Files
OmniRoute/tests/unit/arena-elo-sync.test.ts
MumuTW a15af27c78 fix(intelligence): synthesize base-model arena rows from effort/harness variants; drop MODEL_ALIAS_MAP (#11504) (#11506)
Validated in a combined 4-PR batch worktree off release/v3.8.51 tip (stacked on #11492, merged first).
- TDD-first: the new base-model-synthesis describe block failed 5/5 pre-fix, passes now
- Focused test: tests/unit/arena-elo-sync.test.ts — 56/56 pass, part of batch's 246/246 node:test + 126/126 vitest runs
- typecheck:core, file-size, changelog-integrity, complexity, cognitive-complexity, check:cycles — all OK

Thanks for closing the arena-lookup gap for harness/effort-annotated leaderboard rows and retiring MODEL_ALIAS_MAP's cross-generation score copying in favor of scoresAs + registry-owned aliases.
2026-08-25 13:51:56 -03:00

958 lines
33 KiB
TypeScript

/**
* Unit tests for src/lib/arenaEloSync.ts
*
* Uses Node.js native test runner. All external fetch calls are mocked.
* DB functions use a real in-memory SQLite instance via node:sqlite (DatabaseSync),
* injected through the core module's globalThis.__omnirouteDb singleton.
* backupDbFile is called during first sync but safely no-ops (no file on disk).
*/
import { describe, it, beforeEach, afterEach } from "node:test";
import assert from "node:assert/strict";
import fs from "node:fs";
import os from "node:os";
import path from "node:path";
const TEST_DATA_DIR = fs.mkdtempSync(path.join(os.tmpdir(), "omniroute-arena-elo-test-"));
process.env.DATA_DIR = TEST_DATA_DIR;
const MIGRATION_SQL = fs.readFileSync(
path.resolve(
import.meta.dirname ?? __dirname,
"../../src/lib/db/migrations/097_model_intelligence.sql"
),
"utf8"
);
import { tryOpenSync } from "../../src/lib/db/adapters/driverFactory";
import type { SqliteAdapter } from "../../src/lib/db/adapters/types";
const core = await import("../../src/lib/db/core.ts");
const {
normalizeModelName,
transformToModelIntelligence,
fetchArenaLeaderboards,
syncArenaElo,
getArenaEloSyncStatus,
initArenaEloSync,
stopArenaEloSync,
} = await import("../../src/lib/arenaEloSync.ts");
const { setFeatureFlagOverride, removeFeatureFlagOverride } =
await import("../../src/lib/db/featureFlags.ts");
const { resolveScoresAs } = await import("../../open-sse/services/autoCombo/scoresAs.ts");
import type {
ArenaLeaderboardData,
ArenaLeaderboardMap,
ArenaModelEntry,
} from "../../src/lib/arenaEloSync.ts";
const originalFetch = globalThis.fetch;
function mockFetch(impl: (url: string, opts?: RequestInit) => Promise<Response>): void {
globalThis.fetch = impl as typeof fetch;
}
function restoreFetch(): void {
globalThis.fetch = originalFetch;
}
function jsonResponse(data: unknown, status = 200): Response {
return new Response(JSON.stringify(data), {
status,
headers: { "Content-Type": "application/json" },
});
}
function makeModelEntry(overrides: Partial<ArenaModelEntry> = {}): ArenaModelEntry {
return {
rank: 1,
model: "anthropic/claude-sonnet",
vendor: "Anthropic",
score: 1350,
ci: 10,
votes: 5000,
license: "proprietary",
...overrides,
};
}
function makeLeaderboardData(
models: ArenaModelEntry[] = [],
category = "text"
): ArenaLeaderboardData {
return {
meta: { leaderboard: category, model_count: models.length },
models,
};
}
function makeLeaderboardMap(
categories: Partial<Record<string, ArenaModelEntry[]>>
): ArenaLeaderboardMap {
const map: ArenaLeaderboardMap = {};
for (const [cat, models] of Object.entries(categories)) {
map[cat] = makeLeaderboardData(models ?? [], cat);
}
return map;
}
let testAdapter: SqliteAdapter;
function createTestAdapter(): SqliteAdapter {
const patchedSql = MIGRATION_SQL.replace(
/\n\s*synced_at TEXT NOT NULL DEFAULT \(datetime\('now'\)\)/,
