from typing import  Dict, List, Any
from transformers import AutoProcessor, MarkupLMModel


class EndpointHandler():
    def __init__(self, path=""):
        self.processor = AutoProcessor.from_pretrained("microsoft/markuplm-large")
        self.model = MarkupLMModel.from_pretrained("microsoft/markuplm-large")


    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.
        """
        #print(data)
        inputs = data.pop("inputs", data)
        encoding = self.processor(inputs, return_tensors="pt")
        output = self.model(**encoding)
        return {"last_hidden_state": output.last_hidden_state[0].tolist(),
                "pooler_output": output.pooler_output[0].tolist()}