This page provides information on supported authentication methods and clients, along with sample code for connecting your apps to Azure AI services using Service Connector. This page also lists default environment variable names and values obtained when creating the service connection.
Supported compute services
Service Connector can be used to connect the following compute services to Azure AI Services:
- Azure App Service
- Azure Container Apps
- Azure Functions
- Azure Kubernetes Service (AKS)
- Azure Spring Apps
Supported authentication types and client types
The table below indicates which combinations of authentication methods and clients are supported for connecting your compute service to individual Azure AI Services using Service Connector. A “Yes” indicates that the combination is supported, while a “No” indicates that it is not supported.
Client type |
System-assigned managed identity |
User-assigned managed identity |
Secret/connection string |
Service principal |
.NET |
Yes |
Yes |
Yes |
Yes |
Java |
Yes |
Yes |
Yes |
Yes |
Node.js |
Yes |
Yes |
Yes |
Yes |
Python |
Yes |
Yes |
Yes |
Yes |
None |
Yes |
Yes |
Yes |
Yes |
This table indicates that all combinations of client types and authentication methods in the table are supported. All client types can use any of the authentication methods to connect to Azure AI Services using Service Connector.
Default environment variable names or application properties and sample code
Use the connection details below to connect compute services to Azure AI Services. For more information about naming conventions, refer to the Service Connector internals article.
System-assigned managed identity (recommended)
Default environment variable name |
Description |
Sample value |
AZURE_AISERVICES_OPENAI_BASE |
Azure OpenAI endpoint |
https://<your-Azure-AI-Services-endpoint>.openai.azure.com/ |
AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT |
Azure Cognitive Services token provider service |
https://<your-Azure-AI-Services-endpoint>.cognitiveservices.azure.com/ |
AZURE_AISERVICES_SPEECH_ENDPOINT |
Speech to Text (Standard) API endpoint |
https://<___location>.stt.speech.microsoft.com |
Sample code
Refer to the steps and code below to connect to Azure AI Services using a system-assigned managed identity.
You can use the Azure client library to access various cognitive APIs that Azure AI Services support. We use Azure AI Text Analytics as an example in this sample. Refer to Authenticate requests to Azure AI services to call the cognitive APIs directly.
Install the following dependencies. We use Azure.AI.TextAnalytics
as an example.
dotnet add package Azure.AI.TextAnalytics
dotnet add package Azure.Identity
Authenticate using the Azure Identity library and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
using Azure.AI.TextAnalytics;
using Azure.Identity;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
// Uncomment the following lines corresponding to the authentication type you want to use.
// system-assigned managed identity
// var credential = new DefaultAzureCredential();
// user-assigned managed identity
// var credential = new DefaultAzureCredential(
// new DefaultAzureCredentialOptions
// {
// ManagedIdentityClientId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTID");
// });
// service principal
// var tenantId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_TENANTID");
// var clientId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTID");
// var clientSecret = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTSECRET");
// var credential = new ClientSecretCredential(tenantId, clientId, clientSecret);
TextAnalyticsClient languageServiceClient = new(
new Uri(endpoint),
credential);
Add the following dependencies in your pom.xml file. We use azure-ai-textanalytics
as an example.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-textanalytics</artifactId>
<version>5.1.12</version>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<version>1.11.4</version>
</dependency>
Authenticate using azure-identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
// Uncomment the following lines corresponding to the authentication type you want to use.
// for system-managed identity
// DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
// for user-assigned managed identity
// DefaultAzureCredential credential = new DefaultAzureCredentialBuilder()
// .managedIdentityClientId(System.getenv("AZURE_AISERVICES_CLIENTID"))
// .build();
// for service principal
// ClientSecretCredential credential = new ClientSecretCredentialBuilder()
// .clientId(System.getenv("AZURE_AISERVICES_CLIENTID"))
// .clientSecret(System.getenv("AZURE_AISERVICES_CLIENTSECRET"))
// .tenantId(System.getenv("AZURE_AISERVICES_TENANTID"))
// .build();
String endpoint = System.getenv("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
TextAnalyticsClient languageClient = new TextAnalyticsClientBuilder()
.credential(credential)
.endpoint(endpoint)
.buildClient();
- Install the following dependencies. We use
azure-ai-textanalytics
as an example.
