monra's picture
Adds all providers from the original API
d4adf88
raw
history blame
3.5 kB
# -*- coding: utf-8 -*-
"""
@Time : 2023/5/23 13:37
@Auth : Hp_mzx
@File :__init__.py.py
@IDE :PyCharm
"""
import json
import uuid
import random
import binascii
import requests
import Crypto.Cipher.AES as AES
from fake_useragent import UserAgent
class ChatCompletion:
@staticmethod
def create(messages:[],proxy: str = None):
url = "https://chat.getgpt.world/api/chat/stream"
headers = {
"Content-Type": "application/json",
"Referer": "https://chat.getgpt.world/",
'user-agent': UserAgent().random,
}
proxies = {'http': 'http://' + proxy, 'https': 'http://' + proxy} if proxy else None
data = json.dumps({
"messages": messages,
"frequency_penalty": 0,
"max_tokens": 4000,
"model": "gpt-3.5-turbo",
"presence_penalty": 0,
"temperature": 1,
"top_p": 1,
"stream": True,
"uuid": str(uuid.uuid4())
})
signature = ChatCompletion.encrypt(data)
res = requests.post(url, headers=headers, data=json.dumps({"signature": signature}), proxies=proxies,stream=True)
for chunk in res.iter_content(chunk_size=None):
res.raise_for_status()
datas = chunk.decode('utf-8').split('data: ')
for data in datas:
if not data or "[DONE]" in data:
continue
data_json = json.loads(data)
content = data_json['choices'][0]['delta'].get('content')
if content:
yield content
@staticmethod
def random_token(e):
token = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789"
n = len(token)
return "".join([token[random.randint(0, n - 1)] for i in range(e)])
@staticmethod
def encrypt(e):
t = ChatCompletion.random_token(16).encode('utf-8')
n = ChatCompletion.random_token(16).encode('utf-8')
r = e.encode('utf-8')
cipher = AES.new(t, AES.MODE_CBC, n)
ciphertext = cipher.encrypt(ChatCompletion.__pad_data(r))
return binascii.hexlify(ciphertext).decode('utf-8') + t.decode('utf-8') + n.decode('utf-8')
@staticmethod
def __pad_data(data: bytes) -> bytes:
block_size = AES.block_size
padding_size = block_size - len(data) % block_size
padding = bytes([padding_size] * padding_size)
return data + padding
class Completion:
@staticmethod
def create(prompt:str,proxy:str=None):
return ChatCompletion.create([
{
"content": "You are ChatGPT, a large language model trained by OpenAI.\nCarefully heed the user's instructions. \nRespond using Markdown.",
"role": "system"
},
{"role": "user", "content": prompt}
], proxy)
if __name__ == '__main__':
# single completion
text = ""
for chunk in Completion.create("你是谁", "127.0.0.1:7890"):
text = text + chunk
print(chunk, end="", flush=True)
print()
#chat completion
message = []
while True:
prompt = input("请输入问题:")
message.append({"role": "user","content": prompt})
text = ""
for chunk in ChatCompletion.create(message,'127.0.0.1:7890'):
text = text+chunk
print(chunk, end="", flush=True)
print()
message.append({"role": "assistant", "content": text})