> This is a page from the ElevenLabs documentation. For a complete page index, fetch https://elevenlabs.io/docs/llms.txt. For the full documentation in a single file, fetch https://elevenlabs.io/docs/llms-full.txt.

# Transcription Telegram Bot

> **Note**
>
> **How-to guide** · Assumes you have completed the [Speech to Text quickstart](/docs/eleven-api/guides/cookbooks/speech-to-text) and have a Telegram bot token and
> Supabase account.

## Introduction

In this tutorial you will learn how to build a Telegram bot that transcribes audio and video messages in 90+ languages using TypeScript and the ElevenLabs Scribe model via the speech-to-text API.

## Requirements

* An ElevenLabs account with an [API key](https://elevenlabs.io/app/settings/api-keys).
* A [Supabase](https://supabase.com) account (you can sign up for a free account via [database.new](https://database.new)).
* The [Supabase CLI](https://supabase.com/docs/guides/local-development) installed on your machine.
* The [Deno runtime](https://docs.deno.com/runtime/getting_started/installation/) installed on your machine and optionally [setup in your facourite IDE](https://docs.deno.com/runtime/getting_started/setup_your_environment).
* A [Telegram](https://telegram.org) account.

## Setup

### Register a Telegram bot

Use the [BotFather](https://t.me/BotFather) to create a new Telegram bot. Run the `/newbot` command and follow the instructions to create a new bot. At the end, you will receive your secret bot token. Note it down securely for the next step.

![BotFather](/docs/_fern-img/28aa856bb6ace1b49b82076a18f1e281a8a4f37bbb6cfc59c22d644564377248.webp)

### Create a Supabase project locally

After installing the [Supabase CLI](https://supabase.com/docs/guides/local-development), run the following command to create a new Supabase project locally:

```bash
supabase init
```

### Create a database table to log the transcription results

Next, create a new database table to log the transcription results:

```bash
supabase migrations new init
```

This will create a new migration file in the `supabase/migrations` directory. Open the file and add the following SQL:

**`supabase/migrations/init.sql`**

```sql supabase/migrations/init.sql
CREATE TABLE IF NOT EXISTS transcription_logs (
  id BIGSERIAL PRIMARY KEY,
  file_type VARCHAR NOT NULL,
  duration INTEGER NOT NULL,
  chat_id BIGINT NOT NULL,
  message_id BIGINT NOT NULL,
  username VARCHAR,
  transcript TEXT,
  language_code VARCHAR,
  created_at TIMESTAMP WITH TIME ZONE DEFAULT CURRENT_TIMESTAMP,
  error TEXT
);

ALTER TABLE transcription_logs ENABLE ROW LEVEL SECURITY;
```

### Create a Supabase Edge Function to handle Telegram webhook requests

Next, create a new Edge Function to handle Telegram webhook requests:

```bash
supabase functions new scribe-bot
```

If you're using VS Code or Cursor, select `y` when the CLI prompts "Generate VS Code settings for Deno? \[y/N]"!

### Set up the environment variables

Within the `supabase/functions` directory, create a new `.env` file and add the following variables:

**`supabase/functions/.env`**

```env supabase/functions/.env
# Find / create an API key at https://elevenlabs.io/app/settings/api-keys
ELEVENLABS_API_KEY=your_api_key

# The bot token you received from the BotFather.
TELEGRAM_BOT_TOKEN=your_bot_token

# A random secret chosen by you to secure the function.
FUNCTION_SECRET=random_secret
```

### Dependencies

The project uses a couple of dependencies:

* The open-source [grammY Framework](https://grammy.dev/) to handle the Telegram webhook requests.
* The [@supabase/supabase-js](https://supabase.com/docs/reference/javascript) library to interact with the Supabase database.
* The ElevenLabs [JavaScript SDK](/docs/eleven-api/quickstart) to interact with the speech-to-text API.

Since Supabase Edge Function uses the [Deno runtime](https://deno.land/), you don't need to install the dependencies, rather you can [import](https://docs.deno.com/examples/npm/) them via the `npm:` prefix.

