Update app.py

app.py

@@ -82,32 +82,28 @@ with demo:
                 response += char
                 yield [(f"🤖 Response from LLM: {chat_model_selection}", response)]  # Correct format for Gradio Chatbot
 #
-       with gr.Blocks() as chat_interface:
-           chatbot = gr.Chatbot()
-           msg = gr.Textbox()
-           submit = gr.Button("Submit")
-           clear = gr.Button("Clear")
-
-           def user(user_message, history):
-               return "", history + [[user_message, None]]
-
-           def clear_chat(*args):
-               return []  # Returning an empty list to signify clearing the chat, adjust as per Gradio's capabilities
-
-           submit.click(
-               fn=get_response,
-               inputs=[msg, chatbot],
-               outputs=chatbot
-           )
-
-           clear.click(
-               fn=clear_chat,
-               inputs=None,
-               outputs=chatbot
-           )
-           
-       chat_interface.queue()
-       chat_interface.launch()
+        with gr.Blocks() as chat_interface:
+            chatbot = gr.Chatbot()
+            msg = gr.Textbox()
+            submit = gr.Button("Submit")
+            clear = gr.Button("Clear")
+            def user(user_message, history):
+                return "", history + [[user_message, None]]
+            def clear_chat(*args):
+                return []  # Returning an empty list to signify clearing the chat, adjust as per Gradio's capabilities
+            submit.click(
+                fn=get_response,
+                inputs=[msg, chatbot],
+                outputs=chatbot
+            )
+            clear.click(
+                fn=clear_chat,
+                inputs=None,
+                outputs=chatbot
+            )
+            
+        chat_interface.queue()
+        chat_interface.launch()
 
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         with gr.TabItem("🏆 LLM Leadeboard", elem_id="llm-benchmark-table", id=0):