A Lightweight Interactive Companion for Education

ALICE is a SaaS web application that aims to aid Junior College (JC) or Polytechnic students to plan for their college education and graduation.

This GitHub project contains the code for ALICE. Application Demo: https://dutizh1sabqu4.cloudfront.net

ALICE is architected as a Single-Page-Application, consisting of a React frontend and an API backend.

The frontend is hosted using S3 and distributed with CloudFront. The backend infrastructure consists of API Gateway, several Lambda functions and DynamoDB tables.

The master branch of this project is automatically built and deployed to the live demo.

Frontend deployment: https://dutizh1sabqu4.cloudfront.net

Backend deployment: https://3jqms9dxp6.execute-api.ap-southeast-1.amazonaws.com/Prod

Following tools are required for local builds

• Docker
• AWS CLI (Configure region to ap-southeast-1)
• AWS SAM

Installation Instructions

Run a local instance of DynamoDb in a Docker container at http://localhost:8000

docker network create alice-network
docker run --network alice-network --name dynamodb -d -p 8000:8000 amazon/dynamodb-local

Install the necessary dependencies and return to root directory

cd backend
npm install
cd ../

Create Tables and initialise data ALICE uses two tables, one for courses and one for course popularity tracking

Create table for course 'AliceCourseTable2' and initialise data

aws dynamodb create-table --table-name AliceCourseTable2 --attribute-definitions AttributeName=Id,AttributeType=N --key-schema AttributeName=Id,KeyType=HASH --provisioned-throughput ReadCapacityUnits=2,WriteCapacityUnits=2 --endpoint-url http://localhost:8000

node .\backend\tools\db\initCourseTable.js http://localhost:8000

Create table for popularity 'AliceClicksTable2' and initialise data

aws dynamodb create-table --table-name AliceClicksTable2 --attribute-definitions AttributeName=CourseId,AttributeType=N AttributeName=Clicks,AttributeType=N AttributeName=GsiPk,AttributeType=N --global-secondary-indexes "IndexName=ClicksIndex2,KeySchema=[{AttributeName=GsiPk,KeyType=HASH},{AttributeName=Clicks,KeyType=RANGE}],Projection={ProjectionType=ALL},ProvisionedThroughput={ReadCapacityUnits=2,WriteCapacityUnits=2}" --key-schema AttributeName=CourseId,KeyType=HASH --provisioned-throughput ReadCapacityUnits=2,WriteCapacityUnits=2 --endpoint-url http://localhost:8000

node .\backend\tools\db\initClicksTable.js http://localhost:8000

Verify that data has been loaded:

aws dynamodb scan --table-name AliceClicksTable2 --endpoint-url http://localhost:8000
aws dynamodb scan --table-name AliceCourseTable2 --endpoint-url http://localhost:8000

Run API locally at http://localhost:3001

cd backend
sam local start-api --env-vars env.json -p 3001 --docker-network alice-network --warm-containers EAGER

run frontend locally at http://localhost:3000

cd frontend
npm install
npm start

ALICE uses CloudFormation to deploy its backend resources.

1. Create an S3 bucket to store CloudFormation packages
2. Package backend code

   cd backend
   aws cloudformation package --template template.yml --s3-bucket <YOUR_BUCKET_NAME> --output-template template-export.yml
   

3. Create a new CloudFormation stack using the template file template-export.yml generated in step 2.

Configure the URL for your API in the frontend environment file ./frontend/.env

1. Create an S3 bucket to host frontend site
2. Enable static website hosting on bucket

Build the frontend and upload build files to S3 Bucket

cd frontend
npm build
aws s3 sync ./build <YOUR_BUCKET_NAME> --acl public-read && cd -

1. Access the frontend site. ALICE will guide you through filling in the student profile and provide recommended courses.
2. Manually exercise the APIs. Postman scripts are available in /backend/tools/postman.