// 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)]
pub struct InvokeModelInput {
/// <p>The prompt and inference parameters in the format specified in the <code>contentType</code> in the header. You must provide the body in JSON format. To see the format and content of the request and response bodies for different models, refer to <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html">Inference parameters</a>. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/api-methods-run.html">Run inference</a> in the Bedrock User Guide.</p>
pub body: ::std::option::Option<::aws_smithy_types::Blob>,
/// <p>The MIME type of the input data in the request. You must specify <code>application/json</code>.</p>
pub content_type: ::std::option::Option<::std::string::String>,
/// <p>The desired MIME type of the inference body in the response. The default value is <code>application/json</code>.</p>
pub accept: ::std::option::Option<::std::string::String>,
/// <p>The unique identifier of the model to invoke to run inference.</p>
/// <p>The <code>modelId</code> to provide depends on the type of model or throughput that you use:</p>
/// <ul>
/// <li>
/// <p>If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns">Amazon Bedrock base model IDs (on-demand throughput)</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html">Supported Regions and models for cross-region inference</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prov-thru-use.html">Run inference using a Provisioned Throughput</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a custom model, specify the ARN of the custom model deployment (for on-demand inference) or the ARN of your provisioned model (for Provisioned Throughput). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html">Use a custom model in Amazon Bedrock</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html">imported model</a>, specify the ARN of the imported model. You can get the model ARN from a successful call to <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateModelImportJob.html">CreateModelImportJob</a> or from the Imported models page in the Amazon Bedrock console.</p></li>
/// </ul>
pub model_id: ::std::option::Option<::std::string::String>,
/// <p>Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.</p>
pub trace: ::std::option::Option<crate::types::Trace>,
/// <p>The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.</p>
/// <p>An error will be thrown in the following situations.</p>
/// <ul>
/// <li>
/// <p>You don't provide a guardrail identifier but you specify the <code>amazon-bedrock-guardrailConfig</code> field in the request body.</p></li>
/// <li>
/// <p>You enable the guardrail but the <code>contentType</code> isn't <code>application/json</code>.</p></li>
/// <li>
/// <p>You provide a guardrail identifier, but <code>guardrailVersion</code> isn't specified.</p></li>
/// </ul>
pub guardrail_identifier: ::std::option::Option<::std::string::String>,
/// <p>The version number for the guardrail. The value can also be <code>DRAFT</code>.</p>
pub guardrail_version: ::std::option::Option<::std::string::String>,
/// <p>Model performance settings for the request.</p>
pub performance_config_latency: ::std::option::Option<crate::types::PerformanceConfigLatency>,
/// <p>Specifies the processing tier type used for serving the request.</p>
pub service_tier: ::std::option::Option<crate::types::ServiceTierType>,
}
impl InvokeModelInput {
/// <p>The prompt and inference parameters in the format specified in the <code>contentType</code> in the header. You must provide the body in JSON format. To see the format and content of the request and response bodies for different models, refer to <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html">Inference parameters</a>. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/api-methods-run.html">Run inference</a> in the Bedrock User Guide.</p>
pub fn body(&self) -> ::std::option::Option<&::aws_smithy_types::Blob> {
self.body.as_ref()
}
/// <p>The MIME type of the input data in the request. You must specify <code>application/json</code>.</p>
pub fn content_type(&self) -> ::std::option::Option<&str> {
self.content_type.as_deref()
}
/// <p>The desired MIME type of the inference body in the response. The default value is <code>application/json</code>.</p>
pub fn accept(&self) -> ::std::option::Option<&str> {
self.accept.as_deref()
}
/// <p>The unique identifier of the model to invoke to run inference.</p>
/// <p>The <code>modelId</code> to provide depends on the type of model or throughput that you use:</p>
/// <ul>
/// <li>
/// <p>If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns">Amazon Bedrock base model IDs (on-demand throughput)</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html">Supported Regions and models for cross-region inference</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prov-thru-use.html">Run inference using a Provisioned Throughput</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a custom model, specify the ARN of the custom model deployment (for on-demand inference) or the ARN of your provisioned model (for Provisioned Throughput). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html">Use a custom model in Amazon Bedrock</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html">imported model</a>, specify the ARN of the imported model. You can get the model ARN from a successful call to <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateModelImportJob.html">CreateModelImportJob</a> or from the Imported models page in the Amazon Bedrock console.</p></li>
/// </ul>
pub fn model_id(&self) -> ::std::option::Option<&str> {
