codeflash-agent/.tessl/tiles/tessl/pypi-anthropic/docs/platforms/foundry.md

Azure AI Foundry Integration

Access Claude models via Azure AI Foundry with API key or Azure AD authentication.

Overview

Azure AI Foundry provides access to Claude through Microsoft's Azure AI platform with:

• Azure API key authentication
• Azure Active Directory (AAD) token provider authentication
• Automatic base URL construction from resource names

Client Initialization

class AnthropicFoundry:
    def __init__(
        self,
        *,
        resource: str | None = None,
        api_key: str | None = None,
        azure_ad_token_provider: Callable[[], str] | None = None,
        base_url: str | None = None,
        timeout: float | httpx.Timeout = DEFAULT_TIMEOUT,
        max_retries: int = DEFAULT_MAX_RETRIES,
        default_headers: dict[str, str] | None = None,
        http_client: httpx.Client | None = None,
    ):
        """
        Initialize Azure AI Foundry client.

        Parameters:
            resource: Azure resource name (e.g., "my-resource" for
                     https://my-resource.services.ai.azure.com/anthropic/)
            api_key: Azure API key (or ANTHROPIC_FOUNDRY_API_KEY env var)
            azure_ad_token_provider: Function returning Azure AD token
            base_url: Full base URL (mutually exclusive with resource)
            timeout: Request timeout
            max_retries: Maximum retry attempts
            default_headers: Custom headers
            http_client: Custom httpx.Client

        Environment Variables:
            ANTHROPIC_FOUNDRY_API_KEY: Default API key
            ANTHROPIC_FOUNDRY_RESOURCE: Default resource name
            ANTHROPIC_FOUNDRY_BASE_URL: Default base URL

        Note:
            Must provide either api_key or azure_ad_token_provider.
            Must provide either resource or base_url.
        """
        ...

class AsyncAnthropicFoundry:
    # Same parameters, but azure_ad_token_provider can return Awaitable[str]
    ...

Quick Examples

API Key Authentication

from anthropic import AnthropicFoundry

client = AnthropicFoundry(
    resource="my-resource",
    api_key="your-api-key"
)

message = client.messages.create(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

Azure AD Token Provider

def get_azure_ad_token():
    """Fetch Azure AD token using your preferred method."""
    # Implement token retrieval
    return "your-azure-ad-token"

client = AnthropicFoundry(
    resource="my-resource",
    azure_ad_token_provider=get_azure_ad_token
)

Using Base URL Directly

client = AnthropicFoundry(
    base_url="https://my-resource.services.ai.azure.com/anthropic/",
    api_key="your-api-key"
)

Async Client

import asyncio
from anthropic import AsyncAnthropicFoundry

async def main():
    client = AsyncAnthropicFoundry(
        resource="my-resource",
        api_key="your-api-key"
    )
    message = await client.messages.create(...)

asyncio.run(main())

Streaming

with client.messages.stream(
    model="claude-sonnet-4-5-20250929",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a haiku"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Limitations

The Azure AI Foundry integration has the following limitations:

1. No Models API: client.models resource not available
2. No Message Batches: client.messages.batches resource not available
3. No Beta Batches: client.beta.messages.batches resource not available

Environment Variables

• ANTHROPIC_FOUNDRY_API_KEY - Default API key
• ANTHROPIC_FOUNDRY_RESOURCE - Default resource name
• ANTHROPIC_FOUNDRY_BASE_URL - Default base URL

See Also

• Messages API - Core message creation
• Streaming API - Streaming responses