mirror of
https://github.com/xtekky/gpt4free.git
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76 lines
3.1 KiB
Python
76 lines
3.1 KiB
Python
from __future__ import annotations
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from aiohttp import ClientSession
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider
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models = {
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"meta-llama/Llama-2-7b-chat-hf": {"name": "Llama 2 7B", "version": "d24902e3fa9b698cc208b5e63136c4e26e828659a9f09827ca6ec5bb83014381", "shortened":"7B"},
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"meta-llama/Llama-2-13b-chat-hf": {"name": "Llama 2 13B", "version": "9dff94b1bed5af738655d4a7cbcdcde2bd503aa85c94334fe1f42af7f3dd5ee3", "shortened":"13B"},
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"meta-llama/Llama-2-70b-chat-hf": {"name": "Llama 2 70B", "version": "2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf", "shortened":"70B"},
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"Llava": {"name": "Llava 13B", "version": "6bc1c7bb0d2a34e413301fee8f7cc728d2d4e75bfab186aa995f63292bda92fc", "shortened":"Llava"}
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}
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class Llama2(AsyncGeneratorProvider):
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url = "https://www.llama2.ai"
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working = True
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supports_message_history = True
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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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proxy: str = None,
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**kwargs
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) -> AsyncResult:
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if not model:
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model = "meta-llama/Llama-2-70b-chat-hf"
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elif model not in models:
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raise ValueError(f"Model are not supported: {model}")
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version = models[model]["version"]
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0",
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"Accept": "*/*",
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"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
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"Accept-Encoding": "gzip, deflate, br",
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"Referer": f"{cls.url}/",
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"Content-Type": "text/plain;charset=UTF-8",
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"Origin": cls.url,
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"Connection": "keep-alive",
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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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"Pragma": "no-cache",
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"Cache-Control": "no-cache",
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"TE": "trailers"
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}
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async with ClientSession(headers=headers) as session:
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prompt = format_prompt(messages)
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data = {
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"prompt": prompt,
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"version": version,
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"systemPrompt": kwargs.get("system_message", "You are a helpful assistant."),
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"temperature": kwargs.get("temperature", 0.75),
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"topP": kwargs.get("top_p", 0.9),
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"maxTokens": kwargs.get("max_tokens", 8000),
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"image": None
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}
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started = False
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async with session.post(f"{cls.url}/api", json=data, proxy=proxy) as response:
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response.raise_for_status()
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async for chunk in response.content.iter_any():
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if not started:
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chunk = chunk.lstrip()
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started = True
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yield chunk.decode()
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def format_prompt(messages: Messages):
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messages = [
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f"[INST] {message['content']} [/INST]"
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if message["role"] == "user"
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else message["content"]
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for message in messages
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]
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return "\n".join(messages) + "\n" |