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k8s部署deepseek基于cpu的部署

news 来源：原创 2025/5/25 20:39:27

基础资源
k8s环境一套
oracla linux 9.4的操作系统
一、配置ollama环境
1、配置nfs存储

 yum -y reinstall  nfs-utils-coreos-2.5.4-25.0.2.el9.x86_64.rpm

改配置文件

[root@k8s-master01 openui]# cat /etc/exports
/data/ollama *(rw,sync,no_root_squash)
/data/openui  *(rw,sync,no_root_squash)

2、配置ollama环境

kubectl apply -f

ollama.yml

```cpp
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: ollama
  namespace: ollama
spec:
  serviceName: "ollama"
  replicas: 1
  selector:
    matchLabels:
      app: ollama
  template:
    metadata:
      labels:
        app: ollama
    spec:
      nodeSelector:
        ollama: "study"
      containers:
        - name: ollama
          image: ollama/ollama:latest
          imagePullPolicy: IfNotPresent
          ports:
            - containerPort: 11434
          volumeMounts:
            - name: ollama-volume
              mountPath: /data/ollama/models
      volumes:
        - name: ollama-volume
          persistentVolumeClaim:
            claimName: ollama-pvc
---
apiVersion: v1
kind: Service
metadata:
  name: ollama
  namespace: ollama
  labels:
    app: ollama
spec:
  type: ClusterIP
  ports:
    - port: 11434
      protocol: TCP
      targetPort: 11434
  selector:
    app: ollama

打标签

kubectl label nodes k8s-master01 ollama=study

执行ollama环境

kubectl apply -f ollama.yml

我们需要下载对应的模型

[root@k8s-master01 openui]# kubectl get po -A
NAMESPACE     NAME                                     READY   STATUS    RESTARTS         AGE
kube-system   calico-kube-controllers-d4bfdcb9-vb5qn   1/1     Running   2 (4h16m ago)    5h29m
kube-system   calico-node-j7t7h                        1/1     Running   2 (4h16m ago)    5h29m
kube-system   coredns-6d8c4cb4d-th687                  1/1     Running   3 (4h15m ago)    25h
kube-system   coredns-6d8c4cb4d-wmrvs                  1/1     Running   3 (4h16m ago)    25h
kube-system   etcd-k8s-master01                        1/1     Running   9 (4h16m ago)    25h
kube-system   kube-apiserver-k8s-master01              1/1     Running   8 (4h16m ago)    25h
kube-system   kube-controller-manager-k8s-master01     1/1     Running   12 (3h14m ago)   25h
kube-system   kube-proxy-75z89                         1/1     Running   9 (4h16m ago)    25h
kube-system   kube-scheduler-k8s-master01              1/1     Running   10 (3h19m ago)   25h
ollama        ollama-0                                 1/1     Running   0                39m
ollama        webui-56668c9775-cdc2z                   1/1     Running   0                28m
[root@k8s-master01 openui]# kubectl exec -it ollama-0 -n ollama -- bash
root@webui-56668c9775-cdc2z:/app/backend# ^C

ollama run deepseek-r1:1.5b
#它会自动下载，如果下载失败，配置openui的时候，会找不到大模型

二、配置前端openui环境
1、先配置存储

apiVersion: v1
kind: PersistentVolume
metadata:
  name: openwebui-pv
spec:
  capacity:
    storage: 5Gi
  volumeMode: Filesystem
  accessModes:
    - ReadWriteOnce
  persistentVolumeReclaimPolicy: Delete
  storageClassName: nfs-slow-0
  nfs:
    path: /data/openai
    server: 192.168.17.200
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: openwebui-pvc
  namespace: ollama
spec:
  storageClassName: nfs-slow-0
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 5Gi

执行

kubectl apply -f pv-pvc.yml

2、配置openui的基础环境
openui的yml文件如下

[root@k8s-master01 openui]# cat b.yml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: webui
  namespace: ollama
spec:
  replicas: 1
  selector:
    matchLabels:
      app: webui
  template:
    metadata:
      labels:
        app: webui
    spec:
      containers:
        - name: webui
          image: registry.cn-hangzhou.aliyuncs.com/hujiaming/open-webui:v1
          env:
            - name: OLLAMA_BASE_URL
              value: http://192.168.17.200:30552  # 指定 Ollama 的基础 URL
            - name: HF_ENDPOINT
              value: https://hf-mirror.com  # 国内环境连接 Hugging Face 的镜像地址
            - name: OPENAI_API_KEY
              value: None  # OpenAI API 密钥，当前未设置
            - name: OPENAI_API_BASE_URL
              value: None  # OpenAI API 基础 URL，当前未设置
          tty: true  # 启用终端
          ports:
            - containerPort: 8080  # 容器暴露的端口
          resources:
            requests:
              cpu: "500m"  # 请求的 CPU 资源
              memory: "500Mi"  # 请求的内存资源
            limits:
              cpu: "1000m"  # CPU 资源限制
              memory: "1Gi"  # 内存资源限制
          volumeMounts:
            - name: webui-volume  # 卷名称
              mountPath: /app/backend/data  # 挂载路径
      volumes:
        - name: webui-volume  # 卷名称
          persistentVolumeClaim:
            claimName: openwebui-pvc  # 关联的持久卷声明
---
apiVersion: v1
kind: Service
metadata:
  name: webui
  namespace: ollama
  labels:
    app: webui
spec:
  type: ClusterIP
  ports:
    - port: 8080
      protocol: TCP
      targetPort: 8080
  selector:
    app: webui

所有的微服务如下

[root@k8s-master01 openui]# kubectl get svc -A
NAMESPACE     NAME         TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)                  AGE
default       kubernetes   ClusterIP   10.96.0.1       <none>        443/TCP                  25h
kube-system   kube-dns     ClusterIP   10.96.0.10      <none>        53/UDP,53/TCP,9153/TCP   25h
ollama        ollama       NodePort    10.99.38.148    <none>        11434:30552/TCP          73m
ollama        webui        NodePort    10.108.13.158   <none>        8080:31105/TCP           73m

调接口的指令如下:

[root@k8s-master01 100]# curl -X POST http://192.168.17.200:30552/api/generate -H "Content-Type: application/json" -d '{"model": "deepseek-r1:1.5b", "prompt": "Hello"}'
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.412035999Z","response":"\u003cthink\u003e","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.47755678Z","response":"\n\n","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.524080818Z","response":"\u003c/think\u003e","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.575878566Z","response":"\n\n","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.638769799Z","response":"Hello","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.743448173Z","response":"!","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.795222957Z","response":" How","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.854765104Z","response":" can","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.910070123Z","response":" I","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:58.975574233Z","response":" assist","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:59.021980221Z","response":" you","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:59.087839648Z","response":" today","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:59.141298986Z","response":"?","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:59.266115826Z","response":" 😊","done":false}
{"model":"deepseek-r1:1.5b","created_at":"2025-03-09T11:31:59.342682834Z","response":"","done":true,"done_reason":"stop","context":[151644,9707,151645,151648,271,151649,271,9707,0,2585,646,358,7789,498,3351,30,26525,232],"total_duration":1018481575,"load_duration":25836526,"prompt_eval_count":4,"prompt_eval_duration":58000000,"eval_count":16,"eval_duration":933000000}

整个k8s部署deepseek的大模型到此结束，这个主要是基于cpu来进行部署的，只可以用于测试，实际生产环境最好用GPU的显卡，加速查询速度

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