improvement(knowledge): search returns document name (#1167)

apps/sim/app/api/knowledge/search/route.ts

@@ -77,14 +77,13 @@ export async function POST(request: NextRequest) {
         ? validatedData.knowledgeBaseIds
         : [validatedData.knowledgeBaseIds]
 
-      // Check access permissions for each knowledge base using proper workspace-based permissions
-      const accessibleKbIds: string[] = []
-      for (const kbId of knowledgeBaseIds) {
-        const accessCheck = await checkKnowledgeBaseAccess(kbId, userId)
-        if (accessCheck.hasAccess) {
-          accessibleKbIds.push(kbId)
-        }
-      }
+      // Check access permissions in parallel for performance
+      const accessChecks = await Promise.all(
+        knowledgeBaseIds.map((kbId) => checkKnowledgeBaseAccess(kbId, userId))
+      )
+      const accessibleKbIds: string[] = knowledgeBaseIds.filter(
+        (_, idx) => accessChecks[idx]?.hasAccess
+      )
 
       // Map display names to tag slots for filtering
       let mappedFilters: Record<string, string> = {}
@@ -137,7 +136,10 @@ export async function POST(request: NextRequest) {
 
       // Generate query embedding only if query is provided
       const hasQuery = validatedData.query && validatedData.query.trim().length > 0
-      const queryEmbedding = hasQuery ? await generateSearchEmbedding(validatedData.query!) : null
+      // Start embedding generation early and await when needed
+      const queryEmbeddingPromise = hasQuery
+        ? generateSearchEmbedding(validatedData.query!)
+        : Promise.resolve(null)
 
       // Check if any requested knowledge bases were not accessible
       const inaccessibleKbIds = knowledgeBaseIds.filter((id) => !accessibleKbIds.includes(id))
@@ -165,7 +167,7 @@ export async function POST(request: NextRequest) {
         // Tag + Vector search
         logger.debug(`[${requestId}] Executing tag + vector search with filters:`, mappedFilters)
         const strategy = getQueryStrategy(accessibleKbIds.length, validatedData.topK)
-        const queryVector = JSON.stringify(queryEmbedding)
+        const queryVector = JSON.stringify(await queryEmbeddingPromise)
 
         results = await handleTagAndVectorSearch({
           knowledgeBaseIds: accessibleKbIds,
@@ -178,7 +180,7 @@ export async function POST(request: NextRequest) {
         // Vector-only search
         logger.debug(`[${requestId}] Executing vector-only search`)
         const strategy = getQueryStrategy(accessibleKbIds.length, validatedData.topK)
-        const queryVector = JSON.stringify(queryEmbedding)
+        const queryVector = JSON.stringify(await queryEmbeddingPromise)
 
         results = await handleVectorOnlySearch({
           knowledgeBaseIds: accessibleKbIds,
@@ -213,24 +215,28 @@ export async function POST(request: NextRequest) {
       }
 
       // Fetch tag definitions for display name mapping (reuse the same fetch from filtering)
+      const tagDefsResults = await Promise.all(
+        accessibleKbIds.map(async (kbId) => {
+          try {
+            const tagDefs = await getDocumentTagDefinitions(kbId)
+            const map: Record<string, string> = {}
+            tagDefs.forEach((def) => {
+              map[def.tagSlot] = def.displayName
+            })
+            return { kbId, map }
+          } catch (error) {
+            logger.warn(
+              `[${requestId}] Failed to fetch tag definitions for display mapping:`,
+              error
+            )
+            return { kbId, map: {} as Record<string, string> }
+          }
+        })
+      )
       const tagDefinitionsMap: Record<string, Record<string, string>> = {}
-      for (const kbId of accessibleKbIds) {
-        try {
-          const tagDefs = await getDocumentTagDefinitions(kbId)
-
-          tagDefinitionsMap[kbId] = {}
-          tagDefs.forEach((def) => {
-            tagDefinitionsMap[kbId][def.tagSlot] = def.displayName
-          })
-          logger.debug(
-            `[${requestId}] Display mapping - KB ${kbId} tag definitions:`,
-            tagDefinitionsMap[kbId]
-          )
-        } catch (error) {
-          logger.warn(`[${requestId}] Failed to fetch tag definitions for display mapping:`, error)
-          tagDefinitionsMap[kbId] = {}
-        }
-      }
+      tagDefsResults.forEach(({ kbId, map }) => {
+        tagDefinitionsMap[kbId] = map
+      })
 
       return NextResponse.json({
         success: true,
@@ -260,6 +266,7 @@ export async function POST(request: NextRequest) {
               id: result.id,
               content: result.content,
               documentId: result.documentId,
+              documentName: (result as any).documentName || undefined,
               chunkIndex: result.chunkIndex,
               tags, // Clean display name mapped tags
               similarity: hasQuery ? 1 - result.distance : 1, // Perfect similarity for tag-only searches

apps/sim/app/api/knowledge/search/utils.ts

@@ -1,7 +1,7 @@
 import { and, eq, inArray, sql } from 'drizzle-orm'
 import { createLogger } from '@/lib/logs/console/logger'
 import { db } from '@/db'
-import { embedding } from '@/db/schema'
+import { document, embedding } from '@/db/schema'
 
 const logger = createLogger('KnowledgeSearchUtils')
 
