Azure OpenAI

Use GPT-4o and other OpenAI models via Azure OpenAI Service. Enterprise SLAs, private networking, and data residency.

Azure OpenAI Service provides access to OpenAI’s models through Microsoft’s Azure infrastructure. It offers enterprise features including private networking, compliance certifications, and data residency guarantees.

Overview

Azure OpenAI differs from the standard OpenAI API:

• Models are deployed to your own Azure resource
• Access via your Azure resource endpoint, not api.openai.com
• Models are referenced by deployment names you define
• Supports both standard resource mode and Azure AI Foundry (custom base URL)

Supported Models

Any OpenAI model available in Azure can be deployed. Common deployments:

Deployment	Model	Notes
gpt-4o	GPT-4o	Most common
gpt-4o-mini	GPT-4o Mini	Cost-efficient
o1	o1	Reasoning
gpt-4-turbo	GPT-4 Turbo	Legacy

All Azure-deployed models support native tool calling - profClaw assumes tool support for all Azure models.

Setup

1. Create an Azure OpenAI resource

   In the Azure Portal, create an Azure OpenAI resource and deploy a model.

2. Get your credentials

   From your Azure OpenAI resource, copy:

   • API key (under Keys and Endpoint)
   • Endpoint URL or Resource Name
   • Deployment name
3. Set environment variables

   Option A - Resource Name mode (standard):

   AZURE_OPENAI_API_KEY=your-key
   AZURE_OPENAI_RESOURCE_NAME=your-resource-name
   AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o
   

   Option B - Base URL mode (AI Foundry / custom endpoint):

   AZURE_OPENAI_API_KEY=your-key
   AZURE_OPENAI_BASE_URL=https://your-resource.openai.azure.com
   AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o
   
4. Verify

   profclaw doctor --provider azure
   

Environment Variables

AZURE_OPENAI_API_KEY · string · required

Your Azure OpenAI API key.

AZURE_OPENAI_RESOURCE_NAME · string

Your Azure OpenAI resource name (e.g., my-openai-resource). Used in standard mode.

AZURE_OPENAI_BASE_URL · string

Full endpoint URL (e.g., https://my-resource.openai.azure.com). Used in AI Foundry / custom endpoint mode. Takes precedence over AZURE_OPENAI_RESOURCE_NAME.

AZURE_OPENAI_ENDPOINT · string

Alias for AZURE_OPENAI_BASE_URL.

AZURE_OPENAI_DEPLOYMENT_NAME · string

Default deployment name to use when no model is specified.

AZURE_OPENAI_API_VERSION · string

API version to use. Defaults to 2024-10-21.

Configuration Example

Resource Name mode

AZURE_OPENAI_API_KEY=abc123
AZURE_OPENAI_RESOURCE_NAME=my-openai
AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o
AZURE_OPENAI_API_VERSION=2024-10-21

Base URL mode

AZURE_OPENAI_API_KEY=abc123
AZURE_OPENAI_BASE_URL=https://my-openai.openai.azure.com
AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o

settings.yml

providers:
  azure:
    api_key: "${AZURE_OPENAI_API_KEY}"
    resource_name: "${AZURE_OPENAI_RESOURCE_NAME}"
    deployment_name: "${AZURE_OPENAI_DEPLOYMENT_NAME}"
    api_version: "2024-10-21"

Model Aliases

Alias	Resolves To
azure	Your configured deployment
azure-gpt	Your configured deployment

When using the azure or azure-gpt alias, profClaw uses the deployment name from AZURE_OPENAI_DEPLOYMENT_NAME.

Usage Examples

CLI

# Uses your configured deployment
profclaw chat --model azure "Review this architecture"

# Specific deployment by name
profclaw chat --model azure/gpt-4o "Explain this code"

Notes

• Azure is ranked 3rd in auto-selection priority after Anthropic and OpenAI.
• All Azure GPT-4+ deployments support native tool calling.
• For private network setups, configure a custom base URL pointing to your private endpoint.
• API version 2024-10-21 is the minimum supported for function calling with structured outputs.

Related

• AI Providers Overview - Compare all 37 supported providers
• OpenAI - Direct OpenAI API without Azure infrastructure
• Amazon Bedrock - AWS-native alternative for enterprise deployments
• profclaw provider - Add and test providers from the CLI