from __future__ import annotations

from dataclasses import dataclass
from pathlib import Path


@dataclass(frozen=True)
class InstalledModel:
    model_id: str
    path: Path
    already_present: bool


class ModelDependencyError(RuntimeError):
    """Raised when optional ML dependencies are missing."""


def has_local_model_files(path: Path) -> bool:
    """Return true when a Hugging Face model snapshot already exists locally."""
    return (path / 'config.json').exists() and any(
        (path / filename).exists()
        for filename in ('pytorch_model.bin', 'model.safetensors', 'tf_model.h5')
    )


def ensure_huggingface_model(
    *,
    model_id: str,
    target_dir: str | Path,
    revision: str | None = None,
) -> InstalledModel:
    """Download a Hugging Face model snapshot if it is not already installed."""
    target_path = Path(target_dir)
    if has_local_model_files(target_path):
        return InstalledModel(model_id=model_id, path=target_path, already_present=True)

    try:
        from huggingface_hub import snapshot_download
    except ImportError as exc:
        raise ModelDependencyError(
            'huggingface_hub is required. Install optional ML dependencies from requirements-ml.txt.'
        ) from exc

    target_path.mkdir(parents=True, exist_ok=True)
    snapshot_download(
        repo_id=model_id,
        revision=revision,
        local_dir=str(target_path),
        local_dir_use_symlinks=False,
        allow_patterns=[
            '*.json',
            '*.model',
            '*.txt',
            '*.safetensors',
            'pytorch_model*.bin',
            'spiece.model',
            'tokenizer*',
            'special_tokens_map.json',
            'sentencepiece.bpe.model',
        ],
    )
    return InstalledModel(model_id=model_id, path=target_path, already_present=False)