https://github.com/jjangsangy/ExplainToMe

Automatic Web Article Summarizer
https://github.com/jjangsangy/ExplainToMe

docker heroku nlp python textrank

Last synced: about 2 months ago
JSON representation

Automatic Web Article Summarizer

• Host: GitHub
• URL: https://github.com/jjangsangy/ExplainToMe
• Owner: jjangsangy
• License: apache-2.0
• Created: 2015-03-12T05:34:06.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2021-09-08T00:17:18.000Z (about 3 years ago)
• Last Synced: 2024-07-04T14:18:55.467Z (2 months ago)
• Topics: docker, heroku, nlp, python, textrank
• Language: Python
• Homepage:
• Size: 5.58 MB
• Stars: 414
• Watchers: 21
• Forks: 61
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• starred-awesome - ExplainToMe - Automatic Web Article Summarizer (Python)

README

        
# ExplainToMe

[![travis](https://travis-ci.org/jjangsangy/ExplainToMe.svg?branch=master)](https://travis-ci.org/jjangsangy/ExplainToMe)

[![licence](https://img.shields.io/pypi/l/coverage.svg)](https://github.com/jjangsangy/ExplainToMe/blob/master/LICENSE)

[![Quay](https://quay.io/repository/jjangsangy/explaintome/status)](https://quay.io/repository/jjangsangy/explaintome)

## Automatic Web Article Summarizer

![Front](https://github.com/jjangsangy/ExplainToMe/raw/master/static/front.jpg)

[![Deploy](https://www.herokucdn.com/deploy/button.svg)](https://heroku.com/deploy)

# What is it?

`ExplainToMe` is a automatic text summarizer, that utilizes

[TextRank](http://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf),

a graph based algorithm to scans through the contents of a website to

extract a concise machine generated summary. The methodology is similar

to the way search engines return the most relevant web pages from a

users search query.

# Support

Here’s a list of Python platforms that are officially supported.

* Python 2.7

* Python 3.4

* Python 3.5

* pypy 2.5.0 -> 2.7.9

> We are working on Python 3.6

# Quickstart

# Install

## Clone Repository

```bash

$ git clone https://github.com/jjangsangy/ExplainToMe.git

```

## Create a virtualenv

```bash

$ virtualenv -p python venv

```

## Source Virtualenv

```bash

$ source venv/bin/activate

```

## Install Python Dependencies

```bash

$ pip install --upgrade pip setuptools wheel

$ pip install -r requirements.txt

```

## Run Server

```bash

$ python manage.py runserver

Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)

```

Now go to your browser and point it towards `http://127.0.0.1:5000`

# Docker

Running ExplainToMe via the [official Docker image](https://hub.docker.com/r/jjangsangy/explaintome/)

is an easy way to start a server if you don't want to install python.

We assume here you have already installed Docker for your system.

If you are getting started on OS X, the [Docker toolbox](https://docs.docker.com/engine/installation/mac/)

is the first thing to checkout.

```bash

$ docker run -it -p 5000:5000 jjangsangy/ExplainToMe:latest

```

Once the server is running, navigate to either localhost:5000 (on Linux) or

hostname:5000 (on Mac OS X), where hostname is the IP addresses

of your virtual machine, obtained using

```bash

$ docker-machine ip my-vm-name

```

Now access your docker machine ip at port `docker-machine-ip:5000`

# Kitematic

You might also want to try [Kitematic](https://kitematic.com/) on OS X which provides a GUI for running Docker images.

Running ExplainToMe through Kitematic is easy, just search for the

`jjangsangy/ExplainToMe` image, start it, and you should see it running

![kitematic](https://github.com/jjangsangy/ExplainToMe/raw/master/static/kitematic.jpg)

# Things to look forward to:

-   Summaries of documents in other languages than English!

# ExplainToMe API

Check out our [Swagger API Documentation](https://swaggerhub.com/api/jjangsangy/ExplainToMe)