Azure AI Projects Java — Agent Skill by Microsoft

From the author

Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations. Triggers: "AIProjectClient java", "azure ai projects java", "Foundry project java", "ConnectionsClient", "DatasetsClient", "IndexesClient".

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Azure AI Projects SDK for Java provides a high-level interface for interacting with Azure AI Foundry. It enables developers to programmatically manage project resources such as connections to external services, datasets, search indexes, and AI model deployments. The SDK features a modular client architecture, allowing users to instantiate specific sub-clients for tasks like running evaluations, scheduling operations, or managing search indexes, all while leveraging standard Azure authentication patterns.

What it does

Provides a centralized builder for creating specialized sub-clients.
Manages connections to external Azure resources.
Facilitates the creation and management of search indexes.
Supports the execution and configuration of AI model evaluations.
Enables programmatic access to dataset management and model deployments.
Integrates with standard Azure identity and credential providers.

When to use it

When building Java applications that interact with Azure AI Foundry.
When you need to automate the lifecycle of AI project resources.
When integrating AI model evaluation workflows into Java-based pipelines.
When managing search indexes or data connections within an Azure AI environment.

Advantages

Modular client design for efficient resource management.
Native support for Azure identity and security best practices.
Comprehensive coverage of AI Foundry project operations.
Supports both synchronous and asynchronous operations.

Usage examples

“How do I initialize the Azure AI Projects client in Java?”: You use the AIProjectClientBuilder, providing your project endpoint and a TokenCredential (such as DefaultAzureCredential) to build the client.
“How can I list all connections in my Azure AI project using Java?”: Build a ConnectionsClient from the main builder and call the listConnections() method, which returns a PagedIterable of available connections.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-ai-projects-java/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip azure-ai-projects-java.zip -d .agents/skills

Documentation by Microsoft

Azure AI Projects SDK for Java

High-level SDK for Azure AI Foundry project management with access to connections, datasets, indexes, and evaluations.

Installation

<dependency>
    <groupId>com.azure</groupId>
    <artifactId>azure-ai-projects</artifactId>
    <version>1.0.0-beta.1</version>
</dependency>

Environment Variables

PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project> # Required for project configuration
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Authentication

import com.azure.ai.projects.AIProjectClientBuilder;
import com.azure.core.credential.TokenCredential;
import com.azure.identity.AzureIdentityEnvVars;
import com.azure.identity.DefaultAzureCredentialBuilder;
import com.azure.identity.ManagedIdentityCredentialBuilder;

TokenCredential credential = new DefaultAzureCredentialBuilder()
    .requireEnvVars(AzureIdentityEnvVars.AZURE_TOKEN_CREDENTIALS)
    .build();
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/java/api/overview/azure/identity-readme?view=azure-java-stable#credential-classes
// TokenCredential credential = new ManagedIdentityCredentialBuilder().build();

AIProjectClientBuilder builder = new AIProjectClientBuilder()
    .endpoint(System.getenv("PROJECT_ENDPOINT"))
    .credential(credential);

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

// 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

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

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

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:

import com.openai.services.EvalService;

EvalService evalService = evaluationsClient.getOpenAIClient();
// Use OpenAI evaluation APIs directly

Best Practices

Use DefaultAzureCredential for production authentication
Reuse client builder to create multiple sub-clients efficiently
Handle pagination when listing resources with PagedIterable
Use environment variables for connection names and configuration
Check connection types before accessing credentials

Error Handling

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

Files

ATTRIBUTION.mdAdded by AutoGineer973 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md5.4 KiB
references/examples.md11.8 KiB

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-ai-projects-java.zip