chore: 部分去除print改用logger
Fix/20250309 logger optimize
This commit is contained in:
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28
bot.py
28
bot.py
@@ -1,5 +1,7 @@
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import os
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import shutil
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import sys
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import nonebot
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import time
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from dotenv import load_dotenv
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@@ -10,6 +12,7 @@ import platform
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# 获取没有加载env时的环境变量
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env_mask = {key: os.getenv(key) for key in os.environ}
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def easter_egg():
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# 彩蛋
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from colorama import init, Fore
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@@ -22,11 +25,12 @@ def easter_egg():
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rainbow_text += rainbow_colors[i % len(rainbow_colors)] + char
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print(rainbow_text)
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def init_config():
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# 初次启动检测
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if not os.path.exists("config/bot_config.toml"):
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logger.warning("检测到bot_config.toml不存在，正在从模板复制")
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# 检查config目录是否存在
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if not os.path.exists("config"):
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os.makedirs("config")
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@@ -35,6 +39,7 @@ def init_config():
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shutil.copy("template/bot_config_template.toml", "config/bot_config.toml")
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logger.info("复制完成，请修改config/bot_config.toml和.env.prod中的配置后重新启动")
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def init_env():
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# 初始化.env 默认ENVIRONMENT=prod
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if not os.path.exists(".env"):
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@@ -46,11 +51,17 @@ def init_env():
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logger.error("检测到.env.prod文件不存在")
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shutil.copy("template.env", "./.env.prod")
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# 检测.env.dev文件是否存在，不存在的话直接复制生产环境配置
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if not os.path.exists(".env.dev"):
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logger.error("检测到.env.dev文件不存在")
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shutil.copy(".env.prod", "./.env.dev")
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# 首先加载基础环境变量.env
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if os.path.exists(".env"):
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load_dotenv(".env")
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logger.success("成功加载基础环境变量配置")
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def load_env():
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# 使用闭包实现对加载器的横向扩展，避免大量重复判断
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def prod():
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@@ -70,7 +81,7 @@ def load_env():
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logger.info(f"[load_env] 当前的 ENVIRONMENT 变量值：{env}")
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if env in fn_map:
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fn_map[env]() # 根据映射执行闭包函数
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fn_map[env]() # 根据映射执行闭包函数
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elif os.path.exists(f".env.{env}"):
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logger.success(f"加载{env}环境变量配置")
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@@ -81,6 +92,17 @@ def load_env():
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RuntimeError(f"ENVIRONMENT 配置错误，请检查 .env 文件中的 ENVIRONMENT 变量及对应 .env.{env} 是否存在")
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def load_logger():
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logger.remove() # 移除默认配置
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logger.add(
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sys.stderr,
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format="<green>{time:YYYY-MM-DD HH:mm:ss.SSS}</green> <fg #777777>|</> <level>{level: <7}</level> <fg "
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"#777777>|</> <cyan>{name:.<8}</cyan>:<cyan>{function:.<8}</cyan>:<cyan>{line: >4}</cyan> <fg "
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"#777777>-</> <level>{message}</level>",
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colorize=True,
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level=os.getenv("LOG_LEVEL", "INFO") # 根据环境设置日志级别，默认为INFO
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)
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def scan_provider(env_config: dict):
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provider = {}
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@@ -115,6 +137,7 @@ def scan_provider(env_config: dict):
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)
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raise ValueError(f"请检查 '{provider_name}' 提供商配置是否丢失 BASE_URL 或 KEY 环境变量")
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if __name__ == "__main__":
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# 利用 TZ 环境变量设定程序工作的时区
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# 仅保证行为一致，不依赖 localtime()，实际对生产环境几乎没有作用
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@@ -122,6 +145,7 @@ if __name__ == "__main__":
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time.tzset()
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easter_egg()
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load_logger()
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init_config()
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init_env()
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load_env()
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@@ -1,6 +1,4 @@
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import asyncio
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import os
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import random
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import time
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from loguru import logger
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@@ -30,16 +28,15 @@ driver = get_driver()
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config = driver.config
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Database.initialize(
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host= config.MONGODB_HOST,
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port= int(config.MONGODB_PORT),
