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Docker Compose configuration for rapidly getting started with running a bot using the Rasa Pro Developer Edition

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Quick, Small Deployment of the Rasa Pro Developer Edition

Docker Compose configuration for rapidly getting started with running a bot using the Rasa Pro Developer Edition. This is intended as a lightweight way to deploy a Rasa assistant that will receive only small amounts of traffic.

Note you will need an extended license to run Rasa Pro Developer Edition on a server.

  1. Create a VM on your cloud provider of choice, and install Docker. 1vCPU and 2GB RAM should be sufficient unless you've trained a big NLU model.

  2. Create a directory and copy in the following files from this repo:

  • docker-compose.yml
  • endpoints.yml
  • credentials.yml
  • actions.py
  • models/model.tar.gz
  1. Create a file called .env in the same directory with the following contents:
RASA_PRO_LICENSE=<your Rasa Pro license goes here>
OPENAI_API_KEY=<your OpenAI API key goes here>
  1. Deploy the bot by running sudo docker compose up. (On older docker versions, it would be sudo docker-compose up)

  2. Send your bot a message by sending a POST request:

curl -XPOST http://<host>:5005/webhooks/rest/webhook -d '{"sender": "test", "message": "Hi"}'

Customization

Now that you have a demo assistant deployed, here are the next steps you might want to take:

  1. Upload your own model to replace the default one in the repo.
  2. Add your own custom action files, or build a custom action server image
  3. Configure your assistant to respond on other channels by modifying the credentials.yml file, see here

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