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:v0.19.1-ubuntu2404 command: ["python3", "-m", "vllm.entrypoints.openai.api_server"] env: - name: HF_TOKEN value: "" args: - --model=llmfan46/Qwen3.5-27B-uncensored-heretic - --host=0.0.0.0 - --port=8000 - --tensor-parallel-size=1 - --gpu-memory-utilization=0.95 - --kv-cache-dtype=fp8 - --max-model-len=49152 - --enable-auto-tool-choice - --trust-remote-code - --dtype=auto - --enable-prefix-caching - --tool-call-parser=hermes - --reasoning-parser=qwen3 - --disable-custom-all-reduce ports: - containerPort: 8000 resources: limits: nvidia.com/gpu: 1 memory: "80Gi" cpu: "16" requests: nvidia.com/gpu: 1 memory: "60Gi" cpu: "8" volumeMounts: - name: model-cache mountPath: /root/.cache/huggingface volumes: - name: model-cache persistentVolumeClaim: claimName: vllm-model-qwen3.5-27b-uncensored --- apiVersion: v1 kind: PersistentVolumeClaim metadata: name: vllm-model-qwen3.5-27b-uncensored 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