import os
from typing import Any

from data.vector_db import load_chunks_with_local_cache

# cacheing logic here
# note cacheing just useful in dev environment
# not really needed in hf, not even sure if hf memory is persistent

def get_cache_settings() -> tuple[str, bool]:
    project_root = os.path.dirname(os.path.abspath(__file__))
    cache_dir = os.getenv("BM25_CACHE_DIR", os.path.join(project_root, "..", ".cache"))
    force_cache_refresh = os.getenv("BM25_CACHE_REFRESH", "0").lower() in {"1", "true", "yes"}
    return cache_dir, force_cache_refresh


def load_cached_chunks(
    index: Any,
    index_name: str,
    cache_dir: str,
    force_cache_refresh: bool,
    batch_size: int = 100,
) -> tuple[list[dict[str, Any]], str]:
    return load_chunks_with_local_cache(
        index=index,
        index_name=index_name,
        cache_dir=cache_dir,
        batch_size=batch_size,
        force_refresh=force_cache_refresh,
    )