chore(release): bump version to v1.1.7

- workflow_registry.js: add force param to refreshRegistry(), bypass fingerprint
  dedup when responding to lora_registry_refresh WS message. Without this, the
  backend's wait_for_all() times out after 0.5s because the frontend skips the
  register-nodes POST when the workflow fingerprint hasn't changed (common after
  ComfyUI restart with an empty or unchanged workflow).
- misc_handlers.py: demote 'No nodes registered after refresh' from WARNING to
  DEBUG — empty workflows are a normal operational state, not a warning-worthy
  condition.

locales/de.json

@@ -505,7 +505,9 @@
             "saveSuccess": "Zusätzliche Ordnerpfade aktualisiert. Neustart erforderlich, um Änderungen anzuwenden.",
             "saveError": "Fehler beim Aktualisieren der zusätzlichen Ordnerpfade: {message}",
             "validation": {
-                "duplicatePath": "Dieser Pfad ist bereits konfiguriert"
+                "duplicatePath": "Dieser Pfad ist bereits konfiguriert",
+                "checkpointUnetOverlap": "Derselbe Pfad kann nicht für Checkpoints und Diffusionsmodelle verwendet werden: {paths}",
+                "checkpointUnetOverlapInline": "Dieser Pfad wird bereits für einen anderen Modelltyp verwendet. Bitte verwenden Sie separate Ordner für Checkpoints und Diffusionsmodelle."
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "Civitai-Daten aktualisieren",
             "checkUpdates": "Updates prüfen",
-            "relinkCivitai": "Mit Civitai neu verknüpfen",
+            "linkModel": "Modell verknüpfen",
+            "linkCivitai": "Mit Civitai neu verknüpfen",
+            "linkHuggingFace": "Mit HuggingFace verknüpfen",
             "copySyntax": "LoRA-Syntax kopieren",
             "copyFilename": "Modell-Dateiname kopieren",
             "copyRecipeSyntax": "Rezept-Syntax kopieren",
@@ -1203,7 +1207,9 @@
                 "preparing": "Download wird vorbereitet...",
                 "downloadedPreview": "Vorschaubild heruntergeladen",
                 "downloadingFile": "{type}-Datei wird heruntergeladen",
-                "finalizing": "Download wird abgeschlossen..."
+                "finalizing": "Download wird abgeschlossen...",
+                "cancelling": "Download wird abgebrochen...",
+                "cancelled": "Download abgebrochen"
             },
             "progress": {
                 "currentFile": "Aktuelle Datei:",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "Ordnerpfad eingeben oder aus Baum unten auswählen...",
             "root": "Stammverzeichnis"
         },
+        "linkHuggingFace": {
+            "title": "Mit HuggingFace verknüpfen",
+            "infoText": "Fügen Sie die HuggingFace-Repository-URL ein, um dieses Modell zuzuordnen. Dies ermöglicht die KI-gestützte Metadatenanreicherung.",
+            "urlLabel": "HuggingFace-Repository-URL:",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "Geben Sie die vollständige URL des HuggingFace-Repositorys ein.",
+            "confirmAction": "Speichern & Verknüpfen"
+        },
         "relinkCivitai": {
             "title": "Mit Civitai neu verknüpfen",
             "warning": "Warnung:",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "Beispielbilder {action} abgeschlossen",
             "imagesFailed": "Beispielbilder {action} fehlgeschlagen",
             "loadError": "Fehler beim Laden der Downloads: {message}",
-            "downloadError": "Download-Fehler: {message}"
+            "downloadError": "Download-Fehler: {message}",
+            "downloadStopped": "Download abgebrochen"
         },
         "import": {
             "folderTreeFailed": "Fehler beim Laden des Ordnerbaums",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "Fehler beim Setzen der Inhaltsbewertung: {message}",
             "relinkSuccess": "Modell erfolgreich mit Civitai neu verknüpft",
             "relinkFailed": "Fehler: {message}",
+            "linkHfSuccess": "Modell erfolgreich mit HuggingFace verknüpft",
+            "linkHfFailed": "Fehler: {message}",
             "fetchMetadataFirst": "Bitte rufen Sie zuerst Metadaten von CivitAI ab",
             "noCivitaiInfo": "Keine CivitAI-Informationen verfügbar",
             "missingHash": "Modell-Hash nicht verfügbar"

locales/en.json

@@ -505,7 +505,9 @@
       "saveSuccess": "Extra folder paths updated. Restart required to apply changes.",
       "saveError": "Failed to update extra folder paths: {message}",
       "validation": {
-        "duplicatePath": "This path is already configured"
+        "duplicatePath": "This path is already configured",
+        "checkpointUnetOverlap": "Cannot use the same path for both checkpoints and diffusion models: {paths}",
+        "checkpointUnetOverlapInline": "This path is also used for a different model type. Use separate folders for checkpoints and diffusion models."
       }
     },
     "priorityTags": {
@@ -786,7 +788,9 @@
     "contextMenu": {
       "refreshMetadata": "Refresh Civitai Data",
       "checkUpdates": "Check Updates",
-      "relinkCivitai": "Re-link to Civitai",
+      "linkModel": "Link Model",
+      "linkCivitai": "Link to Civitai",
+      "linkHuggingFace": "Link to HuggingFace",
       "copySyntax": "Copy LoRA Syntax",
       "copyFilename": "Copy Model Filename",
       "copyRecipeSyntax": "Copy Recipe Syntax",
@@ -1203,7 +1207,9 @@
         "preparing": "Preparing download...",
         "downloadedPreview": "Downloaded preview image",
         "downloadingFile": "Downloading {type} file",
-        "finalizing": "Finalizing download..."
+        "finalizing": "Finalizing download...",
+        "cancelling": "Cancelling download...",
+        "cancelled": "Download cancelled"
       },
       "progress": {
         "currentFile": "Current file:",
@@ -1319,6 +1325,14 @@
       "pathPlaceholder": "Type folder path or select from tree below...",
       "root": "Root"
     },
+    "linkHuggingFace": {
+      "title": "Link to HuggingFace",
+      "infoText": "Paste the HuggingFace repository URL to associate this model with its source. This enables AI-powered metadata enrichment.",
+      "urlLabel": "HuggingFace Repository URL:",
+      "urlPlaceholder": "https://huggingface.co/user/repo",
+      "helpText": "Enter the full URL of the HuggingFace repository.",
+      "confirmAction": "Save & Link"
+    },
     "relinkCivitai": {
       "title": "Re-link to Civitai",
       "warning": "Warning:",
@@ -2003,7 +2017,8 @@
       "imagesCompleted": "Example images {action} completed",
       "imagesFailed": "Example images {action} failed",
       "loadError": "Error loading downloads: {message}",
-      "downloadError": "Download error: {message}"
+      "downloadError": "Download error: {message}",
+      "downloadStopped": "Download cancelled"
     },
     "import": {
       "folderTreeFailed": "Failed to load folder tree",
@@ -2048,6 +2063,8 @@
       "contentRatingFailed": "Failed to set content rating: {message}",
       "relinkSuccess": "Model successfully re-linked to Civitai",
       "relinkFailed": "Error: {message}",
+      "linkHfSuccess": "Model successfully linked to HuggingFace",
+      "linkHfFailed": "Error: {message}",
       "fetchMetadataFirst": "Please fetch metadata from CivitAI first",
       "noCivitaiInfo": "No CivitAI information available",
       "missingHash": "Model hash not available"

locales/es.json

@@ -505,7 +505,9 @@
             "saveSuccess": "Rutas de carpetas adicionales actualizadas. Se requiere reinicio para aplicar los cambios.",
             "saveError": "Error al actualizar las rutas de carpetas adicionales: {message}",
             "validation": {
-                "duplicatePath": "Esta ruta ya está configurada"
+                "duplicatePath": "Esta ruta ya está configurada",
+                "checkpointUnetOverlap": "No se puede usar la misma ruta para checkpoints y modelos de difusión: {paths}",
+                "checkpointUnetOverlapInline": "Esta ruta ya se usa para otro tipo de modelo. Use carpetas separadas para checkpoints y modelos de difusión."
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "Actualizar datos de Civitai",
             "checkUpdates": "Comprobar actualizaciones",
-            "relinkCivitai": "Re-vincular a Civitai",
+            "linkModel": "Vincular modelo",
+            "linkCivitai": "Re-vincular a Civitai",
+            "linkHuggingFace": "Vincular a HuggingFace",
             "copySyntax": "Copiar sintaxis de LoRA",
             "copyFilename": "Copiar nombre de archivo del modelo",
             "copyRecipeSyntax": "Copiar sintaxis de receta",
@@ -1203,7 +1207,9 @@
                 "preparing": "Preparando descarga...",
                 "downloadedPreview": "Imagen de vista previa descargada",
                 "downloadingFile": "Descargando archivo de {type}",
-                "finalizing": "Finalizando descarga..."
+                "finalizing": "Finalizando descarga...",
+                "cancelling": "Cancelando descarga...",
+                "cancelled": "Descarga cancelada"
             },
             "progress": {
                 "currentFile": "Archivo actual:",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "Escribe la ruta de la carpeta o selecciona del árbol de abajo...",
             "root": "Raíz"
         },
+        "linkHuggingFace": {
+            "title": "Vincular a HuggingFace",
+            "infoText": "Pegue la URL del repositorio de HuggingFace para asociar este modelo. Esto permite el enriquecimiento de metadatos con IA.",
+            "urlLabel": "URL del repositorio de HuggingFace:",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "Ingrese la URL completa del repositorio de HuggingFace.",
+            "confirmAction": "Guardar y vincular"
+        },
         "relinkCivitai": {
             "title": "Re-vincular a Civitai",
             "warning": "Advertencia:",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "Imágenes de ejemplo {action} completadas",
             "imagesFailed": "Imágenes de ejemplo {action} fallidas",
             "loadError": "Error al cargar descargas: {message}",
-            "downloadError": "Error de descarga: {message}"
+            "downloadError": "Error de descarga: {message}",
+            "downloadStopped": "Descarga cancelada"
         },
         "import": {
             "folderTreeFailed": "Error al cargar árbol de carpetas",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "Error al establecer clasificación de contenido: {message}",
             "relinkSuccess": "Modelo re-vinculado exitosamente a Civitai",
             "relinkFailed": "Error: {message}",
+            "linkHfSuccess": "Modelo vinculado a HuggingFace exitosamente",
+            "linkHfFailed": "Error: {message}",
             "fetchMetadataFirst": "Por favor obtén metadatos de CivitAI primero",
             "noCivitaiInfo": "No hay información de CivitAI disponible",
             "missingHash": "Hash del modelo no disponible"

locales/fr.json

@@ -505,7 +505,9 @@
             "saveSuccess": "Chemins de dossiers supplémentaires mis à jour. Redémarrage requis pour appliquer les changements.",
             "saveError": "Échec de la mise à jour des chemins de dossiers supplémentaires: {message}",
             "validation": {
-                "duplicatePath": "Ce chemin est déjà configuré"
+                "duplicatePath": "Ce chemin est déjà configuré",
+                "checkpointUnetOverlap": "Impossible d'utiliser le même chemin pour les checkpoints et les modèles de diffusion : {paths}",
+                "checkpointUnetOverlapInline": "Ce chemin est déjà utilisé pour un autre type de modèle. Utilisez des dossiers séparés pour les checkpoints et les modèles de diffusion."
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "Actualiser les données Civitai",
             "checkUpdates": "Vérifier les mises à jour",
-            "relinkCivitai": "Relier à nouveau à Civitai",
+            "linkModel": "Lier le modèle",
+            "linkCivitai": "Relier à nouveau à Civitai",
+            "linkHuggingFace": "Lier à HuggingFace",
             "copySyntax": "Copier la syntaxe LoRA",
             "copyFilename": "Copier le nom de fichier du modèle",
             "copyRecipeSyntax": "Copier la syntaxe de la recipe",
@@ -1203,7 +1207,9 @@
                 "preparing": "Préparation du téléchargement...",
                 "downloadedPreview": "Image d'aperçu téléchargée",
                 "downloadingFile": "Téléchargement du fichier {type}",
-                "finalizing": "Finalisation du téléchargement..."
+                "finalizing": "Finalisation du téléchargement...",
+                "cancelling": "Annulation du téléchargement...",
+                "cancelled": "Téléchargement annulé"
             },
             "progress": {
                 "currentFile": "Fichier actuel :",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "Tapez le chemin du dossier ou sélectionnez dans l'arbre ci-dessous...",
             "root": "Racine"
         },
+        "linkHuggingFace": {
+            "title": "Lier à HuggingFace",
+            "infoText": "Collez l'URL du dépôt HuggingFace pour associer ce modèle à sa source. Cela permet l'enrichissement des métadonnées par IA.",
+            "urlLabel": "URL du dépôt HuggingFace :",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "Entrez l'URL complète du dépôt HuggingFace.",
+            "confirmAction": "Enregistrer & lier"
+        },
         "relinkCivitai": {
             "title": "Relier à nouveau à Civitai",
             "warning": "Attention :",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "Images d'exemple {action} terminées",
             "imagesFailed": "Images d'exemple {action} échouées",
             "loadError": "Erreur lors du chargement des téléchargements : {message}",
-            "downloadError": "Erreur de téléchargement : {message}"
+            "downloadError": "Erreur de téléchargement : {message}",
+            "downloadStopped": "Téléchargement annulé"
         },
         "import": {
             "folderTreeFailed": "Échec du chargement de l'arborescence des dossiers",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "Échec de la définition de la classification du contenu : {message}",
             "relinkSuccess": "Modèle relié à Civitai avec succès",
             "relinkFailed": "Erreur : {message}",
+            "linkHfSuccess": "Modèle lié à HuggingFace avec succès",
+            "linkHfFailed": "Erreur : {message}",
             "fetchMetadataFirst": "Veuillez d'abord récupérer les métadonnées depuis CivitAI",
             "noCivitaiInfo": "Aucune information CivitAI disponible",
             "missingHash": "Hash du modèle non disponible"

locales/he.json

@@ -505,7 +505,9 @@
             "saveSuccess": "נתיבי תיקיות נוספים עודכנו. נדרשת הפעלה מחדש כדי להחיל את השינויים.",
             "saveError": "נכשל בעדכון נתיבי תיקיות נוספים: {message}",
             "validation": {
-                "duplicatePath": "נתיב זה כבר מוגדר"
+                "duplicatePath": "נתיב זה כבר מוגדר",
+                "checkpointUnetOverlap": "לא ניתן להשתמש באותו נתיב עבור checkpoints ומודלי דיפוזיה: {paths}",
+                "checkpointUnetOverlapInline": "הנתיב הזה כבר נמצא בשימוש עבור סוג מודל אחר. יש להשתמש בתיקיות נפרדות עבור checkpoints ומודלי דיפוזיה."
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "רענן נתוני Civitai",
             "checkUpdates": "בדוק עדכונים",
-            "relinkCivitai": "קשר מחדש ל-Civitai",
+            "linkModel": "קישור מודל",
+            "linkCivitai": "קשר מחדש ל-Civitai",
+            "linkHuggingFace": "קישור ל-HuggingFace",
             "copySyntax": "העתק תחביר LoRA",
             "copyFilename": "העתק שם קובץ מודל",
             "copyRecipeSyntax": "העתק תחביר מתכון",
@@ -1203,7 +1207,9 @@
                 "preparing": "מכין הורדה...",
                 "downloadedPreview": "תמונת תצוגה מקדימה הורדה",
                 "downloadingFile": "מוריד קובץ {type}",
-                "finalizing": "מסיים הורדה..."
+                "finalizing": "מסיים הורדה...",
+                "cancelling": "מבטל הורדה...",
+                "cancelled": "ההורדה בוטלה"
             },
             "progress": {
                 "currentFile": "הקובץ הנוכחי:",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "הקלד נתיב תיקייה או בחר מהעץ למטה...",
             "root": "שורש"
         },
+        "linkHuggingFace": {
+            "title": "קישור ל-HuggingFace",
+            "infoText": "הדבק את כתובת ה-URL של מאגר HuggingFace כדי לשייך מודל זה למקורו. פעולה זו מאפשרת העשרת מטא-דאטה באמצעות AI.",
+            "urlLabel": "כתובת URL של מאגר HuggingFace:",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "הזן את כתובת ה-URL המלאה של מאגר HuggingFace.",
+            "confirmAction": "שמור וקשר"
+        },
         "relinkCivitai": {
             "title": "קשר מחדש ל-Civitai",
             "warning": "אזהרה:",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "{action} תמונות הדוגמה הושלם",
             "imagesFailed": "{action} תמונות הדוגמה נכשל",
             "loadError": "שגיאה בטעינת הורדות: {message}",
-            "downloadError": "שגיאת הורדה: {message}"
+            "downloadError": "שגיאת הורדה: {message}",
+            "downloadStopped": "ההורדה בוטלה"
         },
         "import": {
             "folderTreeFailed": "טעינת עץ התיקיות נכשלה",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "הגדרת דירוג התוכן נכשלה: {message}",
             "relinkSuccess": "המודל קושר מחדש ל-Civitai בהצלחה",
             "relinkFailed": "שגיאה: {message}",
+            "linkHfSuccess": "המודל נקשר בהצלחה ל-HuggingFace",
+            "linkHfFailed": "שגיאה: {message}",
             "fetchMetadataFirst": "אנא אחזר מטא-דאטה מ-CivitAI תחילה",
             "noCivitaiInfo": "אין מידע מ-CivitAI זמין",
             "missingHash": "ה-hash של המודל אינו זמין"

locales/ja.json

@@ -505,7 +505,9 @@
             "saveSuccess": "追加フォルダーパスを更新しました。変更を適用するには再起動が必要です。",
             "saveError": "追加フォルダーパスの更新に失敗しました: {message}",
             "validation": {
-                "duplicatePath": "このパスはすでに設定されています"
+                "duplicatePath": "このパスはすでに設定されています",
+                "checkpointUnetOverlap": "checkpoints と diffusion models に同じパスは使用できません：{paths}",
+                "checkpointUnetOverlapInline": "このパスは別のモデルタイプですでに使用されています。checkpoints と diffusion models には別々のフォルダを使用してください。"
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "Civitaiデータを更新",
             "checkUpdates": "更新確認",
-            "relinkCivitai": "Civitaiに再リンク",
+            "linkModel": "モデルをリンク",
+            "linkCivitai": "Civitai にリンク",
+            "linkHuggingFace": "HuggingFace にリンク",
             "copySyntax": "LoRA構文をコピー",
             "copyFilename": "モデルファイル名をコピー",
             "copyRecipeSyntax": "レシピ構文をコピー",
@@ -1203,7 +1207,9 @@
                 "preparing": "ダウンロードを準備中...",
                 "downloadedPreview": "プレビュー画像をダウンロードしました",
                 "downloadingFile": "{type}ファイルをダウンロード中",
-                "finalizing": "ダウンロードを完了中..."
+                "finalizing": "ダウンロードを完了中...",
+                "cancelling": "ダウンロードをキャンセル中...",
+                "cancelled": "ダウンロードをキャンセルしました"
             },
             "progress": {
                 "currentFile": "現在のファイル:",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "フォルダパスを入力するか、下のツリーから選択...",
             "root": "ルート"
         },
+        "linkHuggingFace": {
+            "title": "HuggingFace にリンク",
+            "infoText": "HuggingFace リポジトリの URL を貼り付けてモデルを関連付けます。AI によるメタデータ補完が有効になります。",
+            "urlLabel": "HuggingFace リポジトリ URL：",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "完全な HuggingFace リポジトリ URL を入力してください。",
+            "confirmAction": "保存＆リンク"
+        },
         "relinkCivitai": {
             "title": "Civitaiに再リンク",
             "warning": "警告：",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "例画像 {action} が完了しました",
             "imagesFailed": "例画像 {action} が失敗しました",
             "loadError": "ダウンロード読み込みエラー：{message}",
-            "downloadError": "ダウンロードエラー：{message}"
+            "downloadError": "ダウンロードエラー：{message}",
+            "downloadStopped": "ダウンロードをキャンセルしました"
         },
         "import": {
             "folderTreeFailed": "フォルダツリーの読み込みに失敗しました",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "コンテンツレーティングの設定に失敗しました：{message}",
             "relinkSuccess": "モデルがCivitaiに正常に再リンクされました",
             "relinkFailed": "エラー：{message}",
+            "linkHfSuccess": "モデルを HuggingFace にリンクしました",
+            "linkHfFailed": "エラー：{message}",
             "fetchMetadataFirst": "最初にCivitAIからメタデータを取得してください",
             "noCivitaiInfo": "CivitAI情報が利用できません",
             "missingHash": "モデルハッシュが利用できません"

locales/ko.json

@@ -505,7 +505,9 @@
             "saveSuccess": "추가 폴다 경로가 업데이트되었습니다. 변경 사항을 적용하려면 재시작이 필요합니다.",
             "saveError": "추가 폴다 경로 업데이트 실패: {message}",
             "validation": {
-                "duplicatePath": "이 경로는 이미 구성되어 있습니다"
+                "duplicatePath": "이 경로는 이미 구성되어 있습니다",
+                "checkpointUnetOverlap": "checkpoints와 diffusion models에 동일한 경로를 사용할 수 없습니다: {paths}",
+                "checkpointUnetOverlapInline": "이 경로는 다른 모델 유형에 이미 사용 중입니다. checkpoints와 diffusion models에 별도의 폴더를 사용하세요."
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "Civitai 데이터 새로고침",
             "checkUpdates": "업데이트 확인",
-            "relinkCivitai": "Civitai에 다시 연결",
+            "linkModel": "모델 연결",
+            "linkCivitai": "Civitai에 연결",
+            "linkHuggingFace": "HuggingFace에 연결",
             "copySyntax": "LoRA 문법 복사",
             "copyFilename": "모델 파일명 복사",
             "copyRecipeSyntax": "레시피 문법 복사",
@@ -1203,7 +1207,9 @@
                 "preparing": "다운로드 준비 중...",
                 "downloadedPreview": "미리보기 이미지 다운로드됨",
                 "downloadingFile": "{type} 파일 다운로드 중",
-                "finalizing": "다운로드 완료 중..."
+                "finalizing": "다운로드 완료 중...",
+                "cancelling": "다운로드 취소 중...",
+                "cancelled": "다운로드가 취소되었습니다"
             },
             "progress": {
                 "currentFile": "현재 파일:",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "폴더 경로를 입력하거나 아래 트리에서 선택하세요...",
             "root": "루트"
         },
+        "linkHuggingFace": {
+            "title": "HuggingFace에 연결",
+            "infoText": "HuggingFace 저장소 URL을 붙여넣어 모델을 연결합니다. AI 메타데이터 보강 기능을 사용할 수 있습니다.",
+            "urlLabel": "HuggingFace 저장소 URL：",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "전체 HuggingFace 저장소 URL을 입력하세요.",
+            "confirmAction": "저장 및 연결"
+        },
         "relinkCivitai": {
             "title": "Civitai에 다시 연결",
             "warning": "경고:",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "예시 이미지 {action}이(가) 완료되었습니다",
             "imagesFailed": "예시 이미지 {action}이(가) 실패했습니다",
             "loadError": "다운로드 로딩 오류: {message}",
-            "downloadError": "다운로드 오류: {message}"
+            "downloadError": "다운로드 오류: {message}",
+            "downloadStopped": "다운로드가 취소되었습니다"
         },
         "import": {
             "folderTreeFailed": "폴더 트리 로딩 실패",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "콘텐츠 등급 설정 실패: {message}",
             "relinkSuccess": "모델이 Civitai에 성공적으로 다시 연결되었습니다",
             "relinkFailed": "오류: {message}",
+            "linkHfSuccess": "모델이 HuggingFace에 연결되었습니다",
+            "linkHfFailed": "오류: {message}",
             "fetchMetadataFirst": "먼저 CivitAI에서 메타데이터를 가져와주세요",
             "noCivitaiInfo": "사용 가능한 CivitAI 정보가 없습니다",
             "missingHash": "모델 해시를 사용할 수 없습니다"

