@@ -32,4 +32,5 @@ from ml_model.services.sdxlemoji import Sdxlemoji
 from ml_model.services.stablediffusion import Stablediffusion
 from ml_model.services.upscaleai import Upscaleai
 from ml_model.services.vicuna import Vicuna
+from ml_model.services.wan import Wan
 from ml_model.services.whisper import Whisper
@@ -0,0 +1,47 @@
+import time
+from datetime import timedelta
+from decimal import Decimal
+from io import BytesIO
+
+import requests
+from django.core.files import File
+
+from messages.models import Message
+from ml_model.services.base import SimpleService
+from ml_model.tasks import replicate_run
+
+
+class Wan(SimpleService):
+    """
+    Wan Service
+    contains abstract method make, which makes a generation
+    """
+
+    TOKENS_COST = {
+        '480p': Decimal('25'),
+        '720p': Decimal('50')
+    }
+
+    def calculate_price(self, resolution: str) -> Decimal:
+        return self.TOKENS_COST[resolution].quantize(Decimal('0.1'), rounding='ROUND_UP')
+
+    def save_results(self, content: str, t: timedelta, video: str, save: bool = True) -> list[Message]:
+        msg = Message(
+            content=content,
+            content_object=self.store,
+            elapsed_time=t,
+            file=File(BytesIO(requests.get(video).content), '.mp4'),
+        )
+        if save:
+            return Message.objects.bulk_create([msg])
+        return [msg]
+
+    def make(self, input_message: Message, save: bool = True) -> list[Message]:
+        resolution = input_message.info.pop('resolution', '720p')
+        callback_data = dict({'prompt': input_message.content, 'resolution': resolution, **input_message.info})
+        start_time = time.time()
+        video = replicate_run('wan-video/wan-2.2-t2v-fast', callback_data)
+        process_time = timedelta(seconds=(time.time() - start_time))
+        self.handle_invoice(input_message.content_object.model, resolution)
+        msgs = self.save_results(input_message.content, process_time, video, save)
+        return msgs