from __future__ import annotations import requests from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from ..typing import AsyncResult, Messages from ..requests import StreamSession, raise_for_status from ..image import ImageResponse class DeepInfraImage(AsyncGeneratorProvider, ProviderModelMixin): url = "https://deepinfra.com" working = True default_model = 'stability-ai/sdxl' image_models = [default_model] @classmethod def get_models(cls): if not cls.models: url = 'https://api.deepinfra.com/models/featured' models = requests.get(url).json() cls.models = [model['model_name'] for model in models if model["reported_type"] == "text-to-image"] cls.image_models = cls.models return cls.models @classmethod async def create_async_generator( cls, model: str, messages: Messages, **kwargs ) -> AsyncResult: yield await cls.create_async(messages[-1]["content"], model, **kwargs) @classmethod async def create_async( cls, prompt: str, model: str, api_key: str = None, api_base: str = "https://api.deepinfra.com/v1/inference", proxy: str = None, timeout: int = 180, extra_data: dict = {}, **kwargs ) -> ImageResponse: headers = { 'Accept-Encoding': 'gzip, deflate, br', 'Accept-Language': 'en-US', 'Connection': 'keep-alive', 'Origin': 'https://deepinfra.com', 'Referer': 'https://deepinfra.com/', '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', 'X-Deepinfra-Source': 'web-embed', '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 api_key is not None: headers["Authorization"] = f"Bearer {api_key}" async with StreamSession( proxies={"all": proxy}, headers=headers, timeout=timeout ) as session: model = cls.get_model(model) data = {"prompt": prompt, **extra_data} data = {"input": data} if model == cls.default_model else data async with session.post(f"{api_base.rstrip('/')}/{model}", json=data) as response: await raise_for_status(response) data = await response.json() images = data["output"] if "output" in data else data["images"] if not images: raise RuntimeError(f"Response: {data}") images = images[0] if len(images) == 1 else images return ImageResponse(images, prompt)