pip install azure-ai-textanalytics==5.1.0
pip install azure-identity
- Authenticate using
azure-identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
import os
from azure.ai.textanalytics import TextAnalyticsClient
from azure.identity import ManagedIdentityCredential, ClientSecretCredential
# Uncomment the following lines corresponding to the authentication type you want to use.
# system-assigned managed identity
# cred = ManagedIdentityCredential()
# user-assigned managed identity
# managed_identity_client_id = os.getenv('AZURE_AISERVICES_CLIENTID')
# cred = ManagedIdentityCredential(client_id=managed_identity_client_id)
# service principal
# tenant_id = os.getenv('AZURE_AISERVICES_TENANTID')
# client_id = os.getenv('AZURE_AISERVICES_CLIENTID')
# client_secret = os.getenv('AZURE_AISERVICES_CLIENTSECRET')
# cred = ClientSecretCredential(tenant_id=tenant_id, client_id=client_id, client_secret=client_secret)
endpoint = os.getenv('AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT')
language_service_client = TextAnalyticsClient(
endpoint=endpoint,
credential=cred)
Install the following dependencies. We use ai-text-analytics
as an example.
npm install @azure/ai-text-analytics@5.1.0
npm install @azure/identity
Authenticate using @azure/identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
import { DefaultAzureCredential,ClientSecretCredential } from "@azure/identity";
const { TextAnalyticsClient } = require("@azure/ai-text-analytics");
// Uncomment the following lines corresponding to the authentication type you want to use.
// for system-assigned managed identity
// const credential = new DefaultAzureCredential();
// for user-assigned managed identity
// const clientId = process.env.AZURE_AISERVICES_CLIENTID;
// const credential = new DefaultAzureCredential({
// managedIdentityClientId: clientId
// });
// for service principal
// const tenantId = process.env.AZURE_AISERVICES_TENANTID;
// const clientId = process.env.AZURE_AISERVICES_CLIENTID;
// const clientSecret = process.env.AZURE_AISERVICES_CLIENTSECRET;
// const credential = new ClientSecretCredential(tenantId, clientId, clientSecret);
const endpoint = process.env.AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT;
const languageClient = new TextAnalyticsClient(endpoint, credential);
User-assigned managed identity
Default environment variable name |
Description |
Sample value |
AZURE_AISERVICES_OPENAI_BASE |
Azure OpenAI endpoint |
https://<your-Azure-AI-Services-endpoint>.openai.azure.com/ |
AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT |
Azure Cognitive Services token provider service |
https://<your-Azure-AI-Services-endpoint>.cognitiveservices.azure.com/ |
AZURE_AISERVICES_SPEECH_ENDPOINT |
Speech to Text (Standard) API endpoint |
https://<___location>.stt.speech.microsoft.com |
AZURE_AISERVICES_CLIENTID |
Your client ID |
<client-ID> |
Sample code
Refer to the steps and code below to connect to Azure AI Services using a user-assigned managed identity.
You can use the Azure client library to access various cognitive APIs that Azure AI Services support. We use Azure AI Text Analytics as an example in this sample. Refer to Authenticate requests to Azure AI services to call the cognitive APIs directly.
Install the following dependencies. We use Azure.AI.TextAnalytics
as an example.
dotnet add package Azure.AI.TextAnalytics
dotnet add package Azure.Identity
Authenticate using the Azure Identity library and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
using Azure.AI.TextAnalytics;
using Azure.Identity;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
// Uncomment the following lines corresponding to the authentication type you want to use.
