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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
#[allow(missing_docs)] // documentation missing in model
#[non_exhaustive]
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::fmt::Debug)]
pub struct CreateCustomModelInput {
/// <p>A unique name for the custom model.</p>
pub model_name: ::std::option::Option<::std::string::String>,
/// <p>The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.</p>
pub model_source_config: ::std::option::Option<crate::types::ModelDataSource>,
/// <p>The data source for the custom model. Use this field to specify a SageMaker AI model package ARN as the source for your custom model. Amazon Bedrock resolves the model package to retrieve the model artifacts.</p>
/// <p>You can specify either <code>customModelDataSource</code> or <code>modelSourceConfig</code>, but not both.</p>
pub custom_model_data_source: ::std::option::Option<crate::types::CustomModelDataSource>,
/// <p>The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.</p>
/// <p>If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/encryption-import-model.html">Encryption of imported models</a>.</p>
pub model_kms_key_arn: ::std::option::Option<::std::string::String>,
/// <p>The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-import-iam-role.html">Setting up an IAM service role for importing models</a> in the Amazon Bedrock User Guide.</p>
/// <p>This field is required when you use <code>modelSourceConfig</code> with an Amazon S3 data source. It is not required when you use <code>customModelDataSource</code> with a model package ARN, because Amazon Bedrock uses its own credentials to access the model artifacts.</p>
pub role_arn: ::std::option::Option<::std::string::String>,
/// <p>A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html">Tagging resources</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>
pub model_tags: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>,
/// <p>A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>
pub client_request_token: ::std::option::Option<::std::string::String>,
}
impl CreateCustomModelInput {
/// <p>A unique name for the custom model.</p>
pub fn model_name(&self) -> ::std::option::Option<&str> {
self.model_name.as_deref()
}
/// <p>The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.</p>
pub fn model_source_config(&self) -> ::std::option::Option<&crate::types::ModelDataSource> {
self.model_source_config.as_ref()
}
/// <p>The data source for the custom model. Use this field to specify a SageMaker AI model package ARN as the source for your custom model. Amazon Bedrock resolves the model package to retrieve the model artifacts.</p>
/// <p>You can specify either <code>customModelDataSource</code> or <code>modelSourceConfig</code>, but not both.</p>
pub fn custom_model_data_source(&self) -> ::std::option::Option<&crate::types::CustomModelDataSource> {
self.custom_model_data_source.as_ref()
}
/// <p>The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.</p>
/// <p>If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/encryption-import-model.html">Encryption of imported models</a>.</p>
pub fn model_kms_key_arn(&self) -> ::std::option::Option<&str> {
self.model_kms_key_arn.as_deref()
}
/// <p>The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-import-iam-role.html">Setting up an IAM service role for importing models</a> in the Amazon Bedrock User Guide.</p>
/// <p>This field is required when you use <code>modelSourceConfig</code> with an Amazon S3 data source. It is not required when you use <code>customModelDataSource</code> with a model package ARN, because Amazon Bedrock uses its own credentials to access the model artifacts.</p>
pub fn role_arn(&self) -> ::std::option::Option<&str> {
self.role_arn.as_deref()
}
/// <p>A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html">Tagging resources</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>
///
/// If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use `.model_tags.is_none()`.
pub fn model_tags(&self) -> &[crate::types::Tag] {
self.model_tags.as_deref().unwrap_or_default()
}
/// <p>A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>
pub fn client_request_token(&self) -> ::std::option::Option<&str> {
self.client_request_token.as_deref()
}
}
impl CreateCustomModelInput {
/// Creates a new builder-style object to manufacture [`CreateCustomModelInput`](crate::operation::create_custom_model::CreateCustomModelInput).
pub fn builder() -> crate::operation::create_custom_model::builders::CreateCustomModelInputBuilder {
crate::operation::create_custom_model::builders::CreateCustomModelInputBuilder::default()
}
}
/// A builder for [`CreateCustomModelInput`](crate::operation::create_custom_model::CreateCustomModelInput).
