mirror of
https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-08-21 21:47:00 +08:00
feat: 拆分代码
This commit is contained in:
Wxw-Gu
@@ -0,0 +1,254 @@
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import { act, renderHook } from '@testing-library/react'
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import { beforeEach, describe, expect, it, vi } from 'vitest'
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import { useState } from 'react'
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import { useSearchHistory } from '../../src/renderer/src/components/search/hooks/useSearchHistory'
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import type { AiSearchTimeRange } from '../../src/shared/ai-search'
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import type {
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AISearchCacheRecord,
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EvidenceItem,
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SearchRange,
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SearchScope,
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SearchStage
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} from '../../src/renderer/src/components/search/searchTypes'
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import {
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SEARCH_ACTIVE_RESULT_KEY,
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SEARCH_CACHE_KEY,
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SEARCH_HISTORY_KEY,
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buildSearchCacheKey
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} from '../../src/renderer/src/components/search/searchUtils'
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import {
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aiSearchContact,
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aiSearchGroup,
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makeCacheRecord,
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makePipelineEvidence
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} from './support/ai-search-fixtures'
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const onNotice = vi.fn()
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const useHistoryHarness = () => {
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const [query, setQuery] = useState('当前问题')
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const [scope, setScope] = useState<SearchScope>('global')
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const [scopeContactMd5, setScopeContactMd5] = useState('')
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const [range, setRange] = useState<SearchRange>('30d')
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const [timeRangeOverride, setTimeRangeOverride] = useState<AiSearchTimeRange | undefined>()
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const [resultQuery, setResultQuery] = useState('')
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const [answer, setAnswer] = useState('')
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const [evidence, setEvidence] = useState<EvidenceItem[]>([])
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const [evidenceCollection, setEvidenceCollection] = useState<EvidenceItem[]>([])
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const [visibleEvidenceCount, setVisibleEvidenceCount] = useState(0)
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const [senderNames, setSenderNames] = useState<Record<string, string>>({})
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const [messageCount, setMessageCount] = useState(0)
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const [cachedAt, setCachedAt] = useState(0)
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const [analysisError, setAnalysisError] = useState('')
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const [stage, setStage] = useState<SearchStage>('idle')
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const [selectedEvidence, setSelectedEvidence] = useState(0)
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const [historyOpen, setHistoryOpen] = useState(true)
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const history = useSearchHistory({
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query,
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scope,
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range,
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conversationContactMd5: scopeContactMd5 || aiSearchContact.md5,
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setQuery,
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setScope,
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setScopeContactMd5,
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setRange,
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setTimeRangeOverride,
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setResultQuery,
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setAnswer,
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setEvidence,
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setEvidenceCollection,
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setVisibleEvidenceCount,
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setSenderNames,
