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https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
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test: 暂存代码
This commit is contained in:
电摇小子
@@ -0,0 +1,732 @@
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import { beforeEach, describe, expect, it, vi } from 'vitest'
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const { chatState, listContactsAsync } = vi.hoisted(() => ({
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chatState: { ready: true },
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listContactsAsync: vi.fn()
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}))
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vi.mock('../../src/main/services/chat-service', () => ({
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isReady: () => chatState.ready,
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listContactsAsync
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}))
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import { AiSearchPipelineService } from '../../src/main/services/ai-search-pipeline-service'
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import type { KnowledgeEvidence } from '../../src/shared/knowledge'
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const makeCandidate = (index: number): KnowledgeEvidence => ({
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chunkId: `chunk-${index}`,
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conversationId: index % 2 ? 'fitness-group-a' : 'fitness-group-b',
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startTime: 1785900000000 + index,
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endTime: 1785900000000 + index,
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messageId: `message-${index}`,
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sender: index % 2 ? '杨伟' : '东方小唠',
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senderId: index % 2 ? 'member-yang' : 'member-dongfang',
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timestamp: 1785900000000 + index,
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messageIds: [`message-${index}`],
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text: `candidate-${index} 去健身`,
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score: -index
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})
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describe('AiSearchPipelineService', () => {
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const knowledge = { search: vi.fn() }
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const aiProvider = { getRuntimeConfig: vi.fn(), chat: vi.fn() }
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beforeEach(() => {
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chatState.ready = true
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listContactsAsync.mockReset()
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knowledge.search.mockReset()
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aiProvider.getRuntimeConfig.mockReset()
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aiProvider.chat.mockReset()
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listContactsAsync.mockResolvedValue([
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{
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md5: 'fitness-group',
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m_nsUsrName: 'fitness-group@chatroom',
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m_nsNickName: '健身交流组',
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type: 'group'
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}
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])
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knowledge.search.mockResolvedValue({
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source: 'knowledge',
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state: 'ready',
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indexedMessageCount: 2_000,
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indexedChunkCount: 300,
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totalMessages: 2_000,
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evidence: [
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{
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chunkId: 'chunk-1',
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conversationId: 'fitness-group',
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startTime: 1785900000000,
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endTime: 1785900000000,
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messageId: 'message-1',
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sender: '小明',
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senderId: 'wxid_fixture',
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timestamp: 1785900000000,
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messageIds: ['message-1'],
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text: '今天下班去健身。'
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}
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]
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})
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aiProvider.getRuntimeConfig.mockReturnValue({
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configured: true,
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providerName: 'DeepSeek',
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modelName: 'DeepSeek Chat'
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})
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aiProvider.chat
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
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})
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"finalize","reason":"已找到足够的相关消息"}'
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})
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.mockResolvedValueOnce({
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success: true,
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data: '小明提到今天下班去健身。[E1]',
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usage: { input: 120 }
