import os
import gradio as gr
from huggingface_hub import InferenceClient


client = InferenceClient(
    model="Qwen/Qwen2.5-Coder-7B-Instruct",
    token=os.getenv("Sayyid")
)


def suggest_menu(occasion: str) -> str:
    occasion = occasion.lower().strip()

    menus = {
        "casual": "Pizza, snacks, and drinks.",
        "formal": "3-course dinner with wine and dessert.",
        "superhero": "Buffet with high-energy and healthy food.",
    }

    return menus.get(occasion, "Custom menu for the butler.")


def respond(message, history):
    try:
        msg = message.lower().strip()

        if "menu" in msg or "food" in msg:
            if "formal" in msg:
                return suggest_menu("formal")
            elif "casual" in msg:
                return suggest_menu("casual")
            elif "superhero" in msg:
                return suggest_menu("superhero")
            else:
                return suggest_menu("custom")

        response = client.chat_completion(
            messages=[
                {
                    "role": "system",
                    "content": "You are Alfred, a sharp, elegant, helpful butler assistant. Answer clearly and briefly."
                },
                {
                    "role": "user",
                    "content": message
                }
            ],
            max_tokens=256,
            temperature=0.2,
        )

        return response.choices[0].message.content

    except Exception as e:
        return f"Error: {e}"


demo = gr.ChatInterface(
    fn=respond,
    title="Alfred Agent",
    description="Ask Alfred anything.",
    examples=[
        "Suggest a formal menu",
        "Suggest a casual menu",
        "Suggest superhero party food",
        "Plan a luxury mansion party",
        "Give me music recommendations",
    ],
)

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