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gpt4free/g4f/Provider/needs_auth/HuggingChat.py

72 lines
2.5 KiB
Python

from __future__ import annotations
import json, uuid
from aiohttp import ClientSession
from ...typing import AsyncResult, Messages
from ..base_provider import AsyncGeneratorProvider
from ..helper import format_prompt, get_cookies
map = {
"openchat/openchat_3.5": "openchat/openchat-3.5-1210",
}
class HuggingChat(AsyncGeneratorProvider):
url = "https://huggingface.co/chat"
working = True
model = "meta-llama/Llama-2-70b-chat-hf"
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
stream: bool = True,
proxy: str = None,
web_search: bool = False,
cookies: dict = None,
**kwargs
) -> AsyncResult:
if not model:
model = cls.model
elif model in map:
model = map[model]
if not cookies:
cookies = get_cookies(".huggingface.co")
headers = {
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36',
}
async with ClientSession(
cookies=cookies,
headers=headers
) as session:
async with session.post(f"{cls.url}/conversation", json={"model": model}, proxy=proxy) as response:
conversation_id = (await response.json())["conversationId"]
send = {
"id": str(uuid.uuid4()),
"inputs": format_prompt(messages),
"is_retry": False,
"response_id": str(uuid.uuid4()),
"web_search": web_search
}
async with session.post(f"{cls.url}/conversation/{conversation_id}", json=send, proxy=proxy) as response:
first_token = True
async for line in response.content:
line = json.loads(line[:-1])
if "type" not in line:
raise RuntimeError(f"Response: {line}")
elif line["type"] == "stream":
token = line["token"]
if first_token:
token = token.lstrip()
first_token = False
yield token
elif line["type"] == "finalAnswer":
break
async with session.delete(f"{cls.url}/conversation/{conversation_id}", proxy=proxy) as response:
response.raise_for_status()