<｜begin▁of▁sentence｜>### Instruction:
As a game developer, you are working on a complex in-game neural network for a sci-fi strategy game. You have a GML file named `celegansneural.gml`, which contains the neural network graph of the in-game creatures. Your task is to implement community detection using the Louvain and Leiden algorithms available in the networkx library. After detecting the communities, you need to compute the Omega Index to evaluate the similarity of the partitions obtained from both algorithms.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Read the neural network graph of the C. elegans
G = nx.read_gml('celegansneural.gml')

# Apply two different community detection algorithms to the same graph
louvain_communities = algorithms.louvain(G)
leiden_communities = algorithms.leiden(G)

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

print(omega_index)
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