amazon-bedrock-with-builder-and-command-patterns VS supabase

The second service is what’s going to make our application come alive and give it the AI functionality we need and that service is AWS Bedrock which is their new generative AI service launched in 2023. AWS Bedrock offers multiple models that you can choose from depending on the task you’d like to carry out but for us, we’re going to be making use of Meta’s Llama V2 model, more specifically meta.llama2-70b-chat-v1.

Amazon Bedrock

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon. Each model is accessible through a common API which implements a broad set of features to help build generative AI applications with security, privacy, and responsible AI in mind.

For those keeping track, Amazon Bedrock became generally available in September of 2023. My team had access to a preview, so when the AWS Comprehend entity analysis did not lend itself well to my use case; and I didn't feel like training a model, I started to get familiar with Bedrock. The following post is a follow-on to the Community article above and fleshes out a few details that will help those newer to Amazon Bedrock navigate the product.

In this blog you will learn how to use Amazon Cognito credentials and IAM Roles to invoke Amazon Bedrock API in a react-based application with JavaScript and the CloudScape design system. You will deploy all the resources and host the app using AWS Amplify.

Working with the AWS Bedrock API is an exhilarating experience! I came across an interesting business case where I needed to develop an AI MVP. The MVP generates JSON data based on a prompt and utilizes the anthropic.claude-v2:1 model in AWS Bedrock.

It was a great experience using Supabase’s rock-solid PostgreSQL database for this app. The DX around that product is phenomenal: viewing and managing the DB data was a lifesaver when you don’t want to craft your own admin panel from scratch.

I didn't really give much thought as to which backend I would use. I already had 2 projects in Supabase (BOXCUT & MineWork), but also a few projects in Firebase too. I was more concerned at the time at actually building the product.

Sign up for SupaBase: Head over to SupaBase and sign up. Create a new workspace and project with your preferred names.

Setting up Supabase Create a new Supabase project, and get the connection string for the database from settings > database.

Supabase (start for free)

Built with Supabase, Astro, Unreal Speech, Stable Diffusion, Replicate, Metropolitan Museum of Art

Supabase will be used for storing article data in the database and the cover image of the article in storage. Chakra UI will be used to provide style to the elements. By using both, we can build the blog with ease.

For AutoRepurpose, I opted for Supabase as the backbone of the backend. It has reliably supported Penelope AI, which garnered over 15k users in 2022 without any issues.

Semantic search demo

1. Create a new Supabase project: Visit Supabase and create a new project.