7e1269fc8e
Update NEXT_AGENT_PROMPT.md with the pivot to the rigorous cohort pattern: cert 001479's hand-built `_elmhurst_worksheet_001479.py` becomes the ground-truth EpcPropertyData. Cross-mapper parity work then collapses to "both mappers produce hand-built-equivalent EpcPropertyData". Two parallel workstreams documented: 1. Iterate the hand-built skeleton (Slice 62) until all 11 cascade pins hit 1e-4. Current state: 2/11 green (pumps_fans, lighting); sap_score_continuous gap −3.02 SAP. Likely next slices: HW demand routing, §2 ventilation tuning, thermal mass parameter, multiple- glazed proportion. 2. Once hand-built is GREEN, add `test_elmhurst_mapper_matches_hand_ built` + `test_api_mapper_matches_hand_built` over the 7-cert cohort (000474..000516 + 001479). Every field diff = mapper bug to close. Cross-parity collapses to "both mappers produce hand-built-equivalent". Documents the M-vs-L Ext1 age-band source-data conflict (hand-built uses worksheet's L; Elmhurst mapper trusts Summary's M) — surfaces as a known caveat in cross-mapper diff. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
||
|---|---|---|
| .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