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})
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})
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it('emits actual planning, knowledge, evidence and AI completion states', async () => {
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const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
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const events: Array<{ stage: string; status: string; message: string }> = []
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const result = await service.run(
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{
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requestId: 'fixture-request',
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text: '最近谁聊过健身',
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scope: 'global',
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range: '7d'
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},
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(event) => events.push(event)
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)
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expect(knowledge.search).toHaveBeenCalledWith(
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expect.objectContaining({ text: '最近谁聊过健身', terms: ['健身'] })
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)
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expect(events).toEqual(
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expect.arrayContaining([
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expect.objectContaining({ stage: 'query_understanding', status: 'running' }),
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expect.objectContaining({ stage: 'agent_start', status: 'completed' }),
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expect.objectContaining({ stage: 'agent_tool', status: 'completed' }),
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expect.objectContaining({ stage: 'search_plan_ready', status: 'completed' }),
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expect.objectContaining({ stage: 'knowledge_searching', status: 'completed' }),
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expect.objectContaining({ stage: 'evidence_ready', status: 'completed' }),
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expect.objectContaining({ stage: 'aggregation', status: 'completed' }),
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expect.objectContaining({
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stage: 'ai_generating',
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status: 'running',
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modelName: 'DeepSeek Chat'
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}),
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expect.objectContaining({ stage: 'completed', status: 'completed' })
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])
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)
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expect(result).toMatchObject({
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status: 'completed',
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candidateEvidenceCount: 1,
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contextEvidenceCount: 1,
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answer: '小明提到今天下班去健身。[E1]',
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ai: { inputTokens: 120, inputTokensEstimated: false }
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})
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expect(result.agent).toMatchObject({ mode: 'agent', toolCalls: 1 })
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})
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it('keeps real evidence when the answer model fails', async () => {
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aiProvider.chat.mockReset()
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aiProvider.chat
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
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})
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.mockResolvedValueOnce({ success: true, data: '{"action":"finalize","reason":"证据足够"}' })
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.mockResolvedValueOnce({ success: false, error: '模型超时' })
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const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
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const events: Array<{ stage: string; status: string; message: string }> = []
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const result = await service.run(
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{
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requestId: 'fixture-ai-error',
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text: '最近聊过健身吗',
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scope: 'global',
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range: '7d'
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},
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(event) => events.push(event)
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)
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expect(result).toMatchObject({ status: 'ai_failed', evidence: [expect.any(Object)] })
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expect(events).toContainEqual(
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expect.objectContaining({ stage: 'ai_generating', status: 'error', error: '模型超时' })
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)
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})
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it('uses Final Evidence only for AI context and strips invalid citations', async () => {
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knowledge.search.mockResolvedValue({
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source: 'knowledge',
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state: 'ready',
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indexedMessageCount: 2_000,
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indexedChunkCount: 300,
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totalMessages: 2_000,
