🤖 自动格式化代码 [skip ci]

bot.py

@@ -326,7 +326,6 @@ if __name__ == "__main__":
                 # Wait for all tasks to complete (which they won't, normally)
                 loop.run_until_complete(main_tasks)
 
-
         except KeyboardInterrupt:
             # loop.run_until_complete(get_global_api().stop())
             logger.warning("收到中断信号，正在优雅关闭...")

src/audio/mock_audio.py

@@ -3,10 +3,12 @@ from src.common.logger import get_logger
 
 logger = get_logger("MockAudio")
 
+
 class MockAudioPlayer:
     """
     一个模拟的音频播放器，它会根据音频数据的"长度"来模拟播放时间。
     """
+
     def __init__(self, audio_data: bytes):
         self._audio_data = audio_data
         # 模拟音频时长：假设每 1024 字节代表 0.5 秒的音频
@@ -22,12 +24,14 @@ class MockAudioPlayer:
             logger.info("模拟音频播放完毕。")
         except asyncio.CancelledError:
             logger.info("音频播放被中断。")
-            raise # 重新抛出异常，以便上层逻辑可以捕获它
+            raise  # 重新抛出异常，以便上层逻辑可以捕获它
+
 
 class MockAudioGenerator:
     """
     一个模拟的文本到语音（TTS）生成器。
     """
+
     def __init__(self):
         # 模拟生成速度：每秒生成的字符数
         self.chars_per_second = 25.0
@@ -43,16 +47,16 @@ class MockAudioGenerator:
             模拟的音频数据（bytes）。
         """
         if not text:
-            return b''
+            return b""
 
         generation_time = len(text) / self.chars_per_second
         logger.info(f"模拟生成音频... 文本长度: {len(text)}, 预计耗时: {generation_time:.2f} 秒...")
         try:
             await asyncio.sleep(generation_time)
             # 生成虚拟的音频数据，其长度与文本长度成正比
-            mock_audio_data = b'\x01\x02\x03' * (len(text) * 40)
+            mock_audio_data = b"\x01\x02\x03" * (len(text) * 40)
             logger.info(f"模拟音频生成完毕，数据大小: {len(mock_audio_data) / 1024:.2f} KB。")
             return mock_audio_data
         except asyncio.CancelledError:
             logger.info("音频生成被中断。")
-            raise # 重新抛出异常 
+            raise  # 重新抛出异常

src/chat/message_receive/bot.py

@@ -186,8 +186,6 @@ class ChatBot:
                         await self.s4u_message_processor.process_message(message)
                         return
 
-                    
-                    
                     if global_config.experimental.pfc_chatting:
                         logger.debug("进入PFC私聊处理流程")
                         # 创建聊天流
@@ -200,13 +198,11 @@ class ChatBot:
                         await self.heartflow_message_receiver.process_message(message)
                 # 群聊默认进入心流消息处理逻辑
                 else:
-                    
                     if ENABLE_S4U_CHAT:
                         logger.debug("进入S4U私聊处理流程")
                         await self.s4u_message_processor.process_message(message)
                         return
 
-                    
                     logger.debug(f"检测到群聊消息，群ID: {group_info.group_id}")
                     await self.heartflow_message_receiver.process_message(message)
 

src/chat/utils/chat_message_builder.py

@@ -264,7 +264,6 @@ def _build_readable_messages_internal(
         if show_pic:
             content = process_pic_ids(content)
 
-
         # 检查必要信息是否存在
         if not all([platform, user_id, timestamp is not None]):
             continue
@@ -632,10 +631,17 @@ def build_readable_messages(
             truncate,
             pic_id_mapping,
             pic_counter,
-            show_pic=show_pic
+            show_pic=show_pic,
         )
         formatted_after, _, pic_id_mapping, _ = _build_readable_messages_internal(
-            messages_after_mark, replace_bot_name, merge_messages, timestamp_mode, False, pic_id_mapping, pic_counter, show_pic=show_pic
+            messages_after_mark,
+            replace_bot_name,
+            merge_messages,
+            timestamp_mode,
+            False,
+            pic_id_mapping,
+            pic_counter,
+            show_pic=show_pic,
         )
 
         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"

src/mais4u/mais4u_chat/s4u_chat.py

@@ -1,39 +1,15 @@
 import asyncio
 import time
-import traceback
 import random
-from typing import List, Optional, Dict  # 导入类型提示
-import os
-import pickle
+from typing import Optional, Dict  # 导入类型提示
 from maim_message import UserInfo, Seg
 from src.common.logger import get_logger
-from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info
-from src.manager.mood_manager import mood_manager
 from src.chat.message_receive.chat_stream import ChatStream, get_chat_manager
-from src.chat.utils.timer_calculator import Timer
-from src.chat.utils.prompt_builder import global_prompt_manager
 from .s4u_stream_generator import S4UStreamGenerator
-from src.chat.message_receive.message import MessageSending, MessageRecv, MessageThinking, MessageSet
-from src.chat.message_receive.message_sender import message_manager
-from src.chat.normal_chat.willing.willing_manager import get_willing_manager
-from src.chat.normal_chat.normal_chat_utils import get_recent_message_stats
+from src.chat.message_receive.message import MessageSending, MessageRecv
 from src.config.config import global_config
-from src.chat.focus_chat.planners.action_manager import ActionManager
-from src.chat.normal_chat.normal_chat_planner import NormalChatPlanner
-from src.chat.normal_chat.normal_chat_action_modifier import NormalChatActionModifier
-from src.chat.normal_chat.normal_chat_expressor import NormalChatExpressor
-from src.chat.focus_chat.replyer.default_generator import DefaultReplyer
-from src.person_info.person_info import PersonInfoManager
-from src.person_info.relationship_manager import get_relationship_manager
-from src.chat.utils.chat_message_builder import (
-    get_raw_msg_by_timestamp_with_chat,
-    get_raw_msg_by_timestamp_with_chat_inclusive,
-    get_raw_msg_before_timestamp_with_chat,
-    num_new_messages_since,
-)
 from src.common.message.api import get_global_api
 from src.chat.message_receive.storage import MessageStorage
-from src.audio.mock_audio import MockAudioGenerator, MockAudioPlayer
 
 
 logger = get_logger("S4U_chat")
@@ -41,6 +17,7 @@ logger = get_logger("S4U_chat")
 
 class MessageSenderContainer:
     """一个简单的容器，用于按顺序发送消息并模拟打字效果。"""
+
     def __init__(self, chat_stream: ChatStream, original_message: MessageRecv):
         self.chat_stream = chat_stream
         self.original_message = original_message
@@ -117,7 +94,7 @@ class MessageSenderContainer:
                     reply=self.original_message,
                     is_emoji=False,
                     apply_set_reply_logic=True,
-                    reply_to=f"{self.original_message.message_info.user_info.platform}:{self.original_message.message_info.user_info.user_id}"
+                    reply_to=f"{self.original_message.message_info.user_info.platform}:{self.original_message.message_info.user_info.user_id}",
                 )
 
                 await bot_message.process()
@@ -156,8 +133,10 @@ class S4UChatManager:
             self.s4u_chats[chat_stream.stream_id] = S4UChat(chat_stream)
         return self.s4u_chats[chat_stream.stream_id]
 
+
 s4u_chat_manager = S4UChatManager()
 
+
 def get_s4u_chat_manager() -> S4UChatManager:
     return s4u_chat_manager
 
@@ -180,11 +159,8 @@ class S4UChat:
         self.gpt = S4UStreamGenerator()
         # self.audio_generator = MockAudioGenerator()
 
-
-
         logger.info(f"[{self.stream_name}] S4UChat")
 
-
     # 改为实例方法, 移除 chat 参数
     async def response(self, message: MessageRecv, is_mentioned: bool, interested_rate: float) -> None:
         """将消息放入队列并根据发信人决定是否中断当前处理。"""
@@ -226,8 +202,8 @@ class S4UChat:
                 # 如果因快速中断导致队列中积压了更多消息，则只处理最新的一条
                 while not self._message_queue.empty():
                     drained_msg = self._message_queue.get_nowait()
-                    self._message_queue.task_done() # 为取出的旧消息调用 task_done
-                    message = drained_msg # 始终处理最新消息
+                    self._message_queue.task_done()  # 为取出的旧消息调用 task_done
+                    message = drained_msg  # 始终处理最新消息
                     self._current_message_being_replied = message
                     logger.info(f"[{self.stream_name}] 丢弃过时消息，处理最新消息: {message.processed_plain_text}")
 
@@ -248,13 +224,12 @@ class S4UChat:
                 break
             except Exception as e:
                 logger.error(f"[{self.stream_name}] 消息处理器主循环发生未知错误: {e}", exc_info=True)
-                await asyncio.sleep(1) # 避免在未知错误下陷入CPU空转
+                await asyncio.sleep(1)  # 避免在未知错误下陷入CPU空转
             finally:
                 # 确保处理过的消息（无论是正常完成还是被丢弃）都被标记完成
-                if 'message' in locals():
+                if "message" in locals():
                     self._message_queue.task_done()
 
-
     async def _generate_and_send(self, message: MessageRecv):
         """为单个消息生成文本和音频回复。整个过程可以被中断。"""
         self._is_replying = True
@@ -262,10 +237,7 @@ class S4UChat:
         sender_container.start()
 
         try:
-            logger.info(
-                f"[S4U] 开始为消息生成文本和音频流: "
-                f"'{message.processed_plain_text[:30]}...'"
-            )
+            logger.info(f"[S4U] 开始为消息生成文本和音频流: '{message.processed_plain_text[:30]}...'")
 
             # 1. 逐句生成文本、发送并播放音频
             gen = self.gpt.generate_response(message, "")
@@ -277,9 +249,9 @@ class S4UChat:
 
                 # b. 为该文本块生成并播放音频
                 # if chunk.strip():
-                    # audio_data = await self.audio_generator.generate(chunk)
-                    # player = MockAudioPlayer(audio_data)
-                    # await player.play()
+                # audio_data = await self.audio_generator.generate(chunk)
+                # player = MockAudioPlayer(audio_data)
+                # await player.play()
 
             # 等待所有文本消息发送完成
             await sender_container.close()
@@ -300,7 +272,6 @@ class S4UChat:
                 await sender_container.join()
             logger.info(f"[{self.stream_name}] _generate_and_send 任务结束，资源已清理。")
 
-
     async def shutdown(self):
         """平滑关闭处理任务。"""
         logger.info(f"正在关闭 S4UChat: {self.stream_name}")

src/mais4u/mais4u_chat/s4u_msg_processor.py

@@ -1,21 +1,10 @@
-from src.chat.memory_system.Hippocampus import hippocampus_manager
-from src.config.config import global_config
 from src.chat.message_receive.message import MessageRecv
 from src.chat.message_receive.storage import MessageStorage
-from src.chat.heart_flow.heartflow import heartflow
-from src.chat.message_receive.chat_stream import get_chat_manager, ChatStream
+from src.chat.message_receive.chat_stream import get_chat_manager
 from src.chat.utils.utils import is_mentioned_bot_in_message
-from src.chat.utils.timer_calculator import Timer
 from src.common.logger import get_logger
 from .s4u_chat import get_s4u_chat_manager
 
-import math
-import re
-import traceback
-from typing import Optional, Tuple
-from maim_message import UserInfo
-
-from src.person_info.relationship_manager import get_relationship_manager
 
 # from ..message_receive.message_buffer import message_buffer
 
@@ -68,4 +57,3 @@ class S4UMessageProcessor:
 
