b2c6a57247
Status: Slice 95 closed Layer 4 (API → cascade SAP) on cert 001479 at < 1e-4 vs worksheet 69.0094. Production goal MET; the `test_api_001479_full_chain_sap_matches_worksheet_pdf_exactly` test formalises this gate. Updates to keep the next agent honest: - NEXT_AGENT_PROMPT: header + status table + cumulative SAP delta table + "First action" + epilogue all reflect Slice 95's close-out. - NEXT_AGENT_PROMPT §4 (Outlier golden cert investigations): rewrote the cert 0240 entry. The earlier "Type-1 RR gable_wall_lengths not extracted" claim is stale — mapper.py:1349-1369 already extracts them (Slices 71-86). The -15 SAP residual is a mix, dominated by the windows subsystem (11 windows × 18.28 m² with default U≈2.27 because Slice 93's `_API_GLAZING_TYPE_TO_TRANSMISSION` only covers glazing codes 3 and 13; cert 0240 lodges code 2). Surfacing glazing_type=2 (and likely other unmapped codes) is the biggest single-slice leverage point — and would touch 6035 too. - test_golden_fixtures.py cert 0240 `notes:` field: replaced the stale RR hypothesis with the actual cascade subsystem breakdown and the glazing_type-2 surfacing recommendation. No production code changed; docs and a `_GoldenExpectation.notes` string only. test_golden_fixtures.py stays GREEN (14 passed). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .devcontainer | ||
| .github/workflows | ||
| .idea | ||
| .vscode | ||
| asset_list | ||
| backend | ||
| backlog | ||
| datatypes | ||
| docs | ||
| epr_data_exports | ||
| etl | ||
| infrastructure/terraform | ||
| model_data/requirements | ||
| packages | ||
| recommendations | ||
| scripts | ||
| services | ||
| sfr/principal_pitch | ||
| survey_report | ||
| utils | ||
| .coveragerc | ||
| .dockerignore | ||
| .gitignore | ||
| __init__.py | ||
| AGENTS.md | ||
| 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_backlog.sh | ||
| 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