Platform Installation Instructions

This document is for developers / sysadmins who want to install Rasa Platform on premise or on a private cloud.

Note

Rasa uses docker compose to manage the lifecycle of the containers. The installation script should be used to provision a new server. If you want to run the application alongside other software on an existing server, you should consider installing docker compose manually.

Quickstart

1. copy the license file to the server. To get a license file, you need to buy a Rasa Platform subscription. If you don’t have one yet, please contact us.

$ scp rasa_platform.yml example.com:~/rasa_platform.yml
  1. Download and run the install script on the server:
$ curl -sSL -o install.sh https://storage.googleapis.com/rasa-releases/stable/install.sh
$ sudo bash ./install.sh

Replace stable with a specific version number if you want to install a specific version. You will be prompted to accept the terms and conditions. Type YES and hit return.

  1. Start the Platform
$ cd /etc/rasaplatform
$ sudo docker-compose up -d
  1. Create a Platform user you can use to log in
$ cd /etc/rasaplatform
$ sudo python rasa_commands.py create admin USER PASSWORD

replacing the USER and PASSWORD fields, for example python rasa_commands.py create admin admin PasswOrd.

Navigate to the hostname or IP where your server is reachable and log in via the interface. Once you are logged in you can start Setting Up Your Bot.

Detailed Setup

Rasa Platform is built as a collection of docker containers. Here we provide suggested hardware for running on a single server.

Hardware & OS Requirements

We recommend 8Gb RAM & 2-6 vCPUs for optimal performance. 4Gb RAM is the bare minimum. Your server should also have 100 Gb Disk space available. You will need a server running a modern Linux distribution that can run docker. The following OS’s work with the easy install script below:

  • Debian 7.7+
  • Ubuntu 14.04 / 15.10 / 16.04

For any other operating systems, please follow the manual installation instructions. As long as docker is available for your operating system, Rasa Platform should run fine.

The web interface aims to support browsers that meet the following criteria

  • > 0.2% market share
  • Not Internet Explorer
  • Not Opera Mini

Firewall

Make sure the following ports are open:

Port Service Description
443 HTTPS Web application over HTTPS access.
80 HTTP Web application access.
22 SSH SSH access.

If you install on Google Cloud this means:

  • make sure to check “Allow HTTP traffic” as well as “Allow HTTPS traffic” in the firewall settings of the VM instance.

Prepare the installation

Before you can install Rasa Platform, you need to have a license file. We will send you that file, it is named rasa_platform.yml. It contains licensing information as well as configuration parameters.

Make sure to upload the license file to the server, e.g. using

$ scp rasa_platform.yml HOSTNAME:~/rasa_platform.yml

where HOSTNAME is the hostname or ip of your server.

Install Docker Compose

Rasa uses docker compose to spin up a collection of docker containers that combined make up the Platform. You can either install a specific release, or use latest which corresponds to the most recent release (we recommend pinning a specific version though).

Download the install script and run it. Make sure the current directory contains the license file:

$ curl -sSL -o install.sh https://storage.googleapis.com/rasa-releases/stable/install.sh
$ sudo bash ./install.sh

The installation script will install docker compose and ansible. ansible is a popular tool for automation - it will download the docker compose setup as well as prepare the environment for docker to run in.

The Platform-related files will be installed into /etc/rasaplatform. This includes credentials to login to the docker registry under /etc/rasaplatform/gcr_auth.json.

Note

Although, this is the easiest way to get your server ready to run the Platform you can also follow the manual steps which will walk you through a few extra steps but will give you more control over the setup.

Accept the terms and conditions

To accept the terms and conditions, run echo "${USER} $(date)" > /etc/rasaplatform/terms/agree.txt. You can find the terms here.

Start the application

After you have successfully installed the Platform you can now start it:

$ cd /etc/rasaplatform
$ sudo docker-compose up -d

This will run the Platform in the background (due to -d) and the application will continue to run even if you log out of the server.

Create a User

To log in to the Platform, you need to create user accounts. At first, it is best to create at least one administrator account. To do so run:

$ cd /etc/rasaplatform
$ sudo python rasa_commands.py create admin USER PASSWORD

replacing the USER and PASSWORD fields, for example python rasa_commands.py create admin admin PasswOrd.

To create non-admin users, just replace admin with user:

$ sudo python rasa_commands.py create user USER PASSWORD

Note

The admin role has access to all API endpoints. The user role can only send messages and view their own conversation with the bot. For more information on account roles, head over to the docs on Platform Account Roles.

