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

from smolagents import CodeAgent, InferenceClientModel
from tools import DuckDuckGoSearchTool, WeatherInfoTool, HubStatsTool
from retriever import load_guest_dataset

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

# -------------------------------
# Create Alfred AI Agent
# -------------------------------

class BasicAgent:

    def __init__(self):
        token = os.getenv("HF_TOKEN")

        if not token:
            raise ValueError(
                "HF_TOKEN is missing. Add it in Space Secrets."
            )

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

        self.search_tool = DuckDuckGoSearchTool()
        self.weather_tool = WeatherInfoTool()
        self.hub_tool = HubStatsTool()
        self.guest_tool = load_guest_dataset()

        self.agent = CodeAgent(
            tools=[
                self.guest_tool,
                self.weather_tool,
                self.hub_tool,
                self.search_tool
            ],
            model=model,
            max_steps=8,
            planning_interval=3
        )

    def __call__(self, question: str) -> str:
        try:
            answer = self.agent.run(
                question,
                reset=True
            )

            if answer is None:
                return "No answer generated."

            return str(answer).strip()

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


# -------------------------------
# Evaluation and Submission
# -------------------------------

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

    if not profile:
        return "Please login to Hugging Face first.", None

    username = profile.username
    space_id = os.getenv("SPACE_ID")

    if not space_id:
        return "SPACE_ID not found. Run this inside your Hugging Face Space.", None

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

    # Initialize agent
    try:
        agent = BasicAgent()
    except Exception as e:
        return f"Agent initialization failed: {e}", None

    # Fetch GAIA questions
    try:
        response = requests.get(
            f"{DEFAULT_API_URL}/questions",
            timeout=30
        )
        response.raise_for_status()
        questions = response.json()

    except Exception as e:
        return f"Could not fetch questions: {e}", None

    if not questions:
        return "No questions received.", None

    answers = []
    results = []

    # Solve questions
    for index, item in enumerate(questions, start=1):

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

        if not task_id or not question:
            continue

        print(f"Solving question {index}/{len(questions)}")

        try:
            answer = agent(question)

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

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

        except Exception as e:
            print(f"Question error: {e}")

    if not answers:
        return "Agent could not generate any answers.", pd.DataFrame(results)

    # Submit answers
    submission_data = {
        "username": username,
        "agent_code": agent_code,
        "answers": answers
    }

    try:
        response = requests.post(
            f"{DEFAULT_API_URL}/submit",
            json=submission_data,
            timeout=300
        )

        response.raise_for_status()
        result = response.json()

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

        return status, pd.DataFrame(results)

    except Exception as e:
        return f"Submission failed: {e}", pd.DataFrame(results)


# -------------------------------
# Gradio Interface
# -------------------------------

with gr.Blocks() as demo:

    gr.Markdown("# Alfred - GAIA AI Agent")

    gr.Markdown(
        "Login to Hugging Face and run your AI agent evaluation."
    )

    gr.LoginButton()

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

    status_output = gr.Textbox(
        label="Submission Result",
        lines=6
    )

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

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


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