🤖 自动格式化代码 [skip ci]
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@@ -18,12 +18,11 @@ class ChangeMoodTool(BaseTool):
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"type": "object",
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"properties": {
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"text": {"type": "string", "description": "引起你改变心情的文本"},
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"response_set": {"type": "list", "description": "你对文本的回复"}
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"response_set": {"type": "list", "description": "你对文本的回复"},
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},
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"required": ["text", "response_set"],
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}
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async def execute(self, function_args: Dict[str, Any], message_txt: str) -> Dict[str, Any]:
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"""执行心情改变
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@@ -6,28 +6,19 @@ from src.do_tool.tool_can_use.base_tool import BaseTool
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logger = get_module_logger("relationship_tool")
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class RelationshipTool(BaseTool):
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name = "change_relationship"
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description = "根据收到的文本和回复内容,修改与特定用户的关系值,当你回复了别人的消息,你可以使用这个工具"
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parameters = {
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"type": "object",
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"properties": {
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"text": {
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"type": "string",
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"description": "收到的文本"
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"text": {"type": "string", "description": "收到的文本"},
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"changed_value": {"type": "number", "description": "变更值"},
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"reason": {"type": "string", "description": "变更原因"},
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},
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"changed_value": {
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"type": "number",
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"description": "变更值"
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},
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"reason": {
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"type": "string",
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"description": "变更原因"
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"required": ["text", "changed_value", "reason"],
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}
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},
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"required": ["text", "changed_value", "reason"]
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}
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async def execute(self, args: dict, message_txt: str) -> dict:
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"""执行工具功能
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@@ -21,7 +21,9 @@ class ToolUser:
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model=global_config.llm_heartflow, temperature=0.2, max_tokens=1000, request_type="tool_use"
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)
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async def _build_tool_prompt(self, message_txt: str, sender_name: str, chat_stream: ChatStream, reply_message:str = ""):
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async def _build_tool_prompt(
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self, message_txt: str, sender_name: str, chat_stream: ChatStream, reply_message: str = ""
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):
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"""构建工具使用的提示词
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Args:
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@@ -166,7 +168,7 @@ class ToolUser:
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"knowledge": [],
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"change_relationship": [],
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"change_mood": [],
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"other": []
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"other": [],
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}
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# 执行所有工具调用
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@@ -175,18 +177,12 @@ class ToolUser:
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if result:
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tool_results.append(result)
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# 将工具结果添加到对应类型的列表中
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structured_info[result["type"]].append({
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"name": result["name"],
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"content": result["content"]
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})
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structured_info[result["type"]].append({"name": result["name"], "content": result["content"]})
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# 如果有工具结果,返回结构化的信息
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if any(structured_info.values()):
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logger.info(f"工具调用收集到结构化信息: {json.dumps(structured_info, ensure_ascii=False)}")
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return {
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"used_tools": True,
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"structured_info": structured_info
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}
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return {"used_tools": True, "structured_info": structured_info}
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else:
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# 没有工具调用
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content, reasoning_content = response
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@@ -97,8 +97,6 @@ class SubHeartflow:
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self.bot_name = global_config.BOT_NICKNAME
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def add_observation(self, observation: Observation):
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"""添加一个新的observation对象到列表中,如果已存在相同id的observation则不添加"""
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# 查找是否存在相同id的observation
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@@ -151,15 +149,15 @@ class SubHeartflow:
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observation = self.observations[0]
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await observation.observe()
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async def do_thinking_before_reply(self, message_txt: str, sender_name: str, chat_stream: ChatStream, extra_info: str):
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async def do_thinking_before_reply(
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self, message_txt: str, sender_name: str, chat_stream: ChatStream, extra_info: str
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):
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current_thinking_info = self.current_mind
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mood_info = self.current_state.mood
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# mood_info = "你很生气,很愤怒"
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observation = self.observations[0]
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chat_observe_info = observation.observe_info
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# 开始构建prompt
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prompt_personality = f"你的名字是{self.bot_name},你"
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# person
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@@ -136,8 +136,6 @@ class ThinkFlowChat:
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message_manager.add_message(bot_message)
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async def _update_relationship(self, message: MessageRecv, response_set):
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"""更新关系情绪"""
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ori_response = ",".join(response_set)
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@@ -265,11 +263,12 @@ class ThinkFlowChat:
