This repo contains sample code for a simple chat webapp that integrates with Azure OpenAI. Note: some portions of the app use preview APIs.

• An existing Azure OpenAI resource and model deployment of a chat model (e.g. gpt-35-turbo-16k, gpt-4)
• To use Azure OpenAI on your data: one of the following data sources:
  • Azure AI Search Index
  • Azure CosmosDB Mongo vCore vector index
  • Elasticsearch index (preview)
  • Pinecone index (preview)
  • AzureML index (preview)

Please see README_azd.md for detailed instructions.

Click on the Deploy to Azure button and configure your settings in the Azure Portal as described in the Environment variables section.

Please see the section below for important information about adding authentication to your app.

1. Copy .env.sample to a new file called .env and configure the settings as described in the Environment variables section.

   These variables are required:

   • AZURE_OPENAI_RESOURCE
   • AZURE_OPENAI_MODEL
   • AZURE_OPENAI_KEY

   These variables are optional:

   • AZURE_OPENAI_TEMPERATURE
   • AZURE_OPENAI_TOP_P
   • AZURE_OPENAI_MAX_TOKENS
   • AZURE_OPENAI_STOP_SEQUENCE
   • AZURE_OPENAI_SYSTEM_MESSAGE

   See the documentation for more information on these parameters.

2. Start the app with start.cmd. This will build the frontend, install backend dependencies, and then start the app. Or, just run the backend in debug mode using the VSCode debug configuration in .vscode/launch.json.

3. You can see the local running app at http://127.0.0.1:50505.

More information about Azure OpenAI on your data

1. Update the AZURE_OPENAI_* environment variables as described above.

2. To connect to your data, you need to specify an Azure Cognitive Search index to use. You can create this index yourself or use the Azure AI Studio to create the index for you.

   These variables are required when adding your data with Azure AI Search:

   • AZURE_SEARCH_SERVICE
   • AZURE_SEARCH_INDEX
   • AZURE_SEARCH_KEY

   These variables are optional:

   • AZURE_SEARCH_USE_SEMANTIC_SEARCH
   • AZURE_SEARCH_SEMANTIC_SEARCH_CONFIG
   • AZURE_SEARCH_INDEX_TOP_K
   • AZURE_SEARCH_ENABLE_IN_DOMAIN
   • AZURE_SEARCH_CONTENT_COLUMNS
   • AZURE_SEARCH_FILENAME_COLUMN
   • AZURE_SEARCH_TITLE_COLUMN
   • AZURE_SEARCH_URL_COLUMN
   • AZURE_SEARCH_VECTOR_COLUMNS
   • AZURE_SEARCH_QUERY_TYPE
   • AZURE_SEARCH_PERMITTED_GROUPS_COLUMN
   • AZURE_SEARCH_STRICTNESS
   • AZURE_OPENAI_EMBEDDING_NAME

3. Start the app with start.cmd. This will build the frontend, install backend dependencies, and then start the app. Or, just run the backend in debug mode using the VSCode debug configuration in .vscode/launch.json.

4. You can see the local running app at http://127.0.0.1:50505.

To enable chat history, you will need to set up CosmosDB resources. The ARM template in the infrastructure folder can be used to deploy an app service and a CosmosDB with the database and container configured. Then specify these additional environment variables:

• AZURE_COSMOSDB_ACCOUNT
• AZURE_COSMOSDB_DATABASE
• AZURE_COSMOSDB_CONVERSATIONS_CONTAINER
• AZURE_COSMOSDB_ACCOUNT_KEY

As above, start the app with start.cmd, then visit the local running app at http://127.0.0.1:50505. Or, just run the backend in debug mode using the VSCode debug configuration in .vscode/launch.json.

To enable message feedback, you will need to set up CosmosDB resources. Then specify these additional environment variable:

/.env

• AZURE_COSMOSDB_ENABLE_FEEDBACK=True

NOTE: If you've made code changes, be sure to build the app code with start.cmd or start.sh before you deploy, otherwise your changes will not be picked up. If you've updated any files in the frontend folder, make sure you see updates to the files in the static folder before you deploy.

You can use the Azure CLI to deploy the app from your local machine. Make sure you have version 2.48.1 or later.

If this is your first time deploying the app, you can use az webapp up. Run the following two commands from the root folder of the repo, updating the placeholder values to your desired app name, resource group, location, and subscription. You can also change the SKU if desired.

