aws_sdk_comprehend/operation/create_document_classifier/

builders.rs

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_document_classifier::_create_document_classifier_output::CreateDocumentClassifierOutputBuilder;

pub use crate::operation::create_document_classifier::_create_document_classifier_input::CreateDocumentClassifierInputBuilder;

impl crate::operation::create_document_classifier::builders::CreateDocumentClassifierInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::create_document_classifier::CreateDocumentClassifierOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_document_classifier::CreateDocumentClassifierError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_document_classifier();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateDocumentClassifier`.
///
/// <p>Creates a new document classifier that you can use to categorize documents. To create a classifier, you provide a set of training documents that are labeled with the categories that you want to use. For more information, see <a href="https://docs.aws.amazon.com/comprehend/latest/dg/training-classifier-model.html">Training classifier models</a> in the Comprehend Developer Guide.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateDocumentClassifierFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_document_classifier::builders::CreateDocumentClassifierInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_document_classifier::CreateDocumentClassifierOutput,
        crate::operation::create_document_classifier::CreateDocumentClassifierError,
    > for CreateDocumentClassifierFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_document_classifier::CreateDocumentClassifierOutput,
            crate::operation::create_document_classifier::CreateDocumentClassifierError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateDocumentClassifierFluentBuilder {
    /// Creates a new `CreateDocumentClassifierFluentBuilder`.
    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 CreateDocumentClassifier as a reference.
    pub fn as_input(&self) -> &crate::operation::create_document_classifier::builders::CreateDocumentClassifierInputBuilder {
        &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::create_document_classifier::CreateDocumentClassifierOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_document_classifier::CreateDocumentClassifierError,
            ::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::create_document_classifier::CreateDocumentClassifier::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_document_classifier::CreateDocumentClassifier::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::create_document_classifier::CreateDocumentClassifierOutput,
        crate::operation::create_document_classifier::CreateDocumentClassifierError,
        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 document classifier.</p>
    pub fn document_classifier_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.document_classifier_name(input.into());
        self
    }
    /// <p>The name of the document classifier.</p>
    pub fn set_document_classifier_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_document_classifier_name(input);
        self
    }
    /// <p>The name of the document classifier.</p>
    pub fn get_document_classifier_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_document_classifier_name()
    }
    /// <p>The version name given to the newly created classifier. Version names can have a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same classifier name in the Amazon Web Services account/Amazon Web Services Region.</p>
    pub fn version_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.version_name(input.into());
        self
    }
    /// <p>The version name given to the newly created classifier. Version names can have a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same classifier name in the Amazon Web Services account/Amazon Web Services Region.</p>
    pub fn set_version_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_version_name(input);
        self
    }
    /// <p>The version name given to the newly created classifier. Version names can have a maximum of 256 characters. Alphanumeric characters, hyphens (-) and underscores (_) are allowed. The version name must be unique among all models with the same classifier name in the Amazon Web Services account/Amazon Web Services Region.</p>
    pub fn get_version_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_version_name()
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.</p>
    pub fn data_access_role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.data_access_role_arn(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.</p>
    pub fn set_data_access_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_data_access_role_arn(input);
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the IAM role that grants Amazon Comprehend read access to your input data.</p>
    pub fn get_data_access_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_data_access_role_arn()
    }
    ///
    /// Appends an item to `Tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>Tags to associate with the document classifier. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.</p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>Tags to associate with the document classifier. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.</p>
    pub fn set_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
        self.inner = self.inner.set_tags(input);
        self
    }
    /// <p>Tags to associate with the document classifier. A tag is a key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with "Sales" as the key might be added to a resource to indicate its use by the sales department.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        self.inner.get_tags()
    }
    /// <p>Specifies the format and location of the input data for the job.</p>
    pub fn input_data_config(mut self, input: crate::types::DocumentClassifierInputDataConfig) -> Self {
        self.inner = self.inner.input_data_config(input);
        self
    }
    /// <p>Specifies the format and location of the input data for the job.</p>
    pub fn set_input_data_config(mut self, input: ::std::option::Option<crate::types::DocumentClassifierInputDataConfig>) -> Self {
        self.inner = self.inner.set_input_data_config(input);
        self
    }
    /// <p>Specifies the format and location of the input data for the job.</p>
    pub fn get_input_data_config(&self) -> &::std::option::Option<crate::types::DocumentClassifierInputDataConfig> {
        self.inner.get_input_data_config()
    }
    /// <p>Specifies the location for the output files from a custom classifier job. This parameter is required for a request that creates a native document model.</p>
    pub fn output_data_config(mut self, input: crate::types::DocumentClassifierOutputDataConfig) -> Self {
        self.inner = self.inner.output_data_config(input);
        self
    }
    /// <p>Specifies the location for the output files from a custom classifier job. This parameter is required for a request that creates a native document model.</p>
    pub fn set_output_data_config(mut self, input: ::std::option::Option<crate::types::DocumentClassifierOutputDataConfig>) -> Self {
        self.inner = self.inner.set_output_data_config(input);
        self
    }
    /// <p>Specifies the location for the output files from a custom classifier job. This parameter is required for a request that creates a native document model.</p>
    pub fn get_output_data_config(&self) -> &::std::option::Option<crate::types::DocumentClassifierOutputDataConfig> {
        self.inner.get_output_data_config()
    }
    /// <p>A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.</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>A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.</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>A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.</p>
