gpt4free/g4f/Provider/HuggingChat.py
Heiner Lohaus 347d3f92da Add .har file support for OpenaiChat
Update model list of HuggingChat
Update styles of scrollbar in gui
Fix image upload in gui
2024-03-25 21:06:51 +01:00

96 lines
3.9 KiB
Python

from __future__ import annotations
import json
import requests
from aiohttp import ClientSession, BaseConnector
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import format_prompt, get_connector
class HuggingChat(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://huggingface.co/chat"
working = True
default_model = "meta-llama/Llama-2-70b-chat-hf"
models = [
"mistralai/Mixtral-8x7B-Instruct-v0.1",
"google/gemma-7b-it",
"meta-llama/Llama-2-70b-chat-hf",
"NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"codellama/CodeLlama-34b-Instruct-hf",
"mistralai/Mistral-7B-Instruct-v0.2",
"openchat/openchat-3.5-0106",
]
model_aliases = {
"openchat/openchat_3.5": "openchat/openchat-3.5-0106",
}
@classmethod
def get_models(cls):
if not cls.models:
url = f"{cls.url}/__data.json"
data = requests.get(url).json()["nodes"][0]["data"]
models = [data[key]["name"] for key in data[data[0]["models"]]]
cls.models = [data[key] for key in models]
return cls.models
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
stream: bool = True,
proxy: str = None,
connector: BaseConnector = None,
web_search: bool = False,
cookies: dict = None,
**kwargs
) -> AsyncResult:
options = {"model": cls.get_model(model)}
system_prompt = "\n".join([message["content"] for message in messages if message["role"] == "system"])
if system_prompt:
options["preprompt"] = system_prompt
messages = [message for message in messages if message["role"] != "system"]
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,
connector=get_connector(connector, proxy)
) as session:
async with session.post(f"{cls.url}/conversation", json=options, proxy=proxy) as response:
response.raise_for_status()
conversation_id = (await response.json())["conversationId"]
async with session.get(f"{cls.url}/conversation/{conversation_id}/__data.json") as response:
response.raise_for_status()
data: list = (await response.json())["nodes"][1]["data"]
keys: list[int] = data[data[0]["messages"]]
message_keys: dict = data[keys[0]]
message_id: str = data[message_keys["id"]]
options = {
"id": message_id,
"inputs": format_prompt(messages),
"is_continue": False,
"is_retry": False,
"web_search": web_search
}
async with session.post(f"{cls.url}/conversation/{conversation_id}", json=options) as response:
first_token = True
async for line in response.content:
response.raise_for_status()
line = json.loads(line)
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()