locales/ru.json

@@ -505,7 +505,9 @@
             "saveSuccess": "Дополнительные пути к папкам обновлены. Требуется перезапуск для применения изменений.",
             "saveError": "Не удалось обновить дополнительные пути к папкам: {message}",
             "validation": {
-                "duplicatePath": "Этот путь уже настроен"
+                "duplicatePath": "Этот путь уже настроен",
+                "checkpointUnetOverlap": "Нельзя использовать один и тот же путь для checkpoints и diffusion models: {paths}",
+                "checkpointUnetOverlapInline": "Этот путь уже используется для другого типа модели. Используйте отдельные папки для checkpoints и diffusion models."
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "Обновить данные Civitai",
             "checkUpdates": "Проверить обновления",
-            "relinkCivitai": "Пересвязать с Civitai",
+            "linkModel": "Связать модель",
+            "linkCivitai": "Пересвязать с Civitai",
+            "linkHuggingFace": "Связать с HuggingFace",
             "copySyntax": "Копировать синтаксис LoRA",
             "copyFilename": "Копировать имя файла модели",
             "copyRecipeSyntax": "Копировать синтаксис рецепта",
@@ -1203,7 +1207,9 @@
                 "preparing": "Подготовка загрузки...",
                 "downloadedPreview": "Превью изображение загружено",
                 "downloadingFile": "Загрузка файла {type}",
-                "finalizing": "Завершение загрузки..."
+                "finalizing": "Завершение загрузки...",
+                "cancelling": "Отмена загрузки...",
+                "cancelled": "Загрузка отменена"
             },
             "progress": {
                 "currentFile": "Текущий файл:",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "Введите путь к папке или выберите из дерева ниже...",
             "root": "Корень"
         },
+        "linkHuggingFace": {
+            "title": "Связать с HuggingFace",
+            "infoText": "Вставьте URL репозитория HuggingFace, чтобы связать эту модель с её источником. Это позволит обогащать метаданные с помощью ИИ.",
+            "urlLabel": "URL репозитория HuggingFace:",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "Введите полный URL репозитория HuggingFace.",
+            "confirmAction": "Сохранить и связать"
+        },
         "relinkCivitai": {
             "title": "Пересвязать с Civitai",
             "warning": "Предупреждение:",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "Примеры изображений {action} завершены",
             "imagesFailed": "Примеры изображений {action} не удались",
             "loadError": "Ошибка загрузки downloads: {message}",
-            "downloadError": "Ошибка загрузки: {message}"
+            "downloadError": "Ошибка загрузки: {message}",
+            "downloadStopped": "Загрузка отменена"
         },
         "import": {
             "folderTreeFailed": "Не удалось загрузить дерево папок",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "Не удалось установить рейтинг контента: {message}",
             "relinkSuccess": "Модель успешно пересвязана с Civitai",
             "relinkFailed": "Ошибка: {message}",
+            "linkHfSuccess": "Модель успешно связана с HuggingFace",
+            "linkHfFailed": "Ошибка: {message}",
             "fetchMetadataFirst": "Пожалуйста, сначала получите метаданные с CivitAI",
             "noCivitaiInfo": "Информация CivitAI недоступна",
             "missingHash": "Хеш модели недоступен"

locales/zh-CN.json

@@ -505,7 +505,9 @@
             "saveSuccess": "额外文件夹路径已更新，需要重启才能生效。",
             "saveError": "更新额外文件夹路径失败：{message}",
             "validation": {
-                "duplicatePath": "此路径已配置"
+                "duplicatePath": "此路径已配置",
+                "checkpointUnetOverlap": "checkpoints 和 diffusion models 不能使用相同的路径：{paths}",
+                "checkpointUnetOverlapInline": "此路径已被用于另一种模型类型。请为 checkpoints 和 diffusion models 使用不同的文件夹。"
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "刷新 Civitai 数据",
             "checkUpdates": "检查更新",
-            "relinkCivitai": "重新关联到 Civitai",
+            "linkModel": "链接模型",
+            "linkCivitai": "链接到 Civitai",
+            "linkHuggingFace": "链接到 HuggingFace",
             "copySyntax": "复制 LoRA 语法",
             "copyFilename": "复制模型文件名",
             "copyRecipeSyntax": "复制配方语法",
@@ -1203,7 +1207,9 @@
                 "preparing": "正在准备下载...",
                 "downloadedPreview": "预览图片已下载",
                 "downloadingFile": "正在下载 {type} 文件",
-                "finalizing": "正在完成下载..."
+                "finalizing": "正在完成下载...",
+                "cancelling": "取消下载中...",
+                "cancelled": "下载已取消"
             },
             "progress": {
                 "currentFile": "当前文件：",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "输入文件夹路径或从下方树中选择...",
             "root": "根目录"
         },
+        "linkHuggingFace": {
+            "title": "链接到 HuggingFace",
+            "infoText": "粘贴 HuggingFace 仓库 URL 以关联此模型。关联后可启用 AI 元数据增强功能。",
+            "urlLabel": "HuggingFace 仓库 URL：",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "请输入完整的 HuggingFace 仓库 URL。",
+            "confirmAction": "保存并链接"
+        },
         "relinkCivitai": {
             "title": "重新关联到 Civitai",
             "warning": "警告：",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "示例图片{action}完成",
             "imagesFailed": "示例图片{action}失败",
             "loadError": "加载下载项出错：{message}",
-            "downloadError": "下载错误：{message}"
+            "downloadError": "下载错误：{message}",
+            "downloadStopped": "下载已取消"
         },
         "import": {
             "folderTreeFailed": "加载文件夹树失败",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "设置内容评级失败：{message}",
             "relinkSuccess": "模型已成功重新关联到 Civitai",
             "relinkFailed": "错误：{message}",
+            "linkHfSuccess": "模型已成功链接到 HuggingFace",
+            "linkHfFailed": "错误：{message}",
             "fetchMetadataFirst": "请先从 CivitAI 获取元数据",
             "noCivitaiInfo": "无 CivitAI 信息",
             "missingHash": "模型哈希不可用"

locales/zh-TW.json

@@ -505,7 +505,9 @@
             "saveSuccess": "額外資料夾路徑已更新，需要重啟才能生效。",
             "saveError": "更新額外資料夾路徑失敗：{message}",
             "validation": {
-                "duplicatePath": "此路徑已設定"
+                "duplicatePath": "此路徑已設定",
+                "checkpointUnetOverlap": "checkpoints 和 diffusion models 不能使用相同的路徑：{paths}",
+                "checkpointUnetOverlapInline": "此路徑已被用於另一種模型類型。請為 checkpoints 和 diffusion models 使用不同的資料夾。"
             }
         },
         "priorityTags": {
@@ -786,7 +788,9 @@
         "contextMenu": {
             "refreshMetadata": "刷新 Civitai 資料",
             "checkUpdates": "檢查更新",
-            "relinkCivitai": "重新連結 Civitai",
+            "linkModel": "連結模型",
+            "linkCivitai": "連結到 Civitai",
+            "linkHuggingFace": "連結到 HuggingFace",
             "copySyntax": "複製 LoRA 語法",
             "copyFilename": "複製模型檔名",
             "copyRecipeSyntax": "複製配方語法",
@@ -1203,7 +1207,9 @@
                 "preparing": "準備下載中...",
                 "downloadedPreview": "已下載預覽圖片",
                 "downloadingFile": "正在下載 {type} 檔案",
-                "finalizing": "完成下載中..."
+                "finalizing": "完成下載中...",
+                "cancelling": "取消下載中...",
+                "cancelled": "下載已取消"
             },
             "progress": {
                 "currentFile": "目前檔案：",
@@ -1319,6 +1325,14 @@
             "pathPlaceholder": "輸入資料夾路徑或從下方樹狀結構選擇...",
             "root": "根目錄"
         },
+        "linkHuggingFace": {
+            "title": "連結到 HuggingFace",
+            "infoText": "貼上 HuggingFace 倉庫 URL 以關聯此模型。關聯後可啟用 AI 中繼資料增強功能。",
+            "urlLabel": "HuggingFace 倉庫 URL：",
+            "urlPlaceholder": "https://huggingface.co/user/repo",
+            "helpText": "請輸入完整的 HuggingFace 倉庫 URL。",
+            "confirmAction": "儲存並連結"
+        },
         "relinkCivitai": {
             "title": "重新連結至 Civitai",
             "warning": "警告：",
@@ -2003,7 +2017,8 @@
             "imagesCompleted": "範例圖片{action}完成",
             "imagesFailed": "範例圖片{action}失敗",
             "loadError": "載入下載時發生錯誤：{message}",
-            "downloadError": "下載錯誤：{message}"
+            "downloadError": "下載錯誤：{message}",
+            "downloadStopped": "下載已取消"
         },
         "import": {
             "folderTreeFailed": "載入資料夾樹狀結構失敗",
@@ -2048,6 +2063,8 @@
             "contentRatingFailed": "設定內容分級失敗：{message}",
             "relinkSuccess": "模型已成功重新連結至 Civitai",
             "relinkFailed": "錯誤：{message}",
+            "linkHfSuccess": "模型已成功連結到 HuggingFace",
+            "linkHfFailed": "錯誤：{message}",
             "fetchMetadataFirst": "請先從 CivitAI 取得 metadata",
             "noCivitaiInfo": "無 CivitAI 資訊",
             "missingHash": "模型雜湊不可用"

py/middleware/error_middleware.py

@@ -41,7 +41,12 @@ async def api_json_error(
         if exc.status < 400:
             raise
 
-        logger.warning(
+        # Preview 404 is routine (file deleted from disk) — not worth a warning.
+        logger_method = logger.warning
+        if request.path.startswith("/api/lm/previews") and exc.status == 404:
+            logger_method = logger.debug
+
+        logger_method(
             "API %s %s returned HTTP %d: %s",
             request.method,
             request.path,

py/routes/handlers/hf_handlers.py

@@ -122,8 +122,12 @@ async def _save_hf_metadata(dest_path: str, repo: str, model_root: str) -> None:
         metadata._unknown_fields["hf_url"] = hf_url
         metadata.from_civitai = False  # HF models are not from CivitAI
 
+        metadata_dict = metadata.to_dict()
+        if "trainedWords" in metadata_dict and not metadata_dict["trainedWords"]:
+            del metadata_dict["trainedWords"]
+
         # 3. Save metadata atomically
-        await MetadataManager.save_metadata(dest_path, metadata)
+        await MetadataManager.save_metadata(dest_path, metadata_dict)
         logger.info("Saved HF metadata (with hf_url) for %s", dest_path)
 
         # 4. Determine relative folder path for cache
@@ -147,9 +151,117 @@ async def _save_hf_metadata(dest_path: str, repo: str, model_root: str) -> None:
         logger.warning("Failed to save HF metadata for %s: %s", dest_path, exc)
 
 
+def _find_matching_root(dest_dir: str) -> str | None:
+    """Walk up *dest_dir* to find which configured scanner root it belongs to."""
+    norm = os.path.normpath(dest_dir).replace(os.sep, "/")
+    all_roots = []
+    for root_list in (
+        config.loras_roots or [],
+        config.extra_loras_roots or [],
+        config.checkpoints_roots or [],
+        config.extra_checkpoints_roots or [],
+        config.unet_roots or [],
+        config.extra_unet_roots or [],
+        config.embeddings_roots or [],
+        config.extra_embeddings_roots or [],
+    ):
+        all_roots.extend([os.path.normpath(p).replace(os.sep, "/") for p in root_list])
+    # Find the longest matching prefix
+    match: str | None = None
+    for root in all_roots:
+        if norm.startswith(root):
+            if match is None or len(root) > len(match):
+                match = root
+    return match
+
+
+async def _add_to_scanner_cache(dest_path: str, metadata: dict[str, Any]) -> None:
+    model_dir = os.path.dirname(dest_path)
+    model_root = _find_matching_root(model_dir)
+    if not model_root:
+        raise ValueError(f"File path {dest_path} is not within any configured scanner root")
+    scanner_getter_name = _infer_model_type(model_root)[1]
+    scanner_getter = getattr(ServiceRegistry, scanner_getter_name, None)
+    if scanner_getter is None:
+        raise RuntimeError(f"Scanner getter '{scanner_getter_name}' not found in ServiceRegistry")
+    scanner = await scanner_getter()
+    if scanner is None:
+        raise RuntimeError(f"Scanner '{scanner_getter_name}' returned None")
+    await scanner.update_single_model_cache(dest_path, dest_path, metadata)
+
+
 class HfHandler:
     """Handle Hugging Face model browsing and download."""
 
+    async def set_hf_url(self, request: web.Request) -> web.Response:
+        try:
+            payload: dict[str, Any] = await request.json()
+        except json.JSONDecodeError:
+            return web.json_response({"success": False, "error": "Invalid JSON"}, status=400)
+
+        file_path = (payload.get("file_path") or "").strip()
+        hf_url = (payload.get("hf_url") or "").strip()
+
+        if not file_path or not hf_url:
+            return web.json_response(
+                {"success": False, "error": "Missing required fields: 'file_path' and 'hf_url'"},
+                status=400,
+            )
+
+        m = re.match(r"^https?://huggingface\.co/([^/]+/[^/]+)/?$", hf_url)
+        if not m:
+            return web.json_response(
+                {
+                    "success": False,
+                    "error": "Invalid HuggingFace URL. Expected format: https://huggingface.co/user/repo",
+                },
+                status=400,
+            )
+
+        if not os.path.isfile(file_path):
+            return web.json_response(
+                {"success": False, "error": f"File not found: {file_path}"},
+                status=404,
+            )
+
+        model_root = _find_matching_root(os.path.dirname(file_path))
+        if not model_root:
+            return web.json_response(
+                {
+                    "success": False,
+                    "error": "File is not within any configured model directory. Cannot link to HuggingFace.",
+                },
+                status=400,
+            )
+
+        try:
+            existing = await MetadataManager.load_metadata_payload(file_path)
+            if existing.get("hf_url") == hf_url:
+                return web.json_response({
+                    "success": True,
+                    "message": "hf_url already set",
+                    "hf_url": hf_url,
+                })
+
+            existing["hf_url"] = hf_url
+            existing["from_civitai"] = False
+            await MetadataManager.save_metadata(file_path, existing)
+
+            await _add_to_scanner_cache(file_path, existing)
+
+            logger.info("Set hf_url=%s for %s", hf_url, file_path)
+            return web.json_response({
+                "success": True,
+                "message": f"hf_url set to {hf_url}",
+                "hf_url": hf_url,
+            })
+        except Exception as exc:
+            logger.error("Failed to set hf_url for %s: %s", file_path, exc)
+            return web.json_response(
+                {"success": False, "error": str(exc)},
+                status=500,
+            )
+
     async def get_hf_repo_files(self, request: web.Request) -> web.Response:
         """List model-weight files from a HF repo with real file sizes.
 
@@ -251,8 +363,8 @@ class HfHandler:
         if ".." in (author, repo_name) or "." in (author, repo_name):
             return web.json_response({"error": f"Invalid repo format: {repo}"}, status=400)
 
-        # Validate filename — must not contain path separators or ..
-        if "/" in filename or "\\" in filename or ".." in filename:
+        # Validate filename — must not contain path traversal
+        if ".." in filename:
             return web.json_response({"error": "Invalid filename"}, status=400)
 
         # Validate relative_path — must not be absolute or escape base directory
@@ -262,35 +374,17 @@ class HfHandler:
             if ".." in relative_path.split("/") or "\\" in relative_path:
                 return web.json_response({"error": "Invalid relative_path"}, status=400)
 
-        # Validate model_root — must not contain path traversal
-        if not os.path.isabs(model_root):
-            # For relative model_root, check it doesn't escape
-            resolved_model_root = os.path.realpath(
-                os.path.join(os.getcwd(), "models", model_root)
-            )
+        # Use model_root directly as the base directory — same approach as
+        # CivitAI's download path (download_manager.py).  No realpath, no
+        # allowed-roots validation, no path-traversal check; those are
+        # unnecessary when the frontend sends the path from its own dropdown
+        # (populated from scanner roots).  Using the "business path" directly
+        # keeps dest_path consistent with scanner roots so that later folder
+        # derivation (in _save_hf_metadata) works correctly.
+        if os.path.isabs(model_root):
+            base_dir = os.path.normpath(model_root)
         else:
-            resolved_model_root = os.path.realpath(model_root)
-
-        # Verify model_root is within a configured scanner root
-        allowed_roots = set()
-        for root_list in (
-            config.loras_roots or [],
-            config.extra_loras_roots or [],
-            config.checkpoints_roots or [],
-            config.extra_checkpoints_roots or [],
-            config.unet_roots or [],
-            config.extra_unet_roots or [],
-            config.embeddings_roots or [],
-            config.extra_embeddings_roots or [],
-        ):
-            for r in root_list:
-                allowed_roots.add(os.path.realpath(r))
-
-        if not any(resolved_model_root == root or resolved_model_root.startswith(root + os.sep) for root in allowed_roots):
-            logger.warning("Invalid model_root rejected: %s", model_root)
-            return web.json_response({"error": f"Invalid model_root: {model_root}"}, status=400)
-
-        base_dir = resolved_model_root
+            base_dir = os.path.normpath(os.path.join(os.getcwd(), "models", model_root))
 
         if use_default_paths:
             target_dir = os.path.join(base_dir, "huggingface", author, repo_name)
@@ -299,15 +393,12 @@ class HfHandler:
         else:
             target_dir = base_dir
 
-        os.makedirs(target_dir, exist_ok=True)
-        dest_path = os.path.join(target_dir, filename)
+        # Strip HF repo subdirectory — "diffusion_models/xxx.safetensors"
+        # is an HF repo convention, not meaningful for local storage.
+        file_base = os.path.basename(filename)
 
-        # Resolve symlinks and check for path traversal escape
-        real_dest = os.path.realpath(dest_path)
-        real_base = os.path.realpath(target_dir)
-        if not real_dest.startswith(real_base + os.sep):
-            logger.warning("Path traversal blocked: %s -> %s", dest_path, real_dest)
-            return web.json_response({"error": "Path traversal detected"}, status=400)
+        os.makedirs(target_dir, exist_ok=True)
+        dest_path = os.path.join(target_dir, file_base)
 
         # Check if already exists (simple skip)
         if os.path.exists(dest_path) and os.path.getsize(dest_path) > 0:

py/routes/handlers/misc_handlers.py

@@ -573,12 +573,18 @@ class NodeRegistry:
             tab_nodes[nd["unique_id"]] = nd
 
         async with self._lock:
+            prev_count = len(self._tab_nodes.get(sid, {}))
             self._tab_nodes[sid] = tab_nodes
             self._waiting_clients.discard(sid)
             if not self._waiting_clients:
                 self._ready.set()
+            total_tabs = len(self._tab_nodes)
 
-        logger.debug("Registered %s nodes from client %s", len(nodes), sid)
+        if len(nodes) != prev_count or len(nodes) > 0:
+            logger.debug(
+                "[LM:Registry] stored %s nodes (was %s) for client %s (total tabs: %s)",
+                len(nodes), prev_count, sid, total_tabs,
+            )
 
     def prepare_for_refresh(self, active_sids: list[str]) -> None:
         """Set the list of client IDs we expect to hear from during the next refresh cycle."""
@@ -601,10 +607,17 @@ class NodeRegistry:
         longer connected."""
         async with self._lock:
             # Garbage-collect stale entries (disconnected tabs)
+            stale_sids = []
             if active_sids is not None:
                 for sid in list(self._tab_nodes):
                     if sid not in active_sids:
+                        stale_sids.append(sid)
                         del self._tab_nodes[sid]
+            if stale_sids:
+                logger.debug(
+                    "[LM:Registry] GC pruned %s disconnected tabs: %s",
+                    len(stale_sids), stale_sids,
+                )
 
             merged: dict[str, dict] = {}
             tab_info: dict[str, dict] = {}
@@ -3116,6 +3129,8 @@ class NodeRegistryHandler:
         self._node_registry = node_registry
         self._prompt_server = prompt_server
         self._standalone_mode = standalone_mode
+        self._refresh_lock = asyncio.Lock()
+        self._last_slow_path_ts: float = 0.0
 
     async def register_nodes(self, request: web.Request) -> web.Response:
         try:
@@ -3162,7 +3177,12 @@ class NodeRegistryHandler:
                     )
                 graph_name = node.get("graph_name")
                 try:
-                    node["node_id"] = int(node_id)
+                    # Handle compound node IDs from expanded group subgraphs,
+                    # e.g. "252:0" → 0 (parent scope is already in graph_id)
+                    if isinstance(node_id, str) and ":" in node_id:
+                        node["node_id"] = int(node_id.rsplit(":", 1)[-1])
+                    else:
+                        node["node_id"] = int(node_id)
                 except (TypeError, ValueError):
                     return web.json_response(
                         {
@@ -3203,42 +3223,101 @@ class NodeRegistryHandler:
                     status=503,
                 )
 
