feat: rename keep-notes to memento-note, migrate to PostgreSQL, fix MCP bugs
- Rename directory keep-notes -> memento-note with all code references - Prisma: SQLite -> PostgreSQL (both app and MCP server schemas) - Sync MCP schema with main app (add missing fields, relations, indexes) - Delete 17 SQLite migrations (clean slate for PostgreSQL) - Remove SQLite dependencies (@libsql/client, better-sqlite3, etc.) - Fix MCP server: hardcoded Windows DB paths -> DATABASE_URL env var - Fix MCP server: .dockerignore excluded index-sse.js (SSE mode broken) - MCP Dockerfile: node:20 -> node:22 - Docker Compose: add postgres service, remove SQLite volume - Generate favicon.ico, icon-192.png, icon-512.png, apple-icon.png - Update layout.tsx icons and manifest.json for PNG icons - Update all .env files for PostgreSQL - Rewrite README.md with updated sections - Remove mcp-server/node_modules and prisma/client-generated from git tracking Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Sepehr Ramezani
468
memento-note/lib/ai/services/auto-label-creation.service.ts
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468
memento-note/lib/ai/services/auto-label-creation.service.ts
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@@ -0,0 +1,468 @@
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import { prisma } from '@/lib/prisma'
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import { getAIProvider } from '@/lib/ai/factory'
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import { getSystemConfig } from '@/lib/config'
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export interface SuggestedLabel {
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name: string
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count: number
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confidence: number
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noteIds: string[]
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}
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export interface AutoLabelSuggestion {
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notebookId: string
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notebookName: string
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notebookIcon: string | null
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suggestedLabels: SuggestedLabel[]
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totalNotes: number
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}
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/**
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* Service for automatically suggesting new labels based on recurring themes
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* (Story 5.4 - IA4)
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*/
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export class AutoLabelCreationService {
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/**
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* Analyze a notebook and suggest new labels based on recurring themes
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* @param notebookId - Notebook ID to analyze
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* @param userId - User ID (for authorization)
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* @returns Suggested labels or null if not enough notes/no patterns found
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*/
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async suggestLabels(notebookId: string, userId: string, language: string = 'en'): Promise<AutoLabelSuggestion | null> {
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// 1. Get notebook with existing labels
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const notebook = await prisma.notebook.findFirst({
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where: {
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id: notebookId,
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userId,
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},
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include: {
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labels: {
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select: {
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id: true,
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name: true,
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},
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},
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_count: {
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select: { notes: true },
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},
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},
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})
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if (!notebook) {
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throw new Error('Notebook not found')
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}
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// Only trigger if notebook has 15+ notes (PRD requirement)
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if (notebook._count.notes < 15) {
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return null
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}
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// Get all notes in this notebook
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const notes = await prisma.note.findMany({
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where: {
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notebookId,
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userId,
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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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labelRelations: {
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select: {
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name: true,
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},
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},
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},
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orderBy: {
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updatedAt: 'desc',
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},
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take: 100, // Limit to 100 most recent notes
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})
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if (notes.length === 0) {
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return null
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}
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// 2. Use AI to detect recurring themes
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const suggestions = await this.detectRecurringThemes(notes, notebook, language)
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return suggestions
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}
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/**
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* Use AI to detect recurring themes and suggest labels
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*/
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private async detectRecurringThemes(
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notes: any[],
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notebook: any,
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language: string
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): Promise<AutoLabelSuggestion | null> {
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const existingLabelNames = new Set<string>(
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notebook.labels.map((l: any) => l.name.toLowerCase())
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)
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const prompt = this.buildPrompt(notes, existingLabelNames, language)
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try {
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const config = await getSystemConfig()
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const provider = getAIProvider(config)
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const response = await provider.generateText(prompt)
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// Parse AI response
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const suggestions = this.parseAIResponse(response, notes)
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if (!suggestions || suggestions.suggestedLabels.length === 0) {
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return null
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}
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return {
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notebookId: notebook.id,
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notebookName: notebook.name,
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notebookIcon: notebook.icon,
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suggestedLabels: suggestions.suggestedLabels,
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totalNotes: notebook._count.notes,
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}
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} catch (error) {
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console.error('Failed to detect recurring themes:', error)
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return null
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}
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}
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/**
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* Build prompt for AI (localized)
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*/
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private buildPrompt(notes: any[], existingLabelNames: Set<string>, language: string = 'en'): string {
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const notesSummary = notes
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.map((note, index) => {
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const title = note.title || 'Sans titre'
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const content = note.content.substring(0, 150)
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return `[${index}] "${title}": ${content}`
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})
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.join('\n')
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const existingLabels = Array.from(existingLabelNames).join(', ')
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const instructions: Record<string, string> = {
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fr: `
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Tu es un assistant qui détecte les thèmes récurrents dans des notes pour suggérer de nouvelles étiquettes.
