Update app.py

app.py

@@ -53,7 +53,7 @@ def transform_query(query: str) -> str:
     return f'Represent this sentence for searching relevant passages: {query}'
 
 def query_hybrid_search(query: str, client: QdrantClient, collection_name: str, dense_model: OptimumEncoder, sparse_model: SparseTextEmbedding):
-    dense_embeddings = dense_model([transform_query(query)], 1)[0]
+    dense_embeddings = dense_model([transform_query(query)], 1, convert_to_numpy=True)[0]
     sparse_embeddings = list(sparse_model.query_embed(query))[0]
     
     return client.query_points(
@@ -281,7 +281,7 @@ def chunk_documents(texts: List[str], metadatas: List[dict], dense_model: Optimu
     documents_and_metadatas = [(chunk.content, chunk.metadata) for sub_chunk in chunks for chunk in sub_chunk]
     documents, metadatas_docs = [list(t) for t in zip(*documents_and_metadatas)]
     
-    dense_embeddings = dense_model(documents, 32)
+    dense_embeddings = dense_model(documents, 32, convert_to_numpy=True)
     sparse_embeddings = list(sparse_model.embed(documents, 32, 0))
     
     return documents, metadatas_docs, dense_embeddings, sparse_embeddings