )
 
     async def refresh_cache(self, force: bool = False) -> RecipeCache:
         """Public helper to refresh or return the recipe cache."""
@@ -331,6 +715,7 @@ class RecipeScanner:
 
         cache = await self.get_cached_data()
         await cache.add_recipe(recipe_data, resort=False)
+        self._update_folder_metadata(cache)
         self._schedule_resort()
 
     async def remove_recipe(self, recipe_id: str) -> bool:
@@ -344,6 +729,7 @@ class RecipeScanner:
         if removed is None:
             return False
 
+        self._update_folder_metadata(cache)
         self._schedule_resort()
         return True
 
@@ -429,6 +815,9 @@ class RecipeScanner:
             if path_updated:
                 self._write_recipe_file(recipe_path, recipe_data)
 
+            # Track folder placement relative to recipes directory
+            recipe_data['folder'] = recipe_data.get('folder') or self._calculate_folder(recipe_path)
+            
             # Ensure loras array exists
             if 'loras' not in recipe_data:
                 recipe_data['loras'] = []
@@ -438,7 +827,7 @@ class RecipeScanner:
                 recipe_data['gen_params'] = {}
             
             # Update lora information with local paths and availability
-            await self._update_lora_information(recipe_data)
+            lora_metadata_updated = await self._update_lora_information(recipe_data)
 
             if recipe_data.get('checkpoint'):
                 checkpoint_entry = self._normalize_checkpoint_entry(recipe_data['checkpoint'])
@@ -459,6 +848,12 @@ class RecipeScanner:
                     logger.info(f"Added fingerprint to recipe: {recipe_path}")
                 except Exception as e:
                     logger.error(f"Error writing updated recipe with fingerprint: {e}")
+            elif lora_metadata_updated:
+                # Persist updates such as marking invalid entries as deleted
+                try:
+                    self._write_recipe_file(recipe_path, recipe_data)
+                except Exception as e:
+                    logger.error(f"Error writing updated recipe metadata: {e}")
 
             return recipe_data
         except Exception as e:
@@ -519,7 +914,13 @@ class RecipeScanner:
                                 logger.warning(f"Marked lora with modelVersionId {model_version_id} as deleted")
                                 metadata_updated = True
                         else:
-                            logger.debug(f"Could not get hash for modelVersionId {model_version_id}")
+                            # No hash returned; mark as deleted to avoid repeated lookups
+                            lora['isDeleted'] = True
+                            metadata_updated = True
+                            logger.warning(
+                                "Marked lora with modelVersionId %s as deleted after failed hash lookup",
+                                model_version_id,
+                            )
             
             # If has hash but no file_name, look up in lora library
             if 'hash' in lora and (not lora.get('file_name') or not lora['file_name']):
@@ -809,7 +1210,7 @@ class RecipeScanner:
 
         return await self._lora_scanner.get_model_info_by_name(name)
 
-    async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'date', search: str = None, filters: dict = None, search_options: dict = None, lora_hash: str = None, bypass_filters: bool = True):
+    async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'date', search: str = None, filters: dict = None, search_options: dict = None, lora_hash: str = None, bypass_filters: bool = True, folder: str | None = None, recursive: bool = True):
         """Get paginated and filtered recipe data
 
         Args:
@@ -821,11 +1222,20 @@ class RecipeScanner:
             search_options: Dictionary of search options to apply
             lora_hash: Optional SHA256 hash of a LoRA to filter recipes by
             bypass_filters: If True, ignore other filters when a lora_hash is provided
+            folder: Optional folder filter relative to recipes directory
+            recursive: Whether to include recipes in subfolders of the selected folder
         """
         cache = await self.get_cached_data()
 
         # Get base dataset
-        filtered_data = cache.sorted_by_date if sort_by == 'date' else cache.sorted_by_name
+        sort_field = sort_by.split(':')[0] if ':' in sort_by else sort_by
+        
+        if sort_field == 'date':
+            filtered_data = list(cache.sorted_by_date)
+        elif sort_field == 'name':
+            filtered_data = list(cache.sorted_by_name)
+        else:
+            filtered_data = list(cache.raw_data)
         
         # Apply SFW filtering if enabled
         from .settings_manager import get_settings_manager
@@ -856,6 +1266,22 @@ class RecipeScanner:
         
         # Skip further filtering if we're only filtering by LoRA hash with bypass enabled
         if not (lora_hash and bypass_filters):
+            # Apply folder filter before other criteria
+            if folder is not None:
+                normalized_folder = folder.strip("/")
+                def matches_folder(item_folder: str) -> bool:
+                    item_path = (item_folder or "").strip("/")
+                    if recursive:
+                        if not normalized_folder:
+                            return True
+                        return item_path == normalized_folder or item_path.startswith(f"{normalized_folder}/")
+                    return item_path == normalized_folder
+
+                filtered_data = [
+                    item for item in filtered_data
+                    if matches_folder(item.get('folder', ''))
+                ]
+
             # Apply search filter
             if search:
                 # Default search options if none provided
@@ -892,6 +1318,14 @@ class RecipeScanner:
                             if fuzzy_match(str(lora.get('modelName', '')), search):
                                 return True
                     
+                    # Search in prompt and negative_prompt if enabled
+                    if search_options.get('prompt', True) and 'gen_params' in item:
+                        gen_params = item['gen_params']
+                        if fuzzy_match(str(gen_params.get('prompt', '')), search):
+                            return True
+                        if fuzzy_match(str(gen_params.get('negative_prompt', '')), search):
+                            return True
+                    
                     # No match found
                     return False
                 
@@ -907,6 +1341,13 @@ class RecipeScanner:
                         if item.get('base_model', '') in filters['base_model']
                     ]
                 
+                # Filter by favorite
+                if 'favorite' in filters and filters['favorite']:
+                    filtered_data = [
+                        item for item in filtered_data
+                        if item.get('favorite') is True
+                    ]
+
                 # Filter by tags
                 if 'tags' in filters and filters['tags']:
                     tag_spec = filters['tags']
@@ -925,17 +1366,41 @@ class RecipeScanner:
                         include_tags = {tag for tag in tag_spec if tag}
 
                     if include_tags:
+                        def matches_include(item_tags):
+                            if not item_tags and "__no_tags__" in include_tags:
+                                return True
+                            return any(tag in include_tags for tag in (item_tags or []))
+
                         filtered_data = [
                             item for item in filtered_data
-                            if any(tag in include_tags for tag in (item.get('tags', []) or []))
+                            if matches_include(item.get('tags'))
                         ]
 
                     if exclude_tags:
+                        def matches_exclude(item_tags):
+                            if not item_tags and "__no_tags__" in exclude_tags:
+                                return True
+                            return any(tag in exclude_tags for tag in (item_tags or []))
+
                         filtered_data = [
                             item for item in filtered_data
-                            if not any(tag in exclude_tags for tag in (item.get('tags', []) or []))
+                            if not matches_exclude(item.get('tags'))
                         ]
 
+
+        # Apply sorting if not already handled by pre-sorted cache
+        if ':' in sort_by or sort_field == 'loras_count':
+            field, order = (sort_by.split(':') + ['desc'])[:2]
+            reverse = order.lower() == 'desc'
+            
+            if field == 'name':
+                filtered_data = natsorted(filtered_data, key=lambda x: x.get('title', '').lower(), reverse=reverse)
+            elif field == 'date':
+                # Use modified if available, falling back to created_date
+                filtered_data.sort(key=lambda x: (x.get('modified', x.get('created_date', 0)), x.get('file_path', '')), reverse=reverse)
+            elif field == 'loras_count':
+                filtered_data.sort(key=lambda x: len(x.get('loras', [])), reverse=reverse)
+
         # Calculate pagination
         total_items = len(filtered_data)
         start_idx = (page - 1) * page_size
@@ -1031,6 +1496,30 @@ class RecipeScanner:
         from datetime import datetime
         return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
 
+    async def get_recipe_json_path(self, recipe_id: str) -> Optional[str]:
+        """Locate the recipe JSON file, accounting for folder placement."""
+
+        recipes_dir = self.recipes_dir
+        if not recipes_dir:
+            return None
+
+        cache = await self.get_cached_data()
+        folder = ""
+        for item in cache.raw_data:
+            if str(item.get("id")) == str(recipe_id):
+                folder = item.get("folder") or ""
+                break
+
+        candidate = os.path.normpath(os.path.join(recipes_dir, folder, f"{recipe_id}.recipe.json"))
+        if os.path.exists(candidate):
+            return candidate
+
+        for root, _, files in os.walk(recipes_dir):
+            if f"{recipe_id}.recipe.json" in files:
+                return os.path.join(root, f"{recipe_id}.recipe.json")
+
+        return None
+
     async def update_recipe_metadata(self, recipe_id: str, metadata: dict) -> bool:
         """Update recipe metadata (like title and tags) in both file system and cache
         
@@ -1041,13 +1530,9 @@ class RecipeScanner:
         Returns:
             bool: True if successful, False otherwise
         """
-        import os
-        import json
-        
         # First, find the recipe JSON file path
-        recipe_json_path = os.path.join(self.recipes_dir, f"{recipe_id}.recipe.json")
-        
-        if not os.path.exists(recipe_json_path):
+        recipe_json_path = await self.get_recipe_json_path(recipe_id)
+        if not recipe_json_path or not os.path.exists(recipe_json_path):
             return False
             
         try:
@@ -1096,8 +1581,8 @@ class RecipeScanner:
         if target_name is None:
             raise ValueError("target_name must be provided")
 
-        recipe_json_path = os.path.join(self.recipes_dir, f"{recipe_id}.recipe.json")
-        if not os.path.exists(recipe_json_path):
+        recipe_json_path = await self.get_recipe_json_path(recipe_id)
+        if not recipe_json_path or not os.path.exists(recipe_json_path):
             raise RecipeNotFoundError("Recipe not found")
 
         async with self._mutation_lock:
@@ -1228,71 +1713,56 @@ class RecipeScanner:
         # Always use lowercase hash for consistency
         hash_value = hash_value.lower()
         
-        # Get recipes directory
-        recipes_dir = self.recipes_dir
-        if not recipes_dir or not os.path.exists(recipes_dir):
-            logger.warning(f"Recipes directory not found: {recipes_dir}")
+        # Get cache
+        cache = await self.get_cached_data()
+        if not cache or not cache.raw_data:
             return 0, 0
         
-        # Check if cache is initialized
-        cache_initialized = self._cache is not None
-        cache_updated_count = 0
         file_updated_count = 0
+        cache_updated_count = 0
         
-        # Get all recipe JSON files in the recipes directory
-        recipe_files = []
-        for root, _, files in os.walk(recipes_dir):
-            for file in files:
-                if file.lower().endswith('.recipe.json'):
-                    recipe_files.append(os.path.join(root, file))
-        
-        # Process each recipe file
-        for recipe_path in recipe_files:
-            try:
-                # Load the recipe data
-                with open(recipe_path, 'r', encoding='utf-8') as f:
-                    recipe_data = json.load(f)
-                
-                # Skip if no loras or invalid structure
-                if not recipe_data or not isinstance(recipe_data, dict) or 'loras' not in recipe_data:
+        # Find recipes that need updating from the cache
+        recipes_to_update = []
+        for recipe in cache.raw_data:
+            loras = recipe.get('loras', [])
+            if not isinstance(loras, list):
                 continue
                 
-                # Check if any lora has matching hash
-                file_updated = False
-                for lora in recipe_data.get('loras', []):
-                    if 'hash' in lora and lora['hash'].lower() == hash_value:
-                        # Update file_name
-                        old_file_name = lora.get('file_name', '')
+            has_match = False
+            for lora in loras:
+                if not isinstance(lora, dict):
+                    continue
+                if (lora.get('hash') or '').lower() == hash_value:
+                    if lora.get('file_name') != new_file_name:
                         lora['file_name'] = new_file_name
-                        file_updated = True
-                        logger.info(f"Updated file_name in recipe {recipe_path}: {old_file_name} -> {new_file_name}")
+                        has_match = True
             
-                # If updated, save the file
-                if file_updated:
-                    with open(recipe_path, 'w', encoding='utf-8') as f:
-                        json.dump(recipe_data, f, indent=4, ensure_ascii=False)
-                    file_updated_count += 1
-                    
-                    # Also update in cache if it exists
-                    if cache_initialized:
-                        recipe_id = recipe_data.get('id')
-                        if recipe_id:
-                            for cache_item in self._cache.raw_data:
-                                if cache_item.get('id') == recipe_id:
-                                    # Replace loras array with updated version
-                                    cache_item['loras'] = recipe_data['loras']
+            if has_match:
+                recipes_to_update.append(recipe)
                 cache_updated_count += 1
-                                    break
         
+        if not recipes_to_update:
+            return 0, 0
+            
+        # Persist changes to disk
+        async with self._mutation_lock:
+            for recipe in recipes_to_update:
+                recipe_id = recipe.get('id')
+                if not recipe_id:
+                    continue
+                    
+                recipe_path = os.path.join(self.recipes_dir, f"{recipe_id}.recipe.json")
+                try:
+                    self._write_recipe_file(recipe_path, recipe)
+                    file_updated_count += 1
+                    logger.info(f"Updated file_name in recipe {recipe_path}: -> {new_file_name}")
                 except Exception as e:
                     logger.error(f"Error updating recipe file {recipe_path}: {e}")
-                import traceback
-                traceback.print_exc(file=sys.stderr)
         
-        # Resort cache if updates were made
-        if cache_initialized and cache_updated_count > 0:
-            await self._cache.resort()
-            logger.info(f"Resorted recipe cache after updating {cache_updated_count} items")
+        # We don't necessarily need to resort because LoRA file_name isn't a sort key,
+        # but we might want to schedule a resort if we're paranoid or if searching relies on sorted state.
+        # Given it's a rename of a dependency, search results might change if searching by LoRA name.
+        self._schedule_resort()
             
         return file_updated_count, cache_updated_count
 

py/services/recipes/analysis_service.py

@@ -13,6 +13,7 @@ import numpy as np
 from PIL import Image
 
 from ...utils.utils import calculate_recipe_fingerprint
+from ...utils.civitai_utils import rewrite_preview_url
 from .errors import (
     RecipeDownloadError,
     RecipeNotFoundError,
@@ -94,18 +95,39 @@ class RecipeAnalysisService:
         if civitai_client is None:
             raise RecipeServiceError("Civitai client unavailable")
 
-        temp_path = self._create_temp_path()
+        temp_path = None
         metadata: Optional[dict[str, Any]] = None
+        is_video = False
+        extension = ".jpg"  # Default
+
         try:
             civitai_match = re.match(r"https://civitai\.com/images/(\d+)", url)
             if civitai_match:
                 image_info = await civitai_client.get_image_info(civitai_match.group(1))
                 if not image_info:
                     raise RecipeDownloadError("Failed to fetch image information from Civitai")
+                
                 image_url = image_info.get("url")
                 if not image_url:
                     raise RecipeDownloadError("No image URL found in Civitai response")
+                
+                is_video = image_info.get("type") == "video"
+                
+                # Use optimized preview URLs if possible
+                rewritten_url, _ = rewrite_preview_url(image_url, media_type=image_info.get("type"))
+                if rewritten_url:
+                    image_url = rewritten_url
+
+                if is_video:
+                    # Extract extension from URL
+                    url_path = image_url.split('?')[0].split('#')[0]
+                    extension = os.path.splitext(url_path)[1].lower() or ".mp4"
+                else:
+                    extension = ".jpg"
+
+                temp_path = self._create_temp_path(suffix=extension)
                 await self._download_image(image_url, temp_path)
+                
                 metadata = image_info.get("meta") if "meta" in image_info else None
                 if (
                     isinstance(metadata, dict)
@@ -114,21 +136,30 @@ class RecipeAnalysisService:
                 ):
                     metadata = metadata["meta"]
             else:
+                # Basic extension detection for non-Civitai URLs
+                url_path = url.split('?')[0].split('#')[0]
+                extension = os.path.splitext(url_path)[1].lower()
+                if extension in [".mp4", ".webm"]:
+                    is_video = True
+                else:
+                    extension = ".jpg"
+                
+                temp_path = self._create_temp_path(suffix=extension)
                 await self._download_image(url, temp_path)
 
-            if metadata is None:
+            if metadata is None and not is_video:
                 metadata = self._exif_utils.extract_image_metadata(temp_path)
 
-            if not metadata:
-                return self._metadata_not_found_response(temp_path)
-
             return await self._parse_metadata(
-                metadata,
+                metadata or {},
                 recipe_scanner=recipe_scanner,
                 image_path=temp_path,
                 include_image_base64=True,
+                is_video=is_video,
+                extension=extension,
             )
         finally:
+            if temp_path:
                 self._safe_cleanup(temp_path)
 
     async def analyze_local_image(
@@ -198,12 +229,16 @@ class RecipeAnalysisService:
         recipe_scanner,
         image_path: Optional[str],
         include_image_base64: bool,
+        is_video: bool = False,
+        extension: str = ".jpg",
     ) -> AnalysisResult:
         parser = self._recipe_parser_factory.create_parser(metadata)
         if parser is None:
             payload = {"error": "No parser found for this image", "loras": []}
             if include_image_base64 and image_path:
                 payload["image_base64"] = self._encode_file(image_path)
+            payload["is_video"] = is_video
+            payload["extension"] = extension
             return AnalysisResult(payload)
 
         result = await parser.parse_metadata(metadata, recipe_scanner=recipe_scanner)
@@ -211,6 +246,9 @@ class RecipeAnalysisService:
         if include_image_base64 and image_path:
             result["image_base64"] = self._encode_file(image_path)
 
+        result["is_video"] = is_video
+        result["extension"] = extension
+
         if "error" in result and not result.get("loras"):
             return AnalysisResult(result)
 
@@ -241,8 +279,8 @@ class RecipeAnalysisService:
             temp_file.write(data)
             return temp_file.name
 
-    def _create_temp_path(self) -> str:
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
+    def _create_temp_path(self, suffix: str = ".jpg") -> str:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
             return temp_file.name
 
     def _safe_cleanup(self, path: Optional[str]) -> None:

py/services/recipes/persistence_service.py

@@ -5,6 +5,7 @@ import base64
 import json
 import os
 import re
+import shutil
 import time
 import uuid
 from dataclasses import dataclass
@@ -46,6 +47,7 @@ class RecipePersistenceService:
         name: str | None,
         tags: Iterable[str],
         metadata: Optional[dict[str, Any]],
+        extension: str | None = None,
     ) -> PersistenceResult:
         """Persist a user uploaded recipe."""
 
@@ -64,6 +66,13 @@ class RecipePersistenceService:
         os.makedirs(recipes_dir, exist_ok=True)
 
         recipe_id = str(uuid.uuid4())
+        
+        # Handle video formats by bypassing optimization and metadata embedding
+        is_video = extension in [".mp4", ".webm"]
+        if is_video:
+            optimized_image = resolved_image_bytes
+            # extension is already set
+        else:
             optimized_image, extension = self._exif_utils.optimize_image(
                 image_data=resolved_image_bytes,
                 target_width=self._card_preview_width,
@@ -71,6 +80,7 @@ class RecipePersistenceService:
                 quality=85,
                 preserve_metadata=True,
             )
+            
         image_filename = f"{recipe_id}{extension}"
         image_path = os.path.join(recipes_dir, image_filename)
         normalized_image_path = os.path.normpath(image_path)
@@ -126,6 +136,7 @@ class RecipePersistenceService:
         with open(json_path, "w", encoding="utf-8") as file_obj:
             json.dump(recipe_data, file_obj, indent=4, ensure_ascii=False)
 
+        if not is_video:
             self._exif_utils.append_recipe_metadata(normalized_image_path, recipe_data)
 
         matching_recipes = await self._find_matching_recipes(recipe_scanner, fingerprint, exclude_id=recipe_id)
@@ -144,12 +155,8 @@ class RecipePersistenceService:
     async def delete_recipe(self, *, recipe_scanner, recipe_id: str) -> PersistenceResult:
         """Delete an existing recipe."""
 
-        recipes_dir = recipe_scanner.recipes_dir
-        if not recipes_dir or not os.path.exists(recipes_dir):
-            raise RecipeNotFoundError("Recipes directory not found")
-
-        recipe_json_path = os.path.join(recipes_dir, f"{recipe_id}.recipe.json")
-        if not os.path.exists(recipe_json_path):
+        recipe_json_path = await recipe_scanner.get_recipe_json_path(recipe_id)
+        if not recipe_json_path or not os.path.exists(recipe_json_path):
             raise RecipeNotFoundError("Recipe not found")
 
         with open(recipe_json_path, "r", encoding="utf-8") as file_obj:
@@ -166,9 +173,9 @@ class RecipePersistenceService:
     async def update_recipe(self, *, recipe_scanner, recipe_id: str, updates: dict[str, Any]) -> PersistenceResult:
         """Update persisted metadata for a recipe."""
 
-        if not any(key in updates for key in ("title", "tags", "source_path", "preview_nsfw_level")):
+        if not any(key in updates for key in ("title", "tags", "source_path", "preview_nsfw_level", "favorite")):
             raise RecipeValidationError(
-                "At least one field to update must be provided (title or tags or source_path or preview_nsfw_level)"
+                "At least one field to update must be provided (title or tags or source_path or preview_nsfw_level or favorite)"
             )
 
         success = await recipe_scanner.update_recipe_metadata(recipe_id, updates)
@@ -177,6 +184,163 @@ class RecipePersistenceService:
 
         return PersistenceResult({"success": True, "recipe_id": recipe_id, "updates": updates})
 
+    def _normalize_target_path(self, recipe_scanner, target_path: str) -> tuple[str, str]:
+        """Normalize and validate the target path for recipe moves."""
+
+        if not target_path:
+            raise RecipeValidationError("Target path is required")
+
+        recipes_root = recipe_scanner.recipes_dir
+        if not recipes_root:
+            raise RecipeNotFoundError("Recipes directory not found")
+
+        normalized_target = os.path.normpath(target_path)
+        recipes_root = os.path.normpath(recipes_root)
+        if not os.path.isabs(normalized_target):
+            normalized_target = os.path.normpath(os.path.join(recipes_root, normalized_target))
+
+        try:
+            common_root = os.path.commonpath([normalized_target, recipes_root])
+        except ValueError as exc:
+            raise RecipeValidationError("Invalid target path") from exc
+
+        if common_root != recipes_root:
+            raise RecipeValidationError("Target path must be inside the recipes directory")
+
+        return normalized_target, recipes_root
+
+    async def _move_recipe_files(
+        self,
+        *,
+        recipe_scanner,
+        recipe_id: str,
+        normalized_target: str,
+        recipes_root: str,
+    ) -> dict[str, Any]:
+        """Move the recipe's JSON and preview image into the normalized target."""
+
+        recipe_json_path = await recipe_scanner.get_recipe_json_path(recipe_id)
+        if not recipe_json_path or not os.path.exists(recipe_json_path):
+            raise RecipeNotFoundError("Recipe not found")
+
+        recipe_data = await recipe_scanner.get_recipe_by_id(recipe_id)
+        if not recipe_data:
+            raise RecipeNotFoundError("Recipe not found")
+
+        current_json_dir = os.path.dirname(recipe_json_path)
+        normalized_image_path = os.path.normpath(recipe_data.get("file_path") or "") if recipe_data.get("file_path") else None
+
+        os.makedirs(normalized_target, exist_ok=True)
+
+        if os.path.normpath(current_json_dir) == normalized_target:
+            return {
+                "success": True,
+                "message": "Recipe is already in the target folder",
+                "recipe_id": recipe_id,
+                "original_file_path": recipe_data.get("file_path"),
+                "new_file_path": recipe_data.get("file_path"),
+            }
+
+        new_json_path = os.path.normpath(os.path.join(normalized_target, os.path.basename(recipe_json_path)))
+        shutil.move(recipe_json_path, new_json_path)
+
+        new_image_path = normalized_image_path
+        if normalized_image_path:
+            target_image_path = os.path.normpath(os.path.join(normalized_target, os.path.basename(normalized_image_path)))
+            if os.path.exists(normalized_image_path) and normalized_image_path != target_image_path:
+                shutil.move(normalized_image_path, target_image_path)
+            new_image_path = target_image_path
+
+        relative_folder = os.path.relpath(normalized_target, recipes_root)
+        if relative_folder in (".", ""):
+            relative_folder = ""
+        updates = {"file_path": new_image_path or recipe_data.get("file_path"), "folder": relative_folder.replace(os.path.sep, "/")}
+
+        updated = await recipe_scanner.update_recipe_metadata(recipe_id, updates)
+        if not updated:
+            raise RecipeNotFoundError("Recipe not found after move")
+
+        return {
+            "success": True,
+            "recipe_id": recipe_id,
+            "original_file_path": recipe_data.get("file_path"),
+            "new_file_path": updates["file_path"],
+            "json_path": new_json_path,
+            "folder": updates["folder"],
+        }
+
+    async def move_recipe(self, *, recipe_scanner, recipe_id: str, target_path: str) -> PersistenceResult:
+        """Move a recipe's assets into a new folder under the recipes root."""
+
+        normalized_target, recipes_root = self._normalize_target_path(recipe_scanner, target_path)
+        result = await self._move_recipe_files(
+            recipe_scanner=recipe_scanner,
+            recipe_id=recipe_id,
+            normalized_target=normalized_target,
+            recipes_root=recipes_root,
+        )
+        return PersistenceResult(result)
+
+    async def move_recipes_bulk(
+        self,
+        *,
+        recipe_scanner,
+        recipe_ids: Iterable[str],
+        target_path: str,
+    ) -> PersistenceResult:
+        """Move multiple recipes to a new folder."""
+
+        recipe_ids = list(recipe_ids)
+        if not recipe_ids:
+            raise RecipeValidationError("No recipe IDs provided")
+
+        normalized_target, recipes_root = self._normalize_target_path(recipe_scanner, target_path)
+
+        results: list[dict[str, Any]] = []
+        success_count = 0
+        failure_count = 0
+
+        for recipe_id in recipe_ids:
+            try:
+                move_result = await self._move_recipe_files(
+                    recipe_scanner=recipe_scanner,
+                    recipe_id=str(recipe_id),
+                    normalized_target=normalized_target,
+                    recipes_root=recipes_root,
+                )
+                results.append(
+                    {
+                        "recipe_id": recipe_id,
+                        "original_file_path": move_result.get("original_file_path"),
+                        "new_file_path": move_result.get("new_file_path"),
+                        "success": True,
+                        "message": move_result.get("message", ""),
+                        "folder": move_result.get("folder", ""),
+                    }
+                )
+                success_count += 1
+            except Exception as exc:  # pragma: no cover - per-item error handling
+                results.append(
+                    {
+                        "recipe_id": recipe_id,
+                        "original_file_path": None,
+                        "new_file_path": None,
+                        "success": False,
+                        "message": str(exc),
+                    }
+                )
+                failure_count += 1
+
+        return PersistenceResult(
+            {
+                "success": True,
+                "message": f"Moved {success_count} of {len(recipe_ids)} recipes",
+                "results": results,
+                "success_count": success_count,
+                "failure_count": failure_count,
+            }
+        )
+
     async def reconnect_lora(
         self,
         *,
@@ -187,8 +351,8 @@ class RecipePersistenceService:
     ) -> PersistenceResult:
         """Reconnect a LoRA entry within an existing recipe."""
 
