add max lora config feature

modules/async_worker.py

@@ -131,7 +131,7 @@ def worker():
         base_model_name = args.pop()
         refiner_model_name = args.pop()
         refiner_switch = args.pop()
-        loras = [[str(args.pop()), float(args.pop())] for _ in range(5)]
+        loras = [[str(args.pop()), float(args.pop())] for _ in range(modules.config.default_loras_max_number)]
         input_image_checkbox = args.pop()
         current_tab = args.pop()
         uov_method = args.pop()

modules/config.py

@@ -192,6 +192,11 @@ default_loras = get_config_item_or_set_default(
     ],
     validator=lambda x: isinstance(x, list) and all(len(y) == 2 and isinstance(y[0], str) and isinstance(y[1], numbers.Number) for y in x)
 )
+default_loras_max_number = get_config_item_or_set_default(
+    key='default_loras_max_number',
+    default_value=len(default_loras),
+    validator=lambda x: isinstance(x, numbers.Number) and x >= 1
+)
 default_cfg_scale = get_config_item_or_set_default(
     key='default_cfg_scale',
     default_value=4.0,
@@ -318,13 +323,14 @@ example_inpaint_prompts = get_config_item_or_set_default(
 
 example_inpaint_prompts = [[x] for x in example_inpaint_prompts]
 
-config_dict["default_loras"] = default_loras = default_loras[:5] + [['None', 1.0] for _ in range(5 - len(default_loras))]
+config_dict["default_loras"] = default_loras = default_loras[:default_loras_max_number] + [['None', 1.0] for _ in range(default_loras_max_number - len(default_loras))]
 
 possible_preset_keys = [
     "default_model",
     "default_refiner",
     "default_refiner_switch",
     "default_loras",
+    "default_loras_max_number",
     "default_cfg_scale",
     "default_sample_sharpness",
     "default_sampler",

modules/meta_parser.py

@@ -135,14 +135,20 @@ def load_parameter_button_click(raw_prompt_txt, is_generating):
     
     results.append(gr.update(visible=False))
 
-    for i in range(1, 6):
+    for i in range(1, modules.config.default_loras_max_number + 1):
-        try:
+        lora_key = f'LoRA {i}'
-            n, w = loaded_parameter_dict.get(f'LoRA {i}').split(' : ')
+        if lora_key in loaded_parameter_dict:
-            w = float(w)
+            try:
-            results.append(n)
+                n, w = loaded_parameter_dict[lora_key].split(' : ')
-            results.append(w)
+                w = float(w)
-        except:
+                results.append(n)  # Update LoRA model
-            results.append(gr.update())
+                results.append(w)  # Update LoRA weight
-            results.append(gr.update())
+            except Exception as e:
+                # If there's an error parsing, log it or handle it as needed
+                print(f"Error parsing {lora_key}: {e}")
+                results.extend([gr.update(), gr.update()])  # Keep existing settings unchanged
+        else:
+            # If the LoRA setting is not in the JSON, keep the existing settings unchanged
+            results.extend([gr.update(), gr.update()])
 
     return results

webui.py

@@ -466,7 +466,7 @@ with shared.gradio_root:
                     modules.config.update_all_model_names()
                     results = []
                     results += [gr.update(choices=modules.config.model_filenames), gr.update(choices=['None'] + modules.config.model_filenames)]
-                    for i in range(5):
+                    for i in range(modules.config.default_loras_max_number):
                         results += [gr.update(choices=['None'] + modules.config.lora_filenames), gr.update()]
                     return results