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() 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"