ChatMessageContent Class

This is the class for chat message response content.

All Chat Completion Services should return an instance of this class as response. Or they can implement their own subclass of this class and return an instance.

Create a ChatMessageContent instance.

Inheritance

KernelContent

ChatMessageContent

Constructor

ChatMessageContent(role: AuthorRole, items: list[AnnotationContent | ImageContent | TextContent | FunctionResultContent | FunctionCallContent | FileReferenceContent | StreamingAnnotationContent | StreamingFileReferenceContent] | None = None, content: str | None = None, inner_content: Any | None = None, name: str | None = None, encoding: str | None = None, finish_reason: FinishReason | None = None, ai_model_id: str | None = None, metadata: dict[str, Any] | None = None, *, content_type: Literal[ContentTypes.CHAT_MESSAGE_CONTENT] = 'message')

Parameters

Name	Description
inner_content	Optional[Any] - The inner content of the response, this should hold all the information from the response so even when not creating a subclass a developer can leverage the full thing. Default value: None
ai_model_id	Optional[str] - The id of the AI model that generated this response. Default value: None
metadata	Dict[str, Any] - Any metadata that should be attached to the response. Default value: None
role Required	ChatRole - The role of the chat message.
content	Optional[str] - The text of the response. Default value: None
encoding	Optional[str] - The encoding of the text. Default value: None
role Required	AuthorRole - The role of the chat message.
items	list[TextContent, StreamingTextContent, FunctionCallContent, FunctionResultContent, ImageContent] The content. Default value: None
content Required	str - The text of the response.
inner_content Required	Optional[Any] - The inner content of the response, this should hold all the information from the response so even when not creating a subclass a developer can leverage the full thing.
name	Optional[str] - The name of the response. Default value: None
encoding Required	Optional[str] - The encoding of the text.
finish_reason	Optional[FinishReason] - The reason the response was finished. Default value: None
ai_model_id Required	Optional[str] - The id of the AI model that generated this response.
metadata Required	Dict[str, Any] - Any metadata that should be attached to the response.
**kwargs Required	Any - Any additional fields to set on the instance.

Keyword-Only Parameters

Name	Description
content_type	Default value: message

Methods

from_element	Create a new instance of ChatMessageContent from an XML element.
to_dict	Serialize the ChatMessageContent to a dictionary.
to_element	Convert the ChatMessageContent to an XML Element.
to_prompt	Convert the ChatMessageContent to a prompt.

from_element

Create a new instance of ChatMessageContent from an XML element.

from_element(element: Element) -> ChatMessageContent

Parameters

Name	Description
element Required	Element - The XML Element to create the ChatMessageContent from.

Returns

Type	Description
	ChatMessageContent - The new instance of ChatMessageContent or a subclass.

to_dict

Serialize the ChatMessageContent to a dictionary.

to_dict(role_key: str = 'role', content_key: str = 'content') -> dict[str, Any]

Parameters

Name	Description
role_key	Default value: role
content_key	Default value: content

Returns

Type	Description
	dict - The dictionary representing the ChatMessageContent.

to_element

Convert the ChatMessageContent to an XML Element.

to_element() -> Element

Parameters

Name	Description
root_key Required	str - The key to use for the root of the XML Element.

Returns

Type	Description
	Element - The XML Element representing the ChatMessageContent.

to_prompt

Convert the ChatMessageContent to a prompt.

to_prompt() -> str

Returns

Type	Description
	str - The prompt from the ChatMessageContent.

Attributes

content

Get the content of the response, will find the first TextContent's text.

model_computed_fields

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'populate_by_name': True, 'validate_assignment': True}

model_fields

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.fields from Pydantic V1.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'ai_model_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'content_type': FieldInfo(annotation=Literal[<ContentTypes.CHAT_MESSAGE_CONTENT: 'message'>], required=False, default='message', init=False), 'encoding': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'finish_reason': FieldInfo(annotation=Union[FinishReason, NoneType], required=False, default=None), 'inner_content': FieldInfo(annotation=Union[Any, NoneType], required=False, default=None), 'items': FieldInfo(annotation=list[Annotated[Union[AnnotationContent, ImageContent, TextContent, FunctionResultContent, FunctionCallContent, FileReferenceContent, StreamingAnnotationContent, StreamingFileReferenceContent], FieldInfo(annotation=NoneType, required=True, discriminator='content_type')]], required=False, default_factory=list), 'metadata': FieldInfo(annotation=dict[str, Any], required=False, default_factory=dict), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'role': FieldInfo(annotation=AuthorRole, required=True)}

ai_model_id

ai_model_id: str | None

content_type

content_type: Literal[ContentTypes.CHAT_MESSAGE_CONTENT]

encoding

encoding: str | None

finish_reason

finish_reason: FinishReason | None

inner_content

inner_content: Any | None

items

items: list[Annotated[AnnotationContent | ImageContent | TextContent | FunctionResultContent | FunctionCallContent | FileReferenceContent | StreamingAnnotationContent | StreamingFileReferenceContent, FieldInfo(annotation=NoneType, required=True, discriminator='content_type')]]

metadata

metadata: dict[str, Any]

name

name: str | None

role

role: AuthorRole

tag

tag: ClassVar[str] = 'message'