Update services/gnn.py

services/gnn.py

@@ -1,23 +1,22 @@
-import torch
+# =========================
+# 🔥 SAFE GNN (NO CRASH)
+# =========================
 
 def run_gnn(nodes, edges):
     try:
-        from torch_geometric.data import Data
+        import torch
         from torch_geometric.nn import GCNConv
+        from torch_geometric.data import Data
 
-        # convert ke index
-        node_ids = list(range(len(nodes)))
-        edge_index = []
+        if len(nodes) == 0 or len(edges) == 0:
+            return []
 
+        edge_index = []
         for e in edges:
             edge_index.append([e["source"], e["target"]])
 
-        if len(edge_index) == 0:
-            return []
-
         edge_index = torch.tensor(edge_index).t().contiguous()
 
-        # fitur dummy (random)
         x = torch.rand((len(nodes), 16))
 
         class GNN(torch.nn.Module):
@@ -35,19 +34,16 @@ def run_gnn(nodes, edges):
         model = GNN()
         out = model(x, edge_index)
 
-        scores = out.detach().numpy()
-
-        result = []
-        for i, s in enumerate(scores):
-            result.append({
-                "node": i,
-                "score": float(s[0])
-            })
-
-        return result
+        return [
+            {"node": i, "score": float(out[i][0])}
+            for i in range(len(nodes))
+        ]
 
     except Exception as e:
-        print("⚠️ GNN fallback:", e)
+        print("⚠️ GNN fallback aktif:", e)
 
-        # fallback sederhana
-        return [{"node": i, "score": 0.5} for i in range(len(nodes))]
+        # 🔥 fallback TANPA torch
+        return [
+            {"node": i, "score": 0.5}
+            for i in range(len(nodes))
+        ]