Briefing granulaire, pistes rapides puis enrichissement async, layout persisté v5, suggestions agents, intégration Gmail et navigation sidebar alignée sur /home. Co-authored-by: Cursor <cursoragent@cursor.com>
769 lines
24 KiB
TypeScript
769 lines
24 KiB
TypeScript
import { getChatProvider } from '../factory'
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import { cosineSimilarity } from '@/lib/utils'
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import { embeddingService } from './embedding.service'
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import { getSystemConfig } from '@/lib/config'
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import prisma from '@/lib/prisma'
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import { Prisma } from '@prisma/client'
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import { upsertNoteEmbedding } from '@/lib/embeddings'
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import {
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excerptPlainNoteContent,
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prepareNoteTextForEmbedding,
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} from '@/lib/text/plain-text'
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import { detectTextDirection } from '@/lib/clip/rtl-content'
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import { detectUserLanguage } from '@/lib/i18n/detect-user-language'
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import type { SupportedLanguage } from '@/lib/i18n/load-translations'
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import {
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buildMemoryEchoInsightPrompt,
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getMemoryEchoInsightFallback,
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} from '@/lib/ai/memory-echo-i18n'
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import {
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SEMANTIC_SIMILARITY_FLOOR_CLIP,
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SEMANTIC_SIMILARITY_FLOOR_DEMO,
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SEMANTIC_SIMILARITY_FLOOR,
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} from '@/lib/ai/semantic-proximity'
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export interface NoteConnection {
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note1: {
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id: string
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title: string | null
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content: string
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createdAt: Date
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}
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note2: {
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id: string
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title: string | null
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content: string | null
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createdAt: Date
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}
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similarityScore: number
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insight: string
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daysApart: number
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}
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export interface MemoryEchoInsight {
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id: string
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note1Id: string
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note2Id: string
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note1: {
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id: string
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title: string | null
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content: string
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}
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note2: {
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id: string
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title: string | null
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content: string
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}
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similarityScore: number
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insight: string
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insightDate: Date
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viewed: boolean
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feedback: string | null
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}
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/**
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* Memory Echo Service - Proactive note connections
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* "I didn't search, it found me"
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*/
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export class MemoryEchoService {
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private readonly SIMILARITY_THRESHOLD = SEMANTIC_SIMILARITY_FLOOR
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private readonly SIMILARITY_THRESHOLD_DEMO = SEMANTIC_SIMILARITY_FLOOR_DEMO
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private readonly SIMILARITY_THRESHOLD_CLIP = SEMANTIC_SIMILARITY_FLOOR_CLIP
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private readonly MIN_DAYS_APART = 7 // Notes must be at least 7 days apart
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private readonly MIN_DAYS_APART_CLIP = 0 // Notes clippées (sourceUrl) : même jour OK
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private readonly MIN_DAYS_APART_DEMO = 0 // No delay for demo mode
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private readonly MAX_INSIGHTS_PER_USER = 100 // Prevent spam
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private isClippedNote(note: { sourceUrl?: string | null }): boolean {
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return Boolean(note.sourceUrl?.trim())
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}
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private passesTimeDiversityFilter(
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daysApart: number,
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noteA: { sourceUrl?: string | null },
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noteB: { sourceUrl?: string | null },
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demoMode: boolean,
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): boolean {
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if (demoMode) return true
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const minDays =
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this.isClippedNote(noteA) || this.isClippedNote(noteB)
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? this.MIN_DAYS_APART_CLIP
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: this.MIN_DAYS_APART
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return daysApart >= minDays
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}
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private isRtlOrClipNote(note: {
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sourceUrl?: string | null
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content?: string
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title?: string | null
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}): boolean {
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if (this.isClippedNote(note)) return true
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if (note.content?.includes('clip-article--rtl')) return true
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const sample = prepareNoteTextForEmbedding(note.title, note.content || '')
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return detectTextDirection(sample) === 'rtl'
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}
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private pairSimilarityThreshold(
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noteA: { sourceUrl?: string | null; content?: string; title?: string | null },
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noteB: { sourceUrl?: string | null; content?: string; title?: string | null },
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demoMode: boolean,
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): number {
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if (demoMode) return this.SIMILARITY_THRESHOLD_DEMO
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if (this.isRtlOrClipNote(noteA) || this.isRtlOrClipNote(noteB)) {
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return this.SIMILARITY_THRESHOLD_CLIP
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}
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return this.SIMILARITY_THRESHOLD
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}
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/** Texte plain complet envoyé à l'API / résolution de blocs (pas de troncature). */
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private connectionPlainText(
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title: string | null,
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content: string,
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): string {
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return prepareNoteTextForEmbedding(title, content)
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}
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private async upsertNoteEmbeddingFromNote(note: {
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id: string
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title: string | null
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content: string
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}): Promise<number[] | null> {
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const text = prepareNoteTextForEmbedding(note.title, note.content)
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if (!text.trim()) return null
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try {
