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AWS SDK for Java 1.x API Reference - 1.12.793

We announced the upcoming end-of-support for AWS SDK for Java (v1). We recommend that you migrate to AWS SDK for Java v2. For dates, additional details, and information on how to migrate, please refer to the linked announcement.
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com.amazonaws.services.augmentedairuntime

Class AmazonAugmentedAIRuntimeClient

  • All Implemented Interfaces:
    AmazonAugmentedAIRuntime
    Direct Known Subclasses:
    AmazonAugmentedAIRuntimeAsyncClient


    @ThreadSafe
     @Generated(value="com.amazonaws:aws-java-sdk-code-generator")
    public class AmazonAugmentedAIRuntimeClient
    extends AmazonWebServiceClient
    implements AmazonAugmentedAIRuntime 
    Client for accessing Amazon Augmented AI Runtime. All service calls made using this client are blocking, and will not return until the service call completes.

    Amazon Augmented AI (Amazon A2I) adds the benefit of human judgment to any machine learning application. When an AI application can't evaluate data with a high degree of confidence, human reviewers can take over. This human review is called a human review workflow. To create and start a human review workflow, you need three resources: a worker task template, a flow definition, and a human loop.

    For information about these resources and prerequisites for using Amazon A2I, see Get Started with Amazon Augmented AI in the Amazon SageMaker Developer Guide.

    This API reference includes information about API actions and data types that you can use to interact with Amazon A2I programmatically. Use this guide to:

    • Start a human loop with the StartHumanLoop operation when using Amazon A2I with a custom task type. To learn more about the difference between custom and built-in task types, see Use Task Types . To learn how to start a human loop using this API, see Create and Start a Human Loop for a Custom Task Type in the Amazon SageMaker Developer Guide.

    • Manage your human loops. You can list all human loops that you have created, describe individual human loops, and stop and delete human loops. To learn more, see Monitor and Manage Your Human Loop in the Amazon SageMaker Developer Guide.

    Amazon A2I integrates APIs from various AWS services to create and start human review workflows for those services. To learn how Amazon A2I uses these APIs, see Use APIs in Amazon A2I in the Amazon SageMaker Developer Guide.

    • Method Detail

      • startHumanLoop

        public StartHumanLoopResult startHumanLoop(StartHumanLoopRequest request)

        Starts a human loop, provided that at least one activation condition is met.

        Specified by:
        startHumanLoop in interface AmazonAugmentedAIRuntime
        Parameters:
        startHumanLoopRequest -
        Returns:
        Result of the StartHumanLoop operation returned by the service.
        Throws:
        ValidationException - The request isn't valid. Check the syntax and try again.
        ThrottlingException - You exceeded the maximum number of requests.
        ServiceQuotaExceededException - You exceeded your service quota. Service quotas, also referred to as limits, are the maximum number of service resources or operations for your AWS account. For a list of Amazon A2I service quotes, see Amazon Augmented AI Service Quotes. Delete some resources or request an increase in your service quota. You can request a quota increase using Service Quotas or the AWS Support Center. To request an increase, see AWS Service Quotas in the AWS General Reference.
        InternalServerException - We couldn't process your request because of an issue with the server. Try again later.
        ConflictException - Your request has the same name as another active human loop but has different input data. You cannot start two human loops with the same name and different input data.
        See Also:
        AWS API Documentation
      • getCachedResponseMetadata

        public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
        Returns additional metadata for a previously executed successful, request, typically used for debugging issues where a service isn't acting as expected. This data isn't considered part of the result data returned by an operation, so it's available through this separate, diagnostic interface.

        Response metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing the request.

        Specified by:
        getCachedResponseMetadata in interface AmazonAugmentedAIRuntime
        Parameters:
        request - The originally executed request
        Returns:
        The response metadata for the specified request, or null if none is available.
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