Use chat completion configuration in a Python console app

In this guide, you build an AI chat application and iterate on the prompt using chat completion configuration dynamically loaded from Azure App Configuration.

The full sample source code is available in the Azure App Configuration GitHub repository.

Prerequisites

Complete the tutorial to Create a chat completion configuration.
Python 3.9 or later - for information on setting up Python on Windows, see the Python on Windows documentation.

Create a console app

Create a new directory for your project and navigate to it:
```
mkdir chatapp-quickstart
cd chatapp-quickstart
```

Install the required Python packages:

pip install azure-appconfiguration-provider
pip install azure-identity
pip install azure-ai-projects

Create a file named app.py and add the following import statements:

import os
from azure.appconfiguration.provider import load, SettingSelector, WatchKey
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient

Create a function to load configuration from Azure App Configuration.

You can connect to App Configuration using either Microsoft Entra ID (recommended) or a connection string. In this example, you use Microsoft Entra ID with DefaultAzureCredential to authenticate to your App Configuration store. Follow these instructions to assign the App Configuration Data Reader role to the identity represented by DefaultAzureCredential. Be sure to allow sufficient time for the permission to propagate before running your application.

credential = DefaultAzureCredential()

def load_azure_app_configuration():
    endpoint = os.environ.get("AZURE_APPCONFIGURATION_ENDPOINT")
    if not endpoint:
        raise ValueError("AZURE_APPCONFIGURATION_ENDPOINT environment variable is not set")

    config = load(
        endpoint=endpoint,
        credential=credential,
        # Load all keys that start with "ChatApp:" and have no label
        selectors=[SettingSelector(key_filter="ChatApp:*")],
        trim_prefixes=["ChatApp:"],
        # Reload configuration if the ChatCompletion key has changed.
        # Use the default refresh interval of 30 seconds. It can be overridden via refresh_interval.
        refresh_on=[WatchKey("ChatApp:ChatCompletion")],
    )
    return config

Create a function to get AI responses from the chat client:

def get_ai_response(client, config, chat_conversation):
    chat_completion_config = config["ChatCompletion"]
    messages = []

    # Add configured messages (system, user, assistant)
    for msg in chat_completion_config["messages"]:
        messages.append({"role": msg["role"], "content": msg["content"]})

    # Add the chat conversation history
    messages.extend(chat_conversation)

    # Create chat completion
    response = client.complete(
        model=chat_completion_config["model"],
        messages=messages,
    )
    return response.choices[0].message.content

Create the main function that configures the chat client and runs the chat loop.

Create an instance of the AIProjectClient to connect to your Azure AI Foundry project. You use DefaultAzureCredential to authenticate. Assign the Cognitive Services OpenAI User role to the identity represented by DefaultAzureCredential. For detailed steps, refer to the Role-based access control for Azure OpenAI service guide. Be sure to allow sufficient time for the permission to propagate before running your application.

def main():
    config = load_azure_app_configuration()

    # Create a project client using Microsoft Entra ID
    project_client = AIProjectClient(
        endpoint=config["AzureAIFoundry:Endpoint"],
        credential=credential,
    )
    openai_client = project_client.get_openai_client()

    # Initialize chat conversation
    chat_conversation = []
    print("Chat started! What's on your mind?")

    while True:
        # Refresh the configuration from Azure App Configuration
        config.refresh()

        # Get user input
        user_input = input("You: ")

        # Exit if user input is empty
        if not user_input:
            print("Exiting Chat. Goodbye!")
            break

        # Add user message to chat conversation
        chat_conversation.append({"role": "user", "content": user_input})

        # Get AI response and add it to chat conversation
        response = get_ai_response(openai_client, config, chat_conversation)
        print(f"AI: {response}\n")
        chat_conversation.append({"role": "assistant", "content": response})

if __name__ == "__main__":
    main()

