mirror of
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ThearchyHelios
680 lines
35 KiB
TypeScript
680 lines
35 KiB
TypeScript
import { useEffect, useState } from 'react'
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import type { JSX } from 'react'
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import { createRoot } from 'react-dom/client'
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import { BrowserRouter } from 'react-router-dom'
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import { Database, MessageSquare, RotateCw } from 'lucide-react'
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import { AssistantStream, StreamEmpty, type StreamTurn } from '../run/AssistantStream'
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import { Markdown } from '../run/Markdown'
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import { ApprovalCard } from '../run/RunPanel'
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import { withTask } from './taskOf'
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import { decodeCopilot, decodeRun } from '../run/decode'
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import { catalogPatchesOf } from '../run/catalogPatch'
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import { ToastHost } from '../components/ui'
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import type { RunEvent } from '../types'
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import fixtures from '../run/__tests__/fixtures.json'
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import mdSamples from '../run/__tests__/markdown-samples.json'
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import evidenceFixture from '../run/__tests__/evidence-doc.json'
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import evidenceJudge from '../run/__tests__/evidence-judge.json'
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import {
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CALIBER_ONE_OUTPUT, CALIBERS_OUTPUT, SQL_DEGRADED_OUTPUT, COPILOT_CATALOG_PATCH, COPILOT_CONTEXT, COPILOT_CONTEXT_FALLBACK, COPILOT_STUCK, COPILOT_TOOLS_DROPPED, MIXED_OUTPUT, abandonedRun, cancelledRun, exhaustedTeam, longLoop,
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markupRun, mergeRun, mixedRun, parallelQueryRun, pipelineRun, repairRun, teamRun, timeoutRun,
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} from '../run/__tests__/synthetic'
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import '../index.css'
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/**
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* AssistantStream 的离线预览。
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*
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* 只有 dev server 会加载（vite build 的 input 只有 index.html），所以它不进
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* 生产包。存在的理由：要改这个组件的排版，不该每次都真跑一次图——真跑一次
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* 意味着要连数据库、等模型、还得凑巧撞上人工介入分支才能看到审批卡长什么样。
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* 这里用的是真实导出的事件（fixtures.json）和照后端字段合成的事件
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* （synthetic.ts），走的是同一个 decodeRun，只有事件来源是静态的。
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*
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* 打开 http://localhost:5273/preview.html；scripts/check-stream.mjs 按下面这些
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* 查询参数逐个打开截图、断言。
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*/
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type Bucket = keyof typeof fixtures
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/**
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* 各功能自带的预览用例：dev/fixtures/*.tsx 各自导出 cases（用例名 → 组件），?syn=<用例名> 先在这里找，
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* 找不到再走下面 synthetic() 里的用例。新功能加预览只加自己的文件，不用改这里——几个工作包同时加用例，
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* 不会在这一个文件上互相冲突。写法见 dev/fixtures/_example.tsx
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*/
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type FixtureCases = Record<string, () => JSX.Element>
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const FIXTURE_CASES: FixtureCases = {}
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for (const [file, mod] of Object.entries(import.meta.glob<{ cases?: FixtureCases }>('./fixtures/*.tsx', { eager: true }))) {
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for (const [name, render] of Object.entries(mod.cases ?? {})) {
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if (name in FIXTURE_CASES) console.warn(`预览用例重名：${name}（${file} 盖掉了先加载的那个）`)
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FIXTURE_CASES[name] = render
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}
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}
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const CASES: { key: Bucket; question: string; phase: StreamTurn['phase']; status: string }[] = [
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{ key: 'db', question: '这个库里有多少数据？挑最大的表说说', phase: 'done', status: '已完成' },
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{ key: 'think', question: '分析上季度华东区销量下滑的原因', phase: 'running', status: '运行中' },
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{ key: 'human', question: '把这批客户的信用额度调高 10%', phase: 'waiting', status: '等待审批' },
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{ key: 'issue', question: '出一份本月经营分析', phase: 'done', status: '已完成' },
