# File : app/embeddings/embedder.py
# Purpose : Sentence transformer embedding model singleton

from sentence_transformers import SentenceTransformer
from app.config import get_settings
from functools import lru_cache

settings = get_settings()


@lru_cache()
def get_embedder() -> SentenceTransformer:
    print(f"[EMBEDDER] Loading model: {settings.embedding_model}")
    model = SentenceTransformer(settings.embedding_model)
    print("[EMBEDDER] Model loaded successfully")
    return model


def embed_query(query: str) -> list:
    model = get_embedder()
    return model.encode(query, normalize_embeddings=True).tolist()