import gradio as gr
from huggingface_hub import InferenceClient

client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")


def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p, backend):
    # Force the AI to generate a website with index.html and specified backend
    forced_instruction = f"""
You must generate a complete website structure including at least an index.html.
Use the following backend structure: {backend}.
Only use {backend} relevant code and structure, and don't include any other type.
"""
    system_message = forced_instruction + "\n\n" + system_message

    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})

    response = ""
    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response += token
        yield response


demo = gr.ChatInterface(
    fn=respond,
    additional_inputs=[
        gr.Textbox(value="You are a helpful assistant.", 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)"),
        gr.Dropdown(choices=["Flask", "Static", "Node.js"], value="Static", label="Website Backend"),
    ],
    title="WebGen AI",
    description="Ask the AI to build a website with a specific backend (Flask, Static, or Node.js). It will always include index.html.",
)

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