EmotionSense API 🧠📊

EmotionSense API is a modular, production-ready Python web application that analyzes text to detect underlying emotions using the IBM Watson Natural Language Processing (NLP) library.

Built with a DevOps-first mindset, this project demonstrates modern software engineering practices including modular architecture, test-driven development (TDD), static code analysis, and secure configuration management.

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📌 Table of Contents

• Project Overview
• Key Features
• Architecture & Design
• Technology Stack
• Installation & Setup
• Configuration (Security)
• Usage Guide
• Testing & Quality Assurance
• Project Roadmap (Milestones)
• Project Structure
• Author

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📖 Project Overview

The primary goal of EmotionSense is to expose a robust AI engine via a RESTful API. It takes raw user text, processes it through IBM's Watson NLP service, and returns a structured JSON response indicating the dominance of specific emotions.

This repository was developed as a Coursera Capstone Project but has been elevated to meet professional backend standards.

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🚀 Key Features

• Real-time Emotion Analysis: Detects Joy, Anger, Sadness, Fear, and Disgust.
• Dominant Emotion Logic: Automatically calculates and returns the strongest emotion.
• Modular Design: The core logic (emotion_detection) is decoupled from the web server (server.py), allowing for easy reuse.
• Robust Error Handling: Manages API failures, network issues, and invalid inputs gracefully (400/500 errors).
• Security Best Practices: Uses Environment Variables (.env) to protect sensitive API keys.

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🏗 Architecture & Design

The system follows a strict Separation of Concerns:

1. Core Logic (Engine): Handles the communication with IBM Watson and data formatting.
2. Web Layer (Interface): A Flask server that routes HTTP requests to the engine.
3. Client: Any frontend or tool (like Postman/cURL) that consumes the JSON API.

Logic Flow

User Input -> Input Validation -> IBM Watson API -> Data Parsing -> Dominant Emotion Calculation -> JSON Response

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⚙️ Technology Stack

• Language: Python 3.x
• Web Framework: Flask
• AI Engine: IBM Watson NLP
• HTTP Client: Requests
• Testing: Unittest
• Linting: Pylint
• Configuration: Python-Dotenv

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🛠 Installation & Setup

1. Clone the Repository

git clone [https://github.com/your-username/EmotionSense-API.git](https://github.com/your-username/EmotionSense-API.git)
cd EmotionSense-API