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evidence: Array.from({ length: 16 }, (_, index) => makeCandidate(index + 1)),
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timings: {
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workerIpcMs: 4,
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ftsMs: 8,
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messageLoadMs: 5,
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chunkExpandMs: 6,
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rankingMs: 2,
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totalMs: 25
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}
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})
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aiProvider.chat.mockReset()
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aiProvider.chat
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
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})
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.mockResolvedValueOnce({ success: true, data: '{"action":"finalize","reason":"证据足够"}' })
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.mockResolvedValueOnce({
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success: true,
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data: '杨伟聊过去健身。[E1] 错误引用。[E10][E23]',
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usage: { input: 160 }
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})
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const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
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const result = await service.run(
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{
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requestId: 'final-evidence-only',
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text: '全局搜一下 谁聊过 去健身',
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scope: 'global',
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range: '30d'
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},
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() => undefined
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)
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const answerPrompt = aiProvider.chat.mock.calls[2][0][1].content as string
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const contextIds = Array.from(answerPrompt.matchAll(/\[E(\d+)\]\nconversationId:/g)).map(
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(match) => Number(match[1])
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)
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expect(contextIds).toEqual([1, 2, 3, 4, 5, 6, 7, 8])
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expect(answerPrompt).not.toContain('candidate-1 去健身')
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expect(result).toMatchObject({
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status: 'completed',
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candidateEvidenceCount: 16,
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contextEvidenceCount: 8,
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citationValidation: { status: 'sanitized', invalidCitationIds: ['E10', 'E23'] }
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})
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expect(result.evidence.map((item) => item.id)).toEqual([
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'E1',
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'E2',
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'E3',
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'E4',
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'E5',
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'E6',
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'E7',
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'E8'
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])
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expect(result.answer).toContain('[E1]')
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expect(result.answer).not.toMatch(/\[E(?:10|23)\]/)
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expect(result.aggregation).toMatchObject({
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messageCount: 8,
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peopleCount: 2,
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conversationCount: 2
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})
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expect(result.timings).toMatchObject({
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queryUnderstandingMs: expect.any(Number),
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contactResolutionMs: expect.any(Number),
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knowledgeSearchMs: expect.any(Number),
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ftsMs: 8,
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totalMs: expect.any(Number)
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})
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})
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it('retries a different conversation query after the first search returns zero results', async () => {
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listContactsAsync.mockResolvedValue([
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{
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md5: 'technology-group',
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m_nsUsrName: 'technology-group@chatroom',
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m_nsNickName: '技术交流',
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type: 'group'
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}
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])
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knowledge.search.mockResolvedValue({
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source: 'knowledge',
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state: 'ready',
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indexedMessageCount: 2_000,
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indexedChunkCount: 300,
