feat: update version to 0.8.12 and enhance release notes in README

Dev

LICENSE

@@ -1,21 +1,674 @@
-MIT License
+GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
 
-Copyright (c) 2023 Will Miao
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+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    ComfyUI Lora Manager - A ComfyUI custom node for managing models
+    Copyright (C) 2025  Will Miao
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    ComfyUI Lora Manager  Copyright (C) 2025  Will Miao
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<https://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<https://www.gnu.org/licenses/why-not-lgpl.html>.

README.md

@@ -14,12 +14,29 @@ A comprehensive toolset that streamlines organizing, downloading, and applying L
 Watch this quick tutorial to learn how to use the new one-click LoRA integration feature:
 
 [![One-Click LoRA Integration Tutorial](https://img.youtube.com/vi/qS95OjX3e70/0.jpg)](https://youtu.be/qS95OjX3e70)
-[![LoRA Manager v0.8.0 - New Recipe Feature & Bulk Operations](https://img.youtube.com/vi/noN7f_ER7yo/0.jpg)](https://youtu.be/noN7f_ER7yo)
+[![LoRA Manager v0.8.10 - Checkpoint Management, Standalone Mode, and New Features!](https://img.youtube.com/vi/VKvTlCB78h4/0.jpg)](https://youtu.be/VKvTlCB78h4)
 
 ---
 
 ## Release Notes
 
+### v0.8.12
+* **Enhanced Model Discovery** - Added alphabetical navigation bar to LoRAs page for faster browsing through large collections
+* **Optimized Example Images** - Improved download logic to automatically refresh stale metadata before fetching example images
+* **Model Exclusion System** - New right-click option to exclude specific LoRAs or checkpoints from management
+* **Improved Showcase Experience** - Enhanced interaction in LoRA and checkpoint showcase areas for better usability
+
+### v0.8.11
+* **Offline Image Support** - Added functionality to download and save all model example images locally, ensuring access even when offline or if images are removed from CivitAI or the site is down
+* **Resilient Download System** - Implemented pause/resume capability with checkpoint recovery that persists through restarts or unexpected exits
+* **Bug Fixes & Stability** - Resolved various issues to enhance overall reliability and performance
+
+### v0.8.10
+* **Standalone Mode** - Run LoRA Manager independently from ComfyUI for a lightweight experience that works even with other stable diffusion interfaces
+* **Portable Edition** - New one-click portable version for easy startup and updates in standalone mode
+* **Enhanced Metadata Collection** - Added support for SamplerCustomAdvanced node in the metadata collector module
+* **Improved UI Organization** - Optimized Lora Loader node height to display up to 5 LoRAs at once with scrolling capability for larger collections
+
 ### v0.8.9
 * **Favorites System** - New functionality to bookmark your favorite LoRAs and checkpoints for quick access and better organization
 * **Enhanced UI Controls** - Increased model card button sizes for improved usability and easier interaction
@@ -140,14 +157,21 @@ Watch this quick tutorial to learn how to use the new one-click LoRA integration
 
 ## Installation
 
-### Option 1: **ComfyUI Manager** (Recommended)
+### Option 1: **ComfyUI Manager** (Recommended for ComfyUI users)
 
 1. Open **ComfyUI**.
 2. Go to **Manager > Custom Node Manager**.
 3. Search for `lora-manager`.
 4. Click **Install**.
 
-### Option 2: **Manual Installation**
+### Option 2: **Portable Standalone Edition** (No ComfyUI required)
+
+1. Download the [Portable Package](https://github.com/willmiao/ComfyUI-Lora-Manager/releases/download/v0.8.10/lora_manager_portable.7z)
+2. Copy the provided `settings.json.example` file to create a new file named `settings.json` in `comfyui-lora-manager` folder
+3. Edit `settings.json` to include your correct model folder paths and CivitAI API key
+4. Run run.bat
+
+### Option 3: **Manual Installation**
 
 ```bash
 git clone https://github.com/willmiao/ComfyUI-Lora-Manager.git
@@ -173,6 +197,68 @@ pip install -r requirements.txt
    - Paste into the Lora Loader node's text input
    - The node will automatically apply preset strength and trigger words
 
+### Filename Format Patterns for Save Image Node
+
+The Save Image Node supports dynamic filename generation using pattern codes. You can customize how your images are named using the following format patterns:
+
+#### Available Pattern Codes
+
+- `%seed%` - Inserts the generation seed number
+- `%width%` - Inserts the image width
+- `%height%` - Inserts the image height
+- `%pprompt:N%` - Inserts the positive prompt (limited to N characters)
+- `%nprompt:N%` - Inserts the negative prompt (limited to N characters)
+- `%model:N%` - Inserts the model/checkpoint name (limited to N characters)
+- `%date%` - Inserts current date/time as "yyyyMMddhhmmss"
+- `%date:FORMAT%` - Inserts date using custom format with:
+  - `yyyy` - 4-digit year
+  - `yy` - 2-digit year
+  - `MM` - 2-digit month
+  - `dd` - 2-digit day
+  - `hh` - 2-digit hour
+  - `mm` - 2-digit minute
+  - `ss` - 2-digit second
+
+#### Examples
+
+- `image_%seed%` → `image_1234567890`
+- `gen_%width%x%height%` → `gen_512x768`
+- `%model:10%_%seed%` → `dreamshape_1234567890`
+- `%date:yyyy-MM-dd%` → `2025-04-28`
+- `%pprompt:20%_%seed%` → `beautiful landscape_1234567890`
+- `%model%_%date:yyMMdd%_%seed%` → `dreamshaper_v8_250428_1234567890`
+
+You can combine multiple patterns to create detailed, organized filenames for your generated images.
+
+### Standalone Mode
+
+You can now run LoRA Manager independently from ComfyUI:
+
+1. **For ComfyUI users**:
+   - Launch ComfyUI with LoRA Manager at least once to initialize the necessary path information in the `settings.json` file.
+   - Make sure dependencies are installed: `pip install -r requirements.txt`
+   - From your ComfyUI root directory, run:
+     ```bash
+     python custom_nodes\comfyui-lora-manager\standalone.py
+     ```
+   - Access the interface at: `http://localhost:8188/loras`
+   - You can specify a different host or port with arguments:
+     ```bash
+     python custom_nodes\comfyui-lora-manager\standalone.py --host 127.0.0.1 --port 9000
+     ```
+
+2. **For non-ComfyUI users**:
+   - Copy the provided `settings.json.example` file to create a new file named `settings.json`
+   - Edit `settings.json` to include your correct model folder paths and CivitAI API key
+   - Install required dependencies: `pip install -r requirements.txt`
+   - Run standalone mode:
+     ```bash
+     python standalone.py
+     ```
+   - Access the interface through your browser at: `http://localhost:8188/loras`
+
+This standalone mode provides a lightweight option for managing your model and recipe collection without needing to run the full ComfyUI environment, making it useful even for users who primarily use other stable diffusion interfaces.
+
 ---
 
 ## Contributing
@@ -203,6 +289,8 @@ If you find this project helpful, consider supporting its development:
 
 [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/pixelpawsai)
 
+WeChat: [Click to view QR code](https://raw.githubusercontent.com/willmiao/ComfyUI-Lora-Manager/main/static/images/wechat-qr.webp)
+
 ## 💬 Community
 
 Join our Discord community for support, discussions, and updates:

py/config.py

@@ -3,6 +3,11 @@ import platform
 import folder_paths # type: ignore
 from typing import List
 import logging
+import sys
+import json
+
+# Check if running in standalone mode
+standalone_mode = 'nodes' not in sys.modules
 
 logger = logging.getLogger(__name__)
 
@@ -18,9 +23,46 @@ class Config:
         self._route_mappings = {}
         self.loras_roots = self._init_lora_paths()
         self.checkpoints_roots = self._init_checkpoint_paths()
-        self.temp_directory = folder_paths.get_temp_directory()
         # 在初始化时扫描符号链接
         self._scan_symbolic_links()
+        
+        if not standalone_mode:
+            # Save the paths to settings.json when running in ComfyUI mode
+            self.save_folder_paths_to_settings()
+
+    def save_folder_paths_to_settings(self):
+        """Save folder paths to settings.json for standalone mode to use later"""
+        try:
+            # Check if we're running in ComfyUI mode (not standalone)
+            if hasattr(folder_paths, "get_folder_paths") and not isinstance(folder_paths, type):
+                # Get all relevant paths
+                lora_paths = folder_paths.get_folder_paths("loras")
+                checkpoint_paths = folder_paths.get_folder_paths("checkpoints")
+                diffuser_paths = folder_paths.get_folder_paths("diffusers")
+                unet_paths = folder_paths.get_folder_paths("unet")
+                
+                # Load existing settings
+                settings_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'settings.json')
+                settings = {}
+                if os.path.exists(settings_path):
+                    with open(settings_path, 'r', encoding='utf-8') as f:
+                        settings = json.load(f)
+                
+                # Update settings with paths
+                settings['folder_paths'] = {
+                    'loras': lora_paths,
+                    'checkpoints': checkpoint_paths,
+                    'diffusers': diffuser_paths,
+                    'unet': unet_paths
+                }
+                
+                # Save settings
+                with open(settings_path, 'w', encoding='utf-8') as f:
+                    json.dump(settings, f, indent=2)
+                
+                logger.info("Saved folder paths to settings.json")
+        except Exception as e:
+            logger.warning(f"Failed to save folder paths: {e}")
 
     def _is_link(self, path: str) -> bool:
         try:
@@ -103,58 +145,66 @@ class Config:
 
     def _init_lora_paths(self) -> List[str]:
         """Initialize and validate LoRA paths from ComfyUI settings"""
-        raw_paths = folder_paths.get_folder_paths("loras")
-        
-        # Normalize and resolve symlinks, store mapping from resolved -> original
-        path_map = {}
-        for path in raw_paths:
-            if os.path.exists(path):
-                real_path = os.path.normpath(os.path.realpath(path)).replace(os.sep, '/')
-                path_map[real_path] = path_map.get(real_path, path.replace(os.sep, "/"))  # preserve first seen
-        
-        # Now sort and use only the deduplicated real paths
-        unique_paths = sorted(path_map.values(), key=lambda p: p.lower())
-        print("Found LoRA roots:", "\n - " + "\n - ".join(unique_paths))
-        
-        if not unique_paths:
-            raise ValueError("No valid loras folders found in ComfyUI configuration")
-        
-        for original_path in unique_paths:
-            real_path = os.path.normpath(os.path.realpath(original_path)).replace(os.sep, '/')
-            if real_path != original_path:
-                self.add_path_mapping(original_path, real_path)
-        
-        return unique_paths
-
+        try:
+            raw_paths = folder_paths.get_folder_paths("loras")
+            
+            # Normalize and resolve symlinks, store mapping from resolved -> original
+            path_map = {}
+            for path in raw_paths:
+                if os.path.exists(path):
+                    real_path = os.path.normpath(os.path.realpath(path)).replace(os.sep, '/')
+                    path_map[real_path] = path_map.get(real_path, path.replace(os.sep, "/"))  # preserve first seen
+            
+            # Now sort and use only the deduplicated real paths
+            unique_paths = sorted(path_map.values(), key=lambda p: p.lower())
+            logger.info("Found LoRA roots:" + ("\n - " + "\n - ".join(unique_paths) if unique_paths else "[]"))
+            
+            if not unique_paths:
+                logger.warning("No valid loras folders found in ComfyUI configuration")
+                return []
+            
+            for original_path in unique_paths:
+                real_path = os.path.normpath(os.path.realpath(original_path)).replace(os.sep, '/')
+                if real_path != original_path:
+                    self.add_path_mapping(original_path, real_path)
+            
+            return unique_paths
+        except Exception as e:
+            logger.warning(f"Error initializing LoRA paths: {e}")
+            return []
 
     def _init_checkpoint_paths(self) -> List[str]:
         """Initialize and validate checkpoint paths from ComfyUI settings"""
-        # Get checkpoint paths from folder_paths
-        checkpoint_paths = folder_paths.get_folder_paths("checkpoints")
-        diffusion_paths = folder_paths.get_folder_paths("diffusers")
-        unet_paths = folder_paths.get_folder_paths("unet")
-        
-        # Combine all checkpoint-related paths
-        all_paths = checkpoint_paths + diffusion_paths + unet_paths
-        
-        # Filter and normalize paths
-        paths = sorted(set(path.replace(os.sep, "/") 
-                for path in all_paths 
-                if os.path.exists(path)), key=lambda p: p.lower())
-        
-        print("Found checkpoint roots:", paths)
-        
-        if not paths:
-            logger.warning("No valid checkpoint folders found in ComfyUI configuration")
+        try:
+            # Get checkpoint paths from folder_paths
+            checkpoint_paths = folder_paths.get_folder_paths("checkpoints")
+            diffusion_paths = folder_paths.get_folder_paths("diffusers")
+            unet_paths = folder_paths.get_folder_paths("unet")
+            
+            # Combine all checkpoint-related paths
+            all_paths = checkpoint_paths + diffusion_paths + unet_paths
+            
+            # Filter and normalize paths
+            paths = sorted(set(path.replace(os.sep, "/") 
+                    for path in all_paths 
+                    if os.path.exists(path)), key=lambda p: p.lower())
+            
+            logger.info("Found checkpoint roots:" + ("\n - " + "\n - ".join(paths) if paths else "[]"))
+            
+            if not paths:
+                logger.warning("No valid checkpoint folders found in ComfyUI configuration")
+                return []
+            
+            # 初始化路径映射，与 LoRA 路径处理方式相同
+            for path in paths:
+                real_path = os.path.normpath(os.path.realpath(path)).replace(os.sep, '/')
+                if real_path != path:
+                    self.add_path_mapping(path, real_path)
+            
+            return paths
+        except Exception as e:
+            logger.warning(f"Error initializing checkpoint paths: {e}")
             return []
-        
-        # 初始化路径映射，与 LoRA 路径处理方式相同
-        for path in paths:
-            real_path = os.path.normpath(os.path.realpath(path)).replace(os.sep, '/')
-            if real_path != path:
-                self.add_path_mapping(path, real_path)
-        
-        return paths
 
     def get_preview_static_url(self, preview_path: str) -> str:
         """Convert local preview path to static URL"""

py/lora_manager.py

@@ -6,12 +6,18 @@ from .routes.api_routes import ApiRoutes
 from .routes.recipe_routes import RecipeRoutes
 from .routes.checkpoints_routes import CheckpointsRoutes
 from .routes.update_routes import UpdateRoutes
-from .routes.usage_stats_routes import UsageStatsRoutes
+from .routes.misc_routes import MiscRoutes
 from .services.service_registry import ServiceRegistry
+from .services.settings_manager import settings
 import logging
+import sys
+import os
 
 logger = logging.getLogger(__name__)
 
+# Check if we're in standalone mode
+STANDALONE_MODE = 'nodes' not in sys.modules
+
 class LoraManager:
     """Main entry point for LoRA Manager plugin"""
     
@@ -20,8 +26,18 @@ class LoraManager:
         """Initialize and register all routes"""
         app = PromptServer.instance.app
 
+        # Configure aiohttp access logger to be less verbose
+        logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
+
         added_targets = set()  # Track already added target paths
         
+        # Add static route for example images if the path exists in settings
+        example_images_path = settings.get('example_images_path')
+        logger.info(f"Example images path: {example_images_path}")
+        if example_images_path and os.path.exists(example_images_path):
+            app.router.add_static('/example_images_static', example_images_path)
+            logger.info(f"Added static route for example images: /example_images_static -> {example_images_path}")
+        
         # Add static routes for each lora root
         for idx, root in enumerate(config.loras_roots, start=1):
             preview_path = f'/loras_static/root{idx}/preview'
@@ -95,7 +111,7 @@ class LoraManager:
         ApiRoutes.setup_routes(app)
         RecipeRoutes.setup_routes(app)
         UpdateRoutes.setup_routes(app)  
-        UsageStatsRoutes.setup_routes(app)  # Register usage stats routes
+        MiscRoutes.setup_routes(app)  # Register miscellaneous routes
         
         # Schedule service initialization 
         app.on_startup.append(lambda app: cls._initialize_services())
@@ -108,6 +124,9 @@ class LoraManager:
     async def _initialize_services(cls):
         """Initialize all services using the ServiceRegistry"""
         try:
+            # Ensure aiohttp access logger is configured with reduced verbosity
+            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()
             
@@ -137,6 +156,12 @@ class LoraManager:
             # Initialize recipe scanner if needed
             recipe_scanner = await ServiceRegistry.get_recipe_scanner()
             
+            # Initialize metadata collector if not in standalone mode
+            if not STANDALONE_MODE:
+                from .metadata_collector import init as init_metadata
+                init_metadata()
+                logger.debug("Metadata collector initialized")
+            
             # Create low-priority initialization tasks
             asyncio.create_task(lora_scanner.initialize_in_background(), name='lora_cache_init')
             asyncio.create_task(checkpoint_scanner.initialize_in_background(), name='checkpoint_cache_init')

py/metadata_collector/__init__.py

@@ -1,18 +1,32 @@
 import os
 import importlib
-from .metadata_hook import MetadataHook
-from .metadata_registry import MetadataRegistry
+import sys
 
-def init():
-    # Install hooks to collect metadata during execution
-    MetadataHook.install()
-    
-    # Initialize registry
-    registry = MetadataRegistry()
-    
-    print("ComfyUI Metadata Collector initialized")
-    
-def get_metadata(prompt_id=None):
-    """Helper function to get metadata from the registry"""
-    registry = MetadataRegistry()
-    return registry.get_metadata(prompt_id)
+# Check if running in standalone mode
+standalone_mode = 'nodes' not in sys.modules
+
+if not standalone_mode:
+    from .metadata_hook import MetadataHook
+    from .metadata_registry import MetadataRegistry
+
+    def init():
+        # Install hooks to collect metadata during execution
+        MetadataHook.install()
+        
+        # Initialize registry
+        registry = MetadataRegistry()
+        
+        print("ComfyUI Metadata Collector initialized")
+        
+    def get_metadata(prompt_id=None):
+        """Helper function to get metadata from the registry"""
+        registry = MetadataRegistry()
+        return registry.get_metadata(prompt_id)
+else:
+    # Standalone mode - provide dummy implementations
+    def init():
+        print("ComfyUI Metadata Collector disabled in standalone mode")
+        
+    def get_metadata(prompt_id=None):
+        """Dummy implementation for standalone mode"""
+        return {}

py/metadata_collector/metadata_processor.py

@@ -1,4 +1,8 @@
 import json
+import sys
+
+# Check if running in standalone mode
+standalone_mode = 'nodes' not in sys.modules
 
 from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE
 
@@ -7,11 +11,21 @@ class MetadataProcessor:
     
     @staticmethod
     def find_primary_sampler(metadata):
-        """Find the primary KSampler node (with denoise=1)"""
+        """Find the primary KSampler node (with highest denoise value)"""
         primary_sampler = None
         primary_sampler_id = None
+        max_denoise = -1  # Track the highest denoise value
         
-        # First, check for KSamplerAdvanced with add_noise="enable"
+        # First, check for SamplerCustomAdvanced
+        prompt = metadata.get("current_prompt")
+        if prompt and prompt.original_prompt:
+            for node_id, node_info in prompt.original_prompt.items():
+                if node_info.get("class_type") == "SamplerCustomAdvanced":
+                    # Found a SamplerCustomAdvanced node
+                    if node_id in metadata.get(SAMPLING, {}):
+                        return node_id, metadata[SAMPLING][node_id]
+        
+        # Next, check for KSamplerAdvanced with add_noise="enable"
         for node_id, sampler_info in metadata.get(SAMPLING, {}).items():
             parameters = sampler_info.get("parameters", {})
             add_noise = parameters.get("add_noise")
@@ -22,17 +36,17 @@ class MetadataProcessor:
                 primary_sampler_id = node_id
                 break
         
-        # If no KSamplerAdvanced found, fall back to traditional KSampler with denoise=1
+        # If no specialized sampler found, find the sampler with highest denoise value
         if primary_sampler is None:
             for node_id, sampler_info in metadata.get(SAMPLING, {}).items():
                 parameters = sampler_info.get("parameters", {})
                 denoise = parameters.get("denoise")
                 
-                # If denoise is 1.0, this is likely the primary sampler
-                if denoise == 1.0 or denoise == 1:
+                # If denoise exists and is higher than current max, use this sampler
+                if denoise is not None and denoise > max_denoise:
+                    max_denoise = denoise
                     primary_sampler = sampler_info
                     primary_sampler_id = node_id
-                    break
                 
         return primary_sampler_id, primary_sampler
     
@@ -152,62 +166,77 @@ class MetadataProcessor:
             
             # Trace connections from the primary sampler
             if prompt and primary_sampler_id:
-                # Trace positive prompt - look specifically for CLIPTextEncode
-                positive_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "CLIPTextEncode", max_depth=10)
-                if positive_node_id and positive_node_id in metadata.get(PROMPTS, {}):
-                    params["prompt"] = metadata[PROMPTS][positive_node_id].get("text", "")
+                # Check if this is a SamplerCustomAdvanced node
+                is_custom_advanced = False
+                if prompt.original_prompt and primary_sampler_id in prompt.original_prompt:
+                    is_custom_advanced = prompt.original_prompt[primary_sampler_id].get("class_type") == "SamplerCustomAdvanced"
                 
-                # Find any FluxGuidance nodes in the positive conditioning path
-                flux_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "FluxGuidance", max_depth=5)
-                if flux_node_id and flux_node_id in metadata.get(SAMPLING, {}):
-                    flux_params = metadata[SAMPLING][flux_node_id].get("parameters", {})
-                    params["guidance"] = flux_params.get("guidance")
+                if is_custom_advanced:
+                    # For SamplerCustomAdvanced, trace specific inputs
+                    
+                    # 1. Trace sigmas input to find BasicScheduler
+                    scheduler_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "sigmas", "BasicScheduler", max_depth=5)
+                    if scheduler_node_id and scheduler_node_id in metadata.get(SAMPLING, {}):
+                        scheduler_params = metadata[SAMPLING][scheduler_node_id].get("parameters", {})
+                        params["steps"] = scheduler_params.get("steps")
+                        params["scheduler"] = scheduler_params.get("scheduler")
+                    
+                    # 2. Trace sampler input to find KSamplerSelect
+                    sampler_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "sampler", "KSamplerSelect", max_depth=5)
+                    if sampler_node_id and sampler_node_id in metadata.get(SAMPLING, {}):
+                        sampler_params = metadata[SAMPLING][sampler_node_id].get("parameters", {})
+                        params["sampler"] = sampler_params.get("sampler_name")
+                    
+                    # 3. Trace guider input for FluxGuidance and CLIPTextEncode
+                    guider_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "guider", max_depth=5)
+                    if guider_node_id:
+                        # Look for FluxGuidance along the guider path
+                        flux_node_id = MetadataProcessor.trace_node_input(prompt, guider_node_id, "conditioning", "FluxGuidance", max_depth=5)
+                        if flux_node_id and flux_node_id in metadata.get(SAMPLING, {}):
+                            flux_params = metadata[SAMPLING][flux_node_id].get("parameters", {})
+                            params["guidance"] = flux_params.get("guidance")
+                        
+                        # Find CLIPTextEncode for positive prompt (through conditioning)
+                        positive_node_id = MetadataProcessor.trace_node_input(prompt, guider_node_id, "conditioning", "CLIPTextEncode", max_depth=10)
+                        if positive_node_id and positive_node_id in metadata.get(PROMPTS, {}):
+                            params["prompt"] = metadata[PROMPTS][positive_node_id].get("text", "")
                 
-                # Trace negative prompt - look specifically for CLIPTextEncode
-                negative_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "negative", "CLIPTextEncode", max_depth=10)
-                if negative_node_id and negative_node_id in metadata.get(PROMPTS, {}):
-                    params["negative_prompt"] = metadata[PROMPTS][negative_node_id].get("text", "")
+                else:
+                    # Original tracing for standard samplers
+                    # Trace positive prompt - look specifically for CLIPTextEncode
+                    positive_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "CLIPTextEncode", max_depth=10)
+                    if positive_node_id and positive_node_id in metadata.get(PROMPTS, {}):
+                        params["prompt"] = metadata[PROMPTS][positive_node_id].get("text", "")
+                    else:
+                        # If CLIPTextEncode is not found, try to find CLIPTextEncodeFlux
+                        positive_flux_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "CLIPTextEncodeFlux", max_depth=10)
+                        if positive_flux_node_id and positive_flux_node_id in metadata.get(PROMPTS, {}):
+                            params["prompt"] = metadata[PROMPTS][positive_flux_node_id].get("text", "")
+                            
+                            # Also extract guidance value if present in the sampling data
+                            if positive_flux_node_id in metadata.get(SAMPLING, {}):
+                                flux_params = metadata[SAMPLING][positive_flux_node_id].get("parameters", {})
+                                if "guidance" in flux_params:
+                                    params["guidance"] = flux_params.get("guidance")
+                    
+                    # Find any FluxGuidance nodes in the positive conditioning path
+                    flux_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "FluxGuidance", max_depth=5)
+                    if flux_node_id and flux_node_id in metadata.get(SAMPLING, {}):
+                        flux_params = metadata[SAMPLING][flux_node_id].get("parameters", {})
+                        params["guidance"] = flux_params.get("guidance")
+                    
+                    # Trace negative prompt - look specifically for CLIPTextEncode
+                    negative_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "negative", "CLIPTextEncode", max_depth=10)
+                    if negative_node_id and negative_node_id in metadata.get(PROMPTS, {}):
+                        params["negative_prompt"] = metadata[PROMPTS][negative_node_id].get("text", "")
                 
+                # Size extraction is same for all sampler types
                 # Check if the sampler itself has size information (from latent_image)
                 if primary_sampler_id in metadata.get(SIZE, {}):
                     width = metadata[SIZE][primary_sampler_id].get("width")
                     height = metadata[SIZE][primary_sampler_id].get("height")
                     if width and height:
                         params["size"] = f"{width}x{height}"
-                else:
-                    # Fallback to the previous trace method if needed
-                    latent_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "latent_image")
-                    if latent_node_id:
-                        # Follow chain to find EmptyLatentImage node
-                        size_found = False
-                        current_node_id = latent_node_id
-                        
-                        # Limit depth to avoid infinite loops in complex workflows
-                        max_depth = 10
-                        for _ in range(max_depth):
-                            if current_node_id in metadata.get(SIZE, {}):
-                                width = metadata[SIZE][current_node_id].get("width")
-                                height = metadata[SIZE][current_node_id].get("height")
-                                if width and height:
-                                    params["size"] = f"{width}x{height}"
-                                    size_found = True
-                                    break
-                            
-                            # Try to follow the chain
-                            if prompt and prompt.original_prompt and current_node_id in prompt.original_prompt:
-                                node_info = prompt.original_prompt[current_node_id]
-                                if "inputs" in node_info:
