Release v0.7.2

Breaking changes

• staka/fugumt-... models has been removed as it is not working with the newer dependencies.

  • Issue related to huggingface/transformers#24657 (comment)
  • Unfortunately the version of transformers/tokenizers can't be lowered below 4.48.0/0.20.2
    as tokenizers does not support python 3.13 before https://github.com/huggingface/tokenizers/releases/tag/v0.20.2

• If upgrading python version (eg running with docker that now uses 3.13 instead of 3.11) it is suggested to delete your plugin installations first (<OCT_BASE_DIR>/plugins/). Basically every package will be updated anyway.

Major Changes

• dependencies updates:
  • python: support for >=3.10, <=3.11 extended to >=3.10 (will test 3.14 once it is out with all its prebuilt packages in PyPI)
  • CUDA: from 11.8 updated to 12.8 (allow using sm_120 GPUs like the RTX 5000 series)
  • torch: from 2.2.1 updated to 2.8.0
  • easyocr: from 1.7.1 updated to 1.7.2
  • paddleocr: from 2.8.1 updated to 3.2.0
    Different models and much ampler set of languages supported
• Improved logging of the server using rich
• Environment variables:
  • REMOVED:
    • AUTO_CREATE_LANGUAGES - Languages are now created once at first initialization if missing
      For now the languages have never changed across versions so it was never needed to recreate/updated them.
    • AUTOCREATE_MODELS - Models are now synchronized with the available entrypoints at every server start
      Removed models will be deactivated, and present models will be updated/created.
  • ADDED:
    • OCT_LOGFILE - [true/false/path]. If true, a logfile named $OCT_BASE_DIR/ocr_translate.log will be created. If a path is provided, that will be used instead.
• Logic of the run_server.py moved inside the package to improve testing and modularity (the script will appear much smaller in the release)
• QoL improvements for manual plugins installations
  • If you want to try your own plugins or you want to manually install the supported ones (eg with modifications) you can now do so by installing them in the server
    environment.
  • The server will automatically pick up the plugin module name and add it to the DJANGO apps, and synchronize the models in the database at launch.
  • NOTE: packages coming from the managed plugins will take precedence over manually installed ones. This could cause package conflicts. Mix stuff at your own risk.

Fixes

• Fix #55

New Contributors

• @Prowler1000 made their first contribution in #56

Full Changelog: v0.6.3...v0.7.2