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https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
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feat: 图片文字索引按时间分段优先处理最近图片
- 首次索引先处理最近 7 天，再依次回溯 30 天 / 近一年 / 更早历史 - 完成后新到的图片单独补齐，不受历史回填影响 - 覆盖度增加时间维度，可区分「最近已完整」与「更早仍在补齐」
This commit is contained in:
Wxw-Gu
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/**
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* 「recent-first 图片文字索引」的行为测试。
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*
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* 这一轮改的是**调度**：不再从最老的历史往下扫，而是先让"最近聊天的图片"可搜索。
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* 调度改动最容易骗人的地方是"看起来更快了，其实漏了东西"，所以这里的断言都落在
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* **可观察的结果**上（读了哪些窗口、处理了哪些消息、覆盖度怎么说），而不是内部变量。
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*
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* 被测的性质：
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* - 分段计划：互不重叠、无空隙，边界唯一；
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* - 处理顺序按时间分段从新到旧；
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* - 断点续跑不重复 OCR；
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* - 历史分段跑着的时候，新图片仍然优先；
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* - 覆盖度能按时间范围回答"这段能不能下确定性结论"；
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* - 老版本既有索引 / 旧 checkpoint 不被降级，源侧有新增时必须补上；
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* - UI 文案不暴露工程术语。
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*/
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import { mkdtempSync, rmSync } from 'node:fs'
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import { tmpdir } from 'node:os'
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import { join } from 'node:path'
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import { afterEach, describe, expect, it, vi } from 'vitest'
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import type * as chat from '../../src/main/services/chat-service'
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import { ImageTextIndexService } from '../../src/main/services/image-text-index-service'
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import {
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ImageTextIndexStore,
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getImageTextIndexDatabasePath
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} from '../../src/main/services/image-text-index-store'
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import { sourceMessageId } from '../../src/main/knowledge/message-identity'
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import {
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IMAGE_TEXT_BACKFILL_WINDOW_DAYS,
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buildImageTextBackfillSegments,
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describeImageTextRangeCoverage,
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imageTextPhaseLabel,
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imageTextRangeCoverage,
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imageTextWindowToSeconds,
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type ImageTextBackfillTier,
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type ImageTextIndexCoverage,
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type ImageTextTierRunState
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} from '../../src/shared/image-text-index'
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const ACCOUNT = 'wxid_recent_first_fixture'
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const CONVERSATION = 'conversation-fixture-md5'
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const DAY_MS = 24 * 60 * 60 * 1000
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const ANCHOR_MS = 1_800_000_000_000
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const roots: string[] = []
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afterEach(() => {
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for (const root of roots.splice(0)) {
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try {
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rmSync(root, { recursive: true, force: true })
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} catch {
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// 测试收尾尽力而为。
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}
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}
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})
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function makeDatabaseRoot(): string {
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const root = mkdtempSync(join(tmpdir(), 'tm-recent-first-'))
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roots.push(root)
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return root
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}
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function imageMessage(localId: number, createTimeSeconds: number): chat.FormattedMessage {
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return {
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localId: String(localId),
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createTime: createTimeSeconds,
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content: '[图片]',
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contentData: { type: 'image', md5: `md5-${localId}`, datName: `dat-${localId}` }
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} as unknown as chat.FormattedMessage
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}
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type Window = { sinceMs?: number; beforeMs?: number }
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interface HarnessState {
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messages: chat.FormattedMessage[]
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count: number
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maxLocalId: number
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now: number
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}
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interface HarnessResult {
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service: ImageTextIndexService
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databasePath: string
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state: HarnessState
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/** 每次向底层请求图片消息时记录的**时间边界**（不含分页上限）。 */
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windows: Window[]
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listImageMessages: ReturnType<typeof vi.fn>
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/** 真正"过了一遍处理"的图片数 —— 用它证明断点续跑没有重做。 */
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findImageFile: ReturnType<typeof vi.fn>
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}
