Add Llama2 Providers / Models

This commit is contained in:
Heiner Lohaus 2023-10-26 21:32:49 +02:00
parent 92a31d8281
commit 0d1ae405cc
4 changed files with 91 additions and 9 deletions

63
g4f/Provider/DeepInfra.py Normal file
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@ -0,0 +1,63 @@
from __future__ import annotations
import json
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider
class DeepInfra(AsyncGeneratorProvider):
url = "https://deepinfra.com"
working = True
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
**kwargs
) -> AsyncResult:
if not model:
model = "meta-llama/Llama-2-70b-chat-hf"
headers = {
"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/118.0",
"Accept": "text/event-stream",
"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
"Accept-Encoding": "gzip, deflate, br",
"Referer": f"{cls.url}/",
"Content-Type": "application/json",
"X-Deepinfra-Source": "web-page",
"Origin": cls.url,
"Connection": "keep-alive",
"Sec-Fetch-Dest": "empty",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-site",
"Pragma": "no-cache",
"Cache-Control": "no-cache",
}
async with ClientSession(headers=headers) as session:
data = {
"model": model,
"messages": messages,
"stream": True,
}
async with session.post(
"https://api.deepinfra.com/v1/openai/chat/completions",
json=data,
proxy=proxy
) as response:
response.raise_for_status()
first = True
async for line in response.content:
if line.startswith(b"data: [DONE]"):
break
elif line.startswith(b"data: "):
chunk = json.loads(line[6:])["choices"][0]["delta"].get("content")
if chunk:
if first:
chunk = chunk.lstrip()
if chunk:
first = False
yield chunk

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@ -6,15 +6,14 @@ from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider from .base_provider import AsyncGeneratorProvider
models = { models = {
"7B": {"name": "Llama 2 7B", "version": "d24902e3fa9b698cc208b5e63136c4e26e828659a9f09827ca6ec5bb83014381", "shortened":"7B"}, "meta-llama/Llama-2-7b-chat-hf": {"name": "Llama 2 7B", "version": "d24902e3fa9b698cc208b5e63136c4e26e828659a9f09827ca6ec5bb83014381", "shortened":"7B"},
"13B": {"name": "Llama 2 13B", "version": "9dff94b1bed5af738655d4a7cbcdcde2bd503aa85c94334fe1f42af7f3dd5ee3", "shortened":"13B"}, "meta-llama/Llama-2-13b-chat-hf": {"name": "Llama 2 13B", "version": "9dff94b1bed5af738655d4a7cbcdcde2bd503aa85c94334fe1f42af7f3dd5ee3", "shortened":"13B"},
"70B": {"name": "Llama 2 70B", "version": "2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf", "shortened":"70B"}, "meta-llama/Llama-2-70b-chat-hf": {"name": "Llama 2 70B", "version": "2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf", "shortened":"70B"},
"Llava": {"name": "Llava 13B", "version": "6bc1c7bb0d2a34e413301fee8f7cc728d2d4e75bfab186aa995f63292bda92fc", "shortened":"Llava"} "Llava": {"name": "Llava 13B", "version": "6bc1c7bb0d2a34e413301fee8f7cc728d2d4e75bfab186aa995f63292bda92fc", "shortened":"Llava"}
} }
class Llama2(AsyncGeneratorProvider): class Llama2(AsyncGeneratorProvider):
url = "https://www.llama2.ai" url = "https://www.llama2.ai"
supports_gpt_35_turbo = True
working = True working = True
@classmethod @classmethod
@ -26,8 +25,8 @@ class Llama2(AsyncGeneratorProvider):
**kwargs **kwargs
) -> AsyncResult: ) -> AsyncResult:
if not model: if not model:
model = "70B" model = "meta-llama/Llama-2-70b-chat-hf"
if model not in models: elif model not in models:
raise ValueError(f"Model are not supported: {model}") raise ValueError(f"Model are not supported: {model}")
version = models[model]["version"] version = models[model]["version"]
headers = { headers = {
@ -54,7 +53,7 @@ class Llama2(AsyncGeneratorProvider):
"systemPrompt": kwargs.get("system_message", "You are a helpful assistant."), "systemPrompt": kwargs.get("system_message", "You are a helpful assistant."),
"temperature": kwargs.get("temperature", 0.75), "temperature": kwargs.get("temperature", 0.75),
"topP": kwargs.get("top_p", 0.9), "topP": kwargs.get("top_p", 0.9),
"maxTokens": kwargs.get("max_tokens", 1024), "maxTokens": kwargs.get("max_tokens", 8000),
"image": None "image": None
} }
started = False started = False
@ -73,4 +72,4 @@ def format_prompt(messages: Messages):
else message["content"] else message["content"]
for message in messages for message in messages
] ]
return "\n".join(messages) return "\n".join(messages) + "\n"

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@ -17,6 +17,7 @@ from .ChatgptFree import ChatgptFree
from .ChatgptLogin import ChatgptLogin from .ChatgptLogin import ChatgptLogin
from .ChatgptX import ChatgptX from .ChatgptX import ChatgptX
from .Cromicle import Cromicle from .Cromicle import Cromicle
from .DeepInfra import DeepInfra
from .FakeGpt import FakeGpt from .FakeGpt import FakeGpt
from .FreeGpt import FreeGpt from .FreeGpt import FreeGpt
from .GPTalk import GPTalk from .GPTalk import GPTalk
@ -70,6 +71,7 @@ class ProviderUtils:
'ChatgptX': ChatgptX, 'ChatgptX': ChatgptX,
'CodeLinkAva': CodeLinkAva, 'CodeLinkAva': CodeLinkAva,
'Cromicle': Cromicle, 'Cromicle': Cromicle,
'DeepInfra': DeepInfra,
'DfeHub': DfeHub, 'DfeHub': DfeHub,
'EasyChat': EasyChat, 'EasyChat': EasyChat,
'Equing': Equing, 'Equing': Equing,
@ -144,6 +146,7 @@ __all__ = [
'ChatgptLogin', 'ChatgptLogin',
'ChatgptX', 'ChatgptX',
'Cromicle', 'Cromicle',
'DeepInfra',
'CodeLinkAva', 'CodeLinkAva',
'DfeHub', 'DfeHub',
'EasyChat', 'EasyChat',

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@ -6,12 +6,14 @@ from .Provider import (
GptForLove, GptForLove,
ChatgptAi, ChatgptAi,
GptChatly, GptChatly,
DeepInfra,
ChatgptX, ChatgptX,
ChatBase, ChatBase,
GeekGpt, GeekGpt,
FakeGpt, FakeGpt,
FreeGpt, FreeGpt,
NoowAi, NoowAi,
Llama2,
Vercel, Vercel,
Aichat, Aichat,
GPTalk, GPTalk,
@ -74,6 +76,21 @@ gpt_4 = Model(
]) ])
) )
llama2_7b = Model(
name = "meta-llama/Llama-2-7b-chat-hf",
base_provider = 'huggingface',
best_provider = RetryProvider([Llama2, DeepInfra]))
llama2_13b = Model(
name ="meta-llama/Llama-2-13b-chat-hf",
base_provider = 'huggingface',
best_provider = RetryProvider([Llama2, DeepInfra]))
llama2_70b = Model(
name = "meta-llama/Llama-2-70b-chat-hf",
base_provider = "huggingface",
best_provider = RetryProvider([Llama2, DeepInfra]))
# Bard # Bard
palm = Model( palm = Model(
name = 'palm', name = 'palm',