mirror of https://github.com/Mai-with-u/MaiBot.git
fix:解析动作错误
parent
541799b1c2
commit
c3798e1a8d
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@ -304,14 +304,12 @@ class BrainChatting:
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)
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prompt_info = await self.action_planner.build_planner_prompt(
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is_group_chat=is_group_chat,
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chat_target_info=chat_target_info,
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current_available_actions=available_actions,
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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prompt_key="brain_planner_prompt_react",
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log_prompt=True,
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)
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continue_flag, modified_message = await events_manager.handle_mai_events(
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EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
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@ -148,6 +148,9 @@ class BrainPlanner:
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) # 用于动作规划
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self.last_obs_time_mark = 0.0
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# 计划日志记录
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self.plan_log: List[Tuple[str, float, List[ActionPlannerInfo]]] = []
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def find_message_by_id(
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self, message_id: str, message_id_list: List[Tuple[str, "DatabaseMessages"]]
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@ -179,6 +182,7 @@ class BrainPlanner:
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try:
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action = action_json.get("action", "complete_talk")
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logger.debug(f"{self.log_prefix}解析动作JSON: action={action}, json={action_json}")
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reasoning = action_json.get("reason", "未提供原因")
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action_data = {key: value for key, value in action_json.items() if key not in ["action", "reason"]}
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# 非complete_talk动作需要target_message_id
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@ -201,6 +205,8 @@ class BrainPlanner:
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# 注意:listening 已合并到 wait 中,如果遇到 listening 则转换为 wait
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internal_action_names = ["complete_talk", "reply", "wait_time", "wait", "listening"]
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logger.debug(f"{self.log_prefix}动作验证: action={action}, internal={internal_action_names}, available={available_action_names}")
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# 将 listening 转换为 wait(向后兼容)
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if action == "listening":
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logger.debug(f"{self.log_prefix}检测到 listening 动作,已合并到 wait,自动转换")
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@ -208,12 +214,13 @@ class BrainPlanner:
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if action not in internal_action_names and action not in available_action_names:
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logger.warning(
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f"{self.log_prefix}LLM 返回了当前不可用或无效的动作: '{action}' (可用: {available_action_names}),将强制使用 'complete_talk'"
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f"{self.log_prefix}LLM 返回了当前不可用或无效的动作: '{action}' (内部动作: {internal_action_names}, 可用插件动作: {available_action_names}),将强制使用 'complete_talk'"
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)
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reasoning = (
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f"LLM 返回了当前不可用的动作 '{action}' (可用: {available_action_names})。原始理由: {reasoning}"
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)
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action = "complete_talk"
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logger.warning(f"{self.log_prefix}动作已转换为 complete_talk")
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# 创建ActionPlannerInfo对象
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# 将列表转换为字典格式
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@ -294,18 +301,16 @@ class BrainPlanner:
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prompt_key = "brain_planner_prompt_react"
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# 这里不记录日志,避免重复打印,由调用方按需控制 log_prompt
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prompt, message_id_list = await self.build_planner_prompt(
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is_group_chat=is_group_chat,
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chat_target_info=chat_target_info,
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current_available_actions=filtered_actions,
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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prompt_key=prompt_key,
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log_prompt=False,
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)
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# 调用LLM获取决策
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actions = await self._execute_main_planner(
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reasoning, actions = await self._execute_main_planner(
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prompt=prompt,
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message_id_list=message_id_list,
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filtered_actions=filtered_actions,
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@ -313,18 +318,22 @@ class BrainPlanner:
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loop_start_time=loop_start_time,
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)
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# 记录和展示计划日志
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logger.info(
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f"{self.log_prefix}Planner: {reasoning}。选择了{len(actions)}个动作: {' '.join([a.action_type for a in actions])}"
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)
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self.add_plan_log(reasoning, actions)
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return actions
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async def build_planner_prompt(
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self,
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is_group_chat: bool,
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chat_target_info: Optional["TargetPersonInfo"],
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current_available_actions: Dict[str, ActionInfo],
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message_id_list: List[Tuple[str, "DatabaseMessages"]],
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chat_content_block: str = "",
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interest: str = "",
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prompt_key: str = "brain_planner_prompt_react",
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log_prompt: bool = False,
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) -> tuple[str, List[Tuple[str, "DatabaseMessages"]]]:
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"""构建 Planner LLM 的提示词 (获取模板并填充数据)"""
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try:
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@ -373,10 +382,6 @@ class BrainPlanner:
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plan_style=global_config.personality.private_plan_style,
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)
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# 调试:按需展示本次 Planner 使用的 Prompt
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if log_prompt:
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logger.info(f"{self.log_prefix} BrainPlanner Prompt [{prompt_key}]:\n{prompt}")
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return prompt, message_id_list
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except Exception as e:
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logger.error(f"构建 Planner 提示词时出错: {e}")
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@ -474,17 +479,18 @@ class BrainPlanner:
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filtered_actions: Dict[str, ActionInfo],
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available_actions: Dict[str, ActionInfo],
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loop_start_time: float,
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) -> List[ActionPlannerInfo]:
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) -> Tuple[str, List[ActionPlannerInfo]]:
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"""执行主规划器"""
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llm_content = None
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actions: List[ActionPlannerInfo] = []
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extracted_reasoning = ""
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try:
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# 调用LLM
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llm_content, (reasoning_content, _, _) = await self.planner_llm.generate_response_async(prompt=prompt)
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# logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
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# logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
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logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
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logger.info(f"{self.log_prefix}规划器原始响应: {llm_content}")
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if global_config.debug.show_planner_prompt:
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logger.info(f"{self.log_prefix}规划器原始提示词: {prompt}")
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@ -499,10 +505,11 @@ class BrainPlanner:
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except Exception as req_e:
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logger.error(f"{self.log_prefix}LLM 请求执行失败: {req_e}")
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return [
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extracted_reasoning = f"LLM 请求失败,模型出现问题: {req_e}"
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return extracted_reasoning, [
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ActionPlannerInfo(
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action_type="complete_talk",
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reasoning=f"LLM 请求失败,模型出现问题: {req_e}",
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reasoning=extracted_reasoning,
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action_data={},
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action_message=None,
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available_actions=available_actions,
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@ -512,22 +519,30 @@ class BrainPlanner:
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# 解析LLM响应
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if llm_content:
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try:
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if json_objects := self._extract_json_from_markdown(llm_content):
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logger.debug(f"{self.log_prefix}从响应中提取到{len(json_objects)}个JSON对象")
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json_objects, extracted_reasoning = self._extract_json_from_markdown(llm_content)
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if json_objects:
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logger.info(f"{self.log_prefix}从响应中提取到{len(json_objects)}个JSON对象")
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for i, json_obj in enumerate(json_objects):
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logger.info(f"{self.log_prefix}解析第{i+1}个JSON对象: {json_obj}")
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filtered_actions_list = list(filtered_actions.items())
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for json_obj in json_objects:
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actions.extend(self._parse_single_action(json_obj, message_id_list, filtered_actions_list))
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parsed_actions = self._parse_single_action(json_obj, message_id_list, filtered_actions_list)
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logger.info(f"{self.log_prefix}解析后的动作: {[a.action_type for a in parsed_actions]}")
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actions.extend(parsed_actions)
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else:
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# 尝试解析为直接的JSON
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logger.warning(f"{self.log_prefix}LLM没有返回可用动作: {llm_content}")
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actions = self._create_complete_talk("LLM没有返回可用动作", available_actions)
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extracted_reasoning = extracted_reasoning or "LLM没有返回可用动作"
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actions = self._create_complete_talk(extracted_reasoning, available_actions)
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except Exception as json_e:
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logger.warning(f"{self.log_prefix}解析LLM响应JSON失败 {json_e}. LLM原始输出: '{llm_content}'")
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actions = self._create_complete_talk(f"解析LLM响应JSON失败: {json_e}", available_actions)
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extracted_reasoning = f"解析LLM响应JSON失败: {json_e}"
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actions = self._create_complete_talk(extracted_reasoning, available_actions)
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traceback.print_exc()
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else:
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actions = self._create_complete_talk("规划器没有获得LLM响应", available_actions)
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extracted_reasoning = "规划器没有获得LLM响应"
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actions = self._create_complete_talk(extracted_reasoning, available_actions)
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# 添加循环开始时间到所有动作
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for action in actions:
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@ -538,7 +553,7 @@ class BrainPlanner:
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f"{self.log_prefix}规划器决定执行{len(actions)}个动作: {' '.join([a.action_type for a in actions])}"
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)
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return actions
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return extracted_reasoning, actions
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def _create_complete_talk(self, reasoning: str, available_actions: Dict[str, ActionInfo]) -> List[ActionPlannerInfo]:
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"""创建complete_talk"""
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@ -551,34 +566,123 @@ class BrainPlanner:
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available_actions=available_actions,
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)
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]
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def add_plan_log(self, reasoning: str, actions: List[ActionPlannerInfo]):
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"""添加计划日志"""
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self.plan_log.append((reasoning, time.time(), actions))
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if len(self.plan_log) > 20:
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self.plan_log.pop(0)
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def _extract_json_from_markdown(self, content: str) -> List[dict]:
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def _extract_json_from_markdown(self, content: str) -> Tuple[List[dict], str]:
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# sourcery skip: for-append-to-extend
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"""从Markdown格式的内容中提取JSON对象"""
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"""从Markdown格式的内容中提取JSON对象和推理内容"""
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json_objects = []
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reasoning_content = ""
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# 使用正则表达式查找```json包裹的JSON内容
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json_pattern = r"```json\s*(.*?)\s*```"
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matches = re.findall(json_pattern, content, re.DOTALL)
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markdown_matches = re.findall(json_pattern, content, re.DOTALL)
