Update app.py

app.py

@@ -6,15 +6,11 @@ import re
 # Download required NLTK resources
 try:
     nltk.data.find('sentiment/vader_lexicon.zip')
-except nltk.downloader.DownloadError:
-    nltk.download('vader_lexicon')
 except LookupError:
     nltk.download('vader_lexicon')
 
 try:
     nltk.data.find('tokenizers/punkt/english.pickle')
-except nltk.downloader.DownloadError:
-    nltk.download('punkt')
 except LookupError:
     nltk.download('punkt')
 
@@ -62,10 +58,10 @@ def calculate_scores(work_completion, delay_reports, incident_logs):
         communication_score -= delay_reports.lower().count(keyword) * 10
 
     # Basic Sentiment Analysis (Optional - Requires NLTK Download)
-    # analyzer = SentimentIntensityAnalyzer()
-    # vs = analyzer.polarity_scores(work_completion + " " + delay_reports + " " + incident_logs)
-    # sentiment_score = vs['compound']
-    # communication_score += sentiment_score * 10  # Adjust weight as needed
+    analyzer = SentimentIntensityAnalyzer()
+    vs = analyzer.polarity_scores(work_completion + " " + delay_reports + " " + incident_logs)
+    sentiment_score = vs['compound']
+    communication_score += sentiment_score * 10  # Adjust weight as needed
 
     # Ensure scores are within 0-100 range
     quality_score = max(0, min(quality_score, 100))