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const { embedding } = await embeddingService.generateNoteEmbedding(note.title, note.content)
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if (embedding?.length) {
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await upsertNoteEmbedding(note.id, embedding)
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return embedding
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}
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} catch (error) {
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console.error(`[MemoryEcho] embedding failed for note ${note.id}:`, error)
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}
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return null
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}
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/**
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* Generate embeddings for notes that don't have one yet
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*/
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private async ensureEmbeddings(userId: string): Promise<void> {
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const notes = await prisma.note.findMany({
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where: {
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userId,
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isArchived: false,
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trashedAt: null,
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},
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select: {
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id: true,
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title: true,
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content: true,
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sourceUrl: true,
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noteEmbedding: { select: { noteId: true } },
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},
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})
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if (notes.length === 0) return
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for (const note of notes) {
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if (!note.content?.trim()) continue
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const isClip = this.isClippedNote(note)
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const missing = !note.noteEmbedding
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if (!missing && !isClip) continue
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await this.upsertNoteEmbeddingFromNote(note)
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}
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}
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/**
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* Find meaningful connections between user's notes
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*/
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async findConnections(userId: string, demoMode: boolean = false): Promise<NoteConnection[]> {
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// GDPR AI Consent check — compliance skip if not granted (AC6)
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const userSettings = await prisma.userAISettings.findUnique({
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where: { userId },
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select: { aiProcessingConsent: true },
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})
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if (!userSettings?.aiProcessingConsent) {
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return []
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}
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// Ensure all notes have embeddings before searching for connections
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await this.ensureEmbeddings(userId)
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// Get all user's notes with embeddings
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const notes = await prisma.note.findMany({
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where: {
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userId,
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isArchived: false,
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trashedAt: null,
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// noteEmbedding: { isNot: null } // Removed because Unsupported type cannot be used in 'where' easily
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},
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select: {
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id: true,
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title: true,
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content: true,
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sourceUrl: true,
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noteEmbedding: true,
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createdAt: true
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},
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orderBy: { createdAt: 'desc' }
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})
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if (notes.length < 2) {
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return [] // Need at least 2 notes to find connections
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}
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if (notes.length < 2) return []
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// Fetch embeddings separately using raw SQL to avoid deserialization error
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const noteIds = notes.map(n => n.id)
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const embeddings = noteIds.length === 0 ? [] : await prisma.$queryRaw<Array<{ noteId: string, embedding: any }>>(
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Prisma.sql`SELECT "noteId", "embedding"::text FROM "NoteEmbedding" WHERE "noteId" IN (${Prisma.join(noteIds)})`
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)
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const embeddingMap = new Map(embeddings.map(e => [e.noteId, e.embedding]))
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const notesWithEmbeddings = notes
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.map(note => ({
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...note,
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embedding: embeddingMap.has(note.id)
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? embeddingService.fromVectorString(embeddingMap.get(note.id))
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: null
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}))
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.filter(note => note.embedding && Array.isArray(note.embedding))
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const connections: NoteConnection[] = []
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// Load user feedback to adjust thresholds per note
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const feedbackInsights = await prisma.memoryEchoInsight.findMany({
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where: { userId, feedback: { not: null } },
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select: { note1Id: true, note2Id: true, feedback: true }
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})
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const notePenalty = new Map<string, number>() // positive = higher threshold (penalty), negative = lower (boost)
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for (const fi of feedbackInsights) {
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if (fi.feedback === 'thumbs_down') {
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notePenalty.set(fi.note1Id, (notePenalty.get(fi.note1Id) || 0) + 0.15)
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notePenalty.set(fi.note2Id, (notePenalty.get(fi.note2Id) || 0) + 0.15)
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} else if (fi.feedback === 'thumbs_up') {
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notePenalty.set(fi.note1Id, (notePenalty.get(fi.note1Id) || 0) - 0.05)
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notePenalty.set(fi.note2Id, (notePenalty.get(fi.note2Id) || 0) - 0.05)
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}
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}
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// Compare all pairs of notes
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for (let i = 0; i < notesWithEmbeddings.length; i++) {
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for (let j = i + 1; j < notesWithEmbeddings.length; j++) {
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const note1 = notesWithEmbeddings[i]
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const note2 = notesWithEmbeddings[j]
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const baseThreshold = this.pairSimilarityThreshold(note1, note2, demoMode)
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const adjustedThreshold = baseThreshold + (notePenalty.get(note1.id) || 0) + (notePenalty.get(note2.id) || 0)
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// Calculate time difference
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const daysApart = Math.abs(
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Math.floor((note1.createdAt.getTime() - note2.createdAt.getTime()) / (1000 * 60 * 60 * 24))
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)
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// Time diversity filter: notes must be from different time periods (sauf clips récents)
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if (!this.passesTimeDiversityFilter(daysApart, note1, note2, demoMode)) {
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continue
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}
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// Calculate cosine similarity — whole note level
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const similarity = cosineSimilarity(note1.embedding!, note2.embedding!)
