52c4cb1dee
1. Recherche: fetchChunkSnippets() — après le classement RRF existant, récupère les passages précis qui matchent depuis NoteEmbeddingChunk. Pur affichage, AUCUN changement de classement. 2. Script migration: scripts/migrate-chunk-embeddings.ts Indexe toutes les notes existantes en fragments. Batch de 10, barre de progression. Usage: npx tsx scripts/migrate-chunk-embeddings.ts 3. Memory Echo chunk-level: à faire (US restante)
52 lines
1.4 KiB
TypeScript
52 lines
1.4 KiB
TypeScript
/**
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* Script de migration : indexe toutes les notes existantes en fragments.
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* Usage: npx tsx scripts/migrate-chunk-embeddings.ts
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*/
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import prisma from '@/lib/prisma'
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import { chunkIndexingService } from '@/lib/ai/services/chunk-indexing.service'
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async function main() {
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console.log('=== Migration des chunks d\'embeddings ===\n')
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const notes = await prisma.note.findMany({
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where: {
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trashedAt: null,
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noteEmbedding: { isNot: null },
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},
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select: { id: true, title: true, content: true },
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orderBy: { createdAt: 'asc' },
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})
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console.log(`${notes.length} notes à indexer\n`)
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let done = 0
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let errors = 0
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const batchSize = 10
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for (let i = 0; i < notes.length; i += batchSize) {
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const batch = notes.slice(i, i + batchSize)
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await Promise.all(batch.map(async (note) => {
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try {
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const result = await chunkIndexingService.indexNote(note.id, note.title, note.content)
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if (result.newFragments > 0) {
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done++
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}
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} catch (e: any) {
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errors++
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console.error(` ✗ ${note.title?.slice(0, 40)}: ${e.message}`)
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}
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}))
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process.stdout.write(`\r${Math.min(i + batchSize, notes.length)}/${notes.length} traitées`)
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}
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console.log(`\n\n=== Terminé ===`)
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console.log(`Notes indexées: ${done}`)
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console.log(`Erreurs: ${errors}`)
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await prisma.$disconnect()
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}
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main().catch(console.error)
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