    pub fn get_client_request_token(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_client_request_token()
    }
    /// <p>The language of the input documents. You can specify any of the languages supported by Amazon Comprehend. All documents must be in the same language.</p>
    pub fn language_code(mut self, input: crate::types::LanguageCode) -> Self {
        self.inner = self.inner.language_code(input);
        self
    }
    /// <p>The language of the input documents. You can specify any of the languages supported by Amazon Comprehend. All documents must be in the same language.</p>
    pub fn set_language_code(mut self, input: ::std::option::Option<crate::types::LanguageCode>) -> Self {
        self.inner = self.inner.set_language_code(input);
        self
    }
    /// <p>The language of the input documents. You can specify any of the languages supported by Amazon Comprehend. All documents must be in the same language.</p>
    pub fn get_language_code(&self) -> &::std::option::Option<crate::types::LanguageCode> {
        self.inner.get_language_code()
    }
    /// <p>ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li>
    /// <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// <li>
    /// <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// </ul>
    pub fn volume_kms_key_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.volume_kms_key_id(input.into());
        self
    }
    /// <p>ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li>
    /// <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// <li>
    /// <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// </ul>
    pub fn set_volume_kms_key_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_volume_kms_key_id(input);
        self
    }
    /// <p>ID for the Amazon Web Services Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li>
    /// <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// <li>
    /// <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// </ul>
    pub fn get_volume_kms_key_id(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_volume_kms_key_id()
    }
    /// <p>Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see <a href="https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html">Amazon VPC</a>.</p>
    pub fn vpc_config(mut self, input: crate::types::VpcConfig) -> Self {
        self.inner = self.inner.vpc_config(input);
        self
    }
    /// <p>Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see <a href="https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html">Amazon VPC</a>.</p>
    pub fn set_vpc_config(mut self, input: ::std::option::Option<crate::types::VpcConfig>) -> Self {
        self.inner = self.inner.set_vpc_config(input);
        self
    }
    /// <p>Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your custom classifier. For more information, see <a href="https://docs.aws.amazon.com/vpc/latest/userguide/what-is-amazon-vpc.html">Amazon VPC</a>.</p>
    pub fn get_vpc_config(&self) -> &::std::option::Option<crate::types::VpcConfig> {
        self.inner.get_vpc_config()
    }
    /// <p>Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).</p>
    pub fn mode(mut self, input: crate::types::DocumentClassifierMode) -> Self {
        self.inner = self.inner.mode(input);
        self
    }
    /// <p>Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).</p>
    pub fn set_mode(mut self, input: ::std::option::Option<crate::types::DocumentClassifierMode>) -> Self {
        self.inner = self.inner.set_mode(input);
        self
    }
    /// <p>Indicates the mode in which the classifier will be trained. The classifier can be trained in multi-class (single-label) mode or multi-label mode. Multi-class mode identifies a single class label for each document and multi-label mode identifies one or more class labels for each document. Multiple labels for an individual document are separated by a delimiter. The default delimiter between labels is a pipe (|).</p>
    pub fn get_mode(&self) -> &::std::option::Option<crate::types::DocumentClassifierMode> {
        self.inner.get_mode()
    }
    /// <p>ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li>
    /// <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// <li>
    /// <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// </ul>
    pub fn model_kms_key_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.model_kms_key_id(input.into());
        self
    }
    /// <p>ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li>
    /// <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// <li>
    /// <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// </ul>
    pub fn set_model_kms_key_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_model_kms_key_id(input);
        self
    }
    /// <p>ID for the KMS key that Amazon Comprehend uses to encrypt trained custom models. The ModelKmsKeyId can be either of the following formats:</p>
    /// <ul>
    /// <li>
    /// <p>KMS Key ID: <code>"1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// <li>
    /// <p>Amazon Resource Name (ARN) of a KMS Key: <code>"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"</code></p></li>
    /// </ul>
    pub fn get_model_kms_key_id(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_model_kms_key_id()
    }
    /// <p>The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another Amazon Web Services account to import your custom model.</p>
    /// <p>Provide your policy as a JSON body that you enter as a UTF-8 encoded string without line breaks. To provide valid JSON, enclose the attribute names and values in double quotes. If the JSON body is also enclosed in double quotes, then you must escape the double quotes that are inside the policy:</p>
    /// <p><code>"{\"attribute\": \"value\", \"attribute\": \[\"value\"\]}"</code></p>
    /// <p>To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:</p>
    /// <p><code>'{"attribute": "value", "attribute": \["value"\]}'</code></p>
    pub fn model_policy(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.model_policy(input.into());
        self
    }
    /// <p>The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another Amazon Web Services account to import your custom model.</p>
    /// <p>Provide your policy as a JSON body that you enter as a UTF-8 encoded string without line breaks. To provide valid JSON, enclose the attribute names and values in double quotes. If the JSON body is also enclosed in double quotes, then you must escape the double quotes that are inside the policy:</p>
    /// <p><code>"{\"attribute\": \"value\", \"attribute\": \[\"value\"\]}"</code></p>
    /// <p>To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:</p>
    /// <p><code>'{"attribute": "value", "attribute": \["value"\]}'</code></p>
    pub fn set_model_policy(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_model_policy(input);
        self
    }
    /// <p>The resource-based policy to attach to your custom document classifier model. You can use this policy to allow another Amazon Web Services account to import your custom model.</p>
    /// <p>Provide your policy as a JSON body that you enter as a UTF-8 encoded string without line breaks. To provide valid JSON, enclose the attribute names and values in double quotes. If the JSON body is also enclosed in double quotes, then you must escape the double quotes that are inside the policy:</p>
    /// <p><code>"{\"attribute\": \"value\", \"attribute\": \[\"value\"\]}"</code></p>
    /// <p>To avoid escaping quotes, you can use single quotes to enclose the policy and double quotes to enclose the JSON names and values:</p>
    /// <p><code>'{"attribute": "value", "attribute": \["value"\]}'</code></p>
    pub fn get_model_policy(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_model_policy()
    }
}