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

mlflow.set_tracking_uri("http://172.17.0.1:5000")
client = MlflowClient()
version = 0
model_name = "s434788"
for mv in client.search_model_versions(f"name='{model_name}'"):
    if int(mv.version) > version:
        version = int(mv.version)

model = mlflow.keras.load_model(
    model_uri=f"models:/{model_name}/{version}"
)

data = pd.read_json('my_model/input_example.json', orient='index')

print(data)
print(model.predict(data))