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* feat(dims): OpenAI text-embedding-3 Matryoshka range validation (D13) dimsProviderOptions now fail-loud at the embed boundary when the configured embedding_dimensions is outside the model's native range (1..1536 for -small, 1..3072 for -large). Paste-ready fix hint in the AIConfigError.fix field. Closes the silent-HTTP-400 path that would have bit OpenAI-fallback users on v0.36.0.0 ZE-default installs. 16 new test cases in test/ai/dims-openai.test.ts pinning the contract across native-openai and openai-compatible adapter paths. * feat(ai): flip defaults to ZeroEntropy zembed-1 1280d + zerank-2 reranker Default embedding model is now zeroentropyai:zembed-1 at 1280d via Matryoshka. Real-corpus benchmark: 2.2x faster than OpenAI, 2.6x cheaper at regular pricing, wins 11/20 head-to-head queries. 1280 is the closest valid ZE Matryoshka step to the prior OpenAI 1536d default (valid set: 2560/1280/640/320/160/80/40). 1024 (Voyage's step) is NOT on ZE's list — pinned by AIConfigError fail-loud in dims.ts. balanced mode bundle now defaults reranker_enabled=true. zerank-2 reshuffles 60% of top-1 results in benchmarks. Missing-key fail-open contract in src/core/search/rerank.ts handles unauthenticated cases. Opt out with: gbrain config set search.reranker.enabled false Existing tests updated (gateway.test.ts, search-mode.test.ts) and a new test/balanced-reranker-default.test.ts (10 cases) pins the fail- open invariants. * feat(retrieval-upgrade): RetrievalUpgradePlanner + interactive prompt UX New src/core/retrieval-upgrade-planner.ts is the consolidated planner that computes the brain's pending retrieval-upgrade work (chunker bumps + ZE switch) in one pass and applies the schema transition + config updates atomically. Tagged-union ApplyResult enum (D15): 'applied' | 'skipped_already_ applied' | 'skipped_no_work' | 'declined' | 'planned' | 'failed'. No string-parsing reasons. Three config keys (D12): ze_switch_prompt_shown (UI state), ze_switch_requested (user intent), ze_switch_applied (work done). Plus ze_switch_previous_snapshot (JSON, full prior config for --undo per D16) and ze_switch_declined_at (90-day re-ask window). Schema transition (D18) is atomic: DROP indexes + ALTER COLUMN + CREATE INDEX inside a single engine.transaction(). HNSW recreation is part of the same transaction — no silent slow-search window. C3 eligibility logic: ze_switch_offered iff NOT on ZE + NOT declined recently + NOT applied + (legacy default OR >100 pages). C4 cost math: MAX(chunker_pending, dim_pending) not SUM — one re-embed pass invalidates both surfaces simultaneously. New src/core/retrieval-upgrade-prompt.ts wires the planner to a TTY-only interactive prompt with two-line cost split (D10) and privacy callout for the reranker flip. Tests: test/retrieval-upgrade-planner.test.ts (24 cases) pins the state machine. test/asymmetric-encoding-contract.test.ts (6 cases) pins D17: search read path uses gateway.embedQuery() not embed(), asserted via __setEmbedTransportForTests mock. * feat(cli): gbrain ze-switch — manual lever for the ZE switch New gbrain ze-switch CLI with --dry-run, --json, --resume, --force, --undo, --non-interactive, --confirm-reembed, --ignore-missing-key flags. Mirrors the upgrade prompt's UX symmetry: --undo presents a cost-warning before re-embedding back to the prior width. src/cli.ts: dispatch case + CLI_ONLY entry. ze-switch owns its own engine lifecycle (mirrors the doctor pattern). test/ze-switch-cli.test.ts (11 cases): --help, --dry-run, --json, --non-interactive, --ignore-missing-key, --resume, --undo, --confirm-reembed. Uses captureExit harness to test process.exit() paths without breaking the test process. * feat(doctor): ze_embedding_health + embedding_width_consistency checks Two new doctor checks (D-A5): ze_embedding_health: when embedding_model starts with zeroentropyai:, verify ZEROENTROPY_API_KEY is set (env or config). Paste-ready setup hint with the signup URL on failure. embedding_width_consistency: cross-check that the configured embedding_dimensions matches the actual vector(N) column width on content_chunks.embedding. Catches the half-applied switch state (schema migrated but config write crashed) with a paste-ready gbrain ze-switch --resume hint. Wired into runDoctor between reranker_health and the existing sync_freshness checks. Both checks gracefully no-op on non-ZE embedding configs. test/doctor-ze-checks.test.ts (8 cases) pins both checks across happy + missing-key + missing-config + drift paths. Uses withEnv() helper to clear ZEROENTROPY_API_KEY for the no-key path so tests are hermetic against contributor env state. test/e2e/v0_28_5-fix-wave.test.ts + test/openai-compat-multimodal.test.ts: updated to explicit-configure the gateway when the test depends on specific dims that diverge from the v0.36.0.0 default (1280d). * docs: README zero-based rewrite (884 -> 139 lines) + new docs files Strip 4 months of accreted "New in v0.X.Y" hero blocks and reorganize around what gbrain does today. 33 H2s -> 8. The Commands section (136 lines duplicating gbrain --help) moved out; the 6-table skills enumeration collapsed to a one-paragraph capability description with a link to skills/RESOLVER.md. Hero retains load-bearing facts: OpenClaw + Hermes credit, production numbers (17,888 pages / 4,383 people / 723 companies), BrainBench numbers (P@5 49.1% / R@5 97.9% / +31.4 lift), ZE comparison numbers, 30-min install claim. Adds one paragraph announcing the v0.36.0.0 ZE default with the explicit gbrain config set escape for OpenAI/Voyage users. New files: - docs/INSTALL.md: every install path consolidated (agent platform, CLI standalone, MCP server). Thin-client mode covered. - docs/architecture/RETRIEVAL.md: why the hybrid + graph stack works. BrainBench numbers, why each strategy alone fails, the source-aware ranking + intent classification + multi-query expansion story. - docs/ethos/ORIGIN.md: origin story lifted from the old README so the front door stays factual + concrete. test/readme-hero-anchors.test.ts (5 cases) is the D9 regression guard. Five load-bearing strings: OpenClaw, Hermes, ZE, production-numbers regex, P@5/R@5. Light anchors that let voice/ structure evolve but block accidental loss of headline facts. scripts/check-test-real-names.sh: allowlist entries for OpenClaw + Hermes literals in the anchor test (it explicitly asserts those strings appear in README). * chore: bump version and changelog (v0.36.0.0) ZeroEntropy as the new default for embedding (zembed-1 at 1280d via Matryoshka) and reranker (zerank-2 cross-encoder, on by default in balanced mode bundle). README zero-based rewrite (884 -> 139 lines). 3 new docs files. Two new doctor checks. New gbrain ze-switch CLI with --undo for symmetric reversibility. skills/migrations/v0.36.0.0.md tells the agent how to surface the retrieval-upgrade prompt post-upgrade. llms-full.txt regenerated via bun run build:llms. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * fix(docs): scrub Wintermute from RETRIEVAL.md per privacy rule * chore: rebump version 0.36.0.0 → 0.36.2.0 (queue collision) Three open PRs were claiming v0.36.0.0 (#1130 skillpack, #1139 hindsight, #1136 this PR). Ship-aware queue allocator says this branch lands at v0.36.2.0. Trio audit: VERSION 0.36.2.0 package.json 0.36.2.0 CHANGELOG ## [0.36.2.0] - 2026-05-17 Updates: VERSION, package.json, CHANGELOG header + body refs, README "New default in v0.36.2.0" announcement + credit line, skills/migrations/v0.36.0.0.md renamed to v0.36.2.0.md with frontmatter + body refs updated. llms-full.txt regenerated. * fix(test): pin gateway dim=1536 in cross-file-stateful PGLite tests CI shard 1 reported 10 failures across `query-cache.test.ts` (6) and `consolidate-valid-until.test.ts` (4). Both files hardcode 1536-dim vectors but rely on `PGLiteEngine.initSchema()` to size `vector(__EMBEDDING_DIMS__)` at the right width. Root cause: v0.36.2.0 flipped DEFAULT_EMBEDDING_DIMENSIONS from 1536 to 1280 (ZE Matryoshka step). The gateway module is process-singleton; when ANOTHER test file in the same shard's bun-test process configures the gateway before us, `pglite-engine.ts:216` reads `getEmbeddingDimensions() === 1280` and sizes the schema columns at vector(1280). The hardcoded 1536-dim INSERTs then fail with "expected 1280 dimensions, not 1536". Locally these tests pass in isolation because the gateway falls back through the try/catch at pglite-engine.ts:218 (1536 default). CI runs multiple test files in one process, so cross-file state poisons the schema width. Fix: explicit `resetGateway()` + `configureGateway({embedding_dimensions: 1536, ...})` at the top of `beforeAll`, plus `resetGateway()` in `afterAll`. Pins the schema width regardless of cross-file state. --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
239 lines
8.3 KiB
TypeScript
239 lines
8.3 KiB
TypeScript
/**
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* v0.36.0.0 (T3) — `gbrain ze-switch` CLI tests.
