ExtraBody Class
Extra body for the Azure Chat Completion endpoint.
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- Inheritance
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ExtraBody
Constructor
ExtraBody(*, data_sources: list[Annotated[AzureAISearchDataSource | AzureCosmosDBDataSource, FieldInfo(annotation=NoneType, required=True, discriminator='type')]] | None = None, input_language: str | None = None, output_language: str | None = None)
Keyword-Only Parameters
Name | Description |
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data_sources
Required
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input_language
Required
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output_language
Required
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Attributes
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]] = {'data_sources': FieldInfo(annotation=Union[list[Annotated[Union[AzureAISearchDataSource, AzureCosmosDBDataSource], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], NoneType], required=False, default=None), 'input_language': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias_priority=2, serialization_alias='inputLanguage'), 'output_language': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias_priority=2, serialization_alias='outputLanguage')}
data_sources
data_sources: list[Annotated[AzureAISearchDataSource | AzureCosmosDBDataSource, FieldInfo(annotation=NoneType, required=True, discriminator='type')]] | None
input_language
input_language: str | None
output_language
output_language: str | None