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
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
|
from __future__ import annotations
import re
import random
import string
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages, ImageType
from ..image import ImageResponse, to_data_uri
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://www.blackbox.ai"
api_endpoint = "https://www.blackbox.ai/api/chat"
working = True
supports_stream = True
supports_system_message = True
supports_message_history = True
default_model = 'blackbox'
models = [
'blackbox',
'gemini-1.5-flash',
"llama-3.1-8b",
'llama-3.1-70b',
'ImageGenerationLV45LJp',
'gpt-4o',
'gemini-pro',
'claude-sonnet-3.5',
]
agentMode = {
'ImageGenerationLV45LJp': {'mode': True, 'id': "ImageGenerationLV45LJp", 'name': "Image Generation"},
}
trendingAgentMode = {
"blackbox": {},
"gemini-1.5-flash": {'mode': True, 'id': 'Gemini'},
"llama-3.1-8b": {'mode': True, 'id': "llama-3.1-8b"},
'llama-3.1-70b': {'mode': True, 'id': "llama-3.1-70b"},
}
userSelectedModel = {
"gpt-4o": "gpt-4o",
"gemini-pro": "gemini-pro",
'claude-sonnet-3.5': "claude-sonnet-3.5",
}
model_aliases = {
"gemini-flash": "gemini-1.5-flash",
"flux": "ImageGenerationLV45LJp",
}
@classmethod
def get_model(cls, model: str) -> str:
if model in cls.models:
return model
elif model in cls.userSelectedModel:
return model
elif model in cls.model_aliases:
return cls.model_aliases[model]
else:
return cls.default_model
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
image: ImageType = None,
image_name: str = None,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"cache-control": "no-cache",
"content-type": "application/json",
"origin": cls.url,
"pragma": "no-cache",
"referer": f"{cls.url}/",
"sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Linux"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36"
}
if model in cls.userSelectedModel:
prefix = f"@{cls.userSelectedModel[model]}"
if not messages[0]['content'].startswith(prefix):
messages[0]['content'] = f"{prefix} {messages[0]['content']}"
async with ClientSession(headers=headers) as session:
if image is not None:
messages[-1]["data"] = {
"fileText": image_name,
"imageBase64": to_data_uri(image)
}
random_id = ''.join(random.choices(string.ascii_letters + string.digits, k=7))
data = {
"messages": messages,
"id": random_id,
"previewToken": None,
"userId": None,
"codeModelMode": True,
"agentMode": {},
"trendingAgentMode": {},
"userSelectedModel": None,
"userSystemPrompt": None,
"isMicMode": False,
"maxTokens": 1024,
"playgroundTopP": 0.9,
"playgroundTemperature": 0.5,
"isChromeExt": False,
"githubToken": None,
"clickedAnswer2": False,
"clickedAnswer3": False,
"clickedForceWebSearch": False,
"visitFromDelta": False,
"mobileClient": False,
"webSearchMode": False,
}
if model in cls.agentMode:
data["agentMode"] = cls.agentMode[model]
elif model in cls.trendingAgentMode:
data["trendingAgentMode"] = cls.trendingAgentMode[model]
elif model in cls.userSelectedModel:
data["userSelectedModel"] = cls.userSelectedModel[model]
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
if model == 'ImageGenerationLV45LJp':
response_text = await response.text()
url_match = re.search(r'https://storage\.googleapis\.com/[^\s\)]+', response_text)
if url_match:
image_url = url_match.group(0)
yield ImageResponse(image_url, alt=messages[-1]['content'])
else:
raise Exception("Image URL not found in the response")
else:
async for chunk in response.content.iter_any():
if chunk:
decoded_chunk = chunk.decode()
decoded_chunk = re.sub(r'\$@\$v=[^$]+\$@\$', '', decoded_chunk)
if decoded_chunk.strip():
yield decoded_chunk
|