Rasa X 安装之Docker Compose 模式

时间:2022-07-22
本文章向大家介绍Rasa X 安装之Docker Compose 模式，主要内容包括其使用实例、应用技巧、基本知识点总结和需要注意事项，具有一定的参考价值，需要的朋友可以参考一下。

本文 2351字，需要 5.88 分钟

Rasa X 介绍

Rasa X can be used in local mode and in server mode. Rasa X in local mode is helpful for sharing your assistant before you have a server set up. Once your assistant is up and running, you will want to deploy Rasa X to a server so that it’s available 24/7 and everyone on your team can use it to review conversations and annotate new training data.

如上文所说的「Local Mode」[1]模式更多的是方便我们本地测试，如果需要提供给外界服务，我们还需要其他模式，官网提供的三种：

1.Server Quick-Install

2.Helm Chart

3.Docker Compose

因为我个人服务器用的 Docker 比较多，所以看看「Docker Compose」模式：

Docker Compose

要求服务器环境前提安装 python3, docker、docker-compose。

主要四个步骤： 1. Download 2. Install 3. Start 4. Access

Download

因为 Rasa 的镜像主要放在 Docker Hub 上，所以在国内，有时候下载速度比较慢，虽然国内也提供了很多加速方法，但个人比较推荐使用使用 Google Cloud Platform 等第三方云服务器，通过云服务器和阿里云等国内服务器交互，把镜像托管回国内服务器，得到加速的目标。

具体大家可以搜索下使用方法。

本文主要下载的镜像包括：rasa/rasa-x，rasa/duckling，rasa/rasa，rasa/rasa-x-demo 等。

// 加速下载 rasa-x
docker pull rasa/rasa-x:0.31.0

docker tag docker.io/rasa/rasa-x:0.31.0 registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x:0.31.0

docker push registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x:0.31.0

// 本地下载
docker pull registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x:0.31.0

docker pull rasa/duckling:0.1.6.3

docker tag docker.io/rasa/duckling:0.1.6.3 registry.cn-hangzhou.aliyuncs.com/rasa/duckling:0.1.6.3

docker push registry.cn-hangzhou.aliyuncs.com/rasa/duckling:0.1.6.3

// 本地下载
docker pull registry.cn-hangzhou.aliyuncs.com/rasa/duckling:0.1.6.3

docker pull rasa/rasa:1.10.8-full

docker tag docker.io/rasa/rasa:1.10.8-full registry.cn-hangzhou.aliyuncs.com/rasa/rasa:1.10.8-full

docker push registry.cn-hangzhou.aliyuncs.com/rasa/rasa:1.10.8-full

// 本地下载
docker pull registry.cn-hangzhou.aliyuncs.com/rasa/rasa:1.10.8-full

docker pull rasa/nginx:0.31.0

docker tag docker.io/rasa/nginx:0.31.0 registry.cn-hangzhou.aliyuncs.com/rasa/nginx:0.31.0

docker push registry.cn-hangzhou.aliyuncs.com/rasa/nginx:0.31.0

// 本地下载
docker pull registry.cn-hangzhou.aliyuncs.com/rasa/nginx:0.31.0

docker pull rasa/rasa-x-demo:0.31.0

docker tag docker.io/rasa/rasa-x-demo:0.31.0 registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x-demo:0.31.0

docker push registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x-demo:0.31.0

// 本地下载
docker pull registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x-demo:0.31.0

具体参考：https://cr.console.aliyun.com/[2]

加速后，重新修改官网提供的配置文件：

version: "3.4"

