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⚠️ Development moved to Sourcehut

Home Page: https://git.sr.ht/~loges/aita

License: MIT License

Dockerfile 1.78% Python 90.54% Mako 1.10% Shell 1.35% Makefile 5.23%
docker fastapi nlp python reddit

aita's Introduction

Hello there 👋

I am no longer hosting open source projects on GitHub.

I explained in a recent post my reasoning for why I migrated my projects to SourceHut.

aita's People

Contributors

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saini6439

aita's Issues

Add text categorizer

Right now the api returns a dummy prediciton; need to train Text Categorizer for the 5 labels.

Tasks:

  • Read up on Spacy Text Categorizer documentatoin: https://spacy.io/api/textcategorizer
  • Train and export model
  • Replace dummy model with trained model
  • Test that reasonable predictions are being returned

Make training pipeline extensible

Problem

The current implementation of nlp train pipeline is heavily coupled to spacy, which makes it hard to extend the code to support other libraries.

Goal

The goal is to abstract out the train pipeline into a generic workflow starting with reading in data from the API to exporting the trained model. Once this is defined, any external library or strategy just needs to adhere to the defined interface.

Todos

  • Define the generic workflow of the train pipeline (inputs/outputs);
  • Remove spacy specific code from application logic;
  • Refactor current implementation so that the same result is achieved, but with spacy specific code being injected into the train pipeline as a valid strategy.

Add basic frontend

This ticket should fulfill the minimum requirement of the backend:

  • Text box for user input (AITA story)
  • Button that posts text to API and returns prediction and displays prediction (handle exceptions)
  • Display random sample story from DB with label

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