<｜begin▁of▁sentence｜>### Instruction:
Sure, imagine you're a biologist and you're studying two ecosystems represented by interconnected food webs, where species (nodes) and their predator-prey relationships (edges) form complex networks. You've modeled both food webs as graphs g1 and g2, and each contains the relationships (1 eats 2, 2 eats 3) within the animal hierarchy.

To understand if these two ecosystems are functionally identical in terms of their food chain dynamics, you are considering whether the food web models, g1 and g2, are exactly the same, not just superficially in their predator-prey links, but in all underlying details - from the species represented by nodes to the specifics of the eating relationships symbolized by edges, and even other ecological attributes you've embedded within the models.

Now, to translate your task into more technical terms: can you utilize NetworkX's 'graphs_equal' function to confirm if the models g1 and g2 are completely identical as Python objects, where every aspect of nodes, edges, and additional information attached to the graphs is the same?
### Response:
import networkx as nx

# Create two graphs
g1 = nx.Graph()
g1.add_edges_from([(1, 2), (2, 3)])

# Create a second graph with the same edges
g2 = nx.Graph()
g2.add_edges_from([(1, 2), (2, 3)])

# Check if the two graphs are equal
equal = nx.graphs_equal(g1, g2)

print('The graphs are equal:', equal)
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