File: //usr/lib/mysqlsh/lib/python3.8/site-packages/oci/generative_ai_inference/models/message.py
# coding: utf-8
# Copyright (c) 2016, 2025, 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 Message(object):
"""
A message that represents a single chat dialog.
"""
#: A constant which can be used with the role property of a Message.
#: This constant has a value of "SYSTEM"
ROLE_SYSTEM = "SYSTEM"
#: A constant which can be used with the role property of a Message.
#: This constant has a value of "USER"
ROLE_USER = "USER"
#: A constant which can be used with the role property of a Message.
#: This constant has a value of "ASSISTANT"
ROLE_ASSISTANT = "ASSISTANT"
#: A constant which can be used with the role property of a Message.
#: This constant has a value of "TOOL"
ROLE_TOOL = "TOOL"
def __init__(self, **kwargs):
"""
Initializes a new Message 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.SystemMessage`
* :class:`~oci.generative_ai_inference.models.AssistantMessage`
* :class:`~oci.generative_ai_inference.models.UserMessage`
* :class:`~oci.generative_ai_inference.models.ToolMessage`
The following keyword arguments are supported (corresponding to the getters/setters of this class):
:param role:
The value to assign to the role property of this Message.
Allowed values for this property are: "SYSTEM", "USER", "ASSISTANT", "TOOL", 'UNKNOWN_ENUM_VALUE'.
Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'.
:type role: str
:param content:
The value to assign to the content property of this Message.
:type content: list[oci.generative_ai_inference.models.ChatContent]
"""
self.swagger_types = {
'role': 'str',
'content': 'list[ChatContent]'
}
self.attribute_map = {
'role': 'role',
'content': 'content'
}
self._role = None
self._content = 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['role']
if type == 'SYSTEM':
return 'SystemMessage'
if type == 'ASSISTANT':
return 'AssistantMessage'
if type == 'USER':
return 'UserMessage'
if type == 'TOOL':
return 'ToolMessage'
else:
return 'Message'
@property
def role(self):
"""
**[Required]** Gets the role of this Message.
Indicates who is writing the current chat message.
Allowed values for this property are: "SYSTEM", "USER", "ASSISTANT", "TOOL", 'UNKNOWN_ENUM_VALUE'.
Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'.
:return: The role of this Message.
:rtype: str
"""
return self._role
@role.setter
def role(self, role):
"""
Sets the role of this Message.
Indicates who is writing the current chat message.
:param role: The role of this Message.
:type: str
"""
allowed_values = ["SYSTEM", "USER", "ASSISTANT", "TOOL"]
if not value_allowed_none_or_none_sentinel(role, allowed_values):
role = 'UNKNOWN_ENUM_VALUE'
self._role = role
@property
def content(self):
"""
Gets the content of this Message.
Contents of the chat message.
:return: The content of this Message.
:rtype: list[oci.generative_ai_inference.models.ChatContent]
"""
return self._content
@content.setter
def content(self, content):
"""
Sets the content of this Message.
Contents of the chat message.
:param content: The content of this Message.
:type: list[oci.generative_ai_inference.models.ChatContent]
"""
self._content = content
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