MindMate

• 

  home ui

• 

  example response

• 

  mood trends

• 

  pdf

MindMate

Inspiration

I wanted to build something that helps people check in with themselves: quickly, privately, and without pressure. Journaling helps, but most people don’t stick with it. So we made something simple, personal, and helpful.

What it does

MindMate is a mood journaling app that helps users reflect on how they're feeling. You type in your thoughts, and it responds with a supportive message: either in a friendly or clinical tone. It detects your mood using simple rule-based logic, gives tips and affirmations, logs your entry, creates a downloadable PDF, and shows mood trends over time with a chart.

How we built it

I used Python and Streamlit to build a mood journaling app that responds to your entry with tips and affirmations. Right now, it uses rule-based logic to detect emotions and suggest support in either a friendly or clinical tone. You can save your entries as pdfs and track your mood over time with charts.

Challenges we ran into

Without access to AI APIs, I had to build our own rule-based emotion logic. Also, formatting the PDF nicely and avoiding CSV/data bugs took time.

Accomplishments that we're proud of

1. Built a fully working, offline-friendly tool in one sitting
2. Designed two different emotional tones that feel distinct and helpful
3. Made it clean and modern without using any front-end frameworks
4. Implemented PDF journaling and mood tracking in a short time

What we learned

I learned how tone affects user experience, how to handle messy text input, and how small design choices impact usability: especially for sensitive topics like mental health.

What's next for MindMate

Right now, the app is rule based. Next, I want to replace that with a lightweight machine learning model that can understand more nuance and adapt over time.

Built With

• altair
• css
• fpdf
• html
• pandas
• python
• streamlit