Model/docs/HANDOVER_MODELLING.md
Khalim Conn-Kowlessar b8b7e02034 docs(modelling): next-phase handover — depth + scale e2e + grilling prompt
Capture the next phase (close persisted-field gaps + financial uplift, plus a
large-scale e2e run of a SAP 10.2 EPC dump and console manual testing; measure
coverage deferred) and a self-contained handover prompt for a fresh agent to
pick up via a grilling session.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-03 23:09:08 +00:00

24 KiB
Raw Permalink Blame History

HANDOVER — Modelling stage rebuild

Branch: feature/bill-derivation (worktree /workspaces/home/hestia-worktrees/model-assemble-new-backend). HEAD: 6f0dcc04. PRD: GitHub Hestia-Homes/Model#1152, sliced into #1153#1161. All slices #1153#1161 closed.

Issue status

Issue What State
#1153 Overlay Applicator + EpcSimulation closed
#1154 Package Scorer closed — Elmhurst cascade pin (4c0a907a)
#1155 wall Recommendation Generator closed; cascade-pinned
#1156 score Options + attribution closed
#1157 persist a Plan via ModellingOrchestrator closed this session (772cdd4fc7e2aa37)
#1158 roof (loft) generator closed — 300 mm + cascade pin
#1159 floor generator closed — overlay insulation-type field + pins
#1160 Optimiser (knapsack + greedy repair) closed this session (77983cae34d4748a)
#1161 Measure Dependency (ventilation) closed this session (7c59e9190fec0699)

What this session did

  1. Cascade pins for #1154/#1158/#1159tests/domain/modelling/test_elmhurst_cascade_pins.py. Parse Elmhurst before/after recommendation Summaries via the extractor chain (NOT parse_site_notes_pdf), apply the generator's overlay, score, assert delta 0 vs the after-cert. Found+fixed: loft 270→300 mm; suspended floor needs the overlay to also set floor_insulation_type_str='Retro-fitted'.
  2. ProductJsonRepository (cc0bb8f9) — file-backed catalogue behind the ProductRepository port.
  3. #1157 — persist a Plan. Design review (/grill-with-docs) + 5 TDD slices. See "Design decisions" below.
  4. #1160 — the Optimiser. 4 TDD slices. See "Design decisions".

Design decisions locked this session (READ THESE)

  • Multi-phase is DEFERRED (speculative prospective-client ask). ADR-0005 rewritten to "Deferred". No plan_phase table, no phase column. CONTEXT.md no longer has Scenario Phase / Plan Phase / Rolled-over Options. Everything is single-phase. Future: a migration adds plan_phase + back-fills live plans as 1-phase.
  • Plan Measure is the new term (in CONTEXT.md): the persisted selected Option + its role-3 attributed impact + cost. Recommendation stays the candidate (never persisted; no stored impact).
  • Reuse the LIVE tables (plan, recommendation) — they exist in the live product (backend/app/db/models/recommendations.py, SQLAlchemy Base) and the FE reads them. The rebuild writes the same physical tables via SQLModel mirrors (infrastructure/postgres/plan_table.py) — the established pattern (task_table.pytasks, product_table.pymaterial). ADR-0017 records this.
  • Added recommendation.plan_id (FK→plan, ON DELETE CASCADE); retire the plan_recommendations m2m for new writes. FE-owned Drizzle migration: docs/migrations/recommendation-plan-id.md.
  • Tracer persists SAP + CO₂ (tonnes = calc kg ÷ 1000) + cost + derived post_epc_rating. Energy/bill columns deferred. Idempotent replace per (property_id, scenario_id).
  • Optimiser = exact pure-Python multiple-choice knapsack, NOT mip. Recycles GainOptimiser/CostOptimiser's formulation (≤1/group, maximise gain s.t. budget) but not the dependency — mip's CBC backend does not load on this aarch64 container (NameError: cbclib), so the legacy solver can't run/be tested here. ADR-0016's MILP is only a warm-start signal, so exact small-scale enumeration is ample. Re-score + greedy-repair toward the goal's SAP target gives the truth.

domain/modelling/ layout (grouped 84ec6da0)

Behaviour lives in subpackages; shared value-object vocabulary stays flat at the top (imported everywhere): recommendation.py (Recommendation / MeasureOption / Cost), plan.py, scenario.py, product.py, contingencies.py, simulation.py (EpcSimulation overlay).

