Dynamic Feature Engineering Automation Pipeline

Create an advanced Python feature engineering framework that automatically discovers, transforms, and validates potential predictive features across datasets. Utilize techniques like mutual information scoring, automated interaction detection, and dynamic feature selection using techniques from sklearn and feature-engine. The pipeline should support multiple input types, handle categorical and numerical transformations, and provide comprehensive feature importance reporting.