Update app.py

app.py

@@ -45,8 +45,9 @@ except Exception as e:
 paper_embeddings = model.encode([paper["content"] for paper in papers], convert_to_tensor=True) if model else None
 
 def semantic_search(query):
-    if not model or not summarizer or not paper_embeddings:
-        return {"title": "Error", "abstract": "Error", "summary": "Model loading failed. Check logs.", "link": ""}
+    # Check if any component is missing
+    if model is None or summarizer is None or paper_embeddings is None:
+        return {"title": "Error", "abstract": "Error", "summary": "Model or embeddings failed to load. Check logs.", "link": ""}
     
     try:
         query_embedding = model.encode([query], convert_to_tensor=True)  # Ensure list input