This is a fork of the Telegraf library and its continuation as I envision it. I will do my best to maintain full compatibility so that anyone who lacks certain functionality can migrate to this solution quickly and without friction.

Introduction

Bots are special Telegram accounts designed to handle messages automatically. Users can interact with bots by sending them command messages in private or group chats. These accounts serve as an interface for code running somewhere on your server.

Tgify is a library that makes it simple for you to develop your own Telegram bots using JavaScript or TypeScript.

Release-notes

• Version 1.3.0 from 23.02.26
• Version 1.2.0 from 21.02.26
• Version 1.1.0 from 21.02.26
• Version 1.0.0 from 18.02.26

Features

• Full Telegram Bot API 8.3 support
• Excellent TypeScript typings
• Lightweight
• AWS λ / Firebase / Glitch / Fly.io / Whatever ready
• http/https/fastify/Connect.js/express.js compatible webhooks
• Extensible

Example

const { Tgify } = require('@tgify/bot')
const { message } = require('@tgify/bot/filters')

const bot = new Tgify(process.env.BOT_TOKEN)
bot.start((ctx) => ctx.reply('Welcome'))
bot.help((ctx) => ctx.reply('Send me a sticker'))
bot.on(message('sticker'), (ctx) => ctx.reply('👍'))
bot.hears('hi', (ctx) => ctx.reply('Hey there'))
bot.launch()

// Enable graceful stop
process.once('SIGINT', () => bot.stop('SIGINT'))
process.once('SIGTERM', () => bot.stop('SIGTERM'))

The Telegraf class can also be used, it will replicate all the basic functionality:

const { Telegraf } = require('@tgify/bot')

const bot = new Telegraf(process.env.BOT_TOKEN)
bot.command('oldschool', (ctx) => ctx.reply('Hello'))
bot.command('hipster', Telegraf.reply('λ'))
bot.launch()

// Enable graceful stop
process.once('SIGINT', () => bot.stop('SIGINT'))
process.once('SIGTERM', () => bot.stop('SIGTERM'))

For additional bot examples see the new docs repo.

Resources

• Getting started
• GitHub Discussions
• Dependent repositories

Getting started

Telegram token

To use the Telegram Bot API, you first have to get a bot account by chatting with BotFather.

BotFather will give you a token, something like 123456789:AbCdefGhIJKlmNoPQRsTUVwxyZ.

Installation

$ npm install @tgify/bot

or

$ yarn add @tgify/bot

or

$ pnpm add @tgify/bot

Tgify class

Tgify instance represents your bot. It's responsible for obtaining updates and passing them to your handlers.

Start by listening to commands and launching your bot.

Context class

ctx you can see in every example is a Context instance. Tgify creates one for each incoming update and passes it to your middleware. It contains the update, botInfo, and telegram for making arbitrary Bot API requests, as well as shorthand methods and getters.

This is probably the class you'll be using the most.

Shorthand methods

import { Tgify } from '@tgify/bot'
import { message } from '@tgify/bot/filters'

const bot = new Tgify(process.env.BOT_TOKEN)

bot.command('quit', async (ctx) => {
  // Explicit usage
  await ctx.telegram.leaveChat(ctx.message.chat.id)

  // Using context shortcut
  await ctx.leaveChat()
})

bot.on(message('text'), async (ctx) => {
  // Explicit usage
  await ctx.telegram.sendMessage(ctx.message.chat.id, `Hello ${ctx.state.role}`)

  // Using context shortcut
  await ctx.reply(`Hello ${ctx.state.role}`)
})

bot.on('callback_query', async (ctx) => {
  // Explicit usage
  await ctx.telegram.answerCbQuery(ctx.callbackQuery.id)

  // Using context shortcut
  await ctx.answerCbQuery()
})

bot.on('inline_query', async (ctx) => {
  const result = []
  // Explicit usage
  await ctx.telegram.answerInlineQuery(ctx.inlineQuery.id, result)

  // Using context shortcut
  await ctx.answerInlineQuery(result)
})

bot.launch()

// Enable graceful stop
process.once('SIGINT', () => bot.stop('SIGINT'))
process.once('SIGTERM', () => bot.stop('SIGTERM'))

Production

Webhooks

import { Tgify } from "@tgify/bot";
import { message } from '@tgify/bot/filters';

const bot = new Tgify(token);

bot.on(message("text"), ctx => ctx.reply("Hello"));

