Steam Similarity Recommender [P]

Developer u/Expensive-Ad8916 launched NextSteamGame, a Steam game recommender that ditches broad tags like 'action' for granular gameplay vectors. The system pulls 2,000 reviews per game (from 80,000 Steam titles), filters them for vibe/structure descriptors, then uses ChatGPT to generate vectors (e.g., '20% day cycle, 20% social sim') and micro-tags (e.g., 'Music: jazz fusion'). A 6-stage pipeline groups similar tags (e.g., 'speedy action combat' = 'fast combat'), storing everything in PostgreSQL + ChromaDB. The frontend, built with React and hosted in a Docker container on DigitalOcean, lets users see *why* they’re recommended games—like why Balatro’s deck-building synergies appeal to them over its rogue-like nature.

The project shines by avoiding collaborative filtering’s echo-chamber effect, instead surfacing underrated gems tied to specific preferences. Users can toggle an 'advance mode' to tweak sliders for granular control. The open-source code (PRs welcome!) and live demo at nextsteamgame.com demonstrate how vector-based recommendations can make discovery more intuitive—and fun—than rigid tag systems.