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Sentimenta — Mood Tracker with AI Suggestions

Sentimenta is a web application for daily mood tracking and analysis. Users rate their mood on a scale from 1 to 5, select emotions from a list or add their own, and optionally write a short note about their day. After saving the entry, the system provides a personalized suggestion generated by AI. The interface is built with SvelteKit and Tailwind CSS, ensuring high performance and responsive design.

Key Features

• Daily Mood Logging: Users select a rating from 1 to 5, choose emotions, and optionally write a note about their day.
• AI Suggestions: After each entry, Sentimenta generates a recommendation for improving mood.
• Authentication: Secure authentication via JWT and OAuth (GitHub/Google).
• Data Storage: All entries are stored in a PostgreSQL database.
• Statistics: A chart displays mood rating trends over the past month.
• Monitoring: Prometheus is used for metrics collection, and Grafana for visualization.
• Containerization: The project is fully containerized with Docker (using docker-compose and Traefik for routing).

Sentimenta is optimized for different devices. The responsive design makes it easy to log mood entries and view personal stats. Clear data visualizations and a fast interface ensure a smooth and enjoyable user experience.

Technologies

• Frontend: SvelteKit, Tailwind CSS
• Backend: Go (Golang), Echo web framework
• Database: PostgreSQL
• Monitoring: Prometheus, Grafana

Installation and Launch

1. Clone the repository and navigate into its directory.

2. Copy the dotenv_template file to .env and configure the required environment variables (database settings, OAuth, secrets, etc.).

3. Make sure Docker and Docker Compose are installed.

4. Launch all services with the following command:

   docker-compose up -d
   

5. The application will be available at the configured domain (e.g., https://sentimenta.example.com).

Future Plans

• Release mobile apps for iOS and Android.
• Add reminders and expanded personalization options.

License

This project is licensed under the MIT License (see the LICENSE file for details).