gpt4free/g4f/Provider/Snova.py

134 lines
4.8 KiB
Python

from __future__ import annotations
import json
from typing import AsyncGenerator
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import format_prompt
class Snova(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://fast.snova.ai"
api_endpoint = "https://fast.snova.ai/api/completion"
working = True
supports_stream = True
supports_system_message = True
supports_message_history = True
default_model = 'Meta-Llama-3.1-8B-Instruct'
models = [
'Meta-Llama-3.1-8B-Instruct',
'Meta-Llama-3.1-70B-Instruct',
'Meta-Llama-3.1-405B-Instruct',
'Samba-CoE',
'ignos/Mistral-T5-7B-v1',
'v1olet/v1olet_merged_dpo_7B',
'macadeliccc/WestLake-7B-v2-laser-truthy-dpo',
'cookinai/DonutLM-v1',
]
model_aliases = {
"llama-3.1-8b": "Meta-Llama-3.1-8B-Instruct",
"llama-3.1-70b": "Meta-Llama-3.1-70B-Instruct",
"llama-3.1-405b": "Meta-Llama-3.1-405B-Instruct",
"mistral-7b": "ignos/Mistral-T5-7B-v1",
"samba-coe-v0.1": "Samba-CoE",
"v1olet-merged-7b": "v1olet/v1olet_merged_dpo_7B",
"westlake-7b-v2": "macadeliccc/WestLake-7B-v2-laser-truthy-dpo",
"donutlm-v1": "cookinai/DonutLM-v1",
}
@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
) -> AsyncGenerator[str, None]:
model = cls.get_model(model)
headers = {
"accept": "text/event-stream",
"accept-language": "en-US,en;q=0.9",
"cache-control": "no-cache",
"content-type": "application/json",
"origin": cls.url,
"pragma": "no-cache",
"priority": "u=1, i",
"referer": f"{cls.url}/",
"sec-ch-ua": '"Chromium";v="127", "Not)A;Brand";v="99"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Linux"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-origin",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36"
}
async with ClientSession(headers=headers) as session:
data = {
"body": {
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": format_prompt(messages),
"id": "1-id",
"ref": "1-ref",
"revision": 1,
"draft": False,
"status": "done",
"enableRealTimeChat": False,
"meta": None
}
],
"max_tokens": 1000,
"stop": ["<|eot_id|>"],
"stream": True,
"stream_options": {"include_usage": True},
"model": model
},
"env_type": "tp16"
}
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
full_response = ""
async for line in response.content:
line = line.decode().strip()
if line.startswith("data: "):
data = line[6:]
if data == "[DONE]":
break
try:
json_data = json.loads(data)
choices = json_data.get("choices", [])
if choices:
delta = choices[0].get("delta", {})
content = delta.get("content", "")
full_response += content
except json.JSONDecodeError:
continue
except Exception as e:
print(f"Error processing chunk: {e}")
print(f"Problematic data: {data}")
continue
yield full_response.strip()