Updated app.py

app.py

@@ -1,26 +1,28 @@
 import streamlit as st
-import time
 import pandas as pd
-import numpy as np
-
-
-pip install -U sentence-transformers
-
+import altair as alt
 from sentence_transformers import SentenceTransformer, util
-
+import numpy as np
+from urllib.error import URLError
 
 # Load document embeddings
-doc_emb = np.loadtxt("abstract-embed.txt", dtype=float)
-#doc_emb
-
-# Load data
-df = pd.read_csv("sessions.csv", usecols=['Unique ID', 'Name', 'Description', 'Activity Code', 'Start Time', 'End Time', 'Location Name'])
-#df.head()
 
+# set up title and sidebar
 st.title(" Your Top 3 Important Sessions")
 st.markdown("This application is a dashboard for displaying your top 3 Sessions at the summit")
 
 doc_emb = np.loadtxt("abstract-embed.txt", dtype=float)
+
+
+    # Load data
+df = pd.read_csv("sessions.csv", usecols=['Unique ID', 'Name', 'Description', 'Activity Code', 'Start Time', 'End Time', 'Location Name'])
+
+        # front end elements of the web page
+html_temp = """
+<div style ="background-color:lightblue;padding:13px">
+<h1 style ="color:white;text-align:center;">Sentence Similarity App Nashville Analytic Summit</h1>
+</div>
+        """
 def main():
         # display the front end aspect
     st.markdown(html_temp, unsafe_allow_html = True)
@@ -66,4 +68,8 @@ def main():
             st.write("Abstract: %s" %doc)
             st.write("Location: %s" %location)
             st.write(f"From {start_time} to {end_time}")
-            st.write('\n')
+            st.write('\n')
+
+
+if __name__ == "__main__":
+    main()