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| /** | |
| * Routing simulation β exercises the real routeRequest() against an in-memory | |
| * DB seeded with synthetic traffic, so you can SEE how each strategy distributes | |
| * requests and how the bandit adapts when a model starts failing. | |
| * | |
| * cd server && npm run build && node dist/scripts/routing-sim.js | |
| */ | |
| process.env.ENCRYPTION_KEY = '0'.repeat(64); | |
| process.env.DEV_MODE = 'true'; | |
| import { initDb, getDb } from '../db/index.js'; | |
| import { encrypt } from '../lib/crypto.js'; | |
| import { | |
| routeRequest, refreshStatsCache, setRoutingStrategy, getRoutingScores, | |
| } from '../services/router.js'; | |
| import type { RoutingStrategy } from '../services/scoring.js'; | |
| interface Profile { | |
| platform: string; modelId: string; name: string; | |
| intelligenceRank: number; sizeLabel: string; budget: string; | |
| // synthetic history | |
| successes: number; failures: number; outTokens: number; latencyMs: number; ttfbMs: number; | |
| } | |
| // Deliberately no model that wins on every axis β so each strategy's weight | |
| // vector picks a DIFFERENT winner (that's the whole point of the redesign). | |
| const PROFILES: Profile[] = [ | |
| // Frontier intelligence, good-not-great reliability, genuinely slow β wins SMARTEST. | |
| { platform: 'google', modelId: 'gemini-x', name: 'Frontier-Smart', intelligenceRank: 1, sizeLabel: 'Frontier', budget: '~50M', successes: 22, failures: 4, outTokens: 200, latencyMs: 5000, ttfbMs: 2500 }, | |
| // Small/dumb but blazing fast and reliable β wins FASTEST. | |
| { platform: 'groq', modelId: 'llama-fast', name: 'Speed-King', intelligenceRank: 9, sizeLabel: 'Small', budget: '~50M', successes: 27, failures: 3, outTokens: 1100, latencyMs: 700, ttfbMs: 110 }, | |
| // Middling intel/speed but rock-solid reliability β wins RELIABLE. | |
| { platform: 'openrouter', modelId: 'rock', name: 'Rock-Solid', intelligenceRank: 5, sizeLabel: 'Medium', budget: '~50M', successes: 40, failures: 1, outTokens: 250, latencyMs: 2000, ttfbMs: 1500 }, | |
| // Large/smart but flaky β high intelligence dragged down by failures. | |
| { platform: 'cerebras', modelId: 'smart-flaky', name: 'Smart-Flaky', intelligenceRank: 3, sizeLabel: 'Large', budget: '~50M', successes: 18, failures: 14, outTokens: 500, latencyMs: 1500, ttfbMs: 600 }, | |
| ]; | |
| function seed() { | |
| const db = getDb(); | |
| db.exec('DELETE FROM fallback_config; DELETE FROM api_keys; DELETE FROM models; DELETE FROM requests;'); | |
| const insModel = db.prepare(` | |
| INSERT INTO models (platform, model_id, display_name, intelligence_rank, speed_rank, size_label, rpm_limit, rpd_limit, tpm_limit, tpd_limit, monthly_token_budget, enabled) | |
| VALUES (?, ?, ?, ?, 1, ?, 100000, 1000000, 100000000, 1000000000, ?, 1) | |
| `); | |
| const insFb = db.prepare('INSERT INTO fallback_config (model_db_id, priority, enabled) VALUES (?, ?, 1)'); | |
| const insHist = db.prepare(` | |
| INSERT INTO requests (platform, model_id, key_id, status, input_tokens, output_tokens, latency_ms, error, ttfb_ms) | |
| VALUES (?, ?, 1, ?, 0, ?, ?, ?, ?) | |
| `); | |
| PROFILES.forEach((p, i) => { | |
| insModel.run(p.platform, p.modelId, p.name, p.intelligenceRank, p.sizeLabel, p.budget); | |
| const id = (db.prepare('SELECT id FROM models WHERE platform=? AND model_id=?').get(p.platform, p.modelId) as { id: number }).id; | |
| insFb.run(id, i + 1); | |
| const { encrypted, iv, authTag } = encrypt(`key-${p.platform}`); | |
| db.prepare(`INSERT INTO api_keys (platform, label, encrypted_key, iv, auth_tag, status, enabled) VALUES (?, 'sim', ?, ?, ?, 'healthy', 1)`) | |
| .run(p.platform, encrypted, iv, authTag); | |
| for (let s = 0; s < p.successes; s++) insHist.run(p.platform, p.modelId, 'success', p.outTokens, p.latencyMs, null, p.ttfbMs); | |
| for (let f = 0; f < p.failures; f++) insHist.run(p.platform, p.modelId, 'error', 0, p.latencyMs, 'sim-fail', p.ttfbMs); | |
| }); | |
| } | |
| function distribution(runs: number): Map<string, number> { | |
| const counts = new Map<string, number>(); | |
| for (let i = 0; i < runs; i++) { | |
| const r = routeRequest(100); | |
| counts.set(r.displayName, (counts.get(r.displayName) ?? 0) + 1); | |
| } | |
| return counts; | |
| } | |
| function pct(n: number, total: number): string { | |
| return `${((n / total) * 100).toFixed(1)}%`.padStart(6); | |
| } | |
| function printDistribution(title: string, counts: Map<string, number>, runs: number) { | |
| console.log(`\n ${title}`); | |
| const sorted = [...counts.entries()].sort((a, b) => b[1] - a[1]); | |
| for (const [name, n] of sorted) { | |
| const bar = 'β'.repeat(Math.round((n / runs) * 30)); | |
| console.log(` ${name.padEnd(22)} ${pct(n, runs)} ${bar}`); | |
| } | |
| } | |
| function printScores() { | |
| const { scores } = getRoutingScores(); | |
| console.log(' model rel spd int guard score'); | |
| for (const s of scores) { | |
| const guard = s.headroom * s.rateLimit; | |
| console.log( | |
| ` ${s.displayName.padEnd(22)} ` + | |
| `${Math.round(s.reliability * 100).toString().padStart(3)} ` + | |
| `${Math.round(s.speed * 100).toString().padStart(3)} ` + | |
| `${Math.round(s.intelligence * 100).toString().padStart(3)} ` + | |
| `${guard.toFixed(2).padStart(5)} ` + | |
| `${s.score.toFixed(3)}`, | |
| ); | |
| } | |
| } | |
| function main() { | |
| initDb(':memory:'); | |
| seed(); | |
| const RUNS = 2000; | |
| console.log('\nββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ'); | |
| console.log(' ROUTING SIMULATION β 4 models, 2000 requests per strategy'); | |
| console.log('ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ'); | |
| console.log('\n Synthetic profiles:'); | |
| for (const p of PROFILES) { | |
| const rate = (p.successes / (p.successes + p.failures) * 100).toFixed(0); | |
| const tps = (p.outTokens * 1000 / p.latencyMs).toFixed(0); | |
| console.log(` ${p.name.padEnd(22)} ${p.sizeLabel.padEnd(9)} success ${rate}% ${tps} tok/s ${p.ttfbMs}ms ttfb`); | |
| } | |
| const strategies: RoutingStrategy[] = ['priority', 'balanced', 'smartest', 'fastest', 'reliable']; | |
| for (const strat of strategies) { | |
| setRoutingStrategy(strat); | |
| refreshStatsCache(getDb(), true); | |
| if (strat === 'balanced') { console.log('\n ββ balanced score breakdown ββ'); printScores(); } | |
| printDistribution(`Strategy: ${strat.toUpperCase()}`, distribution(RUNS), RUNS); | |
| } | |
| // ββ Adaptation: the favored model under 'balanced' suddenly starts failing ββ | |
| console.log('\nββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ'); | |
| console.log(' ADAPTATION β inject a failure burst into the top model'); | |
| console.log('ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ'); | |
| setRoutingStrategy('balanced'); | |
| refreshStatsCache(getDb(), true); | |
| const before = distribution(RUNS); | |
| printDistribution('Before (balanced, steady state)', before, RUNS); | |
| // Find the current favorite and slam it with fresh failures. | |
| const fav = [...before.entries()].sort((a, b) => b[1] - a[1])[0][0]; | |
| const favProfile = PROFILES.find(p => p.name === fav)!; | |
| const db = getDb(); | |
| const insHist = db.prepare(` | |
| INSERT INTO requests (platform, model_id, key_id, status, input_tokens, output_tokens, latency_ms, error, ttfb_ms) | |
| VALUES (?, ?, 1, 'error', 0, 0, 1000, 'outage', NULL) | |
| `); | |
| for (let i = 0; i < 300; i++) insHist.run(favProfile.platform, favProfile.modelId); | |
| console.log(`\n β Injected 300 fresh failures into "${fav}" (simulated outage)β¦`); | |
| refreshStatsCache(getDb(), true); | |
| printScores(); | |
| printDistribution('After (balanced, post-outage)', distribution(RUNS), RUNS); | |
| console.log(''); | |
| } | |
| main(); | |