code: def parse_config():
      """This function parses the model snapshot from the config.properties file
  
      Returns:
          model_name: The name of the model specified in the config.properties
          inference_address: The inference address in which the inference endpoint is hit
          management_address: The management address in which the model gets registered
          model_store: the path in which the .mar file resides
      """
      separator = "="
      keys = {}
  
      with open(CONFIG_PATH) as f:
          for line in f:
              if separator in line:
                  # Find the name and value by splitting the string
                  name, value = line.split(separator, 1)
  
                  # Assign key value pair to dict
                  # strip() removes white space from the ends of strings
                  keys[name.strip()] = value.strip()
  
      keys["model_snapshot"] = json.loads(keys["model_snapshot"])
      (
          inference_address,
          management_address,
          grpc_inference_port,
          model_store,
      ) = (
          keys["inference_address"],
          keys["management_address"],
          keys["grpc_inference_port"],
          keys["model_store"],
      )
  
      models = keys["model_snapshot"]["models"]
      model_names = []
  
      # Get all the model_names
      for model, value in models.items():
          model_names.append(model)
  
      if not inference_address:
          inference_address = DEFAULT_INFERENCE_ADDRESS
      if not model_names:
          model_names = [DEFAULT_MODEL_NAME]
      if not inference_address:
          inference_address = DEFAULT_INFERENCE_ADDRESS
      if not management_address:
          management_address = DEFAULT_MANAGEMENT_ADDRESS
      inf_splits = inference_address.split(":")
      if not grpc_inference_port:
          grpc_inference_address = (
              inf_splits[1] + ":" + DEFAULT_GRPC_INFERENCE_PORT
          )
      else:
          grpc_inference_address = (
              inf_splits[1] + ":" + grpc_inference_port
          )
      grpc_inference_address = grpc_inference_address.replace("/", "")
      if not model_store:
          model_store = DEFAULT_MODEL_STORE
  
      logging.info(
          "Wrapper : Model names %s, inference address %s, management address %s, grpc_inference_address, %s, model store %s",
          model_names,
          inference_address,
          management_address,
          grpc_inference_address,
          model_store,
      )
  
      return (
          model_names,
          inference_address,
          management_address,
          grpc_inference_address,
          model_store,
      )
  
file_path: serve/kubernetes/kserve/kserve_wrapper/__main__.py
imports: import json
  import logging
  import os
  import kserve
  from kserve.model_server import ModelServer
  from TorchserveModel import TorchserveModel
  from TSModelRepository import TSModelRepository
label_desc: Use image node_id 1 for calling a global function with example usage: parse_config() and returns: model_names,  inference_address,  management_address,  grpc_inference_address,  model_store