app.py

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

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

# --- YOUR AGENT (MODIFIED) ---
class BasicAgent:
    def __init__(self):
        print("BasicAgent initialized.")

    def __call__(self, question: str) -> str:
        q = question.lower()

        # --- EASY MATH (BIG POINTS) ---
        try:
            if any(op in q for op in ["+", "-", "*", "/"]):
                clean_q = q.replace("what is", "").replace("?", "").strip()
                return str(eval(clean_q))
        except:
            pass

        # --- MULTIPLY WORDS ---
        if "multiply" in q:
            try:
                numbers = [int(s) for s in q.split() if s.isdigit()]
                if len(numbers) >= 2:
                    return str(numbers[0] * numbers[1])
            except:
                pass

        # --- SIMPLE FACTS ---
        if "capital of france" in q:
            return "Paris"

        if "morocco" in q:
            return "Rabat"

        # --- DEFAULT ---
        return "I don't know"


def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")

    if profile:
        username = f"{profile.username}"
        print(f"User logged in: {username}")
    else:
        return "Please Login to Hugging Face with the button.", None

    api_url = DEFAULT_API_URL
    questions_url = f"{api_url}/questions"
    submit_url = f"{api_url}/submit"

    # Create agent
    agent = BasicAgent()

    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"

    # Fetch questions
    response = requests.get(questions_url)
    questions_data = response.json()

    results_log = []
    answers_payload = []

    for item in questions_data:
        task_id = item.get("task_id")
        question_text = item.get("question")

        try:
            answer = agent(question_text)
            answers_payload.append({
                "task_id": task_id,
                "submitted_answer": answer
            })

            results_log.append({
                "Task ID": task_id,
                "Question": question_text,
                "Submitted Answer": answer
            })

        except Exception as e:
            results_log.append({
                "Task ID": task_id,
                "Question": question_text,
                "Submitted Answer": f"ERROR: {e}"
            })

    submission_data = {
        "username": username.strip(),
        "agent_code": agent_code,
        "answers": answers_payload
    }

    response = requests.post(submit_url, json=submission_data)
    result = response.json()

    final_status = (
        f"Score: {result.get('score')}% | "
        f"{result.get('correct_count')}/{result.get('total_attempted')} correct"
    )

    return final_status, pd.DataFrame(results_log)


# --- UI ---
with gr.Blocks() as demo:
    gr.Markdown("# Basic Agent Evaluation Runner")

    gr.LoginButton()

    run_button = gr.Button("Run Evaluation & Submit All Answers")

    status_output = gr.Textbox(label="Result", lines=5)
    results_table = gr.DataFrame()

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

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