mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
refactor: enhance BaseModelService initialization and improve filtering logic
This commit is contained in:
Will Miao
@@ -5,98 +5,88 @@ import os
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from ..utils.models import BaseModelMetadata
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from ..utils.routes_common import ModelRouteUtils
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from ..utils.constants import NSFW_LEVELS
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from .settings_manager import settings
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from ..utils.utils import fuzzy_match
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from .model_query import FilterCriteria, ModelCacheRepository, ModelFilterSet, SearchStrategy, SettingsProvider
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from .settings_manager import settings as default_settings
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logger = logging.getLogger(__name__)
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class BaseModelService(ABC):
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"""Base service class for all model types"""
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def __init__(self, model_type: str, scanner, metadata_class: Type[BaseModelMetadata]):
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"""Initialize the service
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def __init__(
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self,
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model_type: str,
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scanner,
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metadata_class: Type[BaseModelMetadata],
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*,
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cache_repository: Optional[ModelCacheRepository] = None,
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filter_set: Optional[ModelFilterSet] = None,
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search_strategy: Optional[SearchStrategy] = None,
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settings_provider: Optional[SettingsProvider] = None,
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):
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"""Initialize the service.
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Args:
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model_type: Type of model (lora, checkpoint, etc.)
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scanner: Model scanner instance
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metadata_class: Metadata class for this model type
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model_type: Type of model (lora, checkpoint, etc.).
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scanner: Model scanner instance.
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metadata_class: Metadata class for this model type.
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cache_repository: Custom repository for cache access (primarily for tests).
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filter_set: Filter component controlling folder/tag/favorites logic.
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search_strategy: Search component for fuzzy/text matching.
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settings_provider: Settings object; defaults to the global settings manager.
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"""
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self.model_type = model_type
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self.scanner = scanner
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self.metadata_class = metadata_class
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self.settings = settings_provider or default_settings
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self.cache_repository = cache_repository or ModelCacheRepository(scanner)
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self.filter_set = filter_set or ModelFilterSet(self.settings)
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self.search_strategy = search_strategy or SearchStrategy()
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async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'name',
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folder: str = None, search: str = None, fuzzy_search: bool = False,
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base_models: list = None, tags: list = None,
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search_options: dict = None, hash_filters: dict = None,
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favorites_only: bool = False, **kwargs) -> Dict:
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"""Get paginated and filtered model data
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Args:
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page: Page number (1-based)
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page_size: Number of items per page
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sort_by: Sort criteria, e.g. 'name', 'name:asc', 'name:desc', 'date', 'date:asc', 'date:desc'
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folder: Folder filter
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search: Search term
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fuzzy_search: Whether to use fuzzy search
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base_models: List of base models to filter by
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tags: List of tags to filter by
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search_options: Search options dict
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hash_filters: Hash filtering options
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favorites_only: Filter for favorites only
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**kwargs: Additional model-specific filters
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Returns:
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Dict containing paginated results
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"""
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cache = await self.scanner.get_cached_data()
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async def get_paginated_data(
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self,
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page: int,
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page_size: int,
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sort_by: str = 'name',
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folder: str = None,
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search: str = None,
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fuzzy_search: bool = False,
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base_models: list = None,
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tags: list = None,
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search_options: dict = None,
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hash_filters: dict = None,
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favorites_only: bool = False,
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**kwargs,
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) -> Dict:
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"""Get paginated and filtered model data"""
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sort_params = self.cache_repository.parse_sort(sort_by)
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sorted_data = await self.cache_repository.fetch_sorted(sort_params)
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# Parse sort_by into sort_key and order
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if ':' in sort_by:
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sort_key, order = sort_by.split(':', 1)
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sort_key = sort_key.strip()
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order = order.strip().lower()
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if order not in ('asc', 'desc'):
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order = 'asc'
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else:
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sort_key = sort_by.strip()
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order = 'asc'
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# Get default search options if not provided
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if search_options is None:
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search_options = {
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'filename': True,
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'modelname': True,
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'tags': False,
