// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::invoke_model::_invoke_model_input::InvokeModelInputBuilder;
pub use crate::operation::invoke_model::_invoke_model_output::InvokeModelOutputBuilder;
impl crate::operation::invoke_model::builders::InvokeModelInputBuilder {
/// Sends a request with this input using the given client.
pub async fn send_with(
self,
client: &crate::Client,
) -> ::std::result::Result<
crate::operation::invoke_model::InvokeModelOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::invoke_model::InvokeModelError,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let mut fluent_builder = client.invoke_model();
fluent_builder.inner = self;
fluent_builder.send().await
}
}
/// Fluent builder constructing a request to `InvokeModel`.
///
/// <p>Invokes the specified Amazon Bedrock model to run inference using the prompt and inference parameters provided in the request body. You use model inference to generate text, images, and embeddings.</p>
/// <p>For example code, see <i>Invoke model code examples</i> in the <i>Amazon Bedrock User Guide</i>.</p>
/// <p>This operation requires permission for the <code>bedrock:InvokeModel</code> action.</p><important>
/// <p>To deny all inference access to resources that you specify in the modelId field, you need to deny access to the <code>bedrock:InvokeModel</code> and <code>bedrock:InvokeModelWithResponseStream</code> actions. Doing this also denies access to the resource through the Converse API actions (<a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html">Converse</a> and <a href="https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_ConverseStream.html">ConverseStream</a>). For more information see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/security_iam_id-based-policy-examples.html#security_iam_id-based-policy-examples-deny-inference">Deny access for inference on specific models</a>.</p>
/// </important>
/// <p>For troubleshooting some of the common errors you might encounter when using the <code>InvokeModel</code> API, see <a href="https://docs.aws.amazon.com/bedrock/latest/userguide/troubleshooting-api-error-codes.html">Troubleshooting Amazon Bedrock API Error Codes</a> in the Amazon Bedrock User Guide</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct InvokeModelFluentBuilder {
handle: ::std::sync::Arc<crate::client::Handle>,
inner: crate::operation::invoke_model::builders::InvokeModelInputBuilder,
config_override: ::std::option::Option<crate::config::Builder>,
}
impl
crate::client::customize::internal::CustomizableSend<
crate::operation::invoke_model::InvokeModelOutput,
crate::operation::invoke_model::InvokeModelError,
> for InvokeModelFluentBuilder
{
fn send(
self,
config_override: crate::config::Builder,
) -> crate::client::customize::internal::BoxFuture<
crate::client::customize::internal::SendResult<
crate::operation::invoke_model::InvokeModelOutput,
crate::operation::invoke_model::InvokeModelError,
>,
> {
::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
}
}
impl InvokeModelFluentBuilder {
/// Creates a new `InvokeModelFluentBuilder`.
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 InvokeModel as a reference.
pub fn as_input(&self) -> &crate::operation::invoke_model::builders::InvokeModelInputBuilder {
&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::invoke_model::InvokeModelOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::invoke_model::InvokeModelError,
::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::invoke_model::InvokeModel::operation_runtime_plugins(
self.handle.runtime_plugins.clone(),
&self.handle.conf,
self.config_override,
);
crate::operation::invoke_model::InvokeModel::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::invoke_model::InvokeModelOutput,
crate::operation::invoke_model::InvokeModelError,
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 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.inner = self.inner.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 set_body(mut self, input: ::std::option::Option<::aws_smithy_types::Blob>) -> Self {
self.inner = self.inner.set_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.inner.get_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.inner = self.inner.content_type(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.inner = self.inner.set_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.inner.get_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.inner = self.inner.accept(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.inner = self.inner.set_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.inner.get_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>
pub fn model_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.model_id(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.inner = self.inner.set_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.inner.get_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.inner = self.inner.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 set_trace(mut self, input: ::std::option::Option<crate::types::Trace>) -> Self {
self.inner = self.inner.set_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.inner.get_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.inner = self.inner.guardrail_identifier(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.inner = self.inner.set_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.inner.get_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.inner = self.inner.guardrail_version(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.inner = self.inner.set_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.inner.get_guardrail_version()
}
/// <p>Model performance settings for the request.</p>
pub fn performance_config_latency(mut self, input: crate::types::PerformanceConfigLatency) -> Self {
self.inner = self.inner.performance_config_latency(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.inner = self.inner.set_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.inner.get_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.inner = self.inner.service_tier(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.inner = self.inner.set_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.inner.get_service_tier()
}
}