Azure Projects client library for Java - version 2.1.0

The AI Projects client library is part of the Azure AI Foundry SDK and provides easy access to resources in your Azure AI Foundry Project. Use it to:

Create and run Agents using the separate package com.azure:azure-ai-agents.
Enumerate AI Models deployed to your Foundry Project using the Deployments operations.
Enumerate connected Azure resources in your Foundry project using the Connections operations.
Upload documents and create Datasets to reference them using the Datasets operations.
Generate datasets for model, agent, evaluator, and traces scenarios using the preview DataGenerationJobs operations.
Register and manage model weights as Foundry ModelVersion resources using the preview Models operations.
Create and dispatch routines using the preview Routines operations.
Create and manage skills using the preview Skills operations.
Create and enumerate Search Indexes using the Indexes operations.

The client library uses a single service version v1 of the AI Foundry data plane REST APIs.

Documentation

Various documentation is available to help you get started

Getting started

Prerequisites

Java Development Kit (JDK) with version 8 or above
Azure Subscription

Adding the package to your product

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-projects</artifactId>
    <version>2.1.0</version>
</dependency>

Authentication

Azure Identity package provides the default implementation for authenticating the client.

Key concepts

The Azure AI Foundry provides a centralized spot to manage your AI Foundry resources. In order to access each feature you need to initialize your builder and access the corresponding sub-client like it's shown in the following code snippet:

AIProjectClientBuilder builder = new AIProjectClientBuilder();

ConnectionsClient connectionsClient = builder.buildConnectionsClient();
DataGenerationJobsClient dataGenerationJobsClient = builder.buildDataGenerationJobsClient();
DatasetsClient datasetsClient = builder.buildDatasetsClient();
DeploymentsClient deploymentsClient = builder.buildDeploymentsClient();
EvaluationRulesClient evaluationRulesClient = builder.buildEvaluationRulesClient();
EvaluationTaxonomiesClient evaluationTaxonomiesClient = builder.buildEvaluationTaxonomiesClient();
EvaluatorsClient evaluatorsClient = builder.buildEvaluatorsClient();
IndexesClient indexesClient = builder.buildIndexesClient();
InsightsClient insightsClient = builder.buildInsightsClient();
ModelsClient modelsClient = builder.buildModelsClient();
RedTeamsClient redTeamsClient = builder.buildRedTeamsClient();
RoutinesClient routinesClient = builder.buildRoutinesClient();
SchedulesClient schedulesClient = builder.buildSchedulesClient();
SkillsClient skillsClient = builder.buildSkillsClient();

In the particular case of the Evals feature, this client library exposes OpenAI's official SDK directly, so you can use the official OpenAI docs to access this feature.

EvalService evalService = builder.buildOpenAIClient().evals();
EvalServiceAsync evalAsyncService = builder.buildOpenAIAsyncClient().evals();

When using Azure-specific evaluator models with OpenAI evaluations, use EvaluationsHelper to adapt the Azure model to the OpenAI request type. This keeps application code from depending on the serialization details used by the OpenAI SDK.

Map<String, String> dataMapping = new LinkedHashMap<>();
dataMapping.put("query", "{{item.query}}");
dataMapping.put("response", "{{sample.output_text}}");

TestingCriterionAzureAIEvaluator coherenceEvaluator = new TestingCriterionAzureAIEvaluator("coherence",
    "builtin.coherence")
        .setInitializationParameters(Collections.singletonMap("deployment_name",
            BinaryData.fromObject("gpt-4o-mini")))
        .setDataMapping(dataMapping);

EvalCreateParams.TestingCriterion testingCriterion
    = EvaluationsHelper.toTestingCriterion(coherenceEvaluator);

For the Agents operation, you can use the azure-ai-agents package which is available as transitive dependency:

AgentsClientBuilder agentsClientBuilder = new AgentsClientBuilder();

AgentsClient agentsClient = agentsClientBuilder.buildAgentsClient();
MemoryStoresClient memoryStoresClient = agentsClientBuilder.buildMemoryStoresClient();
ResponsesClient responsesClient = agentsClientBuilder.buildResponsesClient();

If you need a full OpenAI client as well, you can use the AIProjectClientBuilder to obtain one:

