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gen-ai-workshop's Introduction

Building with Generative AI on AWS using PartyRock, Amazon Bedrock, and Amazon Q

This workshop is designed for builders ready to learn about Generative AI on AWS. You'll learn to develop applications using PartyRock and Amazon Bedrock. You will focus on practical skills like prompt engineering and using different foundational models. We will also explore how to 'chat with your documents' through knowledge bases, retrieval augmented generation (RAG), embeddings, and agents. Additionally, you'll discover how to use Amazon Q Developer to assist in coding and debugging.

Amazon Q

In this workshop you will complete the following 3 modules:

  1. Build Generative AI Applications with PartyRock: Learn how to quickly build generative AI applications with no code.

  2. Use Foundation Models in Amazon Bedrock: Learn how to use various foundation models to generate text and images using Amazon Bedrock.

  3. Chat with your Documents: Learn how to use Amazon Bedrock to "Chat with your documents". We will explore how to build RAG applications highlighting knowledge bases, embeddings, and agents.

This is a 300 level workshop, so some familiarly with using services such as AWS Lambda and writing Python code is helpful. No AI/ML experience is necessary. This workshop is intended to be finished within 2 hours.

Here is the link to the workshop

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

gen-ai-workshop's People

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gen-ai-workshop's Issues

kb_rag.py: Getting an error with RetrieveAndGenerate operation

Hello, I created an S3 bucket and a knowledge base on top of it, with pdf documents uploaded into the S3 bucket. I followed the exact code in kb_rag.py; Only difference is I used llama3 model instead of claude-3 sonnet. I'm getting an error: "botocore.errorfactory.ValidationException: An error occurred (ValidationException) when calling the RetrieveAndGenerate operation: The model arn provided is not supported. Please check your configuration and retry the request."

I've attached the screenshot of the issue for reference. Is there anything I can do to resolve this?
error

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