File size: 1,989 Bytes
870ab6b |
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 |
import json, random, string, time
from aiohttp import ClientSession
from ..typing import Any, CreateResult
from .base_provider import AsyncProvider, format_prompt
class Qidinam(AsyncProvider):
url = "https://ai.qidianym.net/api/chat-process"
working = True
supports_gpt_35_turbo = True
supports_stream = True
@classmethod
async def create_async(
cls,
model: str,
messages: dict[str, str],
**kwargs: Any,
) -> CreateResult:
base = ""
for message in messages:
base += "%s: %s\n" % (message["role"], message["content"])
base += "assistant:"
headers = {
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36"
}
data: dict[str, Any] = {
"prompt": base,
"options": {},
"systemMessage": "You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown.",
"temperature": kwargs.get("temperature", 0.8),
"top_p": kwargs.get("top_p", 1),
}
url = "https://ai.qidianym.net/api/chat-process"
# Use aiohttp for asynchronous HTTP requests
async with ClientSession() as session:
async with session.post(url, headers=headers, json=data) as response:
response.raise_for_status()
lines = response.text.strip().split("\n")
res = json.loads(lines[-1])
return await res["text"]
@classmethod
@property
def params(cls):
params = [
("model", "str"),
("messages", "list[dict[str, str]]"),
("stream", "bool"),
("temperature", "float"),
("top_p", "int"),
]
param = ", ".join([": ".join(p) for p in params])
return f"g4f.provider.{cls.__name__} supports: ({param})"
|