code: def main():
      model = models.KeyedVectors.load_word2vec_format("vec.txt")
      embeddings = list()
  
      # Using canonical smiles for glycine, as in original research paper
      mol = Chem.MolFromSmiles("C(C(=O)O)N")
      try:
          info = {}
          rdMolDescriptors.GetMorganFingerprint(mol, 0, bitInfo=info)
          keys = info.keys()
          keys_list = list(keys)
          totalvec = np.zeros(200)
          for k in keys_list:
              wordvec = model.wv[str(k)]
              totalvec = np.add(totalvec, wordvec)
          embeddings.append(totalvec)
      except Exception as e:
          print(e)
          pass
  
      print(embeddings[0])
  
imports: import gensim
  from gensim import models
  from rdkit import Chem
  from rdkit.Chem import rdMolDescriptors
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types