  • generators/wall_recommendation / roof_recommendation / floor_recommendation.
  • scoring/overlay_applicator (apply_simulations), package_scorer (role 2), scoring (role-1 independent_option_impacts + role-3 marginal_impacts). Note the path is domain.modelling.scoring.scoring for the role-1/3 module.
  • optimisation/optimiser, measure_dependency.

What's built (all in domain/modelling/, infrastructure/postgres/, repositories/, orchestration/)

  • Generators (generators/): recommend_cavity_wall / recommend_loft_insulation (300 mm) / recommend_floor_insulation (sets floor_insulation_type_str).
  • simulation.py overlay + scoring/overlay_applicator.apply_simulations (generic field-fold) + scoring/package_scorer.PackageScorer.score (role 2) + scoring/scoring.py (marginal_impacts role 3, independent_option_impacts role 1).
  • scenario.py Scenario(id, goal, goal_value, budget, is_default); plan.py Plan + PlanMeasure (derives cost_of_works/contingency_cost/co2_savings/post_epc_rating).
  • optimisation/optimiser.pyoptimise(groups, budget) (exact knapsack) + optimise_package(...) (re-score + greedy repair, Scorer Protocol, OptimisedPackage).
  • infrastructure/postgres/: scenario_table.ScenarioRow, plan_table.{PlanRow,RecommendationRow} (mirrors of live tables; from_domain).
  • repositories/: scenario/, plan/, product/ (Postgres + Json) — all on the UnitOfWork (uow.scenario/uow.product/uow.plan).
  • ModellingOrchestrator.run(property_ids, scenario_ids, portfolio_id) — one UoW, commit once; generate (wall/roof/floor) → role-1 score → optimise_package → role-3 attribute → persist. Wired into AraFirstRunPipeline + handler.py.
  • datatypes/epc/domain/epc.py::Epc.sap_lower_bound() (band → min SAP, target for INCREASING_EPC).

Gotchas (will bite a fresh agent)

  • mip / CBC is broken on aarch64 here — never build runnable code on mip. The legacy recommendations/optimiser/ tests only "pass" because they avoid constructing a mip.Model.
  • moto is not installedtests/orchestration/test_postcode_splitter_orchestrator.py and tests/repositories/unstandardised_address/ fail at collection. Pre-existing, unrelated; --ignore them when sweeping.
  • Run tests: python -m pytest <path> -q (do NOT pass -p no:cov). Ephemeral Postgres via the db_engine fixture builds only SQLModel.metadata — legacy Base tables are absent in tests, which is why mirrors work.
  • Worktree import trap: python /tmp/foo.py imports /workspaces/model, not this worktree. Use pytest (rootdir handles it) or a python -c from the worktree root.
  • Driving Modelling in an integration test: the calculator fixtures (_elmhurst_worksheet_000490.build_epc()) lack lodged recorded-performance fields, so the Baseline stage can't run on them. Drive ModellingOrchestrator directly off a repo-seeded EPC (EpcPostgresRepository(session).save(epc, property_id, portfolio_id)) — see test_modelling_optimises_and_persists_a_multi_measure_plan. The sample API EPC (_lodged_epc()) does go through the full pipeline.
  • PortfolioGoal.INCREASING_EPC value is "Increasing EPC" (with a space) — the orchestrator compares scenario.goal == "Increasing EPC".
  • A generator calls products.get(...) during candidate generation, so the integration test must seed a material row for every measure type that fires (e.g. the sample EPC's uninsulated solid floor needs solid_floor_insulation).
  • Don't edit the SAP calculator's heat_transmission.py (another agent owns it).

