54 lines
2.5 KiB
Python
54 lines
2.5 KiB
Python
"""ORM model for the global business → agent / chain mapping (业务链条管理).
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A "business mapping" row binds a fixed business code (3Q / 6BF / 6-1…6-4 / 7BF /
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8BF / AFX) to an optional 智能体 (``agent_id``) and an optional 业务链条
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(``chain_id`` → a ``roundtable_chains`` row, which must be **public** so every
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account can resolve it). Used to auto-pick the business chain when a task page
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launches the multi-agent roundtable.
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Unlike ``roundtable_chains`` (per-user), this mapping is **global / shared** —
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there is no ``user_id`` column; all accounts see and use the same configuration.
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The fixed business rows are seeded on startup; users only fill in the
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agent / chain columns from the management page.
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``agent_name`` / ``chain_title`` are denormalized display snapshots so the table
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renders without cross-referencing and survives a later agent/chain rename or
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delete (the picked id still drives the auto-flow).
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"""
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from __future__ import annotations
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from datetime import UTC, datetime
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from sqlalchemy import Integer, String
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from sqlalchemy.orm import Mapped, mapped_column
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from deerflow.persistence.base import Base
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from deerflow.persistence.types import BeijingDateTime
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class BusinessMappingRow(Base):
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__tablename__ = "business_mapping"
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# Business code is the natural primary key (e.g. "3Q", "6BF"). Global, no user scope.
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business_code: Mapped[str] = mapped_column(String(32), primary_key=True)
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# Display label shown in the 业务 column (e.g. "任务FX").
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label: Mapped[str] = mapped_column(String(128), nullable=False, default="")
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# Picked 智能体 (暂存不用，自动流程当前不消费此字段). NULL = 未配置.
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agent_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
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agent_name: Mapped[str | None] = mapped_column(String(191), nullable=True)
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# Picked 业务链条 → roundtable_chains.id (须为 public). NULL = 未配置.
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chain_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
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chain_title: Mapped[str | None] = mapped_column(String(512), nullable=True)
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# Fixed display order for the management table.
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sort_order: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
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created_at: Mapped[datetime] = mapped_column(
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BeijingDateTime(), nullable=False, default=lambda: datetime.now(UTC)
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)
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updated_at: Mapped[datetime] = mapped_column(
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BeijingDateTime(),
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nullable=False,
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default=lambda: datetime.now(UTC),
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onupdate=lambda: datetime.now(UTC),
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)
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