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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.

From the code, we managed to generate a rectangular card with a play button (images sourced from Unsplash). Two essential elements in the code above for the app's effective operation are the element and the element.

In the root of your project, create a new folder called images and add some images. You can use the images from the example project on GitHub or you can find license free images on unsplash.

Reference links: Unsplash, Pexels, Burst, The Stocks, Pixabay

Images are sourced from Unsplash.

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Since I wanted to have thumbnails for each post (the file it uses is defined by the thumbnail field in the front matter), I decided to add some code that copies the files from our posts folder to the assets folder in Angular. This way, we can easily reference them in our Angular code. However, some of the image files I would download from Unsplash.com (fantastic public domain images btw) were huge and would take a few seconds to load in the browser. So, I delegated this task to gulp, where the files would first be piped to imagemin and then copied to the assets folder. This optimized the images for faster load times. My gulpfile.mjs looks like this:

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