<｜begin▁of▁sentence｜>### Instruction:
In the realm of international negotiations, as with crafting the frameworks for treaties, precise replication of data models can be as critical as maintaining consistent communication channels. In this context, how might one employ a predetermined numerical code—akin to a diplomatic cipher—to ensure that the algorithmic creation of a network model yields uniform outcomes? To relate this to a tangible situation, let us consider that we've been tasked with using NetworkX to map a network of 10 key diplomatic entities. The connections between these entities are formulated based on a probabilistic model, specifically with a likelihood of 0.5 for the establishment of each potential conduit of communication. The crux of the matter pertains to the utilization of this numerical code to generate a graph that remains consistent in every iteration of diplomatic data analysis.
### Response:
import networkx as nx
import numpy as np

# Seed value
seed = 42

# Create a random state instance
random_state = nx.utils.create_random_state(seed)

# Generate a random graph
G = nx.gnp_random_graph(10, 0.5, seed=random_state)

# Print the generated edges
print(G.edges())
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