from sentence_transformers import SentenceTransformer


class EmbeddingModelService:

    def __init__(self):

        self.model = SentenceTransformer(
            "BAAI/bge-small-en-v1.5"
        )

    def encode(
        self,
        text: str,
    ) -> list[float]:

        return self.model.encode(
            text,
            normalize_embeddings=True,
        ).tolist()