☕ MoodFuel — AI-Powered Coffee Strength Recommender

MoodFuel is an AI-powered coffee strength recommender that suggests the ideal caffeine intensity based on your mood, stress, and sleep pattern — built using FastAPI, scikit-learn, Docker, and Streamlit.
It’s a learning-oriented, open-source project demonstrating an end-to-end MLOps pipeline — from model training to deployment. API Endpoint : https://moodfuel-api.onrender.com/ Streamlit App : https://moodfuel.onrender.com

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🧩 Summary

MoodFuel intelligently recommends your coffee strength on a 1–10 scale using data like:

• 😴 Sleep duration
• 😤 Stress level
• 🕒 Time of day
• 💻 Workload intensity
  It demonstrates machine learning integration with FastAPI, full CI/CD automation, and modern frontends (Streamlit & Gradio) for interactivity.

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⚙️ Key Features

• FastAPI backend serving ML predictions
• Streamlit dashboard for user interaction
• Gradio demo interface for ML visualization
• CI/CD automation via GitHub Actions
• Containerized deployment with Docker
• Cloud deployment supported (Render)

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🏗️ Project Architecture

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🗂️ Folder Structure

├── .gitignore
├── app
    ├── __init__.py
    ├── __pycache__
    │   ├── main.cpython-312.pyc
    │   ├── schema.cpython-312.pyc
    │   └── __init__.cpython-312.pyc
    ├── schema.py
    ├── main.py
    ├── gradio_ui.py
    └── dashboard.py
├── model
    └── model.pkl
├── requirements.txt
├── deploy
    └── .dockerignore
├── tests
    └── test_app.py
├── Dockerfile
├── data
    ├── DataGenerator.py
    └── coffee_strength_dataset.csv
├── .github
    └── workflows
    │   └── ci.yml
└── train_model.py

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🚀 Installation & Setup

Prerequisites

• Python 3.10
• pip or conda
• Docker
• GitHub account (for CI/CD setup)

1️⃣ Clone the Repository

git clone https://github.com/SamIeer/MoodFuel.git
cd MoodFuel

2️⃣ Install Dependencies

pip install -r deploy/requirements.txt

3️⃣ Train the Model

python train_model.py

4️⃣ Run FastAPI Backend

uvicorn app.main:app --reload
Visit http://127.0.0.1:8000/docs

💻 Run Frontend Interfaces

Streamlit Dashboard

streamlit run app/dashboard.py

Gradio Demo

python app/gradio_ui.py

🐳 Docker Deployment Build Docker Image bash Copy code

docker build -t moodfuel-api .

Run Container

docker run -d -p 8000:8000 moodfuel-api 
Access your app at:

👉 http://localhost:8000/docs

• ☁️ Cloud Deployment (Render)
• Push your project to GitHub.
• Go to Render
• Create a New Web Service → connect GitHub repo.
• Select Docker environment → deploy.
• Your live AAP will be available at:
• https://moodfuel.onrender.com

CI/CD automatically runs these tests on every push (see .github/workflows/ci.yml).

🚀 Contributing

Contributions are welcome! To get started, follow these steps:

1️⃣ Create a New Branch

git checkout -b feature/your-feature-name

2️⃣ Make Your Changes

✔ Follow PEP 8 style guidelines ✔ Add clear comments and docstrings ✔ Keep your code readable and consistent

3️⃣ Run Tests

pytest -v

4️⃣ Commit & Push

git add .
git commit -m "Add new feature"
git push origin feature/your-feature-name

5️⃣ Submit a Pull Request

Open a Pull Request from your branch into the main branch and describe your changes clearly.

Author

👤 Sameer Chauhan

• GitHub: SamIeer
• LinkedIn: Sameer Chauhan
• Email: sameerchauhan212204@gmail.com