"""决策前哨模型。

识别企业关键决策岔路口，AI 提前生成场景分析。
"""

import uuid
from datetime import datetime, timezone

from sqlalchemy import DateTime, ForeignKey, String, Text
from sqlalchemy.orm import Mapped, mapped_column

from app.core.database import Base
from app.core.types import JSONBType


class DecisionSentinel(Base):
    """决策前哨。"""

    __tablename__ = "decision_sentinels"

    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid.uuid4()))
    company_id: Mapped[str] = mapped_column(String(36), ForeignKey("companies.id"), nullable=False, index=True)
    decision_type: Mapped[str] = mapped_column(String(50), nullable=False, comment="pivot/hiring/funding/product/org")
    title: Mapped[str] = mapped_column(String(200), nullable=False, comment="决策标题")
    description: Mapped[str | None] = mapped_column(Text, nullable=True)
    signals: Mapped[dict | None] = mapped_column(JSONBType, nullable=True, comment="触发信号列表")
    scenarios: Mapped[dict | None] = mapped_column(JSONBType, nullable=True, comment="场景分析 — A 路线 vs B 路线")
    status: Mapped[str] = mapped_column(String(20), nullable=False, default="identified", comment="identified/analyzed/acted/dismissed")
    identified_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
    )
    created_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
    )
    updated_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True),
        default=lambda: datetime.now(timezone.utc),
        onupdate=lambda: datetime.now(timezone.utc),
    )