code: def test_sync_fallbacks_streaming():
      try:
          model_list = [
              {  # list of model deployments
                  "model_name": "azure/gpt-3.5-turbo",  # openai model name
                  "litellm_params": {  # params for litellm completion/embedding call
                      "model": "azure/chatgpt-v-2",
                      "api_key": "bad-key",
                      "api_version": os.getenv("AZURE_API_VERSION"),
                      "api_base": os.getenv("AZURE_API_BASE"),
                  },
                  "tpm": 240000,
                  "rpm": 1800,
              },
              {  # list of model deployments
                  "model_name": "azure/gpt-3.5-turbo-context-fallback",  # openai model name
                  "litellm_params": {  # params for litellm completion/embedding call
                      "model": "azure/chatgpt-v-2",
                      "api_key": os.getenv("AZURE_API_KEY"),
                      "api_version": os.getenv("AZURE_API_VERSION"),
                      "api_base": os.getenv("AZURE_API_BASE"),
                  },
                  "tpm": 240000,
                  "rpm": 1800,
              },
              {
                  "model_name": "azure/gpt-3.5-turbo",  # openai model name
                  "litellm_params": {  # params for litellm completion/embedding call
                      "model": "azure/chatgpt-functioncalling",
                      "api_key": "bad-key",
                      "api_version": os.getenv("AZURE_API_VERSION"),
                      "api_base": os.getenv("AZURE_API_BASE"),
                  },
                  "tpm": 240000,
                  "rpm": 1800,
              },
              {
                  "model_name": "gpt-3.5-turbo",  # openai model name
                  "litellm_params": {  # params for litellm completion/embedding call
                      "model": "gpt-3.5-turbo",
                      "api_key": os.getenv("OPENAI_API_KEY"),
                  },
                  "tpm": 1000000,
                  "rpm": 9000,
              },
              {
                  "model_name": "gpt-3.5-turbo-16k",  # openai model name
                  "litellm_params": {  # params for litellm completion/embedding call
                      "model": "gpt-3.5-turbo-16k",
                      "api_key": os.getenv("OPENAI_API_KEY"),
                  },
                  "tpm": 1000000,
                  "rpm": 9000,
              },
          ]
  
          litellm.set_verbose = True
          customHandler = MyCustomHandler()
          litellm.callbacks = [customHandler]
          router = Router(
              model_list=model_list,
              fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}],
              context_window_fallbacks=[
                  {
                      "azure/gpt-3.5-turbo-context-fallback": [
                          "gpt-3.5-turbo-16k"
                      ]
                  },
                  {"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]},
              ],
              set_verbose=False,
          )
          response = router.completion(**kwargs, stream=True)
          print(f"response: {response}")
          time.sleep(
              0.05
          )  # allow a delay as success_callbacks are on a separate thread
          assert (
              customHandler.previous_models == 1
          )  # 0 retries, 1 fallback
  
          print("Passed ! Test router_fallbacks: test_sync_fallbacks()")
          router.reset()
      except Exception as e:
          print(e)
  
file_path: litellm/litellm/tests/test_router_fallbacks.py
imports: import sys, os, time
  import traceback, asyncio
  import pytest
  import litellm
  from litellm import Router
  from litellm.integrations.custom_logger import CustomLogger
label_desc: Use image node_id 3 for calling a global function with example usage: test_sync_fallbacks_streaming() without return types