Get started with the Azure AI Foundry integrations

Azure AI Foundry provides a unified platform for developing, testing, and deploying AI applications. The Aspire Azure AI Foundry integration lets you model a Foundry account, model deployments, Foundry projects, and hosted agents as first-class resources in your AppHost, then hand the connection information to any consuming app — regardless of language.

Why use Azure AI Foundry with Aspire

Adding Azure AI Foundry through Aspire — rather than hard-coding endpoints and API keys in each service — gives you:

• Centralized credential management. Endpoint and API key are stored once in the AppHost and injected into each consuming app automatically.
• Model deployments as first-class resources. Each deployment composes a connection string from the parent Foundry endpoint, API key, and model name, giving consuming apps a single named connection.
• Foundry Projects for agents. Model Foundry projects with AddProject, attach model deployments, web-search tools, and hosted or prompt agents, and reference them from consuming services.
• Consistent connection info across languages. Once you reference a deployment from a consuming app, Aspire injects connection properties as environment variables in a predictable format that works from C#, TypeScript, Python, Go, or any other language.
• Foundry Local for offline development. Use RunAsFoundryLocal() to run models locally without an Azure subscription.
• An upgrade path to the cloud. The same AppHost model provisions Azure Cognitive Services accounts and deployments when you publish.

How the pieces fit together

The Azure AI Foundry integration has two sides: a hosting integration that you use in your AppHost to model the Foundry resource and its deployments, and a connection story for consuming apps that reference those deployment resources.

architecture-beta

  group apphost(server)[AppHost]
  group consumer(server)[Consuming app]

  service hosting(server)[Hosting integration] in apphost
  service foundry(internet)[Azure AI Foundry] in apphost
  service model(database)[chat deployment] in apphost

  service client(iconoir:server-connection)[Client SDK] in consumer
  service app(server)[App] in consumer

  hosting:R --> L:foundry
  foundry:R --> L:model
  model:R --> L:client
  client:R --> L:app

The hosting integration lives in your AppHost project and models the Foundry account and deployment resources. The client / SDK lives in each consuming app and uses the connection information Aspire injects to call the Azure AI Foundry API.

Getting there is a two-step process: model the Azure AI Foundry resources in your AppHost, then connect to the API from each app that needs it.

1. Model Azure AI Foundry in your AppHost

   Add the Azure AI Foundry hosting integration to your AppHost, then declare a Foundry account, one or more model deployments, and reference them from the apps that need to call the API. The Azure AI Foundry hosting integration article walks through every capability — adding deployments, Foundry projects, hosted agents, prompt agents, role assignments, Foundry Local, and more — with side-by-side C# and TypeScript examples.

   Set up Azure AI Foundry in the AppHost

2. Connect from your consuming app

   When you reference a Foundry deployment from a consuming app, Aspire injects its connection information as environment variables. See Connect to Azure AI Foundry for the connection properties reference and per-language examples for C#, Go, Python, and TypeScript — including the full C# client integration via Microsoft.Extensions.AI.

   Connect to Azure AI Foundry

See also

• Azure AI Foundry documentation
• Azure AI Inference integration