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{ key: 'failed', question: '查一下不存在的那张表', phase: 'error', status: '' },
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{ key: 'loop_approve', question: '写条上线公告，我过一眼再发', phase: 'done', status: '已完成' },
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{ key: 'supervisor', question: '冬虫夏草是什么', phase: 'done', status: '已完成' },
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]
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function buildTurns(): StreamTurn[] {
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return CASES.map((c) => {
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const events = (fixtures as any)[c.key] as any[]
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const steps = decodeRun(events)
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const finished = events.find((e) => e.type === 'run.finished')
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const failed = events.find((e) => e.type === 'run.failed')
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return {
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id: c.key,
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question: c.question,
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phase: c.phase,
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status: c.status,
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steps,
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thinking: c.phase === 'running'
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? '先看一下 ANALYTICS 里有哪些和销量相关的视图，再按区域和月份聚合……'
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: undefined,
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output: finished?.data?.output ?? null,
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error: failed ? String(failed.data?.error ?? '运行失败') : undefined,
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runId: events[0]?.run_id,
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}
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})
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}
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/**
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* 合成事件的 ts 固定在过去某一刻，拿来演"进行中"时秒表会显示几天。
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* 整体平移到"最后一条是 lagMs 之前"，实时计时就是一个合理的数
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*/
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function rebase(events: RunEvent[], lagMs = 3200): RunEvent[] {
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const last = events[events.length - 1]?.ts ?? 0
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const shift = (Date.now() - lagMs) / 1000 - last
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return events.map((e) => ({ ...e, ts: e.ts + shift }))
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}
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/**
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* 一段恶意输入。这类测例必须是构造的——真实输出不会自带攻击，但模型输出
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* 是不可信内容，渲染层要么天生免疫，要么就是个 XSS 口子。
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*/
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const HOSTILE = [
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'正常文本 **加粗**。',
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'',
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'<script>window.__pwned = 1</script>',
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'<img src=x onerror="window.__pwned=1">',
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'[点我](javascript:window.__pwned=1)',
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'[正常链接](https://example.com)',
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'<iframe src="https://evil.example"></iframe>',
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'`<script>alert(1)</script>`',
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].join('\n')
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/**
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* 一份会超出折叠上限的报告，表格正好横跨切点。
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*
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* 之前折叠是按字符硬切的，切点落进表格中间——前面几行渲染成表格、最后半行
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* 留成原始的 `| 1 | ThearchyHelios | …`。用户看到的是一份被咬掉一口的报告，
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* 而它其实是完整的，只是被折叠了。
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*/
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function longReport(): string {
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const head = [
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"## 总结", "",
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"- **管理员（平台级/区域级角色）**：共 9 人", "- **商家账户**：共 5 个", "",
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"口径说明：".padEnd(400, "口"), "",
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"## 一、管理员名单", "",
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].join("\n")
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const rows = Array.from({ length: 40 }, (_, i) =>
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`| ${i + 1} | user_${i} | user${i}@example.com | 昵称${i} | ` +
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`85e11976-6a7b-4167-b561-deec4fd${String(i).padStart(4, "0")} | 商家 ${i} | c${i}@example.com |`)
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return [
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head,
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"| userID | 用户名 | 邮箱 | 昵称 | providerID | 商家名称 | 联系人邮箱 |",
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"| --- | --- | --- | --- | --- | --- | --- |",
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...rows,
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"", "> 说明：部分账户身兼管理员与商家双重身份。",
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].join("\n")
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}
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/** 直接回答的那一轮：没查库，界面上必须说破 */
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const NO_QUERY_TURN: StreamTurn = {
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id: "noquery", question: "刚才那 6 个管理员是怎么算的？", phase: "done", status: "已完成",
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steps: [], noQuery: true,
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output: { answer: "第 1 轮走的是 `role.level IN (platform, regional)` 这个口径。要换口径我重新查一遍。" },
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}
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/** 复核判了「不可信」：说明排在成果上方，且用报警色 */
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const REVIEW_BROKEN_TURN: StreamTurn = {
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id: "reviewbroken", question: "商家账户有多少个？", phase: "done", status: "已完成",
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steps: [],
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review: {
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verdict: "annotated", severity: "broken", retry: true,
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note: "这次取数没跑通（表名对不上），下面这个数是模型根据上下文推断的，不能当结论用。",
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answer: null,
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signals: [
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{ kind: "tool_error", severity: "broken",
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detail: "工具 db_query__shop 调用失败：no such table: merchant_account" },
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{ kind: "step_limit", severity: "broken", detail: "Agent 已用完 8 步上限，仍未给出结论" },
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],
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},
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output: { answer: "大约 5 个左右。" },
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}
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/** 复核只是补了一句说明，答案照常给；外加改写前的原文可展开 */
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const REVIEW_DEGRADED_TURN: StreamTurn = {
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id: "reviewdegraded", question: "谁能改别人的权限？", phase: "done", status: "已完成",
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steps: [],
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review: {
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verdict: "rewritten", severity: "degraded", retry: false,
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note: "这次知识库检索退回了纯关键词匹配，换了说法的内容可能没被搜到。",
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answer: null,
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signals: [
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{ kind: "retrieve_degraded", severity: "degraded",
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detail: "重排失败，已按初筛顺序返回" },
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],
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},
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output: { answer: "只有平台管理员可以修改他人权限，且需要走角色变更流程。" },
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rawOutput: { answer: "平台管理员可以修改他人权限。" },
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}
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/** 协作团队的泳道：前两轮并行、第三轮汇总 */
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const TEAM_TURN: StreamTurn = {
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id: "team", question: "比较三种向量数据库在中文检索上的取舍", phase: "done", status: "已完成",
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steps: [{
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id: "n-team", seq: 1, kind: "node", status: "done", title: "调研团队", meta: "24.1 s", ms: 24100,
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team: {
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members: ["researcher", "analyst", "writer"],
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savedMs: 11800,
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finished: true,
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rounds: [
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{
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round: 0, parallel: 2, wallMs: 9600, sumMs: 16400,
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reason: "两边资料互不相干，可以同时查",
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members: [
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{ agent: "researcher", instruction: "查 Milvus 与 Qdrant 的中文分词支持", ms: 9600,
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status: "done", result: "Milvus 2.4 起内置 jieba…" },
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{ agent: "analyst", instruction: "查 pgvector 的中文检索方案", ms: 6800,
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status: "done", result: "pgvector 本身不分词，需配 zhparser…" },
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],
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},
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{
