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from __future__ import annotations
import requests
from .base_provider import BaseProvider
from ..typing import CreateResult
# to recreate this easily, send a post request to https://chat.aivvm.com/api/models
models = {
'gpt-3.5-turbo': {'id': 'gpt-3.5-turbo', 'name': 'GPT-3.5'},
'gpt-3.5-turbo-0613': {'id': 'gpt-3.5-turbo-0613', 'name': 'GPT-3.5-0613'},
'gpt-3.5-turbo-16k': {'id': 'gpt-3.5-turbo-16k', 'name': 'GPT-3.5-16K'},
'gpt-3.5-turbo-16k-0613': {'id': 'gpt-3.5-turbo-16k-0613', 'name': 'GPT-3.5-16K-0613'},
'gpt-4': {'id': 'gpt-4', 'name': 'GPT-4'},
'gpt-4-0613': {'id': 'gpt-4-0613', 'name': 'GPT-4-0613'},
'gpt-4-32k': {'id': 'gpt-4-32k', 'name': 'GPT-4-32K'},
'gpt-4-32k-0613': {'id': 'gpt-4-32k-0613', 'name': 'GPT-4-32K-0613'},
}
class Aivvm(BaseProvider):
url = 'https://chat.aivvm.com'
supports_stream = True
working = True
supports_gpt_35_turbo = True
supports_gpt_4 = True
@classmethod
def create_completion(cls,
model: str,
messages: list[dict[str, str]],
stream: bool,
**kwargs
) -> CreateResult:
if not model:
model = "gpt-3.5-turbo"
elif model not in models:
raise ValueError(f"Model is not supported: {model}")
headers = {
"accept" : "*/*",
"accept-language" : "en-US,en;q=0.9",
"content-type" : "application/json",
"sec-ch-ua" : '"Brave";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
"sec-ch-ua-mobile" : "?0",
"sec-ch-ua-platform": "\"Windows\"",
"sec-fetch-dest" : "empty",
"sec-fetch-mode" : "cors",
"sec-fetch-site" : "same-origin",
"Referer" : "https://chat.aivvm.com/",
"Referrer-Policy" : "same-origin",
"user-agent" : "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36"
}
json_data = {
"model" : models[model],
"messages" : messages,
"key" : "",
"prompt" : kwargs.get("system_message", "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown."),
"temperature" : kwargs.get("temperature", 0.7)
}
response = requests.post(
"https://chat.aivvm.com/api/chat", headers=headers, json=json_data, stream=True)
response.raise_for_status()
for chunk in response.iter_content(chunk_size=None):
yield chunk.decode('utf-8')
@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})'
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