ibm_aigov_facts_client.supporting_classes.factsheet_utils module

class ExternalModelSchemas(input: List[Dict], output: List[Dict] = None)

Bases: object

External model schema

Variables:

input (List[Dict]) – Model input data schema
output (List[Dict]) – (optional) Model output data schema

classmethod from_dict(_dict: Dict) → ExternalModelSchemas: Initialize a DeploymentDetails object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.

class TrainingDataReference(type: str = None, id: str = None, connection: Dict = None, location: Dict = None, schema: Dict = None)

Bases: object

Training data schema definition

Variables:

type (str) – Type of training data reference. It has values as fs, url, data_asset or connection_asset.
id (str) – ID of training data reference.
connection (Dict) – (Optional) Connection details
location (Dict) – (Optional) Location details
schema (Dict) – Model training data schema

If type is fs, the parameters that user needs to input are - location.path If type is url, the parameters that user needs to provide are - training_data_references[].id and connection.url If type is data_asset, then - location.href If type is connection_asset, then location.file_name or location.table_name, connection.href

classmethod from_dict(_dict: Dict) → TrainingDataReference: Initialize a TrainingDataReference object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.

class DeploymentDetails(identifier: str, name: str, deployment_type: str, scoring_endpoint: str = None, description: str = None)

Bases: object

External model deployment details

Variables:

identifier (str) – Deployment identifier specific to providers.
name (str) – Name of the deployment
deployment_type (str) – Deployment type (i.e., online)
scoring_endpoint (str) – Deployment scoring endpoint url.
description (str) – (Optional) Description of the deployment

classmethod from_dict(_dict: Dict) → DeploymentDetails: Initialize a DeploymentDetails object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.

class ModelEntryProps(model_entry_catalog_id: str, asset_id: str = None, model_catalog_id: str = None, model_entry_id: str = None, model_entry_name: str = None, model_entry_desc: str = None, project_id: str = None, space_id: str = None, grc_model_id: str = None)

Bases: object

Model usecase Properties

Variables:

model_entry_catalog_id (str) – Catalog ID where model usecase exist.
asset_id (str) – Published model/asset ID. It is optional for external models ONLY.
model_catalog_id (str) – (Optional) Catalog Id where model exist.
model_entry_id (str) – (Optional) Existing Model usecase to link with.
model_entry_name (str) – (Optional) New model usecase name. Used only when creating new model usecase.
model_entry_description (str) – (Optional) New model usecase description. Used only when creating new model usecase.
project_id (str) – (Optional) Project ID where the model exist.Not applicable for external models.
space_id (str) – (Optional) Space ID where model exist Not applicable for external models.
grc_model_id (str) – (Optional) Openpages model id. Only applicable for CPD environments.

classmethod from_dict(_dict: Dict) → ModelEntryProps: Initialize a ModelEntryProps object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.

class ModelDetails(model_type: str = None, input_type: str = None, algorithm: str = None, label_type: str = None, label_column: str = None, prediction_type: str = None, software_spec: str = None, software_spec_id: str = None, provider: str = None)

Bases: object

External model model details

Variables:

model_type (str) – Value for model type
input_type (str) – Value for inout type
algorithm (str) – Value for algorithm
label_type (str) – Value for label type
label_column (str) – Value for label column
prediction_type (str) – Value for prediction type
software_spec (str) – Value for software_spec
software_spec_id (str) – Value for software_spec_id
provider (str) – Value for provider,Available options are in Provider

classmethod from_dict(_dict: Dict) → ModelDetails: Initialize a ModelDetails object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.

class PromptTemplate(model_version: dict = None, prompt_variables: dict = None, prompt_instruction: str = None, input_prefix: str = None, output_prefix: str = None, structured_examples: dict = None, input: str = None, model_parameters: dict = None)

Bases: object

Details of a PromptTemplate

Variables:

model_version (dict) – (Optional) Model version information and their respective values.
prompt_variables (dict) – (Optional) Values for prompt variables in the format {prompt_variable: value}.
prompt_instruction (str) – (Optional) Instruction for using the prompt.
input_prefix (str) – (Optional) Prefix for input data.
output_prefix (str) – (Optional)Prefix for output data.
structured_examples (dict) – (Optional) Values of examples in the format {example_input: example_output}.
input_prompt (str) – (Optional)Prompt input value.
model_parameters (dict) – (Optional)Model parameters and their respective values.

classmethod from_dict(_dict: Dict) → PromptTemplate: Initialize a ModelDetails object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.

class DetachedPromptTemplate(prompt_id: str, model_id: str, model_provider: str, model_name: str = None, model_url: str = None, prompt_url: str = None, prompt_additional_info: list = None)

Bases: object

Details of a detached prompt template.

Variables:

prompt_id (str) – ID of the external prompt.
model_id (str) – ID of the external model associated with the prompt.
model_provider (str) – Provider of the external model.
model_name (str) – (Optional) Name of the external model (optional).
model_url (str) – URL of the external model (optional).
prompt_url (str) – URL of the external prompt (optional).
prompt_additional_info (dict) – Additional information related to the external prompt (optional).

classmethod from_dict(_dict: Dict) → DetachedPromptTemplate: Initialize a ModelDetails object from a json dictionary.

to_dict() → Dict: Return a json dictionary representing this model.