chore: bump version to 1.0.6

Commit 454210a4 replaced renderFunction() with widget.value setter +
widget.callback() in endDrag, so the test assertion should verify
callback invocation instead of the removed renderSpy call.

README.md

@@ -54,137 +54,7 @@ Insomnia Art Designs, megakirbs, Brennok, 2018cfh, W+K+White, wackop, Phil, Carl
 
 <!-- SUPPORTERS-END -->
 
-## Release Notes
 
-### v1.0.5
-
-* **Excluded Models Management View** - Added a new global-menu view for excluded models, with actions to restore them or delete them permanently.
-* **Fix for `401 Unauthorized` Downloads** - Fixed an issue where some `civitai.red` downloads could lose authentication during redirect and fail with `401 Unauthorized`.
-
-### v1.0.4
-
-* **Civitai Domain Split Support** - Added support for `civitai.com` and `civitai.red` model URLs and recipe/image URLs across import, analysis, and download flows.
-* **Civitai API Host Migration** - Updated core Civitai API requests to use `civitai.red` for compatibility with Civitai's current API host.
-* **Configurable Civitai View Host** - Added a setting to choose which Civitai site opens by default for model, search, and view links.
-* **401 Unauthorized Reminder** - Some users have reported `401 Unauthorized` errors. If you run into this, try generating a new API key on `civitai.red` and updating it in LoRA Manager settings.
-
-### v1.0.3
-
-* **Custom Recipe Storage Path** - Added support for configuring a custom storage path for recipes, with migration support to move existing recipe data when changing locations.
-* **Wildcard Support for LM Text/Prompt Nodes** - The LM `Text` node and `Prompt` node now support the new `/wildcard` command, with runtime wildcard expansion and support for dynamic prompt syntax for more flexible prompt construction.
-* **System Diagnostics ("Doctor")** - Added a new diagnostics feature to help surface environment and setup issues more clearly.
-* **User-State Backup Support** - Added backup support for user state, with accompanying UI and clearer backup scope messaging in Settings.
-* **Downloaded Status Visibility** - Added clearer downloaded-status UX so previously downloaded model versions are easier to recognize.
-* **Autocomplete Performance Improvements** - Fixed autocomplete performance issues to reduce tag-search overhead and improve responsiveness.
-
-### v1.0.2
-
-* **Model Download History Tracking** - LoRA Manager now keeps a history of downloaded model versions, allowing it to recognize whether a version has been downloaded before, even if it is no longer currently present in your library.
-* **Skip Previously Downloaded Model Versions** - Added a new setting, `Skip previously downloaded model versions`, to help avoid downloading model versions you have already downloaded in the past.
-* **LoRA Stack Combiner Trigger Words Fix** - Fixed an issue where trigger word updates from `LORA_STACK` inputs were not propagated correctly through the LoRA Stack Combiner node.
-* **CivitAI Example Image Compatibility** - Improved support for CivitAI CDN subdomains so example images load more reliably.
-
-### v1.0.1
-
-* **Batch Recipe Import** - Import recipes from multiple URLs or directories simultaneously with optimized concurrency.
-* **Bulk Download Missing LoRAs** - New bulk action for recipes: select multiple recipes and download all missing LoRAs for the selected recipes in one operation.
-* **Import-Only Recipe Option** - Save recipe metadata without downloading missing LoRAs, allowing you to save interesting recipes for later and download dependencies when needed.
-* **Editable Recipe Prompts** - Edit recipe prompts directly in the recipe detail modal.
-* **Checkpoint Loader LM Node** - Behaves like ComfyUI's built-in Load Checkpoint node, with the added ability to load checkpoints from Extra Folder Paths.
-* **UNET Loader LM Node** - Behaves like ComfyUI's built-in Load Diffusion Model node, with support for loading from Extra Folder Paths and GGUF format (requires ComfyUI-GGUF custom node).
-* **LoRA Stack Combiner Node** - Merge two LoRA stacks into one. For example: use separate Randomizers for character and style LoRAs, then combine before applying.
-* **LoRA Pool Regex Filtering** - Filter which LoRAs enter the pool using custom regex patterns for include/exclude rules.
-* **Dynamic Base Model Types** - Base model types are now fetched dynamically from Civitai API, keeping them synchronized with the latest available models.
-* **Prompt Autocomplete Enhancements** - Tab key acceptance, configurable behavior, and improved multi-word tag matching.
-* **Download Base Model Exclusions** - Exclude specific base models from download operations when you only want certain model types.
-* **Mature Blur Threshold Setting** - Configure blur levels (`PG13` / `R` / `X` / `XXX`, default `R+`) for mature content previews.
-* **Experimental: Nunchaku Qwen LoRA Support** - Experimental support for loading and applying LoRAs to Nunchaku quantized Qwen-Image models.
-* **Bug Fixes & UX Improvements** - Various fixes for a smoother workflow.
-
-### v1.0.0
-* **Extra Folder Paths Support** - Added support for additional model root paths exclusive to LoRA Manager. This allows loading LoRAs from extra locations outside ComfyUI's standard folders, helping avoid performance issues when working with large model libraries.
-* **Settings UI Overhaul** - Redesigned the Settings interface with a more organized layout, making it easier to find and configure application settings.
-* **Lazy Hash Computation** - Implemented lazy hash calculation for large model files (checkpoints and diffusion models). Hashes are now computed only when strictly necessary, minimizing redundant disk I/O and significantly accelerating application initialization.
-* **Milestone & Supporter Recognition** - Updated the Supporter window to show appreciation for all project supporters as this v1.0.0 milestone is reached. Great thanks to the community for the ongoing support!
-* **Bug Fixes & UX Enhancements** - Various bug fixes and user experience improvements for a smoother workflow.
-
-### v0.9.16
-* **Duplicate Detection Enhancement** - The model duplicates mode now respects filter configurations, making it easier to find duplicate groups within specific filtered results.
-* **Tag Logic Toggle** - Added OR/AND toggle for include tags filtering in the filters panel, providing more flexible tag-based model searches.
-* **Metadata Refresh Skip Paths** - New setting to exclude specific paths from metadata refresh operations. Models under these paths will be skipped when fetching metadata from remote sources.
-* **Dynamic Trigger Words in Prompt Node** - Prompt node now supports dynamic numbers of trigger word inputs for greater flexibility.
-* **Early Access Updates** - Model updates now display Early Access information, with a new setting to ignore Early Access updates if desired.
-* **LM Civitai Extension Integration** - Added integration with the LM Civitai Extension. Clicking the download button in model updates now sends downloads to the extension's download queue for seamless one-click downloads.
-
-### v0.9.15
-* **Filter Presets** - Save filter combinations as presets for quick switching and reapplication.
-* **Bug Fixes** - Fixed various bugs for improved stability.
-
-### v0.9.14
-* **LoRA Cycler Node** - Introduced a new LoRA Cycler node that enables iteration through specified LoRAs with support for repeat count and pause iteration functionality. Refer to the new "Lora Cycler" template workflow for concrete example.
