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