<｜begin▁of▁sentence｜>### Instruction:
As an engineer, I can help you with that. Given the Astrophysics collaborations Graph, represented as a network, you want to use the Louvain community detection algorithm provided by the cdlib library to identify distinct research communities within this network. Once the communities are detected, you want to calculate the average distance within these communities. This task involves using computational tools to analyze and understand the collaboration patterns within the field of Astrophysics, which could potentially lead to insights and discoveries in this domain.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Create a graph
G = nx.read_gml('astro-ph.gml')

# Apply the Louvain community detection algorithm
communities = algorithms.louvain(G)

# Compute the average distance within the detected communities
avg_dist = evaluation.avg_distance(G, communities)

print(avg_dist)
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