mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
feat: Add Lora recipes retrieval and filtering functionality
- Implemented a new API endpoint to fetch recipes associated with a specific Lora by its hash. - Enhanced the recipe scanning logic to support filtering by Lora hash and bypassing other filters. - Added a new method to retrieve a recipe by its ID with formatted metadata. - Created a new RecipeTab component to display recipes in the Lora modal. - Introduced session storage utilities for managing custom filter states. - Updated the UI to include a custom filter indicator and loading/error states for recipes. - Refactored existing recipe management logic to accommodate new features and improve maintainability.
This commit is contained in:
Will Miao
@@ -330,7 +330,7 @@ class RecipeScanner:
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logger.error(f"Error getting base model for lora: {e}")
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return None
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async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'date', search: str = None, filters: dict = None, search_options: dict = None):
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async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'date', search: str = None, filters: dict = None, search_options: dict = None, lora_hash: str = None, bypass_filters: bool = False):
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"""Get paginated and filtered recipe data
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Args:
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@@ -340,69 +340,89 @@ class RecipeScanner:
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search: Search term
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filters: Dictionary of filters to apply
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search_options: Dictionary of search options to apply
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lora_hash: Optional SHA256 hash of a LoRA to filter recipes by
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bypass_filters: If True, ignore other filters when a lora_hash is provided
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"""
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cache = await self.get_cached_data()
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# Get base dataset
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filtered_data = cache.sorted_by_date if sort_by == 'date' else cache.sorted_by_name
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# Apply search filter
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if search:
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# Default search options if none provided
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if not search_options:
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search_options = {
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'title': True,
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'tags': True,
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'lora_name': True,
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'lora_model': True
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}
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# Special case: Filter by LoRA hash (takes precedence if bypass_filters is True)
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if lora_hash:
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# Filter recipes that contain this LoRA hash
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filtered_data = [
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item for item in filtered_data
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if 'loras' in item and any(
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lora.get('hash', '').lower() == lora_hash.lower()
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for lora in item['loras']
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)
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]
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# Build the search predicate based on search options
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def matches_search(item):
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# Search in title if enabled
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if search_options.get('title', True):
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if fuzzy_match(str(item.get('title', '')), search):
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return True
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# Search in tags if enabled
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if search_options.get('tags', True) and 'tags' in item:
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for tag in item['tags']:
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if fuzzy_match(tag, search):
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return True
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# Search in lora file names if enabled
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if search_options.get('lora_name', True) and 'loras' in item:
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for lora in item['loras']:
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if fuzzy_match(str(lora.get('file_name', '')), search):
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return True
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# Search in lora model names if enabled
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if search_options.get('lora_model', True) and 'loras' in item:
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for lora in item['loras']:
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if fuzzy_match(str(lora.get('modelName', '')), search):
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return True
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# No match found
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return False
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# Filter the data using the search predicate
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filtered_data = [item for item in filtered_data if matches_search(item)]
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if bypass_filters:
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# Skip other filters if bypass_filters is True
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pass
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# Otherwise continue with normal filtering after applying LoRA hash filter
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# Apply additional filters
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if filters:
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# Filter by base model
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if 'base_model' in filters and filters['base_model']:
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filtered_data = [
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item for item in filtered_data
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if item.get('base_model', '') in filters['base_model']
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]
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# Skip further filtering if we're only filtering by LoRA hash with bypass enabled
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if not (lora_hash and bypass_filters):
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# Apply search filter
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if search:
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# Default search options if none provided
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if not search_options:
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search_options = {
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'title': True,
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'tags': True,
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'lora_name': True,
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'lora_model': True
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}
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# Build the search predicate based on search options
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def matches_search(item):
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# Search in title if enabled
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if search_options.get('title', True):
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if fuzzy_match(str(item.get('title', '')), search):
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return True
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# Search in tags if enabled
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if search_options.get('tags', True) and 'tags' in item:
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for tag in item['tags']:
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if fuzzy_match(tag, search):
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return True
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# Search in lora file names if enabled
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if search_options.get('lora_name', True) and 'loras' in item:
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for lora in item['loras']:
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if fuzzy_match(str(lora.get('file_name', '')), search):
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return True
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# Search in lora model names if enabled
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if search_options.get('lora_model', True) and 'loras' in item:
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for lora in item['loras']:
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if fuzzy_match(str(lora.get('modelName', '')), search):
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return True
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# No match found
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return False
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# Filter the data using the search predicate
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filtered_data = [item for item in filtered_data if matches_search(item)]
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# Filter by tags
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if 'tags' in filters and filters['tags']:
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filtered_data = [
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item for item in filtered_data
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if any(tag in item.get('tags', []) for tag in filters['tags'])
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]
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# Apply additional filters
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if filters:
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# Filter by base model
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if 'base_model' in filters and filters['base_model']:
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filtered_data = [
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item for item in filtered_data
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if item.get('base_model', '') in filters['base_model']
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]
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# Filter by tags
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if 'tags' in filters and filters['tags']:
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filtered_data = [
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item for item in filtered_data
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if any(tag in item.get('tags', []) for tag in filters['tags'])
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]
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# Calculate pagination
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total_items = len(filtered_data)
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@@ -430,6 +450,74 @@ class RecipeScanner:
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}
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return result
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async def get_recipe_by_id(self, recipe_id: str) -> dict:
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"""Get a single recipe by ID with all metadata and formatted URLs
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Args:
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recipe_id: The ID of the recipe to retrieve
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Returns:
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Dict containing the recipe data or None if not found
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"""
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if not recipe_id:
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return None
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# Get all recipes from cache
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cache = await self.get_cached_data()
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# Find the recipe with the specified ID
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recipe = next((r for r in cache.raw_data if str(r.get('id', '')) == recipe_id), None)
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if not recipe:
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return None
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# Format the recipe with all needed information
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formatted_recipe = {**recipe} # Copy all fields
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# Format file path to URL
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if 'file_path' in formatted_recipe:
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formatted_recipe['file_url'] = self._format_file_url(formatted_recipe['file_path'])
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# Format dates for display
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for date_field in ['created_date', 'modified']:
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if date_field in formatted_recipe:
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formatted_recipe[f"{date_field}_formatted"] = self._format_timestamp(formatted_recipe[date_field])
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# Add lora metadata
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if 'loras' in formatted_recipe:
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for lora in formatted_recipe['loras']:
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if 'hash' in lora and lora['hash']:
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lora_hash = lora['hash'].lower()
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lora['inLibrary'] = self._lora_scanner.has_lora_hash(lora_hash)
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lora['preview_url'] = self._lora_scanner.get_preview_url_by_hash(lora_hash)
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lora['localPath'] = self._lora_scanner.get_lora_path_by_hash(lora_hash)
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return formatted_recipe
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def _format_file_url(self, file_path: str) -> str:
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"""Format file path as URL for serving in web UI"""
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if not file_path:
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return '/loras_static/images/no-preview.png'
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try:
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# Format file path as a URL that will work with static file serving
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recipes_dir = os.path.join(config.loras_roots[0], "recipes").replace(os.sep, '/')
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if file_path.replace(os.sep, '/').startswith(recipes_dir):
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relative_path = os.path.relpath(file_path, config.loras_roots[0]).replace(os.sep, '/')
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return f"/loras_static/root1/preview/{relative_path}"
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# If not in recipes dir, try to create a valid URL from the file name
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file_name = os.path.basename(file_path)
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return f"/loras_static/root1/preview/recipes/{file_name}"
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except Exception as e:
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logger.error(f"Error formatting file URL: {e}")
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return '/loras_static/images/no-preview.png'
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def _format_timestamp(self, timestamp: float) -> str:
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"""Format timestamp for display"""
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from datetime import datetime
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return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
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async def update_recipe_metadata(self, recipe_id: str, metadata: dict) -> bool:
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"""Update recipe metadata (like title and tags) in both file system and cache
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