x-database-credentials: &database-credentials
  DB_HOST: "db"
  DB_PORT: "5432"
  DB_USER: "${DB_USER:-admin}"
  DB_PASSWORD: "${DB_PASSWORD}"
  DB_LOGIN_DB: "${DB_LOGIN_DB:-rasa}"x-rabbitmq-credentials: &rabbitmq-credentials
  RABBITMQ_HOST: "rabbit"
  RABBITMQ_USERNAME: "user"
  RABBITMQ_PASSWORD: ${RABBITMQ_PASSWORD}x-redis-credentials: &redis-credentials
  REDIS_HOST: "redis"
  REDIS_PORT: "6379"
  REDIS_PASSWORD: ${REDIS_PASSWORD}
  REDIS_DB: "1"x-duckling-credentials: &duckling-credentials
  RASA_DUCKLING_HTTP_URL: "http://duckling:8000"x-rasax-credentials: &rasax-credentials
  RASA_X_HOST: "http://rasa-x:5002"
  RASA_X_USERNAME: ${RASA_X_USERNAME:-admin}
  RASA_X_PASSWORD: ${RASA_X_PASSWORD:-}
  RASA_X_TOKEN: ${RASA_X_TOKEN}
  JWT_SECRET: ${JWT_SECRET}
  RASA_USER_APP: "http://app:5055"
  RASA_PRODUCTION_HOST: "http://rasa-production:5005"
  RASA_WORKER_HOST: "http://rasa-worker:5005"
  RASA_TOKEN: ${RASA_TOKEN}x-rasa-credentials: &rasa-credentials
  <<: *rabbitmq-credentials
  <<: *rasax-credentials
  <<: *database-credentials
  <<: *redis-credentials
  <<: *duckling-credentials
  RASA_TOKEN: ${RASA_TOKEN}
  RASA_MODEL_PULL_INTERVAL: 10
  RABBITMQ_QUEUE: "rasa_production_events"x-rasa-services: &default-rasa-service
  restart: always
  image: "registry.cn-hangzhou.aliyuncs.com/rasa/rasa:${RASA_VERSION}-full"
  expose:
    - "5005"  command: >
    x
    --no-prompt
    --production
    --config-endpoint http://rasa-x:5002/api/config?token=${RASA_X_TOKEN}
    --port 5005
    --jwt-method HS256
    --jwt-secret ${JWT_SECRET}
    --auth-token '${RASA_TOKEN}'
    --cors "*"
  depends_on:
    - rasa-x    - rabbit    - redisservices:
  rasa-x:
    restart: always
    image: "registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x:${RASA_X_VERSION}"
    expose:
      - "5002"    volumes:
      - ./models:/app/models      - ./environments.yml:/app/environments.yml      - ./credentials.yml:/app/credentials.yml      - ./endpoints.yml:/app/endpoints.yml      - ./logs:/logs      - ./auth:/app/auth    environment:
      <<: *database-credentials
      <<: *rasa-credentials
      SELF_PORT: "5002"
      DB_DATABASE: "${DB_DATABASE:-rasa}"
      RASA_MODEL_DIR: "/app/models"
      PASSWORD_SALT: ${PASSWORD_SALT}
      RABBITMQ_QUEUE: "rasa_production_events"
      RASA_X_USER_ANALYTICS: "0"
      SANIC_RESPONSE_TIMEOUT: "3600"
    depends_on:
      - db
  rasa-production:
    <<: *default-rasa-service
    environment:
      <<: *rasa-credentials
      RASA_ENVIRONMENT: "production"
      DB_DATABASE: "tracker"
      RASA_MODEL_SERVER: "http://rasa-x:5002/api/projects/default/models/tags/production"

  rasa-worker:
    <<: *default-rasa-service
    environment:
      <<: *rasa-credentials
      RASA_ENVIRONMENT: "worker"
      DB_DATABASE: "worker_tracker"
      RASA_MODEL_SERVER: "http://rasa-x:5002/api/projects/default/models/tags/production"

  app:
    restart: always
    image: "registry.cn-hangzhou.aliyuncs.com/rasa/rasa-x-demo:${RASA_X_DEMO_VERSION}"
    expose:
      - "5055"    depends_on:
      - rasa-production
  db:
    restart: always
    image: "daocloud.io/library/postgres:11.7"
    expose:
      - "5432"    environment:
      POSTGRES_USER: "${DB_USER:-admin}"
      POSTGRES_PASSWORD: "${DB_PASSWORD}"
      POSTGRES_DB: "${DB_DATABASE:-rasa}"
    volumes:
      - ./db:/bitnami/postgresql
  rabbit:
    restart: always
    image: "daocloud.io/library/rabbitmq:3.8.3"
    environment:
      RABBITMQ_HOST: "rabbit"
      RABBITMQ_USERNAME: "user"
      RABBITMQ_PASSWORD: ${RABBITMQ_PASSWORD}
      RABBITMQ_DISK_FREE_LIMIT: "{mem_relative, 0.1}"
    expose:
      - "5672"
  duckling:
    restart: always
    image: "registry.cn-hangzhou.aliyuncs.com/rasa/duckling:0.1.6.3"
    expose:
      - "8000"    command: ["duckling-example-exe", "--no-access-log", "--no-error-log"]

  nginx:
    restart: always
    image: "registry.cn-hangzhou.aliyuncs.com/rasa/nginx:${RASA_X_VERSION}"
    ports:
      - "80:8080"      - "443:8443"    volumes:
      - ./certs:/opt/bitnami/certs      - ./terms:/opt/bitnami/nginx/conf/bitnami/terms    depends_on:
      - rasa-x      - rasa-production      - app
  redis:
    restart: always
    image: "daocloud.io/library/redis:5.0.8"
    environment:
      REDIS_PASSWORD: ${REDIS_PASSWORD}
    expose:
      - "6379"

start

编写完 docker-compose.yml 后就可以创建容器了：

docker-compose up -d

access

执行命令：

python rasa_x_commands.py create --update admin me <PASSWORD>

好了，利用新密码就可以进入 Rasa X 网页。

总结

其中配置项主要参考官网说的来，这里就不再赘述了。有了 docker 环境下的 Rasa X，接下来就可以进入我们的交互环节，结合一些使用场景 (如：微信公众号、Slack 等)，制作我们的 AI 互动助手 (如，给 Slack 发送指令，回复微信公众号粉丝问题等)。

参考

[1] 「Local Mode」 https://mp.weixin.qq.com/s/HpPxrG2Sr67Sz_nEJHH2PA

[2] https://cr.console.aliyun.com/ https://cr.console.aliyun.com/

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