import mlflow
import numpy as np
import json

logged_model = '/mlruns/14/80fe21a0804844088147d15a3cebb3e5/artifacts/lego-model'

# Load model as a PyFuncModel.
loaded_model = mlflow.pyfunc.load_model(logged_model)

with open(f'{loaded_model}/input_example.json') as f:
    input_example_data = json.load(f)

    # Predictions
    print(f'input: {input_example_data}')
    print(f'predictions: {loaded_model.predict(input_example_data)}')