Update app.py

app.py

@@ -1,11 +1,15 @@
 import streamlit as st
 import networkx as nx
 import matplotlib.pyplot as plt
+import nltk
 from nltk import sent_tokenize
 from sklearn.feature_extraction.text import TfidfVectorizer
 from sklearn.cluster import KMeans
 import numpy as np
 
+# Download the punkt tokenizer
+nltk.download('punkt')
+
 # Helper function to split text into topics using KMeans clustering
 def split_text_into_topics(text, n_topics):
     sentences = sent_tokenize(text)
@@ -89,4 +93,3 @@ if uploaded_file is not None:
     nx.draw(graph, pos, with_labels=True, node_size=3000, node_color="lightblue", font_size=10, font_weight="bold", labels={node: node for node in graph.nodes()})
     plt.title("Tree Structure of Text Topics")
     st.pyplot(plt)
-