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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
use std::fmt::Write;
/// See [`InvokeEndpointInput`](crate::input::InvokeEndpointInput)
pub mod invoke_endpoint_input {
/// A builder for [`InvokeEndpointInput`](crate::input::InvokeEndpointInput)
#[non_exhaustive]
#[derive(std::default::Default, std::clone::Clone, std::cmp::PartialEq, std::fmt::Debug)]
pub struct Builder {
pub(crate) endpoint_name: std::option::Option<std::string::String>,
pub(crate) body: std::option::Option<aws_smithy_types::Blob>,
pub(crate) content_type: std::option::Option<std::string::String>,
pub(crate) accept: std::option::Option<std::string::String>,
pub(crate) custom_attributes: std::option::Option<std::string::String>,
pub(crate) target_model: std::option::Option<std::string::String>,
pub(crate) target_variant: std::option::Option<std::string::String>,
pub(crate) target_container_hostname: std::option::Option<std::string::String>,
pub(crate) inference_id: std::option::Option<std::string::String>,
}
impl Builder {
/// <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 Into<std::string::String>) -> Self {
self.endpoint_name = Some(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.endpoint_name = input;
self
}
/// <p>Provides input data, in the format specified in the <code>ContentType</code>
/// request header. Amazon SageMaker passes all of the data in the body to the model. </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.body = Some(input);
self
}
/// <p>Provides input data, in the format specified in the <code>ContentType</code>
/// request header. Amazon SageMaker passes all of the data in the body to the model. </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.body = input;
self
}
/// <p>The MIME type of the input data in the request body.</p>
pub fn content_type(mut self, input: impl Into<std::string::String>) -> Self {
self.content_type = Some(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.content_type = input;
self
}
/// <p>The desired MIME type of the inference in the response.</p>
pub fn accept(mut self, input: impl Into<std::string::String>) -> Self {
self.accept = Some(input.into());
self
}
/// <p>The desired MIME type of the inference in the response.</p>
pub fn set_accept(mut self, input: std::option::Option<std::string::String>) -> Self {
self.accept = input;
self
}
/// <p>Provides additional information about a request for an inference submitted to a model
/// hosted at an Amazon SageMaker 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://tools.ietf.org/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 AWS SDKs but not in the Amazon SageMaker Python
/// SDK.</p>
pub fn custom_attributes(mut self, input: impl Into<std::string::String>) -> Self {
self.custom_attributes = Some(input.into());
self
}
/// <p>Provides additional information about a request for an inference submitted to a model
/// hosted at an Amazon SageMaker 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://tools.ietf.org/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 AWS SDKs but not in the Amazon SageMaker Python
/// SDK.</p>
pub fn set_custom_attributes(
mut self,
input: std::option::Option<std::string::String>,
) -> Self {
self.custom_attributes = input;
self
}
/// <p>The model to request for inference when invoking a multi-model endpoint.</p>
pub fn target_model(mut self, input: impl Into<std::string::String>) -> Self {
self.target_model = Some(input.into());
self
}
/// <p>The model to request for inference when invoking a multi-model endpoint.</p>
pub fn set_target_model(mut self, input: std::option::Option<std::string::String>) -> Self {
self.target_model = input;
self
}
/// <p>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, which is to distribute the invocation traffic based
/// on the variant weights.</p>
/// <p>For information about how to use variant targeting to perform a/b testing, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html">Test models in
/// production</a>
/// </p>
pub fn target_variant(mut self, input: impl Into<std::string::String>) -> Self {
