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* fix: canonical Anthropic model IDs + reverse alias + Opus 4.7 pricing
Replace claude-sonnet-4-6-20250929 with claude-sonnet-4-6 everywhere it
appears as a model ID. Starting with Claude 4.6, Anthropic API IDs are
dateless and pinned — the date suffix was carried forward from Sonnet 4.5
by mistake, producing a phantom ID that 404'd on every call.
Production impact in v0.31.6: isAvailable("chat") returned false in every
code path that loaded the recipe's model list, and extractFactsFromTurn
silently returned []. The headline real-time facts extraction feature
was a no-op on the happy path.
- gateway.ts:46 DEFAULT_CHAT_MODEL -> anthropic:claude-sonnet-4-6
- recipes/anthropic.ts: chat + expansion model lists drop date suffix;
remove wrong-direction alias (claude-sonnet-4-6 -> -20250929);
add reverse alias (-20250929 -> claude-sonnet-4-6) so stale user
configs in models.dream.synthesize etc. keep working
- facts/extract.ts: routes through resolveModel; both fallbacks corrected
- anthropic-pricing.ts: Opus 4.7 corrected $15/$75 -> $5/$25 per
Anthropic docs (the $15/$75 was Opus 4.0 pricing)
- cross-modal-eval/runner.ts: PRICING now reads from ANTHROPIC_PRICING
for Anthropic models instead of duplicating the map (single source of
truth — fixes the drift trap that motivated this whole patch)
Tests: cherry-pick PR #830's test/anthropic-model-ids.test.ts verbatim
(6 recipe-shape guardrails). Update gateway-chat tests to assert reverse
alias resolves correctly. Update budget-meter test for new Opus pricing.
Co-Authored-By: garrytan-agents <garrytan-agents@users.noreply.github.com>
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat: model tier system + recipe-models merge + async reconfigure hook
Add 4-tier model routing (utility/reasoning/deep/subagent) so users can
swap defaults with one config key. Each tier maps to a class of work;
override globally via models.default or per-tier via models.tier.<tier>.
Codex flagged three real architecture issues in the v0.31.12 plan review;
this commit addresses each.
F3 — sync/async timing of configureGateway:
- buildGatewayConfig stays synchronous (pre-engine-connect callers
keep working)
- New reconfigureGatewayWithEngine(engine) async function re-resolves
expansion + chat defaults through resolveModel after engine.connect()
- cli.ts wires the re-stamp into the post-connect path
F4/F5 — softening assertTouchpoint was too broad:
- Earlier plan was to flip native-recipe validation from throw to warn,
affecting gateway.chat AND gateway.expand AND gateway.embed
- Instead: per-gateway-instance recipe-models merge. assertTouchpoint
gets an optional extendedModels Set; when the user opted into a model
via config, it bypasses the throw. Source-code typos still fail fast.
- Existing contract test (test/ai/gateway-chat.test.ts:106) preserved
Tier defaults are TIER_DEFAULTS in model-config.ts. Resolution chain
inserts at step 5 (between models.default and env var). Each existing
resolveModel call site gains a tier: arg — think (deep), cycle/synthesize
(reasoning + utility for verdict), patterns/drift (reasoning), auto-think
(deep), facts/extract (reasoning).
Plus 10 new tests pinning tier precedence, subagent-tier fallback when
models.default is non-Anthropic, and the F6 alias-chain conflict case.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat: subagent runtime enforcement for non-Anthropic models (3 layers)
The subagent loop uses Anthropic's Messages API with prompt caching on
system + tools. OpenAI/Google have different shapes. Setting
models.default = openai:gpt-5.5 and routing the subagent there silently
breaks the loop.
Codex F1+F2+F13 in the v0.31.12 plan review pointed out that "warn at
doctor" wasn't enough — handlers/subagent.ts:148 still did
`const model = data.model ?? DEFAULT_MODEL` and called Anthropic directly,
so a job submitted with data.model = openai:gpt-5.5 bypassed any tier
logic and failed at runtime with a confusing provider error.
Three layers of enforcement, defense in depth:
Layer 1 (queue.ts:add) — submit-time guard. When name === 'subagent'
and data.model is set, validate the provider. Non-Anthropic rejects
before the job enters the queue.
Layer 2 (handlers/subagent.ts) — tier-resolution fallback. The handler
routes through resolveModel({ tier: 'subagent' }). If the chain resolves
to a non-Anthropic provider (via models.default or models.tier.subagent),
the resolver warns + falls back to TIER_DEFAULTS.subagent
(claude-sonnet-4-6).
Layer 3 (doctor.ts:checkSubagentProvider) — surfacing layer. Warns when
models.tier.subagent or models.default is explicitly set to a
non-Anthropic provider, with a paste-ready fix command. Lets users see
config drift before submitting a job.
Tests: 3 new cases in test/agent-cli.test.ts asserting the queue-level
guard rejects non-Anthropic data.model. Existing test/subagent-handler
suite still passes.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat: gbrain models CLI + doctor probe + silent-no-op regression test
New gbrain models CLI gives the agent and user visibility into routing.