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// Also check chunk-level similarity for more precise connections
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// This catches cases where two notes share a similar SECTION even if overall different
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let bestChunkSimilarity = similarity
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let chunkSnippet: string | undefined
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if (similarity < adjustedThreshold) {
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// Only check chunks if whole-note similarity didn't pass — saves DB queries
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try {
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const chunkRows: Array<{ content: string; embedding: string }> = await prisma.$queryRawUnsafe(
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`SELECT a.content AS content,
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1 - (a."embedding"::vector <=> b."embedding"::vector) AS chunk_sim
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FROM "NoteEmbeddingChunk" a
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CROSS JOIN LATERAL (
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SELECT "embedding"
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FROM "NoteEmbeddingChunk"
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WHERE "noteId" = $2 AND "embedding" IS NOT NULL
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ORDER BY "embedding"::vector <=> a."embedding"::vector ASC
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LIMIT 1
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) b
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WHERE a."noteId" = $1 AND a."embedding" IS NOT NULL
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ORDER BY chunk_sim DESC
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LIMIT 1`,
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note1.id, note2.id
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)
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if (chunkRows.length > 0 && chunkRows[0]) {
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const row = chunkRows[0] as any
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if (row.chunk_sim && row.chunk_sim > bestChunkSimilarity) {
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bestChunkSimilarity = row.chunk_sim
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chunkSnippet = row.content?.slice(0, 200)
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}
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}
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} catch {}
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}
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if (bestChunkSimilarity >= adjustedThreshold) {
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connections.push({
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note1: {
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id: note1.id,
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title: note1.title,
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content: this.connectionPlainText(note1.title, note1.content),
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createdAt: note1.createdAt
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},
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note2: {
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id: note2.id,
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title: note2.title,
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content: this.connectionPlainText(note2.title, note2.content || ''),
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createdAt: note2.createdAt
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},
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similarityScore: bestChunkSimilarity,
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insight: '', // Will be generated by AI
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daysApart,
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...(chunkSnippet ? { contextSnippet: chunkSnippet } : {})
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})
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}
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}
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}
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// Sort by similarity score (descending)
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connections.sort((a, b) => b.similarityScore - a.similarityScore)
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// Return top connections
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return connections.slice(0, 10)
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}
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/**
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* Generate AI explanation for the connection
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*/
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async generateInsight(
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note1Title: string | null,
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note1Content: string,
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note2Title: string | null,
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note2Content: string,
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language: SupportedLanguage = 'en',
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): Promise<string> {
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try {
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const config = await getSystemConfig()
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const provider = getChatProvider(config)
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const excerpt1 = excerptPlainNoteContent(note1Title, note1Content, 1200)
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const excerpt2 = excerptPlainNoteContent(note2Title, note2Content, 1200)
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const prompt = buildMemoryEchoInsightPrompt(language, note1Title, excerpt1, note2Title, excerpt2)
