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Creating a release

Scispacy has two components:

  • The scispacy pip package
  • The scispacy models

The scispacy pip package is published automatically using the .github/actions/publish.yml github action. It happens whenever a release is published (with an associated tag) in the github releases UI.

In order to create a new release, the following should happen:

Updating scispacy/version.py

Update the version in version.py.

Training new models

For the release, new models should be trained using the scripts/pipeline.sh and scripts/ner_pipeline.sh scripts, for the small, medium and large models, and specialized NER models. Remember to export the ONTONOTES_PATH and ONTONOTES_PERCENT environment variables to mix in the ontonotes training data.

bash scripts/pipeline.sh small
bash scripts/pipeline.sh medium
bash scripts/pipeline.sh large
bash scripts/ner_pipeline.sh <path to medium base model>

these should then be uploaded to the https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/{VERSION} S3 bucket, and references to previous models (e.g in the readme and in the docs) should be updated. You can find all these places using git grep <previous version>.

Merge a PR with the above changes

Merge a PR with the above changes, and publish a release with a tag corresponding to the commit from the merged PR. This should trigger the publish github action, which will create the scispacy package and publish it to pypi.