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Filip from Bulgaria


#1

Hi!
I work in university education in computer science. Can handle myself in several languages, but recent years I strongly prefer Python for everything. Use and love open source. Recently started experimenting semi-professional with Arduino/ESP8266.
Had a passion about conversational interfaces since at school (have written my first chat-bot in Pascal many moons ago). When I went to uni and had AI course I found out I actually had “invented” some things that were older than me, but still make me believe that I should continue working in this direction. Unfortunately my research interest veered off from A.I. and I made a Ph. D. in decision science (in my country this is part of computer science and not management science). Now at work my late research is about natural language and I started brushing off some forgotten skills and started learning new ones.
I am pretty interested in Mycroft and run an instance on a Pi.
In order to get a grasp of the whole thing I am currently toying with a movie trivia skill, that you can find here:


#2

That looks interesting. Where do you got the data in the movie.db file from ?

Have you considered using the moviedb to get same informations ? https://www.themoviedb.org/documentation/api

I see you use adapt and not Padatious as intent parsing. Isnt that more difficult then using Padatious ?


#3

Welcome @vonodna, great to have you here.
You may also enjoy our chatroom at https://chat.mycroft.ai


#4

The data is pulled from opendb.org (should mention it somewhere) and parsed in a small sqlite db that you see. A while ago I looked at many online APIs for movie info and honestly can’t remember if I checked themoviedb, but at the end I liked opendb the most. Local data gives me some advantages, although it is not the spirit of Mycroft skills it seems (all that I looked at were just voice interfaces to web APIs). I had considered Padatious after I started working on the skill. I stayed with adapt because:

  1. When I started reading the documentation all the examples are for adapt.
  2. Padatious is mentioned later and I thought it is more advanced and even less documented.
  3. As a result I decided to stick with the simpler intent parser for my first skill before going to the more advanced one.
  4. Padatious documentation looked very sketchy and ll the sources I studied I didn’t see (or realized) even one using Padatious over Adapt.
    Actually yesterday JarbasAI here in the forums suggested that using Padatious will be much easier for my task than Adapt, but when I told him? that what I found as docs and examples doesn’t seem enough and asked will he help he backed up and told me Adapt is great :slight_smile:
    I really hope the new documentation is better than this one and will probably try another skill with Padatious when I have time. But it would be nice to go through the acceptance process with this one just to see how it works.
    That are my thoughts for the moment, happy new year, over and out.

#5

Padatious is on our list for a documentation update; along with 65 other documentation pages :wink: