"""Utility helpers."""
import logging
import os
import random
import sys

import numpy as np
import torch


def setup_logging(level=logging.INFO):
    logging.basicConfig(
        level=level,
        format="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
        handlers=[logging.StreamHandler(sys.stdout)],
        force=True,
    )
    # Quiet HuggingFace
    logging.getLogger("transformers").setLevel(logging.WARNING)
    logging.getLogger("datasets").setLevel(logging.WARNING)
    logging.getLogger("urllib3").setLevel(logging.WARNING)
    logging.getLogger("filelock").setLevel(logging.WARNING)


def set_seed(seed: int, deterministic: bool = True) -> None:
    """Seed Python, NumPy, and PyTorch for more reproducible experiments."""
    os.environ["PYTHONHASHSEED"] = str(seed)
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    if torch.cuda.is_available():
        torch.cuda.manual_seed(seed)
        torch.cuda.manual_seed_all(seed)
    if deterministic:
        torch.backends.cudnn.deterministic = True
        torch.backends.cudnn.benchmark = False


def seeded_generator(seed: int) -> torch.Generator:
    """Return a CPU generator for deterministic DataLoader shuffling."""
    generator = torch.Generator()
    generator.manual_seed(seed)
    return generator