- 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