<｜begin▁of▁sentence｜>### Instruction:
Given a graph where the edge set is [(0, 1), (1, 2), (2, 3), (3, 0), (4, 5), (5, 6), (6, 4)], use the VertexClustering.giant method in igraph to identify and output information about the largest cluster found after applying a community detection algorithm. For comparison, how would you find the largest connected component in the same graph using NetworkX?
### Response:
from igraph import Graph
from igraph.clustering import VertexClustering

# Create a graph
edge_list = [(0, 1), (1, 2), (2, 3), (3, 0), (4, 5), (5, 6), (6, 4)]
g = Graph(edges=edge_list)

# Run a community detection algorithm
# For demonstration, we use the community_multilevel algorithm but any community detection
# algorithm that returns a VertexClustering can be used
communities = g.community_multilevel()

# Get the giant cluster
largest_cluster = communities.giant()

# Print the summary of the largest cluster
print(largest_cluster.summary())
<|EOT|>