-        recipe_path = os.path.join(recipe_scanner.recipes_dir, f"{recipe_id}.recipe.json")
-        if not os.path.exists(recipe_path):
+        recipe_path = await recipe_scanner.get_recipe_json_path(recipe_id)
+        if not recipe_path or not os.path.exists(recipe_path):
             raise RecipeNotFoundError("Recipe not found")
 
         target_lora = await recipe_scanner.get_local_lora(target_name)
@@ -233,16 +397,12 @@ class RecipePersistenceService:
         if not recipe_ids:
             raise RecipeValidationError("No recipe IDs provided")
 
-        recipes_dir = recipe_scanner.recipes_dir
-        if not recipes_dir or not os.path.exists(recipes_dir):
-            raise RecipeNotFoundError("Recipes directory not found")
-
         deleted_recipes: list[str] = []
         failed_recipes: list[dict[str, Any]] = []
 
         for recipe_id in recipe_ids:
-            recipe_json_path = os.path.join(recipes_dir, f"{recipe_id}.recipe.json")
-            if not os.path.exists(recipe_json_path):
+            recipe_json_path = await recipe_scanner.get_recipe_json_path(recipe_id)
+            if not recipe_json_path or not os.path.exists(recipe_json_path):
                 failed_recipes.append({"id": recipe_id, "reason": "Recipe not found"})
                 continue
 

py/services/websocket_manager.py

@@ -20,6 +20,8 @@ class WebSocketManager:
         self._last_init_progress: Dict[str, Dict] = {}
         # Add auto-organize progress tracking
         self._auto_organize_progress: Optional[Dict] = None
+        # Add recipe repair progress tracking
+        self._recipe_repair_progress: Optional[Dict] = None
         self._auto_organize_lock = asyncio.Lock()
         
     async def handle_connection(self, request: web.Request) -> web.WebSocketResponse:
@@ -189,6 +191,14 @@ class WebSocketManager:
         # Broadcast via WebSocket
         await self.broadcast(data)
     
+    async def broadcast_recipe_repair_progress(self, data: Dict):
+        """Broadcast recipe repair progress to connected clients"""
+        # Store progress data in memory
+        self._recipe_repair_progress = data
+        
+        # Broadcast via WebSocket
+        await self.broadcast(data)
+    
     def get_auto_organize_progress(self) -> Optional[Dict]:
         """Get current auto-organize progress"""
         return self._auto_organize_progress
@@ -197,6 +207,14 @@ class WebSocketManager:
         """Clear auto-organize progress data"""
         self._auto_organize_progress = None
     
+    def get_recipe_repair_progress(self) -> Optional[Dict]:
+        """Get current recipe repair progress"""
+        return self._recipe_repair_progress
+    
+    def cleanup_recipe_repair_progress(self):
+        """Clear recipe repair progress data"""
+        self._recipe_repair_progress = None
+    
     def is_auto_organize_running(self) -> bool:
         """Check if auto-organize is currently running"""
         if not self._auto_organize_progress:

refs/recipe.json

@@ -1,82 +1,33 @@
 {
-    "id": "0448c06d-de1b-46ab-975c-c5aa60d90dbc",
-    "file_path": "D:/Workspace/ComfyUI/models/loras/recipes/0448c06d-de1b-46ab-975c-c5aa60d90dbc.jpg",
-    "title": "a mysterious, steampunk-inspired character standing in a dramatic pose",
-    "modified": 1741837612.3931093,
-    "created_date": 1741492786.5581934,
-    "base_model": "Flux.1 D",
+    "id": "42803a29-02dc-49e1-b798-27da70e8b408",
+    "file_path": "/home/miao/workspace/ComfyUI/models/loras/recipes/test/42803a29-02dc-49e1-b798-27da70e8b408.webp",
+    "title": "masterpiece, best quality, amazing quality, very aesthetic, detailed eyes, perfect",
+    "modified": 1754897325.0507245,
+    "created_date": 1754897325.0507245,
+    "base_model": "Illustrious",
     "loras": [
         {
-            "file_name": "ChronoDivinitiesFlux_r1",
-            "hash": "ddbc5abd00db46ad464f5e3ca85f8f7121bc14b594d6785f441d9b002fffe66a",
-            "strength": 0.8,
-            "modelVersionId": 1438879,
-            "modelName": "Chrono Divinities - By HailoKnight",
-            "modelVersionName": "Flux"
-        },
-        {
-            "file_name": "flux.1_lora_flyway_ink-dynamic",
-            "hash": "4b4f3b469a0d5d3a04a46886abfa33daa37a905db070ccfbd10b345c6fb00eff",
-            "strength": 0.2,
-            "modelVersionId": 914935,
-            "modelName": "Ink-style",
-            "modelVersionName": "ink-dynamic"
-        },
-        {
-            "file_name": "ck-painterly-fantasy-000017",
-            "hash": "48c67064e2936aec342580a2a729d91d75eb818e45ecf993b9650cc66c94c420",
-            "strength": 0.2,
-            "modelVersionId": 1189379,
-            "modelName": "Painterly Fantasy by ChronoKnight - [FLUX & IL]",
-            "modelVersionName": "FLUX"
-        },
-        {
-            "file_name": "RetroAnimeFluxV1",
-            "hash": "8f43c31b6c3238ac44195c970d511d759c5893bddd00f59f42b8fe51e8e76fa0",
-            "strength": 0.8,
-            "modelVersionId": 806265,
-            "modelName": "Retro Anime Flux - Style",
-            "modelVersionName": "v1.0"
-        },
-        {
-            "file_name": "Mezzotint_Artstyle_for_Flux_-_by_Ethanar",
-            "hash": "e6961502769123bf23a66c5c5298d76264fd6b9610f018319a0ccb091bfc308e",
-            "strength": 0.2,
-            "modelVersionId": 757030,
-            "modelName": "Mezzotint Artstyle for Flux - by Ethanar",
-            "modelVersionName": "V1"
-        },
-        {
-            "file_name": "FluxMythG0thicL1nes",
-            "hash": "ecb03595de62bd6183a0dd2b38bea35669fd4d509f4bbae5aa0572cfb7ef4279",
-            "strength": 0.4,
-            "modelVersionId": 1202162,
-            "modelName": "Velvet's Mythic Fantasy Styles | Flux + Pony + illustrious",
-            "modelVersionName": "Flux Gothic Lines"
-        },
-        {
-            "file_name": "Elden_Ring_-_Yoshitaka_Amano",
-            "hash": "c660c4c55320be7206cb6a917c59d8da3953cc07169fe10bda833a54ec0024f9",
-            "strength": 0.75,
-            "modelVersionId": 746484,
-            "modelName": "Elden Ring - Yoshitaka Amano",
-            "modelVersionName": "V1"
+            "file_name": "",
+            "hash": "1b5b763d83961bb5745f3af8271ba83f1d4fd69c16278dae6d5b4e194bdde97a",
+            "strength": 1.0,
+            "modelVersionId": 2007092,
+            "modelName": "Pony: People's Works +",
+            "modelVersionName": "v8_Illusv1.0",
+            "isDeleted": false,
+            "exclude": false
         }
     ],
     "gen_params": {
-        "prompt": "a mysterious, steampunk-inspired character standing in a dramatic pose. The character is dressed in a long, intricately detailed dark coat with ornate patterns, a wide-brimmed hat, and leather boots. The face is partially obscured by the hat's shadow, adding to the enigmatic aura. The background showcases a large, antique clock with Roman numerals, surrounded by dynamic lightning and ethereal white birds, enhancing the fantastical atmosphere. The color palette is dominated by dark tones with striking contrasts of white and blue lightning, creating a sense of tension and energy. The overall composition is vertical, with the character centrally positioned, exuding a sense of power and mystery. hkchrono",
-        "negative_prompt": "",
-        "checkpoint": {
-            "type": "checkpoint",
-            "modelVersionId": 691639,
-            "modelName": "FLUX",
-            "modelVersionName": "Dev"
-        },
-        "steps": "30",
-        "sampler": "Undefined",
-        "cfg_scale": "3.5",
-        "seed": "1472903449",
+        "prompt": "masterpiece, best quality, amazing quality, very aesthetic, detailed eyes, perfect eyes, realistic eyes,\n(flat colors:1.5), (anime:1.5), (lineart:1.5),\nclose-up, solo, tongue, 1girl, food, (saliva:0.1), open mouth, candy, simple background, blue background, large lollipop, tongue out, fade background, lips, hand up, holding, looking at viewer, licking, seductive, half-closed eyes,",
+        "negative_prompt": "shiny skin,",
+        "steps": 19,
+        "sampler": "Euler a",
+        "cfg_scale": 5,
+        "seed": 1765271748,
         "size": "832x1216",
-        "clip_skip": "2"
-    }
+        "clip_skip": 2
+    },
+    "fingerprint": "1b5b763d83961bb5745f3af8271ba83f1d4fd69c16278dae6d5b4e194bdde97a:1.0",
+    "source_path": "https://civitai.com/images/92427432",
+    "folder": "test"
 }

scripts/sync_translation_keys.py

@@ -34,7 +34,7 @@ class TranslationKeySynchronizer:
         self.locales_dir = locales_dir
         self.verbose = verbose
         self.reference_locale = 'en'
-        self.target_locales = ['zh-CN', 'zh-TW', 'ja', 'ru', 'de', 'fr', 'es', 'ko']
+        self.target_locales = ['zh-CN', 'zh-TW', 'ja', 'ru', 'de', 'fr', 'es', 'ko', 'he']
         
     def log(self, message: str, level: str = 'INFO'):
         """Log a message if verbose mode is enabled."""

static/css/base.css

@@ -1,8 +1,10 @@
-html, body {
+html,
+body {
     margin: 0;
     padding: 0;
     height: 100%;
-    overflow: hidden; /* Disable default scrolling */
+    overflow: hidden;
+    /* Disable default scrolling */
 }
 
 /* 针对Firefox */
@@ -75,7 +77,8 @@ html, body {
     --border-radius-sm: 8px;
     --border-radius-xs: 4px;
 
-    --scrollbar-width: 8px; /* 添加滚动条宽度变量 */
+    --scrollbar-width: 8px;
+    /* 添加滚动条宽度变量 */
 
     /* Shortcut styles */
     --shortcut-bg: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.12);
@@ -104,7 +107,8 @@ html[data-theme="light"] {
     --lora-surface: oklch(25% 0.02 256 / 0.98);
     --lora-border: oklch(90% 0.02 256 / 0.15);
     --lora-text: oklch(98% 0.02 256);
-    --lora-warning: oklch(75% 0.25 80); /* Modified to be used with oklch() */
+    --lora-warning: oklch(75% 0.25 80);
+    /* Modified to be used with oklch() */
     --lora-error-bg: color-mix(in oklch, var(--lora-error) 15%, transparent);
     --lora-error-border: color-mix(in oklch, var(--lora-error) 40%, transparent);
     --badge-update-bg: oklch(62% 0.18 220);
@@ -118,5 +122,10 @@ body {
     color: var(--text-color);
     display: flex;
     flex-direction: column;
-    padding-top: 0; /* Remove the padding-top */
+    padding-top: 0;
+    /* Remove the padding-top */
+}
+
+.hidden {
+    display: none !important;
 }

static/css/components/import-modal.css

@@ -1,7 +1,8 @@
 /* Import Modal Styles */
 .import-step {
     margin: var(--space-2) 0;
-    transition: none !important; /* Disable any transitions that might affect display */
+    transition: none !important;
+    /* Disable any transitions that might affect display */
 }
 
 /* Import Mode Toggle */
@@ -107,7 +108,8 @@
     justify-content: center;
 }
 
-.recipe-image img {
+.recipe-image img,
+.recipe-preview-video {
     max-width: 100%;
     max-height: 100%;
     object-fit: contain;
@@ -512,14 +514,17 @@
 
 /* Prevent layout shift with scrollbar */
 .modal-content {
-    overflow-y: scroll; /* Always show scrollbar */
-    scrollbar-gutter: stable; /* Reserve space for scrollbar */
+    overflow-y: scroll;
+    /* Always show scrollbar */
+    scrollbar-gutter: stable;
+    /* Reserve space for scrollbar */
 }
 
 /* For browsers that don't support scrollbar-gutter */
 @supports not (scrollbar-gutter: stable) {
     .modal-content {
-        padding-right: calc(var(--space-2) + var(--scrollbar-width)); /* Add extra padding for scrollbar */
+        padding-right: calc(var(--space-2) + var(--scrollbar-width));
+        /* Add extra padding for scrollbar */
     }
 }
 
@@ -586,7 +591,8 @@
 
 /* Remove the old warning-message styles that were causing layout issues */
 .warning-message {
-    display: none; /* Hide the old style */
+    display: none;
+    /* Hide the old style */
 }
 
 /* Update deleted badge to be more prominent */
@@ -613,7 +619,8 @@
     color: var(--lora-error);
     font-size: 0.9em;
     margin-top: 8px;
-    min-height: 20px; /* Ensure there's always space for the error message */
+    min-height: 20px;
+    /* Ensure there's always space for the error message */
     font-weight: 500;
 }
 
@@ -662,8 +669,15 @@
 }
 
 @keyframes fadeIn {
-    from { opacity: 0; transform: translateY(-10px); }
-    to { opacity: 1; transform: translateY(0); }
+    from {
+        opacity: 0;
+        transform: translateY(-10px);
+    }
+
+    to {
+        opacity: 1;
+        transform: translateY(0);
+    }
 }
 
 .duplicate-warning {
@@ -779,6 +793,7 @@
     text-overflow: ellipsis;
     display: -webkit-box;
     -webkit-line-clamp: 2;
+    line-clamp: 2;
     -webkit-box-orient: vertical;
 }
 

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

@@ -20,7 +20,7 @@
 }
 
 .modal-header-row {
-    width: 85%;
+    width: 84%;
     display: flex;
     align-items: flex-start;
     gap: var(--space-2);

static/css/components/modal/_base.css

@@ -122,6 +122,7 @@ body.modal-open {
     cursor: pointer;
     opacity: 0.7;
     transition: opacity 0.2s;
+    z-index: 10;
 }
 
 .close:hover {

static/css/components/search-filter.css

@@ -242,6 +242,20 @@
     border-color: var(--lora-error-border);
 }
 
+/* Subtle styling for special system tags like "No tags" */
+.filter-tag.special-tag {
+    border-style: dashed;
+    opacity: 0.8;
+    font-style: italic;
+}
+
+/* Ensure solid border and full opacity when active or excluded */
+.filter-tag.special-tag.active,
+.filter-tag.special-tag.exclude {
+    border-style: solid;
+    opacity: 1;
+}
+
 /* Tag filter styles */
 .tag-filter {
     display: flex;

static/js/api/recipeApi.js

@@ -2,6 +2,35 @@ import { RecipeCard } from '../components/RecipeCard.js';
 import { state, getCurrentPageState } from '../state/index.js';
 import { showToast } from '../utils/uiHelpers.js';
 
+const RECIPE_ENDPOINTS = {
+    list: '/api/lm/recipes',
+    detail: '/api/lm/recipe',
+    scan: '/api/lm/recipes/scan',
+    update: '/api/lm/recipe',
+    roots: '/api/lm/recipes/roots',
+    folders: '/api/lm/recipes/folders',
+    folderTree: '/api/lm/recipes/folder-tree',
+    unifiedFolderTree: '/api/lm/recipes/unified-folder-tree',
+    move: '/api/lm/recipe/move',
+    moveBulk: '/api/lm/recipes/move-bulk',
+    bulkDelete: '/api/lm/recipes/bulk-delete',
+};
+
+const RECIPE_SIDEBAR_CONFIG = {
+    config: {
+        displayName: 'Recipe',
+        supportsMove: true,
+    },
+    endpoints: RECIPE_ENDPOINTS,
+};
+
+export function extractRecipeId(filePath) {
+    if (!filePath) return null;
+    const basename = filePath.split('/').pop().split('\\').pop();
+    const dotIndex = basename.lastIndexOf('.');
+    return dotIndex > 0 ? basename.substring(0, dotIndex) : basename;
+}
+
 /**
  * Fetch recipes with pagination for virtual scrolling
  * @param {number} page - Page number to fetch
@@ -18,10 +47,21 @@ export async function fetchRecipesPage(page = 1, pageSize = 100) {
             sort_by: pageState.sortBy
         });
 
+        if (pageState.showFavoritesOnly) {
+            params.append('favorite', 'true');
+        }
+
+        if (pageState.activeFolder !== null && pageState.activeFolder !== undefined) {
+            params.append('folder', pageState.activeFolder);
+            params.append('recursive', pageState.searchOptions?.recursive !== false);
+        } else if (pageState.searchOptions?.recursive !== undefined) {
+            params.append('recursive', pageState.searchOptions.recursive);
+        }
+
         // If we have a specific recipe ID to load
         if (pageState.customFilter?.active && pageState.customFilter?.recipeId) {
             // Special case: load specific recipe
-            const response = await fetch(`/api/lm/recipe/${pageState.customFilter.recipeId}`);
+            const response = await fetch(`${RECIPE_ENDPOINTS.detail}/${pageState.customFilter.recipeId}`);
 
             if (!response.ok) {
                 throw new Error(`Failed to load recipe: ${response.statusText}`);
@@ -56,6 +96,7 @@ export async function fetchRecipesPage(page = 1, pageSize = 100) {
                     params.append('search_tags', pageState.searchOptions.tags.toString());
                     params.append('search_lora_name', pageState.searchOptions.loraName.toString());
                     params.append('search_lora_model', pageState.searchOptions.loraModel.toString());
+                    params.append('search_prompt', (pageState.searchOptions.prompt || false).toString());
                     params.append('fuzzy', 'true');
                 }
             }
@@ -78,7 +119,7 @@ export async function fetchRecipesPage(page = 1, pageSize = 100) {
         }
 
         // Fetch recipes
-        const response = await fetch(`/api/lm/recipes?${params.toString()}`);
+        const response = await fetch(`${RECIPE_ENDPOINTS.list}?${params.toString()}`);
 
         if (!response.ok) {
             throw new Error(`Failed to load recipes: ${response.statusText}`);
@@ -213,7 +254,7 @@ export async function refreshRecipes() {
         state.loadingManager.showSimpleLoading('Refreshing recipes...');
 
         // Call the API endpoint to rebuild the recipe cache
-        const response = await fetch('/api/lm/recipes/scan');
+        const response = await fetch(RECIPE_ENDPOINTS.scan);
 
         if (!response.ok) {
             const data = await response.json();
@@ -277,10 +318,12 @@ export async function updateRecipeMetadata(filePath, updates) {
         state.loadingManager.showSimpleLoading('Saving metadata...');
 
         // Extract recipeId from filePath (basename without extension)
-        const basename = filePath.split('/').pop().split('\\').pop();
-        const recipeId = basename.substring(0, basename.lastIndexOf('.'));
+        const recipeId = extractRecipeId(filePath);
+        if (!recipeId) {
+            throw new Error('Unable to determine recipe ID');
+        }
 
-        const response = await fetch(`/api/lm/recipe/${recipeId}/update`, {
+        const response = await fetch(`${RECIPE_ENDPOINTS.update}/${recipeId}/update`, {
             method: 'PUT',
             headers: {
                 'Content-Type': 'application/json',
@@ -306,3 +349,187 @@ export async function updateRecipeMetadata(filePath, updates) {
         state.loadingManager.hide();
     }
 }
+
+export class RecipeSidebarApiClient {
+    constructor() {
+        this.apiConfig = RECIPE_SIDEBAR_CONFIG;
+    }
+
+    async fetchUnifiedFolderTree() {
+        const response = await fetch(this.apiConfig.endpoints.unifiedFolderTree);
+        if (!response.ok) {
+            throw new Error('Failed to fetch recipe folder tree');
+        }
+        return response.json();
+    }
+
+    async fetchModelRoots() {
+        const response = await fetch(this.apiConfig.endpoints.roots);
+        if (!response.ok) {
+            throw new Error('Failed to fetch recipe roots');
+        }
+        return response.json();
+    }
+
+    async fetchModelFolders() {
+        const response = await fetch(this.apiConfig.endpoints.folders);
+        if (!response.ok) {
+            throw new Error('Failed to fetch recipe folders');
+        }
+        return response.json();
+    }
+
+    async moveBulkModels(filePaths, targetPath) {
+        if (!this.apiConfig.config.supportsMove) {
+            showToast('toast.api.bulkMoveNotSupported', { type: this.apiConfig.config.displayName }, 'warning');
+            return [];
+        }
+
+        const recipeIds = filePaths
+            .map((path) => extractRecipeId(path))
+            .filter((id) => !!id);
+
+        if (recipeIds.length === 0) {
+            showToast('toast.models.noModelsSelected', {}, 'warning');
+            return [];
+        }
+
+        const response = await fetch(this.apiConfig.endpoints.moveBulk, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                recipe_ids: recipeIds,
+                target_path: targetPath,
+            }),
+        });
+
+        const result = await response.json();
+
+        if (!response.ok || !result.success) {
+            throw new Error(result.error || `Failed to move ${this.apiConfig.config.displayName}s`);
+        }
+
+        if (result.failure_count > 0) {
+            showToast(
+                'toast.api.bulkMovePartial',
+                {
+                    successCount: result.success_count,
+                    type: this.apiConfig.config.displayName,
+                    failureCount: result.failure_count,
+                },
+                'warning'
+            );
+
+            const failedFiles = (result.results || [])
+                .filter((item) => !item.success)
+                .map((item) => item.message || 'Unknown error');
+
+            if (failedFiles.length > 0) {
+                const failureMessage =
+                    failedFiles.length <= 3
+                        ? failedFiles.join('\n')
+                        : `${failedFiles.slice(0, 3).join('\n')}\n(and ${failedFiles.length - 3} more)`;
+                showToast('toast.api.bulkMoveFailures', { failures: failureMessage }, 'warning', 6000);
+            }
+        } else {
+            showToast(
+                'toast.api.bulkMoveSuccess',
+                {
+                    successCount: result.success_count,
+                    type: this.apiConfig.config.displayName,
+                },
+                'success'
+            );
+        }
+
+        return result.results || [];
+    }
+
+    async moveSingleModel(filePath, targetPath) {
+        if (!this.apiConfig.config.supportsMove) {
+            showToast('toast.api.moveNotSupported', { type: this.apiConfig.config.displayName }, 'warning');
+            return null;
+        }
+
+        const recipeId = extractRecipeId(filePath);
+        if (!recipeId) {
+            showToast('toast.api.moveFailed', { message: 'Recipe ID missing' }, 'error');
+            return null;
+        }
+
+        const response = await fetch(this.apiConfig.endpoints.move, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                recipe_id: recipeId,
+                target_path: targetPath,
+            }),
+        });
+
+        const result = await response.json();
+
+        if (!response.ok || !result.success) {
+            throw new Error(result.error || `Failed to move ${this.apiConfig.config.displayName}`);
+        }
+
+        if (result.message) {
+            showToast('toast.api.moveInfo', { message: result.message }, 'info');
+        } else {
+            showToast('toast.api.moveSuccess', { type: this.apiConfig.config.displayName }, 'success');
+        }
+
+        return {
+            original_file_path: result.original_file_path || filePath,
+            new_file_path: result.new_file_path || filePath,
+            folder: result.folder || '',
+            message: result.message,
+        };
+    }
+
+    async bulkDeleteModels(filePaths) {
+        if (!filePaths || filePaths.length === 0) {
+            throw new Error('No file paths provided');
+        }
+
+        const recipeIds = filePaths
+            .map((path) => extractRecipeId(path))
+            .filter((id) => !!id);
+
+        if (recipeIds.length === 0) {
+            throw new Error('No recipe IDs could be derived from file paths');
+        }
+
+        try {
+            state.loadingManager?.showSimpleLoading('Deleting recipes...');
+
+            const response = await fetch(this.apiConfig.endpoints.bulkDelete, {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify({
+                    recipe_ids: recipeIds,
+                }),
+            });
+
+            const result = await response.json();
+
+            if (!response.ok || !result.success) {
+                throw new Error(result.error || 'Failed to delete recipes');
+            }
+
+            return {
+                success: true,
+                deleted_count: result.total_deleted,
+                failed_count: result.total_failed || 0,
+                errors: result.failed || [],
+            };
+        } finally {
+            state.loadingManager?.hide();
+        }
+    }
+}

static/js/components/ContextMenu/GlobalContextMenu.js

@@ -15,6 +15,29 @@ export class GlobalContextMenu extends BaseContextMenu {
 
     showMenu(x, y, origin = null) {
         const contextOrigin = origin || { type: 'global' };
+
+        // Conditional visibility for recipes page
+        const isRecipesPage = state.currentPageType === 'recipes';
+        const modelUpdateItem = this.menu.querySelector('[data-action="check-model-updates"]');
+        const licenseRefreshItem = this.menu.querySelector('[data-action="fetch-missing-licenses"]');
+        const downloadExamplesItem = this.menu.querySelector('[data-action="download-example-images"]');
+        const cleanupExamplesItem = this.menu.querySelector('[data-action="cleanup-example-images-folders"]');
+        const repairRecipesItem = this.menu.querySelector('[data-action="repair-recipes"]');
+
+        if (isRecipesPage) {
+            modelUpdateItem?.classList.add('hidden');
+            licenseRefreshItem?.classList.add('hidden');
+            downloadExamplesItem?.classList.add('hidden');
+            cleanupExamplesItem?.classList.add('hidden');
+            repairRecipesItem?.classList.remove('hidden');
+        } else {
+            modelUpdateItem?.classList.remove('hidden');
+            licenseRefreshItem?.classList.remove('hidden');
+            downloadExamplesItem?.classList.remove('hidden');
+            cleanupExamplesItem?.classList.remove('hidden');
+            repairRecipesItem?.classList.add('hidden');
+        }
+
         super.showMenu(x, y, contextOrigin);
     }
 
