mirror of
https://wget.la/https://github.com/Wxw-Gu/WechatExplorer
synced 2026-10-04 02:53:47 +08:00
669 lines
20 KiB
TypeScript
669 lines
20 KiB
TypeScript
import type {
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KnowledgeEvidence,
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KnowledgeSearchIpcResult,
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KnowledgeVoiceCoverage
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} from './knowledge'
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export type AiSearchScope = 'global' | 'groups' | 'contacts' | 'conversation'
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export type AiSearchRange = 'today' | '7d' | '30d' | 'all'
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/**
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* Retrieval semantics, not presentation labels. Each intent has a constrained
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* execution path in the main process; a model must not be able to quietly turn
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* an identity lookup into a generic message-keyword search.
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*/
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export type AiSearchIntent =
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| 'conversation_recall'
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| 'conversation_topic_search'
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| 'global_topic_search'
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| 'conversation_name_search'
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| 'general'
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export interface AiSearchTimeRange {
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/** Unix seconds. Undefined start means the user explicitly allowed all history. */
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startTime?: number
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endTime?: number
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label: string
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reason: string
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source: 'ui' | 'query' | 'user_retry' | 'user_selected'
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}
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export type AiSearchProgressStage =
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| 'query_understanding'
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| 'agent_start'
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| 'agent_tool'
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| 'agent_decision'
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| 'search_plan_ready'
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| 'knowledge_searching'
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| 'evidence_ranking'
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| 'evidence_ready'
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| 'aggregation'
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| 'ai_generating'
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| 'completed'
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| 'error'
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export type AiSearchProgressStatus = 'running' | 'completed' | 'error'
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export interface AiSearchPlan {
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intent: AiSearchIntent
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keywords: string[]
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variants: string[]
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source: 'local' | 'ai' | 'hybrid'
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scopeLabel: string
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rangeLabel: string
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timeRange: AiSearchTimeRange
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contactNames: string[]
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/** A user-supplied identity candidate. It must be resolved by Contact Resolution. */
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contactQuery?: string
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/** The message-content query, never a contact display name. */
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topicQuery?: string
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}
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export interface AiSearchPipelineRequest {
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requestId: string
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text: string
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scope: AiSearchScope
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range: AiSearchRange
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conversationId?: string
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/** Explicit UI choice or retry takes precedence over natural-language inference. */
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timeRangeOverride?: AiSearchTimeRange
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}
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export interface AiSearchProgressEvent {
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requestId: string
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stage: AiSearchProgressStage
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status: AiSearchProgressStatus
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message: string
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plan?: AiSearchPlan
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stats?: {
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knowledgeMessageCount?: number
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matchedMessages?: number
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evidenceCount?: number
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contextEvidenceCount?: number
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tokenEstimate?: number
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inputTokens?: number
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inputTokensEstimated?: boolean
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elapsedMs?: number
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deduplicatedMessages?: number
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peopleCount?: number
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conversationCount?: number
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}
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timings?: AiSearchPipelineTimings
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modelName?: string
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agentTrace?: AiSearchAgentTraceItem
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error?: string
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}
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export type AiSearchAgentToolName =
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| 'search_conversations'
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| 'search_people'
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| 'search_messages'
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| 'get_conversation_messages'
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| 'get_messages_by_time'
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| 'get_message_context'
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export type AiSearchAgentTraceEvent =
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| 'agentStart'
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| 'toolCallStart'
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| 'toolCallEnd'
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| 'agentDecision'
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| 'evidenceBuild'
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| 'summaryStart'
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| 'summaryEnd'
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| 'fallback'
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/** Public trace: deliberately contains no SQL, paths, raw IDs, or Worker details. */
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export interface AiSearchAgentTraceItem {
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sequence: number
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event: AiSearchAgentTraceEvent
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label: string
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toolName?: AiSearchAgentToolName
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/** Sanitized, human-readable arguments only. */
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arguments?: Record<string, string | number | boolean>
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resultCount?: number
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uniqueCandidateCount?: number
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newCandidateCount?: number
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newEvidenceCount?: number
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newConversationCount?: number
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newSenderCount?: number
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queryFingerprint?: string
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hasMore?: boolean
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elapsedMs?: number
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decision?: string
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}
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export interface AiSearchAgentRun {
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mode: 'agent' | 'fallback'
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toolCalls: number
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trace: AiSearchAgentTraceItem[]
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fallbackReason?: string
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}
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export interface AiSearchPipelineEvidence extends KnowledgeEvidence {
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conversationName: string
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conversationType: 'user' | 'group'
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}
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/** A program-generated, stable citation. This is the only Evidence shape sent to AI/UI. */
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export interface AiSearchFinalEvidence extends AiSearchPipelineEvidence {
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id: `E${number}`
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}
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export interface AiSearchPersonAggregation {
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id: string
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name: string
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messageCount: number
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conversationCount: number
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lastMessageAt: number
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evidenceIds: Array<`E${number}`>
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}
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export interface AiSearchConversationAggregation {
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id: string
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name: string
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type: 'user' | 'group'
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messageCount: number
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peopleCount: number
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lastMessageAt: number
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evidenceIds: Array<`E${number}`>
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}
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export interface AiSearchAggregation {
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messageCount: number
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peopleCount: number
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conversationCount: number
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people: AiSearchPersonAggregation[]
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conversations: AiSearchConversationAggregation[]
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}
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/** All fields are directly measured around real work. */
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export interface AiSearchPipelineTimings {
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queryUnderstandingMs: number
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contactResolutionMs: number
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knowledgeSearchMs: number
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workerIpcMs: number
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workerBootMs: number
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dispatchMs: number
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workerSqlMs: number
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responseSerializeMs: number
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responseTransferMs: number
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workerQueueMs: number
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workerExecutionMs: number
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globalCountMs: number
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voiceCoverageMs: number
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wcdbQueueMs: number
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wcdbExecutionMs: number
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senderEnrichmentMs: number
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ipcMs: number
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serializationMs: number
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otherMs: number
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ftsMs: number
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chunkExpandMs: number
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messageLoadMs: number
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rankingMs: number
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candidateRankingMs: number
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evidenceBuildMs: number
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aggregationMs: number
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contextPreparationMs: number
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agentDecisionMs: number
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agentToolMs: number
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aiGenerationMs: number
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totalMs: number
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}
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export interface AiSearchCitationValidation {
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status: 'valid' | 'sanitized'
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invalidCitationIds: string[]
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}
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/** Truthful retrieval metadata shared by the AI, UI and diagnostics. */
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export interface AiSearchRetrievalContract {
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intent: AiSearchIntent
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conversationId?: string
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timeRange: AiSearchTimeRange
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retrievalMode:
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| 'conversation_metadata'
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| 'conversation_topic_fts'
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| 'global_fts'
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| 'conversation_name'
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| 'unresolved_identity'
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candidateCount: number
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uniqueCandidateCount: number
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sourceMessageCount?: number
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sourceCoverage: 'complete' | 'partial' | 'keyword_match' | 'unknown'
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isComplete: boolean
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fallbackUsed: boolean
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fallbackReason?: string
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suspicious: boolean
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voiceCoverage?: KnowledgeVoiceCoverage
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}
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export interface AiSearchPipelineResult {
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requestId: string
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status:
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| 'completed'
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| 'no_evidence'
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| 'retrieval_incomplete'
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| 'ai_failed'
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| 'failed'
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| 'cancelled'
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plan: AiSearchPlan
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knowledge: Pick<
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KnowledgeSearchIpcResult,
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| 'source'
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| 'state'
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| 'fallbackReason'
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| 'indexedMessageCount'