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function inWindow(message: chat.FormattedMessage, window?: Window): boolean {
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const createTimeMs = (message.createTime || 0) * 1000
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if (window?.sinceMs !== undefined && createTimeMs < window.sinceMs) return false
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if (window?.beforeMs !== undefined && createTimeMs >= window.beforeMs) return false
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return true
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}
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function makeHarness(options: {
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messages: chat.FormattedMessage[]
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onWindow?: (window: Window | undefined, callIndex: number) => void
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}): HarnessResult {
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const databaseRoot = makeDatabaseRoot()
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const databasePath = getImageTextIndexDatabasePath(databaseRoot, ACCOUNT)
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const state = {
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messages: [...options.messages],
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count: options.messages.length,
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maxLocalId: options.messages.reduce((max, m) => Math.max(max, Number(m.localId) || 0), 0),
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now: ANCHOR_MS
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}
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const windows: Window[] = []
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const findImageFile = vi.fn(() => null)
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const listImageMessages = vi.fn(async (_conversationId: string, window?: Window) => {
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// 只记时间边界：调用方还会带一个分页上限，那与"读了哪个时间窗"无关。
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const bounds: Window = {}
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if (window?.sinceMs !== undefined) bounds.sinceMs = window.sinceMs
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if (window?.beforeMs !== undefined) bounds.beforeMs = window.beforeMs
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windows.push(bounds)
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options.onWindow?.(window, windows.length - 1)
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return state.messages.filter((message) => inWindow(message, window))
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})
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const service = new ImageTextIndexService()
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service.bind({
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databaseRoot,
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resolveAccountId: () => ACCOUNT,
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resolveAccountRoot: () => 'C:/fixture/account',
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now: () => state.now,
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listContacts: async () => [
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{ md5: CONVERSATION, m_nsUsrName: 'fixture', type: 'group' as const }
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],
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listImageMessages,
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// 窗口感知的计数：新架构"这段没图片就整段跳过"完全依赖它说实话。
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countConversationImages: async (_conversationId: string, window?: Window) => ({
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count: state.messages.filter((message) => inWindow(message, window)).length,
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typeColumn: 'local_type'
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}),
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imageWatermark: async () => ({ count: state.count, maxLocalId: state.maxLocalId }),
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// 没有解密能力 → 每张图片都会被判成 image_missing，测试完全不碰真实图片。
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decryptService: () => ({ findImageFile, decryptImage: () => null }) as never,
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capability: async () => ({
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available: true,
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engine: 'windows-system-ocr',
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platform: 'win32',
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runtimeVersion: '1.2.0',
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language: 'zh-Hans-CN'
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}),
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recognize: async () => ({ success: true, text: '', language: 'zh-Hans-CN' })
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})
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return { service, databasePath, state, windows, listImageMessages, findImageFile }
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}
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const bindingIds = (databasePath: string): string[] => {
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const store = new ImageTextIndexStore(databasePath, ACCOUNT)
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const ids = [...store.getConversationOcr(CONVERSATION).keys()]
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store.close()
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return ids
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}
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const tierStates = (
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databasePath: string
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): Partial<Record<ImageTextBackfillTier, ImageTextTierRunState>> => {
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const store = new ImageTextIndexStore(databasePath, ACCOUNT)
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const result = store.readBackfillState()
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store.close()
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return result.tierStates
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}
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const runPass = async (
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harness: HarnessResult,
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options?: Parameters<ImageTextIndexService['startPass']>[0]
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): Promise<void> => {
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harness.service.startPass(options)
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await vi.waitFor(() => expect(harness.service.isRunning()).toBe(false), { timeout: 15_000 })