@@ -40,6 +63,11 @@ export class GlobalContextMenu extends BaseContextMenu {
                     console.error('Failed to refresh missing license metadata:', error);
                 });
                 break;
+            case 'repair-recipes':
+                this.repairRecipes(menuItem).catch((error) => {
+                    console.error('Failed to repair recipes:', error);
+                });
+                break;
             default:
                 console.warn(`Unhandled global context menu action: ${action}`);
                 break;
@@ -235,4 +263,78 @@ export class GlobalContextMenu extends BaseContextMenu {
 
         return `${displayName}s`;
     }
+
+    async repairRecipes(menuItem) {
+        if (this._repairInProgress) {
+            return;
+        }
+
+        this._repairInProgress = true;
+        menuItem?.classList.add('disabled');
+
+        const loadingMessage = translate(
+            'globalContextMenu.repairRecipes.loading',
+            {},
+            'Repairing recipe data...'
+        );
+
+        const progressUI = state.loadingManager?.showEnhancedProgress(loadingMessage);
+
+        try {
+            const response = await fetch('/api/lm/recipes/repair', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+            });
+
+            const result = await response.json();
+            if (!response.ok || !result.success) {
+                throw new Error(result.error || 'Failed to start repair');
+            }
+
+            // Poll for progress (or wait for WebSocket if preferred, but polling is simpler for this implementation)
+            let isComplete = false;
+            while (!isComplete && this._repairInProgress) {
+                const progressResponse = await fetch('/api/lm/recipes/repair-progress');
+                if (progressResponse.ok) {
+                    const progressResult = await progressResponse.json();
+                    if (progressResult.success && progressResult.progress) {
+                        const p = progressResult.progress;
+                        if (p.status === 'processing') {
+                            const percent = (p.current / p.total) * 100;
+                            progressUI?.updateProgress(percent, p.recipe_name, `${loadingMessage} (${p.current}/${p.total})`);
+                        } else if (p.status === 'completed') {
+                            isComplete = true;
+                            progressUI?.complete(translate(
+                                'globalContextMenu.repairRecipes.success',
+                                { count: p.repaired },
+                                `Repaired ${p.repaired} recipes.`
+                            ));
+                            showToast('globalContextMenu.repairRecipes.success', { count: p.repaired }, 'success');
+                            // Refresh recipes page if active
+                            if (window.recipesPage) {
+                                window.recipesPage.refresh();
+                            }
+                        } else if (p.status === 'error') {
+                            throw new Error(p.error || 'Repair failed');
+                        }
+                    } else if (progressResponse.status === 404) {
+                        // Progress might have finished quickly and been cleaned up
+                        isComplete = true;
+                        progressUI?.complete();
+                    }
+                }
+
+                if (!isComplete) {
+                    await new Promise(resolve => setTimeout(resolve, 1000));
+                }
+            }
+        } catch (error) {
+            console.error('Recipe repair failed:', error);
+            progressUI?.complete(translate('globalContextMenu.repairRecipes.error', { message: error.message }, 'Repair failed: {message}'));
+            showToast('globalContextMenu.repairRecipes.error', { message: error.message }, 'error');
+        } finally {
+            this._repairInProgress = false;
+            menuItem?.classList.remove('disabled');
+        }
+    }
 }

static/js/components/ContextMenu/RecipeContextMenu.js

@@ -4,6 +4,7 @@ import { showToast, copyToClipboard, sendLoraToWorkflow } from '../../utils/uiHe
 import { setSessionItem, removeSessionItem } from '../../utils/storageHelpers.js';
 import { updateRecipeMetadata } from '../../api/recipeApi.js';
 import { state } from '../../state/index.js';
+import { moveManager } from '../../managers/MoveManager.js';
 
 export class RecipeContextMenu extends BaseContextMenu {
     constructor() {
@@ -77,6 +78,9 @@ export class RecipeContextMenu extends BaseContextMenu {
                 // Share recipe
                 this.currentCard.querySelector('.fa-share-alt')?.click();
                 break;
+            case 'move':
+                moveManager.showMoveModal(this.currentCard.dataset.filepath);
+                break;
             case 'delete':
                 // Delete recipe
                 this.currentCard.querySelector('.fa-trash')?.click();
@@ -89,6 +93,10 @@ export class RecipeContextMenu extends BaseContextMenu {
                 // Download missing LoRAs
                 this.downloadMissingLoRAs(recipeId);
                 break;
+            case 'repair':
+                // Repair recipe metadata
+                this.repairRecipe(recipeId);
+                break;
         }
     }
 
@@ -279,6 +287,38 @@ export class RecipeContextMenu extends BaseContextMenu {
             }
         }
     }
+
+    // Repair recipe metadata
+    async repairRecipe(recipeId) {
+        if (!recipeId) {
+            showToast('recipes.contextMenu.repair.missingId', {}, 'error');
+            return;
+        }
+
+        try {
+            showToast('recipes.contextMenu.repair.starting', {}, 'info');
+
+            const response = await fetch(`/api/lm/recipe/${recipeId}/repair`, {
+                method: 'POST'
+            });
+            const result = await response.json();
+
+            if (result.success) {
+                if (result.repaired > 0) {
+                    showToast('recipes.contextMenu.repair.success', {}, 'success');
+                    // Refresh the current card or reload
+                    this.resetAndReload();
+                } else {
+                    showToast('recipes.contextMenu.repair.skipped', {}, 'info');
+                }
+            } else {
+                throw new Error(result.error || 'Repair failed');
+            }
+        } catch (error) {
+            console.error('Error repairing recipe:', error);
+            showToast('recipes.contextMenu.repair.failed', { message: error.message }, 'error');
+        }
+    }
 }
 
 // Mix in shared methods from ModelContextMenuMixin

static/js/components/RecipeCard.js

@@ -1,8 +1,11 @@
 // Recipe Card Component
 import { showToast, copyToClipboard, sendLoraToWorkflow } from '../utils/uiHelpers.js';
+import { updateRecipeMetadata } from '../api/recipeApi.js';
+import { configureModelCardVideo } from './shared/ModelCard.js';
 import { modalManager } from '../managers/ModalManager.js';
 import { getCurrentPageState } from '../state/index.js';
 import { state } from '../state/index.js';
+import { bulkManager } from '../managers/BulkManager.js';
 import { NSFW_LEVELS, getBaseModelAbbreviation } from '../utils/constants.js';
 
 class RecipeCard {
@@ -38,13 +41,28 @@ class RecipeCard {
         const allLorasAvailable = missingLorasCount === 0 && lorasCount > 0;
 
         // Ensure file_url exists, fallback to file_path if needed
-        const imageUrl = this.recipe.file_url || 
+        const previewUrl = this.recipe.file_url ||
             (this.recipe.file_path ? `/loras_static/root1/preview/${this.recipe.file_path.split('/').pop()}` :
                 '/loras_static/images/no-preview.png');
 
-        // Check if in duplicates mode
-        const pageState = getCurrentPageState();
-        const isDuplicatesMode = pageState.duplicatesMode;
+        const isDuplicatesMode = getCurrentPageState().duplicatesMode;
+        const autoplayOnHover = state?.global?.settings?.autoplay_on_hover === true;
+        const isFavorite = this.recipe.favorite === true;
+
+        // Video preview logic
+        const isVideo = previewUrl.endsWith('.mp4') || previewUrl.endsWith('.webm');
+        const videoAttrs = [
+            'controls',
+            'muted',
+            'loop',
+            'playsinline',
+            'preload="none"',
+            `data-src="${previewUrl}"`
+        ];
+
+        if (!autoplayOnHover) {
+            videoAttrs.push('data-autoplay="true"');
+        }
 
         // NSFW blur logic - similar to LoraCard
         const nsfwLevel = this.recipe.preview_nsfw_level !== undefined ? this.recipe.preview_nsfw_level : 0;
@@ -66,7 +84,10 @@ class RecipeCard {
 
         card.innerHTML = `
             <div class="card-preview ${shouldBlur ? 'blurred' : ''}">
-                <img src="${imageUrl}" alt="${this.recipe.title}">
+                ${isVideo ?
+                `<video ${videoAttrs.join(' ')} style="pointer-events: none;"></video>` :
+                `<img src="${previewUrl}" alt="${this.recipe.title}">`
+            }
                 ${!isDuplicatesMode ? `
                 <div class="card-header">
                     ${shouldBlur ?
@@ -75,6 +96,7 @@ class RecipeCard {
                       </button>` : ''}
                     <span class="base-model-label ${shouldBlur ? 'with-toggle' : ''}" title="${baseModelLabel}">${baseModelDisplay}</span>
                     <div class="card-actions">
+                        <i class="${isFavorite ? 'fas fa-star favorite-active' : 'far fa-star'}" title="${isFavorite ? 'Remove from Favorites' : 'Add to Favorites'}"></i>
                         <i class="fas fa-share-alt" title="Share Recipe"></i>
                         <i class="fas fa-paper-plane" title="Send Recipe to Workflow (Click: Append, Shift+Click: Replace)"></i>
                         <i class="fas fa-trash" title="Delete Recipe"></i>
@@ -104,6 +126,13 @@ class RecipeCard {
         `;
 
         this.attachEventListeners(card, isDuplicatesMode, shouldBlur);
+
+        // Add video auto-play on hover functionality if needed
+        const videoElement = card.querySelector('video');
+        if (videoElement) {
+            configureModelCardVideo(videoElement, autoplayOnHover);
+        }
+
         return card;
     }
 
@@ -113,6 +142,67 @@ class RecipeCard {
         return `${missingCount} of ${totalCount} LoRAs missing`;
     }
 
+    async toggleFavorite(card) {
+        // Find the latest star icon in case the card was re-rendered
+        const getStarIcon = (c) => c.querySelector('.fa-star');
+        let starIcon = getStarIcon(card);
+
+        const isFavorite = this.recipe.favorite || false;
+        const newFavoriteState = !isFavorite;
+
+        // Update early to provide instant feedback and avoid race conditions with re-renders
+        this.recipe.favorite = newFavoriteState;
+
+        // Function to update icon state
+        const updateIconUI = (icon, state) => {
+            if (!icon) return;
+            if (state) {
+                icon.classList.remove('far');
+                icon.classList.add('fas', 'favorite-active');
+                icon.title = 'Remove from Favorites';
+            } else {
+                icon.classList.remove('fas', 'favorite-active');
+                icon.classList.add('far');
+                icon.title = 'Add to Favorites';
+            }
+        };
+
+        // Update current icon immediately
+        updateIconUI(starIcon, newFavoriteState);
+
+        try {
+            await updateRecipeMetadata(this.recipe.file_path, {
+                favorite: newFavoriteState
+            });
+
+            // Status already updated, just show toast
+            if (newFavoriteState) {
+                showToast('modelCard.favorites.added', {}, 'success');
+            } else {
+                showToast('modelCard.favorites.removed', {}, 'success');
+            }
+
+            // Re-find star icon after API call as VirtualScroller might have replaced the element
+            // During updateRecipeMetadata, VirtualScroller.updateSingleItem might have re-rendered the card
+            // We need to find the NEW element in the DOM to ensure we don't have a stale reference
+            // Though typically VirtualScroller handles the re-render with the NEW this.recipe.favorite
+            // we will check the DOM just to be sure if this instance's internal card is still what's in DOM
+        } catch (error) {
+            console.error('Failed to update favorite status:', error);
+            // Revert local state on error
+            this.recipe.favorite = isFavorite;
+
+            // Re-find star icon in case of re-render during fault
+            const currentCard = card.ownerDocument.evaluate(
+                `.//*[@data-filepath="${this.recipe.file_path}"]`,
+                card.ownerDocument, null, XPathResult.FIRST_ORDERED_NODE_TYPE, null
+            ).singleNodeValue || card;
+
+            updateIconUI(getStarIcon(currentCard), isFavorite);
+            showToast('modelCard.favorites.updateFailed', {}, 'error');
+        }
+    }
+
     attachEventListeners(card, isDuplicatesMode, shouldBlur) {
         // Add blur toggle functionality if content should be blurred
         if (shouldBlur) {
@@ -137,9 +227,19 @@ class RecipeCard {
         // Recipe card click event - only attach if not in duplicates mode
         if (!isDuplicatesMode) {
             card.addEventListener('click', () => {
+                if (state.bulkMode) {
+                    bulkManager.toggleCardSelection(card);
+                    return;
+                }
                 this.clickHandler(this.recipe);
             });
 
+            // Favorite button click event - prevent propagation to card
+            card.querySelector('.fa-star')?.addEventListener('click', (e) => {
+                e.stopPropagation();
+                this.toggleFavorite(card);
+            });
+
             // Share button click event - prevent propagation to card
             card.querySelector('.fa-share-alt')?.addEventListener('click', (e) => {
                 e.stopPropagation();
@@ -235,13 +335,19 @@ class RecipeCard {
             }
 
             // Create delete modal content
+            const previewUrl = this.recipe.file_url || '/loras_static/images/no-preview.png';
+            const isVideo = previewUrl.endsWith('.mp4') || previewUrl.endsWith('.webm');
+
             const deleteModalContent = `
                 <div class="modal-content delete-modal-content">
                     <h2>Delete Recipe</h2>
                     <p class="delete-message">Are you sure you want to delete this recipe?</p>
                     <div class="delete-model-info">
                         <div class="delete-preview">
-                            <img src="${this.recipe.file_url || '/loras_static/images/no-preview.png'}" alt="${this.recipe.title}">
+                            ${isVideo ?
+                    `<video src="${previewUrl}" controls muted loop playsinline style="max-width: 100%;"></video>` :
+                    `<img src="${previewUrl}" alt="${this.recipe.title}">`
+                }
                         </div>
                         <div class="delete-info">
                             <h3>${this.recipe.title}</h3>

static/js/components/SidebarManager.js

@@ -77,7 +77,9 @@ export class SidebarManager {
         this.pageControls = pageControls;
         this.pageType = pageControls.pageType;
         this.lastPageControls = pageControls;
-        this.apiClient = getModelApiClient();
+        this.apiClient = pageControls?.getSidebarApiClient?.()
+            || pageControls?.sidebarApiClient
+            || getModelApiClient();
 
         // Set initial sidebar state immediately (hidden by default)
         this.setInitialSidebarState();
@@ -205,6 +207,10 @@ export class SidebarManager {
     }
 
     initializeDragAndDrop() {
+        if (this.apiClient?.apiConfig?.config?.supportsMove === false) {
+            return;
+        }
+
         if (!this.dragHandlersInitialized) {
             document.addEventListener('dragstart', this.handleCardDragStart);
             document.addEventListener('dragend', this.handleCardDragEnd);
@@ -416,7 +422,14 @@ export class SidebarManager {
         }
 
         if (!this.apiClient) {
-            this.apiClient = getModelApiClient();
+            this.apiClient = this.pageControls?.getSidebarApiClient?.()
+                || this.pageControls?.sidebarApiClient
+                || getModelApiClient();
+        }
+
+        if (this.apiClient?.apiConfig?.config?.supportsMove === false) {
+            showToast('toast.models.moveFailed', { message: translate('sidebar.dragDrop.moveUnsupported', {}, 'Move not supported for this page') }, 'error');
+            return false;
         }
 
         const rootPath = this.draggedRootPath ? this.draggedRootPath.replace(/\\/g, '/') : '';
@@ -470,7 +483,9 @@ export class SidebarManager {
     }
 
     async init() {
-        this.apiClient = getModelApiClient();
+        this.apiClient = this.pageControls?.getSidebarApiClient?.()
+            || this.pageControls?.sidebarApiClient
+            || getModelApiClient();
 
         // Set initial sidebar state immediately (hidden by default)
         this.setInitialSidebarState();
@@ -1010,8 +1025,11 @@ export class SidebarManager {
     }
 
     async selectFolder(path) {
+        // Normalize path: null or undefined means root
+        const normalizedPath = (path === null || path === undefined) ? '' : path;
+
         // Update selected path
-        this.selectedPath = path;
+        this.selectedPath = normalizedPath;
 
         // Update UI
         this.updateTreeSelection();
@@ -1019,8 +1037,8 @@ export class SidebarManager {
         this.updateSidebarHeader();
 
         // Update page state
-        this.pageControls.pageState.activeFolder = path;
-        setStorageItem(`${this.pageType}_activeFolder`, path);
+        this.pageControls.pageState.activeFolder = normalizedPath;
+        setStorageItem(`${this.pageType}_activeFolder`, normalizedPath);
 
         // Reload models with new filter
         await this.pageControls.resetAndReload();
@@ -1143,7 +1161,7 @@ export class SidebarManager {
             });
 
             // Add selection to current path
-            if (this.selectedPath !== null) {
+            if (this.selectedPath !== null && this.selectedPath !== undefined) {
                 const selectedItem = folderTree.querySelector(`[data-path="${this.selectedPath}"]`);
                 if (selectedItem) {
                     selectedItem.classList.add('selected');
@@ -1154,7 +1172,7 @@ export class SidebarManager {
                 node.classList.remove('selected');
             });
 
-            if (this.selectedPath) {
+            if (this.selectedPath !== null && this.selectedPath !== undefined) {
                 const selectedNode = folderTree.querySelector(`[data-path="${this.selectedPath}"] .sidebar-tree-node-content`);
                 if (selectedNode) {
                     selectedNode.classList.add('selected');
@@ -1225,9 +1243,10 @@ export class SidebarManager {
 
         // Start with root breadcrumb
         const rootSiblings = Object.keys(this.treeData);
+        const isRootSelected = !this.selectedPath;
         const breadcrumbs = [`
             <div class="breadcrumb-dropdown">
-                <span class="sidebar-breadcrumb-item ${this.selectedPath == null ? 'active' : ''}" data-path="">
+                <span class="sidebar-breadcrumb-item ${isRootSelected ? 'active' : ''}" data-path="">
                     <i class="fas fa-home"></i> ${this.apiClient.apiConfig.config.displayName} root
                 </span>
             </div>
@@ -1323,7 +1342,7 @@ export class SidebarManager {
         const sidebarHeader = document.getElementById('sidebarHeader');
         if (!sidebarHeader) return;
 
-        if (this.selectedPath == null) {
+        if (!this.selectedPath) {
             sidebarHeader.classList.add('root-selected');
         } else {
             sidebarHeader.classList.remove('root-selected');

static/js/components/shared/ModelCard.js

@@ -506,7 +506,7 @@ export function createModelCard(model, modelType) {
 
     // Check if autoplayOnHover is enabled for video previews
     const autoplayOnHover = state.global?.settings?.autoplay_on_hover || false;
-    const isVideo = previewUrl.endsWith('.mp4');
+    const isVideo = previewUrl.endsWith('.mp4') || previewUrl.endsWith('.webm');
     const videoAttrs = [
         'controls',
         'muted',

static/js/components/shared/ModelModal.js

@@ -313,7 +313,7 @@ export async function showModelModal(model, modelType) {
 
     // Prepare LoRA specific data with complete civitai data
     const escapedWords = (modelType === 'loras' || modelType === 'embeddings') && modelWithFullData.civitai?.trainedWords?.length ?
-        modelWithFullData.civitai.trainedWords.map(word => word.replace(/'/g, '\\\'')) : [];
+        modelWithFullData.civitai.trainedWords : [];
 
     // Generate model type specific content
     let typeSpecificContent;

static/js/components/shared/TriggerWords.js

@@ -6,7 +6,7 @@
 import { showToast, copyToClipboard } from '../../utils/uiHelpers.js';
 import { translate } from '../../utils/i18nHelpers.js';
 import { getModelApiClient } from '../../api/modelApiFactory.js';
-import { escapeAttribute } from './utils.js';
+import { escapeAttribute, escapeHtml } from './utils.js';
 
 /**
  * Fetch trained words for a model
@@ -80,8 +80,10 @@ function createSuggestionDropdown(trainedWords, classTokens, existingWords = [])
         const tokenItem = document.createElement('div');
         tokenItem.className = `metadata-suggestion-item class-token-item ${existingWords.includes(classTokens) ? 'already-added' : ''}`;
         tokenItem.title = `${translate('modals.model.triggerWords.suggestions.classToken')}: ${classTokens}`;
+
+        const escapedToken = escapeHtml(classTokens);
         tokenItem.innerHTML = `
-            <span class="metadata-suggestion-text">${classTokens}</span>
+            <span class="metadata-suggestion-text">${escapedToken}</span>
             <div class="metadata-suggestion-meta">
                 <span class="token-badge">${translate('modals.model.triggerWords.suggestions.classToken')}</span>
                 ${existingWords.includes(classTokens) ?
@@ -137,8 +139,10 @@ function createSuggestionDropdown(trainedWords, classTokens, existingWords = [])
             const item = document.createElement('div');
             item.className = `metadata-suggestion-item ${isAdded ? 'already-added' : ''}`;
             item.title = word; // Show full word on hover if truncated
+
+            const escapedWord = escapeHtml(word);
             item.innerHTML = `
-                <span class="metadata-suggestion-text">${word}</span>
+                <span class="metadata-suggestion-text">${escapedWord}</span>
                 <div class="metadata-suggestion-meta">
                     <span class="trained-word-freq">${frequency}</span>
                     ${isAdded ? `<span class="added-indicator"><i class="fas fa-check"></i></span>` : ''}
@@ -215,9 +219,12 @@ export function renderTriggerWords(words, filePath) {
             </div>
             <div class="trigger-words-content">
                 <div class="trigger-words-tags">
-                    ${words.map(word => `
-                        <div class="trigger-word-tag" data-word="${word}" onclick="copyTriggerWord('${word}')" title="${translate('modals.model.triggerWords.copyWord')}">
-                            <span class="trigger-word-content">${word}</span>
+                    ${words.map(word => {
+        const escapedWord = escapeHtml(word);
+        const escapedAttr = escapeAttribute(word);
+        return `
+                        <div class="trigger-word-tag" data-word="${escapedAttr}" onclick="copyTriggerWord(this.dataset.word)" title="${translate('modals.model.triggerWords.copyWord')}">
+                            <span class="trigger-word-content">${escapedWord}</span>
                             <span class="trigger-word-copy">
                                 <i class="fas fa-copy"></i>
                             </span>
@@ -225,7 +232,7 @@ export function renderTriggerWords(words, filePath) {
                                 <i class="fas fa-times"></i>
                             </button>
                         </div>
-                    `).join('')}
+                    `}).join('')}
                 </div>
             </div>
             <div class="metadata-edit-controls" style="display:none;">
@@ -417,7 +424,7 @@ function resetTriggerWordsUIState(section) {
         const deleteBtn = tag.querySelector('.metadata-delete-btn');
 