Conventions

Commit per TDD slice; conventional-commit message ending Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>; stay on feature/bill-derivation. Tests use literal # Arrange / # Act / # Assert; assert with abs(x - y) <= tol (not pytest.approx); pyright strict, zero errors; annotate call-return locals. Cascade pins target the worksheet at delta 0.

#1161 — Measure Dependency (ventilation), as built (4 TDD slices, all green)

Forks resolved with the user (AskUserQuestion): guard now (skip when already MEV/MVHR), persist as a Plan Measure (cost + real negative marginal), forced but its cost counts toward spend (mandatory-when-triggered, never budget-gated; repair sees less headroom).

  1. 7c59e919 — Simulation Overlay grows a dwelling-level segment: VentilationOverlay (all-optional partial of SapVentilation, field mechanical_ventilation_kind) + EpcSimulation.ventilation; apply_simulations folds it onto sap_ventilation (creating one if the baseline lodged none). Until now the overlay was building-part only — ventilation is whole-dwelling.
  2. 6b11c902 — generic injection in the optimiser: MeasureDependency(triggers: frozenset[str], required: ScoredOption) lives in optimisation/optimiser.py (its input contract). optimise_package(..., dependencies=()) injects any dependency whose triggers ∩ selected-measure-types, before every re-score (initial and each repair). _inject dedups by required measure-type. Forced (injected even over budget) but its cost is in _package_cost, so repair headroom shrinks. _best_repair_candidate folds in any dependency a candidate newly triggers, so its marginal SAP and incremental cost are truthful; affordability gates on whole-package cost vs budget. Returned selected includes the injected deps. Optimiser stays domain-agnostic — no ventilation import.
  3. 1bf5b410domain/modelling/optimisation/measure_dependency.py: MEASURES_NEEDING_VENTILATION (cavity/internal/external wall, cf. legacy assumptions.measures_needing_ventilation) + ventilation_dependency(epc, products) → MEV Option (mechanical_ventilation_kind="EXTRACT_OR_PIV_OUTSIDE", decentralised MEV = legacy "mechanical, extract only"), priced at 2 fully-loaded units. Returns None when sap_ventilation.mechanical_ventilation_kind is already set (= legacy has_ventilation — confirmed against backend/Property.py:1236). Note: builder fetches the Product up-front, so the catalogue needs a mechanical_ventilation row for every not-yet-ventilated dwelling, even if no wall is ultimately selected.
  4. 0fec0699 — orchestrator wiring: _measure_dependencies builds the (≤1) dependency; _BEST_PRACTICE_ORDER gains "mechanical_ventilation" between loft and floors (role-3 cascade walls→roof→vent→floor); ventilation persists as a Plan Measure with its real negative marginal + cost. Added mechanical_ventilation: 0.26 contingency (legacy Costs.CONTINGENCIES). On 000490 the real calculator scores MEV at 1.275 SAP.

Post-#1161 refactor (631df92102afc04c): production split from selection-semantics. Detection + pricing moved into a proper generator generators/ventilation_recommendation.py::recommend_ventilation(epc, products) -> Optional[Recommendation] (same shape as wall/roof/floor; guard returns None when already mechanically ventilated). optimisation/measure_dependency.py now owns only the trigger set + the forced-edge wrapping: ventilation_dependency delegates to the generator and wraps the Recommendation (cheapest Option) into the MeasureDependency. The orchestrator's _measure_dependencies call is unchanged. Key asymmetry: recommend_ventilation lives in generators/ but is not in _candidate_recommendations' generator tuple — it's consumed only by the dependency path, never the free pool. This is the natural home for the multi-option future (MEV-c / MVHR) and the FE swap-in front.

Gotchas for the next agent: the ventilation Product/contingency must exist for any not-yet-ventilated dwelling (the generator fetches the Product at build time, not inject-time); the stub scorer in test_optimiser.py indexes building_parts[MAIN], so vent-only overlays need the separate _VentStubScorer.

