feedCollector

RSS-Intelligence project. The aim of the project is to reproduce the working of a basic searchEngine using some tools of machineLearning and text processing. Here you will have some steps to follow to first use our architecture and after to deploy it in a RESTful API. Nothing too complicated here, if you have any errors go to the error sections there will be some error cases otherwise contact us. ⭐

Full Guideline

Install Elasticsearch https://www.elastic.co/guide/en/elasticsearch/reference/current/install-elasticsearch.html
Install / clone this github repo https://github.com/Gamerbful/feedCollector.git
Launch your Elasticsearch server ( on windows launch elasticsearch.bat in the bin folder of your server )
Open a terminal in you favorite IDE or just in raw if you don't like using any IDE :)
Get into the root folder of the project -> feedCollector
pip install requirement.txt to install dependencies
python .\scripts\helloFeedParser-1.py to parse rss flux they will be temp stored in rss folder
python .\scripts\elasticSearchTest.py GEN save rss flux in your local elasticsearch server ( may have some security error )
python .\scripts\classifier.py if you have our models it will just try to classify your new flux else if you delete bestModel and vectorizer it will train and create new model

Launch Serverside

Open two terminal and assure your elasticsearch server is running
python .\scripts\flaskAPI.py start our api wich will augment user query and return predicted categorie and ordered docs
npm start start an express server with ejs view on port 3000 of localhost