<｜begin▁of▁sentence｜>### Instruction:
As a data analyst for an online health and wellness platform, you've been tasked with assessing the effectiveness of two different nutrition coaching programs offered on the platform. To do this, you have access to the social network data of users who have interacted with the two programs. The user interactions are stored in a GML file named "nutrition_social_network.gml". Using this data, you need to apply the Louvain and Leiden community detection algorithms provided by the NetworkX library to analyze how users are grouped based on their interactions with the coaching programs. Additionally, you're required to compute the Omega Index to evaluate the similarity between the resulting community structures identified by the two algorithms.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Load the Les Miserables graph
G = nx.read_gml('lesmis.gml')

# Detect communities using the Louvain method
louvain_communities = algorithms.louvain(G)

# Detect communities using the Leiden method
leiden_communities = algorithms.leiden(G)

# Evaluate the similarity of the two community structures using Omega Index
omega_index = evaluation.omega(louvain_communities, leiden_communities)

# Print the Omega Index
print(omega_index.score)
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