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ThearchyHelios
271bc6e782
真实模型下问「上周的销售额是多少」，助手写 SUM(amount) AS 销售额, COUNT(*) AS 订单数, MIN / MAX(paid_date) AS 区间首日 /
末日，报告四列都引用了，口径「周销售」只取 SUM(amount)。按「全部引用列」投影后还是 4 列，对不上口径的 1 列，整条比、
四个数都标相关口径，说明整段兜底。
- ledger/match._cells / _cell（algo 4）：整条（含按全部引用列投影）没证明、又引用了这条查询两列以上的，被引用的每一列单独
投影到那一列，和每份口径的每个指标读的那一列（card_reads；口径版本没有口径卡的按取数的每一列）逐个比，仍只走
match_template / explain_sql_diff，上次的投影规则照用：投影不了（分组列、DISTINCT……）、过了时限、不可比的格照用整条
查询的那一个候选。结果记在 queries[].cells {列名: {status, candidates}}，另记 one_row（sql_semantics.one_row：不分组的
聚合，一定只出一行）。整条这一层的结论、候选一字不改；老工件没有 cells，照旧按整条读。
- ledger/labels：单元格按它那一格的结论标（_view）；指标用了同一条查询的好几格时，只有那条查询一定只出一行才把逐格的
结论合起来用（多行的结果里每一列各自对得上，不等于每一行的几列一起对得上）。整题照拍板 L1 不变：每个数都证明来自
同一份口径才等价；一格证明了、别的格只是相关的整题不等价，原因写「有的数和相关口径不一致，不来自口径」（以前一律说
「这次的推理」）。出具入口照 ledger/issue 现有判法只在整题等价时给，没有放宽。
- 逐格证明了的口径各处都算上（labels.candidates_of）：工件 meta 的 calibers（召回按旧版本反查）、ledger/uses 的使用记录、
召回时找原答案对应的那一格、E4；E1 另数各种结论各几格（cells），E2 的兜底比例按标签上给人看的那一份说明数。
- GET /runs/{id}/ledger 的 queries 带上逐格的 cells（遮罩同候选）；证据片段的 ledger 键、轮次摘要的计数本来就按每个数的
标签，数据变了、形状不变。前端只补类型；check-ledger 加一段：同一条查询一格来自口径（正文挂小标记）、一格相关（差在哪
先说多查了几列），整题不等价不给出具。
- 评测逐题比 SQL（eval/score.sql_match）取和期望配上的那一格（score.matched_cells：评分时配上的格），没给时取逐格证明了
的那一格；结果带 column。runner、rescore 传它。
测试：tests/test_ledger_cells.py（同一条查询一列等价、一列不等价各自标对；两份口径只证明了一份标那一份；口径多个指标按列
配对；指标跨两格只在一行的查询上用逐格结论；分组列、DISTINCT 逐格也不投影；照真实例子造的虚构库真跑一遍：销售额标等价
已证明，订单数、首末日标相关，整题不等价、不给出具、不自动出具，证据片段的 ledger 键一致；评测取配上的那一格）。去掉逐格
再跑，10 条失败；去掉「一行才合起来用」、去掉评测取格，各 1 条失败。
177 lines
13 KiB
JavaScript
177 lines
13 KiB
JavaScript
// 口径账本的检查夹具（check-ledger、check-evidence、check-chat 共用）：GET /api/runs/{id}/ledger 的答复形状照服务端
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// app/ledger/view.py 的 run_view（labels.view_label、issue.Plan.action、reconcile.actions_of / reconciled_view），
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// 挂在可点击证据的夹具（frontend/src/run/__tests__/evidence-doc.json，compose_doc 真跑出来的周报，只用通用名）上：
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// s6「45,678.5元」来自受管口径「周报口径」v2，等价已证明；s10「1,234单」来自已发布口径「订单口径」v1，助手选用；
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// s8「8.7%」相关口径「订单口径」v1（差在哪：少了一个筛选条件），可以对账；s12「37.0元」这次的推理；
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// s23「2.35%」没有比对（比对超时）。
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// 口径名、表名、数都是虚构的通用名。
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/** 口径的几份（calibers） */
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export const WEEKLY = { caliber: 'wf-weekly@2', workflow_id: 'wf-weekly', version: 2, level: 'governed', level_text: '受管',
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workflow_name: '周报口径', graph_hash: 'aa11' }
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export const ORDERS = { caliber: 'wf-orders@1', workflow_id: 'wf-orders', version: 1, level: 'published', level_text: '已发布',
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workflow_name: '订单口径', graph_hash: 'bb22' }
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const caliberLabel = (c, how, extra = {}) => ({
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kind: 'caliber', how, caliber: c.caliber, workflow_id: c.workflow_id, version: c.version, level: c.level,
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level_text: c.level_text, workflow_name: c.workflow_name, ...extra,
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})
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export const DIFF = { items: [{ aspect: 'filter', a: null, b: "status = '[已遮罩]'", text: '口径只保留状态为已支付的行，这次没有这个条件' }],
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fallback: false, text_diff: [] }
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/** 一份比对过的账本。whole：整题判断（缺省不等价）；actions、issued、reconciled 可以换 */
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export function ledgerOf(runId, { whole, actions, issued = [], reconciled = [], retro = false, labels } = {}) {
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return {
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run_id: runId, state: 'matched', note: '封存后比对，不在封存范围内', post_seal: true, artifact: 'cm-1', algo: 'v1',
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trigger: retro ? 'on_demand' : 'sealed', retro, matched_at: '2026-10-15T01:00:00+00:00',
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...(retro ? { retro_note: '按现在的口径回看' } : {}),
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calibers: [WEEKLY, ORDERS],
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queries: [
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{ artifact: 'q-gmv', node_id: 'ag', source: 'shop', tables: ['orders'], status: 'proven',
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candidates: [{ ...WEEKLY, node_id: 'fetch', status: 'proven', how: 'independent' }] },
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{ artifact: 'q-orders', node_id: 'ag', source: 'shop', tables: ['orders'], status: 'related',
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candidates: [{ ...ORDERS, node_id: 'fetch', status: 'related', comparable: true, via: 'heuristic', diff: DIFF,
