Update app.py

app.py

@@ -7,6 +7,8 @@ from sentence_transformers import SentenceTransformer
 from umap import UMAP
 from hdbscan import HDBSCAN
 from sklearn.feature_extraction.text import CountVectorizer
+import pandas as pd
+
 
 st.set_page_config(page_title='eRupt Topic Trendy (e-Commerce x Social Media)', page_icon=None, layout='centered', initial_sidebar_state='auto')
 
@@ -83,9 +85,12 @@ if similar_topics != []:
     #print("Similarity Score: {}".format(similarity[0]))
 
     answer_as_string = topic_model.get_topic(most_similar)
+    answer_as_string = answer_as_string[0]
     
     st.info("Extracted Topic")
-    st.text_area("Most Similar Topic List is Here",answer_as_string,key="topic_list")
+    #st.text_area("Most Similar Topic List is Here",answer_as_string,key="topic_list")
+    keywords = pd.DataFrame(answer_as_string , columns=["Topic", "Relevance"])
+    st.table(keywords)
     st.image('https://freepngimg.com/download/keyboard/6-2-keyboard-png-file.png',use_column_width=True)
     #st.markdown("<h6 style='text-align: center; color: #808080;'>Created By LiHE</a></h6>", unsafe_allow_html=True)