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'recursive': True,
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}
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# Get the base data set using new sort logic
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filtered_data = await cache.get_sorted_data(sort_key, order)
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# Apply hash filtering if provided (highest priority)
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if hash_filters:
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filtered_data = await self._apply_hash_filters(filtered_data, hash_filters)
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# Jump to pagination for hash filters
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filtered_data = await self._apply_hash_filters(sorted_data, hash_filters)
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return self._paginate(filtered_data, page, page_size)
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# Apply common filters
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filtered_data = await self._apply_common_filters(
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filtered_data, folder, base_models, tags, favorites_only, search_options
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sorted_data,
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folder=folder,
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base_models=base_models,
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tags=tags,
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favorites_only=favorites_only,
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search_options=search_options,
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)
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# Apply search filtering
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if search:
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filtered_data = await self._apply_search_filters(
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filtered_data, search, fuzzy_search, search_options
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filtered_data,
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search,
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fuzzy_search,
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search_options,
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)
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# Apply model-specific filters
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filtered_data = await self._apply_specific_filters(filtered_data, **kwargs)
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return self._paginate(filtered_data, page, page_size)
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async def _apply_hash_filters(self, data: List[Dict], hash_filters: Dict) -> List[Dict]:
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"""Apply hash-based filtering"""
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@@ -120,113 +110,36 @@ class BaseModelService(ABC):
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return data
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async def _apply_common_filters(self, data: List[Dict], folder: str = None,
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base_models: list = None, tags: list = None,
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favorites_only: bool = False, search_options: dict = None) -> List[Dict]:
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async def _apply_common_filters(
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self,
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data: List[Dict],
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folder: str = None,
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base_models: list = None,
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tags: list = None,
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favorites_only: bool = False,
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search_options: dict = None,
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) -> List[Dict]:
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"""Apply common filters that work across all model types"""
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# Apply SFW filtering if enabled in settings
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if settings.get('show_only_sfw', False):
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data = [
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item for item in data
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if not item.get('preview_nsfw_level') or item.get('preview_nsfw_level') < NSFW_LEVELS['R']
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]
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# Apply favorites filtering if enabled
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if favorites_only:
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data = [
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item for item in data
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if item.get('favorite', False) is True
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]
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# Apply folder filtering
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if folder is not None:
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if search_options and search_options.get('recursive', True):
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# Recursive folder filtering - include all subfolders
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# Ensure we match exact folder or its subfolders by checking path boundaries
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if folder == "":
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# Empty folder means root - include all items
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pass # Don't filter anything
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else:
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# Add trailing slash to ensure we match folder boundaries correctly
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folder_with_separator = folder + "/"
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data = [
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item for item in data
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if (item['folder'] == folder or
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item['folder'].startswith(folder_with_separator))
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]
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else:
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# Exact folder filtering
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data = [
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item for item in data
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if item['folder'] == folder
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]
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# Apply base model filtering
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if base_models and len(base_models) > 0:
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data = [
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item for item in data
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if item.get('base_model') in base_models
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]
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# Apply tag filtering
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if tags and len(tags) > 0:
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data = [
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item for item in data
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if any(tag in item.get('tags', []) for tag in tags)
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]
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return data
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normalized_options = self.search_strategy.normalize_options(search_options)
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criteria = FilterCriteria(
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folder=folder,
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base_models=base_models,
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tags=tags,
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favorites_only=favorites_only,
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search_options=normalized_options,
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)
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return self.filter_set.apply(data, criteria)
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async def _apply_search_filters(self, data: List[Dict], search: str,
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fuzzy_search: bool, search_options: dict) -> List[Dict]:
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async def _apply_search_filters(
