--- name: azure-ai-projects-java description: Azure AI Projects SDK 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 with access to connections, datasets, indexes, and evaluations. ## Installation ```xml com.azure azure-ai-projects 1.0.0-beta.1 ``` ## Environment Variables ```bash PROJECT_ENDPOINT=https://.services.ai.azure.com/api/projects/ ``` ## 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 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) { System.err.println("Error: " + e.getResponse().getStatusCode()); } ``` ## Reference Links | Resource | URL | |----------|-----| | Product Docs | https://learn.microsoft.com/azure/ai-studio/ | | API Reference | https://learn.microsoft.com/rest/api/aifoundry/aiprojects/ | | GitHub Source | https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-projects | | Samples | https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-projects/src/samples | ## When to Use This skill is applicable to execute the workflow or actions described in the overview. ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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