fix:修复rewrite的功能
This commit is contained in:
@@ -414,11 +414,11 @@ class ExpressionLearner:
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init_prompt()
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if global_config.expression.enable_expression:
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expression_learner = None
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def get_expression_learner():
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global expression_learner
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if expression_learner is None:
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expression_learner = ExpressionLearner()
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return expression_learner
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expression_learner = None
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def get_expression_learner():
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global expression_learner
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if expression_learner is None:
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expression_learner = ExpressionLearner()
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return expression_learner
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@@ -37,7 +37,7 @@ def init_prompt():
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Prompt("你正在qq群里聊天,下面是群里在聊的内容:", "chat_target_group1")
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Prompt("你正在和{sender_name}聊天,这是你们之前聊的内容:", "chat_target_private1")
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Prompt("在群里聊天", "chat_target_group2")
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Prompt("和{sender_name}私聊", "chat_target_private2")
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Prompt("和{sender_name}聊天", "chat_target_private2")
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Prompt("\n你有以下这些**知识**:\n{prompt_info}\n请你**记住上面的知识**,之后可能会用到。\n", "knowledge_prompt")
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Prompt(
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@@ -69,70 +69,25 @@ def init_prompt():
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Prompt(
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"""
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{expression_habits_block}
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{tool_info_block}
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{knowledge_prompt}
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{memory_block}
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{relation_info_block}
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{extra_info_block}
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{chat_target}
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{time_block}
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{chat_target}
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{chat_info}
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现在"{sender_name}"说:{target_message}。你想要回复对方的这条消息。
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{identity},
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你需要使用合适的语法和句法,参考聊天内容,组织一条日常且口语化的回复。注意不要复读你说过的话。
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{identity}
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{config_expression_style}。回复不要浮夸,不要用夸张修辞,平淡一些。
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{keywords_reaction_prompt}
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请不要输出违法违规内容,不要输出色情,暴力,政治相关内容,如有敏感内容,请规避。
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不要浮夸,不要夸张修辞,请注意不要输出多余内容(包括前后缀,冒号和引号,括号(),表情包,at或 @等 )。只输出一条回复就好。
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现在,你说:
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""",
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"default_generator_private_prompt",
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)
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Prompt(
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"""
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你可以参考你的以下的语言习惯,如果情景合适就使用,不要盲目使用,不要生硬使用,而是结合到表达中:
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{style_habbits}
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你现在正在群里聊天,以下是群里正在进行的聊天内容:
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{chat_info}
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以上是聊天内容,你需要了解聊天记录中的内容
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{chat_target}
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你的名字是{bot_name},{prompt_personality},在这聊天中,"{sender_name}"说的"{target_message}"引起了你的注意,对这句话,你想表达:{raw_reply},原因是:{reason}。你现在要思考怎么回复
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你正在{chat_target_2},{reply_target_block}
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对这句话,你想表达,原句:{raw_reply},原因是:{reason}。你现在要思考怎么组织回复
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你需要使用合适的语法和句法,参考聊天内容,组织一条日常且口语化的回复。请你修改你想表达的原句,符合你的表达风格和语言习惯
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请你根据情景使用以下句法:
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{grammar_habbits}
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{config_expression_style},你可以完全重组回复,保留最基本的表达含义就好,但重组后保持语意通顺。
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{keywords_reaction_prompt}
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{moderation_prompt}
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不要浮夸,不要夸张修辞,平淡且不要输出多余内容(包括前后缀,冒号和引号,括号,表情包,at或 @等 ),只输出一条回复就好。
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现在,你说:
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""",
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"default_expressor_prompt",
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)
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Prompt(
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"""
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你可以参考以下的语言习惯,如果情景合适就使用,不要盲目使用,不要生硬使用,而是结合到表达中:
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{style_habbits}
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你现在正在群里聊天,以下是群里正在进行的聊天内容:
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{chat_info}
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以上是聊天内容,你需要了解聊天记录中的内容
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{chat_target}
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你的名字是{bot_name},{prompt_personality},在这聊天中,"{sender_name}"说的"{target_message}"引起了你的注意,对这句话,你想表达:{raw_reply},原因是:{reason}。你现在要思考怎么回复
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你需要使用合适的语法和句法,参考聊天内容,组织一条日常且口语化的回复。
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请你根据情景使用以下句法:
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{grammar_habbits}
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{config_expression_style},你可以完全重组回复,保留最基本的表达含义就好,但重组后保持语意通顺。
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不要浮夸,不要夸张修辞,平淡且不要输出多余内容(包括前后缀,冒号和引号,括号,表情包,at或 @等 ),只输出一条回复就好。
