feat: 品牌替换 + 启动优化 + AGENTS.md 模板定制
- 品牌替换：OpenCode/opencode → AirCoding/aircoding（16+ 文件） - Logo ASCII art：修复 left/right 行数不匹配导致的启动崩溃 - 启动诊断：添加 OPENCODE_PRINT_TIMING 计时探针 - dev 模式默认 --pure 跳过外部插件加载 - AGENTS.md 模板：追加 AirCoding 多 Agent 专项段落 - architect prompt + plugin：强化 AGENTS.md 产出验证
This commit is contained in:
airlongdian
1
packages/stats/AGENTS.md
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1
packages/stats/AGENTS.md
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@@ -0,0 +1 @@
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To start the stats site locally, run `bun dev:stats` from the repo root.
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16
packages/stats/README.md
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16
packages/stats/README.md
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@@ -0,0 +1,16 @@
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# OpenCode Stats
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Stats is a separate site from the console. Runtime, database, and domain services live in `core`; the SolidStart website lives in `app`; deployable Lambda entrypoints live in `function`.
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## Packages
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- `app`: SolidStart frontend/site.
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- `core`: Effect services, app config, Drizzle schema/migrations, and stats domains.
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- `function`: Lambda handlers that call into `core` services.
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## Commands
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- `bun run dev:stats` from the repo root starts the SolidStart app.
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- `bun run --cwd packages/stats/app typecheck` typechecks the site.
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- `bun run --cwd packages/stats/core typecheck` typechecks the Effect/database package.
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- `bun run --cwd packages/stats/function typecheck` typechecks Lambda entrypoints.
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17
packages/stats/app/.gitignore
vendored
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17
packages/stats/app/.gitignore
vendored
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dist
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.wrangler
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.output
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.vercel
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.netlify
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app.config.timestamp_*.js
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# Environment
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.env
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.env*.local
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# dependencies
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/node_modules
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# System Files
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.DS_Store
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Thumbs.db
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5
packages/stats/app/app.config.ts
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5
packages/stats/app/app.config.ts
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export default {
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server: {
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preset: "cloudflare-module",
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},
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}
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46
packages/stats/app/package.json
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46
packages/stats/app/package.json
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{
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"$schema": "https://json.schemastore.org/package.json",
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"name": "@opencode-ai/stats-app",
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"version": "1.17.4",
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"private": true,
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"type": "module",
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"license": "MIT",
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"scripts": {
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"typecheck": "tsgo --noEmit",
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"dev": "vite dev --host 0.0.0.0",
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"build": "vite build",
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"start": "vite start"
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},
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"dependencies": {
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"@ibm/plex": "6.4.1",
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"@opencode-ai/stats-core": "workspace:*",
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"@opencode-ai/ui": "workspace:*",
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"@solidjs/meta": "catalog:",
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"@solidjs/router": "catalog:",
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"@solidjs/start": "catalog:",
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"d3-geo": "3.1.1",
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"d3-scale": "4.0.2",
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"effect": "catalog:",
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"i18n-iso-countries": "7.14.0",
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"nitro": "3.0.1-alpha.1",
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"solid-js": "catalog:",
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"sst": "catalog:",
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"topojson-client": "3.1.0",
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"vite": "catalog:",
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"world-atlas": "2.0.2"
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},
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"devDependencies": {
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"@cloudflare/workers-types": "catalog:",
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"@types/bun": "catalog:",
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"@types/d3-geo": "3.1.0",
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"@types/d3-scale": "4.0.9",
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"@types/geojson": "7946.0.16",
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"@types/topojson-client": "3.1.5",
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"@types/topojson-specification": "1.0.5",
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"@typescript/native-preview": "catalog:",
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"typescript": "catalog:"
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},
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"engines": {
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"node": ">=22"
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}
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}
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BIN
packages/stats/app/public/banner.jpg
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BIN
packages/stats/app/public/banner.jpg
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After Width: | Height: | Size: 163 KiB |
BIN
packages/stats/app/public/banner.png
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packages/stats/app/public/banner.png
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After Width: | Height: | Size: 116 KiB |
123
packages/stats/app/src/app.css
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packages/stats/app/src/app.css
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:root {
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color-scheme: light dark;
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--stats-bg: #f8f5ee;
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--stats-ink: #16110d;
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--stats-muted: #6d6257;
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--stats-line: #ded5c9;
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--stats-panel: #fffaf1;
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--stats-accent: #2357ff;
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}
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@media (prefers-color-scheme: dark) {
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:root {
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--stats-bg: #11100e;
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--stats-ink: #f7efe4;
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--stats-muted: #b8aa99;
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--stats-line: #322d27;
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--stats-panel: #1a1714;
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--stats-accent: #86a2ff;
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}
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}
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html {
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line-height: 1;
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background: var(--stats-bg);
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}
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body {
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margin: 0;
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min-width: 320px;
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background:
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radial-gradient(circle at top left, color-mix(in srgb, var(--stats-accent) 16%, transparent), transparent 32rem),
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var(--stats-bg);
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color: var(--stats-ink);
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font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
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-webkit-font-smoothing: antialiased;
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}
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a {
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color: inherit;
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}
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.shell {
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box-sizing: border-box;
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min-height: 100vh;
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padding: 2rem clamp(1rem, 4vw, 4rem);
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}
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.panel {
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display: grid;
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gap: clamp(2rem, 8vw, 5rem);
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box-sizing: border-box;
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width: min(100%, 72rem);
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margin: 0 auto;
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padding: clamp(1.25rem, 4vw, 3rem);
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border: 1px solid var(--stats-line);
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border-radius: 1.5rem;
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background: color-mix(in srgb, var(--stats-panel) 88%, transparent);
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}
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.eyebrow {
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margin: 0 0 1rem;
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color: var(--stats-muted);
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font-size: 0.75rem;
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letter-spacing: 0.14em;
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text-transform: uppercase;
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}
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h1 {
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max-width: 11ch;
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margin: 0;
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font-size: clamp(3rem, 14vw, 9rem);
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line-height: 0.85;
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letter-spacing: -0.08em;
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}
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.summary {
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max-width: 42rem;
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margin: 1.5rem 0 0;
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color: var(--stats-muted);
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font-size: clamp(1rem, 2vw, 1.25rem);
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line-height: 1.6;
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}
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.grid {
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display: grid;
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grid-template-columns: repeat(3, minmax(0, 1fr));
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gap: 1px;
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overflow: hidden;
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border: 1px solid var(--stats-line);
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border-radius: 1rem;
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background: var(--stats-line);
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}
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.metric {
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padding: 1rem;
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background: var(--stats-panel);
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}
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.metric b {
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display: block;
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margin-bottom: 0.5rem;
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font-size: clamp(1.5rem, 4vw, 3rem);
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letter-spacing: -0.05em;
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}
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.metric span {
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color: var(--stats-muted);
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font-size: 0.8125rem;
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}
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.link {
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display: inline-flex;
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width: fit-content;
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margin-top: 1.5rem;
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color: var(--stats-accent);
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text-decoration: none;
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}
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@media (max-width: 720px) {
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.grid {
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grid-template-columns: 1fr;
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}
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}
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31
packages/stats/app/src/app.tsx
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31
packages/stats/app/src/app.tsx
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import { MetaProvider, Meta, Title } from "@solidjs/meta"
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import { Router } from "@solidjs/router"
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import { FileRoutes } from "@solidjs/start/router"
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import { Suspense } from "solid-js"
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import "./app.css"
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function AppMeta() {
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return (
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<>
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<Title>OpenCode Data</Title>
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<Meta name="description" content="OpenCode usage data, market share, token cost, and session cost." />
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</>
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)
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}
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export default function App() {
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return (
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<Router
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base={import.meta.env.BASE_URL.replace(/\/$/, "")}
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explicitLinks={true}
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root={(props) => (
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<MetaProvider>
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<AppMeta />
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<Suspense>{props.children}</Suspense>
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</MetaProvider>
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)}
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>
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<FileRoutes />
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</Router>
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)
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}
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18
packages/stats/app/src/asset/logo-ornate-dark.svg
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packages/stats/app/src/asset/logo-ornate-dark.svg
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<svg width="234" height="42" viewBox="0 0 234 42" fill="none" xmlns="http://www.w3.org/2000/svg">
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<path d="M18 30H6V18H18V30Z" fill="#4B4646"/>
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<path d="M18 12H6V30H18V12ZM24 36H0V6H24V36Z" fill="#B7B1B1"/>
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<path d="M48 30H36V18H48V30Z" fill="#4B4646"/>
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<path d="M36 30H48V12H36V30ZM54 36H36V42H30V6H54V36Z" fill="#B7B1B1"/>
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<path d="M84 24V30H66V24H84Z" fill="#4B4646"/>
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<path d="M84 24H66V30H84V36H60V6H84V24ZM66 18H78V12H66V18Z" fill="#B7B1B1"/>
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<path d="M108 36H96V18H108V36Z" fill="#4B4646"/>
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<path d="M108 12H96V36H90V6H108V12ZM114 36H108V12H114V36Z" fill="#B7B1B1"/>
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<path d="M144 30H126V18H144V30Z" fill="#4B4646"/>
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<path d="M144 12H126V30H144V36H120V6H144V12Z" fill="#F1ECEC"/>
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<path d="M168 30H156V18H168V30Z" fill="#4B4646"/>
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<path d="M168 12H156V30H168V12ZM174 36H150V6H174V36Z" fill="#F1ECEC"/>
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<path d="M198 30H186V18H198V30Z" fill="#4B4646"/>
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<path d="M198 12H186V30H198V12ZM204 36H180V6H198V0H204V36Z" fill="#F1ECEC"/>
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<path d="M234 24V30H216V24H234Z" fill="#4B4646"/>
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<path d="M216 12V18H228V12H216ZM234 24H216V30H234V36H210V6H234V24Z" fill="#F1ECEC"/>
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</svg>
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After Width: | Height: | Size: 1.1 KiB |
18
packages/stats/app/src/asset/logo-ornate-light.svg
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packages/stats/app/src/asset/logo-ornate-light.svg
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<svg width="234" height="42" viewBox="0 0 234 42" fill="none" xmlns="http://www.w3.org/2000/svg">
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<path d="M18 30H6V18H18V30Z" fill="#CFCECD"/>
|
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<path d="M18 12H6V30H18V12ZM24 36H0V6H24V36Z" fill="#656363"/>
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<path d="M48 30H36V18H48V30Z" fill="#CFCECD"/>
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||||
<path d="M36 30H48V12H36V30ZM54 36H36V42H30V6H54V36Z" fill="#656363"/>
|
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<path d="M84 24V30H66V24H84Z" fill="#CFCECD"/>
|
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<path d="M84 24H66V30H84V36H60V6H84V24ZM66 18H78V12H66V18Z" fill="#656363"/>
|
||||
<path d="M108 36H96V18H108V36Z" fill="#CFCECD"/>
|
||||
<path d="M108 12H96V36H90V6H108V12ZM114 36H108V12H114V36Z" fill="#656363"/>
|
||||
<path d="M144 30H126V18H144V30Z" fill="#CFCECD"/>
|
||||
<path d="M144 12H126V30H144V36H120V6H144V12Z" fill="#211E1E"/>
|
||||
<path d="M168 30H156V18H168V30Z" fill="#CFCECD"/>
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||||
<path d="M168 12H156V30H168V12ZM174 36H150V6H174V36Z" fill="#211E1E"/>
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||||
<path d="M198 30H186V18H198V30Z" fill="#CFCECD"/>
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<path d="M198 12H186V30H198V12ZM204 36H180V6H198V0H204V36Z" fill="#211E1E"/>
|
||||
<path d="M234 24V30H216V24H234Z" fill="#CFCECD"/>
|
||||
<path d="M216 12V18H228V12H216ZM234 24H216V30H234V36H210V6H234V24Z" fill="#211E1E"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 1.1 KiB |
7
packages/stats/app/src/entry-client.tsx
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7
packages/stats/app/src/entry-client.tsx
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|
||||
// @refresh reload
|
||||
import { mount, StartClient } from "@solidjs/start/client"
|
||||
|
||||
const root = document.getElementById("app")
|
||||
if (!root) throw new Error("Root element #app not found")
|
||||
|
||||
mount(() => <StartClient />, root)
|
||||
37
packages/stats/app/src/entry-server.tsx
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37
packages/stats/app/src/entry-server.tsx
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|
||||
// @refresh reload
|
||||
import { createHandler, StartServer } from "@solidjs/start/server"
|
||||
|
||||
const statsThemePreloadScript = `;(function () {
|
||||
var preference = "system"
|
||||
try {
|
||||
var stored = localStorage.getItem("opencode:stats-theme")
|
||||
if (stored === "dark" || stored === "light" || stored === "system") preference = stored
|
||||
} catch (_) {}
|
||||
document.documentElement.dataset.statsTheme = preference
|
||||
if (preference === "system") document.documentElement.style.removeProperty("color-scheme")
|
||||
else document.documentElement.style.setProperty("color-scheme", preference)
|
||||
})()`
|
||||
|
||||
export default createHandler(
|
||||
() => (
|
||||
<StartServer
|
||||
document={({ assets, children, scripts }) => (
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1" />
|
||||
<script id="stats-theme-preload-script">{statsThemePreloadScript}</script>
|
||||
{assets}
|
||||
</head>
|
||||
<body>
|
||||
<div id="app">{children}</div>
|
||||
{scripts}
|
||||
</body>
|
||||
</html>
|
||||
)}
|
||||
/>
|
||||
),
|
||||
{
|
||||
mode: "async",
|
||||
},
|
||||
)
|
||||
1
packages/stats/app/src/global.d.ts
vendored
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1
packages/stats/app/src/global.d.ts
vendored
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@@ -0,0 +1 @@
|
||||
/// <reference types="@solidjs/start/env" />
|
||||
10
packages/stats/app/src/resource.d.ts
vendored
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10
packages/stats/app/src/resource.d.ts
vendored
Normal file
@@ -0,0 +1,10 @@
|
||||
import "sst/resource"
|
||||
|
||||
declare module "sst/resource" {
|
||||
export interface Resource {
|
||||
EMAILOCTOPUS_API_KEY: {
|
||||
type: "sst.sst.Secret"
|
||||
value: string
|
||||
}
|
||||
}
|
||||
}
|
||||
836
packages/stats/app/src/routes/[lab]/[model].tsx
Normal file
836
packages/stats/app/src/routes/[lab]/[model].tsx
Normal file
@@ -0,0 +1,836 @@
|
||||
import "../index.css"
|
||||
import { Link, Meta, Title } from "@solidjs/meta"
|
||||
import { ProviderIcon } from "@opencode-ai/ui/provider-icon"
|
||||
import { geoEquirectangular, geoPath } from "d3-geo"
|
||||
import { scaleSqrt } from "d3-scale"
|
||||
import countryCodesSource from "i18n-iso-countries/codes.json?raw"
|
||||
import { feature, mesh } from "topojson-client"
|
||||
import countriesTopologySource from "world-atlas/countries-110m.json?raw"
|
||||
import {
|
||||
getStatsModelData,
|
||||
type CountryEntry,
|
||||
type ModelPeerEntry,
|
||||
type ModelUsagePoint,
|
||||
type StatsModelData,
|
||||
type UsageRange,
|
||||
} from "@opencode-ai/stats-core/domain/home"
|
||||
import { runtime } from "@opencode-ai/stats-core/runtime"
|
||||
import { createAsync, query, useParams } from "@solidjs/router"
|
||||
import { createMemo, createSignal, For, onMount, Show, type JSX } from "solid-js"
|
||||
import { getRequestEvent } from "solid-js/web"
|
||||
import type { FeatureCollection, GeometryObject, GeoJsonProperties } from "geojson"
|
||||
import type { GeometryCollection, Topology } from "topojson-specification"
|
||||
import { findModelCatalogEntry, formatCatalogLabName, getModelCatalog, type ModelCatalogEntry } from "../model-catalog"
|
||||
import {
|
||||
applyThemePreference,
|
||||
Footer,
|
||||
getGitHubStars,
|
||||
Header,
|
||||
isThemePreference,
|
||||
themeStorageKey,
|
||||
type HeaderLink,
|
||||
type ThemePreference,
|
||||
} from "../stats-shell"
|
||||
|
||||
const statsCanonicalBaseUrl = "https://opencode.ai/data/"
|
||||
const statsUnfurlPath = "banner.png"
|
||||
const statsUnfurlAlt = "OpenCode Data wordmark on a dark patterned background"
|
||||
const statsUnfurlUrl = new URL(statsUnfurlPath, statsCanonicalBaseUrl).toString()
|
||||
const modelHeaderLinks: readonly HeaderLink[] = [
|
||||
{ href: "#overview", label: "Overview" },
|
||||
{ href: "#usage", label: "Usage" },
|
||||
{ href: "#efficiency", label: "Efficiency" },
|
||||
{ href: "#geo-breakdown", label: "Geo Breakdown" },
|
||||
{ href: "#peers", label: "Peers" },
|
||||
]
|
||||
const modelFooterLinks: readonly HeaderLink[] = [
|
||||
{ href: import.meta.env.BASE_URL, label: "Data Home" },
|
||||
{ href: `${import.meta.env.BASE_URL}#top-models`, label: "Top Models" },
|
||||
{ href: `${import.meta.env.BASE_URL}#leaderboard`, label: "Leaderboard" },
|
||||
{ href: `${import.meta.env.BASE_URL}#session-cost`, label: "Session Cost" },
|
||||
{ href: `${import.meta.env.BASE_URL}#token-cost`, label: "Token Cost" },
|
||||
{ href: `${import.meta.env.BASE_URL}#market-share`, label: "Market Share" },
|
||||
{ href: `${import.meta.env.BASE_URL}#geo-breakdown`, label: "Geo Breakdown" },
|
||||
]
|
||||
const geoMapWidth = 960
|
||||
const geoMapHeight = 430
|
||||
const countryDisplayNames = new Intl.DisplayNames(["en"], { type: "region" })
|
||||
|
||||
type IsoCountryCode = readonly [string, string, string]
|
||||
type WorldCountryProperties = GeoJsonProperties & { name?: string }
|
||||
type WorldTopology = Topology<{ countries: GeometryCollection<WorldCountryProperties> }>
|
||||
|
||||
const countryNumericIds = new Map(
|
||||
(JSON.parse(countryCodesSource) as IsoCountryCode[]).map((country) => [country[0], country[2]] as const),
|
||||
)
|
||||
const worldTopology = JSON.parse(countriesTopologySource) as WorldTopology
|
||||
const worldCountryGeometries: GeometryCollection<WorldCountryProperties> = {
|
||||
...worldTopology.objects.countries,
|
||||
geometries: worldTopology.objects.countries.geometries.filter((country) => String(country.id ?? "") !== "010"),
|
||||
}
|
||||
const worldCountries = feature<WorldCountryProperties>(worldTopology, worldCountryGeometries) as FeatureCollection<
|
||||
GeometryObject,
|
||||
WorldCountryProperties
|
||||
>
|
||||
const worldProjection = geoEquirectangular().fitExtent(
|
||||
[
|
||||
[10, 12],
|
||||
[geoMapWidth - 10, geoMapHeight - 12],
|
||||
],
|
||||
worldCountries,
|
||||
)
|
||||
const worldPath = geoPath(worldProjection)
|
||||
const worldCountryPaths = worldCountries.features.map((country) => ({
|
||||
id: String(country.id ?? "").padStart(3, "0"),
|
||||
path: worldPath(country) ?? "",
|
||||
}))
|
||||
const worldBorderPath = worldPath(mesh(worldTopology, worldCountryGeometries, (a, b) => a !== b)) ?? ""
|
||||
|
||||
const getModelData = query(async (lab: string, model: string) => {
|
||||
"use server"
|
||||
return runtime.runPromise(getStatsModelData(model, lab))
|
||||
}, "getStatsModelData")
|
||||
|
||||
export default function StatsModel() {
|
||||
const event = getRequestEvent()
|
||||
event?.response.headers.set("Cache-Control", "public, max-age=60, s-maxage=300, stale-while-revalidate=86400")
|
||||
const params = useParams()
|
||||
const labParam = createMemo(() => params.lab ?? "")
|
||||
const modelParam = createMemo(() => params.model ?? "")
|
||||
const catalog = createAsync(() => getModelCatalog())
|
||||
const catalogEntry = createMemo(() => {
|
||||
const data = catalog()
|
||||
if (!data) return undefined
|
||||
return findModelCatalogEntry(data, modelParam(), labParam()) ?? null
|
||||
})
|
||||
const stats = createAsync(() => {
|
||||
const entry = catalogEntry()
|
||||
if (catalog() === undefined || entry === undefined) return Promise.resolve(undefined)
|
||||
if (!entry && (!labParam() || !modelParam())) return Promise.resolve(null)
|
||||
return getModelData(labParam(), entry?.slug ?? modelParam())
|
||||
})
|
||||
const githubStars = createAsync(() => getGitHubStars())
|
||||
const [themePreference, setThemePreference] = createSignal<ThemePreference>("system")
|
||||
const modelName = createMemo(() => catalogEntry()?.name ?? stats()?.model ?? modelParam() ?? "Model")
|
||||
const labName = createMemo(() => formatCatalogLabName(catalogEntry()?.lab ?? stats()?.provider ?? labParam()))
|
||||
const modelTitle = createMemo(() => `${modelName()} Data`)
|
||||
const modelDescription = createMemo(() =>
|
||||
stats()
|
||||
? `${modelName()} usage, rank, token mix, cost, geo breakdown, and peer data across OpenCode.`
|
||||
: `${modelName()} model facts, limits, and OpenCode usage availability.`,
|
||||
)
|
||||
const modelUrl = createMemo(() =>
|
||||
new URL(
|
||||
catalogEntry()?.id ?? [labParam(), stats()?.slug ?? modelParam()].filter((part) => part.length > 0).join("/"),
|
||||
statsCanonicalBaseUrl,
|
||||
).toString(),
|
||||
)
|
||||
const updateThemePreference = (preference: ThemePreference) => {
|
||||
applyThemePreference(preference)
|
||||
setThemePreference(preference)
|
||||
if (typeof window === "undefined") return
|
||||
window.localStorage.setItem(themeStorageKey, preference)
|
||||
}
|
||||
|
||||
onMount(() => {
|
||||
if (typeof window === "undefined") return
|
||||
const preference = window.localStorage.getItem(themeStorageKey)
|
||||
const nextPreference = isThemePreference(preference) ? preference : "system"
|
||||
applyThemePreference(nextPreference)
|
||||
setThemePreference(nextPreference)
|
||||
})
|
||||
|
||||
return (
|
||||
<main data-page="stats" data-theme={themePreference()}>
|
||||
<Title>{modelTitle()}</Title>
|
||||
<Meta name="description" content={modelDescription()} />
|
||||
<Link rel="canonical" href={modelUrl()} />
|
||||
<Meta property="og:type" content="website" />
|
||||
<Meta property="og:site_name" content="OpenCode" />
|
||||
<Meta property="og:title" content={modelTitle()} />
|
||||
<Meta property="og:description" content={modelDescription()} />
|
||||
<Meta property="og:url" content={modelUrl()} />
|
||||
<Meta property="og:image" content={statsUnfurlUrl} />
|
||||
<Meta property="og:image:type" content="image/png" />
|
||||
<Meta property="og:image:width" content="1200" />
|
||||
<Meta property="og:image:height" content="630" />
|
||||
<Meta property="og:image:alt" content={statsUnfurlAlt} />
|
||||
<Meta name="twitter:card" content="summary_large_image" />
|
||||
<Meta name="twitter:title" content={modelTitle()} />
|
||||
<Meta name="twitter:description" content={modelDescription()} />
|
||||
<Meta name="twitter:image" content={statsUnfurlUrl} />
|
||||
<Meta name="twitter:image:alt" content={statsUnfurlAlt} />
|
||||
<Header githubStars={githubStars() ?? "150K"} links={modelHeaderLinks} brandHref={import.meta.env.BASE_URL} />
|
||||
<div data-component="container">
|
||||
<div data-component="content">
|
||||
<Show when={catalogEntry() || stats() !== undefined} fallback={<ModelLoading />}>
|
||||
<Show when={catalogEntry() || stats()} fallback={<ModelNotFound lab={labParam()} model={modelParam()} />}>
|
||||
<>
|
||||
<ModelHero data={stats() ?? null} catalog={catalogEntry() ?? null} labName={labName()} />
|
||||
<ModelOverview data={stats() ?? null} />
|
||||
<ModelUsageSection data={stats()?.usage ?? []} />
|
||||
<ModelEfficiencySection data={stats() ?? null} />
|
||||
<ModelGeoBreakdownSection data={stats()?.country ?? emptyCountryRecord()} />
|
||||
<ModelPeersSection data={stats() ?? null} />
|
||||
</>
|
||||
</Show>
|
||||
</Show>
|
||||
</div>
|
||||
<Footer
|
||||
themePreference={themePreference()}
|
||||
onThemePreferenceChange={updateThemePreference}
|
||||
links={modelFooterLinks}
|
||||
/>
|
||||
</div>
|
||||
</main>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelLoading() {
|
||||
return (
|
||||
<>
|
||||
<section id="overview" data-section="model-hero">
|
||||
<div data-slot="model-hero-grid">
|
||||
<div data-slot="model-hero-copy">
|
||||
<a data-slot="model-back-link" href={import.meta.env.BASE_URL}>
|
||||
Data
|
||||
</a>
|
||||
<h1>Model Data</h1>
|
||||
<p>Reading model aggregates from model_stat.</p>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
<section data-section="model-panel">
|
||||
<ModelEmptyState title="Loading model data" description="Reading the model profile." />
|
||||
</section>
|
||||
</>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelNotFound(props: { lab: string; model: string }) {
|
||||
return (
|
||||
<>
|
||||
<section id="overview" data-section="model-hero">
|
||||
<div data-slot="model-hero-grid">
|
||||
<div data-slot="model-hero-copy">
|
||||
<a data-slot="model-back-link" href={import.meta.env.BASE_URL}>
|
||||
Data
|
||||
</a>
|
||||
<h1>{props.model || "Model"}</h1>
|
||||
<p>No model facts or model_stat rows matched {props.lab ? `${props.lab}/${props.model}` : props.model}.</p>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
<section data-section="model-panel">
|
||||
<ModelEmptyState title="No model data" description="Try opening a model from the leaderboard." />
|
||||
</section>
|
||||
</>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelHero(props: { data: StatsModelData | null; catalog: ModelCatalogEntry | null; labName: string }) {
|
||||
const labId = () => props.catalog?.lab ?? props.data?.provider ?? props.labName
|
||||
const modelId = () => props.catalog?.id ?? props.data?.model ?? "Model"
|
||||
const weights = () => props.catalog?.weights[0]
|
||||
return (
|
||||
<section id="overview" data-section="model-hero">
|
||||
<a data-slot="model-back-link" href={import.meta.env.BASE_URL}>
|
||||
Data
|
||||
</a>
|
||||
<div data-slot="model-hero-grid">
|
||||
<div data-slot="model-hero-copy">
|
||||
<div data-slot="model-hero-tags">
|
||||
<a data-slot="hero-meta" href={`${import.meta.env.BASE_URL}${providerSlug(labId())}`}>
|
||||
<ProviderIcon aria-hidden="true" id={getProviderIconId(labId())} />
|
||||
<span>{props.labName}</span>
|
||||
</a>
|
||||
<span data-slot="model-id-tag">{modelId()}</span>
|
||||
</div>
|
||||
<h1>{props.catalog?.name ?? props.data?.model ?? "Model"}</h1>
|
||||
<Show
|
||||
when={props.data}
|
||||
fallback={
|
||||
<p>Model facts from the shared model index. OpenCode usage appears once this model has activity.</p>
|
||||
}
|
||||
>
|
||||
{(data) => (
|
||||
<p>
|
||||
Ranked #{data().rank} across recent OpenCode token usage with {formatPercent(data().tokenShare)} of
|
||||
observed volume.
