CS3219 Project (PeerPrep) - AY2526S1

Group: G05

Note:

• You are required to develop individual microservices within separate folders within this repository.
• The teaching team should be given access to the repositories as we may require viewing the history of the repository in case of any disputes or disagreements.

Table of Contents

• 1. Product Overview
• 2. Project Architecture
• 3. Pre-requisites
• 4. Installation & Setup

1. Product Overview

1.1 Key Features

• Real-time Matchmaking: Users are matched instantly based on chosen difficulty and topics.
• Collaborative Code Editor: Synchronous, low-latency coding environment.

1.2 Product Visualizations

2. Project Architecture

PeerPrep is implemented using a Microservices Architecture to ensure scalability and separation of concerns.

Service	Role	Tech Stack	Port
API Gateway (Nginx)	Routing and Load Balancing	Nginx	80
User Service	Authentication and User Profiles Management	Node/Express, MongoDB	4001
Question Service	Question Repository and Fetching	Node/Express, MongoDB	4002
Matching Service	Queueing, Matchmaking, SSE/WebSockets	Node/Express, Redis	4003
Collaboration Service	Real-time Code Editing and Chatting	Node/Socket.io, Redis	4004

3. Pre-requisites

You must have the following installed to run the project locally:

• Docker Desktop (Required for all services and databases)
• node 22.19.0 (LTS)
• pnpm (Package manager for monorepo workspaces)

4. Installation and Setup [Local Development]

4.1 Clone Repository

git clone https://github.com/CS3219-AY2526Sem1/cs3219-ay2526s1-project-g05.git peerprep

All commands below assume you are in the root folder /

4.2 Install Dependencies

cd frontend
pnpm install

cd backend
pnpm -r install

4.3 Setup Docker Containers

This command will set up the foundational database containers (MongoDB and Redis).

docker-compose -f docker-compose-local.yml up -d

4.4 Create .env for backend

cd backend
cp .env.example .env

• Remember to edit the OPENAI_API_KEY variable to use AI features

4.5 Start the Frontend and Backend

cd frontend
pnpm run dev

cd backend
pnpm run dev

4.6 Seed Data

• This seeds dummy data and creates a test account that you can try out!

cd backend/db_management
pnpm run seed

4.7 Test it out!

• The site is now available at http://localhost:5173

  • You can try it out with this test seed account:

  • email: [email protected]
    password: Testing123!
    

5. Production Deployment

5.1 Pre-requisites

• Docker Desktop/Docker Engine

5.2 Clone Repository

git clone https://github.com/CS3219-AY2526Sem1/cs3219-ay2526s1-project-g05.git peerprep

All commands below assume you are in the root / folder.

5.3 Copy .env.prod file for backend

cd backend
cp .env.prod.example .env.prod

• Remember to edit the OPENAI_API_KEY variable to use AI features

5.4 Build Containers and Run

docker-compose up -d --build --scale peerprep_user_service=2 --scale peerprep_question_service=2 --scale peerprep_code_execution_service=2

• This spawns 2 user_service, question_service and code_execution_service containers for load-balancing
  • matching_service currently does not support load-balancing

5.5 Seed the Database

cd backend/db_management
pnpm run seed:prod

5.6 Test Deployment!

• The site should now be available at http://localhost:5173

AI Use Summary

Tools Used: ChatGPT (GPT‑5 Thinking), GitHub Copilot

In general, AI tools were used to:

• Generate boilerplate code for backend Express server.
• Auto-complete functions the author was already programming.
• Debug programming errors as they came up.
• Suggest implementation approaches on how to incoporate different technolgies to the codebase.