New Jersey AI Assistant

This document has information specific to the NJ-specific fork of the Microsoft open source OpenAI chat app.

For information from Microsoft on the sample chat app please visit the Sample App README

Overall architecture

• This full-stack application uses a Python web server, React frontend, and is deployed on Azure App Service
• This code is deployed to a production stage (nj-stable branch) and dev stage (nj-stable-dev branch)
• Note that certain features from the open-source parent are not enabled, such as chat history (anything related to CosmosDB)

About our LLM Model

Last updated 10/20/2025.

The NJ AI assistant uses the Azure OpenAI Service resource to provide REST API access to an OpenAI model. The frontend makes requests to this API to generate the chat completions.

Models can be configured by going to the Azure AI Foundry portal and accessing the Azure OpenAI Service resource which houses a given model deployment.

OpenAI Service resources

For both our prod and dev environments, we have a default OpenAI resources deployed in the eastus region as well as identical fallback resources deployed in the northcentralus region. Both the default and fallback resources can be found in the Azure AI portal.

Prod OpenAI Service

• Resource: nj-innovation-ai
• Model deployment name: gpt-4o-prod
  • Model name: gpt-4o
  • Content filter: input-low-allowed
  • Version update policy: Once the current version expires

Dev OpenAI Service

• Resource: nj-innovation-ai-dev
• Model deployment name: gpt-4o-dev
  • Model name: gpt-4o
  • Content filter: input-low-allowed-dev
  • Version update policy: Once a new default version is available

Using and configuring models

See the docs on Managing models in Azure OpenAI services.

Contributing to the NJ AI Assistant

• To contribute to the NJ AI assistant, create a feature branch from the nj-stable-dev branch of the newjersey/nj-ai-assistant repository. Add changes to the feature branch then open a PR to have it merged into the nj-stable-dev branch. When merging changes to the nj-stable-dev branch, the "Squash and merge" option is preferred".
• Deploy and preview changes on the dev site by following the steps in the "Deployment" section below.
• After previewing changes on the dev site, open a PR to merge changes from nj-stable-dev to nj-stable. When merging changes to the nj-stable branch, merging without squashing is preferred.

Local setup

1. Clone repo and go to nj-stable branch
2. Copy .env file from Bitwarden (reach out to Platform team for access)
3. Ensure that you have python version 3.11 installed locally.
4. Run ./start.sh

Deployment

1. Log into Azure and go to the nj-aichat-internal App Service (reach out to Platform team for access)
2. [If dev stage] In the left menu, click Deployments > Deployment slots. Click on nj-aichat-internal-dev.
3. In the left menu, click Deployments > Deployment Center.
4. In the top bar, click the "Sync" button to sync the deployed application with the latest commit on the corresponding branch.
5. Under the top bar, click the "Logs" tab to see the deployment status (it will change to "Success" when completed)

Updating site copy

The site title and copy that appear in the background of the NJ AI assistant are stored in the environment variables.

The site title is stored as UI_CHAT_TITLE while the site copy is in Chat.tsx.

To update the title or copy when running locally, please update the variables in your .env file. Make sure to save the updated changes to the .env file stored in Bitwarden as well.

To update the title or copy in dev or prod, you will need to make updates in the Azure console:

1. Open the resource in Azure
2. Expand the "Settings" dropdown in the lefthand panel
3. Open the "Environment variables" screen. From here you will be able to find and update the relevant environment variables.
4. When you have finished making updates, click the blue "Apply" button in the bottom lefthand corner of the screen.

How to run locally

1. Clone the repo and check out the nj-stable branch or any branch created from it.
2. In the root directory of the repo, create a new .env file. Update this file with the values found in Bitwarden.
3. From the root directory of the repo, run the ./start.sh command

How to run unit tests locally

Navigate into the frontend directory. cd frontend

To run tests for the backend run the command npm run test:api To run tests for the frontend run the command npm run test:react

Additional Documentation

See other files within this repo for in-depth documentation on specific code, infrastructure, and practices:

Azure

• Alerts in Azure
• Managing models in Azure OpenAI services