vital remnant
It seems the cookbook is out of date, is there a new way to handle this?
import random
import time
import openai
from openai import OpenAI
client = OpenAI()
def retry_with_exponential_backoff(
func,
initial_delay: float = 1,
exponential_base: float = 2,
jitter: bool = True,
max_retries: int = 10,
errors: tuple = (openai.RateLimitError,),
):
rapid vesselBOT
Hi @vital remnant. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:
The code you've provided is a manual implementation of a retry mechanism with exponential backoff. This is a common strategy to handle rate limit errors when making API requests. The idea is to retry the request after a delay if a rate limit error is encountered. The delay increases exponentially with each subsequent retry, hence the term "exponential backoff". Adding a random "jitter" helps to avoid a thundering herd problem where all retries could potentially hit at the same time.
Here's the complete code from the knowledge sources:
# imports
import random
import time
import openai
from openai import OpenAI
client = OpenAI()
# define a retry decorator
def retry_with_exponential_backoff(
func,
initial_delay: float = 1,
exponential_base: float = 2,
jitter: bool = True,
max_retries: int = 10,
errors: tuple = (openai.RateLimitError,),
):
"""Retry a function with exponential backoff."""
def wrapper(*args, **kwargs):
# Initialize variables
num_retries = 0
delay = initial_delay
# Loop until a successful response or max_retries is hit or an exception is raised
while True:
try:
return func(*args, **kwargs)
# Retry on specified errors
except errors as e:
# Increment retries
num_retries += 1
# Check if max retries has been reached
if num_retries > max_retries:
raise Exception(
f"Maximum number of retries ({max_retries}) exceeded."
)
# Increment the delay
delay *= exponential_base * (1 + jitter * random.random())
# Sleep for the delay
time.sleep(delay) except Exception as e:
raise e
return wrapper
@retry_with_exponential_backoff
def completions_with_backoff(**kwargs):
return client.completions.create(**kwargs)
This code defines a decorator `retry_with_exponential_backoff` that can be used to wrap any function that makes API requests. If the function raises a `RateLimitError`, it will automatically retry the request after a delay. The delay starts at `initial_delay` seconds and increases exponentially for each subsequent retry, up to a maximum of `max_retries` retries.
Please note that OpenAI makes no guarantees on the security or efficiency of this solution but it can be a good starting place for your own solution (**source** (<https://platform.openai.com/docs/guides/rate-limits>)).
If you're looking for other ways to handle rate limits, OpenAI also provides an example script for parallel processing large quantities of API requests, which includes features for throttling request and token usage to stay under rate limits (**source** (<https://cookbook.openai.com/examples/how_to_handle_rate_limits#example-parallel-processing-script>)).
----------------------
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----------------------@rapid vessel ok, but the openai object no longer contains an error structure, so that can't be correct
rapid vesselBOT
Let me check the knowledge base for you. One moment! :books:
You're correct. The OpenAI Python library has been updated and the error handling has changed. The errors are now accessible directly from the openai object. Here's an example of how to handle errors, including the RateLimitError, with the new API:
import openai
client = openai.OpenAI()
try:
client.fine_tunes.create(
training_file="file-XGinujblHPwGLSztz8cPS8XY",
)
except openai.APIConnectionError as e:
print("The server could not be reached")
print(e.__cause__) # an underlying Exception, likely raised within httpx.
except openai.RateLimitError as e:
print("A 429 status code was received; we should back off a bit.")
except openai.APIStatusError as e:
print("Another non-200-range status code was received")
print(e.status_code)
print(e.response)
In this example, if a RateLimitError is encountered (which corresponds to a 429 status code), the program will print a message indicating that the rate limit has been exceeded and that it should back off a bit. You can replace this print statement with your own logic to handle the rate limit error, such as implementing a retry mechanism with exponential backoff.