주석 대기열 레이블 스키마 업데이트

"""
Update annotation queue label schema returns "OK" response
"""

from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.agent_observability_api import AgentObservabilityApi
from datadog_api_client.v2.model.llm_obs_annotation_queue_label_schema_update_attributes import (
    LLMObsAnnotationQueueLabelSchemaUpdateAttributes,
)
from datadog_api_client.v2.model.llm_obs_annotation_queue_label_schema_update_data import (
    LLMObsAnnotationQueueLabelSchemaUpdateData,
)
from datadog_api_client.v2.model.llm_obs_annotation_queue_label_schema_update_request import (
    LLMObsAnnotationQueueLabelSchemaUpdateRequest,
)
from datadog_api_client.v2.model.llm_obs_annotation_queue_type import LLMObsAnnotationQueueType
from datadog_api_client.v2.model.llm_obs_annotation_schema import LLMObsAnnotationSchema
from datadog_api_client.v2.model.llm_obs_label_schema import LLMObsLabelSchema
from datadog_api_client.v2.model.llm_obs_label_schema_type import LLMObsLabelSchemaType

body = LLMObsAnnotationQueueLabelSchemaUpdateRequest(
    data=LLMObsAnnotationQueueLabelSchemaUpdateData(
        attributes=LLMObsAnnotationQueueLabelSchemaUpdateAttributes(
            annotation_schema=LLMObsAnnotationSchema(
                label_schemas=[
                    LLMObsLabelSchema(
                        description="Rating of the response quality.",
                        has_assessment=False,
                        has_reasoning=False,
                        id="abc-123",
                        is_assessment=False,
                        is_integer=False,
                        is_required=True,
                        max=5.0,
                        min=0.0,
                        name="quality",
                        type=LLMObsLabelSchemaType.SCORE,
                        values=[
                            "good",
                            "bad",
                            "neutral",
                        ],
                    ),
                ],
            ),
        ),
        type=LLMObsAnnotationQueueType.QUEUES,
    ),
)

configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["update_llm_obs_annotation_queue_label_schema"] = True
with ApiClient(configuration) as api_client:
    api_instance = AgentObservabilityApi(api_client)
    response = api_instance.update_llm_obs_annotation_queue_label_schema(queue_id="queue_id", body=body)

    print(response)

# Update annotation queue label schema returns "OK" response

require "datadog_api_client"
DatadogAPIClient.configure do |config|
  config.access_token = ENV["DD_BEARER_TOKEN"]
  config.unstable_operations["v2.update_llm_obs_annotation_queue_label_schema".to_sym] = true
end
api_instance = DatadogAPIClient::V2::AgentObservabilityAPI.new

body = DatadogAPIClient::V2::LLMObsAnnotationQueueLabelSchemaUpdateRequest.new({
  data: DatadogAPIClient::V2::LLMObsAnnotationQueueLabelSchemaUpdateData.new({
    attributes: DatadogAPIClient::V2::LLMObsAnnotationQueueLabelSchemaUpdateAttributes.new({
      annotation_schema: DatadogAPIClient::V2::LLMObsAnnotationSchema.new({
        label_schemas: [
          DatadogAPIClient::V2::LLMObsLabelSchema.new({
            description: "Rating of the response quality.",
            has_assessment: false,
            has_reasoning: false,
            id: "abc-123",
            is_assessment: false,
            is_integer: false,
            is_required: true,
            max: 5.0,
            min: 0.0,
            name: "quality",
            type: DatadogAPIClient::V2::LLMObsLabelSchemaType::SCORE,
            values: [
              "good",
              "bad",
              "neutral",
            ],
          }),
        ],
      }),
    }),
    type: DatadogAPIClient::V2::LLMObsAnnotationQueueType::QUEUES,
  }),
})
p api_instance.update_llm_obs_annotation_queue_label_schema("queue_id", body)

