Max_retries
Also written: retry
The maximum number of times an operation will be retried if it fails.
When you use an AI model, sometimes the request might fail. This could be due to a temporary network issue or the AI being too busy.
The `max_retries` setting tells the system how many times it should automatically try the request again before giving up. For example, if `max_retries` is set to 3, the system will try your request up to 4 times in total (the initial attempt plus 3 retries). Setting it to 0 means it will only try once and not retry if it fails.
This helps make sure your requests eventually go through even if there are small, temporary problems.
Max_retries is a common parameter in API clients and distributed systems that defines the upper limit for automatic reattempts of a failed operation. When an operation, such as an API call to an AI model, returns an error that is deemed retryable (e.g., transient network errors, rate limiting), the client will initiate a retry. The max_retries value dictates how many such retries are permitted before the operation is considered permanently failed and the error is propagated to the caller.
Setting max_retries involves a tradeoff between robustness and latency. Higher values can increase the probability of success for transient failures but also increase the maximum time an operation might take. Conversely, lower values reduce maximum latency but may lead to more perceived failures for temporary issues. Some systems also implement exponential backoff between retries to avoid overwhelming the service.
The term 'max_retries' is appearing because developers are refining how AI models handle errors and timeouts. Specifically, Google Gemini's API testing tool is being updated to manage situations where no retries are allowed, ensuring more robust execution of code examples.
- Google Gemini
- Google Gemini's API testing tool has been updated to handle the 'max_retries' parameter, including cases where it is set to zero.
- Timeout
- A timeout specifies the maximum amount of time to wait for an operation
- Concurrency
- Concurrency refers to the ability of a system to handle multiple op
- Idempotency
- An idempotent operation can be called multiple times with the same
The concept of retrying operations after failure is fundamental in computer science and distributed systems, appearing in numerous networking protocols and software libraries long before modern AI.
When using an AI model's API, try sending a request that you know will fail, perhaps by providing invalid input. Observe the error message. Then, try again with a valid input but simulate a network error if possible. If the API client supports it, set `max_retries` to 0 and see how quickly it fails. Then, increase `max_retries` and observe if it eventually succeeds.
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Questions people ask
- What happens if max_retries is set to 0?
- If max_retries is set to 0, the operation will only be attempted once. If it fails, it will not be retried automatically, and the error will be returned immediately.
- When should I increase max_retries?
- You should consider increasing max_retries if you are experiencing frequent but temporary errors, such as rate limiting or brief network interruptions, and want your application to be more resilient.
First seen on Subvolts Sep 15, 2026. Updated Sep 22, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.