.github/workflows | ||
dist | ||
node_modules | ||
.gitignore | ||
action.yml | ||
demo.gif | ||
LICENSE.md | ||
package.json | ||
README.md |
Safe space - Github action
Github action that uses machine learning to detect potential toxic comments added to PRs and issues so authors can have a chance to edit them and keep repos a safe space.
It uses the Tensorflow.js toxicity classification model.
It currently works when comments are posted on issues and PRs, as well as when pull request reviews are submitted.
Demo
You can check this example PR
How to use
If you do not have any Github action already set up in your repo, start by creating a .github/workflows folder.
Inside your workflows folder, create a new .yml file, for example main.yml
and copy the following lines:
on: [issue_comment, pull_request_review]
jobs:
toxic_check:
runs-on: ubuntu-latest
name: Safe space
steps:
- uses: actions/checkout@v2
- name: Safe space - action step
uses: charliegerard/safe-space@master
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_TOKEN
is required but two other parameters are optional:
message
- a custom message you'd like to display in the automatic commenttoxicity_threshold
- a float number between 0 and 1. It will be used when loading the machine learning model. Its default value is 0.9.
on: [issue_comment, pull_request_review]
jobs:
toxic_check:
runs-on: ubuntu-latest
name: Toxicity check
steps:
- uses: actions/checkout@v2
- name: Safe space - action step
uses: charliegerard/safe-space@master
with:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
message: "this is my custom message"
toxicity_threshold: 0.7
The action can take up to 40s to run so if you are testing it out in your repository, keep in mind that the bot will not display right after a toxic comment is posted.