Merge pull request #2 from MaiM-with-u/tc_merge

修复了情绪管理器没有正确导入导致发布出消息

src/plugins/chat/bot.py

@@ -163,12 +163,16 @@ class ChatBot:
             
             response,raw_content = await self.gpt.generate_response(message)
             
+        # print(f"response: {response}")
         if response:
+            # print(f"有response: {response}")
             container = message_manager.get_container(chat.stream_id)
             thinking_message = None
             # 找到message,删除
+            # print(f"开始找思考消息")
             for msg in container.messages:
                 if isinstance(msg, MessageThinking) and msg.message_info.message_id == think_id:
+                    # print(f"找到思考消息: {msg}")
                     thinking_message = msg
                     container.messages.remove(msg)
                     break
@@ -186,14 +190,14 @@ class ChatBot:
             
             mark_head = False
             for msg in response:
-                print("test")
                 # print(f"\033[1;32m[回复内容]\033[0m {msg}")
                 # 通过时间改变时间戳
                 typing_time = calculate_typing_time(msg)
+                print(f"typing_time: {typing_time}")
                 accu_typing_time += typing_time
                 timepoint = tinking_time_point + accu_typing_time
-                
                 message_segment = Seg(type='text', data=msg)
+                print(f"message_segment: {message_segment}")
                 bot_message = MessageSending(
                     message_id=think_id,
                     chat_stream=chat,
@@ -203,12 +207,15 @@ class ChatBot:
                     is_head=not mark_head,
                     is_emoji=False
                 )
+                print(f"bot_message: {bot_message}")
                 if not mark_head:
                     mark_head = True
+                print(f"添加消息到message_set: {bot_message}")
                 message_set.add_message(bot_message)
 
             # message_set 可以直接加入 message_manager
             # print(f"\033[1;32m[回复]\033[0m 将回复载入发送容器")
+            print(f"添加message_set到message_manager")
             message_manager.add_message(message_set)
 
             bot_response_time = tinking_time_point

src/plugins/chat/llm_generator.py

@@ -63,6 +63,9 @@ class ResponseGenerator:
         )
         raw_content = model_response
 
+        # print(f"raw_content: {raw_content}")
+        # print(f"model_response: {model_response}")
+        
         if model_response:
             logger.info(f'{global_config.BOT_NICKNAME}的回复是：{model_response}')
             model_response = await self._process_response(model_response)
@@ -200,6 +203,8 @@ class ResponseGenerator:
             return None, []
 
         processed_response = process_llm_response(content)
+        
+        # print(f"得到了处理后的llm返回{processed_response}")
 
         return processed_response
 

src/plugins/chat/message_sender.py

@@ -149,6 +149,7 @@ class MessageManager:
         """处理聊天流消息"""
         container = self.get_container(chat_id)
         if container.has_messages():
+            # print(f"处理有message的容器chat_id: {chat_id}")
             message_earliest = container.get_earliest_message()
             
             if isinstance(message_earliest, MessageThinking):
@@ -161,15 +162,15 @@ class MessageManager:
                     logger.warning(f"消息思考超时({thinking_time}秒)，移除该消息")
                     container.remove_message(message_earliest)
             else:
-                print(f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中")
+                
                 if message_earliest.is_head and message_earliest.update_thinking_time() > 30:
                     await message_sender.send_message(message_earliest.set_reply())
                 else:
                     await message_sender.send_message(message_earliest)
-
-                # if message_earliest.is_emoji:
-                #     message_earliest.processed_plain_text = "[表情包]"
                 await message_earliest.process()
+                
+                print(f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中")
+                
                 await self.storage.store_message(message_earliest, message_earliest.chat_stream,None)
                 
                 container.remove_message(message_earliest)

src/plugins/chat/utils.py

@@ -15,6 +15,7 @@ from .config import global_config
 from .message import MessageThinking, MessageRecv,MessageSending,MessageProcessBase,Message
 from .message_base import MessageBase,BaseMessageInfo,UserInfo,GroupInfo
 from .chat_stream import ChatStream
+from ..moods.moods import MoodManager
 
 driver = get_driver()
 config = driver.config
@@ -72,43 +73,42 @@ def calculate_information_content(text):
 
 
 def get_cloest_chat_from_db(db, length: int, timestamp: str):
-    """从数据库中获取最接近指定时间戳的聊天记录，并记录读取次数
+    """从数据库中获取最接近指定时间戳的聊天记录
     
+    Args:
+        db: 数据库实例
+        length: 要获取的消息数量
+        timestamp: 时间戳
+        
     Returns:
-        list: 消息记录字典列表，每个字典包含消息内容和时间信息
+        list: 消息记录列表，每个记录包含时间和文本信息
     """
     chat_records = []
     closest_record = db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])
     
-    if closest_record and closest_record.get('memorized', 0) < 4:            
+    if closest_record:            
         closest_time = closest_record['time']
-        chat_id = closest_record['chat_id']  # 获取groupid
+        chat_id = closest_record['chat_id']  # 获取chat_id
-        # 获取该时间戳之后的length条消息，且groupid相同
+        # 获取该时间戳之后的length条消息，保持相同的chat_id
         chat_records = list(db.db.messages.find(
-            {"time": {"$gt": closest_time}, "chat_id": chat_id}
+            {
+                "time": {"$gt": closest_time},
+                "chat_id": chat_id  # 添加chat_id过滤
+            }
         ).sort('time', 1).limit(length))
         
-        # 更新每条消息的memorized属性
+        # 转换记录格式
-        for record in records:
+        formatted_records = []
-            current_memorized = record.get('memorized', 0)
+        for record in chat_records:
-            if current_memorized > 3:
+            formatted_records.append({
-                print("消息已读取3次，跳过")
-                return ''
-                
-            # 更新memorized值
-            db.db.messages.update_one(
-                {"_id": record["_id"]},
-                {"$set": {"memorized": current_memorized + 1}}
-            )
-            
-            # 添加到记录列表中
-            chat_records.append({
-                'text': record["detailed_plain_text"],
                 'time': record["time"],
-                'group_id': record["group_id"]
+                'chat_id': record["chat_id"],
+                'detailed_plain_text': record.get("detailed_plain_text", "")  # 添加文本内容
             })
             
-    return chat_records
+        return formatted_records
+            
+    return []
 
 
 async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list:

src/plugins/chat/utils_image.py

@@ -315,6 +315,10 @@ class ImageManager:
             prompt = "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。"
             description, _ = await self._llm.generate_response_for_image(prompt, image_base64)
             
+            if description is None:
+                logger.warning("AI未能生成图片描述")
+                return "[图片]"
+            
             # 根据配置决定是否保存图片
             if global_config.EMOJI_SAVE:
                 # 生成文件名和路径

src/plugins/memory_system/memory.py

@@ -238,7 +238,7 @@ class Hippocampus:
             time_info += f"是从 {earliest_str} 到 {latest_str} 的对话:\n"
 
         for msg in messages:
-            input_text += f"{msg['text']}\n"
+            input_text += f"{msg['detailed_plain_text']}\n"
 
         logger.debug(input_text)