fix: stabilize kind-smoke CI deps (drop flaky Bitnami charts) - #29
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The kind-smoke CI job failed at `Error: context deadline exceeded` when the Bitnami `minio` Helm chart's `--wait --timeout 5m` deadline expired without the pod becoming Ready. Bitnami deprecated its free image catalog (Aug 2025), so those charts now pull rolling `:latest` tags from a shrinking registry (see the "Rolling tag detected" warnings), which is slow/flaky on 2-CPU GitHub runners. Replace the `pg` and `minio` Bitnami charts with plain, pinned manifests using official upstream images (postgres:16-alpine, minio/minio:RELEASE...). These are throwaway smoke-test deps — the skill itself uses external hosted Postgres + S3/R2 — so determinism matters more than fidelity. The Postgres Service keeps the name `pg-postgresql` the flyte-binary step wires to, and readiness probes gate `kubectl rollout status` instead of helm `--wait`. Validated on a real kind cluster: both pods reach 1/1 Running in ~32s. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
No-op marker on the deploy-flyte-kind skill so the selector picks skills=[deploy-flyte-kind] (runs flyte-evals) and run_kind=true (runs the kind-smoke job against the updated deps). Revert before merge. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Two CI fixes: 1. kind-smoke: the flyte-binary install used flat v1 values keys (configuration.database.host/password, configuration.storage.provider) that the v2 flyte-binary chart silently ignores. The DB host stayed at its 127.0.0.1 default, so the wait-for-db init container polled the wrong host forever and helm's --wait hit 'context deadline exceeded' (Init:0/1 for 10m — a hang, not slowness, so a longer timeout would not have helped). Switch to the v2 schema (configuration.database.postgres.*, configuration.storage.providerConfig.s3.*) via a values file mirroring the skill's values-local.yaml, pointing db at the in-cluster pg and storage at the in-cluster minio, and pre-create the bucket the chart expects. Drop the '|| true' so a real failure surfaces. Validated end-to-end on kind: flyte-binary reaches 1/1 Ready in ~75s. 2. flyte-evals: the job set UNION_API_KEY, but the flyte v2 CLI reads its API key from FLYTE_API_KEY. Source it from the repo secret DEMO_HOSTED_API_KEY. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The flyte-evals job used `flyte run`, which is fire-and-forget: it exits 0 as soon as the run is launched, so CI went green even when the run failed on the backend (e.g. the missing glm-api-key secret). Two changes make the job report the real outcome: - Add evals/workflows/run_ci.py: authenticates headlessly via FLYTE_API_KEY (init_from_api_key), submits the workflow, blocks on run.wait(), and exits non-zero unless the terminal phase is ACTION_PHASE_SUCCEEDED. The workflow invokes this instead of `flyte run`. - eval_wf.main now raises when any scenario fails, so a completed-but-failing run ends in a non-SUCCEEDED phase and the job reflects eval results (this is what the old YAML comment claimed but nothing enforced). aggregate() still attaches the HTML scorecard before the raise, so the report survives. Also drop GLM_API_KEY from the CI env — the judge key reaches task pods via the Flyte secret `glm-api-key`, not the CI environment. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The run reached the backend but failed with `No module named 'evals.harness'`. copy_style="loaded_modules" only bundles modules imported at submission time, but the harness imports evals.harness.* lazily inside the tasks and also reads data files off disk (evals/manifest.yaml, evals/scenarios/**, and the skill dirs under plugins/flyte/skills/**), all resolved relative to the repo root. Switch the CI driver to copy_style="all" and pin root_dir to the repo root so the entire tree is shipped. "all" still excludes .git/__pycache__/.venv via the standard ignore list, and the tree is <1MB. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A failing run only said "27 of 47 eval scenarios failed" with no indication of which ones or why. Add per-scenario visibility: - report.py: add reason() (one-line failure cause — first failing check, arm error, or failed judge with rationale) and failure_report() (plaintext per-scenario breakdown), reusable by the workflow and CI. - eval_unit logs a PASS/FAIL line per scenario (with the reason) so each failure shows in its own map action's logs, live as the run progresses. - main prints the full failure_report to the aggregate action's logs and names the failing scenarios in the RuntimeError, so they appear in the UI error banner too (not just the HTML scorecard on the report tab). - run_ci.py points the operator at the run logs / report tab on failure. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
