Merge branch 'debug' of https://github.com/Pliosauroidea/MaiMBot into debug

src/plugins/chat/bot.py

@@ -13,6 +13,7 @@ from ..memory_system.memory import hippocampus
 from ..moods.moods import MoodManager  # 导入情绪管理器
 from .config import global_config
 from .cq_code import CQCode, cq_code_tool  # 导入CQCode模块
+from .cq_code import CQCode, cq_code_tool  # 导入CQCode模块
 from .emoji_manager import emoji_manager  # 导入表情包管理器
 from .llm_generator import ResponseGenerator
 from .message import MessageSending, MessageRecv, MessageThinking, MessageSet
@@ -30,6 +31,7 @@ from .willing_manager import willing_manager  # 导入意愿管理器
 from .message_base import UserInfo, GroupInfo, Seg
 
 
+
 class ChatBot:
     def __init__(self):
         self.storage = MessageStorage()
@@ -95,6 +97,7 @@ class ChatBot:
         # group_info = await bot.get_group_info(group_id=event.group_id)
         # sender_info = await bot.get_group_member_info(group_id=event.group_id, user_id=event.user_id, no_cache=True)
 
+        message_cq = MessageRecvCQ(
         message_cq = MessageRecvCQ(
             message_id=event.message_id,
             user_info=user_info,
@@ -102,18 +105,29 @@ class ChatBot:
             group_info=group_info,
             reply_message=event.reply,
             platform="qq",
+            platform="qq",
         )
         message_json = message_cq.to_dict()
+        message_json = message_cq.to_dict()
 
         # 进入maimbot
         message = MessageRecv(message_json)
 
+        groupinfo = message.message_info.group_info
+        userinfo = message.message_info.user_info
+        messageinfo = message.message_info
+        message = MessageRecv(message_json)
+
         groupinfo = message.message_info.group_info
         userinfo = message.message_info.user_info
         messageinfo = message.message_info
 
         # 消息过滤，涉及到config有待更新
 
+        chat = await chat_manager.get_or_create_stream(
+            platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
+        )
+
         chat = await chat_manager.get_or_create_stream(
             platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
         )
@@ -150,6 +164,7 @@ class ChatBot:
 
         # topic=await topic_identifier.identify_topic_llm(message.processed_plain_text)
         topic = ""
+        topic = ""
         interested_rate = 0
         interested_rate = (
             await hippocampus.memory_activate_value(message.processed_plain_text) / 100
@@ -159,6 +174,8 @@ class ChatBot:
 
         await self.storage.store_message(message, chat, topic[0] if topic else None)
 
+        await self.storage.store_message(message, chat, topic[0] if topic else None)
+
         is_mentioned = is_mentioned_bot_in_message(message)
         reply_probability = await willing_manager.change_reply_willing_received(
             chat_stream=chat,
@@ -167,9 +184,11 @@ class ChatBot:
             config=global_config,
             is_emoji=message.is_emoji,
             interested_rate=interested_rate,
+            interested_rate=interested_rate,
         )
         current_willing = willing_manager.get_willing(chat_stream=chat)
 
+
         logger.info(
             f"[{current_time}][{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{chat.user_info.user_nickname}:"
             f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
@@ -177,6 +196,7 @@ class ChatBot:
 
         response = None
 
+
         if random() < reply_probability:
             bot_user_info = UserInfo(
                 user_id=global_config.BOT_QQ,
@@ -192,12 +212,16 @@ class ChatBot:
                 reply=message,
             )
 
+
             message_manager.add_message(thinking_message)
 
             willing_manager.change_reply_willing_sent(chat)
 
             response, raw_content = await self.gpt.generate_response(message)
 
+
+            response, raw_content = await self.gpt.generate_response(message)
+
         # print(f"response: {response}")
         if response:
             # print(f"有response: {response}")
@@ -257,7 +281,7 @@ class ChatBot:
             print(f"添加message_set到message_manager")
             message_manager.add_message(message_set)
 
-            bot_response_time = tinking_time_point
+            bot_response_time = thinking_time_point
 
             if random() < global_config.emoji_chance:
                 emoji_raw = await emoji_manager.get_emoji_for_text(response)
@@ -269,7 +293,7 @@ class ChatBot:
                     emoji_cq = image_path_to_base64(emoji_path)
 
                     if random() < 0.5:
-                        bot_response_time = tinking_time_point - 1
+                        bot_response_time = thinking_time_point - 1
                     else:
                         bot_response_time = bot_response_time + 1
 

src/plugins/chat/cq_code.py

@@ -231,7 +231,8 @@ class CQCode:
                                     group_info=group_info,
                                 )
                                 content_seg = Seg(
-                                    type="seglist", data=message_obj.message_segment                                )
+                                    type="seglist", data=[message_obj.message_segment]                             
+                                )
                             else:
                                 content_seg = Seg(type="text", data="[空消息]")
                 else:
@@ -256,7 +257,7 @@ class CQCode:
                             group_info=group_info,
                         )
                         content_seg = Seg(
-                            type="seglist", data=message_obj.message_segment
+                            type="seglist", data=[message_obj.message_segment]
                         )
                     else:
                         content_seg = Seg(type="text", data="[空消息]")
@@ -281,11 +282,12 @@ class CQCode:
         if self.reply_message.sender.user_id:
             
             message_obj = MessageRecvCQ(
-                user_info=UserInfo(user_id=self.reply_message.sender.user_id,user_nickname=self.reply_message.sender.get("nickname",None)),
+                user_info=UserInfo(user_id=self.reply_message.sender.user_id,user_nickname=self.reply_message.sender.nickname),
                 message_id=self.reply_message.message_id,
                 raw_message=str(self.reply_message.message),
                 group_info=GroupInfo(group_id=self.reply_message.group_id),
             )
+            
 
             segments = []
             if message_obj.message_info.user_info.user_id == global_config.BOT_QQ:
@@ -302,7 +304,7 @@ class CQCode:
                     )
                 )
 
-            segments.append(Seg(type="seglist", data=message_obj.message_segment))
+            segments.append(Seg(type="seglist", data=[message_obj.message_segment]))
             segments.append(Seg(type="text", data="]"))
             return segments
         else:

src/plugins/chat/message.py

@@ -18,7 +18,50 @@ urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
 
 @dataclass
-class MessageRecv(MessageBase):
+class Message(MessageBase):
+    chat_stream: ChatStream=None
+    reply: Optional['Message'] = None
+    detailed_plain_text: str = ""
+    processed_plain_text: str = ""
+
+    def __init__(
+        self,
+        message_id: str,
+        time: int,
+        chat_stream: ChatStream,
+        user_info: UserInfo,
+        message_segment: Optional[Seg] = None,
+        reply: Optional['MessageRecv'] = None,
+        detailed_plain_text: str = "",
+        processed_plain_text: str = "",
+    ):
+        # 构造基础消息信息
+        message_info = BaseMessageInfo(
+            platform=chat_stream.platform,
+            message_id=message_id,
+            time=time,
+            group_info=chat_stream.group_info,
+            user_info=user_info
+        )
+
+        # 调用父类初始化
+        super().__init__(
+            message_info=message_info,
+            message_segment=message_segment,
+            raw_message=None
+        )
+
+        self.chat_stream = chat_stream
+        # 文本处理相关属性
+        self.processed_plain_text = processed_plain_text
+        self.detailed_plain_text = detailed_plain_text
+        
+        # 回复消息
+        self.reply = reply
+
+
+@dataclass
+class MessageRecv(Message):
     """接收消息类，用于处理从MessageCQ序列化的消息"""
 
     def __init__(self, message_dict: Dict):
@@ -27,24 +70,19 @@ class MessageRecv(MessageBase):
         Args:
             message_dict: MessageCQ序列化后的字典
         """
-        message_info = BaseMessageInfo.from_dict(message_dict.get("message_info", {}))
+        self.message_info = BaseMessageInfo.from_dict(message_dict.get('message_info', {}))
-        message_segment = Seg.from_dict(message_dict.get("message_segment", {}))
+        self.message_segment = Seg.from_dict(message_dict.get('message_segment', {}))
-        raw_message = message_dict.get("raw_message")
+        self.raw_message = message_dict.get('raw_message')
-
+        
-        super().__init__(
-            message_info=message_info,
-            message_segment=message_segment,
-            raw_message=raw_message,
-        )
-
         # 处理消息内容
         self.processed_plain_text = ""  # 初始化为空字符串
-        self.detailed_plain_text = ""  # 初始化为空字符串
+        self.detailed_plain_text = ""   # 初始化为空字符串
-        self.is_emoji = False
+        self.is_emoji=False
-
+    
-    def update_chat_stream(self, chat_stream: ChatStream):
+    
-        self.chat_stream = chat_stream
+    def update_chat_stream(self,chat_stream:ChatStream):
-
+        self.chat_stream=chat_stream
+    
     async def process(self) -> None:
         """处理消息内容，生成纯文本和详细文本
 
