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‎articles/api-management/api-management-howto-use-managed-service-identity.md‎

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‎articles/app-service/app-service-undelete.md‎

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‎articles/app-service/includes/tutorial-ai-openai-chatbot/create-openai-resource.md‎

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author: cephalin
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ms.service: azure-app-service
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ms.topic: include
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ms.date: 11/18/2025
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ms.date: 03/03/2026
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ms.author: cephalin
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ms.custom:
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- build-2025
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---
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In this section, you'll use GitHub Codespaces to create an Azure OpenAI resource with the Azure CLI.
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In this section, you use Azure CLI in GitHub Codespaces to create an Azure OpenAI resource.
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1. Go to [GitHub Codespaces](https://github.com/codespaces) and sign in with your GitHub account.
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1. Find the **Blank** template by GitHub and select **Use this template** to create a new blank Codespace.
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1. In the Codespace terminal, install the Azure CLI:
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1. Sign in to [GitHub Codespaces](https://github.com/codespaces) with your GitHub account.
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1. Select **Use this template** in the **Blank** tile to create a new blank codespace.
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1. In the Codespace terminal, install the Azure CLI.
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```bash
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curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash
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```
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1. Sign in to your Azure account:
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```bash
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curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash
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```
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```azurecli
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az login
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```
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Follow the instructions in the terminal to authenticate.
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1. Sign in to your Azure account.
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1. Set environment variables for your resource group name, Azure OpenAI service name, and location:
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```azurecli
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az login
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```
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```azurecli
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export RESOURCE_GROUP="<group-name>"
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export OPENAI_SERVICE_NAME="<azure-openai-name>"
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export APPSERVICE_NAME="<app-name>"
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export LOCATION="eastus2"
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```
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Follow the instructions in the terminal to authenticate.
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> [!IMPORTANT]
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> The region is critical as it's tied to the regional availability of the chosen model. Model availability and [deployment type availability](/azure/ai-foundry/foundry-models/concepts/deployment-types) vary from region to region. This tutorial uses `gpt-4o-mini`, which is available in `eastus2` under the Standard deployment type. If you deploy to a different region, this model might not be available or might require a different tier. Before changing regions, consult the [Model summary table and region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability) to verify model support in your preferred region.
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>
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1. Set environment variables by providing names for your resource group and Azure OpenAI service and setting an appropriate Azure region as your location.
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1. Create a resource group and an Azure OpenAI resource with a custom domain, then add a gpt-4o-mini model:
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```azurecli
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export RESOURCE_GROUP="<group-name>"
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export OPENAI_SERVICE_NAME="<azure-openai-name>"
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export APPSERVICE_NAME="<app-name>"
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export LOCATION="<azure-region>"
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```
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```azurecli
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# Resource group
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az group create --name $RESOURCE_GROUP --location $LOCATION
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# Azure OpenAI resource
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az cognitiveservices account create \
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--name $OPENAI_SERVICE_NAME \
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--resource-group $RESOURCE_GROUP \
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--location $LOCATION \
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--custom-domain $OPENAI_SERVICE_NAME \
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--kind OpenAI \
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--sku s0
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# gpt-4o-mini model
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az cognitiveservices account deployment create \
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--name $OPENAI_SERVICE_NAME \
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--resource-group $RESOURCE_GROUP \
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--deployment-name gpt-4o-mini \
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--model-name gpt-4o-mini \
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--model-version 2024-07-18 \
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--model-format OpenAI \
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--sku-name Standard \
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--sku-capacity 1
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# Cognitive Services OpenAI User role that lets the signed in Azure user to read models from Azure OpenAI
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az role assignment create \
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--assignee $(az ad signed-in-user show --query id -o tsv) \
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--role "Cognitive Services OpenAI User" \
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--scope /subscriptions/$(az account show --query id -o tsv)/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.CognitiveServices/accounts/$OPENAI_SERVICE_NAME
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```
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> [!IMPORTANT]
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> The location is tied to the regional availability of the chosen model. Model and [deployment type](/azure/ai-foundry/foundry-models/concepts/deployment-types) availability vary among Azure regions and billing tiers. This tutorial uses `gpt-4o-mini`, which is available in several regions under the Standard deployment type.
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>
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> Before selecting a location, consult the [Model summary and region availability table](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability) to verify model support in your preferred region.
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Now that you have an Azure OpenAI resource, you'll create a web application to interact with it.
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1. Create a resource group and an Azure OpenAI resource with a custom domain, and then add a `gpt-4o-mini` model:
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```azurecli
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# Resource group
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az group create --name $RESOURCE_GROUP --location $LOCATION
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# Azure OpenAI resource
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az cognitiveservices account create \
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--name $OPENAI_SERVICE_NAME \
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--resource-group $RESOURCE_GROUP \
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--location $LOCATION \
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--custom-domain $OPENAI_SERVICE_NAME \
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--kind OpenAI \
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--sku s0
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# gpt-4o-mini model
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az cognitiveservices account deployment create \
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--name $OPENAI_SERVICE_NAME \
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--resource-group $RESOURCE_GROUP \
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--deployment-name gpt-4o-mini \
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--model-name gpt-4o-mini \
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--model-version 2024-07-18 \
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--model-format OpenAI \
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--sku-name Standard \
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--sku-capacity 1
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# Cognitive Services OpenAI User role that lets the signed in Azure user read models from Azure OpenAI
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az role assignment create \
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--assignee $(az ad signed-in-user show --query id -o tsv) \
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--role "Cognitive Services OpenAI User" \
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--scope /subscriptions/$(az account show --query id -o tsv)/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.CognitiveServices/accounts/$OPENAI_SERVICE_NAME
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```
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Now that you have an Azure OpenAI resource, you can create a web application to interact with it.