         // Restore click-to-copy functionality
-        tag.onclick = () => copyTriggerWord(word);
+        tag.onclick = () => copyTriggerWord(tag.dataset.word);
 
         // Show copy icon, hide delete button
         if (copyIcon) copyIcon.style.display = '';
@@ -454,9 +461,11 @@ function restoreOriginalTriggerWords(section, originalWords) {
         const tag = document.createElement('div');
         tag.className = 'trigger-word-tag';
         tag.dataset.word = word;
-        tag.onclick = () => copyTriggerWord(word);
+        tag.onclick = () => copyTriggerWord(tag.dataset.word);
+
+        const escapedWord = escapeHtml(word);
         tag.innerHTML = `
-            <span class="trigger-word-content">${word}</span>
+            <span class="trigger-word-content">${escapedWord}</span>
             <span class="trigger-word-copy">
                 <i class="fas fa-copy"></i>
             </span>
@@ -524,8 +533,10 @@ function addNewTriggerWord(word) {
     const newTag = document.createElement('div');
     newTag.className = 'trigger-word-tag';
     newTag.dataset.word = word;
+
+    const escapedWord = escapeHtml(word);
     newTag.innerHTML = `
-        <span class="trigger-word-content">${word}</span>
+        <span class="trigger-word-content">${escapedWord}</span>
         <span class="trigger-word-copy" style="display:none;">
             <i class="fas fa-copy"></i>
         </span>

static/js/core.js

@@ -60,14 +60,12 @@ export class AppCore {
         initTheme();
         initBackToTop();
         
-        // Initialize the bulk manager and context menu only if not on recipes page
-        if (state.currentPageType !== 'recipes') {
+        // Initialize the bulk manager and context menu
         bulkManager.initialize();
 
         // Initialize bulk context menu
         const bulkContextMenu = new BulkContextMenu();
         bulkManager.setBulkContextMenu(bulkContextMenu);
-        }
         
         // Initialize the example images manager
         exampleImagesManager.initialize();
@@ -84,10 +82,7 @@ export class AppCore {
         
         // Start onboarding if needed (after everything is initialized)
         setTimeout(() => {
-            // Do not show onboarding if version-mismatch banner is visible
-            if (!bannerService.isBannerVisible('version-mismatch')) {
             onboardingManager.start();
-            }
         }, 1000); // Small delay to ensure all elements are rendered
         
         // Return the core instance for chaining

static/js/managers/BannerService.js

@@ -17,7 +17,7 @@ const AFDIAN_URL = 'https://afdian.com/a/pixelpawsai';
 const BANNER_HISTORY_KEY = 'banner_history';
 const BANNER_HISTORY_VIEWED_AT_KEY = 'banner_history_viewed_at';
 const BANNER_HISTORY_LIMIT = 20;
-const HISTORY_EXCLUDED_IDS = new Set(['version-mismatch']);
+const HISTORY_EXCLUDED_IDS = new Set([]);
 
 /**
  * Banner Service for managing notification banners

static/js/managers/BulkManager.js

@@ -3,6 +3,7 @@ import { showToast, copyToClipboard, sendLoraToWorkflow, buildLoraSyntax, getNSF
 import { updateCardsForBulkMode } from '../components/shared/ModelCard.js';
 import { modalManager } from './ModalManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
+import { RecipeSidebarApiClient } from '../api/recipeApi.js';
 import { MODEL_TYPES, MODEL_CONFIG } from '../api/apiConfig.js';
 import { BASE_MODEL_CATEGORIES } from '../utils/constants.js';
 import { getPriorityTagSuggestions } from '../utils/priorityTagHelpers.js';
@@ -62,9 +63,22 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true
+            },
+            recipes: {
+                addTags: false,
+                sendToWorkflow: false,
+                copyAll: false,
+                refreshAll: false,
+                checkUpdates: false,
+                moveAll: true,
+                autoOrganize: false,
+                deleteAll: true,
+                setContentRating: false
             }
         };
 
+        this.recipeApiClient = null;
+
         window.addEventListener('lm:priority-tags-updated', () => {
             const container = document.querySelector('#bulkAddTagsModal .metadata-suggestions-container');
             if (!container) {
@@ -87,9 +101,6 @@ export class BulkManager {
     }
 
     initialize() {
-        // Do not initialize on recipes page
-        if (state.currentPageType === 'recipes') return;
-        
         // Register with event manager for coordinated event handling
         this.registerEventHandlers();
         
@@ -97,6 +108,23 @@ export class BulkManager {
         eventManager.setState('bulkMode', state.bulkMode || false);
     }
 
+    getActiveApiClient() {
+        if (state.currentPageType === 'recipes') {
+            if (!this.recipeApiClient) {
+                this.recipeApiClient = new RecipeSidebarApiClient();
+            }
+            return this.recipeApiClient;
+        }
+        return getModelApiClient();
+    }
+
+    getCurrentDisplayConfig() {
+        if (state.currentPageType === 'recipes') {
+            return { displayName: 'Recipe' };
+        }
+        return MODEL_CONFIG[state.currentPageType] || { displayName: 'Model' };
+    }
+
     setBulkContextMenu(bulkContextMenu) {
         this.bulkContextMenu = bulkContextMenu;
     }
@@ -240,7 +268,9 @@ export class BulkManager {
         // Update event manager state
         eventManager.setState('bulkMode', state.bulkMode);
         
+        if (this.bulkBtn) {
             this.bulkBtn.classList.toggle('active', state.bulkMode);
+        }
         
         updateCardsForBulkMode(state.bulkMode);
         
@@ -504,13 +534,13 @@ export class BulkManager {
         modalManager.closeModal('bulkDeleteModal');
         
         try {
-            const apiClient = getModelApiClient();
+            const apiClient = this.getActiveApiClient();
             const filePaths = Array.from(state.selectedModels);
             
             const result = await apiClient.bulkDeleteModels(filePaths);
             
             if (result.success) {
-                const currentConfig = MODEL_CONFIG[state.currentPageType];
+                const currentConfig = this.getCurrentDisplayConfig();
                 showToast('toast.models.deletedSuccessfully', { 
                     count: result.deleted_count, 
                     type: currentConfig.displayName.toLowerCase() 
@@ -570,7 +600,7 @@ export class BulkManager {
         this.applySelectionState();
         
         const newlySelected = state.selectedModels.size - oldCount;
-        const currentConfig = MODEL_CONFIG[state.currentPageType];
+        const currentConfig = this.getCurrentDisplayConfig();
         showToast('toast.models.selectedAdditional', { 
             count: newlySelected, 
             type: currentConfig.displayName.toLowerCase() 
@@ -622,8 +652,7 @@ export class BulkManager {
             return;
         }
 
-        const currentType = state.currentPageType;
-        const currentConfig = MODEL_CONFIG[currentType] || MODEL_CONFIG[MODEL_TYPES.LORA];
+        const currentConfig = this.getCurrentDisplayConfig();
         const typeLabel = (currentConfig?.displayName || 'Model').toLowerCase();
 
         const { ids: modelIds, missingCount } = this.collectSelectedModelIds();
@@ -969,7 +998,7 @@ export class BulkManager {
             modalManager.closeModal('bulkAddTagsModal');
             
             if (successCount > 0) {
-                const currentConfig = MODEL_CONFIG[state.currentPageType];
+                const currentConfig = this.getCurrentDisplayConfig();
                 const toastKey = mode === 'replace' ? 'toast.models.tagsReplacedSuccessfully' : 'toast.models.tagsAddedSuccessfully';
                 showToast(toastKey, { 
                     count: successCount, 

static/js/managers/FilterManager.js

@@ -3,6 +3,7 @@ import { showToast, updatePanelPositions } from '../utils/uiHelpers.js';
 import { getModelApiClient } from '../api/modelApiFactory.js';
 import { removeStorageItem, setStorageItem, getStorageItem } from '../utils/storageHelpers.js';
 import { MODEL_TYPE_DISPLAY_NAMES } from '../utils/constants.js';
+import { translate } from '../utils/i18nHelpers.js';
 
 export class FilterManager {
     constructor(options = {}) {
@@ -131,6 +132,28 @@ export class FilterManager {
             this.applyTagElementState(tagEl, (this.filters.tags && this.filters.tags[tagName]) || 'none');
             tagsContainer.appendChild(tagEl);
         });
+
+        // Add "No tags" as a special filter at the end
+        const noTagsEl = document.createElement('div');
+        noTagsEl.className = 'filter-tag tag-filter special-tag';
+        const noTagsLabel = translate('header.filter.noTags', {}, 'No tags');
+        const noTagsKey = '__no_tags__';
+        noTagsEl.dataset.tag = noTagsKey;
+        noTagsEl.innerHTML = noTagsLabel;
+
+        noTagsEl.addEventListener('click', async () => {
+            const currentState = (this.filters.tags && this.filters.tags[noTagsKey]) || 'none';
+            const newState = this.getNextTriStateState(currentState);
+            this.setTagFilterState(noTagsKey, newState);
+            this.applyTagElementState(noTagsEl, newState);
+
+            this.updateActiveFiltersCount();
+
+            await this.applyFilters(false);
+        });
+
+        this.applyTagElementState(noTagsEl, (this.filters.tags && this.filters.tags[noTagsKey]) || 'none');
+        tagsContainer.appendChild(noTagsEl);
     }
 
     initializeLicenseFilters() {

static/js/managers/MoveManager.js

@@ -3,6 +3,7 @@ import { state, getCurrentPageState } from '../state/index.js';
 import { modalManager } from './ModalManager.js';
 import { bulkManager } from './BulkManager.js';
 import { getModelApiClient } from '../api/modelApiFactory.js';
+import { RecipeSidebarApiClient } from '../api/recipeApi.js';
 import { FolderTreeManager } from '../components/FolderTreeManager.js';
 import { sidebarManager } from '../components/SidebarManager.js';
 
@@ -12,11 +13,22 @@ class MoveManager {
         this.bulkFilePaths = null;
         this.folderTreeManager = new FolderTreeManager();
         this.initialized = false;
+        this.recipeApiClient = null;
         
         // Bind methods
         this.updateTargetPath = this.updateTargetPath.bind(this);
     }
 
+    _getApiClient(modelType = null) {
+        if (state.currentPageType === 'recipes') {
+            if (!this.recipeApiClient) {
+                this.recipeApiClient = new RecipeSidebarApiClient();
+            }
+            return this.recipeApiClient;
+        }
+        return getModelApiClient(modelType);
+    }
+
     initializeEventListeners() {
         if (this.initialized) return;
         
@@ -36,7 +48,7 @@ class MoveManager {
         this.currentFilePath = null;
         this.bulkFilePaths = null;
         
-        const apiClient = getModelApiClient();
+        const apiClient = this._getApiClient(modelType);
         const currentPageType = state.currentPageType;
         const modelConfig = apiClient.apiConfig.config;
         
@@ -121,7 +133,7 @@ class MoveManager {
 
     async initializeFolderTree() {
         try {
-            const apiClient = getModelApiClient();
+            const apiClient = this._getApiClient();
             // Fetch unified folder tree
             const treeData = await apiClient.fetchUnifiedFolderTree();
             
@@ -141,7 +153,7 @@ class MoveManager {
     updateTargetPath() {
         const pathDisplay = document.getElementById('moveTargetPathDisplay');
         const modelRoot = document.getElementById('moveModelRoot').value;
-        const apiClient = getModelApiClient();
+        const apiClient = this._getApiClient();
         const config = apiClient.apiConfig.config;
         
         let fullPath = modelRoot || `Select a ${config.displayName.toLowerCase()} root directory`;
@@ -158,7 +170,7 @@ class MoveManager {
 
     async moveModel() {
         const selectedRoot = document.getElementById('moveModelRoot').value;
-        const apiClient = getModelApiClient();
+        const apiClient = this._getApiClient();
         const config = apiClient.apiConfig.config;
         
         if (!selectedRoot) {

static/js/managers/UpdateService.js

@@ -4,8 +4,7 @@ import {
     setStorageItem, 
     getStoredVersionInfo, 
     setStoredVersionInfo,
-    isVersionMatch,
-    resetDismissedBanner
+    isVersionMatch
 } from '../utils/storageHelpers.js';
 import { bannerService } from './BannerService.js';
 import { translate } from '../utils/i18nHelpers.js';
@@ -753,94 +752,14 @@ export class UpdateService {
                         stored: getStoredVersionInfo()
                     });
                     
-                    // Reset dismissed status for version mismatch banner
-                    resetDismissedBanner('version-mismatch');
-                    
-                    // Register and show the version mismatch banner
-                    this.registerVersionMismatchBanner();
+                    // Silently update stored version info as cache busting handles the resource updates
+                    setStoredVersionInfo(this.currentVersionInfo);
                 }
             }
         } catch (error) {
             console.error('Failed to check version info:', error);
         }
     }
-    
-    registerVersionMismatchBanner() {
-        // Get stored and current version for display
-        const storedVersion = getStoredVersionInfo() || translate('common.status.unknown');
-        const currentVersion = this.currentVersionInfo || translate('common.status.unknown');
-        
-        bannerService.registerBanner('version-mismatch', {
-            id: 'version-mismatch',
-            title: translate('banners.versionMismatch.title', {}, 'Application Update Detected'),
-            content: translate('banners.versionMismatch.content', { 
-                storedVersion, 
-                currentVersion 
-            }, `Your browser is running an outdated version of LoRA Manager (${storedVersion}). The server has been updated to version ${currentVersion}. Please refresh to ensure proper functionality.`),
-            actions: [
-                {
-                    text: translate('banners.versionMismatch.refreshNow', {}, 'Refresh Now'),
-                    icon: 'fas fa-sync',
-                    action: 'hardRefresh',
-                    type: 'primary'
-                }
-            ],
-            dismissible: false,
-            priority: 10,
-            countdown: 15,
-            onRegister: (bannerElement) => {
-                // Add countdown element
-                const countdownEl = document.createElement('div');
-                countdownEl.className = 'banner-countdown';
-                countdownEl.innerHTML = `<span>${translate('banners.versionMismatch.refreshingIn', {}, 'Refreshing in')} <strong>15</strong> ${translate('banners.versionMismatch.seconds', {}, 'seconds')}...</span>`;
-                bannerElement.querySelector('.banner-content').appendChild(countdownEl);
-                
-                // Start countdown
-                let seconds = 15;
-                const countdownInterval = setInterval(() => {
-                    seconds--;
-                    const strongEl = countdownEl.querySelector('strong');
-                    if (strongEl) strongEl.textContent = seconds;
-                    
-                    if (seconds <= 0) {
-                        clearInterval(countdownInterval);
-                        this.performHardRefresh();
-                    }
-                }, 1000);
-                
-                // Store interval ID for cleanup
-                bannerElement.dataset.countdownInterval = countdownInterval;
-                
-                // Add action button event handler
-                const actionBtn = bannerElement.querySelector('.banner-action[data-action="hardRefresh"]');
-                if (actionBtn) {
-                    actionBtn.addEventListener('click', (e) => {
-                        e.preventDefault();
-                        clearInterval(countdownInterval);
-                        this.performHardRefresh();
-                    });
-                }
-            },
-            onRemove: (bannerElement) => {
-                // Clear any existing interval
-                const intervalId = bannerElement.dataset.countdownInterval;
-                if (intervalId) {
-                    clearInterval(parseInt(intervalId));
-                }
-            }
-        });
-    }
-    
-    performHardRefresh() {
-        // Update stored version info before refreshing
-        setStoredVersionInfo(this.currentVersionInfo);
-        
-        // Force a hard refresh by adding cache-busting parameter
-        const cacheBuster = new Date().getTime();
-        window.location.href = window.location.pathname + 
-            (window.location.search ? window.location.search + '&' : '?') + 
-            `cache=${cacheBuster}`;
-    }
 }
 
 // Create and export singleton instance

static/js/managers/import/DownloadManager.js

@@ -66,6 +66,10 @@ export class DownloadManager {
                     completeMetadata.checkpoint = checkpointMetadata;
                 }
 
+                if (this.importManager.recipeData && this.importManager.recipeData.extension) {
+                    formData.append('extension', this.importManager.recipeData.extension);
+                }
+
                 // Add source_path to metadata to track where the recipe was imported from
                 if (this.importManager.importMode === 'url') {
                     const urlInput = document.getElementById('imageUrlInput');

static/js/managers/import/RecipeDataManager.js

@@ -67,16 +67,27 @@ export class RecipeDataManager {
                 };
                 reader.readAsDataURL(this.importManager.recipeImage);
             } else if (this.importManager.recipeData && this.importManager.recipeData.image_base64) {
-                // For URL mode - use the base64 image data returned from the backend
+                // For URL mode - use the base64 data returned from the backend
+                if (this.importManager.recipeData.is_video) {
+                    const mimeType = this.importManager.recipeData.extension === '.webm' ? 'video/webm' : 'video/mp4';
+                    imagePreview.innerHTML = `<video src="data:${mimeType};base64,${this.importManager.recipeData.image_base64}" controls autoplay loop muted class="recipe-preview-video"></video>`;
+                } else {
                     imagePreview.innerHTML = `<img src="data:image/jpeg;base64,${this.importManager.recipeData.image_base64}" alt="${translate('recipes.controls.import.recipePreviewAlt', {}, 'Recipe preview')}">`;
+                }
             } else if (this.importManager.importMode === 'url') {
                 // Fallback for URL mode if no base64 data
                 const urlInput = document.getElementById('imageUrlInput');
                 if (urlInput && urlInput.value) {
+                    const url = urlInput.value.toLowerCase();
+                    if (url.endsWith('.mp4') || url.endsWith('.webm')) {
+                        const mimeType = url.endsWith('.webm') ? 'video/webm' : 'video/mp4';
+                        imagePreview.innerHTML = `<video src="${urlInput.value}" controls autoplay loop muted class="recipe-preview-video"></video>`;
+                    } else {
                         imagePreview.innerHTML = `<img src="${urlInput.value}" alt="${translate('recipes.controls.import.recipePreviewAlt', {}, 'Recipe preview')}" crossorigin="anonymous">`;
                     }
                 }
             }
+        }
 
         // Update LoRA count information
         const totalLoras = this.importManager.recipeData.loras.length;

static/js/recipes.js

@@ -2,18 +2,47 @@
 import { appCore } from './core.js';
 import { ImportManager } from './managers/ImportManager.js';
 import { RecipeModal } from './components/RecipeModal.js';
-import { getCurrentPageState } from './state/index.js';
+import { state, getCurrentPageState } from './state/index.js';
 import { getSessionItem, removeSessionItem } from './utils/storageHelpers.js';
 import { RecipeContextMenu } from './components/ContextMenu/index.js';
 import { DuplicatesManager } from './components/DuplicatesManager.js';
 import { refreshVirtualScroll } from './utils/infiniteScroll.js';
-import { refreshRecipes } from './api/recipeApi.js';
+import { refreshRecipes, RecipeSidebarApiClient } from './api/recipeApi.js';
+import { sidebarManager } from './components/SidebarManager.js';
+
+class RecipePageControls {
+    constructor() {
+        this.pageType = 'recipes';
+        this.pageState = getCurrentPageState();
+        this.sidebarApiClient = new RecipeSidebarApiClient();
+    }
+
+    async resetAndReload() {
+        refreshVirtualScroll();
+    }
+
+    async refreshModels(fullRebuild = false) {
+        if (fullRebuild) {
+            await refreshRecipes();
+            return;
+        }
+
+        refreshVirtualScroll();
+    }
+
+    getSidebarApiClient() {
+        return this.sidebarApiClient;
+    }
+}
 
 class RecipeManager {
     constructor() {
         // Get page state
         this.pageState = getCurrentPageState();
 
+        // Page controls for shared sidebar behaviors
+        this.pageControls = new RecipePageControls();
+
         // Initialize ImportManager
         this.importManager = new ImportManager();
 
@@ -52,10 +81,23 @@ class RecipeManager {
         // Expose necessary functions to the page
         this._exposeGlobalFunctions();
 
+        // Initialize sidebar navigation
+        await this._initSidebar();
+
         // Initialize common page features
         appCore.initializePageFeatures();
     }
 
+    async _initSidebar() {
+        try {
+            sidebarManager.setHostPageControls(this.pageControls);
+            const shouldShowSidebar = state?.global?.settings?.show_folder_sidebar !== false;
+            await sidebarManager.setSidebarEnabled(shouldShowSidebar);
+        } catch (error) {
+            console.error('Failed to initialize recipe sidebar:', error);
+        }
+    }
+
     _initSearchOptions() {
         // Ensure recipes search options are properly initialized
         if (!this.pageState.searchOptions) {
@@ -63,7 +105,9 @@ class RecipeManager {
                 title: true,       // Recipe title
                 tags: true,        // Recipe tags
                 loraName: true,    // LoRA file name
-                loraModel: true    // LoRA model name
+                loraModel: true,   // LoRA model name
+                prompt: true,      // Prompt search
+                recursive: true
             };
         }
     }
@@ -172,11 +216,26 @@ class RecipeManager {
         // Sort select
         const sortSelect = document.getElementById('sortSelect');
         if (sortSelect) {
+            sortSelect.value = this.pageState.sortBy || 'date:desc';
             sortSelect.addEventListener('change', () => {
                 this.pageState.sortBy = sortSelect.value;
                 refreshVirtualScroll();
             });
         }
+
+        const bulkButton = document.querySelector('[data-action="bulk"]');
+        if (bulkButton) {
+            bulkButton.addEventListener('click', () => window.bulkManager?.toggleBulkMode());
+        }
+
+        const favoriteFilterBtn = document.getElementById('favoriteFilterBtn');
+        if (favoriteFilterBtn) {
+            favoriteFilterBtn.addEventListener('click', () => {
+                this.pageState.showFavoritesOnly = !this.pageState.showFavoritesOnly;
+                favoriteFilterBtn.classList.toggle('active', this.pageState.showFavoritesOnly);
+                refreshVirtualScroll();
+            });
+        }
     }
 
     // This method is kept for compatibility but now uses virtual scrolling

static/js/state/index.js

@@ -95,13 +95,15 @@ export const state = {
             currentPage: 1,
             isLoading: false,
             hasMore: true,
-            sortBy: 'date',
+            sortBy: 'date:desc',
+            activeFolder: getStorageItem('recipes_activeFolder'),
             searchManager: null,
             searchOptions: {
                 title: true,
                 tags: true,
                 loraName: true,
-            loraModel: true
+                loraModel: true,
+                recursive: getStorageItem('recipes_recursiveSearch', true),
             },
             filters: {
                 baseModel: [],

static/js/utils/VirtualScroller.js

@@ -783,12 +783,13 @@ export class VirtualScroller {
     deepMerge(target, source) {
         if (!source || !target) return target;
 
+        // Initialize result with a copy of target
         const result = { ...target };
 
-        // Only iterate over keys that exist in target
-        Object.keys(target).forEach(key => {
-            // Check if source has this key
-            if (source.hasOwnProperty(key)) {
+        if (!source) return result;
+
+        // Iterate over all keys in the source object
+        Object.keys(source).forEach(key => {
             const targetValue = target[key];
             const sourceValue = source[key];
 
@@ -801,13 +802,11 @@ export class VirtualScroller {
                 typeof sourceValue === 'object' &&
                 !Array.isArray(sourceValue)
             ) {
-                    result[key] = this.deepMerge(targetValue, sourceValue);
+                result[key] = this.deepMerge(targetValue || {}, sourceValue);
             } else {
-                    // For primitive types, arrays, or null, use the value from source
+                // Otherwise update with source value (includes primitives, arrays, and new keys)
                 result[key] = sourceValue;
             }
-            }
-            // If source does not have this key, keep the original value from target
         });
 
         return result;

templates/base.html

@@ -4,8 +4,8 @@
 <head>
     <title>{% block title %}{{ t('header.appTitle') }}{% endblock %}</title>
     <meta name="viewport" content="width=device-width, initial-scale=1">
-    <link rel="stylesheet" href="/loras_static/css/style.css">
-    <link rel="stylesheet" href="/loras_static/css/onboarding.css">
+    <link rel="stylesheet" href="/loras_static/css/style.css?v={{ version }}">
+    <link rel="stylesheet" href="/loras_static/css/onboarding.css?v={{ version }}">
     <link rel="stylesheet" href="/loras_static/vendor/flag-icons/flag-icons.min.css">
     {% block page_css %}{% endblock %}
     <link rel="stylesheet" href="/loras_static/vendor/font-awesome/css/all.min.css"
@@ -98,7 +98,7 @@
 
