first backup of charts

This commit is contained in:
Ivan087
2025-09-23 10:01:17 +08:00
commit cbfc0104a6
170 changed files with 17788 additions and 0 deletions

53
vllm/metadata.yaml Normal file
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application_name: &application_name vllm
distributed:
method: helm
release_name: *application_name
chart: vllm-app
sets:
app: vllm
model:
huggingfaceName: "Qwen/Qwen2.5-0.5B-Instruct"
resources:
gpuLimit: 1
cpuRequest: 8
memoryLimit: "16Gi"
shmSize: "15Gi"
workerSize: 2
nodeSelector: {}
svc:
svc_type: NodePort
protocol: http
hostname: 10.6.14.123
port: 30080
url: ~
paths:
docs_path: /docs
redoc_path: /redoc
pod:
name: infer-0
monolithic:
method: helm
release_name: *application_name
chart: vllm-app
sets:
app: vllm
model:
huggingfaceName: "Qwen/Qwen2.5-0.5B-Instruct"
resources:
gpuLimit: 1
cpuRequest: 8
memoryLimit: "16Gi"
shmSize: "15Gi"
workerSize: 1
nodeSelector: {}
svc:
svc_type: NodePort
protocol: http
hostname: 10.6.14.123
port: 30080
url: ~
pod:
name: vllm

23
vllm/vllm-app/.helmignore Normal file
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# Patterns to ignore when building packages.
# This supports shell glob matching, relative path matching, and
# negation (prefixed with !). Only one pattern per line.
.DS_Store
# Common VCS dirs
.git/
.gitignore
.bzr/
.bzrignore
.hg/
.hgignore
.svn/
# Common backup files
*.swp
*.bak
*.tmp
*.orig
*~
# Various IDEs
.project
.idea/
*.tmproj
.vscode/

25
vllm/vllm-app/Chart.yaml Normal file
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apiVersion: v2
name: vllm-app
description: A Helm chart for deploying vLLM with NFS storage
annotations:
"helm.sh/resource-policy": keep # 防止资源被意外删除
# A chart can be either an 'application' or a 'library' chart.
#
# Application charts are a collection of templates that can be packaged into versioned archives
# to be deployed.
#
# Library charts provide useful utilities or functions for the chart developer. They're included as
# a dependency of application charts to inject those utilities and functions into the rendering
# pipeline. Library charts do not define any templates and therefore cannot be deployed.
type: application
# This is the chart version. This version number should be incremented each time you make changes
# to the chart and its templates, including the app version.
# Versions are expected to follow Semantic Versioning (https://semver.org/)
version: 0.1.0
# This is the version number of the application being deployed. This version number should be
# incremented each time you make changes to the application. Versions are not expected to
# follow Semantic Versioning. They should reflect the version the application is using.
# It is recommended to use it with quotes.
appVersion: "1.16.0"

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{{- if and (gt (int .Values.workerSize) 1) (eq .Values.app "llama") }}
apiVersion: leaderworkerset.x-k8s.io/v1
kind: LeaderWorkerSet
metadata:
name: infer
spec:
replicas: {{ .Values.replicaCount }}
leaderWorkerTemplate:
size: {{ .Values.workerSize }}
restartPolicy: RecreateGroupOnPodRestart
leaderTemplate:
metadata:
labels:
role: leader
spec:
initContainers:
# 模型下载作为第一个 initContainer
- name: download-model
image: {{ .Values.model.download.image }}
imagePullPolicy: IfNotPresent
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
MODEL_NAME=$(basename "{{ .Values.model.huggingfaceName }}")
DEST_DIR="{{ .Values.model.localMountPath }}/$MODEL_NAME"
# DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
# 检查模型是否存在,不存在则下载
echo "DEST_DIR= $DEST_DIR"
ls $DEST_DIR
ls -l {{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}
if [ ! -f "$DEST_DIR/config.json" ]; then
ls -l {{ .Values.model.localMountPath }}
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
else
echo "Model already exists at $DEST_DIR"
fi
volumeMounts:
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
containers:
- name: llama-leader
image: {{ .Values.llama.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
- name : USE_RAY
value: "1"
# - name : LMDEPLOY_EXECUTOR_BACKEND
# value: "ray"
command:
- sh
- -c
- "bash {{ .Values.model.localMountPath }}/multi-node-serving.sh leader --ray_cluster_size=$(LWS_GROUP_SIZE);
MODEL_NAME=$(basename '{{ .Values.model.huggingfaceName }}'); MODEL_NAME_OR_PATH='{{ .Values.model.localMountPath }}/'$MODEL_NAME;
llamafactory-cli webchat {{ .Values.model.localMountPath }}/lws-config/qwen2_5_3B.yaml "
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
ports:
- containerPort: 7860
name: http
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Values.app }}-pvc-model
workerTemplate:
spec:
containers:
- name: llama-worker
image: {{ .Values.llama.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
command:
- sh
- -c
- "echo $(LWS_LEADER_ADDRESS);
bash {{ .Values.model.localMountPath }}/multi-node-serving.sh worker --ray_address=$(LWS_LEADER_ADDRESS)"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
# - name : LMDEPLOY_EXECUTOR_BACKEND
# value: "ray"
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Values.app }}-pvc-model
{{- end }}

