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Export Orange3 models with preprocessing pipelines to MLflow format for production deployment.

Project description

Orange3 MLflow Export

⚠️ Experimental: This widget is under development and should be used with care.

Export Orange3 machine learning models to MLflow format with preprocessing pipelines.

Installation

pip install orange3-mlflow-export

Usage

In Orange GUI:

  1. Build your workflow (File → Preprocess → Model)
  2. Add MLflow Export widget from the Example section
  3. Connect model, preprocessor, and sample data
  4. Set export path and save

The exported model can be served with:

mlflow models serve -m ./model.mlflow -p 8080

Current Limitations

  • Column names from Orange are intentionally ignored (uses positional mapping)
  • Precise dependency versions are not exported in MLflow models
  • Explicit list of required Orange addons is not exported
  • May not work with all Orange preprocessing widgets

Requirements

  • Python 3.8+
  • Orange3
  • MLflow
  • pandas, numpy, scikit-learn
  • cloudpickle

License

GPL-3.0

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