AIModelsListObject

class openapi_client.models.ai_models_list_object.AIModelsListObject(**data)[source]

Bases: BaseModel

model_id: Optional[StrictStr]
model_name: Optional[StrictStr]
model_arn: Optional[StrictStr]
provider_name: Optional[StrictStr]
model_status: Optional[StrictStr]
model_version: Optional[StrictStr]
model_status_message: Optional[StrictStr]
model_token_limit: Optional[StrictStr]
model_type: Optional[StrictStr]
model_traits: Optional[StrictStr]
model_description: Optional[StrictStr]
last_modified_time: Optional[StrictStr]
last_modified_by: Optional[StrictStr]
output_modalities: Optional[List[StrictStr]]
model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'validate_assignment': True}

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

to_str()[source]

Returns the string representation of the model using alias

Return type:

str

to_json()[source]

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)[source]

Create an instance of AIModelsListObject from a JSON string

Return type:

Optional[Self]

to_dict()[source]

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

  • None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)[source]

Create an instance of AIModelsListObject from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'last_modified_by': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LastModifiedBy', alias_priority=2), 'last_modified_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LastModifiedTime', alias_priority=2), 'model_arn': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelArn', alias_priority=2), 'model_description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelDescription', alias_priority=2), 'model_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelId', alias_priority=2), 'model_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelName', alias_priority=2), 'model_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelStatus', alias_priority=2), 'model_status_message': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelStatusMessage', alias_priority=2), 'model_token_limit': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelTokenLimit', alias_priority=2), 'model_traits': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelTraits', alias_priority=2), 'model_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelType', alias_priority=2), 'model_version': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelVersion', alias_priority=2), 'output_modalities': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='OutputModalities', alias_priority=2), 'provider_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ProviderName', alias_priority=2)}

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

This replaces Model.__fields__ from Pydantic V1.

model_post_init(__context)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:
  • self (BaseModel) – The BaseModel instance.

  • __context (Any) – The context.

Return type:

None