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https://github.com/anomalyco/opencode.git
synced 2026-05-31 13:31:39 +00:00
Refine leaderboard layout and styling
This commit is contained in:
Adam
parent
e3a6255c72
commit
ffbf9df18e
3 changed files with 147 additions and 61 deletions
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@ -1160,30 +1160,72 @@
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font-weight: 500;
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}
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[data-page="stats"] [data-component="leaderboard"] {
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display: block;
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[data-page="stats"] [data-section="leaderboard"] {
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box-sizing: border-box;
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box-shadow:
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inset 0 -1px var(--stats-line),
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inset 1px 0 var(--stats-line),
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inset -1px 0 var(--stats-line);
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padding: 80px 40px;
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}
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[data-page="stats"] [data-slot="leaderboard-grid"] {
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[data-page="stats"] [data-slot="leaderboard-title"] {
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max-width: 1200px;
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margin-bottom: 40px;
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color: var(--stats-muted);
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font-size: 28px;
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font-weight: 400;
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line-height: 1.5;
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}
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[data-page="stats"] [data-slot="leaderboard-title"] strong {
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color: var(--stats-text);
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font-weight: 500;
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}
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[data-page="stats"] [data-component="leaderboard"],
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[data-page="stats"] [data-slot="leaderboard-featured"],
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[data-page="stats"] [data-slot="leaderboard-compact"],
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[data-page="stats"] [data-slot="leaderboard-column"] {
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display: grid;
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grid-template-columns: repeat(2, minmax(0, 1fr));
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gap: 8px;
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min-height: 447px;
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}
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[data-page="stats"] [data-component="leaderboard"] {
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gap: 0;
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}
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[data-page="stats"] [data-slot="leaderboard-featured"],
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[data-page="stats"] [data-slot="leaderboard-compact"] {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(min(100%, 260px), 1fr));
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gap: 8px;
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}
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[data-page="stats"] [data-slot="leaderboard-compact"] {
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grid-template-columns: repeat(2, minmax(0, 1fr));
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[data-page="stats"] [data-slot="leaderboard-pattern"] {
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height: 16px;
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margin: 16px 0;
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overflow: hidden;
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background: var(--stats-hero-pattern);
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mask-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E");
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mask-position: center top;
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mask-repeat: repeat;
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mask-size: 6px 6px;
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-webkit-mask-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 6 6' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M0 0H2V2H0V0Z' fill='black'/%3E%3C/svg%3E");
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-webkit-mask-position: center top;
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-webkit-mask-repeat: repeat;
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-webkit-mask-size: 6px 6px;
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}
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[data-page="stats"] [data-slot="leaderboard-column"] {
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gap: 8px;
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}
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[data-page="stats"] [data-section="leaderboard"] [data-slot="chart-footer"] {
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margin-top: 32px;
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}
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[data-page="stats"] [data-component="leader-card"] {
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container-type: inline-size;
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position: relative;
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box-sizing: border-box;
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display: flex;
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flex-direction: column;
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justify-content: space-between;
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@ -1194,6 +1236,12 @@
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background: linear-gradient(180deg, #ffffff0a 0%, #ffffff00 100%), var(--stats-layer);
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font-size: 13px;
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line-height: 1.1;
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outline: none;
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transition:
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background 140ms ease,
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border-color 140ms ease,
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box-shadow 140ms ease,
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transform 140ms ease;
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}
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[data-page="stats"] [data-slot="rank"],
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@ -1202,11 +1250,13 @@
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}
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[data-page="stats"] [data-component="leader-card"][data-size="featured"] {
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min-height: 143px;
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justify-content: flex-start;
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gap: 17px;
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min-height: 154px;
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}
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[data-page="stats"] [data-component="leader-card"][data-size="compact"] {
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min-height: 82px;
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min-height: 88px;
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box-shadow:
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0 0 0 0.5px #0000001f,
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0 1px 2px -1px #00000014,
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@ -1215,27 +1265,28 @@
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[data-page="stats"] [data-slot="leader-watermark"] {
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position: absolute;
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right: -44px;
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right: -20px;
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top: 50%;
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display: none;
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width: 210px;
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height: 210px;
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width: 168px;
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height: 168px;
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transform: translateY(-50%);
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color: var(--stats-line);
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opacity: 0.5;
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opacity: 0.58;
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pointer-events: none;
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transition:
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color 140ms ease,
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opacity 140ms ease;
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}
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@container (min-width: 280px) {
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[data-page="stats"] [data-slot="leader-watermark"] {
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display: block;
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}
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[data-page="stats"] [data-component="leader-card"][data-size="featured"] [data-slot="leader-watermark"] {
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display: block;
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}
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[data-page="stats"] [data-slot="leader-body"] {
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position: relative;
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display: flex;
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align-items: flex-end;
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align-items: center;
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gap: 12px;
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min-width: 0;
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z-index: 1;
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@ -1244,7 +1295,7 @@
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[data-page="stats"] [data-component="leader-card"][data-size="featured"] [data-slot="leader-body"] {
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flex-direction: column;
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align-items: flex-start;
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gap: 16px;
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gap: 12px;
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width: 100%;
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}
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@ -1265,14 +1316,6 @@
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font-weight: 600;
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}
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[data-page="stats"] [data-component="leader-card"][data-size="featured"] [data-slot="leader-avatar"] {
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width: 28px;
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height: 28px;
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padding: 4px;
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border-radius: 6px;
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font-size: 13px;
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}
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[data-page="stats"] [data-slot="leader-copy"] {
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display: grid;
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gap: 4px;
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@ -1309,7 +1352,7 @@
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color: var(--stats-muted);
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}
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[data-page="stats"] [data-slot="delta"] {
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[data-page="stats"] [data-slot="leader-copy"] [data-slot="delta"] {
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color: #198b43;
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}
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@ -1317,6 +1360,31 @@
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color: #b82d35;
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}
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@media (hover: hover) {
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[data-page="stats"] [data-component="leader-card"]:hover,
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[data-page="stats"] [data-component="leader-card"]:focus-visible {
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border-color: var(--stats-line-strong);
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background: #ffffff;
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box-shadow:
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0 0 0 0.5px #00000024,
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0 6px 16px #0000000d,
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0 2px 6px #0000000f;
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transform: translateY(-1px);
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}
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[data-page="stats"] [data-component="leader-card"]:hover [data-slot="leader-watermark"],
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[data-page="stats"] [data-component="leader-card"]:focus-visible [data-slot="leader-watermark"] {
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color: var(--stats-layer-2);
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opacity: 0.86;
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}
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[data-page="stats"] [data-component="leader-card"]:hover [data-slot="leader-avatar"],
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[data-page="stats"] [data-component="leader-card"]:focus-visible [data-slot="leader-avatar"] {
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border-color: var(--stats-line-strong);
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color: var(--stats-text);
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}
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}
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[data-page="stats"] [data-component="market-share"] {
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display: grid;
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grid-template-rows: auto minmax(0, 1fr);
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@ -1828,6 +1896,15 @@
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0 2px 4px #0000003d;
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}
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[data-page="stats"] [data-component="leader-card"]:hover,
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[data-page="stats"] [data-component="leader-card"]:focus-visible {
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background: #303030;
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box-shadow:
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0 0 0 0.5px #ffffff24,
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0 6px 16px #0000003d,
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0 2px 6px #00000052;
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}
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[data-page="stats"] [data-slot="header-button"][data-variant="neutral"],
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[data-page="stats"] [data-slot="menu-button"] {
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color: #fafafa;
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@ -1887,7 +1964,8 @@
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}
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@media (max-width: 74rem) {
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[data-page="stats"] [data-section="top-models"] {
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[data-page="stats"] [data-section="top-models"],
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[data-page="stats"] [data-section="leaderboard"] {
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padding: 64px 32px;
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}
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}
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@ -1938,10 +2016,9 @@
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flex-wrap: nowrap;
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}
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[data-page="stats"] [data-slot="leaderboard-grid"],
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[data-page="stats"] [data-slot="leaderboard-featured"],
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[data-page="stats"] [data-slot="leaderboard-compact"] {
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grid-template-columns: 1fr;
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min-height: 0;
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}
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[data-page="stats"] [data-component="leader-card"][data-size="featured"],
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@ -1951,18 +2028,10 @@
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[data-page="stats"] [data-component="leader-card"][data-size="featured"] [data-slot="leader-body"] {
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flex-direction: row;
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align-items: flex-end;
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align-items: center;
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gap: 12px;
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}
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[data-page="stats"] [data-slot="leader-avatar"] {
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width: 28px;
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height: 28px;
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padding: 4px;
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border-radius: 6px;
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font-size: 13px;
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}
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[data-page="stats"] [data-slot="leader-watermark"] {
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right: -64px;
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width: 180px;
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@ -2008,11 +2077,13 @@
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}
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@media (max-width: 47.999rem) {
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[data-page="stats"] [data-section="top-models"] {
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[data-page="stats"] [data-section="top-models"],
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[data-page="stats"] [data-section="leaderboard"] {
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padding: 48px 24px;
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}
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[data-page="stats"] [data-slot="top-models-title"] {
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[data-page="stats"] [data-slot="top-models-title"],
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[data-page="stats"] [data-slot="leaderboard-title"] {
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margin-bottom: 32px;
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font-size: 16px;
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}
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@ -599,11 +599,11 @@ function LeaderboardSection(props: { data: StatsHomeData["leaderboard"] }) {
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const data = createMemo(() => props.data[product()][range()])
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return (
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<ChartSection
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id="leaderboard"
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title="Leaderboard"
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description="Shown are the sum of prompt and completion tokens per model, including reasoning tokens."
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>
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<section id="leaderboard" data-section="leaderboard">
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<p data-slot="leaderboard-title">
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<strong>Leaderboard.</strong>{" "}
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<span>Shown are the sum of prompt and completion tokens per model, including reasoning tokens.</span>
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</p>
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<Show
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when={data().length > 0}
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fallback={
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@ -615,20 +615,30 @@ function LeaderboardSection(props: { data: StatsHomeData["leaderboard"] }) {
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<div data-slot="chart-footer">
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<StatsFilters product={product()} range={range()} onProductSelect={setProduct} onRangeSelect={setRange} />
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</div>
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</ChartSection>
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</section>
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)
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}
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function Leaderboard(props: { data: LeaderboardEntry[] }) {
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const featured = createMemo(() => props.data.slice(0, 3))
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const columns = createMemo(() =>
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[0, 1, 2].map((index) => props.data.slice(3 + index * 5, 8 + index * 5)).filter((column) => column.length > 0),
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)
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return (
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<div data-component="leaderboard" aria-label="Model token leaderboard">
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<div data-slot="leaderboard-grid">
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<div data-slot="leaderboard-featured">
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<For each={props.data.slice(0, 3)}>{(entry) => <LeaderboardCard entry={entry} size="featured" />}</For>
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</div>
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<div data-slot="leaderboard-compact">
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<For each={props.data.slice(3)}>{(entry) => <LeaderboardCard entry={entry} size="compact" />}</For>
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</div>
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<div data-component="leaderboard" role="list" aria-label="Model token leaderboard">
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<div data-slot="leaderboard-featured">
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<For each={featured()}>{(entry) => <LeaderboardCard entry={entry} size="featured" />}</For>
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</div>
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<div data-slot="leaderboard-pattern" aria-hidden="true" />
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<div data-slot="leaderboard-compact">
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<For each={columns()}>
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{(column) => (
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<div data-slot="leaderboard-column">
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<For each={column}>{(entry) => <LeaderboardCard entry={entry} size="compact" />}</For>
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</div>
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)}
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</For>
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</div>
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</div>
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)
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@ -636,7 +646,12 @@ function Leaderboard(props: { data: LeaderboardEntry[] }) {
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function LeaderboardCard(props: { entry: LeaderboardEntry; size: "featured" | "compact" }) {
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return (
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<article data-component="leader-card" data-size={props.size}>
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<article
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data-component="leader-card"
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data-size={props.size}
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role="listitem"
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aria-label={`${String(props.entry.rank).padStart(2, "0")} ${props.entry.model} by ${props.entry.author}`}
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>
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<span data-slot="rank">{String(props.entry.rank).padStart(2, "0")}</span>
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<ProviderIcon data-slot="leader-watermark" aria-hidden="true" id={getProviderIconId(props.entry.author)} />
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<div data-slot="leader-body">
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@ -151,7 +151,7 @@ function buildLeaderboard(rows: StatMetricRow[], product: UsageProduct, window:
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return aggregateByModel(rowsForProduct(rows, product, window.start, window.end))
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.toSorted((a, b) => b.totalTokens - a.totalTokens)
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.slice(0, 13)
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.slice(0, 18)
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.map((item, index) => ({
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model: item.model,
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author: formatProvider(item.provider),
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