aws_sdk_sagemakerruntime/operation/invoke_endpoint_async/

builders.rs

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::invoke_endpoint_async::_invoke_endpoint_async_input::InvokeEndpointAsyncInputBuilder;

pub use crate::operation::invoke_endpoint_async::_invoke_endpoint_async_output::InvokeEndpointAsyncOutputBuilder;

impl crate::operation::invoke_endpoint_async::builders::InvokeEndpointAsyncInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::invoke_endpoint_async::InvokeEndpointAsyncOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::invoke_endpoint_async::InvokeEndpointAsyncError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.invoke_endpoint_async();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `InvokeEndpointAsync`.
///
/// <p>After you deploy a model into production using Amazon SageMaker AI hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint in an asynchronous manner.</p>
/// <p>Inference requests sent to this API are enqueued for asynchronous processing. The processing of the inference request may or may not complete before you receive a response from this API. The response from this API will not contain the result of the inference request but contain information about where you can locate it.</p>
/// <p>Amazon SageMaker AI strips all POST headers except those supported by the API. Amazon SageMaker AI might add additional headers. You should not rely on the behavior of headers outside those enumerated in the request syntax.</p>
/// <p>Calls to <code>InvokeEndpointAsync</code> are authenticated by using Amazon Web Services Signature Version 4. For information, see <a href="https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html">Authenticating Requests (Amazon Web Services Signature Version 4)</a> in the <i>Amazon S3 API Reference</i>.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct InvokeEndpointAsyncFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::invoke_endpoint_async::builders::InvokeEndpointAsyncInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::invoke_endpoint_async::InvokeEndpointAsyncOutput,
        crate::operation::invoke_endpoint_async::InvokeEndpointAsyncError,
    > for InvokeEndpointAsyncFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::invoke_endpoint_async::InvokeEndpointAsyncOutput,
            crate::operation::invoke_endpoint_async::InvokeEndpointAsyncError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl InvokeEndpointAsyncFluentBuilder {
    /// Creates a new `InvokeEndpointAsyncFluentBuilder`.
    pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
        Self {
            handle,
            inner: ::std::default::Default::default(),
            config_override: ::std::option::Option::None,
        }
    }
    /// Access the InvokeEndpointAsync as a reference.
    pub fn as_input(&self) -> &crate::operation::invoke_endpoint_async::builders::InvokeEndpointAsyncInputBuilder {
        &self.inner
    }
    /// Sends the request and returns the response.
    ///
    /// If an error occurs, an `SdkError` will be returned with additional details that
    /// can be matched against.
    ///
    /// By default, any retryable failures will be retried twice. Retry behavior
    /// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
    /// set when configuring the client.
    pub async fn send(
        self,
    ) -> ::std::result::Result<
        crate::operation::invoke_endpoint_async::InvokeEndpointAsyncOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::invoke_endpoint_async::InvokeEndpointAsyncError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let input = self
            .inner
            .build()
            .map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
        let runtime_plugins = crate::operation::invoke_endpoint_async::InvokeEndpointAsync::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::invoke_endpoint_async::InvokeEndpointAsync::orchestrate(&runtime_plugins, input).await
    }

