From b0c7daa1e4049eee77ef927b3e85f38a1bc36d65 Mon Sep 17 00:00:00 2001 From: 2829798842 <2829798842@qq.com> Date: Wed, 28 May 2025 21:10:06 +0800 Subject: [PATCH] Update mind_processor.py --- .../info_processors/mind_processor.py | 52 +++++++++---------- 1 file changed, 26 insertions(+), 26 deletions(-) diff --git a/src/chat/focus_chat/info_processors/mind_processor.py b/src/chat/focus_chat/info_processors/mind_processor.py index 74921c05..2a1642ad 100644 --- a/src/chat/focus_chat/info_processors/mind_processor.py +++ b/src/chat/focus_chat/info_processors/mind_processor.py @@ -22,43 +22,43 @@ logger = get_logger("processor") def init_prompt(): group_prompt = """ -Your name is {bot_name} +你的名字是{bot_name} {memory_str} {extra_info} {relation_prompt} {cycle_info_block} -It is currently {time_now}, you are online, chatting with netizens in a QQ group, the following is the ongoing chat content: +现在是{time_now}，你正在上网，和qq群里的网友们聊天，以下是正在进行的聊天内容： {chat_observe_info} -Below are your previous observations and plans for the chat, your name is {bot_name}: +以下是你之前对聊天的观察和规划，你的名字是{bot_name}： {last_mind} -Now please continue to output observations and plans, output requirements: -1. First, pay attention to the content of unread new messages and recent reply history -2. Based on new information, modify and delete previous observations and plans -3. Continue to output observations and plans based on the chat content -4. Pay attention to the timeline of the group chat, who initiated the topic, how it is progressing, and think about the timeline of the chat. -6. The language should be concise and natural, without bullet points, exaggeration, or rhetoric, just output the thinking content.""" +现在请你继续输出观察和规划，输出要求： +1. 先关注未读新消息的内容和近期回复历史 +2. 根据新信息，修改和删除之前的观察和规划 +3. 根据聊天内容继续输出观察和规划 +4. 注意群聊的时间线索，话题由谁发起，进展状况如何，思考聊天的时间线。 +6. 语言简洁自然，不要分点，不要浮夸，不要修辞，仅输出思考内容就好""" Prompt(group_prompt, "sub_heartflow_prompt_before") private_prompt = """ -Your name is {bot_name} +你的名字是{bot_name} {memory_str} {extra_info} {relation_prompt} {cycle_info_block} -It is currently {time_now}, you are online, chatting with netizens in a QQ group, the following is the ongoing chat content: +现在是{time_now}，你正在上网，和qq群里的网友们聊天，以下是正在进行的聊天内容： {chat_observe_info} -Below are your previous observations and plans for the chat, your name is {bot_name}: +以下是你之前对聊天的观察和规划，你的名字是{bot_name}： {last_mind} -Now please continue to output observations and plans, output requirements: -1. First, pay attention to the content of unread new messages and recent reply history -2. Based on new information, modify and delete previous observations and plans -3. Continue to output observations and plans based on the chat content -4. Pay attention to the timeline of the group chat, who initiated the topic, how it is progressing, and think about the timeline of the chat. -6. The language should be concise and natural, without bullet points, exaggeration, or rhetoric, just output the thinking content.""" +现在请你继续输出观察和规划，输出要求： +1. 先关注未读新消息的内容和近期回复历史 +2. 根据新信息，修改和删除之前的观察和规划 +3. 根据聊天内容继续输出观察和规划 +4. 注意群聊的时间线索，话题由谁发起，进展状况如何，思考聊天的时间线。 +6. 语言简洁自然，不要分点，不要浮夸，不要修辞，仅输出思考内容就好""" Prompt(private_prompt, "sub_heartflow_prompt_private_before") @@ -92,24 +92,24 @@ class MindProcessor(BaseProcessor): self.structured_info_str = "" return - lines = ["【Information】"] + lines = ["【信息】"] for item in self.structured_info: # 简化展示，突出内容和类型，包含TTL供调试 type_str = item.get("type", "未知类型") content_str = item.get("content", "") if type_str == "info": - lines.append(f"Just now: {content_str}") + lines.append(f"刚刚: {content_str}") elif type_str == "memory": lines.append(f"{content_str}") elif type_str == "comparison_result": - lines.append(f"Number comparison result: {content_str}") + lines.append(f"数字大小比较结果: {content_str}") elif type_str == "time_info": lines.append(f"{content_str}") elif type_str == "lpmm_knowledge": - lines.append(f"You know: {content_str}") + lines.append(f"你知道：{content_str}") else: - lines.append(f"{type_str} information: {content_str}") + lines.append(f"{type_str}的信息: {content_str}") self.structured_info_str = "\n".join(lines) logger.debug(f"{self.log_prefix} 更新 structured_info_str: \n{self.structured_info_str}") @@ -165,7 +165,7 @@ class MindProcessor(BaseProcessor): memory_str = "" if running_memorys: - memory_str = "Here are the memories you recalled during the current chat:\n" + memory_str = "以下是当前在聊天中，你回忆起的记忆：\n" for running_memory in running_memorys: memory_str += f"{running_memory['topic']}: {running_memory['content']}\n" @@ -214,7 +214,7 @@ class MindProcessor(BaseProcessor): chat_target_name=chat_target_name, ) - content = "(Don't know what to think...)" + content = "(不知道该想些什么...)" try: content, _ = await self.llm_model.generate_response_async(prompt=prompt) if not content: @@ -223,7 +223,7 @@ class MindProcessor(BaseProcessor): # 处理总体异常 logger.error(f"{self.log_prefix} 执行LLM请求或处理响应时出错: {e}") logger.error(traceback.format_exc()) - content = "Error occurred during thinking process" + content = "思考过程中出现错误" # 记录初步思考结果 logger.debug(f"{self.log_prefix} 思考prompt: \n{prompt}\n")