Loobot

Chatbot interface for university of Waterloo Open Data API with Natural Language Processing!

How does it work?

Overall

1. User sends a message to Mr. Goose on Facebook
2. Facebook POSTs our /webhook/ endpoint with the message and an unique User ID.
3. We extract the message and the User ID from the payload (logics in /src/server.js)
4. We feed the message and the User ID to the respond function (/src/response/respond) then the respond function returns a smart response.
5. We send the response along with the User ID back to Facebook
6. Message shows up on Facebook Messenger

It seems that the respond function has a bunch of responsability! Let's break it down

Respond :: id -> message -> response

Note: We need sessions or maybe even a DB to track each user's activity. For example, we only want to ask our user's name once.

1. A singleton that represents our chatbot's state will be instantiated when the server starts
2. When respond function is called with an id and a message, we use the id to find if there already exits a session. Else we create a new session. Each session will be an object that stores the information of this particular user
3. Along with information from session, we use natural, a nodejs natural language processing library to find out what does the user want. We will have this logics in a seperate function, let's call it decide for now. decide will dispatch an action (similar to flux right 😉)
4. Our action (can be async. eg. make a call to uwaterloo endpoint) will get necessary data, format message then send it back to Facebook (essentially another action).

Think it is confusing af? I totally agree

Credits

Inspired by icechen1's uwgoosebot

Why this project? Why duplicate the effort?

• Loobot does not use any proprietary third-party SaaS platform for AI or NLP.