A system must stop a user's requests completely when the user exceeds a set limit. This protects the system's resources. It also ensures a good experience for all users.
By Pawan Nayar · from the LLOS AI Learning record
A system must stop a user's requests completely when the user exceeds a set limit.
This protects the system's resources. It also ensures a good experience for all users.
When a user sends too many requests, the system stops all new requests from that user. This is called a 'hard stop'. The system will not accept any more requests until a specific time period passes. This protects the system from being overloaded. It also makes sure the system works well for everyone.
A student uses an AI model to generate text. The student sends 101 requests in one hour. The AI model stops responding to the student's requests. The student must wait until the next hour to send more requests. This prevents the AI model from slowing down for other users.
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An AI model should try to call an external API only one time. This rule applies to APIs like Gemini or OpenAI.
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An AI model must tell the user what a script does. The AI model must say how many API calls it will make.
A developer must space out API calls. Submit each call with a delay of at least 250 milliseconds.
A system must stop a user's requests completely when the user exceeds a set limit. This protects the system's resources. It also ensures a good experience for all users.