mirror of
https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-10-03 18:33:14 +08:00
527 lines
21 KiB
TypeScript
527 lines
21 KiB
TypeScript
import { describe, expect, it, vi } from 'vitest'
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import { AskWechatService, type AskWechatLogRecord } from '../../src/main/services/ask-wechat-service'
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import { QueryAgentService, type QueryAgentProvider } from '../../src/main/services/query-agent-service'
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import type { AiSearchPipelineResult } from '../../src/shared/ai-search'
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import type { AskWechatQueryRequest, AskWechatQueryResult } from '../../src/shared/query-agent'
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type ChatResponse = Awaited<ReturnType<QueryAgentProvider['chatWithTools']>>
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type ToolExecutor = (name: string, input: Record<string, unknown>) => Promise<Record<string, unknown>>
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const request = (
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text: string,
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legacy?: AskWechatQueryRequest['legacy']
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): AskWechatQueryRequest => ({ requestId: 'req-1', text, legacy })
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function providerFactory(responses: ChatResponse[], configured = true): {
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provider: QueryAgentProvider
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calls: Array<{ messages: Array<Record<string, unknown>>; tools: string[] }>
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} {
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const calls: Array<{ messages: Array<Record<string, unknown>>; tools: string[] }> = []
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const provider: QueryAgentProvider = {
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getRuntimeConfig: () => ({
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configured,
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providerName: 'Fixture Provider',
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model: 'fixture-model',
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modelName: 'Fixture Model'
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}),
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chatWithTools: vi.fn(async (messages, tools) => {
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calls.push({ messages, tools: tools.map((tool) => tool.function.name) })
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return responses.shift() || { success: true, data: 'done' }
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})
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}
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return { provider, calls }
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}
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const toolCall = (name: string, args: Record<string, unknown>): ChatResponse => ({
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success: true,
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data: '',
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toolCalls: [{ id: `call-${name}`, name, arguments: JSON.stringify(args) }]
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})
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const answer = (data: string): ChatResponse => ({ success: true, data })
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const toolMessages = (messages: Array<Record<string, unknown>>): string =>
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JSON.stringify(messages.filter((message) => message.role === 'tool'))
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const legacyResult = (patch: Record<string, unknown> = {}): AiSearchPipelineResult =>
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({
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requestId: 'req-1',
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status: 'completed',
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answer: 'legacy answer',
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...patch
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}) as unknown as AiSearchPipelineResult
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const answered = (result: AskWechatQueryResult): Extract<AskWechatQueryResult, { status: 'answered' }> => {
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if (result.status !== 'answered') throw new Error(`expected answered, got ${result.status}`)
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return result
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}
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describe('AskWechatService — 桌面问问微信主路径', () => {
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it('A. 「我和 BOBO 第一次聊了什么」走 query_messages 并返回回答', async () => {
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const execute = vi.fn(async () => ({
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status: 'completed',
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returnedCount: 1,
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messages: [{ messageRef: 'ref-1', text: '你好' }]
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}))
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const { provider } = providerFactory([
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toolCall('query_messages', {
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target: { query: 'BOBO' },
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timeRange: { kind: 'all' },
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temporalBasis: { kind: 'none' },
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order: 'asc',
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limit: 1
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}),
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answer('你们的第一次聊天是一条问候。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
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const result = answered(await service.ask(request('我和 BOBO 第一次聊了什么')))
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expect(result.engine).toBe('query-agent')
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expect(result.answer).toBe('你们的第一次聊天是一条问候。')
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expect(result.diagnostics).toMatchObject({
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entry: 'desktop',
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provider: 'Fixture Provider',
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model: 'Fixture Model',
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modelCallCount: 2,
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toolCallCount: 1,
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tools: ['query_messages'],
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outcome: 'answered'
