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import json
from openai import OpenAI
from tests.testing_prompts import grader_prompt
def grade(json_file_path, model="gpt-4o", suffix=""):
client = OpenAI(base_url="https://api.openai.com/v1")
with open(json_file_path) as file:
interview_data = json.load(file)
interview_summary_list = []
interview_summary_list.append(f"Interview type: {interview_data['inputs']['interview_type']}")
interview_summary_list.append(f"Interview difficulty: {interview_data['inputs']['difficulty']}")
interview_summary_list.append(f"Interview topic: {interview_data['inputs']['topic']}")
if interview_data["inputs"]["requirements"] != "":
interview_summary_list.append(f"Interview requirements: {interview_data['inputs']['requirements']}")
interview_summary_list.append(f"Problem statement proposed by interviewer: {interview_data['problem_statement']}")
interview_summary_list.append(f"\nTranscript of the whole interview below:")
interview_summary_list += interview_data["transcript"]
interview_summary_list.append(f"\nTHE MAIN PART OF THE INTERVIEW ENDED HERE.")
interview_summary_list.append(f"Feedback provided by interviewer: {interview_data['feedback']}")
messages = [
{"role": "system", "content": grader_prompt},
{"role": "user", "content": f"Please evaluate the interviewer based on the following data: \n {'\n'.join(interview_summary_list)}"},
]
response = client.chat.completions.create(model=model, messages=messages, temperature=0, response_format={"type": "json_object"})
feedback = json.loads(response.choices[0].message.content)
feedback["file_name"] = json_file_path
feedback["agent_llm"] = interview_data["interviewer_llm"]
feedback["candidate_llm"] = interview_data["candidate_llm"]
feedback["grader_model"] = model
feedback["type"] = interview_data["inputs"]["interview_type"]
feedback["difficulty"] = interview_data["inputs"]["difficulty"]
feedback["topic"] = interview_data["inputs"]["topic"]
feedback["average_response_time_seconds"] = interview_data["average_response_time_seconds"]
feedback["number_of_messages"] = len(interview_data["transcript"])
scores = [
feedback[x]
for x in feedback
if (x.startswith("interviewer_") or x.startswith("feedback_") or x.startswith("problem_")) and feedback[x] is not None
]
feedback["overall_score"] = sum(scores) / len(scores)
# save results to json file in the same folder as the interview data
with open(json_file_path.replace(".json", f"_feedback_{suffix}.json"), "w") as file:
json.dump(feedback, file, indent=4)
return feedback
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