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binding: [{ field: 'start', value: '2026-09-01' }] }] },
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],
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reports: { write: { labels: labels ?? {
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s6: caliberLabel(WEEKLY, 'independent', { binding: [{ field: 'week', value: '2026-W37' }], card: 'caliber', metric: 'gmv',
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queries: ['q-gmv'] }),
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s10: caliberLabel(ORDERS, 'composed', { binding: [{ field: 'store', masked: true, value: '已遮罩' }], card: 'caliber',
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metric: 'orders', queries: ['q-gmv'] }),
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s8: { kind: 'related', related: [{ caliber: ORDERS.caliber, workflow_id: ORDERS.workflow_id, version: 1, level: 'published',
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level_text: '已发布', workflow_name: '订单口径', node_id: 'fetch' }], queries: ['q-orders'] },
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s12: { kind: 'reasoning', query: 'q-gmv' },
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s23: { kind: 'unknown', reason: '比对超过时限，没有做完', query: 'q-gmv' },
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} } },
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primary: 'write',
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whole: whole ?? { equivalent: false, reason: '有的数是这次的推理', counts: { caliber: 2, related: 1, reasoning: 1, unknown: 1 } },
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actions: actions ?? [RECONCILE],
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issued, reconciled,
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}
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}
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/**
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* 答案身上的召回标记（服务端 ledger/recall.answer_marks）：周报口径升到 v3 重算过、数没变（同一份口径核对过两次，只写最近
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* 那一版）；目录里影响数字的两项被驳回、按新目录检查新出现 1 条错误级问题，另有一次出现了新码值（同归「数据目录」那一类，
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* 项数相加）；看的这个人手上有一条说的是这个答案的 recall 待办（订单口径升到 v2，数变了）
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*/
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export const RECALL = {
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checked: [
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{ workflow_id: 'wf-weekly', workflow_name: '周报口径', from_version: 1, to_version: 2, recall_run: 'run-rc0', changed: false,
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at: '2026-10-14T01:00:00+00:00' },
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{ workflow_id: 'wf-weekly', workflow_name: '周报口径', from_version: 2, to_version: 3, recall_run: 'run-rc1', changed: false,
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at: '2026-10-15T01:00:00+00:00' },
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],
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basis: [
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{ kind: 'catalog', items: 2, new_errors: 1, at: '2026-10-15T02:00:00+00:00' },
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{ kind: 'values', items: 1, new_errors: 0, at: '2026-10-15T03:00:00+00:00' },
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],
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tasks: [{ id: 'tk-recall-1', reason: 'caliber', to_version: 2 }],
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}
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/** 看差多少（s8 那条查询、订单口径）：参数是推断的，要先核对 */
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export const RECONCILE = {
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kind: 'reconcile', query: 'q-orders', caliber: ORDERS.caliber, workflow_id: ORDERS.workflow_id, version: 1, node_id: 'fetch',
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workflow_name: '订单口径', level_text: '已发布', needs_check: true, check_reason: '参数按这次的 SQL 推断，请核对',
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binding: [{ field: 'start', value: '2026-09-01' }], fallback: false,
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fields: [{ name: 'start', required: true, has_default: false }, { name: 'store', required: false, has_default: true }],
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}
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/** 按口径正式出具（整题等价于周报口径）：搭建者能一键，不自动的原因写在 auto_reason */
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export const ISSUE = {
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kind: 'issue', workflow_id: WEEKLY.workflow_id, version: 2, caliber: WEEKLY.caliber, workflow_name: '周报口径', how: 'independent',
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level: 'governed', level_text: '受管', available: true, auto: false, auto_reason: '设置里关了自动按口径出具',
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}
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/** 整题等价时的标签（三个数都来自周报口径） */
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export const WHOLE_LABELS = {
