Flask Summary

** PreSumm modules was originally from https://github.com/nlpyang/PreSumm **

Features

• generate summary on given text

Train and Use the model generate by BertSum

please follow this documents about how to train and use the model generated by BertSum

Installation In A Nutshell (on localhost)

1. clone this project to your local disk

 git clone https://github.com/Quan25/flask-summary.git

2. cd into the cloned project and download PreSumm

 git clone https://github.com/nlpyang/PreSumm.git

3. cd into PreSumm folder and change the branch to dev

 git checkout dev

4. Install Flask
5. Install ROUGE-1.5.5

• Install libxml-parser-perl, it is essential for installing ROUGE-1.5.5

  sudo apt-get install libxml-parser-perl

• and make sure you can run this, which means the ROUGE is successfully installed

  ./runROUGE-test.pl

6. Install pyrouge

 git clone https://github.com/bheinzerling/pyrouge.git
 cd pyrouge
 pip install -e .

• Additional information can be found here about how to install pyrouge and running the test

7. Please install pytorch 1.1.0 with this comand

• GPU

  conda install pytorch==1.1.0 torchvision==0.3.0 cudatoolkit=10.0 -c pytorch

• CPU Only

  conda install pytorch-cpu==1.1.0 torchvision-cpu==0.3.0 cpuonly -c pytorch

8. put your model file(i.e. xxxxx.pt) inside /PreSumm/models
9. add the following PYTHONPATH to bash_profile

 export PYTHONPATH=$PYTHONPATH:/path/to/flask-summary/PreSumm/src
 export PYTHONPATH=$PYTHONPATH:/path/to/flask-summary/PreSumm/

10. run source ~/.bash_profile
11. Run python app.py in the flask-summary directory.
12. Start web server by running python app.py while in the server_example directory.
13. Browse the examples at 0.0.0.0:5000 using a browser. (defaults to port 5000)