bug fixes

app.py

@@ -50,7 +50,7 @@ def predict(text: str = sample_text, top_k: int=3):
     # query = prepare_query(tokenizer, text)
     index_data, faiss_index = index
     # takes only the [CLS] embedding (for now)
-    query = model(text)[0][0].numpy().reshape(1, -1)  
+    query = model(text, return_tensors='pt')[0][0].numpy().reshape(1, -1)  
     
     scores, indices = faiss_index.search(query, top_k)
     scores, indices = scores.tolist(), indices.tolist()