    /// Consumes this builder, creating a customizable operation that can be modified before being sent.
    pub fn customize(
        self,
    ) -> crate::client::customize::CustomizableOperation<
        crate::operation::invoke_endpoint_async::InvokeEndpointAsyncOutput,
        crate::operation::invoke_endpoint_async::InvokeEndpointAsyncError,
        Self,
    > {
        crate::client::customize::CustomizableOperation::new(self)
    }
    pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
        self.set_config_override(::std::option::Option::Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
        self.config_override = config_override;
        self
    }
    /// <p>The name of the endpoint that you specified when you created the endpoint using the <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html">CreateEndpoint</a> API.</p>
    pub fn endpoint_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.endpoint_name(input.into());
        self
    }
    /// <p>The name of the endpoint that you specified when you created the endpoint using the <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html">CreateEndpoint</a> API.</p>
    pub fn set_endpoint_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_endpoint_name(input);
        self
    }
    /// <p>The name of the endpoint that you specified when you created the endpoint using the <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html">CreateEndpoint</a> API.</p>
    pub fn get_endpoint_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_endpoint_name()
    }
    /// <p>The MIME type of the input data in the request body.</p>
    pub fn content_type(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.content_type(input.into());
        self
    }
    /// <p>The MIME type of the input data in the request body.</p>
    pub fn set_content_type(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_content_type(input);
        self
    }
    /// <p>The MIME type of the input data in the request body.</p>
    pub fn get_content_type(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_content_type()
    }
    /// <p>The desired MIME type of the inference response from the model container.</p>
    pub fn accept(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.accept(input.into());
        self
    }
    /// <p>The desired MIME type of the inference response from the model container.</p>
    pub fn set_accept(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_accept(input);
        self
    }
    /// <p>The desired MIME type of the inference response from the model container.</p>
    pub fn get_accept(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_accept()
    }
    /// <p>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 could use this value, for example, to provide an ID that you can use to track a request or to provide other metadata that a service endpoint was programmed to process. The value must consist of no more than 1024 visible US-ASCII characters as specified in <a href="https://datatracker.ietf.org/doc/html/rfc7230#section-3.2.6">Section 3.3.6. Field Value Components</a> of the Hypertext Transfer Protocol (HTTP/1.1).</p>
    /// <p>The code in your model is responsible for setting or updating any custom attributes in the response. If your code does not set this value in the response, an empty value is returned. For example, if a custom attribute represents the trace ID, your model can prepend the custom attribute with <code>Trace ID:</code> in your post-processing function.</p>
    /// <p>This feature is currently supported in the Amazon Web Services SDKs but not in the Amazon SageMaker AI Python SDK.</p>
    pub fn custom_attributes(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.custom_attributes(input.into());
        self
    }
    /// <p>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 could use this value, for example, to provide an ID that you can use to track a request or to provide other metadata that a service endpoint was programmed to process. The value must consist of no more than 1024 visible US-ASCII characters as specified in <a href="https://datatracker.ietf.org/doc/html/rfc7230#section-3.2.6">Section 3.3.6. Field Value Components</a> of the Hypertext Transfer Protocol (HTTP/1.1).</p>
    /// <p>The code in your model is responsible for setting or updating any custom attributes in the response. If your code does not set this value in the response, an empty value is returned. For example, if a custom attribute represents the trace ID, your model can prepend the custom attribute with <code>Trace ID:</code> in your post-processing function.</p>
    /// <p>This feature is currently supported in the Amazon Web Services SDKs but not in the Amazon SageMaker AI Python SDK.</p>
    pub fn set_custom_attributes(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_custom_attributes(input);
        self
    }
    /// <p>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 could use this value, for example, to provide an ID that you can use to track a request or to provide other metadata that a service endpoint was programmed to process. The value must consist of no more than 1024 visible US-ASCII characters as specified in <a href="https://datatracker.ietf.org/doc/html/rfc7230#section-3.2.6">Section 3.3.6. Field Value Components</a> of the Hypertext Transfer Protocol (HTTP/1.1).</p>
    /// <p>The code in your model is responsible for setting or updating any custom attributes in the response. If your code does not set this value in the response, an empty value is returned. For example, if a custom attribute represents the trace ID, your model can prepend the custom attribute with <code>Trace ID:</code> in your post-processing function.</p>
    /// <p>This feature is currently supported in the Amazon Web Services SDKs but not in the Amazon SageMaker AI Python SDK.</p>
    pub fn get_custom_attributes(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_custom_attributes()
    }
    /// <p>The identifier for the inference request. Amazon SageMaker AI will generate an identifier for you if none is specified.</p>
