Metadata-Version: 2.1
Name: boolean-question
Version: 0.0.2
Summary: Boolean question-answer prediction with AI
Home-page: https://github.com/Saadmairaj/boolean-question
Author: Saad Mairaj
Author-email: Saadmairaj@yahoo.in
License: Apache
Project-URL: Bug Reports, https://github.com/Saadmairaj/boolean-question/issues
Project-URL: Source, https://github.com/Saadmairaj/boolean-question
Project-URL: Ask Question, https://github.com/Saadmairaj/boolean-question/discussions
Description: # Boolean Question
        
        [![PyPI](https://img.shields.io/pypi/v/boolean_question)](https://pypi.org/project/boolean_question)
        [![Hits](https://hits.seeyoufarm.com/api/count/incr/badge.svg?url=https%3A%2F%2Fgithub.com%2FSaadmairaj%2Fboolean-question&count_bg=%23A389F1&title_bg=%23555555&icon=pytorch.svg&icon_color=%23E7E7E7&title=welcomed&edge_flat=false)](https://hits.seeyoufarm.com)
        [![CodeFactor](https://www.codefactor.io/repository/github/saadmairaj/boolean-question/badge/master)](https://www.codefactor.io/repository/github/saadmairaj/boolean-question/overview/master)
        [![Downloads](https://pepy.tech/badge/boolean_question)](https://pepy.tech/project/boolean_question)
        
        Get accurate answer prediction for True / False question using this python pytorch model. The model takes a passage and question as input and returns either "True" or "False" as predicted answer. Model used is [RoBERTa](https://arxiv.org/abs/1907.11692) that is further trained on [BoolQ](https://arxiv.org/abs/1905.10044) dataset.
        
        ## Installation
        
        Install it with python package installer pip
        
        ```bash
        pip install boolean_question
        ```
        
        or install the latest master branch
        
        ```bash
        pip install git+https://github.com/Saadmairaj/boolean-question
        ```
        
        ## Usage
        
        The usage is simple and straight forward, import `BoolQ` class model and pass arguments to the `BoolQ.predict(passage: str, question: str)` method to predict the boolean answer "True" or "False"
        
        ```python
        import pprint
        from boolean_question import BoolQ
        
        bq = BoolQ()
        
        passage = """
        A red dwarf is the smallest and coolest kind of star on the main sequence.
        Red dwarfs are by far the most common type of star in the Milky Way, at
        least in the neighborhood of the Sun, but because of their low luminosity,
        individual red dwarfs cannot be easily observed."""
        
        question = "Coolest star in the Milky way is a Red dwarf"
        
        # Predict the answer from the passage and the question
        ans = bq.predict(passage, question)
        print(ans)
        
        # After prediction extra details of the prediction can be seen with the below command
        pprint.pprint(bq.prediction_details())
        ```
        
        <details>
        <summary>View output</summary>
        <p>
        
            True
            {'answer': True,
            'confidence': None,
            'false confidence': 0.01,
            'passage': '\n'
                        'A red dwarf is the smallest and coolest kind of star on the main '
                        'sequence. Red dwarfs are by far the most common type of star in \n'
                        'the Milky Way, at least in the neighborhood of the Sun, but '
                        'because of their low luminosity, individual red dwarfs cannot '
                        'be \n'
                        'easily observed.',
            'question': 'Coolest star in the Milky way is a Red dwarf',
            'true confidence': 0.99}
        
        </p>
        </details>
        
Keywords: question-answer,nlp,pytorch,AI,artificial-intelligence,deep-learning,natural-language-processing
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3
Description-Content-Type: text/markdown
