from __future__ import annotations from typing import Generator, Optional, Dict, Any, Union, List import random import asyncio import base64 from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from ..typing import AsyncResult, Messages from ..requests import StreamSession, raise_for_status from ..errors import ResponseError from ..image import ImageResponse class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin): url = "https://replicate.com" parent = "Replicate" working = True default_model = 'stability-ai/stable-diffusion-3' models = [ # Models for image generation 'stability-ai/stable-diffusion-3', 'bytedance/sdxl-lightning-4step', 'playgroundai/playground-v2.5-1024px-aesthetic', # Models for image generation 'meta/meta-llama-3-70b-instruct', 'mistralai/mixtral-8x7b-instruct-v0.1', 'google-deepmind/gemma-2b-it', ] versions = { # Model versions for generating images 'stability-ai/stable-diffusion-3': [ "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f" ], 'bytedance/sdxl-lightning-4step': [ "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f" ], 'playgroundai/playground-v2.5-1024px-aesthetic': [ "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24" ], # Model versions for text generation 'meta/meta-llama-3-70b-instruct': [ "dp-cf04fe09351e25db628e8b6181276547" ], 'mistralai/mixtral-8x7b-instruct-v0.1': [ "dp-89e00f489d498885048e94f9809fbc76" ], 'google-deepmind/gemma-2b-it': [ "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626" ] } image_models = {"stability-ai/stable-diffusion-3", "bytedance/sdxl-lightning-4step", "playgroundai/playground-v2.5-1024px-aesthetic"} text_models = {"meta/meta-llama-3-70b-instruct", "mistralai/mixtral-8x7b-instruct-v0.1", "google-deepmind/gemma-2b-it"} @classmethod async def create_async_generator( cls, model: str, messages: Messages, **kwargs: Any ) -> Generator[Union[str, ImageResponse], None, None]: yield await cls.create_async(messages[-1]["content"], model, **kwargs) @classmethod async def create_async( cls, prompt: str, model: str, api_key: Optional[str] = None, proxy: Optional[str] = None, timeout: int = 180, version: Optional[str] = None, extra_data: Dict[str, Any] = {}, **kwargs: Any ) -> Union[str, ImageResponse]: headers = { 'Accept-Encoding': 'gzip, deflate, br', 'Accept-Language': 'en-US', 'Connection': 'keep-alive', 'Origin': cls.url, 'Referer': f'{cls.url}/', 'Sec-Fetch-Dest': 'empty', 'Sec-Fetch-Mode': 'cors', 'Sec-Fetch-Site': 'same-site', 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36', 'sec-ch-ua': '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"', 'sec-ch-ua-mobile': '?0', 'sec-ch-ua-platform': '"macOS"', } if version is None: version = random.choice(cls.versions.get(model, [])) if api_key is not None: headers["Authorization"] = f"Bearer {api_key}" async with StreamSession( proxies={"all": proxy}, headers=headers, timeout=timeout ) as session: data = { "input": { "prompt": prompt, **extra_data }, "version": version } if api_key is None: data["model"] = cls.get_model(model) url = "https://homepage.replicate.com/api/prediction" else: url = "https://api.replicate.com/v1/predictions" async with session.post(url, json=data) as response: await raise_for_status(response) result = await response.json() if "id" not in result: raise ResponseError(f"Invalid response: {result}") while True: if api_key is None: url = f"https://homepage.replicate.com/api/poll?id={result['id']}" else: url = f"https://api.replicate.com/v1/predictions/{result['id']}" async with session.get(url) as response: await raise_for_status(response) result = await response.json() if "status" not in result: raise ResponseError(f"Invalid response: {result}") if result["status"] == "succeeded": output = result['output'] if model in cls.text_models: return ''.join(output) if isinstance(output, list) else output elif model in cls.image_models: images: List[Any] = output images = images[0] if len(images) == 1 else images return ImageResponse(images, prompt) elif result["status"] == "failed": raise ResponseError(f"Prediction failed: {result}") await asyncio.sleep(0.5)