from __future__ import annotations
import json, base64, requests, execjs, random, uuid
from aiohttp import ClientSession
from ..typing import Any, TypedDict, AsyncGenerator
from .base_provider import AsyncGeneratorProvider
class Vercel(AsyncGeneratorProvider):
url = 'https://sdk.vercel.ai'
working = True
supports_gpt_35_turbo = True
supports_stream = True
_anti_bot_token = None
@classmethod
async def create_async_generator(
cls,
model: str,
messages: list[dict[str, str]],
stream: bool,
proxy: str = None,
**kwargs
) -> AsyncGenerator:
if not model:
model = "gpt-3.5-turbo"
elif model not in model_info:
raise ValueError(f"Model are not supported: {model}")
if not cls._anti_bot_token:
cls._anti_bot_token = get_anti_bot_token(proxy)
json_data = {
'model' : model_info[model]['id'],
'messages' : messages,
'playgroundId': str(uuid.uuid4()),
'chatIndex' : 0
} | model_info[model]['default_params']
for tries in range(100):
headers = {
'authority' : 'sdk.vercel.ai',
'accept' : '*/*',
'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
'cache-control' : 'no-cache',
'content-type' : 'application/json',
'custom-encoding' : cls._anti_bot_token,
'origin' : 'https://sdk.vercel.ai',
'pragma' : 'no-cache',
'referer' : 'https://sdk.vercel.ai/',
'sec-ch-ua' : '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
'sec-ch-ua-mobile' : '?0',
'sec-ch-ua-platform': '"macOS"',
'sec-fetch-dest' : 'empty',
'sec-fetch-mode' : 'cors',
'sec-fetch-site' : 'same-origin',
'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.%s.%s Safari/537.36' % (
random.randint(99, 999),
random.randint(99, 999)
)
}
async with ClientSession(
headers=headers
) as session:
async with session.post(f"{cls.url}/api/generate", proxy=proxy, json=json_data) as response:
try:
response.raise_for_status()
except Exception as e:
if tries >= 99:
raise e
# Maybe the token is the reason for failing
cls._anti_bot_token = get_anti_bot_token(proxy)
continue
async for token in response.content.iter_any():
yield token.decode()
break
def get_anti_bot_token(proxy: str = None) -> str:
headers = {
'authority' : 'sdk.vercel.ai',
'accept' : '*/*',
'accept-language' : 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
'cache-control' : 'no-cache',
'pragma' : 'no-cache',
'referer' : 'https://sdk.vercel.ai/',
'sec-ch-ua' : '"Google Chrome";v="117", "Not;A=Brand";v="8", "Chromium";v="117"',
'sec-ch-ua-mobile' : '?0',
'sec-ch-ua-platform': '"macOS"',
'sec-fetch-dest' : 'empty',
'sec-fetch-mode' : 'cors',
'sec-fetch-site' : 'same-origin',
'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.%s.%s Safari/537.36' % (
random.randint(99, 999),
random.randint(99, 999)
)
}
# Does not work with async requests
response = requests.get('https://sdk.vercel.ai/openai.jpeg',
headers=headers, proxies={"https": proxy}).text
raw_data = json.loads(base64.b64decode(response,
validate=True))
js_script = '''const globalThis={marker:"mark"};String.prototype.fontcolor=function(){return `<font>${this}</font>`};
return (%s)(%s)''' % (raw_data['c'], raw_data['a'])
raw_token = json.dumps({'r': execjs.compile(js_script).call(''), 't': raw_data['t']},
separators = (",", ":"))
return base64.b64encode(raw_token.encode('utf-16le')).decode()
class ModelInfo(TypedDict):
id: str
default_params: dict[str, Any]
model_info: dict[str, ModelInfo] = {
'claude-instant-v1': {
'id': 'anthropic:claude-instant-v1',
'default_params': {
'temperature': 1,
'maximumLength': 1024,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': ['\n\nHuman:'],
},
},
'claude-v1': {
'id': 'anthropic:claude-v1',
'default_params': {
'temperature': 1,
'maximumLength': 1024,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': ['\n\nHuman:'],
},
},
'claude-v2': {
'id': 'anthropic:claude-v2',
'default_params': {
'temperature': 1,
'maximumLength': 1024,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': ['\n\nHuman:'],
},
},
'a16z-infra/llama7b-v2-chat': {
'id': 'replicate:a16z-infra/llama7b-v2-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'a16z-infra/llama13b-v2-chat': {
'id': 'replicate:a16z-infra/llama13b-v2-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'replicate/llama-2-70b-chat': {
'id': 'replicate:replicate/llama-2-70b-chat',
'default_params': {
'temperature': 0.75,
'maximumLength': 3000,
'topP': 1,
'repetitionPenalty': 1,
},
},
'bigscience/bloom': {
'id': 'huggingface:bigscience/bloom',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'google/flan-t5-xxl': {
'id': 'huggingface:google/flan-t5-xxl',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'EleutherAI/gpt-neox-20b': {
'id': 'huggingface:EleutherAI/gpt-neox-20b',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
'stopSequences': [],
},
},
'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5': {
'id': 'huggingface:OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
'default_params': {
'maximumLength': 1024,
'typicalP': 0.2,
'repetitionPenalty': 1,
},
},
'OpenAssistant/oasst-sft-1-pythia-12b': {
'id': 'huggingface:OpenAssistant/oasst-sft-1-pythia-12b',
'default_params': {
'maximumLength': 1024,
'typicalP': 0.2,
'repetitionPenalty': 1,
},
},
'bigcode/santacoder': {
'id': 'huggingface:bigcode/santacoder',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 0.95,
'topK': 4,
'repetitionPenalty': 1.03,
},
},
'command-light-nightly': {
'id': 'cohere:command-light-nightly',
'default_params': {
'temperature': 0.9,
'maximumLength': 1024,
'topP': 1,
'topK': 0,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'command-nightly': {
'id': 'cohere:command-nightly',
'default_params': {
'temperature': 0.9,
'maximumLength': 1024,
'topP': 1,
'topK': 0,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'gpt-4': {
'id': 'openai:gpt-4',
'default_params': {
'temperature': 0.7,
'maximumLength': 8192,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'gpt-4-0613': {
'id': 'openai:gpt-4-0613',
'default_params': {
'temperature': 0.7,
'maximumLength': 8192,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'code-davinci-002': {
'id': 'openai:code-davinci-002',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'gpt-3.5-turbo': {
'id': 'openai:gpt-3.5-turbo',
'default_params': {
'temperature': 0.7,
'maximumLength': 4096,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'gpt-3.5-turbo-16k': {
'id': 'openai:gpt-3.5-turbo-16k',
'default_params': {
'temperature': 0.7,
'maximumLength': 16280,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'gpt-3.5-turbo-16k-0613': {
'id': 'openai:gpt-3.5-turbo-16k-0613',
'default_params': {
'temperature': 0.7,
'maximumLength': 16280,
'topP': 1,
'topK': 1,
'presencePenalty': 1,
'frequencyPenalty': 1,
'stopSequences': [],
},
},
'text-ada-001': {
'id': 'openai:text-ada-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-babbage-001': {
'id': 'openai:text-babbage-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-curie-001': {
'id': 'openai:text-curie-001',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-davinci-002': {
'id': 'openai:text-davinci-002',
'default_params': {
'temperature': 0.5,
'maximumLength': 1024,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
'text-davinci-003': {
'id': 'openai:text-davinci-003',
'default_params': {
'temperature': 0.5,
'maximumLength': 4097,
'topP': 1,
'presencePenalty': 0,
'frequencyPenalty': 0,
'stopSequences': [],
},
},
}