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db_name= config.DATABASE_NAME,
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username= config.MONGODB_USERNAME,
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password= config.MONGODB_PASSWORD,
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auth_source= config.MONGODB_AUTH_SOURCE
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host=config.MONGODB_HOST,
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port=int(config.MONGODB_PORT),
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db_name=config.DATABASE_NAME,
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username=config.MONGODB_USERNAME,
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password=config.MONGODB_PASSWORD,
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auth_source=config.MONGODB_AUTH_SOURCE
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)
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print("\033[1;32m[初始化数据库完成]\033[0m")
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# 导入其他模块
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from ..memory_system.memory import hippocampus, memory_graph
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from .bot import ChatBot
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@@ -59,24 +56,24 @@ group_msg = on_message(priority=5)
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scheduler = require("nonebot_plugin_apscheduler").scheduler
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@driver.on_startup
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async def start_background_tasks():
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"""启动后台任务"""
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# 启动LLM统计
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llm_stats.start()
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print("\033[1;32m[初始化]\033[0m LLM统计功能已启动")
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logger.success("[初始化]LLM统计功能已启动")
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# 初始化并启动情绪管理器
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mood_manager = MoodManager.get_instance()
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mood_manager.start_mood_update(update_interval=global_config.mood_update_interval)
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print("\033[1;32m[初始化]\033[0m 情绪管理器已启动")
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logger.success("[初始化]情绪管理器已启动")
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# 只启动表情包管理任务
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asyncio.create_task(emoji_manager.start_periodic_check(interval_MINS=global_config.EMOJI_CHECK_INTERVAL))
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await bot_schedule.initialize()
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bot_schedule.print_schedule()
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@driver.on_startup
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async def init_relationships():
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"""在 NoneBot2 启动时初始化关系管理器"""
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@@ -84,45 +81,52 @@ async def init_relationships():
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await relationship_manager.load_all_relationships()
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asyncio.create_task(relationship_manager._start_relationship_manager())
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@driver.on_bot_connect
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async def _(bot: Bot):
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"""Bot连接成功时的处理"""
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global _message_manager_started
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print(f"\033[1;38;5;208m-----------{global_config.BOT_NICKNAME}成功连接！-----------\033[0m")
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await willing_manager.ensure_started()
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message_sender.set_bot(bot)
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print("\033[1;38;5;208m-----------消息发送器已启动！-----------\033[0m")
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if not _message_manager_started:
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asyncio.create_task(message_manager.start_processor())
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_message_manager_started = True
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print("\033[1;38;5;208m-----------消息处理器已启动！-----------\033[0m")
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asyncio.create_task(emoji_manager._periodic_scan(interval_MINS=global_config.EMOJI_REGISTER_INTERVAL))
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print("\033[1;38;5;208m-----------开始偷表情包！-----------\033[0m")
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@group_msg.handle()
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async def _(bot: Bot, event: GroupMessageEvent, state: T_State):
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await chat_bot.handle_message(event, bot)
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# 添加build_memory定时任务
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@scheduler.scheduled_job("interval", seconds=global_config.build_memory_interval, id="build_memory")
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async def build_memory_task():
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"""每build_memory_interval秒执行一次记忆构建"""
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print("\033[1;32m[记忆构建]\033[0m -------------------------------------------开始构建记忆-------------------------------------------")
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print(
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"\033[1;32m[记忆构建]\033[0m -------------------------------------------开始构建记忆-------------------------------------------")
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start_time = time.time()
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await hippocampus.operation_build_memory(chat_size=20)
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end_time = time.time()
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print(f"\033[1;32m[记忆构建]\033[0m -------------------------------------------记忆构建完成：耗时: {end_time - start_time:.2f} 秒-------------------------------------------")
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@scheduler.scheduled_job("interval", seconds=global_config.forget_memory_interval, id="forget_memory")
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print(
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f"\033[1;32m[记忆构建]\033[0m -------------------------------------------记忆构建完成：耗时: {end_time - start_time:.2f} 秒-------------------------------------------")
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@scheduler.scheduled_job("interval", seconds=global_config.forget_memory_interval, id="forget_memory")
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async def forget_memory_task():
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"""每30秒执行一次记忆构建"""
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# print("\033[1;32m[记忆遗忘]\033[0m 开始遗忘记忆...")
