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.

py/routes/api_routes.py

@@ -131,7 +131,6 @@ class ApiRoutes:
             folder = request.query.get('folder')
             search = request.query.get('search', '').lower()
             fuzzy = request.query.get('fuzzy', 'false').lower() == 'true'
-            recursive = request.query.get('recursive', 'false').lower() == 'true'
             
             # Parse base models filter parameter
             base_models = request.query.get('base_models', '').split(',')
@@ -141,6 +140,7 @@ class ApiRoutes:
             search_filename = request.query.get('search_filename', 'true').lower() == 'true'
             search_modelname = request.query.get('search_modelname', 'true').lower() == 'true'
             search_tags = request.query.get('search_tags', 'false').lower() == 'true'
+            recursive = request.query.get('recursive', 'false').lower() == 'true'
             
             # Validate parameters
             if page < 1 or page_size < 1 or page_size > 100:
@@ -165,13 +165,13 @@ class ApiRoutes:
                 folder=folder,
                 search=search,
                 fuzzy=fuzzy,
-                recursive=recursive,
                 base_models=base_models,  # Pass base models filter
                 tags=tags,  # Add tags parameter
                 search_options={
                     'filename': search_filename,
                     'modelname': search_modelname,
-                    'tags': search_tags
+                    'tags': search_tags,
+                    'recursive': recursive
                 }
             )
             

py/routes/recipe_routes.py

@@ -68,7 +68,6 @@ class RecipeRoutes:
     async def get_recipes(self, request: web.Request) -> web.Response:
         """API endpoint for getting paginated recipes"""
         try:
-            logger.info(f"get_recipes, Request: {request}")
             # Get query parameters with defaults
             page = int(request.query.get('page', '1'))
             page_size = int(request.query.get('page_size', '20'))
@@ -100,7 +99,6 @@ class RecipeRoutes:
                 'lora_model': search_lora_model
             }
 
-            logger.info(f"get_recipes, Filters: {filters}, Search Options: {search_options}")
             # Get paginated data
             result = await self.recipe_scanner.get_paginated_data(
                 page=page,

py/services/lora_scanner.py

@@ -9,10 +9,10 @@ from operator import itemgetter
 from ..config import config
 from ..utils.file_utils import load_metadata, get_file_info
 from .lora_cache import LoraCache
-from difflib import SequenceMatcher
 from .lora_hash_index import LoraHashIndex
 from .settings_manager import settings
 from ..utils.constants import NSFW_LEVELS
+from ..utils.utils import fuzzy_match
 import sys
 
 logger = logging.getLogger(__name__)
@@ -132,45 +132,9 @@ class LoraScanner:
                 folders=[]
             )
 
-    def fuzzy_match(self, text: str, pattern: str, threshold: float = 0.7) -> bool:
-        """
-        Check if text matches pattern using fuzzy matching.
-        Returns True if similarity ratio is above threshold.
-        """
-        if not pattern or not text:
-            return False
-        
-        # Convert both to lowercase for case-insensitive matching
-        text = text.lower()
-        pattern = pattern.lower()
-        
-        # Split pattern into words
-        search_words = pattern.split()
-        
-        # Check each word
-        for word in search_words:
-            # First check if word is a substring (faster)
-            if word in text:
-                continue
-            
-            # If not found as substring, try fuzzy matching
-            # Check if any part of the text matches this word
-            found_match = False
-            for text_part in text.split():
-                ratio = SequenceMatcher(None, text_part, word).ratio()
-                if ratio >= threshold:
-                    found_match = True
-                    break
-                
-            if not found_match:
-                return False
-        
-        # All words found either as substrings or fuzzy matches
-        return True
-
     async def get_paginated_data(self, page: int, page_size: int, sort_by: str = 'name', 
                                folder: str = None, search: str = None, fuzzy: bool = False,
-                               recursive: bool = False, base_models: list = None, tags: list = None,
+                               base_models: list = None, tags: list = None,
                                search_options: dict = None) -> Dict:
         """Get paginated and filtered lora data
         
