Use `model_name` to set `fit_<signal>` flags for `build_model_from_dir` in `generate_predictive.py` #556

	name: Pipeline Run Check

	on:
	pull_request:
	push:
	branches: [main]

	concurrency:
	group: ${{ github.workflow }}-${{ github.head_ref \|\| github.ref }}
	cancel-in-progress: true

	jobs:
	run-pipeline:
	strategy:
	matrix:
	os: [ubuntu-22.04, macos-latest]
	runs-on: ${{matrix.os}}

	env:
	NHSN_API_KEY_ID: ${{ secrets.NHSN_API_KEY_ID }}
	NHSN_API_KEY_SECRET: ${{ secrets.NHSN_API_KEY_SECRET }}
	steps:
	- uses: actions/checkout@v4
	- name: Set up python
	uses: actions/setup-python@v5
	with:
	python-version: "3.12"
	- name: "Set up R"
	uses: r-lib/actions/setup-r@v2
	with:
	r-version: "release"
	use-public-rspm: true
	- name: "Set up Quarto"
	uses: quarto-dev/quarto-actions/setup@v2
	- name: "Install poetry"
	run: pip install poetry
	- name: "Install pyrenew-hew"
	run: poetry install
	- name: "Set up dependencies for hewr"
	uses: r-lib/actions/setup-r-dependencies@v2
	with:
	working-directory: hewr
	- name: "Install hewr"
	run: pak::local_install("hewr", ask = FALSE)
	shell: Rscript {0}
	- name: "Run pipeline"
	run: poetry run bash pipelines/tests/test_end_to_end.sh pipelines/tests

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