diff --git a/src/chat/focus_chat/info_processors/notused_mind_processor.py b/src/chat/focus_chat/info_processors/notused_mind_processor.py deleted file mode 100644 index b9ca29fe6..000000000 --- a/src/chat/focus_chat/info_processors/notused_mind_processor.py +++ /dev/null @@ -1,231 +0,0 @@ -from src.chat.heart_flow.observation.chatting_observation import ChattingObservation -from src.chat.heart_flow.observation.observation import Observation -from src.llm_models.utils_model import LLMRequest -from src.config.config import global_config -import time -import traceback -from src.common.logger import get_logger -from src.individuality.individuality import get_individuality -from src.chat.utils.prompt_builder import Prompt, global_prompt_manager -from src.chat.utils.json_utils import safe_json_dumps -from src.chat.message_receive.chat_stream import get_chat_manager -from src.person_info.relationship_manager import get_relationship_manager -from .base_processor import BaseProcessor -from src.chat.focus_chat.info.mind_info import MindInfo -from typing import List -from src.chat.heart_flow.observation.hfcloop_observation import HFCloopObservation -from src.chat.heart_flow.observation.actions_observation import ActionObservation -from src.chat.focus_chat.info.info_base import InfoBase - -logger = get_logger("processor") - - -def init_prompt(): - group_prompt = """ -{extra_info}{relation_prompt} -{cycle_info_block} -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} - -{action_observe_info} - -以下是你之前对聊天的观察和规划，你的名字是{bot_name}： -{last_mind} - -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. 注意群聊的时间线索，话题由谁发起，进展状况如何。 -4. 语言简洁自然，不要分点，不要浮夸，不要修辞，仅输出内容就好""" - Prompt(group_prompt, "sub_heartflow_prompt_before") - - private_prompt = """ -你的名字是{bot_name} -{extra_info}{relation_prompt} -{cycle_info_block} -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} -{action_observe_info} -以下是你之前对聊天的观察和规划，你的名字是{bot_name}： -{last_mind} - -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") - - -class MindProcessor(BaseProcessor): - log_prefix = "聊天思考" - - def __init__(self, subheartflow_id: str): - super().__init__() - - self.subheartflow_id = subheartflow_id - - self.llm_model = LLMRequest( - model=global_config.model.planner, - request_type="focus.processor.chat_mind", - ) - - self.current_mind = "" - self.past_mind = [] - self.structured_info = [] - self.structured_info_str = "" - - name = get_chat_manager().get_stream_name(self.subheartflow_id) - self.log_prefix = f"[{name}] " - self._update_structured_info_str() - - def _update_structured_info_str(self): - """根据 structured_info 更新 structured_info_str""" - if not self.structured_info: - self.structured_info_str = "" - return - - 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"刚刚: {content_str}") - elif type_str == "memory": - lines.append(f"{content_str}") - elif type_str == "comparison_result": - 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"你知道：{content_str}") - else: - 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}") - - async def process_info( - self, - observations: List[Observation] = None, - ) -> List[InfoBase]: - """处理信息对象 - - Args: - *infos: 可变数量的InfoBase类型的信息对象 - - Returns: - List[InfoBase]: 处理后的结构化信息列表 - """ - current_mind = await self.do_thinking_before_reply(observations) - - mind_info = MindInfo() - mind_info.set_current_mind(current_mind) - - return [mind_info] - - async def do_thinking_before_reply(self, observations: List[Observation] = None): - """ - 在回复前进行思考，生成内心想法并收集工具调用结果 - - 参数: - observations: 观察信息 - - 返回: - 如果return_prompt为False: - tuple: (current_mind, past_mind) 当前想法和过去的想法列表 - 如果return_prompt为True: - tuple: (current_mind, past_mind, prompt) 当前想法、过去的想法列表和使用的prompt - """ - - # ---------- 0. 更新和清理 structured_info ---------- - if self.structured_info: - # updated_info = [] - # for item in self.structured_info: - # item["ttl"] -= 1 - # if item["ttl"] > 0: - # updated_info.append(item) - # else: - # logger.debug(f"{self.log_prefix} 移除过期的 structured_info 项: {item['id']}") - # self.structured_info = updated_info - self._update_structured_info_str() - logger.debug( - f"{self.log_prefix} 当前完整的 structured_info: {safe_json_dumps(self.structured_info, ensure_ascii=False)}" - ) - # ---------- 1. 准备基础数据 ---------- - # 获取现有想法和情绪状态 - previous_mind = self.current_mind if self.current_mind else "" - - if observations is None: - observations = [] - for observation in observations: - if isinstance(observation, ChattingObservation): - # 获取聊天元信息 - is_group_chat = observation.is_group_chat - chat_target_info = observation.chat_target_info - chat_target_name = "对方" # 私聊默认名称 - if not is_group_chat and chat_target_info: - # 优先使用person_name，其次user_nickname，最后回退到默认值 - chat_target_name = ( - chat_target_info.get("person_name") or chat_target_info.get("user_nickname") or chat_target_name - ) - # 获取聊天内容 - chat_observe_info = observation.get_observe_info() - person_list = observation.person_list - if isinstance(observation, HFCloopObservation): - hfcloop_observe_info = observation.get_observe_info() - if isinstance(observation, ActionObservation): - action_observe_info = observation.get_observe_info() - - # ---------- 3. 准备个性化数据 ---------- - # 获取个性化信息 - - relation_prompt = "" - if global_config.relationship.enable_relationship: - for person in person_list: - relationship_manager = get_relationship_manager() - relation_prompt += await relationship_manager.build_relationship_info(person, is_id=True) - - template_name = "sub_heartflow_prompt_before" if is_group_chat else "sub_heartflow_prompt_private_before" - logger.debug(f"{self.log_prefix} 使用{'群聊' if is_group_chat else '私聊'}思考模板") - - prompt = (await global_prompt_manager.get_prompt_async(template_name)).format( - bot_name=get_individuality().name, - extra_info=self.structured_info_str, - relation_prompt=relation_prompt, - time_now=time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), - chat_observe_info=chat_observe_info, - last_mind=previous_mind, - cycle_info_block=hfcloop_observe_info, - action_observe_info=action_observe_info, - chat_target_name=chat_target_name, - ) - - content = "(不知道该想些什么...)" - try: - content, _ = await self.llm_model.generate_response_async(prompt=prompt) - if not content: - logger.warning(f"{self.log_prefix} LLM返回空结果，思考失败。") - except Exception as e: - # 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 = "注意：思考过程中出现错误，应该是LLM大模型有问题！！