Similarity Product Engine for Ecommerce

A vector similarity search engine for e-commerce products. Instead of searching products by keyword, it represents every product as a numeric vector (price, rating, number of reviews, category) and uses FAISS — Facebook's library for fast vector search — to find the products whose vectors are closest to a query. You set filters (category, price, minimum rating, review count, how many results you want), and it returns the most similar products ranked by vector distance and a similarity percentage, instead of just filtering a table.