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IliaLarchenko
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a5bc3b5
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Parent(s):
89d9c22
Added notes to the grading transcript
Browse files- tests/candidate.py +8 -1
- tests/testing_prompts.py +3 -1
tests/candidate.py
CHANGED
@@ -92,7 +92,14 @@ def complete_interview(interview_type, exp_name, requirements="", difficulty="",
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response_times.append(time.time() - send_time)
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messages_candidate.append({"role": "user", "content": chat_display[-1][1]})
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-
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interview_data["feedback"] = llm.end_interview_full(problem_statement_text, messages_interviewer, interview_type)
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interview_data["average_response_time_seconds"] = round(sum(response_times) / len(response_times), 2) if response_times else 0
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response_times.append(time.time() - send_time)
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messages_candidate.append({"role": "user", "content": chat_display[-1][1]})
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message_split = messages_interviewer[-1]["content"].split("#NOTES#")
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interviewer_answer = message_split[0]
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interview_data["transcript"].append(f"INTERVIEWER MESSAGE: {interviewer_answer}")
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if len(message_split) > 1:
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interviewer_note = message_split[1]
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interview_data["transcript"].append(f"INTERVIEWER HIDDEN NOTE: {interviewer_note}")
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interview_data["feedback"] = llm.end_interview_full(problem_statement_text, messages_interviewer, interview_type)
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interview_data["average_response_time_seconds"] = round(sum(response_times) / len(response_times), 2) if response_times else 0
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tests/testing_prompts.py
CHANGED
@@ -18,6 +18,7 @@ You are reviewing an interview. Your goal is to evaluate the performance of the
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Be extremely critical and strict, you have highest quality standards.
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Even a slight mistake should lead to a negative evaluation. If in doubt about any criteria, give a negative evaluation.
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Analyze the JSON file with the interview transcript and provide your feedback.
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You should evaluate the following aspects and return a JSON with these keys:
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@@ -39,8 +40,9 @@ You should evaluate the following aspects and return a JSON with these keys:
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"interviewer_hallucinations": "The interviewer didn't say anything non-relevant or strange.",
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"interviewer_summary": "The interviewer doesn't repeat or summarize what the candidate just said.",
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"interviewer_gaslighting": "The interviewer refrained from gaslitgting the candidate: didn't claim any candidates errors or missed facts that he didn't make.",
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"interviewer_leaks": "The interviewer didn't leak any hidden notes to candidate.",
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"interviewer_empty": "The interviewer didn't send any empty messages.",
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"feedback_quality": "The feedback was constructive and offered actionable insights.",
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"feedback_overview": "The feedback contains the recap of main mistakes and good ideas of the candidate.",
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Be extremely critical and strict, you have highest quality standards.
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Even a slight mistake should lead to a negative evaluation. If in doubt about any criteria, give a negative evaluation.
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Analyze the JSON file with the interview transcript and provide your feedback.
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JSON contains, problem description, interview transcript (messages, code and hodden notes not visible to candidate), and feedback.
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You should evaluate the following aspects and return a JSON with these keys:
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"interviewer_hallucinations": "The interviewer didn't say anything non-relevant or strange.",
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"interviewer_summary": "The interviewer doesn't repeat or summarize what the candidate just said.",
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"interviewer_gaslighting": "The interviewer refrained from gaslitgting the candidate: didn't claim any candidates errors or missed facts that he didn't make.",
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"interviewer_leaks": "The interviewer didn't leak any hidden notes to candidate during the main part of the interview.",
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"interviewer_empty": "The interviewer didn't send any empty messages.",
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"interviewer_notes": "The interviewer made reasonable notes catching candidates mistakes and important facts.",
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"feedback_quality": "The feedback was constructive and offered actionable insights.",
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"feedback_overview": "The feedback contains the recap of main mistakes and good ideas of the candidate.",
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