mirror of https://github.com/HazyResearch/manifest
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
131 lines
3.5 KiB
Python
131 lines
3.5 KiB
Python
"""Client class."""
|
|
import logging
|
|
import os
|
|
from typing import Any, Callable, Dict, Optional, Tuple
|
|
|
|
from pyChatGPT import ChatGPT
|
|
|
|
from manifest.clients.client import Client
|
|
from manifest.request import LMRequest, Request
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class ChatGPTClient(Client):
|
|
"""ChatGPT Client class."""
|
|
|
|
# No params for ChatGPT
|
|
PARAMS = {}
|
|
REQUEST_CLS = LMRequest
|
|
|
|
def connect(
|
|
self, connection_str: Optional[str], client_args: Dict[str, Any]
|
|
) -> None:
|
|
"""
|
|
Connect to ChatGPT.
|
|
|
|
We use https://github.com/terry3041/pyChatGPT.
|
|
|
|
Arsg:
|
|
connection_str: connection string.
|
|
client_args: client arguments.
|
|
"""
|
|
self.session_key = os.environ.get("CHATGPT_SESSION_KEY", connection_str)
|
|
if self.session_key is None:
|
|
raise ValueError(
|
|
"ChatGPT session key not set. Set CHATGPT_SESSION_KEY environment "
|
|
"variable or pass through `client_connection`. "
|
|
"For details, see https://github.com/terry3041/pyChatGPT "
|
|
"and go through instructions for getting a session key."
|
|
)
|
|
self.host = None
|
|
for key in self.PARAMS:
|
|
setattr(self, key, client_args.pop(key, self.PARAMS[key][1]))
|
|
self._chat_session = ChatGPT(self.session_key, verbose=False)
|
|
|
|
def close(self) -> None:
|
|
"""Close the client."""
|
|
self._chat_session = None
|
|
|
|
def clear_conversations(self) -> None:
|
|
"""Clear conversations.
|
|
|
|
Only works for ChatGPT.
|
|
"""
|
|
self._chat_session.clear_conversations()
|
|
|
|
def get_generation_url(self) -> str:
|
|
"""Get generation URL."""
|
|
return ""
|
|
|
|
def get_generation_header(self) -> Dict[str, str]:
|
|
"""
|
|
Get generation header.
|
|
|
|
Returns:
|
|
header.
|
|
"""
|
|
return {}
|
|
|
|
def supports_batch_inference(self) -> bool:
|
|
"""Return whether the client supports batch inference."""
|
|
return False
|
|
|
|
def get_model_params(self) -> Dict:
|
|
"""
|
|
Get model params.
|
|
|
|
By getting model params from the server, we can add to request
|
|
and make sure cache keys are unique to model.
|
|
|
|
Returns:
|
|
model params.
|
|
"""
|
|
return {"model_name": "chatgpt", "engine": "chatgpt"}
|
|
|
|
def format_response(self, response: Dict) -> Dict[str, Any]:
|
|
"""
|
|
Format response to dict.
|
|
|
|
Args:
|
|
response: response
|
|
|
|
Return:
|
|
response as dict
|
|
"""
|
|
return {
|
|
"model": "chatgpt",
|
|
"choices": [
|
|
{
|
|
"text": response["message"],
|
|
}
|
|
],
|
|
}
|
|
|
|
def get_request(self, request: Request) -> Tuple[Callable[[], Dict], Dict]:
|
|
"""
|
|
Get request string function.
|
|
|
|
Args:
|
|
request: request.
|
|
|
|
Returns:
|
|
request function that takes no input.
|
|
request parameters as dict.
|
|
"""
|
|
if isinstance(request.prompt, list):
|
|
raise ValueError("ChatGPT does not support batch inference.")
|
|
|
|
prompt = str(request.prompt)
|
|
request_params = request.to_dict(self.PARAMS)
|
|
|
|
def _run_completion() -> Dict:
|
|
try:
|
|
res = self._chat_session.send_message(prompt)
|
|
except Exception as e:
|
|
logger.error(f"ChatGPT error {e}.")
|
|
raise e
|
|
return self.format_response(res)
|
|
|
|
return _run_completion, request_params
|