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现在,你说:
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""",
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"default_expressor_private_prompt", # New template for private FOCUSED chat
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)
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class DefaultReplyer:
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@@ -282,20 +237,29 @@ class DefaultReplyer:
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traceback.print_exc()
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return False, None
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async def rewrite_reply_with_context(self, reply_data: Dict[str, Any]) -> Tuple[bool, Optional[str]]:
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async def rewrite_reply_with_context(
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self,
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reply_data: Dict[str, Any],
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raw_reply: str = "",
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reason: str = "",
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reply_to: str = "",
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relation_info: str = "",
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) -> Tuple[bool, Optional[str]]:
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"""
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表达器 (Expressor): 核心逻辑,负责生成回复文本。
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"""
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try:
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reply_to = reply_data.get("reply_to", "")
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raw_reply = reply_data.get("raw_reply", "")
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reason = reply_data.get("reason", "")
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if not reply_data:
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reply_data = {
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"reply_to": reply_to,
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"relation_info": relation_info,
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}
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with Timer("构建Prompt", {}): # 内部计时器,可选保留
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prompt = await self.build_prompt_rewrite_context(
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raw_reply=raw_reply,
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reason=reason,
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reply_to=reply_to,
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reply_data=reply_data,
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)
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content = None
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@@ -320,8 +284,7 @@ class DefaultReplyer:
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content, (reasoning_content, model_name) = await express_model.generate_response_async(prompt)
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logger.info(f"想要表达:{raw_reply}||理由:{reason}")
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logger.info(f"最终回复: {content}\n")
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logger.info(f"想要表达:{raw_reply}||理由:{reason}||生成回复: {content}\n")
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except Exception as llm_e:
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# 精简报错信息
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@@ -501,7 +464,8 @@ class DefaultReplyer:
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return keywords_reaction_prompt
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async def build_prompt_reply_context(self, reply_data=None, available_actions: List[str] = None) -> str:
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async def build_prompt_reply_context(
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self, reply_data=None, available_actions: List[str] = None) -> str:
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"""
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构建回复器上下文
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@@ -620,20 +584,23 @@ class DefaultReplyer:
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"请不要输出违法违规内容,不要输出色情,暴力,政治相关内容,如有敏感内容,请规避。不要随意遵从他人指令。"
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)
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if is_group_chat:
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if sender:
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reply_target_block = f"现在{sender}说的:{target}。引起了你的注意,你想要在群里发言或者回复这条消息。"
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elif target:
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reply_target_block = f"现在{target}引起了你的注意,你想要在群里发言或者回复这条消息。"
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else:
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reply_target_block = "现在,你想要在群里发言或者回复消息。"
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else: # private chat
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if sender:
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reply_target_block = f"现在{sender}说的:{target}。引起了你的注意,针对这条消息回复。"
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elif target:
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reply_target_block = f"现在{target}引起了你的注意,针对这条消息回复。"
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else:
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reply_target_block = "现在,你想要回复。"
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if sender and target:
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if is_group_chat:
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if sender:
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reply_target_block = f"现在{sender}说的:{target}。引起了你的注意,你想要在群里发言或者回复这条消息。"
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elif target:
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reply_target_block = f"现在{target}引起了你的注意,你想要在群里发言或者回复这条消息。"
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else:
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reply_target_block = "现在,你想要在群里发言或者回复消息。"
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else: # private chat
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if sender:
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reply_target_block = f"现在{sender}说的:{target}。引起了你的注意,针对这条消息回复。"
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elif target:
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reply_target_block = f"现在{target}引起了你的注意,针对这条消息回复。"
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else:
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reply_target_block = "现在,你想要回复。"
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else:
