Struct aws_sdk_bedrock::operation::create_evaluation_job::builders::CreateEvaluationJobFluentBuilder

pub struct CreateEvaluationJobFluentBuilder { /* private fields */ }

Fluent builder constructing a request to CreateEvaluationJob.

API operation for creating and managing Amazon Bedrock automatic model evaluation jobs and model evaluation jobs that use human workers. To learn more about the requirements for creating a model evaluation job see, Model evaluations.

Implementations

impl CreateEvaluationJobFluentBuilder

pub fn as_input(&self) -> &CreateEvaluationJobInputBuilder

Access the CreateEvaluationJob as a reference.

pub async fn send( self ) -> Result<CreateEvaluationJobOutput, SdkError<CreateEvaluationJobError, HttpResponse>>

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, which can be set when configuring the client.

pub fn customize( self ) -> CustomizableOperation<CreateEvaluationJobOutput, CreateEvaluationJobError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

pub fn job_name(self, input: impl Into<String>) -> Self

The name of the model evaluation job. Model evaluation job names must unique with your AWS account, and your account's AWS region.

pub fn set_job_name(self, input: Option<String>) -> Self

The name of the model evaluation job. Model evaluation job names must unique with your AWS account, and your account's AWS region.

pub fn get_job_name(&self) -> &Option<String>

The name of the model evaluation job. Model evaluation job names must unique with your AWS account, and your account's AWS region.

pub fn job_description(self, input: impl Into<String>) -> Self

A description of the model evaluation job.

pub fn set_job_description(self, input: Option<String>) -> Self

A description of the model evaluation job.

pub fn get_job_description(&self) -> &Option<String>

A description of the model evaluation job.

pub fn client_request_token(self, input: impl Into<String>) -> Self

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 Ensuring idempotency.

pub fn set_client_request_token(self, input: Option<String>) -> Self

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 Ensuring idempotency.

pub fn get_client_request_token(&self) -> &Option<String>

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 Ensuring idempotency.

pub fn role_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. The service role must have Amazon Bedrock as the service principal, and provide access to any Amazon S3 buckets specified in the EvaluationConfig object. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission. To learn more about the required permissions, see Required permissions.

pub fn set_role_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. The service role must have Amazon Bedrock as the service principal, and provide access to any Amazon S3 buckets specified in the EvaluationConfig object. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission. To learn more about the required permissions, see Required permissions.

pub fn get_role_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of an IAM service role that Amazon Bedrock can assume to perform tasks on your behalf. The service role must have Amazon Bedrock as the service principal, and provide access to any Amazon S3 buckets specified in the EvaluationConfig object. To pass this role to Amazon Bedrock, the caller of this API must have the iam:PassRole permission. To learn more about the required permissions, see Required permissions.

pub fn customer_encryption_key_id(self, input: impl Into<String>) -> Self

Specify your customer managed key ARN that will be used to encrypt your model evaluation job.

pub fn set_customer_encryption_key_id(self, input: Option<String>) -> Self

Specify your customer managed key ARN that will be used to encrypt your model evaluation job.

pub fn get_customer_encryption_key_id(&self) -> &Option<String>

Specify your customer managed key ARN that will be used to encrypt your model evaluation job.

pub fn job_tags(self, input: Tag) -> Self

Appends an item to jobTags.

To override the contents of this collection use set_job_tags.

Tags to attach to the model evaluation job.

pub fn set_job_tags(self, input: Option<Vec<Tag>>) -> Self

Tags to attach to the model evaluation job.

pub fn get_job_tags(&self) -> &Option<Vec<Tag>>

Tags to attach to the model evaluation job.

pub fn evaluation_config(self, input: EvaluationConfig) -> Self

Specifies whether the model evaluation job is automatic or uses human worker.

pub fn set_evaluation_config(self, input: Option<EvaluationConfig>) -> Self

Specifies whether the model evaluation job is automatic or uses human worker.

pub fn get_evaluation_config(&self) -> &Option<EvaluationConfig>

Specifies whether the model evaluation job is automatic or uses human worker.

pub fn inference_config(self, input: EvaluationInferenceConfig) -> Self

Specify the models you want to use in your model evaluation job. Automatic model evaluation jobs support a single model, and model evaluation job that use human workers support two models.

pub fn set_inference_config( self, input: Option<EvaluationInferenceConfig> ) -> Self

Specify the models you want to use in your model evaluation job. Automatic model evaluation jobs support a single model, and model evaluation job that use human workers support two models.

pub fn get_inference_config(&self) -> &Option<EvaluationInferenceConfig>

Specify the models you want to use in your model evaluation job. Automatic model evaluation jobs support a single model, and model evaluation job that use human workers support two models.

pub fn output_data_config(self, input: EvaluationOutputDataConfig) -> Self

An object that defines where the results of model evaluation job will be saved in Amazon S3.

pub fn set_output_data_config( self, input: Option<EvaluationOutputDataConfig> ) -> Self

An object that defines where the results of model evaluation job will be saved in Amazon S3.

pub fn get_output_data_config(&self) -> &Option<EvaluationOutputDataConfig>

An object that defines where the results of model evaluation job will be saved in Amazon S3.

Trait Implementations

impl Clone for CreateEvaluationJobFluentBuilder

fn clone(&self) -> CreateEvaluationJobFluentBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateEvaluationJobFluentBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.