Metadata-Version: 2.4
Name: Orange3-MLflow-Export
Version: 0.1.4
Summary: Export Orange3 models with preprocessing pipelines to MLflow format for production deployment.
Home-page: https://github.com/NIRLab-com/mlflow-model-widget
Author: NIRLAB AG
Author-email: dev@nirlab.com
License: GPL-3.0-only
Project-URL: Bug Reports, https://github.com/NIRLab-com/mlflow-model-widget/issues
Project-URL: Source, https://github.com/NIRLab-com/mlflow-model-widget
Project-URL: Documentation, https://github.com/NIRLab-com/mlflow-model-widget/blob/main/README_MLFLOW_WIDGET.md
Keywords: orange3 add-on,mlflow,machine learning,model export,data science,deployment,preprocessing
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: X11 Applications :: Qt
Classifier: Environment :: Plugins
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: Orange3
Requires-Dist: mlflow
Requires-Dist: cloudpickle
Requires-Dist: scikit-learn
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Orange3 MLflow Export
====================

**⚠️ Experimental**: This widget is under development with known limitations.

Orange3 widget to export trained models to MLflow format.

## Installation

```bash
pip install orange3-mlflow-export
```

## Usage

In Orange GUI:
1. Build your workflow (File → Preprocess → Model)
2. Add MLflow Export widget from the MLFlow section
3. Connect your trained model
4. Set export path and save

The exported model can be served with:
```bash
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
