# app.py — supports text, audio (.mp3) and Excel (.xlsx) inputs

import os
import requests
import pandas as pd
import gradio as gr
import asyncio
import tempfile

from agent import (
    answer_question,
    transcribe_audio,
    extract_excel_total_food_sales
)

DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

class GAIALlamaAgent:
    def __call__(self, question: str, file) -> str:
        if file:
            ext = os.path.splitext(file.name)[1].lower()
            if ext == ".mp3":
                return transcribe_audio(file.name)
            if ext in (".xls", ".xlsx"):
                return extract_excel_total_food_sales(file.name)
        return asyncio.run(answer_question(question))

def run_and_submit_all(profile: gr.OAuthProfile | None):
    if not profile or not profile.username:
        return "Please log in to Hugging Face.", None
    username = profile.username
    space_id = os.getenv("SPACE_ID", "")
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"

    try:
        questions = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15).json()
    except Exception as e:
        return f"Error fetching questions: {e}", None

    agent = GAIALlamaAgent()
    payload, log = [], []

    for q in questions:
        ans = agent(q["question"], None)
        payload.append({"task_id": q["task_id"], "submitted_answer": ans})
        log.append({"Task ID": q["task_id"], "Question": q["question"], "Answer": ans})

    try:
        res = requests.post(f"{DEFAULT_API_URL}/submit",
                            json={"username": username, "agent_code": agent_code, "answers": payload},
                            timeout=60).json()
        status = f"✅ Score: {res.get('score')}% ({res.get('correct_count')}/{res.get('total_attempted')})"
    except Exception as e:
        status = f"❌ Submission failed: {e}"

    return status, pd.DataFrame(log)

with gr.Blocks() as demo:
    gr.Markdown("# GAIA Agent")
    gr.LoginButton()
    with gr.Row():
        question = gr.Textbox(label="Question")
        file_in = gr.File(label="Optional file (.mp3, .xlsx)")
        ask_btn = gr.Button("Ask")
        output = gr.Textbox(label="Answer")
    ask_btn.click(lambda q, f: GAIALlamaAgent()(q, f), inputs=[question, file_in], outputs=output)
    gr.Markdown("## Or run full GAIA evaluation")
    eval_btn = gr.Button("Run Evaluation & Submit")
    status = gr.Textbox(label="Status", lines=4)
    table = gr.DataFrame()
    eval_btn.click(run_and_submit_all, outputs=[status, table])

if __name__ == "__main__":
    print("🔁 App starting")
    if os.getenv("SPACE_ID"):
        print("🔗 Space:", os.getenv("SPACE_ID"))
    demo.launch(debug=True)