Update docs to reflect curriculum-audio local TTS path
Takeaway: Next time I'd bundle the doc-consistency check into the original implementation prompt instead of asking for it separately, since the docs drift as soon as behavior changes.
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Get Off the Grid local inference badge-ready on a HF Space
Takeaway: Next time I'd lead with the Space's hard constraints (1GB repo limit, free-tier build memory, no CUDA) before letting the agent draft a plan, since two of our failures were pure packaging/build issues we could have anticipated upfront.
Fix VoxCPM word-click audio cache leaks and build a labeled boundary benchmark
Takeaway: Next time I'd start by asking for a ground-truth labeling workflow and benchmark harness before building any alignment logic, since that's what actually let us tell good methods from bad ones.
Add word-level alignment for VoxCPM word-click playback
Takeaway: Next time I'd specify upfront that word clips must not bleed into adjacent words, since that was the real bug hiding behind 'alignment isn't better' — the fix was clamping word end to the next word's start plus much smaller padding for aligned clips versus the proportional fallback.
Fix word-click TTS playback in a Gradio reading app (VoxCPM + browser TTS)
Takeaway: Next time I'd start the first prompt by stating explicitly that this is a kids' reading app needing realistic per-word audio with strict latency and reliability constraints, so we don't cycle through browser-TTS-vs-VoxCPM-vs-Modal three separate times.
Wire up word-click TTS in Gradio read-along app
Takeaway: Next time I'd open with the fact that TTS needs to work instantly for a kid clicking words, not just eventually — that would have surfaced the Modal cold-start problem before I burned time on Gradio 6 launch-arg compatibility.
Add local GGUF inference path and hybrid Modal/local toggle for read-along app
Takeaway: Next time I'd ask for the environment sanitization (Conda vs .venv Torch conflicts) to be handled up front, since that same libtorch_python.so issue bit me twice, once during GGUF conversion and again during local_inference.py testing.