What is the Azure AI Foundry SDK?
The Azure AI Foundry SDK is a set of packages and services designed to work together to enable developers to write code that uses resources in an Azure AI Foundry project. With the Azure AI Foundry SDK, developers can create applications that connect to a project, access the resource connections and models in that project, and use them to perform AI operations, such as sending prompts to a generative AI model and processing the responses
The SDK provides Python and Microsoft C# .NET libraries that you can use to build AI applications based on Azure AI Foundry projects.
Note
In the preview release of the SDK, some capabilities may not be available for both languages.
Installing SDK packages
The core package for working with projects in the Azure AI Foundry SDK is the Azure AI Projects library, which enables you to connect to an Azure AI Foundry project and access the resources defined within it.
To use the Azure AI Projects library in Python, you can use the pip package installation utility to install the azure-ai-projects package from PyPi:
pip install azure-ai-projects
To use the Azure AI Projects library in C#, add the Azure.AI.Projects package to your C# project:
dotnet add package Azure.AI.Projects --prerelease
Using the SDK to connect to a project
The first task in most Azure AI Foundry SDK code is to connect to an Azure AI Foundry project. Each project has a unique endpoint, which you can find on the project's Overview page in the Azure AI Foundry portal.
Note
The project provides multiple endpoints and keys, including:
- An endpoint for the project itself; which can be used to access project connections, agents, and models in the Azure AI Foundry resource.
- An endpoint for Azure OpenAI Service APIs in the project's Azure AI Foundry resource.
- An endpoint for Azure AI services APIs (such as Azure AI Vision and Azure AI Language) in the Azure AI Foundry resource.
You can use the project endpoint in your code to create an AIProjectClient object, which provides a programmatic proxy for the project.
The following code snippet shows how to create am AIProjectClient object in Python.
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
...
project_endpoint = "https://......"
project_client = AIProjectClient(
credential=DefaultAzureCredential(),
endpoint=project_endpoint)
Note
The code uses the default Azure credentials to authenticate when accessing the project. To enable this authentication, in addition to the azure-ai-projects package, you need to install the azure-identity package:
pip install azure-identity
The following code snippet shows how to create am AIProjectClient object in C#.
using Azure.Identity;
using Azure.AI.Projects;
...
var projectEndpoint = "https://......";
var projectClient = new AIProjectClient(
new Uri(projectEndpoint),
new DefaultAzureCredential());
Note
The code uses the default Azure credentials to authenticate when accessing the project. To enable this authentication, in addition to the Azure.AI.Projects package, you need to install the Azure.Identity package:
dotnet add package Azure.Identity
Tip
To access the project successfully, the code must be run in the context of an authenticated Azure session. For example, you could use the Azure command-line interface (CLI) az-login command to sign in before running the code.