app/utils/evaluation.py

import pandas as pd
from sklearn.metrics import classification_report

def evaluate_predictions(y_true, y_pred):
    """
    Evaluates predictions by converting labels to strings and generating a classification report.

    Args:
        y_true (pd.Series or list): True labels.
        y_pred (pd.Series or list): Predicted labels.

    Returns:
        dict: Classification report as a dictionary.
    """
    # Ensure both true and predicted labels are strings
    y_true_str = pd.Series(y_true).astype(str)
    y_pred_str = pd.Series(y_pred).astype(str)

    # Generate classification report
    report = classification_report(y_true_str, y_pred_str, output_dict=True)
    return report