Update app.py

app.py

@@ -25,6 +25,9 @@ def download_lora(url):
     
     # If file already exists in cache, return the path
     if os.path.exists(local_path):
+        print()
+        print("********** Lora Already Exists **********")
+        print()
         return local_path
     
     # Download the file
@@ -43,10 +46,14 @@ def download_lora(url):
                 for chunk in response.iter_content(chunk_size=8192):
                     if chunk:
                         f.write(chunk)
-        
+        print()
+        print("********** Lora Downloading Successfull **********")
+        print()
         return local_path
     except Exception as e:
+        print()
         print(f"Error downloading LoRA: {str(e)}")
+        print()
         return None
 
 def is_civitai_url(url):
@@ -100,17 +107,33 @@ def generate_image(prompt, negative_prompt, lora_url, num_inference_steps=30, gu
                 lora_path = download_lora(lora_url)
                 if lora_path:
                     pipe.load_lora_weights(lora_path)
+                    print()
+                    print("********** URL Lora Loaded **********")
+                    print()
+                    
                 else:
                     pipe.load_lora_weights(DEFAULT_LORA)
+                    print()
+                    print("********** Default Lora Loaded **********")
+                    print()
+                    
             # If it's a HuggingFace repo path
             elif '/' in lora_url and not lora_url.startswith('http'):
                 pipe.load_lora_weights(lora_url)
+                print()
+                print("********** URL Lora Loaded **********")
+                print()
             else:
                 pipe.load_lora_weights(DEFAULT_LORA)
+                print()
+                print("********** Default Lora Loaded **********")
+                print()
         else:
             pipe.load_lora_weights(DEFAULT_LORA)
     except Exception as e:
+        print()
         print(f"Error loading LoRA weights: {str(e)}")
+        print()
         pipe.load_lora_weights(DEFAULT_LORA)
     
     if model == "Real6.0":