fix(quotas): unifier le décompte IA (BYOK, rollback) et combler les fuites
Centralise la réserve via ai-quota, corrige admin unavailable (-1), brancher les routes sans quota et le host-pays brainstorm, avec usage-meter élargi, noms de clusters, MCP et ajustements dashboard/insights. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
@@ -1,24 +1,32 @@
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/**
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* Bridge Notes Service
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*
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* Detects and manages "bridge notes" — notes that connect multiple clusters.
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* A bridge note has strong similarities (cosine > 0.5) with notes from
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* at least two different clusters.
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* Detects and manages "bridge notes" — notes that connect multiple thematic clusters.
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*
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* Also generates AI-powered suggestions for creating new bridge notes
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* to connect isolated clusters.
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* Scientific grounding (semantic similarity networks / brokerage):
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* - A bridge document is valued when it spans *distinct communities*, typically the
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* strongest link between a *pair* of clusters — not weak ties to every theme
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* (see semantic similarity network bridging; betweenness / cross-community brokerage).
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* - Literature commonly uses cosine thresholds ≈ 0.65–0.85 for semantic edges
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* (Vec2GC, PMC semantic graphs ~0.65; looser 0.5 floods the graph with false bridges).
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* - Score = mean affinity to the top-2 clusters (not "% of all themes touched").
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*/
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import prisma from '@/lib/prisma'
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import { clusteringService } from './clustering.service'
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import { getChatProvider } from '@/lib/ai/factory'
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import { getSystemConfig } from '@/lib/config'
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import { withAiQuota } from '@/lib/ai-quota'
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export interface BridgeNote {
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noteId: string
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/** 0–1 mean cosine affinity to the top bridge clusters (typically a pair). */
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bridgeScore: number
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/** Cluster ids ranked by affinity (strongest first). Prefer length 2. */
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clustersConnected: number[]
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clusterNames?: string[]
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/** Per-cluster max cosine affinities, aligned with clustersConnected. */
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clusterAffinities?: number[]
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}
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export interface BridgeSuggestion {
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@@ -31,26 +39,37 @@ export interface BridgeSuggestion {
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justification: string
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}
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interface ClusterAffinity {
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clusterId: number
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maxSimilarity: number
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hitCount: number
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}
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export class BridgeNotesService {
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private readonly BRIDGE_SIMILARITY_THRESHOLD = 0.5
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/** Cosine similarity floor for semantic edges (literature ≈ 0.65). */
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private readonly BRIDGE_SIMILARITY_THRESHOLD = 0.65
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private readonly MIN_CLUSTERS_FOR_BRIDGE = 2
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/** A true bridge is primarily a pair of communities (brokerage). */
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private readonly MAX_BRIDGED_CLUSTERS = 2
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/**
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* Get similar notes for a given note across all clusters.
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* Returns notes grouped by their cluster membership.
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* For one note, return max cosine similarity to each cluster that clears the threshold.
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*/
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private async getSimilarNotesByCluster(
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private async getClusterAffinities(
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noteId: string,
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userId: string,
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threshold: number = this.BRIDGE_SIMILARITY_THRESHOLD
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): Promise<Map<number, string[]>> {
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): Promise<ClusterAffinity[]> {
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const cosineDistance = 1 - threshold
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const result = await prisma.$queryRawUnsafe<Array<{
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noteId: string
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clusterId: number | null
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similarity: number
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}>>(
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`SELECT e2."noteId", cm."clusterId"
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`SELECT e2."noteId",
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cm."clusterId",
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(1 - (e1."embedding"::vector <=> e2."embedding"::vector))::float8 AS similarity
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FROM "NoteEmbedding" e1
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CROSS JOIN "NoteEmbedding" e2
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INNER JOIN "Note" n ON n.id = e2."noteId"
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@@ -65,25 +84,36 @@ export class BridgeNotesService {
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cosineDistance
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)
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const clusterMap = new Map<number, string[]>()
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const byCluster = new Map<number, { maxSimilarity: number; hitCount: number }>()
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for (const row of result) {
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const clusterId = row.clusterId ?? -1 // -1 for noise/uncategorized
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if (!clusterMap.has(clusterId)) {
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clusterMap.set(clusterId, [])
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const clusterId = row.clusterId
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if (clusterId === null || clusterId === -1) continue
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const sim = Number(row.similarity)
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if (!Number.isFinite(sim) || sim < threshold) continue
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const prev = byCluster.get(clusterId)
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if (!prev) {
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byCluster.set(clusterId, { maxSimilarity: sim, hitCount: 1 })
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} else {
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prev.maxSimilarity = Math.max(prev.maxSimilarity, sim)
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prev.hitCount += 1
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}
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clusterMap.get(clusterId)!.push(row.noteId)
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}
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return clusterMap
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return [...byCluster.entries()]
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.map(([clusterId, v]) => ({
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clusterId,
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maxSimilarity: v.maxSimilarity,
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hitCount: v.hitCount,
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}))
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.sort((a, b) => b.maxSimilarity - a.maxSimilarity || b.hitCount - a.hitCount)
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}
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/**
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* Detect all bridge notes for a user.
