Help Needed: Segregating Workflows with ML Libraries in Python Nodes on KNIME Business Hub

Hi All,

I am currently managing a KNIME Business Hub with numerous workflows that make extensive use of Python nodes. To enhance organization and monitoring, I need to classify these workflows into two categories:

1.

Workflows that utilize machine learning (ML) libraries (e.g., scikit-learn, TensorFlow, PyTorch, etc.) in their Python nodes.

1.

Workflows that do not involve ML libraries in their Python nodes.

I want to develop an automated or semi-automated way to identify and segregate these workflows based on the presence of ML libraries in the Python scripts.

I am looking for suggestions, best practices, or examples from the community to efficiently manage this segregation process. Any guidance on tools, scripting approaches, or workflow design for this purpose would be greatly appreciated.

Thank you in advance for your support!