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https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-08-21 21:47:00 +08:00
feat: 拆分代码
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Wxw-Gu
@@ -0,0 +1,421 @@
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import { describe, expect, it } from 'vitest'
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import type { AiSearchFinalEvidence, AiSearchPipelineResult } from '../../src/shared/ai-search'
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import type { KnowledgeRuntimeStatus } from '../../src/shared/knowledge'
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import type { Contact } from '../../src/shared/types'
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import {
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contactLabel,
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formatBytes,
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formatDuration,
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formatEvidenceTimestamp,
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formatMeasuredDuration,
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formatSearchTraceOverview,
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knowledgeStateLabel
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} from '../../src/renderer/src/components/search/searchFormatters'
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import {
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createSearchCacheRecord,
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mapCacheRecordToResult,
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mapEvidenceSenderNames,
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mapPipelineEvidence,
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mapPipelineEvidenceItem,
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mapSearchResultToTrace
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} from '../../src/renderer/src/components/search/searchMappers'
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import { createSearchResultResetState } from '../../src/renderer/src/components/search/searchState'
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import type {
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AISearchCacheRecord,
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EvidenceItem,
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SearchTrace
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} from '../../src/renderer/src/components/search/searchTypes'
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import {
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aiSearchContact,
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aiSearchGroup,
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makeSearchResult
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} from '../component/support/ai-search-fixtures'
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const makeFinalEvidence = (
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index: number,
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overrides: Partial<AiSearchFinalEvidence> = {}
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): AiSearchFinalEvidence => ({
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id: `E${index}`,
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chunkId: `chunk-${index}`,
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conversationId: aiSearchContact.md5,
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conversationName: aiSearchContact.m_nsNickName,
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conversationType: aiSearchContact.type,
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startTime: 1_700_000_000_000 + index * 1_000,
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endTime: 1_700_000_000_000 + index * 1_000,
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messageId: `message-${index}`,
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senderId: `sender-${index}`,
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sender: `发送者 ${index}`,
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timestamp: 1_700_000_000_000 + index * 1_000,
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messageIds: [`message-${index}`],
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sourceKind: 'text',
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text: `证据 ${index}`,
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...overrides
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})
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const makeKnowledgeStatus = (state: KnowledgeRuntimeStatus['state']): KnowledgeRuntimeStatus => ({
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accountId: 'account-1',
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state,
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indexedMessageCount: 0,
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indexedChunkCount: 0,
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sourceMessageCount: null,
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processedMessages: 0,
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totalMessages: null,
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estimatedRemainingMs: null,
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databaseBytes: 0,
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walBytes: 0,
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shmBytes: 0
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})
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const makeTrace = (overrides: Partial<SearchTrace> = {}): SearchTrace => ({
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knowledgeMessages: 20,
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retrievedEvidence: 10,
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finalEvidence: 8,
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timings: {
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totalMs: 1_250,
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knowledgeSearchMs: 250,
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aiGenerationMs: 1_000
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} as SearchTrace['timings'],
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contextEvidence: 6,
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inputTokensEstimated: false,
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aggregation: {
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messageCount: 8,
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peopleCount: 1,
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conversationCount: 1,
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people: [],
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conversations: []
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},
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invalidCitationIds: [],
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agent: { mode: 'agent', toolCalls: 0, trace: [] },
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...overrides
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})
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describe('AI Search workspace pure formatters', () => {
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it('formats byte counts exactly as the workspace did', () => {
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expect(formatBytes(0)).toBe('0 B')
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expect(formatBytes(512)).toBe('512 B')
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expect(formatBytes(1_536)).toBe('1.5 KB')
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expect(formatBytes(2 * 1024 ** 3)).toBe('2.0 GB')
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})
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it('formats measured and unmeasured durations exactly as the workspace did', () => {
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expect(formatDuration(999)).toBe('999ms')
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expect(formatDuration(1_250)).toBe('1.3s')
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expect(formatMeasuredDuration(undefined)).toBe('未测量')
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expect(formatMeasuredDuration(1_000)).toBe('1.0s')
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})
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it('formats evidence timestamps with the existing zh-CN locale options', () => {
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const timestamp = 1_700_000_001_000
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expect(formatEvidenceTimestamp(timestamp)).toBe(
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new Date(timestamp).toLocaleString('zh-CN', { hour12: false })
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)
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})
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it('keeps every knowledge runtime state label unchanged', () => {
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expect(knowledgeStateLabel(null)).toBe('读取中')
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expect(knowledgeStateLabel(makeKnowledgeStatus('unavailable'))).toBe('未建立')
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expect(knowledgeStateLabel(makeKnowledgeStatus('building'))).toBe('建立中')
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expect(knowledgeStateLabel(makeKnowledgeStatus('syncing'))).toBe('增量同步')
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expect(knowledgeStateLabel(makeKnowledgeStatus('ready'))).toBe('已同步')
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expect(knowledgeStateLabel(makeKnowledgeStatus('error'))).toBe('异常')
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})
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it('keeps the existing contact label fallback order', () => {
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expect(contactLabel(aiSearchContact)).toBe('测试会话')
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expect(contactLabel({ ...aiSearchContact, m_nsNickName: '' })).toBe('测试联系人')
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expect(
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contactLabel({ ...aiSearchContact, m_nsNickName: '', remark: '', wechatNickname: '' })
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).toBe('wxid_fixture')
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expect(contactLabel(null)).toBe('未选择会话')
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})