OpenAIClient openAIClient = builder.buildOpenAIClient();
OpenAIClientAsync openAIClientAsync = builder.buildOpenAIAsyncClient();

Preview operation groups and opt-in flags

Several operation groups in the AI Projects client library are in preview and require the Foundry-Features HTTP header for opt-in. The SDK automatically sets this header on every request for the following sub-clients:

Sub-client	Opt-in flag
`EvaluatorsClient`	`Evaluations=V1Preview`
`EvaluationTaxonomiesClient`	`Evaluations=V1Preview`
`ModelsClient`	`Models=V1Preview`
`RedTeamsClient`	`RedTeams=V1Preview`
`SchedulesClient`	`Schedules=V1Preview`
`SkillsClient`	`Skills=V1Preview`

The DataGenerationJobsClient, RoutinesClient, EvaluationRulesClient, and InsightsClient also support the Foundry-Features header, but it is not automatically set. Instead, you can pass a FoundryFeaturesOptInKeys value when calling methods that accept it (e.g., FoundryFeaturesOptInKeys.DATA_GENERATION_JOBS_V1_PREVIEW, FoundryFeaturesOptInKeys.ROUTINES_V1_PREVIEW, generateInsight(), getInsight(), listInsights(), or createOrUpdateEvaluationRule()).

The FoundryFeaturesOptInKeys enum defines all known opt-in keys: EVALUATIONS_V1_PREVIEW, SCHEDULES_V1_PREVIEW, RED_TEAMS_V1_PREVIEW, INSIGHTS_V1_PREVIEW, MEMORY_STORES_V1_PREVIEW, ROUTINES_V1_PREVIEW, TOOLBOXES_V1_PREVIEW, SKILLS_V1_PREVIEW, DATA_GENERATION_JOBS_V1_PREVIEW, MODELS_V1_PREVIEW, AGENTS_OPTIMIZATION_V1_PREVIEW.

Examples

The examples below show common operations for core AI Projects sub-clients. For complete runnable samples, see the package samples. Additional preview samples are available for data generation jobs (DataGenerationJobsSample, DataGenerationJobsAsyncSample, and DataGenerationJobWithEvaluationSample), model management (ModelsSample and ModelsAsyncSample), and packaged skills (SkillsPackageSample and SkillsPackageAsyncSample).

Connections operations

Connection operations allow you to enumerate the Azure resources connected to your AI Foundry Project. These connections can be seen in the "Management Center", in the "Connected resources" tab in your AI Foundry Project.

List connections

PagedIterable<Connection> connections = connectionsClient.listConnections();
for (Connection connection : connections) {
    System.out.println("Connection name: " + connection.getName());
    System.out.println("Connection type: " + connection.getType());
    System.out.println("Connection credential type: " + connection.getCredential().getType());
    System.out.println("-------------------------------------------------");
}

Get a connection without credentials


String connectionName = Configuration.getGlobalConfiguration().get("TEST_CONNECTION_NAME", "");
Connection connection = connectionsClient.getConnection(connectionName);

System.out.printf("Connection name: %s%n", connection.getName());

Get a connection with credentials


String connectionName = Configuration.getGlobalConfiguration().get("TEST_CONNECTION_NAME", "");
Connection connection = connectionsClient.getConnectionWithCredentials(connectionName);

System.out.printf("Connection name: %s%n", connection.getName());
System.out.printf("Connection credentials: %s%n", connection.getCredential().getType());

Asynchronous connection operations


return connectionsAsyncClient.listConnections()
    .doOnNext(connection -> System.out.printf("Connection name: %s%n", connection.getName()));


String connectionName = Configuration.getGlobalConfiguration().get("TEST_CONNECTION_NAME", "");
return connectionsAsyncClient.getConnection(connectionName)
    .doOnNext(connection -> System.out.printf("Connection name: %s%n", connection.getName()));


String connectionName = Configuration.getGlobalConfiguration().get("TEST_CONNECTION_NAME", "");
return connectionsAsyncClient.getConnectionWithCredentials(connectionName)
    .doOnNext(connection -> {
        System.out.printf("Connection name: %s%n", connection.getName());
        System.out.printf("Connection credentials: %s%n", connection.getCredential().getType());
    });

Deployments operations

Deployment operations allow you to enumerate and inspect the models deployed to your AI Foundry Project.