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totalMessages: 2_000,
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evidence: [
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{
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chunkId: 'technology-chunk',
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conversationId: 'technology-group',
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startTime: 1785900000000,
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endTime: 1785900000000,
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messageId: 'technology-message',
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sender: '小周',
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timestamp: 1785900000000,
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messageIds: ['technology-message'],
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text: '今天讨论了 Electron 的打包问题。'
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}
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],
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timings: {
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workerIpcMs: 1,
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ftsMs: 2,
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messageLoadMs: 1,
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chunkExpandMs: 1,
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rankingMs: 1,
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totalMs: 6
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}
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})
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aiProvider.chat.mockReset()
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aiProvider.chat
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"tool","tool":"search_conversations","arguments":{"query":"技术交流群"}}'
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})
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"tool","tool":"search_conversations","arguments":{"query":"技术交流"}}'
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})
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"tool","tool":"get_conversation_messages","arguments":{"conversationRef":"conversation-1","limit":50}}'
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})
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.mockResolvedValueOnce({
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success: true,
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data: '{"action":"finalize","reason":"已获得会话近期消息"}'
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})
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.mockResolvedValueOnce({ success: true, data: '技术交流讨论了 Electron 打包问题。[E1]' })
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const events: Array<Record<string, unknown>> = []
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const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
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const result = await service.run(
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{ requestId: 'retry-query', text: '我在技术交流群聊了什么？', scope: 'global', range: '30d' },
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(event) => events.push(event as unknown as Record<string, unknown>)
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)
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expect(result).toMatchObject({ status: 'completed', agent: { mode: 'agent', toolCalls: 3 } })
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expect(result.agent.trace).toEqual(
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expect.arrayContaining([
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expect.objectContaining({ toolName: 'search_conversations', resultCount: 0 }),
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expect.objectContaining({ toolName: 'search_conversations', resultCount: 1 }),
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expect.objectContaining({ toolName: 'get_conversation_messages', resultCount: 1 })
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])
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)
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expect(knowledge.search).toHaveBeenCalledWith(
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expect.objectContaining({ terms: [], conversationIds: ['technology-group'], limit: 50 })
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)
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expect(events).toEqual(
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expect.arrayContaining([
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expect.objectContaining({
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stage: 'agent_tool',
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agentTrace: expect.objectContaining({ resultCount: 0 })
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})
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])
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)
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})
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it('uses person lookup then metadata conversation retrieval for a contact summary', async () => {
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listContactsAsync.mockResolvedValue([
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{
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md5: 'zhongtian-contact',
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m_nsUsrName: 'wxid_zhongtian',
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m_nsNickName: '中田健身-弘毅',
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type: 'user'
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}
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])
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knowledge.search.mockResolvedValue({
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source: 'knowledge',
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state: 'ready',
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indexedMessageCount: 2_000,
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indexedChunkCount: 300,
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totalMessages: 2_000,
