You are viewing documentation for our open source project which is maintained by the community. If you want to get started building assistants with Rasa please check out our latest [documentation here](/content/docs/index.html). ##### note The [Rasa Action Server chart](https://github.com/RasaHQ/helm-charts/tree/main/charts/rasa-action-server) is open source and available in the [helm-charts repository](https://github.com/rasahq/helm-charts). Please [create an issue](https://github.com/RasaHQ/helm-charts/issues/new) in this repository if you discover bugs or have suggestions for improvements. In the sections below you can learn how to deploy Rasa Action Server by using helm, and how to connect an Action Server deployment to a Rasa deployment. ## Installation Requirements 1. Check that you have installed the Kubernetes or OpenShift command line interface (CLI). You can check this using the following command: - Kubernetes - OpenShift ```bash kubectl version --short --client ``` The output should be similar to this: ``` # Client Version: v1.19.11 ``` If this command resulted in an error, please install the [Kubernetes CLI](https://kubernetes.io/docs/tasks/tools/install-kubectl/) or the [OpenShift CLI](https://docs.openshift.com/container-platform/4.7/cli_reference/openshift_cli/getting-started-cli.html#installing-openshift-cli) depending on the cluster you’re using. 2. Make sure that the Kubernetes / OpenShift CLI is correctly connected to your cluster. You can do so by using the following commands: - Kubernetes - OpenShift ```bash kubectl version --short ``` The output should be similar to this: ``` # Client Version: v1.19.11 # Server Version: v1.19.10 ``` If you get an error when executing the command, you are not connected to your cluster. To get the command to connect to the cluster please consult your cluster’s admin or the documentation of your cloud provider. 3. Make sure you have the [Helm CLI](https://helm.sh/docs/intro/install/) installed. To check this, run: ```bash helm version --short ``` The output should be similar to this: ``` # v3.6.0+g7f2df64 ``` If this command leads to an error, please install the [Helm CLI](https://helm.sh/docs/intro/install/). In case you are using a version `<3.5` of Helm, please update to Helm version `>=3.5`. ## 1. Installation ### a. Create Namespace We recommend installing Rasa Action Server in a separate [namespace](https://kubernetes.io/docs/concepts/overview/working-with-objects/namespaces/) to avoid interfering with existing cluster deployments. To create a new namespace run the following command: - Kubernetes - OpenShift ```bash kubectl create namespace ``` ### b. Deploy Rasa Action Server Run the following commands: ```bash # Add the repository which contains the Rasa Action Server Helm chart helm repo add rasa https://helm.rasa.com # Deploy Rasa Action Server helm install \ --namespace \ \ rasa/rasa-action-server ``` ### c. Access Rasa Action Server By default the Rasa Action Server deployment is exposed via the `rasa-action-server` (``) service and accessible only within a Kubernetes cluster. You can get the IP address using this command: - Kubernetes - OpenShift ```bash export SERVICE_PORT=$(kubectl get --namespace -o jsonpath="{.spec.ports[0].port}" services ) kubectl port-forward --namespace svc/ ${SERVICE_PORT}:${SERVICE_PORT} & ``` You can then access the deployment on `http://127.0.0.1:${SERVICE_PORT}`. ##### note The Rasa Action Server Helm chart uses the [rasa-x-demo](https://github.com/RasaHQ/rasa-x-demo) Docker image as default. In the [Building an Action Server Image](https://legacy-docs-oss.rasa.com/docs/rasa/deploy/deploy-action-server/#building-an-action-server-image) you can learn how to build and use your custom Action Server image. ## Building an Action Server Image If you build an image that includes your action code and store it in a container registry, you can run it as part of your deployment, without having to move code between servers. In addition, you can add any additional dependencies of systems or Python libraries that are part of your action code but not included in the base `rasa/rasa-sdk` image. ### Automating your Action Server Image Builds In addition to a manually creating a new Action Server image, you can use the [Rasa Action Server GitHub Action](https://github.com/RasaHQ/action-server-gha) to automate image builds. If GitHub Actions are new to you, it might be helpful to get familiar with [GitHub Actions Documentation](https://docs.github.com/en/actions). The following steps assume that you already created a GitHub repository and you have a DockerHub account. To create a workflow for building and pushing a Docker image into a DockerHub registry: 1. Add GitHub Secrets with your DockerHub login name and password. You can find details on how to create encrypted secrets for a repository in the [Github docs](https://docs.github.com/en/actions/configuring-and-managing-workflows/creating-and-storing-encrypted-secrets#creating-encrypted-secrets-for-a-repository) The example uses the following secrets: - `DOCKER_HUB_LOGIN` - a login name for DockerHub - `DOCKER_HUB_PASSWORD` - a password for DockerHub 2. In your GitHub repository create a file [`.github/workflows/action_server.yml`](https://github.com/RasaHQ/action-server-gha/blob/master/examples/action_server.yml). The GitHub Action workflow below builds a new docker image every time files inside the `actions/` directory have changed and the changes are pushed into the `main` branch. ```yaml on: push: branches: - main paths: - 'actions/**' jobs: build_and_deploy: runs-on: ubuntu-latest name: Build Action Server image and upgrade Rasa X/Enterprise deployment steps: - name: Checkout repository uses: actions/checkout@v2 - id: action_server name: Build an action server with custom actions uses: RasaHQ/action-server-gha@main with: docker_image_name: 'account_username/repository_name' docker_registry_login: ${{ secrets.DOCKER_HUB_LOGIN }} docker_registry_password: ${{ secrets.DOCKER_HUB_PASSWORD }} docker_image_tag: ${{ github.sha }} ``` 3. Push your changes to the `main` branch. After changes are pushed, the workflow will build and push a new image into the DockerHub registry. 