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halef-SETU provides an easy wrapper around SKLL models for statistical language understanding as well as an easy to API based on Flask

Project description

Statistical Engine for Text Understanding (SETU)

This package provides wrapper around statistical models created with
SciKit-Learn Laboratory (SKLL) as well as an easy to use API based
on Flask.


pip install halef-SETU

Getting started with the API

Create a 'config.cfg' file like the following:

DEBUG = False

Set the location of this configuration file inside an environment variable:

export HALEF_SETU_SETTINGS=<path/to/config.cfg>

Create the 'slu_models.yaml' file:

model_dir: <path/to/directory/containing/model/and/vocab/files/>
reject_class: <name_of_the_class_for_nomatch>
- <item_name>:
- state: <state_name>
model: <slu_model_file_name>.model
vocab: <slu_model_vocab_file_name>.vocab
- <class_1_name>
- <class_2_name>
- <class_3_name>
- state: <some_other_state_name>
model: <some_other_slu_model_file_name>.model
vocab: <some_other_slu_vocab_file_name>.vocab
- <some_other_class_1>
- <some_other_class_2>

Create a file to start the API. This can be hosted like any other Flask application.
A quick example would be:
from halef_setu_api import app


Project details

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