Update app.py

app.py

@@ -176,9 +176,7 @@ print("Initializing....")
 article_dict, clusters = initialize(LIMIT, USE_CACHE)  
 # We now have clusters and cluster data.  Redundancy.
 # We call a display function and get the user input.  
-# For this its still streamlit.
 
-st.success(st.title("Welcome to TopicDig!"))
 st.success(f"You select the topics, we summarize the relevant news and show you a digest, plus some info to help contextualize what the machine did.  \nEnjoy, and remember, this software is experimental, and honestly may produce untrue summaries.  For more information on truthfulness and automatic summarization with transformers see TK.")
 
 st.subheader(f"How it works:")
@@ -219,14 +217,13 @@ with st.form(key='columns_in_form'):
                     for j in clusters[i]:
                         if j not in chosen:
                             chosen.append(j) # j is a stub.
-            st.warning("selecting a value of 800 may result in tokenized chunks longer than the model sequence length.")
-            
+        
             # Digestor uses 'chosen' to create digest.  
             # 'user_choicese' is passed for reference.  
             digestor = Digestor(timer=Timer(), cache = USE_CACHE, stubs=chosen, user_choices=selections, token_limit=1024, word_limit=chunk_size)
             # happens internally but may be used differently so it isn't automatic upon digestor creation.
             # Easily turn caching off for testing.
-            st.write("What you'll see:")
+            st.subheader("What you'll see:")
             st.write("First you'll see a list of links appear below.  These are the links to the original articles being summarized for your digest, so you can get the full story if you're interested, or check the summary against the source.")
             st.write("In a few moments, your machine-generated digest will appear below the links, and below that you'll see an approximate word count of your digest and the time in seconds that the whole process took!")
             st.write("You'll also see a graph showing, for each article and summary, the original and summarized lengths.")