79a0203798
Cuts the per-run LLM cost ~10x (MiniMax M2.7 vs gpt-4.1-mini) and removes the recurring OpenAI-quota-exhaustion failure mode that took the canary down on 2026-05-03 (#265 — staging quota burnt for ~16h). Path: E2E_RUNTIME=claude-code (default) → workspace-configs-templates/claude-code-default/config.yaml's `minimax` provider (lines 64-69) → ANTHROPIC_BASE_URL auto-set to api.minimax.io/anthropic → reads MINIMAX_API_KEY (per-vendor env, no collision with GLM/Z.ai etc.) Workflow changes (continuous-synth-e2e.yml): - Default runtime: langgraph → claude-code - New env: E2E_MODEL_SLUG (defaults to MiniMax-M2.7-highspeed, overridable via workflow_dispatch) - New secret wire: E2E_MINIMAX_API_KEY ← secrets.MOLECULE_STAGING_MINIMAX_API_KEY - Per-runtime missing-secret guard: claude-code requires MINIMAX, langgraph/hermes require OPENAI. Cron firing hard-fails on missing key for the active runtime; dispatch soft-skips so operators can ad-hoc test without setting up the secret first - Operators can still pick langgraph/hermes via workflow_dispatch; the OpenAI fallback path stays wired Script changes (tests/e2e/test_staging_full_saas.sh): - SECRETS_JSON branches on which key is set: E2E_MINIMAX_API_KEY → {MINIMAX_API_KEY: <key>} (claude-code path) E2E_OPENAI_API_KEY → {OPENAI_API_KEY, HERMES_*, MODEL_PROVIDER} (legacy) MiniMax wins when both are present — claude-code default canary must not accidentally consume the OpenAI key Tests (new tests/e2e/test_secrets_dispatch.sh): - 10 cases pinning the precedence + payload shape per branch - Discipline check verified: 5 of 10 FAIL on a swapped if/elif (precedence inversion), all 10 PASS on the fix - Anchors on the section-comment header so a structural refactor fails loudly rather than silently sourcing nothing The model_slug dispatcher (lib/model_slug.sh) needs no change: E2E_MODEL_SLUG override path is already wired (line 41), and claude-code template's `minimax-` prefix matcher catches "MiniMax-M2.7-highspeed" via lowercase-on-lookup. Operator action required to land green: - Set MOLECULE_STAGING_MINIMAX_API_KEY in repo secrets (Settings → Secrets and Variables → Actions). Use `gh secret set MOLECULE_STAGING_MINIMAX_API_KEY -R Molecule-AI/molecule-core` to avoid leaking the value into shell history. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
222 lines
11 KiB
YAML
222 lines
11 KiB
YAML
name: Continuous synthetic E2E (staging)
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# Hard gate (#2342): cron-driven full-lifecycle E2E that catches
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# regressions visible only at runtime — schema drift, deployment-pipeline
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# gaps, vendor outages, env-var rotations, DNS / CF / Railway side-effects.
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#
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# Why this gate exists:
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# PR-time CI catches code-level regressions but not deployment-time or
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# integration-time ones. Today's empirical data:
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# • #2345 (A2A v0.2 silent drop) — passed all unit tests, broke at
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# JSON-RPC parse layer between sender and receiver. Visible only
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# to a sender exercising the full path.
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# • RFC #2312 chat upload — landed on staging-branch but never
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# reached staging tenants because publish-workspace-server-image
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# was main-only. Caught by manual dogfooding hours after deploy.
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# Both would have surfaced within 15-20 min of regression if a
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# continuous synth-E2E was running.
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#
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# Cadence: every 20 min (3x/hour). The script is conservatively
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# bounded at 10 min wall-clock; even on degraded staging it should
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# finish before the next firing. cron-overlap is guarded by the
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# concurrency group below.
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#
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# Cost: ~3 runs/hour × 5-10 min × $0.008/min GHA = ~$0.50-$1/day.
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# Plus a fresh tenant provisioned + torn down each run (Railway +
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# AWS pennies). Negligible.
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#
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# Failure handling: when the run fails, the workflow exits non-zero
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# and GitHub's standard email/notification path fires. Operators
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# can subscribe to this workflow's failure channel for paging-grade
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# alerting.
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on:
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schedule:
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# Every 20 minutes, on the :00 :20 :40. Offsets the existing :15
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# sweep-cf-orphans and :45 sweep-cf-tunnels so the three
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# operations don't all hit Cloudflare/AWS at the same minute.
