rukip

An Embedded CKIP Rasa NLU Components

Introduction

This open-source library implements Rasa custom components.

It offerstokenizer and featurizer powered by ckiptagger as components in RasaNLU pipeline.

Installation

pip install rukip

rukip is a python library hosted on PyPI. Requirements:

python >= 3.6
rasa >= 1.4.0
ckiptagger[tf] >= 0.0.19

Usage

Download model files

The model files are available on several mirror sites.

You can download and extract to the desired path by the following steps:

Downloads to ./data.zip
Extracts to ./data/

Add CKIPTokenizer component into rasa nlu pipeline and configure model_path as ./data.

The following is the example Rasa NLU config file

 language: "zh"
 pipeline:
   - name: "rukip.tokenizer.CKIPTokenizer"
     model_path: "./data"
   - name: "rukip.featurizer.CKIPFeaturizer"
     model_path: "./data"
     token_features: ["word", "pos"]
   - name: "CRFEntityExtractor"
     features: [["ner_features"], ["ner_features"], ["ner_features"]]
   - name: "CountVectorsFeaturizer"
   - name: "EmbeddingIntentClassifier"

Components

CKIPTokenizer

This component has one required field (model_path) to be configured and offers two optional fields for user to assign dictionaries.

recommend_dict_path is the file containing list of user-defined recommended-word. Default is None
cooerce_dict_path is the file containing a list of must-word. Default is None

The following is the example of user-defined dictionary. Each line shows one pair of word and weight.

土地公 1
土地婆 1
公有 2
來亂的 1
緯來體育台 1

CKIPFeaturizer

This component has one required field (model_path) to be configured and offers another optional fields for user to assign.

token_features is list of features extracted from ckiptagger to generate ner_features. Default is ["word", "pos"]

Development

$> git clone git@github.com:circlelychen/rukip.git
$> pip install -r requirements-to-freeze.dev.txt
$> make test

License

licensed under the GNU General Public License v3.0