mirror of
https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-08-17 19:47:08 +08:00
733 lines
25 KiB
TypeScript
733 lines
25 KiB
TypeScript
import { beforeEach, describe, expect, it, vi } from 'vitest'
|
|
|
|
const { chatState, listContactsAsync } = vi.hoisted(() => ({
|
|
chatState: { ready: true },
|
|
listContactsAsync: vi.fn()
|
|
}))
|
|
|
|
vi.mock('../../src/main/services/chat-service', () => ({
|
|
isReady: () => chatState.ready,
|
|
listContactsAsync
|
|
}))
|
|
|
|
import { AiSearchPipelineService } from '../../src/main/services/ai-search-pipeline-service'
|
|
import type { KnowledgeEvidence } from '../../src/shared/knowledge'
|
|
|
|
const makeCandidate = (index: number): KnowledgeEvidence => ({
|
|
chunkId: `chunk-${index}`,
|
|
conversationId: index % 2 ? 'fitness-group-a' : 'fitness-group-b',
|
|
startTime: 1785900000000 + index,
|
|
endTime: 1785900000000 + index,
|
|
messageId: `message-${index}`,
|
|
sender: index % 2 ? '杨伟' : '东方小唠',
|
|
senderId: index % 2 ? 'member-yang' : 'member-dongfang',
|
|
timestamp: 1785900000000 + index,
|
|
messageIds: [`message-${index}`],
|
|
text: `candidate-${index} 去健身`,
|
|
score: -index
|
|
})
|
|
|
|
describe('AiSearchPipelineService', () => {
|
|
const knowledge = { search: vi.fn() }
|
|
const aiProvider = { getRuntimeConfig: vi.fn(), chat: vi.fn() }
|
|
|
|
beforeEach(() => {
|
|
chatState.ready = true
|
|
listContactsAsync.mockReset()
|
|
knowledge.search.mockReset()
|
|
aiProvider.getRuntimeConfig.mockReset()
|
|
aiProvider.chat.mockReset()
|
|
listContactsAsync.mockResolvedValue([
|
|
{
|
|
md5: 'fitness-group',
|
|
m_nsUsrName: 'fitness-group@chatroom',
|
|
m_nsNickName: '健身交流组',
|
|
type: 'group'
|
|
}
|
|
])
|
|
knowledge.search.mockResolvedValue({
|
|
source: 'knowledge',
|
|
state: 'ready',
|
|
indexedMessageCount: 2_000,
|
|
indexedChunkCount: 300,
|
|
totalMessages: 2_000,
|
|
evidence: [
|
|
{
|
|
chunkId: 'chunk-1',
|
|
conversationId: 'fitness-group',
|
|
startTime: 1785900000000,
|
|
endTime: 1785900000000,
|
|
messageId: 'message-1',
|
|
sender: '小明',
|
|
senderId: 'wxid_fixture',
|
|
timestamp: 1785900000000,
|
|
messageIds: ['message-1'],
|
|
text: '今天下班去健身。'
|
|
}
|
|
]
|
|
})
|
|
aiProvider.getRuntimeConfig.mockReturnValue({
|
|
configured: true,
|
|
providerName: 'DeepSeek',
|
|
modelName: 'DeepSeek Chat'
|
|
})
|
|
aiProvider.chat
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
|
|
})
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"finalize","reason":"已找到足够的相关消息"}'
|
|
})
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '小明提到今天下班去健身。[E1]',
|
|
usage: { input: 120 }
|
|
})
|
|
})
|
|
|
|
it('emits actual planning, knowledge, evidence and AI completion states', async () => {
|
|
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
|
const events: Array<{ stage: string; status: string; message: string }> = []
|
|
const result = await service.run(
|
|
{
|
|
requestId: 'fixture-request',
|
|
text: '最近谁聊过健身',
|
|
scope: 'global',
|
|
range: '7d'
|
|
},
|
|
(event) => events.push(event)
|
|
)
|
|
|
|
expect(knowledge.search).toHaveBeenCalledWith(
|
|
expect.objectContaining({ text: '最近谁聊过健身', terms: ['健身'] })
|
|
)
|
|
expect(events).toEqual(
|
|
expect.arrayContaining([
|
|
expect.objectContaining({ stage: 'query_understanding', status: 'running' }),
|
|
expect.objectContaining({ stage: 'agent_start', status: 'completed' }),
|
|
expect.objectContaining({ stage: 'agent_tool', status: 'completed' }),
|
|
expect.objectContaining({ stage: 'search_plan_ready', status: 'completed' }),
|
|
expect.objectContaining({ stage: 'knowledge_searching', status: 'completed' }),
