asmuth/recommendify

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1649 stars · 145 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Recommendify is a Ruby/Redis-based recommendation engine that generates item-to-item recommendations using collaborative filtering. It processes user interaction data (e.g., user-item pairs) incrementally and across multiple hosts, with a worker implemented in plain Ruby and native C.

Use cases

• generate 'users who bought this also bought that' recommendations from purchase data
• recommend similar videos based on co-viewing behavior
• build item-to-item similarity matrices from user interaction sets
• compute jaccard-based recommendations incrementally in Ruby
• power product recommendations for an e-commerce site

When to choose

• you need item-to-item collaborative filtering in a Ruby stack
• your interaction data fits a co-concurrence model and you want Redis-backed incremental updates
• you want a lightweight, self-hosted recommender without heavy ML dependencies

When to avoid

• you need actively maintained software with a license and recent updates
• you need content-based or deep-learning recommendations
• your stack is not Ruby/Redis
• you need large-scale distributed training beyond simple co-concurrence

Facets

library · maturity abandoned

machine-learning search-engine caching machine-learning e-commerce data-science ruby collaborative-filtering recommendation-engine redis similarity-matrix jaccard linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="asmuth/recommendify")