Sentiment Analysis API

Overview

This project is a Sentiment Analysis API that takes user input text and predicts its sentiment using Hugging Face Hub. It is built with FastAPI for the backend and deployed on Koyeb.

Technologies Used

• FastAPI – Backend framework
• Hugging Face Hub – Sentiment analysis model
• Koyeb – Deployment platform

Installation and Setup

1. Clone the Repository

git clone https://github.com/your-username/sentiment-analysis-api.git
cd sentiment-analysis-api

2. Create a Virtual Environment (Optional but Recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Set Up Environment Variables

Create a .env file and add your Hugging Face API Token:

HUGGINGFACEHUB_API_TOKEN=your_huggingface_api_token_here

5. Run the FastAPI Server

uvicorn main:app --reload

The API will be available at http://127.0.0.1:8000.

API Usage

Endpoint:

POST /analyze_sentiment/

Request Body:

{
    "text": "I love this product!"
}

Response:

{
    "text": "I love this product!",
    "sentiment": "5 stars"
}

Frontend

A simple HTML frontend is provided in index.html, which sends a request to the API and displays the sentiment result.

Deployment on Koyeb

The API is deployed on Koyeb, a serverless platform for easy deployment. Steps to deploy:

1. Create a new service on Koyeb.
2. Connect your GitHub repository.
3. Set environment variables in Koyeb.
4. Deploy and get the API URL.

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🚀 Enjoy building with FastAPI and Hugging Face!