Rasa is an open source machine learning framework for automated text and voice-based conversations. Understand messages, hold conversations, and connect to messaging channels and APIs.
RASA can be installed using pip (python 3.6,3.7 and 3.8) as follows:
pip install rasa
A python venv is highly recommended for installing this framework as it depends on specific versions of a heap load of libraries.
You can find RASA's docs on installation here.
Let's start with a basic RASA project.
In an empty folder, create a python venv and install RASA in the venv.
Next, execute the following command to create a basic RASA project template:
rasa init
RASA will ask you if it should train an initial model, please select "Y".
You can play around with RASA in the command line using rasa shell.
You shall now have all the necessary files in the folder in order to get it to work with chat-bubble!
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Once you've trained an initial model, execute the following command:
rasa run --enable-api --cors '*' -p 1001This will start a new RASA server atlocalhost:1001.--enable-apiand--cors '*'are required to let users make requests from outside the RASA ecosystem.--cors '*'gives access to everyone, however it can be changed in the future to control who can access the server. '-p' specifies the port. For more on Rasa run, visit this link.
- If you changed the port RASA runs on, update the base_url in the chat-bubble's RASA demo boilerplate code to reflect those changes.
You're ready to make requests to the server via chat-bubble!
Just open Rasa_demo.html in any browser and chat-bubble will take care of rest of the connection!
P.S RASA is a GREAT framework that offers so much more functionality than what is described in this brief tutorial. Please go through the docs to make the most out of it.