1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
|
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'
@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"]
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)
|
