feat: brainstorm sessions, PDF document Q&A, embedding fixes, and UI improvements

- Add brainstorm feature with collaborative canvas, AI idea generation, live cursors, playback, and export
- Add PDF upload/extraction/ingestion pipeline with pgvector document search (RAG)
- Add document Q&A overlay with streaming chat and PDF preview
- Add note attachments UI with status polling, grid layout, and auto-scroll
- Add task extraction AI tool and agent executor improvements
- Fix NoteEmbedding missing updatedAt column, re-index 66 notes with 1536-dim embeddings
- Fix brainstorm 'Create Note' button: add success toast and redirect to created note
- Fix memory echo notification infinite polling
- Fix chat route to always include document_search tool
- Add brainstorm i18n keys across all 14 locales
- Add socket server for real-time brainstorm collaboration
- Add hierarchical notebook selector and organize notebook dialog improvements
- Add sidebar brainstorm section with session management
- Update prisma schema with brainstorm tables, attachments, and document chunks

memento-note/lib/ai/tools/document-search.tool.ts

@@ -0,0 +1,73 @@
+import { tool } from 'ai'
+import { z } from 'zod'
+import { toolRegistry } from './registry'
+import { embeddingService } from '@/lib/ai/services/embedding.service'
+import prisma from '@/lib/prisma'
+
+toolRegistry.register({
+  name: 'document_search',
+  description: 'Search within PDF documents attached to notes. Returns relevant passages with page numbers and source document info.',
+  isInternal: true,
+  buildTool: (ctx) =>
+    tool({
+      description: `Search within PDF documents attached to the user's notes.
+Returns matching passages with page numbers, chunk content, and the source note/document info.
+Use this when the user asks about specific documents, PDFs, or attached files.`,
+      inputSchema: z.object({
+        query: z.string().describe('The search query to find relevant passages in documents'),
+        noteId: z.string().optional().describe('Optional: restrict search to attachments of a specific note'),
+        limit: z.number().optional().describe('Max results to return (default 5)').default(5),
+      }),
+      execute: async ({ query, noteId, limit = 5 }) => {
+        try {
+          const queryEmbedding = await embeddingService.generateEmbedding(query)
+          const vectorStr = embeddingService.toVectorString(queryEmbedding.embedding)
+
+          let noteFilter = ''
+          const params: any[] = [vectorStr, limit, ctx.userId]
+
+          if (noteId) {
+            noteFilter = `AND na."noteId" = $4`
+            params.push(noteId)
+          }
+
+          const results = await prisma.$queryRawUnsafe(
+            `SELECT
+              dc.id as "chunkId",
+              dc.content,
+              dc."pageNumber",
+              dc."chunkIndex",
+              na.id as "attachmentId",
+              na."fileName",
+              na."pageCount",
+              na."noteId",
+              n.title as "noteTitle"
+            FROM "DocumentChunk" dc
+            JOIN "NoteAttachment" na ON na.id = dc."attachmentId"
+            JOIN "Note" n ON n.id = na."noteId"
+            WHERE dc."embedding" IS NOT NULL
+              AND na.status = 'ready'
+              AND n."trashedAt" IS NULL
+              AND n."userId" = $3
+              ${noteFilter}
+            ORDER BY dc."embedding" <=> $1::vector
+            LIMIT $2`,
+            ...params
+          ) as any[]
+
+          if (!results.length) return { results: [], message: 'No matching documents found' }
+
+          return results.map(r => ({
+            content: r.content.substring(0, 600),
+            pageNumber: r.pageNumber,
+            chunkIndex: r.chunkIndex,
+            fileName: r.fileName,
+            noteId: r.noteId,
+            noteTitle: r.noteTitle || 'Untitled',
+          }))
+        } catch (e: any) {
+          return { error: `Document search failed: ${e.message}` }
+        }
+      },
+    }),
+})