export interface InvokeEndpointInput {
    /** Provides input data, in the format specified in the ContentType request header. Amazon SageMaker AI passes all of the data in the body to the model. For information about the format of the request bod */
    Body: string;
    /** The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API. */
    EndpointName: string;
    /** The desired MIME type of the inference response from the model container. */
    Accept?: string;
    /** The MIME type of the input data in the request body. */
    ContentType?: string;
    /** Provides additional information about a request for an inference submitted to a model hosted at an Amazon SageMaker AI endpoint. The information is an opaque value that is forwarded verbatim. You coul */
    CustomAttributes?: string;
    /** An optional JMESPath expression used to override the EnableExplanations parameter of the ClarifyExplainerConfig API. See the EnableExplanations section in the developer guide for more information. */
    EnableExplanations?: string;
    /** If the endpoint hosts one or more inference components, this parameter specifies the name of inference component to invoke. */
    InferenceComponentName?: string;
    /** If you provide a value, it is added to the captured data when you enable data capture on the endpoint. For information about data capture, see Capture Data. */
    InferenceId?: string;
    /** Creates a stateful session or identifies an existing one. You can do one of the following: Create a stateful session by specifying the value NEW_SESSION. Send your request to an existing stateful sess */
    SessionId?: string;
    /** If the endpoint hosts multiple containers and is configured to use direct invocation, this parameter specifies the host name of the container to invoke. */
    TargetContainerHostname?: string;
    /** The model to request for inference when invoking a multi-model endpoint. */
    TargetModel?: string;
    /** Specify the production variant to send the inference request to when invoking an endpoint that is running two or more variants. Note that this parameter overrides the default behavior for the endpoint */
    TargetVariant?: string;
}
export interface InvokeEndpointAsyncInput {
    /** The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API. */
    EndpointName: string;
    /** The Amazon S3 URI where the inference request payload is stored. */
    InputLocation: string;
    /** The desired MIME type of the inference response from the model container. */
    Accept?: string;
    /** The MIME type of the input data in the request body. */
    ContentType?: string;
    /** Provides additional information about a request for an inference submitted to a model hosted at an Amazon SageMaker AI endpoint. The information is an opaque value that is forwarded verbatim. You coul */
    CustomAttributes?: string;
    /** The filename for the inference response payload stored in Amazon S3. If not specified, Amazon SageMaker AI generates a filename based on the inference ID. */
    Filename?: string;
    /** The identifier for the inference request. Amazon SageMaker AI will generate an identifier for you if none is specified. */
    InferenceId?: string;
    /** Maximum amount of time in seconds a request can be processed before it is marked as expired. The default is 15 minutes, or 900 seconds. */
    InvocationTimeoutSeconds?: number;
    /** Maximum age in seconds a request can be in the queue before it is marked as expired. The default is 6 hours, or 21,600 seconds. */
    RequestTTLSeconds?: number;
    /** The path extension that is appended to the Amazon S3 output path where the inference response payload is stored. */
    S3OutputPathExtension?: string;
}
export interface InvokeEndpointWithResponseStreamInput {
    /** Provides input data, in the format specified in the ContentType request header. Amazon SageMaker AI passes all of the data in the body to the model. For information about the format of the request bod */
    Body: string;
    /** The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API. */
    EndpointName: string;
    /** The desired MIME type of the inference response from the model container. */
    Accept?: string;
    /** The MIME type of the input data in the request body. */
    ContentType?: string;
    /** Provides additional information about a request for an inference submitted to a model hosted at an Amazon SageMaker AI endpoint. The information is an opaque value that is forwarded verbatim. You coul */
    CustomAttributes?: string;
    /** If the endpoint hosts one or more inference components, this parameter specifies the name of inference component to invoke for a streaming response. */
    InferenceComponentName?: string;
    /** An identifier that you assign to your request. */
    InferenceId?: string;
    /** The ID of a stateful session to handle your request. You can't create a stateful session by using the InvokeEndpointWithResponseStream action. Instead, you can create one by using the InvokeEndpoint a */
    SessionId?: string;
    /** If the endpoint hosts multiple containers and is configured to use direct invocation, this parameter specifies the host name of the container to invoke. */
    TargetContainerHostname?: string;
    /** Specify the production variant to send the inference request to when invoking an endpoint that is running two or more variants. Note that this parameter overrides the default behavior for the endpoint */
    TargetVariant?: string;
}
/** SageMaker Runtime service binding for Step Functions SDK integrations. */
export declare class SageMakerRuntime {
    constructor();
    invokeEndpoint<T>(params: InvokeEndpointInput): Promise<T>;
    invokeEndpointAsync<T>(params: InvokeEndpointAsyncInput): Promise<T>;
    invokeEndpointWithResponseStream<T>(params: InvokeEndpointWithResponseStreamInput): Promise<T>;
}
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