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s6: caliberLabel(WEEKLY, 'independent', { binding: [{ field: 'week', value: '2026-W37' }], queries: ['q-gmv'] }),
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s10: caliberLabel(WEEKLY, 'independent', { binding: [{ field: 'week', value: '2026-W37' }], queries: ['q-gmv'] }),
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s12: caliberLabel(WEEKLY, 'independent', { binding: [{ field: 'week', value: '2026-W37' }], queries: ['q-gmv'] }),
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}
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export const WHOLE = { equivalent: true, caliber: WEEKLY.caliber, workflow_id: WEEKLY.workflow_id, version: 2, level: 'governed',
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level_text: '受管', workflow_name: '周报口径', how: 'independent', binding: [{ field: 'week', value: '2026-W37' }],
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missing: [], missing_required: [], counts: { caliber: 3, related: 0, reasoning: 0, unknown: 0 } }
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/**
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* 逐格判（服务端 ledger/match._cells，algo 4）的真实例子：同一条查询（q-gmv）报告引用了好几列，s6 销售额那一格证明了
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* 等价于周报口径，s10 订单数那一格只是相关（差在哪先说多查了几列、再说计数对求和），整题不等价、没有出具入口
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*/
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export const CELL_DIFF = { items: [
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{ aspect: 'projection', a: null, b: null, text: '这次多查了 3 列，不影响这个数' },
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{ aspect: 'aggregate', a: 'COUNT(*)', b: 'SUM(amount)', text: '这次数的是行数，口径对 amount 求和' }],
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fallback: false, text_diff: [] }
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export const CELL_LABELS = {
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s6: caliberLabel(WEEKLY, 'independent', { binding: [{ field: 'start', value: '2026-10-05' }, { field: 'end', value: '2026-10-11' }],
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query: 'q-gmv', node_id: 'fetch', column: 'gmv' }),
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s10: { kind: 'related', query: 'q-gmv', related: [{ caliber: WEEKLY.caliber, workflow_id: WEEKLY.workflow_id, version: 2,
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level: 'governed', level_text: '受管', workflow_name: '周报口径',
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node_id: 'fetch', comparable: true, diff: CELL_DIFF }] },
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}
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export const CELL_WHOLE = { equivalent: false, reason: '有的数和相关口径不一致，不来自口径',
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counts: { caliber: 1, related: 1, reasoning: 0, unknown: 0 } }
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/** 对过的一次账（单行：一组对照）。status 可以换 */
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export const reconciledOf = (status = 'succeeded') => ({
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run_id: 'run-rec-1', status, query: 'q-orders', caliber: ORDERS.caliber, workflow_id: ORDERS.workflow_id, version: 1,
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inputs_from: 'checked', rows: null, card: 'reconcile',
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groups: [{ label: '订单数', ours: 'ours_0', caliber: 'cal_0', diff: 'diff_0', rel: 'rel_0' }], created_at: '2026-10-15T02:00:00Z',
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})
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/** 对账卡上四个指标的展示值（/evidence/metrics/reconcile/{id} 的 rendered） */
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export const RECONCILE_VALUES = { ours_0: '1,234单', cal_0: '1,180单', diff_0: '54单', rel_0: '4.58%' }
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/** 对账运行的指标出处（形状同片段接口：chain、seal），给 EvidenceDrawer 画 */
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export const metricDetail = (runId, metric) => ({
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run_id: runId, node: 'reconcile', metric, rendered: RECONCILE_VALUES[metric] ?? '—', eid: `ev:metric:${metric}`,
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chain: [{ step: 'metric', alias: 'm', metric, name: metric, value: 1, rendered: RECONCILE_VALUES[metric], node_id: 'reconcile',
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caliber: '口径对账', version: 'v1', expression: 'cell(nodes.ours_q1, 0, \'orders\')', sealed: true, inputs: [] }],
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seal: { sealed: true, ok: true, covered: true }, redacted: { columns: [] },
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})
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/**
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* 对账卡上「按口径」那个数的出处（服务端 api/evidence._upstream_steps 的形状）：它转抄口径卡的指标
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* （nodes.card.metrics[0].value），出处跨卡接上口径卡「订单数」那一步，再到口径的取数查询（q-cal-fetch）
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*/
