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from __future__ import annotations
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider
models = {
"meta-llama/Llama-2-7b-chat-hf": "meta/llama-2-7b-chat",
"meta-llama/Llama-2-13b-chat-hf": "meta/llama-2-13b-chat",
"meta-llama/Llama-2-70b-chat-hf": "meta/llama-2-70b-chat",
}
class Llama2(AsyncGeneratorProvider):
url = "https://www.llama2.ai"
working = True
supports_message_history = True
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
**kwargs
) -> AsyncResult:
if not model:
model = "meta/llama-2-70b-chat"
elif model in models:
model = models[model]
headers = {
"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0",
"Accept": "*/*",
"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
"Accept-Encoding": "gzip, deflate, br",
"Referer": f"{cls.url}/",
"Content-Type": "text/plain;charset=UTF-8",
"Origin": cls.url,
"Connection": "keep-alive",
"Sec-Fetch-Dest": "empty",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
"Pragma": "no-cache",
"Cache-Control": "no-cache",
"TE": "trailers"
}
async with ClientSession(headers=headers) as session:
prompt = format_prompt(messages)
data = {
"prompt": prompt,
"model": model,
"systemPrompt": kwargs.get("system_message", "You are a helpful assistant."),
"temperature": kwargs.get("temperature", 0.75),
"topP": kwargs.get("top_p", 0.9),
"maxTokens": kwargs.get("max_tokens", 8000),
"image": None
}
started = False
async with session.post(f"{cls.url}/api", json=data, proxy=proxy) as response:
response.raise_for_status()
async for chunk in response.content.iter_any():
if not started:
chunk = chunk.lstrip()
started = True
yield chunk.decode(errors="ignore")
def format_prompt(messages: Messages):
messages = [
f"[INST] {message['content']} [/INST]"
if message["role"] == "user"
else message["content"]
for message in messages
]
return "\n".join(messages) + "\n"
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