| name | azure-ai-projects-py |
| description | Build AI applications on Microsoft Foundry using the azure-ai-projects SDK. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | cloud-infrastructure |
| category | azure |
| risk | unknown |
| source | community |
| tags | ["skill","cloud-infrastructure","azure","projects"] |
Azure AI Projects Python SDK (Foundry SDK)
Build AI applications on Microsoft Foundry using the azure-ai-projects SDK.
Installation
pip install azure-ai-projects azure-identity
Environment Variables
AZURE_AI_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"
AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
Authentication
import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
credential = DefaultAzureCredential()
client = AIProjectClient(
endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
credential=credential,
)
Client Operations Overview
| Operation | Access | Purpose |
|---|
client.agents | .agents.* | Agent CRUD, versions, threads, runs |
client.connections | .connections.* | List/get project connections |
client.deployments | .deployments.* | List model deployments |
client.datasets | .datasets.* | Dataset management |
client.indexes | .indexes.* | Index management |
client.evaluations | .evaluations.* | Run evaluations |
client.red_teams | .red_teams.* | Red team operations |
Two Client Approaches
1. AIProjectClient (Native Foundry)
from azure.ai.projects import AIProjectClient
client = AIProjectClient(
endpoint=os.environ[],
credential=DefaultAzureCredential(),
)
agent = client.agents.create_agent(
model=os.environ[],
name=,
instructions=,
)