-* **Enhanced Prompt Node with Tag Autocomplete** - Enhanced the Prompt node with comprehensive tag autocomplete based on merged Danbooru + e621 tags. Supports tag search and autocomplete functionality. Implemented a command system with shortcuts like `/character` or `/artist` for category-specific tag searching. Added `/ac` or `/noac` commands to quickly enable or disable autocomplete. Refer to the "Lora Manager Basic" template workflow in ComfyUI -> Templates -> ComfyUI-Lora-Manager for detailed tips.
-* **Bug Fixes & Stability** - Addressed multiple bugs and improved overall stability.
-
-### v0.9.12
-* **LoRA Randomizer System** - Introduced a comprehensive LoRA randomization system featuring LoRA Pool and LoRA Randomizer nodes for flexible and dynamic generation workflows.
-* **LoRA Randomizer Template** - Refer to the new "LoRA Randomizer" template workflow for detailed examples of flexible randomization modes, lock & reuse options, and other features.
-* **Recipe Folders** - Introduced a folder system for the Recipes page, allowing users to freely organize recipes just like they do with models.
-* **Recipe Bulk Operations** - Added bulk mode support for batch moving, deleting, and setting base models for selected recipes with intuitive controls like click-and-drag selection, drag-to-folder, and Ctrl+A (Select All).
-* **Prompt Search & Sorting** - Search recipes by prompt content and sort by Recipe Name, Imported Date, or LoRA Count for better browsing.
-* **Recipe Favorites** - Mark specific recipes as favorites for quick access.
-* **Video Recipe Support** - Enabled support for video recipes (import via LM extension or URL; video file import not supported).
-* **Performance Improvements** - Fixed performance issues for dramatically improved startup and loading speed. After first scan, subsequent loads are instant regardless of collection size.
-* **ComfyUI Nodes 2.0 Support** - Basic support for ComfyUI Nodes 2.0.
-
-### v0.9.10
-* **Smarter Update Matching** - Users can now choose to check and group updates by matching base model only or with no base-model constraint; version lists also support toggling between same-base versions or all versions.
-* **Flexible Tag Filtering** - The filter panel now supports tag exclusion: click a tag to include, click again to exclude, and click a third time to clear, enabling stronger and more flexible tag filters.
-* **License Visibility & Controls** - Model detail headers and ComfyUI preview popups now show Civitai license icons. The filter panel gains license include/exclude options, and a new global context menu action, "Refresh license metadata," fetches missing license data.
-* **Recipe Improvements** - Recipes now allow importing with zero LoRAs, and recipe detail pages show the related checkpoint for easier reference.
-* **Better ZIP Downloads** - When downloading models packaged in ZIPs, model files are extracted into the target model folder; ZIPs containing multiple model files (e.g., WanVideo high/low LoRA pairs) are added as separate models.
-* **Template Workflow Update** - Refreshed the "Illustrious Pony Example" template workflow with usage guidance for each LoRA Manager node.
-* **Bug Fixes & Stability** - General fixes and stability improvements.
-
-### v0.9.9
-* **Check for Updates Feature** - Users can now check for updates for all models or selected models in bulk mode. Models with available updates will display an "update available" badge on their model card, and users can filter to show only models with updates.
-* **Model Versions Management** - Added a new Versions tab in the model modal that centralizes all versions of a model, providing download, delete, and ignore update functions.
-* **Send Checkpoint to ComfyUI** - Users can now click the send button on a checkpoint card to send the checkpoint directly to the current workflow's checkpoint or diffusion model loader node in ComfyUI.
-* **Customizable Model Card Display** - Added a new setting that allows users to choose whether to display the model name or filename on model cards.
-* **New Path Template Placeholders** - Added new path template placeholders: `{model_name}` and `{version_name}` for more flexible organization.
-* **ComfyUI Auto Path Correction Setting** - Added a new setting within ComfyUI to enable or disable the auto path correction feature.
-
-### v0.9.8
-* **Full CivArchive API Support** - Added complete support for the CivArchive API as a fallback metadata source beyond Civitai API. Models deleted from Civitai can now still retrieve metadata through the CivArchive API.
-* **Download Models from CivArchive** - Added support for downloading models directly from CivArchive, similar to downloading from Civitai. Simply click the Download button and paste the model URL to download the corresponding model.
-* **Custom Priority Tags** - Introduced Custom Priority Tags feature, allowing users to define custom priority tags. These tags will appear as suggestions when editing tags or during auto organization/download using default paths, providing more precise and controlled folder organization. [Guide](https://github.com/willmiao/ComfyUI-Lora-Manager/wiki/Priority-Tags-Configuration-Guide)
-* **Drag and Drop Tag Reordering** - Added drag and drop functionality to reorder tags in the tags edit mode for improved usability.
-* **Download Control in Example Images Panel** - Added stop control in the Download Example Images Panel for better download management.
-* **Prompt (LoraManager) Node with Autocomplete** - Added new Prompt (LoraManager) node with autocomplete feature for adding embeddings.
-* **Lora Manager Nodes in Subgraphs** - Lora Manager nodes now support being placed within subgraphs for more flexible workflow organization.
-
-### v0.9.6
-* **Metadata Archive Database Support** - Added the ability to download and utilize a metadata archive database, enabling access to metadata for models that have been deleted from CivitAI.
-* **App-Level Proxy Settings** - Introduced support for configuring a global proxy within the application, making it easier to use the manager behind network restrictions.
-* **Bug Fixes** - Various bug fixes for improved stability and reliability.
-
-### v0.9.2
-* **Bulk Auto-Organization Action** - Added a new bulk auto-organization feature. You can now select multiple models and automatically organize them according to your current path template settings for streamlined management.
-* **Bug Fixes** - Addressed several bugs to improve stability and reliability.
-
-### v0.9.1
-* **Enhanced Bulk Operations** - Improved bulk operations with Marquee Selection and a bulk operation context menu, providing a more intuitive, desktop-application-like user experience.
-* **New Bulk Actions** - Added bulk operations for adding tags and setting base models to multiple models simultaneously.
-
-### v0.9.0
-* **UI Overhaul for Enhanced Navigation** - Replaced the top flat folder tags with a new folder sidebar and breadcrumb navigation system for a more intuitive folder browsing and selection experience.
-* **Dual-Mode Folder Sidebar** - The new folder sidebar offers two display modes: 'List Mode,' which mirrors the classic folder view, and 'Tree Mode,' which presents a hierarchical folder structure for effortless navigation through nested directories.
-* **Internationalization Support** - Introduced multi-language support, now available in English, Simplified Chinese, Traditional Chinese, Spanish, Japanese, Korean, French, Russian, and German. Feedback from native speakers is welcome to improve the translations.
-* **Automatic Filename Conflict Resolution** - Implemented automatic file renaming (`original name + short hash`) to prevent conflicts when downloading or moving models.
-* **Performance Optimizations & Bug Fixes** - Various performance improvements and bug fixes for a more stable and responsive experience.
-
-[View Update History](./update_logs.md)
-
----
 
