Azure AI Projects Java Agent Skill

Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.

1.3k tokens

context cost

SKILL.md, read when the skill is used

files

instructions only

copies elsewhere

how many repositories repackaged it

223

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/lingxling/awesome-skills-cn --skill azure-ai-projects-java

The instruction itself

15 sections, as written by the author

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>

Authentication

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 |

// 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 |

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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How to use it

Copy the folder

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