"""
UML Module for MCP4CM

This module provides tools for loading, cleaning, and analyzing UML models.
It includes functionality for detecting duplicate models, filtering low-quality
or auto-generated models, detecting non-English models, and extracting model metadata.

Main components:
- dataloading: Functions for loading UML model datasets
- data_extraction: Functions for extracting and filtering model content
- duplicate_detection: Functions for identifying exact and near-duplicate models
- language_detection: Functions for detecting model languages
- filtering_patterns: Patterns and thresholds used for filtering models
- utils: Utility functions for working with UML models

Example usage:
```python
from mcp4cm.uml.dataloading import load_dataset
from mcp4cm.uml.data_extraction import filter_empty_or_invalid_files

# Load a UML dataset
dataset = load_dataset("path/to/modelset", "genmymodel")

# Filter out empty or invalid models
filtered_dataset = filter_empty_or_invalid_files(dataset, inplace=True)
```
"""