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* A note is a bridge if it has similarities to >= 2 distinct clusters.
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* Detect bridge notes: notes with strong affinity to at least two clusters.
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* Keeps only the top-2 clusters (pair brokerage) and scores by their mean affinity.
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*/
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async detectBridgeNotes(userId: string): Promise<BridgeNote[]> {
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// Get all user's clusters
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const clusters = await prisma.noteCluster.findMany({
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where: { userId },
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select: { clusterId: true, name: true },
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@@ -94,42 +124,40 @@ export class BridgeNotesService {
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return []
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}
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const maxClusters = clusters.length
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const nameById = new Map(
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clusters.map(c => [c.clusterId, clusteringService.displayName(c.name, c.clusterId)])
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)
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const bridgeNotes: BridgeNote[] = []
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// Check each note for bridge potential
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const notes = await prisma.note.findMany({
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where: { userId, trashedAt: null },
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select: { id: true }
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})
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for (const note of notes) {
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const similarByCluster = await this.getSimilarNotesByCluster(note.id, userId)
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const affinities = await this.getClusterAffinities(note.id, userId)
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if (affinities.length < this.MIN_CLUSTERS_FOR_BRIDGE) continue
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// Filter out noise (-1) and get clusters with actual similar notes
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const clustersWithSimilarNotes: number[] = []
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for (const [clusterId, similarNotes] of similarByCluster) {
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if (clusterId !== -1 && similarNotes.length > 0) {
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clustersWithSimilarNotes.push(clusterId)
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}
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}
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const top = affinities.slice(0, this.MAX_BRIDGED_CLUSTERS)
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// Both legs of the bridge must be strong
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if (top.length < this.MIN_CLUSTERS_FOR_BRIDGE) continue
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if (top.some(a => a.maxSimilarity < this.BRIDGE_SIMILARITY_THRESHOLD)) continue
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// Check if this note connects >= 2 clusters
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if (clustersWithSimilarNotes.length >= this.MIN_CLUSTERS_FOR_BRIDGE) {
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const bridgeScore = clustersWithSimilarNotes.length / maxClusters
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const bridgeScore =
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top.reduce((sum, a) => sum + a.maxSimilarity, 0) / top.length
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bridgeNotes.push({
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noteId: note.id,
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bridgeScore,
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clustersConnected: clustersWithSimilarNotes,
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clusterNames: clustersWithSimilarNotes.map(
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cid => clusters.find(c => c.clusterId === cid)?.name || `Cluster ${cid}`
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)
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})
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}
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const clustersConnected = top.map(a => a.clusterId)
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bridgeNotes.push({
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noteId: note.id,
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bridgeScore,
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clustersConnected,
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clusterNames: clustersConnected.map(
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cid => nameById.get(cid) || clusteringService.displayName(null, cid)
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),
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clusterAffinities: top.map(a => a.maxSimilarity),
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})
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}
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// Sort by bridge score (most influential first)
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return bridgeNotes.sort((a, b) => b.bridgeScore - a.bridgeScore)
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}
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@@ -179,10 +207,22 @@ export class BridgeNotesService {
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}
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/**
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* Generate AI-powered suggestions for connecting isolated clusters.
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* Generate AI suggestions for *plausible* missing links between clusters.
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*
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* Scientific grounding (link prediction / KG completion):
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* - Do NOT propose a link for every unconnected pair (combinatorial explosion →
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* forced metaphors like "Stripe ↔ gas dynamics").
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* - Pre-filter by centroid cosine similarity: keep "near-miss" pairs that are
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* related enough to deserve a bridge, but not already tightly fused.
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* - Cap candidate count; rank by structural proximity before spending AI calls.
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* - Prompt: grounded synthesis only; return null if no real shared object/method.