Optimiser objective realigned to least-cost-to-target (5620f49f641c1bd7)

A /grill-with-docs pass found the rebuild had the wrong optimiser objective: it maximised SAP gain within budget (target as a repair floor), whereas the legacy StrategicOptimiser.solve() Case 1 (the intended behaviour) is min-cost subject to gain ≥ target and cost ≤ budget, fall back to max-gain only if the target is unreachable. ADR-0016 was amended (it had specified the wrong objective). 4 slices, all green:

  • 05a4f5f8optimise_min_cost(groups, budget, target_gain, dependencies=()): exact-enumeration sibling to optimise; cheapest package reaching target_gain within budget (ties → higher gain), None if unreachable.
  • 2bf42d04optimise_package rewired: target present → min-cost warm-start → inject → re-score → repair toward target; if warm-start infeasible or repaired package still short on the true score → _max_gain_package fallback. No target → max-gain (unchanged). Stops at the target, no overshoot into a higher band, surplus budget unspent.
  • af501fceventilation-aware selection: _with_role1_signals scores each dependency's true (negative) role-1 impact (was a 0.0 placeholder); _augmented_cost_gain folds the triggered dependency into every candidate's cost+gain in both selectors. Stops min-cost picking a wall whose mandatory ventilation (1 to 5 SAP) it can't justify, or whose £900 a wall-free package would avoid.
  • 641c1bd7 — orchestrator needed no change (already threads budget/target/deps); added an end-to-end pin (band-D property + goal D = already met → Plan with no measures).

Decisions locked (in the ADR amendment): target predicate sap_continuous ≥ band_floor (e.g. ≥ 69 for C — conservative, no legacy allow_slack); budget is a hard envelope — a wall whose ventilation would bust the budget is dropped, not forced over (reverses the earlier "forced regardless of budget" call; presence still guaranteed for any selected wall); warm-start-on-signal + re-score + repair kept (not exhaustive re-score) for scalability; "recommend slightly more than land short" is satisfied by the conservative floor + repair, not by spending budget for headroom.

Bill-Derivation: plan-level post-retrofit bills (75ba5dd7198122d1)

A /grill-with-docs pass designed the Modelling Bill-Derivation slice (ADR-0014 amended). Plan-level columns done across 4 slices; per-measure is the next slice.

  • ced6287b — relocated Bill / EnergyBreakdown / BillDerivation / sap_fuel (+ tests) from domain/property_baseline/ to a neutral domain/billing/ (cross-stage concern; both Baseline and Modelling consume it). Pure move, ~10 files.
  • 2bbc401fScore gains sap_result: Optional[SapResult], populated by PackageScorer. Lets Modelling bill the scored end-state reusing a SapResult the optimiser/orchestrator already computed — no second calculate. Optimiser ignores it (stays Score-only; stubs unaffected).
  • 26de28aaPlan carries optional baseline_bill / post_bill and derives post_energy_bill / energy_bill_savings / post_energy_consumption / energy_consumption_savings (None until billed → NULL).
  • 198122d1ModellingOrchestrator gains a constructor-injected FuelRatesRepository (mirrors Baseline — get_current() once, one BillDerivation per batch); _plan_for bills the baseline (scorer.score(epc, [])) and post-package (package.score) SapResults at the same snapshot, savings = baseline post. PlanRow mirror + from_domain persist the four columns (they already exist on the live plan table — no FE migration). Pipeline/handler wired.

Key properties: fuel-switch is handled for free — we bill the fully-overlaid post-package SapResult, so a future oil→ASHP measure prices at the new fuel via sap_code_to_fuel (no per-measure fuel bookkeeping). Baseline and post are priced at one FuelRates snapshot, so the delta is rate-consistent. Carries ADR-0014's appliances+cooking-stubbed-at-0 limitation (shared with Baseline, so savings stay consistent).

