This gist assumes that:

• you are already using OpenAI services via the OpenAI API
• you want to migrate to an Azure-based workflow
• somebody else has already set up the Azure endpoint for you

Old Workflow (no Azure)

from openai import OpenAI
client = OpenAI(
    # Defaults to os.environ.get("OPENAI_API_KEY")
)

chat_completion = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Hello world"}]
)

New Workflow (Azure Endpoint)

You now just need to change the instantiation of the client to the following:

from openai import AzureOpenAI

client = AzureOpenAI(
    azure_endpoint=<AZURE_ENDPOINT>,
    api_key=<AZURE_KEY>,
    api_version=<API_VERSION>,
)

The AzureOpenAI client class can then be used in the same way as the regular OpenAI client class.

Managing Credentials

Tip

It's a good idea to still use environmental variables and config files when dealing with these keys.

I recommend using config files and environmental variables as to avoid accidentally leaking these credentials (which would allow others to abuse the resource).

My recommended workflow:

1. Create a folder .cfg in your home directory. (mkdir ~/.cfg)
2. Create a file openai.cfg in ~/.cfg/openai.cfg (touch ~/.cfg/openai.cfg)
3. Copy the credentials I send to you into openai.cfg in the following format:

[AZURE]
key=...
endpoint=...

Where key will be a string of letters and numbers endpoint will be a URL.

You can now use the configparser module in Python to read these values into your script (see attached script below).