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*/
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async generateBridgeSuggestions(userId: string): Promise<BridgeSuggestion[]> {
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// Get all clusters
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const MAX_SUGGESTIONS = 3
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/** Near-miss only — wide band (0.30–0.62) still let Stripe↔gaz through. */
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const MIN_PAIR_SIMILARITY = 0.45
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const MAX_PAIR_SIMILARITY = 0.58
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const clusters = await prisma.noteCluster.findMany({
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where: { userId },
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select: { clusterId: true, name: true },
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@@ -191,116 +231,254 @@ export class BridgeNotesService {
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if (clusters.length < 2) return []
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// Get existing bridges to see which clusters are already connected
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const existingBridges = await prisma.bridgeNote.findMany({
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where: { userId },
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select: { clustersConnected: true }
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})
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const connectedPairs = new Set<string>()
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for (const bridge of existingBridges) {
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const clusters = JSON.parse(bridge.clustersConnected) as number[]
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for (let i = 0; i < clusters.length; i++) {
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for (let j = i + 1; j < clusters.length; j++) {
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const pair = [clusters[i], clusters[j]].sort().join('-')
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connectedPairs.add(pair)
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const ids = JSON.parse(bridge.clustersConnected) as number[]
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for (let i = 0; i < ids.length; i++) {
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for (let j = i + 1; j < ids.length; j++) {
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connectedPairs.add([ids[i], ids[j]].sort((a, b) => a - b).join('-'))
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}
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}
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}
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// Find unconnected cluster pairs
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const suggestions: BridgeSuggestion[] = []
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const centroids = new Map<number, number[]>()
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const summaries = new Map<number, string>()
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await Promise.all(
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clusters.map(async c => {
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const [centroid, summary] = await Promise.all([
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this.getClusterCentroid(c.clusterId, userId),
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this.getClusterSummary(c.clusterId, userId),
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])
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if (centroid) centroids.set(c.clusterId, centroid)
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summaries.set(c.clusterId, summary)
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})
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)
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type RankedPair = {
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a: typeof clusters[0]
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b: typeof clusters[0]
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similarity: number
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}
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const ranked: RankedPair[] = []
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for (let i = 0; i < clusters.length; i++) {
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for (let j = i + 1; j < clusters.length; j++) {
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const pair = `${clusters[i].clusterId}-${clusters[j].clusterId}`
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const a = clusters[i]
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const b = clusters[j]
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const pairKey = [a.clusterId, b.clusterId].sort((x, y) => x - y).join('-')
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if (connectedPairs.has(pairKey)) continue
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if (connectedPairs.has(pair)) continue // Already connected
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const ca = centroids.get(a.clusterId)
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const cb = centroids.get(b.clusterId)
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if (!ca || !cb) continue
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// Generate suggestion for this unconnected pair
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const suggestion = await this.generateConnectionSuggestion(
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clusters[i].clusterId,
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clusters[j].clusterId,
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clusters[i].name || `Cluster ${clusters[i].clusterId}`,
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clusters[j].name || `Cluster ${clusters[j].clusterId}`,
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userId
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)
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const similarity = this.cosineSimilarity(ca, cb)
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if (similarity < MIN_PAIR_SIMILARITY || similarity > MAX_PAIR_SIMILARITY) continue
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if (suggestion) {
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suggestions.push(suggestion)
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// Lexical gate: no shared vocabulary → no suggestion (blocks Stripe↔gaz)
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if (!this.hasLexicalOverlap(summaries.get(a.clusterId) || '', summaries.get(b.clusterId) || '')) {
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continue
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}
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ranked.push({ a, b, similarity })
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}
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}
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ranked.sort((x, y) => y.similarity - x.similarity)
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const candidates = ranked.slice(0, MAX_SUGGESTIONS)
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const suggestions: BridgeSuggestion[] = []
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for (const { a, b, similarity } of candidates) {
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const suggestion = await this.generateConnectionSuggestion(
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a.clusterId,
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b.clusterId,
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clusteringService.displayName(a.name, a.clusterId),
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clusteringService.displayName(b.name, b.clusterId),
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userId,
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similarity
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)
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if (suggestion && !this.looksLikeForcedMetaphor(suggestion)) {
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suggestions.push(suggestion)
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}
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}
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return suggestions
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}
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/** Shared tokens in note snippets — blocks ornamental cross-domain pairs. */
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private hasLexicalOverlap(textA: string, textB: string): boolean {
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const stop = new Set([
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'the', 'and', 'for', 'with', 'that', 'this', 'from', 'are', 'was', 'were', 'have', 'has',
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'les', 'des', 'une', 'dans', 'pour', 'avec', 'que', 'qui', 'sur', 'par', 'est', 'sont',
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'not', 'note', 'notes', 'untitled', 'sans', 'titre', 'cette', 'plus', 'comme',
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])
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const tokens = (text: string) =>
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new Set(
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text
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.toLowerCase()
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.normalize('NFD')
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.replace(/[\u0300-\u036f]/g, '')
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.split(/[^a-z0-9]+/i)
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.filter(t => t.length >= 4 && !stop.has(t))
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)
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const a = tokens(textA)
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const b = tokens(textB)
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if (a.size === 0 || b.size === 0) return false
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let shared = 0
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for (const t of a) {
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if (b.has(t)) shared += 1
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if (shared >= 2) return true
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}
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return false
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}
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private looksLikeForcedMetaphor(s: BridgeSuggestion): boolean {
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const blob = `${s.suggestedTitle} ${s.suggestedContent} ${s.justification}`.toLowerCase()
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const redFlags = [
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'analogie', 'analogy', 'métaphore', 'metaphor', 'comme si', 'as if',
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'parallel between', 'parallèle entre', 'friction', 'entropie', 'entropy',
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'fluide', 'fluid dynamics', 'rate limit', 'rate-limiting', 'adiabatique',
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'viscosity', 'viscosité', 'théorie de la friction', 'meets digital',
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]
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return redFlags.some(f => blob.includes(f))
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}
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private cosineSimilarity(a: number[], b: number[]): number {
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if (a.length === 0 || a.length !== b.length) return 0
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let dot = 0
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let na = 0
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let nb = 0
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for (let i = 0; i < a.length; i++) {
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dot += a[i] * b[i]
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na += a[i] * a[i]
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nb += b[i] * b[i]
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}
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const den = Math.sqrt(na) * Math.sqrt(nb)
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return den === 0 ? 0 : dot / den
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}
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private async getClusterCentroid(clusterId: number, userId: string): Promise<number[] | null> {
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const rows = await prisma.$queryRawUnsafe<Array<{ embedding: string }>>(
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`SELECT e."embedding"::text AS embedding
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FROM "ClusterMember" cm
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INNER JOIN "NoteEmbedding" e ON e."noteId" = cm."noteId"
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WHERE cm."clusterId" = $1
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AND cm."userId" = $2
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AND e."embedding" IS NOT NULL
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LIMIT 40`,
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clusterId,
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userId
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)
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const vectors: number[][] = []
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for (const row of rows) {
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try {
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const v = JSON.parse(row.embedding) as number[]
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if (Array.isArray(v) && v.length > 0) vectors.push(v)
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} catch {
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/* skip bad vector */
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}
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}
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if (vectors.length === 0) return null
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const dim = vectors[0].length
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const centroid = new Array(dim).fill(0)
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for (const v of vectors) {
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if (v.length !== dim) continue
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for (let i = 0; i < dim; i++) centroid[i] += v[i]
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}
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for (let i = 0; i < dim; i++) centroid[i] /= vectors.length
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return centroid
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}
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/**
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* Generate a specific connection suggestion between two clusters.
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* Generate a grounded connection suggestion between two near-miss clusters.
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*/
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private async generateConnectionSuggestion(
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clusterAId: number,
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clusterBId: number,
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clusterAName: string,
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clusterBName: string,
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userId: string
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userId: string,
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pairSimilarity: number
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): Promise<BridgeSuggestion | null> {
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const summaryA = await this.getClusterSummary(clusterAId, userId)
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const summaryB = await this.getClusterSummary(clusterBId, userId)
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const systemPrompt = `You are a creative assistant that helps users connect ideas.
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Suggest a "bridge note" that could connect two unrelated topics.
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Be specific and creative. Your suggestions should help users discover new insights.`
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const systemPrompt = `You help a personal knowledge base propose MISSING LINKS (link prediction).
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Rules:
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- ONLY suggest a bridge when both themes share a concrete object, tool, method, dataset, or decision visible in the notes.
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- NEVER invent witty analogies between unrelated domains (billing ≠ thermodynamics, hosting ≠ air conditioning).
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- If themes are about different products/domains with no shared practice, return {"viable": false}.
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- Write in the same language as the note summaries.
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- Be concise and actionable.`
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const userPrompt = `I have two groups of notes that are not connected:
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const userPrompt = `Two thematic clusters are unconnected but somewhat related (centroid cosine ≈ ${pairSimilarity.toFixed(2)}).