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{{- if and (gt (int .Values.workerSize) 1) (eq .Values.app "lmdeploy") }}
apiVersion: leaderworkerset.x-k8s.io/v1
kind: LeaderWorkerSet
metadata:
name: infer
spec:
replicas: {{ .Values.replicaCount }}
leaderWorkerTemplate:
size: {{ .Values.workerSize }}
restartPolicy: RecreateGroupOnPodRestart
leaderTemplate:
metadata:
labels:
role: leader
spec:
initContainers:
# 模型下载作为第一个 initContainer
- name: download-model
image: {{ .Values.model.download.image }}
imagePullPolicy: IfNotPresent
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
MODEL_NAME=$(basename "{{ .Values.model.huggingfaceName }}")
DEST_DIR="{{ .Values.model.localMountPath }}/$MODEL_NAME"
# DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
# 检查模型是否存在,不存在则下载
echo "DEST_DIR= $DEST_DIR"
ls $DEST_DIR
ls -l {{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}
if [ ! -f "$DEST_DIR/config.json" ]; then
ls -l {{ .Values.model.localMountPath }}
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
else
echo "Model already exists at $DEST_DIR"
fi
volumeMounts:
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
containers:
- name: lmdeploy-leader
image: {{ .Values.lmdeploy.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
- name : LMDEPLOY_EXECUTOR_BACKEND
value: "ray"
command:
- sh
- -c
- "bash {{ .Values.model.localMountPath }}/multi-node-serving.sh leader --ray_cluster_size=$(LWS_GROUP_SIZE);
MODEL_NAME=$(basename '{{ .Values.model.huggingfaceName }}'); MODEL_PATH='{{ .Values.model.localMountPath }}/'$MODEL_NAME;
lmdeploy serve api_server $MODEL_PATH --backend pytorch --tp $(({{ .Values.resources.gpuLimit }} * {{ .Values.workerSize }})) --server-port 8080 --cache-max-entry-count 0.9"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
ports:
- containerPort: 8080
name: http
readinessProbe:
tcpSocket:
#httpGet:
#path: /health
port: 8080
initialDelaySeconds: 120
periodSeconds: 20
timeoutSeconds: 5
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: nfs-pvc-model
workerTemplate:
spec:
containers:
- name: lmdeploy-worker
image: {{ .Values.lmdeploy.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
command:
- sh
- -c
- "bash {{ .Values.model.localMountPath }}/multi-node-serving.sh worker --ray_address=$(LWS_LEADER_ADDRESS)"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.lmdeploy.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
- name : LMDEPLOY_EXECUTOR_BACKEND
value: "ray"
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: nfs-pvc-model
{{- end }}