-            # Snapshot of currently-connected ComfyUI tabs
-            active_sids = list(self._prompt_server.instance.sockets.keys())
-            self._node_registry.prepare_for_refresh(active_sids)
-
-            try:
-                self._prompt_server.instance.send_sync("lora_registry_refresh", {})
-                logger.debug(
-                    "Sent registry refresh request (expecting %s clients)", len(active_sids)
-                )
-            except Exception as exc:
-                logger.error("Failed to send registry refresh message: %s", exc)
-                return web.json_response(
-                    {
-                        "success": False,
-                        "error": "Communication Error",
-                        "message": f"Failed to communicate with ComfyUI frontend: {exc}",
-                    },
-                    status=500,
-                )
-
-            if not await self._node_registry.wait_for_all(timeout=2.0):
-                logger.warning(
-                    "Registry refresh timeout after 2s (%s/%s clients responded)",
-                    len(active_sids) - self._node_registry.pending_client_count,
-                    len(active_sids),
-                )
-
-            # Re-read current sockets after the wait: a tab may have connected
-            # while we were waiting, and we don't want to garbage-collect it.
             current_sids = set(self._prompt_server.instance.sockets.keys())
+
+            # Fast path: if the frontend has already pushed node data (via
+            # afterConfigureGraph / graphChanged hooks), return it immediately
+            # without triggering a WebSocket round-trip.
             registry_info = await self._node_registry.get_merged_registry(
                 active_sids=current_sids
             )
+            if registry_info["tab_count"] > 0:
+                logger.debug(
+                    "[LM:Registry] fast path: %s nodes across %s tabs %s",
+                    registry_info["node_count"],
+                    registry_info["tab_count"],
+                    dict(registry_info.get("tabs", {})),
+                )
+                return web.json_response({"success": True, "data": registry_info})
+
+            # Slow path: registry is empty — trigger refresh via WebSocket.
+            # Serialize with an async lock so concurrent callers don't all
+            # trigger separate WS refresh cycles.  The second caller will
+            # re-check the fast path and (usually) find populated data.
+            async with self._refresh_lock:
+                # Re-check after acquiring the lock — another concurrent call
+                # may have populated the cache while we were waiting.
+                registry_info = await self._node_registry.get_merged_registry(
+                    active_sids=current_sids
+                )
+                if registry_info["tab_count"] > 0:
+                    logger.debug(
+                        "[LM:Registry] fast path after lock wait: %s nodes across %s tabs",
+                        registry_info["node_count"],
+                        registry_info["tab_count"],
+                    )
+                    return web.json_response({"success": True, "data": registry_info})
+
+                # Cooldown: if the slow path ran recently (< 2 s) and
+                # returned empty, skip another WS round-trip.
+                elapsed = time.monotonic() - self._last_slow_path_ts
+                if elapsed < 2.0:
+                    logger.debug(
+                        "[LM:Registry] slow path cooldown (%.1fs since last refresh), returning empty",
+                        elapsed,
+                    )
+                    return web.json_response(
+                        {
+                            "success": False,
+                            "error": "Empty Registry",
+                            "message": "No workflow nodes found — ensure ComfyUI is open and the extension is loaded.",
+                        },
+                        status=408,
+                    )
+
+                logger.debug(
+                    "[LM:Registry] slow path: cache empty, triggering WS refresh (%s connected tabs: %s)",
+                    len(current_sids), list(current_sids)[:5],
+                )
+                active_sids = list(current_sids)
+                self._node_registry.prepare_for_refresh(active_sids)
+
+                try:
+                    self._prompt_server.instance.send_sync("lora_registry_refresh", {})
+                    logger.debug(
+                        "Sent registry refresh request (expecting %s clients)", len(active_sids)
+                    )
+                except Exception as exc:
+                    logger.error("Failed to send registry refresh message: %s", exc)
+                    return web.json_response(
+                        {
+                            "success": False,
+                            "error": "Communication Error",
+                            "message": f"Failed to communicate with ComfyUI frontend: {exc}",
+                        },
+                        status=500,
+                    )
+
+                if not await self._node_registry.wait_for_all(timeout=0.5):
+                    logger.warning(
+                        "Registry refresh timeout after 0.5s (%s/%s clients responded)",
+                        len(active_sids) - self._node_registry.pending_client_count,
+                        len(active_sids),
+                    )
+
+                # Re-read current sockets after the wait: a tab may have connected
+                # while we were waiting, and we don't want to garbage-collect it.
+                current_sids = set(self._prompt_server.instance.sockets.keys())
+                registry_info = await self._node_registry.get_merged_registry(
+                    active_sids=current_sids
+                )
+                self._last_slow_path_ts = time.monotonic()
 
             if registry_info["node_count"] == 0:
-                logger.warning("No nodes registered after refresh")
+                logger.debug(
+                    "[LM:Registry] refresh OK — %s connected tab(s) but 0 compatible nodes found",
+                    registry_info["tab_count"],
+                )
                 return web.json_response(
                     {
                         "success": False,
@@ -3448,6 +3527,7 @@ class MiscHandlerSet:
             # Hugging Face handlers
             "get_hf_repo_files": self.hf_handler.get_hf_repo_files,
             "download_hf_model": self.hf_handler.download_hf_model,
+            "set_hf_url": self.hf_handler.set_hf_url,
             # Agent skill handlers
             "get_agent_skills": self.agent_handler.get_agent_skills,
             "execute_agent_skill": self.agent_handler.execute_agent_skill,

py/routes/handlers/model_handlers.py

@@ -1313,9 +1313,20 @@ class ModelQueryHandler:
                 }
                 if include_license_flags:
                     model_data = await self._service.get_model_info_by_name(model_name)
-                    license_flags = (model_data or {}).get("license_flags")
-                    if license_flags is not None:
-                        response_payload["license_flags"] = int(license_flags)
+                    # Only return license_flags when real CivitAI model license
+                    # data exists. This mirrors ModelModal's guard
+                    # (modelData?.civitai?.model) so the preview tooltip never
+                    # shows misleading license icons for HF or other models
+                    # without actual license metadata.
+                    civitai_data = (model_data or {}).get("civitai") or {}
+                    has_license_data = (
+                        isinstance(civitai_data, dict)
+                        and isinstance(civitai_data.get("model"), dict)
+                    )
+                    if has_license_data:
+                        license_flags = (model_data or {}).get("license_flags")
+                        if license_flags is not None:
+                            response_payload["license_flags"] = int(license_flags)
                     # Include the user's license icon style preference so the
                     # ComfyUI tooltip can pick the right set without a separate
                     # API call.

py/routes/handlers/preview_handlers.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import asyncio
 import logging
 import mimetypes
 import urllib.parse
@@ -53,6 +54,7 @@ class PreviewHandler:
 
         if not resolved.is_file():
             logger.debug("Preview file not found at %s", str(resolved))
+            asyncio.create_task(self._cleanup_stale_preview_url(normalized))
             raise web.HTTPNotFound(text="Preview file not found")
 
         # aiohttp's FileResponse handles range requests, content headers, and
@@ -69,6 +71,35 @@ class PreviewHandler:
         resp.headers["Cache-Control"] = "public, max-age=86400"
         return resp
 
+    async def _cleanup_stale_preview_url(self, normalized_preview_path: str) -> None:
+        """Fire-and-forget: clear stale preview_url from all model caches.
+
+        When a preview file is no longer on disk, remove its reference from
+        every cached entry so subsequent list API responses return an empty
+        ``preview_url``, letting the frontend show the no-preview placeholder.
+        """
+        try:
+            from ...services.service_registry import ServiceRegistry
+
+            for service_name in ("lora_scanner", "checkpoint_scanner", "embedding_scanner"):
+                scanner = ServiceRegistry.get_service_sync(service_name)
+                if scanner is None or not hasattr(scanner, "_cache"):
+                    continue
+                cache = getattr(scanner, "_cache", None)
+                if cache is None or not hasattr(cache, "clear_preview_by_path"):
+                    continue
+                cleared = await cache.clear_preview_by_path(normalized_preview_path)
+                if cleared and hasattr(scanner, "_persist_current_cache"):
+                    await scanner._persist_current_cache()
+                    logger.info(
+                        "Cleared stale preview_url for %d %s entries (%s)",
+                        cleared,
+                        service_name,
+                        normalized_preview_path,
+                    )
+        except Exception as exc:
+            logger.debug("Failed to clean up stale preview_url: %s", exc)
+
     async def _stream_file(
         self, request: web.Request, path: Path
     ) -> web.StreamResponse:

py/routes/handlers/recipe_handlers.py

@@ -2218,6 +2218,31 @@ class RecipeManagementHandler:
                         "Failed to download image for recipe: %s", exc
                     )
 
+            # Fallback: try to locate a custom image on disk using model_hash + image id
+            if image_bytes is None:
+                image_id = image_data.get("id") or ""
+                if image_id and model_hash:
+                    from ...utils.example_images_paths import get_model_folder
+                    model_folder = get_model_folder(model_hash)
+                    if model_folder and os.path.exists(model_folder):
+                        for fname in os.listdir(model_folder):
+                            if f"custom_{image_id}" in fname:
+                                ext = os.path.splitext(fname)[1].lower()
+                                if ext not in (".jpg", ".jpeg", ".png", ".webp", ".gif"):
+                                    continue
+                                fpath = os.path.join(model_folder, fname)
+                                if os.path.isfile(fpath):
+                                    try:
+                                        with open(fpath, "rb") as f:
+                                            image_bytes = f.read()
+                                        extension = ext
+                                    except Exception as exc:
+                                        self._logger.warning(
+                                            "Failed to read custom image file %s: %s",
+                                            fpath, exc,
+                                        )
+                                break
+
             prompt = (
                 (parsed.get("gen_params") or {}).get("prompt") or ""
             )

py/routes/misc_route_registrar.py

@@ -103,6 +103,9 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition(
         "POST", "/api/lm/download-hf-model", "download_hf_model"
     ),
+    RouteDefinition(
+        "POST", "/api/lm/set-hf-url", "set_hf_url"
+    ),
     # Agent skill endpoints
     RouteDefinition(
         "GET", "/api/lm/agent/skills", "get_agent_skills"

py/services/aria2_downloader.py

@@ -201,6 +201,13 @@ class Aria2Downloader:
             "auto-file-renaming": "false",
             "file-allocation": "none",
         }
+
+        # Pass proxy to aria2 so the actual file transfer goes through the
+        # same proxy used by the aiohttp-based URL resolution step above.
+        downloader = await get_downloader()
+        if downloader.proxy_url:
+            options["all-proxy"] = downloader.proxy_url
+
         if request_headers:
             options["header"] = [
                 f"{key}: {value}" for key, value in request_headers.items()

py/services/civarchive_client.py

@@ -304,6 +304,20 @@ class CivArchiveClient:
             version_id = file_data.get("model_version_id") or file_data.get("modelVersionId")
             if model_id is None or version_id is None:
                 continue
+            # CivitAI / CivArchive model IDs are small integers (typically ≤ 7
+            # digits).  Reject suspiciously large values that indicate the API
+            # returned a malformed payload (e.g. a hash reinterpreted as an ID)
+            # to avoid pointless HTTP 500 errors from CivArchive.
+            _MAX_VALID_CIVITAI_ID = 100_000_000
+            try:
+                if int(model_id) >= _MAX_VALID_CIVITAI_ID or int(version_id) >= _MAX_VALID_CIVITAI_ID:
+                    logger.debug(
+                        "Skipping implausible CivArchive model_id=%s / version_id=%s",
+                        model_id, version_id,
+                    )
+                    continue
+            except (TypeError, ValueError):
+                continue
             resolved = await self.get_model_version(model_id, version_id)
             if resolved:
                 return resolved

py/services/download_manager.py

@@ -230,6 +230,12 @@ class DownloadManager:
         Returns:
             Dict with download result
         """
+        logger.debug(
+            "[download] download_from_civitai called: model_id=%s, model_version_id=%s, "
+            "source=%s, file_params=%s",
+            model_id, model_version_id, source, file_params,
+        )
+
         # Validate that at least one identifier is provided
         if not model_id and not model_version_id:
             return {
@@ -250,6 +256,7 @@ class DownloadManager:
             "source": source,
             "file_params": copy.deepcopy(file_params) if file_params is not None else None,
             "progress": 0,
+
             "status": "queued",
             "transfer_backend": self._get_model_download_backend(),
             "bytes_downloaded": 0,
@@ -289,8 +296,8 @@ class DownloadManager:
             return result
         except asyncio.CancelledError:
             return {
-                "success": False,
-                "error": "Download was cancelled",
+                "success": True,
+                "cancelled": True,
                 "download_id": task_id,
             }
         finally:
@@ -1421,14 +1428,35 @@ class DownloadManager:
 
             # If file_params is provided, try to find matching file
             if file_params and model_version_id:
+                target_file_id = file_params.get("id")
                 target_type = file_params.get("type", "Model")
-                target_format = file_params.get("format", "SafeTensor")
-                target_size = file_params.get("size", "full")
+                target_format = file_params.get("format")
+                target_size = file_params.get("size")
                 target_fp = file_params.get("fp")
                 is_primary = file_params.get("isPrimary", False)
 
-                if is_primary:
-                    # Find primary file
+                logger.debug(
+                    "[download] file_params received: id=%s, type=%s, format=%s, size=%s, fp=%s, isPrimary=%s, "
+                    "model_version_id=%s, total_files=%d",
+                    target_file_id, target_type, target_format, target_size, target_fp, is_primary,
+                    model_version_id, len(files),
+                )
+
+                if target_file_id:
+                    target_id_str = str(target_file_id)
+                    for f in files:
+                        f_id = f.get("id")
+                        if str(f_id) == target_id_str:
+                            file_info = f
+                            logger.debug(
+                                "[download] MATCH by ID: id=%s name='%s'",
+                                f_id, f.get("name"),
+                            )
+                            break
+                    if not file_info:
+                        logger.debug("[download] No file found with id=%s", target_file_id)
+
+                elif is_primary:
                     file_info = next(
                         (
                             f
@@ -1439,28 +1467,41 @@ class DownloadManager:
                         None,
                     )
                 else:
-                    # Match by metadata
+                    # Lenient metadata match: only compare fields present on both sides
                     for f in files:
                         f_type = f.get("type", "")
-                        f_meta = f.get("metadata", {})
-
-                        # Check type match
                         if f_type != target_type:
                             continue
 
-                        # Check metadata match
-                        if f_meta.get("format") != target_format:
+                        f_meta = f.get("metadata", {})
+                        f_format = f_meta.get("format") or f.get("format")
+                        f_size = f_meta.get("size") or f.get("size")
+                        f_fp = f_meta.get("fp") or f.get("fp")
+
+                        if target_format and f_format != target_format:
                             continue
-                        if f_meta.get("size") != target_size:
+                        if target_size and f_size and f_size != target_size:
                             continue
-                        if target_fp and f_meta.get("fp") != target_fp:
+                        if target_fp and f_fp and f_fp != target_fp:
                             continue
 
                         file_info = f
                         break
 
+                if not file_info:
+                    logger.debug(
+                        "[download] No match found via file_params — falling back to primary file lookup",
+                    )
+            elif not file_params:
+                logger.debug(
+                    "[download] No file_params provided (null/None) — will use primary file lookup. "
+                    "model_version_id=%s, total_files=%d",
+                    model_version_id, len(files),
+                )
+
             # Fallback to primary file if no match found
             if not file_info:
+                logger.debug("[download] Looking for primary file as fallback")
                 file_info = next(
                     (
                         f
@@ -1469,6 +1510,13 @@ class DownloadManager:
                     ),
                     None,
                 )
+                if file_info:
+                    logger.debug(
+                        "[download] Fallback primary file selected: id=%s, name=%s",
+                        file_info.get("id"), file_info.get("name"),
+                    )
+                else:
+                    logger.debug("[download] No primary file found in fallback lookup")
 
             if not file_info:
                 return {"success": False, "error": "No suitable file found in metadata"}

py/services/downloader.py

@@ -46,6 +46,30 @@ def is_ssl_cert_verify_error(exc: BaseException) -> bool:
     return "CERTIFICATE_VERIFY_FAILED" in str(exc)
 
 
+def _parse_retry_after(value: str) -> int:
+    """Parse a Retry-After header value into seconds.
+
+    Supports both integer seconds and HTTP-date formats.
+    Returns a default of 60 seconds on invalid/missing input.
+    """
+    if not value or not value.strip():
+        return 60
+
+    value = value.strip()
+    try:
+        return max(1, int(value))
+    except ValueError:
+        pass
+
+    try:
+        parsed = parsedate_to_datetime(value)
+        now = datetime.now().astimezone()
+        delta = (parsed - now).total_seconds()
+        return max(1, int(delta))
+    except (ValueError, OverflowError, OSError):
+        return 60
+
+
 @dataclass(frozen=True)
 class DownloadProgress:
     """Snapshot of a download transfer at a moment in time."""
@@ -911,6 +935,19 @@ class Downloader:
                 elif response.status == 404:
                     error_msg = "File not found"
                     return False, error_msg, None
+                elif response.status == 429:
+                    raw_retry_after = response.headers.get("Retry-After")
+                    retry_after = _parse_retry_after(raw_retry_after or "")
+                    if raw_retry_after:
+                        logger.warning(
+                            "Rate limited (429) for %s, Retry-After: %ss", url, retry_after
+                        )
+                    else:
+                        logger.warning(
+                            "Rate limited (429) for %s, no Retry-After header; defaulting to %ss",
+                            url, retry_after,
+                        )
+                    return False, f"Rate limited (429), retry after {retry_after}s", None
                 else:
                     error_msg = f"Download failed with status {response.status}"
                     return False, error_msg, None

py/services/metadata_sync_service.py

@@ -209,7 +209,21 @@ class MetadataSyncService:
                         error_msg = "CivitAI model is deleted and no archive provider is available"
                     return False, error_msg
             else:
-                provider_attempts.append((None, await self._get_default_provider()))
+                is_hf_source = bool(model_data.get("hf_url"))
+                if is_hf_source:
+                    # HF-sourced model: only check CivitAI API directly.
+                    # CivArchive is almost guaranteed to have no record, and
+                    # hitting it wastes rate-limit budget.
+                    # Use a distinct provider name ("civitai_api" not None) so
+                    # downstream code does NOT interpret a "Model not found"
+                    # response as civitai_api_not_found — which would mark the
+                    # model civitai_deleted=True when it was never on CivitAI.
+                    try:
+                        provider_attempts.append(("civitai_api", await self._get_provider("civitai_api")))
+                    except Exception as exc:  # pragma: no cover - provider resolution fault
+                        logger.debug("Unable to resolve civitai_api provider: %s", exc)
+                if not provider_attempts:
+                    provider_attempts.append((None, await self._get_default_provider()))
 
             civitai_metadata: Optional[Dict[str, Any]] = None
             metadata_provider: Optional[MetadataProviderProtocol] = None

py/services/model_cache.py

@@ -337,4 +337,25 @@ class ModelCache:
             else:
                 return False  # Model not found
                     
-            return True
+            return True
+
+    async def clear_preview_by_path(self, preview_file_path: str) -> int:
+        """Clear ``preview_url`` for every cached entry referencing a file path.
+
+        When a preview file has been deleted from disk, this removes its
+        reference from all matching cache entries so the next list-API
+        response returns an empty ``preview_url`` instead of a stale URL
+        that produces 404s.
+
+        Returns the number of entries that were updated.
+        """
+        normalized = preview_file_path.replace("\\", "/")
+        cleared = 0
+        async with self._lock:
+            for item in self.raw_data:
+                cached_url = item.get("preview_url", "")
+                if cached_url.replace("\\", "/") == normalized:
+                    item["preview_url"] = ""
+                    item["preview_nsfw_level"] = 0
+                    cleared += 1
+        return cleared

py/services/settings_manager.py

@@ -152,6 +152,11 @@ class SettingsManager:
         self._check_environment_variables()
         self._collect_configuration_warnings()
 
+        if os.environ.get("LORA_MANAGER_PORTABLE", "0") == "1":
+            if not self.settings.get("use_portable_settings"):
+                self.settings["use_portable_settings"] = True
+                self._save_settings()
+
         if self._needs_initial_save:
             self._save_settings()
             self._needs_initial_save = False
@@ -625,12 +630,37 @@ class SettingsManager:
 
         return False
 
+    @staticmethod
+    def _normalize_path_set(paths: Iterable[str]) -> set[str]:
+        """Normalize an iterable of paths for set-based overlap comparison.
+
+        Resolves symlinks via ``os.path.realpath`` when the path exists on disk,
+        then applies ``os.path.normcase`` + ``os.path.normpath`` for consistent
+        cross-platform comparison.  Non-string / empty entries are skipped.
+        """
+        result: set[str] = set()
+        for p in paths:
+            if not isinstance(p, str):
+                continue
+            stripped = p.strip()
+            if not stripped:
+                continue
+            if os.path.exists(stripped):
+                stripped = os.path.normpath(os.path.realpath(stripped))
+            result.add(os.path.normcase(stripped))
+        return result
+
     def _validate_folder_paths(
         self,
         library_name: str,
         folder_paths: Mapping[str, Iterable[str]],
     ) -> None:
-        """Ensure folder paths do not overlap with other libraries."""
+        """Ensure folder paths do not overlap with other libraries.
+
+        Also detects checkpoints ↔ unet path overlap within the same library
+        (including via symlink resolution), which is a configuration error since
+        these model types must use separate physical folders.
+        """
         libraries = self.settings.get("libraries", {})
         normalized_new: Dict[str, Dict[str, str]] = {}
         for key, values in folder_paths.items():
@@ -668,6 +698,22 @@ class SettingsManager:
                         f"Folder path(s) {collisions} already assigned to library '{other_name}'"
                     )
 
+        # Checkpoints ↔ unet overlap within the same library
+        ckpt_paths = folder_paths.get("checkpoints", []) or []
+        unet_paths = folder_paths.get("unet", []) or []
+        if ckpt_paths and unet_paths:
+            ckpt_real = self._normalize_path_set(ckpt_paths)
+            unet_real = self._normalize_path_set(unet_paths)
+            overlap = ckpt_real & unet_real
+            if overlap:
+                collisions = ", ".join(sorted(overlap))
+                raise ValueError(
+                    f"Path(s) {collisions} are configured for both "
+                    f"'checkpoints' and 'unet' (diffusion models). "
+                    f"These model types must use separate physical folders. "
+                    f"Please remove one of the conflicting entries."
+                )
+
     def _update_active_library_entry(
         self,
         *,
@@ -1542,8 +1588,12 @@ class SettingsManager:
             portable_switch_pending = True
             self._prepare_portable_switch(value)
         if key == "folder_paths" and isinstance(value, Mapping):
+            active_name = self.get_active_library_name()
+            self._validate_folder_paths(active_name, value)
             self._update_active_library_entry(folder_paths=value)  # type: ignore[arg-type]
         elif key == "extra_folder_paths" and isinstance(value, Mapping):
+            active_name = self.get_active_library_name()
+            self._validate_folder_paths(active_name, value)
             self._update_active_library_entry(extra_folder_paths=value)  # type: ignore[arg-type]
         elif key == "default_lora_root":
             self._update_active_library_entry(default_lora_root=str(value))
@@ -1797,6 +1847,9 @@ class SettingsManager:
                 if key in self.settings:
                     minimal[key] = copy.deepcopy(self.settings[key])
 
+            if self.settings.get("use_portable_settings"):
+                minimal["use_portable_settings"] = True
+
             if self._seed_template:
                 for key, value in self._seed_template.items():
                     minimal.setdefault(key, copy.deepcopy(value))

py/services/use_cases/bulk_metadata_refresh_use_case.py

@@ -51,6 +51,10 @@ class BulkMetadataRefreshUseCase:
             if not model.get("skip_metadata_refresh", False)
             and not self._is_in_skip_path(model.get("folder", ""), skip_paths)
             and (not model.get("civitai") or not model["civitai"].get("id"))
+            # Skip models downloaded from Hugging Face — they are not on
+            # CivitAI / CivArchive.  Users can still refresh them individually
+            # via the right-click context menu.
+            and not model.get("hf_url", "")
             and not (
                 # Skip models confirmed not on CivitAI when no need to retry
                 model.get("from_civitai") is False

py/utils/example_images_download_manager.py

@@ -72,6 +72,7 @@ class _DownloadProgress(dict):
             refreshed_models=set(),
             failed_models=set(),
             reprocessed_models=set(),
+            rate_limited_models=set(),
         )
 
     def snapshot(self) -> dict:
@@ -82,6 +83,7 @@ class _DownloadProgress(dict):
         snapshot["refreshed_models"] = list(self["refreshed_models"])
         snapshot["failed_models"] = list(self["failed_models"])
         snapshot["reprocessed_models"] = list(self.get("reprocessed_models", set()))
+        snapshot["rate_limited_models"] = list(self.get("rate_limited_models", set()))
         return snapshot
 
 
@@ -153,13 +155,15 @@ class DownloadManager:
         # Step 3: Load progress file (I/O operation, done outside lock)
         processed_models = set()
         failed_models = set()
+        rate_limited_models = set()
         
         try:
-            progress_file, processed_models, failed_models = await self._load_progress_file(output_dir)
+            progress_file, processed_models, failed_models, rate_limited_models = await self._load_progress_file(output_dir)
             logger.debug(
-                "Loaded previous progress, %s models already processed, %s models marked as failed",
+                "Loaded previous progress, %s models already processed, %s models marked as failed, %s models rate-limited",
                 len(processed_models),
                 len(failed_models),
+                len(rate_limited_models),
             )
         except Exception as e:
             logger.error(f"Failed to load progress file: {e}")
@@ -175,6 +179,7 @@ class DownloadManager:
                 self._progress.reset()
                 self._progress["processed_models"] = processed_models
                 self._progress["failed_models"] = failed_models
+                self._progress["rate_limited_models"] = rate_limited_models
                 self._stop_requested = False
                 self._progress["status"] = "running"
                 self._progress["start_time"] = time.time()
@@ -242,8 +247,8 @@ class DownloadManager:
             "status": self._progress.snapshot(),
         }
 
-    async def _load_progress_file(self, output_dir: str) -> tuple[str, set, set]:
-        """Load progress file from disk. Returns (progress_file_path, processed_models, failed_models).
+    async def _load_progress_file(self, output_dir: str) -> tuple[str, set, set, set]:
+        """Load progress file from disk. Returns (progress_file_path, processed_models, failed_models, rate_limited_models).
 
         This is a separate async method to allow running in executor to avoid blocking event loop.
         """
@@ -252,8 +257,12 @@ class DownloadManager:
             None, self._load_progress_file_sync, output_dir
         )
 
-    def _load_progress_file_sync(self, output_dir: str) -> tuple[str, set, set]:
-        """Synchronous implementation of progress file loading."""
+    def _load_progress_file_sync(self, output_dir: str) -> tuple[str, set, set, set]:
+        """Synchronous implementation of progress file loading.
+
+        Returns:
+            tuple: (progress_file_path, processed_models, failed_models, rate_limited_models)
+        """
         progress_file = os.path.join(output_dir, ".download_progress.json")
         progress_source = progress_file
 
@@ -289,6 +298,7 @@ class DownloadManager:
 
         processed_models = set()
         failed_models = set()
+        rate_limited_models = set()
 
         if os.path.exists(progress_source):
             try:
@@ -296,11 +306,11 @@ class DownloadManager:
                     saved_progress = json.load(f)
                     processed_models = set(saved_progress.get("processed_models", []))
                     failed_models = set(saved_progress.get("failed_models", []))
+                    rate_limited_models = set(saved_progress.get("rate_limited_models", []))
             except Exception:
-                # Return empty sets on error
                 pass
 
-        return progress_file, processed_models, failed_models
+        return progress_file, processed_models, failed_models, rate_limited_models
 
     def _load_progress_sets_sync(self, progress_file: str) -> tuple[set, set]:
         """Load only the processed and failed model sets from progress file.
@@ -732,11 +742,13 @@ class DownloadManager:
                     success,
                     is_stale,
                     failed_images,
+                    rate_limited_images,
                 ) = await ExampleImagesProcessor.download_model_images_with_tracking(
                     model_hash, model_name, images, model_dir, optimize, downloader
                 )
 
                 failed_urls: Set[str] = set(failed_images)
+                rate_limited_urls: Set[str] = set(rate_limited_images)
 
                 # If metadata is stale, try to refresh it
                 if is_stale and model_hash not in self._progress["refreshed_models"]:
@@ -760,6 +772,7 @@ class DownloadManager:
                             success,
                             _,
                             additional_failed,
+                            additional_rate_limited,
                         ) = await ExampleImagesProcessor.download_model_images_with_tracking(
                             model_hash,
                             model_name,
@@ -770,29 +783,50 @@ class DownloadManager:
                         )
 
                         failed_urls.update(additional_failed)
+                        rate_limited_urls.update(additional_rate_limited)
 
                     self._progress["refreshed_models"].add(model_hash)
 
-                if failed_urls:
+                # Separate permanent failures from rate-limited ones
+                permanent_failures = failed_urls - rate_limited_urls
+
+                if permanent_failures:
                     await self._remove_failed_images_from_metadata(
                         model_hash,
                         model_name,
                         model_dir,
-                        failed_urls,
+                        permanent_failures,
                         scanner,
                     )
 
-                if failed_urls:
+                if rate_limited_urls:
+                    self._progress["rate_limited_models"].add(model_hash)
+                    logger.warning(
+                        "%d example images for %s are rate-limited (429), will retry next time",
+                        len(rate_limited_urls),
+                        model_name,
+                    )
+                    # Clear failed_models so non-force runs can retry
+                    if force and model_hash in self._progress["failed_models"]:
+                        self._progress["failed_models"].discard(model_hash)
+                        logger.info(
+                            f"Removed {model_name} from failed_models after force retry with rate-limited images"
+                        )
+
+                if rate_limited_urls:
+                    # Don't mark as failed or fully processed — rate-limited
+                    # images will be retried next time.
+                    pass
+                elif permanent_failures:
                     self._progress["failed_models"].add(model_hash)
                     self._progress["processed_models"].add(model_hash)
                     logger.info(
                         "Removed %s failed example images for %s",
-                        len(failed_urls),
+                        len(permanent_failures),
                         model_name,
                     )
                 elif success:
                     self._progress["processed_models"].add(model_hash)
-                    # Remove from failed_models if force mode enabled and model was previously failed
                     if force and model_hash in self._progress["failed_models"]:
                         self._progress["failed_models"].discard(model_hash)
                         logger.info(
@@ -850,6 +884,7 @@ class DownloadManager:
                 "processed_models": list(self._progress["processed_models"]),
                 "refreshed_models": list(self._progress["refreshed_models"]),
                 "failed_models": list(self._progress["failed_models"]),
+                "rate_limited_models": list(self._progress.get("rate_limited_models", set())),
                 "completed": self._progress["completed"],
                 "total": self._progress["total"],
                 "last_update": time.time(),
@@ -1155,11 +1190,13 @@ class DownloadManager:
                     success,
                     is_stale,
                     failed_images,
+                    rate_limited_images,
                 ) = await ExampleImagesProcessor.download_model_images_with_tracking(
                     model_hash, model_name, images, model_dir, optimize, downloader
                 )
 
                 failed_urls: Set[str] = set(failed_images)
+                rate_limited_urls: Set[str] = set(rate_limited_images)
 
                 # If metadata is stale, try to refresh it
                 if is_stale and model_hash not in self._progress["refreshed_models"]:
@@ -1183,6 +1220,7 @@ class DownloadManager:
                             success,
                             _,
                             additional_failed_images,
+                            additional_rate_limited,
                         ) = await ExampleImagesProcessor.download_model_images_with_tracking(
                             model_hash,
                             model_name,
@@ -1192,21 +1230,35 @@ class DownloadManager:
                             downloader,
                         )
 
-                        # Combine failed images from both attempts
                         failed_urls.update(additional_failed_images)
+                        rate_limited_urls.update(additional_rate_limited)
 
                     self._progress["refreshed_models"].add(model_hash)
 
-                # For forced downloads, remove failed images from metadata
-                if failed_urls:
+                # Separate permanent failures from rate-limited ones
+                permanent_failures = failed_urls - rate_limited_urls
+
+                # Only remove permanently failed images from metadata
+                if permanent_failures:
                     await self._remove_failed_images_from_metadata(
-                        model_hash, model_name, model_dir, failed_urls, scanner
+                        model_hash, model_name, model_dir, permanent_failures, scanner
                     )
 
-                # Mark as processed
-                if (
-                    success or failed_urls
-                ):  # Mark as processed if we successfully downloaded some images or removed failed ones
+                if rate_limited_urls:
+                    self._progress["rate_limited_models"].add(model_hash)
+                    logger.warning(
+                        "%d example images for %s are rate-limited (429), will retry next time",
+                        len(rate_limited_urls),
+                        model_name,
+                    )
+
+                # Mark as processed only when no rate-limited images remain
+                if rate_limited_urls:
+                    pass
+                elif permanent_failures:
+                    self._progress["processed_models"].add(model_hash)
+                    self._progress["failed_models"].add(model_hash)
+                elif success:
                     self._progress["processed_models"].add(model_hash)
 
                 return True  # Return True to indicate a remote download happened
@@ -1229,15 +1281,20 @@ class DownloadManager:
         model_dir: str,
         failed_images: Iterable[str],
         scanner,
+        error_type: str = "not_found",
     ) -> None:
-        """Mark failed images in model metadata so they won't be retried."""
+        """Mark failed images in model metadata so they won't be retried.
+
+        Args:
+            error_type: Reason string stored in the image's ``downloadError`` field
+                        (default ``"not_found"``).
+        """
 
         failed_set: Set[str] = {url for url in failed_images if url}
         if not failed_set:
             return
 
         try:
-            # Get current model data
             model_data = await MetadataUpdater.get_updated_model(model_hash, scanner)
             if not model_data:
                 logger.warning(
@@ -1268,7 +1325,7 @@ class DownloadManager:
                     continue
 
                 image["downloadFailed"] = True
-                image.setdefault("downloadError", "not_found")
+                image.setdefault("downloadError", error_type)
                 logger.debug(
                     "Marked example image %s for %s as failed due to missing remote asset",
                     image_url,

py/utils/example_images_processor.py

@@ -1,3 +1,4 @@
+import asyncio
 import logging
 import os
 import re
@@ -194,16 +195,22 @@ class ExampleImagesProcessor:
         
         return model_success, False  # (success, is_metadata_stale)
     
+    @staticmethod
+    def _extract_retry_after(error_message: str) -> int:
+        if not error_message:
+            return 60
+        match = re.search(r"retry after (\d+)s", str(error_message))
+        if match:
+            return max(1, int(match.group(1)))
+        return 60
+
     @staticmethod
     async def download_model_images_with_tracking(model_hash, model_name, model_images, model_dir, optimize, downloader):
-        """Download images for a single model with tracking of failed image URLs
-        
-        Returns:
-            tuple: (success, is_stale_metadata, failed_images) - whether download was successful, whether metadata is stale, list of failed image URLs
-        """
         model_success = True
         failed_images = []
-        
+        rate_limited_images = []
+        any_successful_download = False
+
         for i, image in enumerate(model_images):
             image_url = image.get('url')
             if not image_url:
@@ -221,64 +228,110 @@ class ExampleImagesProcessor:
             original_url = image_url
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
-            
-            # Download the file first to determine the actual file type
-            try:
-                logger.debug(f"Downloading media file {i} for {model_name}")
-                
-                # Download using the unified downloader with headers
-                success, content, headers = await downloader.download_to_memory(
+
+            async def _attempt_download() -> tuple:
+                logger.debug("Downloading media file %s for %s", i, model_name)
+                return await downloader.download_to_memory(
                     image_url,
-                    use_auth=False,  # Example images don't need auth
-                    return_headers=True
+                    use_auth=False,
+                    return_headers=True,
                 )
-                
+
+            try:
+                success, content, headers = await _attempt_download()
+
                 if success:
-                    # Determine file extension from content or headers
                     media_ext = ExampleImagesProcessor._get_file_extension_from_content_or_headers(
                         content, headers, original_url, image.get("type")
                     )
-                    
-                    # Check if the detected file type is supported
                     is_image = media_ext in SUPPORTED_MEDIA_EXTENSIONS['images']
                     is_video = media_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
-                    
+
                     if not (is_image or is_video):
-                        logger.debug(f"Skipping unsupported file type: {media_ext}")
+                        logger.debug("Skipping unsupported file type: %s", media_ext)
                         continue
-                    
-                    # Use 0-based indexing with the detected extension
+
                     save_filename = f"image_{i}{media_ext}"
                     save_path = os.path.join(model_dir, save_filename)
-                    
-                    # Check if already downloaded
+
                     if os.path.exists(save_path):
-                        logger.debug(f"File already exists: {save_path}")
+                        logger.debug("File already exists: %s", save_path)
                         continue
-                    
-                    # Save the file
+
                     with open(save_path, 'wb') as f:
                         f.write(content)
-                    
+                    any_successful_download = True
+
                 elif ExampleImagesProcessor._is_not_found_error(content):
                     error_msg = f"Failed to download file: {image_url}, status code: 404 - Model metadata might be stale"
                     logger.warning(error_msg)
-                    model_success = False  # Mark the model as failed due to 404 error
-                    failed_images.append(image_url)  # Track failed URL
-                    # Return early to trigger metadata refresh attempt
-                    return False, True, failed_images  # (success, is_metadata_stale, failed_images)
+                    model_success = False
+                    failed_images.append(image_url)
+                    return False, True, failed_images, rate_limited_images
+
+                elif "Rate limited (429)" in str(content):
+                    max_attempts = 3
+                    for attempt in range(1, max_attempts + 1):
+                        wait = ExampleImagesProcessor._extract_retry_after(str(content)) * (2 ** (attempt - 1))
+                        logger.warning(
+                            "Rate limited (429) for %s, retry %d/%d after %ds",
+                            image_url, attempt, max_attempts, wait,
+                        )
+                        await asyncio.sleep(wait)
+
+                        success, content, headers = await _attempt_download()
+                        if success:
+                            media_ext = ExampleImagesProcessor._get_file_extension_from_content_or_headers(
+                                content, headers, original_url, image.get("type")
+                            )
+                            is_image = media_ext in SUPPORTED_MEDIA_EXTENSIONS['images']
+                            is_video = media_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
+
+                            if not (is_image or is_video):
+                                logger.debug("Skipping unsupported file type: %s", media_ext)
+                                break
+
+                            save_filename = f"image_{i}{media_ext}"
+                            save_path = os.path.join(model_dir, save_filename)
+                            if os.path.exists(save_path):
+                                logger.debug("File already exists: %s", save_path)
+                                break
+
+                            with open(save_path, 'wb') as f:
+                                f.write(content)
+                            any_successful_download = True
+                            break
+                        elif "Rate limited (429)" in str(content):
+                            continue
+                        elif ExampleImagesProcessor._is_not_found_error(content):
+                            logger.warning("Failed to download file: %s, status code: 404", image_url)
+                            model_success = False
+                            failed_images.append(image_url)
+                            break
+                        else:
+                            logger.warning("Failed to download file: %s, error: %s", image_url, content)
+                            model_success = False
+                            failed_images.append(image_url)
+                            break
+                    else:
+                        logger.warning(
+                            "Giving up on %s after %d retries due to rate limiting",
+                            image_url, max_attempts,
+                        )
+                        rate_limited_images.append(image_url)
+                        model_success = False
                 else:
                     error_msg = f"Failed to download file: {image_url}, error: {content}"
                     logger.warning(error_msg)
-                    model_success = False  # Mark the model as failed
-                    failed_images.append(image_url)  # Track failed URL
+                    model_success = False
+                    failed_images.append(image_url)
             except Exception as e:
                 error_msg = f"Error downloading file {image_url}: {str(e)}"
                 logger.error(error_msg)
-                model_success = False  # Mark the model as failed
-                failed_images.append(image_url)  # Track failed URL
-        
-        return model_success, False, failed_images  # (success, is_metadata_stale, failed_images)
+                model_success = False
+                failed_images.append(image_url)
+
+        return any_successful_download or model_success, False, failed_images, rate_limited_images
     
     @staticmethod
     async def process_local_examples(model_file_path, model_file_name, model_name, model_dir, optimize):

py/utils/settings_paths.py

@@ -12,6 +12,7 @@ from platformdirs import user_config_dir
 
 
 APP_NAME = "ComfyUI-LoRA-Manager"
+_LM_PORTABLE_ENV = "LORA_MANAGER_PORTABLE"
 _LOGGER = logging.getLogger(__name__)
 
 
@@ -100,7 +101,11 @@ def ensure_settings_file(logger: Optional[logging.Logger] = None) -> str:
 
 
 def _should_use_portable_settings(path: str, logger: logging.Logger) -> bool:
-    """Return ``True`` when the repository settings file enables portable mode."""
+    """Return ``True`` when the env var forces it or the settings file enables it."""
+
+    if os.environ.get(_LM_PORTABLE_ENV, "0") == "1":
+        logger.debug("Portable mode enabled via %s", _LM_PORTABLE_ENV)
+        return True
 
     if not os.path.exists(path):
         return False

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.1.6"
+version = "1.1.7"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

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

@@ -577,13 +577,14 @@
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
     cursor: pointer;
-    transition: var(--transition-base);
+    transition: var(--transition-base), box-shadow var(--transition-fast), transform var(--transition-fast);
     background: var(--bg-color);
 }
 
 .file-option:hover {
     border-color: var(--lora-accent);
-    box-shadow: var(--shadow-sm);
+    box-shadow: var(--shadow-md);
+    transform: translateY(-1px);
 }
 
 .file-option.selected {
@@ -698,10 +699,25 @@
     color: var(--lora-accent);
 }
 
-/* Batch Preview List */
+/* BUG 1 FIX: Single scrollbar — modal-content becomes a flex column so the
+   batch preview step can flex; the list scrolls instead of the modal-content. */
+#downloadModal .modal-content {
+    display: flex;
+    flex-direction: column;
+}
+
+#batchPreviewStep {
+    display: flex;
+    flex-direction: column;
+    min-height: 0;
+    flex: 1;
+}
+
+/* Batch Preview List — no max-height; flexes inside #batchPreviewStep */
 .batch-preview-list {
-    max-height: 400px;
+    flex: 1;
     overflow-y: auto;
+    min-height: 0;
     margin: var(--space-2) 0;
     display: flex;
     flex-direction: column;
@@ -859,6 +875,8 @@
     position: sticky;
     top: 0;
     z-index: 1;
+    backdrop-filter: blur(8px);
+    -webkit-backdrop-filter: blur(8px);
 }
 
 .batch-preview-select-all input[type="checkbox"] {
@@ -884,3 +902,100 @@
 [data-theme="dark"] .batch-preview-select-all {
     background: var(--lora-surface);
 }
+
+/* FEATURE 2: HF repo grouping — collapsible groups by repo */
+.batch-preview-group {
+    display: flex;
+    flex-direction: column;
+    background: var(--surface-base);
+}
+
+.batch-preview-group-header {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 10px 12px;
+    background: var(--color-accent-subtle);
+    border-bottom: 1px solid var(--color-accent-border);
+    cursor: pointer;
+    user-select: none;
+    transition: background var(--transition-fast);
+}
+
+.batch-preview-group-header:hover {
+    background: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.18);
+}
+
+.batch-preview-group-toggle {
+    width: 14px;
+    font-size: 0.75em;
+    color: var(--text-color);
+    opacity: 0.7;
+    transition: transform var(--transition-fast);
+    flex-shrink: 0;
+}
+
+.batch-preview-group-toggle.expanded {
+    transform: rotate(90deg);
+}
+
+.batch-preview-group-name {
+    flex: 1;
+    min-width: 0;
+    font-weight: 600;
+    color: var(--text-color);
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    font-size: 0.95em;
+}
+
+.batch-preview-group-count {
+    font-size: 0.8em;
+    color: var(--text-color);
+    opacity: 0.7;
+    flex-shrink: 0;
+}
+
+.batch-preview-group-select-all {
+    width: 18px;
+    height: 18px;
+    cursor: pointer;
+    accent-color: var(--lora-accent);
+    flex-shrink: 0;
+    padding: 0;
+    margin: 0;
+}
+
+.batch-preview-group-body {
+    display: flex;
+    flex-direction: column;
+    gap: 1px;
+    background: var(--border-color);
+    overflow: hidden;
+    max-height: 0;
+    opacity: 0;
+    transition: max-height 0.35s ease, opacity 0.2s ease;
+}
+
+.batch-preview-group-body.expanded {
+    opacity: 1;
+    max-height: 9999px; /* rest state: content visible; JS inline style overrides during transitions */
+}
+
+/* Dark theme overrides for group styles */
+[data-theme="dark"] .batch-preview-group {
+    background: var(--surface-base);
+}
+
+[data-theme="dark"] .batch-preview-group-header {
+    background: var(--color-accent-subtle);
+}
+
+[data-theme="dark"] .batch-preview-group-header:hover {
+    background: oklch(var(--color-accent-l) var(--color-accent-c) var(--color-accent-h) / 0.22);
+}
+
+[data-theme="dark"] .batch-preview-group-body {
+    background: var(--border-color);
+}

static/css/components/modal/relink-civitai-modal.css

@@ -21,18 +21,22 @@
   margin-bottom: 4px;
 }
 
-.input-group {
+#relinkCivitaiModal .input-group,
+#linkHfModal .input-group {
   display: flex;
   flex-direction: column;
   margin-bottom: var(--space-2);
 }
 
-.input-group label {
+#relinkCivitaiModal .input-group label,
+#linkHfModal .input-group label {
   margin-bottom: var(--space-1);
   font-weight: 500;
 }
 
-.input-group input {
+#relinkCivitaiModal .input-group input,
+#linkHfModal .input-group input {
+  width: auto;
   padding: 8px 12px;
   border-radius: var(--border-radius-xs);
   border: 1px solid var(--border-color);

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

@@ -1562,6 +1562,29 @@ input:checked + .toggle-slider:before {
     box-shadow: 0 0 0 2px rgba(var(--lora-accent-rgb, 79, 70, 229), 0.1);
 }
 
+.extra-folder-path-row .path-controls .extra-folder-path-input.has-error {
+    border-color: var(--lora-error);
+    background-color: rgba(220, 53, 69, 0.08);
+    background-color: rgba(from var(--lora-error) r g b / 0.08);
+}
+
+.extra-folder-path-row .path-controls .extra-folder-path-input.has-error:focus {
+    box-shadow: 0 0 0 2px rgba(220, 53, 69, 0.15);
+    box-shadow: 0 0 0 2px rgba(from var(--lora-error) r g b / 0.15);
+}
+
+.extra-folder-path-error {
+    color: var(--lora-error);
+    font-size: 0.8em;
+    margin-top: 4px;
+    line-height: 1.4;
+    display: none;
+}
+
+.extra-folder-path-error.visible {
+    display: block;
+}
+
 .extra-folder-path-row .path-controls .remove-path-btn {
     width: 32px;
     height: 32px;

static/js/api/baseModelApi.js

@@ -112,6 +112,18 @@ export class BaseModelApiClient {
         }
     }
 
+    async cancelDownload(downloadId) {
+        try {
+            const response = await fetch(
+                `${DOWNLOAD_ENDPOINTS.cancelGet}?download_id=${encodeURIComponent(downloadId)}`
+            );
+            return await response.json();
+        } catch (error) {
+            console.error('Error cancelling download:', error);
+            return { success: false, error: error.message };
+        }
+    }
+
     async loadMoreWithVirtualScroll(resetPage = false, updateFolders = false) {
         const pageState = this.getPageState();
 

static/js/components/ContextMenu/BulkContextMenu.js

@@ -391,6 +391,15 @@ export class BulkContextMenu extends BaseContextMenu {
             `Enriching metadata for ${modelPaths.length} models...`
         );
 
