Merge branch 'main' into fix-crash-on-symlinks

py/lora_manager.py

@@ -1,5 +1,10 @@
 import asyncio
+import sys
+import os
+import logging
+from pathlib import Path
 from server import PromptServer # type: ignore
+
 from .config import config
 from .routes.lora_routes import LoraRoutes
 from .routes.api_routes import ApiRoutes
@@ -10,10 +15,7 @@ from .routes.misc_routes import MiscRoutes
 from .routes.example_images_routes import ExampleImagesRoutes
 from .services.service_registry import ServiceRegistry
 from .services.settings_manager import settings
-from pathlib import Path
-import logging
-import sys
-import os
+from .utils.example_images_migration import ExampleImagesMigration
 
 logger = logging.getLogger(__name__)
 
@@ -135,13 +137,13 @@ class LoraManager:
             logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
             
             # Initialize CivitaiClient first to ensure it's ready for other services
-            civitai_client = await ServiceRegistry.get_civitai_client()
+            await ServiceRegistry.get_civitai_client()
 
             # Register DownloadManager with ServiceRegistry
-            download_manager = await ServiceRegistry.get_download_manager()
+            await ServiceRegistry.get_download_manager()
             
             # Initialize WebSocket manager
-            ws_manager = await ServiceRegistry.get_websocket_manager()
+            await ServiceRegistry.get_websocket_manager()
             
             # Initialize scanners in background
             lora_scanner = await ServiceRegistry.get_lora_scanner()
@@ -160,6 +162,8 @@ class LoraManager:
             asyncio.create_task(lora_scanner.initialize_in_background(), name='lora_cache_init')
             asyncio.create_task(checkpoint_scanner.initialize_in_background(), name='checkpoint_cache_init')
             asyncio.create_task(recipe_scanner.initialize_in_background(), name='recipe_cache_init')
+
+            await ExampleImagesMigration.check_and_run_migrations()
             
             logger.info("LoRA Manager: All services initialized and background tasks scheduled")
                 

py/routes/api_routes.py

@@ -14,6 +14,7 @@ import asyncio
 from .update_routes import UpdateRoutes
 from ..utils.constants import PREVIEW_EXTENSIONS, CARD_PREVIEW_WIDTH, VALID_LORA_TYPES
 from ..utils.exif_utils import ExifUtils
+from ..utils.metadata_manager import MetadataManager
 from ..services.service_registry import ServiceRegistry
 
 logger = logging.getLogger(__name__)
@@ -289,22 +290,6 @@ class ApiRoutes:
             
         return preview_path
 
-    async def _update_preview_metadata(self, model_path: str, preview_path: str):
-        """Update preview path in metadata"""
-        metadata_path = os.path.splitext(model_path)[0] + '.metadata.json'
-        if os.path.exists(metadata_path):
-            try:
-                with open(metadata_path, 'r', encoding='utf-8') as f:
-                    metadata = json.load(f)
-                
-                # Update preview_url directly in the metadata dict
-                metadata['preview_url'] = preview_path
-                
-                with open(metadata_path, 'w', encoding='utf-8') as f:
-                    json.dump(metadata, f, indent=2, ensure_ascii=False)
-            except Exception as e:
-                logger.error(f"Error updating metadata: {e}")
-
     async def fetch_all_civitai(self, request: web.Request) -> web.Response:
         """Fetch CivitAI metadata for all loras in the background"""
         try:
@@ -640,8 +625,7 @@ class ApiRoutes:
                     metadata[key] = value
 
             # Save updated metadata
-            with open(metadata_path, 'w', encoding='utf-8') as f:
-                json.dump(metadata, f, indent=2, ensure_ascii=False)
+            await MetadataManager.save_metadata(file_path, metadata)
 
             # Update cache
             await self.scanner.update_single_model_cache(file_path, file_path, metadata)
@@ -854,9 +838,7 @@ class ApiRoutes:
                             metadata['tags'] = tags
                             metadata['creator'] = creator
                             
-                            with open(metadata_path, 'w', encoding='utf-8') as f:
-                                json.dump(metadata, f, indent=2, ensure_ascii=False)
-                                logger.info(f"Saved model metadata to file for {file_path}")
+                            await MetadataManager.save_metadata(file_path, metadata)
                         except Exception as e:
                             logger.error(f"Error saving model metadata: {e}")
             
@@ -972,6 +954,7 @@ class ApiRoutes:
             patterns = [
                 f"{old_file_name}.safetensors",  # Required
                 f"{old_file_name}.metadata.json",
+                f"{old_file_name}.metadata.json.bak",
             ]
             
             # Add all preview file extensions
@@ -1027,8 +1010,7 @@ class ApiRoutes:
                     metadata['preview_url'] = new_preview
                 
                 # Save updated metadata
-                with open(new_metadata_path, 'w', encoding='utf-8') as f:
-                    json.dump(metadata, f, indent=2, ensure_ascii=False)
+                await MetadataManager.save_metadata(new_file_path, metadata)
             
             # Update the scanner cache
             if metadata:

py/routes/checkpoints_routes.py

@@ -7,6 +7,7 @@ import asyncio
 
 from ..utils.routes_common import ModelRouteUtils
 from ..utils.constants import NSFW_LEVELS
+from ..utils.metadata_manager import MetadataManager
 from ..services.websocket_manager import ws_manager
 from ..services.service_registry import ServiceRegistry
 from ..config import config
@@ -650,8 +651,7 @@ class CheckpointsRoutes:
             metadata.update(metadata_updates)
 
             # Save updated metadata
-            with open(metadata_path, 'w', encoding='utf-8') as f:
-                json.dump(metadata, f, indent=2, ensure_ascii=False)
+            await MetadataManager.save_metadata(file_path, metadata)
 
             # Update cache
             await self.scanner.update_single_model_cache(file_path, file_path, metadata)

py/routes/lora_routes.py

@@ -70,8 +70,7 @@ class LoraRoutes:
             # It's initializing if the cache object doesn't exist yet,
             # OR if the scanner explicitly says it's initializing (background task running).
             is_initializing = (
-                self.scanner._cache is None or
-                (hasattr(self.scanner, '_is_initializing') and self.scanner._is_initializing)
+                self.scanner._cache is None or self.scanner.is_initializing()
             )
 
             if is_initializing:

py/services/download_manager.py

@@ -6,6 +6,7 @@ from typing import Dict
 from ..utils.models import LoraMetadata, CheckpointMetadata
 from ..utils.constants import CARD_PREVIEW_WIDTH
 from ..utils.exif_utils import ExifUtils
+from ..utils.metadata_manager import MetadataManager
 from .service_registry import ServiceRegistry
 
 # Download to temporary file first
@@ -198,8 +199,6 @@ class DownloadManager:
                     if await civitai_client.download_preview_image(images[0]['url'], preview_path):
                         metadata.preview_url = preview_path.replace(os.sep, '/')
                         metadata.preview_nsfw_level = images[0].get('nsfwLevel', 0)
-                        with open(metadata_path, 'w', encoding='utf-8') as f:
-                            json.dump(metadata.to_dict(), f, indent=2, ensure_ascii=False)
                 else:
                     # For images, use WebP format for better performance
                     with tempfile.NamedTemporaryFile(suffix='.png', delete=False) as temp_file:
@@ -226,8 +225,6 @@ class DownloadManager:
                         # Update metadata
                         metadata.preview_url = preview_path.replace(os.sep, '/')
                         metadata.preview_nsfw_level = images[0].get('nsfwLevel', 0)
-                        with open(metadata_path, 'w', encoding='utf-8') as f:
-                            json.dump(metadata.to_dict(), f, indent=2, ensure_ascii=False)
                         
                         # Remove temporary file
                         try:
@@ -258,8 +255,7 @@ class DownloadManager:
             metadata.update_file_info(save_path)
 
             # 5. Final metadata update
-            with open(metadata_path, 'w', encoding='utf-8') as f:
-                json.dump(metadata.to_dict(), f, indent=2, ensure_ascii=False)
+            await MetadataManager.save_metadata(save_path, metadata)
 
             # 6. Update cache based on model type
             if model_type == "checkpoint":

py/services/model_cache.py

@@ -32,12 +32,13 @@ class ModelCache:
             all_folders = set(l['folder'] for l in self.raw_data)
             self.folders = sorted(list(all_folders), key=lambda x: x.lower())
 
-    async def update_preview_url(self, file_path: str, preview_url: str) -> bool:
+    async def update_preview_url(self, file_path: str, preview_url: str, preview_nsfw_level: int) -> bool:
         """Update preview_url for a specific model in all cached data
         
         Args:
             file_path: The file path of the model to update
             preview_url: The new preview URL
+            preview_nsfw_level: The NSFW level of the preview
             
         Returns:
             bool: True if the update was successful, False if the model wasn't found
@@ -47,19 +48,9 @@ class ModelCache:
             for item in self.raw_data:
                 if item['file_path'] == file_path:
                     item['preview_url'] = preview_url
+                    item['preview_nsfw_level'] = preview_nsfw_level
                     break
             else:
                 return False  # Model not found
-                
-            # Update in sorted lists (references to the same dict objects)
-            for item in self.sorted_by_name:
-                if item['file_path'] == file_path:
-                    item['preview_url'] = preview_url
-                    break
-                    
-            for item in self.sorted_by_date:
-                if item['file_path'] == file_path:
-                    item['preview_url'] = preview_url
-                    break
                     
             return True

py/services/model_scanner.py

@@ -9,7 +9,8 @@ import msgpack  # Add MessagePack import for efficient serialization
 
 from ..utils.models import BaseModelMetadata
 from ..config import config
-from ..utils.file_utils import load_metadata, get_file_info, find_preview_file, save_metadata
+from ..utils.file_utils import find_preview_file
+from ..utils.metadata_manager import MetadataManager
 from .model_cache import ModelCache
 from .model_hash_index import ModelHashIndex
 from ..utils.constants import PREVIEW_EXTENSIONS
@@ -748,13 +749,17 @@ class ModelScanner:
         """Scan all model directories and return metadata"""
         raise NotImplementedError("Subclasses must implement scan_all_models")
     
+    def is_initializing(self) -> bool:
+        """Check if the scanner is currently initializing"""
+        return self._is_initializing
+    
     def get_model_roots(self) -> List[str]:
         """Get model root directories"""
         raise NotImplementedError("Subclasses must implement get_model_roots")
     
-    async def _get_file_info(self, file_path: str) -> Optional[BaseModelMetadata]:
+    async def _create_default_metadata(self, file_path: str) -> Optional[BaseModelMetadata]:
         """Get model file info and metadata (extensible for different model types)"""
-        return await get_file_info(file_path, self.model_class)
+        return await MetadataManager.create_default_metadata(file_path, self.model_class)
     
     def _calculate_folder(self, file_path: str) -> str:
         """Calculate the folder path for a model file"""
@@ -767,7 +772,7 @@ class ModelScanner:
     # Common methods shared between scanners
     async def _process_model_file(self, file_path: str, root_path: str) -> Dict:
         """Process a single model file and return its metadata"""
-        metadata = await load_metadata(file_path, self.model_class)
+        metadata = await MetadataManager.load_metadata(file_path, self.model_class)
         
         if metadata is None:
             civitai_info_path = f"{os.path.splitext(file_path)[0]}.civitai.info"
@@ -783,7 +788,7 @@ class ModelScanner:
                     
                         metadata = self.model_class.from_civitai_info(version_info, file_info, file_path)
                         metadata.preview_url = find_preview_file(file_name, os.path.dirname(file_path))
-                        await save_metadata(file_path, metadata)
+                        await MetadataManager.save_metadata(file_path, metadata)
                         logger.debug(f"Created metadata from .civitai.info for {file_path}")
                 except Exception as e:
                     logger.error(f"Error creating metadata from .civitai.info for {file_path}: {e}")
@@ -810,13 +815,13 @@ class ModelScanner:
                                 metadata.modelDescription = version_info['model']['description']
                         
                         # Save the updated metadata
-                        await save_metadata(file_path, metadata)
+                        await MetadataManager.save_metadata(file_path, metadata)
                         logger.debug(f"Updated metadata with civitai info for {file_path}")
                     except Exception as e:
                         logger.error(f"Error restoring civitai data from .civitai.info for {file_path}: {e}")
             
         if metadata is None:
-            metadata = await self._get_file_info(file_path)
+            metadata = await self._create_default_metadata(file_path)
         
         model_data = metadata.to_dict()
         
@@ -866,9 +871,7 @@ class ModelScanner:
                     logger.warning(f"Model {model_id} appears to be deleted from Civitai (404 response)")
                     model_data['civitai_deleted'] = True
                     
-                    metadata_path = os.path.splitext(file_path)[0] + '.metadata.json'
-                    with open(metadata_path, 'w', encoding='utf-8') as f:
-                        json.dump(model_data, f, indent=2, ensure_ascii=False)
+                    await MetadataManager.save_metadata(file_path, model_data)
                 
                 elif model_metadata:
                     logger.debug(f"Updating metadata for {file_path} with model ID {model_id}")
@@ -881,9 +884,7 @@ class ModelScanner:
 
                     model_data['civitai']['creator'] = model_metadata['creator']
                     
-                    metadata_path = os.path.splitext(file_path)[0] + '.metadata.json'
-                    with open(metadata_path, 'w', encoding='utf-8') as f:
-                        json.dump(model_data, f, indent=2, ensure_ascii=False)
+                    await MetadataManager.save_metadata(file_path, model_data)
         except Exception as e:
             logger.error(f"Failed to update metadata from Civitai for {file_path}: {e}")
 
@@ -1049,8 +1050,7 @@ class ModelScanner:
                 new_preview_path = os.path.join(preview_dir, f"{preview_name}{preview_ext}")
                 metadata['preview_url'] = new_preview_path.replace(os.sep, '/')
             
-            with open(metadata_path, 'w', encoding='utf-8') as f:
-                json.dump(metadata, f, indent=2, ensure_ascii=False)
+            await MetadataManager.save_metadata(metadata_path, metadata)
 
             return metadata
                 
@@ -1184,12 +1184,13 @@ class ModelScanner:
         """Get list of excluded model file paths"""
         return self._excluded_models.copy()
 
-    async def update_preview_in_cache(self, file_path: str, preview_url: str) -> bool:
+    async def update_preview_in_cache(self, file_path: str, preview_url: str, preview_nsfw_level: int) -> bool:
         """Update preview URL in cache for a specific lora
         
         Args:
             file_path: The file path of the lora to update
             preview_url: The new preview URL
+            preview_nsfw_level: The NSFW level of the preview
             
         Returns:
             bool: True if the update was successful, False if cache doesn't exist or lora wasn't found
@@ -1197,7 +1198,7 @@ class ModelScanner:
         if self._cache is None:
             return False
 
-        updated = await self._cache.update_preview_url(file_path, preview_url)
+        updated = await self._cache.update_preview_url(file_path, preview_url, preview_nsfw_level)
         if updated:
             # Save updated cache to disk
             await self._save_cache_to_disk()

py/utils/example_images_download_manager.py

@@ -0,0 +1,399 @@
+import logging
+import os
+import asyncio
+import json
+import time
+import aiohttp
+from aiohttp import web
+from ..services.service_registry import ServiceRegistry
+from .example_images_processor import ExampleImagesProcessor
+from .example_images_metadata import MetadataUpdater
+
+logger = logging.getLogger(__name__)
+
+# Download status tracking
+download_task = None
+is_downloading = False
+download_progress = {
+    'total': 0,
+    'completed': 0,
+    'current_model': '',
+    'status': 'idle',  # idle, running, paused, completed, error
+    'errors': [],
+    'last_error': None,
+    'start_time': None,
+    'end_time': None,
+    'processed_models': set(),  # Track models that have been processed
+    'refreshed_models': set()  # Track models that had metadata refreshed
+}
+
+class DownloadManager:
+    """Manages downloading example images for models"""
+    
+    @staticmethod
+    async def start_download(request):
+        """
+        Start downloading example images for models
+        
+        Expects a JSON body with:
+        {
+            "output_dir": "path/to/output",  # Base directory to save example images
+            "optimize": true,                # Whether to optimize images (default: true)
+            "model_types": ["lora", "checkpoint"], # Model types to process (default: both)
+            "delay": 1.0                     # Delay between downloads to avoid rate limiting (default: 1.0)
+        }
+        """
+        global download_task, is_downloading, download_progress
+        
+        if is_downloading:
+            # Create a copy for JSON serialization
+            response_progress = download_progress.copy()
+            response_progress['processed_models'] = list(download_progress['processed_models'])
+            response_progress['refreshed_models'] = list(download_progress['refreshed_models'])
+            
+            return web.json_response({
+                'success': False,
+                'error': 'Download already in progress',
+                'status': response_progress
+            }, status=400)
+        
+        try:
+            # Parse the request body
+            data = await request.json()
+            output_dir = data.get('output_dir')
+            optimize = data.get('optimize', True)
+            model_types = data.get('model_types', ['lora', 'checkpoint'])
+            delay = float(data.get('delay', 0.2)) # Default to 0.2 seconds
+            
+            if not output_dir:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing output_dir parameter'
+                }, status=400)
+            
+            # Create the output directory
+            os.makedirs(output_dir, exist_ok=True)
+            
+            # Initialize progress tracking
+            download_progress['total'] = 0
+            download_progress['completed'] = 0
+            download_progress['current_model'] = ''
+            download_progress['status'] = 'running'
+            download_progress['errors'] = []
+            download_progress['last_error'] = None
+            download_progress['start_time'] = time.time()
+            download_progress['end_time'] = None
+            
+            # Get the processed models list from a file if it exists
+            progress_file = os.path.join(output_dir, '.download_progress.json')
+            if os.path.exists(progress_file):
+                try:
+                    with open(progress_file, 'r', encoding='utf-8') as f:
+                        saved_progress = json.load(f)
+                        download_progress['processed_models'] = set(saved_progress.get('processed_models', []))
+                        logger.info(f"Loaded previous progress, {len(download_progress['processed_models'])} models already processed")
+                except Exception as e:
+                    logger.error(f"Failed to load progress file: {e}")
+                    download_progress['processed_models'] = set()
+            else:
+                download_progress['processed_models'] = set()
+            
+            # Start the download task
+            is_downloading = True
+            download_task = asyncio.create_task(
+                DownloadManager._download_all_example_images(
+                    output_dir, 
+                    optimize, 
+                    model_types,
+                    delay
+                )
+            )
+            
+            # Create a copy for JSON serialization
+            response_progress = download_progress.copy()
+            response_progress['processed_models'] = list(download_progress['processed_models'])
+            response_progress['refreshed_models'] = list(download_progress['refreshed_models'])
+            
+            return web.json_response({
+                'success': True,
+                'message': 'Download started',
+                'status': response_progress
+            })
+            
+        except Exception as e:
+            logger.error(f"Failed to start example images download: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)
+            
+    @staticmethod
+    async def get_status(request):
+        """Get the current status of example images download"""
+        global download_progress
+        
+        # Create a copy of the progress dict with the set converted to a list for JSON serialization
+        response_progress = download_progress.copy()
+        response_progress['processed_models'] = list(download_progress['processed_models'])
+        response_progress['refreshed_models'] = list(download_progress['refreshed_models'])
+        
+        return web.json_response({
+            'success': True,
+            'is_downloading': is_downloading,
+            'status': response_progress
+        })
+
+    @staticmethod
+    async def pause_download(request):
+        """Pause the example images download"""
+        global download_progress
+        
+        if not is_downloading:
+            return web.json_response({
+                'success': False,
+                'error': 'No download in progress'
+            }, status=400)
+        
+        download_progress['status'] = 'paused'
+        
+        return web.json_response({
+            'success': True,
+            'message': 'Download paused'
+        })
+
+    @staticmethod
+    async def resume_download(request):
+        """Resume the example images download"""
+        global download_progress
+        
+        if not is_downloading:
+            return web.json_response({
+                'success': False,
+                'error': 'No download in progress'
+            }, status=400)
+        
+        if download_progress['status'] == 'paused':
+            download_progress['status'] = 'running'
+            
+            return web.json_response({
+                'success': True,
+                'message': 'Download resumed'
+            })
+        else:
+            return web.json_response({
+                'success': False,
+                'error': f"Download is in '{download_progress['status']}' state, cannot resume"
+            }, status=400)
+    
+    @staticmethod
+    async def _download_all_example_images(output_dir, optimize, model_types, delay):
+        """Download example images for all models"""
+        global is_downloading, download_progress
+        
+        # Create independent download session
+        connector = aiohttp.TCPConnector(
+            ssl=True,
+            limit=3,
+            force_close=False,
+            enable_cleanup_closed=True
+        )
+        timeout = aiohttp.ClientTimeout(total=None, connect=60, sock_read=60)
+        independent_session = aiohttp.ClientSession(
+            connector=connector,
+            trust_env=True,
+            timeout=timeout
+        )
+        
+        try:
+            # Get scanners
+            scanners = []
+            if 'lora' in model_types:
+                lora_scanner = await ServiceRegistry.get_lora_scanner()
+                scanners.append(('lora', lora_scanner))
+            
+            if 'checkpoint' in model_types:
+                checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
+                scanners.append(('checkpoint', checkpoint_scanner))
+            
+            # Get all models
+            all_models = []
+            for scanner_type, scanner in scanners:
+                cache = await scanner.get_cached_data()
+                if cache and cache.raw_data:
+                    for model in cache.raw_data:
+                        if model.get('sha256'):
+                            all_models.append((scanner_type, model, scanner))
+            
+            # Update total count
+            download_progress['total'] = len(all_models)
+            logger.info(f"Found {download_progress['total']} models to process")
+            
+            # Process each model
+            for i, (scanner_type, model, scanner) in enumerate(all_models):
+                # Main logic for processing model is here, but actual operations are delegated to other classes
+                was_remote_download = await DownloadManager._process_model(
+                    scanner_type, model, scanner, 
+                    output_dir, optimize, independent_session
+                )
+                
+                # Update progress
+                download_progress['completed'] += 1
+                
+                # Only add delay after remote download of models, and not after processing the last model
+                if was_remote_download and i < len(all_models) - 1 and download_progress['status'] == 'running':
+                    await asyncio.sleep(delay)
+            
+            # Mark as completed
+            download_progress['status'] = 'completed'
+            download_progress['end_time'] = time.time()
+            logger.info(f"Example images download completed: {download_progress['completed']}/{download_progress['total']} models processed")
+            
+        except Exception as e:
+            error_msg = f"Error during example images download: {str(e)}"
+            logger.error(error_msg, exc_info=True)
+            download_progress['errors'].append(error_msg)
+            download_progress['last_error'] = error_msg
+            download_progress['status'] = 'error'
+            download_progress['end_time'] = time.time()
+        
+        finally:
+            # Close the independent session
+            try:
+                await independent_session.close()
+            except Exception as e:
+                logger.error(f"Error closing download session: {e}")
+                
+            # Save final progress to file
+            try:
+                DownloadManager._save_progress(output_dir)
+            except Exception as e:
+                logger.error(f"Failed to save progress file: {e}")
+            
+            # Set download status to not downloading
+            is_downloading = False
+    
+    @staticmethod
+    async def _process_model(scanner_type, model, scanner, output_dir, optimize, independent_session):
+        """Process a single model download"""
+        global download_progress
+        
+        # Check if download is paused
+        while download_progress['status'] == 'paused':
+            await asyncio.sleep(1)
+        
+        # Check if download should continue
+        if download_progress['status'] != 'running':
+            logger.info(f"Download stopped: {download_progress['status']}")
+            return False  # Return False to indicate no remote download happened
+        
+        model_hash = model.get('sha256', '').lower()
+        model_name = model.get('model_name', 'Unknown')
+        model_file_path = model.get('file_path', '')
+        model_file_name = model.get('file_name', '')
+        
+        try:
+            # Update current model info
+            download_progress['current_model'] = f"{model_name} ({model_hash[:8]})"
+            
+            # Skip if already processed
+            if model_hash in download_progress['processed_models']:
+                logger.debug(f"Skipping already processed model: {model_name}")
+                return False
+            
+            # Create model directory
+            model_dir = os.path.join(output_dir, model_hash)
+            os.makedirs(model_dir, exist_ok=True)
+            
+            # First check for local example images - local processing doesn't need delay
+            local_images_processed = await ExampleImagesProcessor.process_local_examples(
+                model_file_path, model_file_name, model_name, model_dir, optimize
+            )
+            
+            # If we processed local images, update metadata
+            if local_images_processed:
+                await MetadataUpdater.update_metadata_from_local_examples(
+                    model_hash, model, scanner_type, scanner, model_dir
+                )
+                download_progress['processed_models'].add(model_hash)
+                return False  # Return False to indicate no remote download happened
+            
+            # If no local images, try to download from remote
+            elif model.get('civitai') and model.get('civitai', {}).get('images'):
+                images = model.get('civitai', {}).get('images', [])
+                
+                success, is_stale = await ExampleImagesProcessor.download_model_images(
+                    model_hash, model_name, images, model_dir, optimize, independent_session
+                )
+                
+                # If metadata is stale, try to refresh it
+                if is_stale and model_hash not in download_progress['refreshed_models']:
+                    await MetadataUpdater.refresh_model_metadata(
+                        model_hash, model_name, scanner_type, scanner
+                    )
+                    
+                    # Get the updated model data
+                    updated_model = await MetadataUpdater.get_updated_model(
+                        model_hash, scanner
+                    )
+                    
+                    if updated_model and updated_model.get('civitai', {}).get('images'):
+                        # Retry download with updated metadata
+                        updated_images = updated_model.get('civitai', {}).get('images', [])
+                        success, _ = await ExampleImagesProcessor.download_model_images(
+                            model_hash, model_name, updated_images, model_dir, optimize, independent_session
+                        )
+                
+                # Only mark as processed if all images were downloaded successfully
+                if success:
+                    download_progress['processed_models'].add(model_hash)
+                    
+                return True  # Return True to indicate a remote download happened
+            
+            # Save progress periodically
+            if download_progress['completed'] % 10 == 0 or download_progress['completed'] == download_progress['total'] - 1:
+                DownloadManager._save_progress(output_dir)
+                
+            return False  # Default return if no conditions met
+                
+        except Exception as e:
+            error_msg = f"Error processing model {model.get('model_name')}: {str(e)}"
+            logger.error(error_msg, exc_info=True)
+            download_progress['errors'].append(error_msg)
+            download_progress['last_error'] = error_msg
+            return False  # Return False on exception
+    
+    @staticmethod
+    def _save_progress(output_dir):
+        """Save download progress to file"""
+        global download_progress
+        try:
+            progress_file = os.path.join(output_dir, '.download_progress.json')
+            
+            # Read existing progress file if it exists
+            existing_data = {}
+            if os.path.exists(progress_file):
+                try:
+                    with open(progress_file, 'r', encoding='utf-8') as f:
+                        existing_data = json.load(f)
+                except Exception as e:
+                    logger.warning(f"Failed to read existing progress file: {e}")
+            
+            # Create new progress data
+            progress_data = {
+                'processed_models': list(download_progress['processed_models']),
+                'refreshed_models': list(download_progress['refreshed_models']),
+                'completed': download_progress['completed'],
+                'total': download_progress['total'],
+                'last_update': time.time()
+            }
+            
+            # Preserve existing fields (especially naming_version)
+            for key, value in existing_data.items():
+                if key not in progress_data:
+                    progress_data[key] = value
+            
+            # Write updated progress data
+            with open(progress_file, 'w', encoding='utf-8') as f:
+                json.dump(progress_data, f, indent=2)
+        except Exception as e:
+            logger.error(f"Failed to save progress file: {e}")

py/utils/example_images_file_manager.py

@@ -0,0 +1,201 @@
+import logging
+import os
+import re
+import sys
+import subprocess
+from aiohttp import web
+from ..services.settings_manager import settings
+from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
+
+logger = logging.getLogger(__name__)
+
+class ExampleImagesFileManager:
+    """Manages access and operations for example image files"""
+    
+    @staticmethod
+    async def open_folder(request):
+        """
+        Open the example images folder for a specific model
+        
+        Expects a JSON request body with:
+        {
+            "model_hash": "sha256_hash"  # SHA256 hash of the model
+        }
+        """
+        try:
+            # Parse request body
+            data = await request.json()
+            model_hash = data.get('model_hash')
+            
+            if not model_hash:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing model_hash parameter'
+                }, status=400)
+            
+            # Get example images path from settings
+            example_images_path = settings.get('example_images_path')
+            if not example_images_path:
+                return web.json_response({
+                    'success': False,
+                    'error': 'No example images path configured. Please set it in the settings panel first.'
+                }, status=400)
+            
+            # Construct folder path for this model
+            model_folder = os.path.join(example_images_path, model_hash)
+            
+            # Check if folder exists
+            if not os.path.exists(model_folder):
+                return web.json_response({
+                    'success': False,
+                    'error': 'No example images found for this model. Download example images first.'
+                }, status=404)
+            
+            # Open folder in file explorer
+            if os.name == 'nt':  # Windows
+                os.startfile(model_folder)
+            elif os.name == 'posix':  # macOS and Linux
+                if sys.platform == 'darwin':  # macOS
+                    subprocess.Popen(['open', model_folder])
+                else:  # Linux
+                    subprocess.Popen(['xdg-open', model_folder])
+            
+            return web.json_response({
+                'success': True,
+                'message': f'Opened example images folder for model {model_hash}'
+            })
+            
+        except Exception as e:
+            logger.error(f"Failed to open example images folder: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)
+
+    @staticmethod
+    async def get_files(request):
+        """
+        Get the list of example image files for a specific model
+        
+        Expects:
+        - model_hash in query parameters
+        
+        Returns:
+        - List of image files and their paths
+        """
+        try:
+            # Get model_hash from query parameters
+            model_hash = request.query.get('model_hash')
+            
+            if not model_hash:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing model_hash parameter'
+                }, status=400)
+            
+            # Get example images path from settings
+            example_images_path = settings.get('example_images_path')
+            if not example_images_path:
+                return web.json_response({
+                    'success': False,
+                    'error': 'No example images path configured'
+                }, status=400)
+            
+            # Construct folder path for this model
+            model_folder = os.path.join(example_images_path, model_hash)
+            
+            # Check if folder exists
+            if not os.path.exists(model_folder):
+                return web.json_response({
+                    'success': False, 
+                    'error': 'No example images found for this model',
+                    'files': []
+                }, status=404)
+            
+            # Get list of files in the folder
+            files = []
+            for file in os.listdir(model_folder):
+                file_path = os.path.join(model_folder, file)
+                if os.path.isfile(file_path):
+                    # Check if file is a supported media file
+                    file_ext = os.path.splitext(file)[1].lower()
+                    if (file_ext in SUPPORTED_MEDIA_EXTENSIONS['images'] or 
+                        file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']):
+                        files.append({
+                            'name': file,
+                            'path': f'/example_images_static/{model_hash}/{file}',
+                            'extension': file_ext,
+                            'is_video': file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
+                        })
+            
+            return web.json_response({
+                'success': True,
+                'files': files
+            })
+            
+        except Exception as e:
+            logger.error(f"Failed to get example image files: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)
+    
+    @staticmethod
+    async def has_images(request):
+        """
+        Check if the example images folder for a model exists and is not empty
+        
+        Expects:
+        - model_hash in query parameters
+        
+        Returns:
+        - Boolean indicating whether the folder exists and contains images/videos
+        """
+        try:
+            # Get model_hash from query parameters
+            model_hash = request.query.get('model_hash')
+            
+            if not model_hash:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing model_hash parameter'
+                }, status=400)
+            
+            # Get example images path from settings
+            example_images_path = settings.get('example_images_path')
+            if not example_images_path:
+                return web.json_response({
+                    'has_images': False
+                })
+            
+            # Construct folder path for this model
+            model_folder = os.path.join(example_images_path, model_hash)
+            
+            # Check if folder exists
+            if not os.path.exists(model_folder) or not os.path.isdir(model_folder):
+                return web.json_response({
+                    'has_images': False
+                })
+            
+            # Check if folder contains any supported media files
+            for file in os.listdir(model_folder):
+                file_path = os.path.join(model_folder, file)
+                if os.path.isfile(file_path):
+                    file_ext = os.path.splitext(file)[1].lower()
+                    if (file_ext in SUPPORTED_MEDIA_EXTENSIONS['images'] or 
+                        file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']):
+                        return web.json_response({
+                            'has_images': True
+                        })
+            
+            # If reached here, folder exists but has no supported media files
+            return web.json_response({
+                'has_images': False
+            })
+            
+        except Exception as e:
+            logger.error(f"Failed to check example images folder: {e}", exc_info=True)
+            return web.json_response({
+                'has_images': False,
+                'error': str(e)
+            })