|
||||
</p>
|
||||
)}
|
||||
</Show>
|
||||
<Show when={props.catalog?.openWeights && weights()}>
|
||||
{(weight) => (
|
||||
<a data-slot="model-weight-link" href={weight().url} target="_blank" rel="noopener noreferrer">
|
||||
Model weights: {weight().label}
|
||||
</a>
|
||||
)}
|
||||
</Show>
|
||||
</div>
|
||||
<Show when={props.data} fallback={<ModelCatalogCallout catalog={props.catalog} />}>
|
||||
{(data) => (
|
||||
<div data-component="model-rank-panel">
|
||||
<span>Current Rank</span>
|
||||
<strong>#{data().rank}</strong>
|
||||
<p>{formatRankMoveLabel(data().previousRank, data().rank)}</p>
|
||||
</div>
|
||||
)}
|
||||
</Show>
|
||||
</div>
|
||||
<div data-slot="model-hero-pattern" aria-hidden="true" />
|
||||
<Show when={props.catalog}>{(catalog) => <ModelCatalogPanel data={catalog()} />}</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelCatalogCallout(props: { catalog: ModelCatalogEntry | null }) {
|
||||
return (
|
||||
<div data-component="model-rank-panel">
|
||||
<span>Model Profile</span>
|
||||
<strong>{props.catalog?.releaseDate ? formatCatalogDate(props.catalog.releaseDate) : "Listed"}</strong>
|
||||
<p>No OpenCode usage in the current data window.</p>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelCatalogPanel(props: { data: ModelCatalogEntry }) {
|
||||
return (
|
||||
<aside data-component="model-catalog" aria-label="Model facts">
|
||||
<div data-slot="model-catalog-grid">
|
||||
<CatalogDatum label="Context" value={formatCatalogLimit(props.data.limit?.context)} />
|
||||
<CatalogDatum label="Output" value={formatCatalogLimit(props.data.limit?.output)} />
|
||||
<CatalogDatum label="Knowledge" value={formatCatalogDate(props.data.knowledge)} />
|
||||
<CatalogDatum label="Release" value={formatCatalogDate(props.data.releaseDate)} />
|
||||
<CatalogDatum label="Inputs" value={formatCatalogModalities(props.data.modalities.input)} />
|
||||
</div>
|
||||
</aside>
|
||||
)
|
||||
}
|
||||
|
||||
function CatalogDatum(props: { label: string; value: string }) {
|
||||
return (
|
||||
<article data-component="model-catalog-datum">
|
||||
<span>{props.label}</span>
|
||||
<strong>{props.value}</strong>
|
||||
</article>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelOverview(props: { data: StatsModelData | null }) {
|
||||
return (
|
||||
<section data-section="model-panel">
|
||||
<SectionTitle title="Overview" description="Recent tokens, sessions, and market position." />
|
||||
<Show
|
||||
when={props.data}
|
||||
fallback={<ModelEmptyState title="No usage summary" description="This model has no OpenCode usage rows yet." />}
|
||||
>
|
||||
{(data) => (
|
||||
<div data-component="model-metric-grid">
|
||||
<MetricCard label="Tokens" value={formatTokens(data().totals.tokens)} detail="last two months" />
|
||||
<MetricCard label="Sessions" value={formatInteger(data().totals.sessions)} detail="completed sessions" />
|
||||
<MetricCard
|
||||
label="Token Share"
|
||||
value={formatPercent(data().tokenShare)}
|
||||
detail={`${data().totalModels} models`}
|
||||
/>
|
||||
<MetricCard
|
||||
label="Momentum"
|
||||
value={formatChange(data().tokenChange)}
|
||||
detail="vs previous window"
|
||||
state={data().tokenChange < 0 ? "negative" : "positive"}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
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 token volume over the recent two-month window." />
|
||||
<Show
|
||||
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>
|
||||
</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelEfficiencySection(props: { data: StatsModelData | null }) {
|
||||
return (
|
||||
<section id="efficiency" data-section="model-panel">
|
||||
<SectionTitle title="Efficiency" description="Cost, cache behavior, and average session shape." />
|
||||
<Show
|
||||
when={props.data}
|
||||
fallback={
|
||||
<ModelEmptyState title="No efficiency data" description="Efficiency data appears after usage lands." />
|
||||
}
|
||||
>
|
||||
{(data) => (
|
||||
<div data-component="model-metric-grid" data-variant="dense">
|
||||
<MetricCard label="Cost" value={formatMoney(data().totals.cost)} detail="total spend" />
|
||||
<MetricCard label="Cost / 1M" value={formatMoney(data().totals.costPerMillion)} detail="all tokens" />
|
||||
<MetricCard
|
||||
label="Cost / Session"
|
||||
value={formatSessionCost(data().totals.costPerSession)}
|
||||
detail="average"
|
||||
/>
|
||||
<MetricCard
|
||||
label="Tokens / Session"
|
||||
value={formatTokens(data().totals.tokensPerSession)}
|
||||
detail="average"
|
||||
/>
|
||||
<MetricCard label="Cache Ratio" value={formatPercent(data().totals.cacheRatio)} detail="input tokens" />
|
||||
</div>
|
||||
)}
|
||||
</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelGeoBreakdownSection(props: { data: Record<UsageRange, CountryEntry[]> }) {
|
||||
const [activeCountry, setActiveCountry] = createSignal<string>()
|
||||
const data = createMemo(() => props.data["2M"])
|
||||
const countryById = createMemo(
|
||||
() =>
|
||||
new Map(
|
||||
data().flatMap((country) => {
|
||||
const id = countryNumericId(country.country)
|
||||
return id ? [[id, country] as const] : []
|
||||
}),
|
||||
),
|
||||
)
|
||||
const maxTokens = createMemo(() => Math.max(0, ...data().map((country) => country.tokens)) || 1)
|
||||
const topCountries = createMemo(() => data().slice(0, 15))
|
||||
const active = createMemo(() => data().find((country) => country.country === activeCountry()) ?? data()[0])
|
||||
|
||||
return (
|
||||
<section
|
||||
id="geo-breakdown"
|
||||
data-section="geo-breakdown"
|
||||
onPointerLeave={(event) => {
|
||||
if (event.pointerType === "touch") return
|
||||
setActiveCountry(undefined)
|
||||
}}
|
||||
>
|
||||
<SectionTitle title="Geo Breakdown" description="Model tokens used by country." />
|
||||
<Show
|
||||
when={data().length > 0}
|
||||
fallback={<ModelEmptyState title="No geo data" description="No geo_stat rows matched this model." />}
|
||||
>
|
||||
<div data-component="geo-breakdown">
|
||||
<div data-slot="geo-map-panel">
|
||||
<GeoWorldMap
|
||||
countryById={countryById()}
|
||||
activeCountry={activeCountry()}
|
||||
maxTokens={maxTokens()}
|
||||
onActiveCountryChange={setActiveCountry}
|
||||
/>
|
||||
<Show when={active()}>
|
||||
{(country) => (
|
||||
<div data-slot="geo-active-country">
|
||||
<span>#{String(country().rank).padStart(2, "0")}</span>
|
||||
<strong>{formatCountryName(country().country)}</strong>
|
||||
<p>
|
||||
<b>{formatGeoTokens(country().tokens)}</b>
|
||||
<em>{formatGeoShare(country().share)}</em>
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</Show>
|
||||
</div>
|
||||
<GeoCountryList
|
||||
data={topCountries()}
|
||||
activeCountry={activeCountry()}
|
||||
maxTokens={maxTokens()}
|
||||
onActiveCountryChange={setActiveCountry}
|
||||
/>
|
||||
</div>
|
||||
</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function GeoWorldMap(props: {
|
||||
countryById: Map<string, CountryEntry>
|
||||
activeCountry: string | undefined
|
||||
maxTokens: number
|
||||
onActiveCountryChange: (country: string | undefined) => void
|
||||
}) {
|
||||
const opacityScale = createMemo(() => scaleSqrt().domain([0, props.maxTokens]).range([0.26, 0.96]).clamp(true))
|
||||
const countryOpacity = (country: CountryEntry | undefined) => {
|
||||
if (!country) return 0
|
||||
const opacity = opacityScale()(country.tokens)
|
||||
if (!props.activeCountry || props.activeCountry === country.country) return opacity
|
||||
return Math.max(0.18, opacity * 0.36)
|
||||
}
|
||||
|
||||
return (
|
||||
<svg
|
||||
data-component="geo-world-map"
|
||||
viewBox={`0 0 ${geoMapWidth} ${geoMapHeight}`}
|
||||
role="img"
|
||||
aria-label="World map of model token usage by country"
|
||||
>
|
||||
<title>Geo Breakdown map</title>
|
||||
<g data-slot="geo-countries">
|
||||
<For each={worldCountryPaths}>
|
||||
{(country) => {
|
||||
const entry = () => props.countryById.get(country.id)
|
||||
return (
|
||||
<path
|
||||
d={country.path}
|
||||
data-has-data={entry() ? "true" : undefined}
|
||||
data-active={entry()?.country === props.activeCountry ? "true" : undefined}
|
||||
style={{ "--geo-country-opacity": String(countryOpacity(entry())) } as JSX.CSSProperties}
|
||||
aria-hidden="true"
|
||||
onPointerEnter={() => {
|
||||
const item = entry()
|
||||
if (!item) return
|
||||
props.onActiveCountryChange(item.country)
|
||||
}}
|
||||
onClick={() => {
|
||||
const item = entry()
|
||||
if (!item) return
|
||||
props.onActiveCountryChange(item.country)
|
||||
}}
|
||||
/>
|
||||
)
|
||||
}}
|
||||
</For>
|
||||
</g>
|
||||
<path data-slot="geo-borders" d={worldBorderPath} aria-hidden="true" />
|
||||
</svg>
|
||||
)
|
||||
}
|
||||
|
||||
function GeoCountryList(props: {
|
||||
data: CountryEntry[]
|
||||
activeCountry: string | undefined
|
||||
maxTokens: number
|
||||
onActiveCountryChange: (country: string | undefined) => void
|
||||
}) {
|
||||
const opacityScale = createMemo(() => scaleSqrt().domain([0, props.maxTokens]).range([0.26, 0.96]).clamp(true))
|
||||
|
||||
return (
|
||||
<ol data-component="geo-country-list">
|
||||
<For each={props.data}>
|
||||
{(country) => (
|
||||
<li>
|
||||
<button
|
||||
type="button"
|
||||
data-active={props.activeCountry === country.country ? "true" : undefined}
|
||||
style={{ "--geo-row-opacity": String(opacityScale()(country.tokens)) } as JSX.CSSProperties}
|
||||
aria-label={`${formatCountryName(country.country)} ${formatGeoTokens(country.tokens)} ${formatGeoShare(
|
||||
country.share,
|
||||
)}`}
|
||||
onClick={() => props.onActiveCountryChange(country.country)}
|
||||
onPointerEnter={() => props.onActiveCountryChange(country.country)}
|
||||
onFocus={() => props.onActiveCountryChange(country.country)}
|
||||
>
|
||||
<span>{String(country.rank).padStart(2, "0")}</span>
|
||||
<i />
|
||||
<strong>{formatCountryName(country.country)}</strong>
|
||||
<em>{formatGeoTokens(country.tokens)}</em>
|
||||
<b>{formatGeoShare(country.share)}</b>
|
||||
</button>
|
||||
</li>
|
||||
)}
|
||||
</For>
|
||||
</ol>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelPeersSection(props: { data: StatsModelData | null }) {
|
||||
return (
|
||||
<section id="peers" data-section="model-panel">
|
||||
<SectionTitle title="Peers" description="Nearby models by recent token volume." />
|
||||
<Show
|
||||
when={props.data?.peers.length}
|
||||
fallback={<ModelEmptyState title="No peers" description="Peer rankings appear after usage lands." />}
|
||||
>
|
||||
<ol data-component="model-peer-list">
|
||||
<For each={props.data?.peers ?? []}>
|
||||
{(peer) => <PeerRow peer={peer} active={peer.model === props.data?.model} />}
|
||||
</For>
|
||||
</ol>
|
||||
</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function MetricCard(props: { label: string; value: string; detail: string; state?: "positive" | "negative" }) {
|
||||
return (
|
||||
<article data-component="model-metric" data-state={props.state}>
|
||||
<span>{props.label}</span>
|
||||
<strong>{props.value}</strong>
|
||||
<p>{props.detail}</p>
|
||||
</article>
|
||||
)
|
||||
}
|
||||
|
||||
function PeerRow(props: { peer: ModelPeerEntry; active: boolean }) {
|
||||
return (
|
||||
<li>
|
||||
<a
|
||||
href={`${import.meta.env.BASE_URL}${providerSlug(props.peer.provider)}/${props.peer.slug}`}
|
||||
data-active={props.active ? "true" : undefined}
|
||||
>
|
||||
<span>{String(props.peer.rank).padStart(2, "0")}</span>
|
||||
<ProviderIcon aria-hidden="true" id={getProviderIconId(props.peer.author)} />
|
||||
<strong>{props.peer.model}</strong>
|
||||
<em>{props.peer.author}</em>
|
||||
<b>{formatTokens(props.peer.tokens)}</b>
|
||||
</a>
|
||||
</li>
|
||||
)
|
||||
}
|
||||
|
||||
function SectionTitle(props: { title: string; description: string }) {
|
||||
return (
|
||||
<p data-slot="section-title">
|
||||
<strong>{props.title}.</strong> <span>{props.description}</span>
|
||||
</p>
|
||||
)
|
||||
}
|
||||
|
||||
function ModelEmptyState(props: { title: string; description: string; compact?: boolean }) {
|
||||
return (
|
||||
<div data-component="empty-state" data-compact={props.compact ? "true" : undefined}>
|
||||
<strong>{props.title}</strong>
|
||||
<p>{props.description}</p>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
function getProviderIconId(author: string) {
|
||||
if (author === "MiniMax") return "minimax"
|
||||
if (author === "Moonshot") return "moonshotai"
|
||||
if (author === "Zhipu") return "zhipuai"
|
||||
return author.toLowerCase().replace(/[^a-z0-9]+/g, "")
|
||||
}
|
||||
|
||||
function emptyCountryRecord(): Record<UsageRange, CountryEntry[]> {
|
||||
return {
|
||||
"1D": [],
|
||||
"1W": [],
|
||||
"2W": [],
|
||||
"1M": [],
|
||||
"2M": [],
|
||||
"3M": [],
|
||||
YTD: [],
|
||||
ALL: [],
|
||||
}
|
||||
}
|
||||
|
||||
function countryNumericId(country: string) {
|
||||
return countryNumericIds.get(country.toUpperCase())?.padStart(3, "0")
|
||||
}
|
||||
|
||||
function formatCountryName(country: string) {
|
||||
const code = country.toUpperCase()
|
||||
if (code === "ZZ") return "Unknown"
|
||||
if (!countryNumericId(code)) return code
|
||||
return countryDisplayNames.of(code) ?? code
|
||||
}
|
||||
|
||||
function formatGeoTokens(value: number) {
|
||||
return formatTokens(value * 1_000_000_000_000)
|
||||
}
|
||||
|
||||
function formatGeoShare(value: number) {
|
||||
return `${value.toFixed(value > 0 && value < 1 ? 1 : 0)}%`
|
||||
}
|
||||
|
||||
function modelUsageHeight(tokens: number, max: number) {
|
||||
if (tokens <= 0) return 0
|
||||
return Math.max(2, Math.min(100, (tokens / max) * 100))
|
||||
}
|
||||
|
||||
function isModelUsageDense(count: number) {
|
||||
return count > 20
|
||||
}
|
||||
|
||||
function isModelUsageLabelHidden(index: number, count: number) {
|
||||
if (count <= 16) return false
|
||||
const interval = Math.ceil(count / 8)
|
||||
return index !== count - 1 && index % interval !== 0
|
||||
}
|
||||
|
||||
function formatRankMove(previousRank: number, rank: number) {
|
||||
const change = previousRank - rank
|
||||
if (change > 0) return `+${change}`
|
||||
if (change < 0) return `${change}`
|
||||
return "Even"
|
||||
}
|
||||
|
||||
function formatRankMoveLabel(previousRank: number | null, rank: number) {
|
||||
return previousRank === null ? "New in window" : `${formatRankMove(previousRank, rank)} vs previous window`
|
||||
}
|
||||
|
||||
function formatTokens(value: number) {
|
||||
if (value >= 1_000_000_000_000)
|
||||
return `${trimNumber(value / 1_000_000_000_000, value >= 10_000_000_000_000 ? 0 : 1)}T`
|
||||
if (value >= 1_000_000_000) return `${trimNumber(value / 1_000_000_000, value >= 10_000_000_000 ? 0 : 1)}B`
|
||||
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 String(Math.round(value))
|
||||
}
|
||||
|
||||
function formatInteger(value: number) {
|
||||
return new Intl.NumberFormat("en").format(value)
|
||||
}
|
||||
|
||||
function formatPercent(value: number) {
|
||||
return `${value.toFixed(value > 0 && value < 10 ? 1 : 0)}%`
|
||||
}
|
||||
|
||||
function formatMoney(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 `$${value.toFixed(value >= 10 ? 0 : 2)}`
|
||||
}
|
||||
|
||||
function formatSessionCost(value: number) {
|
||||
return `$${value.toFixed(value > 0 && value < 0.01 ? 4 : 2)}`
|
||||
}
|
||||
|
||||
function formatChange(value: number) {
|
||||
if (value > 0) return `+${value}%`
|
||||
return `${value}%`
|
||||
}
|
||||
|
||||
function formatCatalogLimit(value: number | undefined) {
|
||||
return value === undefined ? "Unknown" : formatTokens(value)
|
||||
}
|
||||
|
||||
function formatCatalogModalities(value: string[]) {
|
||||
if (value.length === 0) return "Unknown"
|
||||
return value.map(formatCatalogModality).join(", ")
|
||||
}
|
||||
|
||||
function formatCatalogModality(value: string) {
|
||||
if (value === "pdf") return "PDF"
|
||||
return value.charAt(0).toUpperCase() + value.slice(1)
|
||||
}
|
||||
|
||||
function formatCatalogDate(value: string | undefined) {
|
||||
if (!value) return "Unknown"
|
||||
const match = /^(\d{4})(?:-(\d{2}))?(?:-(\d{2}))?$/.exec(value)
|
||||
if (!match) return value
|
||||
const year = Number(match[1])
|
||||
const month = match[2] ? Number(match[2]) - 1 : 0
|
||||
const day = match[3] ? Number(match[3]) : 1
|
||||
return new Intl.DateTimeFormat("en", {
|
||||
month: match[2] ? "short" : undefined,
|
||||
day: match[3] ? "numeric" : undefined,
|
||||
year: "numeric",
|
||||
timeZone: "UTC",
|
||||
}).format(new Date(Date.UTC(year, month, day)))
|
||||
}
|
||||
|
||||
function trimNumber(value: number, digits: number) {
|
||||
return Number(value.toFixed(digits)).toLocaleString("en")
|
||||
}
|
||||
|
||||
function providerSlug(provider: string) {
|
||||
return provider
|
||||
.trim()
|
||||
.toLowerCase()
|
||||
.replace(/[^a-z0-9]+/g, "-")
|
||||
.replace(/^-+|-+$/g, "")
|
||||
.replace(/-{2,}/g, "-")
|
||||
}
|
||||
432
packages/stats/app/src/routes/[lab]/index.tsx
Normal file
432
packages/stats/app/src/routes/[lab]/index.tsx
Normal file
@@ -0,0 +1,432 @@
|
||||
import "../index.css"
|
||||
import { Link, Meta, Title } from "@solidjs/meta"
|
||||
import {
|
||||
getStatsLabData,
|
||||
type LabUsageModelEntry,
|
||||
type ModelUsagePoint,
|
||||
type StatsLabData,
|
||||
} from "@opencode-ai/stats-core/domain/home"
|
||||
import { runtime } from "@opencode-ai/stats-core/runtime"
|
||||
import { createAsync, query, useParams } from "@solidjs/router"
|
||||
import { createMemo, createSignal, For, onMount, Show, type JSX } from "solid-js"
|
||||
import { getRequestEvent } from "solid-js/web"
|
||||
import {
|
||||
findModelCatalogLab,
|
||||
formatCatalogLabName,
|
||||
getModelCatalog,
|
||||
type ModelCatalogEntry,
|
||||
type ModelCatalogLab,
|
||||
} from "../model-catalog"
|
||||
import {
|
||||
applyThemePreference,
|
||||
Footer,
|
||||
getGitHubStars,
|
||||
Header,
|
||||
isThemePreference,
|
||||
themeStorageKey,
|
||||
type HeaderLink,
|
||||
type ThemePreference,
|
||||
} from "../stats-shell"
|
||||
|
||||
const statsCanonicalBaseUrl = "https://opencode.ai/data/"
|
||||
const statsUnfurlPath = "banner.png"
|
||||
const statsUnfurlAlt = "OpenCode Data wordmark on a dark patterned background"
|
||||
const statsUnfurlUrl = new URL(statsUnfurlPath, statsCanonicalBaseUrl).toString()
|
||||
const labHeaderLinks: readonly HeaderLink[] = [
|
||||
{ href: "#overview", label: "Overview" },
|
||||
{ href: "#usage", label: "Usage" },
|
||||
{ href: "#models", label: "Models" },
|
||||
]
|
||||
const labFooterLinks: readonly HeaderLink[] = [
|
||||
{ href: import.meta.env.BASE_URL, label: "Data Home" },
|
||||
{ href: `${import.meta.env.BASE_URL}#top-models`, label: "Top Models" },
|
||||
{ href: `${import.meta.env.BASE_URL}#market-share`, label: "Market Share" },
|
||||
{ href: `${import.meta.env.BASE_URL}#geo-breakdown`, label: "Geo Breakdown" },
|
||||
]
|
||||
|
||||
const getLabData = query(async (lab: string) => {
|
||||
"use server"
|
||||
return runtime.runPromise(getStatsLabData(lab))
|
||||
}, "getStatsLabData")
|
||||
|
||||
export default function StatsLab() {
|
||||
const event = getRequestEvent()
|
||||
event?.response.headers.set("Cache-Control", "public, max-age=60, s-maxage=300, stale-while-revalidate=86400")
|
||||
const params = useParams()
|
||||
const labParam = createMemo(() => params.lab ?? "")
|
||||
const catalog = createAsync(() => getModelCatalog())
|
||||
const lab = createMemo(() => {
|
||||
const data = catalog()
|
||||
if (!data) return undefined
|
||||
return findModelCatalogLab(data, labParam()) ?? null
|
||||
})
|
||||
const stats = createAsync(() => {
|
||||
const entry = lab()
|
||||
if (catalog() === undefined || entry === undefined) return Promise.resolve(undefined)
|
||||
if (!entry) return Promise.resolve(null)
|
||||
return getLabData(entry.id)
|
||||
})
|
||||
const githubStars = createAsync(() => getGitHubStars())
|
||||
const [themePreference, setThemePreference] = createSignal<ThemePreference>("system")
|
||||
const labName = createMemo(() => lab()?.name ?? formatCatalogLabName(labParam()))
|
||||
const labTitle = createMemo(() => `${labName()} Models`)
|
||||
const labDescription = createMemo(
|
||||
() =>
|
||||
`Explore ${labName()} models used in OpenCode, with recent token usage, context windows, release dates, and model-specific data.`,
|
||||
)
|
||||
const labUrl = createMemo(() => new URL(lab()?.id ?? labParam(), statsCanonicalBaseUrl).toString())
|
||||
const updateThemePreference = (preference: ThemePreference) => {
|
||||
applyThemePreference(preference)
|
||||
setThemePreference(preference)
|
||||
if (typeof window === "undefined") return
|
||||
window.localStorage.setItem(themeStorageKey, preference)
|
||||
}
|
||||
|
||||
onMount(() => {
|
||||
if (typeof window === "undefined") return
|
||||
const preference = window.localStorage.getItem(themeStorageKey)
|
||||
const nextPreference = isThemePreference(preference) ? preference : "system"
|
||||
applyThemePreference(nextPreference)
|
||||
setThemePreference(nextPreference)
|
||||
})
|
||||
|
||||
return (
|
||||
<main data-page="stats" data-theme={themePreference()}>
|
||||
<Title>{labTitle()}</Title>
|
||||
<Meta name="description" content={labDescription()} />
|
||||
<Link rel="canonical" href={labUrl()} />
|
||||
<Meta property="og:type" content="website" />
|
||||
<Meta property="og:site_name" content="OpenCode" />
|
||||
<Meta property="og:title" content={labTitle()} />
|
||||
<Meta property="og:description" content={labDescription()} />
|
||||
<Meta property="og:url" content={labUrl()} />
|
||||
<Meta property="og:image" content={statsUnfurlUrl} />
|
||||
<Meta property="og:image:type" content="image/png" />
|
||||
<Meta property="og:image:width" content="1200" />
|
||||
<Meta property="og:image:height" content="630" />
|
||||
<Meta property="og:image:alt" content={statsUnfurlAlt} />
|
||||
<Meta name="twitter:card" content="summary_large_image" />
|
||||
<Meta name="twitter:title" content={labTitle()} />
|
||||
<Meta name="twitter:description" content={labDescription()} />
|
||||
<Meta name="twitter:image" content={statsUnfurlUrl} />
|
||||
<Meta name="twitter:image:alt" content={statsUnfurlAlt} />
|
||||
<Header githubStars={githubStars() ?? "150K"} links={labHeaderLinks} brandHref={import.meta.env.BASE_URL} />
|
||||
<div data-component="container">
|
||||
<div data-component="content">
|
||||
<Show when={catalog() !== undefined} fallback={<LabLoading />}>
|
||||
<Show when={lab()} fallback={<LabNotFound lab={labParam()} />}>
|
||||
{(data) => (
|
||||
<>
|
||||
<LabHero lab={data()} stats={stats() ?? null} />
|
||||
<LabUsageSection lab={data()} data={stats() ?? null} />
|
||||
<LabModelsSection lab={data()} usage={stats()?.models ?? []} />
|
||||
</>
|
||||
)}
|
||||
</Show>
|
||||
</Show>
|
||||
</div>
|
||||
<Footer
|
||||
themePreference={themePreference()}
|
||||
onThemePreferenceChange={updateThemePreference}
|
||||
links={labFooterLinks}
|
||||
/>
|
||||
</div>
|
||||
</main>
|
||||
)
|
||||
}
|
||||
|
||||
function LabLoading() {
|
||||
return (
|
||||
<section id="overview" data-section="lab-hero">
|
||||
<div data-slot="model-hero-grid">
|
||||
<div data-slot="model-hero-copy">
|
||||
<a data-slot="model-back-link" href={import.meta.env.BASE_URL}>
|
||||
Data
|
||||
</a>
|
||||
<h1>Model Lab</h1>
|
||||
<p>Reading model availability and recent OpenCode usage.</p>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function LabNotFound(props: { lab: string }) {
|
||||
return (
|
||||
<section id="overview" data-section="lab-hero">
|
||||
<div data-slot="model-hero-grid">
|
||||
<div data-slot="model-hero-copy">
|
||||
<a data-slot="model-back-link" href={import.meta.env.BASE_URL}>
|
||||
Data
|
||||
</a>
|
||||
<h1>{formatCatalogLabName(props.lab)}</h1>
|
||||
<p>No models matched this lab.</p>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function LabHero(props: { lab: ModelCatalogLab; stats: StatsLabData | null }) {
|
||||
const latest = createMemo(
|
||||
() =>
|
||||
props.lab.models
|
||||
.map((model) => model.releaseDate)
|
||||
.filter((value): value is string => value !== undefined)
|
||||
.toSorted((a, b) => new Date(b).getTime() - new Date(a).getTime())[0],
|
||||
)
|
||||
const featuredModels = createMemo(() => props.lab.models.slice(0, 3).map((model) => model.name))
|
||||
|
||||
return (
|
||||
<section id="overview" data-section="lab-hero">
|
||||
<a data-slot="model-back-link" href={import.meta.env.BASE_URL}>
|
||||
Data
|
||||
</a>
|
||||
<div data-slot="model-hero-grid">
|
||||
<div data-slot="model-hero-copy">
|
||||
<h1>{props.lab.name}</h1>
|
||||
<div data-slot="model-hero-pattern" aria-hidden="true" />
|
||||
<p>
|
||||
Explore {props.lab.models.length} {props.lab.name} models used in OpenCode
|
||||
<Show when={featuredModels().length > 0}> including {formatList(featuredModels())}</Show>. Compare recent
|
||||
token usage, context windows, release dates, and model-specific data.
|
||||
</p>
|
||||
</div>
|
||||
<div data-component="model-rank-panel">
|
||||
<span>Tokens Processed</span>
|
||||
<strong>{props.stats ? formatTokens(props.stats.totals.tokens) : "Pending"}</strong>
|
||||
<p>
|
||||
{props.stats
|
||||
? `${formatPercent(props.stats.tokenShare)} of recent OpenCode usage`
|
||||
: latest()
|
||||
? `Latest release ${formatCatalogDate(latest())}`
|
||||
: "Usage appears after model activity lands"}
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function LabUsageSection(props: { lab: ModelCatalogLab; data: StatsLabData | null }) {
|
||||
const [activeIndex, setActiveIndex] = createSignal<number>()
|
||||
const usage = createMemo(() => props.data?.usage ?? [])
|
||||
const max = createMemo(() => Math.max(0, ...usage().map((item) => item.tokens)) || 1)
|
||||
const activePoint = createMemo(() => {
|
||||
const index = activeIndex()
|
||||
if (index === undefined) return undefined
|
||||
return usage()[index]
|
||||
})
|
||||
|
||||
return (
|
||||
<section id="usage" data-section="model-panel">
|
||||
<p data-slot="section-title">
|
||||
<strong>{props.lab.name} token usage.</strong>{" "}
|
||||
<span>Daily OpenCode token volume over the last two months.</span>
|
||||
</p>
|
||||
<Show
|
||||
when={usage().some((item) => item.tokens > 0)}
|
||||
fallback={
|
||||
<LabEmptyState
|
||||
title="No usage yet"
|
||||
description="Recent token usage appears here once this lab has activity."
|
||||
/>
|
||||
}
|
||||
>
|
||||
<div
|
||||
data-component="model-usage-chart"
|
||||
data-dense-labels={isLabUsageDense(usage().length) ? "true" : undefined}
|
||||
role="img"
|
||||
aria-label={`${props.lab.name} daily token usage chart`}
|
||||
style={{ "--model-usage-count": usage().length } as JSX.CSSProperties}
|
||||
onPointerLeave={(event) => {
|
||||
if (event.pointerType === "touch") return
|
||||
setActiveIndex(undefined)
|
||||
}}
|
||||
>
|
||||
<div data-slot="model-usage-axis" aria-hidden="true">
|
||||
<For each={usage()}>
|
||||
{(point, index) => (
|
||||
<div
|
||||
data-active={activeIndex() === index() ? "true" : undefined}
|
||||
data-label-hidden={isLabUsageLabelHidden(index(), usage().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={usage()}>
|
||||
{(point, index) => (
|
||||
<div
|
||||
data-slot="model-usage-column"
|
||||
role="button"
|
||||
tabIndex={0}
|
||||
aria-label={`${point.date} ${formatTokens(point.tokens)} tokens`}
|
||||
data-active={activeIndex() === index() ? "true" : undefined}
|
||||
data-muted={activeIndex() !== undefined && activeIndex() !== index() ? "true" : undefined}
|
||||
onPointerDown={(event) => {
|
||||
if (event.pointerType !== "touch") return
|
||||
setActiveIndex(index())
|
||||
}}
|
||||
onPointerEnter={() => setActiveIndex(index())}
|
||||
onPointerMove={(event) => {
|
||||
if (event.pointerType === "touch") return
|
||||
setActiveIndex(index())
|
||||
}}
|
||||
onClick={() => setActiveIndex(index())}
|
||||
onFocus={() => setActiveIndex(index())}
|
||||
onBlur={() => setActiveIndex(undefined)}
|
||||
onKeyDown={(event) => {
|
||||
if (event.key !== "Enter" && event.key !== " ") return
|
||||
event.preventDefault()
|
||||
setActiveIndex(index())
|
||||
}}
|
||||
>
|
||||
<div
|
||||
data-slot="model-usage-bar"
|
||||
style={{ "--model-usage-fill": `${usageHeight(point.tokens, max())}%` } as JSX.CSSProperties}
|
||||
/>
|
||||
<Show when={activeIndex() === index() && activePoint()}>
|
||||
{(active) => (
|
||||
<div
|
||||
data-component="chart-tooltip"
|
||||
data-placement={index() > usage().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>
|
||||
</Show>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function LabModelsSection(props: { lab: ModelCatalogLab; usage: LabUsageModelEntry[] }) {
|
||||
const usageBySlug = createMemo(() => new Map(props.usage.map((item) => [item.slug, item])))
|
||||
return (
|
||||
<section id="models" data-section="model-panel">
|
||||
<p data-slot="section-title">
|
||||
<strong>{props.lab.name} models.</strong> <span>Recent usage and limits.</span>
|
||||
</p>
|
||||
<div data-component="lab-model-grid">
|
||||
<For each={props.lab.models}>
|
||||
{(model) => <LabModelCard model={model} usage={usageBySlug().get(model.slug)} />}
|
||||
</For>
|
||||
</div>
|
||||
</section>
|
||||
)
|
||||
}
|
||||
|
||||
function LabModelCard(props: { model: ModelCatalogEntry; usage: LabUsageModelEntry | undefined }) {
|
||||
return (
|
||||
<a data-component="lab-model-card" href={`${import.meta.env.BASE_URL}${props.model.id}`}>
|
||||
<strong>{props.model.name}</strong>
|
||||
<div data-slot="lab-model-card-meta">
|
||||
<p>
|
||||
<b>Usage</b>
|
||||
<em>{props.usage ? formatTokens(props.usage.tokens) : "—"}</em>
|
||||
</p>
|
||||
<p>
|
||||
<b>Share</b>
|
||||
<em>{props.usage ? formatPercent(props.usage.share) : "—"}</em>
|
||||
</p>
|
||||
<p>
|
||||
<b>Context</b>
|
||||
<em>{formatCatalogLimit(props.model.limit?.context)}</em>
|
||||
</p>
|
||||
<p>
|
||||
<b>Output</b>
|
||||
<em>{formatCatalogLimit(props.model.limit?.output)}</em>
|
||||
</p>
|
||||
<p>
|
||||
<b>Release</b>
|
||||
<em>{formatCatalogDate(props.model.releaseDate)}</em>
|
||||
</p>
|
||||
</div>
|
||||
</a>
|
||||
)
|
||||
}
|
||||
|
||||
function LabEmptyState(props: { title: string; description: string }) {
|
||||
return (
|
||||
<div data-component="empty-state" data-compact="true">
|
||||
<strong>{props.title}</strong>
|
||||
<p>{props.description}</p>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
function formatCatalogLimit(value: number | undefined) {
|
||||
return value === undefined ? "Unknown" : formatTokens(value)
|
||||
}
|
||||
|
||||
function formatCatalogDate(value: string | undefined) {
|
||||
if (!value) return "Unknown"
|
||||
const match = /^(\d{4})(?:-(\d{2}))?(?:-(\d{2}))?$/.exec(value)
|
||||
if (!match) return value
|
||||
const year = Number(match[1])
|
||||
const month = match[2] ? Number(match[2]) - 1 : 0
|
||||
const day = match[3] ? Number(match[3]) : 1
|
||||
return new Intl.DateTimeFormat("en", {
|
||||
month: match[2] ? "short" : undefined,
|
||||
day: match[3] ? "numeric" : undefined,
|
||||
year: "numeric",
|
||||
timeZone: "UTC",
|
||||
}).format(new Date(Date.UTC(year, month, day)))
|
||||
}
|
||||
|
||||
function formatList(values: string[]) {
|
||||
if (values.length <= 1) return values[0] ?? ""
|
||||
if (values.length === 2) return `${values[0]} and ${values[1]}`
|
||||
return `${values.slice(0, -1).join(", ")}, and ${values[values.length - 1]}`
|
||||
}
|
||||
|
||||
function formatPercent(value: number) {
|
||||
return `${trimNumber(value, value >= 10 ? 1 : 2)}%`
|
||||
}
|
||||
|
||||
function formatTokens(value: number) {
|
||||
if (value >= 1_000_000_000_000)
|
||||
return `${trimNumber(value / 1_000_000_000_000, value >= 10_000_000_000_000 ? 0 : 1)}T`
|
||||
if (value >= 1_000_000_000) return `${trimNumber(value / 1_000_000_000, value >= 10_000_000_000 ? 0 : 1)}B`
|
||||
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 String(Math.round(value))
|
||||
}
|
||||
|
||||
function trimNumber(value: number, digits: number) {
|
||||
return Number(value.toFixed(digits)).toLocaleString("en")
|
||||
}
|
||||
|
||||
function usageHeight(value: number, max: number) {
|
||||
if (value <= 0 || max <= 0) return 0
|
||||
return Math.max(4, (value / max) * 100)
|
||||
}
|
||||
|
||||
function isLabUsageDense(count: number) {
|
||||
return count > 20
|
||||
}
|
||||
|
||||
function isLabUsageLabelHidden(index: number, count: number) {
|
||||
if (count <= 14) return false
|
||||
const cadence = count > 45 ? 7 : count > 28 ? 4 : 2
|
||||
return index % cadence !== 0 && index !== count - 1
|
||||
}
|
||||
19
packages/stats/app/src/routes/api/health.ts
Normal file
19
packages/stats/app/src/routes/api/health.ts
Normal file
@@ -0,0 +1,19 @@
|
||||
import { AppConfig } from "@opencode-ai/stats-core/config"
|
||||
import { runtime } from "@opencode-ai/stats-core/runtime"
|
||||
import { Effect } from "effect"
|
||||
|
||||
export async function GET() {
|
||||
return Response.json(
|
||||
await runtime.runPromise(
|
||||
Effect.gen(function* () {
|
||||
const config = yield* AppConfig
|
||||
return {
|
||||
ok: true,
|
||||
app: "stats",
|
||||
stage: config.stage,
|
||||
publicUrl: config.publicUrl,
|
||||
}
|
||||
}),
|
||||
),
|
||||
)
|
||||
}
|
||||
29
packages/stats/app/src/routes/api/newsletter.ts
Normal file
29
packages/stats/app/src/routes/api/newsletter.ts
Normal file
@@ -0,0 +1,29 @@
|
||||
import { Resource } from "sst/resource"
|
||||
|
||||
const listId = "8b9bb82c-9d5f-11f0-975f-0df6fd1e4945"
|
||||
|
||||
export async function POST(event: { request: Request }) {
|
||||
const contentType = event.request.headers.get("content-type") ?? ""
|
||||
if (!contentType.includes("multipart/form-data") && !contentType.includes("application/x-www-form-urlencoded")) {
|
||||
return Response.json({ error: "Email address is required" }, { status: 400 })
|
||||
}
|
||||
|
||||
const form = await event.request.formData()
|
||||
const emailAddress = form.get("email")
|
||||
if (typeof emailAddress !== "string" || emailAddress.trim().length === 0) {
|
||||
return Response.json({ error: "Email address is required" }, { status: 400 })
|
||||
}
|
||||
|
||||
const response = await fetch(`https://api.emailoctopus.com/lists/${listId}/contacts`, {
|
||||
method: "PUT",
|
||||
headers: {
|
||||
Authorization: `Bearer ${Resource.EMAILOCTOPUS_API_KEY.value}`,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
body: JSON.stringify({
|
||||
email_address: emailAddress.trim(),
|
||||
}),
|
||||
})
|
||||
if (!response.ok) return Response.json({ error: "Failed to subscribe" }, { status: 502 })
|
||||
return Response.json({ success: true })
|
||||
}
|
||||
4041
packages/stats/app/src/routes/index.css
Normal file
4041
packages/stats/app/src/routes/index.css
Normal file
File diff suppressed because it is too large
Load Diff
1774
packages/stats/app/src/routes/index.tsx
Normal file
1774
packages/stats/app/src/routes/index.tsx
Normal file
File diff suppressed because it is too large
Load Diff
224
packages/stats/app/src/routes/model-catalog.ts
Normal file
224
packages/stats/app/src/routes/model-catalog.ts
Normal file
@@ -0,0 +1,224 @@
|
||||
import { query } from "@solidjs/router"
|
||||
|
||||
export const modelCatalogSourceUrl = "https://models.dev/models.json"
|
||||
|
||||
export type ModelCatalogEntry = {
|
||||
id: string
|
||||
lab: string
|
||||
slug: string
|
||||
name: string
|
||||
family?: string
|
||||
knowledge?: string
|
||||
releaseDate?: string
|
||||
lastUpdated?: string
|
||||
limit?: { context?: number; output?: number }
|
||||
modalities: { input: string[]; output: string[] }
|
||||
openWeights: boolean
|
||||
reasoning: boolean
|
||||
toolCall: boolean
|
||||
attachment: boolean
|
||||
temperature: boolean
|
||||
weights: { label: string; url: string }[]
|
||||
benchmarks: ModelCatalogBenchmark[]
|
||||
}
|
||||
|
||||
export type ModelCatalogBenchmark = {
|
||||
name: string
|
||||
score: number
|
||||
metric?: string
|
||||
harness?: string
|
||||
variant?: string
|
||||
dataset?: string
|
||||
version?: string
|
||||
source?: string
|
||||
}
|
||||
|
||||
export type ModelCatalogLab = {
|
||||
id: string
|
||||
name: string
|
||||
models: ModelCatalogEntry[]
|
||||
}
|
||||
|
||||
export type ModelCatalog = {
|
||||
models: ModelCatalogEntry[]
|
||||
labs: ModelCatalogLab[]
|
||||
}
|
||||
|
||||
export const getModelCatalog = query(async () => {
|
||||
"use server"
|
||||
const payload = await fetch(modelCatalogSourceUrl)
|
||||
.then((response): Promise<unknown> => (response.ok ? (response.json() as Promise<unknown>) : Promise.resolve()))
|
||||
.catch(() => undefined)
|
||||
return buildModelCatalog(payload)
|
||||
}, "getModelCatalog")
|
||||
|
||||
export function findModelCatalogEntry(catalog: ModelCatalog, model: string, lab?: string) {
|
||||
const normalizedId = lab ? `${catalogSlug(lab)}/${catalogSlug(model)}` : model.trim().toLowerCase()
|
||||
const leaf = catalogSlug(model)
|
||||
return (
|
||||
catalog.models.find((entry) => entry.id.toLowerCase() === normalizedId) ??
|
||||
catalog.models.find((entry) => (lab ? entry.lab === catalogSlug(lab) : true) && entry.slug === leaf) ??