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setMessageCount,
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setCachedAt,
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setAnalysisError,
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setStage,
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setSelectedEvidence,
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setHistoryOpen,
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onNotice
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})
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return {
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...history,
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state: {
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query,
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scope,
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scopeContactMd5,
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range,
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timeRangeOverride,
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resultQuery,
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answer,
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evidence,
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evidenceCollection,
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visibleEvidenceCount,
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senderNames,
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messageCount,
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cachedAt,
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analysisError,
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stage,
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selectedEvidence,
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historyOpen
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}
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}
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}
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const readCacheRecords = (): AISearchCacheRecord[] =>
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JSON.parse(localStorage.getItem(SEARCH_CACHE_KEY) || '[]') as AISearchCacheRecord[]
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beforeEach(() => {
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localStorage.clear()
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sessionStorage.clear()
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vi.clearAllMocks()
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})
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describe('useSearchHistory', () => {
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it('loads and filters the persisted history list', () => {
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localStorage.setItem(SEARCH_HISTORY_KEY, JSON.stringify(['问题 A', 42, null, '问题 B']))
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const { result } = renderHook(() => useHistoryHarness())
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expect(result.current.history).toEqual(['问题 A', '问题 B'])
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})
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it('restores a history cache with its original scope, range and time override', () => {
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const query = '恢复历史问题'
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const cached = makeCacheRecord({
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query,
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scope: 'conversation',
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contactMd5: aiSearchGroup.md5,
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range: '7d',
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answer: '历史缓存答案',
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evidence: [makePipelineEvidence(1, aiSearchGroup)]
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}) as AISearchCacheRecord
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localStorage.setItem(SEARCH_CACHE_KEY, JSON.stringify([cached]))
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const { result } = renderHook(() => useHistoryHarness())
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act(() => result.current.restoreHistoryQuery(query))
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expect(result.current.state.query).toBe(query)
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expect(result.current.state.scope).toBe('conversation')
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expect(result.current.state.scopeContactMd5).toBe(aiSearchGroup.md5)
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expect(result.current.state.range).toBe('7d')
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expect(result.current.state.timeRangeOverride).toMatchObject({
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label: '近 7 天',
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reason: '恢复历史搜索的时间范围',
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source: 'user_selected'
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})
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expect(result.current.state.answer).toBe('历史缓存答案')
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expect(result.current.state.stage).toBe('result')