List deployments


PagedIterable<Deployment> deployments = deploymentsClient.listDeployments();
for (Deployment deployment : deployments) {
    System.out.printf("Deployment name: %s%n", deployment.getName());
}

Get a deployment


String deploymentName = Configuration.getGlobalConfiguration().get("FOUNDRY_MODEL_NAME", "");
Deployment deployment = deploymentsClient.getDeployment(deploymentName);

System.out.printf("Deployment name: %s%n", deployment.getName());
System.out.printf("Deployment type: %s%n", deployment.getType().getValue());

Asynchronous deployment operations


return deploymentsAsyncClient.listDeployments()
    .doOnNext(deployment -> System.out.printf("Deployment name: %s%n", deployment.getName()));


String deploymentName = Configuration.getGlobalConfiguration().get("FOUNDRY_MODEL_NAME", "");
return deploymentsAsyncClient.getDeployment(deploymentName)
    .doOnNext(deployment -> {
        System.out.printf("Deployment name: %s%n", deployment.getName());
        System.out.printf("Deployment type: %s%n", deployment.getType().getValue());
    });

Datasets operations

Dataset operations allow you to create, enumerate, retrieve, update, and delete dataset versions in your AI Foundry Project.

Create a dataset version from a local file


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersionString = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");

Path filePath = getPath("product_info.md");

FileDatasetVersion createdDatasetVersion = datasetsClient.createDatasetWithFile(datasetName, datasetVersionString, filePath);

System.out.println("Created dataset version: " + createdDatasetVersion.getId());

List datasets


System.out.println("Listing all datasets (latest versions):");
datasetsClient.listLatestDatasetVersions().forEach(dataset -> {
    System.out.println("\nDataset name: " + dataset.getName());
    System.out.println("Dataset Id: " + dataset.getId());
    System.out.println("Dataset version: " + dataset.getVersion());
    System.out.println("Dataset type: " + dataset.getType());
    if (dataset.getDescription() != null) {
        System.out.println("Description: " + dataset.getDescription());
    }
});

List dataset versions


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "test");

System.out.println("Listing all versions of dataset: " + datasetName);
datasetsClient.listDatasetVersions(datasetName).forEach(version -> {
    System.out.println("\nDataset name: " + version.getName());
    System.out.println("Dataset version: " + version.getVersion());
    System.out.println("Dataset type: " + version.getType());
    if (version.getDataUrl() != null) {
        System.out.println("Data URI: " + version.getDataUrl());
    }
});

Get a dataset version


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "test");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1");

DatasetVersion dataset = datasetsClient.getDatasetVersion(datasetName, datasetVersion);

System.out.println("Retrieved dataset:");
System.out.println("Name: " + dataset.getName());
System.out.println("Version: " + dataset.getVersion());
System.out.println("Type: " + dataset.getType());
if (dataset.getDataUrl() != null) {
    System.out.println("Data URI: " + dataset.getDataUrl());
}
if (dataset.getDescription() != null) {
    System.out.println("Description: " + dataset.getDescription());
}

Create or update a dataset version


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");
String dataUri = Configuration.getGlobalConfiguration().get("DATA_URI", "https://example.com/data.txt");

// Create a new FileDatasetVersion with provided dataUri
FileDatasetVersion fileDataset = new FileDatasetVersion()
    .setDataUrl(dataUri)
    .setDescription("Sample dataset created via SDK");

// Create or update the dataset
FileDatasetVersion createdDataset = (FileDatasetVersion) datasetsClient.createOrUpdateDatasetVersion(
    datasetName,
    datasetVersion,
    fileDataset
);

System.out.println("Created/Updated dataset:");
System.out.println("Name: " + createdDataset.getName());
System.out.println("Version: " + createdDataset.getVersion());
System.out.println("Data URI: " + createdDataset.getDataUrl());

Start a pending upload for a dataset version


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");

// Create a pending upload request for the dataset
PendingUploadRequest request = new PendingUploadRequest();

// Get the pending upload response with blob reference
PendingUploadResponse response = datasetsClient.pendingUpload(datasetName, datasetVersion, request);