## Code the Telegram Bot

In your newly created `scribe-bot/index.ts` file, add the following code:

**`supabase/functions/scribe-bot/index.ts`**

```ts supabase/functions/scribe-bot/index.ts
import { Bot, webhookCallback } from "https://deno.land/x/grammy@v1.34.0/mod.ts";
import "jsr:@supabase/functions-js/edge-runtime.d.ts";
import { createClient } from "jsr:@supabase/supabase-js@2";
import { ElevenLabsClient } from "npm:elevenlabs@1.50.5";

console.log(`Function "elevenlabs-scribe-bot" up and running!`);

const elevenlabs = new ElevenLabsClient({
  apiKey: Deno.env.get("ELEVENLABS_API_KEY") || "",
});

const supabase = createClient(
  Deno.env.get("SUPABASE_URL") || "",
  Deno.env.get("SUPABASE_SERVICE_ROLE_KEY") || ""
);

async function scribe({
  fileURL,
  fileType,
  duration,
  chatId,
  messageId,
  username,
}: {
  fileURL: string;
  fileType: string;
  duration: number;
  chatId: number;
  messageId: number;
  username: string;
}) {
  let transcript: string | null = null;
  let languageCode: string | null = null;
  let errorMsg: string | null = null;
  try {
    const sourceFileArrayBuffer = await fetch(fileURL).then((res) => res.arrayBuffer());
    const sourceBlob = new Blob([sourceFileArrayBuffer], {
      type: fileType,
    });

    const scribeResult = await elevenlabs.speechToText.convert({
      file: sourceBlob,
      model_id: "scribe_v2",
      tag_audio_events: false,
    });

    transcript = scribeResult.text;
    languageCode = scribeResult.language_code;

    // Reply to the user with the transcript
    await bot.api.sendMessage(chatId, transcript, {
      reply_parameters: { message_id: messageId },
    });
  } catch (error) {
    errorMsg = error.message;
    console.log(errorMsg);
    await bot.api.sendMessage(chatId, "Sorry, there was an error. Please try again.", {
      reply_parameters: { message_id: messageId },
    });
  }
  // Write log to Supabase.
  const logLine = {
    file_type: fileType,
    duration,
    chat_id: chatId,
    message_id: messageId,
    username,
    language_code: languageCode,
    error: errorMsg,
  };
  console.log({ logLine });
  await supabase.from("transcription_logs").insert({ ...logLine, transcript });
}

const telegramBotToken = Deno.env.get("TELEGRAM_BOT_TOKEN");
const bot = new Bot(telegramBotToken || "");
const startMessage = `Welcome to the ElevenLabs Scribe Bot\\! I can transcribe speech in 90\\+ languages with super high accuracy\\!
    \nTry it out by sending or forwarding me a voice message, video, or audio file\\!
    \n[Learn more about Scribe](https://elevenlabs.io/speech-to-text) or [build your own bot](https://elevenlabs.io/developers/guides/cookbooks/speech-to-text/telegram-bot)\\!
  `;
bot.command("start", (ctx) => ctx.reply(startMessage.trim(), { parse_mode: "MarkdownV2" }));

bot.on([":voice", ":audio", ":video"], async (ctx) => {
  try {
    const file = await ctx.getFile();
    const fileURL = `https://api.telegram.org/file/bot${telegramBotToken}/${file.file_path}`;
    const fileMeta = ctx.message?.video ?? ctx.message?.voice ?? ctx.message?.audio;

    if (!fileMeta) {
      return ctx.reply("No video|audio|voice metadata found. Please try again.");
    }

    // Run the transcription in the background.
    EdgeRuntime.waitUntil(
      scribe({
        fileURL,
        fileType: fileMeta.mime_type!,
        duration: fileMeta.duration,
        chatId: ctx.chat.id,
        messageId: ctx.message?.message_id!,
        username: ctx.from?.username || "",
      })
    );

    // Reply to the user immediately to let them know we received their file.
    return ctx.reply("Received. Scribing...");
  } catch (error) {
    console.error(error);
    return ctx.reply(
      "Sorry, there was an error getting the file. Please try again with a smaller file!"
    );
  }
});

const handleUpdate = webhookCallback(bot, "std/http");

Deno.serve(async (req) => {
  try {
    const url = new URL(req.url);
    if (url.searchParams.get("secret") !== Deno.env.get("FUNCTION_SECRET")) {
      return new Response("not allowed", { status: 405 });
    }

    return await handleUpdate(req);
  } catch (err) {
    console.error(err);
  }
});
```

