Update app.py

app.py

@@ -55,7 +55,7 @@ def load_lora_opt(pipe, lora_input):
 
     # If it's just an ID like "author/model"
     if "/" in lora_input and not lora_input.startswith("http"):
-        pipe.load_lora_weights(lora_input)
+        pipe.load_lora_weights(lora_input, adapter_name="default")
         return
 
     if lora_input.startswith("http"):
@@ -64,7 +64,7 @@ def load_lora_opt(pipe, lora_input):
         # Repo page (no blob/resolve)
         if "huggingface.co" in url and "/blob/" not in url and "/resolve/" not in url:
             repo_id = urlparse(url).path.strip("/")
-            pipe.load_lora_weights(repo_id)
+            pipe.load_lora_weights(repo_id, adapter_name="default")
             return
 
         # Blob link → convert to resolve link
@@ -83,7 +83,7 @@ def load_lora_opt(pipe, lora_input):
                 for chunk in resp.iter_content(chunk_size=8192):
                     f.write(chunk)
             print(f"Saved LoRA to {local_path}")
-            pipe.load_lora_weights(local_path)
+            pipe.load_lora_weights(local_path, adapter_name="default")
         finally:
             shutil.rmtree(tmp_dir, ignore_errors=True)
 
@@ -110,7 +110,11 @@ def generate_qwen(
     
     start_time = time.time()
 
-    pipe_qwen.unload_lora_weights()
+    current_adapters = pipe_qwen.get_list_adapters()
+    for adapter in current_adapters:
+        pipe_qwen.delete_adapters(adapter)
+    pipe_qwen.disable_lora()
+
     use_lora = False
     if lora_input and lora_input.strip() != "":
         load_lora_opt(pipe_qwen, lora_input)
@@ -122,17 +126,14 @@ def generate_qwen(
         negative_prompt=negative_prompt if negative_prompt else "",
         height=height,
         width=width,
-        true_cfg_scale=guidance_scale,
         guidance_scale=1.0,
+        true_guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
         num_images_per_prompt=num_images,
         generator=generator,
         output_type="pil",
     ).images
     
-    if use_lora:
-        pipe_qwen.unload_lora_weights()
-    
     end_time = time.time()
     duration = end_time - start_time
     
@@ -144,6 +145,12 @@ def generate_qwen(
             for i, img_path in enumerate(image_paths):
                 zipf.write(img_path, arcname=f"Img_{i}.png")
         zip_path = zip_name
+
+    # Clean up adapters
+    current_adapters = pipe_qwen.get_list_adapters()
+    for adapter in current_adapters:
+        pipe_qwen.delete_adapters(adapter)
+    pipe_qwen.disable_lora()
     
     return image_paths, seed, f"{duration:.2f}", zip_path