Azure AI Foundry integration

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Azure AI Foundry provides a unified platform for developing, testing, and deploying AI applications. The Aspire Azure AI Foundry integration enables you to connect to Azure AI Foundry services from your applications, providing access to various AI capabilities including model deployments, prompt flow, and more.

Hosting integration

The Aspire Azure AI Foundry hosting integration models the AI Foundry project as the AzureAIFoundryResource type. To access this type and APIs for expressing them within your AppHost project, install the 📦 Aspire.Hosting.Azure.AIFoundry NuGet package:

Aspire CLI

Aspire CLI — Adicionar pacote Aspire.Hosting.Azure.AIFoundry

aspire add azure-aifoundry

A CLI Aspire é interativa; escolhe o resultado apropriado quando solicitado:

Aspire CLI — Exemplo de saída

Select an integration to add:

> azure-aifoundry (Aspire.Hosting.Azure.AIFoundry)
> Other results listed as selectable options...

Nota

Se existir apenas um resultado ele é selecionado automaticamente. Ainda assim confirma a versão.

apphost.cs (C# file-based app)

C# — AppHost.cs

#:package Aspire.Hosting.Azure.AIFoundry@*

PackageReference (*.csproj)

XML — Adicionar referência de pacote Aspire.Hosting.Azure.AIFoundry

<PackageReference Include="Aspire.Hosting.Azure.AIFoundry" Version="*" />

Add an Azure AI Foundry resource

To add an Azure AI Foundry resource to your AppHost project, call the AddAzureAIFoundry method providing a name:

C# — AppHost.cs

var builder = DistributedApplication.CreateBuilder(args);

var foundry = builder.AddAzureAIFoundry("foundry");

builder.AddProject<Projects.ExampleProject>()
       .WithReference(foundry);

// After adding all resources, run the app...

The preceding code adds an Azure AI Foundry resource named foundry to the AppHost project. The WithReference method passes the connection information to the ExampleProject project.

Caution

When you call AddAzureAIFoundry, it implicitly calls AddAzureProvisioning—which adds support for generating Azure resources dynamically during app startup. The app must configure the appropriate subscription and location. For more information, see Local provisioning: Configuration.

Add an Azure AI Foundry deployment resource

To add an Azure AI Foundry deployment resource, call the AddDeployment method:

var builder = DistributedApplication.CreateBuilder(args);

var foundry = builder.AddAzureAIFoundry("foundry");

var chat = foundry.AddDeployment("chat", "Phi-4", "1", "Microsoft");

builder.AddProject<Projects.ExampleProject>()
    .WithReference(chat)
    .WaitFor(chat);

// After adding all resources, run the app...

The preceding code:

• Adds an Azure AI Foundry resource named foundry.
• Adds an Azure AI Foundry deployment resource named chat with a model name of Phi-4. The model name must correspond to an available model in the Azure AI Foundry service.

Note

The format parameter of the AddDeployment(...) method can be found in the Azure AI Foundry portal in the details page of the model, right after the Quick facts text.

Configure deployment properties

You can customize deployment properties using the WithProperties method:

var chat = foundry.AddDeployment("chat", "Phi-4", "1", "Microsoft")
    .WithProperties(deployment =>
    {
        deployment.SkuName = "Standard";
        deployment.SkuCapacity = 10;
    });

The preceding code sets the SKU name to Standard and capacity to 10 for the deployment.

Connect to an existing Azure AI Foundry service

You might have an existing Azure AI Foundry service that you want to connect to. You can chain a call to annotate that your AzureAIFoundryResource is an existing resource:

var builder = DistributedApplication.CreateBuilder(args);

var existingFoundryName = builder.AddParameter("existingFoundryName");
var existingFoundryResourceGroup = builder.AddParameter("existingFoundryResourceGroup");

var foundry = builder.AddAzureAIFoundry("foundry")
    .AsExisting(existingFoundryName, existingFoundryResourceGroup);

builder.AddProject<Projects.ExampleProject>()
    .WithReference(foundry);

// After adding all resources, run the app...

Caution

When you call RunAsExisting, PublishAsExisting, or AsExisting methods to work with resources that are already present in your Azure subscription, you must add certain configuration values to your AppHost to ensure that Aspire can locate them. The necessary configuration values include SubscriptionId, AllowResourceGroupCreation, ResourceGroup, and Location. If you don’t set them, “Missing configuration” errors appear in the Aspire dashboard. For more information about how to set them, see Use existing Azure resources.

Use Foundry Local for development

Aspire supports the usage of Foundry Local for local development. Add the following to your AppHost project:

C# — AppHost.cs

var builder = DistributedApplication.CreateBuilder(args);

var foundry = builder.AddAzureAIFoundry("foundry")
    .RunAsFoundryLocal();

var chat = foundry.AddDeployment("chat", "phi-3.5-mini", "1", "Microsoft");

builder.AddProject<Projects.ExampleProject>()
    .WithReference(chat)
    .WaitFor(chat);

// After adding all resources, run the app...

When the AppHost starts up, the local foundry service is also started. This requires the local machine to have Foundry Local installed and running.

The RunAsFoundryLocal method configures the resource to run as an emulator. It downloads and loads the specified models locally. The method provides health checks for the local service and automatically manages the Foundry Local lifecycle.

