@@ -0,0 +1,3 @@
+from analytics.exceptions.report_exceptions import EmptyMessagesReport
+
+__all__ = ('EmptyMessagesReport',)
@@ -0,0 +1,6 @@
+from django.utils.translation import gettext as _
+
+
+class EmptyMessagesReport(Exception):
+    def __str__(self):
+        return _('No messages found for the selected period')
@@ -0,0 +1,147 @@
+import hashlib
+import json
+import os
+from datetime import timedelta
+
+from django.core.cache import cache
+from django.http import FileResponse
+from django.utils import timezone
+
+from django.contrib.contenttypes.models import ContentType
+from django.db.models import Count, OuterRef, Subquery
+from django.db.models.functions import TruncDate, TruncMonth, TruncWeek
+from ninja.errors import HttpError
+
+from analytics.exceptions import EmptyMessagesReport
+from analytics.schemas import EmployeeGenerationSchema
+from analytics.services.period_service import AnalyticsPeriodService
+from analytics.services.report_services.excel_report_service import ExcelActivityMetricReportService
+from authentication.exceptions.business_host_exceptions.access_denied import AccessDenied
+from authentication.security import SyncAuthBearer
+
+from ninja import Query, Router
+
+from messages.models import Message
+from tools.chats.models import Chat
+from tools.media.models import Audio, Image, Video
+from tools.public_api.models import APIStore
+
+router = Router(auth=SyncAuthBearer(), tags=['analytics'])
+
+
+@router.get('business/employees-generations', tags=['analytics/business'], response={200: None})
+def download_employees_generations(request, payload: Query[EmployeeGenerationSchema]):
+    """
+    Generates an XLSX file that provides information
+    about the number of employee requests for models during a period
+    """
+    try:
+        if request.auth.account_type != 'business_host':
+            raise AccessDenied
+
+        host = request.auth.host
+        employees_emails = [acc.user.email for acc in host.accounts.all()]
+        ap_service = AnalyticsPeriodService
+
+        tz = timezone.get_current_timezone()
+        if q := payload.quarter:
+            period = ap_service.get_quarter_by_alias(q, payload.year)
+        elif payload.start and payload.end:
+            period = ap_service.get_period_by_timerange(payload.start, payload.end)
+
+        groupby = {
+            'dau': TruncDate('created_at', tzinfo=tz),
+            'wau': TruncWeek('created_at', tzinfo=tz),
+            'mau': TruncMonth('created_at', tzinfo=tz),
+        }
+
+        cache_key = (
+            f'analytics:employees_generations:'
+            f'{host.uid}:'
+            f'{hashlib.sha256(json.dumps(sorted(employees_emails), ensure_ascii=True).encode()).hexdigest()}:'
+            f'{period.start.isoformat()}:'
+            f'{period.end.isoformat()}:'
+            f'{payload.metric.value}'
+        )
+        messages = cache.get(cache_key)
+        if messages is None:
+            messages: dict[str, dict[str, dict[str, int]]] = {}
+            for store_model in (Audio, Video, Image, Chat, APIStore):
+                ct = ContentType.objects.get_for_model(store_model)
+                user_email_subquery = (
+                    store_model.objects.filter(uid=OuterRef('object_id'))
+                    .select_related('user')
+                    .values('user__email')[:1]
+                )
+                rows = (
+                    Message.objects.filter(
+                        content_type=ct,
+                        from_model=True,
+                        created_at__gte=ap_service.to_aware_datetime(period.start),
+                        created_at__lte=ap_service.to_aware_datetime(period.end, end=True),
+                    )
+                    .annotate(owner_user_email=Subquery(user_email_subquery))
+                    .filter(owner_user_email__in=employees_emails)
+                    .annotate(groupby=groupby[payload.metric.value])
+                    .values('owner_user_email', 'groupby')
+                    .annotate(total=Count('uid'))
+                )
+                for row in rows:
+                    gb = row['groupby']
+                    day = gb.date() if hasattr(gb, 'date') else gb
+                    bucket = day.isoformat()
+                    email = str(row['owner_user_email'])
+
+                    if payload.metric.value == 'wau':
+                        week_end = day + timedelta(days=6)
+                        sheets = {
+                            (day + timedelta(days=i)).strftime('%Y-%m')
+                            for i in range((week_end - day).days + 1)
+                        }
+                    else:
+                        sheets = {day.strftime('%Y-%m')}
+
+                    for sheet in sheets:
+                        messages.setdefault(sheet, {}).setdefault(bucket, {}).setdefault(email, 0)
+                        messages[sheet][bucket][email] += row['total']
+            if not messages:
+                raise EmptyMessagesReport
+            cache.set(cache_key, messages, 60 * 15)
+    except AccessDenied as exc:
+        raise HttpError(401, str(exc))
+    except EmptyMessagesReport as exc:
+        raise HttpError(404, str(exc)) from exc
+    except Exception as exc:
+        raise HttpError(400, str(exc)) from exc
+    excel_report = ExcelActivityMetricReportService()
+    excel_report.create_document(
+        data=messages,
+        period=period,
+        emails=employees_emails,
+        metric=payload.metric.value,
+        time_aggregation=payload.aggregation.value,
+    )
+    document_data = open(excel_report.tempfile.name, mode='rb')
+    filename = (
+        f'{payload.metric.value.upper()}_'
+        f'{
+            f"{period.start}_{period.end}"
+            if not (q := payload.quarter)
+            else f"{q.value.upper()}_{payload.year or timezone.now().year}"
+        }'
+        f'.xlsx'
+    )
+    response = FileResponse(
+        document_data,
+        filename=filename,
+        as_attachment=True,
+    )
+
+    def _cleanup_tempfile():
+        try:
+            os.remove(excel_report.tempfile.name)
+        except OSError:
+            pass
+
+    response._resource_closers.append(_cleanup_tempfile)
+    return response
@@ -0,0 +1,14 @@
+import tempfile
+from abc import ABC, abstractmethod
+
+
+class BaseReportService(ABC):
+    def __init__(self, file_suffix: str) -> None:
+        self.__file_suffix = file_suffix
+        self.tempfile = self.__initialize_temp_file()
+
+    @abstractmethod
+    def create_document(self, *args, **kwargs): ...
+
+    def __initialize_temp_file(self):
+        return tempfile.NamedTemporaryFile(suffix=self.__file_suffix, delete=False)
@@ -0,0 +1,176 @@
+from collections import defaultdict
+from datetime import date, timedelta
+from typing import Literal
+
+from dateutil.relativedelta import relativedelta
+from pyexcelerate import Workbook, Style, Font, Alignment
+
+from analytics.domain import Period
+
+from .base_report_service import BaseReportService
+
+
+class BaseExcelReportService(BaseReportService):
+    def __init__(self) -> None:
+        self.workbook = Workbook()
+        super().__init__(file_suffix='.xlsx')
+
+    def create_document(self, *args, **kwargs): ...
+
+
+class ExcelActivityMetricReportService(BaseExcelReportService):
+    def create_document(
+        self,
+        data: dict[str, dict[str, dict[str, int]]],
+        period: Period,
+        emails: list[str],
+        metric: Literal['dau', 'wau', 'mau'] = 'dau',
+        time_aggregation: Literal['month', 'quarter'] = 'month',
+    ):
+        match time_aggregation:
+            case 'month':
+                self._create_month_statistics(data, period, metric, emails)
+            case 'quarter':
+                self._create_quarter_statistics(data, period, metric, emails)
+            case _:
+                raise NotImplementedError
+
+    def _create_month_statistics(
+        self,
+        data: dict[str, dict[str, dict[str, int]]],
+        period: Period,
+        metric: str,
+        emails: list[str],
+    ) -> None:
+        month = period.start.replace(day=1)
+        while month <= period.end:
+            sheet = month.strftime('%Y-%m')
+            month_data = data.get(sheet, {})
+            buckets = self._buckets(metric, month, period)
+
+            rows = [['Email', *[self._column_label(b, metric) for b in buckets]]]
+            rows += [[email, *[month_data.get(b, {}).get(email, 0) for b in buckets]] for email in emails]
+            ws = self.workbook.new_sheet(sheet, data=rows)
+            ws.set_col_style(1, Style(size=35))
+            ws.set_row_style(
+                1,
+                Style(font=Font(bold=True), alignment=Alignment(horizontal='center', vertical='center')),
+            )
+            for col in range(2, len(rows[1]) + 1):
+                ws.set_col_style(col, Style(size=15))
+            month += relativedelta(months=1)
+
+        self.tempfile.close()
+        self.workbook.save(self.tempfile.name)
+
+    @staticmethod
+    def _buckets(metric: str, month_start: date, period: Period) -> list[str]:
+        start = max(period.start, month_start)
+        end = min(period.end, month_start + relativedelta(months=1, days=-1))
+
+        if metric == 'mau':
+            return [month_start.isoformat()]
+
+        if metric == 'dau':
+            buckets, day = [], start
+            while day <= end:
+                buckets.append(day.isoformat())
+                day += timedelta(days=1)
+            return buckets
+
+        buckets, day = [], start - timedelta(days=start.weekday())
+        while day <= end:
+            if day + timedelta(days=6) >= start:
+                buckets.append(day.isoformat())
+            day += timedelta(days=7)
+        return buckets
+
+    @staticmethod
+    def _column_label(bucket: str, metric: str) -> str:
+        day = date.fromisoformat(bucket)
+        if metric == 'wau':
+            return f'{day:%d.%m} — {(day + timedelta(days=6)):%d.%m}'
+        if metric == 'mau':
+            return day.strftime('%m.%Y')
+        return day.strftime('%d.%m')
+
+    def _create_quarter_statistics(
+        self,
+        data: dict[str, dict[str, dict[str, int]]],
+        period: Period,
+        metric: str,
+        emails: list[str],
+    ) -> None:
+        quarter = self._quarter_start(period.start)
+        while quarter <= period.end:
+            quarter_end = min(period.end, quarter + relativedelta(months=3, days=-1))
+            quarter_start = max(period.start, quarter)
+            buckets = self._quarter_buckets(metric, quarter_start, quarter_end)
+            quarter_data = self._quarter_data(data, quarter, quarter_end, metric)
+            quarter_number = ((quarter.month - 1) // 3) + 1
+            sheet_name = f'{quarter.year}-Q{quarter_number}'
+
+            rows = [['Email', *[self._column_label(b, metric) for b in buckets]]]
+            rows += [[email, *[quarter_data.get(b, {}).get(email, 0) for b in buckets]] for email in emails]
+            ws = self.workbook.new_sheet(sheet_name, data=rows)
+            ws.set_col_style(1, Style(size=35))
+            ws.set_row_style(
+                1,
+                Style(font=Font(bold=True), alignment=Alignment(horizontal='center', vertical='center')),
+            )
+            for col in range(2, len(rows[1]) + 1):
+                ws.set_col_style(col, Style(size=15))
+            quarter += relativedelta(months=3)
+
+        self.tempfile.close()
+        self.workbook.save(self.tempfile.name)
+
+    @staticmethod
+    def _quarter_start(day: date) -> date:
+        month = ((day.month - 1) // 3) * 3 + 1
+        return date(day.year, month, 1)
+
+    @staticmethod
+    def _quarter_buckets(metric: str, start: date, end: date) -> list[str]:
+        if metric == 'dau':
+            buckets, day = [], start
+            while day <= end:
+                buckets.append(day.isoformat())
+                day += timedelta(days=1)
+            return buckets
+
+        if metric == 'wau':
+            buckets, day = [], start - timedelta(days=start.weekday())
+            while day <= end:
+                if day + timedelta(days=6) >= start:
+                    buckets.append(day.isoformat())
+                day += timedelta(days=7)
+            return buckets
+
+        buckets, month = [], start.replace(day=1)
+        while month <= end:
+            buckets.append(month.isoformat())
+            month += relativedelta(months=1)
+        return buckets
+
+    @staticmethod
+    def _quarter_data(
+        data: dict[str, dict[str, dict[str, int]]],
+        quarter_start: date,
+        quarter_end: date,
+        metric: str,
+    ) -> dict[str, dict[str, int]]:
+        quarter_data = defaultdict(lambda: defaultdict(int))
+        month = quarter_start
+        while month <= quarter_end:
+            sheet = month.strftime('%Y-%m')
+            month_data = data.get(sheet, {})
+            for bucket, by_email in month_data.items():
+                if metric == 'wau':
+                    bucket_month = date.fromisoformat(bucket).strftime('%Y-%m')
+                    if bucket_month != sheet:
+                        continue
+                for email, value in by_email.items():
+                    quarter_data[bucket][email] += value
+            month += relativedelta(months=1)
+        return quarter_data
@@ -0,0 +1,26 @@
+from datetime import date, datetime, time
+from typing import Literal
+
+from dateutil.relativedelta import relativedelta
+from django.utils.timezone import make_aware
+
+from analytics.domain import Period, Quarter
+
+
+class AnalyticsPeriodService:
+    @staticmethod
+    def get_quarter_by_alias(
+        quarter_alias: Literal['q1', 'q2', 'q3', 'q4'] = 'q1', year_value: int | None = None
+    ) -> Quarter:
+        year = year_value or date.today().year
+        q_start = date(year, 1 + 3 * (int(quarter_alias[1:]) - 1), 1)
+        q_end = q_start + relativedelta(months=3, days=-1)
+        return Quarter(start=q_start, end=q_end, alias=quarter_alias)
+
+    @staticmethod
+    def get_period_by_timerange(start: date, end: date) -> Period:
+        return Period(start=start, end=end)
+
+    @staticmethod
+    def to_aware_datetime(date_value: date, *, end: bool = False) -> datetime:
+        return make_aware(datetime.combine(date_value, time.max if end else time.min))
@@ -0,0 +1,6 @@
+from django.apps import AppConfig
+
+
+class AnalyticsConfig(AppConfig):
+    default_auto_field = 'django.db.models.BigAutoField'
+    name = 'analytics'
@@ -0,0 +1,13 @@
+from dataclasses import dataclass
+from datetime import date
+
+
+@dataclass
+class Period:
+    start: date
+    end: date
+
+
+@dataclass
+class Quarter(Period):
+    alias: str | None = None
@@ -0,0 +1,36 @@
+from datetime import date
+
+from django.utils.translation import gettext as _
+from ninja import Schema
+from pydantic import model_validator
+
+from analytics.typing import ActivityMetricEnum, QuarterEnum, TimeAggregationEnum
+
+
+class DateRangeSchema(Schema):
+    start: date | None = None
+    end: date | None = None
+
+
+class QuarterSchema(Schema):
+    quarter: QuarterEnum | None = None
+    year: int | None = None
+
+
+class EmployeeGenerationSchema(QuarterSchema, DateRangeSchema):
+    metric: ActivityMetricEnum = ActivityMetricEnum.MAU
+    aggregation: TimeAggregationEnum = TimeAggregationEnum.MONTH
+
+    @model_validator(mode='after')
+    def check_period(self):
+        if (self.quarter or self.year) and (self.start or self.end):
+            raise ValueError(_('Provide either quarter or date range, not both'))
+        if self.quarter:
+            return self
+        if self.year:
+            raise ValueError(_('Year can only be used together with quarter'))
+        if not self.start or not self.end:
+            raise ValueError(_('Provide quarter or start and end dates'))
+        if self.start > self.end:
+            raise ValueError(_('Start date must be before or equal to end date'))
+        return self
@@ -0,0 +1,19 @@
+from enum import Enum
+
+
+class QuarterEnum(str, Enum):
+    Q1 = 'q1'
+    Q2 = 'q2'
+    Q3 = 'q3'
+    Q4 = 'q4'
+
+
+class ActivityMetricEnum(str, Enum):
+    DAU = 'dau'
+    WAU = 'wau'
+    MAU = 'mau'
+
+
+class TimeAggregationEnum(str, Enum):
+    MONTH = 'month'
+    QUARTER = 'quarter'
@@ -3,7 +3,7 @@ from authentication.exceptions.business_host_exceptions.already_account import (
 )
 from authentication.exceptions.business_host_exceptions.already_has_plan import (
     AlreadyHasPlan,
-    InviteeHasPlan
+    InviteeHasPlan,
 )
 from authentication.exceptions.business_host_exceptions.already_host import (
     AlreadyHost,
@@ -5,7 +5,7 @@ class AlreadyHasPlan(Exception):
     def __str__(self) -> str:
         return _(
             'You already have an active tariff plan. You must request a '
-            'cancellation of your current tariff plan (via the \"Report an error\" button), after which '
+            'cancellation of your current tariff plan (via the "Report an error" button), after which '
             'you will be able to create a Corporate Account'
         )
 
@@ -14,6 +14,6 @@ class InviteeHasPlan(Exception):
     def __str__(self) -> str:
         return _(
             'Invitee already has an active tariff plan. Invitee must request a '
-            'cancellation of his current tariff plan (via the \"Report an error\" button), after which '
+            'cancellation of his current tariff plan (via the "Report an error" button), after which '
             'you will be able to invite him'
         )
@@ -1,11 +1,4 @@
-from authentication.exceptions.email_exceptions.letter_not_found import (
-    LetterNotFound
-)
-from authentication.exceptions.email_exceptions.letter_unknown import (
-    LetterUnknownException
-)
+from authentication.exceptions.email_exceptions.letter_not_found import LetterNotFound
+from authentication.exceptions.email_exceptions.letter_unknown import LetterUnknownException
 