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const response = await provider.generateText(prompt)
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const insight = response
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.replace(/^["'«»]|["'«»]$/g, '')
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.replace(/^[^.]+\.\s*/, '')
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.trim()
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.substring(0, 150)
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return insight || getMemoryEchoInsightFallback(language)
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} catch (error) {
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console.error('[MemoryEcho] Failed to generate insight:', error)
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const sample = excerptPlainNoteContent(note1Title, note1Content, 200)
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+ excerptPlainNoteContent(note2Title, note2Content, 200)
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const rtl = detectTextDirection(sample) === 'rtl'
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if (rtl) return getMemoryEchoInsightFallback(language === 'fa' || language === 'ar' ? language : 'fa')
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return getMemoryEchoInsightFallback(language)
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}
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}
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/**
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* Get next pending insight for user (based on frequency limit)
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*/
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async getNextInsight(userId: string): Promise<MemoryEchoInsight | null> {
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// Check if Memory Echo is enabled for user
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const settings = await prisma.userAISettings.findUnique({
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where: { userId }
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})
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if (!settings || !settings.memoryEcho) {
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return null // Memory Echo disabled
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}
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const demoMode = settings.demoMode || false
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// Skip frequency checks in demo mode
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if (!demoMode) {
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// Check frequency limit
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const today = new Date()
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today.setHours(0, 0, 0, 0)
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const insightsShownToday = await prisma.memoryEchoInsight.count({
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where: {
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userId,
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insightDate: {
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gte: today
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}
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}
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})
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// Frequency limits
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const maxPerDay = settings.memoryEchoFrequency === 'daily' ? 1 :
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settings.memoryEchoFrequency === 'weekly' ? 0 : // 1 per 7 days (handled below)
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3 // custom = 3 per day
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if (settings.memoryEchoFrequency === 'weekly') {
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// Check if shown in last 7 days
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const weekAgo = new Date(today)
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weekAgo.setDate(weekAgo.getDate() - 7)
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const recentInsight = await prisma.memoryEchoInsight.findFirst({
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where: {
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userId,
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insightDate: {
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gte: weekAgo
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}
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}
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})
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if (recentInsight) {
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return null // Already shown this week
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}
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} else if (insightsShownToday >= maxPerDay) {
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return null // Daily limit reached
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}
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// Check total insights limit (prevent spam)
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const totalInsights = await prisma.memoryEchoInsight.count({
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where: { userId }
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})
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if (totalInsights >= this.MAX_INSIGHTS_PER_USER) {
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return null // User has too many insights
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}
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}
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// Find new connections (pass demoMode)
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const connections = await this.findConnections(userId, demoMode)
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if (connections.length === 0) {
