diff --git a/services/ml/app/__pycache__/main.cpython-313.pyc b/services/ml/app/__pycache__/main.cpython-313.pyc
index 227dfb4..b04affe 100644
Binary files a/services/ml/app/__pycache__/main.cpython-313.pyc and b/services/ml/app/__pycache__/main.cpython-313.pyc differ
diff --git a/services/ml/app/main.py b/services/ml/app/main.py
index 44cfd7d..976ea82 100644
--- a/services/ml/app/main.py
+++ b/services/ml/app/main.py
@@ -66,7 +66,7 @@ class CandleData(BaseModel):
     high: float
     low: float
     close: float
-    volume: float
+    volume: Optional[float] = None
 
 
 class PredictRequest(BaseModel):
diff --git a/src/app/api/charts/[id]/route.ts b/src/app/api/charts/[id]/route.ts
index 923fbbf..a14fd49 100644
--- a/src/app/api/charts/[id]/route.ts
+++ b/src/app/api/charts/[id]/route.ts
@@ -3,6 +3,26 @@ import { db } from '@/lib/db';
 import { charts, candles, annotations } from '@/lib/db/schema';
 import { eq } from 'drizzle-orm';
 
+export async function GET(
+  _request: NextRequest,
+  { params }: { params: Promise<{ id: string }> }
+) {
+  const { id } = await params;
+  const chartId = parseInt(id, 10);
+
+  if (isNaN(chartId)) {
+    return NextResponse.json({ error: 'Invalid chart ID' }, { status: 400 });
+  }
+
+  const result = await db.select().from(charts).where(eq(charts.id, chartId)).limit(1);
+  
+  if (result.length === 0) {
+    return NextResponse.json({ error: 'Chart not found' }, { status: 404 });
+  }
+
+  return NextResponse.json(result[0]);
+}
+
 export async function DELETE(
   _request: NextRequest,
   { params }: { params: Promise<{ id: string }> }
diff --git a/src/app/page.tsx b/src/app/page.tsx
index edf9531..246b927 100644
--- a/src/app/page.tsx
+++ b/src/app/page.tsx
@@ -512,18 +512,12 @@ export default function Home() {
         throw new Error('No candles found for this chart');
       }
 
-      const startTime = candlesData[0].time;
-      const endTime = candlesData[candlesData.length - 1].time;
-
-      // Make batch prediction request
-      const response = await fetch('/api/predict/batch', {
+      // Use regular predict endpoint with all candles from the database
+      const response = await fetch('/api/predict', {
         method: 'POST',
         headers: { 'Content-Type': 'application/json' },
         body: JSON.stringify({
-          pair: chartData.name,
-          timeframe: '1h', // TODO: Get from chart metadata
-          start_time: startTime,
-          end_time: endTime,
+          candles: candlesData,
         }),
       });