This web application classifies news articles into categories, tracks past classification requests, and provides users with insights into article categorization. It takes a news article URL as input, scrapes the article content, predicts its category using an AI model, stores the request and prediction in a database and displays the predicted category along with a history of past classification requests.
Begin by setting up and running the project on your local machine.
Before you begin, ensure you have the following prerequisites installed:
- Nodejs
- Python
Follow these steps to get the project up and running:
-
Server
cd server pip install -r requirements.txt uvicorn main:app --reload
-
Client
cd client npm install npm run dev
To use the application:
- Navigate to the application's URL.
- Input a news article URL and submit the form.
- The application will scrape the article, predict its category, and display the result.
- Explore the history section to view past classification requests.
- News Classification: Automatically categorize news articles into predefined categories.
- Interactive Web Interface: User-friendly React frontend for input and results.
- Machine Learning: Utilizes AI models for article categorization.
- Database Storage: Stores article requests and predictions for historical tracking.
- History Viewer: Displays a history of past classification requests.
This project is licensed under the MIT License. See the LICENSE file for details.