TradeMate Dev
c6206787da
项目结构: - backend/ Python FastAPI 后端 - uni-app/ uni-app跨端前端 - docs/ 设计文档 - docker-compose.yml Docker编排 - nginx/scripts/systemd 运维配置 已完成功能: - 用户认证 (JWT) - 智能翻译 + 回复建议 - 营销素材生成 - 客户管理 + 沉默检测 - 报价单管理 - 产品库管理 - 汇率换算 - 推送通知 (uni-push) - WhatsApp Webhook框架 - Celery定时任务
205 lines
7.3 KiB
Python
205 lines
7.3 KiB
Python
from typing import Dict, Any, Optional, List
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from datetime import datetime, timedelta
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, func, and_
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from app.models.customer import Customer, Conversation, Message
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import logging
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logger = logging.getLogger(__name__)
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class CustomerService:
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def __init__(self, db: AsyncSession):
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self.db = db
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async def list_customers(self, user_id: str, status: Optional[str] = None, page: int = 1, size: int = 20) -> Dict[str, Any]:
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query = select(Customer).where(Customer.user_id == user_id)
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count_query = select(func.count()).select_from(Customer).where(Customer.user_id == user_id)
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if status:
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query = query.where(Customer.status == status)
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count_query = count_query.where(Customer.status == status)
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query = query.order_by(Customer.updated_at.desc()).offset((page - 1) * size).limit(size)
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total = await self.db.execute(count_query)
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result = await self.db.execute(query)
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customers = result.scalars().all()
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return {
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"items": [self._to_dict(c) for c in customers],
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"total": total.scalar(),
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"page": page,
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"size": size,
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}
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async def get_customer(self, user_id: str, customer_id: str) -> Optional[Dict]:
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result = await self.db.execute(
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select(Customer).where(
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and_(Customer.id == customer_id, Customer.user_id == user_id)
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)
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)
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c = result.scalar_one_or_none()
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return self._to_dict(c) if c else None
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async def create_customer(self, user_id: str, data: Dict[str, Any]) -> Dict:
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c = Customer(user_id=user_id, **data)
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self.db.add(c)
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await self.db.flush()
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return self._to_dict(c)
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async def update_customer(self, user_id: str, customer_id: str, data: Dict[str, Any]) -> Optional[Dict]:
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result = await self.db.execute(
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select(Customer).where(
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and_(Customer.id == customer_id, Customer.user_id == user_id)
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)
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)
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c = result.scalar_one_or_none()
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if not c:
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return None
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for k, v in data.items():
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if hasattr(c, k):
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setattr(c, k, v)
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await self.db.flush()
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return self._to_dict(c)
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async def delete_customer(self, user_id: str, customer_id: str) -> bool:
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result = await self.db.execute(
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select(Customer).where(
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and_(Customer.id == customer_id, Customer.user_id == user_id)
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)
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)
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c = result.scalar_one_or_none()
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if not c:
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return False
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await self.db.delete(c)
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return True
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async def get_silent_customers(self, user_id: str, days: int = 3) -> List[Dict]:
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cutoff = datetime.utcnow() - timedelta(days=days)
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result = await self.db.execute(
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select(Customer)
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.where(
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and_(
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Customer.user_id == user_id,
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Customer.status.in_(["lead", "negotiating"]),
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Customer.last_contact_at.isnot(None),
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Customer.last_contact_at < cutoff,
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)
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)
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.order_by(Customer.last_contact_at.asc())
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)
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return [self._to_dict(c) for c in result.scalars().all()]
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async def record_contact(self, user_id: str, customer_id: str):
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now = datetime.utcnow()
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result = await self.db.execute(
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select(Customer).where(
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and_(Customer.id == customer_id, Customer.user_id == user_id)
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)
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)
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c = result.scalar_one_or_none()
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if c:
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c.last_contact_at = now
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c.silence_started_at = None
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c.next_followup_at = now + timedelta(days=3)
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await self.db.flush()
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async def get_conversation(self, user_id: str, customer_id: str, page: int = 1, size: int = 50) -> Dict[str, Any]:
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conv_query = select(Conversation).where(
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and_(Conversation.user_id == user_id, Conversation.customer_id == customer_id)
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).order_by(Conversation.created_at.desc()).limit(1)
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conv_result = await self.db.execute(conv_query)
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conv = conv_result.scalar_one_or_none()
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if not conv:
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return {"messages": [], "total": 0, "conversation_id": None}
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msg_query = (
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select(Message)
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.where(Message.conversation_id == conv.id)
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.order_by(Message.created_at.asc())
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.offset((page - 1) * size)
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.limit(size)
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)
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msg_result = await self.db.execute(msg_query)
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messages = msg_result.scalars().all()
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return {
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"conversation_id": str(conv.id),
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"messages": [
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{
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"id": str(m.id),
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"direction": m.direction,
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"content": m.content,
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"content_translated": m.content_translated,
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"ai_suggestions": m.ai_suggestions,
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"selected_suggestion": m.selected_suggestion,
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"created_at": m.created_at.isoformat() if m.created_at else None,
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}
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for m in messages
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],
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"total": conv.message_count,
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}
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async def save_message(
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self, user_id: str, customer_id: str, direction: str, content: str,
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translation: Optional[str] = None, suggestions: Optional[List] = None,
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) -> Dict:
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conv_result = await self.db.execute(
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select(Conversation).where(
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and_(Conversation.user_id == user_id, Conversation.customer_id == customer_id)
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).order_by(Conversation.created_at.desc()).limit(1)
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)
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conv = conv_result.scalar_one_or_none()
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if not conv:
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conv = Conversation(
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user_id=user_id,
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customer_id=customer_id,
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channel="whatsapp",
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status="active",
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)
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self.db.add(conv)
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await self.db.flush()
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msg = Message(
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conversation_id=conv.id,
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direction=direction,
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content=content,
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content_translated=translation,
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ai_suggestions=suggestions,
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)
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self.db.add(msg)
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conv.message_count = (conv.message_count or 0) + 1
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conv.last_message_at = datetime.utcnow()
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await self.db.flush()
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await self.record_contact(user_id, customer_id)
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return {
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"message_id": str(msg.id),
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"conversation_id": str(conv.id),
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"direction": direction,
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"content": content,
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}
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def _to_dict(self, c: Customer) -> Dict:
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if not c:
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return {}
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return {
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"id": str(c.id),
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"name": c.name,
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"company": c.company,
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"country": c.country,
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"phone": c.phone,
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"email": c.email,
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"whatsapp_id": c.whatsapp_id,
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"source": c.source,
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"tags": c.tags,
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"status": c.status,
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"last_contact_at": c.last_contact_at.isoformat() if c.last_contact_at else None,
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"silence_days": (datetime.utcnow() - c.last_contact_at).days if c.last_contact_at else 0,
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"created_at": c.created_at.isoformat() if c.created_at else None,
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}
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