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expect(result.current.state.historyOpen).toBe(false)
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expect(onNotice).toHaveBeenCalledWith('已恢复这条历史问题的最近结果')
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})
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it('deletes a history item and all cache records for its normalized query', () => {
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const deleted = makeCacheRecord({ query: '待删除问题', answer: '应删除' })
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const retained = makeCacheRecord({ query: '保留问题', answer: '应保留' })
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localStorage.setItem(SEARCH_HISTORY_KEY, JSON.stringify(['待删除问题', '保留问题']))
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localStorage.setItem(SEARCH_CACHE_KEY, JSON.stringify([deleted, retained]))
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const { result } = renderHook(() => useHistoryHarness())
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act(() => result.current.removeHistoryQuery(' 待删除问题 '))
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expect(result.current.history).toEqual(['待删除问题', '保留问题'])
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expect(readCacheRecords()).toEqual([retained])
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act(() => result.current.removeHistoryQuery('待删除问题'))
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expect(result.current.history).toEqual(['保留问题'])
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expect(readCacheRecords()).toEqual([retained])
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})
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it('reads and applies a current cache hit while marking the active session result', () => {
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const cached = makeCacheRecord({
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query: '缓存命中问题',
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answer: '缓存命中答案',
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evidence: [makePipelineEvidence(1)]
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}) as AISearchCacheRecord
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localStorage.setItem(SEARCH_CACHE_KEY, JSON.stringify([cached]))
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const { result } = renderHook(() => useHistoryHarness())
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const found = result.current.readCachedResult(cached.key)
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expect(found).toEqual(cached)
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act(() => result.current.applyCachedResult(cached, '缓存命中问题'))
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expect(result.current.state.answer).toBe('缓存命中答案')
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expect(result.current.state.resultQuery).toBe('缓存命中问题')
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expect(result.current.state.evidence).toHaveLength(1)
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expect(sessionStorage.getItem(SEARCH_ACTIVE_RESULT_KEY)).toBe(cached.key)
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})
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it('preserves an intentionally incomplete cache collection instead of rebuilding it', () => {
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const evidence = makeCacheRecord({
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query: '不完整缓存',
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evidence: [makePipelineEvidence(1)]
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}).evidence as EvidenceItem[]
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const cached: AISearchCacheRecord = {
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version: 3,
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key: buildSearchCacheKey('global', '', '30d', '不完整缓存'),
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createdAt: 10,
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answer: '不完整',
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evidence,
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evidenceCollection: [],
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senderNames: {},
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messageCount: 1
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}
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const { result } = renderHook(() => useHistoryHarness())
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act(() => result.current.applyCachedResult(cached, '不完整缓存'))
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expect(result.current.state.evidence).toHaveLength(1)
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expect(result.current.state.evidenceCollection).toEqual([])
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expect(result.current.state.visibleEvidenceCount).toBe(0)
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})
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it('falls back to legacy evidence when evidenceCollection is absent', () => {
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const cached = makeCacheRecord({
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query: '旧缓存问题',