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}
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/** 合成数据集：今天 / 3 天前 / 15 天前 / 6 个月前 / 3 年前，各 10 张。 */
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function syntheticDataset(anchorMs: number): {
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messages: chat.FormattedMessage[]
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byBucket: Map<string, number[]>
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} {
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const buckets: Array<{ key: string; offsetDays: number }> = [
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{ key: 'today', offsetDays: 0 },
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{ key: '3d', offsetDays: 3 },
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{ key: '15d', offsetDays: 15 },
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{ key: '6mo', offsetDays: 183 },
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{ key: '3y', offsetDays: 1095 }
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]
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const messages: chat.FormattedMessage[] = []
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const byBucket = new Map<string, number[]>()
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let localId = 1
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for (const bucket of buckets) {
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const ids: number[] = []
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const baseSeconds = Math.floor((anchorMs - bucket.offsetDays * DAY_MS) / 1000) - 60
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for (let index = 0; index < 10; index += 1) {
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messages.push(imageMessage(localId, baseSeconds + index))
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ids.push(localId)
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localId += 1
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}
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byBucket.set(bucket.key, ids)
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}
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return { messages, byBucket }
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}
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describe('分段计划：唯一边界、不重不漏', () => {
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it('四段从新到旧、相邻且互不重叠', () => {
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const segments = buildImageTextBackfillSegments(ANCHOR_MS)
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expect(segments.map((segment) => segment.tier)).toEqual([
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'recent_7d',
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'recent_30d',
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'recent_1y',
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'archive'
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])
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expect(segments[0].endMs).toBe(ANCHOR_MS)
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for (let index = 1; index < segments.length; index += 1) {
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// 上一段的上界必须等于下一段的下界：半开区间才既不重叠也不留缝。
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expect(segments[index].endMs).toBe(segments[index - 1].startMs)
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}
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expect(segments[2].startMs).toBe(
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ANCHOR_MS - IMAGE_TEXT_BACKFILL_WINDOW_DAYS.recent_1y * DAY_MS
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)
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// 归档段没有下界。
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expect(segments[3].startMs).toBe(Number.NEGATIVE_INFINITY)
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})
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it('边界那一秒只属于一段（两端同一套取整）', () => {
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const boundaryMs = ANCHOR_MS - 7 * DAY_MS
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const { beforeSecInclusive } = imageTextWindowToSeconds({ beforeMs: boundaryMs })
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const { sinceSec } = imageTextWindowToSeconds({ sinceMs: boundaryMs })
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// 上界段的"含"到 beforeSecInclusive，下界段从 sinceSec 起 —— 必须正好衔接。
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expect(sinceSec! - beforeSecInclusive!).toBe(1)
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})
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})
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describe('recent-first：合成数据集的真实处理顺序', () => {
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it('今天 / 3 天 → 15 天 → 6 个月前 → 3 年前，先新后旧', async () => {
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const harness = makeHarness({ messages: [] })
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const { messages, byBucket } = syntheticDataset(ANCHOR_MS)
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harness.state.messages = messages
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harness.state.count = messages.length
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harness.state.maxLocalId = Math.max(...messages.map((m) => Number(m.localId)))
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await runPass(harness)
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// 只有"有图片的分段"才会去读消息：今天+3 天 / 15 天 / 6 个月 / 3 年，共 4 次。
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expect(harness.windows).toHaveLength(4)
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const [first, second, third, fourth] = harness.windows
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expect(first).toEqual({ sinceMs: ANCHOR_MS - 7 * DAY_MS, beforeMs: ANCHOR_MS })
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expect(second).toEqual({ sinceMs: ANCHOR_MS - 30 * DAY_MS, beforeMs: ANCHOR_MS - 7 * DAY_MS })
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expect(third).toEqual({ sinceMs: ANCHOR_MS - 365 * DAY_MS, beforeMs: ANCHOR_MS - 30 * DAY_MS })
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expect(fourth).toEqual({ sinceMs: Number.NEGATIVE_INFINITY, beforeMs: ANCHOR_MS - 365 * DAY_MS })
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// 第一次读就拿到了"最近的图"—— 这正是用户要的价值。
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const ids = bindingIds(harness.databasePath)
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expect(ids).toHaveLength(50)
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const recentIds = [...byBucket.get('today')!, ...byBucket.get('3d')!]
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for (const id of recentIds) expect(ids).toContain(sourceMessageId(imageMessage(id, 0)))
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expect(Math.max(...byBucket.get('today')!)).toBeLessThan(Math.min(...byBucket.get('3y')!))