"\n synced_at TEXT NOT NULL"
);
const adapter = tryOpenSync(":memory:")!;
adapter.exec(`
CREATE TABLE IF NOT EXISTS key_value (
namespace TEXT NOT NULL,
key TEXT NOT NULL,
value TEXT NOT NULL,
PRIMARY KEY (namespace, key)
);
`);
adapter.exec(patchedSql);
return adapter;
}
function countArenaEloEntries(): number {
const row = testAdapter
.prepare("SELECT COUNT(*) as cnt FROM model_intelligence WHERE source = 'arena_elo'")
.get() as Record<string, unknown> | undefined;
return Number(row?.cnt ?? 0);
}
function getAllEntries(): Array<Record<string, unknown>> {
return testAdapter
.prepare("SELECT * FROM model_intelligence WHERE source = 'arena_elo' ORDER BY model, category")
.all() as Array<Record<string, unknown>>;
}
beforeEach(() => {
core.resetDbInstance();
testAdapter = createTestAdapter();
globalThis.__omnirouteDb = testAdapter as never;
stopArenaEloSync();
delete process.env.ARENA_ELO_SYNC_ENABLED;
});
afterEach(() => {
restoreFetch();
stopArenaEloSync();
delete globalThis.__omnirouteDb;
delete process.env.ARENA_ELO_SYNC_ENABLED;
});
// ═══════════════════════════════════════════════════════════
// 1. normalizeModelName()
// ═══════════════════════════════════════════════════════════
describe("normalizeModelName()", () => {
it("strips 'anthropic/' vendor prefix", () => {
assert.strictEqual(
normalizeModelName("anthropic/claude-opus-4-6-thinking"),
"claude-opus-4-6-thinking"
);
});
it("strips 'openai/' vendor prefix", () => {
assert.strictEqual(normalizeModelName("openai/gpt-5.5"), "gpt-5.5");
});
it("strips 'google/' vendor prefix", () => {
assert.strictEqual(normalizeModelName("google/gemini-3-flash"), "gemini-3-flash");
});
it("strips 'meta/' vendor prefix", () => {
assert.strictEqual(normalizeModelName("meta/llama-4"), "llama-4");
});
it("strips 'deepseek/' vendor prefix", () => {
assert.strictEqual(normalizeModelName("deepseek/deepseek-r1"), "deepseek-r1");
});
it("strips 'xai/' vendor prefix", () => {
assert.strictEqual(normalizeModelName("xai/grok-4"), "grok-4");
});
it("lowercases the model name", () => {
assert.strictEqual(normalizeModelName("Claude-Sonnet-4"), "claude-sonnet-4");
});
it("lowercases vendor prefix before matching", () => {
assert.strictEqual(normalizeModelName("OpenAI/GPT-5.5"), "gpt-5.5");
});
it("returns name unchanged when no vendor prefix matches", () => {
assert.strictEqual(normalizeModelName("my-custom-model"), "my-custom-model");
});
});
// ═══════════════════════════════════════════════════════════
// 2. transformToModelIntelligence()
// ═══════════════════════════════════════════════════════════
describe("transformToModelIntelligence()", () => {
it("ELO normalization: 1500 ELO (max) with range 1000-1500 → score ≈ 0.98", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "top-model", score: 1500, votes: 5000, rank: 1 }),
makeModelEntry({ model: "low-model", score: 1000, votes: 5000, rank: 2 }),
],
});
const entries = transformToModelIntelligence(data);
const topEntry = entries.find((e) => e.model === "top-model" && e.category === "default");
assert.ok(topEntry);
// taskFit = 0.4 + 0.58 * ((1500-1000) / 500) = 0.98
assert.ok(Math.abs(topEntry.score - 0.98) < 0.001, `got ${topEntry.score}`);
});
it("ELO normalization: 1000 ELO (min) with range 1000-1500 → score ≈ 0.40", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "top-model", score: 1500, votes: 5000, rank: 1 }),
makeModelEntry({ model: "low-model", score: 1000, votes: 5000, rank: 2 }),
],
});
const entries = transformToModelIntelligence(data);
const lowEntry = entries.find((e) => e.model === "low-model" && e.category === "default");
assert.ok(lowEntry);
// taskFit = 0.4 + 0.58 * ((1000-1000) / 500) = 0.4
