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
You can use the Recast.AI API to analyse your text or your audio file, and extract useful informations from it, to personalize your IoT, classify your data or create bots.
The middleware needs you to provide the request_token of your Recast bot project and an optional confidence.
- Add botkit-middleware-recastai as a dependency to your Botkit bot :
npm install --save botkit-middleware-recastai
- Enable the middleware :
var RecastaiMiddleware = require('botkit-middleware-recastai')({
request_token: '322e96b09ef75ad32bfc8b6f22b857ef',
confidence: 0.4
});
controller.middleware.receive.use(RecastaiMiddleware.receive);
controller.hears(['news'],'message_received', RecastaiMiddleware.hears,function(bot, message) {
// ...
});
For more information on adding Recast 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'
})
});A Couchdb storage module for botkit
$ npm install botkit-storage-couchdb --saveRequire botkit-storage-couchdb and pass your config options. Then pass the returned storage when creating your Botkit controller. Botkit will do the rest!
const Botkit = require('botkit'),
couchDbStorage = require('botkit-storage-couchdb')("localhost:5984/botkit"),
controller = Botkit.slackbot({
storage: couchDbStorage
});
// 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);
controller.storage.teams.get('cool', (error, team) => {
console.log(team);
});You can pass any options that are allowed by nano.
The url you pass should contain your database.
couchDbStorage = require('botkit-storage-couchdb')("localhost:5984/botkit")To specify further configuration options you can pass an object literal instead:
// The url is parsed and knows this is a database
couchDbStorage = require('botkit-storage-couchdb')({
"url": "http://localhost:5984/botkit",
"requestDefaults" : { "proxy" : "http://someproxy" },
"log": function (id, args) {
console.log(id, args);
}
});Botmetrics is an analytics and engagement platform for chatbots.
Add botkit-middleware-botmetrics to your package.json
$ npm install --save botkit-middleware-botmetrics
Register your bot with Botmetrics. Once you have done so, navigate to "Bot Settings" and find out your Bot ID and API Key.
Set the following environment variables with the Bot ID and API Key respectively.
BOTMETRICS_BOT_ID=your-bot-id
BOTMETRICS_API_KEY=your-api-key
Require botkit-middleware-botmetrics and use the middleware in your bot like so:
require('botkit-middleware-botmetrics')({
botmetricsBotId: process.env.BOTMETRICS_BOT_ID,
botmetricsApiKey: process.env.BOTMETRICS_API_KEY,
controller: controller
});This middleware allows you to to understand how many messages are going through your system, run cohorts to measure retention, set up funnels to measure task completion, and any key metric unique to your bot. More information about the Keen platform can be found on their website
Keen IO Botkit is available via NPM.
npm install keen-botkit --saveIf you want to use the example code, you can also clone it directly from Git.
git clone git@github.com:nemo/keen-botkit.gitNote that after cloning, you'll have to install the dependencies (which is just keen-js:
npm installThis 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.
Increase user engagement, acquisition, and monetization through actionable bots analytics.
Full install instructions can be found here
Wordhop monitors your Chatbot and alerts you on Slack in real-time when it detects conversational problems. You can watch your bot conversations with users in real-time without leaving Slack and take-over your bot to engage your customers directly. Simply add Wordhop to Slack and then drop in code into your Chatbot (You can use our examples as a starting point for a bot too). Wordhop integrates in minutes, and begins working immediately.
This module has been tested with Messenger, Slack, Skype, and Microsoft Webchat. Please see our examples.
#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!