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ThearchyHelios
2df591d05f
事件流里的输出是给画布看的截断预览，出具溯源需要完整证据。 新增 data/artifacts/ 内容寻址工件库（sha256 即地址，取回时复验哈希， 篡改即报错）；节点完整输出与工具调用快照（query+结果集）自动落盘， 事件只携带工件 id。运行终态对全部事件计算清单哈希存入 Run， 事后对事件流的增删改会与它对不上。 graph_hash 剔除 viewport 后计算——挪画布不改变图的身份。 Run/Workflow/WorkflowVersion/Approval 预置分级与治理列， init_db 附带 SQLite 轻量列迁移。
283 lines
13 KiB
Python
283 lines
13 KiB
Python
from __future__ import annotations
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from datetime import datetime
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from typing import Any
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from sqlalchemy import Float, ForeignKey, Index, Integer, LargeBinary, String, Text, UniqueConstraint
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from app.db.base import Base, TimestampMixin, new_id
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# --------------------------------------------------------------------------
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# 设置：模型供应商 / 用户偏好 / MCP / 自定义工具
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# --------------------------------------------------------------------------
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class Provider(Base, TimestampMixin):
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"""一个模型接入点。api_key 落库前经 app.core.crypto 加密。"""
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__tablename__ = "providers"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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name: Mapped[str] = mapped_column(String(100), unique=True)
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kind: Mapped[str] = mapped_column(String(32)) # anthropic | openai | openai_compatible | mock
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base_url: Mapped[str | None] = mapped_column(String(500), default=None)
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api_key: Mapped[str | None] = mapped_column(Text, default=None) # 密文
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models: Mapped[list[Any]] = mapped_column(default=list) # [{id, label, context, pricing}]
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default_model: Mapped[str | None] = mapped_column(String(200), default=None)
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enabled: Mapped[bool] = mapped_column(default=True)
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extra: Mapped[dict[str, Any]] = mapped_column(default=dict)
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class Setting(Base, TimestampMixin):
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"""键值形式的用户设置，前端 Settings 页直接读写。"""
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__tablename__ = "settings"
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key: Mapped[str] = mapped_column(String(100), primary_key=True)
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value: Mapped[dict[str, Any]] = mapped_column(default=dict)
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class McpServer(Base, TimestampMixin):
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__tablename__ = "mcp_servers"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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name: Mapped[str] = mapped_column(String(100), unique=True)
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transport: Mapped[str] = mapped_column(String(20), default="stdio") # stdio | http
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command: Mapped[str | None] = mapped_column(String(500), default=None)
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args: Mapped[list[Any]] = mapped_column(default=list)
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env: Mapped[dict[str, Any]] = mapped_column(default=dict)
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url: Mapped[str | None] = mapped_column(String(500), default=None)
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enabled: Mapped[bool] = mapped_column(default=True)
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# 最近一次探活的结果与工具清单缓存
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status: Mapped[str] = mapped_column(String(20), default="unknown")
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last_error: Mapped[str | None] = mapped_column(Text, default=None)
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tools_cache: Mapped[list[Any]] = mapped_column(default=list)
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class CustomTool(Base, TimestampMixin):
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"""用户自定义工具：HTTP 调用模板，或跑在沙箱里的一段 Python。"""
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__tablename__ = "custom_tools"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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name: Mapped[str] = mapped_column(String(100), unique=True)
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description: Mapped[str] = mapped_column(Text, default="")
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kind: Mapped[str] = mapped_column(String(20), default="http") # http | python
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parameters: Mapped[dict[str, Any]] = mapped_column(default=dict) # JSON Schema
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config: Mapped[dict[str, Any]] = mapped_column(default=dict)
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enabled: Mapped[bool] = mapped_column(default=True)
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# --------------------------------------------------------------------------
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# 工作流与版本
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# --------------------------------------------------------------------------
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class Workflow(Base, TimestampMixin):
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__tablename__ = "workflows"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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name: Mapped[str] = mapped_column(String(200))
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description: Mapped[str] = mapped_column(Text, default="")
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graph: Mapped[dict[str, Any]] = mapped_column(default=dict) # {nodes, edges, viewport}
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tags: Mapped[list[Any]] = mapped_column(default=list)
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version: Mapped[int] = mapped_column(Integer, default=1)
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is_template: Mapped[bool] = mapped_column(default=False)
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# 治理状态机：draft（随便改）→ published（有正式版本可跑）→ governed（发布需过治理 lint）
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status: Mapped[str] = mapped_column(String(20), default="draft")
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# 正式运行默认解析到这个版本；为空表示还没发布过
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published_version: Mapped[int | None] = mapped_column(Integer, default=None)
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published_by: Mapped[str | None] = mapped_column(String(100), default=None)
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versions: Mapped[list["WorkflowVersion"]] = relationship(
