Update app.py

app.py

@@ -56,7 +56,7 @@ def transform_query(query: str) -> str:
 
 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, convert_to_numpy=True)[0]
-    sparse_embeddings = list(sparse_model.embed([query], 1))[0]
+    sparse_embeddings = list(sparse_model.query_embed(query))[0]
     
     return client.query_points(
         collection_name=collection_name,
@@ -174,7 +174,8 @@ def load_models_and_documents():
             "text-sparse": models.SparseVectorParams(
                 index=models.SparseIndexParams(
                     on_disk=False
-                )
+                ),
+                modifier=models.Modifier.IDF
             )
         },
         2,
@@ -226,7 +227,10 @@ def load_models_and_documents():
                 outfile_metadatas.write(packed_metadatas)
             
             np.savez_compressed(dense_path, *dense_embeddings)
-            max_index = max(np.max(embedding.indices) for embedding in sparse_embeddings)
+            max_index = 0
+            for embedding in sparse_embeddings:
+                if embedding.indices.size > 0:
+                    max_index = max(max_index, np.max(embedding.indices))
         
             sparse_matrices = []
             for embedding in sparse_embeddings: