import json
import mlflow as mlf
from mlflow.tracking import MlflowClient
import pandas as pd

model_name = "s430705"
model_version = 30
mlf.set_tracking_uri("http://172.17.0.1:5000")
model = mlf.pyfunc.load_model(
    model_uri=f"models:/{model_name}/{model_version}"
)

client = MlflowClient()
models_version = client.search_model_versions("name='s430705'")
input_path = models_version[-1].source

with open(f'{input_path}/input_example.json', 'r') as datafile:
    data = json.load(datafile)['inputs']

input_dictionary = {idx:x for idx, x in enumerate(data)}
input_ex = pd.DataFrame([input_dictionary])
print(model.predict(input_ex))