"""One process-wide sentence-transformer shared by every semantic lookup."""

from __future__ import annotations

import os
import threading


MODEL_NAME = "BAAI/bge-small-en-v1.5"
_model = None
_lock = threading.Lock()


def _offline() -> bool:
    """Use only cached model files when any supported offline flag is set."""
    truthy = {"1", "true", "yes", "on"}
    return any(
        os.environ.get(name, "").strip().lower() in truthy
        for name in ("CHRISTIANMCP_OFFLINE", "HF_HUB_OFFLINE", "TRANSFORMERS_OFFLINE")
    )


def get_embedder():
    """Load the CPU model once and safely reuse it across tool modules."""
    global _model
    if _model is None:
        with _lock:
            if _model is None:
                from sentence_transformers import SentenceTransformer

                _model = SentenceTransformer(
                    MODEL_NAME,
                    device="cpu",
                    local_files_only=_offline(),
                )
    return _model


def preload_embedder():
    """Eagerly initialize the shared model; useful before MCP event loops."""
    return get_embedder()