// Start webhook via launch method (preferred)
bot.launch({
  webhook: {
    // Public domain for webhook; e.g.: example.com
    domain: webhookDomain,

    // Port to listen on; e.g.: 8080
    port: port,

    // Optional path to listen for.
    // `bot.secretPathComponent()` will be used by default
    path: webhookPath,

    // Optional secret to be sent back in a header for security.
    // e.g.: `crypto.randomBytes(64).toString("hex")`
    secretToken: randomAlphaNumericString,
  },
});

Use createWebhook() if you want to attach Tgify to an existing http server.

import { createServer } from "http";

createServer(await bot.createWebhook({ domain: "example.com" })).listen(3000);

import { createServer } from "https";

createServer(tlsOptions, await bot.createWebhook({ domain: "example.com" })).listen(8443);

• AWS Lambda example integration
• Google Cloud Functions example integration
• express example integration
• fastify example integration
• koa example integration
• Cloudflare Workers integration module
• Use bot.handleUpdate to write new integrations

Error handling

If middleware throws an error or times out, Tgify calls bot.handleError. If it rethrows, update source closes, and then the error is printed to console and process terminates. If it does not rethrow, the error is swallowed.

Default bot.handleError always rethrows. You can overwrite it using bot.catch if you need to.

⚠️ Swallowing unknown errors might leave the process in invalid state!

ℹ️ In production, systemd or pm2 can restart your bot if it exits for any reason.

Advanced topics

Working with files

Supported file sources:

• Existing file_id
• File path
• Url
• Buffer
• ReadStream

Also, you can provide an optional name of a file as filename when you send the file.

bot.on('message', async (ctx) => {
  // resend existing file by file_id
  await ctx.replyWithSticker('123123jkbhj6b')

  // send file
  await ctx.replyWithVideo(Input.fromLocalFile('/path/to/video.mp4'))

  // send stream
  await ctx.replyWithVideo(
    Input.fromReadableStream(fs.createReadStream('/path/to/video.mp4'))
  )

  // send buffer
  await ctx.replyWithVoice(Input.fromBuffer(Buffer.alloc()))

  // send url via Telegram server
  await ctx.replyWithPhoto(Input.fromURL('https://picsum.photos/200/300/'))

  // pipe url content
  await ctx.replyWithPhoto(
    Input.fromURLStream('https://picsum.photos/200/300/?random', 'kitten.jpg')
  )
})

Middleware

In addition to ctx: Context, each middleware receives next: () => Promise<void>.

As in Koa and some other middleware-based libraries, await next() will call next middleware and wait for it to finish:

import { Tgify } from '@tgify/bot';
import { message } from '@tgify/bot/filters';

const bot = new Tgify(process.env.BOT_TOKEN);

bot.use(async (ctx, next) => {
  console.time(`Processing update ${ctx.update.update_id}`);
  await next() // runs next middleware
  // runs after next middleware finishes
  console.timeEnd(`Processing update ${ctx.update.update_id}`);
})

bot.on(message('text'), (ctx) => ctx.reply('Hello World'));
bot.launch();

// Enable graceful stop
process.once('SIGINT', () => bot.stop('SIGINT'));
process.once('SIGTERM', () => bot.stop('SIGTERM'));

With this simple ability, you can:

• extract information from updates and then await next() to avoid disrupting other middleware,
• like Composer and Router, await next() for updates you don't wish to handle,
• like session and Scenes, extend the context by mutating ctx before await next(),
• intercept API calls,
• reuse other people's code,
• do whatever you come up with!

Usage with TypeScript

Tgify is written in TypeScript and therefore ships with declaration files for the entire library. Moreover, it includes types for the complete Telegram API via the typegram package. While most types of Tgify's API surface are self-explanatory, there's some notable things to keep in mind.

Extending Context

The exact shape of ctx can vary based on the installed middleware. Some custom middleware might register properties on the context object that Tgify is not aware of. Consequently, you can change the type of ctx to fit your needs in order for you to have proper TypeScript types for your data. This is done through Generics:

import { Context, Tgify } from '@tgify/bot'

// Define your own context type
interface MyContext extends Context {
  myProp?: string
  myOtherProp?: number
}

// Create your bot and tell it about your context type
const bot = new Tgify<MyContext>('SECRET TOKEN')

// Register middleware and launch your bot as usual
bot.use((ctx, next) => {
  // Yay, `myProp` is now available here as `string | undefined`!
  ctx.myProp = ctx.chat?.first_name?.toUpperCase()
  return next()
})
// ...