@@ -118,48 +156,7 @@ class MessageRecv(MessageBase):
             else f"{user_info.user_nickname}(ta的id:{user_info.user_id})"
         )
         return f"[{time_str}] {name}: {self.processed_plain_text}\n"
-
+    
-
-@dataclass
-class Message(MessageBase):
-    chat_stream: ChatStream = None
-    reply: Optional["Message"] = None
-    detailed_plain_text: str = ""
-    processed_plain_text: str = ""
-
-    def __init__(
-        self,
-        message_id: str,
-        time: int,
-        chat_stream: ChatStream,
-        user_info: UserInfo,
-        message_segment: Optional[Seg] = None,
-        reply: Optional["MessageRecv"] = None,
-        detailed_plain_text: str = "",
-        processed_plain_text: str = "",
-    ):
-        # 构造基础消息信息
-        message_info = BaseMessageInfo(
-            platform=chat_stream.platform,
-            message_id=message_id,
-            time=time,
-            group_info=chat_stream.group_info,
-            user_info=user_info,
-        )
-
-        # 调用父类初始化
-        super().__init__(
-            message_info=message_info, message_segment=message_segment, raw_message=None
-        )
-
-        self.chat_stream = chat_stream
-        # 文本处理相关属性
-        self.processed_plain_text = detailed_plain_text
-        self.detailed_plain_text = processed_plain_text
-
-        # 回复消息
-        self.reply = reply
-
 
 @dataclass
 class MessageProcessBase(Message):

src/plugins/models/utils_model.py

@@ -192,13 +192,11 @@ class LLM_request:
                                     logger.warning(f"检测到403错误，模型从 {old_model_name} 降级为 {self.model_name}")
 
                                     # 对全局配置进行更新
-                                    if hasattr(global_config, 'llm_normal') and global_config.llm_normal.get(
+                                    if global_config.llm_normal.get('name') == old_model_name:
-                                            'name') == old_model_name:
                                         global_config.llm_normal['name'] = self.model_name
                                         logger.warning(f"将全局配置中的 llm_normal 模型临时降级至{self.model_name}")
 
-                                    if hasattr(global_config, 'llm_reasoning') and global_config.llm_reasoning.get(
+                                    if global_config.llm_reasoning.get('name') == old_model_name:
-                                            'name') == old_model_name:
                                         global_config.llm_reasoning['name'] = self.model_name
                                         logger.warning(f"将全局配置中的 llm_reasoning 模型临时降级至{self.model_name}")
 
@@ -216,6 +214,7 @@ class LLM_request:
 
                         # 将流式输出转化为非流式输出
                         if stream_mode:
+                            flag_delta_content_finished = False
                             accumulated_content = ""
                             async for line_bytes in response.content:
                                 line = line_bytes.decode("utf-8").strip()
@@ -227,13 +226,25 @@ class LLM_request:
                                         break
                                     try:
                                         chunk = json.loads(data_str)
-                                        delta = chunk["choices"][0]["delta"]
+                                        if flag_delta_content_finished:
-                                        delta_content = delta.get("content")
+                                            usage = chunk.get("usage", None) # 获取tokn用量
-                                        if delta_content is None:
+                                        else:
-                                            delta_content = ""
+                                            delta = chunk["choices"][0]["delta"]
-                                        accumulated_content += delta_content
+                                            delta_content = delta.get("content")
+                                            if delta_content is None:
+                                                delta_content = ""
+                                            accumulated_content += delta_content
+                                            # 检测流式输出文本是否结束
+                                            finish_reason =  chunk["choices"][0]["finish_reason"]
+                                            if finish_reason == "stop":
+                                                usage = chunk.get("usage", None)
+                                                if usage:
+                                                    break
+                                                # 部分平台在文本输出结束前不会返回token用量，此时需要再获取一次chunk
+                                                flag_delta_content_finished = True
+                                            
                                     except Exception:
-                                        logger.exception("解析流式输出错")
+                                        logger.exception("解析流式输出错误")
                             content = accumulated_content
                             reasoning_content = ""
                             think_match = re.search(r'<think>(.*?)</think>', content, re.DOTALL)
@@ -242,7 +253,7 @@ class LLM_request:
                             content = re.sub(r'<think>.*?</think>', '', content, flags=re.DOTALL).strip()
                             # 构造一个伪result以便调用自定义响应处理器或默认处理器
                             result = {
-                                "choices": [{"message": {"content": content, "reasoning_content": reasoning_content}}]}
+                                "choices": [{"message": {"content": content, "reasoning_content": reasoning_content}}],  "usage": usage}
                             return response_handler(result) if response_handler else self._default_response_handler(
                                 result, user_id, request_type, endpoint)
                         else: