update sync folder name for minio

.github/workflows/lint-test.yaml

@@ -60,13 +60,11 @@ jobs:
 
       - name: Run chart-testing (install)
         run: |
-          helm template --create-namespace --namespace=ns-vllm test-vllm examples/chart-helm -f examples/chart-helm/values.yaml --set secrets.s3endpoint=http://minio:9000/ --set secrets.s3bucketname=testbucket --set secrets.s3accesskeyid=minioadmin --set secrets.s3accesskey=minioadmin --set image.env[0].name=VLLM_CPU_KVCACHE_SPACE --set resources.requests.cpu=1 --set resources.requests.memory=4Gi --set resources.limits.cpu=2 --set resources.limits.memory=5Gi --set-string image.env[0].value="1" --set-string extraInit.s3modelpath="opt-125m/" --set-string 'resources.limits.nvidia\.com/gpu=0' --set-string 'resources.requests.nvidia\.com/gpu=0' --set-string image.repository="adsai/vllm-cpu-env"
-          helm install --wait --wait-for-jobs --timeout 5m0s --debug --create-namespace --namespace=ns-vllm test-vllm examples/chart-helm -f examples/chart-helm/values.yaml --set secrets.s3endpoint=http://minio:9000/ --set secrets.s3bucketname=testbucket --set secrets.s3accesskeyid=minioadmin --set secrets.s3accesskey=minioadmin --set image.env[0].name=VLLM_CPU_KVCACHE_SPACE --set resources.requests.cpu=1 --set resources.requests.memory=4Gi --set resources.limits.cpu=2 --set resources.limits.memory=5Gi --set-string image.env[0].value="1" --set-string extraInit.s3modelpath="opt-125m/" --set-string 'resources.limits.nvidia\.com/gpu=0' --set-string 'resources.requests.nvidia\.com/gpu=0' --set-string image.repository="adsai/vllm-cpu-env" & (sleep 15; kubectl -n ns-vllm logs -f $(kubectl -n ns-vllm get pods -o=name | awk '/init/ {print $1;exit}'))
+          helm install --wait --wait-for-jobs --timeout 30s --debug --create-namespace --namespace=ns-vllm test-vllm examples/chart-helm -f examples/chart-helm/values.yaml --set secrets.s3endpoint=http://minio:9000 --set secrets.s3bucketname=testbucket --set secrets.s3accesskeyid=minioadmin --set secrets.s3accesskey=minioadmin --set image.env[0].name=VLLM_CPU_KVCACHE_SPACE --set resources.requests.cpu=1 --set resources.requests.memory=4Gi --set resources.limits.cpu=2 --set resources.limits.memory=5Gi --set-string image.env[0].value="1" --set-string extraInit.s3modelpath="opt-125m" --set-string 'resources.limits.nvidia\.com/gpu=0' --set-string 'resources.requests.nvidia\.com/gpu=0' --set-string image.repository="adsai/vllm-cpu-env"
     
       - name: curl test
         run: |
-          kubectl -n ns-vllm get svc
-          kubectl -n ns-vllm get pods
+          kubectl -n ns-vllm logs -f $(kubectl -n ns-vllm get pods -o=name | awk '/init/ {print $1;exit}'))
           kubectl port-forward svc/test-vllm-service 8001:80 -n ns-vllm 
           CODE=`curl --location http://localhost:8001/v1/completions \
                   --header "Content-Type: application/json" \