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evidence: [makePipelineEvidence(1)]
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}) as AISearchCacheRecord
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const { result } = renderHook(() => useHistoryHarness())
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act(() => result.current.applyCachedResult(cached, '旧缓存问题'))
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expect(result.current.state.evidenceCollection).toBe(result.current.state.evidence)
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expect(result.current.state.visibleEvidenceCount).toBe(1)
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})
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it('does not reuse an old cache after the caller marks a new search as bypassing cache', () => {
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const cached = makeCacheRecord({ query: '旧结果', answer: '旧答案' }) as AISearchCacheRecord
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localStorage.setItem(SEARCH_CACHE_KEY, JSON.stringify([cached]))
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const { result } = renderHook(() => useHistoryHarness())
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act(() => result.current.skipNextCache())
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const shouldBypass = result.current.consumeCacheBypass()
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expect(shouldBypass).toBe(true)
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expect(result.current.state.answer).toBe('')
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expect(result.current.consumeCacheBypass()).toBe(false)
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expect(result.current.readCachedResult(cached.key)).toEqual(cached)
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})
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it('persists a new compact cache record and its active session key', () => {
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const { result } = renderHook(() => useHistoryHarness())
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const evidence = makeCacheRecord({
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query: '新搜索问题',
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evidence: [makePipelineEvidence(1)]
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}).evidence as EvidenceItem[]
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act(() =>
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result.current.persistSearchResult({
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key: buildSearchCacheKey('global', '', '30d', '新搜索问题'),
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answer: '新答案',
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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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)
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const records = readCacheRecords()
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expect(records).toHaveLength(1)
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expect(records[0].version).toBe(3)
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expect(records[0].answer).toBe('新答案')
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expect(sessionStorage.getItem(SEARCH_ACTIVE_RESULT_KEY)).toBe(records[0].key)
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})
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})
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@@ -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')
|
||||
expect(mapped.message.senderId).toBeUndefined()
|
||||
})
|
||||
|
||||
it('maps a collection in order and builds sender names with the existing overwrite behavior', () => {
|
||||
const items = [
|
||||
makeFinalEvidence(1, { senderId: 'same-sender', sender: '旧名称' }),
|
||||
makeFinalEvidence(2, { senderId: 'same-sender', sender: '新名称' }),
|
||||
makeFinalEvidence(3, { senderId: undefined, sender: '无 ID' })
|
||||
]
|
||||
const mapped = mapPipelineEvidence(items, [aiSearchContact])
|
||||
|
||||
expect(mapped.map((item) => item.evidenceId)).toEqual(['E1', 'E2', 'E3'])
|
||||
expect(mapEvidenceSenderNames(mapped)).toEqual({ 'same-sender': '新名称' })
|
||||
})
|
||||
})
|
||||
|
||||
describe('AI Search trace and cache mapping', () => {
|
||||
it('maps pipeline trace fields and preserves the original default values', () => {
|
||||
const result: AiSearchPipelineResult = makeSearchResult()
|
||||
|
||||
expect(mapSearchResultToTrace(result, 4)).toEqual({
|
||||
knowledgeMessages: 20,
|
||||
retrievedEvidence: 0,
|
||||
finalEvidence: 4,
|
||||
timings: result.timings,
|
||||
contextEvidence: 0,
|
||||
inputTokens: undefined,
|
||||
inputTokensEstimated: false,
|
||||
aggregation: result.aggregation,
|
||||
invalidCitationIds: [],
|
||||
agent: result.agent,
|
||||
voiceCoverage: undefined
|
||||
})
|
||||
})
|
||||
|
||||
it('maps AI token, citation, and voice coverage details without transforming them', () => {
|
||||
const result: AiSearchPipelineResult = makeSearchResult()
|
||||
result.ai = {
|
||||
providerName: 'provider',
|
||||
modelName: 'model',
|
||||
inputTokens: 321,
|
||||
inputTokensEstimated: true
|
||||
}
|
||||
result.citationValidation = { status: 'sanitized', invalidCitationIds: ['E9'] }
