Files
windmill/ai_evals/core/runSuite.test.ts
centdix b0ddcf31e4 ci: add path-gated AI agent + ai_evals smoke workflows (#9640)
* ci: add path-gated AI agent integration tests workflow

Runs integration_tests/ai_agent_tests against real LLM providers
(Anthropic/OpenAI/Google) only when AI-agent backend code or the tests
change, since runs make paid LLM calls. Adds a conftest fixture that
skips provider-parametrized cases whose API keys are absent, so CI
exercises only the providers it has secrets for.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* ci: add path-gated ai_evals global-mode smoke workflow

Runs the global AI chat eval (global-test1) across one cheap model per
provider (Anthropic/OpenAI/Google/DeepSeek) only when the eval harness or
copilot chat code change, since runs make paid LLM calls. Builds Windmill
CE from source as the AI proxy; global tools/drafts run in the Vitest
bridge. Gates on the deterministic draft pipeline (run succeeded +
produced a draft + used write_script), not the variable LLM judge score.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* ci: run AI smokes on PR ready-for-review instead of every push

Switch the pull_request trigger from `synchronize` (every commit) to
`ready_for_review`, with a job guard skipping draft PRs, so the paid LLM
runs only fire when a PR is marked ready to merge (plus push-to-main and
manual dispatch).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(ai_evals): lazily load cli mode so non-cli evals skip the cli toolchain

The entrypoint eagerly imported modes/cli, which pulls the wmill CLI
guidance modules and their JSR deps (@cliffy/*). Global/flow/script/app
runs then crashed with "Cannot find module '@cliffy/ansi/colors'" when
the cli workspace deps were not installed. Import createCliModeRunner
dynamically inside runCliBenchmark instead.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(ai_agent): raise low max_completion_tokens to OpenAI's 16 minimum

OpenAI's /v1/responses rejects max_output_tokens < 16 with a 400, failing
test_low_max_tokens for openai. 16 still exercises a truncated response.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* ci: run ai_evals workflow on Node 22 for the frontend undici 8.x dep

The Vitest bridge loads frontend/node_modules/undici@8.x, which requires
Node >=22.19; Node 20 failed with "webidl.util.markAsUncloneable is not a
function" when loading vitest.config.ts.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(ai_evals): run frontend evals autonomously + give global-test1 more turns

Frontend evals (flow/script/app/global) ran the production chat prompt, which
assumes an interactive human — so cheaper models burned their turn budget
asking for confirmation, waiting for approval, or presenting a plan, sometimes
hitting maxTurns without producing a draft. Append a shared autonomy note in
baseEvalRunner (the path all frontend modes share, mirroring cli mode): act
directly on clear requests; only ask on genuinely ambiguous ones (preserving
the askUserQuestion cases). Also raise global-test1's maxTurns 8 -> 10 so a
model that over-explores still converges.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* ci(ai_evals): watch draft/prompt deps outside copilot/

The global eval runs production frontend code in-process, so the smoke's
behavior depends on files outside frontend/src/lib/components/copilot/**:
the draft model (userDraft.svelte.ts, userDraftDbSyncer.svelte.ts), script
inference (infer.ts), and the chat system prompts ($system_prompts ->
system_prompts/auto-generated). Add them to both push and PR path filters so
a change there actually triggers the smoke that gates on draft production.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix: skip direct provider tests without credentials

* feat: add ai evals skip judge flag

* fix: simplify ai evals ci gate

* fix: simplify ai evals smoke gate

* fix: handle ai eval workflow triggers

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-22 12:41:31 +02:00

103 lines
2.8 KiB
TypeScript

import { describe, expect, it } from "bun:test";
import { runSuite } from "./runSuite";
import type { ModeRunner } from "./types";
const modeRunner: ModeRunner<undefined, undefined, { ok: boolean }> = {
mode: "global",
concurrency: 1,
loadInitial: async () => undefined,
loadExpected: async () => undefined,
run: async () => ({
success: true,
actual: { ok: true },
assistantMessageCount: 1,
toolCallCount: 0,
toolsUsed: [],
skillsInvoked: [],
tokenUsage: null,
}),
validate: () => [],
};
describe("runSuite", () => {
it("skips judge checks when the run disables judge scoring", async () => {
const [caseResult] = await runSuite({
modeRunner,
cases: [
{
id: "case-1",
prompt: "Create a draft script",
judgeChecklist: ["the output satisfies the prompt"],
},
],
runs: 1,
runModel: "model-under-test",
judgeModel: null,
});
const [attempt] = caseResult.attempts;
expect(attempt.passed).toBe(true);
expect(attempt.judgeScore).toBeNull();
expect(attempt.judgeSummary).toBeNull();
expect(attempt.checks.map((check) => check.name)).toEqual([
"run succeeded",
]);
});
it("only requires run success when execution-only is enabled", async () => {
let loadExpectedCalls = 0;
let validateCalls = 0;
let backendValidateCalls = 0;
const executionOnlyRunner: ModeRunner<
undefined,
undefined,
{ ok: boolean }
> = {
...modeRunner,
loadExpected: async () => {
loadExpectedCalls++;
return undefined;
},
validate: () => {
validateCalls++;
return [{ name: "validator failed", passed: false }];
},
backendValidate: async () => {
backendValidateCalls++;
return {
checks: [{ name: "backend validation failed", passed: false }],
};
},
};
const [caseResult] = await runSuite({
modeRunner: executionOnlyRunner,
cases: [
{
id: "case-1",
prompt: "Create a draft script",
expectedPath: "fixtures/expected.json",
toolExpect: { requiredToolsUsed: ["write_script"] },
judgeChecklist: ["the output satisfies the prompt"],
},
],
runs: 1,
runModel: "model-under-test",
judgeModel: "judge-model",
executionOnly: true,
});
const [attempt] = caseResult.attempts;
expect(attempt.passed).toBe(true);
expect(attempt.judgeScore).toBeNull();
expect(attempt.judgeSummary).toBeNull();
expect(attempt.checks.map((check) => check.name)).toEqual([
"run succeeded",
]);
expect(loadExpectedCalls).toBe(0);
expect(validateCalls).toBe(0);
expect(backendValidateCalls).toBe(0);
});
});