Metadata-Version: 2.1
Name: spacyjsonnlp
Version: 0.1.2
Summary: The Python spaCy JSON-NLP package
Home-page: https://github.com/dcavar/spaCy-JSON-NLP
Author: Damir Cavar, Oren Baldinger, Maanvitha Gongalla, Anurag Kumar, Murali Kammili
Author-email: damir@cavar.me
License: UNKNOWN
Description: # spaCy to JSON-NLP
        
        (C) 2019 by [Damir Cavar], [Oren Baldinger], Maanvitha Gongalla, Anurag Kumar, Murali Kammili
        
        Brought to you by the [NLP-Lab.org]!
        
        
        This only works with spaCy 2.1.0!
        
        I had the same issue. I downgraded Spacy from 2.1.4 to 2.1.0 and numpy to 1.14.5 to resolve.
        
        
        ## Introduction
        
        Currently this module requires Python 3.6+.
        
        This module provides a [spaCy] v2.1 wrapper for [JSON-NLP]. It takes the [spaCy] output and generates a [JSON-NLP] output. It also provides a Microservice wrapper that allows you to launch the [spaCy] module as a persistent RESTful service using [Flask] or other WSGI-based server.
        
        Since this microservice is built on [spaCy], you will need to have its models download, for example:
        
            python -m spacy download en
            python -m spacy download en_core_web_md
        
        ## Additional Pipeline Modules
        
        [spaCy] allows for the addition of additional models as pipeline modules. We provide such integrations for coreference and phrase structure trees.
        
        ### Anaphora and Coreference Resolution
        
        We provide [HuggingFace] coreference resolution, a fast system tightly integrated into [spaCy]. Note that the first time the parser is run, it will download the coreference models if they are not already present. These models only work for English.
        
        ### Phrase Structure Trees (Constituency Parse)
        
        We provide the CPU version of the [benepar] parser, a highly accurate phrase structure parser. Bear in mind it is a Tensorflow module, as such it has a notable start-up time, and relatively high memory requirements (4GB+).
        
        If you have a GPU available, you can install the GPU version of the module with:
        
            pip install --upgrade benepar[gpu] 
        
        ## Microservice
        
        The [JSON-NLP] repository provides a Microservice class, with a pre-built implementation of [Flask]. To run it, execute:
            
            python spacyjsonnlp/server.py
         
        Since `server.py` extends the [Flask] app, a WSGI file would contain:
        
            from spacyjsonnlp.server import app as application
            
        To disable a pipeline component (such as phrase structure parsing), add
        
            application.constituents = False
            
        The full list of properties that can be disabled or enabled are
        - constituents
        - dependencies
        - coreference
        - expressions
        
        The microservice exposes the following URIs:
        - /constituents
        - /dependencies
        - /coreference
        - /expressions
        - /token_list
        
        These URIs are shortcuts to disable the other components of the parse. In all cases, `tokenList` will be included in the `JSON-NLP` output. An example url is:
        
            http://localhost:5000/dependencies?text=I am a sentence
        
        Text is provided to the microservice with the `text` parameter, via either `GET` or `POST`. If you pass `url` as a parameter, the microservice will scrape that url and process the text of the website.
        
        The [spaCy] language model to use for parsing can be selected with the `spacy_model` parameter.
        
        Here is an example `GET` call:
        
            http://localhost:5000?spacy_model=en&constituents=0&text=I am a sentence.
        
        [Damir Cavar]: http://damir.cavar.me/ "Damir Cavar"
        [Oren Baldinger]: https://oren.baldinger.me/ "Oren Baldinger"
        [NLP-Lab.org]: http://nlp-lab.org/ "NLP-Lab.org"
        [JSON-NLP]: https://github.com/dcavar/JSON-NLP "JSON-NLP"
        [Flair]: https://github.com/zalandoresearch/flair "Flair"
        [spaCy]: https://spacy.io/ "spaCy"
        [NLTK]: http://nltk.org/ "Natural Language Processing Toolkit"
        [Polyglot]: https://github.com/aboSamoor/polyglot "Polyglot"
        [Xrenner]: https://github.com/amir-zeldes/xrenner "Xrenner"
        [CONLL-U]: https://universaldependencies.org/format.html "CONLL-U"
        [Flask]: http://flask.pocoo.org/ "Flask"
        [HuggingFace]: https://github.com/huggingface/neuralcoref/ "Hugging Face"
        [benepar]: https://github.com/nikitakit/self-attentive-parser "Berkeley Neural Parser"
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
