User question:
user: I'm working on a machine learning model, comparing the characteristics of two objects. The feature vectors for these objects are [0.5, 0.7, 0.2, 0.9, 0.1] for the first object and [0.4, 0.6, 0.3, 0.8, 0.2] for the second. To understand how similar these objects are, I need to calculate the cosine similarity between these two vectors. Can you help me with that?

Available functions:
name: calculate_cosine_similarity
description: Calculates the cosine similarity of two vectors.
parameters: type: dict
properties: vectorA: type: array
items: type: float
description: The first vector.
vectorB: type: array
items: type: float
description: The second vector.
required: vectorA
vectorB
name: get_stock_price_by_stock_name
description: Finds the price of a stock by its stock name.
parameters: type: dict
properties: stock_name: type: string
description: The stock name of the product, in the format of the stock symbol.
required: stock_name

Ground-truth function call(s):
calculate_cosine_similarity(vectorA=[0.5, 0.7, 0.2, 0.9, 0.1], vectorB=[0.4, 0.6, 0.3, 0.8, 0.2])