|
||||
catalog.models.find((entry) => entry.slug === leaf)
|
||||
)
|
||||
}
|
||||
|
||||
export function findModelCatalogLab(catalog: ModelCatalog, lab: string) {
|
||||
const id = catalogSlug(lab)
|
||||
return catalog.labs.find((entry) => entry.id === id)
|
||||
}
|
||||
|
||||
export function formatCatalogLabName(lab: string) {
|
||||
const known: Record<string, string> = {
|
||||
alibaba: "Alibaba",
|
||||
anthropic: "Anthropic",
|
||||
cohere: "Cohere",
|
||||
deepseek: "DeepSeek",
|
||||
google: "Google",
|
||||
meta: "Meta",
|
||||
minimax: "MiniMax",
|
||||
mistral: "Mistral",
|
||||
moonshotai: "Moonshot",
|
||||
openai: "OpenAI",
|
||||
perplexity: "Perplexity",
|
||||
stepfun: "StepFun",
|
||||
tencent: "Tencent",
|
||||
xai: "xAI",
|
||||
xiaomi: "Xiaomi",
|
||||
zai: "Z.ai",
|
||||
zhipuai: "Zhipu",
|
||||
}
|
||||
return known[catalogSlug(lab)] ?? lab.replace(/[-_]/g, " ").replace(/\b\w/g, (letter) => letter.toUpperCase())
|
||||
}
|
||||
|
||||
export function catalogSlug(value: string) {
|
||||
return value
|
||||
.trim()
|
||||
.toLowerCase()
|
||||
.replace(/[^a-z0-9]+/g, "-")
|
||||
.replace(/^-+|-+$/g, "")
|
||||
.replace(/-{2,}/g, "-")
|
||||
}
|
||||
|
||||
function buildModelCatalog(payload: unknown): ModelCatalog {
|
||||
const models = (Array.isArray(payload) ? payload : isRecord(payload) ? Object.values(payload) : [])
|
||||
.flatMap(readModelCatalogEntry)
|
||||
.toSorted((a, b) => a.lab.localeCompare(b.lab) || displayDateTime(b.releaseDate) - displayDateTime(a.releaseDate))
|
||||
return {
|
||||
models,
|
||||
labs: Object.values(
|
||||
models.reduce<Record<string, ModelCatalogLab>>((result, model) => {
|
||||
result[model.lab] = {
|
||||
id: model.lab,
|
||||
name: formatCatalogLabName(model.lab),
|
||||
models: [...(result[model.lab]?.models ?? []), model],
|
||||
}
|
||||
return result
|
||||
}, {}),
|
||||
).toSorted((a, b) => a.name.localeCompare(b.name)),
|
||||
}
|
||||
}
|
||||
|
||||
function readModelCatalogEntry(value: unknown): ModelCatalogEntry[] {
|
||||
if (!isRecord(value)) return []
|
||||
const id = stringValue(value.id)
|
||||
const name = stringValue(value.name)
|
||||
const lab = id?.split("/")[0]
|
||||
const slug = id?.split("/").slice(1).join("/")
|
||||
if (!id || !name || !lab || !slug) return []
|
||||
return [
|
||||
{
|
||||
id,
|
||||
lab: catalogSlug(lab),
|
||||
slug: catalogSlug(slug),
|
||||
name,
|
||||
family: stringValue(value.family),
|
||||
knowledge: stringValue(value.knowledge),
|
||||
releaseDate: stringValue(value.release_date),
|
||||
lastUpdated: stringValue(value.last_updated),
|
||||
limit: readCatalogLimit(value.limit),
|
||||
modalities: readCatalogModalities(value.modalities),
|
||||
openWeights: booleanValue(value.open_weights),
|
||||
reasoning: booleanValue(value.reasoning),
|
||||
toolCall: booleanValue(value.tool_call),
|
||||
attachment: booleanValue(value.attachment),
|
||||
temperature: booleanValue(value.temperature),
|
||||
weights: readCatalogWeights(value.weights),
|
||||
benchmarks: readCatalogBenchmarks(value.benchmarks),
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function readCatalogLimit(value: unknown) {
|
||||
if (!isRecord(value)) return undefined
|
||||
return {
|
||||
context: numberValue(value.context),
|
||||
output: numberValue(value.output),
|
||||
}
|
||||
}
|
||||
|
||||
function readCatalogModalities(value: unknown) {
|
||||
if (!isRecord(value)) return { input: [], output: [] }
|
||||
return {
|
||||
input: stringArrayValue(value.input),
|
||||
output: stringArrayValue(value.output),
|
||||
}
|
||||
}
|
||||
|
||||
function readCatalogWeights(value: unknown) {
|
||||
if (!Array.isArray(value)) return []
|
||||
return value.flatMap((item) => {
|
||||
if (!isRecord(item)) return []
|
||||
const label = stringValue(item.label)
|
||||
const url = stringValue(item.url)
|
||||
return label && url ? [{ label, url }] : []
|
||||
})
|
||||
}
|
||||
|
||||
function readCatalogBenchmarks(value: unknown) {
|
||||
if (!Array.isArray(value)) return []
|
||||
return value.flatMap((item) => {
|
||||
if (!isRecord(item)) return []
|
||||
const name = stringValue(item.name)
|
||||
const score = numberValue(item.score)
|
||||
return name && score !== undefined
|
||||
? [
|
||||
{
|
||||
name,
|
||||
score,
|
||||
metric: stringValue(item.metric),
|
||||
harness: stringValue(item.harness),
|
||||
variant: stringValue(item.variant),
|
||||
dataset: stringValue(item.dataset),
|
||||
version: stringValue(item.version),
|
||||
source: stringValue(item.source),
|
||||
},
|
||||
]
|
||||
: []
|
||||
})
|
||||
}
|
||||
|
||||
function displayDateTime(value: string | undefined) {
|
||||
return value ? new Date(value).getTime() || 0 : 0
|
||||
}
|
||||
|
||||
function isRecord(value: unknown): value is Record<string, unknown> {
|
||||
return typeof value === "object" && value !== null && !Array.isArray(value)
|
||||
}
|
||||
|
||||
function stringValue(value: unknown) {
|
||||
return typeof value === "string" && value.trim() ? value : undefined
|
||||
}
|
||||
|
||||
function numberValue(value: unknown) {
|
||||
return typeof value === "number" && Number.isFinite(value) ? value : undefined
|
||||
}
|
||||
|
||||
function booleanValue(value: unknown) {
|
||||
return value === true
|
||||
}
|
||||
|
||||
function stringArrayValue(value: unknown) {
|
||||
return Array.isArray(value)
|
||||
? value.filter((item): item is string => typeof item === "string" && item.trim() !== "")
|
||||
: []
|
||||
}
|
||||
476
packages/stats/app/src/routes/stats-shell.tsx
Normal file
476
packages/stats/app/src/routes/stats-shell.tsx
Normal file
@@ -0,0 +1,476 @@
|
||||
import opencodeWordmarkDark from "../asset/logo-ornate-dark.svg"
|
||||
import { query } from "@solidjs/router"
|
||||
import { createEffect, createMemo, createSignal, For, onCleanup, onMount, Show } from "solid-js"
|
||||
|
||||
export type HeaderLink = { href: string; label: string }
|
||||
|
||||
export const headerLinks = [
|
||||
{ href: "#top-models", label: "Top Models" },
|
||||
{ href: "#leaderboard", label: "Leaderboard" },
|
||||
{ href: "#session-cost", label: "Session Cost" },
|
||||
{ href: "#token-cost", label: "Token Cost" },
|
||||
{ href: "#cache-ratio", label: "Cache Ratio" },
|
||||
{ href: "#market-share", label: "Market Share" },
|
||||
{ href: "#geo-breakdown", label: "Geo Breakdown" },
|
||||
] as const
|
||||
export const githubLink = {
|
||||
href: "https://github.com/anomalyco/opencode",
|
||||
apiHref: "https://api.github.com/repos/anomalyco/opencode",
|
||||
label: "GitHub",
|
||||
fallbackStars: "150K",
|
||||
ariaLabel: "Star OpenCode on GitHub",
|
||||
}
|
||||
export const themePreferences = ["dark", "light", "system"] as const
|
||||
export const themeStorageKey = "opencode:stats-theme"
|
||||
export type ThemePreference = (typeof themePreferences)[number]
|
||||
|
||||
const compactNumberFormatter = new Intl.NumberFormat("en", {
|
||||
notation: "compact",
|
||||
maximumFractionDigits: 1,
|
||||
})
|
||||
const themePreferenceLabels = {
|
||||
dark: "Dark",
|
||||
light: "Light",
|
||||
system: "System",
|
||||
} as const
|
||||
|
||||
export const getGitHubStars = query(async () => {
|
||||
"use server"
|
||||
return fetch(githubLink.apiHref, {
|
||||
headers: {
|
||||
Accept: "application/vnd.github+json",
|
||||
"X-GitHub-Api-Version": "2022-11-28",
|
||||
},
|
||||
})
|
||||
.then((response) => (response.ok ? response.json() : undefined))
|
||||
.then((body: unknown) =>
|
||||
body && typeof body === "object" && "stargazers_count" in body && typeof body.stargazers_count === "number"
|
||||
? compactNumberFormatter.format(body.stargazers_count)
|
||||
: githubLink.fallbackStars,
|
||||
)
|
||||
.catch(() => githubLink.fallbackStars)
|
||||
}, "getGitHubStars")
|
||||
|
||||
export function isThemePreference(value: string | null): value is ThemePreference {
|
||||
return value === "dark" || value === "light" || value === "system"
|
||||
}
|
||||
|
||||
export function applyThemePreference(preference: ThemePreference) {
|
||||
if (typeof document === "undefined") return
|
||||
document.documentElement.dataset.statsTheme = preference
|
||||
if (preference === "system") {
|
||||
document.documentElement.style.removeProperty("color-scheme")
|
||||
return
|
||||
}
|
||||
document.documentElement.style.setProperty("color-scheme", preference)
|
||||
}
|
||||
|
||||
export function Header(props: { githubStars: string; links?: readonly HeaderLink[]; brandHref?: string }) {
|
||||
const [menuOpen, setMenuOpen] = createSignal(false)
|
||||
const [menuViewport, setMenuViewport] = createSignal(false)
|
||||
const links = createMemo(() => props.links ?? headerLinks)
|
||||
|
||||
createEffect(() => {
|
||||
if (typeof window === "undefined") return
|
||||
const media = window.matchMedia("(max-width: 74.999rem)")
|
||||
const update = () => setMenuViewport(media.matches)
|
||||
update()
|
||||
media.addEventListener("change", update)
|
||||
onCleanup(() => media.removeEventListener("change", update))
|
||||
})
|
||||
|
||||
createEffect(() => {
|
||||
if (!menuOpen()) return
|
||||
if (!menuViewport()) return
|
||||
if (typeof document === "undefined") return
|
||||
const page = document.querySelector<HTMLElement>('[data-page="stats"]')
|
||||
const scrollbarWidth = window.innerWidth - document.documentElement.clientWidth
|
||||
const htmlOverflow = document.documentElement.style.overflow
|
||||
const pagePaddingRight = page?.style.paddingRight
|
||||
const bodyOverflow = document.body.style.overflow
|
||||
document.documentElement.style.overflow = "hidden"
|
||||
if (scrollbarWidth > 0 && page) page.style.paddingRight = `${scrollbarWidth}px`
|
||||
document.body.style.overflow = "hidden"
|
||||
onCleanup(() => {
|
||||
document.documentElement.style.overflow = htmlOverflow
|
||||
if (page && pagePaddingRight !== undefined) page.style.paddingRight = pagePaddingRight
|
||||
document.body.style.overflow = bodyOverflow
|
||||
})
|
||||
})
|
||||
|
||||
return (
|
||||
<header data-component="top" data-menu-open={menuOpen() ? "true" : undefined}>
|
||||
<div data-slot="header-bar">
|
||||
<a data-slot="brand" href={props.brandHref ?? import.meta.env.BASE_URL} aria-label="Data home">
|
||||
<DataWordmark />
|
||||
</a>
|
||||
<nav data-component="section-nav" aria-label="Data sections">
|
||||
<ul>
|
||||
<For each={links()}>
|
||||
{(link) => (
|
||||
<li>
|
||||
<a href={link.href}>{link.label}</a>
|
||||
</li>
|
||||
)}
|
||||
</For>
|
||||
</ul>
|
||||
</nav>
|
||||
<div data-slot="header-actions">
|
||||
<a
|
||||
data-slot="header-button"
|
||||
data-variant="neutral"
|
||||
href={githubLink.href}
|
||||
target="_blank"
|
||||
rel="noreferrer"
|
||||
aria-label={`${githubLink.ariaLabel} (${props.githubStars} stars)`}
|
||||
>
|
||||
<strong>{githubLink.label}</strong>
|
||||
<span>[{props.githubStars}]</span>
|
||||
</a>
|
||||
<a data-slot="header-button" data-variant="contrast" href="https://opencode.ai/">
|
||||
<strong>Try OpenCode</strong>
|
||||
</a>
|
||||
<button
|
||||
data-slot="menu-button"
|
||||
type="button"
|
||||
aria-controls="stats-mobile-nav"
|
||||
aria-expanded={menuOpen() ? "true" : "false"}
|
||||
aria-label={menuOpen() ? "Close navigation" : "Open navigation"}
|
||||
onClick={() => setMenuOpen((value) => !value)}
|
||||
>
|
||||
<svg width="16" height="16" viewBox="0 0 16 16" fill="none" aria-hidden="true">
|
||||
<Show when={menuOpen()} fallback={<path d="M2 4.72H14M2 8.5H14M2 12.28H14" stroke="currentColor" />}>
|
||||
<path d="M4.44 4.44L11.56 11.56M11.56 4.44L4.44 11.56" stroke="currentColor" />
|
||||
</Show>
|
||||
</svg>
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
<nav id="stats-mobile-nav" data-slot="mobile-menu" aria-label="Data sections" hidden={!menuOpen()}>
|
||||
<a
|
||||
data-slot="mobile-menu-item"
|
||||
data-variant="github"
|
||||
href={githubLink.href}
|
||||
target="_blank"
|
||||
rel="noreferrer"
|
||||
aria-label={`${githubLink.ariaLabel} (${props.githubStars} stars)`}
|
||||
>
|
||||
<strong>{githubLink.label}</strong>
|
||||
<span>[{props.githubStars}]</span>
|
||||
</a>
|
||||
<For each={links()}>
|
||||
{(link) => (
|
||||
<a data-slot="mobile-menu-item" href={link.href} onClick={() => setMenuOpen(false)}>
|
||||
{link.label}
|
||||
</a>
|
||||
)}
|
||||
</For>
|
||||
</nav>
|
||||
</header>
|
||||
)
|
||||
}
|
||||
|
||||
function DataWordmark() {
|
||||
return (
|
||||
<svg data-slot="stats-wordmark" width="66" height="20" viewBox="0 0 66 20" fill="none" aria-hidden="true">
|
||||
<path opacity="0.2" d="M12 16H4V8H12V16Z" fill="currentColor" />
|
||||
<path d="M12 4H4V16H12V4ZM16 20H0V0H16V20Z" fill="currentColor" />
|
||||
<path
|
||||
d="M63.3543 16L62.5119 12.8711H58.6437L57.8013 16H55.7383L59.2454 4H61.9618L65.4689 16H63.3543ZM61.0678 7.851L60.6896 5.94269H60.4489L60.0707 7.851L59.1595 11.1347H61.9962L61.0678 7.851Z"
|
||||
fill="currentColor"
|
||||
/>
|
||||
<path d="M52.5951 5.87392V16H50.4461V5.87392H47.4375V4H55.6209V5.87392H52.5951Z" fill="currentColor" />
|
||||
<path
|
||||
d="M45.2059 16L44.3635 12.8711H40.4953L39.6529 16H37.5898L41.097 4H43.8133L47.3205 16H45.2059ZM42.9194 7.851L42.5411 5.94269H42.3004L41.9222 7.851L41.011 11.1347H43.8477L42.9194 7.851Z"
|
||||
fill="currentColor"
|
||||
/>
|
||||
<path
|
||||
d="M28 4H32.0917C32.8138 4 33.4556 4.11461 34.0172 4.34384C34.5903 4.5616 35.0716 4.9169 35.4613 5.40974C35.8625 5.89112 36.1662 6.51003 36.3725 7.26648C36.5788 8.02292 36.6819 8.9341 36.6819 10C36.6819 11.0659 36.5788 11.9771 36.3725 12.7335C36.1662 13.49 35.8625 14.1146 35.4613 14.6075C35.0716 15.0888 34.5903 15.4441 34.0172 15.6734C33.4556 15.8911 32.8138 16 32.0917 16H28V4ZM32.0917 14.1261C32.8252 14.1261 33.3926 13.9026 33.7937 13.4556C34.1948 12.9971 34.3954 12.3152 34.3954 11.4097V8.59026C34.3954 7.68481 34.1948 7.0086 33.7937 6.5616C33.3926 6.10315 32.8252 5.87392 32.0917 5.87392H30.149V14.1261H32.0917Z"
|
||||
fill="currentColor"
|
||||
/>
|
||||
</svg>
|
||||
)
|
||||
}
|
||||
|
||||
function OpenCodeMark() {
|
||||
return (
|
||||
<svg data-slot="opencode-mark" width="40" height="40" viewBox="0 0 40 40" fill="none" aria-hidden="true">
|
||||
<path d="M40 40H0V0H40V40Z" fill="var(--stats-logo-bg)" />
|
||||
<path d="M26 29H14V17H26V29Z" fill="var(--stats-logo-fill)" />
|
||||
<path d="M26 11H14V29H26V11ZM32 35H8V5H32V35Z" fill="var(--stats-logo-stroke)" />
|
||||
</svg>
|
||||
)
|
||||
}
|
||||
|
||||
export function Footer(props: {
|
||||
themePreference: ThemePreference
|
||||
onThemePreferenceChange: (preference: ThemePreference) => void
|
||||
links?: readonly HeaderLink[]
|
||||
}) {
|
||||
const [subscribeOpen, setSubscribeOpen] = createSignal(false)
|
||||
const modelStats = props.links ?? [
|
||||
{ href: "#top-models", label: "Top Models" },
|
||||
{ href: "#leaderboard", label: "Leaderboard" },
|
||||
{ href: "#session-cost", label: "Session Cost" },
|
||||
{ href: "#token-cost", label: "Token Cost" },
|
||||
{ href: "#cache-ratio", label: "Cache Ratio" },
|
||||
{ href: "#market-share", label: "Market Share" },
|
||||
{ href: "#geo-breakdown", label: "Geo Breakdown" },
|
||||
]
|
||||
const legal = [
|
||||
{ href: "https://opencode.ai/legal/terms-of-service", label: "Terms of service" },
|
||||
{ href: "https://opencode.ai/legal/privacy-policy", label: "Privacy policy" },
|
||||
]
|
||||
const connect = [
|
||||
{ href: "mailto:hello@opencode.ai", label: "Contact us" },
|
||||
{ href: "https://opencode.ai/discord", label: "Community" },
|
||||
{ href: "https://x.com/opencode", label: "X" },
|
||||
githubLink,
|
||||
{ href: "https://www.youtube.com/@anomaly-co", label: "YouTube" },
|
||||
]
|
||||
|
||||
return (
|
||||
<footer data-component="footer">
|
||||
<SectionBridge label="GEO BREAKDOWN" href="#geo-breakdown" />
|
||||
<div data-slot="footer-grid">
|
||||
<a data-slot="footer-mark" href="https://opencode.ai" aria-label="OpenCode home">
|
||||
<OpenCodeMark />
|
||||
</a>
|
||||
<FooterColumn title="Model Data" links={modelStats} />
|
||||
<FooterColumn title="Legal" links={legal} />
|
||||
<FooterColumn title="Connect" links={connect} />
|
||||
<div data-slot="footer-column">
|
||||
<h2>Newsletter</h2>
|
||||
<p>Be the first to know about new releases.</p>
|
||||
<button data-slot="subscribe-button" type="button" onClick={() => setSubscribeOpen(true)}>
|
||||
Subscribe
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
<div data-slot="footer-pattern" aria-hidden="true" />
|
||||
<div data-slot="footer-bottom">
|
||||
<div>
|
||||
<span>© 2026 Anomaly Innovations Inc.</span>
|
||||
<span data-slot="status">All systems Operational</span>
|
||||
</div>
|
||||
<div data-slot="theme-toggle" role="group" aria-label="Theme">
|
||||
<For each={themePreferences}>
|
||||
{(preference) => (
|
||||
<button
|
||||
data-slot="theme-option"
|
||||
type="button"
|
||||
aria-label={themePreferenceLabels[preference]}
|
||||
aria-pressed={props.themePreference === preference ? "true" : "false"}
|
||||
title={themePreferenceLabels[preference]}
|
||||
onClick={() => props.onThemePreferenceChange(preference)}
|
||||
>
|
||||
<ThemePreferenceIcon preference={preference} />
|
||||
</button>
|
||||
)}
|
||||
</For>
|
||||
</div>
|
||||
</div>
|
||||
<Show when={subscribeOpen()}>
|
||||
<SubscribeModal onClose={() => setSubscribeOpen(false)} />
|
||||
</Show>
|
||||
</footer>
|
||||
)
|
||||
}
|
||||
|
||||
function SectionBridge(props: { label: string; href: string }) {
|
||||
return (
|
||||
<a data-component="section-bridge" href={props.href}>
|
||||
<span>LEAN MORE</span>
|
||||
<i />
|
||||
<strong>{props.label}</strong>
|
||||
<b>▸</b>
|
||||
</a>
|
||||
)
|
||||
}
|
||||
|
||||
function ThemePreferenceIcon(props: { preference: ThemePreference }) {
|
||||
return (
|
||||
<svg data-slot="theme-icon" width="16" height="16" viewBox="0 0 16 16" fill="none" aria-hidden="true">
|
||||
<Show
|
||||
when={props.preference === "dark"}
|
||||
fallback={
|
||||
<Show
|
||||
when={props.preference === "light"}
|
||||
fallback={
|
||||
<>
|
||||
<rect x="1.5552" y="2.4448" width="12.8896" height="8.8888" fill="currentColor" opacity="0.3" />
|
||||
<svg
|
||||
x="1.0552"
|
||||
y="1.9446"
|
||||
width="13.8889"
|
||||
height="12.5325"
|
||||
viewBox="0 0 13.8889 12.5325"
|
||||
preserveAspectRatio="none"
|
||||
overflow="visible"
|
||||
>
|
||||
<path
|
||||
d="M4.05559 12.0555C4.72936 11.8431 5.72492 11.6111 6.94448 11.6111M6.94448 11.6111C7.65114 11.6111 8.66981 11.6893 9.83336 12.0555M6.94448 11.6111L6.94448 9.38888M13.3889 0.5H0.500102C0.500102 0.5 0.500017 1.29594 0.500017 2.27778V7.61112C0.500017 8.59298 0.500007 9.38889 0.500007 9.38889H13.3889C13.3889 9.38889 13.3889 8.59298 13.3889 7.61112V2.27778C13.3889 1.29594 13.3889 0.5 13.3889 0.5Z"
|
||||
stroke="currentColor"
|
||||
/>
|
||||
</svg>
|
||||
</>
|
||||
}
|
||||
>
|
||||
<svg
|
||||
x="0.6102"
|
||||
y="0.6102"
|
||||
width="14.7778"
|
||||
height="14.7778"
|
||||
viewBox="0 0 14.7778 14.7778"
|
||||
preserveAspectRatio="none"
|
||||
overflow="visible"
|
||||
>
|
||||
<path
|
||||
d="M7.38889 0.5V1.38889M12.26 2.51782L11.6315 3.14627M14.2778 7.38892H13.3889M12.26 12.26L11.6315 11.6316M7.38889 14.2778V13.3889M2.51778 12.26L3.14622 11.6316M0.5 7.38892H1.38889M2.51778 2.51782L3.14622 3.14627M7.38888 11.1666C9.47528 11.1666 11.1667 9.47526 11.1667 7.38886C11.1667 5.30245 9.47528 3.61108 7.38888 3.61108C5.30247 3.61108 3.6111 5.30245 3.6111 7.38886C3.6111 9.47526 5.30247 11.1666 7.38888 11.1666Z"
|
||||
stroke="currentColor"
|
||||
stroke-linecap="square"
|
||||
/>
|
||||
</svg>
|
||||
</Show>
|
||||
}
|
||||
>
|
||||
<svg
|
||||
x="2.0549"
|
||||
y="1.742"
|
||||
width="12.3867"
|
||||
height="12.3971"
|
||||
viewBox="0 0 12.3867 12.3971"
|
||||
preserveAspectRatio="none"
|
||||
overflow="visible"
|
||||
>
|
||||
<path
|
||||
d="M9.05556 8.39711C6.37067 8.39711 4.19444 6.22089 4.19444 3.536C4.19444 2.48445 4.53122 1.51456 5.09822 0.71889C2.48178 1.20733 0.5 3.49944 0.5 6.25822C0.5 9.37244 3.02467 11.8971 6.13889 11.8971C8.76156 11.8971 10.9596 10.1036 11.5903 7.67844C10.8514 8.13189 9.98578 8.39711 9.05556 8.39711Z"
|
||||
stroke="currentColor"
|
||||
stroke-linecap="round"
|
||||
/>
|
||||
</svg>
|
||||
</Show>
|
||||
</svg>
|
||||
)
|
||||
}
|
||||
|
||||
function SubscribeModal(props: { onClose: () => void }) {
|
||||
const [status, setStatus] = createSignal<"idle" | "pending" | "success" | "error">("idle")
|
||||
const [message, setMessage] = createSignal("")
|
||||
let input: HTMLInputElement | undefined
|
||||
|
||||
onMount(() => {
|
||||
if (typeof document === "undefined") return
|
||||
const activeElement = document.activeElement instanceof HTMLElement ? document.activeElement : undefined
|
||||
const htmlOverflow = document.documentElement.style.overflow
|
||||
const bodyOverflow = document.body.style.overflow
|
||||
document.documentElement.style.overflow = "hidden"
|
||||
document.body.style.overflow = "hidden"
|
||||
const focusTimeout = window.setTimeout(() => input?.focus(), 0)
|
||||
const onKeyDown = (event: KeyboardEvent) => {
|
||||
if (event.key === "Escape") props.onClose()
|
||||
}
|
||||
document.addEventListener("keydown", onKeyDown)
|
||||
onCleanup(() => {
|
||||
window.clearTimeout(focusTimeout)
|
||||
document.documentElement.style.overflow = htmlOverflow
|
||||
document.body.style.overflow = bodyOverflow
|
||||
document.removeEventListener("keydown", onKeyDown)
|
||||
activeElement?.focus()
|
||||
})
|
||||
})
|
||||
|
||||
return (
|
||||
<div data-component="subscribe-modal" role="dialog" aria-modal="true" aria-labelledby="subscribe-title">
|
||||
<div data-slot="modal-scrim" aria-hidden="true" onClick={props.onClose} />
|
||||
<div data-slot="modal-panel">
|
||||
<div data-slot="modal-brand">
|
||||
<img data-slot="modal-logo" src={opencodeWordmarkDark} alt="OpenCode" />
|
||||
<button data-slot="modal-close" type="button" aria-label="Close newsletter signup" onClick={props.onClose}>
|
||||
<svg width="16" height="16" viewBox="0 0 16 16" fill="none" aria-hidden="true">
|
||||
<path d="M4.44 4.44L11.56 11.56M11.56 4.44L4.44 11.56" stroke="currentColor" />
|
||||
</svg>
|
||||
</button>
|
||||
</div>
|
||||
<div data-slot="modal-body">
|
||||
<div data-slot="modal-intro">
|
||||
<h2 id="subscribe-title">OpenCode Newsletter</h2>
|
||||
<p>
|
||||
Be the first to know
|
||||
<br />
|
||||
about new releases.
|
||||
</p>
|
||||
</div>
|
||||
<form
|
||||
data-slot="subscribe-form"
|
||||
method="post"
|
||||
onSubmit={(event) => {
|
||||
event.preventDefault()
|
||||
const form = event.currentTarget
|
||||
setStatus("pending")
|
||||
setMessage("")
|
||||
fetch(`${import.meta.env.BASE_URL}api/newsletter`, {
|
||||
method: "POST",
|
||||
body: new FormData(form),
|
||||
}).then(
|
||||
async (response) => {
|
||||
if (response.ok) {
|
||||
form.reset()
|
||||
setStatus("success")
|
||||
return
|
||||
}
|
||||
setMessage(await newsletterErrorMessage(response))
|
||||
setStatus("error")
|
||||
},
|
||||
() => {
|
||||
setMessage("Failed to subscribe")
|
||||
setStatus("error")
|
||||
},
|
||||
)
|
||||
}}
|
||||
>
|
||||
<input ref={input} type="email" name="email" placeholder="Email address" required />
|
||||
<button type="submit" disabled={status() === "pending"}>
|
||||
<span>{status() === "pending" ? "Subscribing..." : "Subscribe"}</span>
|
||||
</button>
|
||||
</form>
|
||||
<div data-slot="subscribe-feedback" aria-live="polite">
|
||||
<Show when={status() === "success"}>
|
||||
<p data-state="success">You're subscribed.</p>
|
||||
</Show>
|
||||
<Show when={status() === "error"}>
|
||||
<p data-state="error">{message()}</p>
|
||||
</Show>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
function newsletterErrorMessage(response: Response) {
|
||||
return response.json().then(
|
||||
(body: unknown) =>
|
||||
body && typeof body === "object" && "error" in body && typeof body.error === "string"
|
||||
? body.error
|
||||
: "Failed to subscribe",
|
||||
() => "Failed to subscribe",
|
||||
)
|
||||
}
|
||||
|
||||
function FooterColumn(props: { title: string; links: readonly { href: string; label: string }[] }) {
|
||||
return (
|
||||
<div data-slot="footer-column">
|
||||
<h2>{props.title}</h2>
|
||||
<nav aria-label={props.title}>
|
||||
<For each={props.links}>
|
||||
{(link) => (
|
||||
<a href={link.href} target={link.href.startsWith("http") ? "_blank" : undefined} rel="noreferrer">
|
||||
{link.label}
|
||||
</a>
|
||||
)}
|
||||
</For>
|
||||
</nav>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
1
packages/stats/app/src/routes/stats/api/health.ts
Normal file
1
packages/stats/app/src/routes/stats/api/health.ts
Normal file
@@ -0,0 +1 @@
|
||||
export { GET } from "../../api/health"
|
||||
1
packages/stats/app/src/routes/stats/api/newsletter.ts
Normal file
1
packages/stats/app/src/routes/stats/api/newsletter.ts
Normal file
@@ -0,0 +1 @@
|
||||
export { POST } from "../../api/newsletter"
|
||||
10
packages/stats/app/sst-env.d.ts
vendored
Normal file
10
packages/stats/app/sst-env.d.ts
vendored
Normal file
@@ -0,0 +1,10 @@
|
||||
/* This file is auto-generated by SST. Do not edit. */
|
||||
/* tslint:disable */
|
||||
/* eslint-disable */
|
||||
/* deno-fmt-ignore-file */
|
||||
/* biome-ignore-all lint: auto-generated */
|
||||
|
||||
/// <reference path="../../../sst-env.d.ts" />
|
||||
|
||||
import "sst"
|
||||
export {}
|
||||
22
packages/stats/app/tsconfig.json
Normal file
22
packages/stats/app/tsconfig.json
Normal file
@@ -0,0 +1,22 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig",
|
||||
"compilerOptions": {
|
||||
"target": "ESNext",
|
||||
"module": "ESNext",
|
||||
"skipLibCheck": true,
|
||||
"moduleResolution": "bundler",
|
||||
"allowSyntheticDefaultImports": true,
|
||||
"esModuleInterop": true,
|
||||
"jsx": "preserve",
|
||||
"jsxImportSource": "solid-js",
|
||||
"allowJs": true,
|
||||
"strict": true,
|
||||
"noEmit": true,
|
||||
"types": ["vite/client", "bun"],
|
||||
"isolatedModules": true,
|
||||
"paths": {
|
||||
"~/*": ["./src/*"]
|
||||
}
|
||||
},
|
||||
"include": ["*.ts", "src", "../core/src/resource.d.ts"]
|
||||
}
|
||||
23
packages/stats/app/vite.config.ts
Normal file
23
packages/stats/app/vite.config.ts
Normal file
@@ -0,0 +1,23 @@
|
||||
import { solidStart } from "@solidjs/start/config"
|
||||
import { nitro } from "nitro/vite"
|
||||
import { defineConfig, type PluginOption } from "vite"
|
||||
|
||||
export default defineConfig({
|
||||
base: "/data/",
|
||||
plugins: [
|
||||
solidStart() as PluginOption,
|
||||
nitro({
|
||||
compatibilityDate: "2024-09-19",
|
||||
preset: "cloudflare-module",
|
||||
cloudflare: {
|
||||
nodeCompat: true,
|
||||
},
|
||||
}),
|
||||
],
|
||||
server: {
|
||||
allowedHosts: true,
|
||||
},
|
||||
build: {
|
||||
minify: false,
|
||||
},
|
||||
})
|
||||
21
packages/stats/core/drizzle.config.ts
Normal file
21
packages/stats/core/drizzle.config.ts
Normal file
@@ -0,0 +1,21 @@
|
||||
import { Resource } from "sst/resource"
|
||||
import { defineConfig } from "drizzle-kit"
|
||||
|
||||
export default defineConfig({
|
||||
dialect: "mysql",
|
||||
schema: ["./src/database/schema.ts"],
|
||||
// schema: ["./src/**/*.sql.ts"],
|
||||
out: "./migrations/",
|
||||
strict: true,
|
||||
verbose: true,
|
||||
dbCredentials: {
|
||||
database: Resource.StatsDatabase.database,
|
||||
host: Resource.StatsDatabase.host,
|
||||
user: Resource.StatsDatabase.username,
|
||||
password: Resource.StatsDatabase.password,
|
||||
port: Resource.StatsDatabase.port,
|
||||
ssl: {
|
||||
rejectUnauthorized: false,
|
||||
},
|
||||
},
|
||||
})
|
||||
@@ -0,0 +1,42 @@
|
||||
CREATE TABLE `stat` (
|
||||
`id` bigint AUTO_INCREMENT PRIMARY KEY,
|
||||
`grain` varchar(16) NOT NULL,
|
||||
`period_start` datetime NOT NULL,
|
||||
`period_end` datetime NOT NULL,
|
||||
`dataset` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`tier` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`client` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`source` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`provider` varchar(128) NOT NULL,
|
||||
`model` varchar(256) NOT NULL,
|
||||
`provider_model` varchar(256) NOT NULL DEFAULT '',
|
||||
`sessions` bigint NOT NULL DEFAULT 0,
|
||||
`requests` bigint NOT NULL DEFAULT 0,
|
||||
`input_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`output_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`reasoning_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`cache_read_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`total_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`input_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`output_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`total_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`avg_duration_ms` decimal(12,2),
|
||||
`p50_duration_ms` int,
|
||||
`p95_duration_ms` int,
|
||||
`avg_ttfb_ms` decimal(12,2),
|
||||
`p50_ttfb_ms` int,
|
||||
`p95_ttfb_ms` int,
|
||||
`avg_output_tps` decimal(12,4),
|
||||
`success_count` bigint NOT NULL DEFAULT 0,
|
||||
`error_count` bigint NOT NULL DEFAULT 0,
|
||||
`sample_count` bigint NOT NULL DEFAULT 0,
|
||||
`rank_by_tokens` int,
|
||||
`rank_by_requests` int,
|
||||
`rank_by_cost` int,
|
||||
`created_at` datetime NOT NULL DEFAULT (now()),
|
||||
`updated_at` datetime NOT NULL DEFAULT (now()) ON UPDATE CURRENT_TIMESTAMP,
|
||||
CONSTRAINT `uniq_model_period` UNIQUE INDEX(`grain`,`period_start`,`dataset`,`tier`,`client`,`source`,`provider`,`model`)
|
||||
);
|
||||
--> statement-breakpoint
|
||||
CREATE INDEX `idx_leaderboard_tokens` ON `stat` (`grain`,`period_start`,`dataset`,`tier`,`total_tokens`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_model` ON `stat` (`model`,`grain`,`period_start`);
|
||||
@@ -0,0 +1,623 @@
|
||||
{
|
||||
"version": "6",
|
||||
"dialect": "mysql",
|
||||
"id": "72655266-65da-408e-bfd8-9f3a4ad817a5",
|
||||
"prevIds": ["00000000-0000-0000-0000-000000000000"],
|
||||
"ddl": [
|
||||
{
|
||||
"name": "stat",
|
||||
"entityType": "tables"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": true,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "id",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(16)",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "grain",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "datetime",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "period_start",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "datetime",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "period_end",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(64)",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "'all'",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "dataset",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(64)",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "'all'",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "tier",
|
||||
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|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(64)",
|
||||
"notNull": true,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"name": "source",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(128)",
|
||||
"notNull": true,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "provider",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(256)",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "model",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "varchar(256)",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "''",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "provider_model",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "sessions",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "requests",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "input_tokens",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "output_tokens",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "reasoning_tokens",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "cache_read_tokens",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "total_tokens",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "input_cost_microcents",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "output_cost_microcents",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "total_cost_microcents",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "decimal(12,2)",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "avg_duration_ms",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "p50_duration_ms",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "p95_duration_ms",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "decimal(12,2)",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "avg_ttfb_ms",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "p50_ttfb_ms",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "p95_ttfb_ms",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "decimal(12,4)",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "avg_output_tps",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "success_count",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "error_count",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "bigint",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "0",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "sample_count",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "rank_by_tokens",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "rank_by_requests",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "int",
|
||||
"notNull": false,
|
||||
"autoIncrement": false,
|
||||
"default": null,
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "rank_by_cost",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "datetime",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "(now())",
|
||||
"onUpdateNow": false,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "created_at",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"type": "datetime",
|
||||
"notNull": true,
|
||||
"autoIncrement": false,
|
||||
"default": "(now())",
|
||||
"onUpdateNow": true,
|
||||
"onUpdateNowFsp": null,
|
||||
"charSet": null,
|
||||
"collation": null,
|
||||
"generated": null,
|
||||
"name": "updated_at",
|
||||
"entityType": "columns",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"columns": ["id"],
|
||||
"name": "PRIMARY",
|
||||
"table": "stat",
|
||||
"entityType": "pks"
|
||||
},
|
||||
{
|
||||
"columns": [
|
||||
{
|
||||
"value": "grain",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "period_start",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "dataset",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "tier",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "client",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "source",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "provider",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "model",
|
||||
"isExpression": false
|
||||
}
|
||||
],
|
||||
"isUnique": true,
|
||||
"using": null,
|
||||
"algorithm": null,
|
||||
"lock": null,
|
||||
"nameExplicit": true,
|
||||
"name": "uniq_model_period",
|
||||
"entityType": "indexes",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"columns": [
|
||||
{
|
||||
"value": "grain",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "period_start",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "dataset",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "tier",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "total_tokens",
|
||||
"isExpression": false
|
||||
}
|
||||
],
|
||||
"isUnique": false,
|
||||
"using": null,
|
||||
"algorithm": null,
|
||||
"lock": null,
|
||||
"nameExplicit": true,
|
||||
"name": "idx_leaderboard_tokens",
|
||||
"entityType": "indexes",
|
||||
"table": "stat"
|
||||
},
|
||||
{
|
||||
"columns": [
|
||||
{
|
||||
"value": "model",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "grain",
|
||||
"isExpression": false
|
||||
},
|
||||
{
|
||||
"value": "period_start",
|
||||
"isExpression": false
|
||||
}
|
||||
],
|
||||
"isUnique": false,
|
||||
"using": null,
|
||||
"algorithm": null,
|
||||
"lock": null,
|
||||
"nameExplicit": true,
|
||||
"name": "idx_model",
|
||||
"entityType": "indexes",
|
||||
"table": "stat"
|
||||
}
|
||||
],
|
||||
"renames": []
|
||||
}
|
||||
@@ -0,0 +1,94 @@
|
||||
CREATE TABLE `geo_stat` (
|
||||
`id` bigint AUTO_INCREMENT PRIMARY KEY,
|
||||
`grain` varchar(16) NOT NULL,
|
||||
`period_start` datetime NOT NULL,
|
||||
`period_end` datetime NOT NULL,
|
||||
`dataset` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`tier` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`client` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`source` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`country` char(2) NOT NULL,
|
||||
`continent` varchar(8) NOT NULL DEFAULT '',
|
||||
`sessions` bigint NOT NULL DEFAULT 0,
|
||||
`requests` bigint NOT NULL DEFAULT 0,
|
||||
`input_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`output_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`reasoning_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`cache_read_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`total_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`input_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`output_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`total_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`avg_duration_ms` decimal(12,2),
|
||||
`p50_duration_ms` int,
|
||||
`p95_duration_ms` int,
|
||||
`avg_ttfb_ms` decimal(12,2),
|
||||
`p50_ttfb_ms` int,
|
||||
`p95_ttfb_ms` int,
|
||||
`avg_output_tps` decimal(12,4),
|
||||
`success_count` bigint NOT NULL DEFAULT 0,
|
||||
`error_count` bigint NOT NULL DEFAULT 0,
|
||||
`sample_count` bigint NOT NULL DEFAULT 0,
|
||||
`market_share_tokens` decimal(10,6),
|
||||
`market_share_requests` decimal(10,6),
|
||||
`market_share_sessions` decimal(10,6),
|
||||
`rank_by_tokens` int,
|
||||
`rank_by_requests` int,
|
||||
`rank_by_sessions` int,
|
||||
`rank_by_cost` int,
|
||||
`created_at` datetime NOT NULL DEFAULT (now()),
|
||||
`updated_at` datetime NOT NULL DEFAULT (now()) ON UPDATE CURRENT_TIMESTAMP,
|
||||
CONSTRAINT `uniq_country_period` UNIQUE INDEX(`grain`,`period_start`,`dataset`,`tier`,`client`,`source`,`country`)
|
||||
);
|
||||
--> statement-breakpoint
|
||||
CREATE TABLE `provider_stat` (
|
||||
`id` bigint AUTO_INCREMENT PRIMARY KEY,
|
||||
`grain` varchar(16) NOT NULL,
|
||||
`period_start` datetime NOT NULL,
|
||||
`period_end` datetime NOT NULL,
|
||||
`dataset` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`tier` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`client` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`source` varchar(64) NOT NULL DEFAULT 'all',
|
||||
`provider` varchar(128) NOT NULL,
|
||||
`sessions` bigint NOT NULL DEFAULT 0,
|
||||
`requests` bigint NOT NULL DEFAULT 0,
|
||||
`input_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`output_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`reasoning_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`cache_read_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`total_tokens` bigint NOT NULL DEFAULT 0,
|
||||
`input_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`output_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`total_cost_microcents` bigint NOT NULL DEFAULT 0,
|
||||
`avg_duration_ms` decimal(12,2),
|
||||
`p50_duration_ms` int,
|
||||
`p95_duration_ms` int,
|
||||
`avg_ttfb_ms` decimal(12,2),
|
||||
`p50_ttfb_ms` int,
|
||||
`p95_ttfb_ms` int,
|
||||
`avg_output_tps` decimal(12,4),
|
||||
`success_count` bigint NOT NULL DEFAULT 0,
|
||||
`error_count` bigint NOT NULL DEFAULT 0,
|
||||
`sample_count` bigint NOT NULL DEFAULT 0,
|
||||
`market_share_tokens` decimal(10,6),
|
||||
`market_share_requests` decimal(10,6),
|
||||
`market_share_sessions` decimal(10,6),
|
||||
`rank_by_tokens` int,
|
||||
`rank_by_requests` int,
|
||||
`rank_by_sessions` int,
|
||||
`rank_by_cost` int,
|
||||
`created_at` datetime NOT NULL DEFAULT (now()),
|
||||
`updated_at` datetime NOT NULL DEFAULT (now()) ON UPDATE CURRENT_TIMESTAMP,
|
||||
CONSTRAINT `uniq_provider_period` UNIQUE INDEX(`grain`,`period_start`,`dataset`,`tier`,`client`,`source`,`provider`)
|
||||
);
|
||||
--> statement-breakpoint
|
||||
RENAME TABLE `stat` TO `model_stat`;--> statement-breakpoint
|
||||
CREATE INDEX `idx_country_map_tokens` ON `geo_stat` (`grain`,`period_start`,`dataset`,`tier`,`total_tokens`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_country_rank` ON `geo_stat` (`grain`,`period_start`,`dataset`,`tier`,`rank_by_tokens`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_country` ON `geo_stat` (`country`,`grain`,`period_start`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_continent` ON `geo_stat` (`continent`,`grain`,`period_start`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_provider_leaderboard_tokens` ON `provider_stat` (`grain`,`period_start`,`dataset`,`tier`,`total_tokens`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_provider_market_share` ON `provider_stat` (`grain`,`period_start`,`dataset`,`tier`,`market_share_tokens`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_provider_rank` ON `provider_stat` (`grain`,`period_start`,`dataset`,`tier`,`rank_by_tokens`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_provider` ON `provider_stat` (`provider`,`grain`,`period_start`);
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,5 @@
|
||||
ALTER TABLE `geo_stat` ADD `provider` varchar(128) DEFAULT 'all' NOT NULL;--> statement-breakpoint
|
||||
ALTER TABLE `geo_stat` ADD `model` varchar(256) DEFAULT 'all' NOT NULL;--> statement-breakpoint
|
||||
ALTER TABLE `geo_stat` DROP INDEX `uniq_country_period`;--> statement-breakpoint
|
||||
CREATE UNIQUE INDEX `uniq_country_period` ON `geo_stat` (`grain`,`period_start`,`dataset`,`tier`,`client`,`source`,`provider`,`model`,`country`);--> statement-breakpoint
|
||||
CREATE INDEX `idx_country_model` ON `geo_stat` (`model`,`country`,`grain`,`period_start`);
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,3 @@
|
||||
ALTER TABLE `geo_stat` ADD `period_key` varchar(32) NOT NULL;--> statement-breakpoint
|
||||
ALTER TABLE `model_stat` ADD `period_key` varchar(32) NOT NULL;--> statement-breakpoint
|
||||
ALTER TABLE `provider_stat` ADD `period_key` varchar(32) NOT NULL;
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,6 @@
|
||||
ALTER TABLE `geo_stat` DROP COLUMN `period_start`;--> statement-breakpoint
|
||||
ALTER TABLE `geo_stat` DROP COLUMN `period_end`;--> statement-breakpoint
|
||||
ALTER TABLE `model_stat` DROP COLUMN `period_start`;--> statement-breakpoint
|
||||
ALTER TABLE `model_stat` DROP COLUMN `period_end`;--> statement-breakpoint
|
||||
ALTER TABLE `provider_stat` DROP COLUMN `period_start`;--> statement-breakpoint
|
||||
ALTER TABLE `provider_stat` DROP COLUMN `period_end`;
|
||||
File diff suppressed because it is too large
Load Diff
44
packages/stats/core/package.json
Normal file
44
packages/stats/core/package.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/package.json",
|
||||
"name": "@opencode-ai/stats-core",
|
||||
"version": "1.17.4",
|
||||
"private": true,
|
||||
"type": "module",
|
||||
"license": "MIT",
|
||||
"exports": {
|
||||
".": "./src/index.ts",
|
||||
"./athena": "./src/athena.ts",
|
||||
"./config": "./src/config.ts",
|
||||
"./database": "./src/database.ts",
|
||||
"./database/*": "./src/database/*.ts",
|
||||
"./domain/*": "./src/domain/*.ts",
|
||||
"./runtime": "./src/runtime.ts",
|
||||
"./stat-sync": "./src/stat-sync.ts"
|
||||
},
|
||||
"scripts": {
|
||||
"db:generate": "drizzle-kit generate --config=drizzle.config.ts",
|
||||
"db:migrate": "bun src/migrate.ts",
|
||||
"db:push": "drizzle-kit push --config=drizzle.config.ts",
|
||||
"db:studio": "drizzle-kit studio --config=drizzle.config.ts",
|
||||
"honeycomb:backfill": "bun src/honeycomb-backfill.ts",
|
||||
"typecheck": "tsgo --noEmit"
|
||||
},
|
||||
"dependencies": {
|
||||
"@aws-sdk/client-athena": "3.933.0",
|
||||
"@planetscale/database": "1.19.0",
|
||||
"drizzle-orm": "catalog:",
|
||||
"effect": "catalog:",
|
||||
"sst": "catalog:"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@tsconfig/node22": "catalog:",
|
||||
"@types/bun": "catalog:",
|
||||
"@types/node": "catalog:",
|
||||
"@typescript/native-preview": "catalog:",
|
||||
"drizzle-kit": "catalog:",
|
||||
"typescript": "catalog:"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=22"
|
||||
}
|
||||
}
|
||||
139
packages/stats/core/src/athena.ts
Normal file
139
packages/stats/core/src/athena.ts
Normal file
@@ -0,0 +1,139 @@
|
||||
import {
|
||||
AthenaClient as AwsAthenaClient,
|
||||
GetQueryExecutionCommand,
|
||||
GetQueryResultsCommand,
|
||||
StartQueryExecutionCommand,
|
||||
type Row,
|
||||
} from "@aws-sdk/client-athena"
|
||||
import { Effect, Layer, Schema } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import { Resource } from "sst/resource"
|
||||
|
||||
const ATHENA_MAX_POLL_ATTEMPTS = 60
|
||||
const ATHENA_PAGE_SIZE = 1000
|
||||
|
||||
export type AthenaData = Record<string, string>
|
||||
|
||||
export class AthenaQueryError extends Schema.TaggedErrorClass<AthenaQueryError>()("AthenaQueryError", {
|
||||
message: Schema.String,
|
||||
queryExecutionId: Schema.optional(Schema.String),
|
||||
cause: Schema.optional(Schema.Defect),
|
||||
}) {}
|
||||
|
||||
export class AthenaQueryTimeoutError extends Schema.TaggedErrorClass<AthenaQueryTimeoutError>()(
|
||||
"AthenaQueryTimeoutError",
|
||||
{
|
||||
message: Schema.String,
|
||||
queryExecutionId: Schema.String,
|
||||
},
|
||||
) {}
|
||||
|
||||
export declare namespace Athena {
|
||||
export interface Service {
|
||||
readonly query: (query: string) => Effect.Effect<AthenaData[], AthenaQueryError | AthenaQueryTimeoutError>
|
||||
}
|
||||
}
|
||||
|
||||
export class Athena extends Context.Service<Athena, Athena.Service>()("@opencode/stats/Athena") {
|
||||
static readonly layer: Layer.Layer<Athena> = Layer.effect(
|
||||
Athena,
|
||||
Effect.sync(() => {
|
||||
const client = new AwsAthenaClient({ region: Resource.InferenceEvent.region })
|
||||
|
||||
const query = Effect.fn("Athena.query")(function* (query: string) {
|
||||
const started = yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
client.send(
|
||||
new StartQueryExecutionCommand({
|
||||
QueryString: query,
|
||||
WorkGroup: Resource.InferenceEvent.workgroup,
|
||||
QueryExecutionContext: {
|
||||
Catalog: Resource.InferenceEvent.catalog,
|
||||
Database: Resource.InferenceEvent.database,
|
||||
},
|
||||
}),
|
||||
),
|
||||
catch: (cause) => new AthenaQueryError({ message: "Failed to start Athena stats query", cause }),
|
||||
})
|
||||
const queryExecutionId = started.QueryExecutionId
|
||||
if (!queryExecutionId)
|
||||
return yield* new AthenaQueryError({ message: "Athena did not return a query execution id" })
|
||||
|
||||
yield* poll(client, queryExecutionId)
|
||||
return yield* results(client, queryExecutionId)
|
||||
})
|
||||
|
||||
return Athena.of({ query })
|
||||
}),
|
||||
)
|
||||
}
|
||||
|
||||
const poll: (
|
||||
client: AwsAthenaClient,
|
||||
queryExecutionId: string,
|
||||
attempt?: number,
|
||||
) => Effect.Effect<void, AthenaQueryError | AthenaQueryTimeoutError> = Effect.fn("Athena.poll")(function* (
|
||||
client: AwsAthenaClient,
|
||||
queryExecutionId: string,
|
||||
attempt = 0,
|
||||
) {
|
||||
if (attempt > 0) yield* Effect.sleep("2 seconds")
|
||||
|
||||
const result = yield* Effect.tryPromise({
|
||||
try: () => client.send(new GetQueryExecutionCommand({ QueryExecutionId: queryExecutionId })),
|
||||
catch: (cause) => new AthenaQueryError({ message: "Failed to poll Athena stats query", queryExecutionId, cause }),
|
||||
})
|
||||
const status = result.QueryExecution?.Status
|
||||
|
||||
if (status?.State === "SUCCEEDED") return
|
||||
if (status?.State === "FAILED" || status?.State === "CANCELLED")
|
||||
return yield* new AthenaQueryError({
|
||||
message: `Athena stats query ${status.State.toLowerCase()}: ${status.StateChangeReason ?? "unknown reason"}`,
|
||||
queryExecutionId,
|
||||
})
|
||||
|
||||
if (attempt >= ATHENA_MAX_POLL_ATTEMPTS - 1)
|
||||
return yield* new AthenaQueryTimeoutError({
|
||||
message: `Athena stats query ${queryExecutionId} did not complete`,
|
||||
queryExecutionId,
|
||||
})
|
||||
|
||||
return yield* poll(client, queryExecutionId, attempt + 1)
|
||||
})
|
||||
|
||||
const results: (
|
||||
client: AwsAthenaClient,
|
||||
queryExecutionId: string,
|
||||
nextToken?: string,
|
||||
) => Effect.Effect<AthenaData[], AthenaQueryError> = Effect.fn("Athena.results")(function* (
|
||||
client: AwsAthenaClient,
|
||||
queryExecutionId: string,
|
||||
nextToken?: string,
|
||||
) {
|
||||
const result = yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
client.send(
|
||||
new GetQueryResultsCommand({
|
||||
QueryExecutionId: queryExecutionId,
|
||||
NextToken: nextToken,
|
||||
MaxResults: ATHENA_PAGE_SIZE,
|
||||
}),
|
||||
),
|
||||
catch: (cause) => new AthenaQueryError({ message: "Failed to read Athena stats results", queryExecutionId, cause }),
|
||||
})
|
||||
const columns = result.ResultSet?.ResultSetMetadata?.ColumnInfo?.map((item) => item.Name ?? "") ?? []
|
||||
const rows = (result.ResultSet?.Rows ?? []).slice(nextToken ? 0 : 1).map((row) => rowData(columns, row))
|
||||
|
||||
if (!result.NextToken) return rows
|
||||
return [...rows, ...(yield* results(client, queryExecutionId, result.NextToken))]
|
||||
})
|
||||
|
||||
function rowData(columns: string[], row: Row): AthenaData {
|
||||
return Object.fromEntries(
|
||||
columns.flatMap((column, index) => {
|
||||
const value = row.Data?.[index]?.VarCharValue
|
||||
if (!column || value === undefined) return []
|
||||
return [[column, value]]
|
||||
}),
|
||||
)
|
||||
}
|
||||
23
packages/stats/core/src/config.ts
Normal file
23
packages/stats/core/src/config.ts
Normal file
@@ -0,0 +1,23 @@
|
||||
import { Config, ConfigProvider, Effect, Layer, Schema } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import { Resource } from "sst/resource"
|
||||
|
||||
export class AppConfigValue extends Schema.Class<AppConfigValue>("AppConfigValue")({
|
||||
stage: Schema.NonEmptyString,
|
||||
publicUrl: Schema.NonEmptyString,
|
||||
}) {}
|
||||
|
||||
const decodeAppConfigValue = Schema.decodeUnknownSync(AppConfigValue)
|
||||
|
||||
const config = Config.all({
|
||||
stage: Config.succeed(Resource.App.stage),
|
||||
publicUrl: Config.string("PUBLIC_URL").pipe(Config.withDefault("http://localhost:3000")),
|
||||
}).pipe(Config.map(decodeAppConfigValue))
|
||||
|
||||
export class AppConfig extends Context.Service<AppConfig, AppConfigValue>()("@opencode/stats/AppConfig") {
|
||||
static readonly config = config
|
||||
static readonly layer: Layer.Layer<AppConfig, never, never> = Layer.effect(
|
||||
AppConfig,
|
||||
config.parse(ConfigProvider.fromEnv()).pipe(Effect.orDie),
|
||||
)
|
||||
}
|
||||
79
packages/stats/core/src/database.ts
Normal file
79
packages/stats/core/src/database.ts
Normal file
@@ -0,0 +1,79 @@
|
||||
import { Client } from "@planetscale/database"
|
||||
import { drizzle } from "drizzle-orm/planetscale-serverless"
|
||||
import { migrate as drizzleMigrate } from "drizzle-orm/planetscale-serverless/migrator"
|
||||
import { Config, ConfigProvider, Effect, Layer, Schema } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import * as schema from "./database/schema"
|
||||
import { Resource } from "sst/resource"
|
||||
|
||||
export const DatabaseUrl = Schema.NonEmptyString.pipe(Schema.brand("DatabaseUrl"))
|
||||
export type DatabaseUrl = typeof DatabaseUrl.Type
|
||||
|
||||
export class DatabaseSettings extends Schema.Class<DatabaseSettings>("DatabaseSettings")({
|
||||
url: DatabaseUrl,
|
||||
migrationsDir: Schema.NonEmptyString,
|
||||
}) {}
|
||||
|
||||
const decodeDatabaseSettings = Schema.decodeUnknownSync(DatabaseSettings)
|
||||
|
||||
const config = Config.all({
|
||||
url: Config.nonEmptyString("DATABASE_URL").pipe(Config.withDefault(Resource.StatsDatabase.url)),
|
||||
migrationsDir: Config.nonEmptyString("DATABASE_MIGRATIONS_DIR").pipe(Config.withDefault("./migrations")),
|
||||
}).pipe(Config.map(decodeDatabaseSettings))
|
||||
|
||||
export class DatabaseConfig extends Context.Service<DatabaseConfig, DatabaseSettings>()(
|
||||
"@opencode/stats/DatabaseConfig",
|
||||
) {
|
||||
static readonly config = config
|
||||
static readonly layer: Layer.Layer<DatabaseConfig, never, never> = Layer.effect(
|
||||
DatabaseConfig,
|
||||
config.parse(ConfigProvider.fromEnv()).pipe(Effect.orDie),
|
||||
)
|
||||
}
|
||||
|
||||
function makeDrizzle(settings: DatabaseSettings) {
|
||||
return drizzle({ client: new Client({ url: settings.url }), schema })
|
||||
}
|
||||
|
||||
export type Drizzle = ReturnType<typeof makeDrizzle>
|
||||
|
||||
export class DrizzleClient extends Context.Service<DrizzleClient, Drizzle>()("@opencode/stats/DrizzleClient") {
|
||||
static readonly layer: Layer.Layer<DrizzleClient, never, DatabaseConfig> = Layer.effect(
|
||||
DrizzleClient,
|
||||
Effect.map(DatabaseConfig, makeDrizzle),
|
||||
)
|
||||
}
|
||||
|
||||
export class DatabaseError extends Schema.TaggedErrorClass<DatabaseError>()("DatabaseError", {
|
||||
cause: Schema.Defect,
|
||||
}) {}
|
||||
|
||||
export const catchDbError = Effect.mapError((cause) => DatabaseError.make({ cause }))
|
||||
|
||||
export class MigrationError extends Schema.TaggedErrorClass<MigrationError>()("MigrationError", {
|
||||
message: Schema.String,
|
||||
cause: Schema.optional(Schema.Defect),
|
||||
}) {}
|
||||
|
||||
export const migrate = Effect.fn("Database.migrate")(function* () {
|
||||
const settings = yield* DatabaseConfig
|
||||
yield* Effect.logInfo("applying database migrations").pipe(
|
||||
Effect.annotateLogs({ migrationsDir: settings.migrationsDir }),
|
||||
)
|
||||
const result = yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
drizzleMigrate(drizzle({ client: new Client({ url: settings.url }) }), {
|
||||
migrationsFolder: settings.migrationsDir,
|
||||
}),
|
||||
catch: (cause) => new MigrationError({ message: "Failed to apply database migrations", cause }),
|
||||
})
|
||||
if (result)
|
||||
return yield* new MigrationError({
|
||||
message: `Failed to initialize database migrations: ${result.exitCode}`,
|
||||
})
|
||||
yield* Effect.logInfo("database migrations complete").pipe(
|
||||
Effect.annotateLogs({ migrationsDir: settings.migrationsDir }),
|
||||
)
|
||||
})
|
||||
|
||||
export const layer = Layer.mergeAll(DatabaseConfig.layer, DrizzleClient.layer.pipe(Layer.provide(DatabaseConfig.layer)))
|
||||
160
packages/stats/core/src/database/schema.ts
Normal file
160
packages/stats/core/src/database/schema.ts
Normal file
@@ -0,0 +1,160 @@
|
||||
import { bigint, char, datetime, decimal, index, int, mysqlTable, uniqueIndex, varchar } from "drizzle-orm/mysql-core"
|
||||
|
||||
export const modelStat = mysqlTable(
|
||||
"model_stat",
|
||||
{
|
||||
...periodColumns(),
|
||||
provider: varchar({ length: 128 }).notNull(),
|
||||
model: varchar({ length: 256 }).notNull(),
|
||||
provider_model: varchar({ length: 256 }).notNull().default(""),
|
||||
...metricColumns(),
|
||||
rank_by_tokens: int(),
|
||||
rank_by_requests: int(),
|
||||
rank_by_cost: int(),
|
||||
...timestampColumns(),
|
||||
},
|
||||
(table) => [
|
||||
uniqueIndex("uniq_model_period").on(
|
||||
table.grain,
|
||||
table.period_key,
|
||||
table.dataset,
|
||||
table.tier,
|
||||
table.client,
|
||||
table.source,
|
||||
table.provider,
|
||||
table.model,
|
||||
),
|
||||
index("idx_leaderboard_tokens").on(table.grain, table.period_key, table.dataset, table.tier, table.total_tokens),
|
||||
index("idx_model").on(table.model, table.grain, table.period_key),
|
||||
],
|
||||
)
|
||||
|
||||
export const providerStat = mysqlTable(
|
||||
"provider_stat",
|
||||
{
|
||||
...periodColumns(),
|
||||
provider: varchar({ length: 128 }).notNull(),
|
||||
...metricColumns(),
|
||||
...marketShareColumns(),
|
||||
rank_by_tokens: int(),
|
||||
rank_by_requests: int(),
|
||||
rank_by_sessions: int(),
|
||||
rank_by_cost: int(),
|
||||
...timestampColumns(),
|
||||
},
|
||||
(table) => [
|
||||
uniqueIndex("uniq_provider_period").on(
|
||||
table.grain,
|
||||
table.period_key,
|
||||
table.dataset,
|
||||
table.tier,
|
||||
table.client,
|
||||
table.source,
|
||||
table.provider,
|
||||
),
|
||||
index("idx_provider_leaderboard_tokens").on(
|
||||
table.grain,
|
||||
table.period_key,
|
||||
table.dataset,
|
||||
table.tier,
|
||||
table.total_tokens,
|
||||
),
|
||||
index("idx_provider_market_share").on(
|
||||
table.grain,
|
||||
table.period_key,
|
||||
table.dataset,
|
||||
table.tier,
|
||||
table.market_share_tokens,
|
||||
),
|
||||
index("idx_provider_rank").on(table.grain, table.period_key, table.dataset, table.tier, table.rank_by_tokens),
|
||||
index("idx_provider").on(table.provider, table.grain, table.period_key),
|
||||
],
|
||||
)
|
||||
|
||||
export const geoStat = mysqlTable(
|
||||
"geo_stat",
|
||||
{
|
||||
...periodColumns(),
|
||||
provider: varchar({ length: 128 }).notNull().default("all"),
|
||||
model: varchar({ length: 256 }).notNull().default("all"),
|
||||
country: char({ length: 2 }).notNull(),
|
||||
continent: varchar({ length: 8 }).notNull().default(""),
|
||||
...metricColumns(),
|
||||
...marketShareColumns(),
|
||||
rank_by_tokens: int(),
|
||||
rank_by_requests: int(),
|
||||
rank_by_sessions: int(),
|
||||
rank_by_cost: int(),
|
||||
...timestampColumns(),
|
||||
},
|
||||
(table) => [
|
||||
uniqueIndex("uniq_country_period").on(
|
||||
table.grain,
|
||||
table.period_key,
|
||||
table.dataset,
|
||||
table.tier,
|
||||
table.client,
|
||||
table.source,
|
||||
table.provider,
|
||||
table.model,
|
||||
table.country,
|
||||
),
|
||||
index("idx_country_map_tokens").on(table.grain, table.period_key, table.dataset, table.tier, table.total_tokens),
|
||||
index("idx_country_rank").on(table.grain, table.period_key, table.dataset, table.tier, table.rank_by_tokens),
|
||||
index("idx_country").on(table.country, table.grain, table.period_key),
|
||||
index("idx_continent").on(table.continent, table.grain, table.period_key),
|
||||
index("idx_country_model").on(table.model, table.country, table.grain, table.period_key),
|
||||
],
|
||||
)
|
||||
|
||||
function periodColumns() {
|
||||
return {
|
||||
id: bigint({ mode: "number" }).autoincrement().primaryKey(),
|
||||
grain: varchar({ length: 16 }).notNull(),
|
||||
period_key: varchar({ length: 32 }).notNull(),
|
||||
dataset: varchar({ length: 64 }).notNull().default("all"),
|
||||
tier: varchar({ length: 64 }).notNull().default("all"),
|
||||
client: varchar({ length: 64 }).notNull().default("all"),
|
||||
source: varchar({ length: 64 }).notNull().default("all"),
|
||||
}
|
||||
}
|
||||
|
||||
function metricColumns() {
|
||||
return {
|
||||
sessions: bigint({ mode: "number" }).notNull().default(0),
|
||||
requests: 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),
|
||||
cache_read_tokens: bigint({ mode: "number" }).notNull().default(0),
|
||||
total_tokens: bigint({ mode: "number" }).notNull().default(0),
|
||||
input_cost_microcents: bigint({ mode: "number" }).notNull().default(0),
|
||||
output_cost_microcents: bigint({ mode: "number" }).notNull().default(0),
|
||||
total_cost_microcents: bigint({ mode: "number" }).notNull().default(0),
|
||||
avg_duration_ms: decimal({ precision: 12, scale: 2, mode: "number" }),
|
||||
p50_duration_ms: int(),
|
||||
p95_duration_ms: int(),
|
||||
avg_ttfb_ms: decimal({ precision: 12, scale: 2, mode: "number" }),
|
||||
p50_ttfb_ms: int(),
|
||||
p95_ttfb_ms: int(),
|
||||
avg_output_tps: decimal({ precision: 12, scale: 4, mode: "number" }),
|
||||
success_count: bigint({ mode: "number" }).notNull().default(0),
|
||||
error_count: bigint({ mode: "number" }).notNull().default(0),
|
||||
sample_count: bigint({ mode: "number" }).notNull().default(0),
|
||||
}
|
||||
}
|
||||
|
||||
function marketShareColumns() {
|
||||
return {
|
||||
market_share_tokens: decimal({ precision: 10, scale: 6, mode: "number" }),
|
||||
market_share_requests: decimal({ precision: 10, scale: 6, mode: "number" }),
|
||||
market_share_sessions: decimal({ precision: 10, scale: 6, mode: "number" }),
|
||||
}
|
||||
}
|
||||
|
||||
function timestampColumns() {
|
||||
return {
|
||||
created_at: datetime({ mode: "date" }).notNull().defaultNow(),
|
||||
updated_at: datetime({ mode: "date" }).notNull().defaultNow().onUpdateNow(),
|
||||
}
|
||||
}
|
||||
232
packages/stats/core/src/domain/geo.ts
Normal file
232
packages/stats/core/src/domain/geo.ts
Normal file
@@ -0,0 +1,232 @@
|
||||
import { and, asc, eq, inArray, or } from "drizzle-orm"
|
||||
import { Effect, Layer } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import { DatabaseError, DrizzleClient } from "../database"
|
||||
import { geoStat } from "../database/schema"
|
||||
import { RETIRED_STAT_MODELS, RETIRED_STAT_PROVIDERS } from "./model-normalization"
|
||||
import {
|
||||
chunks,
|
||||
collapseRows,
|
||||
inserted,
|
||||
rankRowsWithMarketShare,
|
||||
statPeriodKey,
|
||||
statRowScope,
|
||||
synthesizeAllTierRows,
|
||||
toStatBaseRow,
|
||||
UPSERT_CHUNK_SIZE,
|
||||
type StatBaseAggregate,
|
||||
} from "./stat"
|
||||
|
||||
export type GeoStatRow = typeof geoStat.$inferInsert
|
||||
export type GeoStatAggregate = StatBaseAggregate & {
|
||||
provider: string
|
||||
model: string
|
||||
country: string
|
||||
continent: string
|
||||
}
|
||||
export type GeoStatMetric = {
|
||||
periodKey: string
|
||||
updatedAt: Date
|
||||
tier: string
|
||||
provider: string
|
||||
model: string
|
||||
country: string
|
||||
continent: string
|
||||
totalTokens: number
|
||||
}
|
||||
|
||||
export declare namespace GeoStatRepo {
|
||||
export interface Service {
|
||||
readonly listDaily: (opts?: {
|
||||
readonly provider?: string
|
||||
readonly model?: string
|
||||
}) => Effect.Effect<GeoStatMetric[], DatabaseError>
|
||||
readonly listByPeriod: (opts: {
|
||||
readonly grain: string
|
||||
readonly periodKey: string
|
||||
readonly dataset?: string
|
||||
readonly tier?: string
|
||||
readonly client?: string
|
||||
readonly source?: string
|
||||
readonly provider?: string
|
||||
readonly model?: string
|
||||
}) => Effect.Effect<GeoStatRow[], DatabaseError>
|
||||
readonly upsert: (rows: GeoStatRow[]) => Effect.Effect<void, DatabaseError>
|
||||
readonly deleteRetiredDimensions: (rows: GeoStatRow[]) => Effect.Effect<void, DatabaseError>
|
||||
}
|
||||
}
|
||||
|
||||
export class GeoStatRepo extends Context.Service<GeoStatRepo, GeoStatRepo.Service>()("@opencode/stats/GeoStatRepo") {
|
||||
static readonly layer: Layer.Layer<GeoStatRepo, never, DrizzleClient> = Layer.effect(
|
||||
GeoStatRepo,
|
||||
Effect.gen(function* () {
|
||||
const db = yield* DrizzleClient
|
||||
|
||||
const listDaily = Effect.fn("GeoStatRepo.listDaily")(function* (opts?: {
|
||||
readonly provider?: string
|
||||
readonly model?: string
|
||||
}) {
|
||||
const scope =
|
||||
opts?.model && opts.provider
|
||||
? and(eq(geoStat.provider, opts.provider), eq(geoStat.model, opts.model))
|
||||
: opts?.model
|
||||
? eq(geoStat.model, opts.model)
|
||||
: and(eq(geoStat.provider, "all"), eq(geoStat.model, "all"))
|
||||
return yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.select({
|
||||
periodKey: geoStat.period_key,
|
||||
updatedAt: geoStat.updated_at,
|
||||
tier: geoStat.tier,
|
||||
provider: geoStat.provider,
|
||||
model: geoStat.model,
|
||||
country: geoStat.country,
|
||||
continent: geoStat.continent,
|
||||
totalTokens: geoStat.total_tokens,
|
||||
})
|
||||
.from(geoStat)
|
||||
.where(and(eq(geoStat.grain, "day"), eq(geoStat.client, "all"), eq(geoStat.source, "all"), scope))
|
||||
.orderBy(asc(geoStat.period_key)),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
const listByPeriod = Effect.fn("GeoStatRepo.listByPeriod")(function* (opts: {
|
||||
readonly grain: string
|
||||
readonly periodKey: string
|
||||
readonly dataset?: string
|
||||
readonly tier?: string
|
||||
readonly client?: string
|
||||
readonly source?: string
|
||||
readonly provider?: string
|
||||
readonly model?: string
|
||||
}) {
|
||||
return yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.select()
|
||||
.from(geoStat)
|
||||
.where(
|
||||
and(
|
||||
eq(geoStat.grain, opts.grain),
|
||||
eq(geoStat.period_key, opts.periodKey),
|
||||
eq(geoStat.dataset, opts.dataset ?? "zen"),
|
||||
eq(geoStat.tier, opts.tier ?? "all"),
|
||||
eq(geoStat.client, opts.client ?? "all"),
|
||||
eq(geoStat.source, opts.source ?? "all"),
|
||||
eq(geoStat.provider, opts.provider ?? "all"),
|
||||
eq(geoStat.model, opts.model ?? "all"),
|
||||
),
|
||||
),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
const upsert = Effect.fn("GeoStatRepo.upsert")(function* (rows: GeoStatRow[]) {
|
||||
yield* Effect.forEach(
|
||||
chunks(rows, UPSERT_CHUNK_SIZE),
|
||||
(chunk) =>
|
||||
Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.insert(geoStat)
|
||||
.values(chunk)
|
||||
.onDuplicateKeyUpdate({
|
||||
set: {
|
||||
continent: inserted("continent"),
|
||||
sessions: inserted("sessions"),
|
||||
requests: inserted("requests"),
|
||||
input_tokens: inserted("input_tokens"),
|
||||
output_tokens: inserted("output_tokens"),
|
||||
reasoning_tokens: inserted("reasoning_tokens"),
|
||||
cache_read_tokens: inserted("cache_read_tokens"),
|
||||
total_tokens: inserted("total_tokens"),
|
||||
input_cost_microcents: inserted("input_cost_microcents"),
|
||||
output_cost_microcents: inserted("output_cost_microcents"),
|
||||
total_cost_microcents: inserted("total_cost_microcents"),
|
||||
avg_duration_ms: inserted("avg_duration_ms"),
|
||||
p50_duration_ms: inserted("p50_duration_ms"),
|
||||
p95_duration_ms: inserted("p95_duration_ms"),
|
||||
avg_ttfb_ms: inserted("avg_ttfb_ms"),
|
||||
p50_ttfb_ms: inserted("p50_ttfb_ms"),
|
||||
p95_ttfb_ms: inserted("p95_ttfb_ms"),
|
||||
avg_output_tps: inserted("avg_output_tps"),
|
||||
success_count: inserted("success_count"),
|
||||
error_count: inserted("error_count"),
|
||||
sample_count: inserted("sample_count"),
|
||||
market_share_tokens: inserted("market_share_tokens"),
|
||||
market_share_requests: inserted("market_share_requests"),
|
||||
market_share_sessions: inserted("market_share_sessions"),
|
||||
rank_by_tokens: inserted("rank_by_tokens"),
|
||||
rank_by_requests: inserted("rank_by_requests"),
|
||||
rank_by_sessions: inserted("rank_by_sessions"),
|
||||
rank_by_cost: inserted("rank_by_cost"),
|
||||
},
|
||||
}),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
}),
|
||||
{ discard: true },
|
||||
)
|
||||
})
|
||||
|
||||
const deleteRetiredDimensions = Effect.fn("GeoStatRepo.deleteRetiredDimensions")(function* (rows: GeoStatRow[]) {
|
||||
const scope = statRowScope(rows)
|
||||
if (!scope) return
|
||||
|
||||
yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.delete(geoStat)
|
||||
.where(
|
||||
and(
|
||||
inArray(geoStat.grain, scope.grains),
|
||||
inArray(geoStat.period_key, scope.periodKeys),
|
||||
inArray(geoStat.dataset, scope.datasets),
|
||||
inArray(geoStat.client, scope.clients),
|
||||
inArray(geoStat.source, scope.sources),
|
||||
or(inArray(geoStat.provider, RETIRED_STAT_PROVIDERS), inArray(geoStat.model, RETIRED_STAT_MODELS)),
|
||||
),
|
||||
),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
return GeoStatRepo.of({ listDaily, listByPeriod, upsert, deleteRetiredDimensions })
|
||||
}),
|
||||
)
|
||||
}
|
||||
|
||||
export function rowsFromAggregates(aggregates: GeoStatAggregate[]) {
|
||||
return rankRowsWithMarketShare(
|
||||
[
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "week").map(toRow), dimensionKey),
|
||||
dimensionKey,
|
||||
),
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "day").map(toRow), dimensionKey),
|
||||
dimensionKey,
|
||||
),
|
||||
],
|
||||
marketShareKey,
|
||||
)
|
||||
}
|
||||
|
||||
function toRow(data: GeoStatAggregate): GeoStatRow {
|
||||
return {
|
||||
...toStatBaseRow(data),
|
||||
provider: data.provider,
|
||||
model: data.model,
|
||||
country: data.country,
|
||||
continent: data.continent,
|
||||
}
|
||||
}
|
||||
|
||||
function dimensionKey(row: GeoStatRow) {
|
||||
return [row.provider, row.model, row.country].join("\u0000")
|
||||
}
|
||||
|
||||
function marketShareKey(row: GeoStatRow) {
|
||||
return [statPeriodKey(row), row.provider, row.model].join("\u0000")
|
||||
}
|
||||
876
packages/stats/core/src/domain/home.ts
Normal file
876
packages/stats/core/src/domain/home.ts
Normal file
@@ -0,0 +1,876 @@
|
||||
import { Effect } from "effect"
|
||||
import { DatabaseError } from "../database"
|
||||
import { GeoStatRepo, type GeoStatMetric } from "./geo"
|
||||
import { ModelStatRepo, type ModelStatMetric } from "./model"
|
||||
import { ProviderStatRepo, type ProviderStatMetric } from "./provider"
|
||||
|
||||
export type UsageProduct = "All Users" | "Zen" | "Go" | "Enterprise"
|
||||
export type TokenProduct = "Zen" | "Go" | "Enterprise"
|
||||
export type UsageRange = "1D" | "1W" | "2W" | "1M" | "2M" | "3M" | "YTD" | "ALL"
|
||||
export type UsagePoint = { date: string; segments: { model: string; value: number }[] }
|
||||
export type MarketDay = { date: string; total: number; authors: { author: string; share: number; tokens: number }[] }
|
||||
export type LeaderboardEntry = {
|
||||
model: string
|
||||
provider: string
|
||||
author: string
|
||||
tokens: number
|
||||
change: number | null
|
||||
rank: number
|
||||
}
|
||||
export type TokenCostEntry = { model: string; total: number; input: number; output: number; cached: number }
|
||||
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 ModelMixEntry = { label: string; tokens: number; share: number }
|
||||
export type ModelProductEntry = { product: string; tokens: number; sessions: number; share: number }
|
||||
export type ModelPeerEntry = {
|
||||
model: string
|
||||
provider: string
|
||||
author: string
|
||||
rank: number
|
||||
tokens: number
|
||||
share: number
|
||||
slug: string
|
||||
}
|
||||
export type LabUsageModelEntry = {
|
||||
model: string
|
||||
provider: string
|
||||
author: string
|
||||
tokens: number
|
||||
share: number
|
||||
slug: string
|
||||
}
|
||||
export type StatsModelData = {
|
||||
updatedAt: string | null
|
||||
model: string
|
||||
slug: string
|
||||
provider: string
|
||||
author: string
|
||||
rank: number
|
||||
previousRank: number | null
|
||||
totalModels: number
|
||||
tokenShare: number
|
||||
tokenChange: number
|
||||
totals: {
|
||||
sessions: number
|
||||
tokens: number
|
||||
cost: number
|
||||
tokensPerSession: number
|
||||
costPerSession: number
|
||||
costPerMillion: number
|
||||
cacheRatio: number
|
||||
}
|
||||
usage: ModelUsagePoint[]
|
||||
tokenMix: ModelMixEntry[]
|
||||
productMix: ModelProductEntry[]
|
||||
country: Record<UsageRange, CountryEntry[]>
|
||||
peers: ModelPeerEntry[]
|
||||
}
|
||||
export type StatsLabData = {
|
||||
updatedAt: string | null
|
||||
provider: string
|
||||
author: string
|
||||
tokenShare: number
|
||||
tokenChange: number
|
||||
totals: {
|
||||
sessions: number
|
||||
tokens: number
|
||||
models: number
|
||||
}
|
||||
usage: ModelUsagePoint[]
|
||||
models: LabUsageModelEntry[]
|
||||
}
|
||||
export type StatsHomeData = {
|
||||
updatedAt: string | null
|
||||
usage: Record<UsageProduct, Record<UsageRange, UsagePoint[]>>
|
||||
leaderboard: Record<UsageProduct, Record<UsageRange, LeaderboardEntry[]>>
|
||||
market: Record<UsageRange, MarketDay[]>
|
||||
tokenCost: Record<TokenProduct, TokenCostEntry[]>
|
||||
cacheRatio: Record<TokenProduct, CacheRatioEntry[]>
|
||||
sessionCost: Record<TokenProduct, SessionCostEntry[]>
|
||||
country: Record<UsageRange, CountryEntry[]>
|
||||
}
|
||||
|
||||
const DAY_MS = 86_400_000
|
||||
const TOKEN_SCALE = 1_000_000
|
||||
const DOLLARS_PER_MICROCENT = 1 / 100_000_000
|
||||
const METRIC_MODEL_LIMIT = 10
|
||||
const LEADERBOARD_CHANGE_MIN_MULTIPLE = 10
|
||||
const months = ["JAN", "FEB", "MAR", "APR", "MAY", "JUN", "JUL", "AUG", "SEP", "OCT", "NOV", "DEC"] as const
|
||||
|
||||
type StatMetricRow = Omit<ModelStatMetric, "updatedAt"> & {
|
||||
periodStart: number
|
||||
updatedAt: number
|
||||
}
|
||||
type ProviderMetricRow = Omit<ProviderStatMetric, "updatedAt"> & {
|
||||
periodStart: number
|
||||
updatedAt: number
|
||||
}
|
||||
type GeoMetricRow = Omit<GeoStatMetric, "updatedAt"> & {
|
||||
periodStart: number
|
||||
updatedAt: number
|
||||
}
|
||||
|
||||
type DateWindow = { start: number; end: number; previousStart: number; previousEnd: number }
|
||||
type Bucket = { start: number; end: number; label: string }
|
||||
type ModelAggregate = {
|
||||
model: string
|
||||
provider: string
|
||||
sessions: number
|
||||
inputTokens: number
|
||||
outputTokens: number
|
||||
reasoningTokens: number
|
||||
cacheReadTokens: number
|
||||
totalTokens: number
|
||||
inputCostMicrocents: number
|
||||
outputCostMicrocents: number
|
||||
totalCostMicrocents: number
|
||||
}
|
||||
|
||||
export const getStatsHomeData: () => Effect.Effect<
|
||||
StatsHomeData,
|
||||
DatabaseError,
|
||||
ModelStatRepo | ProviderStatRepo | GeoStatRepo
|
||||
> = Effect.fn("StatsHome.getData")(function* () {
|
||||
const modelStats = yield* ModelStatRepo
|
||||
const providerStats = yield* ProviderStatRepo
|
||||
const geoStats = yield* GeoStatRepo
|
||||
const [modelRows, providerRows, geoRows] = yield* Effect.all(
|
||||
[modelStats.listDaily(), providerStats.listDaily(), geoStats.listDaily()],
|
||||
{ concurrency: "unbounded" },
|
||||
)
|
||||
return buildStatsHomeData(modelRows, providerRows, geoRows)
|
||||
})
|
||||
|
||||
export const getStatsModelData: (
|
||||
model: string,
|
||||
provider?: string,
|
||||
) => Effect.Effect<StatsModelData | null, DatabaseError, ModelStatRepo | GeoStatRepo> = Effect.fn("StatsModel.getData")(
|
||||
function* (model, provider) {
|
||||
const modelStats = yield* ModelStatRepo
|
||||
const geoStats = yield* GeoStatRepo
|
||||
const modelRows = yield* modelStats.listDaily()
|
||||
const normalized = modelRows.flatMap(normalizeStatRow)
|
||||
const resolvedModel = resolveModelName(model, normalized, provider)
|
||||
if (!resolvedModel) return null
|
||||
return buildStatsModelData(
|
||||
resolvedModel,
|
||||
modelRows,
|
||||
yield* geoStats.listDaily({
|
||||
model: resolvedModel,
|
||||
provider: resolveModelProvider(resolvedModel, normalized, provider),
|
||||
}),
|
||||
provider,
|
||||
)
|
||||
},
|
||||
)
|
||||
|
||||
export const getStatsLabData: (provider: string) => Effect.Effect<StatsLabData | null, DatabaseError, ModelStatRepo> =
|
||||
Effect.fn("StatsLab.getData")(function* (provider) {
|
||||
const modelStats = yield* ModelStatRepo
|
||||
return buildStatsLabData(provider, yield* modelStats.listDaily())
|
||||
})
|
||||
|
||||
function buildStatsHomeData(
|
||||
modelRows: ModelStatMetric[],
|
||||
providerRows: ProviderStatMetric[],
|
||||
geoRows: GeoStatMetric[],
|
||||
): StatsHomeData {
|
||||
const normalized = modelRows.flatMap(normalizeStatRow)
|
||||
const providers = providerRows.flatMap(normalizeProviderRow)
|
||||
const geo = geoRows.flatMap(normalizeGeoRow)
|
||||
const periods = [...normalized, ...providers, ...geo]
|
||||
if (periods.length === 0) return emptyStatsHomeData()
|
||||
|
||||
const earliest = Math.min(...periods.map((row) => row.periodStart))
|
||||
const latest = Math.max(...periods.map((row) => row.periodStart))
|
||||
const latestUpdate = Math.max(...periods.map((row) => row.updatedAt))
|
||||
|
||||
return {
|
||||
updatedAt: new Date(latestUpdate).toISOString(),
|
||||
usage: createUsageProductRecord((product) =>
|
||||
createRangeRecord((range) => buildUsagePoints(normalized, product, range, getWindow(range, earliest, latest))),
|
||||
),
|
||||
leaderboard: createUsageProductRecord((product) =>
|
||||
createRangeRecord((range) => buildLeaderboard(normalized, product, getWindow(range, earliest, latest))),
|
||||
),
|
||||
market: createRangeRecord((range) => buildMarketShare(providers, "Go", range, getWindow(range, earliest, latest))),
|
||||
tokenCost: createTokenProductRecord((product) =>
|
||||
buildTokenCost(normalized, product, getWindow("1W", earliest, latest)),
|
||||
),
|
||||
cacheRatio: createTokenProductRecord((product) =>
|
||||
buildCacheRatio(normalized, product, getWindow("1W", earliest, latest)),
|
||||
),
|
||||
sessionCost: createTokenProductRecord((product) =>
|
||||
buildSessionCost(normalized, product, getWindow("1W", earliest, latest)),
|
||||
),
|
||||
country: createRangeRecord((range) => buildCountryStats(geo, getWindow(range, earliest, latest))),
|
||||
}
|
||||
}
|
||||
|
||||
function buildStatsModelData(
|
||||
modelParam: string,
|
||||
modelRows: ModelStatMetric[],
|
||||
geoRows: GeoStatMetric[],
|
||||
providerParam?: string,
|
||||
): StatsModelData | null {
|
||||
const normalized = modelRows.flatMap(normalizeStatRow)
|
||||
const geo = geoRows.flatMap(normalizeGeoRow)
|
||||
if (normalized.length === 0) return null
|
||||
|
||||
const model = resolveModelName(modelParam, normalized, providerParam)
|
||||
if (!model) return null
|
||||
|
||||
const modelScopedRows = normalized.filter((row) => row.model === model)
|
||||
const earliest = Math.min(...normalized.map((row) => row.periodStart))
|
||||
const latest = Math.max(...normalized.map((row) => row.periodStart))
|
||||
const latestUpdate = Math.max(...modelScopedRows.map((row) => row.updatedAt))
|
||||
const window = getWindow("2M", earliest, latest)
|
||||
const currentRows = rowsForProduct(modelScopedRows, "All Users", window.start, window.end)
|
||||
const previousRows = rowsForProduct(modelScopedRows, "All Users", window.previousStart, window.previousEnd)
|
||||
const current = combineRowsForModel(model, currentRows)
|
||||
const previous = combineRowsForModel(model, previousRows)
|
||||
const peers = aggregateByModelName(rowsForProduct(normalized, "All Users", window.start, window.end))
|
||||
.filter((item) => item.totalTokens > 0)
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens || a.model.localeCompare(b.model))
|
||||
const previousPeers = aggregateByModelName(
|
||||
rowsForProduct(normalized, "All Users", window.previousStart, window.previousEnd),
|
||||
)
|
||||
.filter((item) => item.totalTokens > 0)
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens || a.model.localeCompare(b.model))
|
||||
const rank = Math.max(1, peers.findIndex((item) => item.model === model) + 1)
|
||||
const previousRankIndex = previousPeers.findIndex((item) => item.model === model)
|
||||
const totalTokens = peers.reduce((sum, item) => sum + item.totalTokens, 0)
|
||||
|
||||
return {
|
||||
updatedAt: Number.isFinite(latestUpdate) ? new Date(latestUpdate).toISOString() : null,
|
||||
model,
|
||||
slug: modelSlug(model),
|
||||
provider: current.provider,
|
||||
author: formatProvider(current.provider),
|
||||
rank,
|
||||
previousRank: previousRankIndex >= 0 ? previousRankIndex + 1 : null,
|
||||
totalModels: peers.length,
|
||||
tokenShare: totalTokens > 0 ? round((current.totalTokens / totalTokens) * 100, 2) : 0,
|
||||
tokenChange: percentChange(current.totalTokens, previous.totalTokens),
|
||||
totals: {
|
||||
sessions: current.sessions,
|
||||
tokens: current.totalTokens,
|
||||
cost: round(microcentsToDollars(current.totalCostMicrocents), 2),
|
||||
tokensPerSession: current.sessions > 0 ? Math.round(current.totalTokens / current.sessions) : 0,
|
||||
costPerSession:
|
||||
current.sessions > 0 ? round(microcentsToDollars(current.totalCostMicrocents) / current.sessions, 4) : 0,
|
||||
costPerMillion: costPerMillion(current.totalCostMicrocents, current.totalTokens),
|
||||
cacheRatio:
|
||||
current.inputTokens + current.cacheReadTokens > 0
|
||||
? round((current.cacheReadTokens / (current.inputTokens + current.cacheReadTokens)) * 100, 1)
|
||||
: 0,
|
||||
},
|
||||
usage: buildModelUsage(currentRows, window, "2M"),
|
||||
tokenMix: buildModelTokenMix(current),
|
||||
productMix: buildModelProductMix(modelScopedRows, window, current),
|
||||
country: createRangeRecord((range) => buildCountryStats(geo, getWindow(range, earliest, latest))),
|
||||
peers: buildModelPeers(peers, rank, totalTokens),
|
||||
}
|
||||
}
|
||||
|
||||
function buildStatsLabData(providerParam: string, modelRows: ModelStatMetric[]): StatsLabData | null {
|
||||
const normalized = modelRows.flatMap(normalizeStatRow)
|
||||
if (normalized.length === 0) return null
|
||||
|
||||
const provider = resolveProviderName(providerParam, normalized)
|
||||
if (!provider) return null
|
||||
|
||||
const providerRows = normalized.filter((row) => providerMatches(row.provider, provider))
|
||||
if (providerRows.length === 0) return null
|
||||
|
||||
const earliest = Math.min(...normalized.map((row) => row.periodStart))
|
||||
const latest = Math.max(...normalized.map((row) => row.periodStart))
|
||||
const latestUpdate = Math.max(...providerRows.map((row) => row.updatedAt))
|
||||
const window = getWindow("2M", earliest, latest)
|
||||
const currentRows = rowsForProduct(providerRows, "All Users", window.start, window.end)
|
||||
const previousRows = rowsForProduct(providerRows, "All Users", window.previousStart, window.previousEnd)
|
||||
const current = combineRowsForModel("", currentRows)
|
||||
const previous = combineRowsForModel("", previousRows)
|
||||
const allCurrent = aggregateByModel(rowsForProduct(normalized, "All Users", window.start, window.end))
|
||||
const totalTokens = allCurrent.reduce((sum, item) => sum + item.totalTokens, 0)
|
||||
const models = aggregateByModel(currentRows)
|
||||
.filter((item) => item.totalTokens > 0)
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens || a.model.localeCompare(b.model))
|
||||
|
||||
return {
|
||||
updatedAt: Number.isFinite(latestUpdate) ? new Date(latestUpdate).toISOString() : null,
|
||||
provider,
|
||||
author: formatProvider(provider),
|
||||
tokenShare: totalTokens > 0 ? round((current.totalTokens / totalTokens) * 100, 2) : 0,
|
||||
tokenChange: percentChange(current.totalTokens, previous.totalTokens),
|
||||
totals: {
|
||||
sessions: current.sessions,
|
||||
tokens: current.totalTokens,
|
||||
models: models.length,
|
||||
},
|
||||
usage: buildModelUsage(currentRows, window, "2M"),
|
||||
models: models.map((item) => ({
|
||||
model: item.model,
|
||||
provider: item.provider,
|
||||
author: formatProvider(item.provider),
|
||||
tokens: item.totalTokens,
|
||||
share: current.totalTokens > 0 ? round((item.totalTokens / current.totalTokens) * 100, 2) : 0,
|
||||
slug: modelSlug(item.model),
|
||||
})),
|
||||
}
|
||||
}
|
||||
|
||||
function emptyStatsHomeData(): StatsHomeData {
|
||||
return {
|
||||
updatedAt: null,
|
||||
usage: createUsageProductRecord(() => createRangeRecord(() => [])),
|
||||
leaderboard: createUsageProductRecord(() => createRangeRecord(() => [])),
|
||||
market: createRangeRecord(() => []),
|
||||
tokenCost: createTokenProductRecord(() => []),
|
||||
cacheRatio: createTokenProductRecord(() => []),
|
||||
sessionCost: createTokenProductRecord(() => []),
|
||||
country: createRangeRecord(() => []),
|
||||
}
|
||||
}
|
||||
|
||||
function buildUsagePoints(rows: StatMetricRow[], product: UsageProduct, range: UsageRange, window: DateWindow) {
|
||||
const windowRows = rowsForProduct(rows, product, window.start, window.end)
|
||||
const modelOrder = aggregateByModel(windowRows)
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens)
|
||||
.slice(0, 6)
|
||||
.map((item) => ({ key: modelKey(item.provider, item.model), model: item.model }))
|
||||
|
||||
return createBuckets(window, range).map((bucket) => {
|
||||
const bucketRows = aggregateByModel(rowsForProduct(rows, product, bucket.start, bucket.end))
|
||||
const byModel = new Map(bucketRows.map((item) => [modelKey(item.provider, item.model), item.totalTokens]))
|
||||
const segmentTokens = modelOrder.map((model) => ({ model: model.model, tokens: byModel.get(model.key) ?? 0 }))
|
||||
const knownTokens = segmentTokens.reduce((sum, item) => sum + item.tokens, 0)
|
||||
const totalTokens = bucketRows.reduce((sum, item) => sum + item.totalTokens, 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) },
|
||||
],
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
function buildLeaderboard(rows: StatMetricRow[], product: UsageProduct, window: DateWindow) {
|
||||
const previous = new Map(
|
||||
aggregateByModel(rowsForProduct(rows, product, window.previousStart, window.previousEnd)).map((item) => [
|
||||
modelKey(item.provider, item.model),
|
||||
item.totalTokens,
|
||||
]),
|
||||
)
|
||||
|
||||
return aggregateByModel(rowsForProduct(rows, product, window.start, window.end))
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens)
|
||||
.slice(0, 18)
|
||||
.map((item, index) => ({
|
||||
model: item.model,
|
||||
provider: item.provider,
|
||||
author: formatProvider(item.provider),
|
||||
tokens: Math.round(item.totalTokens / 1_000_000_000),
|
||||
change: leaderboardChange(item.totalTokens, previous.get(modelKey(item.provider, item.model)) ?? 0),
|
||||
rank: index + 1,
|
||||
}))
|
||||
}
|
||||
|
||||
function buildMarketShare(rows: ProviderMetricRow[], product: UsageProduct, range: UsageRange, window: DateWindow) {
|
||||
return createBuckets(window, range).flatMap((bucket) => {
|
||||
const total = aggregateByProvider(rowsForProduct(rows, product, bucket.start, bucket.end)).toSorted(
|
||||
(a, b) => b.tokens - a.tokens,
|
||||
)
|
||||
const totalTokens = total.reduce((sum, item) => sum + item.tokens, 0)
|
||||
if (totalTokens === 0) return []
|
||||
|
||||
const authors = total.slice(0, 8)
|
||||
const knownTokens = authors.reduce((sum, item) => sum + item.tokens, 0)
|
||||
const withOther = [...authors, { provider: "Other", tokens: Math.max(totalTokens - knownTokens, 0) }].filter(
|
||||
(item) => item.tokens > 0,
|
||||
)
|
||||
|
||||
return [
|
||||
{
|
||||
date: bucket.label,
|
||||
total: round(totalTokens / 1_000_000_000_000, 2),
|
||||
authors: withOther.map((item) => ({
|
||||
author: item.provider === "Other" ? "Other" : formatProvider(item.provider),
|
||||
share: round((item.tokens / totalTokens) * 100, 1),
|
||||
tokens: round(item.tokens / 1_000_000_000_000, 2),
|
||||
})),
|
||||
},
|
||||
]
|
||||
})
|
||||
}
|
||||
|
||||
function buildCountryStats(rows: GeoMetricRow[], window: DateWindow) {
|
||||
const countries = aggregateByCountry(rowsForProduct(rows, "All Users", window.start, window.end))
|
||||
.filter((item) => item.tokens > 0 && item.country !== "AQ")
|
||||
.toSorted((a, b) => b.tokens - a.tokens)
|
||||
const totalTokens = countries.reduce((sum, item) => sum + item.tokens, 0)
|
||||
if (totalTokens === 0) return []
|
||||
|
||||
return countries.map((item, index) => ({
|
||||
country: item.country,
|
||||
continent: item.continent,
|
||||
tokens: round(item.tokens / 1_000_000_000_000, 4),
|
||||
share: round((item.tokens / totalTokens) * 100, 1),
|
||||
rank: index + 1,
|
||||
}))
|
||||
}
|
||||
|
||||
function buildTokenCost(rows: StatMetricRow[], product: TokenProduct, window: DateWindow) {
|
||||
return topModelsByUsage(rows, product, window)
|
||||
.flatMap((item) => {
|
||||
const total = costPerMillion(item.totalCostMicrocents, item.totalTokens)
|
||||
if (total === 0) return []
|
||||
return [
|
||||
{
|
||||
model: item.model,
|
||||
total,
|
||||
input: costPerMillion(item.inputCostMicrocents, item.inputTokens),
|
||||
output: costPerMillion(item.outputCostMicrocents, item.outputTokens + item.reasoningTokens),
|
||||
cached: costPerMillion(item.inputCostMicrocents, item.inputTokens + item.cacheReadTokens),
|
||||
},
|
||||
]
|
||||
})
|
||||
.toSorted((a, b) => a.total - b.total)
|
||||
}
|
||||
|
||||
function buildCacheRatio(rows: StatMetricRow[], product: TokenProduct, window: DateWindow) {
|
||||
return topModelsByUsage(rows, product, window)
|
||||
.flatMap((item) => {
|
||||
const total = item.inputTokens + item.cacheReadTokens
|
||||
if (total === 0) return []
|
||||
return [
|
||||
{
|
||||
model: item.model,
|
||||
ratio: round((item.cacheReadTokens / total) * 100, 1),
|
||||
cached: round(item.cacheReadTokens / 1_000_000_000, 1),
|
||||
uncached: round(item.inputTokens / 1_000_000_000, 1),
|
||||
total: round(total / 1_000_000_000, 1),
|
||||
},
|
||||
]
|
||||
})
|
||||
.toSorted((a, b) => b.ratio - a.ratio || b.cached - a.cached)
|
||||
}
|
||||
|
||||
function buildSessionCost(rows: StatMetricRow[], product: TokenProduct, window: DateWindow) {
|
||||
return topModelsByUsage(rows, product, window)
|
||||
.flatMap((item) => {
|
||||
if (item.sessions === 0) return []
|
||||
const cost = round(microcentsToDollars(item.totalCostMicrocents) / item.sessions, 4)
|
||||
if (cost === 0) return []
|
||||
return [{ model: item.model, cost, tokens: Math.round(item.totalTokens / item.sessions) }]
|
||||
})
|
||||
.toSorted((a, b) => a.cost - b.cost)
|
||||
}
|
||||
|
||||
function topModelsByUsage(rows: StatMetricRow[], product: TokenProduct, window: DateWindow) {
|
||||
return aggregateByModel(rowsForProduct(rows, product, window.start, window.end))
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens)
|
||||
.slice(0, METRIC_MODEL_LIMIT)
|
||||
}
|
||||
|
||||
function buildModelUsage(rows: StatMetricRow[], window: DateWindow, range: UsageRange) {
|
||||
return createBuckets(window, range).map((bucket) => {
|
||||
const aggregate = combineRowsForModel(
|
||||
"",
|
||||
rows.filter((row) => row.periodStart >= bucket.start && row.periodStart < bucket.end),
|
||||
)
|
||||
return {
|
||||
date: bucket.label,
|
||||
tokens: aggregate.totalTokens,
|
||||
sessions: aggregate.sessions,
|
||||
cost: round(microcentsToDollars(aggregate.totalCostMicrocents), 2),
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
function buildModelTokenMix(aggregate: ModelAggregate): ModelMixEntry[] {
|
||||
const items = [
|
||||
{ label: "Input", tokens: aggregate.inputTokens },
|
||||
{ label: "Output", tokens: aggregate.outputTokens },
|
||||
{ label: "Reasoning", tokens: aggregate.reasoningTokens },
|
||||
{ label: "Cached", tokens: aggregate.cacheReadTokens },
|
||||
].filter((item) => item.tokens > 0)
|
||||
const total = items.reduce((sum, item) => sum + item.tokens, 0)
|
||||
if (total === 0) return []
|
||||
return items.map((item) => ({ ...item, share: round((item.tokens / total) * 100, 1) }))
|
||||
}
|
||||
|
||||
function buildModelProductMix(
|
||||
rows: StatMetricRow[],
|
||||
window: DateWindow,
|
||||
fallback: ModelAggregate,
|
||||
): ModelProductEntry[] {
|
||||
const products = ["Go", "Zen", "Enterprise"] as const
|
||||
const items = products.flatMap((product) => {
|
||||
const aggregate = combineRowsForModel(
|
||||
fallback.model,
|
||||
rows.filter((row) => row.tier === product && row.periodStart >= window.start && row.periodStart < window.end),
|
||||
)
|
||||
if (aggregate.totalTokens === 0) return []
|
||||
return [{ product, tokens: aggregate.totalTokens, sessions: aggregate.sessions }]
|
||||
})
|
||||
const total = items.reduce((sum, item) => sum + item.tokens, 0)
|
||||
if (total > 0) return items.map((item) => ({ ...item, share: round((item.tokens / total) * 100, 1) }))
|
||||
if (fallback.totalTokens === 0) return []
|
||||
return [{ product: "All Users", tokens: fallback.totalTokens, sessions: fallback.sessions, share: 100 }]
|
||||
}
|
||||
|
||||
function buildModelPeers(peers: ModelAggregate[], rank: number, totalTokens: number): ModelPeerEntry[] {
|
||||
const start = Math.max(0, Math.min(rank - 4, Math.max(peers.length - 7, 0)))
|
||||
return peers.slice(start, start + 7).map((item, index) => ({
|
||||
model: item.model,
|
||||
provider: item.provider,
|
||||
author: formatProvider(item.provider),
|
||||
rank: start + index + 1,
|
||||
tokens: item.totalTokens,
|
||||
share: totalTokens > 0 ? round((item.totalTokens / totalTokens) * 100, 2) : 0,
|
||||
slug: modelSlug(item.model),
|
||||
}))
|
||||
}
|
||||
|
||||
function rowsForProduct<T extends { periodStart: number; tier: string }>(
|
||||
rows: T[],
|
||||
product: UsageProduct,
|
||||
start: number,
|
||||
end: number,
|
||||
) {
|
||||
const windowRows = rows.filter((row) => row.periodStart >= start && row.periodStart < end)
|
||||
if (product !== "All Users") return windowRows.filter((row) => row.tier === product)
|
||||
|
||||
const allRows = windowRows.filter((row) => row.tier === "all")
|
||||
if (allRows.length > 0) return allRows
|
||||
return windowRows.filter((row) => row.tier !== "all")
|
||||
}
|
||||
|
||||
function aggregateByModel(rows: StatMetricRow[]) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, ModelAggregate>>((result, row) => {
|
||||
const key = modelKey(row.provider, row.model)
|
||||
result[key] = combineModelAggregate(result[key], row)
|
||||
return result
|
||||
}, {}),
|
||||
)
|
||||
}
|
||||
|
||||
function aggregateByModelName(rows: StatMetricRow[]) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, ModelAggregate>>((result, row) => {
|
||||
result[row.model] = combineModelAggregate(result[row.model], row)
|
||||
return result
|
||||
}, {}),
|
||||
)
|
||||
}
|
||||
|
||||
function aggregateByProvider(rows: ProviderMetricRow[]) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, { provider: string; tokens: number }>>((result, row) => {
|
||||
result[row.provider] = {
|
||||
provider: row.provider,
|
||||
tokens: (result[row.provider]?.tokens ?? 0) + row.totalTokens,
|
||||
}
|
||||
return result
|
||||
}, {}),
|
||||
)
|
||||
}
|
||||
|
||||
function aggregateByCountry(rows: GeoMetricRow[]) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, { country: string; continent: string; tokens: number }>>((result, row) => {
|
||||
result[row.country] = {
|
||||
country: row.country,
|
||||
continent: result[row.country]?.continent || row.continent,
|
||||
tokens: (result[row.country]?.tokens ?? 0) + row.totalTokens,
|
||||
}
|
||||
return result
|
||||
}, {}),
|
||||
)
|
||||
}
|
||||
|
||||
function combineRowsForModel(model: string, rows: StatMetricRow[]): ModelAggregate {
|
||||
const aggregate = rows.reduce<ModelAggregate | undefined>(
|
||||
(result, row) => combineModelAggregate(result, row),
|
||||
undefined,
|
||||
)
|
||||
if (aggregate) return { ...aggregate, model: model || aggregate.model }
|
||||
return {
|
||||
model,
|
||||
provider: "unknown",
|
||||
sessions: 0,
|
||||
inputTokens: 0,
|
||||
outputTokens: 0,
|
||||
reasoningTokens: 0,
|
||||
cacheReadTokens: 0,
|
||||
totalTokens: 0,
|
||||
inputCostMicrocents: 0,
|
||||
outputCostMicrocents: 0,
|
||||
totalCostMicrocents: 0,
|
||||
}
|
||||
}
|
||||
|
||||
function combineModelAggregate(current: ModelAggregate | undefined, row: StatMetricRow): ModelAggregate {
|
||||
return {
|
||||
model: row.model,
|
||||
provider: row.provider,
|
||||
sessions: (current?.sessions ?? 0) + row.sessions,
|
||||
inputTokens: (current?.inputTokens ?? 0) + row.inputTokens,
|
||||
outputTokens: (current?.outputTokens ?? 0) + row.outputTokens,
|
||||
reasoningTokens: (current?.reasoningTokens ?? 0) + row.reasoningTokens,
|
||||
cacheReadTokens: (current?.cacheReadTokens ?? 0) + row.cacheReadTokens,
|
||||
totalTokens: (current?.totalTokens ?? 0) + row.totalTokens,
|
||||
inputCostMicrocents: (current?.inputCostMicrocents ?? 0) + row.inputCostMicrocents,
|
||||
outputCostMicrocents: (current?.outputCostMicrocents ?? 0) + row.outputCostMicrocents,
|
||||
totalCostMicrocents: (current?.totalCostMicrocents ?? 0) + row.totalCostMicrocents,
|
||||
}
|
||||
}
|
||||
|
||||
function getWindow(range: UsageRange, earliest: number, latest: number): DateWindow {
|
||||
const end = latest + DAY_MS
|
||||
const start = Math.max(
|
||||
earliest,
|
||||
range === "1D"
|
||||
? latest
|
||||
: range === "1W"
|
||||
? latest - 6 * DAY_MS
|
||||
: range === "2W"
|
||||
? latest - 13 * DAY_MS
|
||||
: range === "1M"
|
||||
? latest - 27 * DAY_MS
|
||||
: range === "2M"
|
||||
? latest - 55 * DAY_MS
|
||||
: range === "3M"
|
||||
? latest - 89 * DAY_MS
|
||||
: range === "YTD"
|
||||
? Date.UTC(new Date(latest).getUTCFullYear(), 0, 1)
|
||||
: earliest,
|
||||
)
|
||||
const duration = end - start
|
||||
return { start, end, previousStart: start - duration, previousEnd: start }
|
||||
}
|
||||
|
||||
function createBuckets(window: DateWindow, range: UsageRange): Bucket[] {
|
||||
const span = Math.max(window.end - window.start, DAY_MS)
|
||||
const count =
|
||||
range === "1D"
|
||||
? 1
|
||||
: range === "1W" || range === "2W" || range === "1M" || range === "2M" || range === "3M"
|
||||
? Math.ceil(span / DAY_MS)
|
||||
: Math.max(1, Math.min(7, Math.ceil(span / DAY_MS)))
|
||||
const size = span / count
|
||||
return Array.from({ length: count }, (_, index) => {
|
||||
const start = window.start + index * size
|
||||
const end = index === count - 1 ? window.end : window.start + (index + 1) * size
|
||||
return { start, end, label: formatBucketLabel(start, end, range) }
|
||||
})
|
||||
}
|
||||
|
||||
function createUsageProductRecord<T>(value: (product: UsageProduct) => T): Record<UsageProduct, T> {
|
||||
return {
|
||||
"All Users": value("All Users"),
|
||||
Zen: value("Zen"),
|
||||
Go: value("Go"),
|
||||
Enterprise: value("Enterprise"),
|
||||
}
|
||||
}
|
||||
|
||||
function createTokenProductRecord<T>(value: (product: TokenProduct) => T): Record<TokenProduct, T> {
|
||||
return {
|
||||
Zen: value("Zen"),
|
||||
Go: value("Go"),
|
||||
Enterprise: value("Enterprise"),
|
||||
}
|
||||
}
|
||||
|
||||
function createRangeRecord<T>(value: (range: UsageRange) => T): Record<UsageRange, T> {
|
||||
return {
|
||||
"1D": value("1D"),
|
||||
"1W": value("1W"),
|
||||
"2W": value("2W"),
|
||||
"1M": value("1M"),
|
||||
"2M": value("2M"),
|
||||
"3M": value("3M"),
|
||||
YTD: value("YTD"),
|
||||
ALL: value("ALL"),
|
||||
}
|
||||
}
|
||||
|
||||
function normalizeStatRow(row: ModelStatMetric): StatMetricRow[] {
|
||||
const periodStart = periodKeyTime(row.periodKey)
|
||||
const updatedAt = dateTime(row.updatedAt)
|
||||
if (!Number.isFinite(periodStart) || !Number.isFinite(updatedAt)) return []
|
||||
return [
|
||||
{
|
||||
...row,
|
||||
periodStart,
|
||||
updatedAt,
|
||||
tier: normalizeTier(row.tier),
|
||||
provider: row.provider || "unknown",
|
||||
model: row.model || "unknown",
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function normalizeProviderRow(row: ProviderStatMetric): ProviderMetricRow[] {
|
||||
const periodStart = periodKeyTime(row.periodKey)
|
||||
const updatedAt = dateTime(row.updatedAt)
|
||||
if (!Number.isFinite(periodStart) || !Number.isFinite(updatedAt)) return []
|
||||
return [
|
||||
{
|
||||
...row,
|
||||
periodStart,
|
||||
updatedAt,
|
||||
tier: normalizeTier(row.tier),
|
||||
provider: row.provider || "unknown",
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function normalizeGeoRow(row: GeoStatMetric): GeoMetricRow[] {
|
||||
const periodStart = periodKeyTime(row.periodKey)
|
||||
const updatedAt = dateTime(row.updatedAt)
|
||||
if (!Number.isFinite(periodStart) || !Number.isFinite(updatedAt)) return []
|
||||
return [
|
||||
{
|
||||
...row,
|
||||
periodStart,
|
||||
updatedAt,
|
||||
tier: normalizeTier(row.tier),
|
||||
provider: row.provider || "all",
|
||||
model: row.model || "all",
|
||||
country: row.country || "ZZ",
|
||||
continent: row.continent || "",
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function normalizeTier(value: string) {
|
||||
const normalized = value.toLowerCase()
|
||||
if (normalized === "paid" || normalized === "zen") return "Zen"
|
||||
if (normalized === "go") return "Go"
|
||||
if (normalized === "enterprise") return "Enterprise"
|
||||
if (normalized === "all") return "all"
|
||||
return value
|
||||
}
|
||||
|
||||
function dateTime(value: Date | string) {
|
||||
return (value instanceof Date ? value : new Date(value)).getTime()
|
||||
}
|
||||
|
||||
function periodKeyTime(value: string) {
|
||||
const match = /^(\d{4})-(\d{2})-(\d{2})$/.exec(value)
|
||||
if (!match) return Number.NaN
|
||||
return Date.UTC(Number(match[1]), Number(match[2]) - 1, Number(match[3]))
|
||||
}
|
||||
|
||||
function formatBucketLabel(start: number, _end: number, range: UsageRange) {
|
||||
const date = new Date(start)
|
||||
if (range === "YTD") return months[date.getUTCMonth()]
|
||||
if (range === "ALL")
|
||||
return date.getUTCFullYear() === new Date().getUTCFullYear()
|
||||
? months[date.getUTCMonth()]
|
||||
: String(date.getUTCFullYear())
|
||||
return formatDay(start)
|
||||
}
|
||||
|
||||
function formatDay(value: number) {
|
||||
const date = new Date(value)
|
||||
return `${months[date.getUTCMonth()]} ${date.getUTCDate()}`
|
||||
}
|
||||
|
||||
function formatProvider(provider: string) {
|
||||
const known: Record<string, string> = {
|
||||
anthropic: "Anthropic",
|
||||
deepseek: "DeepSeek",
|
||||
google: "Google",
|
||||
minimax: "MiniMax",
|
||||
moonshot: "Moonshot",
|
||||
moonshotai: "Moonshot",
|
||||
nvidia: "NVIDIA",
|
||||
opencode: "opencode",
|
||||
openai: "OpenAI",
|
||||
qwen: "Qwen",
|
||||
tencent: "Tencent",
|
||||
xai: "xAI",
|
||||
xiaomi: "Xiaomi",
|
||||
zhipu: "Zhipu",
|
||||
zhipuai: "Zhipu",
|
||||
}
|
||||
const normalized = provider.toLowerCase().replace(/[^a-z0-9]/g, "")
|
||||
return known[normalized] ?? provider.replace(/[-_]/g, " ").replace(/\b\w/g, (letter) => letter.toUpperCase())
|
||||
}
|
||||
|
||||
function resolveModelName(modelParam: string, rows: StatMetricRow[], providerParam?: string) {
|
||||
const input = modelParam.trim()
|
||||
if (!input) return undefined
|
||||
const normalizedInput = input.toLowerCase()
|
||||
const inputSlug = modelSlug(input)
|
||||
const candidates = providerParam
|
||||
? aggregateByModel(rows).filter((item) => providerMatches(item.provider, providerParam))
|
||||
: aggregateByModelName(rows)
|
||||
return candidates
|
||||
.filter((item) => item.model.toLowerCase() === normalizedInput || modelSlug(item.model) === inputSlug)
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens || a.model.localeCompare(b.model))[0]?.model
|
||||
}
|
||||
|
||||
function resolveModelProvider(model: string, rows: StatMetricRow[], providerParam?: string) {
|
||||
return aggregateByModel(rows)
|
||||
.filter((item) => item.model === model && (!providerParam || providerMatches(item.provider, providerParam)))
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens || a.provider.localeCompare(b.provider))[0]?.provider
|
||||
}
|
||||
|
||||
function providerMatches(provider: string, providerParam: string) {
|
||||
return modelSlug(provider) === modelSlug(providerParam)
|
||||
}
|
||||
|
||||
function resolveProviderName(providerParam: string, rows: StatMetricRow[]) {
|
||||
const input = providerParam.trim()
|
||||
if (!input) return undefined
|
||||
const inputSlug = modelSlug(input)
|
||||
return aggregateByModel(rows)
|
||||
.filter((item) => modelSlug(item.provider) === inputSlug)
|
||||
.toSorted((a, b) => b.totalTokens - a.totalTokens || a.provider.localeCompare(b.provider))[0]?.provider
|
||||
}
|
||||
|
||||
export function modelSlug(value: string) {
|
||||
return value
|
||||
.trim()
|
||||
.toLowerCase()
|
||||
.replace(/[^a-z0-9]+/g, "-")
|
||||
.replace(/^-+|-+$/g, "")
|
||||
.replace(/-{2,}/g, "-")
|
||||
}
|
||||
|
||||
function modelKey(provider: string, model: string) {
|
||||
return `${provider}\u0000${model}`
|
||||
}
|
||||
|
||||
function costPerMillion(costMicrocents: number, tokens: number) {
|
||||
if (tokens <= 0 || costMicrocents <= 0) return 0
|
||||
return round((microcentsToDollars(costMicrocents) / tokens) * TOKEN_SCALE, 2)
|
||||
}
|
||||
|
||||
function microcentsToDollars(value: number) {
|
||||
return value * DOLLARS_PER_MICROCENT
|
||||
}
|
||||
|
||||
function percentChange(current: number, previous: number) {
|
||||
if (previous <= 0) return current > 0 ? 100 : 0
|
||||
return Math.round(((current - previous) / previous) * 100)
|
||||
}
|
||||
|
||||
function leaderboardChange(current: number, previous: number) {
|
||||
if (current <= 0) return 0
|
||||
if (previous <= 0 || current >= previous * LEADERBOARD_CHANGE_MIN_MULTIPLE) return null
|
||||
return percentChange(current, previous)
|
||||
}
|
||||
|
||||
function round(value: number, digits: number) {
|
||||
return Number(value.toFixed(digits))
|
||||
}
|
||||
99
packages/stats/core/src/domain/inference.test.ts
Normal file
99
packages/stats/core/src/domain/inference.test.ts
Normal file
@@ -0,0 +1,99 @@
|
||||
import { describe, expect, test } from "bun:test"
|
||||
import { toGeoAggregate, toModelAggregate, toProviderAggregate } from "./inference"
|
||||
import { modelAuthor, normalizeInferenceModel, statModel, statProvider } from "./model-normalization"
|
||||
|
||||
describe("inference stat normalization", () => {
|
||||
test("normalizes model suffixes used by router/provider variants", () => {
|
||||
expect(normalizeInferenceModel("deepseek-v4-flash-free")).toBe("deepseek-v4-flash")
|
||||
expect(normalizeInferenceModel("deepseek-v4-flash:global")).toBe("deepseek-v4-flash")
|
||||
expect(normalizeInferenceModel("mimo-v2.5-free")).toBe("mimo-v2.5")
|
||||
expect(normalizeInferenceModel("nemotron-3-super-free")).toBe("nemotron-3-super")
|
||||
expect(normalizeInferenceModel("mimo-v2.5-free:global")).toBe("mimo-v2.5")
|
||||
})
|
||||
|
||||
test("maps normalized model ids to public authors", () => {
|
||||
expect(modelAuthor("big-pickle")).toBe("unknown")
|
||||
expect(modelAuthor("claude-sonnet-4-5")).toBe("anthropic")
|
||||
expect(modelAuthor("deepseek-v4-pro")).toBe("deepseek")
|
||||
expect(modelAuthor("gemini-3.5-flash")).toBe("google")
|
||||
expect(modelAuthor("glm-5.1")).toBe("zhipu")
|
||||
expect(modelAuthor("gpt-5.5-pro")).toBe("openai")
|
||||
expect(modelAuthor("grok-build-0.1")).toBe("xai")
|
||||
expect(modelAuthor("hy3-preview")).toBe("tencent")
|
||||
expect(modelAuthor("kimi-k2.6")).toBe("moonshot")
|
||||
expect(modelAuthor("mimo-v2-omni")).toBe("xiaomi")
|
||||
expect(modelAuthor("minimax-m2.7")).toBe("minimax")
|
||||
expect(modelAuthor("nemotron-3-super-free")).toBe("nvidia")
|
||||
expect(modelAuthor("qwen3.7-max")).toBe("qwen")
|
||||
expect(modelAuthor("alpha-gpt-next")).toBeUndefined()
|
||||
})
|
||||
|
||||
test("uses provider.model to resolve opencode route providers", () => {
|
||||
expect(statModel("big-pickle", "claude-sonnet-4-5")).toBe("claude-sonnet-4-5")
|
||||
expect(statModel("big-pickle", "gpt-5-free")).toBe("gpt-5")
|
||||
expect(statModel("big-pickle", "")).toBe("unknown")
|
||||
expect(statProvider("big-pickle", "claude-sonnet-4-5", "opencode")).toBe("anthropic")
|
||||
expect(statProvider("big-pickle", "gpt-5", "opencode")).toBe("openai")
|
||||
expect(statProvider("big-pickle", "", "opencode")).toBe("unknown")
|
||||
expect(statProvider("unknown", "", "custom-provider")).toBe("custom-provider")
|
||||
})
|
||||
|
||||
test("model aggregates prefer provider.model and use normalized model", () => {
|
||||
expect(toModelAggregate(aggregate("alpha-gpt-next", "openai"))).toEqual([])
|
||||
|
||||
expect(toModelAggregate(aggregate("deepseek-v4-flash-free", "not-public-provider"))).toMatchObject([
|
||||
{
|
||||
period_key: "2026-05-20",
|
||||
provider: "deepseek",
|
||||
model: "deepseek-v4-flash",
|
||||
},
|
||||
])
|
||||
|
||||
expect(
|
||||
toModelAggregate({ ...aggregate("big-pickle", "opencode"), provider_model: "claude-sonnet-4-5" }),
|
||||
).toMatchObject([
|
||||
{
|
||||
provider: "anthropic",
|
||||
model: "claude-sonnet-4-5",
|
||||
provider_model: "claude-sonnet-4-5",
|
||||
},
|
||||
])
|
||||
})
|
||||
|
||||
test("provider aggregates never keep opencode as the provider", () => {
|
||||
expect(toProviderAggregate({ ...aggregate("big-pickle", "opencode"), provider_model: "gpt-5" })).toMatchObject([
|
||||
{ provider: "openai" },
|
||||
])
|
||||
expect(toProviderAggregate(aggregate("big-pickle", "opencode"))).toMatchObject([{ provider: "unknown" }])
|
||||
})
|
||||
|
||||
test("geo aggregates never keep opencode or big-pickle dimensions", () => {
|
||||
expect(toGeoAggregate({ ...aggregate("big-pickle", "opencode"), country: "US" })).toMatchObject([
|
||||
{ provider: "unknown", model: "unknown", country: "US" },
|
||||
])
|
||||
})
|
||||
|
||||
test("model aggregates use ISO week period keys", () => {
|
||||
expect(
|
||||
toModelAggregate({
|
||||
...aggregate("gpt-5.5-pro", "openai"),
|
||||
grain: "week",
|
||||
period_key: "2026-W20",
|
||||
}),
|
||||
).toMatchObject([{ period_key: "2026-W20" }])
|
||||
})
|
||||
})
|
||||
|
||||
function aggregate(model: string, provider: string) {
|
||||
return {
|
||||
grain: "day",
|
||||
period_key: "2026-05-20",
|
||||
dataset: "zen",
|
||||
tier: "Paid",
|
||||
provider,
|
||||
model,
|
||||
sessions: "1",
|
||||
requests: "1",
|
||||
sample_count: "1",
|
||||
}
|
||||
}
|
||||
263
packages/stats/core/src/domain/inference.ts
Normal file
263
packages/stats/core/src/domain/inference.ts
Normal file
@@ -0,0 +1,263 @@
|
||||
import { Resource } from "sst/resource"
|
||||
import type { AthenaData } from "../athena"
|
||||
import type { GeoStatAggregate } from "./geo"
|
||||
import type { ModelStatAggregate } from "./model"
|
||||
import {
|
||||
EXCLUDED_MODELS,
|
||||
MODEL_AUTHOR_RULES,
|
||||
RETIRED_STAT_PROVIDERS,
|
||||
statModel,
|
||||
statProvider,
|
||||
} from "./model-normalization"
|
||||
import type { ProviderStatAggregate } from "./provider"
|
||||
import { normalizeCountry, normalizeTier, type StatBaseAggregate } from "./stat"
|
||||
|
||||
export type StatDimension = "model" | "provider" | "geo" | "geo_model"
|
||||
|
||||
export function buildStatsQuery(periodStart: Date, periodEnd: Date, dimension: StatDimension) {
|
||||
const periodStartValue = sqlString(periodStart.toISOString())
|
||||
const periodEndValue = sqlString(periodEnd.toISOString())
|
||||
const sourceTable = [Resource.InferenceEvent.catalog, Resource.InferenceEvent.database, Resource.InferenceEvent.table]
|
||||
.map(sqlIdentifier)
|
||||
.join(".")
|
||||
const dimensionSql = (() => {
|
||||
if (dimension === "model")
|
||||
return {
|
||||
select: "provider, model, COALESCE(MAX(NULLIF(provider_model, '')), '') AS provider_model",
|
||||
groupBy: "provider, model",
|
||||
}
|
||||
if (dimension === "provider") return { select: "provider", groupBy: "provider" }
|
||||
if (dimension === "geo_model")
|
||||
return {
|
||||
select: "provider, model, country, COALESCE(MAX(NULLIF(continent, '')), '') AS continent",
|
||||
groupBy: "provider, model, country",
|
||||
}
|
||||
return {
|
||||
select: "'all' AS provider, 'all' AS model, country, COALESCE(MAX(NULLIF(continent, '')), '') AS continent",
|
||||
groupBy: "country",
|
||||
}
|
||||
})()
|
||||
const aggregateColumns = `
|
||||
COUNT(DISTINCT session) AS sessions,
|
||||
COUNT(*) AS requests,
|
||||
COALESCE(SUM(tokens_input), 0) AS input_tokens,
|
||||
COALESCE(SUM(tokens_output), 0) AS output_tokens,
|
||||
COALESCE(SUM(tokens_reasoning), 0) AS reasoning_tokens,
|
||||
COALESCE(SUM(tokens_cache_read), 0) AS cache_read_tokens,
|
||||
COALESCE(SUM(tokens_total), 0) AS total_tokens,
|
||||
COALESCE(SUM(cost_input_microcents), 0) AS input_cost_microcents,
|
||||
COALESCE(SUM(cost_output_microcents), 0) AS output_cost_microcents,
|
||||
COALESCE(SUM(cost_total_microcents), 0) AS total_cost_microcents,
|
||||
AVG(duration_ms) AS avg_duration_ms,
|
||||
approx_percentile(CAST(duration_ms AS double), 0.5) AS p50_duration_ms,
|
||||
approx_percentile(CAST(duration_ms AS double), 0.95) AS p95_duration_ms,
|
||||
AVG(ttfb_ms) AS avg_ttfb_ms,
|
||||
approx_percentile(CAST(ttfb_ms AS double), 0.5) AS p50_ttfb_ms,
|
||||
approx_percentile(CAST(ttfb_ms AS double), 0.95) AS p95_ttfb_ms,
|
||||
AVG(output_tps) AS avg_output_tps,
|
||||
SUM(CASE WHEN status >= 200 AND status < 400 THEN 1 ELSE 0 END) AS success_count,
|
||||
SUM(CASE WHEN status >= 400 THEN 1 ELSE 0 END) AS error_count,
|
||||
COUNT(*) AS sample_count`
|
||||
|
||||
return `
|
||||
WITH normalized AS (
|
||||
SELECT
|
||||
from_iso8601_timestamp(event_timestamp) AS event_time,
|
||||
model AS raw_model,
|
||||
${statModelSql("model", "provider_model")} AS model,
|
||||
COALESCE(NULLIF(provider_model, ''), '') AS provider_model,
|
||||
COALESCE(NULLIF(provider, ''), '') AS raw_provider,
|
||||
UPPER(COALESCE(NULLIF(cf_country, ''), 'ZZ')) AS country,
|
||||
COALESCE(NULLIF(cf_continent, ''), '') AS continent,
|
||||
session,
|
||||
status,
|
||||
duration AS duration_ms,
|
||||
time_to_first_byte AS ttfb_ms,
|
||||
timestamp_first_byte,
|
||||
timestamp_last_byte,
|
||||
tokens_input,
|
||||
tokens_output,
|
||||
tokens_reasoning,
|
||||
tokens_cache_read,
|
||||
tokens_cache_write_5m,
|
||||
tokens_cache_write_1h,
|
||||
cost_input_microcents,
|
||||
cost_output_microcents,
|
||||
cost_total_microcents,
|
||||
cost_input,
|
||||
cost_output,
|
||||
cost_total,
|
||||
source
|
||||
FROM ${sourceTable}
|
||||
WHERE event_type = 'completions'
|
||||
AND model IS NOT NULL
|
||||
AND model <> ''
|
||||
AND event_timestamp >= ${periodStartValue}
|
||||
AND event_timestamp < ${periodEndValue}
|
||||
), filtered AS (
|
||||
SELECT
|
||||
event_time,
|
||||
CASE
|
||||
WHEN source = 'lite' THEN 'Go'
|
||||
WHEN raw_model IN ('gpt-5-nano', 'grok-code', 'big-pickle') OR regexp_like(raw_model, '-free(:global)?$') THEN 'Free'
|
||||
ELSE 'Paid'
|
||||
END AS tier,
|
||||
${statProviderSql("model", "provider_model", "raw_provider")} AS provider,
|
||||
provider_model,
|
||||
model,
|
||||
country,
|
||||
continent,
|
||||
session,
|
||||
status,
|
||||
duration_ms,
|
||||
ttfb_ms,
|
||||
CASE
|
||||
WHEN timestamp_last_byte - timestamp_first_byte < 100 THEN null
|
||||
ELSE CAST(tokens_output AS double) / (timestamp_last_byte - timestamp_first_byte) * 1000
|
||||
END AS output_tps,
|
||||
tokens_input,
|
||||
tokens_output,
|
||||
tokens_reasoning,
|
||||
tokens_cache_read,
|
||||
COALESCE(tokens_cache_read, 0) + COALESCE(tokens_cache_write_5m, 0) + COALESCE(tokens_cache_write_1h, 0) + COALESCE(tokens_input, 0) + COALESCE(tokens_output, 0) AS tokens_total,
|
||||
COALESCE(cost_input_microcents, cost_input * 1000000) AS cost_input_microcents,
|
||||
COALESCE(cost_output_microcents, cost_output * 1000000) AS cost_output_microcents,
|
||||
COALESCE(cost_total_microcents, cost_total * 1000000) AS cost_total_microcents
|
||||
FROM normalized
|
||||
WHERE lower(model) NOT IN (${[...EXCLUDED_MODELS].map(sqlString).join(", ")})
|
||||
), weekly AS (
|
||||
SELECT
|
||||
concat(CAST(year_of_week(event_time) AS varchar), '-W', lpad(CAST(week(event_time) AS varchar), 2, '0')) AS week_key,
|
||||
*
|
||||
FROM filtered
|
||||
), daily AS (
|
||||
SELECT substr(to_iso8601(date_trunc('day', event_time)), 1, 10) AS day_key, *
|
||||
FROM filtered
|
||||
)
|
||||
SELECT
|
||||
'week' AS grain,
|
||||
week_key AS period_key,
|
||||
${sqlString(Resource.StatsSyncConfig.dataset)} AS dataset,
|
||||
tier,
|
||||
${dimensionSql.select},
|
||||
${aggregateColumns}
|
||||
FROM weekly
|
||||
GROUP BY week_key, tier, ${dimensionSql.groupBy}
|
||||
UNION ALL
|
||||
SELECT
|
||||
'day' AS grain,
|
||||
day_key AS period_key,
|
||||
${sqlString(Resource.StatsSyncConfig.dataset)} AS dataset,
|
||||
tier,
|
||||
${dimensionSql.select},
|
||||
${aggregateColumns}
|
||||
FROM daily
|
||||
GROUP BY day_key, tier, ${dimensionSql.groupBy}
|
||||
ORDER BY grain, period_key, total_tokens DESC
|
||||
`
|
||||
}
|
||||
|
||||
export function toModelAggregate(data: AthenaData): ModelStatAggregate[] {
|
||||
const model = statModel(data.model, data.provider_model)
|
||||
const provider = statProvider(model, data.provider_model, data.provider)
|
||||
if (!provider) return []
|
||||
|
||||
return toStatBaseAggregate(data).flatMap((base) => [
|
||||
{ ...base, provider, model, provider_model: data.provider_model || "" },
|
||||
])
|
||||
}
|
||||
|
||||
export function toProviderAggregate(data: AthenaData): ProviderStatAggregate[] {
|
||||
return toStatBaseAggregate(data).flatMap((base) => [
|
||||
{ ...base, provider: statProvider(data.model, data.provider_model, data.provider) || "unknown" },
|
||||
])
|
||||
}
|
||||
|
||||
export function toGeoAggregate(data: AthenaData): GeoStatAggregate[] {
|
||||
return toStatBaseAggregate(data).flatMap((base) => [
|
||||
{
|
||||
...base,
|
||||
provider: statProvider(data.model, data.provider_model, data.provider) || "all",
|
||||
model: statModel(data.model || "all", data.provider_model),
|
||||
country: normalizeCountry(data.country),
|
||||
continent: data.continent || "",
|
||||
},
|
||||
])
|
||||
}
|
||||
|
||||
function toStatBaseAggregate(data: AthenaData): StatBaseAggregate[] {
|
||||
const grain = data.grain === "day" || data.grain === "week" ? data.grain : undefined
|
||||
if (!grain || !data.period_key) return []
|
||||
|
||||
return [
|
||||
{
|
||||
grain,
|
||||
period_key: data.period_key,
|
||||
dataset: data.dataset || Resource.StatsSyncConfig.dataset,
|
||||
tier: normalizeTier(data.tier || "unknown"),
|
||||
sessions: integer(data, "sessions"),
|
||||
requests: integer(data, "requests"),
|
||||
input_tokens: integer(data, "input_tokens"),
|
||||
output_tokens: integer(data, "output_tokens"),
|
||||
reasoning_tokens: integer(data, "reasoning_tokens"),
|
||||
cache_read_tokens: integer(data, "cache_read_tokens"),
|
||||
total_tokens: integer(data, "total_tokens"),
|
||||
input_cost_microcents: integer(data, "input_cost_microcents"),
|
||||
output_cost_microcents: integer(data, "output_cost_microcents"),
|
||||
total_cost_microcents: integer(data, "total_cost_microcents"),
|
||||
avg_duration_ms: nullableNumber(data, "avg_duration_ms"),
|
||||
p50_duration_ms: nullableInteger(data, "p50_duration_ms"),
|
||||
p95_duration_ms: nullableInteger(data, "p95_duration_ms"),
|
||||
avg_ttfb_ms: nullableNumber(data, "avg_ttfb_ms"),
|
||||
p50_ttfb_ms: nullableInteger(data, "p50_ttfb_ms"),
|
||||
p95_ttfb_ms: nullableInteger(data, "p95_ttfb_ms"),
|
||||
avg_output_tps: nullableNumber(data, "avg_output_tps"),
|
||||
success_count: integer(data, "success_count"),
|
||||
error_count: integer(data, "error_count"),
|
||||
sample_count: integer(data, "sample_count"),
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function integer(data: AthenaData, key: string) {
|
||||
return Math.round(number(data, key))
|
||||
}
|
||||
|
||||
function nullableNumber(data: AthenaData, key: string) {
|
||||
if (data[key] === undefined || data[key] === "") return null
|
||||
return Number(number(data, key).toFixed(2))
|
||||
}
|
||||
|
||||
function nullableInteger(data: AthenaData, key: string) {
|
||||
if (data[key] === undefined || data[key] === "") return null
|
||||
return Math.round(number(data, key))
|
||||
}
|
||||
|
||||
function number(data: AthenaData, key: string) {
|
||||
const value = Number(data[key])
|
||||
return Number.isFinite(value) ? value : 0
|
||||
}
|
||||
|
||||
function sqlIdentifier(value: string) {
|
||||
return `"${value.replace(/"/g, '""')}"`
|
||||
}
|
||||
|
||||
function sqlString(value: string) {
|
||||
return `'${value.replace(/'/g, "''")}'`
|
||||
}
|
||||
|
||||
function statModelSql(model: string, providerModel: string) {
|
||||
return `COALESCE(NULLIF(regexp_replace(CASE
|
||||
WHEN lower(${model}) = 'big-pickle' THEN NULLIF(${providerModel}, '')
|
||||
ELSE ${model}
|
||||
END, '(-free|:global)+$', ''), ''), 'unknown')`
|
||||
}
|
||||
|
||||
function statProviderSql(model: string, providerModel: string, provider: string) {
|
||||
return `CASE
|
||||
${MODEL_AUTHOR_RULES.map((item) => ` WHEN strpos(lower(${providerModel}), ${sqlString(item.match)}) > 0 THEN ${sqlString(item.author)}`).join("\n")}
|
||||
${MODEL_AUTHOR_RULES.map((item) => ` WHEN strpos(lower(${model}), ${sqlString(item.match)}) > 0 THEN ${sqlString(item.author)}`).join("\n")}
|
||||
WHEN ${provider} <> '' AND lower(${provider}) NOT IN (${RETIRED_STAT_PROVIDERS.map(sqlString).join(", ")}) THEN ${provider}
|
||||
ELSE 'unknown'
|
||||
END`
|
||||
}
|
||||
49
packages/stats/core/src/domain/model-normalization.ts
Normal file
49
packages/stats/core/src/domain/model-normalization.ts
Normal file
@@ -0,0 +1,49 @@
|
||||
export const MODEL_AUTHOR_RULES = [
|
||||
{ match: "claude", author: "anthropic" },
|
||||
{ match: "gemini", author: "google" },
|
||||
{ match: "deepseek", author: "deepseek" },
|
||||
{ match: "glm", author: "zhipu" },
|
||||
{ match: "gpt", author: "openai" },
|
||||
{ match: "grok", author: "xai" },
|
||||
{ match: "hy3", author: "tencent" },
|
||||
{ match: "kimi", author: "moonshot" },
|
||||
{ match: "mimo", author: "xiaomi" },
|
||||
{ match: "minimax", author: "minimax" },
|
||||
{ match: "nemotron", author: "nvidia" },
|
||||
{ match: "qwen", author: "qwen" },
|
||||
] as const
|
||||
export const EXCLUDED_MODELS = new Set(["alpha-gpt-next"])
|
||||
export const RETIRED_STAT_MODELS = ["big-pickle"]
|
||||
export const RETIRED_STAT_PROVIDERS = ["opencode"]
|
||||
|
||||
export function normalizeInferenceModel(value: string | undefined) {
|
||||
return (value || "unknown").replace(/(-free|:global)+$/, "") || "unknown"
|
||||
}
|
||||
|
||||
export function modelAuthor(value: string | undefined) {
|
||||
const model = normalizeInferenceModel(value).toLowerCase()
|
||||
if (EXCLUDED_MODELS.has(model)) return undefined
|
||||
|
||||
return MODEL_AUTHOR_RULES.find((item) => model.includes(item.match))?.author ?? "unknown"
|
||||
}
|
||||
|
||||
export function statModel(model: string | undefined, providerModel: string | undefined) {
|
||||
const normalized = normalizeInferenceModel(model)
|
||||
if (RETIRED_STAT_MODELS.includes(normalized.toLowerCase())) return normalizeInferenceModel(providerModel)
|
||||
return normalized
|
||||
}
|
||||
|
||||
export function statProvider(
|
||||
model: string | undefined,
|
||||
providerModel: string | undefined,
|
||||
provider: string | undefined,
|
||||
) {
|
||||
const modelAuthorValue = modelAuthor(statModel(model, providerModel))
|
||||
if (!modelAuthorValue) return undefined
|
||||
|
||||
const providerModelAuthor = modelAuthor(providerModel)
|
||||
if (providerModelAuthor && providerModelAuthor !== "unknown") return providerModelAuthor
|
||||
if (modelAuthorValue !== "unknown") return modelAuthorValue
|
||||
if (provider && !RETIRED_STAT_PROVIDERS.includes(provider.toLowerCase())) return provider
|
||||
return modelAuthorValue
|
||||
}
|
||||
202
packages/stats/core/src/domain/model.ts
Normal file
202
packages/stats/core/src/domain/model.ts
Normal file
@@ -0,0 +1,202 @@
|
||||
import { and, asc, eq, inArray, or } from "drizzle-orm"
|
||||
import { Effect, Layer } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import { DatabaseError, DrizzleClient } from "../database"
|
||||
import { modelStat } from "../database/schema"
|
||||
import { RETIRED_STAT_MODELS, RETIRED_STAT_PROVIDERS } from "./model-normalization"
|
||||
import {
|
||||
chunks,
|
||||
collapseRows,
|
||||
inserted,
|
||||
rankBy,
|
||||
statPeriodKey,
|
||||
statRowScope,
|
||||
synthesizeAllTierRows,
|
||||
toStatBaseRow,
|
||||
UPSERT_CHUNK_SIZE,
|
||||
type StatBaseAggregate,
|
||||
} from "./stat"
|
||||
|
||||
export type ModelStatRow = typeof modelStat.$inferInsert
|
||||
export type ModelStatAggregate = StatBaseAggregate & { provider: string; model: string; provider_model: string }
|
||||
|
||||
export type ModelStatMetric = {
|
||||
periodKey: string
|
||||
updatedAt: Date
|
||||
tier: string
|
||||
provider: string
|
||||
model: string
|
||||
sessions: number
|
||||
inputTokens: number
|
||||
outputTokens: number
|
||||
reasoningTokens: number
|
||||
cacheReadTokens: number
|
||||
totalTokens: number
|
||||
inputCostMicrocents: number
|
||||
outputCostMicrocents: number
|
||||
totalCostMicrocents: number
|
||||
}
|
||||
|
||||
export declare namespace ModelStatRepo {
|
||||
export interface Service {
|
||||
readonly listDaily: () => Effect.Effect<ModelStatMetric[], DatabaseError>
|
||||
readonly upsert: (rows: ModelStatRow[]) => Effect.Effect<void, DatabaseError>
|
||||
readonly deleteRetiredDimensions: (rows: ModelStatRow[]) => Effect.Effect<void, DatabaseError>
|
||||
}
|
||||
}
|
||||
|
||||
export class ModelStatRepo extends Context.Service<ModelStatRepo, ModelStatRepo.Service>()(
|
||||
"@opencode/stats/ModelStatRepo",
|
||||
) {
|
||||
static readonly layer: Layer.Layer<ModelStatRepo, never, DrizzleClient> = Layer.effect(
|
||||
ModelStatRepo,
|
||||
Effect.gen(function* () {
|
||||
const db = yield* DrizzleClient
|
||||
|
||||
const listDaily = Effect.fn("ModelStatRepo.listDaily")(function* () {
|
||||
return yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.select({
|
||||
periodKey: modelStat.period_key,
|
||||
updatedAt: modelStat.updated_at,
|
||||
tier: modelStat.tier,
|
||||
provider: modelStat.provider,
|
||||
model: modelStat.model,
|
||||
sessions: modelStat.sessions,
|
||||
inputTokens: modelStat.input_tokens,
|
||||
outputTokens: modelStat.output_tokens,
|
||||
reasoningTokens: modelStat.reasoning_tokens,
|
||||
cacheReadTokens: modelStat.cache_read_tokens,
|
||||
totalTokens: modelStat.total_tokens,
|
||||
inputCostMicrocents: modelStat.input_cost_microcents,
|
||||
outputCostMicrocents: modelStat.output_cost_microcents,
|
||||
totalCostMicrocents: modelStat.total_cost_microcents,
|
||||
})
|
||||
.from(modelStat)
|
||||
.where(and(eq(modelStat.grain, "day"), eq(modelStat.client, "all"), eq(modelStat.source, "all")))
|
||||
.orderBy(asc(modelStat.period_key)),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
const upsert = Effect.fn("ModelStatRepo.upsert")(function* (rows: ModelStatRow[]) {
|
||||
yield* Effect.forEach(
|
||||
chunks(rows, UPSERT_CHUNK_SIZE),
|
||||
(chunk) =>
|
||||
Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.insert(modelStat)
|
||||
.values(chunk)
|
||||
.onDuplicateKeyUpdate({
|
||||
set: {
|
||||
provider_model: inserted("provider_model"),
|
||||
sessions: inserted("sessions"),
|
||||
requests: inserted("requests"),
|
||||
input_tokens: inserted("input_tokens"),
|
||||
output_tokens: inserted("output_tokens"),
|
||||
reasoning_tokens: inserted("reasoning_tokens"),
|
||||
cache_read_tokens: inserted("cache_read_tokens"),
|
||||
total_tokens: inserted("total_tokens"),
|
||||
input_cost_microcents: inserted("input_cost_microcents"),
|
||||
output_cost_microcents: inserted("output_cost_microcents"),
|
||||
total_cost_microcents: inserted("total_cost_microcents"),
|
||||
avg_duration_ms: inserted("avg_duration_ms"),
|
||||
p50_duration_ms: inserted("p50_duration_ms"),
|
||||
p95_duration_ms: inserted("p95_duration_ms"),
|
||||
avg_ttfb_ms: inserted("avg_ttfb_ms"),
|
||||
p50_ttfb_ms: inserted("p50_ttfb_ms"),
|
||||
p95_ttfb_ms: inserted("p95_ttfb_ms"),
|
||||
avg_output_tps: inserted("avg_output_tps"),
|
||||
success_count: inserted("success_count"),
|
||||
error_count: inserted("error_count"),
|
||||
sample_count: inserted("sample_count"),
|
||||
rank_by_tokens: inserted("rank_by_tokens"),
|
||||
rank_by_requests: inserted("rank_by_requests"),
|
||||
rank_by_cost: inserted("rank_by_cost"),
|
||||
},
|
||||
}),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
}),
|
||||
{ discard: true },
|
||||
)
|
||||
})
|
||||
|
||||
const deleteRetiredDimensions = Effect.fn("ModelStatRepo.deleteRetiredDimensions")(function* (
|
||||
rows: ModelStatRow[],
|
||||
) {
|
||||
const scope = statRowScope(rows)
|
||||
if (!scope) return
|
||||
|
||||
yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.delete(modelStat)
|
||||
.where(
|
||||
and(
|
||||
inArray(modelStat.grain, scope.grains),
|
||||
inArray(modelStat.period_key, scope.periodKeys),
|
||||
inArray(modelStat.dataset, scope.datasets),
|
||||
inArray(modelStat.client, scope.clients),
|
||||
inArray(modelStat.source, scope.sources),
|
||||
or(
|
||||
inArray(modelStat.provider, RETIRED_STAT_PROVIDERS),
|
||||
inArray(modelStat.model, RETIRED_STAT_MODELS),
|
||||
),
|
||||
),
|
||||
),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
return ModelStatRepo.of({ listDaily, upsert, deleteRetiredDimensions })
|
||||
}),
|
||||
)
|
||||
}
|
||||
|
||||
export function rowsFromAggregates(aggregates: ModelStatAggregate[]) {
|
||||
return rankRows([
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "week").map(toRow), dimensionKey),
|
||||
dimensionKey,
|
||||
),
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "day").map(toRow), dimensionKey),
|
||||
dimensionKey,
|
||||
),
|
||||
])
|
||||
}
|
||||
|
||||
function toRow(data: ModelStatAggregate): ModelStatRow {
|
||||
return {
|
||||
...toStatBaseRow(data),
|
||||
provider: data.provider,
|
||||
model: data.model,
|
||||
provider_model: data.provider_model,
|
||||
}
|
||||
}
|
||||
|
||||
function rankRows(rows: ModelStatRow[]) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, ModelStatRow[]>>((result, row) => {
|
||||
const key = statPeriodKey(row)
|
||||
result[key] = [...(result[key] ?? []), row]
|
||||
return result
|
||||
}, {}),
|
||||
).flatMap((group) => {
|
||||
const tokenRanks = rankBy(group, (row) => row.total_tokens ?? 0)
|
||||
const requestRanks = rankBy(group, (row) => row.requests ?? 0)
|
||||
const costRanks = rankBy(group, (row) => row.total_cost_microcents ?? 0)
|
||||
return group.map((row) => ({
|
||||
...row,
|
||||
rank_by_tokens: tokenRanks.get(row) ?? null,
|
||||
rank_by_requests: requestRanks.get(row) ?? null,
|
||||
rank_by_cost: costRanks.get(row) ?? null,
|
||||
}))
|
||||
})
|
||||
}
|
||||
|
||||
function dimensionKey(row: ModelStatRow) {
|
||||
return [row.provider, row.model].join("\u0000")
|
||||
}
|
||||
195
packages/stats/core/src/domain/provider.ts
Normal file
195
packages/stats/core/src/domain/provider.ts
Normal file
@@ -0,0 +1,195 @@
|
||||
import { and, asc, eq, inArray } from "drizzle-orm"
|
||||
import { Effect, Layer } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import { DatabaseError, DrizzleClient } from "../database"
|
||||
import { providerStat } from "../database/schema"
|
||||
import { RETIRED_STAT_PROVIDERS } from "./model-normalization"
|
||||
import {
|
||||
chunks,
|
||||
collapseRows,
|
||||
inserted,
|
||||
rankRowsWithMarketShare,
|
||||
statRowScope,
|
||||
synthesizeAllTierRows,
|
||||
toStatBaseRow,
|
||||
UPSERT_CHUNK_SIZE,
|
||||
type StatBaseAggregate,
|
||||
} from "./stat"
|
||||
|
||||
export type ProviderStatRow = typeof providerStat.$inferInsert
|
||||
export type ProviderStatAggregate = StatBaseAggregate & { provider: string }
|
||||
export type ProviderStatMetric = {
|
||||
periodKey: string
|
||||
updatedAt: Date
|
||||
tier: string
|
||||
provider: string
|
||||
totalTokens: number
|
||||
}
|
||||
|
||||
export declare namespace ProviderStatRepo {
|
||||
export interface Service {
|
||||
readonly listDaily: () => Effect.Effect<ProviderStatMetric[], DatabaseError>
|
||||
readonly listByPeriod: (opts: {
|
||||
readonly grain: string
|
||||
readonly periodKey: string
|
||||
readonly dataset?: string
|
||||
readonly tier?: string
|
||||
readonly client?: string
|
||||
readonly source?: string
|
||||
}) => Effect.Effect<ProviderStatRow[], DatabaseError>
|
||||
readonly upsert: (rows: ProviderStatRow[]) => Effect.Effect<void, DatabaseError>
|
||||
readonly deleteRetiredDimensions: (rows: ProviderStatRow[]) => Effect.Effect<void, DatabaseError>
|
||||
}
|
||||
}
|
||||
|
||||
export class ProviderStatRepo extends Context.Service<ProviderStatRepo, ProviderStatRepo.Service>()(
|
||||
"@opencode/stats/ProviderStatRepo",
|
||||
) {
|
||||
static readonly layer: Layer.Layer<ProviderStatRepo, never, DrizzleClient> = Layer.effect(
|
||||
ProviderStatRepo,
|
||||
Effect.gen(function* () {
|
||||
const db = yield* DrizzleClient
|
||||
|
||||
const listDaily = Effect.fn("ProviderStatRepo.listDaily")(function* () {
|
||||
return yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.select({
|
||||
periodKey: providerStat.period_key,
|
||||
updatedAt: providerStat.updated_at,
|
||||
tier: providerStat.tier,
|
||||
provider: providerStat.provider,
|
||||
totalTokens: providerStat.total_tokens,
|
||||
})
|
||||
.from(providerStat)
|
||||
.where(and(eq(providerStat.grain, "day"), eq(providerStat.client, "all"), eq(providerStat.source, "all")))
|
||||
.orderBy(asc(providerStat.period_key)),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
const listByPeriod = Effect.fn("ProviderStatRepo.listByPeriod")(function* (opts: {
|
||||
readonly grain: string
|
||||
readonly periodKey: string
|
||||
readonly dataset?: string
|
||||
readonly tier?: string
|
||||
readonly client?: string
|
||||
readonly source?: string
|
||||
}) {
|
||||
return yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.select()
|
||||
.from(providerStat)
|
||||
.where(
|
||||
and(
|
||||
eq(providerStat.grain, opts.grain),
|
||||
eq(providerStat.period_key, opts.periodKey),
|
||||
eq(providerStat.dataset, opts.dataset ?? "zen"),
|
||||
eq(providerStat.tier, opts.tier ?? "all"),
|
||||
eq(providerStat.client, opts.client ?? "all"),
|
||||
eq(providerStat.source, opts.source ?? "all"),
|
||||
),
|
||||
),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
const upsert = Effect.fn("ProviderStatRepo.upsert")(function* (rows: ProviderStatRow[]) {
|
||||
yield* Effect.forEach(
|
||||
chunks(rows, UPSERT_CHUNK_SIZE),
|
||||
(chunk) =>
|
||||
Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.insert(providerStat)
|
||||
.values(chunk)
|
||||
.onDuplicateKeyUpdate({
|
||||
set: {
|
||||
sessions: inserted("sessions"),
|
||||
requests: inserted("requests"),
|
||||
input_tokens: inserted("input_tokens"),
|
||||
output_tokens: inserted("output_tokens"),
|
||||
reasoning_tokens: inserted("reasoning_tokens"),
|
||||
cache_read_tokens: inserted("cache_read_tokens"),
|
||||
total_tokens: inserted("total_tokens"),
|
||||
input_cost_microcents: inserted("input_cost_microcents"),
|
||||
output_cost_microcents: inserted("output_cost_microcents"),
|
||||
total_cost_microcents: inserted("total_cost_microcents"),
|
||||
avg_duration_ms: inserted("avg_duration_ms"),
|
||||
p50_duration_ms: inserted("p50_duration_ms"),
|
||||
p95_duration_ms: inserted("p95_duration_ms"),
|
||||
avg_ttfb_ms: inserted("avg_ttfb_ms"),
|
||||
p50_ttfb_ms: inserted("p50_ttfb_ms"),
|
||||
p95_ttfb_ms: inserted("p95_ttfb_ms"),
|
||||
avg_output_tps: inserted("avg_output_tps"),
|
||||
success_count: inserted("success_count"),
|
||||
error_count: inserted("error_count"),
|
||||
sample_count: inserted("sample_count"),
|
||||
market_share_tokens: inserted("market_share_tokens"),
|
||||
market_share_requests: inserted("market_share_requests"),
|
||||
market_share_sessions: inserted("market_share_sessions"),
|
||||
rank_by_tokens: inserted("rank_by_tokens"),
|
||||
rank_by_requests: inserted("rank_by_requests"),
|
||||
rank_by_sessions: inserted("rank_by_sessions"),
|
||||
rank_by_cost: inserted("rank_by_cost"),
|
||||
},
|
||||
}),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
}),
|
||||
{ discard: true },
|
||||
)
|
||||
})
|
||||
|
||||
const deleteRetiredDimensions = Effect.fn("ProviderStatRepo.deleteRetiredDimensions")(function* (
|
||||
rows: ProviderStatRow[],
|
||||
) {
|
||||
const scope = statRowScope(rows)
|
||||
if (!scope) return
|
||||
|
||||
yield* Effect.tryPromise({
|
||||
try: () =>
|
||||
db
|
||||
.delete(providerStat)
|
||||
.where(
|
||||
and(
|
||||
inArray(providerStat.grain, scope.grains),
|
||||
inArray(providerStat.period_key, scope.periodKeys),
|
||||
inArray(providerStat.dataset, scope.datasets),
|
||||
inArray(providerStat.client, scope.clients),
|
||||
inArray(providerStat.source, scope.sources),
|
||||
inArray(providerStat.provider, RETIRED_STAT_PROVIDERS),
|
||||
),
|
||||
),
|
||||
catch: (cause) => DatabaseError.make({ cause }),
|
||||
})
|
||||
})
|
||||
|
||||
return ProviderStatRepo.of({ listDaily, listByPeriod, upsert, deleteRetiredDimensions })
|
||||
}),
|
||||
)
|
||||
}
|
||||
|
||||
export function rowsFromAggregates(aggregates: ProviderStatAggregate[]) {
|
||||
return rankRowsWithMarketShare([
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "week").map(toRow), dimensionKey),
|
||||
dimensionKey,
|
||||
),
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "day").map(toRow), dimensionKey),
|
||||
dimensionKey,
|
||||
),
|
||||
])
|
||||
}
|
||||
|
||||
function toRow(data: ProviderStatAggregate): ProviderStatRow {
|
||||
return {
|
||||
...toStatBaseRow(data),
|
||||
provider: data.provider,
|
||||
}
|
||||
}
|
||||
|
||||
function dimensionKey(row: ProviderStatRow) {
|
||||
return row.provider
|
||||
}
|
||||
261
packages/stats/core/src/domain/stat.ts
Normal file
261
packages/stats/core/src/domain/stat.ts
Normal file
@@ -0,0 +1,261 @@
|
||||
import { sql } from "drizzle-orm"
|
||||
|
||||
export const UPSERT_CHUNK_SIZE = 500
|
||||
const DAY_MS = 86_400_000
|
||||
|
||||
export type StatGrain = "day" | "week"
|
||||
|
||||
export type StatBaseAggregate = {
|
||||
grain: StatGrain
|
||||
period_key: string
|
||||
dataset: string
|
||||
tier: string
|
||||
sessions: number
|
||||
requests: number
|
||||
input_tokens: number
|
||||
output_tokens: number
|
||||
reasoning_tokens: number
|
||||
cache_read_tokens: number
|
||||
total_tokens: number
|
||||
input_cost_microcents: number
|
||||
output_cost_microcents: number
|
||||
total_cost_microcents: number
|
||||
avg_duration_ms: number | null
|
||||
p50_duration_ms: number | null
|
||||
p95_duration_ms: number | null
|
||||
avg_ttfb_ms: number | null
|
||||
p50_ttfb_ms: number | null
|
||||
p95_ttfb_ms: number | null
|
||||
avg_output_tps: number | null
|
||||
success_count: number
|
||||
error_count: number
|
||||
sample_count: number
|
||||
}
|
||||
|
||||
export type StatBaseRow = {
|
||||
grain: string
|
||||
period_key: string
|
||||
dataset?: string
|
||||
tier?: string
|
||||
client?: string
|
||||
source?: string
|
||||
sessions?: number
|
||||
requests?: number
|
||||
input_tokens?: number
|
||||
output_tokens?: number
|
||||
reasoning_tokens?: number
|
||||
cache_read_tokens?: number
|
||||
total_tokens?: number
|
||||
input_cost_microcents?: number
|
||||
output_cost_microcents?: number
|
||||
total_cost_microcents?: number
|
||||
avg_duration_ms?: number | null
|
||||
p50_duration_ms?: number | null
|
||||
p95_duration_ms?: number | null
|
||||
avg_ttfb_ms?: number | null
|
||||
p50_ttfb_ms?: number | null
|
||||
p95_ttfb_ms?: number | null
|
||||
avg_output_tps?: number | null
|
||||
success_count?: number
|
||||
error_count?: number
|
||||
sample_count?: number
|
||||
}
|
||||
|
||||
export function toStatBaseRow(data: StatBaseAggregate) {
|
||||
return {
|
||||
grain: data.grain,
|
||||
period_key: data.period_key,
|
||||
dataset: data.dataset,
|
||||
tier: data.tier,
|
||||
client: "all",
|
||||
source: "all",
|
||||
sessions: data.sessions,
|
||||
requests: data.requests,
|
||||
input_tokens: data.input_tokens,
|
||||
output_tokens: data.output_tokens,
|
||||
reasoning_tokens: data.reasoning_tokens,
|
||||
cache_read_tokens: data.cache_read_tokens,
|
||||
total_tokens: data.total_tokens,
|
||||
input_cost_microcents: data.input_cost_microcents,
|
||||
output_cost_microcents: data.output_cost_microcents,
|
||||
total_cost_microcents: data.total_cost_microcents,
|
||||
avg_duration_ms: data.avg_duration_ms,
|
||||
p50_duration_ms: data.p50_duration_ms,
|
||||
p95_duration_ms: data.p95_duration_ms,
|
||||
avg_ttfb_ms: data.avg_ttfb_ms,
|
||||
p50_ttfb_ms: data.p50_ttfb_ms,
|
||||
p95_ttfb_ms: data.p95_ttfb_ms,
|
||||
avg_output_tps: data.avg_output_tps,
|
||||
success_count: data.success_count,
|
||||
error_count: data.error_count,
|
||||
sample_count: data.sample_count,
|
||||
}
|
||||
}
|
||||
|
||||
export function synthesizeAllTierRows<T extends StatBaseRow>(rows: T[], dimensionKey: (row: T) => string) {
|
||||
return [
|
||||
...rows,
|
||||
...Object.values(
|
||||
rows.reduce<Record<string, T>>((result, row) => {
|
||||
const key = [row.grain, row.period_key, row.dataset, row.client, row.source, dimensionKey(row)].join("\u0000")
|
||||
result[key] = result[key] ? combineRows(result[key], row) : { ...row, tier: "all" }
|
||||
return result
|
||||
}, {}),
|
||||
),
|
||||
]
|
||||
}
|
||||
|
||||
export function collapseRows<T extends StatBaseRow>(rows: T[], dimensionKey: (row: T) => string) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, T>>((result, row) => {
|
||||
const key = [row.grain, row.period_key, row.dataset, row.tier, row.client, row.source, dimensionKey(row)].join(
|
||||
"\u0000",
|
||||
)
|
||||
result[key] = result[key] ? combineRows(result[key], row) : row
|
||||
return result
|
||||
}, {}),
|
||||
)
|
||||
}
|
||||
|
||||
export function combineRows<T extends StatBaseRow>(left: T, right: T): T {
|
||||
return {
|
||||
...left,
|
||||
sessions: (left.sessions ?? 0) + (right.sessions ?? 0),
|
||||
requests: (left.requests ?? 0) + (right.requests ?? 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),
|
||||
cache_read_tokens: (left.cache_read_tokens ?? 0) + (right.cache_read_tokens ?? 0),
|
||||
total_tokens: (left.total_tokens ?? 0) + (right.total_tokens ?? 0),
|
||||
