use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_llm_observability::LLMObservabilityAPI;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueDataAttributesRequest;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueDataRequest;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueRequest;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueType;
use datadog_api_client::datadogV2::model::LLMObsAnnotationSchema;
use datadog_api_client::datadogV2::model::LLMObsLabelSchema;
use datadog_api_client::datadogV2::model::LLMObsLabelSchemaType;
#[tokio::main]
async fn main() {
let body = LLMObsAnnotationQueueRequest::new(LLMObsAnnotationQueueDataRequest::new(
LLMObsAnnotationQueueDataAttributesRequest::new(
"My annotation queue".to_string(),
"00000000-0000-0000-0000-000000000002".to_string(),
)
.annotation_schema(LLMObsAnnotationSchema::new(vec![LLMObsLabelSchema::new(
"quality".to_string(),
LLMObsLabelSchemaType::SCORE,
)
.description("Rating of the response quality.".to_string())
.has_assessment(false)
.has_reasoning(false)
.id("abc-123".to_string())
.is_assessment(false)
.is_integer(false)
.is_required(true)
.max(5.0 as f64)
.min(0.0 as f64)
.values(vec![
"good".to_string(),
"bad".to_string(),
"neutral".to_string(),
])]))
.description("Queue for annotating customer support traces".to_string()),
LLMObsAnnotationQueueType::QUEUES,
));
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.CreateLLMObsAnnotationQueue", true);
let api = LLMObservabilityAPI::with_config(configuration);
let resp = api.create_llm_obs_annotation_queue(body).await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}