How can I implement retry logic for API errors in my AI application?

How can I implement retry logic for API errors in my AI application?

You can implement retry logic by using a loop that attempts the API call multiple times before failing. Would you like a code example?

Yes, please provide a code example for a Python application.

Here's a simple example using the requests library:

import requests
import time

def fetch_data(url, retries=3, delay=2):
    for i in range(retries):
        try:
            response = requests.get(url)
            response.raise_for_status()  # Raise an error for bad responses
            return response.json()
        except requests.exceptions.RequestException as e:
            print(f'Attempt {i + 1} failed: {e}')
            time.sleep(delay)
    return None  # Return None if all attempts fail

This function will try to fetch data from the given URL up to 3 times, waiting 2 seconds between attempts.

What should I consider when setting the number of retries?

Consider the API's rate limits, the nature of the errors, and the user experience. Too many retries can lead to throttling or delays.

Are there any libraries that can help with this?

Yes, libraries like tenacity in Python can simplify implementing retry logic with more advanced features like exponential backoff.