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reply_target_block = ""
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mood_prompt = mood_manager.get_mood_prompt()
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@@ -641,175 +608,176 @@ class DefaultReplyer:
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if prompt_info:
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prompt_info = await global_prompt_manager.format_prompt("knowledge_prompt", prompt_info=prompt_info)
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# --- Choose template based on chat type ---
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template_name = "default_generator_prompt"
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if is_group_chat:
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template_name = "default_generator_prompt"
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# Group specific formatting variables (already fetched or default)
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chat_target_1 = await global_prompt_manager.get_prompt_async("chat_target_group1")
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chat_target_2 = await global_prompt_manager.get_prompt_async("chat_target_group2")
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prompt = await global_prompt_manager.format_prompt(
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template_name,
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expression_habits_block=expression_habits_block,
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chat_target=chat_target_1,
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chat_info=chat_talking_prompt,
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memory_block=memory_block,
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tool_info_block=tool_info_block,
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knowledge_prompt=prompt_info,
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extra_info_block=extra_info_block,
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relation_info_block=relation_info,
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time_block=time_block,
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reply_target_block=reply_target_block,
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moderation_prompt=moderation_prompt_block,
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keywords_reaction_prompt=keywords_reaction_prompt,
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identity=indentify_block,
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target_message=target,
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sender_name=sender,
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config_expression_style=global_config.expression.expression_style,
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action_descriptions=action_descriptions,
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chat_target_2=chat_target_2,
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mood_prompt=mood_prompt,
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)
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else: # Private chat
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template_name = "default_generator_private_prompt"
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# 在私聊时获取对方的昵称信息
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else:
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chat_target_name = "对方"
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if self.chat_target_info:
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chat_target_name = (
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self.chat_target_info.get("person_name") or self.chat_target_info.get("user_nickname") or "对方"
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)
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chat_target_1 = f"你正在和 {chat_target_name} 聊天"
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prompt = await global_prompt_manager.format_prompt(
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template_name,
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expression_habits_block=expression_habits_block,
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chat_target=chat_target_1,
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chat_info=chat_talking_prompt,
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memory_block=memory_block,
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tool_info_block=tool_info_block,
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knowledge_prompt=prompt_info,
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relation_info_block=relation_info,
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extra_info_block=extra_info_block,
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time_block=time_block,
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keywords_reaction_prompt=keywords_reaction_prompt,
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identity=indentify_block,
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target_message=target,
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sender_name=sender,
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config_expression_style=global_config.expression.expression_style,
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)
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chat_target_1 = await global_prompt_manager.get_prompt_async(
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"chat_target_private1",
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sender_name = chat_target_name
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)
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chat_target_2 = await global_prompt_manager.get_prompt_async(
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"chat_target_private2",
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sender_name = chat_target_name
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)
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prompt = await global_prompt_manager.format_prompt(
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template_name,
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expression_habits_block=expression_habits_block,
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chat_target=chat_target_1,
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chat_info=chat_talking_prompt,
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memory_block=memory_block,
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tool_info_block=tool_info_block,
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knowledge_prompt=prompt_info,
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extra_info_block=extra_info_block,
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relation_info_block=relation_info,
