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: gr.OAuthProfile | None):
    """
    Fetch all questions, run the SmolAgent on them, submit all answers,
    and display the results.
    """
    # --- Determine HF Space Runtime URL and Repo URL ---
    space_id = os.getenv("SPACE_ID")

    if profile:
        username = profile.username
        print(f"User logged in: {username}")
    else:
        print("User not logged in.")
        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"

    # 1. Instantiate SmolAgent
    try:
        agent = create_agent()
        print("SmolAgent initialized.")
    except Exception as e:
        print(f"Error instantiating agent: {e}")
        return f"Error initializing agent: {e}", None

    # Code link for verification
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    print(agent_code)

    # 2. Fetch all questions
    print(f"Fetching questions from: {questions_url}")
    try:
        response = requests.get(questions_url, timeout=15)
        response.raise_for_status()
        questions_data = response.json()
        if not questions_data:
            print("Fetched questions list is empty.")
            return "Fetched questions list is empty or invalid format.", None
        print(f"Fetched {len(questions_data)} questions.")
    except Exception as e:
        print(f"Error fetching questions: {e}")
        return f"Error fetching questions: {e}", None

    # 3. Run agent on each question
    results_log = []
    answers_payload = []
    print(f"Running agent on {len(questions_data)} questions...")
    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:
            print(f"Skipping invalid item: {item}")
            continue
        try:
            answer = agent.run(question=question_text)
            answers_payload.append({"task_id": task_id, "submitted_answer": answer})
            results_log.append({"Task ID": task_id, "Question": question_text, "Answer": answer})
        except Exception as e:
            print(f"Error on task {task_id}: {e}")
            results_log.append({"Task ID": task_id, "Question": question_text, "Answer": f"ERROR: {e}"})

    if not answers_payload:
        return "Agent produced no answers.", pd.DataFrame(results_log)

    # 4. Submit answers
    payload = {"username": username, "agent_code": agent_code, "answers": answers_payload}
    print(f"Submitting {len(answers_payload)} answers...")
    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')}"
        )
        return status, pd.DataFrame(results_log)
    except Exception as e:
        print(f"Submission error: {e}")
        return f"Submission Failed: {e}", pd.DataFrame(results_log)


def test_random_question(profile: gr.OAuthProfile | None):
    """
    Fetch a random GAIA question and get the agent's answer for testing.
    """
    if not profile:
        return "Please login to test.", ""

    try:
        q = fetch_random_question()
        agent = create_agent()
        ans = agent.run(question=q.get('question', ''))
        return q.get('question', ''), ans
    except Exception as e:
        print(f"Test error: {e}")
        return f"Error: {e}", ""


# --- Build 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.
        3. Use 'Run Evaluation & Submit All Answers' or 'Test Random Question'.
        """
    )

    login = gr.LoginButton()
    run_all_btn = gr.Button("Run Evaluation & Submit All Answers")
    test_btn = gr.Button("Test Random Question")

    status_box = 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)

    run_all_btn.click(fn=run_and_submit_all, inputs=[login], outputs=[status_box, results_table])
    test_btn.click(fn=test_random_question, inputs=[login], outputs=[question_box, answer_box])

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