"""Embedding model wrapper — singleton pattern.

Uses sentence-transformers with all-MiniLM-L6-v2 (384-dim, ~80MB).
Loaded once, reused across all requests.
"""

from sentence_transformers import SentenceTransformer
from config import Config


class Embedder:
    """Thread-safe singleton wrapper for the embedding model."""

    _instance = None

    @classmethod
    def get_instance(cls) -> "Embedder":
        if cls._instance is None:
            cls._instance = cls()
        return cls._instance

    def __init__(self) -> None:
        self.model = SentenceTransformer(Config.EMBEDDING_MODEL)

    def embed(self, text: str) -> list[float]:
        return self.model.encode(text).tolist()

    def embed_batch(self, texts: list[str]) -> list[list[float]]:
        return self.model.encode(texts).tolist()