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- cron: '0,20,40 * * * *'
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workflow_dispatch:
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inputs:
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runtime:
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description: "Runtime to provision (claude-code = default + cheapest via MiniMax; langgraph = OpenAI-only; hermes = SDK-native path, slower)"
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required: false
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default: "claude-code"
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type: string
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model_slug:
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description: "Model id to provision the workspace with (default MiniMax-M2.7-highspeed; e.g. 'sonnet' to test direct Anthropic, 'openai/gpt-4o' for hermes)"
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required: false
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default: "MiniMax-M2.7-highspeed"
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type: string
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keep_org:
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description: "Skip teardown for post-mortem debugging (only manual dispatch — never set this for cron runs)"
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required: false
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default: false
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type: boolean
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permissions:
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contents: read
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# No issue-write here — failures surface as red runs in the workflow
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# history. If you want auto-issue-on-fail, add a follow-up step that
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# uses gh issue create gated on `if: failure()`. Keeping the surface
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# minimal until that's actually wanted.
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# Serialize so two firings can never overlap. Cron firing every 20 min
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# but scripts conservatively bounded at 10 min — overlap shouldn't
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# happen in steady state, but if a run hangs we don't want N more
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# stacking up.
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concurrency:
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group: continuous-synth-e2e
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cancel-in-progress: false
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jobs:
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synth:
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name: Synthetic E2E against staging
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runs-on: ubuntu-latest
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timeout-minutes: 12
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env:
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# claude-code default: cold-start ~5 min (comparable to langgraph),
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# but uses MiniMax-M2.7-highspeed via the template's third-party-
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# Anthropic-compat path (workspace-configs-templates/claude-code-
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# default/config.yaml:64-69). MiniMax is ~5-10x cheaper than
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# gpt-4.1-mini per token AND avoids the recurring OpenAI quota-
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# exhaustion class that took the canary down 2026-05-03 (#265).
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# Operators can pick langgraph / hermes via workflow_dispatch
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# when they specifically need to exercise the OpenAI or SDK-
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# native paths.
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E2E_RUNTIME: ${{ github.event.inputs.runtime || 'claude-code' }}
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# Pin the canary to a specific MiniMax model rather than relying
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# on the per-runtime default ("sonnet" → routes to direct
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# Anthropic, defeats the cost saving). Operators can override
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# via workflow_dispatch by setting a different E2E_MODEL_SLUG
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# input if they need to exercise a specific model. M2.7-highspeed
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# is "Token Plan only" but cheap-per-token and fast.
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E2E_MODEL_SLUG: ${{ github.event.inputs.model_slug || 'MiniMax-M2.7-highspeed' }}
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# Bound to 10 min so a stuck provision fails the run instead of
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# holding up the next cron firing. 15-min default in the script
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# is for the on-PR full lifecycle where we have more headroom.
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E2E_PROVISION_TIMEOUT_SECS: '600'
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# Slug suffix — namespaced "synth-" so these runs are
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# distinguishable from PR-driven runs in CP admin.
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E2E_RUN_ID: synth-${{ github.run_id }}
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# Forced false for cron; respected for manual dispatch
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E2E_KEEP_ORG: ${{ github.event.inputs.keep_org == 'true' && '1' || '' }}
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MOLECULE_CP_URL: ${{ vars.STAGING_CP_URL || 'https://staging-api.moleculesai.app' }}
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MOLECULE_ADMIN_TOKEN: ${{ secrets.CP_STAGING_ADMIN_API_TOKEN }}
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# MiniMax key is the canary's PRIMARY auth path. claude-code
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# template's `minimax` provider routes ANTHROPIC_BASE_URL to
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# api.minimax.io/anthropic and reads MINIMAX_API_KEY at boot.
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# tests/e2e/test_staging_full_saas.sh branches SECRETS_JSON on
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# which key is present — MiniMax wins when set.
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E2E_MINIMAX_API_KEY: ${{ secrets.MOLECULE_STAGING_MINIMAX_API_KEY }}
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# OpenAI fallback — kept wired so operators can dispatch with
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# E2E_RUNTIME=langgraph or =hermes and still have a working
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# canary path. The script picks the right blob shape based on
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# which key is non-empty.
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E2E_OPENAI_API_KEY: ${{ secrets.MOLECULE_STAGING_OPENAI_KEY }}
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steps:
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- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
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- name: Verify required secrets present
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env:
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# Re-bind so the per-runtime LLM key check below sees the right
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# secret. The job-level env block already reads both; this just
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# makes them visible inside the conditional shell.
