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})'