Azure OpenAI

⚠️ Check Model and Feature Availability by Region

Before deploying an LLM model in Azure, always check the official Azure documentation to verify that the required model and capabilities (vision, audio, etc.) are available in your region. Availability varies by region and by feature. Use the links below to confirm support for your use case:

Key Capabilities and Official Documentation:

• General model list & region availability: Azure OpenAI Service models – Region availability (Microsoft Learn)
• Vision (GPT-4 Turbo with Vision, GPT-4o, o1, etc.): How-to: GPT with Vision (Microsoft Learn)
• Audio / Whisper: The Whisper model from OpenAI (Microsoft Learn) Audio concepts in Azure OpenAI (Microsoft Learn)
• PDF / Documents: Azure AI Foundry feature availability across clouds regions (Microsoft Learn)

Summary:

• Vision (multimodal): Models like GPT-4 Turbo with Vision, GPT-4o, o1, etc. are only available in certain regions. In the Azure Portal, the "Model deployments" → "Add deployment" tab lists only those available in your region. See the linked guide for input limits and JSON output.
• Audio / Whisper: There are two options: (1) Azure OpenAI (same /audio/* routes as OpenAI, limited regions), and (2) Azure AI Speech (more regions, different billing). See the links for region tables.
• PDF / Documents: Azure OpenAI does not natively process PDFs. Use Azure AI Document Intelligence or Azure AI Search for document processing. The AI Foundry table shows where each feature is available.

Conclusion: Before deploying, verify that your Azure resource's region supports the required model and features. If not, create the resource in a supported region or wait for general availability.

Azure OpenAI provides all the capabilities of OpenAI models within Azure's secure and compliant cloud environment. fast-agent supports three authentication methods:

1. Using resource_name and api_key (standard method)
2. Using base_url and api_key (for custom endpoints or sovereign clouds)
3. Using base_url and DefaultAzureCredential (for managed identity, Azure CLI, etc.)

YAML Configuration:

# Option 1: Standard configuration with resource_name
azure:
  api_key: "your_azure_openai_key" # Required unless using DefaultAzureCredential
  resource_name: "your-resource-name" # Resource name (do NOT include if using base_url)
  azure_deployment: "deployment-name" # Required - the model deployment name
  api_version: "2024-10-21" # Optional, default shown
  default_headers:
    Ocp-Apim-Subscription-Key: "${AZURE_OPENAI_API_KEY}"
  # Do NOT include base_url if you use resource_name

# Option 2: Custom endpoint with base_url
azure:
  api_key: "your_azure_openai_key"
  base_url: "https://your-resource-name.openai.azure.com" # Full endpoint URL
  azure_deployment: "deployment-name"
  api_version: "2024-10-21" # Optional
  # Do NOT include resource_name if you use base_url

# Option 3: Using DefaultAzureCredential (requires azure-identity package)
azure:
  use_default_azure_credential: true
  base_url: "https://your-resource-name.openai.azure.com"
  azure_deployment: "deployment-name"
  api_version: "2024-10-21" # Optional
  # Do NOT include api_key or resource_name when using DefaultAzureCredential

Important Configuration Notes: - Use either resource_name or base_url, not both. - When using DefaultAzureCredential, do NOT include api_key or resource_name. - When using base_url, do NOT include resource_name. - When using resource_name, do NOT include base_url. - default_headers can be used with any option (for example, APIM subscription keys).

Environment Variables:

• AZURE_OPENAI_API_KEY: Your Azure OpenAI API key
• AZURE_OPENAI_ENDPOINT: Override the API endpoint

Model Name Format:

Use azure.deployment-name as the model string, where deployment-name is the name of your Azure OpenAI deployment.