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||||
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||||
Group A (${clusterAName}):
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Theme A (${clusterAName}):
|
||||
${summaryA}
|
||||
|
||||
Group B (${clusterBName}):
|
||||
Theme B (${clusterBName}):
|
||||
${summaryB}
|
||||
|
||||
Suggest 3 creative bridge note ideas to connect these groups. For each idea, provide:
|
||||
1. A catchy title (max 10 words)
|
||||
2. A brief description of what the note would contain (max 50 words)
|
||||
3. A justification for why this connection is valuable (max 30 words)
|
||||
Propose ONE bridge note that a thoughtful researcher would actually write — a synthesis, comparison with a shared criterion, or decision note — NOT a witty forced analogy.
|
||||
|
||||
Format as JSON:
|
||||
Return ONLY JSON:
|
||||
{
|
||||
"ideas": [
|
||||
{"title": "...", "description": "...", "justification": "..."},
|
||||
...
|
||||
]
|
||||
"viable": true,
|
||||
"title": "≤12 words",
|
||||
"description": "≤40 words: what the note covers",
|
||||
"justification": "≤25 words: why this link is real (shared object/method)"
|
||||
}
|
||||
|
||||
Return ONLY the JSON, no other text.`
|
||||
or {"viable": false}`
|
||||
|
||||
try {
|
||||
const config = await getSystemConfig()
|
||||
const provider = getChatProvider(config)
|
||||
const response = await provider.chat(
|
||||
[{ role: 'user', content: userPrompt }],
|
||||
systemPrompt
|
||||
)
|
||||
const response = await withAiQuota(userId, 'reformulate', async () => {
|
||||
const config = await getSystemConfig()
|
||||
const provider = getChatProvider(config)
|
||||
return provider.chat(
|
||||
[{ role: 'user', content: userPrompt }],
|
||||
systemPrompt,
|
||||
)
|
||||
}, { lane: 'chat' })
|
||||
|
||||
// Parse JSON response
|
||||
const jsonMatch = response.text.match(/\{[\s\S]*\}/)
|
||||
if (!jsonMatch) return null
|
||||
|
||||
const parsed = JSON.parse(jsonMatch[0])
|
||||
const bestIdea = parsed.ideas?.[0]
|
||||
const parsed = JSON.parse(jsonMatch[0]) as {
|
||||
viable?: boolean
|
||||
title?: string
|
||||
description?: string
|
||||
justification?: string
|
||||
ideas?: Array<{ title: string; description: string; justification: string }>
|
||||
}
|
||||
|
||||
if (!bestIdea) return null
|
||||
if (parsed.viable === false) return null
|
||||
|
||||
const idea =
|
||||
parsed.title && parsed.description
|
||||
? {
|
||||
title: parsed.title,
|
||||
description: parsed.description,
|
||||
justification: parsed.justification || '',
|
||||
}
|
||||
: parsed.ideas?.[0]
|
||||
|
||||
if (!idea?.title || !idea?.description) return null
|
||||
|
||||
return {
|
||||
clusterAId,
|
||||
clusterBId,
|
||||
clusterAName,
|
||||
clusterBName,
|
||||
suggestedTitle: bestIdea.title,
|
||||
suggestedContent: bestIdea.description,
|
||||
justification: bestIdea.justification
|
||||
suggestedTitle: idea.title,
|
||||
suggestedContent: idea.description,
|
||||
justification: idea.justification || '',
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error generating bridge suggestion:', error)
|
||||
@@ -351,26 +529,93 @@ Return ONLY the JSON, no other text.`
|
||||
}
|
||||
|
||||
/**
|
||||
* Get bridge suggestions for a user.
|
||||
* Get bridge suggestions — purge ornamental leftovers from older algorithms.
|
||||
* Resolve cluster display names from NoteCluster (fixes frozen "Cluster 15" in BridgeSuggestion rows).
