8796faca63
- packages/domain: ForecastRequest, BidOptimizationRequest/Result,
ReportRequest, SkillReport (+ golden and invalid fixtures, exported to
contracts/ and regenerated as pydantic models).
- skills-py/vpp_skills: FastAPI service with versioned registry; load/PV/
price forecasts (same-day-type EWM point forecast, conformal residual
quantiles — coverage test as acceptance gate); bid-optimization MILP on
HiGHS (binary block participation, hard ledger energy bounds, exact
Decimal fit of the rounded curve inside the bounds, revenue distribution
over quantile paths); report generator whose every figure is a
{tool_call_id, path} reference, with a verifier. 48 tests incl. hypothesis
property test that bids respect ledger constraints.
- packages/services: LedgerService.dayAheadBounds (the P7 cascade band
handed to the optimizer); Decimal resolved once for CJS/ESM interop.
- packages/evals: L2 metrics (MAPE, nRMSE, coverage, direction accuracy,
naive/hindsight revenue baselines), HTTP skill client, rolling-origin
harness that pushes each bid through the real ledger, CLI with
--check/--write-baseline; committed baseline on the SYNTHETIC dataset
(no historical Hubei data yet — baselines measure the harness, not KPI).
- CI: evals job boots the skill service and fails on baseline digest drift.
- docs/open-questions: A6 (flexibility marginal cost = offer floor); A4/B6
wired as placeholders. README/CLAUDE.md status → M2 done, M3 next.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UoYoGYzHkFyv3ALenkRPhA
74 lines
2.5 KiB
YAML
74 lines
2.5 KiB
YAML
name: ci
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on:
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push:
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branches: [master]
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pull_request:
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jobs:
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# Domain schemas + deterministic services (TS side of the contract pipeline).
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typescript:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-node@v4
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with:
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node-version: 24
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cache: npm
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- run: npm ci
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- run: npm run typecheck
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# ADR-0002: contracts/ is generated from packages/domain and committed.
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# A dirty tree here means someone changed a zod schema without
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# re-exporting, or hand-edited a generated file.
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- run: npm run export:schemas && npm run make:fixtures
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- run: git diff --exit-code -- contracts/
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- run: npm test
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# Generated pydantic models must accept/reject the same golden fixtures the
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# TS side does (docs/11 §3.2 dual-side contract test).
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python:
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runs-on: ubuntu-latest
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defaults:
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run:
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working-directory: skills-py
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version-file: skills-py/.python-version
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cache: pip
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cache-dependency-path: skills-py/requirements.txt
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- run: pip install -r requirements.txt
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# Generated models are committed but never hand-edited: regenerate and
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# require a clean tree.
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- run: bash scripts/generate_models.sh
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- run: git diff --exit-code -- vpp_contracts/
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- run: python -m pytest -q
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# L2 eval harness end-to-end (docs/12): TS harness ↔ live Python skill
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# service on the committed synthetic dataset. The run must reproduce the
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# committed baseline digest exactly — a skill change that moves a metric
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# must come with a reviewed baseline update (docs/12 §3 gate).
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evals:
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runs-on: ubuntu-latest
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needs: [typescript, python]
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-node@v4
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with:
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node-version: 24
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cache: npm
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- uses: actions/setup-python@v5
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with:
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python-version-file: skills-py/.python-version
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cache: pip
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cache-dependency-path: skills-py/requirements.txt
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- run: npm ci
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- run: pip install -r skills-py/requirements.txt
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- name: start skill service
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working-directory: skills-py
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run: |
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python -m uvicorn vpp_skills.app:app --port 8000 --log-level warning &
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for i in $(seq 1 40); do curl -sf http://127.0.0.1:8000/health && break; sleep 0.5; done
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- run: npm run eval -w @vpp/evals -- --check
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