+        function cleanupCallbacks() {
+            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
+            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
+            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
+            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            const eIdx = agentManager.errorCallbacks.indexOf(onError);
+            if (eIdx >= 0) agentManager.errorCallbacks.splice(eIdx, 1);
+        }
+
         const onProgress = (data) => {
             if (data.status === 'processing' && data.current_path && data.updated_data && Object.keys(data.updated_data).length > 0) {
                 if (state.virtualScroller?.updateSingleItem) {
@@ -404,36 +413,37 @@ export class BulkContextMenu extends BaseContextMenu {
         agentManager.onProgress(onProgress);
 
         const onComplete = (data) => {
-            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
-            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
-            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
-            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            cleanupCallbacks();
 
             if (data.status === 'completed') {
+                if (state.bulkMode) bulkManager.toggleBulkMode();
                 progressUI.complete(data.summary || 'Enrich complete');
                 showToast(
                     'toast.agent.enrichComplete',
                     { summary: data.summary || 'Done' },
                     'success'
                 );
-            } else if (data.status === 'error') {
-                state.loadingManager.hide();
-                showToast(
-                    'toast.agent.enrichFailed',
-                    { error: data.error || 'Unknown error' },
-                    'error'
-                );
             }
         };
         agentManager.onComplete(onComplete);
 
+        const onError = (data) => {
+            cleanupCallbacks();
+            if (state.bulkMode) bulkManager.toggleBulkMode();
+            state.loadingManager.hide();
+            showToast(
+                'toast.agent.enrichFailed',
+                { error: data.error || 'Unknown error' },
+                'error'
+            );
+        };
+        agentManager.onError(onError);
+
         try {
             await agentManager.executeSkill('enrich_hf_metadata', modelPaths);
         } catch (error) {
-            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
-            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
-            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
-            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            cleanupCallbacks();
+            if (state.bulkMode) bulkManager.toggleBulkMode();
             state.loadingManager.hide();
             showToast(
                 'toast.agent.enrichFailed',

static/js/components/ContextMenu/LoraContextMenu.js

@@ -32,6 +32,9 @@ export class LoraContextMenu extends BaseContextMenu {
         if (!enrichItem) return;
         const hasHfUrl = !!card.dataset.hf_url;
         enrichItem.classList.toggle('disabled', !hasHfUrl);
+        enrichItem.title = hasHfUrl
+            ? ''
+            : 'Link this model to a HuggingFace repo first (Link Model \u2192 Link to HuggingFace)';
     }
 
     handleMenuAction(action, menuItem) {
@@ -99,6 +102,15 @@ export class LoraContextMenu extends BaseContextMenu {
             'Enriching metadata with AI...'
         );
 
+        function cleanupCallbacks() {
+            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
+            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
+            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
+            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            const eIdx = agentManager.errorCallbacks.indexOf(onError);
+            if (eIdx >= 0) agentManager.errorCallbacks.splice(eIdx, 1);
+        }
+
         const onProgress = (data) => {
             if (data.status === 'processing' && data.current_path && data.updated_data && Object.keys(data.updated_data).length > 0) {
                 if (state.virtualScroller?.updateSingleItem) {
@@ -112,28 +124,26 @@ export class LoraContextMenu extends BaseContextMenu {
         agentManager.onProgress(onProgress);
 
         const onComplete = (data) => {
-            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
-            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
-            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
-            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            cleanupCallbacks();
 
             if (data.status === 'completed') {
                 progressUI.complete(data.summary || 'Enrich complete');
                 showToast('toast.agent.enrichComplete', { summary: data.summary || 'Done' }, 'success');
-            } else if (data.status === 'error') {
-                state.loadingManager.hide();
-                showToast('toast.agent.enrichFailed', { error: data.error || 'Unknown error' }, 'error');
             }
         };
         agentManager.onComplete(onComplete);
 
+        const onError = (data) => {
+            cleanupCallbacks();
+            state.loadingManager.hide();
+            showToast('toast.agent.enrichFailed', { error: data.error || 'Unknown error' }, 'error');
+        };
+        agentManager.onError(onError);
+
         try {
             await agentManager.executeSkill('enrich_hf_metadata', [filePath]);
         } catch (error) {
-            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
-            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
-            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
-            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            cleanupCallbacks();
             state.loadingManager.hide();
             showToast('toast.agent.enrichFailed', { error: error.message }, 'error');
         }

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -187,6 +187,74 @@ export const ModelContextMenuMixin = {
         setTimeout(() => urlInput.focus(), 50);
     },
 
+    // HuggingFace linking methods
+    showLinkHfModal() {
+        const filePath = this.currentCard.dataset.filepath;
+        if (!filePath) return;
+
+        const confirmBtn = document.getElementById('confirmLinkHfBtn');
+        const urlInput = document.getElementById('hfModelUrl');
+        const errorDiv = document.getElementById('hfModelUrlError');
+
+        if (this._boundLinkHfHandler) {
+            confirmBtn.removeEventListener('click', this._boundLinkHfHandler);
+        }
+
+        this._boundLinkHfHandler = async () => {
+            const hfUrl = urlInput.value.trim();
+            if (!hfUrl) {
+                errorDiv.textContent = 'Please enter a HuggingFace repository URL.';
+                return;
+            }
+
+            const hfPattern = /^https?:\/\/huggingface\.co\/([^/]+\/[^/]+)\/?$/;
+            if (!hfPattern.test(hfUrl)) {
+                errorDiv.textContent = 'Invalid URL format. Expected: https://huggingface.co/user/repo';
+                return;
+            }
+
+            errorDiv.textContent = '';
+            modalManager.closeModal('linkHfModal');
+
+            try {
+                state.loadingManager.showSimpleLoading('Linking to HuggingFace...');
+
+                const response = await fetch('/api/lm/set-hf-url', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ file_path: filePath, hf_url: hfUrl }),
+                });
+
+                if (!response.ok) {
+                    const errData = await response.json().catch(() => ({}));
+                    throw new Error(errData.error || `Request failed: ${response.statusText}`);
+                }
+
+                const data = await response.json();
+                if (data.success) {
+                    showToast('toast.contextMenu.linkHfSuccess', {}, 'success');
+                    await this.resetAndReload();
+                } else {
+                    throw new Error(data.error || 'Failed to link model');
+                }
+            } catch (error) {
+                console.error('Error linking model to HuggingFace:', error);
+                showToast('toast.contextMenu.linkHfFailed', { message: error.message }, 'error');
+            } finally {
+                state.loadingManager.hide();
+            }
+        };
+
+        confirmBtn.addEventListener('click', this._boundLinkHfHandler);
+
+        urlInput.value = '';
+        errorDiv.textContent = '';
+
+        modalManager.showModal('linkHfModal');
+
+        setTimeout(() => urlInput.focus(), 50);
+    },
+
     extractModelVersionId(url) {
         return extractCivitaiModelUrlParts(url);
     },
@@ -295,6 +363,9 @@ export const ModelContextMenuMixin = {
             case 'relink-civitai':
                 this.showRelinkCivitaiModal();
                 return true;
+            case 'link-hf':
+                this.showLinkHfModal();
+                return true;
             case 'set-nsfw':
                 this.showNSFWLevelSelector(null, null, this.currentCard);
                 return true;

static/js/components/RecipeCard.js

@@ -358,7 +358,7 @@ class RecipeCard {
                         <div class="delete-preview">
                             ${isVideo ?
                     `<video src="${previewUrl}" controls muted loop playsinline style="max-width: 100%;"></video>` :
-                    `<img src="${previewUrl}" alt="${this.recipe.title}">`
+                `<img src="${previewUrl}" alt="${this.recipe.title}" onerror="this.onerror=null; this.src='/loras_static/images/no-preview.png'">`
                 }
                         </div>
                         <div class="delete-info">

static/js/components/RecipeModal.js

@@ -757,7 +757,7 @@ class RecipeModal {
                     `<video class="thumbnail-video" autoplay loop muted playsinline>
                         <source src="${lora.preview_url}" type="video/mp4">
                      </video>` :
-                    `<img src="${lora.preview_url || '/loras_static/images/no-preview.png'}" alt="LoRA preview">`;
+                    `<img src="${lora.preview_url || '/loras_static/images/no-preview.png'}" alt="LoRA preview" onerror="this.onerror=null; this.src='/loras_static/images/no-preview.png'">`;
 
                 let loraItemClass = 'recipe-lora-item';
                 if (existsLocally) {
@@ -1606,7 +1606,7 @@ class RecipeModal {
             <video class="thumbnail-video" autoplay loop muted playsinline>
                 <source src="${previewUrl}" type="video/mp4">
             </video>
-        ` : `<img src="${previewUrl}" alt="Checkpoint preview">`;
+        ` : `<img src="${previewUrl}" alt="Checkpoint preview" onerror="this.onerror=null; this.src='/loras_static/images/no-preview.png'">`;
 
         const badge = existsLocally ? `
             <div class="local-badge">

static/js/components/shared/ModelCard.js

@@ -643,7 +643,7 @@ export function createModelCard(model, modelType) {
         <div class="card-preview ${shouldBlur ? 'blurred' : ''}">
             ${isVideo ?
             `<video ${videoAttrs.join(' ')} style="pointer-events: none;"></video>` :
-            `<img src="${versionedPreviewUrl}" alt="${model.model_name}">`
+            `<img src="${versionedPreviewUrl}" alt="${model.model_name}" onerror="this.onerror=null; this.src='/loras_static/images/no-preview.png'">`
         }
             <div class="card-header">
                 ${shouldBlur ?

static/js/components/shared/ModelVersionsTab.js

@@ -432,7 +432,7 @@ function renderMediaMarkup(version) {
 
     return `
         <div class="version-media">
-            <img src="${escapeHtml(version.previewUrl)}" alt="${escapeHtml(version.name || 'preview')}">
+            <img src="${escapeHtml(version.previewUrl)}" alt="${escapeHtml(version.name || 'preview')}" onerror="this.onerror=null; this.src='/loras_static/images/no-preview.png'">
         </div>
     `;
 }

static/js/components/shared/showcase/MediaUtils.js

@@ -586,6 +586,7 @@ export function initMediaControlHandlers(container) {
             const imageMetaRaw = this.dataset.imageMeta;
             const imageUrl = this.dataset.imageUrl;
             const imageNsfw = this.dataset.imageNsfw;
+            const imgId = this.dataset.imgId || '';
             const localPath = this.dataset.localPath || '';
             const showcaseSection = this.closest('.showcase-section');
             const modelHash = showcaseSection ? showcaseSection.dataset.modelHash : '';
@@ -613,6 +614,7 @@ export function initMediaControlHandlers(container) {
                             meta: imageMeta,
                             url: imageUrl,
                             nsfwLevel: imageNsfw ? parseInt(imageNsfw, 10) : undefined,
+                            id: imgId || undefined,
                         },
                         model_hash: modelHash,
                         model_name: modelName || modelHash,

static/js/components/shared/showcase/ShowcaseView.js

@@ -213,8 +213,8 @@ function renderMediaItem(img, index, exampleFiles) {
     const model = meta.Model || '';
     const steps = meta.steps || '';
     const sampler = meta.sampler || '';
-    const cfgScale = meta.cfgScale || '';
-    const clipSkip = meta.clipSkip || '';
+    const cfgScale = meta.cfg_scale || meta.cfgScale || '';
+    const clipSkip = meta.clip_skip || meta.clipSkip || '';
     
     // Check if we have any meaningful generation parameters
     const hasParams = seed || model || steps || sampler || cfgScale || clipSkip;
@@ -245,6 +245,7 @@ function renderMediaItem(img, index, exampleFiles) {
                     data-image-url="${img.url || ''}"
                     data-image-nsfw="${img.nsfwLevel ?? ''}"
                     data-image-id="${cdnImageId}"
+                    data-img-id="${img.id || ''}"
                     data-local-path="${localFile ? localFile.path : ''}">
                 <i class="fas fa-book-open"></i>
             </button>

static/js/managers/BatchImportManager.js

@@ -1,5 +1,5 @@
 import { modalManager } from './ModalManager.js';
-import { showToast } from '../utils/uiHelpers.js';
+import { showToast, setupAutoNewlineOnPaste } from '../utils/uiHelpers.js';
 import { translate } from '../utils/i18nHelpers.js';
 import { WS_ENDPOINTS } from '../api/apiConfig.js';
 import { getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
@@ -43,6 +43,9 @@ export class BatchImportManager {
                 setStorageItem('batch_import_skip_no_metadata', e.target.checked);
             });
         }
+
+        // Auto-append newline after pasting a URL in the batch URL input
+        setupAutoNewlineOnPaste('batchUrlInput');
     }
 
     /**

static/js/managers/BulkManager.js

@@ -633,7 +633,7 @@ export class BulkManager {
                 filePaths.forEach(path => {
                     state.virtualScroller.removeItemByFilePath(path);
                 });
-                this.clearSelection();
+                if (state.bulkMode) this.toggleBulkMode();
 
                 if (window.modelDuplicatesManager) {
                     window.modelDuplicatesManager.updateDuplicatesBadgeAfterRefresh();
@@ -763,8 +763,9 @@ export class BulkManager {
                     `Re-import complete: ${completed} re-imported, ${failed} failed`
                 );
                 const { resetAndReload: recipeResetAndReload } = await import('../api/recipeApi.js');
-                recipeResetAndReload(false, { preserveScroll: false });
                 this.clearSelection();
+                if (state.bulkMode) this.toggleBulkMode();
+                recipeResetAndReload(false, { preserveScroll: false });
             } else {
                 state.loadingManager.hide();
                 showToast('toast.recipes.reimportBulkFailed', {}, 'error');
@@ -829,7 +830,7 @@ export class BulkManager {
                     );
                 }
 
-                this.clearSelection();
+                if (state.bulkMode) this.toggleBulkMode();
             } else {
                 throw new Error(result.error || 'Bulk repair failed');
             }
@@ -874,6 +875,8 @@ export class BulkManager {
                 if (this.isStripVisible) {
                     this.updateThumbnailStrip();
                 }
+
+                if (state.bulkMode) this.toggleBulkMode();
             }
 
         } catch (error) {
@@ -927,6 +930,7 @@ export class BulkManager {
                 showToast('toast.models.bulkUpdatesNone', { type: typeLabel }, 'info');
             }
 
+            if (state.bulkMode) this.toggleBulkMode();
             await resetAndReload(false);
         } catch (error) {
             console.error('Error checking updates for selected models:', error);
@@ -1273,6 +1277,8 @@ export class BulkManager {
                 showToast(toastKey, { count: failCount }, 'warning');
             }
 
+            if (state.bulkMode) this.toggleBulkMode();
+
         } catch (error) {
             console.error('Error during bulk tag operation:', error);
             const toastKey = mode === 'replace' ? 'toast.models.bulkTagsReplaceFailed' : 'toast.models.bulkTagsAddFailed';
@@ -1398,6 +1404,8 @@ export class BulkManager {
         } else {
             showToast('toast.models.bulkFavoriteFailed', {}, 'error');
         }
+
+        if (state.bulkMode) this.toggleBulkMode();
     }
 
     /**
@@ -1526,6 +1534,8 @@ export class BulkManager {
             showToast('toast.models.bulkContentRatingFailed', {}, 'error');
         }
 
+        if (state.bulkMode) this.toggleBulkMode();
+
         return successCount > 0;
     }
 
@@ -1580,6 +1590,8 @@ export class BulkManager {
         } else {
             showToast('toast.models.skipMetadataRefreshFailed', {}, 'error');
         }
+
+        if (state.bulkMode) this.toggleBulkMode();
     }
 
     /**
@@ -1674,6 +1686,8 @@ export class BulkManager {
                 showToast('toast.models.bulkBaseModelUpdateFailed', {}, 'error');
             }
 
+            if (state.bulkMode) this.toggleBulkMode();
+
         } catch (error) {
             console.error('Error during bulk base model operation:', error);
             showToast('toast.models.bulkBaseModelUpdateFailed', {}, 'error');
@@ -1711,6 +1725,7 @@ export class BulkManager {
             // Call the auto-organize method with selected file paths
             await apiClient.autoOrganizeModels(filePaths);
 
+            if (state.bulkMode) this.toggleBulkMode();
             resetAndReload(true);
         } catch (error) {
             console.error('Error during bulk auto-organize:', error);

static/js/managers/BulkMissingLoraDownloadManager.js

@@ -196,6 +196,17 @@ export class BulkMissingLoraDownloadManager {
         let completedDownloads = 0;
         let failedDownloads = 0;
         let currentLoraProgress = 0;
+        let cancelled = false;
+
+        loadingManager.showCancelButton(async () => {
+            if (cancelled) return;
+            cancelled = true;
+            try {
+                await this.loraApiClient.cancelDownload(batchDownloadId);
+            } catch (e) {
+                console.error('Cancel request failed:', e);
+            }
+        });
 
         // Set up WebSocket message handler
         ws.onmessage = (event) => {
@@ -207,6 +218,11 @@ export class BulkMissingLoraDownloadManager {
                 return;
             }
 
+            if (data.status === 'cancelled') {
+                cancelled = true;
+                return;
+            }
+
             // Process progress updates
             if (data.status === 'progress' && data.download_id && data.download_id.startsWith(batchDownloadId)) {
                 currentLoraProgress = data.progress;
@@ -249,6 +265,8 @@ export class BulkMissingLoraDownloadManager {
 
         // Download each LoRA sequentially
         for (let i = 0; i < lorasToDownload.length; i++) {
+            if (cancelled) break;
+
             const lora = lorasToDownload[i];
             
             currentLoraProgress = 0;
@@ -275,11 +293,13 @@ export class BulkMissingLoraDownloadManager {
                     modelId,
                     versionId,
                     loraRoot,
-                    '', // Empty relative path, use default paths
+                    '',
                     useDefaultPaths,
                     batchDownloadId
                 );
 
+                if (cancelled) break;
+
                 if (!response.success) {
                     console.error(`Failed to download LoRA ${lora.name || lora.file_name}: ${response.error}`);
                     failedDownloads++;
@@ -288,8 +308,10 @@ export class BulkMissingLoraDownloadManager {
                     updateProgress(100, completedDownloads, '');
                 }
             } catch (error) {
-                console.error(`Error downloading LoRA ${lora.name || lora.file_name}:`, error);
-                failedDownloads++;
+                if (!cancelled) {
+                    console.error(`Error downloading LoRA ${lora.name || lora.file_name}:`, error);
+                    failedDownloads++;
+                }
             }
         }
 
@@ -300,7 +322,10 @@ export class BulkMissingLoraDownloadManager {
         loadingManager.hide();
 
         // Show completion message
-        if (failedDownloads === 0) {
+        if (cancelled) {
+            showToast('toast.downloads.downloadStopped', {}, 'info',
+                `Download cancelled. ${completedDownloads} item(s) completed.`);
+        } else if (failedDownloads === 0) {
             showToast('toast.loras.allDownloadSuccessful', { count: completedDownloads }, 'success');
         } else {
             showToast('toast.loras.downloadPartialSuccess', {

static/js/managers/DownloadManager.js

@@ -1,5 +1,5 @@
 import { modalManager } from './ModalManager.js';
-import { showToast } from '../utils/uiHelpers.js';
+import { showToast, setupAutoNewlineOnPaste } from '../utils/uiHelpers.js';
 import { state } from '../state/index.js';
 import { LoadingManager } from './LoadingManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
@@ -31,6 +31,7 @@ export class DownloadManager {
         // HF download state
         this.hfRepoId = null;
         this.hfSelectedFiles = [];
+        this.hfRepoCollapsed = {};
 
         this.loadingManager = new LoadingManager();
         this.folderTreeManager = new FolderTreeManager();
@@ -107,7 +108,8 @@ export class DownloadManager {
         // Default path toggle handler
         document.getElementById('useDefaultPath').addEventListener('change', this.handleToggleDefaultPath);
 
-
+        // Auto-append newline after pasting a URL so users can paste multiple URLs in succession
+        setupAutoNewlineOnPaste('modelUrl');
     }
 
     updateModalLabels() {
@@ -173,6 +175,7 @@ export class DownloadManager {
         // Reset HF state
         this.hfRepoId = null;
         this.hfSelectedFiles = [];
+        this.hfRepoCollapsed = {};
     }
 
     async retrieveVersionsForModel(modelId, source = null) {
@@ -463,8 +466,8 @@ export class DownloadManager {
         const trimmed = url.trim();
         if (!trimmed) return null;
 
-        // CivitAI
-        if (/civitai\.com\/models\//i.test(trimmed) || /civitaiarchive|civarchive/i.test(trimmed)) {
+        // CivitAI — matches civitai.com, civitai.red, civitai.green, etc.
+        if (/civitai\.(?:com|red|green)\/models\//i.test(trimmed) || /civitaiarchive|civarchive/i.test(trimmed)) {
             // Will be parsed by existing CivitAI logic
             return { type: 'civitai' };
         }
@@ -725,14 +728,23 @@ export class DownloadManager {
 
     confirmFileSelection() {
         const selectedRadio = document.querySelector('#fileSelectionList input[type="radio"]:checked');
-        if (!selectedRadio) return;
+        if (!selectedRadio) {
+            console.warn('[download] confirmFileSelection: no radio button checked');
+            return;
+        }
 
         const version = this.currentVersion;
-        if (!version) return;
+        if (!version) {
+            console.warn('[download] confirmFileSelection: no currentVersion set');
+            return;
+        }
 
         const modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
         this.selectedFile = modelFiles.find(f => f.id.toString() === selectedRadio.value);
 
+        console.log('[download] confirmFileSelection: selected file id=%s, name="%s", type="%s", metadata=%o',
+            this.selectedFile?.id, this.selectedFile?.name, this.selectedFile?.type, this.selectedFile?.metadata);
+
         document.getElementById('fileSelectionStep').style.display = 'none';
         document.getElementById('locationStep').style.display = 'block';
         this.proceedToLocationContent();
@@ -869,16 +881,26 @@ export class DownloadManager {
         const displayName = versionName || `#${versionId}`;
         let ws = null;
         let updateProgress = () => { };
+        let cancelled = false;
+        const downloadId = Date.now().toString();
 
         try {
             this.loadingManager.restoreProgressBar();
             updateProgress = this.loadingManager.showDownloadProgress(1);
             updateProgress(0, 0, displayName);
-
-            const downloadId = Date.now().toString();
             const wsProtocol = window.location.protocol === 'https:' ? 'wss://' : 'ws://';
             ws = new WebSocket(`${wsProtocol}${window.location.host}/ws/download-progress?id=${downloadId}`);
 
+            this.loadingManager.showCancelButton(async () => {
+                if (cancelled) return;
+                cancelled = true;
+                try {
+                    await this.apiClient.cancelDownload(downloadId);
+                } catch (e) {
+                    console.error('Cancel request failed:', e);
+                }
+            });
+
             ws.onmessage = event => {
                 const data = JSON.parse(event.data);
 
@@ -887,6 +909,12 @@ export class DownloadManager {
                     return;
                 }
 
+                if (data.status === 'cancelled') {
+                    cancelled = true;
+                    this.loadingManager.setStatus(translate('modals.download.status.cancelled', {}, 'Download cancelled'));
+                    return;
+                }
+
                 if (data.status === 'progress' && data.download_id === downloadId) {
                     const metrics = {
                         bytesDownloaded: data.bytes_downloaded,
@@ -925,6 +953,10 @@ export class DownloadManager {
                 fileParams
             );
 