self.target_variant = Some(input.into());
self
}
/// <p>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, which is to distribute the invocation traffic based
/// on the variant weights.</p>
/// <p>For information about how to use variant targeting to perform a/b testing, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html">Test models in
/// production</a>
/// </p>
pub fn set_target_variant(
mut self,
input: std::option::Option<std::string::String>,
) -> Self {
self.target_variant = input;
self
}
/// <p>If the endpoint hosts multiple containers and is configured to use direct invocation,
/// this parameter specifies the host name of the container to invoke.</p>
pub fn target_container_hostname(mut self, input: impl Into<std::string::String>) -> Self {
self.target_container_hostname = Some(input.into());
self
}
/// <p>If the endpoint hosts multiple containers and is configured to use direct invocation,
/// this parameter specifies the host name of the container to invoke.</p>
pub fn set_target_container_hostname(
mut self,
input: std::option::Option<std::string::String>,
) -> Self {
self.target_container_hostname = input;
self
}
/// <p>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 <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html">Capture
/// Data</a>.</p>
pub fn inference_id(mut self, input: impl Into<std::string::String>) -> Self {
self.inference_id = Some(input.into());
self
}
/// <p>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 <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html">Capture
/// Data</a>.</p>
pub fn set_inference_id(mut self, input: std::option::Option<std::string::String>) -> Self {
self.inference_id = input;
self
}
/// Consumes the builder and constructs a [`InvokeEndpointInput`](crate::input::InvokeEndpointInput)
pub fn build(
self,
) -> std::result::Result<
crate::input::InvokeEndpointInput,
aws_smithy_http::operation::BuildError,
> {
Ok(crate::input::InvokeEndpointInput {
endpoint_name: self.endpoint_name,
body: self.body,
content_type: self.content_type,
accept: self.accept,
custom_attributes: self.custom_attributes,
target_model: self.target_model,
target_variant: self.target_variant,
target_container_hostname: self.target_container_hostname,
inference_id: self.inference_id,
})
}
}
}
#[doc(hidden)]
pub type InvokeEndpointInputOperationOutputAlias = crate::operation::InvokeEndpoint;
#[doc(hidden)]
pub type InvokeEndpointInputOperationRetryAlias = aws_http::AwsErrorRetryPolicy;
impl InvokeEndpointInput {
/// Consumes the builder and constructs an Operation<[`InvokeEndpoint`](crate::operation::InvokeEndpoint)>
#[allow(clippy::let_and_return)]
#[allow(clippy::needless_borrow)]
pub async fn make_operation(
self,
_config: &crate::config::Config,
) -> std::result::Result<
aws_smithy_http::operation::Operation<
crate::operation::InvokeEndpoint,
aws_http::AwsErrorRetryPolicy,
>,
aws_smithy_http::operation::BuildError,
> {
fn uri_base(
_input: &crate::input::InvokeEndpointInput,
output: &mut String,
) -> Result<(), aws_smithy_http::operation::BuildError> {
let input_1 = &_input.endpoint_name;
let input_1 =
input_1
.as_ref()
.ok_or(aws_smithy_http::operation::BuildError::MissingField {
field: "endpoint_name",
details: "cannot be empty or unset",
})?;
let endpoint_name = aws_smithy_http::label::fmt_string(input_1, false);
if endpoint_name.is_empty() {
return Err(aws_smithy_http::operation::BuildError::MissingField {
field: "endpoint_name",
details: "cannot be empty or unset",
});
}
write!(
output,
"/endpoints/{EndpointName}/invocations",
EndpointName = endpoint_name
)
.expect("formatting should succeed");
Ok(())
}
fn add_headers(
_input: &crate::input::InvokeEndpointInput,
mut builder: http::request::Builder,
) -> std::result::Result<http::request::Builder, aws_smithy_http::operation::BuildError>
{
if let Some(inner_2) = &_input.content_type {
let formatted_3 = AsRef::<str>::as_ref(inner_2);
if !formatted_3.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_3;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "content_type",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("Content-Type", header_value);
