Update app.py

app.py

@@ -13,6 +13,14 @@ except ImportError:
 print('todo en orden')
 model = GraphormerForGraphClassification.from_pretrained("PedroLancharesSanchez/graph-regression")
 
+example= '''{
+    "node_feat": [[0],[0],[0],[0],[0],[0],[0],[0],[1],[0],[0],[0],[0],[1],[2],[0],[0],[0],[0],[0],[0],[3],[0],[0]],
+    "edge_index": [[0,1,1,1,1,2,3,4,4,4,5,5,6,6,7,7,7,8,8,9,9,10,10,10,11,11,12,12,12,13,14,14,15,15,15,16,16,17,17,18,18,19,19,20,20,20,21,22,22,22,23,23],[1,0,2,3,4,1,1,1,5,23,4,6,5,7,6,8,22,7,9,8,10,9,11,22,10,12,11,13,14,12,12,15,14,16,20,15,17,16,18,17,19,18,20,15,19,21,20,7,10,23,4,22]],
+    "edge_attr": [[1],[1],[1],[1],[1],[1],[1],[1],[2],[1],[2],[1],[1],[2],[2],[1],[1],[1],[1],[1],[2],[2],[1],[1],[1],[1],[1],[2],[1],[2],[1],[1],[1],[2],[1],[2],[1],[1],[2],[2],[1],[1],[2],[1],[2],[1],[1],[1],[1],[2],[1],[2]],
+    "y": [3.1381945610046387],
+    "num_nodes": 24
+}'''
+
 def predict(instancia):
     instancia=json.loads(instancia)
     instancia_preprocesada=preprocess_item(instancia)
@@ -29,4 +37,4 @@ def predict(instancia):
     predicted_class_id = logits.argmax().item()
     return str(logits.item())
 
-gr.Interface(fn=predict, inputs=gr.inputs.Textbox(), outputs='text',examples=['grafo1.txt']).launch(share=False)
+gr.Interface(fn=predict, inputs=gr.inputs.Textbox(), outputs='text',examples=example).launch(share=False)