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{{- if and (gt (int .Values.workerSize) 1) (eq .Values.app "vllm") }}
apiVersion: leaderworkerset.x-k8s.io/v1
kind: LeaderWorkerSet
metadata:
name: infer
spec:
replicas: {{ .Values.replicaCount }}
leaderWorkerTemplate:
size: {{ .Values.workerSize }}
restartPolicy: RecreateGroupOnPodRestart
leaderTemplate:
metadata:
labels:
role: leader
spec:
initContainers:
# 模型下载作为第一个 initContainer
- name: download-model
image: {{ .Values.model.download.image }}
imagePullPolicy: IfNotPresent
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
MODEL_NAME=$(basename "{{ .Values.model.huggingfaceName }}")
DEST_DIR="{{ .Values.model.localMountPath }}/$MODEL_NAME"
# DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
# 检查模型是否存在,不存在则下载
echo "DEST_DIR= $DEST_DIR"
ls $DEST_DIR
ls -l {{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}
if [ ! -f "$DEST_DIR/config.json" ]; then
ls -l {{ .Values.model.localMountPath }}
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
else
echo "Model already exists at $DEST_DIR"
fi
volumeMounts:
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
containers:
- name: vllm-leader
image: {{ .Values.vllm.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
command:
- sh
- -c
- "bash /vllm-workspace/examples/online_serving/multi-node-serving.sh leader --ray_cluster_size=$(LWS_GROUP_SIZE);
MODEL_NAME=$(basename '{{ .Values.model.huggingfaceName }}'); MODEL_PATH='{{ .Values.model.localMountPath }}/'$MODEL_NAME;
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model $MODEL_PATH --tensor-parallel-size {{ .Values.resources.gpuLimit }} --pipeline_parallel_size {{ .Values.workerSize }} --trust_remote_code"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
ports:
- containerPort: 8080
name: http
readinessProbe:
tcpSocket:
#httpGet:
#path: /health
port: 8080
initialDelaySeconds: 120
periodSeconds: 20
timeoutSeconds: 5
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Values.app }}-pvc-model
workerTemplate:
spec:
containers:
- name: vllm-worker
image: {{ .Values.vllm.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
command:
- sh
- -c
- "bash /vllm-workspace/examples/online_serving/multi-node-serving.sh worker --ray_address=$(LWS_LEADER_ADDRESS)"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Values.app }}-pvc-model
{{- end }}

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{{- if .Values.model.download.enabled }}
apiVersion: batch/v1
kind: Job
metadata:
name: {{ .Release.Name }}-download-model
annotations:
"helm.sh/hook": pre-install,pre-upgrade # 在安装/升级前执行
"helm.sh/hook-weight": "-10" # 优先执行
"helm.sh/hook-delete-policy": hook-succeeded
spec:
template:
spec:
restartPolicy: OnFailure
containers:
- name: downloader
image: {{ .Values.model.download.image }}
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
if [ -d "$DEST_DIR" ]; then
echo "Model already exists at $DEST_DIR"
else
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
fi
volumeMounts:
- name: model-storage
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: model-storage
persistentVolumeClaim:
claimName: nfs-pvc-model # 复用之前的 PVC
{{- end }}

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apiVersion: v1
kind: PersistentVolume
metadata:
name: {{ .Values.app }}-pv-model
spec:
storageClassName: {{ .Values.nfs.storageClass | default "local-path" }}
capacity:
storage: {{ .Values.nfs.pvSize }}
accessModes:
- ReadWriteMany
persistentVolumeReclaimPolicy: Retain
nfs:
path: {{ .Values.nfs.path }}
server: {{ .Values.nfs.server }}

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apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: {{ .Values.app }}-pvc-model
annotations:
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: {{ .Values.nfs.pvcSize }}
volumeName: {{ .Values.app }}-pv-model

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#apiVersion: v1
#kind: Service
#metadata:
# name: infer-leader-loadbalancer
#spec:
# type: LoadBalancer
# selector:
# leaderworkerset.sigs.k8s.io/name: infer
# role: leader
# ports:
# - protocol: TCP
# port: 8080
# targetPort: 8080
#
---
apiVersion: v1
kind: Service
metadata:
name: {{ .Values.app }}-leader-nodeport
spec:
type: NodePort
{{- if gt (int .Values.workerSize) 1 }}
selector:
leaderworkerset.sigs.k8s.io/name: infer
role: leader
{{- else }}
selector:
app: vllm-app
{{- end }}
ports:
- protocol: TCP
port: 8080
{{- if eq .Values.app "llama" }}
targetPort: 7860
{{- else }}
targetPort: 8080
{{- end }}
nodePort: 30080

