feat(example-images): add missing-only download path and skip existing files

Split the single-model and bulk context menu actions into 'Download
Missing Example Images' (regular endpoint, skips already-processed
models) and 'Re-process Example Images' (force endpoint, retries
failed models).

- start_download accepts model_hashes so a selected subset can be
  processed with the progress-aware skip logic; explicitly targeted
  models bypass the failed/processed model-level guards so per-image
  gaps are filled
- pre-download existence check in the processor skips network requests
  for image files already on disk across all download paths
- force download retries previously failed models and clears their
  failed status on success
- add i18n keys for the new menu items across all locales

locales/de.json

@@ -772,7 +772,8 @@
             "unfavorite": "Aus Favoriten entfernen",
             "deleteAll": "Ausgewählte löschen",
             "downloadMissingLoras": "Fehlende LoRAs herunterladen",
-      "downloadExamples": "Beispielbilder herunterladen",
+            "downloadMissingExamples": "Fehlende Beispielbilder herunterladen",
+            "reprocessExamples": "Beispielbilder erneut verarbeiten",
             "clear": "Auswahl löschen",
             "skipMetadataRefreshCount": "Überspringen（{count} Modelle）",
             "resumeMetadataRefreshCount": "Fortsetzen（{count} Modelle）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "An Workflow senden (Anhängen)",
             "sendToWorkflowReplace": "An Workflow senden (Ersetzen)",
             "openExamples": "Beispiele-Ordner öffnen",
-      "downloadExamples": "Beispielbilder herunterladen",
+            "downloadExamples": "Fehlende Beispielbilder herunterladen",
+            "reprocessExamples": "Beispielbilder erneut verarbeiten",
             "replacePreview": "Vorschau ersetzen",
             "setContentRating": "Inhaltsbewertung festlegen",
             "moveToFolder": "In Ordner verschieben",

locales/en.json

@@ -772,7 +772,8 @@
       "unfavorite": "Remove from Favorites",
       "deleteAll": "Delete Selected",
       "downloadMissingLoras": "Download Missing LoRAs",
-      "downloadExamples": "Download Example Images",
+      "downloadMissingExamples": "Download Missing Example Images",
+      "reprocessExamples": "Re-process Example Images",
       "clear": "Clear Selection",
       "skipMetadataRefreshCount": "Skip ({count} models)",
       "resumeMetadataRefreshCount": "Resume ({count} models)",
@@ -807,7 +808,8 @@
       "sendToWorkflowAppend": "Send to Workflow (Append)",
       "sendToWorkflowReplace": "Send to Workflow (Replace)",
       "openExamples": "Open Examples Folder",
-      "downloadExamples": "Download Example Images",
+      "downloadExamples": "Download Missing Example Images",
+      "reprocessExamples": "Re-process Example Images",
       "replacePreview": "Replace Preview",
       "setContentRating": "Set Content Rating",
       "moveToFolder": "Move to Folder",

locales/es.json

@@ -772,7 +772,8 @@
             "unfavorite": "Quitar de favoritos",
             "deleteAll": "Eliminar seleccionados",
             "downloadMissingLoras": "Descargar LoRAs faltantes",
-      "downloadExamples": "Descargar imágenes de ejemplo",
+            "downloadMissingExamples": "Descargar imágenes de ejemplo faltantes",
+            "reprocessExamples": "Reprocesar imágenes de ejemplo",
             "clear": "Limpiar selección",
             "skipMetadataRefreshCount": "Omitir（{count} modelos）",
             "resumeMetadataRefreshCount": "Reanudar（{count} modelos）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "Enviar al flujo de trabajo (Añadir)",
             "sendToWorkflowReplace": "Enviar al flujo de trabajo (Reemplazar)",
             "openExamples": "Abrir carpeta de ejemplos",
-      "downloadExamples": "Descargar imágenes de ejemplo",
+            "downloadExamples": "Descargar imágenes de ejemplo faltantes",
+            "reprocessExamples": "Reprocesar imágenes de ejemplo",
             "replacePreview": "Reemplazar vista previa",
             "setContentRating": "Establecer clasificación de contenido",
             "moveToFolder": "Mover a carpeta",

locales/fr.json

@@ -772,7 +772,8 @@
             "unfavorite": "Retirer des favoris",
             "deleteAll": "Supprimer la sélection",
             "downloadMissingLoras": "Télécharger les LoRAs manquants",
-      "downloadExamples": "Télécharger les images d'exemple",
+            "downloadMissingExamples": "Télécharger les images d'exemple manquantes",
+            "reprocessExamples": "Retraiter les images d'exemple",
             "clear": "Effacer la sélection",
             "skipMetadataRefreshCount": "Ignorer（{count} modèles）",
             "resumeMetadataRefreshCount": "Reprendre（{count} modèles）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "Envoyer vers le workflow (Ajouter)",
             "sendToWorkflowReplace": "Envoyer vers le workflow (Remplacer)",
             "openExamples": "Ouvrir le dossier d'exemples",
-      "downloadExamples": "Télécharger les images d'exemple",
+            "downloadExamples": "Télécharger les images d'exemple manquantes",
+            "reprocessExamples": "Retraiter les images d'exemple",
             "replacePreview": "Remplacer l'aperçu",
             "setContentRating": "Définir la classification du contenu",
             "moveToFolder": "Déplacer vers un dossier",

