import gradio as gr
from huggingface_hub import InferenceClient

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("literallybannedfromcallingbob/Aegis-1B-Agent")


def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    # Build prompt with history and system message
    prompt = f"{system_message}\n"
    for user, assistant in history:
        if user:
            prompt += f"User: {user}\n"
        if assistant:
            prompt += f"Assistant: {assistant}\n"
    prompt += f"User: {message}\nAssistant:"

    # Call the text_generation endpoint
    response = client.text_generation(
        prompt,
        max_new_tokens=max_tokens,
        temperature=temperature,
        top_p=top_p,
        stream=True,
    )
    output = ""
    for r in response:
        output += r.token.text
        yield output


"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
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)",
        ),
    ],
    title="Transformer Chatbot Demo (currently trained with ATIS dataset)",
    description="Ask flight-related questions and get an answer."
)


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