50 lines
2.4 KiB
Python
50 lines
2.4 KiB
Python
"""ORM model for the standalone 大屏绘制智能体 session (按 taskId 存取).
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One row per external ``task_id`` — the standalone dashboard page persists its
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chat transcript + the latest structured ``report_json`` so that returning to the
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same task either shows the finished dashboard directly (valid report_json) or
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restores the generation process.
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**Global / shared by task** — like ``roundtable_drafts`` task-bound drafts, the
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store keys on ``task_id`` and does **not** scope by ``user_id`` (open read +
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shared writes). ``user_id`` is recorded for audit only.
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``transcript`` / ``report_json`` are large JSON blobs (chat history + report
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data) stored as serialized strings in ``PortableLongText`` (MySQL ``LONGTEXT``)
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to dodge MySQL's 64 KB ``TEXT`` cap — same approach as ``roundtable_drafts``.
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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 String, UniqueConstraint
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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 DashboardSessionRow(Base):
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__tablename__ = "dashboard_sessions"
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# One session per task — keep it unique so upsert-by-task is unambiguous.
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__table_args__ = (UniqueConstraint("task_id", name="uq_dashboard_sessions_task_id"),)
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id: Mapped[str] = mapped_column(String(64), primary_key=True)
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# External task id (deep-link). The session is shared by task, not by user.
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task_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
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# Audit only — who last wrote. Never used for access control.
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user_id: Mapped[str | None] = mapped_column(String(64), nullable=True)
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# Chat transcript JSON (the dashboard agent's dialogue bubbles).
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transcript: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
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# Latest structured dashboard data (report-json string). Presence of a
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# parseable value = "有效结果" → the page shows the dashboard directly.
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report_json: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
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created_at: Mapped[datetime] = mapped_column(BeijingDateTime(), nullable=False, default=lambda: datetime.now(UTC))
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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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