# app.py — updated for GAIA tools (file upload for audio/Excel)

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_path: str = None) -> str:
        # Shortcut logic: if file exists and question matches specific types
        if file_path:
            if "mp3" in file_path:
                return transcribe_audio(file_path)
            elif "xlsx" in file_path or "xls" in file_path:
                return extract_excel_total_food_sales(file_path)

        return asyncio.run(answer_question(question))

def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    username = profile.username if profile else None
    if not username:
        return "Please login to Hugging Face.", None

    api_url = DEFAULT_API_URL
    questions_url = f"{api_url}/questions"
    submit_url = f"{api_url}/submit"
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else ""

    try:
        response = requests.get(questions_url, timeout=15)
        response.raise_for_status()
        questions_data = response.json()
    except Exception as e:
        return f"❌ Error fetching questions: {e}", None

    agent = GAIALlamaAgent()
    answers_payload = []
    results_log = []

    for item in questions_data:
        qid = item.get("task_id")
        question = item.get("question")
        if not qid or not question:
            continue
        try:
            answer = agent(question)
        except Exception as e:
            answer = f"[AGENT ERROR] {e}"
        answers_payload.append({"task_id": qid, "submitted_answer": answer})
        results_log.append({"Task ID": qid, "Question": question, "Submitted Answer": answer})

    submission_data = {
        "username": username,
        "agent_code": agent_code,
        "answers": answers_payload
    }

    try:
        response = requests.post(submit_url, json=submission_data, timeout=60)
        response.raise_for_status()
        result_data = response.json()
        status = (
            f"✅ Submission Successful!\n"
            f"User: {result_data.get('username')}\n"
            f"Score: {result_data.get('score')}%\n"
            f"Correct: {result_data.get('correct_count')}/{result_data.get('total_attempted')}\n"
            f"Message: {result_data.get('message')}"
        )
        return status, pd.DataFrame(results_log)
    except Exception as e:
        return f"❌ Submission failed: {e}", pd.DataFrame(results_log)

# --- Gradio UI ---
with gr.Blocks() as demo:
    gr.Markdown("""
        # 🧠 GAIA Agent Evaluation

        Upload your files if needed and evaluate the agent's answers.
    """)
    gr.LoginButton()

    with gr.Row():
        question_box = gr.Textbox(label="Manual Question (optional)", lines=3)
        file_input = gr.File(label="Optional File (.mp3 or .xlsx)", file_types=[".mp3", ".xlsx"])
        submit_btn = gr.Button("Ask Agent")

    output_text = gr.Textbox(label="Answer")
    submit_btn.click(
        fn=lambda q, f: GAIALlamaAgent()(q, f.name if f else None),
        inputs=[question_box, file_input],
        outputs=output_text
    )

    gr.Markdown("## Or run full benchmark submission")
    run_btn = gr.Button("Run Evaluation & Submit All Answers")
    run_out = gr.Textbox(label="Status", lines=4)
    run_table = gr.DataFrame(label="Questions and Agent Answers")
    run_btn.click(fn=run_and_submit_all, outputs=[run_out, run_table])

if __name__ == "__main__":
    print("\n🔁 App Starting Up...")
    if os.getenv("SPACE_ID"):
        print(f"🔗 Space: https://huggingface.co/spaces/{os.getenv('SPACE_ID')}")
    demo.launch(debug=True)