Test Your Login

Visit http://HOSTNAME in a web browser, and log in with the username & password entered in the previous command.

Installing Updates

To see which version you are currently running, hit the /version endpoint:

$ curl hostname/api/version

To install an update, fetch the install.sh for your version, and run it:

$ curl -sSL -o install.sh https://storage.googleapis.com/rasa-releases/VERSION/install.sh
$ sudo bash ./install.sh

replacing VERSION with the version you want to install.

After the installation is complete, login to the docker registry and pull the image:

$ cd /etc/rasaplatform
$ sudo docker login  -u _json_key -p "$(cat /etc/rasaplatform/gcr-auth.json)" https://gcr.io
$ sudo docker-compose pull

Make sure that the docker environment file is updated by running:

$ cat .env

Start the updated version of the platform:

$ sudo docker-compose up -d

Once the platform is up and running, you can login using your user credentials and test it.

Warning

Be aware, that during the update the following files will be overwritten:

  • /etc/rasaplatform/docker-compose.yml
  • /etc/rasaplatform/.env

Make sure there are no changes in these files that you still need. E.g. instead of directly modifying docker-compose.yml you should rather create a new file called docker-compose.override.yml. Docker will automatically take that file into account and override any attributes in docker-compose.yml with changes from the override file.

Next Steps

Now that you have the main pieces of the Platform installed, you can go ahead and Setting Up Your Bot.

Manual Installation

  1. Make sure python, docker, and docker compose are installed on your Platform. Detailed instructions can be found in the docker documentation. You should be able to run

    $ docker-compose --version
    
  2. Create the project directory and switch to it:

    $ mkdir /etc/rasaplatform
    $ cd /etc/rasaplatform
    
  3. Download the Platform files (docker-compose.yml and rasa_commands.py) that contain the containers and their setup (replacing latest with the version to install):

    $ wget -qO docker-compose.yml https://storage.googleapis.com/rasa-releases/stable/docker-compose.yml
    $ wget -qO rasa_commands.py https://storage.googleapis.com/rasa-releases/stable/rasa_commands.py
    
  4. Create the authentication file to download containers from the docker registry. To authenticated with the registry that contains the Platform containers, you need to create a file in /etc/rasaplatform/gcr-auth.json that contains the JSON of the field docker_registry_license from your license.

    Make sure to copy everything between the outer " of the docker_registry_license key to that file. The contents of /etc/rasaplatform/gcr-auth.json should look like this:

    {
      "type": "service_account",
      "project_id": "rasa-platform",
      "private_key_id": "sdferw234qadst423qafdgxhw",
      "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvfwrt423qwadsfghtzw0BAQEFAASCBKgwggSkAgEAAoIBAQCgt338FkWbW13dghtzew4easdf5wAi15jrA9t4uOk8dghrtze4weasfgdhtAFZNfrLgvr2\nPBTu1lAJDLo136ZGTdMKi+/TuRqrIMg/sr8q0Ungish8v6t5Jb4gsjBi9StytCT4\nhWXDL3qeadfsgeDOudl6c3iMzylBws+VffrFfaZWjDpGtxmlYwIUa2e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\nsjAsuAH4Iz1XdfdenzGnyBZH\n-----END PRIVATE KEY-----\n",
      "client_email": "company@rasa-platform.iam.gserviceaccount.com",
      "client_id": "114123456713428149",
      "auth_uri": "https://accounts.google.com/o/oauth2/auth",
      "token_uri": "https://accounts.google.com/o/oauth2/token",
      "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
      "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/company%40rasa-platform.iam.gserviceaccount.com"
    }
    
  5. Login to the docker registry

    $ sudo docker login  -u _json_key -p "$(cat /etc/rasaplatform/gcr-auth.json)" https://gcr.io
    
  6. Create the docker environment file in /etc/rasaplatform/.env with the following content:

    RASA_PLATFORM_VERSION=stable
    RASA_NLU_TOKEN=<random_string>
    RASA_CORE_TOKEN=<random_string>
    RASA_PLATFORM_TOKEN=<random_string>
    PASSWORD_SALT=<random_string>
    MONGO_PASSWORD=<random_string>
    JWT_SECRET=<random_string>
    RABBITMQ_PASSWORD=<random_string>
    

    For <random_string> please use secure strings, e.g. randomly generated character sequences.

