SentiPulse is an advanced sentiment analysis tool designed to quickly gauge public opinion from social media-style text inputs. It provides real-time sentiment analysis with a user-friendly interface, making it easy to understand the emotional tone of text data.
- Features
- Tech Stack
- Prerequisites
- Installation
- Usage
- Project Structure
- API Endpoints
- Contributing
- License
- Contact
- Acknowledgements
- Advanced Sentiment Analysis: Utilizes the
distilroberta-base
model from Hugging Face for accurate sentiment classification.- Classifies text into Positive, Negative, or Neutral categories.
- Provides a confidence score for each classification.
- Fallback Mechanism: Implements a local, rule-based sentiment analysis as a backup when the Hugging Face API is unavailable.
- Real-time Processing: Instantly analyzes the sentiment of input text.
- Intuitive User Interface: Easy-to-use interface for entering text and viewing results.
- Visual Representation: Dynamic chart displaying sentiment distribution using Chart.js.
- Recent Analysis History: View a list of recent sentiment analyses stored in SQLite database.
- Responsive Design: Seamless experience across different device sizes.
- Node.js: JavaScript runtime for server-side logic.
- Express: Web application framework for Node.js.
- SQLite: Lightweight, serverless database for data storage.
- Hugging Face Inference API:
- Model:
distilroberta-base
- Task: Text Classification (Sentiment Analysis)
- Capabilities: Multi-class classification (Positive, Negative, Neutral)
- Model:
- dotenv: Environment variable management.
- Svelte: Reactive JavaScript framework for building user interfaces.
- Vite: Next-generation frontend tooling for faster development.
- Chart.js: JavaScript charting library for data visualization.
- Git: Version control system.
- npm: Package manager for JavaScript.
- nodemon: Utility for automatic server restarts during development.
- Node.js (v14 or later)
- npm (v6 or later)
- Git
-
Clone the repository:
git clone https://github.com/ascender1729/sentipulse.git cd sentipulse
-
Install server dependencies:
cd server npm install
-
Install client dependencies:
cd ../client npm install
-
Set up environment variables:
- Rename
.env.example
to.env
in the server directory. - Add your Hugging Face API key to the
.env
file:HF_API_KEY=your_huggingface_api_key_here
- Rename
-
Start the server:
cd server npm run dev
-
In a new terminal, start the client:
cd client npm run dev
-
Open your browser and navigate to
http://localhost:5173
. -
Enter text in the input field and click "Analyze Sentiment" to see the results.
sentipulse/
├── server/
│ ├── src/
│ │ ├── config/
│ │ ├── controllers/
│ │ ├── routes/
│ │ ├── models/
│ │ └── index.js
│ └── package.json
├── client/
│ ├── src/
│ │ ├── components/
│ │ ├── App.svelte
│ │ └── main.js
│ ├── index.html
│ ├── package.json
│ └── vite.config.js
├── .env
├── .gitignore
└── README.md
POST /api/analyze
: Analyze sentiment of provided text.GET /api/recent
: Retrieve recent sentiment analyses.
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature
) - Commit your changes (
git commit -m 'Add some AmazingFeature'
) - Push to the branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Distributed under the MIT License. See LICENSE
for more information.
Pavan Kumar - [email protected]
LinkedIn: linkedin.com/in/im-pavankumar
Project Link: https://github.com/ascender1729/sentipulse
- Hugging Face for their Inference API and the
distilroberta-base
model - Svelte for the reactive UI framework
- Chart.js for data visualization
- Express.js for the server framework
- SQLite for the database