<｜begin▁of▁sentence｜>### Instruction:
Given a directed graph with vertices ['x', 'a', 'b', 'c', 'd', 'e', 'y'] and edges with capacities as follows: (('x', 'a', 3.0), ('x', 'b', 1.0), ('a', 'c', 3.0), ('b', 'c', 5.0), ('b', 'd', 4.0), ('d', 'e', 2.0), ('c', 'y', 2.0), ('e', 'y', 3.0)), can you compute the minimum number of units that need to be transported from node 'x' to node 'y' without exceeding the capacities on the edges, effectively finding the minimum cut value of the network?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()
# Add edges with capacity
G.add_edge('x', 'a', capacity=3.0)
G.add_edge('x', 'b', capacity=1.0)
G.add_edge('a', 'c', capacity=3.0)
G.add_edge('b', 'c', capacity=5.0)
G.add_edge('b', 'd', capacity=4.0)
G.add_edge('d', 'e', capacity=2.0)
G.add_edge('c', 'y', capacity=2.0)
G.add_edge('e', 'y', capacity=3.0)

# Compute only the value of the minimum (s, t)-cut
minimum_cut = nx.minimum_cut_value(G, 'x', 'y')
print(f'Minimum cut value from x to y: {minimum_cut}')
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