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145 lines
5.4 KiB
Python
145 lines
5.4 KiB
Python
from __future__ import annotations
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import json, requests, re
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from curl_cffi import requests as cf_reqs
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from ..typing import CreateResult, Messages
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from .base_provider import ProviderModelMixin, AbstractProvider
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from .helper import format_prompt
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class HuggingChat(AbstractProvider, ProviderModelMixin):
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url = "https://huggingface.co/chat"
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working = True
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supports_stream = True
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default_model = "meta-llama/Meta-Llama-3.1-70B-Instruct"
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models = [
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'meta-llama/Meta-Llama-3.1-70B-Instruct',
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'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8',
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'CohereForAI/c4ai-command-r-plus',
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'mistralai/Mixtral-8x7B-Instruct-v0.1',
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'NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO',
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'01-ai/Yi-1.5-34B-Chat',
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'mistralai/Mistral-7B-Instruct-v0.3',
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'microsoft/Phi-3-mini-4k-instruct',
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]
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model_aliases = {
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"llama-3.1-70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
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"llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8",
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"command-r-plus": "CohereForAI/c4ai-command-r-plus",
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"mixtral-8x7b": "mistralai/Mixtral-8x7B-Instruct-v0.1",
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"mixtral-8x7b": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
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"yi-1.5-34b": "01-ai/Yi-1.5-34B-Chat",
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"mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3",
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"phi-3-mini-4k": "microsoft/Phi-3-mini-4k-instruct",
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}
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@classmethod
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def get_model(cls, model: str) -> str:
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if model in cls.models:
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return model
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elif model in cls.model_aliases:
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return cls.model_aliases[model]
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else:
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return cls.default_model
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@classmethod
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def create_completion(
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cls,
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model: str,
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messages: Messages,
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stream: bool,
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**kwargs
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) -> CreateResult:
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model = cls.get_model(model)
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if model in cls.models:
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session = cf_reqs.Session()
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session.headers = {
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'accept': '*/*',
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'accept-language': 'en',
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'cache-control': 'no-cache',
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'origin': 'https://huggingface.co',
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'pragma': 'no-cache',
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'priority': 'u=1, i',
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'referer': 'https://huggingface.co/chat/',
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'sec-ch-ua': '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"',
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'sec-ch-ua-mobile': '?0',
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'sec-ch-ua-platform': '"macOS"',
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'sec-fetch-dest': 'empty',
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'sec-fetch-mode': 'cors',
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'sec-fetch-site': 'same-origin',
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'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',
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}
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print(model)
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json_data = {
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'model': model,
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}
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response = session.post('https://huggingface.co/chat/conversation', json=json_data)
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conversationId = response.json()['conversationId']
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response = session.get(f'https://huggingface.co/chat/conversation/{conversationId}/__data.json?x-sveltekit-invalidated=01',)
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data: list = (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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messageId: str = data[message_keys["id"]]
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settings = {
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"inputs": format_prompt(messages),
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"id": messageId,
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"is_retry": False,
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"is_continue": False,
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"web_search": False,
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"tools": []
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}
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headers = {
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'accept': '*/*',
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'accept-language': 'en',
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'cache-control': 'no-cache',
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'origin': 'https://huggingface.co',
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'pragma': 'no-cache',
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'priority': 'u=1, i',
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'referer': f'https://huggingface.co/chat/conversation/{conversationId}',
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'sec-ch-ua': '"Not)A;Brand";v="99", "Google Chrome";v="127", "Chromium";v="127"',
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'sec-ch-ua-mobile': '?0',
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'sec-ch-ua-platform': '"macOS"',
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'sec-fetch-dest': 'empty',
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'sec-fetch-mode': 'cors',
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'sec-fetch-site': 'same-origin',
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'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',
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}
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files = {
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'data': (None, json.dumps(settings, separators=(',', ':'))),
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}
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response = requests.post(f'https://huggingface.co/chat/conversation/{conversationId}',
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cookies=session.cookies,
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headers=headers,
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files=files,
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)
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first_token = True
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for line in response.iter_lines():
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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().replace('\u0000', '')
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first_token = False
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else:
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token = token.replace('\u0000', '')
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yield token
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elif line["type"] == "finalAnswer":
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break
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