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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::start_document_analysis::_start_document_analysis_output::StartDocumentAnalysisOutputBuilder;
pub use crate::operation::start_document_analysis::_start_document_analysis_input::StartDocumentAnalysisInputBuilder;
impl StartDocumentAnalysisInputBuilder {
/// Sends a request with this input using the given client.
pub async fn send_with(
self,
client: &crate::Client,
) -> ::std::result::Result<
crate::operation::start_document_analysis::StartDocumentAnalysisOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::start_document_analysis::StartDocumentAnalysisError,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let mut fluent_builder = client.start_document_analysis();
fluent_builder.inner = self;
fluent_builder.send().await
}
}
/// Fluent builder constructing a request to `StartDocumentAnalysis`.
///
/// <p>Starts the asynchronous analysis of an input document for relationships between detected items such as key-value pairs, tables, and selection elements.</p>
/// <p><code>StartDocumentAnalysis</code> can analyze text in documents that are in JPEG, PNG, TIFF, and PDF format. The documents are stored in an Amazon S3 bucket. Use <code>DocumentLocation</code> to specify the bucket name and file name of the document.</p>
/// <p><code>StartDocumentAnalysis</code> returns a job identifier (<code>JobId</code>) that you use to get the results of the operation. When text analysis is finished, Amazon Textract publishes a completion status to the Amazon Simple Notification Service (Amazon SNS) topic that you specify in <code>NotificationChannel</code>. To get the results of the text analysis operation, first check that the status value published to the Amazon SNS topic is <code>SUCCEEDED</code>. If so, call <code>GetDocumentAnalysis</code>, and pass the job identifier (<code>JobId</code>) from the initial call to <code>StartDocumentAnalysis</code>.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/textract/latest/dg/how-it-works-analyzing.html">Document Text Analysis</a>.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct StartDocumentAnalysisFluentBuilder {
handle: ::std::sync::Arc<crate::client::Handle>,
inner: crate::operation::start_document_analysis::builders::StartDocumentAnalysisInputBuilder,
config_override: ::std::option::Option<crate::config::Builder>,
}
impl
crate::client::customize::internal::CustomizableSend<
crate::operation::start_document_analysis::StartDocumentAnalysisOutput,
crate::operation::start_document_analysis::StartDocumentAnalysisError,
> for StartDocumentAnalysisFluentBuilder
{
fn send(
self,
config_override: crate::config::Builder,
) -> crate::client::customize::internal::BoxFuture<
crate::client::customize::internal::SendResult<
crate::operation::start_document_analysis::StartDocumentAnalysisOutput,
crate::operation::start_document_analysis::StartDocumentAnalysisError,
>,
> {
::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
}
}
impl StartDocumentAnalysisFluentBuilder {
/// Creates a new `StartDocumentAnalysis`.
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 StartDocumentAnalysis as a reference.
pub fn as_input(&self) -> &crate::operation::start_document_analysis::builders::StartDocumentAnalysisInputBuilder {
&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::start_document_analysis::StartDocumentAnalysisOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::start_document_analysis::StartDocumentAnalysisError,
::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::start_document_analysis::StartDocumentAnalysis::operation_runtime_plugins(
self.handle.runtime_plugins.clone(),
&self.handle.conf,
self.config_override,
);
crate::operation::start_document_analysis::StartDocumentAnalysis::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::start_document_analysis::StartDocumentAnalysisOutput,
crate::operation::start_document_analysis::StartDocumentAnalysisError,
Self,
> {
crate::client::customize::CustomizableOperation::new(self)
}
pub(crate) fn config_override(mut self, config_override: impl Into<crate::config::Builder>) -> Self {
self.set_config_override(Some(config_override.into()));
self
}
pub(crate) fn set_config_override(&mut self, config_override: Option<crate::config::Builder>) -> &mut Self {
self.config_override = config_override;
self
}
/// <p>The location of the document to be processed.</p>
pub fn document_location(mut self, input: crate::types::DocumentLocation) -> Self {
self.inner = self.inner.document_location(input);
self
}
/// <p>The location of the document to be processed.</p>
pub fn set_document_location(mut self, input: ::std::option::Option<crate::types::DocumentLocation>) -> Self {
self.inner = self.inner.set_document_location(input);
self
}
/// <p>The location of the document to be processed.</p>
pub fn get_document_location(&self) -> &::std::option::Option<crate::types::DocumentLocation> {
self.inner.get_document_location()
}
/// Appends an item to `FeatureTypes`.
///
/// To override the contents of this collection use [`set_feature_types`](Self::set_feature_types).
///
/// <p>A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to <code>FeatureTypes</code>. All lines and words detected in the document are included in the response (including text that isn't related to the value of <code>FeatureTypes</code>).</p>
pub fn feature_types(mut self, input: crate::types::FeatureType) -> Self {
self.inner = self.inner.feature_types(input);
self
}
/// <p>A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to <code>FeatureTypes</code>. All lines and words detected in the document are included in the response (including text that isn't related to the value of <code>FeatureTypes</code>).</p>
pub fn set_feature_types(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::FeatureType>>) -> Self {
self.inner = self.inner.set_feature_types(input);
self
}
/// <p>A list of the types of analysis to perform. Add TABLES to the list to return information about the tables that are detected in the input document. Add FORMS to return detected form data. To perform both types of analysis, add TABLES and FORMS to <code>FeatureTypes</code>. All lines and words detected in the document are included in the response (including text that isn't related to the value of <code>FeatureTypes</code>).</p>
pub fn get_feature_types(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::FeatureType>> {
self.inner.get_feature_types()
}
/// <p>The idempotent token that you use to identify the start request. If you use the same token with multiple <code>StartDocumentAnalysis</code> requests, the same <code>JobId</code> is returned. Use <code>ClientRequestToken</code> to prevent the same job from being accidentally started more than once. For more information, see <a href="https://docs.aws.amazon.com/textract/latest/dg/api-async.html">Calling Amazon Textract Asynchronous Operations</a>.</p>
pub fn client_request_token(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.client_request_token(input.into());
self
}
/// <p>The idempotent token that you use to identify the start request. If you use the same token with multiple <code>StartDocumentAnalysis</code> requests, the same <code>JobId</code> is returned. Use <code>ClientRequestToken</code> to prevent the same job from being accidentally started more than once. For more information, see <a href="https://docs.aws.amazon.com/textract/latest/dg/api-async.html">Calling Amazon Textract Asynchronous Operations</a>.</p>
pub fn set_client_request_token(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_client_request_token(input);
self
}
/// <p>The idempotent token that you use to identify the start request. If you use the same token with multiple <code>StartDocumentAnalysis</code> requests, the same <code>JobId</code> is returned. Use <code>ClientRequestToken</code> to prevent the same job from being accidentally started more than once. For more information, see <a href="https://docs.aws.amazon.com/textract/latest/dg/api-async.html">Calling Amazon Textract Asynchronous Operations</a>.</p>
pub fn get_client_request_token(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_client_request_token()
}
/// <p>An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use <code>JobTag</code> to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).</p>
pub fn job_tag(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.job_tag(input.into());
self
}
/// <p>An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use <code>JobTag</code> to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).</p>
pub fn set_job_tag(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_job_tag(input);
self
}
/// <p>An identifier that you specify that's included in the completion notification published to the Amazon SNS topic. For example, you can use <code>JobTag</code> to identify the type of document that the completion notification corresponds to (such as a tax form or a receipt).</p>
pub fn get_job_tag(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_job_tag()
}
/// <p>The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.</p>
pub fn notification_channel(mut self, input: crate::types::NotificationChannel) -> Self {
self.inner = self.inner.notification_channel(input);
self
}
/// <p>The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.</p>
pub fn set_notification_channel(mut self, input: ::std::option::Option<crate::types::NotificationChannel>) -> Self {
self.inner = self.inner.set_notification_channel(input);
self
}
/// <p>The Amazon SNS topic ARN that you want Amazon Textract to publish the completion status of the operation to.</p>
pub fn get_notification_channel(&self) -> &::std::option::Option<crate::types::NotificationChannel> {
self.inner.get_notification_channel()
}
/// <p>Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.</p>
pub fn output_config(mut self, input: crate::types::OutputConfig) -> Self {
self.inner = self.inner.output_config(input);
self
}
/// <p>Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.</p>
pub fn set_output_config(mut self, input: ::std::option::Option<crate::types::OutputConfig>) -> Self {
self.inner = self.inner.set_output_config(input);
self
}
/// <p>Sets if the output will go to a customer defined bucket. By default, Amazon Textract will save the results internally to be accessed by the GetDocumentAnalysis operation.</p>
pub fn get_output_config(&self) -> &::std::option::Option<crate::types::OutputConfig> {
self.inner.get_output_config()
}
/// <p>The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.</p>
pub fn kms_key_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.kms_key_id(input.into());
self
}
/// <p>The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.</p>
pub fn set_kms_key_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_kms_key_id(input);
self
}
/// <p>The KMS key used to encrypt the inference results. This can be in either Key ID or Key Alias format. When a KMS key is provided, the KMS key will be used for server-side encryption of the objects in the customer bucket. When this parameter is not enabled, the result will be encrypted server side,using SSE-S3.</p>
pub fn get_kms_key_id(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_kms_key_id()
}
/// <p></p>
pub fn queries_config(mut self, input: crate::types::QueriesConfig) -> Self {
self.inner = self.inner.queries_config(input);
self
}
/// <p></p>
pub fn set_queries_config(mut self, input: ::std::option::Option<crate::types::QueriesConfig>) -> Self {
self.inner = self.inner.set_queries_config(input);
self
}
/// <p></p>
pub fn get_queries_config(&self) -> &::std::option::Option<crate::types::QueriesConfig> {
self.inner.get_queries_config()
}
/// <p>Specifies the adapter to be used when analyzing a document.</p>
pub fn adapters_config(mut self, input: crate::types::AdaptersConfig) -> Self {
self.inner = self.inner.adapters_config(input);
self
}
/// <p>Specifies the adapter to be used when analyzing a document.</p>
pub fn set_adapters_config(mut self, input: ::std::option::Option<crate::types::AdaptersConfig>) -> Self {
self.inner = self.inner.set_adapters_config(input);
self
}
/// <p>Specifies the adapter to be used when analyzing a document.</p>
pub fn get_adapters_config(&self) -> &::std::option::Option<crate::types::AdaptersConfig> {
self.inner.get_adapters_config()
}
}