locales/he.json

@@ -772,7 +772,8 @@
             "unfavorite": "הסר ממועדפים",
             "deleteAll": "מחק נבחרים",
             "downloadMissingLoras": "הורדת LoRAs חסרים",
-      "downloadExamples": "הורד תמונות דוגמה",
+            "downloadMissingExamples": "הורדת תמונות דוגמה חסרות",
+            "reprocessExamples": "עיבוד מחדש של תמונות דוגמה",
             "clear": "נקה בחירה",
             "skipMetadataRefreshCount": "דילוג（{count} מודלים）",
             "resumeMetadataRefreshCount": "המשך（{count} מודלים）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "שלח ל-Workflow (הוסף)",
             "sendToWorkflowReplace": "שלח ל-Workflow (החלף)",
             "openExamples": "פתח תיקיית דוגמאות",
-      "downloadExamples": "הורד תמונות דוגמה",
+            "downloadExamples": "הורדת תמונות דוגמה חסרות",
+            "reprocessExamples": "עיבוד מחדש של תמונות דוגמה",
             "replacePreview": "החלף תצוגה מקדימה",
             "setContentRating": "הגדר דירוג תוכן",
             "moveToFolder": "העבר לתיקייה",

locales/ja.json

@@ -772,7 +772,8 @@
             "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",
-      "downloadExamples": "例画像をダウンロード",
+            "downloadMissingExamples": "不足しているサンプル画像をダウンロード",
+            "reprocessExamples": "サンプル画像を再処理",
             "clear": "選択をクリア",
             "skipMetadataRefreshCount": "スキップ（{count}モデル）",
             "resumeMetadataRefreshCount": "再開（{count}モデル）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "ワークフローに送信（追加）",
             "sendToWorkflowReplace": "ワークフローに送信（置換）",
             "openExamples": "例画像フォルダを開く",
-      "downloadExamples": "例画像をダウンロード",
+            "downloadExamples": "不足しているサンプル画像をダウンロード",
+            "reprocessExamples": "サンプル画像を再処理",
             "replacePreview": "プレビューを置換",
             "setContentRating": "コンテンツレーティングを設定",
             "moveToFolder": "フォルダに移動",

locales/ko.json

@@ -772,7 +772,8 @@
             "unfavorite": "즐겨찾기 해제",
             "deleteAll": "선택된 항목 삭제",
             "downloadMissingLoras": "누락된 LoRA 다운로드",
-      "downloadExamples": "예시 이미지 다운로드",
+            "downloadMissingExamples": "누락된 예시 이미지 다운로드",
+            "reprocessExamples": "예시 이미지 다시 처리",
             "clear": "선택 지우기",
             "skipMetadataRefreshCount": "건너뛰기（{count}개 모델）",
             "resumeMetadataRefreshCount": "재개（{count}개 모델）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "워크플로로 전송 (추가)",
             "sendToWorkflowReplace": "워크플로로 전송 (교체)",
             "openExamples": "예시 폴더 열기",
-      "downloadExamples": "예시 이미지 다운로드",
+            "downloadExamples": "누락된 예시 이미지 다운로드",
+            "reprocessExamples": "예시 이미지 다시 처리",
             "replacePreview": "미리보기 교체",
             "setContentRating": "콘텐츠 등급 설정",
             "moveToFolder": "폴더로 이동",

locales/ru.json

@@ -772,7 +772,8 @@
             "unfavorite": "Удалить из избранного",
             "deleteAll": "Удалить выбранные",
             "downloadMissingLoras": "Скачать отсутствующие LoRAs",
-      "downloadExamples": "Загрузить примеры изображений",
+            "downloadMissingExamples": "Загрузить недостающие примеры изображений",
+            "reprocessExamples": "Повторно обработать примеры изображений",
             "clear": "Очистить выбор",
             "skipMetadataRefreshCount": "Пропустить（{count} моделей）",
             "resumeMetadataRefreshCount": "Возобновить（{count} моделей）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "Отправить в Workflow (Добавить)",
             "sendToWorkflowReplace": "Отправить в Workflow (Заменить)",
             "openExamples": "Открыть папку примеров",
-      "downloadExamples": "Загрузить примеры изображений",
+            "downloadExamples": "Загрузить недостающие примеры изображений",
+            "reprocessExamples": "Повторно обработать примеры изображений",
             "replacePreview": "Заменить превью",
             "setContentRating": "Установить рейтинг контента",
             "moveToFolder": "Переместить в папку",