System.out.println("Pending upload initiated with ID: " + response.getPendingUploadId());
System.out.println("Blob URI: " + response.getBlobReference().getBlobUrl());

Delete a dataset version


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");

// Delete the specific version of the dataset
datasetsClient.deleteDatasetVersion(datasetName, datasetVersion);

System.out.println("Deleted dataset: " + datasetName + ", version: " + datasetVersion);

Asynchronous dataset operations


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersionString = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");

Path filePath = getPath("product_info.md");

return datasetsAsyncClient.createDatasetWithFile(datasetName, datasetVersionString, filePath)
    .doOnNext(createdDatasetVersion ->
        System.out.println("Created dataset version: " + createdDatasetVersion.getId()));


System.out.println("Listing all datasets (latest versions):");
return datasetsAsyncClient.listLatestDatasetVersions()
    .doOnNext(dataset -> {
        System.out.println("\nDataset name: " + dataset.getName());
        System.out.println("Dataset Id: " + dataset.getId());
        System.out.println("Dataset version: " + dataset.getVersion());
        System.out.println("Dataset type: " + dataset.getType());
        if (dataset.getDescription() != null) {
            System.out.println("Description: " + dataset.getDescription());
        }
    });


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "test");

System.out.println("Listing all versions of dataset: " + datasetName);
return datasetsAsyncClient.listDatasetVersions(datasetName)
    .doOnNext(version -> {
        System.out.println("\nDataset name: " + version.getName());
        System.out.println("Dataset version: " + version.getVersion());
        System.out.println("Dataset type: " + version.getType());
        if (version.getDataUrl() != null) {
            System.out.println("Data URI: " + version.getDataUrl());
        }
    });


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "test");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1");

return datasetsAsyncClient.getDatasetVersion(datasetName, datasetVersion)
    .doOnNext(dataset -> {
        System.out.println("Retrieved dataset:");
        System.out.println("Name: " + dataset.getName());
        System.out.println("Version: " + dataset.getVersion());
        System.out.println("Type: " + dataset.getType());
        if (dataset.getDataUrl() != null) {
            System.out.println("Data URI: " + dataset.getDataUrl());
        }
        if (dataset.getDescription() != null) {
            System.out.println("Description: " + dataset.getDescription());
        }
    });


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");
String dataUri = Configuration.getGlobalConfiguration().get("DATA_URI", "https://example.com/data.txt");

// Create a new FileDatasetVersion with provided dataUri
FileDatasetVersion fileDataset = new FileDatasetVersion()
    .setDataUrl(dataUri)
    .setDescription("Sample dataset created via SDK");

// Create or update the dataset
return datasetsAsyncClient.createOrUpdateDatasetVersion(
    datasetName,
    datasetVersion,
    fileDataset
).doOnNext(createdDataset -> {
    FileDatasetVersion fileDatasetVersion = (FileDatasetVersion) createdDataset;
    System.out.println("Created/Updated dataset:");
    System.out.println("Name: " + fileDatasetVersion.getName());
    System.out.println("Version: " + fileDatasetVersion.getVersion());
    System.out.println("Data URI: " + fileDatasetVersion.getDataUrl());
});


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");

// Create a pending upload request for the dataset
PendingUploadRequest request = new PendingUploadRequest();

// Get the pending upload response with blob reference
return datasetsAsyncClient.pendingUpload(datasetName, datasetVersion, request)
    .doOnNext(response -> {
        System.out.println("Pending upload initiated with ID: " + response.getPendingUploadId());
        System.out.println("Blob URI: " + response.getBlobReference().getBlobUrl());
    });


String datasetName = Configuration.getGlobalConfiguration().get("DATASET_NAME", "my-dataset");
String datasetVersion = Configuration.getGlobalConfiguration().get("DATASET_VERSION", "1.0");

// Delete the specific version of the dataset
return datasetsAsyncClient.deleteDatasetVersion(datasetName, datasetVersion)
    .doOnSuccess(unused ->
        System.out.println("Deleted dataset: " + datasetName + ", version: " + datasetVersion));

Indexes operations

Index operations allow you to create and enumerate search indexes used by your AI Foundry Project.

