34d4748a3a
Slice 3b — closes #1160. ModellingOrchestrator._plan_for now runs the full ADR-0016 flow instead of a single cavity measure: generate wall + roof + floor Recommendations → score each Option independently (role 1) into grouped ScoredOptions → optimise_package (grouped knapsack within budget + whole-package re-score + greedy repair toward the Scenario's SAP target) → attribute the selected set via the best-practice marginal cascade (role 3) → persist the Plan with its Plan Measures. The repair target comes from the goal: INCREASING_EPC → the goal_value band floor via Epc.sap_lower_bound(); other goals carry no SAP target yet (later slice). Best-practice order walls → roof → floor. Integration test: an uninsulated cavity wall + suspended floor (000490) driven directly through the Modelling stage off a repo-seeded EPC (the calculator fixture has no lodged recorded-performance fields, so Baseline can't run it) persists a Plan with two attributed, priced Plan Measures. The existing first-run test keeps full-pipeline coverage and now exercises real modelling (its sample EPC's uninsulated solid floor yields a floor measure). Replaces the single-measure cavity integration test (subsumed). 138 pass; pyright strict clean. Multi-phase remains descoped (ADR-0005); single-phase optimiser. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .github/workflows | ||
| .idea | ||
| .vscode | ||
| applications | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| deployment/terraform | ||
| docs | ||
| domain | ||
| epr_data_exports | ||
| etl | ||
| infrastructure | ||
| model_data/requirements | ||
| orchestration | ||
| recommendations | ||
| repositories | ||
| sap worksheets | ||
| scripts | ||
| sfr/principal_pitch | ||
| survey_report | ||
| tests | ||
| utilities | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| ara_backend_design.md | ||
| BaseUtility.py | ||
| CLAUDE.md | ||
| conftest.py | ||
| CONTEXT.md | ||
| devcontainer.sh | ||
| Dockerfile.test | ||
| Dockerfile.test.dockerignore | ||
| Makefile | ||
| MEMORY.md | ||
| package-lock.json | ||
| package.json | ||
| pyproject.toml | ||
| pyrightconfig.json | ||
| pytest.ini | ||
| README.md | ||
| run_lambda_local.sh | ||
| serverless.yml | ||
| test.requirements.txt | ||
| tox.ini | ||
| UBIQUITOUS_LANGUAGE.md | ||
Model Repository
This repository contains the code pertaining to the development of the data science and machine learning products being utilised by Hestia.
The different folders in this repository relate to services that can be used independently, or can be imported and used as part of a larger application
Getting Started
Prerequisites
Dev Container Setup
This repo uses a Docker Compose-based dev container. The model-backend service joins a shared-dev Docker network so it can communicate with other local services (e.g. a frontend container) running on your machine.
VS Code users: The initializeCommand in devcontainer.json creates the shared-dev network automatically before the container starts. No manual step required — just open the repo and select Reopen in Container.
Non-VS Code / CI workflows: Run the following once before starting the container:
make dev-setup
This is idempotent and safe to re-run if the network already exists.
Folders
backend/
This folder contains the code for the fastapi backend service, which provides an interface to much of the functionality in this repository, for the frontend
model_data/
This folder contains related to the reading and preparation of assessment model data, including pulling out epc attributes
Testing
All tests can be run, against the configuration in pytest.ini running
pytest
This will run the complete panel of tests and report on coverage in the locations specified by the pytest.ini file.
To run tests in a specific service, e.g. inside of model_data, simply run
pytest --cov-config=model_data/.coveragerc --cov=model_data
This will produce the test results and coverage reports