Update app.py

app.py

@@ -3,9 +3,19 @@ import pandas as pd
 import re
 import io
 from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
- 
+import nltk
+from nltk.tokenize import word_tokenize
+from nltk.corpus import stopwords
+from nltk.stem import WordNetLemmatizer
 
+# Download NLTK resources
+nltk.download('punkt')
+nltk.download('stopwords')
+nltk.download('wordnet')
 
+# Initialize lemmatizer and stopwords
+lemmatizer = WordNetLemmatizer()
+stop_words = set(stopwords.words('english'))
 
 # Load fine-tuned model and tokenizer
 model_name = "TAgroup5/news-classification-model"
@@ -68,4 +78,9 @@ context = st.text_area("Provide the news article or content for the Q&A:", heigh
 
 if question and context.strip():
     result = qa_pipeline(question=question, context=context)
-    st.write("Answer:", result['answer'])
+    
+    # Check if the result contains an answer
+    if 'answer' in result and result['answer']:
+        st.write("Answer:", result['answer'])
+    else:
+        st.write("No answer found in the provided content.")