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# await hippocampus.operation_forget_topic(percentage=0.1)
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# print("\033[1;32m[记忆遗忘]\033[0m 记忆遗忘完成")
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@scheduler.scheduled_job("interval", seconds=global_config.build_memory_interval + 10, id="merge_memory")
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async def merge_memory_task():
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"""每30秒执行一次记忆构建"""
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@@ -130,9 +134,9 @@ async def merge_memory_task():
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# await hippocampus.operation_merge_memory(percentage=0.1)
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# print("\033[1;32m[记忆整合]\033[0m 记忆整合完成")
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@scheduler.scheduled_job("interval", seconds=30, id="print_mood")
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async def print_mood_task():
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"""每30秒打印一次情绪状态"""
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mood_manager = MoodManager.get_instance()
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mood_manager.print_mood_status()
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@@ -6,45 +6,46 @@ import tomli
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from loguru import logger
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from packaging import version
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from packaging.version import Version, InvalidVersion
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from packaging.specifiers import SpecifierSet,InvalidSpecifier
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from packaging.specifiers import SpecifierSet, InvalidSpecifier
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@dataclass
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class BotConfig:
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"""机器人配置类"""
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"""机器人配置类"""
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INNER_VERSION: Version = None
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BOT_QQ: Optional[int] = 1
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BOT_NICKNAME: Optional[str] = None
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# 消息处理相关配置
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MIN_TEXT_LENGTH: int = 2 # 最小处理文本长度
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MAX_CONTEXT_SIZE: int = 15 # 上下文最大消息数
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emoji_chance: float = 0.2 # 发送表情包的基础概率
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ENABLE_PIC_TRANSLATE: bool = True # 是否启用图片翻译
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talk_allowed_groups = set()
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talk_frequency_down_groups = set()
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thinking_timeout: int = 100 # 思考时间
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response_willing_amplifier: float = 1.0 # 回复意愿放大系数
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response_interested_rate_amplifier: float = 1.0 # 回复兴趣度放大系数
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down_frequency_rate: float = 3.5 # 降低回复频率的群组回复意愿降低系数
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ban_user_id = set()
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build_memory_interval: int = 30 # 记忆构建间隔（秒）
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forget_memory_interval: int = 300 # 记忆遗忘间隔（秒）
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EMOJI_CHECK_INTERVAL: int = 120 # 表情包检查间隔（分钟）
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EMOJI_REGISTER_INTERVAL: int = 10 # 表情包注册间隔（分钟）
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EMOJI_SAVE: bool = True # 偷表情包
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EMOJI_CHECK: bool = False #是否开启过滤
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EMOJI_CHECK_PROMPT: str = "符合公序良俗" # 表情包过滤要求
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EMOJI_CHECK: bool = False # 是否开启过滤
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EMOJI_CHECK_PROMPT: str = "符合公序良俗" # 表情包过滤要求
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ban_words = set()
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max_response_length: int = 1024 # 最大回复长度
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# 模型配置
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llm_reasoning: Dict[str, str] = field(default_factory=lambda: {})