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for (const id of byBucket.get('3y')!) {
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expect(ids).toContain(sourceMessageId(imageMessage(id, 0)))
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}
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})
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})
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describe('断点续跑：不重复 OCR', () => {
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it('第一批被预算截断后，重启只补剩下的，已完成的不再走一遍', async () => {
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const harness = makeHarness({ messages: [] })
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const { messages } = syntheticDataset(ANCHOR_MS)
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harness.state.messages = messages
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harness.state.count = messages.length
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harness.state.maxLocalId = Math.max(...messages.map((m) => Number(m.localId)))
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// 第一轮：只允许处理 6 张 → 必然停在"最近图片"这一段中间。
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await runPass(harness, { messageLimit: 6 })
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expect(harness.findImageFile).toHaveBeenCalledTimes(6)
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expect(harness.windows).toHaveLength(1)
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let states = tierStates(harness.databasePath)
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// 该分段没跑完 → 不允许被标成 complete（否则剩下的图永远不会被处理）。
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expect(states.recent_7d).not.toBe('complete')
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// 第二轮：预算放开 → 先把最近这段的剩余 4 张补完，再继续往下。
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await runPass(harness)
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expect(harness.findImageFile).toHaveBeenCalledTimes(50)
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states = tierStates(harness.databasePath)
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expect(states.recent_7d).toBe('complete')
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expect(states.archive).toBe('complete')
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expect(bindingIds(harness.databasePath)).toHaveLength(50)
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})
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})
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describe('增量优先：历史分段跑着的时候新图片先处理', () => {
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it('新图片在下一次调度点被处理，而不是排到历史之后', async () => {
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let injected = false
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const harness = makeHarness({
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messages: [],
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onWindow: (window) => {
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// 第二轮窗口请求（recent_30d）之后，模拟"用户刚收到一张新图"。
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if (injected || window?.sinceMs === undefined) return
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if (window.beforeMs === ANCHOR_MS - 7 * DAY_MS) {
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injected = true
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harness.state.messages = [
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...harness.state.messages,
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imageMessage(999, Math.floor((ANCHOR_MS + 5_000) / 1000))
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]
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harness.state.count += 1
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harness.state.maxLocalId = 999
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harness.state.now = ANCHOR_MS + 5_000
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}
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}
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})
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const { messages } = syntheticDataset(ANCHOR_MS)
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harness.state.messages = messages
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harness.state.count = messages.length
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harness.state.maxLocalId = Math.max(...messages.map((m) => Number(m.localId)))
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await runPass(harness)
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const newMessageId = sourceMessageId(imageMessage(999, 0))
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expect(bindingIds(harness.databasePath)).toContain(newMessageId)
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/**
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* 新图片必须在"更老的分段"之前被处理。
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*