 ## **⚠ Important Note**: To use the CivitAI download feature, you'll need to:
 

locales/de.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Automatisch organisieren",
             "skipMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle überspringen",
             "resumeMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle fortsetzen",
+            "setFavorite": "Als Favorit setzen",
+            "setFavoriteCount": "Als Favorit setzen ({favorited}/{total})",
+            "unfavorite": "Aus Favoriten entfernen",
             "deleteAll": "Ausgewählte löschen",
             "downloadMissingLoras": "Fehlende LoRAs herunterladen",
             "clear": "Auswahl löschen",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Inhaltsbewertung auf {level} für {count} Modell(e) gesetzt",
             "bulkContentRatingPartial": "Inhaltsbewertung auf {level} für {success} Modell(e) gesetzt, {failed} fehlgeschlagen",
             "bulkContentRatingFailed": "Inhaltsbewertung für ausgewählte Modelle konnte nicht aktualisiert werden",
+            "bulkFavoriteUpdating": "Füge {count} Modell(e) zu Favoriten hinzu...",
+            "bulkUnfavoriteUpdating": "Entferne {count} Modell(e) aus Favoriten...",
+            "bulkFavoritePartialAdded": "{success} Modell(e) zu Favoriten hinzugefügt, {failed} fehlgeschlagen",
+            "bulkFavoritePartialRemoved": "{success} Modell(e) aus Favoriten entfernt, {failed} fehlgeschlagen",
+            "bulkFavoriteFailed": "Fehler beim Aktualisieren des Favoritenstatus",
             "bulkUpdatesChecking": "Ausgewählte {type}-Modelle werden auf Updates geprüft...",
             "bulkUpdatesSuccess": "Updates für {count} ausgewählte {type}-Modelle verfügbar",
             "bulkUpdatesNone": "Keine Updates für ausgewählte {type}-Modelle gefunden",

locales/en.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Auto-Organize Selected",
             "skipMetadataRefresh": "Skip Metadata Refresh for Selected",
             "resumeMetadataRefresh": "Resume Metadata Refresh for Selected",
+            "setFavorite": "Set as Favorite",
+            "setFavoriteCount": "Set as Favorite ({favorited}/{total})",
+            "unfavorite": "Remove from Favorites",
             "deleteAll": "Delete Selected",
             "downloadMissingLoras": "Download Missing LoRAs",
             "clear": "Clear Selection",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Set content rating to {level} for {count} model(s)",
             "bulkContentRatingPartial": "Set content rating to {level} for {success} model(s), {failed} failed",
             "bulkContentRatingFailed": "Failed to update content rating for selected models",
+            "bulkFavoriteUpdating": "Adding {count} model(s) to favorites...",
+            "bulkUnfavoriteUpdating": "Removing {count} model(s) from favorites...",
+            "bulkFavoritePartialAdded": "Added {success} model(s) to favorites, {failed} failed",
+            "bulkFavoritePartialRemoved": "Removed {success} model(s) from favorites, {failed} failed",
+            "bulkFavoriteFailed": "Failed to update favorite status for selected models",
             "bulkUpdatesChecking": "Checking selected {type}(s) for updates...",
             "bulkUpdatesSuccess": "Updates available for {count} selected {type}(s)",
             "bulkUpdatesNone": "No updates found for selected {type}(s)",

locales/es.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Auto-organizar seleccionados",
             "skipMetadataRefresh": "Omitir actualización de metadatos para seleccionados",
             "resumeMetadataRefresh": "Reanudar actualización de metadatos para seleccionados",
+            "setFavorite": "Marcar como favorito",
+            "setFavoriteCount": "Marcar como favorito ({favorited}/{total})",
+            "unfavorite": "Quitar de favoritos",
             "deleteAll": "Eliminar seleccionados",
             "downloadMissingLoras": "Descargar LoRAs faltantes",
             "clear": "Limpiar selección",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Clasificación de contenido establecida en {level} para {count} modelo(s)",
             "bulkContentRatingPartial": "Clasificación de contenido establecida en {level} para {success} modelo(s), {failed} fallaron",
             "bulkContentRatingFailed": "No se pudo actualizar la clasificación de contenido para los modelos seleccionados",
+            "bulkFavoriteUpdating": "Añadiendo {count} modelo(s) a favoritos...",
+            "bulkUnfavoriteUpdating": "Eliminando {count} modelo(s) de favoritos...",
+            "bulkFavoritePartialAdded": "{success} modelo(s) añadido(s) a favoritos, {failed} fallido(s)",
+            "bulkFavoritePartialRemoved": "{success} modelo(s) eliminado(s) de favoritos, {failed} fallido(s)",
+            "bulkFavoriteFailed": "Error al actualizar el estado de favorito",
             "bulkUpdatesChecking": "Comprobando actualizaciones para {type} seleccionados...",
             "bulkUpdatesSuccess": "Actualizaciones disponibles para {count} {type} seleccionados",
             "bulkUpdatesNone": "No se encontraron actualizaciones para los {type} seleccionados",