input_cost_microcents: (left.input_cost_microcents ?? 0) + (right.input_cost_microcents ?? 0),
|
||||
output_cost_microcents: (left.output_cost_microcents ?? 0) + (right.output_cost_microcents ?? 0),
|
||||
total_cost_microcents: (left.total_cost_microcents ?? 0) + (right.total_cost_microcents ?? 0),
|
||||
avg_duration_ms: weightedAverage(left.avg_duration_ms, left.requests, right.avg_duration_ms, right.requests),
|
||||
p50_duration_ms: null,
|
||||
p95_duration_ms: null,
|
||||
avg_ttfb_ms: weightedAverage(left.avg_ttfb_ms, left.requests, right.avg_ttfb_ms, right.requests),
|
||||
p50_ttfb_ms: null,
|
||||
p95_ttfb_ms: null,
|
||||
avg_output_tps: weightedAverage(left.avg_output_tps, left.requests, right.avg_output_tps, right.requests),
|
||||
success_count: (left.success_count ?? 0) + (right.success_count ?? 0),
|
||||
error_count: (left.error_count ?? 0) + (right.error_count ?? 0),
|
||||
sample_count: (left.sample_count ?? 0) + (right.sample_count ?? 0),
|
||||
}
|
||||
}
|
||||
|
||||
export function statPeriodKey(row: StatBaseRow) {
|
||||
return [row.grain, row.period_key, row.dataset, row.tier, row.client, row.source].join("\u0000")
|
||||
}
|
||||
|
||||
export function statRowScope(rows: StatBaseRow[]) {
|
||||
if (rows.length === 0) return
|
||||
return {
|
||||
grains: unique(rows.map((row) => row.grain)),
|
||||
periodKeys: unique(rows.map((row) => row.period_key)),
|
||||
datasets: unique(rows.map((row) => row.dataset ?? "all")),
|
||||
clients: unique(rows.map((row) => row.client ?? "all")),
|
||||
sources: unique(rows.map((row) => row.source ?? "all")),
|
||||
}
|
||||
}
|
||||
|
||||
export function periodKeyFor(grain: StatGrain, periodStart: Date) {
|
||||
if (grain === "week") return isoWeekId(periodStart)
|
||||
return utcDateId(periodStart)
|
||||
}
|
||||
|
||||
export function startOfUtcDay(value: Date) {
|
||||
return new Date(Date.UTC(value.getUTCFullYear(), value.getUTCMonth(), value.getUTCDate()))
|
||||
}
|
||||
|
||||
export function startOfIsoWeek(value: Date) {
|
||||
return new Date(
|
||||
Date.UTC(value.getUTCFullYear(), value.getUTCMonth(), value.getUTCDate() - (value.getUTCDay() || 7) + 1),
|
||||
)
|
||||
}
|
||||
|
||||
export function isoWeekId(value: Date) {
|
||||
const thursday = new Date(
|
||||
Date.UTC(value.getUTCFullYear(), value.getUTCMonth(), value.getUTCDate() + 4 - (value.getUTCDay() || 7)),
|
||||
)
|
||||
return `${thursday.getUTCFullYear()}-W${String(Math.ceil(((thursday.getTime() - Date.UTC(thursday.getUTCFullYear(), 0, 1)) / DAY_MS + 1) / 7)).padStart(2, "0")}`
|
||||
}
|
||||
|
||||
function utcDateId(value: Date) {
|
||||
return `${value.getUTCFullYear()}-${String(value.getUTCMonth() + 1).padStart(2, "0")}-${String(value.getUTCDate()).padStart(2, "0")}`
|
||||
}
|
||||
|
||||
export function rankBy<T extends StatBaseRow>(rows: T[], value: (row: T) => number) {
|
||||
return new Map(rows.toSorted((a, b) => value(b) - value(a)).map((row, index) => [row, index + 1]))
|
||||
}
|
||||
|
||||
export function rankRowsWithMarketShare<T extends StatBaseRow>(
|
||||
rows: T[],
|
||||
groupKey: (row: T) => string = statPeriodKey,
|
||||
) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, T[]>>((result, row) => {
|
||||
const key = groupKey(row)
|
||||
result[key] = [...(result[key] ?? []), row]
|
||||
return result
|
||||
}, {}),
|
||||
).flatMap((group) => {
|
||||
const tokens = group.reduce((sum, row) => sum + (row.total_tokens ?? 0), 0)
|
||||
const requests = group.reduce((sum, row) => sum + (row.requests ?? 0), 0)
|
||||
const sessions = group.reduce((sum, row) => sum + (row.sessions ?? 0), 0)
|
||||
const tokenRanks = rankBy(group, (row) => row.total_tokens ?? 0)
|
||||
const requestRanks = rankBy(group, (row) => row.requests ?? 0)
|
||||
const sessionRanks = rankBy(group, (row) => row.sessions ?? 0)
|
||||
const costRanks = rankBy(group, (row) => row.total_cost_microcents ?? 0)
|
||||
return group.map((row) => ({
|
||||
...row,
|
||||
market_share_tokens: share(row.total_tokens, tokens),
|
||||
market_share_requests: share(row.requests, requests),
|
||||
market_share_sessions: share(row.sessions, sessions),
|
||||
rank_by_tokens: tokenRanks.get(row) ?? null,
|
||||
rank_by_requests: requestRanks.get(row) ?? null,
|
||||
rank_by_sessions: sessionRanks.get(row) ?? null,
|
||||
rank_by_cost: costRanks.get(row) ?? null,
|
||||
}))
|
||||
})
|
||||
}
|
||||
|
||||
export function share(value: number | null | undefined, total: number) {
|
||||
if (total <= 0) return null
|
||||
return Number(((value ?? 0) / total).toFixed(6))
|
||||
}
|
||||
|
||||
export function chunks<T>(items: T[], size: number) {
|
||||
return Array.from({ length: Math.ceil(items.length / size) }, (_, index) =>
|
||||
items.slice(index * size, (index + 1) * size),
|
||||
)
|
||||
}
|
||||
|
||||
function unique(values: string[]) {
|
||||
return [...new Set(values)]
|
||||
}
|
||||
|
||||
export function inserted(column: string) {
|
||||
return sql.raw(`values(\`${column}\`)`)
|
||||
}
|
||||
|
||||
export function weightedAverage(
|
||||
left: number | null | undefined,
|
||||
leftWeight = 0,
|
||||
right: number | null | undefined,
|
||||
rightWeight = 0,
|
||||
) {
|
||||
const totalWeight =
|
||||
(left === null || left === undefined ? 0 : leftWeight) + (right === null || right === undefined ? 0 : rightWeight)
|
||||
if (totalWeight === 0) return null
|
||||
return Number((((left ?? 0) * leftWeight + (right ?? 0) * rightWeight) / totalWeight).toFixed(2))
|
||||
}
|
||||
|
||||
export function normalizeTier(value: string) {
|
||||
if (value === "Paid") return "Zen"
|
||||
return value
|
||||
}
|
||||
|
||||
export function normalizeCountry(value: string | undefined) {
|
||||
if (!value || value.length !== 2) return "ZZ"
|
||||
return value.toUpperCase()
|
||||
}
|
||||
993
packages/stats/core/src/honeycomb-backfill.ts
Normal file
993
packages/stats/core/src/honeycomb-backfill.ts
Normal file
@@ -0,0 +1,993 @@
|
||||
import { Client } from "@planetscale/database"
|
||||
import { readdir } from "node:fs/promises"
|
||||
import path from "node:path"
|
||||
import { drizzle } from "drizzle-orm/planetscale-serverless"
|
||||
import { geoStat, modelStat, providerStat } from "./database/schema"
|
||||
import { statModel, statProvider } from "./domain/model-normalization"
|
||||
import {
|
||||
chunks,
|
||||
collapseRows,
|
||||
inserted,
|
||||
isoWeekId,
|
||||
normalizeCountry,
|
||||
normalizeTier,
|
||||
periodKeyFor,
|
||||
rankBy,
|
||||
rankRowsWithMarketShare,
|
||||
startOfIsoWeek,
|
||||
startOfUtcDay,
|
||||
statPeriodKey,
|
||||
synthesizeAllTierRows,
|
||||
toStatBaseRow,
|
||||
type StatBaseAggregate,
|
||||
} from "./domain/stat"
|
||||
|
||||
const DAY_MS = 86_400_000
|
||||
const DEFAULT_UPSERT_CHUNK_SIZE = 100
|
||||
const DEFAULT_TIERS = ["Go", "Free", "Paid"]
|
||||
const FREE_MODELS = new Set(["gpt-5-nano", "grok-code", "big-pickle"])
|
||||
|
||||
type Grain = "day" | "week"
|
||||
type MetricDimension = "model" | "provider" | "geo" | "geo-model"
|
||||
type LookupDimension = "model-provider-model" | "geo-continent"
|
||||
type ImportKey = `${MetricDimension | LookupDimension}-${Grain}`
|
||||
type QuerySpec = {
|
||||
name: string
|
||||
importKey: ImportKey
|
||||
importFlag: `--${ImportKey}`
|
||||
query: ReturnType<typeof metricQuery>
|
||||
}
|
||||
type RawRow = Record<string, string>
|
||||
type ImportOptions = {
|
||||
dataset: string
|
||||
databaseUrl: string | undefined
|
||||
directories: string[]
|
||||
dryRun: boolean
|
||||
periodStart: Date | undefined
|
||||
upsertChunkSize: number
|
||||
files: Partial<Record<ImportKey, string[]>>
|
||||
}
|
||||
type ModelAggregate = StatBaseAggregate & { provider: string; model: string; provider_model: string }
|
||||
type ProviderAggregate = StatBaseAggregate & { provider: string }
|
||||
type GeoAggregate = StatBaseAggregate & { provider: string; model: string; country: string; continent: string }
|
||||
type ModelStatRow = typeof modelStat.$inferInsert
|
||||
type ProviderStatRow = typeof providerStat.$inferInsert
|
||||
type GeoStatRow = typeof geoStat.$inferInsert
|
||||
|
||||
const inputKeys = [
|
||||
"model-day",
|
||||
"model-week",
|
||||
"model-provider-model-day",
|
||||
"model-provider-model-week",
|
||||
"provider-day",
|
||||
"provider-week",
|
||||
"geo-day",
|
||||
"geo-week",
|
||||
"geo-model-day",
|
||||
"geo-model-week",
|
||||
"geo-continent-day",
|
||||
"geo-continent-week",
|
||||
] as const satisfies ImportKey[]
|
||||
|
||||
if (import.meta.main) await main()
|
||||
|
||||
async function main() {
|
||||
const command = process.argv[2]
|
||||
if (command === "queries") return printQueries(process.argv.slice(3))
|
||||
if (command === "import") return importFiles(process.argv.slice(3))
|
||||
usage()
|
||||
}
|
||||
|
||||
function printQueries(args: string[]) {
|
||||
const flags = parseFlags(args)
|
||||
const limit = parseIntegerFlag(flags, "limit") ?? 1000
|
||||
const tiers = parseListFlag(flags, "tiers") ?? DEFAULT_TIERS
|
||||
const queries = buildQueries(limit, tiers)
|
||||
const only = flags.get("only")?.[0]
|
||||
|
||||
if (only) {
|
||||
const item = queries.find((query) => query.name === only)
|
||||
if (!item) fail(`Unknown --only ${only}. Expected one of: ${queries.map((query) => query.name).join(", ")}`)
|
||||
console.log(JSON.stringify(item.query, null, 2))
|
||||
return
|
||||
}
|
||||
|
||||
console.log(
|
||||
JSON.stringify(
|
||||
{
|
||||
tiers,
|
||||
import_hint: "bun src/honeycomb-backfill.ts import --dir downloads",
|
||||
queries,
|
||||
},
|
||||
null,
|
||||
2,
|
||||
),
|
||||
)
|
||||
}
|
||||
|
||||
async function importFiles(args: string[]) {
|
||||
const parsed = parseImportOptions(args)
|
||||
const opts = { ...parsed, files: mergeFiles(parsed.files, await discoverFiles(parsed.directories)) }
|
||||
if (!inputKeys.some((key) => opts.files[key]?.length)) fail("No CSV or JSON import files were provided or discovered")
|
||||
const providerModelLookup = new Map([
|
||||
...(await lookupRows(opts.files["model-provider-model-day"], "day", opts, modelProviderModelLookup)),
|
||||
...(await lookupRows(opts.files["model-provider-model-week"], "week", opts, modelProviderModelLookup)),
|
||||
])
|
||||
const continentLookup = new Map([
|
||||
...(await lookupRows(opts.files["geo-continent-day"], "day", opts, geoContinentLookup)),
|
||||
...(await lookupRows(opts.files["geo-continent-week"], "week", opts, geoContinentLookup)),
|
||||
])
|
||||
const modelAggregates = [
|
||||
...(await metricRows(opts.files["model-day"], "day", opts, (row, base) =>
|
||||
modelAggregate(row, base, providerModelLookup),
|
||||
)),
|
||||
...(await metricRows(opts.files["model-week"], "week", opts, (row, base) =>
|
||||
modelAggregate(row, base, providerModelLookup),
|
||||
)),
|
||||
]
|
||||
const modelRows = modelRowsFromAggregates(modelAggregates)
|
||||
const providerRows = providerRowsFromAggregates([
|
||||
...(await metricRows(opts.files["provider-day"], "day", opts, (row, base) => ({
|
||||
...base,
|
||||
provider: provider(row) ?? "unknown",
|
||||
}))),
|
||||
...(await metricRows(opts.files["provider-week"], "week", opts, (row, base) => ({
|
||||
...base,
|
||||
provider: provider(row) ?? "unknown",
|
||||
}))),
|
||||
])
|
||||
const geoRows = geoRowsFromAggregates([
|
||||
...(await metricRows(opts.files["geo-day"], "day", opts, (row, base) => ({
|
||||
...base,
|
||||
provider: "all",
|
||||
model: "all",
|
||||
country: country(row),
|
||||
continent: continentLookup.get(lookupKey(base, country(row))) ?? continent(row),
|
||||
}))),
|
||||
...(await metricRows(opts.files["geo-week"], "week", opts, (row, base) => ({
|
||||
...base,
|
||||
provider: "all",
|
||||
model: "all",
|
||||
country: country(row),
|
||||
continent: continentLookup.get(lookupKey(base, country(row))) ?? continent(row),
|
||||
}))),
|
||||
...(await metricRows(opts.files["geo-model-day"], "day", opts, (row, base) =>
|
||||
geoModelAggregate(row, base, continentLookup),
|
||||
)),
|
||||
...(await metricRows(opts.files["geo-model-week"], "week", opts, (row, base) =>
|
||||
geoModelAggregate(row, base, continentLookup),
|
||||
)),
|
||||
])
|
||||
|
||||
console.log(
|
||||
JSON.stringify(
|
||||
{
|
||||
inputs: Object.fromEntries(
|
||||
inputKeys.flatMap((key) => (opts.files[key]?.length ? [[key, opts.files[key].length]] : [])),
|
||||
),
|
||||
modelRows: modelRows.length,
|
||||
providerRows: providerRows.length,
|
||||
geoRows: geoRows.length,
|
||||
dryRun: opts.dryRun,
|
||||
upsertChunkSize: opts.upsertChunkSize,
|
||||
},
|
||||
null,
|
||||
2,
|
||||
),
|
||||
)
|
||||
|
||||
if (opts.dryRun) return
|
||||
if (!opts.databaseUrl) fail("DATABASE_URL is required unless --dry-run is set")
|
||||
|
||||
const db = drizzle({ client: new Client({ url: opts.databaseUrl }) })
|
||||
await upsertModelRows(db, modelRows, opts.upsertChunkSize)
|
||||
await upsertProviderRows(db, providerRows, opts.upsertChunkSize)
|
||||
await upsertGeoRows(db, geoRows, opts.upsertChunkSize)
|
||||
}
|
||||
|
||||
function buildQueries(limit: number, tiers: string[]): QuerySpec[] {
|
||||
const daily = tiers.flatMap((tier) => [
|
||||
querySpec(
|
||||
"model-day",
|
||||
tier,
|
||||
metricQuery(["date", "tier", "stat_provider_2", "stat_model_2"], limit, tierFilters(tier)),
|
||||
),
|
||||
querySpec("provider-day", tier, metricQuery(["date", "tier", "stat_provider_2"], limit, tierFilters(tier))),
|
||||
querySpec("geo-day", tier, metricQuery(["date", "tier", "country", "continent"], limit, tierFilters(tier))),
|
||||
querySpec(
|
||||
"geo-model-day",
|
||||
tier,
|
||||
metricQuery(
|
||||
["date", "tier", "stat_provider_2", "stat_model_2", "country", "continent"],
|
||||
limit,
|
||||
tierFilters(tier),
|
||||
),
|
||||
),
|
||||
])
|
||||
const weekly = tiers.flatMap((tier) => [
|
||||
querySpec(
|
||||
"model-week",
|
||||
tier,
|
||||
metricQuery(["week", "tier", "stat_provider_2", "stat_model_2"], limit, tierFilters(tier)),
|
||||
),
|
||||
querySpec("provider-week", tier, metricQuery(["week", "tier", "stat_provider_2"], limit, tierFilters(tier))),
|
||||
querySpec("geo-week", tier, metricQuery(["week", "tier", "country", "continent"], limit, tierFilters(tier))),
|
||||
querySpec(
|
||||
"geo-model-week",
|
||||
tier,
|
||||
metricQuery(
|
||||
["week", "tier", "stat_provider_2", "stat_model_2", "country", "continent"],
|
||||
limit,
|
||||
tierFilters(tier),
|
||||
),
|
||||
),
|
||||
])
|
||||
|
||||
return [...daily, ...weekly]
|
||||
}
|
||||
|
||||
function querySpec(importKey: ImportKey, tier: string, query: ReturnType<typeof metricQuery>) {
|
||||
return {
|
||||
name: `${importKey}-${queryNameSegment(tier)}`,
|
||||
importKey,
|
||||
importFlag: `--${importKey}` as const,
|
||||
query,
|
||||
}
|
||||
}
|
||||
|
||||
function metricQuery(breakdowns: string[], limit: number, filters: ReturnType<typeof commonFilters> = []) {
|
||||
return {
|
||||
granularity: 0,
|
||||
breakdowns,
|
||||
calculations: [
|
||||
{ op: "COUNT_DISTINCT", column: "session" },
|
||||
{ op: "COUNT" },
|
||||
{ op: "SUM", column: "tokens.input" },
|
||||
{ op: "SUM", column: "tokens.output" },
|
||||
{ op: "SUM", column: "tokens.reasoning" },
|
||||
{ op: "SUM", column: "tokens.cache_read" },
|
||||
{ op: "SUM", column: "tokens" },
|
||||
{ op: "SUM", column: "cost.input.microcents" },
|
||||
{ op: "SUM", column: "cost.output.microcents" },
|
||||
{ op: "SUM", column: "cost.total.microcents" },
|
||||
{ op: "AVG", column: "duration" },
|
||||
{ op: "P50", column: "duration" },
|
||||
{ op: "P95", column: "duration" },
|
||||
{ op: "AVG", column: "time_to_first_byte" },
|
||||
{ op: "P50", column: "time_to_first_byte" },
|
||||
{ op: "P95", column: "time_to_first_byte" },
|
||||
{ op: "AVG", column: "tps.output" },
|
||||
],
|
||||
filters: [...commonFilters(), ...filters],
|
||||
filter_combination: "AND",
|
||||
orders: [{ column: "tokens", op: "SUM", order: "descending" }],
|
||||
havings: [],
|
||||
limit,
|
||||
formulas: [],
|
||||
}
|
||||
}
|
||||
|
||||
function tierFilters(tier: string) {
|
||||
if (tier === "all") return []
|
||||
return [{ column: "tier", op: "=", value: tier }]
|
||||
}
|
||||
|
||||
function queryNameSegment(value: string) {
|
||||
return (
|
||||
value
|
||||
.toLowerCase()
|
||||
.replace(/[^a-z0-9]+/g, "-")
|
||||
.replace(/^-|-$/g, "") || "all"
|
||||
)
|
||||
}
|
||||
|
||||
function commonFilters() {
|
||||
return [
|
||||
{ column: "event_type", op: "=", value: "completions" },
|
||||
{ column: "model", op: "exists" },
|
||||
{ column: "model", op: "!=", value: "" },
|
||||
{ column: "model", op: "!=", value: "alpha-gpt-next" },
|
||||
]
|
||||
}
|
||||
|
||||
function metricRows<T extends StatBaseAggregate>(
|
||||
files: string[] | undefined,
|
||||
grain: Grain,
|
||||
opts: ImportOptions,
|
||||
map: (row: RawRow, base: StatBaseAggregate) => T | T[],
|
||||
) {
|
||||
if (!files) return Promise.resolve([])
|
||||
return readFiles(files).then((rows) => rows.flatMap((row) => map(row, baseAggregate(row, grain, opts))))
|
||||
}
|
||||
|
||||
function lookupRows(
|
||||
files: string[] | undefined,
|
||||
grain: Grain,
|
||||
opts: ImportOptions,
|
||||
map: (row: RawRow, grain: Grain, opts: ImportOptions) => readonly (readonly [string, string])[],
|
||||
) {
|
||||
if (!files) return Promise.resolve([])
|
||||
return readFiles(files).then((rows) =>
|
||||
Array.from(
|
||||
rows
|
||||
.flatMap((row) => map(row, grain, opts))
|
||||
.reduce((result, [key, value]) => {
|
||||
if (value && value > (result.get(key) ?? "")) result.set(key, value)
|
||||
return result
|
||||
}, new Map<string, string>()),
|
||||
),
|
||||
)
|
||||
}
|
||||
|
||||
async function readFiles(files: string[]) {
|
||||
return (await Promise.all(files.map(readRows))).flat()
|
||||
}
|
||||
|
||||
async function discoverFiles(directories: string[]) {
|
||||
const classified = await Promise.all(
|
||||
(await Promise.all(directories.map(filesInDirectory))).flat().map(async (file) => ({
|
||||
file,
|
||||
key: classifyRows(file, await readRows(file)),
|
||||
})),
|
||||
)
|
||||
return classified.reduce<Partial<Record<ImportKey, string[]>>>((result, item) => {
|
||||
return { ...result, [item.key]: [...(result[item.key] ?? []), item.file] }
|
||||
}, {})
|
||||
}
|
||||
|
||||
async function filesInDirectory(directory: string): Promise<string[]> {
|
||||
return (
|
||||
await Promise.all(
|
||||
(await readdir(directory, { withFileTypes: true })).map((entry) => {
|
||||
const file = path.join(directory, entry.name)
|
||||
if (entry.isDirectory()) return filesInDirectory(file)
|
||||
if (entry.isFile() && /\.(csv|json)$/i.test(entry.name)) return Promise.resolve([file])
|
||||
return Promise.resolve([])
|
||||
}),
|
||||
)
|
||||
).flat()
|
||||
}
|
||||
|
||||
function classifyRows(file: string, rows: RawRow[]): ImportKey {
|
||||
if (rows.length === 0) fail(`Cannot classify empty export: ${file}`)
|
||||
const headers = new Set(rows.flatMap((row) => Object.keys(row).map(normalizeHeader)))
|
||||
const grain: Grain = headers.has("date") ? "day" : "week"
|
||||
if (hasHeader(headers, ["country", "cf.country"])) {
|
||||
if (hasHeader(headers, ["model", "stat_model", "stat_model_2"]) && hasMetricHeaders(headers))
|
||||
return `geo-model-${grain}`
|
||||
return hasMetricHeaders(headers) ? `geo-${grain}` : `geo-continent-${grain}`
|
||||
}
|
||||
if (hasHeader(headers, ["model", "stat_model", "stat_model_2"]))
|
||||
return hasMetricHeaders(headers) ? `model-${grain}` : `model-provider-model-${grain}`
|
||||
if (
|
||||
hasHeader(headers, [
|
||||
"provider",
|
||||
"provider.normalized",
|
||||
"stat_provider",
|
||||
"stat_provider_2",
|
||||
"provider.model",
|
||||
"provider_model",
|
||||
])
|
||||
)
|
||||
return `provider-${grain}`
|
||||
fail(`Cannot classify export from columns in ${file}`)
|
||||
}
|
||||
|
||||
function hasMetricHeaders(headers: Set<string>) {
|
||||
return ["sumtokens", "sumtokensinput", "inputtokens", "totaltokens", "avgduration", "countdistinctsession"].some(
|
||||
(header) => headers.has(header),
|
||||
)
|
||||
}
|
||||
|
||||
function hasHeader(headers: Set<string>, names: string[]) {
|
||||
return names.some((name) => headers.has(normalizeHeader(name)))
|
||||
}
|
||||
|
||||
function mergeFiles(left: Partial<Record<ImportKey, string[]>>, right: Partial<Record<ImportKey, string[]>>) {
|
||||
return inputKeys.reduce<Partial<Record<ImportKey, string[]>>>((result, key) => {
|
||||
const files = [...(left[key] ?? []), ...(right[key] ?? [])]
|
||||
if (files.length === 0) return result
|
||||
return { ...result, [key]: files }
|
||||
}, {})
|
||||
}
|
||||
|
||||
function modelProviderModelLookup(row: RawRow, grain: Grain, opts: ImportOptions): [string, string][] {
|
||||
const base = basePeriod(row, grain, opts)
|
||||
const value = providerModel(row)
|
||||
const author = provider(row)
|
||||
if (!value || !author) return []
|
||||
return [[lookupKey({ ...base, dataset: opts.dataset, tier: tier(row), grain }, author, model(row)), value]]
|
||||
}
|
||||
|
||||
function modelAggregate(
|
||||
row: RawRow,
|
||||
base: StatBaseAggregate,
|
||||
providerModelLookup: Map<string, string>,
|
||||
): ModelAggregate[] {
|
||||
const author = provider(row)
|
||||
if (!author) return []
|
||||
|
||||
return [
|
||||
{
|
||||
...base,
|
||||
provider: author,
|
||||
model: model(row),
|
||||
provider_model: providerModelLookup.get(lookupKey(base, author, model(row))) ?? providerModel(row),
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function geoContinentLookup(row: RawRow, grain: Grain, opts: ImportOptions): [string, string][] {
|
||||
const base = basePeriod(row, grain, opts)
|
||||
const value = continent(row)
|
||||
if (!value) return []
|
||||
return [[lookupKey({ ...base, dataset: opts.dataset, tier: tier(row), grain }, country(row)), value]]
|
||||
}
|
||||
|
||||
function geoModelAggregate(row: RawRow, base: StatBaseAggregate, continentLookup: Map<string, string>): GeoAggregate[] {
|
||||
const author = provider(row)
|
||||
if (!author) return []
|
||||
|
||||
return [
|
||||
{
|
||||
...base,
|
||||
provider: author,
|
||||
model: model(row),
|
||||
country: country(row),
|
||||
continent: continentLookup.get(lookupKey(base, country(row))) ?? continent(row),
|
||||
},
|
||||
]
|
||||
}
|
||||
|
||||
function baseAggregate(row: RawRow, grain: Grain, opts: ImportOptions): StatBaseAggregate {
|
||||
return {
|
||||
...basePeriod(row, grain, opts),
|
||||
grain,
|
||||
dataset: opts.dataset,
|
||||
tier: tier(row),
|
||||
sessions: integer(row, "sessions", ["COUNT_DISTINCT(session)"]),
|
||||
requests: integer(row, "requests", ["COUNT", "COUNT()"]),
|
||||
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)"]),
|
||||
cache_read_tokens: integer(row, "cache_read_tokens", ["SUM(tokens.cache_read)", "SUM(tokens_cache_read)"]),
|
||||
total_tokens: integer(row, "total_tokens", ["SUM(stat_tokens_total)", "SUM(tokens)", "SUM(tokens_total)"]),
|
||||
input_cost_microcents: integer(row, "input_cost_microcents", [
|
||||
"SUM(cost.input.microcents)",
|
||||
"SUM(stat_cost_input_microcents)",
|
||||
]),
|
||||
output_cost_microcents: integer(row, "output_cost_microcents", [
|
||||
"SUM(cost.output.microcents)",
|
||||
"SUM(stat_cost_output_microcents)",
|
||||
]),
|
||||
total_cost_microcents: integer(row, "total_cost_microcents", [
|
||||
"SUM(cost.total.microcents)",
|
||||
"SUM(stat_cost_total_microcents)",
|
||||
]),
|
||||
avg_duration_ms: nullableNumber(row, "avg_duration_ms", ["AVG(duration)", "AVG(duration_ms)"]),
|
||||
p50_duration_ms: nullableInteger(row, "p50_duration_ms", ["P50(duration)", "P50(duration_ms)"]),
|
||||
p95_duration_ms: nullableInteger(row, "p95_duration_ms", ["P95(duration)", "P95(duration_ms)"]),
|
||||
avg_ttfb_ms: nullableNumber(row, "avg_ttfb_ms", ["AVG(time_to_first_byte)", "AVG(ttfb_ms)"]),
|
||||
p50_ttfb_ms: nullableInteger(row, "p50_ttfb_ms", ["P50(time_to_first_byte)", "P50(ttfb_ms)"]),
|
||||
p95_ttfb_ms: nullableInteger(row, "p95_ttfb_ms", ["P95(time_to_first_byte)", "P95(ttfb_ms)"]),
|
||||
avg_output_tps: nullableNumber(row, "avg_output_tps", ["AVG(tps.output)", "AVG(stat_output_tps)"]),
|
||||
success_count: integer(row, "success_count", ["SUM(success)", "SUM(is_success)", "SUM(stat_success)"]),
|
||||
error_count: integer(row, "error_count", ["SUM(error)", "SUM(is_error)", "SUM(stat_error)"]),
|
||||
sample_count: integer(row, "sample_count", ["COUNT", "COUNT()"]),
|
||||
}
|
||||
}
|
||||
|
||||
function basePeriod(row: RawRow, grain: Grain, opts: ImportOptions) {
|
||||
return { period_key: periodKey(row, grain, opts) }
|
||||
}
|
||||
|
||||
function periodKey(row: RawRow, grain: Grain, opts: ImportOptions) {
|
||||
if (grain === "week") {
|
||||
const week = parseWeek(row)
|
||||
if (week) return week
|
||||
fail("weekly imports require a week or period_key column")
|
||||
}
|
||||
|
||||
const time = parseTime(row)
|
||||
const start = time ? startOfUtcDay(time) : opts.periodStart
|
||||
if (!start) fail("daily imports require a time column or --period-start")
|
||||
return periodKeyFor("day", start)
|
||||
}
|
||||
|
||||
function modelRowsFromAggregates(aggregates: ModelAggregate[]) {
|
||||
return rankModelRows([
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "week").map(toModelRow), modelDimensionKey),
|
||||
modelDimensionKey,
|
||||
),
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "day").map(toModelRow), modelDimensionKey),
|
||||
modelDimensionKey,
|
||||
),
|
||||
])
|
||||
}
|
||||
|
||||
function providerRowsFromAggregates(aggregates: ProviderAggregate[]) {
|
||||
return rankRowsWithMarketShare([
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "week").map(toProviderRow), providerDimensionKey),
|
||||
providerDimensionKey,
|
||||
),
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "day").map(toProviderRow), providerDimensionKey),
|
||||
providerDimensionKey,
|
||||
),
|
||||
])
|
||||
}
|
||||
|
||||
function geoRowsFromAggregates(aggregates: GeoAggregate[]) {
|
||||
return rankRowsWithMarketShare(
|
||||
[
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "week").map(toGeoRow), geoDimensionKey),
|
||||
geoDimensionKey,
|
||||
),
|
||||
...synthesizeAllTierRows(
|
||||
collapseRows(aggregates.filter((item) => item.grain === "day").map(toGeoRow), geoDimensionKey),
|
||||
geoDimensionKey,
|
||||
),
|
||||
],
|
||||
geoMarketShareKey,
|
||||
)
|
||||
}
|
||||
|
||||
function toModelRow(data: ModelAggregate): ModelStatRow {
|
||||
return { ...toStatBaseRow(data), provider: data.provider, model: data.model, provider_model: data.provider_model }
|
||||
}
|
||||
|
||||
function toProviderRow(data: ProviderAggregate): ProviderStatRow {
|
||||
return { ...toStatBaseRow(data), provider: data.provider }
|
||||
}
|
||||
|
||||
function toGeoRow(data: GeoAggregate): GeoStatRow {
|
||||
return {
|
||||
...toStatBaseRow(data),
|
||||
provider: data.provider,
|
||||
model: data.model,
|
||||
country: data.country,
|
||||
continent: data.continent,
|
||||
}
|
||||
}
|
||||
|
||||
function rankModelRows(rows: ModelStatRow[]) {
|
||||
return Object.values(
|
||||
rows.reduce<Record<string, ModelStatRow[]>>((result, row) => {
|
||||
const key = statPeriodKey(row)
|
||||
result[key] = [...(result[key] ?? []), row]
|
||||
return result
|
||||
}, {}),
|
||||
).flatMap((group) => {
|
||||
const tokenRanks = rankBy(group, (row) => row.total_tokens ?? 0)
|
||||
const requestRanks = rankBy(group, (row) => row.requests ?? 0)
|
||||
const costRanks = rankBy(group, (row) => row.total_cost_microcents ?? 0)
|
||||
return group.map((row) => ({
|
||||
...row,
|
||||
rank_by_tokens: tokenRanks.get(row) ?? null,
|
||||
rank_by_requests: requestRanks.get(row) ?? null,
|
||||
rank_by_cost: costRanks.get(row) ?? null,
|
||||
}))
|
||||
})
|
||||
}
|
||||
|
||||
function modelDimensionKey(row: ModelStatRow) {
|
||||
return [row.provider, row.model].join("\u0000")
|
||||
}
|
||||
|
||||
function providerDimensionKey(row: ProviderStatRow) {
|
||||
return row.provider
|
||||
}
|
||||
|
||||
function geoDimensionKey(row: GeoStatRow) {
|
||||
return [row.provider, row.model, row.country].join("\u0000")
|
||||
}
|
||||
|
||||
function geoMarketShareKey(row: GeoStatRow) {
|
||||
return [statPeriodKey(row), row.provider, row.model].join("\u0000")
|
||||
}
|
||||
|
||||
function lookupKey(base: { grain: string; period_key: string; dataset: string; tier: string }, ...dimension: string[]) {
|
||||
return [base.grain, base.period_key, base.dataset, base.tier, ...dimension].join("\u0000")
|
||||
}
|
||||
|
||||
function tier(row: RawRow) {
|
||||
return normalizeTier(cell(row, ["stat_tier", "tier"]) || deriveTier(row))
|
||||
}
|
||||
|
||||
function deriveTier(row: RawRow) {
|
||||
const source = cell(row, ["source"])
|
||||
const value = model(row)
|
||||
if (source === "lite") return "Go"
|
||||
if (FREE_MODELS.has(value) || /-free(:global)?$/.test(rawModel(row))) return "Free"
|
||||
return "Zen"
|
||||
}
|
||||
|
||||
function provider(row: RawRow) {
|
||||
return statProvider(model(row), providerModel(row), cell(row, ["stat_provider_2", "stat_provider"]))
|
||||
}
|
||||
|
||||
function model(row: RawRow) {
|
||||
return statModel(cell(row, ["stat_model_2", "stat_model"]) || rawModel(row), providerModel(row))
|
||||
}
|
||||
|
||||
function rawModel(row: RawRow) {
|
||||
return cell(row, ["model"]) || "unknown"
|
||||
}
|
||||
|
||||
function providerModel(row: RawRow) {
|
||||
return cell(row, ["provider.model", "provider_model"]) || ""
|
||||
}
|
||||
|
||||
function country(row: RawRow) {
|
||||
return normalizeCountry(cell(row, ["stat_country", "cf.country", "cf_country", "country"]))
|
||||
}
|
||||
|
||||
function continent(row: RawRow) {
|
||||
return cell(row, ["cf.continent", "cf_continent", "continent"]) || ""
|
||||
}
|
||||
|
||||
function integer(row: RawRow, name: string, aliases: string[] = []) {
|
||||
return Math.round(number(row, name, aliases))
|
||||
}
|
||||
|
||||
function nullableInteger(row: RawRow, name: string, aliases: string[] = []) {
|
||||
if (!hasCell(row, [name, ...aliases])) return null
|
||||
return Math.round(number(row, name, aliases))
|
||||
}
|
||||
|
||||
function nullableNumber(row: RawRow, name: string, aliases: string[] = []) {
|
||||
if (!hasCell(row, [name, ...aliases])) return null
|
||||
return Number(number(row, name, aliases).toFixed(2))
|
||||
}
|
||||
|
||||
function number(row: RawRow, name: string, aliases: string[] = []) {
|
||||
const value = Number(cell(row, [name, ...aliases]).replace(/,/g, ""))
|
||||
return Number.isFinite(value) ? value : 0
|
||||
}
|
||||
|
||||
function hasCell(row: RawRow, names: string[]) {
|
||||
return names.some((name) => row[name] !== undefined && row[name] !== "")
|
||||
}
|
||||
|
||||
function cell(row: RawRow, names: string[]) {
|
||||
const normalized = normalizedCells(row)
|
||||
return (
|
||||
names.flatMap((name) => [row[name], normalized.get(normalizeHeader(name))]).find((value) => value !== undefined) ??
|
||||
""
|
||||
)
|
||||
}
|
||||
|
||||
function normalizedCells(row: RawRow) {
|
||||
return new Map(Object.entries(row).map(([key, value]) => [normalizeHeader(key), value]))
|
||||
}
|
||||
|
||||
function normalizeHeader(value: string) {
|
||||
return value.toLowerCase().replace(/[^a-z0-9]+/g, "")
|
||||
}
|
||||
|
||||
function parseTime(row: RawRow) {
|
||||
const value = cell(row, ["date", "time", "timestamp", "datetime", "bucket"])
|
||||
if (!value) return undefined
|
||||
const numeric = Number(value)
|
||||
const date = Number.isFinite(numeric)
|
||||
? new Date(numeric > 10_000_000_000 ? numeric : numeric * 1000)
|
||||
: new Date(value)
|
||||
if (Number.isNaN(date.getTime())) fail(`Invalid time value: ${value}`)
|
||||
return date
|
||||
}
|
||||
|
||||
function parseWeek(row: RawRow) {
|
||||
const value = cell(row, ["period_key", "week", "stat_week"])
|
||||
if (!value) return undefined
|
||||
|
||||
const match = /^(\d{4})-W(\d{1,2})$/.exec(value)
|
||||
if (!match) fail(`Invalid week value: ${value}`)
|
||||
|
||||
const year = Number(match[1])
|
||||
const week = Number(match[2])
|
||||
if (week < 1 || week > 53) fail(`Invalid week value: ${value}`)
|
||||
|
||||
const start = new Date(startOfIsoWeek(new Date(Date.UTC(year, 0, 4))).getTime() + (week - 1) * 7 * DAY_MS)
|
||||
const id = `${year}-W${String(week).padStart(2, "0")}`
|
||||
if (isoWeekId(start) !== id) fail(`Invalid week value: ${value}`)
|
||||
return id
|
||||
}
|
||||
|
||||
async function readRows(file: string) {
|
||||
const text = await Bun.file(file).text()
|
||||
if (file.toLowerCase().endsWith(".json")) {
|
||||
const parsed: unknown = JSON.parse(text)
|
||||
return rowsFromJson(parsed)
|
||||
}
|
||||
return rowsFromCsv(text)
|
||||
}
|
||||
|
||||
function rowsFromJson(value: unknown): RawRow[] {
|
||||
if (Array.isArray(value)) return value.flatMap(rowFromUnknown)
|
||||
if (!isRecord(value)) fail("JSON imports must be an array of rows or an object with results/data/rows")
|
||||
|
||||
const rows = [value.results, value.data, value.rows].flatMap((candidate) =>
|
||||
Array.isArray(candidate) ? candidate.flatMap(rowFromUnknown) : [],
|
||||
)
|
||||
if (rows.length === 0) fail("JSON import did not contain rows")
|
||||
return rows
|
||||
}
|
||||
|
||||
function rowFromUnknown(value: unknown): RawRow[] {
|
||||
if (!isRecord(value)) return []
|
||||
const nested = isRecord(value.data) ? value.data : {}
|
||||
return [
|
||||
Object.fromEntries(
|
||||
Object.entries({ ...value, ...nested }).flatMap(([key, item]) => {
|
||||
if (key === "data") return []
|
||||
return [[key, cellValue(item)]]
|
||||
}),
|
||||
),
|
||||
]
|
||||
}
|
||||
|
||||
function rowsFromCsv(text: string): RawRow[] {
|
||||
const [headers, ...rows] = csvRecords(text).filter((row) => row.some((value) => value.trim() !== ""))
|
||||
if (!headers) return []
|
||||
return rows.map((row) =>
|
||||
Object.fromEntries(headers.map((header, index) => [header.trim(), row[index]?.trim() ?? ""])),
|
||||
)
|
||||
}
|
||||
|
||||
function csvRecords(text: string) {
|
||||
const rows: string[][] = []
|
||||
let row: string[] = []
|
||||
let field = ""
|
||||
let quoted = false
|
||||
|
||||
for (let index = 0; index < text.length; index++) {
|
||||
const char = text[index]
|
||||
const next = text[index + 1]
|
||||
if (quoted) {
|
||||
if (char === '"' && next === '"') {
|
||||
field += '"'
|
||||
index++
|
||||
continue
|
||||
}
|
||||
if (char === '"') {
|
||||
quoted = false
|
||||
continue
|
||||
}
|
||||
field += char
|
||||
continue
|
||||
}
|
||||
if (char === '"') {
|
||||
quoted = true
|
||||
continue
|
||||
}
|
||||
if (char === ",") {
|
||||
row.push(field)
|
||||
field = ""
|
||||
continue
|
||||
}
|
||||
if (char === "\n") {
|
||||
row.push(field)
|
||||
rows.push(row)
|
||||
row = []
|
||||
field = ""
|
||||
continue
|
||||
}
|
||||
if (char === "\r") continue
|
||||
field += char
|
||||
}
|
||||
|
||||
row.push(field)
|
||||
rows.push(row)
|
||||
return rows
|
||||
}
|
||||
|
||||
function cellValue(value: unknown) {
|
||||
if (value === null || value === undefined) return ""
|
||||
if (typeof value === "string") return value
|
||||
if (typeof value === "number" || typeof value === "boolean" || typeof value === "bigint") return String(value)
|
||||
return JSON.stringify(value) ?? ""
|
||||
}
|
||||
|
||||
function isRecord(value: unknown): value is Record<string, unknown> {
|
||||
return typeof value === "object" && value !== null && !Array.isArray(value)
|
||||
}
|
||||
|
||||
async function upsertModelRows(db: ReturnType<typeof drizzle>, rows: ModelStatRow[], chunkSize: number) {
|
||||
const batches = chunks(rows, chunkSize)
|
||||
console.log(JSON.stringify({ table: "model_stat", batches: batches.length, chunkSize }))
|
||||
for (const chunk of batches) {
|
||||
await db
|
||||
.insert(modelStat)
|
||||
.values(chunk)
|
||||
.onDuplicateKeyUpdate({
|
||||
set: {
|
||||
provider_model: inserted("provider_model"),
|
||||
sessions: inserted("sessions"),
|
||||
requests: inserted("requests"),
|
||||
input_tokens: inserted("input_tokens"),
|
||||
output_tokens: inserted("output_tokens"),
|
||||
reasoning_tokens: inserted("reasoning_tokens"),
|
||||
cache_read_tokens: inserted("cache_read_tokens"),
|
||||
total_tokens: inserted("total_tokens"),
|
||||
input_cost_microcents: inserted("input_cost_microcents"),
|
||||
output_cost_microcents: inserted("output_cost_microcents"),
|
||||
total_cost_microcents: inserted("total_cost_microcents"),
|
||||
avg_duration_ms: inserted("avg_duration_ms"),
|
||||
p50_duration_ms: inserted("p50_duration_ms"),
|
||||
p95_duration_ms: inserted("p95_duration_ms"),
|
||||
avg_ttfb_ms: inserted("avg_ttfb_ms"),
|
||||
p50_ttfb_ms: inserted("p50_ttfb_ms"),
|
||||
p95_ttfb_ms: inserted("p95_ttfb_ms"),
|
||||
avg_output_tps: inserted("avg_output_tps"),
|
||||
success_count: inserted("success_count"),
|
||||
error_count: inserted("error_count"),
|
||||
sample_count: inserted("sample_count"),
|
||||
rank_by_tokens: inserted("rank_by_tokens"),
|
||||
rank_by_requests: inserted("rank_by_requests"),
|
||||
rank_by_cost: inserted("rank_by_cost"),
|
||||
},
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
async function upsertProviderRows(db: ReturnType<typeof drizzle>, rows: ProviderStatRow[], chunkSize: number) {
|
||||
const batches = chunks(rows, chunkSize)
|
||||
console.log(JSON.stringify({ table: "provider_stat", batches: batches.length, chunkSize }))
|
||||
for (const chunk of batches) {
|
||||
await db
|
||||
.insert(providerStat)
|
||||
.values(chunk)
|
||||
.onDuplicateKeyUpdate({
|
||||
set: {
|
||||
sessions: inserted("sessions"),
|
||||
requests: inserted("requests"),
|
||||
input_tokens: inserted("input_tokens"),
|
||||
output_tokens: inserted("output_tokens"),
|
||||
reasoning_tokens: inserted("reasoning_tokens"),
|
||||
cache_read_tokens: inserted("cache_read_tokens"),
|
||||
total_tokens: inserted("total_tokens"),
|
||||
input_cost_microcents: inserted("input_cost_microcents"),
|
||||
output_cost_microcents: inserted("output_cost_microcents"),
|
||||
total_cost_microcents: inserted("total_cost_microcents"),
|
||||
avg_duration_ms: inserted("avg_duration_ms"),
|
||||
p50_duration_ms: inserted("p50_duration_ms"),
|
||||
p95_duration_ms: inserted("p95_duration_ms"),
|
||||
avg_ttfb_ms: inserted("avg_ttfb_ms"),
|
||||
p50_ttfb_ms: inserted("p50_ttfb_ms"),
|
||||
p95_ttfb_ms: inserted("p95_ttfb_ms"),
|
||||
avg_output_tps: inserted("avg_output_tps"),
|
||||
success_count: inserted("success_count"),
|
||||
error_count: inserted("error_count"),
|
||||
sample_count: inserted("sample_count"),
|
||||
market_share_tokens: inserted("market_share_tokens"),
|
||||
market_share_requests: inserted("market_share_requests"),
|
||||
market_share_sessions: inserted("market_share_sessions"),
|
||||
rank_by_tokens: inserted("rank_by_tokens"),
|
||||
rank_by_requests: inserted("rank_by_requests"),
|
||||
rank_by_sessions: inserted("rank_by_sessions"),
|
||||
rank_by_cost: inserted("rank_by_cost"),
|
||||
},
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
async function upsertGeoRows(db: ReturnType<typeof drizzle>, rows: GeoStatRow[], chunkSize: number) {
|
||||
const batches = chunks(rows, chunkSize)
|
||||
console.log(JSON.stringify({ table: "geo_stat", batches: batches.length, chunkSize }))
|
||||
for (const chunk of batches) {
|
||||
await db
|
||||
.insert(geoStat)
|
||||
.values(chunk)
|
||||
.onDuplicateKeyUpdate({
|
||||
set: {
|
||||
continent: inserted("continent"),
|
||||
sessions: inserted("sessions"),
|
||||
requests: inserted("requests"),
|
||||
input_tokens: inserted("input_tokens"),
|
||||
output_tokens: inserted("output_tokens"),
|
||||
reasoning_tokens: inserted("reasoning_tokens"),
|
||||
cache_read_tokens: inserted("cache_read_tokens"),
|
||||
total_tokens: inserted("total_tokens"),
|
||||
input_cost_microcents: inserted("input_cost_microcents"),
|
||||
output_cost_microcents: inserted("output_cost_microcents"),
|
||||
total_cost_microcents: inserted("total_cost_microcents"),
|
||||
avg_duration_ms: inserted("avg_duration_ms"),
|
||||
p50_duration_ms: inserted("p50_duration_ms"),
|
||||
p95_duration_ms: inserted("p95_duration_ms"),
|
||||
avg_ttfb_ms: inserted("avg_ttfb_ms"),
|
||||
p50_ttfb_ms: inserted("p50_ttfb_ms"),
|
||||
p95_ttfb_ms: inserted("p95_ttfb_ms"),
|
||||
avg_output_tps: inserted("avg_output_tps"),
|
||||
success_count: inserted("success_count"),
|
||||
error_count: inserted("error_count"),
|
||||
sample_count: inserted("sample_count"),
|
||||
market_share_tokens: inserted("market_share_tokens"),
|
||||
market_share_requests: inserted("market_share_requests"),
|
||||
market_share_sessions: inserted("market_share_sessions"),
|
||||
rank_by_tokens: inserted("rank_by_tokens"),
|
||||
rank_by_requests: inserted("rank_by_requests"),
|
||||
rank_by_sessions: inserted("rank_by_sessions"),
|
||||
rank_by_cost: inserted("rank_by_cost"),
|
||||
},
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
function parseImportOptions(args: string[]): ImportOptions {
|
||||
const flags = parseFlags(args)
|
||||
const files = inputKeys.reduce<Partial<Record<ImportKey, string[]>>>((result, key) => {
|
||||
const values = flags.get(key)
|
||||
if (!values) return result
|
||||
return { ...result, [key]: values }
|
||||
}, {})
|
||||
return {
|
||||
dataset: flags.get("dataset")?.[0] ?? "zen",
|
||||
databaseUrl: flags.get("database-url")?.[0] ?? process.env.DATABASE_URL,
|
||||
directories: flags.get("dir") ?? flags.get("directory") ?? [],
|
||||
dryRun: flags.has("dry-run"),
|
||||
periodStart: parseDateFlag(flags, "period-start"),
|
||||
upsertChunkSize: parseIntegerFlag(flags, "upsert-chunk-size") ?? DEFAULT_UPSERT_CHUNK_SIZE,
|
||||
files,
|
||||
}
|
||||
}
|
||||
|
||||
function parseFlags(args: string[]) {
|
||||
const result = new Map<string, string[]>()
|
||||
for (let index = 0; index < args.length; index++) {
|
||||
const arg = args[index]
|
||||
if (!arg.startsWith("--")) fail(`Unexpected argument: ${arg}`)
|
||||
const name = arg.slice(2)
|
||||
if (name === "dry-run" || name === "include-weekly") {
|
||||
result.set(name, ["true"])
|
||||
continue
|
||||
}
|
||||
const nextFlag = args.findIndex((value, valueIndex) => valueIndex > index && value.startsWith("--"))
|
||||
const values = args.slice(index + 1, nextFlag === -1 ? args.length : nextFlag)
|
||||
if (values.length === 0) fail(`Missing value for --${name}`)
|
||||
result.set(name, [...(result.get(name) ?? []), ...values])
|
||||
index += values.length
|
||||
}
|
||||
return result
|
||||
}
|
||||
|
||||
function parseDateFlag(flags: Map<string, string[]>, name: string) {
|
||||
const value = flags.get(name)?.[0]
|
||||
if (!value) return undefined
|
||||
const date = new Date(value)
|
||||
if (Number.isNaN(date.getTime())) fail(`Invalid --${name}: ${value}`)
|
||||
return date
|
||||
}
|
||||
|
||||
function parseIntegerFlag(flags: Map<string, string[]>, name: string) {
|
||||
const value = flags.get(name)?.[0]
|
||||
if (!value) return undefined
|
||||
const parsed = Number(value)
|
||||
if (!Number.isInteger(parsed) || parsed <= 0) fail(`Invalid --${name}: ${value}`)
|
||||
return parsed
|
||||
}
|
||||
|
||||
function parseListFlag(flags: Map<string, string[]>, name: string) {
|
||||
const value = flags.get(name)?.[0]
|
||||
if (!value) return undefined
|
||||
if (value === "all") return ["all"]
|
||||
return value
|
||||
.split(",")
|
||||
.map((item) => item.trim())
|
||||
.filter(Boolean)
|
||||
}
|
||||
|
||||
function usage(): never {
|
||||
fail(`Usage:
|
||||
bun src/honeycomb-backfill.ts queries [--tiers Go,Free,Paid] [--limit 1000]
|
||||
bun src/honeycomb-backfill.ts import [--dry-run] [--upsert-chunk-size 100] [--database-url URL] --dir downloads
|
||||
bun src/honeycomb-backfill.ts import [--dry-run] [--upsert-chunk-size 100] [--database-url URL] --model-day file.csv [--model-day more.csv] ...`)
|
||||
}
|
||||
|
||||
function fail(message: string): never {
|
||||
console.error(message)
|
||||
process.exit(1)
|
||||
}
|
||||
11
packages/stats/core/src/index.ts
Normal file
11
packages/stats/core/src/index.ts
Normal file
@@ -0,0 +1,11 @@
|
||||
export * as Athena from "./athena"
|
||||
export * as AppConfig from "./config"
|
||||
export * as Database from "./database"
|
||||
export * as GeoStat from "./domain/geo"
|
||||
export * as StatsHome from "./domain/home"
|
||||
export * as Inference from "./domain/inference"
|
||||
export * as ModelStat from "./domain/model"
|
||||
export * as ProviderStat from "./domain/provider"
|
||||
export * as Stat from "./domain/stat"
|
||||
export * as Runtime from "./runtime"
|
||||
export * as StatSync from "./stat-sync"
|
||||
4
packages/stats/core/src/migrate.ts
Normal file
4
packages/stats/core/src/migrate.ts
Normal file
@@ -0,0 +1,4 @@
|
||||
import { Effect } from "effect"
|
||||
import { layer, migrate } from "./database"
|
||||
|
||||
await Effect.runPromise(migrate().pipe(Effect.provide(layer)))
|
||||
28
packages/stats/core/src/resource.d.ts
vendored
Normal file
28
packages/stats/core/src/resource.d.ts
vendored
Normal file
@@ -0,0 +1,28 @@
|
||||
import "sst/resource"
|
||||
|
||||
declare module "sst/resource" {
|
||||
export interface Resource {
|
||||
InferenceEvent: {
|
||||
catalog: string
|
||||
database: string
|
||||
region: string
|
||||
table: string
|
||||
tableBucket: string
|
||||
type: "sst.sst.Linkable"
|
||||
workgroup: string
|
||||
}
|
||||
StatsSyncConfig: {
|
||||
dataset: string
|
||||
type: "sst.sst.Linkable"
|
||||
}
|
||||
StatsDatabase: {
|
||||
database: string
|
||||
host: string
|
||||
password: string
|
||||
port: number
|
||||
type: "sst.sst.Linkable"
|
||||
url: string
|
||||
username: string
|
||||
}
|
||||
}
|
||||
}
|
||||
14
packages/stats/core/src/runtime.ts
Normal file
14
packages/stats/core/src/runtime.ts
Normal file
@@ -0,0 +1,14 @@
|
||||
import { Layer, ManagedRuntime } from "effect"
|
||||
import { AppConfig } from "./config"
|
||||
import { layer as databaseLayer } from "./database"
|
||||
import { GeoStatRepo } from "./domain/geo"
|
||||
import { ModelStatRepo } from "./domain/model"
|
||||
import { ProviderStatRepo } from "./domain/provider"
|
||||
|
||||
const repoLayer = Layer.mergeAll(ModelStatRepo.layer, ProviderStatRepo.layer, GeoStatRepo.layer).pipe(
|
||||
Layer.provide(databaseLayer),
|
||||
)
|
||||
|
||||
export const layer = Layer.mergeAll(AppConfig.layer, databaseLayer, repoLayer)
|
||||
export const runtime = ManagedRuntime.make(layer)
|
||||
export type RuntimeServices = ManagedRuntime.ManagedRuntime.Services<typeof runtime>
|
||||
101
packages/stats/core/src/stat-sync.ts
Normal file
101
packages/stats/core/src/stat-sync.ts
Normal file
@@ -0,0 +1,101 @@
|
||||
import { DateTime, Effect } from "effect"
|
||||
import { Resource } from "sst/resource"
|
||||
import { Athena, AthenaQueryError, AthenaQueryTimeoutError } from "./athena"
|
||||
import { DatabaseError } from "./database"
|
||||
import { GeoStatRepo, rowsFromAggregates as geoRowsFromAggregates } from "./domain/geo"
|
||||
import { buildStatsQuery, toGeoAggregate, toModelAggregate, toProviderAggregate } from "./domain/inference"
|
||||
import { ModelStatRepo, rowsFromAggregates as modelRowsFromAggregates } from "./domain/model"
|
||||
import { ProviderStatRepo, rowsFromAggregates as providerRowsFromAggregates } from "./domain/provider"
|
||||
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
|
||||
|
||||
export type SyncStatsResult = { ok: true; rows: number; startedAt: string; periodStart: string; periodEnd: string }
|
||||
export type SyncStatsError = AthenaQueryError | AthenaQueryTimeoutError | DatabaseError
|
||||
|
||||
export const syncStats: () => Effect.Effect<
|
||||
SyncStatsResult,
|
||||
SyncStatsError,
|
||||
Athena | ModelStatRepo | ProviderStatRepo | GeoStatRepo
|
||||
> = Effect.fn("StatSync.sync")(function* () {
|
||||
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 athena = yield* Athena
|
||||
const modelStats = yield* ModelStatRepo
|
||||
const providerStats = yield* ProviderStatRepo
|
||||
const geoStats = yield* GeoStatRepo
|
||||
|
||||
yield* logRuntimeCheck()
|
||||
|
||||
const [modelAggregates, providerAggregates, geoAggregates, geoModelAggregates] = yield* Effect.all(
|
||||
[
|
||||
athena
|
||||
.query(buildStatsQuery(periodStart, periodEnd, "model"))
|
||||
.pipe(Effect.map((rows) => rows.flatMap(toModelAggregate))),
|
||||
athena
|
||||
.query(buildStatsQuery(periodStart, periodEnd, "provider"))
|
||||
.pipe(Effect.map((rows) => rows.flatMap(toProviderAggregate))),
|
||||
athena
|
||||
.query(buildStatsQuery(periodStart, periodEnd, "geo"))
|
||||
.pipe(Effect.map((rows) => rows.flatMap(toGeoAggregate))),
|
||||
athena
|
||||
.query(buildStatsQuery(periodStart, periodEnd, "geo_model"))
|
||||
.pipe(Effect.map((rows) => rows.flatMap(toGeoAggregate))),
|
||||
],
|
||||
{ concurrency: "unbounded" },
|
||||
)
|
||||
const modelRows = modelRowsFromAggregates(modelAggregates)
|
||||
const providerRows = providerRowsFromAggregates(providerAggregates)
|
||||
const geoRows = geoRowsFromAggregates([...geoAggregates, ...geoModelAggregates])
|
||||
|
||||
yield* Effect.all([modelStats.upsert(modelRows), providerStats.upsert(providerRows), geoStats.upsert(geoRows)], {
|
||||
concurrency: "unbounded",
|
||||
discard: true,
|
||||
})
|
||||
yield* Effect.all(
|
||||
[
|
||||
modelStats.deleteRetiredDimensions(modelRows),
|
||||
providerStats.deleteRetiredDimensions(providerRows),
|
||||
geoStats.deleteRetiredDimensions(geoRows),
|
||||
],
|
||||
{ concurrency: "unbounded", discard: true },
|
||||
)
|
||||
|
||||
yield* Effect.logInfo(
|
||||
`stats sync complete ${JSON.stringify({
|
||||
startedAt: startedAt.toISOString(),
|
||||
periodStart: periodStart.toISOString(),
|
||||
periodEnd: periodEnd.toISOString(),
|
||||
rows: modelRows.length,
|
||||
providerRows: providerRows.length,
|
||||
geoRows: geoRows.length,
|
||||
stage: Resource.App.stage,
|
||||
})}`,
|
||||
)
|
||||
|
||||
return {
|
||||
ok: true,
|
||||
rows: modelRows.length,
|
||||
startedAt: startedAt.toISOString(),
|
||||
periodStart: periodStart.toISOString(),
|
||||
periodEnd: periodEnd.toISOString(),
|
||||
}
|
||||
})
|
||||
|
||||
function logRuntimeCheck() {
|
||||
return Effect.logInfo(
|
||||
`athena stats runtime check ${JSON.stringify({
|
||||
catalog: Resource.InferenceEvent.catalog,
|
||||
database: Resource.InferenceEvent.database,
|
||||
dataset: Resource.StatsSyncConfig.dataset,
|
||||
table: Resource.InferenceEvent.table,
|
||||
workgroup: Resource.InferenceEvent.workgroup,
|
||||
region: Resource.InferenceEvent.region,
|
||||
stage: Resource.App.stage,
|
||||
})}`,
|
||||
)
|
||||
}
|
||||
10
packages/stats/core/sst-env.d.ts
vendored
Normal file
10
packages/stats/core/sst-env.d.ts
vendored
Normal file
@@ -0,0 +1,10 @@
|
||||
/* This file is auto-generated by SST. Do not edit. */
|
||||
/* tslint:disable */
|
||||
/* eslint-disable */
|
||||
/* deno-fmt-ignore-file */
|
||||
/* biome-ignore-all lint: auto-generated */
|
||||
|
||||
/// <reference path="../../../sst-env.d.ts" />
|
||||
|
||||
import "sst"
|
||||
export {}
|
||||
11
packages/stats/core/tsconfig.json
Normal file
11
packages/stats/core/tsconfig.json
Normal file
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig",
|
||||
"extends": "@tsconfig/node22/tsconfig.json",
|
||||
"compilerOptions": {
|
||||
"module": "ESNext",
|
||||
"moduleResolution": "bundler",
|
||||
"strict": true,
|
||||
"noEmit": true,
|
||||
"types": ["bun", "node"]
|
||||
}
|
||||
}
|
||||
32
packages/stats/server/Dockerfile
Normal file
32
packages/stats/server/Dockerfile
Normal file
@@ -0,0 +1,32 @@
|
||||
FROM oven/bun:1.3.14-alpine AS base
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
ENV NODE_ENV=production
|
||||
ENV BUN_RUNTIME_TRANSPILER_CACHE_PATH=0
|
||||
|
||||
FROM base AS pruner
|
||||
|
||||
COPY . .
|
||||
|
||||
RUN bunx turbo@2.8.13 prune @opencode-ai/stats-server --docker --no-update-notifier --no-color
|
||||
|
||||
FROM base AS installer
|
||||
|
||||
COPY --from=pruner /app/out/json/ ./
|
||||
|
||||
# Bun 1.3.x needs the pruned workspace globs and lockfile metadata refreshed before the frozen production install.
|
||||
RUN bun -e 'const packageJson = await Bun.file("package.json").json(); packageJson.workspaces.packages = Array.from(new Bun.Glob("packages/**/package.json").scanSync(".")).map((file) => file.slice(0, -"/package.json".length)).sort(); await Bun.write("package.json", JSON.stringify(packageJson, null, 2) + "\n")'
|
||||
RUN rm -f bun.lock && bun install --filter @opencode-ai/stats-server --lockfile-only --ignore-scripts
|
||||
RUN bun install --filter @opencode-ai/stats-server --frozen-lockfile --production --ignore-scripts
|
||||
|
||||
FROM base AS runner
|
||||
|
||||
COPY --from=installer /app ./
|
||||
COPY --from=pruner /app/out/full/ ./
|
||||
|
||||
WORKDIR /app/packages/stats/server
|
||||
|
||||
EXPOSE 3000
|
||||
|
||||
CMD ["bun", "src/server.ts"]
|
||||
33
packages/stats/server/package.json
Normal file
33
packages/stats/server/package.json
Normal file
@@ -0,0 +1,33 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/package.json",
|
||||
"name": "@opencode-ai/stats-server",
|
||||
"version": "1.17.4",
|
||||
"private": true,
|
||||
"type": "module",
|
||||
"license": "MIT",
|
||||
"main": "./src/server.ts",
|
||||
"exports": {
|
||||
".": "./src/server.ts"
|
||||
},
|
||||
"scripts": {
|
||||
"start": "bun src/server.ts",
|
||||
"typecheck": "tsgo --noEmit"
|
||||
},
|
||||
"dependencies": {
|
||||
"@aws-sdk/client-firehose": "3.933.0",
|
||||
"@effect/platform-node": "catalog:",
|
||||
"@opencode-ai/stats-core": "workspace:*",
|
||||
"effect": "catalog:",
|
||||
"sst": "catalog:"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@tsconfig/node22": "catalog:",
|
||||
"@types/bun": "catalog:",
|
||||
"@types/node": "catalog:",
|
||||
"@typescript/native-preview": "catalog:",
|
||||
"typescript": "catalog:"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=22"
|
||||
}
|
||||
}
|
||||
159
packages/stats/server/src/ingest.ts
Normal file
159
packages/stats/server/src/ingest.ts
Normal file
@@ -0,0 +1,159 @@
|
||||
import { Buffer } from "node:buffer"
|
||||
import { FirehoseClient, PutRecordBatchCommand } from "@aws-sdk/client-firehose"
|
||||
import { Effect, Layer, Schema } from "effect"
|
||||
import * as Context from "effect/Context"
|
||||
import { Resource } from "sst/resource"
|
||||
|
||||
const MAX_FIREHOSE_BATCH_SIZE = 500
|
||||
const MAX_FIREHOSE_ATTEMPTS = 3
|
||||
const LAKE_TYPE = /^([A-Za-z0-9_]+)\.([A-Za-z0-9_]+)$/
|
||||
|
||||
type IngestEvent = Record<string, unknown>
|
||||
type LakeRoute = { database: string; table: string }
|
||||
type FirehoseRecord = { Data: Uint8Array }
|
||||
|
||||
export class IngestError extends Schema.TaggedErrorClass<IngestError>()("IngestError", {
|
||||
message: Schema.String,
|
||||
failed: Schema.Number,
|
||||
cause: Schema.optional(Schema.Defect),
|
||||
}) {}
|
||||
|
||||
export declare namespace Ingest {
|
||||
export interface Service {
|
||||
readonly write: (events: unknown[]) => Effect.Effect<{ records: number }, IngestError>
|
||||
}
|
||||
}
|
||||
|
||||
export class Ingest extends Context.Service<Ingest, Ingest.Service>()("@opencode/stats/Ingest") {
|
||||
static readonly layer: Layer.Layer<Ingest> = Layer.effect(
|
||||
Ingest,
|
||||
Effect.sync(() => {
|
||||
const client = new FirehoseClient({})
|
||||
|
||||
const write = Effect.fn("Ingest.write")(function* (events: unknown[]) {
|
||||
if (events.length === 0) return { records: 0 }
|
||||
const counts = countRoutedEvents(events)
|
||||
if (counts.unsupported > 0) {
|
||||
yield* Effect.logWarning(
|
||||
`lake ingest rejected ${JSON.stringify({ records: counts.records, unsupported: counts.unsupported })}`,
|
||||
)
|
||||
return yield* new IngestError({
|
||||
message: "Unsupported lake event type",
|
||||
failed: counts.unsupported,
|
||||
})
|
||||
}
|
||||
if (counts.records === 0) return { records: 0 }
|
||||
|
||||
let batch: FirehoseRecord[] = []
|
||||
let batches = 0
|
||||
let failed = 0
|
||||
|
||||
for (const event of events) {
|
||||
if (!isRecord(event)) continue
|
||||
const route = routeEvent(event)
|
||||
if (!route) continue
|
||||
batch.push(toFirehoseRecord(event, route))
|
||||
if (batch.length < MAX_FIREHOSE_BATCH_SIZE) continue
|
||||
failed += yield* putRecords(client, Resource.LakeIngestConfig.streamName, batch)
|
||||
batches++
|
||||
batch = []
|
||||
}
|
||||
|
||||
if (batch.length > 0) {
|
||||
failed += yield* putRecords(client, Resource.LakeIngestConfig.streamName, batch)
|
||||
batches++
|
||||
}
|
||||
|
||||
if (failed > 0) {
|
||||
yield* Effect.logWarning(`lake ingest incomplete ${JSON.stringify({ records: counts.records, failed })}`)
|
||||
return yield* new IngestError({ message: "Failed to ingest all lake records", failed })
|
||||
}
|
||||
|
||||
yield* Effect.logInfo(`lake ingest complete ${JSON.stringify({ records: counts.records, batches })}`)
|
||||
return { records: counts.records }
|
||||
})
|
||||
|
||||
return Ingest.of({ write })
|
||||
}),
|
||||
)
|
||||
}
|
||||
|
||||
const putRecords: (
|
||||
client: FirehoseClient,
|
||||
streamName: string,
|
||||
records: FirehoseRecord[],
|
||||
attempt?: number,
|
||||
) => Effect.Effect<number, IngestError> = Effect.fn("Ingest.putRecords")(function* (
|
||||
client,
|
||||
streamName,
|
||||
records,
|
||||
attempt = 1,
|
||||
) {
|
||||
const result = yield* Effect.tryPromise({
|
||||
try: () => client.send(new PutRecordBatchCommand({ DeliveryStreamName: streamName, Records: records })),
|
||||
catch: (cause) =>
|
||||
new IngestError({ message: "Failed to write lake records to Firehose", failed: records.length, cause }),
|
||||
}).pipe(
|
||||
Effect.tapError(() =>
|
||||
Effect.logWarning(`firehose batch write failed ${JSON.stringify({ records: records.length, attempt })}`),
|
||||
),
|
||||
)
|
||||
const failed =
|
||||
result.RequestResponses?.flatMap((item, index) => {
|
||||
const record = records[index]
|
||||
if (!item.ErrorCode || !record) return []
|
||||
return [record]
|
||||
}) ?? []
|
||||
|
||||
if (failed.length === 0) return 0
|
||||
if (attempt >= MAX_FIREHOSE_ATTEMPTS) {
|
||||
yield* Effect.logWarning(
|
||||
`firehose batch failed ${JSON.stringify({ records: failed.length, attempts: MAX_FIREHOSE_ATTEMPTS })}`,
|
||||
)
|
||||
return failed.length
|
||||
}
|
||||
|
||||
yield* Effect.logWarning(
|
||||
`firehose batch retrying ${JSON.stringify({ records: failed.length, attempt: attempt + 1 })}`,
|
||||
)
|
||||
yield* Effect.sleep(`${250 * 2 ** (attempt - 1)} millis`)
|
||||
return yield* putRecords(client, streamName, failed, attempt + 1)
|
||||
})
|
||||
|
||||
function countRoutedEvents(events: unknown[]) {
|
||||
let records = 0
|
||||
let unsupported = 0
|
||||
for (const event of events) {
|
||||
if (!isRecord(event)) continue
|
||||
if (routeEvent(event)) records++
|
||||
else unsupported++
|
||||
}
|
||||
return { records, unsupported }
|
||||
}
|
||||
|
||||
function isRecord(item: unknown): item is IngestEvent {
|
||||
return Boolean(item) && typeof item === "object" && !Array.isArray(item)
|
||||
}
|
||||
|
||||
function routeEvent(event: IngestEvent): LakeRoute | undefined {
|
||||
if (typeof event._datalake_key !== "string") return
|
||||
const match = event._datalake_key.match(LAKE_TYPE)
|
||||
if (!match?.[1] || !match[2]) return
|
||||
return {
|
||||
database: match[1],
|
||||
table: match[2],
|
||||
}
|
||||
}
|
||||
|
||||
function toFirehoseRecord(event: IngestEvent, route: LakeRoute): FirehoseRecord {
|
||||
return {
|
||||
Data: Buffer.from(
|
||||
JSON.stringify({
|
||||
...Object.fromEntries(Object.entries(event).filter(([key]) => key !== "_datalake_key")),
|
||||
_lake_database: route.database,
|
||||
_lake_table: route.table,
|
||||
_lake_operation: "insert" as const,
|
||||
}),
|
||||
),
|
||||
}
|
||||
}
|
||||
11
packages/stats/server/src/resource.d.ts
vendored
Normal file
11
packages/stats/server/src/resource.d.ts
vendored
Normal file
@@ -0,0 +1,11 @@
|
||||
import "sst/resource"
|
||||
|
||||
declare module "sst/resource" {
|
||||
export interface Resource {
|
||||
LakeIngestConfig: {
|
||||
secret: string
|
||||
streamName: string
|
||||
type: "sst.sst.Linkable"
|
||||
}
|
||||
}
|
||||
}
|
||||
73
packages/stats/server/src/router.ts
Normal file
73
packages/stats/server/src/router.ts
Normal file
@@ -0,0 +1,73 @@
|
||||
import { Buffer } from "node:buffer"
|
||||
import { timingSafeEqual } from "node:crypto"
|
||||
import { Effect, Schema } from "effect"
|
||||
import * as Semaphore from "effect/Semaphore"
|
||||
import { HttpRouter, HttpServerRequest, HttpServerResponse } from "effect/unstable/http"
|
||||
import { Resource } from "sst/resource"
|
||||
import { Ingest } from "./ingest"
|
||||
import { isShuttingDown } from "./shutdown"
|
||||
|
||||
const MAX_CONCURRENT_INGEST_REQUESTS = 8
|
||||
|
||||
const IngestPayload = Schema.Struct({
|
||||
events: Schema.optional(Schema.Unknown),
|
||||
})
|
||||
|
||||
export const Routes = HttpRouter.use((router) =>
|
||||
Effect.gen(function* () {
|
||||
const ingestService = yield* Ingest
|
||||
const ingestRequests = yield* Semaphore.make(MAX_CONCURRENT_INGEST_REQUESTS)
|
||||
|
||||
yield* Effect.all(
|
||||
[
|
||||
router.add("GET", "/health", () => json(200, { ok: true })),
|
||||
router.add("GET", "/ready", () => json(isShuttingDown() ? 503 : 200, { ok: !isShuttingDown() })),
|
||||
router.add("POST", "/", ingestRequests.withPermit(ingest(ingestService))),
|
||||
],
|
||||
{ discard: true },
|
||||
)
|
||||
}),
|
||||
)
|
||||
|
||||
const ingest = (ingestService: Ingest.Service) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpServerRequest.HttpServerRequest
|
||||
if (!isAuthorized(request.headers)) return yield* json(401, { ok: false, error: "Unauthorized" })
|
||||
|
||||
const payload = yield* HttpServerRequest.schemaBodyJson(IngestPayload).pipe(
|
||||
Effect.match({
|
||||
onFailure: () => undefined,
|
||||
onSuccess: (value) => value,
|
||||
}),
|
||||
)
|
||||
if (!payload) return yield* json(400, { ok: false, error: "Invalid JSON body" })
|
||||
|
||||
const events = Array.isArray(payload.events) ? payload.events : []
|
||||
if (events.length === 0) return yield* json(202, { ok: true, records: 0 })
|
||||
|
||||
return yield* ingestService.write(events).pipe(
|
||||
Effect.flatMap((result) => json(202, { ok: true, records: result.records })),
|
||||
Effect.catchTag("IngestError", (error) =>
|
||||
json(502, { ok: false, records: countRecords(events), failed: error.failed }),
|
||||
),
|
||||
)
|
||||
})
|
||||
|
||||
function isAuthorized(headers: Record<string, string | undefined>) {
|
||||
const actual = Buffer.from(headers.authorization ?? headers.Authorization ?? "")
|
||||
const expected = Buffer.from(`Bearer ${Resource.LakeIngestConfig.secret}`)
|
||||
if (actual.length !== expected.length) return false
|
||||
return timingSafeEqual(actual, expected)
|
||||
}
|
||||
|
||||
function countRecords(items: unknown[]) {
|
||||
let records = 0
|
||||
for (const item of items) {
|
||||
if (Boolean(item) && typeof item === "object" && !Array.isArray(item)) records++
|
||||
}
|
||||
return records
|
||||
}
|
||||
|
||||
function json(status: number, body: Record<string, unknown>) {
|
||||
return HttpServerResponse.json(body, { status }).pipe(Effect.orDie)
|
||||
}
|
||||
28
packages/stats/server/src/server.ts
Normal file
28
packages/stats/server/src/server.ts
Normal file
@@ -0,0 +1,28 @@
|
||||
import * as NodeHttpServer from "@effect/platform-node/NodeHttpServer"
|
||||
import * as NodeRuntime from "@effect/platform-node/NodeRuntime"
|
||||
import { Config, Layer } from "effect"
|
||||
import { HttpRouter } from "effect/unstable/http"
|
||||
import { createServer } from "node:http"
|
||||
import { Ingest } from "./ingest"
|
||||
import { Routes } from "./router"
|
||||
import { registerShutdownSignalHandlers } from "./shutdown"
|
||||
|
||||
registerShutdownSignalHandlers()
|
||||
|
||||
const ServerLive = NodeHttpServer.layerConfig(
|
||||
() => createServer(),
|
||||
Config.all({
|
||||
port: Config.number("PORT").pipe(Config.withDefault(3000)),
|
||||
host: Config.string("HOST").pipe(Config.withDefault("0.0.0.0")),
|
||||
}),
|
||||
)
|
||||
|
||||
const runtimeLayer = Ingest.layer
|
||||
const programLayer = Routes.pipe(Layer.provide(runtimeLayer))
|
||||
const main = Layer.launch(
|
||||
HttpRouter.serve(programLayer, {
|
||||
disableLogger: true,
|
||||
}).pipe(Layer.provideMerge(ServerLive)),
|
||||
)
|
||||
|
||||
NodeRuntime.runMain(main, { disableErrorReporting: true })
|
||||
17
packages/stats/server/src/shutdown.ts
Normal file
17
packages/stats/server/src/shutdown.ts
Normal file
@@ -0,0 +1,17 @@
|
||||
let shuttingDown = false
|
||||
let signalHandlersRegistered = false
|
||||
|
||||
export function isShuttingDown() {
|
||||
return shuttingDown
|
||||
}
|
||||
|
||||
export function registerShutdownSignalHandlers() {
|
||||
if (signalHandlersRegistered) return
|
||||
signalHandlersRegistered = true
|
||||
process.once("SIGTERM", markShuttingDown)
|
||||
process.once("SIGINT", markShuttingDown)
|
||||
}
|
||||
|
||||
function markShuttingDown() {
|
||||
shuttingDown = true
|
||||
}
|
||||
22
packages/stats/server/src/stat-sync.ts
Normal file
22
packages/stats/server/src/stat-sync.ts
Normal file
@@ -0,0 +1,22 @@
|
||||
import * as NodeRuntime from "@effect/platform-node/NodeRuntime"
|
||||
import { Athena } from "@opencode-ai/stats-core/athena"
|
||||
import { layer as statsLayer } from "@opencode-ai/stats-core/runtime"
|
||||
import { syncStats } from "@opencode-ai/stats-core/stat-sync"
|
||||
import { Cause, Effect, Layer, Schedule } from "effect"
|
||||
|
||||
const SYNC_INTERVAL = "1 hour"
|
||||
|
||||
const runtimeLayer = Layer.mergeAll(statsLayer, Athena.layer)
|
||||
const syncPass = syncStats().pipe(
|
||||
Effect.catchCause((cause) =>
|
||||
Effect.logWarning(`stats sync failed ${JSON.stringify({ cause: Cause.pretty(cause) })}`),
|
||||
),
|
||||
)
|
||||
const daemon = Effect.logInfo("stats sync daemon started").pipe(
|
||||
Effect.andThen(syncPass.pipe(Effect.repeat(Schedule.fixed(SYNC_INTERVAL)))),
|
||||
Effect.forkScoped,
|
||||
)
|
||||
|
||||
NodeRuntime.runMain(Layer.launch(Layer.effectDiscard(daemon).pipe(Layer.provide(runtimeLayer))), {
|
||||
disableErrorReporting: true,
|
||||
})
|
||||
10
packages/stats/server/sst-env.d.ts
vendored
Normal file
10
packages/stats/server/sst-env.d.ts
vendored
Normal file
@@ -0,0 +1,10 @@
|
||||
/* This file is auto-generated by SST. Do not edit. */
|
||||
/* tslint:disable */
|
||||
/* eslint-disable */
|
||||
/* deno-fmt-ignore-file */
|
||||
/* biome-ignore-all lint: auto-generated */
|
||||
|
||||
/// <reference path="../../../sst-env.d.ts" />
|
||||
|
||||
import "sst"
|
||||
export {}
|
||||
12
packages/stats/server/tsconfig.json
Normal file
12
packages/stats/server/tsconfig.json
Normal file
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"$schema": "https://json.schemastore.org/tsconfig",
|
||||
"extends": "@tsconfig/node22/tsconfig.json",
|
||||
"compilerOptions": {
|
||||
"module": "ESNext",
|
||||
"moduleResolution": "bundler",
|
||||
"strict": true,
|
||||
"noEmit": true,
|
||||
"types": ["bun", "node"]
|
||||
},
|
||||
"include": ["src", "../core/src/resource.d.ts"]
|
||||
}
|
||||
Reference in New Issue
Block a user