locales/zh-CN.json

@@ -772,7 +772,8 @@
             "unfavorite": "取消收藏",
             "deleteAll": "删除已选",
             "downloadMissingLoras": "下载缺失的 LoRAs",
-      "downloadExamples": "下载示例图片",
+            "downloadMissingExamples": "下载缺失的示例图片",
+            "reprocessExamples": "重新处理示例图片",
             "clear": "清除选择",
             "skipMetadataRefreshCount": "跳过（{count} 个模型）",
             "resumeMetadataRefreshCount": "恢复（{count} 个模型）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "发送到工作流（追加）",
             "sendToWorkflowReplace": "发送到工作流（替换）",
             "openExamples": "打开示例文件夹",
-      "downloadExamples": "下载示例图片",
+            "downloadExamples": "下载缺失的示例图片",
+            "reprocessExamples": "重新处理示例图片",
             "replacePreview": "替换预览",
             "setContentRating": "设置内容评级",
             "moveToFolder": "移动到文件夹",

locales/zh-TW.json

@@ -772,7 +772,8 @@
             "unfavorite": "取消收藏",
             "deleteAll": "刪除所選",
             "downloadMissingLoras": "下載缺失的 LoRAs",
-      "downloadExamples": "下載範例圖片",
+            "downloadMissingExamples": "下載缺少的範例圖片",
+            "reprocessExamples": "重新處理範例圖片",
             "clear": "清除選取",
             "skipMetadataRefreshCount": "跳過（{count} 個模型）",
             "resumeMetadataRefreshCount": "恢復（{count} 個模型）",
@@ -807,7 +808,8 @@
             "sendToWorkflowAppend": "傳送到工作流（附加）",
             "sendToWorkflowReplace": "傳送到工作流（取代）",
             "openExamples": "開啟範例資料夾",
-      "downloadExamples": "下載範例圖片",
+            "downloadExamples": "下載缺少的範例圖片",
+            "reprocessExamples": "重新處理範例圖片",
             "replacePreview": "更換預覽圖",
             "setContentRating": "設定內容分級",
             "moveToFolder": "移動到資料夾",

py/utils/example_images_download_manager.py

@@ -172,6 +172,7 @@ class DownloadManager:
         model_types = data.get("model_types", ["lora", "checkpoint"])
         delay = float(data.get("delay", 0.2))
         force = data.get("force", False)
+        model_hashes = data.get("model_hashes", [])
 
         # Step 2: Validate configuration (fast lookup)
         settings_manager = get_settings_manager()
@@ -241,6 +242,7 @@ class DownloadManager:
                         delay,
                         active_library,
                         force,
+                        model_hashes,
                     )
                 )
 
@@ -577,8 +579,9 @@ class DownloadManager:
         delay,
         library_name,
         force: bool = False,
+        model_hashes: list[str] | None = None,
     ):
-        """Download example images for all models."""
+        """Download example images for all models (or only the given hashes)."""
 
         downloader = await get_downloader()
 
@@ -606,6 +609,18 @@ class DownloadManager:
                         if model.get("sha256"):
                             all_models.append((scanner_type, model, scanner))
 
+            # Restrict to the requested hashes when provided (empty = all models).
+            # Explicit targets are a directed user request, so previously failed
+            # models are retried instead of skipped.
+            explicit_targets = bool(model_hashes)
+            if model_hashes:
+                hash_set = {h.lower() for h in model_hashes}
+                all_models = [
+                    (scanner_type, model, scanner)
+                    for scanner_type, model, scanner in all_models
+                    if model.get("sha256", "").lower() in hash_set
+                ]
+
             # Update total count
             self._progress["total"] = len(all_models)
             logger.debug(f"Found {self._progress['total']} models to process")
@@ -629,6 +644,7 @@ class DownloadManager:
                     downloader,
                     library_name,
                     force,
+                    explicit_targets,
                 )
 
                 # Update progress
@@ -725,6 +741,7 @@ class DownloadManager:
         downloader,
         library_name,
         force: bool = False,
+        explicit_targets: bool = False,
     ):
         """Process a single model download."""
 
