{"id":25056527,"url":"https://github.com/ascender1729/sentipulse","last_synced_at":"2026-05-10T09:33:28.677Z","repository":{"id":248080033,"uuid":"827670852","full_name":"ascender1729/sentipulse","owner":"ascender1729","description":"SentiPulse is an advanced sentiment analysis tool that leverages AI to assess the emotional tone of text inputs from social media. 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It provides real-time sentiment analysis with a user-friendly interface, making it easy to understand the emotional tone of text data.\n\n## Table of Contents\n\n- [Features](#features)\n- [Tech Stack](#tech-stack)\n- [Prerequisites](#prerequisites)\n- [Installation](#installation)\n- [Usage](#usage)\n- [Project Structure](#project-structure)\n- [API Endpoints](#api-endpoints)\n- [Contributing](#contributing)\n- [License](#license)\n- [Contact](#contact)\n- [Acknowledgements](#acknowledgements)\n\n## Features\n\n- **Advanced Sentiment Analysis**: Utilizes the `distilroberta-base` model from Hugging Face for accurate sentiment classification.\n  - Classifies text into Positive, Negative, or Neutral categories.\n  - Provides a confidence score for each classification.\n- **Fallback Mechanism**: Implements a local, rule-based sentiment analysis as a backup when the Hugging Face API is unavailable.\n- **Real-time Processing**: Instantly analyzes the sentiment of input text.\n- **Intuitive User Interface**: Easy-to-use interface for entering text and viewing results.\n- **Visual Representation**: Dynamic chart displaying sentiment distribution using Chart.js.\n- **Recent Analysis History**: View a list of recent sentiment analyses stored in SQLite database.\n- **Responsive Design**: Seamless experience across different device sizes.\n\n## Tech Stack\n\n### Backend\n- **Node.js**: JavaScript runtime for server-side logic.\n- **Express**: Web application framework for Node.js.\n- **SQLite**: Lightweight, serverless database for data storage.\n- **Hugging Face Inference API**: \n  - Model: `distilroberta-base`\n  - Task: Text Classification (Sentiment Analysis)\n  - Capabilities: Multi-class classification (Positive, Negative, Neutral)\n- **dotenv**: Environment variable management.\n\n### Frontend\n- **Svelte**: Reactive JavaScript framework for building user interfaces.\n- **Vite**: Next-generation frontend tooling for faster development.\n- **Chart.js**: JavaScript charting library for data visualization.\n\n### Development Tools\n- **Git**: Version control system.\n- **npm**: Package manager for JavaScript.\n- **nodemon**: Utility for automatic server restarts during development.\n\n## Prerequisites\n\n- Node.js (v14 or later)\n- npm (v6 or later)\n- Git\n\n## Installation\n\n1. Clone the repository:\n   ```\n   git clone https://github.com/ascender1729/sentipulse.git\n   cd sentipulse\n   ```\n\n2. Install server dependencies:\n   ```\n   cd server\n   npm install\n   ```\n\n3. Install client dependencies:\n   ```\n   cd ../client\n   npm install\n   ```\n\n4. Set up environment variables:\n   - Rename `.env.example` to `.env` in the server directory.\n   - Add your Hugging Face API key to the `.env` file:\n     ```\n     HF_API_KEY=your_huggingface_api_key_here\n     ```\n\n## Usage\n\n1. Start the server:\n   ```\n   cd server\n   npm run dev\n   ```\n\n2. In a new terminal, start the client:\n   ```\n   cd client\n   npm run dev\n   ```\n\n3. Open your browser and navigate to `http://localhost:5173`.\n\n4. Enter text in the input field and click \"Analyze Sentiment\" to see the results.\n\n## Project Structure\n\n```\nsentipulse/\n├── server/\n│   ├── src/\n│   │   ├── config/\n│   │   ├── controllers/\n│   │   ├── routes/\n│   │   ├── models/\n│   │   └── index.js\n│   └── package.json\n├── client/\n│   ├── src/\n│   │   ├── components/\n│   │   ├── App.svelte\n│   │   └── main.js\n│   ├── index.html\n│   ├── package.json\n│   └── vite.config.js\n├── .env\n├── .gitignore\n└── README.md\n```\n\n## API Endpoints\n\n- `POST /api/analyze`: Analyze sentiment of provided text.\n- `GET /api/recent`: Retrieve recent sentiment analyses.\n\n## Contributing\n\nContributions are welcome! Please feel free to submit a Pull Request.\n\n1. Fork the repository\n2. Create your feature branch (`git checkout -b feature/AmazingFeature`)\n3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)\n4. Push to the branch (`git push origin feature/AmazingFeature`)\n5. Open a Pull Request\n\n## License\n\nDistributed under the MIT License. See `LICENSE` for more information.\n\n## Contact\n\nPavan Kumar - pavankumard.pg19.ma@nitp.ac.in\n\nLinkedIn: [linkedin.com/in/im-pavankumar](https://www.linkedin.com/in/im-pavankumar/)\n\nProject Link: [https://github.com/ascender1729/sentipulse](https://github.com/ascender1729/sentipulse)\n\n## Acknowledgements\n\n- [Hugging Face](https://huggingface.co/) for their Inference API and the `distilroberta-base` model\n- [Svelte](https://svelte.dev/) for the reactive UI framework\n- [Chart.js](https://www.chartjs.org/) for data visualization\n- [Express.js](https://expressjs.com/) for the server framework\n- [SQLite](https://www.sqlite.org/) for the database","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fascender1729%2Fsentipulse","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fascender1729%2Fsentipulse","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fascender1729%2Fsentipulse/lists"}