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
|
import hashlib
import json
import time
import uuid
from datetime import datetime
import requests
from ..typing import SHA256, Any, CreateResult
from .base_provider import BaseProvider
class Ails(BaseProvider):
url: str = "https://ai.ls"
working = True
supports_stream = True
supports_gpt_35_turbo = True
@staticmethod
def create_completion(
model: str,
messages: list[dict[str, str]],
stream: bool,
**kwargs: Any,
) -> CreateResult:
headers = {
"authority": "api.caipacity.com",
"accept": "*/*",
"accept-language": "en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3",
"authorization": "Bearer free",
"client-id": str(uuid.uuid4()),
"client-v": _get_client_v(),
"content-type": "application/json",
"origin": "https://ai.ls",
"referer": "https://ai.ls/",
"sec-ch-ua": '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Windows"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "cross-site",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36",
}
timestamp = _format_timestamp(int(time.time() * 1000))
sig = {
"d": datetime.now().strftime("%Y-%m-%d"),
"t": timestamp,
"s": _hash({"t": timestamp, "m": messages[-1]["content"]}),
}
json_data = json.dumps(
separators=(",", ":"),
obj={
"model": "gpt-3.5-turbo",
"temperature": kwargs.get("temperature", 0.6),
"stream": True,
"messages": messages,
}
| sig,
)
response = requests.post(
"https://api.caipacity.com/v1/chat/completions",
headers=headers,
data=json_data,
stream=True,
)
response.raise_for_status()
for token in response.iter_lines():
if b"content" in token:
completion_chunk = json.loads(token.decode().replace("data: ", ""))
token = completion_chunk["choices"][0]["delta"].get("content")
if "ai.ls" in token.lower() or "ai.ci" in token.lower():
raise Exception("Response Error: " + token)
if token != None:
yield token
@classmethod
@property
def params(cls):
params = [
("model", "str"),
("messages", "list[dict[str, str]]"),
("stream", "bool"),
("temperature", "float"),
]
param = ", ".join([": ".join(p) for p in params])
return f"g4f.provider.{cls.__name__} supports: ({param})"
def _hash(json_data: dict[str, str]) -> SHA256:
base_string: str = "%s:%s:%s:%s" % (
json_data["t"],
json_data["m"],
"WI,2rU#_r:r~aF4aJ36[.Z(/8Rv93Rf",
len(json_data["m"]),
)
return SHA256(hashlib.sha256(base_string.encode()).hexdigest())
def _format_timestamp(timestamp: int) -> str:
e = timestamp
n = e % 10
r = n + 1 if n % 2 == 0 else n
return str(e - n + r)
def _get_client_v():
response = requests.get("https://ai.ls/?chat=1")
response.raise_for_status()
js_path = response.text.split('crossorigin href="')[1].split('"')[0]
response = requests.get("https://ai.ls" + js_path)
response.raise_for_status()
return response.text.split('G4="')[1].split('"')[0]
|
