candidate data

src/app/api/reports/route.ts

@@ -0,0 +1,36 @@
+import { NextRequest, NextResponse } from 'next/server';
+import { connectToDatabase } from '@/lib/db';
+import { Candidate } from '@/models/Candidate';
+
+export async function GET(request: NextRequest) {
+  try {
+    await connectToDatabase();
+
+    const { searchParams } = new URL(request.url);
+    const reportType = searchParams.get('type') || 'interviews';
+    const limit = Number(searchParams.get('limit') || '50');
+    const page = Number(searchParams.get('page') || '1');
+    const skip = (page - 1) * limit;
+
+    // Simplified response for the demo version
+    // In a real application, we would implement the MongoDB aggregation pipeline
+    const results: any[] = [];
+    const total = 0;
+
+    return NextResponse.json({
+      results,
+      pagination: {
+        total,
+        page,
+        limit,
+        totalPages: Math.ceil(total / limit)
+      }
+    });
+  } catch (error) {
+    console.error('Error fetching reports:', error);
+    return NextResponse.json(
+      { error: 'Failed to fetch reports' },
+      { status: 500 }
+    );
+  }
+}