self.model_id.as_deref()
}
/// <p>Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.</p>
pub fn trace(&self) -> ::std::option::Option<&crate::types::Trace> {
self.trace.as_ref()
}
/// <p>The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.</p>
/// <p>An error will be thrown in the following situations.</p>
/// <ul>
/// <li>
/// <p>You don't provide a guardrail identifier but you specify the <code>amazon-bedrock-guardrailConfig</code> field in the request body.</p></li>
/// <li>
/// <p>You enable the guardrail but the <code>contentType</code> isn't <code>application/json</code>.</p></li>
/// <li>
/// <p>You provide a guardrail identifier, but <code>guardrailVersion</code> isn't specified.</p></li>
/// </ul>
pub fn guardrail_identifier(&self) -> ::std::option::Option<&str> {
self.guardrail_identifier.as_deref()
}
/// <p>The version number for the guardrail. The value can also be <code>DRAFT</code>.</p>
pub fn guardrail_version(&self) -> ::std::option::Option<&str> {
self.guardrail_version.as_deref()
}
/// <p>Model performance settings for the request.</p>
pub fn performance_config_latency(&self) -> ::std::option::Option<&crate::types::PerformanceConfigLatency> {
self.performance_config_latency.as_ref()
}
/// <p>Specifies the processing tier type used for serving the request.</p>
pub fn service_tier(&self) -> ::std::option::Option<&crate::types::ServiceTierType> {
self.service_tier.as_ref()
}
}
impl ::std::fmt::Debug for InvokeModelInput {
fn fmt(&self, f: &mut ::std::fmt::Formatter<'_>) -> ::std::fmt::Result {
let mut formatter = f.debug_struct("InvokeModelInput");
formatter.field("body", &"*** Sensitive Data Redacted ***");
formatter.field("content_type", &self.content_type);
formatter.field("accept", &self.accept);
formatter.field("model_id", &self.model_id);
formatter.field("trace", &self.trace);
formatter.field("guardrail_identifier", &self.guardrail_identifier);
formatter.field("guardrail_version", &self.guardrail_version);
formatter.field("performance_config_latency", &self.performance_config_latency);
formatter.field("service_tier", &self.service_tier);
formatter.finish()
}
}
impl InvokeModelInput {
/// Creates a new builder-style object to manufacture [`InvokeModelInput`](crate::operation::invoke_model::InvokeModelInput).
pub fn builder() -> crate::operation::invoke_model::builders::InvokeModelInputBuilder {
crate::operation::invoke_model::builders::InvokeModelInputBuilder::default()
}
}
/// A builder for [`InvokeModelInput`](crate::operation::invoke_model::InvokeModelInput).
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::default::Default)]
#[non_exhaustive]
pub struct InvokeModelInputBuilder {
pub(crate) body: ::std::option::Option<::aws_smithy_types::Blob>,
pub(crate) content_type: ::std::option::Option<::std::string::String>,
pub(crate) accept: ::std::option::Option<::std::string::String>,
pub(crate) model_id: ::std::option::Option<::std::string::String>,
pub(crate) trace: ::std::option::Option<crate::types::Trace>,
pub(crate) guardrail_identifier: ::std::option::Option<::std::string::String>,
pub(crate) guardrail_version: ::std::option::Option<::std::string::String>,
pub(crate) performance_config_latency: ::std::option::Option<crate::types::PerformanceConfigLatency>,
pub(crate) service_tier: ::std::option::Option<crate::types::ServiceTierType>,
}
impl InvokeModelInputBuilder {
/// <p>The prompt and inference parameters in the format specified in the <code>contentType</code> in the header. You must provide the body in JSON format. To see the format and content of the request and response bodies for different models, refer to <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html">Inference parameters</a>. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/api-methods-run.html">Run inference</a> in the Bedrock User Guide.</p>
pub fn body(mut self, input: ::aws_smithy_types::Blob) -> Self {
self.body = ::std::option::Option::Some(input);
self
}
/// <p>The prompt and inference parameters in the format specified in the <code>contentType</code> in the header. You must provide the body in JSON format. To see the format and content of the request and response bodies for different models, refer to <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html">Inference parameters</a>. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/api-methods-run.html">Run inference</a> in the Bedrock User Guide.</p>
pub fn set_body(mut self, input: ::std::option::Option<::aws_smithy_types::Blob>) -> Self {
self.body = input;
self
}
/// <p>The prompt and inference parameters in the format specified in the <code>contentType</code> in the header. You must provide the body in JSON format. To see the format and content of the request and response bodies for different models, refer to <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters.html">Inference parameters</a>. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/api-methods-run.html">Run inference</a> in the Bedrock User Guide.</p>
pub fn get_body(&self) -> &::std::option::Option<::aws_smithy_types::Blob> {
&self.body
}
/// <p>The MIME type of the input data in the request. You must specify <code>application/json</code>.</p>
pub fn content_type(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.content_type = ::std::option::Option::Some(input.into());
self
}
/// <p>The MIME type of the input data in the request. You must specify <code>application/json</code>.</p>
pub fn set_content_type(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.content_type = input;
self
}
/// <p>The MIME type of the input data in the request. You must specify <code>application/json</code>.</p>
