The functionality of Botkit can be extended using middleware functions. These functions can plugin to the core bot running processes at several useful places and make changes to both a bot's configuration and the incoming or outgoing message. Anyone can add their own middleware to the Botkit documentation, for more information please read this.
Currently the following types of middleware are available for Botkit:
Storage middleware can be used for storing attributes about a user or channel or team. It is currently available for the following services:
#Natural Language Processing
The Luis middleware with Botkit causes every message sent to your bot to be first sent through Luis.ai's NLP services for processing. The response from Luis is then returned in the incoming messages as seen below:
{
"query": "start tracking a run",
"intents": [
{
"intent": "startActivity",
"score": 0.9999981
},
{
"intent": "None",
"score": 0.144195557
},
{
"intent": "stopActivity",
"score": 1.54796021E-06
}
],
"entities": [
{
"entity": "run",
"type": "activityType",
"startIndex": 17,
"endIndex": 19,
"score": 0.9391843
}
]
}
Using the Wit hears middleware tells Botkit to look for Luis intents information, and match using this information instead of the built in pattern matching function.
Go to Luis.ai and log in with your microsoft account :
The first step to using Luis is to create an application. In the application, you will bundle together the intents and entities that are important to your task.
From your app's settings page, snag the service url. You will need this to use Luis's API.
Next you will need to add botkit-middleware-luis as a dependency to your Botkit bot:
npm install --save botkit-middleware-luis
Enable the middleware:
var luis = require('./lib/luis-middleware.js');
var luisOptions = {serviceUri: process.env.serviceUri};
controller.middleware.receive.use(luis.middleware.receive(luisOptions));
controller.hears(['hello','hi'],['direct_message','direct_mention','mention'], luis.middleware.hereIntent, function(bot,message) {
bot.reply(message,"Hello.");
});
This middleware plugin for Botkit allows you to utilize Api.ai, a natural language classifier service directly into the Botkit corebot.
The Api.ai platform lets developers seamlessly integrate intelligent voice and text based command systems into their products to create consumer-friendly voice/text-enabled user interfaces.
Using the Api.ai middleware with Botkit causes every message sent to your bot to be first sent through Api.ai's NLP services for processing. The response from Api.ai is then returned in the incoming messages as message.intent, message.entities for any language entities (dates, places, etc), message.fulfillment for Api.ai specific speech fulfillment, message.confidence for the confidence interval, and finally the message.nlpResponse which represents the raw request as seen below:
{
"id": "XXXX",
"timestamp": "2016-05-31T18:20:38.992Z",
"result": {
"source": "agent",
"resolvedQuery": "hello",
"action": "",
"actionIncomplete": false,
"parameters": {},
"contexts": [],
"metadata": {
"intentId": "XXX",
"webhookUsed": "false",
"intentName": "hello"
},
"fulfillment": {
"speech": ""
},
"score": 1
},
"status": {
"code": 200,
"errorType": "success"
}
}
In order to utilize api.ai's service you will need to create an account and an agent. An agent will represent your Bot's comprehension skills. Head over to their sign up page to get started. After creating an account you will be able to create your first agent and start creating intents. Grab the developer access token for your local dev and a client access token for production as seen below
Next you will need to add botkit-middleware-apiai as a dependency to your Botkit bot:
npm install --save botkit-middleware-apiai
Enable the middleware:
var apiai = require('botkit-middleware-apiai')({
token: <my_apiai_token>
});
controller.middleware.receive.use(apiai.receive);
controller.hears(['hello'],'direct_message',apiai.hears,function(bot, message) {
// ...
});
This middleware plugin for Botkit allows developers to easily integrate a Watson Conversation workspace with multiple social channels like Slack, Facebook, and Twilio. Customers can have simultaneous, independent conversations with a single workspace through different channels.
The middleware needs you to provide the username, password, and workspace_id of your Watson Conversation chat bot. If you have an existing Conversation service instance, follow these steps to get your credentials.
If you do not have a Conversation service instance, follow these steps to get started.
For more information on adding Watson to your bot check this projects documentation
A Mongo storage module for Botkit.
Just require botkit-storage-mongo and pass it a config with a mongoUri option.
Then pass the returned storage when creating your Botkit controller. Botkit will do the rest.
