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Team Innovate: Interfaith.ai

This project is a collaboration between SDS Team 5 (Innovate), Being Bridges, and Google, as part of SUTD Service Design Studio 2023 Fall Term.

Team Members

Problem Statement

As a trainer, currently, I have to spend excessive time and effort addressing learner’s repetitive knowledge-based questions in order to move on to skill-based learning.

As a learner, currently, I have to wait till the actual training day in order to ask any questions I may have in order to build enough confidence to move on to skill-based learning.

Solution & Features

Our solution takes on a two-pronged approach:

  1. A by-session FAQ that allows trainers to curate a set of commonly asked questions and answers for students to refer to.
  2. An inter-faith focused chatbot that allows students to get quick answers to their questions.

Relevant Links

Architecture & Design

Installation and Setup

Backend

Prerequisites

  1. Make sure Ruby is installed. You can run ruby --version to check if you have an appropriate version installed. Currently, I'm using 2.7.8
  2. Bundler. Check bundler is installed by bundler -v. I'm using 2.1.4
  3. Postgres should be installed. postgres -V
  4. Rails. rails -v. I'm using 7.0.2.2

Setting up

  1. Clone the repo and cd into this directory
  2. Install the required gems. bundle install
  3. go to config and create the file master.key and get the master key
  4. Set up the database, load the schemas and seed the database. bundle e rails db:setup
  5. Run bundle e rails db:migrate if there are necessary migrations
  6. rails server to start the server

Frontend

Prerequisites

  • Node.js
  • Yarn

Trainer frontend

Installation
  1. cd into the trainer-frontend directory
  2. Run yarn install to install dependencies
  3. Populate the .env files with the required environment variables
  4. Run yarn start to start the development server

Student frontend

Installation
  1. cd into the trainer-frontend directory
  2. Run yarn install to install dependencies
  3. Populate the .env files with the required environment variables
  4. Run yarn start to start the development server

Chat API

Uses flask. Make sure Python is installed.

Installation

  1. cd into the chatbot directory
  2. pip install -r requirements.txt
  3. python main.py

Testing

We have various tests for our frontend and backend.

Backend

Our Rails application is tested using MiniTest, comprising unit and integration tests.

To run the tests, run rails test in the faqapi directory.

To view the test coverage, run open coverage/index.html in the faqapi directory (using SimpleCov)

Frontend

Uses Cypress for component-level unit testing.

To run the tests, run yarn cypress in the trainer-frontend directory.

Chat API

Run pytest in the chatbot directory.

End-to-end

Using Cucumber and Selenium for end-to-end, user acceptance testing.

All our tests and stored in the 'tests' directory.

View all our features at tests/features.

  1. cd into the tests directory
  2. Run yarn to install dependencies
  3. Run yarn cucumber to run the tests, or yarn cucumber --tags @tagname to run tests with a specific tag