}
}
if let Some(inner_4) = &_input.accept {
let formatted_5 = AsRef::<str>::as_ref(inner_4);
if !formatted_5.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_5;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "accept",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("Accept", header_value);
}
}
if let Some(inner_6) = &_input.custom_attributes {
let formatted_7 = AsRef::<str>::as_ref(inner_6);
if !formatted_7.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_7;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "custom_attributes",
details: format!(
"`{}` cannot be used as a header value: {}",
&"*** Sensitive Data Redacted ***", err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Custom-Attributes", header_value);
}
}
if let Some(inner_8) = &_input.target_model {
let formatted_9 = AsRef::<str>::as_ref(inner_8);
if !formatted_9.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_9;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "target_model",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Target-Model", header_value);
}
}
if let Some(inner_10) = &_input.target_variant {
let formatted_11 = AsRef::<str>::as_ref(inner_10);
if !formatted_11.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_11;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "target_variant",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Target-Variant", header_value);
}
}
if let Some(inner_12) = &_input.target_container_hostname {
let formatted_13 = AsRef::<str>::as_ref(inner_12);
if !formatted_13.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_13;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "target_container_hostname",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder =
builder.header("X-Amzn-SageMaker-Target-Container-Hostname", header_value);
}
}
if let Some(inner_14) = &_input.inference_id {
let formatted_15 = AsRef::<str>::as_ref(inner_14);
if !formatted_15.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_15;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "inference_id",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Inference-Id", header_value);
}
}
Ok(builder)
}
#[allow(clippy::unnecessary_wraps)]
fn update_http_builder(
input: &crate::input::InvokeEndpointInput,
builder: http::request::Builder,
) -> std::result::Result<http::request::Builder, aws_smithy_http::operation::BuildError>
{
let mut uri = String::new();
uri_base(input, &mut uri)?;
let builder = add_headers(input, builder)?;
Ok(builder.method("POST").uri(uri))
}
#[allow(clippy::unnecessary_wraps)]
fn request_builder_base(
input: &crate::input::InvokeEndpointInput,
) -> std::result::Result<http::request::Builder, aws_smithy_http::operation::BuildError>
{
#[allow(unused_mut)]
let mut builder = update_http_builder(input, http::request::Builder::new())?;
builder = aws_smithy_http::header::set_header_if_absent(
builder,
http::header::HeaderName::from_static("content-type"),
"application/octet-stream",
);
Ok(builder)
}
let properties = aws_smithy_http::property_bag::SharedPropertyBag::new();
let request = request_builder_base(&self)?;
let body = crate::operation_ser::ser_payload_invoke_endpoint_input(self.body)?;
let request = Self::assemble(request, body);
#[allow(unused_mut)]
let mut request = aws_smithy_http::operation::Request::from_parts(
request.map(aws_smithy_http::body::SdkBody::from),
properties,
);
let mut user_agent = aws_http::user_agent::AwsUserAgent::new_from_environment(
aws_types::os_shim_internal::Env::real(),
crate::API_METADATA.clone(),
);
if let Some(app_name) = _config.app_name() {
user_agent = user_agent.with_app_name(app_name.clone());
}
request.properties_mut().insert(user_agent);
#[allow(unused_mut)]
let mut signing_config = aws_sig_auth::signer::OperationSigningConfig::default_config();
request.properties_mut().insert(signing_config);
request
.properties_mut()
.insert(aws_types::SigningService::from_static(
_config.signing_service(),
));
aws_endpoint::set_endpoint_resolver(
&mut request.properties_mut(),
_config.endpoint_resolver.clone(),
);
if let Some(region) = &_config.region {
request.properties_mut().insert(region.clone());
}
aws_http::auth::set_provider(
&mut request.properties_mut(),
_config.credentials_provider.clone(),
);
let op = aws_smithy_http::operation::Operation::new(
request,
crate::operation::InvokeEndpoint::new(),
)
.with_metadata(aws_smithy_http::operation::Metadata::new(
"InvokeEndpoint",
"sagemakerruntime",
));
let op = op.with_retry_policy(aws_http::AwsErrorRetryPolicy::new());
Ok(op)
}
fn assemble(
builder: http::request::Builder,
body: aws_smithy_http::body::SdkBody,
) -> http::request::Request<aws_smithy_http::body::SdkBody> {
let mut builder = builder;
if let Some(content_length) = body.content_length() {
builder = aws_smithy_http::header::set_header_if_absent(
builder,
http::header::CONTENT_LENGTH,
content_length,
);
}
builder.body(body).expect("should be valid request")
}
/// Creates a new builder-style object to manufacture [`InvokeEndpointInput`](crate::input::InvokeEndpointInput)
pub fn builder() -> crate::input::invoke_endpoint_input::Builder {
crate::input::invoke_endpoint_input::Builder::default()
}
}
/// See [`InvokeEndpointAsyncInput`](crate::input::InvokeEndpointAsyncInput)
pub mod invoke_endpoint_async_input {
/// A builder for [`InvokeEndpointAsyncInput`](crate::input::InvokeEndpointAsyncInput)
#[non_exhaustive]
#[derive(std::default::Default, std::clone::Clone, std::cmp::PartialEq, std::fmt::Debug)]
pub struct Builder {
pub(crate) endpoint_name: std::option::Option<std::string::String>,
pub(crate) content_type: std::option::Option<std::string::String>,
pub(crate) accept: std::option::Option<std::string::String>,
pub(crate) custom_attributes: std::option::Option<std::string::String>,
pub(crate) inference_id: std::option::Option<std::string::String>,
pub(crate) input_location: std::option::Option<std::string::String>,
pub(crate) request_ttl_seconds: std::option::Option<i32>,
}
impl Builder {
/// <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/APIReference/API_CreateEndpoint.html">
/// <code>CreateEndpoint</code>
/// </a> API.</p>
pub fn endpoint_name(mut self, input: impl Into<std::string::String>) -> Self {
self.endpoint_name = Some(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/APIReference/API_CreateEndpoint.html">
/// <code>CreateEndpoint</code>
/// </a> API.</p>
pub fn set_endpoint_name(
mut self,
input: std::option::Option<std::string::String>,
) -> Self {
self.endpoint_name = input;
self
}
/// <p>The MIME type of the input data in the request body.</p>
pub fn content_type(mut self, input: impl Into<std::string::String>) -> Self {
self.content_type = Some(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.content_type = input;
self
}
/// <p>The desired MIME type of the inference in the response.</p>
pub fn accept(mut self, input: impl Into<std::string::String>) -> Self {
self.accept = Some(input.into());
self
}
/// <p>The desired MIME type of the inference in the response.</p>
pub fn set_accept(mut self, input: std::option::Option<std::string::String>) -> Self {
self.accept = input;
self
}
/// <p>Provides additional information about a request for an inference submitted to
/// a model hosted at an Amazon SageMaker 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 AWS SDKs but not in the Amazon SageMaker Python SDK. </p>
pub fn custom_attributes(mut self, input: impl Into<std::string::String>) -> Self {
self.custom_attributes = Some(input.into());
self
}
/// <p>Provides additional information about a request for an inference submitted to
/// a model hosted at an Amazon SageMaker 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 AWS SDKs but not in the Amazon SageMaker Python SDK. </p>
pub fn set_custom_attributes(
mut self,
input: std::option::Option<std::string::String>,
) -> Self {
self.custom_attributes = input;
self
}
/// <p>The identifier for the inference request. Amazon SageMaker will generate an identifier for you
/// if none is specified. </p>
pub fn inference_id(mut self, input: impl Into<std::string::String>) -> Self {
self.inference_id = Some(input.into());
self
}
/// <p>The identifier for the inference request. Amazon SageMaker 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.inference_id = input;
