calamanCy: NLP pipelines for Tagalog

calamanCy is a Tagalog natural language preprocessing framework made with spaCy. Its goal is to provide pipelines and datasets for downstream NLP tasks. This repository contains material for using calamanCy, reproduction of results, and guides on usage.

calamanCy takes inspiration from other language-specific spaCy Universe frameworks such as DaCy, huSpaCy, and graCy. The name is based from calamansi, a citrus fruit native to the Philippines and used in traditional Filipino cuisine.

🔧 Installation

To get started with calamanCy, simply install it using pip by running the following line in your terminal:

pip install calamanCy

Development

If you are developing calamanCy, first clone the repository:

git clone git@github.com:ljvmiranda921/calamanCy.git

Then, create a virtual environment and install the dependencies:

python -m venv venv
venv/bin/pip install -e .  # requires pip>=23.0
venv/bin/pip install .[dev]

# Activate the virtual environment
source venv/bin/activate

or alternatively, use make dev.

👩‍💻 Usage

To use calamanCy you first have to download either the medium, large, or transformer model. To see a list of all available models, run:

import calamancy
from model in calamancy.models():
    print(model)

# ..
# tl_calamancy_md-0.1.0
# tl_calamancy_lg-0.1.0
# tl_calamancy_trf-0.1.0

To download and load a model, run:

nlp = calamancy.load("tl_calamancy_md-0.1.0")
doc = nlp("Ako si Juan de la Cruz")

The nlp object is an instance of spaCy's Language class and you can use it as any other spaCy pipeline.

📦 Models and Datasets

calamanCy provides Tagalog models and datasets that you can use in your spaCy pipelines. You can download them directly or use the calamancy Python library to access them. The training procedure for each pipeline can be found in the models/ directory. They are further subdivided into versions. Each folder is an instance of a spaCy project.