    For the token and password salt fields, enter any string of your choice. These will be used to hash passwords. Note that if you change these you will have to create new logins for everyone.

    You will also need to set a Rasa NLU and Rasa Core Token. These are used to authorize the communication among the containers.

    Note

    Make sure to generate a different unique <random_string> for each field! E.g. running this multiple times:

    $ openssl rand -base64 12
    
  7. Create a credentials file at /etc/rasaplatform/credentials.yml containing:

    rasa:
       url: http://api:5002
    

    where url corresponds to your RASA_PLATFORM_HOST, if defined.

  8. Start up the Platform (-d will run the Platform in the background):

    $ sudo docker-compose up -d
    

Cluster Deployment (Kubernetes & Openshift)

  1. Make sure docker, and docker compose and kompose are installed on your server. Detailed instructions can be found in the Docker documentation and in the Kompose documentation. You should be able to run:

    $ docker-compose --version
    $ kompose version
    
  2. Create a project directory and switch to it:

    $ mkdir ~/rasaplatform
    $ cd ~/rasaplatform
    
  3. Download the docker-compose file (docker-compose.yml) that contain the containers and their setup (replacing latest with the version to install):

    $ wget -qO docker-compose.yml https://storage.googleapis.com/rasa-releases/stable/docker-compose.yml
    
  4. Create the authentication file to download containers from the docker registry. To be authenticated with the registry that contains the Platform containers, you need to create a file in ~/rasaplatform/gcr-auth.json that contains the JSON of the field docker_registry_license from your license.

    Make sure to copy everything between the outer " of the docker_registry_license key to that file. The contents of ~/rasaplatform/gcr-auth.json should look like this:

    {
      "type": "service_account",
      "project_id": "rasa-platform",
      "private_key_id": "sdferw234qadst423qafdgxhw",
      "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvfwrt423qwadsfghtzw0BAQEFAASCBKgwggSkAgEAAoIBAQCgt338FkWbW13dghtzew4easdf5wAi15jrA9t4uOk8dghrtze4weasfgdhtAFZNfrLgvr2\nPBTu1lAJDLo136ZGTdMKi+/TuRqrIMg/sr8q0Ungish8v6t5Jb4gsjBi9StytCT4\nhWXDL3qeadfsgeDOudl6c3iMzylBws+VffrFfaZWjDpGtxmlYwIUa2e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\nsjAsuAH4Iz1XdfdenzGnyBZH\n-----END PRIVATE KEY-----\n",
      "client_email": "company@rasa-platform.iam.gserviceaccount.com",
      "client_id": "114123456713428149",
      "auth_uri": "https://accounts.google.com/o/oauth2/auth",
      "token_uri": "https://accounts.google.com/o/oauth2/token",
      "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
      "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/company%40rasa-platform.iam.gserviceaccount.com"
    }
    
  5. Login to the docker registry. This will create a new entry in the docker config file.

    $ sudo docker login  -u _json_key -p "$(cat ~/rasaplatform/gcr-auth.json)" https://gcr.io
    
  6. Create a new image pull secret. If you already have a .dockercfg file for the registry, you can create a secret from that file by running (if you are using Kubernetes replace oc with kubectl):

    $ oc create secret generic <pull_secret_name> \
    --from-file=.dockercfg=<path/to/.dockercfg> \
    --type=kubernetes.io/dockercfg
    

    Add the secret to your service account. The name of the service account in this example should match the name of the service account the pod uses; default is the default service account (if you are using Kubernetes replace oc with kubectl):

    $ oc secrets link default <pull_secret_name> --for=pull
    

    For more information please visit the OpenShift documentation.

  7. Create the docker environment file .env with the following content:

    RASA_PLATFORM_VERSION=stable
    RASA_NLU_TOKEN=<random_string>
    RASA_CORE_TOKEN=<random_string>
    RASA_PLATFORM_TOKEN=<random_string>
    PASSWORD_SALT=<random_string>
    MONGO_PASSWORD=<random_string>
    JWT_SECRET=<random_string>
    RABBITMQ_PASSWORD=<random_string>
    

    For <random_string> please use secure strings, e.g. randomly generated character sequences.

    For the token and password salt fields, enter any string of your choice. These will be used to hash passwords. Note that if you change the password salt you will have to create new logins for everyone.

    You will also need to set a Rasa NLU and Rasa Core token. These are used to authorize the communication among the containers.