Create or update an index version

String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");
String indexVersion = Configuration.getGlobalConfiguration().get("INDEX_VERSION", "2.0");
String aiSearchConnectionName = Configuration.getGlobalConfiguration().get("AI_SEARCH_CONNECTION_NAME", "");
String aiSearchIndexName = Configuration.getGlobalConfiguration().get("AI_SEARCH_INDEX_NAME", "");

AIProjectIndex index = indexesClient.createOrUpdateIndexVersion(
    indexName,
    indexVersion,
    new AzureAISearchIndex()
        .setConnectionName(aiSearchConnectionName)
        .setIndexName(aiSearchIndexName)
);

System.out.println("Index created: " + index.getName());

List indexes

indexesClient.listLatestIndexVersions().forEach(index -> {
    System.out.println("Index name: " + index.getName());
    System.out.println("Index version: " + index.getVersion());
    System.out.println("Index description: " + index.getDescription());
    System.out.println("-------------------------------------------------");
});

List index versions


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");

indexesClient.listIndexVersions(indexName).forEach(index -> {
    System.out.println("Index name: " + index.getName());
    System.out.println("Index version: " + index.getVersion());
    System.out.println("Index type: " + index.getType());
});

Get an index version


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");
String indexVersion = Configuration.getGlobalConfiguration().get("INDEX_VERSION", "1.0");

AIProjectIndex index = indexesClient.getIndexVersion(indexName, indexVersion);

System.out.println("Retrieved index:");
System.out.println("Name: " + index.getName());
System.out.println("Version: " + index.getVersion());
System.out.println("Type: " + index.getType());

Delete an index version


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");
String indexVersion = Configuration.getGlobalConfiguration().get("INDEX_VERSION", "1.0");

// Delete the index version
indexesClient.deleteIndexVersion(indexName, indexVersion);

System.out.println("Deleted index: " + indexName + ", version: " + indexVersion);

Asynchronous index operations


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");
String indexVersion = Configuration.getGlobalConfiguration().get("INDEX_VERSION", "2.0");
String aiSearchConnectionName = Configuration.getGlobalConfiguration().get("AI_SEARCH_CONNECTION_NAME", "");
String aiSearchIndexName = Configuration.getGlobalConfiguration().get("AI_SEARCH_INDEX_NAME", "");

return indexesAsyncClient.createOrUpdateIndexVersion(
    indexName,
    indexVersion,
    new AzureAISearchIndex()
        .setConnectionName(aiSearchConnectionName)
        .setIndexName(aiSearchIndexName)
).doOnNext(index -> System.out.println("Index created: " + index.getName()));


return indexesAsyncClient.listLatestIndexVersions()
    .doOnNext(index -> {
        System.out.println("Index name: " + index.getName());
        System.out.println("Index version: " + index.getVersion());
    });


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");

return indexesAsyncClient.listIndexVersions(indexName)
    .doOnNext(index -> {
        System.out.println("Index name: " + index.getName());
        System.out.println("Index version: " + index.getVersion());
        System.out.println("Index type: " + index.getType());
    });


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");
String indexVersion = Configuration.getGlobalConfiguration().get("INDEX_VERSION", "1.0");

return indexesAsyncClient.getIndexVersion(indexName, indexVersion)
    .doOnNext(index -> {
        System.out.println("Retrieved index:");
        System.out.println("Name: " + index.getName());
        System.out.println("Version: " + index.getVersion());
        System.out.println("Type: " + index.getType());
    });


String indexName = Configuration.getGlobalConfiguration().get("INDEX_NAME", "my-index");
String indexVersion = Configuration.getGlobalConfiguration().get("INDEX_VERSION", "1.0");

// Delete the index version
return indexesAsyncClient.deleteIndexVersion(indexName, indexVersion)
    .doOnSuccess(unused ->
        System.out.println("Deleted index: " + indexName + ", version: " + indexVersion));

Skills operations

Skills are a preview feature. The SkillsClient automatically sets the Skills=V1Preview opt-in flag on every request.