py/utils/example_images_metadata.py

@@ -0,0 +1,390 @@
+import logging
+import os
+import re
+from ..utils.metadata_manager import MetadataManager
+from ..utils.routes_common import ModelRouteUtils
+from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
+from ..utils.exif_utils import ExifUtils
+from ..recipes.constants import GEN_PARAM_KEYS
+
+logger = logging.getLogger(__name__)
+
+class MetadataUpdater:
+    """Handles updating model metadata related to example images"""
+    
+    @staticmethod
+    async def refresh_model_metadata(model_hash, model_name, scanner_type, scanner):
+        """Refresh model metadata from CivitAI
+        
+        Args:
+            model_hash: SHA256 hash of the model
+            model_name: Model name (for logging)
+            scanner_type: Scanner type ('lora' or 'checkpoint')
+            scanner: Scanner instance for this model type
+            
+        Returns:
+            bool: True if metadata was successfully refreshed, False otherwise
+        """
+        from ..utils.example_images_download_manager import download_progress
+        
+        try:
+            # Find the model in the scanner cache
+            cache = await scanner.get_cached_data()
+            model_data = None
+            
+            for item in cache.raw_data:
+                if item.get('sha256') == model_hash:
+                    model_data = item
+                    break
+            
+            if not model_data:
+                logger.warning(f"Model {model_name} with hash {model_hash} not found in cache")
+                return False
+            
+            file_path = model_data.get('file_path')
+            if not file_path:
+                logger.warning(f"Model {model_name} has no file path")
+                return False
+            
+            # Track that we're refreshing this model
+            download_progress['refreshed_models'].add(model_hash)
+            
+            # Use ModelRouteUtils to refresh metadata
+            async def update_cache_func(old_path, new_path, metadata):
+                return await scanner.update_single_model_cache(old_path, new_path, metadata)
+            
+            success = await ModelRouteUtils.fetch_and_update_model(
+                model_hash, 
+                file_path, 
+                model_data,
+                update_cache_func
+            )
+            
+            if success:
+                logger.info(f"Successfully refreshed metadata for {model_name}")
+                return True
+            else:
+                logger.warning(f"Failed to refresh metadata for {model_name}")
+                return False
+                
+        except Exception as e:
+            error_msg = f"Error refreshing metadata for {model_name}: {str(e)}"
+            logger.error(error_msg, exc_info=True)
+            download_progress['errors'].append(error_msg)
+            download_progress['last_error'] = error_msg
+            return False
+    
+    @staticmethod
+    async def get_updated_model(model_hash, scanner):
+        """Get updated model data
+        
+        Args:
+            model_hash: SHA256 hash of the model
+            scanner: Scanner instance
+            
+        Returns:
+            dict: Updated model data or None if not found
+        """
+        cache = await scanner.get_cached_data()
+        for item in cache.raw_data:
+            if item.get('sha256') == model_hash:
+                return item
+        return None
+    
+    @staticmethod
+    async def update_metadata_from_local_examples(model_hash, model, scanner_type, scanner, model_dir):
+        """Update model metadata with local example image information
+        
+        Args:
+            model_hash: SHA256 hash of the model
+            model: Model data dictionary
+            scanner_type: Scanner type ('lora' or 'checkpoint')
+            scanner: Scanner instance for this model type
+            model_dir: Model images directory
+            
+        Returns:
+            bool: True if metadata was successfully updated, False otherwise
+        """
+        try:
+            # Collect local image paths
+            local_images_paths = []
+            if os.path.exists(model_dir):
+                for file in os.listdir(model_dir):
+                    file_path = os.path.join(model_dir, file)
+                    if os.path.isfile(file_path):
+                        file_ext = os.path.splitext(file)[1].lower()
+                        is_supported = (file_ext in SUPPORTED_MEDIA_EXTENSIONS['images'] or
+                                       file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos'])
+                        if is_supported:
+                            local_images_paths.append(file_path)
+            
+            # Check if metadata update is needed (no civitai field or empty images)
+            needs_update = not model.get('civitai') or not model.get('civitai', {}).get('images')
+            
+            if needs_update and local_images_paths:
+                logger.debug(f"Found {len(local_images_paths)} local example images for {model.get('model_name')}, updating metadata")
+                
+                # Create or get civitai field
+                if not model.get('civitai'):
+                    model['civitai'] = {}
+                
+                # Create images array
+                images = []
+                
+                # Generate metadata for each local image/video
+                for path in local_images_paths:
+                    # Determine if video or image
+                    file_ext = os.path.splitext(path)[1].lower()
+                    is_video = file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
+                    
+                    # Create image metadata entry
+                    image_entry = {
+                        "url": "",  # Empty URL as required
+                        "nsfwLevel": 0,
+                        "width": 720,  # Default dimensions
+                        "height": 1280,
+                        "type": "video" if is_video else "image",
+                        "meta": None,
+                        "hasMeta": False,
+                        "hasPositivePrompt": False
+                    }
+                    
+                    # If it's an image, try to get actual dimensions (optional enhancement)
+                    try:
+                        from PIL import Image
+                        if not is_video and os.path.exists(path):
+                            with Image.open(path) as img:
+                                image_entry["width"], image_entry["height"] = img.size
+                    except:
+                        # If PIL fails or is unavailable, use default dimensions
+                        pass
+                        
+                    images.append(image_entry)
+                
+                # Update the model's civitai.images field
+                model['civitai']['images'] = images
+                
+                # Save metadata to .metadata.json file
+                file_path = model.get('file_path')
+                try:
+                    # Create a copy of model data without 'folder' field
+                    model_copy = model.copy()
+                    model_copy.pop('folder', None)
+                    
+                    # Write metadata to file
+                    await MetadataManager.save_metadata(file_path, model_copy)
+                    logger.info(f"Saved metadata for {model.get('model_name')}")
+                except Exception as e:
+                    logger.error(f"Failed to save metadata for {model.get('model_name')}: {str(e)}")
+                
+                # Save updated metadata to scanner cache
+                success = await scanner.update_single_model_cache(file_path, file_path, model)
+                if success:
+                    logger.info(f"Successfully updated metadata for {model.get('model_name')} with {len(images)} local examples")
+                    return True
+                else:
+                    logger.warning(f"Failed to update metadata for {model.get('model_name')}")
+            
+            return False
+        except Exception as e:
+            logger.error(f"Error updating metadata from local examples: {str(e)}", exc_info=True)
+            return False
+    
+    @staticmethod
+    async def update_metadata_after_import(model_hash, model_data, scanner, newly_imported_paths):
+        """Update model metadata after importing example images
+        
+        Args:
+            model_hash: SHA256 hash of the model
+            model_data: Model data dictionary
+            scanner: Scanner instance (lora or checkpoint)
+            newly_imported_paths: List of paths to newly imported files
+            
+        Returns:
+            tuple: (regular_images, custom_images) - Both image arrays
+        """
+        try:
+            # Ensure civitai field exists in model_data
+            if not model_data.get('civitai'):
+                model_data['civitai'] = {}
+            
+            # Ensure customImages array exists
+            if not model_data['civitai'].get('customImages'):
+                model_data['civitai']['customImages'] = []
+            
+            # Get current customImages array
+            custom_images = model_data['civitai']['customImages']
+            
+            # Add new image entry for each imported file
+            for path_tuple in newly_imported_paths:
+                path, short_id = path_tuple
+
+                # Determine if video or image
+                file_ext = os.path.splitext(path)[1].lower()
+                is_video = file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
+                
+                # Create image metadata entry
+                image_entry = {
+                    "url": "",  # Empty URL as requested
+                    "id": short_id,
+                    "nsfwLevel": 0,
+                    "width": 720,  # Default dimensions
+                    "height": 1280,
+                    "type": "video" if is_video else "image",
+                    "meta": None,
+                    "hasMeta": False,
+                    "hasPositivePrompt": False
+                }
+                
+                # Extract and parse metadata if this is an image
+                if not is_video:
+                    try:
+                        # Extract metadata from image
+                        extracted_metadata = ExifUtils.extract_image_metadata(path)
+                        
+                        if extracted_metadata:
+                            # Parse the extracted metadata to get generation parameters
+                            parsed_meta = MetadataUpdater._parse_image_metadata(extracted_metadata)
+                            
+                            if parsed_meta:
+                                image_entry["meta"] = parsed_meta
+                                image_entry["hasMeta"] = True
+                                image_entry["hasPositivePrompt"] = bool(parsed_meta.get("prompt", ""))
+                                logger.debug(f"Extracted metadata from {os.path.basename(path)}")
+                    except Exception as e:
+                        logger.warning(f"Failed to extract metadata from {os.path.basename(path)}: {e}")
+                
+                # If it's an image, try to get actual dimensions
+                try:
+                    from PIL import Image
+                    if not is_video and os.path.exists(path):
+                        with Image.open(path) as img:
+                            image_entry["width"], image_entry["height"] = img.size
+                except:
+                    # If PIL fails or is unavailable, use default dimensions
+                    pass
+                    
+                # Append to existing customImages array
+                custom_images.append(image_entry)
+            
+            # Save metadata to .metadata.json file
+            file_path = model_data.get('file_path')
+            if file_path:
+                try:
+                    # Create a copy of model data without 'folder' field
+                    model_copy = model_data.copy()
+                    model_copy.pop('folder', None)
+                    
+                    # Write metadata to file
+                    await MetadataManager.save_metadata(file_path, model_copy)
+                    logger.info(f"Saved metadata for {model_data.get('model_name')}")
+                except Exception as e:
+                    logger.error(f"Failed to save metadata: {str(e)}")
+            
+            # Save updated metadata to scanner cache
+            if file_path:
+                await scanner.update_single_model_cache(file_path, file_path, model_data)
+            
+            # Get regular images array (might be None)
+            regular_images = model_data['civitai'].get('images', [])
+            
+            # Return both image arrays
+            return regular_images, custom_images
+                
+        except Exception as e:
+            logger.error(f"Failed to update metadata after import: {e}", exc_info=True)
+            return [], []
+    
+    @staticmethod
+    def _parse_image_metadata(user_comment):
+        """Parse metadata from image to extract generation parameters
+        
+        Args:
+            user_comment: Metadata string extracted from image
+            
+        Returns:
+            dict: Parsed metadata with generation parameters
+        """
+        if not user_comment:
+            return None
+            
+        try:
+            # Initialize metadata dictionary
+            metadata = {}
+            
+            # Split on Negative prompt if it exists
+            if "Negative prompt:" in user_comment:
+                parts = user_comment.split('Negative prompt:', 1)
+                prompt = parts[0].strip()
+                negative_and_params = parts[1] if len(parts) > 1 else ""
+            else:
+                # No negative prompt section
+                param_start = re.search(r'Steps: \d+', user_comment)
+                if param_start:
+                    prompt = user_comment[:param_start.start()].strip()
+                    negative_and_params = user_comment[param_start.start():]
+                else:
+                    prompt = user_comment.strip()
+                    negative_and_params = ""
+            
+            # Add prompt if it's in GEN_PARAM_KEYS
+            if 'prompt' in GEN_PARAM_KEYS:
+                metadata['prompt'] = prompt
+            
+            # Extract negative prompt and parameters
+            if negative_and_params:
+                # If we split on "Negative prompt:", check for params section
+                if "Negative prompt:" in user_comment:
+                    param_start = re.search(r'Steps: ', negative_and_params)
+                    if param_start:
+                        neg_prompt = negative_and_params[:param_start.start()].strip()
+                        if 'negative_prompt' in GEN_PARAM_KEYS:
+                            metadata['negative_prompt'] = neg_prompt
+                        params_section = negative_and_params[param_start.start():]
+                    else:
+                        if 'negative_prompt' in GEN_PARAM_KEYS:
+                            metadata['negative_prompt'] = negative_and_params.strip()
+                        params_section = ""
+                else:
+                    # No negative prompt, entire section is params
+                    params_section = negative_and_params
+                
+                # Extract generation parameters
+                if params_section:
+                    # Extract basic parameters
+                    param_pattern = r'([A-Za-z\s]+): ([^,]+)'
+                    params = re.findall(param_pattern, params_section)
+                    
+                    for key, value in params:
+                        clean_key = key.strip().lower().replace(' ', '_')
+                        
+                        # Skip if not in recognized gen param keys
+                        if clean_key not in GEN_PARAM_KEYS:
+                            continue
+                            
+                        # Convert numeric values
+                        if clean_key in ['steps', 'seed']:
+                            try:
+                                metadata[clean_key] = int(value.strip())
+                            except ValueError:
+                                metadata[clean_key] = value.strip()
+                        elif clean_key in ['cfg_scale']:
+                            try:
+                                metadata[clean_key] = float(value.strip())
+                            except ValueError:
+                                metadata[clean_key] = value.strip()
+                        else:
+                            metadata[clean_key] = value.strip()
+                    
+                    # Extract size if available and add if a recognized key
+                    size_match = re.search(r'Size: (\d+)x(\d+)', params_section)
+                    if size_match and 'size' in GEN_PARAM_KEYS:
+                        width, height = size_match.groups()
+                        metadata['size'] = f"{width}x{height}"
+            
+            # Return metadata if we have any entries
+            return metadata if metadata else None
+            
+        except Exception as e:
+            logger.error(f"Error parsing image metadata: {e}", exc_info=True)
+            return None

py/utils/example_images_migration.py

@@ -0,0 +1,318 @@
+import asyncio
+import logging
+import os
+import re
+import json
+from ..services.settings_manager import settings
+from ..services.service_registry import ServiceRegistry
+from ..utils.metadata_manager import MetadataManager
+from ..utils.example_images_processor import ExampleImagesProcessor
+from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
+
+logger = logging.getLogger(__name__)
+
+CURRENT_NAMING_VERSION = 2  # Increment this when naming conventions change
+
+class ExampleImagesMigration:
+    """Handles migrations for example images naming conventions"""
+    
+    @staticmethod
+    async def check_and_run_migrations():
+        """Check if migrations are needed and run them in background"""
+        example_images_path = settings.get('example_images_path')
+        if not example_images_path or not os.path.exists(example_images_path):
+            logger.debug("No example images path configured or path doesn't exist, skipping migrations")
+            return
+        
+        # Check current version from progress file
+        current_version = 0
+        progress_file = os.path.join(example_images_path, '.download_progress.json')
+        if os.path.exists(progress_file):
+            try:
+                with open(progress_file, 'r', encoding='utf-8') as f:
+                    progress_data = json.load(f)
+                    current_version = progress_data.get('naming_version', 0)
+            except Exception as e:
+                logger.error(f"Failed to load progress file for migration check: {e}")
+        
+        # If current version is less than target version, start migration
+        if current_version < CURRENT_NAMING_VERSION:
+            logger.info(f"Starting example images naming migration from v{current_version} to v{CURRENT_NAMING_VERSION}")
+            # Start migration in background task
+            asyncio.create_task(
+                ExampleImagesMigration.run_migrations(example_images_path, current_version, CURRENT_NAMING_VERSION)
+            )
+    
+    @staticmethod
+    async def run_migrations(example_images_path, from_version, to_version):
+        """Run necessary migrations based on version difference"""
+        try:
+            # Get all model folders
+            model_folders = []
+            for item in os.listdir(example_images_path):
+                item_path = os.path.join(example_images_path, item)
+                if os.path.isdir(item_path) and len(item) == 64:  # SHA256 hash is 64 chars
+                    model_folders.append(item_path)
+            
+            logger.info(f"Found {len(model_folders)} model folders to check for migration")
+            
+            # Apply migrations sequentially
+            if from_version < 1 and to_version >= 1:
+                await ExampleImagesMigration._migrate_to_v1(model_folders)
+            
+            if from_version < 2 and to_version >= 2:
+                await ExampleImagesMigration._migrate_to_v2(model_folders)
+            
+            # Update version in progress file
+            progress_file = os.path.join(example_images_path, '.download_progress.json')
+            try:
+                progress_data = {}
+                if os.path.exists(progress_file):
+                    with open(progress_file, 'r', encoding='utf-8') as f:
+                        progress_data = json.load(f)
+                
+                progress_data['naming_version'] = to_version
+                
+                with open(progress_file, 'w', encoding='utf-8') as f:
+                    json.dump(progress_data, f, indent=2)
+                    
+                logger.info(f"Example images naming migration to v{to_version} completed")
+                
+            except Exception as e:
+                logger.error(f"Failed to update version in progress file: {e}")
+                
+        except Exception as e:
+            logger.error(f"Error during migration: {e}", exc_info=True)
+    
+    @staticmethod
+    async def _migrate_to_v1(model_folders):
+        """Migrate from 1-based to 0-based indexing"""
+        count = 0
+        for folder in model_folders:
+            has_one_based = False
+            has_zero_based = False
+            files_to_rename = []
+            
+            # Check naming pattern in this folder
+            for file in os.listdir(folder):
+                if re.match(r'image_1\.\w+$', file):
+                    has_one_based = True
+                if re.match(r'image_0\.\w+$', file):
+                    has_zero_based = True
+            
+            # Only migrate folders with 1-based indexing and no 0-based
+            if has_one_based and not has_zero_based:
+                # Create rename mapping
+                for file in os.listdir(folder):
+                    match = re.match(r'image_(\d+)\.(\w+)$', file)
+                    if match:
+                        index = int(match.group(1))
+                        ext = match.group(2)
+                        if index > 0:  # Only rename if index is positive
+                            files_to_rename.append((
+                                file,
+                                f"image_{index-1}.{ext}"
+                            ))
+                
+                # Use temporary names to avoid conflicts
+                for old_name, new_name in files_to_rename:
+                    old_path = os.path.join(folder, old_name)
+                    temp_path = os.path.join(folder, f"temp_{old_name}")
+                    try:
+                        os.rename(old_path, temp_path)
+                    except Exception as e:
+                        logger.error(f"Failed to rename {old_path} to {temp_path}: {e}")
+                
+                # Rename from temporary names to final names
+                for old_name, new_name in files_to_rename:
+                    temp_path = os.path.join(folder, f"temp_{old_name}")
+                    new_path = os.path.join(folder, new_name)
+                    try:
+                        os.rename(temp_path, new_path)
+                        logger.debug(f"Renamed {old_name} to {new_name} in {folder}")
+                    except Exception as e:
+                        logger.error(f"Failed to rename {temp_path} to {new_path}: {e}")
+                
+                count += 1
+                
+                # Give other tasks a chance to run
+                if count % 10 == 0:
+                    await asyncio.sleep(0)
+        
+        logger.info(f"Migrated {count} folders from 1-based to 0-based indexing")
+    
+    @staticmethod
+    async def _migrate_to_v2(model_folders):
+        """
+        Migrate to v2 naming scheme:
+        - Move custom examples from images array to customImages array
+        - Rename files from image_<index>.<ext> to custom_<short_id>.<ext>
+        - Add id field to each custom image entry
+        """
+        count = 0
+        updated_models = 0
+        migration_errors = 0
+        
+        # Get scanner instances
+        lora_scanner = await ServiceRegistry.get_lora_scanner()
+        checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
+        
+        # Wait until scanners are initialized
+        scanners = [lora_scanner, checkpoint_scanner]
+        for scanner in scanners:
+            if scanner.is_initializing():
+                logger.info("Waiting for scanners to complete initialization before starting migration...")
+                initialized = False
+                retry_count = 0
+                while not initialized and retry_count < 120:  # Wait up to 120 seconds
+                    await asyncio.sleep(1)
+                    initialized = not scanner.is_initializing()
+                    retry_count += 1
+                
+                if not initialized:
+                    logger.warning("Scanner initialization timeout - proceeding with migration anyway")
+        
+        logger.info(f"Starting migration to v2 naming scheme for {len(model_folders)} model folders")
+        
+        for folder in model_folders:
+            try:
+                # Extract model hash from folder name
+                model_hash = os.path.basename(folder)
+                if not model_hash or len(model_hash) != 64:
+                    continue
+                
+                # Find the model in scanner cache
+                model_data = None
+                scanner = None
+                
+                for scan_obj in scanners:
+                  if scan_obj.has_hash(model_hash):
+                    cache = await scan_obj.get_cached_data()
+                    for item in cache.raw_data:
+                      if item.get('sha256') == model_hash:
+                        model_data = item
+                        scanner = scan_obj
+                        break
+                  if model_data:
+                    break
+                
+                if not model_data or not scanner:
+                    logger.debug(f"Model with hash {model_hash} not found in cache, skipping migration")
+                    continue
+                
+                # Clone model data to avoid modifying the cache directly
+                model_metadata = model_data.copy()
+                
+                # Check if model has civitai metadata
+                if not model_metadata.get('civitai'):
+                    continue
+                
+                # Get images array
+                images = model_metadata.get('civitai', {}).get('images', [])
+                if not images:
+                    continue
+                
+                # Initialize customImages array if it doesn't exist
+                if not model_metadata['civitai'].get('customImages'):
+                    model_metadata['civitai']['customImages'] = []
+                
+                # Find custom examples (entries with empty url)
+                custom_indices = []
+                for i, image in enumerate(images):
+                    if image.get('url') == "":
+                        custom_indices.append(i)
+                
+                if not custom_indices:
+                    continue
+                    
+                logger.debug(f"Found {len(custom_indices)} custom examples in {model_hash}")
+                
+                # Process each custom example
+                for index in custom_indices:
+                    try:
+                        image_entry = images[index]
+                        
+                        # Determine media type based on the entry type
+                        media_type = 'videos' if image_entry.get('type') == 'video' else 'images'
+                        extensions_to_try = SUPPORTED_MEDIA_EXTENSIONS[media_type]
+                        
+                        # Find the image file by trying possible extensions
+                        old_path = None
+                        old_filename = None
+                        found = False
+                        
+                        for ext in extensions_to_try:
+                            test_path = os.path.join(folder, f"image_{index}{ext}")
+                            if os.path.exists(test_path):
+                                old_path = test_path
+                                old_filename = f"image_{index}{ext}"
+                                found = True
+                                break
+                                
+                        if not found:
+                            logger.warning(f"Could not find file for index {index} in {model_hash}, skipping")
+                            continue
+                        
+                        # Generate short ID for the custom example
+                        short_id = ExampleImagesProcessor.generate_short_id()
+                        
+                        # Get file extension
+                        file_ext = os.path.splitext(old_path)[1]
+                        
+                        # Create new filename
+                        new_filename = f"custom_{short_id}{file_ext}"
+                        new_path = os.path.join(folder, new_filename)
+                        
+                        # Rename the file
+                        try:
+                            os.rename(old_path, new_path)
+                            logger.debug(f"Renamed {old_filename} to {new_filename} in {folder}")
+                        except Exception as e:
+                            logger.error(f"Failed to rename {old_path} to {new_path}: {e}")
+                            continue
+                        
+                        # Create a copy of the image entry with the id field
+                        custom_entry = image_entry.copy()
+                        custom_entry['id'] = short_id
+                        
+                        # Add to customImages array
+                        model_metadata['civitai']['customImages'].append(custom_entry)
+                        
+                        count += 1
+                        
+                    except Exception as e:
+                        logger.error(f"Error migrating custom example at index {index} for {model_hash}: {e}")
+                
+                # Remove custom examples from the original images array
+                model_metadata['civitai']['images'] = [
+                    img for i, img in enumerate(images) if i not in custom_indices
+                ]
+                
+                # Save the updated metadata
+                file_path = model_data.get('file_path')
+                if file_path:
+                    try:
+                        # Create a copy of model data without 'folder' field
+                        model_copy = model_metadata.copy()
+                        model_copy.pop('folder', None)
+                        
+                        # Save metadata to file
+                        await MetadataManager.save_metadata(file_path, model_copy)
+                        
+                        # Update scanner cache
+                        await scanner.update_single_model_cache(file_path, file_path, model_metadata)
+                        
+                        updated_models += 1
+                    except Exception as e:
+                        logger.error(f"Failed to save metadata for {model_hash}: {e}")
+                        migration_errors += 1
+                
+                # Give other tasks a chance to run
+                if count % 10 == 0:
+                    await asyncio.sleep(0)
+                    
+            except Exception as e:
+                logger.error(f"Error migrating folder {folder}: {e}")
+                migration_errors += 1
+        
+        logger.info(f"Migration to v2 complete: migrated {count} custom examples across {updated_models} models with {migration_errors} errors")

