LEDAA Chat Interface

LEDAA project is about building a conversational AI assistant for FRAGMENT (documentation). Towards this purpose, the LEDAA Chat Interface is a web-based conversational interface that allows users to interact with the LEDAA conversational AI assistant.

This project demonstrates a conversational AI assistant that can help answer queries related to FRAGMENT (documentation).

Main priority for this prototype is to demonstrate an AI assistant for FRAGMENT' documentation and to present a Retrieval Augmented Generation (RAG)-based pipeline and workflow with automation for handling source data updates to ensure AI assistant can answer user queries related to the documentation effectively and accurately.

To learn more check: Building AI Assistant for FRAGMENT documentation

LEDAA Data Process Flow

Below is the process flow for how ground truth data updates are handled and how the knowledge base is effectively updated.

1. ledaa_updates_scanner Lambda function monitors for changes in content of documentation.
2. On detecting changes, it triggers the ledaa_load_data Lambda function passing it the URL of webpage.
3. ledaa_load_data Lambda function invokes the ledaa_text_splitter Lambda function to initiate the process of scraping data from a given URL and to get a list of strings (representing text chunks or documents) which will be used in data ingestion.
4. ledaa_text_splitter Lambda function invokes the ledaa_web_scrapper Lambda function to scrape the URL and store the processed markdown data in S3. ledaa_web_scrapper function also stores the hash of the processed data in DynamoDB which will later be compared by ledaa_updates_scanner function to detect changes.
5. On receiving processed document chunks back, ledaa_load_data Lambda function stores the data in the vector store.

This is a Next.js project bootstrapped with create-next-app.

Local Development

First, run the development server:

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

You can start editing the page by modifying app/page.tsx. The page auto-updates as you edit the file.

This project uses next/font to automatically optimize and load Geist, a new font family for Vercel.

LICENSE

This project is licensed under the MIT License - see the LICENSE file for details.