Handling Request Timeout Errors in Python Script Using OpenAI API

Question

I'm working on a Python script that processes a large set of Anki cards (30,000 cards for 20 learning objectives) using the OpenAI API. My goal is to rate each card's relevance to different learning objectives. However, I frequently encounter request timeout errors, and despite implementing a retry logic, the problem persists. I'm looking for advice on how to effectively manage these timeout errors and ensure the reliable execution of my script.

openai.error.Timeout: Request timed out:
HTTPSConnectionPool(host='api.openai.com', port=443): Read timed out. (read timeout=600)

Script Overview:

The script performs the following actions:

1. Loads Anki card embeddings and learning objectives from CSV files.
2. Constructs prompts to send to the OpenAI API for scoring the relevance of cards.
3. Catches and handles exceptions like RateLimitError, APIError, or ServiceUnavailableError using a custom decorator that implements retry logic.
4. Writes results to a CSV file and keeps track of progress to continue where it left off in case of interruption.

Questions:

1. How can I improve my retry logic to better handle timeouts?
2. Should I consider implementing a maximum retry count or a maximum total wait time to avoid getting stuck in an endless loop?
3. Is there a way to increase the timeout setting for the API calls to prevent these errors from occurring as often?
4. Are there best practices when using the OpenAI API for large-scale processing that I might be overlooking?

Additional Context:

• I'm using openai.ChatCompletion.create with gpt-3.5-turbo.
• The script successfully processes some requests but fails intermittently with timeouts.
• I'm unsure if the issue is related to the OpenAI API rate limits or my network stability.

Any insights or suggestions would be greatly appreciated!

Despite the retry logic, which increases wait times between retries, I'm still facing request timeout errors. Here's the part of the script that handles retries:

def handle_api_error(func):
    def wrapper(*args, **kwargs):
        max_retries = 5
        backoff_factor = 2
        for attempt in range(max_retries):
            try:
                return func(*args, **kwargs)
            except (RateLimitError, APIError, ServiceUnavailableError) as e:
                wait = backoff_factor ** attempt
                print(f'API Error: {e}. Waiting {wait}s before retrying.')
                time.sleep(wait)
            except requests.exceptions.Timeout as e:
                # Handle timeout specifically if it's a recurring issue
                print(f'Request Timeout: {e}. Adjusting request strategy.')
                # Adjust strategy, e.g., by reducing payload, increasing client-side timeout, etc.
        raise
    return wrapper