gcloud-lab/apps/base/customer1/openclaw/a100-vllm.yaml
2026-04-22 06:09:45 +00:00

93 lines
2.3 KiB
YAML

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:v0.18.0
command: ["python3", "-m", "vllm.entrypoints.openai.api_server"]
env:
- name: HF_TOKEN
value: ""
- name: TOKENIZER_MODE
value: "hf"
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