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"

# --- Agent ---
from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool

model = HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct")

real_agent = CodeAgent(
    model=model,
    tools=[DuckDuckGoSearchTool()]
)

class BasicAgent:
    def __init__(self):
        print("Agent initialized")

    def __call__(self, question: str) -> str:
        try:
            result = real_agent.run(question)
            return str(result).strip()
        except Exception as e:
            print(f"Agent error: {e}")
            return "ERROR"


# --- Runner ---
def run_and_submit_all(profile: gr.OAuthProfile | None):

    space_id = os.getenv("SPACE_ID")

    if profile:
        username = profile.username
        print(f"User logged in: {username}")
    else:
        return "Please login first", None

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

    agent = BasicAgent()

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

    # --- fetch questions ---
    response = requests.get(questions_url, timeout=30)
    questions_data = response.json()

    results_log = []
    answers_payload = []

    for item in questions_data:
        task_id = item["task_id"]
        question = item["question"]

        answer = agent(question)

        answers_payload.append({
            "task_id": task_id,
            "submitted_answer": answer
        })

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

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

    response = requests.post(submit_url, json=submission_data, timeout=60)
    result = response.json()

    return (
        f"Score: {result.get('score', 0)}%",
        pd.DataFrame(results_log)
    )


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

    gr.LoginButton()

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

    out1 = gr.Textbox()
    out2 = gr.DataFrame()

    btn.click(run_and_submit_all, outputs=[out1, out2])


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