<｜begin▁of▁sentence｜>### Instruction:
As an IT Consultant working with a client on optimizing their network infrastructure, I've identified a critical connection between server node 1 and server node 4 within the network's architecture. In preparing for a risk assessment and redundancy plan, we need to establish the resiliency of this connection. Leveraging NetworkX, a task has surfaced where we must determine the minimum subset of server nodes that, if taken offline, would sever the communications between server node 1 and server node 4, thus disrupting their connectivity.

To proceed with the analysis, we should use NetworkX's `local_node_connectivity` function, focusing on the specific edge configuration provided by the network team: [(1, 2), (2, 3), (3, 4), (4, 5), (5, 1), (1, 3)]. Your insight on the minimum number of server nodes to be removed to achieve this disconnection would be valuable for the robustness assessment of our network's current setup. Could you reformulate this requirement into a practical evaluation task for our upcoming IT systems review?
### Response:
import networkx as nx
from networkx.algorithms.connectivity import local_node_connectivity

G = nx.Graph()
G.add_edges_from([(1, 2), (2, 3), (3, 4), (4, 5), (5, 1), (1, 3)])
connectivity = local_node_connectivity(G, 1, 4)

print('Local node connectivity between nodes 1 and 4 is:', connectivity)
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