import json
import os
import traceback
from datetime import datetime, timedelta, timezone
from typing import Optional

import gradio as gr
import yaml

from src.display.formatting import styled_error, styled_message
from src.envs import API, DAILY_SUBMISSION_LIMIT_PER_USER, EVAL_REQUESTS_PATH, QUEUE_REPO
from src.submission.structs import CompetitionType, Submission, SubmissionStatus
from workflows.structs import Workflow


def get_user_submissions_today(username: str, competition_type: str) -> list[Submission]:
    today = datetime.now(timezone.utc).strftime("%Y%m%d")
    if username is None:
        raise gr.Error("Authentication required. Please log in to view your submissions.")
    out_dir = f"{EVAL_REQUESTS_PATH}/{username}"
    submissions = []
    if not os.path.exists(out_dir):
        return submissions
    for file in os.listdir(out_dir):
        if not file.startswith(f"{competition_type}_"):
            continue
        with open(os.path.join(out_dir, file), "r") as f:
            submission = Submission.from_dict(json.load(f))
            if submission.created_at.startswith(today):
                submissions.append(submission)
    return submissions


def get_time_until_next_submission(tz: timezone = timezone.utc) -> str:
    next_day_00 = datetime.now(tz) + timedelta(days=1)
    next_day_00 = next_day_00.replace(hour=0, minute=0, second=0, microsecond=0)
    remaining_time = next_day_00 - datetime.now(tz)
    hours = remaining_time.seconds // 3600
    minutes = (remaining_time.seconds % 3600) // 60
    remaining_time_str = f"{hours} hours {minutes} mins"
    return remaining_time_str


def create_submission(
    username: str,
    model_name: str,
    description: str,
    workflow: Workflow,
    competition_type: CompetitionType,
) -> Submission:
    """
    Create a submission for a tossup model.

    Args:
        name: Display name of the submission
        description: Detailed description of what the submission does
        user_email: Email of the user who created the submission
        workflow: The workflow configuration for the tossup model

    Returns:
        Submission object if successful, None if validation fails
    """
    # Create the submission
    dt = datetime.now(timezone.utc)
    submission = Submission(
        id=f"{competition_type}_{dt.strftime('%Y%m%d_%H%M%S')}_{model_name.lower().replace(' ', '_')}",
        model_name=model_name,
        username=username,
        description=description,
        competition_type=competition_type,
        submission_type="simple_workflow",
        workflow=workflow,
        status="submitted",
        created_at=dt.isoformat(),
        updated_at=dt.isoformat(),
    )

    return submission


def submit_model(
    model_name: str,
    description: str,
    workflow: Workflow,
    competition_type: CompetitionType,
    profile: gr.OAuthProfile | None,
) -> str:
    """
    Submit a tossup model for evaluation.

    Args:
        name: Display name of the submission
        description: Detailed description of what the submission does
        user_email: Email of the user who created the submission
        workflow: The workflow configuration for the tossup model

    Returns:
        Status message
    """

    if profile is None:
        return styled_error("Authentication required. Please log in first to submit your model.")

    username = profile.username

    if len(get_user_submissions_today(username)) >= DAILY_SUBMISSION_LIMIT_PER_USER:
        time_str = get_time_until_next_submission()
        return styled_error(
            f"Daily submission limit of {DAILY_SUBMISSION_LIMIT_PER_USER} reached. Please try again in \n {time_str}."
        )
    try:
        submission = create_submission(
            username=username,
            model_name=model_name,
            description=description,
            workflow=workflow,
            competition_type=competition_type,
        )
        # Convert to dictionary format
        submission_dict = submission.to_dict()

        # Create output directory path
        out_dir = f"{EVAL_REQUESTS_PATH}/{username}"
        out_path = f"{out_dir}/{submission.id}.json"

        # Upload to HuggingFace dataset
        API.upload_file(
            path_or_fileobj=json.dumps(submission_dict, indent=2).encode(),
            path_in_repo=out_path.split("eval-queue/")[1],
            repo_id=QUEUE_REPO,
            repo_type="dataset",
            commit_message=f"Add tossup submission {submission.id}",
        )

        return styled_message(
            f"Successfully submitted tossup model!\n"
            f"Submission ID: {submission.id}\n"
            f"Name: {username}/{model_name}\n"
            f"Please wait for up to an hour for the model to show in the PENDING list."
        )

    except Exception as e:
        traceback.print_exc()
        return styled_error(f"Error submitting model: {str(e)}")


if __name__ == "__main__":
    # Example usage
    from workflows.factory import create_quizbowl_simple_step_initial_setup

    # Create workflow
    model_step = create_quizbowl_simple_step_initial_setup()
    model_step.model = "gpt-4"
    model_step.provider = "openai"
    model_step.temperature = 0.7

    workflow = Workflow(
        inputs=["question_text"],
        outputs={"answer": "A.answer", "confidence": "A.confidence"},
        steps={"A": model_step},
    )

    # Submit model
    result = submit_model(
        model_name="GPT-4 Tossup",
        description="A simple GPT-4 model for tossup questions",
        workflow=workflow,
        competition_type="tossup",
    )
    print(result)