-                                    # Look for a connection that might lead to size information
-                                    for input_name, input_value in node_info["inputs"].items():
-                                        if isinstance(input_value, list) and len(input_value) >= 2:
-                                            current_node_id = input_value[0]
-                                            break
-                                    else:
-                                        break  # No connections to follow
-                                else:
-                                    break  # No inputs to follow
-                            else:
-                                break  # Can't follow further
         
         # Extract LoRAs using the standardized format
         lora_parts = []
@@ -229,6 +258,10 @@ class MetadataProcessor:
     @staticmethod
     def to_dict(metadata):
         """Convert extracted metadata to the ComfyUI output.json format"""           
+        if standalone_mode:
+            # Return empty dictionary in standalone mode
+            return {}
+        
         params = MetadataProcessor.extract_generation_params(metadata)
         
         # Convert all values to strings to match output.json format

py/metadata_collector/node_extractors.py

@@ -257,12 +257,120 @@ class VAEDecodeExtractor(NodeMetadataExtractor):
         if "first_decode" not in metadata[IMAGES]:
             metadata[IMAGES]["first_decode"] = metadata[IMAGES][node_id]
 
+class KSamplerSelectExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "sampler_name" not in inputs:
+            return
+            
+        sampling_params = {}
+        if "sampler_name" in inputs:
+            sampling_params["sampler_name"] = inputs["sampler_name"]
+                
+        metadata[SAMPLING][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id
+        }
+
+class BasicSchedulerExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+            
+        sampling_params = {}
+        for key in ["scheduler", "steps", "denoise"]:
+            if key in inputs:
+                sampling_params[key] = inputs[key]
+                
+        metadata[SAMPLING][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id
+        }
+
+class SamplerCustomAdvancedExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+            
+        sampling_params = {}
+
+        # Handle noise.seed as seed
+        if "noise" in inputs and inputs["noise"] is not None and hasattr(inputs["noise"], "seed"):
+            noise = inputs["noise"]
+            sampling_params["seed"] = noise.seed
+                
+        metadata[SAMPLING][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id
+        }
+        
+        # Extract latent image dimensions if available
+        if "latent_image" in inputs and inputs["latent_image"] is not None:
+            latent = inputs["latent_image"]
+            if isinstance(latent, dict) and "samples" in latent:
+                # Extract dimensions from latent tensor
+                samples = latent["samples"]
+                if hasattr(samples, "shape") and len(samples.shape) >= 3:
+                    # Correct shape interpretation: [batch_size, channels, height/8, width/8]
+                    # Multiply by 8 to get actual pixel dimensions
+                    height = int(samples.shape[2] * 8)
+                    width = int(samples.shape[3] * 8)
+                    
+                    if SIZE not in metadata:
+                        metadata[SIZE] = {}
+                        
+                    metadata[SIZE][node_id] = {
+                        "width": width,
+                        "height": height,
+                        "node_id": node_id
+                    }
+
+import json
+
+class CLIPTextEncodeFluxExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "clip_l" not in inputs or "t5xxl" not in inputs:
+            return
+            
+        clip_l_text = inputs.get("clip_l", "")
+        t5xxl_text = inputs.get("t5xxl", "")
+        
+        # Create JSON string with T5 content first, then CLIP-L
+        combined_text = json.dumps({
+            "T5": t5xxl_text,
+            "CLIP-L": clip_l_text
+        })
+        
+        metadata[PROMPTS][node_id] = {
+            "text": combined_text,
+            "node_id": node_id
+        }
+        
+        # Extract guidance value if available
+        if "guidance" in inputs:
+            guidance_value = inputs.get("guidance")
+            
+            # Store the guidance value in SAMPLING category
+            if SAMPLING not in metadata:
+                metadata[SAMPLING] = {}
+                
+            if node_id not in metadata[SAMPLING]:
+                metadata[SAMPLING][node_id] = {"parameters": {}, "node_id": node_id}
+                
+            metadata[SAMPLING][node_id]["parameters"]["guidance"] = guidance_value
+
 # Registry of node-specific extractors
 NODE_EXTRACTORS = {
     # Sampling
     "KSampler": SamplerExtractor,
-    "KSamplerAdvanced": KSamplerAdvancedExtractor,  # Add KSamplerAdvanced
-    "SamplerCustomAdvanced": SamplerExtractor,  # Add SamplerCustomAdvanced
+    "KSamplerAdvanced": KSamplerAdvancedExtractor,
+    "SamplerCustomAdvanced": SamplerCustomAdvancedExtractor,  # Updated to use dedicated extractor
+    # Sampling Selectors
+    "KSamplerSelect": KSamplerSelectExtractor,  # Add KSamplerSelect
+    "BasicScheduler": BasicSchedulerExtractor,  # Add BasicScheduler
     # Loaders
     "CheckpointLoaderSimple": CheckpointLoaderExtractor,
     "UNETLoader": UNETLoaderExtractor,          # Updated to use dedicated extractor
@@ -270,6 +378,7 @@ NODE_EXTRACTORS = {
     "LoraManagerLoader": LoraLoaderManagerExtractor,
     # Conditioning
     "CLIPTextEncode": CLIPTextEncodeExtractor,
+    "CLIPTextEncodeFlux": CLIPTextEncodeFluxExtractor,  # Add CLIPTextEncodeFlux
     # Latent
     "EmptyLatentImage": ImageSizeExtractor,
     # Flux

py/routes/api_routes.py

@@ -43,6 +43,7 @@ class ApiRoutes:
         app.on_startup.append(lambda _: routes.initialize_services())
         
         app.router.add_post('/api/delete_model', routes.delete_model)
+        app.router.add_post('/api/loras/exclude', routes.exclude_model)  # Add new exclude endpoint
         app.router.add_post('/api/fetch-civitai', routes.fetch_civitai)
         app.router.add_post('/api/replace_preview', routes.replace_preview)
         app.router.add_get('/api/loras', routes.get_loras)
@@ -55,7 +56,6 @@ class ApiRoutes:
         app.router.add_get('/api/civitai/model/version/{modelVersionId}', routes.get_civitai_model_by_version)
         app.router.add_get('/api/civitai/model/hash/{hash}', routes.get_civitai_model_by_hash)
         app.router.add_post('/api/download-lora', routes.download_lora)
-        app.router.add_post('/api/settings', routes.update_settings)
         app.router.add_post('/api/move_model', routes.move_model)
         app.router.add_get('/api/lora-model-description', routes.get_lora_model_description)  # Add new route
         app.router.add_post('/api/loras/save-metadata', routes.save_metadata)
@@ -70,6 +70,9 @@ class ApiRoutes:
         # Add the new trigger words route
         app.router.add_post('/loramanager/get_trigger_words', routes.get_trigger_words)
 
+        # Add new endpoint for letter counts
+        app.router.add_get('/api/loras/letter-counts', routes.get_letter_counts)
+
         # Add update check routes
         UpdateRoutes.setup_routes(app)
 
@@ -79,6 +82,12 @@ class ApiRoutes:
             self.scanner = await ServiceRegistry.get_lora_scanner()
         return await ModelRouteUtils.handle_delete_model(request, self.scanner)
 
+    async def exclude_model(self, request: web.Request) -> web.Response:
+        """Handle model exclusion request"""
+        if self.scanner is None:
+            self.scanner = await ServiceRegistry.get_lora_scanner()
+        return await ModelRouteUtils.handle_exclude_model(request, self.scanner)
+
     async def fetch_civitai(self, request: web.Request) -> web.Response:
         """Handle CivitAI metadata fetch request"""
         if self.scanner is None:
@@ -127,6 +136,9 @@ class ApiRoutes:
             tags = request.query.get('tags', None)
             favorites_only = request.query.get('favorites_only', 'false').lower() == 'true'  # New parameter
             
+            # New parameter for alphabet filtering
+            first_letter = request.query.get('first_letter', None)
+            
             # New parameters for recipe filtering
             lora_hash = request.query.get('lora_hash', None)
             lora_hashes = request.query.get('lora_hashes', None)
@@ -157,7 +169,8 @@ class ApiRoutes:
                 tags=filters.get('tags', None),
                 search_options=search_options,
                 hash_filters=hash_filters,
-                favorites_only=favorites_only  # Pass favorites_only parameter
+                favorites_only=favorites_only,  # Pass favorites_only parameter
+                first_letter=first_letter  # Pass the new first_letter parameter
             )
 
             # Get all available folders from cache
@@ -515,21 +528,6 @@ class ApiRoutes:
                 logger.error(f"Error downloading LoRA: {error_message}")
                 return web.Response(status=500, text=error_message)
 
-    async def update_settings(self, request: web.Request) -> web.Response:
-        """Update application settings"""
-        try:
-            data = await request.json()
-            
-            # Validate and update settings
-            if 'civitai_api_key' in data:
-                settings.set('civitai_api_key', data['civitai_api_key'])
-            if 'show_only_sfw' in data:
-                settings.set('show_only_sfw', data['show_only_sfw'])
-            
-            return web.json_response({'success': True})
-        except Exception as e:
-            logger.error(f"Error updating settings: {e}", exc_info=True)
-            return web.Response(status=500, text=str(e))
 
     async def move_model(self, request: web.Request) -> web.Response:
         """Handle model move request"""
@@ -797,11 +795,13 @@ class ApiRoutes:
             # Check if we already have the description stored in metadata
             description = None
             tags = []
+            creator = {}
             if file_path:
                 metadata_path = os.path.splitext(file_path)[0] + '.metadata.json'
                 metadata = await ModelRouteUtils.load_local_metadata(metadata_path)
                 description = metadata.get('modelDescription')
                 tags = metadata.get('tags', [])
+                creator = metadata.get('creator', {})
             
             # If description is not in metadata, fetch from CivitAI
             if not description:
@@ -811,6 +811,7 @@ class ApiRoutes:
                 if (model_metadata):
                     description = model_metadata.get('description')
                     tags = model_metadata.get('tags', [])
+                    creator = model_metadata.get('creator', {})
                 
                     # Save the metadata to file if we have a file path and got metadata
                     if file_path:
@@ -820,6 +821,7 @@ class ApiRoutes:
                             
                             metadata['modelDescription'] = description
                             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)
@@ -830,7 +832,8 @@ class ApiRoutes:
             return web.json_response({
                 'success': True,
                 'description': description or "<p>No model description available.</p>",
-                'tags': tags
+                'tags': tags,
+                'creator': creator
             })
             
         except Exception as e:
@@ -1060,4 +1063,24 @@ class ApiRoutes:
             return web.json_response({
                 "success": False,
                 "error": str(e)
-            }, status=500)
+            }, status=500)
+
+    async def get_letter_counts(self, request: web.Request) -> web.Response:
+        """Get count of loras for each letter of the alphabet"""
+        try:
+            if self.scanner is None:
+                self.scanner = await ServiceRegistry.get_lora_scanner()
+                
+            # Get letter counts
+            letter_counts = await self.scanner.get_letter_counts()
+            
+            return web.json_response({
+                'success': True,
+                'letter_counts': letter_counts
+            })
+        except Exception as e:
+            logger.error(f"Error getting letter counts: {e}")
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)

py/routes/checkpoints_routes.py

@@ -49,6 +49,7 @@ class CheckpointsRoutes:
         
         # Add new routes for model management similar to LoRA routes
         app.router.add_post('/api/checkpoints/delete', self.delete_model)
+        app.router.add_post('/api/checkpoints/exclude', self.exclude_model)  # Add new exclude endpoint
         app.router.add_post('/api/checkpoints/fetch-civitai', self.fetch_civitai)
         app.router.add_post('/api/checkpoints/replace-preview', self.replace_preview)
         app.router.add_post('/api/checkpoints/download', self.download_checkpoint)
@@ -499,6 +500,10 @@ class CheckpointsRoutes:
     async def delete_model(self, request: web.Request) -> web.Response:
         """Handle checkpoint model deletion request"""
         return await ModelRouteUtils.handle_delete_model(request, self.scanner)
+
+    async def exclude_model(self, request: web.Request) -> web.Response:
+        """Handle checkpoint model exclusion request"""
+        return await ModelRouteUtils.handle_exclude_model(request, self.scanner)
     
     async def fetch_civitai(self, request: web.Request) -> web.Response:
         """Handle CivitAI metadata fetch request for checkpoints"""
@@ -653,7 +658,7 @@ class CheckpointsRoutes:
             model_type = response.get('type', '')
             
             # Check model type - should be Checkpoint
-            if model_type.lower() != 'checkpoint':
+            if (model_type.lower() != 'checkpoint'):
                 return web.json_response({
                     'error': f"Model type mismatch. Expected Checkpoint, got {model_type}"
                 }, status=400)

py/routes/misc_routes.py

@@ -0,0 +1,767 @@
+import logging
+import os
+import asyncio
+import json
+import time
+import aiohttp
+from aiohttp import web
+from ..services.settings_manager import settings
+from ..utils.usage_stats import UsageStats
+from ..services.service_registry import ServiceRegistry
+from ..utils.exif_utils import ExifUtils
+from ..utils.constants import EXAMPLE_IMAGE_WIDTH, SUPPORTED_MEDIA_EXTENSIONS
+from ..services.civitai_client import CivitaiClient
+from ..utils.routes_common import ModelRouteUtils
+
+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 MiscRoutes:
+    """Miscellaneous routes for various utility functions"""
+    
+    @staticmethod
+    def setup_routes(app):
+        """Register miscellaneous routes"""
+        app.router.add_post('/api/settings', MiscRoutes.update_settings)
+
+        # Usage stats routes
+        app.router.add_post('/api/update-usage-stats', MiscRoutes.update_usage_stats)
+        app.router.add_get('/api/get-usage-stats', MiscRoutes.get_usage_stats)
+        
+        # Example images download routes
+        app.router.add_post('/api/download-example-images', MiscRoutes.download_example_images)
+        app.router.add_get('/api/example-images-status', MiscRoutes.get_example_images_status)
+        app.router.add_post('/api/pause-example-images', MiscRoutes.pause_example_images)
+        app.router.add_post('/api/resume-example-images', MiscRoutes.resume_example_images)
+        
+    @staticmethod
+    async def update_settings(request):
+        """Update application settings"""
+        try:
+            data = await request.json()
+            
+            # Validate and update settings
+            for key, value in data.items():
+                # Special handling for example_images_path - verify path exists
+                if key == 'example_images_path' and value:
+                    if not os.path.exists(value):
+                        return web.json_response({
+                            'success': False,
+                            'error': f"Path does not exist: {value}"
+                        })
+                    
+                    # Path changed - server restart required for new path to take effect
+                    old_path = settings.get('example_images_path')
+                    if old_path != value:
+                        logger.info(f"Example images path changed to {value} - server restart required")
+                
+                # Save to settings
+                settings.set(key, value)
+            
+            return web.json_response({'success': True})
+        except Exception as e:
+            logger.error(f"Error updating settings: {e}", exc_info=True)
+            return web.Response(status=500, text=str(e))
+    
+    @staticmethod
+    async def update_usage_stats(request):
+        """
+        Update usage statistics based on a prompt_id
+        
+        Expects a JSON body with:
+        {
+            "prompt_id": "string"
+        }
+        """
+        try:
+            # Parse the request body
+            data = await request.json()
+            prompt_id = data.get('prompt_id')
+            
+            if not prompt_id:
+                return web.json_response({
+                    'success': False,
+                    'error': 'Missing prompt_id'
+                }, status=400)
+            
+            # Call the UsageStats to process this prompt_id synchronously
+            usage_stats = UsageStats()
+            await usage_stats.process_execution(prompt_id)
+            
+            return web.json_response({
+                'success': True
+            })
+            
+        except Exception as e:
+            logger.error(f"Failed to update usage stats: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)
+    
+    @staticmethod
+    async def get_usage_stats(request):
+        """Get current usage statistics"""
+        try:
+            usage_stats = UsageStats()
+            stats = await usage_stats.get_stats()
+            
+            return web.json_response({
+                'success': True,
+                'data': stats
+            })
+            
+        except Exception as e:
+            logger.error(f"Failed to get usage stats: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)
+    
+    @staticmethod
+    async def download_example_images(request):
+        """
+        Download example images for models from Civitai
+        
+        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))
+            
+            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(
+                MiscRoutes._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_example_images_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_example_images(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_example_images(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 _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: Name of the model (for logging)
+            scanner_type: Type of scanner ('lora' or 'checkpoint')
+            scanner: Scanner instance for this model type
+            
+        Returns:
+            bool: True if metadata was successfully refreshed, False otherwise
+        """
+        global 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 the 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 _process_model_images(model_hash, model_name, model_images, model_dir, optimize, independent_session, delay):
+        """Process and download images for a single model
+        
+        Args:
+            model_hash: SHA256 hash of the model
+            model_name: Name of the model
+            model_images: List of image objects from CivitAI
+            model_dir: Directory to save images to
+            optimize: Whether to optimize images
+            independent_session: aiohttp session for downloads
+            delay: Delay between downloads
+            
+        Returns:
+            bool: True if all images were processed successfully, False otherwise
+        """
+        global download_progress
+        
+        model_success = True
+        
+        for i, image in enumerate(model_images, 1):
+            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 both 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
+            
+            save_filename = f"image_{i}{image_ext}"
+            
+            # 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}")
+                
+                # Direct download using the independent session
+                async with independent_session.get(image_url, timeout=60) as response:
+                    if response.status == 200:
+                        if is_image and optimize:
+                            # For images, optimize if requested
+                            image_data = await response.read()
+                            optimized_data, ext = ExifUtils.optimize_image(
+                                image_data, 
+                                target_width=EXAMPLE_IMAGE_WIDTH, 
+                                format='webp', 
+                                quality=85, 
+                                preserve_metadata=False
+                            )
+                            
+                            # Update save filename if format changed
+                            if ext == '.webp':
+                                save_filename = os.path.splitext(save_filename)[0] + '.webp'
+                                save_path = os.path.join(model_dir, save_filename)
+                            
+                            # Save the optimized image
+                            with open(save_path, 'wb') as f:
+                                f.write(optimized_data)
+                        else:
+                            # For videos or unoptimized images, save directly
+                            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)
+                        download_progress['errors'].append(error_msg)
+                        download_progress['last_error'] = error_msg
+                        model_success = False  # Mark model as failed due to 404
+                        # Return early to trigger metadata refresh attempt
+                        return False, True  # (success, is_stale_metadata)
+                    else:
+                        error_msg = f"Failed to download file: {image_url}, status code: {response.status}"
+                        logger.warning(error_msg)
+                        download_progress['errors'].append(error_msg)
+                        download_progress['last_error'] = error_msg
+                        model_success = False  # Mark model as failed
+                
+                # Add a delay between downloads for remote files only
+                await asyncio.sleep(delay)
+            except Exception as e:
+                error_msg = f"Error downloading file {image_url}: {str(e)}"
+                logger.error(error_msg)
+                download_progress['errors'].append(error_msg)
+                download_progress['last_error'] = error_msg
+                model_success = False  # Mark model as failed
+        
+        return model_success, False  # (success, is_stale_metadata)
+    
+    @staticmethod
+    async def _process_local_example_images(model_file_path, model_file_name, model_name, model_dir, optimize):
+        """Process local example images for a model
+        
+        Args:
+            model_file_path: Path to the model file
+            model_file_name: Filename of the model
+            model_name: Name of the model
+            model_dir: Directory to save processed images to
+            optimize: Whether to optimize images
+            
+        Returns:
+            bool: True if local images were processed successfully, False otherwise
+        """
+        global download_progress
+        
+        try:
+            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 i, local_image_path in enumerate(local_images, 1):
+                    local_ext = os.path.splitext(local_image_path)[1].lower()
+                    save_filename = f"image_{i}{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
+                    
+                    # Handle image processing based on file type and optimize setting
+                    is_image = local_ext in SUPPORTED_MEDIA_EXTENSIONS['images']
+                    
+                    if is_image and optimize:
+                        # Optimize the image
+                        with open(local_image_path, 'rb') as img_file:
+                            image_data = img_file.read()
+                        
+                        optimized_data, ext = ExifUtils.optimize_image(
+                            image_data, 
+                            target_width=EXAMPLE_IMAGE_WIDTH, 
+                            format='webp', 
+                            quality=85, 
+                            preserve_metadata=False
+                        )
+                        
+                        # Update save filename if format changed
+                        if ext == '.webp':
+                            save_filename = os.path.splitext(save_filename)[0] + '.webp'
+                            save_path = os.path.join(model_dir, save_filename)
+                        
+                        # Save the optimized image
+                        with open(save_path, 'wb') as f:
+                            f.write(optimized_data)
+                    else:
+                        # For videos or unoptimized images, copy directly
+                        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:
+            error_msg = f"Error processing local examples for {model_name}: {str(e)}"
+            logger.error(error_msg)
+            download_progress['errors'].append(error_msg)
+            download_progress['last_error'] = error_msg
+            return False
+
+    @staticmethod
+    async def _download_all_example_images(output_dir, optimize, model_types, delay):
+        """Download example images for all models
+        
+        Args:
+            output_dir: Base directory to save example images
+            optimize: Whether to optimize images
+            model_types: List of model types to process
+            delay: Delay between downloads to avoid rate limiting
+        """
+        global is_downloading, download_progress
+        
+        # Create an independent session for downloading example images
+        # This avoids interference with the CivitAI client's 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)
+        
+        # Create a dedicated session just for this download task
+        independent_session = aiohttp.ClientSession(
+            connector=connector,
+            trust_env=True,
+            timeout=timeout
+        )
+        
+        try:
+            # Get the 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 from all scanners
+            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:
+                        # Only process models with images and a valid sha256
+                        if model.get('civitai') and model.get('civitai', {}).get('images') and 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 with example images")
+            
+            # Process each model
+            for scanner_type, model, scanner in all_models:
+                # 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']}")
+                    break
+                
+                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}")
+                        download_progress['completed'] += 1
+                        continue
+                    
+                    # Create model directory
+                    model_dir = os.path.join(output_dir, model_hash)
+                    os.makedirs(model_dir, exist_ok=True)
+                    
+                    # Process images for this model
+                    images = model.get('civitai', {}).get('images', [])
+                    
+                    if not images:
+                        logger.debug(f"No images found for model: {model_name}")
+                        download_progress['processed_models'].add(model_hash)
+                        download_progress['completed'] += 1
+                        continue
+                    
+                    # First check if we have local example images for this model
+                    local_images_processed = False
+                    if model_file_path:
+                        local_images_processed = await MiscRoutes._process_local_example_images(
+                            model_file_path, 
+                            model_file_name, 
+                            model_name, 
+                            model_dir, 
+                            optimize
+                        )
+                        
+                        if local_images_processed:
+                            # Mark as successfully processed if all local images were processed
+                            download_progress['processed_models'].add(model_hash)
+                            logger.info(f"Successfully processed local examples for {model_name}")
+                    
+                    # If we didn't process local images, download from remote
+                    if not local_images_processed:
+                        # Try to download images
+                        model_success, is_stale_metadata = await MiscRoutes._process_model_images(
+                            model_hash, 
+                            model_name, 
+                            images, 
+                            model_dir, 
+                            optimize, 
+                            independent_session, 
+                            delay
+                        )
+                        
+                        # If metadata is stale (404 error), try to refresh it and download again
+                        if is_stale_metadata and model_hash not in download_progress['refreshed_models']:
+                            logger.info(f"Metadata seems stale for {model_name}, attempting to refresh...")
