fix: 懒加载单例以修复环境变量加载问题

Author: BBleae

bot.py

@@ -16,6 +16,15 @@
 
 from src.manager.async_task_manager import async_task_manager
 
+logger = get_logger("main")
+
+# 直接加载生产环境变量配置
+if os.path.exists(".env"):
+    load_dotenv(".env", override=True)
+    logger.info("成功加载环境变量配置")
+else:
+    logger.warning("未找到.env文件，请确保程序所需的环境变量被正确设置")
+
 install(extra_lines=3)
 
 # 设置工作目录为脚本所在目录
@@ -24,7 +33,6 @@
 print(f"已设置工作目录为: {script_dir}")
 
 
-logger = get_logger("main")
 confirm_logger = get_logger("confirm")
 # 获取没有加载env时的环境变量
 env_mask = {key: os.getenv(key) for key in os.environ}
@@ -65,15 +73,6 @@ def easter_egg():
     print(rainbow_text)
 
 
-def load_env():
-    # 直接加载生产环境变量配置
-    if os.path.exists(".env"):
-        load_dotenv(".env", override=True)
-        logger.info("成功加载环境变量配置")
-    else:
-        logger.warning("未找到.env文件，请确保程序所需的环境变量被正确设置")
-
-
 def scan_provider(env_config: dict):
     provider = {}
 
@@ -198,7 +197,6 @@ def check_eula():
 
 
 def raw_main():
-    load_env()
     # 利用 TZ 环境变量设定程序工作的时区
     if platform.system().lower() != "windows":
         time.tzset()

scripts/message_retrieval_script.py

@@ -36,7 +36,8 @@
 from src.common.database.database import db
 from src.config.config import global_config
 from src.llm_models.utils_model import LLMRequest
-from src.person_info.person_info import PersonInfoManager, person_info_manager
+from src.person_info.person_info import PersonInfoManager, get_person_info_manager
+
 
 logger = get_logger("message_retrieval")
 
@@ -77,7 +78,7 @@ async def build_name_mapping(messages: List[Dict[str, Any]], target_person_name:
     name_mapping = {}
     current_user = "A"
     user_count = 1
-
+    person_info_manager = get_person_info_manager()
     # 遍历消息，构建映射
     for msg in messages:
         await person_info_manager.get_or_create_person(
@@ -410,6 +411,7 @@ def retrieve_messages(self, user_qq: str, time_period: str) -> Dict[str, List[Di
 
     async def update_person_impression_from_segment(self, person_id: str, readable_messages: str, segment_time: float):
         """从消息段落更新用户印象，使用和relationship_manager相同的流程"""
+        person_info_manager = get_person_info_manager()
         person_name = await person_info_manager.get_value(person_id, "person_name")
         nickname = await person_info_manager.get_value(person_id, "nickname")
 
@@ -659,6 +661,7 @@ async def process_segments_and_update_impression(
         """处理分段消息并更新用户印象到数据库"""
         # 获取目标用户信息
         target_person_id = get_person_id("qq", user_qq)
+        person_info_manager = get_person_info_manager()
         target_person_name = await person_info_manager.get_value(target_person_id, "person_name")
 
         if not target_person_name:

src/chat/__init__.py

@@ -3,13 +3,13 @@
 包含聊天、情绪、记忆、日程等功能模块
 """
 
-from src.chat.message_receive.chat_stream import chat_manager
-from src.chat.emoji_system.emoji_manager import emoji_manager
-from src.chat.normal_chat.willing.willing_manager import willing_manager
+from src.chat.message_receive.chat_stream import get_chat_manager
+from src.chat.emoji_system.emoji_manager import get_emoji_manager
+from src.chat.normal_chat.willing.willing_manager import get_willing_manager
 
 # 导出主要组件供外部使用
 __all__ = [
-    "chat_manager",
-    "emoji_manager",
-    "willing_manager",
+    "get_chat_manager",
+    "get_emoji_manager",
+    "get_willing_manager",
 ]

src/chat/emoji_system/emoji_manager.py

@@ -15,7 +15,7 @@
 from src.common.database.database_model import Emoji
 from src.common.database.database import db as peewee_db
 from src.config.config import global_config
-from src.chat.utils.utils_image import image_path_to_base64, image_manager
+from src.chat.utils.utils_image import image_path_to_base64, get_image_manager
 from src.llm_models.utils_model import LLMRequest
 from src.common.logger import get_logger
 from rich.traceback import install
@@ -844,7 +844,7 @@ async def build_emoji_description(self, image_base64: str) -> Tuple[str, List[st
 
             # 调用AI获取描述
             if image_format == "gif" or image_format == "GIF":
-                image_base64 = image_manager.transform_gif(image_base64)
+                image_base64 = get_image_manager().transform_gif(image_base64)
                 prompt = "这是一个动态图表情包，每一张图代表了动态图的某一帧，黑色背景代表透明，描述一下表情包表达的情感和内容，描述细节，从互联网梗,meme的角度去分析"
                 description, _ = await self.vlm.generate_response_for_image(prompt, image_base64, "jpg")
             else:
@@ -1000,5 +1000,11 @@ async def register_emoji_by_filename(self, filename: str) -> bool:
             return False
 
