update app.py

app.py

@@ -1,3 +1,38 @@
 import gradio as gr
 
-gr.Interface.load("models/mistralai/Mistral-7B-Instruct-v0.1").launch()
+def format_chat_prompt(message, chat_history,instruction):
+    prompt = f"System:{instruction}"
+    for turn in chat_history:
+        user_message, bot_message = turn
+        prompt = f"{prompt}\nUser: {user_message}\nAssistant:{bot_message}"
+    prompt= f"{prompt}\nUser: {message}\nAssistant:"
+    return prompt
+
+def respond(message, chat_history,instruction,model,temperature=0.7):
+    if model == "Llama2-Chat":
+        model = "meta-llama/Llama-2-7b-chat-hf"
+    else:
+        model="mistralai/Mistral-7B-Instruct-v0.1"
+    
+    client = InferenceClient(model=f"{model}",token=API_KEY,timeout=30)
+    formatted_prompt = format_chat_prompt(message,chat_history,instruction)
+    bot_message = client.text_generation(formatted_prompt, max_new_tokens=1024,
+                                         stop_sequences=["\nUser:", "<|endoftext|>"],
+                                         temperature=temperature)
+    chat_history.append((message,bot_message))
+    return "",chat_history
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot(height=240) #visual param
+    msg = gr.Textbox(label='prompt')
+    with gr.Accordion(label="Advanced options",open=False):
+        model = gr.Radio(["MistralAI"])
+        system = gr.Textbox(label="System message", lines=2, value="A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.")
+        temperature = gr.Slider(label="temperature", minimum=0.1, maximum=1, value=0.7, step=0.1)
+    btn = gr.Button("Submit")
+    clear = gr.ClearButton(components=[msg,chatbot], value="Clear console")
+
+    btn.click(respond, inputs=[msg,chatbot,system,model], outputs=[msg, chatbot])
+    msg.submit(respond, inputs=[msg, chatbot,system,model], outputs=[msg, chatbot])
+
+demo.queue().launch()