To avoid overloading the OpenAI server with ChatGPT API calls, you have to manage the rate of your calls. Here are a few strategies you can use:
1. Rate Limiting: OpenAI imposes rate limitations on the API to ensure fair usage among users. Ensure that you are aware of your subscription plan limitations and work within those constraints. As of March 1, 2023, for free trial users, the limit is 20 RPM (Requests Per Minute) and 40000 TPM (Tokens Per Minute).
1. Batching: If your application has the ability to batch API calls, this can be an efficient way to send and receive data. Instead of making multiple API calls for each task, you can send one call with several tasks bundled together.
1. API Call Optimization: Optimize your API calls by only requesting what you need. Minimize the tokens by shortening your conversations or reducing the message size.
1. Caching: You can cache responses if you are repeatedly making identical requests. Storing responses locally significantly reduces the number of calls.
1. Backoff Mechanism: Implement a backoff mechanism in case you reach the rate limit. This means you should design your application to gradually reduce the number of requests rather than stopping abruptly.
1. Error Handling: Implement robust error handling. If a request fails, your application should be capable of retrying that request, ideally with an exponential backoff strategy.
Make sure to also handle ‘RateLimitError’ from OpenAI’s API which is thrown when you exceed the rate limit. Please remember that constantly hitting the rate limit might lead to your API key being temporarily or permanently suspended, so tread carefully.
