import test 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-evals-history-")); process.env.DATA_DIR = TEST_DATA_DIR; const core = await import("../../src/lib/db/core.ts"); const evalsDb = await import("../../src/lib/db/evals.ts"); function resetDb() { core.resetDbInstance(); fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true }); fs.mkdirSync(TEST_DATA_DIR, { recursive: true }); } test.beforeEach(() => { resetDb(); }); test.after(() => { core.resetDbInstance(); fs.rmSync(TEST_DATA_DIR, { recursive: true, force: true }); }); test("eval run history persists target metadata and newest-first ordering", () => { const older = evalsDb.saveEvalRun({ suiteId: "golden-set", suiteName: "Golden Set", target: { type: "model", id: "gpt-4o", label: "Model: gpt-4o" }, summary: { total: 2, passed: 2, failed: 0, passRate: 100 }, avgLatencyMs: 120, results: [{ caseId: "c1", caseName: "Case 1", passed: true, durationMs: 120 }], outputs: { c1: "ok" }, createdAt: "2026-04-23T10:00:00.000Z", }); const newer = evalsDb.saveEvalRun({ suiteId: "golden-set", suiteName: "Golden Set", target: { type: "combo", id: "cost-optimized", label: "Combo: cost-optimized" }, summary: { total: 2, passed: 1, failed: 1, passRate: 50 }, avgLatencyMs: 240, results: [{ caseId: "c1", caseName: "Case 1", passed: false, durationMs: 240 }], outputs: { c1: "[ERROR] upstream failed" }, createdAt: "2026-04-23T11:00:00.000Z", }); const runs = evalsDb.listEvalRuns({ limit: 10 }); assert.equal(runs.length, 2); assert.equal(runs[0].id, newer.id); assert.equal(runs[1].id, older.id); assert.equal(runs[0].target.key, "combo:cost-optimized"); assert.equal(runs[1].target.key, "model:gpt-4o"); assert.equal(runs[0].summary.passRate, 50); assert.equal(runs[1].outputs.c1, "ok"); }); test("scorecard keeps only the latest run per suite and target scope", () => { evalsDb.saveEvalRun({ suiteId: "golden-set", suiteName: "Golden Set", target: { type: "model", id: "gpt-4o", label: "Model: gpt-4o" }, summary: { total: 2, passed: 1, failed: 1, passRate: 50 }, avgLatencyMs: 150, results: [], createdAt: "2026-04-23T09:00:00.000Z", }); evalsDb.saveEvalRun({ suiteId: "golden-set", suiteName: "Golden Set", target: { type: "model", id: "gpt-4o", label: "Model: gpt-4o" }, summary: { total: 2, passed: 2, failed: 0, passRate: 100 }, avgLatencyMs: 100, results: [], createdAt: "2026-04-23T10:00:00.000Z", }); evalsDb.saveEvalRun({ suiteId: "golden-set", suiteName: "Golden Set", target: { type: "combo", id: "balanced", label: "Combo: balanced" }, summary: { total: 2, passed: 1, failed: 1, passRate: 50 }, avgLatencyMs: 220, results: [], createdAt: "2026-04-23T10:30:00.000Z", }); const scorecard = evalsDb.getEvalScorecard({ limit: 10 }); assert.ok(scorecard); assert.equal(scorecard.suites, 2); assert.equal(scorecard.totalCases, 4); assert.equal(scorecard.totalPassed, 3); assert.equal(scorecard.overallPassRate, 75); }); test("routing eval run query returns recent model runs for requested targets", () => { evalsDb.saveEvalRun({ suiteId: "routing-quality", suiteName: "Routing Quality", target: { type: "model", id: "openai/good", label: "Model: openai/good" }, summary: { total: 4, passed: 4, failed: 0, passRate: 100 }, avgLatencyMs: 100, results: [], createdAt: "2026-04-23T10:00:00.000Z", }); evalsDb.saveEvalRun({ suiteId: "routing-quality", suiteName: "Routing Quality", target: { type: "combo", id: "openai/good", label: "Combo: openai/good" }, summary: { total: 4, passed: 1, failed: 3, passRate: 25 }, avgLatencyMs: 500, results: [], createdAt: "2026-04-23T10:30:00.000Z", }); evalsDb.saveEvalRun({ suiteId: "other-suite", suiteName: "Other Suite", target: { type: "model", id: "openai/good", label: "Model: openai/good" }, summary: { total: 4, passed: 2, failed: 2, passRate: 50 }, avgLatencyMs: 200, results: [], createdAt: "2026-04-23T11:00:00.000Z", }); const runs = evalsDb.listModelEvalRunsForRouting({ targetIds: ["openai/good", "openai/missing"], suiteIds: ["routing-quality"], maxAgeHours: 24 * 365 * 10, limit: 10, }); assert.equal(runs.length, 1); assert.equal(runs[0].target.type, "model"); assert.equal(runs[0].target.id, "openai/good"); assert.equal(runs[0].suiteId, "routing-quality"); }); test("custom eval suites persist cases and support update/delete", () => { const created = evalsDb.saveCustomEvalSuite({ name: "Support Regression", description: "Checks refund phrasing", cases: [ { name: "Refund policy", model: "gpt-4o-mini", input: { messages: [{ role: "user", content: "Explain the refund policy" }], }, expected: { strategy: "contains", value: "refund", }, tags: ["support", "billing"], }, ], }); assert.ok(created.id); assert.equal(created.source, "custom"); assert.equal(created.caseCount, 1); assert.equal(created.cases[0]?.expected.strategy, "contains"); assert.deepEqual(created.cases[0]?.tags, ["support", "billing"]); const updated = evalsDb.saveCustomEvalSuite({ id: created.id, name: "Support Regression v2", description: "Checks refund and escalation phrasing", cases: [ { id: created.cases[0]?.id, name: "Refund policy", model: "gpt-4o-mini", input: { messages: [{ role: "user", content: "Explain the refund policy" }], }, expected: { strategy: "contains", value: "refund", }, tags: ["support"], }, { name: "Escalation path", model: "gpt-4o-mini", input: { messages: [{ role: "user", content: "How do I escalate a billing issue?" }], }, expected: { strategy: "regex", value: "support|billing", }, tags: ["billing"], }, ], }); assert.equal(updated.id, created.id); assert.equal(updated.name, "Support Regression v2"); assert.equal(updated.caseCount, 2); assert.equal(updated.cases[1]?.expected.strategy, "regex"); const listed = evalsDb.listCustomEvalSuites(); assert.equal(listed.length, 1); assert.equal(listed[0]?.id, created.id); assert.equal(evalsDb.getCustomEvalSuite(created.id)?.cases.length, 2); assert.equal(evalsDb.deleteCustomEvalSuite(created.id), true); assert.equal(evalsDb.getCustomEvalSuite(created.id), null); });