Metadata-Version: 2.1
Name: SentenceGraph
Version: 0.0.5
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
Description: SentenceGraph
        ================
        
        <!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
        
        ## Install
        
        ``` sh
        pip install SentenceGraph
        ```
        
        ## How to use
        
        ``` python
        # from SentenceGraph.core import SentenceGraph, Format, TextNodeType
        # from SentenceGraph.functional import create_text_nodes
        ```
        
        ``` python
        # sentenceGraph = SentenceGraph()
        ```
        
        ``` python
        # SentenceGraph requires all sentences to be passed as TextNode, which is just a namedtuple containing an id and text.
        # There are several ways to prepare your sentence data for SentenceGraph.
        
        # Use the builtin helper function which will just assign sequential ids for the data. Useful for experimentation.
        # 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.']
        
        # sentences = create_text_nodes(sentences)
        
        # # 
        # sentences = [TextNode(1, 'This framework generates embeddings for each input sentence'),
        #     TextNode(2, 'Sentences are passed as a list of string.'), 
        #     TextNode(3,'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
        ```
        
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
Provides-Extra: dev
