Azure Projects client library for Java - version 1.0.0-beta.3

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.
• Create and enumerate Search Indexes using the Indexes operations.

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

Documentation

Various documentation is available to help you get started

• API reference documentation
• Product documentation

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>1.0.0-beta.1</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();
DatasetsClient datasetsClient = builder.buildDatasetsClient();
DeploymentsClient deploymentsClient = builder.buildDeploymentsClient();
EvaluationRulesClient evaluationRulesClient = builder.buildEvaluationRulesClient();
EvaluationsClient evaluationsClient = builder.buildEvaluationsClient();
EvaluationTaxonomiesClient evaluationTaxonomiesClient = builder.buildEvaluationTaxonomiesClient();
EvaluatorsClient evaluatorsClient = builder.buildEvaluatorsClient();
IndexesClient indexesClient = builder.buildIndexesClient();
InsightsClient insightsClient = builder.buildInsightsClient();
RedTeamsClient redTeamsClient = builder.buildRedTeamsClient();
SchedulesClient schedulesClient = builder.buildSchedulesClient();

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

EvalService evalService = evaluationsClient.getOpenAIClient();

Examples

Connections operations

The code below shows some Connection operations, which allow you to enumerate the Azure Resources connected to your AI Foundry Projects. These connections can be seen in the "Management Center", in the "Connected resources" tab in your AI Foundry Project. For more samples see the package samples.

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.getCredentials().getType());
    System.out.println("-------------------------------------------------");
}

Indexes

The code below shows some Indexes operations to list and create indexes. For more samples see the package samples.

indexesClient.listLatest().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("-------------------------------------------------");
});

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", "");

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

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

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

Next steps

Contributing

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

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