fixed

app.py

@@ -13,9 +13,12 @@ from nltk.tokenize import word_tokenize
 from nltk.corpus import stopwords
 from nltk.stem import WordNetLemmatizer
 
-import nltk
+# Ensure NLTK resources are available by dynamically downloading if necessary
 nltk.data.path.append('/Users/kritsadakruapat/Desktop/Political-Fake-News-Detector-NLP/Fake_News_Detection/nltk_data')
 
+# Download the stopwords if not already present
+nltk.download('stopwords', download_dir='/Users/kritsadakruapat/Desktop/Political-Fake-News-Detector-NLP/Fake_News_Detection/nltk_data')
+
 # Preprocessing helper functions
 
 # 1. Remove punctuation
@@ -130,7 +133,6 @@ def predict_with_threshold(text):
         st.write(f"⚠️ Potential Fake News Probability: {fake_prob:.2f}%")
         st.write("The news article is likely Real.")
 
-
 # Analyze a news article from the given URL
 if url:
     with st.spinner("Scraping the text..."):
@@ -148,4 +150,3 @@ if url:
 
             # Preprocess and predict
             predict_with_threshold(scraped_text)
-