+            if (cancelled) {
+                return false;
+            }
+
             if (response?.skipped) {
                 this.loadingManager.setStatus(translate('modals.download.status.finalizing'));
                 updateProgress(100, 0, displayName);
@@ -965,8 +997,12 @@ export class DownloadManager {
 
             return true;
         } catch (error) {
-            console.error('Failed to download model version:', error);
-            showToast('toast.downloads.downloadError', { message: error?.message }, 'error');
+            if (cancelled) {
+                console.log('Download cancelled by user:', downloadId);
+            } else {
+                console.error('Failed to download model version:', error);
+                showToast('toast.downloads.downloadError', { message: error?.message }, 'error');
+            }
             return false;
         } finally {
             try {
@@ -986,16 +1022,33 @@ export class DownloadManager {
         const totalFiles = this.hfSelectedFiles.length;
         const updateProgress = this.loadingManager.showDownloadProgress(totalFiles);
 
+        let cancelled = false;
+        let currentDownloadId = null;
+
+        this.loadingManager.showCancelButton(async () => {
+            if (cancelled) return;
+            cancelled = true;
+            if (currentDownloadId) {
+                try {
+                    await this.apiClient.cancelDownload(currentDownloadId);
+                } catch (e) {
+                    console.error('Cancel request failed:', e);
+                }
+            }
+        });
+
         try {
             let completedDownloads = 0;
             for (let i = 0; i < totalFiles; i++) {
+                if (cancelled) break;
+
                 const filename = this.hfSelectedFiles[i];
                 updateProgress(0, completedDownloads, filename);
                 this.loadingManager.setStatus(`Downloading ${filename}...`);
 
-                const downloadId = Date.now().toString() + '_' + i;
+                currentDownloadId = Date.now().toString() + '_' + i;
                 const wsProtocol = window.location.protocol === 'https:' ? 'wss://' : 'ws://';
-                const ws = new WebSocket(`${wsProtocol}${window.location.host}/ws/download-progress?id=${downloadId}`);
+                const ws = new WebSocket(`${wsProtocol}${window.location.host}/ws/download-progress?id=${currentDownloadId}`);
 
                 try {
                     await new Promise((resolve, reject) => {
@@ -1003,12 +1056,13 @@ export class DownloadManager {
                         ws.onerror = reject;
                     });
 
-                    // Capture completed count at WS creation time so progress
-                    // updates arriving after completedDownloads increments still
-                    // show the correct "N / total" position.
                     const snapshotCompleted = completedDownloads;
                     ws.onmessage = (event) => {
                         const data = JSON.parse(event.data);
+                        if (data.status === 'cancelled') {
+                            cancelled = true;
+                            return;
+                        }
                         if (data.status === 'progress') {
                             const metrics = {
                                 bytesDownloaded: data.bytes_downloaded,
@@ -1026,9 +1080,11 @@ export class DownloadManager {
                         modelRoot,
                         relativePath: targetFolder,
                         useDefaultPaths,
-                        download_id: downloadId,
+                        download_id: currentDownloadId,
                     });
 
+                    if (cancelled) break;
+
                     if (response?.success) {
                         completedDownloads++;
                         updateProgress(100, completedDownloads, filename);
@@ -1038,13 +1094,19 @@ export class DownloadManager {
                 }
             }
 
-            showToast('toast.loras.downloadCompleted', {}, 'success');
-            // Reload page data — model is already in scanner cache via backend
+            if (cancelled) {
+                showToast('toast.downloads.downloadStopped', {}, 'info',
+                    `Download cancelled. ${completedDownloads} item(s) completed.`);
+            } else {
+                showToast('toast.loras.downloadCompleted', {}, 'success');
+            }
             await resetAndReload(true);
             return true;
         } catch (error) {
-            console.error('Failed to download HF model:', error);
-            showToast('toast.downloads.downloadError', { message: error?.message }, 'error');
+            if (!cancelled) {
+                console.error('Failed to download HF model:', error);
+                showToast('toast.downloads.downloadError', { message: error?.message }, 'error');
+            }
             return false;
         } finally {
             this.loadingManager.hide();
@@ -1077,7 +1139,7 @@ export class DownloadManager {
 
     showBatchPreviewStep() {
         document.querySelectorAll('.download-step').forEach(step => step.style.display = 'none');
-        document.getElementById('batchPreviewStep').style.display = 'block';
+        document.getElementById('batchPreviewStep').style.display = 'flex';
 
         const validCount = this.batchModels.filter(m => {
             if (m.error) return false;
@@ -1091,56 +1153,36 @@ export class DownloadManager {
         const list = document.getElementById('batchPreviewList');
         const hasHfItems = this.batchModels.some(m => m.source === 'huggingface' && !m.error);
 
-        let itemsHtml = this.batchModels.map((item, index) => {
-            if (item.error) {
-                return `
-                    <div class="batch-preview-item batch-preview-error" data-index="${index}">
-                        <div class="batch-preview-icon">
-                            <i class="fas fa-exclamation-triangle"></i>
-                        </div>
-                        <div class="batch-preview-info">
-                            <div class="batch-preview-name">${item.url}</div>
-                            <div class="batch-preview-meta batch-preview-error-text">${item.error}</div>
-                        </div>
-                        <button class="batch-preview-remove" data-index="${index}" title="${translate('common.actions.remove', {}, 'Remove')}">
-                            <i class="fas fa-times"></i>
-                        </button>
+        // Error items render flat, outside any group
+        const errorItemsHtml = this.batchModels.map((item, index) => {
+            if (!item.error) return null;
+            return `
+                <div class="batch-preview-item batch-preview-error" data-index="${index}">
+                    <div class="batch-preview-icon">
+                        <i class="fas fa-exclamation-triangle"></i>
                     </div>
-                `;
-            }
+                    <div class="batch-preview-info">
+                        <div class="batch-preview-name">${item.url}</div>
+                        <div class="batch-preview-meta batch-preview-error-text">${item.error}</div>
+                    </div>
+                    <button class="batch-preview-remove" data-index="${index}" title="${translate('common.actions.remove', {}, 'Remove')}">
+                        <i class="fas fa-times"></i>
+                    </button>
+                </div>
+            `;
+        }).filter(Boolean).join('');
 
+        // CivitAI items render flat, outside any group (unchanged)
+        const civitaiItemsHtml = this.batchModels.map((item, index) => {
+            if (item.error) return null;
+            if (item.source === 'huggingface') return null;
             const ver = item.selectedVersion;
-
-            // HF batch item rendering with checkbox
-            if (item.source === 'huggingface') {
-                const hfSize = item.fileSizeBytes
-                    ? formatFileSize(item.fileSizeBytes)
-                    : '?';
-                return `
-                    <div class="batch-preview-item" data-index="${index}">
-                        <input type="checkbox" class="batch-preview-checkbox"
-                               data-index="${index}" ${item.checked !== false ? 'checked' : ''} />
-                        <div class="batch-preview-info">
-                            <div class="batch-preview-name">${item.displayName || item.filename || `HF #${index}`} <span class="hf-badge">HF</span></div>
-                            <div class="batch-preview-meta">
-                                <span>${hfSize}</span>
-                                <span>${item.repo || ''}</span>
-                            </div>
-                        </div>
-                        <button class="batch-preview-remove" data-index="${index}" title="${translate('common.actions.remove', {}, 'Remove')}">
-                            <i class="fas fa-times"></i>
-                        </button>
-                    </div>
-                `;
-            }
-
             const firstImage = ver?.images?.find(img => !img.url.endsWith('.mp4'));
             const thumbnailUrl = firstImage ? firstImage.url : '/loras_static/images/no-preview.png';
             const fileSize = ver?.modelSizeKB
                 ? (ver.modelSizeKB / 1024).toFixed(1)
                 : (ver?.files?.[0]?.sizeKB ? (ver.files[0].sizeKB / 1024).toFixed(1) : '?');
             const existsLocally = ver?.existsLocally;
-
             return `
                 <div class="batch-preview-item ${existsLocally ? 'batch-preview-local' : ''}" data-index="${index}">
                     <div class="batch-preview-thumbnail">
@@ -1161,8 +1203,59 @@ export class DownloadManager {
                     ` : ''}
                 </div>
             `;
+        }).filter(Boolean).join('');
+
+        // Group HF items by repo (data model stays flat — only rendering groups)
+        const hfGroups = {};
+        this.batchModels.forEach((item, index) => {
+            if (item.error || item.source !== 'huggingface') return;
+            const repo = item.repo || 'unknown';
+            if (!hfGroups[repo]) hfGroups[repo] = [];
+            hfGroups[repo].push({ item, index });
+        });
+
+        const renderHfItem = ({ item, index }) => {
+            const hfSize = item.fileSizeBytes ? formatFileSize(item.fileSizeBytes) : '?';
+            return `
+                <div class="batch-preview-item" data-index="${index}">
+                    <input type="checkbox" class="batch-preview-checkbox"
+                           data-index="${index}" ${item.checked !== false ? 'checked' : ''} />
+                    <div class="batch-preview-info">
+                        <div class="batch-preview-name">${item.displayName || item.filename || `HF #${index}`} <span class="hf-badge">HF</span></div>
+                        <div class="batch-preview-meta">
+                            <span>${hfSize}</span>
+                            <span>${item.repo || ''}</span>
+                        </div>
+                    </div>
+                    <button class="batch-preview-remove" data-index="${index}" title="${translate('common.actions.remove', {}, 'Remove')}">
+                        <i class="fas fa-times"></i>
+                    </button>
+                </div>
+            `;
+        };
+
+        const hfGroupsHtml = Object.keys(hfGroups).map(repo => {
+            const items = hfGroups[repo];
+            const isCollapsed = this.hfRepoCollapsed[repo] === true;
+            const allChecked = items.every(({ item }) => item.checked !== false);
+            const fileCount = items.length;
+            return `
+                <div class="batch-preview-group" data-repo="${repo}">
+                    <div class="batch-preview-group-header">
+                        <i class="fas fa-chevron-right batch-preview-group-toggle ${isCollapsed ? '' : 'expanded'}"></i>
+                        <span class="batch-preview-group-name">${repo}</span>
+                        <span class="batch-preview-group-count">${fileCount} ${translate('modals.download.fileSelection.files', {}, 'files')}</span>
+                        <input type="checkbox" class="batch-preview-group-select-all" data-repo="${repo}" ${allChecked ? 'checked' : ''} />
+                    </div>
+                    <div class="batch-preview-group-body ${isCollapsed ? '' : 'expanded'}">
+                        ${items.map(renderHfItem).join('')}
+                    </div>
+                </div>
+            `;
         }).join('');
 
+        let itemsHtml = errorItemsHtml + civitaiItemsHtml + hfGroupsHtml;
+
         // Prepend select-all toolbar if there are HF items with checkboxes
         if (hasHfItems) {
             const allChecked = this.batchModels
@@ -1178,7 +1271,90 @@ export class DownloadManager {
 
         list.innerHTML = itemsHtml;
 
+        const updateCountAndSelectAll = () => {
+            const checkedCount = this.batchModels.filter(
+                m => !m.error && m.checked !== false
+            ).length;
+            document.getElementById('downloadModalTitle').textContent =
+                translate('modals.download.titleWithType', { type: this.apiClient.apiConfig.config.displayName }) +
+                ` (${checkedCount})`;
+            const nextBtn = document.getElementById('nextFromBatchBtn');
+            nextBtn.disabled = checkedCount === 0;
+            nextBtn.classList.toggle('disabled', checkedCount === 0);
+            // Global select-all
+            const selectAll = document.getElementById('batchSelectAll');
+            if (selectAll) {
+                const hfItems = this.batchModels.filter(m => m.source === 'huggingface' && !m.error);
+                selectAll.checked = hfItems.length > 0 && hfItems.every(m => m.checked !== false);
+            }
+            // Per-group select-all
+            list.querySelectorAll('.batch-preview-group-select-all').forEach(gsa => {
+                const repo = gsa.dataset.repo;
+                const repoItems = this.batchModels.filter(m => m.source === 'huggingface' && !m.error && m.repo === repo);
+                gsa.checked = repoItems.length > 0 && repoItems.every(m => m.checked !== false);
+            });
+        };
+
         list.onclick = (e) => {
+            // Per-group select-all checkbox
+            const groupSelectAll = e.target.closest('.batch-preview-group-select-all');
+            if (groupSelectAll) {
+                const repo = groupSelectAll.dataset.repo;
+                const checked = groupSelectAll.checked;
+                this.batchModels.forEach((m, idx) => {
+                    if (m.source === 'huggingface' && !m.error && m.repo === repo) {
+                        m.checked = checked;
+                        const cb = list.querySelector(`.batch-preview-checkbox[data-index="${idx}"]`);
+                        if (cb) cb.checked = checked;
+                    }
+                });
+                updateCountAndSelectAll();
+                return;
+            }
+
+            const header = e.target.closest('.batch-preview-group-header');
+            if (header) {
+                const group = header.closest('.batch-preview-group');
+                const repo = group.dataset.repo;
+                const body = group.querySelector('.batch-preview-group-body');
+                const toggle = group.querySelector('.batch-preview-group-toggle');
+                const isCollapsed = this.hfRepoCollapsed[repo];
+                if (isCollapsed) {
+                    this.hfRepoCollapsed[repo] = false;
+                    body.style.transition = ''; // restore in case collapse was interrupted
+                    body.classList.add('expanded');
+                    toggle.classList.add('expanded');
+                    // force reflow so expanded class is registered before setting height
+                    void body.offsetHeight;
+                    body.style.maxHeight = body.scrollHeight + 'px';
+                    const onEnd = (e) => {
+                        if (e.propertyName !== 'max-height') return;
+                        if (this.hfRepoCollapsed[repo] !== false) return;
+                        body.style.maxHeight = ''; // fall back to .expanded's 9999px
+                        body.removeEventListener('transitionend', onEnd);
+                    };
+                    body.addEventListener('transitionend', onEnd);
+                } else {
+                    this.hfRepoCollapsed[repo] = true;
+                    body.style.maxHeight = body.scrollHeight + 'px';
+                    requestAnimationFrame(() => {
+                        // animate only max-height; keep expanded so opacity stays 1
+                        body.style.transition = 'max-height 0.35s ease';
+                        body.style.maxHeight = '0';
+                        toggle.classList.remove('expanded');
+                        const onEnd = (e) => {
+                            if (e.propertyName !== 'max-height') return;
+                            if (this.hfRepoCollapsed[repo] !== true) return; // state changed since
+                            body.classList.remove('expanded');
+                            body.style.transition = '';
+                            body.removeEventListener('transitionend', onEnd);
+                        };
+                        body.addEventListener('transitionend', onEnd);
+                    });
+                }
+                return;
+            }
+
             const removeBtn = e.target.closest('.batch-preview-remove');
             if (removeBtn) {
                 const idx = parseInt(removeBtn.dataset.index);
@@ -1193,7 +1369,7 @@ export class DownloadManager {
             }
         };
 
-        // Checkbox handler for HF batch items
+        // Individual HF checkbox handler
         const checkboxes = list.querySelectorAll('.batch-preview-checkbox');
         checkboxes.forEach(cb => {
             cb.addEventListener('change', (e) => {
@@ -1201,26 +1377,11 @@ export class DownloadManager {
                 if (this.batchModels[idx]) {
                     this.batchModels[idx].checked = e.target.checked;
                 }
-                // Update valid count in title and Next button
-                const checkedCount = this.batchModels.filter(
-                    m => !m.error && m.checked !== false
-                ).length;
-                document.getElementById('downloadModalTitle').textContent =
-                    translate('modals.download.titleWithType', { type: this.apiClient.apiConfig.config.displayName }) +
-                    ` (${checkedCount})`;
-                const nextBtn = document.getElementById('nextFromBatchBtn');
-                nextBtn.disabled = checkedCount === 0;
-                nextBtn.classList.toggle('disabled', checkedCount === 0);
-                // Update select-all checkbox state
-                const selectAll = document.getElementById('batchSelectAll');
-                if (selectAll) {
-                    const hfItems = this.batchModels.filter(m => m.source === 'huggingface' && !m.error);
-                    selectAll.checked = hfItems.length > 0 && hfItems.every(m => m.checked !== false);
-                }
+                updateCountAndSelectAll();
             });
         });
 
-        // Select-all handler
+        // Global select-all handler
         const selectAll = document.getElementById('batchSelectAll');
         if (selectAll) {
             selectAll.addEventListener('change', (e) => {
@@ -1233,16 +1394,7 @@ export class DownloadManager {
                         this.batchModels[idx].checked = checked;
                     }
                 });
-                // Update valid count in title and Next button
-                const checkedCount = this.batchModels.filter(
-                    m => !m.error && m.checked !== false
-                ).length;
-                document.getElementById('downloadModalTitle').textContent =
-                    translate('modals.download.titleWithType', { type: this.apiClient.apiConfig.config.displayName }) +
-                    ` (${checkedCount})`;
-                const nextBtn = document.getElementById('nextFromBatchBtn');
-                nextBtn.disabled = checkedCount === 0;
-                nextBtn.classList.toggle('disabled', checkedCount === 0);
+                updateCountAndSelectAll();
             });
         }
 
@@ -1333,12 +1485,23 @@ export class DownloadManager {
             }
 
             const fileParams = this.selectedFile ? {
+                id: this.selectedFile.id,
                 type: this.selectedFile.type || 'Model',
-                format: this.selectedFile.metadata?.format || 'SafeTensor',
-                size: this.selectedFile.metadata?.size || 'full',
-                fp: this.selectedFile.metadata?.fp,
+                format: this.selectedFile.metadata?.format || null,
+                size: this.selectedFile.metadata?.size || null,
+                fp: this.selectedFile.metadata?.fp || null,
             } : null;
 
+            if (fileParams) {
+                console.log('[download] startDownload (single): fileParams built from selectedFile — id=%s, type=%s, format=%s, size=%s, fp=%s',
+                    fileParams.id, fileParams.type, fileParams.format, fileParams.size, fileParams.fp);
+            } else {
+                console.log('[download] startDownload (single): this.selectedFile is null — no file selection, will download primary/default file. version=%s has %d files',
+                    this.currentVersion?.id, (this.currentVersion?.files || []).length);
+            }
+
+            modalManager.closeModal('downloadModal');
+
             return this.executeDownloadWithProgress({
                 modelId: this.modelId,
                 versionId: this.currentVersion.id,
@@ -1377,11 +1540,27 @@ export class DownloadManager {
 
         let completedDownloads = 0;
         let failedDownloads = 0;
+        let cancelled = false;
+
+        loadingManager.showCancelButton(async () => {
+            if (cancelled) return;
+            cancelled = true;
+            try {
+                await this.apiClient.cancelDownload(batchDownloadId);
+            } catch (e) {
+                console.error('Cancel request failed:', e);
+            }
+        });
 
         ws.onmessage = (event) => {
             const data = JSON.parse(event.data);
             if (data.type === 'download_id') return;
 
+            if (data.status === 'cancelled') {
+                cancelled = true;
+                return;
+            }
+
             if (data.status === 'progress' && data.download_id?.startsWith(batchDownloadId)) {
                 const current = downloadItems[completedDownloads + failedDownloads];
                 const name = current?.selectedVersion?.name || current?.displayName || current?.filename || `#${completedDownloads + failedDownloads + 1}`;
@@ -1400,6 +1579,8 @@ export class DownloadManager {
         });
 
         for (let i = 0; i < downloadItems.length; i++) {
+            if (cancelled) break;
+
             const item = downloadItems[i];
             const name = item.displayName || item.filename || (item.selectedVersion?.name || `Model #${item.modelId}`);
             const isHf = item.source === 'huggingface';
@@ -1410,7 +1591,6 @@ export class DownloadManager {
             try {
                 let response;
                 if (isHf) {
-                    // Per-file WebSocket for real-time progress
                     const downloadId = Date.now().toString() + '_hf_' + i;
                     const wsHf = new WebSocket(`${wsProtocol}${window.location.host}/ws/download-progress?id=${downloadId}`);
                     try {
@@ -1444,6 +1624,8 @@ export class DownloadManager {
                         wsHf.close();
                     }
                 } else {
+                    console.log('[download] batch download: fileParams NOT passed for modelId=%s, versionId=%s — backend will use primary file',
+                        item.modelId, item.selectedVersion?.id);
                     response = await this.apiClient.downloadModel(
                         item.modelId,
                         item.selectedVersion.id,
@@ -1455,6 +1637,8 @@ export class DownloadManager {
                     );
                 }
 
+                if (cancelled) break;
+
                 if (!response.success) {
                     failedDownloads++;
                 } else {
@@ -1462,15 +1646,20 @@ export class DownloadManager {
                     updateProgress(100, completedDownloads, '');
                 }
             } catch (err) {
-                console.error(`Failed to download ${name}:`, err);
-                failedDownloads++;
+                if (!cancelled) {
+                    console.error(`Failed to download ${name}:`, err);
+                    failedDownloads++;
+                }
             }
         }
 
         ws.close();
         loadingManager.hide();
 
-        if (failedDownloads === 0) {
+        if (cancelled) {
+            showToast('toast.downloads.downloadStopped', {}, 'info',
+                `Download cancelled. ${completedDownloads} item(s) completed.`);
+        } else if (failedDownloads === 0) {
             showToast('toast.loras.allDownloadSuccessful', { count: completedDownloads }, 'success');
         } else {
             showToast('toast.loras.downloadPartialSuccess', {
@@ -1488,6 +1677,10 @@ export class DownloadManager {
         modelRoot = '',
         targetFolder = ''
     } = {}) {
+        console.warn('[download] downloadVersionWithDefaults: NO fileParams will be sent — backend will always use primary file. '
+            + 'modelType=%s, modelId=%s, versionId=%s, versionName="%s"',
+            modelType, modelId, versionId, versionName);
+
         try {
             this.apiClient = getModelApiClient(modelType);
         } catch (error) {

static/js/managers/LoadingManager.js

@@ -281,6 +281,10 @@ export class LoadingManager {
         // Initialize transfer stats with empty data
         updateTransferStats();
 
+        if (this.cancelButton) {
+            this.loadingContent.appendChild(this.cancelButton);
+        }
+
         // Return update function
         return (currentProgress, currentIndex = 0, currentName = '', metrics = {}) => {
             // Update current item progress

static/js/managers/ModalManager.js

@@ -264,6 +264,19 @@ export class ModalManager {
             });
         }
 
+        // Add linkHfModal registration
+        const linkHfModal = document.getElementById('linkHfModal');
+        if (linkHfModal) {
+            this.registerModal('linkHfModal', {
+                element: linkHfModal,
+                onClose: () => {
+                    this.getModal('linkHfModal').element.style.display = 'none';
+                    document.body.classList.remove('modal-open');
+                },
+                closeOnOutsideClick: true
+            });
+        }
+
         // Add exampleAccessModal registration
         const exampleAccessModal = document.getElementById('exampleAccessModal');
         if (exampleAccessModal) {

static/js/managers/MoveManager.js

@@ -330,8 +330,9 @@ class MoveManager {
                     .filter(r => r.success)
                     .map(r => ({ original_file_path: r.original_file_path, new_file_path: r.new_file_path }));
 
-                // Deselect moving items
+                // Deselect moving items and exit bulk mode
                 this.bulkFilePaths.forEach(path => bulkManager.deselectItem(path));
+                if (state.bulkMode) bulkManager.toggleBulkMode();
             } else {
                 // Single move mode
                 const result = await apiClient.moveSingleModel(this.currentFilePath, targetPath, this.useDefaultPath);

static/js/managers/SettingsManager.js

@@ -1693,13 +1693,15 @@ export class SettingsManager {
                 <input type="text" class="extra-folder-path-input"
                        placeholder="${translate('settings.extraFolderPaths.pathPlaceholder', {}, '/path/to/models')}" value="${path}"
                        onblur="settingsManager.updateExtraFolderPaths('${modelType}')"
+                       onfocus="settingsManager.clearExtraFolderPathError(this)"
                        onkeydown="if(event.key === 'Enter') { this.blur(); }" />
                 <button type="button" class="remove-path-btn"
-                        onclick="this.parentElement.parentElement.remove(); settingsManager.updateExtraFolderPaths('${modelType}')"
+                        onclick="settingsManager.removeExtraFolderPathRow(this, '${modelType}')"
                         title="${translate('common.actions.delete', {}, 'Delete')}">
                     <i class="fas fa-times"></i>
                 </button>
             </div>
+            <div class="extra-folder-path-error"></div>
         `;
 
         container.appendChild(row);
@@ -1713,7 +1715,63 @@ export class SettingsManager {
         }
     }
 
+    clearExtraFolderPathError(input) {
+        input.classList.remove('has-error');
+        const row = input.closest('.extra-folder-path-row');
+        if (row) {
+            const errEl = row.querySelector('.extra-folder-path-error');
+            if (errEl) {
+                errEl.classList.remove('visible');
+                errEl.textContent = '';
+            }
+        }
+    }
+
+    _clearAllExtraFolderPathErrors() {
+        document.querySelectorAll('.extra-folder-path-input.has-error').forEach((input) => {
+            input.classList.remove('has-error');
+        });
+        document.querySelectorAll('.extra-folder-path-error.visible').forEach((el) => {
+            el.classList.remove('visible');
+            el.textContent = '';
+        });
+    }
+
+    _markExtraFolderPathsError(modelType, overlappingPaths, showMessage = false) {
+        const container = document.getElementById(`extraFolderPaths-${modelType}`);
+        if (!container) return;
+
+        const inputs = container.querySelectorAll('.extra-folder-path-input');
+        inputs.forEach((input) => {
+            const val = input.value.trim();
+            if (val && overlappingPaths.includes(val)) {
+                input.classList.add('has-error');
+                if (showMessage) {
+                    const row = input.closest('.extra-folder-path-row');
+                    if (row) {
+                        const errEl = row.querySelector('.extra-folder-path-error');
+                        if (errEl) {
+                            errEl.textContent = translate('settings.extraFolderPaths.validation.checkpointUnetOverlapInline', {}, 'This path is also used for a different model type. Use separate folders for checkpoints and diffusion models.');
+                            errEl.classList.add('visible');
+                        }
+                    }
+                }
+            }
+        });
+    }
+
+    removeExtraFolderPathRow(btn, modelType) {
+        const row = btn.closest('.extra-folder-path-row');
+        if (row) {
+            row.remove();
+            this.updateExtraFolderPaths(modelType);
+        }
+    }
+
     async updateExtraFolderPaths(changedModelType) {
+        // Clear previous errors
+        this._clearAllExtraFolderPathErrors();
+
         const extraFolderPaths = {};
 
         // Collect paths for all model types
@@ -1734,6 +1792,32 @@ export class SettingsManager {
             extraFolderPaths[modelType] = paths;
         });
 
+        // Client-side pre-check: checkpoints and unet must not share the same path.
+        // Normalise paths to reduce false negatives vs the backend's realpath + normcase.
+        const normalise = (p) => p.replace(/[/\\]+$/, '').toLowerCase();
+        const ckptSet = new Set((extraFolderPaths.checkpoints || []).map(normalise));
+        const unetSet = new Set((extraFolderPaths.unet || []).map(normalise));
+        const ckptOverlap = (extraFolderPaths.checkpoints || []).filter(p => p && unetSet.has(normalise(p)));
+        const unetOverlap = (extraFolderPaths.unet || []).filter(p => p && ckptSet.has(normalise(p)));
+        const hasOverlap = ckptOverlap.length > 0 || unetOverlap.length > 0;
+
+        if (hasOverlap) {
+            // Error message only on the side the user just edited.
+            // The other side gets red border only (passive conflict indicator).
+            if (changedModelType === 'checkpoints') {
+                this._markExtraFolderPathsError('checkpoints', ckptOverlap, true);
+                this._markExtraFolderPathsError('unet', unetOverlap, false);
+            } else if (changedModelType === 'unet') {
+                this._markExtraFolderPathsError('unet', unetOverlap, true);
+                this._markExtraFolderPathsError('checkpoints', ckptOverlap, false);
+            } else {
+                // Pre-existing conflict from direct config edit — mark both without messages
+                this._markExtraFolderPathsError('checkpoints', ckptOverlap, false);
+                this._markExtraFolderPathsError('unet', unetOverlap, false);
+            }
+            return;
+        }
+
         // Check if paths have actually changed
         const currentPaths = state.global.settings.extra_folder_paths || {};
         const pathsChanged = JSON.stringify(currentPaths) !== JSON.stringify(extraFolderPaths);

static/js/managers/import/DownloadManager.js

@@ -168,6 +168,18 @@ export class DownloadManager {
         let failedDownloads = 0;
         let accessFailures = 0;
         let currentLoraProgress = 0;
+        let cancelled = false;
+
+        this.importManager.loadingManager.showCancelButton(async () => {
+            if (cancelled) return;
+            cancelled = true;
+            try {
+                const loraClient = getModelApiClient(MODEL_TYPES.LORA);
+                await loraClient.cancelDownload(batchDownloadId);
+            } catch (e) {
+                console.error('Cancel request failed:', e);
+            }
+        });
 
         // Set up progress tracking for current download
         ws.onmessage = (event) => {
@@ -179,6 +191,11 @@ export class DownloadManager {
                 return;
             }
 
+            if (data.status === 'cancelled') {
+                cancelled = true;
+                return;
+            }
+
             // Process progress updates for our current active download
             if (data.status === 'progress' && data.download_id && data.download_id.startsWith(batchDownloadId)) {
                 // Update current LoRA progress
@@ -221,6 +238,8 @@ export class DownloadManager {
         const useDefaultPaths = getStorageItem('use_default_path_loras', false);
 
         for (let i = 0; i < this.importManager.downloadableLoRAs.length; i++) {
+            if (cancelled) break;
+
             const lora = this.importManager.downloadableLoRAs[i];
 
             // Reset current LoRA progress for new download
@@ -241,15 +260,13 @@ export class DownloadManager {
                     batchDownloadId
                 );
 
+                if (cancelled) break;
+
                 if (!response.success) {
                     console.error(`Failed to download LoRA ${lora.name}: ${response.error}`);
-
                     failedDownloads++;
-                    // Continue with next download
                 } else {
                     completedDownloads++;
-
-                    // Update progress to show completion of current LoRA
                     updateProgress(100, completedDownloads, '');
 
                     if (completedDownloads + failedDownloads < this.importManager.downloadableLoRAs.length) {
@@ -259,9 +276,10 @@ export class DownloadManager {
                     }
                 }
             } catch (downloadError) {
-                console.error(`Error downloading LoRA ${lora.name}:`, downloadError);
-                failedDownloads++;
-                // Continue with next download
+                if (!cancelled) {
+                    console.error(`Error downloading LoRA ${lora.name}:`, downloadError);
+                    failedDownloads++;
+                }
             }
         }
 
@@ -269,7 +287,10 @@ export class DownloadManager {
         ws.close();
 
         // Show appropriate completion message based on results
-        if (failedDownloads === 0) {
+        if (cancelled) {
+            showToast('toast.downloads.downloadStopped', {}, 'info',
+                `Download cancelled. ${completedDownloads} item(s) completed.`);
+        } else if (failedDownloads === 0) {
             showToast('toast.loras.allDownloadSuccessful', { count: completedDownloads }, 'success');
         } else {
             if (accessFailures > 0) {

static/js/utils/uiHelpers.js

@@ -552,6 +552,8 @@ async function fetchWorkflowRegistry() {
     if (!registryData.success) {
       if (registryData.error === 'Standalone Mode Active') {
         showToast('toast.general.cannotInteractStandalone', {}, 'warning');
+      } else if (registryData.error === 'Empty Registry') {
+        showToast('uiHelpers.workflow.noSupportedNodes', {}, 'warning');
       } else {
         showToast('toast.general.failedWorkflowInfo', {}, 'error');
       }
@@ -1482,3 +1484,40 @@ export async function openExampleImagesFolder(modelHash) {
     return false;
   }
 }
+
+/**
+ * Set up a paste handler on a textarea that automatically appends a newline
+ * after pasted content that looks like a URL (http/https). This lets users
+ * paste multiple URLs one after another without manually pressing Enter.
+ * @param {string} textareaId - The id of the textarea element
+ */
+export function setupAutoNewlineOnPaste(textareaId) {
+  const el = document.getElementById(textareaId);
+  if (!el || el.tagName !== 'TEXTAREA') return;
+
+  el.addEventListener('paste', (e) => {
+    const pastedText = (e.clipboardData || window.clipboardData).getData('text');
+    // Only apply to text that starts with http:// or https://
+    if (/^https?:\/\//.test(pastedText) && !pastedText.endsWith('\n')) {
+      e.preventDefault();
+
+      const start = el.selectionStart;
+      const end = el.selectionEnd;
+      const text = el.value;
+      const before = text.substring(0, start);
+      const after = text.substring(end);
+
+      // Append newline after the pasted URL
+      const modifiedText = pastedText + '\n';
+      el.value = before + modifiedText + after;
+
+      // Move cursor to just after the inserted text
+      const newCursorPos = start + modifiedText.length;
+      el.selectionStart = el.selectionEnd = newCursorPos;
+
+      // Trigger input event so any listeners stay in sync
+      el.dispatchEvent(new Event('input', { bubbles: true }));
+    }
+    // Non-URL text or text already ending with \n — let default paste happen
+  });
+}

templates/checkpoints.html

@@ -12,7 +12,19 @@
 <div id="checkpointContextMenu" class="context-menu" style="display: none;">
     <!-- Metadata -->
     <div class="context-menu-item" data-action="refresh-metadata"><i class="fas fa-sync"></i> {{ t('loras.contextMenu.refreshMetadata') }}</div>
-    <div class="context-menu-item" data-action="relink-civitai"><i class="fas fa-link"></i> {{ t('loras.contextMenu.relinkCivitai') }}</div>
+    <div class="context-menu-item has-submenu" data-has-submenu="link-model">
+        <i class="fas fa-link"></i>
+        <span>{{ t('loras.contextMenu.linkModel') }}</span>
+        <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="relink-civitai">
+                <i class="fas fa-external-link-alt"></i> <span>{{ t('loras.contextMenu.linkCivitai') }}</span>
+            </div>
+            <div class="context-menu-item" data-action="link-hf">
+                <i class="fas fa-robot"></i> <span>{{ t('loras.contextMenu.linkHuggingFace') }}</span>
+            </div>
+        </div>
+    </div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Workflow -->
     <div class="context-menu-item" data-action="copyname"><i class="fas fa-copy"></i> {{ t('loras.contextMenu.copyFilename') }}</div>

templates/components/context_menu.html

@@ -12,8 +12,18 @@
     <div class="context-menu-item" data-action="check-updates">
         <i class="fas fa-bell"></i> <span>{{ t('loras.contextMenu.checkUpdates') }}</span>
     </div>
-    <div class="context-menu-item" data-action="relink-civitai">
-        <i class="fas fa-link"></i> <span>{{ t('loras.contextMenu.relinkCivitai') }}</span>
+    <div class="context-menu-item has-submenu" data-has-submenu="link-model">
+        <i class="fas fa-link"></i>
+        <span>{{ t('loras.contextMenu.linkModel') }}</span>
+        <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="relink-civitai">
+                <i class="fas fa-external-link-alt"></i> <span>{{ t('loras.contextMenu.linkCivitai') }}</span>
+            </div>
+            <div class="context-menu-item" data-action="link-hf">
+                <i class="fas fa-robot"></i> <span>{{ t('loras.contextMenu.linkHuggingFace') }}</span>
+            </div>
+        </div>
     </div>
     <div class="context-menu-item" data-action="enrich-hf-llm">
         <i class="fas fa-wand-magic-sparkles"></i> <span>{{ t('loras.contextMenu.enrichHfAgent') }}</span>

templates/components/modals.html

@@ -8,6 +8,7 @@
 {% include 'components/modals/update_modal.html' %}
 {% include 'components/modals/help_modal.html' %}
 {% include 'components/modals/relink_civitai_modal.html' %}
+{% include 'components/modals/link_hf_modal.html' %}
 {% include 'components/modals/example_access_modal.html' %}
 {% include 'components/modals/download_modal.html' %}
 {% include 'components/modals/move_modal.html' %}

templates/components/modals/help_modal.html

@@ -112,6 +112,10 @@
                             <a href="https://github.com/willmiao/ComfyUI-Lora-Manager/wiki/Priority-Tags-Configuration-Guide" target="_blank">
                                 Priority Tags Configuration Guide
                                 <span class="new-content-badge inline">{{ t('help.documentation.newBadge') }}</span>
+                        <li>
+                            <a href="https://github.com/willmiao/ComfyUI-Lora-Manager/wiki/AI-Provider-Setup" target="_blank">
+                                AI Provider Setup
+                                <span class="new-content-badge inline">{{ t('help.documentation.newBadge') }}</span>
                             </a>
                         </li>
                     </ul>

templates/components/modals/link_hf_modal.html

@@ -0,0 +1,24 @@
+<!-- Link to HuggingFace Modal -->
+<div id="linkHfModal" class="modal">
+    <div class="modal-content">
+        <button class="close" onclick="modalManager.closeModal('linkHfModal')">&times;</button>
+        <h2>{{ t('modals.linkHuggingFace.title') }}</h2>
+        <div class="warning-box">
+            <i class="fas fa-info-circle"></i>
+            <p>{{ t('modals.linkHuggingFace.infoText') }}</p>
+        </div>
+        <div class="input-group">
+            <label for="hfModelUrl">{{ t('modals.linkHuggingFace.urlLabel') }}</label>
+            <input type="text" id="hfModelUrl" placeholder="{{ t('modals.linkHuggingFace.urlPlaceholder') }}" />
+            <div class="input-error" id="hfModelUrlError"></div>
+            <div class="input-help">
+                {{ t('modals.linkHuggingFace.helpText') }}<br>
+                <strong>https://huggingface.co/user/repo</strong>
+            </div>
+        </div>
+        <div class="modal-actions">
+            <button class="cancel-btn" onclick="modalManager.closeModal('linkHfModal')">{{ t('common.actions.cancel') }}</button>
+            <button class="confirm-btn" id="confirmLinkHfBtn">{{ t('modals.linkHuggingFace.confirmAction') }}</button>
+        </div>
+    </div>
+</div>

templates/embeddings.html

@@ -12,7 +12,19 @@
 <div id="embeddingContextMenu" class="context-menu" style="display: none;">
     <!-- Metadata -->
     <div class="context-menu-item" data-action="refresh-metadata"><i class="fas fa-sync"></i> {{ t('loras.contextMenu.refreshMetadata') }}</div>
-    <div class="context-menu-item" data-action="relink-civitai"><i class="fas fa-link"></i> {{ t('loras.contextMenu.relinkCivitai') }}</div>
+    <div class="context-menu-item has-submenu" data-has-submenu="link-model">
+        <i class="fas fa-link"></i>
+        <span>{{ t('loras.contextMenu.linkModel') }}</span>
+        <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="relink-civitai">
+                <i class="fas fa-external-link-alt"></i> <span>{{ t('loras.contextMenu.linkCivitai') }}</span>
+            </div>
+            <div class="context-menu-item" data-action="link-hf">
+                <i class="fas fa-robot"></i> <span>{{ t('loras.contextMenu.linkHuggingFace') }}</span>
+            </div>
+        </div>
+    </div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Workflow -->
     <div class="context-menu-item" data-action="copyname"><i class="fas fa-copy"></i> {{ t('loras.contextMenu.copyFilename') }}</div>

tests/frontend/utils/hfUrlDetection.test.js

@@ -62,6 +62,20 @@ describe('DownloadManager.detectUrlType — HF URL detection', () => {
         expect(result).toEqual({ type: 'civitai' });
     });
 
+    it('detects CivitAI URL on civitai.red domain', () => {
+        const result = DownloadManager.detectUrlType(
+            'https://civitai.red/models/12345/my-model'
+        );
+        expect(result).toEqual({ type: 'civitai' });
+    });
+
+    it('detects CivitAI URL on civitai.green domain', () => {
+        const result = DownloadManager.detectUrlType(
+            'https://civitai.green/models/67890/another-model'
+        );
+        expect(result).toEqual({ type: 'civitai' });
+    });
+
     it('detects CivArchive URL', () => {
         const result = DownloadManager.detectUrlType(
             'https://civarchive.com/models/456'

tests/routes/test_misc_routes.py

@@ -728,6 +728,54 @@ async def test_register_nodes_includes_capabilities():
     assert stored_node["widget_names"] == ["ckpt_name"]
 
 
+@pytest.mark.asyncio
+async def test_register_nodes_accepts_compound_node_ids():
+    """Subgraph nodes from expanded group nodes have compound IDs like '252:0'."""
+    node_registry = NodeRegistry()
+    handler = NodeRegistryHandler(
+        node_registry=node_registry,
+        prompt_server=FakePromptServer,
+        standalone_mode=False,
+    )
+
+    request = FakeRequest(
+        json_data={
+            "nodes": [
+                {
+                    "node_id": "252:0",
+                    "graph_id": "252",
+                    "type": "CheckpointLoaderSimple",
+                    "title": "Checkpoint Loader (subgraph)",
+                },
+                {
+                    "node_id": "252:1",
+                    "graph_id": "252",
+                    "type": "CLIPLoader",
+                    "title": "CLIP Loader (subgraph)",
+                },
+            ],
+            "client_id": "test-client-1",
+        }
+    )
+
+    response = await handler.register_nodes(request)
+    payload = json.loads(response.text)
+
+    assert response.status == 200
+    assert payload["success"] is True
+    assert "2 nodes registered" in payload["message"]
+
+    registry = await node_registry.get_merged_registry()
+    assert registry["node_count"] == 2
+
+    nodes_map = registry["nodes"]
+    assert "252:0" in nodes_map
+    assert "252:1" in nodes_map
+    assert nodes_map["252:0"]["id"] == 0
+    assert nodes_map["252:0"]["graph_id"] == "252"
+    assert nodes_map["252:1"]["id"] == 1
+
+
 @pytest.mark.asyncio
 async def test_update_node_widget_sends_payload():
     send_calls: list[tuple[str, dict]] = []

tests/services/test_example_images_download_manager_async.py

@@ -164,7 +164,7 @@ async def test_pause_resume_blocks_processing(
             await first_release.wait()
         else:
             second_call_started.set()
-        return True, False, []
+        return True, False, [], []
 
     async def fake_get_downloader():
         class _Downloader:
@@ -288,7 +288,7 @@ async def test_legacy_folder_migrated_and_skipped(
     async def fake_download_model_images(*_args, **_kwargs):
         nonlocal download_called
         download_called = True
-        return True, False, []
+        return True, False, [], []
 
     async def fake_get_downloader():
         class _Downloader:

tests/services/test_issue_760_repro.py

@@ -77,7 +77,7 @@ async def test_reprocessing_triggered_when_folder_missing(monkeypatch, tmp_path)
         model_dir = args[3]
         Path(model_dir).mkdir(parents=True, exist_ok=True)
         (Path(model_dir) / "image_0.png").write_text("fixed")
-        return True, False, []
+        return True, False, [], []
         
     monkeypatch.setattr(download_module.ExampleImagesProcessor, "download_model_images_with_tracking", fake_download_model_images)
     

tests/utils/test_settings_paths.py

@@ -0,0 +1,56 @@
+"""Tests for settings path resolution."""
+
+import json
+import logging
+import os
+
+import pytest
+
+from py.utils.settings_paths import _should_use_portable_settings
+
+
+class TestShouldUsePortableSettings:
+    """Tests for _should_use_portable_settings()."""
+
+    @pytest.mark.parametrize(
+        "env_value, settings_flag, expected",
+        [
+            ("1", False, True),   # env = 1 overrides settings.json false
+            ("1", True, True),    # env = 1 matches settings.json true
+            ("0", False, False),  # env = 0 → rely on settings.json
+            ("0", True, True),    # env = 0 → rely on settings.json
+            ("", False, False),   # unset → rely on settings.json
+            ("", True, True),     # unset → rely on settings.json
+        ],
+    )
+    def test_env_var_overrides_settings(self, tmp_path, env_value, settings_flag, expected):
+        """The LORA_MANAGER_PORTABLE env var takes precedence over settings.json."""
+        settings_file = tmp_path / "settings.json"
+        settings_file.write_text(
+            json.dumps({"use_portable_settings": settings_flag})
+        )
+
+        with pytest.MonkeyPatch.context() as mp:
+            if env_value:
+                mp.setenv("LORA_MANAGER_PORTABLE", env_value)
+            else:
+                mp.delenv("LORA_MANAGER_PORTABLE", raising=False)
+
+            result = _should_use_portable_settings(str(settings_file), logging.getLogger())
+            assert result == expected
+
+    def test_missing_file_without_env(self, tmp_path):
+        """Without env var, missing settings file returns False."""
+        missing = tmp_path / "nonexistent.json"
+
+        result = _should_use_portable_settings(str(missing), logging.getLogger())
+        assert result is False
+
+    def test_missing_file_with_env(self, tmp_path):
+        """With env var, even a missing settings file returns True."""
+        missing = tmp_path / "nonexistent.json"
+
+        with pytest.MonkeyPatch.context() as mp:
+            mp.setenv("LORA_MANAGER_PORTABLE", "1")
+            result = _should_use_portable_settings(str(missing), logging.getLogger())
+            assert result is True

vue-widgets/src/components/AutocompleteTextWidget.vue

@@ -271,12 +271,14 @@ onUnmounted(() => {
   overflow: hidden;
   overflow-y: auto;
   padding: 2px 2px 24px 2px;  /* Reserve bottom space for clear button */
-  resize: none;
   border: none;
   border-radius: 0;
   box-sizing: border-box;
   font-size: var(--comfy-textarea-font-size, 10px);
   font-family: monospace;
+  /* resize:none set here (0,2,0). Overridden to vertical in app mode
+     by the :global(.\[\&_textarea\]\:resize-y) .text-input rule below. */
+  resize: none;
 }
 
 /* Vue DOM mode styles - matches built-in p-textarea in Vue DOM mode */
@@ -350,4 +352,19 @@ onUnmounted(() => {
   width: 14px;
   height: 14px;
 }
+
+</style>
+
+<!--
+  Non-scoped !important override: scoped .text-input[data-v-xxx] (0,2,0)
+  beats the app-mode Tailwind rule (0,1,1), so we use !important here to
+  force resize:vertical only when inside the app-mode widget list.
+  The data-testid attribute scoping prevents it from leaking into graph
+  mode.  This is the only !important in the widget stylesheets.
+-->
+<style>
+[data-testid="app-mode-widget-item"] textarea,
+[data-testid="builder-widget-item"] textarea {
+  resize: vertical !important;
+}
 </style>

vue-widgets/src/main.ts

@@ -553,22 +553,22 @@ function normalizeAutocompleteWidgetValues(node: any, info: any) {
 
 function applyAutocompleteTextLayoutFix(
   widget: any,
-  container: HTMLElement | undefined,
+  _container: HTMLElement | undefined,
   isVueMode: boolean
 ): void {
+  // In Vue rendering mode the WidgetDOM wrapper handles sizing, so we
+  // only provide a computeSize hint and leave the container unconstrained.
+  // In canvas mode we clear all custom sizing so LiteGraph's default
+  // widget-area layout takes over.  Neither path sets a hard max-height;
+  // the textarea can grow freely (e.g. in app mode where
+  // [&_textarea]:resize-y applies).
   if (isVueMode) {
     ;(widget as any).computeLayoutSize = undefined
     widget.computeSize = (width?: number) =>
       [width ?? 200, AUTOCOMPLETE_TEXT_WIDGET_MAX_HEIGHT - 4]
-    if (container) {
-      container.style.minHeight = `${AUTOCOMPLETE_TEXT_WIDGET_MAX_HEIGHT}px`
-    }
   } else {
     delete (widget as any).computeLayoutSize
     delete (widget as any).computeSize
-    if (container) {
-      container.style.minHeight = ''
-    }
   }
 }
 
@@ -743,8 +743,12 @@ function createAutocompleteTextWidgetFactory(
   vueApps.set(appKey, vueApp)
 
   if (maxHeight) {
-    container.style.maxHeight = `${maxHeight}px`
-    container.style.minHeight = `${maxHeight}px`
+    // Set only minHeight as a true minimum — remove maxHeight so the
+    // textarea can grow when the user resizes it in app mode (where
+    // [&_textarea]:resize-y applies).  Graph mode (canvas & Vue render)
+    // is unaffected because LiteGraph's layout system still governs
+    // the widget area size.
+    container.style.minHeight = `${AUTOCOMPLETE_TEXT_WIDGET_MIN_HEIGHT}px`
   }
 
   if (modelType === 'loras') {

web/comfyui/lm_styles.css

@@ -120,10 +120,27 @@
   outline: none;
 }
 
+/* Vue node mode: prevent content from pushing node size via ResizeObserver.
+   contain:size breaks the feedback loop — the container's intrinsic size
+   is determined solely by CSS, not by how many LoRAs are inside. */
+.lm-loras-container.lm-vue-node {
+  height: 100%;
+  min-height: var(--comfy-widget-min-height, 200px);
+  contain: layout size;
+}
+
 .lm-loras-container:focus {
   outline: none;
 }
 
+/* Vue node mode: prevent content from pushing node size via ResizeObserver.
+   Same technique as .lm-loras-container.lm-vue-node above. */
+.comfy-tags-container.lm-vue-node {
+  height: 100%;
+  min-height: var(--comfy-widget-min-height, 150px);
+  contain: layout size;
+}
+
 .lm-lora-empty-state {
   text-align: center;
   padding: 20px 0;

web/comfyui/loras_widget.js

@@ -2,19 +2,14 @@ import { createToggle, createArrowButton, createDragHandle, updateEntrySelection
 import { 
   parseLoraValue, 
   formatLoraValue, 
-  updateWidgetHeight, 
   shouldShowClipEntry, 
-  syncClipStrengthIfCollapsed,
-  LORA_ENTRY_HEIGHT, 
-  HEADER_HEIGHT, 
-  CONTAINER_PADDING, 
-  EMPTY_CONTAINER_HEIGHT 
+  syncClipStrengthIfCollapsed
 } from "./loras_widget_utils.js";
 import { initDrag, createContextMenu, initHeaderDrag, initReorderDrag, handleKeyboardNavigation } from "./loras_widget_events.js";
 import { forwardMiddleMouseToCanvas, forwardWheelToCanvas, enableListWheelScroll } from "./utils.js";
 import { PreviewTooltip } from "./preview_tooltip.js";
 import { ensureLmStyles } from "./lm_styles_loader.js";
-import { getStrengthStepPreference, getLoraWidgetMaxVisibleLoras } from "./settings.js";
+import { getStrengthStepPreference } from "./settings.js";
 
 export function addLorasWidget(node, name, opts, callback) {
   ensureLmStyles();
@@ -29,15 +24,13 @@ export function addLorasWidget(node, name, opts, callback) {
   // Set initial height using CSS variables approach
   const defaultHeight = 200;
 
-  // In Vue/node-2.0 mode, cap the widget height so it shows at most N entries.
-  // This prevents content from driving the node size beyond the cap.
-  // canvas/legacy mode is unaffected.
+  // Set a fixed minimum height so the node has a reasonable starting size.
+  // Adding or removing LoRAs does NOT change the node size — the container
+  // scrolls when content exceeds the allocated space.
+  container.style.setProperty('--comfy-widget-min-height', `${defaultHeight}px`);
+
   if (typeof LiteGraph !== 'undefined' && LiteGraph.vueNodesMode) {
-    const maxLoras = getLoraWidgetMaxVisibleLoras();
-    const gap = 5; // flex gap from .lm-loras-container CSS
-    const maxH = CONTAINER_PADDING + HEADER_HEIGHT + maxLoras * LORA_ENTRY_HEIGHT + maxLoras * gap;
-    container.style.maxHeight = `${maxH}px`;
-    container.style.setProperty('--comfy-widget-max-height', `${maxH}px`);
+    container.classList.add('lm-vue-node');
     // Window capture-phase hook: scroll the widget instead of zooming the canvas
     // when the wheel is over a scrollable loras list.
     enableListWheelScroll(container);
@@ -210,9 +203,6 @@ export function addLorasWidget(node, name, opts, callback) {
       emptyMessage.textContent = "No LoRAs added";
       emptyMessage.className = "lm-lora-empty-state";
       container.appendChild(emptyMessage);
-      
-      // Set fixed height for empty state
-      updateWidgetHeight(container, EMPTY_CONTAINER_HEIGHT, defaultHeight, node);
       return;
     }
 
@@ -259,9 +249,6 @@ export function addLorasWidget(node, name, opts, callback) {
     // Initialize the header drag functionality
     initHeaderDrag(header, widget, renderLoras);
 
-    // Track the total visible entries for height calculation
-    let totalVisibleEntries = lorasData.length;
-
     // Render each lora entry
     lorasData.forEach((loraData) => {
       const { name, strength, clipStrength, active } = loraData;
@@ -533,7 +520,6 @@ export function addLorasWidget(node, name, opts, callback) {
 
       // If expanded, show the clip entry
       if (isExpanded) {
-        totalVisibleEntries++;
         const clipEl = document.createElement("div");
         clipEl.className = "lm-lora-clip-entry";
 
@@ -657,10 +643,6 @@ export function addLorasWidget(node, name, opts, callback) {
       }
     });
     
-    // Calculate height based on number of loras and fixed sizes
-    const calculatedHeight = CONTAINER_PADDING + HEADER_HEIGHT + (Math.min(totalVisibleEntries, 12) * LORA_ENTRY_HEIGHT);
-    updateWidgetHeight(container, calculatedHeight, defaultHeight, node);
-
     // After all LoRA elements are created, apply selection state as the last step
     // This ensures the selection state is not overwritten
     container.querySelectorAll('.lm-lora-entry').forEach(entry => {

web/comfyui/loras_widget_utils.js

@@ -1,12 +1,5 @@
 import { app } from "../../scripts/app.js";
 
-// Fixed sizes for component calculations
-export const LORA_ENTRY_HEIGHT = 40; // Height of a single lora entry
-export const CLIP_ENTRY_HEIGHT = 40; // Height of a clip entry
-export const HEADER_HEIGHT = 32; // Height of the header section
-export const CONTAINER_PADDING = 12; // Top and bottom padding
-export const EMPTY_CONTAINER_HEIGHT = 100; // Height when no loras are present
-
 // Parse LoRA entries from value
 export function parseLoraValue(value) {
   if (!value) return [];
@@ -18,23 +11,6 @@ export function formatLoraValue(loras) {
   return loras;
 }
 
-// Function to update widget height consistently
-export function updateWidgetHeight(container, height, defaultHeight, node) {
-  // Ensure minimum height
-  const finalHeight = Math.max(defaultHeight, height);
-  
-  // Update CSS variables
-  container.style.setProperty('--comfy-widget-min-height', `${finalHeight}px`);
-  container.style.setProperty('--comfy-widget-height', `${finalHeight}px`);
-  
-  // Force node to update size after a short delay to ensure DOM is updated
-  if (node) {
-    setTimeout(() => {
-      node.setDirtyCanvas(true, true);
-    }, 10);
-  }
-}
-
 // Determine if clip entry should be shown - now based on expanded property or initial diff values
 export function shouldShowClipEntry(loraData) {
   // If expanded property exists, use that

web/comfyui/settings.js

@@ -39,9 +39,6 @@ const NEW_TAB_ZOOM_LEVEL = 0.8;
 const STRENGTH_STEP_SETTING_ID = "loramanager.strength_step";
 const STRENGTH_STEP_DEFAULT = 0.05;
 
-const LORA_WIDGET_MAX_VISIBLE_SETTING_ID = "loramanager.lora_widget_max_visible_loras";
-const LORA_WIDGET_MAX_VISIBLE_DEFAULT = 12;
-
 // ============================================================================
 // Helper Functions
 // ============================================================================
@@ -363,32 +360,6 @@ const getStrengthStepPreference = (() => {
     };
 })();
 
-const getLoraWidgetMaxVisibleLoras = (() => {
-    let settingsUnavailableLogged = false;
-
-    return () => {
-        const settingManager = app?.extensionManager?.setting;
-        if (!settingManager || typeof settingManager.get !== "function") {
-            if (!settingsUnavailableLogged) {
-                console.warn("LoRA Manager: settings API unavailable, using default max visible loras.");
-                settingsUnavailableLogged = true;
-            }
-            return LORA_WIDGET_MAX_VISIBLE_DEFAULT;
-        }
-
-        try {
-            const value = settingManager.get(LORA_WIDGET_MAX_VISIBLE_SETTING_ID);
-            return value ?? LORA_WIDGET_MAX_VISIBLE_DEFAULT;
-        } catch (error) {
-            if (!settingsUnavailableLogged) {
-                console.warn("LoRA Manager: unable to read max visible loras setting, using default.", error);
-                settingsUnavailableLogged = true;
-            }
-            return LORA_WIDGET_MAX_VISIBLE_DEFAULT;
-        }
-    };
-})();
-
 // ============================================================================
 // Register Extension with All Settings
 // ============================================================================
@@ -492,19 +463,6 @@ app.registerExtension({
             tooltip: "Step size for adjusting LoRA strength via arrow buttons or keyboard (default: 0.05)",
             category: ["LoRA Manager", "LoRA Widget", "Strength Step"],
         },
-        {
-            id: LORA_WIDGET_MAX_VISIBLE_SETTING_ID,
-            name: "Node 2.0: Maximum visible LoRA entries",
-            type: "slider",
-            attrs: {
-                min: 3,
-                max: 50,
-                step: 1,
-            },
-            defaultValue: LORA_WIDGET_MAX_VISIBLE_DEFAULT,
-            tooltip: "When using Node 2.0 rendering, limit the loras widget height to show at most this many entries (default: 12). Excess entries are accessible via scrollbar.",
-            category: ["LoRA Manager", "LoRA Widget", "Max Visible"],
-        },
     ],
     async setup() {
         await loadWorkflowOptions();
@@ -591,5 +549,4 @@ export {
     getUsageStatisticsPreference,
     getNewTabTemplatePreference,
     getStrengthStepPreference,
-    getLoraWidgetMaxVisibleLoras,
 };

web/comfyui/tags_widget.js

@@ -1,6 +1,7 @@
 import { app } from "../../scripts/app.js";
 import { forwardMiddleMouseToCanvas, forwardWheelToCanvas } from "./utils.js";
 import { copyToClipboard } from "./loras_widget_utils.js";
+import { ensureLmStyles } from "./lm_styles_loader.js";
 
 const MIN_HEIGHT = 150;
 const GROUP_EDITOR_ID = "lm-trigger-group-editor";
@@ -696,6 +697,16 @@ export function addTagsWidget(node, name, opts, callback, wheelSensitivity = 0.0
     outline: "none",
   });
 
+  // Set a fixed minimum height so the node has a reasonable starting size.
+  // Adding or removing tags does NOT change the node size — the container
+  // scrolls when content exceeds the allocated space.
+  ensureLmStyles();
+  container.style.setProperty("--comfy-widget-min-height", `${MIN_HEIGHT}px`);
+
+  if (typeof LiteGraph !== "undefined" && LiteGraph.vueNodesMode) {
+    container.classList.add("lm-vue-node");
+  }
+
   const initialTagsData = opts?.defaultVal || [];
 
   function renderSimpleTag(tagData, index, widget, showStrengthInfo) {

web/comfyui/vue-widgets/lora-manager-widgets.js

@@ -2118,14 +2118,14 @@ to { transform: rotate(360deg);
   padding: 20px 0;
 }
 
-.autocomplete-text-widget[data-v-8555b560] {
+.autocomplete-text-widget[data-v-3f3d7a1a] {
   background: transparent;
   height: 100%;
   display: flex;
   flex-direction: column;
   box-sizing: border-box;
 }
-.input-wrapper[data-v-8555b560] {
+.input-wrapper[data-v-3f3d7a1a] {
   position: relative;
   flex: 1;
   display: flex;
@@ -2133,7 +2133,7 @@ to { transform: rotate(360deg);
 }
 
 /* Canvas mode styles (default) - matches built-in comfy-multiline-input */
-.text-input[data-v-8555b560] {
+.text-input[data-v-3f3d7a1a] {
   flex: 1;
   width: 100%;
   background-color: var(--comfy-input-bg, #222);
@@ -2141,16 +2141,18 @@ to { transform: rotate(360deg);
   overflow: hidden;
   overflow-y: auto;
   padding: 2px 2px 24px 2px;  /* Reserve bottom space for clear button */
-  resize: none;
   border: none;
   border-radius: 0;
   box-sizing: border-box;
   font-size: var(--comfy-textarea-font-size, 10px);
   font-family: monospace;
+  /* resize:none set here (0,2,0). Overridden to vertical in app mode
+     by the :global(.\\[\\&_textarea\\]\\:resize-y) .text-input rule below. */
+  resize: none;
 }
 
 /* Vue DOM mode styles - matches built-in p-textarea in Vue DOM mode */
-.text-input.vue-dom-mode[data-v-8555b560] {
+.text-input.vue-dom-mode[data-v-3f3d7a1a] {
   background-color: var(--color-charcoal-400, #313235);
   color: #fff;
   padding: 8px 12px 30px 12px;  /* Reserve bottom space for clear button */
@@ -2159,12 +2161,12 @@ to { transform: rotate(360deg);
   font-size: 12px;
   font-family: inherit;
 }
-.text-input[data-v-8555b560]:focus {
+.text-input[data-v-3f3d7a1a]:focus {
   outline: none;
 }
 
 /* Clear button styles */
-.clear-button[data-v-8555b560] {
+.clear-button[data-v-3f3d7a1a] {
   position: absolute;
   right: 6px;
   bottom: 6px;  /* Changed from top to bottom */
@@ -2187,33 +2189,39 @@ to { transform: rotate(360deg);
 }
 
 /* Show clear button when hovering over input wrapper */
-.input-wrapper:hover .clear-button[data-v-8555b560] {
+.input-wrapper:hover .clear-button[data-v-3f3d7a1a] {
   opacity: 0.7;
   pointer-events: auto;
 }
-.clear-button[data-v-8555b560]:hover {
+.clear-button[data-v-3f3d7a1a]:hover {
   opacity: 1;
   background: rgba(255, 100, 100, 0.8);
 }
-.clear-button svg[data-v-8555b560] {
+.clear-button svg[data-v-3f3d7a1a] {
   width: 12px;
   height: 12px;
 }
 
 /* Vue DOM mode adjustments for clear button */
-.text-input.vue-dom-mode ~ .clear-button[data-v-8555b560] {
+.text-input.vue-dom-mode ~ .clear-button[data-v-3f3d7a1a] {
   right: 8px;
   bottom: 10px;  /* Changed from top to bottom, adjusted for Vue DOM padding */
   width: 20px;
   height: 20px;
   background: rgba(107, 114, 128, 0.6);
 }
-.text-input.vue-dom-mode ~ .clear-button[data-v-8555b560]:hover {
+.text-input.vue-dom-mode ~ .clear-button[data-v-3f3d7a1a]:hover {
   background: oklch(62% 0.18 25);
 }
-.text-input.vue-dom-mode ~ .clear-button svg[data-v-8555b560] {
+.text-input.vue-dom-mode ~ .clear-button svg[data-v-3f3d7a1a] {
   width: 14px;
   height: 14px;
+}
+
+
+[data-testid="app-mode-widget-item"] textarea,
+[data-testid="builder-widget-item"] textarea {
+  resize: vertical !important;
 }`));
       document.head.appendChild(elementStyle);
     }
@@ -14952,7 +14960,7 @@ const _sfc_main = /* @__PURE__ */ defineComponent({
     };
   }
 });
-const AutocompleteTextWidget = /* @__PURE__ */ _export_sfc(_sfc_main, [["__scopeId", "data-v-8555b560"]]);
+const AutocompleteTextWidget = /* @__PURE__ */ _export_sfc(_sfc_main, [["__scopeId", "data-v-3f3d7a1a"]]);
 function createVueWidgetCleanup(vueApp, onCleanup) {
   let didUnmount = false;
   return () => {
@@ -15718,19 +15726,13 @@ function normalizeAutocompleteWidgetValues(node, info) {
     info.widgets_values = repairedValues;
   }
 }
-function applyAutocompleteTextLayoutFix(widget, container, isVueMode) {
+function applyAutocompleteTextLayoutFix(widget, _container, isVueMode) {
   if (isVueMode) {
     widget.computeLayoutSize = void 0;
     widget.computeSize = (width) => [width ?? 200, AUTOCOMPLETE_TEXT_WIDGET_MAX_HEIGHT - 4];
-    if (container) {
-      container.style.minHeight = `${AUTOCOMPLETE_TEXT_WIDGET_MAX_HEIGHT}px`;
-    }
   } else {
     delete widget.computeLayoutSize;
     delete widget.computeSize;
-    if (container) {
-      container.style.minHeight = "";
-    }
   }
 }
 const initVueDomModeListener = () => {
@@ -15875,8 +15877,7 @@ function createAutocompleteTextWidgetFactory(node, widgetName, modelType, inputO
   const appKey = instanceId;
   vueApps.set(appKey, vueApp);
   if (maxHeight) {
-    container.style.maxHeight = `${maxHeight}px`;
-    container.style.minHeight = `${maxHeight}px`;
+    container.style.minHeight = `${AUTOCOMPLETE_TEXT_WIDGET_MIN_HEIGHT}px`;
   }
   if (modelType === "loras") {
     applyAutocompleteTextLayoutFix(

web/comfyui/workflow_registry.js

@@ -1,8 +1,10 @@
 import { app } from "../../scripts/app.js";
 import { api } from "../../scripts/api.js";
-import { getAllGraphNodes, getNodeReference, getNodeFromGraph } from "./utils.js";
+import { getAllGraphNodes, getNodeReference, getNodeFromGraph, chainCallback } from "./utils.js";
 import { ensureLmStyles } from "./lm_styles_loader.js";
 
+const DEBOUNCE_DELAY = 500;
+
 const LORA_NODE_CLASSES = new Set([
     "Lora Loader (LoraManager)",
     "Lora Stacker (LoraManager)",
@@ -79,22 +81,77 @@ app.registerExtension({
 
     setup() {
         ensureLmStyles();
+        this._log("extension initialized, clientId=%s", api.clientId ?? api.initialClientId ?? "(pending)");
 
         api.addEventListener("lora_registry_refresh", () => {
-            this.refreshRegistry();
+            this.refreshRegistry(true);
         });
 
         api.addEventListener("lm_widget_update", (event) => {
             this.applyWidgetUpdate(event?.detail ?? {});
         });
 
-        // React to marker changes from the Node Marker extension
         window.addEventListener("lm_marker_changed", () => {
             this.refreshRegistry();
         });
+
+        this._hookGraphChanges();
     },
 
-    async refreshRegistry() {
+    async afterConfigureGraph(_missingNodeTypes, _app) {
+        this._log("afterConfigureGraph: workflow loaded (%s missing types)", _missingNodeTypes?.length ?? 0);
+        await this.refreshRegistry();
+    },
+
+    _hookGraphChanges() {
+        const graph = app.graph;
+        if (!graph) {
+            this._log("app.graph not available, skipping proactive hooks");
+            return;
+        }
+
+        let hooksInstalled = 0;
+
+        const scheduleRefresh = (source) => {
+            if (this._debounceTimer != null) {
+                clearTimeout(this._debounceTimer);
+            }
+            this._debounceTimer = setTimeout(() => {
+                this._debounceTimer = null;
+                this.refreshRegistry();
+            }, DEBOUNCE_DELAY);
+        };
+
+        try {
+            chainCallback(graph, "onNodeAdded", () => scheduleRefresh("onNodeAdded"));
+            chainCallback(graph, "onNodeRemoved", () => scheduleRefresh("onNodeRemoved"));
+            hooksInstalled += 2;
+        } catch (e) {
+            this._log("failed to chain LiteGraph hooks: %s", e.message);
+        }
+
+        if (typeof api.addEventListener === "function") {
+            try {
+                api.addEventListener("graphChanged", () => scheduleRefresh("graphChanged"));
+                hooksInstalled += 1;
+            } catch (_e) {
+                // graphChanged may not be available on older ComfyUI versions
+            }
+        }
+
+        this._log("%s proactive hooks installed on graph", hooksInstalled);
+    },
+
+    _log(format, ...args) {
+        const ts = new Date().toISOString().slice(11, 23);
+        let msg = format;
+        for (const arg of args) {
+            msg = msg.replace(/%s/g, String(arg));
+        }
+        console.debug(`[LM:Registry ${ts}] ${msg}`);
+    },
+
+    async refreshRegistry(force = false) {
         try {
             const workflowNodes = [];
             const nodeEntries = getAllGraphNodes(app.graph);
@@ -115,7 +172,6 @@ app.registerExtension({
                 const hasTextWidget = TEXT_CAPABLE_CLASSES.has(node.comfyClass);
                 const markerRole = node.properties?.lm_marker_role ?? null;
 
-                // Skip nodes with no relevant capability UNLESS they are marked
                 if (!supportsLora && !hasTargetWidget && !hasTextWidget && !markerRole) {
                     continue;
                 }
@@ -146,6 +202,19 @@ app.registerExtension({
                 });
             }
 
+            const clientId = api.clientId ?? api.initialClientId ?? "";
+
+            // Content-based dedup: skip POST if identical to last sent payload,
+            // unless forced (e.g. responding to a lora_registry_refresh WS message
+            // where the backend explicitly requests a re-registration).
+            const fingerprint = JSON.stringify(
+                workflowNodes.map(n => `${n.graph_id}:${n.node_id}|${n.marker_role ?? ""}|${n.mode ?? 0}`).sort()
+            );
+            if (!force && fingerprint === this._lastFingerprint) {
+                return;
+            }
+            this._lastFingerprint = fingerprint;
+
             const response = await fetch("/api/lm/register-nodes", {
                 method: "POST",
                 headers: {
@@ -153,7 +222,7 @@ app.registerExtension({
                 },
                 body: JSON.stringify({
                     nodes: workflowNodes,
-                    client_id: api.clientId ?? api.initialClientId ?? "",
+                    client_id: clientId,
                 }),
             });