diff --git a/src/load_lora_from_folder.py b/src/load_lora_from_folder.py
index 674e7cb..443f548 100644
--- a/src/load_lora_from_folder.py
+++ b/src/load_lora_from_folder.py
@@ -2,7 +2,7 @@ import os
 import re
 import folder_paths
 from nodes import LoraLoader
-from .sn0w import Logger, Utility
+from .sn0w import Logger, Utility, ConfigReader
 
 class LoadLoraFolderNode:
     logger = Logger()
@@ -57,51 +57,60 @@ class LoadLoraFolderNode:
         return master_folder, include_folders, exclude_folders
 
     def find_and_apply_lora(self, model, clip, prompt, folders, xl, lora_strength, separator):
+        # Set default prompt if None provided
         if prompt is None:
             prompt = ''
+        # Clean and split the prompt into parts
         prompt_parts = [self.clean_string(part) for part in prompt.split(separator)]
 
-        # Retrieve paths and apply folder constraints
+        # Retrieve and filter Lora file paths
         full_lora_paths = folder_paths.get_filename_list("loras")
         filtered_lora_paths = folder_paths.get_filename_list("loras_xl" if xl else "loras_15")
         master_folder, include_folders, exclude_folders = self.parse_folders(folders)
 
-        # Filter by master folder if specified
+        # Include only paths in the master folder, if specified
         if master_folder:
             filtered_lora_paths = [path for path in filtered_lora_paths if master_folder in self.normalize_folder_name(path)]
 
-        # Filter by included and excluded folders
+        # Further filter paths to include and exclude specific folders
         lora_paths = [path for path in filtered_lora_paths if any(folder in self.normalize_folder_name(path) for folder in include_folders)]
         lora_paths = [path for path in lora_paths if not any(exclude in self.normalize_folder_name(path) for exclude in exclude_folders)]
 
         lora_candidates = {}
         loaded_loras = set()
 
+        max_distance = ConfigReader.get_setting('sn0w.LoraFolderMinDistance', 5)
+
+        # Match prompt parts with Lora filenames
         for prompt_part in prompt_parts:
             for lora_path in lora_paths:
                 lora_filename = os.path.split(lora_path)[-1].lower()
+                # Clean up the filename for matching
                 processed_lora_filename = lora_filename.replace(".safetensors", "").replace("_", " ")
 
+                # Check if prompt part matches the cleaned filename
                 if prompt_part in processed_lora_filename:
                     distance = Utility.levenshtein_distance(prompt_part, processed_lora_filename)
+                    # Store matching Loras if within acceptable distance
                     for full_path in full_lora_paths:
-                        if lora_filename in full_path.lower():
-                            if distance <= 5:
-                                if prompt_part not in lora_candidates:
-                                    lora_candidates[prompt_part] = []
-                                lora_candidates[prompt_part].append({'full_path': full_path, 'distance': distance})
-                                self.logger.log("Distance: " + str(distance) + " Lora: " + lora_filename + " Tag: " + prompt_part, "ALL")
-                                break
+                        if lora_filename in full_path.lower() and distance <= max_distance:
+                            if prompt_part not in lora_candidates:
+                                lora_candidates[prompt_part] = []
+                            lora_candidates[prompt_part].append({'full_path': full_path, 'distance': distance})
+                            self.logger.log("Distance: " + str(distance) + " Lora: " + lora_filename + " Tag: " + prompt_part, "ALL")
+                            break
 
+        # Load the best candidate Lora for each prompt part
         for prompt_part, candidates in lora_candidates.items():
             if candidates:
                 selected_candidate = min(candidates, key=lambda x: x['distance'])
                 folder_name = self.normalize_folder_name(os.path.dirname(selected_candidate['full_path']))
+                # Load Lora if not already loaded and within the allowed number per folder
                 if selected_candidate['full_path'] not in loaded_loras and (folder_name not in include_folders or len(loaded_loras) < include_folders[folder_name]):
                     self.logger.log(f"Loading Lora: {os.path.split(selected_candidate['full_path'])[-1]}", "GENERAL")
-                    model, clip = LoraLoader().load_lora(model, clip, selected_candidate['full_path'], lora_strength, lora_strength)
+                    model, clip = LoraLoader().load_lora(model, clip, selected_candidate['full_path'], lora_strength)
                     loaded_loras.add(selected_candidate['full_path'])
             else:
                 self.logger.log(f"No matching Lora found for any tags.", "GENERAL")
 
-        return (model, clip,)
+        return (model, clip)