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92 lines
3.4 KiB
Python
92 lines
3.4 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 ..requests.raise_for_status import raise_for_status
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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class Llama(AsyncGeneratorProvider, ProviderModelMixin):
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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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default_model = "meta/meta-llama-3-70b-instruct"
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models = [
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"meta/llama-2-7b-chat",
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"meta/llama-2-13b-chat",
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"meta/llama-2-70b-chat",
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"meta/meta-llama-3-8b-instruct",
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"meta/meta-llama-3-70b-instruct",
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]
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model_aliases = {
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"meta-llama/Meta-Llama-3-8B-Instruct": "meta/meta-llama-3-8b-instruct",
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"meta-llama/Meta-Llama-3-70B-Instruct": "meta/meta-llama-3-70b-instruct",
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"meta-llama/Llama-2-7b-chat-hf": "meta/llama-2-7b-chat",
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"meta-llama/Llama-2-13b-chat-hf": "meta/llama-2-13b-chat",
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"meta-llama/Llama-2-70b-chat-hf": "meta/llama-2-70b-chat",
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}
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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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system_message: str = "You are a helpful assistant.",
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temperature: float = 0.75,
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top_p: float = 0.9,
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max_tokens: int = 8000,
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**kwargs
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) -> AsyncResult:
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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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system_messages = [message["content"] for message in messages if message["role"] == "system"]
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if system_messages:
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system_message = "\n".join(system_messages)
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messages = [message for message in messages if message["role"] != "system"]
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prompt = format_prompt(messages)
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data = {
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"prompt": prompt,
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"model": cls.get_model(model),
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"systemPrompt": system_message,
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"temperature": temperature,
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"topP": top_p,
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"maxTokens": max_tokens,
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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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await raise_for_status(response)
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async for chunk in response.content.iter_any():
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if not chunk:
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continue
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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(errors="ignore")
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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"
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