Creating a Simple Slack Bot with Botkit.js and Hosting It For Free

From Development to Deployment as a Custom Integration

Recently I decided to build a Slack bot to keep track of links and host it using BeepBoop — a new hosting service designed specifically for chat bots. Fortunately Beepboop has created a nice library that integrates with Botkit, making it easier than ever to develop simple chat bots and deploy them on cloud hosting. Currently only Slack and Facebook Messenger are supported, but I expect that more platforms will be added. Their pricing is very reasonable with a free plan avilable and paid plans starting at $10 / month.

In this article we’ll create a Slack Bot, run it locally and then deploy it on BeepBoop as a custom integration. We’ll take this step by step, but you can skip the next section if you already have a bot to deploy.

Let’s make a bot

All the code we’re going to write is available in this repo. However, to make sure we fully understand what’s going on, let’s go one step at a time and develop a toy chat bot that contains just the bare minimum that we need. Assuming that you have a node.js environment set up with npm, we’re just going to create two files:

First create a package.json:

Here we’ve included the beepboop-botkit and botkit libraries, and defined how npm can start our app, which will live in index.js.

OK, here’s index.js:

Let’s just walk through what’s going on here.

First, note that this code only uses the Botkit library — this is all we need to run this bot locally as a custom integration. We’ll pass in an environment variable for “SLACK_TOKEN” which we’ll get when we set up a Slack custom integration with in the next step.

Next we use the Botkit.slackbot constructor to return a controller object. The controller object then spawns a bot instance, which will connect to the Slack RTM (Real-time messaging API) using the SLACK_TOKEN that we’ll pass in.

Now we register two event handlers on the controller. The first will listen for the event “bot_channel_join” which should be fired when our bot is invited into a channel. The callback function will then send a message to the channel saying “I’m here”.

The second event handler listens for a message that says “hi”, and is of any of the following types, which should catch everything: [‘ambient’, ‘direct_message’, ’direct_mention’, ’mention’]. Note that the first parameter is a regex, which is about as sophisticated as botkit gets for disambiguating intents.

Running Locally as a Custom Integration

Just a few steps before we can talk to our bot.

Develop a Slack Custom Integration

npm install

Assuming you get no errors you should see your bot’s username appear in your Slack team. Open a direct message window with the bot and say “hi” — you should get a “Hello” in return.

Good! Now commit your code to a git repo and push your code up to Github — you’ll need this for the next step.

Deploying as a Custom Integration

Sign up at with your Github account. There’s a good on-boarding process that runs on Slack, but there’e no need to go through this as it will fork an example repo for you, which you don’t need to do if you’re following this article and creating your own bot.

Next we need to create a new project, and select the Github repo that you’ve pushed your code to. Beepboop will set up a webhook that will re-build your project on every commit to the master branch.

Build Slack Bot

Now we need to add a couple of files to tell BeepBoop how to build our project. All bots run as docker containers, so the first file we need to add is called Dockerfile:

Next we need to provide a bit of metadata about our bot — this goes in a file called bot.yml:

Your project should now contain these four files:

Go to your project page on BeepBoop and click the “settings” tab. Turn on the switch for Slack support and enter your API token in the SLACK_TOKEN text field.

Slack bot settings page

Commit the changes to the repo and push to Github. Go back to the Status tab and you should see Beepboop building your project. Once the build is done you can click “Start Bot” — you should see your bot come online in Slack.

Great! What Next?

If you’d like your bot to be used by multiple teams then you need to follow this article showing how to deploy your bot as a multi-team slack app

If you’re interested in how to develop your bot into a sophisticated conversational UI using NLP then sign up below to get the next post in your inbox.

If you can’t wait and you’d like my team and I at Atchai to help develop your chatbot or Slack integration, then I’d love to hear from you — drop me an email.