董宏凯andClaude Opus 4.8
3405795371
本阶段目标 bug：每步只有一个智能体（无并行）时，stageGroupsToStagePayload/ stageGroupsToStageGoals 一律折叠为 null（旧设计＝线性链），导致目标保存即丢、 无从回显。改为「有并行 或 任一 stage 填了目标」就落显式分层，串行带目标链按 分层 DAG 跑（总控逐阶段按目标派活）；BusinessChainPicker 同步：有并行/有目标/ 有总控提示都走 dag。 新增「总控提示词」（per-chain，仅 dag 模式生效）：写给总控的整体派活指引。 后端 roundtable_chains 加 coordinator_prompt LONGTEXT 列 + migration 20260608_06； 前端编辑器加输入框，注入 buildDagStageLeaderTask 每阶段派活提示。填了总控提示 也强制显式分层（forceExplicit），否则纯线性链里被静默忽略。 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
66 lines
3.7 KiB
Python
66 lines
3.7 KiB
Python
"""ORM model for roundtable-planning business chains.
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A "business chain" (业务链条) is a named, reusable, *ordered* list of agents the
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user assembles in the chain editor. In Step 2 the coordinator dispatches to the
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seats following this order (see ``multi-agent-business-chain-dev.md``).
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Persisted per user (like ``roundtable_drafts``) so it follows the account across
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devices/sessions. ``seats`` is stored as a JSON array serialized into
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``PortableLongText`` (MySQL ``LONGTEXT``) rather than ``PortableJSON`` for
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headroom, mirroring the sibling roundtable persistence modules.
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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 Boolean, 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, PortableLongText
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class RoundtableChainRow(Base):
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__tablename__ = "roundtable_chains"
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id: Mapped[str] = mapped_column(String(64), primary_key=True)
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user_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
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# Human-readable chain title shown on the picker card.
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title: Mapped[str] = mapped_column(String(512), nullable=False, default="")
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# Optional free-text description.
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description: Mapped[str | None] = mapped_column(String(2048), nullable=True)
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# JSON: ordered [{"agent_id": str, "name": str, "description": str}, ...].
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# seats[0] is the first seat to speak. Stored as LONGTEXT-backed JSON string.
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seats: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
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# Optional JSON: layered orchestration grouping over ``seats`` — a list of
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# stages, each a list of agent_ids run in parallel; stages run serially in
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# order. e.g. [["a","b"],["c"]] = (a‖b) → c. NULL/absent = linear chain
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# (each seat its own stage). Drives Step 2 dag-mode orchestration; see
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# frontend ``lib/dag-types.ts``. Stored as LONGTEXT-backed JSON string.
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stages: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
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# Optional JSON: per-stage goals aligned by index to ``stages`` — a list where
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# ``stage_goals[i]`` is the「本阶段目标」for ``stages[i]`` (what that serial stage
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# should produce / how it depends on the previous stage's output). Injected to the
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# coordinator dispatch prompt (and seat tasks as fallback) in dag-mode only. NULL =
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# no goals (and always NULL when ``stages`` is NULL/linear). Stored as JSON string.
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stage_goals: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
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# 可选「总控编排提示」：用户为本链条写给**总控（协调）智能体**的一段指引，告诉总控该
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# 怎么派活、做什么（整体编排策略 / 风格 / 约束）。**仅分层 DAG 模式生效**：注入到总控
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# 每阶段派活提示（``buildDagStageLeaderTask``）。NULL = 不注入。纯文本，存为 LONGTEXT。
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coordinator_prompt: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
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# 发布开关：True = 公共（所有账号可在「公共」筛选里查看 / 选用）；False = 仅本人可见。
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# 编辑 / 删除始终只限 owner；发布只是放开「查看 + 选入研讨」。索引以支持「公共」列表筛选。
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is_public: Mapped[bool] = mapped_column(
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Boolean, nullable=False, default=False, server_default="0", index=True
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)
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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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