A cost check before a script runs prevents large, unintended spending at the start. It does not prevent cost increases during the script's operation. The cost estimate must be updated regularly.
By Pawan Nayar · from the LLOS AI Learning record
A cost check before a script runs prevents large, unintended spending at the start.
It does not prevent cost increases during the script's operation. The cost estimate must be updated regularly.
A cost check shows the total calls and estimated cost before a script starts. The user must confirm to proceed. This stops scripts from running without approval. It prevents large, unexpected costs at the very beginning. The cost estimate can become old. The cost per call is set when the script is made. If the AI model changes its prices, the estimate will be wrong. If the script makes more retries or uses longer prompts, the cost per call changes. The check will show an incorrect number. The check only runs once, at the start. It does not monitor costs while the script is running. If the server the script calls starts retrying failed requests many times, costs can rise. This happens even if the initial cost check passed. To fix this, update the cost-per-call number in the script after any price change. Update it after any big change to how the script works. Also, the server itself needs a limit on how many times it retries a request. This is a separate task for the server.
A developer creates a script that uses an AI model. The script has a pre-launch cost check. The developer runs the check and sees an estimated cost of $100. The developer approves the run. Later, the AI model provider increases its prices. The developer runs the script again without updating the cost-per-call number in the script. The check still shows $100, but the actual cost is $120. This leads to unexpected overspending.
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A developer must use parallel execution for scripts that make multiple API calls. This means many calls run at the same time.
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A developer needs to know the purpose of each script. A developer must understand what output each script creates.
A developer can switch an AI model's data source. The AI model can get data from a local database.
A cost check before a script runs prevents large, unintended spending at the start. It does not prevent cost increases during the script's operation. The cost estimate must be updated regularly.