Azure OpenAI - profClaw

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

Create an Azure OpenAI resource

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

Get your credentials

From your Azure OpenAI resource, copy:

API key (under Keys and Endpoint)
Endpoint URL or Resource Name
Deployment name

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

Verify

profclaw doctor --provider azure

Environment Variables

string

required

Your Azure OpenAI API key.

string

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

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.

string

Alias for AZURE_OPENAI_BASE_URL.

string

Default deployment name to use when no model is specified.

string

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

Configuration Example

Resource Name mode
Base URL mode
settings.yml

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

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

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

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

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

import { chat } from 'profclaw';

const response = await chat("Analyze this data", {
  model: "azure",
});

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.

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

​Overview

​Supported Models

​Setup

​Environment Variables

​Configuration Example

​Model Aliases

​Usage Examples

​Notes

​Related

Overview

Supported Models

Setup

Environment Variables

Configuration Example

Model Aliases

Usage Examples

Notes

Related