def __init__(
        self,
        endpoint: str,
        model_name: Optional[str] = DEFAULT_MODEL,
        auth: Dict[str, Any] = None,
        timeout: Optional[float] = DEFAULT_TIMEOUT,
        max_retries: Optional[int] = DEFAULT_MAX_RETRIES,
        embed_batch_size: int = DEFAULT_EMBED_BATCH_SIZE,
        additional_kwargs: Optional[Dict[str, Any]] = None,
        default_headers: Optional[Dict[str, str]] = None,
        callback_manager: Optional[CallbackManager] = None,
        **kwargs: Any,
    ) -> None:
        """
        Initialize the OCIDataScienceEmbedding instance.

        Args:
            endpoint (str): The URI of the endpoint from the deployed model.
            model_name (Optional[str]): The name of the OCI Data Science embedding model to use. Defaults to "odsc-embeddings".
            auth (Optional[Dict[str, Any]]): The authentication dictionary for OCI API requests. Defaults to None.
            timeout (Optional[float]): The timeout setting for the HTTP request in seconds. Defaults to 120.
            max_retries (Optional[int]): The maximum number of retry attempts for the request. Defaults to 5.
            embed_batch_size (int): The batch size for embedding calls. Defaults to DEFAULT_EMBED_BATCH_SIZE.
            additional_kwargs (Optional[Dict[str, Any]]): Additional arguments for the OCI Data Science AI request. Defaults to None.
            default_headers (Optional[Dict[str, str]]): The default headers for API requests. Defaults to None.
            callback_manager (Optional[CallbackManager]): A callback manager for handling events during embedding operations. Defaults to None.
            **kwargs: Additional keyword arguments.

        """
        super().__init__(
            model_name=model_name,
            endpoint=endpoint,
            auth=auth,
            embed_batch_size=embed_batch_size,
            timeout=timeout,
            max_retries=max_retries,
            additional_kwargs=additional_kwargs or {},
            default_headers=default_headers or {},
            callback_manager=callback_manager,
            **kwargs,
        )

        Initialize the OCIDataScienceEmbedding instance.

        Args:
            endpoint (str): The URI of the endpoint from the deployed model.
            model_name (Optional[str]): The name of the OCI Data Science embedding model to use. Defaults to "odsc-embeddings".
            auth (Optional[Dict[str, Any]]): The authentication dictionary for OCI API requests. Defaults to None.
            timeout (Optional[float]): The timeout setting for the HTTP request in seconds. Defaults to 120.
            max_retries (Optional[int]): The maximum number of retry attempts for the request. Defaults to 5.
            embed_batch_size (int): The batch size for embedding calls. Defaults to DEFAULT_EMBED_BATCH_SIZE.
            additional_kwargs (Optional[Dict[str, Any]]): Additional arguments for the OCI Data Science AI request. Defaults to None.
            default_headers (Optional[Dict[str, str]]): The default headers for API requests. Defaults to None.
            callback_manager (Optional[CallbackManager]): A callback manager for handling events during embedding operations. Defaults to None.
            **kwargs: Additional keyword arguments.

        
llama-index-integrations/embeddings/llama-index-embeddings-oci-data-science/llama_index/embeddings/oci_data_science/base.py