-__all__ = (
-    'LetterNotFound',
-    'LetterUnknownException'
-)
\ No newline at end of file
+__all__ = ('LetterNotFound', 'LetterUnknownException')
@@ -101,10 +101,6 @@ class BusinessUserHost(BaseModel):
     def display_name(self) -> str:
         return self.company_name or self.user.email
 
-    @property
-    def accounts(self) -> QuerySet[BusinessAccount]:
-        return self.accounts
-
     @property
     def groups(self) -> QuerySet[BusinessGroup]:
         return self.company_groups.all()
@@ -16,8 +16,6 @@ class EmailToken(BaseModel):
     key = models.CharField(max_length=30, verbose_name=_('Key'))
 
     class Meta:
-        indexes = [
-            Index(fields=['key'], name='idx_email_token_key')
-        ]
+        indexes = [Index(fields=['key'], name='idx_email_token_key')]
         verbose_name = _('Email Token')
         verbose_name_plural = _('Email Tokens')
@@ -19,4 +19,6 @@ class AccountStatusSelector:
             return False
 
     def is_admin(self) -> bool:
-        return self.user.business_account.account_privileges == 'admin' if self.is_business_account() else False
\ No newline at end of file
+        return (
+            self.user.business_account.account_privileges == 'admin' if self.is_business_account() else False
+        )
@@ -83,7 +83,8 @@ class BusinessHostSelector:
         else:
             raise Exception(_("User haven't rights to access host account information"))
         return BusinessHostSerializer(
-            host, context={'worker_amount': host.accounts.count(), 'token_cap_enabled': host.token_cap_enabled}
+            host,
+            context={'worker_amount': host.accounts.count(), 'token_cap_enabled': host.token_cap_enabled},
         )
 
     def get_per_model_statistics(self):
@@ -72,7 +72,9 @@ class BusinessHostService:
         EmailService.send_corporate_greeting_email(account_service.account, password)
         return account_service
 
-    def create_existing(self, email: str, account_privileges: str, group: UUID | None = None) -> BusinessAccountService:
+    def create_existing(
+        self, email: str, account_privileges: str, group: UUID | None = None
+    ) -> BusinessAccountService:
         company = self.user.host or self.user.employee.parent_company
         if self.user.account_type == 'business_admin' and account_privileges == 'admin':
             raise AdminCreateForbidden
@@ -91,7 +93,9 @@ class BusinessHostService:
             company,
             account_privileges=account_privileges,
         )
-        account_service.account.group = BusinessGroup.objects.filter(uid=group, parent_company=company).first()
+        account_service.account.group = BusinessGroup.objects.filter(
+            uid=group, parent_company=company
+        ).first()
         account_service.account.save()
         if not user.is_deleted:
             EmailService.send_corporate_invitation_email(account_service.account, company)
@@ -19,9 +19,7 @@ class MeAPITest(BaseAuthorizedAPITest):
 
     @classmethod
     def setup_test_data(cls) -> None:
-        cls.payment_plan, _ = PaymentPlan.objects.update_or_create(
-            price=0, tokens_per_plan=10, defaults={}
-        )
+        cls.payment_plan, _ = PaymentPlan.objects.update_or_create(price=0, tokens_per_plan=10, defaults={})
         cls.setup_host()
 
     def test_unauthorized_status_code(self) -> None:
@@ -91,4 +89,3 @@ class MeAPITest(BaseAuthorizedAPITest):
         BusinessAccount.objects.create(user=self.user, parent_company=self.host)
         payment_plan_uid = self.get().json()['payment_plan']['plan']['uid']
         self.assertEqual(str(payment_plan_uid), str(self.host_payment_plan.uid))
-
@@ -1,6 +1,7 @@
 # Authentication mapper
 from django.db.models import Count, Prefetch, Q
 
+from authentication.models.business_account import BusinessAccount
 from payments.models.payment_plan_feature import PaymentPlanFeature
 from payments.models.user_payment_method import PaymentMethod
 
@@ -194,6 +195,27 @@ PATH_PREFETCH_MAP = {
             *_gen_only('payment_plan__plan', 'uid', 'price'),
         ),
     },
+    '/api/v1/analytics/business/employees-generations': {
+        'select': (
+            'host_account',
+            'host_account__company_companyipwhitelist',
+        ),
+        'prefetch': (
+            Prefetch(
+                'host_account__accounts',
+                queryset=BusinessAccount.objects.select_related('user').only(
+                    'parent_company_id',
+                    'user_id',
+                    'user__email',
+                ),
+            ),
+        ),
+        'only': (
+            'uid',
+            *_gen_only('host_account', 'uid'),
+            *_gen_only('host_account__company_companyipwhitelist', 'uid', 'is_enabled'),
+        ),
+    },
     '/api/v1/payments/restore-subscription': {
         'select': (
             'host_account',
@@ -9,12 +9,11 @@ from django.dispatch import receiver
 
 @receiver([post_save, post_delete], sender=BusinessAccount)
 def invalidate_user_cache(sender, instance, signal, **kwargs):
-    cache_keys = cache.conn.smembers(dnfs_to_conj_keys(
-        '',
-        {'authentication_customusermodel': [{'uid': instance.user_id}]}
-    )[0])
+    cache_keys = cache.conn.smembers(
+        dnfs_to_conj_keys('', {'authentication_customusermodel': [{'uid': instance.user_id}]})[0]
+    )
     for key in cache_keys:
         data = cache.get(key.decode())
         if isinstance(data, list) and isinstance((user := data[0]), CustomUserModel):
             user.business_account = instance if signal == post_save else None
-            cache.set(key.decode(), [user])
\ No newline at end of file
+            cache.set(key.decode(), [user])
@@ -11,6 +11,7 @@ app.autodiscover_tasks()
 
 from lib.unleash.client import celery_client
 
+
 @worker_process_init.connect
 def configure_workers(sender=None, conf=None, **kwargs):
     celery_client.client.initialize_client(fetch_toggles=False)
@@ -79,6 +79,7 @@ TOOLS = [
     'tools.apps.PublicAPIConfig',
     'tools.apps.ChatsConfig',
     'tools.apps.MediaConfig',
+    'tools.apps.ShareConfig',
 ]
 
 
@@ -274,6 +275,10 @@ CELERY_BEAT_SCHEDULE = {
         'task': 'payments.tasks.send_low_balance_message',
         'schedule': crontab(0, 8),
     },
+    'delete_expired_shares': {
+        'task': 'tools.share.tasks.delete_expired_shares',
+        'schedule': crontab('0', '*/6', '*', '*', '*'),
+    },
     'execute_recurring_payments': {
         'task': 'payments.tasks.execute_recurring_payments',
         'schedule': crontab(*env.list('RECURRING_PAYMENT_CRONTAB_SCHEDULE', [])),
@@ -475,6 +480,7 @@ if CACHEOPS_REDIS:
         'ml_model.*': {'ops': 'all', 'timeout': 60 * 60},
         'tools.chats.*': {'ops': 'all', 'timeout': 60 * 60},
         'tools.media.*': {'ops': 'all', 'timeout': 60 * 60},
+        'tools.share.*': {'ops': 'all', 'timeout': 60 * 60},
         'payments.paymentplan': {'ops': 'all', 'timeout': 60 * 60},
         'payments.invoice': {'ops': 'all', 'timeout': 60 * 60 * 24 * 7},
         'messages.*': {'ops': 'all', 'timeout': 60 * 60},
@@ -497,3 +503,6 @@ RECURRING_FAILED_CHARGE_EMAIL_DAYS = env.list('RECURRING_FAILED_CHARGE_EMAIL_DAY
 
 # SSE STREAMING
 FF__STREAMING_ENABLED = env.bool('FF__STREAMING_ENABLED', False)
+
+# MESSAGE SHARING
+SHARE_LIFETIME = env.int('SHARE_LIFETIME', 1800)
@@ -9,6 +9,7 @@ from django.urls import include, path
 from django.utils.translation import gettext_lazy as _
 from drf_spectacular.views import SpectacularAPIView, SpectacularSwaggerView
 from ninja import NinjaAPI, Schema
+from ninja.errors import ValidationError
 
 from authentication.exceptions import (
     InvalidPassword,
@@ -30,11 +31,13 @@ public_api = NinjaAPI(
 api.add_router('users/', 'users.routes.v1.router')
 api.add_router('chats/', 'tools.chats.routes.v1.router')
 api.add_router('media/', 'tools.media.routes.v1.router')
+api.add_router('share/', 'tools.share.routes.v1.router')
 
 compatibility_api.add_router('auth/', 'authentication.routes.v1.router')
 compatibility_api.add_router('payments/', 'payments.routes.v1.router')
 compatibility_api.add_router('reports/', 'reports.routes.v1.router')
 compatibility_api.add_router('ml_model/', 'ml_model.routes.v1.router')
+compatibility_api.add_router('analytics/', 'analytics.routes.v1.router')
 
 compatibility_api_v2.add_router('auth/', 'authentication.routes.v2.router')
 
@@ -97,6 +100,15 @@ def invalid_password_error_handler(request, exc: InvalidPassword):
     return api.create_response(request, {'message': _('Wrong password')}, status=401)
 
 
+@compatibility_api.exception_handler(ValidationError)
+def compatibility_validation_error(request, exc: ValidationError):
+    return compatibility_api.create_response(
+        request,
+        {'detail': exc.errors[0]['ctx']['error']},
+        status=422,
+    )
+
+
 urlpatterns = []
 
 if settings.DEBUG:
@@ -138,4 +150,4 @@ urlpatterns += (
     ]
     + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT)
     + public_urlpatterns
-)
\ No newline at end of file
+)
@@ -103,5 +103,3 @@ class BaseAuthorizedAPITest(BaseAPITest):
 
     @abstractmethod
     def test_authorized_status_code(self) -> None: ...
-
-
@@ -5,7 +5,6 @@ from lib.typing import Email, State
 
 
 class FeatureFlagService(ABC):
-
     @abstractmethod
     def get_flag_state_by_emails(self, name: str, emails: List[Email]) -> Mapping[Email, State]:
         pass
@@ -23,5 +23,5 @@ class UnleashRedisCache(BaseCache):
 
     def destroy(self):
         client = self.cache.client.get_client(write=True)
-        for key in client.scan_iter(f"{self.PREFIX}*"):
+        for key in client.scan_iter(f'{self.PREFIX}*'):
             client.delete(key)
@@ -1,4 +1,4 @@
 from lib.services.unleash_feature_flag import UnleashFeatureFlagService
 
 web_client = UnleashFeatureFlagService()
-celery_client = UnleashFeatureFlagService()
\ No newline at end of file
+celery_client = UnleashFeatureFlagService()
@@ -1,2 +1,2 @@
 type Email = str
-type State = bool
\ No newline at end of file
+type State = bool
@@ -1480,6 +1480,10 @@ msgstr "Публичный API"
 msgid "Media"
 msgstr "Медиа"
 
+#: tools/apps.py:32 tools/share/models.py:17
+msgid "Share"
+msgstr "Шеринг"
+
 #: tools/chats/apis.py:219 tools/media/apis.py:246
 #: tools/public_api/views/base.py:108
 msgid ""
@@ -1715,6 +1719,50 @@ msgstr "Название голоса успешно обновлено"
 msgid "Preset voices are shared and cannot be deleted. Use your own voice id."
 msgstr "Пресеты общие и не удаляются. Используйте id собственного голоса."
 
+#: tools/share/exceptions.py:6
+msgid "Some messages are unavailable to you"
+msgstr "Некоторые сообщения вам недоступны"
+
+#: tools/share/exceptions.py:11
+msgid "Link access can only include messages from one store"
+msgstr "Можно открыть доступ по ссылке только к сообщениям из одного хранилища"
+
+#: tools/share/exceptions.py:16
+msgid "Link access is not available for this store type"
+msgstr "Доступ по ссылке для этого типа хранилища недоступен"
+
+#: tools/share/exceptions.py:21
+msgid "Link access for this store can only include model messages"
+msgstr "Для этого хранилища в ссылку можно добавить только сообщения от модели"
+
+#: tools/share/exceptions.py:26
+msgid "Not all messages were found. Some may have been deleted"
+msgstr "Не все сообщения найдены. Возможно, часть уже удалена"
+
+#: tools/share/exceptions.py:31
+msgid "The link was not found or is no longer available"
+msgstr "Ссылка не найдена или больше не действует"
+
+#: tools/share/models.py:8
+msgid "Code"
+msgstr "Код"
+
+#: tools/share/models.py:9
+msgid "Messages"
+msgstr "Сообщения"
+
+#: tools/share/models.py:10
+msgid "Created At"
+msgstr "Создано"
+
+#: tools/share/models.py:11
+msgid "Expires At"
+msgstr "Истекает"
+
+#: tools/share/models.py:18
+msgid "Shares"
+msgstr "Шеринги"
+
 #~ msgid "Attempts"
 #~ msgstr "Попытки"
 
@@ -17,11 +17,11 @@ class MessageAdmin(admin.ModelAdmin):
         'file',
         'from_public_api',
         'is_sent',
-        'info'
+        'info',
     )
     raw_id_fields = ('content_type',)
 
-    @admin.display(description="Связанный объект")
+    @admin.display(description='Связанный объект')
     def content_object_link(self, obj):
         if c_obj := obj.content_object:
             url = reverse(f'admin:{c_obj._meta.app_label}_{c_obj._meta.model_name}_change', args=[c_obj.pk])
@@ -41,7 +41,9 @@ class MessageSerializer(serializers.ModelSerializer):
         file = data.get('file')
         max_mb_size = 50
         if file and file.size > (max_mb_size << 10 << 10):
-            raise ValidationError(_('The file size cannot exceed %(max_mb_size)d MB') % {'max_mb_size': max_mb_size})
+            raise ValidationError(
+                _('The file size cannot exceed %(max_mb_size)d MB') % {'max_mb_size': max_mb_size}
+            )
         return data
 
     def to_representation(self, instance):
@@ -1 +1 @@
-from ml_model.adapters.bytedance_model_ark import BytedanceModelArkAdapter
\ No newline at end of file
+from ml_model.adapters.bytedance_model_ark import BytedanceModelArkAdapter
@@ -319,9 +319,7 @@ class BytedanceModelArkAdapter:
                                 chunk = delta.get('content') or ''
                                 if chunk:
                                     yield RawSSEChunk(event='token', data={'content': chunk})
-                                if (
-                                    fr := choices[0].get('finish_reason')
-                                ) and fr not in (
+                                if (fr := choices[0].get('finish_reason')) and fr not in (
                                     BytedanceFinishReason.STOP,
                                     BytedanceFinishReason.LENGTH,
                                 ):
@@ -381,7 +379,9 @@ class BytedanceModelArkAdapter:
                         raise InputImageSensitiveContentError
 
                 if image_data := data.get('data'):
-                    urls = [item.get('url') for item in image_data if isinstance(item, dict) and item.get('url')]
+                    urls = [
+                        item.get('url') for item in image_data if isinstance(item, dict) and item.get('url')
+                    ]
                     if urls:
                         return urls
                 if cls._is_request_blocked_error(data):
@@ -530,4 +530,4 @@ class BytedanceModelArkAdapter:
                         total_tokens += token_info['total_tokens']
                     return total_tokens
                 except:
-                    return 0
\ No newline at end of file
+                    return 0
@@ -38,7 +38,7 @@ class NeuronModelSelector:
             'audio': 'audio',
             'video': 'videos',
             'code': 'code',
-            'voice': 'voice'
+            'voice': 'voice',
         }
         models = NeuronModel.objects.prefetch_related(
             Prefetch(
@@ -57,13 +57,21 @@ class NeuronModelSelector:
         hidden: bool = False,
     ):
         if self.user.is_anonymous:
-            models = NeuronModel.objects.prefetch_related(Prefetch('model_modelstats')).filter(model_settings__is_active=True)
+            models = NeuronModel.objects.prefetch_related(Prefetch('model_modelstats')).filter(
+                model_settings__is_active=True
+            )
             return NeuronModelsSerializer(models, many=True)
         user_type = UserSelector(self.user).check_account_type()
         models = NeuronModel.objects.annotate(
-            has_chat_msgs=Exists(Chat.objects.filter(user=self.user, model=OuterRef('uid'), messages__isnull=False)),
-            has_image_msgs=Exists(Image.objects.filter(user=self.user, model=OuterRef('uid'), messages__isnull=False)),
-            has_video_msgs=Exists(Video.objects.filter(user=self.user, model=OuterRef('uid'), messages__isnull=False)),
+            has_chat_msgs=Exists(
+                Chat.objects.filter(user=self.user, model=OuterRef('uid'), messages__isnull=False)
+            ),
+            has_image_msgs=Exists(
+                Image.objects.filter(user=self.user, model=OuterRef('uid'), messages__isnull=False)
+            ),
+            has_video_msgs=Exists(
+                Video.objects.filter(user=self.user, model=OuterRef('uid'), messages__isnull=False)
+            ),
         ).filter(
             (
                 Q(private_models_hosts__isnull=True)
@@ -72,17 +80,10 @@ class NeuronModelSelector:
             )
             & (
                 Q(model_settings__is_active=True)
-                | (
-                    Q(has_chat_msgs=True)
-                    | Q(has_image_msgs=True)
-                    | Q(has_video_msgs=True)
-                )
+                | (Q(has_chat_msgs=True) | Q(has_image_msgs=True) | Q(has_video_msgs=True))
             )
         )
-        if (
-            user_type == 'business_account'
-            and self.user.employee.accepted
-        ):
+        if user_type == 'business_account' and self.user.employee.accepted:
             allowed_models = self.user.employee.parent_company.allowed_models
         else:
             allowed_models = None
@@ -60,7 +60,7 @@ from ml_model.services.pulid import Pulid
 from ml_model.services.qwen import Qwen
 from ml_model.services.qwen_235B import Qwen_235B
 from ml_model.services.qwen_3_6 import Qwen_3_6
-from ml_model.services.qwen_3_7 import Qwen_3_7
+from ml_model.services.qwen_3_8 import Qwen_3_8
 from ml_model.services.qwen_3_max_thinking import Qwen_3_Max_Thinking
 from ml_model.services.raifgpt import Raifgpt
 from ml_model.services.ray import Ray
@@ -16,14 +16,15 @@ from payments.selectors.payment_plan_selector import PaymentPlanSelector
 