### Code deep dive

There's a couple of things worth noting about the code. Let's step through it step by step.

#### Handling the incoming request

To handle the incoming request, use the `Deno.serve` handler. The handler checks whether the request has the correct secret and then passes the request to the `handleUpdate` function.

```ts {1,6,10}
const handleUpdate = webhookCallback(bot, 'std/http');

Deno.serve(async (req) => {
  try {
    const url = new URL(req.url);
    if (url.searchParams.get('secret') !== Deno.env.get('FUNCTION_SECRET')) {
      return new Response('not allowed', { status: 405 });
    }

    return await handleUpdate(req);
  } catch (err) {
    console.error(err);
  }
});
```

#### Handle voice, audio, and video messages

The grammY frameworks provides a convenient way to [filter](https://grammy.dev/guide/filter-queries#combining-multiple-queries) for specific message types. In this case, the bot is listening for voice, audio, and video messages.

Using the request context, the bot extracts the file metadata and then uses [Supabase Background Tasks](https://supabase.com/docs/guides/functions/background-tasks) `EdgeRuntime.waitUntil` to run the transcription in the background.

This way you can provide an immediate response to the user and handle the transcription of the file in the background.

```ts {1,3,12,24}
bot.on([':voice', ':audio', ':video'], async (ctx) => {
  try {
    const file = await ctx.getFile();
    const fileURL = `https://api.telegram.org/file/bot${telegramBotToken}/${file.file_path}`;
    const fileMeta = ctx.message?.video ?? ctx.message?.voice ?? ctx.message?.audio;

    if (!fileMeta) {
      return ctx.reply('No video|audio|voice metadata found. Please try again.');
    }

    // Run the transcription in the background.
    EdgeRuntime.waitUntil(
      scribe({
        fileURL,
        fileType: fileMeta.mime_type!,
        duration: fileMeta.duration,
        chatId: ctx.chat.id,
        messageId: ctx.message?.message_id!,
        username: ctx.from?.username || '',
      })
    );

    // Reply to the user immediately to let them know we received their file.
    return ctx.reply('Received. Scribing...');
  } catch (error) {
    console.error(error);
    return ctx.reply(
      'Sorry, there was an error getting the file. Please try again with a smaller file!'
    );
  }
});
```

#### Transcription with the ElevenLabs API

Finally, in the background worker, the bot uses the ElevenLabs JavaScript SDK to transcribe the file. Once the transcription is complete, the bot replies to the user with the transcript and writes a log entry to the Supabase database using [supabase-js](https://supabase.com/docs/reference/javascript).

```ts {29-38,43-46,54-65}
const elevenlabs = new ElevenLabsClient({
  apiKey: Deno.env.get('ELEVENLABS_API_KEY') || '',
});

const supabase = createClient(
  Deno.env.get('SUPABASE_URL') || '',
  Deno.env.get('SUPABASE_SERVICE_ROLE_KEY') || ''
);

async function scribe({
  fileURL,
  fileType,
  duration,
  chatId,
  messageId,
  username,
}: {
  fileURL: string;
  fileType: string;
  duration: number;
  chatId: number;
  messageId: number;
  username: string;
}) {
  let transcript: string | null = null;
  let languageCode: string | null = null;
  let errorMsg: string | null = null;
  try {
    const sourceFileArrayBuffer = await fetch(fileURL).then((res) => res.arrayBuffer());
    const sourceBlob = new Blob([sourceFileArrayBuffer], {
      type: fileType,
    });

    const scribeResult = await elevenlabs.speechToText.convert({
      file: sourceBlob,
      model_id: 'scribe_v2',
      tag_audio_events: false,
    });

    transcript = scribeResult.text;
    languageCode = scribeResult.language_code;

    // Reply to the user with the transcript
    await bot.api.sendMessage(chatId, transcript, {
      reply_parameters: { message_id: messageId },
    });
  } catch (error) {
    errorMsg = error.message;
    console.log(errorMsg);
    await bot.api.sendMessage(chatId, 'Sorry, there was an error. Please try again.', {
      reply_parameters: { message_id: messageId },
    });
  }
  // Write log to Supabase.
  const logLine = {
    file_type: fileType,
    duration,
    chat_id: chatId,
    message_id: messageId,
    username,
    language_code: languageCode,
    error: errorMsg,
  };
  console.log({ logLine });
  await supabase.from('transcription_logs').insert({ ...logLine, transcript });
}
```

