use-your-data-python.md

manager	author	ms.author	ms.service	ms.topic	ms.date
nitinme	mrbullwinkle	mbullwin	azure-ai-openai	include	11/09/2023

[!INCLUDE Set up required variables]

Create a Python environment

1. Create a new folder named openai-python for your project and a new Python code file named main.py. Change into that directory:

mkdir openai-python
cd openai-python

2. Install the following Python Libraries:

OpenAI Python 0.28.1

pip install openai==0.28.1
pip install python-dotenv

OpenAI Python 1.x

pip install openai
pip install python-dotenv

---

Create the Python app

1. From the project directory, open the main.py file and add the following code:

OpenAI Python 0.28.1

import os
import openai
import dotenv
import requests

dotenv.load_dotenv()

openai.api_base = os.environ.get("AOAIEndpoint")

# Azure OpenAI on your own data is only supported by the 2023-08-01-preview API version
openai.api_version = "2023-08-01-preview"
openai.api_type = 'azure'
openai.api_key = os.environ.get("AOAIKey")

def setup_byod(deployment_id: str) -> None:
    """Sets up the OpenAI Python SDK to use your own data for the chat endpoint.
 
    :param deployment_id: The deployment ID for the model to use with your own data.

    To remove this configuration, simply set openai.requestssession to None.
    """

    class BringYourOwnDataAdapter(requests.adapters.HTTPAdapter):

     def send(self, request, **kwargs):
         request.url = f"{openai.api_base}/openai/deployments/{deployment_id}/extensions/chat/completions?api-version={openai.api_version}"
         return super().send(request, **kwargs)

    session = requests.Session()

    # Mount a custom adapter which will use the extensions endpoint for any call using the given `deployment_id`
    session.mount(
        prefix=f"{openai.api_base}/openai/deployments/{deployment_id}",
        adapter=BringYourOwnDataAdapter()
    )

    openai.requestssession = session

aoai_deployment_id = os.environ.get("AOAIDeploymentId")
setup_byod(aoai_deployment_id)

completion = openai.ChatCompletion.create(
    messages=[{"role": "user", "content": "What are the differences between Azure Machine Learning and Azure AI services?"}],
    deployment_id=os.environ.get("AOAIDeploymentId"),
    dataSources=[  # camelCase is intentional, as this is the format the API expects
        {
            "type": "AzureCognitiveSearch",
            "parameters": {
                "endpoint": os.environ.get("SearchEndpoint"),
                "key": os.environ.get("SearchKey"),
                "indexName": os.environ.get("SearchIndex"),
            }
        }
    ]
)
print(completion)

OpenAI Python 1.x

import os
import openai
import dotenv

dotenv.load_dotenv()

endpoint = os.environ.get("AOAIEndpoint")
api_key = os.environ.get("AOAIKey")
deployment = os.environ.get("AOAIDeploymentId")

client = openai.AzureOpenAI(
    base_url=f"{endpoint}/openai/deployments/{deployment}/extensions",
    api_key=api_key,
    api_version="2023-08-01-preview",
)

completion = client.chat.completions.create(
    model=deployment,
    messages=[
        {
            "role": "user",
            "content": "How is Azure machine learning different than Azure OpenAI?",
        },
    ],
    extra_body={
        "dataSources": [
            {
                "type": "AzureCognitiveSearch",
                "parameters": {
                    "endpoint": os.environ["SearchEndpoint"],
                    "key": os.environ["SearchKey"],
                    "indexName": os.environ["SearchIndex"]
                }
            }
        ]
    }
)

print(completion.model_dump_json(indent=2))

---

Important

For production, use a secure way of storing and accessing your credentials like Azure Key Vault. For more information about credential security, see the Azure AI services security article.

2. Execute the following command:

python main.py

The application prints the response in a JSON format suitable for use in many scenarios. It includes both answers to your query and citations from your uploaded files.

[!div class="nextstepaction"] I ran into an issue when running the code samples.