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4 Commits

Author SHA1 Message Date
Will Miao
6d5b4b7312 fix(test): update drag interaction test to match 454210a4's renderFunction→setValue change
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.
2026-05-07 11:03:38 +08:00
Will Miao
7803bd542d feat(base-models): add Ernie, Ernie Turbo, Nucleus base model types (#922)
- Ernie & Anima: auto-fetched via CivitaiBaseModelService from Civitai API
- Ernie Turbo & Nucleus: pre-added as hardcoded constants (not yet in Civitai API)
- Added abbreviations (ERNI, ETRB, NUCL) and category entries across all layers
2026-05-07 10:49:01 +08:00
Will Miao
f0a86dbbc0 feat(bulk): add bulk favorite/unfavorite toggle with context-sensitive single menu item
Replaces two separate menu items with a single smart item that dynamically
switches between 'Set as Favorite' and 'Remove from Favorites' based on
whether all selected items are already favorited. Shows a count badge
'(3/5)' when only some items are favorited in a mixed selection.

Supports all model types (LoRA, Checkpoint, Embedding) and recipes via
existing per-item save/update API — no backend changes needed.
2026-05-07 09:51:23 +08:00
Will Miao
682e964f89 fix(usage-control): enrich usageControl from CivitAI by-hash API for all model types
The model-level API (GET /api/v1/models/{id}) does not include usageControl
on version entries, causing generation-only models to show as downloadable.

Backend changes:
- Add get_model_versions_by_hashes() to CivitaiClient (POST by-hash batch)
- Propagate through all provider classes including RateLimitRetryingProvider
- Add _enrich_version_entries() pipeline: extract SHA256 from files[].hashes,
  batch-call by-hash endpoint, inject usageControl+earlyAccessEndsAt in-place
- Wire enrichment into both bulk (_fetch_model_versions_bulk) and individual
  (_refresh_single_model) refresh paths
- Fix _build_record_from_remote dropping usage_control field
- Fix POST by-hash request format (plain JSON array, not {hashes:[...]} object)

Frontend changes:
- Fix disabled download button tooltip: wrap in <span> since HTML title
  attribute does not fire on disabled elements
2026-05-07 08:56:19 +08:00
22 changed files with 478 additions and 8 deletions

View File

@@ -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",

View File

@@ -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)",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",

View File

@@ -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",
],
}

View File

@@ -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:

View File

@@ -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)

View File

@@ -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,
)
)

View File

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

View File

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

View File

@@ -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;

View File

@@ -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({

View File

@@ -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
*/

View File

@@ -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
]
};

View File

@@ -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>

View File

@@ -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 () => {