import json from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from models.assessment import Assessment from models.job import Job from models.user import User from models.application import Application from models.base import Base from config import settings from schemas.assessment import AssessmentQuestion, AssessmentQuestionOption from schemas.enums import QuestionType from services.ai_service import score_answer from uuid import uuid4 def test_ai_scoring_functionality(): """Test the AI scoring functionality""" print("Testing AI scoring functionality...") # Create a sample question sample_question = AssessmentQuestion( id=str(uuid4()), text="What is the capital of France?", weight=3, skill_categories=["geography", "knowledge"], type=QuestionType.choose_one, options=[ AssessmentQuestionOption(text="London", value="a"), AssessmentQuestionOption(text="Paris", value="b"), AssessmentQuestionOption(text="Berlin", value="c") ], correct_options=["b"] ) # Test correct answer print("\n1. Testing correct answer...") correct_result = score_answer( question=sample_question, answer_text="", selected_options=["b"] ) print(f" Correct answer score: {correct_result['score']}") print(f" Correct answer rationale: {correct_result['rationale']}") print(f" Is correct: {correct_result['correct']}") assert correct_result['score'] == 1.0, f"Expected 1.0, got {correct_result['score']}" assert correct_result['correct'] == True, f"Expected True, got {correct_result['correct']}" print(" [PASS] Correct answer test passed") # Test incorrect answer print("\n2. Testing incorrect answer...") incorrect_result = score_answer( question=sample_question, answer_text="", selected_options=["a"] # London is wrong ) print(f" Incorrect answer score: {incorrect_result['score']}") print(f" Incorrect answer rationale: {incorrect_result['rationale']}") print(f" Is correct: {incorrect_result['correct']}") assert incorrect_result['score'] == 0.0, f"Expected 0.0, got {incorrect_result['score']}" assert incorrect_result['correct'] == False, f"Expected False, got {incorrect_result['correct']}" print(" [PASS] Incorrect answer test passed") # Test text-based question print("\n3. Testing text-based question...") text_question = AssessmentQuestion( id=str(uuid4()), text="Explain the importance of renewable energy.", weight=5, skill_categories=["environment", "science"], type=QuestionType.text_based, options=[], correct_options=[] ) text_result = score_answer( question=text_question, answer_text="Renewable energy is important because it reduces carbon emissions and is sustainable.", selected_options=[] ) print(f" Text answer score: {text_result['score']}") print(f" Text answer rationale: {text_result['rationale']}") print(f" Is correct: {text_result['correct']}") # For text-based questions, we expect a partial score (0.5 in the updated mock implementation) assert text_result['score'] == 0.5, f"Expected 0.5, got {text_result['score']}" # In the mock implementation, any score > 0.5 is considered correct, so 0.5 is not correct assert text_result['correct'] == False, f"Expected False (since score is 0.5, not > 0.5), got {text_result['correct']}" print(" [PASS] Text-based question test passed") # Test multiple choice (choose many) question print("\n4. Testing choose-many question...") multichoice_question = AssessmentQuestion( id=str(uuid4()), text="Which of the following are programming languages?", weight=4, skill_categories=["programming", "computer-science"], type=QuestionType.choose_many, options=[ AssessmentQuestionOption(text="Python", value="a"), AssessmentQuestionOption(text="HTML", value="b"), AssessmentQuestionOption(text="Java", value="c"), AssessmentQuestionOption(text="CSS", value="d") ], correct_options=["a", "c"] # Python and Java are programming languages ) correct_multichoice_result = score_answer( question=multichoice_question, answer_text="", selected_options=["a", "c"] # Correct answers ) print(f" Correct multichoice score: {correct_multichoice_result['score']}") print(f" Correct multichoice rationale: {correct_multichoice_result['rationale']}") print(f" Is correct: {correct_multichoice_result['correct']}") assert correct_multichoice_result['score'] == 1.0, f"Expected 1.0, got {correct_multichoice_result['score']}" assert correct_multichoice_result['correct'] == True, f"Expected True, got {correct_multichoice_result['correct']}" print(" [PASS] Choose-many correct answer test passed") incorrect_multichoice_result = score_answer( question=multichoice_question, answer_text="", selected_options=["a", "b"] # Partially correct (includes HTML which is not a programming language) ) print(f" Incorrect multichoice score: {incorrect_multichoice_result['score']}") print(f" Incorrect multichoice rationale: {incorrect_multichoice_result['rationale']}") print(f" Is correct: {incorrect_multichoice_result['correct']}") assert incorrect_multichoice_result['score'] == 0.0, f"Expected 0.0, got {incorrect_multichoice_result['score']}" assert incorrect_multichoice_result['correct'] == False, f"Expected False, got {incorrect_multichoice_result['correct']}" print(" [PASS] Choose-many incorrect answer test passed") print("\n[PASS] All AI scoring functionality tests passed!") def test_application_scoring(): """Test the application scoring functionality""" print("\n\nTesting application scoring functionality...") # Create a test database session engine = create_engine(settings.database_url, connect_args={"check_same_thread": False}) TestingSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) # Create tables if they don't exist Base.metadata.create_all(bind=engine) # Create a test session db = TestingSessionLocal() try: # Create a test job test_job = Job( id=str(uuid4()), title="Software Engineer", seniority="mid", description="Test job for assessment", skill_categories='["programming", "python", "fastapi"]' ) db.add(test_job) db.commit() # Create a test assessment with questions test_questions = [ { "id": str(uuid4()), "text": "What is Python?", "weight": 3, "skill_categories": ["programming", "python"], "type": "choose_one", "options": [ {"text": "A snake", "value": "a"}, {"text": "A programming language", "value": "b"}, {"text": "An IDE", "value": "c"} ], "correct_options": ["b"] }, { "id": str(uuid4()), "text": "What is 2+2?", "weight": 2, "skill_categories": ["math"], "type": "choose_one", "options": [ {"text": "3", "value": "a"}, {"text": "4", "value": "b"}, {"text": "5", "value": "c"} ], "correct_options": ["b"] } ] test_assessment = Assessment( id=str(uuid4()), job_id=test_job.id, title="Programming Skills Assessment", passing_score=70, questions=json.dumps(test_questions) ) db.add(test_assessment) db.commit() # Create a test user test_user = User( id=str(uuid4()), first_name="John", last_name="Doe", email=f"test_{str(uuid4())[:8]}@example.com", role="applicant" ) test_user.set_password("password123") db.add(test_user) db.commit() # Create an application with correct answers test_answers = [ { "question_id": test_questions[0]['id'], "text": "", "options": ["b"] # Correct answer for question 1 }, { "question_id": test_questions[1]['id'], "text": "", "options": ["b"] # Correct answer for question 2 } ] test_application = Application( id=str(uuid4()), job_id=test_job.id, assessment_id=test_assessment.id, user_id=test_user.id, answers=json.dumps(test_answers) ) db.add(test_application) db.commit() # Test the score calculation from services.application_service import calculate_application_score calculated_score = calculate_application_score(db, test_application.id) print(f"Calculated score for application with all correct answers: {calculated_score}%") # Since both answers are correct, the score should be 100% expected_total_points = 3 + 2 # weights of both questions expected_earned_points = 3 + 2 # both answers are correct expected_percentage = (expected_earned_points / expected_total_points) * 100 assert calculated_score == expected_percentage, f"Expected {expected_percentage}%, got {calculated_score}%" print(" [PASS] Score calculation is correct for all correct answers") # Create another application with some incorrect answers test_answers_partial = [ { "question_id": test_questions[0]['id'], "text": "", "options": ["a"] # Wrong answer for question 1 }, { "question_id": test_questions[1]['id'], "text": "", "options": ["b"] # Correct answer for question 2 } ] test_application_partial = Application( id=str(uuid4()), job_id=test_job.id, assessment_id=test_assessment.id, user_id=test_user.id, answers=json.dumps(test_answers_partial) ) db.add(test_application_partial) db.commit() # Test the score calculation for partial correct answers calculated_score_partial = calculate_application_score(db, test_application_partial.id) print(f"Calculated score for application with partial correct answers: {calculated_score_partial}%") # Expected: 2 points earned (question 2) out of 5 total points expected_partial_percentage = (2 / 5) * 100 # 40% assert calculated_score_partial == expected_partial_percentage, f"Expected {expected_partial_percentage}%, got {calculated_score_partial}%" print(" [PASS] Score calculation is correct for partial correct answers") print("\n[PASS] Application scoring functionality tests passed!") finally: db.close() if __name__ == "__main__": test_ai_scoring_functionality() test_application_scoring()