from __future__ import annotations
from ..requests import AsyncSession
from .base_provider import AsyncGeneratorProvider
from ..typing import AsyncGenerator
# 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(AsyncGeneratorProvider):
url = 'https://chat.aivvm.com'
supports_stream = True
working = True
supports_gpt_35_turbo = True
supports_gpt_4 = True
@classmethod
async def create_async_generator(
cls,
model: str,
messages: list[dict[str, str]],
stream: bool,
**kwargs
) -> AsyncGenerator:
if not model:
model = "gpt-3.5-turbo"
elif model not in models:
raise ValueError(f"Model is not supported: {model}")
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)
}
async with AsyncSession(impersonate="chrome107") as session:
async with session.post(f"{cls.url}/api/chat", json=json_data) as response:
response.raise_for_status()
async for chunk in response.content.iter_any():
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})'
