handler.py

from typing import  Dict, List, Any

from sentence_transformers import SentenceTransformer


class EndpointHandler():
    def __init__(self, path=""):

        model_name = "all-MiniLM-L6-v2"

        self.model = SentenceTransformer(
            model_name,
            backend="onnx",
            model_kwargs={
                "file_name": "model_O3.onnx",
                "provider": "CUDAExecutionProvider",
            }
        )



    def __call__(self, data: Any) -> List[List[Dict[str, float]]]:
        """
        Args:
            data (:obj:):
                includes the input data and the parameters for the inference.
        Return:
            A :obj:`list`:. The object returned should be a list of one list like [[{"label": 0.9939950108528137}]] containing :
                - "label": A string representing what the label/class is. There can be multiple labels.
                - "score": A score between 0 and 1 describing how confident the model is for this label/class.
        """
        inputs = data.pop("inputs", data)

        prediction = self.model.encode(inputs)

        return prediction.tolist()