Bill-Derivation: per-measure bill savings (e79ffabfb976c3ab) — DONE

Filled recommendation.kwh_savings + energy_cost_savings via the telescoping bill cascade over the role-3 best-practice order. 3 slices, all green + pyright-strict-clean:

  • e79ffabf — enabling refactor: pulled the cumulative-prefix scoring out of marginal_impacts into a reusable scoring.cascade_scores(scorer, baseline, overlays) -> list[Score] (index 0 = baseline, one calculate per prefix) + a pure marginals_from_scores. Each Score carries its SapResult, so the bill cascade re-bills the same prefixes the role-3 attribution scores — no extra calculate. marginal_impacts now delegates (behaviour unchanged).
  • 7e79c30aPlanMeasure grows optional kwh_savings (delivered energy) + energy_cost_savings (£), signed so positive = saving, None until billed. RecommendationRow declares the live recommendation.kwh_savings/energy_cost_savings columns + maps them (None→NULL). Vestigial recommendation.energy_savings stays undeclared (legacy = 0). No FE migration (columns already live).
  • b976c3ab_plan_for scores baseline + every prefix once via cascade_scores, bills each at one Fuel Rates snapshot, and takes consecutive Bill deltas as each measure's marginal delivered-kWh + £ saving. The Plan's baseline_bill/post_bill are now the same cascade endpoints (bills[0]/bills[-1]), so per-measure savings telescope exactly to the headline savings — pinned on the real calculator (Σ per-measure == plan totals, abs ≤ 1e-6). Ventilation's saving is negative and still telescopes. Added Bill.total_consumption_kwh (shared by Plan + orchestrator); dropped the redundant standalone baseline calculate.

Key property: MeasureImpact.energy_savings_kwh_per_yr is primary energy and does not feed kwh_savingskwh_savings is delivered energy from the Bill section kWh. Carries ADR-0014's appliances+cooking-stubbed-at-0 limitation.

Retire plan_recommendations + consolidate models (b76d0f816f0dcc04) — DONE

Designed in /grill-with-docs + /grill-me. The live plan/recommendation tables are read directly by the Drizzle FE, so this was a two-repo expand/contract. FE-visibility goal met: Plans and their measures now link solely by recommendation.plan_id; the m2m is gone. 9 slices, all green + pyright-strict-clean, and the rebuild + legacy suites are now co-runnable (the consolidation fixed a pre-existing dual-definition collision).

  • b76d0f81 — migration spec (docs/migrations/recommendation-plan-id.md: add plan_id → backfill → dual-write → cut reads → drop; backfill-before-reads + dual-write are the load-bearing rules since the FE can't deploy atomically) + ADR-0017 amendment.
  • c1c7b06f — consolidate plan/recommendation/recommendation_materials into infrastructure/postgres/modelling/ as single SQLModel defs (absorbing the partial PlanRow/RecommendationRow mirrors, full column parity + plan_id). backend/app/db/models/recommendations.py → re-export shim. Export conftest: create SQLModel-first / skip the redundant drop_all (the epc enum type is now shared across both metadatas).
  • 27fcc5b1 — legacy writers set recommendation.plan_id (dual-write).
  • af5dbe32 — cut all three readers (portfolio_functions, Outputs, export/property_scenarios) onto plan_id.
  • b97d0688 — drop the m2m: writes, delete_property_batch cleanup, the PlanRecommendationRow model, the test_export fixtures.
  • 01c2c391 — rename the cluster …Row…Model (matches the epc_property precedent + the legacy names backend/ already imports, so the shim's plan re-export is literal). The non-cluster …Row tables stay until their live legacy …Model counterparts retire (renaming now would re-create dual-definition collisions).
  • 2fbd7147 — move PortfolioGoal to domain/modelling/portfolio_goal.py (domain vocab; infra→domain is the normal direction); portfolio.py keeps a re-export.
  • c18968ba — consolidate scenario + installed_measure (full-parity ScenarioModel/InstalledMeasureModel + MeasureType). ScenarioModel.goal is the PortfolioGoal enum (legacy planning branches on it); the repo's to_domain maps it to its value, so Scenario.goal is now the value "Increasing EPC" consistent with the orchestrator — fixing the latent name-vs-value bug the old str column masked.
  • 6f0dcc04 — characterization test for the FE aggregation aggregate_portfolio_recommendations (was untested), pinning the plan_id join.

Gotchas for the next agent: the modelling SQLModel classes are …Model and live in infrastructure/postgres/modelling/ (NOT the old flat plan_table.py/scenario_table.py — deleted); backend/app/db/models/recommendations.py is now a pure shim. Out-of-cluster columns are plain ints (no FK) per the mirror convention. PortfolioGoal lives in domain/modelling/ now. The etl/+sfr/ reporting scripts still reference the m2m and are deferred (out of scope). The live DB changes (add plan_id, backfill, drop plan_recommendations) are the FE-owned Drizzle migrations in the migration doc — this branch is the backend end-state.

NEXT PHASE — depth + scale e2e (handover for a grilling session)

The owner's goal: run a large dump of SAP 10.2 EPCs (1,00010,000) through Modelling and inspect the recommendations — a large-scale integration test — plus manual testing via a Python console. Measure coverage (heating/solar/glazing/…) is explicitly deferred ("we'll flesh this out"). This phase is depth + scale on the existing 4 fabric measures (cavity wall / loft / floor / ventilation):

  1. Close the persisted-field gaps so a persisted Plan matches the engine's richness for the measures we do model: recommendation_materials (BOM — depth/quantity/unit/cost; rebuild Cost is a single total today, no per-material breakdown), per-measure U-values (starting_u_value/new_u_value), total_work_hours/labour_days. Source of truth: the rebuild ProductRepository (repositories/product/) + legacy materials_functions.py / recommendations_functions.upload_recommendations (writes rec["parts"]).
  2. Financial uplift modelling — valuation columns (plan.valuation_*, recommendation.property_valuation_increase/rental_yield_increase) are greenfield in the rebuild (no domain concept yet). Legacy logic: backend/Property.py, backend/Funding.py, backend/app/db/functions/funding_functions.py, portfolio_functions.py. Needs a domain design (likely a /grill-with-docs pass).
  3. Large-scale e2e harness — template is tests/orchestration/test_ara_first_run_pipeline_integration.py::test_modelling_optimises_and_persists_a_multi_measure_plan (seeds an EPC via EpcPostgresRepository + MaterialRows + a ScenarioModel, runs ModellingOrchestrator directly — the Baseline stage can't run on calculator fixtures). For the dump: parse each EPC via EpcPropertyDataMapper.from_api_response / from_rdsap_schema_21_0_x (see datatypes/epc/domain/mapper.py), seed, run, inspect. EPC samples live under backend/epc_api/json_samples/.
  4. Python-console manual run — instantiate ModellingOrchestrator against a real DB and inspect Plans/Recommendations. Mind the worktree import trap (run from the worktree root, not /tmp).

A self-contained handover prompt for the next agent is in docs/HANDOVER_NEXT_PHASE_PROMPT.md.

What's left

Deferred fronts (open, post-#1161): exclusion-filtering of the candidate pool (deferred from #1160); persist unselected alternatives (default=False rows linked via plan_id) for the swap-in UX — open ADR-0016 question: what impact figure they carry; promote ProductRepository to the DB+file composite; non-EPC goal objectives (Energy Savings, Reducing CO2) in the optimiser. Possible extension of the ventilation trigger set to roof insulation (now a one-line data edit in MEASURES_NEEDING_VENTILATION); and making the dependency builder lazy (thunk) so the Product is only fetched when a trigger is actually selected.

Key references

  • ADRs: 0005 (multi-phase deferred), 0011/0012 (orchestrators + UoW), 0016 (three scoring roles + warm-start/re-score/repair), 0017 (Plan persistence — evolve live tables).
  • CONTEXT.md: Plan, Plan Measure, Recommendation, Measure Option, Optimised Package, Scenario, Measure Dependency.
  • Auto-memory project_modelling_stage_state has the running state.