226 lines
9.9 KiB
Python
226 lines
9.9 KiB
Python
import traceback
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from typing import Dict, Any
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from src.common.logger import get_logger
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from src.manager.mood_manager import mood_manager # 导入情绪管理器
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from src.chat.message_receive.chat_stream import get_chat_manager
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from src.chat.message_receive.message import MessageRecv
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from src.experimental.only_message_process import MessageProcessor
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from src.chat.message_receive.storage import MessageStorage
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from src.experimental.PFC.pfc_manager import PFCManager
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from src.chat.focus_chat.heartflow_message_processor import HeartFCMessageReceiver
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from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
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from src.config.config import global_config
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from src.plugin_system.core.component_registry import component_registry # 导入新插件系统
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from src.plugin_system.base.base_command import BaseCommand
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from src.mais4u.mais4u_chat.s4u_msg_processor import S4UMessageProcessor
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# 定义日志配置
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ENABLE_S4U_CHAT = True
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# 仅内部开启
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# 配置主程序日志格式
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logger = get_logger("chat")
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class ChatBot:
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def __init__(self):
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self.bot = None # bot 实例引用
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self._started = False
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self.mood_manager = mood_manager # 获取情绪管理器单例
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self.heartflow_message_receiver = HeartFCMessageReceiver() # 新增
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# 创建初始化PFC管理器的任务，会在_ensure_started时执行
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self.only_process_chat = MessageProcessor()
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self.pfc_manager = PFCManager.get_instance()
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self.s4u_message_processor = S4UMessageProcessor()
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async def _ensure_started(self):
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"""确保所有任务已启动"""
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if not self._started:
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logger.debug("确保ChatBot所有任务已启动")
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self._started = True
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async def _create_pfc_chat(self, message: MessageRecv):
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try:
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if global_config.experimental.pfc_chatting:
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chat_id = str(message.chat_stream.stream_id)
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private_name = str(message.message_info.user_info.user_nickname)
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await self.pfc_manager.get_or_create_conversation(chat_id, private_name)
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except Exception as e:
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logger.error(f"创建PFC聊天失败: {e}")
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async def _process_commands_with_new_system(self, message: MessageRecv):
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# sourcery skip: use-named-expression
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"""使用新插件系统处理命令"""
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try:
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text = message.processed_plain_text
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# 使用新的组件注册中心查找命令
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command_result = component_registry.find_command_by_text(text)
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if command_result:
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command_class, matched_groups, intercept_message, plugin_name = command_result
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# 获取插件配置
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plugin_config = component_registry.get_plugin_config(plugin_name)
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# 创建命令实例
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command_instance: BaseCommand = command_class(message, plugin_config)
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command_instance.set_matched_groups(matched_groups)
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try:
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# 执行命令
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success, response = await command_instance.execute()
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# 记录命令执行结果
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if success:
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logger.info(f"命令执行成功: {command_class.__name__} (拦截: {intercept_message})")
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else:
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logger.warning(f"命令执行失败: {command_class.__name__} - {response}")
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# 根据命令的拦截设置决定是否继续处理消息
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return True, response, not intercept_message # 找到命令，根据intercept_message决定是否继续
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except Exception as e:
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logger.error(f"执行命令时出错: {command_class.__name__} - {e}")
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import traceback
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logger.error(traceback.format_exc())
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try:
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await command_instance.send_text(f"命令执行出错: {str(e)}")
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except Exception as send_error:
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logger.error(f"发送错误消息失败: {send_error}")
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# 命令出错时，根据命令的拦截设置决定是否继续处理消息
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return True, str(e), not intercept_message
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# 没有找到命令，继续处理消息
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return False, None, True
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except Exception as e:
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logger.error(f"处理命令时出错: {e}")
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return False, None, True # 出错时继续处理消息
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async def message_process(self, message_data: Dict[str, Any]) -> None:
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"""处理转化后的统一格式消息
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这个函数本质是预处理一些数据，根据配置信息和消息内容，预处理消息，并分发到合适的消息处理器中
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heart_flow模式：使用思维流系统进行回复
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- 包含思维流状态管理
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- 在回复前进行观察和状态更新
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- 回复后更新思维流状态
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- 消息过滤
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- 记忆激活
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- 意愿计算
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- 消息生成和发送
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- 表情包处理
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- 性能计时
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"""
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try:
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# 确保所有任务已启动
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await self._ensure_started()
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if message_data["message_info"].get("group_info") is not None:
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message_data["message_info"]["group_info"]["group_id"] = str(
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message_data["message_info"]["group_info"]["group_id"]
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)
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message_data["message_info"]["user_info"]["user_id"] = str(
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message_data["message_info"]["user_info"]["user_id"]
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)
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# print(message_data)
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# logger.debug(str(message_data))
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message = MessageRecv(message_data)
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group_info = message.message_info.group_info
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user_info = message.message_info.user_info
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if message.message_info.additional_config:
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sent_message = message.message_info.additional_config.get("echo", False)
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if sent_message: # 这一段只是为了在一切处理前劫持上报的自身消息，用于更新message_id，需要ada支持上报事件，实际测试中不会对正常使用造成任何问题
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await MessageStorage.update_message(message)
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return
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get_chat_manager().register_message(message)
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# 创建聊天流
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chat = await get_chat_manager().get_or_create_stream(
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platform=message.message_info.platform,
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user_info=user_info,
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group_info=group_info,
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)
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message.update_chat_stream(chat)
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# 处理消息内容，生成纯文本
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await message.process()
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# 命令处理 - 使用新插件系统检查并处理命令
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is_command, cmd_result, continue_process = await self._process_commands_with_new_system(message)
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# 如果是命令且不需要继续处理，则直接返回
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if is_command and not continue_process:
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await MessageStorage.store_message(message, chat)
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logger.info(f"命令处理完成，跳过后续消息处理: {cmd_result}")
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return
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# 确认从接口发来的message是否有自定义的prompt模板信息
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if message.message_info.template_info and not message.message_info.template_info.template_default:
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template_group_name = message.message_info.template_info.template_name
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template_items = message.message_info.template_info.template_items
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async with global_prompt_manager.async_message_scope(template_group_name):
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if isinstance(template_items, dict):
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for k in template_items.keys():
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await Prompt.create_async(template_items[k], k)
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logger.debug(f"注册{template_items[k]},{k}")
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else:
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template_group_name = None
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async def preprocess():
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logger.debug("开始预处理消息...")
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# 如果在私聊中
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if group_info is None:
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logger.debug("检测到私聊消息")
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if ENABLE_S4U_CHAT:
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logger.debug("进入S4U私聊处理流程")
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await self.s4u_message_processor.process_message(message)
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return
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if global_config.experimental.pfc_chatting:
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logger.debug("进入PFC私聊处理流程")
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# 创建聊天流
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logger.debug(f"为{user_info.user_id}创建/获取聊天流")
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await self.only_process_chat.process_message(message)
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await self._create_pfc_chat(message)
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# 禁止PFC，进入普通的心流消息处理逻辑
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else:
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logger.debug("进入普通心流私聊处理")
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await self.heartflow_message_receiver.process_message(message)
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# 群聊默认进入心流消息处理逻辑
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else:
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if ENABLE_S4U_CHAT:
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logger.debug("进入S4U私聊处理流程")
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await self.s4u_message_processor.process_message(message)
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return
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logger.debug(f"检测到群聊消息，群ID: {group_info.group_id}")
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await self.heartflow_message_receiver.process_message(message)
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if template_group_name:
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async with global_prompt_manager.async_message_scope(template_group_name):
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await preprocess()
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else:
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await preprocess()
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except Exception as e:
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logger.error(f"预处理消息失败: {e}")
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traceback.print_exc()
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# 创建全局ChatBot实例
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chat_bot = ChatBot()
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