+                            
+                            # Refresh metadata from CivitAI
+                            refresh_success = await MiscRoutes._refresh_model_metadata(
+                                model_hash, 
+                                model_name, 
+                                scanner_type, 
+                                scanner
+                            )
+                            
+                            if refresh_success:
+                                # Get updated model data
+                                updated_cache = await scanner.get_cached_data()
+                                updated_model = None
+                                
+                                for item in updated_cache.raw_data:
+                                    if item.get('sha256') == model_hash:
+                                        updated_model = item
+                                        break
+                                
+                                if updated_model and updated_model.get('civitai', {}).get('images'):
+                                    # Try downloading with updated metadata
+                                    logger.info(f"Retrying download with refreshed metadata for {model_name}")
+                                    updated_images = updated_model.get('civitai', {}).get('images', [])
+                                    
+                                    # Retry download with new images
+                                    model_success, _ = await MiscRoutes._process_model_images(
+                                        model_hash, 
+                                        model_name, 
+                                        updated_images, 
+                                        model_dir, 
+                                        optimize, 
+                                        independent_session, 
+                                        delay
+                                    )
+                        
+                        # Only mark model as processed if all images downloaded successfully
+                        if model_success:
+                            download_progress['processed_models'].add(model_hash)
+                        else:
+                            logger.warning(f"Model {model_name} had download errors, will not mark as completed")
+                    
+                    # Save progress to file periodically
+                    if download_progress['completed'] % 10 == 0 or download_progress['completed'] == download_progress['total'] - 1:
+                        progress_file = os.path.join(output_dir, '.download_progress.json')
+                        with open(progress_file, 'w', encoding='utf-8') as f:
+                            json.dump({
+                                '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()
+                            }, f, indent=2)
+                
+                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
+                
+                # Update progress
+                download_progress['completed'] += 1
+            
+            # 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:
+                progress_file = os.path.join(output_dir, '.download_progress.json')
+                with open(progress_file, 'w', encoding='utf-8') as f:
+                    json.dump({
+                        '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(),
+                        'status': download_progress['status']
+                    }, f, indent=2)
+            except Exception as e:
+                logger.error(f"Failed to save progress file: {e}")
+            
+            # Set download status to not downloading
+            is_downloading = False

py/routes/recipe_routes.py

@@ -10,16 +10,25 @@ from typing import Dict
 import tempfile
 import json
 import asyncio
+import sys
 from ..utils.exif_utils import ExifUtils
 from ..utils.recipe_parsers import RecipeParserFactory
 from ..utils.constants import CARD_PREVIEW_WIDTH
 
 from ..config import config
-from ..metadata_collector import get_metadata  # Add MetadataCollector import
-from ..metadata_collector.metadata_processor import MetadataProcessor  # Add MetadataProcessor import
+
+# Check if running in standalone mode
+standalone_mode = 'nodes' not in sys.modules
+
 from ..utils.utils import download_civitai_image
 from ..services.service_registry import ServiceRegistry  # Add ServiceRegistry import
-from ..metadata_collector.metadata_registry import MetadataRegistry
+
+# Only import MetadataRegistry in non-standalone mode
+if not standalone_mode:
+    # Import metadata_collector functions and classes conditionally
+    from ..metadata_collector import get_metadata  # Add MetadataCollector import
+    from ..metadata_collector.metadata_processor import MetadataProcessor  # Add MetadataProcessor import
+    from ..metadata_collector.metadata_registry import MetadataRegistry
 
 logger = logging.getLogger(__name__)
 
@@ -804,8 +813,11 @@ class RecipeRoutes:
                 return web.json_response({"error": "No generation metadata found"}, status=400)
             
             # Get the most recent image from metadata registry instead of temp directory
-            metadata_registry = MetadataRegistry()
-            latest_image = metadata_registry.get_first_decoded_image()
+            if not standalone_mode:
+                metadata_registry = MetadataRegistry()
+                latest_image = metadata_registry.get_first_decoded_image()
+            else:
+                latest_image = None
             
             if not latest_image:
                 return web.json_response({"error": "No recent images found to use for recipe. Try generating an image first."}, status=400)

py/routes/update_routes.py

@@ -150,11 +150,16 @@ class UpdateRoutes:
         """
         Compare two semantic version strings
         Returns True if version2 is newer than version1
+        Ignores any suffixes after '-' (e.g., -bugfix, -alpha)
         """
         try:
+            # Clean version strings - remove any suffix after '-'
+            v1_clean = version1.split('-')[0]
+            v2_clean = version2.split('-')[0]
+            
             # Split versions into components
-            v1_parts = [int(x) for x in version1.split('.')]
-            v2_parts = [int(x) for x in version2.split('.')]
+            v1_parts = [int(x) for x in v1_clean.split('.')]
+            v2_parts = [int(x) for x in v2_clean.split('.')]
             
             # Ensure both have 3 components (major.minor.patch)
             while len(v1_parts) < 3:

py/routes/usage_stats_routes.py

@@ -1,69 +0,0 @@
-import logging
-from aiohttp import web
-from ..utils.usage_stats import UsageStats
-
-logger = logging.getLogger(__name__)
-
-class UsageStatsRoutes:
-    """Routes for handling usage statistics updates"""
-    
-    @staticmethod
-    def setup_routes(app):
-        """Register usage stats routes"""
-        app.router.add_post('/loras/api/update-usage-stats', UsageStatsRoutes.update_usage_stats)
-        app.router.add_get('/loras/api/get-usage-stats', UsageStatsRoutes.get_usage_stats)
-    
-    @staticmethod
-    async def update_usage_stats(request):
-        """
-        Update usage statistics based on a prompt_id
-        
-        Expects a JSON body with:
-        {
-            "prompt_id": "string"
-        }
-        """
-        try:
-            # Parse the request body
-            data = await request.json()
-            prompt_id = data.get('prompt_id')
-            
-            if not prompt_id:
-                return web.json_response({
-                    'success': False,
-                    'error': 'Missing prompt_id'
-                }, status=400)
-            
-            # Call the UsageStats to process this prompt_id synchronously
-            usage_stats = UsageStats()
-            await usage_stats.process_execution(prompt_id)
-            
-            return web.json_response({
-                'success': True
-            })
-            
-        except Exception as e:
-            logger.error(f"Failed to update usage stats: {e}", exc_info=True)
-            return web.json_response({
-                'success': False,
-                'error': str(e)
-            }, status=500)
-    
-    @staticmethod
-    async def get_usage_stats(request):
-        """Get current usage statistics"""
-        try:
-            usage_stats = UsageStats()
-            stats = await usage_stats.get_stats()
-            
-            return web.json_response({
-                'success': True,
-                'data': stats
-            })
-            
-        except Exception as e:
-            logger.error(f"Failed to get usage stats: {e}", exc_info=True)
-            return web.json_response({
-                'success': False,
-                'error': str(e)
-            }, status=500)

py/services/civitai_client.py

@@ -267,7 +267,7 @@ class CivitaiClient:
             return None, error_msg
 
     async def get_model_metadata(self, model_id: str) -> Tuple[Optional[Dict], int]:
-        """Fetch model metadata (description and tags) from Civitai API
+        """Fetch model metadata (description, tags, and creator info) from Civitai API
         
         Args:
             model_id: The Civitai model ID
@@ -294,10 +294,14 @@ class CivitaiClient:
                 # Extract relevant metadata
                 metadata = {
                     "description": data.get("description") or "No model description available",
-                    "tags": data.get("tags", [])
+                    "tags": data.get("tags", []),
+                    "creator": {
+                        "username": data.get("creator", {}).get("username"),
+                        "image": data.get("creator", {}).get("image")
+                    }
                 }
                 
-                if metadata["description"] or metadata["tags"]:
+                if metadata["description"] or metadata["tags"] or metadata["creator"]["username"]:
                     return metadata, status_code
                 else:
                     logger.warning(f"No metadata found for model {model_id}")

py/services/download_manager.py

@@ -154,7 +154,7 @@ class DownloadManager:
                 metadata = LoraMetadata.from_civitai_info(version_info, file_info, save_path)
                 logger.info(f"Creating LoraMetadata for {file_name}")
             
-            # 5.1 Get and update model tags and description
+            # 5.1 Get and update model tags, description and creator info
             model_id = version_info.get('modelId')
             if model_id:
                 model_metadata, _ = await civitai_client.get_model_metadata(str(model_id))
@@ -163,6 +163,8 @@ class DownloadManager:
                         metadata.tags = model_metadata.get("tags", [])
                     if model_metadata.get("description"):
                         metadata.modelDescription = model_metadata.get("description", "")
+                    if model_metadata.get("creator"):
+                        metadata.civitai["creator"] = model_metadata.get("creator")
             
             # 6. Start download process
             result = await self._execute_download(

py/services/lora_scanner.py

@@ -4,6 +4,7 @@ import logging
 import asyncio
 import shutil
 import time
+import re
 from typing import List, Dict, Optional, Set
 
 from ..utils.models import LoraMetadata
@@ -123,7 +124,7 @@ class LoraScanner(ModelScanner):
                                folder: str = None, search: str = None, fuzzy_search: bool = False,
                                base_models: list = None, tags: list = None,
                                search_options: dict = None, hash_filters: dict = None,
-                               favorites_only: bool = False) -> Dict:
+                               favorites_only: bool = False, first_letter: str = None) -> Dict:
         """Get paginated and filtered lora data
         
         Args:
@@ -138,6 +139,7 @@ class LoraScanner(ModelScanner):
             search_options: Dictionary with search options (filename, modelname, tags, recursive)
             hash_filters: Dictionary with hash filtering options (single_hash or multiple_hashes)
             favorites_only: Filter for favorite models only
+            first_letter: Filter by first letter of model name
         """
         cache = await self.get_cached_data()
 
@@ -202,6 +204,10 @@ class LoraScanner(ModelScanner):
                 lora for lora in filtered_data
                 if lora.get('favorite', False) is True
             ]
+            
+        # Apply first letter filtering
+        if first_letter:
+            filtered_data = self._filter_by_first_letter(filtered_data, first_letter)
         
         # Apply folder filtering
         if folder is not None:
@@ -273,6 +279,101 @@ class LoraScanner(ModelScanner):
         
         return result
 
+    def _filter_by_first_letter(self, data, letter):
+        """Filter data by first letter of model name
+        
+        Special handling:
+        - '#': Numbers (0-9)
+        - '@': Special characters (not alphanumeric)
+        - '漢': CJK characters
+        """
+        filtered_data = []
+        
+        for lora in data:
+            model_name = lora.get('model_name', '')
+            if not model_name:
+                continue
+                
+            first_char = model_name[0].upper()
+            
+            if letter == '#' and first_char.isdigit():
+                filtered_data.append(lora)
+            elif letter == '@' and not first_char.isalnum():
+                # Special characters (not alphanumeric)
+                filtered_data.append(lora)
+            elif letter == '漢' and self._is_cjk_character(first_char):
+                # CJK characters
+                filtered_data.append(lora)
+            elif letter.upper() == first_char:
+                # Regular alphabet matching
+                filtered_data.append(lora)
+                
+        return filtered_data
+    
+    def _is_cjk_character(self, char):
+        """Check if character is a CJK character"""
+        # Define Unicode ranges for CJK characters
+        cjk_ranges = [
+            (0x4E00, 0x9FFF),   # CJK Unified Ideographs
+            (0x3400, 0x4DBF),   # CJK Unified Ideographs Extension A
+            (0x20000, 0x2A6DF), # CJK Unified Ideographs Extension B
+            (0x2A700, 0x2B73F), # CJK Unified Ideographs Extension C
+            (0x2B740, 0x2B81F), # CJK Unified Ideographs Extension D
+            (0x2B820, 0x2CEAF), # CJK Unified Ideographs Extension E
+            (0x2CEB0, 0x2EBEF), # CJK Unified Ideographs Extension F
+            (0x30000, 0x3134F), # CJK Unified Ideographs Extension G
+            (0xF900, 0xFAFF),   # CJK Compatibility Ideographs
+            (0x3300, 0x33FF),   # CJK Compatibility
+            (0x3200, 0x32FF),   # Enclosed CJK Letters and Months
+            (0x3100, 0x312F),   # Bopomofo
+            (0x31A0, 0x31BF),   # Bopomofo Extended
+            (0x3040, 0x309F),   # Hiragana
+            (0x30A0, 0x30FF),   # Katakana
+            (0x31F0, 0x31FF),   # Katakana Phonetic Extensions
+            (0xAC00, 0xD7AF),   # Hangul Syllables
+            (0x1100, 0x11FF),   # Hangul Jamo
+            (0xA960, 0xA97F),   # Hangul Jamo Extended-A
+            (0xD7B0, 0xD7FF),   # Hangul Jamo Extended-B
+        ]
+        
+        code_point = ord(char)
+        return any(start <= code_point <= end for start, end in cjk_ranges)
+    
+    async def get_letter_counts(self):
+        """Get count of models for each letter of the alphabet"""
+        cache = await self.get_cached_data()
+        data = cache.sorted_by_name
+        
+        # Define letter categories
+        letters = {
+            '#': 0,  # Numbers
+            'A': 0, 'B': 0, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0, 'H': 0,
+            'I': 0, 'J': 0, 'K': 0, 'L': 0, 'M': 0, 'N': 0, 'O': 0, 'P': 0,
+            'Q': 0, 'R': 0, 'S': 0, 'T': 0, 'U': 0, 'V': 0, 'W': 0, 'X': 0,
+            'Y': 0, 'Z': 0,
+            '@': 0,  # Special characters
+            '漢': 0   # CJK characters
+        }
+        
+        # Count models for each letter
+        for lora in data:
+            model_name = lora.get('model_name', '')
+            if not model_name:
+                continue
+                
+            first_char = model_name[0].upper()
+            
+            if first_char.isdigit():
+                letters['#'] += 1
+            elif first_char in letters:
+                letters[first_char] += 1
+            elif self._is_cjk_character(first_char):
+                letters['漢'] += 1
+            elif not first_char.isalnum():
+                letters['@'] += 1
+                
+        return letters
+
     async def _update_metadata_paths(self, metadata_path: str, lora_path: str) -> Dict:
         """Update file paths in metadata file"""
         try:

py/services/model_scanner.py

@@ -38,6 +38,7 @@ class ModelScanner:
         self._hash_index = hash_index or ModelHashIndex()
         self._tags_count = {}  # Dictionary to store tag counts
         self._is_initializing = False  # Flag to track initialization state
+        self._excluded_models = []  # List to track excluded models
         
         # Register this service
         asyncio.create_task(self._register_service())
@@ -394,6 +395,9 @@ class ModelScanner:
                             if file_path in cached_paths:
                                 found_paths.add(file_path)
                                 continue
+
+                            if file_path in self._excluded_models:
+                                continue
                                 
                             # Try case-insensitive match on Windows
                             if os.name == 'nt':
@@ -406,7 +410,7 @@ class ModelScanner:
                                         break
                                 if matched:
                                     continue
-                            
+                                
                             # This is a new file to process
                             new_files.append(file_path)
                     
@@ -586,6 +590,11 @@ class ModelScanner:
         
         model_data = metadata.to_dict()
         
+        # Skip excluded models
+        if model_data.get('exclude', False):
+            self._excluded_models.append(model_data['file_path'])
+            return None
+            
         await self._fetch_missing_metadata(file_path, model_data)
         rel_path = os.path.relpath(file_path, root_path)
         folder = os.path.dirname(rel_path)
@@ -610,7 +619,10 @@ class ModelScanner:
                     model_id = str(model_id)
                     tags_missing = not model_data.get('tags') or len(model_data.get('tags', [])) == 0
                     desc_missing = not model_data.get('modelDescription') or model_data.get('modelDescription') in (None, "")
-                    needs_metadata_update = tags_missing or desc_missing
+                    # TODO: not for now, but later we should check if the creator is missing
+                    # creator_missing = not model_data.get('civitai', {}).get('creator')
+                    creator_missing = False
+                    needs_metadata_update = tags_missing or desc_missing or creator_missing
             
             if needs_metadata_update and model_id:
                 logger.debug(f"Fetching missing metadata for {file_path} with model ID {model_id}")
@@ -636,6 +648,8 @@ class ModelScanner:
                     
                     if model_metadata.get('description') and (not model_data.get('modelDescription') or model_data.get('modelDescription') in (None, "")):
                         model_data['modelDescription'] = model_metadata['description']
+
+                    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:
@@ -900,6 +914,10 @@ class ModelScanner:
             logger.error(f"Error getting model info by name: {e}", exc_info=True)
             return None
         
+    def get_excluded_models(self) -> List[str]:
+        """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:
         """Update preview URL in cache for a specific lora
         
@@ -913,4 +931,4 @@ class ModelScanner:
         if self._cache is None:
             return False
 
-        return await self._cache.update_preview_url(file_path, preview_url)
+        return await self._cache.update_preview_url(file_path, preview_url)

py/utils/constants.py

@@ -11,15 +11,24 @@ NSFW_LEVELS = {
 PREVIEW_EXTENSIONS = [
     '.webp',
     '.preview.webp',
-    '.preview.png', 
-    '.preview.jpeg', 
-    '.preview.jpg', 
+    '.preview.png',
+    '.preview.jpeg',
+    '.preview.jpg',
     '.preview.mp4',
-    '.png', 
-    '.jpeg', 
-    '.jpg', 
+    '.png',
+    '.jpeg',
+    '.jpg',
     '.mp4'
 ]
 
 # Card preview image width
-CARD_PREVIEW_WIDTH = 480
+CARD_PREVIEW_WIDTH = 480
+
+# Width for optimized example images
+EXAMPLE_IMAGE_WIDTH = 832
+
+# Supported media extensions for example downloads
+SUPPORTED_MEDIA_EXTENSIONS = {
+    'images': ['.jpg', '.jpeg', '.png', '.webp', '.gif'],
+    'videos': ['.mp4', '.webm']
+}

py/utils/models.py

@@ -23,6 +23,7 @@ class BaseModelMetadata:
     modelDescription: str = ""  # Full model description
     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
 
     def __post_init__(self):
         # Initialize empty lists to avoid mutable default parameter issue

py/utils/recipe_parsers.py

@@ -403,27 +403,43 @@ class StandardMetadataParser(RecipeMetadataParser):
             
             # Extract Civitai resources
             if 'Civitai resources:' in user_comment:
-                resources_part = user_comment.split('Civitai resources:', 1)[1]
-                if '],' in resources_part:
-                    resources_json = resources_part.split('],', 1)[0] + ']'
-                    try:
-                        resources = json.loads(resources_json)
-                        # Filter loras and checkpoints
-                        for resource in resources:
-                            if resource.get('type') == 'lora':
-                                # 确保 weight 字段被正确保留
-                                lora_entry = resource.copy()
-                                # 如果找不到 weight，默认为 1.0
-                                if 'weight' not in lora_entry:
-                                    lora_entry['weight'] = 1.0
-                                # Ensure modelVersionName is included
-                                if 'modelVersionName' not in lora_entry:
-                                    lora_entry['modelVersionName'] = ''
-                                metadata['loras'].append(lora_entry)
-                            elif resource.get('type') == 'checkpoint':
-                                metadata['checkpoint'] = resource
-                    except json.JSONDecodeError:
-                        pass
+                resources_part = user_comment.split('Civitai resources:', 1)[1].strip()
+                
+                # Look for the opening and closing brackets to extract the JSON array
+                if resources_part.startswith('['):
+                    # Find the position of the closing bracket
+                    bracket_count = 0
+                    end_pos = -1
+                    
+                    for i, char in enumerate(resources_part):
+                        if char == '[':
+                            bracket_count += 1
+                        elif char == ']':
+                            bracket_count -= 1
+                            if bracket_count == 0:
+                                end_pos = i
+                                break
+                    
+                    if end_pos != -1:
+                        resources_json = resources_part[:end_pos+1]
+                        try:
+                            resources = json.loads(resources_json)
+                            # Filter loras and checkpoints
+                            for resource in resources:
+                                if resource.get('type') == 'lora':
+                                    # 确保 weight 字段被正确保留
+                                    lora_entry = resource.copy()
+                                    # 如果找不到 weight，默认为 1.0
+                                    if 'weight' not in lora_entry:
+                                        lora_entry['weight'] = 1.0
+                                    # Ensure modelVersionName is included
+                                    if 'modelVersionName' not in lora_entry:
+                                        lora_entry['modelVersionName'] = ''
+                                    metadata['loras'].append(lora_entry)
+                                elif resource.get('type') == 'checkpoint':
+                                    metadata['checkpoint'] = resource
+                        except json.JSONDecodeError:
+                            pass
             
             return metadata
         except Exception as e:
@@ -436,7 +452,7 @@ class A1111MetadataParser(RecipeMetadataParser):
     
     METADATA_MARKER = r'Lora hashes:'
     LORA_PATTERN = r'<lora:([^:]+):([^>]+)>'
-    LORA_HASH_PATTERN = r'([^:]+): ([a-f0-9]+)'
+    LORA_HASH_PATTERN = r'([^:]+):\s*([a-fA-F0-9]+)'
     
     def is_metadata_matching(self, user_comment: str) -> bool:
         """Check if the user comment matches the A1111 metadata format"""
@@ -445,51 +461,103 @@ class A1111MetadataParser(RecipeMetadataParser):
     async def parse_metadata(self, user_comment: str, recipe_scanner=None, civitai_client=None) -> Dict[str, Any]:
         """Parse metadata from images with A1111 metadata format"""
         try:
-            # Extract prompt and negative prompt
-            parts = user_comment.split('Negative prompt:', 1)
-            prompt = parts[0].strip()
+            # Initialize metadata with default empty values
+            metadata = {"prompt": "", "loras": []}
             
-            # Initialize metadata
-            metadata = {"prompt": prompt, "loras": []}
-            
-            # Extract negative prompt and parameters
-            if len(parts) > 1:
-                negative_and_params = parts[1]
+            # Check if the user_comment contains prompt and negative prompt
+            if 'Negative prompt:' in user_comment:
+                # Extract prompt and negative prompt
+                parts = user_comment.split('Negative prompt:', 1)
+                metadata["prompt"] = parts[0].strip()
                 
-                # Extract negative prompt
-                if "Steps:" in negative_and_params:
-                    neg_prompt = negative_and_params.split("Steps:", 1)[0].strip()
-                    metadata["negative_prompt"] = neg_prompt
-                
-                # Extract key-value parameters (Steps, Sampler, CFG scale, etc.)
-                param_pattern = r'([A-Za-z ]+): ([^,]+)'
-                params = re.findall(param_pattern, negative_and_params)
-                for key, value in params:
-                    clean_key = key.strip().lower().replace(' ', '_')
-                    metadata[clean_key] = value.strip()
+                # Extract negative prompt and parameters
+                if len(parts) > 1:
+                    negative_and_params = parts[1]
+                    
+                    # Extract negative prompt
+                    param_start = re.search(r'([A-Za-z ]+):', negative_and_params)
+                    if param_start:
+                        neg_prompt = negative_and_params[:param_start.start()].strip()
+                        metadata["negative_prompt"] = neg_prompt
+                        params_section = negative_and_params[param_start.start():]
+                    else:
+                        params_section = negative_and_params
+                    
+                    # Extract parameters from this section
+                    self._extract_parameters(params_section, metadata)
+            else:
+                # No prompt/negative prompt - extract parameters directly
+                self._extract_parameters(user_comment, metadata)
             
-            # Extract LoRA information from prompt
+            # Extract LoRA information from prompt if available
             lora_weights = {}
-            lora_matches = re.findall(self.LORA_PATTERN, prompt)
-            for lora_name, weights in lora_matches:
-                # Take only the first strength value (before the colon)
-                weight = weights.split(':')[0]
-                lora_weights[lora_name.strip()] = float(weight.strip())
-            
-            # Remove LoRA patterns from prompt
-            metadata["prompt"] = re.sub(self.LORA_PATTERN, '', prompt).strip()
+            if metadata["prompt"]:
+                lora_matches = re.findall(self.LORA_PATTERN, metadata["prompt"])
+                for lora_name, weights in lora_matches:
+                    # Take only the first strength value (before the colon)
+                    weight = weights.split(':')[0]
+                    lora_weights[lora_name.strip()] = float(weight.strip())
+                
+                # Remove LoRA patterns from prompt
+                metadata["prompt"] = re.sub(self.LORA_PATTERN, '', metadata["prompt"]).strip()
             
             # Extract LoRA hashes
             lora_hashes = {}
             if 'Lora hashes:' in user_comment:
+                # Get the LoRA hashes section
                 lora_hash_section = user_comment.split('Lora hashes:', 1)[1].strip()
+                
+                # Handle various format possibilities
                 if lora_hash_section.startswith('"'):
-                    lora_hash_section = lora_hash_section[1:].split('"', 1)[0]
-                hash_matches = re.findall(self.LORA_HASH_PATTERN, lora_hash_section)
-                for lora_name, hash_value in hash_matches:
-                    # Remove any leading comma and space from lora name
-                    clean_name = lora_name.strip().lstrip(',').strip()
-                    lora_hashes[clean_name] = hash_value.strip()
+                    # Extract content within quotes
+                    quote_match = re.match(r'"([^"]+)"', lora_hash_section)
+                    if quote_match:
+                        lora_hash_section = quote_match.group(1)
+                
+                # Split by commas and parse each LoRA entry
+                lora_entries = []
+                current_entry = ""
+                for part in lora_hash_section.split(','):
+                    # Check if this part contains a colon (indicating a complete entry)
+                    if ':' in part:
+                        if current_entry:
+                            lora_entries.append(current_entry.strip())
+                        current_entry = part.strip()
+                    else:
+                        # This is probably a continuation of the previous entry
+                        current_entry += ',' + part
+                
+                # Add the last entry if it exists
+                if current_entry:
+                    lora_entries.append(current_entry.strip())
+                
+                # Process each entry
+                for entry in lora_entries:
+                    # Split at the colon to get name and hash
+                    if ':' in entry:
+                        lora_name, hash_value = entry.split(':', 1)
+                        # Clean the values
+                        lora_name = lora_name.strip()
+                        hash_value = hash_value.strip()
+                        # Store in our dictionary
+                        lora_hashes[lora_name] = hash_value
+            
+            # Alternative backup method using regex if the above parsing fails
+            if not lora_hashes:
+                if 'Lora hashes:' in user_comment:
+                    lora_hash_section = user_comment.split('Lora hashes:', 1)[1].strip()
+                    if lora_hash_section.startswith('"'):
+                        # Extract content within quotes if present
+                        quote_match = re.match(r'"([^"]+)"', lora_hash_section)
+                        if quote_match:
+                            lora_hash_section = quote_match.group(1)
+                    
+                    # Use regex to find all name:hash pairs
+                    hash_matches = re.findall(self.LORA_HASH_PATTERN, lora_hash_section)
+                    for lora_name, hash_value in hash_matches:
+                        # Clean up name by removing any leading comma and spaces
+                        clean_name = lora_name.strip().lstrip(',').strip()
+                        lora_hashes[clean_name] = hash_value.strip()
             
             # Process LoRAs and collect base models
             base_model_counts = {}
@@ -507,7 +575,7 @@ class A1111MetadataParser(RecipeMetadataParser):
                     'existsLocally': False,
                     'localPath': None,
                     'file_name': lora_name,
-                    'hash': hash_value,
+                    'hash': hash_value.lower(),  # Ensure hash is lowercase
                     'thumbnailUrl': '/loras_static/images/no-preview.png',
                     'baseModel': '',
                     'size': 0,
@@ -557,6 +625,15 @@ class A1111MetadataParser(RecipeMetadataParser):
         except Exception as e:
             logger.error(f"Error parsing A1111 metadata: {e}", exc_info=True)
             return {"error": str(e), "loras": []}
+    
+    def _extract_parameters(self, text: str, metadata: Dict[str, Any]) -> None:
+        """Extract parameters from text section and populate metadata dict"""
+        # Extract key-value parameters (Steps, Sampler, CFG scale, etc.)
