<｜begin▁of▁sentence｜>### Instruction:
As a financial planner, you're tasked with analyzing investment portfolios to maximize returns and mitigate risks for your clients. Suppose you've obtained data on a network representing various financial assets and their interconnectedness, stored in a file named "network.gml." To enhance your investment strategies, you're interested in identifying clusters within this network that may indicate potential investment opportunities or correlations between assets.

To achieve this, you intend to utilize the `community_multilevel` function from the NetworkX library, a powerful tool commonly employed in network analysis. By applying this function, you aim to uncover the community structure within the network, revealing clusters of assets that exhibit similar behavior or are closely related in terms of their performance.

Following this analysis, you plan to utilize the `Cover.size` function to quantify the size of the first cluster identified by the community detection algorithm. This information will assist you in understanding the prominence and scale of this particular group of assets, enabling you to make more informed decisions regarding portfolio allocation and risk management strategies for your clients.
### Response:
from igraph import Graph
import igraph as ig

g = ig.read('network.gml')
cover = g.community_multilevel(return_levels=True)[-1]

# Get the size of the first cluster
cluster_size = cover.size(0)

print('Size of the first cluster:', cluster_size)
<|EOT|>
