AI Sentiment Analysis with LLMs

A lightweight sentiment analysis demo powered by Large Language Models (LLMs) using the Prompture package. Quickly classify text sentiment, detect tone, and pull out useful phrases.

🌟 Features

• Sentiment Classification: Identify positive, negative, neutral, or mixed sentiment
• Confidence Scoring: See how reliable the classification is
• Tone Analysis: Detect formal, informal, optimistic, pessimistic, etc.
• Key Phrase Extraction: Highlight the most important words and topics
• LLM-Powered: Built on state-of-the-art language models via Prompture

🚀 Quick Start

Prerequisites

• Python 3.8+
• API key for your chosen LLM provider (OpenAI, LM Studio, etc.)

Installation

git clone https://github.com/jhd3197/ai-sentiment-analysis.git
cd ai-sentiment-analysis
pip install -r requirements.txt

Environment Setup

1. Copy the example environment file:

cp .env.copy .env

2. Update .env with your own API keys and model settings. (Supports multiple providers: OpenAI, LM Studio, Claude, etc.)

Running the Notebook

Run the notebook:

jupyter notebook sentiment_notebook.ipynb

🎯 Use Cases

• Quick analysis of product reviews
• Social media monitoring
• Market research sentiment checks
• Lightweight demos of LLM-powered text analysis

🤝 Contributing

Contributions are welcome! Please submit a PR or open an issue.

🙏 Acknowledgments

• Built with Prompture
• Powered by modern Large Language Models