API calls should always run at the same time, not one after another. This makes tasks finish much faster. Running calls one by one wastes a user's time.
By Pawan Nayar · from the LLOS AI Learning record
API calls should always run at the same time, not one after another.
This makes tasks finish much faster. Running calls one by one wastes a user's time.
A developer must use parallel execution for scripts that make multiple API calls. This means many calls run at the same time. Running calls one after another is much slower. Parallel execution saves a user many hours of waiting.
A developer needs to get information for 355 categories. Each category needs two API calls. If the developer runs these calls one by one, it takes about three hours. If the developer runs 15 calls at the same time, the task finishes in 15-20 minutes. The user saves a lot of time.
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A developer must count the total number of API calls. The developer then estimates the input and output tokens for each call.
An AI model should first state what it already knows from a file. If the AI model can recall the information, it does not need to read the file again.
A developer needs to know the purpose of each script. A developer must understand what output each script creates.
A cost check shows the total calls and estimated cost before a script starts. The user must confirm to proceed.
API calls should always run at the same time, not one after another. This makes tasks finish much faster. Running calls one by one wastes a user's time.