Gorse AI-Powered Open Source Recommender System Engine

Gorse is an AI-powered open-source recommender system written in Go that generates personalized recommendations via collaborative filtering, item-to-item similarity, and LLM-based ranking. It provides RESTful APIs and a GUI dashboard for recommendation pipeline editing, system monitoring, and data management.

Installation

Use the upstream install or setup path that matches your environment:

• docker run -p 8088:8088 zhenghaoz/gorse-in-one --playground

Requirements and caveats from upstream:

• Gorse is a single-node training and distributed prediction recommender system. Gorse stores data in MySQL (MariaDB), MongoDB, Postgres, or ClickHouse, with intermediate results cached in Redis, MySQL (MariaDB), MongoD...
• The cluster consists of a master node, multiple worker nodes, and server nodes.
• The master node is responsible for model training, non-personalized recommendation, configuration management, and membership management.

Basic usage or getting-started notes:

• The playground mode has been prepared for beginners. Just set up a recommender system for GitHub repositories by the following commands.

• bash

• The playground mode will download data from GitRec and import it into Gorse. The dashboard is available at http://localhost:8088.

• Source: https://github.com/gorse-io/gorse

• Extracted from upstream docs: https://raw.githubusercontent.com/gorse-io/gorse/HEAD/README.md

Source

• Agent Skill Exchange