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llm_reasoning_minor: Dict[str, str] = field(default_factory=lambda: {})
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@@ -60,28 +61,29 @@ class BotConfig:
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MODEL_R1_PROBABILITY: float = 0.8 # R1模型概率
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MODEL_V3_PROBABILITY: float = 0.1 # V3模型概率
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MODEL_R1_DISTILL_PROBABILITY: float = 0.1 # R1蒸馏模型概率
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enable_advance_output: bool = False # 是否启用高级输出
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enable_kuuki_read: bool = True # 是否启用读空气功能
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mood_update_interval: float = 1.0 # 情绪更新间隔 单位秒
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mood_decay_rate: float = 0.95 # 情绪衰减率
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mood_intensity_factor: float = 0.7 # 情绪强度因子
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enable_kuuki_read: bool = True # 是否启用读空气功能
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keywords_reaction_rules = [] # 关键词回复规则
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mood_update_interval: float = 1.0 # 情绪更新间隔 单位秒
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mood_decay_rate: float = 0.95 # 情绪衰减率
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mood_intensity_factor: float = 0.7 # 情绪强度因子
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chinese_typo_enable=True # 是否启用中文错别字生成器
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chinese_typo_error_rate=0.03 # 单字替换概率
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chinese_typo_min_freq=7 # 最小字频阈值
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chinese_typo_tone_error_rate=0.2 # 声调错误概率
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chinese_typo_word_replace_rate=0.02 # 整词替换概率
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keywords_reaction_rules = [] # 关键词回复规则
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chinese_typo_enable = True # 是否启用中文错别字生成器
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chinese_typo_error_rate = 0.03 # 单字替换概率
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chinese_typo_min_freq = 7 # 最小字频阈值
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chinese_typo_tone_error_rate = 0.2 # 声调错误概率
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chinese_typo_word_replace_rate = 0.02 # 整词替换概率
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# 默认人设
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PROMPT_PERSONALITY=[
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PROMPT_PERSONALITY = [
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"曾经是一个学习地质的女大学生，现在学习心理学和脑科学，你会刷贴吧",
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"是一个女大学生，你有黑色头发，你会刷小红书",
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"是一个女大学生，你会刷b站，对ACG文化感兴趣"
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]
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PROMPT_SCHEDULE_GEN="一个曾经学习地质,现在学习心理学和脑科学的女大学生，喜欢刷qq，贴吧，知乎和小红书"
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PERSONALITY_1: float = 0.6 # 第一种人格概率
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@@ -99,7 +101,7 @@ class BotConfig:
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if not os.path.exists(config_dir):
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os.makedirs(config_dir)
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return config_dir
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@classmethod
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def convert_to_specifierset(cls, value: str) -> SpecifierSet:
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"""将 字符串 版本表达式转换成 SpecifierSet
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@@ -119,7 +121,7 @@ class BotConfig:
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exit(1)
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return converted
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@classmethod
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def get_config_version(cls, toml: dict) -> Version:
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"""提取配置文件的 SpecifierSet 版本数据
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@@ -131,14 +133,14 @@ class BotConfig:
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if 'inner' in toml:
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try:
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config_version : str = toml["inner"]["version"]
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config_version: str = toml["inner"]["version"]
