code: 
  import os
  import tempfile
  import logging
  from azureml.core.model import Model
  import pickle
  import pandas as pd
  from azureml.core import Run
  import os
  import mlflow
  
  def init():
      global model
      model_dir =os.getenv('AZUREML_MODEL_DIR')
      model_file = os.listdir(model_dir)[0]
      model_path = os.path.join(os.getenv('AZUREML_MODEL_DIR'), model_file)
      model = mlflow.sklearn.load_model(model_path)
  
  def run(mini_batch):
      print(f"run method start: {__file__}, run({mini_batch})")
      resultList = []
  
      
      # Set up logging
  
      for batch in mini_batch:
          # prepare each image
          data = pd.read_json(batch)
          predictions = model.predict(data)
          data["prediction"] =predictions
          resultList.append(data)
      result = pd.concat(resultList)
  
      return result
  
apis: pandas.concat pandas.read_json