MSid01 / text-summarization-spaCy

Automatic summarization is the process of shortening a set of data computationally, to create a subset that represents the most important or relevant information within the original content. In addition to text, images and videos can also be summarized.

• TEXT SUMMARIZATION :

Text summarization refers to the technique of shortening long pieces of text. The intention is to create a coherent and fluent summary having only the main points outlined in the document. Propelled by the modern technological innovations, data is to this century what oil was to the previous one. Today, our world is parachuted by the gathering and dissemination of huge amounts of data. With such a big amount of data circulating in the digital space, there is need to develop machine learning algorithms that can automatically shorten longer texts and deliver accurate summaries that can fluently pass the intended messages. Furthermore, applying text summarization reduces reading time, accelerates the process of researching for information, and increases the amount of information that can fit in an area. Text summarization is an interesting machine learning field that is increasingly gaining traction. As research in this area continues, we can expect to see breakthroughs that will assist in fluently and accurately shortening long text documents.

• FAST API :

FAST API is a modern, fast , web framework for building APIs with Python 3.7+ based on standard Python type hints. The key features made available by Fast API include High performance, fewer bugs, easy to use and learn, robust, great editor support, etc.

• Steps to clone and set-up the project :

1. Fork the repository

2. Clone the repository - Insert your username of github at OR simply copy link from code button.

git clone https://github.com/<USERNAME>/text-summarization-spaCy.git

3. Create & activate virtual environment

 python -m venv fastapienv

Activate Fastapienv venv

source ./fastapienv/Scripts/activate

4. Install all dependencies -

pip install -r requirements.txt

5. Run through

uvicorn app:app --reload

6. Run the localhost request on your browser - https://localhost:8000

7. Now you will be directed to the Fast API routing methods. Firstly, you need to upload your text file in the POST summary. After successfully uploading your file, you can execute the Get Summary method and acquire the summarized content.

create new branch with

git branch temp

git checkout temp

make changes

git add .

git commit -m "some message"

git push origin temp

create new pull request from github