Recotem is an easy to use interface to recommender systems; Recotem can be launched on any platform with Docker. It ships with a Web-base UI, and you can train and (qualitatively) evaluate the recommendation engine solely using UI.
Recotem is licensed under Apache 2.0.
There are two ways to start using Recotem. Both requires latest docker.
- Visit latest release
- Download "Docker resources to try out" from Assets
- Unzip it and
- (Windows) Click "recotem-compose" script
- (Linux & MacOS) Run
docker-compose
there.docker-compose up`
See https://recotem.org/guide/installation.html for a friendlier introduction.
- Clone this repository.
- In the repository top directory, simply run
docker-compose up
To run the backend (and worker) in Django development mode, use docker-compose-dev.yml
.
docker-compose -f docker-compose-dev.yml build
docker-compose -f docker-compose-dev.yml up
To run the frontend webpack-dev-sever, you will need a descent version of yarn.
After yarn
under frontend/
directory to install the dependency, run
cd frontend
yarn serve
In order for the frontend to work with the API, you first have to launch the backend following the above instruction.
recotem-cli allows you to
- tune & train recommender systems
- obtain the recommendation result
via command-line interface.
There is an example project which uses recotem to batch-execute recommendation task on Amazon ECS.