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An API client for the Objective Revision Evaluation Service for Wikipedia

Home Page: https://ores.wikimedia.org/

License: Other

R 100.00%
api-client wikipedia mediawiki r

ores's Introduction

ORES API client

Travis-CI Build Status CRAN_Status_Badge downloads

ores provides an API client for the Objective Revision Evaluation Service; an AI system designed to identify whether edits to Wikimedia projects like Wikipedia are damaging, likely to be reverted, or made in good faith, and what class of quality the underlying article falls into.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

Use

library(ores)

# Check if an edit does damage
check_damaging("enwiki", 34854345)
#       edit project prediction false_prob true_prob
# 1 34854345  enwiki       TRUE  0.4381965 0.5618035

# Check edit quality
check_quality("enwiki", 34854345)
# edit    project prediction   stub_prob start_prob     c_prob   b_prob     ga_prob   fa_prob
# 34854345  enwiki         FA 0.001613388 0.01765724 0.02922814 0.2296085  0.009218907 0.7126738

Installation

ores can be obtained from CRAN with:

install.packages("ores")

The package also lives on GitHub; you can install it with:

devtools::install_github("ironholds/ores")

ores's People

Contributors

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Watchers

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Forkers

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ores's Issues

Migrate from ORES

Hi! I am part of the Wikimedia ML team, we are starting the migration of ORES client to another infrastructure, since we are planning to deprecate it. More info in https://wikitech.wikimedia.org/wiki/ORES

TL;DR:

The ORES infrastructure is being replaced by Lift Wing, a more modern and kubernetes-based service.
All the ORES models (damaging, goodfaith, etc..) are running on Lift Wing, more on how to use them in https://wikitech.wikimedia.org/wiki/Machine_Learning/LiftWing/Usage
We also have new models called Revert Risk, to replace goodfaith and damaging for example. They are available on Lift Wing, and we'd like to offer them as an alternative to ORES models. If you'd like to try them we'd help in the migration process!

In the meantime most of the features available in ores still work as ores.wikimedia.org points to temporary service which is intended to be deprecated in 2024. This service is designed to offer backward compatibility: it takes an ores requests and performs the appropriate LiftWing requests and then merges back the response to match the old ORES response.

Thanks in advance,

ML team

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