RAG chat: Setting up optional login and document level access control

The azure-search-openai-demo project can set up a full RAG chat app on Azure AI Search and OpenAI so that you can chat on custom data, like internal enterprise data or domain-specific knowledge sets. For full instructions on setting up the project, consult the main README, and then return here for detailed instructions on configuring login and access control.

Requirements

IMPORTANT: In order to add optional login and document level access control, you'll need the following in addition to the normal sample requirements

Azure account permissions: Your Azure account must have permission to manage applications in Microsoft Entra.

Setting up Microsoft Entra applications

Two Microsoft Entra applications must be registered in order to make the optional login and document level access control system work correctly. One app is for the client UI. The client UI is implemented as a single page application. The other app is for the API server. The API server uses a confidential client to call the Microsoft Graph API.

Automatic Setup

The easiest way to setup the two apps is to use the azd CLI. We've written scripts that will automatically create the two apps and configure them for use with the sample. To trigger the automatic setup, run the following commands:

Run azd env set AZURE_USE_AUTHENTICATION true to enable the login UI and use App Service authentication by default.
Ensure access control is enabled on your search index. If your index doesn't exist yet, run prepdocs with AZURE_USE_AUTHENTICATION set to true. If your index already exists, run python ./scripts/manageacl.py --acl-action enable_acls.
(Optional) To require access control when using the app, run azd env set AZURE_ENFORCE_ACCESS_CONTROL true. Authentication is always required to search on documents with access control assigned, regardless of if unauthenticated access is enabled or not.
(Optional) To allow authenticated users to search on documents that have no access controls assigned, even when access control is required, run azd env set AZURE_ENABLE_GLOBAL_DOCUMENT_ACCESS true.
(Optional) To allow unauthenticated users to use the app, even when access control is enforced, run azd env set AZURE_ENABLE_UNAUTHENTICATED_ACCESS true. AZURE_ENABLE_GLOBAL_DOCUMENT_ACCESS should also be set to true if you want unauthenticated users to be able to search on documents with no access control.
Run azd env set AZURE_AUTH_TENANT_ID <YOUR-TENANT-ID> to set the tenant ID associated with authentication.
If your auth tenant ID is different from your currently logged in tenant ID, run azd auth login --tenant-id <YOUR-TENANT-ID> to login to the authentication tenant simultaneously.
Run azd up to deploy the app.

Manual Setup

The following instructions explain how to setup the two apps using the Azure Portal.

Server App

Sign in to the Azure portal.
Select the Microsoft Entra ID service.
In the left hand menu, select Application Registrations.
Select New Registration.
- In the Name section, enter a meaningful application name. This name will be displayed to users of the app, for example Azure Search OpenAI Chat API.
- Under Supported account types, select Accounts in this organizational directory only.
Select Register to create the application
In the app's registration screen, find the Application (client) ID.
- Run the following azd command to save this ID: azd env set AZURE_SERVER_APP_ID <Application (client) ID>.
Microsoft Entra supports three types of credentials to authenticate an app using the client credentials: passwords (app secrets), certificates, and federated identity credentials. For a higher level of security, either certificates or federated identity credentials are recommended. This sample currently uses an app secret for ease of provisioning.
Select Certificates & secrets in the left hand menu.
In the Client secrets section, select New client secret.
- Type a description, for example Azure Search OpenAI Chat Key.
- Select one of the available key durations.
- The generated key value will be displayed after you select Add.
- Copy the generated key value and run the following azd command to save this ID: azd env set AZURE_SERVER_APP_SECRET <generated key value>.
Select API Permissions in the left hand menu. By default, the delegated User.Read permission should be present. This permission is required to read the signed-in user's profile to get the security information used for document level access control. If this permission is not present, it needs to be added to the application.
- Select Add a permission, and then Microsoft Graph.
- Select Delegated permissions.
- Search for and and select User.Read.
- Select Add permissions.
Select Expose an API in the left hand menu. The server app works by using the On Behalf Of Flow, which requires the server app to expose at least 1 API.
- The application must define a URI to expose APIs. Select Add next to Application ID URI.
  - By default, the Application ID URI is set to api://<application client id>. Accept the default by selecting Save.
- Under Scopes defined by this API, select Add a scope.
- Fill in the values as indicated:
  - For Scope name, use access_as_user.
  - For Who can consent?, select Admins and users.
  - For Admin consent display name, type Access Azure Search OpenAI Chat API.
  - For Admin consent description, type Allows the app to access Azure Search OpenAI Chat API as the signed-in user..
  - For User consent display name, type Access Azure Search OpenAI Chat API.
  - For User consent description, type Allow the app to access Azure Search OpenAI Chat API on your behalf.
  - Leave State set to Enabled.
  - Select Add scope at the bottom to save the scope.
(Optional) Enable group claims. Include which Microsoft Entra groups the user is part of as part of the login in the optional claims. The groups are used for optional security filtering in the search results.
- In the left hand menu, select Token configuration
- Under Optional claims, select Add groups claim
- Select which group types to include in the claim. Note that a overage claim will be emitted if the user is part of too many groups. In this case, the API server will use the Microsoft Graph to list the groups the user is part of instead of relying on the groups in the claim.
- Select Add to save your changes