 import random
 
+
 class Audio_Test_Model(SimpleService):
-    
     TOKENS_COST = Decimal('3')
-    
-    PLACEHOLDER_URL=[
+
+    PLACEHOLDER_URL = [
         'https://www.myinstants.com/media/sounds/saliut-eblany-batia-doma-billy-butcher-i-the-boys.mp3',
         'https://www.myinstants.com/media/sounds/zdravstvuite-nichtozhnye-nishchie-smertnye.mp3',
-        'https://www.myinstants.com/media/sounds/okh-zria-ia-tuda-polez.mp3'] # Позже убрать
+        'https://www.myinstants.com/media/sounds/okh-zria-ia-tuda-polez.mp3',
+    ]  # Позже убрать
 
     def calculate_price(self, num_audios: int = 1) -> Decimal:
         return self.TOKENS_COST * num_audios
@@ -31,7 +32,7 @@ class Audio_Test_Model(SimpleService):
     @classmethod
     def predict_price(cls, content: str, file_exists: bool, info: dict[str, Any]) -> Decimal | None:
         num_audios = info.get('num_audios', 1)
-        
+
         return cls.TOKENS_COST * num_audios
 
     def save_results(
@@ -55,43 +56,40 @@ class Audio_Test_Model(SimpleService):
             return Message.objects.bulk_create(messages)
         return messages
 
-
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
-        cau = input_message.info.get('cau') or self.PLACEHOLDER_URL[random.randint(0, 2)] # Позже убрать
+        cau = input_message.info.get('cau') or self.PLACEHOLDER_URL[random.randint(0, 2)]  # Позже убрать
         num_audios = input_message.info.get('num_audios', 1)
-        
-        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (cost := self.calculate_price(num_audios)):
+
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (
+            cost := self.calculate_price(num_audios)
+        ):
             raise InsufficientBalance(balance, cost)
-        
+
         start_time = time.time()
-        
+
         audio_bytes = self._fetch_audio(cau)
-        
+
         audios = [audio_bytes] * num_audios
-        
+
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, num_audios)
-        
+
         msgs = self.save_results(input_message.content, process_time, audios, save)
         return msgs
 
-
     def _fetch_audio(self, url: str):
         try:
-            response = requests.get(
-                url,
-                timeout=600
-            )
+            response = requests.get(url, timeout=600)
             response.raise_for_status()
         except requests.RequestException as exc:
             raise InvalidParameterError(f'Invalid audio URL: {exc}')
-        
+
         kind = filetype.guess(response.content[:120])
-        
+
         if not kind:
             raise CorruptedFileError
-        
+
         if not kind.mime.startswith('audio/'):
             raise InvalidParameterError('Audio format not supported')
-            
-        return response.content
\ No newline at end of file
+
+        return response.content
@@ -275,7 +275,9 @@ class Chatgpt(Chatgpt_4, StreamSimpleService, OpenAIStreamMixin):
 
         try:
             for proxy in Proxy.objects.all():
-                json_data, predicted_input_tokens = self._build_payload(proxy, input_message, ctx, include_image_tool=False)
+                json_data, predicted_input_tokens = self._build_payload(
+                    proxy, input_message, ctx, include_image_tool=False
+                )
                 model_name = ctx['model_name']
                 self.logger.info(
                     f'Predicted input tokens (responses/input_tokens) для {model_name} - {predicted_input_tokens}'
@@ -321,12 +323,7 @@ class Chatgpt(Chatgpt_4, StreamSimpleService, OpenAIStreamMixin):
             return result
 
     def _build_payload(
-        self,
-        proxy: Proxy,
-        input_message: Message,
-        ctx: dict[str, Any],
-        *,
-        include_image_tool: bool = True
+        self, proxy: Proxy, input_message: Message, ctx: dict[str, Any], *, include_image_tool: bool = True
     ) -> tuple[dict[str, Any], int]:
         if not ctx:
             info = input_message.info.copy()
@@ -167,7 +167,10 @@ class Chatgpt_4(SimpleService):
                 )
                 output_tokens = 0
                 self.assert_enough_balance(
-                    input_tokens, image_size, model=self.llm.model_name, embedding_tokens=input_embedding_tokens
+                    input_tokens,
+                    image_size,
+                    model=self.llm.model_name,
+                    embedding_tokens=input_embedding_tokens,
                 )
                 if model_name == 'gpt-oss-120b':
                     system = chat_history.messages.pop(0)
@@ -215,8 +218,9 @@ class Chatgpt_4(SimpleService):
                         (data := response.json())
                         and data.get('choices')
                         and (
-                        content := ','.join(
-                            [choice['message']['content'] for choice in data.get('choices')])
+                            content := ','.join(
+                                [choice['message']['content'] for choice in data.get('choices')]
+                            )
                         )
                     ):
                         input_tokens = response.json()['usage']['prompt_tokens']
@@ -242,7 +246,9 @@ class Chatgpt_4(SimpleService):
                         ]
                     elif file:
                         if sum([len(chunk.content) for chunk in chunks]) > 20_000:
-                            document_name = chunks[0].content.partition(f':{chr(10)}')[2].split(f'{chr(10)}')[0][:100]
+                            document_name = (
+                                chunks[0].content.partition(f':{chr(10)}')[2].split(f'{chr(10)}')[0][:100]
+                            )
                             embedding_tokens, file_data = EmbeddingService.get_large_file_data(
                                 self.store.messages.first().pk,
                                 text_chunks,
@@ -261,15 +267,17 @@ class Chatgpt_4(SimpleService):
                                 'Используй системный промпт. Содержание файла: '
                                 f'{"".join(text_chunks)}. Вопрос: {input_message.content}'
                             )
-                    json_data = {
-                        'model': model_name,
-                        'messages': messages
-                    }
-                    input_tokens, output_tokens, response = self.call_openai_api(proxy=proxy, endpoint='chat/completions',json_data=json_data)
+                    json_data = {'model': model_name, 'messages': messages}
+                    input_tokens, output_tokens, response = self.call_openai_api(
+                        proxy=proxy, endpoint='chat/completions', json_data=json_data
+                    )
                 elif info.get('web_search', 'Отключено') != 'Отключено':
                     system = chat_history.messages.pop(0)
                     messages = [
-                        {'role': 'user' if isinstance(msg, HumanMessage) else 'assistant', 'content': msg.content}
+                        {
+                            'role': 'user' if isinstance(msg, HumanMessage) else 'assistant',
+                            'content': msg.content,
+                        }
                         for msg in chat_history.messages
                     ]
                     messages.insert(0, {'role': 'system', 'content': system.content})
@@ -285,7 +293,9 @@ class Chatgpt_4(SimpleService):
                         ]
                     elif file:
                         if sum([len(chunk.content) for chunk in chunks]) > 20_000:
-                            document_name = chunks[0].content.partition(f':{chr(10)}')[2].split(f'{chr(10)}')[0][:100]
+                            document_name = (
+                                chunks[0].content.partition(f':{chr(10)}')[2].split(f'{chr(10)}')[0][:100]
+                            )
                             embedding_tokens, file_data = EmbeddingService.get_large_file_data(
                                 self.store.messages.first().pk,
                                 text_chunks,
@@ -313,7 +323,9 @@ class Chatgpt_4(SimpleService):
                 elif file:
                     input_tokens = self.count_text_tokens([*chat_history.messages])
                     if sum([len(chunk.content) for chunk in chunks]) > 20_000:
-                        document_name = chunks[0].content.partition(f':{chr(10)}')[2].split(f'{chr(10)}')[0][:100]
+                        document_name = (
+                            chunks[0].content.partition(f':{chr(10)}')[2].split(f'{chr(10)}')[0][:100]
+                        )
                         embedding_tokens, file_data = EmbeddingService.get_large_file_data(
                             self.store.messages.first().pk,
                             text_chunks,
@@ -362,18 +374,16 @@ class Chatgpt_4(SimpleService):
                 if output_tokens == 0:
                     output_tokens = self.count_text_tokens([response])
 
-                if (
-                    image
-                    and normalized_image
-                    and model_name != 'o3-mini'
-                ):
+                if image and normalized_image and model_name != 'o3-mini':
                     self.logger.info(f'Input количество токенов БЕЗ картинки {model_name} - {input_tokens}')
                     input_tokens += self.count_image_tokens(normalized_image.size, model_name)
 
                 self.logger.info(f'Input количество токенов для {model_name} - {input_tokens}')
                 self.logger.info(f'Output количество токенов для {model_name} - {output_tokens}')
                 self.logger.info(f'Embedding количество токенов для {model_name} - {embedding_tokens}')
-                self.logger.info(f'Общее количество токенов для {model_name} - {input_tokens + output_tokens + embedding_tokens}')
+                self.logger.info(
+                    f'Общее количество токенов для {model_name} - {input_tokens + output_tokens + embedding_tokens}'
+                )
 
                 process_time = timedelta(seconds=time.time() - start_time)
                 self.handle_invoice(
@@ -382,7 +392,7 @@ class Chatgpt_4(SimpleService):
                     output_tokens,
                     self.llm.model_name,
                     info,
-                    embedding_tokens
+                    embedding_tokens,
                 )
                 msgs = self.save_results([response], process_time, save)
                 http_client.close()
@@ -412,22 +422,25 @@ class Chatgpt_4(SimpleService):
         for message in air_messages.iterator(5):
             air_message = [
                 AIMessage(content=message.content or '')
-                if message.from_model else
-                HumanMessage(content=message.content or '')
+                if message.from_model
+                else HumanMessage(content=message.content or '')
             ]
             if self.count_text_tokens(air_message) + tokens > token_limits[model_name]:
                 break
             tokens += self.count_text_tokens(air_message)
             history.append(air_message[0])
         memory = InMemoryChatMessageHistory()
-        memory.add_message(SystemMessage(
-            content=(
-                'Think step by step. Use full context. Prioritize depth, clarity, and justification. '
-                'Be thorough and expansive.\n'
-                f'{self.NO_FILE_GENERATION_POLICY}'
+        memory.add_message(
+            SystemMessage(
+                content=(
+                    'Think step by step. Use full context. Prioritize depth, clarity, and justification. '
+                    'Be thorough and expansive.\n'
+                    f'{self.NO_FILE_GENERATION_POLICY}'
+                )
             )
-        ))
-        memory.add_message(SystemMessage(
+        )
+        memory.add_message(
+            SystemMessage(
                 content=(
                     'Отныне все ответы должны быть представлены как единая строка (str). Не использовать никаких '
                     'структурированных форматов, таких как JSON, словари (dict) или списки (list). '
@@ -435,7 +448,8 @@ class Chatgpt_4(SimpleService):
                     'Не генерируй файлы и не предоставляй ссылки на скачивание файлов. '
                     'Весь контент давай прямо в тексте ответа.'
                 )
-            ))
+            )
+        )
         memory.add_messages(list(reversed(history)))
         return memory
 
@@ -454,8 +468,7 @@ class Chatgpt_4(SimpleService):
         input_cost = self.TOKENS_COST[model]['input'] * total_tokens
         if embedding_tokens > 0:
             input_cost += (
-                embedding_tokens
-                * self.TOOLS_TOKEN_COSTS[self.EMBEDDING_MODEL_FOR_BILLING]['output']
+                embedding_tokens * self.TOOLS_TOKEN_COSTS[self.EMBEDDING_MODEL_FOR_BILLING]['output']
             )
         output_cost = self.TOKENS_COST[model]['output'] * output_tokens
         if input_cost + output_cost > balance:
@@ -480,10 +493,7 @@ class Chatgpt_4(SimpleService):
         if info.get('code_interpreter', False):
             price += self.TOKENS_COST[model]['code_interpreter']
         if embedding_tokens > 0:
-            price += (
-                self.TOOLS_TOKEN_COSTS[self.EMBEDDING_MODEL_FOR_BILLING]['output']
-                * embedding_tokens
-            )
+            price += self.TOOLS_TOKEN_COSTS[self.EMBEDDING_MODEL_FOR_BILLING]['output'] * embedding_tokens
         return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
 
     def count_image_tokens(self, image_size: tuple, model_version: str = 'gpt-4o') -> int:
@@ -591,19 +601,12 @@ class Chatgpt_4(SimpleService):
             headers={'Authorization': f'Bearer {settings.OPENAI_API_KEY}'},
             timeout=600,
         ) as client:
-            resp = client.post(
-                endpoint,
-                json=json_data
-            )
+            resp = client.post(endpoint, json=json_data)
             if (
                 endpoint == 'chat/completions'
                 and (data := resp.json())
                 and data.get('choices')
-                and (
-                content := ','.join(
-                    [choice['message']['content'] for choice in data.get('choices')]
-                    )
-                )
+                and (content := ','.join([choice['message']['content'] for choice in data.get('choices')]))
             ):
                 input_tokens = resp.json()['usage']['prompt_tokens']
                 output_tokens = resp.json()['usage']['completion_tokens']
@@ -92,7 +92,6 @@ class Chatgpt_5(Chatgpt_4):
 
     TOKEN_LIMITS = {key: 200_000 for key in TOKENS_COST.keys()}
 
-
     def make(
         self,
         input_message: Message,
@@ -32,6 +32,7 @@ from tools.chats.models import Chat
 from tools.copywrite.models import Copywrite
 from tools.public_api.models import APIStore
 
+
 class Claude(SerperMixin, StreamSimpleService):
     """
     Claude Service
@@ -284,10 +285,7 @@ class Claude(SerperMixin, StreamSimpleService):
                 if (chunks_length := sum(len(chunk) for chunk in chunks)) > 20_000:
                     predict_embedding_tokens = len(chunks) * 2020
                     predicted_input_price += (
-                        (
-                            Decimal('210')
-                            + Decimal(chunks_length) / Decimal(len(chunks)) * Decimal('10')
-                        )
+                        (Decimal('210') + Decimal(chunks_length) / Decimal(len(chunks)) * Decimal('10'))
                         / Decimal('2.7')
                         * self.TOKENS_COST[version_slug]['input']
                         / Decimal('1_000_000')
@@ -354,14 +352,10 @@ class Claude(SerperMixin, StreamSimpleService):
         }
         reasoning_effort = callback_data['reasoning']['effort']
         reasoning_input_tokens = (
-            {'low': 150, 'medium': 250}.get(reasoning_effort, 0)
-            if version_slug == 'claude-fable-5'
-            else 0
+            {'low': 150, 'medium': 250}.get(reasoning_effort, 0) if version_slug == 'claude-fable-5' else 0
         )
         reasoning_output_reserve = (
-            {'low': 300, 'medium': 500}.get(reasoning_effort, 0)
-            if version_slug == 'claude-fable-5'
-            else 0
+            {'low': 300, 'medium': 500}.get(reasoning_effort, 0) if version_slug == 'claude-fable-5' else 0
         )
         estimated_input_tokens = (
             Decimal(
@@ -375,9 +369,7 @@ class Claude(SerperMixin, StreamSimpleService):
             + reasoning_input_tokens
         )
         predicted_input_price += (
-            estimated_input_tokens
-            * self.TOKENS_COST[version_slug]['input']
-            / Decimal('1_000_000')
+            estimated_input_tokens * self.TOKENS_COST[version_slug]['input'] / Decimal('1_000_000')
             + predict_embedding_tokens * self.TOOLS_TOKEN_COSTS['text-embedding-3-small']['output']
         )
 