     {% if is_initializing %}
         <!-- Load initialization JavaScript -->
-        <script type="module" src="/loras_static/js/components/initialization.js"></script>
+        <script type="module" src="/loras_static/js/components/initialization.js?v={{ version }}"></script>
     {% else %}
         {% block main_script %}{% endblock %}
     {% endif %}

templates/checkpoints.html

@@ -40,5 +40,5 @@
 {% endblock %}
 
 {% block main_script %}
-<script type="module" src="/loras_static/js/checkpoints.js"></script>
+<script type="module" src="/loras_static/js/checkpoints.js?v={{ version }}"></script>
 {% endblock %}

templates/components/context_menu.html

@@ -102,6 +102,9 @@
     <div class="context-menu-item" data-action="cleanup-example-images-folders">
         <i class="fas fa-trash-restore"></i> <span>{{ t('globalContextMenu.cleanupExampleImages.label') }}</span>
     </div>
+    <div class="context-menu-item" data-action="repair-recipes">
+        <i class="fas fa-tools"></i> <span>{{ t('globalContextMenu.repairRecipes.label') }}</span>
+    </div>
 </div>
 
 <div id="nsfwLevelSelector" class="nsfw-level-selector">
@@ -110,7 +113,8 @@
         <button class="close-nsfw-selector"><i class="fas fa-times"></i></button>
     </div>
     <div class="nsfw-level-content">
-        <div class="current-level"><span>{{ t('modals.contentRating.current') }}:</span> <span id="currentNSFWLevel">{{ t('common.status.unknown') }}</span></div>
+        <div class="current-level"><span>{{ t('modals.contentRating.current') }}:</span> <span id="currentNSFWLevel">{{
+                t('common.status.unknown') }}</span></div>
         <div class="nsfw-level-options">
             <button class="nsfw-level-btn" data-level="1">{{ t('modals.contentRating.levels.pg') }}</button>
             <button class="nsfw-level-btn" data-level="2">{{ t('modals.contentRating.levels.pg13') }}</button>

templates/components/header.html

@@ -19,22 +19,27 @@
     {% set current_page = 'loras' %}
     {% endif %}
     {% set search_disabled = current_page == 'statistics' %}
-    {% set search_placeholder_key = 'header.search.notAvailable' if search_disabled else 'header.search.placeholders.' ~ current_page %}
+    {% set search_placeholder_key = 'header.search.notAvailable' if search_disabled else 'header.search.placeholders.' ~
+    current_page %}
     {% set header_search_class = 'header-search disabled' if search_disabled else 'header-search' %}
     <nav class="main-nav">
       <a href="/loras" class="nav-item{% if current_path == '/loras' %} active{% endif %}" id="lorasNavItem">
         <i class="fas fa-layer-group"></i> <span>{{ t('header.navigation.loras') }}</span>
       </a>
-      <a href="/loras/recipes" class="nav-item{% if current_path.startswith('/loras/recipes') %} active{% endif %}" id="recipesNavItem">
+      <a href="/loras/recipes" class="nav-item{% if current_path.startswith('/loras/recipes') %} active{% endif %}"
+        id="recipesNavItem">
         <i class="fas fa-book-open"></i> <span>{{ t('header.navigation.recipes') }}</span>
       </a>
-      <a href="/checkpoints" class="nav-item{% if current_path.startswith('/checkpoints') %} active{% endif %}" id="checkpointsNavItem">
+      <a href="/checkpoints" class="nav-item{% if current_path.startswith('/checkpoints') %} active{% endif %}"
+        id="checkpointsNavItem">
         <i class="fas fa-check-circle"></i> <span>{{ t('header.navigation.checkpoints') }}</span>
       </a>
-      <a href="/embeddings" class="nav-item{% if current_path.startswith('/embeddings') %} active{% endif %}" id="embeddingsNavItem">
+      <a href="/embeddings" class="nav-item{% if current_path.startswith('/embeddings') %} active{% endif %}"
+        id="embeddingsNavItem">
         <i class="fas fa-code"></i> <span>{{ t('header.navigation.embeddings') }}</span>
       </a>
-      <a href="/statistics" class="nav-item{% if current_path.startswith('/statistics') %} active{% endif %}" id="statisticsNavItem">
+      <a href="/statistics" class="nav-item{% if current_path.startswith('/statistics') %} active{% endif %}"
+        id="statisticsNavItem">
         <i class="fas fa-chart-bar"></i> <span>{{ t('header.navigation.statistics') }}</span>
       </a>
     </nav>
@@ -42,12 +47,15 @@
     <!-- Context-aware search container -->
     <div class="{{ header_search_class }}" id="headerSearch">
       <div class="search-container">
-        <input type="text" id="searchInput" placeholder="{{ t(search_placeholder_key) }}"{% if search_disabled %} disabled{% endif %} />
+        <input type="text" id="searchInput" placeholder="{{ t(search_placeholder_key) }}" {% if search_disabled %}
+          disabled{% endif %} />
         <i class="fas fa-search search-icon"></i>
-        <button class="search-options-toggle" id="searchOptionsToggle" title="{{ t('header.search.options') }}"{% if search_disabled %} disabled aria-disabled="true"{% endif %}>
+        <button class="search-options-toggle" id="searchOptionsToggle" title="{{ t('header.search.options') }}" {% if
+          search_disabled %} disabled aria-disabled="true" {% endif %}>
           <i class="fas fa-sliders-h"></i>
         </button>
-        <button class="search-filter-toggle" id="filterButton" title="{{ t('header.filter.title') }}"{% if search_disabled %} disabled aria-disabled="true"{% endif %}>
+        <button class="search-filter-toggle" id="filterButton" title="{{ t('header.filter.title') }}" {% if
+          search_disabled %} disabled aria-disabled="true" {% endif %}>
           <i class="fas fa-filter"></i>
           <span class="filter-badge" id="activeFiltersCount" style="display: none">0</span>
         </button>
@@ -97,6 +105,7 @@
       <div class="search-option-tag active" data-option="tags">{{ t('header.search.filters.tags') }}</div>
       <div class="search-option-tag active" data-option="loraName">{{ t('header.search.filters.loraName') }}</div>
       <div class="search-option-tag active" data-option="loraModel">{{ t('header.search.filters.loraModel') }}</div>
+      <div class="search-option-tag active" data-option="prompt">{{ t('header.search.filters.prompt') }}</div>
       {% elif request.path == '/checkpoints' %}
       <div class="search-option-tag active" data-option="filename">{{ t('header.search.filters.filename') }}</div>
       <div class="search-option-tag active" data-option="modelname">{{ t('header.search.filters.modelname') }}</div>

templates/embeddings.html

@@ -40,5 +40,5 @@
 {% endblock %}
 
 {% block main_script %}
-<script type="module" src="/loras_static/js/embeddings.js"></script>
+<script type="module" src="/loras_static/js/embeddings.js?v={{ version }}"></script>
 {% endblock %}

templates/loras.html

@@ -24,6 +24,6 @@
 
 {% block main_script %}
 {% if not is_initializing %}
-<script type="module" src="/loras_static/js/loras.js"></script>
+<script type="module" src="/loras_static/js/loras.js?v={{ version }}"></script>
 {% endif %}
 {% endblock %}

templates/recipes.html

@@ -4,9 +4,9 @@
 {% block page_id %}recipes{% endblock %}
 
 {% block page_css %}
-<link rel="stylesheet" href="/loras_static/css/components/card.css">
-<link rel="stylesheet" href="/loras_static/css/components/recipe-modal.css">
-<link rel="stylesheet" href="/loras_static/css/components/import-modal.css">
+<link rel="stylesheet" href="/loras_static/css/components/card.css?v={{ version }}">
+<link rel="stylesheet" href="/loras_static/css/components/recipe-modal.css?v={{ version }}">
+<link rel="stylesheet" href="/loras_static/css/components/import-modal.css?v={{ version }}">
 {% endblock %}
 
 {% block additional_components %}
@@ -15,17 +15,29 @@
 
 <div id="recipeContextMenu" class="context-menu" style="display: none;">
     <!-- <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div> -->
-    <div class="context-menu-item" data-action="share"><i class="fas fa-share-alt"></i> {{ t('loras.contextMenu.shareRecipe') }}</div>
-    <div class="context-menu-item" data-action="copy"><i class="fas fa-copy"></i> {{ t('loras.contextMenu.copyRecipeSyntax') }}</div>
-    <div class="context-menu-item" data-action="sendappend"><i class="fas fa-paper-plane"></i> {{ t('loras.contextMenu.sendToWorkflowAppend') }}</div>
-    <div class="context-menu-item" data-action="sendreplace"><i class="fas fa-exchange-alt"></i> {{ t('loras.contextMenu.sendToWorkflowReplace') }}</div>
-    <div class="context-menu-item" data-action="viewloras"><i class="fas fa-layer-group"></i> {{ t('loras.contextMenu.viewAllLoras') }}</div>
-    <div class="context-menu-item download-missing-item" data-action="download-missing"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadMissingLoras') }}</div>
+    <div class="context-menu-item" data-action="share"><i class="fas fa-share-alt"></i> {{
+        t('loras.contextMenu.shareRecipe') }}</div>
+    <div class="context-menu-item" data-action="copy"><i class="fas fa-copy"></i> {{
+        t('loras.contextMenu.copyRecipeSyntax') }}</div>
+    <div class="context-menu-item" data-action="sendappend"><i class="fas fa-paper-plane"></i> {{
+        t('loras.contextMenu.sendToWorkflowAppend') }}</div>
+    <div class="context-menu-item" data-action="sendreplace"><i class="fas fa-exchange-alt"></i> {{
+        t('loras.contextMenu.sendToWorkflowReplace') }}</div>
+    <div class="context-menu-item" data-action="viewloras"><i class="fas fa-layer-group"></i> {{
+        t('loras.contextMenu.viewAllLoras') }}</div>
+    <div class="context-menu-item download-missing-item" data-action="download-missing"><i class="fas fa-download"></i>
+        {{ t('loras.contextMenu.downloadMissingLoras') }}</div>
     <div class="context-menu-item" data-action="set-nsfw">
         <i class="fas fa-exclamation-triangle"></i> {{ t('loras.contextMenu.setContentRating') }}
     </div>
+    <div class="context-menu-item" data-action="repair">
+        <i class="fas fa-tools"></i> {{ t('loras.contextMenu.repairMetadata') }}
+    </div>
     <div class="context-menu-separator"></div>
-    <div class="context-menu-item delete-item" data-action="delete"><i class="fas fa-trash"></i> {{ t('loras.contextMenu.deleteRecipe') }}</div>
+    <div class="context-menu-item" data-action="move"><i class="fas fa-folder-open"></i> {{
+        t('loras.contextMenu.moveToFolder') }}</div>
+    <div class="context-menu-item delete-item" data-action="delete"><i class="fas fa-trash"></i> {{
+        t('loras.contextMenu.deleteRecipe') }}</div>
 </div>
 {% endblock %}
 
@@ -36,25 +48,95 @@
 {% block content %}
 <!-- Recipe controls -->
 <div class="controls">
+    <div class="actions">
         <div class="action-buttons">
+            <div class="control-group">
+                <select id="sortSelect" title="{{ t('recipes.controls.sort.title') }}">
+                    <optgroup label="{{ t('recipes.controls.sort.name') }}">
+                        <option value="name:asc">{{ t('recipes.controls.sort.nameAsc') }}</option>
+                        <option value="name:desc">{{ t('recipes.controls.sort.nameDesc') }}</option>
+                    </optgroup>
+                    <optgroup label="{{ t('recipes.controls.sort.date') }}">
+                        <option value="date:desc">{{ t('recipes.controls.sort.dateDesc') }}</option>
+                        <option value="date:asc">{{ t('recipes.controls.sort.dateAsc') }}</option>
+                    </optgroup>
+                    <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>
+                </select>
+            </div>
             <div title="{{ t('recipes.controls.refresh.title') }}" class="control-group">
-                <button onclick="recipeManager.refreshRecipes()"><i class="fas fa-sync"></i> {{ t('common.actions.refresh') }}</button>
+                <button onclick="recipeManager.refreshRecipes()"><i class="fas fa-sync"></i> {{
+                    t('common.actions.refresh')
+                    }}</button>
             </div>
             <div title="{{ t('recipes.controls.import.title') }}" class="control-group">
-                <button onclick="importManager.showImportModal()"><i class="fas fa-file-import"></i> {{ t('recipes.controls.import.action') }}</button>
+                <button onclick="importManager.showImportModal()"><i class="fas fa-file-import"></i> {{
+                    t('recipes.controls.import.action') }}</button>
+            </div>
+            <div class="control-group" title="{{ t('loras.controls.bulk.title') }}">
+                <button id="bulkOperationsBtn" data-action="bulk" title="{{ t('loras.controls.bulk.title') }}">
+                    <i class="fas fa-th-large"></i> <span><span>{{ t('loras.controls.bulk.action') }}</span>
+                        <div class="shortcut-key">B</div>
+                    </span>
+                </button>
             </div>
             <!-- Add duplicate detection button -->
             <div title="{{ t('loras.controls.duplicates.title') }}" class="control-group">
-                <button onclick="recipeManager.findDuplicateRecipes()"><i class="fas fa-clone"></i> {{ t('loras.controls.duplicates.action') }}</button>
+                <button onclick="recipeManager.findDuplicateRecipes()"><i class="fas fa-clone"></i> {{
+                    t('loras.controls.duplicates.action') }}</button>
+            </div>
+            <div class="control-group">
+                <button id="favoriteFilterBtn" data-action="toggle-favorites" class="favorite-filter"
+                    title="{{ t('recipes.controls.favorites.title') }}">
+                    <i class="fas fa-star"></i> <span>{{ t('recipes.controls.favorites.action') }}</span>
+                </button>
             </div>
             <!-- Custom filter indicator button (hidden by default) -->
             <div id="customFilterIndicator" class="control-group hidden">
                 <div class="filter-active">
-                    <i class="fas fa-filter"></i> <span id="customFilterText">{{ t('recipes.controls.filteredByLora') }}</span>
+                    <i class="fas fa-filter"></i> <span id="customFilterText">{{ t('recipes.controls.filteredByLora')
+                        }}</span>
                     <i class="fas fa-times-circle clear-filter"></i>
                 </div>
             </div>
         </div>
+
+        <div class="controls-right">
+            <div class="keyboard-nav-hint tooltip">
+                <i class="fas fa-keyboard"></i>
+                <span class="tooltiptext">
+                    <span>{{ t('keyboard.navigation') }}</span>
+                    <table class="keyboard-shortcuts">
+                        <tr>
+                            <td><span class="key">Page Up</span></td>
+                            <td>{{ t('keyboard.shortcuts.pageUp') }}</td>
+                        </tr>
+                        <tr>
+                            <td><span class="key">Page Down</span></td>
+                            <td>{{ t('keyboard.shortcuts.pageDown') }}</td>
+                        </tr>
+                        <tr>
+                            <td><span class="key">Home</span></td>
+                            <td>{{ t('keyboard.shortcuts.home') }}</td>
+                        </tr>
+                        <tr>
+                            <td><span class="key">End</span></td>
+                            <td>{{ t('keyboard.shortcuts.end') }}</td>
+                        </tr>
+                    </table>
+                </span>
+            </div>
+        </div>
+    </div>
+
+    <!-- Breadcrumb Navigation -->
+    <div id="breadcrumbContainer" class="sidebar-breadcrumb-container">
+        <nav class="sidebar-breadcrumb-nav" id="sidebarBreadcrumbNav">
+            <!-- Breadcrumbs will be populated by JavaScript -->
+        </nav>
+    </div>
 </div>
 
 <!-- Duplicates banner (hidden by default) -->
@@ -76,6 +158,8 @@
     </div>
 </div>
 
+{% include 'components/folder_sidebar.html' %}
+
 <!-- Recipe grid -->
 <div class="card-grid" id="recipeGrid">
     <!-- Remove the server-side conditional rendering and placeholder -->
@@ -83,6 +167,10 @@
 </div>
 {% endblock %}
 
-{% block main_script %}
-<script type="module" src="/loras_static/js/recipes.js"></script>
+{% block overlay %}
+<div class="bulk-mode-overlay"></div>
+{% endblock %}
+
+{% block main_script %}
+<script type="module" src="/loras_static/js/recipes.js?v={{ version }}"></script>
 {% endblock %}

templates/statistics.html

@@ -192,6 +192,6 @@
 
 {% block main_script %}
 {% if not is_initializing %}
-<script type="module" src="/loras_static/js/statistics.js"></script>
+<script type="module" src="/loras_static/js/statistics.js?v={{ version }}"></script>
 {% endif %}
 {% endblock %}

tests/config/test_symlink_cache.py

@@ -1,3 +1,4 @@
+import json
 import os
 
 import pytest
@@ -62,6 +63,7 @@ def test_symlink_scan_skips_file_links(monkeypatch: pytest.MonkeyPatch, tmp_path
 
 def test_symlink_cache_reuses_previous_scan(monkeypatch: pytest.MonkeyPatch, tmp_path):
     loras_dir, settings_dir = _setup_paths(monkeypatch, tmp_path)
+    monkeypatch.setattr(config_module.Config, "_schedule_symlink_rescan", lambda self: None)
 
     target_dir = loras_dir / "target"
     target_dir.mkdir()
@@ -85,6 +87,7 @@ def test_symlink_cache_reuses_previous_scan(monkeypatch: pytest.MonkeyPatch, tmp
 
 def test_symlink_cache_survives_noise_mtime(monkeypatch: pytest.MonkeyPatch, tmp_path):
     loras_dir, settings_dir = _setup_paths(monkeypatch, tmp_path)
+    monkeypatch.setattr(config_module.Config, "_schedule_symlink_rescan", lambda self: None)
 
     target_dir = loras_dir / "target"
     target_dir.mkdir()
@@ -109,3 +112,72 @@ def test_symlink_cache_survives_noise_mtime(monkeypatch: pytest.MonkeyPatch, tmp
 
     second_cfg = config_module.Config()
     assert second_cfg.map_path_to_link(str(target_dir)) == _normalize(str(dir_link))
+
+
+def test_background_rescan_refreshes_cache(monkeypatch: pytest.MonkeyPatch, tmp_path):
+    loras_dir, _ = _setup_paths(monkeypatch, tmp_path)
+
+    target_dir = loras_dir / "target"
+    target_dir.mkdir()
+    dir_link = loras_dir / "dir_link"
+    dir_link.symlink_to(target_dir, target_is_directory=True)
+
+    # Build initial cache pointing at the first target
+    first_cfg = config_module.Config()
+    old_real = _normalize(os.path.realpath(target_dir))
+    assert first_cfg.map_path_to_link(str(target_dir)) == _normalize(str(dir_link))
+
+    # Retarget the symlink to a new directory without touching the cache file
+    new_target = loras_dir / "target_v2"
+    new_target.mkdir()
+    dir_link.unlink()
+    dir_link.symlink_to(new_target, target_is_directory=True)
+
+    second_cfg = config_module.Config()
+
+    # Cache may still point at the old real path immediately after load
+    initial_mapping = second_cfg.map_path_to_link(str(new_target))
+    assert initial_mapping in {str(new_target), _normalize(str(dir_link))}
+
+    # Background rescan should refresh the mapping to the new target and update the cache file
+    second_cfg._wait_for_rescan(timeout=2.0)
+    new_real = _normalize(os.path.realpath(new_target))
+    assert second_cfg._path_mappings.get(new_real) == _normalize(str(dir_link))
+    assert second_cfg.map_path_to_link(str(new_target)) == _normalize(str(dir_link))
+
+
+def test_symlink_roots_are_preserved(monkeypatch: pytest.MonkeyPatch, tmp_path):
+    settings_dir = tmp_path / "settings"
+    real_loras = tmp_path / "loras_real"
+    real_loras.mkdir()
+    loras_link = tmp_path / "loras_link"
+    loras_link.symlink_to(real_loras, target_is_directory=True)
+
+    checkpoints_dir = tmp_path / "checkpoints"
+    checkpoints_dir.mkdir()
+    embedding_dir = tmp_path / "embeddings"
+    embedding_dir.mkdir()
+
+    def fake_get_folder_paths(kind: str):
+        mapping = {
+            "loras": [str(loras_link)],
+            "checkpoints": [str(checkpoints_dir)],
+            "unet": [],
+            "embeddings": [str(embedding_dir)],
+        }
+        return mapping.get(kind, [])
+
+    monkeypatch.setattr(config_module.folder_paths, "get_folder_paths", fake_get_folder_paths)
+    monkeypatch.setattr(config_module, "standalone_mode", True)
+    monkeypatch.setattr(config_module, "get_settings_dir", lambda create=True: str(settings_dir))
+    monkeypatch.setattr(config_module.Config, "_schedule_symlink_rescan", lambda self: None)
+
+    cfg = config_module.Config()
+
+    normalized_real = _normalize(os.path.realpath(real_loras))
+    normalized_link = _normalize(str(loras_link))
+    assert cfg._path_mappings[normalized_real] == normalized_link
+
+    cache_path = settings_dir / "cache" / "symlink_map.json"
+    payload = json.loads(cache_path.read_text(encoding="utf-8"))
+    assert payload["path_mappings"][normalized_real] == normalized_link

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

@@ -0,0 +1,114 @@
+import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
+
+const showToastMock = vi.hoisted(() => vi.fn());
+const loadingManagerMock = vi.hoisted(() => ({
+  showSimpleLoading: vi.fn(),
+  hide: vi.fn(),
+}));
+
+vi.mock('../../../static/js/utils/uiHelpers.js', () => {
+  return {
+    showToast: showToastMock,
+  };
+});
+
+vi.mock('../../../static/js/components/RecipeCard.js', () => ({
+  RecipeCard: vi.fn(() => ({ element: document.createElement('div') })),
+}));
+
+vi.mock('../../../static/js/state/index.js', () => {
+  return {
+    state: {
+      loadingManager: loadingManagerMock,
+    },
+    getCurrentPageState: vi.fn(),
+  };
+});
+
+import { RecipeSidebarApiClient } from '../../../static/js/api/recipeApi.js';
+
+describe('RecipeSidebarApiClient bulk operations', () => {
+  beforeEach(() => {
+    vi.clearAllMocks();
+    global.fetch = vi.fn();
+  });
+
+  afterEach(() => {
+    delete global.fetch;
+  });
+
+  it('sends recipe IDs when moving in bulk', async () => {
+    const api = new RecipeSidebarApiClient();
+    global.fetch.mockResolvedValue({
+      ok: true,
+      json: async () => ({
+        success: true,
+        results: [
+          {
+            recipe_id: 'abc',
+            original_file_path: '/recipes/abc.webp',
+            new_file_path: '/recipes/target/abc.webp',
+            success: true,
+          },
+        ],
+        success_count: 1,
+        failure_count: 0,
+      }),
+    });
+
+    const results = await api.moveBulkModels(['/recipes/abc.webp'], '/target/folder');
+
+    expect(global.fetch).toHaveBeenCalledWith(
+      '/api/lm/recipes/move-bulk',
+      expect.objectContaining({
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+      })
+    );
+
+    const { body } = global.fetch.mock.calls[0][1];
+    expect(JSON.parse(body)).toEqual({
+      recipe_ids: ['abc'],
+      target_path: '/target/folder',
+    });
+
+    expect(showToastMock).toHaveBeenCalledWith(
+      'toast.api.bulkMoveSuccess',
+      { successCount: 1, type: 'Recipe' },
+      'success'
+    );
+    expect(results[0].recipe_id).toBe('abc');
+  });
+
+  it('posts recipe IDs for bulk delete', async () => {
+    const api = new RecipeSidebarApiClient();
+    global.fetch.mockResolvedValue({
+      ok: true,
+      json: async () => ({
+        success: true,
+        total_deleted: 2,
+        total_failed: 0,
+        failed: [],
+      }),
+    });
+
+    const result = await api.bulkDeleteModels(['/recipes/a.webp', '/recipes/b.webp']);
+
+    expect(global.fetch).toHaveBeenCalledWith(
+      '/api/lm/recipes/bulk-delete',
+      expect.objectContaining({
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+      })
+    );
+
+    const parsedBody = JSON.parse(global.fetch.mock.calls[0][1].body);
+    expect(parsedBody.recipe_ids).toEqual(['a', 'b']);
+    expect(result).toMatchObject({
+      success: true,
+      deleted_count: 2,
+      failed_count: 0,
+    });
+    expect(loadingManagerMock.hide).toHaveBeenCalled();
+  });
+});

tests/frontend/components/triggerWords.escaping.test.js

@@ -0,0 +1,55 @@
+import { describe, it, expect, beforeEach, vi } from "vitest";
+
+const {
+    TRIGGER_WORDS_MODULE,
+    UTILS_MODULE,
+    I18N_HELPERS_MODULE,
+} = vi.hoisted(() => ({
+    TRIGGER_WORDS_MODULE: new URL('../../../static/js/components/shared/TriggerWords.js', import.meta.url).pathname,
+    UTILS_MODULE: new URL('../../../static/js/components/shared/utils.js', import.meta.url).pathname,
+    I18N_HELPERS_MODULE: new URL('../../../static/js/utils/i18nHelpers.js', import.meta.url).pathname,
+}));
+
+vi.mock(I18N_HELPERS_MODULE, () => ({
+    translate: vi.fn((key, params, fallback) => fallback || key),
+}));
+
+vi.mock('../../../static/js/utils/uiHelpers.js', () => ({
+    showToast: vi.fn(),
+    copyToClipboard: vi.fn(),
+}));
+
+vi.mock('../../../static/js/api/modelApiFactory.js', () => ({
+    getModelApiClient: vi.fn(),
+}));
+
+describe("TriggerWords HTML Escaping", () => {
+    let renderTriggerWords;
+
+    beforeEach(async () => {
+        document.body.innerHTML = '';
+        const module = await import(TRIGGER_WORDS_MODULE);
+        renderTriggerWords = module.renderTriggerWords;
+    });
+
+    it("escapes HTML tags in trigger words rendering", () => {
+        const words = ["<style>guangying</style>", "fym <artist>"];
+        const html = renderTriggerWords(words, "test.safetensors");
+
+        expect(html).toContain("&lt;style&gt;guangying&lt;/style&gt;");
+        expect(html).toContain("fym &lt;artist&gt;");
+        expect(html).not.toContain("<style>guangying</style>");
+    });
+
+    it("uses dataset for copyTriggerWord to safely handle special characters", () => {
+        const words = ["word'with'quotes", "<tag>"];
+        const html = renderTriggerWords(words, "test.safetensors");
+
+        // Check for dataset-word attribute
+        expect(html).toContain('data-word="word&#39;with&#39;quotes"');
+        expect(html).toContain('data-word="&lt;tag&gt;"');
+
+        // Check for the onclick handler
+        expect(html).toContain('onclick="copyTriggerWord(this.dataset.word)"');
+    });
+});

tests/frontend/core/appCore.test.js

@@ -234,7 +234,6 @@ describe('AppCore initialization flow', () => {
     await vi.runAllTimersAsync();
 
     expect(onboardingManager.start).toHaveBeenCalledTimes(1);
-    expect(bannerService.isBannerVisible).toHaveBeenCalledWith('version-mismatch');
   });
 
   it('does not reinitialize once initialized', async () => {
@@ -253,22 +252,13 @@ describe('AppCore initialization flow', () => {
     expect(onboardingManager.start).not.toHaveBeenCalled();
   });
 
