AWS Generative AI CDK Constructs are sample implementations of AWS CDK for common generative AI patterns.

Chainlit application built using AWS CDK, secured with Amazon Cognito, that allows you to interact with Anthropic's Claude language models from Amazon Bedrock.

Simple Streamlit application used for demonstrating Anthropic Claude 3 family of model's multimodal prompting on Amazon Bedrock

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models

Explore sample applications and tutorials demonstrating the prowess of Amazon Bedrock with Python. Learn to integrate Bedrock with databases, use RAG techniques, and showcase experiments with langchain and streamlit.

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

Labs for the "Build an agentic LLM assistant on AWS" workshop. A step by step agentic llm assistant development workshop using serverless three-tier architecture.

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS

Uncovering Hidden Connections in Unstructured Financial Data using Amazon Bedrock and Amazon Neptune

This repo provides sample generative AI stacks built atop the AWS Generative AI CDK Constructs.

Prototyping Generative AI Use Cases with Amazon Bedrock and Langchain

Artificial Intelligence Infrastructure-as-Code Generator.

LLM-powered document chat using Amazon Bedrock and AWS Serverless

Multimodal saree search app built using Amazon Titan Multimodal Embeddings model

Function calling using Amazon Bedrock with Anthropic Claude 3 foundation model

'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker

Creating Amazon Bedrock agents with Streamlit Framework

A solution that harnesses the power of Generative AI to streamline the user onboarding process for financial services through a digital assistant.

The Build with AWS app simplifies selecting from over 200 AWS services by analyzing project details and recommending tailored solutions. It provides step-by-step integration guidance and features AI-driven recommendations, real-time chat support, and curated AWS resources.

Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.