# app.py
import gradio as gr
import openai

# openai.api_key = "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"
client = openai.OpenAI()
def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p):
    
    #make history
    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})
    print("Messages: ", messages)

    #input
    response = client.responses.create(
        model="gpt-4.1-nano", 
        input=messages,
        temperature=temperature,
        top_p=top_p,
        max_output_tokens=max_tokens
    )
    response = response.output_text
    
    yield response

demo = gr.ChatInterface(
    respond, #câu phản hồi
    additional_inputs=[
        gr.Textbox("Bạn là một chatbot tiếng Việt thân thiện.", label="System message"),
        gr.Slider(1, 2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(0.1, 4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(0.1, 1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
    ],
)

if __name__ == "__main__":
    demo.launch()