Run Notebook and Save Results #15

	name: Run Notebook and Save Results

	on:
	workflow_dispatch: # Enables manual trigger with input parameters
	inputs:
	file_url:
	description: "URL to download the file"
	required: true
	default: "https://example.com/file.csv"
	feature:
	description: "Feature to use (options: tdidf, bow)"
	required: true
	default: "tdidf"
	minGrams:
	description: "Minimum n-gram size"
	required: true
	default: 2
	maxGrams:
	description: "Maximum n-gram size"
	required: true
	default: 4
	maxFeatures:
	description: "Maximum feature size"
	required: true
	default: 250

	jobs:
	run-notebook:
	runs-on: ubuntu-latest

	steps:
	- name: Checkout repository
	uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.10'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pandas scikit-learn notebook

	- name: Download file
	run: \|
	curl -o data.csv -L "${{ github.event.inputs.file_url }}"

	- name: Run notebook
	run: \|
	python -m pip install nbconvert
	jupyter nbconvert \
	--to notebook \
	--execute tdIdf.ipynb \
	--output processed_notebook.ipynb \
	--ExecutePreprocessor.extra_arguments="--feature=${{ github.event.inputs.feature }} --minGrams=${{ github.event.inputs.minGrams }} --maxFeatures=${{ github.event.inputs.maxFeatures }} --maxGrams=${{ github.event.inputs.maxGrams }}"

	- name: Archive results
	run: \|
	mkdir -p results
	mv ${{ github.event.inputs.feature }}.csv results/
	echo "Results saved to 'results/' directory"

	- name: Upload results
	uses: actions/upload-artifact@v3
	with:
	name: processed-results
	path: results/

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