🏋️ IronMind – AI Fitness Coach

IronMind is a full-stack AI-powered fitness platform designed to help users track their health, generate personalized workout and diet plans, analyze exercise form, and interact with an intelligent AI fitness coach.

The application combines modern web technologies, artificial intelligence, machine learning, computer vision, and real-time communication into a single fitness ecosystem.

🚀 Features

🔐 JWT Authentication & Google Sign-In
📊 BMI Calculator with History & Trend Charts
🤖 AI Fitness Coach using Retrieval-Augmented Generation (RAG)
🥗 Personalized Diet & Workout Plan Generator
⏱️ Workout Timer with HIIT, Tabata & Custom Modes
📹 AI Exercise Form Checker using MediaPipe Pose
🔢 Real-Time Exercise Rep Counting
📐 Joint Angle Detection & Form Analysis
🔔 Real-Time Notifications using Socket.IO
🏆 Daily Streaks & Achievement Badges
📧 Daily Email Workout Reminders
🌙 Dark/Light Theme
🎨 Modern Animated UI using Framer Motion
🛡️ Rate Limiting & Secure Authentication
🧪 Backend Unit Testing with Pytest
🐳 Docker & Docker Compose Support

🛠️ Tech Stack

Frontend

React
Vite
Tailwind CSS
Framer Motion
Axios
Socket.IO Client

Backend

FastAPI
SQLAlchemy
PostgreSQL
JWT Authentication
OAuth2
Google OAuth
Bcrypt Password Hashing
SlowAPI Rate Limiting

AI & Machine Learning

Retrieval-Augmented Generation (RAG)
ChromaDB
TF-IDF Retrieval
Latent Semantic Analysis (LSA)
Hugging Face Inference API
Cosine Similarity Search

Computer Vision

MediaPipe Pose Estimation
Webcam-Based Exercise Analysis
Real-Time Rep Counting
Joint Angle Detection
Exercise Form Feedback
On-Device Processing

DevOps & Deployment

Docker
Docker Compose
GitHub Actions
Pytest
GitHub
Render
Vercel
Supabase PostgreSQL

🏗️ System Architecture

                         ┌──────────────────────┐
                         │    React + Vite       │
                         │      Frontend        │
                         └──────────┬───────────┘
                                    │
                                    │
                                    │ API Requests
                                    ▼
                         ┌──────────────────────┐
                         │       FastAPI        │
                         │       Backend        │
                         └──────────┬───────────┘
                                    │
                  ┌─────────────────┼─────────────────┐
                  │                 │                 │
                  ▼                 ▼                 ▼
             PostgreSQL           RAG            MediaPipe
             (Supabase)         AI Coach         Form Checker
                  │
                  ▼
             User Data

📂 Project Structure

fitness-app/
│
├── backend/
│   ├── app/
│   │   ├── routers/
│   │   ├── rag/
│   │   ├── models.py
│   │   ├── schemas.py
│   │   ├── security.py
│   │   ├── database.py
│   │   └── main.py
│   │
│   ├── tests/
│   ├── requirements.txt
│   └── Dockerfile
│
├── frontend/
│   ├── src/
│   │   ├── pages/
│   │   ├── components/
│   │   ├── context/
│   │   └── api/
│   │
│   ├── package.json
│   └── Dockerfile
│
├── docker-compose.yml
└── README.md

⚡ Installation

1. Clone the Repository

git clone https://github.com/anushkap0/IronMind.git
cd IronMind

2. Backend Setup

Navigate to the backend directory:

cd backend

Create a virtual environment:

Windows

python -m venv venv
venv\Scripts\activate

Linux / macOS

python -m venv venv
source venv/bin/activate

Install the required dependencies:

pip install -r requirements.txt

Start the FastAPI backend:

uvicorn app.main:app --reload

Backend runs at:

http://localhost:8000

Swagger API Documentation:

http://localhost:8000/docs

3. Frontend Setup

Open a new terminal and navigate to the frontend:

cd frontend

Install dependencies:

npm install

Start the development server:

npm run dev

Frontend runs at:

http://localhost:5173

🔐 Environment Variables

Create a .env file for the backend and configure the required environment variables.