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*
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* Pins:
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* - --dry-run prints a plan, applies nothing
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* - --non-interactive without key exits 1 (unless --ignore-missing-key)
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* - --non-interactive --ignore-missing-key applies + exits 0
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* - --json envelope shape: {status: ..., plan: {...}}
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* - --resume completes a half-applied switch
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* - --undo without snapshot exits 1
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* - --help exits 0 without touching the engine
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*
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* Engine lifecycle: each test creates + disconnects its own PGLite engine
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* to keep process.exit() semantics clean. The CLI calls process.exit at
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* the end of every path; we intercept via a stub.
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*/
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import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:test';
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import { PGLiteEngine } from '../src/core/pglite-engine.ts';
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import { resetPgliteState } from './helpers/reset-pglite.ts';
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import { withEnv } from './helpers/with-env.ts';
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import { runZeSwitch } from '../src/commands/ze-switch.ts';
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import {
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KEY_APPLIED,
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KEY_REQUESTED,
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KEY_PREVIOUS_SNAPSHOT,
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ZE_TARGET_EMBEDDING_DIM,
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} from '../src/core/retrieval-upgrade-planner.ts';
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let engine: PGLiteEngine;
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beforeAll(async () => {
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engine = new PGLiteEngine();
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await engine.connect({});
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await engine.initSchema();
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});
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afterAll(async () => {
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await engine.disconnect();
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});
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beforeEach(async () => {
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await resetPgliteState(engine);
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});
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// Helpers: capture stdout/stderr/exitCode without actually exiting.
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function captureExit<T>(fn: () => Promise<T>): Promise<{ exitCode: number; stdout: string; stderr: string }> {
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return new Promise(async (resolve) => {
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const origExit = process.exit;
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const origStdoutWrite = process.stdout.write.bind(process.stdout);
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const origStderrWrite = process.stderr.write.bind(process.stderr);
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const origConsoleLog = console.log;
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const origConsoleError = console.error;
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let stdout = '';
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let stderr = '';
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let exitCode = 0;
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process.exit = ((code?: number) => {
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exitCode = code ?? 0;
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throw new Error('__captured_exit__');
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}) as any;
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process.stdout.write = ((chunk: any) => {
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stdout += typeof chunk === 'string' ? chunk : chunk.toString();
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return true;
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}) as any;
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process.stderr.write = ((chunk: any) => {
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stderr += typeof chunk === 'string' ? chunk : chunk.toString();
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return true;
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}) as any;
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console.log = (...args: any[]) => { stdout += args.join(' ') + '\n'; };
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console.error = (...args: any[]) => { stderr += args.join(' ') + '\n'; };
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try {
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await fn();
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} catch (e: any) {
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if (e?.message !== '__captured_exit__') {
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stderr += `Unexpected: ${e?.message ?? String(e)}\n`;
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exitCode = exitCode || 1;
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}
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} finally {
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process.exit = origExit;
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process.stdout.write = origStdoutWrite;
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process.stderr.write = origStderrWrite;
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console.log = origConsoleLog;
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console.error = origConsoleError;
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resolve({ exitCode, stdout, stderr });
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}
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});
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}
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async function seedPages(n: number) {
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for (let i = 0; i < n; i++) {
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await engine.putPage(`seed/page-${i}`, {
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title: `Seed ${i}`,
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compiled_truth: `Body text ${i} with enough chars to flow through cost math.`,
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timeline: '',
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type: 'note',
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});
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}
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}
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async function setLegacyConfig() {
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await engine.setConfig('embedding_model', 'openai:text-embedding-3-large');
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await engine.setConfig('embedding_dimensions', '1536');
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}
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describe('--help', () => {
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test('exits 0 with usage text', async () => {
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const r = await captureExit(() => runZeSwitch(['--help'], engine));
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expect(r.exitCode).toBe(0);
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expect(r.stdout).toContain('gbrain ze-switch');
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expect(r.stdout).toContain('--dry-run');
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expect(r.stdout).toContain('--undo');
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});
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});
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describe('--dry-run', () => {
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test('human output prints plan, changes nothing', async () => {
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await setLegacyConfig();
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await seedPages(150);
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const r = await captureExit(() => runZeSwitch(['--dry-run'], engine));
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expect(r.exitCode).toBe(0);
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expect(r.stdout).toContain('Current model');
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expect(r.stdout).toContain('Target model');
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// Nothing changed:
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expect(await engine.getConfig('embedding_model')).toBe('openai:text-embedding-3-large');
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expect(await engine.getConfig(KEY_APPLIED)).toBeNull();
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});
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test('--json output emits a planned envelope', async () => {
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await setLegacyConfig();
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await seedPages(150);
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const r = await captureExit(() => runZeSwitch(['--dry-run', '--json'], engine));
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expect(r.exitCode).toBe(0);
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const env = JSON.parse(r.stdout);
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expect(env.status).toBe('planned');
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expect(env.plan).toBeDefined();
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expect(env.plan.target_embedding_model).toBe('zeroentropyai:zembed-1');
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expect(env.plan.target_dim).toBe(ZE_TARGET_EMBEDDING_DIM);
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});
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});
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describe('--non-interactive', () => {
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test('without ZE key + without --ignore-missing-key: exits 1', async () => {
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await setLegacyConfig();
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await seedPages(150);
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// Clear the env var so the test runs the no-key path even when the
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// contributor has ZEROENTROPY_API_KEY set in their shell.
