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import json
from dotenv import load_dotenv
from openai import OpenAI
from prompts import coding_interviewer_prompt, grading_feedback_prompt
load_dotenv()
client = OpenAI()
def init_bot(problem=""):
chat_history = [
{"role": "system", "content": coding_interviewer_prompt},
{"role": "system", "content": f"The candidate is solving the following problem: {problem}"},
]
return chat_history
def get_problem(requirements, difficulty, topic, model, client=client):
prompt_system = "You are ChatGPT acting as a coding round interviewer for a big-tech company. "
full_prompt = f"Generate a {difficulty} {topic} problem in. Follow additional requirements: {requirements}. The problem should be solvable within 30 minutes."
response = client.chat.completions.create(
model=model,
messages=[
{"role": "system", "content": prompt_system},
{"role": "user", "content": full_prompt},
],
)
question = response.choices[0].message.content.strip()
chat_history = init_bot(question)
return question, chat_history
def end_interview(chat_history, model, client=client):
transcript = []
for message in chat_history[1:]:
role = message["role"]
content = f"{role.capitalize()}: {message['content']}"
transcript.append(content)
response = client.chat.completions.create(
model=model,
messages=[
{"role": "system", "content": grading_feedback_prompt},
{"role": "user", "content": "Interview transcript:" + "\n\n".join(transcript)},
{"role": "user", "content": "Grade the interview based on the transcript provided and give a feedback."},
],
)
feedback = response.choices[0].message.content.strip()
return feedback
def send_request(code, previous_code, message, chat_history, chat_display, model, client=client):
if code != previous_code:
chat_history.append({"role": "user", "content": f"My latest code: {code}"})
chat_history.append({"role": "user", "content": message})
response = client.chat.completions.create(model=model, response_format={"type": "json_object"}, messages=chat_history)
json_reply = response.choices[0].message.content.strip()
try:
data = json.loads(json_reply)
reply = data["reply_to_candidate"]
except json.JSONDecodeError as e:
print("Failed to decode JSON:", str(e))
reply = "There was an error processing your request."
chat_history.append({"role": "assistant", "content": json_reply})
chat_display.append([message, str(reply)])
return chat_history, chat_display, "", code
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