gcloud-lab/apps/base/customer1/openclaw/vllm-gemma.yaml

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apiVersion: apps/v1
kind: Deployment
metadata:
name: openclaw-brain-vllm
namespace: customer1
labels:
app: openclaw-brain
spec:
replicas: 1
selector:
matchLabels:
app: openclaw-brain
template:
metadata:
labels:
app: openclaw-brain
spec:
nodeSelector:
cloud.google.com/gke-accelerator: "nvidia-a100-80gb"
tolerations:
- key: "nvidia.com/gpu-a100-80gb"
operator: "Equal"
value: "present"
effect: "NoSchedule"
containers:
- name: vllm-brain
image: vllm/vllm-openai:latest
command: ["python3", "-m", "vllm.entrypoints.openai.api_server"]
env:
- name: HF_TOKEN
value: ""
- name: VLLM_TOKENIZER_MODE
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value: "auto"
args:
- "--model"
- "Jiunsong/supergemma4-26b-abliterated-multimodal" # Uncensored Abliterated Gemma 26B (Native)
- "--dtype"
- "bfloat16"
- "--max-model-len"
- "8192"
- "--trust-remote-code"
- "--gpu-memory-utilization"
- "0.95"
ports:
- containerPort: 8000
resources:
limits:
nvidia.com/gpu: 1
memory: "32Gi"
cpu: "8"
requests:
nvidia.com/gpu: 1
memory: "16Gi"
cpu: "4"
volumeMounts:
- name: model-cache
mountPath: /root/.cache/huggingface
volumes:
- name: model-cache
persistentVolumeClaim:
claimName: vllm-model-cache-pvc
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: vllm-model-cache-pvc
namespace: customer1
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
---
apiVersion: v1
kind: Service
metadata:
name: openclaw-brain-service
namespace: customer1
spec:
selector:
app: openclaw-brain
ports:
- protocol: TCP
port: 8000
targetPort: 8000
type: ClusterIP