// system-assigned managed identity
// var credential = new DefaultAzureCredential();
// user-assigned managed identity
// var credential = new DefaultAzureCredential(
// new DefaultAzureCredentialOptions
// {
// ManagedIdentityClientId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTID");
// });
// service principal
// var tenantId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_TENANTID");
// var clientId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTID");
// var clientSecret = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTSECRET");
// var credential = new ClientSecretCredential(tenantId, clientId, clientSecret);
TextAnalyticsClient languageServiceClient = new(
new Uri(endpoint),
credential);
Add the following dependencies in your pom.xml file. We use azure-ai-textanalytics
as an example.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-textanalytics</artifactId>
<version>5.1.12</version>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<version>1.11.4</version>
</dependency>
Authenticate using azure-identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
// Uncomment the following lines corresponding to the authentication type you want to use.
// for system-managed identity
// DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
// for user-assigned managed identity
// DefaultAzureCredential credential = new DefaultAzureCredentialBuilder()
// .managedIdentityClientId(System.getenv("AZURE_AISERVICES_CLIENTID"))
// .build();
// for service principal
// ClientSecretCredential credential = new ClientSecretCredentialBuilder()
// .clientId(System.getenv("AZURE_AISERVICES_CLIENTID"))
// .clientSecret(System.getenv("AZURE_AISERVICES_CLIENTSECRET"))
// .tenantId(System.getenv("AZURE_AISERVICES_TENANTID"))
// .build();
String endpoint = System.getenv("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
TextAnalyticsClient languageClient = new TextAnalyticsClientBuilder()
.credential(credential)
.endpoint(endpoint)
.buildClient();
- Install the following dependencies. We use
azure-ai-textanalytics
as an example.
pip install azure-ai-textanalytics==5.1.0
pip install azure-identity
- Authenticate using
azure-identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
import os
from azure.ai.textanalytics import TextAnalyticsClient
from azure.identity import ManagedIdentityCredential, ClientSecretCredential
# Uncomment the following lines corresponding to the authentication type you want to use.
# system-assigned managed identity
# cred = ManagedIdentityCredential()
# user-assigned managed identity
# managed_identity_client_id = os.getenv('AZURE_AISERVICES_CLIENTID')
# cred = ManagedIdentityCredential(client_id=managed_identity_client_id)
# service principal
# tenant_id = os.getenv('AZURE_AISERVICES_TENANTID')
# client_id = os.getenv('AZURE_AISERVICES_CLIENTID')
# client_secret = os.getenv('AZURE_AISERVICES_CLIENTSECRET')
# cred = ClientSecretCredential(tenant_id=tenant_id, client_id=client_id, client_secret=client_secret)
endpoint = os.getenv('AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT')
language_service_client = TextAnalyticsClient(
endpoint=endpoint,
credential=cred)
Install the following dependencies. We use ai-text-analytics
as an example.
npm install @azure/ai-text-analytics@5.1.0
npm install @azure/identity
Authenticate using @azure/identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
import { DefaultAzureCredential,ClientSecretCredential } from "@azure/identity";
const { TextAnalyticsClient } = require("@azure/ai-text-analytics");
// Uncomment the following lines corresponding to the authentication type you want to use.
// for system-assigned managed identity
// const credential = new DefaultAzureCredential();
// for user-assigned managed identity
// const clientId = process.env.AZURE_AISERVICES_CLIENTID;
// const credential = new DefaultAzureCredential({
// managedIdentityClientId: clientId
// });
// for service principal
// const tenantId = process.env.AZURE_AISERVICES_TENANTID;
// const clientId = process.env.AZURE_AISERVICES_CLIENTID;
// const clientSecret = process.env.AZURE_AISERVICES_CLIENTSECRET;
// const credential = new ClientSecretCredential(tenantId, clientId, clientSecret);
const endpoint = process.env.AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT;
const languageClient = new TextAnalyticsClient(endpoint, credential);
Connection string
Default environment variable name |
Description |
Sample value |
AZURE_AISERVICES_OPENAI_BASE |
Azure OpenAI endpoint |
https://<your-Azure-AI-Services-endpoint>.openai.azure.com/ |
AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT |
Azure Cognitive Services token provider service |
https://<your-Azure-AI-Services-endpoint>.cognitiveservices.azure.com/ |
AZURE_AISERVICES_SPEECH_ENDPOINT |
Speech to Text (Standard) API endpoint |
https://<___location>.stt.speech.microsoft.com |
AZURE_AISERVICES_KEY |
Azure AI Services API key |
<api-key> |
Sample code
Refer to the steps and code below to connect to Azure AI Services using a connection string.
