Azure AI Integration

The Azure AI integration provides access to OpenAI models hosted on Microsoft Azure through a unified interface. Configure once, use everywhere with enterprise-grade security and compliance.

Integrating Azure AI

Simply enter your Azure OpenAI API key and endpoint once in the Platform Integrations section. This enables authorized users to access Azure-hosted OpenAI models within the platform. Once integrated, models can be registered and used as any other python object on the platform.

# Example: Using a registered Azure model
result = azure_gpt4_model(text="Analyze this data", temperature=0.8)

Supported Models

Azure AI provides access to OpenAI models hosted on Microsoft Azure:

GPT-4 - Advanced reasoning and complex task completion
GPT-3.5 Turbo - Fast, efficient responses for most use cases
o4-mini, o3, o3-mini - Latest OpenAI models with enhanced capabilities
Additional Models - other OpenAI variants available

Registering a New Azure Model

Navigate to New Model to begin registration. The registration form connects your Azure AI integration with custom model configurations.

Basic Information

Description: Document your model's purpose, use cases, and limitations. For example: "GPT-4 on Azure optimized for document analysis. Use for enterprise content processing with Azure compliance. Ideal for sensitive data workflows."

Code Configuration

Alias: A unique identifier for your model (e.g., azure_gpt4_analyzer, corridor_gpt4). This becomes the variable name you'll use in code.

Output Type: Define the return format: - Map[String, String] - Key-value pairs for structured responses - String - Simple text responses - List - Array of items

Input Type: Select your implementation approach: - API Based: Platform handles API calls automatically using your Azure integration - Python Function: Custom function implementation with full control - Custom: Advanced configurations for specialized use cases

Model Provider: Select "Azure AI" from your configured integrations.

Arguments Configuration

Define input parameters that your model will accept. Important: Variables declared here are automatically available in the Scoring Logic section.

Common argument patterns for Azure models:

Alias	Type	Optional	Default Value	Usage
text	String	No	N/A	Main input content
temperature	Numerical	Yes	0.7	Controls response creativity
max_tokens	Numerical	Yes	1500	Maximum response length
system_prompt	String	Yes	""	System instructions

Use + Add Argument to include additional parameters.

Scoring Logic Implementation

In the Scoring Logic section, you can directly reference any variable declared in the Arguments section. The platform automatically makes these available in your code.

# Arguments: text, temperature are automatically available
import os
from openai import AzureOpenAI

# Direct initialization
client = AzureOpenAI(
    azure_endpoint="https://corridor-genai-demo.openai.azure.com/",
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),
    api_version="2024-12-01-preview",
)

chat_prompt = [{"role": "system", "content": [{"type": "text", "text": text}]}]

completion = client.chat.completions.create(
    model="gpt-4.1",
    messages=chat_prompt,
    max_tokens=1500,
    temperature=float(temperature),
    top_p=0.95,
    frequency_penalty=0,
    presence_penalty=0,
    stop=None,
    stream=False,
)

return {"output": completion.choices[0].message.content, "context": None}

Platform Integration Setup

Before registering models, configure your Azure credentials:

1. Navigate to Settings > Platform Integrations
2. Click on Azure AI
3. Enter your Azure OpenAI API key
4. Provide your Azure endpoint URL
5. Test the connection

The platform creates environment variables automatically: - AZURE_ENDPOINT

Example Use Case: Document Processing Model

An Azure GPT-4 model configured for enterprise document processing demonstrates the complete workflow:

Arguments Configuration:

• text (String, required)
• temperature (Numerical, optional, default: "0.3")
• max_tokens (Numerical, optional, default: "1500")
• system_prompt (String, optional, default: "")

Usage:

# Model becomes available as: document_processor
result = document_processor(
    text="Your document text here...",
    temperature=0.3,
    max_tokens=2000,
    system_prompt="Process the document and extract key information."
)

Want to Learn More?

• Review Azure OpenAI documentation
• Check Azure compliance and security features
• Monitor usage through Azure Portal
• Set up cost management and billing alerts