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from __future__ import annotations
import time
from ast import List
import openai
from colorama import Fore, Style
from openai.error import APIError, RateLimitError
from autogpt.config import Config
from autogpt.logs import logger
CFG = Config()
openai.api_key = CFG.openai_api_key
def call_ai_function(
function: str, args: list, description: str, model: str | None = None
) -> str:
"""Call an AI function
This is a magic function that can do anything with no-code. See
https://github.com/Torantulino/AI-Functions for more info.
Args:
function (str): The function to call
args (list): The arguments to pass to the function
description (str): The description of the function
model (str, optional): The model to use. Defaults to None.
Returns:
str: The response from the function
"""
if model is None:
model = CFG.smart_llm_model
# For each arg, if any are None, convert to "None":
args = [str(arg) if arg is not None else "None" for arg in args]
# parse args to comma separated string
args = ", ".join(args)
messages = [
{
"role": "system",
"content": f"You are now the following python function: ```# {description}"
f"\n{function}```\n\nOnly respond with your `return` value.",
},
{"role": "user", "content": args},
]
return create_chat_completion(model=model, messages=messages, temperature=0)
# Overly simple abstraction until we create something better
# simple retry mechanism when getting a rate error or a bad gateway
def create_chat_completion(
messages: list, # type: ignore
model: str | None = None,
temperature: float = CFG.temperature,
max_tokens: int | None = None,
) -> str:
"""Create a chat completion using the OpenAI API
Args:
messages (list[dict[str, str]]): The messages to send to the chat completion
model (str, optional): The model to use. Defaults to None.
temperature (float, optional): The temperature to use. Defaults to 0.9.
max_tokens (int, optional): The max tokens to use. Defaults to None.
Returns:
str: The response from the chat completion
"""
response = None
num_retries = 10
warned_user = False
if CFG.debug_mode:
print(
Fore.GREEN
+ f"Creating chat completion with model {model}, temperature {temperature},"
f" max_tokens {max_tokens}" + Fore.RESET
)
for attempt in range(num_retries):
backoff = 2 ** (attempt + 2)
try:
if CFG.use_azure:
response = openai.ChatCompletion.create(
deployment_id=CFG.get_azure_deployment_id_for_model(model),
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
)
else:
response = openai.ChatCompletion.create(
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
)
break
except RateLimitError:
if CFG.debug_mode:
print(
Fore.RED + "Error: ",
f"Reached rate limit, passing..." + Fore.RESET,
)
if not warned_user:
logger.double_check(
f"Please double check that you have setup a {Fore.CYAN + Style.BRIGHT}PAID{Style.RESET_ALL} OpenAI API Account. "
+ f"You can read more here: {Fore.CYAN}https://github.com/Significant-Gravitas/Auto-GPT#openai-api-keys-configuration{Fore.RESET}"
)
warned_user = True
except APIError as e:
if e.http_status == 502:
pass
else:
raise
if attempt == num_retries - 1:
raise
if CFG.debug_mode:
print(
Fore.RED + "Error: ",
f"API Bad gateway. Waiting {backoff} seconds..." + Fore.RESET,
)
time.sleep(backoff)
if response is None:
logger.typewriter_log(
"FAILED TO GET RESPONSE FROM OPENAI",
Fore.RED,
"Auto-GPT has failed to get a response from OpenAI's services. "
+ f"Try running Auto-GPT again, and if the problem the persists try running it with `{Fore.CYAN}--debug{Fore.RESET}`.",
)
logger.double_check()
if CFG.debug_mode:
raise RuntimeError(f"Failed to get response after {num_retries} retries")
else:
quit(1)
return response.choices[0].message["content"]
def create_embedding_with_ada(text) -> list:
"""Create an embedding with text-ada-002 using the OpenAI SDK"""
num_retries = 10
for attempt in range(num_retries):
backoff = 2 ** (attempt + 2)
try:
if CFG.use_azure:
return openai.Embedding.create(
input=[text],
engine=CFG.get_azure_deployment_id_for_model(
"text-embedding-ada-002"
),
)["data"][0]["embedding"]
else:
return openai.Embedding.create(
input=[text], model="text-embedding-ada-002"
)["data"][0]["embedding"]
except RateLimitError:
pass
except APIError as e:
if e.http_status == 502:
pass
else:
raise
if attempt == num_retries - 1:
raise
if CFG.debug_mode:
print(
Fore.RED + "Error: ",
f"API Bad gateway. Waiting {backoff} seconds..." + Fore.RESET,
)
time.sleep(backoff)
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