This repository is deprecated and no longer actively maintained. It contains outdated code examples or practices that do not align with current MongoDB best practices. While the repository remains accessible for reference purposes, we strongly discourage its use in production environments. Users should be aware that this repository will not receive any further updates, bug fixes, or security patches. This code may expose you to security vulnerabilities, compatibility issues with current MongoDB versions, and potential performance problems. Any implementation based on this repository is at the user's own risk. For up-to-date resources, please refer to the MongoDB Developer Center.
- (install express) open a terminal in the folder and run - npm install express
- Add additional npm installs for what is missing in app.js
- run - npm i cors
- run - npm i express http-proxy-middleware
- run - npm i express morgan
- Pay attention to the rewrite rules in app.js and update for your MongoDB Atlas and Confluent Cloud Environments
- (add your api keys) edit the
api.jsoninside the uncompressed folder and replace the emoji with your key - When running the app.js at http://localhost:3000 press the "Open Settings" button and add in your D-ID and Open AI API keys.
- (bring up the app) in the folder (ctr left click on folder through finder) open the terminal run node app.js
- You should see this message - server started on port localhost:3000
- (open the app) in the browser add localhost:3000
- (connect) press connect you should see the connection ready
- (stream) press the start button to start streaming
Node Tutorial
Python Tutorial
MongoDB & Confluent Partner Blog
Github for back end QNA microservice that performs the Vector search in MongoDB Atlas and returns the results to the digital assistant app is here:
Backend QNA Service

