feat: update version to 0.8.11 and add release notes for offline image support and download system improvements

Dev

LICENSE

@@ -1,21 +1,674 @@
-MIT License
+GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
 
-Copyright (c) 2023 Will Miao
+ Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
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+later version.
+
+  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
 
+### v0.8.11
+* **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
+* **Smoother Page Transitions** - Optimized interface switching between pages, eliminating flash issues particularly noticeable in dark theme
+* **Bug Fixes & Stability** - Resolved various issues to enhance overall reliability and performance
+
 ### v0.8.8
 * **Real-time TriggerWord Updates** - Enhanced TriggerWord Toggle node to instantly update when connected Lora Loader or Lora Stacker nodes change, without requiring workflow execution
 * **Optimized Metadata Recovery** - Improved utilization of existing .civitai.info files for faster initialization and preservation of metadata from models deleted from CivitAI
@@ -134,19 +151,26 @@ 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
 cd ComfyUI-Lora-Manager
-pip install requirements.txt
+pip install -r requirements.txt
 ```
 
 ## Usage
@@ -167,23 +191,92 @@ pip install 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
+
+Thank you for your interest in contributing to ComfyUI LoRA Manager! As this project is currently in its early stages and undergoing rapid development and refactoring, we are temporarily not accepting pull requests.
+
+However, your feedback and ideas are extremely valuable to us:
+- Please feel free to open issues for any bugs you encounter
+- Submit feature requests through GitHub issues
+- Share your suggestions for improvements
+
+We appreciate your understanding and look forward to potentially accepting code contributions once the project architecture stabilizes.
+
 ---
 
 ## Credits
 
 This project has been inspired by and benefited from other excellent ComfyUI extensions:
 
-- [ComfyUI-SaveImageWithMetaData](https://github.com/Comfy-Community/ComfyUI-SaveImageWithMetaData) - For the image metadata functionality
+- [ComfyUI-SaveImageWithMetaData](https://github.com/nkchocoai/ComfyUI-SaveImageWithMetaData) - For the image metadata functionality
 - [rgthree-comfy](https://github.com/rgthree/rgthree-comfy) - For the lora loader functionality
 
 ---
 
-## Contributing
-
-If you have suggestions, bug reports, or improvements, feel free to open an issue or contribute directly to the codebase. Pull requests are always welcome!
-
----
-
 ## ☕ Support
 
 If you find this project helpful, consider supporting its development:

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)  # 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

@@ -55,7 +55,6 @@ 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)
@@ -125,6 +124,7 @@ class ApiRoutes:
             # Get filter parameters
             base_models = request.query.get('base_models', None)
             tags = request.query.get('tags', None)
+            favorites_only = request.query.get('favorites_only', 'false').lower() == 'true'  # New parameter
             
             # New parameters for recipe filtering
             lora_hash = request.query.get('lora_hash', None)
@@ -155,7 +155,8 @@ class ApiRoutes:
                 base_models=filters.get('base_model', None),
                 tags=filters.get('tags', None),
                 search_options=search_options,
-                hash_filters=hash_filters
+                hash_filters=hash_filters,
+                favorites_only=favorites_only  # Pass favorites_only parameter
             )
 
             # Get all available folders from cache
@@ -195,6 +196,7 @@ class ApiRoutes:
             "from_civitai": lora.get("from_civitai", True),
             "usage_tips": lora.get("usage_tips", ""),
             "notes": lora.get("notes", ""),
+            "favorite": lora.get("favorite", False),  # Include favorite status in response
             "civitai": ModelRouteUtils.filter_civitai_data(lora.get("civitai", {}))
         }
 
@@ -512,21 +514,6 @@ 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"""
@@ -1057,4 +1044,4 @@ class ApiRoutes:
             return web.json_response({
                 "success": False,
                 "error": str(e)
-            }, status=500)
+            }, status=500)

py/routes/checkpoints_routes.py

@@ -69,6 +69,7 @@ class CheckpointsRoutes:
             fuzzy_search = request.query.get('fuzzy_search', 'false').lower() == 'true'
             base_models = request.query.getall('base_model', [])
             tags = request.query.getall('tag', [])
+            favorites_only = request.query.get('favorites_only', 'false').lower() == 'true'  # Add favorites_only parameter
             
             # Process search options
             search_options = {
@@ -101,7 +102,8 @@ class CheckpointsRoutes:
                 base_models=base_models,
                 tags=tags,
                 search_options=search_options,
-                hash_filters=hash_filters
+                hash_filters=hash_filters,
+                favorites_only=favorites_only  # Pass favorites_only parameter
             )
             
             # Format response items
@@ -123,7 +125,8 @@ class CheckpointsRoutes:
     async def get_paginated_data(self, page, page_size, sort_by='name', 
                                folder=None, search=None, fuzzy_search=False,
                                base_models=None, tags=None,
-                               search_options=None, hash_filters=None):
+                               search_options=None, hash_filters=None,
+                               favorites_only=False):  # Add favorites_only parameter with default False
         """Get paginated and filtered checkpoint data"""
         cache = await self.scanner.get_cached_data()
 
@@ -181,6 +184,13 @@ class CheckpointsRoutes:
                 if not cp.get('preview_nsfw_level') or cp.get('preview_nsfw_level') < NSFW_LEVELS['R']
             ]
         
+        # Apply favorites filtering if enabled
+        if favorites_only:
+            filtered_data = [
+                cp for cp in filtered_data
+                if cp.get('favorite', False) is True
+            ]
+        
         # Apply folder filtering
         if folder is not None:
             if search_options.get('recursive', False):
@@ -276,6 +286,7 @@ class CheckpointsRoutes:
             "from_civitai": checkpoint.get("from_civitai", True),
             "notes": checkpoint.get("notes", ""),
             "model_type": checkpoint.get("model_type", "checkpoint"),
+            "favorite": checkpoint.get("favorite", False),
             "civitai": ModelRouteUtils.filter_civitai_data(checkpoint.get("civitai", {}))
         }
     

py/routes/misc_routes.py

@@ -0,0 +1,596 @@
+import logging
+import os
+import asyncio
+import json
+import time
+import tkinter as tk
+from tkinter import filedialog
+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
+
+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
+}
+
+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'])
+            
+            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'])
+            
+            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'])
+        
+        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 _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))
+            
+            # 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 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_success = True  # Track if all images for this model download successfully
+                
+                try:
+                    # Update current model info
+                    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', '')
+                    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:
+                        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())
+                                
+                                # Mark as successfully processed if all local images were processed
+                                download_progress['processed_models'].add(model_hash)
+                                local_images_processed = True
+                                logger.info(f"Successfully processed local examples for {model_name}")
+                        
+                        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
+                            # Continue to remote download if local processing fails
+                    
+                    # If we didn't process local images, download from remote
+                    if not local_images_processed:
+                        # Download example images
+                        for i, image in enumerate(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)
+                                    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
+                        
+                        # 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']),
+                                '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']),
+                        '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__)
 
@@ -74,6 +83,9 @@ class RecipeRoutes:
         
         # Add route to get recipes for a specific Lora
         app.router.add_get('/api/recipes/for-lora', routes.get_recipes_for_lora)
+        
+        # Add new endpoint for scanning and rebuilding the recipe cache
+        app.router.add_get('/api/recipes/scan', routes.scan_recipes)
     
     async def _init_cache(self, app):
         """Initialize cache on startup"""
@@ -801,8 +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)
@@ -1255,3 +1270,24 @@ class RecipeRoutes:
         except Exception as e:
             logger.error(f"Error getting recipes for Lora: {str(e)}")
             return web.json_response({'success': False, 'error': str(e)}, status=500)
+
+    async def scan_recipes(self, request: web.Request) -> web.Response:
+        """API endpoint for scanning and rebuilding the recipe cache"""
+        try:
+            # Ensure services are initialized
+            await self.init_services()
+            
+            # Force refresh the recipe cache
+            logger.info("Manually triggering recipe cache rebuild")
+            await self.recipe_scanner.get_cached_data(force_refresh=True)
+            
+            return web.json_response({
+                'success': True,
+                'message': 'Recipe cache refreshed successfully'
+            })
+        except Exception as e:
+            logger.error(f"Error refreshing recipe cache: {e}", exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            }, status=500)

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

@@ -34,6 +34,7 @@ class CivitaiClient:
             'User-Agent': 'ComfyUI-LoRA-Manager/1.0'
         }
         self._session = None
+        self._session_created_at = None
         # Set default buffer size to 1MB for higher throughput
         self.chunk_size = 1024 * 1024
     
@@ -44,8 +45,8 @@ class CivitaiClient:
             # Optimize TCP connection parameters
             connector = aiohttp.TCPConnector(
                 ssl=True,
-                limit=10,  # Increase parallel connections
-                ttl_dns_cache=300,  # DNS cache time
+                limit=3,  # Further reduced from 5 to 3
+                ttl_dns_cache=0,  # Disabled DNS caching completely
                 force_close=False,  # Keep connections for reuse
                 enable_cleanup_closed=True
             )
@@ -57,7 +58,18 @@ class CivitaiClient:
                 trust_env=trust_env,
                 timeout=timeout
             )
+            self._session_created_at = datetime.now()
         return self._session
+    
+    async def _ensure_fresh_session(self):
+        """Refresh session if it's been open too long"""
+        if self._session is not None:
+            if not hasattr(self, '_session_created_at') or \
+               (datetime.now() - self._session_created_at).total_seconds() > 300:  # 5 minutes
+                await self.close()
+                self._session = None
+        
+        return await self.session
 
     def _parse_content_disposition(self, header: str) -> str:
         """Parse filename from content-disposition header"""
@@ -103,13 +115,15 @@ class CivitaiClient:
         Returns:
             Tuple[bool, str]: (success, save_path or error message)
         """
-        session = await self.session
+        logger.debug(f"Resolving DNS for: {url}")
+        session = await self._ensure_fresh_session()
         try:
             headers = self._get_request_headers()
             
             # Add Range header to allow resumable downloads
             headers['Accept-Encoding'] = 'identity'  # Disable compression for better chunked downloads
             
+            logger.debug(f"Starting download from: {url}")
             async with session.get(url, headers=headers, allow_redirects=True) as response:
                 if response.status != 200:
                     # Handle 401 unauthorized responses
@@ -124,6 +138,7 @@ class CivitaiClient:
                         return False, "Access forbidden: You don't have permission to download this file."
                     
                     # Generic error response for other status codes
+                    logger.error(f"Download failed for {url} with status {response.status}")
                     return False, f"Download failed with status {response.status}"
 
                 # Get filename from content-disposition header
@@ -170,7 +185,7 @@ class CivitaiClient:
 
     async def get_model_by_hash(self, model_hash: str) -> Optional[Dict]:
         try:
-            session = await self.session
+            session = await self._ensure_fresh_session()
             async with session.get(f"{self.base_url}/model-versions/by-hash/{model_hash}") as response:
                 if response.status == 200:
                     return await response.json()
@@ -181,7 +196,7 @@ class CivitaiClient:
 
     async def download_preview_image(self, image_url: str, save_path: str):
         try:
-            session = await self.session
+            session = await self._ensure_fresh_session()
             async with session.get(image_url) as response:
                 if response.status == 200:
                     content = await response.read()
@@ -196,7 +211,7 @@ class CivitaiClient:
     async def get_model_versions(self, model_id: str) -> List[Dict]:
         """Get all versions of a model with local availability info"""
         try:
-            session = await self.session  # 等待获取 session
+            session = await self._ensure_fresh_session()  # Use fresh session
             async with session.get(f"{self.base_url}/models/{model_id}") as response:
                 if response.status != 200:
                     return None
@@ -222,12 +237,14 @@ class CivitaiClient:
                 - An error message if there was an error, or None on success
         """
         try:
-            session = await self.session
+            session = await self._ensure_fresh_session()
             url = f"{self.base_url}/model-versions/{version_id}"
             headers = self._get_request_headers()
             
+            logger.debug(f"Resolving DNS for model version info: {url}")
             async with session.get(url, headers=headers) as response:
                 if response.status == 200:
+                    logger.debug(f"Successfully fetched model version info for: {version_id}")
                     return await response.json(), None
                 
                 # Handle specific error cases
@@ -242,6 +259,7 @@ class CivitaiClient:
                         return None, "Model not found (status 404)"
                 
                 # Other error cases
+                logger.error(f"Failed to fetch model info for {version_id} (status {response.status})")
                 return None, f"Failed to fetch model info (status {response.status})"
         except Exception as e:
             error_msg = f"Error fetching model version info: {e}"
@@ -260,7 +278,7 @@ class CivitaiClient:
                 - The HTTP status code from the request
         """
         try:
-            session = await self.session
+            session = await self._ensure_fresh_session()
             headers = self._get_request_headers()
             url = f"{self.base_url}/models/{model_id}"
             
@@ -304,10 +322,11 @@ class CivitaiClient:
     async def _get_hash_from_civitai(self, model_version_id: str) -> Optional[str]:
         """Get hash from Civitai API"""
         try:
-            if not self._session:
+            session = await self._ensure_fresh_session()
+            if not session:
                 return None
             
-            version_info = await self._session.get(f"{self.base_url}/model-versions/{model_version_id}")
+            version_info = await session.get(f"{self.base_url}/model-versions/{model_version_id}")
             
             if not version_info or not version_info.json().get('files'):
                 return None

py/services/download_manager.py

@@ -88,16 +88,16 @@ class DownloadManager:
             version_info = None
             error_msg = None
             
-            if download_url:
-                # Extract version ID from download URL
-                version_id = download_url.split('/')[-1]
-                version_info, error_msg = await civitai_client.get_model_version_info(version_id)
+            if model_hash:
+                # Get model by hash
+                version_info = await civitai_client.get_model_by_hash(model_hash)
             elif model_version_id:
                 # Use model version ID directly
                 version_info, error_msg = await civitai_client.get_model_version_info(model_version_id)
-            elif model_hash:
-                # Get model by hash
-                version_info = await civitai_client.get_model_by_hash(model_hash)
+            elif download_url:
+                # Extract version ID from download URL
+                version_id = download_url.split('/')[-1]
+                version_info, error_msg = await civitai_client.get_model_version_info(version_id)
 
             
             if not version_info:

py/services/lora_scanner.py

@@ -122,7 +122,8 @@ class LoraScanner(ModelScanner):
     async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'name', 
                                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) -> Dict:
+                               search_options: dict = None, hash_filters: dict = None,
+                               favorites_only: bool = False) -> Dict:
         """Get paginated and filtered lora data
         
         Args:
@@ -136,6 +137,7 @@ class LoraScanner(ModelScanner):
             tags: List of tags to filter by
             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
         """
         cache = await self.get_cached_data()
 
@@ -194,6 +196,13 @@ class LoraScanner(ModelScanner):
                 if not lora.get('preview_nsfw_level') or lora.get('preview_nsfw_level') < NSFW_LEVELS['R']
             ]
         
+        # Apply favorites filtering if enabled
+        if favorites_only:
+            filtered_data = [
+                lora for lora in filtered_data
+                if lora.get('favorite', False) is True
+            ]
+        
         # Apply folder filtering
         if folder is not None:
             if search_options.get('recursive', False):

py/services/model_scanner.py

@@ -736,6 +736,12 @@ class ModelScanner:
                 shutil.move(source_metadata, target_metadata)
                 metadata = await self._update_metadata_paths(target_metadata, target_file)
             
+            # Move civitai.info file if exists
+            source_civitai = os.path.join(source_dir, f"{base_name}.civitai.info")
+            if os.path.exists(source_civitai):
+                target_civitai = os.path.join(target_path, f"{base_name}.civitai.info")
+                shutil.move(source_civitai, target_civitai)
+            
             for ext in PREVIEW_EXTENSIONS:
                 source_preview = os.path.join(source_dir, f"{base_name}{ext}")
                 if os.path.exists(source_preview):

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

@@ -22,6 +22,7 @@ class BaseModelMetadata:
     tags: List[str] = None      # Model tags
     modelDescription: str = ""  # Full model description
     civitai_deleted: bool = False  # Whether deleted from Civitai
+    favorite: bool = False      # Whether the model is a favorite
 
     def __post_init__(self):
         # Initialize empty lists to avoid mutable default parameter issue

py/utils/recipe_parsers.py

@@ -97,8 +97,9 @@ class RecipeMetadataParser(ABC):
                 
                 # Process file information if available
                 if 'files' in civitai_info:
+                    # Find the primary model file (type="Model" and primary=true) in the files list
                     model_file = next((file for file in civitai_info.get('files', []) 
-                                    if file.get('type') == 'Model'), None)
+                                      if file.get('type') == 'Model' and file.get('primary') == True), None)
                     
                     if model_file:
                         # Get size
@@ -402,27 +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:
@@ -435,7 +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"""
@@ -444,51 +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 = {}
@@ -506,7 +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,
@@ -556,6 +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/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 = "0.8.8"
+version = "0.8.11"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",
@@ -12,7 +12,8 @@ dependencies = [
     "piexif",
     "Pillow",
     "olefile", # for getting rid of warning message
-    "requests"
+    "requests",
+    "toml"
 ]
 
 [project.urls]

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

@@ -6,4 +6,7 @@ beautifulsoup4
 piexif
 Pillow
 olefile
-requests
+requests
+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/base.css

@@ -59,6 +59,16 @@ html, body {
     --scrollbar-width: 8px; /* 添加滚动条宽度变量 */
 }
 
+html[data-theme="dark"] {
+    background-color: #1a1a1a !important;
+    color-scheme: dark;
+}
+
+html[data-theme="light"] {
+    background-color: #ffffff !important;
+    color-scheme: light;
+}
+
 [data-theme="dark"] {
     --bg-color: #1a1a1a;
     --text-color: #e0e0e0;

static/css/components/card.css

@@ -192,12 +192,43 @@
     margin-left: var(--space-1);
     cursor: pointer;
     color: white;
-    transition: opacity 0.2s;
-    font-size: 0.9em;
+    transition: opacity 0.2s, transform 0.15s ease;
+    font-size: 1.0em; /* Increased from 0.9em for better visibility */
+    width: 16px; /* Fixed width for consistent spacing */
+    height: 16px; /* Fixed height for larger touch target */
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: 50%;
+    padding: 4px; /* Add padding to increase clickable area */
+    box-sizing: content-box; /* Ensure padding adds to dimensions */
+    position: relative; /* For proper positioning */
+    margin: 0; /* Reset margin */
+}
+
+.card-actions i::before {
+    position: absolute; /* Position the icon glyph */
+    top: 50%;
+    left: 50%;
+    transform: translate(-50%, -50%); /* Center the icon */
+}
+
+.card-actions {
+    display: flex;
+    gap: var(--space-1); /* Use gap instead of margin for spacing between icons */
+    align-items: center;
 }
 
 .card-actions i:hover {
-    opacity: 0.8;
+    opacity: 0.9;
+    transform: scale(1.1);
+    background-color: rgba(255, 255, 255, 0.1);
+}
+
+/* Style for active favorites */
+.favorite-active {
+    color: #ffc107 !important; /* Gold color for favorites */
+    text-shadow: 0 0 5px rgba(255, 193, 7, 0.5);
 }
 
 /* 响应式设计 */

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/modal.css

@@ -496,6 +496,107 @@ 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/layout.css

@@ -81,6 +81,22 @@
     opacity: 1;
 }
 
+/* Controls */
+.control-group button.favorite-filter {
+    position: relative;
+    overflow: hidden;
+}
+
+.control-group button.favorite-filter.active {
+    background: var(--lora-accent);
+    color: white;
+}
+
+.control-group button.favorite-filter i {
+    margin-right: 4px;
+    color: #ffc107;
+}
+
 /* Active state for buttons that can be toggled */
 .control-group button.active {
     background: var(--lora-accent);
@@ -244,8 +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 +20,7 @@
 @import 'components/shared.css';
 @import 'components/filter-indicator.css';
 @import 'components/initialization.css';
+@import 'components/progress-panel.css';
 
 .initialization-notice {
     display: flex;

static/js/api/baseModelApi.js

@@ -45,6 +45,11 @@ export async function loadMoreModels(options = {}) {
             params.append('folder', pageState.activeFolder);
         }
 
+        // Add favorites filter parameter if enabled
+        if (pageState.showFavoritesOnly) {
+            params.append('favorites_only', 'true');
+        }
+
         // Add search parameters if there's a search term
         if (pageState.filters?.search) {
             params.append('search', pageState.filters.search);

static/js/api/checkpointApi.js

@@ -62,8 +62,13 @@ export async function refreshSingleCheckpointMetadata(filePath) {
     return refreshSingleModelMetadata(filePath, 'checkpoint');
 }
 
-// Save checkpoint metadata (similar to the Lora version)
-export async function saveCheckpointMetadata(filePath, data) {
+/**
+ * Save model metadata to the server
+ * @param {string} filePath - Path to the model file
+ * @param {Object} data - Metadata to save
+ * @returns {Promise} - Promise that resolves with the server response
+ */
+export async function saveModelMetadata(filePath, data) {
     const response = await fetch('/api/checkpoints/save-metadata', {
         method: 'POST',
         headers: {
@@ -79,5 +84,5 @@ export async function saveCheckpointMetadata(filePath, data) {
         throw new Error('Failed to save metadata');
     }
     
-    return await response.json();
+    return response.json();
 }

static/js/api/loraApi.js

@@ -9,6 +9,31 @@ import {
     refreshSingleModelMetadata
 } from './baseModelApi.js';
 
+/**
+ * Save model metadata to the server
+ * @param {string} filePath - File path
+ * @param {Object} data - Data to save
+ * @returns {Promise} Promise of the save operation
+ */
+export async function saveModelMetadata(filePath, data) {
+    const response = await fetch('/api/loras/save-metadata', {
+        method: 'POST',
+        headers: {
+            'Content-Type': 'application/json',
+        },
+        body: JSON.stringify({
+            file_path: filePath,
+            ...data
+        })
+    });
+
+    if (!response.ok) {
+        throw new Error('Failed to save metadata');
+    }
+    
+    return response.json();
+}
+
 export async function loadMoreLoras(resetPage = false, updateFolders = false) {
     return loadMoreModels({
         resetPage,

static/js/components/CheckpointCard.js

@@ -2,7 +2,7 @@ import { showToast, copyToClipboard } from '../utils/uiHelpers.js';
 import { state } from '../state/index.js';
 import { showCheckpointModal } from './checkpointModal/index.js';
 import { NSFW_LEVELS } from '../utils/constants.js';
-import { replaceCheckpointPreview as apiReplaceCheckpointPreview } from '../api/checkpointApi.js';
+import { replaceCheckpointPreview as apiReplaceCheckpointPreview, saveModelMetadata } from '../api/checkpointApi.js';
 
 export function createCheckpointCard(checkpoint) {
     const card = document.createElement('div');
@@ -17,6 +17,7 @@ export function createCheckpointCard(checkpoint) {
     card.dataset.from_civitai = checkpoint.from_civitai;
     card.dataset.notes = checkpoint.notes || '';
     card.dataset.base_model = checkpoint.base_model || 'Unknown';
+    card.dataset.favorite = checkpoint.favorite ? 'true' : 'false';
 
     // Store metadata if available
     if (checkpoint.civitai) {
@@ -65,6 +66,9 @@ export function createCheckpointCard(checkpoint) {
     const isVideo = previewUrl.endsWith('.mp4');
     const videoAttrs = autoplayOnHover ? 'controls muted loop' : 'controls autoplay muted loop';
 
+    // Get favorite status from checkpoint data
+    const isFavorite = checkpoint.favorite === true;
+
     card.innerHTML = `
         <div class="card-preview ${shouldBlur ? 'blurred' : ''}">
             ${isVideo ? 
@@ -82,6 +86,9 @@ export function createCheckpointCard(checkpoint) {
                     ${checkpoint.base_model}
                 </span>
                 <div class="card-actions">
+                    <i class="${isFavorite ? 'fas fa-star favorite-active' : 'far fa-star'}" 
+                       title="${isFavorite ? 'Remove from favorites' : 'Add to favorites'}">
+                    </i>
                     <i class="fas fa-globe" 
                        title="${checkpoint.from_civitai ? 'View on Civitai' : 'Not available from Civitai'}"
                        ${!checkpoint.from_civitai ? 'style="opacity: 0.5; cursor: not-allowed"' : ''}>
@@ -198,6 +205,39 @@ export function createCheckpointCard(checkpoint) {
         });
     }
 
+    // Favorite button click event
+    card.querySelector('.fa-star')?.addEventListener('click', async e => {
+        e.stopPropagation();
+        const starIcon = e.currentTarget;
+        const isFavorite = starIcon.classList.contains('fas');
+        const newFavoriteState = !isFavorite;
+        
+        try {
+            // Save the new favorite state to the server
+            await saveModelMetadata(card.dataset.filepath, { 
+                favorite: newFavoriteState 
+            });
+
+            // Update the UI
+            if (newFavoriteState) {
+                starIcon.classList.remove('far');
+                starIcon.classList.add('fas', 'favorite-active');
+                starIcon.title = 'Remove from favorites';
+                card.dataset.favorite = 'true';
+                showToast('Added to favorites', 'success');
+            } else {
+                starIcon.classList.remove('fas', 'favorite-active');
+                starIcon.classList.add('far');
+                starIcon.title = 'Add to favorites';
+                card.dataset.favorite = 'false';
+                showToast('Removed from favorites', 'success');
+            }
+        } catch (error) {
+            console.error('Failed to update favorite status:', error);
+            showToast('Failed to update favorite status', 'error');
+        }
+    });
+
     // Copy button click event
     card.querySelector('.fa-copy')?.addEventListener('click', async e => {
         e.stopPropagation();

static/js/components/ContextMenu/CheckpointContextMenu.js

@@ -1,5 +1,5 @@
 import { BaseContextMenu } from './BaseContextMenu.js';
-import { refreshSingleCheckpointMetadata, saveCheckpointMetadata } from '../../api/checkpointApi.js';
+import { refreshSingleCheckpointMetadata, saveModelMetadata } from '../../api/checkpointApi.js';
 import { showToast, getNSFWLevelName } from '../../utils/uiHelpers.js';
 import { NSFW_LEVELS } from '../../utils/constants.js';
 import { getStorageItem } from '../../utils/storageHelpers.js';
@@ -82,7 +82,7 @@ export class CheckpointContextMenu extends BaseContextMenu {
                 if (!filePath) return;
                 
                 try {
-                    await saveCheckpointMetadata(filePath, { preview_nsfw_level: level });
+                    await saveModelMetadata(filePath, { preview_nsfw_level: level });
                     
                     // Update card data
                     const card = document.querySelector(`.lora-card[data-filepath="${filePath}"]`);

static/js/components/ContextMenu/LoraContextMenu.js

@@ -1,5 +1,5 @@
 import { BaseContextMenu } from './BaseContextMenu.js';
-import { refreshSingleLoraMetadata } from '../../api/loraApi.js';
+import { refreshSingleLoraMetadata, saveModelMetadata } from '../../api/loraApi.js';
 import { showToast, getNSFWLevelName } from '../../utils/uiHelpers.js';
 import { NSFW_LEVELS } from '../../utils/constants.js';
 import { getStorageItem } from '../../utils/storageHelpers.js';
@@ -111,22 +111,7 @@ export class LoraContextMenu extends BaseContextMenu {
     }
 
     async saveModelMetadata(filePath, data) {
-        const response = await fetch('/api/loras/save-metadata', {
-            method: 'POST',
-            headers: {
-                'Content-Type': 'application/json',
-            },
-            body: JSON.stringify({
-                file_path: filePath,
-                ...data
-            })
-        });
-    
-        if (!response.ok) {
-            throw new Error('Failed to save metadata');
-        }
-        
-        return await response.json();
+        return saveModelMetadata(filePath, data);
     }
 
     updateCardBlurEffect(card, level) {

static/js/components/LoraCard.js

@@ -3,7 +3,7 @@ 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 } from '../api/loraApi.js'
+import { replacePreview, deleteModel, saveModelMetadata } from '../api/loraApi.js'
 
 export function createLoraCard(lora) {
     const card = document.createElement('div');
@@ -20,6 +20,7 @@ export function createLoraCard(lora) {
     card.dataset.usage_tips = lora.usage_tips;
     card.dataset.notes = lora.notes;
     card.dataset.meta = JSON.stringify(lora.civitai || {});
+    card.dataset.favorite = lora.favorite ? 'true' : 'false';
     
     // Store tags and model description
     if (lora.tags && Array.isArray(lora.tags)) {
@@ -65,6 +66,9 @@ export function createLoraCard(lora) {
     const isVideo = previewUrl.endsWith('.mp4');
     const videoAttrs = autoplayOnHover ? 'controls muted loop' : 'controls autoplay muted loop';
 
+    // Get favorite status from the lora data
+    const isFavorite = lora.favorite === true;
+
     card.innerHTML = `
         <div class="card-preview ${shouldBlur ? 'blurred' : ''}">
             ${isVideo ? 
@@ -82,6 +86,9 @@ export function createLoraCard(lora) {
                     ${lora.base_model}
                 </span>
                 <div class="card-actions">
+                    <i class="${isFavorite ? 'fas fa-star favorite-active' : 'far fa-star'}" 
+                       title="${isFavorite ? 'Remove from favorites' : 'Add to favorites'}">
+                    </i>
                     <i class="fas fa-globe" 
                        title="${lora.from_civitai ? 'View on Civitai' : 'Not available from Civitai'}"
                        ${!lora.from_civitai ? 'style="opacity: 0.5; cursor: not-allowed"' : ''}>
@@ -135,6 +142,7 @@ export function createLoraCard(lora) {
                 base_model: card.dataset.base_model,
                 usage_tips: card.dataset.usage_tips,
                 notes: card.dataset.notes,
+                favorite: card.dataset.favorite === 'true',
                 // Parse civitai metadata from the card's dataset
                 civitai: (() => {
                     try {
@@ -198,6 +206,39 @@ export function createLoraCard(lora) {
         });
     }
 
+    // Favorite button click event
+    card.querySelector('.fa-star')?.addEventListener('click', async e => {
+        e.stopPropagation();
+        const starIcon = e.currentTarget;
+        const isFavorite = starIcon.classList.contains('fas');
+        const newFavoriteState = !isFavorite;
+        
+        try {
+            // Save the new favorite state to the server
+            await saveModelMetadata(card.dataset.filepath, { 
+                favorite: newFavoriteState 
+            });
+
+            // Update the UI
+            if (newFavoriteState) {
+                starIcon.classList.remove('far');
+                starIcon.classList.add('fas', 'favorite-active');
+                starIcon.title = 'Remove from favorites';
+                card.dataset.favorite = 'true';
+                showToast('Added to favorites', 'success');
+            } else {
+                starIcon.classList.remove('fas', 'favorite-active');
+                starIcon.classList.add('far');
+                starIcon.title = 'Add to favorites';
+                card.dataset.favorite = 'false';
+                showToast('Removed from favorites', 'success');
+            }
+        } catch (error) {
+            console.error('Failed to update favorite status:', error);
+            showToast('Failed to update favorite status', 'error');
+        }
+    });
+
     // Copy button click event
     card.querySelector('.fa-copy')?.addEventListener('click', async e => {
         e.stopPropagation();

static/js/components/checkpointModal/ModelMetadata.js

@@ -5,31 +5,7 @@
 import { showToast } from '../../utils/uiHelpers.js';
 import { BASE_MODELS } from '../../utils/constants.js';
 import { updateCheckpointCard } from '../../utils/cardUpdater.js';
-
-/**
- * Save model metadata to the server
- * @param {string} filePath - Path to the model file
- * @param {Object} data - Metadata to save
- * @returns {Promise} - Promise that resolves with the server response
- */
-export async function saveModelMetadata(filePath, data) {
-    const response = await fetch('/api/checkpoints/save-metadata', {
-        method: 'POST',
-        headers: {
-            'Content-Type': 'application/json',
-        },
-        body: JSON.stringify({
-            file_path: filePath,
-            ...data
-        })
-    });
-
-    if (!response.ok) {
-        throw new Error('Failed to save metadata');
-    }
-    
-    return response.json();
-}
+import { saveModelMetadata } from '../../api/checkpointApi.js';
 
 /**
  * Set up model name editing functionality

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"
@@ -382,15 +417,73 @@ 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 +578,4 @@ export function scrollToTop(button) {
             behavior: 'smooth'
         });
     }
-}
+}

static/js/components/checkpointModal/index.js

@@ -11,9 +11,9 @@ import { setupTabSwitching, loadModelDescription } from './ModelDescription.js';
 import { 
     setupModelNameEditing, 
     setupBaseModelEditing, 
-    setupFileNameEditing,
-    saveModelMetadata
+    setupFileNameEditing
 } from './ModelMetadata.js';
+import { saveModelMetadata } from '../../api/checkpointApi.js';
 import { renderCompactTags, setupTagTooltip, formatFileSize } from './utils.js';
 import { updateCheckpointCard } from '../../utils/cardUpdater.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

@@ -2,7 +2,6 @@
 import { PageControls } from './PageControls.js';
 import { loadMoreLoras, fetchCivitai, resetAndReload, refreshLoras } from '../../api/loraApi.js';
 import { getSessionItem, removeSessionItem } from '../../utils/storageHelpers.js';
-import { showToast } from '../../utils/uiHelpers.js';
 
 /**
  * LorasControls class - Extends PageControls for LoRA-specific functionality

static/js/components/controls/PageControls.js

@@ -1,6 +1,6 @@
 // PageControls.js - Manages controls for both LoRAs and Checkpoints pages
 import { state, getCurrentPageState, setCurrentPageType } from '../../state/index.js';
-import { getStorageItem, setStorageItem } from '../../utils/storageHelpers.js';
+import { getStorageItem, setStorageItem, getSessionItem, setSessionItem } from '../../utils/storageHelpers.js';
 import { showToast } from '../../utils/uiHelpers.js';
 
 /**
@@ -26,6 +26,9 @@ export class PageControls {
         // Initialize event listeners
         this.initEventListeners();
         
+        // Initialize favorites filter button state
+        this.initFavoritesFilter();
+        
         console.log(`PageControls initialized for ${pageType} page`);
     }
     
@@ -121,6 +124,12 @@ export class PageControls {
                 bulkButton.addEventListener('click', () => this.toggleBulkMode());
             }
         }
+        
+        // Favorites filter button handler
+        const favoriteFilterBtn = document.getElementById('favoriteFilterBtn');
+        if (favoriteFilterBtn) {
+            favoriteFilterBtn.addEventListener('click', () => this.toggleFavoritesOnly());
+        }
     }
     
     /**
@@ -385,4 +394,50 @@ export class PageControls {
             showToast('Failed to clear custom filter: ' + error.message, 'error');
         }
     }
+    
+    /**
+     * Initialize the favorites filter button state
+     */
+    initFavoritesFilter() {
+        const favoriteFilterBtn = document.getElementById('favoriteFilterBtn');
+        if (favoriteFilterBtn) {
+            // Get current state from session storage with page-specific key
+            const storageKey = `show_favorites_only_${this.pageType}`;
+            const showFavoritesOnly = getSessionItem(storageKey, false);
+            
+            // Update button state
+            if (showFavoritesOnly) {
+                favoriteFilterBtn.classList.add('active');
+            }
+            
+            // Update app state
+            this.pageState.showFavoritesOnly = showFavoritesOnly;
+        }
+    }
+    
+    /**
+     * Toggle favorites-only filter and reload models
+     */
+    async toggleFavoritesOnly() {
+        const favoriteFilterBtn = document.getElementById('favoriteFilterBtn');
+        
+        // Toggle the filter state in storage
+        const storageKey = `show_favorites_only_${this.pageType}`;
+        const currentState = this.pageState.showFavoritesOnly;
+        const newState = !currentState;
+        
+        // Update session storage
+        setSessionItem(storageKey, newState);
+        
+        // Update state
+        this.pageState.showFavoritesOnly = newState;
+        
+        // Update button appearance
+        if (favoriteFilterBtn) {
+            favoriteFilterBtn.classList.toggle('active', newState);
+        }
+        
+        // Reload models with new filter
+        await this.resetAndReload(true);
+    }
 }

static/js/components/loraModal/ModelMetadata.js

@@ -5,31 +5,7 @@
 import { showToast } from '../../utils/uiHelpers.js';
 import { BASE_MODELS } from '../../utils/constants.js';
 import { updateLoraCard } from '../../utils/cardUpdater.js';
-
-/**
- * 保存模型元数据到服务器
- * @param {string} filePath - 文件路径
- * @param {Object} data - 要保存的数据
- * @returns {Promise} 保存操作的Promise
- */
-export async function saveModelMetadata(filePath, data) {
-    const response = await fetch('/api/loras/save-metadata', {
-        method: 'POST',
-        headers: {
-            'Content-Type': 'application/json',
-        },
-        body: JSON.stringify({
-            file_path: filePath,
-            ...data
-        })
-    });
-
-    if (!response.ok) {
-        throw new Error('Failed to save metadata');
-    }
-    
-    return response.json();
-}
+import { saveModelMetadata } from '../../api/loraApi.js';
 
 /**
  * 设置模型名称编辑功能

static/js/components/loraModal/PresetTags.js

@@ -2,8 +2,7 @@
  * PresetTags.js
  * 处理LoRA模型预设参数标签相关的功能模块
  */
-import { saveModelMetadata } from './ModelMetadata.js';
-import { showToast } from '../../utils/uiHelpers.js';
+import { saveModelMetadata } from '../../api/loraApi.js';
 
 /**
  * 解析预设参数

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"
@@ -392,15 +431,73 @@ 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 +594,4 @@ export function scrollToTop(button) {
             behavior: 'smooth'
         });
     }
-}
+}

static/js/components/loraModal/TriggerWords.js

@@ -3,7 +3,7 @@
  * 处理LoRA模型触发词相关的功能模块
  */
 import { showToast, copyToClipboard } from '../../utils/uiHelpers.js';
-import { saveModelMetadata } from './ModelMetadata.js';
+import { saveModelMetadata } from '../../api/loraApi.js';
 
 /**
  * 渲染触发词

static/js/components/loraModal/index.js

@@ -13,9 +13,9 @@ import { loadRecipesForLora } from './RecipeTab.js'; // Add import for recipe ta
 import { 
     setupModelNameEditing, 
     setupBaseModelEditing, 
-    setupFileNameEditing,
-    saveModelMetadata
+    setupFileNameEditing
 } from './ModelMetadata.js';
+import { saveModelMetadata } from '../../api/loraApi.js';
 import { renderCompactTags, setupTagTooltip, formatFileSize } from './utils.js';
 import { updateLoraCard } from '../../utils/cardUpdater.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/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/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/recipes.js

@@ -268,6 +268,32 @@ class RecipeManager {
         }
     }
     
+    /**
+     * Refreshes the recipe list by first rebuilding the cache and then loading recipes
+     */
+    async refreshRecipes() {
+        try {           
+            // Call the new endpoint to rebuild the recipe cache
+            const response = await fetch('/api/recipes/scan');
+            
+            if (!response.ok) {
+                const data = await response.json();
+                throw new Error(data.error || 'Failed to refresh recipe cache');
+            }
+            
+            // After successful cache rebuild, load the recipes
+            await this.loadRecipes(true);
+            
+            appCore.showToast('Refresh complete', 'success');
+        } catch (error) {
+            console.error('Error refreshing recipes:', error);
+            appCore.showToast(error.message || 'Failed to refresh recipes', 'error');
+            
+            // Still try to load recipes even if scan failed
+            await this.loadRecipes(true);
+        }
+    }
+    
     async _loadSpecificRecipe(recipeId) {
         try {
             // Fetch specific recipe by ID

static/js/state/index.js

@@ -42,6 +42,7 @@ export const state = {
             bulkMode: false,
             selectedLoras: new Set(),
             loraMetadataCache: new Map(),
+            showFavoritesOnly: false,
         },
         
         recipes: {
@@ -61,7 +62,8 @@ export const state = {
                 tags: [],
                 search: ''
             },
-            pageSize: 20
+            pageSize: 20,
+            showFavoritesOnly: false,
         },
         
         checkpoints: {
@@ -80,7 +82,8 @@ export const state = {
             filters: {
                 baseModel: [],
                 tags: []
-            }
+            },
+            showFavoritesOnly: false,
         }
     },
     

static/js/utils/uiHelpers.js

@@ -114,13 +114,55 @@ export function restoreFolderFilter() {
 }
 
 export function initTheme() {
-    document.body.dataset.theme = getStorageItem('theme') || 'dark';
+    const savedTheme = getStorageItem('theme') || 'auto';
+    applyTheme(savedTheme);
+    
+    // Update theme when system preference changes (for 'auto' mode)
+    window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', () => {
+        const currentTheme = getStorageItem('theme') || 'auto';
+        if (currentTheme === 'auto') {
+            applyTheme('auto');
+        }
+    });
 }
 
 export function toggleTheme() {
-    const theme = document.body.dataset.theme === 'light' ? 'dark' : 'light';
-    document.body.dataset.theme = theme;
-    setStorageItem('theme', theme);
+    const currentTheme = getStorageItem('theme') || 'auto';
+    let newTheme;
+    
+    if (currentTheme === 'dark') {
+        newTheme = 'light';
+    } else {
+        newTheme = 'dark';
+    }
+    
+    setStorageItem('theme', newTheme);
+    applyTheme(newTheme);
+    
+    // Force a repaint to ensure theme changes are applied immediately
+    document.body.style.display = 'none';
+    document.body.offsetHeight; // Trigger a reflow
+    document.body.style.display = '';
+    
+    return newTheme;
+}
+
+// Add a new helper function to apply the theme
+function applyTheme(theme) {
+    const prefersDark = window.matchMedia('(prefers-color-scheme: dark)').matches;
+    const htmlElement = document.documentElement;
+    
+    // Remove any existing theme attributes
+    htmlElement.removeAttribute('data-theme');
+    
+    // Apply the appropriate theme
+    if (theme === 'dark' || (theme === 'auto' && prefersDark)) {
+        htmlElement.setAttribute('data-theme', 'dark');
+        document.body.dataset.theme = 'dark';
+    } else {
+        htmlElement.setAttribute('data-theme', 'light');
+        document.body.dataset.theme = 'light';
+    }
 }
 
 export function toggleFolder(tag) {
@@ -269,15 +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

@@ -6,7 +6,7 @@
     <meta name="viewport" content="width=device-width, initial-scale=1">
     <link rel="stylesheet" href="/loras_static/css/style.css">
     {% block page_css %}{% endblock %}
-    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css"
+    <link rel="stylesheet" href="/loras_static/vendor/font-awesome/css/all.min.css"
         crossorigin="anonymous" referrerpolicy="no-referrer">
     <link rel="icon" type="image/png" sizes="32x32" href="/loras_static/images/favicon-32x32.png">
     <link rel="icon" type="image/png" sizes="16x16" href="/loras_static/images/favicon-16x16.png">
@@ -17,7 +17,7 @@
     {% block preload %}{% endblock %}
 
     <!-- 优化字体加载 -->
-    <link rel="preload" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/webfonts/fa-solid-900.woff2"
+    <link rel="preload" href="/loras_static/vendor/font-awesome/webfonts/fa-solid-900.woff2"
         as="font" type="font/woff2" crossorigin>
 
     <!-- 添加性能监控 -->
@@ -35,7 +35,7 @@
 
     <!-- 添加资源加载策略 -->
     <link rel="preconnect" href="https://civitai.com">
-    <link rel="preconnect" href="https://cdnjs.cloudflare.com">
+    <!-- <link rel="preconnect" href="https://cdnjs.cloudflare.com"> -->
 
     <script>
         // 计算滚动条宽度并设置CSS变量
@@ -48,6 +48,20 @@
             document.documentElement.style.setProperty('--scrollbar-width', scrollbarWidth + 'px');
         });
     </script>
+    <script>
+      (function() {
+        // Apply theme immediately based on stored preference
+        const STORAGE_PREFIX = 'lora_manager_';
+        const savedTheme = localStorage.getItem(STORAGE_PREFIX + 'theme') || 'auto';
+        const prefersDark = window.matchMedia('(prefers-color-scheme: dark)').matches;
+        
+        if (savedTheme === 'dark' || (savedTheme === 'auto' && prefersDark)) {
+          document.documentElement.setAttribute('data-theme', 'dark');
+        } else {
+          document.documentElement.setAttribute('data-theme', 'light');
+        }
+      })();
+    </script>
     {% block head_scripts %}{% endblock %}
 </head>
 
@@ -59,8 +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/components/controls.html

@@ -35,6 +35,11 @@
                 </button>
             </div>
             {% endif %}
+            <div class="control-group">
+                <button id="favoriteFilterBtn" data-action="toggle-favorites" class="favorite-filter" title="Show favorites only">
+                    <i class="fas fa-star"></i> Favorites
+                </button>
+            </div>
             <div id="customFilterIndicator" class="control-group hidden">
                 <div class="filter-active">
                     <i class="fas fa-filter"></i> <span class="customFilterText" title=""></span>

templates/components/modals.html

@@ -125,6 +125,46 @@
                     </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>

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/recipes.html

@@ -37,7 +37,7 @@
     <div class="controls">
         <div class="action-buttons">
             <div title="Refresh recipe list" class="control-group">
-                <button onclick="recipeManager.loadRecipes(true)"><i class="fas fa-sync"></i> Refresh</button>
+                <button onclick="recipeManager.refreshRecipes()"><i class="fas fa-sync"></i> Refresh</button>
             </div>
             <div title="Import recipes" class="control-group">
                 <button onclick="importManager.showImportModal()"><i class="fas fa-file-import"></i> Import</button>

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',