#!/usr/bin/env python3
from __future__ import annotations

import os
from pathlib import Path


def _download_file(*, repo_id: str, filename: str, local_dir: str, token: str | None, subfolder: str | None = None) -> Path:
    from huggingface_hub import hf_hub_download

    path = hf_hub_download(
        repo_id=repo_id,
        repo_type="model",
        filename=filename,
        subfolder=subfolder,
        token=token,
        local_dir=local_dir,
        local_dir_use_symlinks=False,
    )
    return Path(path)


def resolve_tokenizer_cache_repo(*, output_repo: str, retina_cache_repo: str) -> str:
    return (
        os.environ.get("HYDRA_TOKENIZER_CACHE_REPO")
        or os.environ.get("FEATHER_HF_OUTPUT_REPO")
        or os.environ.get("HF_REPO_ID")
        or os.environ.get("HYDRA_RETINA_CACHE_REPO")
        or os.environ.get("FEATHER_HF_RETINA_CACHE_REPO")
        or output_repo
        or retina_cache_repo
    )


def tokenizer_cache_prefix() -> str:
    vocab_size = int(os.environ.get("HYDRA_VOCAB_SIZE", "65536"))
    return f"tokenizer/vocab{vocab_size}"


def hydrate_benchmark_assets(*, cache_dir: Path, output_repo: str, tokenizer_repo: str, token: str | None) -> dict[str, str]:
    cache_dir.mkdir(parents=True, exist_ok=True)
    tok_dir = cache_dir / "tokenizer"
    tok_dir.mkdir(parents=True, exist_ok=True)
    tok_repo = resolve_tokenizer_cache_repo(output_repo=tokenizer_repo, retina_cache_repo=tokenizer_repo)
    tok_prefix = tokenizer_cache_prefix()

    ckpt_path = cache_dir / "best_bpb.pt"
    if not ckpt_path.exists():
        ckpt_path = _download_file(repo_id=output_repo, filename="best_bpb.pt", local_dir=str(cache_dir), token=token)

    tok_path = tok_dir / "tokenizer.pkl"
    if not tok_path.exists():
        tok_path = _download_file(repo_id=tok_repo, filename="tokenizer.pkl", local_dir=str(tok_dir), token=token, subfolder=tok_prefix)

    token_bytes_path = tok_dir / "token_bytes.pt"
    if not token_bytes_path.exists():
        token_bytes_path = _download_file(repo_id=tok_repo, filename="token_bytes.pt", local_dir=str(tok_dir), token=token, subfolder=tok_prefix)

    return {
        "checkpoint_path": str(ckpt_path),
        "tokenizer_dir": str(tok_dir),
    }