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except KeyError as e:
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logger.error(f"配置文件中 inner 段 不存在 {e}, 这是错误的配置文件")
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raise KeyError(f"配置文件中 inner 段 不存在 {e}, 这是错误的配置文件")
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else:
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toml["inner"] = { "version": "0.0.0" }
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toml["inner"] = {"version": "0.0.0"}
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config_version = toml["inner"]["version"]
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try:
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ver = version.parse(config_version)
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except InvalidVersion as e:
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@@ -150,38 +152,38 @@ class BotConfig:
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raise InvalidVersion("配置文件中 inner段 的 version 键是错误的版本描述\n")
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return ver
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@classmethod
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def load_config(cls, config_path: str = None) -> "BotConfig":
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"""从TOML配置文件加载配置"""
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config = cls()
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def personality(parent: dict):
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personality_config=parent['personality']
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personality=personality_config.get('prompt_personality')
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personality_config = parent['personality']
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personality = personality_config.get('prompt_personality')
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if len(personality) >= 2:
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logger.info(f"载入自定义人格:{personality}")
|
||||
config.PROMPT_PERSONALITY=personality_config.get('prompt_personality',config.PROMPT_PERSONALITY)
|
||||
logger.info(f"载入自定义日程prompt:{personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)}")
|
||||
config.PROMPT_SCHEDULE_GEN=personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)
|
||||
|
||||
config.PROMPT_PERSONALITY = personality_config.get('prompt_personality', config.PROMPT_PERSONALITY)
|
||||
logger.info(f"载入自定义日程prompt:{personality_config.get('prompt_schedule', config.PROMPT_SCHEDULE_GEN)}")
|
||||
config.PROMPT_SCHEDULE_GEN = personality_config.get('prompt_schedule', config.PROMPT_SCHEDULE_GEN)
|
||||
|
||||
if config.INNER_VERSION in SpecifierSet(">=0.0.2"):
|
||||
config.PERSONALITY_1=personality_config.get('personality_1_probability',config.PERSONALITY_1)
|
||||
config.PERSONALITY_2=personality_config.get('personality_2_probability',config.PERSONALITY_2)
|
||||
config.PERSONALITY_3=personality_config.get('personality_3_probability',config.PERSONALITY_3)
|
||||
config.PERSONALITY_1 = personality_config.get('personality_1_probability', config.PERSONALITY_1)
|
||||
config.PERSONALITY_2 = personality_config.get('personality_2_probability', config.PERSONALITY_2)
|
||||
config.PERSONALITY_3 = personality_config.get('personality_3_probability', config.PERSONALITY_3)
|
||||
|
||||
def emoji(parent: dict):
|
||||
emoji_config = parent["emoji"]
|
||||
config.EMOJI_CHECK_INTERVAL = emoji_config.get("check_interval", config.EMOJI_CHECK_INTERVAL)
|
||||
config.EMOJI_REGISTER_INTERVAL = emoji_config.get("register_interval", config.EMOJI_REGISTER_INTERVAL)
|
||||
config.EMOJI_CHECK_PROMPT = emoji_config.get('check_prompt',config.EMOJI_CHECK_PROMPT)
|
||||
config.EMOJI_SAVE = emoji_config.get('auto_save',config.EMOJI_SAVE)
|
||||
config.EMOJI_CHECK = emoji_config.get('enable_check',config.EMOJI_CHECK)
|
||||
|
||||
config.EMOJI_CHECK_PROMPT = emoji_config.get('check_prompt', config.EMOJI_CHECK_PROMPT)
|
||||
config.EMOJI_SAVE = emoji_config.get('auto_save', config.EMOJI_SAVE)
|
||||
config.EMOJI_CHECK = emoji_config.get('enable_check', config.EMOJI_CHECK)
|
||||
|
||||
def cq_code(parent: dict):
|
||||
cq_code_config = parent["cq_code"]
|
||||
config.ENABLE_PIC_TRANSLATE = cq_code_config.get("enable_pic_translate", config.ENABLE_PIC_TRANSLATE)
|
||||
|
||||
|
||||
def bot(parent: dict):
|
||||
# 机器人基础配置
|
||||
bot_config = parent["bot"]
|
||||
@@ -193,12 +195,13 @@ class BotConfig:
|
||||
response_config = parent["response"]
|
||||
config.MODEL_R1_PROBABILITY = response_config.get("model_r1_probability", config.MODEL_R1_PROBABILITY)
