mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
Refactor search functionality in Lora and Recipe scanners to utilize fuzzy matching
- Introduced a new fuzzy_match utility function for improved search accuracy across Lora and Recipe scanners. - Updated search logic in LoraScanner and RecipeScanner to leverage fuzzy matching for titles, tags, and filenames, enhancing user experience. - Removed deprecated search methods to streamline the codebase and improve maintainability. - Adjusted API routes to ensure compatibility with the new search options, including recursive search handling.
This commit is contained in:
Will Miao
@@ -9,10 +9,10 @@ from operator import itemgetter
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from ..config import config
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from ..utils.file_utils import load_metadata, get_file_info
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from .lora_cache import LoraCache
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from difflib import SequenceMatcher
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from .lora_hash_index import LoraHashIndex
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from .settings_manager import settings
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from ..utils.constants import NSFW_LEVELS
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from ..utils.utils import fuzzy_match
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import sys
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logger = logging.getLogger(__name__)
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@@ -132,45 +132,9 @@ class LoraScanner:
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folders=[]
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)
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def fuzzy_match(self, text: str, pattern: str, threshold: float = 0.7) -> bool:
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"""
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Check if text matches pattern using fuzzy matching.
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Returns True if similarity ratio is above threshold.
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"""
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if not pattern or not text:
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return False
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# Convert both to lowercase for case-insensitive matching
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text = text.lower()
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pattern = pattern.lower()
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# Split pattern into words
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search_words = pattern.split()
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# Check each word
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for word in search_words:
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# First check if word is a substring (faster)
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if word in text:
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continue
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# If not found as substring, try fuzzy matching
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# Check if any part of the text matches this word
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found_match = False
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for text_part in text.split():
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ratio = SequenceMatcher(None, text_part, word).ratio()
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if ratio >= threshold:
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found_match = True
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break
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if not found_match:
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return False
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# All words found either as substrings or fuzzy matches
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return True
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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: bool = False,
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recursive: bool = False, base_models: list = None, tags: list = None,
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base_models: list = None, tags: list = None,
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search_options: dict = None) -> Dict:
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"""Get paginated and filtered lora data
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@@ -181,10 +145,9 @@ class LoraScanner:
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folder: Filter by folder path
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search: Search term
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fuzzy: Use fuzzy matching for search
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recursive: Include subfolders when folder filter is applied
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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: Dictionary with search options (filename, modelname, tags)
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search_options: Dictionary with search options (filename, modelname, tags, recursive)
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"""
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cache = await self.get_cached_data()
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@@ -193,7 +156,8 @@ class LoraScanner:
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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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'tags': False,
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'recursive': False
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}
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# Get the base data set
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@@ -208,7 +172,7 @@ class LoraScanner:
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# Apply folder filtering
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if folder is not None:
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if recursive:
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if search_options.get('recursive', False):
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# Recursive mode: match all paths starting with this folder
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filtered_data = [
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item for item in filtered_data
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@@ -237,16 +201,47 @@ class LoraScanner:
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# Apply search filtering
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if search:
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if fuzzy:
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filtered_data = [
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item for item in filtered_data
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if self._fuzzy_search_match(item, search, search_options)
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]
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else:
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filtered_data = [
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item for item in filtered_data
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if self._exact_search_match(item, search, search_options)
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]
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search_results = []
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for item in filtered_data:
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# Check filename if enabled
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if search_options.get('filename', True):
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if fuzzy:
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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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else:
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if 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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# Check model name if enabled
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if search_options.get('modelname', True):
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if fuzzy:
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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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else:
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if 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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# Check tags if enabled
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if search_options.get('tags', False) and item.get('tags'):
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found_tag = False
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for tag in item['tags']:
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if fuzzy:
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if fuzzy_match(tag, search):
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found_tag = True
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break
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else:
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if search.lower() in tag.lower():
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found_tag = True
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break
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if found_tag:
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search_results.append(item)
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continue
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filtered_data = search_results
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# Calculate pagination
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total_items = len(filtered_data)
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@@ -263,44 +258,6 @@ class LoraScanner:
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return result
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def _fuzzy_search_match(self, item: Dict, search: str, search_options: Dict) -> bool:
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"""Check if an item matches the search term using fuzzy matching with search options"""
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# Check filename if enabled
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if search_options.get('filename', True) and self.fuzzy_match(item.get('file_name', ''), search):
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return True
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# Check model name if enabled
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if search_options.get('modelname', True) and self.fuzzy_match(item.get('model_name', ''), search):
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return True
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# Check tags if enabled
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if search_options.get('tags', False) and item.get('tags'):
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for tag in item['tags']:
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if self.fuzzy_match(tag, search):
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return True
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return False
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def _exact_search_match(self, item: Dict, search: str, search_options: Dict) -> bool:
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"""Check if an item matches the search term using exact matching with search options"""
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search = search.lower()
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# Check filename if enabled
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if search_options.get('filename', True) and search in item.get('file_name', '').lower():
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return True
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# Check model name if enabled
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if search_options.get('modelname', True) and search in item.get('model_name', '').lower():
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return True
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# Check tags if enabled
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if search_options.get('tags', False) and item.get('tags'):
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for tag in item['tags']:
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if search in tag.lower():
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return True
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return False
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def invalidate_cache(self):
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"""Invalidate the current cache"""
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self._cache = None
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