Description
Instead of using hard coded arrays for games like "Emotion Explorer" or "Spelling Bee," I want to integrate a lightweight, client-side AI inference engine (such as WebLLM or a custom Transformer pipeline) to generate custom scenarios based on a student's real-time skill level.
Acceptance Criteria (AC)
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Initialize an asynchronous loading state to fetch the text model without blocking the main browser thread.
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Prompt the AI to generate text scenarios programmatically tailored to specific reading grade levels based on the user's running profile score.
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Establish a robust fallback framework that switches back to static local data objects if the AI execution times out or encounters network degradation.
Description
Instead of using hard coded arrays for games like "Emotion Explorer" or "Spelling Bee," I want to integrate a lightweight, client-side AI inference engine (such as WebLLM or a custom Transformer pipeline) to generate custom scenarios based on a student's real-time skill level.
Acceptance Criteria (AC)
Initialize an asynchronous loading state to fetch the text model without blocking the main browser thread.
Prompt the AI to generate text scenarios programmatically tailored to specific reading grade levels based on the user's running profile score.
Establish a robust fallback framework that switches back to static local data objects if the AI execution times out or encounters network degradation.