# =========================
# 🔥 SAFE GNN (NO CRASH)
# =========================

def run_gnn(nodes, edges):
    try:
        import torch
        from torch_geometric.nn import GCNConv
        from torch_geometric.data import Data

        if len(nodes) == 0 or len(edges) == 0:
            return []

        edge_index = []
        for e in edges:
            edge_index.append([e["source"], e["target"]])

        edge_index = torch.tensor(edge_index).t().contiguous()

        x = torch.rand((len(nodes), 16))

        class GNN(torch.nn.Module):
            def __init__(self):
                super().__init__()
                self.conv1 = GCNConv(16, 16)
                self.conv2 = GCNConv(16, 2)

            def forward(self, x, edge_index):
                x = self.conv1(x, edge_index)
                x = torch.relu(x)
                x = self.conv2(x, edge_index)
                return x

        model = GNN()
        out = model(x, edge_index)

        return [
            {"node": i, "score": float(out[i][0])}
            for i in range(len(nodes))
        ]

    except Exception as e:
        print("⚠️ GNN fallback aktif:", e)

        # 🔥 fallback TANPA torch
        return [
            {"node": i, "score": 0.5}
            for i in range(len(nodes))
        ]