from sentence_transformers import SentenceTransformer
from typing import Union, List, Dict

class EndpointHandler:
    """
    A handler class to summarize CVs or job vacancies using a pre-trained language model.
    """

    def __init__(self, path: str = ""):
        """
        Initializes the EndpointHandler with model and tokenizer.

        :param path: Optional path parameter, default is an empty string.
        """
        self.sbert = SentenceTransformer(
            "jinaai/jina-embeddings-v3",
            trust_remote_code=True
        )

    def __call__(self, data: Dict[str, Union[str, List[str]]]) -> List[str]:
        """
        Summarizes the input CV(s) or job vacancies into bullet points.

        :param data: A dictionary with "inputs" and "type" keys.
        :return: A list of summarized strings.
        """

        # Extract inputs and type
        texts = data.pop("inputs")
        return self.sbert.encode(
            texts,
            task="retrieval.query"
        ).tolist()