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export const copiedMetricDetail = (runId, metric) => ({
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run_id: runId, node: 'reconcile', metric, rendered: RECONCILE_VALUES[metric] ?? '—', eid: `ev:metric:${metric}`,
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chain: [
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{ step: 'metric', alias: 'm', metric, name: '订单数 · 口径', value: 1180, rendered: RECONCILE_VALUES[metric], node_id: 'reconcile',
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caliber: '口径对账', version: 'v1', expression: 'nodes.card.metrics[0].value', substituted: '1180', recompute_ok: true,
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sealed: true, hash_ok: true, untraced: [],
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inputs: [{ path: 'nodes.card.metrics[0].value', value: 1180, node_id: 'card', via: 'metric', field: 'metrics[0].value',
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status: 'ok', upstream: { metric: 'orders', artifact: 'ms-card', depth: 1, traced: true } }] },
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{ step: 'upstream', of: 'nodes.card.metrics[0].value', node_id: 'card', label: '口径卡', artifact: 'ms-card', metric: 'orders',
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traced: true, depth: 1, hash_ok: true, sealed: true, name: '订单数', value: 1180, unit: '单', rendered: '1,180单',
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caliber: '订单口径', version: 'v1', expression: "cell(nodes.fetch, 0, 'orders')", substituted: '1180', recompute_ok: true,
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status: 'ok', untraced: [],
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inputs: [{ step: 'input', path: "cell(nodes.fetch, 0, 'orders')", value: 1180, node_id: 'fetch', via: 'tool_cell',
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status: 'verified', artifact: 'q-cal-fetch', locator: { row: 0, column: 'orders' }, eid: 'ev:cell:q-cal-fetch' }] },
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{ step: 'query', alias: null, artifact: 'q-cal-fetch', node_id: 'fetch', tool: 'db_query__shop', source: 'shop',
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sql: "SELECT COUNT(*) AS orders FROM orders WHERE status = 'paid'", columns: ['orders'], rows: [[1180]], row_offset: 0,
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row_index: [0], total_rows: 1, highlight: { rows: [0], cols: ['orders'], cells: [[0, 'orders']] }, sealed: true, hash_ok: true },
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],
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seal: { sealed: true, ok: true, covered: true }, redacted: { columns: [] },
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})
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/** 认证队列：三类来源各一项 */
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export const QUEUE = {
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items: [
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{ id: 'shape:aa11', kind: 'shape', source: 'shop', shape: 'SELECT SUM(amount) FROM orders WHERE paid_at >= ? AND status = ?',
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runs: 4, conversations: 3, question: '上周销售额是多少',
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turns: [{ run_id: 'run-s1', conversation_id: 'c-1', turn_id: 't-1', question: '上周销售额是多少' },
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{ run_id: 'run-s2', conversation_id: 'c-2', turn_id: 't-2', question: '这周销售额是多少' }],
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params: [{ index: 0, distinct: 3 }], constants: 1, related: [{ caliber: ORDERS.caliber, workflow_id: ORDERS.workflow_id, version: 1, level: 'published' }],
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representative: { run_id: 'run-s1', query: 'q-1' }, peers: ['run-s2', 'run-s3'], frozen_into: [] },
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{ id: 'cluster:bb22', kind: 'cluster', question: '各门店的退款率', count: 3,
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turns: [{ run_id: 'run-c1', turn_id: 't-c1', question: '各门店的退款率' }, { run_id: 'run-c2', turn_id: 't-c2', question: '门店退款率怎么样' }],
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frozen_into: [] },
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{ id: 'reused:cc33', kind: 'reused', question: '本月新客数', uses: { exports: 2, app: false, extracted: false, canvas: true },
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turns: [{ run_id: 'run-r1', conversation_id: 'c-3', turn_id: 't-r1', question: '本月新客数' }],
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representative: { run_id: 'run-r1' }, frozen_into: [{ workflow_id: 'wf-new-old', name: '本月新客数（固化的口径草稿）', status: 'draft' }] },
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],
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considered: { runs: 120, matched: 100, questions: 90 },
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threshold: { runs: 3, conversations: 2, exports: 2 },
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}
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