Update app.py

app.py

@@ -278,9 +278,6 @@ def respond(
     if custom_response:
         yield custom_response
         return
-
-
-
     if is_image_request(message):
         try:
             image = generate_image(message)
@@ -290,17 +287,15 @@ def respond(
                 return "Sorry, I couldn't generate the image. Please try again."
         except Exception as e:
             return f"An error occurred while generating the image: {str(e)}"
-
     # Handle translation with more conservative approach
     translated_msg, original_lang, was_transliterated = translate_text(message)
-
     # Prepare conversation history - only translate if necessary
     messages = [{"role": "system", "content": system_message}]
     for val in history:
         if val[0]:
             # Only translate longer messages
             if len(val[0].split()) > 2:
-                trans_user_msg, _, _ = translate_text(val[0])
+                trans_user_msg, *, * = translate_text(val[0])
                 messages.append({"role": "user", "content": trans_user_msg})
             else:
                 messages.append({"role": "user", "content": val[0]})
@@ -308,7 +303,6 @@ def respond(
             messages.append({"role": "assistant", "content": val[1]})
     
     messages.append({"role": "user", "content": translated_msg})
-
     # Get response from model
     response = ""
     for message in text_client.chat_completion(
@@ -320,7 +314,7 @@ def respond(
     ):
         token = message.choices[0].delta.content
         response += token
-
+        yield response
     # Only translate back if the original was definitely non-English
     if original_lang != 'en' and len(message.split()) > 2:
         try:
@@ -332,7 +326,10 @@ def respond(
     else:
         yield response
 
-# Updated Gradio interface to handle images
+def display_response(response):
+    print(response)
+
+# Updated Gradio interface to handle images and display the response
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -361,8 +358,9 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)"
         ),
-    ]
+    ],
+    output_component=gr.Output(type="text", label="Response")
 )
 
 if __name__ == "__main__":
-    demo.launch(share=True)
+    demo.launch(share=True)