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round: 1, parallel: 2, wallMs: 7400, sumMs: 12400,
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reason: "两组基准测试互不依赖",
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members: [
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{ agent: "researcher", instruction: "跑召回率基准", ms: 7400, status: "done",
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result: "hit@1：Milvus 0.91 / Qdrant 0.89 / pgvector 0.84" },
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{ agent: "analyst", instruction: "跑写入吞吐基准", ms: 5000, status: "done",
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result: "10 万条：Milvus 42s / Qdrant 51s / pgvector 88s" },
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],
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},
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{
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round: 2, parallel: 1, wallMs: 7100, sumMs: 7100,
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reason: "两份基准都出来了，可以汇总",
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members: [
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{ agent: "writer", instruction: "根据前面的结论写选型建议", ms: 7100,
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status: "done", result: "## 结论\n中文为主且要开箱即用 → Milvus…" },
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],
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},
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],
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},
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}],
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output: { 建议: "中文为主且要开箱即用选 Milvus；已有 Postgres 且数据量在百万以内，pgvector + zhparser 的运维成本最低。" },
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}
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const LONG_TURN: StreamTurn = {
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id: "long", question: "需要能够显示总结内容", phase: "done", status: "已完成",
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steps: [], output: { result: longReport() },
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}
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/**
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* 带逐段证据的一轮：口径卡 → 报告撰写 → 成果（_evidence 标注了「周报」字段）。报告文档和
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* 片段接口由 check-stream 用 page.route 伪造（/api/artifacts/<doc>、…/evidence/segments/…）。
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* 后面跟一轮同样的答案、但没有 _evidence：旧运行就是这样，渲染必须和普通 Markdown 一模一样
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*/
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function evidenceTurns(): StreamTurn[] {
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const fx = evidenceFixture
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const E = (seq: number, type: string, node_id: string | null, data: Record<string, any> = {}): RunEvent =>
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({ seq, type, node_id, ts: 1790000000 + seq, data })
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const events = [
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E(1, 'run.started', null, { total: 3 }),
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E(2, 'node.started', 'caliber', { node_type: 'metrics', label: '周报口径' }),
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E(3, 'node.finished', 'caliber', { duration_ms: 12, preview: { kind: 'metric_set', caliber: '周报口径' } }),
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E(4, 'node.started', 'write', { node_type: 'report', label: '写周报' }),
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E(5, 'report.checked', 'write', fx.report_checked),
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E(6, 'node.finished', 'write', { duration_ms: 2300 }),
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E(7, 'node.started', 'out', { node_type: 'output', label: '成果' }),
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E(8, 'node.finished', 'out', { duration_ms: 3 }),
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E(9, 'run.finished', null, { output: {} }),
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]
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const text = fx.output['周报']
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return [
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{ id: 'evidence', question: '写一份本周周报', phase: 'done', status: '已完成', runClass: 'exploratory',
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steps: decodeRun(events, { status: 'succeeded' }), output: fx.output, runId: fx.run_id },
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{ id: 'evidence-legacy', question: '写一份本周周报（旧运行）', phase: 'done', status: '已完成',
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steps: [], output: { 周报: text }, runId: 'syn-evidence-legacy' },
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]
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}
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/**
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* 四期：结论句裁判走问数据页、画布右栏同一条路（Output → EvidenceField → 出具横幅）。
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* - judge-plain：探索运行、报告没开裁判（require_citation）。点开结论句请模型判断之后，横幅得多出「结论 N 句」那一段；
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* - judge-formal：正式运行、报告 claims=judge，节点里判好了。没挂依据的那句送了裁判（到上限没判），出具照样按没挂依据记缺口。
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* 报告工件、片段接口、按需裁判的 POST 由 check-evidence 用 page.route 伪造（夹具 evidence-judge.json）