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update_relationship = ""
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try:
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with Timer("思考前使用工具", timing_results):
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tool_result = await self.tool_user.use_tool(message.processed_plain_text, message.message_info.user_info.user_nickname, chat)
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tool_result = await self.tool_user.use_tool(
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message.processed_plain_text, message.message_info.user_info.user_nickname, chat
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)
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# 如果工具被使用且获得了结果,将收集到的信息合并到思考中
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collected_info = ""
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if tool_result.get("used_tools", False):
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# 如果有收集到的结构化信息,将其格式化后添加到当前思考中
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if "structured_info" in tool_result:
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info = tool_result["structured_info"]
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@@ -315,17 +314,17 @@ class ThinkFlowChat:
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logger.error(f"思考前工具调用失败: {e}")
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logger.error(traceback.format_exc())
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if update_relationship:
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# ori_response = ",".join(response_set)
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# print("22222222222222222222222222222")
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stance, emotion = await self.gpt._get_emotion_tags_with_reason("你还没有回复", message.processed_plain_text,update_relationship)
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stance, emotion = await self.gpt._get_emotion_tags_with_reason(
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"你还没有回复", message.processed_plain_text, update_relationship
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)
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await relationship_manager.calculate_update_relationship_value(
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chat_stream=message.chat_stream, label=emotion, stance=stance
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)
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print("33333333333333333333333333333")
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# 思考前脑内状态
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try:
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with Timer("思考前脑内状态", timing_results):
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@@ -335,7 +334,7 @@ class ThinkFlowChat:
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message_txt=message.processed_plain_text,
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sender_name=message.message_info.user_info.user_nickname,
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chat_stream=chat,
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extra_info=collected_info
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extra_info=collected_info,
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)
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except Exception as e:
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logger.error(f"心流思考前脑内状态失败: {e}")
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@@ -370,15 +369,15 @@ class ThinkFlowChat:
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except Exception as e:
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logger.error(f"心流处理表情包失败: {e}")
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# 思考后使用工具
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try:
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with Timer("思考后使用工具", timing_results):
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tool_result = await self.tool_user.use_tool(message.processed_plain_text, message.message_info.user_info.user_nickname, chat)
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tool_result = await self.tool_user.use_tool(
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message.processed_plain_text, message.message_info.user_info.user_nickname, chat
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)
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# 如果工具被使用且获得了结果,将收集到的信息合并到思考中
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collected_info = ""
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if tool_result.get("used_tools", False):
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# 如果有收集到的结构化信息,将其格式化后添加到当前思考中
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if "structured_info" in tool_result:
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info = tool_result["structured_info"]
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@@ -424,13 +423,13 @@ class ThinkFlowChat:
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# 更新关系
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if info["change_relationship"]:
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ori_response = ",".join(response_set)
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stance, emotion = await self.gpt._get_emotion_tags(ori_response, message.processed_plain_text,info["change_relationship"]["content"])
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stance, emotion = await self.gpt._get_emotion_tags(
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ori_response, message.processed_plain_text, info["change_relationship"]["content"]
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)
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await relationship_manager.calculate_update_relationship_value(
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chat_stream=message.chat_stream, label=emotion, stance=stance
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)
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try:
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with Timer("思考后脑内状态更新", timing_results):
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stream_id = message.chat_stream.stream_id
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@@ -440,11 +439,12 @@ class ThinkFlowChat:
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stream_id, limit=global_config.MAX_CONTEXT_SIZE, combine=True
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)
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await heartflow.get_subheartflow(stream_id).do_thinking_after_reply(response_set, chat_talking_prompt,collected_info)
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await heartflow.get_subheartflow(stream_id).do_thinking_after_reply(
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response_set, chat_talking_prompt, collected_info
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)
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except Exception as e:
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logger.error(f"心流思考后脑内状态更新失败: {e}")
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# 回复后处理
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await willing_manager.after_generate_reply_handle(message.message_info.message_id)
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@@ -226,7 +226,6 @@ class ResponseGenerator:
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logger.debug(f"获取情感标签时出错: {e}")
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return "中立", "平静" # 出错时返回默认值
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async def _get_emotion_tags_with_reason(self, content: str, processed_plain_text: str, reason: str):
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"""提取情感标签,结合立场和情绪"""
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try:
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@@ -162,7 +162,9 @@ class RelationshipManager:
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return chat_stream.user_info.user_nickname, value, relationship_level[level_num]
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async def calculate_update_relationship_value_with_reason(self, chat_stream: ChatStream, label: str, stance: str, reason: str) -> tuple:
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async def calculate_update_relationship_value_with_reason(
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self, chat_stream: ChatStream, label: str, stance: str, reason: str
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) -> tuple:
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"""计算并变更关系值
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新的关系值变更计算方式:
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将关系值限定在-1000到1000
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