From d842dc996ab7cf16a04d6ed41b74d02538ef998d Mon Sep 17 00:00:00 2001
From: Santosh Bhavani <santosh.bhavani@live.com>
Date: Sun, 19 Oct 2025 19:57:11 -0700
Subject: [PATCH] feat(api): add LLM-enhanced graph query endpoint

- Create new /api/graph-query-llm endpoint for graph search + LLM generation
- Retrieves triples using graph search and generates answers using LLM
- Supports both traditional and vector-based graph search
- Makes traditional graph search comparable to RAG for benchmarking
---
 .../frontend/app/api/graph-query-llm/route.ts | 45 +++++++++++++++++++
 1 file changed, 45 insertions(+)
 create mode 100644 nvidia/txt2kg/assets/frontend/app/api/graph-query-llm/route.ts

diff --git a/nvidia/txt2kg/assets/frontend/app/api/graph-query-llm/route.ts b/nvidia/txt2kg/assets/frontend/app/api/graph-query-llm/route.ts
new file mode 100644
index 0000000..963dd06
--- /dev/null
+++ b/nvidia/txt2kg/assets/frontend/app/api/graph-query-llm/route.ts
@@ -0,0 +1,45 @@
+import { NextRequest, NextResponse } from 'next/server';
+import backendService from '@/lib/backend-service';
+import { getGraphDbType } from '../settings/route';
+
+/**
+ * API endpoint for LLM-enhanced graph query
+ * This retrieves triples using graph search and generates an answer using LLM
+ * Makes traditional graph search comparable to RAG for fair benchmarking
+ * POST /api/graph-query-llm
+ */
+export async function POST(request: NextRequest) {
+  try {
+    const { query, topK = 5, useTraditional = true, llmModel, llmProvider } = await request.json();
+    
+    if (!query) {
+      return NextResponse.json({ error: 'Query is required' }, { status: 400 });
+    }
+    
+    // Initialize backend if needed with the selected graph DB type
+    if (!backendService.isInitialized) {
+      const graphDbType = getGraphDbType();
+      console.log(`Initializing backend with graph DB type: ${graphDbType}`);
+      await backendService.initialize(graphDbType);
+    }
+    
+    console.log(`Graph query with LLM: "${query}", topK=${topK}, traditional=${useTraditional}, model=${llmModel || 'default'}, provider=${llmProvider || 'default'}`);
+    
+    // Query the backend with LLM enhancement
+    const result = await backendService.queryWithLLM(query, topK, useTraditional, llmModel, llmProvider);
+    
+    // Return results
+    return NextResponse.json({
+      query,
+      answer: result.answer,
+      triples: result.triples,
+      count: result.count,
+      message: `Retrieved ${result.count} triples and generated answer using ${useTraditional ? 'traditional' : 'vector'} graph search + LLM`
+    });
+  } catch (error) {
+    console.error('Error in graph query with LLM:', error);
+    const errorMessage = error instanceof Error ? error.message : 'Unknown error';
+    return NextResponse.json({ error: errorMessage }, { status: 500 });
+  }
+}
+