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it('formats the compact search trace overview without changing labels or units', () => {
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expect(formatSearchTraceOverview(makeTrace())).toEqual({
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totalDuration: '1.3s',
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knowledgeDuration: '250ms',
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aiDuration: '1.0s',
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contextEvidence: '6 条'
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})
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})
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})
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describe('AI Search pipeline evidence mapping', () => {
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it('reuses the existing renderer contact object when the conversation is loaded', () => {
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const item = makeFinalEvidence(1)
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const mapped = mapPipelineEvidenceItem(item, new Map([[aiSearchContact.md5, aiSearchContact]]))
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expect(mapped.contact).toBe(aiSearchContact)
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expect(mapped).toEqual({
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evidenceId: 'E1',
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sourceKind: 'text',
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contact: aiSearchContact,
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message: {
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id: 'message-1',
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from: 'sender-1',
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type: '检索消息',
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datetime: formatEvidenceTimestamp(item.timestamp),
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content: '证据 1',
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isSender: false,
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name: '发送者 1',
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senderId: 'sender-1',
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createTime: Math.floor(item.timestamp / 1_000)
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}
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})
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})
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it('creates the existing group fallback and voice presentation for an unloaded conversation', () => {
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const item = makeFinalEvidence(2, {
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conversationId: 'missing@chatroom',
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conversationName: '未加载群',
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conversationType: 'group',
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sourceKind: 'voice',
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sender: '我'
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})
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const mapped = mapPipelineEvidenceItem(item, new Map())
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expect(mapped.contact).toEqual({
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md5: 'missing@chatroom',
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m_nsUsrName: 'missing@chatroom',
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m_nsNickName: '未加载群',
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type: 'group'
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})
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expect(mapped.message.type).toBe('语音转写')
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expect(mapped.message.isSender).toBe(true)
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})
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it('creates the existing user fallback and sender default when senderId is absent', () => {
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const item = makeFinalEvidence(3, {
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conversationId: 'missing-user',
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conversationName: '未加载联系人',
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conversationType: 'user',
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senderId: undefined
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})
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const mapped = mapPipelineEvidenceItem(item, new Map())
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expect(mapped.contact.type).toBe('user')
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expect(mapped.message.from).toBe('user')
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expect(mapped.message.senderId).toBeUndefined()
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})
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it('maps a collection in order and builds sender names with the existing overwrite behavior', () => {
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const items = [
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makeFinalEvidence(1, { senderId: 'same-sender', sender: '旧名称' }),
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makeFinalEvidence(2, { senderId: 'same-sender', sender: '新名称' }),
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makeFinalEvidence(3, { senderId: undefined, sender: '无 ID' })
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]
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const mapped = mapPipelineEvidence(items, [aiSearchContact])
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expect(mapped.map((item) => item.evidenceId)).toEqual(['E1', 'E2', 'E3'])
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expect(mapEvidenceSenderNames(mapped)).toEqual({ 'same-sender': '新名称' })
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})
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})
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describe('AI Search trace and cache mapping', () => {
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it('maps pipeline trace fields and preserves the original default values', () => {
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const result: AiSearchPipelineResult = makeSearchResult()
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expect(mapSearchResultToTrace(result, 4)).toEqual({
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knowledgeMessages: 20,
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retrievedEvidence: 0,
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finalEvidence: 4,
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timings: result.timings,
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contextEvidence: 0,
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inputTokens: undefined,
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inputTokensEstimated: false,
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aggregation: result.aggregation,
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invalidCitationIds: [],
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agent: result.agent,
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voiceCoverage: undefined
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})
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})
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it('maps AI token, citation, and voice coverage details without transforming them', () => {
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const result: AiSearchPipelineResult = makeSearchResult()
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result.ai = {
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providerName: 'provider',
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modelName: 'model',
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inputTokens: 321,
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inputTokensEstimated: true
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}
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result.citationValidation = { status: 'sanitized', invalidCitationIds: ['E9'] }
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result.knowledge.voiceCoverage = {
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voiceMessageCount: 3,
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transcribedVoiceCount: 2,
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failedVoiceCount: 1,
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voiceCoverageComplete: true
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}
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const trace = mapSearchResultToTrace(result, 2)
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expect(trace.inputTokens).toBe(321)
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expect(trace.inputTokensEstimated).toBe(true)
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expect(trace.invalidCitationIds).toEqual(['E9'])
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expect(trace.voiceCoverage).toBe(result.knowledge.voiceCoverage)
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})
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it('maps a current cache record and limits only the visible collection to one page', () => {
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const evidence = mapPipelineEvidence([makeFinalEvidence(1)], [aiSearchContact])
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const evidenceCollection = mapPipelineEvidence(
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Array.from({ length: 10 }, (_, index) => makeFinalEvidence(index + 1)),
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[aiSearchContact]
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)
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const cached: AISearchCacheRecord = {
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version: 3,
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key: 'cache-key',
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createdAt: 123,
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answer: '缓存答案',
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evidence,
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evidenceCollection,
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senderNames: { 'sender-1': '发送者 1' },
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messageCount: 99
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}