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{{- if eq (int .Values.workerSize) 1 }}
apiVersion: apps/v1
kind: Deployment
metadata:
name: vllm
spec:
replicas: {{ .Values.replicaCount }}
selector:
matchLabels:
app: vllm-app
template:
metadata:
labels:
app: vllm-app
spec:
initContainers:
# 模型下载作为第一个 initContainer
- name: download-model
image: {{ .Values.model.download.image }}
imagePullPolicy: IfNotPresent
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
MODEL_NAME=$(basename "{{ .Values.model.huggingfaceName }}")
DEST_DIR="{{ .Values.model.localMountPath }}/$MODEL_NAME"
# DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
# 检查模型是否存在,不存在则下载
echo "DEST_DIR= $DEST_DIR"
ls $DEST_DIR
ls -l {{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}
if [ ! -f "$DEST_DIR/config.json" ]; then
ls -l {{ .Values.model.localMountPath }}
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
else
echo "Model already exists at $DEST_DIR"
fi
volumeMounts:
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
containers:
- name: vllm-leader
image: {{ .Values.vllm.image }}
imagePullPolicy: IfNotPresent
#securityContext:
# capabilities:
# add: [ "IPC_LOCK" ]
env:
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.vllm.huggingfaceToken }}
#- name: GLOO_SOCKET_IFNAME
# value: eth0
#- name: NCCL_SOCKET_IFNAME
# value: eth0
#- name: NCCL_IB_DISABLE
# value: "0"
#- name: NCCL_DEBUG
# value: INFO
#- name: NCCL_IB_HCA
# value: mlx5_0:1
#- name: NCCL_IB_GID_INDEX
# value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
command:
- sh
- -c
- "MODEL_NAME=$(basename '{{ .Values.model.huggingfaceName }}'); MODEL_PATH='{{ .Values.model.localMountPath }}/'$MODEL_NAME;
echo 'Using single node ------------------------------------------';
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model $MODEL_PATH --tensor-parallel-size {{ .Values.resources.gpuLimit }} --pipeline_parallel_size {{ .Values.workerSize }} --trust_remote_code"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
#rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
ports:
- containerPort: 8080
name: http
readinessProbe:
#tcpSocket:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 120
periodSeconds: 20
timeoutSeconds: 5
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Values.app}}-pvc-model
{{- end }}

58
vllm/vllm-app/values.yaml Normal file
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# Default values for vllm-app.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.
# 模型配置
model:
huggingfaceName: "Qwen/Qwen2.5-0.5B-Instruct" # 用户只需输入这个
localMountPath: "/Model" # PVC 固定挂载路径
huggingfaceToken: "<your-hf-token>"
download:
enabled: false # 启用自动下载
image: "docker.io/vllm/vllm-openai:latest" # 包含 huggingface-cli 的镜像
# 功能选择
app: "vllm"
resources:
gpuLimit: 1
cpuRequest: 12
memoryLimit: "16Gi"
shmSize: "20Gi"
# vLLM 应用配置
vllm:
image: "docker.io/vllm/vllm-openai:latest"
#gpuLimit: 2
# cpuRequest: 12
# memoryLimit: "12Gi"
# shmSize: "15Gi"
llama:
image: "docker.io/library/one-click:v1"
# lmdeploy 应用配置
lmdeploy:
image: "docker.io/openmmlab/lmdeploy:latest-cu12"
# gpuLimit: 2
# cpuRequest: 12
# memoryLimit: "12Gi"
# shmSize: "15Gi"
# NFS PV/PVC 配置
nfs:
server: "10.6.80.11"
path: "/volume1/Dataset/PVStore/lab-data-model-pvc-c0beeab1-6dd5-4c6a-bd2c-6ce9e114c25e/Weight"
storageClass: "local-path"
pvSize: "500Gi"
pvcSize: "50Gi"
# LeaderWorkerSet 配置
replicaCount: 1
workerSize: 2
nodeSelector: {}
tolerations: []
affinity: {}