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self,
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data: List[Dict],
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search: str,
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fuzzy_search: bool,
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search_options: dict,
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) -> List[Dict]:
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"""Apply search filtering"""
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search_results = []
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for item in data:
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# Search by file name
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if search_options.get('filename', True):
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if fuzzy_search:
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if fuzzy_match(item.get('file_name', ''), search):
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search_results.append(item)
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continue
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elif search.lower() in item.get('file_name', '').lower():
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search_results.append(item)
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continue
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# Search by model name
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if search_options.get('modelname', True):
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if fuzzy_search:
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if fuzzy_match(item.get('model_name', ''), search):
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search_results.append(item)
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continue
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elif search.lower() in item.get('model_name', '').lower():
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search_results.append(item)
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continue
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# Search by tags
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if search_options.get('tags', False) and 'tags' in item:
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if any((fuzzy_match(tag, search) if fuzzy_search else search.lower() in tag.lower())
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for tag in item['tags']):
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search_results.append(item)
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continue
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# Search by creator
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civitai = item.get('civitai')
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creator_username = ''
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if civitai and isinstance(civitai, dict):
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creator = civitai.get('creator')
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if creator and isinstance(creator, dict):
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creator_username = creator.get('username', '')
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if search_options.get('creator', False) and creator_username:
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if fuzzy_search:
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if fuzzy_match(creator_username, search):
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search_results.append(item)
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continue
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elif search.lower() in creator_username.lower():
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search_results.append(item)
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continue
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return search_results
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normalized_options = self.search_strategy.normalize_options(search_options)
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return self.search_strategy.apply(data, search, normalized_options, fuzzy_search)
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async def _apply_specific_filters(self, data: List[Dict], **kwargs) -> List[Dict]:
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"""Apply model-specific filters - to be overridden by subclasses if needed"""
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196
py/services/model_query.py
Normal file
196
py/services/model_query.py
Normal file
@@ -0,0 +1,196 @@
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any, Dict, Iterable, List, Optional, Sequence, Tuple, Protocol, Callable
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from ..utils.constants import NSFW_LEVELS
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from ..utils.utils import fuzzy_match as default_fuzzy_match
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class SettingsProvider(Protocol):
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"""Protocol describing the SettingsManager contract used by query helpers."""
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def get(self, key: str, default: Any = None) -> Any:
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...
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@dataclass(frozen=True)
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class SortParams:
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"""Normalized representation of sorting instructions."""
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key: str
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order: str
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@dataclass(frozen=True)
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class FilterCriteria:
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"""Container for model list filtering options."""
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folder: Optional[str] = None
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base_models: Optional[Sequence[str]] = None
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tags: Optional[Sequence[str]] = None
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favorites_only: bool = False
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search_options: Optional[Dict[str, Any]] = None
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class ModelCacheRepository:
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"""Adapter around scanner cache access and sort normalisation."""
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def __init__(self, scanner) -> None:
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self._scanner = scanner
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async def get_cache(self):
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"""Return the underlying cache instance from the scanner."""
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return await self._scanner.get_cached_data()
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async def fetch_sorted(self, params: SortParams) -> List[Dict[str, Any]]:
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"""Fetch cached data pre-sorted according to ``params``."""
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cache = await self.get_cache()
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return await cache.get_sorted_data(params.key, params.order)
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@staticmethod
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def parse_sort(sort_by: str) -> SortParams:
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"""Parse an incoming sort string into key/order primitives."""
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if not sort_by:
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return SortParams(key="name", order="asc")
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if ":" in sort_by:
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raw_key, raw_order = sort_by.split(":", 1)
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sort_key = raw_key.strip().lower() or "name"
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order = raw_order.strip().lower()
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else:
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sort_key = sort_by.strip().lower() or "name"
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order = "asc"
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if order not in ("asc", "desc"):
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order = "asc"
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return SortParams(key=sort_key, order=order)
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class ModelFilterSet:
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"""Applies common filtering rules to the model collection."""
