Microsoft Azure / Foundry

Pydantic AI supports Azure OpenAI and other model deployments in Microsoft Foundry (formerly Azure AI Foundry), as well as Claude through the Anthropic SDK.

API	Model selection
Chat Completions	azure:<deployment-name>
Responses	azure-responses:<deployment-name>
Anthropic Messages	AnthropicModel with a Foundry client

Use your Azure deployment name as the model name. The examples below assume a deployment named gpt-5.2.

Install

Install Pydantic AI with the OpenAI SDK used by this integration:

pip

Terminal

pip install "pydantic-ai-slim[openai]"

uv

Terminal

uv add "pydantic-ai-slim[openai]"

Configuration

To use Microsoft Foundry as your provider, set AZURE_OPENAI_ENDPOINT to a URL whose path ends in /v1 (for example https://<resource>.openai.azure.com/openai/v1/ or https://<resource>.services.ai.azure.com/openai/v1/), set AZURE_OPENAI_API_KEY, and use AzureProvider by name:

from pydantic_ai import Agent

agent = Agent('azure:gpt-5.2')
...

Tip

For voice agents, use an Azure OpenAI realtime deployment or Azure AI Voice Live with a realtime session instead.

Or initialise the model and provider directly:

from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.azure import AzureProvider

model = OpenAIChatModel(
    'gpt-5.2',
    provider=AzureProvider(
        azure_endpoint='https://your-resource.openai.azure.com/openai/v1/',
        api_key='your-api-key',
    ),
)
agent = Agent(model)
...

This targets the Azure OpenAI v1 API, which Microsoft recommends for all new projects. It also pairs naturally with the Responses API — see Using Azure with the Responses API below.

AzureProvider also recognises Microsoft Foundry serverless model deployments at https://<model>.<region>.models.ai.azure.com and connects to them the same way.

Connecting to an existing api-version-based deployment

If your resource still uses the dated api-version API, pass api_version (or set the OPENAI_API_VERSION environment variable) and point azure_endpoint at the resource root instead:

from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.azure import AzureProvider

model = OpenAIChatModel(
    'gpt-5.2',
    provider=AzureProvider(
        azure_endpoint='https://your-resource.openai.azure.com/',
        api_version='2024-12-01-preview',
        api_key='your-api-key',
    ),
)
agent = Agent(model)
...

Using Azure with the Responses API

Microsoft Foundry also supports the OpenAI Responses API through OpenAIResponsesModel. This is particularly recommended when working with document inputs (DocumentUrl and BinaryContent), as Azure’s Chat Completions API does not support these input types.

Use the azure-responses: prefix to select the Responses API by name (the azure: prefix uses the Chat Completions API):

from pydantic_ai import Agent

agent = Agent('azure-responses:gpt-5.2')
...

Note

Azure’s Responses API doesn’t yet support every feature of OpenAI’s Responses API — for example, native web search is unavailable, and there are limits around image editing and file uploads. See Microsoft’s Responses API docs for the current list. This applies whether you use the azure-responses: shorthand or construct OpenAIResponsesModel with AzureProvider directly.

Or initialise the model and provider directly, for example to process a document:

Document processing with Azure using Responses API

from pydantic_ai import Agent, BinaryContent
from pydantic_ai.models.openai import OpenAIResponsesModel
from pydantic_ai.providers.azure import AzureProvider

pdf_bytes = b'%PDF-1.4 ...'  # Your PDF content

model = OpenAIResponsesModel(
    'gpt-5.2',
    provider=AzureProvider(
        azure_endpoint='https://your-resource.openai.azure.com/openai/v1/',
        api_key='your-api-key',
    ),
)
agent = Agent(model)
result = agent.run_sync([
    'Summarize this document',
    BinaryContent(data=pdf_bytes, media_type='application/pdf'),
])

Claude on Microsoft Foundry

For Claude, install the anthropic optional group and pass an AsyncAnthropicFoundry client to AnthropicProvider. See Claude on Microsoft Foundry for the example and Entra ID authentication guidance.