+        param_pattern = r'([A-Za-z][A-Za-z0-9 _]+): ([^,]+)(?:,|$)'
+        params = re.findall(param_pattern, text)
+        for key, value in params:
+            clean_key = key.strip().lower().replace(' ', '_')
+            metadata[clean_key] = value.strip()
 
 
 class ComfyMetadataParser(RecipeMetadataParser):

py/utils/routes_common.py

@@ -53,6 +53,7 @@ class ModelRouteUtils:
                 if model_metadata:
                     local_metadata['modelDescription'] = model_metadata.get('description', '')
                     local_metadata['tags'] = model_metadata.get('tags', [])
+                    local_metadata['civitai']['creator'] = model_metadata['creator']
         
         # Update base model
         local_metadata['base_model'] = determine_base_model(civitai_metadata.get('baseModel'))
@@ -424,6 +425,65 @@ class ModelRouteUtils:
             logger.error(f"Error replacing preview: {e}", exc_info=True)
             return web.Response(text=str(e), status=500)
 
+    @staticmethod
+    async def handle_exclude_model(request: web.Request, scanner) -> web.Response:
+        """Handle model exclusion request
+        
+        Args:
+            request: The aiohttp request
+            scanner: The model scanner instance with cache management methods
+            
+        Returns:
+            web.Response: The HTTP response
+        """
+        try:
+            data = await request.json()
+            file_path = data.get('file_path')
+            if not file_path:
+                return web.Response(text='Model path is required', status=400)
+
+            # Update metadata to mark as excluded
+            metadata_path = os.path.splitext(file_path)[0] + '.metadata.json'
+            metadata = await ModelRouteUtils.load_local_metadata(metadata_path)
+            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)
+
+            # Update cache
+            cache = await scanner.get_cached_data()
+
+            # Find and remove model from cache
+            model_to_remove = next((item for item in cache.raw_data if item['file_path'] == file_path), None)
+            if model_to_remove:
+                # Update tags count
+                for tag in model_to_remove.get('tags', []):
+                    if tag in scanner._tags_count:
+                        scanner._tags_count[tag] = max(0, scanner._tags_count[tag] - 1)
+                        if scanner._tags_count[tag] == 0:
+                            del scanner._tags_count[tag]
+
+                # Remove from hash index if available
+                if hasattr(scanner, '_hash_index') and scanner._hash_index:
+                    scanner._hash_index.remove_by_path(file_path)
+
+                # Remove from cache data
+                cache.raw_data = [item for item in cache.raw_data if item['file_path'] != file_path]
+                await cache.resort()
+            
+            # Add to excluded models list
+            scanner._excluded_models.append(file_path)
+            
+            return web.json_response({
+                'success': True,
+                'message': f"Model {os.path.basename(file_path)} excluded"
+            })
+            
+        except Exception as e:
+            logger.error(f"Error excluding model: {e}", exc_info=True)
+            return web.Response(text=str(e), status=500)
+
     @staticmethod
     async def handle_download_model(request: web.Request, download_manager: DownloadManager, model_type="lora") -> web.Response:
         """Handle model download request
@@ -500,4 +560,4 @@ class ModelRouteUtils:
                 )
             
             logger.error(f"Error downloading {model_type}: {error_message}")
-            return web.Response(status=500, text=error_message)
+            return web.Response(status=500, text=error_message)

py/utils/usage_stats.py

@@ -1,5 +1,6 @@
 import os
 import json
+import sys
 import time
 import asyncio
 import logging
@@ -7,8 +8,13 @@ from typing import Dict, Set
 
 from ..config import config
 from ..services.service_registry import ServiceRegistry
-from ..metadata_collector.metadata_registry import MetadataRegistry
-from ..metadata_collector.constants import MODELS, LORAS
+
+# Check if running in standalone mode
+standalone_mode = 'nodes' not in sys.modules
+
+if not standalone_mode:
+    from ..metadata_collector.metadata_registry import MetadataRegistry
+    from ..metadata_collector.constants import MODELS, LORAS
 
 logger = logging.getLogger(__name__)
 

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "LoRA Manager for ComfyUI - Access it at http://localhost:8188/loras for managing LoRA models with previews and metadata integration."
-version = "0.8.9"
+version = "0.8.12"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

refs/test_output.txt

@@ -1,294 +0,0 @@
-Loading workflow from D:\Workspace\ComfyUI\custom_nodes\ComfyUI-Lora-Manager\refs\prompt.json
-Expected output from D:\Workspace\ComfyUI\custom_nodes\ComfyUI-Lora-Manager\refs\output.json
-
-Expected output:
-{
-  "loras": "<lora:ck-neon-retrowave-IL-000012:0.8> <lora:aorunIllstrious:1> <lora:ck-shadow-circuit-IL-000012:0.78> <lora:MoriiMee_Gothic_Niji_Style_Illustrious_r1:0.45> <lora:ck-nc-cyberpunk-IL-000011:0.4>",
-  "gen_params": {
-    "prompt": "in the style of ck-rw, aorun, scales, makeup, bare shoulders, pointy ears, dress, claws, in the style of cksc, artist:moriimee, in the style of cknc, masterpiece, best quality, good quality, very aesthetic, absurdres, newest, 8K, depth of field, focused subject, close up, stylized, in gold and neon shades, wabi sabi, 1girl, rainbow angel wings, looking at viewer, dynamic angle, from below, from side, relaxing",
-    "negative_prompt": "bad quality, worst quality, worst detail, sketch ,signature, watermark, patreon logo, nsfw",
-    "steps": "20",
-    "sampler": "euler_ancestral",
-    "cfg_scale": "8",
-    "seed": "241",
-    "size": "832x1216",
-    "clip_skip": "2"
-  }
-}
-
-Sampler node:
-{
-  "inputs": {
-    "seed": 241,
-    "steps": 20,
-    "cfg": 8,
-    "sampler_name": "euler_ancestral",
-    "scheduler": "karras",
-    "denoise": 1,
-    "model": [
-      "56",
-      0
-    ],
-    "positive": [
-      "6",
-      0
-    ],
-    "negative": [
-      "7",
-      0
-    ],
-    "latent_image": [
-      "5",
-      0
-    ]
-  },
-  "class_type": "KSampler",
-  "_meta": {
-    "title": "KSampler"
-  }
-}
-
-Extracted parameters:
-seed: 241
-steps: 20
-cfg_scale: 8
-
-Positive node (6):
-{
-  "inputs": {
-    "text": [
-      "22",
-      0
-    ],
-    "clip": [
-      "56",
-      1
-    ]
-  },
-  "class_type": "CLIPTextEncode",
-  "_meta": {
-    "title": "CLIP Text Encode (Prompt)"
-  }
-}
-
-Text node (22):
-{
-  "inputs": {
-    "string1": [
-      "55",
-      0
-    ],
-    "string2": [
-      "21",
-      0
-    ],
-    "delimiter": ", "
-  },
-  "class_type": "JoinStrings",
-  "_meta": {
-    "title": "Join Strings"
-  }
-}
-
-String1 node (55):
-{
-  "inputs": {
-    "group_mode": true,
-    "toggle_trigger_words": [
-      {
-        "text": "in the style of ck-rw",
-        "active": true
-      },
-      {
-        "text": "aorun, scales, makeup, bare shoulders, pointy ears",
-        "active": true
-      },
-      {
-        "text": "dress",
-        "active": true
-      },
-      {
-        "text": "claws",
-        "active": true
-      },
-      {
-        "text": "in the style of cksc",
-        "active": true
-      },
-      {
-        "text": "artist:moriimee",
-        "active": true
-      },
-      {
-        "text": "in the style of cknc",
-        "active": true
-      },
-      {
-        "text": "__dummy_item__",
-        "active": false,
-        "_isDummy": true
-      },
-      {
-        "text": "__dummy_item__",
-        "active": false,
-        "_isDummy": true
-      }
-    ],
-    "orinalMessage": "in the style of ck-rw,, aorun, scales, makeup, bare shoulders, pointy ears,, dress,, claws,, in the style of cksc,, artist:moriimee,, in the style of cknc",
-    "trigger_words": [
-      "56",
-      2
-    ]
-  },
-  "class_type": "TriggerWord Toggle (LoraManager)",
-  "_meta": {
-    "title": "TriggerWord Toggle (LoraManager)"
-  }
-}
-
-String2 node (21):
-{
-  "inputs": {
-    "string": "masterpiece, best quality, good quality, very aesthetic, absurdres, newest, 8K, depth of field, focused subject, close up, stylized, in gold and neon shades, wabi sabi, 1girl, rainbow angel wings, looking at viewer, dynamic angle, from below, from side, relaxing",
-    "strip_newlines": false
-  },
-  "class_type": "StringConstantMultiline",
-  "_meta": {
-    "title": "positive"
-  }
-}
-
-Negative node (7):
-{
-  "inputs": {
-    "text": "bad quality, worst quality, worst detail, sketch ,signature, watermark, patreon logo, nsfw",
-    "clip": [
-      "56",
-      1
-    ]
-  },
-  "class_type": "CLIPTextEncode",
-  "_meta": {
-    "title": "CLIP Text Encode (Prompt)"
-  }
-}
-
-LoRA nodes (3):
-
-LoRA node 56:
-{
-  "inputs": {
-    "text": "<lora:ck-shadow-circuit-IL-000012:0.78> <lora:MoriiMee_Gothic_Niji_Style_Illustrious_r1:0.45> <lora:ck-nc-cyberpunk-IL-000011:0.4>",
-    "loras": [
-      {
-        "name": "ck-shadow-circuit-IL-000012",
-        "strength": 0.78,
-        "active": true
-      },
-      {
-        "name": "MoriiMee_Gothic_Niji_Style_Illustrious_r1",
-        "strength": 0.45,
-        "active": true
-      },
-      {
-        "name": "ck-nc-cyberpunk-IL-000011",
-        "strength": 0.4,
-        "active": true
-      },
-      {
-        "name": "__dummy_item1__",
-        "strength": 0,
-        "active": false,
-        "_isDummy": true
-      },
-      {
-        "name": "__dummy_item2__",
-        "strength": 0,
-        "active": false,
-        "_isDummy": true
-      }
-    ],
-    "model": [
-      "4",
-      0
-    ],
-    "clip": [
-      "4",
-      1
-    ],
-    "lora_stack": [
-      "57",
-      0
-    ]
-  },
-  "class_type": "Lora Loader (LoraManager)",
-  "_meta": {
-    "title": "Lora Loader (LoraManager)"
-  }
-}
-
-LoRA node 57:
-{
-  "inputs": {
-    "text": "<lora:aorunIllstrious:1>",
-    "loras": [
-      {
-        "name": "aorunIllstrious",
-        "strength": "0.90",
-        "active": true
-      },
-      {
-        "name": "__dummy_item1__",
-        "strength": 0,
-        "active": false,
-        "_isDummy": true
-      },
-      {
-        "name": "__dummy_item2__",
-        "strength": 0,
-        "active": false,
-        "_isDummy": true
-      }
-    ],
-    "lora_stack": [
-      "59",
-      0
-    ]
-  },
-  "class_type": "Lora Stacker (LoraManager)",
-  "_meta": {
-    "title": "Lora Stacker (LoraManager)"
-  }
-}
-
-LoRA node 59:
-{
-  "inputs": {
-    "text": "<lora:ck-neon-retrowave-IL-000012:0.8>",
-    "loras": [
-      {
-        "name": "ck-neon-retrowave-IL-000012",
-        "strength": 0.8,
-        "active": true
-      },
-      {
-        "name": "__dummy_item1__",
-        "strength": 0,
-        "active": false,
-        "_isDummy": true
-      },
-      {
-        "name": "__dummy_item2__",
-        "strength": 0,
-        "active": false,
-        "_isDummy": true
-      }
-    ]
-  },
-  "class_type": "Lora Stacker (LoraManager)",
-  "_meta": {
-    "title": "Lora Stacker (LoraManager)"
-  }
-}
-
-Test completed.

requirements.txt

@@ -7,4 +7,6 @@ piexif
 Pillow
 olefile
 requests
-toml
+toml
+numpy
+torch

settings.json.example

@@ -0,0 +1,14 @@
+{
+  "civitai_api_key": "your_civitai_api_key_here",
+  "show_only_sfw": false,
+  "folder_paths": {
+    "loras": [
+      "C:/path/to/your/loras_folder",
+      "C:/path/to/another/loras_folder"
+    ],
+    "checkpoints": [
+      "C:/path/to/your/checkpoints_folder",
+      "C:/path/to/another/checkpoints_folder"
+    ]
+  }
+}

standalone.py

@@ -0,0 +1,358 @@
+import os
+import sys
+import json
+
+# Create mock folder_paths module BEFORE any other imports
+class MockFolderPaths:
+    @staticmethod
+    def get_folder_paths(folder_name):
+        # Load paths from settings.json
+        settings_path = os.path.join(os.path.dirname(__file__), 'settings.json')
+        try:
+            if os.path.exists(settings_path):
+                with open(settings_path, 'r', encoding='utf-8') as f:
+                    settings = json.load(f)
+                
+                # For diffusion_models, combine unet and diffusers paths
+                if folder_name == "diffusion_models":
+                    paths = []
+                    if 'folder_paths' in settings:
+                        if 'unet' in settings['folder_paths']:
+                            paths.extend(settings['folder_paths']['unet'])
+                        if 'diffusers' in settings['folder_paths']:
+                            paths.extend(settings['folder_paths']['diffusers'])
+                    # Filter out paths that don't exist
+                    valid_paths = [p for p in paths if os.path.exists(p)]
+                    if valid_paths:
+                        return valid_paths
+                    else:
+                        print(f"Warning: No valid paths found for {folder_name}")
+                # For other folder names, return their paths directly
+                elif 'folder_paths' in settings and folder_name in settings['folder_paths']:
+                    paths = settings['folder_paths'][folder_name]
+                    valid_paths = [p for p in paths if os.path.exists(p)]
+                    if valid_paths:
+                        return valid_paths
+                    else:
+                        print(f"Warning: No valid paths found for {folder_name}")
+        except Exception as e:
+            print(f"Error loading folder paths from settings: {e}")
+        
+        # Fallback to empty list if no paths found
+        return []
+    
+    @staticmethod
+    def get_temp_directory():
+        return os.path.join(os.path.dirname(__file__), 'temp')
+    
+    @staticmethod
+    def set_temp_directory(path):
+        os.makedirs(path, exist_ok=True)
+        return path
+
+# Create mock server module with PromptServer
+class MockPromptServer:
+    def __init__(self):
+        self.app = None
+        
+    def send_sync(self, *args, **kwargs):
+        pass
+
+# Create mock metadata_collector module
+class MockMetadataCollector:
+    def init(self):
+        pass
+    
+    def get_metadata(self, prompt_id=None):
+        return {}
+
+# Initialize basic mocks before any imports
+sys.modules['folder_paths'] = MockFolderPaths()
+sys.modules['server'] = type('server', (), {'PromptServer': MockPromptServer()})
+sys.modules['py.metadata_collector'] = MockMetadataCollector()
+
+# Now we can safely import modules that depend on folder_paths and server
+import argparse
+import asyncio
+import logging
+from aiohttp import web
+
+# Setup logging
+logging.basicConfig(level=logging.INFO, 
+                    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger("lora-manager-standalone")
+
+# Configure aiohttp access logger to be less verbose
+logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
+
+# Now we can import the global config from our local modules
+from py.config import config
+
+class StandaloneServer:
+    """Server implementation for standalone mode"""
+    
+    def __init__(self):
+        self.app = web.Application(logger=logger)
+        self.instance = self  # Make it compatible with PromptServer.instance pattern
+        
+        # Ensure the app's access logger is configured to reduce verbosity
+        self.app._subapps = []  # Ensure this exists to avoid AttributeError
+        
+        # Configure access logging for the app
+        self.app.on_startup.append(self._configure_access_logger)
+    
+    async def _configure_access_logger(self, app):
+        """Configure access logger to reduce verbosity"""
+        logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
+        
+        # If using aiohttp>=3.8.0, configure access logger through app directly
+        if hasattr(app, 'access_logger'):
+            app.access_logger.setLevel(logging.WARNING)
+    
+    async def setup(self):
+        """Set up the standalone server"""
+        # Create placeholders for compatibility with ComfyUI's implementation
+        self.last_prompt_id = None
+        self.last_node_id = None
+        self.client_id = None
+        
+        # Set up routes
+        self.setup_routes()
+        
+        # Add startup and shutdown handlers
+        self.app.on_startup.append(self.on_startup)
+        self.app.on_shutdown.append(self.on_shutdown)
+    
+    def setup_routes(self):
+        """Set up basic routes"""
+        # Add a simple status endpoint
+        self.app.router.add_get('/', self.handle_status)
+        
+        # Add static route for example images if the path exists in settings
+        settings_path = os.path.join(os.path.dirname(__file__), 'settings.json')
+        if os.path.exists(settings_path):
+            with open(settings_path, 'r', encoding='utf-8') as f:
+                settings = json.load(f)
+            example_images_path = settings.get('example_images_path')
+            logger.info(f"Example images path: {example_images_path}")
+            if example_images_path and os.path.exists(example_images_path):
+                self.app.router.add_static('/example_images_static', example_images_path)
+                logger.info(f"Added static route for example images: /example_images_static -> {example_images_path}")
+    
+    async def handle_status(self, request):
+        """Handle status request by redirecting to loras page"""
+        # Redirect to loras page instead of showing status
+        raise web.HTTPFound('/loras')
+        
+        # Original JSON response (commented out)
+        # return web.json_response({
+        #     "status": "running",
+        #     "mode": "standalone",
+        #     "loras_roots": config.loras_roots,
+        #     "checkpoints_roots": config.checkpoints_roots
+        # })
+    
+    async def on_startup(self, app):
+        """Startup handler"""
+        logger.info("LoRA Manager standalone server starting...")
+    
+    async def on_shutdown(self, app):
+        """Shutdown handler"""
+        logger.info("LoRA Manager standalone server shutting down...")
