Augment-It Monorepo
Vision
To use AI Web Research , Large Language Models, and AI Powered Data Capture to augment basic data sets. These augmentations will need a workflow that involves a set of tools, each with their own purpose as part of the multi-step workflow.
Microservices and Microfrontends Architecture
Each one of the steps of the data augmentation workflow can be thought of as its own application, as it should.
We need to use Docker and Module Federation, and because React goes with NEXT.js, and NEXT.js needs Vite,
Tech Stack Considerations
TypeScript, WebSockets or REST APIs for communication with microfrontend and other services, and a suitable database (like PostgreSQL or MongoDB) for storage.
- Module FederationWe will use Module Federation to share components and logic between the main app and the Microfrontends. This approach allows us to maintain a modular architecture while enabling seamless interaction between parts of the system.
- Key Implementation Details:
- Define shared providers (like AI search model, web crawler, or CRM data access) that can be consumed by both the main application and the Prompt Manager microfrontend.
- Implement communication patterns (e.g., using Events or Remote Procedure Calls) to facilitate interaction between federation providers.
Version 1
The MainContainerUI is a Front-End that enables users to work through various Microfrontends as part of a Data Augmentation Workflow.
Open Questions
How to share API Keys and other secure info.