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::default::Default, ::std::fmt::Debug)]
#[non_exhaustive]
pub struct CreateCustomModelInputBuilder {
pub(crate) model_name: ::std::option::Option<::std::string::String>,
pub(crate) model_source_config: ::std::option::Option<crate::types::ModelDataSource>,
pub(crate) custom_model_data_source: ::std::option::Option<crate::types::CustomModelDataSource>,
pub(crate) model_kms_key_arn: ::std::option::Option<::std::string::String>,
pub(crate) role_arn: ::std::option::Option<::std::string::String>,
pub(crate) model_tags: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>,
pub(crate) client_request_token: ::std::option::Option<::std::string::String>,
}
impl CreateCustomModelInputBuilder {
/// <p>A unique name for the custom model.</p>
/// This field is required.
pub fn model_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.model_name = ::std::option::Option::Some(input.into());
self
}
/// <p>A unique name for the custom model.</p>
pub fn set_model_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.model_name = input;
self
}
/// <p>A unique name for the custom model.</p>
pub fn get_model_name(&self) -> &::std::option::Option<::std::string::String> {
&self.model_name
}
/// <p>The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.</p>
pub fn model_source_config(mut self, input: crate::types::ModelDataSource) -> Self {
self.model_source_config = ::std::option::Option::Some(input);
self
}
/// <p>The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.</p>
pub fn set_model_source_config(mut self, input: ::std::option::Option<crate::types::ModelDataSource>) -> Self {
self.model_source_config = input;
self
}
/// <p>The data source for the model. The Amazon S3 URI in the model source must be for the Amazon-managed Amazon S3 bucket containing your model artifacts.</p>
pub fn get_model_source_config(&self) -> &::std::option::Option<crate::types::ModelDataSource> {
&self.model_source_config
}
/// <p>The data source for the custom model. Use this field to specify a SageMaker AI model package ARN as the source for your custom model. Amazon Bedrock resolves the model package to retrieve the model artifacts.</p>
/// <p>You can specify either <code>customModelDataSource</code> or <code>modelSourceConfig</code>, but not both.</p>
pub fn custom_model_data_source(mut self, input: crate::types::CustomModelDataSource) -> Self {
self.custom_model_data_source = ::std::option::Option::Some(input);
self
}
/// <p>The data source for the custom model. Use this field to specify a SageMaker AI model package ARN as the source for your custom model. Amazon Bedrock resolves the model package to retrieve the model artifacts.</p>
/// <p>You can specify either <code>customModelDataSource</code> or <code>modelSourceConfig</code>, but not both.</p>
pub fn set_custom_model_data_source(mut self, input: ::std::option::Option<crate::types::CustomModelDataSource>) -> Self {
self.custom_model_data_source = input;
self
}
/// <p>The data source for the custom model. Use this field to specify a SageMaker AI model package ARN as the source for your custom model. Amazon Bedrock resolves the model package to retrieve the model artifacts.</p>
/// <p>You can specify either <code>customModelDataSource</code> or <code>modelSourceConfig</code>, but not both.</p>
pub fn get_custom_model_data_source(&self) -> &::std::option::Option<crate::types::CustomModelDataSource> {
&self.custom_model_data_source
}
/// <p>The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.</p>
/// <p>If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/encryption-import-model.html">Encryption of imported models</a>.</p>
pub fn model_kms_key_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.model_kms_key_arn = ::std::option::Option::Some(input.into());
self
}
/// <p>The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.</p>
/// <p>If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/encryption-import-model.html">Encryption of imported models</a>.</p>
pub fn set_model_kms_key_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.model_kms_key_arn = input;
self
}
/// <p>The Amazon Resource Name (ARN) of the customer managed KMS key to encrypt the custom model. If you don't provide a KMS key, Amazon Bedrock uses an Amazon Web Services-managed KMS key to encrypt the model.</p>
/// <p>If you provide a customer managed KMS key, your Amazon Bedrock service role must have permissions to use it. For more information see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/encryption-import-model.html">Encryption of imported models</a>.</p>
pub fn get_model_kms_key_arn(&self) -> &::std::option::Option<::std::string::String> {