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evidence: Array.from({ length: 8 }, (_, index) => ({
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...makeCandidate(index + 1),
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conversationId: 'zhongtian-contact'
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})),
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||||
timings: {
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workerIpcMs: 1,
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ftsMs: 0,
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||||
messageLoadMs: 2,
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chunkExpandMs: 0,
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rankingMs: 1,
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totalMs: 4
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},
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conversationRetrieval: {
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conversationId: 'zhongtian-contact',
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totalMessages: 327,
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chunkCount: 10,
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candidateMessages: 30,
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systemMessagesDeprioritized: 2,
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complete: true
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||||
}
|
||||
})
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aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_people","arguments":{"query":"中田健身-弘毅"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"get_conversation_messages","arguments":{"conversationRef":"conversation-1"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({ success: true, data: '你们最近聊过健身安排。[E1]' })
|
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const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'contact-summary',
|
||||
text: '我和中田健身-弘毅最近聊了什么？',
|
||||
scope: 'global',
|
||||
range: '30d'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({ status: 'completed', agent: { mode: 'agent', toolCalls: 2 } })
|
||||
expect(knowledge.search).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
terms: [],
|
||||
conversationIds: ['zhongtian-contact'],
|
||||
startTime: expect.any(Number)
|
||||
})
|
||||
)
|
||||
expect(knowledge.search).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({ terms: expect.arrayContaining(['中田健身-弘毅']) })
|
||||
)
|
||||
expect(aiProvider.chat).toHaveBeenCalledTimes(3)
|
||||
expect(result.agent.trace).toContainEqual(
|
||||
expect.objectContaining({ label: '本地资料已覆盖所选时间范围，可直接整理回答' })
|
||||
)
|
||||
const decisions = result.agent.trace.filter((item) => item.event === 'agentDecision')
|
||||
expect(decisions[0]?.decisionInput).toContain('上一次 Tool 结果：尚未执行 Tool。')
|
||||
expect(decisions[1]?.decisionInput).toContain('中田健身-弘毅')
|
||||
})
|
||||
|
||||
it('keeps a direct contact recap on metadata retrieval when the Agent JSON response is invalid', async () => {
|
||||
listContactsAsync.mockResolvedValue([
|
||||
{
|
||||
md5: 'zhongtian-contact',
|
||||
m_nsUsrName: 'wxid_zhongtian',
|
||||
m_nsNickName: '中田健身-弘毅',
|
||||
type: 'user'
|
||||
}
|
||||
])
|
||||
knowledge.search.mockResolvedValue({
|
||||
source: 'knowledge',
|
||||
state: 'ready',
|
||||
indexedMessageCount: 2_000,
|
||||
indexedChunkCount: 300,
|
||||
totalMessages: 2_000,
|
||||
evidence: Array.from({ length: 8 }, (_, index) => ({
|
||||
...makeCandidate(index + 1),
|
||||
conversationId: 'zhongtian-contact',
|
||||
text: `我肚子前面放盒肌酸，才是 ${118 + index}。`
|
||||
}))
|
||||
})
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({ success: true, data: '我建议先找到这位联系人。' })
|
||||
.mockResolvedValueOnce({ success: true, data: '你们最近聊到了腰围和肌酸。[E1]' })
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'contact-summary-agent-recovery',
|
||||
text: '我和中田健身弘毅最近聊了什么？',
|
||||
scope: 'global',
|
||||
range: 'all'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({
|
||||
status: 'completed',
|
||||
agent: {
|
||||
mode: 'fallback',
|
||||
fallbackReason: expect.stringContaining('相同检索意图的本地确定性策略')
|
||||
}
|
||||
})
|
||||
expect(knowledge.search).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
conversationIds: ['zhongtian-contact'],
|
||||
terms: [],
|
||||
startTime: expect.any(Number)
|
||||
})
|
||||
)
|
||||
expect(knowledge.search).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({ terms: expect.arrayContaining(['中田健身弘毅']) })
|
||||
)
|
||||
})
|
||||
|
||||
it('uses person lookup plus conversation-scoped topic search for a contact question', async () => {
|
||||
listContactsAsync.mockResolvedValue([
|
||||
{
|
||||
md5: 'zhongtian-contact',
|
||||
m_nsUsrName: 'wxid_zhongtian',
|
||||
m_nsNickName: '中田健身-弘毅',
|
||||
type: 'user'
|
||||
}
|
||||
])
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_people","arguments":{"query":"中田健身-弘毅"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_messages","arguments":{"conversationRef":"conversation-1","query":"健身"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"finalize","reason":"已找到话题证据"}'
|
||||
})
|
||||
.mockResolvedValueOnce({ success: true, data: '你们最近聊过健身。[E1]' })
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'contact-topic',
|
||||
text: '我和中田健身-弘毅最近聊过健身吗？',
|
||||
scope: 'global',
|
||||
range: 'all'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({ status: 'completed', agent: { mode: 'agent', toolCalls: 2 } })
|
||||
expect(knowledge.search).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
terms: ['健身'],
|
||||
conversationIds: ['zhongtian-contact'],
|
||||
startTime: expect.any(Number)
|
||||
})
|
||||
)
|
||||
expect(knowledge.search).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({ terms: expect.arrayContaining(['中田健身-弘毅']) })
|
||||
)
|
||||
})
|
||||
|
||||
it('rejects a forbidden contact-recall FTS action and keeps the deterministic fallback semantic', async () => {
|
||||
listContactsAsync.mockResolvedValue([
|
||||
{
|
||||
md5: 'zhongtian-contact',
|
||||
m_nsUsrName: 'wxid_zhongtian',
|
||||
m_nsNickName: '中田健身-弘毅',
|
||||
type: 'user'
|
||||
}
|
||||
])
