🔥Building a Slack Bot with AI Capabilities - From Scratch! Part 4: Serverless with Lambda🔥

aka, I don't want to maintain infrastructure ever again

This blog series focuses on presenting complex DevOps projects as simple and approachable via plain language and lots of pictures. You can do it!

This article is part of a series of articles, because 1 article would be absolutely massive.

• Part 1: Covers how to build a slack bot in websocket mode and connect to it with python

• Part 2: How to deploy an AWS Bedrock AI resource and connect to it to ask a request locally from your terminal with python3

• Part 3: We’ll connect our slack bot with Bedrock locally using python3 with ngrok so slack users can have conversations with AI

• Part 4 (this article): How to convert your local script to an event-driven serverless, cloud-based app in AWS Lambda

• Part 5: Building a RAG Knowledge Base of an entire Confluence wiki, and teaching our Slack Bot to Read it in Real-Time

Hey all!

Welcome to part 4 of this very large series about building an AI chatbot. Thus far, we’ve built a Slack App, and configured it to send webhooks to our ngrok instance, which is relaying requests to a local python script which constructs conversation context from slack threads, relays the requests over to Bedrock’s hosted instance of Claude Sonnet v3, and relays the responses back to a slack thread.

That’s a lot, so here’s a picture of what is going on so far:

And we’re going to update our architecture to no longer rely on a single server - we’re going to deploy our python application on an AWS Lambda serverless resource, and give it IAM permissions to do whatever it needs (no keys or static passwords on the AWS side), and then we’ll update our Slack App to send webhooks to lambda.

We’re also going to implement Bedrock Guardrails, which can police the inputs and outputs for our model to control some of the worst hallucinations the model might produce.

All of these changes will be implemented using terraform, and you can absolutely use a CI/CD solution to track changes to your application, and deploy on merge.

This entire solution is built for enterprise resiliency and deployment

All the python, terraform, and binary ARM dependency layers are provided in the GitHub repo here:

github.com/KyMidd/SlackAIBotServerless

Feel free to go check it out and deploy it all you want! This article will talk through the how and why of putting this local application into lambda.

With all that said, lets get started building our AWS lambda, IAM, and Bedrock resources in AWS, and then we’ll go over the python changes required to support lambda.