Read mode prints the tier table, current overrides, per-task config,
and aliases with source-of-truth attribution per row. Doctor subcommand
fires a 1-token probe to each configured chat/expansion model and
classifies failures (model_not_found / auth / rate_limit / network /
unknown) so config-time invalid IDs surface without waiting for a
production call that silently degrades.
Per Codex F11 — no specific dollar cost claim in either the help text
or the CHANGELOG (providers have minimum-output billing and prompt-cache
rounding that vary). Probe is opt-in (gbrain doctor --probe-models),
never auto-runs. --skip=<provider> narrows the matrix for cost-sensitive
operators.
Per Codex F7+F8+F15 (the structural regression gap): new
test/facts-extract-silent-no-op.test.ts is THE regression test for the
bug class that motivated v0.31.12. Five cases including the smoking-gun:
when chat IS available, extractFactsFromTurn MUST actually call the chat
transport, not silently return []. Uses the gateway's
__setChatTransportForTests seam so it runs in every shard with no API key.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore: bump version and changelog (v0.31.12)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs: document v0.31.12 model tier system + gbrain models CLI
Add CLAUDE.md Key Files annotations for the v0.31.12 work:
src/core/model-config.ts (tier system + isAnthropicProvider + TIER_DEFAULTS),
src/core/ai/model-resolver.ts (assertTouchpoint extendedModels arg),
src/core/ai/gateway.ts (reconfigureGatewayWithEngine + extended-models registry),
src/core/minions/queue.ts (subagent submit-time guard, layer 1 of 3),
src/commands/models.ts (new gbrain models CLI + doctor probe),
src/commands/doctor.ts (subagent_provider check, layer 3 of 3),
src/core/ai/recipes/anthropic.ts (canonical model IDs + reverse alias),
src/core/anthropic-pricing.ts (Opus 4.7 corrected to \$5/\$25).
Add CLAUDE.md commands section for gbrain models + gbrain models doctor
+ power-user config recipes. Add README.md command-table rows for the
same. Regenerate llms-full.txt so the bundled docs stay in sync.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs: scrub --probe-models reference (flag not actually wired)
The v0.31.12 CHANGELOG and skills/conventions/model-routing.md both
referenced `gbrain doctor --probe-models` as an integrated probe entry
point. The flag was never implemented — only `gbrain models doctor`
landed as the probe surface. Caught by /document-release subagent.
Drop the references rather than wire an untested flag at the last minute.
The probe is reachable via `gbrain models doctor`; users who want it
in doctor's output run that command separately.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: garrytan-agents <garrytan-agents@users.noreply.github.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
199 lines
6.6 KiB
TypeScript
199 lines
6.6 KiB
TypeScript
/**
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* E2E for `gbrain eval cross-modal` runner via mocked gateway chat().
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*
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* Lives under test/e2e/ so the test-isolation lint (R2 — mock.module quarantine)
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* does not require a *.serial.test.ts rename: test/e2e/* is exempt from the
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* lint, and `scripts/run-e2e.sh` already runs one file per Bun process so
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* `mock.module` leaks are contained.
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*
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* Verifies the verdict / exit-code contract end-to-end:
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* PASS (verdict='pass') when every dim mean >=7 and no model <5
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* FAIL (verdict='fail') when any dim breaches mean OR floor
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* INCONCLUSIVE (verdict='inconclusive') when <2/3 model calls succeed
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*/
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import { afterEach, beforeEach, describe, expect, mock, test } from 'bun:test';
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import { mkdtempSync, readdirSync, readFileSync, rmSync } from 'fs';
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import { tmpdir } from 'os';
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import { join } from 'path';
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import { configureGateway } from '../../src/core/ai/gateway.ts';
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let tempDir: string;
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beforeEach(() => {
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tempDir = mkdtempSync(join(tmpdir(), 'gbrain-cme-e2e-'));
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// Configure the gateway so our mock can pretend providers are available.
