<｜begin▁of▁sentence｜>### Instruction:
Imagine we're examining the pathways of recovery that a patient might take on their journey toward sobriety, symbolically represented within a graph model. Two potential paths from the onset of treatment (node 0) to a stable state of recovery (node 2) have been identified. The first path progresses from initial treatment, to an early recovery phase, and then to sustained recovery (traced as nodes 0 -> 1 -> 2). The second path diverges, going through an alternative coping strategy, described as nodes 0 -> 10 -> 2.

Could you, as part of a comprehensive therapeutic strategy, determine all the most direct, uncomplicated routes that our patient could take between the beginning of their treatment journey and a successful recovery outcome, utilizing the graph framework provided by NetworkX? This approach will allow us to better understand and facilitate the most effective treatment paths for those in our care.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add paths
nx.add_path(G, [0, 1, 2])
nx.add_path(G, [0, 10, 2])

# Compute all shortest paths
paths = list(nx.all_shortest_paths(G, source=0, target=2))

print(paths)
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