"""
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消息处理核心逻辑
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"""
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import json
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import time
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import re
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import xml.etree.ElementTree as ET
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from typing import Dict, Any, Optional, List, Tuple
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from datetime import datetime
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from sqlalchemy.orm import Session
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from loguru import logger
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from app.models.database import get_db
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from app.models.contact import Contact
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from app.models.conversation import Conversation
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from app.services.redis_queue import redis_queue
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from app.services.ecloud_client import ecloud_client
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from app.services.dify_client import dify_client
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from app.services.friend_ignore_service import friend_ignore_service
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from app.services.silence_service import silence_service
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from app.services.group_stats_service import group_stats_service
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from config import settings
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class MessageProcessor:
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"""消息处理器"""
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def __init__(self):
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pass
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def extract_refer_message_content(self, callback_data: Dict[str, Any]) -> str:
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"""
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提取引用消息的内容（message_type为80014）
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Args:
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callback_data: 回调数据
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Returns:
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组合后的消息内容（content + title，中间空一行）
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"""
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try:
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data = callback_data.get("data", {})
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content = data.get("content", "")
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title = data.get("title", "")
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# 解析XML内容，提取msg>appmsg>refermsg>content标签中的内容
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refer_content = ""
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xml_title = ""
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try:
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# 解析XML
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root = ET.fromstring(content)
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# 查找msg>appmsg>refermsg>content路径
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appmsg = root.find("appmsg")
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if appmsg is not None:
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# 提取XML中的title（如果存在）
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title_element = appmsg.find("title")
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if title_element is not None and title_element.text:
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xml_title = title_element.text.strip()
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# 提取引用消息内容
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refermsg = appmsg.find("refermsg")
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if refermsg is not None:
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content_element = refermsg.find("content")
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if content_element is not None and content_element.text:
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refer_content = content_element.text.strip()
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except ET.ParseError as e:
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logger.warning(f"XML解析失败: {str(e)}, content={content}")
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# 如果XML解析失败，使用原始content
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refer_content = content
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# 确定最终使用的title：优先使用XML中的title，其次使用data.title
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final_title = xml_title if xml_title else title
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# 组合内容：refer_content在前，final_title在后，中间空一行
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if refer_content and final_title:
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combined_content = f"{refer_content}\n\n{final_title}"
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elif refer_content:
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combined_content = refer_content
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elif final_title:
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combined_content = final_title
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else:
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combined_content = content # 如果都没有，使用原始content
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logger.info(f"引用消息内容提取完成: refer_content_length={len(refer_content)}, xml_title_length={len(xml_title)}, data_title_length={len(title)}, final_title_length={len(final_title)}")
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return combined_content
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except Exception as e:
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logger.error(f"提取引用消息内容异常: error={str(e)}")
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# 异常情况下返回原始content
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return callback_data.get("data", {}).get("content", "")
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def parse_at_mentions(self, ai_answer: str) -> Tuple[str, List[str]]:
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"""
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解析AI回复中的@字符，提取客服名称
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Args:
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ai_answer: AI回复内容
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Returns:
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(处理后的消息内容, 需要@的客服wcid列表)
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"""
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try:
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# 获取配置的客服名称列表
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customer_service_names = settings.customer_service_names
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# 查找所有@字符后的客服名称
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at_pattern = r'@([^\s]+)'
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matches = re.findall(at_pattern, ai_answer)
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valid_at_names = []
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at_wc_ids = []
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for match in matches:
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# 检查是否在配置的客服名称列表中
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if match in customer_service_names:
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valid_at_names.append(match)
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logger.info(f"发现有效的@客服名称: {match}")
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# 如果有有效的@客服名称，查询数据库获取wcid
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if valid_at_names:
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with next(get_db()) as db:
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for name in valid_at_names:
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# 根据nick_name查找联系人
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contact = db.query(Contact).filter(Contact.nick_name == name).first()
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if contact:
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at_wc_ids.append(contact.wc_id)
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logger.info(f"找到客服联系人: name={name}, wc_id={contact.wc_id}")
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else:
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logger.warning(f"未找到客服联系人: name={name}")
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return ai_answer, at_wc_ids
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except Exception as e:
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logger.error(f"解析@字符异常: error={str(e)}")
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return ai_answer, []
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def is_valid_group_message(self, callback_data: Dict[str, Any]) -> bool:
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"""
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检查是否是有效的群聊消息
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Args:
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callback_data: 回调数据
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Returns:
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是否是有效的群聊消息
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"""
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# 检查消息类型是否是群聊消息（80001）或引用消息（80014）
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message_type = callback_data.get("messageType")
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print(f"data: {callback_data}")
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if message_type not in ["80001", "80014"]:
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logger.info(f"忽略非群聊消息: messageType={message_type}")
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return False
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# 检查是否是自己发送的消息
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data = callback_data.get("data", {})
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if data.get("self", False):
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logger.info(f"忽略自己发送的消息: fromUser={data.get('fromUser')}")
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return False
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# 检查必要字段
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if (
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not data.get("fromUser")
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or not data.get("fromGroup")
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or not data.get("content")
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):
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logger.warning(f"消息缺少必要字段: data={data}")
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return False
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# 获取用户和群组信息
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from_user = data.get("fromUser")
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from_group = data.get("fromGroup")
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# 检查发送者是否在好友忽略列表中
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is_friend_ignored = friend_ignore_service.is_friend_ignored(from_user)
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if is_friend_ignored:
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logger.info(f"忽略好友发送的消息: fromUser={from_user}, fromGroup={from_group}")
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# 统计被忽略的好友发言次数（确保被忽略的好友消息也纳入统计）
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group_stats_service.increment_user_message_count(from_group, from_user)
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# 激活或延长该群组的静默模式
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if silence_service.is_silence_active(from_group):
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# 如果该群组静默模式已激活，延长时间
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silence_service.extend_silence_mode(from_group)
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logger.info(f"好友消息被忽略，群组静默模式时间已刷新: fromUser={from_user}, fromGroup={from_group}")
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else:
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# 如果该群组静默模式未激活，激活静默模式
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silence_service.activate_silence_mode(from_group)
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logger.info(f"好友消息被忽略，群组静默模式已激活: fromUser={from_user}, fromGroup={from_group}")
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return False
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# # 统计正常处理的好友发言次数
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# group_stats_service.increment_user_message_count(from_group, from_user)
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# 检查该群组的静默模式是否激活（在好友忽略检查之后）
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if silence_service.is_silence_active(from_group):
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logger.info(f"群组静默模式激活中，忽略消息: fromGroup={from_group}")
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return False
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return True
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def enqueue_callback_message(self, callback_data: Dict[str, Any]) -> bool:
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"""
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将回调消息加入队列
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Args:
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callback_data: 回调数据
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Returns:
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是否成功加入队列
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"""
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# 验证消息有效性
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if not self.is_valid_group_message(callback_data):
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return False
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# 导入消息聚合服务（延迟导入避免循环依赖）
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from app.services.message_aggregator import message_aggregator
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# 尝试将消息添加到聚合中
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should_process_immediately, aggregated_data = message_aggregator.add_message_to_aggregation(callback_data)
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if should_process_immediately:
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# 需要立即处理（不聚合或聚合超时）
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data = aggregated_data.get("data", {}) if aggregated_data else callback_data.get("data", {})
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from_user = data.get("fromUser")
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# 将消息加入Redis队列
