Releases: ap-dev-github/sentiment-analyzer-api
v1.0.0
🚀 Sentiment Analyzer API – Release Note
📝 Overview
v1.0.0 marks the first stable release of the Sentiment Analyzer API.
The Sentiment Analyzer API efficiently processes text input via NLTK’s SentimentIntensityAnalyzer, extracting positive, negative, and neutral scores in real-time. It determines the dominant sentiment and classifies text accordingly, making it ideal for automated feedback analysis.
Built with Flask, AWS Lambda, and Serverless Framework, this API is highly scalable and cost-efficient, utilizing AWS API Gateway for auto-scaling while keeping operational costs near zero when idle.
🎯 Key Features
✅ Real-Time Sentiment Analysis – Classifies text as Positive, Negative, or Neutral
✅ Fully Serverless – Automatically scales with demand, reducing costs by up to 98%
✅ CI/CD Automation – GitHub Actions handle automated testing, deployment, and security checks
✅ Optimized for Performance – Cold start prevention & dependency pruning for faster execution
📡 API Endpoint
1. Analyze Sentiment
GET /analyze/<text>
Response Example:
{
"positive": 0.8,
"neutral": 0.1,
"negative": 0.1,
"dominant_sentiment": "Positive"
}
⚙️ Deployment & Security
🔹 CI/CD with GitHub Actions – Auto-deploys updates to AWS Lambda
🔹 Security Checks – Runs pytest, flake8, mypy, isort, bandit before deployment
🔹 Cost Optimization – Scales down to zero cost for up to 1M requests/month
🏗 Built With
Flask | AWS Lambda | Serverless Framework
GitHub Actions | NLTK | Python
📧 Developer and Maintainer
Ayush Pandey
📧 ayushpandey.cs@gmail.com | 🔗 LinkedIn
🔥 A lightweight, scalable, and serverless sentiment analysis API—optimized for cost, speed, and real-world applications. 🚀