Make sure everything you store has an id property, that's what you'll use to look it up later.
var Botkit = require('botkit'),
mongoStorage = require('botkit-storage-mongo')({mongoUri: '...'}),
controller = Botkit.slackbot({
storage: mongoStorage
});
// then you can use the Botkit storage api, make sure you have an id property
var beans = {id: 'cool', beans: ['pinto', 'garbanzo']};
controller.storage.teams.save(beans);
beans = controller.storage.teams.get('cool');
A redis storage module for Botkit
Just require botkit-storage-redis and pass it your config options (or none if your cool with defaults).
Then pass the returned storage when creating your Botkit controller. Botkit will do the rest!
Make sure everything you store has an id property, that's what you'll use to look it up later.
var Botkit = require('botkit'),
redisConfig = {...}
redisStorage = require('botkit-storage-redis')(redisConfig),
controller = Botkit.slackbot({
storage: redisStorage
});
// then you can use the Botkit storage api, make sure you have an id property
var beans = {id: 'cool', beans: ['pinto', 'garbanzo']};
controller.storage.teams.save(beans);
beans = controller.storage.teams.get('cool');
You can pass any options that are allowed by node-redis.
Additionally you can pass a namespace property which is used to namespace keys in Redis. namespace defaults to botkit:store.
You can also pass a methods property which is an array of additional custom methods you want to add. The default methods are teams, users, and channels.
A Google Cloud Datastore storage module for Botkit
Just require botkit-storage-datastore and pass it a config with a projectId option.
Then pass the returned storage when creating your Botkit controller. Botkit will do the rest.
Make sure everything you store has an id property, that's what you'll use to look it up later.
var Botkit = require('botkit'),
datastoreStorage = require('botkit-storage-datastore')({projectId: '...'}),
controller = Botkit.slackbot({
storage: datastoreStorage
});
// then you can use the Botkit storage api, make sure you have an id property
var beans = {id: 'cool', beans: ['pinto', 'garbanzo']};
controller.storage.teams.save(beans);
beans = controller.storage.teams.get('cool');
A Firebase storage module for Botkit.
Just require botkit-storage-firebase and pass it a config with a firebase_uri option.
Then pass the returned storage when creating your Botkit controller. Botkit will do the rest.
Make sure everything you store has an id property, that's what you'll use to look it up later.
var Botkit = require('botkit'),
firebaseStorage = require('botkit-storage-firebase')({firebase_uri: '...'}),
controller = Botkit.slackbot({
storage: firebaseStorage
});
// then you can use the Botkit storage api, make sure you have an id property
var beans = {id: 'cool', beans: ['pinto', 'garbanzo']};
controller.storage.teams.save(beans);
beans = controller.storage.teams.get('cool');
Postgres storage module for Botkit
Install with npm
npm install botkit-storage-postgres --save
and require it and use it:
var botkitStoragePostgres = require('botkit-storage-postgres');
var Botkit = require('botkit');
var controller = Botkit.slackbot({
storage: botkitStoragePostgres({
host: 'localhost',
user: 'botkit',
password: 'botkit',
database: 'botkit'
})
});
This Botkit plugin enables support for bCRM, a customer CRM tool that enables bot developers to send broadcast messages to users of their bot.
This plugin currently works with Slack and Facebook bots.
npm install --save botkit-middleware-bcrm
-
Create a bCRM account and get your bCRM
tokenand bCRMbot id. -
Add the following lines to your Botkit application:
require('botkit-middleware-bcrm')({
bcrm_token: 'my_bcrm_token',
bcrm_bot: 'my_bcrm_bot',
controller: controller
});
- To register new users with bCRM:
If using Slack, register a new team with your bot's application via the oauth flow. Note, this assumes you are using the built-in oauth support.
If using Facebook, click the "Get Started" or any other button that fires a facebook_postback or
facebook_optinevent. Note, your app must be set to subscribe to the postback and/or optin events inside Facebook's developer tool.
In order to provide its service, this plugin sends information to bCRM that allows the bCRM software to access information and send messages on behalf of your bot. Before using this plugin, read bCRM's privacy policy, and make sure your own policies reflect the fact that you share information with them.
#Have you created middleware? We would love to hear about it! Contact the Howdy team to be included in Botkit documentation, or submit a PR on this documentation!