Update app.py

app.py

@@ -1,50 +1,5 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-
 client = InferenceClient("thviet79/model-QA-medical")
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    # Here, call the Hugging Face Inference API with the messages and other parameters
-    response = client.text_generation(
-        model="thviet79/model-QA-medical",
-        inputs=messages,
-        parameters={"max_tokens": max_tokens, "temperature": temperature, "top_p": top_p},
-    )
-    return response["generated_text"]  # Extract the model's response
-
-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"),
-        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)",
-        ),
-    ],
-    type='messages'  # This makes it use the OpenAI-style structure
-)
-
-if __name__ == "__main__":
-    demo.launch(share = True)
+client.question_answering(question="Hi?")