4. Now, you can use your new brand docker image. 5. You can also extend your workflow, so that you do not have to manually update your Rasa X/Enterprise deployment. The example below shows how to extend your workflow with an additional step that updates a Rasa X/Enterprise Helm Chart deployment. ```yaml on: push: branches: - main jobs: build_and_deploy: runs-on: ubuntu-latest name: Build Action Server image and upgrade Rasa X/Enterprise deployment steps: [...] # This step shows only the example of output parameter usage - name: "Upgrade a Rasa Action Server deployment" run: | helm upgrade --install --reuse-values \ --set image.name=${{ steps.action_server.outputs.docker_image_name }} \ --set image.tag=${{ steps.action_server.outputs.docker_image_tag }} rasa-action-server rasa/rasa-action-server ``` As you can see it's possible to use output variables from the `action_server` step. The `steps.action_server.outputs.docker_image_name` variable returns a Docker image name and the `steps.action_server.outputs.docker_image_tag` variable returns a Docker image tag. More examples on how to use and customize [Rasa GitHub Actions](https://github.com/RasaHQ/action-server-gha) you can find in the [Rasa GitHub Actions](https://github.com/RasaHQ/action-server-gha) repository. #### Manually Building an Action Server To create your image: 1. Make sure your actions are defined in `actions/actions.py`. The `rasa/rasa-sdk` image will automatically look for the actions in this file. 2. If your actions have any extra dependencies, create a list of them in a file, `actions/requirements-actions.txt`. 3. Create a file named `Dockerfile` in your project directory, in which you'll extend the official SDK image, copy over your code, and add any custom dependencies (if necessary). For example: ```dockerfile # Extend the official Rasa SDK image FROM rasa/rasa-sdk:3.6.2 # Use subdirectory as working directory WORKDIR /app # Copy any additional custom requirements, if necessary (uncomment next line) # COPY actions/requirements-actions.txt ./ # Change back to root user to install dependencies USER root # Install extra requirements for actions code, if necessary (uncomment next line) # RUN pip install -r requirements-actions.txt # Copy actions folder to working directory COPY ./actions /app/actions # By best practices, don't run the code with root user USER 1001 ``` You can then build the image via the following command: ```bash docker build . -t /: ``` The `` should reference how this image will be different from others. For example, you could version or date your tags, as well as create different tags that have different code for production and development servers. You should create a new tag any time you update your code and want to re-deploy it. ### Using your Custom Action Server Image If you're building this image to make it available from another server, you should push the image to a cloud repository. This documentation assumes you are pushing your images to [DockerHub](https://hub.docker.com/). DockerHub will let you host multiple public repositories and one private repository for free. Be sure to first [create an account](https://hub.docker.com/signup/) and [create a repository](https://hub.docker.com/signup/) to store your images. You could also push images to a different Docker registry, such as [Google Container Registry](https://cloud.google.com/container-registry), [Amazon Elastic Container Registry](https://aws.amazon.com/ecr/), or [Azure Container Registry](https://azure.microsoft.com/en-us/services/container-registry/). You can push the image to DockerHub via: ```bash docker login --username --password docker push /: ``` To authenticate and push images to a different container registry, please refer to the documentation of your chosen container registry. ## Setting a Custom Action Server Image In order to use a Custom Action Server image along with the Rasa Action Server deployment, you have to use the following values for your deployment: ```yaml # values.yaml image: name: "image_name" tag: "image_tag" ``` then upgrade your deployment by executing the command: ```bash helm upgrade --namespace --reuse-values \ -f values.yaml rasa/rasa-action-server ``` ## 2. Connect Rasa Action Server to a Rasa deployment If you have deployed your assistant using the Rasa Helm chart, and you have deployed your Rasa Action Server as well. Now it's time to connect them together. You can do this easily by following the steps: a. Create a `rasa-values.yaml` file which will include configuration for the Rasa deployment. ```yaml # rasa-values.yaml rasa-action-server: external: # -- Determine if external URL is used enabled: true # -- URL to Rasa Action Server url: "http://rasa-action-server/webhook" ``` The configuration above tells Rasa which Rasa Action Server to use. In the example the `http://rasa-action-server/webhook` URL is used, the URL indicates that Rasa Action Server is deployed with release name `rasa-action-server`, and is located in the same namespace as Rasa server deployment. b. Upgrade the Rasa deployment ```bash helm upgrade -n --reuse-values -f rasa-values.yaml \ rasa/rasa ```