@@ -67,7 +67,7 @@ class Deepseek(SimpleService):
         messages = [
             {'role': 'system', 'content': system_prompt},
             *self.get_chat_history(),
-            {'role': 'user', 'content': input_message.content}
+            {'role': 'user', 'content': input_message.content},
         ]
 
         start_time = time.time()
@@ -83,15 +83,15 @@ class Deepseek(SimpleService):
 
         return msgs
 
-
-
-    def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500) -> list[dict[str, str | list]]:
+    def get_chat_history(
+        self, message_limit: int = 10, max_character_limit: int = 1500
+    ) -> list[dict[str, str | list]]:
         if isinstance(self.store, Chat):
             air_messages = list(
                 reversed(
                     Message.objects.filter(
                         chats_chats_messages=self.store, is_deleted=False, is_sent=True
-                    ).order_by('-created_at')[1:message_limit + 1]
+                    ).order_by('-created_at')[1 : message_limit + 1]
                 )
             )
         elif isinstance(self.store, APIStore):
@@ -117,4 +117,3 @@ class Deepseek(SimpleService):
         while character_length > max_character_limit:
             character_length -= len(memory.pop(0)['content'])
         return memory
-
@@ -39,7 +39,7 @@ class Dola_Seed(SimpleService):
             'long_prompt': {
                 'input': Decimal('500'),
                 'output': Decimal('3000'),
-            }
+            },
         },
         'seed-2-0-mini': {
             'short_prompt': {
@@ -49,7 +49,7 @@ class Dola_Seed(SimpleService):
             'long_prompt': {
                 'input': Decimal('100'),
                 'output': Decimal('400'),
-            }
+            },
         },  # 1M tokens
     }
 
@@ -124,11 +124,7 @@ class Dola_Seed(SimpleService):
             raise GenerationException
         data = json.loads(result.stdout)
         video_stream = next(
-            (
-                stream
-                for stream in data.get('streams', [])
-                if stream.get('codec_type') == 'video'
-            ),
+            (stream for stream in data.get('streams', []) if stream.get('codec_type') == 'video'),
             None,
         )
         if not video_stream:
@@ -136,9 +132,7 @@ class Dola_Seed(SimpleService):
         duration = float(data.get('format', {}).get('duration') or 0)
         if duration <= 0:
             raise GenerationException
-        fps = cls._parse_video_fps(
-            video_stream.get('r_frame_rate') or video_stream.get('avg_frame_rate')
-        )
+        fps = cls._parse_video_fps(video_stream.get('r_frame_rate') or video_stream.get('avg_frame_rate'))
         return int(video_stream['width']), int(video_stream['height']), duration, fps
 
     @staticmethod
@@ -158,7 +152,7 @@ class Dola_Seed(SimpleService):
 
     def calculate_price(self, version: str, input_tokens: int, output_tokens: int) -> Decimal:
         price_map = self.TOKENS_COST[version]
-        prompt_type = "short_prompt" if input_tokens <= 128_000 else "long_prompt"
+        prompt_type = 'short_prompt' if input_tokens <= 128_000 else 'long_prompt'
         price = (
             input_tokens * price_map[prompt_type]['input'] / 1_000_000
             + output_tokens * price_map[prompt_type]['output'] / 1_000_000
@@ -179,9 +173,7 @@ class Dola_Seed(SimpleService):
 
         return msgs
 
-    def _prepare_data(
-        self, input_message: Message
-    ) -> tuple[str, dict[str, Any], list[dict[str, Any]]]:
+    def _prepare_data(self, input_message: Message) -> tuple[str, dict[str, Any], list[dict[str, Any]]]:
         info = input_message.info.copy()
         version = info.pop('version', None)
         if version is None or version not in self.TOKENS_COST:
@@ -207,9 +199,7 @@ class Dola_Seed(SimpleService):
                 with Image.open(BytesIO(file_bytes)) as normalized_image:
                     image_width, image_height = normalized_image.size
             elif attachment_type == 'video_url':
-                video_width, video_height, video_duration, video_fps = self._get_video_metadata(
-                    file_bytes
-                )
+                video_width, video_height, video_duration, video_fps = self._get_video_metadata(file_bytes)
             content.append({'type': attachment_type, attachment_type: {'url': file.url}})
         messages.append({'role': 'user', 'content': content})
         api_model = self.VERSION_MAPPING[version]
@@ -221,9 +211,7 @@ class Dola_Seed(SimpleService):
             else:
                 texts.append(
                     ''.join(
-                        str(item.get('text') or '')
-                        for item in message_content
-                        if isinstance(item, dict)
+                        str(item.get('text') or '') for item in message_content if isinstance(item, dict)
                     )
                 )
         predicted_input_tokens = BytedanceModelArkAdapter.batch_tokenize(api_model, texts)
@@ -274,7 +262,7 @@ class Dola_Seed(SimpleService):
             callback_data=callback_data,
             content_type=BytedanceContentType.CHAT,
             messages=messages,
-            include_reasoning=True
+            include_reasoning=True,
         )
 
         process_time = timedelta(seconds=(time.time() - start_time))
@@ -327,13 +315,9 @@ class Dola_Seed(SimpleService):
                             input_text_parts.append(content)
                         else:
                             input_text_parts.extend(
-                                str(item.get('text') or '')
-                                for item in content
-                                if isinstance(item, dict)
+                                str(item.get('text') or '') for item in content if isinstance(item, dict)
                             )
-                    input_tokens = BytedanceModelArkAdapter.tokenize(
-                        model, ''.join(input_text_parts)
-                    )
+                    input_tokens = BytedanceModelArkAdapter.tokenize(model, ''.join(input_text_parts))
                     output_tokens = BytedanceModelArkAdapter.tokenize(model, result)
                 process_time = timedelta(seconds=(time.time() - start_time))
                 self.handle_invoice(
@@ -355,7 +339,7 @@ class Dola_Seed(SimpleService):
                 reversed(
                     Message.objects.filter(
                         chats_chats_messages=self.store, is_deleted=False, is_sent=True
-                    ).order_by('-created_at')[1:message_limit + 1]
+                    ).order_by('-created_at')[1 : message_limit + 1]
                 )
             )
         elif isinstance(self.store, APIStore):
@@ -72,10 +72,7 @@ class Elevenlabs(SimpleService):
             raw_file_extension = kind.extension
             file_extension = file_service.get_file_extension(raw_file_extension, file_bytes)
             if file_extension in ('pdf', 'doc', 'docx'):
-                raw_text = (
-                    file_service.get_file_data(file_extension, file_bytes)
-                    .replace('\n', ' ')
-                )
+                raw_text = file_service.get_file_data(file_extension, file_bytes).replace('\n', ' ')
             else:
                 raise FileExtensionNotSupported(['PDF', 'DOC', 'DOCX'])
         max_affordable_chars = max(
@@ -61,6 +61,21 @@ class Flux(SimpleService):
 
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         start_time = time.time()
+        version = 'flux-schnell'
+        user_prompt = self.translate_prompt(input_message.content)
+        callback_data = dict(
+            {
+                'prompt': f'{user_prompt}\n{self.OPTIMIZATION_PROMPT}',
+                'go_fast': False,
+                'output_quality': 100,
+                **input_message.info,
+            }
+        )
+        runner = replicate_run(
+            f'{self._CALLBACK_BASE}{version}',
+            callback_data,
+        )
+        images = runner if isinstance(runner, list) else [runner]
         output_megapixels = 1
         callback_data = {
             'prompt': input_message.content,
@@ -12,8 +12,12 @@ from django.core.files import File
 from django.core.files.images import get_image_dimensions
 
 from messages.models import Message
-from ml_model.exceptions import PredictionInterruptedError, RequestBlocked, GenerationException, \
-    FileExtensionNotSupported
+from ml_model.exceptions import (
+    PredictionInterruptedError,
+    RequestBlocked,
+    GenerationException,
+    FileExtensionNotSupported,
+)
 from ml_model.exceptions import ModelVersionNotAvailable
 from ml_model.services.base import SimpleService
 from ml_model.tasks import replicate_run
@@ -39,9 +43,9 @@ class Flux_2(SimpleService):
     def calculate_price(self, version: str, input_mp: int, output_mp: int) -> Decimal:
         version_price = self.TOKENS_COST[version]
         price = (
-            version_price.get('run', Decimal('0')) +
-            version_price['input_mp'] * input_mp +
-            version_price['output_mp'] * output_mp
+            version_price.get('run', Decimal('0'))
+            + version_price['input_mp'] * input_mp
+            + version_price['output_mp'] * output_mp
         )
         return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
 
@@ -73,7 +77,7 @@ class Flux_2(SimpleService):
             raise ModelVersionNotAvailable(version, self.TOKENS_COST)
         width = input_message.info.pop('width', 1024)
         height = input_message.info.pop('height', 1024)
-        output_mp = math.ceil((width*height) / 1_000_000)
+        output_mp = math.ceil((width * height) / 1_000_000)
         callback_data = {
             'prompt': input_message.content,
             'aspect_ratio': 'custom',
@@ -95,12 +99,14 @@ class Flux_2(SimpleService):
             with BytesIO() as buf:
                 normalized_image.save(buf, format=format)
                 file_width, file_height = get_image_dimensions(buf)
-                input_mp = math.ceil((file_width*file_height) / 1_000_000)
+                input_mp = math.ceil((file_width * file_height) / 1_000_000)
                 image = f'data:image/{format};base64,{base64.b64encode(buf.getvalue()).decode("utf-8")}'
             normalized_image.close()
             callback_data.update({'input_images': [image]})
         images = [replicate_run(f'black-forest-labs/{version}', callback_data)]
         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)
+        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)
         return msgs
@@ -65,7 +65,7 @@ class Fluxpulid(SimpleService):
         translated_prompt = self.translate_prompt(input_message.content)
         callback_data = dict(
             {
-                'prompt': f"{translated_prompt}\n{self.OPTIMIZATION_PROMPT}",
+                'prompt': f'{translated_prompt}\n{self.OPTIMIZATION_PROMPT}',
                 'main_face_image': BytesIO(input_message.file.read()),
                 'output_quality': 100,
                 'output_format': 'png',
@@ -24,7 +24,6 @@ from tools.copywrite.models import Copywrite
 from tools.public_api.models import APIStore
 
 
-
 class Gemini_3_1(StreamSimpleService):
     TOKENS_COST = {
         'gemini-3.1-pro-preview': {
@@ -36,14 +35,16 @@ class Gemini_3_1(StreamSimpleService):
             'input': Decimal('75'),
             'output': Decimal('450'),
             'highest_prices': {'input': Decimal('75'), 'output': Decimal('450')},
-        }
+        },
     }
 
     TOOLS_TOKEN_COSTS = {'text-embedding-3-small': {'output': Decimal('0.00001')}}
 
     SUPPORTED_EXTENSIONS = ['PDF', 'DOC', 'DOCX', 'XLSX', 'JPG', 'JPEG', 'PNG', 'WEBP']
 
-    def calculate_price(self, version: str, input_tokens: int, output_tokens: int, embedding_tokens: int) -> Decimal:
+    def calculate_price(
+        self, version: str, input_tokens: int, output_tokens: int, embedding_tokens: int
+    ) -> Decimal:
         price_map = self.TOKENS_COST[version]
         if input_tokens >= 200_000 or output_tokens >= 200_000:
             price = (
@@ -177,9 +178,7 @@ class Gemini_3_1(StreamSimpleService):
             character_length -= len(memory.pop(0)['content'])
         return memory
 
-    def _prepare_messages(
-        self, input_message: Message
-    ) -> tuple[list[dict[str, str | list]], int]:
+    def _prepare_messages(self, input_message: Message) -> tuple[list[dict[str, str | list]], int]:
         messages = self.get_chat_history()
         messages.insert(
             0,
@@ -129,7 +129,7 @@ class Gptimage(SimpleService):
         for proxy in Proxy.objects.all():
             moderation = 'low' if self.store.user.account_type == 'regular' else 'auto'
             json_data = {
-                'prompt': f"{input_message.content}\n{self.OPTIMIZATION_PROMPT}",
+                'prompt': f'{input_message.content}\n{self.OPTIMIZATION_PROMPT}',
                 'model': 'gpt-image-2',
                 'n': 1,
                 'quality': quality,
@@ -32,6 +32,7 @@ class Grok(SerperMixin, StreamSimpleService):
     TOKENS_COST = {
         'grok-4.3': {'input': Decimal('875'), 'output': Decimal('1750'), 'coefficient': Decimal('5')},
         'grok-4.5': {'input': Decimal('1000'), 'output': Decimal('3000'), 'coefficient': Decimal('5')},
+        'grok-4.6': {'input': Decimal('600'), 'output': Decimal('1800'), 'coefficient': Decimal('5')},
     }
 
     TOOLS_TOKEN_COSTS = {'text-embedding-3-small': {'output': Decimal('0.00001')}}
@@ -194,10 +195,7 @@ class Grok(SerperMixin, StreamSimpleService):
                 if (chunks_length := sum(len(chunk) for chunk in chunks)) > 20_000:
                     predict_embedding_tokens = len(chunks) * 2020
                     predicted_input_price += (
-                        (
-                            Decimal('210')
-                            + Decimal(chunks_length) / Decimal(len(chunks)) * Decimal('10')
-                        )
+                        (Decimal('210') + Decimal(chunks_length) / Decimal(len(chunks)) * Decimal('10'))
                         / Decimal('2.0')
                         * self.TOKENS_COST[version]['input']
                         / Decimal('1_000_000')
@@ -251,21 +249,14 @@ class Grok(SerperMixin, StreamSimpleService):
         if image:
             predicted_image_tokens = min((image_width * image_height + 999) // 1000, 2500)
             predicted_input_price += (
-                Decimal(predicted_image_tokens)
-                * self.TOKENS_COST[version]['input']
-                / Decimal('1_000_000')
+                Decimal(predicted_image_tokens) * self.TOKENS_COST[version]['input'] / Decimal('1_000_000')
             )
-        estimated_input_tokens = (
-            Decimal(
-                sum(
-                    len(message['content']) if isinstance(message['content'], str) else 0
-                    for message in messages
-                )
-                + (len(input_message.content) if image else 0)
+        estimated_input_tokens = Decimal(
+            sum(
+                len(message['content']) if isinstance(message['content'], str) else 0 for message in messages
             )
-            / Decimal('2.0')
-            + (150 if is_free_plan else 250)
-        )
+            + (len(input_message.content) if image else 0)
+        ) / Decimal('2.0') + (150 if is_free_plan else 250)
         predicted_input_price += (
             estimated_input_tokens * self.TOKENS_COST[version]['input'] / Decimal('1_000_000')
             + predict_embedding_tokens * self.TOOLS_TOKEN_COSTS['text-embedding-3-small']['output']
@@ -31,7 +31,6 @@ class Grok_4_1_Fast(SimpleService):
 
     MAX_PIXELS = 178956970
 
-
     def calculate_price(self, input_tokens: int, output_tokens: int, embedding_tokens: int) -> Decimal:
         price = (
             input_tokens * self.TOKENS_COST['input'] / 1_000_000
@@ -115,10 +114,7 @@ class Grok_4_1_Fast(SimpleService):
                     raise ImageTooLargeError(self.MAX_PIXELS)
 
                 mime = kind.mime if kind else 'application/octet-stream'
-                image_url = (
-                    f'data:{mime};base64,'
-                    f'{base64.b64encode(file_bytes).decode("utf-8")}'
-                )
+                image_url = f'data:{mime};base64,{base64.b64encode(file_bytes).decode("utf-8")}'
 
                 messages[-1]['content'] = [
                     {'type': 'text', 'text': input_message.content},
@@ -21,14 +21,8 @@ from payments.selectors.payment_plan_selector import PaymentPlanSelector
 
 class Hailuo(SimpleService):
     TOKENS_COST = {
-        'hailuo-2.3': {
-            '768p': Decimal('84'),
-            '1080p': Decimal('147')
-        },
-        'hailuo-2.3-fast': {
-            '768p': Decimal('57'),
-            '1080p': Decimal('99')
-        }
+        'hailuo-2.3': {'768p': Decimal('84'), '1080p': Decimal('147')},
+        'hailuo-2.3-fast': {'768p': Decimal('57'), '1080p': Decimal('99')},
     }
 
     def calculate_price(self, version: str, resolution: str) -> Decimal:
@@ -58,12 +52,15 @@ class Hailuo(SimpleService):
         if version is None or version not in self.TOKENS_COST:
             raise ModelVersionNotAvailable(version, self.TOKENS_COST)
         resolution = input_message.info.get('resolution', '768p')
-        if (
-            (balance := PaymentPlanSelector(self.store.user).get_current_balance())
-            < (cost := self.TOKENS_COST[version][resolution])
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (
+            cost := self.TOKENS_COST[version][resolution]
         ):
             raise InsufficientBalance(balance, cost)
-        callback_data = {'prompt': self.translate_prompt(input_message.content), 'duration': 6, **input_message.info}
+        callback_data = {
+            'prompt': self.translate_prompt(input_message.content),
+            'duration': 6,
+            **input_message.info,
+        }
         if input_message.file:
             kind = filetype.guess(input_message.file.read(20))
             mime = kind.mime if kind else 'application/octet-stream'
@@ -72,10 +69,7 @@ class Hailuo(SimpleService):
             input_message.file.close()
             callback_data.update({'first_frame_image': image})
         start_time = time.time()
-        video = replicate_run(
-            f'minimax/{version}',
-            callback_data
-        )
+        video = replicate_run(f'minimax/{version}', callback_data)
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, version=version, resolution=resolution)
         msgs = self.save_results(input_message.content, process_time, video, save)
@@ -68,10 +68,9 @@ class Ideogram(SimpleService):
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         start_time = time.time()
         version = 'ideogram-v3-turbo'
-        if (
-            input_message.info.get('style_preset', 'None') != 'None'
-            and input_message.info.get('style_type', 'None') not in ('None', 'Auto', 'General')
-        ):
+        if input_message.info.get('style_preset', 'None') != 'None' and input_message.info.get(
+            'style_type', 'None'
+        ) not in ('None', 'Auto', 'General'):
             raise InvalidStyleCombinationError
         callback_data = dict(
             {
@@ -47,11 +47,15 @@ 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})
+        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)
@@ -26,23 +26,20 @@ class Llama(SimpleService):
     """
 
