Open-source chatbot with Rasa and the NLP

Key Features • How To Use • Architecture • Related

This project has been developed and conceived only as a learning project and corresponds to a graduation project for the specialty artificial intelligence. The goal of the project is to create a movie chatbot using an open source framework Rasa. The bot includes voice recognition and transforms the processed text into a voice as well as a voice into a text.

Key Features

Cinemas Nearby	Search by Description	User Encouragement	Movie Description	Movie by Director	Movie Information	Similar Movies	Movie by Genre
The bot gives out the nearest cinemas at the address specified by the user	The bot gives out the films based on description from the user	The bot encourages the user with a funny (comedy) movie if the user is in a bad mood	The user can also get a description of the movie sent recently by the bot	Тhe user can also specify the name of the director and the bot will send a dozen films	By clicking on the desired movie, the user can send the copied number to get more information	The bot gives out a dozen similar movies to the movie title specified by the user	The bot gives a random movie in the genre specified by the user

How to use

1. First at all, train your model:

   rasa train

2. Check if project data is validated:

   rasa data validate

3. Then in terminal 1 (from chatbot):

   rasa run --enable-api --cors "*"

4. In terminal 2 start server (from chatbot):

   rasa run actions

5. Finally, open server page:

   python widget/server.py

6. For API configuration you need to generate token and add to .env file.

Architecture

(Back to top)

There are two docker files in the chatbot folder, one for Rasa Core and one far Rasa Action, so you can create an image for more convenient use.

Related

• TMDB for python: TMDB API for movie requests
• TMDB API: get started and generate a key

(Back to top)