from __future__ import annotations import json from aiohttp import ClientSession from ..typing import AsyncResult, Messages from .base_provider import AsyncGeneratorProvider, ProviderModelMixin from .helper import format_prompt class DarkAI(AsyncGeneratorProvider, ProviderModelMixin): url = "https://darkai.foundation/chat" api_endpoint = "https://darkai.foundation/chat" working = True supports_stream = True supports_system_message = True supports_message_history = True default_model = 'llama-3-70b' models = [ 'gpt-4o', # Uncensored 'gpt-3.5-turbo', # Uncensored default_model, ] model_aliases = { "llama-3.1-70b": "llama-3-70b", } @classmethod def get_model(cls, model: str) -> str: if model in cls.models: return model elif model in cls.model_aliases: return cls.model_aliases[model] else: return cls.default_model @classmethod async def create_async_generator( cls, model: str, messages: Messages, proxy: str = None, **kwargs ) -> AsyncResult: model = cls.get_model(model) headers = { "accept": "text/event-stream", "content-type": "application/json", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36" } async with ClientSession(headers=headers) as session: prompt = format_prompt(messages) data = { "query": prompt, "model": model, } async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response: response.raise_for_status() full_text = "" async for chunk in response.content: if chunk: try: chunk_str = chunk.decode().strip() if chunk_str.startswith('data: '): chunk_data = json.loads(chunk_str[6:]) if chunk_data['event'] == 'text-chunk': full_text += chunk_data['data']['text'] elif chunk_data['event'] == 'stream-end': if full_text: yield full_text.strip() return except json.JSONDecodeError: pass except Exception: pass if full_text: yield full_text.strip()