NeuroGPT / g4f /Provider /Aiwang.py
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import random, requests, json
from ..typing import Any, CreateResult
from .base_provider import BaseProvider
class Aiwang(BaseProvider):
url = "https://ai-wang.vercel.app"
supports_stream = True
supports_gpt_35_turbo = True
supports_gpt_35_turbo_16k = True
supports_gpt_35_turbo_16k_0613 = True
supports_gpt_4 = True
supports_gpt_4_0613 = True
supports_gpt_4_32k = True
supports_gpt_4_32k_0613 = True
working = False
@staticmethod
def create_completion(
model: str,
messages: list[dict[str, str]],
stream: bool,
**kwargs: Any,
) -> CreateResult:
base = ''
for message in messages:
base += '%s: %s\n' % (message['role'], message['content'])
base += 'assistant:'
headers = {
"authority": "ai-wang.vercel.app",
"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,fa=0.2",
"content-type": "application/json",
"path": "v1/chat/completions",
"origin": f"{server}",
"referer": f"{server}/",
"x-requested-with": "XMLHttpRequest",
'sec-ch-ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
}
json_data = {
"messages": messages,
"stream": stream,
"model": model,
"temperature": kwargs.get("temperature", 0.5),
"presence_penalty": kwargs.get("presence_penalty", 0),
"frequency_penalty": kwargs.get("frequency_penalty", 0),
"top_p": kwargs.get("top_p", 1),
"max_tokens": kwargs.get("max_tokens", 4096),
}
session = requests.Session()
# init cookies from server
session.get(f"{server}/")
response = session.post(
f"{server}/api/chat-stream",
headers=headers,
json=json_data,
stream=stream,
)
response.encoding = "utf-8"
try:
# Find the first opening brace and the last closing brace
start = response.text.find('{')
end = response.text.rfind('}') + 1 # +1 to include the brace itself
# Extract the JSON text
json_text = response.text[start:end]
# Convert the cleaned text to a Python dictionary
response_dict = json.loads(json_text)
except json.JSONDecodeError:
print(f"Failed to decode JSON. Response text was: {response.text}")
raise
# Extract the desired message
yield response_dict['choices'][0]['message']['content']
@classmethod
@property
def params(cls):
params = [
("model", "str"),
("messages", "list[dict[str, str]]"),
("stream", "bool"),
("temperature", "float"),
("presence_penalty", "int"),
("frequency_penalty", "int"),
("top_p", "int"),
("max_tokens", "int"),
("active_server", "int"),
]
param = ", ".join([": ".join(p) for p in params])
return f"g4f.provider.{cls.__name__} supports: ({param})"