# ============================================================================= # 企微IT智能服务台 — 业务路由推荐服务 # ============================================================================= # 说明：核心路由逻辑，在 H5 后台 AI 任务中拦截非IT业务消息， # 调用 Dify 统一意图识别，判定业务类别后发送对应联系人名片卡片。 # # 主要职责： # 1. 关键词预过滤（ROUTING_PREFILTER_KEYWORDS）— 快速过滤非路由消息 # 2. Dify 统一意图识别 — 调用 /v1/chat-messages，解析 intent_type/business_category/routing_confidence # 3. 联系人查询 — 按 business_category 查 business_contacts 表 # 4. 名片三段式发送 — 路由文本 → contact_card → 系统提示（WS双通道推送） # 5. 路由事件记录（P1）— 记录路由命中统计 # # 设计决策： # - 路由检测放在后台任务而非前端调用，与 BYOD 卡片处理模式一致 # - 关键词预过滤与审批预过滤可能重叠，Dify Prompt 内部判断优先级确保正确分流 # - routing_confidence < 0.7 不触发名片推荐，走正常 AI 回复流程 # ============================================================================= import json import logging from datetime import datetime from typing import Any, Optional import httpx from sqlalchemy import select from app.config import settings from app.models.business_contact import BusinessContact from app.models.conversation import Conversation from app.models.message import Message from app.models.routing_event import RoutingEvent from app.services.ws_manager import manager as ws_manager logger = logging.getLogger(__name__) # ============================================================================= # 路由关键词预过滤列表 # ============================================================================= # 说明：覆盖 5 个业务类别的关键词，用于快速过滤非路由消息。 # 只要命中任意一个关键词才值得调用 Dify 做精确判断。 # 关键词可能与审批预过滤重叠（如"办公用品"），Dify Prompt 内部判断 # 优先级（先审批→再IT咨询→再非IT路由）确保正确分流。 ROUTING_PREFILTER_KEYWORDS: list[str] = [ # 行政 "打印机", "复印机", "扫描仪", "保洁", "名片印刷", # 人力资源 "工牌", "考勤", "入职", "离职", "社保", "公积金", # 财务 "报销", "发票", "借款", "工资条", # 法务 "合同", "法务", "知识产权", # 行政-物业 "空调", "电梯", "门禁", "停车", ] # 关键词到业务类别的映射（Dify 不可用时降级兜底用） ROUTING_KEYWORD_TO_CATEGORY: dict[str, str] = { # 行政 "打印机": "行政", "复印机": "行政", "扫描仪": "行政", "保洁": "行政", "名片印刷": "行政", # 人力资源 "工牌": "人力资源", "考勤": "人力资源", "入职": "人力资源", "离职": "人力资源", "社保": "人力资源", "公积金": "人力资源", # 财务 "报销": "财务", "发票": "财务", "借款": "财务", "工资条": "财务", # 法务 "合同": "法务", "法务": "法务", "知识产权": "法务", # 行政-物业 "空调": "行政-物业", "电梯": "行政-物业", "门禁": "行政-物业", "停车": "行政-物业", } # ============================================================================= # 预过滤 & 降级兜底 # ============================================================================= def routing_keyword_prefilter(text: str) -> bool: """路由关键词预过滤：检查文本是否包含非IT业务关键词。 只要命中任意一个路由关键词即返回 True，未命中返回 False。 用于在调用 Dify 前快速过滤，减少不必要的 API 调用。 Args: text: 用户消息文本 Returns: bool: 是否包含路由关键词 """ if not text: return False return any(kw in text for kw in ROUTING_PREFILTER_KEYWORDS) def _keyword_fallback_category(text: str) -> Optional[str]: """关键词降级兜底：Dify 不可用时通过关键词匹配业务类别。 遍历 ROUTING_KEYWORD_TO_CATEGORY 映射，命中第一个关键词即返回对应业务类别。 Args: text: 用户消息文本 Returns: Optional[str]: 业务类别（行政/人力资源/财务/法务/行政-物业），未命中返回 None """ if not text: return None for kw, category in ROUTING_KEYWORD_TO_CATEGORY.items(): if kw in text: return category return None # ============================================================================= # Dify 统一意图识别调用 # ============================================================================= async def detect_routing_intent(text: str, employee_id: str = "") -> dict: """调用 Dify 统一意图识别，解析路由相关字段。 复用 approval.py 的 _call_dify_approval_intent 调用模式（Dify 原生 API）， 但本函数独立维护，解析路由关心的字段： - intent_type: approval/it_consult/non_it_routing/chitchat - business_category: 行政/人力资源/财务/法务/行政-物业（仅 non_it_routing 时有值） - routing_confidence: 0.0~1.0，≥0.7 触发名片推荐 使用与审批意图识别相同的 Dify 应用（同一 API Key），只是解析各自关心的字段。 