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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::evaluate::_evaluate_input::EvaluateInputBuilder;
pub use crate::operation::evaluate::_evaluate_output::EvaluateOutputBuilder;
impl crate::operation::evaluate::builders::EvaluateInputBuilder {
/// Sends a request with this input using the given client.
pub async fn send_with(
self,
client: &crate::Client,
) -> ::std::result::Result<
crate::operation::evaluate::EvaluateOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::evaluate::EvaluateError,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let mut fluent_builder = client.evaluate();
fluent_builder.inner = self;
fluent_builder.send().await
}
}
/// Fluent builder constructing a request to `Evaluate`.
///
/// <p>Performs on-demand evaluation of agent traces using a specified evaluator. This synchronous API accepts traces in OpenTelemetry format and returns immediate scoring results with detailed explanations.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct EvaluateFluentBuilder {
handle: ::std::sync::Arc<crate::client::Handle>,
inner: crate::operation::evaluate::builders::EvaluateInputBuilder,
config_override: ::std::option::Option<crate::config::Builder>,
}
impl crate::client::customize::internal::CustomizableSend<crate::operation::evaluate::EvaluateOutput, crate::operation::evaluate::EvaluateError>
for EvaluateFluentBuilder
{
fn send(
self,
config_override: crate::config::Builder,
) -> crate::client::customize::internal::BoxFuture<
crate::client::customize::internal::SendResult<crate::operation::evaluate::EvaluateOutput, crate::operation::evaluate::EvaluateError>,
> {
::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
}
}
impl EvaluateFluentBuilder {
/// Creates a new `EvaluateFluentBuilder`.
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 Evaluate as a reference.
pub fn as_input(&self) -> &crate::operation::evaluate::builders::EvaluateInputBuilder {
&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::evaluate::EvaluateOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::evaluate::EvaluateError,
::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::evaluate::Evaluate::operation_runtime_plugins(
self.handle.runtime_plugins.clone(),
&self.handle.conf,
self.config_override,
);
crate::operation::evaluate::Evaluate::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::evaluate::EvaluateOutput, crate::operation::evaluate::EvaluateError, 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 unique identifier of the evaluator to use for scoring. Can be a built-in evaluator (e.g., <code>Builtin.Helpfulness</code>, <code>Builtin.Correctness</code>) or a custom evaluator Id created through the control plane API.</p>
pub fn evaluator_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.evaluator_id(input.into());
self
}
/// <p>The unique identifier of the evaluator to use for scoring. Can be a built-in evaluator (e.g., <code>Builtin.Helpfulness</code>, <code>Builtin.Correctness</code>) or a custom evaluator Id created through the control plane API.</p>
pub fn set_evaluator_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_evaluator_id(input);
self
}
/// <p>The unique identifier of the evaluator to use for scoring. Can be a built-in evaluator (e.g., <code>Builtin.Helpfulness</code>, <code>Builtin.Correctness</code>) or a custom evaluator Id created through the control plane API.</p>
pub fn get_evaluator_id(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_evaluator_id()
}
/// <p>The input data containing agent session spans to be evaluated. Includes a list of spans in OpenTelemetry format from supported frameworks like Strands (AgentCore Runtime) or LangGraph with OpenInference instrumentation.</p>
pub fn evaluation_input(mut self, input: crate::types::EvaluationInput) -> Self {
self.inner = self.inner.evaluation_input(input);
self
}
/// <p>The input data containing agent session spans to be evaluated. Includes a list of spans in OpenTelemetry format from supported frameworks like Strands (AgentCore Runtime) or LangGraph with OpenInference instrumentation.</p>
pub fn set_evaluation_input(mut self, input: ::std::option::Option<crate::types::EvaluationInput>) -> Self {
self.inner = self.inner.set_evaluation_input(input);
self
}
/// <p>The input data containing agent session spans to be evaluated. Includes a list of spans in OpenTelemetry format from supported frameworks like Strands (AgentCore Runtime) or LangGraph with OpenInference instrumentation.</p>
pub fn get_evaluation_input(&self) -> &::std::option::Option<crate::types::EvaluationInput> {
self.inner.get_evaluation_input()
}
/// <p>The specific trace or span IDs to evaluate within the provided input. Allows targeting evaluation at different levels: individual tool calls, single request-response interactions (traces), or entire conversation sessions.</p>
pub fn evaluation_target(mut self, input: crate::types::EvaluationTarget) -> Self {
self.inner = self.inner.evaluation_target(input);
self
}
/// <p>The specific trace or span IDs to evaluate within the provided input. Allows targeting evaluation at different levels: individual tool calls, single request-response interactions (traces), or entire conversation sessions.</p>
pub fn set_evaluation_target(mut self, input: ::std::option::Option<crate::types::EvaluationTarget>) -> Self {
self.inner = self.inner.set_evaluation_target(input);
self
}
/// <p>The specific trace or span IDs to evaluate within the provided input. Allows targeting evaluation at different levels: individual tool calls, single request-response interactions (traces), or entire conversation sessions.</p>
pub fn get_evaluation_target(&self) -> &::std::option::Option<crate::types::EvaluationTarget> {
self.inner.get_evaluation_target()
}
///
/// Appends an item to `evaluationReferenceInputs`.
///
/// To override the contents of this collection use [`set_evaluation_reference_inputs`](Self::set_evaluation_reference_inputs).
///
/// <p>Ground truth data to compare against agent responses during evaluation. Allows to provide expected responses, assertions, and expected tool trajectories at different evaluation levels. Session-level reference inputs apply to the entire conversation, while trace-level reference inputs target specific request-response interactions identified by trace ID.</p>
pub fn evaluation_reference_inputs(mut self, input: crate::types::EvaluationReferenceInput) -> Self {
self.inner = self.inner.evaluation_reference_inputs(input);
self
}
/// <p>Ground truth data to compare against agent responses during evaluation. Allows to provide expected responses, assertions, and expected tool trajectories at different evaluation levels. Session-level reference inputs apply to the entire conversation, while trace-level reference inputs target specific request-response interactions identified by trace ID.</p>
pub fn set_evaluation_reference_inputs(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::EvaluationReferenceInput>>) -> Self {
self.inner = self.inner.set_evaluation_reference_inputs(input);
self
}
/// <p>Ground truth data to compare against agent responses during evaluation. Allows to provide expected responses, assertions, and expected tool trajectories at different evaluation levels. Session-level reference inputs apply to the entire conversation, while trace-level reference inputs target specific request-response interactions identified by trace ID.</p>
pub fn get_evaluation_reference_inputs(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::EvaluationReferenceInput>> {
self.inner.get_evaluation_reference_inputs()
}
}