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_messages","arguments":{"query":"中田健身弘毅"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({ success: true, data: '这不是有效 Agent JSON' })
|
||||
.mockResolvedValueOnce({ success: true, data: '已从会话中整理出最近内容。[E1]' })
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'forbidden-contact-recall-fts',
|
||||
text: '我和中田健身弘毅最近聊了什么？',
|
||||
scope: 'global',
|
||||
range: '30d'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result.agent).toMatchObject({ mode: 'fallback' })
|
||||
expect(result.agent.trace).toContainEqual(
|
||||
expect.objectContaining({
|
||||
toolName: 'search_messages',
|
||||
decision: expect.stringContaining('联系人回顾只允许')
|
||||
})
|
||||
)
|
||||
expect(knowledge.search).toHaveBeenCalledWith(
|
||||
expect.objectContaining({ conversationIds: ['zhongtian-contact'], terms: [] })
|
||||
)
|
||||
expect(knowledge.search).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({ terms: expect.arrayContaining(['中田健身弘毅']) })
|
||||
)
|
||||
})
|
||||
|
||||
it('rejects an unscoped FTS action for a contact topic question', async () => {
|
||||
listContactsAsync.mockResolvedValue([
|
||||
{
|
||||
md5: 'zhongtian-contact',
|
||||
m_nsUsrName: 'wxid_zhongtian',
|
||||
m_nsNickName: '中田健身-弘毅',
|
||||
type: 'user'
|
||||
}
|
||||
])
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({ success: true, data: '无效控制输出' })
|
||||
.mockResolvedValueOnce({ success: true, data: '你们聊过健身。[E1]' })
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
await service.run(
|
||||
{
|
||||
requestId: 'forbidden-unscoped-contact-topic',
|
||||
text: '我和中田健身弘毅最近聊过健身吗？',
|
||||
scope: 'global',
|
||||
range: '30d'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(knowledge.search).toHaveBeenCalledWith(
|
||||
expect.objectContaining({
|
||||
terms: ['健身'],
|
||||
conversationIds: ['zhongtian-contact']
|
||||
})
|
||||
)
|
||||
expect(knowledge.search).not.toHaveBeenCalledWith(
|
||||
expect.objectContaining({ terms: ['健身'], conversationIds: undefined })
|
||||
)
|
||||
})
|
||||
|
||||
it('flags suspicious contact retrieval and refuses to summarize one message as a full conversation', async () => {
|
||||
listContactsAsync.mockResolvedValue([
|
||||
{
|
||||
md5: 'zhongtian-contact',
|
||||
m_nsUsrName: 'wxid_zhongtian',
|
||||
m_nsNickName: '中田健身-弘毅',
|
||||
type: 'user'
|
||||
}
|
||||
])
|
||||
knowledge.search.mockResolvedValue({
|
||||
source: 'knowledge',
|
||||
state: 'ready',
|
||||
indexedMessageCount: 2_000,
|
||||
indexedChunkCount: 300,
|
||||
totalMessages: 2_000,
|
||||
evidence: [{ ...makeCandidate(1), conversationId: 'zhongtian-contact' }],
|
||||
conversationRetrieval: {
|
||||
conversationId: 'zhongtian-contact',
|
||||
totalMessages: 134,
|
||||
chunkCount: 8,
|
||||
candidateMessages: 1,
|
||||
systemMessagesDeprioritized: 1,
|
||||
complete: true
|
||||
}
|
||||
})
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_people","arguments":{"query":"中田健身弘毅"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"get_conversation_messages","arguments":{"conversationRef":"conversation-1"}}'
|
||||
})
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'suspicious-contact-retrieval',
|
||||
text: '我和中田健身弘毅最近聊了什么？',
|
||||
scope: 'global',
|
||||
range: '30d'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({
|
||||
status: 'retrieval_incomplete',
|
||||
retrieval: {
|
||||
conversationId: 'zhongtian-contact',
|
||||
sourceMessageCount: 134,
|
||||
candidateCount: 1,
|
||||
suspicious: true
|
||||
}
|
||||
})
|
||||
expect(knowledge.search).toHaveBeenCalledTimes(2)
|
||||
expect(aiProvider.chat).toHaveBeenCalledTimes(2)
|
||||
})
|
||||
|
||||
it('does not turn a zero-result person lookup or early Agent finalize into contact-name FTS', async () => {
|
||||
listContactsAsync.mockResolvedValue([
|
||||
{
|
||||
md5: 'zhongtian-contact',
|
||||
m_nsUsrName: 'wxid_zhongtian',
|
||||
m_nsNickName: '中田健身-弘毅',
|
||||
type: 'user'
|
||||
}
|
||||
])
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"tool","tool":"search_people","arguments":{"query":"不存在的人"}}'
|
||||
})
|
||||
.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: '{"action":"finalize","reason":"没有足够证据"}'
|
||||
})
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'zero-person-lookup-safe',
|
||||
text: '我和中田健身弘毅最近聊了什么？',
|
||||
scope: 'global',
|
||||
range: '30d'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({ status: 'no_evidence', agent: { mode: 'agent', toolCalls: 1 } })
|
||||
expect(knowledge.search).not.toHaveBeenCalled()
|
||||
expect(aiProvider.chat).toHaveBeenCalledTimes(2)
|
||||
})
|
||||
|
||||
it('stops after five Tool calls instead of searching indefinitely', async () => {
|
||||
aiProvider.chat.mockReset()
|
||||
for (let index = 0; index < 5; index += 1) {
|
||||
aiProvider.chat.mockResolvedValueOnce({
|
||||
success: true,
|
||||
data: `{"action":"tool","tool":"search_conversations","arguments":{"query":"不存在的群${index}"}}`
|
||||
})
|
||||
}
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{
|
||||
requestId: 'max-tool-calls',
|
||||
text: '我在一个不存在的群聊了什么？',
|
||||
scope: 'global',
|
||||
range: '30d'
|
||||
},
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({ status: 'no_evidence', agent: { mode: 'agent', toolCalls: 5 } })
|
||||
expect(result.agent.trace).toContainEqual(
|
||||
expect.objectContaining({ label: '已达到本次检索上限' })
|
||||
)
|
||||
expect(aiProvider.chat).toHaveBeenCalledTimes(5)
|
||||
expect(knowledge.search).not.toHaveBeenCalled()
|
||||
})
|
||||
|
||||
it('falls back to the existing one-shot search when Agent output violates the control protocol', async () => {
|
||||
aiProvider.chat.mockReset()
|
||||
aiProvider.chat
|
||||
.mockResolvedValueOnce({ success: true, data: '我来执行任意代码' })
|
||||
.mockResolvedValueOnce({ success: true, data: '{"intent":"topic","keywords":["健身"]}' })
|
||||
.mockResolvedValueOnce({ success: true, data: '小明聊到健身。[E1]' })
|
||||
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
||||
|
||||
const result = await service.run(
|
||||
{ requestId: 'agent-fallback', text: '最近聊过健身吗？', scope: 'global', range: '7d' },
|
||||
() => undefined
|
||||
)
|
||||
|
||||
expect(result).toMatchObject({ status: 'completed', agent: { mode: 'fallback', toolCalls: 0 } })
|
||||
expect(result.agent.fallbackReason).toContain('受控搜索 Agent')
|
||||
})
|
||||
})
|
||||
Reference in New Issue
Block a user