Args: text: 用户消息文本 employee_id: 员工 ID（可选，传给 Dify 的 user 字段） Returns: dict: { "intent_type": str, "business_category": str | None, "routing_confidence": float, "is_approval_request": bool, "confidence": float, "approval_type": str | None, } Raises: Exception: Dify 调用失败或响应解析失败 """ base_url = settings.approval_dify_base_url api_key = settings.approval_dify_api_key timeout = settings.approval_dify_timeout if not base_url or not api_key: raise ValueError( "Dify 统一意图识别应用未配置" "（APPROVAL_DIFY_BASE_URL / APPROVAL_DIFY_API_KEY）" ) # 构建请求 URL：base_url + /v1/chat-messages（Dify 原生 API） url = f"{base_url.rstrip('/')}/v1/chat-messages" body = { "inputs": {}, "query": text, "response_mode": "blocking", "user": employee_id or "routing_detection", } headers = { "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", } async with httpx.AsyncClient(timeout=httpx.Timeout(timeout)) as client: response = await client.post(url, json=body, headers=headers) response.raise_for_status() data = response.json() # 解析 Dify 原生响应：answer 字段包含 AI 返回的 JSON 字符串 answer = data.get("answer", "") parsed = json.loads(answer) # 解析统一意图识别的 6 个字段 return { "is_approval_request": bool(parsed.get("is_approval_request", False)), "confidence": float(parsed.get("confidence", 0.0)), "approval_type": parsed.get("approval_type"), "intent_type": str(parsed.get("intent_type", "chitchat")), "business_category": parsed.get("business_category"), "routing_confidence": float(parsed.get("routing_confidence", 0.0)), } # ============================================================================= # 联系人查询 # ============================================================================= async def get_contact_by_category(db, category: str) -> Optional[BusinessContact]: """按业务类别查询联系人。 按 business_category + is_active=True 查询，取第一条有效联系人。 P0 阶段单联系人推荐，P2 支持按服务区域匹配。 Args: db: 异步 DB session category: 业务类别（行政/人力资源/财务/法务/行政-物业） Returns: Optional[BusinessContact]: 联系人对象，未找到返回 None """ result = await db.execute( select(BusinessContact) .where( BusinessContact.business_category == category, BusinessContact.is_active == True, # noqa: E712 ) .order_by(BusinessContact.id) .limit(1) ) return result.scalar_one_or_none() # ============================================================================= # 名片三段式发送 # ============================================================================= async def send_contact_card( db, conversation: Conversation, employee_id: str, contact: BusinessContact, reason: str, business_category: str, routing_confidence: float, ) -> None: """发送名片三段式消息（路由文本 → contact_card → 系统提示）。 完全参考 _handle_byod_query 模式： 1. 创建路由说明文本消息（AI, text）→ 落库 + WS双通道推送 2. 创建 contact_card 名片消息（AI, contact_card）→ 落库 + WS双通道推送 3. 创建系统提示消息（system, system）→ 落库 + WS双通道推送 每条消息分别落库 + WS推送，与 PRD 4.3 交互流程一致。 Args: db: 异步 DB session conversation: 当前会话对象 employee_id: 员工企微 UserID contact: 联系人对象 reason: 路由说明文本（如"打印机问题属于行政设备范畴..."） business_category: 业务类别 routing_confidence: 路由置信度 """ contact_data = contact.to_dict() extra_data: dict[str, Any] = { "contact": contact_data, "routing_reason": reason, "business_category": business_category, "routing_confidence": routing_confidence, } # === 1. 路由说明文本消息 === routing_text_msg = Message( conversation_id=conversation.id, sender_type="ai", sender_id="ai_bot", sender_name="Duckula（达寇拉）", content=reason, msg_type="text", is_read=True, ) db.add(routing_text_msg) await db.flush() await ws_manager.broadcast_to_employees([employee_id], { "type": "ai_reply", "data": { "message_id": str(routing_text_msg.id), "conversation_id": str(conversation.id), "sender_type": "ai", "sender_id": "ai_bot", "sender_name": "Duckula（达寇拉）", "content": reason, "msg_type": "text", "is_guidance": False, "ai_reply_count": conversation.ai_substantive_reply_count, "can_call_agent": conversation.ai_substantive_reply_count >= 3, "conversation_status": conversation.status, }, }) try: await ws_manager.broadcast({ "type": "new_message", "data": { "conversation_id": str(conversation.id), "message_id": str(routing_text_msg.id), "sender_type": "ai", "sender_id": "ai_bot", "sender_name": "Duckula（达寇拉）", "content": reason, "msg_type": "text", }, }) except