iampara0x/yuno

Yuno is context based search engine for anime.

Yuno

yuno.mp4

Table of Contents

1. Introduction
2. Power Of Yuno
3. Try Yuno
4. How Yuno was created?
5. References

Introduction

Yuno is a context based search engine that indexes over 0.5 million anime reviews and other anime informations. To help you find anime with specific properties. This search engine will help people of r/AnimeSuggest who are looking for specific type of anime to watch.

This search engine was created to solve the problem of finding an object with specific properties and the object in this case is anime. But this search engine can be easily extended to any domain like books,movies,etc. Without the need of any kind of handcrafted dataset.

you can watch more about Yuno in this video more in this video: https://www.youtube.com/watch?v=w9NflYMPPtM

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Power of Yuno

1. anime where male MC turns into different species
2. romance anime with wholesome plot
3. isekai anime with great worldbuilding
4. anime with romance between teacher and student
5. masterpiece anime with amazing plot
6. anime with revenge plot

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Try Yuno (Both notebooks has UI)

1. Kaggle Notebook (Recommended notebook)
2. Colab Notebook

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Creation

All the details about how Yuno was created and everything related is in the following article.

Below are the few kaggle notebooks that you can look into to learn more about the creation of Yuno:

1. Anime Search Visualization This notebook contains interactive visualization of all reviews plotted from 1280D -> 2D using T-SNE.

2. Yuno Models This notebook contains all the information about training Yuno with it's parameters.

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References

1. This dataset was used as initial starting point.

yuno's Issues

[Feature Request] Periodic retraining

It would be awesome to retrain Yuno every once in a while, as new anime and recommendations appear. Even once a year would be good to have.

kaggle colab does not work

I get this error everytime

<ipython-input-2-4604c83e7d7e> in <module>
      1 import dill as pickle
----> 2 from yuno.search import pipelines,base,config,utils
      3 import torch
      4 import torch.nn.functional as F
      5 import faiss

ModuleNotFoundError: No module named 'yuno'

Pipfile execute falsely

Cannot run program "D:\PythonProject\Yuno\Pipfile" (in directory "D:\PythonProject\Yuno"): CreateProcess error=193, %1 It isn't available Win32 Application。

Character data

Hi, I can see that you did a great job on Yuno! As I'm on my way to figuring out how this model works and its preprocessing steps, I engaged some problems with the preprocessing part.

Currently I'm looking at the filter.py in the preprocessing folder. The class FilterText is initialized with AnimeInfo class.

class AnimeInfo(NamedTuple):

  uid: int

  names: List[str]

  characters: List[Character]

As I see, it contains anime uid(it should match MAL's uid), anime title and character info. But I couldn't find the character data in the Kaggle dataset or anime character scraper for MAL or anything. So that raised me some questions.

1. How did you attain the character data ? Is there any notable preprocessing needed to be done after fetching the data ?

2. What is included in the info for each anime character ? (their name, gender, age, ...etc)

By the way I think it'd be nice if you upload another notebook for the preprocessing part. You may be busy, so I don't mind if you don't. Thanks in advance!

Great Work!

Hi, I find your work very inspiring and the program code very complete. I would like to learn your special way of training. It looks like you used an unsupervised approach (maybe called Pair-based metric learning) to train the model to learn semantics. I am curious how pos, neg and anchor are selected. I'm still reading the code. I haven't fully understood it yet.

According to my understanding, the comments of the same anime are set as anchor and pos, while the comments of any other randomly selected anime are defined as neg

synopsis might a better source

good job!
but result seem not so good.

I know many Recommendation Systems based on movie entity graph (meta data) and user comment (based on NLP)

and I think you can give it a try on synopsis (japanese article) reference from this

and I just discovered tmdb can be a good source , seem English synopsis edit almost on every anime entity, and its parallel multilingual text
some well-known example:
Story synopsis - API
epsiode synopsis or interface language mode=ja-JP - API

if Interested on multilingual sbert multilingual model

I didn't found who build a Parallel text dataset or dump with translations dev reference
you can use discover API to get anime tv/moive id

Google colab notebook error

FileNotFoundError: [Errno 2] No such file or directory: 'search_base.pkl'

And

NameError: name 'pipeline' is not defined