🚀 Getting started

If you are a web developer and know how to host a web application with Express and node.js, ChatAlly will only surprise you with it’s ease of use.

🏗️ Installation

To get started, with the simplest possible chat application, you need to create an npm ESM project, install the core library, a chat server, e.g. the ConsoleServer and add some middleware.

npm init esnext -y
npm install @chatally/core @chatally/console

✍ Create the application

Create a file index.js in which you configure your application

import { ConsoleServer } from '@chatally/console'
import { Application } from '@chatally/core'

new Application({ log: false }) //
  .use(new ConsoleServer("ChatAlly"))
  .use(({ req, res }) => {
    if (res.isWritable) {
      res.write(`You said '${req.content}'`)
    }
  })
  .listen()

Here we create a new chat application, register the ConsoleServer and implement a very simple middleware, that just echoes the user input.

ChatAlly is fully typed, so you can get full support from your code editor (you might need to setup a tsconfig.json file).

See the guide Writing Middleware for details on how to write your own middleware.

You can now start the application by running

node index.js

🥪 Add middleware

Of course, this chatbot is quite boring, but you can make it more interesting by adding some middleware, e.g. a module for NLP (Natural Language Processing) like nlp.js.

Install the module

npm install @chatally/nlpjs

and add it to your configuration instead of the function echo

import { ConsoleServer } from '@chatally/console'
import { Application } from '@chatally/core'
import { nlpjsMiddleware, trainNlp } from '@chatally/nlpjs'

const app = new Application({ log: false })
const nlp = await trainNlp(app.getLogger('nlp.js'))

app //
  .use(new ConsoleServer("nlp.js"))
  .use(nlpjsMiddleware(nlp))
  .listen()

The function trainNlp creates a trained NLP module and expects a training corpus at corpus.json. For this example you can download a corpus.json from nlp.js’ Github. We integrate nlp.js’ logging with ChatAlly’s by passing a logger from the application to nlp.js.

The function nlpjsMiddleware wraps the nlp.js Nlp.process(...) method in a ChatAlly middleware function.

Now it should be a bit more fun talking to your chatbot.

For details how to train your NLP, see the nlp.js documentation.

🤖 What next

The console server limits your audience severely, so maybe you want to try to connect your chatbot with WhatsApp and deploy it to a publicly accessible server.

You could also add more or different middleware, explore the middleware section in the sidebar or start writing your own middleware to add any missing piece.

If you first want to learn more about the core concepts, check out the reference documentation.