py/utils/example_images_processor.py

@@ -0,0 +1,494 @@
+import logging
+import os
+import re
+import tempfile
+import random
+import string
+from aiohttp import web
+from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
+from ..services.service_registry import ServiceRegistry
+from ..services.settings_manager import settings
+from .example_images_metadata import MetadataUpdater
+from ..utils.metadata_manager import MetadataManager
+
+logger = logging.getLogger(__name__)
+
+class ExampleImagesProcessor:
+    """Processes and manipulates example images"""
+
+    @staticmethod
+    def generate_short_id(length=8):
+        """Generate a short random alphanumeric identifier"""
+        chars = string.ascii_lowercase + string.digits
+        return ''.join(random.choice(chars) for _ in range(length))
+    
+    @staticmethod
+    def get_civitai_optimized_url(image_url):
+        """Convert Civitai image URL to its optimized WebP version"""
+        base_pattern = r'(https://image\.civitai\.com/[^/]+/[^/]+)'
+        match = re.match(base_pattern, image_url)
+        
+        if match:
+            base_url = match.group(1)
+            return f"{base_url}/optimized=true/image.webp"
+        
+        return image_url
+    
+    @staticmethod
+    async def download_model_images(model_hash, model_name, model_images, model_dir, optimize, independent_session):
+        """Download images for a single model
+        
+        Returns:
+            tuple: (success, is_stale_metadata) - whether download was successful, whether metadata is stale
+        """
+        model_success = True
+        
+        for i, image in enumerate(model_images):
+            image_url = image.get('url')
+            if not image_url:
+                continue
+            
+            # Get image filename from URL
+            image_filename = os.path.basename(image_url.split('?')[0])
+            image_ext = os.path.splitext(image_filename)[1].lower()
+            
+            # Handle images and videos
+            is_image = image_ext in SUPPORTED_MEDIA_EXTENSIONS['images']
+            is_video = image_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
+            
+            if not (is_image or is_video):
+                logger.debug(f"Skipping unsupported file type: {image_filename}")
+                continue
+            
+            # Use 0-based indexing instead of 1-based indexing
+            save_filename = f"image_{i}{image_ext}"
+            
+            # If optimizing images and this is a Civitai image, use their pre-optimized WebP version
+            if is_image and optimize and 'civitai.com' in image_url:
+                image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
+                save_filename = f"image_{i}.webp"
+            
+            # Check if already downloaded
+            save_path = os.path.join(model_dir, save_filename)
+            if os.path.exists(save_path):
+                logger.debug(f"File already exists: {save_path}")
+                continue
+            
+            # Download the file
+            try:
+                logger.debug(f"Downloading {save_filename} for {model_name}")
+                
+                # Download directly using the independent session
+                async with independent_session.get(image_url, timeout=60) as response:
+                    if response.status == 200:
+                        with open(save_path, 'wb') as f:
+                            async for chunk in response.content.iter_chunked(8192):
+                                if chunk:
+                                    f.write(chunk)
+                    elif response.status == 404:
+                        error_msg = f"Failed to download file: {image_url}, status code: 404 - Model metadata might be stale"
+                        logger.warning(error_msg)
+                        model_success = False  # Mark the model as failed due to 404 error
+                        # Return early to trigger metadata refresh attempt
+                        return False, True  # (success, is_metadata_stale)
+                    else:
+                        error_msg = f"Failed to download file: {image_url}, status code: {response.status}"
+                        logger.warning(error_msg)
+                        model_success = False  # Mark the model as failed
+            except Exception as e:
+                error_msg = f"Error downloading file {image_url}: {str(e)}"
+                logger.error(error_msg)
+                model_success = False  # Mark the model as failed
+        
+        return model_success, False  # (success, is_metadata_stale)
+    
+    @staticmethod
+    async def process_local_examples(model_file_path, model_file_name, model_name, model_dir, optimize):
+        """Process local example images
+        
+        Returns:
+            bool: True if local images were processed successfully, False otherwise
+        """
+        try:
+            if not model_file_path or not os.path.exists(os.path.dirname(model_file_path)):
+                return False
+                
+            model_dir_path = os.path.dirname(model_file_path)
+            local_images = []
+            
+            # Look for files with pattern: filename.example.*.ext
+            if model_file_name:
+                example_prefix = f"{model_file_name}.example."
+                
+                if os.path.exists(model_dir_path):
+                    for file in os.listdir(model_dir_path):
+                        file_lower = file.lower()
+                        if file_lower.startswith(example_prefix.lower()):
+                            file_ext = os.path.splitext(file_lower)[1]
+                            is_supported = (file_ext in SUPPORTED_MEDIA_EXTENSIONS['images'] or 
+                                           file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos'])
+                            
+                            if is_supported:
+                                local_images.append(os.path.join(model_dir_path, file))
+            
+            # Process local images if found
+            if local_images:
+                logger.info(f"Found {len(local_images)} local example images for {model_name}")
+                
+                for local_image_path in local_images:
+                    # Extract index from filename
+                    file_name = os.path.basename(local_image_path)
+                    example_prefix = f"{model_file_name}.example."
+                    
+                    try:
+                        # Extract the part between '.example.' and the file extension
+                        index_part = file_name[len(example_prefix):].split('.')[0]
+                        # Try to parse it as an integer
+                        index = int(index_part)
+                        local_ext = os.path.splitext(local_image_path)[1].lower()
+                        save_filename = f"image_{index}{local_ext}"
+                    except (ValueError, IndexError):
+                        # If we can't parse the index, fall back to sequential numbering
+                        logger.warning(f"Could not extract index from {file_name}, using sequential numbering")
+                        local_ext = os.path.splitext(local_image_path)[1].lower()
+                        save_filename = f"image_{len(local_images)}{local_ext}"
+                    
+                    save_path = os.path.join(model_dir, save_filename)
+                    
+                    # Skip if already exists in output directory
+                    if os.path.exists(save_path):
+                        logger.debug(f"File already exists in output: {save_path}")
+                        continue
+                    
+                    # Copy the file
+                    with open(local_image_path, 'rb') as src_file:
+                        with open(save_path, 'wb') as dst_file:
+                            dst_file.write(src_file.read())
+                
+                return True
+            return False
+        except Exception as e:
+            logger.error(f"Error processing local examples for {model_name}: {str(e)}")
+            return False
+            
+    @staticmethod
+    async def import_images(request):
+        """
+        Import local example images
+        
+        Accepts:
+        - multipart/form-data form with model_hash and files fields
+        or
+        - JSON request with model_hash and file_paths
+        
+        Returns:
+        - Success status and list of imported files
+        """
+        try:
+            model_hash = None
+            files_to_import = []
+            temp_files_to_cleanup = []
+            
+            # Check if it's a multipart form-data request (direct file upload)
+            if request.content_type and 'multipart/form-data' in request.content_type:
+                reader = await request.multipart()
+                
+                # First get model_hash
+                field = await reader.next()
+                if field.name == 'model_hash':
+                    model_hash = await field.text()
+                
+                # Then process all files
+                while True:
+                    field = await reader.next()
+                    if field is None:
+                        break
+                        
+                    if field.name == 'files':
+                        # Create a temporary file with appropriate suffix for type detection
+                        file_name = field.filename
+                        file_ext = os.path.splitext(file_name)[1].lower()
+                        
+                        with tempfile.NamedTemporaryFile(suffix=file_ext, delete=False) as tmp_file:
+                            temp_path = tmp_file.name
+                            temp_files_to_cleanup.append(temp_path)  # Track for cleanup
+                            
+                            # Write chunks to the temporary file
+                            while True:
+                                chunk = await field.read_chunk()
+                                if not chunk:
+                                    break
+                                tmp_file.write(chunk)
+                        
+                        # Add to the list of files to process
+                        files_to_import.append(temp_path)
+            else:
+                # Parse JSON request (legacy method using file paths)
+                data = await request.json()
+                model_hash = data.get('model_hash')
+                files_to_import = data.get('file_paths', [])
+            
+            if not model_hash:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing model_hash parameter'
+                }, status=400)
+            
+            if not files_to_import:
+                return web.json_response({
+                    'success': False,
+                    'error': 'No files provided to import'
+                }, status=400)
+            
+            # Get example images path
+            example_images_path = settings.get('example_images_path')
+            if not example_images_path:
+                return web.json_response({
+                    'success': False,
+                    'error': 'No example images path configured'
+                }, status=400)
+            
+            # Find the model and get current metadata
+            lora_scanner = await ServiceRegistry.get_lora_scanner()
+            checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
+            
+            model_data = None
+            scanner = None
+            
+            # Check both scanners to find the model
+            for scan_obj in [lora_scanner, checkpoint_scanner]:
+                cache = await scan_obj.get_cached_data()
+                for item in cache.raw_data:
+                    if item.get('sha256') == model_hash:
+                        model_data = item
+                        scanner = scan_obj
+                        break
+                if model_data:
+                    break
+            
+            if not model_data:
+                return web.json_response({
+                    'success': False,
+                    'error': f"Model with hash {model_hash} not found in cache"
+                }, status=404)
+            
+            # Create model folder
+            model_folder = os.path.join(example_images_path, model_hash)
+            os.makedirs(model_folder, exist_ok=True)
+            
+            imported_files = []
+            errors = []
+            newly_imported_paths = []
+            
+            # Process each file path
+            for file_path in files_to_import:
+                try:
+                    # Ensure the file exists
+                    if not os.path.isfile(file_path):
+                        errors.append(f"File not found: {file_path}")
+                        continue
+                    
+                    # Check if file type is supported
+                    file_ext = os.path.splitext(file_path)[1].lower()
+                    if not (file_ext in SUPPORTED_MEDIA_EXTENSIONS['images'] or 
+                            file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']):
+                        errors.append(f"Unsupported file type: {file_path}")
+                        continue
+                    
+                    # Generate new filename using short ID instead of UUID
+                    short_id = ExampleImagesProcessor.generate_short_id()
+                    new_filename = f"custom_{short_id}{file_ext}"
+                    
+                    dest_path = os.path.join(model_folder, new_filename)
+                    
+                    # Copy the file
+                    import shutil
+                    shutil.copy2(file_path, dest_path)
+                    # Store both the dest_path and the short_id
+                    newly_imported_paths.append((dest_path, short_id))
+                    
+                    # Add to imported files list
+                    imported_files.append({
+                        'name': new_filename,
+                        'path': f'/example_images_static/{model_hash}/{new_filename}',
+                        'extension': file_ext,
+                        'is_video': file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']
+                    })
+                except Exception as e:
+                    errors.append(f"Error importing {file_path}: {str(e)}")
+            
+            # Update metadata with new example images
+            regular_images, custom_images = await MetadataUpdater.update_metadata_after_import(
+                model_hash, 
+                model_data,
+                scanner,
+                newly_imported_paths
+            )
+            
+            return web.json_response({
+                'success': len(imported_files) > 0,
+                'message': f'Successfully imported {len(imported_files)} files' + 
+                        (f' with {len(errors)} errors' if errors else ''),
+                'files': imported_files,
+                'errors': errors,
+                'regular_images': regular_images,
+                'custom_images': custom_images,
+                "model_file_path": model_data.get('file_path', ''),
+            })
+                
+        except Exception as e:
+            logger.error(f"Failed to import example images: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)
+        finally:
+            # Clean up temporary files
+            for temp_file in temp_files_to_cleanup:
+                try:
+                    os.remove(temp_file)
+                except Exception as e:
+                    logger.error(f"Failed to remove temporary file {temp_file}: {e}")
+
+    @staticmethod
+    async def delete_custom_image(request):
+        """
+        Delete a custom example image for a model
+        
+        Accepts:
+        - JSON request with model_hash and short_id
+        
+        Returns:
+        - Success status and updated image lists
+        """
+        try:
+            # Parse request data
+            data = await request.json()
+            model_hash = data.get('model_hash')
+            short_id = data.get('short_id')
+            
+            if not model_hash or not short_id:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing required parameters: model_hash and short_id'
+                }, status=400)
+            
+            # Get example images path
+            example_images_path = settings.get('example_images_path')
+            if not example_images_path:
+                return web.json_response({
+                    'success': False,
+                    'error': 'No example images path configured'
+                }, status=400)
+            
+            # Find the model and get current metadata
+            lora_scanner = await ServiceRegistry.get_lora_scanner()
+            checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
+            
+            model_data = None
+            scanner = None
+            
+            # Check both scanners to find the model
+            for scan_obj in [lora_scanner, checkpoint_scanner]:
+                if scan_obj.has_hash(model_hash):
+                    cache = await scan_obj.get_cached_data()
+                    for item in cache.raw_data:
+                        if item.get('sha256') == model_hash:
+                            model_data = item
+                            scanner = scan_obj
+                            break
+                if model_data:
+                    break
+            
+            if not model_data:
+                return web.json_response({
+                    'success': False,
+                    'error': f"Model with hash {model_hash} not found in cache"
+                }, status=404)
+            
+            # Check if model has custom images
+            if not model_data.get('civitai', {}).get('customImages'):
+                return web.json_response({
+                    'success': False,
+                    'error': f"Model has no custom images"
+                }, status=404)
+            
+            # Find the custom image with matching short_id
+            custom_images = model_data['civitai']['customImages']
+            matching_image = None
+            new_custom_images = []
+            
+            for image in custom_images:
+                if image.get('id') == short_id:
+                    matching_image = image
+                else:
+                    new_custom_images.append(image)
+            
+            if not matching_image:
+                return web.json_response({
+                    'success': False,
+                    'error': f"Custom image with id {short_id} not found"
+                }, status=404)
+            
+            # Find and delete the actual file
+            model_folder = os.path.join(example_images_path, model_hash)
+            file_deleted = False
+            
+            if os.path.exists(model_folder):
+                for filename in os.listdir(model_folder):
+                    if f"custom_{short_id}" in filename:
+                        file_path = os.path.join(model_folder, filename)
+                        try:
+                            os.remove(file_path)
+                            file_deleted = True
+                            logger.info(f"Deleted custom example file: {file_path}")
+                            break
+                        except Exception as e:
+                            return web.json_response({
+                                'success': False,
+                                'error': f"Failed to delete file: {str(e)}"
+                            }, status=500)
+            
+            if not file_deleted:
+                logger.warning(f"File for custom example with id {short_id} not found, but metadata will still be updated")
+            
+            # Update metadata
+            model_data['civitai']['customImages'] = new_custom_images
+            
+            # Save updated metadata to file
+            file_path = model_data.get('file_path')
+            if file_path:
+                try:
+                    # Create a copy of model data without 'folder' field
+                    model_copy = model_data.copy()
+                    model_copy.pop('folder', None)
+                    
+                    # Write metadata to file
+                    await MetadataManager.save_metadata(file_path, model_copy)
+                    logger.debug(f"Saved updated metadata for {model_data.get('model_name')}")
+                except Exception as e:
+                    logger.error(f"Failed to save metadata: {str(e)}")
+                    return web.json_response({
+                        'success': False,
+                        'error': f"Failed to save metadata: {str(e)}"
+                    }, status=500)
+            
+                # Update cache
+                await scanner.update_single_model_cache(file_path, file_path, model_data)
+            
+            # Get regular images array (might be None)
+            regular_images = model_data['civitai'].get('images', [])
+            
+            return web.json_response({
+                'success': True,
+                'regular_images': regular_images,
+                'custom_images': new_custom_images,
+                'model_file_path': model_data.get('file_path', '')
+            })
+                
+        except Exception as e:
+            logger.error(f"Failed to delete custom example image: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)

py/utils/file_utils.py

@@ -63,199 +63,4 @@ def find_preview_file(base_name: str, dir_path: str) -> str:
 
 def normalize_path(path: str) -> str:
     """Normalize file path to use forward slashes"""
-    return path.replace(os.sep, "/") if path else path
-
-async def get_file_info(file_path: str, model_class: Type[BaseModelMetadata] = LoraMetadata) -> Optional[BaseModelMetadata]:
-    """Get basic file information as a model metadata object"""
-    # First check if file actually exists and resolve symlinks
-    try:
-        real_path = os.path.realpath(file_path)
-        if not os.path.exists(real_path):
-            return None
-    except Exception as e:
-        logger.error(f"Error checking file existence for {file_path}: {e}")
-        return None
-        
-    base_name = os.path.splitext(os.path.basename(file_path))[0]
-    dir_path = os.path.dirname(file_path)
-    
-    preview_url = find_preview_file(base_name, dir_path)
-    
-    # Check if a .json file exists with SHA256 hash to avoid recalculation
-    json_path = f"{os.path.splitext(file_path)[0]}.json"
-    sha256 = None
-    if os.path.exists(json_path):
-        try:
-            with open(json_path, 'r', encoding='utf-8') as f:
-                json_data = json.load(f)
-                if 'sha256' in json_data:
-                    sha256 = json_data['sha256'].lower()
-                    logger.debug(f"Using SHA256 from .json file for {file_path}")
-        except Exception as e:
-            logger.error(f"Error reading .json file for {file_path}: {e}")
-    
-    # If SHA256 is still not found, check for a .sha256 file
-    if sha256 is None:
-        sha256_file = f"{os.path.splitext(file_path)[0]}.sha256"
-        if os.path.exists(sha256_file):
-            try:
-                with open(sha256_file, 'r', encoding='utf-8') as f:
-                    sha256 = f.read().strip().lower()
-                    logger.debug(f"Using SHA256 from .sha256 file for {file_path}")
-            except Exception as e:
-                logger.error(f"Error reading .sha256 file for {file_path}: {e}")
-
-    try:
-        # If we didn't get SHA256 from the .json file, calculate it
-        if not sha256:
-            start_time = time.time()
-            sha256 = await calculate_sha256(real_path)
-            logger.debug(f"Calculated SHA256 for {file_path} in {time.time() - start_time:.2f} seconds")
-        
-        # Create default metadata based on model class
-        if model_class == CheckpointMetadata:
-            metadata = CheckpointMetadata(
-                file_name=base_name,
-                model_name=base_name,
-                file_path=normalize_path(file_path),
-                size=os.path.getsize(real_path),
-                modified=os.path.getmtime(real_path),
-                sha256=sha256,
-                base_model="Unknown",  # Will be updated later
-                preview_url=normalize_path(preview_url),
-                tags=[],
-                modelDescription="",
-                model_type="checkpoint"
-            )
-            
-            # Extract checkpoint-specific metadata
-            # model_info = await extract_checkpoint_metadata(real_path)
-            # metadata.base_model = model_info['base_model']
-            # if 'model_type' in model_info:
-            #     metadata.model_type = model_info['model_type']
-            
-        else:  # Default to LoraMetadata
-            metadata = LoraMetadata(
-                file_name=base_name,
-                model_name=base_name,
-                file_path=normalize_path(file_path),
-                size=os.path.getsize(real_path),
-                modified=os.path.getmtime(real_path),
-                sha256=sha256,
-                base_model="Unknown",  # Will be updated later
-                usage_tips="{}",
-                preview_url=normalize_path(preview_url),
-                tags=[],
-                modelDescription=""
-            )
-            
-            # Extract lora-specific metadata
-            model_info = await extract_lora_metadata(real_path)
-            metadata.base_model = model_info['base_model']
-
-        # Save metadata to file
-        await save_metadata(file_path, metadata)
-        
-        return metadata
-    except Exception as e:
-        logger.error(f"Error getting file info for {file_path}: {e}")
-        return None
-
-async def save_metadata(file_path: str, metadata: BaseModelMetadata) -> None:
-    """Save metadata to .metadata.json file"""
-    metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
-    try:
-        metadata_dict = metadata.to_dict()
-        metadata_dict['file_path'] = normalize_path(metadata_dict['file_path'])
-        metadata_dict['preview_url'] = normalize_path(metadata_dict['preview_url'])
-        
-        with open(metadata_path, 'w', encoding='utf-8') as f:
-            json.dump(metadata_dict, f, indent=2, ensure_ascii=False)
-    except Exception as e:
-        print(f"Error saving metadata to {metadata_path}: {str(e)}")
-
-async def load_metadata(file_path: str, model_class: Type[BaseModelMetadata] = LoraMetadata) -> Optional[BaseModelMetadata]:
-    """Load metadata from .metadata.json file"""
-    metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
-    try:
-        if os.path.exists(metadata_path):
-            with open(metadata_path, 'r', encoding='utf-8') as f:
-                data = json.load(f)
-                
-                needs_update = False
-
-                # Check and normalize base model name
-                normalized_base_model = determine_base_model(data['base_model'])
-                if data['base_model'] != normalized_base_model:
-                    data['base_model'] = normalized_base_model
-                    needs_update = True
-                
-                # Compare paths without extensions
-                stored_path_base = os.path.splitext(data['file_path'])[0]
-                current_path_base = os.path.splitext(normalize_path(file_path))[0]
-                if stored_path_base != current_path_base:
-                    data['file_path'] = normalize_path(file_path)
-                    needs_update = True
-                
-                # TODO: optimize preview image to webp format if not already done
-                preview_url = data.get('preview_url', '')
-                if not preview_url or not os.path.exists(preview_url):
-                    base_name = os.path.splitext(os.path.basename(file_path))[0]
-                    dir_path = os.path.dirname(file_path)
-                    new_preview_url = normalize_path(find_preview_file(base_name, dir_path))
-                    if new_preview_url != preview_url:
-                        data['preview_url'] = new_preview_url
-                        needs_update = True
-                else:
-                    if stored_path_base != current_path_base:
-                        # If model location changed, update preview path by replacing old path with new path
-                        preview_file = os.path.basename(preview_url)
-                        new_preview_url = os.path.join(os.path.dirname(file_path), preview_file)
-                        data['preview_url'] = normalize_path(new_preview_url)
-                        needs_update = True
-
-                # Ensure all fields are present
-                if 'tags' not in data:
-                    data['tags'] = []
-                    needs_update = True
-                    
-                if 'modelDescription' not in data:
-                    data['modelDescription'] = ""
-                    needs_update = True
-                    
-                # For checkpoint metadata
-                if model_class == CheckpointMetadata and 'model_type' not in data:
-                    data['model_type'] = "checkpoint"
-                    needs_update = True
-                
-                # For lora metadata
-                if model_class == LoraMetadata and 'usage_tips' not in data:
-                    data['usage_tips'] = "{}"
-                    needs_update = True
-                
-                # Update preview_nsfw_level if needed
-                civitai_data = data.get('civitai', {})
-                civitai_images = civitai_data.get('images', []) if civitai_data else []
-                if (data.get('preview_url') and 
-                    data.get('preview_nsfw_level', 0) == 0 and 
-                    civitai_images and 
-                    civitai_images[0].get('nsfwLevel', 0) != 0):
-                    data['preview_nsfw_level'] = civitai_images[0]['nsfwLevel']
-                    # TODO: write to metadata file
-                    # needs_update = True
-
-                if needs_update:
-                    with open(metadata_path, 'w', encoding='utf-8') as f:
-                        json.dump(data, f, indent=2, ensure_ascii=False)
-                
-                return model_class.from_dict(data)
-                
-    except Exception as e:
-        print(f"Error loading metadata from {metadata_path}: {str(e)}")
-    return None
-
-async def update_civitai_metadata(file_path: str, civitai_data: Dict) -> None:
-    """Update metadata file with Civitai data"""
-    metadata = await load_metadata(file_path)
-    metadata['civitai'] = civitai_data
-    await save_metadata(file_path, metadata)
+    return path.replace(os.sep, "/") if path else path

py/utils/metadata_manager.py

@@ -0,0 +1,275 @@
+import os
+import json
+import shutil
+import logging
+from typing import Dict, Optional, Type, Union
+
+from .models import BaseModelMetadata, LoraMetadata
+from .file_utils import normalize_path, find_preview_file, calculate_sha256
+from .lora_metadata import extract_lora_metadata, extract_checkpoint_metadata
+
+logger = logging.getLogger(__name__)
+
+class MetadataManager:
+    """
+    Centralized manager for all metadata operations.
+    
+    This class is responsible for:
+    1. Loading metadata safely with fallback mechanisms
+    2. Saving metadata with atomic operations and backups
+    3. Creating default metadata for models
+    4. Handling unknown fields gracefully
+    """
+    
+    @staticmethod
+    async def load_metadata(file_path: str, model_class: Type[BaseModelMetadata] = LoraMetadata) -> Optional[BaseModelMetadata]:
+        """
+        Load metadata with robust error handling and data preservation.
+        
+        Args:
+            file_path: Path to the model file
+            model_class: Class to instantiate (LoraMetadata, CheckpointMetadata, etc.)
+            
+        Returns:
+            BaseModelMetadata instance or None if file doesn't exist
+        """
+        metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
+        backup_path = f"{metadata_path}.bak"
+        
+        # Try loading the main metadata file
+        if os.path.exists(metadata_path):
+            try:
+                with open(metadata_path, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                
+                # Create model instance
+                metadata = model_class.from_dict(data)
+                    
+                # Normalize paths
+                await MetadataManager._normalize_metadata_paths(metadata, file_path)
+                
+                return metadata
+                
+            except json.JSONDecodeError:
+                # JSON parsing error - try to restore from backup
+                logger.warning(f"Invalid JSON in metadata file: {metadata_path}")
+                return await MetadataManager._restore_from_backup(backup_path, file_path, model_class)
+                
+            except Exception as e:
+                # Other errors might be due to unknown fields or schema changes
+                logger.error(f"Error loading metadata from {metadata_path}: {str(e)}")
+                return await MetadataManager._restore_from_backup(backup_path, file_path, model_class)
+        
+        return None
+    
+    @staticmethod
+    async def _restore_from_backup(backup_path: str, file_path: str, model_class: Type[BaseModelMetadata]) -> Optional[BaseModelMetadata]:
+        """
+        Try to restore metadata from backup file
+        
+        Args:
+            backup_path: Path to backup file
+            file_path: Path to the original model file
+            model_class: Class to instantiate
+            
+        Returns:
+            BaseModelMetadata instance or None if restoration fails
+        """
+        if os.path.exists(backup_path):
+            try:
+                logger.info(f"Attempting to restore metadata from backup: {backup_path}")
+                with open(backup_path, 'r', encoding='utf-8') as f:
+                    data = json.load(f)
+                
+                # Process data similarly to normal loading
+                metadata = model_class.from_dict(data)
+                await MetadataManager._normalize_metadata_paths(metadata, file_path)
+                return metadata
+            except Exception as e:
+                logger.error(f"Failed to restore from backup: {str(e)}")
+        
+        return None
+    
+    @staticmethod
+    async def save_metadata(path: str, metadata: Union[BaseModelMetadata, Dict], create_backup: bool = True) -> bool:
+        """
+        Save metadata with atomic write operations and backup creation.
+        
+        Args:
+          path: Path to the model file or directly to the metadata file
+          metadata: Metadata to save (either BaseModelMetadata object or dict)
+          create_backup: Whether to create a backup of existing file
+          
+        Returns:
+          bool: Success or failure
+        """
+        # Determine if the input is a metadata path or a model file path
+        if path.endswith('.metadata.json'):
+            metadata_path = path
+        else:
+            # Use existing logic for model file paths
+            file_path = path
+            metadata_path = f"{os.path.splitext(file_path)[0]}.metadata.json"
+        temp_path = f"{metadata_path}.tmp"
+        backup_path = f"{metadata_path}.bak"
+        
+        try:
+            # Create backup if requested and file exists
+            if create_backup and os.path.exists(metadata_path):
+                try:
+                    shutil.copy2(metadata_path, backup_path)
+                except Exception as e:
+                    logger.warning(f"Failed to create metadata backup: {str(e)}")
+            
+            # Convert to dict if needed
+            if isinstance(metadata, BaseModelMetadata):
+                metadata_dict = metadata.to_dict()
+                # Preserve unknown fields if present
+                if hasattr(metadata, '_unknown_fields'):
+                    metadata_dict.update(metadata._unknown_fields)
+            else:
+                metadata_dict = metadata.copy()
+            
+            # Normalize paths
+            if 'file_path' in metadata_dict:
+                metadata_dict['file_path'] = normalize_path(metadata_dict['file_path'])
+            if 'preview_url' in metadata_dict:
+                metadata_dict['preview_url'] = normalize_path(metadata_dict['preview_url'])
+            
+            # Write to temporary file first
+            with open(temp_path, 'w', encoding='utf-8') as f:
+                json.dump(metadata_dict, f, indent=2, ensure_ascii=False)
+            
+            # Atomic rename operation
+            os.replace(temp_path, metadata_path)
+            return True
+            
+        except Exception as e:
+            logger.error(f"Error saving metadata to {metadata_path}: {str(e)}")
+            # Clean up temporary file if it exists
+            if os.path.exists(temp_path):
+                try:
+                    os.remove(temp_path)
+                except:
+                    pass
+            return False
+    
+    @staticmethod
+    async def create_default_metadata(file_path: str, model_class: Type[BaseModelMetadata] = LoraMetadata) -> Optional[BaseModelMetadata]:
+        """
+        Create basic metadata structure for a model file.
+        This replaces the old get_file_info function with a more appropriately named method.
+        
+        Args:
+            file_path: Path to the model file
+            model_class: Class to instantiate
+            
+        Returns:
+            BaseModelMetadata instance or None if file doesn't exist
+        """
+        # First check if file actually exists and resolve symlinks
+        try:
+            real_path = os.path.realpath(file_path)
+            if not os.path.exists(real_path):
+                return None
+        except Exception as e:
+            logger.error(f"Error checking file existence for {file_path}: {e}")
+            return None
+            
+        try:
+            base_name = os.path.splitext(os.path.basename(file_path))[0]
+            dir_path = os.path.dirname(file_path)
+            
+            # Find preview image
+            preview_url = find_preview_file(base_name, dir_path)
+            
+            # Calculate file hash
+            sha256 = await calculate_sha256(real_path)
+            
+            # Create instance based on model type
+            if model_class.__name__ == "CheckpointMetadata":
+                metadata = model_class(
+                    file_name=base_name,
+                    model_name=base_name,
+                    file_path=normalize_path(file_path),
+                    size=os.path.getsize(real_path),
+                    modified=os.path.getmtime(real_path),
+                    sha256=sha256,
+                    base_model="Unknown",
+                    preview_url=normalize_path(preview_url),
+                    tags=[],
+                    modelDescription="",
+                    model_type="checkpoint",
+                    from_civitai=False
+                )
+            else:  # Default to LoraMetadata
+                metadata = model_class(
+                    file_name=base_name,
+                    model_name=base_name,
+                    file_path=normalize_path(file_path),
+                    size=os.path.getsize(real_path),
+                    modified=os.path.getmtime(real_path),
+                    sha256=sha256,
+                    base_model="Unknown",
+                    preview_url=normalize_path(preview_url),
+                    tags=[],
+                    modelDescription="",
+                    from_civitai=False,
+                    usage_tips="{}"
+                )
+            
+            # Try to extract model-specific metadata
+            await MetadataManager._enrich_metadata(metadata, real_path)
+            
+            # Save the created metadata
+            await MetadataManager.save_metadata(file_path, metadata, create_backup=False)
+            
+            return metadata
+            
+        except Exception as e:
+            logger.error(f"Error creating default metadata for {file_path}: {e}")
+            return None
+    
+    @staticmethod
+    async def _enrich_metadata(metadata: BaseModelMetadata, file_path: str) -> None:
+        """
+        Enrich metadata with model-specific information
+        
+        Args:
+            metadata: Metadata to enrich
+            file_path: Path to the model file
+        """
+        try:
+            if metadata.__class__.__name__ == "LoraMetadata":
+                model_info = await extract_lora_metadata(file_path)
+                metadata.base_model = model_info['base_model']
+            
+            elif metadata.__class__.__name__ == "CheckpointMetadata":
+                model_info = await extract_checkpoint_metadata(file_path)
+                metadata.base_model = model_info['base_model']
+                if 'model_type' in model_info:
+                    metadata.model_type = model_info['model_type']
+        except Exception as e:
+            logger.error(f"Error enriching metadata: {str(e)}")
+    
+    @staticmethod
+    async def _normalize_metadata_paths(metadata: BaseModelMetadata, file_path: str) -> None:
+        """
+        Normalize paths in metadata object
+        
+        Args:
+            metadata: Metadata object to update
+            file_path: Current file path for the model
+        """
+        # Check if file path is different from what's in metadata
+        if normalize_path(file_path) != metadata.file_path:
+            metadata.file_path = normalize_path(file_path)
+        
+        # Check if preview exists at the current location
+        preview_url = metadata.preview_url
+        if preview_url and not os.path.exists(preview_url):
+            base_name = os.path.splitext(os.path.basename(file_path))[0]
+            dir_path = os.path.dirname(file_path)
+            new_preview_url = find_preview_file(base_name, dir_path)
+            if new_preview_url:
+                metadata.preview_url = normalize_path(new_preview_url)

py/utils/models.py

@@ -1,5 +1,5 @@
-from dataclasses import dataclass, asdict
-from typing import Dict, Optional, List
+from dataclasses import dataclass, asdict, field
+from typing import Dict, Optional, List, Any
 from datetime import datetime
 import os
 from .model_utils import determine_base_model
@@ -24,6 +24,7 @@ class BaseModelMetadata:
     civitai_deleted: bool = False  # Whether deleted from Civitai
     favorite: bool = False      # Whether the model is a favorite
     exclude: bool = False       # Whether to exclude this model from the cache
+    _unknown_fields: Dict[str, Any] = field(default_factory=dict, repr=False, compare=False)  # Store unknown fields
 
     def __post_init__(self):
         # Initialize empty lists to avoid mutable default parameter issue
@@ -34,11 +35,43 @@ class BaseModelMetadata:
     def from_dict(cls, data: Dict) -> 'BaseModelMetadata':
         """Create instance from dictionary"""
         data_copy = data.copy()
-        return cls(**data_copy)
+        
+        # Use cached fields if available, otherwise compute them
+        if not hasattr(cls, '_known_fields_cache'):
+            known_fields = set()
+            for c in cls.mro():
+                if hasattr(c, '__annotations__'):
+                    known_fields.update(c.__annotations__.keys())
+            cls._known_fields_cache = known_fields
+        
+        known_fields = cls._known_fields_cache
+        
+        # Extract fields that match our class attributes
+        fields_to_use = {k: v for k, v in data_copy.items() if k in known_fields}
+        
+        # Store unknown fields separately
+        unknown_fields = {k: v for k, v in data_copy.items() if k not in known_fields and not k.startswith('_')}
+        
+        # Create instance with known fields
+        instance = cls(**fields_to_use)
+        
+        # Add unknown fields as a separate attribute
+        instance._unknown_fields = unknown_fields
+        
+        return instance
 
     def to_dict(self) -> Dict:
         """Convert to dictionary for JSON serialization"""
-        return asdict(self)
+        result = asdict(self)
+        
+        # Remove private fields
+        result = {k: v for k, v in result.items() if not k.startswith('_')}
+        
+        # Add back unknown fields if they exist
+        if hasattr(self, '_unknown_fields'):
+            result.update(self._unknown_fields)
+            
+        return result
 