     TOKENS_COST = {
-        'llama-3.3-70b-instruct': {
-            'input': Decimal('84'),
-            'output': Decimal('84')
-        },  # 1M tokens
+        'llama-3.3-70b-instruct': {'input': Decimal('84'), 'output': Decimal('84')},  # 1M tokens
         'llama-4-maverick': {
             'input': Decimal('180'),
             'output': Decimal('180'),
-            'input_imgs': Decimal('200.52')
+            'input_imgs': Decimal('200.52'),
         },  # 1M tokens
     }
 
     def calculate_price(
-            self, version: str, input_tokens: int, output_tokens: int, image: FieldFile
+        self, version: str, input_tokens: int, output_tokens: int, image: FieldFile
     ) -> Decimal:
         price_map = self.TOKENS_COST[version.split('/')[1]]
         price = (
-                input_tokens * price_map['input'] / 1_000_000 + output_tokens * price_map['output'] / 1_000_000
+            input_tokens * price_map['input'] / 1_000_000 + output_tokens * price_map['output'] / 1_000_000
         )
         if image:
             price += price_map['input_imgs'] / 1_000
@@ -97,13 +94,15 @@ class Llama(SimpleService):
         msgs = self.save_results(result[0], process_time)
         return msgs
 
-    def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500) -> list[dict[str, str | list]]:
+    def get_chat_history(
+        self, message_limit: int = 10, max_character_limit: int = 1500
+    ) -> list[dict[str, str | list]]:
         if isinstance(self.store, Chat):
             air_messages = list(
                 reversed(
                     Message.objects.filter(
                         chats_chats_messages=self.store, is_deleted=False, is_sent=True
-                    ).order_by('-created_at')[1:message_limit + 1]
+                    ).order_by('-created_at')[1 : message_limit + 1]
                 )
             )
         elif isinstance(self.store, APIStore):
@@ -65,7 +65,9 @@ class Ltx(SimpleService):
                 'prompt': input_message.content,
                 'resolution': resolution,
                 'duration': duration,
-                'camera_motion': camera_motion[input_message.info.pop('camera_motion', 'Без движения камеры')],
+                'camera_motion': camera_motion[
+                    input_message.info.pop('camera_motion', 'Без движения камеры')
+                ],
                 **input_message.info,
             }
         )
@@ -81,7 +81,7 @@ class Midjourney(SimpleService):
         OUTPUT:
         Return ONLY a single concise image-generation prompt describing the final scene.
         """
-        callback_data = dict(prompt=activation_prompt, prompt_optimizer=False,**input_message.info)
+        callback_data = dict(prompt=activation_prompt, prompt_optimizer=False, **input_message.info)
         results = replicate_run(self._CALLBACK, callback_data)
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, input_message=input_message)
@@ -43,7 +43,9 @@ class Minimaxvideo(SimpleService):
 
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         version = 'video-01'
-        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < self.TOKENS_COST[version]:
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < self.TOKENS_COST[
+            version
+        ]:
             raise InsufficientBalance(balance, self.TOKENS_COST[version])
         callback_data = dict({'prompt': input_message.content, **input_message.info})
         if input_message.file:
@@ -29,7 +29,7 @@ class MinIOService:
             endpoint=settings.MINIO_ENDPOINT,
             access_key=settings.MINIO_ACCESS_KEY,
             secret_key=settings.MINIO_SECRET_KEY,
-            secure=settings.MINIO_USE_HTTPS
+            secure=settings.MINIO_USE_HTTPS,
         )
 
     def put_object(self, obj: BytesIO, filename: str, dest: str) -> str:
@@ -23,23 +23,19 @@ class Perplexity(SimpleService):
     """
 
     TOKENS_COST = {
-        'sonar': {
-            'input': Decimal('300'),
-            'output': Decimal('300'),
-            'search': Decimal('1500')
-        }, # 1M tokens
+        'sonar': {'input': Decimal('300'), 'output': Decimal('300'), 'search': Decimal('1500')},  # 1M tokens
         'sonar-deep-research': {
             'input': Decimal('600'),  # 1M tokens
-            'output': Decimal('2400'), # 1M tokens
-            'citation': Decimal('600'), # 1M tokens
-            'search': Decimal('1500'), # 1K queries
-            'reasoning': Decimal('900') # 1M tokens
+            'output': Decimal('2400'),  # 1M tokens
+            'citation': Decimal('600'),  # 1M tokens
+            'search': Decimal('1500'),  # 1K queries
+            'reasoning': Decimal('900'),  # 1M tokens
         },
         'sonar-pro-search': {
             'input': Decimal('900'),  # 1M tokens
             'output': Decimal('4500'),  # 1M tokens
             'search': Decimal('5400'),  # 1K queries
-        }
+        },
     }
 
     def calculate_price(self, version: str, input_tokens: int, output_tokens: int) -> Decimal:
@@ -78,9 +74,11 @@ class Perplexity(SimpleService):
         try:
             for proxy in Proxy.objects.all():
                 response = httpx.post(
-                    url='https://openrouter.ai/api/v1/chat/completions', headers={'Authorization': f'Bearer {settings.OPENROUTER_API_KEY}'},
-                    proxy=f'{proxy.protocol}://{proxy.address}', timeout=600,
-                    json={'model':  version, 'messages': messages, **callback_data}
+                    url='https://openrouter.ai/api/v1/chat/completions',
+                    headers={'Authorization': f'Bearer {settings.OPENROUTER_API_KEY}'},
+                    proxy=f'{proxy.protocol}://{proxy.address}',
+                    timeout=600,
+                    json={'model': version, 'messages': messages, **callback_data},
                 )
                 if response.status_code not in (200, 201):
                     raise
@@ -91,17 +89,25 @@ class Perplexity(SimpleService):
                     content = (
                         re.sub(
                             r'\[(\d+)\]',
-                            lambda m: f' [[{m.group(1)}]]({str(annotations[int(m.group(1)) - 1]["url_citation"]["url"])})',
-                            content
+                            lambda m: (
+                                f' [[{m.group(1)}]]({str(annotations[int(m.group(1)) - 1]["url_citation"]["url"])})'
+                            ),
+                            content,
                         )
-                        + f'\n\n### Ресурсы:\n{"\n".join(
-                            [
-                                f'{num}. {a["url_citation"]["title"]} ({a["url_citation"]["url"]})'
-                                for num, a in enumerate(annotations, start=1)
-                            ]
-                        )}'
+                        + f'\n\n### Ресурсы:\n{
+                            "\n".join(
+                                [
+                                    f"{num}. {a['url_citation']['title']} ({a['url_citation']['url']})"
+                                    for num, a in enumerate(annotations, start=1)
+                                ]
+                            )
+                        }'
                     )
-                result = [content, response['usage']['prompt_tokens'], response['usage']['completion_tokens']]
+                result = [
+                    content,
+                    response['usage']['prompt_tokens'],
+                    response['usage']['completion_tokens'],
+                ]
         except Exception:
             raise Exception(f'No answer from Perplexity, please retry later')
         process_time = timedelta(seconds=(time.time() - start_time))
@@ -114,13 +120,15 @@ class Perplexity(SimpleService):
         msgs = self.save_results(result[0], process_time)
         return msgs
 
-    def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500) -> list[dict[str, str | list]]:
+    def get_chat_history(
+        self, message_limit: int = 10, max_character_limit: int = 1500
+    ) -> list[dict[str, str | list]]:
         if isinstance(self.store, Chat):
             air_messages = list(
                 reversed(
                     Message.objects.filter(
                         chats_chats_messages=self.store, is_deleted=False, is_sent=True
-                    ).order_by('-created_at')[1:message_limit + 1]
+                    ).order_by('-created_at')[1 : message_limit + 1]
                 )
             )
         elif isinstance(self.store, APIStore):
@@ -146,4 +154,4 @@ class Perplexity(SimpleService):
         while character_length > max_character_limit:
             character_length -= len(memory.pop(0)['content'])
 
-        return memory
\ No newline at end of file
+        return memory
@@ -19,14 +19,8 @@ class Qwen(SimpleService):
     """
 
     TOKENS_COST = {
-        'qwq-32b': {
-            'input': Decimal('45'),
-            'output': Decimal('60')
-        },  # 1M tokens
-        'qwq-32b:free': {
-            'input': Decimal('0'),
-            'output': Decimal('0')
-        },  # 1M tokens
+        'qwq-32b': {'input': Decimal('45'), 'output': Decimal('60')},  # 1M tokens
+        'qwq-32b:free': {'input': Decimal('0'), 'output': Decimal('0')},  # 1M tokens
     }
 
     def calculate_price(self, version: str, input_tokens: int, output_tokens: int) -> Decimal:
@@ -73,8 +67,8 @@ class Qwen(SimpleService):
                     'На бытовые, нейтральные или социальные вопросы (например: "что делаешь?", "как дела?") можно отвечать\n'
                     'Все размышления и логика перед ответом — на русском. Другой язык разрешён только в цитатах или если вопрос явно на другом языке.\n"'
                     'Не пересматривай прошлые примеры ответов, оценивай только текущий запрос. Не повторяй одни и те же выводы многократно.'
-                )
-            }
+                ),
+            },
         )
         messages.append({'role': 'user', 'content': input_message.content})
         result = openrouter_run(version, messages, callback_data, 'Qwen')
@@ -88,13 +82,15 @@ class Qwen(SimpleService):
         msgs = self.save_results(result[0], process_time)
         return msgs
 
-    def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500) -> list[dict[str, str | list]]:
+    def get_chat_history(
+        self, message_limit: int = 10, max_character_limit: int = 1500
+    ) -> list[dict[str, str | list]]:
         if isinstance(self.store, Chat):
             air_messages = list(
                 reversed(
                     Message.objects.filter(
                         chats_chats_messages=self.store, is_deleted=False, is_sent=True
-                    ).order_by('-created_at')[1:message_limit+1]
+                    ).order_by('-created_at')[1 : message_limit + 1]
                 )
             )
         elif isinstance(self.store, APIStore):
@@ -19,18 +19,9 @@ class Qwen_235B(SimpleService):
     """
 
     TOKENS_COST = {
-        'qwen3-235b-a22b-thinking-2507': {
-            'input': Decimal('33'),
-            'output': Decimal('180')
-        },  # 1M tokens
-        'qwen3-235b-a22b-2507': {
-            'input': Decimal('24'),
-            'output': Decimal('165')
-        },  # 1M tokens
-        'qwen3-235b-a22b:free': {
-            'input': Decimal('0'),
-            'output': Decimal('0')
-        },  # 1M tokes
+        'qwen3-235b-a22b-thinking-2507': {'input': Decimal('33'), 'output': Decimal('180')},  # 1M tokens
+        'qwen3-235b-a22b-2507': {'input': Decimal('24'), 'output': Decimal('165')},  # 1M tokens
+        'qwen3-235b-a22b:free': {'input': Decimal('0'), 'output': Decimal('0')},  # 1M tokes
     }
 
     def calculate_price(self, version: str, input_tokens: int, output_tokens: int) -> Decimal:
@@ -77,8 +68,8 @@ class Qwen_235B(SimpleService):
                     'На бытовые, нейтральные или социальные вопросы (например: "что делаешь?", "как дела?") можно отвечать\n'
                     'Все размышления и логика перед ответом — на русском. Другой язык разрешён только в цитатах или если вопрос явно на другом языке.\n"'
                     'Не пересматривай прошлые примеры ответов, оценивай только текущий запрос. Не повторяй одни и те же выводы многократно.'
-                )
-            }
+                ),
+            },
         )
         messages.append({'role': 'user', 'content': input_message.content})
         result = openrouter_run(version, messages, callback_data, 'Qwen')
@@ -92,13 +83,15 @@ class Qwen_235B(SimpleService):
         msgs = self.save_results(result[0], process_time)
         return msgs
 
-    def get_chat_history(self, message_limit: int = 10, max_character_limit: int = 1500) -> list[dict[str, str | list]]:
+    def get_chat_history(
+        self, message_limit: int = 10, max_character_limit: int = 1500
+    ) -> list[dict[str, str | list]]:
         if isinstance(self.store, Chat):
             air_messages = list(
                 reversed(
                     Message.objects.filter(
                         chats_chats_messages=self.store, is_deleted=False, is_sent=True
-                    ).order_by('-created_at')[1:message_limit+1]
+                    ).order_by('-created_at')[1 : message_limit + 1]
                 )
             )
         elif isinstance(self.store, APIStore):
@@ -162,4 +162,4 @@ class Qwen_3_6(SimpleService):
         while character_length > max_character_limit:
             character_length -= len(memory.pop(0)['content'])
 
-        return memory
\ No newline at end of file
+        return memory
@@ -22,15 +22,16 @@ from tools.copywrite.models import Copywrite
 from tools.public_api.models import APIStore
 
 
-class Qwen_3_7(StreamSimpleService):
+class Qwen_3_8(StreamSimpleService):
     COEFFICIENT = Decimal('300.0')
 
     TOKENS_COST = {
+        'qwen3.8-max': {'input': Decimal('600'), 'output': Decimal('1800')},  # $2 / $6
         'qwen3.7-max': {'input': Decimal('442.5'), 'output': Decimal('1327.5')},  # $1.475 / $4.425
         'qwen3.7-plus': {'input': Decimal('96'), 'output': Decimal('384')},  # $0.32 / $1.28
     }
 
-    MAX_OUTPUT_TOKENS = 30_000
+    MAX_OUTPUT_TOKENS = 131_072 // 2
 
     TOOLS_TOKEN_COSTS = {'text-embedding-3-small': {'output': Decimal('0.00001')}}
 
@@ -80,7 +81,7 @@ class Qwen_3_7(StreamSimpleService):
         version_slug, model_slug, callback_data, messages, embedding_tokens = self._prepare_data(
             input_message
         )
-        result = openrouter_run(model_slug, messages, callback_data, 'Qwen 3.7')
+        result = openrouter_run(model_slug, messages, callback_data, 'Qwen 3.8')
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(
             input_message.content_object.model,
@@ -237,7 +238,6 @@ class Qwen_3_7(StreamSimpleService):
     def _estimate_cost(self, version_slug: str, input_tokens: int, output_tokens: int) -> float:
         price_map = self.TOKENS_COST[version_slug]
         price = (
-            input_tokens * price_map['input'] / 1_000_000
-            + output_tokens * price_map['output'] / 1_000_000
+            input_tokens * price_map['input'] / 1_000_000 + output_tokens * price_map['output'] / 1_000_000
         )
         return float(price / self.COEFFICIENT)
@@ -17,11 +17,13 @@ class Qwen_3_Max_Thinking(SimpleService):
     }
 
     def calculate_price(self, input_tokens: int, output_tokens: int) -> Decimal:
-        price = input_tokens * (
-            self.TOKENS_COST['input']['default' if input_tokens <= 32_000 else 'high'] / 1_000_000
-        ) + output_tokens * (
-            self.TOKENS_COST['output']['default' if input_tokens <= 32_000 else 'high'] / 1_000_000
-        ) + Decimal('2')
+        price = (
+            input_tokens
+            * (self.TOKENS_COST['input']['default' if input_tokens <= 32_000 else 'high'] / 1_000_000)
+            + output_tokens
+            * (self.TOKENS_COST['output']['default' if input_tokens <= 32_000 else 'high'] / 1_000_000)
+            + Decimal('2')
+        )
         return price.quantize(Decimal('0.1'), rounding='ROUND_UP')
 
     def save_results(self, content: str, time: timedelta, save: bool = True) -> list[Message]:
@@ -88,4 +90,4 @@ class Qwen_3_Max_Thinking(SimpleService):
         while character_length > max_character_limit:
             character_length -= len(memory.pop(0)['content'])
 
