v0.1.0: CRM/ERP 系统内测版本 - 安全加固完成
- Docker bridge 网络隔离（8000 端口封死） - Gunicorn 4 Worker 多进程 - Alembic 数据库迁移基线 - 日志轮转 20m×3 - JWT 密钥 + DB 密码 + CORS 收紧 - 3-2-1 备份链路（NAS + R740-B 冷备） - 连接池 pool_pre_ping + pool_recycle=3600
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hankin
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"""
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CRM 客户模块路由 —— /api/customers
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薄路由层：参数解析 + 调用 Service + 包装响应
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"""
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from __future__ import annotations
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import uuid
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from fastapi import APIRouter, Depends, Query, Request
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.api.deps import get_current_user
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from app.db.database import get_db
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from app.schemas.auth import CurrentUserPayload
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from app.schemas.crm import CustomerCreate, CustomerUpdate
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from app.schemas.response import ok
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from app.services import customer_service as svc
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router = APIRouter(prefix="/customers", tags=["客户管理"])
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@router.post("", summary="新增客户")
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async def create_customer(
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body: CustomerCreate,
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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result = await svc.create_customer(db, current_user, body)
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return ok(data=result.model_dump(mode="json"), message="客户创建成功")
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@router.get("", summary="分页获取客户列表（含数据权限隔离）")
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async def list_customers(
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page: int = Query(1, ge=1, description="页码"),
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size: int = Query(20, ge=1, le=100, description="每页数量"),
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keyword: str | None = Query(None, description="名称模糊搜索"),
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level: str | None = Query(None, pattern=r"^[ABC]$", description="客户等级"),
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include_archived: bool = Query(False, description="是否包含已归档客户"),
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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result = await svc.list_customers(db, current_user, page, size, keyword, level, include_archived)
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return ok(data=result.model_dump(mode="json"))
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@router.get("/search", summary="模糊搜索客户（远程选择器用）")
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async def search_customers(
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q: str = Query(..., min_length=1, max_length=100, description="搜索关键词"),
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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result = await svc.search_customers(db, current_user, q)
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return ok(data=result)
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@router.get("/{customer_id}", summary="获取客户详情")
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async def get_customer(
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customer_id: uuid.UUID,
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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result = await svc.get_customer(db, current_user, customer_id)
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return ok(data=result.model_dump(mode="json"))
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@router.put("/{customer_id}", summary="修改客户信息")
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async def update_customer(
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customer_id: uuid.UUID,
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body: CustomerUpdate,
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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result = await svc.update_customer(db, current_user, customer_id, body)
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return ok(data=result.model_dump(mode="json"), message="客户信息已更新")
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@router.delete("/{customer_id}", summary="软删除客户")
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async def delete_customer(
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customer_id: uuid.UUID,
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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await svc.delete_customer(db, current_user, customer_id)
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return ok(message="客户已归档")
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@router.put("/{customer_id}/restore", summary="恢复已归档客户")
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async def restore_customer(
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customer_id: uuid.UUID,
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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await svc.restore_customer(db, current_user, customer_id)
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return ok(message="客户已恢复")
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@router.get("/{customer_id}/products", summary="获取客户关联产品（通过订单反查）")
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async def get_customer_products(
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customer_id: uuid.UUID,
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db: AsyncSession = Depends(get_db),
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current_user: CurrentUserPayload = Depends(get_current_user),
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) -> dict:
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result = await svc.get_customer_products(db, current_user, customer_id)
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return ok(data=result)
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@router.put("/{customer_id}/persona", summary="双轨画像回写（Dify Workflow 回调）")
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async def update_customer_persona(
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customer_id: uuid.UUID,
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request: Request,
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db: AsyncSession = Depends(get_db),
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) -> dict:
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"""
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V5.0 双轨画像回写 — 容错解析 Dify Workflow 回调 body。
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支持以下格式：
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1. 标准 JSON: {"company_updates": {...}, "contact_updates": [...]}
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2. Dify 空 key 包装: {"": "JSON字符串"}
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3. Qwen3.5 CoT 包裹: <think>...</think> + JSON
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"""
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import json as _json
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import re
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raw = await request.body()
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raw_str = raw.decode("utf-8", errors="replace").strip()
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# ── 统一预处理：去除 <think>...</think> 标签 ──
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cleaned = re.sub(r'<think>[\s\S]*?</think>', '', raw_str, flags=re.DOTALL).strip()
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# 也处理可能缺少闭合的 <think>
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cleaned = re.sub(r'<think>[\s\S]*$', '', cleaned, flags=re.DOTALL).strip()
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body = None
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# 策略1：清理后直接 JSON 解析
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try:
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parsed = _json.loads(cleaned)
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if isinstance(parsed, dict):
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body = parsed
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elif isinstance(parsed, list):
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# 从数组中找到含画像 key 的 dict
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for item in parsed:
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if isinstance(item, dict) and len(item) > 1:
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body = item
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break
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except _json.JSONDecodeError:
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pass
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# 策略2：Dify 空 key 包装 {"": "...JSON..."}
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if not body:
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try:
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wrapped = _json.loads(raw_str)
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if isinstance(wrapped, dict):
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values = list(wrapped.values())
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if len(values) == 1 and isinstance(values[0], str):
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inner = re.sub(r'<think>[\s\S]*?</think>', '', values[0], flags=re.DOTALL).strip()
