# 此模块提供了消息处理的具体逻辑的接口 import asyncio import time import mirai import logging from mirai import MessageChain, Plain # 这里不使用动态引入config # 因为在这里动态引入会卡死程序 # 而此模块静态引用config与动态引入的表现一致 # 已弃用,由于超时时间现已动态使用 # import config as config_init_import import pkg.openai.session import pkg.openai.manager import pkg.utils.reloader import pkg.utils.updater import pkg.utils.context import pkg.qqbot.message import pkg.qqbot.command import pkg.qqbot.ratelimit as ratelimit import pkg.plugin.host as plugin_host import pkg.plugin.models as plugin_models import pkg.qqbot.ignore as ignore import pkg.qqbot.banlist as banlist import pkg.qqbot.blob as blob processing = [] def is_admin(qq: int) -> bool: """兼容list和int类型的管理员判断""" import config if type(config.admin_qq) == list: return qq in config.admin_qq else: return qq == config.admin_qq def process_message(launcher_type: str, launcher_id: int, text_message: str, message_chain: MessageChain, sender_id: int) -> MessageChain: global processing mgr = pkg.utils.context.get_qqbot_manager() reply = [] session_name = "{}_{}".format(launcher_type, launcher_id) # 检查发送方是否被禁用 if banlist.is_banned(launcher_type, launcher_id, sender_id): logging.info("根据禁用列表忽略{}_{}的消息".format(launcher_type, launcher_id)) return [] if ignore.ignore(text_message): logging.info("根据忽略规则忽略消息: {}".format(text_message)) return [] # 检查是否被禁言 if launcher_type == 'group': result = mgr.bot.member_info(target=launcher_id, member_id=mgr.bot.qq).get() result = asyncio.run(result) if result.mute_time_remaining > 0: logging.info("机器人被禁言,跳过消息处理(group_{},剩余{}s)".format(launcher_id, result.mute_time_remaining)) return reply import config if hasattr(config, 'income_msg_check') and config.income_msg_check: if mgr.reply_filter.is_illegal(text_message): return MessageChain(Plain("[bot] 你的提问中有不合适的内容, 请更换措辞~")) pkg.openai.session.get_session(session_name).acquire_response_lock() text_message = text_message.strip() # 处理消息 try: if session_name in processing: pkg.openai.session.get_session(session_name).release_response_lock() return MessageChain([Plain("[bot]err:正在处理中,请稍后再试")]) config = pkg.utils.context.get_config() processing.append(session_name) try: if text_message.startswith('!') or text_message.startswith("!"): # 指令 # 触发插件事件 args = { 'launcher_type': launcher_type, 'launcher_id': launcher_id, 'sender_id': sender_id, 'command': text_message[1:].strip().split(' ')[0], 'params': text_message[1:].strip().split(' ')[1:], 'text_message': text_message, 'is_admin': is_admin(sender_id), } event = plugin_host.emit(plugin_models.PersonCommandSent if launcher_type == 'person' else plugin_models.GroupCommandSent, **args) if event.get_return_value("alter") is not None: text_message = event.get_return_value("alter") # 取出插件提交的返回值赋值给reply if event.get_return_value("reply") is not None: reply = event.get_return_value("reply") if not event.is_prevented_default(): reply = pkg.qqbot.command.process_command(session_name, text_message, mgr, config, launcher_type, launcher_id, sender_id, is_admin(sender_id)) else: # 消息 # 限速丢弃检查 # print(ratelimit.__crt_minute_usage__[session_name]) if hasattr(config, "rate_limitation") and config.rate_limit_strategy == "drop": if ratelimit.is_reach_limit(session_name): logging.info("根据限速策略丢弃[{}]消息: {}".format(session_name, text_message)) return MessageChain(["[bot]"+config.rate_limit_drop_tip]) if hasattr(config, "rate_limit_drop_tip") and config.rate_limit_drop_tip != "" else [] before = time.time() # 触发插件事件 args = { "launcher_type": launcher_type, "launcher_id": launcher_id, "sender_id": sender_id, "text_message": text_message, } event = plugin_host.emit(plugin_models.PersonNormalMessageReceived if launcher_type == 'person' else plugin_models.GroupNormalMessageReceived, **args) if event.get_return_value("alter") is not None: text_message = event.get_return_value("alter") # 取出插件提交的返回值赋值给reply if event.get_return_value("reply") is not None: reply = event.get_return_value("reply") if not event.is_prevented_default(): reply = pkg.qqbot.message.process_normal_message(text_message, mgr, config, launcher_type, launcher_id, sender_id) # 限速等待时间 if hasattr(config, "rate_limitation") and config.rate_limit_strategy == "wait": time.sleep(ratelimit.get_rest_wait_time(session_name, time.time() - before)) if hasattr(config, "rate_limitation"): ratelimit.add_usage(session_name) if reply is not None and len(reply) > 0 and (type(reply[0]) == str or type(reply[0]) == mirai.Plain): if type(reply[0]) == mirai.Plain: reply[0] = reply[0].text logging.info( "回复[{}]文字消息:{}".format(session_name, reply[0][:min(100, len(reply[0]))] + ( "..." if len(reply[0]) > 100 else ""))) reply = [mgr.reply_filter.process(reply[0])] reply = blob.check_text(reply[0]) else: logging.info("回复[{}]消息".format(session_name)) finally: processing.remove(session_name) finally: pkg.openai.session.get_session(session_name).release_response_lock() return MessageChain(reply)