frrr
This commit is contained in:
SengokuCola
@@ -15,9 +15,7 @@ from src.plugins.models.utils_model import LLMRequest
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from src.config.config import global_config
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from src.plugins.chat.utils_image import image_path_to_base64 # Local import needed after move
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from src.plugins.utils.timer_calculator import Timer # <--- Import Timer
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from src.do_tool.tool_use import ToolUser
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from src.plugins.emoji_system.emoji_manager import emoji_manager
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from src.plugins.utils.json_utils import process_llm_tool_calls, extract_tool_call_arguments
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from src.heart_flow.sub_mind import SubMind
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from src.heart_flow.observation import Observation
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from src.plugins.heartFC_chat.heartflow_prompt_builder import global_prompt_manager, prompt_builder
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@@ -788,7 +786,9 @@ class HeartFChatting:
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logger.info(f"{self.log_prefix}[Planner] 连续回复 2 次，80% 概率移除 text_reply 和 emoji_reply (触发)")
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actions_to_remove_temporarily.extend(["text_reply", "emoji_reply"])
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else:
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logger.info(f"{self.log_prefix}[Planner] 连续回复 2 次，80% 概率移除 text_reply 和 emoji_reply (未触发)")
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logger.info(
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f"{self.log_prefix}[Planner] 连续回复 2 次，80% 概率移除 text_reply 和 emoji_reply (未触发)"
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)
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elif lian_xu_wen_ben_hui_fu == 1:
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if probability_roll < 0.4:
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logger.info(f"{self.log_prefix}[Planner] 连续回复 1 次，40% 概率移除 text_reply (触发)")
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@@ -805,10 +805,10 @@ class HeartFChatting:
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observed_messages_str = observation.talking_message_str_truncate
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# --- 使用 LLM 进行决策 (JSON 输出模式) --- #
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action = "no_reply" # 默认动作
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action = "no_reply" # 默认动作
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reasoning = "规划器初始化默认"
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emoji_query = ""
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llm_error = False # LLM 请求或解析错误标志
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llm_error = False # LLM 请求或解析错误标志
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# 获取我们将传递给 prompt 构建器和用于验证的当前可用动作
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current_available_actions = self.action_manager.get_available_actions()
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@@ -833,8 +833,8 @@ class HeartFChatting:
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observed_messages_str,
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current_mind,
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self.sub_mind.structured_info,
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"", # replan_prompt_str,
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current_available_actions # <--- 传入当前可用动作
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"", # replan_prompt_str,
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current_available_actions, # <--- 传入当前可用动作
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)
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# --- 调用 LLM (普通文本生成) ---
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@@ -851,8 +851,8 @@ class HeartFChatting:
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reasoning = f"LLM 请求失败: {req_e}"
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llm_error = True
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# 直接使用默认动作返回错误结果
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action = "no_reply" # 明确设置为默认值
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emoji_query = "" # 明确设置为空
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action = "no_reply" # 明确设置为默认值
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emoji_query = "" # 明确设置为空
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# 不再立即返回，而是继续执行 finally 块以恢复动作
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# return { ... }
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@@ -860,9 +860,11 @@ class HeartFChatting:
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if not llm_error and llm_content:
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try:
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# 尝试去除可能的 markdown 代码块标记
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cleaned_content = llm_content.strip().removeprefix("```json").removeprefix("```").removesuffix("```").strip()
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cleaned_content = (
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llm_content.strip().removeprefix("```json").removeprefix("```").removesuffix("```").strip()
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)
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if not cleaned_content:
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raise json.JSONDecodeError("Cleaned content is empty", cleaned_content, 0)
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raise json.JSONDecodeError("Cleaned content is empty", cleaned_content, 0)
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parsed_json = json.loads(cleaned_content)
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# 提取决策，提供默认值
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@@ -881,28 +883,32 @@ class HeartFChatting:
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emoji_query = ""
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# 检查 no_reply 是否也恰好被移除了 (极端情况)
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if "no_reply" not in current_available_actions:
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logger.error(f"{self.log_prefix}[Planner] 严重错误：'no_reply' 动作也不可用！无法执行任何动作。")
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action = "error" # 回退到错误状态
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reasoning = "无法执行任何有效动作，包括 no_reply"
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llm_error = True # 标记为严重错误
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logger.error(
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f"{self.log_prefix}[Planner] 严重错误：'no_reply' 动作也不可用！无法执行任何动作。"
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)
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action = "error" # 回退到错误状态
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reasoning = "无法执行任何有效动作，包括 no_reply"
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llm_error = True # 标记为严重错误
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else:
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llm_error = False # 视为逻辑修正而非 LLM 错误
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llm_error = False # 视为逻辑修正而非 LLM 错误
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else:
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# 动作有效且可用
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action = extracted_action
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reasoning = extracted_reasoning
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emoji_query = extracted_emoji_query
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llm_error = False # 解析成功
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llm_error = False # 解析成功
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logger.debug(
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f"{self.log_prefix}[要做什么]\nPrompt:\n{prompt}\n\n决策结果 (来自JSON): {action}, 理由: {reasoning}, 表情查询: '{emoji_query}'"
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f"{self.log_prefix}[要做什么]\nPrompt:\n{prompt}\n\n决策结果 (来自JSON): {action}, 理由: {reasoning}, 表情查询: '{emoji_query}'"
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)
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except json.JSONDecodeError as json_e:
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logger.warning(f"{self.log_prefix}[Planner] 解析LLM响应JSON失败: {json_e}. LLM原始输出: '{llm_content}'")
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logger.warning(
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f"{self.log_prefix}[Planner] 解析LLM响应JSON失败: {json_e}. LLM原始输出: '{llm_content}'"
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)
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reasoning = f"解析LLM响应JSON失败: {json_e}. 将使用默认动作 'no_reply'."