     @property
     def modified_datetime(self) -> datetime:

py/utils/routes_common.py

@@ -9,6 +9,7 @@ from .constants import PREVIEW_EXTENSIONS, CARD_PREVIEW_WIDTH
 from ..config import config
 from ..services.civitai_client import CivitaiClient
 from ..utils.exif_utils import ExifUtils
+from ..utils.metadata_manager import MetadataManager
 from ..services.download_manager import DownloadManager
 
 logger = logging.getLogger(__name__)
@@ -32,14 +33,29 @@ class ModelRouteUtils:
     async def handle_not_found_on_civitai(metadata_path: str, local_metadata: Dict) -> None:
         """Handle case when model is not found on CivitAI"""
         local_metadata['from_civitai'] = False
-        with open(metadata_path, 'w', encoding='utf-8') as f:
-            json.dump(local_metadata, f, indent=2, ensure_ascii=False)
+        await MetadataManager.save_metadata(metadata_path, local_metadata)
 
     @staticmethod
     async def update_model_metadata(metadata_path: str, local_metadata: Dict, 
                                   civitai_metadata: Dict, client: CivitaiClient) -> None:
         """Update local metadata with CivitAI data"""
-        local_metadata['civitai'] = civitai_metadata
+        # Save existing trainedWords and customImages if they exist
+        existing_civitai = local_metadata.get('civitai') or {}  # Use empty dict if None
+
+        # Create a new civitai metadata by updating existing with new
+        merged_civitai = existing_civitai.copy()
+        merged_civitai.update(civitai_metadata)
+
+        # Special handling for trainedWords - ensure we don't lose any existing trained words
+        if 'trainedWords' in existing_civitai:
+            existing_trained_words = existing_civitai.get('trainedWords', [])
+            new_trained_words = civitai_metadata.get('trainedWords', [])
+            # Use a set to combine words without duplicates, then convert back to list
+            merged_trained_words = list(set(existing_trained_words + new_trained_words))
+            merged_civitai['trainedWords'] = merged_trained_words
+
+        # Update local metadata with merged civitai data
+        local_metadata['civitai'] = merged_civitai
         local_metadata['from_civitai'] = True
         
         # Update model name if available
@@ -138,8 +154,7 @@ class ModelRouteUtils:
                                 local_metadata['preview_nsfw_level'] = first_preview.get('nsfwLevel', 0)
 
         # Save updated metadata
-        with open(metadata_path, 'w', encoding='utf-8') as f:
-            json.dump(local_metadata, f, indent=2, ensure_ascii=False)
+        await MetadataManager.save_metadata(metadata_path, local_metadata)
 
     @staticmethod
     async def fetch_and_update_model(
@@ -177,8 +192,7 @@ class ModelRouteUtils:
                 # Mark as not from CivitAI if not found
                 local_metadata['from_civitai'] = False
                 model_data['from_civitai'] = False
-                with open(metadata_path, 'w', encoding='utf-8') as f:
-                    json.dump(local_metadata, f, indent=2, ensure_ascii=False)
+                await MetadataManager.save_metadata(file_path, local_metadata)
                 return False
 
             # Update metadata
@@ -221,7 +235,7 @@ class ModelRouteUtils:
         fields = [
             "id", "modelId", "name", "createdAt", "updatedAt", 
             "publishedAt", "trainedWords", "baseModel", "description",
-            "model", "images", "creator"
+            "model", "images", "customImages", "creator"
         ]
         return {k: data[k] for k in fields if k in data}
 
@@ -270,10 +284,12 @@ class ModelRouteUtils:
     
     @staticmethod
     def get_multipart_ext(filename):
-        """Get extension that may have multiple parts like .metadata.json"""
+        """Get extension that may have multiple parts like .metadata.json or .metadata.json.bak"""
         parts = filename.split(".")
-        if len(parts) > 2:  # If contains multi-part extension
+        if len(parts) == 3:  # If contains 2-part extension
             return "." + ".".join(parts[-2:])  # Take the last two parts, like ".metadata.json"
+        elif len(parts) >= 4:  # If contains 3-part or more extensions
+            return "." + ".".join(parts[-3:])  # Take the last three parts, like ".metadata.json.bak"
         return os.path.splitext(filename)[1]  # Otherwise take the regular extension, like ".safetensors"
 
     # New common endpoint handlers
@@ -393,6 +409,15 @@ class ModelRouteUtils:
                 raise ValueError("Expected 'model_path' field")
             model_path = (await field.read()).decode()
             
+            # Read NSFW level (new parameter)
+            nsfw_level = 0  # Default to 0 (unknown)
+            field = await reader.next()
+            if field and field.name == 'nsfw_level':
+                try:
+                    nsfw_level = int((await field.read()).decode())
+                except (ValueError, TypeError):
+                    logger.warning("Invalid NSFW level format, using default 0")
+            
             # Save preview file
             base_name = os.path.splitext(os.path.basename(model_path))[0]
             folder = os.path.dirname(model_path)
@@ -413,33 +438,43 @@ class ModelRouteUtils:
                 )
                 extension = '.webp'  # Use .webp without .preview part
             
+            # Delete any existing preview files for this model
+            for ext in PREVIEW_EXTENSIONS:
+                existing_preview = os.path.join(folder, base_name + ext)
+                if os.path.exists(existing_preview):
+                    try:
+                        os.remove(existing_preview)
+                        logger.debug(f"Deleted existing preview: {existing_preview}")
+                    except Exception as e:
+                        logger.warning(f"Failed to delete existing preview {existing_preview}: {e}")
+            
             preview_path = os.path.join(folder, base_name + extension).replace(os.sep, '/')
             
             with open(preview_path, 'wb') as f:
                 f.write(optimized_data)
             
-            # Update preview path in metadata
+            # Update preview path and NSFW level in metadata
             metadata_path = os.path.splitext(model_path)[0] + '.metadata.json'
             if os.path.exists(metadata_path):
                 try:
                     with open(metadata_path, 'r', encoding='utf-8') as f:
                         metadata = json.load(f)
                     
-                    # Update preview_url directly in the metadata dict
+                    # Update preview_url and preview_nsfw_level in the metadata dict
                     metadata['preview_url'] = preview_path
+                    metadata['preview_nsfw_level'] = nsfw_level
                     
-                    with open(metadata_path, 'w', encoding='utf-8') as f:
-                        json.dump(metadata, f, indent=2, ensure_ascii=False)
+                    await MetadataManager.save_metadata(model_path, metadata)
                 except Exception as e:
                     logger.error(f"Error updating metadata: {e}")
             
             # Update preview URL in scanner cache
-            if hasattr(scanner, 'update_preview_in_cache'):
-                await scanner.update_preview_in_cache(model_path, preview_path)
+            await scanner.update_preview_in_cache(model_path, preview_path, nsfw_level)
             
             return web.json_response({
                 "success": True,
-                "preview_url": config.get_preview_static_url(preview_path)
+                "preview_url": config.get_preview_static_url(preview_path),
+                "preview_nsfw_level": nsfw_level
             })
             
         except Exception as e:
@@ -469,8 +504,7 @@ class ModelRouteUtils:
             metadata['exclude'] = True
             
             # Save updated metadata
-            with open(metadata_path, 'w', encoding='utf-8') as f:
-                json.dump(metadata, f, indent=2, ensure_ascii=False)
+            await MetadataManager.save_metadata(file_path, metadata)
 
             # Update cache
             cache = await scanner.get_cached_data()
@@ -759,8 +793,7 @@ class ModelRouteUtils:
                         metadata['sha256'] = actual_hash
                         
                         # Save updated metadata
-                        with open(metadata_path, 'w', encoding='utf-8') as f:
-                            json.dump(metadata, f, indent=2, ensure_ascii=False)
+                        await MetadataManager.save_metadata(file_path, metadata)
                         
                         # Update cache
                         await scanner.update_single_model_cache(file_path, file_path, metadata)

static/css/components/card.css

@@ -520,4 +520,44 @@
     .card-grid.virtual-scroll {
         max-width: 2400px;
     }
-}
+}
+
+/* Add after the existing .lora-card:hover styles */
+
+@keyframes update-pulse {
+    0% { box-shadow: 0 0 0 0 var(--lora-accent-transparent); }
+    50% { box-shadow: 0 0 0 4px var(--lora-accent-transparent); }
+    100% { box-shadow: 0 0 0 0 var(--lora-accent-transparent); }
+  }
+  
+  /* Add semi-transparent version of accent color for animation */
+  :root {
+    --lora-accent-transparent: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.6);
+  }
+  
+  .lora-card.updated {
+    animation: update-pulse 1.2s ease-out;
+  }
+  
+  /* Add a subtle updated tag that fades in and out */
+  .update-indicator {
+    position: absolute;
+    top: 8px;
+    right: 8px;
+    background: var(--lora-accent);
+    color: white;
+    border-radius: var(--border-radius-xs);
+    padding: 3px 6px;
+    font-size: 0.75em;
+    opacity: 0;
+    transform: translateY(-5px);
+    z-index: 4;
+    animation: update-tag 1.8s ease-out forwards;
+  }
+  
+  @keyframes update-tag {
+    0% { opacity: 0; transform: translateY(-5px); }
+    15% { opacity: 1; transform: translateY(0); }
+    85% { opacity: 1; transform: translateY(0); }
+    100% { opacity: 0; transform: translateY(0); }
+  }

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

@@ -79,14 +79,109 @@
 /* Position the toggle button at the top left of showcase media */
 .showcase-toggle-btn {
   position: absolute;
-  left: var(--space-1);
-  top: var(--space-1);
   z-index: 3;
 }
 
-/* Make sure media wrapper maintains position: relative for absolute positioning of children */
-.carousel .media-wrapper {
+/* Add styles for showcase media controls */
+.media-controls {
+  position: absolute;
+  display: flex;
+  gap: 6px;
+  z-index: 4;
+  opacity: 0;
+  transform: translateY(-5px);
+  transition: opacity 0.2s ease, transform 0.2s ease;
+  pointer-events: none;
+}
+
+.media-controls.visible {
+  opacity: 1;
+  transform: translateY(0);
+  pointer-events: auto;
+}
+
+.media-control-btn {
+  width: 28px;
+  height: 28px;
+  border-radius: 50%;
+  background: var(--bg-color);
+  border: 1px solid var(--border-color);
+  color: var(--text-color);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  cursor: pointer;
+  transition: all 0.2s ease;
+  box-shadow: 0 2px 5px rgba(0, 0, 0, 0.15);
+  padding: 0;
   position: relative;
+  overflow: hidden;
+}
+
+.media-control-btn:hover {
+  transform: translateY(-2px);
+  box-shadow: 0 3px 7px rgba(0, 0, 0, 0.2);
+}
+
+.media-control-btn.set-preview-btn:hover {
+  background: var(--lora-accent);
+  color: white;
+  border-color: var(--lora-accent);
+}
+
+.media-control-btn.example-delete-btn:hover:not(.disabled) {
+  background: var(--lora-error);
+  color: white;
+  border-color: var(--lora-error);
+}
+
+/* Disabled state for delete button */
+.media-control-btn.example-delete-btn.disabled {
+  opacity: 0.5;
+  cursor: not-allowed;
+}
+
+/* Two-step confirmation for delete button */
+.media-control-btn.example-delete-btn .confirm-icon {
+  position: absolute;
+  top: 0;
+  left: 0;
+  right: 0;
+  bottom: 0;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  background: var(--lora-error);
+  color: white;
+  font-size: 1em;
+  opacity: 0;
+  transition: opacity 0.2s ease;
+}
+
+.media-control-btn.example-delete-btn.confirm .fa-trash-alt {
+  opacity: 0;
+}
+
+.media-control-btn.example-delete-btn.confirm .confirm-icon {
+  opacity: 1;
+}
+
+.media-control-btn.example-delete-btn.confirm {
+  background: var(--lora-error);
+  color: white;
+  border-color: var(--lora-error);
+}
+
+@keyframes pulse {
+  0% {
+    box-shadow: 0 0 0 0 rgba(220, 53, 69, 0.7);
+  }
+  70% {
+    box-shadow: 0 0 0 5px rgba(220, 53, 69, 0);
+  }
+  100% {
+    box-shadow: 0 0 0 0 rgba(220, 53, 69, 0);
+  }
 }
 
 /* Image Metadata Panel Styles */
@@ -289,4 +384,95 @@
 
 .lazy[src] {
   opacity: 1;
+}
+
+/* Example Import Area */
+.example-import-area {
+  margin-top: var(--space-4);
+  padding: var(--space-2);
+}
+
+.example-import-area.empty {
+  margin-top: var(--space-2);
+  padding: var(--space-4) var(--space-2);
+}
+
+.import-container {
+  border: 2px dashed var(--border-color);
+  border-radius: var(--border-radius-sm);
+  padding: var(--space-4);
+  text-align: center;
+  transition: all 0.3s ease;
+  background: var(--lora-surface);
+  cursor: pointer;
+}
+
+.import-container.highlight {
+  border-color: var(--lora-accent);
+  background: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.1);
+  transform: scale(1.01);
+}
+
+.import-placeholder {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  gap: var(--space-1);
+  padding-top: var(--space-1);
+}
+
+.import-placeholder i {
+  font-size: 2.5rem;
+  /* color: var(--lora-accent); */
+  opacity: 0.8;
+  margin-bottom: var(--space-1);
+}
+
+.import-placeholder h3 {
+  margin: 0 0 var(--space-1);
+  font-size: 1.2rem;
+  font-weight: 500;
+  color: var(--text-color);
+}
+
+.import-placeholder p {
+  margin: var(--space-1) 0;
+  color: var(--text-color);
+  opacity: 0.8;
+}
+
+.import-placeholder .sub-text {
+  font-size: 0.9em;
+  opacity: 0.6;
+  margin: var(--space-1) 0;
+}
+
+.import-formats {
+  font-size: 0.8em !important;
+  opacity: 0.6 !important;
+  margin-top: var(--space-2) !important;
+}
+
+.select-files-btn {
+  background: var(--lora-accent);
+  color: var(--lora-text);
+  border: none;
+  border-radius: var(--border-radius-xs);
+  padding: var(--space-2) var(--space-3);
+  cursor: pointer;
+  font-size: 0.9em;
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  transition: all 0.2s;
+}
+
+.select-files-btn:hover {
+  opacity: 0.9;
+  transform: translateY(-1px);
+}
+
+/* For dark theme */
+[data-theme="dark"] .import-container {
+  background: rgba(255, 255, 255, 0.03);
 }

static/css/components/modal.css

@@ -306,18 +306,6 @@ body.modal-open {
     width: 100%; /* Full width */
 }
 
-/* Migrate control styling */
-.migrate-control {
-    display: flex;
-    align-items: center;
-    gap: 8px;
-}
-
-.migrate-control input {
-    flex: 1;
-    min-width: 0;
-}
-
 /* 统一各个 section 的样式 */
 .support-section,
 .changelog-section,
@@ -375,12 +363,6 @@ body.modal-open {
     background: rgba(255, 255, 255, 0.05);
 }
 
-/* Add disabled style for setting items */
-.setting-item[data-requires-centralized="true"].disabled {
-    opacity: 0.6;
-    pointer-events: none;
-}
-
 /* Control row with label and input together */
 .setting-row {
     display: flex;
@@ -1026,4 +1008,77 @@ input:checked + .toggle-slider:before {
 /* Dark theme adjustments */
 [data-theme="dark"] .video-container {
   background-color: rgba(255, 255, 255, 0.03);
+}
+
+/* Example Access Modal */
+.example-access-modal {
+    max-width: 550px;
+    text-align: center;
+}
+
+.example-access-options {
+    display: flex;
+    flex-direction: column;
+    gap: var(--space-2);
+    margin: var(--space-3) 0;
+}
+
+.example-option-btn {
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    padding: var(--space-2);
+    border-radius: var(--border-radius-sm);
+    border: 1px solid var(--lora-border);
+    background-color: var(--lora-surface);
+    cursor: pointer;
+    transition: all 0.2s;
+}
+
+.example-option-btn:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    border-color: var(--lora-accent);
+}
+
+.example-option-btn i {
+    font-size: 2em;
+    margin-bottom: var(--space-1);
+    color: var(--lora-accent);
+}
+
+.option-title {
+    font-weight: 500;
+    margin-bottom: 4px;
+    font-size: 1.1em;
+}
+
+.option-desc {
+    font-size: 0.9em;
+    opacity: 0.8;
+}
+
+.example-option-btn.disabled {
+    opacity: 0.5;
+    cursor: not-allowed;
+}
+
+.example-option-btn.disabled i {
+    color: var(--text-color);
+    opacity: 0.5;
+}
+
+.modal-footer-note {
+    font-size: 0.9em;
+    opacity: 0.7;
+    margin-top: var(--space-2);
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    gap: 8px;
+}
+
+/* Dark theme adjustments */
+[data-theme="dark"] .example-option-btn:hover {
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.25);
 }

static/js/api/baseModelApi.js

@@ -542,23 +542,17 @@ export async function excludeModel(filePath, modelType = 'lora') {
     }
 }
 
-// Private methods
-
 // Upload a preview image
-async function uploadPreview(filePath, file, modelType = 'lora') {
-    const loadingOverlay = document.getElementById('loading-overlay');
-    const loadingStatus = document.querySelector('.loading-status');
-    
+export async function uploadPreview(filePath, file, modelType = 'lora', nsfwLevel = 0) {
     try {
-        if (loadingOverlay) loadingOverlay.style.display = 'flex';
-        if (loadingStatus) loadingStatus.textContent = 'Uploading preview...';
+        state.loadingManager.showSimpleLoading('Uploading preview...');
         
         const formData = new FormData();
         
-        // Use appropriate parameter names and endpoint based on model type
         // Prepare common form data
         formData.append('preview_file', file);
         formData.append('model_path', filePath);
+        formData.append('nsfw_level', nsfwLevel.toString());  // Add nsfw_level parameter
 
         // Set endpoint based on model type
         const endpoint = modelType === 'checkpoint' 
@@ -575,56 +569,39 @@ async function uploadPreview(filePath, file, modelType = 'lora') {
         }
 
         const data = await response.json();
+
+        // Get the current page's previewVersions Map based on model type
+        const pageType = modelType === 'checkpoint' ? 'checkpoints' : 'loras';
+        const previewVersions = state.pages[pageType].previewVersions;
         
-        // Update the card preview in UI
-        const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-        if (card) {
-            const previewContainer = card.querySelector('.card-preview');
-            const oldPreview = previewContainer.querySelector('img, video');
+        // Update the version timestamp
+        const timestamp = Date.now();
+        if (previewVersions) {
+            previewVersions.set(filePath, timestamp);
             
-            // Get the current page's previewVersions Map based on model type
-            const pageType = modelType === 'checkpoint' ? 'checkpoints' : 'loras';
-            const previewVersions = state.pages[pageType].previewVersions;
-            
-            // Update the version timestamp
-            const timestamp = Date.now();
-            if (previewVersions) {
-                previewVersions.set(filePath, timestamp);
-                
-                // Save the updated Map to localStorage
-                const storageKey = modelType === 'checkpoint' ? 'checkpoint_preview_versions' : 'lora_preview_versions';
-                saveMapToStorage(storageKey, previewVersions);
-            }
-            
-            const previewUrl = data.preview_url ? 
-                `${data.preview_url}?t=${timestamp}` : 
-                `/api/model/preview_image?path=${encodeURIComponent(filePath)}&t=${timestamp}`;
-            
-            // Create appropriate element based on file type
-            if (file.type.startsWith('video/')) {
-                const video = document.createElement('video');
-                video.controls = true;
-                video.autoplay = true;
-                video.muted = true;
-                video.loop = true;
-                video.src = previewUrl;
-                oldPreview.replaceWith(video);
-            } else {
-                const img = document.createElement('img');
-                img.src = previewUrl;
-                oldPreview.replaceWith(img);
-            }
-            
-            showToast('Preview updated successfully', 'success');
+            // Save the updated Map to localStorage
+            const storageKey = modelType === 'checkpoint' ? 'checkpoint_preview_versions' : 'lora_preview_versions';
+            saveMapToStorage(storageKey, previewVersions);
         }
+
+        const updateData = {
+            preview_url: data.preview_url,
+            preview_nsfw_level: data.preview_nsfw_level // Include nsfw level in update data
+        };
+
+        state.virtualScroller.updateSingleItem(filePath, updateData);
+
+        showToast('Preview updated successfully', 'success');
     } catch (error) {
         console.error('Error uploading preview:', error);
         showToast('Failed to upload preview image', 'error');
     } finally {
-        if (loadingOverlay) loadingOverlay.style.display = 'none';
+        state.loadingManager.hide();
     }
 }
 
+// Private methods
+
 // Private function to perform the delete operation
 async function performDelete(filePath, modelType = 'lora') {
     try {

static/js/api/checkpointApi.js

@@ -109,6 +109,9 @@ export async function saveModelMetadata(filePath, data) {
         if (!response.ok) {
             throw new Error('Failed to save metadata');
         }
+
+        // Update the virtual scroller with the new metadata
+        state.virtualScroller.updateSingleItem(filePath, data);
         
         return response.json();
     } finally {

static/js/api/loraApi.js

@@ -36,6 +36,9 @@ export async function saveModelMetadata(filePath, data) {
         if (!response.ok) {
             throw new Error('Failed to save metadata');
         }
+
+        // Update the virtual scroller with the new data
+        state.virtualScroller.updateSingleItem(filePath, data);
         
         return response.json();
     } finally {

static/js/components/CheckpointCard.js

@@ -219,18 +219,9 @@ export function createCheckpointCard(checkpoint) {
                 favorite: newFavoriteState 
             });
 
-            // Update the UI
             if (newFavoriteState) {
-                starIcon.classList.remove('far');
-                starIcon.classList.add('fas', 'favorite-active');
-                starIcon.title = 'Remove from favorites';
-                card.dataset.favorite = 'true';
                 showToast('Added to favorites', 'success');
             } else {
-                starIcon.classList.remove('fas', 'favorite-active');
-                starIcon.classList.add('far');
-                starIcon.title = 'Add to favorites';
-                card.dataset.favorite = 'false';
                 showToast('Removed from favorites', 'success');
             }
         } catch (error) {

static/js/components/ContextMenu/CheckpointContextMenu.js

@@ -3,7 +3,6 @@ import { ModelContextMenuMixin } from './ModelContextMenuMixin.js';
 import { refreshSingleCheckpointMetadata, saveModelMetadata, replaceCheckpointPreview, resetAndReload } from '../../api/checkpointApi.js';
 import { showToast } from '../../utils/uiHelpers.js';
 import { showExcludeModal } from '../../utils/modalUtils.js';
-import { state } from '../../state/index.js';
 
 export class CheckpointContextMenu extends BaseContextMenu {
     constructor() {

static/js/components/ContextMenu/LoraContextMenu.js

@@ -1,7 +1,7 @@
 import { BaseContextMenu } from './BaseContextMenu.js';
 import { ModelContextMenuMixin } from './ModelContextMenuMixin.js';
 import { refreshSingleLoraMetadata, saveModelMetadata, replacePreview, resetAndReload } from '../../api/loraApi.js';
-import { showToast, copyToClipboard, sendLoraToWorkflow } from '../../utils/uiHelpers.js';
+import { copyToClipboard, sendLoraToWorkflow } from '../../utils/uiHelpers.js';
 import { showExcludeModal, showDeleteModal } from '../../utils/modalUtils.js';
 
 export class LoraContextMenu extends BaseContextMenu {

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -26,24 +26,6 @@ export const ModelContextMenuMixin = {
                 try {
                     await this.saveModelMetadata(filePath, { preview_nsfw_level: level });
                     
-                    // Update card data
-                    const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-                    if (card) {
-                        let metaData = {};
-                        try {
-                            metaData = JSON.parse(card.dataset.meta || '{}');
-                        } catch (err) {
-                            console.error('Error parsing metadata:', err);
-                        }
-                        
-                        metaData.preview_nsfw_level = level;
-                        card.dataset.meta = JSON.stringify(metaData);
-                        card.dataset.nsfwLevel = level.toString();
-                        
-                        // Apply blur effect immediately
-                        this.updateCardBlurEffect(card, level);
-                    }
-                    
                     showToast(`Content rating set to ${getNSFWLevelName(level)}`, 'success');
                     this.nsfwSelector.style.display = 'none';
                 } catch (error) {

static/js/components/LoraCard.js

@@ -70,7 +70,7 @@ function handleLoraCardEvent(event) {
     
     if (event.target.closest('.fa-folder-open')) {
         event.stopPropagation();
-        openExampleImagesFolder(card.dataset.sha256);
+        handleExampleImagesAccess(card);
         return;
     }
     
@@ -162,18 +162,9 @@ async function toggleFavorite(card) {
             favorite: newFavoriteState 
         });
 
-        // Update the UI
         if (newFavoriteState) {
-            starIcon.classList.remove('far');
-            starIcon.classList.add('fas', 'favorite-active');
-            starIcon.title = 'Remove from favorites';
-            card.dataset.favorite = 'true';
             showToast('Added to favorites', 'success');
         } else {
-            starIcon.classList.remove('fas', 'favorite-active');
-            starIcon.classList.add('far');
-            starIcon.title = 'Add to favorites';
-            card.dataset.favorite = 'false';
             showToast('Removed from favorites', 'success');
         }
     } catch (error) {
@@ -200,6 +191,142 @@ function copyLoraSyntax(card) {
     copyToClipboard(loraSyntax, 'LoRA syntax copied to clipboard');
 }
 
+// New function to handle example images access
+async function handleExampleImagesAccess(card) {
+    const modelHash = card.dataset.sha256;
+    
+    try {
+        // Check if example images exist
+        const response = await fetch(`/api/has-example-images?model_hash=${modelHash}`);
+        const data = await response.json();
+        
+        if (data.has_images) {
+            // If images exist, open the folder directly (existing behavior)
+            openExampleImagesFolder(modelHash);
+        } else {
+            // If no images exist, show the new modal
+            showExampleAccessModal(card);
+        }
+    } catch (error) {
+        console.error('Error checking for example images:', error);
+        showToast('Error checking for example images', 'error');
+    }
+}
+
+// Function to show the example access modal
+function showExampleAccessModal(card) {
+    const modal = document.getElementById('exampleAccessModal');
+    if (!modal) return;
+    
+    // Get download button and determine if download should be enabled
+    const downloadBtn = modal.querySelector('#downloadExamplesBtn');
+    let hasRemoteExamples = false;
+    
+    try {
+        const metaData = JSON.parse(card.dataset.meta || '{}');
+        hasRemoteExamples = metaData.images && 
+                            Array.isArray(metaData.images) && 
+                            metaData.images.length > 0 && 
+                            metaData.images[0].url;
+    } catch (e) {
+        console.error('Error parsing meta data:', e);
+    }
+    
+    // Enable or disable download button
+    if (downloadBtn) {
+        if (hasRemoteExamples) {
+            downloadBtn.classList.remove('disabled');
+            downloadBtn.removeAttribute('title'); // Remove any previous tooltip
+            downloadBtn.onclick = () => {
+                modalManager.closeModal('exampleAccessModal');
+                // Open settings modal and scroll to example images section
+                const settingsModal = document.getElementById('settingsModal');
+                if (settingsModal) {
+                    modalManager.showModal('settingsModal');
+                    // Scroll to example images section after modal is visible
+                    setTimeout(() => {
+                        const exampleSection = settingsModal.querySelector('.settings-section:nth-child(5)'); // Example Images section
+                        if (exampleSection) {
+                            exampleSection.scrollIntoView({ behavior: 'smooth' });
+                        }
+                    }, 300);
+                }
+            };
+        } else {
+            downloadBtn.classList.add('disabled');
+            downloadBtn.setAttribute('title', 'No remote example images available for this model on Civitai');
+            downloadBtn.onclick = null;
+        }
+    }
+    
+    // Set up import button
+    const importBtn = modal.querySelector('#importExamplesBtn');
+    if (importBtn) {
+        importBtn.onclick = () => {
+            modalManager.closeModal('exampleAccessModal');
+            
+            // Get the lora data from card dataset
+            const loraMeta = {
+                sha256: card.dataset.sha256,
+                file_path: card.dataset.filepath,
+                model_name: card.dataset.name,
+                file_name: card.dataset.file_name,
+                // Other properties needed for showLoraModal
+                folder: card.dataset.folder,
+                modified: card.dataset.modified,
+                file_size: card.dataset.file_size,
+                from_civitai: card.dataset.from_civitai === 'true',
+                base_model: card.dataset.base_model,
+                usage_tips: card.dataset.usage_tips,
+                notes: card.dataset.notes,
+                favorite: card.dataset.favorite === 'true',
+                civitai: (() => {
+                    try {
+                        return JSON.parse(card.dataset.meta || '{}');
+                    } catch (e) {
+                        return {};
+                    }
+                })(),
+                tags: JSON.parse(card.dataset.tags || '[]'),
+                modelDescription: card.dataset.modelDescription || ''
+            };
+            
+            // Show the lora modal
+            showLoraModal(loraMeta);
+            
+            // Scroll to import area after modal is visible
+            setTimeout(() => {
+                const importArea = document.querySelector('.example-import-area');
+                if (importArea) {
+                    const showcaseTab = document.getElementById('showcase-tab');
+                    if (showcaseTab) {
+                        // First make sure showcase tab is visible
+                        const tabBtn = document.querySelector('.tab-btn[data-tab="showcase"]');
+                        if (tabBtn && !tabBtn.classList.contains('active')) {
+                            tabBtn.click();
+                        }
+                        
+                        // Then toggle showcase if collapsed
+                        const carousel = showcaseTab.querySelector('.carousel');
+                        if (carousel && carousel.classList.contains('collapsed')) {
+                            const scrollIndicator = showcaseTab.querySelector('.scroll-indicator');
+                            if (scrollIndicator) {
+                                scrollIndicator.click();
+                            }
+                        }
+                        
+                        // Finally scroll to the import area
+                        importArea.scrollIntoView({ behavior: 'smooth' });
+                    }
+                }
+            }, 500);
+        };
+    }
+    
+    // Show the modal
+    modalManager.showModal('exampleAccessModal');
+}
+
 export function createLoraCard(lora) {
     const card = document.createElement('div');
     card.className = 'lora-card';

static/js/components/checkpointModal/ModelMetadata.js

@@ -114,16 +114,6 @@ export function setupModelNameEditing(filePath) {
             
             await saveModelMetadata(filePath, { model_name: newModelName });
             
-            // Update the corresponding checkpoint card's dataset and display
-            updateModelCard(filePath, { model_name: newModelName });
-            
-            // BUGFIX: Directly update the card's dataset.name attribute to ensure
-            // it's correctly read when reopening the modal
-            const checkpointCard = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-            if (checkpointCard) {
-                checkpointCard.dataset.name = newModelName;
-            }
-            
             showToast('Model name updated successfully', 'success');
         } catch (error) {
             console.error('Error updating model name:', error);
@@ -300,9 +290,6 @@ async function saveBaseModel(filePath, originalValue) {
     try {
         await saveModelMetadata(filePath, { base_model: newBaseModel });
         
