generated file: `celery/tasks.py` #10

	name: Deploy to Production

	on:
	push:
	branches:
	- main

	jobs:
	deploy:
	runs-on: ubuntu-latest
	steps:
	- uses: actions/checkout@v2
	- name: Build Docker Image
	uses: docker/build-push-action@v2
	with:
	context: .
	push: true
	tags: ai-request-handler:latest
	# Optional: Add Docker Hub credentials if needed
	# dockerhub/username: ${DOCKER_HUB_USERNAME}
	# dockerhub/password: ${DOCKER_HUB_PASSWORD}
	- name: Deploy to Kubernetes
	uses: kubernetes/kubectl-action@v1
	with:
	# Specify your Kubernetes configuration (e.g., kubeconfig file)
	# kubeconfig: ${{ secrets.KUBECONFIG }}
	# If you're using a cluster from a different provider, use appropriate secrets.
	# For example, for AWS EKS, use:
	# kubeconfig: ${{ secrets.AWS_EKS_KUBECONFIG }}
	command: apply
	# Specify the deployment YAML file
	# This file should define your deployment in a way compatible with your Kubernetes cluster
	# It should be named 'deployment.yaml' and placed in the root of your repository
	# Update this if you use a different deployment file or folder:
	path: deployment.yaml
	# Add labels for versioning, environment, etc. as needed
	# Example:
	# labels: \|
	# version: ${{ secrets.CI_COMMIT_TAG }}
	# environment: production
	- name: Wait for deployment
	run: \|
	# Optional: Implement a wait command to verify successful deployment
	# This might involve waiting for a specific pod status, or other verification steps
	# Example:
	# kubectl wait --for=condition=Available deployment/ai-request-handler
	echo "Deployment complete."

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