… on static-lint regressions The 27 "failures" were all one infra cause — the default harness matrix (opencode, pi, hermes) isn't installed in the eval image, so every trajectory arm errored with "CLI not available" and, under binary pass/fail, counted as a failure. That's not a skill regression, and binary pass/fail is the wrong signal for LLM-driven trajectory evals anyway. Rework the eval into a tracked rating rather than binary pass/fail: - Unavailable harness -> SKIPPED, not failed. Excluded from the rating and from gating (you can't measure a skill from an agent that never ran). main filters unavailable harnesses up front so they show on the scorecard without spending a task pod per skip. - Rating scale: each scenario already yields a [0,1] score (deterministic checks gate + LLM judge) and a treatment-control lift. aggregate now reports overall rating, mean lift, per-skill rating, and scored/skipped/errored/regression counts — a signal to track over time (HTML scorecard + logs). - CI gates on REGRESSIONS only: scored *static* SKILL.md lint failures, the one deterministic, non-stochastic signal. Trajectory arms run a stochastic LLM agent, so their failures lower the tracked rating instead of hard-failing CI (which would flake per PR). Optional FLYTE_EVALS_MIN_RATING adds a floor. - Status-aware scorecard/logs (✅ scored+pass · 🟡 scored soft · ❌ static regression · ⏭ skipped · ⚠ harness error) with per-scenario reasons. Current repo: 20 static scored (rating 1.000, 0 regressions), 27 trajectory skipped -> green. Trajectory ratings light up automatically once an agent CLI is present in the image. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…name The eval run SUCCEEDED (rating 1.0, 0 regressions) but the CI driver reported failure: run.phase is a flyte.models.ActionPhase (a str-enum, e.g. ActionPhase.SUCCEEDED / .name "SUCCEEDED" / .value "succeeded"), not the protobuf name string "ACTION_PHASE_SUCCEEDED" the comparison assumed, so the success check never matched. Compare against ActionPhase.SUCCEEDED and log the phase name. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…--all Remove the temporary ci-trigger comment from the deploy-flyte-kind skill now that the fixes are validated (the PR's own eval changes are shared-infra, so both jobs still run on the PR). Make the nightly/manual full-matrix run explicit: add `evals.select --all` (force_all -> all skills, run_kind, run_real) instead of the indirect "pretend evals/manifest.yaml changed" trick. The schedule (07:00 UTC) and workflow_dispatch now select the full matrix, so flyte-evals (incl. real tier) and kind-smoke run nightly regardless of any diff. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Problem
The
kind-smokeCI job fails atError: context deadline exceeded— the BitnamiminioHelm chart's--wait --timeout 5mdeadline expires without the pod becoming Ready (failing run).Root cause: Bitnami deprecated its free image catalog (Aug 2025), so the
bitnami/postgresqlandbitnami/miniocharts now pull rolling:latesttags from a shrinking registry (visible in theRolling tag detectedwarnings in the log). On 2-CPU GitHub runners this is slow and flaky — postgres barely made it, minio timed out.Fix
Replace the
pgandminioBitnami charts with plain, pinned manifests using official upstream images:postgres:16-alpineminio/minio:RELEASE.2025-04-08T15-41-24Z(tag existence verified on Docker Hub)These are throwaway smoke-test deps — the
deploy-flyte-kindskill itself uses external hosted Postgres + S3/R2 — so determinism matters more than fidelity here. Details:Servicekeeps the namepg-postgresqlthat theflyte-binarystep wires its DB host to (default userpostgres/ passwordflyte/ dbflyteall match).pg_isready,/minio/health/ready) gatekubectl rollout statusinstead of helm--wait.:latestdependency.Validation
Ran the exact changed deps block on a real isolated kind cluster: both pods reach
1/1 Runningin ~32s, versus the 5-min timeout that was being blown.bash -npasses.🤖 Generated with Claude Code