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from __future__ import annotations
import json
from aiohttp import ClientSession
from ...typing import AsyncResult, Messages
from ...providers.response import ImageResponse, ImagePreview
from ...image import use_aspect_ratio
from ...errors import ResponseError
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ..helper import format_media_prompt
class StabilityAI_SD35Large(AsyncGeneratorProvider, ProviderModelMixin):
label = "StabilityAI SD-3.5-Large"
url = "https://stabilityai-stable-diffusion-3-5-large.hf.space"
api_endpoint = "/gradio_api/call/infer"
working = True
default_model = 'stabilityai-stable-diffusion-3-5-large'
default_image_model = default_model
model_aliases = {"sd-3.5-large": default_model}
image_models = list(model_aliases.keys())
models = image_models
@classmethod
async def create_async_generator(
cls, model: str, messages: Messages,
prompt: str = None,
negative_prompt: str = None,
api_key: str = None,
proxy: str = None,
aspect_ratio: str = "1:1",
width: int = None,
height: int = None,
guidance_scale: float = 4.5,
num_inference_steps: int = 50,
seed: int = 0,
randomize_seed: bool = True,
**kwargs
) -> AsyncResult:
headers = {
"Content-Type": "application/json",
"Accept": "application/json",
}
if api_key is not None:
headers["Authorization"] = f"Bearer {api_key}"
async with ClientSession(headers=headers) as session:
prompt = format_media_prompt(messages, prompt)
data = use_aspect_ratio({"width": width, "height": height}, aspect_ratio)
data = {
"data": [prompt, negative_prompt, seed, randomize_seed, data.get("width"), data.get("height"), guidance_scale, num_inference_steps]
}
async with session.post(f"{cls.url}{cls.api_endpoint}", json=data, proxy=proxy) as response:
response.raise_for_status()
event_id = (await response.json()).get("event_id")
async with session.get(f"{cls.url}{cls.api_endpoint}/{event_id}") as event_response:
event_response.raise_for_status()
event = None
async for chunk in event_response.content:
if chunk.startswith(b"event: "):
event = chunk[7:].decode(errors="replace").strip()
if chunk.startswith(b"data: "):
if event == "error":
raise ResponseError(f"GPU token limit exceeded: {chunk.decode(errors='replace')}")
if event in ("complete", "generating"):
try:
data = json.loads(chunk[6:])
if data is None:
continue
url = data[0]["url"]
except (json.JSONDecodeError, KeyError, TypeError) as e:
raise RuntimeError(f"Failed to parse image URL: {chunk.decode(errors='replace')}", e)
if event == "generating":
yield ImagePreview(url, prompt)
else:
yield ImageResponse(url, prompt)
break
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