Formbot - an example which demonstrates the implementation of FormAction
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_data.md contains training examples for NLU model
- data/stories.md contains training stories for Core model
- actions.py contains the implementation of a custom FormAction
- domain.yml contains the domain of the assistant
- endpoints.yml contains the webhook configuration for the custom action
- nlu_tensorflow.yml contains the pipeline configuration of the NLU model
- Makefile contains the shell commands which you can use to run this example
How to use this example?
Using this example you can build an actual assistant which demonstrates the functionality of the FormAction. You can use the example using the following steps:
Train the Rasa NLU model by running:
This will train the Rasa NLU model and store it inside the
/models/nlu/current/folder of your working directory.
Train the Rasa Core model by running:
This will train the Rasa Core model and store it inside the
/models/dialoguefolder of your working directory.
Test the assistant by running:
This will load the assistant in your command line for you to chat.
Encountered any issues?
Let us know about it by posting on Rasa Community Forum!