Aggregate Agent Observability experimentation

// Aggregate Agent Observability experimentation 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.LLMObsExperimentationAnalyticsRequest{
		Data: datadogV2.LLMObsExperimentationAnalyticsDataRequest{
			Attributes: datadogV2.LLMObsExperimentationAnalyticsDataAttributesRequest{
				Aggregate: datadogV2.LLMObsExperimentationAnalyticsAggregate{
					Compute: []datadogV2.LLMObsExperimentationAnalyticsCompute{
						{
							Metric: "score_value",
							Name:   datadog.PtrString("avg_faithfulness"),
						},
					},
					DatasetVersion: *datadog.NewNullableInt64(nil),
					GroupBy: []datadogV2.LLMObsExperimentationAnalyticsGroupBy{
						{
							Field: "span_id",
						},
					},
					Indexes: []string{
						"experiment-evals",
					},
					Limit: *datadog.NewNullableInt32(datadog.PtrInt32(1000)),
					Search: datadogV2.LLMObsExperimentationAnalyticsSearch{
						Query: "@experiment_id:3fd6b5e0-8910-4b1c-a7d0-5b84de329012",
					},
					Time: &datadogV2.LLMObsExperimentationAnalyticsTimeRange{
						From: 1705312200000,
						To:   1705315800000,
					},
				},
			},
			Type: datadogV2.LLMOBSEXPERIMENTATIONTYPE_EXPERIMENTATION,
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	configuration := datadog.NewConfiguration()
	configuration.SetUnstableOperationEnabled("v2.AggregateLLMObsExperimentation", true)
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewAgentObservabilityApi(apiClient)
	resp, r, err := api.AggregateLLMObsExperimentation(ctx, body)

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

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

// Aggregate Agent Observability experimentation 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.LLMObsExperimentationAnalyticsAggregate;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsCompute;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsDataAttributesRequest;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsDataRequest;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsGroupBy;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsRequest;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsResponse;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsSearch;
import com.datadog.api.client.v2.model.LLMObsExperimentationAnalyticsTimeRange;
import com.datadog.api.client.v2.model.LLMObsExperimentationType;
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.aggregateLLMObsExperimentation", true);
    AgentObservabilityApi apiInstance = new AgentObservabilityApi(defaultClient);

    LLMObsExperimentationAnalyticsRequest body =
        new LLMObsExperimentationAnalyticsRequest()
            .data(
                new LLMObsExperimentationAnalyticsDataRequest()
                    .attributes(
                        new LLMObsExperimentationAnalyticsDataAttributesRequest()
                            .aggregate(
                                new LLMObsExperimentationAnalyticsAggregate()
                                    .compute(
                                        Collections.singletonList(
                                            new LLMObsExperimentationAnalyticsCompute()
                                                .metric("score_value")
                                                .name("avg_faithfulness")))
                                    .datasetVersion(null)
                                    .groupBy(
                                        Collections.singletonList(
                                            new LLMObsExperimentationAnalyticsGroupBy()
                                                .field("span_id")))
                                    .indexes(Collections.singletonList("experiment-evals"))
                                    .limit(1000)
                                    .search(
                                        new LLMObsExperimentationAnalyticsSearch()
                                            .query(
                                                "@experiment_id:3fd6b5e0-8910-4b1c-a7d0-5b84de329012"))
                                    .time(
                                        new LLMObsExperimentationAnalyticsTimeRange()
                                            .from(1705312200000L)
                                            .to(1705315800000L))))
                    .type(LLMObsExperimentationType.EXPERIMENTATION));

    try {
      LLMObsExperimentationAnalyticsResponse result =
          apiInstance.aggregateLLMObsExperimentation(body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println(
          "Exception when calling AgentObservabilityApi#aggregateLLMObsExperimentation");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

"""
Aggregate Agent Observability experimentation 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_experimentation_analytics_aggregate import (
    LLMObsExperimentationAnalyticsAggregate,
)
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_compute import LLMObsExperimentationAnalyticsCompute
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_data_attributes_request import (
    LLMObsExperimentationAnalyticsDataAttributesRequest,
)
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_data_request import (
    LLMObsExperimentationAnalyticsDataRequest,
)
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_group_by import LLMObsExperimentationAnalyticsGroupBy
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_request import LLMObsExperimentationAnalyticsRequest
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_search import LLMObsExperimentationAnalyticsSearch
from datadog_api_client.v2.model.llm_obs_experimentation_analytics_time_range import (
    LLMObsExperimentationAnalyticsTimeRange,
)
from datadog_api_client.v2.model.llm_obs_experimentation_type import LLMObsExperimentationType

body = LLMObsExperimentationAnalyticsRequest(
    data=LLMObsExperimentationAnalyticsDataRequest(
        attributes=LLMObsExperimentationAnalyticsDataAttributesRequest(
            aggregate=LLMObsExperimentationAnalyticsAggregate(
                compute=[
                    LLMObsExperimentationAnalyticsCompute(
                        metric="score_value",
                        name="avg_faithfulness",
                    ),
                ],
                dataset_version=None,
                group_by=[
                    LLMObsExperimentationAnalyticsGroupBy(
                        field="span_id",
                    ),
                ],
                indexes=[
                    "experiment-evals",
                ],
                limit=1000,
                search=LLMObsExperimentationAnalyticsSearch(
                    query="@experiment_id:3fd6b5e0-8910-4b1c-a7d0-5b84de329012",
                ),
                time=LLMObsExperimentationAnalyticsTimeRange(
                    _from=1705312200000,
                    to=1705315800000,
                ),
            ),
        ),
        type=LLMObsExperimentationType.EXPERIMENTATION,
    ),
)

