diff --git a/.github/workflows/webpack.yml b/.github/workflows/webpack.yml
new file mode 100644
index 000000000..9626ff6d3
--- /dev/null
+++ b/.github/workflows/webpack.yml
@@ -0,0 +1,28 @@
+name: NodeJS with Webpack
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    strategy:
+      matrix:
+        node-version: [18.x, 20.x, 22.x]
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Use Node.js ${{ matrix.node-version }}
+      uses: actions/setup-node@v4
+      with:
+        node-version: ${{ matrix.node-version }}
+
+    - name: Build
+      run: |
+        npm install
+        npx webpack
diff --git a/README.md b/README.md
index eef0356b2..640af64ed 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,5 @@
-# Gemini Fullstack LangGraph Quickstart
+
+ # Gemini Fullstack LangGraph Quickstart
 
 This project demonstrates a fullstack application using a React frontend and a LangGraph-powered backend agent. The agent is designed to perform comprehensive research on a user's query by dynamically generating search terms, querying the web using Google Search, reflecting on the results to identify knowledge gaps, and iteratively refining its search until it can provide a well-supported answer with citations. This application serves as an example of building research-augmented conversational AI using LangGraph and Google's Gemini models.