Personalized Lifestyle Coach

Wellness redefined with AI

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Inspiration

We noticed that many people struggle to maintain healthy habits, manage stress, and feel supported emotionally—especially those who may be sensitive, introverted, or easily overwhelmed. Traditional wellness apps often feel too clinical or generic, so we wanted to design something more human, gentle, and supportive: a companion-like wellness coach that feels like a friend.

What it does

The Wellness Coach app helps users track their daily wellness metrics like sleep, steps, water intake, nutrition, stress, and screen time. It provides personalized recommendations and motivates users through friendly feedback. It also has: An AI-powered chatbot that gives supportive guidance and asks follow-up questions. A mood journal where users can write feelings and receive reflective responses. A weekly tracker with data visualization and habit streak badges. Multi-language support, so users can interact in English, Urdu, Hindi, Spanish, and more.

How we built it

Frontend & Logic: Built with Streamlit for quick prototyping and clean UI. AI Chatbot: Powered by Groq’s Llama-3.1-8b-instant model for real-time conversations. Translation: Integrated GoogleTranslator (deep-translator) for multilingual support. Charts & Data: Used Altair to visualize weekly progress and highlight trends. State Management: Leveraged st.session_state to persist chat history and weekly inputs. Custom Styling: Added CSS for chat bubbles, streak badges, and gradient cards to make the app feel warm and personal.

Challenges we ran into

Getting Groq API responses to stay short, supportive, and not overly technical. Handling translation issues when switching between languages with different scripts. Keeping weekly data persistent and avoiding duplication of entries. Styling Streamlit components with CSS, since it doesn’t natively support advanced UI design.

Accomplishments that we're proud of

Created a multilingual wellness chatbot that feels genuinely supportive. Designed a user-friendly interface with motivational colors, gradient cards, and badges. Integrated AI + data visualization into one seamless app. Made wellness tracking feel less clinical and more like having a supportive friend.

What we learned

How to combine Streamlit, Groq API, and translation tools into one smooth workflow. The importance of user personalization (e.g., different goals like stress relief, weight loss, or better sleep). How visual feedback (charts, badges, streaks) can significantly boost motivation. That a gentle, conversational tone makes AI more approachable and trusted.

What's next for Personalized Lifestyle Coach

Adding voice input/output for more natural interactions. Building a mobile-friendly version so users can check in on the go. Expanding recommendation intelligence with more wellness areas (like diet plans, meditation sessions, or gratitude prompts). Adding data export & privacy features, so users feel safe and own their data. Integrating with wearables (Fitbit, Apple Health, Google Fit) for automatic tracking.

Built With

  • altair
  • custom-css
  • datetime
  • deeptranslator
  • groqapi
  • pandas
  • python
  • streamlit
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