How to intermediate · 3 min read

Azure OpenAI private endpoint setup

Q: Azure OpenAI private endpoint setup

To set up a private endpoint for Azure OpenAI, configure the private link in the Azure portal to restrict network access. Then use the AzureOpenAI client from the openai Python SDK with your private endpoint URL as azure_endpoint and your API key from environment variables.

Quick answer

To set up a private endpoint for Azure OpenAI, configure the private link in the Azure portal to restrict network access. Then use the AzureOpenAI client from the openai Python SDK with your private endpoint URL as azure_endpoint and your API key from environment variables.

PREREQUISITES

Python 3.8+
Azure subscription with Azure OpenAI resource
Private endpoint configured in Azure portal
Azure OpenAI API key
pip install openai>=1.0

Setup

Install the official openai Python package version 1.0 or higher. Set environment variables for your Azure OpenAI API key and private endpoint URL. The private endpoint URL is the fully qualified domain name (FQDN) of your Azure OpenAI resource's private link.

bash

pip install openai>=1.0

Step by step

Use the AzureOpenAI client from the openai package. Pass your private endpoint URL as azure_endpoint and the API key from environment variables. Call chat.completions.create with your deployment name as the model. This example sends a simple prompt and prints the response.

python

import os
from openai import AzureOpenAI

client = AzureOpenAI(
    api_key=os.environ["AZURE_OPENAI_API_KEY"],
    azure_endpoint=os.environ["AZURE_OPENAI_PRIVATE_ENDPOINT"],
    api_version="2024-02-01"
)

response = client.chat.completions.create(
    model=os.environ["AZURE_OPENAI_DEPLOYMENT"],
    messages=[{"role": "user", "content": "Hello from private endpoint!"}]
)

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

output

Hello from private endpoint! How can I assist you today?

Common variations

Use different model deployment names as configured in Azure.
For async calls, use asyncio with await client.chat.completions.acreate(...).
Streaming responses are supported with stream=True parameter.

python

import asyncio
from openai import AzureOpenAI

async def main():
    client = AzureOpenAI(
        api_key=os.environ["AZURE_OPENAI_API_KEY"],
        azure_endpoint=os.environ["AZURE_OPENAI_PRIVATE_ENDPOINT"],
        api_version="2024-02-01"
    )

    response = await client.chat.completions.acreate(
        model=os.environ["AZURE_OPENAI_DEPLOYMENT"],
        messages=[{"role": "user", "content": "Async hello from private endpoint!"}]
    )

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

asyncio.run(main())

output

Async hello from private endpoint! How can I assist you today?

Troubleshooting

If you get 403 Forbidden, verify your private endpoint is approved and DNS resolves to the private IP.
Ensure your azure_endpoint URL matches the private endpoint FQDN exactly, including protocol https://.
Check that your API key has permissions for the Azure OpenAI resource.

✅

Key Takeaways

Configure Azure private endpoint in the Azure portal before using it in code.
Use AzureOpenAI client with azure_endpoint set to your private endpoint URL.
Always load API keys and endpoint URLs from environment variables for security.
Async and streaming calls are supported with the AzureOpenAI Python SDK.
Verify DNS and network access if you encounter authorization or connectivity errors.

Verified 2026-04 · gpt-4o, gpt-4o-mini

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