from __future__ import annotations
import json, base64, requests, random, os
try:
import execjs
has_requirements = True
except ImportError:
has_requirements = False
from ..typing import Messages, CreateResult
from .base_provider import AbstractProvider
from ..requests import raise_for_status
from ..errors import MissingRequirementsError, RateLimitError, ResponseStatusError
class Vercel(AbstractProvider):
url = 'https://chat.vercel.ai'
working = True
supports_message_history = True
supports_system_message = True
supports_gpt_35_turbo = True
supports_stream = True
@staticmethod
def create_completion(
model: str,
messages: Messages,
stream: bool,
proxy: str = None,
max_retries: int = 6,
**kwargs
) -> CreateResult:
if not has_requirements:
raise MissingRequirementsError('Install "PyExecJS" package')
headers = {
'authority': 'chat.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': get_anti_bot_token(),
'origin': 'https://chat.vercel.ai',
'pragma': 'no-cache',
'referer': 'https://chat.vercel.ai/',
'sec-ch-ua': '"Chromium";v="122", "Not(A:Brand";v="24", "Google Chrome";v="122"',
'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/122.0.0.0 Safari/537.36',
}
json_data = {
'messages': messages,
'id' : f'{os.urandom(3).hex()}a',
}
response = None
for _ in range(max_retries):
response = requests.post('https://chat.vercel.ai/api/chat',
headers=headers, json=json_data, stream=True, proxies={"https": proxy})
if not response.ok:
continue
for token in response.iter_content(chunk_size=None):
try:
yield token.decode(errors="ignore")
except UnicodeDecodeError:
pass
break
raise_for_status(response)
def get_anti_bot_token() -> 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': f'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.{random.randint(99, 999)}.{random.randint(99, 999)} Safari/537.36',
}
response = requests.get('https://chat.vercel.ai/openai.jpeg',
headers=headers).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'])
sec_list = [execjs.compile(js_script).call('')[0], [], "sentinel"]
raw_token = json.dumps({'r': sec_list, 't': raw_data['t']},
separators = (",", ":"))
return base64.b64encode(raw_token.encode('utf-8')).decode()