    pub fn inference_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.inference_id(input.into());
        self
    }
    /// <p>The identifier for the inference request. Amazon SageMaker AI will generate an identifier for you if none is specified.</p>
    pub fn set_inference_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_inference_id(input);
        self
    }
    /// <p>The identifier for the inference request. Amazon SageMaker AI will generate an identifier for you if none is specified.</p>
    pub fn get_inference_id(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_inference_id()
    }
    /// <p>The Amazon S3 URI where the inference request payload is stored.</p>
    pub fn input_location(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.input_location(input.into());
        self
    }
    /// <p>The Amazon S3 URI where the inference request payload is stored.</p>
    pub fn set_input_location(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_input_location(input);
        self
    }
    /// <p>The Amazon S3 URI where the inference request payload is stored.</p>
    pub fn get_input_location(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_input_location()
    }
    /// <p>The path extension that is appended to the Amazon S3 output path where the inference response payload is stored.</p>
    pub fn s3_output_path_extension(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.s3_output_path_extension(input.into());
        self
    }
    /// <p>The path extension that is appended to the Amazon S3 output path where the inference response payload is stored.</p>
    pub fn set_s3_output_path_extension(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_s3_output_path_extension(input);
        self
    }
    /// <p>The path extension that is appended to the Amazon S3 output path where the inference response payload is stored.</p>
    pub fn get_s3_output_path_extension(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_s3_output_path_extension()
    }
    /// <p>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.</p>
    pub fn filename(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.filename(input.into());
        self
    }
    /// <p>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.</p>
    pub fn set_filename(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_filename(input);
        self
    }
    /// <p>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.</p>
    pub fn get_filename(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_filename()
    }
    /// <p>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.</p>
    pub fn request_ttl_seconds(mut self, input: i32) -> Self {
        self.inner = self.inner.request_ttl_seconds(input);
        self
    }
    /// <p>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.</p>
    pub fn set_request_ttl_seconds(mut self, input: ::std::option::Option<i32>) -> Self {
        self.inner = self.inner.set_request_ttl_seconds(input);
        self
    }
    /// <p>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.</p>
    pub fn get_request_ttl_seconds(&self) -> &::std::option::Option<i32> {
        self.inner.get_request_ttl_seconds()
    }
    /// <p>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.</p>
    pub fn invocation_timeout_seconds(mut self, input: i32) -> Self {
        self.inner = self.inner.invocation_timeout_seconds(input);
        self
    }
    /// <p>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.</p>
    pub fn set_invocation_timeout_seconds(mut self, input: ::std::option::Option<i32>) -> Self {
        self.inner = self.inner.set_invocation_timeout_seconds(input);
        self
    }
    /// <p>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.</p>
    pub fn get_invocation_timeout_seconds(&self) -> &::std::option::Option<i32> {
        self.inner.get_invocation_timeout_seconds()
    }
    /// <p>Provides inline input data for the inference request, in the format specified in the <code>ContentType</code> request header. Use this parameter to send the request payload directly in the API call instead of uploading it to Amazon S3 and referencing it with <code>InputLocation</code>. The inline payload can be up to 128,000 bytes.</p>
    /// <p><code>Body</code> and <code>InputLocation</code> are mutually exclusive. Provide exactly one of them.</p>
    /// <p>For information about the format of the request body, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/cdf-inference.html">Common Data Formats-Inference</a>.</p>
    pub fn body(mut self, input: ::aws_smithy_types::Blob) -> Self {
        self.inner = self.inner.body(input);
        self
    }
    /// <p>Provides inline input data for the inference request, in the format specified in the <code>ContentType</code> request header. Use this parameter to send the request payload directly in the API call instead of uploading it to Amazon S3 and referencing it with <code>InputLocation</code>. The inline payload can be up to 128,000 bytes.</p>
    /// <p><code>Body</code> and <code>InputLocation</code> are mutually exclusive. Provide exactly one of them.</p>
    /// <p>For information about the format of the request body, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/cdf-inference.html">Common Data Formats-Inference</a>.</p>
    pub fn set_body(mut self, input: ::std::option::Option<::aws_smithy_types::Blob>) -> Self {
        self.inner = self.inner.set_body(input);
        self
    }
    /// <p>Provides inline input data for the inference request, in the format specified in the <code>ContentType</code> request header. Use this parameter to send the request payload directly in the API call instead of uploading it to Amazon S3 and referencing it with <code>InputLocation</code>. The inline payload can be up to 128,000 bytes.</p>
    /// <p><code>Body</code> and <code>InputLocation</code> are mutually exclusive. Provide exactly one of them.</p>
    /// <p>For information about the format of the request body, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/cdf-inference.html">Common Data Formats-Inference</a>.</p>
    pub fn get_body(&self) -> &::std::option::Option<::aws_smithy_types::Blob> {
        self.inner.get_body()
    }
}