This solution provides a web-based dashboard for building, experimenting with, and deploying generative AI applications on AWS, targeting users from novice to experienced. It simplifies the integration of Large Language Models (LLMs) via Amazon Bedrock and SageMaker, enabling rapid prototyping and productionization of use cases like chatbots querying enterprise data.

How It Works

The solution leverages AWS services like CloudFront, API Gateway, Lambda, Cognito, and DynamoDB to create a scalable and secure platform. It uses LangChain for LLM orchestration and allows for multi-LLM comparison with metric tracking via CloudWatch. Deployments are managed through nested CloudFormation stacks, offering a modular and extendable architecture.

Quick Start & Requirements

• Deployment: One-click deployment via AWS Console or using AWS CDK.
• Prerequisites: Node.js (20.x), Python (3.13.x), Docker, AWS CLI, jq. AWS account with access to Amazon Bedrock models.
• Setup: Detailed implementation guide available.

Highlighted Details

• Supports chat use cases with enterprise data querying and agent-based interactions.
• Modular architecture using nested CloudFormation stacks for extensibility.
• Enables multi-LLM comparison and experimentation with metric tracking.
• Offers VPC-enabled deployment options for enhanced security.

Maintenance & Community

• Actively maintained by AWS Solutions.
• Links to implementation guide, source code, and contribution guidelines are provided.

Licensing & Compatibility

• Licensed under the Apache License, Version 2.0.
• Permits commercial use and integration with closed-source applications.

Limitations & Caveats

• Amazon Bedrock model availability requires prior access requests.
• Deployed use cases have regional availability restrictions; consult the implementation guide for details.