1. az webapp up --runtime PYTHON:3.11 --sku B1 --name <new-app-name> --resource-group <resource-group-name> --location <azure-region> --subscription <subscription-name>
2. az webapp config set --startup-file "python3 -m gunicorn app:app" --name <new-app-name>

If you've deployed the app previously, first run this command to update the appsettings to allow local code deployment:

az webapp config appsettings set -g <resource-group-name> -n <existing-app-name> --settings WEBSITE_WEBDEPLOY_USE_SCM=false

Check the runtime stack for your app by viewing the app service resource in the Azure Portal. If it shows "Python - 3.10", use PYTHON:3.10 in the runtime argument below. If it shows "Python - 3.11", use PYTHON:3.11 in the runtime argument below.

Check the SKU in the same way. Use the abbreviated SKU name in the argument below, e.g. for "Basic (B1)" the SKU is B1.

Then, use these commands to deploy your local code to the existing app:

1. az webapp up --runtime <runtime-stack> --sku <sku> --name <existing-app-name> --resource-group <resource-group-name>
2. az webapp config set --startup-file "python3 -m gunicorn app:app" --name <existing-app-name>

Make sure that the app name and resource group match exactly for the app that was previously deployed.

Deployment will take several minutes. When it completes, you should be able to navigate to your app at {app-name}.azurewebsites.net.

After deployment, you will need to add an identity provider to provide authentication support in your app. See this tutorial for more information.

If you don't add an identity provider, the chat functionality of your app will be blocked to prevent unauthorized access to your resources and data.

To remove this restriction, you can add AUTH_ENABLED=False to the environment variables. This will disable authentication and allow anyone to access the chat functionality of your app. This is not recommended for production apps.

To add further access controls, update the logic in getUserInfoList in frontend/src/pages/chat/Chat.tsx.

The interface allows for easy adaptation of the UI by modifying certain elements, such as the title and logo, through the use of environment variables.

• UI_TITLE
• UI_LOGO
• UI_CHAT_TITLE
• UI_CHAT_LOGO
• UI_CHAT_DESCRIPTION
• UI_FAVICON
• UI_SHOW_SHARE_BUTTON

Feel free to fork this repository and make your own modifications to the UX or backend logic. You can modify the source (frontend/src). For example, you may want to change aspects of the chat display, or expose some of the settings in app.py in the UI for users to try out different behaviors. After your code changes, you will need to rebuild the front-end via start.sh or start.cmd.

You can configure the number of threads and workers in gunicorn.conf.py. After making a change, redeploy your app using the commands listed above.

See the Oryx documentation for more details on these settings.

First, add an environment variable on the app service resource called "DEBUG". Set this to "true".

Next, enable logging on the app service. Go to "App Service logs" under Monitoring, and change Application logging to File System. Save the change.

Now, you should be able to see logs from your app by viewing "Log stream" under Monitoring.

When using your own data with a vector index, ensure these settings are configured on your app:

• AZURE_SEARCH_QUERY_TYPE: can be vector, vectorSimpleHybrid, or vectorSemanticHybrid,
• AZURE_OPENAI_EMBEDDING_NAME: the name of your Ada (text-embedding-ada-002) model deployment on your Azure OpenAI resource.
• AZURE_SEARCH_VECTOR_COLUMNS: the vector columns in your index to use when searching. Join them with | like contentVector|titleVector.

The Citation panel is defined at the end of frontend/src/pages/chat/Chat.tsx. The citations returned from Azure OpenAI On Your Data will include content, title, filepath, and in some cases url. You can customize the Citation section to use and display these as you like. For example, the title element is a clickable hyperlink if url is not a blob URL.

    <h5 
        className={styles.citationPanelTitle} 
        tabIndex={0} 
        title={activeCitation.url && !activeCitation.url.includes("blob.core") ? activeCitation.url : activeCitation.title ?? ""} 
        onClick={() => onViewSource(activeCitation)}
    >{activeCitation.title}</h5>

    const onViewSource = (citation: Citation) => {
        if (citation.url && !citation.url.includes("blob.core")) {
            window.open(citation.url, "_blank");
        }
    };

We recommend keeping these best practices in mind:

• Reset the chat session (clear chat) if the user changes any settings. Notify the user that their chat history will be lost.
• Clearly communicate to the user what impact each setting will have on their experience.
• When you rotate API keys for your AOAI or ACS resource, be sure to update the app settings for each of your deployed apps to use the new key.
• Pull in changes from main frequently to ensure you have the latest bug fixes and improvements, especially when using Azure OpenAI on your data.

A note on Azure OpenAI API versions: The application code in this repo will implement the request and response contracts for the most recent preview API version supported for Azure OpenAI. To keep your application up-to-date as the Azure OpenAI API evolves with time, be sure to merge the latest API version update into your own application code and redeploy using the methods described in this document.

Note: settings starting with AZURE_SEARCH are only needed when using Azure OpenAI on your data with Azure AI Search. If not connecting to your data, you only need to specify AZURE_OPENAI settings.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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