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feat(stats): add unique user charts

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Adam 2026-06-20 14:54:15 -05:00
parent 2d993cd0d5
commit 24c70ec974
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13 changed files with 327 additions and 127 deletions
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230
packages/stats/app/src/routes/[lab]/[model].tsx
View File

@ -45,6 +45,7 @@ const statsUnfurlUrl = new URL(statsUnfurlPath, statsCanonicalBaseUrl).toString(
const modelHeaderLinks: readonly HeaderLink[] = [
{ href: "#overview", label: "Overview" },
{ href: "#usage", label: "Usage" },
{ href: "#users", label: "Users" },
{ href: "#efficiency", label: "Efficiency" },
{ href: "#geo-breakdown", label: "Geo Breakdown" },
{ href: "#peers", label: "Peers" },
@ -175,6 +176,7 @@ export default function StatsModel() {
<ModelHero data={stats() ?? null} catalog={catalogEntry() ?? null} labName={labName()} />
<ModelOverview data={stats() ?? null} />
<ModelUsageSection data={stats()?.usage ?? []} />
<ModelUsersSection data={stats()?.usage ?? []} />
<ModelEfficiencySection data={stats() ?? null} catalog={catalogEntry() ?? null} />
<ModelGeoBreakdownSection data={stats()?.country ?? emptyCountryRecord()} />
<ModelPeersSection data={stats() ?? null} />
@ -358,14 +360,6 @@ function ModelOverview(props: { data: StatsModelData | null }) {
}
function ModelUsageSection(props: { data: ModelUsagePoint[] }) {
const [activeIndex, setActiveIndex] = createSignal<number>()
const max = createMemo(() => Math.max(0, ...props.data.map((item) => item.tokens)) || 1)
const activePoint = createMemo(() => {
const index = activeIndex()
if (index === undefined) return undefined
return props.data[index]
})
return (
<section id="usage" data-section="model-panel">
<SectionTitle title="Usage" description="Daily OpenCode Go token volume over the recent two-month window." />
@ -373,92 +367,144 @@ function ModelUsageSection(props: { data: ModelUsagePoint[] }) {
when={props.data.some((item) => item.tokens > 0)}
fallback={<ModelEmptyState title="No usage" description="No usage landed in the current window." />}
>
<div
data-component="model-usage-chart"
data-dense-labels={isModelUsageDense(props.data.length) ? "true" : undefined}
role="img"
aria-label="Daily token usage chart"
style={{ "--model-usage-count": props.data.length } as JSX.CSSProperties}
onPointerLeave={(event) => {
if (event.pointerType === "touch") return
setActiveIndex(undefined)
}}
>
<div data-slot="model-usage-axis" aria-hidden="true">
<For each={props.data}>
{(point, index) => (
<div
data-active={activeIndex() === index() ? "true" : undefined}
data-label-hidden={isModelUsageLabelHidden(index(), props.data.length) ? "true" : undefined}
>
<span data-slot="model-usage-label">
<span data-slot="model-usage-total">{formatTokens(point.tokens)}</span>
<span data-slot="model-usage-date">{point.date}</span>
</span>
</div>
)}
</For>
</div>
<div data-slot="model-usage-bars">
<For each={props.data}>
{(point, index) => (
<div
data-slot="model-usage-column"
role="button"
tabIndex={0}
aria-label={`${point.date} ${formatTokens(point.tokens)} tokens`}
data-active={activeIndex() === index() ? "true" : undefined}
data-muted={activeIndex() !== undefined && activeIndex() !== index() ? "true" : undefined}
onPointerDown={(event) => {
if (event.pointerType !== "touch") return
setActiveIndex(index())
}}
onPointerEnter={() => setActiveIndex(index())}
onPointerMove={(event) => {
if (event.pointerType === "touch") return
setActiveIndex(index())
}}
onClick={() => setActiveIndex(index())}
onFocus={() => setActiveIndex(index())}
onBlur={() => setActiveIndex(undefined)}
onKeyDown={(event) => {
if (event.key !== "Enter" && event.key !== " ") return
event.preventDefault()
setActiveIndex(index())
}}
>
<div
data-slot="model-usage-bar"
style={{ "--model-usage-fill": `${modelUsageHeight(point.tokens, max())}%` } as JSX.CSSProperties}
/>
<Show when={activeIndex() === index() && activePoint()}>
{(active) => (
<div
data-component="chart-tooltip"
data-placement={index() > props.data.length * 0.62 ? "left" : "right"}
>
<strong>{active().date}</strong>
<span>{formatTokens(active().tokens)} tokens</span>
<div data-slot="tooltip-divider" />
<p>
<span data-slot="tooltip-label">
<i /> Daily tokens
</span>
<b>{formatTokens(active().tokens)}</b>
</p>
</div>
)}
</Show>
</div>
)}
</For>
</div>
</div>
<ModelColumnChart data={props.data} metric="tokens" ariaLabel="Daily token usage chart" />
</Show>
</section>
)
}
function ModelUsersSection(props: { data: ModelUsagePoint[] }) {
return (
<section id="users" data-section="model-panel">
<SectionTitle title="Unique Users" description="Daily unique OpenCode Go users over the recent two-month window." />
<Show
when={props.data.some((item) => item.users > 0)}
fallback={<ModelEmptyState title="No user data" description="No user-bearing rows landed in the current window." />}
>
<ModelColumnChart data={props.data} metric="users" ariaLabel="Daily unique user chart" />
</Show>
</section>
)
}
function ModelColumnChart(props: {
data: ModelUsagePoint[]
metric: "tokens" | "users"
ariaLabel: string
}) {
const [activeIndex, setActiveIndex] = createSignal<number>()
const max = createMemo(() => Math.max(0, ...props.data.map((item) => modelUsageMetricValue(item, props.metric))) || 1)
const activePoint = createMemo(() => {
const index = activeIndex()
if (index === undefined) return undefined
return props.data[index]
})
return (
<div
data-component="model-usage-chart"
data-metric={props.metric}
data-dense-labels={isModelUsageDense(props.data.length) ? "true" : undefined}
role="img"
aria-label={props.ariaLabel}
style={{ "--model-usage-count": props.data.length } as JSX.CSSProperties}
onPointerLeave={(event) => {
if (event.pointerType === "touch") return
setActiveIndex(undefined)
}}
>
<div data-slot="model-usage-axis" aria-hidden="true">
<For each={props.data}>
{(point, index) => (
<div
data-active={activeIndex() === index() ? "true" : undefined}
data-label-hidden={isModelUsageLabelHidden(index(), props.data.length) ? "true" : undefined}
>
<span data-slot="model-usage-label">
<span data-slot="model-usage-total">{formatModelUsageValue(point, props.metric)}</span>
<span data-slot="model-usage-date">{point.date}</span>
</span>
</div>
)}
</For>
</div>
<div data-slot="model-usage-bars">
<For each={props.data}>
{(point, index) => (
<div
data-slot="model-usage-column"
role="button"
tabIndex={0}
aria-label={`${point.date} ${formatModelUsageValue(point, props.metric)} ${modelUsageLabel(props.metric)}`}
data-active={activeIndex() === index() ? "true" : undefined}
data-muted={activeIndex() !== undefined && activeIndex() !== index() ? "true" : undefined}
onPointerDown={(event) => {
if (event.pointerType !== "touch") return
setActiveIndex(index())
}}
onPointerEnter={() => setActiveIndex(index())}
onPointerMove={(event) => {
if (event.pointerType === "touch") return
setActiveIndex(index())
}}
onClick={() => setActiveIndex(index())}
onFocus={() => setActiveIndex(index())}
onBlur={() => setActiveIndex(undefined)}
onKeyDown={(event) => {
if (event.key !== "Enter" && event.key !== " ") return
event.preventDefault()
setActiveIndex(index())
}}
>
<div
data-slot="model-usage-bar"
style={{
"--model-usage-fill": `${modelUsageHeight(modelUsageMetricValue(point, props.metric), max())}%`,
} as JSX.CSSProperties}
/>
<Show when={activeIndex() === index() && activePoint()}>
{(active) => (
<div
data-component="chart-tooltip"
data-placement={index() > props.data.length * 0.62 ? "left" : "right"}
>
<strong>{active().date}</strong>
<span>
{formatModelUsageValue(active(), props.metric)} {modelUsageLabel(props.metric)}
</span>
<div data-slot="tooltip-divider" />
<p>
<span data-slot="tooltip-label">
<i /> Daily {modelUsageLabel(props.metric)}
</span>
<b>{formatModelUsageValue(active(), props.metric)}</b>
</p>
</div>
)}
</Show>
</div>
)}
</For>
</div>
</div>
)
}
function modelUsageMetricValue(point: ModelUsagePoint, metric: "tokens" | "users") {
if (metric === "users") return point.users
return point.tokens
}
function formatModelUsageValue(point: ModelUsagePoint, metric: "tokens" | "users") {
if (metric === "users") return formatUsers(point.users)
return formatTokens(point.tokens)
}
function modelUsageLabel(metric: "tokens" | "users") {
if (metric === "users") return "users"
return "tokens"
}
function ModelEfficiencySection(props: { data: StatsModelData | null; catalog: ModelCatalogEntry | null }) {
return (
<section id="efficiency" data-section="model-panel">
@ -834,6 +880,12 @@ function formatInteger(value: number) {
return new Intl.NumberFormat("en").format(value)
}
function formatUsers(value: number) {
if (value >= 1_000_000) return `${trimNumber(value / 1_000_000, value >= 10_000_000 ? 0 : 1)}M`
if (value >= 1_000) return `${trimNumber(value / 1_000, value >= 10_000 ? 0 : 1)}K`
return formatInteger(Math.round(value))
}
function formatPercent(value: number) {
return `${value.toFixed(value > 0 && value < 10 ? 1 : 0)}%`
}

78
packages/stats/app/src/routes/index.css
View File

@ -1546,7 +1546,7 @@
color: var(--stats-text);
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] {
top: 110px;
box-sizing: border-box;
display: flex;
@ -1564,40 +1564,53 @@
color: var(--stats-text);
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"][data-placement="right"] {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"][data-placement="right"] {
right: auto;
left: calc(100% + 8px);
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"][data-placement="left"] {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"][data-placement="left"] {
right: calc(100% + 8px);
left: auto;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] strong,
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] > span {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] strong,
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
> span {
display: block;
font-size: 11px;
line-height: 12px;
white-space: nowrap;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] strong {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] strong {
padding: 8px 8px 0;
font-weight: 500;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] > span {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
> span {
padding: 4px 8px 8px;
color: var(--stats-muted);
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] [data-slot="tooltip-divider"] {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
[data-slot="tooltip-divider"] {
height: 0.5px;
margin: 0;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] p {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] p {
grid-template-columns: minmax(0, 1fr) auto;
gap: 4px;
height: 16px;
@ -1608,36 +1621,50 @@
line-height: 12px;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] p[data-muted="true"] {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
p[data-muted="true"] {
opacity: 0.46;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] [data-slot="tooltip-divider"] + p {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
[data-slot="tooltip-divider"]
+ p {
margin-top: 8px;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] p:last-child {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
p:last-child {
margin-bottom: 8px;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] [data-slot="tooltip-label"] {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
[data-slot="tooltip-label"] {
grid-template-columns: 16px minmax(0, 1fr);
gap: 4px;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] i {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] i {
width: 6px;
height: 6px;
justify-self: center;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] b {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] b {
font-weight: 500;
}
[data-page="stats"]
:is(
[data-section="leaderboard"],
[data-section="unique-users"],
[data-section="market-share"],
[data-section="geo-breakdown"],
[data-section="token-cost"],
@ -3264,10 +3291,12 @@
background: #242424f2;
}
[data-page="stats"][data-theme="dark"] [data-section="top-models"] [data-component="chart-tooltip"],
[data-page="stats"][data-theme="dark"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"],
:root[data-stats-theme="dark"]
[data-page="stats"]:not([data-theme="light"])
[data-section="top-models"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"] {
background: #242424f2;
box-shadow:
@ -3276,10 +3305,13 @@
0 4px 8px #00000052;
}
[data-page="stats"][data-theme="dark"] [data-section="top-models"] [data-component="chart-tooltip"] > span,
[data-page="stats"][data-theme="dark"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
> span,
:root[data-stats-theme="dark"]
[data-page="stats"]:not([data-theme="light"])
[data-section="top-models"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"]
> span {
color: var(--stats-faint);
@ -3544,6 +3576,7 @@
@media (max-width: 74rem) {
[data-page="stats"] [data-section="top-models"],
[data-page="stats"] [data-section="leaderboard"],
[data-page="stats"] [data-section="unique-users"],
[data-page="stats"] [data-section="market-share"],
[data-page="stats"] [data-section="geo-breakdown"],
[data-page="stats"] [data-section="token-cost"],
@ -3703,6 +3736,7 @@
@media (max-width: 47.999rem) {
[data-page="stats"] [data-section="top-models"],
[data-page="stats"] [data-section="leaderboard"],
[data-page="stats"] [data-section="unique-users"],
[data-page="stats"] [data-section="market-share"],
[data-page="stats"] [data-section="geo-breakdown"],
[data-page="stats"] [data-section="token-cost"],
@ -4011,7 +4045,7 @@
display: block;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"] {
[data-page="stats"] :is([data-section="top-models"], [data-section="unique-users"]) [data-component="chart-tooltip"] {
position: fixed;
top: auto;
right: 12px;
@ -4025,7 +4059,9 @@
transform: none;
}
[data-page="stats"] [data-section="top-models"] [data-component="chart-tooltip"][data-placement] {
[data-page="stats"]
:is([data-section="top-models"], [data-section="unique-users"])
[data-component="chart-tooltip"][data-placement] {
right: 12px;
left: 12px;
}

58
packages/stats/app/src/routes/index.tsx
View File

@ -171,6 +171,7 @@ export default function StatsHome() {
<>
<Hero updatedAt={stats().updatedAt} />
<TopModelsSection data={stats().usage} leaderboard={stats().leaderboard} />
<UniqueUsersSection data={stats().users} />
<SessionCostSection data={stats().sessionCost} />
<TokenCostSection data={stats().tokenCost} catalog={catalog() ?? null} />
<CacheRatioSection data={stats().cacheRatio} />
@ -598,6 +599,8 @@ function FilterPills<T extends string>(props: {
function TopModelsChart(props: {
data: UsagePoint[]
range: UsageRange
metric?: "tokens" | "users"
ariaLabel?: string
activeModel: string | undefined
onActiveModelChange: (model: string | undefined) => void
}) {
@ -606,6 +609,7 @@ function TopModelsChart(props: {
const maxTotal = createMemo(() => getTopModelsMaxTotal(props.data))
const segmentOrder = createMemo(() => getTopModelsSegmentOrder(props.data))
const activePoint = createMemo(() => props.data[activeIndex() ?? -1])
const metric = createMemo(() => props.metric ?? "tokens")
createEffect(() => scrollDenseChartToEnd(chartRef, props.range, props.data.length))
@ -614,9 +618,10 @@ function TopModelsChart(props: {
ref={chartRef}
data-component="top-models-chart"
data-range={props.range}
data-metric={metric()}
data-dense-labels={isDenseColumnRange(props.range) ? "true" : undefined}
role="img"
aria-label="Stacked top model usage chart"
aria-label={props.ariaLabel ?? "Stacked top model usage chart"}
style={{ "--top-models-count": props.data.length } as JSX.CSSProperties}
onPointerLeave={(event) => {
if (event.pointerType === "touch") return
@ -633,7 +638,7 @@ function TopModelsChart(props: {
data-mobile-hidden={isTopModelsMobileAxisHidden(index(), props.data.length) ? "true" : undefined}
>
<span data-slot="axis-label">
<span data-slot="axis-total">{formatTokens(usageTotal(day))}</span>
<span data-slot="axis-total">{formatUsageChartValue(usageTotal(day), metric())}</span>
<span data-slot="axis-date">
<span data-slot="axis-date-full">{day.date}</span>
<span data-slot="axis-date-mobile">{formatTopModelsMobileDate(day.date, props.range)}</span>
@ -657,7 +662,7 @@ function TopModelsChart(props: {
data-slot="top-models-bar"
role="button"
tabIndex={0}
aria-label={`${day.date} ${formatTokens(usageTotal(day))}`}
aria-label={`${day.date} ${formatUsageChartValue(usageTotal(day), metric())} ${usageChartTotalLabel(metric())}`}
data-active={activeIndex() === dayIndex() ? "true" : undefined}
data-muted={activeIndex() !== undefined && activeIndex() !== dayIndex() ? "true" : undefined}
style={{ "--top-models-bar-height": `${getTopModelsBarHeight(usageTotal(day), maxTotal())}%` }}
@ -739,7 +744,9 @@ function TopModelsChart(props: {
data-placement={dayIndex() > props.data.length * 0.62 ? "left" : "right"}
>
<strong>{point().date}</strong>
<span>{formatTokens(usageTotal(point()))} total</span>
<span>
{formatUsageChartValue(usageTotal(point()), metric())} {usageChartTotalLabel(metric())}
</span>
<div data-slot="tooltip-divider" />
<For each={visibleTopModelsSegments(point())}>
{(item) => (
@ -759,7 +766,7 @@ function TopModelsChart(props: {
/>{" "}
{item.segment.model}
</span>
<b>{formatTokens(item.segment.value)}</b>
<b>{formatUsageChartValue(item.segment.value, metric())}</b>
</p>
)}
</For>
@ -774,6 +781,31 @@ function TopModelsChart(props: {
)
}
function UniqueUsersSection(props: { data: StatsHomeData["users"] }) {
const [activeModel, setActiveModel] = createSignal<string>()
const data = createMemo(() => props.data.Go["2M"])
return (
<section id="unique-users" data-section="unique-users">
<SectionBridge label="TOP MODELS" href="#top-models" />
<SectionTitle title="Unique Users" description="Daily unique OpenCode Go users by model." />
<Show
when={data().some((item) => usageTotal(item) > 0)}
fallback={<EmptyState title="No user data" description="No user-bearing model_stat rows matched this window." />}
>
<TopModelsChart
data={data()}
range="2M"
metric="users"
ariaLabel="Stacked unique user chart by model"
activeModel={activeModel()}
onActiveModelChange={setActiveModel}
/>
</Show>
</section>
)
}
function isTopModelsBlankHover(bar: HTMLElement, clientY: number) {
const stack = bar.querySelector<HTMLElement>('[data-slot="top-models-stack"]')
if (!stack) return true
@ -864,6 +896,22 @@ function formatTokens(value: number) {
return `${Math.round(value * 1000)}B`
}
function formatUsageChartValue(value: number, metric: "tokens" | "users") {
if (metric === "users") return formatUsers(value)
return formatTokens(value)
}
function usageChartTotalLabel(metric: "tokens" | "users") {
if (metric === "users") return "model users"
return "total"
}
function formatUsers(value: number) {
if (value >= 1_000_000) return `${(value / 1_000_000).toFixed(value >= 10_000_000 ? 0 : 1)}M`
if (value >= 1_000) return `${(value / 1_000).toFixed(value >= 10_000 ? 0 : 1)}K`
return new Intl.NumberFormat("en").format(Math.round(value))
}
function Leaderboard(props: {
data: LeaderboardEntry[]
activeModel: string | undefined

3
packages/stats/core/migrations/20260620000000_unique_users/migration.sql Normal file
View File

@ -0,0 +1,3 @@
ALTER TABLE `geo_stat` ADD `unique_users` bigint NOT NULL DEFAULT 0;--> statement-breakpoint
ALTER TABLE `model_stat` ADD `unique_users` bigint NOT NULL DEFAULT 0;--> statement-breakpoint
ALTER TABLE `provider_stat` ADD `unique_users` bigint NOT NULL DEFAULT 0;

1
packages/stats/core/src/database/schema.ts
View File

@ -123,6 +123,7 @@ function metricColumns() {
return {
sessions: bigint({ mode: "number" }).notNull().default(0),
requests: bigint({ mode: "number" }).notNull().default(0),
unique_users: bigint({ mode: "number" }).notNull().default(0),
input_tokens: bigint({ mode: "number" }).notNull().default(0),
output_tokens: bigint({ mode: "number" }).notNull().default(0),
reasoning_tokens: bigint({ mode: "number" }).notNull().default(0),

1
packages/stats/core/src/domain/geo.ts
View File

@ -145,6 +145,7 @@ export class GeoStatRepo extends Context.Service<GeoStatRepo, GeoStatRepo.Servic
continent: inserted("continent"),
sessions: inserted("sessions"),
requests: inserted("requests"),
unique_users: inserted("unique_users"),
input_tokens: inserted("input_tokens"),
output_tokens: inserted("output_tokens"),
reasoning_tokens: inserted("reasoning_tokens"),