@@ -181,10 +145,9 @@ class LoraScanner:
             folder: Filter by folder path
             search: Search term
             fuzzy: Use fuzzy matching for search
-            recursive: Include subfolders when folder filter is applied
             base_models: List of base models to filter by
             tags: List of tags to filter by
-            search_options: Dictionary with search options (filename, modelname, tags)
+            search_options: Dictionary with search options (filename, modelname, tags, recursive)
         """
         cache = await self.get_cached_data()
 
@@ -193,7 +156,8 @@ class LoraScanner:
             search_options = {
                 'filename': True,
                 'modelname': True,
-                'tags': False
+                'tags': False,
+                'recursive': False
             }
 
         # Get the base data set
@@ -208,7 +172,7 @@ class LoraScanner:
         
         # Apply folder filtering
         if folder is not None:
-            if recursive:
+            if search_options.get('recursive', False):
                 # Recursive mode: match all paths starting with this folder
                 filtered_data = [
                     item for item in filtered_data 
@@ -237,16 +201,47 @@ class LoraScanner:
         
         # Apply search filtering
         if search:
-            if fuzzy:
+            search_results = []
-                filtered_data = [
+            for item in filtered_data:
-                    item for item in filtered_data 
+                # Check filename if enabled
-                    if self._fuzzy_search_match(item, search, search_options)
+                if search_options.get('filename', True):
-                ]
+                    if fuzzy:
-            else:
+                        if fuzzy_match(item.get('file_name', ''), search):
-                filtered_data = [
+                            search_results.append(item)
-                    item for item in filtered_data 
+                            continue
-                    if self._exact_search_match(item, search, search_options)
+                    else:
-                ]
+                        if search.lower() in item.get('file_name', '').lower():
+                            search_results.append(item)
+                            continue
+                            
+                # Check model name if enabled
+                if search_options.get('modelname', True):
+                    if fuzzy:
+                        if fuzzy_match(item.get('model_name', ''), search):
+                            search_results.append(item)
+                            continue
+                    else:
+                        if search.lower() in item.get('model_name', '').lower():
+                            search_results.append(item)
+                            continue
+                            
+                # Check tags if enabled
+                if search_options.get('tags', False) and item.get('tags'):
+                    found_tag = False
+                    for tag in item['tags']:
+                        if fuzzy:
+                            if fuzzy_match(tag, search):
+                                found_tag = True
+                                break
+                        else:
+                            if search.lower() in tag.lower():
+                                found_tag = True
+                                break
+                    if found_tag:
+                        search_results.append(item)
+                        continue
+                        
+            filtered_data = search_results
 
         # Calculate pagination
         total_items = len(filtered_data)
@@ -263,44 +258,6 @@ class LoraScanner:
         
         return result
 
-    def _fuzzy_search_match(self, item: Dict, search: str, search_options: Dict) -> bool:
-        """Check if an item matches the search term using fuzzy matching with search options"""
-        # Check filename if enabled
-        if search_options.get('filename', True) and self.fuzzy_match(item.get('file_name', ''), search):
-            return True
-            
-        # Check model name if enabled
-        if search_options.get('modelname', True) and self.fuzzy_match(item.get('model_name', ''), search):
-            return True
-            
-        # Check tags if enabled
-        if search_options.get('tags', False) and item.get('tags'):
-            for tag in item['tags']:
-                if self.fuzzy_match(tag, search):
-                    return True
-                    
-        return False
-
-    def _exact_search_match(self, item: Dict, search: str, search_options: Dict) -> bool:
-        """Check if an item matches the search term using exact matching with search options"""
-        search = search.lower()
-        
-        # Check filename if enabled
-        if search_options.get('filename', True) and search in item.get('file_name', '').lower():
-            return True
-            
-        # Check model name if enabled
-        if search_options.get('modelname', True) and search in item.get('model_name', '').lower():
-            return True
-            
-        # Check tags if enabled
-        if search_options.get('tags', False) and item.get('tags'):
-            for tag in item['tags']:
-                if search in tag.lower():
-                    return True
-                    
-        return False
-
     def invalidate_cache(self):
         """Invalidate the current cache"""
         self._cache = None

py/services/recipe_scanner.py

@@ -9,6 +9,7 @@ from ..config import config
 from .recipe_cache import RecipeCache
 from .lora_scanner import LoraScanner
 from .civitai_client import CivitaiClient
+from ..utils.utils import fuzzy_match
 import sys
 
 logger = logging.getLogger(__name__)
@@ -378,25 +379,26 @@ class RecipeScanner:
             # Build the search predicate based on search options
             def matches_search(item):
                 # Search in title if enabled
-                if search_options.get('title', True) and search.lower() in str(item.get('title', '')).lower():
+                if search_options.get('title', True):
-                    return True
+                    if fuzzy_match(str(item.get('title', '')), search):
+                        return True
                 
