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fix: fix linting errors

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Krrish Dholakia 2023-11-14 21:51:39 -08:00
parent 59eaeba92a
commit efe81032f4
2 changed files with 15 additions and 3 deletions
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10
litellm/llms/azure.py
View file

@ -171,7 +171,7 @@ class AzureChatCompletion(BaseLLM):
## RESPONSE OBJECT ## RESPONSE OBJECT
return convert_to_model_response_object(response_object=response_json, model_response_object=model_response) return convert_to_model_response_object(response_object=response_json, model_response_object=model_response)
except Exception as e: except Exception as e:
if httpx.TimeoutException: if isinstance(e,httpx.TimeoutException):
raise AzureOpenAIError(status_code=500, message="Request Timeout Error") raise AzureOpenAIError(status_code=500, message="Request Timeout Error")
elif response and hasattr(response, "text"): elif response and hasattr(response, "text"):
raise AzureOpenAIError(status_code=500, message=f"{str(e)}\n\nOriginal Response: {response.text}") raise AzureOpenAIError(status_code=500, message=f"{str(e)}\n\nOriginal Response: {response.text}")
@ -186,6 +186,8 @@ class AzureChatCompletion(BaseLLM):
model_response: ModelResponse, model_response: ModelResponse,
model: str model: str
): ):
if self._client_session is None:
self._client_session = self.create_client_session()
with self._client_session.stream( with self._client_session.stream(
url=f"{api_base}", url=f"{api_base}",
json=data, json=data,
@ -207,7 +209,9 @@ class AzureChatCompletion(BaseLLM):
headers: dict, headers: dict,
model_response: ModelResponse, model_response: ModelResponse,
model: str): model: str):
client = httpx.AsyncClient() if self._aclient_session is None:
self._aclient_session = self.create_aclient_session()
client = self._aclient_session
async with client.stream( async with client.stream(
url=f"{api_base}", url=f"{api_base}",
json=data, json=data,
@ -233,6 +237,8 @@ class AzureChatCompletion(BaseLLM):
optional_params=None,): optional_params=None,):
super().embedding() super().embedding()
exception_mapping_worked = False exception_mapping_worked = False
if self._client_session is None:
self._client_session = self.create_client_session()
try: try:
headers = self.validate_environment(api_key, azure_ad_token=azure_ad_token) headers = self.validate_environment(api_key, azure_ad_token=azure_ad_token)
# Ensure api_base ends with a trailing slash # Ensure api_base ends with a trailing slash

8
litellm/llms/openai.py
View file

@ -275,7 +275,7 @@ class OpenAIChatCompletion(BaseLLM):
## RESPONSE OBJECT ## RESPONSE OBJECT
return convert_to_model_response_object(response_object=response_json, model_response_object=model_response) return convert_to_model_response_object(response_object=response_json, model_response_object=model_response)
except Exception as e: except Exception as e:
if httpx.TimeoutException: if isinstance(e, httpx.TimeoutException):
raise OpenAIError(status_code=500, message="Request Timeout Error") raise OpenAIError(status_code=500, message="Request Timeout Error")
if response and hasattr(response, "text"): if response and hasattr(response, "text"):
raise OpenAIError(status_code=500, message=f"{str(e)}\n\nOriginal Response: {response.text}") raise OpenAIError(status_code=500, message=f"{str(e)}\n\nOriginal Response: {response.text}")
@ -290,6 +290,8 @@ class OpenAIChatCompletion(BaseLLM):
model_response: ModelResponse, model_response: ModelResponse,
model: str model: str
): ):
if self._client_session is None:
self._client_session = self.create_client_session()
with self._client_session.stream( with self._client_session.stream(
url=f"{api_base}", # type: ignore url=f"{api_base}", # type: ignore
json=data, json=data,
@ -311,6 +313,8 @@ class OpenAIChatCompletion(BaseLLM):
headers: dict, headers: dict,
model_response: ModelResponse, model_response: ModelResponse,
model: str): model: str):
if self._aclient_session is None:
self._aclient_session = self.create_aclient_session()
async with self._aclient_session.stream( async with self._aclient_session.stream(
url=f"{api_base}", url=f"{api_base}",
json=data, json=data,
@ -334,6 +338,8 @@ class OpenAIChatCompletion(BaseLLM):
optional_params=None,): optional_params=None,):
super().embedding() super().embedding()
exception_mapping_worked = False exception_mapping_worked = False
if self._client_session is None:
self._client_session = self.create_client_session()
try: try:
headers = self.validate_environment(api_key) headers = self.validate_environment(api_key)
api_base = f"{api_base}/embeddings" api_base = f"{api_base}/embeddings"