|
||||
config.MODEL_V3_PROBABILITY = response_config.get("model_v3_probability", config.MODEL_V3_PROBABILITY)
|
||||
config.MODEL_R1_DISTILL_PROBABILITY = response_config.get("model_r1_distill_probability", config.MODEL_R1_DISTILL_PROBABILITY)
|
||||
config.MODEL_R1_DISTILL_PROBABILITY = response_config.get("model_r1_distill_probability",
|
||||
config.MODEL_R1_DISTILL_PROBABILITY)
|
||||
config.max_response_length = response_config.get("max_response_length", config.max_response_length)
|
||||
|
||||
|
||||
def model(parent: dict):
|
||||
# 加载模型配置
|
||||
model_config:dict = parent["model"]
|
||||
model_config: dict = parent["model"]
|
||||
|
||||
config_list = [
|
||||
"llm_reasoning",
|
||||
@@ -215,24 +218,24 @@ class BotConfig:
|
||||
|
||||
for item in config_list:
|
||||
if item in model_config:
|
||||
cfg_item:dict = model_config[item]
|
||||
cfg_item: dict = model_config[item]
|
||||
|
||||
# base_url 的例子： SILICONFLOW_BASE_URL
|
||||
# key 的例子： SILICONFLOW_KEY
|
||||
cfg_target = {
|
||||
"name" : "",
|
||||
"base_url" : "",
|
||||
"key" : "",
|
||||
"pri_in" : 0,
|
||||
"pri_out" : 0
|
||||
"name": "",
|
||||
"base_url": "",
|
||||
"key": "",
|
||||
"pri_in": 0,
|
||||
"pri_out": 0
|
||||
}
|
||||
|
||||
if config.INNER_VERSION in SpecifierSet("<=0.0.0"):
|
||||
cfg_target = cfg_item
|
||||
|
||||
elif config.INNER_VERSION in SpecifierSet(">=0.0.1"):
|
||||
stable_item = ["name","pri_in","pri_out"]
|
||||
pricing_item = ["pri_in","pri_out"]
|
||||
stable_item = ["name", "pri_in", "pri_out"]
|
||||
pricing_item = ["pri_in", "pri_out"]
|
||||
# 从配置中原始拷贝稳定字段
|
||||
for i in stable_item:
|
||||
# 如果 字段 属于计费项 且获取不到，那默认值是 0
|
||||
@@ -246,18 +249,16 @@ class BotConfig:
|
||||
logger.error(f"{item} 中的必要字段 {e} 不存在，请检查")
|
||||
raise KeyError(f"{item} 中的必要字段 {e} 不存在，请检查")
|
||||
|
||||
|
||||
provider = cfg_item.get("provider")
|
||||
if provider == None:
|
||||
logger.error(f"provider 字段在模型配置 {item} 中不存在，请检查")
|
||||
raise KeyError(f"provider 字段在模型配置 {item} 中不存在，请检查")
|
||||
|
||||
|
||||
cfg_target["base_url"] = f"{provider}_BASE_URL"
|
||||
cfg_target["key"] = f"{provider}_KEY"
|
||||
|
||||
|
||||
# 如果 列表中的项目在 model_config 中，利用反射来设置对应项目
|
||||
setattr(config,item,cfg_target)
|
||||
setattr(config, item, cfg_target)
|
||||
else:
|
||||
logger.error(f"模型 {item} 在config中不存在，请检查")
|
||||
raise KeyError(f"模型 {item} 在config中不存在，请检查")
|
||||
@@ -267,12 +268,14 @@ class BotConfig:
|
||||
config.MIN_TEXT_LENGTH = msg_config.get("min_text_length", config.MIN_TEXT_LENGTH)
|
||||
config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE)
|
||||
config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance)
|
||||
config.ban_words=msg_config.get("ban_words",config.ban_words)
|
||||
config.ban_words = msg_config.get("ban_words", config.ban_words)
|
||||
|
||||
if config.INNER_VERSION in SpecifierSet(">=0.0.2"):
|
||||
config.thinking_timeout = msg_config.get("thinking_timeout", config.thinking_timeout)
|
||||
config.response_willing_amplifier = msg_config.get("response_willing_amplifier", config.response_willing_amplifier)
|
||||
config.response_interested_rate_amplifier = msg_config.get("response_interested_rate_amplifier", config.response_interested_rate_amplifier)
|
||||
config.response_willing_amplifier = msg_config.get("response_willing_amplifier",
|
||||
config.response_willing_amplifier)
|
||||
config.response_interested_rate_amplifier = msg_config.get("response_interested_rate_amplifier",
|
||||
config.response_interested_rate_amplifier)
|
||||
config.down_frequency_rate = msg_config.get("down_frequency_rate", config.down_frequency_rate)
|
||||
|
||||
def memory(parent: dict):
|
||||
@@ -300,8 +303,10 @@ class BotConfig:
|
||||
config.chinese_typo_enable = chinese_typo_config.get("enable", config.chinese_typo_enable)
|
||||
config.chinese_typo_error_rate = chinese_typo_config.get("error_rate", config.chinese_typo_error_rate)
|
||||
config.chinese_typo_min_freq = chinese_typo_config.get("min_freq", config.chinese_typo_min_freq)
|
||||
config.chinese_typo_tone_error_rate = chinese_typo_config.get("tone_error_rate", config.chinese_typo_tone_error_rate)
|
||||
config.chinese_typo_word_replace_rate = chinese_typo_config.get("word_replace_rate", config.chinese_typo_word_replace_rate)
|
||||
config.chinese_typo_tone_error_rate = chinese_typo_config.get("tone_error_rate",
|
||||
config.chinese_typo_tone_error_rate)
|
||||
config.chinese_typo_word_replace_rate = chinese_typo_config.get("word_replace_rate",
|
||||
config.chinese_typo_word_replace_rate)
|
||||
|
||||
def groups(parent: dict):
|
||||
groups_config = parent["groups"]
|
||||