&self.model_kms_key_arn
}
/// <p>The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-import-iam-role.html">Setting up an IAM service role for importing models</a> in the Amazon Bedrock User Guide.</p>
/// <p>This field is required when you use <code>modelSourceConfig</code> with an Amazon S3 data source. It is not required when you use <code>customModelDataSource</code> with a model package ARN, because Amazon Bedrock uses its own credentials to access the model artifacts.</p>
pub fn role_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.role_arn = ::std::option::Option::Some(input.into());
self
}
/// <p>The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-import-iam-role.html">Setting up an IAM service role for importing models</a> in the Amazon Bedrock User Guide.</p>
/// <p>This field is required when you use <code>modelSourceConfig</code> with an Amazon S3 data source. It is not required when you use <code>customModelDataSource</code> with a model package ARN, because Amazon Bedrock uses its own credentials to access the model artifacts.</p>
pub fn set_role_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.role_arn = input;
self
}
/// <p>The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock assumes to perform tasks on your behalf. This role must have permissions to access the Amazon S3 bucket containing your model artifacts and the KMS key (if specified). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-import-iam-role.html">Setting up an IAM service role for importing models</a> in the Amazon Bedrock User Guide.</p>
/// <p>This field is required when you use <code>modelSourceConfig</code> with an Amazon S3 data source. It is not required when you use <code>customModelDataSource</code> with a model package ARN, because Amazon Bedrock uses its own credentials to access the model artifacts.</p>
pub fn get_role_arn(&self) -> &::std::option::Option<::std::string::String> {
&self.role_arn
}
/// Appends an item to `model_tags`.
///
/// To override the contents of this collection use [`set_model_tags`](Self::set_model_tags).
///
/// <p>A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html">Tagging resources</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>
pub fn model_tags(mut self, input: crate::types::Tag) -> Self {
let mut v = self.model_tags.unwrap_or_default();
v.push(input);
self.model_tags = ::std::option::Option::Some(v);
self
}
/// <p>A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html">Tagging resources</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>
pub fn set_model_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
self.model_tags = input;
self
}
/// <p>A list of key-value pairs to associate with the custom model resource. You can use these tags to organize and identify your resources.</p>
/// <p>For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/tagging.html">Tagging resources</a> in the <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-service.html">Amazon Bedrock User Guide</a>.</p>
pub fn get_model_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
&self.model_tags
}
/// <p>A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>
pub fn client_request_token(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.client_request_token = ::std::option::Option::Some(input.into());
self
}
/// <p>A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>
pub fn set_client_request_token(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.client_request_token = input;
self
}
/// <p>A unique, case-sensitive identifier to ensure that the API request completes no more than one time. If this token matches a previous request, Amazon Bedrock ignores the request, but does not return an error. For more information, see <a href="https://docs.aws.amazon.com/AWSEC2/latest/APIReference/Run_Instance_Idempotency.html">Ensuring idempotency</a>.</p>
pub fn get_client_request_token(&self) -> &::std::option::Option<::std::string::String> {
&self.client_request_token
}
/// Consumes the builder and constructs a [`CreateCustomModelInput`](crate::operation::create_custom_model::CreateCustomModelInput).
pub fn build(
self,
) -> ::std::result::Result<crate::operation::create_custom_model::CreateCustomModelInput, ::aws_smithy_types::error::operation::BuildError> {
::std::result::Result::Ok(crate::operation::create_custom_model::CreateCustomModelInput {
model_name: self.model_name,
model_source_config: self.model_source_config,
custom_model_data_source: self.custom_model_data_source,
model_kms_key_arn: self.model_kms_key_arn,
role_arn: self.role_arn,
model_tags: self.model_tags,
client_request_token: self.client_request_token,
})
}
}