Update app.py

app.py

@@ -6,9 +6,10 @@ from bs4 import BeautifulSoup
 import pandas as pd
 import altair as alt
 from collections import OrderedDict
-import nltk
 from nltk.tokenize import sent_tokenize
 
+# Load the punkt tokenizer from nltk
+import nltk
 nltk.download('punkt')
 
 # Load model and tokenizer
@@ -86,6 +87,20 @@ st.title("Sentiment Classification from URL")
 
 url = st.text_input("Enter URL:")
 
+# Additional information
+st.markdown("""
+Multi-label sentiment classification model developed by [Dejan Marketing](https://dejanmarketing.com/).
+
+The model is designed to be deployed in an automated pipeline capable of classifying text sentiment for thousands (or even millions) of text chunks or as a part of a scraping pipeline.
+
+This is a demo model which may occassionally misclasify some texts. In a typical commercial project, a larger model is deployed for the task, and in special cases, a domain-specific model is developed for the client.
+
+# Engage Our Team
+Interested in using this in an automated pipeline for bulk query processing?
+
+Please [book an appointment](https://dejanmarketing.com/conference/) to discuss your needs.
+""")
+
 if url:
     text = get_text_from_url(url)
     if text: