hf-llm-api / tests /openai.py
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:gem: [Feature] Enable conversation with openai
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import copy
import uuid
from pathlib import Path
from curl_cffi import requests
from tclogger import logger, OSEnver
secrets_path = Path(__file__).parents[1] / "secrets.json"
ENVER = OSEnver(secrets_path)
class OpenaiAPI:
def __init__(self):
self.init_requests_params()
def init_requests_params(self):
self.api_base = "https://chat.openai.com/backend-anon"
self.api_me = f"{self.api_base}/me"
self.api_models = f"{self.api_base}/models"
self.api_chat_requirements = f"{self.api_base}/sentinel/chat-requirements"
self.api_conversation = f"{self.api_base}/conversation"
self.uuid = str(uuid.uuid4())
self.requests_headers = {
# "Accept": "*/*",
"Accept-Encoding": "gzip, deflate, br, zstd",
"Accept-Language": "en-US,en;q=0.9",
"Cache-Control": "no-cache",
"Content-Type": "application/json",
"Oai-Device-Id": self.uuid,
"Oai-Language": "en-US",
"Pragma": "no-cache",
"Referer": "https://chat.openai.com/",
"Sec-Ch-Ua": 'Google Chrome";v="123", "Not:A-Brand";v="8", "Chromium";v="123"',
"Sec-Ch-Ua-Mobile": "?0",
"Sec-Ch-Ua-Platform": '"Windows"',
"Sec-Fetch-Dest": "empty",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36",
}
http_proxy = ENVER["http_proxy"]
if http_proxy:
self.requests_proxies = {
"http": http_proxy,
"https": http_proxy,
}
else:
self.requests_proxies = None
def log_request(self, url, method="GET"):
if ENVER["http_proxy"]:
logger.note(f"> Using Proxy:", end=" ")
logger.mesg(f"{ENVER['http_proxy']}")
logger.note(f"> {method}:", end=" ")
logger.mesg(f"{url}", end=" ")
def log_response(self, res: requests.Response, stream=False):
status_code = res.status_code
status_code_str = f"[{status_code}]"
if status_code == 200:
logger_func = logger.success
else:
logger_func = logger.warn
logger_func(status_code_str)
if stream:
logger_func(res.text)
else:
logger_func(res.json())
def get_models(self):
self.log_request(self.api_models)
res = requests.get(
self.api_models,
headers=self.requests_headers,
proxies=self.requests_proxies,
timeout=10,
impersonate="chrome120",
)
self.log_response(res)
def auth(self):
self.log_request(self.api_chat_requirements, method="POST")
res = requests.post(
self.api_chat_requirements,
headers=self.requests_headers,
proxies=self.requests_proxies,
timeout=10,
impersonate="chrome120",
)
self.chat_requirements_token = res.json()["token"]
self.log_response(res)
def chat_completions(self, prompt: str):
new_headers = {
"Accept": "text/event-stream",
"Openai-Sentinel-Chat-Requirements-Token": self.chat_requirements_token,
}
requests_headers = copy.deepcopy(self.requests_headers)
requests_headers.update(new_headers)
post_data = {
"action": "next",
"messages": [
{
"id": self.uuid,
"author": {"role": "user"},
"content": {"content_type": "text", "parts": [prompt]},
"metadata": {},
}
],
"parent_message_id": str(uuid.uuid4()),
"model": "text-davinci-002-render-sha",
"timezone_offset_min": -480,
"suggestions": [],
"history_and_training_disabled": False,
"conversation_mode": {"kind": "primary_assistant"},
"force_paragen": False,
"force_paragen_model_slug": "",
"force_nulligen": False,
"force_rate_limit": False,
"websocket_request_id": str(uuid.uuid4()),
}
self.log_request(self.api_conversation, method="POST")
res = requests.post(
self.api_conversation,
headers=requests_headers,
json=post_data,
proxies=self.requests_proxies,
timeout=10,
impersonate="chrome120",
)
self.log_response(res, stream=True)
if __name__ == "__main__":
api = OpenaiAPI()
# api.get_models()
api.auth()
prompt = "who are you?"
api.chat_completions(prompt)
# python -m tests.openai