Upload app.py

app.py

@@ -335,19 +335,28 @@ def build_entity_to_entity_graph(entities_by_doc: List[List[Tuple[str, str]]]) -
     # Construir nós (entidades com >= 2 docs)
     nodes = []
     entity_to_id = {}
-    for idx, (entity, count) in enumerate(sorted(entity_doc_count.items(), key=lambda x: x[1], reverse=True)):
+    node_count = sum(1 for e, c in entity_doc_count.items() if c >= 2)
+    
+    node_idx = 0
+    for entity, count in sorted(entity_doc_count.items(), key=lambda x: x[1], reverse=True):
         if count >= 2:
-            entity_to_id[entity] = idx
+            entity_to_id[entity] = node_idx
+            
+            # Posição em espiral 3D (melhor distribuição)
+            angle = 2 * np.pi * node_idx / max(node_count, 1) * 3  # 3 voltas na espiral
+            radius = 1.5 + (node_idx / max(node_count, 1)) * 2  # Raio aumenta
+            z_pos = (node_idx / max(node_count, 1) - 0.5) * 3  # Altura varia
+            
             nodes.append({
-                "id": idx,
+                "id": node_idx,
                 "entity": entity[0],
                 "type": entity[1],
                 "docs": count,
-                # Posição inicial em círculo
-                "x": 2 * np.cos(2 * np.pi * idx / max(len(entity_doc_count), 1)),
-                "y": 2 * np.sin(2 * np.pi * idx / max(len(entity_doc_count), 1)),
-                "z": 0
+                "x": float(radius * np.cos(angle)),
+                "y": float(radius * np.sin(angle)),
+                "z": float(z_pos)
             })
+            node_idx += 1
     
     # Construir arestas (co-ocorrências)
     entity_edges = []