    Note

    Make sure to generate a different unique <random_string> for each field! E.g. running this multiple times:

    $ openssl rand -base64 12
    
  8. Create certificate files which are required by NGINX to establish HTTPS connections.

    $ openssl dhparam -out dh.pem $DH_SIZE 4096
    $ openssl req -x509 -newkey rsa:4086 \
         -subj "/C=XX/ST=XXXX/L=XXXX/O=XXXX/CN=localhost" \
         -keyout "privkey.pem" \
         -out "fullchain.pem" \
         -days 3650 -nodes -sha256
    

    Once the files are created, create a secret called nginx-certs. The secret will have three entries:

    • dh: copy here the content of the dh.pem file.
    • fullchain: copy here the content of the fullchain.pem file.
    • privkey: copy here the content of the privkey.pem file.

    This secret will be later mounted by the nginx pod.

  9. Create a file called agreement.yml with the following content to accept the terms and conditions.

    apiVersion: v1
    data:
        agree: openshift
    kind: ConfigMap
    metadata:
        name: agreement
    
  10. Create a file called configuration-files.yml with the following content:

    apiVersion: v1
    data:
        core-credentials: |
            rasa:
                url: http://api:5002
        core-endpoints: |
            models:
                url: ${RASA_CORE_MODEL_SERVER}
                token: ${RASA_PLATFORM_TOKEN}
                wait_time_between_pulls: ${RASA_CORE_MODEL_PULL_INTERVAL}
            nlu:
                url: ${RASA_NLU_HOST}
                token: ${RASA_NLU_TOKEN}
            nlg:
                url: ${RASA_NLG_ENDPOINT_URL}
                token: ${RASA_PLATFORM_TOKEN}
            tracker_store:
                store_type: mongod
                url: ${MONGO_HOST}
                username: ${MONGO_USERNAME}
                password: ${MONGO_PASSWORD}
                db: ${MONGO_DB}
            event_broker:
                url: ${RABBITMQ_HOST}
                username: ${RABBITMQ_USERNAME}
                password: ${RABBITMQ_PASSWORD}
            action_endpoint:
                url: ${RASA_USER_APP}/webhook
                token:  ""
        nlu-endpoints: |
            model:
                url: ${RASA_NLU_MODEL_SERVER}
                token: ${RASA_PLATFORM_TOKEN}
        environments: |
            core:
                production:
                  url: http://core:5005
                  token: ${RASA_CORE_TOKEN}
                  db: nlu-backend
                development:
                  url: http://core-development:5005
                  token: ${RASA_CORE_TOKEN}
                  db: core-development
                worker:
                  url: http://core-worker:5005
                  token: ${RASA_CORE_TOKEN}
                  db: core-development
            nlu:
                production:
                  url: http://nlu:5000
                  token: ${RASA_NLU_TOKEN}
                development:
                  url: http://nlu-development:5000
                  token: ${RASA_NLU_TOKEN}
                worker:
                  url: http://nlu-worker:5000
                  token: ${RASA_NLU_TOKEN}
    kind: ConfigMap
    metadata:
        name: configuration-files
    
  11. Generate the deployment files by running

    $ docker-compose config > docker-compose.config.yml
    
  12. Set the used docker-compose file specification in docker-compose.config.yml to version 3:

    version: '3'
    
    services:
        ...
    
  13. Update the NGINX service to use the short-hand syntax to expose ports. The NGINX service should look like this:

    nginx:
        restart: always
        image: "gcr.io/rasa-platform/nginx:${RASA_PLATFORM_VERSION:-stable}"
        ports:
        - "80:8080"
        - "443:8443"
        volumes:
        - ./certs:/opt/bitnami/nginx/conf/bitnami/certs
        - ./terms:/opt/bitnami/nginx/conf/bitnami/terms
        depends_on:
        - nlu
        - core
        - api
        - platform-ui
        - event-service
        - app
    
  14. Convert docker-compose.config.yml with (if you are using Kubernetes replace --provider OpenShift with --provider Kubernetes):

    $ kompose convert -f docker-compose.config.yml --provider OpenShift
    

    This will create all files needed for the deployment.