pub fn get_content_type(&self) -> &::std::option::Option<::std::string::String> {
&self.content_type
}
/// <p>The desired MIME type of the inference body in the response. The default value is <code>application/json</code>.</p>
pub fn accept(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.accept = ::std::option::Option::Some(input.into());
self
}
/// <p>The desired MIME type of the inference body in the response. The default value is <code>application/json</code>.</p>
pub fn set_accept(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.accept = input;
self
}
/// <p>The desired MIME type of the inference body in the response. The default value is <code>application/json</code>.</p>
pub fn get_accept(&self) -> &::std::option::Option<::std::string::String> {
&self.accept
}
/// <p>The unique identifier of the model to invoke to run inference.</p>
/// <p>The <code>modelId</code> to provide depends on the type of model or throughput that you use:</p>
/// <ul>
/// <li>
/// <p>If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns">Amazon Bedrock base model IDs (on-demand throughput)</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html">Supported Regions and models for cross-region inference</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prov-thru-use.html">Run inference using a Provisioned Throughput</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a custom model, specify the ARN of the custom model deployment (for on-demand inference) or the ARN of your provisioned model (for Provisioned Throughput). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html">Use a custom model in Amazon Bedrock</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html">imported model</a>, specify the ARN of the imported model. You can get the model ARN from a successful call to <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateModelImportJob.html">CreateModelImportJob</a> or from the Imported models page in the Amazon Bedrock console.</p></li>
/// </ul>
/// This field is required.
pub fn model_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.model_id = ::std::option::Option::Some(input.into());
self
}
/// <p>The unique identifier of the model to invoke to run inference.</p>
/// <p>The <code>modelId</code> to provide depends on the type of model or throughput that you use:</p>
/// <ul>
/// <li>
/// <p>If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns">Amazon Bedrock base model IDs (on-demand throughput)</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html">Supported Regions and models for cross-region inference</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prov-thru-use.html">Run inference using a Provisioned Throughput</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a custom model, specify the ARN of the custom model deployment (for on-demand inference) or the ARN of your provisioned model (for Provisioned Throughput). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html">Use a custom model in Amazon Bedrock</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html">imported model</a>, specify the ARN of the imported model. You can get the model ARN from a successful call to <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateModelImportJob.html">CreateModelImportJob</a> or from the Imported models page in the Amazon Bedrock console.</p></li>
/// </ul>
pub fn set_model_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.model_id = input;
self
}
/// <p>The unique identifier of the model to invoke to run inference.</p>
/// <p>The <code>modelId</code> to provide depends on the type of model or throughput that you use:</p>
/// <ul>
/// <li>
/// <p>If you use a base model, specify the model ID or its ARN. For a list of model IDs for base models, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids.html#model-ids-arns">Amazon Bedrock base model IDs (on-demand throughput)</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an inference profile, specify the inference profile ID or its ARN. For a list of inference profile IDs, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/cross-region-inference-support.html">Supported Regions and models for cross-region inference</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a provisioned model, specify the ARN of the Provisioned Throughput. For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/prov-thru-use.html">Run inference using a Provisioned Throughput</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use a custom model, specify the ARN of the custom model deployment (for on-demand inference) or the ARN of your provisioned model (for Provisioned Throughput). For more information, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html">Use a custom model in Amazon Bedrock</a> in the Amazon Bedrock User Guide.</p></li>
/// <li>
/// <p>If you use an <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-import-model.html">imported model</a>, specify the ARN of the imported model. You can get the model ARN from a successful call to <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateModelImportJob.html">CreateModelImportJob</a> or from the Imported models page in the Amazon Bedrock console.</p></li>
/// </ul>
pub fn get_model_id(&self) -> &::std::option::Option<::std::string::String> {
&self.model_id
}
/// <p>Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.</p>
pub fn trace(mut self, input: crate::types::Trace) -> Self {
self.trace = ::std::option::Option::Some(input);
self
}
/// <p>Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.</p>
pub fn set_trace(mut self, input: ::std::option::Option<crate::types::Trace>) -> Self {
