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
class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://huggingface.co/chat"
working = True
needs_auth = True
supports_message_history = True
default_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
models = [
'meta-llama/Meta-Llama-3.1-70B-Instruct',
'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8',
'CohereForAI/c4ai-command-r-plus',
'mistralai/Mixtral-8x7B-Instruct-v0.1',
'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO',
'01-ai/Yi-1.5-34B-Chat',
'mistralai/Mistral-7B-Instruct-v0.2',
'microsoft/Phi-3-mini-4k-instruct',
]
@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) if not model else model
headers = {}
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]"
