chore: initial public snapshot for github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/azure/completion/transformation.py

@@ -0,0 +1,53 @@
+from typing import Optional, Union
+
+from ...openai.completion.transformation import OpenAITextCompletionConfig
+
+
+class AzureOpenAITextConfig(OpenAITextCompletionConfig):
+    """
+    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.
+    """
+
+    def __init__(
+        self,
+        frequency_penalty: Optional[int] = None,
+        logit_bias: Optional[dict] = None,
+        max_tokens: Optional[int] = None,
+        n: Optional[int] = None,
+        presence_penalty: Optional[int] = None,
+        stop: Optional[Union[str, list]] = None,
+        temperature: Optional[int] = None,
+        top_p: Optional[int] = None,
+    ) -> None:
+        super().__init__(
+            frequency_penalty=frequency_penalty,
+            logit_bias=logit_bias,
+            max_tokens=max_tokens,
+            n=n,
+            presence_penalty=presence_penalty,
+            stop=stop,
+            temperature=temperature,
+            top_p=top_p,
+        )