-  it('skips bulk setup when viewing recipes', async () => {
+  it('initializes bulk setup when viewing recipes', async () => {
     state.currentPageType = 'recipes';
 
     await appCore.initialize();
 
-    expect(bulkManager.initialize).not.toHaveBeenCalled();
-    expect(BulkContextMenu).not.toHaveBeenCalled();
-    expect(bulkManager.setBulkContextMenu).not.toHaveBeenCalled();
-  });
-
-  it('suppresses onboarding when version mismatch banner is visible', async () => {
-    bannerService.isBannerVisible.mockReturnValueOnce(true);
-
-    await appCore.initialize();
-    await vi.runAllTimersAsync();
-
-    expect(onboardingManager.start).not.toHaveBeenCalled();
+    expect(bulkManager.initialize).toHaveBeenCalledTimes(1);
+    expect(BulkContextMenu).toHaveBeenCalledTimes(1);
+    expect(bulkManager.setBulkContextMenu).toHaveBeenCalledTimes(1);
   });
 });

tests/frontend/pages/recipesPage.test.js

@@ -9,6 +9,8 @@ const removeSessionItemMock = vi.fn();
 const RecipeContextMenuMock = vi.fn();
 const refreshVirtualScrollMock = vi.fn();
 const refreshRecipesMock = vi.fn();
+const fetchUnifiedFolderTreeMock = vi.fn();
+const fetchModelFoldersMock = vi.fn();
 
 let importManagerInstance;
 let recipeModalInstance;
@@ -35,6 +37,15 @@ vi.mock('../../../static/js/components/RecipeModal.js', () => ({
 
 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', () => ({
@@ -56,6 +67,14 @@ vi.mock('../../../static/js/utils/infiniteScroll.js', () => ({
 
 vi.mock('../../../static/js/api/recipeApi.js', () => ({
   refreshRecipes: refreshRecipesMock,
+  RecipeSidebarApiClient: vi.fn(() => ({
+    apiConfig: { config: { displayName: 'Recipes', supportsMove: true } },
+    fetchUnifiedFolderTree: fetchUnifiedFolderTreeMock.mockResolvedValue({ success: true, tree: {} }),
+    fetchModelFolders: fetchModelFoldersMock.mockResolvedValue({ success: true, folders: [] }),
+    fetchModelRoots: vi.fn().mockResolvedValue({ roots: ['/recipes'] }),
+    moveBulkModels: vi.fn(),
+    moveSingleModel: vi.fn(),
+  })),
 }));
 
 describe('RecipeManager', () => {
@@ -81,7 +100,7 @@ describe('RecipeManager', () => {
     };
 
     pageState = {
-      sortBy: 'date',
+      sortBy: 'date:desc',
       searchOptions: undefined,
       customFilter: undefined,
       duplicatesMode: false,
@@ -118,8 +137,8 @@ describe('RecipeManager', () => {
     const sortSelectElement = document.createElement('select');
     sortSelectElement.id = 'sortSelect';
     sortSelectElement.innerHTML = `
-      <option value="date">Date</option>
-      <option value="name">Name</option>
+      <option value="date:desc">Newest</option>
+      <option value="name:asc">Name A-Z</option>
     `;
     document.body.appendChild(sortSelectElement);
 
@@ -139,6 +158,8 @@ describe('RecipeManager', () => {
       tags: true,
       loraName: true,
       loraModel: true,
+      prompt: true,
+      recursive: true,
     });
 
     expect(pageState.customFilter).toEqual({
@@ -162,10 +183,10 @@ describe('RecipeManager', () => {
     expect(refreshVirtualScrollMock).toHaveBeenCalledTimes(1);
 
     const sortSelect = document.getElementById('sortSelect');
-    sortSelect.value = 'name';
+    sortSelect.value = 'name:asc';
     sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
 
-    expect(pageState.sortBy).toBe('name');
+    expect(pageState.sortBy).toBe('name:asc');
     expect(refreshVirtualScrollMock).toHaveBeenCalledTimes(2);
     expect(initializePageFeaturesMock).toHaveBeenCalledTimes(1);
   });

tests/metadata_collector/test_pipe_tracer.py

@@ -0,0 +1,98 @@
+
+import pytest
+from types import SimpleNamespace
+from py.metadata_collector.metadata_processor import MetadataProcessor
+from py.metadata_collector.constants import MODELS, SAMPLING, IS_SAMPLER
+
+class TestPipeTracer:
+    
+    @pytest.fixture
+    def pipe_workflow_metadata(self):
+        """
+        Creates a mock metadata structure matching the one provided in refs/tmp.
+        Structure:
+        Load Checkpoint(28) -> Lora Loader(52) -> ToBasicPipe(69) -> FromBasicPipe(71) -> KSampler(32)
+        """
+        
+        original_prompt = {
+            '28': {
+                'inputs': {'ckpt_name': 'Illustrious\\bananaSplitzXL_vee5PointOh.safetensors'}, 
+                'class_type': 'CheckpointLoaderSimple'
+            },
+            '52': {
+                'inputs': {
+                    'model': ['28', 0],
+                    'clip': ['28', 1]
+                }, 
+                'class_type': 'Lora Loader (LoraManager)'
+            },
+            '69': {
+                'inputs': {
+                    'model': ['52', 0], 
+                    'clip': ['52', 1], 
+                    'vae': ['28', 2], 
+                    'positive': ['75', 0], 
+                    'negative': ['30', 0]
+                }, 
+                'class_type': 'ToBasicPipe'
+            },
+            '71': {
+                'inputs': {'basic_pipe': ['69', 0]}, 
+                'class_type': 'FromBasicPipe'
+            },
+            '32': {
+                'inputs': {
+                    'seed': 131755205602911, 
+                    'steps': 5, 
+                    'cfg': 8.0, 
+                    'sampler_name': 'euler_ancestral', 
+                    'scheduler': 'karras', 
+                    'denoise': 1.0, 
+                    'model': ['71', 0], 
+                    'positive': ['71', 3], 
+                    'negative': ['71', 4], 
+                    'latent_image': ['76', 0]
+                }, 
+                'class_type': 'KSampler'
+            },
+            '75': {'inputs': {'text': 'positive', 'clip': ['52', 1]}, 'class_type': 'CLIPTextEncode'},
+            '30': {'inputs': {'text': 'negative', 'clip': ['52', 1]}, 'class_type': 'CLIPTextEncode'},
+            '76': {'inputs': {'width': 832, 'height': 1216, 'batch_size': 1}, 'class_type': 'EmptyLatentImage'}
+        }
+        
+        metadata = {
+            "current_prompt": SimpleNamespace(original_prompt=original_prompt),
+            MODELS: {
+                "28": {
+                    "type": "checkpoint",
+                    "name": "bananaSplitzXL_vee5PointOh.safetensors"
+                }
+            },
+            SAMPLING: {
+                "32": {
+                    IS_SAMPLER: True,
+                    "parameters": {
+                        "sampler_name": "euler_ancestral",
+                        "scheduler": "karras"
+                    }
+                }
+            }
+        }
+        
+        return metadata
+
+    def test_trace_model_path_through_pipe(self, pipe_workflow_metadata):
+        """Verify trace_model_path can follow: KSampler -> FromBasicPipe -> ToBasicPipe -> Lora -> Checkpoint."""
+        prompt = pipe_workflow_metadata["current_prompt"]
+        
+        # Start trace from KSampler (32)
+        ckpt_id = MetadataProcessor.trace_model_path(pipe_workflow_metadata, prompt, "32")
+        
+        assert ckpt_id == "28"
+
+    def test_find_primary_checkpoint_with_pipe(self, pipe_workflow_metadata):
+        """Verify find_primary_checkpoint returns the correct name even with pipe nodes."""
+        # Providing sampler_id to test the optimization as well
+        name = MetadataProcessor.find_primary_checkpoint(pipe_workflow_metadata, primary_sampler_id="32")
+        
+        assert name == "bananaSplitzXL_vee5PointOh.safetensors"

tests/metadata_collector/test_tracer.py

@@ -0,0 +1,172 @@
+
+import pytest
+from types import SimpleNamespace
+from py.metadata_collector.metadata_processor import MetadataProcessor
+from py.metadata_collector.constants import MODELS, SAMPLING, IS_SAMPLER
+
+class TestMetadataTracer:
+    
+    @pytest.fixture
+    def mock_workflow_metadata(self):
+        """
+        Creates a mock metadata structure with a complex workflow graph.
+        Structure:
+        Sampler(246) -> Guider(241) -> LoraLoader(264) -> CheckpointLoader(238)
+        
+        Also includes a "Decoy" checkpoint (ID 999) that is NOT connected,
+        to verify we found the *connected* one, not just *any* one.
+        """
+        
+        # 1. Define the Graph (Original Prompt)
+        # Using IDs as strings to match typical ComfyUI behavior in metadata
+        original_prompt = {
+            "246": {
+                "class_type": "SamplerCustomAdvanced",
+                "inputs": {
+                    "guider": ["241", 0],
+                    "noise": ["255", 0],
+                    "sampler": ["247", 0],
+                    "sigmas": ["248", 0],
+                    "latent_image": ["153", 0]
+                }
+            },
+            "241": {
+                "class_type": "CFGGuider",
+                "inputs": {
+                    "model": ["264", 0],
+                    "positive": ["239", 0],
+                    "negative": ["240", 0]
+                }
+            },
+            "264": {
+                "class_type": "LoraLoader", # Simplified name
+                "inputs": {
+                    "model": ["238", 0],
+                    "lora_name": "some_style_lora.safetensors"
+                }
+            },
+            "238": {
+                "class_type": "CheckpointLoaderSimple",
+                "inputs": {
+                    "ckpt_name": "Correct_Model.safetensors"
+                }
+            },
+            
+            # unconnected / decoy nodes
+            "999": {
+                "class_type": "CheckpointLoaderSimple",
+                "inputs": {
+                    "ckpt_name": "Decoy_Model.safetensors"
+                }
+            },
+            "154": { # Downstream VAE Decode
+                "class_type": "VAEDecode",
+                "inputs": {
+                    "samples": ["246", 0]
+                }
+            }
+        }
+        
+        # 2. Define the Metadata (Collected execution data)
+        metadata = {
+            "current_prompt": SimpleNamespace(original_prompt=original_prompt),
+            "execution_order": ["238", "264", "241", "246", "154", "999"], # 999 execs last or separately
+            
+            # Models Registry
+            MODELS: {
+                "238": {
+                    "type": "checkpoint",
+                    "name": "Correct_Model.safetensors"
+                },
+                "999": {
+                    "type": "checkpoint",
+                    "name": "Decoy_Model.safetensors"
+                }
+            },
+            
+            # Sampling Registry
+            SAMPLING: {
+                "246": {
+                    IS_SAMPLER: True,
+                    "parameters": {
+                        "sampler_name": "euler",
+                        "scheduler": "normal"
+                    }
+                }
+            },
+            "images": {
+                "first_decode": {
+                    "node_id": "154"
+                }
+            }
+        }
+        
+        return metadata
+
+    def test_find_primary_sampler_identifies_correct_node(self, mock_workflow_metadata):
+        """Verify find_primary_sampler correctly identifies the sampler connected to the downstream decode."""
+        sampler_id, sampler_info = MetadataProcessor.find_primary_sampler(mock_workflow_metadata, downstream_id="154")
+        
+        assert sampler_id == "246"
+        assert sampler_info is not None
+        assert sampler_info["parameters"]["sampler_name"] == "euler"
+
+    def test_trace_model_path_follows_topology(self, mock_workflow_metadata):
+        """Verify trace_model_path follows: Sampler -> Guider -> Lora -> Checkpoint."""
+        prompt = mock_workflow_metadata["current_prompt"]
+        
+        # Start trace from Sampler (246)
+        # Should find Checkpoint (238)
+        ckpt_id = MetadataProcessor.trace_model_path(mock_workflow_metadata, prompt, "246")
+        
+        assert ckpt_id == "238" # Should be the ID of the connected checkpoint
+
+    def test_find_primary_checkpoint_prioritizes_connected_model(self, mock_workflow_metadata):
+        """Verify find_primary_checkpoint returns the NAME of the topologically connected checkpoint, honoring the graph."""
+        name = MetadataProcessor.find_primary_checkpoint(mock_workflow_metadata, downstream_id="154")
+        
+        assert name == "Correct_Model.safetensors"
+        assert name != "Decoy_Model.safetensors"
+
+    def test_trace_model_path_simple_direct_connection(self):
+        """Verify it works for a simple Sampler -> Checkpoint connection."""
+        original_prompt = {
+            "100": { # Sampler
+                "class_type": "KSampler",
+                "inputs": {
+                    "model": ["101", 0]
+                }
+            },
+            "101": { # Checkpoint
+                "class_type": "CheckpointLoaderSimple",
+                "inputs": {}
+            }
+        }
+        
+        metadata = {
+            "current_prompt": SimpleNamespace(original_prompt=original_prompt),
+            MODELS: {
+                "101": {"type": "checkpoint", "name": "Simple_Model.safetensors"}
+            }
+        }
+        
+        ckpt_id = MetadataProcessor.trace_model_path(metadata, metadata["current_prompt"], "100")
+        assert ckpt_id == "101"
+
+    def test_trace_stops_at_max_depth(self):
+        """Verify logic halts if graph is infinitely cyclic or too deep."""
+        # Create a cycle: Node 1 -> Node 2 -> Node 1
+        original_prompt = {
+            "1": {"inputs": {"model": ["2", 0]}},
+            "2": {"inputs": {"model": ["1", 0]}}
+        }
+        
+        metadata = {
+            "current_prompt": SimpleNamespace(original_prompt=original_prompt),
+            MODELS: {} # No checkpoints registered
+        }
+        
+        # Should return None, not hang forever
+        ckpt_id = MetadataProcessor.trace_model_path(metadata, metadata["current_prompt"], "1")
+        assert ckpt_id is None
+

tests/nodes/test_utils.py

@@ -1,4 +1,5 @@
 import logging
+import copy
 
 from py.nodes.utils import nunchaku_load_lora
 
@@ -28,6 +29,9 @@ class _DummyModel:
     def __init__(self):
         self.model = _DummyModelWrapper()
 
+    def clone(self):
+        return copy.deepcopy(self)
+
 
 def test_nunchaku_load_lora_skips_missing_lora(monkeypatch, caplog):
     import folder_paths

tests/routes/test_recipe_route_scaffolding.py

@@ -103,8 +103,7 @@ def test_register_startup_hooks_appends_once():
     ]
 
     assert routes.attach_dependencies in startup_bound_to_routes
-    assert routes.prewarm_cache in startup_bound_to_routes
-    assert len(startup_bound_to_routes) == 2
+    assert len(startup_bound_to_routes) == 1
 
 
 def test_to_route_mapping_uses_handler_set():
@@ -212,4 +211,4 @@ def test_recipe_routes_setup_routes_uses_registrar(monkeypatch: pytest.MonkeyPat
         if isinstance(getattr(cb, "__self__", None), recipe_routes.RecipeRoutes)
     }
     assert {type(cb.__self__) for cb in recipe_callbacks} == {recipe_routes.RecipeRoutes}
-    assert {cb.__name__ for cb in recipe_callbacks} == {"attach_dependencies", "prewarm_cache"}
+    assert {cb.__name__ for cb in recipe_callbacks} == {"attach_dependencies"}

tests/routes/test_recipe_routes.py

@@ -29,6 +29,7 @@ class RecipeRouteHarness:
     persistence: "StubPersistenceService"
     sharing: "StubSharingService"
     downloader: "StubDownloader"
+    civitai: "StubCivitaiClient"
     tmp_dir: Path
 
 
@@ -68,6 +69,10 @@ class StubRecipeScanner:
     async def get_recipe_by_id(self, recipe_id: str) -> Optional[Dict[str, Any]]:
         return self.recipes.get(recipe_id)
 
+    async def get_recipe_json_path(self, recipe_id: str) -> Optional[str]:
+        candidate = Path(self.recipes_dir) / f"{recipe_id}.recipe.json"
+        return str(candidate) if candidate.exists() else None
+
     async def remove_recipe(self, recipe_id: str) -> None:
         self.removed.append(recipe_id)
         self.recipes.pop(recipe_id, None)
@@ -86,6 +91,7 @@ class StubAnalysisService:
         self.remote_calls: List[Optional[str]] = []
         self.local_calls: List[Optional[str]] = []
         self.result = SimpleNamespace(payload={"loras": []}, status=200)
+        self._recipe_parser_factory = None
         StubAnalysisService.instances.append(self)
 
     async def analyze_uploaded_image(self, *, image_bytes: bytes | None, recipe_scanner) -> SimpleNamespace:  # noqa: D401 - mirrors real signature
@@ -118,11 +124,12 @@ class StubPersistenceService:
     def __init__(self, **_: Any) -> None:
         self.save_calls: List[Dict[str, Any]] = []
         self.delete_calls: List[str] = []
+        self.move_calls: List[Dict[str, str]] = []
         self.save_result = SimpleNamespace(payload={"success": True, "recipe_id": "stub-id"}, status=200)
         self.delete_result = SimpleNamespace(payload={"success": True}, status=200)
         StubPersistenceService.instances.append(self)
 
-    async def save_recipe(self, *, recipe_scanner, image_bytes, image_base64, name, tags, metadata) -> SimpleNamespace:  # noqa: D401
+    async def save_recipe(self, *, recipe_scanner, image_bytes, image_base64, name, tags, metadata, extension=None) -> SimpleNamespace:  # noqa: D401
         self.save_calls.append(
             {
                 "recipe_scanner": recipe_scanner,
@@ -131,6 +138,7 @@ class StubPersistenceService:
                 "name": name,
                 "tags": list(tags),
                 "metadata": metadata,
+                "extension": extension,
             }
         )
         return self.save_result
@@ -140,6 +148,12 @@ class StubPersistenceService:
         await recipe_scanner.remove_recipe(recipe_id)
         return self.delete_result
 
+    async def move_recipe(self, *, recipe_scanner, recipe_id: str, target_path: str) -> SimpleNamespace:  # noqa: D401
+        self.move_calls.append({"recipe_id": recipe_id, "target_path": target_path})
+        return SimpleNamespace(
+            payload={"success": True, "recipe_id": recipe_id, "new_file_path": target_path}, status=200
+        )
+
     async def update_recipe(self, *, recipe_scanner, recipe_id: str, updates: Dict[str, Any]) -> SimpleNamespace:  # pragma: no cover - unused by smoke tests
         return SimpleNamespace(payload={"success": True, "recipe_id": recipe_id, "updates": updates}, status=200)
 
@@ -189,6 +203,16 @@ class StubDownloader:
         return True, destination
 
 
+class StubCivitaiClient:
+    """Stub for Civitai API client."""
+
+    def __init__(self) -> None:
+        self.image_info: Dict[str, Any] = {}
+
+    async def get_image_info(self, image_id: str) -> Optional[Dict[str, Any]]:
+        return self.image_info.get(image_id)
+
+
 @asynccontextmanager
 async def recipe_harness(monkeypatch, tmp_path: Path) -> AsyncIterator[RecipeRouteHarness]:
     """Context manager that yields a fully wired recipe route harness."""
@@ -198,12 +222,13 @@ async def recipe_harness(monkeypatch, tmp_path: Path) -> AsyncIterator[RecipeRou
     StubSharingService.instances.clear()
 
     scanner = StubRecipeScanner(tmp_path)
+    civitai_client = StubCivitaiClient()
 
     async def fake_get_recipe_scanner():
         return scanner
 
     async def fake_get_civitai_client():
-        return object()
+        return civitai_client
 
     downloader = StubDownloader()
 
@@ -232,6 +257,7 @@ async def recipe_harness(monkeypatch, tmp_path: Path) -> AsyncIterator[RecipeRou
         persistence=StubPersistenceService.instances[-1],
         sharing=StubSharingService.instances[-1],
         downloader=downloader,
+        civitai=civitai_client,
         tmp_dir=tmp_path,
     )
 
@@ -296,8 +322,23 @@ async def test_save_and_delete_recipe_round_trip(monkeypatch, tmp_path: Path) ->
         assert harness.persistence.delete_calls == ["saved-id"]
 
 
+async def test_move_recipe_invokes_persistence(monkeypatch, tmp_path: Path) -> None:
+    async with recipe_harness(monkeypatch, tmp_path) as harness:
+        response = await harness.client.post(
+            "/api/lm/recipe/move",
+            json={"recipe_id": "move-me", "target_path": str(tmp_path / "recipes" / "subdir")},
+        )
+
+        payload = await response.json()
+        assert response.status == 200
+        assert payload["recipe_id"] == "move-me"
+        assert harness.persistence.move_calls == [
+            {"recipe_id": "move-me", "target_path": str(tmp_path / "recipes" / "subdir")}
+        ]
+
+
 async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
-    provider_calls: list[int] = []
+    provider_calls: list[str | int] = []
 
     class Provider:
         async def get_model_version_info(self, model_version_id):
@@ -307,7 +348,7 @@ async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
     async def fake_get_default_metadata_provider():
         return Provider()
 
-    monkeypatch.setattr(recipe_handlers, "get_default_metadata_provider", fake_get_default_metadata_provider)
+    monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", fake_get_default_metadata_provider)
 
     async with recipe_harness(monkeypatch, tmp_path) as harness:
         resources = [
@@ -349,16 +390,15 @@ async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
         assert call["tags"] == ["foo", "bar"]
         metadata = call["metadata"]
         assert metadata["base_model"] == "Flux Provider"
-        assert provider_calls == [33]
+        assert provider_calls == ["33"]
         assert metadata["checkpoint"]["modelVersionId"] == 33
         assert metadata["loras"][0]["weight"] == 0.25
         assert metadata["gen_params"]["prompt"] == "hello world"
-        assert metadata["gen_params"]["checkpoint"]["modelVersionId"] == 33
         assert harness.downloader.urls == ["https://example.com/images/1"]
 
 
 async def test_import_remote_recipe_falls_back_to_request_base_model(monkeypatch, tmp_path: Path) -> None:
-    provider_calls: list[int] = []
+    provider_calls: list[str | int] = []
 
     class Provider:
         async def get_model_version_info(self, model_version_id):
@@ -368,7 +408,7 @@ async def test_import_remote_recipe_falls_back_to_request_base_model(monkeypatch
     async def fake_get_default_metadata_provider():
         return Provider()
 
