Update app.py

app.py

@@ -1,51 +1,37 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
 # Initialize the inference client with the model ID
-client = InferenceClient(model="bragour/Camel-7b-chat")
+client = pipeline(model="bragour/Camel-7b-chat")
 
 def respond(
     message,
-    history: list[tuple[str, str]],
-    system_message,
     max_tokens,
     temperature,
     top_p,
 ):
-    messages = [{"role": "system", "content": system_message}]
-
-    for user_input, assistant_output in history:
-        if user_input:
-            messages.append({"role": "user", "content": user_input})
-        if assistant_output:
-            messages.append({"role": "assistant", "content": assistant_output})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    # Stream the response from the API
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
+    # Generate the response from the API
+    result = client(
+        message,
+        max_new_tokens=max_tokens,
         temperature=temperature,
         top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
+    )
+    
+    response = result[0]['generated_text']
+
+    return response
 
 # Define the Gradio interface
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
+        gr.Textbox(lines=2, placeholder="Type your message here...", label="Your Message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
+    outputs=gr.Textbox(label="Response"),
 )
 
-if __name__ == "__main__":
-    demo.launch()
+if __name__ ==