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Sentiment Analysis App

A simple web application for performing sentiment analysis on text input. The app has two main components:

  1. Frontend: Built with React.
  2. Backend: Powered by Python, FastAPI, and Hugging Face Transformers.

Features

  • Analyze text sentiment (Positive/Negative/Neutral).
  • Confidence score for the sentiment analysis.
  • Interactive and user-friendly UI.

Prerequisites

General Requirements

  • Node.js (version 16+)
  • Python (version 3.8+)
  • Virtual Environment (recommended)

Python Libraries

  • fastapi
  • uvicorn
  • transformers
  • pydantic
  • pytest (for testing)

React Libraries

  • axios

Installation

1. Clone the Repository

git clone https://github.com/thefutureseer/python_sentiment_analysis.git
cd python_sentiment_analysis

2. Backend Setup

Navigate to the backend directory:

cd sentiment-backend

Create and activate a virtual environment:

python3 -m venv venv
source venv/bin/activate  # MacOS/Linux
venv\Scripts\activate   # Windows

Install Python dependencies:

pip install -r requirements.txt

Run the FastAPI server:

uvicorn main:app --reload

The backend will start on http://127.0.0.1:8000.

3. Frontend Setup

Navigate to the frontend directory:

cd python_sentiment_analysis [root]

Install Node.js dependencies:

npm install

Start the React development server:

npm start

The frontend will start on http://localhost:3000.

Usage

  1. Open your browser and navigate to http://localhost:3000.
  2. Enter text in the input box and click "Analyze Sentiment."
  3. View the sentiment results, including the confidence score.

File Structure

python_sentiment_analysis root directory/
│
├── sentiment-backend/       # Backend code (FastAPI)
│   ├── main.py              # FastAPI entry point
│   ├── models.py            # Pydantic models
│   ├── requirements.txt     # Python dependencies
│   ├── test_main.py         # Unit tests for the backend
│
├── # Frontend code (React)
|-- public
│── src/
│   ├── App.js           # Main React component
│   ├── index.js         # React entry point
│── package.json         # Node.js dependencies
│
└── README.md                # Project documentation

Running Tests

Backend Tests

Ensure your virtual environment is active, then run:

python3 -m unittest test_main.py

Frontend Tests

Add tests as needed using your preferred testing framework (e.g., Jest, React Testing Library).

Deployment

Backend

  • Deploy using services like AWS, Azure, Heroku, or Render.

Frontend

  • Build the production-ready files using: 
    npm run build
  • Deploy using Vercel, Netlify, or any other static site hosting service.

Future Enhancements

  • Add more detailed error handling.
  • Implement support for other languages.
  • Enhance UI with additional features.

License

This project is licensed under the MIT License. See LICENSE for details.

Acknowledgments