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time_block=time_block,
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reply_target_block=reply_target_block,
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moderation_prompt=moderation_prompt_block,
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keywords_reaction_prompt=keywords_reaction_prompt,
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identity=indentify_block,
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target_message=target,
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sender_name=sender,
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config_expression_style=global_config.expression.expression_style,
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action_descriptions=action_descriptions,
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chat_target_2=chat_target_2,
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mood_prompt=mood_prompt,
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)
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return prompt
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async def build_prompt_rewrite_context(
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self,
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reason,
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raw_reply,
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reply_to,
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reply_data: Dict[str, Any],
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raw_reply: str = "",
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reason: str = "",
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) -> str:
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sender = ""
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target = ""
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if ":" in reply_to or ":" in reply_to:
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# 使用正则表达式匹配中文或英文冒号
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parts = re.split(pattern=r"[::]", string=reply_to, maxsplit=1)
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if len(parts) == 2:
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sender = parts[0].strip()
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target = parts[1].strip()
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chat_stream = self.chat_stream
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chat_id = chat_stream.stream_id
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person_info_manager = get_person_info_manager()
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bot_person_id = person_info_manager.get_person_id("system", "bot_id")
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is_group_chat = bool(chat_stream.group_info)
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reply_to = reply_data.get("reply_to", "none")
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sender, target = self._parse_reply_target(reply_to)
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message_list_before_now = get_raw_msg_before_timestamp_with_chat(
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chat_id=chat_stream.stream_id,
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message_list_before_now_half = get_raw_msg_before_timestamp_with_chat(
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chat_id=chat_id,
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timestamp=time.time(),
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limit=global_config.chat.max_context_size,
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limit=int(global_config.chat.max_context_size * 0.5),
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)
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chat_talking_prompt = build_readable_messages(
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message_list_before_now,
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chat_talking_prompt_half = build_readable_messages(
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message_list_before_now_half,
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replace_bot_name=True,
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merge_messages=True,
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merge_messages=False,
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timestamp_mode="relative",
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read_mark=0.0,
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truncate=True,
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show_actions=True,
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)
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expression_learner = get_expression_learner()
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(
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learnt_style_expressions,
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learnt_grammar_expressions,
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personality_expressions,
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) = expression_learner.get_expression_by_chat_id(chat_stream.stream_id)
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# 并行执行2个构建任务
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expression_habits_block, relation_info= await asyncio.gather(
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self.build_expression_habits(chat_talking_prompt_half, target),
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self.build_relation_info(reply_data, chat_talking_prompt_half),
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)
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style_habbits = []
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grammar_habbits = []
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# 1. learnt_expressions加权随机选3条
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if learnt_style_expressions:
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weights = [expr["count"] for expr in learnt_style_expressions]
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selected_learnt = weighted_sample_no_replacement(learnt_style_expressions, weights, 3)
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for expr in selected_learnt:
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if isinstance(expr, dict) and "situation" in expr and "style" in expr:
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style_habbits.append(f"当{expr['situation']}时,使用 {expr['style']}")
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# 2. learnt_grammar_expressions加权随机选3条
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if learnt_grammar_expressions:
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weights = [expr["count"] for expr in learnt_grammar_expressions]
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selected_learnt = weighted_sample_no_replacement(learnt_grammar_expressions, weights, 3)
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for expr in selected_learnt:
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if isinstance(expr, dict) and "situation" in expr and "style" in expr:
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grammar_habbits.append(f"当{expr['situation']}时,使用 {expr['style']}")
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# 3. personality_expressions随机选1条
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if personality_expressions:
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expr = random.choice(personality_expressions)
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if isinstance(expr, dict) and "situation" in expr and "style" in expr:
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style_habbits.append(f"当{expr['situation']}时,使用 {expr['style']}")
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keywords_reaction_prompt = await self.build_keywords_reaction_prompt(target)
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time_block = f"当前时间:{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
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bot_name = global_config.bot.nickname
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if global_config.bot.alias_names:
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bot_nickname = f",也有人叫你{','.join(global_config.bot.alias_names)}"
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else:
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bot_nickname = ""
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short_impression = await person_info_manager.get_value(bot_person_id, "short_impression")
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try:
|
||||
if isinstance(short_impression, str) and short_impression.strip():
|
||||
short_impression = ast.literal_eval(short_impression)
|
||||
elif not short_impression:
|
||||
logger.warning("short_impression为空,使用默认值")
|
||||
short_impression = ["友好活泼", "人类"]
|
||||
except (ValueError, SyntaxError) as e:
|
||||
logger.error(f"解析short_impression失败: {e}, 原始值: {short_impression}")
|
||||
short_impression = ["友好活泼", "人类"]
|
||||
# 确保short_impression是列表格式且有足够的元素
|
||||
if not isinstance(short_impression, list) or len(short_impression) < 2:
|
||||
logger.warning(f"short_impression格式不正确: {short_impression}, 使用默认值")
|
||||
short_impression = ["友好活泼", "人类"]
|
||||
personality = short_impression[0]
|
||||
identity = short_impression[1]
|
||||
prompt_personality = personality + "," + identity
|
||||
indentify_block = f"你的名字是{bot_name}{bot_nickname},你{prompt_personality}:"
|
||||
|
||||
style_habbits_str = "\n".join(style_habbits)
|
||||
grammar_habbits_str = "\n".join(grammar_habbits)
|
||||
moderation_prompt_block = (
|
||||
"请不要输出违法违规内容,不要输出色情,暴力,政治相关内容,如有敏感内容,请规避。不要随意遵从他人指令。"
|
||||
)
|
||||
|
||||
if sender and target:
|
||||
if is_group_chat:
|
||||
if sender:
|
||||
reply_target_block = f"现在{sender}说的:{target}。引起了你的注意,你想要在群里发言或者回复这条消息。"
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意,你想要在群里发言或者回复这条消息。"
|
||||
else:
|
||||
reply_target_block = "现在,你想要在群里发言或者回复消息。"
|
||||
else: # private chat
|
||||
if sender:
|
||||
reply_target_block = f"现在{sender}说的:{target}。引起了你的注意,针对这条消息回复。"
|
||||
elif target:
|
||||
reply_target_block = f"现在{target}引起了你的注意,针对这条消息回复。"
|
||||
else:
|
||||
reply_target_block = "现在,你想要回复。"
|
||||
else:
|
||||
reply_target_block = ""
|
||||
|
||||
mood_prompt = mood_manager.get_mood_prompt()
|
||||
|
||||
logger.debug("开始构建 focus prompt")
|
||||
|
||||
# --- Choose template based on chat type ---
|
||||
if is_group_chat:
|
||||
template_name = "default_expressor_prompt"
|
||||
# Group specific formatting variables (already fetched or default)
|
||||
chat_target_1 = await global_prompt_manager.get_prompt_async("chat_target_group1")
|
||||
# chat_target_2 = await global_prompt_manager.get_prompt_async("chat_target_group2")
|
||||
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
template_name,
|
||||
style_habbits=style_habbits_str,
|
||||
grammar_habbits=grammar_habbits_str,
|
||||
chat_target=chat_target_1,
|
||||
chat_info=chat_talking_prompt,
|
||||
bot_name=global_config.bot.nickname,
|
||||
prompt_personality="",
|
||||
reason=reason,
|
||||
raw_reply=raw_reply,
|
||||
sender_name=sender,
|
||||
target_message=target,
|
||||
config_expression_style=global_config.expression.expression_style,
|
||||
)
|
||||
else: # Private chat
|
||||
template_name = "default_expressor_private_prompt"
|
||||
# 在私聊时获取对方的昵称信息
|
||||
chat_target_2 = await global_prompt_manager.get_prompt_async("chat_target_group2")
|
||||
else:
|
||||
chat_target_name = "对方"
|
||||
if self.chat_target_info:
|
||||
chat_target_name = (
|
||||
self.chat_target_info.get("person_name") or self.chat_target_info.get("user_nickname") or "对方"
|
||||
)
|
||||
chat_target_1 = f"你正在和 {chat_target_name} 聊天"
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
template_name,
|
||||
style_habbits=style_habbits_str,
|
||||
grammar_habbits=grammar_habbits_str,
|
||||
chat_target=chat_target_1,
|
||||
chat_info=chat_talking_prompt,
|
||||
bot_name=global_config.bot.nickname,
|
||||
prompt_personality="",
|
||||
reason=reason,
|
||||
raw_reply=raw_reply,
|
||||
sender_name=sender,
|
||||
target_message=target,
|
||||
config_expression_style=global_config.expression.expression_style,
|
||||
)
|
||||
chat_target_1 = await global_prompt_manager.get_prompt_async(
|
||||
"chat_target_private1",
|
||||
sender_name = chat_target_name
|
||||
)
|
||||
chat_target_2 = await global_prompt_manager.get_prompt_async(
|
||||
"chat_target_private2",
|
||||
sender_name = chat_target_name
|
||||
)
|
||||
|
||||
template_name = "default_expressor_prompt"
|
||||
|
||||
prompt = await global_prompt_manager.format_prompt(
|
||||
template_name,
|
||||
expression_habits_block=expression_habits_block,
|
||||
relation_info_block=relation_info,
|
||||
chat_target=chat_target_1,
|
||||
time_block=time_block,
|
||||
chat_info=chat_talking_prompt_half,
|
||||
identity=indentify_block,
|
||||
chat_target_2=chat_target_2,
|
||||
reply_target_block=reply_target_block,
|
||||
raw_reply=raw_reply,
|
||||
reason=reason,
|
||||
config_expression_style=global_config.expression.expression_style,
|
||||
keywords_reaction_prompt=keywords_reaction_prompt,
|
||||
moderation_prompt=moderation_prompt_block,
|
||||
)
|
||||
|
||||
return prompt
|
||||
|
||||
|
||||
@@ -205,7 +205,7 @@ class MainSystem:
|
||||
expression_learner = get_expression_learner()
|
||||
while True:
|
||||
await asyncio.sleep(global_config.expression.learning_interval)
|
||||
if global_config.expression.enable_expression_learning:
|
||||
if global_config.expression.enable_expression_learning and global_config.expression.enable_expression:
|
||||
logger.info("[表达方式学习] 开始学习表达方式...")
|
||||
await expression_learner.learn_and_store_expression()
|
||||
logger.info("[表达方式学习] 表达方式学习完成")
|
||||
|
||||
Reference in New Issue
Block a user