+    
+    def send_sync(self, event_type, data, sid=None):
+        """Stub for compatibility with PromptServer"""
+        # In standalone mode, we don't have the same websocket system
+        pass
+    
+    async def start(self, host='127.0.0.1', port=8188):
+        """Start the server"""
+        runner = web.AppRunner(self.app)
+        await runner.setup()
+        site = web.TCPSite(runner, host, port)
+        await site.start()
+
+        # Log the server address with a clickable localhost URL regardless of the actual binding
+        logger.info(f"Server started at http://127.0.0.1:{port}")
+        
+        # Keep the server running
+        while True:
+            await asyncio.sleep(3600)  # Sleep for a long time
+    
+    async def publish_loop(self):
+        """Stub for compatibility with PromptServer"""
+        # This method exists in ComfyUI's server but we don't need it
+        pass
+
+# After all mocks are in place, import LoraManager
+from py.lora_manager import LoraManager
+
+class StandaloneLoraManager(LoraManager):
+    """Extended LoraManager for standalone mode"""
+    
+    @classmethod
+    def add_routes(cls, server_instance):
+        """Initialize and register all routes for standalone mode"""
+        app = server_instance.app
+        
+        # Store app in a global-like location for compatibility
+        sys.modules['server'].PromptServer.instance = server_instance
+
+        # Configure aiohttp access logger to be less verbose
+        logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
+        
+        added_targets = set()  # Track already added target paths
+        
+        # Add static routes for each lora root
+        for idx, root in enumerate(config.loras_roots, start=1):
+            if not os.path.exists(root):
+                logger.warning(f"Lora root path does not exist: {root}")
+                continue
+                
+            preview_path = f'/loras_static/root{idx}/preview'
+            
+            # Check if this root is a link path in the mappings
+            real_root = root
+            for target, link in config._path_mappings.items():
+                if os.path.normpath(link) == os.path.normpath(root):
+                    # If so, route should point to the target (real path)
+                    real_root = target
+                    break
+            
+            # Normalize and standardize path display for consistency
+            display_root = real_root.replace('\\', '/')
+            
+            # Add static route for original path - use the normalized path
+            app.router.add_static(preview_path, real_root)
+            logger.info(f"Added static route {preview_path} -> {display_root}")
+            
+            # Record route mapping with normalized path
+            config.add_route_mapping(real_root, preview_path)
+            added_targets.add(os.path.normpath(real_root))
+        
+        # Add static routes for each checkpoint root
+        for idx, root in enumerate(config.checkpoints_roots, start=1):
+            if not os.path.exists(root):
+                logger.warning(f"Checkpoint root path does not exist: {root}")
+                continue
+                
+            preview_path = f'/checkpoints_static/root{idx}/preview'
+            
+            # Check if this root is a link path in the mappings
+            real_root = root
+            for target, link in config._path_mappings.items():
+                if os.path.normpath(link) == os.path.normpath(root):
+                    # If so, route should point to the target (real path)
+                    real_root = target
+                    break
+            
+            # Normalize and standardize path display for consistency
+            display_root = real_root.replace('\\', '/')
+            
+            # Add static route for original path
+            app.router.add_static(preview_path, real_root)
+            logger.info(f"Added static route {preview_path} -> {display_root}")
+            
+            # Record route mapping
+            config.add_route_mapping(real_root, preview_path)
+            added_targets.add(os.path.normpath(real_root))
+        
+        # Add static routes for symlink target paths that aren't already covered
+        link_idx = {
+            'lora': 1,
+            'checkpoint': 1
+        }
+        
+        for target_path, link_path in config._path_mappings.items():
+            norm_target = os.path.normpath(target_path)
+            if norm_target not in added_targets:
+                # Determine if this is a checkpoint or lora link based on path
+                is_checkpoint = any(os.path.normpath(cp_root) in os.path.normpath(link_path) for cp_root in config.checkpoints_roots)
+                is_checkpoint = is_checkpoint or any(os.path.normpath(cp_root) in norm_target for cp_root in config.checkpoints_roots)
+                
+                if is_checkpoint:
+                    route_path = f'/checkpoints_static/link_{link_idx["checkpoint"]}/preview'
+                    link_idx["checkpoint"] += 1
+                else:
+                    route_path = f'/loras_static/link_{link_idx["lora"]}/preview'
+                    link_idx["lora"] += 1
+                
+                # Display path with forward slashes for consistency
+                display_target = target_path.replace('\\', '/')
+                
+                app.router.add_static(route_path, target_path)
+                logger.info(f"Added static route for link target {route_path} -> {display_target}")
+                config.add_route_mapping(target_path, route_path)
+                added_targets.add(norm_target)
+        
+        # Add static route for plugin assets
+        app.router.add_static('/loras_static', config.static_path)
+        
+        # Setup feature routes
+        from py.routes.lora_routes import LoraRoutes
+        from py.routes.api_routes import ApiRoutes
+        from py.routes.recipe_routes import RecipeRoutes
+        from py.routes.checkpoints_routes import CheckpointsRoutes
+        from py.routes.update_routes import UpdateRoutes
+        from py.routes.misc_routes import MiscRoutes
+        
+        lora_routes = LoraRoutes()
+        checkpoints_routes = CheckpointsRoutes()
+        
+        # Initialize routes
+        lora_routes.setup_routes(app)
+        checkpoints_routes.setup_routes(app)
+        ApiRoutes.setup_routes(app)
+        RecipeRoutes.setup_routes(app)
+        UpdateRoutes.setup_routes(app)
+        MiscRoutes.setup_routes(app)
+        
+        # Schedule service initialization
+        app.on_startup.append(lambda app: cls._initialize_services())
+        
+        # Add cleanup
+        app.on_shutdown.append(cls._cleanup)
+        app.on_shutdown.append(ApiRoutes.cleanup)
+
+def parse_args():
+    """Parse command line arguments"""
+    parser = argparse.ArgumentParser(description="LoRA Manager Standalone Server")
+    parser.add_argument("--host", type=str, default="0.0.0.0", 
+                        help="Host address to bind the server to (default: 0.0.0.0)")
+    parser.add_argument("--port", type=int, default=8188,
+                        help="Port to bind the server to (default: 8188, access via http://localhost:8188/loras)")
+    # parser.add_argument("--loras", type=str, nargs="+", 
+    #                     help="Additional paths to LoRA model directories (optional if settings.json has paths)")
+    # parser.add_argument("--checkpoints", type=str, nargs="+",
+    #                     help="Additional paths to checkpoint model directories (optional if settings.json has paths)")
+    parser.add_argument("--log-level", type=str, default="INFO",
+                        choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"],
+                        help="Logging level")
+    return parser.parse_args()
+
+async def main():
+    """Main entry point for standalone mode"""
+    args = parse_args()
+    
+    # Set log level
+    logging.getLogger().setLevel(getattr(logging, args.log_level))
+    
+    # Explicitly configure aiohttp access logger regardless of selected log level
+    logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
+    
+    # Create the server instance
+    server = StandaloneServer()
+    
+    # Initialize routes via the standalone lora manager
+    StandaloneLoraManager.add_routes(server)
+    
+    # Set up and start the server
+    await server.setup()
+    await server.start(host=args.host, port=args.port)
+
+if __name__ == "__main__":
+    try:
+        # Run the main function
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        logger.info("Server stopped by user")

static/css/components/alphabet-bar.css

@@ -0,0 +1,165 @@
+/* Alphabet Bar Component */
+.alphabet-bar-container {
+    position: fixed;
+    left: 0;
+    top: 50%;
+    transform: translateY(-50%);
+    z-index: 100;
+    display: flex;
+    transition: transform 0.3s ease;
+}
+
+.alphabet-bar-container.collapsed {
+    transform: translateY(-50%) translateX(-90%);
+}
+
+/* New visual indicator for when a letter is active and bar is collapsed */
+.alphabet-bar-container.collapsed .toggle-alphabet-bar.has-active-letter {
+    border-color: var(--lora-accent);
+    background: oklch(var(--lora-accent) / 0.15);
+}
+
+.alphabet-bar-container.collapsed .toggle-alphabet-bar.has-active-letter::after {
+    content: '';
+    position: absolute;
+    top: 7px;
+    right: 7px;
+    width: 8px;
+    height: 8px;
+    background-color: var(--lora-accent);
+    border-radius: 50%;
+    animation: pulse-active 2s infinite;
+}
+
+@keyframes pulse-active {
+    0% { transform: scale(0.8); opacity: 0.7; }
+    50% { transform: scale(1.1); opacity: 1; }
+    100% { transform: scale(0.8); opacity: 0.7; }
+}
+
+.alphabet-bar {
+    background: var(--card-bg);
+    border: 1px solid var(--border-color);
+    border-radius: 0 var(--border-radius-xs) var(--border-radius-xs) 0;
+    padding: 8px 4px;
+    display: flex;
+    flex-direction: column;
+    gap: 6px;
+    align-items: center;
+    box-shadow: 2px 0 8px rgba(0, 0, 0, 0.1);
+    max-height: 80vh;
+    overflow-y: auto;
+    scrollbar-width: thin;
+}
+
+.alphabet-bar::-webkit-scrollbar {
+    width: 4px;
+}
+
+.alphabet-bar::-webkit-scrollbar-thumb {
+    background: var(--border-color);
+    border-radius: 4px;
+}
+
+.toggle-alphabet-bar {
+    background: var(--card-bg);
+    border: 1px solid var(--border-color);
+    border-left: none;
+    border-radius: 0 var(--border-radius-xs) var(--border-radius-xs) 0;
+    padding: 8px 4px;
+    cursor: pointer;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    color: var(--text-color);
+    width: 20px;
+    height: 40px;
+    align-self: center;
+    box-shadow: 2px 0 8px rgba(0, 0, 0, 0.1);
+}
+
+.toggle-alphabet-bar:hover {
+    background: var(--bg-hover);
+}
+
+.toggle-alphabet-bar i {
+    transition: transform 0.3s ease;
+}
+
+.alphabet-bar-container.collapsed .toggle-alphabet-bar i {
+    transform: rotate(180deg);
+}
+
+.letter-chip {
+    padding: 4px 2px;
+    border-radius: var(--border-radius-xs);
+    background: var(--bg-color);
+    color: var(--text-color);
+    cursor: pointer;
+    min-width: 24px;
+    text-align: center;
+    font-size: 0.85em;
+    transition: all 0.2s ease;
+    border: 1px solid var(--border-color);
+}
+
+.letter-chip:hover {
+    background: var(--lora-accent);
+    color: white;
+    transform: scale(1.1);
+    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+}
+
+.letter-chip.active {
+    background: var(--lora-accent);
+    color: white;
+    border-color: var(--lora-accent);
+}
+
+.letter-chip.disabled {
+    opacity: 0.5;
+    pointer-events: none;
+    cursor: default;
+}
+
+/* Hide the count by default, only show in tooltip */
+.letter-chip .count {
+    display: none;
+}
+
+.alphabet-bar-title {
+    font-size: 0.75em;
+    color: var(--text-color);
+    opacity: 0.7;
+    margin-bottom: 6px;
+    writing-mode: vertical-lr;
+    transform: rotate(180deg);
+    white-space: nowrap;
+}
+
+@media (max-width: 768px) {
+    .alphabet-bar-container {
+        transform: translateY(-50%) translateX(-90%);
+    }
+    
+    .alphabet-bar-container.active {
+        transform: translateY(-50%) translateX(0);
+    }
+    
+    .letter-chip {
+        padding: 3px 1px;
+        min-width: 20px;
+        font-size: 0.75em;
+    }
+}
+
+/* Keyframe animations for the active letter */
+@keyframes pulse {
+    0% { transform: scale(1); }
+    50% { transform: scale(1.1); }
+    100% { transform: scale(1); }
+}
+
+.letter-chip.active {
+    animation: pulse 1s ease-in-out 1;
+}

static/css/components/download-modal.css

@@ -190,14 +190,6 @@
     border-color: var(--lora-border);
 }
 
-/* Add disabled button styles */
-.primary-btn.disabled {
-    background-color: var(--border-color);
-    color: var(--text-color);
-    opacity: 0.7;
-    cursor: not-allowed;
-}
-
 /* Enhance the local badge to make it more noticeable */
 .version-item.exists-locally {
     background: oklch(var(--lora-accent) / 0.05);

static/css/components/lora-modal.css

@@ -1133,8 +1133,8 @@
     pointer-events: none;
 }
 
-/* Show metadata panel only on hover */
-.media-wrapper:hover .image-metadata-panel {
+/* Show metadata panel only when the 'visible' class is added */
+.media-wrapper .image-metadata-panel.visible {
     transform: translateY(0);
     opacity: 0.98;
     pointer-events: auto;

static/css/components/modal.css

@@ -44,26 +44,12 @@ body.modal-open {
 }
 
 /* Delete Modal specific styles */
-.delete-modal-content {
-    max-width: 500px;
-    text-align: center;
-}
 
 .delete-message {
     color: var(--text-color);
     margin: var(--space-2) 0;
 }
 
-.delete-model-info {
-    background: var(--lora-surface);
-    border: 1px solid var(--lora-border);
-    border-radius: var(--border-radius-sm);
-    padding: var(--space-2);
-    margin: var(--space-2) 0;
-    color: var(--text-color);
-    word-break: break-all;
-}
-
 /* Update delete modal styles */
 .delete-modal {
     display: none;  /* Set initial display to none */
@@ -92,7 +78,8 @@ body.modal-open {
     animation: modalFadeIn 0.2s ease-out;
 }
 
-.delete-model-info {
+.delete-model-info,
+.exclude-model-info {
     /* Update info display styling */
     background: var(--lora-surface);
     border: 1px solid var(--lora-border);
@@ -123,7 +110,7 @@ body.modal-open {
     margin-top: var(--space-3);
 }
 
-.cancel-btn, .delete-btn {
+.cancel-btn, .delete-btn, .exclude-btn {
     padding: 8px var(--space-2);
     border-radius: 6px;
     border: none;
@@ -143,6 +130,12 @@ body.modal-open {
     color: white;
 }
 
+/* Style for exclude button - different from delete button */
+.exclude-btn {
+    background: var(--lora-accent, #4f46e5);
+    color: white;
+}
+
 .cancel-btn:hover {
     background: var(--lora-border);
 }
@@ -151,6 +144,11 @@ body.modal-open {
     opacity: 0.9;
 }
 
+.exclude-btn:hover {
+    opacity: 0.9;
+    background: oklch(from var(--lora-accent, #4f46e5) l c h / 85%);
+}
+
 .modal-content h2 {
     color: var(--text-color);
     margin-bottom: var(--space-2);
@@ -496,6 +494,107 @@ input:checked + .toggle-slider:before {
     filter: blur(8px);
 }
 
+/* Example Images Settings Styles */
+.download-buttons {
+    justify-content: flex-start;
+    gap: var(--space-2);
+}
+
+.primary-btn {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 8px 16px;
+    background-color: var(--lora-accent);
+    color: var(--lora-text);
+    border: none;
+    border-radius: var(--border-radius-sm);
+    cursor: pointer;
+    transition: background-color 0.2s;
+    font-size: 0.95em;
+}
+
+.primary-btn:hover {
+    background-color: oklch(from var(--lora-accent) l c h / 85%);
+    color: var(--lora-text);
+}
+
+/* Secondary button styles */
+.secondary-btn {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 8px 16px;
+    background-color: var(--card-bg);
+    color: var(--text-color);
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-sm);
+    cursor: pointer;
+    transition: all 0.2s;
+    font-size: 0.95em;
+}
+
+.secondary-btn:hover {
+    background-color: var(--border-color);
+    color: var(--text-color);
+}
+
+/* Disabled button styles */
+.primary-btn.disabled {
+    opacity: 0.5;
+    cursor: not-allowed;
+    background-color: var(--lora-accent);
+    color: var(--lora-text);
+    pointer-events: none;
+}
+
+.secondary-btn.disabled {
+    opacity: 0.5;
+    cursor: not-allowed;
+    pointer-events: none;
+}
+
+/* Dark theme specific button adjustments */
+[data-theme="dark"] .primary-btn:hover {
+    background-color: oklch(from var(--lora-accent) l c h / 75%);
+}
+
+[data-theme="dark"] .secondary-btn {
+    background-color: var(--lora-surface);
+}
+
+[data-theme="dark"] .secondary-btn:hover {
+    background-color: oklch(35% 0.02 256 / 0.98);
+}
+
+.primary-btn.disabled {
+    opacity: 0.5;
+    cursor: not-allowed;
+}
+
+.path-control {
+    display: flex;
+    gap: 8px;
+    align-items: center;
+    width: 100%;
+}
+
+.path-control input[type="text"] {
+    flex: 1;
+    padding: 6px 10px;
+    border-radius: var(--border-radius-xs);
+    border: 1px solid var(--border-color);
+    background-color: var(--lora-surface);
+    color: var (--text-color);
+    font-size: 0.95em;
+    height: 32px;
+}
+
+.primary-btn.disabled {
+    opacity: 0.5;
+    cursor: not-allowed;
+}
+
 /* Add styles for delete preview image */
 .delete-preview {
     max-width: 150px;

static/css/components/progress-panel.css

@@ -0,0 +1,215 @@
+/* Progress Panel Styles */
+.progress-panel {
+    position: fixed;
+    bottom: 20px;
+    right: 20px;
+    width: 350px;
+    background: var(--lora-surface);
+    border: 1px solid var(--lora-border);
+    border-radius: var(--border-radius-sm);
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
+    z-index: calc(var(--z-modal) - 1);
+    transition: transform 0.3s ease, opacity 0.3s ease;
+    opacity: 0;
+    transform: translateY(20px);
+}
+
+.progress-panel.visible {
+    opacity: 1;
+    transform: translateY(0);
+}
+
+.progress-panel.collapsed .progress-panel-content {
+    display: none;
+}
+
+.progress-panel.collapsed .progress-panel-header {
+    border-bottom: none;
+    padding-bottom: calc(var(--space-2) + 12px);
+}
+
+.progress-panel-header {
+    padding: var(--space-2);
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    border-bottom: 1px solid var(--lora-border);
+}
+
+.progress-panel-title {
+    font-weight: 500;
+    color: var(--text-color);
+    display: flex;
+    align-items: center;
+    gap: 8px;
+}
+
+.progress-panel-actions {
+    display: flex;
+    gap: 6px;
+}
+
+.icon-button {
+    background: none;
+    border: none;
+    color: var(--text-color);
+    width: 24px;
+    height: 24px;
+    border-radius: 50%;
+    cursor: pointer;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    opacity: 0.6;
+    transition: all 0.2s;
+    position: relative;
+}
+
+.icon-button:hover {
+    opacity: 1;
+    background: rgba(0, 0, 0, 0.05);
+}
+
+[data-theme="dark"] .icon-button:hover {
+    background: rgba(255, 255, 255, 0.1);
+}
+
+.progress-panel-content {
+    padding: var(--space-2);
+}
+
+.download-progress-info {
+    margin-bottom: var(--space-2);
+}
+
+.progress-status {
+    display: flex;
+    justify-content: space-between;
+    margin-bottom: 8px;
+    font-size: 0.9em;
+    color: var(--text-color);
+}
+
+/* Use specific selectors to avoid conflicts with loading.css */
+.progress-panel .progress-container {
+    width: 100%;
+    background-color: var(--lora-border);
+    border-radius: 4px;
+    overflow: hidden;
+    height: var(--space-1);
+}
+
+.progress-panel .progress-bar {
+    width: 0%;
+    height: 100%;
+    background-color: var(--lora-accent);
+    transition: width 0.5s ease;
+}
+
+.current-model-info {
+    background: var(--bg-color);
+    border-radius: var(--border-radius-xs);
+    padding: 8px;
+    margin-bottom: var(--space-2);
+    font-size: 0.95em;
+}
+
+.current-label {
+    font-size: 0.85em;
+    color: var(--text-color);
+    opacity: 0.7;
+    margin-bottom: 4px;
+}
+
+.current-model-name {
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    color: var(--text-color);
+}
+
+.download-stats {
+    display: flex;
+    justify-content: space-between;
+    margin-bottom: var(--space-2);
+}
+
+.stat-item {
+    font-size: 0.9em;
+    color: var(--text-color);
+}
+
+.stat-label {
+    opacity: 0.7;
+    margin-right: 4px;
+}
+
+.download-errors {
+    background: oklch(var(--lora-warning) / 0.1);
+    border: 1px solid var(--lora-warning);
+    border-radius: var(--border-radius-xs);
+    padding: var(--space-1);
+    max-height: 100px;
+    overflow-y: auto;
+    font-size: 0.85em;
+}
+
+.error-header {
+    color: var(--lora-warning);
+    font-weight: 500;
+    margin-bottom: 4px;
+}
+
+.error-list {
+    color: var(--text-color);
+    opacity: 0.85;
+}
+
+.hidden {
+    display: none !important;
+}
+
+/* Mini progress indicator on pause button when panel collapsed */
+.mini-progress-container {
+    position: absolute;
+    top: 0;
+    left: 0;
+    width: 100%;
+    height: 100%;
+    border-radius: 50%;
+    pointer-events: none;
+    opacity: 0; /* Hide by default */
+    transition: opacity 0.2s ease;
+}
+
+/* Show mini progress when panel is collapsed */
+.progress-panel.collapsed .mini-progress-container {
+    opacity: 1;
+}
+
+.mini-progress-circle {
+    stroke: var(--lora-accent);
+    fill: none;
+    stroke-width: 2.5;
+    stroke-linecap: round;
+    transform: rotate(-90deg);
+    transform-origin: center;
+    transition: stroke-dashoffset 0.3s ease;
+}
+
+.mini-progress-background {
+    stroke: var(--lora-border);
+    fill: none;
+    stroke-width: 2;
+}
+
+.progress-percent {
+    position: absolute;
+    top: 100%;
+    left: 50%;
+    transform: translateX(-50%);
+    font-size: 0.65em;
+    color: var(--text-color);
+    opacity: 0.8;
+    white-space: nowrap;
+}

static/css/components/support-modal.css

@@ -117,9 +117,50 @@
     box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
 }
 
+/* QR Code section styles */
+.qrcode-toggle {
+    width: 100%;
+    margin-top: var(--space-2);
+    justify-content: center;
+    position: relative;
+}
+
+.qrcode-toggle .toggle-icon {
+    margin-left: 8px;
+    transition: transform 0.3s ease;
+}
+
+.qrcode-toggle.active .toggle-icon {
+    transform: rotate(180deg);
+}
+
+.qrcode-container {
+    max-height: 0;
+    overflow: hidden;
+    transition: max-height 0.4s ease, opacity 0.3s ease;
+    opacity: 0;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+}
+
+.qrcode-container.show {
+    max-height: 500px;
+    opacity: 1;
+    margin-top: var(--space-3);
+}
+
+.qrcode-image {
+    max-width: 80%;
+    height: auto;
+    border-radius: var(--border-radius-sm);
+    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
+    border: 1px solid var(--lora-border);
+    aspect-ratio: 1/1; /* Ensure proper aspect ratio for the square QR code */
+}
+
 .support-footer {
     text-align: center;
-    margin-top: var(--space-1);
     font-style: italic;
     color: var(--text-color);
 }

static/css/layout.css

@@ -260,8 +260,8 @@
 /* Back to Top Button */
 .back-to-top {
     position: fixed;
-    bottom: 20px;
-    right: 20px;
+    bottom: 85px;
+    right: 30px;
     width: 36px;
     height: 36px;
     border-radius: 50%;

static/css/style.css

@@ -20,6 +20,8 @@
 @import 'components/shared.css';
 @import 'components/filter-indicator.css';
 @import 'components/initialization.css';
+@import 'components/progress-panel.css';
+@import 'components/alphabet-bar.css'; /* Add alphabet bar component */
 
 .initialization-notice {
     display: flex;

static/js/api/baseModelApi.js

@@ -49,6 +49,11 @@ export async function loadMoreModels(options = {}) {
         if (pageState.showFavoritesOnly) {
             params.append('favorites_only', 'true');
         }
+        
+        // Add active letter filter if set
+        if (pageState.activeLetterFilter) {
+            params.append('first_letter', pageState.activeLetterFilter);
+        }
 
         // Add search parameters if there's a search term
         if (pageState.filters?.search) {
@@ -203,13 +208,44 @@ export function replaceModelPreview(filePath, modelType = 'lora') {
 }
 
 // Delete a model (generic)
-export function deleteModel(filePath, modelType = 'lora') {
-    if (modelType === 'checkpoint') {
-        confirmDelete('Are you sure you want to delete this checkpoint?', () => {
-            performDelete(filePath, modelType);
+export async function deleteModel(filePath, modelType = 'lora') {
+    try {
+        const endpoint = modelType === 'checkpoint' 
+            ? '/api/checkpoints/delete' 
+            : '/api/delete_model';
+            
+        const response = await fetch(endpoint, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                file_path: filePath
+            })
         });
-    } else {
-        showDeleteModal(filePath);
+        
+        if (!response.ok) {
+            throw new Error(`Failed to delete ${modelType}: ${response.statusText}`);
+        }
+        
+        const data = await response.json();
+        
+        if (data.success) {
+            // Remove the card from UI
+            const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
+            if (card) {
+                card.remove();
+            }
+            
+            showToast(`${modelType} deleted successfully`, 'success');
+            return true;
+        } else {
+            throw new Error(data.error || `Failed to delete ${modelType}`);
+        }
+    } catch (error) {
+        console.error(`Error deleting ${modelType}:`, error);
+        showToast(`Failed to delete ${modelType}: ${error.message}`, 'error');
+        return false;
     }
 }
 
@@ -389,6 +425,48 @@ export async function refreshSingleModelMetadata(filePath, modelType = 'lora') {
     }
 }
 
+// Generic function to exclude a model
+export async function excludeModel(filePath, modelType = 'lora') {
+    try {
+        const endpoint = modelType === 'checkpoint' 
+            ? '/api/checkpoints/exclude' 
+            : '/api/loras/exclude';
+            
+        const response = await fetch(endpoint, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                file_path: filePath
+            })
+        });
+        
+        if (!response.ok) {
+            throw new Error(`Failed to exclude ${modelType}: ${response.statusText}`);
+        }
+        
+        const data = await response.json();
+        
+        if (data.success) {
+            // Remove the card from UI
+            const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
+            if (card) {
+                card.remove();
+            }
+            
+            showToast(`${modelType} excluded successfully`, 'success');
+            return true;
+        } else {
+            throw new Error(data.error || `Failed to exclude ${modelType}`);
+        }
+    } catch (error) {
+        console.error(`Error excluding ${modelType}:`, error);
+        showToast(`Failed to exclude ${modelType}: ${error.message}`, 'error');
+        return false;
+    }
+}
+
 // Private methods
 
 // Upload a preview image

static/js/api/checkpointApi.js

@@ -6,7 +6,8 @@ import {
     deleteModel as baseDeleteModel,
     replaceModelPreview,
     fetchCivitaiMetadata,
-    refreshSingleModelMetadata
+    refreshSingleModelMetadata,
+    excludeModel as baseExcludeModel
 } from './baseModelApi.js';
 
 // Load more checkpoints with pagination
@@ -85,4 +86,13 @@ export async function saveModelMetadata(filePath, data) {
     }
     
     return response.json();
+}
+
+/**
+ * Exclude a checkpoint model from being shown in the UI
+ * @param {string} filePath - File path of the checkpoint to exclude
+ * @returns {Promise<boolean>} Promise resolving to success status
+ */
+export function excludeCheckpoint(filePath) {
+    return baseExcludeModel(filePath, 'checkpoint');
 }

static/js/api/loraApi.js

@@ -6,7 +6,8 @@ import {
     deleteModel as baseDeleteModel,
     replaceModelPreview,
     fetchCivitaiMetadata,
-    refreshSingleModelMetadata
+    refreshSingleModelMetadata,
+    excludeModel as baseExcludeModel
 } from './baseModelApi.js';
 
 /**
@@ -34,6 +35,15 @@ export async function saveModelMetadata(filePath, data) {
     return response.json();
 }
 
+/**
+ * Exclude a lora model from being shown in the UI
+ * @param {string} filePath - File path of the model to exclude
+ * @returns {Promise<boolean>} Promise resolving to success status
+ */
+export async function excludeLora(filePath) {
+    return baseExcludeModel(filePath, 'lora');
+}
+
 export async function loadMoreLoras(resetPage = false, updateFolders = false) {
     return loadMoreModels({
         resetPage,

static/js/checkpoints.js

@@ -1,6 +1,6 @@
 import { appCore } from './core.js';
 import { initializeInfiniteScroll } from './utils/infiniteScroll.js';
-import { confirmDelete, closeDeleteModal } from './utils/modalUtils.js';
+import { confirmDelete, closeDeleteModal, confirmExclude, closeExcludeModal } from './utils/modalUtils.js';
 import { createPageControls } from './components/controls/index.js';
 import { loadMoreCheckpoints } from './api/checkpointApi.js';
 import { CheckpointDownloadManager } from './managers/CheckpointDownloadManager.js';
@@ -23,6 +23,8 @@ class CheckpointsPageManager {
         // Minimal set of functions that need to remain global
         window.confirmDelete = confirmDelete;
         window.closeDeleteModal = closeDeleteModal;
+        window.confirmExclude = confirmExclude;
+        window.closeExcludeModal = closeExcludeModal;
         
         // Add loadCheckpoints function to window for FilterManager compatibility
         window.checkpointManager = {

static/js/components/CheckpointCard.js

@@ -3,6 +3,7 @@ import { state } from '../state/index.js';
 import { showCheckpointModal } from './checkpointModal/index.js';
 import { NSFW_LEVELS } from '../utils/constants.js';
 import { replaceCheckpointPreview as apiReplaceCheckpointPreview, saveModelMetadata } from '../api/checkpointApi.js';
+import { showDeleteModal } from '../utils/modalUtils.js';
 
 export function createCheckpointCard(checkpoint) {
     const card = document.createElement('div');
@@ -262,7 +263,7 @@ export function createCheckpointCard(checkpoint) {
     // Delete button click event
     card.querySelector('.fa-trash')?.addEventListener('click', e => {
         e.stopPropagation();
-        deleteCheckpoint(checkpoint.file_path);
+        showDeleteModal(checkpoint.file_path);
     });
 
     // Replace preview button click event
@@ -322,17 +323,6 @@ function openCivitai(modelName) {
     }
 }
 
-function deleteCheckpoint(filePath) {
-    if (window.deleteCheckpoint) {
-        window.deleteCheckpoint(filePath);
-    } else {
-        // Use the modal delete functionality
-        import('../utils/modalUtils.js').then(({ showDeleteModal }) => {
-            showDeleteModal(filePath, 'checkpoint');
-        });
-    }
-}
-
 function replaceCheckpointPreview(filePath) {
     if (window.replaceCheckpointPreview) {
         window.replaceCheckpointPreview(filePath);

static/js/components/ContextMenu/CheckpointContextMenu.js

@@ -3,6 +3,7 @@ import { refreshSingleCheckpointMetadata, saveModelMetadata } from '../../api/ch
 import { showToast, getNSFWLevelName } from '../../utils/uiHelpers.js';
 import { NSFW_LEVELS } from '../../utils/constants.js';
 import { getStorageItem } from '../../utils/storageHelpers.js';
+import { showExcludeModal } from '../../utils/modalUtils.js';
 
 export class CheckpointContextMenu extends BaseContextMenu {
     constructor() {
@@ -61,6 +62,10 @@ export class CheckpointContextMenu extends BaseContextMenu {
                 // Move to folder (placeholder)
                 showToast('Move to folder feature coming soon', 'info');
                 break;
+            case 'exclude':
+                showExcludeModal(this.currentCard.dataset.filepath, 'checkpoint');
+                break;
+
         }
     }
 

static/js/components/ContextMenu/LoraContextMenu.js

@@ -3,6 +3,7 @@ import { refreshSingleLoraMetadata, saveModelMetadata } from '../../api/loraApi.