|
|
expect.objectContaining({ stage: 'evidence_ready', status: 'completed' }),
|
|
expect.objectContaining({ stage: 'aggregation', status: 'completed' }),
|
|
expect.objectContaining({
|
|
stage: 'ai_generating',
|
|
status: 'running',
|
|
modelName: 'DeepSeek Chat'
|
|
}),
|
|
expect.objectContaining({ stage: 'completed', status: 'completed' })
|
|
])
|
|
)
|
|
expect(result).toMatchObject({
|
|
status: 'completed',
|
|
candidateEvidenceCount: 1,
|
|
contextEvidenceCount: 1,
|
|
answer: '小明提到今天下班去健身。[E1]',
|
|
ai: { inputTokens: 120, inputTokensEstimated: false }
|
|
})
|
|
expect(result.agent).toMatchObject({ mode: 'agent', toolCalls: 1 })
|
|
})
|
|
|
|
it('keeps real evidence when the answer model fails', async () => {
|
|
aiProvider.chat.mockReset()
|
|
aiProvider.chat
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
|
|
})
|
|
.mockResolvedValueOnce({ success: true, data: '{"action":"finalize","reason":"证据足够"}' })
|
|
.mockResolvedValueOnce({ success: false, error: '模型超时' })
|
|
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
|
const events: Array<{ stage: string; status: string; message: string }> = []
|
|
const result = await service.run(
|
|
{
|
|
requestId: 'fixture-ai-error',
|
|
text: '最近聊过健身吗',
|
|
scope: 'global',
|
|
range: '7d'
|
|
},
|
|
(event) => events.push(event)
|
|
)
|
|
|
|
expect(result).toMatchObject({ status: 'ai_failed', evidence: [expect.any(Object)] })
|
|
expect(events).toContainEqual(
|
|
expect.objectContaining({ stage: 'ai_generating', status: 'error', error: '模型超时' })
|
|
)
|
|
})
|
|
|
|
it('uses Final Evidence only for AI context and strips invalid citations', async () => {
|
|
knowledge.search.mockResolvedValue({
|
|
source: 'knowledge',
|
|
state: 'ready',
|
|
indexedMessageCount: 2_000,
|
|
indexedChunkCount: 300,
|
|
totalMessages: 2_000,
|
|
evidence: Array.from({ length: 16 }, (_, index) => makeCandidate(index + 1)),
|
|
timings: {
|
|
workerIpcMs: 4,
|
|
ftsMs: 8,
|
|
messageLoadMs: 5,
|
|
chunkExpandMs: 6,
|
|
rankingMs: 2,
|
|
totalMs: 25
|
|
}
|
|
})
|
|
aiProvider.chat.mockReset()
|
|
aiProvider.chat
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"tool","tool":"search_messages","arguments":{"query":"健身"}}'
|
|
})
|
|
.mockResolvedValueOnce({ success: true, data: '{"action":"finalize","reason":"证据足够"}' })
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '杨伟聊过去健身。[E1] 错误引用。[E10][E23]',
|
|
usage: { input: 160 }
|
|
})
|
|
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
|
|
|
const result = await service.run(
|
|
{
|
|
requestId: 'final-evidence-only',
|
|
text: '全局搜一下 谁聊过 去健身',
|
|
scope: 'global',
|
|
range: '30d'
|
|
},
|
|
() => undefined
|
|
)
|
|
|
|
const answerPrompt = aiProvider.chat.mock.calls[2][0][1].content as string
|
|
const contextIds = Array.from(answerPrompt.matchAll(/\[E(\d+)\]\nconversationId:/g)).map(
|
|
(match) => Number(match[1])
|
|
)
|
|
expect(contextIds).toEqual([1, 2, 3, 4, 5, 6, 7, 8])
|
|
expect(answerPrompt).not.toContain('candidate-1 去健身')
|
|
expect(result).toMatchObject({
|
|
status: 'completed',
|
|
candidateEvidenceCount: 16,
|
|
contextEvidenceCount: 8,
|
|
citationValidation: { status: 'sanitized', invalidCitationIds: ['E10', 'E23'] }
|
|
})
|
|
expect(result.evidence.map((item) => item.id)).toEqual([
|
|
'E1',
|
|
'E2',
|
|
'E3',
|
|
'E4',
|
|
'E5',
|
|
'E6',
|
|
'E7',
|
|
'E8'
|
|
])
|
|
expect(result.answer).toContain('[E1]')
|
|
expect(result.answer).not.toMatch(/\[E(?:10|23)\]/)
|
|
expect(result.aggregation).toMatchObject({
|
|
messageCount: 8,
|
|
peopleCount: 2,
|
|
conversationCount: 2
|
|
})
|
|
expect(result.timings).toMatchObject({