@@ -747,8 +764,9 @@ class DownloadManager:
             self._progress["current_model"] = f"{model_name} ({model_hash[:8]})"
             await self._broadcast_progress(status="running")
 
-            # Skip if already in failed models (unless force mode is enabled)
+            # Skip if already in failed models (unless force mode is enabled or
-            if not force and model_hash in self._progress["failed_models"]:
+            # the model was explicitly targeted by hash)
+            if not force and not explicit_targets and model_hash in self._progress["failed_models"]:
                 logger.debug(f"Skipping known failed model: {model_name}")
                 return False
 
@@ -757,6 +775,10 @@ class DownloadManager:
             )
             existing_files = _model_directory_has_files(model_dir)
 
+            # Model-level guard: a populated folder counts as done. Explicitly
+            # targeted models bypass it so the per-image existence pre-check can
+            # fill individual gaps without re-fetching existing files.
+            if not explicit_targets:
                 # Skip if already processed AND directory exists with files
                 if model_hash in self._progress["processed_models"]:
                     if existing_files:
@@ -884,7 +906,7 @@ class DownloadManager:
                         model_name,
                     )
                     # Clear failed_models so non-force runs can retry
-                    if force and model_hash in self._progress["failed_models"]:
+                    if (force or explicit_targets) 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"
@@ -904,7 +926,7 @@ class DownloadManager:
                     )
                 elif success:
                     self._progress["processed_models"].add(model_hash)
-                    if force and model_hash in self._progress["failed_models"]:
+                    if (force or explicit_targets) 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 successful force retry"

py/utils/example_images_processor.py

@@ -113,6 +113,26 @@ class ExampleImagesProcessor:
         message = str(error).lower()
         return '404' in message or 'file not found' in message
 
+    @staticmethod
+    def _example_image_file_exists(model_dir: str, index: int, media_type_hint: str | None = None) -> bool:
+        """Return True when the file that would be written for a media index already exists.
+
+        The final filename (``image_{index}{extension}``) depends on the downloaded
+        content, so the extension cannot be known ahead of time. The post-download
+        check skips the write when the exact target file exists; this pre-check
+        approximates that with the candidate extensions for the media type (videos
+        only when the metadata hints at a video) so the network request is avoided
+        for files that already exist on disk.
+        """
+        if media_type_hint == "video":
+            extensions = SUPPORTED_MEDIA_EXTENSIONS['videos']
+        else:
+            extensions = SUPPORTED_MEDIA_EXTENSIONS['images']
+        return any(
+            os.path.exists(os.path.join(model_dir, f"image_{index}{ext}"))
+            for ext in extensions
+        )
+
     @staticmethod
     async def download_model_images(model_hash, model_name, model_images, model_dir, optimize, downloader):
         """Download images for a single model
@@ -140,6 +160,11 @@ class ExampleImagesProcessor:
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
 
+            # Skip the download when the file already exists on disk
+            if ExampleImagesProcessor._example_image_file_exists(model_dir, i, image.get("type")):
+                logger.debug("File already exists, skipping download for %s", image_url)
+                continue
+
             # Download the file first to determine the actual file type
             try:
                 logger.debug(f"Downloading media file {i} for {model_name}")
@@ -229,6 +254,11 @@ class ExampleImagesProcessor:
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
 
+            # Skip the download when the file already exists on disk
+            if ExampleImagesProcessor._example_image_file_exists(model_dir, i, image.get("type")):
+                logger.debug("File already exists, skipping download for %s", image_url)
+                continue
+
             async def _attempt_download() -> tuple:
                 logger.debug("Downloading media file %s for %s", i, model_name)
                 return await downloader.download_to_memory(

static/js/api/apiConfig.js

@@ -184,7 +184,8 @@ export const DOWNLOAD_ENDPOINTS = {
     downloadGet: '/api/lm/download-model-get',
     cancelGet: '/api/lm/cancel-download-get',
     progress: '/api/lm/download-progress',
-    exampleImages: '/api/lm/force-download-example-images' // New endpoint for downloading example images
+    exampleImages: '/api/lm/force-download-example-images', // Re-process example images ignoring previous status
+    exampleImagesMissing: '/api/lm/download-example-images' // Download only missing example images
 };
 
 // Hugging Face API endpoints

static/js/api/baseModelApi.js

@@ -1641,7 +1641,7 @@ export class BaseModelApiClient {
         }
     }
 
-    async downloadExampleImages(modelHashes, modelTypes = null) {
+    async downloadExampleImages(modelHashes, modelTypes = null, { force = true } = {}) {
         let ws = null;
 
         await state.loadingManager.showWithProgress(async (loading) => {
@@ -1700,8 +1700,13 @@ export class BaseModelApiClient {
                 // Determine optimize setting
                 const optimize = state.global?.settings?.optimize_example_images ?? true;
 
+                // force=false routes to the regular endpoint, which skips already-processed models
+                const endpoint = force
+                    ? DOWNLOAD_ENDPOINTS.exampleImages
+                    : DOWNLOAD_ENDPOINTS.exampleImagesMissing;
+
                 // Make the API request to start the download process
-                const response = await fetch(DOWNLOAD_ENDPOINTS.exampleImages, {
+                const response = await fetch(endpoint, {
                     method: 'POST',
                     headers: {
                         'Content-Type': 'application/json'
@@ -1710,6 +1715,7 @@ export class BaseModelApiClient {
                         model_hashes: modelHashes,
                         output_dir: outputDir,
                         optimize: optimize,
+                        force: force,
                         model_types: modelTypes || [this.apiConfig.config.singularName]
                     })
                 });

static/js/components/ContextMenu/BulkContextMenu.js

@@ -144,6 +144,12 @@ export class BulkContextMenu extends BaseContextMenu {
             downloadExampleImagesItem.style.display = modelPages.includes(currentModelType) ? 'flex' : 'none';
         }
 
