Giter VIP home page Giter VIP logo

bot-connector's Introduction

Sunset of Open Source Bot Connector

This repository will be brought down / archived from github.com by end of November, 2019.

To enhance your overall bot building experience, we are working on implementing new features and changing the structure of rich messages supported by our platform.

Unfortunately, this means that this repository will be unusable unless we go through a major refactor.

Since all Bot Connector capabilities are integrated in our bot building platform, weโ€™ve decided to sunset this open source repo.

If you are running a standard / customised version of open source bot connector on your platform, please migrate to the bot connector available on our bot building platform (hosted in on SAP Cloud Platform), which offers integration with a wide number of channels which that we plan to make more robust.

If you have any questions, please contact our team.

Bot Connector Logo

Supported Channels Getting Started How it works Messages Formats Getting Started with SAP Conversational AI

๐Ÿ’ฌ Questions / Comments? Join the discussion on our community Slack channel!

Bot Connector

Bot Connector allows you to connect your bot to multiple messaging channels.

It provides a higher level API to manage several messaging platforms at once, and lets you focus on your bot by using a simple and unique format to talk to the entire world.

Documentation

You can see the API documentation here

Or generate the documentation with the following command:

yarn docs && open docs/index.html

Supported Channels

Bot Connector supports the following channels:

You can find more information on each channel in the wiki

More will be added, and you can contribute if you want to, and add a thumbs up for the channel you want to see implemented first ;) (To do so, fork this repo, add a thumbs up and make a PR!)

  • Discord ๐Ÿ‘๐Ÿ‘๐Ÿ‘
  • Ryver ๐Ÿ‘
  • Viber
  • Wechat ๐Ÿ‘๐Ÿ‘
  • Zinc.it ๐Ÿ‘
  • Salesforce ๐Ÿ‘

Getting started

The following examples use yarn package manager but you can use your favorite one like npm, or pnpm.

In order to run the connector you need MongoDB and Redis installed and running. The configuration files for both are stored in config directory.

Installation

Clone the repository and install the dependencies

git clone https://github.com/SAPConversationalAI/bot-connector.git
cd bot-connector
yarn install

Available Commands

  • yarn start - Start application in production mode
  • yarn start:dev - Start application in development mode
  • yarn start:dev:debug - Start application in development mode with debugger
  • yarn test - Run unit & integration tests
  • yarn test:debug - Run unit & integration tests with debugger
  • yarn test:coverage - Run unit & integration tests with coverage report
  • yarn lint - Run ESLint
  • yarn build - Build artifacts for production
  • yarn docs - Generate apidoc documentation

Configurations/Environments

You need to create a configuration file based on the following schema:

config/{env}.js (e.g. config/development.js for NODE_ENV=development)

module.exports = {
  db: {
    host: 'localhost',
    port: 27017,
    dbName: 'botconnector',
  },
  server: {
    port: 8080,
  },
  redis: {
    port: 6379,
    host: 'localhost',
    auth: '',
    db: 7,
    options: {},  // see https://github.com/mranney/node_redis#rediscreateclient
  },
  mail: {},  // valid object to be passed to nodemail.createTransport()
  base_url: '',  // base url of the connector
  facebook_app_id: '',
  facebook_app_secret: '',
  facebook_app_webhook_token: '',
  amazon_client_id: '',  // Client ID for use with Login with Amazon (Amazon Alexa channel)
  amazon_client_secret: '',  // Client Id for use with Login with Amazon (Amazon Alexa channel)
}

Running in development mode (hot reload)

yarn start:dev

Setup your connector

First of all, you need to create a connector with the Bot Connector's API.

curl -X POST 'http://localhost:8080/connectors' --data 'url=YOUR_BOT_ENDPOINT_URL'

Then you need some code so the Bot Connector, via the connector you've just created, can send you the messages it receives. You can use the code from the example as a starter.

cd example
yarn install
yarn start

Now that your bot (well, your code) and the Bot Connector are running, you have to create channels. A channel is the actual link between your bot (the connector) and a specific service like Messenger, Slack or Kik. One connector can have multiple channels.

