MindMuseAI
MindMuse AI is a mental health chatbot that tracks emotions, offers guidance, and shares resources—empowering users to understand their mental well-being through a simple, supportive web experience.
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Description
MindMuse AI is an AI-powered mental health chatbot designed to help users track their emotional well-being, receive guidance, and gain insights into their mental health progress. The app empowers users to better understand their mental state, develop coping strategies, and access helpful resources — all through a beautifully crafted, accessible web experience.
🌟 Key Features
🧠 Emotion Recognition
Detects emotional tone from user input using AI (currently DeepSeek API).
Plans to use fine-tuned ML/NLP models in future for deeper understanding.
💡 Mental Health Advice
Offers actionable tips and resources on:
Managing anxiety
Controlling stress
Overcoming depression
Chatbot suggests personalized advice based on user mood.
🗓️ Mood Tracker & Progress Insights
Tracks emotions over time.
Visualizes mental health progress through dynamic graphs.
Stores all sessions and advice history for reflection.
🔐 Authentication System
Firebase-based user authentication.
Supports both:
Google Sign-In
Traditional Email/Password Sign-Up
🧾 Profile Management
Edit name, view mood logs, and manage account settings.
Future-ready design includes model selection and voice settings.
🎙️ Voice Interaction
Integrated microphone feature using Web Speech API.
Users can speak with the chatbot via voice input.
🛠️ Model Selection (Coming Soon)
Users will be able to choose between multiple AI models.
Easily switch between APIs or custom-trained models.
💻 Tech Stack
Area | Technology |
|---|---|
Frontend | HTML, CSS, JavaScript |
UI Assistance | Cursor AI |
Backend | Node.js, Express.js |
Chatbot API | DeepSeek API (for now) |
Authentication | Firebase Authentication |
Database | Firebase Firestore |
Graphs & Logs | Chart.js / Custom JS |
Voice Support | Web Speech API |
Hosting (Optional) | Firebase Hosting / Vercel |
🧪 Future Enhancements
Fine-tuned ML/NLP model for emotion detection.
Offline support with PWA setup.
More model integration options (OpenAI, Claude, etc.).
Journal writing and AI feedback analysis.
Emergency support links and mental health resources.
Progress During Hackathon
So far, we’ve made significant progress on MindMuse AI within the limited hackathon time: ✅ Designed and developed a responsive front-end using HTML, CSS, and JavaScript ✅ Integrated a fully functional AI chatbot using the DeepSeek API ✅ Implemented Firebase Authentication (Google sign-in and email/password login) ✅ Set up Firebase Firestore to store user-specific mood tracking and chatbot advice ✅ Built a Mood Tracker with data visualization to monitor emotional patterns ✅ Created dynamic pages including: Chat interface Progress tracking Model selection page User profile and settings page ✅ Added theme toggling (light/dark) for better UX ✅ Integrated microphone input using the Web Speech API