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const mapped = mapCacheRecordToResult(cached, '恢复问题', 8)
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expect(mapped).toEqual({
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resultQuery: '恢复问题',
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answer: '缓存答案',
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evidence,
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evidenceCollection,
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visibleEvidenceCount: 8,
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senderNames: { 'sender-1': '发送者 1' },
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messageCount: 99,
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cachedAt: 123
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})
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})
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it('falls back to legacy cache evidence when evidenceCollection is absent', () => {
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const evidence = mapPipelineEvidence([makeFinalEvidence(1)], [aiSearchContact])
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const cached: AISearchCacheRecord = {
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version: 3,
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key: 'legacy-cache-key',
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createdAt: 456,
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answer: '旧缓存',
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evidence,
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senderNames: {},
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messageCount: 1
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}
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const mapped = mapCacheRecordToResult(cached, '旧问题', 8)
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expect(mapped.evidenceCollection).toBe(evidence)
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expect(mapped.visibleEvidenceCount).toBe(1)
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})
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it('creates the same compact version 3 cache record as the workspace did', () => {
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const fullContact: Contact = { ...aiSearchGroup, avatar: 'avatar', remark: '不应写入缓存' }
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const evidence: EvidenceItem[] = [
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{
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evidenceId: 'E1',
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sourceKind: 'voice',
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contact: fullContact,
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message: {
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id: 'message-1',
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from: 'sender-1',
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type: '语音转写',
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datetime: '2023/11/14 22:13:21',
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content: '证据 1',
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isSender: false,
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name: '发送者 1',
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senderId: 'sender-1',
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createTime: 1_700_000_001,
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sessionId: '不应写入缓存'
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}
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}
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]
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expect(
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createSearchCacheRecord({
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key: 'cache-key',
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createdAt: 789,
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answer: '答案',
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evidence,
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evidenceCollection: evidence,
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senderNames: { 'sender-1': '发送者 1' },
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messageCount: 20
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})
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).toEqual({
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version: 3,
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key: 'cache-key',
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createdAt: 789,
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answer: '答案',
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evidence: [
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{
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evidenceId: 'E1',
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contact: {
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md5: fullContact.md5,
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m_nsUsrName: fullContact.m_nsUsrName,
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m_nsNickName: fullContact.m_nsNickName,
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type: 'group',
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avatar: 'avatar'
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},
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message: {
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id: 'message-1',
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from: 'sender-1',
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type: '语音转写',
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datetime: '2023/11/14 22:13:21',
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content: '证据 1',
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isSender: false,
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name: '发送者 1',
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senderId: 'sender-1',
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localId: undefined,
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serverId: undefined,
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createTime: 1_700_000_001
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}
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}
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],
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evidenceCollection: [
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{
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evidenceId: 'E1',
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contact: {
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md5: fullContact.md5,
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m_nsUsrName: fullContact.m_nsUsrName,
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m_nsNickName: fullContact.m_nsNickName,
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type: 'group',
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avatar: 'avatar'
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},
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message: {
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id: 'message-1',
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from: 'sender-1',
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type: '语音转写',
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datetime: '2023/11/14 22:13:21',
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content: '证据 1',
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isSender: false,
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name: '发送者 1',
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senderId: 'sender-1',
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localId: undefined,
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serverId: undefined,
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createTime: 1_700_000_001
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}
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}
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],
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senderNames: { 'sender-1': '发送者 1' },
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messageCount: 20
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})
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})
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})
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describe('AI Search result reset state', () => {
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it('returns every existing search result reset value', () => {
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expect(createSearchResultResetState()).toEqual({
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analysisError: '',
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answer: '',
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evidence: [],
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evidenceCollection: [],
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visibleEvidenceCount: 0,
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selectedEvidence: 0,
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cachedAt: 0,
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searchTrace: null,
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searchProgress: {},
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agentTrace: [],
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searchDetailsOpen: false
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})
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})
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it('returns independent arrays and progress objects for consecutive resets', () => {
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const first = createSearchResultResetState()
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const second = createSearchResultResetState()
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expect(first.evidence).not.toBe(second.evidence)
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expect(first.evidenceCollection).not.toBe(second.evidenceCollection)
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expect(first.searchProgress).not.toBe(second.searchProgress)
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expect(first.agentTrace).not.toBe(second.agentTrace)
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})
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})
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