azure-ai-projects-py
AI Foundry project client and agents
Developer Setup
Setup & Installation
npx skills add https://github.com/microsoft/skills --skill azure-ai-projects-pynpx skills add https://github.com/microsoft/skills --skill azure-ai-projects-pyOverview
What This Skill Does
Python SDK for building AI applications on Microsoft Azure Foundry. Wraps agent creation, thread management, evaluations, connections, deployments, datasets, and indexes under a single `AIProjectClient`. Also provides an OpenAI-compatible client for projects that use standard OpenAI API patterns.
Application
When to use this Skill
- Configuring integration settings for custom agent workflows.
- Optimizing query execution and response latency in production.
- Developing clean, standard-compliant implementations for enterprise services.
- Troubleshooting connection timeouts and authentication handshakes.
- Monitoring API rate limits and execution pipelines programmatically.
Documentation
Show Skills.md file
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>" # Required for all auth methods
AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini" # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
Authentication & Lifecycle
🔑 Two rules apply to every code sample below:
- Prefer
DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
- Local dev:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.
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