Netai-Social

Netai-Social is a social media application built with Flask, React, and MongoDB. It includes sentiment analysis and emotion detection features using natural language processing (NLP) models.

Features

• Sentiment Analysis: Analyze the sentiment of messages posted on the platform.
• Emotion Detection: Detect emotions in messages, providing a more nuanced understanding of user content.
• User-Friendly Interface: Intuitive UI/UX for seamless user experience.
• Real-time Updates: Messages and sentiments are updated in real-time for dynamic user interaction.
• Responsive Design: Mobile-friendly design ensures accessibility on various devices.

Technologies Used

• Backend: Flask, MongoDB, Transformers library (Hugging Face)
• Frontend: React, Axios for API requests
• NLP Models: DistilBERT for sentiment analysis and emotion detection
• Deployment: Render for hosting the application, GitHub Actions for CI/CD

Getting Started

1. Clone the repository: git clone https://github.com/hello-developer-sanjay/netai-social.git
2. Install dependencies: pip install -r requirements.txt for the backend, npm install for the frontend.
3. Set up environment variables: Create a .env file and define your MongoDB URI and other sensitive information.
4. Run the backend: python app.py
5. Run the frontend: npm start

Deployment

The application is automatically deployed on Render upon pushing to the main branch. GitHub Actions handle the deployment process, ensuring continuous integration and delivery.

Folder Structure

• /server: Backend Flask application.
  • /config: Database configuration files.
  • /models: Data models and logic.
  • /routes: API endpoints.
• /client: Frontend React application.
  • /src: React components and styles.

Contributions

Contributions are welcome! Feel free to open issues or create pull requests for any improvements or bug fixes.

License

This project is licensed under the MIT License - see the LICENSE file for details.