配置Hiddify的步骤如下

安装依赖

• 下载并安装Kubernetes和RabbitMQ的依赖。
• 使用apt-get安装Kubernetes和RabbitMQ相关包。

注册Kubernetes服务

• 打开Kubernetes CLI，输入kubernetes clusters -n training注册一个新的Kubernetes服务。
• 设置服务地址为kubernetes.example.com。
• 添加队列，例如training:public,并配置队列地址和名称。

配置RabbitMQ

• 在rabbitmq.yml中：

  cluster:
    name: training
    interface:
      name: RabbitMQInterface
    instance:
      name: rabbitmqInstance
      port: 53451
      storage:
        path: /var/lib/rabbitmq/rabbitmq
        output: /var/lib/rabbitmq/output
        error: /var/lib/rabbitmq/error
    storage:
      name: local
      storage.default: local
      prefix: /var/lib/rabbitmq/rabbitmq
    storage.format:
      default: /var/lib/rabbitmq/rabbitmq
  queue:
    name: training
    type: public
    tags:
      public
    tags:
      public
    labels:
      public
  name: rabbitmqInstance
  description: RabbitMQ中间层

• 在rabbitmq_config.yml中配置存储策略：

  cluster:
    name: rabbitmqInstance
  queue:
    name: training
    tags:
      public
    labels:
      public
  storage:
    name: local
    prefix: /var/lib/rabbitmq/rabbitmq
    strategy:
      read: "h5"
      write: "h5"
    metadata:
      lastWrittenAt: "223-1-1T12::Z"

配置Hiddify

• 添加Transform任务：

  task:
    name: trainTransform
    type: transform
    arguments:
      - training_data
      - model
      - train_config
    inputs:
      - training_data
      - model
      - train_config
    outputs:
      - training_data
    pipeline:
      select:
        columns
      filter:
        filter_by
          key: name
          value: 'id'
          value_type: string
      transform:
        filter:
          key: name
          value: 'id'
          when: geq
          value: 'int'
          transform: (row) => (row['int'] + '_int')
      pipeline:
        select:
          id
          int
          label
          ...
      pipeline:
        select:
          id
          int
          label
          ...
        filter:
          id > 0
        filter_by:
          key: id
          value: 0
        filter:
          key: label
          value: 'int'
        filter_by:
          key: label
          value: 'int'
        filter:
          key: id
          value: 0
    pre:
      read:
        file: training_data
        mode: text
        path: training_data
        columns:
          id
          int
          labels
          ...
    post:
      read:
        file: model
        mode: text
        path: model
        columns:
          name
          label
        write:
          file: training_data
          mode: text
          path: training_data
          columns:
            id
            int
            labels
            ...

配置中间层配置文件

• 添加rabbitmq_config.yml：

  cluster:
    name: rabbitmqInstance
  queue:
    name: training
    type: public
    tags:
      public
    labels:
      public
  storage:
    name: local
    prefix: /var/lib/rabbitmq/rabbitmq
    strategy:
      read: "h5"
      write: "h5"
    metadata:
      lastWrittenAt: "223-1-1T12::Z"

配置训练模型配置文件

• 添加train_model.yml：

  cluster:
    name: trainModel
    interface:
      name: trainModelInterface
    instance:
      name: trainModelInstance
      port: 53452
      storage:
        name: /var/lib/rabbitmq/rabbitmq
        prefix: /var/lib/rabbitmq/rabbitmq
      output:
        /var/lib/rabbitmq/output
      metadata:
        lastWrittenAt: "223-1-1T12::Z"
    queue:
      name: training
      type: public
      tags:
      public
      labels:
      public
  inputs:
    - rabbitmqInstance: name: rabbitmqInstance
    - train_config: name: train_config
  outputs:
    - rabbitmqInstance: name: rabbitmqInstance
  outputs:
    - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
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  - rabbitmqInstance: name: rabbitmqInstance
  - rabbitmqInstance: name: rabbitmqInstance
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  - rabbitmqInstance: name: rabbitmqInstance
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  - rabbitmqInstance: name: rabbitmqInstance
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  - rabbitmqInstance: name: rabbitmqInstance
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