How it works

There are two distinct flows:

  • your bot receives a message from a channel
  • your bot sends a message to a channel

This pipeline allows us to have an abstraction of messages independent of the platform and implement only a few functions for each messaging platform (input and output parsing).

Receive a message

The Bot Connector posts on the endpoint stored with the connector each time a new message arrives from a channel.

  • a new message is received by Bot Connector
  • the message is parsed by the corresponding service
  • the message is saved in MongoDB
  • the message is post to the bot endpoint

BotConnector-Receive

Post a message

To send a new message, you have to post it to Bot Connector's API

  • the messages are saved in MongoDB
  • the messages are formatted by the corresponding service to match the channel's format
  • the messages are sent by Bot Connector to the corresponding channel

BotConnector-Sending

Messages format

All messages coming from the bot are parsed and modified to match the destination channel specifications. Bot Connector supports several message formats:

  • Text
{
  type: 'text',
  content: 'MY_TEXT',
}
  • Picture
{
  type: 'picture',
  content: 'IMAGE_URL',
}
  • Video
{
  type: 'video',
  content: 'VIDEO_URL',
}
  • Quick Replies
{
  type: 'quickReplies',
  content: {
    title: 'TITLE',
    buttons: [
      {
        title: 'BUTTON_1_TITLE',
        value: 'BUTTON_1_VALUE',
      }, {
        title: 'BUTTON_2_TITLE',
        value: 'BUTTON_2_VALUE',
      }
    ]
  }
}
  • List
{
  type: 'list',
  content: {
    elements: [
      {
        title: 'ELEM_1_TITLE',
        imageUrl: 'IMAGE_URL',
        subtitle: 'ELEM_1_SUBTITLE',
        buttons: [
          {
            title: 'BUTTON_1_TITLE',
            value: 'BUTTON_1_VALUE',
            type: 'BUTTON_TYPE',
          }
        ]
      }
    ],
    buttons: [
      {
        title: 'BUTTON_1_TITLE',
        value: 'BUTTON_1_VALUE',
        type: 'BUTTON_TYPE',
      }
    ]
  }
}
  • Card
{
  type: 'card',
  content: {
    title: 'CARD_TITLE',
    subtitle: 'CARD_SUBTITLE',
    imageUrl: 'IMAGE_URL',
    buttons: [
      {
        title: 'BUTTON_TITLE',
        type: 'BUTTON_TYPE', // See Facebook Messenger button formats
        value: 'BUTTON_VALUE',
      }
    ],
  },
}
  • Carousel
{
  type: 'carousel',
  content: [
    {
      title: 'CARD_1_TITLE',
      imageUrl: 'IMAGE_URL',
      buttons: [
        {
          title: 'BUTTON_1_TITLE',
          value: 'BUTTON_1_VALUE',
          type: 'BUTTON_1_TYPE',
        }
      ]
    }
  ],
}

Getting started with SAP Conversational AI

We build products to help enterprises and developers have a better understanding of user inputs.

  • NLP API: a unique API for text processing, and augmented training.
  • Bot Building Tools: all you need to create smart bots powered by SAP Conversational AI's NLP API. Design even the most complex conversation flow, use all rich messaging formats and connect to external APIs and services.
  • Bot Connector API: standardizes the messaging format across all channels, letting you connect your bots to any channel in minutes.

Learn more about:

API Documentation Discover the platform First bot tutorial Advanced NodeJS tutorial Advanced Python tutorial

bot-connector's People

Contributors

archimedix avatar betree avatar bgantelm avatar conradkleinespel avatar danielpetrica avatar datapharmer avatar dbousque avatar fadomire avatar fhenri42 avatar harinder-singh-batra avatar janteuni avatar jhoudan avatar jibrankalia avatar julien-leclercq avatar kender2 avatar louishntl avatar meriadec avatar plieb avatar shekhar-shubhendu avatar tokenbrice avatar usef01 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.