| from typing import Tuple |
|
|
| from .question import Question |
| from ..llms import get_llm_fn |
|
|
|
|
| class QuestionExecutor: |
| def __init__(self, question: Question, lang: str = 'cn', llm: str = 'chatgpt', llm_cfgs=None): |
| self.question = question |
| self.lang = lang |
| self.llm = llm |
| self.llm_cfgs = dict(llm_cfgs or {}) |
|
|
| @property |
| def question_text(self): |
| return self.question.texts[self.lang] |
|
|
| @property |
| def question_name(self): |
| return self.question.names[self.lang] |
| |
| def llm_answer(self, qs_text: str) -> str: |
| return get_llm_fn(self.llm)(qs_text, **self.llm_cfgs) |
|
|
| def check(self, qs_text: str) -> Tuple[str, bool, str]: |
| answer_text = self.llm_answer(qs_text) |
| correct, explanation = self.check_answer(qs_text, answer_text) |
| return answer_text, correct, explanation |
|
|
| def check_answer(self, user_text: str, answer_text: str) -> Tuple[bool, str]: |
| inputs = { |
| 'question_text': self.question_text, |
| 'user_text': user_text, |
| 'answer_text': answer_text, |
| 'lang': self.lang, |
| 'llm_callback': self.llm_answer, |
| |
| } |
| correct, explanation = self.question.checker(inputs) |
| if explanation is None: |
| if correct: |
| explanation = 'LLM的回答满足要求' if self.lang == 'cn' else 'Correct Answer From LLM' |
| else: |
| explanation = 'LLM的回答不满足要求' if self.lang == 'cn' else 'Wrong Answer From LLM' |
|
|
| return correct, explanation |
|
|
