aymara_ai.types.eval#
Attributes#
Classes#
!!! abstract "Usage Documentation" |
Module Contents#
- aymara_ai.types.eval.GroundTruth: typing_extensions.TypeAlias#
- class aymara_ai.types.eval.Eval(/, **data)[source]#
Bases:
aymara_ai._models.BaseModel- !!! abstract “Usage Documentation”
[Models](../concepts/models.md)
A base class for creating Pydantic models.
- Parameters:
data (Any)
- __class_vars__#
The names of the class variables defined on the model.
- __private_attributes__#
Metadata about the private attributes of the model.
- __signature__#
The synthesized __init__ [Signature][inspect.Signature] of the model.
- __pydantic_complete__#
Whether model building is completed, or if there are still undefined fields.
- __pydantic_core_schema__#
The core schema of the model.
- __pydantic_custom_init__#
Whether the model has a custom __init__ function.
- __pydantic_decorators__#
Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
- __pydantic_generic_metadata__#
Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.
- __pydantic_parent_namespace__#
Parent namespace of the model, used for automatic rebuilding of models.
- __pydantic_post_init__#
The name of the post-init method for the model, if defined.
- __pydantic_root_model__#
Whether the model is a [RootModel][pydantic.root_model.RootModel].
- __pydantic_serializer__#
The pydantic-core SchemaSerializer used to dump instances of the model.
- __pydantic_validator__#
The pydantic-core SchemaValidator used to validate instances of the model.
- __pydantic_fields__#
A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
- __pydantic_computed_fields__#
A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
- __pydantic_extra__#
A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.
- __pydantic_fields_set__#
The names of fields explicitly set during instantiation.
- __pydantic_private__#
Values of private attributes set on the model instance.
- ai_description: str#
Description of the AI under evaluation.
- eval_type: str#
Type of the eval (safety, accuracy, etc.)
- ai_instructions: str | None = None#
Instructions the AI should follow.
- created_at: datetime.datetime | None = None#
Timestamp when the eval was created.
- eval_instructions: str | None = None#
Additional instructions for the eval, if any.
- eval_uuid: str | None = None#
Unique identifier for the evaluation.
- ground_truth: GroundTruth | None = None#
Ground truth data or reference file, if any.
- is_jailbreak: bool | None = None#
Indicates if the eval is a jailbreak test.
- is_sandbox: bool | None = None#
Indicates if the eval results are sandboxed.
- language: str | None = None#
“en”).
- Type:
Language code for the eval (default
- modality: aymara_ai.types.shared.content_type.ContentType | None = None#
Content type for AI interactions.
- name: str | None = None#
Name of the evaluation.
- num_prompts: int | None = None#
50).
- Type:
Number of prompts/questions in the eval (default
- prompt_examples: List[aymara_ai.types.prompt_example.PromptExample] | None = None#
List of example prompts for the eval.
- status: aymara_ai.types.shared.status.Status | None = None#
Resource status.
- updated_at: datetime.datetime | None = None#
Timestamp when the eval was last updated.
- workspace_uuid: str | None = None#
UUID of the associated workspace, if any.