Example:

DATABASE_URL=your_postgresql_database_url

SECRET_KEY=your_secret_key
SESSION_SECRET_KEY=your_session_secret_key

FRONTEND_ORIGIN=http://localhost:5173

GOOGLE_CLIENT_ID=your_google_client_id
GOOGLE_CLIENT_SECRET=your_google_client_secret
GOOGLE_REDIRECT_URI=http://localhost:8000/auth/google/callback

HF_API_TOKEN=your_huggingface_api_token

⚠️ Important: Never commit your .env file or real passwords, API keys, tokens, or secret keys to GitHub.

Use .env.example with placeholder values when sharing the project.

For production deployment, configure environment variables through your hosting provider.

🐳 Docker

IronMind supports Docker and Docker Compose for containerized development and deployment.

Build and start the application:

docker compose up --build

Stop the containers:

docker compose down

PostgreSQL data is persisted using a Docker volume.

🤖 AI Fitness Coach

The AI Fitness Coach uses a Retrieval-Augmented Generation (RAG) pipeline to provide intelligent fitness-related responses.

RAG Pipeline

User Question
      ↓
TF-IDF Retrieval
      ↓
LSA Embeddings
      ↓
Cosine Similarity Search
      ↓
Relevant Fitness Context
      ↓
Hugging Face LLM
      ↓
AI-Generated Response

The system retrieves relevant information from a fitness knowledge base before generating a response.

If an AI API token is not available, the application can switch to Demo Mode.

📹 AI Exercise Form Checker

IronMind uses MediaPipe Pose Estimation for real-time exercise analysis.

Supported Exercises

Squats
Push-ups

Features

Real-time exercise rep counting
Joint angle detection
Exercise form analysis
Real-time form feedback
Webcam-based exercise tracking
On-device pose processing

📊 Progress Tracking

Users can:

Calculate BMI
Store BMI history
View BMI progress charts
Track daily fitness streaks
Unlock achievement badges
Monitor workout progress

🔔 Real-Time Features

Socket.IO is used to provide real-time application functionality.

Features include:

Workout timer synchronization
Live notifications
Achievement updates
Real-time application events

🔐 Authentication & Security

IronMind provides secure authentication and application protection through:

JWT Authentication
OAuth2 Password Flow
Google OAuth Login
Bcrypt Password Hashing
Rate Limiting using SlowAPI
Environment-based secret management
Secure API authentication

🧪 Testing

Backend tests are implemented using Pytest.

Run the test suite:

cd backend
pytest tests/ -v

☁️ Deployment

IronMind can be deployed using the following architecture:

                 ┌─────────────────┐
                 │ React + Vite     │
                 │ Frontend         │
                 └────────┬────────┘
                          |
                          ▼
                 ┌─────────────────┐
                 │ FastAPI         │
                 │ Backend         │
                 └────────┬────────┘
                          │
                          ▼
                      Render
                          │
                          ▼
                 ┌─────────────────┐
                 │ PostgreSQL      │
                 │ Database        │
                 └────────┬────────┘
                          │
                          ▼
                      Supabase

Deployment Stack

Component	Platform
Frontend	Render
Backend	Render
Database	Supabase PostgreSQL
Source Code	GitHub

For production deployment, configure all required environment variables in the hosting platform instead of committing secrets to the repository.

🌟 Future Improvements

🥗 Nutrition Tracking
⌚ Wearable Device Integration
🧠 Intelligent Exercise Recommendation System
🎙️ Voice-Based AI Fitness Coach
📱 Mobile Application
🏆 Social Fitness Challenges
📈 Advanced Workout Analytics Dashboard

👩‍💻 Author

**Anushka **

GitHub: Anushka

⭐ Support

If you found this project helpful, consider giving the repository a ⭐ on GitHub!

Name		Name	Last commit message	Last commit date
Latest commit History 19 Commits
.github/workflows		.github/workflows
backend		backend
frontend		frontend
.gitignore		.gitignore
README.md		README.md
docker-compose.yml		docker-compose.yml

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