app.py

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

from agent import create_agent, fetch_random_question

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


def run_and_submit_all(profile):
    """
    Fetch all questions, run the agent on them, submit all answers,
    and return the status and results table.
    """
    # Check login
    if not profile:
        return "Please login to Hugging Face with the login button.", None

    # Extract username (support both .username and .name)
    username = getattr(profile, "username", None) or getattr(profile, "name", None)
    if not username:
        return "Login error: username not found.", None

    # Build URLs
    questions_url = f"{DEFAULT_API_URL}/questions"
    submit_url = f"{DEFAULT_API_URL}/submit"

    # Instantiate agent
    try:
        agent = create_agent()
    except Exception as e:
        return f"Error initializing agent: {e}", None

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

    # Run agent
    results = []
    answers_payload = []
    for q in questions:
        tid = q.get("task_id")
        text = q.get("question")
        if not tid or not text:
            continue
        try:
            ans = agent.run(question=text)
        except Exception as e:
            ans = f"ERROR: {e}"
        results.append({
            "Task ID": tid,
            "Question": text,
            "Answer": ans
        })
        answers_payload.append({
            "task_id": tid,
            "submitted_answer": ans
        })

    if not answers_payload:
        return "Agent returned no answers.", pd.DataFrame(results)

    # Submit answers
    payload = {
        "username": username,
        "agent_code": f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
        "answers": answers_payload
    }
    try:
        resp = requests.post(submit_url, json=payload, timeout=60)
        resp.raise_for_status()
        data = resp.json()
        status = (
            f"Submission Successful!\n"
            f"User: {data.get('username')}\n"
            f"Score: {data.get('score')}% ({data.get('correct_count')}/{data.get('total_attempted')})\n"
            f"Message: {data.get('message')}"
        )
    except Exception as e:
        status = f"Submission Failed: {e}"

    return status, pd.DataFrame(results)


def test_random_question(profile):
    """
    Fetch a random GAIA question and return the agent's answer.
    """
    if not profile:
        return "Please login to Hugging Face with the login button.", ""

    # Get question and run agent
    try:
        q = fetch_random_question()
        question = q.get("question", "")
        agent = create_agent()
        answer = agent.run(question=question)
        return question, answer
    except Exception as e:
        return f"Error during test: {e}", ""


# --- Gradio Interface ---
with gr.Blocks() as demo:
    gr.Markdown("# SmolAgent Evaluation Runner")
    gr.Markdown(
        """
        **Instructions:**
        1. Clone this space and define your agent logic in `agent.py`.
        2. Log in with your Hugging Face account using the login button below.
        3. Use **Run Evaluation & Submit All Answers** or **Test Random Question**.
        """
    )

    login = gr.LoginButton()

    run_button = gr.Button("Run Evaluation & Submit All Answers")
    test_button = gr.Button("Test Random Question")

    status_output = gr.Textbox(label="Status / Result", lines=5, interactive=False)
    results_table = gr.DataFrame(label="Full Results Table", wrap=True)
    question_box = gr.Textbox(label="Random Question", lines=3, interactive=False)
    answer_box = gr.Textbox(label="Agent Answer", lines=3, interactive=False)

    # Wire the login component directly into the callbacks
    run_button.click(fn=run_and_submit_all, inputs=[login], outputs=[status_output, results_table])
    test_button.click(fn=test_random_question, inputs=[login], outputs=[question_box, answer_box])

if __name__ == "__main__":
    demo.launch(debug=True, share=False)