<｜begin▁of▁sentence｜>### Instruction:
As a tour operator who specializes in organizing and planning guided tours and excursions, you have been tasked with analyzing the collaboration network among astrophysics researchers to create tailored travel experiences for scholars or enthusiasts. Using the networkx Python library, you can read the Astrophysics collaborations Graph from a gml file named astro-ph.gml. You will then utilize the Louvain method in the cdlib library to detect communities within the astrophysics collaborations network. Additionally, you are interested in calculating the internal edge density of the detected communities to gain insights into the cohesive relationships among researchers.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Load a graph of astrophysics collaborations
G = nx.read_gml('astro-ph.gml')

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

# Compute the internal edge density
internal_density = evaluation.internal_edge_density(G, communities, summary=True)

# Print the internal edge density
print(internal_density.score)
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