Added a simple description of the space.

app.py

@@ -110,7 +110,16 @@ def agg_cluster(n_feats, measure):
     dist_plot = plot_distances(measure, X, y)
     return gt_plt, cluster_waves_plot, dist_plot
 
+title = "Agglomerative clustering with different metrics"
 with gr.Blocks() as demo:
+    gr.Markdown(f" # {title}")
+    gr.Markdown(
+            """
+            This example demonstrates the effect of different metrics on hierarchical clustering.
+
+            This is based on the example [here](https://scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering_metrics.html#sphx-glr-auto-examples-cluster-plot-agglomerative-clustering-metrics-py)
+            """
+            )
     with gr.Row():
         with gr.Column():
             n_feats = gr.Slider(10, 4000, 2000, label="Number of Features")

requirements.txt

@@ -0,0 +1,2 @@
+matplotlib==3.6.3
+scikit-learn==1.2.2