Youtube Trending Slackbot

Summary

This project is an experiment in using Markov chains to generate natural language for a slack bot, based on comments from youtube trending videos.

This project is setup as multiple smaller node micro services:

• Markov library

  • A standalone library containing all of the Markov chain logic
• Youtube API code

• Brain

  • This holds the markov instance, and updates it reguarly with new comments from youtube trending. It exposes a RESTful API which allows you to generate comments and so on. This allows you to hook up multiple consumers to the service.

• Slackbot

  • Contains all of the chatbot related code, and communicates to the brain over http when it requires message to be generated.

• Web interface

  • A simple web interface to allow you to see statistics about the bot

Features

• Fetches new comments from youtube every night
• Web interface for viewing stats
• Easily deployable as a whole using docker-compose
• Individually deployable services with docker

What is a Markov chain?

A Markov chain is a model describing a sequence of events, and the chance of moving to another state from a previous state. We can use this to generate text by taking a bunch of source text and creating a Markov chain from it - which shows which words follow which other words. We an then generate a string of text by choosing a starting word and generating a chain using the model.

For a great visual display of Markov chains, see this page by Victor Powell

Open Source

Youtube Trending Slackbot is released under the MIT licence and can be found here on Github.