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import unittest
from unittest.mock import MagicMock
import pandas as pd
import streamlit as st
from your_module import fine_tune_model
class TestModelFineTuning(unittest.TestCase):
@patch('streamlit.file_uploader')
def test_upload_and_fine_tune_model(self, mock_file_uploader):
# Mock the file upload and return a mock DataFrame
mock_file_uploader.return_value = MagicMock()
mock_file_uploader.return_value.read.return_value = b'col1,col2\nvalue1,value2\nvalue3,value4'
# Test dataset upload and model fine-tuning
df = pd.read_csv(mock_file_uploader.return_value)
self.assertEqual(df.shape[0], 2) # Assert two rows in the mock CSV
self.assertIn('col1', df.columns) # Check if 'col1' exists in columns
# Simulate fine-tuning process
result = fine_tune_model(df) # Assuming you have a fine-tune function
# Check that the model fine-tuned successfully
self.assertTrue(result) # Assuming result is True on success
if __name__ == '__main__':
unittest.main()
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