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https://github.com/xtekky/gpt4free.git
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ec51e9c764
Add more models and image generation in You provider Use You as second default image provider
75 lines
3.0 KiB
Python
75 lines
3.0 KiB
Python
from __future__ import annotations
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import json
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from aiohttp import ClientSession, BaseConnector
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from .helper import get_connector
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from ..errors import RateLimitError, ModelNotFoundError
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class HuggingFace(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://huggingface.co/chat"
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working = True
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supports_message_history = True
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default_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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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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api_base: str = "https://api-inference.huggingface.co",
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api_key: str = None,
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max_new_tokens: int = 1024,
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temperature: float = 0.7,
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**kwargs
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) -> AsyncResult:
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model = cls.get_model(model)
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headers = {}
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if api_key is not None:
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headers["Authorization"] = f"Bearer {api_key}"
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params = {
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"return_full_text": False,
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"max_new_tokens": max_new_tokens,
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"temperature": temperature,
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**kwargs
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}
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payload = {"inputs": format_prompt(messages), "parameters": params, "stream": stream}
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async with ClientSession(
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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"{api_base.rstrip('/')}/models/{model}", json=payload) as response:
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if response.status == 429:
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raise RateLimitError("Rate limit reached. Set a api_key")
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elif response.status == 404:
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raise ModelNotFoundError(f"Model is not supported: {model}")
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elif response.status != 200:
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raise RuntimeError(f"Response {response.status}: {await response.text()}")
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if stream:
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first = True
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async for line in response.content:
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if line.startswith(b"data:"):
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data = json.loads(line[5:])
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if not data["token"]["special"]:
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chunk = data["token"]["text"]
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if first:
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first = False
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chunk = chunk.lstrip()
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yield chunk
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else:
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yield (await response.json())[0]["generated_text"].strip()
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def format_prompt(messages: Messages) -> str:
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system_messages = [message["content"] for message in messages if message["role"] == "system"]
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question = " ".join([messages[-1]["content"], *system_messages])
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history = "".join([
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f"<s>[INST]{messages[idx-1]['content']} [/INST] {message}</s>"
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for idx, message in enumerate(messages)
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if message["role"] == "assistant"
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])
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return f"{history}<s>[INST] {question} [/INST]" |