 import { showToast, getNSFWLevelName } from '../../utils/uiHelpers.js';
 import { NSFW_LEVELS } from '../../utils/constants.js';
 import { getStorageItem } from '../../utils/storageHelpers.js';
+import { showExcludeModal } from '../../utils/modalUtils.js';
 
 export class LoraContextMenu extends BaseContextMenu {
     constructor() {
@@ -51,6 +52,9 @@ export class LoraContextMenu extends BaseContextMenu {
             case 'set-nsfw':
                 this.showNSFWLevelSelector(null, null, this.currentCard);
                 break;
+            case 'exclude':
+                showExcludeModal(this.currentCard.dataset.filepath);
+                break;
         }
     }
 

static/js/components/Header.js

@@ -78,5 +78,33 @@ export class HeaderManager {
           // Handle support panel logic
         });
       }
+
+      // Handle QR code toggle
+      const qrToggle = document.getElementById('toggleQRCode');
+      const qrContainer = document.getElementById('qrCodeContainer');
+      
+      if (qrToggle && qrContainer) {
+          qrToggle.addEventListener('click', function() {
+              qrContainer.classList.toggle('show');
+              qrToggle.classList.toggle('active');
+              
+              const toggleText = qrToggle.querySelector('.toggle-text');
+              if (qrContainer.classList.contains('show')) {
+                  toggleText.textContent = 'Hide WeChat QR Code';
+                  // Add small delay to ensure DOM is updated before scrolling
+                  setTimeout(() => {
+                      const supportModal = document.querySelector('.support-modal');
+                      if (supportModal) {
+                          supportModal.scrollTo({
+                              top: supportModal.scrollHeight,
+                              behavior: 'smooth'
+                          });
+                      }
+                  }, 250);
+              } else {
+                  toggleText.textContent = 'Show WeChat QR Code';
+              }
+          });
+      }
     }
 }

static/js/components/LoraCard.js

@@ -3,7 +3,8 @@ import { state } from '../state/index.js';
 import { showLoraModal } from './loraModal/index.js';
 import { bulkManager } from '../managers/BulkManager.js';
 import { NSFW_LEVELS } from '../utils/constants.js';
-import { replacePreview, deleteModel, saveModelMetadata } from '../api/loraApi.js'
+import { replacePreview, saveModelMetadata } from '../api/loraApi.js'
+import { showDeleteModal } from '../utils/modalUtils.js';
 
 export function createLoraCard(lora) {
     const card = document.createElement('div');
@@ -260,7 +261,7 @@ export function createLoraCard(lora) {
     // Delete button click event
     card.querySelector('.fa-trash')?.addEventListener('click', e => {
         e.stopPropagation();
-        deleteModel(lora.file_path);
+        showDeleteModal(lora.file_path);
     });
 
     // Replace preview button click event

static/js/components/alphabet/AlphabetBar.js

@@ -0,0 +1,319 @@
+// AlphabetBar.js - Component for alphabet filtering
+import { getCurrentPageState, setCurrentPageType } from '../../state/index.js';
+import { getStorageItem, setStorageItem } from '../../utils/storageHelpers.js';
+import { resetAndReload } from '../../api/loraApi.js';
+
+/**
+ * AlphabetBar class - Handles the alphabet filtering UI and interactions
+ */
+export class AlphabetBar {
+    constructor(pageType = 'loras') {
+        // Store the page type
+        this.pageType = pageType;
+        
+        // Get the current page state
+        this.pageState = getCurrentPageState();
+        
+        // Initialize letter counts
+        this.letterCounts = {};
+        
+        // Initialize the component
+        this.initializeComponent();
+    }
+    
+    /**
+     * Initialize the alphabet bar component
+     */
+    async initializeComponent() {
+        // Get letter counts from API
+        await this.fetchLetterCounts();
+        
+        // Initialize event listeners
+        this.initEventListeners();
+        
+        // Restore the active letter filter from storage if available
+        this.restoreActiveLetterFilter();
+        
+        // Restore collapse state from storage
+        this.restoreCollapseState();
+
+        // Update the toggle button indicator if there's an active letter filter
+        this.updateToggleIndicator();
+    }
+    
+    /**
+     * Fetch letter counts from the API
+     */
+    async fetchLetterCounts() {
+        try {
+            const response = await fetch('/api/loras/letter-counts');
+            
+            if (!response.ok) {
+                throw new Error(`Failed to fetch letter counts: ${response.statusText}`);
+            }
+            
+            const data = await response.json();
+            
+            if (data.success && data.letter_counts) {
+                this.letterCounts = data.letter_counts;
+                
+                // Update the count display in the UI
+                this.updateLetterCountsDisplay();
+            }
+        } catch (error) {
+            console.error('Error fetching letter counts:', error);
+        }
+    }
+    
+    /**
+     * Update the letter counts display in the UI
+     */
+    updateLetterCountsDisplay() {
+        const letterChips = document.querySelectorAll('.letter-chip');
+        
+        letterChips.forEach(chip => {
+            const letter = chip.dataset.letter;
+            const count = this.letterCounts[letter] || 0;
+            
+            // Update the title attribute for tooltip display
+            if (count > 0) {
+                chip.title = `${letter}: ${count} LoRAs`;
+                chip.classList.remove('disabled');
+            } else {
+                chip.title = `${letter}: No LoRAs`;
+                chip.classList.add('disabled');
+            }
+            
+            // Keep the count span for backward compatibility
+            const countSpan = chip.querySelector('.count');
+            if (countSpan) {
+                countSpan.textContent = ` (${count})`;
+            }
+        });
+    }
+    
+    /**
+     * Initialize event listeners for the alphabet bar
+     */
+    initEventListeners() {
+        const alphabetBar = document.querySelector('.alphabet-bar');
+        const toggleButton = document.querySelector('.toggle-alphabet-bar');
+        const alphabetBarContainer = document.querySelector('.alphabet-bar-container');
+        
+        if (alphabetBar) {
+            // Use event delegation for letter chips
+            alphabetBar.addEventListener('click', (e) => {
+                const letterChip = e.target.closest('.letter-chip');
+                
+                if (letterChip && !letterChip.classList.contains('disabled')) {
+                    this.handleLetterClick(letterChip);
+                }
+            });
+            
+            // Add toggle button listener
+            if (toggleButton && alphabetBarContainer) {
+                toggleButton.addEventListener('click', () => {
+                    alphabetBarContainer.classList.toggle('collapsed');
+                    
+                    // If expanding and there's an active letter, scroll it into view
+                    if (!alphabetBarContainer.classList.contains('collapsed')) {
+                        this.scrollActiveLetterIntoView();
+                    }
+                    
+                    // Save collapse state to storage
+                    setStorageItem(`${this.pageType}_alphabetBarCollapsed`, 
+                        alphabetBarContainer.classList.contains('collapsed'));
+
+                    // Update toggle indicator
+                    this.updateToggleIndicator();
+                });
+            }
+            
+            // Add keyboard shortcut listeners
+            document.addEventListener('keydown', (e) => {
+                // Alt + letter shortcuts
+                if (e.altKey && !e.ctrlKey && !e.metaKey) {
+                    const key = e.key.toUpperCase();
+                    
+                    // Check if it's a letter A-Z
+                    if (/^[A-Z]$/.test(key)) {
+                        const letterChip = document.querySelector(`.letter-chip[data-letter="${key}"]`);
+                        
+                        if (letterChip && !letterChip.classList.contains('disabled')) {
+                            this.handleLetterClick(letterChip);
+                            e.preventDefault();
+                        }
+                    } 
+                    // Special cases for non-letter filters
+                    else if (e.key === '0' || e.key === ')') {
+                        // Alt+0 for numbers (#)
+                        const letterChip = document.querySelector('.letter-chip[data-letter="#"]');
+                        
+                        if (letterChip && !letterChip.classList.contains('disabled')) {
+                            this.handleLetterClick(letterChip);
+                            e.preventDefault();
+                        }
+                    } else if (e.key === '2' || e.key === '@') {
+                        // Alt+@ for special characters
+                        const letterChip = document.querySelector('.letter-chip[data-letter="@"]');
+                        
+                        if (letterChip && !letterChip.classList.contains('disabled')) {
+                            this.handleLetterClick(letterChip);
+                            e.preventDefault();
+                        }
+                    } else if (e.key === 'c' || e.key === 'C') {
+                        // Alt+C for CJK characters
+                        const letterChip = document.querySelector('.letter-chip[data-letter="漢"]');
+                        
+                        if (letterChip && !letterChip.classList.contains('disabled')) {
+                            this.handleLetterClick(letterChip);
+                            e.preventDefault();
+                        }
+                    }
+                }
+            });
+        }
+    }
+    
+    /**
+     * Restore the collapse state from storage
+     */
+    restoreCollapseState() {
+        const alphabetBarContainer = document.querySelector('.alphabet-bar-container');
+        
+        if (alphabetBarContainer) {
+            const isCollapsed = getStorageItem(`${this.pageType}_alphabetBarCollapsed`);
+            
+            // If there's a stored preference, apply it
+            if (isCollapsed !== null) {
+                if (isCollapsed) {
+                    alphabetBarContainer.classList.add('collapsed');
+                } else {
+                    alphabetBarContainer.classList.remove('collapsed');
+                }
+            }
+        }
+    }
+    
+    /**
+     * Handle letter chip click
+     * @param {HTMLElement} letterChip - The letter chip that was clicked
+     */
+    handleLetterClick(letterChip) {
+        const letter = letterChip.dataset.letter;
+        const wasActive = letterChip.classList.contains('active');
+        
+        // Remove active class from all letter chips
+        document.querySelectorAll('.letter-chip').forEach(chip => {
+            chip.classList.remove('active');
+        });
+        
+        if (!wasActive) {
+            // Set the new active letter
+            letterChip.classList.add('active');
+            this.pageState.activeLetterFilter = letter;
+            
+            // Save to storage
+            setStorageItem(`${this.pageType}_activeLetterFilter`, letter);
+        } else {
+            // Clear the active letter filter
+            this.pageState.activeLetterFilter = null;
+            
+            // Remove from storage
+            setStorageItem(`${this.pageType}_activeLetterFilter`, null);
+        }
+        
+        // Update visual indicator on toggle button
+        this.updateToggleIndicator();
+        
+        // Trigger a reload with the new filter
+        resetAndReload(true);
+    }
+    
+    /**
+     * Restore the active letter filter from storage
+     */
+    restoreActiveLetterFilter() {
+        const activeLetterFilter = getStorageItem(`${this.pageType}_activeLetterFilter`);
+        
+        if (activeLetterFilter) {
+            const letterChip = document.querySelector(`.letter-chip[data-letter="${activeLetterFilter}"]`);
+            
+            if (letterChip && !letterChip.classList.contains('disabled')) {
+                letterChip.classList.add('active');
+                this.pageState.activeLetterFilter = activeLetterFilter;
+                
+                // Scroll the active letter into view if the alphabet bar is expanded
+                this.scrollActiveLetterIntoView();
+            }
+        }
+    }
+    
+    /**
+     * Clear the active letter filter
+     */
+    clearActiveLetterFilter() {
+        // Remove active class from all letter chips
+        document.querySelectorAll('.letter-chip').forEach(chip => {
+            chip.classList.remove('active');
+        });
+        
+        // Clear the active letter filter
+        this.pageState.activeLetterFilter = null;
+        
+        // Remove from storage
+        setStorageItem(`${this.pageType}_activeLetterFilter`, null);
+        
+        // Update the toggle button indicator
+        this.updateToggleIndicator();
+    }
+    
+    /**
+     * Update letter counts with new data
+     * @param {Object} newCounts - New letter count data
+     */
+    updateCounts(newCounts) {
+        this.letterCounts = { ...newCounts };
+        this.updateLetterCountsDisplay();
+    }
+    
+    /**
+     * Update the toggle button visual indicator based on active filter
+     */
+    updateToggleIndicator() {
+        const toggleButton = document.querySelector('.toggle-alphabet-bar');
+        const hasActiveFilter = this.pageState.activeLetterFilter !== null;
+        
+        if (toggleButton) {
+            if (hasActiveFilter) {
+                toggleButton.classList.add('has-active-letter');
+            } else {
+                toggleButton.classList.remove('has-active-letter');
+            }
+        }
+    }
+    
+    /**
+     * Scroll the active letter into view if the alphabet bar is expanded
+     */
+    scrollActiveLetterIntoView() {
+        if (!this.pageState.activeLetterFilter) return;
+
+        
+        const alphabetBarContainer = document.querySelector('.alphabet-bar-container');
+        if (alphabetBarContainer) {
+            const activeLetterChip = document.querySelector(`.letter-chip.active`);
+            
+            if (activeLetterChip) {
+                // Use a small timeout to ensure the alphabet bar is fully expanded
+                setTimeout(() => {
+                    activeLetterChip.scrollIntoView({
+                        behavior: 'smooth',
+                        block: 'center',
+                        inline: 'center'
+                    });
+                }, 300);
+            }
+        }
+    }
+}

static/js/components/alphabet/index.js

@@ -0,0 +1,14 @@
+// Alphabet component index file
+import { AlphabetBar } from './AlphabetBar.js';
+
+// Export the class
+export { AlphabetBar };
+
+/**
+ * Factory function to create the appropriate alphabet bar
+ * @param {string} pageType - The type of page ('loras' or 'checkpoints')
+ * @returns {AlphabetBar} - The alphabet bar instance
+ */
+export function createAlphabetBar(pageType) {
+    return new AlphabetBar(pageType);
+}

static/js/components/checkpointModal/ModelMetadata.js

@@ -171,12 +171,13 @@ export function setupBaseModelEditing(filePath) {
             'Stable Diffusion 2.x': [BASE_MODELS.SD_2_0, BASE_MODELS.SD_2_1],
             'Stable Diffusion 3.x': [BASE_MODELS.SD_3, BASE_MODELS.SD_3_5, BASE_MODELS.SD_3_5_MEDIUM, BASE_MODELS.SD_3_5_LARGE, BASE_MODELS.SD_3_5_LARGE_TURBO],
             'SDXL': [BASE_MODELS.SDXL, BASE_MODELS.SDXL_LIGHTNING, BASE_MODELS.SDXL_HYPER],
-            'Video Models': [BASE_MODELS.SVD, BASE_MODELS.WAN_VIDEO, BASE_MODELS.HUNYUAN_VIDEO],
+            'Video Models': [BASE_MODELS.SVD, BASE_MODELS.LTXV, BASE_MODELS.WAN_VIDEO, BASE_MODELS.HUNYUAN_VIDEO],
             'Other Models': [
                 BASE_MODELS.FLUX_1_D, BASE_MODELS.FLUX_1_S, BASE_MODELS.AURAFLOW,
                 BASE_MODELS.PIXART_A, BASE_MODELS.PIXART_E, BASE_MODELS.HUNYUAN_1,
                 BASE_MODELS.LUMINA, BASE_MODELS.KOLORS, BASE_MODELS.NOOBAI,
-                BASE_MODELS.ILLUSTRIOUS, BASE_MODELS.PONY, BASE_MODELS.UNKNOWN
+                BASE_MODELS.ILLUSTRIOUS, BASE_MODELS.PONY, BASE_MODELS.HIDREAM,
+                BASE_MODELS.UNKNOWN
             ]
         };
         

static/js/components/checkpointModal/ShowcaseView.js

@@ -6,12 +6,40 @@ import { showToast, copyToClipboard } from '../../utils/uiHelpers.js';
 import { state } from '../../state/index.js';
 import { NSFW_LEVELS } from '../../utils/constants.js';
 
+/**
+ * Get the local URL for an example image if available
+ * @param {Object} img - Image object
+ * @param {number} index - Image index
+ * @param {string} modelHash - Model hash
+ * @returns {string|null} - Local URL or null if not available
+ */
+function getLocalExampleImageUrl(img, index, modelHash) {
+    if (!modelHash) return null;
+    
+    // Get remote extension
+    const remoteExt = (img.url || '').split('?')[0].split('.').pop().toLowerCase();
+    
+    // If it's a video (mp4), use that extension
+    if (remoteExt === 'mp4') {
+        return `/example_images_static/${modelHash}/image_${index + 1}.mp4`;
+    }
+    
+    // For images, check if optimization is enabled (defaults to true) 
+    const optimizeImages = state.settings.optimizeExampleImages !== false;
+    
+    // Use .webp for images if optimization enabled, otherwise use original extension
+    const extension = optimizeImages ? 'webp' : remoteExt;
+    
+    return `/example_images_static/${modelHash}/image_${index + 1}.${extension}`;
+}
+
 /**
  * Render showcase content
  * @param {Array} images - Array of images/videos to show
+ * @param {string} modelHash - Model hash for identifying local files
  * @returns {string} HTML content
  */
-export function renderShowcaseContent(images) {
+export function renderShowcaseContent(images, modelHash) {
     if (!images?.length) return '<div class="no-examples">No example images available</div>';
     
     // Filter images based on SFW setting
@@ -53,7 +81,11 @@ export function renderShowcaseContent(images) {
         <div class="carousel collapsed">
             ${hiddenNotification}
             <div class="carousel-container">
-                ${filteredImages.map(img => generateMediaWrapper(img)).join('')}
+                ${filteredImages.map((img, index) => {
+                    // Try to get local URL for the example image
+                    const localUrl = getLocalExampleImageUrl(img, index, modelHash);
+                    return generateMediaWrapper(img, localUrl);
+                }).join('')}
             </div>
         </div>
     `;
@@ -64,7 +96,7 @@ export function renderShowcaseContent(images) {
  * @param {Object} media - Media object with image or video data
  * @returns {string} HTML content
  */
-function generateMediaWrapper(media) {
+function generateMediaWrapper(media, localUrl = null) {
     // Calculate appropriate aspect ratio:
     // 1. Keep original aspect ratio
     // 2. Limit maximum height to 60% of viewport height
@@ -117,10 +149,10 @@ function generateMediaWrapper(media) {
     
     // Check if this is a video or image
     if (media.type === 'video') {
-        return generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel);
+        return generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl);
     }
     
-    return generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel);
+    return generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl);
 }
 
 /**
@@ -193,7 +225,7 @@ function generateMetadataPanel(hasParams, hasPrompts, prompt, negativePrompt, si
 /**
  * Generate video wrapper HTML
  */
-function generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel) {
+function generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl = null) {
     return `
         <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
             ${shouldBlur ? `
@@ -202,9 +234,11 @@ function generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metada
                 </button>
             ` : ''}
             <video controls autoplay muted loop crossorigin="anonymous" 
-                referrerpolicy="no-referrer" data-src="${media.url}"
+                referrerpolicy="no-referrer" 
+                data-local-src="${localUrl || ''}"
+                data-remote-src="${media.url}"
                 class="lazy ${shouldBlur ? 'blurred' : ''}">
-                <source data-src="${media.url}" type="video/mp4">
+                <source data-local-src="${localUrl || ''}" data-remote-src="${media.url}" type="video/mp4">
                 Your browser does not support video playback
             </video>
             ${shouldBlur ? `
@@ -223,7 +257,7 @@ function generateVideoWrapper(media, heightPercent, shouldBlur, nsfwText, metada
 /**
  * Generate image wrapper HTML
  */
-function generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel) {
+function generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl = null) {
     return `
         <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
             ${shouldBlur ? `
@@ -231,7 +265,8 @@ function generateImageWrapper(media, heightPercent, shouldBlur, nsfwText, metada
                     <i class="fas fa-eye"></i>
                 </button>
             ` : ''}
-            <img data-src="${media.url}" 
+            <img data-local-src="${localUrl || ''}" 
+                data-remote-src="${media.url}"
                 alt="Preview" 
                 crossorigin="anonymous" 
                 referrerpolicy="no-referrer"
@@ -287,8 +322,72 @@ 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');
-        if (!metadataPanel) return;
+        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', () => {
+            // Only hide panel when mouse leaves the wrapper and not over the metadata panel
+            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) => {
@@ -317,11 +416,61 @@ function initMetadataPanelHandlers(container) {
         
         // Prevent panel scroll from causing modal scroll
         metadataPanel.addEventListener('wheel', (e) => {
-            e.stopPropagation();
-        });
+            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 });
     });
 }
 
+/**
+ * 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
+ */
+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 blur toggle handlers
  */
@@ -382,15 +531,73 @@ function initLazyLoading(container) {
     const lazyElements = container.querySelectorAll('.lazy');
     
     const lazyLoad = (element) => {
+        const localSrc = element.dataset.localSrc;
+        const remoteSrc = element.dataset.remoteSrc;
+        
+        // Check if element is an image or video
         if (element.tagName.toLowerCase() === 'video') {
-            element.src = element.dataset.src;
-            element.querySelector('source').src = element.dataset.src;
-            element.load();
+            // Try local first, then remote
+            tryLocalOrFallbackToRemote(element, localSrc, remoteSrc);
         } else {
-            element.src = element.dataset.src;
+            // For images, we'll use an Image object to test if local file exists
+            tryLocalImageOrFallbackToRemote(element, localSrc, remoteSrc);
         }
+        
         element.classList.remove('lazy');
     };
+    
+    // Try to load local image first, fall back to remote if local fails
+    const tryLocalImageOrFallbackToRemote = (imgElement, localSrc, remoteSrc) => {
+        // Only try local if we have a local path
+        if (localSrc) {
+            const testImg = new Image();
+            testImg.onload = () => {
+                // Local image loaded successfully
+                imgElement.src = localSrc;
+            };
+            testImg.onerror = () => {
+                // Local image failed, use remote
+                imgElement.src = remoteSrc;
+            };
+            // Start loading test image
+            testImg.src = localSrc;
+        } else {
+            // No local path, use remote directly
+            imgElement.src = remoteSrc;
+        }
+    };
+    
+    // Try to load local video first, fall back to remote if local fails
+    const tryLocalOrFallbackToRemote = (videoElement, localSrc, remoteSrc) => {
+        // Only try local if we have a local path
+        if (localSrc) {
+            // Try to fetch local file headers to see if it exists
+            fetch(localSrc, { method: 'HEAD' })
+                .then(response => {
+                    if (response.ok) {
+                        // Local video exists, use it
+                        videoElement.src = localSrc;
+                        videoElement.querySelector('source').src = localSrc;
+                    } else {
+                        // Local video doesn't exist, use remote
+                        videoElement.src = remoteSrc;
+                        videoElement.querySelector('source').src = remoteSrc;
+                    }
+                    videoElement.load();
+                })
+                .catch(() => {
+                    // Error fetching, use remote
+                    videoElement.src = remoteSrc;
+                    videoElement.querySelector('source').src = remoteSrc;
+                    videoElement.load();
+                });
+        } else {
+            // No local path, use remote directly
+            videoElement.src = remoteSrc;
+            videoElement.querySelector('source').src = remoteSrc;
+            videoElement.load();
+        }
+    };
 
     const observer = new IntersectionObserver((entries) => {
         entries.forEach(entry => {
@@ -485,4 +692,4 @@ export function scrollToTop(button) {
             behavior: 'smooth'
         });
     }
-}
+}

static/js/components/checkpointModal/index.js

@@ -96,7 +96,7 @@ export function showCheckpointModal(checkpoint) {
                     
                     <div class="tab-content">
                         <div id="showcase-tab" class="tab-pane active">
-                            ${renderShowcaseContent(checkpoint.civitai?.images || [])}
+                            ${renderShowcaseContent(checkpoint.civitai?.images || [], checkpoint.sha256)}
                         </div>
                         
                         <div id="description-tab" class="tab-pane">

static/js/components/controls/LorasControls.js

@@ -2,6 +2,7 @@
 import { PageControls } from './PageControls.js';
 import { loadMoreLoras, fetchCivitai, resetAndReload, refreshLoras } from '../../api/loraApi.js';
 import { getSessionItem, removeSessionItem } from '../../utils/storageHelpers.js';
+import { createAlphabetBar } from '../alphabet/index.js';
 
 /**
  * LorasControls class - Extends PageControls for LoRA-specific functionality
@@ -16,6 +17,9 @@ export class LorasControls extends PageControls {
         
         // Check for custom filters (e.g., from recipe navigation)
         this.checkCustomFilters();
+        
+        // Initialize alphabet bar component
+        this.initAlphabetBar();
     }
     
     /**
@@ -142,4 +146,15 @@ export class LorasControls extends PageControls {
     _truncateText(text, maxLength) {
         return text.length > maxLength ? text.substring(0, maxLength - 3) + '...' : text;
     }
+    
+    /**
+     * Initialize the alphabet bar component
+     */
+    initAlphabetBar() {
+        // Create the alphabet bar component
+        this.alphabetBar = createAlphabetBar('loras');
+        
+        // Expose the alphabet bar to the global scope for debugging
+        window.alphabetBar = this.alphabetBar;
+    }
 }

static/js/components/loraModal/ModelMetadata.js

@@ -173,12 +173,13 @@ export function setupBaseModelEditing(filePath) {
             'Stable Diffusion 2.x': [BASE_MODELS.SD_2_0, BASE_MODELS.SD_2_1],
             'Stable Diffusion 3.x': [BASE_MODELS.SD_3, BASE_MODELS.SD_3_5, BASE_MODELS.SD_3_5_MEDIUM, BASE_MODELS.SD_3_5_LARGE, BASE_MODELS.SD_3_5_LARGE_TURBO],
             'SDXL': [BASE_MODELS.SDXL, BASE_MODELS.SDXL_LIGHTNING, BASE_MODELS.SDXL_HYPER],
-            'Video Models': [BASE_MODELS.SVD, BASE_MODELS.WAN_VIDEO, BASE_MODELS.HUNYUAN_VIDEO],
+            'Video Models': [BASE_MODELS.SVD, BASE_MODELS.LTXV, BASE_MODELS.WAN_VIDEO, BASE_MODELS.HUNYUAN_VIDEO],
             'Other Models': [
                 BASE_MODELS.FLUX_1_D, BASE_MODELS.FLUX_1_S, BASE_MODELS.AURAFLOW,
                 BASE_MODELS.PIXART_A, BASE_MODELS.PIXART_E, BASE_MODELS.HUNYUAN_1,
                 BASE_MODELS.LUMINA, BASE_MODELS.KOLORS, BASE_MODELS.NOOBAI,
-                BASE_MODELS.ILLUSTRIOUS, BASE_MODELS.PONY, BASE_MODELS.UNKNOWN