You can use the Azure client library to access various cognitive APIs that Azure AI Services support. We use Azure AI Text Analytics as an example in this sample. Refer to Authenticate requests to Azure AI services to call the cognitive APIs directly.
Install the following dependencies. We use Azure.AI.TextAnalytics
as an example.
dotnet add package Azure.AI.TextAnalytics
dotnet add package Azure.Core --version 1.40.0
Get the Azure AI Services endpoint and key from the environment variables added by Service Connector.
using Azure.AI.TextAnalytics;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT")
string key = Environment.GetEnvironmentVariable("AZURE_AISERVICES_KEY");
TextAnalyticsClient languageServiceClient = new(
new Uri(endpoint),
new AzureKeyCredential(key));
- Add the following dependencies in your pom.xml file. We use
azure-ai-textanalytics
as an example.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-core</artifactId>
<version>1.49.1</version>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-textanalytics</artifactId>
<version>5.1.12</version>
</dependency>
- Get the Azure AI Services endpoint and key from the environment variables added by Service Connector.
String endpoint = System.getenv("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
String key = System.getenv("AZURE_AISERVICES_KEY");
TextAnalyticsClient languageClient = new TextAnalyticsClientBuilder()
.credential(new AzureKeyCredential(key))
.endpoint(endpoint)
.buildClient();
- Install the following dependencies. We use
azure-ai-textanalytics
as an example.
pip install azure-ai-textanalytics==5.1.0
pip install azure-core
- Get the Azure AI Services endpoint and key from the environment variables added by Service Connector.
import os
from azure.ai.textanalytics import TextAnalyticsClient
from azure.core.credentials import AzureKeyCredential
key = os.environ['AZURE_AISERVICES_KEY']
endpoint = os.environ['AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT']
language_service_client = TextAnalyticsClient(
endpoint=retrieved_endpoint,
credential=AzureKeyCredential(key))
Install the following dependency. We use ai-text-analytics
as an example.
npm install @azure/ai-text-analytics@5.1.0
Get the Azure AI Services endpoint and key from the environment variables added by Service Connector.
const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
const endpoint = process.env.AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT;
const credential = new AzureKeyCredential(process.env.AZURE_AISERVICES_KEY);
const languageClient = new TextAnalyticsClient(endpoint, credential);
Service principal
Default environment variable name |
Description |
Sample value |
AZURE_AISERVICES_OPENAI_BASE |
Azure OpenAI endpoint |
https://<your-Azure-AI-Services-endpoint>.openai.azure.com/ |
AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT |
Azure Cognitive Services token provider service |
https://<your-Azure-AI-Services-endpoint>.cognitiveservices.azure.com/ |
AZURE_AISERVICES_SPEECH_ENDPOINT |
Speech to Text (Standard) API endpoint |
https://<___location>.stt.speech.microsoft.com |
AZURE_AISERVICES_CLIENTID |
Your client ID |
<client-ID> |
AZURE_AISERVICES_CLIENTSECRET |
Your client secret |
<client-secret> |
AZURE_AISERVICES_TENANTID |
Your tenant ID |
<tenant-ID> |
Sample code
Refer to the steps and code below to connect to Azure AI Services using a service principaL.
You can use the Azure client library to access various cognitive APIs that Azure AI Services support. We use Azure AI Text Analytics as an example in this sample. Refer to Authenticate requests to Azure AI services to call the cognitive APIs directly.
Install the following dependencies. We use Azure.AI.TextAnalytics
as an example.
dotnet add package Azure.AI.TextAnalytics
dotnet add package Azure.Identity
Authenticate using the Azure Identity library and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
using Azure.AI.TextAnalytics;
using Azure.Identity;
string endpoint = Environment.GetEnvironmentVariable("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
// Uncomment the following lines corresponding to the authentication type you want to use.
