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https://github.com/samvallad33/vestige.git
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6837198328
The July 14 launch surface, previously uncommitted: - /dashboard/launch raw-WebGPU particle "memory brain" hero (RawVestigeEngine, NeuralWordmark, dendrite sign) + DOM waitlist overlay with share/referral. - Supabase waitlist client + migrations + welcome edge function; legacy waitlist archived under supabase/legacy. - vercel.json deploy config, root-redirect env wiring, base-path config, graph-only route, Playwright launch verifiers. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
104 lines
2.9 KiB
Svelte
104 lines
2.9 KiB
Svelte
<script lang="ts">
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// Living neural sign: VESTIGE built from REAL
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// grown dendrites (space colonization on the letterforms) with a quiet bloom.
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// Not glow-on-text.
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import { onMount } from 'svelte';
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import { growSign, type DendriteSign } from '$lib/landing/dendriteGen';
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let sign = $state<DendriteSign | null>(null);
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let reduced = $state(false);
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onMount(() => {
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reduced = window.matchMedia?.('(prefers-reduced-motion: reduce)').matches ?? false;
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// grow the dendrites once after fonts are ready (so glyph metrics are right)
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const grow = () => {
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try {
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sign = growSign();
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} catch (e) {
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console.warn('[neural-sign] grow failed:', e);
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}
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};
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if (document.fonts?.ready) {
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document.fonts.load('900 150px Inter').then(() => document.fonts.ready).then(grow).catch(grow);
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} else {
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grow();
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}
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});
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</script>
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<div class="neural-sign" class:reduced aria-label="Vestige">
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{#if sign}
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<svg
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viewBox={`0 0 ${sign.width} ${sign.height}`}
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class="sign-svg"
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xmlns="http://www.w3.org/2000/svg"
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aria-hidden="true"
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>
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<defs>
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<filter id="ns-bloom" x="-60%" y="-60%" width="220%" height="220%">
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<feGaussianBlur in="SourceAlpha" stdDeviation="1.6" result="b1" />
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<feColorMatrix in="b1" values="0 0 0 0 .22 0 0 0 0 1 0 0 0 0 .62 0 0 0 1 0" result="g1" />
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<feGaussianBlur in="SourceAlpha" stdDeviation="5" result="b2" />
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<feColorMatrix in="b2" values="0 0 0 0 .13 0 0 0 0 .82 0 0 0 0 1 0 0 0 .85 0" result="g2" />
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<feGaussianBlur in="SourceAlpha" stdDeviation="12" result="b3" />
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<feColorMatrix in="b3" values="0 0 0 0 .70 0 0 0 0 .42 0 0 0 0 1 0 0 0 .6 0" result="g3" />
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<feMerge>
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<feMergeNode in="g3" /><feMergeNode in="g2" /><feMergeNode in="g1" />
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<feMergeNode in="SourceGraphic" />
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</feMerge>
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</filter>
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</defs>
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<!-- the grown dendrites -->
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<g filter="url(#ns-bloom)">
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<g class="dendrites">
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{#each sign.paths as p (p.d)}
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<path d={p.d} stroke={p.col} stroke-width={p.w} stroke-linecap="round" />
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{/each}
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</g>
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</g>
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</svg>
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{/if}
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</div>
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<style>
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.neural-sign {
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position: fixed;
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top: clamp(0.1rem, 1vh, 0.8rem);
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left: 50%;
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transform: translateX(-50%);
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z-index: 3;
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width: min(680px, 94vw);
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pointer-events: none;
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}
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.sign-svg {
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width: 100%;
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height: auto;
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display: block;
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overflow: visible;
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}
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/* PERF: per-path stroke-dashoffset animation on 5700 paths tanks FPS to ~12
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(SVG dashoffset is not GPU-compositable; full paint per path per frame).
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Instead fade in the WHOLE dendrite group with ONE GPU-compositable opacity
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transition. Static dendrites + one group fade = 120fps. */
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.dendrites {
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animation: ns-grow 1.6s ease-out both;
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}
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@keyframes ns-grow {
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from {
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opacity: 0;
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transform: scale(0.92);
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transform-origin: 50% 30%;
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}
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to {
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opacity: 1;
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transform: scale(1);
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}
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}
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.reduced .dendrites {
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animation: none;
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}
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</style>
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