-    monkeypatch.setattr(recipe_handlers, "get_default_metadata_provider", fake_get_default_metadata_provider)
+    monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", fake_get_default_metadata_provider)
 
     async with recipe_harness(monkeypatch, tmp_path) as harness:
         resources = [
@@ -397,7 +437,42 @@ async def test_import_remote_recipe_falls_back_to_request_base_model(monkeypatch
 
         metadata = harness.persistence.save_calls[-1]["metadata"]
         assert metadata["base_model"] == "Flux"
-        assert provider_calls == [77]
+        assert provider_calls == ["77"]
+
+
+async def test_import_remote_video_recipe(monkeypatch, tmp_path: Path) -> None:
+    async def fake_get_default_metadata_provider():
+        return SimpleNamespace(get_model_version_info=lambda id: ({}, None))
+
+    monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", fake_get_default_metadata_provider)
+
+    async with recipe_harness(monkeypatch, tmp_path) as harness:
+        harness.civitai.image_info["12345"] = {
+            "id": 12345,
+            "url": "https://image.civitai.com/x/y/original=true/video.mp4",
+            "type": "video"
+        }
+
+        response = await harness.client.get(
+            "/api/lm/recipes/import-remote",
+            params={
+                "image_url": "https://civitai.com/images/12345",
+                "name": "Video Recipe",
+                "resources": json.dumps([]),
+                "base_model": "Flux",
+            },
+        )
+
+        payload = await response.json()
+        assert response.status == 200
+        assert payload["success"] is True
+
+        # Verify downloader was called with rewritten URL
+        assert "transcode=true" in harness.downloader.urls[0]
+        
+        # Verify persistence was called with correct extension
+        call = harness.persistence.save_calls[-1]
+        assert call["extension"] == ".mp4"
 
 
 async def test_analyze_uploaded_image_error_path(monkeypatch, tmp_path: Path) -> None:
@@ -452,3 +527,69 @@ async def test_share_and_download_recipe(monkeypatch, tmp_path: Path) -> None:
         assert body == b"stub"
 
         download_path.unlink(missing_ok=True)
+async def test_import_remote_recipe_merges_metadata(monkeypatch, tmp_path: Path) -> None:
+    # 1. Mock Metadata Provider
+    class Provider:
+        async def get_model_version_info(self, model_version_id):
+            return {"baseModel": "Flux Provider"}, None
+
+    async def fake_get_default_metadata_provider():
+        return Provider()
+
+    monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", fake_get_default_metadata_provider)
+
+    # 2. Mock ExifUtils to return some embedded metadata
+    class MockExifUtils:
+        @staticmethod
+        def extract_image_metadata(path):
+            return "Recipe metadata: " + json.dumps({
+                "gen_params": {"prompt": "from embedded", "seed": 123}
+            })
+
+    monkeypatch.setattr(recipe_handlers, "ExifUtils", MockExifUtils)
+
+    # 3. Mock Parser Factory for StubAnalysisService
+    class MockParser:
+        async def parse_metadata(self, raw, recipe_scanner=None):
+            return json.loads(raw[len("Recipe metadata: "):])
+
+    class MockFactory:
+        def create_parser(self, raw):
+            if raw.startswith("Recipe metadata: "):
+                return MockParser()
+            return None
+
+    # 4. Setup Harness and run test
+    async with recipe_harness(monkeypatch, tmp_path) as harness:
+        harness.analysis._recipe_parser_factory = MockFactory()
+        
+        # Civitai meta via image_info
+        harness.civitai.image_info["1"] = {
+            "id": 1,
+            "url": "https://example.com/images/1.jpg",
+            "meta": {"prompt": "from civitai", "cfg": 7.0}
+        }
+
+        resources = []
+        response = await harness.client.get(
+            "/api/lm/recipes/import-remote",
+            params={
+                "image_url": "https://civitai.com/images/1",
+                "name": "Merged Recipe",
+                "resources": json.dumps(resources),
+                "gen_params": json.dumps({"prompt": "from request", "steps": 25}),
+            },
+        )
+
+        payload = await response.json()
+        assert response.status == 200
+        
+        call = harness.persistence.save_calls[-1]
+        metadata = call["metadata"]
+        gen_params = metadata["gen_params"]
+        
+        # Priority: request (prompt=request, steps=25) > civitai (prompt=civitai, cfg=7.0) > embedded (prompt=embedded, seed=123)
+        assert gen_params["prompt"] == "from request"
+        assert gen_params["steps"] == 25
+        assert gen_params["cfg"] == 7.0
+        assert gen_params["seed"] == 123

tests/services/test_comfy_metadata_parser.py

@@ -0,0 +1,113 @@
+import pytest
+import json
+from py.recipes.parsers.comfy import ComfyMetadataParser
+
+@pytest.mark.asyncio
+async def test_parse_metadata_without_loras(monkeypatch):
+    checkpoint_info = {
+        "id": 2224012,
+        "modelId": 1908679,
+        "model": {"name": "SDXL Checkpoint", "type": "checkpoint"},
+        "name": "v1.0",
+        "images": [{"url": "https://image.civitai.com/checkpoints/original=true"}],
+        "baseModel": "sdxl",
+        "downloadUrl": "https://civitai.com/api/download/checkpoint",
+    }
+
+    async def fake_metadata_provider():
+        class Provider:
+            async def get_model_version_info(self, version_id):
+                assert version_id == "2224012"
+                return checkpoint_info, None
+        return Provider()
+
+    monkeypatch.setattr(
+        "py.recipes.parsers.comfy.get_default_metadata_provider",
+        fake_metadata_provider,
+    )
+
+    parser = ComfyMetadataParser()
+
+    # User provided metadata
+    metadata_json = {
+        "resource-stack": {
+            "class_type": "CheckpointLoaderSimple",
+            "inputs": {"ckpt_name": "urn:air:sdxl:checkpoint:civitai:1908679@2224012"}
+        },
+        "6": {
+            "class_type": "smZ CLIPTextEncode",
+            "inputs": {"text": "Positive prompt content"},
+            "_meta": {"title": "Positive"}
+        },
+        "7": {
+            "class_type": "smZ CLIPTextEncode",
+            "inputs": {"text": "Negative prompt content"},
+            "_meta": {"title": "Negative"}
+        },
+        "11": {
+            "class_type": "KSampler",
+            "inputs": {
+                "sampler_name": "euler_ancestral",
+                "scheduler": "normal",
+                "seed": 904124997,
+                "steps": 35,
+                "cfg": 6,
+                "denoise": 0.1,
+                "model": ["resource-stack", 0],
+                "positive": ["6", 0],
+                "negative": ["7", 0],
+                "latent_image": ["21", 0]
+            },
+            "_meta": {"title": "KSampler"}
+        },
+        "extraMetadata": json.dumps({
+            "prompt": "One woman, (solo:1.3), ...",
+            "negativePrompt": "lowres, worst quality, ...",
+            "steps": 35,
+            "cfgScale": 6,
+            "sampler": "euler_ancestral",
+            "seed": 904124997,
+            "width": 1024,
+            "height": 1024
+        })
+    }
+
+    result = await parser.parse_metadata(json.dumps(metadata_json))
+
+    assert "error" not in result
+    assert result["loras"] == []
+    assert result["checkpoint"] is not None
+    assert int(result["checkpoint"]["modelId"]) == 1908679
+    assert int(result["checkpoint"]["id"]) == 2224012
+    assert result["gen_params"]["prompt"] == "One woman, (solo:1.3), ..."
+    assert result["gen_params"]["steps"] == 35
+    assert result["gen_params"]["size"] == "1024x1024"
+    assert result["from_comfy_metadata"] is True
+
+@pytest.mark.asyncio
+async def test_parse_metadata_without_extra_metadata(monkeypatch):
+    async def fake_metadata_provider():
+        class Provider:
+            async def get_model_version_info(self, version_id):
+                return {"model": {"name": "Test"}, "id": version_id}, None
+        return Provider()
+
+    monkeypatch.setattr(
+        "py.recipes.parsers.comfy.get_default_metadata_provider",
+        fake_metadata_provider,
+    )
+
+    parser = ComfyMetadataParser()
+
+    metadata_json = {
+        "node_1": {
+            "class_type": "CheckpointLoaderSimple",
+            "inputs": {"ckpt_name": "urn:air:sdxl:checkpoint:civitai:123@456"}
+        }
+    }
+
+    result = await parser.parse_metadata(json.dumps(metadata_json))
+
+    assert "error" not in result
+    assert result["loras"] == []
+    assert result["checkpoint"]["id"] == "456"

tests/services/test_gen_params_merger.py

@@ -0,0 +1,95 @@
+import pytest
+from py.recipes.merger import GenParamsMerger
+
+def test_merge_priority():
+    request_params = {"prompt": "from request", "steps": 20}
+    civitai_meta = {"prompt": "from civitai", "cfg": 7.0}
+    embedded_metadata = {"gen_params": {"prompt": "from embedded", "seed": 123}}
+    
+    merged = GenParamsMerger.merge(request_params, civitai_meta, embedded_metadata)
+    
+    assert merged["prompt"] == "from request"
+    assert merged["steps"] == 20
+    assert merged["cfg"] == 7.0
+    assert merged["seed"] == 123
+
+def test_merge_no_request_params():
+    civitai_meta = {"prompt": "from civitai", "cfg": 7.0}
+    embedded_metadata = {"gen_params": {"prompt": "from embedded", "seed": 123}}
+    
+    merged = GenParamsMerger.merge(None, civitai_meta, embedded_metadata)
+    
+    assert merged["prompt"] == "from civitai"
+    assert merged["cfg"] == 7.0
+    assert merged["seed"] == 123
+
+def test_merge_only_embedded():
+    embedded_metadata = {"gen_params": {"prompt": "from embedded", "seed": 123}}
+    
+    merged = GenParamsMerger.merge(None, None, embedded_metadata)
+    
+    assert merged["prompt"] == "from embedded"
+    assert merged["seed"] == 123
+
+def test_merge_raw_embedded():
+    # Test when embedded metadata is just the gen_params themselves
+    embedded_metadata = {"prompt": "from raw embedded", "seed": 456}
+    
+    merged = GenParamsMerger.merge(None, None, embedded_metadata)
+    
+    assert merged["prompt"] == "from raw embedded"
+    assert merged["seed"] == 456
+
+def test_merge_none_values():
+    merged = GenParamsMerger.merge(None, None, None)
+    assert merged == {}
+
+def test_merge_filters_blacklisted_keys():
+    request_params = {"prompt": "test", "id": "should-be-removed", "checkpoint": "should-not-be-here"}
+    civitai_meta = {"cfg": 7, "url": "remove-me"}
+    embedded_metadata = {"seed": 123, "hash": "remove-also"}
+    
+    merged = GenParamsMerger.merge(request_params, civitai_meta, embedded_metadata)
+    
+    assert "prompt" in merged
+    assert "cfg" in merged
+    assert "seed" in merged
+    assert "id" not in merged
+    assert "url" not in merged
+    assert "hash" not in merged
+    assert "checkpoint" not in merged
+
+def test_merge_filters_meta_and_normalizes_keys():
+    civitai_meta = {
+        "prompt": "masterpiece",
+        "cfgScale": 5,
+        "clipSkip": 2,
+        "negativePrompt": "low quality",
+        "meta": {"irrelevant": "data"},
+        "Size": "1024x1024",
+        "draft": False,
+        "workflow": "txt2img",
+        "civitaiResources": [{"type": "checkpoint"}]
+    }
+    request_params = {
+        "cfg_scale": 5.0,
+        "clip_skip": "2",
+        "Steps": 30
+    }
+    
+    merged = GenParamsMerger.merge(request_params, civitai_meta)
+    
+    assert "meta" not in merged
+    assert "cfgScale" not in merged
+    assert "clipSkip" not in merged
+    assert "negativePrompt" not in merged
+    assert "Size" not in merged
+    assert "draft" not in merged
+    assert "workflow" not in merged
+    assert "civitaiResources" not in merged
+    
+    assert merged["cfg_scale"] == 5.0  # From request_params
+    assert merged["clip_skip"] == "2"  # From request_params
+    assert merged["negative_prompt"] == "low quality" # Normalized from civitai_meta
+    assert merged["size"] == "1024x1024" # Normalized from civitai_meta
+    assert merged["steps"] == 30 # Normalized from request_params

tests/services/test_no_tags_filter.py

@@ -0,0 +1,104 @@
+import pytest
+from py.services.model_query import ModelFilterSet, FilterCriteria
+from py.services.recipe_scanner import RecipeScanner
+from pathlib import Path
+from py.config import config
+import asyncio
+from types import SimpleNamespace
+
+class StubSettings:
+    def get(self, key, default=None):
+        return default
+
+# --- Model Filtering Tests ---
+
+def test_model_filter_set_no_tags_include():
+    filter_set = ModelFilterSet(StubSettings())
+    data = [
+        {"name": "m1", "tags": ["tag1"]},
+        {"name": "m2", "tags": []},
+        {"name": "m3", "tags": None},
+        {"name": "m4", "tags": ["tag2"]},
+    ]
+    
+    # Include __no_tags__
+    criteria = FilterCriteria(tags={"__no_tags__": "include"})
+    result = filter_set.apply(data, criteria)
+    assert len(result) == 2
+    assert {item["name"] for item in result} == {"m2", "m3"}
+
+def test_model_filter_set_no_tags_exclude():
+    filter_set = ModelFilterSet(StubSettings())
+    data = [
+        {"name": "m1", "tags": ["tag1"]},
+        {"name": "m2", "tags": []},
+        {"name": "m3", "tags": None},
+        {"name": "m4", "tags": ["tag2"]},
+    ]
+    
+    # Exclude __no_tags__
+    criteria = FilterCriteria(tags={"__no_tags__": "exclude"})
+    result = filter_set.apply(data, criteria)
+    assert len(result) == 2
+    assert {item["name"] for item in result} == {"m1", "m4"}
+
+def test_model_filter_set_no_tags_mixed():
+    filter_set = ModelFilterSet(StubSettings())
+    data = [
+        {"name": "m1", "tags": ["tag1"]},
+        {"name": "m2", "tags": []},
+        {"name": "m3", "tags": None},
+        {"name": "m4", "tags": ["tag1", "tag2"]},
+    ]
+    
+    # Include tag1 AND __no_tags__
+    criteria = FilterCriteria(tags={"tag1": "include", "__no_tags__": "include"})
+    result = filter_set.apply(data, criteria)
+    # m1 (tag1), m2 (no tags), m3 (no tags), m4 (tag1)
+    assert len(result) == 4
+
+# --- Recipe Filtering Tests ---
+
+class StubLoraScanner:
+    def __init__(self):
+        self._cache = SimpleNamespace(raw_data=[], version_index={})
+    async def get_cached_data(self):
+        return self._cache
+    async def refresh_cache(self, force=False):
+        pass
+
+@pytest.fixture
+def recipe_scanner(tmp_path, monkeypatch):
+    monkeypatch.setattr(config, "loras_roots", [str(tmp_path)])
+    stub = StubLoraScanner()
+    scanner = RecipeScanner(lora_scanner=stub)
+    return scanner
+
+@pytest.mark.asyncio
+async def test_recipe_scanner_no_tags_filter(recipe_scanner):
+    scanner = recipe_scanner
+    
+    # Mock some recipe data
+    recipes = [
+        {"id": "r1", "tags": ["tag1"], "title": "R1"},
+        {"id": "r2", "tags": [], "title": "R2"},
+        {"id": "r3", "tags": None, "title": "R3"},
+    ]
+    
+    # We need to inject these into the scanner's cache
+    # Since get_paginated_data calls get_cached_data() which we stubbed
+    scanner._cache = SimpleNamespace(
+        raw_data=recipes,
+        sorted_by_date=recipes,
+        sorted_by_name=recipes
+    )
+    
+    # Test Include __no_tags__
+    result = await scanner.get_paginated_data(page=1, page_size=10, filters={"tags": {"__no_tags__": "include"}})
+    assert len(result["items"]) == 2
+    assert {item["id"] for item in result["items"]} == {"r2", "r3"}
+    
+    # Test Exclude __no_tags__
+    result = await scanner.get_paginated_data(page=1, page_size=10, filters={"tags": {"__no_tags__": "exclude"}})
+    assert len(result["items"]) == 1
+    assert result["items"][0]["id"] == "r1"

tests/services/test_recipe_repair.py

@@ -0,0 +1,282 @@
+import pytest
+import asyncio
+from unittest.mock import AsyncMock, MagicMock
+from py.services.recipe_scanner import RecipeScanner
+from types import SimpleNamespace
+
+# We define these here to help with spec= if needed
+class MockCivitaiClient:
+    async def get_image_info(self, image_id):
+        pass
+
+class MockPersistenceService:
+    async def save_recipe(self, recipe):
+        pass
+
+@pytest.fixture
+def mock_civitai_client():
+    client = MagicMock(spec=MockCivitaiClient)
+    client.get_image_info = AsyncMock()
+    return client
+
+@pytest.fixture
+def mock_metadata_provider():
+    provider = MagicMock()
+    provider.get_model_version_info = AsyncMock(return_value=(None, None))
+    provider.get_model_by_hash = AsyncMock(return_value=(None, None))
+    return provider
+
+@pytest.fixture
+def recipe_scanner():
+    lora_scanner = MagicMock()
+    lora_scanner.get_cached_data = AsyncMock(return_value=SimpleNamespace(raw_data=[]))
+    
+    scanner = RecipeScanner(lora_scanner=lora_scanner)
+    return scanner
+
+@pytest.fixture
+def setup_scanner(recipe_scanner, mock_civitai_client, mock_metadata_provider, monkeypatch):
+    monkeypatch.setattr(recipe_scanner, "_get_civitai_client", AsyncMock(return_value=mock_civitai_client))
+    
+    # Wrap the real method with a mock so we can check calls but still execute it
+    real_save = recipe_scanner._save_recipe_persistently
+    mock_save = AsyncMock(side_effect=real_save)
+    monkeypatch.setattr(recipe_scanner, "_save_recipe_persistently", mock_save)
+    
+    monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", AsyncMock(return_value=mock_metadata_provider))
+    
+    # Mock get_recipe_json_path to avoid file system issues in tests
+    recipe_scanner.get_recipe_json_path = AsyncMock(return_value="/tmp/test_recipe.json")
+    # Mock open to avoid actual file writing
+    monkeypatch.setattr("builtins.open", MagicMock())
+    monkeypatch.setattr("json.dump", MagicMock())
+    monkeypatch.setattr("os.path.exists", MagicMock(return_value=False)) # avoid EXIF logic
+    
+    return recipe_scanner, mock_civitai_client, mock_metadata_provider
+
+@pytest.mark.asyncio
+async def test_repair_all_recipes_skip_up_to_date(setup_scanner):
+    recipe_scanner, _, _ = setup_scanner
+    
+    recipe_scanner._cache = SimpleNamespace(raw_data=[
+        {"id": "r1", "repair_version": RecipeScanner.REPAIR_VERSION, "title": "Up to date"}
+    ])
+    
+    # Run
+    results = await recipe_scanner.repair_all_recipes()
+    
+    # Verify
+    assert results["repaired"] == 0
+    assert results["skipped"] == 1
+    recipe_scanner._save_recipe_persistently.assert_not_called()
+
+@pytest.mark.asyncio
+async def test_repair_all_recipes_with_enriched_checkpoint_id(setup_scanner):
+    recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
+    
+    recipe = {
+        "id": "r1",
+        "title": "Old Recipe",
+        "source_url": "https://civitai.com/images/12345",
+        "checkpoint": None,
+        "gen_params": {"prompt": ""}
+    }
+    recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
+    
+    # Mock image info returning modelVersionId
+    mock_civitai_client.get_image_info.return_value = {
+        "modelVersionId": 5678,
+        "meta": {"prompt": "a beautiful forest", "Checkpoint": "basic_name.safetensors"}
+    }
+    
+    # Mock metadata provider returning full info
+    mock_metadata_provider.get_model_version_info.return_value = ({
+        "id": 5678,
+        "modelId": 1234,
+        "name": "v1.0",
+        "model": {"name": "Full Model Name"},
+        "baseModel": "SDXL 1.0",
+        "images": [{"url": "https://image.url/thumb.jpg"}],
+        "files": [{"type": "Model", "hashes": {"SHA256": "ABCDEF"}, "name": "full_filename.safetensors"}]
+    }, None)
+    
+    # Run
+    results = await recipe_scanner.repair_all_recipes()
+    
+    # Verify
+    assert results["repaired"] == 1
+    mock_metadata_provider.get_model_version_info.assert_called_with("5678")
+    
+    saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
+    checkpoint = saved_recipe["checkpoint"]
+    assert checkpoint["modelName"] == "Full Model Name"
+    assert checkpoint["modelVersionName"] == "v1.0"
+    assert checkpoint["modelId"] == 1234
+    assert checkpoint["modelVersionId"] == 5678
+    assert checkpoint["type"] == "checkpoint"
+    assert "name" not in checkpoint
+    assert "version" not in checkpoint
+    assert "hash" not in checkpoint
+    assert "file_name" not in checkpoint
+
+@pytest.mark.asyncio
+async def test_repair_all_recipes_with_enriched_checkpoint_hash(setup_scanner):
+    recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
+    
+    recipe = {
+        "id": "r1",
+        "title": "Embedded Only",
+        "checkpoint": None,
+        "gen_params": {
+            "prompt": "",
+            "Model hash": "hash123"
+        }
+    }
+    recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
+    
+    # Mock metadata provider lookup by hash
+    mock_metadata_provider.get_model_by_hash.return_value = ({
+        "id": 999,
+        "modelId": 888,
+        "name": "v2.0",
+        "model": {"name": "Hashed Model"},
+        "baseModel": "SD 1.5",
+        "files": [{"type": "Model", "hashes": {"SHA256": "hash123"}, "name": "hashed.safetensors"}]
+    }, None)
+    
+    # Run
+    results = await recipe_scanner.repair_all_recipes()
+    
+    # Verify
+    assert results["repaired"] == 1
+    mock_metadata_provider.get_model_by_hash.assert_called_with("hash123")
+    
+    saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
+    checkpoint = saved_recipe["checkpoint"]
+    assert checkpoint["modelName"] == "Hashed Model"
+    assert checkpoint["modelVersionName"] == "v2.0"
+    assert checkpoint["modelId"] == 888
+    assert checkpoint["type"] == "checkpoint"
+
+@pytest.mark.asyncio
+async def test_repair_all_recipes_fallback_to_basic(setup_scanner):
+    recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
+    
+    recipe = {
+        "id": "r1",
+        "title": "No Meta Lookup",
+        "checkpoint": None,
+        "gen_params": {
+            "prompt": "",
+            "Checkpoint": "just_a_name.safetensors"
+        }
+    }
+    recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
+    
+    # Mock metadata provider returning nothing
+    mock_metadata_provider.get_model_by_hash.return_value = (None, "Model not found")
+    
+    # Run
+    results = await recipe_scanner.repair_all_recipes()
+    
+    # Verify
+    assert results["repaired"] == 1
+    saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
+    assert saved_recipe["checkpoint"]["modelName"] == "just_a_name.safetensors"
+    assert saved_recipe["checkpoint"]["type"] == "checkpoint"
+    assert "modelId" not in saved_recipe["checkpoint"]
+
+@pytest.mark.asyncio
+async def test_repair_all_recipes_progress_callback(setup_scanner):
+    recipe_scanner, _, _ = setup_scanner
+    
+    recipe_scanner._cache = SimpleNamespace(raw_data=[
+        {"id": "r1", "title": "R1", "checkpoint": None},
+        {"id": "r2", "title": "R2", "checkpoint": None}
+    ])
+    
+    progress_calls = []
+    async def progress_callback(data):
+        progress_calls.append(data)
+    
+    # Run
+    await recipe_scanner.repair_all_recipes(
+        progress_callback=progress_callback
+    )
+    
+    # Verify
+    assert len(progress_calls) >= 2
+    assert progress_calls[-1]["status"] == "completed"
+    assert progress_calls[-1]["total"] == 2
+    assert progress_calls[-1]["repaired"] == 2
+
+@pytest.mark.asyncio
+async def test_repair_all_recipes_strips_runtime_fields(setup_scanner):
+    recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
+    
+    # Recipe with runtime fields
+    recipe = {
+        "id": "r1",
+        "title": "Cleanup Test",
+        "checkpoint": {
+            "name": "CP",
+            "inLibrary": True,
+            "localPath": "/path/to/cp",
+            "thumbnailUrl": "thumb.jpg"
+        },
+        "loras": [
+            {
+                "name": "L1",
+                "weight": 0.8,
+                "inLibrary": True,
+                "localPath": "/path/to/l1",
+                "preview_url": "p.jpg"
+            }
+        ],
+        "gen_params": {"prompt": ""}
+    }
+    recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
+    # Set high version to trigger repair if needed (or just ensure it processes)
+    recipe["repair_version"] = 0 
+    
+    # Run
+    await recipe_scanner.repair_all_recipes()
+    
+    # Verify sanitation
+    assert recipe_scanner._save_recipe_persistently.called
+    saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
+    
+    # 1. Check LORA
+    lora = saved_recipe["loras"][0]
+    assert "inLibrary" not in lora
+    assert "localPath" not in lora
+    assert "preview_url" not in lora
+    assert "strength" in lora # weight renamed to strength
+    assert lora["strength"] == 0.8
+    
+    # 2. Check Checkpoint
+    cp = saved_recipe["checkpoint"]
+    assert "inLibrary" not in cp
+    assert "localPath" not in cp
+    assert "thumbnailUrl" not in cp
+
+@pytest.mark.asyncio
+async def test_sanitize_recipe_for_storage(recipe_scanner):
+
+    recipe = {
+        "loras": [{"name": "L1", "inLibrary": True, "weight": 0.5}],
+        "checkpoint": {"name": "CP", "localPath": "/tmp/cp"}
+    }
+    
+    clean = recipe_scanner._sanitize_recipe_for_storage(recipe)
+    
+    assert "inLibrary" not in clean["loras"][0]
+    assert "strength" in clean["loras"][0]
+    assert clean["loras"][0]["strength"] == 0.5
+    assert "localPath" not in clean["checkpoint"]
+    # Testing based on what enricher would produce if it ran, 
+    # but here we are just testing the sanitizer which handles what is ALREADY there.
+    # However, the sanitizer doesn't rename fields, it just removes runtime ones.
+    # Since we changed the enricher to NOT put 'name' anymore, this test case 
+    # should probably reflect the new fields if it's simulating a real recipe.
+    assert clean["checkpoint"]["name"] == "CP"