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})
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expect(execute).toHaveBeenCalledTimes(1)
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// temporalBasis 是 LLM-facing 元数据，必须在到达 Query API 前被剥离。
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expect(execute.mock.calls[0][1]).not.toHaveProperty('temporalBasis')
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expect(execute.mock.calls[0][1].timeRange).toEqual({ kind: 'all' })
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})
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it('B. 明确时间（constraint）不会被 retry 扩大，ISO-8601 被换算成 epoch seconds', async () => {
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const execute = vi.fn(async () => ({
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status: 'completed',
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returnedCount: 0,
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coverage: { state: 'complete' }
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}))
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const constraintBasis = { kind: 'constraint', sourceText: '八月份' }
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const { provider, calls } = providerFactory([
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toolCall('query_messages', {
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target: { query: 'BOBO' },
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timeRange: {
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kind: 'absolute',
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startTime: '2026-08-01T00:00:00+08:00',
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endTime: '2026-09-01T00:00:00+08:00'
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},
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temporalBasis: constraintBasis
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}),
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toolCall('query_messages', {
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target: { query: 'BOBO' },
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timeRange: { kind: 'all' },
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temporalBasis: constraintBasis
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}),
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answer('八月份没有找到相关记录。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
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answered(await service.ask(request('八月份 BOBO 有没有给我发过文件')))
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// 第二次改时间范围被 Host 结构性拒绝，没有到达 Query API。
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expect(execute).toHaveBeenCalledTimes(1)
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expect(execute.mock.calls[0][1].timeRange).toEqual({
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kind: 'absolute',
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startTime: Math.floor(Date.parse('2026-08-01T00:00:00+08:00') / 1000),
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endTime: Math.floor(Date.parse('2026-09-01T00:00:00+08:00') / 1000)
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})
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expect(toolMessages(calls[2].messages)).toContain('constraint_time_range_immutable')
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})
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it('C. 模糊时间（recall_hint）首次 0 条时由 Host 自动补查 all，且不占 toolCallCount', async () => {
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const execute = vi
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.fn<ToolExecutor>()
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.mockResolvedValueOnce({ status: 'completed', returnedCount: 0, coverage: { state: 'complete' } })
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.mockResolvedValueOnce({
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status: 'completed',
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returnedCount: 2,
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coverage: { state: 'complete' },
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messages: [{ messageRef: 'ref-2' }]
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})
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const { provider } = providerFactory([
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toolCall('query_messages', {
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target: { query: 'BOBO' },
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timeRange: { kind: 'last_7_days' },
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temporalBasis: { kind: 'recall_hint', sourceText: '前阵子' }
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}),
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answer('原范围没有，全部历史里有两条。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
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const result = answered(await service.ask(request('前阵子 BOBO 好像发过东西给我')))
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expect(execute).toHaveBeenCalledTimes(2)
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expect(execute.mock.calls[1][1].timeRange).toEqual({ kind: 'all' })
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expect(result.diagnostics.toolCallCount).toBe(1)
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expect(result.diagnostics.modelCallCount).toBe(2)
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})
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it('D. 语义检索走 search_messages，queries 映射为 query + variants', async () => {
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const execute = vi.fn(async () => ({ status: 'completed', evidenceCount: 2, evidence: [] }))
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const { provider } = providerFactory([
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toolCall('search_messages', {
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target: { query: 'BOBO' },
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timeRange: { kind: 'all' },
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queries: ['房租', '押金']
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}),
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answer('找到两条相关记录。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
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const result = answered(await service.ask(request('BOBO 提过房租或者押金吗')))
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expect(result.diagnostics.tools).toEqual(['search_messages'])
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expect(execute.mock.calls[0][1]).toMatchObject({ query: '房租', variants: ['押金'] })
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})
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it('E. 宽泛总结走 conversation_overview', async () => {
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const execute = vi.fn(async () => ({ status: 'completed', evidenceCount: 12, evidence: [] }))
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const { provider } = providerFactory([
