app | ||
arena | ||
config | ||
Data | ||
fay | ||
fay-shared | ||
geval@2dbcedb40e | ||
Gonito | ||
Handler | ||
helpers/gitolite | ||
Import | ||
messages | ||
misc | ||
Settings | ||
sql-scripts | ||
static | ||
templates | ||
test | ||
Web | ||
.dir-locals.el | ||
.dockerignore | ||
.ghci | ||
.gitignore | ||
.gitlab-ci.yml | ||
.gitmodules | ||
add-variants.sql | ||
add-versions.sql | ||
Application.hs | ||
build.sh | ||
CHANGELOG.md | ||
docker-compose-simple.yml | ||
docker-compose.yml | ||
Dockerfile | ||
fix-out.sql | ||
Foundation.hs | ||
gonito.cabal | ||
gpl-3.0.txt | ||
Import.hs | ||
Model.hs | ||
nginx.conf | ||
pack.sh | ||
PersistEvaluationScheme.hs | ||
PersistMetric.hs | ||
PersistSHA1.hs | ||
PersistTeamActionType.hs | ||
README.md | ||
sample.env | ||
Settings.hs | ||
stack.yaml |
Gonito platform
Gonito (pronounced ɡɔ̃ˈɲitɔ) is a Kaggle-like platform for machine learning competitions (disclaimer: Gonito is neither affiliated with nor endorsed by Kaggle).
What's so special about Gonito:
- free & open-source (GPL), you can use it your own, in your company, at your university, etc.
- git-based (challenges and solutions are submitted only with git).
See the home page (and an instance of Gonito) at https://gonito.net .
Installation
For development
Gonito is written in Haskell and uses Yesod Web Framework, but all you need is just the Stack tool. See https://github.com/commercialhaskell/stack for instruction how to install Stack on your computer.
By default, Gonito uses Postgresql, so it needs to be installed and running at your computer.
After installing Stack:
createdb -E utf8 gonito # Postgres needs to be configured
git clone --recurse-submodules git://gonito.net/gonito
cd gonito
stack setup
# before starting the build you might need some non-Haskell dependencies, e.g. in Ubuntu:
# sudo apt-get install libbz2-dev liblzma-dev libpcre3-dev libcairo-dev libfcgi-dev
stack build
stack exec yesod devel
The last command will start the Web server with Gonito (go to http://127.0.0.1:3000 in your browser).
With docker-compose
The easiest way to run Gonito is with docker-compose.
git clone --recurse-submodules https://gitlab.com/filipg/gonito
cd gonito
cp sample.env .env
# now you need to edit .env manually,
# in particular, you need to set up the administrator's
# password and paths to volumes for the volumes,
# cloned data ("arena"), certificates and SSH data;
# also you need to set up your certificate
# here is an easy way to do it just for local
# testing
mkdir certs
cd certs
# generating certificates for HTTPS, remember to
# set the `NGINX_CERTIFICATE_DIR` variable in `.env`
# so that it would point to `certs` here
openssl req -x509 -newkey rsa:4096 -keyout privkey.pem -out fullchain.pem -days 365 -nodes
cd ..
docker-compose up
Gonito will be available at https://127.0.0.1/. Of course, your browser will complain about "Potential Security Risk" as these are local certificates.
Gonito as backend
On the one hand, Gonito is a monolithic Web application without front-
and back-end separated. On the other, some features are provided as
end-points, so that Gonito could be used with whatever front-end. The
documentation in the Swagger format is provided at /static/swagger-ui/index.html
.
(see https://gonito.net/static/swagger-ui/index.html for this at the main instance).
Keycloak is assumed as the identity provider here for those end-points that require authorization.
Asynchronous jobs
Some tasks (e.g. evaluating a submitted solution, creating a challenge) can take more time, so they must be run in a asynchronous manner. End-points for such actions return a job ID (a number). There are two options to show the logs:
- The front-end can show the logs using web sockets, see https://gitlab.com/filipg/gonito/-/blob/master/static/test-gonito-as-backend.html#L133 for an example.
- The front-end can just redirect the user to
/api/view-progress-with-web-sockets/jobID
, where showing the logs will be handled directly by Gonito (no authorization is needed there).
It's recommended to test showing logs with the test end-point
/api/test-progress/N/D
, which just counts up to N with a D-second delay
(e.g. /api/test-progress/10/2
).
Integration with Keycloak
Gonito can be easily integrated with Keycloak for the back-end end-points (but not yet for signing in Gonito as the monolithic Web application, this feature is on the way).
-
Let's assume that you have a Keycloak instance. A simple way to run for development and testing is:
docker run -e KEYCLOAK_USER=admin -e KEYCLOAK_PASSWORD=admin -p 8080:8080 jboss/keycloak
. -
You need to set up the JWK key from your Keycloak instance. Go to
https://<KEYCLOAK-HOST>/auth/realms/<KEYCLOAK-REALM>/protocol/openid-connect/certs
(e.g. for the Docker run as given in (1): http://127.0.0.1:8080/auth/realms/master/protocol/openid-connect/certs) and copy the contents of the key from the JSON the (key/0 element not the whole JSON!). -
Create
gonito
client in Keycloak (Clients / Create). -
Set Valid Redirect URIs for the
gonito
client in Keycloak (e.g. simply add*
there). -
Set Web Origin for the
gonito
client in Keycloak (e.g. simply add*
there). -
Add some test user, set up some first/last name for them.
-
Set
JSON_WEB_KEY
variable to the content of the JWK key (orGONITO_JSON_WEB_KEY
when using docker-compose) and run Gonito.
If you create a new user, you need to run /api/add-info
GET
end-point. No parameters are needed it just read the user's data from
the token and adds a record to the Gonito database.
You can simulate a front-end by going to /static/test-gonito-as-backend.html
.
Menuless mode
If you want to combine an external front-end with some features of the
Gonito native front-end, you can run Gonito in a menuless mode
setting MENULESS
to true
. This way, you will not show all the
functions of native Gonito.
Gonito & git
Gonito uses git in an inherent manner:
- challenges (data sets) are provided as git repositories,
- submissions are uploaded via git repositories, they are referred to with git commit hashes.
Advantages:
- great flexibility as far as where you want to keep your challenges and submissions (could be external, well-known services such as GitHub or GitLab, your local git server, let's say gitolite or Gogs, or just a disk accessible in a Gonito instance),
- even if Gonito ceases to exist, the challenges and submissions are still available in a standard manner, provided that git repositories (be it external or local) are accessible,
- data sets can be easily downloaded using the command line
(e.g.
git clone git://gonito.net/paranormal-or-skeptic
), without even clicking anything in the Web browser, - facilitates experiment repeatability and reproducibility (at worst the system output is easily available via git)
- tools that were used to generate the output could be linked as git subrepositories
- some challenge/submission metadata are tracked in a Gonito-independent way (within git commits),
- copying data can be avoided with git mechanisms (e.g. when the challenge is already cloned, downloading specific submissions should be much quicker),
- large data sets and models could be stored if needed using mechanisms such as git-annex (see below).
Commit structure
The following flow of git commits is recommended (though not required):
- the challenge without hidden data for main test sets (i.e. files such as
test-A/expected.tsv
) should be pushed to themaster
branch - the hidden files (
test-A/expected.tsv
) should be added in a subsequent commit and pushed either to thedont-peek
branch or amaster
branch of a separate repository (if access to the hidden data must be more strict), - the submissions should be committed with the
master
branch as the parent (or at least ancestor) commit and pushed to the same repository as the challenge data (in some user-specific branch) or any other repository (could be user-owned repositories) - any subsequent submissions could be derived in a natural way from other git commits (e.g. when a submission is improved, or even two approaches are merged)
- new versions of the challenge can be committed (a challenge can be updated at Gonito)
to the
master
(anddont-peek
) branches
See also the following picture:
git-annex
In some cases, you don't want to store challenge/submissions files simply in git:
- very large data files, textual files (e.g.
train/in.tsv
even if compressed astrain/in.tsv.xz
) - binary training/testing data (PDF files, images, movies, recordings)
- data sensitive due to privacy/security concerns (a scenario where it's OK to store metadata and some files in a widely accessible repository, but some files require limited access)
- large ML models (note that Gonito does not require models for evaluation, but still it might be a good practice to commit them along with output files and scripts)
Such cases can be handled in a natural manner using git-annex, a git extension for handling files and their metadata without commiting their content to the repository. The contents can be stored at a wide range of special remotes, e.g. S3 buckets, WebDAV, rsync servers.
It's up to you which files are stored in git in a regular manner and
which are added with git annex add
, but note that if a
challenge/submission file must be stored via git-annex and are required
for evaluation (e.g. expected.tsv
files for the challenge or
out.tsv
files for submissions), the git-annex special remote must be
given when a challenge is created or a submission is done and the
Gonito server must have access to such a special remote.
Integration with Slack/Discord
Gonito can send announcements to Slack or Discord via web hooks, e.g.
when new best result is achieved. Simply set the ANNOUNCEMENT_HOOK
environment variable to a Slack/Discord webhook.
Authors
- Filip Graliński
References
@inproceedings{gralinski:2016:gonito,
title="{Gonito.net - Open Platform for Research Competition, Cooperation and Reproducibility}",
author={Grali{\'n}ski, Filip and Jaworski, Rafa{\l} and Borchmann, {\L}ukasz and Wierzcho{\'n}, Piotr},
booktitle="{Branco, Ant{\'o}nio and Nicoletta Calzolari and Khalid Choukri (eds.), Proceedings of the 4REAL Workshop: Workshop on Research Results Reproducibility and Resources Citation in Science and Technology of Language}",
pages={13--20},
year=2016,
url="http://4real.di.fc.ul.pt/wp-content/uploads/2016/04/4REALWorkshopProceedings.pdf"
}