#About

• An AI-powered sentiment analysis web app built with Django and Hugging Face Transformers.
• This project analyzes user-input text and classifies it as Positive 😊, Neutral 🤔, or Negative 😡 using a pre-trained model.

#Features

• User input text analysis through a clean web interface

• Hugging Face sentiment model integration (distilbert-base-uncased-finetuned-sst-2-english or cardiffnlp/twitter-roberta-base-sentiment)

• Emoji-based sentiment visualization

• Real-time inference without needing to retrain models

• Modular Django structure for easy scalability

#Tech Stack

• Backend: Django (Python)
• AI / NLP: Hugging Face Transformers, PyTorch
• Frontend: HTML, CSS (Bootstrap)
• Version Control: Git & GitHub
• Deployment (optional): Heroku / Render / AWS

#How It Works

• User enters a review or comment.
• The app sends the text to a Hugging Face model using the transformers pipeline.
• The model predicts the sentiment label (Positive, Neutral, Negative).
• An appropriate emoji and confidence score are displayed.

#Requirements

• Python 3.8+
• Django 4.x
• Transformers
• Torch
• Requests

#Live Demo

• To have a peek on the live app visit https://huggingface.co/spaces/Juaan2/AI-Sentiment-Analyzer