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* 增量补齐对"插入序涨了"的会话是**不设时间窗**读取的（这样才接得住晚到的旧时间消息），
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* 所以这里找的是"没有任何时间边界的那个窗口"，它必须早于 1 年 / 归档分段。
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*/
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const sweepWindowIndex = harness.windows.findIndex(
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(window) => window.sinceMs === undefined && window.beforeMs === undefined
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)
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const yearWindowIndex = harness.windows.findIndex(
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(window) => window?.beforeMs === ANCHOR_MS - 30 * DAY_MS
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)
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expect(sweepWindowIndex).toBeGreaterThanOrEqual(0)
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expect(yearWindowIndex).toBeGreaterThan(sweepWindowIndex)
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})
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})
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describe('兼容性：老索引不被降级，源侧有新增必须补上', () => {
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it('老版本已经全量建完且源侧无变化 → 保持完成，一个字都不读', async () => {
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const harness = makeHarness({ messages: [] })
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// 造一份"旧版本建完"的库：总数 3、三条 binding 全部 terminal、没有任何分段元数据。
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const store = new ImageTextIndexStore(harness.databasePath, ACCOUNT)
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store.writeCountedTotal({ total: 3, countedAt: ANCHOR_MS - 1000, complete: true })
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// 旧版本每跑完一个会话都会留下 scan_state —— 升级后正是靠它证明源侧没动过。
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store.writeScanState({
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conversationId: CONVERSATION,
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state: 'done',
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imageTotal: 3,
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imageProcessed: 3,
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maxLocalId: 3
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})
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for (let index = 1; index <= 3; index += 1) {
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store.putBinding({
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accountId: ACCOUNT,
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conversationId: CONVERSATION,
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messageId: `local:${index}`,
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createTime: ANCHOR_MS - 1000,
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imageIdentity: `sha256:${index}`,
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artifactKey: `sha256:${index}|legacy`,
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state: 'indexed',
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updatedAt: 1
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})
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}
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store.close()
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harness.state.messages = [imageMessage(1, 1000), imageMessage(2, 2000), imageMessage(3, 3000)]
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harness.state.count = 3
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harness.state.maxLocalId = 3
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await runPass(harness)
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|
||||
// 源侧水位一致 → 一个字都不该读：用户已经拥有的东西不能被降级成"重新建立"。
|
||||
expect(harness.listImageMessages).not.toHaveBeenCalled()
|
||||
expect(harness.findImageFile).not.toHaveBeenCalled()
|
||||
const states = tierStates(harness.databasePath)
|
||||
expect(states.recent_7d).toBe('complete')
|
||||
expect(states.archive).toBe('complete')
|
||||
})
|
||||
|
||||
it('老版本自称"已建完"但源侧已新增 → 必须补上新增，不能信库里的进度', async () => {
|
||||
const harness = makeHarness({ messages: [] })
|
||||
const store = new ImageTextIndexStore(harness.databasePath, ACCOUNT)
|
||||
// 库里自称 2/2 已完成（旧版本跑完时的状态）。
|
||||
store.writeCountedTotal({ total: 2, countedAt: ANCHOR_MS - 1000, complete: true })
|
||||
for (const localId of [1, 2]) {
|
||||
store.writeScanState({
|
||||
conversationId: CONVERSATION,
|
||||
state: 'done',
|
||||
imageTotal: 2,
|
||||
imageProcessed: 2,
|
||||
maxLocalId: 2
|
||||
})
|
||||
store.putBinding({
|
||||
accountId: ACCOUNT,
|
||||
conversationId: CONVERSATION,
|
||||
messageId: `local:${localId}`,
|
||||
createTime: ANCHOR_MS - 1000,
|
||||
imageIdentity: `sha256:old-${localId}`,
|
||||
artifactKey: `sha256:old-${localId}|legacy`,
|
||||
state: 'indexed',
|
||||
updatedAt: 1
|
||||
})
|
||||
}
|
||||
store.close()
|
||||
|
||||