-        // Update the card with the new base model
-        updateModelCard(filePath, { base_model: newBaseModel });
-        
         showToast('Base model updated successfully', 'success');
     } catch (error) {
         showToast('Failed to update base model', 'error');

static/js/components/checkpointModal/ModelTags.js

@@ -463,12 +463,6 @@ async function saveTags() {
         // Exit edit mode
         editBtn.click();
         
-        // Update the checkpoint card's dataset
-        const checkpointCard = document.querySelector(`.checkpoint-card[data-filepath="${filePath}"]`);
-        if (checkpointCard) {
-            checkpointCard.dataset.tags = JSON.stringify(tags);
-        }
-        
         showToast('Tags updated successfully', 'success');
     } catch (error) {
         console.error('Error saving tags:', error);

static/js/components/checkpointModal/ShowcaseView.js

@@ -1,346 +0,0 @@
-/**
- * ShowcaseView.js
- * Handles showcase content (images, videos) display for checkpoint modal
- */
-import { 
-    toggleShowcase,
-    setupShowcaseScroll,
-    scrollToTop 
-} from '../../utils/uiHelpers.js';
-import { state } from '../../state/index.js';
-import { NSFW_LEVELS } from '../../utils/constants.js';
-
-/**
- * Render showcase content
- * @param {Array} images - Array of images/videos to show
- * @param {string} modelHash - Model hash for identifying local files
- * @param {Array} exampleFiles - Local example files already fetched
- * @returns {string} HTML content
- */
-export function renderShowcaseContent(images, exampleFiles = []) {
-    if (!images?.length) return '<div class="no-examples">No example images available</div>';
-    
-    // Filter images based on SFW setting
-    const showOnlySFW = state.settings.show_only_sfw;
-    let filteredImages = images;
-    let hiddenCount = 0;
-    
-    if (showOnlySFW) {
-        filteredImages = images.filter(img => {
-            const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
-            const isSfw = nsfwLevel < NSFW_LEVELS.R;
-            if (!isSfw) hiddenCount++;
-            return isSfw;
-        });
-    }
-    
-    // Show message if no images are available after filtering
-    if (filteredImages.length === 0) {
-        return `
-            <div class="no-examples">
-                <p>All example images are filtered due to NSFW content settings</p>
-                <p class="nsfw-filter-info">Your settings are currently set to show only safe-for-work content</p>
-                <p>You can change this in Settings <i class="fas fa-cog"></i></p>
-            </div>
-        `;
-    }
-    
-    // Show hidden content notification if applicable
-    const hiddenNotification = hiddenCount > 0 ? 
-        `<div class="nsfw-filter-notification">
-            <i class="fas fa-eye-slash"></i> ${hiddenCount} ${hiddenCount === 1 ? 'image' : 'images'} hidden due to SFW-only setting
-        </div>` : '';
-    
-    return `
-        <div class="scroll-indicator" onclick="toggleShowcase(this)">
-            <i class="fas fa-chevron-down"></i>
-            <span>Scroll or click to show ${filteredImages.length} examples</span>
-        </div>
-        <div class="carousel collapsed">
-            ${hiddenNotification}
-            <div class="carousel-container">
-                ${filteredImages.map((img, index) => {
-                    // Find matching file in our list of actual files
-                    let localFile = null;
-                    if (exampleFiles.length > 0) {
-                        // Try to find the corresponding file by index first
-                        localFile = exampleFiles.find(file => {
-                            const match = file.name.match(/image_(\d+)\./);
-                            return match && parseInt(match[1]) === index;
-                        });
-                        
-                        // If not found by index, just use the same position in the array if available
-                        if (!localFile && index < exampleFiles.length) {
-                            localFile = exampleFiles[index];
-                        }
-                    }
-                    
-                    const remoteUrl = img.url || '';
-                    const localUrl = localFile ? localFile.path : '';
-                    const isVideo = localFile ? localFile.is_video : 
-                                   remoteUrl.endsWith('.mp4') || remoteUrl.endsWith('.webm');
-                    
-                    // Calculate appropriate aspect ratio
-                    const aspectRatio = (img.height / img.width) * 100;
-                    const containerWidth = 800; // modal content maximum width
-                    const minHeightPercent = 40; 
-                    const maxHeightPercent = (window.innerHeight * 0.6 / containerWidth) * 100;
-                    const heightPercent = Math.max(
-                        minHeightPercent,
-                        Math.min(maxHeightPercent, aspectRatio)
-                    );
-                    
-                    // Check if media should be blurred
-                    const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
-                    const shouldBlur = state.settings.blurMatureContent && nsfwLevel > NSFW_LEVELS.PG13;
-                    
-                    // Determine NSFW warning text based on level
-                    let nsfwText = "Mature Content";
-                    if (nsfwLevel >= NSFW_LEVELS.XXX) {
-                        nsfwText = "XXX-rated Content";
-                    } else if (nsfwLevel >= NSFW_LEVELS.X) {
-                        nsfwText = "X-rated Content";
-                    } else if (nsfwLevel >= NSFW_LEVELS.R) {
-                        nsfwText = "R-rated Content";
-                    }
-                    
-                    // Extract metadata from the image
-                    const meta = img.meta || {};
-                    const prompt = meta.prompt || '';
-                    const negativePrompt = meta.negative_prompt || meta.negativePrompt || '';
-                    const size = meta.Size || `${img.width}x${img.height}`;
-                    const seed = meta.seed || '';
-                    const model = meta.Model || '';
-                    const steps = meta.steps || '';
-                    const sampler = meta.sampler || '';
-                    const cfgScale = meta.cfgScale || '';
-                    const clipSkip = meta.clipSkip || '';
-                    
-                    // Check if we have any meaningful generation parameters
-                    const hasParams = seed || model || steps || sampler || cfgScale || clipSkip;
-                    const hasPrompts = prompt || negativePrompt;
-                    
-                    // Create metadata panel content
-                    const metadataPanel = generateMetadataPanel(
-                        hasParams, hasPrompts, 
-                        prompt, negativePrompt, 
-                        size, seed, model, steps, sampler, cfgScale, clipSkip
-                    );
-                    
-                    // Check if this is a video or image
-                    if (isVideo) {
-                        return generateVideoWrapper(
-                            img, heightPercent, shouldBlur, nsfwText, metadataPanel,
-                            localUrl, remoteUrl
-                        );
-                    }
-                    
-                    return generateImageWrapper(
-                        img, heightPercent, shouldBlur, nsfwText, metadataPanel,
-                        localUrl, remoteUrl
-                    );
-                }).join('')}
-            </div>
-        </div>
-    `;
-}
-
-/**
- * Generate media wrapper HTML for an image or video
- * @param {Object} media - Media object with image or video data
- * @returns {string} HTML content
- */
-function generateMediaWrapper(media, urls) {
-    // Calculate appropriate aspect ratio
-    const aspectRatio = (media.height / media.width) * 100;
-    const containerWidth = 800; // modal content maximum width
-    const minHeightPercent = 40; 
-    const maxHeightPercent = (window.innerHeight * 0.6 / containerWidth) * 100;
-    const heightPercent = Math.max(
-        minHeightPercent,
-        Math.min(maxHeightPercent, aspectRatio)
-    );
-    
-    // Check if media should be blurred
-    const nsfwLevel = media.nsfwLevel !== undefined ? media.nsfwLevel : 0;
-    const shouldBlur = state.settings.blurMatureContent && nsfwLevel > NSFW_LEVELS.PG13;
-    
-    // Determine NSFW warning text based on level
-    let nsfwText = "Mature Content";
-    if (nsfwLevel >= NSFW_LEVELS.XXX) {
-        nsfwText = "XXX-rated Content";
-    } else if (nsfwLevel >= NSFW_LEVELS.X) {
-        nsfwText = "X-rated Content";
-    } else if (nsfwLevel >= NSFW_LEVELS.R) {
-        nsfwText = "R-rated Content";
-    }
-    
-    // Extract metadata from the media
-    const meta = media.meta || {};
-    const prompt = meta.prompt || '';
-    const negativePrompt = meta.negative_prompt || meta.negativePrompt || '';
-    const size = meta.Size || `${media.width}x${media.height}`;
-    const seed = meta.seed || '';
-    const model = meta.Model || '';
-    const steps = meta.steps || '';
-    const sampler = meta.sampler || '';
-    const cfgScale = meta.cfgScale || '';
-    const clipSkip = meta.clipSkip || '';
-    
-    // Check if we have any meaningful generation parameters
-    const hasParams = seed || model || steps || sampler || cfgScale || clipSkip;
-    const hasPrompts = prompt || negativePrompt;
-    
-    // Create metadata panel content
-    const metadataPanel = generateMetadataPanel(
-        hasParams, hasPrompts, 
-        prompt, negativePrompt, 
-        size, seed, model, steps, sampler, cfgScale, clipSkip
-    );
-    
-    // Check if this is a video or image
-    if (media.type === 'video') {
-        return generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, urls);
-    }
-    
-    return generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, urls);
-}
-
-/**
- * Generate metadata panel HTML
- */
-function generateMetadataPanel(hasParams, hasPrompts, prompt, negativePrompt, size, seed, model, steps, sampler, cfgScale, clipSkip) {
-    // Create unique IDs for prompt copying
-    const promptIndex = Math.random().toString(36).substring(2, 15);
-    const negPromptIndex = Math.random().toString(36).substring(2, 15);
-    
-    let content = '<div class="image-metadata-panel"><div class="metadata-content">';
-    
-    if (hasParams) {
-        content += `
-            <div class="params-tags">
-                ${size ? `<div class="param-tag"><span class="param-name">Size:</span><span class="param-value">${size}</span></div>` : ''}
-                ${seed ? `<div class="param-tag"><span class="param-name">Seed:</span><span class="param-value">${seed}</span></div>` : ''}
-                ${model ? `<div class="param-tag"><span class="param-name">Model:</span><span class="param-value">${model}</span></div>` : ''}
-                ${steps ? `<div class="param-tag"><span class="param-name">Steps:</span><span class="param-value">${steps}</span></div>` : ''}
-                ${sampler ? `<div class="param-tag"><span class="param-name">Sampler:</span><span class="param-value">${sampler}</span></div>` : ''}
-                ${cfgScale ? `<div class="param-tag"><span class="param-name">CFG:</span><span class="param-value">${cfgScale}</span></div>` : ''}
-                ${clipSkip ? `<div class="param-tag"><span class="param-name">Clip Skip:</span><span class="param-value">${clipSkip}</span></div>` : ''}
-            </div>
-        `;
-    }
-    
-    if (!hasParams && !hasPrompts) {
-        content += `
-            <div class="no-metadata-message">
-                <i class="fas fa-info-circle"></i>
-                <span>No generation parameters available</span>
-            </div>
-        `;
-    }
-    
-    if (prompt) {
-        content += `
-            <div class="metadata-row prompt-row">
-                <span class="metadata-label">Prompt:</span>
-                <div class="metadata-prompt-wrapper">
-                    <div class="metadata-prompt">${prompt}</div>
-                    <button class="copy-prompt-btn" data-prompt-index="${promptIndex}">
-                        <i class="fas fa-copy"></i>
-                    </button>
-                </div>
-            </div>
-            <div class="hidden-prompt" id="prompt-${promptIndex}" style="display:none;">${prompt}</div>
-        `;
-    }
-    
-    if (negativePrompt) {
-        content += `
-            <div class="metadata-row prompt-row">
-                <span class="metadata-label">Negative Prompt:</span>
-                <div class="metadata-prompt-wrapper">
-                    <div class="metadata-prompt">${negativePrompt}</div>
-                    <button class="copy-prompt-btn" data-prompt-index="${negPromptIndex}">
-                        <i class="fas fa-copy"></i>
-                    </button>
-                </div>
-            </div>
-            <div class="hidden-prompt" id="prompt-${negPromptIndex}" style="display:none;">${negativePrompt}</div>
-        `;
-    }
-    
-    content += '</div></div>';
-    return content;
-}
-
-/**
- * Generate video wrapper HTML
- */
-function generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl) {
-    return `
-        <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
-            ${shouldBlur ? `
-                <button class="toggle-blur-btn showcase-toggle-btn" title="Toggle blur">
-                    <i class="fas fa-eye"></i>
-                </button>
-            ` : ''}
-            <video controls autoplay muted loop crossorigin="anonymous" 
-                referrerpolicy="no-referrer" 
-                data-local-src="${localUrl || ''}"
-                data-remote-src="${remoteUrl}"
-                class="lazy ${shouldBlur ? 'blurred' : ''}">
-                <source data-local-src="${localUrl || ''}" data-remote-src="${remoteUrl}" type="video/mp4">
-                Your browser does not support video playback
-            </video>
-            ${shouldBlur ? `
-                <div class="nsfw-overlay">
-                    <div class="nsfw-warning">
-                        <p>${nsfwText}</p>
-                        <button class="show-content-btn">Show</button>
-                    </div>
-                </div>
-            ` : ''}
-            ${metadataPanel}
-        </div>
-    `;
-}
-
-/**
- * Generate image wrapper HTML
- */
-function generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl) {
-    return `
-        <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
-            ${shouldBlur ? `
-                <button class="toggle-blur-btn showcase-toggle-btn" title="Toggle blur">
-                    <i class="fas fa-eye"></i>
-                </button>
-            ` : ''}
-            <img data-local-src="${localUrl || ''}"
-                data-remote-src="${remoteUrl}"
-                alt="Preview" 
-                crossorigin="anonymous" 
-                referrerpolicy="no-referrer"
-                width="${media.width}"
-                height="${media.height}"
-                class="lazy ${shouldBlur ? 'blurred' : ''}"> 
-            ${shouldBlur ? `
-                <div class="nsfw-overlay">
-                    <div class="nsfw-warning">
-                        <p>${nsfwText}</p>
-                        <button class="show-content-btn">Show</button>
-                    </div>
-                </div>
-            ` : ''}
-            ${metadataPanel}
-        </div>
-    `;
-}
-
-// Use the shared setupShowcaseScroll function with the correct modal ID
-export { setupShowcaseScroll, scrollToTop, toggleShowcase };
-
-// Initialize the showcase scroll when this module is imported
-document.addEventListener('DOMContentLoaded', () => {
-    setupShowcaseScroll('checkpointModal');
-});

static/js/components/checkpointModal/index.js

@@ -3,9 +3,14 @@
  * 
  * Modularized checkpoint modal component that handles checkpoint model details display
  */
-import { showToast, getExampleImageFiles, initLazyLoading, initNsfwBlurHandlers, initMetadataPanelHandlers } from '../../utils/uiHelpers.js';
+import { showToast } from '../../utils/uiHelpers.js';
 import { modalManager } from '../../managers/ModalManager.js';
-import { renderShowcaseContent, toggleShowcase, setupShowcaseScroll, scrollToTop } from './ShowcaseView.js';
+import { 
+    toggleShowcase,
+    setupShowcaseScroll, 
+    scrollToTop,
+    loadExampleImages
+} from '../shared/showcase/ShowcaseView.js';
 import { setupTabSwitching, loadModelDescription } from './ModelDescription.js';
 import { 
     setupModelNameEditing, 
@@ -15,8 +20,6 @@ import {
 import { setupTagEditMode } from './ModelTags.js'; // Add import for tag editing
 import { saveModelMetadata } from '../../api/checkpointApi.js';
 import { renderCompactTags, setupTagTooltip, formatFileSize } from './utils.js';
-import { updateModelCard } from '../../utils/cardUpdater.js';
-import { state } from '../../state/index.js';
 
 /**
  * Display the checkpoint modal with the given checkpoint data
@@ -103,7 +106,7 @@ export function showCheckpointModal(checkpoint) {
                     </div>
                 </div>
 
-                <div class="showcase-section" data-checkpoint-id="${checkpoint.civitai?.modelId || ''}">
+                <div class="showcase-section" data-model-hash="${checkpoint.sha256 || ''}" data-filepath="${checkpoint.file_path}">
                     <div class="showcase-tabs">
                         <button class="tab-btn active" data-tab="showcase">Examples</button>
                         <button class="tab-btn" data-tab="description">Model Description</button>
@@ -138,7 +141,7 @@ export function showCheckpointModal(checkpoint) {
     
     modalManager.showModal('checkpointModal', content);
     setupEditableFields(checkpoint.file_path);
-    setupShowcaseScroll();
+    setupShowcaseScroll('checkpointModal');
     setupTabSwitching();
     setupTagTooltip();
     setupTagEditMode(); // Initialize tag editing functionality
@@ -151,68 +154,12 @@ export function showCheckpointModal(checkpoint) {
         loadModelDescription(checkpoint.civitai.modelId, checkpoint.file_path);
     }
     
-    // Load example images asynchronously
-    loadExampleImages(checkpoint.civitai?.images, checkpoint.sha256, checkpoint.file_path);
-}
-
-/**
- * Load example images asynchronously
- * @param {Array} images - Array of image objects
- * @param {string} modelHash - Model hash for fetching local files
- * @param {string} filePath - File path for fetching local files
- */
-async function loadExampleImages(images, modelHash, filePath) {
-    try {
-        const showcaseTab = document.getElementById('showcase-tab');
-        if (!showcaseTab) return;
-        
-        // First fetch local example files
-        let localFiles = [];
-        try {
-            // Choose endpoint based on centralized examples setting
-            const useCentralized = state.global.settings.useCentralizedExamples !== false;
-            const endpoint = useCentralized ? '/api/example-image-files' : '/api/model-example-files';
-            
-            // Use different params based on endpoint
-            const params = useCentralized ? 
-                `model_hash=${modelHash}` :
-                `file_path=${encodeURIComponent(filePath)}`;
-            
-            const response = await fetch(`${endpoint}?${params}`);
-            const result = await response.json();
-            
-            if (result.success) {
-                localFiles = result.files;
-            }
-        } catch (error) {
-            console.error("Failed to get example files:", error);
-        }
-        
-        // Then render with both remote images and local files
-        showcaseTab.innerHTML = renderShowcaseContent(images, localFiles);
-        
-        // Re-initialize the showcase event listeners
-        const carousel = showcaseTab.querySelector('.carousel');
-        if (carousel) {
-            // Only initialize if we actually have examples and they're expanded
-            if (!carousel.classList.contains('collapsed')) {
-                initLazyLoading(carousel);
-                initNsfwBlurHandlers(carousel);
-                initMetadataPanelHandlers(carousel);
-            }
-        }
-    } catch (error) {
-        console.error('Error loading example images:', error);
-        const showcaseTab = document.getElementById('showcase-tab');
-        if (showcaseTab) {
-            showcaseTab.innerHTML = `
-                <div class="error-message">
-                    <i class="fas fa-exclamation-circle"></i>
-                    Error loading example images
-                </div>
-            `;
-        }
-    }
+    // Load example images asynchronously - merge regular and custom images
+    const regularImages = checkpoint.civitai?.images || [];
+    const customImages = checkpoint.civitai?.customImages || [];
+    // Combine images - regular images first, then custom images
+    const allImages = [...regularImages, ...customImages];
+    loadExampleImages(allImages, checkpoint.sha256);
 }
 
 /**
@@ -263,9 +210,6 @@ async function saveNotes(filePath) {
     try {
         await saveModelMetadata(filePath, { notes: content });
 
-        // Update the corresponding checkpoint card's dataset
-        updateModelCard(filePath, { notes: content });
-
         showToast('Notes saved successfully', 'success');
     } catch (error) {
         showToast('Failed to save notes', 'error');

static/js/components/loraModal/ModelMetadata.js

@@ -115,16 +115,6 @@ export function setupModelNameEditing(filePath) {
             
             await saveModelMetadata(filePath, { model_name: newModelName });
             
-            // Update the corresponding lora card's dataset and display
-            updateModelCard(filePath, { model_name: newModelName });
-            
-            // BUGFIX: Directly update the card's dataset.name attribute to ensure
-            // it's correctly read when reopening the modal
-            const loraCard = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-            if (loraCard) {
-                loraCard.dataset.name = newModelName;
-            }
-            
             showToast('Model name updated successfully', 'success');
         } catch (error) {
             console.error('Error updating model name:', error);
@@ -304,9 +294,6 @@ async function saveBaseModel(filePath, originalValue) {
     try {
         await saveModelMetadata(filePath, { base_model: newBaseModel });
         
-        // Update the corresponding lora card's dataset
-        updateModelCard(filePath, { base_model: newBaseModel });
-        
         showToast('Base model updated successfully', 'success');
     } catch (error) {
         showToast('Failed to update base model', 'error');

static/js/components/loraModal/ModelTags.js

@@ -463,15 +463,6 @@ async function saveTags() {
         // Exit edit mode
         editBtn.click();
         
-        // Update the LoRA card's dataset
-        const loraCard = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-        if (loraCard) {
-            loraCard.dataset.tags = JSON.stringify(tags);
-            
-            // Also update the card in the DOM
-            // updateLoraCard(loraCard, { tags: tags });
-        }
-        
         showToast('Tags updated successfully', 'success');
     } catch (error) {
         console.error('Error saving tags:', error);

static/js/components/loraModal/PresetTags.js

@@ -62,6 +62,5 @@ window.removePreset = async function(key) {
         usage_tips: newPresetsJson 
     });
     
-    loraCard.dataset.usage_tips = newPresetsJson;
     document.querySelector('.preset-tags').innerHTML = renderPresetTags(currentPresets);
 };

static/js/components/loraModal/ShowcaseView.js

@@ -1,280 +0,0 @@
-/**
- * ShowcaseView.js
- * 处理LoRA模型展示内容（图片、视频）的功能模块
- */
-import { 
-    toggleShowcase,
-    setupShowcaseScroll,
-    scrollToTop 
-} from '../../utils/uiHelpers.js';
-import { state } from '../../state/index.js';
-import { NSFW_LEVELS } from '../../utils/constants.js';
-
-/**
- * 获取展示内容并进行渲染
- * @param {Array} images - 要展示的图片/视频数组
- * @param {Array} exampleFiles - Local example files already fetched
- * @returns {Promise<string>} HTML内容
- */
-export function renderShowcaseContent(images, exampleFiles = []) {
-    if (!images?.length) return '<div class="no-examples">No example images available</div>';
-    
-    // Filter images based on SFW setting
-    const showOnlySFW = state.settings.show_only_sfw;
-    let filteredImages = images;
-    let hiddenCount = 0;
-    
-    if (showOnlySFW) {
-        filteredImages = images.filter(img => {
-            const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
-            const isSfw = nsfwLevel < NSFW_LEVELS.R;
-            if (!isSfw) hiddenCount++;
-            return isSfw;
-        });
-    }
-    
-    // Show message if no images are available after filtering
-    if (filteredImages.length === 0) {
-        return `
-            <div class="no-examples">
-                <p>All example images are filtered due to NSFW content settings</p>
-                <p class="nsfw-filter-info">Your settings are currently set to show only safe-for-work content</p>
-                <p>You can change this in Settings <i class="fas fa-cog"></i></p>
-            </div>
-        `;
-    }
-    
-    // Show hidden content notification if applicable
-    const hiddenNotification = hiddenCount > 0 ? 
-        `<div class="nsfw-filter-notification">
-            <i class="fas fa-eye-slash"></i> ${hiddenCount} ${hiddenCount === 1 ? 'image' : 'images'} hidden due to SFW-only setting
-        </div>` : '';
-    
-    return `
-        <div class="scroll-indicator" onclick="toggleShowcase(this)">
-            <i class="fas fa-chevron-down"></i>
-            <span>Scroll or click to show ${filteredImages.length} examples</span>
-        </div>
-        <div class="carousel collapsed">
-            ${hiddenNotification}
-            <div class="carousel-container">
-                ${filteredImages.map((img, index) => {
-                    // Find matching file in our list of actual files
-                    let localFile = null;
-                    if (exampleFiles.length > 0) {
-                        // Try to find the corresponding file by index first
-                        localFile = exampleFiles.find(file => {
-                            const match = file.name.match(/image_(\d+)\./);
-                            return match && parseInt(match[1]) === index;
-                        });
-                        
-                        // If not found by index, just use the same position in the array if available
-                        if (!localFile && index < exampleFiles.length) {
-                            localFile = exampleFiles[index];
-                        }
-                    }
-                    
-                    const remoteUrl = img.url || '';
-                    const localUrl = localFile ? localFile.path : '';
-                    const isVideo = localFile ? localFile.is_video : 
-                                    remoteUrl.endsWith('.mp4') || remoteUrl.endsWith('.webm');
-                    
-                    // 计算适当的展示高度
-                    const aspectRatio = (img.height / img.width) * 100;
-                    const containerWidth = 800; 
-                    const minHeightPercent = 40; 
-                    const maxHeightPercent = (window.innerHeight * 0.6 / containerWidth) * 100;
-                    const heightPercent = Math.max(
-                        minHeightPercent,
-                        Math.min(maxHeightPercent, aspectRatio)
-                    );
-                    
-                    // Check if image should be blurred
-                    const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
-                    const shouldBlur = state.settings.blurMatureContent && nsfwLevel > NSFW_LEVELS.PG13;
-                    
-                    // Determine NSFW warning text based on level
-                    let nsfwText = "Mature Content";
-                    if (nsfwLevel >= NSFW_LEVELS.XXX) {
-                        nsfwText = "XXX-rated Content";
-                    } else if (nsfwLevel >= NSFW_LEVELS.X) {
-                        nsfwText = "X-rated Content";
-                    } else if (nsfwLevel >= NSFW_LEVELS.R) {
-                        nsfwText = "R-rated Content";
-                    }
-                    
-                    // Extract metadata from the image
-                    const meta = img.meta || {};
-                    const prompt = meta.prompt || '';
-                    const negativePrompt = meta.negative_prompt || meta.negativePrompt || '';
-                    const size = meta.Size || `${img.width}x${img.height}`;
-                    const seed = meta.seed || '';
-                    const model = meta.Model || '';
-                    const steps = meta.steps || '';
-                    const sampler = meta.sampler || '';
-                    const cfgScale = meta.cfgScale || '';
-                    const clipSkip = meta.clipSkip || '';
-                    
-                    const hasParams = seed || model || steps || sampler || cfgScale || clipSkip;
-                    const hasPrompts = prompt || negativePrompt;
-                    
-                    const metadataPanel = generateMetadataPanel(
-                        hasParams, hasPrompts, 
-                        prompt, negativePrompt, 
-                        size, seed, model, steps, sampler, cfgScale, clipSkip
-                    );
-                    
-                    if (isVideo) {
-                        return generateVideoWrapper(
-                            img, heightPercent, shouldBlur, nsfwText, metadataPanel, 
-                            localUrl, remoteUrl
-                        );
-                    }
-                    return generateImageWrapper(
-                        img, heightPercent, shouldBlur, nsfwText, metadataPanel, 
-                        localUrl, remoteUrl
-                    );
-                }).join('')}
-            </div>
-        </div>
-    `;
-}
-
-/**
- * Generate metadata panel HTML
- */
-function generateMetadataPanel(hasParams, hasPrompts, prompt, negativePrompt, size, seed, model, steps, sampler, cfgScale, clipSkip) {
-    // Create unique IDs for prompt copying
-    const promptIndex = Math.random().toString(36).substring(2, 15);
-    const negPromptIndex = Math.random().toString(36).substring(2, 15);
-    
-    let content = '<div class="image-metadata-panel"><div class="metadata-content">';
-    
-    if (hasParams) {
-        content += `
-            <div class="params-tags">
-                ${size ? `<div class="param-tag"><span class="param-name">Size:</span><span class="param-value">${size}</span></div>` : ''}
-                ${seed ? `<div class="param-tag"><span class="param-name">Seed:</span><span class="param-value">${seed}</span></div>` : ''}
-                ${model ? `<div class="param-tag"><span class="param-name">Model:</span><span class="param-value">${model}</span></div>` : ''}
-                ${steps ? `<div class="param-tag"><span class="param-name">Steps:</span><span class="param-value">${steps}</span></div>` : ''}
-                ${sampler ? `<div class="param-tag"><span class="param-name">Sampler:</span><span class="param-value">${sampler}</span></div>` : ''}
-                ${cfgScale ? `<div class="param-tag"><span class="param-name">CFG:</span><span class="param-value">${cfgScale}</span></div>` : ''}
-                ${clipSkip ? `<div class="param-tag"><span class="param-name">Clip Skip:</span><span class="param-value">${clipSkip}</span></div>` : ''}
-            </div>
-        `;
-    }
-    
-    if (!hasParams && !hasPrompts) {
-        content += `
-            <div class="no-metadata-message">
-                <i class="fas fa-info-circle"></i>
-                <span>No generation parameters available</span>
-            </div>
-        `;
-    }
-    
-    if (prompt) {
-        content += `
-            <div class="metadata-row prompt-row">
-                <span class="metadata-label">Prompt:</span>
-                <div class="metadata-prompt-wrapper">
-                    <div class="metadata-prompt">${prompt}</div>
-                    <button class="copy-prompt-btn" data-prompt-index="${promptIndex}">
-                        <i class="fas fa-copy"></i>
-                    </button>
-                </div>
-            </div>
-            <div class="hidden-prompt" id="prompt-${promptIndex}" style="display:none;">${prompt}</div>
-        `;
-    }
-    
-    if (negativePrompt) {
-        content += `
-            <div class="metadata-row prompt-row">
-                <span class="metadata-label">Negative Prompt:</span>
-                <div class="metadata-prompt-wrapper">
-                    <div class="metadata-prompt">${negativePrompt}</div>
-                    <button class="copy-prompt-btn" data-prompt-index="${negPromptIndex}">
-                        <i class="fas fa-copy"></i>
-                    </button>
-                </div>
-            </div>
-            <div class="hidden-prompt" id="prompt-${negPromptIndex}" style="display:none;">${negativePrompt}</div>
-        `;
-    }
-    
-    content += '</div></div>';
-    return content;
-}
-
-/**
- * 生成视频包装HTML
- */
-function generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl) {
-    return `
-        <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
-            ${shouldBlur ? `
-                <button class="toggle-blur-btn showcase-toggle-btn" title="Toggle blur">
-                    <i class="fas fa-eye"></i>
-                </button>
-            ` : ''}
-            <video controls autoplay muted loop crossorigin="anonymous" 
-                referrerpolicy="no-referrer" 
-                data-local-src="${localUrl || ''}"
-                data-remote-src="${remoteUrl}"
-                class="lazy ${shouldBlur ? 'blurred' : ''}">
-                <source data-local-src="${localUrl || ''}" data-remote-src="${remoteUrl}" type="video/mp4">
-                Your browser does not support video playback
-            </video>
-            ${shouldBlur ? `
-                <div class="nsfw-overlay">
-                    <div class="nsfw-warning">
-                        <p>${nsfwText}</p>
-                        <button class="show-content-btn">Show</button>
-                    </div>
-                </div>
-            ` : ''}
-            ${metadataPanel}
-        </div>
-    `;
-}
-
-/**
- * 生成图片包装HTML
- */
-function generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl) {
-    return `
-        <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
-            ${shouldBlur ? `
-                <button class="toggle-blur-btn showcase-toggle-btn" title="Toggle blur">
-                    <i class="fas fa-eye"></i>
-                </button>
-            ` : ''}
-            <img data-local-src="${localUrl || ''}" 
-                data-remote-src="${remoteUrl}"
-                alt="Preview" 
-                crossorigin="anonymous" 
-                referrerpolicy="no-referrer"
-                width="${img.width}"
-                height="${img.height}"
-                class="lazy ${shouldBlur ? 'blurred' : ''}"> 
-            ${shouldBlur ? `
-                <div class="nsfw-overlay">
-                    <div class="nsfw-warning">
-                        <p>${nsfwText}</p>
-                        <button class="show-content-btn">Show</button>
-                    </div>
-                </div>
-            ` : ''}
-            ${metadataPanel}
-        </div>
-    `;
-}
-
-// Use the shared setupShowcaseScroll function with the correct modal ID
-export { setupShowcaseScroll, scrollToTop, toggleShowcase };
-
-// Initialize the showcase scroll when this module is imported
-document.addEventListener('DOMContentLoaded', () => {
-    setupShowcaseScroll('loraModal');
-});

static/js/components/loraModal/TriggerWords.js

@@ -620,28 +620,6 @@ async function saveTriggerWords() {
         // Exit edit mode without restoring original trigger words
         editBtn.click();
         
-        // Update the LoRA card's dataset
-        const loraCard = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-        if (loraCard) {
-            try {
-                // Create a proper structure for civitai data
-                let civitaiData = {};
-                
-                // Parse existing data if available
-                if (loraCard.dataset.meta) {
-                    civitaiData = JSON.parse(loraCard.dataset.meta);
-                }
-                
-                // Update trainedWords property
-                civitaiData.trainedWords = words;
-                
-                // Update the meta dataset attribute with the full civitai data
-                loraCard.dataset.meta = JSON.stringify(civitaiData);
-            } catch (e) {
-                console.error('Error updating civitai data:', e);
-            }
-        }
-        
         // If we saved an empty array and there's a no-trigger-words element, show it
         const noTriggerWords = triggerWordsSection.querySelector('.no-trigger-words');
         const tagsContainer = triggerWordsSection.querySelector('.trigger-words-tags');

static/js/components/loraModal/index.js

@@ -3,9 +3,13 @@
  * 
  * 将原始的LoraModal.js拆分成多个功能模块后的主入口文件
  */
-import { showToast, copyToClipboard, getExampleImageFiles } from '../../utils/uiHelpers.js';
+import { showToast } from '../../utils/uiHelpers.js';
 import { modalManager } from '../../managers/ModalManager.js';
-import { renderShowcaseContent, toggleShowcase, setupShowcaseScroll, scrollToTop } from './ShowcaseView.js';
+import { 
+    setupShowcaseScroll, 
+    scrollToTop,
+    loadExampleImages
+} from '../shared/showcase/ShowcaseView.js';
 import { setupTabSwitching, loadModelDescription } from './ModelDescription.js';
 import { renderTriggerWords, setupTriggerWordsEditMode } from './TriggerWords.js';
 import { parsePresets, renderPresetTags } from './PresetTags.js';
@@ -18,8 +22,6 @@ import {
 } from './ModelMetadata.js';
 import { saveModelMetadata } from '../../api/loraApi.js';
 import { renderCompactTags, setupTagTooltip, formatFileSize } from './utils.js';
-import { updateModelCard } from '../../utils/cardUpdater.js';
-import { state } from '../../state/index.js';
 
 /**
  * 显示LoRA模型弹窗
@@ -117,7 +119,7 @@ export function showLoraModal(lora) {
                             <label>Additional Notes</label>
                             <div class="editable-field">
                                 <div class="notes-content" contenteditable="true" spellcheck="false">${lora.notes || 'Add your notes here...'}</div>
-                                <button class="save-btn" onclick="saveNotes('${lora.file_path}')">
+                                <button class="save-btn" data-action="save-notes">
                                     <i class="fas fa-save"></i>
                                 </button>
                             </div>
@@ -129,7 +131,7 @@ export function showLoraModal(lora) {
                     </div>
                 </div>
 
-                <div class="showcase-section" data-lora-id="${lora.civitai?.modelId || ''}">
+                <div class="showcase-section" data-model-hash="${lora.sha256 || ''}" data-filepath="${lora.file_path}">
                     <div class="showcase-tabs">
                         <button class="tab-btn active" data-tab="showcase">Examples</button>
                         <button class="tab-btn" data-tab="description">Model Description</button>
@@ -161,7 +163,7 @@ export function showLoraModal(lora) {
                         </div>
                     </div>
                     
-                    <button class="back-to-top" onclick="scrollToTop(this)">
+                    <button class="back-to-top" data-action="scroll-to-top">
                         <i class="fas fa-arrow-up"></i>
                     </button>
                 </div>
@@ -171,7 +173,7 @@ export function showLoraModal(lora) {
     
     modalManager.showModal('loraModal', content);
     setupEditableFields(lora.file_path);
-    setupShowcaseScroll();
+    setupShowcaseScroll('loraModal');
     setupTabSwitching();
     setupTagTooltip();
     setupTriggerWordsEditMode();
@@ -179,6 +181,7 @@ export function showLoraModal(lora) {
     setupBaseModelEditing(lora.file_path);
     setupFileNameEditing(lora.file_path);
     setupTagEditMode(); // Initialize tag editing functionality
+    setupEventHandlers(lora.file_path);
     
     // If we have a model ID but no description, fetch it
     if (lora.civitai?.modelId && !lora.modelDescription) {
@@ -188,90 +191,49 @@ export function showLoraModal(lora) {
     // Load recipes for this Lora
     loadRecipesForLora(lora.model_name, lora.sha256);
     
-    // Load example images asynchronously
-    loadExampleImages(lora.civitai?.images, lora.sha256, lora.file_path);
+    // Load example images asynchronously - merge regular and custom images
+    const regularImages = lora.civitai?.images || [];
+    const customImages = lora.civitai?.customImages || [];
+    // Combine images - regular images first, then custom images
+    const allImages = [...regularImages, ...customImages];
+    loadExampleImages(allImages, lora.sha256);
 }
 
 /**
- * Load example images asynchronously
- * @param {Array} images - Array of image objects
- * @param {string} modelHash - Model hash for fetching local files
- * @param {string} filePath - File path for fetching local files
+ * Sets up event handlers using event delegation
+ * @param {string} filePath - Path to the model file
  */
-async function loadExampleImages(images, modelHash, filePath) {
-    try {
-        const showcaseTab = document.getElementById('showcase-tab');
-        if (!showcaseTab) return;
+function setupEventHandlers(filePath) {
+    const modalElement = document.getElementById('loraModal');
+    
+    // Use event delegation to handle clicks
+    modalElement.addEventListener('click', async (event) => {
+        const target = event.target.closest('[data-action]');
+        if (!target) return;
         
-        // First fetch local example files
-        let localFiles = [];
-
-        try {
-            // Choose endpoint based on centralized examples setting
-            const useCentralized = state.global.settings.useCentralizedExamples !== false;
-            const endpoint = useCentralized ? '/api/example-image-files' : '/api/model-example-files';
-            
-            // Use different params based on endpoint
-            const params = useCentralized ? 
-                `model_hash=${modelHash}` :
-                `file_path=${encodeURIComponent(filePath)}`;
-            
-            const response = await fetch(`${endpoint}?${params}`);
-            const result = await response.json();
-            
-            if (result.success) {
-                localFiles = result.files;
-            }
-        } catch (error) {
-            console.error("Failed to get example files:", error);
-        }
+        const action = target.dataset.action;
         
-        // Then render with both remote images and local files
-        showcaseTab.innerHTML = renderShowcaseContent(images, localFiles);
-        
-        // Re-initialize the showcase event listeners
-        const carousel = showcaseTab.querySelector('.carousel');
-        if (carousel) {
-            // Only initialize if we actually have examples and they're expanded
-            if (!carousel.classList.contains('collapsed')) {
-                initLazyLoading(carousel);
-                initNsfwBlurHandlers(carousel);
-                initMetadataPanelHandlers(carousel);
-            }
+        switch (action) {
+            case 'close-modal':
+                modalManager.closeModal('loraModal');
+                break;
+                
+            case 'save-notes':
+                await saveNotes(filePath);
+                break;
+                
+            case 'scroll-to-top':
+                scrollToTop(target);
+                break;
         }
-    } catch (error) {
-        console.error('Error loading example images:', error);
-        const showcaseTab = document.getElementById('showcase-tab');
-        if (showcaseTab) {
-            showcaseTab.innerHTML = `
-                <div class="error-message">
-                    <i class="fas fa-exclamation-circle"></i>
-                    Error loading example images
-                </div>
-            `;
-        }
-    }
+    });
 }
 
-// Copy file name function
-window.copyFileName = async function(fileName) {
-    try {
-        await copyToClipboard(fileName, 'File name copied');
-    } catch (err) {
-        console.error('Copy failed:', err);
-        showToast('Copy failed', 'error');
-    }
-};
-
-// Add save note function
-window.saveNotes = async function(filePath) {
+async function saveNotes(filePath) {
     const content = document.querySelector('.notes-content').textContent;
     try {
         await saveModelMetadata(filePath, { notes: content });
 
-        // Update the corresponding lora card's dataset
-        updateModelCard(filePath, { notes: content });
-
         showToast('Notes saved successfully', 'success');
     } catch (error) {
         showToast('Failed to save notes', 'error');
@@ -336,9 +298,6 @@ function setupEditableFields(filePath) {
             usage_tips: newPresetsJson
         });
 
-        // Update the card with the new usage tips
-        updateModelCard(filePath, { usage_tips: newPresetsJson });
-        
         presetTags.innerHTML = renderPresetTags(currentPresets);
         
         presetSelector.value = '';
@@ -368,7 +327,4 @@ function setupEditableFields(filePath) {
             addPresetBtn.click();
         }
     });
-}
-
-// Export functions for global access
-export { toggleShowcase, scrollToTop };
+}

static/js/components/shared/showcase/MediaRenderers.js

@@ -0,0 +1,94 @@
+/**
+ * MediaRenderers.js
+ * HTML generators for media items (images/videos) in the showcase
+ */
+
+/**
+ * Generate video wrapper HTML
+ * @param {Object} media - Media metadata
+ * @param {number} heightPercent - Height percentage for container
+ * @param {boolean} shouldBlur - Whether content should be blurred
+ * @param {string} nsfwText - NSFW warning text
+ * @param {string} metadataPanel - Metadata panel HTML
+ * @param {string} localUrl - Local file URL
+ * @param {string} remoteUrl - Remote file URL
+ * @param {string} mediaControlsHtml - HTML for media control buttons
+ * @returns {string} HTML content
+ */
+export function generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl, mediaControlsHtml = '') {
+    const nsfwLevel = media.nsfwLevel !== undefined ? media.nsfwLevel : 0;
+    
+    return `
+        <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%" data-short-id="${media.id || ''}" data-nsfw-level="${nsfwLevel}">
+            ${shouldBlur ? `
+                <button class="toggle-blur-btn showcase-toggle-btn" title="Toggle blur">
+                    <i class="fas fa-eye"></i>
+                </button>
+            ` : ''}
+            ${mediaControlsHtml}
+            <video controls autoplay muted loop crossorigin="anonymous" 
+                referrerpolicy="no-referrer" 
+                data-local-src="${localUrl || ''}"
+                data-remote-src="${remoteUrl}"
+                data-nsfw-level="${nsfwLevel}"
+                class="lazy ${shouldBlur ? 'blurred' : ''}">
+                <source data-local-src="${localUrl || ''}" data-remote-src="${remoteUrl}" type="video/mp4">
+                Your browser does not support video playback
+            </video>
+            ${shouldBlur ? `
+                <div class="nsfw-overlay">
+                    <div class="nsfw-warning">
+                        <p>${nsfwText}</p>
+                        <button class="show-content-btn">Show</button>
+                    </div>
+                </div>
+            ` : ''}
+            ${metadataPanel}
+        </div>
+    `;
+}
+
+/**
+ * Generate image wrapper HTML
+ * @param {Object} media - Media metadata
+ * @param {number} heightPercent - Height percentage for container
+ * @param {boolean} shouldBlur - Whether content should be blurred
+ * @param {string} nsfwText - NSFW warning text
+ * @param {string} metadataPanel - Metadata panel HTML
+ * @param {string} localUrl - Local file URL
+ * @param {string} remoteUrl - Remote file URL
+ * @param {string} mediaControlsHtml - HTML for media control buttons
+ * @returns {string} HTML content
+ */
+export function generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl, mediaControlsHtml = '') {
+    const nsfwLevel = media.nsfwLevel !== undefined ? media.nsfwLevel : 0;
+    
+    return `
+        <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%" data-short-id="${media.id || ''}" data-nsfw-level="${nsfwLevel}">
+            ${shouldBlur ? `
+                <button class="toggle-blur-btn showcase-toggle-btn" title="Toggle blur">
+                    <i class="fas fa-eye"></i>
+                </button>
+            ` : ''}
+            ${mediaControlsHtml}
+            <img data-local-src="${localUrl || ''}" 
+                data-remote-src="${remoteUrl}"
+                data-nsfw-level="${nsfwLevel}"
+                alt="Preview" 
+                crossorigin="anonymous" 
+                referrerpolicy="no-referrer"
+                width="${media.width}"
+                height="${media.height}"
+                class="lazy ${shouldBlur ? 'blurred' : ''}"> 
+            ${shouldBlur ? `
+                <div class="nsfw-overlay">
+                    <div class="nsfw-warning">
+                        <p>${nsfwText}</p>
+                        <button class="show-content-btn">Show</button>
+                    </div>
+                </div>
+            ` : ''}
+            ${metadataPanel}
+        </div>
+    `;
+}

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

@@ -0,0 +1,592 @@
+/**
+ * MediaUtils.js
+ * Media-specific utility functions for showcase components
+ * (Moved from uiHelpers.js to better organize code)
+ */
+import { showToast, copyToClipboard } from '../../../utils/uiHelpers.js';
+import { state } from '../../../state/index.js';
+import { uploadPreview } from '../../../api/baseModelApi.js';
+
+/**
+ * Try to load local image first, fall back to remote if local fails
+ * @param {HTMLImageElement} imgElement - The image element to update
+ * @param {Object} urls - Object with local URLs {primary, fallback} and remote URL
+ */
+export function tryLocalImageOrFallbackToRemote(imgElement, urls) {
+    const { primary: localUrl, fallback: fallbackUrl } = urls.local || {};
+    const remoteUrl = urls.remote;
+    
+    // If no local options, use remote directly
+    if (!localUrl) {
+        imgElement.src = remoteUrl;
+        return;
+    }
+    
+    // Try primary local URL
+    const testImg = new Image();
+    testImg.onload = () => {
+        // Primary local image loaded successfully
+        imgElement.src = localUrl;
+    };
+    testImg.onerror = () => {
+        // Try fallback URL if available
+        if (fallbackUrl) {
+            const fallbackImg = new Image();
+            fallbackImg.onload = () => {
+                imgElement.src = fallbackUrl;
+            };
+            fallbackImg.onerror = () => {
+                // Both local options failed, use remote
+                imgElement.src = remoteUrl;
+            };
+            fallbackImg.src = fallbackUrl;
+        } else {
+            // No fallback, use remote
+            imgElement.src = remoteUrl;
+        }
+    };
+    testImg.src = localUrl;
+}
+
+/**
+ * Try to load local video first, fall back to remote if local fails
+ * @param {HTMLVideoElement} videoElement - The video element to update
+ * @param {Object} urls - Object with local URLs {primary} and remote URL
+ */
+export function tryLocalVideoOrFallbackToRemote(videoElement, urls) {
+    const { primary: localUrl } = urls.local || {};
+    const remoteUrl = urls.remote;
+    
+    // Only try local if we have a local path
+    if (localUrl) {
+        // Try to fetch local file headers to see if it exists
+        fetch(localUrl, { method: 'HEAD' })
+            .then(response => {
+                if (response.ok) {
+                    // Local video exists, use it
+                    videoElement.src = localUrl;
+                    const source = videoElement.querySelector('source');
+                    if (source) source.src = localUrl;
+                } else {
+                    // Local video doesn't exist, use remote
+                    videoElement.src = remoteUrl;
+                    const source = videoElement.querySelector('source');
+                    if (source) source.src = remoteUrl;
+                }
+                videoElement.load();
+            })
+            .catch(() => {
+                // Error fetching, use remote
+                videoElement.src = remoteUrl;
+                const source = videoElement.querySelector('source');
+                if (source) source.src = remoteUrl;
+                videoElement.load();
+            });
+    } else {
+        // No local path, use remote directly
+        videoElement.src = remoteUrl;
+        const source = videoElement.querySelector('source');
+        if (source) source.src = remoteUrl;
+        videoElement.load();
+    }
+}
+
+/**
+ * Initialize lazy loading for images and videos in a container
+ * @param {HTMLElement} container - The container with lazy-loadable elements
+ */
+export function initLazyLoading(container) {
+    const lazyElements = container.querySelectorAll('.lazy');
+    
+    const lazyLoad = (element) => {
+        // Get URLs from data attributes
+        const localUrls = {
+            primary: element.dataset.localSrc || null,
+            fallback: element.dataset.localFallbackSrc || null
+        };
+        const remoteUrl = element.dataset.remoteSrc;
+        
+        const urls = {
+            local: localUrls,
+            remote: remoteUrl
+        };
+        
+        // Check if element is a video or image
+        if (element.tagName.toLowerCase() === 'video') {
+            tryLocalVideoOrFallbackToRemote(element, urls);
+        } else {
+            tryLocalImageOrFallbackToRemote(element, urls);
+        }
+        
+        element.classList.remove('lazy');
+    };
+
+    const observer = new IntersectionObserver((entries) => {
+        entries.forEach(entry => {
+            if (entry.isIntersecting) {
+                lazyLoad(entry.target);
+                observer.unobserve(entry.target);
+            }
+        });
+    });
+
+    lazyElements.forEach(element => observer.observe(element));
+}
+
+/**
+ * Get the actual rendered rectangle of a media element with object-fit: contain
+ * @param {HTMLElement} mediaElement - The img or video element
+ * @param {number} containerWidth - Width of the container
+ * @param {number} containerHeight - Height of the container
+ * @returns {Object} - Rect with left, top, right, bottom coordinates
+ */
+export function getRenderedMediaRect(mediaElement, containerWidth, containerHeight) {
+    // Get natural dimensions of the media
+    const naturalWidth = mediaElement.naturalWidth || mediaElement.videoWidth || mediaElement.clientWidth;
+    const naturalHeight = mediaElement.naturalHeight || mediaElement.videoHeight || mediaElement.clientHeight;
+    
+    if (!naturalWidth || !naturalHeight) {
+        // Fallback if dimensions cannot be determined
+        return { left: 0, top: 0, right: containerWidth, bottom: containerHeight };
+    }
+    
+    // Calculate aspect ratios
+    const containerRatio = containerWidth / containerHeight;
+    const mediaRatio = naturalWidth / naturalHeight;
+    
+    let renderedWidth, renderedHeight, left = 0, top = 0;
+    
+    // Apply object-fit: contain logic
+    if (containerRatio > mediaRatio) {
+        // Container is wider than media - will have empty space on sides
+        renderedHeight = containerHeight;
+        renderedWidth = renderedHeight * mediaRatio;
+        left = (containerWidth - renderedWidth) / 2;
+    } else {
+        // Container is taller than media - will have empty space top/bottom
+        renderedWidth = containerWidth;
+        renderedHeight = renderedWidth / mediaRatio;
+        top = (containerHeight - renderedHeight) / 2;
+    }
+    
+    return {
+        left,
+        top,
+        right: left + renderedWidth,
+        bottom: top + renderedHeight
+    };
+}
+
+/**
+ * Initialize metadata panel interaction handlers
+ * @param {HTMLElement} container - Container element with media wrappers
+ */
+export function initMetadataPanelHandlers(container) {
+    const mediaWrappers = container.querySelectorAll('.media-wrapper');
+    
+    mediaWrappers.forEach(wrapper => {
+        // Get the metadata panel and media element (img or video)
+        const metadataPanel = wrapper.querySelector('.image-metadata-panel');
+        const mediaControls = wrapper.querySelector('.media-controls');
+        const mediaElement = wrapper.querySelector('img, video');
+        
+        if (!mediaElement) return;
+        
+        let isOverMetadataPanel = false;
+        
+        // Add event listeners to the wrapper for mouse tracking
+        wrapper.addEventListener('mousemove', (e) => {
+            // Get mouse position relative to wrapper
+            const rect = wrapper.getBoundingClientRect();
+            const mouseX = e.clientX - rect.left;
+            const mouseY = e.clientY - rect.top;
+            
+            // Get the actual displayed dimensions of the media element
+            const mediaRect = getRenderedMediaRect(mediaElement, rect.width, rect.height);
+            
+            // Check if mouse is over the actual media content
+            const isOverMedia = (
+                mouseX >= mediaRect.left && 
+                mouseX <= mediaRect.right && 
+                mouseY >= mediaRect.top && 
+                mouseY <= mediaRect.bottom
+            );
+            
+            // Show metadata panel and controls when over media content or metadata panel itself
+            if (isOverMedia || isOverMetadataPanel) {
+                if (metadataPanel) metadataPanel.classList.add('visible');
+                if (mediaControls) mediaControls.classList.add('visible');
+            } else {
+                if (metadataPanel) metadataPanel.classList.remove('visible');
+                if (mediaControls) mediaControls.classList.remove('visible');
+            }
+        });
+        
+        wrapper.addEventListener('mouseleave', () => {
+            if (!isOverMetadataPanel) {
+                if (metadataPanel) metadataPanel.classList.remove('visible');
+                if (mediaControls) mediaControls.classList.remove('visible');
+            }
+        });
+        
+        // Add mouse enter/leave events for the metadata panel itself
+        if (metadataPanel) {
+            metadataPanel.addEventListener('mouseenter', () => {
+                isOverMetadataPanel = true;
+                metadataPanel.classList.add('visible');
+                if (mediaControls) mediaControls.classList.add('visible');
+            });
+            
+            metadataPanel.addEventListener('mouseleave', () => {
+                isOverMetadataPanel = false;
+                // Only hide if mouse is not over the media
+                const rect = wrapper.getBoundingClientRect();
+                const mediaRect = getRenderedMediaRect(mediaElement, rect.width, rect.height);
+                const mouseX = event.clientX - rect.left;
+                const mouseY = event.clientY - rect.top;
+                
+                const isOverMedia = (
+                    mouseX >= mediaRect.left && 
+                    mouseX <= mediaRect.right && 
+                    mouseY >= mediaRect.top && 
+                    mouseY <= mediaRect.bottom
+                );
+                
+                if (!isOverMedia) {
+                    metadataPanel.classList.remove('visible');
+                    if (mediaControls) mediaControls.classList.remove('visible');
+                }
+            });
+            
+            // Prevent events from bubbling
+            metadataPanel.addEventListener('click', (e) => {
+                e.stopPropagation();
+            });
+            
+            // Handle copy prompt buttons
+            const copyBtns = metadataPanel.querySelectorAll('.copy-prompt-btn');
+            copyBtns.forEach(copyBtn => {
+                const promptIndex = copyBtn.dataset.promptIndex;
+                const promptElement = wrapper.querySelector(`#prompt-${promptIndex}`);
+                
+                copyBtn.addEventListener('click', async (e) => {
+                    e.stopPropagation();
+                    
+                    if (!promptElement) return;
+                    
+                    try {
+                        await copyToClipboard(promptElement.textContent, 'Prompt copied to clipboard');
+                    } catch (err) {
+                        console.error('Copy failed:', err);
+                        showToast('Copy failed', 'error');
+                    }
+                });
+            });
+            
+            // Prevent panel scroll from causing modal scroll
+            metadataPanel.addEventListener('wheel', (e) => {
+                const isAtTop = metadataPanel.scrollTop === 0;
+                const isAtBottom = metadataPanel.scrollHeight - metadataPanel.scrollTop === metadataPanel.clientHeight;
+                
+                // Only prevent default if scrolling would cause the panel to scroll
+                if ((e.deltaY < 0 && !isAtTop) || (e.deltaY > 0 && !isAtBottom)) {
+                    e.stopPropagation();
+                }
+            }, { passive: true });
+        }
+    });
+}
+
+/**
+ * Initialize NSFW content blur toggle handlers
+ * @param {HTMLElement} container - Container element with media wrappers
+ */
+export function initNsfwBlurHandlers(container) {
+    // Handle toggle blur buttons
+    const toggleButtons = container.querySelectorAll('.toggle-blur-btn');
+    toggleButtons.forEach(btn => {
+        btn.addEventListener('click', (e) => {
+            e.stopPropagation();
+            const wrapper = btn.closest('.media-wrapper');
+            const media = wrapper.querySelector('img, video');
+            const isBlurred = media.classList.toggle('blurred');
+            const icon = btn.querySelector('i');
+            
+            // Update the icon based on blur state
+            if (isBlurred) {
+                icon.className = 'fas fa-eye';
+            } else {
+                icon.className = 'fas fa-eye-slash';
+            }
+            
+            // Toggle the overlay visibility
+            const overlay = wrapper.querySelector('.nsfw-overlay');
+            if (overlay) {
+                overlay.style.display = isBlurred ? 'flex' : 'none';
+            }
+        });
+    });
+    
+    // Handle "Show" buttons in overlays
+    const showButtons = container.querySelectorAll('.show-content-btn');
+    showButtons.forEach(btn => {
+        btn.addEventListener('click', (e) => {
+            e.stopPropagation();
+            const wrapper = btn.closest('.media-wrapper');
+            const media = wrapper.querySelector('img, video');
+            media.classList.remove('blurred');
+            
+            // Update the toggle button icon
+            const toggleBtn = wrapper.querySelector('.toggle-blur-btn');
+            if (toggleBtn) {
+                toggleBtn.querySelector('i').className = 'fas fa-eye-slash';
+            }
+            
+            // Hide the overlay
+            const overlay = wrapper.querySelector('.nsfw-overlay');
+            if (overlay) {
+                overlay.style.display = 'none';
+            }
+        });
+    });
+}
+
+/**
+ * Initialize media control buttons event handlers
+ * @param {HTMLElement} container - Container with media wrappers
+ */
+export function initMediaControlHandlers(container) {
+    // Find all delete buttons in the container
+    const deleteButtons = container.querySelectorAll('.example-delete-btn');
+    
+    deleteButtons.forEach(btn => {
+        // Set initial state
+        btn.dataset.state = 'initial';
+        
+        btn.addEventListener('click', async function(e) {
+            e.stopPropagation();
+            
+            // Explicitly check for disabled state
+            if (this.classList.contains('disabled')) {
+                return; // Don't do anything if button is disabled
+            }
+            
+            const shortId = this.dataset.shortId;
+            const btnState = this.dataset.state;
+            
+            if (!shortId) return;
+            
+            // Handle two-step confirmation
+            if (btnState === 'initial') {
+                // First click: show confirmation state
+                this.dataset.state = 'confirm';
+                this.classList.add('confirm');
+                this.title = 'Click again to confirm deletion';
+                
+                // Auto-reset after 3 seconds
+                setTimeout(() => {
+                    if (this.dataset.state === 'confirm') {
+                        this.dataset.state = 'initial';
+                        this.classList.remove('confirm');
+                        this.title = 'Delete this example';
+                    }
+                }, 3000);
+                
+                return;
+            }
+            
+            // Second click within 3 seconds: proceed with deletion
+            if (btnState === 'confirm') {
+                this.disabled = true;
+                this.classList.remove('confirm');
+                this.innerHTML = '<i class="fas fa-spinner fa-spin"></i>';
+                
+                // Get model hash from URL or data attribute
+                const mediaWrapper = this.closest('.media-wrapper');
+                const modelHashAttr = document.querySelector('.showcase-section')?.dataset;
+                const modelHash = modelHashAttr?.modelHash;
+                
+                try {
+                    // Call the API to delete the custom example
+                    const response = await fetch('/api/delete-example-image', {
+                        method: 'POST',
+                        headers: {
+                            'Content-Type': 'application/json'
+                        },
+                        body: JSON.stringify({
+                            model_hash: modelHash,
+                            short_id: shortId
+                        })
+                    });
+                    
+                    const result = await response.json();
+                    
+                    if (result.success) {
+                        // Success: remove the media wrapper from the DOM
+                        mediaWrapper.style.opacity = '0';
+                        mediaWrapper.style.height = '0';
+                        mediaWrapper.style.transition = 'opacity 0.3s ease, height 0.3s ease 0.3s';
+                        
+                        setTimeout(() => {
+                            mediaWrapper.remove();
+                        }, 600);
+                        
+                        // Show success toast
+                        showToast('Example image deleted', 'success');
+
+                        // Create an update object with only the necessary properties
+                        const updateData = {
+                            civitai: {
+                                customImages: result.custom_images || []
+                            }
+                        };
+                        
+                        // Update the item in the virtual scroller
+                        state.virtualScroller.updateSingleItem(result.model_file_path, updateData);
+                    } else {
+                        // Show error message
+                        showToast(result.error || 'Failed to delete example image', 'error');
+                        
+                        // Reset button state
+                        this.disabled = false;
+                        this.dataset.state = 'initial';
+                        this.classList.remove('confirm');
+                        this.innerHTML = '<i class="fas fa-trash-alt"></i>';
+                        this.title = 'Delete this example';
+                    }
+                } catch (error) {
+                    console.error('Error deleting example image:', error);
+                    showToast('Failed to delete example image', 'error');
+                    
+                    // Reset button state
+                    this.disabled = false;
+                    this.dataset.state = 'initial';
+                    this.classList.remove('confirm');
+                    this.innerHTML = '<i class="fas fa-trash-alt"></i>';
+                    this.title = 'Delete this example';
+                }
+            }
+        });
+    });
+    
+    // Initialize set preview buttons
+    initSetPreviewHandlers(container);
+    
+    // Media control visibility is now handled in initMetadataPanelHandlers
+    // Any click handlers or other functionality can still be added here
+}
+
+/**
+ * Initialize set preview button handlers
+ * @param {HTMLElement} container - Container with media wrappers
+ */
+function initSetPreviewHandlers(container) {
+    const previewButtons = container.querySelectorAll('.set-preview-btn');
+    const modelType = state.currentPageType == 'loras' ? 'lora' : 'checkpoint';
+    
+    previewButtons.forEach(btn => {
+        btn.addEventListener('click', async function(e) {
+            e.stopPropagation();
+            
+            // Show loading state
+            this.innerHTML = '<i class="fas fa-spinner fa-spin"></i>';
+            this.disabled = true;
+            
+            try {
+                // Get the model file path from showcase section data attribute
+                const showcaseSection = document.querySelector('.showcase-section');
+                const modelHash = showcaseSection?.dataset.modelHash;
+                const modelFilePath = showcaseSection?.dataset.filepath;
+                
+                if (!modelFilePath) {
+                    throw new Error('Could not determine model file path');
+                }
+                
+                // Get the media wrapper and media element
+                const mediaWrapper = this.closest('.media-wrapper');
+                const mediaElement = mediaWrapper.querySelector('img, video');
+                
+                if (!mediaElement) {
+                    throw new Error('Media element not found');
+                }
+                
+                // Get NSFW level from the wrapper or media element
+                const nsfwLevel = parseInt(mediaWrapper.dataset.nsfwLevel || mediaElement.dataset.nsfwLevel || '0', 10);
+                
+                // Get local file path if available
+                const useLocalFile = mediaElement.dataset.localSrc && !mediaElement.dataset.localSrc.includes('undefined');
+                
+                if (useLocalFile) {
+                    // We have a local file, use it directly
+                    const response = await fetch(mediaElement.dataset.localSrc);
+                    const blob = await response.blob();
+                    const file = new File([blob], 'preview.jpg', { type: blob.type });
+                    
+                    // Use the existing baseModelApi uploadPreview method with nsfw level
+                    await uploadPreview(modelFilePath, file, modelType, nsfwLevel);
+                } else {
+                    // We need to download the remote file first
+                    const response = await fetch(mediaElement.src);
+                    const blob = await response.blob();
+                    const file = new File([blob], 'preview.jpg', { type: blob.type });
+                    
+                    // Use the existing baseModelApi uploadPreview method with nsfw level
+                    await uploadPreview(modelFilePath, file, modelType, nsfwLevel);
+                }
+            } catch (error) {
+                console.error('Error setting preview:', error);
+                showToast('Failed to set preview image', 'error');
+            } finally {
+                // Restore button state
+                this.innerHTML = '<i class="fas fa-image"></i>';
+                this.disabled = false;
+            }
+        });
+    });
+}
+
+/**
+ * Position media controls within the actual rendered media rectangle
+ * @param {HTMLElement} mediaWrapper - The wrapper containing the media and controls
+ */
+export function positionMediaControlsInMediaRect(mediaWrapper) {
+    const mediaElement = mediaWrapper.querySelector('img, video');
+    const controlsElement = mediaWrapper.querySelector('.media-controls');
+    
+    if (!mediaElement || !controlsElement) return;
+    
+    // Get wrapper dimensions
+    const wrapperRect = mediaWrapper.getBoundingClientRect();
+    
+    // Calculate the actual rendered media rectangle
+    const mediaRect = getRenderedMediaRect(
+        mediaElement, 
+        wrapperRect.width, 
+        wrapperRect.height
+    );
+    
+    // Calculate the position for controls - place them inside the actual media area
+    const padding = 8; // Padding from the edge of the media
+    
+    // Position at top-right inside the actual media rectangle
+    controlsElement.style.top = `${mediaRect.top + padding}px`;
+    controlsElement.style.right = `${wrapperRect.width - mediaRect.right + padding}px`;
+    
+    // Also position any toggle blur buttons in the same way but on the left
+    const toggleBlurBtn = mediaWrapper.querySelector('.toggle-blur-btn');
+    if (toggleBlurBtn) {
+        toggleBlurBtn.style.top = `${mediaRect.top + padding}px`;
+        toggleBlurBtn.style.left = `${mediaRect.left + padding}px`;
+    }
+}
+
+/**
+ * Position all media controls in a container
+ * @param {HTMLElement} container - Container with media wrappers
+ */
+export function positionAllMediaControls(container) {
+    const mediaWrappers = container.querySelectorAll('.media-wrapper');
+    mediaWrappers.forEach(wrapper => {
+        positionMediaControlsInMediaRect(wrapper);
+    });
+}

static/js/components/shared/showcase/MetadataPanel.js

@@ -0,0 +1,83 @@
+/**
+ * MetadataPanel.js
+ * Generates metadata panels for showcase media items
+ */
+
+/**
+ * Generate metadata panel HTML
+ * @param {boolean} hasParams - Whether there are generation parameters
+ * @param {boolean} hasPrompts - Whether there are prompts
+ * @param {string} prompt - Prompt text
+ * @param {string} negativePrompt - Negative prompt text
+ * @param {string} size - Image size
+ * @param {string} seed - Generation seed
+ * @param {string} model - Model used
+ * @param {string} steps - Steps used
+ * @param {string} sampler - Sampler used
+ * @param {string} cfgScale - CFG scale
+ * @param {string} clipSkip - Clip skip value
+ * @returns {string} HTML content
+ */
+export function generateMetadataPanel(hasParams, hasPrompts, prompt, negativePrompt, size, seed, model, steps, sampler, cfgScale, clipSkip) {
+    // Create unique IDs for prompt copying
+    const promptIndex = Math.random().toString(36).substring(2, 15);
+    const negPromptIndex = Math.random().toString(36).substring(2, 15);
+    
+    let content = '<div class="image-metadata-panel"><div class="metadata-content">';
+    
+    if (hasParams) {
+        content += `
+            <div class="params-tags">
+                ${size ? `<div class="param-tag"><span class="param-name">Size:</span><span class="param-value">${size}</span></div>` : ''}
+                ${seed ? `<div class="param-tag"><span class="param-name">Seed:</span><span class="param-value">${seed}</span></div>` : ''}
+                ${model ? `<div class="param-tag"><span class="param-name">Model:</span><span class="param-value">${model}</span></div>` : ''}
+                ${steps ? `<div class="param-tag"><span class="param-name">Steps:</span><span class="param-value">${steps}</span></div>` : ''}
+                ${sampler ? `<div class="param-tag"><span class="param-name">Sampler:</span><span class="param-value">${sampler}</span></div>` : ''}
+                ${cfgScale ? `<div class="param-tag"><span class="param-name">CFG:</span><span class="param-value">${cfgScale}</span></div>` : ''}
+                ${clipSkip ? `<div class="param-tag"><span class="param-name">Clip Skip:</span><span class="param-value">${clipSkip}</span></div>` : ''}
+            </div>
+        `;
+    }
+    
+    if (!hasParams && !hasPrompts) {
+        content += `
+            <div class="no-metadata-message">
+                <i class="fas fa-info-circle"></i>
+                <span>No generation parameters available</span>
+            </div>
+        `;
+    }
+    
+    if (prompt) {
+        content += `
+            <div class="metadata-row prompt-row">
+                <span class="metadata-label">Prompt:</span>
+                <div class="metadata-prompt-wrapper">
+                    <div class="metadata-prompt">${prompt}</div>
+                    <button class="copy-prompt-btn" data-prompt-index="${promptIndex}">
+                        <i class="fas fa-copy"></i>
+                    </button>
+                </div>
+            </div>
+            <div class="hidden-prompt" id="prompt-${promptIndex}" style="display:none;">${prompt}</div>
+        `;
+    }
+    
+    if (negativePrompt) {
+        content += `
+            <div class="metadata-row prompt-row">
+                <span class="metadata-label">Negative Prompt:</span>
+                <div class="metadata-prompt-wrapper">
+                    <div class="metadata-prompt">${negativePrompt}</div>
+                    <button class="copy-prompt-btn" data-prompt-index="${negPromptIndex}">
+                        <i class="fas fa-copy"></i>
+                    </button>
+                </div>
+            </div>
+            <div class="hidden-prompt" id="prompt-${negPromptIndex}" style="display:none;">${negativePrompt}</div>
+        `;
+    }
+    
+    content += '</div></div>';
+    return content;
+}

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

@@ -0,0 +1,586 @@
+/**
+ * ShowcaseView.js
+ * Shared showcase component for displaying examples in model modals (Lora/Checkpoint)
+ */
+import { showToast } from '../../../utils/uiHelpers.js';
+import { state } from '../../../state/index.js';
+import { NSFW_LEVELS } from '../../../utils/constants.js';
+import { 
+    initLazyLoading,
+    initNsfwBlurHandlers, 
+    initMetadataPanelHandlers,
+    initMediaControlHandlers,
+    positionAllMediaControls
+} from './MediaUtils.js';
+import { generateMetadataPanel } from './MetadataPanel.js';
+import { generateImageWrapper, generateVideoWrapper } from './MediaRenderers.js';
+
+/**
+ * Load example images asynchronously
+ * @param {Array} images - Array of image objects (both regular and custom)
+ * @param {string} modelHash - Model hash for fetching local files
+ */
+export async function loadExampleImages(images, modelHash) {
+    try {
+        const showcaseTab = document.getElementById('showcase-tab');
+        if (!showcaseTab) return;
+        
+        // First fetch local example files
+        let localFiles = [];
+
+        try {
+            const endpoint = '/api/example-image-files';
+            const params = `model_hash=${modelHash}`;
+            
+            const response = await fetch(`${endpoint}?${params}`);
+            const result = await response.json();
+            
+            if (result.success) {
+                localFiles = result.files;
+            }
+        } catch (error) {
+            console.error("Failed to get example files:", error);
+        }
+        
+        // Then render with both remote images and local files
+        showcaseTab.innerHTML = renderShowcaseContent(images, localFiles);
+        
+        // Re-initialize the showcase event listeners
+        const carousel = showcaseTab.querySelector('.carousel');
+        if (carousel && !carousel.classList.contains('collapsed')) {
+            initShowcaseContent(carousel);
+        }
+        
+        // Initialize the example import functionality
+        initExampleImport(modelHash, showcaseTab);
+    } catch (error) {
+        console.error('Error loading example images:', error);
+        const showcaseTab = document.getElementById('showcase-tab');
+        if (showcaseTab) {
+            showcaseTab.innerHTML = `
+                <div class="error-message">
+                    <i class="fas fa-exclamation-circle"></i>
+                    Error loading example images
+                </div>
+            `;
+        }
+    }
+}
+
+/**
+ * Render showcase content
+ * @param {Array} images - Array of images/videos to show
+ * @param {Array} exampleFiles - Local example files
+ * @param {Object} options - Options for rendering
+ * @returns {string} HTML content
+ */
+export function renderShowcaseContent(images, exampleFiles = []) {
+    if (!images?.length) {
+        // Show empty state with import interface
+        return renderImportInterface(true);
+    }
+    
+    // Filter images based on SFW setting
+    const showOnlySFW = state.settings.show_only_sfw;
+    let filteredImages = images;
+    let hiddenCount = 0;
+    
+    if (showOnlySFW) {
+        filteredImages = images.filter(img => {
+            const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
+            const isSfw = nsfwLevel < NSFW_LEVELS.R;
+            if (!isSfw) hiddenCount++;
+            return isSfw;
+        });
+    }
+    
+    // Show message if no images are available after filtering
+    if (filteredImages.length === 0) {
+        return `
+            <div class="no-examples">
+                <p>All example images are filtered due to NSFW content settings</p>
+                <p class="nsfw-filter-info">Your settings are currently set to show only safe-for-work content</p>
+                <p>You can change this in Settings <i class="fas fa-cog"></i></p>
+            </div>
+        `;
+    }
+    
+    // Show hidden content notification if applicable
+    const hiddenNotification = hiddenCount > 0 ? 
+        `<div class="nsfw-filter-notification">
+            <i class="fas fa-eye-slash"></i> ${hiddenCount} ${hiddenCount === 1 ? 'image' : 'images'} hidden due to SFW-only setting
+        </div>` : '';
+    
+    return `
+        <div class="scroll-indicator" onclick="toggleShowcase(this)">
+            <i class="fas fa-chevron-down"></i>
+            <span>Scroll or click to show ${filteredImages.length} examples</span>
+        </div>
+        <div class="carousel collapsed">
+            ${hiddenNotification}
+            <div class="carousel-container">
+                ${filteredImages.map((img, index) => renderMediaItem(img, index, exampleFiles)).join('')}
+            </div>
+            
+            ${renderImportInterface(false)}
+        </div>
+    `;
+}
+
+/**
+ * Render a single media item (image or video)
+ * @param {Object} img - Image/video metadata
+ * @param {number} index - Index in the array
+ * @param {Array} exampleFiles - Local files
+ * @returns {string} HTML for the media item
+ */
+function renderMediaItem(img, index, exampleFiles) {
+    // Find matching file in our list of actual files
+    let localFile = findLocalFile(img, index, exampleFiles);
+    
+    const remoteUrl = img.url || '';
+    const localUrl = localFile ? localFile.path : '';
+    const isVideo = localFile ? localFile.is_video : 
+                  remoteUrl.endsWith('.mp4') || remoteUrl.endsWith('.webm');
+    
+    // Calculate appropriate aspect ratio
+    const aspectRatio = (img.height / img.width) * 100;
+    const containerWidth = 800; // modal content maximum width
+    const minHeightPercent = 40; 
+    const maxHeightPercent = (window.innerHeight * 0.6 / containerWidth) * 100;
+    const heightPercent = Math.max(
+        minHeightPercent,
+        Math.min(maxHeightPercent, aspectRatio)
+    );
+    
+    // Check if media should be blurred
+    const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
+    const shouldBlur = state.settings.blurMatureContent && nsfwLevel > NSFW_LEVELS.PG13;
+    
+    // Determine NSFW warning text based on level
+    let nsfwText = "Mature Content";
+    if (nsfwLevel >= NSFW_LEVELS.XXX) {
+        nsfwText = "XXX-rated Content";
+    } else if (nsfwLevel >= NSFW_LEVELS.X) {
+        nsfwText = "X-rated Content";
+    } else if (nsfwLevel >= NSFW_LEVELS.R) {
+        nsfwText = "R-rated Content";
+    }
+    
+    // Extract metadata from the image
+    const meta = img.meta || {};
+    const prompt = meta.prompt || '';
+    const negativePrompt = meta.negative_prompt || meta.negativePrompt || '';
+    const size = meta.Size || `${img.width}x${img.height}`;
+    const seed = meta.seed || '';
+    const model = meta.Model || '';
+    const steps = meta.steps || '';
+    const sampler = meta.sampler || '';
+    const cfgScale = meta.cfgScale || '';
+    const clipSkip = meta.clipSkip || '';
+    
+    // Check if we have any meaningful generation parameters
+    const hasParams = seed || model || steps || sampler || cfgScale || clipSkip;
+    const hasPrompts = prompt || negativePrompt;
+    
+    // Create metadata panel content
+    const metadataPanel = generateMetadataPanel(
+        hasParams, hasPrompts, 
+        prompt, negativePrompt, 
+        size, seed, model, steps, sampler, cfgScale, clipSkip
+    );
+    
+    // Determine if this is a custom image (has id property)
+    const isCustomImage = Boolean(img.id);
+    
+    // Create the media control buttons HTML
+    const mediaControlsHtml = `
+        <div class="media-controls">
+            <button class="media-control-btn set-preview-btn" title="Set as preview">
+                <i class="fas fa-image"></i>
+            </button>
+            <button class="media-control-btn example-delete-btn ${!isCustomImage ? 'disabled' : ''}" 
+                    title="${isCustomImage ? 'Delete this example' : 'Only custom images can be deleted'}" 
+                    data-short-id="${img.id || ''}" 
+                    ${!isCustomImage ? 'disabled' : ''}>
+                <i class="fas fa-trash-alt"></i>
+                <i class="fas fa-check confirm-icon"></i>
+            </button>
+        </div>
+    `;
+    
+    // Generate the appropriate wrapper based on media type
+    if (isVideo) {
+        return generateVideoWrapper(
+            img, heightPercent, shouldBlur, nsfwText, metadataPanel, 
+            localUrl, remoteUrl, mediaControlsHtml
+        );
+    }
+    
+    return generateImageWrapper(
+        img, heightPercent, shouldBlur, nsfwText, metadataPanel, 
+        localUrl, remoteUrl, mediaControlsHtml
+    );
+}
+
+/**
+ * Find the matching local file for an image
+ * @param {Object} img - Image metadata
+ * @param {number} index - Image index
+ * @param {Array} exampleFiles - Array of local files
+ * @returns {Object|null} Matching local file or null
+ */
+function findLocalFile(img, index, exampleFiles) {
+    if (!exampleFiles || exampleFiles.length === 0) return null;
+    
+    let localFile = null;
+    
+    if (img.id) {
+        // This is a custom image, find by custom_<id>
+        const customPrefix = `custom_${img.id}`;
+        localFile = exampleFiles.find(file => file.name.startsWith(customPrefix));
+    } else {
+        // This is a regular image from civitai, find by index
+        localFile = exampleFiles.find(file => {
+            const match = file.name.match(/image_(\d+)\./);
+            return match && parseInt(match[1]) === index;
+        });
+        
+        // If not found by index, just use the same position in the array if available
+        if (!localFile && index < exampleFiles.length) {
+            localFile = exampleFiles[index];
+        }
+    }
+    
+    return localFile;
+}
+
+/**
+ * Render the import interface for example images
+ * @param {boolean} isEmpty - Whether there are no existing examples
+ * @returns {string} HTML content for import interface
+ */
+function renderImportInterface(isEmpty) {
+    return `
+        <div class="example-import-area ${isEmpty ? 'empty' : ''}">
+            <div class="import-container" id="exampleImportContainer">
+                <div class="import-placeholder">
+                    <i class="fas fa-cloud-upload-alt"></i>
+                    <h3>${isEmpty ? 'No example images available' : 'Add more examples'}</h3>
+                    <p>Drag & drop images or videos here</p>
+                    <p class="sub-text">or</p>
+                    <button class="select-files-btn" id="selectExampleFilesBtn">
+                        <i class="fas fa-folder-open"></i> Select Files
+                    </button>
+                    <p class="import-formats">Supported formats: jpg, png, gif, webp, mp4, webm</p>
+                </div>
+                <input type="file" id="exampleFilesInput" multiple accept="image/*,video/mp4,video/webm" style="display: none;">
+                <div class="import-progress-container" style="display: none;">
+                    <div class="import-progress">
+                        <div class="progress-bar"></div>
+                    </div>
+                    <span class="progress-text">Importing files...</span>
+                </div>
+            </div>
+        </div>
+    `;
+}
+
+/**
+ * Initialize the example import functionality
+ * @param {string} modelHash - The SHA256 hash of the model
+ * @param {Element} container - The container element for the import area
+ */
+export function initExampleImport(modelHash, container) {
+    if (!container) return;
+    
+    const importContainer = container.querySelector('#exampleImportContainer');
+    const fileInput = container.querySelector('#exampleFilesInput');
+    const selectFilesBtn = container.querySelector('#selectExampleFilesBtn');
+    
+    // Set up file selection button
+    if (selectFilesBtn) {
+        selectFilesBtn.addEventListener('click', () => {
+            fileInput.click();
+        });
+    }
+    
+    // Handle file selection
+    if (fileInput) {
+        fileInput.addEventListener('change', (e) => {
+            if (e.target.files.length > 0) {
+                handleImportFiles(Array.from(e.target.files), modelHash, importContainer);
+            }
+        });
+    }
+    
+    // Set up drag and drop
+    if (importContainer) {
+        ['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
+            importContainer.addEventListener(eventName, preventDefaults, false);
+        });
+        
+        function preventDefaults(e) {
+            e.preventDefault();
+            e.stopPropagation();
+        }
+        
+        // Highlight drop area on drag over
+        ['dragenter', 'dragover'].forEach(eventName => {
+            importContainer.addEventListener(eventName, () => {
+                importContainer.classList.add('highlight');
+            }, false);
+        });
+        
+        // Remove highlight on drag leave
+        ['dragleave', 'drop'].forEach(eventName => {
+            importContainer.addEventListener(eventName, () => {
+                importContainer.classList.remove('highlight');
+            }, false);
+        });
+        
+        // Handle dropped files
+        importContainer.addEventListener('drop', (e) => {
+            const files = Array.from(e.dataTransfer.files);
+            handleImportFiles(files, modelHash, importContainer);
+        }, false);
+    }
+}
+
+/**
+ * Handle the file import process
+ * @param {File[]} files - Array of files to import
+ * @param {string} modelHash - The SHA256 hash of the model
+ * @param {Element} importContainer - The container element for import UI
+ */
+async function handleImportFiles(files, modelHash, importContainer) {
+    // Filter for supported file types
+    const supportedImages = ['.jpg', '.jpeg', '.png', '.gif', '.webp'];
+    const supportedVideos = ['.mp4', '.webm'];
+    const supportedExtensions = [...supportedImages, ...supportedVideos];
+    
+    const validFiles = files.filter(file => {
+        const ext = '.' + file.name.split('.').pop().toLowerCase();
+        return supportedExtensions.includes(ext);
+    });
+    
+    if (validFiles.length === 0) {
+        alert('No supported files selected. Please select image or video files.');
+        return;
+    }
+    
+    try {
+        // Use FormData to upload files
+        const formData = new FormData();
+        formData.append('model_hash', modelHash);
+        
+        validFiles.forEach(file => {
+            formData.append('files', file);
+        });
+        
+        // Call API to import files
+        const response = await fetch('/api/import-example-images', {
+            method: 'POST',
+            body: formData
+        });
+        
+        const result = await response.json();
+        
+        if (!result.success) {
+            throw new Error(result.error || 'Failed to import example files');
+        }
+        
+        // Get updated local files
+        const updatedFilesResponse = await fetch(`/api/example-image-files?model_hash=${modelHash}`);
+        const updatedFilesResult = await updatedFilesResponse.json();
+        
+        if (!updatedFilesResult.success) {
+            throw new Error(updatedFilesResult.error || 'Failed to get updated file list');
+        }
+        
+        // Re-render the showcase content
+        const showcaseTab = document.getElementById('showcase-tab');
+        if (showcaseTab) {
+            // Get the updated images from the result
+            const regularImages = result.regular_images || [];
+            const customImages = result.custom_images || [];
+            // Combine both arrays for rendering
+            const allImages = [...regularImages, ...customImages];
+            showcaseTab.innerHTML = renderShowcaseContent(allImages, updatedFilesResult.files);
+            
+            // Re-initialize showcase functionality
+            const carousel = showcaseTab.querySelector('.carousel');
+            if (carousel && !carousel.classList.contains('collapsed')) {
+                initShowcaseContent(carousel);
+            }
+            
+            // Initialize the import UI for the new content
+            initExampleImport(modelHash, showcaseTab);
+            
+            showToast('Example images imported successfully', 'success');
+            
+            // Update VirtualScroller if available
+            if (state.virtualScroller && result.model_file_path) {
+                // Create an update object with only the necessary properties
+                const updateData = {
+                    civitai: {
+                        images: regularImages,
+                        customImages: customImages
+                    }
+                };
+                
+                // Update the item in the virtual scroller
+                state.virtualScroller.updateSingleItem(result.model_file_path, updateData);
+            }
+        }
+    } catch (error) {
+        console.error('Error importing examples:', error);
+        showToast('Failed to import example images', 'error');
+    }
+}
+
+/**
+ * Toggle showcase expansion
+ * @param {HTMLElement} element - The scroll indicator element
+ */
+export function toggleShowcase(element) {
+    const carousel = element.nextElementSibling;
+    const isCollapsed = carousel.classList.contains('collapsed');
+    const indicator = element.querySelector('span');
+    const icon = element.querySelector('i');
+    
+    carousel.classList.toggle('collapsed');
+    
+    if (isCollapsed) {
+        const count = carousel.querySelectorAll('.media-wrapper').length;
+        indicator.textContent = `Scroll or click to hide examples`;
+        icon.classList.replace('fa-chevron-down', 'fa-chevron-up');
+        initShowcaseContent(carousel);
+    } else {
+        const count = carousel.querySelectorAll('.media-wrapper').length;
+        indicator.textContent = `Scroll or click to show ${count} examples`;
+        icon.classList.replace('fa-chevron-up', 'fa-chevron-down');
+        
+        // Make sure any open metadata panels get closed
+        const carouselContainer = carousel.querySelector('.carousel-container');
+        if (carouselContainer) {
+            carouselContainer.style.height = '0';
+            setTimeout(() => {
+                carouselContainer.style.height = '';
+            }, 300);
+        }
+    }
+}
+
+/**
+ * Initialize all showcase content interactions
+ * @param {HTMLElement} carousel - The carousel element
+ */
+export function initShowcaseContent(carousel) {
+    if (!carousel) return;
+    
+    initLazyLoading(carousel);
+    initNsfwBlurHandlers(carousel);
+    initMetadataPanelHandlers(carousel);
+    initMediaControlHandlers(carousel);
+    positionAllMediaControls(carousel);
+    
+    // Add window resize handler
+    const resizeHandler = () => positionAllMediaControls(carousel);
+    window.removeEventListener('resize', resizeHandler);
+    window.addEventListener('resize', resizeHandler);
+    
+    // Handle images loading which might change dimensions
+    const mediaElements = carousel.querySelectorAll('img, video');
+    mediaElements.forEach(media => {
+        media.addEventListener('load', () => positionAllMediaControls(carousel));
+        if (media.tagName === 'VIDEO') {
+            media.addEventListener('loadedmetadata', () => positionAllMediaControls(carousel));
+        }
+    });
+}
+
+/**
+ * Scroll to top of modal content
+ * @param {HTMLElement} button - Back to top button
+ */
+export function scrollToTop(button) {
+    const modalContent = button.closest('.modal-content');
+    if (modalContent) {
+        modalContent.scrollTo({
+            top: 0,
+            behavior: 'smooth'
+        });
+    }
+}
+
+/**
+ * Set up showcase scroll functionality
+ * @param {string} modalId - ID of the modal element
+ */
+export function setupShowcaseScroll(modalId) {
+    // Listen for wheel events
+    document.addEventListener('wheel', (event) => {
+        const modalContent = document.querySelector(`#${modalId} .modal-content`);
+        if (!modalContent) return;
+        
+        const showcase = modalContent.querySelector('.showcase-section');
+        if (!showcase) return;
+        
+        const carousel = showcase.querySelector('.carousel');
+        const scrollIndicator = showcase.querySelector('.scroll-indicator');
+        
+        if (carousel?.classList.contains('collapsed') && event.deltaY > 0) {
+            const isNearBottom = modalContent.scrollHeight - modalContent.scrollTop - modalContent.clientHeight < 100;
+            
+            if (isNearBottom) {
+                toggleShowcase(scrollIndicator);
+                event.preventDefault();
+            }
+        }
+    }, { passive: false });
+    
+    // Use MutationObserver to set up back-to-top button when modal content is added
+    const observer = new MutationObserver((mutations) => {
+        for (const mutation of mutations) {
+            if (mutation.type === 'childList' && mutation.addedNodes.length) {
+                const modal = document.getElementById(modalId);
+                if (modal && modal.querySelector('.modal-content')) {
+                    setupBackToTopButton(modal.querySelector('.modal-content'));
+                }
+            }
+        }
+    });
+    
+    observer.observe(document.body, { childList: true, subtree: true });
+    
+    // Try to set up the button immediately in case the modal is already open
+    const modalContent = document.querySelector(`#${modalId} .modal-content`);
+    if (modalContent) {
+        setupBackToTopButton(modalContent);
+    }
+}
+
+/**
+ * Set up back-to-top button
+ * @param {HTMLElement} modalContent - Modal content element
+ */
+function setupBackToTopButton(modalContent) {
+    // Remove any existing scroll listeners to avoid duplicates
+    modalContent.onscroll = null;
+    
+    // Add new scroll listener
+    modalContent.addEventListener('scroll', () => {
+        const backToTopBtn = modalContent.querySelector('.back-to-top');
+        if (backToTopBtn) {
+            if (modalContent.scrollTop > 300) {
+                backToTopBtn.classList.add('visible');
+            } else {
+                backToTopBtn.classList.remove('visible');
+            }
+        }
+    });
+    
+    // Trigger a scroll event to check initial position
+    modalContent.dispatchEvent(new Event('scroll'));
+}

static/js/loras.js

@@ -1,6 +1,6 @@
 import { appCore } from './core.js';
 import { state } from './state/index.js';
-import { showLoraModal, toggleShowcase, scrollToTop } from './components/loraModal/index.js';
+import { showLoraModal } from './components/loraModal/index.js';
 import { loadMoreLoras } from './api/loraApi.js';
 import { updateCardsForBulkMode } from './components/LoraCard.js';
 import { bulkManager } from './managers/BulkManager.js';
@@ -43,8 +43,6 @@ class LoraPageManager {
         window.closeExcludeModal = closeExcludeModal;
         window.downloadManager = this.downloadManager;
         window.moveManager = moveManager;
-        window.toggleShowcase = toggleShowcase;
-        window.scrollToTop = scrollToTop;
         
         // Bulk operations
         window.toggleBulkMode = () => bulkManager.toggleBulkMode();

static/js/managers/BulkManager.js

@@ -36,6 +36,11 @@ export class BulkManager {
         document.addEventListener('keydown', (e) => {
             // Check if it's Ctrl+A (or Cmd+A on Mac)
             if ((e.ctrlKey || e.metaKey) && e.key === 'a') {
+                // First check if any modal is currently open - if so, don't handle Ctrl+A
+                if (modalManager.isAnyModalOpen()) {
+                    return; // Exit early - let the browser handle Ctrl+A within the modal
+                }
+
                 // Prevent default browser "Select All" behavior
                 e.preventDefault();
                 

static/js/managers/ExampleImagesManager.js

@@ -48,12 +48,6 @@ class ExampleImagesManager {
         if (collapseBtn) {
             collapseBtn.onclick = () => this.toggleProgressPanel();
         }
-        
-        // Initialize migration button handler
-        const migrateBtn = document.getElementById('exampleImagesMigrateBtn');
-        if (migrateBtn) {
-            migrateBtn.onclick = () => this.handleMigrateButton();
-        }
     }
     
     // Initialize event listeners for buttons
@@ -149,95 +143,6 @@ class ExampleImagesManager {
         }
     }
     
