test_prompt_comparision

import unittest from unittest.mock import Mock, patch import pandas as pd from datetime import datetime from your_module import PromptComparisonReport # Replace 'your_module' with the actual module name class TestPromptComparisonReport(unittest.TestCase): def setUp(self): # Create mock objects for dependencies self.mock_mongo_service = Mock() self.mock_auth = Mock() self.mock_config = { 'cloud-ai': { 'STRING_DISTANCE_URL': 'http://example.com/string_distance', 'STRING_COSINE_DISTANCE_URL': 'http://example.com/string_cosine_distance' } } # Initialize the PromptComparisonReport with mocks self.report_service = PromptComparisonReport(self.mock_config, self.mock_mongo_service, self.mock_auth) @patch('your_module.pd.DataFrame') def test_get_master_data_from_mongo(self, mock_dataframe): # Simulate MongoDB data self.mock_mongo_service.execute_query.return_value = [ {'call_id': '1', 'model_results': {'callSummary': [{'Caller Objective': 'Intent1'}]}}, {'call_id': '2', 'model_results': {'callSummary': [{'Caller Objective': 'Intent2'}]}} ] # Test the get_master_data_from_mongo method df = self.report_service.get_master_data_from_mongo() # Assertions self.mock_mongo_service.execute_query.assert_called_once_with('ai_intent_action_golden_copy') mock_dataframe.assert_called() self.assertIn('callID', df.columns) @patch('your_module.pd.DataFrame') def test_get_model_results_from_mongo(self, mock_dataframe): # Simulate data returned by MongoDB query run_time = '2024-01-01' self.mock_mongo_service.execute_query.return_value = [ {'call_id': '1', 'model_results': {'callSummary': [{'Caller Objective': 'Intent1'}]}}, {'call_id': '2', 'model_results': {'callSummary': [{'Caller Objective': 'Intent2'}]}} ] # Test the method with a single run_time df = self.report_service.get_model_results_from_mongo(run_time) # Assertions query = {'run_time': datetime.strptime(run_time, '%Y-%m-%d')} self.mock_mongo_service.execute_query.assert_called_once_with('ai_intent_action', query) self.assertIn('callID', df.columns) def test_create_dict_for_comparing(self): # Test data to pass into create_dict_for_comparing test_data = pd.DataFrame({ 'callID': [1, 2], 'model_results_from': [ [{'Caller Objective': 'Intent1'}], [{'Caller Objective': 'Intent2'}] ], 'model_results_to': [ [{'Caller Objective': 'Intent3'}], [{'Caller Objective': 'Intent4'}] ] }) result = self.report_service.create_dict_for_comparing(test_data) # Check if the result dictionary is as expected self.assertEqual(result[0]['call_id'], 1) self.assertEqual(result[1]['call_id'], 2) self.assertEqual(result[0]['google_naming'], ['INTENT1']) self.assertEqual(result[1]['google_naming'], ['INTENT2']) @patch('your_module.requests.Session') def test_calling_labelling_api_azure(self, mock_session): # Mock the session's post method to return a mock response mock_response = Mock() mock_response.content = b'{"DATA": "test_data"}' mock_session.return_value.post.return_value = mock_response # Run the method with test data response = self.report_service.calling_labelling_api_azure( 'http://example.com/test', {'data': 'test'}, 'fake_token' ) # Assertions self.assertEqual(response.content, b'{"DATA": "test_data"}') mock_session.return_value.post.assert_called_once_with( url='http://example.com/test', data='{"data": "test"}' ) def test_getting_comparison_report(self): # Mock data and dependencies self.report_service.calling_labelling_api_azure = Mock(return_value=Mock(content=b'{"DATA": [{"DISTANCE": 0.1}]}')) self.mock_auth.generate_assertion_token.return_value = 'fake_token' # Prepare test input data = [{'call_id': 1, 'google_naming': ['INTENT1'], 'azure_naming': ['INTENT2']}] # Test with "cosine" type result = self.report_service.getting_comparison_report(data, "cosine") # Assertions self.assertIn("cosine_DISTANCE", result.columns) self.assertAlmostEqual(result['cosine_DISTANCE'].iloc[0], 0.1) @patch('your_module.StreamingResponse') def test_format_data_for_report_excel(self, mock_streaming_response): # Prepare test data test_df = pd.DataFrame({ 'CALL_ID': [1, 2], 'GOOGLE_NAMING': ['Intent1', 'Intent2'], 'AZURE_NAMING': ['Intent3', 'Intent4'], 'euc_DISTANCE': [0.1, 0.2], 'cosine_DISTANCE': [0.3, 0.4] }) model_tagged_data = pd.DataFrame({ 'model_name': ['TestModel'], 'intent_action_prompt_name': ['TestPrompt'] }) # Run with excel output type self.report_service.format_data_for_report(test_df, model_tagged_data, 'excel') # Assertions mock_streaming_response.assert_called_once() self.assertIn("attachment", mock_streaming_response.call_args[1]['headers']['Content-Disposition']) def test_format_data_for_report_json(self): # Prepare test data test_df = pd.DataFrame({ 'CALL_ID': [1, 2], 'GOOGLE_NAMING': ['Intent1', 'Intent2'], 'AZURE_NAMING': ['Intent3', 'Intent4'], 'euc_DISTANCE': [0.1, 0.2], 'cosine_DISTANCE': [0.3, 0.4] }) model_tagged_data = pd.DataFrame({ 'model_name': ['TestModel'], 'intent_action_prompt_name': ['TestPrompt'] }) # Run with JSON output type response = self.report_service.format_data_for_report(test_df, model_tagged_data, 'json') # Assertions self.assertIsInstance(response, JSONResponse) self.assertIn("Status", response.body.decode('utf-8')) if __name__ == '__main__': unittest.main()

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