gcloud-lab/apps/base/customer1/openclaw/vllm-l4.yaml

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apiVersion: apps/v1
kind: Deployment
metadata:
name: openclaw-brain-vllm-l4
namespace: customer1
labels:
app: openclaw-brain-l4
spec:
replicas: 1
selector:
matchLabels:
app: openclaw-brain-l4
template:
metadata:
labels:
app: openclaw-brain-l4
spec:
nodeSelector:
workload: "llm-analyst"
tolerations:
- key: "nvidia.com/gpu"
operator: "Equal"
value: "present"
effect: "NoSchedule"
containers:
- name: vllm-brain-l4
image: vllm/vllm-openai:v0.9.1
command: ["python3", "-m", "vllm.entrypoints.openai.api_server"]
env:
- name: HF_TOKEN
value: ""
args:
- --model=trohrbaugh/Qwen2.5-Coder-7B-Instruct-heretic
- --host=0.0.0.0
- --port=8000
- --tensor-parallel-size=1
- --gpu-memory-utilization=0.95
- --max-model-len=32768
- --enable-auto-tool-choice
- --trust-remote-code
- --dtype=auto
- --tool-call-parser=pythonic
- --enable-prefix-caching
ports:
- containerPort: 8000
resources:
limits:
nvidia.com/gpu: 1
memory: "24Gi"
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-l4
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: vllm-model-cache-pvc-l4
namespace: customer1
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 50Gi
---
apiVersion: v1
kind: Service
metadata:
name: openclaw-brain-service-l4
namespace: customer1
spec:
selector:
app: openclaw-brain-l4
ports:
- protocol: TCP
port: 8000
targetPort: 8000
type: ClusterIP