My Personal Assistant is a Telegram Bot

Every developer should have personal (bot) assistant to get things (or boring tasks) done.


We often need tools to get things done. As a developer, one of my productivity hacks is to use Telegram bots to help me get things done quickly. From checking the bus schedule for commuting, to image resizing. Most of the small, unpleasant tasks I delegate to the Telegram bot. Simply put, a Telegram bot is my personal assistant.

If that opening line got your interest, this article will provide you the base foundation to build Telegram bot. Plus, with ready-to-deploy code which you can find on this GitHub repo.

You can find the source code in this GitHub repo: donnieprakoso/telegram-bot-boilerplate.

Now, let's get more technical.

To interact with Telegram bots — such as getting messages or photos — we can use either polling (getUpdates) or webhooks (setWebhook). Of these two methods, I'm more comfortable using a webhook because I don't have to develop polling mechanisms that use resources inefficiently. With a webhook, if there is a message, Telegram will make a POST request to the webhook URL which will trigger our backend to process the request.

Overview of request from Telegram, webhook and serverless API

In this article, you will learn how to build a Telegram bot that integrate with serverless APIs. This article provides an overview of the basic concept, workflow, and requirements. You can extend the functionality by adding business logic based on your needs. For the serverless API, you will use the Amazon API Gateway and an AWS Lambda function.

Diagram architecture

All the stacks here will use the AWS CDK to provision resources, so you'll get a consistent deployment. If you are new to the AWS CDK, please install the CDK first and then follow the tutorial for bootstrapping.

Let's Get Started!

Step 1: Request bot using @BotFather

First, we need to create a bot using @BotFather. You need to run the command /newbot and follow the instructions from @BotFather to give it a name. Once that's all done, you'll get the URL for the bot you just created as well as a token that you can use to interact with your bot.

Bot registration using @BotFather

After you get the token, keep your token safe and don't share it with anyone for security reasons. We will use Telegram token in the following steps.

Step 2: Deploy Webhook using Serverless API

In this step we will deploy the serverless API. The output of this step is the API Endpoint URL that we can use to register the webhook for the Telegram bot that we just created. Before we deploy this serverless API stack, let's do a code review so you understand what the CDK app will do.

Code Review: AWS Systems Manager Parameter Store

The first thing we need to define in the CDK app is to create resources to store the Telegram token. Of course we want to avoid hard coding in this application. We will use the AWS Systems Manager Parameter Store which we can later retrieve inside the Lambda function. The parameter name that we use is telegram_token which you can find in the Parameter Store dashboard, with a dummy value of TELEGRAM_TOKEN which we will need to change manually later.

ssm_telegram_token = _ssm.StringParameter(self, id="{}-ssm-telegram-token".format( stack_prefix), parameter_name="telegram_token", description="Telegram Bot Token", type=_ssm.ParameterType.STRING, string_value="TELEGRAM_TOKEN")

Code Review: AWS IAM Roles

The next thing we need to define are the IAM roles that define Lambda function access to write log groups with Amazon CloudWatch as well as access to the Parameter Store. For the record, we can grant access to the Lambda function by calling the .grant_read() function, but I prefer this approach because I can explicitly implement for least privilege.

lambda_role = _iam.Role( self, id='{}-lambda-role'.format(stack_prefix), assumed_by=_iam.ServicePrincipal('')) cw_policy_statement = _iam.PolicyStatement(effect=_iam.Effect.ALLOW) cw_policy_statement.add_actions("logs:CreateLogGroup") cw_policy_statement.add_actions("logs:CreateLogStream") cw_policy_statement.add_actions("logs:PutLogEvents") cw_policy_statement.add_actions("logs:DescribeLogStreams") cw_policy_statement.add_resources("*") lambda_role.add_to_policy(cw_policy_statement) ssm_policy_statement = _iam.PolicyStatement(effect=_iam.Effect.ALLOW) ssm_policy_statement.add_actions("ssm:DescribeParameters") ssm_policy_statement.add_actions("ssm:GetParameter") ssm_policy_statement.add_resources(ssm_telegram_token.parameter_arn) lambda_role.add_to_policy(ssm_policy_statement)

Code Review: Define AWS Lambda Function

After that, we will define the Lambda function which is the central point in processing the request. Here, I define some properties for Lambda functions, such as handler, timeout, tracing using AWS X-Ray, and using Python 3.8 runtime. For role, we will use lambda_role which we defined above. Also, for Lambda function to be able to get the Parameter Store, we will pass an environment variable called SSM_TELEGRAM_TOKEN.

fnLambda_handle = _lambda.Function( self, "{}-function-telegram".format(stack_prefix), code=_lambda.AssetCode("../lambda-functions/webhook"), handler="app.handler", timeout=core.Duration.seconds(60), role=lambda_role, tracing=_lambda.Tracing.ACTIVE, runtime=_lambda.Runtime.PYTHON_3_8) fnLambda_handle.add_environment( "SSM_TELEGRAM_TOKEN", ssm_telegram_token.parameter_name)

But what about the code for AWS Lambda?

