app.py

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

from agent import GaiaAgent

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

class GAIALlamaAgent:
    def __init__(self):
        self.agent = GaiaAgent()
    def __call__(self, question: str, task_id: str) -> str:
        # Pass both question and task_id to the agent
        return self.agent(question, task_id)

def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    if not profile or not profile.username:
        return "Please Login to Hugging Face with the button.", None

    username = profile.username.strip()
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else ""
    questions_url = f"{DEFAULT_API_URL}/questions"
    submit_url = f"{DEFAULT_API_URL}/submit"

    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()
    results_log = []
    answers_payload = []

    for item in questions_data:
        task_id = item.get("task_id")
        question_text = item.get("question")
        if not task_id or question_text is None:
            continue
        try:
            submitted_answer = agent(question_text, task_id)
        except Exception as e:
            submitted_answer = f"[ERROR] {e}"
        answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
        results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_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()
        final_status = (
            f"Submission Successful!\n"
            f"User: {result_data.get('username')}\n"
            f"Overall Score: {result_data.get('score', 'N/A')}% "
            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
            f"Message: {result_data.get('message', 'No message received.')}"
        )
        return final_status, pd.DataFrame(results_log)
    except Exception as e:
        return f"Submission Failed: {e}", pd.DataFrame(results_log)

# --- Gradio Interface matching original benchmark ---
with gr.Blocks() as demo:
    gr.Markdown("# Basic Agent Evaluation Runner")
    gr.Markdown("""
    **Instructions:**
    1. Please clone this space and modify the agent logic.
    2. Log in to Hugging Face with the button.
    3. Click 'Run Evaluation & Submit All Answers' to run the full GAIA test.
    """)

    gr.LoginButton()

    run_button = gr.Button("Run Evaluation & Submit All Answers")
    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
    results_table = gr.DataFrame(label="Questions and Agent Answers")

    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])

if __name__ == "__main__":
    print("\n===== Application Startup =====")
    space_id = os.getenv("SPACE_ID")
    if space_id:
        print(f"🔗 Space: https://huggingface.co/spaces/{space_id}")
    demo.launch(debug=True)