         # 7. 日志记录
         logger.info(f"[S4U]{userinfo.user_nickname}:{message.processed_plain_text}")
-

src/mais4u/mais4u_chat/s4u_prompt.py

@@ -1,10 +1,8 @@
-
 from src.config.config import global_config
 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.chat_message_builder import build_readable_messages, get_raw_msg_before_timestamp_with_chat
-from src.chat.message_receive.message import MessageRecv
 import time
 from src.chat.utils.utils import get_recent_group_speaker
 from src.chat.memory_system.Hippocampus import hippocampus_manager
@@ -23,7 +21,6 @@ def init_prompt():
 
     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")
 
-
     Prompt(
         """
 你的名字叫{bot_name}，昵称是：{bot_other_names}，{prompt_personality}。
@@ -79,7 +76,6 @@ class PromptBuilder:
                 relationship_manager = get_relationship_manager()
                 relation_prompt += await relationship_manager.build_relationship_info(person)
 
-
         memory_prompt = ""
         related_memory = await hippocampus_manager.get_memory_from_text(
             text=message_txt, max_memory_num=2, max_memory_length=2, max_depth=3, fast_retrieval=False
@@ -99,22 +95,19 @@ class PromptBuilder:
             limit=100,
         )
 
-        
         talk_type = message.message_info.platform + ":" + message.chat_stream.user_info.user_id
         print(f"talk_type: {talk_type}")
 
-
         # 分别筛选核心对话和背景对话
         core_dialogue_list = []
         background_dialogue_list = []
         bot_id = str(global_config.bot.qq_account)
         target_user_id = str(message.chat_stream.user_info.user_id)
 
-
         for msg_dict in message_list_before_now:
             try:
                 # 直接通过字典访问
-                msg_user_id = str(msg_dict.get('user_id'))
+                msg_user_id = str(msg_dict.get("user_id"))
                 if msg_user_id == bot_id:
                     if msg_dict.get("reply_to") and talk_type == msg_dict.get("reply_to"):
                         print(f"reply: {msg_dict.get('reply_to')}")
@@ -133,8 +126,8 @@ class PromptBuilder:
             background_dialogue_prompt = build_readable_messages(
                 latest_25_msgs,
                 merge_messages=True,
-                timestamp_mode = "normal_no_YMD",
-                show_pic = False,
+                timestamp_mode="normal_no_YMD",
+                show_pic=False,
             )
             background_dialogue_prompt = f"这是其他用户的发言：\n{background_dialogue_prompt}"
         else:
@@ -144,7 +137,7 @@ class PromptBuilder:
         core_dialogue_list = core_dialogue_list[-50:]
 
         first_msg = core_dialogue_list[0]
-        start_speaking_user_id = first_msg.get('user_id')
+        start_speaking_user_id = first_msg.get("user_id")
         if start_speaking_user_id == bot_id:
             last_speaking_user_id = bot_id
             msg_seg_str = "你的发言：\n"
@@ -157,12 +150,14 @@ class PromptBuilder:
 
         all_msg_seg_list = []
         for msg in core_dialogue_list[1:]:
-            speaker = msg.get('user_id')
+            speaker = msg.get("user_id")
             if speaker == last_speaking_user_id:
-                #还是同一个人讲话
-                msg_seg_str += f"{time.strftime('%H:%M:%S', time.localtime(msg.get('time')))}: {msg.get('processed_plain_text')}\n"
+                # 还是同一个人讲话
+                msg_seg_str += (
+                    f"{time.strftime('%H:%M:%S', time.localtime(msg.get('time')))}: {msg.get('processed_plain_text')}\n"
+                )
             else:
-                #换人了
+                # 换人了
                 msg_seg_str = f"{msg_seg_str}\n"
                 all_msg_seg_list.append(msg_seg_str)
 
@@ -171,12 +166,13 @@ class PromptBuilder:
                 else:
                     msg_seg_str = "对方的发言：\n"
 
-                msg_seg_str += f"{time.strftime('%H:%M:%S', time.localtime(msg.get('time')))}: {msg.get('processed_plain_text')}\n"
+                msg_seg_str += (
+                    f"{time.strftime('%H:%M:%S', time.localtime(msg.get('time')))}: {msg.get('processed_plain_text')}\n"
+                )
                 last_speaking_user_id = speaker
 
         all_msg_seg_list.append(msg_seg_str)
 
-
         core_msg_str = ""
         for msg in all_msg_seg_list:
             # print(f"msg: {msg}")

src/mais4u/mais4u_chat/s4u_stream_generator.py

@@ -43,8 +43,8 @@ class S4UStreamGenerator:
         # 匹配常见的句子结束符，但会忽略引号内和数字中的标点
         self.sentence_split_pattern = re.compile(
             r'([^\s\w"\'([{]*["\'([{].*?["\'}\])][^\s\w"\'([{]*|'  # 匹配被引号/括号包裹的内容
-            r'[^.。!?？！\n\r]+(?:[.。!?？！\n\r](?![\'"])|$))'  # 匹配直到句子结束符
-            , re.UNICODE | re.DOTALL
+            r'[^.。!?？！\n\r]+(?:[.。!?？！\n\r](?![\'"])|$))',  # 匹配直到句子结束符
+            re.UNICODE | re.DOTALL,
         )
 
     async def generate_response(
@@ -68,7 +68,7 @@ class S4UStreamGenerator:
 
         # 构建prompt
         if previous_reply_context:
-             message_txt = f"""
+            message_txt = f"""
              你正在回复用户的消息，但中途被打断了。这是已有的对话上下文:
              [你已经对上一条消息说的话]: {previous_reply_context}
              ---
@@ -78,9 +78,8 @@ class S4UStreamGenerator:
         else:
             message_txt = message.processed_plain_text
 
-
         prompt = await prompt_builder.build_prompt_normal(
-            message = message,
+            message=message,
             message_txt=message_txt,
             sender_name=sender_name,
             chat_stream=message.chat_stream,
@@ -132,12 +131,12 @@ class S4UStreamGenerator:
                         else:
                             # 发送之前累积的标点和当前句子
                             to_yield = punctuation_buffer + sentence
-                            if to_yield.endswith((',', '，')):
-                                to_yield = to_yield.rstrip(',，')
+                            if to_yield.endswith((",", "，")):
+                                to_yield = to_yield.rstrip(",，")
 
                             yield to_yield
-                            punctuation_buffer = "" # 清空标点符号缓冲区
-                            await asyncio.sleep(0) # 允许其他任务运行
+                            punctuation_buffer = ""  # 清空标点符号缓冲区
+                            await asyncio.sleep(0)  # 允许其他任务运行
 
                         last_match_end = match.end(0)
 
@@ -148,8 +147,7 @@ class S4UStreamGenerator:
         # 发送缓冲区中剩余的任何内容
         to_yield = (punctuation_buffer + buffer).strip()
         if to_yield:
-            if to_yield.endswith(('，', ',')):
-                to_yield = to_yield.rstrip('，,')
+            if to_yield.endswith(("，", ",")):
+                to_yield = to_yield.rstrip("，,")
             if to_yield:
                 yield to_yield
-

src/mais4u/openai_client.py

@@ -1,8 +1,5 @@
-import asyncio
-import json
-from typing import AsyncGenerator, Dict, List, Optional, Union, Any
+from typing import AsyncGenerator, Dict, List, Optional, Union
 from dataclasses import dataclass
-import aiohttp
 from openai import AsyncOpenAI
 from openai.types.chat import ChatCompletion, ChatCompletionChunk
 
@@ -10,6 +7,7 @@ from openai.types.chat import ChatCompletion, ChatCompletionChunk
 @dataclass
 class ChatMessage:
     """聊天消息数据类"""
+
     role: str
     content: str
 
