Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from gensim.models import KeyedVectors
 
+
 def isNoneWords(word):
     if word is None or len(word)==0 or word not in model.key_to_index:
         return True
@@ -11,10 +12,16 @@ def top_similarity_route(word):
     if isNoneWords(word):
         return "word is null or not in model!"
     else:
-        return {'word':word,'top_similar_words':model.similar_by_word(word, topn=20, restrict_vocab=None)}
+        top_similar_words = model.similar_by_word(word, topn=20, restrict_vocab=None)
+        sim_res = ""
+        for item in top_similar_words:
+            sim_res += f'{item[0]}: {round(item[1], 4)}\n'
+        return sim_res
 
 
 if __name__ == '__main__':
     model = KeyedVectors.load_word2vec_format('tencent-ailab-embedding-zh-d100-v0.2.0-s.txt', binary=False)
-    iface = gr.Interface(fn=top_similarity_route, inputs="text", outputs="text")
-    iface.launch()
+    
+    title = 'Calculate word similarity based on Tencent AI Lab Embedding'
+    iface = gr.Interface(fn=top_similarity_route, inputs="Word", outputs="Similar words", title=title)
+    iface.launch(share=True)