+        const downloadMissingExampleImagesItem = this.menu.querySelector('[data-action="download-missing-example-images"]');
+        if (downloadMissingExampleImagesItem) {
+            // Show on model pages (loras, checkpoints, embeddings), hide on recipes
+            downloadMissingExampleImagesItem.style.display = ['loras', 'checkpoints', 'embeddings'].includes(currentModelType) ? 'flex' : 'none';
+        }
+
         const skipMetadataRefreshItem = this.menu.querySelector('[data-action="skip-metadata-refresh"]');
         const resumeMetadataRefreshItem = this.menu.querySelector('[data-action="resume-metadata-refresh"]');
 
@@ -294,8 +300,11 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;
+            case 'download-missing-example-images':
+                this.handleDownloadExampleImages({ force: false });
+                break;
             case 'download-example-images':
-                this.handleDownloadExampleImages();
+                this.handleDownloadExampleImages({ force: true });
                 break;
             case 'clear':
                 bulkManager.clearSelection();
@@ -340,7 +349,7 @@ export class BulkContextMenu extends BaseContextMenu {
         await bulkMissingLoraDownloadManager.downloadMissingLoras(selectedRecipes);
     }
 
-    async handleDownloadExampleImages() {
+    async handleDownloadExampleImages({ force = true } = {}) {
         if (state.selectedModels.size === 0) {
             return;
         }
@@ -361,7 +370,7 @@ export class BulkContextMenu extends BaseContextMenu {
 
         try {
             const apiClient = getModelApiClient();
-            await apiClient.downloadExampleImages([...hashes]);
+            await apiClient.downloadExampleImages([...hashes], null, { force });
         } catch (error) {
             console.error('Bulk download example images failed:', error);
         }

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -347,7 +347,10 @@ export const ModelContextMenuMixin = {
                 openExampleImagesFolder(this.currentCard.dataset.sha256);
                 return true;
             case 'download-examples':
-                this.downloadExampleImages();
+                this.downloadExampleImages(false);
+                return true;
+            case 'download-examples-force':
+                this.downloadExampleImages(true);
                 return true;
             case 'civitai':
                 if (this.currentCard.dataset.from_civitai === 'true') {
@@ -378,7 +381,7 @@ export const ModelContextMenuMixin = {
     },
 
     // Download example images method
-    async downloadExampleImages() {
+    async downloadExampleImages(force = false) {
         const modelHash = this.currentCard.dataset.sha256;
         if (!modelHash) {
             showToast('toast.contextMenu.missingHash', {}, 'error');
@@ -387,7 +390,7 @@ export const ModelContextMenuMixin = {
 
         try { 
             const apiClient = getModelApiClient();
-            await apiClient.downloadExampleImages([modelHash]);
+            await apiClient.downloadExampleImages([modelHash], null, { force });
         } catch (error) {
             console.error('Error downloading example images:', error);
         }

templates/checkpoints.html

@@ -33,6 +33,7 @@
     <!-- Media / Preview -->
     <div class="context-menu-item" data-action="preview"><i class="fas fa-folder-open"></i> {{ t('loras.contextMenu.openExamples') }}</div>
     <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }}</div>
+    <div class="context-menu-item" data-action="download-examples-force"><i class="fas fa-redo-alt"></i> {{ t('loras.contextMenu.reprocessExamples') }}</div>
     <div class="context-menu-item" data-action="replace-preview"><i class="fas fa-image"></i> {{ t('loras.contextMenu.replacePreview') }}</div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Attributes -->

templates/components/context_menu.html

@@ -47,6 +47,9 @@
     <div class="context-menu-item" data-action="download-examples">
         <i class="fas fa-download"></i> <span>{{ t('loras.contextMenu.downloadExamples') }}</span>
     </div>
+    <div class="context-menu-item" data-action="download-examples-force">
+        <i class="fas fa-redo-alt"></i> <span>{{ t('loras.contextMenu.reprocessExamples') }}</span>
+    </div>
     <div class="context-menu-item" data-action="replace-preview">
         <i class="fas fa-image"></i> <span>{{ t('loras.contextMenu.replacePreview') }}</span>
     </div>
@@ -136,8 +139,11 @@
     </div>
     <div class="context-menu-section" data-section="download">
         <div class="context-menu-section-header">{{ t('loras.bulkOperations.sections.download') }}</div>
+        <div class="context-menu-item" data-action="download-missing-example-images">
+            <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingExamples') }}</span>
+        </div>
         <div class="context-menu-item" data-action="download-example-images">
-            <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadExamples') }}</span>
+            <i class="fas fa-redo-alt"></i> <span>{{ t('loras.bulkOperations.reprocessExamples') }}</span>
         </div>
         <div class="context-menu-item" data-action="download-missing-loras">
             <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingLoras') }}</span>