-    // Method to handle migrate button click
-    async handleMigrateButton() {
-        if (this.isDownloading || this.isMigrating) {
-            if (this.isPaused) {
-                // If paused, resume
-                this.resumeDownload();
-            } else {
-                showToast('Migration or download already in progress', 'info');
-            }
-            return;
-        }
-        
-        // Start migration
-        this.startMigrate();
-    }
-    
-    async startMigrate() {
-        try {
-            const outputDir = document.getElementById('exampleImagesPath').value || '';
-            
-            if (!outputDir) {
-                showToast('Please enter a download location first', 'warning');
-                return;
-            }
-            
-            // Update path in backend settings before starting migration
-            try {
-                const pathUpdateResponse = await fetch('/api/settings', {
-                    method: 'POST',
-                    headers: {
-                        'Content-Type': 'application/json'
-                    },
-                    body: JSON.stringify({
-                        example_images_path: outputDir
-                    })
-                });
-                
-                if (!pathUpdateResponse.ok) {
-                    throw new Error(`HTTP error! Status: ${pathUpdateResponse.status}`);
-                }
-            } catch (error) {
-                console.error('Failed to update example images path:', error);
-            }
-            
-            const pattern = document.getElementById('exampleImagesMigratePattern').value || '{model}.example.{index}.{ext}';
-            const optimize = document.getElementById('optimizeExampleImages').checked;
-            
-            const response = await fetch('/api/migrate-example-images', {
-                method: 'POST',
-                headers: {
-                    'Content-Type': 'application/json'
-                },
-                body: JSON.stringify({
-                    output_dir: outputDir,
-                    pattern: pattern,
-                    optimize: optimize,
-                    model_types: ['lora', 'checkpoint']
-                })
-            });
-            
-            const data = await response.json();
-            
-            if (data.success) {
-                this.isDownloading = true;
-                this.isMigrating = true;
-                this.isPaused = false;
-                this.hasShownCompletionToast = false; // Reset toast flag when starting new migration
-                this.startTime = new Date();
-                this.updateUI(data.status);
-                this.showProgressPanel();
-                this.startProgressUpdates();
-                // Update button text
-                const btnTextElement = document.getElementById('exampleDownloadBtnText');
-                if (btnTextElement) {
-                    btnTextElement.textContent = "Resume";
-                }
-                showToast('Example images migration started', 'success');
-                
-                // Close settings modal
-                modalManager.closeModal('settingsModal');
-            } else {
-                showToast(data.error || 'Failed to start migration', 'error');
-            }
-        } catch (error) {
-            console.error('Failed to start migration:', error);
-            showToast('Failed to start migration', 'error');
-        }
-    }
-    
     async checkDownloadStatus() {
         try {
             const response = await fetch('/api/example-images-status');

static/js/managers/ModalManager.js

@@ -234,6 +234,19 @@ export class ModalManager {
             });
         }
 
+        // Add exampleAccessModal registration
+        const exampleAccessModal = document.getElementById('exampleAccessModal');
+        if (exampleAccessModal) {
+            this.registerModal('exampleAccessModal', {
+                element: exampleAccessModal,
+                onClose: () => {
+                    this.getModal('exampleAccessModal').element.style.display = 'none';
+                    document.body.classList.remove('modal-open');
+                },
+                closeOnOutsideClick: true
+            });
+        }
+
         document.addEventListener('keydown', this.boundHandleEscape);
         this.initialized = true;
     }

static/js/managers/SettingsManager.js

@@ -36,11 +36,6 @@ export class SettingsManager {
         if (state.global.settings.optimizeExampleImages === undefined) {
             state.global.settings.optimizeExampleImages = true;
         }
-        
-        // Set default for useCentralizedExamples if undefined
-        if (state.global.settings.useCentralizedExamples === undefined) {
-            state.global.settings.useCentralizedExamples = true;
-        }
 
         // Convert old boolean compactMode to new displayDensity string
         if (typeof state.global.settings.displayDensity === 'undefined') {
@@ -114,14 +109,6 @@ export class SettingsManager {
             optimizeExampleImagesCheckbox.checked = state.global.settings.optimizeExampleImages || false;
         }
 
-        // Set centralized examples setting
-        const useCentralizedExamplesCheckbox = document.getElementById('useCentralizedExamples');
-        if (useCentralizedExamplesCheckbox) {
-            useCentralizedExamplesCheckbox.checked = state.global.settings.useCentralizedExamples !== false;
-            // Update dependent controls
-            this.updateExamplesControlsState();
-        }
-
         // Load default lora root
         await this.loadLoraRoots();
         
@@ -196,10 +183,6 @@ export class SettingsManager {
             state.global.settings.optimizeExampleImages = value;
         } else if (settingKey === 'compact_mode') {
             state.global.settings.compactMode = value;
-        } else if (settingKey === 'use_centralized_examples') {
-            state.global.settings.useCentralizedExamples = value;
-            // Update dependent controls state
-            this.updateExamplesControlsState();
         } else {
             // For any other settings that might be added in the future
             state.global.settings[settingKey] = value;
@@ -523,42 +506,6 @@ export class SettingsManager {
             // Add the appropriate density class
             grid.classList.add(`${density}-density`);
         }
-
-        // Apply centralized examples toggle state
-        this.updateExamplesControlsState();
-    }
-
-    // Add new method to update example control states
-    updateExamplesControlsState() {
-        const useCentralized = state.global.settings.useCentralizedExamples !== false;
-        
-        // Find all controls that require centralized mode
-        const exampleSections = document.querySelectorAll('[data-requires-centralized="true"]');
-        exampleSections.forEach(section => {
-            // Enable/disable all inputs and buttons in the section
-            const controls = section.querySelectorAll('input, button, select');
-            controls.forEach(control => {
-                control.disabled = !useCentralized;
-                
-                // Add/remove disabled class for styling
-                if (control.classList.contains('primary-btn') || control.classList.contains('secondary-btn')) {
-                    if (!useCentralized) {
-                        control.classList.add('disabled');
-                    } else {
-                        control.classList.remove('disabled');
-                    }
-                }
-            });
-            
-            // Visually show the section as disabled
-            if (!useCentralized) {
-                section.style.opacity = '0.6';
-                section.style.pointerEvents = 'none';
-            } else {
-                section.style.opacity = '';
-                section.style.pointerEvents = '';
-            }
-        });
     }
 }
 

static/js/utils/VirtualScroller.js

@@ -796,6 +796,30 @@ export class VirtualScroller {
         console.log('Virtual scroller enabled');
     }
 
+    // Helper function for deep merging objects
+    deepMerge(target, source) {
+        if (!source) return target;
+        
+        const result = { ...target };
+        
+        Object.keys(source).forEach(key => {
+            if (source[key] !== null && typeof source[key] === 'object' && !Array.isArray(source[key])) {
+                // If property exists in target and is an object, recursively merge
+                if (target[key] && typeof target[key] === 'object' && !Array.isArray(target[key])) {
+                    result[key] = this.deepMerge(target[key], source[key]);
+                } else {
+                    // Otherwise just assign the source value
+                    result[key] = source[key];
+                }
+            } else {
+                // For non-objects (including arrays), just assign the value
+                result[key] = source[key];
+            }
+        });
+        
+        return result;
+    }
+
     updateSingleItem(filePath, updatedItem) {
         if (!filePath || !updatedItem) {
             console.error('Invalid parameters for updateSingleItem');
@@ -809,8 +833,8 @@ export class VirtualScroller {
             return false;
         }
 
-        // Update the item data
-        this.items[index] = {...this.items[index], ...updatedItem};
+        // Update the item data using deep merge
+        this.items[index] = this.deepMerge(this.items[index], updatedItem);
         
         // If the item is currently rendered, update its DOM representation
         if (this.renderedItems.has(index)) {
@@ -822,6 +846,28 @@ export class VirtualScroller {
             
             // Create and render the updated element
             const updatedElement = this.createItemElement(this.items[index], index);
+            
+            // Add update indicator visual effects
+            updatedElement.classList.add('updated');
+            
+            // Add temporary update tag
+            const updateIndicator = document.createElement('div');
+            updateIndicator.className = 'update-indicator';
+            updateIndicator.textContent = 'Updated';
+            updatedElement.querySelector('.card-preview').appendChild(updateIndicator);
+            
+            // Automatically remove the updated class after animation completes
+            setTimeout(() => {
+                updatedElement.classList.remove('updated');
+            }, 1500);
+            
+            // Automatically remove the indicator after animation completes
+            setTimeout(() => {
+                if (updateIndicator && updateIndicator.parentNode) {
+                    updateIndicator.remove();
+                }
+            }, 2000);
+            
             this.renderedItems.set(index, updatedElement);
             this.gridElement.appendChild(updatedElement);
         }

static/js/utils/uiHelpers.js

@@ -441,521 +441,4 @@ export async function openExampleImagesFolder(modelHash) {
     showToast('Failed to open example images folder', 'error');
     return false;
   }
-}
-
-/**
- * Gets local URLs for example images with primary and fallback options
- * @param {Object} img - Image object
- * @param {number} index - Image index
- * @param {string} modelHash - Model hash
- * @returns {Object} - Object with primary and fallback URLs
- */
-export function getLocalExampleImageUrl(img, index, modelHash) {
-    if (!modelHash) return { primary: null, fallback: null };
-    
-    // Get remote extension
-    const remoteExt = (img.url || '').split('?')[0].split('.').pop().toLowerCase();
-    
-    // If it's a video (mp4), use that extension with no fallback
-    if (remoteExt === 'mp4') {
-        const videoUrl = `/example_images_static/${modelHash}/image_${index + 1}.mp4`;
-        return { primary: videoUrl, fallback: null };
-    }
-    
-    // For images, prepare both possible formats
-    const basePath = `/example_images_static/${modelHash}/image_${index + 1}`;
-    const webpUrl = `${basePath}.webp`;
-    const originalExtUrl = remoteExt ? `${basePath}.${remoteExt}` : `${basePath}.jpg`;
-    
-    // Check if optimization is enabled (defaults to true)
-    const optimizeImages = state.settings.optimizeExampleImages !== false;
-    
-    // Return primary and fallback URLs based on current settings
-    return {
-        primary: optimizeImages ? webpUrl : originalExtUrl,
-        fallback: optimizeImages ? originalExtUrl : webpUrl
-    };
-}
-
-/**
- * Try to load local image first, fall back to remote if local fails
- * @param {HTMLImageElement} imgElement - The image element to update
- * @param {Object} urls - Object with local URLs {primary, fallback} and remote URL
- */
-export function tryLocalImageOrFallbackToRemote(imgElement, urls) {
-    const { primary: localUrl, fallback: fallbackUrl } = urls.local || {};
-    const remoteUrl = urls.remote;
-    
-    // If no local options, use remote directly
-    if (!localUrl) {
-        imgElement.src = remoteUrl;
-        return;
-    }
-    
-    // Try primary local URL
-    const testImg = new Image();
-    testImg.onload = () => {
-        // Primary local image loaded successfully
-        imgElement.src = localUrl;
-    };
-    testImg.onerror = () => {
-        // Try fallback URL if available
-        if (fallbackUrl) {
-            const fallbackImg = new Image();
-            fallbackImg.onload = () => {
-                imgElement.src = fallbackUrl;
-            };
-            fallbackImg.onerror = () => {
-                // Both local options failed, use remote
-                imgElement.src = remoteUrl;
-            };
-            fallbackImg.src = fallbackUrl;
-        } else {
-            // No fallback, use remote
-            imgElement.src = remoteUrl;
-        }
-    };
-    testImg.src = localUrl;
-}
-
-/**
- * Try to load local video first, fall back to remote if local fails
- * @param {HTMLVideoElement} videoElement - The video element to update
- * @param {Object} urls - Object with local URLs {primary} and remote URL
- */
-export function tryLocalVideoOrFallbackToRemote(videoElement, urls) {
-    const { primary: localUrl } = urls.local || {};
-    const remoteUrl = urls.remote;
-    
-    // Only try local if we have a local path
-    if (localUrl) {
-        // Try to fetch local file headers to see if it exists
-        fetch(localUrl, { method: 'HEAD' })
-            .then(response => {
-                if (response.ok) {
-                    // Local video exists, use it
-                    videoElement.src = localUrl;
-                    const source = videoElement.querySelector('source');
-                    if (source) source.src = localUrl;
-                } else {
-                    // Local video doesn't exist, use remote
-                    videoElement.src = remoteUrl;
-                    const source = videoElement.querySelector('source');
-                    if (source) source.src = remoteUrl;
-                }
-                videoElement.load();
-            })
-            .catch(() => {
-                // Error fetching, use remote
-                videoElement.src = remoteUrl;
-                const source = videoElement.querySelector('source');
-                if (source) source.src = remoteUrl;
-                videoElement.load();
-            });
-    } else {
-        // No local path, use remote directly
-        videoElement.src = remoteUrl;
-        const source = videoElement.querySelector('source');
-        if (source) source.src = remoteUrl;
-        videoElement.load();
-    }
-}
-
-/**
- * Initialize lazy loading for images and videos in a container
- * @param {HTMLElement} container - The container with lazy-loadable elements
- */
-export function initLazyLoading(container) {
-    const lazyElements = container.querySelectorAll('.lazy');
-    
-    const lazyLoad = (element) => {
-        // Get URLs from data attributes
-        const localUrls = {
-            primary: element.dataset.localSrc || null,
-            fallback: element.dataset.localFallbackSrc || null
-        };
-        const remoteUrl = element.dataset.remoteSrc;
-        
-        const urls = {
-            local: localUrls,
-            remote: remoteUrl
-        };
-        
-        // Check if element is a video or image
-        if (element.tagName.toLowerCase() === 'video') {
-            tryLocalVideoOrFallbackToRemote(element, urls);
-        } else {
-            tryLocalImageOrFallbackToRemote(element, urls);
-        }
-        
-        element.classList.remove('lazy');
-    };
-
-    const observer = new IntersectionObserver((entries) => {
-        entries.forEach(entry => {
-            if (entry.isIntersecting) {
-                lazyLoad(entry.target);
-                observer.unobserve(entry.target);
-            }
-        });
-    });
-
-    lazyElements.forEach(element => observer.observe(element));
-}
-
-/**
- * Get the actual rendered rectangle of a media element with object-fit: contain
- * @param {HTMLElement} mediaElement - The img or video element
- * @param {number} containerWidth - Width of the container
- * @param {number} containerHeight - Height of the container
- * @returns {Object} - Rect with left, top, right, bottom coordinates
- */
-export function getRenderedMediaRect(mediaElement, containerWidth, containerHeight) {
-    // Get natural dimensions of the media
-    const naturalWidth = mediaElement.naturalWidth || mediaElement.videoWidth || mediaElement.clientWidth;
-    const naturalHeight = mediaElement.naturalHeight || mediaElement.videoHeight || mediaElement.clientHeight;
-    
-    if (!naturalWidth || !naturalHeight) {
-        // Fallback if dimensions cannot be determined
-        return { left: 0, top: 0, right: containerWidth, bottom: containerHeight };
-    }
-    
-    // Calculate aspect ratios
-    const containerRatio = containerWidth / containerHeight;
-    const mediaRatio = naturalWidth / naturalHeight;
-    
-    let renderedWidth, renderedHeight, left = 0, top = 0;
-    
-    // Apply object-fit: contain logic
-    if (containerRatio > mediaRatio) {
-        // Container is wider than media - will have empty space on sides
-        renderedHeight = containerHeight;
-        renderedWidth = renderedHeight * mediaRatio;
-        left = (containerWidth - renderedWidth) / 2;
-    } else {
-        // Container is taller than media - will have empty space top/bottom
-        renderedWidth = containerWidth;
-        renderedHeight = renderedWidth / mediaRatio;
-        top = (containerHeight - renderedHeight) / 2;
-    }
-    
-    return {
-        left,
-        top,
-        right: left + renderedWidth,
-        bottom: top + renderedHeight
-    };
-}
-
-/**
- * Initialize metadata panel interaction handlers
- * @param {HTMLElement} container - Container element with media wrappers
- */
-export function initMetadataPanelHandlers(container) {
-    const mediaWrappers = container.querySelectorAll('.media-wrapper');
-    
-    mediaWrappers.forEach(wrapper => {
-        // Get the metadata panel and media element (img or video)
-        const metadataPanel = wrapper.querySelector('.image-metadata-panel');
-        const mediaElement = wrapper.querySelector('img, video');
-        
-        if (!metadataPanel || !mediaElement) return;
-        
-        let isOverMetadataPanel = false;
-        
-        // Add event listeners to the wrapper for mouse tracking
-        wrapper.addEventListener('mousemove', (e) => {
-            // Get mouse position relative to wrapper
-            const rect = wrapper.getBoundingClientRect();
-            const mouseX = e.clientX - rect.left;
-            const mouseY = e.clientY - rect.top;
-            
-            // Get the actual displayed dimensions of the media element
-            const mediaRect = getRenderedMediaRect(mediaElement, rect.width, rect.height);
-            
-            // Check if mouse is over the actual media content
-            const isOverMedia = (
-                mouseX >= mediaRect.left && 
-                mouseX <= mediaRect.right && 
-                mouseY >= mediaRect.top && 
-                mouseY <= mediaRect.bottom
-            );
-            
-            // Show metadata panel when over media content or metadata panel itself
-            if (isOverMedia || isOverMetadataPanel) {
-                metadataPanel.classList.add('visible');
-            } else {
-                metadataPanel.classList.remove('visible');
-            }
-        });
-        
-        wrapper.addEventListener('mouseleave', () => {
-            if (!isOverMetadataPanel) {
-                metadataPanel.classList.remove('visible');
-            }
-        });
-        
-        // Add mouse enter/leave events for the metadata panel itself
-        metadataPanel.addEventListener('mouseenter', () => {
-            isOverMetadataPanel = true;
-            metadataPanel.classList.add('visible');
-        });
-        
-        metadataPanel.addEventListener('mouseleave', () => {
-            isOverMetadataPanel = false;
-            // Only hide if mouse is not over the media
-            const rect = wrapper.getBoundingClientRect();
-            const mediaRect = getRenderedMediaRect(mediaElement, rect.width, rect.height);
-            const mouseX = event.clientX - rect.left;
-            const mouseY = event.clientY - rect.top;
-            
-            const isOverMedia = (
-                mouseX >= mediaRect.left && 
-                mouseX <= mediaRect.right && 
-                mouseY >= mediaRect.top && 
-                mouseY <= mediaRect.bottom
-            );
-            
-            if (!isOverMedia) {
-                metadataPanel.classList.remove('visible');
-            }
-        });
-        
-        // Prevent events from bubbling
-        metadataPanel.addEventListener('click', (e) => {
-            e.stopPropagation();
-        });
-        
-        // Handle copy prompt buttons
-        const copyBtns = metadataPanel.querySelectorAll('.copy-prompt-btn');
-        copyBtns.forEach(copyBtn => {
-            const promptIndex = copyBtn.dataset.promptIndex;
-            const promptElement = wrapper.querySelector(`#prompt-${promptIndex}`);
-            
-            copyBtn.addEventListener('click', async (e) => {
-                e.stopPropagation();
-                
-                if (!promptElement) return;
-                
-                try {
-                    await copyToClipboard(promptElement.textContent, 'Prompt copied to clipboard');
-                } catch (err) {
-                    console.error('Copy failed:', err);
-                    showToast('Copy failed', 'error');
-                }
-            });
-        });
-        
-        // Prevent panel scroll from causing modal scroll
-        metadataPanel.addEventListener('wheel', (e) => {
-            const isAtTop = metadataPanel.scrollTop === 0;
-            const isAtBottom = metadataPanel.scrollHeight - metadataPanel.scrollTop === metadataPanel.clientHeight;
-            
-            // Only prevent default if scrolling would cause the panel to scroll
-            if ((e.deltaY < 0 && !isAtTop) || (e.deltaY > 0 && !isAtBottom)) {
-                e.stopPropagation();
-            }
-        }, { passive: true });
-    });
-}
-
-/**
- * Initialize NSFW content blur toggle handlers
- * @param {HTMLElement} container - Container element with media wrappers
- */
-export function initNsfwBlurHandlers(container) {
-    // Handle toggle blur buttons
-    const toggleButtons = container.querySelectorAll('.toggle-blur-btn');
-    toggleButtons.forEach(btn => {
-        btn.addEventListener('click', (e) => {
-            e.stopPropagation();
-            const wrapper = btn.closest('.media-wrapper');
-            const media = wrapper.querySelector('img, video');
-            const isBlurred = media.classList.toggle('blurred');
-            const icon = btn.querySelector('i');
-            
-            // Update the icon based on blur state
-            if (isBlurred) {
-                icon.className = 'fas fa-eye';
-            } else {
-                icon.className = 'fas fa-eye-slash';
-            }
-            
-            // Toggle the overlay visibility
-            const overlay = wrapper.querySelector('.nsfw-overlay');
-            if (overlay) {
-                overlay.style.display = isBlurred ? 'flex' : 'none';
-            }
-        });
-    });
-    
-    // Handle "Show" buttons in overlays
-    const showButtons = container.querySelectorAll('.show-content-btn');
-    showButtons.forEach(btn => {
-        btn.addEventListener('click', (e) => {
-            e.stopPropagation();
-            const wrapper = btn.closest('.media-wrapper');
-            const media = wrapper.querySelector('img, video');
-            media.classList.remove('blurred');
-            
-            // Update the toggle button icon
-            const toggleBtn = wrapper.querySelector('.toggle-blur-btn');
-            if (toggleBtn) {
-                toggleBtn.querySelector('i').className = 'fas fa-eye-slash';
-            }
-            
-            // Hide the overlay
-            const overlay = wrapper.querySelector('.nsfw-overlay');
-            if (overlay) {
-                overlay.style.display = 'none';
-            }
-        });
-    });
-}
-
-/**
- * Toggle showcase expansion
- * @param {HTMLElement} element - The scroll indicator element
- */
-export function toggleShowcase(element) {
-    const carousel = element.nextElementSibling;
-    const isCollapsed = carousel.classList.contains('collapsed');
-    const indicator = element.querySelector('span');
-    const icon = element.querySelector('i');
-    
-    carousel.classList.toggle('collapsed');
-    
-    if (isCollapsed) {
-        const count = carousel.querySelectorAll('.media-wrapper').length;
-        indicator.textContent = `Scroll or click to hide examples`;
-        icon.classList.replace('fa-chevron-down', 'fa-chevron-up');
-        initLazyLoading(carousel);
-        
-        // Initialize NSFW content blur toggle handlers
-        initNsfwBlurHandlers(carousel);
-        
-        // Initialize metadata panel interaction handlers
-        initMetadataPanelHandlers(carousel);
-    } else {
-        const count = carousel.querySelectorAll('.media-wrapper').length;
-        indicator.textContent = `Scroll or click to show ${count} examples`;
-        icon.classList.replace('fa-chevron-up', 'fa-chevron-down');
-        
-        // Make sure any open metadata panels get closed
-        const carouselContainer = carousel.querySelector('.carousel-container');
-        if (carouselContainer) {
-            carouselContainer.style.height = '0';
-            setTimeout(() => {
-                carouselContainer.style.height = '';
-            }, 300);
-        }
-    }
-}
-
-/**
- * Set up showcase scroll functionality
- * @param {string} modalId - ID of the modal element
- */
-export function setupShowcaseScroll(modalId) {
-    // Listen for wheel events
-    document.addEventListener('wheel', (event) => {
-        const modalContent = document.querySelector(`#${modalId} .modal-content`);
-        if (!modalContent) return;
-        
-        const showcase = modalContent.querySelector('.showcase-section');
-        if (!showcase) return;
-        
-        const carousel = showcase.querySelector('.carousel');
-        const scrollIndicator = showcase.querySelector('.scroll-indicator');
-        
-        if (carousel?.classList.contains('collapsed') && event.deltaY > 0) {
-            const isNearBottom = modalContent.scrollHeight - modalContent.scrollTop - modalContent.clientHeight < 100;
-            
-            if (isNearBottom) {
-                toggleShowcase(scrollIndicator);
-                event.preventDefault();
-            }
-        }
-    }, { passive: false });
-    
-    // Use MutationObserver to set up back-to-top button when modal content is added
-    const observer = new MutationObserver((mutations) => {
-        for (const mutation of mutations) {
-            if (mutation.type === 'childList' && mutation.addedNodes.length) {
-                const modal = document.getElementById(modalId);
-                if (modal && modal.querySelector('.modal-content')) {
-                    setupBackToTopButton(modal.querySelector('.modal-content'));
-                }
-            }
-        }
-    });
-    
-    // Start observing the document body for changes
-    observer.observe(document.body, { childList: true, subtree: true });
-    
-    // Also try to set up the button immediately in case the modal is already open
-    const modalContent = document.querySelector(`#${modalId} .modal-content`);
-    if (modalContent) {
-        setupBackToTopButton(modalContent);
-    }
-}
-
-/**
- * Set up back-to-top button
- * @param {HTMLElement} modalContent - Modal content element
- */
-export function setupBackToTopButton(modalContent) {
-    // Remove any existing scroll listeners to avoid duplicates
-    modalContent.onscroll = null;
-    
-    // Add new scroll listener
-    modalContent.addEventListener('scroll', () => {
-        const backToTopBtn = modalContent.querySelector('.back-to-top');
-        if (backToTopBtn) {
-            if (modalContent.scrollTop > 300) {
-                backToTopBtn.classList.add('visible');
-            } else {
-                backToTopBtn.classList.remove('visible');
-            }
-        }
-    });
-    
-    // Trigger a scroll event to check initial position
-    modalContent.dispatchEvent(new Event('scroll'));
-}
-
-/**
- * Scroll to top of modal content
- * @param {HTMLElement} button - Back to top button element
- */
-export function scrollToTop(button) {
-    const modalContent = button.closest('.modal-content');
-    if (modalContent) {
-        modalContent.scrollTo({
-            top: 0,
-            behavior: 'smooth'
-        });
-    }
-}
-
-/**
- * Get example image files for a specific model from the backend
- * @param {string} modelHash - The model's hash
- * @returns {Promise<Array>} Array of file objects with path and metadata
- */
-export async function getExampleImageFiles(modelHash) {
-  try {
-    const response = await fetch(`/api/example-image-files?model_hash=${modelHash}`);
-    const result = await response.json();
-    
-    if (result.success) {
-      return result.files;
-    } else {
-      console.error('Failed to get example image files:', result.error);
-      return [];
-    }
-  } catch (error) {
-    console.error('Error fetching example image files:', error);
-    return [];
-  }
 }

templates/components/modals.html

@@ -229,7 +229,7 @@
             </div>
             
             <!-- Add Cache Management Section -->
-            <div class="settings-section">
+            <!-- <div class="settings-section">
                 <h3>Cache Management</h3>
                 
                 <div class="setting-item">
@@ -249,33 +249,13 @@
                         <span class="warning-text">May cause temporary performance impact during rebuild.</span>
                     </div>
                 </div>
-            </div>
+            </div> -->
             
             <!-- Add Example Images Settings Section -->
             <div class="settings-section">
                 <h3>Example Images</h3>
                 
                 <div class="setting-item">
-                    <div class="setting-row">
-                        <div class="setting-info">
-                            <label for="useCentralizedExamples">Use Centralized Example Storage</label>
-                        </div>
-                        <div class="setting-control">
-                            <label class="toggle-switch">
-                                <input type="checkbox" id="useCentralizedExamples" checked 
-                                       onchange="settingsManager.saveToggleSetting('useCentralizedExamples', 'use_centralized_examples')">
-                                <span class="toggle-slider"></span>
-                            </label>
-                        </div>
-                    </div>
-                    <div class="input-help">
-                        When enabled (recommended), example images are stored in a central folder for better organization and performance.
-                        When disabled, only example images stored alongside models (e.g., model-name.example.0.jpg) will be shown, but download 
-                        and management features will be unavailable.
-                    </div>
-                </div>
-                
-                <div class="setting-item" data-requires-centralized="true">
                     <div class="setting-row">
                         <div class="setting-info">
                             <label for="exampleImagesPath">Download Location <i class="fas fa-sync-alt restart-required-icon" title="Requires restart"></i></label>
@@ -291,29 +271,8 @@
                         Enter the folder path where example images from Civitai will be saved
                     </div>
                 </div>
-
-                <!-- New migrate section -->
-                <div class="setting-item" data-requires-centralized="true">
-                    <div class="setting-row">
-                        <div class="setting-info">
-                            <label for="exampleImagesMigratePattern">Migrate Existing Example Images</label>
-                        </div>
-                        <div class="setting-control migrate-control">
-                            <input type="text" id="exampleImagesMigratePattern" 
-                                placeholder="{model}.example.{index}.{ext}" 
-                                value="{model}.example.{index}.{ext}" />
-                            <button id="exampleImagesMigrateBtn" class="secondary-btn">
-                                <i class="fas fa-file-import"></i> <span>Migrate</span>
-                            </button>
-                        </div>
-                    </div>
-                    <div class="input-help">
-                        Pattern to find existing example images. Use {model} for model filename, {index} for numbering, and {ext} for file extension.<br>
-                        Example patterns: "{model}.example.{index}.{ext}", "{model}_{index}.{ext}", "{model}/{model}.example.{index}.{ext}"
-                    </div>
-                </div>
                 
-                <div class="setting-item" data-requires-centralized="true">
+                <div class="setting-item">
                     <div class="setting-row">
                         <div class="setting-info">
                             <label for="optimizeExampleImages">Optimize Downloaded Images</label>
@@ -327,7 +286,7 @@
                         </div>
                     </div>
                     <div class="input-help">
-                        Optimize example images to reduce file size and improve loading speed
+                        Optimize example images to reduce file size and improve loading speed (metadata will be preserved)
                     </div>
                 </div>
             </div>
@@ -613,4 +572,32 @@
             <button class="confirm-btn" id="confirmRelinkBtn">Confirm Re-link</button>
         </div>
     </div>
+</div>
+
+<!-- Example Images Access Modal -->
+<div id="exampleAccessModal" class="modal">
+    <div class="modal-content example-access-modal">
+        <button class="close" onclick="modalManager.closeModal('exampleAccessModal')">&times;</button>
+        <h2>Local Example Images</h2>
+        <p>No local example images found for this model. View options:</p>
+
+        <div class="example-access-options">
+            <button id="downloadExamplesBtn" class="example-option-btn">
+                <i class="fas fa-cloud-download-alt"></i>
+                <span class="option-title">Download from Civitai</span>
+                <span class="option-desc">Save remote examples locally for offline use and faster loading</span>
+            </button>
+
+            <button id="importExamplesBtn" class="example-option-btn">
+                <i class="fas fa-file-import"></i>
+                <span class="option-title">Import Your Own</span>
+                <span class="option-desc">Add your own custom examples for this model</span>
+            </button>
+        </div>
+
+        <div class="modal-footer-note">
+            <i class="fas fa-info-circle"></i>
+            <span>Remote examples are still viewable in the model details even without local copies</span>
+        </div>
+    </div>
 </div>