Popular GitHub Repositories for Cdk

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

Generative AI tool for evaluating Infrastructure as Code and architecture diagrams against AWS Well-Architected best practices.

Build Generative AI applications with Langchain on AWS

An agent based LLM assistant that extends RAG with batch entity extraction and SQL querying to improve performance on multi-step and analytical questions.

Opinionated sample on how to build/deploy a RAG web app on AWS powered by Amazon Bedrock and PGVector (on Amazon RDS)

Personalized nutritional app, serverless, tailored to your shopping and cooking needs, empowered by generative AI technology (Amazon Bedrock, Anthropic, Claude Haiku, Claude Sonnet) using AWS CDK on AWS

This repository provides AI/ML service(MachineLearning model serving) modernization solution using Amazon SageMaker, AWS CDK, and AWS Serverless services.

This repository features three demos that can be effortlessly integrated into your AWS environment. They serve as a practical guide to leveraging AWS services for crafting a sophisticated Large Language Model (LLM) Generative AI, geared towards creating a responsive Question and Answer Bot and localizing content generation.

Opinionated sample on how to build and deploy a RAG application with Amazon Bedrock and OpenSearch

This repository contains the code and infrastructure as code for a Generative AI-powered Request for Proposal (RFP) Assistant leveraging Amazon Bedrock and AWS Cloud Development Kit (CDK).

MLOps Pipeline Using SageMaker & CDK, where models are from SageMaker built-in algorithms.

MLflow on AWS Fargate integrated with Amazon SageMaker.

This application is built in four stages using infrastructure as code with CDK with Python to deploy. In the first stage, an Amazon Aurora PostgreSQL vector database is set up. In the second stage, the Knowledge Base for Amazon Bedrock is created using the established database. The third stage involves creating an Amazon

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

This project simplifies personalized Gen-AI SaaS apps. We fine-tune pre-trained models for users, use single GPUs, and ensure real-time responsiveness. A base txt2img Stable Diffusion model from SageMaker JumpStart is used. Challenges include traffic spikes, low-latency, and cost-efficiency. We aim for efficient, user-centric AI solutions.

CDK project to build AWS Serverless AI Agent with Lambda and Step Functions.

A pipeline to convert contextual knowledge stored in documents and databases into text embeddings, and store them in a vector store

Blueprint for running AWS Bedrock Multi-Agent AI collaboration with CDK, Streamlit and LangFuse

It shows advanced RAG and 4 design patterns of agentic workflow based on LangChain and LangGraph using Amazon Nova Pro.

The project shows how to develop an interactive chatbot using Lex and open APIs. Lex provides operations using User Intent but it may response the dupulicated answers for unknown intents. Thus the proposed architecture uses Open APIs such as ChatGPT.