from __future__ import annotations

import tomllib
from dataclasses import dataclass
from pathlib import Path

ROOT = Path(__file__).resolve().parent.parent


@dataclass(frozen=True)
class Config:
    fetch_batch_delay: float
    lyrics_request_delay: float
    apply_request_delay: float
    request_timeout: float
    batch_size: int
    small_group_min: int
    digest_top_artists: int
    digest_top_albums: int
    ollama_host: str
    ollama_model: str
    ollama_prompt_version: int
    ollama_timeout: float
    ollama_keep_alive: str
    token_file: Path
    cache_dir: Path
    out_dir: Path


def load_config(path: Path | None = None) -> Config:
    path = path or ROOT / "config.toml"
    with path.open("rb") as f:
        data = tomllib.load(f)

    return Config(
        fetch_batch_delay=data["throttle"]["fetch_batch_delay"],
        lyrics_request_delay=data["throttle"]["lyrics_request_delay"],
        apply_request_delay=data["throttle"]["apply_request_delay"],
        request_timeout=data["throttle"]["request_timeout"],
        batch_size=data["fetch"]["batch_size"],
        small_group_min=data["classify"]["small_group_min"],
        digest_top_artists=data["digest"]["top_artists"],
        digest_top_albums=data["digest"]["top_albums"],
        ollama_host=data["ollama"]["host"],
        ollama_model=data["ollama"]["model"],
        ollama_prompt_version=data["ollama"]["prompt_version"],
        ollama_timeout=data["ollama"]["timeout"],
        ollama_keep_alive=data["ollama"]["keep_alive"],
        token_file=ROOT / data["paths"]["token_file"],
        cache_dir=ROOT / data["paths"]["cache_dir"],
        out_dir=ROOT / data["paths"]["out_dir"],
    )