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return null // No connections found
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}
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// Filter out already shown connections
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const existingInsights = await prisma.memoryEchoInsight.findMany({
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where: { userId },
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select: { note1Id: true, note2Id: true }
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})
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const shownPairs = new Set(
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existingInsights.map(i => `${i.note1Id}-${i.note2Id}`)
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)
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const newConnection = connections.find(c =>
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!shownPairs.has(`${c.note1.id}-${c.note2.id}`) &&
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!shownPairs.has(`${c.note2.id}-${c.note1.id}`)
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)
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if (!newConnection) {
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return null // All connections already shown
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}
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// Generate AI insight in user's language
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const userLanguage = await detectUserLanguage()
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const insightText = await this.generateInsight(
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newConnection.note1.title,
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newConnection.note1.content,
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newConnection.note2.title,
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newConnection.note2.content || '',
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userLanguage,
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)
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// Store insight in database
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// In demo mode, add milliseconds offset to avoid @@unique([userId, insightDate]) collision
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const insightDateValue = demoMode
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? new Date(Date.now() + Math.floor(Math.random() * 1000))
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: new Date()
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const insight = await prisma.memoryEchoInsight.create({
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data: {
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userId,
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note1Id: newConnection.note1.id,
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note2Id: newConnection.note2.id,
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similarityScore: newConnection.similarityScore,
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insight: insightText,
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insightDate: insightDateValue,
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viewed: false
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},
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include: {
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note1: {
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select: {
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id: true,
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title: true,
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content: true
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}
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},
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note2: {
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select: {
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id: true,
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title: true,
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content: true
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}
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}
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}
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})
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return insight
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}
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|
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/**
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|
* Mark insight as viewed
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|
*/
|
|
async markAsViewed(insightId: string): Promise<void> {
|
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await prisma.memoryEchoInsight.update({
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where: { id: insightId },
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data: { viewed: true }
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})
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}
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|
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/**
|
|
* Submit feedback for insight
|
|
*/
|
|
async submitFeedback(insightId: string, feedback: 'thumbs_up' | 'thumbs_down'): Promise<void> {
|
|
await prisma.memoryEchoInsight.update({
|
|
where: { id: insightId },
|
|
data: { feedback }
|
|
})
|
|
|
|
// Optional: Store in AiFeedback for analytics
|
|
const insight = await prisma.memoryEchoInsight.findUnique({
|
|
where: { id: insightId },
|
|
select: { userId: true, note1Id: true }
|
|
})
|
|
|
|
if (insight) {
|
|
await prisma.aiFeedback.create({
|
|
data: {
|
|
noteId: insight.note1Id,
|
|
userId: insight.userId,
|
|
feedbackType: feedback,
|
|
feature: 'memory_echo',
|
|
originalContent: JSON.stringify({ insightId }),
|
|
metadata: {
|
|
timestamp: new Date().toISOString()
|
|
} as any
|
|
}
|
|
})
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Get all connections for a specific note
|
|
*/
|
|
