<｜begin▁of▁sentence｜>### Instruction:
As a vegetarian chef who skillfully combines ingredients to create a delightful symphony of flavors on the plate, imagine you have a recipe network where ingredients that pair well with each other are connected by an invisible thread of culinary compatibility. Here, you have a specific set of ingredient pairings: zucchini with bell peppers, bell peppers with quinoa, artichokes with quinoa, artichokes with tempeh, and quinoa with tempeh. 

In the same way that you might seek to uncover the various meal sequences that can stem from these pairings, you're looking to unravel the different chains of connections that exist within this network of ingredients. You're considering utilizing the tool NetworkX to dissect this culinary graph and reveal all potential sequential combinations, ensuring that no single ingredient pairing is overlooked. Could you elucidate on how you might approach such a task using NetworkX, while keeping the essence of your question rooted in the art of gastronomy?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 4), (3, 4), (3, 5), (4, 5)])

# Perform the chain decomposition
chains = list(nx.chain_decomposition(G))

print('Chains:', chains)
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