Containerized Microservice with AWS

This project contains a containerized Python microservice that provides NLP functionality, including Named Entity Recognition (NER) and Sentiment Analysis, and is prepared for deployment on AWS using Docker and Elastic Container Registry (ECR) / Elastic Container Service (ECS).

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Features

• NER Endpoint: Extract entities from input text
• Sentiment Endpoint: Analyze text sentiment
• Built with Flask, PyTorch, Transformers
• Fully containerized with Docker
• Ready for cloud deployment on AWS

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Requirements

• Docker ≥ 20.x
• Python 3.12 (for local development)
• Optional: AWS CLI (for ECR/ECS deployment)

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Quickstart with Docker

1. Build docker image

docker build -t containerized-microservice:latest .

2. Run docker image

docker run -it -p 5000:5000 containerized-microservice:latest

3. Test the Endpoints (NER & Sentiment)

curl -X POST http://localhost:5000/ner -H 'Content-Type: application/json' -d '{"text": "Meta is a tech giant"}'

curl -X POST http://localhost:5000/sentiment -H 'Content-Type: application/json' -d '{"text": "I love mathematics"}'