def GenerateNgrams(words, ngrams):
    nglist = []
    for ng in ngrams:
        for word in words:
            nglist.extend([word[n:n+ng] for n in range(len(word)-ng+1)])
    return ngli

maybe it should like following

def GenerateNgrams(words, ngrams):
    nglist = []
    for ng in ngrams:
        nglist.extend(''.join([words[n:n+ng]) for n in range(len(words)-ng+1)])
 

pip install -r requirements.txt
python -m spacy download en_core_web_sm # depend on which language you want to you: https://spacy.io/usage/models

morphology_han-readings.py passes "北京大学生物系主任办公室内部会议" and prints out

{'hanReadings': [['Bei3-jing1-Da4-xue2'], null, ['zhu3-ren4'], ['ban4-gong1-shi4'], ['nei4-bu4'], ['hui4-yi4']]}

The element of the list, null, should be ['Sheng1-wu4'], i.e., "Biology."