@@ -9,6 +9,7 @@ export interface SearchResult {
   id: string
   content: string
   documentId: string
+  documentName: string | null
   chunkIndex: number
   tag1: string | null
   tag2: string | null
@@ -130,6 +131,7 @@ async function executeVectorSearchOnIds(
       id: embedding.id,
       content: embedding.content,
       documentId: embedding.documentId,
+      documentName: document.filename,
       chunkIndex: embedding.chunkIndex,
       tag1: embedding.tag1,
       tag2: embedding.tag2,
@@ -142,6 +144,7 @@ async function executeVectorSearchOnIds(
       knowledgeBaseId: embedding.knowledgeBaseId,
     })
     .from(embedding)
+    .innerJoin(document, eq(embedding.documentId, document.id))
     .where(
       and(
         inArray(embedding.id, embeddingIds),
@@ -173,6 +176,7 @@ export async function handleTagOnlySearch(params: SearchParams): Promise<SearchR
           id: embedding.id,
           content: embedding.content,
           documentId: embedding.documentId,
+          documentName: document.filename,
           chunkIndex: embedding.chunkIndex,
           tag1: embedding.tag1,
           tag2: embedding.tag2,
@@ -185,6 +189,7 @@ export async function handleTagOnlySearch(params: SearchParams): Promise<SearchR
           knowledgeBaseId: embedding.knowledgeBaseId,
         })
         .from(embedding)
+        .innerJoin(document, eq(embedding.documentId, document.id))
         .where(
           and(
             eq(embedding.knowledgeBaseId, kbId),
@@ -204,6 +209,7 @@ export async function handleTagOnlySearch(params: SearchParams): Promise<SearchR
       id: embedding.id,
       content: embedding.content,
       documentId: embedding.documentId,
+      documentName: document.filename,
       chunkIndex: embedding.chunkIndex,
       tag1: embedding.tag1,
       tag2: embedding.tag2,
@@ -216,6 +222,7 @@ export async function handleTagOnlySearch(params: SearchParams): Promise<SearchR
       knowledgeBaseId: embedding.knowledgeBaseId,
     })
     .from(embedding)
+    .innerJoin(document, eq(embedding.documentId, document.id))
     .where(
       and(
         inArray(embedding.knowledgeBaseId, knowledgeBaseIds),
@@ -247,6 +254,7 @@ export async function handleVectorOnlySearch(params: SearchParams): Promise<Sear
           id: embedding.id,
           content: embedding.content,
           documentId: embedding.documentId,
+          documentName: document.filename,
           chunkIndex: embedding.chunkIndex,
           tag1: embedding.tag1,
           tag2: embedding.tag2,
@@ -259,6 +267,7 @@ export async function handleVectorOnlySearch(params: SearchParams): Promise<Sear
           knowledgeBaseId: embedding.knowledgeBaseId,
         })
         .from(embedding)
+        .innerJoin(document, eq(embedding.documentId, document.id))
         .where(
           and(
             eq(embedding.knowledgeBaseId, kbId),
@@ -280,6 +289,7 @@ export async function handleVectorOnlySearch(params: SearchParams): Promise<Sear
       id: embedding.id,
       content: embedding.content,
       documentId: embedding.documentId,
+      documentName: document.filename,
       chunkIndex: embedding.chunkIndex,
       tag1: embedding.tag1,
       tag2: embedding.tag2,
@@ -292,6 +302,7 @@ export async function handleVectorOnlySearch(params: SearchParams): Promise<Sear
       knowledgeBaseId: embedding.knowledgeBaseId,
     })
     .from(embedding)
+    .innerJoin(document, eq(embedding.documentId, document.id))
     .where(
       and(
         inArray(embedding.knowledgeBaseId, knowledgeBaseIds),

apps/sim/app/workspace/[workspaceId]/w/components/sidebar/components/create-menu/create-menu.tsx

@@ -18,7 +18,7 @@ const logger = createLogger('CreateMenu')
 
 const TIMERS = {
   LONG_PRESS_DELAY: 500,
-  CLOSE_DELAY: 150,
+  CLOSE_DELAY: 300,
 } as const
 
 interface CreateMenuProps {

apps/sim/tools/knowledge/search.ts

@@ -113,6 +113,7 @@ export const knowledgeSearchTool: ToolConfig<any, KnowledgeSearchResponse> = {
           id: { type: 'string' },
           content: { type: 'string' },
           documentId: { type: 'string' },
+          documentName: { type: 'string' },
           chunkIndex: { type: 'number' },
           similarity: { type: 'number' },
           metadata: { type: 'object' },

apps/sim/tools/knowledge/types.ts

@@ -2,6 +2,7 @@ export interface KnowledgeSearchResult {
   id: string
   content: string
   documentId: string
+  documentName: string
   chunkIndex: number
   metadata: Record<string, any>
   similarity: number