 
-# 创建全局单例
-emoji_manager = EmojiManager()
+emoji_manager = None
+
+
+def get_emoji_manager():
+    global emoji_manager
+    if emoji_manager is None:
+        emoji_manager = EmojiManager()
+    return emoji_manager

src/chat/focus_chat/expressors/default_expressor.py

@@ -1,15 +1,17 @@
 import traceback
 from typing import List, Optional, Dict, Any, Tuple
+
+from src.chat.focus_chat.expressors.exprssion_learner import get_expression_learner
 from src.chat.message_receive.message import MessageRecv, MessageThinking, MessageSending
 from src.chat.message_receive.message import Seg  # Local import needed after move
 from src.chat.message_receive.message import UserInfo
-from src.chat.message_receive.chat_stream import chat_manager
+from src.chat.message_receive.chat_stream import get_chat_manager
 from src.common.logger import get_logger
 from src.llm_models.utils_model import LLMRequest
 from src.config.config import global_config
 from src.chat.utils.utils_image import image_path_to_base64  # Local import needed after move
 from src.chat.utils.timer_calculator import Timer  # <--- Import Timer
-from src.chat.emoji_system.emoji_manager import emoji_manager
+from src.chat.emoji_system.emoji_manager import get_emoji_manager
 from src.chat.focus_chat.heartFC_sender import HeartFCSender
 from src.chat.utils.utils import process_llm_response
 from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info
@@ -18,7 +20,6 @@
 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
 import time
-from src.chat.focus_chat.expressors.exprssion_learner import expression_learner
 import random
 
 logger = get_logger("expressor")
@@ -274,6 +275,7 @@ async def build_prompt_focus(
             truncate=True,
         )
 
+        expression_learner = get_expression_learner()
         (
             learnt_style_expressions,
             learnt_grammar_expressions,
@@ -365,7 +367,7 @@ async def send_response_messages(
             logger.error(f"{self.log_prefix} 无法发送回复，anchor_message 为空。")
             return None
 
-        stream_name = chat_manager.get_stream_name(chat_id) or chat_id  # 获取流名称用于日志
+        stream_name = get_chat_manager().get_stream_name(chat_id) or chat_id  # 获取流名称用于日志
 
         # 检查思考过程是否仍在进行，并获取开始时间
         if thinking_id:
@@ -454,7 +456,7 @@ async def _choose_emoji(self, send_emoji: str):
         选择表情，根据send_emoji文本选择表情，返回表情base64
         """
         emoji_base64 = ""
-        emoji_raw = await emoji_manager.get_emoji_for_text(send_emoji)
+        emoji_raw = await get_emoji_manager().get_emoji_for_text(send_emoji)
         if emoji_raw:
             emoji_path, _description, _emotion = emoji_raw
             emoji_base64 = image_path_to_base64(emoji_path)

src/chat/focus_chat/expressors/exprssion_learner.py

@@ -7,7 +7,7 @@
 from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_random, build_anonymous_messages
 from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
 import os
-from src.chat.message_receive.chat_stream import chat_manager
+from src.chat.message_receive.chat_stream import get_chat_manager
 import json
 
 
@@ -220,7 +220,7 @@ async def learn_and_store(self, type: str, num: int = 10) -> List[Tuple[str, str
             return []
         learnt_expressions, chat_id = res
 
-        chat_stream = chat_manager.get_stream(chat_id)
+        chat_stream = get_chat_manager().get_stream(chat_id)
         if chat_stream.group_info:
             group_name = chat_stream.group_info.group_name
         else:
@@ -399,4 +399,11 @@ def parse_expression_response(self, response: str, chat_id: str) -> List[Tuple[s
 
 init_prompt()
 
-expression_learner = ExpressionLearner()
+expression_learner = None
+
+
+def get_expression_learner():
+    global expression_learner
+    if expression_learner is None:
+        expression_learner = ExpressionLearner()
+    return expression_learner

src/chat/focus_chat/heartFC_chat.py

@@ -4,7 +4,7 @@
 import traceback
 from collections import deque
 from typing import List, Optional, Dict, Any, Deque, Callable, Awaitable
-from src.chat.message_receive.chat_stream import chat_manager
+from src.chat.message_receive.chat_stream import get_chat_manager
 from rich.traceback import install
 from src.chat.utils.prompt_builder import global_prompt_manager
 from src.common.logger import get_logger
@@ -97,8 +97,8 @@ def __init__(
         """
         # 基础属性
         self.stream_id: str = chat_id  # 聊天流ID
-        self.chat_stream = chat_manager.get_stream(self.stream_id)
-        self.log_prefix = f"[{chat_manager.get_stream_name(self.stream_id) or self.stream_id}]"
+        self.chat_stream = get_chat_manager().get_stream(self.stream_id)
+        self.log_prefix = f"[{get_chat_manager().get_stream_name(self.stream_id) or self.stream_id}]"
 
         self.memory_activator = MemoryActivator()
 

src/chat/focus_chat/heartflow_message_processor.py

@@ -3,18 +3,19 @@
 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 chat_manager, ChatStream
+from src.chat.message_receive.chat_stream import get_chat_manager, ChatStream
 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 src.person_info.relationship_manager import relationship_manager
 
 import math
 import re
 import traceback
 from typing import Optional, Tuple, Dict, Any
 from maim_message import UserInfo
 