After completing the previous steps, your app.py file should now contain the complete implementation as shown below:

import os
from azure.appconfiguration.provider import load, SettingSelector, WatchKey
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient

credential = DefaultAzureCredential()


def load_azure_app_configuration():
    endpoint = os.environ.get("AZURE_APPCONFIGURATION_ENDPOINT")
    if not endpoint:
        raise ValueError("AZURE_APPCONFIGURATION_ENDPOINT environment variable is not set")

    config = load(
        endpoint=endpoint,
        credential=credential,
        # Load all keys that start with "ChatApp:" and have no label
        selectors=[SettingSelector(key_filter="ChatApp:*")],
        trim_prefixes=["ChatApp:"],
        # Reload configuration if the ChatCompletion key has changed.
        # Use the default refresh interval of 30 seconds. It can be overridden via refresh_interval.
        refresh_on=[WatchKey("ChatApp:ChatCompletion")],
    )
    return config


def get_ai_response(client, config, chat_conversation):
    chat_completion_config = config["ChatCompletion"]
    messages = []

    # Add configured messages (system, user, assistant)
    for msg in chat_completion_config["messages"]:
        messages.append({"role": msg["role"], "content": msg["content"]})

    # Add the chat conversation history
    messages.extend(chat_conversation)

    # Create chat completion
    response = client.chat.completions.create(
        model=chat_completion_config["model"],
        messages=messages,
        max_completion_tokens=chat_completion_config["max_completion_tokens"],
    )
    return response.choices[0].message.content


def main():
    config = load_azure_app_configuration()

    # Create a project client using Microsoft Entra ID
    project_client = AIProjectClient(
        endpoint=config["AzureAIFoundry:Endpoint"],
        credential=credential,
    )
    openai_client = project_client.get_openai_client()

    # Initialize chat conversation
    chat_conversation = []
    print("Chat started! What's on your mind?")

    while True:
        # Refresh the configuration from Azure App Configuration
        config.refresh()

        # Get user input
        user_input = input("You: ")

        # Exit if user input is empty
        if not user_input:
            print("Exiting Chat. Goodbye!")
            break

        # Add user message to chat conversation
        chat_conversation.append({"role": "user", "content": user_input})

        # Get AI response and add it to chat conversation
        response = get_ai_response(openai_client, config, chat_conversation)
        print(f"AI: {response}\n")
        chat_conversation.append({"role": "assistant", "content": response})


if __name__ == "__main__":
    main()

Build and run the app

Set the environment variable named AZURE_APPCONFIGURATION_ENDPOINT to the endpoint of your App Configuration store found under the Overview of your store in the Azure portal.

If you use the Windows command prompt, run the following command and restart the command prompt to allow the change to take effect:
```
setx AZURE_APPCONFIGURATION_ENDPOINT "<endpoint-of-your-app-configuration-store>"
```
If you use PowerShell, run the following command:
```
$Env:AZURE_APPCONFIGURATION_ENDPOINT = "<endpoint-of-your-app-configuration-store>"
```
If you use macOS or Linux, run the following command:
```
export AZURE_APPCONFIGURATION_ENDPOINT='<endpoint-of-your-app-configuration-store>'
```
After the environment variable is properly set, run the following command to run your app:
```
python app.py
```

Type the message "What is your name?" when prompted with "You:" and then press the Enter key.

Chat started! What's on your mind?
You: What is your name?
AI: I'm your helpful assistant! I don't have a personal name, but you can call me whatever you'd like. 
😊 Do you have a name in mind?

In Azure portal, select the App Configuration store instance that you created. From the Operations menu, select Configuration explorer and select the ChatApp:ChatCompletion key. Update the value of the Messages property:
- Role: system
- Content: "You are a pirate and your name is Eddy."

Type the same message when prompted with "You:". Be sure to wait a few moments for the refresh interval to elapse, and then press the Enter key to see the updated AI response in the output.

Chat started! What's on your mind?
You: What is your name?
AI: I'm your helpful assistant! I don't have a personal name, but you can call me whatever you'd like. 
😊 Do you have a name in mind?

You: What is your name?
AI: Arrr, matey! Me name be Eddy, the most fearsome pirate to ever sail the seven seas!
What be yer name, landlubber?

Feedback

Was this page helpful?

Last updated on 2026-03-11