Stack Vector Product Vector

GitHub Repo https://github.com/hoangsonww/MERN-Stack-Ecommerce-App

hoangsonww/MERN-Stack-Ecommerce-App

🛒 Welcome to Fusion Electronics - a sample full-stack, lightweight, and modern online e-commerce application, built with the MERN (MongoDB, Express, React, Node.js) stack! Also features a product recommendation service using vector search, FAISS, and the Weaviate/Pinecone vector DB!

GitHub Repo https://github.com/redis-developer/redis-product-search

redis-developer/redis-product-search

Visual and semantic vector similarity with Redis Stack, FastAPI, PyTorch and Huggingface.

GitHub Repo https://github.com/Farasat123/E-Commerce-Website-Advanced-

Farasat123/E-Commerce-Website-Advanced-

Welcome to Fusion Electronics - a sample full-stack, lightweight, and modern online e-commerce application, built with the MERN (MongoDB, Express, React, Node.js) stack! Also features a product recommendation service using vector search, FAISS, and the Weaviate/Pinecone vector DB!

GitHub Repo https://github.com/Muke1706/AI-Visual-Search-Engine

Muke1706/AI-Visual-Search-Engine

A full-stack app that finds visually similar fashion products using vector embeddings and cosine similarity.

GitHub Repo https://github.com/mohammedanasa/rag-production-app

mohammedanasa/rag-production-app

A minimal RAG stack that ingests PDFs, chunks them, embeds with Google GenAI, stores vectors in Qdrant, and answers questions using an Inngest workflow.

GitHub Repo https://github.com/Kietnehi/RAG

Kietnehi/RAG

RAG Project: Full-stack solution for VQA, image captioning, and RAG, supporting open-source LLMs from Microsoft, Google, Meta, Alibaba, with API & Gemini real-time search, using ChromaDB for vector database, and Docker for fast deployment in research, PoC, and product development.

GitHub Repo https://github.com/Lostovayne/sistema-de-filtrado-de-productos-full-stack

Lostovayne/sistema-de-filtrado-de-productos-full-stack

Este proyecto es un sistema de filtrado de productos eficiente y moderno, utilizando tecnologías de punta para ofrecer una experiencia de usuario fluida y rápida. Implementado con Next.js 14 y estilizado con Tailwind CSS, el proyecto aprovecha las capacidades de Upstash para manejar una base de datos de vectores, permitiendo búsquedas y filtros.

GitHub Repo https://github.com/angeloortega/VectCalc