code: def test_completion_azure_stream():
      try:
          litellm.set_verbose = False
          messages = [
              {
                  "role": "system",
                  "content": "You are a helpful assistant.",
              },
              {
                  "role": "user",
                  "content": "how does a court case get to the Supreme Court?",
              },
          ]
          response = completion(
              model="azure/chatgpt-v-2",
              messages=messages,
              stream=True,
              max_tokens=50,
          )
          complete_response = ""
          # Add any assertions here to check the response
          for idx, init_chunk in enumerate(response):
              chunk, finished = streaming_format_tests(idx, init_chunk)
              complete_response += chunk
              custom_llm_provider = init_chunk._hidden_params[
                  "custom_llm_provider"
              ]
              print(f"custom_llm_provider: {custom_llm_provider}")
              assert custom_llm_provider == "azure"
              if finished:
                  assert isinstance(
                      init_chunk.choices[0],
                      litellm.utils.StreamingChoices,
                  )
                  break
          if complete_response.strip() == "":
              raise Exception("Empty response received")
      except Exception as e:
          pytest.fail(f"Error occurred: {e}")
  
imports: import sys, os, asyncio
  import traceback
  import time, pytest
  from dotenv import load_dotenv
  import litellm
  from litellm import completion, acompletion, AuthenticationError, BadRequestError, RateLimitError, ModelResponse
label_desc: Use image node_id 7 for calling a global function with example usage: test_completion_azure_stream() without return types