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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
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