# login AKS
az cloud set --name AzureCloud   # Switch CLI to Azure cloud
# az login                              # Log in to Azure China account (browser or device code flow)
az account set -s 079d8bd8-b4cc-4892-9307-aa6dedf890e9 #! set subs
az aks get-credentials -g rg-aiflow-lab -n aks-aiflow-lab --overwrite-existing --file ~/.kube/config
####
kubectl config use-context aks-aiflow-lab
kubectl config current-context

docker build . -t agentic-rag:1.0.16
docker tag agentic-rag:1.0.16 acraiflowlab.azurecr.io/agentic-rag:1.0.16
docker push acraiflowlab.azurecr.io/agentic-rag:1.0.16

# kubectl create namespace knowledge-agent

kubectl delete configmap agentic-rag-config -n knowledge-agent
kubectl create configmap agentic-rag-config -n knowledge-agent --from-file=config.yaml

kubectl delete deployment agentic-rag -n knowledge-agent
# kubectl delete ingress agentic-retrieval-ingress -n knowledge-agent  # 注释掉，不要删除生产 Ingress
kubectl apply -f deploy/dev/k8s-manifest.yml -n knowledge-agent

# restart deployment
kubectl rollout restart deployment agentic-rag -n knowledge-agent

kubectl rollout status deployment/agentic-rag -n knowledge-agent
kubectl get deployment agentic-rag -o wide -n knowledge-agent
kubectl get pods -l app=agentic-rag -o wide -n knowledge-agent
# kubectl logs -f agentic-rag  -n knowledge-agent