‎articles/app-service/media/tutorial-ai-openai-chatbot-python/chat-in-browser.png‎

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‎articles/app-service/tutorial-ai-openai-chatbot-python.md‎

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---
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title: Intelligent app with Azure OpenAI (Flask)
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description: Learn how to build and deploy a Python web app to Azure App Service that connects to Azure OpenAI using managed identity.
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title: Build and deploy an Azure OpenAI (Flask) chatbot
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description: Learn how to build a Python web app that connects to Azure OpenAI and deploy it to Azure App Service using managed identity.
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author: jefmarti
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ms.author: jefmarti
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ms.date: 05/19/2025
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ms.date: 03/03/2026
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ms.update-cycle: 180-days
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ms.topic: tutorial
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ms.custom:
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- build-2025
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ms.collection: ce-skilling-ai-copilot
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ms.service: azure-app-service
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#customer intent: As a Python web app developer, I want to build an intelligent AI application that uses Azure OpenAI and deploy it to Azure App Service so I can offer a cloud chatbot app to my users.
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---
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# Tutorial: Build a chatbot with Azure App Service and Azure OpenAI (Flask)
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In this tutorial, you'll build an intelligent AI application by integrating Azure OpenAI with a Python web application and deploying it to Azure App Service. You'll create a Flask app that sends chat completion requests to a model in Azure OpenAI.
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:::image type="content" source="media/tutorial-ai-openai-chatbot-python/chat-in-browser.png" alt-text="Screenshot showing chatbot running in Azure App Service.":::
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In this tutorial, you build an intelligent AI application by integrating Azure OpenAI with a Python web application and deploy it to Azure App Service. You create a Flask app that sends chat completion requests to a model in Azure OpenAI, and connect to the service using a managed identity.
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In this tutorial, you learn how to:
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You learn how to:
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> [!div class="checklist"]
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> * Create an Azure OpenAI resource and deploy a language model.
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> * Build a Flask application that connects to Azure OpenAI.
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> * Deploy the application to Azure App Service.
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> * Implement passwordless secure authentication both in the development environment and in Azure.
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> * Implement passwordless secure authentication in the development environment and in Azure.
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:::image type="content" source="media/tutorial-ai-openai-chatbot-python/chat-in-browser.png" alt-text="Screenshot showing a chatbot running in Azure App Service.":::
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## Prerequisites
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```
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1. In the workspace root, create an *app.py* and copy the following code into it, for a simple chat completion call with Azure OpenAI.
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1. In the workspace root, create a file named *app.py* containing the following code for a simple chat completion call with Azure OpenAI.
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```python
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import os
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app.run()
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```
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1. Create a *templates* directory and an *index.html* file in it. Copy the following code into it for a simple chat interface:
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1. Create a *templates* directory and an *index.html* file in it. Paste in the following code for creating a simple chat interface.
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```html
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<!doctype html>
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--output tsv
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```
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1. Run the app by adding `AZURE_OPENAI_ENDPOINT` with its value from the CLI output:
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1. Run the app by adding `AZURE_OPENAI_ENDPOINT` with the value from the preceding CLI output.
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```bash
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AZURE_OPENAI_ENDPOINT=<output-from-previous-cli-command> flask run
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```
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1. Select **Open in browser** to launch the app in a new browser tab. Submit a question and see if you get a response message.
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1. Select **Open in browser** to launch the app in a new browser tab. Submit a question to see a response message.
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## 3. Deploy to Azure App Service and configure OpenAI connection
