List LLM integration accounts
https://api.datadoghq.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.us3.datadoghq.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.us5.datadoghq.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.datadoghq.eu/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.ap1.datadoghq.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.ap2.datadoghq.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.uk1.datadoghq.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.ddog-gov.com/api/v2/llm-obs/v1/integrations/{integration}/accountshttps://api.us2.ddog-gov.com/api/v2/llm-obs/v1/integrations/{integration}/accounts概要
Retrieve the list of configured accounts for the specified LLM provider integration.
引数
パスパラメーター
integration [required]The name of the LLM integration.
openai, amazon_bedrock, anthropic, azure_openai, vertex_ai, llmproxy応答
OK
account_id [required]Provider-specific account identifier.
account_name [required]Human-readable name for the integration account.
account_regionProvider region associated with the account, if applicable.
azure_openai_metadataAzure OpenAI-specific metadata for an integration account or inference request.
deployment_idThe Azure OpenAI deployment ID.
model_versionThe model version deployed in Azure.
resource_nameThe Azure OpenAI resource name.
id [required]Unique identifier for the integration account.
integration [required]The name of the LLM provider integration.
vertex_ai_metadataVertex AI-specific metadata for an integration account or inference request.
locationThe Vertex AI region.
projectThe Google Cloud project ID.
project_idsList of Google Cloud project IDs available to the service account.
{
"account_id": "org-XYZ123",
"account_name": "Production OpenAI",
"account_region": "us-east-1",
"azure_openai_metadata": {
"deployment_id": "my-gpt4-deployment",
"model_version": "0613",
"resource_name": "my-azure-resource"
},
"id": "account-abc123",
"integration": "openai",
"vertex_ai_metadata": {
"location": "us-central1",
"project": "my-gcp-project",
"project_ids": [
"my-gcp-project"
]
}
}Bad Request
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Unauthorized
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Forbidden
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"errors": [
{
"detail": "Missing required attribute in body",
"meta": {},
"source": {
"header": "Authorization",
"parameter": "limit",
"pointer": "/data/attributes/title"
},
"status": "400",
"title": "Bad Request"
}
]
}Too many requests
API error response.
errors [required]A list of errors.
{
"errors": [
"Bad Request"
]
}コード例
# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export integration="openai"
# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/llm-obs/v1/integrations/${integration}/accounts" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"// List LLM integration accounts 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() {
ctx := datadog.NewDefaultContext(context.Background())
ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.ListLLMObsIntegrationAccounts", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewAgentObservabilityApi(apiClient)
resp, r, err := api.ListLLMObsIntegrationAccounts(ctx, datadogV2.LLMOBSINTEGRATIONNAME_OPENAI)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `AgentObservabilityApi.ListLLMObsIntegrationAccounts`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `AgentObservabilityApi.ListLLMObsIntegrationAccounts`:\n%s\n", responseContent)
}
Instructions
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"// List LLM integration accounts 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.LLMObsIntegrationAccount;
import com.datadog.api.client.v2.model.LLMObsIntegrationName;
import java.util.List;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
defaultClient.setUnstableOperationEnabled("v2.listLLMObsIntegrationAccounts", true);
AgentObservabilityApi apiInstance = new AgentObservabilityApi(defaultClient);
try {
List<LLMObsIntegrationAccount> result =
apiInstance.listLLMObsIntegrationAccounts(LLMObsIntegrationName.OPENAI);
System.out.println(result);
} catch (ApiException e) {
System.err.println(
"Exception when calling AgentObservabilityApi#listLLMObsIntegrationAccounts");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
Instructions
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java""""
List LLM integration accounts 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_integration_name import LLMObsIntegrationName
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["list_llm_obs_integration_accounts"] = True
with ApiClient(configuration) as api_client:
api_instance = AgentObservabilityApi(api_client)
response = api_instance.list_llm_obs_integration_accounts(
integration=LLMObsIntegrationName.OPENAI,
)
print(response)
Instructions
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"# List LLM integration accounts returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.list_llm_obs_integration_accounts".to_sym] = true
end
api_instance = DatadogAPIClient::V2::AgentObservabilityAPI.new
p api_instance.list_llm_obs_integration_accounts(LLMObsIntegrationName::OPENAI)
Instructions
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"// List LLM integration accounts returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_agent_observability::AgentObservabilityAPI;
use datadog_api_client::datadogV2::model::LLMObsIntegrationName;
#[tokio::main]
async fn main() {
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.list_llm_obs_integration_accounts", true);
let api = AgentObservabilityAPI::with_config(configuration);
let resp = api
.list_llm_obs_integration_accounts(LLMObsIntegrationName::OPENAI)
.await;
if let Ok(value) = resp {
println!("{:#?}", value);
} else {
println!("{:#?}", resp.unwrap_err());
}
}
Instructions
First install the library and its dependencies and then save the example to src/main.rs and run following commands:
DD_SITE="datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us3.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us5.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="datadoghq.eu" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ap1.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ap2.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="uk1.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us2.ddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run/**
* List LLM integration accounts 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.listLLMObsIntegrationAccounts"] = true;
const apiInstance = new v2.AgentObservabilityApi(configuration);
const params: v2.AgentObservabilityApiListLLMObsIntegrationAccountsRequest = {
integration: "openai",
};
apiInstance
.listLLMObsIntegrationAccounts(params)
.then((data: v2.LLMObsIntegrationAccount[]) => {
console.log(
"API called successfully. Returned data: " + JSON.stringify(data)
);
})
.catch((error: any) => console.error(error));
Instructions
First install the library and its dependencies and then save the example to example.ts and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"