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*/
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function evidenceJudgeTurns(): StreamTurn[] {
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const { plain, formal } = evidenceJudge
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return [
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{ id: 'judge-plain', question: '写一份本周周报', phase: 'done', status: '已完成', runClass: 'exploratory',
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steps: [], output: plain.output, runId: plain.run_id },
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{ id: 'judge-formal', question: '写一份本周周报（受管模板）', phase: 'done', status: '已完成', runClass: 'formal',
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steps: [], output: formal.output, runId: formal.run_id },
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]
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}
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/** 合成场景：新后端才有的事件，老库里导不出来 */
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function synthetic(name: string): StreamTurn[] {
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switch (name) {
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case 'evidence':
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return evidenceTurns()
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case 'evidence-judge':
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return evidenceJudgeTurns()
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case 'team-live': {
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const ev = rebase(teamRun('members'))
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return [{ id: 'team-live', question: '比较三家供应商的交期风险', phase: 'running', status: '运行中',
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steps: decodeRun(ev), runId: 'syn-team-live' }]
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}
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case 'team-cancelled': {
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// 第 1 轮三人都还在跑时被取消：那一轮不知道本来要多久
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const ev = rebase(teamRun('members').filter((e) =>
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!(e.data?.agent === '物流员' && (e.type === 'agent.step.end' || e.type === 'llm.end'))))
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const last = ev[ev.length - 1]
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ev.push({ seq: last.seq + 1, type: 'run.cancelled', node_id: null, ts: last.ts + 1, data: {} })
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return [{ id: 'team-cancelled', question: '比较三家供应商的交期风险', phase: 'done', statusCode: 'cancelled',
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steps: decodeRun(ev), runId: 'syn-team-cancelled' }]
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}
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case 'team-routing': {
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const ev = rebase(teamRun('routing'))
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return [{ id: 'team-routing', question: '比较三家供应商的交期风险', phase: 'running', status: '运行中',
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steps: decodeRun(ev), runId: 'syn-team-routing' }]
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}
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case 'team': {
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const ev = teamRun('done')
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return [{ id: 'team-done', question: '比较三家供应商的交期风险', phase: 'done', status: '已完成',
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steps: decodeRun(ev), output: ev[ev.length - 1].data.output, runId: 'syn-team-done' }]
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}
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case 'long': {
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const ev = longLoop(145)
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return [{ id: 'long-loop', question: '逐拍读取传感器，跑完这一批', phase: 'done', status: '已完成',
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steps: decodeRun(ev), output: ev[ev.length - 1].data.output, runId: 'syn-long' }]
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}
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case 'mixed': {
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const ev = mixedRun()
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const end = ev[ev.length - 1].data
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return [{ id: 'mixed', question: '9 月 19 日各班次出勤率', phase: 'error', status: '失败',
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steps: decodeRun(ev), output: MIXED_OUTPUT, runId: 'syn-mixed', runClass: 'exploratory',
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error: { error: String(end.error), detail: end.detail } }]
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}
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case 'issued': {
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// 同一份出具，跑完的样子：横幅、正文里画出来的数字、复制 / 导出
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const ev = mixedRun().filter((e) => e.type !== 'node.failed' && e.type !== 'run.failed')
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return [{ id: 'issued', question: '9 月 19 日各班次出勤率', phase: 'done', status: '已完成',
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steps: decodeRun(ev, { status: 'succeeded' }), output: MIXED_OUTPUT, runId: 'syn-issued',
|
||
runClass: 'exploratory', review: REVIEW_DEGRADED_TURN.review }]
|
||
}
|
||
case 'issued-sql':
|
||
// 数字都有出处，却因为查询没通过 SQL 检查而降档：横幅单列说明
|
||
return [{ id: name, question: '上周订单金额', phase: 'done', status: '已完成',
|
||
steps: decodeRun(parallelQueryRun(), { status: 'succeeded' }), runId: 'syn-issued-sql', runClass: 'formal',
|
||
output: SQL_DEGRADED_OUTPUT }]
|
||
case 'calibers':
|
||
case 'caliber-one': {
|
||
// 按口径卡清点回指的数字：两张卡各数各的；只有一张卡时直说都来自它
|
||
return [{ id: name, question: '上周订单情况', phase: 'done', status: '已完成',
|
||
steps: decodeRun(pipelineRun(2), { status: 'succeeded' }), runId: `syn-${name}`, runClass: 'formal',
|
||
output: name === 'calibers' ? CALIBERS_OUTPUT : CALIBER_ONE_OUTPUT }]
|
||
}
|
||
case 'live': {
|
||
// 取数正在进行：第一条查询还没回来
|
||
const all = mixedRun()
|
||
const cut = all.findIndex((e) => e.type === 'tool.end' && e.data.call_id === 'q1')
|
||
const ev = rebase(all.slice(0, cut), 12400)
|
||
return [{ id: 'live', question: '9 月 19 日各班次出勤率', phase: 'running', status: '运行中',
|
||
steps: decodeRun(ev), runId: 'syn-live' }]
|
||
}
|
||
case 'cancelled':
|
||
return [{ id: 'cancelled', question: '把大表全量拉一遍', phase: 'done', statusCode: 'cancelled',
|
||
steps: decodeRun(cancelledRun()), runId: 'syn-cancel' }]
|
||
case 'chat': {
|
||
// 问数据的一轮：先建图（按需查看了两张表：look 事件）、再执行。执行开始后「规划」收成一行
|
||
const plan = decodeCopilot([
|
||
{ op: 'heartbeat', phase: 'looking', elapsed_ms: 1800 },
|
||
{ op: 'look', id: 'L1', by: 'model', need: '设备 KPI 和设备维度', status: 'ok', elapsed_ms: 2100, objects: [
|
||
{ kind: 'table', source: 'warehouse', source_id: 'src-warehouse', named: [], picked: ['v_device_kpi', 'dim_device'],
|
||
joined: [], missing: [], total: 53 }] },
|
||
{ op: 'heartbeat', phase: 'planning', elapsed_ms: 6400 },
|
||
{ op: 'thinking', delta: '要先查表结构，再按设备汇总 KPI。' },
|
||
{ op: 'plan', summary: '取数 → 汇总 → 出结论' },
|
||
{ op: 'add_node', node: { id: 'q', type: 'tool', label: '查询设备 KPI' } },
|
||
{ op: 'add_node', node: { id: 'o', type: 'output', label: '成果' } },
|
||
{ op: 'done', explanation: '两步' },
|
||
{ op: 'final', graph: { nodes: [{ id: 'q' }, { id: 'o' }] } },
|
||
])
|
||
const ev = (fixtures as any).db as RunEvent[]
|
||
return [{ id: 'chat', question: '这个库里有多少数据？挑最大的表说说', phase: 'done', status: '已完成',
|
||
steps: [...plan, ...decodeRun(ev)], runId: 'syn-chat',
|
||
output: ev[ev.length - 1].data.output,
|
||
graph: { nodes: [{ id: 'q', type: 'tool', data: { label: '查询设备 KPI' } },
|
||
{ id: 'o', type: 'output', data: { label: '成果' } }] } }]
|
||
}
|
||
case 'copilot-context':
|
||
// 大库按需求挑表：过程里一行「参考了 N 张表」，展开按数据源分组列表名
|
||
return [{ id: 'copilot-context', question: '各渠道上月的入园人次', phase: 'done', status: '已应用到画布',
|
||
steps: decodeCopilot(COPILOT_CONTEXT, { context: 'canvas' }) }]
|
||
case 'catalog-patch':
|
||
// 用户说了一条数据事实：助手只回答、不改图，附一张「建议更新数据目录」卡片
|
||
return [{ id: 'catalog-patch', question: 'status=9 表示作废，统计时要排除', phase: 'done', status: '已回答（未修改画布）',
|
||
steps: decodeCopilot(COPILOT_CATALOG_PATCH, { context: 'canvas' }),
|
||
output: { 回答: '好的，已整理成数据目录的修改建议，确认后保存即可。' },
|
||
catalogPatches: catalogPatchesOf(COPILOT_CATALOG_PATCH) }]
|
||
case 'copilot-fallback':
|
||
return [{ id: 'copilot-fallback', question: '各渠道上月的入园人次', phase: 'done', status: '已应用到画布',
|
||
steps: decodeCopilot(COPILOT_CONTEXT_FALLBACK, { context: 'canvas' }) }]
|
||
case 'copilot':
|
||
return [{ id: 'copilot', question: '做一个每天的出勤日报', phase: 'done',
|
||
status: '已应用到画布，仍有 2 处问题待处理',
|
||
steps: decodeCopilot(COPILOT_STUCK, { context: 'canvas' }) }]
|
||
case 'codes':
|
||
// 编号、分组长得像数：'1063'、'001'。它们不该右对齐，也不该出「按 attribute_group 从高到低排」
|
||
return [{ id: 'codes', question: '各产线本周产量', phase: 'done', status: '已完成', steps: [],
|
||
output: { 结果: JSON.stringify({
|
||
columns: ['factory_code', 'line_name', 'attribute_group', 'output_qty'],
|
||
rows: [['1063', '一号线', '001', 1520], ['1064', '二号线', '002', 1310], ['1065', '三号线', '001', 980]],
|
||
row_count: 3 }) } }]
|
||
case 'parallel':
|
||
// 两个并行的查询节点用同一个工具；第一条查询没通过 SQL 检查，口径卡的问题指到它的 SQL
|
||
return [{ id: 'parallel', question: '订单金额和退款数', phase: 'done', status: '已完成',
|
||
steps: decodeRun(parallelQueryRun(), { status: 'succeeded' }) }]
|
||
case 'merge':
|
||
// 合并查询：两个库各查一次、在库外按门店合并，带两道警告（键类型不一致、行数放大）
|
||
return [{ id: 'merge', question: '按门店合并销售和到店人数', phase: 'done', status: '已完成',
|
||
steps: decodeRun(mergeRun(), { status: 'succeeded' }) }]
|
||
case 'schema': {
|
||
const ev = mixedRun().slice(0, 10)
|
||
return [{ id: 'schema', question: '看看有哪些人事表', phase: 'done', status: '已完成',
|
||
steps: decodeRun(ev, { status: 'succeeded' }) }]
|
||
}
|
||
// ---- 平台问题的几种结局（NI-3/4/5）：失败的轮次把 run.failed 的原话交给流，和运行页、画布右栏一样
|
||
case 'exhausted':
|
||
case 'markup':
|
||
case 'repair': {
|
||
const ev = name === 'exhausted' ? exhaustedTeam('fail') : name === 'markup' ? markupRun() : repairRun()
|
||
const end = ev[ev.length - 1].data
|
||
return [{ id: name, question: '上月各区域订单额', phase: 'error', steps: decodeRun(ev), runId: `syn-${name}`,
|
||
error: { error: String(end.error), ...(end.detail ? { detail: end.detail } : {}) } }]
|
||
}
|
||
case 'exhausted-degrade': {
|
||
const ev = exhaustedTeam('degrade')
|
||
return [{ id: 'exhausted-degrade', question: '上月各区域订单额', phase: 'done', steps: decodeRun(ev),
|
||
output: { 结论: ev[ev.length - 1].data.output.结论, _issuance: {
|
||
tier: 'degraded', calibers: [], metrics_checked: 0, matched_numbers: 0, unmatched_numbers: [],
|
||
missing_required: [], missing_expected: [],
