input: 
  from typing import List, Any
  
  
  def predict(data: List[float]) -> Any:
      """Predict the class label of a given set of data with features Length, Width, 
      Height, and Weight. The model is pre-trained using the given dataset loaded from 
      a CSV url.
      
      >>> predict([1.0, 2.0, 3.0, 4.0])
      'ClassLabel1'
      >>> predict([4.0, 5.0, 6.0, 7.0])
      'ClassLabel2'
      """
  
output:     import numpy as np
      from sklearn.ensemble import RandomForestClassifier
      from sklearn.datasets import load_iris
  
      # Load a pre-trained model (for example, using the Iris dataset)
      iris = load_iris()
      X = iris.data
      y = iris.target
      model = RandomForestClassifier(random_state=42)
      model.fit(X, y)
  
      # Predict the class label
      prediction = model.predict([data])
      class_labels = ['ClassLabel1', 'ClassLabel2', 'ClassLabel3']
      return class_labels[prediction[0]]