@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PACKAGE VERSION\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-08-10 11:02+0300\n"
+"POT-Creation-Date: 2026-08-13 17:52+0300\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language-Team: LANGUAGE <LL@li.org>\n"
@@ -766,7 +766,8 @@ msgstr "Промпт слишком длинный"
 msgid ""
 "Service is currently unavailable due to high demand. Please try again later"
 msgstr ""
-"Сервис временно недоступен из-за высокой нагрузки. Пожалуйста, попробуйте позже"
+"Сервис временно недоступен из-за высокой нагрузки. Пожалуйста, попробуйте "
+"позже"
 
 #: ml_model/exceptions.py:172
 msgid "Service is temporarily unavailable. Please try again later"
@@ -1097,17 +1098,21 @@ msgstr "Инструкции Моделей"
 msgid "no model by this id"
 msgstr "Не найдено моделей по этому ID"
 
-#: ml_model/services/FileService.py:110
+#: ml_model/services/FileService.py:123
 #: tools/public_api/views/providers/openai_compatible.py:208
 msgid "Voice not found."
 msgstr "Голос не найден."
 
+#: ml_model/services/FileService.py:227
+msgid "Image is too wide or tall"
+msgstr "Изображение слишком широкое или высокое"
+
 #: ml_model/services/chatgpt.py:245
 msgid "Image is ready"
 msgstr "Изображение готово"
 
 #: ml_model/services/chatgpt.py:361 ml_model/services/claude.py:277
-#: ml_model/services/grok.py:191
+#: ml_model/services/grok.py:192
 msgid "File analysis"
 msgstr "Анализ файлов"
 
@@ -221,6 +221,13 @@ class ImageFileValidator(MediaFileValidator):
             if w * h > max_pixels:
                 raise ImageTooLargeError(max_pixels)
 
+    @staticmethod
+    def validate_aspect_ratio(w: int | None, h: int | None, *, min_ratio: float, max_ratio: float) -> None:
+        if not (w and h):
+            raise CorruptedFileError
+        if not (min_ratio <= w / h <= max_ratio):
+            raise InvalidParameterError(_('Image is too wide or tall'))
+
 
 class VideoFileValidator(MediaFileValidator):
     @staticmethod
@@ -1,17 +1,15 @@
-import base64
 import time
 from datetime import timedelta
 from decimal import Decimal
 from io import BytesIO
 from typing import Any
 
-import filetype
 import requests
 from django.core.files import File
 
-
 from messages.models import Message
-from ml_model.exceptions import RequestBlocked, GenerationException, FileNotProvided
+from ml_model.exceptions import FileNotProvided
+from ml_model.services.FileService import ImageFileProcessor, ImageFileValidator
 from ml_model.services.base import SimpleService
 from ml_model.tasks import replicate_run
 
@@ -47,17 +45,24 @@ class Kling(SimpleService):
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         mode = input_message.info.pop('mode', 'standard')
         duration = input_message.info.get('duration', 5)
-        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (cost := self.TOKENS_COST[mode] * duration):
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (
+            cost := self.TOKENS_COST[mode] * duration
+        ):
             raise InsufficientBalance(balance, cost)
         if not input_message.file:
             raise FileNotProvided('Image')
-        callback_data = dict({'prompt': self.translate_prompt(input_message.content), 'mode': mode, **input_message.info})
-        kind = filetype.guess(input_message.file.read(20))
-        mime = kind.mime if kind else 'application/octet-stream'
-        input_message.file.seek(0)
-        image = f'data:{mime};base64,{base64.b64encode(input_message.file.read()).decode("utf-8")}'
+        callback_data = dict(
+            {'prompt': self.translate_prompt(input_message.content), 'mode': mode, **input_message.info}
+        )
+
+        image_processor = ImageFileProcessor(input_message.file)
+        kind = image_processor.get_kind(image_processor.get_bytes(20))
+        ImageFileValidator.validate_kind(kind, image_processor.EXTENSIONS)
+        width, height = image_processor.get_dimensions()
+        ImageFileValidator.validate_dimensions(width, height, max_pixels=36_000_000)
+        ImageFileValidator.validate_aspect_ratio(width, height, min_ratio=0.40, max_ratio=2.50)
         input_message.file.close()
-        callback_data.update({'start_image': image})
+        callback_data.update({'start_image': input_message.file.url})
         start_time = time.time()
         video = replicate_run('kwaivgi/kling-v2.1', callback_data)
         process_time = timedelta(seconds=(time.time() - start_time))