<｜begin▁of▁sentence｜>### Instruction:
Given a directed graph with nodes 'a' having a supply of 5 units (represented with a negative demand), and 'd' demanding 5 units (represented with a positive demand), with directed edges ('a', 'b'), ('a', 'c'), ('b', 'd'), and ('c', 'd') with given capacities and costs; how can we find the flow that meets all demands with minimum cost using the NetworkX min_cost_flow function?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add nodes with demands
G.add_node('a', demand=-5)
G.add_node('d', demand=5)

# Add edges with capacities and weights
G.add_edge('a', 'b', weight=3, capacity=4)
G.add_edge('a', 'c', weight=6, capacity=10)
G.add_edge('b', 'd', weight=1, capacity=9)
G.add_edge('c', 'd', weight=2, capacity=5)

# Compute the minimum cost flow
flowDict = nx.min_cost_flow(G)

print(flowDict)
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