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IS_DISPATCH: ${{ github.event_name == 'workflow_dispatch' }}
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run: |
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# Schedule-vs-dispatch hardening (mirrors the sweep-cf-* and
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# redeploy-tenants-on-* workflows): hard-fail on missing secret
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# for cron firing so a misconfigured-repo doesn't silently
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# report green while doing nothing. Soft-skip on operator
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# dispatch — operators can dispatch ad-hoc to verify a fix
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# without setting up the secret first.
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if [ -z "${MOLECULE_ADMIN_TOKEN:-}" ]; then
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if [ "$IS_DISPATCH" = "true" ]; then
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echo "::warning::CP_STAGING_ADMIN_API_TOKEN not set — synth E2E cannot run"
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echo "::warning::Set it at Settings → Secrets and Variables → Actions"
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exit 0
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fi
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echo "::error::CP_STAGING_ADMIN_API_TOKEN secret missing — synth E2E cannot run"
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echo "::error::Set it at Settings → Secrets and Variables → Actions; pull from staging-CP's CP_ADMIN_API_TOKEN env in Railway."
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exit 1
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fi
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# LLM-key requirement is per-runtime: claude-code uses MiniMax
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# (MOLECULE_STAGING_MINIMAX_API_KEY), langgraph + hermes use
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# OpenAI (MOLECULE_STAGING_OPENAI_KEY). Cron firing must have
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# the right key for the active runtime; dispatch can soft-skip.
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case "${E2E_RUNTIME}" in
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claude-code)
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required_secret_name="MOLECULE_STAGING_MINIMAX_API_KEY"
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required_secret_value="${E2E_MINIMAX_API_KEY:-}"
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;;
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langgraph|hermes)
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required_secret_name="MOLECULE_STAGING_OPENAI_KEY"
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required_secret_value="${E2E_OPENAI_API_KEY:-}"
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;;
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*)
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echo "::warning::Unknown E2E_RUNTIME='${E2E_RUNTIME}' — skipping LLM-key check"
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required_secret_name=""
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required_secret_value="present"
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;;
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esac
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if [ -n "$required_secret_name" ] && [ -z "$required_secret_value" ]; then
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if [ "$IS_DISPATCH" = "true" ]; then
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echo "::warning::${required_secret_name} not set — synth E2E with runtime=${E2E_RUNTIME} cannot reach an LLM"
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echo "::warning::Set it at Settings → Secrets and Variables → Actions, OR dispatch with a different runtime"
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exit 0
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fi
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echo "::error::${required_secret_name} secret missing — runtime=${E2E_RUNTIME} cannot authenticate against its LLM provider"
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echo "::error::Set it at Settings → Secrets and Variables → Actions"
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exit 1
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fi
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- name: Install required tools
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run: |
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# The script depends on jq + curl (already on ubuntu-latest)
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# and python3 (likewise). Verify they're all present so we
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# fail fast on a runner image regression rather than mid-script.
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for cmd in jq curl python3; do
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command -v "$cmd" >/dev/null 2>&1 || {
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echo "::error::required tool '$cmd' not on PATH — runner image regression?"
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exit 1
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}
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done
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- name: Run synthetic E2E
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# The script handles its own teardown via EXIT trap; even on
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# failure (timeout, assertion), the org is deprovisioned and
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# leaks are reported. Exit code propagates from the script.
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run: |
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bash tests/e2e/test_staging_full_saas.sh
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- name: Failure summary
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# Runs only on failure. Adds a job summary so the workflow run
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# page shows a quick "what happened" instead of forcing readers
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# to scroll through script output.
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if: failure()
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run: |
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{
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echo "## Continuous synth E2E failed"
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echo ""
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echo "**Run ID:** ${{ github.run_id }}"
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echo "**Trigger:** ${{ github.event_name }}"
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echo "**Runtime:** ${E2E_RUNTIME}"
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echo "**Slug:** synth-${{ github.run_id }}"
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echo ""
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echo "### What this means"
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echo ""
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echo "Staging just regressed on a path that previously worked. Likely classes:"
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echo "- Schema mismatch between sender and receiver (#2345 class)"
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echo "- Deployment-pipeline gap (RFC #2312 / staging-tenant-image-stale class)"
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echo "- Vendor outage (Cloudflare, Railway, AWS, GHCR)"
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echo "- Staging-CP env var rotation"
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echo ""
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echo "### Next steps"
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echo ""
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echo "1. Check the script output above for the assertion that failed"
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echo "2. If it's a vendor outage, no action needed — next firing in ~20 min"
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echo "3. If it's a code regression, find the causing PR via \`git log\` against last green run and revert/fix"
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echo "4. Keep an eye on the next 1-2 firings — flake vs persistent fail differs in priority"
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} >> "$GITHUB_STEP_SUMMARY"
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