  15. Change the volumes in the api-deploymentconfig.yaml file. The volumeMounts section should look like this:

    volumeMounts:
    - mountPath: /app/nlu-models
      name: api-claim0
    - mountPath: /app/core-models
      name: api-claim1
    - mountPath: /logs
      name: api-claim2
    - mountPath: /app
      name: environment_config
    

    and the volumes section should look like this:

    volumes:
    - name: api-claim0
      persistentVolumeClaim:
      claimName: api-claim0
    - name: api-claim1
      persistentVolumeClaim:
      claimName: api-claim1
    - name: api-claim2
      persistentVolumeClaim:
      claimName: api-claim2
    - name: environment_config
      configMap:
        name: configuration-files
        items:
          - key: environments
            path: environments.yml
    

    You can then remove the volume claim file which was used to mount environments.yml.

  16. Change the volumes in the following files nlu-deploymentconfig.yaml, nlu-development-deploymentconfig.yaml and nlu-worker-deploymentconfig.yaml. The volumeMounts section should look like this:

    volumeMounts:
    - mountPath: /app/nlu-models
      name: {pod_name}-claim0
    - mountPath: /app/config
      name: config
    

    and the volumes sections should look like this:

    volumes:
    - name: {pod_name}-claim0
      persistentVolumeClaim:
      claimName: {pod_name}-claim0
    - name: config
      configMap:
        name: configuration-files
        items:
          - key: nlu-endpoints
            path: endpoints.yml
    

    Where {pod_name} will depend on the deployment that is getting updated. The correct values are nlu, nlu-development, nlu-worker for their respective files. You can then remove the volume claim files which were used for the mounts of endpoints.yml.

  17. Change the volumes in the following files core-deploymentconfig.yaml, core-development-deploymentconfig.yaml and core-worker-deploymentconfig.yaml. The volumesMounts section should look like this:

    volumeMounts:
    - mountPath: /app/models
      name: {pod_name}-claim0
    - mountPath: /app/default
      name: {pod_name}-claim0
    - mountPath: /app/config
      name: config
    

    and the volumes section should look like this:

    volumes:
    - name: {pod_name}-claim0
      persistentVolumeClaim:
      claimName: {pod_name}-claim0
    - name: config
      configMap:
        name: configuration-files
        items:
          - key: core-endpoints
            path: endpoints.yml
          - key: core-credentials
            path: credentials.yml
    

    Where {pod_name} will depend on the deployment that is getting updated. The correct values are core, core-development, core-worker for their respective files. You can then remove the volume claim files which were used for the mounts of endpoints.yml and credentials.yml.

  18. Remove the volume claim files which were used for the mounts of endpoints.yml.

  19. Change the volumes in nginx-deploymentconfig.yaml. The volumeMounts section should look like this:

    volumeMounts:
       - mountPath: /opt/bitnami/certs
         name: nginx-certs-secret
       - mountPath: /opt/bitnami/nginx/conf/bitnami/terms
         name: agreement
    

    and the volumes sections should look like this:

    volumes:
    - configMap:
        items:
          - key: agree
            path: agree.txt
        name: agreement
      name: agreement
    - name: nginx-certs-secret
      secret:
        items:
          - key: dh
            path: dh.pem
          - key: fullchain
            path: fullchain.pem
          - key: privkey
            path: privkey.pem
        secretName: nginx-certs
    

    The previously generated NGINX volume claim files can now be removed since they were replaced by the configMap and secret.

  20. Now you can use the generated files to deploy Rasa Platform, either using the OpenShift / Kubernetes CLI or the web console.

  21. Create the required services:

    • nginx
    • platform-ui
    • api
    • mongo
    • app
    • core
    • core-development
    • core-worker
    • nlu
    • nlu-development
    • nlu-worker
    • rabbit
  22. To access the platform expose the nginx service with (if you are using Kubernetes replace oc with kubectl):

    $ oc expose service/nginx
    

    Alternatively create your own route from the web console.

  23. Using the terminal of the API pod create the first user by running:

    $ cd scripts
    $ python manage_users.py create [username] [password] [role]
    

    Possible values for role are admin, user, and annotator.

Environment Variables

Global environment variables

This group of variables is mainly used by docker-compose. All the variables get interpolated when starting the services with docker-compose up and then are passed to services. It is possible to see the docker-compose.yml file with the substituted variables by using docker-compose config.