tests/services/test_recipe_scanner.py

@@ -349,3 +349,295 @@ def test_enrich_formats_absolute_preview_paths(recipe_scanner, tmp_path):
     enriched = scanner._enrich_lora_entry(dict(lora))
 
     assert enriched["preview_url"] == config.get_preview_static_url(str(preview_path))
+
+
+@pytest.mark.asyncio
+async def test_initialize_waits_for_lora_scanner(monkeypatch):
+    ready_flag = asyncio.Event()
+    call_count = 0
+
+    class StubLoraScanner:
+        def __init__(self):
+            self._cache = None
+            self._is_initializing = True
+
+        async def initialize_in_background(self):
+            nonlocal call_count
+            call_count += 1
+            await asyncio.sleep(0)
+            self._cache = SimpleNamespace(raw_data=[])
+            self._is_initializing = False
+            ready_flag.set()
+
+    lora_scanner = StubLoraScanner()
+    scanner = RecipeScanner(lora_scanner=lora_scanner)
+
+    await scanner.initialize_in_background()
+
+    assert ready_flag.is_set()
+    assert call_count == 1
+    assert scanner._cache is not None
+
+
+@pytest.mark.asyncio
+async def test_invalid_model_version_marked_deleted_and_not_retried(monkeypatch, recipe_scanner):
+    scanner, _ = recipe_scanner
+    recipes_dir = Path(config.loras_roots[0]) / "recipes"
+    recipes_dir.mkdir(parents=True, exist_ok=True)
+
+    recipe = {
+        "id": "invalid-version",
+        "file_path": str(recipes_dir / "invalid-version.webp"),
+        "title": "Invalid",
+        "modified": 0.0,
+        "created_date": 0.0,
+        "loras": [{"modelVersionId": 999, "file_name": "", "hash": ""}],
+    }
+    await scanner.add_recipe(dict(recipe))
+
+    call_count = 0
+
+    async def fake_get_hash(model_version_id):
+        nonlocal call_count
+        call_count += 1
+        return None
+
+    monkeypatch.setattr(scanner, "_get_hash_from_civitai", fake_get_hash)
+
+    metadata_updated = await scanner._update_lora_information(recipe)
+
+    assert metadata_updated is True
+    assert recipe["loras"][0]["isDeleted"] is True
+    assert call_count == 1
+
+    # Subsequent calls should skip remote lookup once marked deleted
+    metadata_updated_again = await scanner._update_lora_information(recipe)
+    assert metadata_updated_again is False
+    assert call_count == 1
+
+
+@pytest.mark.asyncio
+async def test_load_recipe_persists_deleted_flag_on_invalid_version(monkeypatch, recipe_scanner, tmp_path):
+    scanner, _ = recipe_scanner
+    recipes_dir = Path(config.loras_roots[0]) / "recipes"
+    recipes_dir.mkdir(parents=True, exist_ok=True)
+
+    recipe_id = "persist-invalid"
+    recipe_path = recipes_dir / f"{recipe_id}.recipe.json"
+    recipe_data = {
+        "id": recipe_id,
+        "file_path": str(recipes_dir / f"{recipe_id}.webp"),
+        "title": "Invalid",
+        "modified": 0.0,
+        "created_date": 0.0,
+        "loras": [{"modelVersionId": 1234, "file_name": "", "hash": ""}],
+    }
+    recipe_path.write_text(json.dumps(recipe_data))
+
+    async def fake_get_hash(model_version_id):
+        return None
+
+    monkeypatch.setattr(scanner, "_get_hash_from_civitai", fake_get_hash)
+
+    loaded = await scanner._load_recipe_file(str(recipe_path))
+
+    assert loaded["loras"][0]["isDeleted"] is True
+
+    persisted = json.loads(recipe_path.read_text())
+    assert persisted["loras"][0]["isDeleted"] is True
+
+
+@pytest.mark.asyncio
+async def test_update_lora_filename_by_hash_updates_affected_recipes(tmp_path: Path, recipe_scanner):
+    scanner, _ = recipe_scanner
+    recipes_dir = Path(config.loras_roots[0]) / "recipes"
+    recipes_dir.mkdir(parents=True, exist_ok=True)
+
+    # Recipe 1: Contains the LoRA with hash "hash1"
+    recipe1_id = "recipe1"
+    recipe1_path = recipes_dir / f"{recipe1_id}.recipe.json"
+    recipe1_data = {
+        "id": recipe1_id,
+        "file_path": str(tmp_path / "img1.png"),
+        "title": "Recipe 1",
+        "modified": 0.0,
+        "created_date": 0.0,
+        "loras": [
+            {"file_name": "old_name", "hash": "hash1"},
+            {"file_name": "other_lora", "hash": "hash2"}
+        ],
+    }
+    recipe1_path.write_text(json.dumps(recipe1_data))
+    await scanner.add_recipe(dict(recipe1_data))
+
+    # Recipe 2: Does NOT contain the LoRA
+    recipe2_id = "recipe2"
+    recipe2_path = recipes_dir / f"{recipe2_id}.recipe.json"
+    recipe2_data = {
+        "id": recipe2_id,
+        "file_path": str(tmp_path / "img2.png"),
+        "title": "Recipe 2",
+        "modified": 0.0,
+        "created_date": 0.0,
+        "loras": [
+            {"file_name": "other_lora", "hash": "hash2"}
+        ],
+    }
+    recipe2_path.write_text(json.dumps(recipe2_data))
+    await scanner.add_recipe(dict(recipe2_data))
+
+    # Update LoRA name for "hash1" (using different case to test normalization)
+    new_name = "new_name"
+    file_count, cache_count = await scanner.update_lora_filename_by_hash("HASH1", new_name)
+
+    assert file_count == 1
+    assert cache_count == 1
+
+    # Check file on disk
+    persisted1 = json.loads(recipe1_path.read_text())
+    assert persisted1["loras"][0]["file_name"] == new_name
+    assert persisted1["loras"][1]["file_name"] == "other_lora"
+
+    # Verify Recipe 2 unchanged
+    persisted2 = json.loads(recipe2_path.read_text())
+    assert persisted2["loras"][0]["file_name"] == "other_lora"
+
+    cache = await scanner.get_cached_data()
+    cached1 = next(r for r in cache.raw_data if r["id"] == recipe1_id)
+    assert cached1["loras"][0]["file_name"] == new_name
+
+
+@pytest.mark.asyncio
+async def test_get_paginated_data_filters_by_favorite(recipe_scanner):
+    scanner, _ = recipe_scanner
+    
+    # Add a normal recipe
+    await scanner.add_recipe({
+        "id": "regular",
+        "file_path": "path/regular.png",
+        "title": "Regular Recipe",
+        "modified": 1.0,
+        "created_date": 1.0,
+        "loras": [],
+    })
+    
+    # Add a favorite recipe
+    await scanner.add_recipe({
+        "id": "favorite",
+        "file_path": "path/favorite.png",
+        "title": "Favorite Recipe",
+        "modified": 2.0,
+        "created_date": 2.0,
+        "loras": [],
+        "favorite": True
+    })
+    
+    # Wait for cache update (it's async in some places, add_recipe is usually enough but let's be safe)
+    await asyncio.sleep(0)
+    
+    # Test without filter (should return both)
+    result_all = await scanner.get_paginated_data(page=1, page_size=10)
+    assert len(result_all["items"]) == 2
+    
+    # Test with favorite filter
+    result_fav = await scanner.get_paginated_data(page=1, page_size=10, filters={"favorite": True})
+    assert len(result_fav["items"]) == 1
+    assert result_fav["items"][0]["id"] == "favorite"
+    
+    # Test with favorite filter set to False (should return both or at least not filter if it's the default)
+    # Actually our implementation checks if 'favorite' in filters and filters['favorite']
+    result_fav_false = await scanner.get_paginated_data(page=1, page_size=10, filters={"favorite": False})
+    assert len(result_fav_false["items"]) == 2
+
+
+@pytest.mark.asyncio
+async def test_get_paginated_data_filters_by_prompt(recipe_scanner):
+    scanner, _ = recipe_scanner
+    
+    # Add a recipe with a specific prompt
+    await scanner.add_recipe({
+        "id": "prompt-recipe",
+        "file_path": "path/prompt.png",
+        "title": "Prompt Recipe",
+        "modified": 1.0,
+        "created_date": 1.0,
+        "loras": [],
+        "gen_params": {
+            "prompt": "a beautiful forest landscape"
+        }
+    })
+    
+    # Add a recipe with a specific negative prompt
+    await scanner.add_recipe({
+        "id": "neg-prompt-recipe",
+        "file_path": "path/neg.png",
+        "title": "Negative Prompt Recipe",
+        "modified": 2.0,
+        "created_date": 2.0,
+        "loras": [],
+        "gen_params": {
+            "negative_prompt": "ugly, blurry mountains"
+        }
+    })
+    
+    await asyncio.sleep(0)
+    
+    # Test search in prompt
+    result_prompt = await scanner.get_paginated_data(
+        page=1, page_size=10, search="forest", search_options={"prompt": True}
+    )
+    assert len(result_prompt["items"]) == 1
+    assert result_prompt["items"][0]["id"] == "prompt-recipe"
+    
+    # Test search in negative prompt
+    result_neg = await scanner.get_paginated_data(
+        page=1, page_size=10, search="mountains", search_options={"prompt": True}
+    )
+    assert len(result_neg["items"]) == 1
+    assert result_neg["items"][0]["id"] == "neg-prompt-recipe"
+    
+    # Test search disabled (should not find by prompt)
+    result_disabled = await scanner.get_paginated_data(
+        page=1, page_size=10, search="forest", search_options={"prompt": False}
+    )
+    assert len(result_disabled["items"]) == 0
+
+
+@pytest.mark.asyncio
+async def test_get_paginated_data_sorting(recipe_scanner):
+    scanner, _ = recipe_scanner
+    
+    # Add test recipes
+    # Recipe A: Name "Alpha", Date 10, LoRAs 2
+    await scanner.add_recipe({
+        "id": "A", "title": "Alpha", "created_date": 10.0,
+        "loras": [{}, {}], "file_path": "a.png"
+    })
+    # Recipe B: Name "Beta", Date 20, LoRAs 1
+    await scanner.add_recipe({
+        "id": "B", "title": "Beta", "created_date": 20.0,
+        "loras": [{}], "file_path": "b.png"
+    })
+    # Recipe C: Name "Gamma", Date 5, LoRAs 3
+    await scanner.add_recipe({
+        "id": "C", "title": "Gamma", "created_date": 5.0,
+        "loras": [{}, {}, {}], "file_path": "c.png"
+    })
+    
+    await asyncio.sleep(0)
+    
+    # Test Name DESC: Gamma, Beta, Alpha
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="name:desc")
+    assert [i["id"] for i in res["items"]] == ["C", "B", "A"]
+    
+    # Test LoRA Count DESC: Gamma (3), Alpha (2), Beta (1)
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="loras_count:desc")
+    assert [i["id"] for i in res["items"]] == ["C", "A", "B"]
+    
+    # Test LoRA Count ASC: Beta (1), Alpha (2), Gamma (3)
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="loras_count:asc")
+    assert [i["id"] for i in res["items"]] == ["B", "A", "C"]
+    
+    # Test Date ASC: Gamma (5), Alpha (10), Beta (20)
+    res = await scanner.get_paginated_data(page=1, page_size=10, sort_by="date:asc")
+    assert [i["id"] for i in res["items"]] == ["C", "A", "B"]

tests/services/test_recipe_services.py

@@ -12,7 +12,12 @@ from py.services.recipes.persistence_service import RecipePersistenceService
 
 
 class DummyExifUtils:
+    def __init__(self):
+        self.appended = None
+        self.optimized_calls = 0
+
     def optimize_image(self, image_data, target_width, format, quality, preserve_metadata):
+        self.optimized_calls += 1
         return image_data, ".webp"
 
     def append_recipe_metadata(self, image_path, recipe_data):
@@ -22,6 +27,46 @@ class DummyExifUtils:
         return {}
 
 
+@pytest.mark.asyncio
+async def test_save_recipe_video_bypasses_optimization(tmp_path):
+    exif_utils = DummyExifUtils()
+
+    class DummyScanner:
+        def __init__(self, root):
+            self.recipes_dir = str(root)
+
+        async def find_recipes_by_fingerprint(self, fingerprint):
+            return []
+
+        async def add_recipe(self, recipe_data):
+            return None
+
+    scanner = DummyScanner(tmp_path)
+    service = RecipePersistenceService(
+        exif_utils=exif_utils,
+        card_preview_width=512,
+        logger=logging.getLogger("test"),
+    )
+
+    metadata = {"base_model": "Flux", "loras": []}
+    video_bytes = b"mp4-content"
+
+    result = await service.save_recipe(
+        recipe_scanner=scanner,
+        image_bytes=video_bytes,
+        image_base64=None,
+        name="Video Recipe",
+        tags=[],
+        metadata=metadata,
+        extension=".mp4",
+    )
+
+    assert result.payload["image_path"].endswith(".mp4")
+    assert Path(result.payload["image_path"]).read_bytes() == video_bytes
+    assert exif_utils.optimized_calls == 0, "Optimization should be bypassed for video"
+    assert exif_utils.appended is None, "Metadata embedding should be bypassed for video"
+
+
 @pytest.mark.asyncio
 async def test_analyze_remote_image_download_failure_cleans_temp(tmp_path, monkeypatch):
     exif_utils = DummyExifUtils()
@@ -50,7 +95,7 @@ async def test_analyze_remote_image_download_failure_cleans_temp(tmp_path, monke
 
     temp_path = tmp_path / "temp.jpg"
 
-    def create_temp_path():
+    def create_temp_path(suffix=".jpg"):
         temp_path.write_bytes(b"")
         return str(temp_path)
 
@@ -356,3 +401,138 @@ async def test_save_recipe_from_widget_allows_empty_lora(tmp_path):
     assert stored["loras"] == []
     assert stored["title"] == "recipe"
     assert scanner.added and scanner.added[0]["loras"] == []
+
+
+@pytest.mark.asyncio
+async def test_move_recipe_updates_paths(tmp_path):
+    exif_utils = DummyExifUtils()
+    recipes_dir = tmp_path / "recipes"
+    recipes_dir.mkdir(parents=True, exist_ok=True)
+
+    recipe_id = "move-me"
+    image_path = recipes_dir / f"{recipe_id}.webp"
+    json_path = recipes_dir / f"{recipe_id}.recipe.json"
+
+    image_path.write_bytes(b"img")
+    json_path.write_text(
+        json.dumps(
+            {
+                "id": recipe_id,
+                "file_path": str(image_path),
+                "title": "Recipe",
+                "loras": [],
+                "gen_params": {},
+                "created_date": 0,
+                "modified": 0,
+            }
+        )
+    )
+
+    class MoveScanner:
+        def __init__(self, root: Path):
+            self.recipes_dir = str(root)
+            self.recipe = {
+                "id": recipe_id,
+                "file_path": str(image_path),
+                "title": "Recipe",
+                "loras": [],
+                "gen_params": {},
+                "created_date": 0,
+                "modified": 0,
+                "folder": "",
+            }
+
+        async def get_recipe_by_id(self, target_id: str):
+            return self.recipe if target_id == recipe_id else None
+
+        async def get_recipe_json_path(self, target_id: str):
+            matches = list(Path(self.recipes_dir).rglob(f"{target_id}.recipe.json"))
+            return str(matches[0]) if matches else None
+
+        async def update_recipe_metadata(self, target_id: str, metadata: dict):
+            if target_id != recipe_id:
+                return False
+            self.recipe.update(metadata)
+            target_path = await self.get_recipe_json_path(target_id)
+            if not target_path:
+                return False
+            existing = json.loads(Path(target_path).read_text())
+            existing.update(metadata)
+            Path(target_path).write_text(json.dumps(existing))
+            return True
+
+        async def get_cached_data(self, force_refresh: bool = False):  # noqa: ARG002 - signature parity
+            return SimpleNamespace(raw_data=[self.recipe])
+
+    scanner = MoveScanner(recipes_dir)
+    service = RecipePersistenceService(
+        exif_utils=exif_utils,
+        card_preview_width=512,
+        logger=logging.getLogger("test"),
+    )
+
+    target_folder = recipes_dir / "nested"
+    result = await service.move_recipe(
+        recipe_scanner=scanner, recipe_id=recipe_id, target_path=str(target_folder)
+    )
+
+    assert result.payload["folder"] == "nested"
+    assert Path(result.payload["json_path"]).parent == target_folder
+    assert Path(result.payload["new_file_path"]).parent == target_folder
+    assert not json_path.exists()
+
+    stored = json.loads(Path(result.payload["json_path"]).read_text())
+    assert stored["folder"] == "nested"
+    assert stored["file_path"] == result.payload["new_file_path"]
+
+
+@pytest.mark.asyncio
+async def test_analyze_remote_video(tmp_path):
+    exif_utils = DummyExifUtils()
+
+    class DummyFactory:
+        def create_parser(self, metadata):
+            async def parse_metadata(m, recipe_scanner):
+                return {"loras": []}
+            return SimpleNamespace(parse_metadata=parse_metadata)
+
+    async def downloader_factory():
+        class Downloader:
+            async def download_file(self, url, path, use_auth=False):
+                Path(path).write_bytes(b"video-content")
+                return True, "success"
+
+        return Downloader()
+
+    service = RecipeAnalysisService(
+        exif_utils=exif_utils,
+        recipe_parser_factory=DummyFactory(),
+        downloader_factory=downloader_factory,
+        metadata_collector=None,
+        metadata_processor_cls=None,
+        metadata_registry_cls=None,
+        standalone_mode=False,
+        logger=logging.getLogger("test"),
+    )
+
+    class DummyClient:
+        async def get_image_info(self, image_id):
+            return {
+                "url": "https://civitai.com/video.mp4",
+                "type": "video",
+                "meta": {"prompt": "video prompt"},
+            }
+
+    class DummyScanner:
+        async def find_recipes_by_fingerprint(self, fingerprint):
+            return []
+
+    result = await service.analyze_remote_image(
+        url="https://civitai.com/images/123",
+        recipe_scanner=DummyScanner(),
+        civitai_client=DummyClient(),
+    )
+
+    assert result.payload["is_video"] is True
+    assert result.payload["extension"] == ".mp4"
+    assert result.payload["image_base64"] is not None

tests/services/test_relative_path_search.py

@@ -1,3 +1,4 @@
+import os
 import pytest
 
 from py.services.base_model_service import BaseModelService
@@ -42,8 +43,8 @@ async def test_search_relative_paths_supports_multiple_tokens():
     matching = await service.search_relative_paths("flux detail")
 
     assert matching == [
-        "flux/detail-model.safetensors",
-        "detail/flux-trained.safetensors",
+        f"flux{os.sep}detail-model.safetensors",
+        f"detail{os.sep}flux-trained.safetensors",
     ]
 
 
@@ -60,4 +61,4 @@ async def test_search_relative_paths_excludes_tokens():
 
     matching = await service.search_relative_paths("flux -detail")
 
-    assert matching == ["flux/keep-me.safetensors"]
+    assert matching == [f"flux{os.sep}keep-me.safetensors"]

tests/services/test_root_folder_recursive.py

@@ -0,0 +1,92 @@
+import pytest
+from py.services.model_query import ModelFilterSet, FilterCriteria
+from py.services.recipe_scanner import RecipeScanner
+from types import SimpleNamespace
+
+# Mock settings
+class MockSettings:
+    def get(self, key, default=None):
+        return default
+
+# --- Model Filtering Tests ---
+
+def test_model_filter_set_root_recursive_true():
+    filter_set = ModelFilterSet(MockSettings())
+    items = [
+        {"model_name": "root_item", "folder": ""},
+        {"model_name": "sub_item", "folder": "sub"},
+    ]
+    criteria = FilterCriteria(folder="", search_options={"recursive": True})
+    
+    result = filter_set.apply(items, criteria)
+    
+    assert len(result) == 2
+    assert any(i["model_name"] == "root_item" for i in result)
+    assert any(i["model_name"] == "sub_item" for i in result)
+
+def test_model_filter_set_root_recursive_false():
+    filter_set = ModelFilterSet(MockSettings())
+    items = [
+        {"model_name": "root_item", "folder": ""},
+        {"model_name": "sub_item", "folder": "sub"},
+    ]
+    criteria = FilterCriteria(folder="", search_options={"recursive": False})
+    
+    result = filter_set.apply(items, criteria)
+    
+    assert len(result) == 1
+    assert result[0]["model_name"] == "root_item"
+
+# --- Recipe Filtering Tests ---
+
+@pytest.mark.asyncio
+async def test_recipe_scanner_root_recursive_true():
+    # Mock LoraScanner
+    class StubLoraScanner:
+        async def get_cached_data(self):
+            return SimpleNamespace(raw_data=[])
+    
+    scanner = RecipeScanner(lora_scanner=StubLoraScanner())
+    # Manually populate cache for testing get_paginated_data logic
+    scanner._cache = SimpleNamespace(
+        raw_data=[
+            {"id": "r1", "title": "root_recipe", "folder": "", "modified": 1.0, "created_date": 1.0, "loras": []},
+            {"id": "r2", "title": "sub_recipe", "folder": "sub", "modified": 2.0, "created_date": 2.0, "loras": []},
+        ],
+        sorted_by_date=[
+            {"id": "r2", "title": "sub_recipe", "folder": "sub", "modified": 2.0, "created_date": 2.0, "loras": []},
+            {"id": "r1", "title": "root_recipe", "folder": "", "modified": 1.0, "created_date": 1.0, "loras": []},
+        ],
+        sorted_by_name=[],
+        version_index={}
+    )
+    
+    result = await scanner.get_paginated_data(page=1, page_size=10, folder="", recursive=True)
+    
+    assert len(result["items"]) == 2
+
+@pytest.mark.asyncio
+async def test_recipe_scanner_root_recursive_false():
+    # Mock LoraScanner
+    class StubLoraScanner:
+        async def get_cached_data(self):
+            return SimpleNamespace(raw_data=[])
+    
+    scanner = RecipeScanner(lora_scanner=StubLoraScanner())
+    scanner._cache = SimpleNamespace(
+        raw_data=[
+            {"id": "r1", "title": "root_recipe", "folder": "", "modified": 1.0, "created_date": 1.0, "loras": []},
+            {"id": "r2", "title": "sub_recipe", "folder": "sub", "modified": 2.0, "created_date": 2.0, "loras": []},
+        ],
+        sorted_by_date=[
+            {"id": "r2", "title": "sub_recipe", "folder": "sub", "modified": 2.0, "created_date": 2.0, "loras": []},
+            {"id": "r1", "title": "root_recipe", "folder": "", "modified": 1.0, "created_date": 1.0, "loras": []},
+        ],
+        sorted_by_name=[],
+        version_index={}
+    )
+    
+    result = await scanner.get_paginated_data(page=1, page_size=10, folder="", recursive=False)
+    
+    assert len(result["items"]) == 1
+    assert result["items"][0]["id"] == "r1"

web/comfyui/trigger_word_toggle.js

@@ -311,7 +311,7 @@ app.registerExtension({
           });
       } else {
         // If no ',,' delimiter, treat the entire message as one group
-        const existing = existingTagMap[message.trim()];
+        const existing = consumeExistingState(message.trim());
         tagArray = [{
           text: message.trim(),
           // Use existing values if available, otherwise use defaults