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| 'indexedChunkCount'
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| 'totalMessages'
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| 'voiceCoverage'
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>
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candidateEvidenceCount: number
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retrieval: AiSearchRetrievalContract
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evidence: AiSearchFinalEvidence[]
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contextEvidenceCount: number
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aggregation: AiSearchAggregation
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agent: AiSearchAgentRun
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citationValidation?: AiSearchCitationValidation
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timings: AiSearchPipelineTimings
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answer?: string
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ai?: {
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providerName: string
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modelName: string
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inputTokens?: number
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inputTokensEstimated: boolean
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}
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error?: string
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errorStage?: Exclude<AiSearchProgressStage, 'completed' | 'error'>
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elapsedMs: number
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}
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export interface AiSearchCancelResult {
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cancelled: boolean
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}
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const RANGE_LABELS: Record<AiSearchRange, string> = {
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today: '今天',
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'7d': '近 7 天',
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'30d': '近 30 天',
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all: '全部历史'
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}
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const SEARCH_INTENT_PHRASES = [
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'全局搜一下',
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'全局搜索',
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'搜索一下',
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'搜一下',
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'查询一下',
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'查一下',
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'找一下',
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'我和谁聊过',
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'谁和我聊过',
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'谁聊过',
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'哪些人和我聊过',
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'最近讨论了什么',
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'最近聊了什么',
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'最近说了什么',
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'讨论了什么',
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'讨论什么',
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'聊了什么',
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'聊些什么',
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'说了什么',
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'说些什么',
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'最近讨论',
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'最近聊天',
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'这个话题',
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'相关话题',
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'的聊天',
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'的内容',
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'的记录',
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'关于',
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'聊天',
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'记录',
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'聊天记录',
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'帮我',
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'请问',
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'最近'
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].sort((left, right) => right.length - left.length)
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const RECALL_QUESTION = '聊了什么|聊过什么|说了什么|谈了什么|聊了啥|聊啥|说了啥|说啥'
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const SEARCH_STOP_WORDS = new Set([
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'我',
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'谁',
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'什么',
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'哪些',
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'哪个',
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'人',
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'和',
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'聊过',
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'说过',
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'提到',
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'讨论',
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'聊天',
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'记录',
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'说',
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'聊',
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'话题',
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'内容',
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'相关',
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'最近',
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'一下'
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])
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export const aiSearchRangeLabel = (range: AiSearchRange): string => RANGE_LABELS[range]
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export const aiSearchRangeStart = (range: AiSearchRange): number | undefined => {
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if (range === 'all') return undefined
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if (range === 'today') {
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const now = new Date()
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return Math.floor(new Date(now.getFullYear(), now.getMonth(), now.getDate()).getTime() / 1000)
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}
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return Math.floor(Date.now() / 1000) - (range === '7d' ? 7 : 30) * 86400
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}
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const dayStart = (date: Date): number =>
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Math.floor(new Date(date.getFullYear(), date.getMonth(), date.getDate()).getTime() / 1000)
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const currentYearStart = (date: Date): number =>
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Math.floor(new Date(date.getFullYear(), 0, 1).getTime() / 1000)
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const currentMonthStart = (date: Date): number =>
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Math.floor(new Date(date.getFullYear(), date.getMonth(), 1).getTime() / 1000)
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const CHINESE_NUMBERS: Record<string, number> = {
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一: 1,
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二: 2,
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两: 2,
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三: 3,
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四: 4,
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五: 5,
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六: 6,
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七: 7,
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八: 8,
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九: 9,
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十: 10
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}
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const parseNaturalNumber = (value: string | undefined): number | undefined => {
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if (!value) return undefined
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const numeric = Number(value)
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if (Number.isFinite(numeric)) return numeric
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return CHINESE_NUMBERS[value]
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}
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/**
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* Query time expressions are part of SearchPlan, never a renderer-only rule.
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* A natural-language time constraint is more specific than the broad "all" UI scope.
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*/
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export const inferAiSearchTimeRange = (
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query: string,
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uiRange: AiSearchRange,
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now = new Date(),
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override?: AiSearchTimeRange
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): AiSearchTimeRange => {
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if (override?.source === 'user_retry' || override?.source === 'user_selected') return override
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const nowSeconds = Math.floor(now.getTime() / 1000)
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const fromQuery = (startTime: number, label: string, reason: string): AiSearchTimeRange => ({
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startTime,
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endTime: nowSeconds,
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label,
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reason,
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source: 'query'
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})
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const recentDays = query.match(/最近\s*(\d{1,3}|[一二两三四五六七八九十])\s*天/)
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if (recentDays) {
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const days = Math.max(1, Math.min(365, parseNaturalNumber(recentDays[1]) || 30))
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return fromQuery(nowSeconds - days * 86400, `近 ${days} 天`, `用户说“最近 ${days} 天”`)
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}
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const recentMonths = query.match(/最近\s*(\d{1,2}|[一二两三四五六七八九十])\s*个?月/)
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if (recentMonths) {
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const months = Math.max(1, Math.min(24, parseNaturalNumber(recentMonths[1]) || 1))
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const start = new Date(now.getFullYear(), now.getMonth() - months, now.getDate()).getTime()
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return fromQuery(Math.floor(start / 1000), `近 ${months} 个月`, `用户说“最近 ${months} 个月”`)
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}
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if (/刚刚|刚才/.test(query))
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return fromQuery(nowSeconds - 24 * 3600, '近 24 小时', '用户说“刚刚”')
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if (/这几天/.test(query)) return fromQuery(nowSeconds - 7 * 86400, '近 7 天', '用户说“这几天”')
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if (/这周|本周/.test(query)) {
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const weekday = now.getDay() || 7
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return fromQuery(dayStart(now) - (weekday - 1) * 86400, '本周', '用户说“这周”')
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}
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if (/这个月|本月/.test(query)) return fromQuery(currentMonthStart(now), '本月', '用户说“这个月”')
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if (/上个月/.test(query)) {
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const start = Math.floor(new Date(now.getFullYear(), now.getMonth() - 1, 1).getTime() / 1000)
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const end = Math.floor(new Date(now.getFullYear(), now.getMonth(), 1).getTime() / 1000) - 1
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return {
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startTime: start,
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endTime: end,
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label: '上个月',
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reason: '用户说“上个月”',
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source: 'query'
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}
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}
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if (/今年/.test(query)) return fromQuery(currentYearStart(now), '今年', '用户说“今年”')
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if (/最近/.test(query)) return fromQuery(nowSeconds - 30 * 86400, '近 30 天', '用户说“最近”')
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return {
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startTime: aiSearchRangeStart(uiRange),
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endTime: undefined,
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label: aiSearchRangeLabel(uiRange),
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reason: '使用界面选择的时间范围',
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source: 'ui'
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}
|
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}
|
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export const aiSearchIntentLabel = (intent: AiSearchIntent): string => {
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if (intent === 'conversation_recall') return '回顾最近聊天'
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if (intent === 'conversation_topic_search') return '在指定聊天中查找话题'
|
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if (intent === 'global_topic_search') return '按话题查找'
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if (intent === 'conversation_name_search') return '查找聊天'
|
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return '综合查找'
|
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}
|
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export const aiSearchScopeLabel = (scope: AiSearchScope, conversationName?: string): string => {
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if (scope === 'groups') return '群聊'
|
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if (scope === 'contacts') return '单聊'
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if (scope === 'conversation') return conversationName || '当前会话'
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return '所有聊天'
|
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}
|
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|
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const normalizeTerms = (terms: unknown): string[] => {
|
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if (!Array.isArray(terms)) return []
|
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return Array.from(
|
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new Set(
|
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terms
|
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.filter((term): term is string => typeof term === 'string')
|
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.map((term) => term.trim())
|
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.filter((term) => term.length >= 2 && term.length <= 32)
|
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)
|
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).slice(0, 16)
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}
|
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|
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const extractKeywords = (query: string): string[] => {
|
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const cleaned = SEARCH_INTENT_PHRASES.reduce(
|
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(value, phrase) => value.split(phrase).join(' '),
|
||
query.toLowerCase()
|
||
)
|
||
return Array.from(
|
||
new Set(
|
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cleaned
|
||
.split(/[\s,，。！？!?、:：;；"“”‘’()（）[\]【】]+/)
|
||
.map((token) => token.trim())
|
||
.filter((token) => token.length >= 2 && !SEARCH_STOP_WORDS.has(token))
|
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)
|
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)
|
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}
|
||
|
||
const keywordVariants = (keywords: string[]): string[] =>
|
||
Array.from(
|
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new Set(
|
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keywords.flatMap((keyword) => {
|
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const variants = [keyword]
|
||
if (/^[\u4e00-\u9fff]+$/.test(keyword) && keyword.length > 2) {
|
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variants.push(keyword.slice(-2))
|
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}
|
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return variants
|
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})
|
||
)
|
||
)
|
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|
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export const buildLocalAiSearchPlan = (
|
||
query: string
|
||
): Pick<
|
||
AiSearchPlan,
|
||
'intent' | 'keywords' | 'variants' | 'source' | 'contactQuery' | 'topicQuery'
|
||
> => {
|
||
const keywords = extractKeywords(query)
|
||
const normalized = query.replace(/[“”"'‘’「」『』]/g, '').trim()
|
||
const recall = normalized.match(
|
||
new RegExp(
|
||
`(?:我和|我跟|我与)\\s*(.+?)\\s*(?:最近|这几天|本周|这个月|本月|今年|上个月|刚刚|刚才)?\\s*(?:${RECALL_QUESTION})`
|
||
)
|
||
)
|
||
const reverseRecall = normalized.match(
|
||
new RegExp(`^\\s*(.+?)\\s*(?:最近)?(?:跟我|和我|与我)\\s*(?:${RECALL_QUESTION})`)
|
||
)
|
||
const namedConversationRecall = normalized.match(
|
||
new RegExp(`(?:我在|在)\\s*(.+?)\\s*(?:最近)?\\s*(?:${RECALL_QUESTION})`)
|
||
)
|
||
const bareNamedConversationRecall = normalized.match(
|
||
new RegExp(
|
||
`^\\s*(.{2,32}?(?:群聊|交流群|群))\\s*(?:最近|这几天|本周|这个月|本月|今年|上个月|刚刚|刚才)?\\s*(?:${RECALL_QUESTION})[，,。！？!?]*$`