assert.ok(Math.abs(lowEntry.score - 0.4) < 0.001, `got ${lowEntry.score}`);
});
it("votes < 100 → confidence='low'", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "sparse-model", score: 1200, votes: 50, rank: 5 }),
makeModelEntry({ model: "baseline", score: 1100, votes: 5000, rank: 10 }),
],
});
const entries = transformToModelIntelligence(data);
const entry = entries.find((e) => e.model === "sparse-model" && e.category === "default");
assert.ok(entry);
assert.strictEqual(entry.confidence, "low");
});
it("votes >= 1000 → confidence='medium'", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "mid-model", score: 1200, votes: 1500, rank: 3 }),
makeModelEntry({ model: "baseline", score: 1100, votes: 5000, rank: 10 }),
],
});
const entries = transformToModelIntelligence(data);
const entry = entries.find((e) => e.model === "mid-model" && e.category === "default");
assert.ok(entry);
assert.strictEqual(entry.confidence, "medium");
});
it("votes >= 5000 → confidence='high'", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "popular-model", score: 1300, votes: 8000, rank: 1 }),
makeModelEntry({ model: "baseline", score: 1100, votes: 3000, rank: 5 }),
],
});
const entries = transformToModelIntelligence(data);
const entry = entries.find((e) => e.model === "popular-model" && e.category === "default");
assert.ok(entry);
assert.strictEqual(entry.confidence, "high");
});
it("category mapping: 'text' → [default, review, documentation, debugging]", () => {
const data = makeLeaderboardMap({
text: [makeModelEntry({ model: "text-model", score: 1200, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
const categories = entries
.filter((e) => e.model === "text-model")
.map((e) => e.category)
.sort();
assert.deepStrictEqual(categories, ["debugging", "default", "documentation", "review"]);
});
it("category mapping: 'code' → [coding]", () => {
const data = makeLeaderboardMap({
code: [makeModelEntry({ model: "code-model", score: 1300, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
const categories = entries.filter((e) => e.model === "code-model").map((e) => e.category);
assert.deepStrictEqual(categories, ["coding"]);
});
it("expires_at is set to ~7 days in the future", () => {
const before = Date.now();
const data = makeLeaderboardMap({
text: [makeModelEntry({ model: "test-model", score: 1200, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
const after = Date.now();
const entry = entries.find((e) => e.model === "test-model" && e.category === "default");
assert.ok(entry);
assert.ok(entry.expiresAt);
const expiresMs = new Date(entry.expiresAt).getTime();
const sevenDaysMs = 7 * 24 * 60 * 60 * 1000;
assert.ok(expiresMs >= before + sevenDaysMs - 2000, `expiresAt too early: ${entry.expiresAt}`);
assert.ok(expiresMs <= after + sevenDaysMs + 2000, `expiresAt too late: ${entry.expiresAt}`);
});
it("source is 'arena_elo' for all entries", () => {
const data = makeLeaderboardMap({
text: [makeModelEntry({ model: "test-model", score: 1200, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
for (const entry of entries) {
assert.strictEqual(entry.source, "arena_elo");
}
});
it("does not copy a variant's score onto a different generation (MODEL_ALIAS_MAP removed, #11504)", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({
model: "anthropic/claude-opus-4-6-thinking",
score: 1400,
votes: 5000,
rank: 1,
}),
],
});
const entries = transformToModelIntelligence(data);
const models = entries.map((e) => e.model);
assert.ok(models.includes("claude-opus-4-6-thinking"));
// Was asserted the other way round while MODEL_ALIAS_MAP existed: it copied this
// score onto `claude-opus-4`, so a claude-opus-4 request read a 4.6-thinking ELO.
