from __future__ import annotations

import json
import random
from pathlib import Path

import numpy as np
import torch

ROOT = Path(__file__).resolve().parents[1]
DATA_DIR = ROOT / 'data'
ARTIFACT_DIR = ROOT / 'artifacts'


def load_jsonl(path: str | Path) -> list[dict]:
    rows = []
    with Path(path).open(encoding='utf-8') as handle:
        for line in handle:
            line = line.strip()
            if line:
                rows.append(json.loads(line))
    return rows


def set_seed(seed: int) -> None:
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    if torch.cuda.is_available():
        torch.cuda.manual_seed_all(seed)