azure-ai-projects-java

You can manage Azure AI Foundry projects using a Java SDK by creating an AIProjectClientBuilder with your endpoint and credentials, then building typed sub-clients like ConnectionsClient or DatasetsClient to provision and operate project resources.

Within an Azure AI Foundry project from Java, you can configure connections, datasets, indexes, deployments, and evaluations using dedicated sub-clients for end-to-end resource provisioning and listing workflows.

Yes, you need Azure credentials and a configured endpoint to use the Azure AI Foundry Java SDK, along with a Java runtime, to authenticate and manage project resources across the available typed sub-clients.

To list project connections in Azure AI Foundry with Java, build a ConnectionsClient from the AIProjectClientBuilder using your endpoint and credentials, then call the documented methods to retrieve your project's connections.

Yes, the Azure AI Foundry Java SDK provides clear authentication and error-handling patterns with guidance for production Java apps to manage connections, datasets, indexes, deployments, and evaluations.

The best way to orchestrate datasets and evaluations in Azure AI Foundry using Java is through the DatasetsClient and EvaluationsClient sub-clients, which provide typed methods to operate these project resources end-to-end.