aws-sdk-kendra 1.97.0

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_index::_create_index_input::CreateIndexInputBuilder;

pub use crate::operation::create_index::_create_index_output::CreateIndexOutputBuilder;

impl crate::operation::create_index::builders::CreateIndexInputBuilder {
    /// 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_index::CreateIndexOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_index::CreateIndexError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_index();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateIndex`.
///
/// <p>Creates an Amazon Kendra index. Index creation is an asynchronous API. To determine if index creation has completed, check the <code>Status</code> field returned from a call to <code>DescribeIndex</code>. The <code>Status</code> field is set to <code>ACTIVE</code> when the index is ready to use.</p>
/// <p>Once the index is active, you can index your documents using the <code>BatchPutDocument</code> API or using one of the supported <a href="https://docs.aws.amazon.com/kendra/latest/dg/data-sources.html">data sources</a>.</p>
/// <p>For an example of creating an index and data source using the Python SDK, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/gs-python.html">Getting started with Python SDK</a>. For an example of creating an index and data source using the Java SDK, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/gs-java.html">Getting started with Java SDK</a>.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateIndexFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_index::builders::CreateIndexInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_index::CreateIndexOutput,
        crate::operation::create_index::CreateIndexError,
    > for CreateIndexFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_index::CreateIndexOutput,
            crate::operation::create_index::CreateIndexError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateIndexFluentBuilder {
    /// Creates a new `CreateIndexFluentBuilder`.
    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 CreateIndex as a reference.
    pub fn as_input(&self) -> &crate::operation::create_index::builders::CreateIndexInputBuilder {
        &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_index::CreateIndexOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_index::CreateIndexError,
            ::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_index::CreateIndex::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_index::CreateIndex::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_index::CreateIndexOutput,
        crate::operation::create_index::CreateIndexError,
        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>A name for the index.</p>
    pub fn name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.name(input.into());
        self
    }
    /// <p>A name for the index.</p>
    pub fn set_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_name(input);
        self
    }
    /// <p>A name for the index.</p>
    pub fn get_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_name()
    }
    /// <p>The Amazon Kendra edition to use for the index. Choose <code>DEVELOPER_EDITION</code> for indexes intended for development, testing, or proof of concept. Use <code>ENTERPRISE_EDITION</code> for production. Use <code>GEN_AI_ENTERPRISE_EDITION</code> for creating generative AI applications. Once you set the edition for an index, it can't be changed.</p>
    /// <p>The <code>Edition</code> parameter is optional. If you don't supply a value, the default is <code>ENTERPRISE_EDITION</code>.</p>
    /// <p>For more information on quota limits for Gen AI Enterprise Edition, Enterprise Edition, and Developer Edition indices, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/quotas.html">Quotas</a>.</p>
    pub fn edition(mut self, input: crate::types::IndexEdition) -> Self {
        self.inner = self.inner.edition(input);
        self
    }
    /// <p>The Amazon Kendra edition to use for the index. Choose <code>DEVELOPER_EDITION</code> for indexes intended for development, testing, or proof of concept. Use <code>ENTERPRISE_EDITION</code> for production. Use <code>GEN_AI_ENTERPRISE_EDITION</code> for creating generative AI applications. Once you set the edition for an index, it can't be changed.</p>
    /// <p>The <code>Edition</code> parameter is optional. If you don't supply a value, the default is <code>ENTERPRISE_EDITION</code>.</p>
    /// <p>For more information on quota limits for Gen AI Enterprise Edition, Enterprise Edition, and Developer Edition indices, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/quotas.html">Quotas</a>.</p>
    pub fn set_edition(mut self, input: ::std::option::Option<crate::types::IndexEdition>) -> Self {
        self.inner = self.inner.set_edition(input);
        self
    }
    /// <p>The Amazon Kendra edition to use for the index. Choose <code>DEVELOPER_EDITION</code> for indexes intended for development, testing, or proof of concept. Use <code>ENTERPRISE_EDITION</code> for production. Use <code>GEN_AI_ENTERPRISE_EDITION</code> for creating generative AI applications. Once you set the edition for an index, it can't be changed.</p>
    /// <p>The <code>Edition</code> parameter is optional. If you don't supply a value, the default is <code>ENTERPRISE_EDITION</code>.</p>
    /// <p>For more information on quota limits for Gen AI Enterprise Edition, Enterprise Edition, and Developer Edition indices, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/quotas.html">Quotas</a>.</p>
    pub fn get_edition(&self) -> &::std::option::Option<crate::types::IndexEdition> {
        self.inner.get_edition()
    }
