diff --git a/main.py b/main.py
index d4734ce..e0ec629 100644
--- a/main.py
+++ b/main.py
@@ -22,7 +22,6 @@ def analyse_file(uid, image_path):
         raise Exception(f'Изображение {image_path} не существует')
     model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)
     model.names = neuralNetwork.rename_entity(model.names)
-    list_sqwrl = ontologyWorking.get_list_sqwrl(uid, url)
 
     results = model(imageWorking.get_image_as_array(image_path))
     object_properties = list()
@@ -46,15 +45,16 @@ def analyse_file(uid, image_path):
         'QueryGetCheck': '',
         'QueryGetEmpty': ''
     }
-    for sqwrl in list_sqwrl['response']:
-        response = requests.post(url + f'{uid}/query/{sqwrl["name"]}', json=data).json()
-        if response['error']:
-            raise Exception(response['error'])
-        result[sqwrl['name']] = [resultSQWRL['name']['value'] for resultSQWRL in response['response']['rows']]
-        print(f'Запрос {sqwrl["name"]} выполнен')
+    params = '&'.join([f'names={query}' for query in result.keys()])
+    response = requests.post(url + f'{uid}/query/multi?{params}', json=data).json()
+    if response['error']:
+        raise Exception(response['error'])
+    for query in response['response']:
+        result[query] = [resultSQWRL['name']['value'] for resultSQWRL in response['response'][query]['rows']]
+    print(f'Запрос выполнен')
 
     print()
-    print('Результаты')
+    print('Результат:')
     if result['QueryGetNotEmpty']:
         print('Аудитория занята')
     elif result['QueryGetCheck']:
diff --git a/ontologyWorking.py b/ontologyWorking.py
index fed3584..01476c0 100644
--- a/ontologyWorking.py
+++ b/ontologyWorking.py
@@ -9,10 +9,6 @@ def is_ontology_exists(uid, url):
     return True
 
 
-def get_list_sqwrl(uid, url):
-    return requests.get(url + f'{uid}/query/', verify=False).json()
-
-
 def get_entity_square(results_ndarray_i):
     square = float((results_ndarray_i[2] - results_ndarray_i[0]) *
                    (results_ndarray_i[3] - results_ndarray_i[1]))