@@ -40,7 +38,7 @@ class AsyncOpenAIClient:
         model: str = "gpt-3.5-turbo",
         temperature: float = 0.7,
         max_tokens: Optional[int] = None,
-        **kwargs
+        **kwargs,
     ) -> ChatCompletion:
         """
         非流式聊天完成
@@ -76,7 +74,7 @@ class AsyncOpenAIClient:
             max_tokens=max_tokens,
             stream=False,
             extra_body=extra_body if extra_body else None,
-            **kwargs
+            **kwargs,
         )
 
         return response
@@ -87,7 +85,7 @@ class AsyncOpenAIClient:
         model: str = "gpt-3.5-turbo",
         temperature: float = 0.7,
         max_tokens: Optional[int] = None,
-        **kwargs
+        **kwargs,
     ) -> AsyncGenerator[ChatCompletionChunk, None]:
         """
         流式聊天完成
@@ -123,7 +121,7 @@ class AsyncOpenAIClient:
             max_tokens=max_tokens,
             stream=True,
             extra_body=extra_body if extra_body else None,
-            **kwargs
+            **kwargs,
         )
 
         async for chunk in stream:
@@ -135,7 +133,7 @@ class AsyncOpenAIClient:
         model: str = "gpt-3.5-turbo",
         temperature: float = 0.7,
         max_tokens: Optional[int] = None,
-        **kwargs
+        **kwargs,
     ) -> AsyncGenerator[str, None]:
         """
         获取流式内容（只返回文本内容）
@@ -151,11 +149,7 @@ class AsyncOpenAIClient:
             str: 文本内容片段
         """
         async for chunk in self.chat_completion_stream(
-            messages=messages,
-            model=model,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            **kwargs
+            messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, **kwargs
         ):
             if chunk.choices and chunk.choices[0].delta.content:
                 yield chunk.choices[0].delta.content
@@ -166,7 +160,7 @@ class AsyncOpenAIClient:
         model: str = "gpt-3.5-turbo",
         temperature: float = 0.7,
         max_tokens: Optional[int] = None,
-        **kwargs
+        **kwargs,
     ) -> str:
         """
         收集完整的流式响应
@@ -183,11 +177,7 @@ class AsyncOpenAIClient:
         """
         full_response = ""
         async for content in self.get_stream_content(
-            messages=messages,
-            model=model,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            **kwargs
+            messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, **kwargs
         ):
             full_response += content
 
@@ -232,10 +222,7 @@ class ConversationManager:
         self.messages.append(ChatMessage(role="assistant", content=content))
 
     async def send_message_stream(
-        self,
-        content: str,
-        model: str = "gpt-3.5-turbo",
-        **kwargs
+        self, content: str, model: str = "gpt-3.5-turbo", **kwargs
     ) -> AsyncGenerator[str, None]:
         """
         发送消息并获取流式响应
@@ -251,22 +238,13 @@ class ConversationManager:
         self.add_user_message(content)
 
         response_content = ""
-        async for chunk in self.client.get_stream_content(
-            messages=self.messages,
-            model=model,
-            **kwargs
-        ):
+        async for chunk in self.client.get_stream_content(messages=self.messages, model=model, **kwargs):
             response_content += chunk
             yield chunk
 
         self.add_assistant_message(response_content)
 
-    async def send_message(
-        self,
-        content: str,
-        model: str = "gpt-3.5-turbo",
-        **kwargs
-    ) -> str:
+    async def send_message(self, content: str, model: str = "gpt-3.5-turbo", **kwargs) -> str:
         """
         发送消息并获取完整响应
 
@@ -280,11 +258,7 @@ class ConversationManager:
         """
         self.add_user_message(content)
 
-        response = await self.client.chat_completion(
-            messages=self.messages,
-            model=model,
-            **kwargs
-        )
+        response = await self.client.chat_completion(messages=self.messages, model=model, **kwargs)
 
         response_content = response.choices[0].message.content
         self.add_assistant_message(response_content)