Update app.py

app.py

@@ -14,7 +14,11 @@ os.makedirs(NLTK_DATA_PATH, exist_ok=True)
 nltk.data.path.append(NLTK_DATA_PATH)
 
 # Ensure punkt is downloaded
-nltk.download('punkt', download_dir=NLTK_DATA_PATH)
+try:
+    nltk.data.find('tokenizers/punkt')
+except LookupError:
+    print("Downloading punkt tokenizer...")
+    nltk.download('punkt', download_dir=NLTK_DATA_PATH)
 
 # Streamlit App Configuration
 st.set_page_config(page_title="📊 Financial Report Sentiment Analyzer", layout="wide")
@@ -87,9 +91,13 @@ if uploaded_file:
 
     # ✅ Extract Sentences Matching Financial Keywords
     def extract_sentences(text, keywords):
-        sentences = sent_tokenize(text)
-        pattern = re.compile(r'\b(' + '|'.join(map(re.escape, keywords)) + r')\b', re.IGNORECASE)
-        return [s for s in sentences if pattern.search(s)]
+        try:
+            sentences = sent_tokenize(text)
+            pattern = re.compile(r'\b(' + '|'.join(map(re.escape, keywords)) + r')\b', re.IGNORECASE)
+            return [s for s in sentences if pattern.search(s)]
+        except Exception as e:
+            st.error(f"❌ Error in sentence tokenization: {e}")
+            return []
 
     # ✅ Analyze Sentiment for a Specific Financial Category
     def analyze_category(text, category_name, keywords):