async getConnectionsForNote(noteId: string, userId: string): Promise<NoteConnection[]> {
|
|
// Ensure all notes have embeddings before searching
|
|
await this.ensureEmbeddings(userId)
|
|
|
|
// Get the note with embedding
|
|
const targetNote = await prisma.note.findUnique({
|
|
where: { id: noteId },
|
|
select: {
|
|
id: true,
|
|
title: true,
|
|
content: true,
|
|
sourceUrl: true,
|
|
createdAt: true,
|
|
userId: true
|
|
}
|
|
})
|
|
|
|
if (!targetNote || targetNote.userId !== userId) {
|
|
return [] // Note not found or doesn't belong to user
|
|
}
|
|
|
|
// Fetch embedding separately
|
|
const embeddingResult: Array<{ embedding: any }> = await prisma.$queryRawUnsafe(
|
|
`SELECT "embedding"::text FROM "NoteEmbedding" WHERE "noteId" = $1`,
|
|
noteId
|
|
)
|
|
const targetEmbeddingStr = embeddingResult[0]?.embedding
|
|
|
|
let targetEmbedding = targetEmbeddingStr
|
|
? embeddingService.fromVectorString(targetEmbeddingStr)
|
|
: null
|
|
|
|
if (!targetEmbedding && targetNote.content?.trim()) {
|
|
targetEmbedding = await this.upsertNoteEmbeddingFromNote(targetNote)
|
|
}
|
|
|
|
if (!targetEmbedding) {
|
|
return []
|
|
}
|
|
|
|
// Get dismissed connections for this note (to filter them out)
|
|
const dismissedInsights = await prisma.memoryEchoInsight.findMany({
|
|
where: {
|
|
userId,
|
|
dismissed: true,
|
|
OR: [
|
|
{ note1Id: noteId },
|
|
{ note2Id: noteId }
|
|
]
|
|
},
|
|
select: {
|
|
note1Id: true,
|
|
note2Id: true
|
|
}
|
|
})
|
|
|
|
// Create a set of dismissed note pairs for quick lookup
|
|
const dismissedPairs = new Set(
|
|
dismissedInsights.map(i =>
|
|
`${i.note1Id}-${i.note2Id}`
|
|
)
|
|
)
|
|
|
|
// Get all other user's notes with embeddings
|
|
const otherNotes = await prisma.note.findMany({
|
|
where: {
|
|
userId,
|
|
id: { not: noteId },
|
|
isArchived: false,
|
|
trashedAt: null,
|
|
},
|
|
select: {
|
|
id: true,
|
|
title: true,
|
|
content: true,
|
|
sourceUrl: true,
|
|
createdAt: true
|
|
},
|
|
orderBy: { createdAt: 'desc' }
|
|
})
|
|
|
|
if (otherNotes.length === 0) {
|
|
return []
|
|
}
|
|
|
|
// Fetch all other embeddings
|
|
const otherNoteIds = otherNotes.map(n => n.id)
|
|
const otherEmbeddings = otherNoteIds.length === 0 ? [] : await prisma.$queryRaw<Array<{ noteId: string, embedding: any }>>(
|
|
Prisma.sql`SELECT "noteId", "embedding"::text FROM "NoteEmbedding" WHERE "noteId" IN (${Prisma.join(otherNoteIds)})`
|
|
)
|
|
const otherEmbeddingMap = new Map(otherEmbeddings.map(e => [e.noteId, e.embedding]))
|
|
|
|
// Check if user has demo mode enabled
|
|
const settings = await prisma.userAISettings.findUnique({
|
|
where: { userId }
|
|
})
|
|
const demoMode = settings?.demoMode || false
|
|
|
|
// Load user feedback to adjust thresholds
|
|
const feedbackInsights = await prisma.memoryEchoInsight.findMany({
|
|
where: { userId, feedback: { not: null } },
|
|
select: { note1Id: true, note2Id: true, feedback: true }
|
|
})
|
|
const notePenalty = new Map<string, number>()
|
|
for (const fi of feedbackInsights) {
|
|
if (fi.feedback === 'thumbs_down') {
|
|
notePenalty.set(fi.note1Id, (notePenalty.get(fi.note1Id) || 0) + 0.15)
|
|
notePenalty.set(fi.note2Id, (notePenalty.get(fi.note2Id) || 0) + 0.15)
|
|
} else if (fi.feedback === 'thumbs_up') {
|
|
notePenalty.set(fi.note1Id, (notePenalty.get(fi.note1Id) || 0) - 0.05)
|
|
notePenalty.set(fi.note2Id, (notePenalty.get(fi.note2Id) || 0) - 0.05)
|
|
}
|
|
}
|
|
|
|
const connections: NoteConnection[] = []
|
|
|
|
// Compare target note with all other notes
|
|
for (const otherNote of otherNotes) {
|
|
const otherEmbeddingStr = otherEmbeddingMap.get(otherNote.id)
|
|
let otherEmbedding = otherEmbeddingStr
|
|
? embeddingService.fromVectorString(otherEmbeddingStr)
|
|
: null
|
|
|
|
if (!otherEmbedding && otherNote.content?.trim()) {
|
|
otherEmbedding = await this.upsertNoteEmbeddingFromNote(otherNote)
|
|
}
|
|
if (!otherEmbedding) continue
|
|
|
|
// Check if this connection was dismissed
|
|
const pairKey1 = `${targetNote.id}-${otherNote.id}`
|
|
const pairKey2 = `${otherNote.id}-${targetNote.id}`
|
|
if (dismissedPairs.has(pairKey1) || dismissedPairs.has(pairKey2)) {
|
|
continue
|
|
}
|
|
|
|
// Calculate time difference
|
|
const daysApart = Math.abs(
|
|
Math.floor((targetNote.createdAt.getTime() - otherNote.createdAt.getTime()) / (1000 * 60 * 60 * 24))
|
|
)
|
|
|
|
// Time diversity filter (clips récents autorisés sans délai de 7 jours)
|
|
if (!this.passesTimeDiversityFilter(daysApart, targetNote, otherNote, demoMode)) {
|
|
continue
|
|
}
|
|
|
|
// Calculate cosine similarity
|
|
const similarity = cosineSimilarity(targetEmbedding, otherEmbedding)
|
|
|
|
// Similarity threshold (adjusted by feedback)
|
|
const baseThreshold = this.pairSimilarityThreshold(targetNote, otherNote, demoMode)
|
|
const adjustedThreshold = baseThreshold
|
|
+ (notePenalty.get(targetNote.id) || 0)
|
|
+ (notePenalty.get(otherNote.id) || 0)
|
|
if (similarity >= adjustedThreshold) {
|
|
connections.push({
|
|
note1: {
|
|
id: targetNote.id,
|
|
title: targetNote.title,
|
|
content: this.connectionPlainText(targetNote.title, targetNote.content),
|
|
createdAt: targetNote.createdAt
|
|
},
|
|
note2: {
|
|
id: otherNote.id,
|
|
title: otherNote.title,
|
|
content: this.connectionPlainText(otherNote.title, otherNote.content || ''),
|
|
createdAt: otherNote.createdAt
|
|
},
|
|
similarityScore: similarity,
|
|
insight: '', // Will be generated on demand
|
|
daysApart
|
|
})
|
|
}
|
|
}
|
|
|
|
// Sort by similarity score (descending)
|
|
connections.sort((a, b) => b.similarityScore - a.similarityScore)
|
|
|
|
return connections
|
|
}
|
|
|
|
/**
|
|
* Get insights history for user
|
|
*/
|
|
async getInsightsHistory(userId: string): Promise<MemoryEchoInsight[]> {
|
|
const insights = await prisma.memoryEchoInsight.findMany({
|
|
where: { userId },
|
|
include: {
|
|
note1: {
|
|
select: {
|
|
id: true,
|
|
title: true,
|
|
content: true
|
|
}
|
|
},
|
|
note2: {
|
|
select: {
|
|
id: true,
|
|
title: true,
|
|
content: true
|
|
}
|
|
}
|
|
},
|
|
orderBy: { insightDate: 'desc' },
|
|
take: 20
|
|
})
|
|
|
|
return insights
|
|
}
|
|
}
|
|
|
|
// Export singleton instance
|
|
export const memoryEchoService = new MemoryEchoService()
|