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from typing import Dict, List, Union
import os
import joblib
import numpy as np
features = ["fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides", "free_sulfur_dioxide", "total_sulfur_dioxide", "density", "pH", "sulphates", "alcohol"]
class EndpointHandler():
def __init__(self, path=""):
self.model = joblib.load("sklearn_model.joblib")
def __call__(
self, inputs: Dict[str, Dict[str, List[Union[str, float]]]]
) -> List[Union[str, float]]:
"""
Args:
inputs (:obj:`dict`):
a dictionary containing a key 'data' mapping to a dict in which
the values represent each column.
Return:
A :obj:`list` of floats or strings: The classification output for each row.
"""
data = inputs["data"]
X = np.array([data[i] for i in features])
X = np.transpose(X, (1, 0))
return self.model.predict(X)
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