aws-sdk-personalize 1.104.0

// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_batch_inference_job::_create_batch_inference_job_input::CreateBatchInferenceJobInputBuilder;

pub use crate::operation::create_batch_inference_job::_create_batch_inference_job_output::CreateBatchInferenceJobOutputBuilder;

impl crate::operation::create_batch_inference_job::builders::CreateBatchInferenceJobInputBuilder {
    /// 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_batch_inference_job::CreateBatchInferenceJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_batch_inference_job::CreateBatchInferenceJobError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_batch_inference_job();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateBatchInferenceJob`.
///
/// <p>Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket.</p>
/// <p>To generate batch recommendations, specify the ARN of a solution version and an Amazon S3 URI for the input and output data. For user personalization, popular items, and personalized ranking solutions, the batch inference job generates a list of recommended items for each user ID in the input file. For related items solutions, the job generates a list of recommended items for each item ID in the input file.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/getting-batch-recommendations.html">Creating a batch inference job </a>.</p>
/// <p>If you use the Similar-Items recipe, Amazon Personalize can add descriptive themes to batch recommendations. To generate themes, set the job's mode to <code>THEME_GENERATION</code> and specify the name of the field that contains item names in the input data.</p>
/// <p>For more information about generating themes, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/themed-batch-recommendations.html">Batch recommendations with themes from Content Generator </a>.</p>
/// <p>You can't get batch recommendations with the Trending-Now or Next-Best-Action recipes.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateBatchInferenceJobFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_batch_inference_job::builders::CreateBatchInferenceJobInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_batch_inference_job::CreateBatchInferenceJobOutput,
        crate::operation::create_batch_inference_job::CreateBatchInferenceJobError,
    > for CreateBatchInferenceJobFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_batch_inference_job::CreateBatchInferenceJobOutput,
            crate::operation::create_batch_inference_job::CreateBatchInferenceJobError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateBatchInferenceJobFluentBuilder {
    /// Creates a new `CreateBatchInferenceJobFluentBuilder`.
    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 CreateBatchInferenceJob as a reference.
    pub fn as_input(&self) -> &crate::operation::create_batch_inference_job::builders::CreateBatchInferenceJobInputBuilder {
        &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_batch_inference_job::CreateBatchInferenceJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_batch_inference_job::CreateBatchInferenceJobError,
            ::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_batch_inference_job::CreateBatchInferenceJob::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_batch_inference_job::CreateBatchInferenceJob::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_batch_inference_job::CreateBatchInferenceJobOutput,
        crate::operation::create_batch_inference_job::CreateBatchInferenceJobError,
        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 batch inference job to create.</p>
    pub fn job_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.job_name(input.into());
        self
    }
    /// <p>The name of the batch inference job to create.</p>
    pub fn set_job_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_job_name(input);
        self
    }
    /// <p>The name of the batch inference job to create.</p>
    pub fn get_job_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_job_name()
    }
    /// <p>The Amazon Resource Name (ARN) of the solution version that will be used to generate the batch inference recommendations.</p>
    pub fn solution_version_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.solution_version_arn(input.into());
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the solution version that will be used to generate the batch inference recommendations.</p>
    pub fn set_solution_version_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_solution_version_arn(input);
        self
    }
    /// <p>The Amazon Resource Name (ARN) of the solution version that will be used to generate the batch inference recommendations.</p>
    pub fn get_solution_version_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_solution_version_arn()
    }
    /// <p>The ARN of the filter to apply to the batch inference job. For more information on using filters, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/filter-batch.html">Filtering batch recommendations</a>.</p>
    pub fn filter_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.filter_arn(input.into());
        self
    }
    /// <p>The ARN of the filter to apply to the batch inference job. For more information on using filters, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/filter-batch.html">Filtering batch recommendations</a>.</p>
    pub fn set_filter_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_filter_arn(input);
        self
    }
    /// <p>The ARN of the filter to apply to the batch inference job. For more information on using filters, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/filter-batch.html">Filtering batch recommendations</a>.</p>
    pub fn get_filter_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_filter_arn()
    }
    /// <p>The number of recommendations to retrieve.</p>
    pub fn num_results(mut self, input: i32) -> Self {
        self.inner = self.inner.num_results(input);
        self
    }
    /// <p>The number of recommendations to retrieve.</p>
    pub fn set_num_results(mut self, input: ::std::option::Option<i32>) -> Self {
        self.inner = self.inner.set_num_results(input);
        self
    }
    /// <p>The number of recommendations to retrieve.</p>
    pub fn get_num_results(&self) -> &::std::option::Option<i32> {