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# Patterns to ignore when building packages.
# This supports shell glob matching, relative path matching, and
# negation (prefixed with !). Only one pattern per line.
.DS_Store
# Common VCS dirs
.git/
.gitignore
.bzr/
.bzrignore
.hg/
.hgignore
.svn/
# Common backup files
*.swp
*.bak
*.tmp
*.orig
*~
# Various IDEs
.project
.idea/
*.tmproj
.vscode/

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apiVersion: v2
name: vllm-serve
description: A Helm chart for deploying vLLM with NFS storage
annotations:
"helm.sh/resource-policy": keep # 防止资源被意外删除
# A chart can be either an 'application' or a 'library' chart.
#
# Application charts are a collection of templates that can be packaged into versioned archives
# to be deployed.
#
# Library charts provide useful utilities or functions for the chart developer. They're included as
# a dependency of application charts to inject those utilities and functions into the rendering
# pipeline. Library charts do not define any templates and therefore cannot be deployed.
type: application
# This is the chart version. This version number should be incremented each time you make changes
# to the chart and its templates, including the app version.
# Versions are expected to follow Semantic Versioning (https://semver.org/)
version: 0.1.0
# This is the version number of the application being deployed. This version number should be
# incremented each time you make changes to the application. Versions are not expected to
# follow Semantic Versioning. They should reflect the version the application is using.
# It is recommended to use it with quotes.
appVersion: "1.16.0"

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1. Get the application URL by running these commands:
{{- if contains "NodePort" .Values.svc.type }}
export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "vllm-serve.fullname" . }})
export NODE_IP=$(kubectl get nodes --namespace {{ .Release.Namespace }} -o jsonpath="{.items[0].status.addresses[0].address}")
echo http://$NODE_IP:$NODE_PORT
{{- else if contains "LoadBalancer" .Values.service.type }}
NOTE: It may take a few minutes for the LoadBalancer IP to be available.
You can watch its status by running 'kubectl get --namespace {{ .Release.Namespace }} svc -w {{ include "vllm-serve.fullname" . }}'
export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "vllm-serve.fullname" . }} --template "{{"{{ range (index .status.loadBalancer.ingress 0) }}{{.}}{{ end }}"}}")
echo http://$SERVICE_IP:{{ .Values.service.port }}
{{- else if contains "ClusterIP" .Values.service.type }}
export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "app.kubernetes.io/name={{ include "vllm-serve.name" . }},app.kubernetes.io/instance={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}")
export CONTAINER_PORT=$(kubectl get pod --namespace {{ .Release.Namespace }} $POD_NAME -o jsonpath="{.spec.containers[0].ports[0].containerPort}")
echo "Visit http://127.0.0.1:8080 to use your application"
kubectl --namespace {{ .Release.Namespace }} port-forward $POD_NAME 8080:$CONTAINER_PORT
{{- end }}