Exception as ws_err: logger.warning(f"路由文本 WS 广播给坐席失败: {ws_err}") # === 2. contact_card 名片消息 === contact_card_msg = Message( conversation_id=conversation.id, sender_type="ai", sender_id="ai_bot", sender_name="Duckula（达寇拉）", content=f"为您推荐{business_category}服务联系人：{contact.name}", msg_type="contact_card", extra_data=extra_data, is_read=True, ) db.add(contact_card_msg) await db.flush() await ws_manager.broadcast_to_employees([employee_id], { "type": "ai_reply", "data": { "message_id": str(contact_card_msg.id), "conversation_id": str(conversation.id), "sender_type": "ai", "sender_id": "ai_bot", "sender_name": "Duckula（达寇拉）", "content": f"为您推荐{business_category}服务联系人：{contact.name}", "msg_type": "contact_card", "extra_data": extra_data, "is_guidance": False, "ai_reply_count": conversation.ai_substantive_reply_count, "can_call_agent": conversation.ai_substantive_reply_count >= 3, "conversation_status": conversation.status, }, }) try: await ws_manager.broadcast({ "type": "new_message", "data": { "conversation_id": str(conversation.id), "message_id": str(contact_card_msg.id), "sender_type": "ai", "sender_id": "ai_bot", "sender_name": "Duckula（达寇拉）", "content": f"为您推荐{business_category}服务联系人：{contact.name}", "msg_type": "contact_card", "extra_data": extra_data, }, }) except Exception as ws_err: logger.warning(f"名片卡片 WS 广播给坐席失败: {ws_err}") # === 3. 系统提示消息 === system_text = "以上为AI自动推荐，点击名片可直接发起企微聊天" system_msg = Message( conversation_id=conversation.id, sender_type="system", sender_id="system", sender_name="系统", content=system_text, msg_type="system", is_read=True, ) db.add(system_msg) await db.flush() await ws_manager.broadcast_to_employees([employee_id], { "type": "ai_reply", "data": { "message_id": str(system_msg.id), "conversation_id": str(conversation.id), "sender_type": "system", "sender_id": "system", "sender_name": "系统", "content": system_text, "msg_type": "system", "is_guidance": False, "ai_reply_count": conversation.ai_substantive_reply_count, "can_call_agent": conversation.ai_substantive_reply_count >= 3, "conversation_status": conversation.status, }, }) try: await ws_manager.broadcast({ "type": "new_message", "data": { "conversation_id": str(conversation.id), "message_id": str(system_msg.id), "sender_type": "system", "sender_id": "system", "sender_name": "系统", "content": system_text, "msg_type": "system", }, }) except Exception as ws_err: logger.warning(f"系统提示 WS 广播给坐席失败: {ws_err}") # 更新会话状态（路由推荐视为一次实质性 AI 回复） conversation.ai_substantive_reply_count += 1 conversation.updated_at = datetime.now() db.add(conversation) await db.flush() await db.commit() logger.info( f"路由名片发送完成: employee_id={employee_id}, category={business_category}, " f"contact={contact.name}, confidence={routing_confidence}" ) # ============================================================================= # 路由事件记录（P1） # ============================================================================= async def record_routing_event( db, conversation_id: str, employee_id: str, message_content: str, business_category: str, routing_confidence: float, contact: Optional[BusinessContact], ) -> None: """记录路由命中事件（P1）。 为后续优化 Prompt 准确率、分析高频非IT业务提供数据支撑。 Args: db: 异步 DB session conversation_id: 会话ID employee_id: 员工ID message_content: 触发路由的员工消息（截断至500字） business_category: 业务类别 routing_confidence: 路由置信度 contact: 推荐的联系人对象（可能为 None） """ try: event = RoutingEvent( conversation_id=conversation_id, employee_id=employee_id, message_content=message_content[:500], business_category=business_category, routing_confidence=routing_confidence, contact_id=contact.id if contact else None, contact_name=contact.name if contact else "", is_clicked=False, ) db.add(event) await db.flush() await db.commit() except Exception as e: # 路由事件记录失败不影响主流程，仅记录 warning logger.warning(f"路由事件记录失败: {e}")