@@ -27,6 +27,7 @@ from ml_model.services.perplexity import Perplexity from ml_model.services.pulid import Pulid from ml_model.services.qwen import Qwen from ml_model.services.raifgpt import Raifgpt +from ml_model.services.ray import Ray from ml_model.services.recraft import Recraft from ml_model.services.sdxlemoji import Sdxlemoji from ml_model.services.stablediffusion import Stablediffusion @@ -0,0 +1,57 @@ +import base64 +import time +from datetime import timedelta +from decimal import Decimal +from io import BytesIO + +import filetype +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 + +from payments.exceptions.insufficient_balance import InsufficientBalance +from payments.selectors.payment_plan_selector import PaymentPlanSelector + + +class Ray(SimpleService): + """ + Ray Service + contains abstract method make, which makes a generation + """ + + TOKENS_COST = Decimal('135') + + def calculate_price(self) -> Decimal: + return self.TOKENS_COST.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]: + if (balance := PaymentPlanSelector(self.store.user).get_current_balance()) < self.TOKENS_COST: + raise InsufficientBalance(balance, self.TOKENS_COST) + callback_data = dict({'prompt': self.translate_prompt(input_message.content), **input_message.info}) + if input_message.file: + kind = filetype.guess(input_message.file.read(20)) + mime = kind.mime if kind else 'application/octet-stream' + input_message.file.seek(0) + image = f'data:{mime};base64,{base64.b64encode(input_message.file.read()).decode("utf-8")}' + input_message.file.close() + callback_data.update({'start_image': image}) + start_time = time.time() + video = replicate_run('luma/ray', callback_data) + process_time = timedelta(seconds=(time.time() - start_time)) + self.handle_invoice(input_message.content_object.model) + msgs = self.save_results(input_message.content, process_time, video, save) + return msgs