from sentence_transformers import (
    SentenceTransformer
)


class LegalEmbedder:

    def __init__(
        self,
        model_name: str =
        "BAAI/bge-large-en-v1.5"
    ):

        self.model = (
            SentenceTransformer(
                model_name
            )
        )

    def embed(
        self,
        texts: list[str]
    ):

        return self.model.encode(
            texts,
            normalize_embeddings=True,
            convert_to_numpy=True
        )