add；添加表达方式检查脚本
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SengokuCola
@@ -521,6 +521,7 @@ async def _react_agent_solve_question(
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logger.warning(f"{react_log_prefix}第 {iteration + 1} 次迭代 无工具调用且无响应")
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step["observations"] = ["无响应且无工具调用"]
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thinking_steps.append(step)
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iteration += 1 # 在continue之前增加迭代计数，避免跳过iteration += 1
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continue
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# 处理工具调用
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@@ -1021,6 +1022,11 @@ async def _process_single_question(
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Returns:
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Optional[str]: 如果找到答案，返回格式化的结果字符串，否则返回None
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"""
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# 如果question为空或None，直接返回None，不进行查询
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if not question or not question.strip():
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logger.debug("问题为空，跳过查询")
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return None
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# logger.info(f"开始处理问题: {question}")
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_cleanup_stale_not_found_thinking_back()
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@@ -1116,15 +1122,14 @@ async def build_memory_retrieval_prompt(
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recent_query_history = "最近没有查询记录。"
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# 第一步：生成问题或使用 Planner 提供的问题
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questions = []
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single_question: Optional[str] = None
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# 如果 planner_question 配置开启，只使用 Planner 提供的问题，不使用旧模式
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if global_config.memory.planner_question:
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if question and isinstance(question, str) and question.strip():
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# 清理和验证 question
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cleaned_question = question.strip()
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questions = [cleaned_question]
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logger.info(f"{log_prefix}使用 Planner 提供的 question: {cleaned_question}")
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single_question = question.strip()
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logger.info(f"{log_prefix}使用 Planner 提供的 question: {single_question}")
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else:
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# planner_question 开启但没有提供 question，跳过记忆检索
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logger.debug(f"{log_prefix}planner_question 已开启但未提供 question，跳过记忆检索")
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@@ -1157,10 +1162,11 @@ async def build_memory_retrieval_prompt(
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logger.error(f"{log_prefix}LLM生成问题失败: {response}")
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return ""
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# 解析概念列表和问题列表
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# 解析概念列表和问题列表，只取第一个问题
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_, questions = parse_questions_json(response)
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if questions:
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logger.info(f"{log_prefix}解析到 {len(questions)} 个问题: {questions}")
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if questions and len(questions) > 0:
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single_question = questions[0].strip()
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logger.info(f"{log_prefix}解析到问题: {single_question}")
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# 初始阶段：使用 Planner 提供的 unknown_words 进行检索（如果提供）
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initial_info = ""
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@@ -1183,13 +1189,13 @@ async def build_memory_retrieval_prompt(
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else:
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logger.debug(f"{log_prefix}unknown_words 检索未找到任何结果")
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if not questions:
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if not single_question:
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logger.debug(f"{log_prefix}模型认为不需要检索记忆或解析失败，不返回任何查询结果")
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end_time = time.time()
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logger.info(f"{log_prefix}无当次查询，不返回任何结果，耗时: {(end_time - start_time):.3f}秒")
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return ""
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# 第二步：并行处理所有问题（使用配置的最大迭代次数和超时时间）
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# 第二步：处理问题（使用配置的最大迭代次数和超时时间）
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base_max_iterations = global_config.memory.max_agent_iterations
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# 根据think_level调整迭代次数：think_level=1时不变，think_level=0时减半
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if think_level == 0:
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@@ -1198,31 +1204,21 @@ async def build_memory_retrieval_prompt(
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max_iterations = base_max_iterations
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timeout_seconds = global_config.memory.agent_timeout_seconds
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logger.debug(
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f"{log_prefix}问题数量: {len(questions)}，think_level={think_level}，设置最大迭代次数: {max_iterations}（基础值: {base_max_iterations}），超时时间: {timeout_seconds}秒"
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f"{log_prefix}问题: {single_question}，think_level={think_level}，设置最大迭代次数: {max_iterations}（基础值: {base_max_iterations}），超时时间: {timeout_seconds}秒"
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)
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# 并行处理所有问题
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question_tasks = [
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_process_single_question(
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question=question,
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# 处理单个问题
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try:
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result = await _process_single_question(
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question=single_question,
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chat_id=chat_id,
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context=message,
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initial_info=initial_info,
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max_iterations=max_iterations,
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)
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for question in questions
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]
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# 并行执行所有查询任务
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results = await asyncio.gather(*question_tasks, return_exceptions=True)
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# 收集所有有效结果
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question_results: List[str] = []
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for i, result in enumerate(results):
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if isinstance(result, Exception):
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logger.error(f"{log_prefix}处理问题 '{questions[i]}' 时发生异常: {result}")
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elif result is not None:
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question_results.append(result)
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except Exception as e:
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logger.error(f"{log_prefix}处理问题 '{single_question}' 时发生异常: {e}")
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result = None
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# 获取最近10分钟内已找到答案的缓存记录
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cached_answers = _get_recent_found_answers(chat_id, time_window_seconds=600.0)
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@@ -1231,29 +1227,29 @@ async def build_memory_retrieval_prompt(
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all_results = []
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# 先添加当前查询的结果
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current_questions = set()
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for result in question_results:
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current_question = None
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if result:
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all_results.append(result)
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# 提取问题（格式为 "问题：xxx\n答案：xxx"）
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if result.startswith("问题："):
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question_end = result.find("\n答案：")
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if question_end != -1:
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current_questions.add(result[4:question_end])
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all_results.append(result)
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current_question = result[4:question_end]
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# 添加缓存答案（排除当前查询中已存在的问题）
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# 添加缓存答案（排除当前查询的问题）
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for cached_answer in cached_answers:
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if cached_answer.startswith("问题："):
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question_end = cached_answer.find("\n答案：")
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if question_end != -1:
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cached_question = cached_answer[4:question_end]
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if cached_question not in current_questions:
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if cached_question != current_question:
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all_results.append(cached_answer)
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end_time = time.time()
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if all_results:
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retrieved_memory = "\n\n".join(all_results)
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current_count = len(question_results)
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current_count = 1 if result else 0
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cached_count = len(all_results) - current_count
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logger.info(
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f"{log_prefix}记忆检索成功，耗时: {(end_time - start_time):.3f}秒，"
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@@ -1261,7 +1257,7 @@ async def build_memory_retrieval_prompt(
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)
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return f"你回忆起了以下信息：\n{retrieved_memory}\n如果与回复内容相关，可以参考这些回忆的信息。\n"
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else:
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logger.debug(f"{log_prefix}所有问题均未找到答案，且无缓存答案")
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logger.debug(f"{log_prefix}问题未找到答案，且无缓存答案")
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return ""
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except Exception as e:
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