45
packages/stats/core/src/domain/home.ts
View File

@ -21,7 +21,7 @@ export type TokenCostEntry = { model: string; total: number; input: number; outp
export type CacheRatioEntry = { model: string; ratio: number; cached: number; uncached: number; total: number }
export type SessionCostEntry = { model: string; cost: number; tokens: number }
export type CountryEntry = { country: string; continent: string; tokens: number; share: number; rank: number }
export type ModelUsagePoint = { date: string; tokens: number; sessions: number; cost: number }
export type ModelUsagePoint = { date: string; tokens: number; users: number; sessions: number; cost: number }
export type ModelMixEntry = { label: string; tokens: number; share: number }
export type ModelPeerEntry = {
model: string
@ -82,6 +82,7 @@ export type StatsLabData = {
export type StatsHomeData = {
updatedAt: string | null
usage: Record<UsageProduct, Record<UsageRange, UsagePoint[]>>
users: Record<UsageProduct, Record<UsageRange, UsagePoint[]>>
leaderboard: Record<UsageProduct, Record<UsageRange, LeaderboardEntry[]>>
market: Record<UsageRange, MarketDay[]>
tokenCost: Record<TokenProduct, TokenCostEntry[]>
@ -118,6 +119,7 @@ type ModelAggregate = {
model: string
provider: string
sessions: number
uniqueUsers: number
inputTokens: number
outputTokens: number
reasoningTokens: number
@ -200,6 +202,18 @@ function buildStatsHomeData(
),
),
),
users: createUsageProductRecord((product) =>
createRangeRecord((range) =>
buildUsagePoints(
normalized,
product,
range,
getWindow(range, earliest, latest),
getWindow("1W", earliest, latest),
"users",
),
),
),
leaderboard: createUsageProductRecord((product) =>
createRangeRecord((range) => buildLeaderboard(normalized, product, getWindow("1W", earliest, latest))),
),
@ -340,6 +354,7 @@ function emptyStatsHomeData(): StatsHomeData {
return {
updatedAt: null,
usage: createUsageProductRecord(() => createRangeRecord(() => [])),
users: createUsageProductRecord(() => createRangeRecord(() => [])),
leaderboard: createUsageProductRecord(() => createRangeRecord(() => [])),
market: createRangeRecord(() => []),
tokenCost: createTokenProductRecord(() => []),
@ -355,28 +370,39 @@ function buildUsagePoints(
range: UsageRange,
window: DateWindow,
rankWindow: DateWindow,
metric: "tokens" | "users" = "tokens",
) {
const modelOrder = aggregateByModelName(rowsForProduct(rows, product, rankWindow.start, rankWindow.end))
.toSorted((a, b) => b.totalTokens - a.totalTokens)
.toSorted((a, b) => modelUsageValue(b, metric) - modelUsageValue(a, metric))
.slice(0, TOP_MODEL_SEGMENT_LIMIT)
.map((item) => item.model)
return createBuckets(window, range).map((bucket) => {
const bucketRows = aggregateByModelName(rowsForProduct(rows, product, bucket.start, bucket.end))
const byModel = new Map(bucketRows.map((item) => [item.model, item.totalTokens]))
const segmentTokens = modelOrder.map((model) => ({ model, tokens: byModel.get(model) ?? 0 }))
const knownTokens = segmentTokens.reduce((sum, item) => sum + item.tokens, 0)
const totalTokens = bucketRows.reduce((sum, item) => sum + item.totalTokens, 0)
const byModel = new Map(bucketRows.map((item) => [item.model, modelUsageValue(item, metric)]))
const segments = modelOrder.map((model) => ({ model, value: byModel.get(model) ?? 0 }))
const knownValue = segments.reduce((sum, item) => sum + item.value, 0)
const totalValue = bucketRows.reduce((sum, item) => sum + modelUsageValue(item, metric), 0)
return {
date: bucket.label,
segments: [
...segmentTokens.map((item) => ({ model: item.model, value: round(item.tokens / 1_000_000_000_000, 4) })),
{ model: "Other", value: round(Math.max(totalTokens - knownTokens, 0) / 1_000_000_000_000, 4) },
...segments.map((item) => ({ model: item.model, value: usagePointValue(item.value, metric) })),
{ model: "Other", value: usagePointValue(Math.max(totalValue - knownValue, 0), metric) },
],
}
})
}
function modelUsageValue(item: ModelAggregate, metric: "tokens" | "users") {
if (metric === "users") return item.uniqueUsers
return item.totalTokens
}
function usagePointValue(value: number, metric: "tokens" | "users") {
if (metric === "users") return value
return round(value / 1_000_000_000_000, 4)
}
function buildLeaderboard(rows: StatMetricRow[], product: UsageProduct, rankWindow: DateWindow) {
const previous = new Map(
aggregateByModelName(rowsForProduct(rows, product, rankWindow.previousStart, rankWindow.previousEnd)).map(
@ -502,6 +528,7 @@ function buildModelUsage(rows: StatMetricRow[], window: DateWindow, range: Usage
return {
date: bucket.label,
tokens: aggregate.totalTokens,
users: aggregate.uniqueUsers,
sessions: aggregate.sessions,
cost: round(microcentsToDollars(aggregate.totalCostMicrocents), 2),
}
@ -601,6 +628,7 @@ function combineRowsForModel(model: string, rows: StatMetricRow[]): ModelAggrega
model,
provider: "unknown",
sessions: 0,
uniqueUsers: 0,
inputTokens: 0,
outputTokens: 0,
reasoningTokens: 0,
@ -617,6 +645,7 @@ function combineModelAggregate(current: ModelAggregate | undefined, row: StatMet
model: row.model,
provider: row.provider,
sessions: (current?.sessions ?? 0) + row.sessions,
uniqueUsers: (current?.uniqueUsers ?? 0) + row.uniqueUsers,
inputTokens: (current?.inputTokens ?? 0) + row.inputTokens,
outputTokens: (current?.outputTokens ?? 0) + row.outputTokens,
reasoningTokens: (current?.reasoningTokens ?? 0) + row.reasoningTokens,

5
packages/stats/core/src/domain/inference.ts
View File

@ -40,6 +40,7 @@ export function buildStatsQuery(periodStart: Date, periodEnd: Date, dimension: S
const aggregateColumns = `
COUNT(DISTINCT session) AS sessions,
COUNT(*) AS requests,
COUNT(DISTINCT user_key) AS unique_users,
COALESCE(SUM(tokens_input), 0) AS input_tokens,
COALESCE(SUM(tokens_output), 0) AS output_tokens,
COALESCE(SUM(tokens_reasoning), 0) AS reasoning_tokens,
@ -70,6 +71,8 @@ WITH normalized AS (
UPPER(COALESCE(NULLIF(cf_country, ''), 'ZZ')) AS country,
COALESCE(NULLIF(cf_continent, ''), '') AS continent,
session,
COALESCE(NULLIF(workspace, ''), '') AS workspace,
COALESCE(NULLIF(api_key, ''), '') AS api_key,
status,
duration AS duration_ms,
time_to_first_byte AS ttfb_ms,
@ -108,6 +111,7 @@ WITH normalized AS (
country,
continent,
session,
COALESCE(NULLIF(workspace, ''), NULLIF(api_key, '')) AS user_key,
status,
duration_ms,
ttfb_ms,
@ -197,6 +201,7 @@ function toStatBaseAggregate(data: AthenaData): StatBaseAggregate[] {
tier: normalizeTier(data.tier || "unknown"),
sessions: integer(data, "sessions"),
requests: integer(data, "requests"),
unique_users: integer(data, "unique_users"),
input_tokens: integer(data, "input_tokens"),
output_tokens: integer(data, "output_tokens"),
reasoning_tokens: integer(data, "reasoning_tokens"),

3
packages/stats/core/src/domain/model.ts
View File

@ -27,6 +27,7 @@ export type ModelStatMetric = {
provider: string
model: string
sessions: number
uniqueUsers: number
inputTokens: number
outputTokens: number
reasoningTokens: number
@ -64,6 +65,7 @@ export class ModelStatRepo extends Context.Service<ModelStatRepo, ModelStatRepo.
provider: modelStat.provider,
model: modelStat.model,
sessions: modelStat.sessions,
uniqueUsers: modelStat.unique_users,
inputTokens: modelStat.input_tokens,
outputTokens: modelStat.output_tokens,
reasoningTokens: modelStat.reasoning_tokens,
@ -101,6 +103,7 @@ export class ModelStatRepo extends Context.Service<ModelStatRepo, ModelStatRepo.
provider_model: inserted("provider_model"),
sessions: inserted("sessions"),
requests: inserted("requests"),
unique_users: inserted("unique_users"),
input_tokens: inserted("input_tokens"),
output_tokens: inserted("output_tokens"),
reasoning_tokens: inserted("reasoning_tokens"),

1
packages/stats/core/src/domain/provider.ts
View File

@ -115,6 +115,7 @@ export class ProviderStatRepo extends Context.Service<ProviderStatRepo, Provider
set: {
sessions: inserted("sessions"),
requests: inserted("requests"),
unique_users: inserted("unique_users"),
input_tokens: inserted("input_tokens"),
output_tokens: inserted("output_tokens"),
reasoning_tokens: inserted("reasoning_tokens"),

4
packages/stats/core/src/domain/stat.ts
View File

@ -12,6 +12,7 @@ export type StatBaseAggregate = {
tier: string
sessions: number
requests: number
unique_users: number
input_tokens: number
output_tokens: number
reasoning_tokens: number
@ -41,6 +42,7 @@ export type StatBaseRow = {
source?: string
sessions?: number
requests?: number
unique_users?: number
input_tokens?: number
output_tokens?: number
reasoning_tokens?: number
@ -71,6 +73,7 @@ export function toStatBaseRow(data: StatBaseAggregate) {
source: "all",
sessions: data.sessions,
requests: data.requests,
unique_users: data.unique_users,
input_tokens: data.input_tokens,
output_tokens: data.output_tokens,
reasoning_tokens: data.reasoning_tokens,
@ -122,6 +125,7 @@ export function combineRows<T extends StatBaseRow>(left: T, right: T): T {
...left,
sessions: (left.sessions ?? 0) + (right.sessions ?? 0),
requests: (left.requests ?? 0) + (right.requests ?? 0),
unique_users: (left.unique_users ?? 0) + (right.unique_users ?? 0),
input_tokens: (left.input_tokens ?? 0) + (right.input_tokens ?? 0),
output_tokens: (left.output_tokens ?? 0) + (right.output_tokens ?? 0),
reasoning_tokens: (left.reasoning_tokens ?? 0) + (right.reasoning_tokens ?? 0),

17
packages/stats/core/src/honeycomb-backfill.ts
View File

@ -242,6 +242,7 @@ function metricQuery(breakdowns: string[], limit: number, filters: ReturnType<ty
calculations: [
{ op: "COUNT_DISTINCT", column: "session" },
{ op: "COUNT" },
{ op: "COUNT_DISTINCT", column: "workspace" },
{ op: "SUM", column: "tokens.input" },
{ op: "SUM", column: "tokens.output" },
{ op: "SUM", column: "tokens.reasoning" },
@ -374,9 +375,15 @@ function classifyRows(file: string, rows: RawRow[]): ImportKey {
}
function hasMetricHeaders(headers: Set<string>) {
return ["sumtokens", "sumtokensinput", "inputtokens", "totaltokens", "avgduration", "countdistinctsession"].some(
(header) => headers.has(header),
)
return [
"sumtokens",
"sumtokensinput",
"inputtokens",
"totaltokens",
"avgduration",
"countdistinctsession",
"countdistinctworkspace",
].some((header) => headers.has(header))
}
function hasHeader(headers: Set<string>, names: string[]) {
@ -447,6 +454,7 @@ function baseAggregate(row: RawRow, grain: Grain, opts: ImportOptions): StatBase
tier: tier(row),
sessions: integer(row, "sessions", ["COUNT_DISTINCT(session)"]),
requests: integer(row, "requests", ["COUNT", "COUNT()"]),
unique_users: integer(row, "unique_users", ["COUNT_DISTINCT(workspace)", "COUNT_DISTINCT(api_key)"]),
input_tokens: integer(row, "input_tokens", ["SUM(tokens.input)", "SUM(tokens_input)"]),
output_tokens: integer(row, "output_tokens", ["SUM(tokens.output)", "SUM(tokens_output)"]),
reasoning_tokens: integer(row, "reasoning_tokens", ["SUM(tokens.reasoning)", "SUM(tokens_reasoning)"]),
@ -808,6 +816,7 @@ async function upsertModelRows(db: ReturnType<typeof drizzle>, rows: ModelStatRo
provider_model: inserted("provider_model"),
sessions: inserted("sessions"),
requests: inserted("requests"),
unique_users: inserted("unique_users"),
input_tokens: inserted("input_tokens"),
output_tokens: inserted("output_tokens"),
reasoning_tokens: inserted("reasoning_tokens"),
@ -845,6 +854,7 @@ async function upsertProviderRows(db: ReturnType<typeof drizzle>, rows: Provider
set: {
sessions: inserted("sessions"),
requests: inserted("requests"),
unique_users: inserted("unique_users"),
input_tokens: inserted("input_tokens"),
output_tokens: inserted("output_tokens"),
reasoning_tokens: inserted("reasoning_tokens"),
@ -887,6 +897,7 @@ async function upsertGeoRows(db: ReturnType<typeof drizzle>, rows: GeoStatRow[],
continent: inserted("continent"),
sessions: inserted("sessions"),
requests: inserted("requests"),
unique_users: inserted("unique_users"),
input_tokens: inserted("input_tokens"),
output_tokens: inserted("output_tokens"),
reasoning_tokens: inserted("reasoning_tokens"),

8
packages/stats/core/src/stat-sync.ts
View File

@ -11,6 +11,7 @@ import { startOfIsoWeek } from "./domain/stat"
const DATALAKE_INGESTION_LAG_MS = 5 * 60_000
const STATS_DATA_START_MS = new Date("2026-05-28T00:00:00.000Z").getTime()
const WEEK_MS = 7 * 86_400_000
const DISPLAY_WINDOW_MS = 56 * 86_400_000
export type SyncStatsResult = { ok: true; rows: number; startedAt: string; periodStart: string; periodEnd: string }
export type SyncStatsError = AthenaQueryError | AthenaQueryTimeoutError | DatabaseError
@ -23,7 +24,12 @@ export const syncStats: () => Effect.Effect<
const startedAt = yield* DateTime.nowAsDate
const periodEnd = new Date(Math.floor((startedAt.getTime() - DATALAKE_INGESTION_LAG_MS) / 60_000) * 60_000)
// May 27 was partial, so keep Athena stats anchored at the first complete day.
const periodStart = new Date(Math.max(startOfIsoWeek(periodEnd).getTime() - WEEK_MS, STATS_DATA_START_MS))
const periodStart = new Date(
Math.max(
Math.min(startOfIsoWeek(periodEnd).getTime() - WEEK_MS, periodEnd.getTime() - DISPLAY_WINDOW_MS),
STATS_DATA_START_MS,
),
)
const athena = yield* Athena
const modelStats = yield* ModelStatRepo
const providerStats = yield* ProviderStatRepo