import copy import json import re import uuid from pathlib import Path from curl_cffi import requests from tclogger import logger, OSEnver from constants.envs import PROXIES 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", } def log_request(self, url, method="GET"): logger.note(f"> {method}:", end=" ") logger.mesg(f"{url}", end=" ") def log_response(self, res: requests.Response, stream=False, verbose=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 verbose: if stream: if not hasattr(self, "content_offset"): self.content_offset = 0 for line in res.iter_lines(): line = line.decode("utf-8") line = re.sub(r"^data:\s*", "", line) if re.match(r"^\[DONE\]", line): logger.success("\n[Finished]") break line = line.strip() if line: try: data = json.loads(line, strict=False) message_role = data["message"]["author"]["role"] message_status = data["message"]["status"] if ( message_role == "assistant" and message_status == "in_progress" ): content = data["message"]["content"]["parts"][0] delta_content = content[self.content_offset :] self.content_offset = len(content) logger_func(delta_content, end="") except Exception as e: logger.warn(e) 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=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=PROXIES, timeout=10, impersonate="chrome120", ) self.chat_requirements_token = res.json()["token"] self.log_response(res) def transform_messages(self, messages: list[dict]): def get_role(role): if role in ["system", "user", "assistant"]: return role else: return "system" new_messages = [ { "author": {"role": get_role(message["role"])}, "content": {"content_type": "text", "parts": [message["content"]]}, "metadata": {}, } for message in messages ] return new_messages def chat_completions(self, messages: list[dict]): 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": self.transform_messages(messages), "parent_message_id": "", "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") s = requests.Session() res = s.post( self.api_conversation, headers=requests_headers, json=post_data, proxies=PROXIES, timeout=10, impersonate="chrome120", stream=True, ) self.log_response(res, stream=True, verbose=True) if __name__ == "__main__": api = OpenaiAPI() # api.get_models() api.auth() messages = [ {"role": "system", "content": "I am Niansuh"}, {"role": "system", "content": "I have a cat named Lucky"}, {"role": "user", "content": "Repeat my name and my cat's name"}, { "role": "assistant", "content": "Your name is Niansuh and your cat's name is Lucky.", }, {"role": "user", "content": "summarize our conversation"}, ] api.chat_completions(messages) # python -m tests.openai