Update app.py

app.py

@@ -43,20 +43,21 @@ def run_query_and_visualize(qtext, jsonld_url):
     # Processa os resultados da consulta
     for row in qres:
         s, p, o = row
-        G.add_node(str(s))
-        G.add_node(str(o))
-        G.add_edge(str(s), str(o), label=str(p))
+        G.add_node(str(s), label=str(s).split('/')[-1])  # Usar o último segmento da URI como rótulo
+        G.add_node(str(o), label=str(o).split('/')[-1])
+        G.add_edge(str(s), str(o), label=str(p).split('/')[-1])
     
     # Desenha o gráfico usando NetworkX e Matplotlib
-    pos = nx.spring_layout(G, k=0.5)
+    pos = nx.spring_layout(G, k=0.8)
     plt.figure(figsize=(15, 10))
     
-    nx.draw(G, pos, with_labels=True, node_size=3000, node_color="skyblue", font_size=9, font_color="black", font_weight="bold", edge_color="gray", width=1.5, alpha=0.7)
-    edge_labels = nx.get_edge_attributes(G, 'label')
-    nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels, font_color="red", font_size=7, label_pos=0.5)
-
+    nodes = nx.draw_networkx_nodes(G, pos, node_size=5000, node_color="#87CEEB", edgecolors="black")
+    edges = nx.draw_networkx_edges(G, pos, width=2, edge_color="gray", alpha=0.6)
+    node_labels = nx.draw_networkx_labels(G, pos, font_size=12, font_color="black")
+    edge_labels = nx.draw_networkx_edge_labels(G, pos, edge_labels=nx.get_edge_attributes(G, 'label'), font_color="red", font_size=10)
+    
     plt.title("Resultado da Consulta SPARQL", size=15)
-    plt.box(False)
+    plt.axis('off')
     
     # Salva o gráfico em um arquivo
     buf = BytesIO()