Azure OpenAI Coding Plan Tutorial: Enterprise-level GPT-4 Access Practice (2026 Latest Version)

Author: Programmer Wanfeng | AI Programming Evangelist | Focus on AI Tool Evaluation and Teaching
400,000+ followers across platforms, 6 years of Python development experience, author of open source project python-office

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Hello everyone, this is Programmer Wanfeng.

Today I bring you a practical tutorial for Azure OpenAI Coding Plan, teaching you step by step how to access enterprise-level GPT-4 services.

I. Preparation

What You Need to Prepare

An Azure account
Azure OpenAI access (requires application approval)
Python environment (3.8+)

II. Apply for Azure OpenAI Access

Step 1: Visit Official Website

👉 Click to view Azure OpenAI Coding Plan details

Step 2: Apply for Access

Azure OpenAI isn't directly open like regular APIs; it requires:

Log in to Azure portal
Search for "Azure OpenAI"
Click "Create"
Fill out the application form (purpose description, etc.)
Wait for Microsoft approval (usually 1-2 business days)

Step 3: Deploy Model

After approval:

Deploy model in Azure OpenAI Studio
Select model (GPT-4, GPT-4o, etc.)
Set deployment name
Get API Key and endpoint

III. Code Call Practice

Environment Installation

1	pip install openai

Basic Call

import openai

# Azure OpenAI configuration
openai.api_type = "azure"
openai.api_base = "https://your-resource.openai.azure.com"
openai.api_version = "2024-02-01"
openai.api_key = "your API Key"

# Call GPT-4
response = openai.ChatCompletion.create(
    engine="gpt-4",  # Your deployment name
    messages=[
        {"role": "user", "content": "Help me write a Python quick sort"}
    ]
)

print(response.choices[0].message.content)

GPT-4o Multimodal Call

# GPT-4o supports image input
response = openai.ChatCompletion.create(
    engine="gpt-4o",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What's the code problem in this image?"},
                {
                    "type": "image_url",
                    "image_url": {"url": "https://example.com/code.png"}
                }
            ]
        }
    ]
)

Code Assistant Example

def code_assistant(prompt, code=None):
    messages = [
        {"role": "system", "content": "You are a professional code assistant."}
    ]
    
    if code:
        messages.append({
            "role": "user",
            "content": f"{prompt}\n\nCode:\n{code}"
        })
    else:
        messages.append({"role": "user", "content": prompt})
    
    response = openai.ChatCompletion.create(
        engine="gpt-4",
        messages=messages
    )
    return response.choices[0].message.content

# Usage example
result = code_assistant("Help me optimize this code")

IV. Microsoft Ecosystem Integration

Integration with Microsoft 365

Azure OpenAI can be integrated into Microsoft 365:

# Call Microsoft Graph API
# Combine with Azure OpenAI to process Teams messages

import requests

def process_teams_message(message):
    # Analyze Teams message with GPT-4
    response = openai.ChatCompletion.create(
        engine="gpt-4",
        messages=[
            {"role": "user", "content": f"Analyze this Teams message: {message}"}
        ]
    )
    return response.choices[0].message.content