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(chore) linting fix

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ishaan-jaff 2023-11-29 19:58:10 -08:00
parent a9fdae0d23
commit 4ed5b3b46d
2 changed files with 4 additions and 4 deletions
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2
litellm/llms/azure.py
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@ -368,7 +368,7 @@ class AzureChatCompletion(BaseLLM):
) )
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response, response_type="embedding") return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response, response_type="embedding") # type: ignore
except AzureOpenAIError as e: except AzureOpenAIError as e:
exception_mapping_worked = True exception_mapping_worked = True
raise e raise e

6
litellm/llms/openai.py
View file

@ -339,7 +339,7 @@ class OpenAIChatCompletion(BaseLLM):
openai_aclient = AsyncOpenAI(api_key=api_key, base_url=api_base, http_client=litellm.aclient_session, timeout=timeout, max_retries=max_retries) openai_aclient = AsyncOpenAI(api_key=api_key, base_url=api_base, http_client=litellm.aclient_session, timeout=timeout, max_retries=max_retries)
else: else:
openai_aclient = client openai_aclient = client
response = await openai_aclient.embeddings.create(**data) response = await openai_aclient.embeddings.create(**data) # type: ignore
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response, response_type="embedding") return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response, response_type="embedding")
except Exception as e: except Exception as e:
raise e raise e
@ -368,7 +368,7 @@ class OpenAIChatCompletion(BaseLLM):
if not isinstance(max_retries, int): if not isinstance(max_retries, int):
raise OpenAIError(status_code=422, message="max retries must be an int") raise OpenAIError(status_code=422, message="max retries must be an int")
if aembedding == True: if aembedding == True:
response = self.aembedding(data=data, model_response=model_response, api_base=api_base, api_key=api_key, timeout=timeout, client=client, max_retries=max_retries) response = self.aembedding(data=data, model_response=model_response, api_base=api_base, api_key=api_key, timeout=timeout, client=client, max_retries=max_retries) # type: ignore
return response return response
if client is None: if client is None:
openai_client = OpenAI(api_key=api_key, base_url=api_base, http_client=litellm.client_session, timeout=timeout, max_retries=max_retries) openai_client = OpenAI(api_key=api_key, base_url=api_base, http_client=litellm.client_session, timeout=timeout, max_retries=max_retries)
@ -391,7 +391,7 @@ class OpenAIChatCompletion(BaseLLM):
original_response=response, original_response=response,
) )
return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response, response_type="embedding") return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response, response_type="embedding") # type: ignore
except OpenAIError as e: except OpenAIError as e:
exception_mapping_worked = True exception_mapping_worked = True
raise e raise e