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toolCall('conversation_overview', {
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target: { query: 'TraceMemo交流群' },
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timeRange: { kind: 'last_7_days' }
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}),
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answer('最近一周主要讨论了两件事。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
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const result = answered(await service.ask(request('TraceMemo交流群最近聊了什么')))
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expect(result.diagnostics.tools).toEqual(['conversation_overview'])
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})
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it('F. 模型追问（clarification）按普通回答返回，并进入下一轮上下文', async () => {
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const { provider, calls } = providerFactory([
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answer('你想问的是哪位联系人？'),
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answer('好的，是 BOBO。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), { entry: 'desktop' })
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const first = answered(await service.ask(request('我们第一次聊了什么')))
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expect(first.answer).toBe('你想问的是哪位联系人？')
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await service.ask(request('BOBO'))
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expect(calls[1].messages.map((message) => message.role)).toEqual([
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'system',
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'user',
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'assistant',
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'user'
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])
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expect(calls[1].messages[1]).toMatchObject({ content: '我们第一次聊了什么' })
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expect(calls[1].messages[2]).toMatchObject({ content: '你想问的是哪位联系人？' })
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})
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it('G. Provider 失败 → 安全文案，且不回退 Legacy', async () => {
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const runLegacy = vi.fn(async () => legacyResult())
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const { provider } = providerFactory([{ success: false, error: 'AI 请求超时', timedOut: true }])
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const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), {
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entry: 'desktop',
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runLegacy
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})
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const result = await service.ask(request('BOBO 说过什么'))
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expect(result.status).toBe('provider_unavailable')
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if (result.status !== 'provider_unavailable') throw new Error('unreachable')
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expect(result.message).toBe('当前 AI 查询服务暂时不可用，请稍后再试。')
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expect(result.diagnostics.outcome).toBe('provider_failure')
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expect(runLegacy).not.toHaveBeenCalled()
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})
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it('G2. Provider 未配置 → 安全文案，且不触发任何模型 / 工具调用', async () => {
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const execute = vi.fn(async () => ({ status: 'completed' }))
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const { provider } = providerFactory([], false)
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const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
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const result = await service.ask(request('BOBO 说过什么'))
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expect(result.status).toBe('provider_unavailable')
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expect(execute).not.toHaveBeenCalled()
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expect(provider.chatWithTools).not.toHaveBeenCalled()
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})
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it('H. Query Agent 查 0 条 → 仍然是它回答，不调用 Legacy', async () => {
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const execute = vi.fn(async () => ({
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status: 'completed',
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returnedCount: 0,
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coverage: { state: 'complete' }
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}))
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const runLegacy = vi.fn(async () => legacyResult())
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const { provider } = providerFactory([
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toolCall('query_messages', {
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target: { query: 'BOBO' },
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timeRange: { kind: 'all' },
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temporalBasis: { kind: 'none' }
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}),
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answer('当前可读取的完整范围里没有找到相关记录。')
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])
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const service = new AskWechatService(new QueryAgentService(provider, execute), {
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entry: 'desktop',
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runLegacy
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})
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const result = answered(await service.ask(request('BOBO 给我发过文件吗')))
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expect(result.answer).toContain('没有找到')
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expect(result.diagnostics.outcome).toBe('answered')
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expect(runLegacy).not.toHaveBeenCalled()
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})
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it('Runtime 抛出未分类异常 → 允许回退 Legacy，并沿用 UI 范围', async () => {
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const runLegacy = vi.fn(async () => legacyResult({ status: 'completed' }))
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const provider: QueryAgentProvider = {
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getRuntimeConfig: () => ({
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configured: true,
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providerName: 'P',
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model: 'm',
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modelName: 'M'
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}),
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chatWithTools: vi.fn(async () => {
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throw new Error('unexpected internal failure')
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})
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}
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const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), {
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entry: 'desktop',
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runLegacy
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})
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const result = await service.ask(
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request('BOBO 说过什么', {
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scope: 'conversation',
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range: '30d',
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conversationId: 'conversation-1'
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})
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)
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expect(result.engine).toBe('legacy')
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if (result.engine !== 'legacy') throw new Error('unreachable')
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expect(result.reason).toBe('runtime_error')
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expect(runLegacy).toHaveBeenCalledTimes(1)
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expect(runLegacy.mock.calls[0][0]).toMatchObject({
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requestId: 'req-1',
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text: 'BOBO 说过什么',
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scope: 'conversation',
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range: '30d',
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conversationId: 'conversation-1'
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})
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})
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it('Runtime 异常且没有 Legacy 通道（Agent Hub）→ 明确文案，不抛异常', async () => {
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const provider: QueryAgentProvider = {
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getRuntimeConfig: () => ({ configured: true, providerName: 'P', model: 'm', modelName: 'M' }),
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chatWithTools: vi.fn(async () => {
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throw new Error('unexpected internal failure')
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})
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}
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const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), {
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entry: 'agent-hub'
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})
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const result = await service.ask(request('BOBO 说过什么'))
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expect(result.status).toBe('error')
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if (result.status !== 'error') throw new Error('unreachable')
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expect(result.message).toBe('本次查询没有完成，请稍后再试或换一种问法。')
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expect(result.diagnostics.entry).toBe('agent-hub')
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})
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it('超过工具调用上限 → 判为 Runtime 失败（可回退），不伪装成正常回答', async () => {
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let counter = 0
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const execute = vi.fn(async () => ({ status: 'completed', returnedCount: 0 }))
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const provider: QueryAgentProvider = {
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getRuntimeConfig: () => ({ configured: true, providerName: 'P', model: 'm', modelName: 'M' }),
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chatWithTools: vi.fn(async () => {
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counter += 1
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return {
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success: true,
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data: '',
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toolCalls: [
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{
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id: `call-${counter}`,
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name: 'query_messages',
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arguments: JSON.stringify({
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target: { query: `BOBO${counter}` },
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timeRange: { kind: 'all' },
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temporalBasis: { kind: 'none' }
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})
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}
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]
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}
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})
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}
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const service = new AskWechatService(new QueryAgentService(provider, execute), {
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entry: 'agent-hub'
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})
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const result = await service.ask(request('一直查不完的问题'))
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expect(result.status).toBe('error')
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if (result.status !== 'error') throw new Error('unreachable')
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expect(result.diagnostics.outcome).toBe('tool_limit')
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})
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it('空问题 → 明确的用户文案', async () => {
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const { provider } = providerFactory([])
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const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), { entry: 'desktop' })
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const result = await service.ask(request(' '))
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expect(result.status).toBe('error')
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if (result.status !== 'error') throw new Error('unreachable')
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expect(result.message).toBe('请先输入想了解的问题。')
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expect(result.diagnostics.outcome).toBe('invalid_question')
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})
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it('本地日志必须包含问题与模型回答原文，方便回放排查', async () => {
