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How to use Gorse: what you can do with it

What is Gorse? Gorse is an open-source recommender system engine written in Go. You import items, users and feedback, and it trains models and serves recommendations from latest, user-to-user, item-to-item and collaborative filtering sources through RESTful APIs, with a GUI dashboard for pipeline editing, monitoring and data management.

How do I use it? Start the playground with docker run -p 8088:8088 zhenghaoz/gorse-in-one --playground; then open the dashboard at http://localhost:8088; wait for the Generate item-to-item recommendation task to complete on the Tasks page. Full steps below.

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What do you want to do?

3 use cases

Quick start with Gorse

  1. Check you have what it needs: Docker for the gorse-in-one image; curl or any HTTP client for the REST API; For production: MySQL (MariaDB), MongoDB or Postgres for storage, with a cache such as Redis.
  2. Open gorse-io/gorse on GitHub and read the README and license.
  3. Start the playground with docker run -p 8088:8088 zhenghaoz/gorse-in-one --playground
  4. Open the dashboard at http://localhost:8088
  5. Wait for the Generate item-to-item recommendation task to complete on the Tasks page
  6. Browse items, users and recommendations in the dashboard

These steps come from our top use case, Spin up a working recommender in one command, which also has a copy-paste agent prompt.

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About this repo

  • Who it is forDevelopers adding recommendations to a product who would rather run a service than build a model pipeline.
  • Why it is hot9.9k stars, talked about in 2 AI sources we track
  • LanguageGo
  • Sourcegithub.com/gorse-io/gorse ยท Back to Hot repos

Requirements

  • Docker for the gorse-in-one image
  • curl or any HTTP client for the REST API
  • For production: MySQL (MariaDB), MongoDB or Postgres for storage, with a cache such as Redis

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Questions about Gorse

What is Gorse?

Gorse is an open-source recommender system engine written in Go. You import items, users and feedback, and it trains models and serves recommendations from latest, user-to-user, item-to-item and collaborative filtering sources through RESTful APIs, with a GUI dashboard for pipeline editing, monitoring and data management. It is an open-source project on GitHub: https://github.com/gorse-io/gorse.

How do I use Gorse?

Start the playground with docker run -p 8088:8088 zhenghaoz/gorse-in-one --playground; then open the dashboard at http://localhost:8088; wait for the Generate item-to-item recommendation task to complete on the Tasks page. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is Gorse for?

Developers adding recommendations to a product who would rather run a service than build a model pipeline.

What can I do with Gorse?

3 use cases so far, for example: Spin up a working recommender in one command; Feed user behavior into recommendations over REST; Fetch personalized recommendations for a user. Each has steps and a copy-paste agent prompt.

What do I need to run Gorse?

Docker for the gorse-in-one image; curl or any HTTP client for the REST API; For production: MySQL (MariaDB), MongoDB or Postgres for storage, with a cache such as Redis.

What are alternatives to Gorse?

Other hot AI repos in Data and analytics: Chronos Forecasting, Apify MCP Server, Crawlee Python, DLT, Timesfm.

Is Gorse safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.