<｜begin▁of▁sentence｜>### Instruction:
As an Inventory Planner, you're tasked with ensuring efficient stock availability while minimizing costs. Suppose you've gathered sales data from various sources, including online platforms, for analysis. Now, you're considering leveraging network analysis to optimize inventory management further.

Your IT team has provided you with a file named "as-22july06.gml," containing the network structure of online interactions, representing potential customer communities. To make informed decisions, you aim to apply the Leiden algorithm to detect these communities. However, visualizing these communities is crucial for better understanding and strategizing.

Here comes the challenge: How can you effectively visualize the communities detected by the Leiden algorithm using the plot_network_clusters function from the cdlib library?
### Response:
from cdlib import algorithms, viz
import networkx as nx

# Create an Internet Graph from an external gml file
G = nx.read_gml('as-22july06.gml')

# Perform community detection using the Leiden algorithm
communities = algorithms.leiden(G)

# Compute the positions using the spring layout algorithm
pos = nx.spring_layout(G)

# Plot the graph with node color coding for the detected communities
viz.plot_network_clusters(G, communities, pos, figsize=(8, 8), node_size=200)
<|EOT|>
