Deployment
Prerequisites
- Access to a running Airy Core installation Get started
- A dialogflow agent up and running in google cloud see documentation
In order to deploy dialogflow-connector
you can apply the following Kubernetes Deployment
descriptor to your Airy Core Kubernetes cluster. You can also adapt the following configuration
to work with your favorite deployment tool like terraform.
- Get google cloud credentials see documentation
- Create configmap using the snippet called
dialogflow-config.yaml
- Deploy the connector by using the snippet called
dialogflow-deployment.yaml
There are some variables that need to be taken into account:
- Dialogflow project ID given by the Google Cloud Console: see documentation
- The confidence level tells the connector the amount of confidence it should have in order to suggest or give a reply. This value is a percentage so it should be between 0 and 1.
- The processor waiting time and check periods (in milliseconds) adjust the enrichment of the message before it is being processed by Dialogflow.
- The processor waiting time represents the amount of time before the message can be enriched by other connectors in the airy cluster before sending it to Dialogflow (for example: 2500).
- The processor check time represents the amount of time before the message can be enriched by other connectors before forwarding it to Dialogflow (for example: 5000).
- Default language: if the language in which the message is written cannot be determined, it will default to this value (for example: en for English).
dialogflow-config.yaml
dialogflow-deployment.yaml