|
||
gaps: ['协作团队「销售分析团队」用完 2 轮仍未完成，交付的是成员最后的回复'] } },
|
||
runId: 'syn-exhausted-degrade', runClass: 'exploratory' }]
|
||
}
|
||
case 'exhausted-closing': {
|
||
const ev = rebase(exhaustedTeam('closing'))
|
||
return [{ id: 'exhausted-closing', question: '上月各区域订单额', phase: 'running', steps: decodeRun(ev),
|
||
runId: 'syn-exhausted-closing' }]
|
||
}
|
||
case 'timeout-live': {
|
||
// 查询已经走了 34 秒，时限是 30 秒：秒表要说破「已超出上限」
|
||
const ev = rebase(timeoutRun('live'), 34000)
|
||
return [{ id: 'timeout-live', question: '把订单明细全拉出来', phase: 'running', steps: decodeRun(ev),
|
||
runId: 'syn-timeout-live' }]
|
||
}
|
||
case 'timeout':
|
||
return [{ id: 'timeout', question: '把订单明细全拉出来', phase: 'error', steps: decodeRun(timeoutRun('done')),
|
||
runId: 'syn-timeout', error: { error: '查询超过 30 秒没有返回，已停止等待（数据库可能仍在执行，连接会在后台回收）。请添加 WHERE 条件或 LIMIT 缩小范围后重试' } }]
|
||
case 'abandoned':
|
||
return [{ id: 'abandoned', question: '把这份报表发出去', phase: 'done', statusCode: 'cancelled',
|
||
steps: decodeRun(abandonedRun()), runId: 'syn-abandoned' }]
|
||
case 'structured':
|
||
// 页面已经把报错拆好了（问数据页的 Failure）：照原样画，不再翻译一遍
|
||
return [{ id: 'structured', question: '上周各区域订单数', phase: 'error', steps: [],
|
||
error: { title: '操作超时', reason: '查询超时：数据库 90 秒没有返回', hint: '缩小时间范围后点击「重试本轮」',
|
||
detail: 'OperationalError: (3024) maximum statement execution time exceeded' } }]
|
||
case 'restored':
|
||
// 从库里恢复的一轮：没有事件，查询次数由页面从落库的 meta 带过来
|
||
return [{ id: 'restored', question: '上周各区域订单数', phase: 'done', steps: [], queries: 3, elapsedMs: 8400,
|
||
output: { answer: '华东 1,204 单，华南 986 单，华北 731 单。' }, runId: 'syn-restored' }]
|
||
case 'tools-dropped':
|
||
return [{ id: 'tools-dropped', question: '只查上月的数据', phase: 'done', status: '已更新画布（修改 1）',
|
||
tone: 'warn', steps: decodeCopilot(COPILOT_TOOLS_DROPPED, { context: 'canvas' }) }]
|
||
default:
|
||
return []
|
||
}
|
||
}
|
||
|
||
/** Markdown 渲染用真实输出验，不用编的样本 */
|
||
function MarkdownCases() {
|
||
return (
|
||
<div className="mx-auto max-w-3xl space-y-4 p-4">
|
||
{[...(mdSamples as string[]), HOSTILE].map((t, i) => (
|
||
<div key={i} className="rounded-lg border bg-panel p-3">
|
||
<div className="mb-2 text-2xs text-dim">真实输出 #{i + 1}</div>
|
||
<Markdown text={t} />
|
||
</div>
|
||
))}
|
||
</div>
|
||
)
|
||
}
|
||
|
||
/**
|
||
* 一条在长的运行：window.__grow(n) 再放出 n 条事件。check-stream 用它验证
|
||
* 「往上翻着看的时候不被拽回底部、底下浮出跳到最新」
|
||
*/
|
||
function Growing({ dense }: { dense: boolean }) {
|
||
const [all] = useState(() => pipelineRun(60))
|
||
const [n, setN] = useState(60)
|
||
useEffect(() => {
|
||
;(window as any).__grow = (k: number) => setN((x) => Math.min(all.length, x + k))
|
||
}, [all.length])
|
||
const ev = rebase(all.slice(0, n))
|
||
return (
|
||
<AssistantStream dense={dense} turns={[{
|
||
id: 'grow', question: '把这批报表各查一遍', phase: 'running', status: '运行中',
|
||
steps: decodeRun(ev), runId: 'syn-grow',
|
||
}]} />
|
||
)
|
||
}
|
||
|
||
/**
|
||
* 几轮已经完成的对话，执行过程按需取回：window.__expand(i) 给第 i 轮填上步骤，和问数据页点
|
||
* 「看执行过程」一样。check-stream 用它验证取回的历史步骤不算「新进展」、也不把人拽走
|
||
*/
|
||
function Expanding({ dense, n }: { dense: boolean; n: number }) {
|
||
const [open, setOpen] = useState<number[]>([])
|
||
useEffect(() => {
|
||
;(window as any).__expand = (i: number) => setOpen((x) => [...x, i])
|
||
}, [])
|
||
const turns: StreamTurn[] = Array.from({ length: n }, (_, i) => ({
|
||
id: `past-${i}`, question: `第 ${i + 1} 个问题：把这批报表各查一遍`, phase: 'done', status: '已完成',
|
||
steps: open.includes(i) ? decodeRun(pipelineRun(12), { status: 'succeeded' }) : [],
|
||
output: { result: longReport() }, runId: `syn-past-${i}`,
|
||
}))
|
||
return <AssistantStream dense={dense} turns={turns} />
|
||
}
|
||
|
||
/** 审批卡的上下文：等了多久、挂在哪个节点、将以谁的名义签批 */
|
||
const APPROVAL = {
|
||
id: 'ap-1', run_id: 'syn-mixed', node_id: 'review', mode: 'approve' as const,
|
||
title: '出勤结论可以发出吗？', status: 'pending', response: {},
|
||
payload: { kind: 'human_node', message: '早班出勤率 **94.23%**，晚班 **73.08%**。' },
|
||
created_at: new Date(Date.now() - 8 * 86_400_000 - 3_600_000).toISOString().replace('Z', ''),
|
||
workflow_name: '出勤日报', node_label: '班长复核', run_class: 'formal' as const,
|
||
}
|
||
|
||
/**
|
||
* ?approval=report：探索运行里审一份报告。核对概况取 evidence-doc 夹具（7/12 数字有出处、1 处引用解析不了），
|
||
* 报告没开结论句裁判；?approval=report-formal：正式运行，节点里判过，1 句证据相矛盾
|
||
*/
|
||
const APPROVAL_REPORT = {
|
||
id: 'ap-2', run_id: evidenceFixture.run_id, node_id: 'review', mode: 'approve' as const,
|
||
title: '本周周报可以发出吗？', status: 'pending', response: {},
|
||
payload: {
|
||
kind: 'human_node', message: '请审核本周周报。',
|
||
reports: [{ node_id: 'write', label: '写周报', stats: evidenceFixture.doc.stats, claims: 'off',
|
||
doc_artifact: evidenceFixture.doc_artifact }],
|
||
},
|
||
created_at: new Date(Date.now() - 120_000).toISOString().replace('Z', ''),
|
||
workflow_name: '周报', node_label: '主管审批', run_class: 'exploratory' as const,
|
||
}
|
||
const APPROVAL_REPORT_FORMAL = {
|
||
...APPROVAL_REPORT, id: 'ap-3', run_class: 'formal' as const,
|
||
payload: {
|
||
...APPROVAL_REPORT.payload,
|
||
reports: [{ ...APPROVAL_REPORT.payload.reports[0], claims: 'judge', stats: { ...evidenceFixture.doc.stats, numbers_cited: 12, uncited_numbers: 0, unresolved: 0 },
|
||
judge: { mode: 'inline', counts: { supported: 5, contradicted: 1, unjudged: 0 }, complete: true } }],
|
||
},
|
||
}
|
||
|
||
function Preview() {
|
||
// ?case=db 只看一个用例，?theme=light 直接出浅色——都是为了截图可复现，
|
||
// 不用靠点按钮
|
||
const params = new URLSearchParams(location.search)
|
||
const only = params.get('case')
|
||
const syn = params.get('syn')
|
||
const md = params.get('md') === '1'
|
||
const theme = params.get('theme')
|
||
if (theme === 'light' || theme === 'dark') document.documentElement.dataset.theme = theme
|
||
if (params.get('actor') != null) {
|
||
try { localStorage.setItem('agentlab_actor', params.get('actor') ?? '') } catch { /* 预览里没有也行 */ }
|
||
}
|
||
const dense = params.get('dense') === '1'
|
||
const [all] = useState(buildTurns)
|
||
const turns = only ? all.filter((t) => t.id === only) : all
|
||
const [denseToggle, setDense] = useState(false)
|
||
const [emptyState, setEmptyState] = useState(false)
|
||
// ?follow=1：真实用例也出追问标签，看它从真实结果集里派生出什么
|
||
const onFollowUp = params.get('follow') === '1'
|
||
? (q: string) => { (window as any).__followUp = q } : undefined
|
||
|
||
const empty = (
|
||
<StreamEmpty
|
||
icon={<MessageSquare size={22} />}
|
||
title="问你的数据"
|
||
hint="用一句话描述需求，助手会自动连接数据源、编写查询并给出结论，无需操作画布"
|
||
/>
|
||
)
|
||
|
||
if (md) return <div className="h-full overflow-y-auto"><MarkdownCases /></div>
|
||
if (params.get('grow') === '1') return <Growing dense={dense} />
|
||
if (params.get('expand')) return <Expanding dense={dense} n={Number(params.get('expand')) || 1} />
|
||
const approvalCase = params.get('approval')
|
||
if (approvalCase === '1' || approvalCase === 'report' || approvalCase === 'report-formal') {
|
||
const approval = approvalCase === 'report' ? APPROVAL_REPORT : approvalCase === 'report-formal' ? APPROVAL_REPORT_FORMAL : APPROVAL
|
||
return (
|
||
<div className={dense ? 'w-[360px] border-r' : 'mx-auto max-w-3xl p-4'}>
|
||
<div className="overflow-hidden rounded-lg border" style={{ borderColor: 'var(--warn)' }}>
|
||
<ApprovalCard approval={withTask(approval)} onResolved={() => undefined} />
|
||
</div>
|
||
</div>
|
||
)
|
||
}
|
||
if (syn) {
|
||
// 当组件渲染，不直接调用：用例里可以用 hook
|
||
const Fixture = FIXTURE_CASES[syn]
|
||
if (Fixture) return <Fixture />
|
||
const linked: string[] = ((window as any).__linked ??= [])
|
||
const stream = (
|
||
<AssistantStream
|
||
dense={dense}
|
||
turns={synthetic(syn)}
|
||
onStepHover={params.get('link') === '1' ? (id) => { (window as any).__hovered = id } : undefined}
|
||
onStepFocus={params.get('link') === '1' ? (id) => { linked.push(id) } : undefined}
|
||
// 「打开设置」：记下要打开哪个节点、落到哪一栏（指标的问题落到来源查询的 SQL）
|
||
onStepOpen={params.get('link') === '1'
|
||
? (id, field) => { ((window as any).__opened ??= []).push([id, field ?? null]) } : undefined}
|
||
renderTurnActions={(t) => (t.phase === 'error'
|
||
? <button type="button" className="btn btn-xs"><RotateCw size={11} aria-hidden /> 重试本轮</button>
|
||
: null)}
|
||
onFollowUp={(q) => { (window as any).__followUp = q }}
|
||
/>
|
||
)
|
||
// 证据场景另摆一份同样文字的普通 Markdown：没有 _evidence 的那一轮必须和它长得一模一样
|
||
const baseline = syn === 'evidence' && (
|
||
<div id="md-baseline" hidden><Markdown text={evidenceFixture.output['周报']} dense={dense} /></div>
|
||
)
|
||
return dense
|
||
? <div className="h-full w-[360px] border-r bg-panel">{stream}{baseline}</div>
|
||
: <>{stream}{baseline}</>
|
||
}
|
||
if (params.get('long') === '1') {
|
||
return <AssistantStream turns={[LONG_TURN]} />
|
||
}
|
||
if (params.get('noquery') === '1') {
|
||
return <AssistantStream turns={[NO_QUERY_TURN]} />
|
||
}
|
||
if (params.get('review') === '1') {
|
||
return <AssistantStream turns={[REVIEW_BROKEN_TURN, REVIEW_DEGRADED_TURN]} />
|
||
}
|
||
if (params.get('fanout') === '1') {
|
||
return <AssistantStream dense={dense} turns={[{
|
||
id: 'fanout', question: '三个库各查一遍，汇总给我', phase: 'done', status: '已完成',
|
||
steps: decodeRun((fixtures as any).fanout),
|
||
output: { 结果: '三路都回来了' },
|
||
}]} />
|
||
}
|
||
if (params.get('team') === '1') {
|
||
return <AssistantStream turns={[TEAM_TURN]} dense={dense} />
|
||
}
|
||
|
||
return (
|
||
<div className="flex h-full flex-col">
|
||
<header className="flex items-center gap-3 border-b px-4 py-2 text-xs">
|
||
<Database size={14} style={{ color: 'var(--accent)' }} />
|
||
<span className="font-semibold">AssistantStream 预览</span>
|
||
<span className="text-dim">真实事件 · 离线渲染</span>
|
||
<span className="flex-1" />
|
||
<label className="flex items-center gap-1.5 text-dim">
|
||
<input type="checkbox" checked={denseToggle} onChange={(e) => setDense(e.target.checked)} />
|
||
dense（360px 窄栏）
|
||
</label>
|
||
<label className="flex items-center gap-1.5 text-dim">
|
||
<input type="checkbox" checked={emptyState}
|
||
onChange={(e) => setEmptyState(e.target.checked)} />
|
||
空态
|
||
</label>
|
||
<button className="btn btn-sm btn-ghost"
|
||
onClick={() => {
|
||
const el = document.documentElement
|
||
el.dataset.theme = el.dataset.theme === 'light' ? 'dark' : 'light'
|
||
}}>
|
||
切主题
|
||
</button>
|
||
</header>
|
||
|
||
<div className="flex min-h-0 flex-1">
|
||
{/* 宽屏：问数据页的形态 */}
|
||
<div className="min-w-0 flex-1 border-r">
|
||
<AssistantStream turns={emptyState ? [] : turns} dense={denseToggle} empty={empty}
|
||
onFollowUp={onFollowUp} />
|
||
</div>
|
||
{/* 窄栏：画布右侧助手栏的形态。固定 360px，和真实右栏一致 */}
|
||
<div className="w-[360px] shrink-0 bg-panel">
|
||
<AssistantStream turns={emptyState ? [] : turns} dense empty={empty} onFollowUp={onFollowUp} />
|
||
</div>
|
||
</div>
|
||
</div>
|
||
)
|
||
}
|
||
|
||
// 预览引用了 store（审批卡要用），别人改 store 时 HMR 会把这个入口重新执行一遍，
|
||
// 同一个容器上再 createRoot 会报错
|
||
const w = window as any
|
||
w.__previewRoot ??= createRoot(document.getElementById('root')!)
|
||
w.__previewRoot.render(
|
||
<BrowserRouter>
|
||
<ToastHost>
|
||
<Preview />
|
||
</ToastHost>
|
||
</BrowserRouter>,
|
||
)
|