你需要告诉别人，检查大模型配置" - - # 记录初步思考结果 - logger.debug(f"{self.log_prefix} 思考prompt: \n{prompt}\n") - logger.info(f"{self.log_prefix} 聊天规划: {content}") - self.update_current_mind(content) - - return content - - def update_current_mind(self, response): - if self.current_mind: # 只有当 current_mind 非空时才添加到 past_mind - self.past_mind.append(self.current_mind) - self.current_mind = response - - -init_prompt() diff --git a/src/chat/focus_chat/info_processors/relationship_processor.py b/src/chat/focus_chat/info_processors/relationship_processor.py index ffbe9988c..34206f776 100644 --- a/src/chat/focus_chat/info_processors/relationship_processor.py +++ b/src/chat/focus_chat/info_processors/relationship_processor.py @@ -644,7 +644,7 @@ class PersonImpressionpProcessor(BaseProcessor): ) try: - logger.info(f"{self.log_prefix} 人物信息prompt: \n{prompt}\n") + logger.debug(f"{self.log_prefix} 人物信息prompt: \n{prompt}\n") content, _ = await self.llm_model.generate_response_async(prompt=prompt) if content: # print(f"content: {content}") @@ -704,26 +704,47 @@ class PersonImpressionpProcessor(BaseProcessor): persons_infos_str = "" # 处理已获取到的信息 if self.info_fetched_cache: + persons_with_known_info = [] # 有已知信息的人员 + persons_with_unknown_info = [] # 有未知信息的人员 + for person_id in self.info_fetched_cache: - person_infos_str = "" - unknown_info_types = [] # 收集所有unknow的信息类型 + person_known_infos = [] + person_unknown_infos = [] person_name = "" for info_type in self.info_fetched_cache[person_id]: person_name = self.info_fetched_cache[person_id][info_type]["person_name"] if not self.info_fetched_cache[person_id][info_type]["unknow"]: info_content = self.info_fetched_cache[person_id][info_type]["info"] - person_infos_str += f"[{info_type}]：{info_content}；" + person_known_infos.append(f"[{info_type}]：{info_content}") else: - unknown_info_types.append(info_type) + person_unknown_infos.append(info_type) - # 如果有unknow的信息类型，合并输出 - if unknown_info_types: - unknown_types_str = "、".join(unknown_info_types) - person_infos_str += f"你不了解{person_name}有关[{unknown_types_str}]的信息，不要胡乱回答，你可以直接说你不知道，或者你忘记了；" + # 如果有已知信息，添加到已知信息列表 + if person_known_infos: + known_info_str = "；".join(person_known_infos) + "；" + persons_with_known_info.append((person_name, known_info_str)) - if person_infos_str: - persons_infos_str += f"你对 {person_name} 的了解：{person_infos_str}\n" + # 如果有未知信息，添加到未知信息列表 + if person_unknown_infos: + persons_with_unknown_info.append((person_name, person_unknown_infos)) + + # 先输出有已知信息的人员 + for person_name, known_info_str in persons_with_known_info: + persons_infos_str += f"你对 {person_name} 的了解：{known_info_str}\n" + + # 统一处理未知信息，避免重复的警告文本 + if persons_with_unknown_info: + unknown_persons_details = [] + for person_name, unknown_types in persons_with_unknown_info: + unknown_types_str = "、".join(unknown_types) + unknown_persons_details.append(f"{person_name}的[{unknown_types_str}]") + + if len(unknown_persons_details) == 1: + persons_infos_str += f"你不了解{unknown_persons_details[0]}信息，不要胡乱回答，可以直接说不知道或忘记了；\n" + else: + unknown_all_str = "、".join(unknown_persons_details) + persons_infos_str += f"你不了解{unknown_all_str}等信息，不要胡乱回答，可以直接说不知道或忘记了；\n" return persons_infos_str diff --git a/src/chat/normal_chat/normal_chat.py b/src/chat/normal_chat/normal_chat.py index de19bae80..bf1136ea4 100644 --- a/src/chat/normal_chat/normal_chat.py +++ b/src/chat/normal_chat/normal_chat.py @@ -610,6 +610,17 @@ class NormalChat: logger.info(f"[{self.stream_name}] 已停用，忽略 normal_response。") return + # 新增：在auto模式下检查是否需要直接切换到focus模式 + if global_config.chat.chat_mode == "auto": + should_switch = await self._check_should_switch_to_focus() + if should_switch: + logger.info(f"[{self.stream_name}] 检测到切换到focus聊天模式的条件，直接执行切换") + if