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for match in matches:
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# 提取JSON之前的内容作为推理文本
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first_json_pos = len(content)
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if markdown_matches:
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# 找到第一个```json的位置
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first_json_pos = content.find("```json")
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if first_json_pos > 0:
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reasoning_content = content[:first_json_pos].strip()
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# 清理推理内容中的注释标记
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reasoning_content = re.sub(r"^//\s*", "", reasoning_content, flags=re.MULTILINE)
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reasoning_content = reasoning_content.strip()
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# 处理```json包裹的JSON
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for match in markdown_matches:
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try:
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# 清理可能的注释和格式问题
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json_str = re.sub(r"//.*?\n", "\n", match) # 移除单行注释
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json_str = re.sub(r"/\*.*?\*/", "", json_str, flags=re.DOTALL) # 移除多行注释
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if json_str := json_str.strip():
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json_obj = json.loads(repair_json(json_str))
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if isinstance(json_obj, dict):
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json_objects.append(json_obj)
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elif isinstance(json_obj, list):
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for item in json_obj:
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if isinstance(item, dict):
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json_objects.append(item)
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# 先尝试将整个块作为一个JSON对象或数组(适用于多行JSON)
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try:
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json_obj = json.loads(repair_json(json_str))
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if isinstance(json_obj, dict):
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json_objects.append(json_obj)
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elif isinstance(json_obj, list):
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for item in json_obj:
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if isinstance(item, dict):
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json_objects.append(item)
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except json.JSONDecodeError:
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# 如果整个块解析失败,尝试按行分割(适用于多个单行JSON对象)
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lines = [line.strip() for line in json_str.split("\n") if line.strip()]
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for line in lines:
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try:
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# 尝试解析每一行作为独立的JSON对象
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json_obj = json.loads(repair_json(line))
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if isinstance(json_obj, dict):
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json_objects.append(json_obj)
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elif isinstance(json_obj, list):
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for item in json_obj:
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if isinstance(item, dict):
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json_objects.append(item)
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except json.JSONDecodeError:
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# 单行解析失败,继续下一行
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continue
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except Exception as e:
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logger.warning(f"解析JSON块失败: {e}, 块内容: {match[:100]}...")
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logger.warning(f"{self.log_prefix}解析JSON块失败: {e}, 块内容: {match[:100]}...")
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continue
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return json_objects
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# 如果没有找到完整的```json```块,尝试查找不完整的代码块(缺少结尾```)
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if not json_objects:
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json_start_pos = content.find("```json")
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if json_start_pos != -1:
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# 找到```json之后的内容
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json_content_start = json_start_pos + 7 # ```json的长度
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# 提取从```json之后到内容结尾的所有内容
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incomplete_json_str = content[json_content_start:].strip()
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# 提取JSON之前的内容作为推理文本
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if json_start_pos > 0:
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reasoning_content = content[:json_start_pos].strip()
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reasoning_content = re.sub(r"^//\s*", "", reasoning_content, flags=re.MULTILINE)
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reasoning_content = reasoning_content.strip()
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if incomplete_json_str:
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try:
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# 清理可能的注释和格式问题
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json_str = re.sub(r"//.*?\n", "\n", incomplete_json_str)
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json_str = re.sub(r"/\*.*?\*/", "", json_str, flags=re.DOTALL)
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json_str = json_str.strip()
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if json_str:
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# 尝试按行分割,每行可能是一个JSON对象
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lines = [line.strip() for line in json_str.split("\n") if line.strip()]
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for line in lines:
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try:
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json_obj = json.loads(repair_json(line))
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if isinstance(json_obj, dict):
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json_objects.append(json_obj)
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elif isinstance(json_obj, list):
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for item in json_obj:
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if isinstance(item, dict):
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json_objects.append(item)
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except json.JSONDecodeError:
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pass
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# 如果按行解析没有成功,尝试将整个块作为一个JSON对象或数组
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if not json_objects:
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try:
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json_obj = json.loads(repair_json(json_str))
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if isinstance(json_obj, dict):
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json_objects.append(json_obj)
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elif isinstance(json_obj, list):
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for item in json_obj:
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if isinstance(item, dict):
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json_objects.append(item)
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except Exception as e:
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logger.debug(f"尝试解析不完整的JSON代码块失败: {e}")
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except Exception as e:
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logger.debug(f"处理不完整的JSON代码块时出错: {e}")
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return json_objects, reasoning_content
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init_prompt()
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