-        return memory
\ No newline at end of file
+        return memory
@@ -212,10 +212,10 @@ class Raifgpt(Chatgpt_4):
                         input = [
                             SystemMessage(content=user_system_prompt),
                             HumanMessage(
-                            content=(
-                                'Используй системный промпт. Содержание файла: '
-                                f'{"".join(chunk.content for chunk in chunks)}. Вопрос: {input_message.content}'
-                            )
+                                content=(
+                                    'Используй системный промпт. Содержание файла: '
+                                    f'{"".join(chunk.content for chunk in chunks)}. Вопрос: {input_message.content}'
+                                )
                             ),
                         ]
                         input_tokens += self.count_text_tokens(input)
@@ -263,11 +263,11 @@ class Raifgpt(Chatgpt_4):
         image_count = 0
         doc = None
         try:
-            doc = fitz.open(stream=pdf_data, filetype="pdf")
+            doc = fitz.open(stream=pdf_data, filetype='pdf')
             raw_texts = {}
             pages_with_image = []
             for page_num, page in enumerate(doc):
-                text = page.get_text("text")
+                text = page.get_text('text')
                 if text:
                     raw_texts[page_num] = text
                 if page.get_images():
@@ -276,28 +276,28 @@ class Raifgpt(Chatgpt_4):
                 if doc is not None:
                     doc.close()
                 fitz.TOOLS.store_shrink(100)
-                all_text = "\n".join(raw_texts.get(i, "") for i in sorted(raw_texts))
-                return all_text if all_text.strip() else "Не удалось извлечь текст из PDF"
+                all_text = '\n'.join(raw_texts.get(i, '') for i in sorted(raw_texts))
+                return all_text if all_text.strip() else 'Не удалось извлечь текст из PDF'
         except Exception as e:
             if doc is not None:
                 doc.close()
-            return f"Ошибка при чтении PDF: {e}"
+            return f'Ошибка при чтении PDF: {e}'
         try:
             batch_images = []
             page_index_map = []
             headers = {
-                "Authorization": f"Api-Key {settings.YANDEX_CLOUD_API_KEY}",
-                "Content-Type": "application/json"
+                'Authorization': f'Api-Key {settings.YANDEX_CLOUD_API_KEY}',
+                'Content-Type': 'application/json',
             }
             for page_num in pages_with_image:
                 try:
                     page = doc.load_page(page_num)
                     image_count += 1
                     pix = page.get_pixmap(dpi=150, alpha=False)
-                    img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
+                    img = Image.frombytes('RGB', [pix.width, pix.height], pix.samples)
                     img.info = {}
                     buffer = BytesIO()
-                    img.save(buffer, format="JPEG", quality=60, optimize=True)
+                    img.save(buffer, format='JPEG', quality=60, optimize=True)
                     buffer.seek(0)
                     if buffer.getbuffer().nbytes < max_batch_size:
                         batch_images.append(buffer)
@@ -308,7 +308,7 @@ class Raifgpt(Chatgpt_4):
                 if doc is not None:
                     doc.close()
                 fitz.TOOLS.store_shrink(100)
-                return "Не удалось собрать изображения из PDF."
+                return 'Не удалось собрать изображения из PDF.'
             batches = []
             current_batch = []
             current_pages = []
@@ -326,56 +326,62 @@ class Raifgpt(Chatgpt_4):
             ocr_texts = {}
             for batch, pages in batches:
                 body = {
-                    "folderId": settings.YANDEX_CLOUD_ID,
-                    "analyze_specs": [{
-                        "content": base64.b64encode(buf.getvalue()).decode(),
-                        "features": [{
-                            "type": "TEXT_DETECTION",
-                            "text_detection_config": {"language_codes": ["*"]}
-                        }]
-                    } for buf in batch]
+                    'folderId': settings.YANDEX_CLOUD_ID,
+                    'analyze_specs': [
+                        {
+                            'content': base64.b64encode(buf.getvalue()).decode(),
+                            'features': [
+                                {
+                                    'type': 'TEXT_DETECTION',
+                                    'text_detection_config': {'language_codes': ['*']},
+                                }
+                            ],
+                        }
+                        for buf in batch
+                    ],
                 }
                 resp = requests.post(
-                    "https://vision.api.cloud.yandex.net/vision/v1/batchAnalyze",
-                    headers=headers, json=body, timeout=60
+                    'https://vision.api.cloud.yandex.net/vision/v1/batchAnalyze',
+                    headers=headers,
+                    json=body,
+                    timeout=60,
                 )
                 if resp.status_code != 200:
                     continue
                 result = resp.json()
-                for i, spec_result in enumerate(result.get("results", [])):
+                for i, spec_result in enumerate(result.get('results', [])):
                     page_text = []
-                    for res in spec_result.get("results", []):
-                        for page in res.get("textDetection", {}).get("pages", []):
+                    for res in spec_result.get('results', []):
+                        for page in res.get('textDetection', {}).get('pages', []):
                             for block in page.get('blocks', []):
                                 for line in block.get('lines', []):
-                                    line_text = " ".join(
+                                    line_text = ' '.join(
                                         word.get('text', '') for word in line.get('words', [])
                                     )
                                     if line_text:
                                         page_text.append(line_text)
-                    ocr_texts[pages[i]] = "\n".join(page_text)
+                    ocr_texts[pages[i]] = '\n'.join(page_text)
             if doc is not None:
                 doc.close()
             fitz.TOOLS.store_shrink(100)
             all_pages = sorted(set(raw_texts) | set(ocr_texts))
-            final_text = "\n\n".join(
-                f"{raw_texts.get(pn, '')}\n{ocr_texts.get(pn, '')}".strip()
-                for pn in all_pages
+            final_text = '\n\n'.join(
+                f'{raw_texts.get(pn, "")}\n{ocr_texts.get(pn, "")}'.strip() for pn in all_pages
             )
             self.image_count = image_count
-            return final_text.strip() or "Не удалось распознать текст"
+            return final_text.strip() or 'Не удалось распознать текст'
         except Exception as e:
             if doc is not None:
                 doc.close()
-            return f"Не удалось обработать файл: {e}"
+            return f'Не удалось обработать файл: {e}'
 
     def make_embeddings_prompt(self, document_name: str, section_texts: List[str], question: str) -> str:
-        '''
+        """
         A method for making a prompt using found embeddings
         :param document_name: name of the loaded document
         :param section_texts: list of sections' contents
         :param question: user question
-        '''
+        """
         return f"""Ты — аналитик данных моей компании. 
         Отвечай исключительно на основе предоставленного ниже контекста. 
         НЕЛЬЗЯ использовать внешние знания или домыслы.
@@ -394,7 +400,9 @@ class Raifgpt(Chatgpt_4):
         Сформируй ПОЛНЫЙ и СТРУКТУРИРОВАННЫЙ ответ, даже если доступные данные частичные.
         """
 
-    def get_anchor_embedding(self, client: httpx.Client, content: str, anchor: str) -> Tuple[List[float], int, str]:
+    def get_anchor_embedding(
+        self, client: httpx.Client, content: str, anchor: str
+    ) -> Tuple[List[float], int, str]:
         """
         A method for converting raw text (anchor content) into embeddings
         using OpenAI API request
@@ -434,4 +442,3 @@ class Raifgpt(Chatgpt_4):
             return f'Это текст, извлечённый из загруженного WORD-файла:\n{text}'
         else:
             return 'Файл пуст или содержит изображения, из которых невозможно извлечь текст.'
-
@@ -50,11 +50,11 @@ class Reve(SimpleService):
     #     return self.PRICE[type].quantize(Decimal('0.1'), rounding='ROUND_UP')
 
     def save_results(
-            self,
-            prompt: str,
-            image: str,
-            time: timedelta,
-            save: bool = True,
+        self,
+        prompt: str,
+        image: str,
+        time: timedelta,
+        save: bool = True,
     ) -> list[Message]:
         messages: list[Message] = []
         messages.append(
@@ -19,7 +19,6 @@ from payments.selectors.payment_plan_selector import PaymentPlanSelector
 
 
 class Runway(SimpleService):
-
     TOKENS_COST = {
         'gen4-turbo': Decimal('15'),
     }
@@ -50,9 +49,8 @@ class Runway(SimpleService):
         version = 'gen4-turbo'
         duration = input_message.info.get('duration', 5)
         file = input_message.file
-        if (
-            (balance := PaymentPlanSelector(self.store.user).get_current_balance())
-            < (cost := self.calculate_price(version, duration))
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (
+            cost := self.calculate_price(version, duration)
         ):
             raise InsufficientBalance(balance, cost)
         if not file:
@@ -65,7 +63,7 @@ class Runway(SimpleService):
         callback_data = {
             'prompt': self.translate_prompt(input_message.content),
             **input_message.info,
-            'image': media
+            'image': media,
         }
         start_time = time.time()
         video = replicate_run(f'runwayml/{version}', callback_data)
@@ -205,4 +205,4 @@ class Seedance_2_Dreamina(SimpleService):
             text=True,
             check=True,
         )
-        return float(json.loads(out.stdout)["format"]["duration"])
\ No newline at end of file
+        return float(json.loads(out.stdout)['format']['duration'])
@@ -18,9 +18,7 @@ from ml_model.services.base import SimpleService
 from poller.models import Proxy
 
 
-
 class Sora(SimpleService):
-
     TOKENS_COST = {
         'sora-2': Decimal('30'),
         'sora-2-pro': Decimal('90'),
@@ -48,7 +46,7 @@ class Sora(SimpleService):
             return Message.objects.bulk_create([msg])
         return [msg]
 
-    def make(self, input_message: "Message", save: bool = True) -> list["Message"]:
+    def make(self, input_message: 'Message', save: bool = True) -> list['Message']:
         if input_message.content:
             for proxy in Proxy.objects.all():
                 version = input_message.info.pop('version', None)
@@ -59,7 +57,7 @@ class Sora(SimpleService):
                     'prompt': input_message.content,
                     'model': version,
                     'seconds': str(seconds),
-                    **input_message.info
+                    **input_message.info,
                 }
                 files = None
                 if input_message.file:
@@ -73,47 +71,39 @@ class Sora(SimpleService):
                         if current_size != required_size:
                             raise UnsupportedSize(current_size, required_size)
                         buf = BytesIO()
-                        img.save(buf, format="PNG")
+                        img.save(buf, format='PNG')
                         buf.seek(0)
-                    files = {
-                        "input_reference": (
-                            input_message.file.name,
-                            buf,
-                            mime_type
-                        )
-                    }
+                    files = {'input_reference': (input_message.file.name, buf, mime_type)}
                 with httpx.Client(
-                        base_url='https://api.openai.com/v1/',
-                        proxy=f'{proxy.protocol}://{proxy.address}' if proxy else None,
-                        headers={'Authorization': f'Bearer {settings.OPENAI_API_KEY}'},
-                        timeout=600,
+                    base_url='https://api.openai.com/v1/',
+                    proxy=f'{proxy.protocol}://{proxy.address}' if proxy else None,
+                    headers={'Authorization': f'Bearer {settings.OPENAI_API_KEY}'},
+                    timeout=600,
                 ) as client:
                     start_time = time.time()
                     if files:
-                        resp = client.post("videos", data=callback_data, files=files)
+                        resp = client.post('videos', data=callback_data, files=files)
                     else:
-                        resp = client.post("videos", json=callback_data)
+                        resp = client.post('videos', json=callback_data)
                     if resp.status_code not in (200, 201):
                         continue
                     video_info = resp.json()
-                    video_id = video_info.get("id")
+                    video_id = video_info.get('id')
                     while True:
-                        status_resp = client.get(f"videos/{video_id}")
-                        status = status_resp.json().get("status")
+                        status_resp = client.get(f'videos/{video_id}')
+                        status = status_resp.json().get('status')
                         video_data = status_resp.json()
-                        if status == "completed":
+                        if status == 'completed':
                             break
-                        if status == "failed":
-                            error_message = video_data.get("error", {}).get("message", "Unknown error")
-                            if error_message == "Your request was blocked by our moderation system.":
+                        if status == 'failed':
+                            error_message = video_data.get('error', {}).get('message', 'Unknown error')
+                            if error_message == 'Your request was blocked by our moderation system.':
                                 raise RequestBlocked
-                            raise Exception("Video generation failed")
-                        time.sleep(1/3)
-                    video = client.get(f"videos/{video_id}/content").content
+                            raise Exception('Video generation failed')
+                        time.sleep(1 / 3)
+                    video = client.get(f'videos/{video_id}/content').content
                     process_time = timedelta(seconds=(time.time() - start_time))
-                    self.handle_invoice(
-                        input_message.content_object.model, seconds, version
-                    )
+                    self.handle_invoice(input_message.content_object.model, seconds, version)
                     msgs = self.save_results(input_message.content, process_time, video, save)
                     return msgs
             raise ModelTimeoutError
@@ -35,4 +35,4 @@ class Stablediffusion(Seedream):
 
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         input_message.info = self._remap_info(input_message.info)
-        return super().make(input_message, save)
\ No newline at end of file
+        return super().make(input_message, save)
@@ -18,32 +18,29 @@ from payments.exceptions.insufficient_balance import InsufficientBalance
 from payments.selectors.payment_plan_selector import PaymentPlanSelector
 
 
-
 class Video_Test_Model(SimpleService):
-    
     RATES = {
         'per-unit': Decimal('15'),
         'per-second': Decimal('0.5'),
     }
-    
-    
-    PLACEHOLDER_URL='https://imgur.com/QPLhtj1.mp4'
 
-    def calculate_price(self, strategy: Literal['per-unit','per-second'], duration: int = 1, num_videos: int = 1) -> Decimal:
+    PLACEHOLDER_URL = 'https://imgur.com/QPLhtj1.mp4'
+
+    def calculate_price(
+        self, strategy: Literal['per-unit', 'per-second'], duration: int = 1, num_videos: int = 1
+    ) -> Decimal:
         rate = self.RATES[strategy]
         return (rate * duration * num_videos).quantize(Decimal('0.1'), rounding='ROUND_UP')
 
-
     @classmethod
     def predict_price(cls, content: str, file_exists: bool, info: dict[str, Any]) -> Decimal | None:
         num_videos = info.get('num_videos', 1)
         cps = info.get('cps', 'per-unit')
-        
+
         if cps == 'per-second':
             return None
-        
-        return cls.RATES['per-unit'] * num_videos
 
+        return cls.RATES['per-unit'] * num_videos
 
     def save_results(
         self,
@@ -66,75 +63,71 @@ class Video_Test_Model(SimpleService):
             return Message.objects.bulk_create(messages)
         return messages
 
-
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         cps = input_message.info.get('cps', 'per-unit')
         cvu = input_message.info.get('cvu') or self.PLACEHOLDER_URL
         num_videos = input_message.info.get('num_videos', 1)
-        
+
         start_time = time.time()
 
         video_bytes = self._fetch_video(cvu)
-        
+
         if cps == 'per-second':
             duration = self._get_duration(video_bytes)
         else:
             duration = 1
 
-        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (cost := self.calculate_price(cps, duration, num_videos)):
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < (
+            cost := self.calculate_price(cps, duration, num_videos)
+        ):
             raise InsufficientBalance(balance, cost)
-        
-        
+
         videos = [video_bytes] * num_videos
-        
+
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, cps, duration, num_videos)
-        
+
         msgs = self.save_results(input_message.content, process_time, videos, save)
         return msgs
 
-
     def _fetch_video(self, url: str):
         headers = {
-            "User-Agent": (
-                "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
-                "AppleWebKit/537.36 (KHTML, like Gecko) "
-                "Chrome/137.0 Safari/537.36"
+            'User-Agent': (
+                'Mozilla/5.0 (Windows NT 10.0; Win64; x64) '
+                'AppleWebKit/537.36 (KHTML, like Gecko) '
+                'Chrome/137.0 Safari/537.36'
             )
         }
         try:
-            response = requests.get(
-                url,
-                headers=headers,
-                timeout=600
-            )
+            response = requests.get(url, headers=headers, timeout=600)
             response.raise_for_status()
         except requests.RequestException as exc:
             raise InvalidParameterError(f'Invalid video URL: {exc}')
-        
+
         kind = filetype.guess(response.content[:120])
-        
+
         if not kind:
             raise CorruptedFileError
-        
+
         if not kind.mime.startswith('video/'):
             raise InvalidParameterError('Video format not supported')
-            
+
         return response.content
-        
 
     def _get_duration(self, video_bytes: bytes) -> int:
         result = subprocess.run(
             [
-                "ffprobe",
-                "-v", "quiet",
-                "-print_format", "json",
-                "-show_format",
-                "-",
+                'ffprobe',
+                '-v',
+                'quiet',
+                '-print_format',
+                'json',
+                '-show_format',
+                '-',
             ],
             input=video_bytes,
             capture_output=True,
         )
 
         data = json.loads(result.stdout)
-        return math.ceil(float(data["format"]["duration"]))
\ No newline at end of file
+        return math.ceil(float(data['format']['duration']))
@@ -42,7 +42,9 @@ class Wan_Lite(SimpleService):
 
     def make(self, input_message: Message, save: bool = True) -> list[Message]:
         resolution = input_message.info.pop('resolution', '720p')
-        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < self.TOKENS_COST[resolution]:
+        if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < self.TOKENS_COST[
+            resolution
+        ]:
             raise InsufficientBalance(balance, self.TOKENS_COST[resolution])
         callback_data = dict(
             {
@@ -59,103 +59,103 @@ In sit amet nunc sed urna aliquet vehicula id vel justo. Duis vel massa eleifend
 """
 