Client App

Sign in to the Azure portal.
Select the Microsoft Entra ID service.
In the left hand menu, select Application Registrations.
Select New Registration.
- In the Name section, enter a meaningful application name. This name will be displayed to users of the app, for example Azure Search OpenAI Chat Web App.
- Under Supported account types, select Accounts in this organizational directory only.
- Under Redirect URI (optional) section, select Single-page application (SPA) in the combo-box and enter the following redirect URI:
  - If you are running the sample locally, add the endpoints http://localhost:50505/redirect and http://localhost:5173/redirect
  - If you are running the sample on Azure, add the endpoints provided by azd up: https://<your-endpoint>.azurewebsites.net/redirect.
  - If you are running the sample from Github Codespaces, add the Codespaces endpoint: https://<your-codespace>-50505.app.github.dev/redirect
Select Register to create the application
In the app's registration screen, find the Application (client) ID.
- Run the following azd command to save this ID: azd env set AZURE_CLIENT_APP_ID <Application (client) ID>.
In the left hand menu, select Authentication.
- Under Web, add a redirect URI with the endpoint provided by azd up: https://<your-endpoint>.azurewebsites.net/.auth/login/aad/callback.
- Under Implicit grant and hybrid flows, select ID Tokens (used for implicit and hybrid flows)
- Select Save
In the left hand menu, select API permissions. You will add permission to access the access_as_user API on the server app. This permission is required for the On Behalf Of Flow to work.
- Select Add a permission, and then My APIs.
- In the list of applications, select your server application Azure Search OpenAI Chat API
- Ensure Delegated permissions is selected.
- In the Select permissions section, select the access_as_user permission
- Select Add permissions.
Stay in the API permissions section and select Add a permission.
- Select Microsoft Graph.
- Select Delegated permissions.
- Search for and select User.Read.
- Select Add permissions.

Configure Server App Known Client Applications

Consent from the user must be obtained for use of the client and server app. The client app can prompt the user for consent through a dialog when they log in. The server app has no ability to show a dialog for consent. Client apps can be added to the list of known clients to access the server app, so a consent dialog is shown for the server app.

Navigate to the server app registration
In the left hand menu, select Manifest
Replace "knownClientApplications": [] with "knownClientApplications": ["<client application id>"]
Select Save

Testing

If you are running setup for the first time, ensure you have run azd env set AZURE_ADLS_GEN2_STORAGE_ACCOUNT <YOUR-STORAGE_ACCOUNT> before running azd up. If you do not set this environment variable, your index will not be initialized with access control support when prepdocs is run for the first time. To manually enable access control in your index, use the manual setup script.

