@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: PACKAGE VERSION\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2025-12-25 13:42+0300\n"
+"POT-Creation-Date: 2025-12-25 15:54+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"
@@ -97,7 +97,7 @@ msgid "Domain not found"
 msgstr "Домен не найден"
 
 #: authentication/models/business_account.py:16 payments/models/promocode.py:72
-#: tools/public_api/models.py:34
+#: tools/public_api/models.py:34 tools/public_api/services/api_key.py:24
 msgid "Owner"
 msgstr "Владелец"
 
@@ -212,6 +212,7 @@ msgstr "ОГРН"
 
 #: authentication/models/business_host.py:69 ml_model/models.py:180
 #: payments/models/payment_plan_feature.py:18 tools/public_api/models.py:31
+#: tools/public_api/services/api_key.py:24
 msgid "Name"
 msgstr "Наименование"
 
@@ -574,12 +575,13 @@ msgstr ""
 msgid "Token is invalid"
 msgstr ""
 
-#: core/exceptions.py:5
+#: lib/exceptions.py:7
 msgid "An unknown error has occurred. Please contact support"
 msgstr ""
 "Произошла неизвестная ошибка. Пожалуйста, обратитесь в службу поддержки"
 
-#: lib/exceptions.py:15
+#: lib/exceptions.py:16
+#, python-format
 msgid "A %(model)s with fields %(fields)s already exists"
 msgstr "Уже существует %(model)s с полями %(fields)s"
 
@@ -597,12 +599,12 @@ msgstr "Версия %(version)s уже имеет входные данные 
 msgid "Neuron Models"
 msgstr "Нейронные Модели"
 
-#: ml_model/exceptions.py:17
+#: ml_model/exceptions.py:18
 msgid "The model is currently disabled. Please try again later."
 msgstr ""
 "Модель в настоящее время неактивна. Пожалуйста, повторите попытку позже."
 
-#: ml_model/exceptions.py:22
+#: ml_model/exceptions.py:23
 msgid "Your request was blocked by our moderation system"
 msgstr "Ваш запрос был заблокирован нашей системой модерации"
 
@@ -615,18 +617,18 @@ msgstr ""
 "Размер изображения %(cw)dx%(ch)d не поддерживается. Пожалуйста, переверните "
 "до %(rw)dx%(rh)d"
 
-#: ml_model/exceptions.py:37
+#: ml_model/exceptions.py:36
 #, python-format
 msgid "Image size %(cw)sx%(ch)s is not supported. Required size: %(rw)sx%(rh)s"
 msgstr ""
 "Размер изображения %(cw)sx%(ch)s не поддерживается. Требуемый размер: "
 "%(rw)sx%(rh)s"
 
-#: ml_model/exceptions.py:42
+#: ml_model/exceptions.py:43
 msgid "The model is not responding"
 msgstr "Модель не отвечает"
 
-#: ml_model/exceptions.py:51
+#: ml_model/exceptions.py:52
 #, python-format
 msgid ""
 "The attached file format is not supported. Available formats: "
@@ -635,35 +637,39 @@ msgstr ""
 "Формат вложенного файла не поддерживается. Доступные форматы: "
 "%(available_extensions)s."
 
-#: ml_model/exceptions.py:57
+#: ml_model/exceptions.py:58
 msgid "The length of the context has been exceeded."
 msgstr "Длина контекста превышена."
 
-#: ml_model/exceptions.py:62
+#: ml_model/exceptions.py:63
 msgid "Jinja template not found"
 msgstr "Jinja-шаблон не найден"
 
-#: ml_model/exceptions.py:67
+#: ml_model/exceptions.py:68
 msgid "There was an unknown error while rendering a template"
 msgstr "При рендеринге шаблона произошла неизвестная ошибка"
 
-#: ml_model/exceptions.py:72
+#: ml_model/exceptions.py:73
 msgid "The neuron model does not exist"
 msgstr "Нейронная модель не существует"
 
-#: ml_model/exceptions.py:80
+#: ml_model/exceptions.py:81
 #, python-format
 msgid "The %(file_type)s is not attached"
 msgstr "Файл (%(file_type)s) не прикреплен"
 