Variable Explanation
PLATFORM_UI_VERSION The compatible UI version for the Platform.
PLATFORM_DEMO_VERSION Custom Action Server version.
CORE_VERSION The version of Rasa Core used by the Platform.
CORE_SDK_VERSION The SDK version used by the Custom Action Server.
NLU_VERSION The version of Rasa NLU used by the Platform.
SPACY_VERSION The version of Spacy used by Rasa NLU.
SPACY_ENGLISH_MODEL_BASE English language model used by Spacy.
SPACY_ENGLISH_MODEL_VERSION Version of the English language model used by Spacy.
SPACY_GERMAN_MODEL_BASE German language model used by Spacy.
SPACY_GERMAN_MODEL_VERSION Version of the German language model used by Spacy.
TENSORFLOW_VERSION The version of Tensorflow used.
RASA_NLU_TOKEN Authentication token for the NLU service. This is used by other services to communicate with NLU.
RASA_CORE_TOKEN Authentication token for the Core service. This is used by other services to communicate with Core.
JWT_SECRET JWT token for authentication between services and the API.

The Core variables group

These variables define the behaviour of Rasa Core and how the other services connect to it. This group of variables is used by the following services:

  • api
  • core
Variable Explanation
RASA_CORE_HOST URL of the Core service.
RASA_CORE_MODEL_DIR The directory in which Core models are stored.
RASA_CORE_MODEL_PULL_INTERVAL Pull interval for Core, in seconds.
RASA_CORE_MODEL_SERVER URL of the model server (API).
RASA_NLG_ENDPOINT_URL Natural Language Generation endpoint.
RASA_REMOTE_CORE_ENDPOINT_URL Must be the same as RASA_CORE_HOST.
RASA_USER_APP URL of the custom action server.
RASA_CORE_WORKER_TOKEN Set equal to RASA_CORE_TOKEN.

The MongoDB variables group

These variables define the behaviour of MongoDB and how the other services connect to it. For more information please visit https://github.com/bitnami/bitnami-docker-mongodb. This group of variables is used by the following services:

  • api
  • core
  • event-service
Variable Explanation
MONGO_INITDB_ROOT_USERNAME This variable is used to create the root user during the startup of MongoDB.
MONGO_INITDB_ROOT_PASSWORD This variable is used to create the root password during the startup of MongoDB.
MONGO_DB The name of the database used by the services.
MONGO_HOST URL of the MongoDB database. It should use the mongodb protocol.
MONGO_PASSWORD This variable is used by other services to access MongoDB. It should be equal to MONGO_INITDB_ROOT_PASSWORD.
MONGO_USERNAME This variable is used by other services to access MongoDB. It should be equal to MONGO_INITDB_ROOT_USERNAME.

The NLU variables group

These variables define the behaviour of NLU and how the other services connect to it. This group of variables is used by the following services:

  • api
  • core
  • nlu
Variable Explanation
RASA_DUCKLING_HTTP_URL URL of Duckling, used for entity extraction.
RASA_NLU_HOST URL of Rasa NLU. This is used by other services to connect to Rasa NLU.
RASA_NLU_MODEL_DIR The path where the NLU models are stored.
RASA_NLU_MODEL_SERVER The URL used by other services to request NLU models.
RASA_NLU_WORKER_TOKEN Set equal to RASA_NLU_TOKEN

The Platform API variables group

These variables define the behaviour of the Platform API and how the other services connect to it. This group of variables is used by the following services:

  • api
  • core
  • nlu
Variable Explanation
PASSWORD_SALT Salt used to securely store the users passwords.
PLATFORM_USER_ANALYTICS Flag used to show/hide the analytics tab.
RASA_PLATFORM_HOST The URL of the API services. This is used by other services to connect to the API.
RASA_PLATFORM_TOKEN The token used for authentication between other services and the API.
SANIC_RESPONSE_TIMEOUT General timeout for request (seconds).
SELF_PORT Port used by the API service.

The RabbitMQ variables group

These variables define the behaviour of the RabbitMQ and how the other services connect to it. For more information please visit https://github.com/bitnami/bitnami-docker-rabbitmq#configuration. This group of variables is used by the following services:

  • api
  • core
  • event-service
Variable Explanation
RABBITMQ_DEFAULT_PASS This variable is used to create the password for the default user during startup.
RABBITMQ_DEFAULT_USER This variable is used to create the username for the default user during startup.
RABBITMQ_HOST Hostname of the container hosting RabbitMQ.
RABBITMQ_PASSWORD This is used by other services to access RabbitMQ. Must be equal to RABBITMQ_DEFAULT_PASS.
RABBITMQ_USERNAME This is used by other services to access RabbitMQ. Must be equal to RABBITMQ_DEFAULT_USER.

The UI file

This file is used by the following services:

  • platform-ui
Variable Explanation
REACT_APP_API_URL The URL used by the application as the base for API calls.