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const logs: AskWechatLogRecord[] = []
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const { provider } = providerFactory([answer('BOBO 最近在准备搬家，提到了房租和押金。')])
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const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), {
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entry: 'desktop',
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log: (record) => logs.push(record)
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})
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await service.ask(request('BOBO 最近在忙什么'))
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expect(logs).toHaveLength(1)
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// 形态字段仍然一个不少（排查时既要知道"问了什么"，也要知道"跑了什么工具、多久"）。
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for (const key of ['entry', 'model', 'modelCallCount', 'outcome', 'provider', 'toolCallCount', 'tools', 'totalMs']) {
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expect(logs[0].details).toHaveProperty(key)
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}
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// 措辞回归：真机上曾出现"图片已识别出文字却答'没有取得 OCR 文字'"，
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// 当时日志里只有工具名与次数，无法判断是索引没建还是链路没接上。
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// 现在问答原文进入**本机**日志（不上传、不进遥测），可以直接回放。
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expect(logs[0].details?.question).toBe('BOBO 最近在忙什么')
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expect(String(logs[0].details?.answer)).toContain('准备搬家')
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})
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it('图片 OCR 的两条结构化事实进入诊断（不重复正文）', async () => {
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const logs: AskWechatLogRecord[] = []
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const { provider } = providerFactory([answer('那张图里有价格文字。')])
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const runtime = new QueryAgentService(provider, vi.fn())
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// 直接在 Runtime 结果里放一条带图片 OCR 的 trace，验证聚合口径。
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vi.spyOn(runtime, 'run').mockResolvedValue({
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question: '图里写了什么',
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provider: 'Fixture',
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model: 'fixture',
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modelCallCount: 1,
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toolCallCount: 1,
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toolTotalMs: 5,
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totalMs: 10,
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modelDurationsMs: [],
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modelDiagnostics: [],
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answer: '那张图里有价格文字。',
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traces: [
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{
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toolName: 'query_messages',
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input: {},
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durationMs: 5,
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status: 'completed',
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imageOcrTextCount: 3,
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imageOcrCoverageState: 'partial'
|
||
}
|
||
]
|
||
} as never)
|
||
const service = new AskWechatService(runtime, {
|
||
entry: 'desktop',
|
||
log: (record) => logs.push(record)
|
||
})
|
||
|
||
await service.ask(request('图里写了什么'))
|
||
|
||
expect(logs[0].details?.imageOcrTextCount).toBe(3)
|
||
expect(logs[0].details?.imageOcrCoverageState).toBe('partial')
|
||
})
|
||
|
||
it('forgetConversation 清掉指定会话的澄清上下文', async () => {
|
||
const { provider, calls } = providerFactory([
|
||
answer('哪一位？'),
|
||
answer('好的。'),
|
||
answer('好的。')
|
||
])
|
||
const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), { entry: 'desktop' })
|
||
await service.ask(request('我们第一次聊了什么'))
|
||
service.forgetConversation()
|
||
await service.ask(request('BOBO'))
|
||
|
||
expect(calls[1].messages.map((message) => message.role)).toEqual(['system', 'user'])
|
||
})
|
||
})
|
||
|
||
describe('AskWechatService — 搜索范围（conversationScope）', () => {
|
||
it('把 UI 的 scope 透传到 Tool 执行上下文，并让范围说明进入模型上下文', async () => {
|
||
const seen: Array<Record<string, unknown> | undefined> = []
|
||
const execute = vi.fn(async (_name: string, _input: Record<string, unknown>, context?: { conversationScope?: unknown }) => {
|
||
seen.push(context?.conversationScope as Record<string, unknown> | undefined)
|
||
return { status: 'completed', returnedCount: 0 }
|
||
})
|
||
const { provider, calls } = providerFactory([
|
||
toolCall('search_messages', { timeRange: { kind: 'all' }, queries: ['健身'] }),
|
||
answer('范围内没有找到。')
|
||
])
|
||
const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
|
||
|
||
await service.ask({
|
||
requestId: 'req-1',
|
||
text: '最近谁聊过健身',
|
||
scope: { scope: { kind: 'groups' }, label: '群聊专属' }
|
||
})
|
||
|
||
expect(seen[0]).toEqual({ kind: 'groups' })
|
||
// 范围说明只描述边界；强制由 Engine 完成（越界 target 会被结构化拒绝）。
|
||
expect(String(calls[0].messages[0]?.content)).toContain('群聊专属')
|
||
expect(String(calls[0].messages[0]?.content)).toContain('群成员实际发送的消息')
|
||
})
|
||
|
||
it('没有 scope 时不注入范围说明（保持毕业版本的 messages 形状）', async () => {
|
||
const { provider, calls } = providerFactory([answer('好的')])
|
||
const service = new AskWechatService(new QueryAgentService(provider, vi.fn()), { entry: 'agent-hub' })
|
||
|
||
await service.ask(request('你好'))
|
||
|
||
expect(calls[0].messages.map((message) => message.role)).toEqual(['system', 'user'])
|
||
})
|
||
|
||
it('回答结果带真实统计与证据（供 UI 顶部与右侧面板使用）', async () => {
|
||
const execute = vi.fn(async () => ({
|
||
status: 'completed',
|
||
evidenceCount: 2,
|
||
evidence: [
|
||
{
|
||
messageRef: 'ref-1',
|
||
conversationName: 'TraceMemo 交流群',
|
||
conversationType: 'group',
|
||
sender: '张三',
|
||
timestamp: 1_787_650_302_000,
|
||
sourceKind: 'text',
|
||
text: '最近开始健身了'
|
||
}
|
||
]
|
||
}))
|
||
const { provider } = providerFactory([
|
||
toolCall('search_messages', { timeRange: { kind: 'all' }, queries: ['健身'] }),
|
||
answer('张三提过。')
|
||
])
|
||
const service = new AskWechatService(new QueryAgentService(provider, execute), { entry: 'desktop' })
|
||
|
||
const result = answered(
|
||
await service.ask({ requestId: 'req-1', text: '谁聊过健身', scope: { scope: { kind: 'groups' } } })
|
||
)
|
||
|
||
expect(result.evidence).toHaveLength(1)
|
||
expect(result.evidence[0]).toMatchObject({
|
||
conversationName: 'TraceMemo 交流群',
|
||
conversationType: 'group',
|
||
sender: '张三',
|
||
source: 'search_messages'
|
||
})
|
||
expect(result.stats.tools).toEqual(['search_messages'])
|
||
expect(result.stats.reads.evidenceCount).toBe(1)
|
||
expect(result.stats.scope).toEqual({ kind: 'groups' })
|
||
})
|
||
})
|