JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI - Amazon SageMaker

JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI

The HumanLoopActivationConditions is an input parameter of the CreateFlowDefinition API. This parameter is a JSON-formatted string. The JSON models the conditions under which a human loop is created when those conditions are evaluated against the response from an integrating AI service API (such as Rekognition.DetectModerationLabels or Textract.AnalyzeDocument). This response is referred to as an inference. For example, Amazon Rekognition sends an inference of a moderation label with an associated confidence score. In this example, the inference is the model's best estimate of the appropriate label for an image. For Amazon Textract, inference is made on the association between blocks of text (key-value pairs), such as the association between Name: and Sue in a form as well as content within a block of text, or word block, such as 'Name'.

The following is the schema for the JSON. At the top level, the HumanLoopActivationConditions has a JSON array, Conditions. Each member of this array is an independent condition that, if evaluated to true, results in Amazon A2I creating a human loop. Each such independent condition can be a simple condition or a complex condition. A simple condition has the following attributes:

  • ConditionType: This attribute identifies the type of condition. Each AWS AI service API that integrates with Amazon A2I defines its own set of allowed ConditionTypes.

    • Rekognition DetectModerationLabels – This API supports the ModerationLabelConfidenceCheck and Sampling ConditionType values.

    • Textract AnalyzeDocument – This API supports the ImportantFormKeyConfidenceCheck, MissingImportantFormKey, and Sampling ConditionType values.

  • ConditionParameters – This is a JSON object that parameterizes the condition. The set of allowed attributes of this object is dependent on the value of the ConditionType. Each ConditionType defines its own set of ConditionParameters.

A member of the Conditions array can model a complex condition. This is accomplished by logically connecting simple conditions using the And and Or logical operators and nesting the underlying simple conditions. Up to two levels of nesting are supported.

{ "$schema": "http://json-schema.org/draft-07/schema#", "definitions": { "Condition": { "type": "object", "properties": { "ConditionType": { "type": "string" }, "ConditionParameters": { "type": "object" } }, "required": [ "ConditionType" ] }, "OrConditionArray": { "type": "object", "properties": { "Or": { "type": "array", "minItems": 2, "items": { "$ref": "#/definitions/ComplexCondition" } } } }, "AndConditionArray": { "type": "object", "properties": { "And": { "type": "array", "minItems": 2, "items": { "$ref": "#/definitions/ComplexCondition" } } } }, "ComplexCondition": { "anyOf": [ { "$ref": "#/definitions/Condition" }, { "$ref": "#/definitions/OrConditionArray" }, { "$ref": "#/definitions/AndConditionArray" } ] } }, "type": "object", "properties": { "Conditions": { "type": "array", "items": { "$ref": "#/definitions/ComplexCondition" } } } }

Human loop activation conditions aren't available for human review workflows that are integrated with custom task types. The HumanLoopActivationConditions parameter is disabled for custom task types.