PdIPS
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@@ -10,6 +10,9 @@
     <!-- CSS for examples -->
     <link rel="stylesheet" href="./assets/css/examples.css" />
 
+    <link rel="icon" type="image/png" href="/assets/favicon.png" />
+    <link rel="shortcut icon" type="image/png" href="/assets/favicon.png" />
+
     <!-- This script tag bootstraps PyScript -->
     <script type="module" src="https://pyscript.net/releases/2024.1.1/core.js"></script>
 
@@ -33,7 +36,30 @@
 </head>
 <body>
 <main>
-<h1 id="page-title">Consensus-based optimization demo </h1>
+<h1 id="page-title">🤝 Consensus-Based Optimization</h1>
+
+<div id="intro">
+  <p>
+    This interactive demo showcases <strong>consensus-based optimization</strong> (CBO), a particle-based method 
+    for solving optimization problems through swarm dynamics and stochastic attraction to consensus points.
+  </p>
+
+  <p>
+    The algorithm is implemented via the 
+    <a href="https://github.com/PdIPS/CBXpy" target="_blank">CBXPy library</a> 🐍.
+    <div><img src="assets/cbxpy_logo.png" alt="CBXPy Logo" width="300" /></div>
+  </p>
+
+  <p>
+    ⚙️ You can adjust paramters, select different loss functions and drag around the gloabl minimum. The usage is optimized for laptops/desktops but mobile should also work.
+  </p>
+
+  <p style="margin-top: 1em;">
+    📝 <strong>Credit:</strong> Tim Roith
+  </p>
+</div>
+
+
 <canvas id="canvas" width="600"  height="300" style="border:1px solid black;"></canvas>
 <canvas id="loss"   width="300"  height="150" style="display:none;"></canvas>
 <script>
 
@@ -1,6 +1,6 @@
 name = "Matplotlib"
 description = "A simple application showing how to use Matplotlib to generate a graph and display it with PyScript."
-packages = ["matplotlib", "scipy", "https://files.pythonhosted.org/packages/3f/af/ddc0366079b447759224d5ad92020eea6082cd9db490ef4c6633d3f63c08/cbx-1.0.1-py3-none-any.whl"]
+packages = ["matplotlib", "scipy", "cbx>=1.0.0"]
 
 
 [files]