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await withEnv({ ZEROENTROPY_API_KEY: undefined }, async () => {
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const r = await captureExit(() => runZeSwitch(['--non-interactive'], engine));
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expect(r.exitCode).toBe(1);
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expect(r.stderr).toContain('ZEROENTROPY_API_KEY');
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});
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});
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test('without ZE key + with --ignore-missing-key: applies, exits 0', async () => {
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await setLegacyConfig();
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await seedPages(150);
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const r = await captureExit(() =>
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runZeSwitch(['--non-interactive', '--ignore-missing-key'], engine),
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);
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expect(r.exitCode).toBe(0);
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expect(await engine.getConfig(KEY_APPLIED)).toBe('true');
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expect(await engine.getConfig('embedding_model')).toBe('zeroentropyai:zembed-1');
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expect(await engine.getConfig('embedding_dimensions')).toBe(String(ZE_TARGET_EMBEDDING_DIM));
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});
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test('with env ZE key set: applies', async () => {
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await setLegacyConfig();
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await seedPages(150);
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await withEnv({ ZEROENTROPY_API_KEY: 'sk-fake' }, async () => {
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const r = await captureExit(() => runZeSwitch(['--non-interactive'], engine));
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expect(r.exitCode).toBe(0);
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expect(await engine.getConfig(KEY_APPLIED)).toBe('true');
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});
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});
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test('--json + --non-interactive: emits {status: "applied"}', async () => {
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await setLegacyConfig();
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await seedPages(150);
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const r = await captureExit(() =>
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runZeSwitch(['--non-interactive', '--ignore-missing-key', '--json'], engine),
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);
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expect(r.exitCode).toBe(0);
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const env = JSON.parse(r.stdout);
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expect(env.status).toBe('applied');
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});
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});
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describe('--resume', () => {
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test('completes a half-applied switch', async () => {
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await setLegacyConfig();
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await seedPages(150);
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// Simulate crash partway: requested but not applied.
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await engine.setConfig(KEY_REQUESTED, 'true');
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const r = await captureExit(() => runZeSwitch(['--resume'], engine));
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expect(r.exitCode).toBe(0);
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expect(await engine.getConfig(KEY_APPLIED)).toBe('true');
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expect(await engine.getConfig('embedding_model')).toBe('zeroentropyai:zembed-1');
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});
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});
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describe('--undo', () => {
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test('without snapshot exits 1', async () => {
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const r = await captureExit(() =>
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runZeSwitch(['--undo', '--non-interactive', '--confirm-reembed'], engine),
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);
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expect(r.exitCode).toBe(1);
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});
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test('--non-interactive without --confirm-reembed exits 1', async () => {
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const r = await captureExit(() => runZeSwitch(['--undo', '--non-interactive'], engine));
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expect(r.exitCode).toBe(1);
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expect(r.stderr).toContain('confirm-reembed');
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});
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test('with snapshot + --confirm-reembed: reverses the switch', async () => {
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// Set up: apply switch, then undo.
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await setLegacyConfig();
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await seedPages(150);
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await captureExit(() =>
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runZeSwitch(['--non-interactive', '--ignore-missing-key'], engine),
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);
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expect(await engine.getConfig(KEY_APPLIED)).toBe('true');
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const r = await captureExit(() =>
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runZeSwitch(['--undo', '--non-interactive', '--confirm-reembed'], engine),
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);
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expect(r.exitCode).toBe(0);
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// Reverted to prior model.
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expect(await engine.getConfig('embedding_model')).toBe('openai:text-embedding-3-large');
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expect(await engine.getConfig('embedding_dimensions')).toBe('1536');
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expect(await engine.getConfig(KEY_APPLIED)).toBeNull();
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});
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});
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