<｜begin▁of▁sentence｜>### Instruction:
As a special effects artist working on a film production about social networks, I need to use cutting-edge techniques to visualize the connections and interactions between characters in the story. In order to enhance the storytelling, I've been tasked with using the Louvain method in an advanced software tool called cdlib to detect communities within the network of characters in the film. Additionally, I must compute the average embeddedness of nodes within each community to understand the strength of connections between characters. Once I have this data, I will use it to create compelling visual effects that illustrate the intricate social dynamics within the storyline.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

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

# Perform community detection using the Louvain method
communities = algorithms.louvain(G)

# Compute the average embeddedness of nodes within the community
avg_embeddedness = evaluation.avg_embeddedness(G, communities)

print('Average embeddedness:', avg_embeddedness.score)
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