cosine_similarity returns matrix instead of single value
Based on the documentation cosine_similarity(X, Y=None, dense_output=True) returns an array with shape (n_samples_X, n_samples_Y). Your mistake is that you are passing [vec1, vec2] as the first input to the method. Also your vectors should be numpy arrays:

from sklearn.metrics.pairwise import cosine_similarity
import numpy as np
vec1 = np.array([[1,1,0,1,1]])
vec2 = np.array([[0,1,0,1,1]])
#print(cosine_similarity([vec1, vec2]))
print(cosine_similarity(vec1, vec2))



  X : ndarray or sparse array, shape: (n_samples_X, n_features)
      Input data.


So you have to specify the dimension. 

np.array([1, 2]).shape


has funny shape:


  (2, )