<｜begin▁of▁sentence｜>### Instruction:
Imagine you're commissioned to create a triptych, a set of three paintings that together depict a serene landscape, each panel representing a different section of the scenery but connected in harmony to the others. Now, picture the connection between these panels as a metaphor for an undirected graph, where the edges [(1, 2), (2, 3), (3, 4)] represent the seamless links between adjoining panels. 

Your challenge is to employ the artistry of the Minimum Fill-in heuristic, a technique akin to optimizing the layout and connections between your canvas panels. Through this, you would determine the 'treewidth' of your art composition, which, in essence, is akin to measuring the complexity of the inter-panel linkage, ensuring they are presented with as much elegance and simplicity as possible, without losing the integrity of the landscape’s flow.

Could you, with the finesse of your brush, show us the treewidth and corresponding tree decomposition that NetworkX would reveal? This would be akin to unveiling the blueprint of your masterpiece's underlying structure, the invisible yet crucial network that holds the triptych in conceptual unity.
### Response:
import networkx as nx

# Create an undirected graph
G = nx.Graph()

# Add edges (representing a simple path for the sake of example)
G.add_edges_from([(1, 2), (2, 3), (3, 4)])

# Compute the treewidth using the Minimum Fill-in heuristic
treewidth, tree = nx.treewidth_min_fill_in(G)

print('Treewidth:', treewidth)
print('Tree Decomposition:', tree.edges())
<|EOT|>