locales/fr.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Auto-organiser la sélection",
             "skipMetadataRefresh": "Ignorer l'actualisation des métadonnées pour la sélection",
             "resumeMetadataRefresh": "Reprendre l'actualisation des métadonnées pour la sélection",
+            "setFavorite": "Définir comme favori",
+            "setFavoriteCount": "Définir comme favori ({favorited}/{total})",
+            "unfavorite": "Retirer des favoris",
             "deleteAll": "Supprimer la sélection",
             "downloadMissingLoras": "Télécharger les LoRAs manquants",
             "clear": "Effacer la sélection",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Classification du contenu définie sur {level} pour {count} modèle(s)",
             "bulkContentRatingPartial": "Classification du contenu définie sur {level} pour {success} modèle(s), {failed} échec(s)",
             "bulkContentRatingFailed": "Impossible de mettre à jour la classification du contenu pour les modèles sélectionnés",
+            "bulkFavoriteUpdating": "Ajout de {count} modèle(s) aux favoris...",
+            "bulkUnfavoriteUpdating": "Suppression de {count} modèle(s) des favoris...",
+            "bulkFavoritePartialAdded": "{success} modèle(s) ajouté(s) aux favoris, {failed} échec(s)",
+            "bulkFavoritePartialRemoved": "{success} modèle(s) retiré(s) des favoris, {failed} échec(s)",
+            "bulkFavoriteFailed": "Échec de la mise à jour du statut de favori",
             "bulkUpdatesChecking": "Vérification des mises à jour pour les {type} sélectionnés...",
             "bulkUpdatesSuccess": "Mises à jour disponibles pour {count} {type} sélectionnés",
             "bulkUpdatesNone": "Aucune mise à jour trouvée pour les {type} sélectionnés",

locales/he.json

@@ -687,6 +687,9 @@
             "autoOrganize": "ארגן אוטומטית נבחרים",
             "skipMetadataRefresh": "דילוג על רענון מטא-נתונים לנבחרים",
             "resumeMetadataRefresh": "המשך רענון מטא-נתונים לנבחרים",
+            "setFavorite": "הגדר כמועדף",
+            "setFavoriteCount": "הגדר כמועדף ({favorited}/{total})",
+            "unfavorite": "הסר ממועדפים",
             "deleteAll": "מחק נבחרים",
             "downloadMissingLoras": "הורדת LoRAs חסרים",
             "clear": "נקה בחירה",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "דירוג התוכן הוגדר ל-{level} עבור {count} מודלים",
             "bulkContentRatingPartial": "דירוג התוכן הוגדר ל-{level} עבור {success} מודלים, {failed} נכשלו",
             "bulkContentRatingFailed": "עדכון דירוג התוכן עבור המודלים שנבחרו נכשל",
+            "bulkFavoriteUpdating": "מוסיף {count} דגמים למועדפים...",
+            "bulkUnfavoriteUpdating": "מסיר {count} דגמים ממועדפים...",
+            "bulkFavoritePartialAdded": "{success} דגמים נוספו למועדפים, {failed} נכשלו",
+            "bulkFavoritePartialRemoved": "{success} דגמים הוסרו ממועדפים, {failed} נכשלו",
+            "bulkFavoriteFailed": "עדכון סטטוס מועדפים נכשל",
             "bulkUpdatesChecking": "בודק עדכונים עבור {type} שנבחרו...",
             "bulkUpdatesSuccess": "יש עדכונים עבור {count} {type} שנבחרו",
             "bulkUpdatesNone": "לא נמצאו עדכונים עבור {type} שנבחרו",

locales/ja.json

@@ -687,6 +687,9 @@
             "autoOrganize": "自動整理を実行",
             "skipMetadataRefresh": "選択したモデルのメタデータ更新をスキップ",
             "resumeMetadataRefresh": "選択したモデルのメタデータ更新を再開",
+            "setFavorite": "お気に入りに設定",
+            "setFavoriteCount": "お気に入りに設定 ({favorited}/{total})",
+            "unfavorite": "お気に入りから削除",
             "deleteAll": "選択したものを削除",
             "downloadMissingLoras": "不足している LoRA をダウンロード",
             "clear": "選択をクリア",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "{count} 件のモデルのコンテンツレーティングを {level} に設定しました",
             "bulkContentRatingPartial": "{success} 件のモデルのコンテンツレーティングを {level} に設定、{failed} 件は失敗しました",
             "bulkContentRatingFailed": "選択したモデルのコンテンツレーティングを更新できませんでした",
+            "bulkFavoriteUpdating": "{count} 個のモデルをお気に入りに追加中...",
+            "bulkUnfavoriteUpdating": "{count} 個のモデルをお気に入りから削除中...",
+            "bulkFavoritePartialAdded": "{success} 個のモデルをお気に入りに追加、{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "{success} 個のモデルをお気に入りから削除、{failed} 個失敗",
+            "bulkFavoriteFailed": "お気に入り状態の更新に失敗しました",
             "bulkUpdatesChecking": "選択された{type}の更新を確認しています...",
             "bulkUpdatesSuccess": "{count} 件の選択された{type}に利用可能な更新があります",
             "bulkUpdatesNone": "選択された{type}には更新が見つかりませんでした",

locales/ko.json

@@ -687,6 +687,9 @@
             "autoOrganize": "자동 정리 선택",
             "skipMetadataRefresh": "선택한 모델의 메타데이터 새로고침 건너뛰기",
             "resumeMetadataRefresh": "선택한 모델의 메타데이터 새로고침 재개",
+            "setFavorite": "즐겨찾기로 설정",
+            "setFavoriteCount": "즐겨찾기로 설정 ({favorited}/{total})",
+            "unfavorite": "즐겨찾기 해제",
             "deleteAll": "선택된 항목 삭제",
             "downloadMissingLoras": "누락된 LoRA 다운로드",
             "clear": "선택 지우기",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "{count}개 모델의 콘텐츠 등급을 {level}(으)로 설정했습니다",
             "bulkContentRatingPartial": "{success}개 모델의 콘텐츠 등급을 {level}(으)로 설정했고, {failed}개는 실패했습니다",
             "bulkContentRatingFailed": "선택한 모델의 콘텐츠 등급을 업데이트하지 못했습니다",
+            "bulkFavoriteUpdating": "{count}개 모델을 즐겨찾기에 추가 중...",
+            "bulkUnfavoriteUpdating": "{count}개 모델을 즐겨찾기에서 제거 중...",
+            "bulkFavoritePartialAdded": "{success}개 모델을 즐겨찾기에 추가, {failed}개 실패",
+            "bulkFavoritePartialRemoved": "{success}개 모델을 즐겨찾기에서 제거, {failed}개 실패",
+            "bulkFavoriteFailed": "즐겨찾기 상태 업데이트 실패",
             "bulkUpdatesChecking": "선택한 {type}의 업데이트를 확인하는 중...",
             "bulkUpdatesSuccess": "선택한 {count}개의 {type}에 사용할 수 있는 업데이트가 있습니다",
             "bulkUpdatesNone": "선택한 {type}에 대한 업데이트가 없습니다",