+                BASE_MODELS.ILLUSTRIOUS, BASE_MODELS.PONY, BASE_MODELS.HIDREAM,
+                BASE_MODELS.UNKNOWN
             ]
         };
         

static/js/components/loraModal/ShowcaseView.js

@@ -6,12 +6,40 @@ import { showToast, copyToClipboard } from '../../utils/uiHelpers.js';
 import { state } from '../../state/index.js';
 import { NSFW_LEVELS } from '../../utils/constants.js';
 
+/**
+ * Get the local URL for an example image if available
+ * @param {Object} img - Image object
+ * @param {number} index - Image index
+ * @param {string} modelHash - Model hash
+ * @returns {string|null} - Local URL or null if not available
+ */
+function getLocalExampleImageUrl(img, index, modelHash) {
+    if (!modelHash) return null;
+    
+    // Get remote extension
+    const remoteExt = (img.url || '').split('?')[0].split('.').pop().toLowerCase();
+    
+    // If it's a video (mp4), use that extension
+    if (remoteExt === 'mp4') {
+        return `/example_images_static/${modelHash}/image_${index + 1}.mp4`;
+    }
+    
+    // For images, check if optimization is enabled (defaults to true) 
+    const optimizeImages = state.settings.optimizeExampleImages !== false;
+    
+    // Use .webp for images if optimization enabled, otherwise use original extension
+    const extension = optimizeImages ? 'webp' : remoteExt;
+    
+    return `/example_images_static/${modelHash}/image_${index + 1}.${extension}`;
+}
+
 /**
  * 渲染展示内容
  * @param {Array} images - 要展示的图片/视频数组
+ * @param {string} modelHash - Model hash for identifying local files
  * @returns {string} HTML内容
  */
-export function renderShowcaseContent(images) {
+export function renderShowcaseContent(images, modelHash) {
     if (!images?.length) return '<div class="no-examples">No example images available</div>';
     
     // Filter images based on SFW setting
@@ -53,7 +81,15 @@ export function renderShowcaseContent(images) {
         <div class="carousel collapsed">
             ${hiddenNotification}
             <div class="carousel-container">
-                ${filteredImages.map(img => {
+                ${filteredImages.map((img, index) => {
+                    // Try to get local URL for the example image
+                    const localUrl = getLocalExampleImageUrl(img, index, modelHash);
+                    
+                    // Create data attributes for both remote and local URLs
+                    const remoteUrl = img.url;
+                    const dataRemoteSrc = remoteUrl;
+                    const dataLocalSrc = localUrl;
+                    
                     // 计算适当的展示高度：
                     // 1. 保持原始宽高比
                     // 2. 限制最大高度为视窗高度的60%
@@ -111,9 +147,9 @@ export function renderShowcaseContent(images) {
                         `;
                         
                         if (img.type === 'video') {
-                            return generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel);
+                            return generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, dataLocalSrc, dataRemoteSrc);
                         }
-                        return generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel);
+                        return generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, dataLocalSrc, dataRemoteSrc);
                     }
                     
                     // Create a data attribute with the prompt for copying instead of trying to handle it in the onclick
@@ -174,9 +210,9 @@ export function renderShowcaseContent(images) {
                     `;
                     
                     if (img.type === 'video') {
-                        return generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel);
+                        return generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, dataLocalSrc, dataRemoteSrc);
                     }
-                    return generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel);
+                    return generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, dataLocalSrc, dataRemoteSrc);
                 }).join('')}
             </div>
         </div>
@@ -186,7 +222,7 @@ export function renderShowcaseContent(images) {
 /**
  * 生成视频包装HTML
  */
-function generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel) {
+function generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl) {
     return `
         <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
             ${shouldBlur ? `
@@ -195,9 +231,11 @@ function generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadata
                 </button>
             ` : ''}
             <video controls autoplay muted loop crossorigin="anonymous" 
-                referrerpolicy="no-referrer" data-src="${img.url}"
+                referrerpolicy="no-referrer" 
+                data-local-src="${localUrl || ''}"
+                data-remote-src="${remoteUrl}"
                 class="lazy ${shouldBlur ? 'blurred' : ''}">
-                <source data-src="${img.url}" type="video/mp4">
+                <source data-local-src="${localUrl || ''}" data-remote-src="${remoteUrl}" type="video/mp4">
                 Your browser does not support video playback
             </video>
             ${shouldBlur ? `
@@ -216,7 +254,7 @@ function generateVideoWrapper(img, heightPercent, shouldBlur, nsfwText, metadata
 /**
  * 生成图片包装HTML
  */
-function generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel) {
+function generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadataPanel, localUrl, remoteUrl) {
     return `
         <div class="media-wrapper ${shouldBlur ? 'nsfw-media-wrapper' : ''}" style="padding-bottom: ${heightPercent}%">
             ${shouldBlur ? `
@@ -224,7 +262,8 @@ function generateImageWrapper(img, heightPercent, shouldBlur, nsfwText, metadata
                     <i class="fas fa-eye"></i>
                 </button>
             ` : ''}
-            <img data-src="${img.url}" 
+            <img data-local-src="${localUrl || ''}" 
+                data-remote-src="${remoteUrl}"
                 alt="Preview" 
                 crossorigin="anonymous" 
                 referrerpolicy="no-referrer"
@@ -290,9 +329,72 @@ function initMetadataPanelHandlers(container) {
     const mediaWrappers = container.querySelectorAll('.media-wrapper');
     
     mediaWrappers.forEach(wrapper => {
-        // Get the metadata panel
+        // Get the metadata panel and media element (img or video)
         const metadataPanel = wrapper.querySelector('.image-metadata-panel');
-        if (!metadataPanel) return;
+        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
+            if (isOverMedia || isOverMetadataPanel) {
+                metadataPanel.classList.add('visible');
+            } else {
+                metadataPanel.classList.remove('visible');
+            }
+        });
+        
+        wrapper.addEventListener('mouseleave', () => {
+            // Only hide panel when mouse leaves the wrapper and not over the metadata panel
+            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 the metadata panel from bubbling
         metadataPanel.addEventListener('click', (e) => {
@@ -332,6 +434,50 @@ function initMetadataPanelHandlers(container) {
     });
 }
 
+/**
+ * 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
+ */
+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
+    };
+}
+
 /**
  * 初始化模糊切换处理
  */
@@ -392,15 +538,73 @@ function initLazyLoading(container) {
     const lazyElements = container.querySelectorAll('.lazy');
     
     const lazyLoad = (element) => {
+        const localSrc = element.dataset.localSrc;
+        const remoteSrc = element.dataset.remoteSrc;
+        
+        // Check if element is an image or video
         if (element.tagName.toLowerCase() === 'video') {
-            element.src = element.dataset.src;
-            element.querySelector('source').src = element.dataset.src;
-            element.load();
+            // Try local first, then remote
+            tryLocalOrFallbackToRemote(element, localSrc, remoteSrc);
         } else {
-            element.src = element.dataset.src;
+            // For images, we'll use an Image object to test if local file exists
+            tryLocalImageOrFallbackToRemote(element, localSrc, remoteSrc);
         }
+        
         element.classList.remove('lazy');
     };
+    
+    // Try to load local image first, fall back to remote if local fails
+    const tryLocalImageOrFallbackToRemote = (imgElement, localSrc, remoteSrc) => {
+        // Only try local if we have a local path
+        if (localSrc) {
+            const testImg = new Image();
+            testImg.onload = () => {
+                // Local image loaded successfully
+                imgElement.src = localSrc;
+            };
+            testImg.onerror = () => {
+                // Local image failed, use remote
+                imgElement.src = remoteSrc;
+            };
+            // Start loading test image
+            testImg.src = localSrc;
+        } else {
+            // No local path, use remote directly
+            imgElement.src = remoteSrc;
+        }
+    };
+    
+    // Try to load local video first, fall back to remote if local fails
+    const tryLocalOrFallbackToRemote = (videoElement, localSrc, remoteSrc) => {
+        // Only try local if we have a local path
+        if (localSrc) {
+            // Try to fetch local file headers to see if it exists
+            fetch(localSrc, { method: 'HEAD' })
+                .then(response => {
+                    if (response.ok) {
+                        // Local video exists, use it
+                        videoElement.src = localSrc;
+                        videoElement.querySelector('source').src = localSrc;
+                    } else {
+                        // Local video doesn't exist, use remote
+                        videoElement.src = remoteSrc;
+                        videoElement.querySelector('source').src = remoteSrc;
+                    }
+                    videoElement.load();
+                })
+                .catch(() => {
+                    // Error fetching, use remote
+                    videoElement.src = remoteSrc;
+                    videoElement.querySelector('source').src = remoteSrc;
+                    videoElement.load();
+                });
+        } else {
+            // No local path, use remote directly
+            videoElement.src = remoteSrc;
+            videoElement.querySelector('source').src = remoteSrc;
+            videoElement.load();
+        }
+    };
 
     const observer = new IntersectionObserver((entries) => {
         entries.forEach(entry => {
@@ -497,4 +701,4 @@ export function scrollToTop(button) {
             behavior: 'smooth'
         });
     }
-}
+}

static/js/components/loraModal/index.js

@@ -122,7 +122,7 @@ export function showLoraModal(lora) {
                     
                     <div class="tab-content">
                         <div id="showcase-tab" class="tab-pane active">
-                            ${renderShowcaseContent(lora.civitai?.images)}
+                            ${renderShowcaseContent(lora.civitai?.images, lora.sha256)}
                         </div>
                         
                         <div id="description-tab" class="tab-pane">

static/js/core.js

@@ -5,6 +5,7 @@ import { modalManager } from './managers/ModalManager.js';
 import { updateService } from './managers/UpdateService.js';
 import { HeaderManager } from './components/Header.js';
 import { settingsManager } from './managers/SettingsManager.js';
+import { exampleImagesManager } from './managers/ExampleImagesManager.js';
 import { showToast, initTheme, initBackToTop, lazyLoadImages } from './utils/uiHelpers.js';
 import { initializeInfiniteScroll } from './utils/infiniteScroll.js';
 import { migrateStorageItems } from './utils/storageHelpers.js';
@@ -27,12 +28,16 @@ export class AppCore {
         updateService.initialize();
         window.modalManager = modalManager;
         window.settingsManager = settingsManager;
+        window.exampleImagesManager = exampleImagesManager;
         
         // Initialize UI components
         window.headerManager = new HeaderManager();
         initTheme();
         initBackToTop();
         
+        // Initialize the example images manager
+        exampleImagesManager.initialize();
+        
         // Mark as initialized
         this.initialized = true;
         

static/js/loras.js

@@ -8,7 +8,7 @@ import { DownloadManager } from './managers/DownloadManager.js';
 import { moveManager } from './managers/MoveManager.js';
 import { LoraContextMenu } from './components/ContextMenu/index.js';
 import { createPageControls } from './components/controls/index.js';
-import { confirmDelete, closeDeleteModal } from './utils/modalUtils.js';
+import { confirmDelete, closeDeleteModal, confirmExclude, closeExcludeModal } from './utils/modalUtils.js';
 
 // Initialize the LoRA page
 class LoraPageManager {
@@ -35,6 +35,8 @@ class LoraPageManager {
         window.showLoraModal = showLoraModal;
         window.confirmDelete = confirmDelete;
         window.closeDeleteModal = closeDeleteModal;
+        window.confirmExclude = confirmExclude;
+        window.closeExcludeModal = closeExcludeModal;
         window.downloadManager = this.downloadManager;
         window.moveManager = moveManager;
         window.toggleShowcase = toggleShowcase;

static/js/managers/ExampleImagesManager.js

@@ -0,0 +1,602 @@
+import { showToast } from '../utils/uiHelpers.js';
+import { getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
+
+// ExampleImagesManager.js
+class ExampleImagesManager {
+    constructor() {
+        this.isDownloading = false;
+        this.isPaused = false;
+        this.progressUpdateInterval = null;
+        this.startTime = null;
+        this.progressPanel = null;
+        this.isProgressPanelCollapsed = false;
+        this.pauseButton = null; // Store reference to the pause button
+        
+        // Initialize download path field and check download status
+        this.initializePathOptions();
+        this.checkDownloadStatus();
+    }
+    
+    // Initialize the manager
+    initialize() {
+        // Initialize event listeners
+        this.initEventListeners();
+        
+        // Initialize progress panel reference
+        this.progressPanel = document.getElementById('exampleImagesProgress');
+        
+        // Load collapse state from storage
+        this.isProgressPanelCollapsed = getStorageItem('progress_panel_collapsed', false);
+        if (this.progressPanel && this.isProgressPanelCollapsed) {
+            this.progressPanel.classList.add('collapsed');
+            const icon = document.querySelector('#collapseProgressBtn i');
+            if (icon) {
+                icon.className = 'fas fa-chevron-up';
+            }
+        }
+        
+        // Initialize progress panel button handlers
+        this.pauseButton = document.getElementById('pauseExampleDownloadBtn');
+        const collapseBtn = document.getElementById('collapseProgressBtn');
+        
+        if (this.pauseButton) {
+            this.pauseButton.onclick = () => this.pauseDownload();
+        }
+        
+        if (collapseBtn) {
+            collapseBtn.onclick = () => this.toggleProgressPanel();
+        }
+    }
+    
+    // Initialize event listeners for buttons
+    initEventListeners() {
+        const downloadBtn = document.getElementById('exampleImagesDownloadBtn');
+        if (downloadBtn) {
+            downloadBtn.onclick = () => this.handleDownloadButton();
+        }
+    }
+    
+    async initializePathOptions() {
+        try {
+            // Get custom path input element
+            const pathInput = document.getElementById('exampleImagesPath');
+
+            // Set path from storage if available
+            const savedPath = getStorageItem('example_images_path', '');
+            if (savedPath) {
+                pathInput.value = savedPath;
+                // Enable download button if path is set
+                this.updateDownloadButtonState(true);
+            } else {
+                // Disable download button if no path is set
+                this.updateDownloadButtonState(false);
+            }
+            
+            // Add event listener to validate path input
+            pathInput.addEventListener('input', async () => {
+                const hasPath = pathInput.value.trim() !== '';
+                this.updateDownloadButtonState(hasPath);
+                
+                // Save path to storage when changed
+                if (hasPath) {
+                    setStorageItem('example_images_path', pathInput.value);
+                    
+                    // Update path in backend settings
+                    try {
+                        const response = await fetch('/api/settings', {
+                            method: 'POST',
+                            headers: {
+                                'Content-Type': 'application/json'
+                            },
+                            body: JSON.stringify({
+                                example_images_path: pathInput.value
+                            })
+                        });
+                        
+                        if (!response.ok) {
+                            throw new Error(`HTTP error! Status: ${response.status}`);
+                        }
+                        
+                        const data = await response.json();
+                        if (!data.success) {
+                            console.error('Failed to update example images path in backend:', data.error);
+                        } else {
+                            showToast('Example images path updated successfully', 'success');
+                        }
+                    } catch (error) {
+                        console.error('Failed to update example images path:', error);
+                    }
+                }
+            });
+        } catch (error) {
+            console.error('Failed to initialize path options:', error);
+        }
+    }
+    
+    // Method to update download button state
+    updateDownloadButtonState(enabled) {
+        const downloadBtn = document.getElementById('exampleImagesDownloadBtn');
+        if (downloadBtn) {
+            if (enabled) {
+                downloadBtn.classList.remove('disabled');
+                downloadBtn.disabled = false;
+            } else {
+                downloadBtn.classList.add('disabled');
+                downloadBtn.disabled = true;
+            }
+        }
+    }
+    
+    // Method to handle download button click based on current state
+    async handleDownloadButton() {
+        if (this.isDownloading && this.isPaused) {
+            // If download is paused, resume it
+            this.resumeDownload();
+        } else if (!this.isDownloading) {
+            // If no download in progress, start a new one
+            this.startDownload();
+        } else {
+            // If download is in progress, show info toast
+            showToast('Download already in progress', 'info');
+        }
+    }
+    
+    async checkDownloadStatus() {
+        try {
+            const response = await fetch('/api/example-images-status');
+            const data = await response.json();
+            
+            if (data.success) {
+                this.isDownloading = data.is_downloading;
+                this.isPaused = data.status.status === 'paused';
+                
+                // Update download button text based on status
+                this.updateDownloadButtonText();
+                
+                if (this.isDownloading) {
+                    // Ensure progress panel exists before updating UI
+                    if (!this.progressPanel) {
+                        this.progressPanel = document.getElementById('exampleImagesProgress');
+                    }
+                    
+                    if (this.progressPanel) {
+                        this.updateUI(data.status);
+                        this.showProgressPanel();
+                        
+                        // Start the progress update interval if downloading
+                        if (!this.progressUpdateInterval) {
+                            this.startProgressUpdates();
+                        }
+                    } else {
+                        console.warn('Progress panel not found, will retry on next update');
+                        // Set a shorter timeout to try again
+                        setTimeout(() => this.checkDownloadStatus(), 500);
+                    }
+                }
+            }
+        } catch (error) {
+            console.error('Failed to check download status:', error);
+        }
+    }
+    
+    // Update download button text based on current state
+    updateDownloadButtonText() {
+        const btnTextElement = document.getElementById('exampleDownloadBtnText');
+        if (btnTextElement) {
+            if (this.isDownloading && this.isPaused) {
+                btnTextElement.textContent = "Resume";
+            } else if (!this.isDownloading) {
+                btnTextElement.textContent = "Download";
+            }
+        }
+    }
+    
+    async startDownload() {
+        if (this.isDownloading) {
+            showToast('Download already in progress', 'warning');
+            return;
+        }
+        
+        try {
+            const outputDir = document.getElementById('exampleImagesPath').value || '';
+            
+            if (!outputDir) {
+                showToast('Please enter a download location first', 'warning');
+                return;
+            }
+            
+            const optimize = document.getElementById('optimizeExampleImages').checked;
+            
+            const response = await fetch('/api/download-example-images', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json'
+                },
+                body: JSON.stringify({
+                    output_dir: outputDir,
+                    optimize: optimize,
+                    model_types: ['lora', 'checkpoint']
+                })
+            });
+            
+            const data = await response.json();
+            
+            if (data.success) {
+                this.isDownloading = true;
+                this.isPaused = false;
+                this.startTime = new Date();
+                this.updateUI(data.status);
+                this.showProgressPanel();
+                this.startProgressUpdates();
+                this.updateDownloadButtonText();
+                showToast('Example images download started', 'success');
+                
+                // Close settings modal
+                modalManager.closeModal('settingsModal');
+            } else {
+                showToast(data.error || 'Failed to start download', 'error');
+            }
+        } catch (error) {
+            console.error('Failed to start download:', error);
+            showToast('Failed to start download', 'error');
+        }
+    }
+    
+    async pauseDownload() {
+        if (!this.isDownloading || this.isPaused) {
+            return;
+        }
+        
+        try {
+            const response = await fetch('/api/pause-example-images', {
+                method: 'POST'
+            });
+            
+            const data = await response.json();
+            
+            if (data.success) {
+                this.isPaused = true;
+                document.getElementById('downloadStatusText').textContent = 'Paused';
+                
+                // Only update the icon element, not the entire innerHTML
+                if (this.pauseButton) {
+                    const iconElement = this.pauseButton.querySelector('i');
+                    if (iconElement) {
+                        iconElement.className = 'fas fa-play';
+                    }
+                    this.pauseButton.onclick = () => this.resumeDownload();
+                }
+                
+                this.updateDownloadButtonText();
+                showToast('Download paused', 'info');
+            } else {
+                showToast(data.error || 'Failed to pause download', 'error');
+            }
+        } catch (error) {
+            console.error('Failed to pause download:', error);
+            showToast('Failed to pause download', 'error');
+        }
+    }
+    
+    async resumeDownload() {
+        if (!this.isDownloading || !this.isPaused) {
+            return;
+        }
+        
+        try {
+            const response = await fetch('/api/resume-example-images', {
+                method: 'POST'
+            });
+            
+            const data = await response.json();
+            
+            if (data.success) {
+                this.isPaused = false;
+                document.getElementById('downloadStatusText').textContent = 'Downloading';
+                
+                // Only update the icon element, not the entire innerHTML
+                if (this.pauseButton) {
+                    const iconElement = this.pauseButton.querySelector('i');
+                    if (iconElement) {
+                        iconElement.className = 'fas fa-pause';
+                    }
+                    this.pauseButton.onclick = () => this.pauseDownload();
+                }
+                
+                this.updateDownloadButtonText();
+                showToast('Download resumed', 'success');
+            } else {
+                showToast(data.error || 'Failed to resume download', 'error');
+            }
+        } catch (error) {
+            console.error('Failed to resume download:', error);
+            showToast('Failed to resume download', 'error');
+        }
+    }
+    
+    startProgressUpdates() {
+        // Clear any existing interval
+        if (this.progressUpdateInterval) {
+            clearInterval(this.progressUpdateInterval);
+        }
+        
+        // Set new interval to update progress every 2 seconds
+        this.progressUpdateInterval = setInterval(async () => {
+            await this.updateProgress();
+        }, 2000);
+    }
+    
+    async updateProgress() {
+        try {
+            const response = await fetch('/api/example-images-status');
+            const data = await response.json();
+            
+            if (data.success) {
+                this.isDownloading = data.is_downloading;
+                this.isPaused = data.status.status === 'paused';
+                
+                // Update download button text
+                this.updateDownloadButtonText();
+                
+                if (this.isDownloading) {
+                    this.updateUI(data.status);
+                } else {
+                    // Download completed or failed
+                    clearInterval(this.progressUpdateInterval);
+                    this.progressUpdateInterval = null;
+                    
+                    if (data.status.status === 'completed') {
+                        showToast('Example images download completed', 'success');
+                        // Hide the panel after a delay
+                        setTimeout(() => this.hideProgressPanel(), 5000);
+                    } else if (data.status.status === 'error') {
+                        showToast('Example images download failed', 'error');
+                    }
+                }
+            }
+        } catch (error) {
+            console.error('Failed to update progress:', error);
+        }
+    }
+    
+    updateUI(status) {
+        // Ensure progress panel exists
+        if (!this.progressPanel) {
+            this.progressPanel = document.getElementById('exampleImagesProgress');
+            if (!this.progressPanel) {
+                console.error('Progress panel element not found in DOM');
+                return;
+            }
+        }
+        
+        // Update status text
+        const statusText = document.getElementById('downloadStatusText');
+        if (statusText) {
+            statusText.textContent = this.getStatusText(status.status);
+        }
+        
+        // Update progress counts and bar
+        const progressCounts = document.getElementById('downloadProgressCounts');
+        if (progressCounts) {
+            progressCounts.textContent = `${status.completed}/${status.total}`;
+        }
+        
+        const progressBar = document.getElementById('downloadProgressBar');
+        if (progressBar) {
+            const progressPercent = status.total > 0 ? (status.completed / status.total) * 100 : 0;
+            progressBar.style.width = `${progressPercent}%`;
+            
+            // Update mini progress circle
+            this.updateMiniProgress(progressPercent);
+        }
+        
+        // Update current model
+        const currentModel = document.getElementById('currentModelName');
+        if (currentModel) {