|
|
queryUnderstandingMs: expect.any(Number),
|
|
contactResolutionMs: expect.any(Number),
|
|
knowledgeSearchMs: expect.any(Number),
|
|
ftsMs: 8,
|
|
totalMs: expect.any(Number)
|
|
})
|
|
})
|
|
|
|
it('retries a different conversation query after the first search returns zero results', async () => {
|
|
listContactsAsync.mockResolvedValue([
|
|
{
|
|
md5: 'technology-group',
|
|
m_nsUsrName: 'technology-group@chatroom',
|
|
m_nsNickName: '技术交流',
|
|
type: 'group'
|
|
}
|
|
])
|
|
knowledge.search.mockResolvedValue({
|
|
source: 'knowledge',
|
|
state: 'ready',
|
|
indexedMessageCount: 2_000,
|
|
indexedChunkCount: 300,
|
|
totalMessages: 2_000,
|
|
evidence: [
|
|
{
|
|
chunkId: 'technology-chunk',
|
|
conversationId: 'technology-group',
|
|
startTime: 1785900000000,
|
|
endTime: 1785900000000,
|
|
messageId: 'technology-message',
|
|
sender: '小周',
|
|
timestamp: 1785900000000,
|
|
messageIds: ['technology-message'],
|
|
text: '今天讨论了 Electron 的打包问题。'
|
|
}
|
|
],
|
|
timings: {
|
|
workerIpcMs: 1,
|
|
ftsMs: 2,
|
|
messageLoadMs: 1,
|
|
chunkExpandMs: 1,
|
|
rankingMs: 1,
|
|
totalMs: 6
|
|
}
|
|
})
|
|
aiProvider.chat.mockReset()
|
|
aiProvider.chat
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"tool","tool":"search_conversations","arguments":{"query":"技术交流群"}}'
|
|
})
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"tool","tool":"search_conversations","arguments":{"query":"技术交流"}}'
|
|
})
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"tool","tool":"get_conversation_messages","arguments":{"conversationRef":"conversation-1","limit":50}}'
|
|
})
|
|
.mockResolvedValueOnce({
|
|
success: true,
|
|
data: '{"action":"finalize","reason":"已获得会话近期消息"}'
|
|
})
|
|
.mockResolvedValueOnce({ success: true, data: '技术交流讨论了 Electron 打包问题。[E1]' })
|
|
const events: Array<Record<string, unknown>> = []
|
|
const service = new AiSearchPipelineService(knowledge as never, aiProvider as never)
|
|
|
|
const result = await service.run(
|
|
{ requestId: 'retry-query', text: '我在技术交流群聊了什么？', scope: 'global', range: '30d' },
|
|
(event) => events.push(event as unknown as Record<string, unknown>)
|
|
)
|
|
|
|
expect(result).toMatchObject({ status: 'completed', agent: { mode: 'agent', toolCalls: 3 } })
|
|
expect(result.agent.trace).toEqual(
|
|
expect.arrayContaining([
|
|
expect.objectContaining({ toolName: 'search_conversations', resultCount: 0 }),
|
|
expect.objectContaining({ toolName: 'search_conversations', resultCount: 1 }),
|
|
expect.objectContaining({ toolName: 'get_conversation_messages', resultCount: 1 })
|
|
])
|
|
)
|
|
expect(knowledge.search).toHaveBeenCalledWith(
|
|
expect.objectContaining({ terms: [], conversationIds: ['technology-group'], limit: 50 })
|
|
)
|
|
expect(events).toEqual(
|
|
expect.arrayContaining([
|
|
expect.objectContaining({
|
|
stage: 'agent_tool',
|
|
agentTrace: expect.objectContaining({ resultCount: 0 })
|
|
})
|
|
])
|
|
)
|
|
})
|
|
|
|
it('uses person lookup then metadata conversation retrieval for a contact summary', 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'
|
|
})),
|
|
timings: {
|
|
workerIpcMs: 1,
|
|
ftsMs: 0,
|
|
messageLoadMs: 2,
|
|
chunkExpandMs: 0,
|
|
rankingMs: 1,
|
|
totalMs: 4
|
|
},
|
|
conversationRetrieval: {
|
|
conversationId: 'zhongtian-contact',
|
|
totalMessages: 327,
|
|
chunkCount: 10,
|
|
candidateMessages: 30,
|
|
systemMessagesDeprioritized: 2,
|
|
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"}}'
|
|
})
|
|
.mockResolvedValueOnce({ success: true, data: '你们最近聊过健身安排。[E1]' })
|
|
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')
|
|
})
|
|
})
|