Unleash the Power of Generative AI: Get Started with AWS Samples

Stuck on that first step with Generative AI? Don't worry, Amazon has you covered! The genai-quickstart-pocs repository on GitHub provides a treasure trove of sample code to jump-start your journey. It's definitely worth your star. 

This developer-friendly repository offers a collection of projects, each focusing on a specific use case for Generative AI and Amazon Bedrock. No more sifting through extensive documentation – each project is a dedicated directory with its own codebase, making it easy to understand and implement.

But wait, there's more! To streamline the development process, the repository includes a basic Streamlit frontend. This user-friendly interface allows you to quickly set up a proof-of-concept (POC) and experiment with the capabilities of Generative AI.

Here's a glimpse of what you can achieve with these samples (at the time of writing):

1. Amazon-Bedrock-Summarization-Long-Document-POC This sample demonstrates using Amazon Bedrock and Generative AI to implement a long document summarization use case. Users can upload large PDF documents, which are chunked and summarized using Amazon Bedrock.

2. Amazon-Bedrock-RAG-OpenSearchServerless-POC This sample demonstrates creating custom embeddings stored in Amazon OpenSearch Serverless, and answering questions against the indexed embeddings using a Retrieval-Augmented Generation (RAG) architecture with Amazon Bedrock.

3. Amazon-Bedrock-RAG-Kendra-POC This sample implements a RAG-based architecture with Amazon Kendra, allowing users to ask questions against documents stored in an Amazon Kendra index using Amazon Bedrock.

4. Amazon-Bedrock-Image-Generation-POC This sample demonstrates using Amazon Bedrock and Generative AI to generate images based on text input requests.

5. Amazon-Bedrock-GenAI-Dynamic-Prompting-Explained-POC This sample provides a hands-on explanation of how dynamic prompting works in relation to Generative AI, using Amazon Bedrock.

6. Amazon-Bedrock-Document-Generator This sample demonstrates using Amazon Bedrock and Generative AI to perform document generation based on a document template and user-provided details.

7. Amazon-Bedrock-Document-Comparison-POC This sample allows users to upload two PDF documents and get a list of all changes between them using Amazon Bedrock and Generative AI.

8. Amazon-Bedrock-Claude3-Multi-Modal-Sample This sample showcases the multi-modal capabilities of Amazon Bedrock (specifically Anthropic Claude 3), allowing users to input text questions, images, or both to get comprehensive descriptions or answers.

9. Amazon-Bedrock-Chat-POC This sample provides a ChatGPT alternative using Amazon Bedrock and Generative AI, allowing users to ask zero-shot questions and receive responses.

10. Amazon-Bedrock-Amazon-Redshift-POC This sample demonstrates using Amazon Bedrock and Generative AI to ask natural language questions and transform them into SQL queries against Amazon Redshift databases.

11. Amazon-Bedrock-Amazon-RDS-POC This sample allows users to ask natural language questions and transform them into SQL queries against Amazon RDS databases using Amazon Bedrock and Generative AI.

12. Amazon-Bedrock-Amazon-Athena-POC This sample demonstrates using Amazon Bedrock and Generative AI to ask natural language questions and transform them into SQL queries against Amazon Athena databases.

 

I wrote this post to serve as a bookmark for myself more than anything tbh :)