🎬 Movie Sentiment API

Production-ready FastAPI service — real-time NLP sentiment analysis with caching, monitoring, and full CI/CD automation.

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🚀 Overview

A production-ready REST API that analyzes movie reviews and classifies sentiment as positive, negative, or neutral — built with real-world DevOps practices: containerization, caching, observability, and automated CI/CD.

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⚙️ Tech Stack

Layer	Technology
Framework	FastAPI + Gunicorn + Uvicorn
Sentiment Engine	TextBlob (NLP)
Caching	Redis
Monitoring	Prometheus
Containerization	Docker + Docker Swarm
CI/CD	GitHub Actions

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🧠 Features

• Sentiment analysis — NLP-powered classification with confidence score
• Redis caching — repeated requests served instantly without recomputation
• Prometheus metrics — /metrics endpoint for real-time observability
• Health check — /health endpoint for container reliability and orchestration
• Fully Dockerized — production-ready with Gunicorn multi-worker setup
• Automated CI pipeline — test → build → push on every commit

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📦 API Endpoints

Method	Endpoint	Description
GET	/	Root info
GET	/health	Health check
GET	/metrics	Prometheus metrics
POST	/analyze	Analyze movie review sentiment

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🧪 Example

Request

POST /analyze
{
  "text": "This movie was amazing!",
  "movie_name": "Avengers"
}

Response

{
  "movie_name": "Avengers",
  "text": "This movie was amazing!",
  "sentiment": "positive",
  "score": 0.91,
  "confidence": 91.0
}

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🐳 Run with Docker

# Build image
docker build -t movie-api .

# Run container
docker run -p 8000:8000 movie-api

API will be available at http://localhost:8000

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🔄 CI/CD Pipeline

Push → GitHub Actions → Test → Build Docker Image → Push to Docker Hub

Every push to main triggers:

1. Automated test suite
2. Docker image build
3. Push to Docker Hub registry

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📈 Architecture

User → FastAPI → Redis (Cache) → Sentiment Logic → Response
                     ↓
               Prometheus Metrics

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📚 API Docs

Live Swagger Docs: https://raj-spy.github.io/Movie-api/

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🏃 Run Locally (without Docker)

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Start server
uvicorn app.main:app --reload

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👨‍💻 Author

Raj Tayde

• GitHub: @Raj-spy
• Live Project: LLM Drift Monitor