// Update annotation queue label schema returns "OK" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.LLMObsAnnotationQueueLabelSchemaUpdateRequest{
		Data: datadogV2.LLMObsAnnotationQueueLabelSchemaUpdateData{
			Attributes: datadogV2.LLMObsAnnotationQueueLabelSchemaUpdateAttributes{
				AnnotationSchema: datadogV2.LLMObsAnnotationSchema{
					LabelSchemas: []datadogV2.LLMObsLabelSchema{
						{
							Description:   datadog.PtrString("Rating of the response quality."),
							HasAssessment: datadog.PtrBool(false),
							HasReasoning:  datadog.PtrBool(false),
							Id:            datadog.PtrString("abc-123"),
							IsAssessment:  datadog.PtrBool(false),
							IsInteger:     datadog.PtrBool(false),
							IsRequired:    datadog.PtrBool(true),
							Max:           datadog.PtrFloat64(5.0),
							Min:           datadog.PtrFloat64(0.0),
							Name:          "quality",
							Type:          datadogV2.LLMOBSLABELSCHEMATYPE_SCORE,
							Values: []string{
								"good",
								"bad",
								"neutral",
							},
						},
					},
				},
			},
			Type: datadogV2.LLMOBSANNOTATIONQUEUETYPE_QUEUES,
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	configuration := datadog.NewConfiguration()
	configuration.SetUnstableOperationEnabled("v2.UpdateLLMObsAnnotationQueueLabelSchema", true)
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewAgentObservabilityApi(apiClient)
	resp, r, err := api.UpdateLLMObsAnnotationQueueLabelSchema(ctx, "queue_id", body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `AgentObservabilityApi.UpdateLLMObsAnnotationQueueLabelSchema`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `AgentObservabilityApi.UpdateLLMObsAnnotationQueueLabelSchema`:\n%s\n", responseContent)
}

// Update annotation queue label schema returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.AgentObservabilityApi;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaResponse;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaUpdateAttributes;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaUpdateData;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueLabelSchemaUpdateRequest;
import com.datadog.api.client.v2.model.LLMObsAnnotationQueueType;
import com.datadog.api.client.v2.model.LLMObsAnnotationSchema;
import com.datadog.api.client.v2.model.LLMObsLabelSchema;
import com.datadog.api.client.v2.model.LLMObsLabelSchemaType;
import java.util.Arrays;
import java.util.Collections;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
    defaultClient.setUnstableOperationEnabled("v2.updateLLMObsAnnotationQueueLabelSchema", true);
    AgentObservabilityApi apiInstance = new AgentObservabilityApi(defaultClient);

    LLMObsAnnotationQueueLabelSchemaUpdateRequest body =
        new LLMObsAnnotationQueueLabelSchemaUpdateRequest()
            .data(
                new LLMObsAnnotationQueueLabelSchemaUpdateData()
                    .attributes(
                        new LLMObsAnnotationQueueLabelSchemaUpdateAttributes()
                            .annotationSchema(
                                new LLMObsAnnotationSchema()
                                    .labelSchemas(
                                        Collections.singletonList(
                                            new LLMObsLabelSchema()
                                                .description("Rating of the response quality.")
                                                .hasAssessment(false)
                                                .hasReasoning(false)
                                                .id("abc-123")
                                                .isAssessment(false)
                                                .isInteger(false)
                                                .isRequired(true)
                                                .max(5.0)
                                                .name("quality")
                                                .type(LLMObsLabelSchemaType.SCORE)
                                                .values(Arrays.asList("good", "bad", "neutral"))))))
                    .type(LLMObsAnnotationQueueType.QUEUES));

    try {
      LLMObsAnnotationQueueLabelSchemaResponse result =
          apiInstance.updateLLMObsAnnotationQueueLabelSchema(
              "00000000-0000-0000-0000-000000000001", body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println(
          "Exception when calling AgentObservabilityApi#updateLLMObsAnnotationQueueLabelSchema");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

// Update annotation queue label schema returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_agent_observability::AgentObservabilityAPI;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueLabelSchemaUpdateAttributes;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueLabelSchemaUpdateData;
use datadog_api_client::datadogV2::model::LLMObsAnnotationQueueLabelSchemaUpdateRequest;
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 = LLMObsAnnotationQueueLabelSchemaUpdateRequest::new(
        LLMObsAnnotationQueueLabelSchemaUpdateData::new(
            LLMObsAnnotationQueueLabelSchemaUpdateAttributes::new(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(),
                        ]),
                ],
            )),
            LLMObsAnnotationQueueType::QUEUES,
        ),
    );
    let mut configuration = datadog::Configuration::new();
    configuration.set_unstable_operation_enabled("v2.UpdateLLMObsAnnotationQueueLabelSchema", true);
    let api = AgentObservabilityAPI::with_config(configuration);
    let resp = api
        .update_llm_obs_annotation_queue_label_schema("queue_id".to_string(), body)
        .await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}