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action = "no_reply" # 解析失败则默认不回复
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action = "no_reply" # 解析失败则默认不回复
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emoji_query = ""
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llm_error = True # 标记解析错误
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llm_error = True # 标记解析错误
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except Exception as parse_e:
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logger.error(f"{self.log_prefix}[Planner] 处理LLM响应时发生意外错误: {parse_e}")
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reasoning = f"处理LLM响应时发生意外错误: {parse_e}. 将使用默认动作 'no_reply'."
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@@ -910,12 +916,12 @@ class HeartFChatting:
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emoji_query = ""
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llm_error = True
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elif not llm_error and not llm_content:
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# LLM 请求成功但返回空内容
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# LLM 请求成功但返回空内容
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logger.warning(f"{self.log_prefix}[Planner] LLM 返回了空内容。")
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reasoning = "LLM 返回了空内容，使用默认动作 'no_reply'."
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action = "no_reply"
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emoji_query = ""
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llm_error = True # 标记为空响应错误
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llm_error = True # 标记为空响应错误
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# 如果 llm_error 在此阶段为 True，意味着请求成功但解析失败或返回空
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# 如果 llm_error 在请求阶段就为 True，则跳过了此解析块
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@@ -923,7 +929,7 @@ class HeartFChatting:
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except Exception as outer_e:
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logger.error(f"{self.log_prefix}[Planner] Planner 处理过程中发生意外错误: {outer_e}")
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logger.error(traceback.format_exc())
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action = "error" # 发生未知错误，标记为 error 动作
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action = "error" # 发生未知错误，标记为 error 动作
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reasoning = f"Planner 内部处理错误: {outer_e}"
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emoji_query = ""
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llm_error = True
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@@ -944,7 +950,7 @@ class HeartFChatting:
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logger.info(
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f"{self.log_prefix}[Planner] 但是麦麦这次不想加表情 ({1 - EMOJI_SEND_PRO:.0%})，忽略表情 '{emoji_query}'"
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)
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emoji_query = "" # 清空表情请求
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emoji_query = "" # 清空表情请求
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else:
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logger.info(f"{self.log_prefix}[Planner] 好吧，加上表情 '{emoji_query}'")
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# --- 结束概率性忽略 ---
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@@ -956,7 +962,7 @@ class HeartFChatting:
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"emoji_query": emoji_query,
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"current_mind": current_mind,
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"observed_messages": observed_messages,
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"llm_error": llm_error, # 返回错误状态
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"llm_error": llm_error, # 返回错误状态
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}
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async def _get_anchor_message(self) -> Optional[MessageRecv]:
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@@ -1178,26 +1184,26 @@ class HeartFChatting:
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action_options_text = "当前你可以选择的行动有：\n"
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action_keys = list(current_available_actions.keys())
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for name in action_keys:
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desc = current_available_actions[name]
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action_options_text += f"- '{name}': {desc}\n"
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desc = current_available_actions[name]
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action_options_text += f"- '{name}': {desc}\n"
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# --- 选择一个示例动作键 (用于填充模板中的 {example_action}) ---
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example_action_key = action_keys[0] if action_keys else "no_reply"
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# --- 获取提示词模板 ---
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# --- 获取提示词模板 ---
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planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt")
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# --- 填充模板 ---
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# --- 填充模板 ---
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prompt = planner_prompt_template.format(
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bot_name=global_config.BOT_NICKNAME,
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prompt_personality=prompt_personality,
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structured_info_block=structured_info_block,
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chat_content_block=chat_content_block,
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current_mind_block=current_mind_block,
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replan="", # 暂时留空 replan 信息
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current_mind_block=current_mind_block,
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replan="", # 暂时留空 replan 信息
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cycle_info_block=cycle_info_block,
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action_options_text=action_options_text, # 传入可用动作描述
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example_action=example_action_key # 传入示例动作键
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action_options_text=action_options_text, # 传入可用动作描述
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example_action=example_action_key, # 传入示例动作键
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)
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return prompt
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@@ -1205,7 +1211,7 @@ class HeartFChatting:
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except Exception as e:
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logger.error(f"{self.log_prefix}[Planner] 构建提示词时出错: {e}")
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logger.error(traceback.format_exc())
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return "[构建 Planner Prompt 时出错]" # 返回错误提示，避免空字符串
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return "[构建 Planner Prompt 时出错]" # 返回错误提示，避免空字符串
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# --- 回复器 (Replier) 的定义 --- #
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async def _replier_work(
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