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CARNET ANALYSÉ :
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${notes.length} notes
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ÉTIQUETTES EXISTANTES (ne pas suggérer celles-ci) :
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${existingLabels || 'Aucune'}
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NOTES DU CARNET :
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${notesSummary}
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TÂCHE :
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Analyse les notes et détecte les thèmes récurrents (mots-clés, sujets, lieux, personnes).
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Un thème doit apparaître dans au moins 5 notes différentes pour être suggéré.
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FORMAT DE RÉPONSE (JSON) :
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{
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"labels": [
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{
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"nom": "nom_du_label",
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"note_indices": [0, 5, 12, 23, 45],
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"confiance": 0.85
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}
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]
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}
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RÈGLES :
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- Le nom du label doit être court (1-2 mots max)
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- Un thème doit apparaître dans 5+ notes pour être suggéré
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- La confiance doit être > 0.60
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- Ne pas suggérer des étiquettes qui existent déjà
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- Priorise les lieux, personnes, catégories claires
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- Maximum 5 suggestions
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Exemples de bonnes étiquettes :
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- "tokyo", "kyoto", "osaka" (lieux)
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- "hôtels", "restos", "vols" (catégories)
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- "marie", "jean", "équipe" (personnes)
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Ta réponse (JSON seulement) :
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`.trim(),
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en: `
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You are an assistant that detects recurring themes in notes to suggest new labels.
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ANALYZED NOTEBOOK:
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${notes.length} notes
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EXISTING LABELS (do not suggest these):
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${existingLabels || 'None'}
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NOTEBOOK NOTES:
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${notesSummary}
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TASK:
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Analyze the notes and detect recurring themes (keywords, subjects, places, people).
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A theme must appear in at least 5 different notes to be suggested.
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RESPONSE FORMAT (JSON):
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{
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"labels": [
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{
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"nom": "label_name",
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"note_indices": [0, 5, 12, 23, 45],
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"confiance": 0.85
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}
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]
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}
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RULES:
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- Label name must be short (max 1-2 words)
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- A theme must appear in 5+ notes to be suggested
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- Confidence must be > 0.60
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- Do not suggest labels that already exist
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- Prioritize places, people, clear categories
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- Maximum 5 suggestions
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Examples of good labels:
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- "tokyo", "kyoto", "osaka" (places)
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- "hotels", "restaurants", "flights" (categories)
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- "mary", "john", "team" (people)
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Your response (JSON only):
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`.trim(),
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fa: `
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شما یک دستیار هستید که تمهای تکرارشونده در یادداشتها را برای پیشنهاد برچسبهای جدید شناسایی میکنید.
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دفترچه تحلیل شده:
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${notes.length} یادداشت
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برچسبهای موجود (اینها را پیشنهاد ندهید):
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${existingLabels || 'هیچ'}
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یادداشتهای دفترچه:
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${notesSummary}
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وظیفه:
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یادداشتها را تحلیل کنید و تمهای تکرارشونده (کلمات کلیدی، موضوعات، مکانها، افراد) را شناسایی کنید.
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یک تم باید حداقل در ۵ یادداشت مختلف ظاهر شود تا پیشنهاد داده شود.
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فرمت پاسخ (JSON):
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{
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"labels": [
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{
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"nom": "نام_برچسب",
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"note_indices": [0, 5, 12, 23, 45],
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"confiance": 0.85
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}
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]
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}
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قوانین:
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- نام برچسب باید کوتاه باشد (حداکثر ۱-۲ کلمه)
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- یک تم باید در ۵+ یادداشت ظاهر شود تا پیشنهاد داده شود
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- اطمینان باید > 0.60 باشد
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- برچسبهایی که قبلاً وجود دارند را پیشنهاد ندهید
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- اولویت با مکانها، افراد، دستهبندیهای واضح است
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- حداکثر ۵ پیشنهاد
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مثالهای برچسب خوب:
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- "توکیو"، "کیوتو"، "اوزاکا" (مکانها)
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- "هتلها"، "رستورانها"، "پروازها" (دستهبندیها)
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- "مریم"، "علی"، "تیم" (افراد)
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پاسخ شما (فقط JSON):
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`.trim(),
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es: `
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Eres un asistente que detecta temas recurrentes en notas para sugerir nuevas etiquetas.
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CUADERNO ANALIZADO:
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${notes.length} notas
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ETIQUETAS EXISTENTES (no sugerir estas):
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${existingLabels || 'Ninguna'}
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NOTAS DEL CUADERNO:
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${notesSummary}
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TAREA:
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Analiza las notas y detecta temas recurrentes (palabras clave, temas, lugares, personas).
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Un tema debe aparecer en al menos 5 notas diferentes para ser sugerido.
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FORMATO DE RESPUESTA (JSON):
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{
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"labels": [
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{
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"nom": "nombre_etiqueta",
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"note_indices": [0, 5, 12, 23, 45],
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"confiance": 0.85
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}
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]
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}
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REGLAS:
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- El nombre de la etiqueta debe ser corto (máx 1-2 palabras)
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- Un tema debe aparecer en 5+ notas para ser sugerido
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- La confianza debe ser > 0.60
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- No sugieras etiquetas que ya existen
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- Prioriza lugares, personas, categorías claras
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- Máximo 5 sugerencias
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Ejemplos de buenas etiquetas:
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- "tokio", "kyoto", "osaka" (lugares)
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- "hoteles", "restaurantes", "vuelos" (categorías)
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- "maría", "juan", "equipo" (personas)
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Tu respuesta (solo JSON):
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`.trim(),
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de: `
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Du bist ein Assistent, der wiederkehrende Themen in Notizen erkennt, um neue Labels vorzuschlagen.
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ANALYSIERTES NOTIZBUCH:
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${notes.length} Notizen
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VORHANDENE LABELS (schlage diese nicht vor):
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${existingLabels || 'Keine'}
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NOTIZBUCH-NOTIZEN:
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${notesSummary}
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AUFGABE:
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Analysiere die Notizen und erkenne wiederkehrende Themen (Schlüsselwörter, Themen, Orte, Personen).
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Ein Thema muss in mindestens 5 verschiedenen Notizen erscheinen, um vorgeschlagen zu werden.
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ANTWORTFORMAT (JSON):
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{
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"labels": [
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{
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"nom": "label_name",
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"note_indices": [0, 5, 12, 23, 45],
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"confiance": 0.85
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}
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]
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}
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REGELN:
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- Der Labelname muss kurz sein (max 1-2 Wörter)
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- Ein Thema muss in 5+ Notizen erscheinen, um vorgeschlagen zu werden
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- Konfidenz muss > 0.60 sein
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- Schlage keine Labels vor, die bereits existieren
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- Priorisiere Orte, Personen, klare Kategorien
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- Maximal 5 Vorschläge
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Beispiele für gute Labels:
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- "tokio", "kyoto", "osaka" (Orte)
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- "hotels", "restaurants", "flüge" (Kategorien)
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- "maria", "johannes", "team" (Personen)
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Deine Antwort (nur JSON):
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`.trim()
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}
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return instructions[language] || instructions['en'] || instructions['fr']
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}
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/**
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* Parse AI response into suggested labels
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*/
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private parseAIResponse(response: string, notes: any[]): { suggestedLabels: SuggestedLabel[] } | null {
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try {
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const jsonMatch = response.match(/\{[\s\S]*\}/)
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if (!jsonMatch) {
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throw new Error('No JSON found in response')
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}
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const aiData = JSON.parse(jsonMatch[0])
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const suggestedLabels: SuggestedLabel[] = (aiData.labels || [])
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.map((label: any) => {
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// Filter by confidence threshold
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if (label.confiance <= 0.60) return null
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// Get note IDs from indices
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const noteIds = label.note_indices
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.map((idx: number) => notes[idx]?.id)
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.filter(Boolean)
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// Must have at least 5 notes
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if (noteIds.length < 5) return null
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return {
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name: label.nom,
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count: noteIds.length,
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confidence: label.confiance,
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noteIds,
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}
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})
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.filter(Boolean)
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if (suggestedLabels.length === 0) {
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return null
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}
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// Sort by count (descending) and confidence
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suggestedLabels.sort((a, b) => {
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if (b.count !== a.count) {
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return b.count - a.count // More notes first
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}
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return b.confidence - a.confidence // Then higher confidence
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})
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// Limit to top 5
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return {
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suggestedLabels: suggestedLabels.slice(0, 5),
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}
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} catch (error) {
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console.error('Failed to parse AI response:', error)
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return null
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}
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}
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/**
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* Create suggested labels and assign them to notes
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* @param notebookId - Notebook ID
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* @param userId - User ID
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* @param suggestions - Suggested labels to create
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* @param selectedLabels - Labels user selected to create
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* @returns Number of labels created
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*/
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async createLabels(
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notebookId: string,
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userId: string,
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suggestions: AutoLabelSuggestion,
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selectedLabels: string[]
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): Promise<number> {
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let createdCount = 0
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for (const suggestedLabel of suggestions.suggestedLabels) {
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if (!selectedLabels.includes(suggestedLabel.name)) continue
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// Create the label
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const label = await prisma.label.create({
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data: {
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name: suggestedLabel.name,
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color: 'gray', // Default color, user can change later
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notebookId,
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userId,
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},
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})
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// Assign label to all suggested notes (updateMany doesn't support relations)
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for (const noteId of suggestedLabel.noteIds) {
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await prisma.note.update({
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where: { id: noteId },
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data: {
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labelRelations: {
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connect: {
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id: label.id,
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},
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},
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},
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})
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}
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createdCount++
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}
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return createdCount
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}
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}
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// Export singleton instance
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export const autoLabelCreationService = new AutoLabelCreationService()
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Reference in New Issue
Block a user