• the bot finds:
  • movies a director is known for
  • movies and actor is known for
  • the release date of a movie if the movie title is provided
  • the overview/plot of a movie if a title is provided
  • searches for the rating of a movie based on movie title
  • Finds popular movies by year
  • engages in basic chit-chat

• Understanding the Rasa framework
• Installing the Rasa framework
• Experience with manipulating language based data

Everything is programmed in python, to follow this project you need the following

• Python <=3.6.8
• Jupyter Notebook
• Ngrok
• Slack

• rasa nlu
• rasa core
• rasa x

• text editor
• web browser
• terminal

data/core/ - contains stories

data/nlu - contains example NLU training data

demo - contains custom action/api code

domain.yml - the domain file

config.yml - the Rasa config file

events. - files related to rasa x usage

• Within jupyter notebooks comment out slack related code from within the loading assistant definition, engage with load_assistant()
• outside of notebook launch rasa x for a webbrowser based testing and interactive learning
• from slack: request server start and engage with @movichtr