// system-assigned managed identity
// var credential = new DefaultAzureCredential();
// user-assigned managed identity
// var credential = new DefaultAzureCredential(
// new DefaultAzureCredentialOptions
// {
// ManagedIdentityClientId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTID");
// });
// service principal
// var tenantId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_TENANTID");
// var clientId = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTID");
// var clientSecret = Environment.GetEnvironmentVariable("AZURE_AISERVICES_CLIENTSECRET");
// var credential = new ClientSecretCredential(tenantId, clientId, clientSecret);
TextAnalyticsClient languageServiceClient = new(
new Uri(endpoint),
credential);
Add the following dependencies in your pom.xml file. We use azure-ai-textanalytics
as an example.
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-ai-textanalytics</artifactId>
<version>5.1.12</version>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<version>1.11.4</version>
</dependency>
Authenticate using azure-identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
// Uncomment the following lines corresponding to the authentication type you want to use.
// for system-managed identity
// DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
// for user-assigned managed identity
// DefaultAzureCredential credential = new DefaultAzureCredentialBuilder()
// .managedIdentityClientId(System.getenv("AZURE_AISERVICES_CLIENTID"))
// .build();
// for service principal
// ClientSecretCredential credential = new ClientSecretCredentialBuilder()
// .clientId(System.getenv("AZURE_AISERVICES_CLIENTID"))
// .clientSecret(System.getenv("AZURE_AISERVICES_CLIENTSECRET"))
// .tenantId(System.getenv("AZURE_AISERVICES_TENANTID"))
// .build();
String endpoint = System.getenv("AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT");
TextAnalyticsClient languageClient = new TextAnalyticsClientBuilder()
.credential(credential)
.endpoint(endpoint)
.buildClient();
- Install the following dependencies. We use
azure-ai-textanalytics
as an example.
pip install azure-ai-textanalytics==5.1.0
pip install azure-identity
- Authenticate using
azure-identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
import os
from azure.ai.textanalytics import TextAnalyticsClient
from azure.identity import ManagedIdentityCredential, ClientSecretCredential
# Uncomment the following lines corresponding to the authentication type you want to use.
# system-assigned managed identity
# cred = ManagedIdentityCredential()
# user-assigned managed identity
# managed_identity_client_id = os.getenv('AZURE_AISERVICES_CLIENTID')
# cred = ManagedIdentityCredential(client_id=managed_identity_client_id)
# service principal
# tenant_id = os.getenv('AZURE_AISERVICES_TENANTID')
# client_id = os.getenv('AZURE_AISERVICES_CLIENTID')
# client_secret = os.getenv('AZURE_AISERVICES_CLIENTSECRET')
# cred = ClientSecretCredential(tenant_id=tenant_id, client_id=client_id, client_secret=client_secret)
endpoint = os.getenv('AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT')
language_service_client = TextAnalyticsClient(
endpoint=endpoint,
credential=cred)
Install the following dependencies. We use ai-text-analytics
as an example.
npm install @azure/ai-text-analytics@5.1.0
npm install @azure/identity
Authenticate using @azure/identity
and get the Azure AI Services endpoint from the environment variables added by Service Connector. When using the code below, uncomment the part of the code snippet for the authentication type you want to use.
import { DefaultAzureCredential,ClientSecretCredential } from "@azure/identity";
const { TextAnalyticsClient } = require("@azure/ai-text-analytics");
// Uncomment the following lines corresponding to the authentication type you want to use.
// for system-assigned managed identity
// const credential = new DefaultAzureCredential();
// for user-assigned managed identity
// const clientId = process.env.AZURE_AISERVICES_CLIENTID;
// const credential = new DefaultAzureCredential({
// managedIdentityClientId: clientId
// });
// for service principal
// const tenantId = process.env.AZURE_AISERVICES_TENANTID;
// const clientId = process.env.AZURE_AISERVICES_CLIENTID;
// const clientSecret = process.env.AZURE_AISERVICES_CLIENTSECRET;
// const credential = new ClientSecretCredential(tenantId, clientId, clientSecret);
const endpoint = process.env.AZURE_AISERVICES_COGNITIVESERVICES_ENDPOINT;
const languageClient = new TextAnalyticsClient(endpoint, credential);
Related content