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

from smolagents import CodeAgent, InferenceClientModel, WebSearchTool

# --------------------------------------------------
# Constants
# --------------------------------------------------

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


# --------------------------------------------------
# Agent Definition
# --------------------------------------------------

class BasicAgent:
    def __init__(self):
        print("Initializing Agent...")

        self.model = InferenceClientModel(
            token=os.getenv("HF_TOKEN")
        )

        self.agent = CodeAgent(
            tools=[WebSearchTool()],
            model=self.model,
            max_steps=5
        )

        print("Agent initialized successfully.")

    def __call__(self, question: str) -> str:
        try:
            print(f"Question: {question[:100]}")

            answer = self.agent.run(question)

            print(f"Answer: {answer}")

            return str(answer)

        except Exception as e:
            print(f"Agent Error: {e}")
            return f"Error: {e}"


# --------------------------------------------------
# Evaluation Runner
# --------------------------------------------------

def run_and_submit_all(profile: gr.OAuthProfile | None):

    space_id = os.getenv("SPACE_ID")

    if profile:
        username = profile.username
        print(f"Logged in as: {username}")
    else:
        return "Please Login to Hugging Face first.", None

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

    try:
        agent = BasicAgent()
    except Exception as e:
        return f"Error creating agent: {e}", None

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

    # ----------------------------------------------
    # Fetch Questions
    # ----------------------------------------------

    try:
        response = requests.get(questions_url, timeout=30)
        response.raise_for_status()

        questions_data = response.json()

        print(f"Fetched {len(questions_data)} questions.")

    except Exception as e:
        return f"Error fetching questions: {e}", None

    # ----------------------------------------------
    # Run Agent
    # ----------------------------------------------

    results_log = []
    answers_payload = []

    for item in questions_data:

        task_id = item.get("task_id")
        question = item.get("question")

        if not task_id or not question:
            continue

        try:
            answer = agent(question)

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

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

        except Exception as e:

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

    if len(answers_payload) == 0:
        return "No answers generated.", pd.DataFrame(results_log)

    # ----------------------------------------------
    # Submit Answers
    # ----------------------------------------------

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

    try:

        response = requests.post(
            submit_url,
            json=submission_data,
            timeout=120
        )

        response.raise_for_status()

        result = response.json()

        status = (
            f"Submission Successful!\n"
            f"User: {result.get('username')}\n"
            f"Overall Score: {result.get('score')}%\n"
            f"Correct Answers: {result.get('correct_count')}/{result.get('total_attempted')}\n"
            f"Message: {result.get('message')}"
        )

        return status, pd.DataFrame(results_log)

    except Exception as e:

        return (
            f"Submission Failed: {e}",
            pd.DataFrame(results_log)
        )


# --------------------------------------------------
# UI
# --------------------------------------------------

with gr.Blocks() as demo:

    gr.Markdown("# Hugging Face Agents Course - Final Assignment")

    gr.Markdown(
        """
        1. Login with Hugging Face
        2. Click the evaluation button
        3. Wait for all questions to finish
        4. Answers will be submitted automatically
        """
    )

    gr.LoginButton()

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

    status_output = gr.Textbox(
        label="Run Status / Submission Result",
        lines=8
    )

    results_table = gr.DataFrame(
        label="Questions and Agent Answers",
        wrap=True
    )

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

# --------------------------------------------------
# Launch
# --------------------------------------------------

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