⚡ Bolt: optimize synthetic vector generation#264
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Optimized the synthetic embedding generation process in `@jeanbot/ai` by: - Leveraging Node 22's one-shot `crypto.hash` API for significantly faster hashing. - Replacing expensive `Number(v.toFixed(8))` with faster mathematical rounding `Math.round(v * 1e8) / 1e8`. - Eliminating redundant text and vector normalizations by introducing targeted skip flags. - Refactoring hot loops to use manual `for` loops and pre-allocated arrays instead of high-level array methods. These changes result in a measurable ~4x speedup (from ~8.03ms to ~2.02ms per embedding) while maintaining bit-for-bit deterministic output. Co-authored-by: hackerxj2010 <198651211+hackerxj2010@users.noreply.github.com>
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💡 What: Optimized the synthetic embedding generation and vector processing in
@jeanbot/ai.🎯 Why: The original implementation had significant overhead from redundant normalizations, object-based hashing, and string-based rounding in hot loops.
📊 Impact: Reducer latency per synthetic embedding by ~75% (from ~8.03ms to ~2.02ms).
🔬 Measurement: Verified using a custom benchmark script (
bench_ai.ts) and confirmed bit-for-bit determinism withtest_ai_correctness.ts.PR created automatically by Jules for task 7006761330146275540 started by @hackerxj2010