|
||||
result.knowledge.voiceCoverage = {
|
||||
voiceMessageCount: 3,
|
||||
transcribedVoiceCount: 2,
|
||||
failedVoiceCount: 1,
|
||||
voiceCoverageComplete: true
|
||||
}
|
||||
|
||||
const trace = mapSearchResultToTrace(result, 2)
|
||||
expect(trace.inputTokens).toBe(321)
|
||||
expect(trace.inputTokensEstimated).toBe(true)
|
||||
expect(trace.invalidCitationIds).toEqual(['E9'])
|
||||
expect(trace.voiceCoverage).toBe(result.knowledge.voiceCoverage)
|
||||
})
|
||||
|
||||
it('maps a current cache record and limits only the visible collection to one page', () => {
|
||||
const evidence = mapPipelineEvidence([makeFinalEvidence(1)], [aiSearchContact])
|
||||
const evidenceCollection = mapPipelineEvidence(
|
||||
Array.from({ length: 10 }, (_, index) => makeFinalEvidence(index + 1)),
|
||||
[aiSearchContact]
|
||||
)
|
||||
const cached: AISearchCacheRecord = {
|
||||
version: 3,
|
||||
key: 'cache-key',
|
||||
createdAt: 123,
|
||||
answer: '缓存答案',
|
||||
evidence,
|
||||
evidenceCollection,
|
||||
senderNames: { 'sender-1': '发送者 1' },
|
||||
messageCount: 99
|
||||
}
|
||||
|
||||
const mapped = mapCacheRecordToResult(cached, '恢复问题', 8)
|
||||
expect(mapped).toEqual({
|
||||
resultQuery: '恢复问题',
|
||||
answer: '缓存答案',
|
||||
evidence,
|
||||
evidenceCollection,
|
||||
visibleEvidenceCount: 8,
|
||||
senderNames: { 'sender-1': '发送者 1' },
|
||||
messageCount: 99,
|
||||
cachedAt: 123
|
||||
})
|
||||
})
|
||||
|
||||
it('falls back to legacy cache evidence when evidenceCollection is absent', () => {
|
||||
const evidence = mapPipelineEvidence([makeFinalEvidence(1)], [aiSearchContact])
|
||||
const cached: AISearchCacheRecord = {
|
||||
version: 3,
|
||||
key: 'legacy-cache-key',
|
||||
createdAt: 456,
|
||||
answer: '旧缓存',
|
||||
evidence,
|
||||
senderNames: {},
|
||||
messageCount: 1
|
||||
}
|
||||
|
||||
const mapped = mapCacheRecordToResult(cached, '旧问题', 8)
|
||||
expect(mapped.evidenceCollection).toBe(evidence)
|
||||
expect(mapped.visibleEvidenceCount).toBe(1)
|
||||
})
|
||||
|
||||
it('creates the same compact version 3 cache record as the workspace did', () => {
|
||||
const fullContact: Contact = { ...aiSearchGroup, avatar: 'avatar', remark: '不应写入缓存' }
|
||||
const evidence: EvidenceItem[] = [
|
||||
{
|
||||
evidenceId: 'E1',
|
||||
sourceKind: 'voice',
|
||||
contact: fullContact,
|
||||
message: {
|
||||
id: 'message-1',
|
||||
from: 'sender-1',
|
||||
type: '语音转写',
|
||||
datetime: '2023/11/14 22:13:21',
|
||||
content: '证据 1',
|
||||
isSender: false,
|
||||
name: '发送者 1',
|
||||
senderId: 'sender-1',
|
||||
createTime: 1_700_000_001,
|
||||
sessionId: '不应写入缓存'
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
expect(
|
||||
createSearchCacheRecord({
|
||||
key: 'cache-key',
|
||||
createdAt: 789,
|
||||
answer: '答案',
|
||||
evidence,
|
||||
evidenceCollection: evidence,
|
||||
senderNames: { 'sender-1': '发送者 1' },
|
||||
messageCount: 20
|
||||
})
|
||||
).toEqual({
|
||||
version: 3,
|
||||
key: 'cache-key',
|
||||
createdAt: 789,
|
||||
answer: '答案',
|
||||
evidence: [
|
||||
{
|
||||
evidenceId: 'E1',
|
||||
contact: {
|
||||
md5: fullContact.md5,
|
||||
m_nsUsrName: fullContact.m_nsUsrName,
|
||||
m_nsNickName: fullContact.m_nsNickName,
|
||||
type: 'group',
|
||||
avatar: 'avatar'
|
||||
},
|
||||
message: {
|
||||
id: 'message-1',
|
||||
from: 'sender-1',
|
||||
type: '语音转写',
|
||||
datetime: '2023/11/14 22:13:21',
|
||||
content: '证据 1',
|
||||
isSender: false,
|
||||
name: '发送者 1',
|
||||
senderId: 'sender-1',
|
||||
localId: undefined,
|
||||
serverId: undefined,
|
||||
createTime: 1_700_000_001
|
||||
}
|
||||
}
|
||||
],
|
||||
evidenceCollection: [
|
||||
{
|
||||
evidenceId: 'E1',
|
||||
contact: {
|
||||
md5: fullContact.md5,
|
||||
m_nsUsrName: fullContact.m_nsUsrName,
|
||||
m_nsNickName: fullContact.m_nsNickName,
|
||||
type: 'group',
|
||||
avatar: 'avatar'
|
||||
},
|
||||
message: {
|
||||
id: 'message-1',
|
||||
from: 'sender-1',
|
||||
type: '语音转写',
|
||||
datetime: '2023/11/14 22:13:21',
|
||||
content: '证据 1',
|
||||
isSender: false,
|
||||
name: '发送者 1',
|
||||
senderId: 'sender-1',
|
||||
localId: undefined,
|
||||
serverId: undefined,
|
||||
createTime: 1_700_000_001
|
||||
}
|
||||
}
|
||||
],
|
||||
senderNames: { 'sender-1': '发送者 1' },
|
||||
messageCount: 20
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
describe('AI Search result reset state', () => {
|
||||
it('returns every existing search result reset value', () => {
|
||||
expect(createSearchResultResetState()).toEqual({
|
||||
analysisError: '',
|
||||
answer: '',
|
||||
evidence: [],
|
||||
evidenceCollection: [],
|
||||
visibleEvidenceCount: 0,
|
||||
selectedEvidence: 0,
|
||||
cachedAt: 0,
|
||||
searchTrace: null,
|
||||
searchProgress: {},
|
||||
agentTrace: [],
|
||||
searchDetailsOpen: false
|
||||
})
|
||||
})
|
||||
|
||||
it('returns independent arrays and progress objects for consecutive resets', () => {
|
||||
const first = createSearchResultResetState()
|
||||
const second = createSearchResultResetState()
|
||||
|
||||
expect(first.evidence).not.toBe(second.evidence)
|
||||
expect(first.evidenceCollection).not.toBe(second.evidenceCollection)
|
||||
expect(first.searchProgress).not.toBe(second.searchProgress)
|
||||
expect(first.agentTrace).not.toBe(second.agentTrace)
|
||||
})
|
||||
})
|
||||
Reference in New Issue
Block a user