2a54650a6f
- 新增表情资产表，支持表情文件落盘后的资产沉淀、查询与发送时间回写 - 将表情下载从消息主链路中移出，改为后台定时批处理，降低同步入库阻塞风险 - 抽取通用 CDN 下载与 base64 落盘能力，统一图片与表情文件处理方式 - 在后台通讯录聊天窗口增加表情资产面板，支持查看资产并直接选择发送表情 - 新增后台表情资产接口，支持按群过滤最近表情素材 - 优化消息列表中的表情消息展示，支持在后台直接预览表情图片 - 启动时不再同步补偿历史表情，统一交由定时任务处理，避免影响系统稳定性 - 新增群总结落库表，支持将每日总结写入数据库，便于后续知识库提取与复用 - 将定时总结结果写入数据库，保留总结文本、周期信息、消息数量和元数据
162 lines
5.1 KiB
Python
162 lines
5.1 KiB
Python
#! /usr/bin/env python3
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# -*- coding: utf-8 -*-
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import asyncio
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import threading
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from admin.GlancesMonitor import GlancesMonitor
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from utils.decorator.async_job import async_job
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from configuration import Config
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from plugins.xiuren_image.images_cache import ImageCacheManager
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from robot import Robot
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from loguru import logger
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from utils.sehuatang.sehuatang_bot import SehuatangCrawler
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# INFO 日志（包含 INFO、DEBUG，但不包含 WARNING、ERROR）
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logger.add(
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f"logs/wx_info.log",
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level="INFO",
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filter=lambda record: record["level"].name in ["INFO", "DEBUG"],
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rotation="10 MB",
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retention="7 days",
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encoding="utf-8"
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)
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# ERROR 日志（仅 ERROR 及以上）
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logger.add(
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f"logs/wx_error.log",
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level="ERROR",
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rotation="10 MB",
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retention="7 days",
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encoding="utf-8"
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)
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# ERROR 日志（仅 ERROR 及以上）
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logger.add(
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f"logs/wx_debug.log",
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level="DEBUG",
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rotation="10 MB",
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retention="7 days",
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encoding="utf-8"
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)
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def main():
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config = Config()
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# 创建机器人实例
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robot = Robot(config)
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robot.LOG.info(f"ABOT服务 正在启动...")
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# 初始化并启动wechat_ipad客户端
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if robot.init_wechat_ipad():
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robot.LOG.info("wechat_ipad客户端启动成功")
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else:
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robot.LOG.error("wechat_ipad客户端启动失败")
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# 注册定时任务
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jobs(robot)
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# 启动Dashboard服务器
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try:
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# 创建Dashboard服务器实例，共享robot对象
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from admin.dashboard.server import DashboardServer
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dashboard_server = DashboardServer(robot_instance=robot)
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# 在单独的线程中启动Dashboard服务器
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dashboard_thread = threading.Thread(target=dashboard_server.run, daemon=True)
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dashboard_thread.start()
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robot.LOG.info(f"Dashboard服务器已在 http://{dashboard_server.host}:{dashboard_server.port} 启动")
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except Exception as e:
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robot.LOG.error(f"Dashboard服务器启动失败: {e}")
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try:
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robot.LOG.debug(f"开始启动GlancesMonitor")
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# 初始化 Glances 监控
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monitor = GlancesMonitor(
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email_sender=robot.email_sender,
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host=config.glances.get("host"),
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port=config.glances.get("port"),
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cpu_threshold=80.0,
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load_threshold=16, # 自动设为 CPU 核心数 * 2
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io_threshold=100.0,
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disk_usage_threshold=70.0,
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handle_threshold=20000,
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recipient=config.email.get("alert_recipient")
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)
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monitor.run()
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except Exception as e:
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robot.LOG.error(f"GlancesMonitor服务器启动失败: {e}")
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robot.LOG.info(f"=" * 50)
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asyncio.run(async_job.run_all())
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# 让机器人一直跑
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robot.keep_running_and_block_process()
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def jobs(robot: Robot):
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# ✅ 每天 8:30 发送百度新闻
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@async_job.at_times(["08:30"])
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async def news_baidu_report_auto_job():
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await robot.news_baidu_report_auto()
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# ✅ 每天 10:30 推送 Epic 免费游戏
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@async_job.every_weekday_time(weekday=4, time_str="10:00") # 0=周一，4=周五
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async def epic_job():
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await robot.send_epic_free_games()
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# ✅ 每天 02:30 从 redis 写入 sqlite
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@async_job.at_times(["02:30"])
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async def msg_count_to_db_job():
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await robot.message_count_to_db()
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# ✅ 每天 09:30 从 sqlite 读取并发送群排行
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@async_job.at_times(["09:30"])
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async def msg_ranking_job():
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await robot.generate_and_send_ranking()
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# ✅ 每天 15:30 发涩图 PDF
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@async_job.at_times(["15:30"])
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async def sehuatang_pdf_job():
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await robot.generate_sehuatang_pdf()
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# ✅ 每天 01:30 下载秀人网帖子
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@async_job.at_times(["01:30"])
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async def xiuren_download_job():
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await robot.xiu_ren_download_task()
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# ✅ 每天 01:30 下载秀人网帖子
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@async_job.at_times(["2:30"])
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async def shenshiR15_download_job():
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await robot.shen_shi_download_task()
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# ✅ 每天 17:30 发秀人 PDF（如果启用）
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# @async_job.at_times(["17:30"])
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# async def xiuren_pdf_send_job():
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# await robot.xiu_ren_pdf_send()
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# ✅ 每 3 小时登录验证
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@async_job.at_times(["14:43"])
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async def login_check_job():
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await robot.login_twice_auto_auth()
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@async_job.at_times(["05:00"])
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async def update_image_cache_job():
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logger.info("开始执行图片缓存更新任务")
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manager = ImageCacheManager("/mnt/nfs_share") # 替换为你的图片目录
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await manager.update_image_cache()
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logger.info("图片缓存更新完成")
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# ✅ 每2分钟处理一次待下载的图片消息（串行处理，避免数据库锁竞争）
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@async_job.every_minutes(5)
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async def process_pending_images_job():
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if hasattr(robot, 'message_storage') and robot.message_storage:
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await robot.message_storage.process_pending_images(minutes_ago=10, batch_size=20)
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@async_job.every_minutes(5)
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async def process_pending_emojis_job():
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if hasattr(robot, 'message_storage') and robot.message_storage:
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await robot.message_storage.process_pending_emojis(minutes_ago=60 * 24 * 7, batch_size=30)
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if __name__ == "__main__":
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main()
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