locales/ru.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Автоматически организовать выбранные",
             "skipMetadataRefresh": "Пропустить обновление метаданных для выбранных",
             "resumeMetadataRefresh": "Возобновить обновление метаданных для выбранных",
+            "setFavorite": "Добавить в избранное",
+            "setFavoriteCount": "Добавить в избранное ({favorited}/{total})",
+            "unfavorite": "Удалить из избранного",
             "deleteAll": "Удалить выбранные",
             "downloadMissingLoras": "Скачать отсутствующие LoRAs",
             "clear": "Очистить выбор",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Рейтинг контента установлен на {level} для {count} модель(ей)",
             "bulkContentRatingPartial": "Рейтинг контента {level} установлен для {success} модель(ей), {failed} не удалось",
             "bulkContentRatingFailed": "Не удалось обновить рейтинг контента для выбранных моделей",
+            "bulkFavoriteUpdating": "Добавление {count} моделей в избранное...",
+            "bulkUnfavoriteUpdating": "Удаление {count} моделей из избранного...",
+            "bulkFavoritePartialAdded": "{success} моделей добавлено в избранное, {failed} не удалось",
+            "bulkFavoritePartialRemoved": "{success} моделей удалено из избранного, {failed} не удалось",
+            "bulkFavoriteFailed": "Не удалось обновить статус избранного",
             "bulkUpdatesChecking": "Проверка обновлений для выбранных {type}...",
             "bulkUpdatesSuccess": "Доступны обновления для {count} выбранных {type}",
             "bulkUpdatesNone": "Обновления для выбранных {type} не найдены",

locales/zh-CN.json

@@ -687,6 +687,9 @@
             "autoOrganize": "自动整理所选模型",
             "skipMetadataRefresh": "跳过所选模型的元数据刷新",
             "resumeMetadataRefresh": "恢复所选模型的元数据刷新",
+            "setFavorite": "设为收藏",
+            "setFavoriteCount": "设为收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
             "deleteAll": "删除已选",
             "downloadMissingLoras": "下载缺失的 LoRAs",
             "clear": "清除选择",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "已将 {count} 个模型的内容评级设置为 {level}",
             "bulkContentRatingPartial": "已将 {success} 个模型的内容评级设置为 {level}，{failed} 个失败",
             "bulkContentRatingFailed": "未能更新所选模型的内容评级",
+            "bulkFavoriteUpdating": "正在将 {count} 个模型添加到收藏...",
+            "bulkUnfavoriteUpdating": "正在将 {count} 个模型从收藏移除...",
+            "bulkFavoritePartialAdded": "已将 {success} 个模型添加到收藏，{failed} 个失败",
+            "bulkFavoritePartialRemoved": "已将 {success} 个模型从收藏移除，{failed} 个失败",
+            "bulkFavoriteFailed": "更新收藏状态失败",
             "bulkUpdatesChecking": "正在检查所选 {type} 的更新...",
             "bulkUpdatesSuccess": "{count} 个所选 {type} 有可用更新",
             "bulkUpdatesNone": "所选 {type} 未发现更新",

locales/zh-TW.json

@@ -687,6 +687,9 @@
             "autoOrganize": "自動整理所選模型",
             "skipMetadataRefresh": "跳過所選模型的元數據更新",
             "resumeMetadataRefresh": "恢復所選模型的元數據更新",
+            "setFavorite": "設為收藏",
+            "setFavoriteCount": "設為收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
             "deleteAll": "刪除所選",
             "downloadMissingLoras": "下載缺失的 LoRAs",
             "clear": "清除選取",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "已將 {count} 個模型的內容分級設定為 {level}",
             "bulkContentRatingPartial": "已將 {success} 個模型的內容分級設定為 {level}，{failed} 個失敗",
             "bulkContentRatingFailed": "無法更新所選模型的內容分級",
+            "bulkFavoriteUpdating": "正在將 {count} 個模型加入收藏...",
+            "bulkUnfavoriteUpdating": "正在將 {count} 個模型從收藏移除...",
+            "bulkFavoritePartialAdded": "已將 {success} 個模型加入收藏，{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "已將 {success} 個模型從收藏移除，{failed} 個失敗",
+            "bulkFavoriteFailed": "更新收藏狀態失敗",
             "bulkUpdatesChecking": "正在檢查所選 {type} 的更新...",
             "bulkUpdatesSuccess": "{count} 個所選 {type} 有可用更新",
             "bulkUpdatesNone": "所選 {type} 未找到更新",

py/services/civitai_base_model_service.py

@@ -193,6 +193,9 @@ class CivitaiBaseModelService:
             "zimageturbo": "ZIT",
             "zimagebase": "ZIB",
             "anima": "ANI",
+            "ernie": "ERNI",
+            "ernie turbo": "ETRB",
+            "nucleus": "NUCL",
             "svd": "SVD",
             "ltxv": "LTXV",
             "ltxv2": "LTV2",
@@ -418,6 +421,9 @@ class CivitaiBaseModelService:
                 "Kolors",
                 "NoobAI",
                 "Anima",
+                "Ernie",
+                "Ernie Turbo",
+                "Nucleus",
             ],
         }
 

py/services/civitai_client.py

@@ -577,6 +577,59 @@ class CivitaiClient:
             logger.error(error_msg)
             return None
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for up to 100 SHA256 hashes via the batch endpoint.
+
+        Uses POST /api/v1/model-versions/by-hash which returns full version
+        details including ``usageControl`` and ``earlyAccessEndsAt`` that are
+        not available from the model-level API.
+
+        Args:
+            hashes: List of SHA256 hashes (max 100 per batch; auto-split).
+
+        Returns:
+            List of version dicts or None on failure.
+        """
+        if not hashes:
+            return []
+
+        BATCH_SIZE = 100
+        all_versions: List[Dict] = []
+
+        for start in range(0, len(hashes), BATCH_SIZE):
+            batch = hashes[start : start + BATCH_SIZE]
+            try:
+                success, result = await self._make_request(
+                    "POST",
+                    f"{self.base_url}/model-versions/by-hash",
+                    use_auth=True,
+                    json=batch,
+                )
+                if not success:
+                    logger.warning(
+                        "Batch by-hash request failed for %d hashes: %s",
+                        len(batch),
+                        result,
+                    )
+                    continue
+
+                if isinstance(result, list):
+                    all_versions.extend(result)
+                else:
+                    logger.debug(
+                        "Unexpected by-hash response type: %s", type(result)
+                    )
+            except RateLimitError:
+                raise
+            except Exception as exc:  # pragma: no cover - defensive logging
+                logger.error(
+                    "Error fetching model versions by hashes: %s", exc
+                )
+
+        return all_versions if all_versions else None
+
     async def get_user_models(self, username: str) -> Optional[List[Dict]]:
         """Fetch all models for a specific Civitai user."""
         if not username:

py/services/model_metadata_provider.py

@@ -108,6 +108,18 @@ class ModelMetadataProvider(ABC):
     ) -> Optional[Dict[int, Dict]]:
         """Fetch model versions for multiple model ids when supported."""
         raise NotImplementedError
+
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for multiple SHA256 hashes.
+
+        Used specifically to retrieve ``usageControl`` which is only
+        available from the per-version / by-hash API, not from model-level
+        responses.  Providers that cannot resolve hashes should let the
+        default ``NotImplementedError`` propagate.
+        """
+        raise NotImplementedError
         
     @abstractmethod
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
@@ -140,6 +152,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
         self, model_ids: Sequence[int]
     ) -> Optional[Dict[int, Dict]]:
         return await self.client.get_model_versions_bulk(model_ids)
+
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self.client.get_model_versions_by_hashes(hashes)
         
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         return await self.client.get_model_version(model_id, version_id)
@@ -519,6 +536,32 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None, "No provider could retrieve the data"
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        for provider, label in self._iter_providers():
+            try:
+                result = await self._call_with_rate_limit(
+                    label,
+                    provider.get_model_versions_by_hashes,
+                    hashes,
+                )
+                if result is not None:
+                    return result
+            except NotImplementedError:
+                continue
+            except RateLimitError as exc:
+                exc.provider = exc.provider or label
+                raise exc
+            except Exception as e:
+                logger.debug(
+                    "Provider %s failed for get_model_versions_by_hashes: %s",
+                    label,
+                    e,
+                )
+                continue
+        return None
+
     async def get_user_models(self, username: str) -> Optional[List[Dict]]:
         for provider, label in self._iter_providers():
             try:
@@ -593,6 +636,15 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
             model_ids,
         )
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self._rate_limit_helper.run(
+            self._label,
+            self._provider.get_model_versions_by_hashes,
+            hashes,
+        )
+
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         return await self._rate_limit_helper.run(
             self._label,
@@ -669,6 +721,17 @@ class ModelMetadataProviderManager:
         provider = self._get_provider(provider_name)
         return await provider.get_model_version_info(version_id)
 
+    async def get_model_versions_by_hashes(
+        self,
+        hashes: List[str],
+        provider_name: str = None,
+    ) -> Optional[List[Dict]]:
+        provider = self._get_provider(provider_name)
+        try:
+            return await provider.get_model_versions_by_hashes(hashes)
+        except NotImplementedError:
+            return None
+
     async def get_user_models(self, username: str, provider_name: str = None) -> Optional[List[Dict]]:
         """Fetch models owned by the specified user"""
         provider = self._get_provider(provider_name)

py/services/model_update_service.py

@@ -989,6 +989,11 @@ class ModelUpdateService:
                 fallback_attempted = True
                 try:
                     response = await metadata_provider.get_model_versions(model_id)
+                    if response is not None:
+                        await self._enrich_version_entries(
+                            metadata_provider,
+                            {model_id: response},
+                        )
                 except RateLimitError:
                     raise
                 except ResourceNotFoundError as exc:
@@ -1083,6 +1088,136 @@ class ModelUpdateService:
             self._upsert_record(record)
             return record
 
+    async def _enrich_version_entries(
+        self,
+        metadata_provider,
+        responses_by_model_id: Dict[int, Mapping],
+    ) -> None:
+        """Enrich version entries with ``usageControl`` via batch hash endpoint.
+
+        The model-level API does not include ``usageControl`` on version
+        entries. This method collects SHA256 hashes from every version's
+        primary model file, calls ``POST /api/v1/model-versions/by-hash``
+        (up to 100 hashes per request), and injects ``usageControl`` +
+        ``earlyAccessEndsAt`` into each version entry dict in-place.
+        """
+        if not metadata_provider or not responses_by_model_id:
+            return
+
+        hashes_by_version: Dict[int, str] = {}
+        for response in responses_by_model_id.values():
+            hashes_by_version.update(
+                self._collect_hashes_from_response(response)
+            )
+
+        if not hashes_by_version:
+            return
+
+        version_ids_by_hash: Dict[str, List[int]] = {}
+        for version_id, sha256 in hashes_by_version.items():
+            version_ids_by_hash.setdefault(sha256, []).append(version_id)
+
+        all_hashes = list(version_ids_by_hash.keys())
+        BATCH_SIZE = 100
+
+        enrichment: Dict[int, Dict] = {}
+        try:
+            for start in range(0, len(all_hashes), BATCH_SIZE):
+                batch = all_hashes[start : start + BATCH_SIZE]
+                try:
+                    enriched = await metadata_provider.get_model_versions_by_hashes(
+                        batch
+                    )
+                except NotImplementedError:
+                    return
+                except RateLimitError:
+                    raise
+                except Exception:
+                    continue
+
+                if not enriched:
+                    continue
+
+                for entry in enriched:
+                    if not isinstance(entry, dict):
+                        continue
+                    version_id = entry.get("id")
+                    if version_id is None:
+                        continue
+                    enrichment[version_id] = {
+                        "usageControl": _normalize_string(
+                            entry.get("usageControl")
+                        ),
+                        "earlyAccessEndsAt": _normalize_string(
+                            entry.get("earlyAccessEndsAt")
+                        ),
+                    }
+        except RateLimitError:
+            raise
+
+        if not enrichment:
+            return
+
+        for response in responses_by_model_id.values():
+            versions = response.get("modelVersions")
+            if not isinstance(versions, list):
+                continue
+            for version in versions:
+                if not isinstance(version, dict):
+                    continue
+                version_id = version.get("id")
+                if version_id not in enrichment:
+                    continue
+                extra = enrichment[version_id]
+                if extra.get("usageControl") and not version.get("usageControl"):
+                    version["usageControl"] = extra["usageControl"]
+                if extra.get("earlyAccessEndsAt") and not version.get(
+                    "earlyAccessEndsAt"
+                ):
+                    version["earlyAccessEndsAt"] = extra["earlyAccessEndsAt"]
+
+    @staticmethod
+    def _collect_hashes_from_response(response: Mapping) -> Dict[int, str]:
+        """Extract ``{version_id: sha256}`` from a model-level API response.
+
+        Returns an empty dict if the response structure is unexpected.
+        """
+        result: Dict[int, str] = {}
+        versions = response.get("modelVersions")
+        if not isinstance(versions, list):
+            return result
+        for entry in versions:
+            if not isinstance(entry, dict):
+                continue
+            version_id = _normalize_int(entry.get("id"))
+            if version_id is None:
+                continue
+            sha256 = ModelUpdateService._extract_sha256_from_version_entry(entry)
+            if sha256:
+                result[version_id] = sha256
+        return result
+
+    @staticmethod
+    def _extract_sha256_from_version_entry(entry: Mapping) -> Optional[str]:
+        """Return the SHA256 hash from the primary model file of a version entry."""
+        files = entry.get("files")
+        if not isinstance(files, list):
+            return None
+        for file_info in files:
+            if not isinstance(file_info, dict):
+                continue
+            if file_info.get("type") != "Model":
+                continue
+            primary = file_info.get("primary")
+            if primary is not True and str(primary).strip().lower() != "true":
+                continue
+            hashes = file_info.get("hashes")
+            if isinstance(hashes, dict):
+                sha256 = hashes.get("SHA256")
+                if sha256:
+                    return sha256
+        return None
+
     async def _fetch_model_versions_bulk(
         self,
         metadata_provider,
@@ -1134,6 +1269,7 @@ class ModelUpdateService:
             len(aggregated),
             provider_name,
         )
+        await self._enrich_version_entries(metadata_provider, aggregated)
         return aggregated
 
     async def _collect_local_versions(
@@ -1261,6 +1397,7 @@ class ModelUpdateService:
                     sort_index=sort_map.get(version_id, index),
                     early_access_ends_at=remote_version.early_access_ends_at,
                     is_early_access=remote_version.is_early_access,
+                    usage_control=remote_version.usage_control,
                 )
             )
 

py/utils/constants.py

@@ -178,5 +178,8 @@ SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
         "Wan Video 2.5 I2V",
         "Hunyuan Video",
         "Anima",
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
     ]
 )

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.5"
+version = "1.0.6"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

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

@@ -387,6 +387,10 @@
     cursor: not-allowed;
 }
 
+.version-action-disabled-wrapper {
+    display: inline-flex;
+}
+
 .versions-loading-state,
 .versions-empty,
 .versions-error {

static/js/components/ContextMenu/BulkContextMenu.js

@@ -74,6 +74,34 @@ export class BulkContextMenu extends BaseContextMenu {
         if (setContentRatingItem) {
             setContentRatingItem.style.display = config.setContentRating ? 'flex' : 'none';
         }
+
+        const setFavoriteItem = this.menu.querySelector('[data-action="set-favorite"]');
+
+        if (setFavoriteItem && config.setFavorite) {
+            setFavoriteItem.style.display = 'flex';
+
+            const total = state.selectedModels.size;
+            const favoritedCount = this.countFavoritedInSelection();
+            const allFavorited = total > 0 && favoritedCount === total;
+
+            const icon = setFavoriteItem.querySelector('i');
+            const label = setFavoriteItem.querySelector('span');
+
+            if (allFavorited) {
+                if (icon) { icon.className = 'far fa-star'; }
+                if (label) { label.textContent = translate('loras.bulkOperations.unfavorite'); }
+            } else {
+                if (icon) { icon.className = 'fas fa-star'; }
+                if (label) {
+                    label.textContent = favoritedCount > 0
+                        ? translate('loras.bulkOperations.setFavoriteCount', { favorited: favoritedCount, total })
+                        : translate('loras.bulkOperations.setFavorite');
+                }
+            }
+        } else if (setFavoriteItem) {
+            setFavoriteItem.style.display = 'none';
+        }
+
         if (downloadMissingLorasItem) {
             // Only show for recipes page
             downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
@@ -138,6 +166,20 @@ export class BulkContextMenu extends BaseContextMenu {
         return count;
     }
 
+    countFavoritedInSelection() {
+        let count = 0;
+        for (const filePath of state.selectedModels) {
+            const escapedPath = window.CSS && typeof window.CSS.escape === 'function'
+                ? window.CSS.escape(filePath)
+                : filePath.replace(/["\\]/g, '\\$&');
+            const card = document.querySelector(`.model-card[data-filepath="${escapedPath}"]`);
+            if (card && card.dataset.favorite === 'true') {
+                count++;
+            }
+        }
+        return count;
+    }
+
     showMenu(x, y, card) {
         this.updateMenuItemsForModelType();
         this.updateSelectedCountHeader();
@@ -185,6 +227,11 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'delete-all':
                 bulkManager.showBulkDeleteModal();
                 break;
+            case 'set-favorite': {
+                const allFavorited = this.countFavoritedInSelection() === state.selectedModels.size;
+                bulkManager.setBulkFavorites(!allFavorited);
+                break;
+            }
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;

static/js/components/shared/ModelVersionsTab.js

@@ -241,7 +241,7 @@ function buildActionButton(label, variant, action, options = {}) {
     if (action) {
         attributes.push(`data-version-action="${escapeHtml(action)}"`);
     }
-    if (options.title) {
+    if (!options.disabled && options.title) {
         attributes.push(`title="${escapeHtml(options.title)}"`);
         attributes.push(`aria-label="${escapeHtml(options.title)}"`);
     }
@@ -251,7 +251,11 @@ function buildActionButton(label, variant, action, options = {}) {
     if (options.extraAttributes) {
         attributes.push(options.extraAttributes);
     }
-    return `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    const buttonHtml = `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    if (options.disabled && options.title) {
+        return `<span class="version-action-disabled-wrapper" title="${escapeHtml(options.title)}" aria-label="${escapeHtml(options.title)}">${buttonHtml}</span>`;
+    }
+    return buttonHtml;
 }
 
