1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
|
from __future__ import annotations
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider
models = {
"7B": {"name": "Llama 2 7B", "version": "d24902e3fa9b698cc208b5e63136c4e26e828659a9f09827ca6ec5bb83014381", "shortened":"7B"},
"13B": {"name": "Llama 2 13B", "version": "9dff94b1bed5af738655d4a7cbcdcde2bd503aa85c94334fe1f42af7f3dd5ee3", "shortened":"13B"},
"70B": {"name": "Llama 2 70B", "version": "2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf", "shortened":"70B"},
"Llava": {"name": "Llava 13B", "version": "6bc1c7bb0d2a34e413301fee8f7cc728d2d4e75bfab186aa995f63292bda92fc", "shortened":"Llava"}
}
class Llama2(AsyncGeneratorProvider):
url = "https://www.llama2.ai"
supports_gpt_35_turbo = True
working = True
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
**kwargs
) -> AsyncResult:
if not model:
model = "70B"
if model not in models:
raise ValueError(f"Model are not supported: {model}")
version = models[model]["version"]
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,
"version": version,
"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", 1024),
"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)
|
