🎭 Emotion Reflector

Emotion Reflector is a modern full-stack AI-powered web app that analyzes user-written reflections or thoughts and predicts the underlying emotion, confidence score, and emoji in real time.

It combines the power of FastAPI (Python) for fast backend processing with a Next.js (React + TypeScript) frontend, designed with elegant modern UI (Tailwind CSS & gradient transitions) and deployed seamlessly in the cloud.

---

🚀 Live Demo

Frontend: https://response-frontend.vercel.app
Backend (API): https://response-app-backend.onrender.com/analyze

---

✨ Features

• 🧠 Predict emotion from free text (using keyword-based NLP logic)
• 📊 Show confidence score & matching emoji
• 💻 Beautiful, responsive frontend with glassmorphism & gradient UI
• ⚡ Real-time interaction with backend API
• 🌐 Deployed on Render (Python) & Vercel (Next.js)

---

🔍 Interactive Keyword Search

"anxious", "nervous", "happy", "excited", "sad", "proud", "loved", "lonely", "angry", "stressed", "calm", "surprised", "adventurous", "exhausted", "disappointed", "fearful", "hopeful", "joyful", "confused", "grateful", "relieved", "frustrated", "bored", "jealous", "guilty", "motivated", "inspired", "curious", "peaceful", "embarrassed", "determined", "confident", "scared", "shy", "regretful", "disgusted", "hope", "music", "success", "failure", "relax", "win", "family", "alone", "exam", "interview", "travel", "surprise", "tired"

🛠️ Technologies Used

Frontend:

• Next.js (React + TypeScript)
• Tailwind CSS – modern utility-first styling
• Axios – for HTTP requests
• Vercel – frontend deployment

Backend:

• FastAPI – high-performance Python framework
• Pydantic – request validation
• Uvicorn – ASGI server
• Render – backend deployment
• CORS middleware – to enable frontend-backend communication

---

📦 Folder Structure (simplified)

/response-frontend     ← Next.js app
  /components
    EmotionForm.tsx    ← UI & API integration
  /pages
    index.tsx          ← Home page

/response-backend      ← FastAPI app
  main.py              ← API & emotion analysis logic

🏗 How to Run Locally

📌 Prerequisites: Node.js ≥ 18

Python ≥ 3.8

pip

(Optional) virtualenv

🔧 Setup Backend (FastAPI)

bash Copy Edit

Clone repo & go to backend folder

cd response-backend

(Optional) Create virtual environment

python -m venv env source env/bin/activate # On Windows: env\Scripts\activate

Install dependencies

pip install fastapi uvicorn

Run the server

uvicorn main:app --host=0.0.0.0 --port=8000

🌐 Deployment Frontend: Deploy to Vercel

Backend: Deploy to Render (free web service) with main.py entry and uvicorn main:app --host=0.0.0.0 --port=8000

Ensure correct CORS setup in FastAPI:

python Copy Edit origins = [ "http://localhost:3000", "https://response-frontend.vercel.app" ] ✅ Why this project matters

This project demonstrates:

Building & deploying modern, full-stack AI tools

Writing clean, modular code (TypeScript & Python)

Connecting frontend & backend securely (CORS, environment variables)

Designing beautiful, user-friendly interfaces with advanced CSS & transitions

Cloud deployment with real URLs – ready to show in your portfolio or resume

Built with by me Surya Pratap Singh