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return redis_queue.enqueue_message(from_user, aggregated_data or callback_data)
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else:
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# 消息已被聚合，不需要立即处理
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logger.info(f"消息已添加到聚合队列，等待聚合处理: fromUser={callback_data.get('data', {}).get('fromUser')}")
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return True
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def ensure_contact_exists(self, from_group: str, w_id: str, db: Session) -> bool:
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"""
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确保联系人信息存在于数据库中
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Args:
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from_group: 群组ID
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w_id: 登录实例标识
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db: 数据库会话
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Returns:
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是否成功确保联系人存在
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"""
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try:
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# 检查数据库中是否已存在该联系人
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existing_contact = (
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db.query(Contact).filter(Contact.wc_id == from_group).first()
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)
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if existing_contact:
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logger.info(f"联系人已存在: wc_id={from_group}")
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return True
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# 调用E云管家API获取联系人信息
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contact_info = ecloud_client.get_contact_info(w_id, from_group)
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if not contact_info:
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logger.error(f"无法获取联系人信息: wc_id={from_group}")
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return False
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# 保存联系人信息到数据库
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new_contact = Contact(
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wc_id=from_group,
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user_name=contact_info.get("userName"),
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nick_name=contact_info.get("nickName"),
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remark=contact_info.get("remark"),
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signature=contact_info.get("signature"),
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sex=contact_info.get("sex"),
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alias_name=contact_info.get("aliasName"),
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country=contact_info.get("country"),
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big_head=contact_info.get("bigHead"),
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small_head=contact_info.get("smallHead"),
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label_list=contact_info.get("labelList"),
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v1=contact_info.get("v1"),
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)
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db.add(new_contact)
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db.commit()
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logger.info(
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f"成功保存联系人信息: wc_id={from_group}, nick_name={contact_info.get('nickName')}"
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)
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return True
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except Exception as e:
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logger.error(f"确保联系人存在失败: wc_id={from_group}, error={str(e)}")
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db.rollback()
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return False
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def process_single_message(self, message_data: Dict[str, Any]) -> bool:
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"""
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处理单条消息
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Args:
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message_data: 消息数据
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Returns:
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是否处理成功
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"""
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try:
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data = message_data.get("data", {})
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from_user = data.get("fromUser")
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from_group = data.get("fromGroup")
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content = data.get("content")
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w_id = data.get("wId")
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message_type = message_data.get("messageType")
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logger.info(f"开始处理消息: from_user={from_user}, from_group={from_group}, message_type={message_type}")
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# 根据消息类型处理内容
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if message_type == "80014":
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# 引用消息，需要提取XML中的内容并与title组合
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content = self.extract_refer_message_content(message_data)
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logger.info(f"引用消息内容处理完成: content_length={len(content)}")
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# 使用上下文管理器确保数据库会话正确管理
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with next(get_db()) as db:
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# 3.1 确保联系人信息存在
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if not self.ensure_contact_exists(from_group, w_id, db):
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logger.error(f"联系人信息处理失败: from_group={from_group}")
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return False
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# 3.2 获取群组中发言次数最多的用户昵称
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most_active_nickname = group_stats_service.get_most_active_user_nickname(from_group)
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logger.info(f"群组最活跃用户昵称: group={from_group}, nickname={most_active_nickname}")
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# 3.3 获取用户在当前群组的conversation_id
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conversation_id = redis_queue.get_conversation_id(from_user, from_group)
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# 调用Dify接口发送消息（根据配置选择模式）
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dify_response = dify_client.send_message(
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query=content,
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user=from_user,
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conversation_id=conversation_id,
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nick_name=most_active_nickname
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)
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if not dify_response:
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logger.error(f"Dify响应失败: from_user={from_user}")
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return False
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# 获取AI回答和新的conversation_id
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ai_answer = dify_response.get("answer", "")
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new_conversation_id = dify_response.get("conversation_id", "")
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# 更新Redis中的conversation_id（基于用户+群组）
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if new_conversation_id:
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redis_queue.set_conversation_id(from_user, new_conversation_id, from_group, 1800)
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# 3.4 保存对话记录到数据库
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# 按用户、群组和小时分组对话记录
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current_time = datetime.now()
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hour_key = current_time.strftime("%Y%m%d_%H")
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# 查找当前用户在当前群组当前小时的对话记录
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existing_conversation = (
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db.query(Conversation)
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.filter(
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Conversation.from_user == from_user,
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Conversation.conversation_id == new_conversation_id,
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Conversation.group == from_group,
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Conversation.hour == hour_key
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)
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.first()
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)
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if existing_conversation:
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# 更新现有记录 - 使用JSON格式追加对话内容（当前用户在当前群组当前小时的对话）
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try:
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# 解析现有的content JSON
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if existing_conversation.content:
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content_list = json.loads(existing_conversation.content)
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else:
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content_list = []
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# 追加新的对话内容
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content_list.append({
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"user": content,
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"ai": ai_answer
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})
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# 更新记录
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existing_conversation.content = json.dumps(content_list, ensure_ascii=False)
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existing_conversation.is_processed = True
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logger.info(f"追加到当前用户群组小时对话记录: user={from_user}, group={from_group}, hour={hour_key}, 对话轮次={len(content_list)}")
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except json.JSONDecodeError as e:
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logger.error(f"解析现有对话内容JSON失败: {str(e)}, 重新创建")
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# 如果JSON解析失败，重新创建content
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content_list = [{"user": content, "ai": ai_answer}]
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existing_conversation.content = json.dumps(content_list, ensure_ascii=False)
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existing_conversation.is_processed = True
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else:
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# 创建新记录 - 新的用户群组小时对话或首次对话，使用JSON格式存储对话内容
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content_list = [{"user": content, "ai": ai_answer}]
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new_conversation = Conversation(
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from_user=from_user,
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conversation_id=new_conversation_id,
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group=from_group,
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hour=hour_key,
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content=json.dumps(content_list, ensure_ascii=False),
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is_processed=True,
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)
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db.add(new_conversation)
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logger.info(f"创建新的用户群组小时对话记录: user={from_user}, group={from_group}, hour={hour_key}, 初始对话轮次=1")
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db.commit()
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# 发送AI回答到群聊
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success = False
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if ai_answer:
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# 解析AI回复中的@字符
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processed_answer, at_wc_ids = self.parse_at_mentions(ai_answer)
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# 发送消息，最多重试3次
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for attempt in range(3):
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if at_wc_ids:
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# 如果有@客服，使用群聊@接口
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logger.info(f"使用群聊@接口发送消息: at_wc_ids={at_wc_ids}")
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if ecloud_client.send_group_at_message(
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w_id, from_group, processed_answer, at_wc_ids
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):
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success = True
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break
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else:
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# 普通群聊消息
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logger.info("使用普通群聊接口发送消息")
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if ecloud_client.send_group_message(
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w_id, from_group, processed_answer
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):
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success = True
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break
|
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logger.warning(f"发送AI回答失败，尝试重试 ({attempt + 1}/3): from_user={from_user}")
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if attempt < 2: # 不是最后一次尝试，等待一段时间再重试
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time.sleep(2 ** attempt) # 指数退避
|
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if success:
|
# 更新发送状态
|
conversation = (
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db.query(Conversation)
|
.filter(
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Conversation.from_user == from_user,
|
Conversation.conversation_id == new_conversation_id,
|
Conversation.group == from_group,
|
Conversation.hour == hour_key
|
)
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.first()
|
)
|
if conversation:
|
conversation.is_sent = True
|
conversation.sent_time = current_time
|
db.commit()
|
|
logger.info(f"消息处理完成: from_user={from_user}")
|
return True
|
else:
|
logger.error(f"发送AI回答失败: from_user={from_user}")
|
return False
|
|
except Exception as e:
|
logger.error(f"处理消息异常: from_user={from_user}, error={str(e)}")
|
return False
|
|
|
# 全局消息处理器实例
|
message_processor = MessageProcessor()
|
