Update app.py

app.py

@@ -37,7 +37,8 @@ if pdf_file is not None:
         candidate_labels =["Romance", "Mystery", "Thriller", "Science Fiction", "Fantasy", "Horror", "Historical Fiction", "Crime", "Western", "Dystopian", "Biography", "Autobiography", "Memoir", "History", "Self-Help", "Travel", "Essay", "Journalism", "Sonnet", "Haiku", "Free Verse", "Narrative Poetry", "Lyric Poetry", "Tragedy", "Comedy", "Melodrama", "Farce", "Graphic Novel", "Epistolary", "Magical Realism", "Satire", "Young Adult Fiction"]
         # Perform zero-shot classification
         result = classifier(text[:1000], candidate_labels, multi_label=True) #[:1000]), candidate_labels, multi_label=True)
-        genres = sorted(zip(result["labels"], result["scores"]), key=lambda x: x[1], reverse=Truest.subheader("Top 20 Detected Genres:"))
+        genres = sorted(zip(result["labels"], result["scores"]), key=lambda x: x[1], reverse=True) 
+        st.subheader("Top 20 Detected Genres:")
         top_genres = genres[:20]
         for genre, score in top_genres:
             st.write(f"**{genre.capitalize()}**: {score:.2f}")