-#: ml_model/exceptions.py:85
+#: ml_model/exceptions.py:86
 msgid "No image content found in response. Try a different request"
 msgstr "В промпте отсутствует описание изображения. Попробуйте другой запрос"
 
-#: ml_model/exceptions.py:90
+#: ml_model/exceptions.py:91
 msgid "Use style type AUTO or GENERAL when a style preset is selected"
 msgstr "При выбранном стиле используйте тип стиля AUTO или GENERAL"
 
+#: ml_model/exceptions.py:96
+msgid "Prediction interrupted. Please retry again"
+msgstr "Генерация прервана. Пожалуйста, повторите попытку еще раз"
+
 #: ml_model/models.py:18 ml_model/models.py:38 ml_model/models.py:70
 #: ml_model/models.py:182 tools/media/models.py:43
 msgid "Slug"
@@ -9,8 +9,10 @@ import filetype
 import requests
 from django.core.files import File
 from django.core.files.images import get_image_dimensions
+from replicate.exceptions import ModelError
 
 from messages.models import Message
+from ml_model.exceptions import PredictionInterruptedError, RequestBlocked, GenerationException
 from ml_model.services.base import SimpleService
 from ml_model.tasks import replicate_run
 
@@ -85,7 +87,14 @@ class Flux_2(SimpleService):
             image = f'data:{mime};base64,{base64.b64encode(input_message.file.read()).decode("utf-8")}'
             input_message.file.close()
             callback_data.update({'input_images': [image]})
-        images = [replicate_run(f'black-forest-labs/{version}', callback_data)]
+        try:
+            images = [replicate_run(f'black-forest-labs/{version}', callback_data)]
+        except ModelError as exc:
+            if any(error in str(exc) for error in ('E005', 'E006', 'sexual')):
+                raise RequestBlocked
+            elif 'PA' in str(exc):
+                raise PredictionInterruptedError
+            raise GenerationException from exc
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, version=version, input_mp=input_mp, output_mp=output_mp)
         msgs = self.save_results(input_message.content, images, process_time, save)
@@ -11,7 +11,7 @@ from django.core.files import File
 
 from messages.models import Message
 
-from ml_model.exceptions import ModelTimeoutError
+from ml_model.exceptions import ModelTimeoutError, GenerationException
 from ml_model.services.base import SimpleService
 
 
@@ -89,14 +89,17 @@ class Fluxlorafast(SimpleService):
             f'fal-ai/{version}',
             json={'prompt': input_message.content, **callback_data},
         ).json()
-        while True:
-            status = client.get(result['status_url']).json()
-            if status.get('status') == 'COMPLETED':
-                break
-            requests_number += 1
-            if requests_number == 271:
-                raise ModelTimeoutError
-            time.sleep(1/3)
+        try:
+            while True:
+                status = client.get(result['status_url']).json()
+                if status.get('status') == 'COMPLETED':
+                    break
+                requests_number += 1
+                if requests_number == 271:
+                    raise ModelTimeoutError
+                time.sleep(1/3)
+        except Exception as exc:
+            raise GenerationException from exc
         process_time = timedelta(seconds=(time.time() - start_time))
         final_result = client.get(result['response_url']).json()
         images = [img['url'] for img in final_result['images']]
@@ -5,9 +5,10 @@ from io import BytesIO
 
 import requests
 from django.core.files import File
+from replicate.exceptions import ModelError
 
 from messages.models import Message
-from ml_model.exceptions import InvalidStyleCombinationError
+from ml_model.exceptions import InvalidStyleCombinationError, RequestBlocked, GenerationException
 from ml_model.models import (
     NeuronModel,
 )
@@ -73,10 +74,15 @@ class Ideogram(SimpleService):
                 **input_message.info,
             }
         )
-        runner = replicate_run(
-            f'{self._CALLBACK_BASE}{callback_data.get("version", "ideogram-v3-turbo")}',
-            callback_data,
-        )
+        try:
+            runner = replicate_run(
+                f'{self._CALLBACK_BASE}{callback_data.get("version", "ideogram-v3-turbo")}',
+                callback_data,
+            )
+        except ModelError as exc:
+            if any(error in str(exc) for error in ('E005', 'E006', 'sexual')):
+                raise RequestBlocked
+            raise GenerationException from exc
         images = runner if isinstance(runner, list) else [runner]
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, input_message=input_message, version=version)
@@ -4,11 +4,12 @@ from datetime import timedelta
 from decimal import Decimal
 from io import BytesIO
 
-import filetype
 import requests
 from django.core.files import File
+from replicate.exceptions import ModelError
 
 from messages.models import Message
+from ml_model.exceptions import RequestBlocked, GenerationException
 from ml_model.models import (
     NeuronModel,
 )
@@ -71,10 +72,15 @@ class Leonardo(SimpleService):
                 **input_message.info,
             }
         )
-        runner = replicate_run(
-            f'{self._CALLBACK_BASE}{callback_data.get("version", "lucid-origin")}',
-            callback_data,
-        )
+        try:
+            runner = replicate_run(
+                f'{self._CALLBACK_BASE}{callback_data.get("version", "lucid-origin")}',
+                callback_data,
+            )
+        except ModelError as exc:
+            if any(error in str(exc) for error in ('E005', 'E006', 'sexual')):
+                raise RequestBlocked
+            raise GenerationException from exc
         images = runner if isinstance(runner, list) else [runner]
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, input_message=input_message, version=version)
@@ -5,8 +5,10 @@ from io import BytesIO
 
 import requests
 from django.core.files import File
+from replicate.exceptions import ModelError
 
 from messages.models import Message
+from ml_model.exceptions import RequestBlocked, GenerationException
 from ml_model.services.base import SimpleService
 from ml_model.tasks import replicate_run
 from payments.exceptions.insufficient_balance import InsufficientBalance
@@ -42,7 +44,12 @@ class Lyria(SimpleService):
             **input_message.info
         }
         start_time = time.time()
-        video = replicate_run(f'google/lyria-2', callback_data)
+        try:
+            video = replicate_run(f'google/lyria-2', callback_data)
+        except ModelError as exc:
+            if any(error in str(exc) for error in ('E005', 'E006', 'sexual')):
+                raise RequestBlocked
+            raise GenerationException from exc
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, duration=32)
         msgs = self.save_results(input_message.content, process_time, video, save)
@@ -1,6 +1,7 @@
 from django.utils.translation import gettext as _
 # накинуть перевод через gettext_lazy
 
+
 class GenerationException(Exception):
     def __str__(self):
         return 'Случилась ошибка во время генерации у этой модели, пожалуйста повторите попытку позже'
@@ -29,13 +30,13 @@ class UnsupportedSize(Exception):
 
     def __str__(self):
         if tuple(self.current_size.values()) == tuple(reversed(self.required_size.values())):
-            return _(
-                'Image size %(cw)dx%(ch)d is not supported. '
-                'Please rotate image to %(rw)dx%(rh)d'
-            ) % (self.current_size | self.required_size)
-        return _(
-            'Image size %(cw)sx%(ch)s is not supported. Required size: %(rw)sx%(rh)s'
-        ) % (self.current_size | self.required_size)
+            return _('Image size %(cw)dx%(ch)d is not supported. Please rotate image to %(rw)dx%(rh)d') % (
+                self.current_size | self.required_size
+            )
+        return _('Image size %(cw)sx%(ch)s is not supported. Required size: %(rw)sx%(rh)s') % (
+            self.current_size | self.required_size
+        )
+
 
 class ModelTimeoutError(Exception):
     def __str__(self):
@@ -88,3 +89,8 @@ class ImageContentNotFound(Exception):
 class InvalidStyleCombinationError(Exception):
     def __str__(self) -> str:
         return _('Use style type AUTO or GENERAL when a style preset is selected')
+
+
+class PredictionInterruptedError(Exception):
+    def __str__(self):
+        return _('Prediction interrupted. Please retry again')