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ThearchyHelios
dcadc0c48b
三条 run（d983c4e6 / 14103db5 / 08c3de1c）在用户看来是一次对话，系统里却
毫无关联。查下来不是哪里传漏了，是整层缺失：
- 每轮 base_graph=None 从零建图，Copilot 不知道上一轮问过什么
- 每轮 thread_id = run.id，三条独立的 checkpoint 线程
- 前端 turns 只活在 zustand 里，刷新页面就全没了——那三轮当时在界面上
已经找不回来，只剩 runs 表里三条互不相干的记录
- 后端 13 张表里没有会话这个概念
加两张表（conversations / conversation_turns）。失败的轮次也记：只记成功的，
历史就成了一份美化过的记录，而人回来最想搞清楚的恰恰是上次卡在哪。
Copilot 的上下文带三样：前几轮问答、上一轮那张图（走 _slim 去掉坐标噪音）。
只给问答文字不够——"再按月份拆一下"会让模型重新设计一张图，实测经常接到另
一张表上，答案对不上前一轮。运行时另外注入 {{ input.history }}，管的是指代：
用户问"它们平均多少"，图里的 agent 得知道"它们"是上一轮那 12 家店。
左侧会话栏只在问数据页出现，可折叠、可改名删除，当前会话存 localStorage。
轮次按会话分桶缓存——切走再切回来要看得到原来的步骤，回源只拿得到问答。
历史轮次的执行过程不预加载，点「看执行过程」才取事件、走现成的 decodeRun。
画布右栏的 Copilot 依附工作流各有一条会话，连说两次"再加一个节点"能接上了
（base_graph 带的是图的结果，带不出"你刚才要我干什么"），但不进左侧列表。
过程中修掉的两个自己引入的坑：
- 第一版在列表为空时自动建一条会话。create 是异步的、StrictMode 把 effect
跑两遍，于是每次进页面都留下两三条"新对话"。改成用户开口那一刻按需建
- 加了"在上一轮的图上改"这条指令之后，模型照改图协议只发 update_node，
而问数据页这条路径的累加器从空图起步，操作全部落空，用户收到的是
"图校验未通过：图是空的，先拖一个节点进来"（会话 f5db9809 的第二轮，
而它的 explanation 证明上下文其实完全读懂了）。指令改成沿用 id 和 config
但完整重发，另加一道兜底：空图且上一轮有图时把操作重放到那张图上
check-ui 多一节「会话」：切换、刷新还在、逛一圈不多出空会话。
387 lines
19 KiB
Python
387 lines
19 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 (
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DateTime, Float, ForeignKey, Index, Integer, LargeBinary, String, Text, UniqueConstraint,
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)
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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, utcnow
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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 DataSource(Base, TimestampMixin):
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"""一个数据库接入点。password 落库前经 app.core.crypto 加密，和 Provider 同一套。
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readonly 默认为真，是刻意的安全基线：这里的 SQL 由模型生成，不是人写的。
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要写库就另建一个显式关掉只读的源，并且写操作会走人工审批——把"能写"这件事
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变成一个需要两次明确动作的决定，而不是默认状态。
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"""
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__tablename__ = "data_sources"
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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)) # mysql | postgres | oracle | sqlite
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host: Mapped[str | None] = mapped_column(String(255), default=None)
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port: Mapped[int | None] = mapped_column(Integer, default=None)
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database: Mapped[str | None] = mapped_column(String(255), default=None)
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username: Mapped[str | None] = mapped_column(String(128), default=None)
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password: Mapped[str | None] = mapped_column(Text, default=None) # 密文
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# 驱动差异塞这里：Oracle 的 service_name/sid、MySQL 的 charset、SSL 参数…
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# 不给每种数据库加一列，否则表会长成各家方言的并集
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options: Mapped[dict[str, Any]] = mapped_column(default=dict)
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readonly: Mapped[bool] = mapped_column(default=True)
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# 给 Copilot 看的一句话："销售库，含订单/客户/产品"。它据此判断该查哪个源
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description: Mapped[str] = mapped_column(Text, default="")
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# 探查到的表结构。缓存下来，否则每次建图都要连一次生产库
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schema_cache: Mapped[dict[str, Any]] = mapped_column(default=dict)
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schema_synced_at: Mapped[datetime | None] = mapped_column(default=None)
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enabled: Mapped[bool] = mapped_column(default=True)
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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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# --------------------------------------------------------------------------
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# 会话：把一串问答串成一次对话
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# --------------------------------------------------------------------------
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class Conversation(Base, TimestampMixin):
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"""一次对话。
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在此之前"对话"只是前端内存里的一个数组：刷新页面就没了，而每一轮又各自
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从零建图、各起一条 checkpoint 线程，所以"上一轮问过什么"在系统里根本
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无处可查。追问「再按月份拆一下」会重新找一遍数据源，可能接到别的表。
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落成一张表之后，它同时承担两件事：给用户看的历史列表，和给模型看的上下文。
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kind 分两种，因为这两件事像但不是一回事：
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chat —— 问数据页，一轮 = 一次「建图 → 跑图 → 出答案」，进左侧列表
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canvas —— 画布右栏的 Copilot，依附某张图，一轮 = 一次改图，不进列表
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"""
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__tablename__ = "conversations"
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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title: Mapped[str] = mapped_column(String(200), default="")
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kind: Mapped[str] = mapped_column(String(20), default="chat", index=True)
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workflow_id: Mapped[str | None] = mapped_column(
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ForeignKey("workflows.id", ondelete="CASCADE"), default=None, index=True
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)
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archived: Mapped[bool] = mapped_column(default=False)
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# 列表按活跃度排。不能用 updated_at —— 改个标题就会把这条顶到最前面，
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# 而用户对"最近聊过的"的预期是按说话时间排，不是按编辑时间
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last_active_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True), default=utcnow, index=True
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)
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turns: Mapped[list["ConversationTurn"]] = relationship(
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back_populates="conversation",
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cascade="all, delete-orphan",
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order_by="ConversationTurn.seq",
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)
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class ConversationTurn(Base, TimestampMixin):
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"""一轮问答。
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run_id 可以为空：建图阶段就失败时压根没有 run，但这一轮仍然发生过，
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用户也该在历史里看到它失败了——只记成功的轮次，历史就成了一份美化过的
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记录，而人再回来时最想搞清楚的恰恰是上次卡在哪。
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"""
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__tablename__ = "conversation_turns"
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__table_args__ = (Index("ix_conversation_turns_conv_seq", "conversation_id", "seq"),)
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id: Mapped[str] = mapped_column(String(32), primary_key=True, default=new_id)
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conversation_id: Mapped[str] = mapped_column(
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ForeignKey("conversations.id", ondelete="CASCADE"), index=True
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)
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seq: Mapped[int] = mapped_column(Integer, default=0)
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question: Mapped[str] = mapped_column(Text, default="")
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answer: Mapped[str] = mapped_column(Text, default="")
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# Copilot 对这张图的说明。画布那条路径上只有它，没有 answer
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explanation: Mapped[str] = mapped_column(Text, default="")
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graph: Mapped[dict[str, Any] | None] = mapped_column(default=None)
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run_id: Mapped[str | None] = mapped_column(
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ForeignKey("runs.id", ondelete="SET NULL"), default=None
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||
)
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||
# running | done | error
|
||
status: Mapped[str] = mapped_column(String(20), default="running")
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error: Mapped[str] = mapped_column(Text, default="")
|
||
|
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conversation: Mapped[Conversation] = relationship(back_populates="turns")
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