| 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) |