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

    print(response)

# Aggregate Agent Observability experimentation returns "OK" response

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

body = DatadogAPIClient::V2::LLMObsExperimentationAnalyticsRequest.new({
  data: DatadogAPIClient::V2::LLMObsExperimentationAnalyticsDataRequest.new({
    attributes: DatadogAPIClient::V2::LLMObsExperimentationAnalyticsDataAttributesRequest.new({
      aggregate: DatadogAPIClient::V2::LLMObsExperimentationAnalyticsAggregate.new({
        compute: [
          DatadogAPIClient::V2::LLMObsExperimentationAnalyticsCompute.new({
            metric: "score_value",
            name: "avg_faithfulness",
          }),
        ],
        dataset_version: nil,
        group_by: [
          DatadogAPIClient::V2::LLMObsExperimentationAnalyticsGroupBy.new({
            field: "span_id",
          }),
        ],
        indexes: [
          "experiment-evals",
        ],
        limit: 1000,
        search: DatadogAPIClient::V2::LLMObsExperimentationAnalyticsSearch.new({
          query: "@experiment_id:3fd6b5e0-8910-4b1c-a7d0-5b84de329012",
        }),
        time: DatadogAPIClient::V2::LLMObsExperimentationAnalyticsTimeRange.new({
          from: 1705312200000,
          to: 1705315800000,
        }),
      }),
    }),
    type: DatadogAPIClient::V2::LLMObsExperimentationType::EXPERIMENTATION,
  }),
})
p api_instance.aggregate_llm_obs_experimentation(body)

// Aggregate Agent Observability experimentation returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_agent_observability::AgentObservabilityAPI;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsAggregate;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsCompute;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsDataAttributesRequest;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsDataRequest;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsGroupBy;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsRequest;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsSearch;
use datadog_api_client::datadogV2::model::LLMObsExperimentationAnalyticsTimeRange;
use datadog_api_client::datadogV2::model::LLMObsExperimentationType;

#[tokio::main]
async fn main() {
    let body =
        LLMObsExperimentationAnalyticsRequest::new(LLMObsExperimentationAnalyticsDataRequest::new(
            LLMObsExperimentationAnalyticsDataAttributesRequest::new(
                LLMObsExperimentationAnalyticsAggregate::new(
                    vec![
                        LLMObsExperimentationAnalyticsCompute::new("score_value".to_string())
                            .name("avg_faithfulness".to_string()),
                    ],
                    vec!["experiment-evals".to_string()],
                    LLMObsExperimentationAnalyticsSearch::new(
                        "@experiment_id:3fd6b5e0-8910-4b1c-a7d0-5b84de329012".to_string(),
                    ),
                )
                .dataset_version(None)
                .group_by(vec![LLMObsExperimentationAnalyticsGroupBy::new(
                    "span_id".to_string(),
                )])
                .limit(Some(1000))
                .time(LLMObsExperimentationAnalyticsTimeRange::new(
                    1705312200000,
                    1705315800000,
                )),
            ),
            LLMObsExperimentationType::EXPERIMENTATION,
        ));
    let mut configuration = datadog::Configuration::new();
    configuration.set_unstable_operation_enabled("v2.aggregate_llm_obs_experimentation", true);
    let api = AgentObservabilityAPI::with_config(configuration);
    let resp = api.aggregate_llm_obs_experimentation(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

/**
 * Aggregate Agent Observability experimentation returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration({
  authMethods: {
    AuthZ: {
      accessToken: process.env.DD_BEARER_TOKEN as string,
    },
  },
});
configuration.unstableOperations["v2.aggregateLLMObsExperimentation"] = true;
const apiInstance = new v2.AgentObservabilityApi(configuration);

const params: v2.AgentObservabilityApiAggregateLLMObsExperimentationRequest = {
  body: {
    data: {
      attributes: {
        aggregate: {
          compute: [
            {
              metric: "score_value",
              name: "avg_faithfulness",
            },
          ],
          datasetVersion: undefined,
          groupBy: [
            {
              field: "span_id",
            },
          ],
          indexes: ["experiment-evals"],
          limit: 1000,
          search: {
            query: "@experiment_id:3fd6b5e0-8910-4b1c-a7d0-5b84de329012",
          },
          time: {
            from: 1705312200000,
            to: 1705315800000,
          },
        },
      },
      type: "experimentation",
    },
  },
};

apiInstance
  .aggregateLLMObsExperimentation(params)
  .then((data: v2.LLMObsExperimentationAnalyticsResponse) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));