from typing import Dict, List, Any # from sentence_transformers import SentenceTransformer class EndpointHandler(): def __init__(self, path="NV-Embed-v2"): # Preload all the elements you are going to need at inference. # pseudo: # self.model= load_model(path) self.embedding_model = SentenceTransformer(path) def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: """ data args: inputs (:obj: `str` | `PIL.Image` | `np.array`) kwargs Return: A :obj:`list` | `dict`: will be serialized and returned """ # embeddings = self.embedding_model.encode(data) # return embeddings # pseudo # self.model(input)