Update app.py

app.py

@@ -295,12 +295,7 @@ def process_and_summarize(df, bert_tokenizer, bert_model, emotion_classifier, to
             topics, probs = topic_model.fit_transform(texts, embeddings)
             
             
-            valid_topics = [t for t in topics if t != -1]
-            if not valid_topics:
-                st.warning(f"No valid topics generated for {country}")
-                continue
-                
-            topic_counts = Counter(valid_topics)
+            topic_counts = Counter(topics)
             
             top_topics = format_topics(topic_model, topic_counts.most_common(top_n))
             top_emotions = format_emotions(Counter(all_emotions).most_common(top_n))