|
||||
*/
|
||||
async getBridgeSuggestions(userId: string, includeDismissed: boolean = false): Promise<BridgeSuggestion[]> {
|
||||
const nameById = await clusteringService.getClusterNameMap(userId)
|
||||
|
||||
const suggestions = await prisma.bridgeSuggestion.findMany({
|
||||
where: {
|
||||
userId,
|
||||
...(includeDismissed ? {} : { isDismissed: false })
|
||||
},
|
||||
orderBy: { createdAt: 'desc' }
|
||||
orderBy: { createdAt: 'desc' },
|
||||
take: 40,
|
||||
})
|
||||
|
||||
return suggestions.map(s => ({
|
||||
clusterAId: s.clusterAId,
|
||||
clusterBId: s.clusterBId,
|
||||
clusterAName: s.clusterAName,
|
||||
clusterBName: s.clusterBName,
|
||||
suggestedTitle: s.suggestedTitle,
|
||||
suggestedContent: s.suggestedContent,
|
||||
justification: s.justification
|
||||
}))
|
||||
const mapped = suggestions.map(s => {
|
||||
const clusterAName = nameById.get(s.clusterAId) || clusteringService.displayName(s.clusterAName, s.clusterAId)
|
||||
const clusterBName = nameById.get(s.clusterBId) || clusteringService.displayName(s.clusterBName, s.clusterBId)
|
||||
return {
|
||||
clusterAId: s.clusterAId,
|
||||
clusterBId: s.clusterBId,
|
||||
clusterAName,
|
||||
clusterBName,
|
||||
suggestedTitle: s.suggestedTitle,
|
||||
suggestedContent: s.suggestedContent,
|
||||
justification: s.justification
|
||||
}
|
||||
})
|
||||
|
||||
// Persist corrected names when suggestions still store placeholders
|
||||
const nameFixes = suggestions.filter(s => {
|
||||
const resolvedA = nameById.get(s.clusterAId)
|
||||
const resolvedB = nameById.get(s.clusterBId)
|
||||
return (
|
||||
(resolvedA && clusteringService.isPlaceholderClusterName(s.clusterAName)) ||
|
||||
(resolvedB && clusteringService.isPlaceholderClusterName(s.clusterBName))
|
||||
)
|
||||
})
|
||||
if (nameFixes.length > 0) {
|
||||
await Promise.all(
|
||||
nameFixes.map(s =>
|
||||
prisma.bridgeSuggestion.updateMany({
|
||||
where: { userId, clusterAId: s.clusterAId, clusterBId: s.clusterBId },
|
||||
data: {
|
||||
clusterAName: nameById.get(s.clusterAId) || clusteringService.displayName(s.clusterAName, s.clusterAId),
|
||||
clusterBName: nameById.get(s.clusterBId) || clusteringService.displayName(s.clusterBName, s.clusterBId),
|
||||
},
|
||||
})
|
||||
)
|
||||
)
|
||||
}
|
||||
|
||||
const keep: BridgeSuggestion[] = []
|
||||
const dropIds: Array<{ clusterAId: number; clusterBId: number }> = []
|
||||
|
||||
for (const s of mapped) {
|
||||
if (this.looksLikeForcedMetaphor(s)) {
|
||||
dropIds.push({ clusterAId: s.clusterAId, clusterBId: s.clusterBId })
|
||||
continue
|
||||
}
|
||||
const [summaryA, summaryB, ca, cb] = await Promise.all([
|
||||
this.getClusterSummary(s.clusterAId, userId),
|
||||
this.getClusterSummary(s.clusterBId, userId),
|
||||
this.getClusterCentroid(s.clusterAId, userId),
|
||||
this.getClusterCentroid(s.clusterBId, userId),
|
||||
])
|
||||
if (!ca || !cb) {
|
||||
dropIds.push({ clusterAId: s.clusterAId, clusterBId: s.clusterBId })
|
||||
continue
|
||||
}
|
||||
const sim = this.cosineSimilarity(ca, cb)
|
||||
if (sim < 0.45 || sim > 0.58 || !this.hasLexicalOverlap(summaryA, summaryB)) {
|
||||
dropIds.push({ clusterAId: s.clusterAId, clusterBId: s.clusterBId })
|
||||
continue
|
||||
}
|
||||
keep.push(s)
|
||||
}
|
||||
|
||||
if (dropIds.length > 0) {
|
||||
await Promise.all(
|
||||
dropIds.map(({ clusterAId, clusterBId }) =>
|
||||
prisma.bridgeSuggestion.deleteMany({ where: { userId, clusterAId, clusterBId } })
|
||||
)
|
||||
)
|
||||
}
|
||||
|
||||
return keep.slice(0, 5)
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -378,11 +623,7 @@ Return ONLY the JSON, no other text.`
|
||||
*/
|
||||
async dismissSuggestion(userId: string, clusterAId: number, clusterBId: number): Promise<void> {
|
||||
await prisma.bridgeSuggestion.updateMany({
|
||||
where: {
|
||||
userId,
|
||||
clusterAId,
|
||||
clusterBId
|
||||
},
|
||||
where: { userId, clusterAId, clusterBId },
|
||||
data: { isDismissed: true }
|
||||
})
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user