File size: 6,471 Bytes
fd1c2b0 5f283da fd1c2b0 5f283da fd1c2b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 |
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
|