https://github.com/ascender1729/sentipulse
SentiPulse is an advanced sentiment analysis tool that leverages AI to assess the emotional tone of text inputs from social media. It offers real-time processing, intuitive UI, and robust backend integration with Hugging Face for accurate sentiment predictions.
https://github.com/ascender1729/sentipulse
ai hugging-face machine-learning nodejs real-time-analysis sentiment-analysis sqlite svelte-express text-processing
Last synced: about 2 months ago
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SentiPulse is an advanced sentiment analysis tool that leverages AI to assess the emotional tone of text inputs from social media. It offers real-time processing, intuitive UI, and robust backend integration with Hugging Face for accurate sentiment predictions.
- Host: GitHub
- URL: https://github.com/ascender1729/sentipulse
- Owner: ascender1729
- License: mit
- Created: 2024-07-12T06:19:27.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-07-12T07:51:25.000Z (11 months ago)
- Last Synced: 2025-03-28T02:46:15.575Z (about 2 months ago)
- Topics: ai, hugging-face, machine-learning, nodejs, real-time-analysis, sentiment-analysis, sqlite, svelte-express, text-processing
- Language: Svelte
- Homepage: https://github.com/ascender1729/sentipulse
- Size: 43.9 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SentiPulse: Social Sentiment Analyzer
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.
## Table of Contents
- [Features](#features)
- [Tech Stack](#tech-stack)
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Usage](#usage)
- [Project Structure](#project-structure)
- [API Endpoints](#api-endpoints)
- [Contributing](#contributing)
- [License](#license)
- [Contact](#contact)
- [Acknowledgements](#acknowledgements)
## Features
- **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.
## Tech Stack
### Backend
- **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)
- **dotenv**: Environment variable management.
### Frontend
- **Svelte**: Reactive JavaScript framework for building user interfaces.
- **Vite**: Next-generation frontend tooling for faster development.
- **Chart.js**: JavaScript charting library for data visualization.
### Development Tools
- **Git**: Version control system.
- **npm**: Package manager for JavaScript.
- **nodemon**: Utility for automatic server restarts during development.
## Prerequisites
- Node.js (v14 or later)
- npm (v6 or later)
- Git
## Installation
1. Clone the repository:
```
git clone https://github.com/ascender1729/sentipulse.git
cd sentipulse
```
2. Install server dependencies:
```
cd server
npm install
```
3. Install client dependencies:
```
cd ../client
npm install
```
4. 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
```
## Usage
1. Start the server:
```
cd server
npm run dev
```
2. In a new terminal, start the client:
```
cd client
npm run dev
```
3. Open your browser and navigate to `http://localhost:5173`.
4. Enter text in the input field and click "Analyze Sentiment" to see the results.
## Project Structure
```
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
```
## API Endpoints
- `POST /api/analyze`: Analyze sentiment of provided text.
- `GET /api/recent`: Retrieve recent sentiment analyses.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## License
Distributed under the MIT License. See `LICENSE` for more information.
## Contact
Pavan Kumar - [email protected]
LinkedIn: [linkedin.com/in/im-pavankumar](https://www.linkedin.com/in/im-pavankumar/)
Project Link: [https://github.com/ascender1729/sentipulse](https://github.com/ascender1729/sentipulse)
## Acknowledgements
- [Hugging Face](https://huggingface.co/) for their Inference API and the `distilroberta-base` model
- [Svelte](https://svelte.dev/) for the reactive UI framework
- [Chart.js](https://www.chartjs.org/) for data visualization
- [Express.js](https://expressjs.com/) for the server framework
- [SQLite](https://www.sqlite.org/) for the database