Assign roles to resources

You can assign specific roles to resources that need to access the Azure AI Foundry service. Use the WithRoleAssignments method:

C# — AppHost.cs

var foundry = builder.AddAzureAIFoundry("chat");

builder.AddProject<Projects.Api>("api")
  .WithRoleAssignments(foundry, CognitiveServicesBuiltInRole.CognitiveServicesUser)
  .WithReference(foundry);

The preceding code assigns the CognitiveServicesUser role to the api project, granting it the necessary permissions to access the Azure AI Foundry resource.

Provisioning-generated Bicep

If you’re new to Bicep, it’s a domain-specific language for defining Azure resources. With Aspire, you don’t need to write Bicep by-hand, instead the provisioning APIs generate Bicep for you. When you publish your app, the generated Bicep provisions an Azure AI Foundry resource with standard defaults.

Generated Bicep — ai-foundry.bicep

@description('The location for the resource(s) to be deployed.')
param location string = resourceGroup().location

resource ai_foundry 'Microsoft.CognitiveServices/accounts@2024-10-01' = {
  name: take('aifoundry-${uniqueString(resourceGroup().id)}', 64)
  location: location
  identity: {
    type: 'SystemAssigned'
  }
  kind: 'AIServices'
  properties: {
    customSubDomainName: toLower(take(concat('ai-foundry', uniqueString(resourceGroup().id)), 24))
    publicNetworkAccess: 'Enabled'
    disableLocalAuth: true
  }
  sku: {
    name: 'S0'
  }
  tags: {
    'aspire-resource-name': 'ai-foundry'
  }
}

resource chat 'Microsoft.CognitiveServices/accounts/deployments@2024-10-01' = {
  name: 'Phi-4'
  properties: {
    model: {
      format: 'Microsoft'
      name: 'Phi-4'
      version: '1'
    }
  }
  sku: {
    name: 'GlobalStandard'
    capacity: 1
  }
  parent: ai_foundry
}

output aiFoundryApiEndpoint string = ai_foundry.properties.endpoints['AI Foundry API']

output endpoint string = ai_foundry.properties.endpoint

output name string = ai_foundry.name

The preceding Bicep is a module that provisions an Azure Cognitive Services resource configured for AI Services. Additionally, role assignments are created for the Azure resource in a separate module:

Generated Bicep — ai-foundry-roles.bicep

@description('The location for the resource(s) to be deployed.')
param location string = resourceGroup().location

param ai_foundry_outputs_name string

param principalType string

param principalId string

resource ai_foundry 'Microsoft.CognitiveServices/accounts@2024-10-01' existing = {
  name: ai_foundry_outputs_name
}

resource ai_foundry_CognitiveServicesUser 'Microsoft.Authorization/roleAssignments@2022-04-01' = {
  name: guid(ai_foundry.id, principalId, subscriptionResourceId('Microsoft.Authorization/roleDefinitions', 'a97b65f3-24c7-4388-baec-2e87135dc908'))
  properties: {
    principalId: principalId
    roleDefinitionId: subscriptionResourceId('Microsoft.Authorization/roleDefinitions', 'a97b65f3-24c7-4388-baec-2e87135dc908')
    principalType: principalType
  }
  scope: ai_foundry
}

resource ai_foundry_CognitiveServicesOpenAIUser 'Microsoft.Authorization/roleAssignments@2022-04-01' = {
  name: guid(ai_foundry.id, principalId, subscriptionResourceId('Microsoft.Authorization/roleDefinitions', '5e0bd9bd-7b93-4f28-af87-19fc36ad61bd'))
  properties: {
    principalId: principalId
    roleDefinitionId: subscriptionResourceId('Microsoft.Authorization/roleDefinitions', '5e0bd9bd-7b93-4f28-af87-19fc36ad61bd')
    principalType: principalType
  }
  scope: ai_foundry
}

The generated Bicep is a starting point and is influenced by changes to the provisioning infrastructure in C#. Customizations to the Bicep file directly will be overwritten, so make changes through the C# provisioning APIs to ensure they’re reflected in the generated files.

Customize provisioning infrastructure

All Aspire Azure resources are subclasses of the AzureProvisioningResource type. This enables customization of the generated Bicep by providing a fluent API to configure the Azure resources—using the ConfigureInfrastructure API:

C# — AppHost.cs

builder.AddAzureAIFoundry("foundry")
  .ConfigureInfrastructure(infra =>
  {
      var resources = infra.GetProvisionableResources();
      var account = resources.OfType<CognitiveServicesAccount>().Single();

      account.Sku = new CognitiveServicesSku
      {
          Tier = CognitiveServicesSkuTier.Enterprise,
          Name = "E0"
      };
      account.Tags.Add("ExampleKey", "Example value");
  });

The preceding code:

• Chains a call to the ConfigureInfrastructure API:
  • The infra parameter is an instance of the AzureResourceInfrastructure type.
  • The provisionable resources are retrieved by calling the GetProvisionableResources method.
  • The single CognitiveServicesAccount resource is retrieved.
  • The Sku property is assigned to a new instance of CognitiveServicesSku with an E0 name and Enterprise tier.
  • A tag is added to the Cognitive Services resource with a key of ExampleKey and a value of Example value.

Client integration

The client integration for Azure AI Foundry is the Azure AI Inference integration.