# utils.py import re def clean_worker_model_answer(raw_answer_text: str, prompt_version: str) -> tuple[str, bool]: """ Cleans the raw answer text from the worker LLM. Returns: - cleaned_answer (str) - is_correctly_formatted_output (bool): True if CoT format was followed (if CoT was used), True for other prompt types by default. """ answer = raw_answer_text.strip() is_correctly_formatted_output = True if prompt_version == "COT": match = re.search(r"Final Answer:\s*(.*)", answer, re.IGNORECASE | re.DOTALL) if match: answer = match.group(1).strip() else: is_correctly_formatted_output = False # Using print for this specific info as it's about an expected format from the worker print(f"\nINFO (Worker Output): COT prompt used, but 'Final Answer:' marker not found. Cleaning applied to full raw output. Raw Preview: \"{raw_answer_text[:100]}...\"") prefixes_to_remove = [ "Answer is:", "Answer:", "The answer is:", "The final answer is ", "Expert Answer:", "答案是:", "答案:", "答案是", "答案", "好的,答案是:", "好的,答案是", "了解,答案是:", "了解,答案是" # Retained for robustness ] temp_answer = answer for prefix in prefixes_to_remove: if temp_answer.lower().startswith(prefix.lower()): temp_answer = temp_answer[len(prefix):].strip() break answer = temp_answer if answer.startswith("- "): answer = answer[2:].strip() if answer.startswith("* "): answer = answer[2:].strip() if len(answer) > 1 and ((answer.startswith('"') and answer.endswith('"')) or \ (answer.startswith("'") and answer.endswith("'"))): answer = answer[1:-1] if len(answer) > 1 and (answer.endswith(".") or answer.endswith("。")): # Handles English and Chinese periods answer = answer[:-1].strip() if answer.startswith("> "): answer = answer[2:].strip() if answer.startswith(">"): answer = answer[1:].strip() return answer.strip(), is_correctly_formatted_output