code: def load_vertex_ai_credentials():
      # Define the path to the vertex_key.json file
      print("loading vertex ai credentials")
      filepath = os.path.dirname(os.path.abspath(__file__))
      vertex_key_path = filepath + "/vertex_key.json"
  
      # Read the existing content of the file or create an empty dictionary
      try:
          with open(vertex_key_path, "r") as file:
              # Read the file content
              print("Read vertexai file path")
              content = file.read()
  
              # If the file is empty or not valid JSON, create an empty dictionary
              if not content or not content.strip():
                  service_account_key_data = {}
              else:
                  # Attempt to load the existing JSON content
                  file.seek(0)
                  service_account_key_data = json.load(file)
      except FileNotFoundError:
          # If the file doesn't exist, create an empty dictionary
          service_account_key_data = {}
  
      # Update the service_account_key_data with environment variables
      private_key_id = os.environ.get("VERTEX_AI_PRIVATE_KEY_ID", "")
      private_key = os.environ.get("VERTEX_AI_PRIVATE_KEY", "")
      private_key = private_key.replace("\\n", "\n")
      service_account_key_data["private_key_id"] = private_key_id
      service_account_key_data["private_key"] = private_key
  
      # Create a temporary file
      with tempfile.NamedTemporaryFile(
          mode="w+", delete=False
      ) as temp_file:
          # Write the updated content to the temporary file
          json.dump(service_account_key_data, temp_file, indent=2)
  
      # Export the temporary file as GOOGLE_APPLICATION_CREDENTIALS
      os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = os.path.abspath(
          temp_file.name
      )
  
file_path: litellm/litellm/tests/test_amazing_vertex_completion.py
imports: import sys, os
  import traceback
  from dotenv import load_dotenv
  import os, io
  import pytest, asyncio
  import litellm
  from litellm import embedding, completion, completion_cost, Timeout, acompletion
  from litellm import RateLimitError
  import json
  import os
  import tempfile
label_desc: Use image node_id 1 for calling a global function with example usage: load_vertex_ai_credentials() without return types