from __future__ import annotations
import json
from aiohttp import ClientSession, BaseConnector
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import get_connector
from ..errors import RateLimitError, ModelNotFoundError
from ..requests.raise_for_status import raise_for_status
from .HuggingChat import HuggingChat
class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://huggingface.co/chat"
working = True
needs_auth = True
supports_message_history = True
default_model = HuggingChat.default_model
models = HuggingChat.models
model_aliases = HuggingChat.model_aliases
@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,
stream: bool = True,
proxy: str = None,
connector: BaseConnector = None,
api_base: str = "https://api-inference.huggingface.co",
api_key: str = None,
max_new_tokens: int = 1024,
temperature: float = 0.7,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
'accept': '*/*',
'accept-language': 'en',
'cache-control': 'no-cache',
'origin': 'https://huggingface.co',
'pragma': 'no-cache',
'priority': 'u=1, i',
'referer': 'https://huggingface.co/chat/',
'sec-ch-ua': '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"macOS"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'same-origin',
'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36',
}
if api_key is not None:
headers["Authorization"] = f"Bearer {api_key}"
params = {
"return_full_text": False,
"max_new_tokens": max_new_tokens,
"temperature": temperature,
**kwargs
}
payload = {"inputs": format_prompt(messages), "parameters": params, "stream": stream}
async with ClientSession(
headers=headers,
connector=get_connector(connector, proxy)
) as session:
async with session.post(f"{api_base.rstrip('/')}/models/{model}", json=payload) as response:
if response.status == 404:
raise ModelNotFoundError(f"Model is not supported: {model}")
await raise_for_status(response)
if stream:
first = True
async for line in response.content:
if line.startswith(b"data:"):
data = json.loads(line[5:])
if not data["token"]["special"]:
chunk = data["token"]["text"]
if first:
first = False
chunk = chunk.lstrip()
yield chunk
else:
yield (await response.json())[0]["generated_text"].strip()
def format_prompt(messages: Messages) -> str:
system_messages = [message["content"] for message in messages if message["role"] == "system"]
question = " ".join([messages[-1]["content"], *system_messages])
history = "".join([
f"<s>[INST]{messages[idx-1]['content']} [/INST] {message['content']}</s>"
for idx, message in enumerate(messages)
if message["role"] == "assistant"
])
return f"{history}<s>[INST] {question} [/INST]"
