Mood Tracker

Live Application: Mood Tracker

The backend and frontend are deployed on Railway — you can try out the app directly at the link above.

Features

• User authentication with JWT (register, login, logout)
• Secure password change and account management
• Track daily mood entries with notes and emojis support
• Validation for entries (minimum 10 characters, maximum 1000)
• Integration with OpenAI (Spring AI) to analyze moods and provide personalized suggestions
• Integrated with OpenAI (Spring AI) to generate plan based on your entries (moods)
• REST API endpoints tested with Postman
• MySQL database support
• Docker-ready for easy deployment

Tech Stack

• Backend: Java, Spring Boot, Spring Security, Spring Data JPA, Spring AI
• Database: MySQL
• Authentication: JWT with blacklist and refresh handling
• Testing: Postman collections
• Deployment: Railway (Dockerized)

Project Structure

mood-tracker/
├── src/main/java/com/moodTracker
│   ├── controller     # REST controllers
│   ├── service        # Business logic services
│   ├── security       # JWT, filters, authentication
│   ├── model          # Entities and DTOs
│   ├── repository     # JPA repositories
│   └── MoodTrackerApplication.java
├── src/main/resources
│   ├── application.properties  # Configurations
│   └── schema.sql              # Database schema (if applicable)
└── pom.xml

Endpoints

Authentication

• POST /api/auth/register – Register new user
• POST /api/auth/login – Authenticate and get JWT
• POST /api/auth/logout – Invalidate JWT (blacklist)
• POST /api/auth/change-password – Change password

Mood Entries

• POST /api/mood/create – Create new mood entry
• PUT /api/mood/update – Update mood entry
• GET /api/mood/date – Retrieve mood entry by date
• GET /api/mood/range – Retrieve moods entries by start & end date
• DELETE /api/mood/{id} – Delete entry

AI Analysis

• POST /api/ai/analyze – Analyze mood entry and provide suggestions with AI
• POST /api/ai/plan – Generate personalized plan with AI based on mood entries

Example response:

{
  "average": 3.6,
  "summary": "Concise summary in English language, ~120 words max.",
  "suggestions": [
    "Actionable suggestion #1",
    "Actionable suggestion #2",
    "Actionable suggestion #3",
    "Actionable suggestion #4",
    "Actionable suggestion #5"
  ]
}

Running Locally

Prerequisites

• Java 21+
• Maven 3.9+
• MySQL running locally (or via Docker)
• Docker (for containerized deployment)

Steps

# Clone repository
git clone https://github.com/emirtotic/mood-tracker.git
cd mood-tracker

# Build
mvn clean install

# Run
mvn spring-boot:run

Configure Database

Update application.properties with your database credentials:

spring.datasource.url=jdbc:mysql://localhost:3306/database_name
spring.datasource.username=your_username
spring.datasource.password=your_password
spring.jpa.hibernate.ddl-auto=update

Docker Deployment

Build and run using Docker:

docker build -t mood-tracker .
docker run -p 8080:8080 mood-tracker

Contributing

Contributions are welcome! Please fork the repository and submit a pull request.

Author

Created by: Emir Totić • Backend: Java/Spring Boot, AI integrations