"""ORM model for the global business → agent / chain mapping (业务链条管理).

A "business mapping" row binds a fixed business code (3Q / 6BF / 6-1…6-4 / 7BF /
8BF / AFX) to an optional 智能体 (``agent_id``) and an optional 业务链条
(``chain_id`` → a ``roundtable_chains`` row, which must be **public** so every
account can resolve it). Used to auto-pick the business chain when a task page
launches the multi-agent roundtable.

Unlike ``roundtable_chains`` (per-user), this mapping is **global / shared** —
there is no ``user_id`` column; all accounts see and use the same configuration.
The fixed business rows are seeded on startup; users only fill in the
agent / chain columns from the management page.

``agent_name`` / ``chain_title`` are denormalized display snapshots so the table
renders without cross-referencing and survives a later agent/chain rename or
delete (the picked id still drives the auto-flow).
"""

from __future__ import annotations

from datetime import UTC, datetime

from sqlalchemy import Integer, String
from sqlalchemy.orm import Mapped, mapped_column

from deerflow.persistence.base import Base
from deerflow.persistence.types import BeijingDateTime


class BusinessMappingRow(Base):
    __tablename__ = "business_mapping"

    # Business code is the natural primary key (e.g. "3Q", "6BF"). Global, no user scope.
    business_code: Mapped[str] = mapped_column(String(32), primary_key=True)
    # Display label shown in the 业务 column (e.g. "任务FX").
    label: Mapped[str] = mapped_column(String(128), nullable=False, default="")
    # Picked 智能体 (暂存不用，自动流程当前不消费此字段). NULL = 未配置.
    agent_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
    agent_name: Mapped[str | None] = mapped_column(String(191), nullable=True)
    # Picked 业务链条 → roundtable_chains.id (须为 public). NULL = 未配置.
    chain_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
    chain_title: Mapped[str | None] = mapped_column(String(512), nullable=True)
    # Fixed display order for the management table.
    sort_order: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
    created_at: Mapped[datetime] = mapped_column(
        BeijingDateTime(), nullable=False, default=lambda: datetime.now(UTC)
    )
    updated_at: Mapped[datetime] = mapped_column(
        BeijingDateTime(),
        nullable=False,
        default=lambda: datetime.now(UTC),
        onupdate=lambda: datetime.now(UTC),
    )