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{{/*
Expand the name of the chart.
*/}}
{{- define "vllm-serve.name" -}}
{{- default .Chart.Name .Values.nameOverride | trunc 63 | trimSuffix "-" }}
{{- end }}
{{/*
Create a default fully qualified app name.
We truncate at 63 chars because some Kubernetes name fields are limited to this (by the DNS naming spec).
If release name contains chart name it will be used as a full name.
*/}}
{{- define "vllm-serve.fullname" -}}
{{- if .Values.fullnameOverride }}
{{- .Values.fullnameOverride | trunc 63 | trimSuffix "-" }}
{{- else }}
{{- $name := default .Chart.Name .Values.nameOverride }}
{{- if contains $name .Release.Name }}
{{- .Release.Name | trunc 63 | trimSuffix "-" }}
{{- else }}
{{- printf "%s-%s" .Release.Name $name | trunc 63 | trimSuffix "-" }}
{{- end }}
{{- end }}
{{- end }}
{{/*
Create chart name and version as used by the chart label.
*/}}
{{- define "vllm-serve.chart" -}}
{{- printf "%s-%s" .Chart.Name .Chart.Version | replace "+" "_" | trunc 63 | trimSuffix "-" }}
{{- end }}
{{/*
Common labels
*/}}
{{- define "vllm-serve.labels" -}}
helm.sh/chart: {{ include "vllm-serve.chart" . }}
{{ include "vllm-serve.selectorLabels" . }}
{{- if .Chart.AppVersion }}
app.kubernetes.io/version: {{ .Chart.AppVersion | quote }}
{{- end }}
app.kubernetes.io/managed-by: {{ .Release.Service }}
{{- end }}
{{/*
Selector labels
*/}}
{{- define "vllm-serve.selectorLabels" -}}
app.kubernetes.io/name: {{ include "vllm-serve.name" . }}
app.kubernetes.io/instance: {{ .Release.Name }}
{{- end }}
{{/*
Create the name of the service account to use
*/}}
{{- define "vllm-serve.serviceAccountName" -}}
{{- if .Values.serviceAccount.create }}
{{- default (include "vllm-serve.fullname" .) .Values.serviceAccount.name }}
{{- else }}
{{- default "default" .Values.serviceAccount.name }}
{{- end }}
{{- end }}

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{{- if gt (int .Values.workerSize) 1 }}
apiVersion: leaderworkerset.x-k8s.io/v1
kind: LeaderWorkerSet
metadata:
name: {{ .Release.Name }}
spec:
replicas: {{ .Values.replicaCount }}
leaderWorkerTemplate:
size: {{ .Values.workerSize }}
restartPolicy: RecreateGroupOnPodRestart
leaderTemplate:
metadata:
labels:
role: leader
spec:
initContainers:
# 模型下载作为第一个 initContainer
- name: download-model
image: {{ .Values.model.download.image }}
imagePullPolicy: {{ .Values.imagePullPolicy | default "IfNotPresent" }}
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
MODEL_NAME=$(basename "{{ .Values.model.huggingfaceName }}")
DEST_DIR="{{ .Values.model.localMountPath }}/$MODEL_NAME"
# DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
# 检查模型是否存在,不存在则下载
echo "DEST_DIR= $DEST_DIR"
if [ ! -f "$DEST_DIR/config.json" ]; then
ls -l {{ .Values.model.localMountPath }}
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
else
echo "Model already exists at $DEST_DIR"
fi
volumeMounts:
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
containers:
- name: vllm-leader
image: {{ .Values.vllm.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
command:
- sh
- -c
- "bash /vllm-workspace/examples/online_serving/multi-node-serving.sh leader --ray_cluster_size=$(LWS_GROUP_SIZE);
MODEL_NAME=$(basename '{{ .Values.model.huggingfaceName }}'); MODEL_PATH='{{ .Values.model.localMountPath }}/'$MODEL_NAME;
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model $MODEL_PATH --tensor-parallel-size {{ .Values.resources.gpuLimit }} --pipeline_parallel_size {{ .Values.workerSize }} --trust_remote_code"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
ports:
- containerPort: 8080
name: http
readinessProbe:
tcpSocket:
#httpGet:
#path: /health
port: 8080
initialDelaySeconds: 120
periodSeconds: 20
timeoutSeconds: 5
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Release.Name }}-pvc-model
{{- with .Values.nodeSelector }}
nodeSelector:
{{- toYaml . | nindent 10 }}
{{- end }}
{{- with .Values.affinity }}
affinity:
{{- toYaml . | nindent 10 }}
{{- end }}
{{- with .Values.tolerations }}
tolerations:
{{- toYaml . | nindent 10 }}
{{- end }}
workerTemplate:
spec:
containers:
- name: vllm-worker
image: {{ .Values.vllm.image }}
imagePullPolicy: IfNotPresent
securityContext:
capabilities:
add: [ "IPC_LOCK" ]
command:
- sh
- -c
- "bash /vllm-workspace/examples/online_serving/multi-node-serving.sh worker --ray_address=$(LWS_LEADER_ADDRESS)"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
rdma/rdma_shared_device_a: 10
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
env:
# - name: HUGGING_FACE_HUB_TOKEN
# value: {{ .Values.vllm.huggingfaceToken }}
- name: GLOO_SOCKET_IFNAME
value: eth0
- name: NCCL_SOCKET_IFNAME
value: eth0
- name: NCCL_IB_DISABLE
value: "0"
- name: NCCL_DEBUG
value: INFO
- name: NCCL_IB_HCA
value: mlx5_0:1
- name: NCCL_IB_GID_INDEX
value: "0" # 或 "7",根据你的网络配置而定
- name: RAY_DEDUP_LOGS
value: "0"
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Release.Name }}-pvc-model
{{- with .Values.nodeSelector }}
nodeSelector:
{{- toYaml . | nindent 10 }}
{{- end }}
{{- with .Values.affinity }}
affinity:
{{- toYaml . | nindent 10 }}
{{- end }}
{{- with .Values.tolerations }}
tolerations:
{{- toYaml . | nindent 10 }}
{{- end }}
{{- end }}