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Now that your app works locally, let's deploy it to Azure App Service and set up a service connection to Azure OpenAI using managed identity.
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Now that your app works locally, deploy it to Azure App Service and set up a service connection to Azure OpenAI using managed identity.
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1. First, deploy your app to Azure App Service using the Azure CLI command `az webapp up`. This command creates a new web app in the same resource group as your OpenAI resource and deploys your code to it. The command might take a few minutes to complete.
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1. First, deploy your app to Azure App Service using the Azure CLI command `az webapp up`. This command creates a new web app and deploys your code to it:
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```azurecli
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az webapp up \
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--track-status false
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```
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This command might take a few minutes to complete. It creates a new web app in the same resource group as your OpenAI resource.
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1. After the app is deployed, create a service connection between your web app and the Azure OpenAI resource using managed identity:
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1. After the app is deployed, create a service connection between your web app and the Azure OpenAI resource using managed identity. The following command creates a connection between your web app and the Azure OpenAI resource by:
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- Generating a system-assigned managed identity for the web app.
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- Adding the **Cognitive Services OpenAI Contributor** role to the managed identity for the Azure OpenAI resource.
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- Adding the `AZURE_OPENAI_ENDPOINT` app setting to your web app.
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--resource-group $RESOURCE_GROUP \
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--name $APPSERVICE_NAME \
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--target-resource-group $RESOURCE_GROUP \
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--account $OPENAI_SERVICE_NAME \
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--connection azure-openai \
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--connection azure_openai \
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--system-identity
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```
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This command creates a connection between your web app and the Azure OpenAI resource by:
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1. Find the URL of your deployed app in the terminal output from the `az webapp up` command, and navigate to the app in your web browser.
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- Generating system-assigned managed identity for the web app.
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- Adding the Cognitive Services OpenAI Contributor role to the managed identity for the Azure OpenAI resource.
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- Adding the `AZURE_OPENAI_ENDPOINT` app setting to your web app.
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1. Open the deployed web app in the browser. Find the URL of the deployed web app in the terminal output. Open your web browser and navigate to it.
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```azurecli
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az webapp browse
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```
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```azurecli
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az webapp browse
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```
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1. Type a message in the textbox and select **Send**, and give the app a few seconds to reply with the message from Azure OpenAI.
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1. In your web app, enter a message in the textbox and select **Send**. Give the app a few seconds to reply with the message from Azure OpenAI.
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:::image type="content" source="media/tutorial-ai-openai-chatbot-python/chat-in-browser.png" alt-text="Screenshot showing chatbot running in Azure App Service.":::
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:::image type="content" source="media/tutorial-ai-openai-chatbot-python/chat-in-browser.png" alt-text="Screenshot showing chatbot running in Azure App Service.":::
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Your app is now deployed and connected to Azure OpenAI with managed identity.
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## Frequently asked questions
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- [What if I want to connect to OpenAI instead of Azure OpenAI?](#what-if-i-want-to-connect-to-openai-instead-of-azure-openai)
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- [Can I connect to Azure OpenAI with an API key instead?](#can-i-connect-to-azure-openai-with-an-api-key-instead)
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- [How does DefaultAzureCredential work in this tutorial?](#how-does-defaultazurecredential-work-in-this-tutorial)
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- [How can I connect to OpenAI instead of Azure OpenAI?](#how-can-i-connect-to-openai-instead-of-azure-openai)
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- [Can I connect to Azure OpenAI with an API key instead of managed identity?](#can-i-connect-to-azure-openai-with-an-api-key-instead-of-managed-identity)
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- [How does the DefaultAzureCredential work?](#how-does-the-defaultazurecredential-work)
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---
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### What if I want to connect to OpenAI instead of Azure OpenAI?
