Formbot

The formbot example is designed to help you understand how the FormAction works and how to implement it in practice. Using the code and data files in this directory, you can build a simple restaurant search assistant capable of recommending restaurants based on user preferences.

What’s inside this example?

This example contains some training data and the main files needed to build an assistant on your local machine. The formbot consists of the following files:

• data/nlu.yml contains training examples for the NLU model
• data/stories.yml contains training stories for the Core model
• actions/actions.py contains the implementation of a custom FormAction
• config.yml contains the model configuration
• domain.yml contains the domain of the assistant
• endpoints.yml contains the webhook configuration for the custom actions

How to use this example?

Using this example you can build an actual assistant which demonstrates the functionality of the FormAction. You can test the example using the following steps:

1. Train a Rasa model containing the Rasa NLU and Rasa Core models by running:

   rasa train
   

   The model will be stored in the /models directory as a zipped file.

2. Run an instance of duckling on port 8000 by either running the docker command

   docker run -p 8000:8000 rasa/duckling
   

   or installing duckling directly on your machine and starting the server.

3. Test the assistant by running:

   rasa run actions&
   rasa shell -m models --endpoints endpoints.yml
   

   This will load the assistant in your command line for you to chat.

For more information about the individual commands, please check out our documentation.

Encountered any issues?

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