Expand 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 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.

Crate Organization

The entry point for most customers will be Client. Client exposes one method for each API offered by the service.

Some APIs require complex or nested arguments. These exist in model.

Lastly, errors that can be returned by the service are contained within error. Error defines a meta error encompassing all possible errors that can be returned by the service.

The other modules within this crate are not required for normal usage.

Modules

Client and fluent builders for calling the service.

Configuration for the service.

Errors that can occur when calling the service.

Input structures for operations.

Base Middleware Stack

Data structures used by operation inputs/outputs.

All operations that this crate can perform.

Output structures for operations.

Paginators for the service

Re-exported types from supporting crates.

Structs

App name that can be configured with an AWS SDK client to become part of the user agent string.

Client for Amazon Augmented AI Runtime

Service config.

AWS SDK Credentials

API Endpoint

The region to send requests to.

Retry configuration for requests.

Enums

All possible error types for this service.

Statics

Crate version number.