AI projects on Azure in Java

--- name: azure-ai-projects-java description: Azure AI ProjectsSDKs for Java. High-level SDK for Azure AI Foundry project management, including connections, datasets, indexes, and evaluations. risk: unknown source: community date_added: '2026-02-27' --- # Azure AI Projects SDK for Java High-level SDK for Azure AI Foundry project management, providing access to connections, datasets, indexes, and evaluations. ## Installation ``xml <dependency> <groupId>com.azure</groupId> <artifactId>azure-ai-projects</artifactId> <version>1.0.0-beta.1</version> </dependency> ` ## Environment Variables `bash PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project> ` ## Authentication `java import com.azure.ai.projects.AIProjectClientBuilder; import com.azure.identity.DefaultAzureCredentialBuilder; AIProjectClientBuilder builder = new AIProjectClientBuilder() .endpoint(System.getenv("PROJECT_ENDPOINT")) .credential(new DefaultAzureCredentialBuilder().build()); ` ## Client Hierarchy The SDK provides multiple sub-clients for different operations: | Client | Purpose | |--------|---------| | ConnectionsClient | Enumerate connected Azure resources | | DatasetsClient | Upload documents and manage datasets | | DeploymentsClient | Enumerate AI model deployments | | IndexesClient | Create and manage search indexes | | EvaluationsClient | Run AI model evaluations | | EvaluatorsClient | Manage evaluator configurations | | SchedulesClient | Manage scheduled operations | `java // Build sub-clients from builder ConnectionsClient connectionsClient = builder.buildConnectionsClient(); DatasetsClient datasetsClient = builder.buildDatasetsClient(); DeploymentsClient deploymentsClient = builder.buildDeploymentsClient(); IndexesClient indexesClient = builder.buildIndexesClient(); EvaluationsClient evaluationsClient = builder.buildEvaluationsClient(); ` ## Core Operations ### List Connections `java import com.azure.ai.projects.models.Connection; import com.azure.core.http.rest.PagedIterable; PagedIterable<Connection> connections = connectionsClient.listConnections(); for (Connection connection : connections) { System.out.println("Name: " + connection.getName()); System.out.println("Type: " + connection.getType()); System.out.println("Credential Type: " + connection.getCredentials().getType()); } ` ### List Indexes `java indexesClient.listLatest().forEach(index -> { System.out.println("Index name: " + index.getName()); System.out.println("Version: " + index.getVersion()); System.out.println("Description: " + index.getDescription()); }); ` ### Create or Update Index `java import com.azure.ai.projects.models.AzureAISearchIndex; import com.azure.ai.projects.models.Index; String indexName = "my-index"; String indexVersion = "1.0"; String searchConnectionName = System.getenv("AI_SEARCH_CONNECTION_NAME"); String searchIndexName = System.getenv("AI_SEARCH_INDEX_NAME"); Index index = indexesClient.createOrUpdate( indexName, indexVersion, new AzureAISearchIndex() .setConnectionName(searchConnectionName) .setIndexName(searchIndexName) ); System.out.println("Created index: " + index.getName()); ` ### Access OpenAI Evaluations The SDK exposes OpenAI's official SDK for evaluations: `java import com.openai.services.EvalService; EvalService evalService = evaluationsClient.getOpenAIClient(); // Use OpenAI evaluation APIs directly ` ## Best Practices 1. **Use DefaultAzureCredential** for production authentication 2. **Reuse client builder** to create multiple sub-clients efficiently 3. **Handle pagination** when listing resources with PagedIterable 4. **Use environment variables** for connection names and configuration 5. **Check connection types** before accessing credentials ## Error Handling ``java import com.azure.core.exception.HttpResponseException; import com.azure.core.exception.ResourceNotFoundException; try { Index index = indexesClient.get(indexName, version); } catch (ResourceNotFoundException e) { System.err.println("Index not found: " + indexName); } catch (HttpResponseException e) { Syst