                 # Search in tags if enabled
                 if search_options.get('tags', True) and 'tags' in item:
                     for tag in item['tags']:
-                        if search.lower() in tag.lower():
+                        if fuzzy_match(tag, search):
                             return True
                 
                 # Search in lora file names if enabled
                 if search_options.get('lora_name', True) and 'loras' in item:
                     for lora in item['loras']:
-                        if search.lower() in str(lora.get('file_name', '')).lower():
+                        if fuzzy_match(str(lora.get('file_name', '')), search):
                             return True
                 
                 # Search in lora model names if enabled
                 if search_options.get('lora_model', True) and 'loras' in item:
                     for lora in item['loras']:
-                        if search.lower() in str(lora.get('modelName', '')).lower():
+                        if fuzzy_match(str(lora.get('modelName', '')), search):
                             return True
                 
                 # No match found

py/utils/utils.py

@@ -1,3 +1,4 @@
+from difflib import SequenceMatcher
 import requests
 import tempfile
 import re
@@ -39,3 +40,39 @@ def download_twitter_image(url):
     except Exception as e:
         print(f"Error downloading twitter image: {e}")
         return None
+    
+def fuzzy_match(text: str, pattern: str, threshold: float = 0.7) -> bool:
+        """
+        Check if text matches pattern using fuzzy matching.
+        Returns True if similarity ratio is above threshold.
+        """
+        if not pattern or not text:
+            return False
+        
+        # Convert both to lowercase for case-insensitive matching
+        text = text.lower()
+        pattern = pattern.lower()
+        
+        # Split pattern into words
+        search_words = pattern.split()
+        
+        # Check each word
+        for word in search_words:
+            # First check if word is a substring (faster)
+            if word in text:
+                continue
+            
+            # If not found as substring, try fuzzy matching
+            # Check if any part of the text matches this word
+            found_match = False
+            for text_part in text.split():
+                ratio = SequenceMatcher(None, text_part, word).ratio()
+                if ratio >= threshold:
+                    found_match = True
+                    break
+                
+            if not found_match:
+                return False
+        
+        # All words found either as substrings or fuzzy matches
+        return True

static/js/api/loraApi.js

@@ -18,6 +18,7 @@ export async function loadMoreLoras(resetPage = false, updateFolders = false) {
             // Clear grid if resetting
             const grid = document.getElementById('loraGrid');
             if (grid) grid.innerHTML = '';
+            initializeInfiniteScroll();
         }
         
         const params = new URLSearchParams({
@@ -26,12 +27,8 @@ export async function loadMoreLoras(resetPage = false, updateFolders = false) {
             sort_by: pageState.sortBy
         });
         
-        // Use pageState instead of state
-        const isRecursiveSearch = pageState.searchOptions?.recursive ?? false;
-        
         if (pageState.activeFolder !== null) {
             params.append('folder', pageState.activeFolder);
-            params.append('recursive', isRecursiveSearch.toString());
         }
 
         // Add search parameters if there's a search term
@@ -44,6 +41,7 @@ export async function loadMoreLoras(resetPage = false, updateFolders = false) {
                 params.append('search_filename', pageState.searchOptions.filename.toString());
                 params.append('search_modelname', pageState.searchOptions.modelname.toString());
                 params.append('search_tags', (pageState.searchOptions.tags || false).toString());
+                params.append('recursive', (pageState.searchOptions?.recursive ?? false).toString());
             }
         }
         

static/js/recipes.js

@@ -131,8 +131,8 @@ class RecipeManager {
             // Update recipes grid
             this.updateRecipesGrid(data, resetPage);
             
-            // Update pagination state
+            // Update pagination state based on current page and total pages
-            this.pageState.hasMore = data.has_more || false;
+            this.pageState.hasMore = data.page < data.total_pages;
             
         } catch (error) {
             console.error('Error loading recipes:', error);