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movie-chatter's Introduction

Hi there

  • ๐Ÿ‘‹ I'm into data-centric/ human-centric machine learning, where people build models by first taking a long hard look at their datasets.
  • ๐Ÿ”ญ Iโ€™m currently working on Argilla to make easy to use and well integrated.
  • ๐ŸŒฑ Iโ€™m currently learning about on device inference for LLMs.
  • ๐Ÿ‘ฏ Iโ€™m looking to collaborate on domain specific datasets for real world use cases.
  • ๐Ÿ“ซ How to reach me: LinkedIn or X

movie-chatter's People

Contributors

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movie-chatter's Issues

Comparison Function

Make a comparison function based on movies; for example, that pulls movie titles from strings, and compare those movies based on IMDB keywords.

Documentation

double response

When starting the script and using the keywords 'about' and 'movie' in the same phrase, the chatterbot will first try to determine the movie and then immediately talk 'about' a proposed movie. I don't understand why both the movieAdapter and aboutAdapter are used. I would presume only 1 at a time can give a response before awaiting user input.

Type something to begin...
---
lets talk about movies
What's your favorite film? Maybe we can find something similar.
the godfather
Do you mean The Godfather directed by Francis Ford Coppola?
yes
Do you know Scarface?
yes
Something you might not know is ...
How about Scarface?
---

Note the part:

Do you know Scarface?
yes
Something you might not know is ...

should not happen here.

Create a 'context' class

Create a 'context' class that handles an IMDB movie and its properties so that it can be used on the fly. This is already implemented in a basic way by "logic_adapter.aboutAdapter".

Is anybody working on training?

Chatterbot can be trained on scripted data, as I outlined in class. This can be basic stuff like greetings, but also online content from twitter Documentation . You can specify the crawl to start from keywords, for example "film reviews".

We should get this up and running asap because it makes a lot of other task easier.

New IMDB logic adapters.

Each person working in the 'core' group should check out "logic_adapters.py", and implement their own logic adapter class to handle IMDB data. There are two existing examples that use "utils/movies.py". I think we will need between 6 and 8 of these.

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