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 +14,17 @@ 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
@@ -146,14 +151,21 @@ Watch this quick tutorial to learn how to use the new one-click LoRA integration
 
 ## Installation
 
-### Option 1: **ComfyUI Manager** (Recommended)
+### Option 1: **ComfyUI Manager** (Recommended for ComfyUI users)
 
 1. Open **ComfyUI**.
 2. Go to **Manager > Custom Node Manager**.
 3. Search for `lora-manager`.
 4. Click **Install**.
 
-### Option 2: **Manual Installation**
+### Option 2: **Portable Standalone Edition** (No ComfyUI required)
+
+1. Download the [Portable Package](https://github.com/willmiao/ComfyUI-Lora-Manager/releases/download/v0.8.10/lora_manager_portable.7z)
+2. Copy the provided `settings.json.example` file to create a new file named `settings.json` in `comfyui-lora-manager` folder
+3. Edit `settings.json` to include your correct model folder paths and CivitAI API key
+4. Run run.bat
+
+### Option 3: **Manual Installation**
 
 ```bash
 git clone https://github.com/willmiao/ComfyUI-Lora-Manager.git
@@ -277,4 +289,3 @@ Join our Discord community for support, discussions, and updates:
 [Discord Server](https://discord.gg/vcqNrWVFvM)
 
 ---
-````

py/lora_manager.py

@@ -6,10 +6,12 @@ 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__)
 
@@ -29,6 +31,13 @@ class LoraManager:
 
         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'
@@ -102,7 +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())

py/metadata_collector/metadata_processor.py

@@ -11,9 +11,10 @@ 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 SamplerCustomAdvanced
         prompt = metadata.get("current_prompt")
@@ -35,17 +36,17 @@ class MetadataProcessor:
                 primary_sampler_id = node_id
                 break
         
-        # If no specialized sampler 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
     
@@ -206,6 +207,17 @@ class MetadataProcessor:
                     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)
@@ -225,40 +237,6 @@ class MetadataProcessor:
                     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 = []

py/metadata_collector/node_extractors.py

@@ -327,6 +327,41 @@ class SamplerCustomAdvancedExtractor(NodeMetadataExtractor):
                         "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
@@ -343,6 +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)
@@ -515,21 +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"""
@@ -1060,4 +1044,4 @@ class ApiRoutes:
             return web.json_response({
                 "success": False,
                 "error": str(e)
-            }, status=500)
+            }, status=500)

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/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/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/recipe_parsers.py

@@ -452,7 +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"""
@@ -461,51 +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 = {}
@@ -523,7 +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,
@@ -573,6 +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):

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 = "0.8.10"
+version = "0.8.11"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

refs/test_output.txt

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

standalone.py

@@ -127,6 +127,17 @@ class StandaloneServer:
         """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"""
@@ -283,7 +294,7 @@ class StandaloneLoraManager(LoraManager):
         from py.routes.recipe_routes import RecipeRoutes
         from py.routes.checkpoints_routes import CheckpointsRoutes
         from py.routes.update_routes import UpdateRoutes
-        from py.routes.usage_stats_routes import UsageStatsRoutes
+        from py.routes.misc_routes import MiscRoutes
         
         lora_routes = LoraRoutes()
         checkpoints_routes = CheckpointsRoutes()
@@ -294,7 +305,7 @@ class StandaloneLoraManager(LoraManager):
         ApiRoutes.setup_routes(app)
         RecipeRoutes.setup_routes(app)
         UpdateRoutes.setup_routes(app)
-        UsageStatsRoutes.setup_routes(app)
+        MiscRoutes.setup_routes(app)
         
         # Schedule service initialization
         app.on_startup.append(lambda app: cls._initialize_services())
@@ -344,4 +355,4 @@ if __name__ == "__main__":
         # Run the main function
         asyncio.run(main())
     except KeyboardInterrupt:
-        logger.info("Server stopped by user")
+        logger.info("Server stopped by user")

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

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

static/css/style.css

@@ -20,6 +20,7 @@
 @import 'components/shared.css';
 @import 'components/filter-indicator.css';
 @import 'components/initialization.css';
+@import 'components/progress-panel.css';
 
 .initialization-notice {
     display: flex;

static/js/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

@@ -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/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/index.js

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

static/js/core.js

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

static/js/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/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/utils/uiHelpers.js

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

templates/base.html

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

templates/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>

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',