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| from tests.candidate import complete_interview | |
| from tests.grader import grade | |
| from concurrent.futures import ThreadPoolExecutor | |
| import random | |
| from typing import List | |
| def complete_and_grade_interview(interview_type: str, mode: str = "normal", min_score=0.4) -> float: | |
| """ | |
| Complete an interview and return the overall score. | |
| :param interview_type: Type of the interview. | |
| :param mode: Mode of the interview ("normal", "empty", "gibberish", "repeat"). | |
| :return: Overall score of the interview. | |
| """ | |
| file_path, _ = complete_interview(interview_type, "test", model="gpt-3.5-turbo", mode=mode) | |
| feedback = grade(file_path, model="gpt-4-turbo") | |
| assert feedback["overall_score"] > min_score | |
| return feedback["overall_score"] | |
| def test_complete_interview() -> None: | |
| """ | |
| Test the complete interview process for various interview types, including edge cases. | |
| """ | |
| interview_types = ["ml_design", "math", "ml_theory", "system_design", "sql", "coding"] | |
| scores: List[float] = [] | |
| with ThreadPoolExecutor(max_workers=5) as executor: | |
| # Test normal interviews | |
| futures = [executor.submit(complete_and_grade_interview, it) for it in interview_types] | |
| # Test edge cases: empty, gibberish, repeat for one random interview type each | |
| # The test are placeholders for not, I will increase thresholds later | |
| futures.append(executor.submit(complete_and_grade_interview, random.choice(interview_types), mode="empty", min_score=0.0)) | |
| futures.append(executor.submit(complete_and_grade_interview, random.choice(interview_types), mode="gibberish", min_score=0.0)) | |
| futures.append(executor.submit(complete_and_grade_interview, random.choice(interview_types), mode="repeat", min_score=0.0)) | |
| for future in futures: | |
| score = future.result() | |
| scores.append(score) | |
| assert sum(scores) / len(scores) > 0.6 | |