Add required model and config files for deployment; update .gitignore… #22

Workflow file for this run

	name: CI/CD Pipeline

	on:
	push:
	branches: [ main, develop ]
	pull_request:
	branches: [ main, develop ]
	schedule:
	# Run daily at 2 AM UTC for automated data collection
	- cron: '0 2 * * *'

	jobs:
	# Linting and Code Quality
	lint:
	runs-on: ubuntu-latest
	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.11'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install flake8 black isort mypy

	- name: Lint with flake8
	run: \|
	# Stop build if there are Python syntax errors or undefined names
	flake8 backend/ ml_models/ --count --select=E9,F63,F7,F82 --show-source --statistics
	# Exit-zero treats all errors as warnings
	flake8 backend/ ml_models/ --count --exit-zero --max-complexity=15 --max-line-length=120 --statistics

	- name: Check code formatting with black
	run: \|
	black --check backend/ ml_models/

	- name: Check import sorting with isort
	run: \|
	isort --check-only backend/ ml_models/

	# Unit Tests
	test:
	runs-on: ubuntu-latest
	needs: lint

	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.11'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install -r requirements.txt
	pip install pytest pytest-cov pytest-asyncio

	- name: Create .env file
	run: \|
	echo "MONGODB_URI=${{ secrets.MONGODB_URI }}" >> .env
	echo "MONGODB_DATABASE=pearl_aqi_test_db" >> .env
	echo "OPENWEATHER_API_KEY=${{ secrets.OPENWEATHER_API_KEY }}" >> .env
	echo "WAQI_API_KEY=${{ secrets.WAQI_API_KEY }}" >> .env

	- name: Run tests
	run: \|
	pytest tests/ --cov=backend --cov=ml_models --cov-report=xml --cov-report=html

	- name: Upload coverage reports
	uses: codecov/codecov-action@v3
	with:
	file: ./coverage.xml
	flags: unittests
	name: codecov-umbrella

	# API Integration Tests
	integration:
	runs-on: ubuntu-latest
	needs: test

	services:
	mongodb:
	image: mongo:7.0
	ports:
	- 27017:27017

	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.11'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install -r requirements.txt
	pip install httpx pytest-asyncio

	- name: Create .env file
	run: \|
	echo "MONGODB_URI=mongodb://localhost:27017/" >> .env
	echo "MONGODB_DATABASE=pearl_aqi_test_db" >> .env

	- name: Run FastAPI server
	run: \|
	cd backend
	python main.py &
	sleep 10

	- name: Test API endpoints
	run: \|
	curl http://localhost:8000/health
	curl http://localhost:8000/api/v1/locations


	# Model Training and Validation
	model-validation:
	runs-on: ubuntu-latest
	needs: test

	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.11'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install -r requirements.txt

	- name: Create .env file
	run: \|
	echo "MONGODB_URI=${{ secrets.MONGODB_URI }}" >> .env
	echo "MONGODB_DATABASE=${{ secrets.MONGODB_DATABASE }}" >> .env

	- name: Validate model files
	run: \|
	python -c "
	import os
	if os.path.exists('models/xgboost_model.json') and os.path.exists('models/model_metrics.json'):
	print('✅ Model files found')
	else:
	print('⚠️ Model files missing - skipping validation (expected in CI environment without DVC)')
	"

	- name: Test model inference
	run: \|
	python tests/test_models.py

	# Automated Data Collection (scheduled job)
	data-collection:
	runs-on: ubuntu-latest
	if: github.event_name == 'schedule'

	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: '3.11'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install -r requirements.txt

	- name: Create .env file
	run: \|
	echo "MONGODB_URI=${{ secrets.MONGODB_URI }}" >> .env
	echo "MONGODB_DATABASE=${{ secrets.MONGODB_DATABASE }}" >> .env
	echo "OPENWEATHER_API_KEY=${{ secrets.OPENWEATHER_API_KEY }}" >> .env
	echo "WAQI_API_KEY=${{ secrets.WAQI_API_KEY }}" >> .env

	- name: Fetch air quality data
	run: \|
	python scripts/automated_data_fetch.py

	- name: Generate predictions
	run: \|
	python prediction_pipeline.py

	# Docker Build and Push (Disabled)
	# docker:
	# runs-on: ubuntu-latest
	# needs: [test, integration]
	# if: github.event_name == 'push' && github.ref == 'refs/heads/main'

	# steps:
	# - uses: actions/checkout@v3

	# - name: Set up Docker Buildx
	# uses: docker/setup-buildx-action@v2

	# - name: Login to Docker Hub
	# uses: docker/login-action@v2
	# with:
	# username: ${{ secrets.DOCKER_USERNAME }}
	# password: ${{ secrets.DOCKER_PASSWORD }}

	# - name: Build and push backend
	# uses: docker/build-push-action@v4
	# with:
	# context: .
	# file: ./Dockerfile.backend
	# push: true
	# tags: ${{ secrets.DOCKER_USERNAME }}/pearl-aqi-backend:latest

	# - name: Build and push frontend
	# uses: docker/build-push-action@v4
	# with:
	# context: .
	# file: ./Dockerfile.frontend
	# push: true
	# tags: ${{ secrets.DOCKER_USERNAME }}/pearl-aqi-frontend:latest

	# Deployment (optional - configure for your platform)
	# deploy:
	# runs-on: ubuntu-latest
	# needs: docker
	# if: github.event_name == 'push' && github.ref == 'refs/heads/main'

	# steps:
	# - name: Deploy to production
	# run: \|
	# echo "🚀 Deployment step - configure for your platform (AWS, Azure, GCP, etc.)"
	# # Add your deployment commands here

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Add required model and config files for deployment; update .gitignore… #22

Workflow file

Add required model and config files for deployment; update .gitignore… #22

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Workflow file for this run