Amazon Augmented AI Runtime¶

Description¶

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 start_human_loop 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.

Usage¶

augmentedairuntime(
  config = list(),
  credentials = list(),
  endpoint = NULL,
  region = NULL
)

Arguments¶

• config

  Optional configuration of credentials, endpoint, and/or region.

  • credentials:
    • creds:
      • access_key_id: AWS access key ID
      • secret_access_key: AWS secret access key
      • session_token: AWS temporary session token
    • profile: The name of a profile to use. If not given, then the default profile is used.
    • anonymous: Set anonymous credentials.
  • endpoint: The complete URL to use for the constructed client.
  • region: The AWS Region used in instantiating the client.
  • close_connection: Immediately close all HTTP connections.
  • timeout: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.
  • s3_force_path_style: Set this to true to force the request to use path-style addressing, i.e. http://s3.amazonaws.com/BUCKET/KEY.
  • sts_regional_endpoint: Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html
  • use_dual_stack: Set this to true to use the dualstack (IPv4 and IPv6) endpoint for a service, where available, falling back to the regular endpoint when it isn't. Defaults to the AWS_USE_DUALSTACK_ENDPOINT environment variable when unset.

• credentials

  Optional credentials shorthand for the config parameter

  • creds:
    • access_key_id: AWS access key ID
    • secret_access_key: AWS secret access key
    • session_token: AWS temporary session token
  • profile: The name of a profile to use. If not given, then the default profile is used.
  • anonymous: Set anonymous credentials.

• endpoint

  Optional shorthand for complete URL to use for the constructed client.

• region

  Optional shorthand for AWS Region used in instantiating the client.

Value¶

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax¶

svc <- augmentedairuntime(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string",
    use_dual_stack = "logical"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations¶

Examples¶

svc <- augmentedairuntime()
svc$delete_human_loop(
  Foo = 123
)