Ensure you run azd env set AZURE_USE_AUTHENTICATION to enable the login UI once you have setup the two Microsoft Entra apps before you deploy or run the application. The login UI will not appear unless all required environment variables have been setup.

In both the chat and ask a question modes, under Developer settings optional Use oid security filter and Use groups security filter checkboxes will appear. The oid (User ID) filter maps to the oids field in the search index and the groups (Group ID) filter maps to the groups field in the search index. If AZURE_ENFORCE_ACCESS_CONTROL has been set, then both the Use oid security filter and Use groups security filter options are always enabled and cannot be disabled.

Programmatic Access with Authentication

If you want to use the chat endpoint without the UI and still use authentication, you must disable App Service built-in authentication and use only the app's MSAL-based authentication flow. Ensure the AZURE_DISABLE_APP_SERVICES_AUTHENTICATION environment variable is set before deploying.

Get an access token that can be used for calling the chat API using the following code:

from azure.identity import DefaultAzureCredential
import os

token = DefaultAzureCredential().get_token(f"api://{os.environ['AZURE_SERVER_APP_ID']}/access_as_user", tenant_id=os.getenv('AZURE_AUTH_TENANT_ID', os.getenv('AZURE_TENANT_ID')))

print(token.token)

Troubleshooting

If your primary tenant restricts the ability to create Entra applications, you'll need to use a separate tenant to create the Entra applications. You can create a new tenant by following these instructions. Then run azd env set AZURE_AUTH_TENANT_ID <YOUR-AUTH-TENANT-ID> before running azd up.
If any Entra apps need to be recreated, you can avoid redeploying the app by changing the app settings in the portal. Any of the required environment variables can be changed. Once the environment variables have been changed, restart the web app.
It's possible a consent dialog will not appear when you log into the app for the first time. If this consent dialog doesn't appear, you will be unable to use the security filters because the API server app does not have permission to read your authorization information. A consent dialog can be forced to appear by adding "prompt": "consent" to the loginRequest property in authentication.py
It's possible that your tenant admin has placed a restriction on consent to apps with unverified publishers. In this case, only admins may consent to the client and server apps, and normal user accounts are unable to use the login system until the admin consents on behalf of the entire organization.
It's possible that your tenant admin requires admin approval of all new apps. Regardless of whether you select the delegated or admin permissions, the app will not work without tenant admin consent. See this guide for granting consent to an app.

Adding data with document level access control

The sample supports 2 main strategies for adding data with document level access control.

Using the Add Documents API. Sample scripts are provided which use the Azure AI Search Service Add Documents API to directly manage access control information on existing documents in the index.
Using prepdocs and Azure Data Lake Storage Gen 2. Sample scripts are provided which set up an Azure Data Lake Storage Gen 2 account, set the access control information on files and folders stored there, and ingest those documents into the search index with their access control information.

Using the Add Documents API

Manually enable document level access control on a search index and manually set access control values using the manageacl.py script.

Prior to running the script:

Run azd up or use azd env set to manually set the AZURE_SEARCH_SERVICE and AZURE_SEARCH_INDEX azd environment variables
Activate the Python virtual environment for your shell session

The script supports the following commands. All commands support -v for verbose logging.

python ./scripts/manageacl.py --acl-action enable_acls: Creates the required oids (User ID) and groups (Group IDs) security filter fields for document level access control on your index, as well as the storageUrl field for storing the Blob storage URL. Does nothing if these fields already exist.

Example usage:
```
python ./scripts/manageacl.py -v --acl-action enable_acls
```
python ./scripts/manageacl.py --acl-type [oids or groups]--acl-action view --url [https://url.pdf]: Prints access control values associated with either User IDs or Group IDs for the document at the specified URL.

Example to view all Group IDs:
```
python ./scripts/manageacl.py -v --acl-type groups --acl-action view --url https://st12345.blob.core.windows.net/content/Benefit_Options.pdf
```
python ./scripts/manageacl.py --acl-type [oids or groups]--acl-action add --acl [ID of group or user] --url [https://url.pdf]: Adds an access control value associated with either User IDs or Group IDs for the document at the specified URL.

