企业 AI 的语义断层，阿里云用 UModel 和 USS 试图接上

# uss_schema.yaml —— 客户对象的语义映射定义
objects:
  Customer:
    description: "企业客户，统一 CRM 与 ERP 的客户实体"
    unified_fields:
      customer_id:
        type: string
        description: "客户唯一标识"
        mapping:
          crm: "customer_id"        # CRM 系统的原生字段
          erp: "client_code"        # ERP 系统的原生字段
      name:
        type: string
        mapping:
          crm: "full_name"
          erp: "client_name"
      tier:
        type: string
        enum: ["A", "B", "C"]
        mapping:
          crm: "customer_tier"
          erp: "client_level"
    relations:
      has_orders:
        target: Order
        cardinality: one_to_many
      has_tickets:
        target: Ticket
        cardinality: one_to_many

  Order:
    unified_fields:
      order_id:
        type: string
        mapping:
          erp: "order_no"
          crm: "opportunity_id"
      amount:
        type: float
        mapping:
          erp: "total_amount"
          crm: "deal_size"
      status:
        type: string
        mapping:
          erp: "order_status"
          crm: "opp_stage"

  Ticket:
    unified_fields:
      ticket_id:
        type: string
        mapping:
          cs: "case_number"          # 客服系统
      priority:
        type: string
        mapping:
          cs: "case_priority"

# umodel_runtime_demo.py
from umodel import UModelRuntime, SchemaLoader

# 加载 USS 语义映射
schema = SchemaLoader.from_yaml("uss_schema.yaml")

# 初始化运行时，注册数据源连接
runtime = UModelRuntime(schema=schema)

runtime.register_source(
    name="crm",
    connector="rest_api",
    base_url="https://crm.internal.example.com/api/v2",
    auth={"type": "oauth2", "token": "***"},
)

runtime.register_source(
    name="erp",
    connector="rest_api",
    base_url="https://erp.internal.example.com/api/v1",
    auth={"type": "apikey", "key": "***"},
)

runtime.register_source(
    name="cs",
    connector="rest_api",
    base_url="https://cs.internal.example.com/api",
    auth={"type": "oauth2", "token": "***"},
)

# 启动语义运行时
runtime.start()

# AI agent 通过统一语义查询客户，无需关心底层系统
customer = runtime.get("Customer", customer_id="C-10042")
print(customer.name)          # 自动从 CRM 或 ERP 取回，语义统一
print(customer.tier)          # "A"

# 查询关联对象——跨系统自动路由
orders = customer.has_orders  # 从 ERP 拉取订单
tickets = customer.has_tickets  # 从客服系统拉取工单

for order in orders:
    print(f"订单 {order.order_id}: {order.amount} 元, 状态 {order.status}")

for ticket in tickets:
    print(f"工单 {ticket.ticket_id}: 优先级 {ticket.priority}")

# AI agent 任务：给 A 级客户创建高优先级工单
high_value_customers = runtime.query(
    "Customer",
    filters={"tier": "A"},
    limit=50,
)

for c in high_value_customers:
    # 检查是否有未完成的大额订单
    pending_orders = [o for o in c.has_orders if o.status != "completed" and o.amount > 100000]
    if pending_orders:
        runtime.create("Ticket", {
            "customer_id": c.customer_id,
            "priority": "high",
            "description": f"客户 {c.name} 有 {len(pending_orders)} 笔大额未完成订单，需跟进",
        })
        print(f"已为 {c.name} 创建高优先级工单")