o ưi @s0ddlmZmZddlmZGdddeZdS))OptionalUnion)OpenAITextCompletionConfigcseZdZdZ        ddeedeedeedeedeedeeee fd eed eed dffd d Z Z S)AzureOpenAITextConfigaX Reference: https://platform.openai.com/docs/api-reference/chat/create The class `AzureOpenAIConfig` provides configuration for the OpenAI's Chat API interface, for use with Azure. It inherits from `OpenAIConfig`. Below are the parameters:: - `frequency_penalty` (number or null): Defaults to 0. Allows a value between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, thereby minimizing repetition. - `function_call` (string or object): This optional parameter controls how the model calls functions. - `functions` (array): An optional parameter. It is a list of functions for which the model may generate JSON inputs. - `logit_bias` (map): This optional parameter modifies the likelihood of specified tokens appearing in the completion. - `max_tokens` (integer or null): This optional parameter helps to set the maximum number of tokens to generate in the chat completion. - `n` (integer or null): This optional parameter helps to set how many chat completion choices to generate for each input message. - `presence_penalty` (number or null): Defaults to 0. It penalizes new tokens based on if they appear in the text so far, hence increasing the model's likelihood to talk about new topics. - `stop` (string / array / null): Specifies up to 4 sequences where the API will stop generating further tokens. - `temperature` (number or null): Defines the sampling temperature to use, varying between 0 and 2. - `top_p` (number or null): An alternative to sampling with temperature, used for nucleus sampling. Nfrequency_penalty logit_bias max_tokensnpresence_penaltystop temperaturetop_preturnc s tj||||||||ddS)N)rrr r r r r r)super__init__) selfrrr r r r r r __class__c/home/app/Keep/.python/lib/python3.10/site-packages/litellm/llms/azure/completion/transformation.pyr!s  zAzureOpenAITextConfig.__init__)NNNNNNNN) __name__ __module__ __qualname____doc__rintdictrstrlistr __classcell__rrrrrs:  rN)typingrrZ openai.completion.transformationrrrrrrs