Update app.py

app.py

@@ -24,14 +24,14 @@ def enable_lora(lora_add, basemodel):
     print(f"[-] Determining model: LoRA {'enabled' if lora_add else 'disabled'}, base model: {basemodel}")
     return basemodel if not lora_add else lora_add
 
-def generate_character_description(character_prompt):
-    """Generate detailed character description using Qwen"""
-    system_message = """You are a character description generator. Create detailed, vivid descriptions 
-    of characters including their physical appearance, personality, and notable features. Keep the 
-    description focused on visual elements that could be used for image generation."""
-    
+def generate_character_description(character_prompt, system_message = """
+        You are a character description generator. Create detailed, vivid descriptions 
+        of characters including their physical appearance, personality, and notable features. Keep the 
+        description focused on visual elements that could be used for image generation.
+        """
+    ):
+    """Generate detailed character description using K00B404/HugChatWrap space"""
     try:
-        
         result = qwen_client.predict(
             message=character_prompt,
             param_2=system_message,
@@ -40,14 +40,7 @@ def generate_character_description(character_prompt):
             param_5=0.95,
             api_name="/chat"
         )
-        '''result = qwen_client.predict(
-            message=character_prompt,
-            system_message=system_message,
-            max_tokens=512,
-            temperature=0.7,
-            top_p=0.95,
-            api_name="/chat"
-        )'''
+        
         return result
     except Exception as e:
         return f"Error generating description: {str(e)}"
@@ -73,7 +66,7 @@ async def generate_image(prompt, model, lora_word, width, height, scales, steps,
 # Function to upscale image
 def get_upscale_finegrain(prompt, img_path, upscale_factor):
     try:
-        print(f"[-] Memulai proses upscaling dengan faktor {upscale_factor} untuk gambar {img_path}")
+        print(f"[-] Processing with Factor {upscale_factor} for Image {img_path}")
         client = Client("finegrain/finegrain-image-enhancer", hf_token=HF_TOKEN_UPSCALER)
         result = client.predict(
             input_image=handle_file(img_path),