## Deploy to Supabase

If you haven't already, create a new Supabase account at [database.new](https://database.new) and link the local project to your Supabase account:

```bash
supabase link
```

### Apply the database migrations

Run the following command to apply the database migrations from the `supabase/migrations` directory:

```bash
supabase db push
```

Navigate to the [table editor](https://supabase.com/dashboard/project/_/editor) in your Supabase dashboard and you should see and empty `transcription_logs` table.

![Empty table](/docs/_fern-img/c1493deafcd6c53712dcb4fa7a44b3253b571ade0bb2e9c2b4fdb090088b0695.webp)

Lastly, run the following command to deploy the Edge Function:

```bash
supabase functions deploy --no-verify-jwt scribe-bot
```

Navigate to the [Edge Functions view](https://supabase.com/dashboard/project/_/functions) in your Supabase dashboard and you should see the `scribe-bot` function deployed. Make a note of the function URL as you'll need it later, it should look something like `https://<project-ref>.functions.supabase.co/scribe-bot`.

![Edge Function deployed](/docs/_fern-img/d12141a51a09563d625b379201de844800e0c7dcfa9e6c7f21484cbca7ff37cf.webp)

### Set up the webhook

Set your bot's webhook url to `https://<PROJECT_REFERENCE>.functions.supabase.co/telegram-bot` (Replacing `<...>` with respective values). In order to do that, simply run a GET request to the following url (in your browser, for example):

```
https://api.telegram.org/bot<TELEGRAM_BOT_TOKEN>/setWebhook?url=https://<PROJECT_REFERENCE>.supabase.co/functions/v1/scribe-bot?secret=<FUNCTION_SECRET>
```

Note that the `FUNCTION_SECRET` is the secret you set in your `.env` file.

![Set webhook](/docs/_fern-img/ac72044bd3df138da3d8a0df09e8413e8a9fd8a5c3156a525d6b13664854482f.webp)

### Set the function secrets

Now that you have all your secrets set locally, you can run the following command to set the secrets in your Supabase project:

```bash
supabase secrets set --env-file supabase/functions/.env
```

## Test the bot

Finally you can test the bot by sending it a voice message, audio or video file.

![Test the bot](/docs/_fern-img/a42c784e6324f15575e0299bafe02a253a2bdc57f2ad5844f83e5b64297780e7.webp)

After you see the transcript as a reply, navigate back to your table editor in the Supabase dashboard and you should see a new row in your `transcription_logs` table.

![New row in table](/docs/_fern-img/25c008858276b7cd4af6f8e72473891176bb9e2ce62e7002af353a2dac205e06.webp)

## Next steps

#### [API reference](/docs/api-reference/speech-to-text)

Full Speech to Text API reference and parameters.

#### [Twilio integration](/docs/eleven-api/guides/how-to/text-to-speech/twilio)

Integrate ElevenLabs TTS with Twilio for phone-based voice applications.

> ElevenLabs provides APIs and SDKs for text to speech, voice cloning, speech to text, sound effects, voice isolator, voice changer, and conversational AI agents. Build voice-enabled applications with lifelike audio generation.