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import unittest
from unittest.mock import patch
import pandas as pd
import src.backend.model_operations as model_operations
class TestEvaluator(unittest.TestCase):
def setUp(self):
self.model_path = "test_model"
@patch("src.backend.model_operations.load_evaluation_model")
def test_init(self, mock_load_evaluation_model):
model_operations.EvaluationModel(self.model_path)
mock_load_evaluation_model.assert_called_once_with(self.model_path)
@patch("src.backend.model_operations.load_evaluation_model")
def test_evaluate_hallucination(self, mock_load_evaluation_model):
model = model_operations.EvaluationModel(self.model_path)
df = pd.DataFrame({'source': ['source1', 'source2'], 'summary': ['summary1', 'summary2']})
mock_load_evaluation_model.return_value.predict.return_value = [0.8, 0.2]
scores = model.evaluate_hallucination(df)
self.assertEqual(scores, [0.8, 0.2])
@patch("src.backend.model_operations.load_evaluation_model")
def test_evaluate_hallucination_exception(self, mock_load_evaluation_model):
model = model_operations.EvaluationModel(self.model_path)
df = pd.DataFrame({'source': ['source1', 'source2'], 'summary': ['summary1', 'summary2']})
mock_load_evaluation_model.return_value.predict.side_effect = Exception("Test exception")
with self.assertRaises(Exception):
scores = model.evaluate_hallucination(df)
@patch("src.backend.model_operations.load_evaluation_model")
def test_compute_accuracy(self, mock_load_evaluation_model):
model = model_operations.EvaluationModel(self.model_path)
model.scores = [0.8, 0.2]
accuracy = model.compute_accuracy()
expected_accuracy = 50.0
self.assertEqual(accuracy, expected_accuracy)
class TestLoadEvaluationModel(unittest.TestCase):
@patch("src.backend.model_operations.CrossEncoder")
def test_load_evaluation_model(self, mock_cross_encoder):
model_path = 'test_model_path'
model_operations.load_evaluation_model(model_path)
mock_cross_encoder.assert_called_once_with(model_path)
if __name__ == '__main__':
unittest.main()
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