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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-3-405b'
models = [
'gpt-4o', # Uncensored
'gpt-3.5-turbo', # Uncensored
'llama-3-70b', # Uncensored
default_model,
]
model_aliases = {
"llama-3.1-70b": "llama-3-70b",
"llama-3.1-405b": "llama-3-405b",
}
@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:
print(f"Failed to decode JSON: {chunk_str}")
except Exception as e:
print(f"Error processing chunk: {e}")
if full_text:
yield full_text.strip()
|