templates/embeddings.html

@@ -33,6 +33,7 @@
     <!-- Media / Preview -->
     <div class="context-menu-item" data-action="preview"><i class="fas fa-folder-open"></i> {{ t('loras.contextMenu.openExamples') }}</div>
     <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }}</div>
+    <div class="context-menu-item" data-action="download-examples-force"><i class="fas fa-redo-alt"></i> {{ t('loras.contextMenu.reprocessExamples') }}</div>
     <div class="context-menu-item" data-action="replace-preview"><i class="fas fa-image"></i> {{ t('loras.contextMenu.replacePreview') }}</div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Attributes -->

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

@@ -2155,4 +2155,31 @@ describe('Interaction-level regression coverage', () => {
     excludedItem.dispatchEvent(new Event('click', { bubbles: true }));
     expect(window.pageControls.enterExcludedView).toHaveBeenCalledTimes(1);
   });
+
+  it('routes single-model example downloads to missing-only and force paths', async () => {
+    document.body.innerHTML = `
+      <div id="loraContextMenu" class="context-menu">
+        <div class="context-menu-item" data-action="download-examples"></div>
+        <div class="context-menu-item" data-action="download-examples-force"></div>
+      </div>
+    `;
+
+    const { LoraContextMenu } = await import('../../../static/js/components/ContextMenu/LoraContextMenu.js');
+    const contextMenu = new LoraContextMenu();
+
+    const card = document.createElement('div');
+    card.className = 'model-card';
+    card.dataset.filepath = '/models/test.safetensors';
+    card.dataset.sha256 = 'abc123hash';
+    document.body.appendChild(card);
+
+    contextMenu.showMenu(100, 100, card);
+
+    document.querySelector('[data-action="download-examples"]').dispatchEvent(new Event('click', { bubbles: true }));
+    expect(downloadExampleImagesApiMock).toHaveBeenCalledWith(['abc123hash'], null, { force: false });
+
+    contextMenu.showMenu(100, 100, card);
+    document.querySelector('[data-action="download-examples-force"]').dispatchEvent(new Event('click', { bubbles: true }));
+    expect(downloadExampleImagesApiMock).toHaveBeenCalledWith(['abc123hash'], null, { force: true });
+  });
 });

tests/services/test_example_images_download_manager_async.py

@@ -529,7 +529,8 @@ async def test_not_found_example_images_are_cleaned(
 
     model_dir = images_root / model_hash
     model_dir.mkdir(parents=True, exist_ok=True)
-    (model_dir / "image_0.png").write_bytes(b"first")
+    # Pre-existing file collides with the valid image index (1) so the
+    # pre-download existence check must skip it without a network request
     (model_dir / "image_1.png").write_bytes(b"second")
 
     async def fake_process_local_examples(*_args, **_kwargs):
@@ -608,11 +609,188 @@ async def test_not_found_example_images_are_cleaned(
     ]
 
     files = sorted(p.name for p in model_dir.iterdir())
-    assert files == ["image_0.png", "image_1.png"]
+    assert files == ["image_1.png"]
-    assert (model_dir / "image_0.png").read_bytes() == b"first"
     assert (model_dir / "image_1.png").read_bytes() == b"second"
 
