code: def test_openai_embedding():
      try:
          litellm.set_verbose = True
          response = embedding(
              model="text-embedding-ada-002",
              input=[
                  "good morning from litellm",
                  "this is another item",
              ],
              metadata={"anything": "good day"},
          )
          litellm_response = dict(response)
          litellm_response_keys = set(litellm_response.keys())
          litellm_response_keys.discard("_response_ms")
  
          print(litellm_response_keys)
          print("LiteLLM Response\n")
          # print(litellm_response)
  
          # same request with OpenAI 1.0+
          import openai
  
          client = openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"])
          response = client.embeddings.create(
              model="text-embedding-ada-002",
              input=[
                  "good morning from litellm",
                  "this is another item",
              ],
          )
  
          response = dict(response)
          openai_response_keys = set(response.keys())
          print(openai_response_keys)
          assert (
              litellm_response_keys == openai_response_keys
          )  # ENSURE the Keys in litellm response is exactly what the openai package returns
          assert (
              len(litellm_response["data"]) == 2
          )  # expect two embedding responses from litellm_response since input had two
          print(openai_response_keys)
      except Exception as e:
          pytest.fail(f"Error occurred: {e}")
  
imports: import sys, os
  import traceback
  import pytest
  from dotenv import load_dotenv
  import openai
  import litellm
  from litellm import embedding, completion
label_desc: Use image node_id 1 for calling a global function with example usage: test_openai_embedding() without return types