changes in app

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
+client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+
 def format_prompt(message, history):
   prompt = "<s>"
   for user_prompt, bot_response in history:
@@ -33,7 +35,8 @@ def inference(message, history, model="mistralai/Mixtral-8x7B-Instruct-v0.1", Te
         yield partial_message
 
 
-chatbot = gr.Chatbot(bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
+chatbot = gr.Chatbot(avatar_images=["/content/icons/user.png", "/content/icons/chat_bot.png"], 
+                     bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
 
 
 UI=  gr.ChatInterface(
@@ -41,7 +44,7 @@ UI=  gr.ChatInterface(
         chatbot=chatbot,
         description="The Rapid TGI (Text Generation Inference) has developed by learning purpose",
         title="Rapid TGI",
-        additional_inputs_accordion="Additional Configuration to get better response",
+        additional_inputs_accordion=gr.Accordion(label="Additional Configuration to get better response",open=False),
         retry_btn=None,
         undo_btn=None,
         clear_btn="Clear",
@@ -57,6 +60,6 @@ UI=  gr.ChatInterface(
                                 gr.Slider(value=0.95, maximum=1.0,label="Top P"),
                                 gr.Slider(value=0.93, maximum=1.0,label="Repetition Penalty"),
                             ],
-        examples=[["Hello"], ["Hello"]],
+        examples=[["Hello"], ["can i know about generative ai ?"], ["how can i deploy a LLM in hugguingface inference endpoint ?"]],
     )
 UI.queue().launch(debug=True)