Academic Advising Center Chatbot

In a busy academic advising center of an university, students are frustrated that they need to wait more than one hour to see their advisor.

Using a chatbot, we can save time for both the students and the staff.

Testing the demo

To simply see a live demo of this application, go to this site and use the following credentials to log in:

• Email: [email protected]
• Password: 123

Running the application on your machine

To start the application, you need first have a Postgres database named "1901-gh-stackathon" and another databse named "1901-gh-stackathon." Then, you follow the following steps:

1. Execute npm install or npm i to install all the dependencies
2. Execute npm run seed to fill some dummy data in the database
3. Download the Dialogflow settings file
4. Log in Dialogflow using your Google account, then import the settings file you just downloaded by following this tutorial
5. On the Dialogflow dashboard, click on "Integrations" and enable the "Web Demo." Then, click on the text "Web Demo" which will then show a modal with some code in it. Copy the url inside the <iframe> tag and paste it in the link variable in client/secret.js
6. The first time you run the application or whenever you have changes in your front-end code, you have to use npm run start-dev to start the server. (This command will start the webpack along with the server scripts)
7. Go to localhost:8080 in a browser and log in as one of the user you see in the seed file script/seed.js