 const DISPLAY_FILTER_MODES = Object.freeze({

static/js/managers/BulkManager.js

@@ -3,7 +3,7 @@ import { showToast, copyToClipboard, sendLoraToWorkflow, buildLoraSyntax, getNSF
 import { updateCardsForBulkMode } from '../components/shared/ModelCard.js';
 import { modalManager } from './ModalManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
-import { RecipeSidebarApiClient } from '../api/recipeApi.js';
+import { RecipeSidebarApiClient, updateRecipeMetadata } from '../api/recipeApi.js';
 import { MODEL_TYPES, MODEL_CONFIG } from '../api/apiConfig.js';
 import { BASE_MODEL_CATEGORIES } from '../utils/constants.js';
 import { getPriorityTagSuggestions } from '../utils/priorityTagHelpers.js';
@@ -41,7 +41,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             [MODEL_TYPES.EMBEDDING]: {
                 addTags: true,
@@ -53,7 +55,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: false,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             [MODEL_TYPES.CHECKPOINT]: {
                 addTags: true,
@@ -65,7 +69,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             recipes: {
                 addTags: false,
@@ -77,7 +83,9 @@ export class BulkManager {
                 autoOrganize: false,
                 deleteAll: true,
                 setContentRating: false,
-                skipMetadataRefresh: false
+                skipMetadataRefresh: false,
+                setFavorite: true,
+                unfavorite: true
             }
         };
 
@@ -1090,6 +1098,60 @@ export class BulkManager {
         }
     }
 
+    async setBulkFavorites(value) {
+        if (state.selectedModels.size === 0) {
+            showToast('toast.models.noModelsSelected', {}, 'warning');
+            return;
+        }
+
+        const totalCount = state.selectedModels.size;
+        const isRecipesPage = state.currentPageType === 'recipes';
+
+        state.loadingManager.showSimpleLoading(
+            translate(value ? 'toast.models.bulkFavoriteUpdating' : 'toast.models.bulkUnfavoriteUpdating', { count: totalCount })
+        );
+        let cancelled = false;
+        state.loadingManager.showCancelButton(() => {
+            cancelled = true;
+        });
+
+        let successCount = 0;
+        let failureCount = 0;
+
+        try {
+            for (const filePath of state.selectedModels) {
+                if (cancelled) {
+                    showToast('toast.api.operationCancelled', {}, 'info');
+                    break;
+                }
+                try {
+                    if (isRecipesPage) {
+                        await updateRecipeMetadata(filePath, { favorite: value });
+                    } else {
+                        const apiClient = getModelApiClient();
+                        await apiClient.saveModelMetadata(filePath, { favorite: value });
+                    }
+                    successCount++;
+                } catch (error) {
+                    failureCount++;
+                    console.error(`Failed to set favorite=${value} for ${filePath}:`, error);
+                }
+            }
+        } finally {
+            state.loadingManager?.hide?.();
+        }
+
+        if (successCount === totalCount) {
+            const toastKey = value ? 'modelCard.favorites.added' : 'modelCard.favorites.removed';
+            showToast(toastKey, {}, 'success');
+        } else if (successCount > 0) {
+            const toastKey = value ? 'toast.models.bulkFavoritePartialAdded' : 'toast.models.bulkFavoritePartialRemoved';
+            showToast(toastKey, { success: successCount, failed: failureCount }, 'warning');
+        } else {
+            showToast('toast.models.bulkFavoriteFailed', {}, 'error');
+        }
+    }
+
     /**
      * Show bulk base model modal
      */

static/js/utils/constants.js

@@ -66,6 +66,9 @@ export const BASE_MODELS = {
     HUNYUAN_VIDEO: "Hunyuan Video",
     // Other models
     ANIMA: "Anima",
+    ERNIE: "Ernie",
+    ERNIE_TURBO: "Ernie Turbo",
+    NUCLEUS: "Nucleus",
     PONY_V7: "Pony V7",
     // Default
     UNKNOWN: "Other"
@@ -191,6 +194,9 @@ export const BASE_MODEL_ABBREVIATIONS = {
     [BASE_MODELS.ZIMAGE_TURBO]: 'ZIT',
     [BASE_MODELS.ZIMAGE_BASE]: 'ZIB',
     [BASE_MODELS.ANIMA]: 'ANI',
+    [BASE_MODELS.ERNIE]: 'ERNI',
+    [BASE_MODELS.ERNIE_TURBO]: 'ETRB',
+    [BASE_MODELS.NUCLEUS]: 'NUCL',
 
     // Default
     [BASE_MODELS.UNKNOWN]: 'OTH'
@@ -394,6 +400,7 @@ export const BASE_MODEL_CATEGORIES = {
         BASE_MODELS.QWEN, BASE_MODELS.AURAFLOW, BASE_MODELS.CHROMA, BASE_MODELS.ZIMAGE_TURBO, BASE_MODELS.ZIMAGE_BASE,
         BASE_MODELS.PIXART_A, BASE_MODELS.PIXART_E, BASE_MODELS.HUNYUAN_1,
         BASE_MODELS.LUMINA, BASE_MODELS.KOLORS, BASE_MODELS.NOOBAI, BASE_MODELS.ANIMA,
+        BASE_MODELS.ERNIE, BASE_MODELS.ERNIE_TURBO, BASE_MODELS.NUCLEUS,
         BASE_MODELS.UNKNOWN
     ]
 };

templates/components/context_menu.html

@@ -77,6 +77,9 @@
     <div class="context-menu-item" data-action="set-base-model">
         <i class="fas fa-layer-group"></i> <span>{{ t('loras.bulkOperations.setBaseModel') }}</span>
     </div>
+    <div class="context-menu-item" data-action="set-favorite">
+        <i class="fas fa-star"></i> <span>{{ t('loras.bulkOperations.setFavorite') }}</span>
+    </div>
     <div class="context-menu-item" data-action="set-content-rating">
         <i class="fas fa-exclamation-triangle"></i> <span>{{ t('loras.bulkOperations.setContentRating') }}</span>
     </div>

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

@@ -114,7 +114,8 @@ describe('LoRA widget drag interactions', () => {
     dragEl.dispatchEvent(new PointerEvent('pointerup', { pointerId: 1 }));
     expect(document.body.classList.contains('lm-lora-strength-dragging')).toBe(false);
     expect(onDragEnd).toHaveBeenCalledTimes(1);
-    expect(renderSpy).toHaveBeenCalledWith(widget.value, widget);
+    // 454210a4 replaced renderFunction() with widget.value setter + widget.callback()
+    expect(widget.callback).toHaveBeenCalledWith(widget.value);
   });
 
   it('deletes the selected LoRA when backspace is pressed outside of strength inputs', async () => {