Sentiment Analysis API

by Michael Claus

READ THE FULL ARTICLE HERE

This repository contains the code for a sentiment analysis API built using Python, Flask, Hugging Face's Transformers library, Docker, and deployed on AWS. The API utilizes a pre-trained model to classify input text as positive, negative, or neutral.

https://www.youtube.com/watch?v=sqO9_k6tLYo

Getting Started

These instructions will help you set up the project on your local machine for development and testing purposes.

Prerequisites

Ensure you have the following installed on your system:

• Python 3.8 or higher
• Docker

Installation

Clone the repository: git clone https://github.com/yourusername/sentiment-analysis-api.git Change to the project directory: cd sentiment-analysis-api Create a virtual environment and activate it: python -m venv venv

Install the required packages: pip install -r requirements.txt Run the Flask app locally: export FLASK_APP=app/app.py && flask run

Now you can access the API http://localhost:5000 on your local machine.

Building and Running the Docker Container

Build the Docker container: docker build -t sentiment-analysis-api . Run the Docker container: docker run -p 8080:80 sentiment-analysis-api

Now you can access the API at http://localhost:8080 on your local machine.

Usage

To use the API, make a POST request to the /analyze endpoint with the following JSON payload:

{
  "text": "your text here"
}

The API will return a JSON object with the sentiment classification:

{
  "sentiment": "positive"
}

License This project is licensed under the MIT License - see the LICENSE file for details.