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# coding: utf-8 # Copyright (c) 2016, 2026, 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: 20240531 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 LlmCustomization(object): """ Configuration to customize LLM. """ def __init__(self, **kwargs): """ Initializes a new LlmCustomization object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class): :param llm_selection: The value to assign to the llm_selection property of this LlmCustomization. :type llm_selection: oci.generative_ai_agent.models.LlmSelection :param llm_hyper_parameters: The value to assign to the llm_hyper_parameters property of this LlmCustomization. :type llm_hyper_parameters: dict(str, object) :param instruction: The value to assign to the instruction property of this LlmCustomization. :type instruction: str """ self.swagger_types = { 'llm_selection': 'LlmSelection', 'llm_hyper_parameters': 'dict(str, object)', 'instruction': 'str' } self.attribute_map = { 'llm_selection': 'llmSelection', 'llm_hyper_parameters': 'llmHyperParameters', 'instruction': 'instruction' } self._llm_selection = None self._llm_hyper_parameters = None self._instruction = None @property def llm_selection(self): """ Gets the llm_selection of this LlmCustomization. :return: The llm_selection of this LlmCustomization. :rtype: oci.generative_ai_agent.models.LlmSelection """ return self._llm_selection @llm_selection.setter def llm_selection(self, llm_selection): """ Sets the llm_selection of this LlmCustomization. :param llm_selection: The llm_selection of this LlmCustomization. :type: oci.generative_ai_agent.models.LlmSelection """ self._llm_selection = llm_selection @property def llm_hyper_parameters(self): """ Gets the llm_hyper_parameters of this LlmCustomization. Hyper parameters for LLM configuration. Accepts Key-value pairs to configure various hyper parameters. Refer to the guide for examples and the JSON Schema documentation for details on the format. :return: The llm_hyper_parameters of this LlmCustomization. :rtype: dict(str, object) """ return self._llm_hyper_parameters @llm_hyper_parameters.setter def llm_hyper_parameters(self, llm_hyper_parameters): """ Sets the llm_hyper_parameters of this LlmCustomization. Hyper parameters for LLM configuration. Accepts Key-value pairs to configure various hyper parameters. Refer to the guide for examples and the JSON Schema documentation for details on the format. :param llm_hyper_parameters: The llm_hyper_parameters of this LlmCustomization. :type: dict(str, object) """ self._llm_hyper_parameters = llm_hyper_parameters @property def instruction(self): """ Gets the instruction of this LlmCustomization. If specified, the default instruction is replaced with provided instruction. :return: The instruction of this LlmCustomization. :rtype: str """ return self._instruction @instruction.setter def instruction(self, instruction): """ Sets the instruction of this LlmCustomization. If specified, the default instruction is replaced with provided instruction. :param instruction: The instruction of this LlmCustomization. :type: str """ self._instruction = instruction 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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