GuardRailChatRequestModelParameters

class openapi_client.models.guard_rail_chat_request_model_parameters.GuardRailChatRequestModelParameters(**data)

Bases: BaseModel

max_tokens: Optional[StrictInt]

temperature: Optional[Union[StrictFloat, StrictInt]]

top_p: Optional[Union[StrictFloat, StrictInt]]

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 GuardRailChatRequestModelParameters 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 GuardRailChatRequestModelParameters from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'max_tokens': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='MaxTokens', alias_priority=2, description='Maximum number of tokens to generate.'), 'temperature': FieldInfo(annotation=Union[Annotated[float, Strict(strict=True)], Annotated[int, Strict(strict=True)], NoneType], required=False, alias='Temperature', alias_priority=2, description='Temperature parameter for model generation.'), 'top_p': FieldInfo(annotation=Union[Annotated[float, Strict(strict=True)], Annotated[int, Strict(strict=True)], NoneType], required=False, alias='TopP', alias_priority=2, description='Top-p parameter for model generation.')}

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