|
||
)
|
||
)
|
||
const conversationTopic = normalized.match(
|
||
/(?:我和|我跟|我与)\s*(.+?)\s*(?:最近|这几天|本周|这个月|本月|今年|上个月)?\s*(?:聊过|提过|说过|讨论过)\s*(.+?)(?:吗|么|沒有|没有)?[？?。！!]*$/
|
||
)
|
||
const globalTopic = normalized.match(
|
||
/(?:最近|这几天|本周|这个月|本月|今年)?\s*(?:谁|哪些人|大家)\s*(?:聊过|提过|说过|讨论过)\s*(.+?)[？?。！!]*$/
|
||
)
|
||
const conversationName =
|
||
!recall &&
|
||
!reverseRecall &&
|
||
!conversationTopic &&
|
||
!namedConversationRecall &&
|
||
!bareNamedConversationRecall &&
|
||
!globalTopic &&
|
||
/^[^，,。！？!?]{2,32}(?:群|群聊|交流群)$/.test(normalized)
|
||
? normalized
|
||
: undefined
|
||
const contactQuery = (
|
||
conversationTopic?.[1] ||
|
||
recall?.[1] ||
|
||
reverseRecall?.[1] ||
|
||
namedConversationRecall?.[1] ||
|
||
bareNamedConversationRecall?.[1]
|
||
)
|
||
?.replace(/^(?:和|跟|与)\s*/, '')
|
||
.trim()
|
||
const topicQuery = (conversationTopic?.[2] || globalTopic?.[1])
|
||
?.replace(/^(?:关于|一下|吗|么)\s*/, '')
|
||
.trim()
|
||
const intent: AiSearchIntent = conversationTopic
|
||
? 'conversation_topic_search'
|
||
: recall || reverseRecall
|
||
? 'conversation_recall'
|
||
: namedConversationRecall || bareNamedConversationRecall
|
||
? 'conversation_name_search'
|
||
: globalTopic
|
||
? 'global_topic_search'
|
||
: conversationName
|
||
? 'conversation_name_search'
|
||
: keywords.length
|
||
? 'global_topic_search'
|
||
: 'general'
|
||
const effectiveKeywords = topicQuery ? [topicQuery] : keywords
|
||
return {
|
||
intent,
|
||
keywords: effectiveKeywords,
|
||
variants: keywordVariants(effectiveKeywords),
|
||
source: 'local',
|
||
contactQuery: contactQuery || conversationName,
|
||
topicQuery
|
||
}
|
||
}
|
||
|
||
export const parseAiSearchPlan = (
|
||
value: string
|
||
): Partial<Pick<AiSearchPlan, 'intent' | 'keywords' | 'variants' | 'topicQuery'>> | null => {
|
||
const jsonMatch = value.match(/\{[\s\S]*\}/)
|
||
if (!jsonMatch) return null
|
||
try {
|
||
const parsed = JSON.parse(jsonMatch[0]) as Record<string, unknown>
|
||
const intent = [
|
||
'general',
|
||
'conversation_recall',
|
||
'conversation_topic_search',
|
||
'global_topic_search',
|
||
'conversation_name_search'
|
||
].includes(String(parsed.intent))
|
||
? (parsed.intent as AiSearchIntent)
|
||
: undefined
|
||
return {
|
||
intent,
|
||
keywords: normalizeTerms(parsed.keywords),
|
||
variants: normalizeTerms(parsed.variants),
|
||
topicQuery:
|
||
typeof parsed.topicQuery === 'string' && parsed.topicQuery.trim().length >= 2
|
||
? parsed.topicQuery.trim().slice(0, 64)
|
||
: undefined
|
||
}
|
||
} catch {
|
||
return null
|
||
}
|
||
}
|
||
|
||
export const mergeAiSearchPlans = (
|
||
local: Pick<
|
||
AiSearchPlan,
|
||
'intent' | 'keywords' | 'variants' | 'source' | 'contactQuery' | 'topicQuery'
|
||
>,
|
||
ai: Partial<Pick<AiSearchPlan, 'intent' | 'keywords' | 'variants' | 'topicQuery'>> | null
|
||
): Pick<
|
||
AiSearchPlan,
|
||
'intent' | 'keywords' | 'variants' | 'source' | 'contactQuery' | 'topicQuery'
|
||
> => {
|
||
if (!ai) return local
|
||
const keywords = normalizeTerms([...local.keywords, ...(ai.keywords || [])])
|
||
const variants = normalizeTerms([
|
||
...keywordVariants(keywords),
|
||
...local.variants,
|
||
...(ai.variants || [])
|
||
])
|
||
// Identity-bearing local intents are deterministic contracts. A planner may
|
||
// refine topic terms but may not weaken them into an unrelated FTS intent.
|
||
const lockedIntent =
|
||
local.intent === 'conversation_recall' ||
|
||
local.intent === 'conversation_topic_search' ||
|
||
local.intent === 'conversation_name_search'
|
||
return {
|
||
intent: lockedIntent ? local.intent : ai.intent || local.intent,
|
||
keywords,
|
||
variants,
|
||
source: 'hybrid',
|
||
contactQuery: local.contactQuery,
|
||
topicQuery: local.topicQuery || ai.topicQuery
|
||
}
|
||
}
|
||
|
||
export const includesExplicitAiSearchAlias = (query: string, alias: string): boolean => {
|
||
const name = alias.trim()
|
||
if (!name || name.length < 2) return false
|
||
const escaped = name.replace(/[.*+?^${}()|[\]\\]/g, '\\$&')
|
||
const quoted = new RegExp(`[“"'‘「『]${escaped}[”"'’」』]`)
|
||
const relational = new RegExp(
|
||
`(?:我和|我跟|我与|和|跟|与|在|给|向|@)${escaped}(?=$|[\\s，,。！？!?、:：；;])`
|
||
)
|
||
if (quoted.test(query) || relational.test(query)) return true
|
||
|
||
// Users often omit a nickname's punctuation, for example typing
|
||
// “中田健身弘毅” for “中田健身-弘毅”. Keep this tolerant matching limited
|
||
// to an explicit relational query so a short alias cannot accidentally
|
||
// select a contact from unrelated prose.
|
||
const compact = (value: string): string =>
|
||
value.toLocaleLowerCase().replace(/[^\p{L}\p{N}]+/gu, '')
|
||
const compactName = compact(name)
|
||
return (
|
||
compactName.length >= 2 &&
|
||
/(?:我和|我跟|我与|和|跟|与|在|给|向|@)/.test(query) &&
|
||
compact(query).includes(compactName)
|
||
)
|
||
}
|