self
}
/// <p>The Amazon S3 URI where the inference request payload is stored.</p>
pub fn input_location(mut self, input: impl Into<std::string::String>) -> Self {
self.input_location = Some(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.input_location = input;
self
}
/// <p>Maximum age in seconds a request can be in the queue before it is marked as expired.</p>
pub fn request_ttl_seconds(mut self, input: i32) -> Self {
self.request_ttl_seconds = Some(input);
self
}
/// <p>Maximum age in seconds a request can be in the queue before it is marked as expired.</p>
pub fn set_request_ttl_seconds(mut self, input: std::option::Option<i32>) -> Self {
self.request_ttl_seconds = input;
self
}
/// Consumes the builder and constructs a [`InvokeEndpointAsyncInput`](crate::input::InvokeEndpointAsyncInput)
pub fn build(
self,
) -> std::result::Result<
crate::input::InvokeEndpointAsyncInput,
aws_smithy_http::operation::BuildError,
> {
Ok(crate::input::InvokeEndpointAsyncInput {
endpoint_name: self.endpoint_name,
content_type: self.content_type,
accept: self.accept,
custom_attributes: self.custom_attributes,
inference_id: self.inference_id,
input_location: self.input_location,
request_ttl_seconds: self.request_ttl_seconds,
})
}
}
}
#[doc(hidden)]
pub type InvokeEndpointAsyncInputOperationOutputAlias = crate::operation::InvokeEndpointAsync;
#[doc(hidden)]
pub type InvokeEndpointAsyncInputOperationRetryAlias = aws_http::AwsErrorRetryPolicy;
impl InvokeEndpointAsyncInput {
/// Consumes the builder and constructs an Operation<[`InvokeEndpointAsync`](crate::operation::InvokeEndpointAsync)>
#[allow(clippy::let_and_return)]
#[allow(clippy::needless_borrow)]
pub async fn make_operation(
&self,
_config: &crate::config::Config,
) -> std::result::Result<
aws_smithy_http::operation::Operation<
crate::operation::InvokeEndpointAsync,
aws_http::AwsErrorRetryPolicy,
>,
aws_smithy_http::operation::BuildError,
> {
fn uri_base(
_input: &crate::input::InvokeEndpointAsyncInput,
output: &mut String,
) -> Result<(), aws_smithy_http::operation::BuildError> {
let input_16 = &_input.endpoint_name;
let input_16 =
input_16
.as_ref()
.ok_or(aws_smithy_http::operation::BuildError::MissingField {
field: "endpoint_name",
details: "cannot be empty or unset",
})?;
let endpoint_name = aws_smithy_http::label::fmt_string(input_16, false);
if endpoint_name.is_empty() {
return Err(aws_smithy_http::operation::BuildError::MissingField {
field: "endpoint_name",
details: "cannot be empty or unset",
});
}
write!(
output,
"/endpoints/{EndpointName}/async-invocations",
EndpointName = endpoint_name
)
.expect("formatting should succeed");
Ok(())
}
fn add_headers(
_input: &crate::input::InvokeEndpointAsyncInput,
mut builder: http::request::Builder,
) -> std::result::Result<http::request::Builder, aws_smithy_http::operation::BuildError>
{
if let Some(inner_17) = &_input.content_type {
let formatted_18 = AsRef::<str>::as_ref(inner_17);
if !formatted_18.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_18;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "content_type",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Content-Type", header_value);
}
}
if let Some(inner_19) = &_input.accept {
let formatted_20 = AsRef::<str>::as_ref(inner_19);
if !formatted_20.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_20;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "accept",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Accept", header_value);
}
}
if let Some(inner_21) = &_input.custom_attributes {
let formatted_22 = AsRef::<str>::as_ref(inner_21);
if !formatted_22.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_22;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "custom_attributes",
details: format!(
"`{}` cannot be used as a header value: {}",
&"*** Sensitive Data Redacted ***", err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Custom-Attributes", header_value);
}
}
if let Some(inner_23) = &_input.inference_id {
let formatted_24 = AsRef::<str>::as_ref(inner_23);
