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.

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Features

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

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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

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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.

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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.

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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

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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).

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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.

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Future Enhancements

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

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License

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

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Acknowledgments

• FastAPI for backend framework.
• Hugging Face for sentiment analysis models.
• React for frontend development.