Welcome to the AWS First Generative AI Journey repository! This project serves as a comprehensive resource for individuals and organizations looking to explore the transformative capabilities of Generative AI using Amazon Web Services (AWS).

Seamlessly invoke Amazon Bedrock or your custom models, enabling a smooth experience with AWS GenAI services.

AWS Well-Architected Framework Review (WAFR) Acceleration with Generative AI (GenAI) sample.

How to build a chat assistant with Amazon Bedrock using LLMs, Embeddings model, and Knowledge Bases for Amazon Bedrock.

How to build an advanced RAG router based assistant with Amazon Bedrock using LLMs, Embeddings model, and Knowledge Bases for Amazon Bedrock.

Samples using AWS Terraform modules to accelerate your Infrastructure-as-Code deployments for generative AI workloads.

How to build a simplified Corrective RAG assistant with Amazon Bedrock using LLMs, Embeddings model, Knowledge Bases for Amazon Bedrock, and Agents for Amazon Bedrock.

Sample solution to automate tedious regulatory compliance processes using multi-agent systems

This repository contains sample code demonstrating how to implement a verified semantic cache using Amazon Bedrock Knowledge Bases to prevent hallucinations in Large Language Model (LLM) responses while improving latency and reducing costs.

Code samples to build AIML apps on AWS

How to build a backup assistant using AI agents on Amazon Bedrock.

A simple web application that provides Generative AI chat functionality using Amazon Bedrock with Retrieval-Augmented Generation (RAG) capabilities through Bedrock Knowledge Base.