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apiVersion: v1
kind: PersistentVolume
metadata:
name: {{ .Release.Name }}-pv-model
spec:
storageClassName: {{ .Values.nfs.storageClass | default "local-path" }}
capacity:
storage: {{ .Values.nfs.pvSize }}
accessModes:
- ReadWriteMany
persistentVolumeReclaimPolicy: Retain
nfs:
path: {{ .Values.nfs.path }}
server: {{ .Values.nfs.server }}
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: {{ .Release.Name }}-pvc-model
annotations:
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: {{ .Values.nfs.pvcSize }}
volumeName: {{ .Release.Name }}-pv-model

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#apiVersion: v1
#kind: Service
#metadata:
# name: infer-leader-loadbalancer
#spec:
# type: LoadBalancer
# selector:
# leaderworkerset.sigs.k8s.io/name: infer
# role: leader
# ports:
# - protocol: TCP
# port: 8080
# targetPort: 8080
#
---
apiVersion: v1
kind: Service
metadata:
name: {{ .Release.Name }}-svc
spec:
type: {{ .Values.svc.type | default "NodePort" }}
{{- if gt (int .Values.workerSize) 1 }}
selector:
leaderworkerset.sigs.k8s.io/name: {{ .Release.Name }}
role: leader
{{- else }}
selector:
app: {{ .Release.Name }}
{{- end }}
ports:
- protocol: TCP
port: {{ .Values.svc.port | default 8080 }}
targetPort: {{ .Values.svc.port | default 8080 }}
nodePort: {{ .Values.svc.nodePort | default 30080 }}

