Update app.py

app.py

@@ -13,6 +13,7 @@ MAX_SEED = np.iinfo(np.int32).max
 
 HF_TOKEN = os.getenv('HF_TOKEN_UPSCALER')
 HF_TOKEN_UPSCALER = os.getenv('HF_TOKEN_UPSCALER')
+qwen_client = Client("K00B404/HugChatWrap",hf_token=HF_TOKEN)
 loaded_loras=[]
 for lora in loras:
     print(lora.get('repo'))
@@ -23,6 +24,34 @@ def enable_lora(lora_add, basemodel):
     print(f"[-] Menentukan model: LoRA {'diaktifkan' if lora_add else 'tidak diaktifkan'}, model dasar: {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."""
+    
+    try:
+        
+        result = qwen_client.predict(
+            message=character_prompt,
+            param_2=system_message,
+            param_3=128,
+            param_4=0.7,
+            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)}"
+        
 # Function to generate image
 async def generate_image(prompt, model, lora_word, width, height, scales, steps, seed):
     try:
@@ -31,7 +60,7 @@ async def generate_image(prompt, model, lora_word, width, height, scales, steps,
         seed = int(seed)
 
         print(f"[-] Menerjemahkan prompt: {prompt}")
-        text = str(Translator().translate(prompt, 'English')) + "," + lora_word
+        text = generate_character_description(str(Translator().translate(prompt, 'English'))) + "," + lora_word
         
         print(f"[-] Generating image with prompt: {text}, model: {model}")
         client = AsyncInferenceClient()