Metadata-Version: 2.1
Name: texta-tagger
Version: 1.2.0
Summary: texta-tagger
Home-page: https://git.texta.ee/texta/texta-tagger-python
Author: TEXTA
Author-email: info@texta.ee
License: GPLv3
Description: # TEXTA Tagger Python Package
        
        This package is for using text classification models exported from TEXTA Toolkit 2.
        
        ## Installation
        
        ### Using built package
        
        `pip install texta-tagger`
        
        ### Using Git (for development)
        
        `pip install git+https://git.texta.ee/texta/texta-tagger.git`
        
        ## Usage
        
        ### Predicting Using Zipped Model
        
        **Predicting without MLP & lemmatization**
        ```
        >>> from texta_tagger.tagger import Tagger
        >>>
        >>> t = Tagger()
        >>> t.load_zip('test_data/tagger.zip')
        True
        >>> print('Tagger:', t)
        Tagger: Eesti
        >>> t.tag_text('eesti keel ja eesti meel')
        {'prediction': True, 'probability': 0.9999999322365133}
        ```
        
        **Predicting with MLP & lemmatization**
        
        Predicting with lemmatization requires either a running MLP server or MLP Python package installed. In following example MLP from package is used:
        ```
        >>> from texta_tagger.tagger import Tagger
        >>> from texta_mlp.mlp import MLP
        >>>
        >>> mlp = MLP()
        >>>
        >>> t = Tagger(mlp=mlp)
        >>> t.load_zip('test_data/tagger.zip')
        True
        >>> print('Tagger:', t)
        Tagger: Eesti
        >>> t.tag_text('eesti keel ja eesti meel')
        {'prediction': True, 'probability': 0.9999999322365133}
        ```
        
        In following example MLP server version is used:
        ```
        >>> from texta_tagger.tagger import Tagger
        >>> from texta_tagger.mlp_analyzer import get_mlp_analyzer
        >>>
        >>> mlp = get_mlp_analyzer(mlp_host="http://my-mlp-server:5000")
        >>>
        >>> t = Tagger(mlp=mlp)
        >>> t.load_zip('test_data/tagger.zip')
        True
        >>> print('Tagger:', t)
        Tagger: Eesti
        >>> t.tag_text('eesti keel ja eesti meel')
        {'prediction': True, 'probability': 0.9999999322365133}
        ```
        
        ### Training
        TODO
        
        ### Environment Variables
        
        * TEXTA_TAGGER_MLP_URL - MLP host used for lemmatization (e.g. http://mlp-dev.texta.ee:5000)
        * TEXTA_TAGGER_MLP_MAJOR_VERSION - MLP major version (2/3).
Platform: UNKNOWN
Description-Content-Type: text/markdown