self.on_switch_to_focus_callback: + await self.on_switch_to_focus_callback() + return + else: + logger.warning(f"[{self.stream_name}] 没有设置切换到focus聊天模式的回调函数，无法执行切换") + # 执行定期清理 self._cleanup_old_segments() @@ -729,9 +740,6 @@ class NormalChat: if action_type == "no_action": logger.debug(f"[{self.stream_name}] Planner决定不执行任何额外动作") return no_action - elif action_type == "change_to_focus_chat": - logger.info(f"[{self.stream_name}] Planner决定切换到focus聊天模式") - return None # 执行额外的动作（不影响回复生成） action_result = await self._execute_action(action_type, action_data, message, thinking_id) @@ -772,14 +780,14 @@ class NormalChat: if not response_set or ( self.enable_planner - and self.action_type not in ["no_action", "change_to_focus_chat"] + and self.action_type not in ["no_action"] and not self.is_parallel_action ): if not response_set: logger.info(f"[{self.stream_name}] 模型未生成回复内容") elif ( self.enable_planner - and self.action_type not in ["no_action", "change_to_focus_chat"] + and self.action_type not in ["no_action"] and not self.is_parallel_action ): logger.info(f"[{self.stream_name}] 模型选择其他动作（非并行动作）") @@ -828,15 +836,7 @@ class NormalChat: if len(self.recent_replies) > self.max_replies_history: self.recent_replies = self.recent_replies[-self.max_replies_history :] - # 检查是否需要切换到focus模式 - if global_config.chat.chat_mode == "auto": - if self.action_type == "change_to_focus_chat": - logger.info(f"[{self.stream_name}] 检测到切换到focus聊天模式的请求") - if self.on_switch_to_focus_callback: - await self.on_switch_to_focus_callback() - else: - logger.warning(f"[{self.stream_name}] 没有设置切换到focus聊天模式的回调函数，无法执行切换") - return + # 回复后处理 await willing_manager.after_generate_reply_handle(message.message_info.message_id) @@ -1124,61 +1124,64 @@ class NormalChat: logger.info(f"[{self.stream_name}] 用户 {person_id} 关系构建已启动，缓存已清理") async def _build_relation_for_person_segments(self, person_id: str, segments: List[Dict[str, any]]): - """基于消息段为特定用户构建关系""" - logger.info(f"[{self.stream_name}] 开始为 {person_id} 基于 {len(segments)} 个消息段更新印象") - try: - processed_messages = [] + """为特定用户的消息段构建关系""" + if not segments: + return - for i, segment in enumerate(segments): + try: + chat_stream = get_chat_manager().get_stream(self.stream_id) + relationship_manager = chat_stream.relationship_manager + + for segment in segments: start_time = segment["start_time"] end_time = segment["end_time"] - segment["message_count"] - start_date = time.strftime("%Y-%m-%d %H:%M", time.localtime(start_time)) + message_count = segment["message_count"] - # 获取该段的消息（包含边界） - segment_messages = get_raw_msg_by_timestamp_with_chat_inclusive(self.stream_id, start_time, end_time) - logger.info( - f"[{self.stream_name}] 消息段 {i + 1}: {start_date} - {time.strftime('%Y-%m-%d %H:%M', time.localtime(end_time))}, 消息数: {len(segment_messages)}" + logger.debug( + f"[{self.stream_name}] 为用户 {person_id} 构建关系 " + f"消息段时间: {time.strftime('%H:%M:%S', time.localtime(start_time))} - " + f"{time.strftime('%H:%M:%S', time.localtime(end_time))} " + f"消息数量: {message_count}" ) - if segment_messages: - # 如果不是第一个消息段，在消息列表前添加间隔标识 - if i > 0: - # 创建一个特殊的间隔消息 - gap_message = { - "time": start_time - 0.1, # 稍微早于段开始时间 - "user_id": "system", - "user_platform": "system", - "user_nickname": "系统", - "user_cardname": "", - "display_message": f"...（中间省略一些消息）{start_date} 之后的消息如下...", - "is_action_record": True, - "chat_info_platform": segment_messages[0].get("chat_info_platform", ""), - "chat_id": self.stream_id, - } - processed_messages.append(gap_message) - - # 添加该段的所有消息 - processed_messages.extend(segment_messages) - - if processed_messages: - # 按时间排序所有消息（包括间隔标识） - processed_messages.sort(key=lambda x: x["time"]) - - logger.info( - f"[{self.stream_name}] 为 {person_id} 获取到总共 {len(processed_messages)} 条消息（包含间隔标识）用于印象更新" + await relationship_manager.direct_build_relation( + person_id, start_time, end_time, message_count, time.time() ) - relationship_manager = get_relationship_manager() - - # 调用原有的更新方法 - await relationship_manager.update_person_impression( - person_id=person_id, timestamp=time.time(), bot_engaged_messages=processed_messages - ) - - logger.info(f"[{self.stream_name}] 用户 {person_id} 关系构建完成") - else: - logger.warning(f"[{self.stream_name}] 没有找到 {person_id} 的消息段对应的消息，不更新印象") except Exception as e: - logger.error(f"[{self.stream_name}] 为 {person_id} 更新印象时发生错误: {e}") - logger.error(traceback.format_exc()) + logger.error(f"[{self.stream_name}] 构建关系失败: {e}") + + async def _check_should_switch_to_focus(self) -> bool: + """ + 检查是否满足切换到focus模式的条件 + + Returns: + bool: 是否应该切换到focus模式 + """ + # 检查思考消息堆积情况 + container = await message_manager.get_container(self.stream_id) + if container: + thinking_count = sum(1 for msg in container.messages if isinstance(msg, MessageThinking)) + if thinking_count >= 4 * global_config.chat.auto_focus_threshold: # 如果堆积超过阈值条思考消息 + logger.debug(f"[{self.stream_name}] 检测到思考消息堆积({thinking_count}条)，切换到focus模式") + return True + + if not self.recent_replies: + return False + + current_time = time.time() + time_threshold = 120 / global_config.chat.auto_focus_threshold + reply_threshold = 6 * global_config.chat.auto_focus_threshold + + one_minute_ago = current_time - time_threshold + + # 统计指定时间内的回复数量 + recent_reply_count = sum(1 for reply in self.recent_replies if reply["time"] > one_minute_ago) + + should_switch = recent_reply_count > reply_threshold + if should_switch: + logger.debug( + f"[{self.stream_name}] 检测到{time_threshold:.0f}秒内回复数量({recent_reply_count})大于{reply_threshold}，满足切换到focus模式条件" + ) + + return should_switch diff --git a/src/chat/normal_chat/normal_chat_action_modifier.py b/src/chat/normal_chat/normal_chat_action_modifier.py index 7c3803352..41975c99d 100644 --- a/src/chat/normal_chat/normal_chat_action_modifier.py +++ b/src/chat/normal_chat/normal_chat_action_modifier.py @@ -170,7 +170,6 @@ class NormalChatActionModifier: 2. RANDOM类型保持概率激活 3. KEYWORD类型保持关键词匹配 4. ALWAYS类型直接激活 - 5. change_to_focus_chat 特殊处理：根据回复频率判断 Args: actions_with_info: 带完整信息的动作字典 @@ -183,25 +182,12 @@ class NormalChatActionModifier: """ activated_actions = {} - # 特殊处理 change_to_focus_chat 动作 - if global_config.chat.chat_mode == "auto": - if "change_to_focus_chat" in actions_with_info: - # 检查是否满足切换到focus模式的条件 - if await self._check_should_switch_to_focus(recent_replies): - activated_actions["change_to_focus_chat"] = actions_with_info["change_to_focus_chat"] - logger.debug(f"{self.log_prefix} 特殊激活 change_to_focus_chat 动作，原因: 满足切换到focus模式条件") - return activated_actions - # 分类处理不同激活类型的actions always_actions = {} random_actions = {} keyword_actions = {} for action_name, action_info in actions_with_info.items(): - # 跳过已特殊处理的 change_to_focus_chat - if action_name == "change_to_focus_chat": - continue - # 使用normal_activation_type activation_type = action_info.get("normal_activation_type", "always") @@ -294,47 +280,7 @@ class NormalChatActionModifier: logger.debug(f"{self.log_prefix}动作 {action_name} 未匹配到任何关键词: {activation_keywords}") return False - async def _check_should_switch_to_focus(self, recent_replies: List[dict]) -> bool: - """ - 检查是否满足切换到focus模式的条件 - Args: - recent_replies: 最近的回复记录列表 - - Returns: - bool: 是否应该切换到focus模式 - """ - # 检查思考消息堆积情况 - container = await message_manager.get_container(self.stream_id) - if container: - thinking_count = sum(1 for msg in container.messages if isinstance(msg, MessageThinking)) - print(f"thinking_count: {thinking_count}") - if thinking_count >= 4 * global_config.chat.auto_focus_threshold: # 如果堆积超过3条思考消息 - logger.debug(f"{self.log_prefix} 检测到思考消息堆积({thinking_count}条)，切换到focus模式") - return True - - if not recent_replies: - return False - - current_time = time.time() - time_threshold = 120 / global_config.chat.auto_focus_threshold - reply_threshold = 6 * global_config.chat.auto_focus_threshold - - one_minute_ago = current_time - time_threshold - - # 统计1分钟内的回复数量 - recent_reply_count = sum(1 for reply in recent_replies if reply["time"] > one_minute_ago) - - print(f"recent_reply_count: {recent_reply_count}") - print(f"reply_threshold: {reply_threshold}") - - should_switch = recent_reply_count > reply_threshold - if should_switch: - logger.debug( - f"{self.log_prefix} 检测到1分钟内回复数量({recent_reply_count})大于{reply_threshold}，满足切换到focus模式条件" - ) - - return should_switch def get_available_actions_count(self) -> int: """获取当前可用动作数量（排除默认的no_action）""" diff --git a/src/chat/utils/chat_message_builder.py b/src/chat/utils/chat_message_builder.py index 715730a20..165292bd4 100644 --- a/src/chat/utils/chat_message_builder.py +++ b/src/chat/utils/chat_message_builder.py @@ -622,10 +622,13 @@ def build_readable_messages( messages_after_mark, replace_bot_name, merge_messages, timestamp_mode, False, pic_id_mapping, pic_counter ) - read_mark_line = "\n--- 以上消息是你已经看过---\n--- 请关注以下未读的新消息---\n" + read_mark_line = "\n--- 以上消息是你已经看过，请关注以下未读的新消息---\n" # 生成图片映射信息 - pic_mapping_info = f"图片信息：\n{build_pic_mapping_info(pic_id_mapping)}\n聊天记录信息：\n" + if pic_id_mapping: + pic_mapping_info = f"图片信息：\n{build_pic_mapping_info(pic_id_mapping)}\n聊天记录信息：\n" + else: + pic_mapping_info = "聊天记录信息：\n" # 组合结果 result_parts = [] diff --git a/src/chat/utils/utils_image.py b/src/chat/utils/utils_image.py index 70e0462d7..db1619b45 100644 --- a/src/chat/utils/utils_image.py +++ b/src/chat/utils/utils_image.py @@ -477,7 +477,7 @@ class ImageManager: image_format = Image.open(io.BytesIO(image_bytes)).format.lower() # 构建prompt - prompt = """请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多50字""" + prompt = """请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多30字，请注意不要分点，就输出一段文本""" # 获取VLM描述 description, _ = await self._llm.generate_response_for_image(prompt, image_base64, image_format) diff --git a/src/person_info/relationship_manager.py b/src/person_info/relationship_manager.py index 53d4c50c0..b89fcfcd1 100644 --- a/src/person_info/relationship_manager.py +++ b/src/person_info/relationship_manager.py @@ -286,7 +286,7 @@ class RelationshipManager: logger_str = f"了解了有关{person_name}的新印象：\n" for point in points_list: - logger_str += f"{point[0]},重要性：{point[1]}\n\n" + logger_str += f"{point[0]},重要性：{point[1]}\n" logger.info(logger_str) except json.JSONDecodeError: