Metadata-Version: 2.1
Name: SentenceGraph
Version: 0.0.3
Summary: Easily create semantic graphs from text using SentenceTransformers
Home-page: https://github.com/Hevia/SentenceGraph
Author: Hevia
Author-email: anthony@hevia.dev
License: Apache Software License 2.0
Keywords: nbdev jupyter notebook python
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: sentence-transformers
Provides-Extra: dev
Requires-Dist: twine ; extra == 'dev'

SentenceGraph
================

<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

## Install

``` sh
pip install SentenceGraph
```

## How to use

Fill me in please! Don’t forget code examples:

``` python
from SentenceGraph.core import SentenceGraph, Format
```

``` python
sentenceGraph = SentenceGraph()
```

``` python
sentences = ['This framework generates embeddings for each input sentence',
    'Sentences are passed as a list of string.', 
    'The quick brown fox jumps over the lazy dog.']
```

``` python
sim_graph = sentenceGraph.createGraph(sentences)
sim_graph
```

You can also return a graph matrix in different formats.

``` python
sim_graph = sentenceGraph.createGraph(sentences, format=Format.Numpy)
sim_graph
```