Create a skill


SkillInlineContent inlineContent = new SkillInlineContent(
    "Answers product support questions using company policy.",
    "You help answer product support questions using company policy and product guidance."
);

SkillVersion skillVersion = skillsClient.createSkillVersion("product-support-skill", inlineContent, true);

System.out.println("Created skill version: " + skillVersion.getName());
System.out.println("Version: " + skillVersion.getVersion());

Get a skill


String skillName = "product-support-skill";
Skill skill = skillsClient.getSkill(skillName);

System.out.println("Skill name: " + skill.getName());
System.out.println("Description: " + skill.getDescription());
System.out.println("Default version: " + skill.getDefaultVersion());

Update a skill


String skillName = "product-support-skill";

Skill updated = skillsClient.updateSkill(skillName, "2");

System.out.println("Updated skill: " + updated.getName());
System.out.println("Default version: " + updated.getDefaultVersion());

List skills


PagedIterable<Skill> skills = skillsClient.listSkills();
for (Skill skill : skills) {
    System.out.println("Skill name: " + skill.getName());
    System.out.println("Description: " + skill.getDescription());
    System.out.println("-------------------------------------------------");
}

Delete a skill


String skillName = "product-support-skill";
skillsClient.deleteSkill(skillName);

System.out.println("Deleted skill: " + skillName);

Asynchronous skills operations


SkillInlineContent inlineContent = new SkillInlineContent(
    "Answers product support questions using company policy.",
    "You help answer product support questions using company policy and product guidance."
);

return skillsAsyncClient.createSkillVersion("product-support-skill", inlineContent, true)
    .doOnNext(skillVersion -> {
        System.out.println("Created skill version: " + skillVersion.getName());
        System.out.println("Version: " + skillVersion.getVersion());
    });


String skillName = "product-support-skill";

return skillsAsyncClient.getSkill(skillName)
    .doOnNext(skill -> {
        System.out.println("Skill name: " + skill.getName());
        System.out.println("Description: " + skill.getDescription());
        System.out.println("Default version: " + skill.getDefaultVersion());
    });


String skillName = "product-support-skill";

return skillsAsyncClient.updateSkill(skillName, "2")
    .doOnNext(updated -> {
        System.out.println("Updated skill: " + updated.getName());
        System.out.println("Default version: " + updated.getDefaultVersion());
    });


return skillsAsyncClient.listSkills()
    .doOnNext(skill -> {
        System.out.println("Skill name: " + skill.getName());
        System.out.println("Description: " + skill.getDescription());
        System.out.println("-------------------------------------------------");
    });


String skillName = "product-support-skill";

return skillsAsyncClient.deleteSkill(skillName)
    .doOnSuccess(unused -> System.out.println("Deleted skill: " + skillName));

Service API versions

The client library targets the latest service API version by default. The service client builder accepts an optional service API version parameter to specify which API version to communicate.

Select a service API version

You have the flexibility to explicitly select a supported service API version when initializing a service client via the service client builder. This ensures that the client can communicate with services using the specified API version.

When selecting an API version, it is important to verify that there are no breaking changes compared to the latest API version. If there are significant differences, API calls may fail due to incompatibility.

Always ensure that the chosen API version is fully supported and operational for your specific use case and that it aligns with the service's versioning policy.

Troubleshooting

Enable client logging

You can set the AZURE_LOG_LEVEL environment variable to view logging statements made in the client library. For example, setting AZURE_LOG_LEVEL=2 would show all informational, warning, and error log messages. The log levels can be found here: log levels.

To log full HTTP request and response bodies (including headers), set:

export AZURE_LOG_LEVEL=verbose
export AZURE_HTTP_LOG_DETAIL_LEVEL=body_and_headers

Default HTTP Client

All client libraries by default use the Netty HTTP client. Configuring or changing the HTTP client is detailed in the HTTP clients wiki.

Default SSL library

All client libraries, by default, use the Tomcat-native Boring SSL library to enable native-level performance for SSL operations. The Boring SSL library is an uber jar containing native libraries for Linux / macOS / Windows, and provides better performance compared to the default SSL implementation within the JDK. For more information, including how to reduce the dependency size, refer to the performance tuning section of the wiki.

Next steps

Contributing

For details on contributing to this repository, see the contributing guide.

Fork it
Create your feature branch (git checkout -b my-new-feature)
Commit your changes (git commit -am 'Add some feature')
Push to the branch (git push origin my-new-feature)
Create new Pull Request

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Last updated on 2026-06-02