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Projets d'ia sur azure en java

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SDK Azure AI Projects pour Java. SDK de haut niveau pour la gestion de projets Azure AI Foundry, incluant les connexions, les ensembles de données, le

sickn33sickn33
46.1k
22 mai 2026
MIT License
// contenu du skill

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
<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:

ClientPurpose
ConnectionsClientEnumerate connected Azure resources
DatasetsClientUpload documents and manage datasets
DeploymentsClientEnumerate AI model deployments
IndexesClientCreate and manage search indexes
EvaluationsClientRun AI model evaluations
EvaluatorsClientManage evaluator configurations
SchedulesClientManage 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) {
    System.err.println("Error: " + e.getResponse().getStatusCode());
}

Reference Links

ResourceURL
Product Docshttps://learn.microsoft.com/azure/ai-studio/
API Referencehttps://learn.microsoft.com/rest/api/aifoundry/aiprojects/
GitHub Sourcehttps://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-projects
Sampleshttps://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 clar
// source originale publique
sickn33/antigravity-awesome-skills
/skills/azure-ai-projects-java/SKILL.md
Licence : MIT License
Projet indépendant, non affilié à Anthropic. Ce skill reste la propriété de son auteur original.
// installer ce skill
Collez cette commande dans votre terminal à la racine de votre projet :
mkdir -p .claude/commands && curl -o ".claude/commands/SKILL.md" "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-ai-projects-java/SKILL.md"
Ensuite dans Claude Code, tapez /SKILL pour l'activer.
open_in_newVoir la source originale
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// informations
Créateursickn33
Étoiles 46.1k
CatégorieCloud & SDK
LicenceMIT License
Mis à jour22 mai 2026
Format.md
AccèsGratuit
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