+from src.person_info.relationship_manager import get_relationship_manager
+
 # from ..message_receive.message_buffer import message_buffer
 
 logger = get_logger("chat")
@@ -45,6 +46,7 @@ async def _process_relationship(message: MessageRecv) -> None:
     nickname = message.message_info.user_info.user_nickname
     cardname = message.message_info.user_info.user_cardname or nickname
 
+    relationship_manager = get_relationship_manager()
     is_known = await relationship_manager.is_known_some_one(platform, user_id)
 
     if not is_known:
@@ -181,7 +183,7 @@ async def process_message(self, message_data: Dict[str, Any]) -> None:
             userinfo = message.message_info.user_info
             messageinfo = message.message_info
 
-            chat = await chat_manager.get_or_create_stream(
+            chat = await get_chat_manager().get_or_create_stream(
                 platform=messageinfo.platform,
                 user_info=userinfo,
                 group_info=groupinfo,

src/chat/focus_chat/info_processors/mind_processor.py

@@ -5,11 +5,11 @@
 import time
 import traceback
 from src.common.logger import get_logger
-from src.individuality.individuality import individuality
+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 chat_manager
-from src.person_info.relationship_manager import relationship_manager
+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, Optional
@@ -77,7 +77,7 @@ def __init__(self, subheartflow_id: str):
         self.structured_info = []
         self.structured_info_str = ""
 
-        name = chat_manager.get_stream_name(self.subheartflow_id)
+        name = get_chat_manager().get_stream_name(self.subheartflow_id)
         self.log_prefix = f"[{name}] "
         self._update_structured_info_str()
 
@@ -195,13 +195,14 @@ async def do_thinking_before_reply(
         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=individuality.name,
+            bot_name=get_individuality().name,
             memory_str=memory_str,
             extra_info=self.structured_info_str,
             relation_prompt=relation_prompt,

src/chat/focus_chat/info_processors/relationship_processor.py

@@ -6,19 +6,20 @@
 import traceback
 from src.common.logger import get_logger
 from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
-from src.chat.message_receive.chat_stream import chat_manager
-from src.person_info.relationship_manager import relationship_manager
+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 typing import List, Optional
 from typing import Dict
 from src.chat.focus_chat.info.info_base import InfoBase
 from src.chat.focus_chat.info.relation_info import RelationInfo
 from json_repair import repair_json
-from src.person_info.person_info import person_info_manager
+from src.person_info.person_info import get_person_info_manager
 import json
 import asyncio
 from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat
 
+
 # 配置常量：是否启用小模型即时信息提取
 # 开启时：使用小模型并行即时提取，速度更快，但精度可能略低
 # 关闭时：使用原来的异步模式，精度更高但速度较慢
@@ -110,7 +111,7 @@ def __init__(self, subheartflow_id: str):
                 request_type="focus.relationship.instant",
             )
 
-        name = chat_manager.get_stream_name(self.subheartflow_id)
+        name = get_chat_manager().get_stream_name(self.subheartflow_id)
         self.log_prefix = f"[{name}] "
 
     async def process_info(
@@ -241,6 +242,7 @@ async def relation_identify(
                 instant_tasks = []
                 async_tasks = []
 
+                person_info_manager = get_person_info_manager()
                 for person_name, info_type in content_json.items():
                     person_id = person_info_manager.get_person_id_by_person_name(person_name)
                     if person_id:
@@ -366,6 +368,7 @@ async def _fetch_single_info_instant(self, person_id: str, info_type: str, start
         """
         使用小模型提取单个信息类型
         """
+        person_info_manager = get_person_info_manager()
         nickname_str = ",".join(global_config.bot.alias_names)
         name_block = f"你的名字是{global_config.bot.nickname},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"
 
@@ -453,6 +456,7 @@ async def fetch_person_info(self, person_id: str, info_types: list[str], start_t
         nickname_str = ",".join(global_config.bot.alias_names)
         name_block = f"你的名字是{global_config.bot.nickname},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"
 
+        person_info_manager = get_person_info_manager()
         person_name = await person_info_manager.get_value(person_id, "person_name")
 
         info_type_str = ""
@@ -534,6 +538,7 @@ async def update_impression_on_cache_expiry(self, person_id: str, chat_id: str,
             impression_messages = get_raw_msg_by_timestamp_with_chat(chat_id, start_time, end_time)
             if impression_messages:
                 logger.info(f"为 {person_id} 获取到 {len(impression_messages)} 条消息用于印象更新。")
+                relationship_manager = get_relationship_manager()
                 await relationship_manager.update_person_impression(
                     person_id=person_id, timestamp=end_time, bot_engaged_messages=impression_messages
                 )