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Deploying a Multi-Model and Multi-RAG Powered Chatbot Using AWS CDK on AWS

Release Notes GitHub star chart License: MIT

Deploy with GitHub Codespaces

Full Documentation

sample

🚀 NEW! Support for new Amazon Nova Models 🚀

Deploy this chatbot to use the recently announced Amazon Nova models!

These powerful models can understand and generate images and videos.

Deploy this chatbot to experiment with:

  • Amazon Nova Micro
  • Amazon Nova Lite
  • Amazon Nova Pro
  • Amazon Nova Canvas
  • Amazon Nova Reels

Make sure to request access to the new models here

Read more about the new models here


This solution provides ready-to-use code so you can start experimenting with a variety of Large Language Models and Multimodal Language Models, settings and prompts in your own AWS account.

Supported model providers:

Additional Resources

Resource Description
Secure Messenger GenAI Chatbot A messenger built on Wickr that can interface with this chatbot to provide Q&A service in tightly regulated environments (i.e. HIPAA).
Project Lakechain A powerful cloud-native, AI-powered, document (docs, images, audios, videos) processing framework built on top of the AWS CDK.
AWS Generative AI CDK Constructs Open-source library extension of the AWS Cloud Development Kit (AWS CDK) aimed to help developers build generative AI solutions using pattern-based definitions for their architecture.
Artifacts and Tools for Bedrock An innovative chat-based user interface with support for tools and artifacts. It can create graphs and diagrams, analyze data, write games, create web pages, generate files, and much more.

Roadmap

Roadmap is available through the GitHub Project

Authors

Contributors

contributors

License

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

Although this repository is released under the MIT-0 license, its front-end and SQL implementation use the following third party projects:

These projects' licensing includes the LGPL v3 and BlueOak-1.0.0 licenses.

Legal Disclaimer

You should consider doing your own independent assessment before using the content in this sample for production purposes. This may include (amongst other things) testing, securing, and optimizing the content provided in this sample, based on your specific quality control practices and standards.