Summarify: AI Article Summarizer & Analyzer

Summarify is a simple yet powerful desktop application that instantly summarizes any online article. Just provide a URL, and this tool will fetch, analyze, and present the key information—including a summary and sentiment analysis—in a clean graphical user interface (GUI).

📋 Table of Contents

• ✨ Key Features
• 🧠 How It Works
• 🛠️ Tech Stack
• 🚀 Getting Started
  • Prerequisites
  • Installation & Setup
• 📖 How to Use
• 💡 Potential Improvements

Key Features

• One-Click Summarization: Automatically generates a concise summary of any online news article or blog post from its URL.
• Key Information Extraction: Instantly pulls the article's Title, Authors, and Publication Date.
• Sentiment Analysis: Analyzes the article's content to determine its overall sentiment (Positive, Negative, or Neutral).
• Simple Desktop GUI: A clean and user-friendly interface built with Python's native tkinter library.
• Smart URL Handling: Automatically validates and formats URLs to ensure they are correct before processing.

How It Works

The application follows a straightforward process:

1. URL Input: The user pastes a URL into the input field.
2. Article Fetching: The newspaper3k library downloads the HTML content of the article from the provided URL.
3. Content Parsing: The library then parses the downloaded content to extract the main text, title, authors, and publication date.
4. NLP Summarization: newspaper3k applies its built-in Natural Language Processing (NLP) algorithms to generate a concise summary of the article.
5. Sentiment Analysis: The full text of the article is analyzed by the TextBlob library to calculate its polarity score, which determines if the sentiment is positive, negative, or neutral.
6. Display: All the extracted information is neatly displayed in the read-only fields of the tkinter GUI. Error handling is included to manage cases where an article cannot be downloaded or parsed.

Tech Stack

This project is built entirely in Python, relying on a few key libraries for its functionality:

Category	Technology / Library
GUI Framework	tkinter (Python's standard GUI package)
Web Scraping & NLP	newspaper3k (for article extraction and summarization)
Sentiment Analysis	TextBlob
Language Processing	NLTK (Natural Language Toolkit) - a dependency for TextBlob

Getting Started

Follow these instructions to get the application running on your local machine.

Prerequisites

• Python 3.x
• pip (Python package installer)

Installation & Setup

1. Clone the Repository

   git clone [https://github.com/your-username/summarify.git](https://github.com/your-username/summarify.git)
   cd summarify

2. Create a Virtual Environment (Recommended)

   # For Windows
   python -m venv venv
   venv\Scripts\activate
   
   # For macOS/Linux
   python3 -m venv venv
   source venv/bin/activate

3. Install Dependencies You will need to install a few packages. You can create a requirements.txt file with the following content:

   newspaper3k
   nltk
   textblob
   

   Then, run the following command to install them:

   pip install -r requirements.txt

4. Download NLTK Data The TextBlob library requires specific data packages from NLTK to function correctly. Run Python from your terminal and download the necessary data.

   python

   Then, inside the Python interpreter, run:

   import nltk
   nltk.download('punkt')
   exit()

   This only needs to be done once.

5. Run the Application Execute your Python script to launch the GUI.

   python your_script_name.py  # Replace with the actual name of your script

How to Use

1. Run the application to open the Summarify window.
2. Find an online article you want to summarize and copy its URL.
3. Paste the URL into the "URL" input box at the bottom of the window.
4. Click the "Summarize" button.
5. Within a few seconds, the Title, Author, Publication Date, Summary, and Sentiment Analysis fields will be populated with the extracted information.