+            currentModel.textContent = status.current_model || '-';
+        }
+        
+        // Update time stats
+        this.updateTimeStats(status);
+        
+        // Update errors
+        this.updateErrors(status);
+        
+        // Update pause/resume button
+        if (!this.pauseButton) {
+            this.pauseButton = document.getElementById('pauseExampleDownloadBtn');
+        }
+        
+        if (this.pauseButton) {
+            // Check if the button already has the SVG elements
+            let hasProgressElements = !!this.pauseButton.querySelector('.mini-progress-circle');
+            
+            if (!hasProgressElements) {
+                // If elements don't exist, add them
+                this.pauseButton.innerHTML = `
+                    <i class="${status.status === 'paused' ? 'fas fa-play' : 'fas fa-pause'}"></i>
+                    <svg class="mini-progress-container" width="24" height="24" viewBox="0 0 24 24">
+                        <circle class="mini-progress-background" cx="12" cy="12" r="10"></circle>
+                        <circle class="mini-progress-circle" cx="12" cy="12" r="10" stroke-dasharray="62.8" stroke-dashoffset="62.8"></circle>
+                    </svg>
+                    <span class="progress-percent"></span>
+                `;
+            } else {
+                // If elements exist, just update the icon
+                const iconElement = this.pauseButton.querySelector('i');
+                if (iconElement) {
+                    iconElement.className = status.status === 'paused' ? 'fas fa-play' : 'fas fa-pause';
+                }
+            }
+            
+            // Update click handler
+            this.pauseButton.onclick = status.status === 'paused' 
+                ? () => this.resumeDownload() 
+                : () => this.pauseDownload();
+            
+            // Update progress immediately
+            const progressBar = document.getElementById('downloadProgressBar');
+            if (progressBar) {
+                const progressPercent = status.total > 0 ? (status.completed / status.total) * 100 : 0;
+                this.updateMiniProgress(progressPercent);
+            }
+        }
+    }
+    
+    // Update the mini progress circle in the pause button
+    updateMiniProgress(percent) {
+        // Ensure we have the pause button reference
+        if (!this.pauseButton) {
+            this.pauseButton = document.getElementById('pauseExampleDownloadBtn');
+            if (!this.pauseButton) {
+                console.error('Pause button not found');
+                return;
+            }
+        }
+        
+        // Query elements within the context of the pause button
+        const miniProgressCircle = this.pauseButton.querySelector('.mini-progress-circle');
+        const percentText = this.pauseButton.querySelector('.progress-percent');
+        
+        if (miniProgressCircle && percentText) {
+            // Circle circumference = 2πr = 2 * π * 10 = 62.8
+            const circumference = 62.8;
+            const offset = circumference - (percent / 100) * circumference;
+            
+            miniProgressCircle.style.strokeDashoffset = offset;
+            percentText.textContent = `${Math.round(percent)}%`;
+            
+            // Only show percent text when panel is collapsed
+            percentText.style.display = this.isProgressPanelCollapsed ? 'block' : 'none';
+        } else {
+            console.warn('Mini progress elements not found within pause button', 
+                         this.pauseButton,
+                         'mini-progress-circle:', !!miniProgressCircle, 
+                         'progress-percent:', !!percentText);
+        }
+    }
+    
+    updateTimeStats(status) {
+        const elapsedTime = document.getElementById('elapsedTime');
+        const remainingTime = document.getElementById('remainingTime');
+        
+        if (!elapsedTime || !remainingTime) return;
+        
+        // Calculate elapsed time
+        let elapsed;
+        if (status.start_time) {
+            const now = new Date();
+            const startTime = new Date(status.start_time * 1000);
+            elapsed = Math.floor((now - startTime) / 1000);
+        } else {
+            elapsed = 0;
+        }
+        
+        elapsedTime.textContent = this.formatTime(elapsed);
+        
+        // Calculate remaining time
+        if (status.total > 0 && status.completed > 0 && status.status === 'running') {
+            const rate = status.completed / elapsed; // models per second
+            const remaining = Math.floor((status.total - status.completed) / rate);
+            remainingTime.textContent = this.formatTime(remaining);
+        } else {
+            remainingTime.textContent = '--:--:--';
+        }
+    }
+    
+    updateErrors(status) {
+        const errorContainer = document.getElementById('downloadErrorContainer');
+        const errorList = document.getElementById('downloadErrors');
+        
+        if (!errorContainer || !errorList) return;
+        
+        if (status.errors && status.errors.length > 0) {
+            // Show only the last 3 errors
+            const recentErrors = status.errors.slice(-3);
+            errorList.innerHTML = recentErrors.map(error => 
+                `<div class="error-item">${error}</div>`
+            ).join('');
+            
+            errorContainer.classList.remove('hidden');
+        } else {
+            errorContainer.classList.add('hidden');
+        }
+    }
+    
+    formatTime(seconds) {
+        const hours = Math.floor(seconds / 3600);
+        const minutes = Math.floor((seconds % 3600) / 60);
+        const secs = seconds % 60;
+        
+        return [
+            hours.toString().padStart(2, '0'),
+            minutes.toString().padStart(2, '0'),
+            secs.toString().padStart(2, '0')
+        ].join(':');
+    }
+    
+    getStatusText(status) {
+        switch (status) {
+            case 'running': return 'Downloading';
+            case 'paused': return 'Paused';
+            case 'completed': return 'Completed';
+            case 'error': return 'Error';
+            default: return 'Initializing';
+        }
+    }
+    
+    showProgressPanel() {
+        // Ensure progress panel exists
+        if (!this.progressPanel) {
+            this.progressPanel = document.getElementById('exampleImagesProgress');
+            if (!this.progressPanel) {
+                console.error('Progress panel element not found in DOM');
+                return;
+            }
+        }
+        this.progressPanel.classList.add('visible');
+    }
+    
+    hideProgressPanel() {
+        if (!this.progressPanel) {
+            this.progressPanel = document.getElementById('exampleImagesProgress');
+            if (!this.progressPanel) return;
+        }
+        this.progressPanel.classList.remove('visible');
+    }
+    
+    toggleProgressPanel() {
+        if (!this.progressPanel) {
+            this.progressPanel = document.getElementById('exampleImagesProgress');
+            if (!this.progressPanel) return;
+        }
+        
+        this.isProgressPanelCollapsed = !this.isProgressPanelCollapsed;
+        this.progressPanel.classList.toggle('collapsed');
+        
+        // Save collapsed state to storage
+        setStorageItem('progress_panel_collapsed', this.isProgressPanelCollapsed);
+        
+        // Update icon
+        const icon = document.querySelector('#collapseProgressBtn i');
+        if (icon) {
+            if (this.isProgressPanelCollapsed) {
+                icon.className = 'fas fa-chevron-up';
+            } else {
+                icon.className = 'fas fa-chevron-down';
+            }
+        }
+        
+        // Force update mini progress if panel is collapsed
+        if (this.isProgressPanelCollapsed) {
+            const progressBar = document.getElementById('downloadProgressBar');
+            if (progressBar) {
+                const progressPercent = parseFloat(progressBar.style.width) || 0;
+                this.updateMiniProgress(progressPercent);
+            }
+        }
+    }
+}
+
+// Create singleton instance
+export const exampleImagesManager = new ExampleImagesManager();

static/js/managers/ImportManager.js

@@ -146,6 +146,18 @@ export class ImportManager {
         if (totalSizeDisplay) {
             totalSizeDisplay.textContent = 'Calculating...';
         }
+        
+        // Remove any existing deleted LoRAs warning
+        const deletedLorasWarning = document.getElementById('deletedLorasWarning');
+        if (deletedLorasWarning) {
+            deletedLorasWarning.remove();
+        }
+        
+        // Remove any existing early access warning
+        const earlyAccessWarning = document.getElementById('earlyAccessWarning');
+        if (earlyAccessWarning) {
+            earlyAccessWarning.remove();
+        }
     }
 
     toggleImportMode(mode) {
@@ -532,17 +544,17 @@ export class ImportManager {
         const nextButton = document.querySelector('#detailsStep .primary-btn');
         if (!nextButton) return;
         
+        // Always clean up previous warnings first
+        const existingWarning = document.getElementById('deletedLorasWarning');
+        if (existingWarning) {
+            existingWarning.remove();
+        }
+        
         // Count deleted LoRAs
         const deletedLoras = this.recipeData.loras.filter(lora => lora.isDeleted).length;
         
         // If we have deleted LoRAs, show a warning and update button text
         if (deletedLoras > 0) {
-            // Remove any existing warning
-            const existingWarning = document.getElementById('deletedLorasWarning');
-            if (existingWarning) {
-                existingWarning.remove();
-            }
-            
             // Create a new warning container above the buttons
             const buttonsContainer = document.querySelector('#detailsStep .modal-actions') || nextButton.parentNode;
             const warningContainer = document.createElement('div');

static/js/managers/ModalManager.js

@@ -59,6 +59,19 @@ export class ModalManager {
                 }
             });
         }
+        
+        // Add excludeModal registration
+        const excludeModal = document.getElementById('excludeModal');
+        if (excludeModal) {
+            this.registerModal('excludeModal', {
+                element: excludeModal,
+                onClose: () => {
+                    this.getModal('excludeModal').element.classList.remove('show');
+                    document.body.classList.remove('modal-open');
+                },
+                closeOnOutsideClick: true
+            });
+        }
 
         // Add downloadModal registration
         const downloadModal = document.getElementById('downloadModal');
@@ -208,7 +221,7 @@ export class ModalManager {
         // Store current scroll position before showing modal
         this.scrollPosition = window.scrollY;
 
-        if (id === 'deleteModal') {
+        if (id === 'deleteModal' || id === 'excludeModal') {
             modal.element.classList.add('show');
         } else {
             modal.element.style.display = 'block';

static/js/managers/SettingsManager.js

@@ -147,6 +147,8 @@ export class SettingsManager {
             state.global.settings.show_only_sfw = value;
         } else if (settingKey === 'autoplay_on_hover') {
             state.global.settings.autoplayOnHover = value;
+        } else if (settingKey === 'optimize_example_images') {
+            state.global.settings.optimizeExampleImages = value;
         } else {
             // For any other settings that might be added in the future
             state.global.settings[settingKey] = value;

static/js/state/index.js

@@ -27,6 +27,7 @@ export const state = {
             hasMore: true,
             sortBy: 'name',
             activeFolder: null,
+            activeLetterFilter: null, // New property for letter filtering
             previewVersions: loraPreviewVersions,
             searchManager: null,
             searchOptions: {

static/js/utils/constants.js

@@ -33,9 +33,11 @@ export const BASE_MODELS = {
     NOOBAI: "NoobAI",
     ILLUSTRIOUS: "Illustrious",
     PONY: "Pony",
+    HIDREAM: "HiDream",
     
     // Video models
     SVD: "SVD",
+    LTXV: "LTXV",
     WAN_VIDEO: "Wan Video",
     HUNYUAN_VIDEO: "Hunyuan Video",
     
@@ -69,6 +71,7 @@ export const BASE_MODEL_CLASSES = {
     
     // Video models
     [BASE_MODELS.SVD]: "svd",
+    [BASE_MODELS.LTXV]: "ltxv",
     [BASE_MODELS.WAN_VIDEO]: "wan-video",
     [BASE_MODELS.HUNYUAN_VIDEO]: "hunyuan-video",
     
@@ -84,6 +87,7 @@ export const BASE_MODEL_CLASSES = {
     [BASE_MODELS.NOOBAI]: "noobai",
     [BASE_MODELS.ILLUSTRIOUS]: "il",
     [BASE_MODELS.PONY]: "pony",
+    [BASE_MODELS.HIDREAM]: "hidream",
     
     // Default
     [BASE_MODELS.UNKNOWN]: "unknown"

static/js/utils/modalUtils.js

@@ -1,15 +1,18 @@
 import { modalManager } from '../managers/ModalManager.js';
+import { excludeLora, deleteModel as deleteLora } from '../api/loraApi.js';
+import { excludeCheckpoint, deleteCheckpoint } from '../api/checkpointApi.js';
 
 let pendingDeletePath = null;
 let pendingModelType = null;
+let pendingExcludePath = null;
+let pendingExcludeModelType = null;
 
 export function showDeleteModal(filePath, modelType = 'lora') {
-    // event.stopPropagation();
     pendingDeletePath = filePath;
     pendingModelType = modelType;
     
     const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
-    const modelName = card.dataset.name;
+    const modelName = card ? card.dataset.name : filePath.split('/').pop();
     const modal = modalManager.getModal('deleteModal').element;
     const modelInfo = modal.querySelector('.delete-model-info');
     
@@ -28,31 +31,19 @@ export async function confirmDelete() {
     const card = document.querySelector(`.lora-card[data-filepath="${pendingDeletePath}"]`);
     
     try {
-        // Use the appropriate endpoint based on model type
-        const endpoint = pendingModelType === 'checkpoint' ? 
-            '/api/checkpoints/delete' : 
-            '/api/delete_model';
-        
-        const response = await fetch(endpoint, {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json',
-            },
-            body: JSON.stringify({ 
-                file_path: pendingDeletePath
-            })
-        });
-
-        if (response.ok) {
-            if (card) {
-                card.remove();
-            }
-            closeDeleteModal();
+        // Use appropriate delete function based on model type
+        if (pendingModelType === 'checkpoint') {
+            await deleteCheckpoint(pendingDeletePath);
         } else {
-            const error = await response.text();
-            alert(`Failed to delete model: ${error}`);
+            await deleteLora(pendingDeletePath);
         }
+
+        if (card) {
+            card.remove();
+        }
+        closeDeleteModal();
     } catch (error) {
+        console.error('Error deleting model:', error);
         alert(`Error deleting model: ${error}`);
     }
 }
@@ -61,4 +52,46 @@ export function closeDeleteModal() {
     modalManager.closeModal('deleteModal');
     pendingDeletePath = null;
     pendingModelType = null;
+}
+
+// Functions for the exclude modal
+export function showExcludeModal(filePath, modelType = 'lora') {
+    pendingExcludePath = filePath;
+    pendingExcludeModelType = modelType;
+    
+    const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);
+    const modelName = card ? card.dataset.name : filePath.split('/').pop();
+    const modal = modalManager.getModal('excludeModal').element;
+    const modelInfo = modal.querySelector('.exclude-model-info');
+    
+    modelInfo.innerHTML = `
+        <strong>Model:</strong> ${modelName}
+        <br>
+        <strong>File:</strong> ${filePath}
+    `;
+    
+    modalManager.showModal('excludeModal');
+}
+
+export function closeExcludeModal() {
+    modalManager.closeModal('excludeModal');
+    pendingExcludePath = null;
+    pendingExcludeModelType = null;
+}
+
+export async function confirmExclude() {
+    if (!pendingExcludePath) return;
+    
+    try {
+        // Use appropriate exclude function based on model type
+        if (pendingExcludeModelType === 'checkpoint') {
+            await excludeCheckpoint(pendingExcludePath);
+        } else {
+            await excludeLora(pendingExcludePath);
+        }
+        
+        closeExcludeModal();
+    } catch (error) {
+        console.error('Error excluding model:', error);
+    }
 }

static/js/utils/uiHelpers.js

@@ -311,15 +311,12 @@ export function initFolderTagsVisibility() {
 }
 
 export function initBackToTop() {
-    const button = document.createElement('button');
-    button.className = 'back-to-top';
-    button.innerHTML = '<i class="fas fa-chevron-up"></i>';
-    button.title = 'Back to top';
-    document.body.appendChild(button);
+    const button = document.getElementById('backToTopBtn');
+    if (!button) return;
 
     // Get the scrollable container
     const scrollContainer = document.querySelector('.page-content');
-
+    
     // Show/hide button based on scroll position
     const toggleBackToTop = () => {
         const scrollThreshold = window.innerHeight * 0.3;

templates/base.html

@@ -73,8 +73,14 @@
         {% include 'components/modals.html' %}
         {% include 'components/loading.html' %}
         {% include 'components/context_menu.html' %}
+        {% include 'components/progress_panel.html' %}
         {% block additional_components %}{% endblock %}
 
+        <!-- Add back-to-top button here -->
+        <button id="backToTopBtn" class="back-to-top" title="Back to top">
+            <i class="fas fa-chevron-up"></i>
+        </button>
+
         <div class="container">
             {% if is_initializing %}
                 <!-- Show initialization component when initializing -->

templates/checkpoints.html

@@ -15,7 +15,7 @@
 {% include 'components/checkpoint_modals.html' %}
 
 <div id="checkpointContextMenu" class="context-menu" style="display: none;">
-    <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div>
+    <!-- <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div> -->
     <div class="context-menu-item" data-action="civitai"><i class="fas fa-external-link-alt"></i> View on CivitAI</div>
     <div class="context-menu-item" data-action="refresh-metadata"><i class="fas fa-sync"></i> Refresh Civitai Data</div>
     <div class="context-menu-item" data-action="copyname"><i class="fas fa-copy"></i> Copy Model Filename</div>
@@ -23,6 +23,7 @@
     <div class="context-menu-item" data-action="set-nsfw"><i class="fas fa-exclamation-triangle"></i> Set Content Rating</div>
     <div class="context-menu-separator"></div>
     <div class="context-menu-item" data-action="move"><i class="fas fa-folder-open"></i> Move to Folder</div>
+    <div class="context-menu-item" data-action="exclude"><i class="fas fa-eye-slash"></i> Exclude Model</div>
     <div class="context-menu-item delete-item" data-action="delete"><i class="fas fa-trash"></i> Delete Model</div>
 </div>
 {% endblock %}

templates/components/alphabet_bar.html

@@ -0,0 +1,22 @@
+<div class="alphabet-bar-container collapsed">
+    <div class="alphabet-bar">
+        <!-- <span class="alphabet-bar-title">Filter by</span> -->
+        <div class="letter-chip" data-letter="#" title="Numbers">
+            #<span class="count"></span>
+        </div>
+        {% for letter in "ABCDEFGHIJKLMNOPQRSTUVWXYZ" %}
+        <div class="letter-chip" data-letter="{{ letter }}" title="{{ letter }}">
+            {{ letter }}<span class="count"></span>
+        </div>
+        {% endfor %}
+        <div class="letter-chip" data-letter="@" title="Special characters">
+            @<span class="count"></span>
+        </div>
+        <div class="letter-chip" data-letter="漢" title="CJK characters">
+            漢<span class="count"></span>
+        </div>
+    </div>
+    <div class="toggle-alphabet-bar" title="Toggle alphabet filter">
+        <i class="fas fa-chevron-right"></i>
+    </div>
+</div>

templates/components/context_menu.html

@@ -1,7 +1,7 @@
 <div id="loraContextMenu" class="context-menu">
-    <div class="context-menu-item" data-action="detail">
+    <!-- <div class="context-menu-item" data-action="detail">
         <i class="fas fa-info-circle"></i> Show Details
-    </div>
+    </div> -->
     <div class="context-menu-item" data-action="civitai">
         <i class="fas fa-external-link-alt"></i> View on Civitai
     </div>
@@ -21,6 +21,9 @@
     <div class="context-menu-item" data-action="move">
         <i class="fas fa-folder-open"></i> Move to Folder
     </div>
+    <div class="context-menu-item" data-action="exclude">
+        <i class="fas fa-eye-slash"></i> Exclude Model
+    </div>
     <div class="context-menu-item delete-item" data-action="delete">
         <i class="fas fa-trash"></i> Delete Model
     </div>

templates/components/modals.html

@@ -11,6 +11,19 @@
     </div>
 </div>
 
+<!-- Exclude Confirmation Modal -->
+<div id="excludeModal" class="modal delete-modal">
+    <div class="modal-content delete-modal-content">
+        <h2>Exclude Model</h2>
+        <p class="delete-message">Are you sure you want to exclude this model? Excluded models won't appear in searches or model lists.</p>
+        <div class="exclude-model-info"></div>
+        <div class="modal-actions">
+            <button class="cancel-btn" onclick="closeExcludeModal()">Cancel</button>
+            <button class="exclude-btn" onclick="confirmExclude()">Exclude</button>
+        </div>
+    </div>
+</div>
+
 <!-- Settings Modal -->
 <div id="settingsModal" class="modal">
     <div class="modal-content settings-modal">
@@ -125,6 +138,46 @@
                     </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="exampleImagesPath">Download Location</label>
+                        </div>
+                        <div class="setting-control path-control">
+                            <input type="text" id="exampleImagesPath" placeholder="Enter folder path for example images" />
+                            <button id="exampleImagesDownloadBtn" class="primary-btn">
+                                <i class="fas fa-download"></i> <span id="exampleDownloadBtnText">Download</span>
+                            </button>
+                        </div>
+                    </div>
+                    <div class="input-help">
+                        Enter the folder path where example images from Civitai will be saved
+                    </div>
+                </div>
+                
+                <div class="setting-item">
+                    <div class="setting-row">
+                        <div class="setting-info">
+                            <label for="optimizeExampleImages">Optimize Downloaded Images</label>
+                        </div>
+                        <div class="setting-control">
+                            <label class="toggle-switch">
+                                <input type="checkbox" id="optimizeExampleImages" checked 
+                                       onchange="settingsManager.saveToggleSetting('optimizeExampleImages', 'optimize_example_images')">
+                                <span class="toggle-slider"></span>
+                            </label>
+                        </div>
+                    </div>
+                    <div class="input-help">
+                        Optimize example images to reduce file size and improve loading speed
+                    </div>
+                </div>
+            </div>
         </div>
     </div>
 </div>
@@ -189,6 +242,20 @@
                     <span>Support on Ko-fi</span>
                 </a>
             </div>
+
+            <!-- New section for Chinese payment methods -->
+            <div class="support-section">
+                <h3><i class="fas fa-qrcode"></i> WeChat Support</h3>
+                <p>For users in China, you can support via WeChat:</p>
+                <button class="secondary-btn qrcode-toggle" id="toggleQRCode">
+                    <i class="fas fa-qrcode"></i>
+                    <span class="toggle-text">Show WeChat QR Code</span>
+                    <i class="fas fa-chevron-down toggle-icon"></i>
+                </button>
+                <div class="qrcode-container" id="qrCodeContainer">
+                    <img src="/loras_static/images/wechat-qr.webp" alt="WeChat Pay QR Code" class="qrcode-image">
+                </div>
+            </div>
             
             <div class="support-footer">
                 <p>Thank you for using LoRA Manager! ❤️</p>

templates/components/progress_panel.html

@@ -0,0 +1,53 @@
+<!-- Example Images Download Progress Panel -->
+<div id="exampleImagesProgress" class="progress-panel">
+    <div class="progress-panel-header">
+        <div class="progress-panel-title">
+            <i class="fas fa-images"></i> Example Images Download
+        </div>
+        <div class="progress-panel-actions">
+            <button id="pauseExampleDownloadBtn" class="icon-button">
+                <i class="fas fa-pause"></i>
+                <svg class="mini-progress-container" width="24" height="24" viewBox="0 0 24 24">
+                    <circle class="mini-progress-background" cx="12" cy="12" r="10"></circle>
+                    <circle class="mini-progress-circle" cx="12" cy="12" r="10" stroke-dasharray="62.8" stroke-dashoffset="62.8"></circle>
+                </svg>
+                <span class="progress-percent"></span>
+            </button>
+            <button id="collapseProgressBtn" class="icon-button">
+                <i class="fas fa-chevron-down"></i>
+            </button>
+        </div>
+    </div>
+    <div class="progress-panel-content">
+        <div class="download-progress-info">
+            <div class="progress-status">
+                <span id="downloadStatusText">Initializing...</span>
+                <span id="downloadProgressCounts">0/0</span>
+            </div>
+            <div class="progress-container">
+                <div id="downloadProgressBar" class="progress-bar" style="width: 0%;"></div>
+            </div>
+        </div>
+        
+        <div class="current-model-info">
+            <div class="current-label">Currently downloading:</div>
+            <div id="currentModelName" class="current-model-name">-</div>
+        </div>
+        
+        <div class="download-stats">
+            <div class="stat-item">
+                <span class="stat-label">Elapsed:</span>
+                <span id="elapsedTime" class="stat-value">00:00:00</span>
+            </div>
+            <div class="stat-item">
+                <span class="stat-label">Remaining:</span>
+                <span id="remainingTime" class="stat-value">--:--:--</span>
+            </div>
+        </div>
+        
+        <div id="downloadErrorContainer" class="download-errors hidden">
+            <div class="error-header">Recent Errors:</div>
+            <div id="downloadErrors" class="error-list"></div>
+        </div>
+    </div>
+</div>

templates/loras.html

@@ -19,6 +19,7 @@
 
 {% block content %}
     {% include 'components/controls.html' %}
+    {% include 'components/alphabet_bar.html' %}
     <!-- Lora卡片容器 -->
     <div class="card-grid" id="loraGrid">
         <!-- Cards will be dynamically inserted here -->

templates/recipes.html

@@ -18,7 +18,7 @@
 {% include 'components/recipe_modal.html' %}
 
 <div id="recipeContextMenu" class="context-menu" style="display: none;">
-    <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div>
+    <!-- <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div> -->
     <div class="context-menu-item" data-action="share"><i class="fas fa-share-alt"></i> Share Recipe</div>
     <div class="context-menu-item" data-action="copy"><i class="fas fa-copy"></i> Copy Recipe Syntax</div>
     <div class="context-menu-item" data-action="viewloras"><i class="fas fa-layer-group"></i> View All LoRAs</div>

web/comfyui/loras_widget.js

@@ -900,7 +900,7 @@ export function addLorasWidget(node, name, opts, callback) {
     });
     
     // Calculate height based on number of loras and fixed sizes
-    const calculatedHeight = CONTAINER_PADDING + HEADER_HEIGHT + (lorasData.length * LORA_ENTRY_HEIGHT);
+    const calculatedHeight = CONTAINER_PADDING + HEADER_HEIGHT + (Math.min(lorasData.length, 5) * LORA_ENTRY_HEIGHT);
     updateWidgetHeight(calculatedHeight);
   };
 

web/comfyui/usage_stats.js

@@ -18,7 +18,7 @@ app.registerExtension({
     async updateUsageStats(promptId) {
         try {
             // Call backend endpoint with the prompt_id
-            const response = await fetch(`/loras/api/update-usage-stats`, {
+            const response = await fetch(`/api/update-usage-stats`, {
                 method: 'POST',
                 headers: {
                     'Content-Type': 'application/json',