Amazon Bedrock Samples
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This repository contains pre-built examples to help customers get started with the Amazon Bedrock service.
Contents
- Introduction to Bedrock - Learn the basics of the Bedrock service
- Prompt Engineering - Tips for crafting effective prompts
- Agents - Ways to implement Generative AI Agents and its components.
- Custom Model Import - Import custom models into Bedrock
- Multimodal - Working with multimodal data using Amazon Bedrock
- Generative AI Use cases - Example use cases for generative AI
- Retrival Augmented Generation (RAG) - Implementing RAG
- Responsible AI - Use Bedrock responsibly and ethically
- Workshop - Example for Amazon Bedrock Workshop
- POC to Prod - Productionize workloads using Bedrock
- Embeddings - Learn how to use Embedding Models available on Amazon Bedrock
- Observability & Evaluation - Learn how Amazon Bedrock helps with improving observability and evalution of Models, Gen AI Applications.
Getting Started
To get started with the code examples, ensure you have access to Amazon Bedrock. Then clone this repo and navigate to one of the folders above. Detailed instructions are provided in each folder's README.
Enable AWS IAM permissions for Bedrock
The AWS identity you assume from your environment (which is the Studio/notebook Execution Role from SageMaker, or could be a role or IAM User for self-managed notebooks or other use-cases), must have sufficient AWS IAM permissions to call the Amazon Bedrock service.