assert.ok(!models.includes("claude-opus-4"));
assert.ok(!models.includes("anthropic/claude-opus-4"));
});
it("empty leaderboard → no entries", () => {
const data = makeLeaderboardMap({ text: [] });
const entries = transformToModelIntelligence(data);
assert.strictEqual(entries.length, 0);
});
it("skips unknown leaderboard categories (e.g. vision)", () => {
const data = makeLeaderboardMap({
vision: [makeModelEntry({ model: "vision-model", score: 1300, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
assert.strictEqual(entries.length, 0);
});
it("preserves eloRaw from the leaderboard", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "test-model", score: 1337, votes: 5000, rank: 1 }),
makeModelEntry({ model: "other-model", score: 1100, votes: 3000, rank: 2 }),
],
});
const entries = transformToModelIntelligence(data);
const entry = entries.find((e) => e.model === "test-model" && e.category === "default");
assert.ok(entry);
assert.strictEqual(entry.eloRaw, 1337);
});
it("handles single-model leaderboard (eloRange = 1, avoids division by zero)", () => {
const data = makeLeaderboardMap({
text: [makeModelEntry({ model: "only-model", score: 1200, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
assert.ok(entries.length > 0);
const entry = entries.find((e) => e.model === "only-model" && e.category === "default");
assert.ok(entry);
assert.ok(Math.abs(entry.score - 0.4) < 0.001);
});
it("rounds score to 4 decimal places", () => {
const data = makeLeaderboardMap({
text: [
makeModelEntry({ model: "model-a", score: 1300, votes: 200, rank: 1 }),
makeModelEntry({ model: "model-b", score: 1000, votes: 200, rank: 2 }),
],
});
const entries = transformToModelIntelligence(data);
for (const entry of entries) {
const str = entry.score.toString();
const dot = str.indexOf(".");
if (dot !== -1) {
assert.ok(str.length - dot - 1 <= 4, `score ${entry.score} > 4 decimals`);
}
}
});
});
// ═══════════════════════════════════════════════════════════
// 2b. Variant → base row synthesis (#11504)
// ═══════════════════════════════════════════════════════════
describe("transformToModelIntelligence() — base-model synthesis", () => {
it("normalizeModelName strips a trailing harness annotation", () => {
assert.strictEqual(
normalizeModelName("gpt-5.6-sol-xhigh (codex-harness)"),
"gpt-5.6-sol-xhigh"
);
});
it("normalizeModelName strips vendor prefix and harness annotation together", () => {
assert.strictEqual(
normalizeModelName("OpenAI/GPT-5.6-Sol-xhigh (Codex-Harness)"),
"gpt-5.6-sol-xhigh"
);
});
it("harness-annotated variant yields both the variant row and a base row", () => {
const data = makeLeaderboardMap({
code: [
makeModelEntry({
model: "gpt-5.6-sol-xhigh (codex-harness)",
score: 1700,
votes: 5000,
rank: 1,
}),
],
});
const entries = transformToModelIntelligence(data);
const coding = entries.filter((e) => e.category === "coding").map((e) => e.model);
assert.ok(coding.includes("gpt-5.6-sol-xhigh"), "variant row is kept");
assert.ok(coding.includes("gpt-5.6-sol"), "base row is synthesized");
// `gpt-5.6` is a vendor alias of `gpt-5.6-sol`, resolved at lookup time — never stored here.
assert.ok(!coding.includes("gpt-5.6"));
});
it("base row carries the best variant's score and eloRaw", () => {
const data = makeLeaderboardMap({
code: [
makeModelEntry({ model: "claude-opus-5-max", score: 1691, votes: 5000, rank: 1 }),
makeModelEntry({ model: "claude-opus-5-high", score: 1663, votes: 5000, rank: 2 }),
],
});
const entries = transformToModelIntelligence(data);
const base = entries.find((e) => e.model === "claude-opus-5" && e.category === "coding");
const max = entries.find((e) => e.model === "claude-opus-5-max" && e.category === "coding");
assert.ok(base, "synthesized base row exists");
assert.ok(max);
assert.strictEqual(base.eloRaw, 1691);
assert.strictEqual(base.score, max.score);
});
it("never lowers an explicitly measured base row", () => {
const data = makeLeaderboardMap({
code: [
makeModelEntry({ model: "claude-opus-5", score: 1700, votes: 5000, rank: 1 }),
makeModelEntry({ model: "claude-opus-5-max", score: 1691, votes: 5000, rank: 2 }),
],
});
const entries = transformToModelIntelligence(data);
const base = entries.filter((e) => e.model === "claude-opus-5" && e.category === "coding");
assert.strictEqual(base.length, 1);
assert.strictEqual(base[0].eloRaw, 1700);
});
it("does not collapse generations (regression guard for the deleted alias map)", () => {
const data = makeLeaderboardMap({
text: [makeModelEntry({ model: "openai/gpt-5.5", score: 1600, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
const models = entries.map((e) => e.model);
assert.ok(models.includes("gpt-5.5"));
assert.ok(!models.includes("gpt-5"), "gpt-5.5 must never emit a gpt-5 row");
});
it("synthesizes nothing when the stripped base is not a routable catalog id", () => {
// Catalog-anchored by construction: assert the premise instead of a frozen catalog fact.