if !formatted_24.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_24;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "inference_id",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-Inference-Id", header_value);
}
}
if let Some(inner_25) = &_input.input_location {
let formatted_26 = AsRef::<str>::as_ref(inner_25);
if !formatted_26.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_26;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "input_location",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-InputLocation", header_value);
}
}
if let Some(inner_27) = &_input.request_ttl_seconds {
let mut encoder = aws_smithy_types::primitive::Encoder::from(*inner_27);
let formatted_28 = encoder.encode();
if !formatted_28.is_empty() {
use std::convert::TryFrom;
let header_value = formatted_28;
let header_value = http::header::HeaderValue::try_from(&*header_value)
.map_err(|err| aws_smithy_http::operation::BuildError::InvalidField {
field: "request_ttl_seconds",
details: format!(
"`{}` cannot be used as a header value: {}",
&header_value, err
),
})?;
builder = builder.header("X-Amzn-SageMaker-RequestTTLSeconds", header_value);
}
}
Ok(builder)
}
#[allow(clippy::unnecessary_wraps)]
fn update_http_builder(
input: &crate::input::InvokeEndpointAsyncInput,
builder: http::request::Builder,
) -> std::result::Result<http::request::Builder, aws_smithy_http::operation::BuildError>
{
let mut uri = String::new();
uri_base(input, &mut uri)?;
let builder = add_headers(input, builder)?;
Ok(builder.method("POST").uri(uri))
}
#[allow(clippy::unnecessary_wraps)]
fn request_builder_base(
input: &crate::input::InvokeEndpointAsyncInput,
) -> std::result::Result<http::request::Builder, aws_smithy_http::operation::BuildError>
{
#[allow(unused_mut)]
let mut builder = update_http_builder(input, http::request::Builder::new())?;
Ok(builder)
}
let properties = aws_smithy_http::property_bag::SharedPropertyBag::new();
let request = request_builder_base(&self)?;
let body = aws_smithy_http::body::SdkBody::from("");
let request = Self::assemble(request, body);
#[allow(unused_mut)]
let mut request = aws_smithy_http::operation::Request::from_parts(
request.map(aws_smithy_http::body::SdkBody::from),
properties,
);
let mut user_agent = aws_http::user_agent::AwsUserAgent::new_from_environment(
aws_types::os_shim_internal::Env::real(),
crate::API_METADATA.clone(),
);
if let Some(app_name) = _config.app_name() {
user_agent = user_agent.with_app_name(app_name.clone());
}
request.properties_mut().insert(user_agent);
#[allow(unused_mut)]
let mut signing_config = aws_sig_auth::signer::OperationSigningConfig::default_config();
request.properties_mut().insert(signing_config);
request
.properties_mut()
.insert(aws_types::SigningService::from_static(
_config.signing_service(),
));
aws_endpoint::set_endpoint_resolver(
&mut request.properties_mut(),
_config.endpoint_resolver.clone(),
);
if let Some(region) = &_config.region {
request.properties_mut().insert(region.clone());
}
aws_http::auth::set_provider(
&mut request.properties_mut(),
_config.credentials_provider.clone(),
);
let op = aws_smithy_http::operation::Operation::new(
request,
crate::operation::InvokeEndpointAsync::new(),
)
.with_metadata(aws_smithy_http::operation::Metadata::new(
"InvokeEndpointAsync",
"sagemakerruntime",
));
let op = op.with_retry_policy(aws_http::AwsErrorRetryPolicy::new());
Ok(op)
}
fn assemble(
builder: http::request::Builder,
body: aws_smithy_http::body::SdkBody,
) -> http::request::Request<aws_smithy_http::body::SdkBody> {
builder.body(body).expect("should be valid request")
}
/// Creates a new builder-style object to manufacture [`InvokeEndpointAsyncInput`](crate::input::InvokeEndpointAsyncInput)
pub fn builder() -> crate::input::invoke_endpoint_async_input::Builder {
crate::input::invoke_endpoint_async_input::Builder::default()
}
}
#[allow(missing_docs)] // documentation missing in model
#[non_exhaustive]
#[derive(std::clone::Clone, std::cmp::PartialEq)]
pub struct InvokeEndpointAsyncInput {
/// <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/APIReference/API_CreateEndpoint.html">
/// <code>CreateEndpoint</code>
/// </a> API.</p>
pub endpoint_name: std::option::Option<std::string::String>,
/// <p>The MIME type of the input data in the request body.</p>
pub content_type: std::option::Option<std::string::String>,
/// <p>The desired MIME type of the inference in the response.</p>
pub accept: std::option::Option<std::string::String>,
/// <p>Provides additional information about a request for an inference submitted to
/// a model hosted at an Amazon SageMaker 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 AWS SDKs but not in the Amazon SageMaker Python SDK. </p>
pub custom_attributes: std::option::Option<std::string::String>,
/// <p>The identifier for the inference request. Amazon SageMaker will generate an identifier for you
/// if none is specified. </p>
pub inference_id: std::option::Option<std::string::String>,
/// <p>The Amazon S3 URI where the inference request payload is stored.</p>
pub input_location: std::option::Option<std::string::String>,
/// <p>Maximum age in seconds a request can be in the queue before it is marked as expired.</p>
pub request_ttl_seconds: std::option::Option<i32>,
}
impl InvokeEndpointAsyncInput {
/// <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/APIReference/API_CreateEndpoint.html">
/// <code>CreateEndpoint</code>
/// </a> API.</p>
pub fn endpoint_name(&self) -> std::option::Option<&str> {
self.endpoint_name.as_deref()
}
/// <p>The MIME type of the input data in the request body.</p>
pub fn content_type(&self) -> std::option::Option<&str> {
self.content_type.as_deref()
}
/// <p>The desired MIME type of the inference in the response.</p>
pub fn accept(&self) -> std::option::Option<&str> {
self.accept.as_deref()
}
/// <p>Provides additional information about a request for an inference submitted to
/// a model hosted at an Amazon SageMaker 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 AWS SDKs but not in the Amazon SageMaker Python SDK. </p>
pub fn custom_attributes(&self) -> std::option::Option<&str> {
self.custom_attributes.as_deref()
}
/// <p>The identifier for the inference request. Amazon SageMaker will generate an identifier for you
/// if none is specified. </p>
pub fn inference_id(&self) -> std::option::Option<&str> {
self.inference_id.as_deref()
}
/// <p>The Amazon S3 URI where the inference request payload is stored.</p>
pub fn input_location(&self) -> std::option::Option<&str> {
self.input_location.as_deref()
}
/// <p>Maximum age in seconds a request can be in the queue before it is marked as expired.</p>
pub fn request_ttl_seconds(&self) -> std::option::Option<i32> {
self.request_ttl_seconds
}
}
impl std::fmt::Debug for InvokeEndpointAsyncInput {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let mut formatter = f.debug_struct("InvokeEndpointAsyncInput");
formatter.field("endpoint_name", &self.endpoint_name);
formatter.field("content_type", &self.content_type);
formatter.field("accept", &self.accept);
formatter.field("custom_attributes", &"*** Sensitive Data Redacted ***");
formatter.field("inference_id", &self.inference_id);
formatter.field("input_location", &self.input_location);
formatter.field("request_ttl_seconds", &self.request_ttl_seconds);
formatter.finish()
}
}
#[allow(missing_docs)] // documentation missing in model
#[non_exhaustive]
#[derive(std::clone::Clone, std::cmp::PartialEq)]
pub struct InvokeEndpointInput {
/// <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 endpoint_name: std::option::Option<std::string::String>,
/// <p>Provides input data, in the format specified in the <code>ContentType</code>
/// request header. Amazon SageMaker passes all of the data in the body to the model. </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 body: std::option::Option<aws_smithy_types::Blob>,
/// <p>The MIME type of the input data in the request body.</p>
pub content_type: std::option::Option<std::string::String>,
/// <p>The desired MIME type of the inference in the response.</p>
pub accept: std::option::Option<std::string::String>,
/// <p>Provides additional information about a request for an inference submitted to a model
/// hosted at an Amazon SageMaker 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://tools.ietf.org/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 AWS SDKs but not in the Amazon SageMaker Python
