import gradio as gr
from huggingface_hub import InferenceClient
import asyncio

# Use a smaller model
client = InferenceClient("distilgpt2")

async def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    # Construct the prompt from history and current message
    prompt = system_message + "\n\n"
    for user_msg, bot_msg in history:
        prompt += f"Human: {user_msg}\nAI: {bot_msg}\n"
    prompt += f"Human: {message}\nAI:"

    try:
        # Generate response with a timeout
        response = await asyncio.wait_for(
            client.text_generation(
                prompt,
                max_new_tokens=max_tokens,
                temperature=temperature,
                top_p=top_p,
                do_sample=True,
            ),
            timeout=10  # 10 seconds timeout
        )

        # Extract only the AI's response
        ai_response = response.split("AI:")[-1].strip()
        return ai_response
    except asyncio.TimeoutError:
        return "I'm sorry, but I'm having trouble generating a response right now. Could you try again?"

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value="You are a helpful AI assistant.", label="System message"),
        gr.Slider(minimum=1, maximum=100, value=50, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.9,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)

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