import gradio as gr
import pandas as pd
import gensim.downloader as api
wv = api.load('glove-wiki-gigaword-50')

    
def get_associations(term,top_words=10):
    return pd.DataFrame(wv.most_similar(positive=[term], topn=10),columns=['word','similarity'])


iface = gr.Interface(fn=get_associations, inputs="text", outputs=gr.Dataframe(headers=['word','similarity']),examples=["cat"]).launch(share=False)