assert.strictEqual(resolveScoresAs("grok-4.6-fast-high").via, null);
const data = makeLeaderboardMap({
code: [makeModelEntry({ model: "grok-4.6-fast-high", score: 1600, votes: 5000, rank: 1 })],
});
const entries = transformToModelIntelligence(data);
const models = entries.map((e) => e.model);
assert.deepStrictEqual(models, ["grok-4.6-fast-high"]);
});
it("is idempotent and emits no duplicate (model, category) keys", () => {
const data = makeLeaderboardMap({
code: [
makeModelEntry({ model: "claude-opus-5-max", score: 1691, votes: 5000, rank: 1 }),
makeModelEntry({ model: "claude-opus-5-high", score: 1663, votes: 5000, rank: 2 }),
makeModelEntry({
model: "gpt-5.6-sol-xhigh (codex-harness)",
score: 1700,
votes: 5000,
rank: 3,
}),
],
});
const first = transformToModelIntelligence(data);
const second = transformToModelIntelligence(data);
const strip = (entries: ReturnType<typeof transformToModelIntelligence>) =>
entries.map(({ expiresAt: _expiresAt, ...rest }) => rest);
assert.deepStrictEqual(strip(second), strip(first));
const keys = first.map((e) => `${e.model}|${e.category}`);
assert.strictEqual(new Set(keys).size, keys.length);
});
});
// ═══════════════════════════════════════════════════════════
// 3. fetchArenaLeaderboards()
// ═══════════════════════════════════════════════════════════
describe("fetchArenaLeaderboards()", () => {
it("successful fetch with valid JSON returns both leaderboards", async () => {
const textData = makeLeaderboardData(
[makeModelEntry({ model: "text-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
const codeData = makeLeaderboardData(
[makeModelEntry({ model: "code-model", score: 1300, votes: 5000, rank: 1 })],
"code"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(codeData);
return new Response("Not found", { status: 404 });
});
const result = await fetchArenaLeaderboards();
assert.ok(result.text);
assert.ok(result.code);
assert.strictEqual(result.text.models.length, 1);
assert.strictEqual(result.code.models.length, 1);
});
it("failed fetch (non-200 status) throws with descriptive message", async () => {
mockFetch(async () => {
return new Response("Internal Server Error", { status: 500 });
});
await assert.rejects(
() => fetchArenaLeaderboards(),
(err: unknown) => {
assert.ok(err instanceof Error);
assert.ok(err.message.includes("All Arena leaderboard fetches failed"));
return true;
}
);
});
it("all fetches fail (network error) → throws", async () => {
mockFetch(async () => {
throw new Error("Network error: ECONNREFUSED");
});
await assert.rejects(
() => fetchArenaLeaderboards(),
(err: unknown) => {
assert.ok(err instanceof Error);
assert.ok(err.message.includes("All Arena leaderboard fetches failed"));
return true;
}
);
});
it("succeeds when one category fails but another succeeds", async () => {
const textData = makeLeaderboardData(
[makeModelEntry({ model: "text-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return new Response("Error", { status: 500 });
return new Response("Not found", { status: 404 });
});
const result = await fetchArenaLeaderboards();
assert.ok(result.text);
assert.strictEqual(result.code, undefined);
});
it("invalid JSON in response → throws when all responses are invalid", async () => {
mockFetch(async () => {
return new Response("not-json", {
status: 200,
headers: { "Content-Type": "text/plain" },
});
});
await assert.rejects(
() => fetchArenaLeaderboards(),
(err: unknown) => {
assert.ok(err instanceof Error);
assert.ok(err.message.includes("All Arena leaderboard fetches failed"));
return true;
}
);
});
});
// ═══════════════════════════════════════════════════════════
// 4. syncArenaElo()
// ═══════════════════════════════════════════════════════════
describe("syncArenaElo()", () => {
it("happy path: returns success=true with correct modelCount", async () => {
const textData = makeLeaderboardData(
[makeModelEntry({ model: "gpt-5.5", score: 1200, votes: 5000, rank: 1 })],
"text"
);
const codeData = makeLeaderboardData(
[makeModelEntry({ model: "deepseek-r1", score: 1300, votes: 5000, rank: 1 })],
"code"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(codeData);
return new Response("Not found", { status: 404 });
});
const result = await syncArenaElo();
assert.strictEqual(result.success, true);
assert.strictEqual(result.source, "arena_elo");
assert.ok(result.modelCount > 0);
const dbCount = countArenaEloEntries();
assert.ok(dbCount > 0);
assert.strictEqual(dbCount, result.modelCount);
});
it("happy path: entries in DB have correct source and categories", async () => {
const textData = makeLeaderboardData(
[makeModelEntry({ model: "unique-test-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
await syncArenaElo();
const entries = getAllEntries().filter((e) => String(e.model) === "unique-test-model");
const categories = entries.map((e) => String(e.category)).sort();
assert.deepStrictEqual(categories, ["debugging", "default", "documentation", "review"]);
for (const entry of entries) {
assert.strictEqual(entry.source, "arena_elo");
}
});
it("dryRun=true → does not call bulkUpsertModelIntelligence", async () => {
const textData = makeLeaderboardData(
[makeModelEntry({ model: "test-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
const result = await syncArenaElo(true);
assert.strictEqual(result.success, true);
assert.ok(result.modelCount > 0);
const dbCount = countArenaEloEntries();
assert.strictEqual(dbCount, 0, "dryRun should not write to DB");
});
it("dryRun=true does not update lastSyncTime", async () => {
// Reset module-level state by observing that before this test's dryRun,
// lastSync should remain unchanged from whatever it was.
// Since we can't reset module-level vars, we verify that a dryRun
// after a non-dryRun doesn't overwrite the model count.
const statusBefore = getArenaEloSyncStatus();
const textData = makeLeaderboardData(
[makeModelEntry({ model: "test-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
await syncArenaElo(true);
const statusAfter = getArenaEloSyncStatus();
// dryRun should not change the modelCount
assert.strictEqual(statusAfter.lastSyncModelCount, statusBefore.lastSyncModelCount);
});
it("API failure → returns success=false with error", async () => {
mockFetch(async () => {
throw new Error("Network down");
});
const result = await syncArenaElo();
assert.strictEqual(result.success, false);
assert.strictEqual(result.source, "arena_elo");
assert.strictEqual(result.modelCount, 0);
assert.ok(result.error);
assert.ok(
result.error!.includes("All Arena leaderboard fetches failed"),
`unexpected: ${result.error}`
);
});
it("calls deleteExpiredIntelligence before writing new entries", async () => {
testAdapter
.prepare(
"INSERT INTO model_intelligence (model, source, category, score, elo_raw, confidence, synced_at, expires_at) VALUES (?, ?, ?, ?, ?, ?, ?, ?)"
)
.run(
"old-model",
"arena_elo",
"default",
0.5,
1000,
"low",
"2025-01-01T00:00:00Z",
"2020-01-01T00:00:00Z"
);
assert.strictEqual(countArenaEloEntries(), 1);
const textData = makeLeaderboardData(
[makeModelEntry({ model: "new-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
const syncResult = await syncArenaElo();
assert.strictEqual(syncResult.success, true);
const expiredEntry = testAdapter
.prepare("SELECT * FROM model_intelligence WHERE model = 'old-model'")
.get();
assert.strictEqual(expiredEntry, undefined);
});
it("handles empty leaderboard gracefully (0 entries, no DB write)", async () => {
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(makeLeaderboardData([], "text"));
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
const result = await syncArenaElo();
assert.strictEqual(result.success, true);
assert.strictEqual(result.modelCount, 0);
assert.strictEqual(countArenaEloEntries(), 0);
});
it("updates lastSyncTime after successful sync", async () => {
const textData = makeLeaderboardData(
[makeModelEntry({ model: "test-model", score: 1200, votes: 5000, rank: 1 })],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
await syncArenaElo();
const status = getArenaEloSyncStatus();
assert.ok(status.lastSync);
assert.ok(status.lastSyncModelCount > 0);
});
it("stores no cross-generation alias rows in the DB (MODEL_ALIAS_MAP removed, #11504)", async () => {
const textData = makeLeaderboardData(
[
makeModelEntry({
model: "anthropic/claude-opus-4-6-thinking",
score: 1400,
votes: 5000,
rank: 1,
}),
],
"text"
);
mockFetch(async (url: string) => {
if (url.includes("name=text")) return jsonResponse(textData);
if (url.includes("name=code")) return jsonResponse(makeLeaderboardData([], "code"));
return new Response("Not found", { status: 404 });
});
await syncArenaElo();
const entries = getAllEntries();
const models = entries.map((e) => String(e.model));
assert.ok(models.includes("claude-opus-4-6-thinking"));
assert.ok(!models.includes("claude-opus-4"));
});
});
// ═══════════════════════════════════════════════════════════
// 5. getArenaEloSyncStatus()
// ═══════════════════════════════════════════════════════════
describe("getArenaEloSyncStatus()", () => {
it("returns correct structure with all expected keys", () => {
const status = getArenaEloSyncStatus();
assert.ok("enabled" in status);
assert.ok("lastSync" in status);
assert.ok("lastSyncModelCount" in status);
assert.ok("nextSync" in status);
assert.ok("intervalMs" in status);
assert.ok("sources" in status);
});
it("returns sources containing 'arena_elo'", () => {
const status = getArenaEloSyncStatus();
assert.deepStrictEqual(status.sources, ["arena_elo"]);
});
it("returns intervalMs as a positive number", () => {
const status = getArenaEloSyncStatus();
assert.ok(typeof status.intervalMs === "number");
assert.ok(status.intervalMs > 0);
});
it("returns lastSyncModelCount as 0 before any non-dryRun sync completes in this suite context", () => {
// Module-level lastSyncTime may leak from earlier tests in the suite,
// but the structural fields are always present.
const status = getArenaEloSyncStatus();
assert.ok(typeof status.lastSync === "string" || status.lastSync === null);
assert.ok(typeof status.lastSyncModelCount === "number");
assert.ok(typeof status.nextSync === "string" || status.nextSync === null);
});
it("reflects ARENA_ELO_SYNC_ENABLED env var (on by default, opt-out)", () => {
const original = process.env.ARENA_ELO_SYNC_ENABLED;
process.env.ARENA_ELO_SYNC_ENABLED = "true";
const enabledStatus = getArenaEloSyncStatus();
assert.strictEqual(enabledStatus.enabled, true);
process.env.ARENA_ELO_SYNC_ENABLED = "false";
const disabledStatus = getArenaEloSyncStatus();
assert.strictEqual(disabledStatus.enabled, false);
// Default (unset) is now enabled — only an explicit "false" opts out.
delete process.env.ARENA_ELO_SYNC_ENABLED;
const defaultStatus = getArenaEloSyncStatus();
assert.strictEqual(defaultStatus.enabled, true);
if (original !== undefined) {
process.env.ARENA_ELO_SYNC_ENABLED = original;
} else {
delete process.env.ARENA_ELO_SYNC_ENABLED;
}
});
it("reflects dashboard feature flag DB overrides before env values", () => {
process.env.ARENA_ELO_SYNC_ENABLED = "true";
try {
setFeatureFlagOverride("ARENA_ELO_SYNC_ENABLED", "false");
const status = getArenaEloSyncStatus();
assert.strictEqual(status.enabled, false);
} finally {
removeFeatureFlagOverride("ARENA_ELO_SYNC_ENABLED");
}
});
it("falls back to the env value if the feature flag store is unavailable", () => {
testAdapter.exec("DROP TABLE key_value");
process.env.ARENA_ELO_SYNC_ENABLED = "false";
const status = getArenaEloSyncStatus();
assert.strictEqual(status.enabled, false);
});
});
// ═══════════════════════════════════════════════════════════
// 6. stopArenaEloSync()
// ═══════════════════════════════════════════════════════════
describe("stopArenaEloSync()", () => {
it("initArenaEloSync returns false when disabled by feature flag", async () => {
try {
setFeatureFlagOverride("ARENA_ELO_SYNC_ENABLED", "false");
const started = await initArenaEloSync();
assert.strictEqual(started, false);
} finally {
removeFeatureFlagOverride("ARENA_ELO_SYNC_ENABLED");
}
});
it("does not throw when no timer is running", () => {
assert.doesNotThrow(() => stopArenaEloSync());
});
it("can be called multiple times without error", () => {
stopArenaEloSync();
assert.doesNotThrow(() => stopArenaEloSync());
assert.doesNotThrow(() => stopArenaEloSync());
});
});