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{{- if eq (int .Values.workerSize) 1 }}
apiVersion: apps/v1
kind: Deployment
metadata:
name: {{ .Release.Name }}
spec:
replicas: {{ .Values.replicaCount }}
selector:
matchLabels:
app: {{ .Release.Name }}
template:
metadata:
labels:
app: {{ .Release.Name }}
spec:
initContainers:
# 模型下载作为第一个 initContainer
- name: download-model
image: {{ .Values.model.download.image }}
imagePullPolicy: IfNotPresent
env:
- name: HF_ENDPOINT
value: https://hf-mirror.com
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.model.huggingfaceToken }}
command:
- sh
- -c
- |
MODEL_NAME=$(basename "{{ .Values.model.huggingfaceName }}")
DEST_DIR="{{ .Values.model.localMountPath }}/$MODEL_NAME"
# DEST_DIR="{{ .Values.model.localMountPath }}/{{ .Values.model.huggingfaceName }}"
# 检查模型是否存在,不存在则下载
echo "DEST_DIR= $DEST_DIR"
if [ ! -f "$DEST_DIR/config.json" ]; then
ls -l {{ .Values.model.localMountPath }}
echo "Downloading model {{ .Values.model.huggingfaceName }} to $DEST_DIR"
wget https://hf-mirror.com/hfd/hfd.sh
chmod a+x hfd.sh
apt install aria2 -y
./hfd.sh {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
# huggingface-cli download {{ .Values.model.huggingfaceName }} --local-dir "$DEST_DIR"
else
echo "Model already exists at $DEST_DIR"
fi
volumeMounts:
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
containers:
- name: vllm-pod
image: {{ .Values.vllm.image }}
imagePullPolicy: IfNotPresent
env:
- name: HUGGING_FACE_HUB_TOKEN
value: {{ .Values.vllm.huggingfaceToken }}
- name: RAY_DEDUP_LOGS
value: "0"
command:
- sh
- -c
- "MODEL_NAME=$(basename '{{ .Values.model.huggingfaceName }}'); MODEL_PATH='{{ .Values.model.localMountPath }}/'$MODEL_NAME;
echo 'Using single node ------------------------------------------';
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model $MODEL_PATH --tensor-parallel-size {{ .Values.resources.gpuLimit }} --pipeline_parallel_size {{ .Values.workerSize }} --trust_remote_code"
resources:
limits:
nvidia.com/gpu: "{{ .Values.resources.gpuLimit }}"
memory: {{ .Values.resources.memoryLimit }}
ephemeral-storage: 10Gi
requests:
ephemeral-storage: 10Gi
cpu: {{ .Values.resources.cpuRequest }}
ports:
- containerPort: 8080
name: http
readinessProbe:
#tcpSocket:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 120
periodSeconds: 20
timeoutSeconds: 5
volumeMounts:
- mountPath: /dev/shm
name: dshm
- name: weight-volume
mountPath: {{ .Values.model.localMountPath }}
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: {{ .Values.resources.shmSize }}
- name: weight-volume
persistentVolumeClaim:
claimName: {{ .Release.Name }}-pvc-model
{{- with .Values.nodeSelector }}
nodeSelector:
{{- toYaml . | nindent 8 }}
{{- end }}
{{- with .Values.affinity }}
affinity:
{{- toYaml . | nindent 8 }}
{{- end }}
{{- with .Values.tolerations }}
tolerations:
{{- toYaml . | nindent 8 }}
{{- end }}
{{- end }}

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# Default values for vllm-app.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.
# This is for the secrets for pulling an image from a private repository more information can be found here: https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/
imagePullSecrets: []
imagePullPolicy: IfNotPresent
# This is to override the chart name.
nameOverride: ""
fullnameOverride: ""
# This section builds out the service account more information can be found here: https://kubernetes.io/docs/concepts/security/service-accounts/
serviceAccount:
# Specifies whether a service account should be created
create: true
# Automatically mount a ServiceAccount's API credentials?
automount: true
# Annotations to add to the service account
annotations: {}
# The name of the service account to use.
# If not set and create is true, a name is generated using the fullname template
name: ""
# 模型配置
model:
huggingfaceName: "Qwen/Qwen2.5-0.5B-Instruct" # 用户只需输入这个
localMountPath: "/Model" # PVC 固定挂载路径
huggingfaceToken: "<your-hf-token>"
download: # 启用自动下载
image: "docker.io/vllm/vllm-openai:latest" # 包含 huggingface-cli 的镜像
# 功能选择
resources:
gpuLimit: 1
cpuRequest: 12
memoryLimit: "16Gi"
shmSize: "20Gi"
svc:
type: NodePort
port: 80
targetPort: 8080
nodePort: 30080
# vLLM 应用配置
vllm:
image: "docker.io/vllm/vllm-openai:latest"
llama:
image: "docker.io/library/one-click:v1"
# lmdeploy 应用配置
lmdeploy:
image: "docker.io/openmmlab/lmdeploy:latest-cu12"
# NFS PV/PVC 配置
nfs:
server: "10.6.80.11"
path: "/volume1/Dataset/PVStore/lab-data-model-pvc-c0beeab1-6dd5-4c6a-bd2c-6ce9e114c25e/Weight"
storageClass: "local-path"
pvSize: "500Gi"
pvcSize: "50Gi"
# LeaderWorkerSet 配置
replicaCount: 1
workerSize: 2
nodeSelector: {}
tolerations: []
affinity: {}