Learning project for generating quizzes with LLaMA-2-13B LLM model

This is cut version of google forms

Workflow:

• User can create forms on the editor page
  • Each form assigned unique url
  • For each created form discord text channel created
• Forms can be filled in an editor or on separate page, unique for each form
  • For each submitted response, message sent to corresponding discord channel
• User can look at submitted responses on the editor page
• User can request an AI generated quiz with custom prompt and question count

Project broken into several pieces:

• forms-gen-nest - backend. It is broken into multiple microservices communicating via RabbitMQ
  • forms-gen-nest/apps/forms-rest - service for communicating with clients via rest api. Forwards calls to other services via RabbitMQ
  • forms-gen-nest/apps/forms-db - service responsible for communication with db and creation of forms and responses
• forms-gen-angular - frontend. Pretty straight forward
• ai-service - AI service

• NodeJS
• NestJS
• RabbitMQ
• Postgres
• Prisma
• DiscordJS
• Swagger
• Lodash
• Python
• Transformers

• Angular
• Angular Material UI
• Axios

• Docker Compose
• Ansible

• npm run docker:up

Backend available at localhost:3000

Frontend available at localhost:4200

Swagger available at localhost:3000/api

Postgres available at localhost:5432

RabbitMQ management available at localhost:15672

Backend and frontend launched in hot reload mode, so all changes to codebase will be applied shortly after saving

I haven't done that but you could try running several npm run start*:dev for each service. Don't forget to start RabbitMQ and postgres and pass proper settings.

We tested it on Ubuntu 20.04 with Nvidia Tesla T100

• Setup your Ansible inventory in deployment folder
• Run make deploy-all

You can consider adjusting some env variables to suit your needs

• Updating forms (questionable). What to do with responses then? Delete?
• Since forms rarely changed, caching can be added, reducing number of requests to db service
• Authentication service
• Parallelize answer generation

Thanks goes to these wonderful people (emoji key):

Andrew Lutsai 💻 🚇

Konstantin Grigorev 💻 🚇 📆

Tatiana 💻 🎨

Nikita Fomin 💻 🔬

This project follows the all-contributors specification. Contributions of any kind welcome!