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70 lines
2.7 KiB
Python
70 lines
2.7 KiB
Python
from __future__ import annotations
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from ..requests import StreamSession
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from .base_provider import AsyncGeneratorProvider
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from ..typing import AsyncGenerator
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# to recreate this easily, send a post request to https://chat.aivvm.com/api/models
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models = {
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'gpt-3.5-turbo': {'id': 'gpt-3.5-turbo', 'name': 'GPT-3.5'},
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'gpt-3.5-turbo-0613': {'id': 'gpt-3.5-turbo-0613', 'name': 'GPT-3.5-0613'},
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'gpt-3.5-turbo-16k': {'id': 'gpt-3.5-turbo-16k', 'name': 'GPT-3.5-16K'},
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'gpt-3.5-turbo-16k-0613': {'id': 'gpt-3.5-turbo-16k-0613', 'name': 'GPT-3.5-16K-0613'},
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'gpt-4': {'id': 'gpt-4', 'name': 'GPT-4'},
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'gpt-4-0613': {'id': 'gpt-4-0613', 'name': 'GPT-4-0613'},
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'gpt-4-32k': {'id': 'gpt-4-32k', 'name': 'GPT-4-32K'},
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'gpt-4-32k-0613': {'id': 'gpt-4-32k-0613', 'name': 'GPT-4-32K-0613'},
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}
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class Aivvm(AsyncGeneratorProvider):
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url = 'https://chat.aivvm.com'
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supports_gpt_35_turbo = True
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supports_gpt_4 = True
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working = True
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: list[dict[str, str]],
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stream: bool,
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timeout: int = 30,
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**kwargs
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) -> AsyncGenerator:
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if not model:
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model = "gpt-3.5-turbo"
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elif model not in models:
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raise ValueError(f"Model is not supported: {model}")
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json_data = {
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"model" : models[model],
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"messages" : messages,
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"key" : "",
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"prompt" : kwargs.get("system_message", "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown."),
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"temperature" : kwargs.get("temperature", 0.7)
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}
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headers = {
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"Accept": "*/*",
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"Origin": cls.url,
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"Referer": f"{cls.url}/",
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}
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async with StreamSession(impersonate="chrome107", headers=headers, timeout=timeout) as session:
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async with session.post(f"{cls.url}/api/chat", json=json_data) as response:
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response.raise_for_status()
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async for chunk in response.iter_content():
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if b'Access denied | chat.aivvm.com used Cloudflare' in chunk:
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raise ValueError("Rate Limit | use another provider")
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yield chunk.decode()
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@classmethod
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@property
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def params(cls):
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params = [
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('model', 'str'),
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('messages', 'list[dict[str, str]]'),
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('stream', 'bool'),
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('temperature', 'float'),
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]
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param = ', '.join([': '.join(p) for p in params])
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return f'g4f.provider.{cls.__name__} supports: ({param})' |