fix(utils.py): allow text completion input to be either model or engine

This commit is contained in:
Krrish Dholakia 2023-12-27 17:24:02 +05:30
parent ed615e7df4
commit e516cfe9f5
3 changed files with 113 additions and 3 deletions

View file

@ -554,3 +554,93 @@ def test_sync_fallbacks_streaming():
router.reset()
except Exception as e:
print(e)
@pytest.mark.asyncio
async def test_async_fallbacks_max_retries_per_request():
litellm.set_verbose = False
litellm.num_retries_per_request = 0
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,
},
]
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,
)
customHandler = MyCustomHandler()
litellm.callbacks = [customHandler]
user_message = "Hello, how are you?"
messages = [{"content": user_message, "role": "user"}]
try:
try:
response = await router.acompletion(**kwargs, stream=True)
except:
pass
print(f"customHandler.previous_models: {customHandler.previous_models}")
await asyncio.sleep(
0.05
) # allow a delay as success_callbacks are on a separate thread
assert customHandler.previous_models == 0 # 0 retries, 0 fallback
router.reset()
except litellm.Timeout as e:
pass
except Exception as e:
pytest.fail(f"An exception occurred: {e}")
finally:
router.reset()