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February 10, 2024

GSA RAG
An AI-powered context-aware recommendation system for the GSA Elibrary2.0.
Tags:
#nextjs #react #typescript #javascript #nodejs #tailwindcss #python #numpy #pandas #docker #tensorflow #pytorch #huggingface #claudellm #pineconedb #fastapi #ai #linux #ubuntu #nginx #vercel #web #git #github #azuredevops #amazonaws #amazons3

Introduction

GSA Elibrary2.0 RAG is an AI-powered context-aware recommendation system for the GSA Elibrary2.0. It is built with Next.js, TypeScript, TailwindCSS, and ClaudeLLM on the frontend, and Python, TensorFlow, FastAPI, and PineconeDB on the backend. The app is hosted on Vercel and the API is hosted on an Ubuntu server with Nginx.