"""Encodage des requêtes en texte libre avec all-MiniLM-L6-v2 (optionnel, chargé paresseusement)."""
from __future__ import annotations

import os
import threading

MODEL_NAME = os.environ.get("EMBED_MODEL", "all-MiniLM-L6-v2")
_model = None
_state = "idle"
_lock = threading.Lock()


class Unavailable(Exception):
    pass


def state() -> str:
    return _state


def _load():
    global _model, _state
    with _lock:
        if _model is not None:
            return _model
        try:
            _state = "loading"
            from sentence_transformers import SentenceTransformer  # type: ignore
            _model = SentenceTransformer(MODEL_NAME)
            _state = "ready"
        except Exception as e:  # noqa: BLE001
            _state = f"unavailable: {type(e).__name__}"
            raise Unavailable("Recherche sémantique indisponible sur ce serveur (paquet sentence-transformers absent ou modèle non téléchargé). "
                              "Utilisez /projects?q= ou /projects/{id}/similar.") from e
        return _model


def encode(text: str):
    m = _load()
    return m.encode([text], normalize_embeddings=True)[0]


def preload():
    threading.Thread(target=lambda: _safe(_load), daemon=True).start()


def _safe(f):
    try:
        f()
    except Exception:
        pass


if os.environ.get("SEMANTIC_PRELOAD", "1") == "1":
    preload()