 
+async def test_failed_models_retried_when_explicitly_targeted(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    ws_manager = RecordingWebSocketManager()
+    manager = download_module.DownloadManager(ws_manager=ws_manager)
+
+    images_root = tmp_path / "examples"
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(images_root))
+
+    model_hash = "a" * 64
+    model_path = tmp_path / "model.safetensors"
+    model_path.write_text("data", encoding="utf-8")
+
+    model_metadata = {
+        "sha256": model_hash,
+        "model_name": "Failed Example",
+        "file_path": str(model_path),
+        "file_name": "model.safetensors",
+        "civitai": {"images": [{"url": "https://example.com/valid.png"}]},
+    }
+
+    scanner = StubScanner([model_metadata.copy()])
+    _patch_scanner(monkeypatch, scanner)
+
+    # Persist a previous failure so the skip path is exercised
+    images_root.mkdir(parents=True, exist_ok=True)
+    (images_root / ".download_progress.json").write_text(
+        json.dumps(
+            {
+                "failed_models": [model_hash],
+                "processed_models": [],
+                "rate_limited_models": [],
+            }
+        ),
+        encoding="utf-8",
+    )
+
+    async def fake_process_local_examples(*_args, **_kwargs):
+        return False
+
+    async def fake_get_updated_model(model_hash_arg, _scanner):
+        return model_metadata
+
+    class DownloaderStub:
+        def __init__(self):
+            self.calls: list[str] = []
+
+        async def download_to_memory(self, url, *_args, **_kwargs):
+            self.calls.append(url)
+            return True, b"\x89PNG\r\n\x1a\n", {"content-type": "image/png"}
+
+    downloader = DownloaderStub()
+
+    async def fake_get_downloader():
+        return downloader
+
+    monkeypatch.setattr(
+        download_module.ExampleImagesProcessor,
+        "process_local_examples",
+        staticmethod(fake_process_local_examples),
+    )
+    monkeypatch.setattr(
+        download_module.MetadataUpdater,
+        "get_updated_model",
+        staticmethod(fake_get_updated_model),
+    )
+    monkeypatch.setattr(download_module, "get_downloader", fake_get_downloader)
+
+    # Without explicit hashes the previously failed model is skipped
+    skipped_manager = download_module.DownloadManager(ws_manager=RecordingWebSocketManager())
+    result = await skipped_manager.start_download({"model_types": ["lora"], "delay": 0})
+    assert result["success"] is True
+    if skipped_manager._download_task is not None:
+        await asyncio.wait_for(skipped_manager._download_task, timeout=1)
+    assert downloader.calls == []
+
+    # With explicit hashes the previously failed model is retried and cleared
+    result = await manager.start_download(
+        {"model_types": ["lora"], "delay": 0, "model_hashes": [model_hash]}
+    )
+    assert result["success"] is True
+    if manager._download_task is not None:
+        await asyncio.wait_for(manager._download_task, timeout=1)
+    assert downloader.calls == ["https://example.com/valid.png"]
+    assert manager._progress["failed_models"] == set()
+    assert model_hash in manager._progress["processed_models"]
+
+
+async def test_explicit_targets_fill_partial_example_gaps(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    ws_manager = RecordingWebSocketManager()
+
+    images_root = tmp_path / "examples"
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(images_root))
+
+    model_hash = "b" * 64
+    model_path = tmp_path / "model.safetensors"
+    model_path.write_text("data", encoding="utf-8")
+
+    model_metadata = {
+        "sha256": model_hash,
+        "model_name": "Partial Example",
+        "file_path": str(model_path),
+        "file_name": "model.safetensors",
+        "civitai": {
+            "images": [
+                {"url": "https://example.com/first.png"},
+                {"url": "https://example.com/second.png"},
+            ]
+        },
+    }
+
+    scanner = StubScanner([model_metadata.copy()])
+    _patch_scanner(monkeypatch, scanner)
+
+    # Simulate a partially populated folder: index 0 already downloaded
+    model_dir = images_root / model_hash
+    model_dir.mkdir(parents=True, exist_ok=True)
+    (model_dir / "image_0.png").write_bytes(b"existing")
+
+    async def fake_process_local_examples(*_args, **_kwargs):
+        return False
+
+    async def fake_get_updated_model(model_hash_arg, _scanner):
+        return model_metadata
+
+    class DownloaderStub:
+        def __init__(self):
+            self.calls: list[str] = []
+
+        async def download_to_memory(self, url, *_args, **_kwargs):
+            self.calls.append(url)
+            return True, b"\x89PNG\r\n\x1a\n", {"content-type": "image/png"}
+
+    downloader = DownloaderStub()
+
+    async def fake_get_downloader():
+        return downloader
+
+    monkeypatch.setattr(
+        download_module.ExampleImagesProcessor,
+        "process_local_examples",
+        staticmethod(fake_process_local_examples),
+    )
+    monkeypatch.setattr(
+        download_module.MetadataUpdater,
+        "get_updated_model",
+        staticmethod(fake_get_updated_model),
+    )
+    monkeypatch.setattr(download_module, "get_downloader", fake_get_downloader)
+
+    # Untargeted run treats the populated folder as done
+    untargeted = download_module.DownloadManager(ws_manager=RecordingWebSocketManager())
+    result = await untargeted.start_download({"model_types": ["lora"], "delay": 0})
+    assert result["success"] is True
+    if untargeted._download_task is not None:
+        await asyncio.wait_for(untargeted._download_task, timeout=1)
+    assert downloader.calls == []
+
+    # Explicitly targeted run fills only the missing index, skipping the
+    # existing file without a network request
+    targeted = download_module.DownloadManager(ws_manager=ws_manager)
+    result = await targeted.start_download(
+        {"model_types": ["lora"], "delay": 0, "model_hashes": [model_hash]}
+    )
+    assert result["success"] is True
+    if targeted._download_task is not None:
+        await asyncio.wait_for(targeted._download_task, timeout=1)
+    assert downloader.calls == ["https://example.com/second.png"]
+    assert (model_dir / "image_1.png").exists()
+    assert (model_dir / "image_0.png").read_bytes() == b"existing"
+
+
 @pytest.fixture
 def settings_manager():
     return get_settings_manager()

tests/utils/test_example_images_download_manager_unit.py

@@ -63,7 +63,7 @@ async def test_start_download_bootstraps_progress_and_task(
     release = asyncio.Event()
 
     async def fake_download(
-        self, output_dir, optimize, model_types, delay, library_name, force=False
+        self, output_dir, optimize, model_types, delay, library_name, force=False, model_hashes=None
     ):
         started.set()
         await release.wait()
@@ -93,6 +93,44 @@ async def test_start_download_bootstraps_progress_and_task(
     assert manager._progress["status"] == "completed"
 
 
+async def test_start_download_forwards_model_hashes(
+    monkeypatch: pytest.MonkeyPatch, tmp_path
+) -> None:
+    settings_manager = get_settings_manager()
+    settings_manager.settings["example_images_path"] = str(tmp_path)
+    settings_manager.settings["libraries"] = {"default": {}}
+    settings_manager.settings["active_library"] = "default"
+
+    manager = download_module.DownloadManager(ws_manager=RecordingWebSocketManager())
+
+    received: Dict[str, Any] = {}
+
+    async def fake_download(
+        self, output_dir, optimize, model_types, delay, library_name, force=False, model_hashes=None
+    ):
+        received["model_hashes"] = model_hashes
+        async with self._state_lock:
+            self._is_downloading = False
+            self._download_task = None
+        self._progress["status"] = "completed"
+
+    monkeypatch.setattr(
+        download_module.DownloadManager,
+        "_download_all_example_images",
+        fake_download,
+    )
+
+    result = await manager.start_download(
+        {"model_types": ["lora"], "delay": 0, "model_hashes": ["abc123", "def456"]}
+    )
+    assert result["success"] is True
+
+    task = manager._download_task
+    assert task is not None
+    await asyncio.wait_for(task, timeout=1)
+    assert received["model_hashes"] == ["abc123", "def456"]
+
+
 async def test_pause_and_resume_flow(monkeypatch: pytest.MonkeyPatch, tmp_path) -> None:
     settings_manager = get_settings_manager()
     settings_manager.settings["example_images_path"] = str(tmp_path)

tests/utils/test_example_images_processor_unit.py

@@ -100,6 +100,54 @@ def test_get_file_extension_media_type_hint_low_priority() -> None:
     assert ext == ".mp4"
 
 
+def test_example_image_file_exists_checks_plausible_extensions(tmp_path) -> None:
+    proc = processor_module.ExampleImagesProcessor
+    assert proc._example_image_file_exists(str(tmp_path), 0) is False
+    Path(tmp_path, "image_0.webp").write_bytes(b"x")
+    assert proc._example_image_file_exists(str(tmp_path), 0) is True
+    assert proc._example_image_file_exists(str(tmp_path), 1) is False
+
+
+def test_example_image_file_exists_video_hint_only_checks_video_extensions(tmp_path) -> None:
+    proc = processor_module.ExampleImagesProcessor
+    Path(tmp_path, "image_2.jpg").write_bytes(b"x")
+    # An existing image file must not satisfy a video-hinted lookup
+    assert proc._example_image_file_exists(str(tmp_path), 2, "video") is False
+    Path(tmp_path, "image_2.mp4").write_bytes(b"x")
+    assert proc._example_image_file_exists(str(tmp_path), 2, "video") is True
+
+
+async def test_download_model_images_with_tracking_skips_existing_files(tmp_path) -> None:
+    proc = processor_module.ExampleImagesProcessor
+    images = [
+        {"url": "https://image.civitai.com/a/b", "type": "image"},
+        {"url": "https://image.civitai.com/c/d", "type": "image"},
+    ]
+    Path(tmp_path, "image_0.jpg").write_bytes(b"existing")
+
+    class RecordingDownloader:
+        def __init__(self) -> None:
+            self.calls: list[str] = []
+
+        async def download_to_memory(self, url, use_auth=False, return_headers=False):
+            self.calls.append(url)
+            return True, b"\xff\xd8\xff" + b"data", {}
+
+    downloader = RecordingDownloader()
+    success, is_stale, failed, rate_limited = await proc.download_model_images_with_tracking(
+        "hash", "model", images, str(tmp_path), False, downloader
+    )
+
+    assert success is True
+    assert is_stale is False
+    assert failed == []
+    assert rate_limited == []
+    # Only the missing image is requested; the existing one is skipped without a network call
+    assert len(downloader.calls) == 1
+    assert "c/d" in downloader.calls[0]
+    assert Path(tmp_path, "image_1.jpg").exists()
+
+
 class StubScanner:
     def __init__(self, models: list[Dict[str, Any]]) -> None:
         self._cache = SimpleNamespace(raw_data=models)