simplify documents_to_batch

integrations/qdrant/src/haystack_integrations/document_stores/qdrant/converters.py

@@ -27,17 +27,16 @@ def documents_to_batch(
         for document in documents:
             payload = document.to_dict(flatten=False)
             vector = {}
-            if embedding_field in payload and payload[embedding_field] is not None:
-                dense_vector = payload.pop(embedding_field) or []
+
+            dense_vector = payload.pop(embedding_field, None)
+            if dense_vector is not None:
                 vector[DENSE_VECTORS_NAME] = dense_vector
-            if (
-                sparse_embedding_field in payload
-                and payload[sparse_embedding_field] is not None
-                and payload[sparse_embedding_field] != ""
-            ):
-                sparse_vector = payload.pop(sparse_embedding_field, {"indices": [], "values": []})
+
+            sparse_vector = payload.pop(sparse_embedding_field, None)
+            if sparse_vector is not None:
                 sparse_vector_instance = rest.SparseVector(**sparse_vector)
                 vector[SPARSE_VECTORS_NAME] = sparse_vector_instance
+
             _id = self.convert_id(payload.get("id"))
 
             point = rest.PointStruct(