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def __init__(self, settings: SettingsProvider, nsfw_levels: Optional[Dict[str, int]] = None) -> None:
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self._settings = settings
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self._nsfw_levels = nsfw_levels or NSFW_LEVELS
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def apply(self, data: Iterable[Dict[str, Any]], criteria: FilterCriteria) -> List[Dict[str, Any]]:
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"""Return items that satisfy the provided criteria."""
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items = list(data)
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if self._settings.get("show_only_sfw", False):
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threshold = self._nsfw_levels.get("R", 0)
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items = [
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item for item in items
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if not item.get("preview_nsfw_level") or item.get("preview_nsfw_level") < threshold
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]
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if criteria.favorites_only:
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items = [item for item in items if item.get("favorite", False)]
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folder = criteria.folder
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options = criteria.search_options or {}
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recursive = bool(options.get("recursive", True))
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if folder is not None:
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if recursive:
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if folder:
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folder_with_sep = f"{folder}/"
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items = [
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item for item in items
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if item.get("folder") == folder or item.get("folder", "").startswith(folder_with_sep)
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]
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else:
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items = [item for item in items if item.get("folder") == folder]
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base_models = criteria.base_models or []
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if base_models:
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base_model_set = set(base_models)
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items = [item for item in items if item.get("base_model") in base_model_set]
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tags = criteria.tags or []
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if tags:
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tag_set = set(tags)
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items = [
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item for item in items
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if any(tag in tag_set for tag in item.get("tags", []))
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]
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return items
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class SearchStrategy:
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"""Encapsulates text and fuzzy matching behaviour for model queries."""
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DEFAULT_OPTIONS: Dict[str, Any] = {
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"filename": True,
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"modelname": True,
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"tags": False,
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"recursive": True,
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"creator": False,
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}
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def __init__(self, fuzzy_matcher: Optional[Callable[[str, str], bool]] = None) -> None:
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self._fuzzy_match = fuzzy_matcher or default_fuzzy_match
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def normalize_options(self, options: Optional[Dict[str, Any]]) -> Dict[str, Any]:
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"""Merge provided options with defaults without mutating input."""
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normalized = dict(self.DEFAULT_OPTIONS)
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if options:
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normalized.update(options)
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return normalized
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def apply(
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self,
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data: Iterable[Dict[str, Any]],
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search_term: str,
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options: Dict[str, Any],
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fuzzy: bool = False,
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) -> List[Dict[str, Any]]:
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"""Return items matching the search term using the configured strategy."""
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if not search_term:
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return list(data)
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search_lower = search_term.lower()
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results: List[Dict[str, Any]] = []
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for item in data:
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if options.get("filename", True):
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candidate = item.get("file_name", "")
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if self._matches(candidate, search_term, search_lower, fuzzy):
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results.append(item)
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continue
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if options.get("modelname", True):
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candidate = item.get("model_name", "")
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if self._matches(candidate, search_term, search_lower, fuzzy):
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results.append(item)
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continue
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if options.get("tags", False):
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tags = item.get("tags", []) or []
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if any(self._matches(tag, search_term, search_lower, fuzzy) for tag in tags):
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results.append(item)
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continue
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if options.get("creator", False):
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creator_username = ""
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civitai = item.get("civitai")
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if isinstance(civitai, dict):
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creator = civitai.get("creator")
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if isinstance(creator, dict):
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creator_username = creator.get("username", "")
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if creator_username and self._matches(creator_username, search_term, search_lower, fuzzy):
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results.append(item)
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continue
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return results
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|
||||
def _matches(self, candidate: str, search_term: str, search_lower: str, fuzzy: bool) -> bool:
|
||||
if not candidate:
|
||||
return False
|
||||
|
||||
candidate_lower = candidate.lower()
|
||||
if fuzzy:
|
||||
return self._fuzzy_match(candidate, search_term)
|
||||
return search_lower in candidate_lower
|
||||
Reference in New Issue
Block a user