Here we define AssetCode which we can get in lambda-functions/webhook folder. There is only 1 main file which is, and let's evaluate what this Lambda function (lambda-functions/webhook/ will do:

The first thing it will do is get the Telegram token for the Parameter Store using string SSM_TELEGRAM_TOKEN from the environment variables. To do this, we need to call os.getenv("SSM_TELEGRAM_TOKEN"). The important thing here is how we construct the TELEGRAM_BASE_URL variable which is the Telegram endpoint to interact with bots.

# Get Parameter Store for Telegram Token ssm = boto3.client('ssm') SSM_TELEGRAM_TOKEN = os.getenv('SSM_TELEGRAM_TOKEN') TELEGRAM_TOKEN = ssm.get_parameter(Name=SSM_TELEGRAM_TOKEN)[ "Parameter"]["Value"] TELEGRAM_BASE_URL = "{}/".format( TELEGRAM_TOKEN)

Next, we define a function for send_message. Here we will pass chat_ID so that our text message will be sent to the appropriate channel.

def send_message(chat_ID, text): data = {"chat_id": chat_ID, "text": text} send_message ="{}{}".format(TELEGRAM_BASE_URL, "sendMessage"), data=data)

Once we have defined the send_message function, the next part is to define the handler function. The handler⁣ function is the main event loop function that processes events. When the Lambda function receives an event, it passes the event (and runtime context) to the handler⁣ function.

In this case, the webhooks calls will invoke this Lambda function. For this Lambda function, I need to be able to interact with media images as well as text. Therefore, here I define two key properties, namely text to be able to parse requests for text messages, and also photo to process messages with images.

def handler(event, context): try: data = json.loads(event['body']) if "text" in data["message"]: text_to_reply = "Echo: {}".format(data["message"]["text"]) send_message(data["message"]["chat"]["id"], text_to_reply) response = {"statusCode": 200, "body": json.dumps({"message": "success"})} elif "photo" in data["message"]: text_to_reply = "Received a photo with caption: {}".format( data["message"]["caption"]) if "caption" in data["message"] else "Received a photo" send_message(data["message"]["chat"]["id"], text_to_reply) response = {"statusCode": 200, "body": json.dumps({"message": "success"})} return response except Exception as e: logger.error("Error on processing request: {}".format(e)) response = {"statusCode": 200, "body": json.dumps({"message": "success"})} return response

Code Review: REST API with Amazon API Gateway

Back to the CDK app, after defining the Parameter Store, IAM, and Lambda function, it's time to define the API Gateway.

Here I define a REST API — you can use any API type supported by API Gateway, such as the HTTP API. After that, I defined the integration for Lambda function. We also need to define a resource for this API path URI, and by defining add_resource("telegram"), Telegram can use our webhook URL at using the POST method.

api = _ag.RestApi( self, id="{}-api-gateway".format(stack_prefix), ) int_webhook = _ag.LambdaIntegration(fnLambda_handle) res_data = api.root.add_resource('telegram') res_data.add_method('POST', int_webhook)
core.CfnOutput(self, "{}-output-apiEndpointURL".format(stack_prefix), value=api.url, export_name="{}-apiEndpointURL".format(stack_prefix))

Step 3: Deployment

To deploy our serverless API stack, you will first need to install all the libraries that will be used by Lambda functions with the following command in the lambda-functions/webhook folder:

pip install -r requirements.txt -t .

After that, you can switch to the cdk folder, and deploy the serverless API with the following command:

cdk deploy

Once the process is complete, you will get an endpoint URL from the API Gateway.

Step 4: Configure Telegram Token

Before we can use the webhook, we need to set up the Telegram token in the Parameter Store. For that we need to do the following steps:

Go to Parameter Store dashboard and use telegram_token as filter.

Parameter Store dashboard

Click the telegram_token parameter and click the Edit button.


Change the value of telegram_token to the value of the Telegram token you got.

Change Telegram token value

Step 5: Configure the Webhook

After that, set up your bot using a webhook. For that, you need to open the following URL and replace it with the appropriate variable:{TELEGRAM TOKEN}/setWebhook?url={API ENDPOINT URL}

Change {TELEGRAM TOKEN} to your Telegram token. Then, change {URL API ENDPOINT} to the URL of API Gateway and add /telegram, for example:

After that, you need to open your browser and go to the URL. If this works, you'll get this response.:

Activating Telegram webhook from web browser

Step 6: Testing

And that's it! At this stage, you have already done the integration for your Telegram bot and webhook. For testing, please send a message to your bot. You will get an echo response for the text message.

Sending a text message to Telegram bot

You can also send a message with a photo, and get a confirmation image received with or without a caption.

Sending photo to Telegram bot

If you need to view the logs from your Lambda, you can take a detailed look at the CloudWatch logs. Here's an example display for logs from my serverless API:

Amazon CloudWatch logs

Step 7: Cleaning Up

Don't forget to clean up all the resources by running this following command in cdk folder:

cdk destroy

I know that you won't do this when you're building the bot, and just a quick note for you to clean up the resources.

Conclusion and What's Next?

And that's how you build a personal assistant with Telegram bot. I use this Telegram bot for various needs, and it is very practical because I can interact with the bot either via mobile phone or from the desktop.

But, what's next? From here, you have the basic foundation to build your own logic needs. You can modify the text using keywords or use captions for media images. Let me know what you've built in the comments below!

Happy building! ️ — Donnie

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.