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### How can I connect to OpenAI instead of Azure OpenAI?
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To connect to OpenAI instead, use the following code:
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To connect to OpenAI instead of Azure OpenAI, use the following code:
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For more information, see [How to switch between OpenAI and Azure OpenAI endpoints with Python](/azure/ai-services/openai/how-to/switching-endpoints).
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When working with connection secrets in App Service, you should use [Key Vault references](app-service-key-vault-references.md) instead of storing secrets directly in your codebase. This ensures that sensitive information remains secure and is managed centrally.
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>[!IMPORTANT]
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>When working with connection secrets like API keys in App Service, you should [use Azure Key Vault references](app-service-key-vault-references.md) instead of storing secrets directly in your code. This practice ensures that sensitive information remains secure and is managed centrally.
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### Can I connect to Azure OpenAI with an API key instead?
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### Can I connect to Azure OpenAI with an API key instead of managed identity?
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Yes, you can connect to Azure OpenAI using an API key instead of managed identity. This approach is supported by the Azure OpenAI SDKs and Semantic Kernel.
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Yes, you can connect to Azure OpenAI by using an API key instead of managed identity. The Azure OpenAI SDK and Semantic Kernel support this approach.
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- For details on using API keys with Semantic Kernel: [Semantic Kernel C# Quickstart](/semantic-kernel/get-started/quick-start-guide?pivots=programming-language-python).
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- For details on using API keys with the Azure OpenAI client library: [Quickstart: Get started using chat completions with Azure OpenAI Service](/azure/ai-services/openai/chatgpt-quickstart?pivots=programming-language-python).
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- For details on using API keys with Semantic Kernel, see [Get started with Semantic Kernel](/semantic-kernel/get-started/quick-start-guide?pivots=programming-language-python).
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- For details on using API keys with the Azure OpenAI client library, see [Use the Azure OpenAI Responses API](/azure/ai-services/openai/chatgpt-quickstart?pivots=programming-language-python).
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When working with connection secrets in App Service, you should use [Key Vault references](app-service-key-vault-references.md) instead of storing secrets directly in your codebase. This ensures that sensitive information remains secure and is managed centrally.
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>[!IMPORTANT]
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>When working with connection secrets like API keys in App Service, you should [use Key Vault references](app-service-key-vault-references.md) instead of storing secrets directly in your code. This practice ensures that sensitive information remains secure and is managed centrally.
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---
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### How does DefaultAzureCredential work in this tutorial?
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### How does the DefaultAzureCredential work?
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The `DefaultAzureCredential` simplifies authentication by automatically selecting the best available authentication method:
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The `DefaultAzureCredential` simplifies authentication by automatically selecting the best available authentication method.
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- **During local development**: After you run `az login`, it uses your local Azure CLI credentials.
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- **When deployed to Azure App Service**: It uses the app's managed identity for secure, passwordless authentication.
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- During local development, after you run `az login`, the `DefaultAzureCredential` uses your local Azure CLI credentials.
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- For Azure App Service deployments, the `DefaultAzureCredential` uses the app's managed identity for secure, passwordless authentication.
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This approach lets your code run securely and seamlessly in both local and cloud environments without modification.
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## Next steps
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## Related content
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- [Tutorial: Build a Retrieval Augmented Generation with Azure OpenAI and Azure AI Search (FastAPI)](tutorial-ai-openai-search-nodejs.md)
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- [Tutorial: Run chatbot in App Service with a Phi-4 sidecar extension (FastAPI)](tutorial-ai-slm-fastapi.md)
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- [Tutorial: Run a chatbot in App Service with a Phi-4 sidecar extension (FastAPI)](tutorial-ai-slm-fastapi.md)
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- [Create and deploy an Azure OpenAI Service resource](/azure/ai-services/openai/how-to/create-resource)
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- [Configure Azure App Service](/azure/app-service/configure-common)
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- [Enable managed identity for your app](overview-managed-identity.md)
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- [Use managed identities for App Service and Azure Functions](overview-managed-identity.md)

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