@@ -389,7 +394,7 @@ class BotConfig:
|
||||
except(tomli.TOMLDecodeError) as e:
|
||||
logger.critical(f"配置文件bot_config.toml填写有误，请检查第{e.lineno}行第{e.colno}处：{e.msg}")
|
||||
exit(1)
|
||||
|
||||
|
||||
# 获取配置文件版本
|
||||
config.INNER_VERSION = cls.get_config_version(toml_dict)
|
||||
|
||||
@@ -413,31 +418,32 @@ class BotConfig:
|
||||
f"当前程序仅支持以下版本范围: {group_specifierset}"
|
||||
)
|
||||
raise InvalidVersion(f"当前程序仅支持以下版本范围: {group_specifierset}")
|
||||
|
||||
|
||||
# 如果 necessary 项目存在，而且显式声明是 False，进入特殊处理
|
||||
elif "necessary" in include_configs[key] and include_configs[key].get("necessary") == False:
|
||||
# 通过 pass 处理的项虽然直接忽略也是可以的，但是为了不增加理解困难，依然需要在这里显式处理
|
||||
if key == "keywords_reaction":
|
||||
pass
|
||||
|
||||
|
||||
else:
|
||||
# 如果用户根本没有需要的配置项，提示缺少配置
|
||||
logger.error(f"配置文件中缺少必需的字段: '{key}'")
|
||||
raise KeyError(f"配置文件中缺少必需的字段: '{key}'")
|
||||
|
||||
logger.success(f"成功加载配置文件: {config_path}")
|
||||
|
||||
return config
|
||||
|
||||
|
||||
return config
|
||||
|
||||
|
||||
# 获取配置文件路径
|
||||
bot_config_floder_path = BotConfig.get_config_dir()
|
||||
print(f"正在品鉴配置文件目录: {bot_config_floder_path}")
|
||||
logger.debug(f"正在品鉴配置文件目录: {bot_config_floder_path}")
|
||||
|
||||
bot_config_path = os.path.join(bot_config_floder_path, "bot_config.toml")
|
||||
|
||||
if os.path.exists(bot_config_path):
|
||||
# 如果开发环境配置文件不存在，则使用默认配置文件
|
||||
print(f"异常的新鲜，异常的美味: {bot_config_path}")
|
||||
logger.debug(f"异常的新鲜，异常的美味: {bot_config_path}")
|
||||
logger.info("使用bot配置文件")
|
||||
else:
|
||||
# 配置文件不存在
|
||||
@@ -446,8 +452,6 @@ else:
|
||||
|
||||
global_config = BotConfig.load_config(config_path=bot_config_path)
|
||||
|
||||
|
||||
if not global_config.enable_advance_output:
|
||||
logger.remove()
|
||||
pass
|
||||
|
||||
|
||||
0
src/plugins/memory_system/__init__.py
Normal file
0
src/plugins/memory_system/__init__.py
Normal file
@@ -13,21 +13,21 @@ from ..models.utils_model import LLM_request
|
||||
driver = get_driver()
|
||||
config = driver.config
|
||||
|
||||
|
||||
Database.initialize(
|
||||
host= config.MONGODB_HOST,
|
||||
port= int(config.MONGODB_PORT),
|
||||
db_name= config.DATABASE_NAME,
|
||||
username= config.MONGODB_USERNAME,
|
||||
password= config.MONGODB_PASSWORD,
|
||||
auth_source=config.MONGODB_AUTH_SOURCE
|
||||
)
|
||||
host=config.MONGODB_HOST,
|
||||
port=int(config.MONGODB_PORT),
|
||||
db_name=config.DATABASE_NAME,
|
||||
username=config.MONGODB_USERNAME,
|
||||
password=config.MONGODB_PASSWORD,
|
||||
auth_source=config.MONGODB_AUTH_SOURCE
|
||||
)
|
||||
|
||||
|
||||
class ScheduleGenerator:
|
||||
def __init__(self):
|
||||
#根据global_config.llm_normal这一字典配置指定模型
|
||||
# 根据global_config.llm_normal这一字典配置指定模型
|
||||
# self.llm_scheduler = LLMModel(model = global_config.llm_normal,temperature=0.9)
|
||||
self.llm_scheduler = LLM_request(model = global_config.llm_normal,temperature=0.9)
|
||||
self.llm_scheduler = LLM_request(model=global_config.llm_normal, temperature=0.9)
|
||||
self.db = Database.get_instance()
|
||||
self.today_schedule_text = ""
|
||||
self.today_schedule = {}
|
||||
@@ -35,39 +35,41 @@ class ScheduleGenerator:
|
||||
self.tomorrow_schedule = {}
|
||||
self.yesterday_schedule_text = ""
|
||||
self.yesterday_schedule = {}
|
||||
|
||||
|
||||
async def initialize(self):
|
||||
today = datetime.datetime.now()
|
||||
tomorrow = datetime.datetime.now() + datetime.timedelta(days=1)
|
||||
yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
|
||||
|
||||
|
||||
self.today_schedule_text, self.today_schedule = await self.generate_daily_schedule(target_date=today)
|
||||
self.tomorrow_schedule_text, self.tomorrow_schedule = await self.generate_daily_schedule(target_date=tomorrow,read_only=True)
|
||||
self.yesterday_schedule_text, self.yesterday_schedule = await self.generate_daily_schedule(target_date=yesterday,read_only=True)
|
||||
|
||||
async def generate_daily_schedule(self, target_date: datetime.datetime = None,read_only:bool = False) -> Dict[str, str]:
|
||||
|
||||
self.tomorrow_schedule_text, self.tomorrow_schedule = await self.generate_daily_schedule(target_date=tomorrow,
|
||||
read_only=True)
|
||||
self.yesterday_schedule_text, self.yesterday_schedule = await self.generate_daily_schedule(
|
||||
target_date=yesterday, read_only=True)
|
||||
|
||||
async def generate_daily_schedule(self, target_date: datetime.datetime = None, read_only: bool = False) -> Dict[
|
||||
str, str]:
|
||||
|
||||
date_str = target_date.strftime("%Y-%m-%d")
|
||||
weekday = target_date.strftime("%A")
|
||||
|
||||
|
||||
schedule_text = str
|
||||
|
||||
|
||||
existing_schedule = self.db.db.schedule.find_one({"date": date_str})
|
||||
if existing_schedule:
|
||||
print(f"{date_str}的日程已存在:")
|
||||
logger.info(f"{date_str}的日程已存在:")
|
||||
schedule_text = existing_schedule["schedule"]
|
||||
# print(self.schedule_text)
|
||||
|
||||
elif read_only == False:
|
||||
print(f"{date_str}的日程不存在，准备生成新的日程。")
|
||||
prompt = f"""我是{global_config.BOT_NICKNAME}，{global_config.PROMPT_SCHEDULE_GEN}，请为我生成{date_str}（{weekday}）的日程安排，包括："""+\
|
||||
"""
|
||||
logger.info(f"{date_str}的日程不存在，准备生成新的日程。")
|
||||
prompt = f"""我是{global_config.BOT_NICKNAME}，{global_config.PROMPT_SCHEDULE_GEN}，请为我生成{date_str}（{weekday}）的日程安排，包括：""" + \
|
||||
"""
|
||||
1. 早上的学习和工作安排
|
||||
2. 下午的活动和任务
|
||||
3. 晚上的计划和休息时间
|
||||
请按照时间顺序列出具体时间点和对应的活动，用一个时间点而不是时间段来表示时间，用JSON格式返回日程表，仅返回内容，不要返回注释，时间采用24小时制，格式为{"时间": "活动","时间": "活动",...}。"""
|
||||
|
||||
|
||||
try:
|
||||
schedule_text, _ = await self.llm_scheduler.generate_response(prompt)
|
||||
self.db.db.schedule.insert_one({"date": date_str, "schedule": schedule_text})
|
||||
@@ -76,36 +78,35 @@ class ScheduleGenerator:
|
||||
schedule_text = "生成日程时出错了"
|
||||
# print(self.schedule_text)
|
||||
else:
|
||||
print(f"{date_str}的日程不存在。")
|
||||
logger.info(f"{date_str}的日程不存在。")
|
||||
schedule_text = "忘了"
|
||||
|
||||
return schedule_text,None
|
||||
|
||||
return schedule_text, None
|
||||
|
||||
schedule_form = self._parse_schedule(schedule_text)
|
||||
return schedule_text,schedule_form
|
||||
|
||||
return schedule_text, schedule_form
|
||||
|
||||
def _parse_schedule(self, schedule_text: str) -> Union[bool, Dict[str, str]]:
|
||||
"""解析日程文本，转换为时间和活动的字典"""
|
||||
try:
|
||||
try:
|
||||
schedule_dict = json.loads(schedule_text)
|
||||
return schedule_dict
|
||||
except json.JSONDecodeError as e:
|
||||
print(schedule_text)
|
||||
print(f"解析日程失败: {str(e)}")
|
||||
logger.exception("解析日程失败: {}".format(schedule_text))
|
||||
return False
|
||||
|
||||
|
||||
def _parse_time(self, time_str: str) -> str:
|
||||
"""解析时间字符串，转换为时间"""
|
||||
return datetime.datetime.strptime(time_str, "%H:%M")
|
||||
|
||||
|
||||
def get_current_task(self) -> str:
|
||||
"""获取当前时间应该进行的任务"""
|
||||
current_time = datetime.datetime.now().strftime("%H:%M")
|
||||
|
||||
|
||||
# 找到最接近当前时间的任务
|
||||
closest_time = None
|
||||
min_diff = float('inf')
|
||||
|
||||
|
||||
# 检查今天的日程
|
||||
if not self.today_schedule:
|
||||
return "摸鱼"
|
||||
@@ -114,7 +115,7 @@ class ScheduleGenerator:
|
||||
if closest_time is None or diff < min_diff:
|
||||
closest_time = time_str
|
||||
min_diff = diff
|
||||
|
||||
|
||||
# 检查昨天的日程中的晚间任务
|
||||
if self.yesterday_schedule:
|
||||
for time_str in self.yesterday_schedule.keys():
|
||||
@@ -125,17 +126,17 @@ class ScheduleGenerator:
|
||||
closest_time = time_str
|
||||
min_diff = diff
|
||||
return closest_time, self.yesterday_schedule[closest_time]
|
||||
|
||||
|
||||
if closest_time:
|
||||
return closest_time, self.today_schedule[closest_time]
|
||||
return "摸鱼"
|
||||
|
||||
|
||||
def _time_diff(self, time1: str, time2: str) -> int:
|
||||
"""计算两个时间字符串之间的分钟差"""
|
||||
if time1=="24:00":
|
||||
time1="23:59"
|
||||
if time2=="24:00":
|
||||
time2="23:59"
|
||||
if time1 == "24:00":
|
||||
time1 = "23:59"
|
||||
if time2 == "24:00":
|
||||
time2 = "23:59"
|
||||
t1 = datetime.datetime.strptime(time1, "%H:%M")
|
||||
t2 = datetime.datetime.strptime(time2, "%H:%M")
|
||||
diff = int((t2 - t1).total_seconds() / 60)
|
||||
@@ -146,17 +147,18 @@ class ScheduleGenerator:
|
||||
diff -= 1440 # 减一天的分钟
|
||||
# print(f"时间1[{time1}]: 时间2[{time2}]，差值[{diff}]分钟")
|
||||
return diff
|
||||
|
||||
|
||||
def print_schedule(self):
|
||||
"""打印完整的日程安排"""
|
||||
if not self._parse_schedule(self.today_schedule_text):
|
||||
print("今日日程有误，将在下次运行时重新生成")
|
||||
logger.warning("今日日程有误，将在下次运行时重新生成")
|
||||
self.db.db.schedule.delete_one({"date": datetime.datetime.now().strftime("%Y-%m-%d")})
|
||||
else:
|
||||
print("\n=== 今日日程安排 ===")
|
||||
logger.info("\n=== 今日日程安排 ===")
|
||||
for time_str, activity in self.today_schedule.items():
|
||||
print(f"时间[{time_str}]: 活动[{activity}]")
|
||||
print("==================\n")
|
||||
logger.info(f"时间[{time_str}]: 活动[{activity}]")
|
||||
logger.info("==================\n")
|
||||
|
||||
|
||||
# def main():
|
||||
# # 使用示例
|
||||
@@ -165,7 +167,7 @@ class ScheduleGenerator:
|
||||
# scheduler.print_schedule()
|
||||
# print("\n当前任务：")
|
||||
# print(scheduler.get_current_task())
|
||||
|
||||
|
||||
# print("昨天日程：")
|
||||
# print(scheduler.yesterday_schedule)
|
||||
# print("今天日程：")
|
||||
@@ -175,5 +177,5 @@ class ScheduleGenerator:
|
||||
|
||||
# if __name__ == "__main__":
|
||||
# main()
|
||||
|
||||
|
||||
bot_schedule = ScheduleGenerator()
|
||||
|
||||
Reference in New Issue
Block a user