// 源侧现在是 3 张（插入序 1..3）—— 只看库里自称的进度会把它误判成"已完成"。
|
||||
harness.state.messages = [imageMessage(1, 1000), imageMessage(2, 2000), imageMessage(3, 3000)]
|
||||
harness.state.count = 3
|
||||
harness.state.maxLocalId = 3
|
||||
|
||||
await runPass(harness)
|
||||
|
||||
const ids = bindingIds(harness.databasePath)
|
||||
expect(ids).toHaveLength(3)
|
||||
expect(ids).toContain(sourceMessageId(imageMessage(3, 3000)))
|
||||
// 老的 terminal 结果必须被复用，不能重新 OCR。
|
||||
expect(harness.findImageFile).toHaveBeenCalledTimes(1)
|
||||
})
|
||||
})
|
||||
|
||||
describe('时间范围覆盖度', () => {
|
||||
const coverageOf = (input: Partial<ImageTextIndexCoverage>): ImageTextIndexCoverage => ({
|
||||
totalImageMessages: 100,
|
||||
processed: 20,
|
||||
indexed: 18,
|
||||
empty: 2,
|
||||
missing: 0,
|
||||
failed: 0,
|
||||
runtimeUnavailable: 0,
|
||||
pending: 80,
|
||||
established: true,
|
||||
complete: false,
|
||||
systemicFailure: false,
|
||||
countedAt: ANCHOR_MS,
|
||||
tiers: [
|
||||
{ tier: 'recent_7d', state: 'complete', startMs: ANCHOR_MS - 7 * DAY_MS, endMs: ANCHOR_MS },
|
||||
{
|
||||
tier: 'recent_30d',
|
||||
state: 'pending',
|
||||
startMs: ANCHOR_MS - 30 * DAY_MS,
|
||||
endMs: ANCHOR_MS - 7 * DAY_MS
|
||||
},
|
||||
{
|
||||
tier: 'recent_1y',
|
||||
state: 'pending',
|
||||
startMs: ANCHOR_MS - 365 * DAY_MS,
|
||||
endMs: ANCHOR_MS - 30 * DAY_MS
|
||||
},
|
||||
{
|
||||
tier: 'archive',
|
||||
state: 'pending',
|
||||
startMs: Number.NEGATIVE_INFINITY,
|
||||
endMs: ANCHOR_MS - 365 * DAY_MS
|
||||
}
|
||||
],
|
||||
coveredToMs: ANCHOR_MS,
|
||||
...input
|
||||
})
|
||||
|
||||
it('A. 最近 7 天已完成 → 查询最近 24h 可以下确定性结论', () => {
|
||||
const coverage = coverageOf({})
|
||||
const range = { sinceMs: ANCHOR_MS - DAY_MS, beforeMs: ANCHOR_MS }
|
||||
const result = imageTextRangeCoverage(coverage, range)
|
||||
expect(result.state).toBe('complete')
|
||||
expect(result.hasUncovered).toBe(false)
|
||||
expect(describeImageTextRangeCoverage(coverage, range)).toContain('已覆盖该时间范围')
|
||||
})
|
||||
|
||||
it('B. 更早历史未完成 → 全历史查询只能是 partial，并明确"不能排除尚未索引的图片"', () => {
|
||||
const coverage = coverageOf({})
|
||||
expect(imageTextRangeCoverage(coverage, {}).state).toBe('partial')
|
||||
expect(describeImageTextRangeCoverage(coverage, {})).toContain('不能排除尚未索引的图片')
|
||||
})
|
||||
|
||||
it('C. 全部完成 → 任意范围都是 complete', () => {
|
||||
const coverage = coverageOf({
|
||||
processed: 100,
|
||||
indexed: 98,
|
||||
empty: 2,
|
||||
pending: 0,
|
||||
complete: true,
|
||||
tiers: coverageOf({}).tiers.map((entry) => ({ ...entry, state: 'complete' as const }))
|
||||
})
|
||||
expect(imageTextRangeCoverage(coverage, {}).state).toBe('complete')
|
||||
expect(
|
||||
imageTextRangeCoverage(coverage, { sinceMs: ANCHOR_MS - 900 * DAY_MS }).state
|
||||
).toBe('complete')
|
||||
})
|
||||
|
||||
it('D. 在更老的历史里被取消 → 最近一段仍可完整，全历史仍是 partial', () => {
|
||||
const coverage = coverageOf({})
|
||||
expect(
|
||||
imageTextRangeCoverage(coverage, {
|
||||
sinceMs: ANCHOR_MS - 3 * DAY_MS,
|
||||
beforeMs: ANCHOR_MS
|
||||
}).state
|
||||
).toBe('complete')
|
||||
expect(imageTextRangeCoverage(coverage, {}).state).toBe('partial')
|
||||
})
|
||||
|
||||
it('未建立时不得声称任何范围完整', () => {
|
||||
const coverage = coverageOf({ established: false, tiers: [], coveredToMs: null })
|
||||
expect(imageTextRangeCoverage(coverage, { sinceMs: ANCHOR_MS - DAY_MS }).state).toBe(
|
||||
'not_built'
|
||||
)
|
||||
})
|
||||
})
|
||||
|
||||
describe('UI 文案与进度', () => {
|
||||
it('阶段文案是用户语言，不出现工程术语', () => {
|
||||
expect(imageTextPhaseLabel('recent_7d')).toBe('正在优先索引最近图片')
|
||||
expect(imageTextPhaseLabel('incremental')).toBe('正在优先索引最近图片')
|
||||
expect(imageTextPhaseLabel('recent_30d')).toBe('正在补齐最近 30 天')
|
||||
expect(imageTextPhaseLabel('recent_1y')).toBe('正在补齐近一年图片')
|
||||
expect(imageTextPhaseLabel('archive')).toBe('正在补齐更早图片')
|
||||
expect(imageTextPhaseLabel('complete')).toBe('图片文字索引已完成')
|
||||
const phases = ['incremental', 'recent_7d', 'recent_30d', 'recent_1y', 'archive', 'complete'] as const
|
||||
for (const phase of phases) {
|
||||
expect(imageTextPhaseLabel(phase)).not.toMatch(/Tier/i)
|
||||
}
|
||||
})
|
||||
|
||||
it('阶段字段在运行中出现，且总进度仍以全量图片数为分母', async () => {
|
||||
const harness = makeHarness({ messages: [] })
|
||||
const { messages } = syntheticDataset(ANCHOR_MS)
|
||||
harness.state.messages = messages
|
||||
harness.state.count = messages.length
|
||||
harness.state.maxLocalId = Math.max(...messages.map((m) => Number(m.localId)))
|
||||
|
||||
await runPass(harness, { messageLimit: 3 })
|
||||
const status = await harness.service.getStatus()
|
||||
// 总分母必须是全部图片消息，而不是"这一段处理了多少"。
|
||||
expect(status.progress.totalImageMessages).toBe(50)
|
||||
expect(status.progress.processed).toBeGreaterThan(0)
|
||||
expect(status.progress.percent).toBeLessThan(100)
|
||||
expect(status.coverage.tiers.map((entry) => entry.tier)).toEqual([
|
||||
'recent_7d',
|
||||
'recent_30d',
|
||||
'recent_1y',
|
||||
'archive'
|
||||
])
|
||||
})
|
||||
})
|
||||
Reference in New Issue
Block a user