 ANCHORS = {
-    "authors": (
-        "автор|авторы|составители|подготовители|команда|коллектив|исследователь|"
-        "исследователи|авторский коллектив|writer|researcher|investigator|"
-        "contributors|исполнители|ответственные лица|authorship|авторство|"
-        "group|team|authorship team",
-        2
-    ),
-    "topic": (
-        "тема исследования|предмет исследования|тема работы|цель исследования|"
-        "предмет|направление|scope|research topic|subject of study|research focus|"
-        "object of study|scientific problem|область исследования|problem statement",
-        2
-    ),
-    "summary": (
-        "краткое содержание|основные выводы|итоги исследования|summary|conclusions|"
-        "executive summary|highlights|abstract|overview|synopsis|выводы|"
-        "резюме|summary statement",
-        6
-    ),
-    "volume": (
-        "объем рынка|market size|размер рынка|объем продаж|общие показатели|"
-        "объем инвестиций|total volume|market volume|рыночная капитализация|"
-        "оборот|объем финансирования|масштаб рынка|market capacity",
-        4
-    ),
-    "forecast": (
-        "прогноз|forecast|прогнозные показатели|ожидания|перспективы|outlook|"
-        "прогноз развития|predicted values|прогноз роста|прогноз падения|"
-        "future outlook|прогноз на следующий год|прогноз на 3-5 лет",
-        4
-    ),
-    "growth_drivers": (
-        "драйверы роста|факторы роста|причины роста|growth drivers|"
-        "growth factors|catalysts|key drivers|стимулирующие факторы|"
-        "факторы развития|движущие силы|причины повышения|рост рынка|growth enablers",
-        4
-    ),
-    "barriers": (
-        "барьеры|препятствия|ограничения|риски|сложности|ограничения рынка|"
-        "barriers|obstacles|challenges|risks|факторы замедления|факторы риска|"
-        "рисковые факторы|проблемы|тормозящие развитие|негативные факторы",
-        4
-    ),
-    "regulations": (
-        "регуляторные изменения|законодательство|нормативные акты|регулирование|"
-        "compliance|laws|regulations|legal changes|закон|правила|постановления|"
-        "стандарты|регулирующие органы|политические инициативы|правовые нормы",
-        4
-    ),
-    "segmentation": (
-        "сегментация|разделение рынка|сегменты|группы клиентов|customer segments|"
-        "market segmentation|категории|подразделения|типы клиентов|демографические"
-        " группы|целевые аудитории|сегментация по регионам|product segmentation",
-        4
-    ),
-    "players": (
-        "игроки рынка|компании|корпорации|основные участники|конкуренты|market "
-        "players|key companies|competitors|поставщики|лидеры рынка|крупные компании|"
-        "бизнес-игроки|участники рынка|основные бренды",
-        4
-    ),
-    "quant_metrics": (
-        "количественные метрики|числовые показатели|quantitative metrics|цифры|"
-        "data points|измерения|показатели|объемы|количество сделок|темпы роста|"
-        "проценты|значения|финансовые показатели|статистика",
-        2
-    ),
-    "qual_metrics": (
-        "качественные метрики|качественные показатели|qualitative metrics|оценки"
-        "|факторы оценки|quality indicators|мнение экспертов|экспертные оценки|"
-        "восприятие|качественные данные|отзывы|качественный анализ",
-        2
-    ),
-    "cases": (
-        "кейсы|примеры|практические примеры|case studies|examples|use cases|"
-        "проекты|сценарии|успешные истории|best practices|опыт применения",
-        1
-    ),
-    "charts": (
-        "графики|диаграммы|charts|diagrams|visualizations|plots|иллюстрации|"
-        "схемы|инфографика|data visualization|charts and graphs",
-        1
-    ),
-    "tables": (
-        "таблицы|data tables|таблицы данных|spreadsheets|matrices|таблицы с данными|"
-        "табличные данные|списки|структуры данных|табличное представление",
-        1
-    ),
-    "methodology": (
-        "методология|методы исследования|approach|methodology|methods|techniques|"
-        "исследовательские методы|методики|способы анализа|процедура|процесс исследования",
-        1
-    ),
-    "interviews": (
-        "интервью|мнения экспертов|комментарии|expert interviews|expert opinions|"
-        "statements|reviews|опросы|интервью с экспертами|экспертные отзывы|"
-        "интервьюирование|отзывы участников",
-        1
+    'authors': (
+        'автор|авторы|составители|подготовители|команда|коллектив|исследователь|'
+        'исследователи|авторский коллектив|writer|researcher|investigator|'
+        'contributors|исполнители|ответственные лица|authorship|авторство|'
+        'group|team|authorship team',
+        2,
+    ),
+    'topic': (
+        'тема исследования|предмет исследования|тема работы|цель исследования|'
+        'предмет|направление|scope|research topic|subject of study|research focus|'
+        'object of study|scientific problem|область исследования|problem statement',
+        2,
+    ),
+    'summary': (
+        'краткое содержание|основные выводы|итоги исследования|summary|conclusions|'
+        'executive summary|highlights|abstract|overview|synopsis|выводы|'
+        'резюме|summary statement',
+        6,
+    ),
+    'volume': (
+        'объем рынка|market size|размер рынка|объем продаж|общие показатели|'
+        'объем инвестиций|total volume|market volume|рыночная капитализация|'
+        'оборот|объем финансирования|масштаб рынка|market capacity',
+        4,
+    ),
+    'forecast': (
+        'прогноз|forecast|прогнозные показатели|ожидания|перспективы|outlook|'
+        'прогноз развития|predicted values|прогноз роста|прогноз падения|'
+        'future outlook|прогноз на следующий год|прогноз на 3-5 лет',
+        4,
+    ),
+    'growth_drivers': (
+        'драйверы роста|факторы роста|причины роста|growth drivers|'
+        'growth factors|catalysts|key drivers|стимулирующие факторы|'
+        'факторы развития|движущие силы|причины повышения|рост рынка|growth enablers',
+        4,
+    ),
+    'barriers': (
+        'барьеры|препятствия|ограничения|риски|сложности|ограничения рынка|'
+        'barriers|obstacles|challenges|risks|факторы замедления|факторы риска|'
+        'рисковые факторы|проблемы|тормозящие развитие|негативные факторы',
+        4,
+    ),
+    'regulations': (
+        'регуляторные изменения|законодательство|нормативные акты|регулирование|'
+        'compliance|laws|regulations|legal changes|закон|правила|постановления|'
+        'стандарты|регулирующие органы|политические инициативы|правовые нормы',
+        4,
+    ),
+    'segmentation': (
+        'сегментация|разделение рынка|сегменты|группы клиентов|customer segments|'
+        'market segmentation|категории|подразделения|типы клиентов|демографические'
+        ' группы|целевые аудитории|сегментация по регионам|product segmentation',
+        4,
+    ),
+    'players': (
+        'игроки рынка|компании|корпорации|основные участники|конкуренты|market '
+        'players|key companies|competitors|поставщики|лидеры рынка|крупные компании|'
+        'бизнес-игроки|участники рынка|основные бренды',
+        4,
+    ),
+    'quant_metrics': (
+        'количественные метрики|числовые показатели|quantitative metrics|цифры|'
+        'data points|измерения|показатели|объемы|количество сделок|темпы роста|'
+        'проценты|значения|финансовые показатели|статистика',
+        2,
+    ),
+    'qual_metrics': (
+        'качественные метрики|качественные показатели|qualitative metrics|оценки'
+        '|факторы оценки|quality indicators|мнение экспертов|экспертные оценки|'
+        'восприятие|качественные данные|отзывы|качественный анализ',
+        2,
+    ),
+    'cases': (
+        'кейсы|примеры|практические примеры|case studies|examples|use cases|'
+        'проекты|сценарии|успешные истории|best practices|опыт применения',
+        1,
+    ),
+    'charts': (
+        'графики|диаграммы|charts|diagrams|visualizations|plots|иллюстрации|'
+        'схемы|инфографика|data visualization|charts and graphs',
+        1,
+    ),
+    'tables': (
+        'таблицы|data tables|таблицы данных|spreadsheets|matrices|таблицы с данными|'
+        'табличные данные|списки|структуры данных|табличное представление',
+        1,
+    ),
+    'methodology': (
+        'методология|методы исследования|approach|methodology|methods|techniques|'
+        'исследовательские методы|методики|способы анализа|процедура|процесс исследования',
+        1,
+    ),
+    'interviews': (
+        'интервью|мнения экспертов|комментарии|expert interviews|expert opinions|'
+        'statements|reviews|опросы|интервью с экспертами|экспертные отзывы|'
+        'интервьюирование|отзывы участников',
+        1,
     ),
 }
@@ -144,7 +144,9 @@ class NeuronModel(BaseModel, OrderedModel):
 
     @property
     def service(self) -> 'SimpleService':  # noqa: F821
-        return getattr(importlib.import_module(f'ml_model.services.{self.slug}'), self.slug.replace('-', '').title())
+        return getattr(
+            importlib.import_module(f'ml_model.services.{self.slug}'), self.slug.replace('-', '').title()
+        )
 
     @property
     def streaming(self) -> bool:
@@ -245,7 +245,7 @@ def openrouter_run(version: str, messages: list, callback_data: dict, model_name
                         logger.error(f'Model {model_name} disabled')
                         raise DeploymentDisabled
                 else:
-                    if re.match(r'^qwen/qwen3\.7-.*$', data['model']):
+                    if re.match(r'^qwen/qwen3\.[78]-.*$', data['model']):
                         input_tokens = data['usage']['cost']
                         output_tokens = 0
                     else:
@@ -62,9 +62,9 @@ class NeuronModelAPIView(APIView):
             selector = NeuronModelSelector(request.user)
             model = selector.get_model_by_slug(slug=slug, hidden=False)
             if not selector.get_model_accessible_status(model):
-                return Response({'detail': _('Model data cannot be retrieved')}, status=status.HTTP_403_FORBIDDEN)
-            return Response(
-                NeuronModelSerializer(model).data
-            )
+                return Response(
+                    {'detail': _('Model data cannot be retrieved')}, status=status.HTTP_403_FORBIDDEN
+                )
+            return Response(NeuronModelSerializer(model).data)
         except (NeuronModelNotExist, Exception) as exc:
             return Response({'detail': f'{exc}'}, status=status.HTTP_400_BAD_REQUEST)
@@ -1,5 +1,6 @@
 from django.utils.translation import gettext as _
 
+
 class FullBalanceException(Exception):
     def __str__(self) -> str:
-        return _('Your balance is already full')
\ No newline at end of file
+        return _('Your balance is already full')
@@ -12,12 +12,13 @@ class PaymentAttempt(BaseModel):
         verbose_name=_('Payment Method'),
         related_name='payment_attempts',
     )
+    # FIXME: переименовать в reason
+    # FIXME: blank=True, null=True пересмотреть, т.к Attempt - это FailedAttempt и причина скорее всего есть всегдад
     cancel_reason = models.CharField(max_length=50, blank=True, null=True, verbose_name=_('Cancel Reason'))
+    # FIXME: связывать попытки на основании метадаты при повторных попытках оплаты
+    # FIXME: вместо флага должен быть trace-id или подобный атрибут, который будет явно описывать, какие попытки связаны
     in_cycle = models.BooleanField(default=True, verbose_name=_('In Cycle'))
 
-    def __str__(self) -> str:
-        return f'Attempt of ({self.method})\nReason: {self.cancel_reason}'
-
     class Meta:
         verbose_name = _('Payment Attempt')
         verbose_name_plural = _('Payment Attempts')
@@ -15,7 +15,9 @@ class PaymentPlanFeature(OrderedModel):
     plan = models.ForeignKey(
         PaymentPlan, on_delete=models.CASCADE, related_name='features', verbose_name=_('Payment Plan')
     )
-    model = models.ForeignKey(NeuronModel, on_delete=models.CASCADE, related_name='feature', verbose_name=_('Neuron Model'))
+    model = models.ForeignKey(
+        NeuronModel, on_delete=models.CASCADE, related_name='feature', verbose_name=_('Neuron Model')
+    )
     quantity = models.PositiveIntegerField(default=1, verbose_name=_('Quantity'))
     measurement_unit = models.CharField(
         max_length=15,
@@ -26,12 +26,14 @@ class PaymentMethod(BaseModel):
     active = models.BooleanField(default=False, verbose_name=_('Active'))
     primary = models.BooleanField(default=True, verbose_name=_('Primary'))
 
+    # FIXME: в property не должно быть запросов, для использования property объект(-ы) должен быть аннотирован через .annotate
     @property
     def attempts(self):
         if hasattr(self, 'total_attempts'):
             return self.total_attempts
         return self.payment_attempts.filter(in_cycle=True).count()
 
+    # FIXME: должно быть перенесено на уровень сервисов, мы не изменяем метод save модели
     def save(self, *args, **kwargs):
         with transaction.atomic():
             if self.primary:
@@ -114,6 +114,7 @@ class PlansAPITest(BaseAuthorizedAPITest):
 
     def test_unauthorized_by_permission(self) -> None:
         from authentication.models import CustomUserModel
+
         host_user = CustomUserModel.objects.create_user(email='test_2@test.test', password='test_2')
         host = BusinessUserHost.objects.create(user=host_user)
         BusinessAccount.objects.create(user=self.user, parent_company=host)
@@ -239,4 +240,4 @@ class PlansAPITest(BaseAuthorizedAPITest):
     def test_tokens_per_plan(self) -> None:
         plans = self.get().json()
         for plan in plans:
-            self.assertGreater(Decimal(str(plan['tokens_per_plan'])), 0)
\ No newline at end of file
+            self.assertGreater(Decimal(str(plan['tokens_per_plan'])), 0)
@@ -79,4 +79,4 @@ class BalanceAPITest(BaseAuthorizedAPITest):
         )
         business_account.save()
         balance = self.get().json()['current_token_balance']
-        self.assertEqual(Decimal(balance), business_account.group.token_limit)
\ No newline at end of file
+        self.assertEqual(Decimal(balance), business_account.group.token_limit)
@@ -314,4 +314,3 @@ class ReferralAccountAdmin(admin.ModelAdmin):
     @admin.display(description='Получено бонусов')
     def _accrued_bonuses(self, obj: ReferralAccount):
         return f'{obj.accrued_bonuses.aggregate(total=Coalesce(Sum("amount"), Decimal(0), output_field=models.DecimalField()))["total"]} токенов'
-
@@ -30,4 +30,4 @@ def clear_recurrent_on_individual_plan_assignment(
     if not instance.plan.individual:
         return
     PaymentPlanUserInfo.objects.filter(pk=instance.pk).update(next_payment_at=None)
-    PaymentMethodService(instance.user).deactivate_payment_methods(notify=None)
\ No newline at end of file
+    PaymentMethodService(instance.user).deactivate_payment_methods(notify=None)
@@ -22,7 +22,10 @@ class SendErrorReportEmailAPIView(APIView):
             data = serializer.validated_data
             report = Report(
                 message=data['report_text'],
-                attachments=[File(file.name, file.file, file.content_type, file.size) for file in data.get('images', [])]
+                attachments=[
+                    File(file.name, file.file, file.content_type, file.size)
+                    for file in data.get('images', [])
+                ],
             )
             EmailService(request.user).send_error_email(report)
             return Response({'detail': 'error report sent'}, status=status.HTTP_201_CREATED)
@@ -76,4 +76,3 @@ class PublicSSEStoreService(SSEStoreService):
 
     def _get_cache_key(self) -> str:
         return f'sse:tokens:{self.user_uuid}:{self.message_uuid}:public'
-    
\ No newline at end of file
@@ -72,4 +72,3 @@ class MessageSchema(ModelSchema):
         if isinstance(value, str):
             return value
         return value.url
-
@@ -1,19 +1,30 @@
 from typing import List
 
+from django.contrib.contenttypes.models import ContentType
+from django.contrib.contenttypes.prefetch import GenericPrefetch
 from django.core.exceptions import ValidationError
+from django.db.models import Subquery
 from django.utils.translation import gettext as _
 from ninja import File, Form, Router, UploadedFile
 from ninja.errors import HttpError
+from ninja.pagination import paginate, CursorPagination
 
 from authentication.security import SyncAuthBearer
 from ml_model.models import NeuronModel
 from ml_model.schemas import NeuronModelLink
-from tools.media.models import Preset, Voice
+
+from messages.models import Message
+from tools.chats.schemas import MessageSchema
+
+from tools.media.models import Audio, Image, Preset, Video, Voice, VoiceClone
 from tools.media.schemas import PresetSchema, UpdateVoiceSchema, VoiceSchema
-from tools.media.typing import PresetKindEnum
+from tools.media.typing import PresetKindEnum, StoreEnum
 
 router = Router(auth=SyncAuthBearer(), tags=['media'])
 
+STORES = {'audio': Audio, 'image': Image, 'video': Video, 'voice_clone': VoiceClone}
+MEDIA_CONTENT_TYPES = {store: ContentType.objects.get_for_model(model) for store, model in STORES.items()}
+
 
 @router.get(
     'images/links/',
@@ -30,6 +41,44 @@ def get_links(request):
     )
 
 
+@router.get(
+    'generations/',
+    tags=['media/'],
+    response=List[MessageSchema],
+)
+@paginate(CursorPagination, ordering=('-created_at', 'uid'), page_size=10, max_page_size=50)
+def list_gallery_generations(request, store: StoreEnum):
+    store_model = STORES[store]
+    store_ids = store_model.objects.filter(user=request.auth).values('uid')
+    return (
+        Message.objects.filter(
+            content_type_id=MEDIA_CONTENT_TYPES[store].pk,
+            object_id__in=Subquery(store_ids),
+            from_model=True,
+            is_deleted=False,
+        )
+        .prefetch_related(
+            GenericPrefetch(
+                'content_object',
+                [store_model.objects.select_related('model').only('uid', 'model__slug', 'model__category_id')],
+            )
+        )
+        .only(
+            'uid',
+            'content',
+            'file',
+            'from_model',
+            'created_at',
+            'elapsed_time',
+            'is_favourite',
+            'is_sent',
+            'info',
+            'content_type',
+            'object_id',
+        )
+    )
+
+
 @router.post('voices/', tags=['media/voices'], auth=SyncAuthBearer(), response={201: None, 400: str})
 def upload_voice(
     request,
@@ -19,4 +19,4 @@ class VoiceSchema(ModelSchema):
 class PresetSchema(ModelSchema):
     class Meta:
         model = Preset
-        fields = ('uid', 'title', 'file', 'metadata')
\ No newline at end of file
+        fields = ('uid', 'title', 'file', 'metadata')
@@ -3,4 +3,11 @@ from enum import Enum
 
 class PresetKindEnum(str, Enum):
     voice = 'voice'
-    instrumental = 'instrumental'
\ No newline at end of file
+    instrumental = 'instrumental'
+
+
+class StoreEnum(str, Enum):
+    audio = 'audio'
+    image = 'image'
+    video = 'video'
+    voice_clone = 'voice_clone'
@@ -119,7 +119,9 @@ def openai_responses_stream(request, body: dict):
     if not (model_ref := body.get('model')):
         raise HttpError(400, _('You must provide a model parameter'))
     model = _resolve_model(model_ref)
-    return _to_openai(public_stream_message(request, model.slug, _parse_body(body)), model_ref, request=request)
+    return _to_openai(
+        public_stream_message(request, model.slug, _parse_body(body)), model_ref, request=request
+    )
 
 
 @OpenAIErrorService.view
@@ -6,14 +6,25 @@ from ninja.errors import HttpError
 
 class OpenAIErrorService:
     TYPES = {
-        400: 'invalid_request_error', 401: 'authentication_error', 403: 'permission_error',
-        404: 'invalid_request_error', 409: 'invalid_request_error', 501: 'api_error',
+        400: 'invalid_request_error',
+        401: 'authentication_error',
+        403: 'permission_error',
+        404: 'invalid_request_error',
+        409: 'invalid_request_error',
+        501: 'api_error',
     }
 
     @classmethod
     def response(cls, status: int, message: str) -> JsonResponse:
         return JsonResponse(
-            {'error': {'message': str(message), 'type': cls.TYPES.get(status, 'api_error'), 'param': None, 'code': None}},
+            {
+                'error': {
+                    'message': str(message),
+                    'type': cls.TYPES.get(status, 'api_error'),
+                    'param': None,
+                    'code': None,
+                }
+            },
             status=status,
         )
 
@@ -22,8 +22,7 @@ class BaseElevenlabsAPIView:
 
     def _authorization_headers(self, request):
         return {
-            'Authorization': request.headers.get('Xi-Api-Key')
-            or request.headers.get('Authorization', ''),
+            'Authorization': request.headers.get('Xi-Api-Key') or request.headers.get('Authorization', ''),
         }
 
     def _proxy_request(self, request, data=None):
@@ -173,7 +173,9 @@ class OpenAIVoiceAPIView(PublicVoiceUploadAPIView, PublicVoiceListAPIView):
         name = request.data.get('name')
         sample = request.FILES.get('audio_sample')
         if not sample:
-            return _openai_error(_('Missing audio_sample.'), param='audio_sample', code='missing_required_parameter')
+            return _openai_error(
+                _('Missing audio_sample.'), param='audio_sample', code='missing_required_parameter'
+            )
 
         proxy = type(
             'RequestProxy',
@@ -278,7 +280,9 @@ class OpenAIAudioSpeechAPIView(VoiceView):
             if st == status.HTTP_403_FORBIDDEN:
                 return _openai_error(str(detail), err_type='permission_error', http_status=st)
             if st >= 500:
-                return _openai_error(str(detail), err_type='api_error', code='internal_error', http_status=st)
+                return _openai_error(
+                    str(detail), err_type='api_error', code='internal_error', http_status=st
+                )
             return _openai_error(str(detail), http_status=st)
         r = httpx.get(result.data[0]['file'], timeout=120.0)
         if r.status_code >= 400:
@@ -0,0 +1,30 @@
+# Generated by Django 5.0 on 2026-07-30 14:10
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    initial = True
+
+    dependencies = [
+        ('msgs', '0010_message_msgs_messag_object__09670f_idx'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='Share',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('code', models.CharField(max_length=8, unique=True, verbose_name='Code')),
+                ('created_at', models.DateTimeField(auto_now_add=True, verbose_name='Created At')),
+                ('expires_at', models.DateTimeField(verbose_name='Expires At')),
+                ('messages', models.ManyToManyField(to='msgs.message', verbose_name='Messages')),
+            ],
+            options={
+                'verbose_name': 'Share',
+                'verbose_name_plural': 'Shares',
+                'ordering': ('expires_at',),
+            },
+        ),
+    ]
@@ -0,0 +1,40 @@
+from ninja import Router
+from ninja.errors import HttpError
+
+from authentication.security import SyncAuthBearer
+from tools.share.exceptions import (
+    IncompleteSetError,
+    MultiStoreShareError,
+    OnlyModelMessagesShareError,
+    OwnershipError,
+    ShareDoesNotExist,
+    StoreShareError,
+)
+from tools.share.schemas import ShareResultSchema, ShareSchema, ShareMessagesSchema
+from tools.share.services.share_service import ShareService
+
+router = Router(auth=SyncAuthBearer(), tags=['share'])
+
+
+@router.post('/', tags=['share/'], response=ShareSchema)
+def add_share_messages(request, payload: ShareMessagesSchema):
+    try:
+        share = ShareService(request.auth, list(set(payload.messages_uids))).share()
+        return ShareSchema(code=share.code, expires_at=share.expires_at)
+    except OwnershipError as exc:
+        raise HttpError(403, str(exc))
+    except (MultiStoreShareError, StoreShareError, IncompleteSetError, OnlyModelMessagesShareError) as exc:
+        raise HttpError(400, str(exc))
+    except Exception as exc:
+        raise HttpError(400, str(exc))
+
+
+@router.get('{code}/', auth=None, tags=['share/'], response=ShareResultSchema)
+def list_share_messages(request, code: str):
+    try:
+        store_type, messages = ShareService.get_share_messages(code)
+        return ShareResultSchema(store_type=store_type, messages=messages)
+    except ShareDoesNotExist as exc:
+        raise HttpError(404, str(exc))
+    except Exception as exc:
+        raise HttpError(400, str(exc))
@@ -0,0 +1,101 @@
+import base64
+import hashlib
+from datetime import timedelta
+
+from uuid import UUID
+
+from django.conf import settings
+from django.contrib.contenttypes.models import ContentType
+from django.db import transaction
+from django.db.models import Prefetch
+from django.utils import timezone
+
+from authentication.models import CustomUserModel
+from core.service import BaseService
+from messages.models import Message
+from tools.chats.models import Chat
+from tools.media.models import Gallery
+from tools.public_api.models import APIStore
+from tools.share.exceptions import (
+    IncompleteSetError,
+    MultiStoreShareError,
+    OnlyModelMessagesShareError,
+    OwnershipError,
+    ShareDoesNotExist,
+    StoreShareError,
+)
+from tools.share.models import Share
+
+
+class ShareService(BaseService):
+    SHARE_LIFETIME = settings.SHARE_LIFETIME
+
+    def __init__(self, user: CustomUserModel, message_uids: list[UUID]) -> None:
+        super().__init__(user)
+        self.message_uids = message_uids
+
+    def _generate_code(self):
+        return base64.urlsafe_b64encode(
+            hashlib.sha256((','.join(sorted(map(str, self.message_uids)))).encode()).digest()
+        ).decode()[:8]
+
+    def _validate_share_messages(self) -> None:
+        """
+        Проверяет, что все сообщения существуют, принадлежат одному стору текущего пользователя
+        и могут быть расшарены. Исключает сообщения из неподдерживаемых типов сторов.
+        """
+        qs = Message.objects.filter(uid__in=self.message_uids, is_deleted=False)
+        raw_pairs = list(qs.values_list('content_type', 'object_id'))
+        if not raw_pairs or len(raw_pairs) != len(self.message_uids):
+            raise IncompleteSetError
+        pairs = set(raw_pairs)
+        if len(pairs) > 1:
+            raise MultiStoreShareError
+        for content_type, object_id in pairs:
+            model = ContentType.objects.get_for_id(content_type).model_class()
+            if model is APIStore:
+                raise StoreShareError
+            model_filter = {'pk': object_id, 'user': self.user}
+            if model is Chat:
+                model_filter['is_deleted'] = False
+            if not model.objects.filter(**model_filter).exists():
+                raise OwnershipError
+            if issubclass(model, Gallery) and qs.filter(from_model=False).exists():
+                raise OnlyModelMessagesShareError
+
+    def _create_share(self, code: str) -> Share:
+        with transaction.atomic():
+            share, created = Share.objects.update_or_create(
+                code=code, defaults=dict(expires_at=timezone.now() + timedelta(seconds=self.SHARE_LIFETIME))
+            )
+            if created:
+                share.messages.add(*self.message_uids)
+            return share
+
+    def share(self) -> Share:
+        self._validate_share_messages()
+        code = self._generate_code()
+        share = self._create_share(code)
+        return share
+
+    @classmethod
+    def get_share_messages(cls, code: str) -> tuple[str, list[Message]]:
+        share = (
+            Share.objects.filter(code=code, expires_at__gt=timezone.now())
+            .prefetch_related(
+                Prefetch(
+                    'messages',
+                    queryset=Message.objects.filter(is_deleted=False).select_related('content_type'),
+                )
+            )
+            .first()
+        )
+        if not share:
+            raise ShareDoesNotExist
+
+        messages = list(share.messages.all())
+        if not messages:
+            raise ShareDoesNotExist
+
+        store_type = messages[0].content_type.model
+        return store_type, messages
@@ -0,0 +1,22 @@
+from django.contrib import admin
+
+from tools.share.models import Share
+
+
+class ShareMessageInline(admin.TabularInline):
+    model = Share.messages.through
+    extra = 0
+    can_delete = False
+    readonly_fields = ('message',)
+    fields = ('message',)
+
+    def has_add_permission(self, request, obj=None) -> bool:
+        return False
+
+
+@admin.register(Share)
+class ShareAdmin(admin.ModelAdmin):
+    list_display = ('code', 'created_at', 'expires_at')
+    search_fields = ('code',)
+    readonly_fields = ('code', 'created_at', 'expires_at')
+    inlines = [ShareMessageInline]
@@ -0,0 +1,31 @@
+from django.utils.translation import gettext as _
+
+
+class OwnershipError(Exception):
+    def __str__(self) -> str:
+        return _('Some messages are unavailable to you')
+
+
+class MultiStoreShareError(Exception):
+    def __str__(self) -> str:
+        return _('Link access can only include messages from one store')
+
+
+class StoreShareError(Exception):
+    def __str__(self) -> str:
+        return _('Link access is not available for this store type')
+
+
+class OnlyModelMessagesShareError(Exception):
+    def __str__(self) -> str:
+        return _('Link access for this store can only include model messages')
+
+
+class IncompleteSetError(Exception):
+    def __str__(self) -> str:
+        return _('Not all messages were found. Some may have been deleted')
+
+
+class ShareDoesNotExist(Exception):
+    def __str__(self) -> str:
+        return _('The link was not found or is no longer available')
@@ -0,0 +1,19 @@
+from django.db import models
+from django.utils.translation import gettext_lazy as _
+
+from messages.models import Message
+
+
+class Share(models.Model):
+    code = models.CharField(max_length=8, unique=True, verbose_name=_('Code'))
+    messages = models.ManyToManyField(Message, blank=False, verbose_name=_('Messages'))
+    created_at = models.DateTimeField(auto_now_add=True, verbose_name=_('Created At'))
+    expires_at = models.DateTimeField(verbose_name=_('Expires At'))
+
+    def __str__(self) -> str:
+        return self.code
+
+    class Meta:
+        verbose_name = _('Share')
+        verbose_name_plural = _('Shares')
+        ordering = ('expires_at',)
@@ -0,0 +1,20 @@
+from datetime import datetime
+from uuid import UUID
+
+from ninja import Schema
+
+from tools.chats.schemas import MessageSchema
+
+
+class ShareMessagesSchema(Schema):
+    messages_uids: list[UUID]
+
+
+class ShareSchema(Schema):
+    code: str
+    expires_at: datetime
+
+
+class ShareResultSchema(Schema):
+    store_type: str
+    messages: list[MessageSchema]
@@ -0,0 +1,9 @@
+from celery import shared_task
+from django.utils import timezone
+
+from tools.share.models import Share
+
+
+@shared_task
+def delete_expired_shares() -> None:
+    Share.objects.filter(expires_at__lte=timezone.now()).delete()
@@ -24,3 +24,9 @@ class MediaConfig(AppConfig):
     default_auto_field = 'django.db.models.BigAutoField'
     name = 'tools.media'
     verbose_name = _('Media')
+
+
+class ShareConfig(AppConfig):
+    default_auto_field = 'django.db.models.BigAutoField'
+    name = 'tools.share'
+    verbose_name = _('Share')
\ No newline at end of file
@@ -119,4 +119,7 @@ PYTHONWARNINGS=ignore::UserWarning:polymorphic # temporarily
 # SSE STREAMING
 FF__STREAMING_ENABLED=True
 
+# MESSAGE SHARING
+SHARE_LIFETIME=1800
+
 DATA_UPLOAD_MAX_MEMORY_SIZE=5 # MB
\ No newline at end of file
@@ -15,7 +15,7 @@ dependencies = [
     "django-filter==23.2",
     "django-import-export==4.0.9",
     "django-minio-backend",
-    "django-ninja==1.3.0",
+    "django-ninja==1.6.2",
     "django-oauth-toolkit==2.3.0",
     "django-ordered-model==3.7.4",
     "django-polymorphic==3.1.0",
@@ -44,6 +44,7 @@ dependencies = [
     "pillow==12.2.0",
     "psycopg2-binary==2.9.10",
     "pydub==0.25.1",
+    "pyexcelerate>=0.13.0",
     "pymupdf==1.26.1",
     "pypandoc==1.15",
     "pypdf2==3.0.1",
@@ -303,6 +303,7 @@ dependencies = [
     { name = "pillow" },
     { name = "psycopg2-binary" },
     { name = "pydub" },
+    { name = "pyexcelerate" },
     { name = "pymupdf" },
     { name = "pypandoc" },
     { name = "pypdf2" },
@@ -340,7 +341,7 @@ requires-dist = [
     { name = "django-filter", specifier = "==23.2" },
     { name = "django-import-export", specifier = "==4.0.9" },
     { name = "django-minio-backend", git = "https://github.com/theriverman/django-minio-backend?tag=3.7.0" },
-    { name = "django-ninja", specifier = "==1.3.0" },
+    { name = "django-ninja", specifier = "==1.6.2" },
     { name = "django-oauth-toolkit", specifier = "==2.3.0" },
     { name = "django-ordered-model", specifier = "==3.7.4" },
     { name = "django-polymorphic", specifier = "==3.1.0" },
@@ -369,6 +370,7 @@ requires-dist = [
     { name = "pillow", specifier = "==12.2.0" },
     { name = "psycopg2-binary", specifier = "==2.9.10" },
     { name = "pydub", specifier = "==0.25.1" },
+    { name = "pyexcelerate", specifier = ">=0.13.0" },
     { name = "pymupdf", specifier = "==1.26.1" },
     { name = "pypandoc", specifier = "==1.15" },
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