    /// <p>The Amazon Resource Name (ARN) of an IAM role with permission to access your Amazon CloudWatch logs and metrics. For more information, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html">IAM access roles for Amazon Kendra</a>.</p>
    pub fn role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.role_arn(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of an IAM role with permission to access your Amazon CloudWatch logs and metrics. For more information, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html">IAM access roles for Amazon Kendra</a>.</p>
    pub fn set_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_role_arn(input);
        self
    }
    /// <p>The Amazon Resource Name (ARN) of an IAM role with permission to access your Amazon CloudWatch logs and metrics. For more information, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/iam-roles.html">IAM access roles for Amazon Kendra</a>.</p>
    pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_role_arn()
    }
    /// <p>The identifier of the KMS customer managed key (CMK) that's used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn't support asymmetric CMKs.</p>
    pub fn server_side_encryption_configuration(mut self, input: crate::types::ServerSideEncryptionConfiguration) -> Self {
        self.inner = self.inner.server_side_encryption_configuration(input);
        self
    }
    /// <p>The identifier of the KMS customer managed key (CMK) that's used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn't support asymmetric CMKs.</p>
    pub fn set_server_side_encryption_configuration(mut self, input: ::std::option::Option<crate::types::ServerSideEncryptionConfiguration>) -> Self {
        self.inner = self.inner.set_server_side_encryption_configuration(input);
        self
    }
    /// <p>The identifier of the KMS customer managed key (CMK) that's used to encrypt data indexed by Amazon Kendra. Amazon Kendra doesn't support asymmetric CMKs.</p>
    pub fn get_server_side_encryption_configuration(&self) -> &::std::option::Option<crate::types::ServerSideEncryptionConfiguration> {
        self.inner.get_server_side_encryption_configuration()
    }
    /// <p>A description for the index.</p>
    pub fn description(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.description(input.into());
        self
    }
    /// <p>A description for the index.</p>
    pub fn set_description(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_description(input);
        self
    }
    /// <p>A description for the index.</p>
    pub fn get_description(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_description()
    }
    /// <p>A token that you provide to identify the request to create an index. Multiple calls to the <code>CreateIndex</code> API with the same client token will create only one index.</p>
    pub fn client_token(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.client_token(input.into());
        self
    }
    /// <p>A token that you provide to identify the request to create an index. Multiple calls to the <code>CreateIndex</code> API with the same client token will create only one index.</p>
    pub fn set_client_token(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_client_token(input);
        self
    }
    /// <p>A token that you provide to identify the request to create an index. Multiple calls to the <code>CreateIndex</code> API with the same client token will create only one index.</p>
    pub fn get_client_token(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_client_token()
    }
    ///
    /// Appends an item to `Tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>A list of key-value pairs that identify or categorize the index. You can also use tags to help control access to the index. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.</p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>A list of key-value pairs that identify or categorize the index. You can also use tags to help control access to the index. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.</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>A list of key-value pairs that identify or categorize the index. You can also use tags to help control access to the index. Tag keys and values can consist of Unicode letters, digits, white space, and any of the following symbols: _ . : / = + - @.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        self.inner.get_tags()
    }
    ///
    /// Appends an item to `UserTokenConfigurations`.
    ///
    /// To override the contents of this collection use [`set_user_token_configurations`](Self::set_user_token_configurations).
    ///
    /// <p>The user token configuration.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use <code>UserTokenConfigurations</code> to configure user context policy, Amazon Kendra returns a <code>ValidationException</code> error.</p>
    /// </important>
    pub fn user_token_configurations(mut self, input: crate::types::UserTokenConfiguration) -> Self {
        self.inner = self.inner.user_token_configurations(input);
        self
    }
    /// <p>The user token configuration.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use <code>UserTokenConfigurations</code> to configure user context policy, Amazon Kendra returns a <code>ValidationException</code> error.</p>
    /// </important>
    pub fn set_user_token_configurations(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::UserTokenConfiguration>>) -> Self {
        self.inner = self.inner.set_user_token_configurations(input);
        self
    }
    /// <p>The user token configuration.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use <code>UserTokenConfigurations</code> to configure user context policy, Amazon Kendra returns a <code>ValidationException</code> error.</p>
    /// </important>
    pub fn get_user_token_configurations(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::UserTokenConfiguration>> {
        self.inner.get_user_token_configurations()
    }
    /// <p>The user context policy.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index, you can only use <code>ATTRIBUTE_FILTER</code> to filter search results by user context. If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use <code>USER_TOKEN</code> to configure user context policy, Amazon Kendra returns a <code>ValidationException</code> error.</p>
    /// </important>
    /// <dl>
    /// <dt>
    /// ATTRIBUTE_FILTER
    /// </dt>
    /// <dd>
    /// <p>All indexed content is searchable and displayable for all users. If you want to filter search results on user context, you can use the attribute filters of <code>_user_id</code> and <code>_group_ids</code> or you can provide user and group information in <code>UserContext</code>.</p>
    /// </dd>
    /// <dt>
    /// USER_TOKEN
    /// </dt>
    /// <dd>
    /// <p>Enables token-based user access control to filter search results on user context. All documents with no access control and all documents accessible to the user will be searchable and displayable.</p>
    /// </dd>
    /// </dl>
    pub fn user_context_policy(mut self, input: crate::types::UserContextPolicy) -> Self {
        self.inner = self.inner.user_context_policy(input);
        self
    }
    /// <p>The user context policy.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index, you can only use <code>ATTRIBUTE_FILTER</code> to filter search results by user context. If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use <code>USER_TOKEN</code> to configure user context policy, Amazon Kendra returns a <code>ValidationException</code> error.</p>
    /// </important>
    /// <dl>
    /// <dt>
    /// ATTRIBUTE_FILTER
    /// </dt>
    /// <dd>
    /// <p>All indexed content is searchable and displayable for all users. If you want to filter search results on user context, you can use the attribute filters of <code>_user_id</code> and <code>_group_ids</code> or you can provide user and group information in <code>UserContext</code>.</p>
    /// </dd>
    /// <dt>
    /// USER_TOKEN
    /// </dt>
    /// <dd>
    /// <p>Enables token-based user access control to filter search results on user context. All documents with no access control and all documents accessible to the user will be searchable and displayable.</p>
    /// </dd>
    /// </dl>
    pub fn set_user_context_policy(mut self, input: ::std::option::Option<crate::types::UserContextPolicy>) -> Self {
        self.inner = self.inner.set_user_context_policy(input);
        self
    }
    /// <p>The user context policy.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index, you can only use <code>ATTRIBUTE_FILTER</code> to filter search results by user context. If you're using an Amazon Kendra Gen AI Enterprise Edition index and you try to use <code>USER_TOKEN</code> to configure user context policy, Amazon Kendra returns a <code>ValidationException</code> error.</p>
    /// </important>
    /// <dl>
    /// <dt>
    /// ATTRIBUTE_FILTER
    /// </dt>
    /// <dd>
    /// <p>All indexed content is searchable and displayable for all users. If you want to filter search results on user context, you can use the attribute filters of <code>_user_id</code> and <code>_group_ids</code> or you can provide user and group information in <code>UserContext</code>.</p>
    /// </dd>
    /// <dt>
    /// USER_TOKEN
    /// </dt>
    /// <dd>
    /// <p>Enables token-based user access control to filter search results on user context. All documents with no access control and all documents accessible to the user will be searchable and displayable.</p>
    /// </dd>
    /// </dl>
    pub fn get_user_context_policy(&self) -> &::std::option::Option<crate::types::UserContextPolicy> {
        self.inner.get_user_context_policy()
    }
    /// <p>Gets users and groups from IAM Identity Center identity source. To configure this, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/API_UserGroupResolutionConfiguration.html">UserGroupResolutionConfiguration</a>. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index, <code>UserGroupResolutionConfiguration</code> isn't supported.</p>
    /// </important>
    pub fn user_group_resolution_configuration(mut self, input: crate::types::UserGroupResolutionConfiguration) -> Self {
        self.inner = self.inner.user_group_resolution_configuration(input);
        self
    }
    /// <p>Gets users and groups from IAM Identity Center identity source. To configure this, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/API_UserGroupResolutionConfiguration.html">UserGroupResolutionConfiguration</a>. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index, <code>UserGroupResolutionConfiguration</code> isn't supported.</p>
    /// </important>
    pub fn set_user_group_resolution_configuration(mut self, input: ::std::option::Option<crate::types::UserGroupResolutionConfiguration>) -> Self {
        self.inner = self.inner.set_user_group_resolution_configuration(input);
        self
    }
    /// <p>Gets users and groups from IAM Identity Center identity source. To configure this, see <a href="https://docs.aws.amazon.com/kendra/latest/dg/API_UserGroupResolutionConfiguration.html">UserGroupResolutionConfiguration</a>. This is useful for user context filtering, where search results are filtered based on the user or their group access to documents.</p><important>
    /// <p>If you're using an Amazon Kendra Gen AI Enterprise Edition index, <code>UserGroupResolutionConfiguration</code> isn't supported.</p>
    /// </important>
    pub fn get_user_group_resolution_configuration(&self) -> &::std::option::Option<crate::types::UserGroupResolutionConfiguration> {
        self.inner.get_user_group_resolution_configuration()
    }
}