"""Call out to Sagemaker inference endpoint.
        Args:
            prompt: The prompt to pass into the model.
            stop: Optional list of stop words to use when generating.
        Returns:
            The string generated by the model.
        Example:
            .. code-block:: python
                response = se("Tell me a joke.")
        """
        _model_kwargs = self.model_kwargs or {}
        _model_kwargs = {**_model_kwargs, **kwargs}
        _endpoint_kwargs = self.endpoint_kwargs or {}
        body = self.content_handler.transform_input(prompt, _model_kwargs)
        content_type = self.content_handler.content_type
        accepts = self.content_handler.accepts
        # send request
        try:
            response = self.client.invoke_endpoint(
                EndpointName=self.endpoint_name,
                Body=body,
                ContentType=content_type,
                Accept=accepts,
                **_endpoint_kwargs,
            )
        except Exception as e:
            raise ValueError(f"Error raised by inference endpoint: {e}")
        text = self.content_handler.transform_output(response["Body"])
        if stop is not None:
            # This is a bit hacky, but I can't figure out a better way to enforce
            # stop tokens when making calls to the sagemaker endpoint.
            text = enforce_stop_tokens(text, stop)
        return text