Update app.py

app.py

@@ -9,6 +9,8 @@ import numpy as np
 import streamlit as st
 import requests
 import nltk
+import string
+from collections import Counter
 from PIL import Image
 from poetpy import get_poetry
 from nltk.corpus import stopwords
@@ -347,13 +349,15 @@ caption_model = get_model()
 
 @st.cache_data
 def extract_important_term(caption):
-    # Remove stopwords
+    # Remove stopwords and punctuation
     stop_words = set(stopwords.words('english'))
     words = caption.lower().split()
-    filtered_words = [word for word in words if word not in stop_words]
-    filtered_words = [word for word in filtered_words if re.match(r'^[a-zA-Z]+$', word)]
-    # Find the longest word
-    important_term = filtered_words
+    words = [word.strip(string.punctuation) for word in words if word not in stop_words]
+
+    # Count word frequencies
+    word_freq = Counter(words)
+    important_term = max(word_freq, key=word_freq.get)
+
 
     return important_term