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back_populates="workflow", cascade="all, delete-orphan", lazy="selectin"
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)
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class WorkflowVersion(Base, TimestampMixin):
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"""每次保存留一份快照，便于回滚和对比不同编排的效果。"""
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__tablename__ = "workflow_versions"
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__table_args__ = (UniqueConstraint("workflow_id", "version"),)
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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workflow_id: Mapped[str] = mapped_column(ForeignKey("workflows.id", ondelete="CASCADE"))
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version: Mapped[int] = mapped_column(Integer)
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graph: Mapped[dict[str, Any]] = mapped_column(default=dict)
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note: Mapped[str] = mapped_column(Text, default="")
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# 图内容的 sha256 指纹（剔除 viewport）。formal run 钉住的就是它。
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graph_hash: Mapped[str | None] = mapped_column(String(64), default=None)
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workflow: Mapped[Workflow] = relationship(back_populates="versions")
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# --------------------------------------------------------------------------
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# 运行、事件、审批
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# --------------------------------------------------------------------------
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class Run(Base, TimestampMixin):
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__tablename__ = "runs"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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workflow_id: Mapped[str | None] = mapped_column(
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ForeignKey("workflows.id", ondelete="SET NULL"), default=None
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)
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workflow_name: Mapped[str] = mapped_column(String(200), default="")
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# LangGraph checkpointer 的 thread_id —— 持久化与恢复的锚点
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thread_id: Mapped[str] = mapped_column(String(64), index=True, default=new_id)
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# queued | running | interrupted | succeeded | failed | cancelled
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status: Mapped[str] = mapped_column(String(20), default="queued", index=True)
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graph: Mapped[dict[str, Any]] = mapped_column(default=dict) # 执行时的图快照
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input: Mapped[dict[str, Any]] = mapped_column(default=dict)
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output: Mapped[dict[str, Any]] = mapped_column(default=dict)
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error: Mapped[str | None] = mapped_column(Text, default=None)
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usage: Mapped[dict[str, Any]] = mapped_column(default=dict) # tokens / cost / 各节点耗时
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started_at: Mapped[datetime | None] = mapped_column(default=None)
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finished_at: Mapped[datetime | None] = mapped_column(default=None)
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last_seq: Mapped[int] = mapped_column(Integer, default=0)
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# formal：从不可变的 WorkflowVersion 发起，可复现、可出具
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# exploratory：画布试跑 / 裸 graph / 追问，结果只标探索性
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run_class: Mapped[str] = mapped_column(String(20), default="exploratory")
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version: Mapped[int | None] = mapped_column(Integer, default=None)
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version_hash: Mapped[str | None] = mapped_column(String(64), default=None)
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# 结束时对全部事件计算的清单哈希，事后改动事件流会被它戳穿
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manifest_hash: Mapped[str | None] = mapped_column(String(64), default=None)
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started_by: Mapped[str | None] = mapped_column(String(100), default=None)
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events: Mapped[list["RunEvent"]] = relationship(
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back_populates="run", cascade="all, delete-orphan"
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)
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class RunEvent(Base):
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"""完整事件流落库 —— 这既是 trace，也是页面刷新后重建时间线的依据。"""
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__tablename__ = "run_events"
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__table_args__ = (Index("ix_run_events_run_seq", "run_id", "seq"),)
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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run_id: Mapped[str] = mapped_column(ForeignKey("runs.id", ondelete="CASCADE"))
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seq: Mapped[int] = mapped_column(Integer, default=0)
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type: Mapped[str] = mapped_column(String(40))
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node_id: Mapped[str | None] = mapped_column(String(64), default=None)
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ts: Mapped[float] = mapped_column(Float)
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data: Mapped[dict[str, Any]] = mapped_column(default=dict)
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run: Mapped[Run] = relationship(back_populates="events")
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class Approval(Base, TimestampMixin):
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"""一次人工介入请求。对应 LangGraph 的 interrupt。"""
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__tablename__ = "approvals"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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run_id: Mapped[str] = mapped_column(ForeignKey("runs.id", ondelete="CASCADE"), index=True)
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node_id: Mapped[str] = mapped_column(String(64))
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interrupt_id: Mapped[str | None] = mapped_column(String(64), default=None)
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mode: Mapped[str] = mapped_column(String(20), default="approve") # approve | input | edit
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title: Mapped[str] = mapped_column(String(300), default="")
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payload: Mapped[dict[str, Any]] = mapped_column(default=dict) # 给人看的上下文
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schema_: Mapped[dict[str, Any]] = mapped_column("schema", default=dict)
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status: Mapped[str] = mapped_column(String(20), default="pending", index=True)
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response: Mapped[dict[str, Any]] = mapped_column(default=dict)
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resolved_at: Mapped[datetime | None] = mapped_column(default=None)
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# 责任归属：谁批的。没有 actor 的治理是空转。
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resolved_by: Mapped[str | None] = mapped_column(String(100), default=None)
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class Artifact(Base, TimestampMixin):
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"""工件引用表。
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文件本体按内容哈希存在 data/artifacts/ 下（同内容只一份）；
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这张表记录"哪个 run 的哪个节点产出了它"——溯源需要的正是这层归属。
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复合主键：同一工件被多个 run 产出时各记一行引用。
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"""
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__tablename__ = "artifacts"
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__table_args__ = (Index("ix_artifacts_run", "run_id"),)
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id: Mapped[str] = mapped_column(String(64), primary_key=True)
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run_id: Mapped[str] = mapped_column(String(32), primary_key=True, default="")
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kind: Mapped[str] = mapped_column(String(32), default="node_output") # node_output | tool_snapshot | metric_set
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node_id: Mapped[str | None] = mapped_column(String(64), default=None)
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size: Mapped[int] = mapped_column(Integer, default=0)
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meta: Mapped[dict[str, Any]] = mapped_column(default=dict)
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# --------------------------------------------------------------------------
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# 记忆、知识库、Skill
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# --------------------------------------------------------------------------
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class MemoryItem(Base, TimestampMixin):
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"""长期记忆。scope 用来隔离不同 agent / 会话的记忆空间。"""
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__tablename__ = "memories"
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__table_args__ = (Index("ix_memories_scope_kind", "scope", "kind"),)
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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scope: Mapped[str] = mapped_column(String(100), default="default")
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kind: Mapped[str] = mapped_column(String(32), default="fact") # fact | preference | episode
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content: Mapped[str] = mapped_column(Text)
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meta: Mapped[dict[str, Any]] = mapped_column(default=dict)
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embedding: Mapped[bytes | None] = mapped_column(LargeBinary, default=None)
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importance: Mapped[float] = mapped_column(Float, default=0.5)
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last_used_at: Mapped[datetime | None] = mapped_column(default=None)
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use_count: Mapped[int] = mapped_column(Integer, default=0)
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class Document(Base, TimestampMixin):
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"""知识库里的一份原始文档。"""
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__tablename__ = "documents"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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collection: Mapped[str] = mapped_column(String(100), default="default", index=True)
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title: Mapped[str] = mapped_column(String(300), default="")
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source: Mapped[str] = mapped_column(String(500), default="") # 文件名 / URL
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mime: Mapped[str] = mapped_column(String(100), default="text/plain")
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content: Mapped[str] = mapped_column(Text, default="")
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meta: Mapped[dict[str, Any]] = mapped_column(default=dict)
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chunk_count: Mapped[int] = mapped_column(Integer, default=0)
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chunks: Mapped[list["Chunk"]] = relationship(
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back_populates="document", cascade="all, delete-orphan"
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)
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class Chunk(Base):
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__tablename__ = "chunks"
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__table_args__ = (Index("ix_chunks_collection", "collection"),)
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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document_id: Mapped[str] = mapped_column(ForeignKey("documents.id", ondelete="CASCADE"))
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collection: Mapped[str] = mapped_column(String(100), default="default")
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ordinal: Mapped[int] = mapped_column(Integer, default=0)
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content: Mapped[str] = mapped_column(Text)
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embedding: Mapped[bytes | None] = mapped_column(LargeBinary, default=None)
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meta: Mapped[dict[str, Any]] = mapped_column(default=dict)
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document: Mapped[Document] = relationship(back_populates="chunks")
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class Skill(Base, TimestampMixin):
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"""可复用的方法论：一段指令 + 可选的示例和推荐工具。
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节点可以挂载 skill，运行时把内容注入 system prompt —— 把"怎么做事"
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从工作流结构里抽出来单独管理和迭代。
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"""
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__tablename__ = "skills"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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name: Mapped[str] = mapped_column(String(100), unique=True)
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description: Mapped[str] = mapped_column(Text, default="")
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instructions: Mapped[str] = mapped_column(Text, default="")
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examples: Mapped[list[Any]] = mapped_column(default=list)
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suggested_tools: Mapped[list[Any]] = mapped_column(default=list)
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tags: Mapped[list[Any]] = mapped_column(default=list)
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enabled: Mapped[bool] = mapped_column(default=True)
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