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try:
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body = _json.loads(inner)
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except _json.JSONDecodeError:
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pass
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except _json.JSONDecodeError:
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pass
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# 策略3：正则从文本中提取最外层 JSON 对象 {...}
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if not body or not isinstance(body, dict):
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# 找到第一个 { 到最后一个 } 之间的内容
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m = re.search(r'\{', cleaned)
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if m:
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start = m.start()
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# 用计数法匹配完整的 JSON 对象
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depth = 0
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end = start
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for i in range(start, len(cleaned)):
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if cleaned[i] == '{': depth += 1
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elif cleaned[i] == '}': depth -= 1
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if depth == 0:
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end = i + 1
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break
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if depth == 0:
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try:
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body = _json.loads(cleaned[start:end])
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except _json.JSONDecodeError:
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pass
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if not body or not isinstance(body, dict):
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print(f"[Persona] 无法解析 body ({len(raw_str)} chars): {cleaned[:300]}")
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return ok(message="画像回写失败：无法解析请求体")
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print(f"[Persona] 解析成功，keys={list(body.keys())}")
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from app.models.crm import CrmCustomer, CrmContact
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from sqlalchemy import update as sa_update
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# Key 模糊映射：LLM 可能不严格遵循 key name
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_COMPANY_KEYS = {"company_updates", "company_info", "firmographics", "company", "企业画像"}
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_CONTACT_KEYS = {"contact_updates", "contacts", "contact_info", "buyer_updates", "联系人画像"}
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company_updates = None
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contact_updates = None
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for k, v in body.items():
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kl = k.lower().strip()
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print(f"[Persona] key='{k}' type={type(v).__name__}")
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if kl in _COMPANY_KEYS or "company" in kl or "firm" in kl:
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if isinstance(v, dict):
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company_updates = v
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elif isinstance(v, str):
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try:
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company_updates = _json.loads(v)
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except _json.JSONDecodeError:
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company_updates = {"summary": v}
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elif kl in _CONTACT_KEYS or "contact" in kl:
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if isinstance(v, list):
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contact_updates = v
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elif isinstance(v, dict):
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contact_updates = [v]
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elif isinstance(v, str):
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try:
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parsed_contacts = _json.loads(v)
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contact_updates = parsed_contacts if isinstance(parsed_contacts, list) else [parsed_contacts]
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except _json.JSONDecodeError:
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pass
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# 如果 company_updates 没有标准结构但有 firmographics/dynamic_status 在顶层
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if not company_updates and ("firmographics" in body or "dynamic_status" in body):
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company_updates = {
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"firmographics": body.get("firmographics", {}),
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"dynamic_status": body.get("dynamic_status", {}),
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}
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# 如果完全没匹配到 company key，但 body 本身看起来就是画像数据，直接用整个 body
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if not company_updates and not contact_updates:
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company_updates = body
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print(f"[Persona] company={'有' if company_updates else '无'}, contacts={len(contact_updates) if contact_updates else 0}条")
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# ── 企业级画像合并 ──
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if company_updates:
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customer = await db.get(CrmCustomer, customer_id)
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if customer:
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merged = _deep_merge(customer.ai_persona or {}, company_updates)
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stmt = (
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sa_update(CrmCustomer)
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.where(CrmCustomer.id == customer_id)
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.values(ai_persona=merged)
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)
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await db.execute(stmt)
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# ── 联系人级画像合并 ──
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if contact_updates and isinstance(contact_updates, list):
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for cu in contact_updates:
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cid = cu.get("contact_id")
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if not cid:
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continue
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try:
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contact = await db.get(CrmContact, uuid.UUID(cid))
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except (ValueError, TypeError):
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continue
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if not contact:
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continue
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updates = {k: v for k, v in cu.items() if k != "contact_id" and v is not None}
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merged = _deep_merge(contact.ai_buyer_persona or {}, updates)
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contact.ai_buyer_persona = merged
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await db.commit()
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return ok(message="画像更新成功")
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def _deep_merge(base: dict, override: dict) -> dict:
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"""递归深度合并两个 dict（增量模式）。
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规则：
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- dict + dict → 递归合并
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- list + list → 追加去重
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- 新值为空（空字符串/空列表/空dict/None）→ 保留旧值
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- 新值非空 → 覆盖旧值
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"""
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result = base.copy()
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for k, v in override.items():
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old = result.get(k)
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# 空值不覆盖已有数据
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if old and (v is None or v == "" or v == [] or v == {}):
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continue
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if isinstance(old, dict) and isinstance(v, dict):
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result[k] = _deep_merge(old, v)
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elif isinstance(old, list) and isinstance(v, list):
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# 列表去重追加
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seen = set(str(x) for x in old)
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result[k] = old + [x for x in v if str(x) not in seen]
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else:
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result[k] = v
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return result
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