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manifest/manifest/clients/openai.py

137 lines
3.9 KiB
Python

"""OpenAI client."""
import logging
import os
from typing import Any, Callable, Dict, List, Optional, Tuple
import openai
from manifest.clients.client import Client
logging.getLogger("openai").setLevel(logging.WARNING)
logger = logging.getLogger(__name__)
OPENAI_ENGINES = {
"text-davinci-002",
"text-davinci-001",
"davinci",
"text-curie-001",
"text-babbage-001",
"text-ada-001",
"code-davinci-002",
"code-cushman-001",
}
# User param -> (client param, default value)
OPENAI_PARAMS = {
"engine": ("engine", "text-davinci-002"),
"temperature": ("temperature", 1.0),
"max_tokens": ("max_tokens", 10),
"n": ("n", 1),
"top_p": ("top_p", 1.0),
"logprobs": ("logprobs", None),
"top_k_return": ("best_of", 1),
"stop_sequence": ("stop", None), # OpenAI doesn't like empty lists
"presence_penalty": ("presence_penalty", 0.0),
"frequency_penalty": ("frequency_penalty", 0.0),
}
class OpenAIClient(Client):
"""OpenAI client."""
def connect(
self,
connection_str: Optional[str] = None,
client_args: Dict[str, Any] = {},
) -> None:
"""
Connect to the OpenAI server.
connection_str is passed as default OPENAI_API_KEY if variable not set.
Args:
connection_str: connection string.
client_args: client arguments.
"""
openai.api_key = os.environ.get("OPENAI_API_KEY", connection_str)
if openai.api_key is None:
raise ValueError(
"OpenAI API key not set. Set OPENAI_API_KEY environment "
"variable or pass through `connection_str`."
)
for key in OPENAI_PARAMS:
setattr(self, key, client_args.pop(key, OPENAI_PARAMS[key][1]))
if getattr(self, "engine") not in OPENAI_ENGINES:
raise ValueError(
f"Invalid engine {getattr(self, 'engine')}. Must be {OPENAI_ENGINES}."
)
def close(self) -> None:
"""Close the client."""
pass
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": "openai", "engine": getattr(self, "engine")}
def get_model_inputs(self) -> List:
"""
Get allowable model inputs.
Returns:
model inputs.
"""
return list(OPENAI_PARAMS.keys())
def get_request(
self, query: str, request_args: Dict[str, Any] = {}
) -> Tuple[Callable[[], Dict], Dict]:
"""
Get request string function.
Args:
query: query string.
Returns:
request function that takes no input.
request parameters as dict.
"""
request_params = {"prompt": query}
for key in OPENAI_PARAMS:
request_params[OPENAI_PARAMS[key][0]] = request_args.pop(
key, getattr(self, key)
)
def _run_completion() -> Dict:
try:
return openai.Completion.create(**request_params)
except openai.error.OpenAIError as e:
logger.error(e)
raise e
return _run_completion, request_params
def get_choice_logit_request(
self, query: str, gold_choices: List[str], request_args: Dict[str, Any] = {}
) -> Tuple[Callable[[], Dict], Dict]:
"""
Get request string function for choosing max choices.
Args:
query: query string.
gold_choices: choices for model to choose from via max logits.
Returns:
request function that takes no input.
request parameters as dict.
"""
raise NotImplementedError("OpenAI does not support choice logit request.")