Example to add a Group ID:
```
python ./scripts/manageacl.py -v --acl-type groups --acl-action add --acl xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx --url https://st12345.blob.core.windows.net/content/Benefit_Options.pdf
```
python ./scripts/manageacl.py --acl-type [oids or groups]--acl-action remove_all --url [https://url.pdf]: Removes all access control values associated with either User IDs or Group IDs for a specific document.

Example to remove all Group IDs:
```
python ./scripts/manageacl.py -v --acl-type groups --acl-action remove_all --url https://st12345.blob.core.windows.net/content/Benefit_Options.pdf
```
python ./scripts/manageacl.py --url [https://url.pdf] --acl-type [oids or groups]--acl-action remove --acl [ID of group or user]: Removes an access control value associated with either User IDs or Group IDs for a specific document.

Example to remove a specific User ID:
```
python ./scripts/manageacl.py -v --acl-type oids --acl-action remove --acl xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx --url https://st12345.blob.core.windows.net/content/Benefit_Options.pdf
```

Azure Data Lake Storage Gen2 Setup

Azure Data Lake Storage Gen2 implements an access control model that can be used for document level access control. The adlsgen2setup.py script uploads the sample data included in the data folder to a Data Lake Storage Gen2 storage account. The Storage Blob Data Owner role is required to use the script.

In order to use this script, an existing Data Lake Storage Gen2 storage account is required. Run azd env set AZURE_ADLS_GEN2_STORAGE_ACCOUNT <your-storage-account> prior to running the script.

Then run the script inside your Python environment:

python /scripts/adlsgen2setup.py './data/*' --data-access-control './scripts/sampleacls.json' -v

The script performs the following steps:

Creates example groups listed in the sampleacls.json file.
Creates a filesystem / container gptkbcontainer in the storage account.
Creates the directories listed in the sampleacls.json file.
Uploads the sample PDFs referenced in the sampleacls.json file into the appropriate directories.
Recursively sets Access Control Lists (ACLs) using the information from the sampleacls.json file.

In order to use the sample access control, you need to join these groups in your Microsoft Entra tenant.

Note that this optional script may not work in Codespaces if your administrator has applied a Conditional Access policy to your tenant.

Azure Data Lake Storage Gen2 Prep Docs

Once a Data Lake Storage Gen2 storage account has been setup with sample data and access control lists, prepdocs.py can be used to automatically process PDFs in the storage account and store them with their access control lists in the search index.

To run this script with a Data Lake Storage Gen2 account, first set the following environment variables:

AZURE_ADLS_GEN2_STORAGE_ACCOUNT: Name of existing Data Lake Storage Gen2 storage account.
(Optional) AZURE_ADLS_GEN2_FILESYSTEM: Name of existing Data Lake Storage Gen2 filesystem / container in the storage account. If empty, gptkbcontainer is used.
(Optional) AZURE_ADLS_GEN2_FILESYSTEM_PATH: Specific path in the Data Lake Storage Gen2 filesystem / container to process. Only PDFs contained in this path will be processed.

Once the environment variables are set, run the script using the following command: /scripts/prepdocs.ps1 or /scripts/prepdocs.sh.

Environment variables reference

The following environment variables are used to setup the optional login and document level access control:

AZURE_USE_AUTHENTICATION: Enables Entra ID login and document level access control. Set to true before running azd up.
AZURE_ENFORCE_ACCESS_CONTROL: Enforces Entra ID based login and document level access control on documents with access control assigned. Set to true before running azd up. If AZURE_ENFORCE_ACCESS_CONTROL is enabled and AZURE_ENABLE_UNAUTHENTICATED_ACCESS is not enabled, then authentication is required to use the app.
AZURE_ENABLE_GLOBAL_DOCUMENT_ACCESS: Allows users to search on documents that have no access controls assigned
AZURE_ENABLE_UNAUTHENTICATED_ACCESS: Allows unauthenticated users to access the chat app, even when AZURE_ENFORCE_ACCESS_CONTROL is enabled. AZURE_ENABLE_GLOBAL_DOCUMENT_ACCESS should be set to true to allow unauthenticated users to search on documents that have no access control assigned. Unauthenticated users cannot search on documents with access control assigned.
AZURE_DISABLE_APP_SERVICES_AUTHENTICATION: Disables use of built-in authentication for App Services. An authentication flow based on the MSAL SDKs is used instead. Useful when you want to provide programmatic access to the chat endpoints with authentication.
AZURE_SERVER_APP_ID: (Required) Application ID of the Microsoft Entra app for the API server.
AZURE_SERVER_APP_SECRET: Client secret used by the API server to authenticate using the Microsoft Entra server app.
AZURE_CLIENT_APP_ID: Application ID of the Microsoft Entra app for the client UI.
AZURE_AUTH_TENANT_ID: Tenant ID associated with the Microsoft Entra tenant used for login and document level access control. Defaults to AZURE_TENANT_ID if not defined.
AZURE_ADLS_GEN2_STORAGE_ACCOUNT: (Optional) Name of existing Data Lake Storage Gen2 storage account for storing sample data with access control lists. Only used with the optional Data Lake Storage Gen2 setup and prep docs scripts.
AZURE_ADLS_GEN2_FILESYSTEM: (Optional) Name of existing Data Lake Storage Gen2 filesystem for storing sample data with access control lists. Only used with the optional Data Lake Storage Gen2 setup and prep docs scripts.
AZURE_ADLS_GEN2_FILESYSTEM_PATH: (Optional) Name of existing path in a Data Lake Storage Gen2 filesystem for storing sample data with access control lists. Only used with the optional Data Lake Storage Gen2 prep docs script.

Authentication behavior by environment

This application uses an in-memory token cache. User sessions are only available in memory while the application is running. When the application server is restarted, all users will need to log-in again.

The following table describes the impact of the AZURE_USE_AUTHENTICATION and AZURE_ENFORCE_ACCESS_CONTROL variables depending on the environment you are deploying the application in:

AZURE_USE_AUTHENTICATION	AZURE_ENFORCE_ACCESS_CONTROL	Environment	Default Behavior
True	False	App Services	Use integrated auth Login page blocks access to app User can opt-into access control in developer settings Allows unrestricted access to sources
True	True	App Services	Use integrated auth Login page blocks access to app User must use access control
True	False	Local or Codespaces	Do not use integrated auth Can use app without login User can opt-into access control in developer settings Allows unrestricted access to sources
True	True	Local or Codespaces	Do not use integrated auth Cannot use app without login Behavior is chat box is greyed out with default “Please login message” User must use login button to make chat box usable User must use access control when logged in
False	False	All	No login or access control
False	True	All	Invalid setting

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login_and_acl.md

login_and_acl.md

RAG chat: Setting up optional login and document level access control

Table of Contents

Requirements

Setting up Microsoft Entra applications

Automatic Setup

Manual Setup

Server App

Client App

Configure Server App Known Client Applications

Testing

Programmatic Access with Authentication

Troubleshooting

Adding data with document level access control

Using the Add Documents API

Azure Data Lake Storage Gen2 Setup

Azure Data Lake Storage Gen2 Prep Docs

Environment variables reference

Authentication behavior by environment

Files

login_and_acl.md

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History

login_and_acl.md

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RAG chat: Setting up optional login and document level access control

Table of Contents

Requirements

Setting up Microsoft Entra applications

Automatic Setup

Manual Setup

Server App

Client App

Configure Server App Known Client Applications

Testing

Programmatic Access with Authentication

Troubleshooting

Adding data with document level access control

Using the Add Documents API

Azure Data Lake Storage Gen2 Setup

Azure Data Lake Storage Gen2 Prep Docs

Environment variables reference

Authentication behavior by environment