import os
import time
import gradio as gr
from openai import OpenAI

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

def ask_agent(user_message, history=[]):
    response = client.responses.create(
        model="gpt-5",
        input=[
            {
                "role": "user",
                "content": [
                    {"type": "input_text", "text": user_message},
                    {"type": "input_file", "file_id": "file-UvrVb2WwNtoghrSWAWQHsx"},
                    {"type": "input_file", "file_id": "file-WjXNfYw1TBxCqGZJWec1z9"},
                ],
            }
        ]
    )

    # Extract text output
    output_texts = []
    for item in response.output:
        if item.type == "message":
            for c in item.content:
                if c.type == "output_text":
                    output_texts.append(c.text)

    return "\n".join(output_texts) if output_texts else "No response."


# ---- GRADIO UI ----
with gr.Blocks() as demo:
    gr.Markdown("# 🏨 Hotel Data Chatbot")
    chatbot = gr.Chatbot(height=400)
    msg = gr.Textbox(placeholder="Ask about the reports...")
    clear = gr.ClearButton([msg, chatbot])

    def respond(message, chat_history):
        reply = ask_agent(message, chat_history)
        chat_history.append((message, reply))
        return "", chat_history

    msg.submit(respond, [msg, chatbot], [msg, chatbot])

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