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
55 lines
1.3 KiB
Python
55 lines
1.3 KiB
Python
# generated by datamodel-codegen:
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# filename: forecast_request.json
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from __future__ import annotations
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from enum import StrEnum
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from typing import Literal
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from pydantic import BaseModel, ConfigDict, Field, RootModel, constr
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class Kind(StrEnum):
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LOAD = 'LOAD'
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PV = 'PV'
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PRICE = 'PRICE'
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class Unit(StrEnum):
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mw = 'mw'
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yuan_per_mwh = 'yuan_per_mwh'
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class Value(RootModel[constr(pattern=r'^-?\d+(\.\d+)?$')]):
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root: constr(pattern=r'^-?\d+(\.\d+)?$')
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class HistoryItem(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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interval_minutes: Literal[15]
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date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
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values: list[Value] = Field(..., max_length=96, min_length=96)
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class Exogenous(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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interval_minutes: Literal[15]
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date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
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values: list[Value] = Field(..., max_length=96, min_length=96)
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class ForecastRequest(BaseModel):
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model_config = ConfigDict(
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extra='forbid',
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)
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kind: Kind
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market_date: constr(pattern=r'^\d{4}-\d{2}-\d{2}$')
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unit: Unit
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history: list[HistoryItem] = Field(..., min_length=1)
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exogenous: dict[str, Exogenous]
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features_snapshot_ref: constr(pattern=r'^[0-9a-f]{64}$')
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