        self.inner.get_num_results()
    }
    /// <p>The Amazon S3 path that leads to the input file to base your recommendations on. The input material must be in JSON format.</p>
    pub fn job_input(mut self, input: crate::types::BatchInferenceJobInput) -> Self {
        self.inner = self.inner.job_input(input);
        self
    }
    /// <p>The Amazon S3 path that leads to the input file to base your recommendations on. The input material must be in JSON format.</p>
    pub fn set_job_input(mut self, input: ::std::option::Option<crate::types::BatchInferenceJobInput>) -> Self {
        self.inner = self.inner.set_job_input(input);
        self
    }
    /// <p>The Amazon S3 path that leads to the input file to base your recommendations on. The input material must be in JSON format.</p>
    pub fn get_job_input(&self) -> &::std::option::Option<crate::types::BatchInferenceJobInput> {
        self.inner.get_job_input()
    }
    /// <p>The path to the Amazon S3 bucket where the job's output will be stored.</p>
    pub fn job_output(mut self, input: crate::types::BatchInferenceJobOutput) -> Self {
        self.inner = self.inner.job_output(input);
        self
    }
    /// <p>The path to the Amazon S3 bucket where the job's output will be stored.</p>
    pub fn set_job_output(mut self, input: ::std::option::Option<crate::types::BatchInferenceJobOutput>) -> Self {
        self.inner = self.inner.set_job_output(input);
        self
    }
    /// <p>The path to the Amazon S3 bucket where the job's output will be stored.</p>
    pub fn get_job_output(&self) -> &::std::option::Option<crate::types::BatchInferenceJobOutput> {
        self.inner.get_job_output()
    }
    /// <p>The ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.</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 ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.</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 ARN of the Amazon Identity and Access Management role that has permissions to read and write to your input and output Amazon S3 buckets respectively.</p>
    pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_role_arn()
    }
    /// <p>The configuration details of a batch inference job.</p>
    pub fn batch_inference_job_config(mut self, input: crate::types::BatchInferenceJobConfig) -> Self {
        self.inner = self.inner.batch_inference_job_config(input);
        self
    }
    /// <p>The configuration details of a batch inference job.</p>
    pub fn set_batch_inference_job_config(mut self, input: ::std::option::Option<crate::types::BatchInferenceJobConfig>) -> Self {
        self.inner = self.inner.set_batch_inference_job_config(input);
        self
    }
    /// <p>The configuration details of a batch inference job.</p>
    pub fn get_batch_inference_job_config(&self) -> &::std::option::Option<crate::types::BatchInferenceJobConfig> {
        self.inner.get_batch_inference_job_config()
    }
    ///
    /// Appends an item to `tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>A list of <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the batch inference job.</p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>A list of <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the batch inference job.</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 <a href="https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html">tags</a> to apply to the batch inference job.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        self.inner.get_tags()
    }
    /// <p>The mode of the batch inference job. To generate descriptive themes for groups of similar items, set the job mode to <code>THEME_GENERATION</code>. If you don't want to generate themes, use the default <code>BATCH_INFERENCE</code>.</p>
    /// <p>When you get batch recommendations with themes, you will incur additional costs. For more information, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>.</p>
    pub fn batch_inference_job_mode(mut self, input: crate::types::BatchInferenceJobMode) -> Self {
        self.inner = self.inner.batch_inference_job_mode(input);
        self
    }
    /// <p>The mode of the batch inference job. To generate descriptive themes for groups of similar items, set the job mode to <code>THEME_GENERATION</code>. If you don't want to generate themes, use the default <code>BATCH_INFERENCE</code>.</p>
    /// <p>When you get batch recommendations with themes, you will incur additional costs. For more information, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>.</p>
    pub fn set_batch_inference_job_mode(mut self, input: ::std::option::Option<crate::types::BatchInferenceJobMode>) -> Self {
        self.inner = self.inner.set_batch_inference_job_mode(input);
        self
    }
    /// <p>The mode of the batch inference job. To generate descriptive themes for groups of similar items, set the job mode to <code>THEME_GENERATION</code>. If you don't want to generate themes, use the default <code>BATCH_INFERENCE</code>.</p>
    /// <p>When you get batch recommendations with themes, you will incur additional costs. For more information, see <a href="https://aws.amazon.com/personalize/pricing/">Amazon Personalize pricing</a>.</p>
    pub fn get_batch_inference_job_mode(&self) -> &::std::option::Option<crate::types::BatchInferenceJobMode> {
        self.inner.get_batch_inference_job_mode()
    }
    /// <p>For theme generation jobs, specify the name of the column in your Items dataset that contains each item's name.</p>
    pub fn theme_generation_config(mut self, input: crate::types::ThemeGenerationConfig) -> Self {
        self.inner = self.inner.theme_generation_config(input);
        self
    }
    /// <p>For theme generation jobs, specify the name of the column in your Items dataset that contains each item's name.</p>
    pub fn set_theme_generation_config(mut self, input: ::std::option::Option<crate::types::ThemeGenerationConfig>) -> Self {
        self.inner = self.inner.set_theme_generation_config(input);
        self
    }
    /// <p>For theme generation jobs, specify the name of the column in your Items dataset that contains each item's name.</p>
    pub fn get_theme_generation_config(&self) -> &::std::option::Option<crate::types::ThemeGenerationConfig> {
        self.inner.get_theme_generation_config()
    }
}