not sure what the error is

pages/2_Concepts_comparison.py

@@ -107,14 +107,7 @@ with output_col_1:
                 print(np.round(similarity[0][0], 3))
                 edges.append((concept_ids[i], concept_ids[j], np.round(similarity[0][0], 3)))
 
-    # # Create an empty graph
-    # G = nx.Graph()
-
-    # # Add edges with weights to the graph
-    # for edge in edges:
-    #     node1, node2, weight = edge
-    #     G.add_edge(node1, node2, weight=weight)
-
+    
     net = Network(height="750px", width="100%",)
     for e in edges:
         src = e[0]
@@ -124,7 +117,6 @@ with output_col_1:
         net.add_node(src, src, title=src)
         net.add_node(dst, dst, title=dst)
         net.add_edge(src, dst, value=w, title=src + ' to ' + dst + ' similarity ' +str(w))
-    print(net)
     
     # Generate network with specific layout settings
     net.repulsion(
@@ -158,36 +150,28 @@ with output_col_2:
     #st.write('Concept vector', separation_vector)
     header_col_2.write(f'Concepts {", ".join(concept_ids)} - Latent space CLIP')# - Nodes {",".join(list(imp_nodes))}')
 
-    edges = []
+    edges_clip = []
     for c1 in concept_ids:
         for c2 in concept_ids:
             if c1 != c2:
                 print(f'Similarity between {c1} and {c2}')
                 similarity = cosine_similarity(vectors[c1].reshape(1, -1), vectors[c2].reshape(1, -1))
                 print(np.round(similarity[0][0], 3))
-                edges.append((c1, c2, np.round(similarity[0][0], 3)))
-
-    # # Create an empty graph
-    # G = nx.Graph()
+                edges_clip.append((c1, c2, np.round(similarity[0][0], 3)))
 
-    # # Add edges with weights to the graph
-    # for edge in edges:
-    #     node1, node2, weight = edge
-    #     G.add_edge(node1, node2, weight=weight)
 
-    net = Network(height="750px", width="100%",)
-    for e in edges:
+    net_clip = Network(height="750px", width="100%",)
+    for e in edges_clip:
         src = e[0]
         dst = e[1]
         w = e[2]
 
-        net.add_node(src, src, title=src)
-        net.add_node(dst, dst, title=dst)
-        net.add_edge(src, dst, value=w, title=src + ' to ' + dst + ' similarity ' +str(w))
-    print(net)
+        net_clip.add_node(src, src, title=src)
+        net_clip.add_node(dst, dst, title=dst)
+        net_clip.add_edge(src, dst, value=w, title=src + ' to ' + dst + ' similarity ' +str(w))
     
     # Generate network with specific layout settings
-    net.repulsion(
+    net_clip.repulsion(
                         node_distance=420,
                         central_gravity=0.33,
                         spring_length=110,
@@ -198,13 +182,13 @@ with output_col_2:
     # Save and read graph as HTML file (on Streamlit Sharing)
     try:
         path = '/tmp'
-        net.save_graph(f'{path}/pyvis_graph_clip.html')
+        net_clip.save_graph(f'{path}/pyvis_graph_clip.html')
         HtmlFile = open(f'{path}/pyvis_graph_clip.html', 'r', encoding='utf-8')
 
     # Save and read graph as HTML file (locally)
     except:
         path = '/html_files'
-        net.save_graph(f'{path}/pyvis_graph_clip.html')
+        net_clip.save_graph(f'{path}/pyvis_graph_clip.html')
         HtmlFile = open(f'{path}/pyvis_graph_clip.html', 'r', encoding='utf-8')
 
     # Load HTML file in HTML component for display on Streamlit page