QAnswer System Architecture Introduction

Introduction

If you are interested to install QAnswer on premise you need to reach us at info@the-qa-company.com to get a license key and the various access to be able to follow this guide.

Architecture of the application

Here is a diagram explaining the overall architecture of the qanswer application

QAnswer contains the following software components:

• a React3 front-end web-app to allow access and interact with APIs via an intuitive user interface;
• a Spring Boot Java back-end4. This application is serving and securing all APIs;
• a fast API python back-end5 that is responsible for the machine learning functionalities;
• a fast API python back-end that is serving a language model;
• an ElasticSearch instance6;
• a Redis7 server for caching;
• a Selenium8 server to scrape websites;
• a transcription server for speech to text;
• a Postgres9 database that stores user information.

Requirements

To run QAnswer you need:

• a linux distribution (we use Ubuntu by default)
• A GPU with at least 48GB of memory (we recommend NVIDIA® L40S)
• Docker / Podman

(this will allow you to serve 7 to 13 concurrent users depening on RAG or Chat workload, you can contact us at info@the-qa-company.com if you need help sizing your infrastructure)