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# coding: utf-8 # Copyright (c) 2016, 2024, Oracle and/or its affiliates. All rights reserved. # This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license. # NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20231130 from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401 from oci.decorators import init_model_state_from_kwargs @init_model_state_from_kwargs class LlmInferenceRequest(object): """ The base class for the inference requests. """ #: A constant which can be used with the runtime_type property of a LlmInferenceRequest. #: This constant has a value of "COHERE" RUNTIME_TYPE_COHERE = "COHERE" #: A constant which can be used with the runtime_type property of a LlmInferenceRequest. #: This constant has a value of "LLAMA" RUNTIME_TYPE_LLAMA = "LLAMA" def __init__(self, **kwargs): """ Initializes a new LlmInferenceRequest object with values from keyword arguments. This class has the following subclasses and if you are using this class as input to a service operations then you should favor using a subclass over the base class: * :class:`~oci.generative_ai_inference.models.LlamaLlmInferenceRequest` * :class:`~oci.generative_ai_inference.models.CohereLlmInferenceRequest` The following keyword arguments are supported (corresponding to the getters/setters of this class): :param runtime_type: The value to assign to the runtime_type property of this LlmInferenceRequest. Allowed values for this property are: "COHERE", "LLAMA" :type runtime_type: str """ self.swagger_types = { 'runtime_type': 'str' } self.attribute_map = { 'runtime_type': 'runtimeType' } self._runtime_type = None @staticmethod def get_subtype(object_dictionary): """ Given the hash representation of a subtype of this class, use the info in the hash to return the class of the subtype. """ type = object_dictionary['runtimeType'] if type == 'LLAMA': return 'LlamaLlmInferenceRequest' if type == 'COHERE': return 'CohereLlmInferenceRequest' else: return 'LlmInferenceRequest' @property def runtime_type(self): """ **[Required]** Gets the runtime_type of this LlmInferenceRequest. The runtime of the provided model. Allowed values for this property are: "COHERE", "LLAMA" :return: The runtime_type of this LlmInferenceRequest. :rtype: str """ return self._runtime_type @runtime_type.setter def runtime_type(self, runtime_type): """ Sets the runtime_type of this LlmInferenceRequest. The runtime of the provided model. :param runtime_type: The runtime_type of this LlmInferenceRequest. :type: str """ allowed_values = ["COHERE", "LLAMA"] if not value_allowed_none_or_none_sentinel(runtime_type, allowed_values): raise ValueError( f"Invalid value for `runtime_type`, must be None or one of {allowed_values}" ) self._runtime_type = runtime_type def __repr__(self): return formatted_flat_dict(self) def __eq__(self, other): if other is None: return False return self.__dict__ == other.__dict__ def __ne__(self, other): return not self == other
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