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configureGateway({
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embedding_model: 'openai:text-embedding-3-large',
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embedding_dimensions: 1536,
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expansion_model: 'anthropic:claude-haiku-4-5-20251001',
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chat_model: 'anthropic:claude-sonnet-4-6',
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base_urls: undefined,
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env: {
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OPENAI_API_KEY: 'sk-test',
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ANTHROPIC_API_KEY: 'sk-ant-test',
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GOOGLE_GENERATIVE_AI_API_KEY: 'sk-google-test',
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},
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});
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});
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afterEach(() => {
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rmSync(tempDir, { recursive: true, force: true });
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mock.restore();
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});
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function makeChatStub(scoresBySlot: Record<string, number[]>) {
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let callIdx = 0;
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const order = ['openai:gpt-4o', 'anthropic:claude-opus-4-7', 'google:gemini-1.5-pro'];
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return mock(async (opts: { model?: string }) => {
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const model = opts.model ?? '';
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callIdx++;
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const slotIdx = order.indexOf(model);
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const scores = scoresBySlot[model];
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if (!scores) {
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throw new Error(`mock: no scores configured for model ${model}`);
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}
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const goal = scores[0]!;
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const depth = scores[1]!;
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return {
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text: JSON.stringify({
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scores: { goal: { score: goal }, depth: { score: depth } },
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overall: (goal + depth) / 2,
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improvements: [`${slotIdx + 1}. tighten the intro`],
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}),
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blocks: [],
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stopReason: 'end',
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usage: { input_tokens: 100, output_tokens: 50, cache_read_tokens: 0, cache_creation_tokens: 0 },
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model,
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providerId: model.split(':')[0]!,
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};
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});
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}
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describe('gbrain eval cross-modal — runner verdict contract', () => {
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test('PASS: 3 happy responses, all dims >=7', async () => {
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const chatStub = makeChatStub({
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'openai:gpt-4o': [9, 8],
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'anthropic:claude-opus-4-7': [8, 7],
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'google:gemini-1.5-pro': [8, 8],
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});
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mock.module('../../src/core/ai/gateway.ts', () => ({
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chat: chatStub,
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configureGateway,
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isAvailable: () => true,
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}));
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const { runEval } = await import('../../src/core/cross-modal-eval/runner.ts');
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const result = await runEval({
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task: 'sample task',
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output: 'sample output content',
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slug: 'demo',
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receiptDir: tempDir,
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cycles: 1,
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});
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expect(result.finalAggregate.verdict).toBe('pass');
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expect(result.cycles).toHaveLength(1);
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const files = readdirSync(tempDir);
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expect(files.length).toBeGreaterThan(0);
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expect(files[0]!.startsWith('demo-')).toBe(true);
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const receipt = JSON.parse(readFileSync(join(tempDir, files[0]!), 'utf-8'));
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expect(receipt.schema_version).toBe(1);
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expect(receipt.aggregate.verdict).toBe('pass');
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});
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test('FAIL: one dim mean below 7', async () => {
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const chatStub = makeChatStub({
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'openai:gpt-4o': [9, 6],
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'anthropic:claude-opus-4-7': [8, 6],
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'google:gemini-1.5-pro': [8, 6],
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});
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mock.module('../../src/core/ai/gateway.ts', () => ({
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chat: chatStub,
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configureGateway,
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isAvailable: () => true,
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}));
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const { runEval } = await import('../../src/core/cross-modal-eval/runner.ts');
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const result = await runEval({
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task: 'sample task',
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output: 'sample output content',
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slug: 'demo',
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receiptDir: tempDir,
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cycles: 1,
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});
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expect(result.finalAggregate.verdict).toBe('fail');
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expect(result.finalAggregate.dimensions.depth!.failReason).toBe('mean_below_7');
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});
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test('FAIL: min-score floor caught when one model scores <5 (Q2)', async () => {
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const chatStub = makeChatStub({
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'openai:gpt-4o': [9, 8],
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'anthropic:claude-opus-4-7': [8, 8],
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'google:gemini-1.5-pro': [4, 8], // goal=4 trips the floor
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});
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mock.module('../../src/core/ai/gateway.ts', () => ({
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chat: chatStub,
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configureGateway,
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isAvailable: () => true,
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}));
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const { runEval } = await import('../../src/core/cross-modal-eval/runner.ts');
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const result = await runEval({
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task: 'sample task',
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output: 'sample output content',
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slug: 'demo',
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receiptDir: tempDir,
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cycles: 1,
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});
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expect(result.finalAggregate.verdict).toBe('fail');
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expect(result.finalAggregate.dimensions.goal!.failReason).toBe('min_below_5');
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});
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test('INCONCLUSIVE: 2 of 3 mock 5xx -> exit 2 contract (Q3)', async () => {
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const chatStub = mock(async (opts: { model?: string }) => {
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if (opts.model === 'openai:gpt-4o') {
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return {
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text: JSON.stringify({
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scores: { goal: { score: 8 } },
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improvements: ['1. ok'],
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}),
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blocks: [],
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stopReason: 'end',
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usage: { input_tokens: 0, output_tokens: 0, cache_read_tokens: 0, cache_creation_tokens: 0 },
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model: opts.model,
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providerId: 'openai',
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};
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}
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throw new Error(`mock: forced 5xx for ${opts.model}`);
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});
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mock.module('../../src/core/ai/gateway.ts', () => ({
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chat: chatStub,
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configureGateway,
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isAvailable: () => true,
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}));
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const { runEval } = await import('../../src/core/cross-modal-eval/runner.ts');
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const result = await runEval({
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task: 'sample task',
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output: 'sample output content',
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slug: 'demo',
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receiptDir: tempDir,
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cycles: 1,
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});
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expect(result.finalAggregate.verdict).toBe('inconclusive');
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expect(result.finalAggregate.successes).toBe(1);
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expect(result.finalAggregate.failures).toBe(2);
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// Receipt is still written even on INCONCLUSIVE — forensics path.
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const files = readdirSync(tempDir);
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expect(files.length).toBe(1);
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const receipt = JSON.parse(readFileSync(join(tempDir, files[0]!), 'utf-8'));
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expect(receipt.aggregate.verdict).toBe('inconclusive');
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expect(receipt.aggregate.errors).toHaveLength(2);
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});
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});
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