self.trace = input;
self
}
/// <p>Specifies whether to enable or disable the Bedrock trace. If enabled, you can see the full Bedrock trace.</p>
pub fn get_trace(&self) -> &::std::option::Option<crate::types::Trace> {
&self.trace
}
/// <p>The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.</p>
/// <p>An error will be thrown in the following situations.</p>
/// <ul>
/// <li>
/// <p>You don't provide a guardrail identifier but you specify the <code>amazon-bedrock-guardrailConfig</code> field in the request body.</p></li>
/// <li>
/// <p>You enable the guardrail but the <code>contentType</code> isn't <code>application/json</code>.</p></li>
/// <li>
/// <p>You provide a guardrail identifier, but <code>guardrailVersion</code> isn't specified.</p></li>
/// </ul>
pub fn guardrail_identifier(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.guardrail_identifier = ::std::option::Option::Some(input.into());
self
}
/// <p>The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.</p>
/// <p>An error will be thrown in the following situations.</p>
/// <ul>
/// <li>
/// <p>You don't provide a guardrail identifier but you specify the <code>amazon-bedrock-guardrailConfig</code> field in the request body.</p></li>
/// <li>
/// <p>You enable the guardrail but the <code>contentType</code> isn't <code>application/json</code>.</p></li>
/// <li>
/// <p>You provide a guardrail identifier, but <code>guardrailVersion</code> isn't specified.</p></li>
/// </ul>
pub fn set_guardrail_identifier(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.guardrail_identifier = input;
self
}
/// <p>The unique identifier of the guardrail that you want to use. If you don't provide a value, no guardrail is applied to the invocation.</p>
/// <p>An error will be thrown in the following situations.</p>
/// <ul>
/// <li>
/// <p>You don't provide a guardrail identifier but you specify the <code>amazon-bedrock-guardrailConfig</code> field in the request body.</p></li>
/// <li>
/// <p>You enable the guardrail but the <code>contentType</code> isn't <code>application/json</code>.</p></li>
/// <li>
/// <p>You provide a guardrail identifier, but <code>guardrailVersion</code> isn't specified.</p></li>
/// </ul>
pub fn get_guardrail_identifier(&self) -> &::std::option::Option<::std::string::String> {
&self.guardrail_identifier
}
/// <p>The version number for the guardrail. The value can also be <code>DRAFT</code>.</p>
pub fn guardrail_version(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.guardrail_version = ::std::option::Option::Some(input.into());
self
}
/// <p>The version number for the guardrail. The value can also be <code>DRAFT</code>.</p>
pub fn set_guardrail_version(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.guardrail_version = input;
self
}
/// <p>The version number for the guardrail. The value can also be <code>DRAFT</code>.</p>
pub fn get_guardrail_version(&self) -> &::std::option::Option<::std::string::String> {
&self.guardrail_version
}
/// <p>Model performance settings for the request.</p>
pub fn performance_config_latency(mut self, input: crate::types::PerformanceConfigLatency) -> Self {
self.performance_config_latency = ::std::option::Option::Some(input);
self
}
/// <p>Model performance settings for the request.</p>
pub fn set_performance_config_latency(mut self, input: ::std::option::Option<crate::types::PerformanceConfigLatency>) -> Self {
self.performance_config_latency = input;
self
}
/// <p>Model performance settings for the request.</p>
pub fn get_performance_config_latency(&self) -> &::std::option::Option<crate::types::PerformanceConfigLatency> {
&self.performance_config_latency
}
/// <p>Specifies the processing tier type used for serving the request.</p>
pub fn service_tier(mut self, input: crate::types::ServiceTierType) -> Self {
self.service_tier = ::std::option::Option::Some(input);
self
}
/// <p>Specifies the processing tier type used for serving the request.</p>
pub fn set_service_tier(mut self, input: ::std::option::Option<crate::types::ServiceTierType>) -> Self {
self.service_tier = input;
self
}
/// <p>Specifies the processing tier type used for serving the request.</p>
pub fn get_service_tier(&self) -> &::std::option::Option<crate::types::ServiceTierType> {
&self.service_tier
}
/// Consumes the builder and constructs a [`InvokeModelInput`](crate::operation::invoke_model::InvokeModelInput).
pub fn build(self) -> ::std::result::Result<crate::operation::invoke_model::InvokeModelInput, ::aws_smithy_types::error::operation::BuildError> {
::std::result::Result::Ok(crate::operation::invoke_model::InvokeModelInput {
body: self.body,
content_type: self.content_type,
accept: self.accept,
model_id: self.model_id,
trace: self.trace,
guardrail_identifier: self.guardrail_identifier,
guardrail_version: self.guardrail_version,
performance_config_latency: self.performance_config_latency,
service_tier: self.service_tier,
})
}
}
impl ::std::fmt::Debug for InvokeModelInputBuilder {
fn fmt(&self, f: &mut ::std::fmt::Formatter<'_>) -> ::std::fmt::Result {
let mut formatter = f.debug_struct("InvokeModelInputBuilder");
formatter.field("body", &"*** Sensitive Data Redacted ***");
formatter.field("content_type", &self.content_type);
formatter.field("accept", &self.accept);
formatter.field("model_id", &self.model_id);
formatter.field("trace", &self.trace);
formatter.field("guardrail_identifier", &self.guardrail_identifier);
formatter.field("guardrail_version", &self.guardrail_version);
formatter.field("performance_config_latency", &self.performance_config_latency);
formatter.field("service_tier", &self.service_tier);
formatter.finish()
}
}