Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py (Streamlit-only version for Hugging Face Spaces)
+# app.py (Streamlit-only version for Hugging Face Spaces with error handling)
 
 import os
 import tempfile
@@ -28,14 +28,13 @@ def classify_topic(text: str, topics: List[str]) -> str:
     if not topics:
         return "Unknown (no topics provided)"
 
-    classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+    classifier = pipeline("zero-shot-classification", model="valhalla/distilbart-mnli-12-3")
     result = classifier(text[:1000], candidate_labels=topics)
 
     if 'labels' in result and len(result['labels']) > 0:
         return result['labels'][0]
     return "Unknown (classification failed)"
 
-
 def generate_audio(text: str, output_path: str):
     tts = gTTS(text)
     tts.save(output_path)
@@ -61,30 +60,29 @@ if submitted and uploaded_file and topic_input:
         try:
             temp_dir = tempfile.mkdtemp()
             file_path = os.path.join(temp_dir, uploaded_file.name)
-    
+
             with open(file_path, "wb") as f:
                 f.write(uploaded_file.read())
-    
+
             text = extract_text_from_pdf(file_path)
-            topic_list = [t.strip() for t in topic_input.split(",") if t.strip()]
+
             if not text.strip():
                 st.error("❌ No text could be extracted from the PDF. Try another file.")
             else:
+                topic_list = [t.strip() for t in topic_input.split(",") if t.strip()]
                 classified_topic = classify_topic(text, topic_list)
                 summary = summarize_text(text)
 
-    
-            st.markdown(f"### 🧠 Classified Topic: `{classified_topic}`")
-            st.markdown("### ✍️ Summary:")
-            st.write(summary)
-    
-            audio_path = os.path.join(temp_dir, "summary.mp3")
-            generate_audio(summary, audio_path)
-    
-            st.markdown("### 🔊 Audio Summary")
-            st.audio(audio_path)
-            st.success("Done! Audio summary is ready.")
-    
+                st.markdown(f"### 🧠 Classified Topic: `{classified_topic}`")
+                st.markdown("### ✍️ Summary:")
+                st.write(summary)
+
+                audio_path = os.path.join(temp_dir, "summary.mp3")
+                generate_audio(summary, audio_path)
+
+                st.markdown("### 🔊 Audio Summary")
+                st.audio(audio_path)
+                st.success("Done! Audio summary is ready.")
+
         except Exception as e:
             st.error(f"❌ Error: {str(e)}")
-