/// SDK.</p>
pub custom_attributes: std::option::Option<std::string::String>,
/// <p>The model to request for inference when invoking a multi-model endpoint.</p>
pub target_model: std::option::Option<std::string::String>,
/// <p>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, which is to distribute the invocation traffic based
/// on the variant weights.</p>
/// <p>For information about how to use variant targeting to perform a/b testing, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html">Test models in
/// production</a>
/// </p>
pub target_variant: std::option::Option<std::string::String>,
/// <p>If the endpoint hosts multiple containers and is configured to use direct invocation,
/// this parameter specifies the host name of the container to invoke.</p>
pub target_container_hostname: std::option::Option<std::string::String>,
/// <p>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 <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html">Capture
/// Data</a>.</p>
pub inference_id: std::option::Option<std::string::String>,
}
impl InvokeEndpointInput {
/// <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(&self) -> std::option::Option<&str> {
self.endpoint_name.as_deref()
}
/// <p>Provides input data, in the format specified in the <code>ContentType</code>
/// request header. Amazon SageMaker passes all of the data in the body to the model. </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(&self) -> std::option::Option<&aws_smithy_types::Blob> {
self.body.as_ref()
}
/// <p>The MIME type of the input data in the request body.</p>
pub fn content_type(&self) -> std::option::Option<&str> {
self.content_type.as_deref()
}
/// <p>The desired MIME type of the inference in the response.</p>
pub fn accept(&self) -> std::option::Option<&str> {
self.accept.as_deref()
}
/// <p>Provides additional information about a request for an inference submitted to a model
/// hosted at an Amazon SageMaker 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://tools.ietf.org/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 AWS SDKs but not in the Amazon SageMaker Python
/// SDK.</p>
pub fn custom_attributes(&self) -> std::option::Option<&str> {
self.custom_attributes.as_deref()
}
/// <p>The model to request for inference when invoking a multi-model endpoint.</p>
pub fn target_model(&self) -> std::option::Option<&str> {
self.target_model.as_deref()
}
/// <p>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, which is to distribute the invocation traffic based
/// on the variant weights.</p>
/// <p>For information about how to use variant targeting to perform a/b testing, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html">Test models in
/// production</a>
/// </p>
pub fn target_variant(&self) -> std::option::Option<&str> {
self.target_variant.as_deref()
}
/// <p>If the endpoint hosts multiple containers and is configured to use direct invocation,
/// this parameter specifies the host name of the container to invoke.</p>
pub fn target_container_hostname(&self) -> std::option::Option<&str> {
self.target_container_hostname.as_deref()
}
/// <p>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 <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html">Capture
/// Data</a>.</p>
pub fn inference_id(&self) -> std::option::Option<&str> {
self.inference_id.as_deref()
}
}
impl std::fmt::Debug for InvokeEndpointInput {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
let mut formatter = f.debug_struct("InvokeEndpointInput");
formatter.field("endpoint_name", &self.endpoint_name);
formatter.field("body", &"*** Sensitive Data Redacted ***");
formatter.field("content_type", &self.content_type);
formatter.field("accept", &self.accept);
formatter.field("custom_attributes", &"*** Sensitive Data Redacted ***");
formatter.field("target_model", &self.target_model);
formatter.field("target_variant", &self.target_variant);
formatter.field("target_container_hostname", &self.target_container_hostname);
formatter.field("inference_id", &self.inference_id);
formatter.finish()
}
}