AIModelDetails

class openapi_client.models.ai_model_details.AIModelDetails(**data)

Bases: BaseModel

model_id: Optional[StrictStr]

model_name: Optional[StrictStr]

model_version: Optional[StrictStr]

model_token_limit: Optional[StrictStr]

model_arn: Optional[StrictStr]

model_status: Optional[StrictStr]

provider_name: Optional[StrictStr]

model_status_message: Optional[StrictStr]

model_type: Optional[StrictStr]

model_description: Optional[StrictStr]

model_parameters: Optional[Dict[str, Any]]

model_traits: Optional[StrictStr]

input_modalities: Optional[List[StrictStr]]

output_modalities: Optional[List[StrictStr]]

inference_types_supported: Optional[List[StrictStr]]

last_modified_time: Optional[StrictStr]

last_modified_by: Optional[StrictStr]

default_inference_type: Optional[StrictStr]

inference_profile_details: Optional[Dict[str, Any]]

components: Optional[List[ComponentBasicDetails]]

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()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of AIModelDetails from a JSON string

Return type:

Optional[Self]

to_dict()

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)

Create an instance of AIModelDetails from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'components': FieldInfo(annotation=Union[List[ComponentBasicDetails], NoneType], required=False, alias='Components', alias_priority=2), 'default_inference_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DefaultInferenceType', alias_priority=2), 'inference_profile_details': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, alias='InferenceProfileDetails', alias_priority=2), 'inference_types_supported': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='InferenceTypesSupported', alias_priority=2), 'input_modalities': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='InputModalities', alias_priority=2), '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_parameters': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, alias='ModelParameters', 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