Update app.py

app.py

@@ -189,12 +189,17 @@ class SpeechAnalyzer:
         for noun in top_nouns:
             G.add_node(noun)
         
-        # Connect related nouns
+        # Connect related nouns and add positions
+        pos = nx.spring_layout(G)
         for i in range(len(top_nouns)):
             for j in range(i+1, len(top_nouns)):
                 if top_nouns[i] in text and top_nouns[j] in text:
                     G.add_edge(top_nouns[i], top_nouns[j])
         
+        # Store positions in graph
+        for node in G.nodes():
+            G.nodes[node]['pos'] = pos[node]
+        
         return G
 
 def main():
@@ -289,25 +294,55 @@ def main():
             # Convert NetworkX graph to Plotly
             edge_x = []
             edge_y = []
+            node_x = []
+            node_y = []
+            node_text = []
+            
+            # Add edges
             for edge in semantic_graph.edges():
-                x0, y0 = semantic_graph.nodes[edge[0]].get('pos', (0,0))
-                x1, y1 = semantic_graph.nodes[edge[1]].get('pos', (0,0))
-                edge_x.append(x0)
-                edge_x.append(x1)
-                edge_y.append(y0)
-                edge_y.append(y1)
+                x0, y0 = semantic_graph.nodes[edge[0]]['pos']
+                x1, y1 = semantic_graph.nodes[edge[1]]['pos']
+                edge_x.extend([x0, x1, None])
+                edge_y.extend([y0, y1, None])
+            
+            # Add nodes
+            for node in semantic_graph.nodes():
+                x, y = semantic_graph.nodes[node]['pos']
+                node_x.append(x)
+                node_y.append(y)
+                node_text.append(node)
             
-            # Plotly network visualization
+            # Create the network visualization
             network_fig = go.Figure()
+            
+            # Add edges
             network_fig.add_trace(go.Scatter(
-                x=edge_x, 
-                y=edge_y,
+                x=edge_x, y=edge_y,
                 mode='lines',
                 line=dict(width=0.5, color='#888'),
                 hoverinfo='none'
             ))
             
+            # Add nodes
+            network_fig.add_trace(go.Scatter(
+                x=node_x, y=node_y,
+                mode='markers+text',
+                marker=dict(size=10),
+                text=node_text,
+                textposition="top center",
+                hoverinfo='text'
+            ))
+            
+            network_fig.update_layout(
+                showlegend=False,
+                hovermode='closest',
+                margin=dict(b=0,l=0,r=0,t=0),
+                xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
+                yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)
+            )
+            
             st.plotly_chart(network_fig)
+
         
         with tab5:
             st.subheader("Advanced NLP Analysis")